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Label-free imaging of large samples: 3D rendering and morphological analysis within histological workflows using serial block face imaging Serial block face imaging (SFBI) is a method used to generate 3-dimensional (3D) reconstruction of a sample via serial image acquisition. Several SBFI approaches have been proposed for large samples, differing in the ability to generate contrast as well as in the nature of the detected signal. We propose a new system that detects the endogenous autofluorescence signal of paraffin-embedded samples. The sample preparation is simplified compared to other approaches, and adapted to be integrated into a routine histological preparation. More specifically, it was designed to limit reagent toxicity and to be compatible with downstream histological processing. We show the usefulness of the technique with a wide range of tissues based on the intrinsic autofluorescence signal. Optimization of quality section recovery offers the possibility to develop correlative approaches and multimodal analysis between the 3D dataset with the 2-dimensional (2D) sections. In addition, contrast and resolution of block-face images allow us to successfully perform post processing analysis and morphology quantifications. Overall, our methodology offers a simple, cost effective and rapid approach to obtain quantitative data on a large sample with no specific staining. | bioengineering |
Extending the Boundaries of Cancer Therapeutic Complexity with Literature Data Mining Even though there is high motivation to develop effective monotherapies for cancer, combination drug therapy is still one of the main pillars of oncological treatments. The formation of an effective combinatorial standard of care (SOC) can take many years and its length of development is increasing with complexity of treatment. In this paper, we develop a path to extend the boundaries of complexity in combinatorial cancer treatments using text data mining (TDM). We first used TDM to characterize the current boundaries of cancer treatment complexity. We found that the current complexity limit for clinical trials is 6 drugs per plan and for pre-clinical research is 10. We then developed a TDM based assistive technology, cancer plan builder (CPB), that allows experts to create high complexity combination treatment (HCCT) plans of significantly larger size. We evaluated CPB by comparing it to the standard of care, to fully automated plans and to HCCT plans created by experts without the tool. We found that by average, 86% of elements in the plans generated with CPB are either compatible with standard of care or FDA approved for the correct indication. In addition, CPB assisted plans were superior in every metric to plans generated either automatically or manually. To conclude, we propose a new tool and workflow to handle the vast complexity space of combinatorial cancer treatment facilitate further evaluation of HCCT in experimental cancer research. | bioinformatics |
Multi-task learning uncovers robust translation cis-regulatory features BackgroundMany studies have found that sequence in the 5 untranslated regions (UTRs) impacts the translation rate of an mRNA, but the regulatory grammar that underpins this translation regulation remains elusive. Deep learning methods deployed to analyse massive sequencing datasets offer new solutions to motif discovery. However, existing works focused on extracting sequence motifs in individual datasets, which may not be generalisable to other datasets from the same cell type. We hypothesise that motifs that are genuinely involved in controlling translation rate are the ones that can be extracted from diverse datasets generated by different experimental techniques. In order to reveal more generalised cis-regulatory motifs for RNA translation, we develop a multi-task translation rate predictor, MTtrans, to integrate information from multiple datasets.
ResultsCompared to single-task models, MTtrans reaches a higher prediction accuracy in all the benchmarked datasets generated by various experimental techniques. We show that features learnt in human samples are directly transferable to another dataset in yeast systems, demonstrating its robustness in identifying evolutionarily conserved sequence motifs. Furthermore, our newly generated experimental data corroborated the effect of most of the identified motifs based on MTtrans trained using multiple public datasets, further demonstrating the utility of MTtrans for discovering generalisable motifs.
ConclusionsMTtrans effectively integrates biological insights from diverse experiments and allows robust extraction of translation-associated sequence motifs in 5UTR. | bioinformatics |
GraphPred: An approach to predict multiple DNA motifs from ATAC-seq data using graph neural network and coexisting probability Assay for Transposase-Accessible Chromatin sequencing (ATAC-seq) utilizes hyperactive Tn5 transposase to cut open chromatin and reveal chromatin accessibility at a genome-wide level. ATAC-seq can reveal more kinds of transcription factor binding regions than Chromatin immunoprecipitation sequencing (ChIP-seq) and DNase I hypersensitive sites sequencing (DNase-seq). Transcription factor binding sites (TFBSs) prediction is a crucial step to reveal the functions of TFs from the high throughput sequencing data. TFBSs of the same TF tend to be conserved in the sequence level, which is named motif. Several deep learning models based on the convolutional neural networks are used to find motifs from ATAC-seq data. However, these methods didnt take into account that multiple TFs bind to a given sequence and the probability that a fragment of a given sequence is a TFBS. To find binding sites of multiple TFs, we developed a novel GNN model named GraphPred for TFBSs prediction and finding multiple motifs using the coexisting probability of k-mers. In the light of the experiment results, GraphPred can find more and higher quality motifs from 88 ATAC-seq datasets than comparison tools. Meanwhile, GraphPred achieved an area of eight metrics radar (AEMR) score of 2.31. | bioinformatics |
A real data-based simulation procedure to select an imputation strategy for mixed-type trait data Missing observations in trait datasets pose an obstacle for analyses in myriad biological disciplines. Imputation offers an alternative to removing cases with missing values from datasets. Imputation techniques that incorporate phylogenetic information into their estimations have demonstrated improved accuracy over standard techniques. However, previous studies of phylogenetic imputation tools are largely limited to simulations of numerical trait data, with categorical data not evaluated. It also remains to be explored whether the type of genetic data used affects imputation accuracy. We conducted a real data-based simulation study to compare the performance of imputation methods using a mixed-type trait dataset (lizards and amphisbaenians; order: Squamata). Selected methods included mean/mode imputation, k-nearest neighbour, random forests, and multivariate imputation by chained equations (MICE). Known values were removed from a complete-case dataset to simulate different missingness scenarios: missing completely at random (MCAR), missing at random (MAR), and missing not at random (MNAR). Each method (with and without phylogenetic information derived from mitochondrial and nuclear gene trees) was used to impute the removed values. The performances of the methods were evaluated for each trait and in each missingness scenario. A random forest method supplemented with a nuclear-derived phylogeny performed best overall, and this method was used to impute missing values in the original squamate dataset. Data with imputed values better reflected the characteristics and distributions of the original data compared to the complete-case data. However, phylogeny did not always improve performance for every trait and in every missingness scenario, and caution should be taken when imputing trait data, particularly in cases of extreme bias. Ultimately, these results support the use of a real data-based simulation procedure to select a suitable imputation strategy for a given mixed-type trait dataset. Moreover, they highlight the potential biases that complete-case usage may introduce into analyses.
Author summaryThe issue of missing data is problematic in trait datasets as observations for rare or threatened species are often missing disproportionately. When only complete cases are used in an analysis, derived results may be biased. Imputation is an alternative to complete-case analysis and entails filling in the missing values using known observations. It has been demonstrated that including phylogenetic information in the imputation process improves accuracy of predicted values. However, most previous evaluations of imputation methods for trait datasets are limited to numerical, simulated data, with categorical traits not considered. Using a reptile dataset comprised of both numerical and categorical trait data, we employed a real data-based simulation strategy to select an optimal imputation method for the dataset. We evaluated the performance of four different imputation methods across different missingness scenarios (e.g. missing completely at random, values missing disproportionately for smaller species. Results indicate that imputed data better reflected the original dataset characteristics compared to complete-case data; however, the optimal imputation strategy for a given scenario was contingent on missingness scenario and trait type. As imputation performance varies depending on the properties of a given dataset, a real data-based simulation strategy can be used to provide guidance on best imputation practices. | bioinformatics |
Probing single cell fermentation flux and intercellular exchange networks via pH-microenvironment sensing and inverse modeling The homeostatic control of their environment is an essential task of living cells. It has been hypothesized that when microenvironmental pH inhomogeneities are induced by high cellular metabolic activity, diffusing protons act as signaling molecules, driving the establishment of cross-feeding networks sustained by the cell-to-cell shuttling of overflow products such as lactate. Despite their fundamental role, the extent and dynamics of such networks is largely unknown due to the lack of methods in single cell flux analysis. In this study we provide direct experimental characterization of such exchange networks. We devise a method to quantify single cell fermentation fluxes over time by integrating high-resolution pH microenvironment sensing via ratiometric nanofibers with constraint-based inverse modeling. We apply our method to cell cultures with mixed populations of cancer cells and fibroblasts. We find that the proton trafficking underlying bulk acidification is strongly heterogeneous, with maximal single cell fluxes exceeding typical values by up to 3 orders of magnitude. In addition, a crossover in time from a networked phase sustained by densely connected "hubs" (corresponding to cells with high activity) to a sparse phase dominated by isolated dipolar motifs (i.e. by pair-wise cell-to-cell exchanges) is uncovered, which parallels the time course of bulk acidification. Our method promises to shed light on issues ranging from the homeostatic function of proton exchange to the metabolic coupling of cells with different energetic demands, and paves the way for real-time non-invasive single cell metabolic flux analysis. | biophysics |
Digital holography-based 3D particle localisation for single molecule tweezer techniques We present a three-dimensional imaging technique for fast tracking of microscopic objects in a fluid environment. Our technique couples digital holographic microscopy with three-dimensional localisation via parabolic masking. Compared with existing approaches, our method reconstructs 3D volumes from single-plane images, which greatly simplifies image acquisition, reduces the demand on microscope hardware, and facilitates tracking higher densities of microscopic particles while maintaining similar levels of precision. We demonstrate utility of this method in magnetic tweezer experiments, opening their use to multiplexed single-molecule force spectroscopy assays. We propose that our technique will also be useful in other applications that involve the tracking of microscopic objects in three dimensions.
SIGNIFICANCETracking objects in 3D is a common task in biology, but typically requires the acquisition of image stacks, which is limited by speed, the depth of field of microscope objectives and by the presence of other objects that obscure the illumination. Here we develop HoloMiP (Holographic Microscopy with Parabolic masking), which uses digital holography to reconstruct the three-dimensional images from a single plane allowing tracking of light-scattering objects in 3D. HoloMiP outperforms existing methods in precision, speed, simplicity and tolerance to crowding. We show that it is particularly suitable for fast, multiplexed magnetic tweezer experiments, opening new avenues to high-throughput force spectroscopy. | biophysics |
Mapping mechanical stress in curved epithelia of designed size and shape The function of organs such as lungs, kidneys and mammary glands relies on the three-dimensional geometry of their epithelium. To adopt shapes such as spheres, tubes and ellipsoids, epithelia generate mechanical stresses that are generally unknown. Here we engineered curved epithelial monolayers of controlled size and shape and mapped their state of stress. We designed pressurized epithelia with circular, rectangular and ellipsoidal footprints. We developed a computational method to map the stress tensor in these epithelia. This method establishes a direct correspondence between epithelial shape and mechanical stress without assumptions of material properties. In epithelia with spherical geometry spanning more than one order of magnitude in radius, we show that stress weakly increases with areal strain in a size-independent manner. In epithelia with rectangular and ellipsoidal cross-section we found pronounced stress anisotropies consistent with the asymmetric distribution of tractions measured at the cell-substrate contact line. In these anisotropic profiles, cell shape tended to align with the direction of maximum principal stress but this alignment was non-universal and depended on epithelial geometry. Besides interrogating the fundamental mechanics of epithelia over a broad range of sizes and shapes, our approach will enable a systematic study of how geometry and stress influence epithelial fate and function in three-dimensions. | biophysics |
Sensitization to Ionizing Radiation by MEK inhibition is Dependent on SNAI2 in Fusion-negative Rhabdomyosarcoma In fusion-negative rhabdomyosarcoma (FN-RMS), a pediatric malignancy with skeletal muscle characteristics, > 90% of high-risk patients have mutations that activate the RAS/MEK signaling pathway. We recently discovered that SNAI2, in addition to blocking myogenic differentiation downstream of MEK signaling in FN-RMS, represses pro-apoptotic BIM expression to protect RMS tumors from ionizing radiation (IR). As clinically relevant concentrations of the MEK inhibitor trametinib elicit poor responses in preclinical xenograft models, we investigated the utility of low-dose trametinib in combination with IR for the treatment of RAS-mutant FN-RMS. We hypothesized that trametinib would sensitize FN-RMS to IR through its downregulation of SNAI2 expression. While we observed little to no difference in myogenic differentiation or cell survival with trametinib treatment alone, robust differentiation and reduced survival were observed after IR. Additionally, IR-induced apoptosis was significantly increased in FN-RMS cells treated concurrently with trametinib, as was increased BIM expression. SNAI2s role in these processes was established using overexpression rescue experiments, where overexpression of SNAI2 prevented IR-induced myogenic differentiation and apoptosis. Moreover, combining MEK inhibitor with IR resulted in complete tumor regression and a 2-4-week delay in event free survival (EFS) in preclinical xenograft and PDX models. Our findings demonstrate that the combination of MEK inhibition and IR results in robust differentiation and apoptosis, due to the reduction of SNAI2, which leads to extended EFS in FN-RMS. SNAI2 thus is a biomarker of IR insensitivity and target for future therapies to sensitize aggressive sarcomas to IR. | cancer biology |
Modeling Reactive Species Metabolism in Colorectal Cancer for Identifying Metabolic Targets and Devising Therapeutics Reactive species (RS) are known to play significant roles in cancer development as well as in treating or managing cancer. On the other hand, genome scale metabolic models are being used to understand cell metabolism in disease contexts including cancer, and also in planning strategies to handle diseases. Despite their crucial roles in cancers, the reactive species have not been adequately modeled in the genome scale metabolic models (GSMMs) when probing disease models for their metabolism or detection of drug targets. In this work, we have developed a module of reactive species reactions, which is scalable - it can be integrated with any human metabolic model as it is, or with any metabolic model with fine-tuning. When integrated with a cancer (colorectal cancer in this case) metabolic model, the RS module highlighted the deregulation occurring in important CRC pathways such as fatty acid metabolism, cholesterol metabolism, arachidonic acid and eicosanoid metabolism. We show that the RS module helps in better deciphering crucial metabolic targets for devising better therapeutics such as FDFT1, FADS2 and GUK1 by taking into account the effects mediated by reactive species during colorectal cancer progression. The results from this reactive species integrated CRC metabolic model reinforces ferroptosis as a potential target for colorectal cancer therapy. | systems biology |
Excess glutamate release triggers subunit-specific homeostatic receptor scaling Ionotropic glutamate receptors (GluRs) are targets for modulation in Hebbian and homeostatic synaptic plasticity and are remodeled by development, experience, and disease. Although much is known about activity-dependent mechanisms that regulate GluR composition and abundance, the role of glutamate itself in these processes is unclear. To determine how glutamate sculpts GluR receptive fields, we have manipulated synaptically released glutamate and generated precise CRISPR mutations in the two postsynaptic GluR subtypes at the Drosophila neuromuscular junction, GluRA and GluRB. We first demonstrate that GluRA and GluRB compete to establish postsynaptic receptive fields, and that proper GluR abundance and localization can be orchestrated in the absence of any synaptic glutamate release. However, excess glutamate release adaptively tunes postsynaptic GluR abundance, echoing GluR receptor scaling observed in mammalian systems. Unexpectedly, when GluRA vs GluRB competition is eliminated, excess glutamate homeostatically regulates GluRA abundance, while GluRB abundance is now insensitive to glutamate modulation. Finally, Ca2+ impermeable GluRA receptors are no longer sensitive to homeostatic regulation by glutamate. Thus, excess glutamate, GluR competition, and Ca2+ signaling collaborate to selectively target GluR subtypes for homeostatic regulation at postsynaptic compartments. | neuroscience |
Metacognitive domains are not aligned along a dimension of internal-external information source It is still debated whether metacognition, or the ability to monitor our own mental states, relies on mechanisms that are domain-general (a single mechanism can account for the monitoring of any mental process) or domain-specific (metacognition is accomplished by a collection of multiple monitoring modules, one for each cognitive domain). It has been speculated that two broad categories of metacognitive mechanisms may exist: those that monitor primarily externally-generated vs. those that monitor primarily internally-generated information.
To test this proposed division, we measured metacognitive performance (using m-ratio, a signal detection theoretical measure) in four tasks that could be ranked along an internal-external axis of the source of information, namely memory, motor, visuomotor and visual tasks. We found correlations between m-ratios in visuomotor and motor tasks only; but no correlations between m-ratios in visual and visuomotor tasks, or between motor and memory tasks.
While we found no correlation in metacognitive ability between visual and memory tasks, and a positive correlation between visuomotor and motor tasks, we found no evidence for a correlation between motor and memory tasks. This pattern of correlations does not support the grouping of domains based on whether the source of information is primarily internal or external. We suggest that other groupings could be more reflective of the nature of metacognition and discuss the need to consider other non-domain task-features when using correlations as a way to test the underlying shared mechanisms between domains. | neuroscience |
EEG Frequency Tagging Objectively Measures Biological Motion Perception Various neuroimaging techniques have been developed to study the brain processes underlying biological motion perception. However, brain activity during movement perception captures a multitude of components. As a result, it is often unclear which components reflect the processing of the movement and which components reflect other, secondary processes that build on movement processing (e.g., inferring the agents mood or identity). To address this issue, we developed and validated a new approach that objectively defines the brain response associated with biological motion perception. Specifically, we showed 30 male and female adults a point-light walker moving at a pace of 2.4 Hz and used EEG frequency tagging to measure the brain response coupled to that pace. The results revealed a reliable response at the walking frequency that was reduced by two manipulations known to disrupt biological motion perception, namely phase scrambling and inversion. Interestingly, we also identified a brain response at half the walking frequency (i.e., 1.2 Hz), corresponding to the rate at which the individual dots repeated their trajectory. In contrast to the 2.4 Hz response, the response at 1.2 Hz was increased for scrambled walkers. These results indicate that frequency tagging can be used to measure the visual processing of biological movements and can dissociate between the global (2.4 Hz) and local (1.2 Hz) processes involved in biological motion perception, at different frequencies of the brain signal. | neuroscience |
Disentangling object category representations driven by dynamic and static visual input Humans can label and categorize objects in a visual scene with high accuracy and speed--a capacity well-characterized with neuroimaging studies using static images. However, motion is another cue that could be used by the visual system to classify objects. To determine how motion-defined object category information is processed in the brain, we created a novel stimulus set to isolate motion-defined signals from other sources of information. We extracted movement information from videos of 6 object categories and applied the motion to random dot patterns. Using these stimuli, we investigated whether fMRI responses elicited by motion cues could be decoded at the object category level in functionally defined regions of occipitotemporal and parietal cortex. Participants performed a one-back repetition detection task as they viewed motion-defined stimuli or static images from the original videos. Linear classifiers could decode object category for both stimulus formats in all higher order regions of interest. More posterior occipitotemporal and ventral regions showed higher accuracy in the static condition and more anterior occipitotemporal and dorsal regions showed higher accuracy in the dynamic condition. Significantly above chance classification accuracies were also observed in all regions when training and testing the SVM classifier across stimulus formats. These results demonstrate that motion-defined cues can elicit widespread robust category responses on par with those elicited by luminance cues in regions of object-selective visual cortex. The informational content of these responses overlapped with, but also demonstrated interesting distinctions from, those elicited by static cues.
Significance StatementMuch research on visual object recognition has focused on recognizing objects in static images. However, motion cues are a rich source of information that humans might also use to categorize objects. Here, we present the first study to compare neural representations of several animate and inanimate objects when category information is presented in two formats: static cues or isolated dynamic cues. Our study shows that while higher order brain regions differentially process object categories depending on format, they also contain robust, abstract category representations that generalize across format. These results expand our previous understanding of motion-derived animate and inanimate object category processing and provide useful tools for future research on object category processing driven by multiple sources of visual information. | neuroscience |
Organic Convolution Model of Ventral Visual Path Reproduces the Fine Structure of Shape Tuning in Area V4 This modeling study investigates whether an orderly convergence of neuronal selectivities from cortical areas V1 and V2 can produce the fine structure of shape selective receptive fields found in area V4 recordings. A model of fast object recognition in the ventral visual pathway is made of spiking neurons having simple convergent functional micro-architectures. The model is based on recent findings about the convergent properties of V2 neurons on V1 afferents and makes a novel proposal for how V4 neurons may create selectivity for local curvature through the orderly convergence of different types of afferent inputs from V2. The model also demonstrates a novel method for simulating spiking neurons using tensor programming and GPU hardware: Assuming that convergent functional micro-architectural patterns repeat in topographically organized visual space, the details of individual unit depolarization and spike time is modeled using convolution operations augmented with a custom tensor model of post-synaptic potentials. The model, described as Organic Convolution, suggests that convergent selectivity patterns equivalent to convolution can be created by developmental mechanisms, laying the foundation for object recognition before an organism learns from experience. This study does not investigate developmental mechanisms directly but, using convergent patterns that are hand crafted to match neurophysiological data, shows that the mechanisms giving rise to object recognition may be very simple. As a result, the model suggests an alternative point of view on how deep neural networks may relate to biology. | neuroscience |
Hippocampal subfields and their neocortical interactions during autobiographical memory using submillimeter whole-brain fMRI at 7 Tesla Recent advances in ultra-high field 7 Tesla magnet resonance imaging (7T MRI) have provided unprecedented opportunities to gain insights into the brain mechanisms supporting human cognition. The hippocampus, a heterogeneous brain structure comprising several smaller subfields has been firmly established to play a central role during vivid re-experiencing of autobiographical memories (AM). However, due to technical limitations inherent to MRI investigations of the hippocampus, how hippocampal subfields differentially support AM and how hippocampal subfields functionally connect with other brain regions typically associated with AM retrieval remains elusive. To tackle this knowledge gap, we leveraged technical advances of parallel imaging and employed a customized Echo Planar Imaging (EPI) sequence at 0.9 mm isotropic voxel size over the whole brain while participants re-experienced vivid, detail-rich AM. In addition, we developed a processing pipeline that allows the examination of differential activation of hippocampal subfields in single subject space as well as hippocampal-neocortical interactions at a group level. We found that all hippocampal subfields were engaged during AM retrieval but that one specific hippocampal subfield, the pre/parasubiculum, contributed over and above the other subfields to AM retrieval. Moreover, functional connectivity analyses revealed that the pre/parasubiculum was the only hippocampal subfield that strongly connected to other brain regions typically associated with AM, such as ventromedial prefrontal cortex (vmPFC) and medial/lateral parietal regions. Our results support recent proposals that the pre/parasubiculum may play an essential role in cognitive tasks that rely heavily on visual imagery, such as the vivid re-experience of personal past events. | neuroscience |
A hippocampal-anterior thalamic circuit associated with learning rate in ageing Memory normally declines with ageing and these age-related cognitive changes are associated with changes in brain structure. Episodic memory retrieval has been widely studied during ageing, whereas learning has received less attention. Here we examined the neural correlates of learning rate in ageing. Our study sample consisted of 982 cognitively healthy female and male older participants from the Vallecas Project cohort, without a clinical diagnosis of mild cognitive impairment or dementia. The learning rate across three consecutive verbal memory (Free and Cued Selective Reminding Test) recall trials was used as a predictor of grey matter (GM) and white matter (WM) volume using voxel-based morphometry, and WM microstructure using tract-based spatial statistics on fractional anisotropy (FA) and mean diffusivity (MD) measures. Immediate recall improved by 1.4 items per trial on average, and this learning rate was faster in women and negatively associated with age. Structurally, hippocampal and anterior thalamic GM volume correlated positively with learning rate. Learning also correlated with the integrity of WM microstructure (high FA and low MD) in an extensive network of tracts including bilateral anterior thalamic radiation, fornix, and long-range tracts. These results suggest that structural GM and WM characteristics, centred on a hippocampal-anterior thalamic circuit, support learning capacity in ageing. Specifically, reduced volume and microstructure may explain some of the age-related memory deficits that result from impaired learning.
Significance statementA detailed understanding of age-related memory changes is crucial in an increasingly ageing population, in which memory decline is prevalent. Whilst memory performance is usually quantified by the ability to correctly retrieve information, memory impairment could be caused by a reduced ability to learn or encode information. In a cohort of cognitively healthy ageing participants, we found an association between verbal learning rate and grey matter volume and white matter microstructure in the limbic system. These findings establish the neural underpinnings of the often-overlooked learning phase of the memory process and have important implications for our understanding of neurobiological changes in healthy ageing and their cognitive phenotypes. | neuroscience |
Mixtures of large-scale dynamic functional brain network modes Accurate temporal modelling of functional brain networks is essential in the quest for understanding how such networks facilitate cognition. Researchers are beginning to adopt time-varying analyses for electrophysiological data that capture highly dynamic processes on the order of milliseconds. Typically, these approaches, such as clustering of functional connectivity profiles and Hidden Markov Modelling (HMM), assume mutual exclusivity of networks over time. Whilst a powerful constraint, this assumption may be compromising the ability of these approaches to describe the data effectively. Here, we propose a new generative model for functional connectivity as a time-varying linear mixture of spatially distributed statistical "modes". The temporal evolution of this mixture is governed by a recurrent neural network, which enables the model to generate data with a rich temporal structure. We use a Bayesian framework known as amortised variational inference to learn model parameters from observed data. We call the approach DyNeMo (for Dynamic Network Modes), and show using simulations it outperforms the HMM when the assumption of mutual exclusivity is violated. In resting-state MEG, DyNeMo reveals a mixture of modes that activate on fast time scales of 100-150 ms, which is similar to state lifetimes found using an HMM. In task MEG data, DyNeMo finds modes with plausible, task-dependent evoked responses without any knowledge of the task timings. Overall, DyNeMo provides decompositions that are an approximate remapping of the HMMs while showing improvements in overall explanatory power. However, the magnitude of the improvements suggests that the HMMs assumption of mutual exclusivity can be reasonable in practice. Nonetheless, DyNeMo provides a flexible framework for implementing and assessing future modelling developments. | neuroscience |
State Dependent Coupling of Hippocampal Oscillations Oscillations occurring simultaneously in a given area represent a physiological unit of brain states. They allow for temporal segmentation of spikes and support distinct behaviors. To establish how multiple oscillatory components co-varies simultaneously and influence neuronal firing during sleep and wakefulness, we describe a multi-variate analytical framework for constructing the state space of hippocampal oscillations. Examining the co-occurrence patterns of oscillations on the state space, across species, uncovered the presence of network constraints and distinct set of cross-frequency interactions during wakefulness as compared to sleep. We demonstrated how the state space can be used as a canvas to map the neural firing and found that distinct neurons during navigation were tuned to different set of simultaneously occurring oscillations during sleep. This multivariate analytical framework provides a window to move beyond classical bivariate pipelines, for investigating oscillations and neuronal firing, thereby allowing to factor-in the complexity of oscillation-population interactions. | neuroscience |
Using Transfer Learning for Automated Microbleed Segmentation IntroductionCerebral microbleeds are small perivascular haemorrhages that can occur in both grey and white matter brain regions. Microbleeds are a marker of cerebrovascular pathology, and are associated with an increased risk of cognitive decline and dementia. Microbleeds can be identified and manually segmented by expert radiologists and neurologists, usually from susceptibility-contrast MRI. The latter is hard to harmonize across scanners, while manual segmentation is laborious, time-consuming, and subject to inter- and intra-rater variabiltiy. Automated techniques so far have shown high accuracy at a neighborhood ("patch") level at the expense of a high number of false positives voxel-wise lesions. We aimed to develop an automated, more precise microbleeds segmentation tool able to use standardizable MRI contrasts.
MethodsWe first trained a ResNet50 network on another MRI segmentations task (cerberospinal fluid versus background segmentation) using T1-weighted, T2-weighted, and T2* MRI. We then used transfer learning to train the network for the detection of microbleeds with the same contrasts. As a final step, we employed a combination of morphological operators and rules at the local lesion level to remove false positives. Manual segmentations of microbleeds from 78 participants were used to train and validate the system. We assessed the impact of patch size, freezing weights of the initial layers, mini-batch size, learning rate, as well as data augmentation on the performance of the Microbleed ResNet50 network.
ResultsThe proposed method achieved a high performance, with a patch-level sensitivity, specificity, and accuracy of 99.57%, 99.16%, and 99.93%, respectively. At a per lesion level, sensitivity, precision, and Dice similarity index values were 89.1%, 20.1%, and 0.28 for cortical GM; 100%, 100%, and 1.0 for deep GM; and 91.1%, 44.3%, and 0.58 for WM, respectively.
DiscussionThe proposed microbleed segmentation method is more suitable for the automated detection of microbleeds with high sensitivity. | neuroscience |
Direct observation of the neural computations underlying a single decision Neurobiological investigations of perceptual decision-making have furnished the first glimpse of a flexible cognitive process at the level of single neurons1,2. Neurons in the parietal and prefrontal cortex3-6 are thought to represent the accumulation of noisy evidence, acquired over time, leading to a decision. Neural recordings averaged over many decisions have provided support for the deterministic rise in activity to a termination bound7. Critically, it is the unobserved stochastic component that is thought to confer variability in both choice and decision time8. Here, we elucidate this stochastic, diffusion-like signal on individual decisions by recording simultaneously from hundreds of neurons in the lateral intraparietal cortex (LIP). We show that a small subset of these neurons, previously studied singly, represent a combination of deterministic drift and stochastic diffusion--the integral of noisy evidence--during perceptual decision making, and we provide direct support for the hypothesis that this diffusion signal is the quantity responsible for the variability in choice and reaction times. Neuronal state space and decoding analyses, applied to the whole population, also identify the drift diffusion signal. However, we show that the signal relies on the subset of neurons with response fields that overlap the choice targets. This parsimonious observation would escape detection by these powerful methods, absent a clear hypothesis. | neuroscience |
Space-time resolved inference-based whole-brain neurophysiological mechanism imaging: application to resting-state alpha rhythm Neural mechanisms are complex and difficult to image. This paper presents a new space-time resolved whole-brain imaging framework, called Neurophysiological Mechanism Imaging (NMI), that identifies neurophysiological mechanisms within cerebral cortex at the macroscopic scale. By fitting neural mass models to electromagnetic source imaging data using a novel nonlinear inference method, population averaged membrane potentials and synaptic connection strengths are efficiently and accurately imaged across the whole brain at a resolution afforded by source imaging. The efficiency of the framework enables return of the augmented source imaging results overnight using high performance computing. This suggests it can be used as a practical and novel imaging tool. To demonstrate the framework, it has been applied to resting-state magnetoencephalographic source estimates. The results suggest that endogenous inputs to cingulate, occipital, and inferior frontal cortex are essential modulators of resting-state alpha power. Moreover, endogenous input and inhibitory and excitatory neural populations play varied roles in mediating alpha power in different resting-state sub-networks. The framework can be applied to arbitrary neural mass models and has broad applicability to image neural mechanisms in different brain states.
HighlightsO_LIThe whole-brain imaging framework can disclose the neurophysiological substrates of complicated brain functions in a spatiotemporal manner.
C_LIO_LIDeveloped a semi-analytical Kalman filter to estimate neurophysiological variables in the nonlinear neural mass model efficiently and accurately from large-scale electromagnetic time-series.
C_LIO_LIThe semi-analytical Kalman filter is 7.5 times faster and 5% more accurate in estimating model parameters than the unscented Kalman filter.
C_LIO_LIProvided several group-level statistical observations based on neurophysiological variables and visualised them in a whole-brain manner to show different perspectives of neurophysiological mechanisms.
C_LIO_LIApplied the framework to study resting-state alpha oscillation and found novel relationships between local neurophysiological variables in specific brain regions and alpha power.
C_LI | neuroscience |
Dendrify: a new framework for seamless incorporation of dendrites in Spiking Neural Networks Computational modeling has been indispensable for understanding how subcellular neuronal features influence circuit processing. However, the role of dendritic computations in network-level operations remains largely unexplored. This is partly because existing tools do not allow the development of realistic and efficient network models that account for dendrites. Current spiking neural networks, although efficient, are usually quite simplistic, overlooking essential dendritic properties. Conversely, circuit models with morphologically detailed neuron models are computationally costly, thus impractical for large-network simulations. To bridge the gap between these two extremes, we introduce Dendrify, an open-source Python package compatible with Brian2, designed to facilitate the development of bioinspired spiking neural networks. Dendrify, through simple commands, automatically generates reduced compartmental neuron models with simplified yet biologically relevant dendritic and synaptic integrative properties. Such models strike a good balance between flexibility, performance, and biological accuracy, allowing us to explore dendritic contributions to network-level functions while paving the way for developing more powerful neuromorphic systems. | neuroscience |
Learning of new associations invokes a major change in modulations of cortical beta oscillations in human adults Large-scale cortical beta ({beta}) oscillations have been implicated in the learning processes but their exact role is debated. We explored the dynamics of {beta}-oscillations while 25 adult participants learned, through trial and error, novel associations between four auditory pseudowords and movements of four body extremities. We used MEG to evaluate learninginduced changes in beta modulation accompanying cue-triggered movements.
Our findings showed that spatial-temporal characteristics of movement-related {beta}-oscillations underwent a major transition as learning proceeded. Early in learning, suppression of {beta}-power in multiple cortical areas occurred long before movement initiation and sustained throughout the whole behavioral trial. As learning advanced and task performance reached asymptote, {beta}suppression was replaced by a widespread and prolonged rise in {beta}-power. The {beta}-power rise started shortly after the initiation of correct motor response and mainly comprised the prefrontal and medial temporal regions of the left hemisphere. This post-decision {beta}-power predicted trial-by-trial response times (RT) at both stages of learning (before and after the rules become familiar) but in opposite ways. When a subject started to acquire associative rules and gradually improved task performance, a decrease in RT was correlated with the increase in the post-decision {beta}-band power. Repeatedly correct implementation of the learned rules reversed this correlation in the opposite direction with faster (more confident) responses associated with the weaker post-decision {beta}-band synchronization.
Our findings suggest that maximal beta activity is pertinent to a distinct stage of learning and may serve to strengthen the newly learned association in a distributed memory network. | neuroscience |
Cardiac interoception is enhanced in blind individuals Blind individuals have superior abilities to perform perceptual tasks that rely on exteroceptive information, since visual deprivation is associated with massive cross-modal plasticity. However, it is unknown whether neuroplasticity after visual loss also affects interoception, i.e., the sensations arising from ones inner organs that convey information about the physiological state of the body. Herein, we examine the influence of blindness on cardiac interoception, which is an interoceptive submodality that has important links to emotional processing and bodily self-awareness. We tested 36 blind and 36 age-and sex-matched sighted volunteers and examined their cardiac interoceptive ability using a well-established heartbeat counting task. The results showed that blind individuals had significantly higher accuracy in perceiving their heartbeat than did individuals in a matched sighted control group. In contrast, there were no significant differences between the groups in the metacognitive dimensions of cardiac interception or the purely physiological measurement of heart rate, thereby underscoring that the improved accuracy likely reflects a superior perceptual sensitivity to cardiac interoceptive signals in blind individuals. We conclude that visual deprivation leads to enhanced interoception, which has important implications for the study of the extent of massive cross-modal plasticity after visual loss, understanding emotional processing in blind individuals, and learning how bodily self-awareness can develop and be sustained in the absence of visual experience. | neuroscience |
Characterizing ketamine-induced dissociation using human intracranial neurophysiology: brain dynamics, network activity, and interactions with propofol Subanesthetic doses of ketamine produce rapid and sustained anti-depressant effects in patients with treatment-resistant depression. Unfortunately, the usefulness of ketamine as a treatment is limited by its potential for abuse because of psychotropic side effects such as dissociation. Understanding the brain dynamics and the neural circuits involved in ketamines effects could lend insight into improved therapies for depression with fewer adverse effects. It is believed that ketamine acts via NMDA receptor and hyperpolarization-activated cyclic nucleotide-gated 1 (HCN1) channels to produce changes in oscillatory brain dynamics. Here we show, in humans, a detailed description of the principal oscillatory changes in cortical and subcortical structures by administration of a subanesthetic dose of ketamine. Using recordings from intracranial electrodes, we found that ketamine increased gamma oscillations within prefrontal cortical areas and the hippocampus--structures previously implicated in ketamines antidepressant effects. Furthermore, our studies provide direct evidence of a ketamine-induced 3 Hz oscillation in posteromedial cortex that has been proposed as a mechanism for its dissociative effects. By analyzing changes in neural oscillations after the addition of propofol, whose GABAergic activity antagonizes ketamines NMDA-mediated disinhibition alongside a shared HCN1 inhibitory effect, we identified brain dynamics that could be attributed to NMDA-mediated disinhibition versus HCN1 inhibition. Overall, our results imply that ketamine engages different neural circuits in distinct frequency-dependent patterns of activity to produce its antidepressant and dissociative sensory effects. These insights may help guide the development of novel brain dynamic biomarkers and therapeutics for depression. | neuroscience |
Gestational day 12 moderate prenatal alcohol exposure produces sex-specific social impairments and attenuates prelimbic excitability and amygdala-cortex modulation of adult social behavior. Lifelong social impairments are common in individuals with prenatal alcohol exposure (PAE), and preclinical studies have identified gestational day (G)12 as a vulnerable timepoint for producing social deficits following binge-level PAE. While moderate (m)PAE also produces social impairments, the long-term neuroadaptations underlying them are poorly understood. Activity of the projection from the basolateral amygdala to the prelimbic cortex (BLA[->]PL) leads to social avoidance, and the PL alone is implicated in negative social behaviors, making each of these potential candidates for the neuroadaptations underlying mPAE-induced social impairments. To examine this, we first established that G12 mPAE produced sex-specific social impairments lasting into adulthood. We then chemogenetically inhibited the BLA[->]PL using Clozapine N-Oxide (CNO) during adult social testing. This revealed that CNO reduced social investigation in control males, but had no effect on mPAE males or females of either exposure, indicating that mPAE attenuated the role of this projection in regulating male social behavior and highlighting one potential mechanism by which mPAE affects male social behavior more severely. Using whole-cell electrophysiology, we also examined mPAE-induced changes to PL pyramidal cell physiology and determined that mPAE reduced the excitability of these cells, likely due to increased suppression by inhibitory interneurons. Overall, this work identified two mPAE-induced neuroadaptations that last into adulthood and which may underlie the sexspecific vulnerability to mPAE-induced social impairments. Future research is necessary to expand upon how these circuits modulate both normal and pathological social behavior, and to identify sex-specific mechanisms leading to differential vulnerability in males and females. | neuroscience |
Multifaceted role of RIMBP2 in promoting hearing in murine cochlear hair cells In peripheral, the mammalian cochlea is a remarkable sensory apparatus, owning to its outer and inner hair cells (OHCs and IHCs) that amplify and transmit auditory signals to the brain, respectively. Rab3-interacting molecular (RIM) binding protein 2 (RIMBP2) is widely expressed in receptor cells and neurons, specifically in the active zones for exocytosis of synaptic vesicles (SVs), but its exact functions in the cochlea are not very well understood. We therefore generated a Rimbp2 knockout mouse model (Rimbp2-/-), which exhibited severely impaired hearing with not only elevated hearing thresholds but also increased latencies and reduced amplitudes in the Wave I of their auditory brainstem responses (ABRs). Consistent with the threshold elevation, we found significant loss of OHCs, likely through apoptosis, in the Rimbp2-/- cochlea. Consistent with changes observed in the ABR Wave I, we found greatly reduced exocytosis, both spontaneously and upon stimulation, in Rimbp2-/- IHCs. Specifically, our patch-clamp analysis on IHCs and postsynaptic spiral ganglion neurons (SGNs) revealed not only reduced readily releasable pool (RRP) of SVs but also reduced sustained release rate, along with complete blockade of fast endocytosis, in Rimbp2-/- IHCs. Lastly, with immunostaining of whole-mounted cochleae, we found that while the number of ribbon synapses in Rimbp2-/- IHCs was unchanged, their localization moved subtly but significantly towards the basal pole of IHCs. Taken together, we uncovered an unexpected role of RIMBP2 for OHC survival and a more extensive role in promoting IHC exocytosis than previously believed. | neuroscience |
Replication-competent HIV-1 in human alveolar macrophages and monocytes despite nucleotide pools with elevated dUTP Although CD4+ memory T cells are considered the primary latent reservoir for HIV-1, replication competent HIV has been detected in tissue macrophages in both animal and human studies. During in vitro HIV infection, the depleted nucleotide pool and high dUTP levels in monocyte derived macrophages (MDM) leads to proviruses with high levels of dUMP, which has been implicated in viral restriction or reduced transcription depending on the uracil base excision repair (UBER) competence of the macrophage. Incorporated dUMP has also been detected in viral DNA from circulating monocytes (MC) and alveolar macrophages (AM) of HIV infected patients on antiretroviral therapy (ART), establishing the biological relevance of this phenotype but not the replicative capacity of dUMP-containing proviruses. As compared to in vitro differentiated MDM, AM from normal donors had 6-fold lower levels of dTTP and a 6-fold increased dUTP/dTTP, indicating a highly restrictive dNTP pool for reverse transcription. Expression of uracil DNA glycosylase (UNG) was 8-fold lower in AM compared to the already low levels in MDM. Accordingly, [~]80% of HIV proviruses contained dUMP, which persisted for at least 14-days due to low UNG excision activity. Unlike MDM, AM expression levels of UNG and SAM and HD domain containing deoxynucleoside triphosphate triphosphohydrolase 1 (SAMHD1) increased over 14 days post-HIV infection, while dUTP nucleotidohydrolase expression decreased. These AM-specific effects suggest a restriction response centered on excising uracil from viral DNA copies and increasing relative dUTP levels. Despite the restrictive nucleotide pools, we detected rare replication competent HIV in AM, peripheral MC, and CD4+ T cells from ART-treated donors. These findings indicate that the potential integration block of incorporated dUMP is not realized during in vivo infection of AM and MC due to the near absence of UBER activity. In addition, the increased expression of UNG and SAMHD1 in AM post-infection is too slow to prevent integration. Accordingly, dUMP persists in integrated viruses, which based on in vitro studies, can lead to transcriptional silencing. This possible silencing outcome of persistent dUMP could promote viral latency until the repressive effects of viral dUMP are reversed. | microbiology |
Using Shape Fluctuations to Probe the Mechanics of Stress Granules Surface tension plays a significant role in many functions of biomolecular condensates, from governing the dynamics of droplet coalescence to determining how condensates interact with and deform lipid membranes and biological filaments. To date, however, there is a lack of accurate methods to measure the surface tension of condensates in living cells. Here, we present a high-throughput flicker spectroscopy technique that is able to analyse the thermal fluctuations of the surfaces of tens of thousands of condensates to extract the distribution of surface tensions. Demonstrating this approach on stress granules, we show for the first time that the measured fluctuation spectra cannot be explained by surface tension alone. It is necessary to include an additional energy contribution, which we attribute to an elastic bending rigidity and suggests the presence of structure at the granule-cytoplasm interface. Our data also show that stress granules do not have a spherical base-shape, but fluctuate around a more irregular geometry. Taken together, these results demonstrate quantitatively that the mechanics of stress granules clearly deviate from those expected for simple liquid droplets. | cell biology |
Cellular reprogramming with ATOH1, GFI1, and POU4F3 implicate epigenetic changes and cell-cell signaling as obstacles to hair cell regeneration in mature mammals Reprogramming of the cochlea with hair cell-specific transcription factors such as ATOH1 has been proposed as a potential therapeutic strategy for hearing loss. ATOH1 expression in the developing cochlea can efficiently induce hair cell regeneration but the efficiency of hair cell reprogramming declines rapidly as the cochlea matures. We developed Cre-inducible mice to compare hair cell reprogramming with ATOH1 alone or in combination with two other hair cell transcription factors, GFI1 and POU4F3. In newborn mice, all transcription factor combinations tested produced large numbers of cells with the morphology of hair cells and rudimentary mechanotransduction properties. However, one week later, only a combination of ATOH1, GFI1 and POU4F3 could reprogram non-sensory cells of the cochlea to a hair cell fate, and these new cells were less mature than cells generated by reprogramming one week earlier. We used scRNA-seq and combined scRNA-seq and ATAC-seq to suggest at least two impediments to hair cell reprogramming in older animals. First, hair cell gene loci become less epigenetically accessible in non-sensory cells of the cochlea with increasing age. Second, signaling from hair cells to supporting cells, including Notch signaling, can prevent reprogramming of many supporting cells to hair cells, even with three hair cell transcription factors. Our results shed light on the molecular barriers that must be overcome to promote hair cell regeneration in the adult cochlea. | developmental biology |
Identifying and separating the processes underlying boreal forest understory community assembly Identifying the ecological processes underlying community assembly remains an elusive goal in community ecology. We formalize assembly hypotheses as alternative models and apply each to predict 1,918 out-of-sample boreal forest understory communities to identify and separate the processes driving community assembly. Models are specified within a Bayesian joint species distribution framework that allows for the inclusion and separation of stochastic processes, environmental filtering, and two different species dependence structures. We found clear evidence that study communities are structured by both environmental filtering and compositional dependence highlighting the importance of selection in community assembly. The relative importance of environmental filtering was greater than compositional dependence in predicting both understory communities and the abundance of constituent species across broad suc-cessional and bioclimatic gradients. Contrary to ecological expectations, the inclusion of a flexible residual species dependence structure (accounting for more than compositional dependence) did not improve model predictions after accounting for the strong role of environmental filtering. Our results provide novel inference on the processes underlying community assembly facilitated by applying empirical approximations of alternative assembly processes to predict communities across a range of environmental conditions. | ecology |
Insights into the microbial strain mediated impact on pest insect development Molecular analyses of host-associated microorganisms have demonstrated the essential role that the microbiome plays in host development. Approaches targeting the sequencing of ribosomal genes have successfully identified key species of the host-associated microbiome. However, it remains unclear to what extent the strain-specific characteristics influence the outcome of the host-microbiome interactions. This is particularly important for insect pests, where microbial species might be used as targets for biocontrol purposes. Understanding strain-level variation represents thus a crucial step in determining the microbial impact on hosts. To investigate the microbial strain-level effects on an invasive insect pest, Drosophila suzukii, we compared the impact of monocultures and cocultures of different bacterial and yeast strains. We investigated whether different strains of Gluconobacter and Pichia differentially influenced the larval development of the pest. Fly trait measurements demonstrated beneficial, although variable, impact of these microbial strains on the fitness of suzukii. Using cocultures of microbial strains, we found that in some combinations, the beneficial effects were intermediate between those of the respective monocultures. In contrast, in other cases, strong inhibitory effects were observed. Hence, our study reports that strain-level effects within species are present in D. suzukii, reinforcing the importance of assessing the impact of associated microbiota on pest insects at the strain level.
HighlightsO_LIMicrobial strains make up an essential part of the diversity of an insect hosts
C_LIO_LICharacterizing and accounting for strain-specific impact on a pests life-history traits and different combinations of strains constitute an important step in our understanding of the pest management strategies.
C_LIO_LIWe investigated whether there was any strain-specific impact of bacteria and yeasts on the larval development of a frugivorous pest.
C_LIO_LIWe observed that strains varied in their impact, both as monocultures and cocultures, indicating their importance in modifying the host ecology.
C_LIO_LIOur study adds to the growing literature on the importance of strains in pest insects.
C_LI | ecology |
The damage-independent evolution of ageing by selective destruction Ageing is currently believed to reflect the accumulation of molecular damage due to energetic costs of maintenance, as proposed in disposable soma theory (DST). Here we use agent-based modelling to describe an alternative theory by which ageing could undergo positive selection independent of energetic costs. We suggest that the selective advantage of aberrant cells with fast growth might necessitate a mechanism of counterselection we name selective destruction that specifically removes the faster cells from tissues, preventing the morbidity and mortality risks they pose. The resulting survival advantage of slower mutants could switch the direction of selection, allowing them to outcompete both fast mutants and wildtype cells, causing them to spread and induce ageing in the form of a metabolic slowdown.
Selective destruction could therefore provide a proximal cause of ageing that is both consistent with the gene expression hallmarks of ageing, and independent of accumulating damage. Furthermore, negligible senescence would acquire a new meaning of increased basal mortality. | evolutionary biology |
Prediction of local convergent shifts in evolutionary rates with phyloConverge characterizes the phenotypic associations and modularity of regulatory elements Physiological and morphological adaptations to extreme environments arise from the molecular evolution of protein-coding regions and regulatory elements (REs) that regulate gene expression. Comparative genomics methods can characterize genetic elements that underlie the organism-level adaptations, but convergence analyses of REs are often limited by their evolutionary properties. A RE can be modularly composed of multiple transcription factor binding sites (TFBS) that may each experience different evolutionary pressures. The modular composition and rapid turnover of TFBS also enables a compensatory mechanism among nearby TFBS that allows for weaker sequence conservation/divergence than intuitively expected. Here, we introduce phyloConverge, a comparative genomics method that can perform fast, fine-grained local convergence analysis of genetic elements. phyloConverge calibrates for local shifts in evolutionary rates using a combination of maximum likelihood-based estimation of nucleotide substitution rates and phylogenetic permutation tests. Using the classical convergence case of mammalian adaptation to subterranean environments, we validate that phyloConverge identifies rate-accelerated conserved non-coding elements (CNEs) that are strongly correlated with ocular tissues, with improved specificity compared to competing methods. We use phyloConverge to perform TFBS-scale and nucleotide-scale scoring to dissect each CNE into subregions with uneven convergence signals and demonstrate its utility for understanding the modularity and pleiotropy of REs. Subterranean-accelerated regions are also enriched for molecular pathways and TFBS motifs associated with neuronal phenotypes, suggesting that subterranean eye degeneration may coincide with a remodeling of the nervous system. phyloConverge offers a rapid and accurate approach for understanding the evolution and modularity of regulatory elements underlying phenotypic adaptation. | evolutionary biology |
Subfunctionalized expression drives evolutionary retention of ribosomal protein paralogs in vertebrates The formation of paralogs through gene duplication is a core evolutionary process. For paralogs that encode components of protein complexes such as the ribosome, a central question is whether they encode functionally distinct proteins, or whether they exist to maintain appropriate total expression of equivalent proteins. Here, we systematically tested evolutionary models of paralog function using the mammalian ribosomal protein paralogs eS27 (Rps27) and eS27L (Rps27l) as a case study. We first showed that eS27 and eS27L have inversely correlated mRNA abundance across cell types, with the highest eS27 in lymphocytes and the highest eS27L in mammary alveolar cells and hepatocytes. By endogenously tagging the eS27 and eS27L proteins, we demonstrated that eS27- and eS27L- ribosomes associate preferentially with different transcripts. Furthermore, we generated murine eS27 and eS27L loss-of-function alleles that are homozygous lethal at different developmental stages. However, strikingly, we found that expressing eS27 protein from the endogenous eS27L locus, or vice versa, completely rescues loss-of-function lethality and yields mice with no detectable deficits. Together, these findings suggest that eS27 and eS27L are evolutionarily retained because their subfunctionalized expression patterns render both genes necessary to achieve the requisite total expression of two equivalent proteins across cell types. Our work represents the most in-depth characterization of a mammalian ribosomal protein paralog to date and highlights the importance of considering both protein function and expression when investigating paralogs. | genetics |
Reversing Radiation-Induced Immunosuppression Using a New Therapeutic Modality Radiation-induced immune suppression poses significant health challenges for millions of patients undergoing cancer chemotherapy and radiotherapy treatment, and astronauts and space tourists travelling to outer space. While a limited number of recombinant protein therapies, such a Sargramostim, are approved for accelerating hematologic recovery, the pronounced role of granulocyte-macrophage colony-stimulating factor (GM-CSF or CSF2) as a proinflammatory cytokine poses additional challenges in creating immune dysfunction towards pathogenic autoimmune diseases. Here we present an approach to high-throughput drug-discovery, target validation, and lead molecule identification using nucleic acid-based molecules. These Nanoligomer molecules are rationally designed using a bioinformatics and an artificial intelligence (AI)-based ranking method and synthesized as a single-modality combining 6-different design elements to up- or downregulate gene expression of target gene, resulting in elevated or diminished protein expression of intended target. This method additionally alters related gene network targets ultimately resulting in pathway modulation. This approach was used to perturb and identify the most effective upstream regulators and canonical pathways for therapeutic intervention to reverse radiation-induced immunosuppression. The lead Nanoligomer identified in a screen of human donor derived peripheral blood mononuclear cells (PBMCs) upregulated Erythropoietin (EPO) and showed the greatest reversal of radiation induced cytokine changes. It was further tested in vivo in a mouse radiation-model with low-dose (3 mg/kg) intraperitoneal administration and was shown to regulate gene expression of epo in lung tissue as well as counter immune suppression. These results point to the broader applicability of our approach towards drug-discovery, and potential for further investigation of lead molecule as reversible gene therapy to treat adverse health outcomes induced by radiation exposure. | genomics |
Rank concordance of polygenic indices: Implications for personalised intervention and gene-environment interplay Polygenic indices (PGIs) are increasingly used to identify individuals at high risk of developing diseases and disorders and are advocated as a screening tool for personalised intervention in medicine and education. The performance of PGIs is typically assessed in terms of the amount of phenotypic variance they explain in independent prediction samples. However, the correct ranking of individuals in the PGI distribution is a more important performance metric when identifying individuals at high genetic risk. We empirically assess the rank concordance between PGIs that are created with different construction methods and discovery samples, focusing on cardiovascular disease (CVD) and educational attainment (EA). We find that the rank correlations between the constructed PGIs vary strongly (Spearman correlations between 0.17 and 0.94 for CVD, and between 0.40 and 0.85 for EA), indicating highly unstable rankings across different PGIs for the same trait. Simulations show that measurement error in PGIs is responsible for a substantial part of PGI rank discordance. Potential consequences for personalised medicine in CVD and research on gene-environment (GxE) interplay are illustrated using data from the UK Biobank. | genomics |
Genome-wide DNA methylation patterns harbor signatures of hatchling sex and past incubation temperature in a species with environmental sex determination Conservation of thermally sensitive species depends on monitoring organismal and population-level responses to environmental change in real time. Epigenetic processes are increasingly recognized as key integrators of environmental conditions into developmentally plastic responses, and attendant epigenomic datasets hold potential for revealing cryptic phenotypes relevant to conservation efforts. Here, we demonstrate the utility of genome-wide DNA methylation (DNAm) patterns in the face of climate change for a group of especially vulnerable species, those with temperature-dependent sex determination (TSD). Due to their reliance on thermal cues during development to determine sexual fate, contemporary shifts in temperature are predicted to skew offspring sex ratios and ultimately destabilize sensitive populations. Using reduced-representation bisulfite sequencing, we profiled the DNA methylome in blood cells of hatchling American alligator (Alligator mississippiensis), a TSD species lacking reliable markers of sexual dimorphism in early life-stages. We identified 120 sex-associated differentially methylated cytosines (DMCs; FDR < 0.1) in hatchlings incubated under a range of temperatures, as well as 707 unique temperature-associated DMCs. We further developed DNAm-based models capable of predicting hatchling sex with 100% accuracy and past incubation temperature with a mean absolute error of 1.2{degrees}C based on the methylation status of 20 and 24 loci, respectively. Though largely independent of epigenomic patterning occurring in the embryonic gonad during TSD, DNAm patterns in blood cells may serve as non-lethal markers of hatchling sex and past incubation conditions in conservation applications. These findings also raise intriguing questions regarding tissue-specific epigenomic patterning in the context of developmental plasticity. | genomics |
Impact of Pericytes on the Stabilisation of Microvascular Networks in Microfluidic Systems in Response to Nanotoxicity Recapitulating the normal physiology of the microvasculature is pivotal in the development of more complex in vitro models and organ-on-chip design. Pericytes are an important component of the vasculature, promoting vessel stability, inhibiting vascular permeability and maintaining the vascular hierarchical architecture. This report presents a microfluidic model exploring interactions between endothelial cells and pericytes. We identify basal conditions required to form stable and reproducible endothelial networks. We then investigate interactions between endothelial cells and pericytes via direct co-culture. In our system, pericytes inhibited vessel hyperplasia and maintained vessel length in prolonged culture (>10 days). In addition, these vessels displayed barrier function and expression of junction markers associated with vessel maturation, including VE-cadherin, {beta}-catenin and ZO-1. Furthermore, pericytes maintained vessel integrity following stress (nutrient starvation) and inhibited vessel regression, in contrast to the striking dissociation of networks in endothelial monocultures. This response was also observed when endothelial/pericyte co-cultures were exposed to high concentrations of moderately toxic cationic nanoparticles used for gene delivery. This study highlights the importance of pericytes in protecting vascular networks from stress and external agents and their importance to the design of advanced in vitro models, including for the testing of nanotoxicity, to better recapitulate physiological response and avoid false positives. | bioengineering |
Bioprinting microporous functional living materials from protein-based core-shell microgels Living materials have emerged as systems bringing together material science and biology to allow the engineering and augmenting of living systems with novel functionalities. Bioprinting promises accurate control over the formation of such complex materials through programmable deposition of cells in soft materials, but current approaches had limited success on fine-tunning cell microenvironments while generating robust macroscopic morphologies. Here, we address this challenge through the use of microgel ink to bioprint functional living materials. Jammed core-shell microgels are microfluidically functionalized with cells in the aqueous cores which can promote the growth of both microbial communities and mammalian cellular spheroids, followed by an interparticle annealing to give covalently stabilized functional scaffolds with controlled microporosity that enhances the mass transfer of nutrients and metabolites. Different microbial consortia are immobilized in scaffolds towards versatile applications; more importantly, by compartmentalizing microbial consortia at microscale, the collective bioactivities of both consortia are significantly enhanced, shedding light on strategies to augment living materials with bioprocessing capabilities. | bioengineering |
Privacy-Aware Kinship Inference in Admixed Populations using Projection on Reference Panels Estimation of genetic relatedness, or kinship, is used occasionally for recreational purposes and in forensic applications. While numerous methods were developed to estimate kinship, they suffer from high computational requirements and often make an untenable assumption of homogeneous population ancestry of the samples. Moreover, genetic privacy is generally overlooked in the usage of kinship estimation methods. There can be ethical concerns about finding unknown familial relationships in 3rd party databases. Similar ethical concerns may arise while estimating and reporting sensitive population-level statistics such as inbreeding coefficients for the concerns around marginalization and stigmatization. Here, we make use of existing reference panels with a projection-based approach that simplifies kinship estimation in the admixed populations. We use simulated and real datasets to demonstrate the accuracy and efficiency of kinship estimation. We present a secure federated kinship estimation framework and implement a secure kinship estimator using homomorphic encryption-based primitives for computing relatedness between samples in 2 different sites while genotype data is kept confidential. | bioinformatics |
Clair3-Trio: high-performance Nanopore long-read variant calling in family trios with Trio-to-Trio deep neural networks Accurate identification of genetic variants from family child-mother-father trio sequencing data is important in genomics. However, state-of-the-art approaches treat variant calling from trios as three independent tasks, which limits their calling accuracy for Nanopore long-read sequencing data. For better trio variant calling, we introduce Clair3-Trio, the first variant caller tailored for family trio data from Nanopore long-reads. Clair3-Trio employs a Trio-to-Trio deep neural network model, which allows it to input the trio sequencing information and output all of the trios predicted variants within a single model to improve variant calling. We also present MCVLoss, a novel loss function tailor-made for variant calling in trios, leveraging the explicit encoding of the Mendelian inheritance. Clair3-Trio showed comprehensive improvement in experiments. It predicted far fewer Mendelian inheritance violation variations than current state-of-the-art methods. We also demonstrated that our Trio-to-Trio model is more accurate than competing architectures. Clair3-Trio is accessible as a free, open-source project at https://github.com/HKU-BAL/Clair3-Trio. | bioinformatics |
Mass photometric detection and quantification of nanoscale α-synuclein phase separation -Synuclein (-Syn) liquid-liquid phase separation (LLPS) leads to irreversible amyloid fibril formation associated with Parkinsons disease pathogenesis. Critical concentrations of -Syn LLPS are relatively high under physiological solution conditions. Moreover, -Syn exhibits delayed LLPS kinetics under certain conditions which deviates from the behaviour predicted by classical homogeneous nucleation theory. In the current body of work, using interferometric light scattering (iSCAT), also known as mass photometry, we experimentally probe that -Syn can form nanoscale phase separated assemblies/clusters, containing tens to hundreds of molecules-- both above and below the critical LLPS concentration down to physiologically relevant scales. The formation of these clusters is instantaneous, even under conditions where the formation of microscopically visible droplets takes several days. However, they account for a very small volume fraction below saturation concentration. The slow growth of the nanoclusters can be attributed to a kinetic barrier which can be overcome by increasing the solution temperature to just below the droplet melting point. We provide reasons for caution in quantifying dilute phase concentrations for -Syn LLPS samples containing nanoscale droplets--which can only be separated using ultracentrifugation. In addition, we also delineate that the presence of certain surfaces facilitates -Syn droplet nucleation under conditions of delayed kinetics but is not a mandatory prerequisite for nanocluster formation. Taken together, our findings reveal that phase separation of -Syn occurs at a wider range of solution conditions than predicted so far and provides an important step towards understanding -Syn LLPS within physiological scales.
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[email protected]@1fdc4bdorg.highwire.dtl.DTLVardef@17f8aa8org.highwire.dtl.DTLVardef@682598_HPS_FORMAT_FIGEXP M_FIG C_FIG | biophysics |
Aminomethanesulfonic acid illuminates the boundary between full and partial agonists of the pentameric glycine receptor To clarify the determinants of agonist efficacy in pentameric ligand-gated ion channels we examined a new compound, aminomethanesulfonic acid (AMS), a molecule intermediate in structure between glycine and taurine. Despite wide availability, to date there are no reports of AMS action on glycine receptors, perhaps because AMS is unstable at physiological pH. Here we show that at pH 5, AMS is an efficacious agonist, eliciting in zebrafish 1 glycine receptors a maximum single channel open probability of 0.85, much greater than that of {beta}-alanine (0.54) or taurine (0.12), and second only to that of glycine itself (0.96). Thermodynamic cycle analysis of the efficacy of these closely related agonists shows supra-additive interaction between changes in the length of the agonist molecule and the size of the anionic moiety. Single particle cryo-EM structures of AMS-bound glycine receptors show that the AMS-bound agonist pocket is as compact as with glycine, and three-dimensional classification demonstrates that the channel populates the open and the desensitized states, like glycine, but not the closed intermediate state associated with the weaker partial agonists, {beta}-alanine and taurine. Because AMS is on the cusp between full and partial agonists, it provides a new tool to help us understand agonist action in the pentameric superfamily of ligand-gated ion channels. | biophysics |
Manufacturing highly potent CD20/CD19-targeted iCasp9 regulatable CAR-T cells using the Quantum pBac-based CAR-T (qCART) system for clinical application CD19-targeted chimeric antigen receptor therapies (CAR19) have driven a paradigm shift in the treatment of relapsed/refractory B-cell malignancies. However, >50% of CAR19-treated patients experienced progressive disease mainly due to antigen escape and low persistence. Clinical prognosis is heavily influenced by CAR-T cell function and systemic cytokine toxicities. Furthermore, it remains a challenge to efficiently, cost-effectively, and consistently manufacture clinically relevant number of virally engineered CAR-T cells. Using a highly efficient piggyBac transposon-based vector, Quantum pBac, we developed a virus-free cell engineering system, Quantum CAR-T (qCART), for development and production of multiplex CAR-T therapies. Here, we demonstrated in vitro and in vivo that consistent, robust, and functional CD20/CD19 dual-targeted CAR-T stem cell memory (TSCM) cells can be efficiently manufactured using the qCART system for clinical application. qCART-manufactured CAR-T cells from cancer patients expanded efficiently, rapidly eradicated tumors, and can be safely controlled via an iCasp9 suicide gene-inducing drug. | cancer biology |
Quantum CART (qCART), a piggyBac-based system for development and production of virus-free multiplex CAR-T cell therapy Chimeric antigen receptor T (CAR-T) cell therapy has the potential to transform cancer treatment. However, CAR-T therapy application is currently limited to certain types of relapse and refractory liquid tumors. To unlock the full potential of CAR-T therapy, technologic breakthroughs will be needed in multiple areas, including optimization of autologous CAR-T development, shortening the innovation cycle, and further manufacturing advancement of next-generation CAR-T therapies. Here, we established a simple and robust virus-free multiplex Quantum CART (qCART) system that seamlessly and synergistically integrates four platforms: 1. GTailor for rapid identification of lead CAR construct design, 2. Quantum Nufect for effective but gentle electroporation-based gene delivery, 3. Quantum pBac, featuring a virus-free transposon-based vector with large payload capacity and potentially safe integration profile, and 4. iCellar for robust and high-quality CAR+ T memory stem cell (TSCM) expansion. This robust, virus-free multiplex qCART system is expected to unleash the full potential of CAR-T therapy for treating diseases.
Significance StatementChimeric antigen receptor T (CAR-T) cell therapy is currently ineffective against solid tumors. Here, we showcase Quantum CART (qCART), a simple and robust system that seamlessly and synergistically integrates four platforms for optimal production of multiplex virus-free CAR-T cells: GTailor for rapid identification of lead CAR candidates; Quantum Nufect for effective but gentle electroporation-based gene delivery; Quantum pBac, featuring a highly efficient, high payload capacity virus-free gene therapy vector and potentially safe integration profile; and iCellar for robust and high quality CAR-T cell expansion. We demonstrate that qCART is a simple and robust system for cost-effective and time-efficient manufacturing of T memory stem cell (TSCM) multiplex CAR-T cells. | cancer biology |
AI inspired discovery of new biomarkers for clinical prognosis of liver cancer Tissue biomarkers are crucial for cancer diagnosis, prognosis assessment, and treatment planning. However, few of current biomarkers used in clinics are robust enough to show a true analytical and clinical value. Thus the search for additional tissue biomarkers, including the strategies to identify them, is imperative. Recently, the capabilities of deep learning (DL)-based computational pathology in cancer diagnosis and prognosis have been explored, but the limited interpretability and generalizability make the results difficult to be accepted in clinical practice. Here we present an interpretable human-centric DL-guided framework--PathFinder (Pathological-biomarker-finder)-- that can inspire pathologists to discover new tissue biomarkers from well-performing DL models, which bridges the gap between DL and clinical prognosis. By combining sparse multi-class tissue spatial distribution information of whole slide images (WSIs) with attribution methods, PathFinder can achieve localization, characterization, and verification of potential biomarkers, while guaranteeing state-of-the-art prognostic performance. With the inspiration of PathFinder, we discovered that tumor necrosis in liver cancer, a long-neglected factor, has a strong relationship with patient prognosis. Thus we proposed two clinically independent indicators, including necrosis area fraction and tumor necrosis distribution, for practical prognosis, and verified their potentials in clinical prognosis according to Reporting Recommendations for Tumor Marker Prognostic Studies (REMARK)-derived criteria. Our work demonstrates a successful example of introducing artificial intelligence (AI) into clinical practice in a knowledge discovery way, which can be adopted in identifying biomarkers in various cancer types and modalities. | cancer biology |
Structural snapshots of nitrosoglutathione binding and reactivity underlying S-nitrosylation of photosynthetic GAPDH S-nitrosylation is a redox post-translational modification widely recognized to play an important role in cellular signaling as it can modulate protein function and conformation. At the physiological level, nitrosoglutathione (GSNO) is considered the major physiological NO-releasing compound due to its ability to transfer the NO moiety to protein thiols. GSNO can also induce protein S-glutathionylation but the structural determinants regulating its redox specificity are not fully elucidated. In this study, we employed photosynthetic glyceraldehyde-3-phosphate dehydrogenase from Chlamydomonas reinhardtii (CrGAPA) to investigate the molecular mechanisms underlying GSNO-dependent thiol oxidation. We first observed that GSNO causes enzyme inhibition by specifically inducing S-nitrosylation. Treatment with reducing agents restores CrGAPA activity completely. While the cofactor NADP+ only partially protects from GSNO-mediated S-nitrosylation, the resultant inactivation is completely blocked by the presence of the substrate 1,3-bisphosphoglycerate, indicating that the S-nitrosylation of the catalytic Cys149 is responsible of CrGAPA inactivation. The crystal structures of CrGAPA in complex with NADP+ and NAD+ reveal a general structural similarity with other photosynthetic GAPDH. Starting from the 3D structure, we carried out molecular dynamics simulations to identify the protein residues involved in GSNO binding. Quantum mechanical/molecular mechanical calculations were performed to investigate the reaction mechanism of GSNO with CrGAPA Cys149 and to disclose the relative contribution of protein residues in modulating the activation barrier of the trans-nitrosylation reaction. Based on our findings, we provide functional and structural insights into the response of CrGAPA to GSNO-dependent regulation, possibly expanding the mechanistic features to other protein cysteines susceptible to be oxidatively modified by GSNO. | plant biology |
Neurotransmitter content heterogeneity within an interneuron class shapes inhibitory transmission at a central synapse Neurotransmitter content is deemed the most basic defining criterion for neuronal classes, contrasting with the intercellular heterogeneity of many other molecular and functional features. Here we show, in the adult mouse brain, that neurotransmitter content variegation within a neuronal class is a component of its functional heterogeneity. Most Golgi cells (GoCs), the well-defined class of cerebellar interneurons inhibiting granule cells (GrCs), contain cytosolic glycine, accumulated by the neuronal transporter GlyT2, and GABA in various proportions. To assess the functional consequence of this neurotransmitter variation, we paired GrCs recordings with optogenetic stimulations of single GoCs, which preserve the intracellular transmitter mixture. We show that the strength and decay kinetics of GrCs IPSCs, which are entirely mediated by GABAA receptors are negatively correlated to the presynaptic expression of GlyT2 by GoCs. We isolate a slow spillover component of GrCs inhibition that is also affected by the expression of GlyT2, leading to a 56 % decrease in relative charge. Acute manipulations of cytosolic GABA and glycine supply recapitulate the modulation of IPSC charge, supporting the hypothesis that presynaptic loading of glycine negatively impact the GABAergic transmission in mixed interneurons through a competition for vesicular filling. Our results suggest that heterogeneity of neurotransmitter supply within the GoC class may provide a presynaptic mechanism to tune the gain of the stereotypic granular layer microcircuit, thereby expanding the realm of possible dynamic behavior. | neuroscience |
Right inferior frontal cortex damage impairs the initiation of inhibitory control, but not its implementation Inhibitory control is one of the most important control functions in the human brain. Much of our understanding of its neural basis comes from seminal work showing that lesions to the right inferior frontal cortex (rIFC) increase stop-signal reaction time (SSRT), a latent variable that expresses the speed of inhibitory control. However, recent work has identified substantial limitations of the SSRT method. Notably, SSRT is confounded by trigger failures: stop-signal trials in which inhibitory control was never initiated. Such trials inflate SSRT, but are typically indicative of attentional, rather than inhibitory deficits. Here, we used hierarchical Bayesian modeling to identify stop-signal trigger failures in human rIFC lesion patients, non-rIFC lesion patients, and healthy comparisons. Furthermore, we measured scalp-EEG to detect {beta}-bursts, a neurophysiological index of inhibitory control. rIFC lesion patients showed a more than five-fold increase in trigger failure trials and did not exhibit the typical increase of stop-related frontal {beta}- bursts. However, on trials in which such {beta}-bursts did occur, rIFC patients showed the typical subsequent upregulation of {beta} over sensorimotor areas, indicating that their ability to implement inhibitory control, once triggered, is intact. These findings suggest that the role of rIFC in inhibitory control has to be fundamentally reinterpreted. | neuroscience |
Fewer but higher quality of pollinator visits determines plant invasion success in simulated plant-pollinator networks O_LIInvasive plants often use mutualisms to establish and spread in their new habitats. These plants tend to be well-integrated into plant-pollinator networks in terms of being visited by resident pollinators similarly or more frequently than the native plants.
C_LIO_LIThe long-term persistence of non-native plants, however, not only depends on the quantity of visits they receive but also on the visit quality and the resulting reproductive success, which have been rarely studied in a network context.
C_LIO_LIWe evaluated the potential of non-native plants to invade and impact plant-pollinator networks based on their ability to attract pollinators via production of floral rewards, to produce and attach pollen on pollinators, and the consequent seed production and population growth.
C_LIO_LIWe simulated the introduction of different types of non-native plants into thousands of different networks using a model that includes population dynamics of plants and pollinators, quantity and quality of pollinator visits, the dynamics of floral rewards, and pollinators adaptive foraging.
C_LIO_LIWe found the counterintuitive result that introduced plants visited by fewer pollinators were more successful at securing the high-quality visits necessary to invade. These plants did not experience the depletion of floral rewards that plants visited by too many pollinators experienced, which caused pollinators to reassign their visits to other plants and, therefore, dilute the conspecific pollen they carried.
C_LIO_LINative pollinators increased their abundance with the plant invasions, but the reallocated foraging effort concentrated on invaders reduced the quantity and quality of visits to native plants and made the networks visitation structure more modular and nested. These effects were buffered by plant richness.
C_LIO_LIInterestingly, the significant changes in visitation structure only caused a minimal decline in native plant abundance and no extinctions.
C_LIO_LIOur results call for evaluating the impact of invasive plants not only on visitation rates and network structure, but also on the demographics of native plants, which depend on other processes beyond pollination including seed production and recruitment.
C_LI | ecology |
Regional context for balancing sagebrush- and woodland-dependent songbird needs with targeted pinyon-juniper management in the sagebrush biome Tree expansion among historic grassland and shrubland systems is a global phenomenon, which results in dramatic influences on ecosystem processes and wildlife populations. In the western US, pinyon-juniper woodlands have expanded by as much as six-fold among sagebrush steppe landscapes since the late nineteenth century, with demonstrated negative impacts to the behavior, demography, and population dynamics of species that rely on intact sagebrush rangelands. Notably, greater sage-grouse (Centrocercus urophasianus) are unable to tolerate even low conifer cover, which can result in population declines and local extirpation. Removing expanding conifer cover has been demonstrated to increase sage grouse population growth rates and sagebrush-obligate songbird abundance. However, advances in restoring sagebrush habitats have been met with concern about unintended impacts to species that rely on conifer woodlands, notably the pinyon jay (Gymnorhinus cyanocephalus) whose population declines are distinctive among birds breeding in pinyon-juniper woodlands. We modeled indices to abundance in relation to multi-scale habitat features for nine songbirds reliant on both sagebrush and pinyon-juniper woodlands for breeding. Findings demonstrate that targeted sage grouse habitat restoration under the Sage Grouse Initiative is not at odds with protection of pinyon jay populations. Rather, conifer management has largely occurred in the northern sagebrush ecosystem where models suggest that past cuts likely benefit Brewers sparrow and sage thrasher while avoiding pinyon jay habitat. Extending our spatial modeling further south beyond the sagebrush biome could better equip conservationists with more comprehensive decision-support, particularly where pinyon jays face additional pressures of drought-induced tree mortality. | ecology |
Beyond Pairwise Interactions: Higher-Order Dynamics in Protein Interaction Networks Protein interactions form a complex dynamic system that shapes cell phenotype and function; in this regard, network analysis is a powerful tool for studying the dynamics of cellular processes. Graph-based models are limited, however, in that these models consider only pairwise relationships. Higher-order interactions are well-characterized in biology, including protein complex formation and feedback or feedforward loops. These higher-order relationships are better represented by a hypergraph as a generalized network model. Here, we present an approach to analyzing dynamic gene expression data using a hypergraph model and quantify network heterogeneity via Forman-Ricci curvature. We observe, on a global level, increased network curvature in pluripotent stem cells and cancer cells. Further, we use local curvature to conduct pathway analysis in a melanoma dataset, finding increased curvature in several oncogenic pathways and decreased curvature in tumor suppressor pathways. We compare this approach to a graph-based model and a differential gene expression approach. | systems biology |
Single cell transcriptomic profiling of tauopathy in a novel 3D neuron-astrocyte coculture model The use of iPSC derived brain organoid models to study neurodegenerative disease has been hampered by a lack of systems that accurately and expeditiously recapitulate pathogenesis in the context of neuron-glial interactions. Here we report development of a system, termed AstTau, which propagates toxic human tau oligomers in iPSC derived neuron-astrocyte spheroids. The AstTau system develops much of the neuronal and astrocytic pathology observed in tauopathies including misfolded, phosphorylated, oligomeric, and fibrillar tau, strong neurodegeneration, and reactive astrogliosis. Single cell transcriptomic profiling combined with immunochemistry characterizes a model system that can more closely recapitulate late-stage changes in adult neurodegeneration. The transcriptomic studies demonstrate striking changes in neuroinflammatory and heat shock protein (HSP) chaperone systems in the disease process. Treatment with the HSP90 inhibitor PU-H71 was used to address the putative dysfunctional HSP epichaperome and produced a strong reduction of pathology and neurodegeneration, highlighting the potential of AstTau as a rapid and reproducible tool for drug discovery. | neuroscience |
Clemastine fumarate enhances myelination and promotes functional recovery in a syndromic ASD mouse model of Pitt-Hopkins Syndrome Pitt-Hopkins syndrome (PTHS) is an autism spectrum disorder (ASD) caused by autosomal dominant mutations in the Transcription Factor 4 gene (TCF4). One pathobiological process caused by Tcf4 mutation is a cell autonomous reduction in oligodendrocytes (OLs) and myelination. In this study, we show that clemastine is effective at restoring myelination defects in a PTHS mouse model. In vitro, clemastine treatment reduced excess oligodendrocyte precursor cells (OPCs) and normalized OL density. In vivo, two-week intraperitoneal administration of clemastine also normalized OPC and OL density in the cortex of Tcf4 mutant mice and appeared to increase the number of axons undergoing myelination, as EM imaging of the corpus callosum showed a significant increase in uncompacted myelin. Importantly, this treatment paradigm resulted in functional rescue by improving electrophysiology and behavior. Together, these results provide preclinical evidence that remyelination therapies may be beneficial in PTHS and potentially other neurodevelopmental disorders characterized by demyelination. | neuroscience |
The Colon Mucosal Sialylglycome Is Redox-Regulated by the Golgi Enzyme QSOX1 Mucus shields the intestinal epithelium from pathogens and provides a supportive environment for commensal bacteria. Mucus is composed of enormous, heavily glycosylated proteins called mucins, which become disulfide crosslinked in a multi-step biosynthetic pathway culminating in the Golgi apparatus and secretory granules of goblet cells. We observed that knockout mice lacking the Golgi-localized disulfide catalyst QSOX1 produced poorly protective colon mucus, were hypersensitive to induced colitis, and had an altered microbiome. The initial hypothesis arising from these observations was that QSOX1 catalyzes disulfide crosslinking of mucins. Contrary to this hypothesis, the disulfide-mediated polymerization of mucins and related glycoproteins proceeded normally without QSOX1. Instead, we found that QSOX1 forms regulatory disulfides in Golgi glycosyltransferases and thereby promotes effective sialylation of the colon glycome. Our findings reveal that enzymatic control of Golgi redox state impacts glycan elaboration in goblet cells, and that this pathway is crucial for maintaining mucosal function. | cell biology |
Regulation of astrocyte lipid metabolism and ApoE secretion by the microglial oxysterol, 25-hydroxycholesterol Neuroinflammation is a major hallmark of Alzheimers disease and several other neurological and psychiatric disorders and is often associated with dysregulated cholesterol metabolism. Relative to homeostatic microglia, activated microglia express higher levels of Ch25h, an enzyme that hydroxylates cholesterol to produce 25-hydroxycholesterol (25HC). 25HC is an oxysterol with interesting immune roles stemming from its ability to regulate cholesterol biosynthesis. Since astrocytes synthesize cholesterol in the brain and transport it to other cells via apolipoprotein E (ApoE)-containing lipoproteins, we hypothesized that secreted 25HC from microglia may influence lipid metabolism as well as extracellular ApoE derived from astrocytes. Here we show that astrocytes take up externally added 25HC and respond with altered lipid metabolism. 25HC increased extracellular levels of ApoE lipoprotein particles without altering Apoe mRNA expression, due to elevated Abca1 expression via activation of LXRs and decreased ApoE reuptake due to suppressed Ldlr expression via inhibition of SREBP. Astrocytes metabolized 25HC to limit its effects on lipid metabolism via Cyp7b1, an enzyme responsible for 7-hydroxylation of 25HC. Knockdown of Cyp7b1 expression with siRNA prolonged the effects of 25HC on astrocyte lipid metabolism. 25HC also suppressed Srebf2 expression to reduce cholesterol synthesis in astrocytes but did not affect fatty acid levels or the genes required for fatty acid synthesis. We further show that 25HC led to a doubling of the amount of cholesterol esters and their concomitant storage in lipid droplets. Our results suggest an important role for 25HC in regulating astrocyte lipid metabolism. | cell biology |
Patterning of the female reproductive tract along antero-posterior and dorso-ventral axes is dependent on Amhr2+ mesenchyme in mice Morphogenesis of the female reproductive tract is regulated by the mesenchyme. However, the identity of the mesenchymal lineage that directs the patterning of the female reproductive tract has not been determined. Using in vivo genetic cell ablation, we identified Amhr2+ mesenchyme as an essential mesenchymal population in patterning the female reproductive tract. After partial ablation of Amhr2+ mesenchymal cells, the oviduct failed to develop its characteristic coiling due to decreased epithelial proliferation and tubule elongation during development. The uterus displayed a reduction in size and showed decreased cellular proliferation in both epithelial and mesenchymal compartments. More importantly, in the uterus, partial ablation of Amhr2+ mesenchyme caused abnormal lumen shape and altered the direction of its long axis from the dorsal-ventral axis to the left-right axis (i.e. perpendicular to the dorsal-ventral axis). Despite these morphological defects, epithelia underwent normal differentiation into secretory and ciliated cells in the oviduct and glandular epithelial cells in the uterus. These results demonstrated that Amhr2+ mesenchyme can direct female reproductive tract morphogenesis by regulating epithelial proliferation and lumen shape without affecting the differentiation of epithelial cell types. | developmental biology |
Modeling fragment counts improves single-cell ATAC-seq analysis Single-cell ATAC-sequencing (scATAC-seq) coverage in regulatory regions is typically binarized as an indicator of open chromatin. However, the implications of scATAC-seq data binarization have never been assessed. Here, we show that the goodness-of-fit of existing models and their applications including clustering, cell type identification, and batch integration, are improved by a quantitative treatment of the fragment counts. These results have immediate implications for scATAC-seq analysis. | bioinformatics |
Membrane curvature sensing and stabilization by the autophagic LC3 lipidation machinery How the highly curved phagophore membrane is stabilized during autophagy initiation is a major open question in autophagosome biogenesis. Here, we use in vitro reconstitution on membrane nanotubes and molecular dynamics simulations to investigate how core autophagy proteins in the LC3 lipidation cascade interact with curved membranes, providing insight into possible roles in regulating membrane shape during autophagosome biogenesis. ATG12-5-16L1 was up to 100-fold enriched on highly curved nanotubes relative to flat membranes. At high surface density, ATG12-5-16L1 binding increased the curvature of the nanotubes. While WIPI2 binding directs membrane recruitment, the amphipathic helix 2 of ATG16L1 is responsible for curvature sensitivity. Molecular dynamics simulations revealed that helix 2 of ATG16L1 inserts shallowly into the membrane, explaining its curvature-sensitive binding to the membrane. These observations show how the binding of the ATG12-5-16L1 complex to the early phagophore rim could stabilize membrane curvature and facilitate autophagosome growth. | biophysics |
Quantification of cell penetrating peptide mediated delivery of proteins in plant leaves Protein delivery to plants offers many opportunities for plant bioengineering via gene editing and through direction of protein-protein interactions. However, the delivery of proteins to plants presents both practical and analytical challenges. We present a GFP bimolecular fluorescence complementation-based tool, delivered complementation in planta (DCIP), which allows for unambiguous and quantitative measurement of protein delivery in leaves. Using DCIP, we demonstrate cell-penetrating peptide mediated cytosolic delivery of peptides and recombinant proteins in Nicotiana benthamiana. We show that DCIP enables quantitative measurement of delivery efficiency and enables functional screening of cell penetrating peptide sequences. We also use DCIP to evidence an endocytosis independent mechanism of nona-arginine cell penetrating peptide delivery. In addition to the importance cell penetrating peptide sequence, we show that cargo stability may play an important role in delivery effectiveness. Finally, we demonstrate that DCIP detects cell penetrating peptide mediated delivery of recombinantly expressed proteins into intact leaves. As a proof of concept, we also show that ectopic protein-protein interactions can be formed using delivered recombinant proteins. By using a cell penetrating peptide to deliver the actin binding peptide, Lifeact, fused to GFP11, we enable fluorescence complementation-based scaffolding of a GFP1-10 fusion protein to endogenous f-actin in plant leaves. DCIP offers a new and powerful tool for interrogating cytosolic delivery of proteins in plants and outlines new techniques for engineering plant biology. | plant biology |
IPT9, a cis-zeatin cytokinin biosynthesis gene, promotes root growth Cytokinin and auxin are plant hormones that coordinate many aspects of plant development. Their interactions in plant underground growth are well established, occurring at the levels of metabolism, signaling, and transport. Unlike many plant hormone classes, cytokinins are represented by more than one active molecule. Multiple mutant lines, blocking specific parts of cytokinin biosynthetic pathways, have enabled research in plants with deficiencies in specific cytokinin-types. While most of these mutants have confirmed the impeding effect of cytokinin on root growth, the ipt29 double mutant instead surprisingly exhibits reduced primary root length compared to wild type. This mutant is impaired in cis-zeatin (cZ) production, a cytokinin-type that had been considered inactive in the past. Here we have further investigated the intriguing ipt29 root phenotype, opposite to known cytokinin functions, and the (bio)activity of cZ. Our data suggest that despite the ipt29 short-root phenotype, cZ application has a negative impact on primary root growth and can activate a cytokinin response in the stele. Grafting experiments revealed that the root phenotype of ipt29 depends on local signaling which does not relate to directly to cytokinin levels. Notably, ipt29 displayed increased auxin levels in the root tissue. Moreover, analyses of the differential contributions of ipt2 and ipt9 to the ipt29 short-root phenotype demonstrated that, despite its deficiency on cZ levels, ipt2 does not show any root phenotype or auxin homeostasis variation while ipt9 mutants were indistinguishable from ipt29. We conclude that IPT9 functions may go beyond cZ biosynthesis, directly or indirectly, implicating effects on auxin homeostasis and therefore influencing plant growth. | plant biology |
A model of decentralized vision in the sea urchin Diadema africanum Sea urchins can detect light and move in relation to luminous stimuli despite lacking eyes. They presumably detect light through photoreceptor cells distributed on their body surface. However, there is currently no mechanistic explanation of how these animals can process light to detect visual stimuli and produce oriented movement. Here, we present a model of decentralized vision in echinoderms that includes all known processing stages, from photoreceptor cells to radial nerve neurons to neurons contained in the oral nerve ring encircling the mouth of the animals. In the model, light stimuli captured by photoreceptor cells produce neural activity in the radial nerve neurons. In turn, neural activity in the radial nerves is integrated in the oral nerve ring to produce a profile of neural activity reaching spatially across several ambulacra. This neural activity is read out to produce a model of movement. The model captures the pattern of behavior observed in sea urchin Diadema africanum probed with a variety of physical stimuli. The specific pattern of neural connections used in the model makes testable predictions on the properties of single neurons and aggregate neural behavior in Diadema africanum and other echinoderms, offering a potential understanding of the mechanism of visual orientation in these animals. | systems biology |
The Systematic Optimization of Square Wave Electroporation for Six Commonly Used Human Cell Lines During cellular electroporation, the formation of transient pores allow for the diffusion of innately impermeable molecules. The diversity of cell and membrane structure results in unique properties with respect to sensitivity to electric fields. The growing use of human cell lines in biomedical research and technology has led to a demand for protocols that can effectively and economically perform electroporation. We electroporated six human cell lines using a fluorescent reporter to investigate the effects of pulse electric field strength, pulse duration, and DNA concentration during electroporation. It was found that the cell lines all responded to electric field strengths within 400-950V/cm with viability decreasing with increasing voltage. It was also observed that the concentration of DNA used directly impacts transfection efficiency and cell viability as well. To better characterize square wave electroporation, we adopted a model where the pulse is described by its energy density (J/L) with respect to the sample buffer volume. It was determined that the key electrical characteristics of electroporation can be generalized with this value to provide a simplified measure of pulse intensity. The resulting analysis was consistent with other models, indicating cell type specific optimal electrical and DNA concentrations. | cell biology |
Identification of sex-determining loci in hybridizing Catostomus fish species 1Despite the near-universality of gonochorism (separate sexes) in eukaryotic organisms, the underlying mechanisms of sex determination are poorly understood and highly variable in some taxa. In hybridizing species, sex determination mechanisms may promote or impede reproductive isolation depending on whether mechanisms are similar between species. In Catostomus fishes, contemporary hybridization is variable and extensive. In the present study, we aim to describe the genetic basis of sex determination in bluehead (Catostomus discobolus) and white suckers (Catostomus commersonii) to understand the impact of sex determination on reproductive isolation. We used genotyping-by-sequencing genomic data from Catostomus species and their hybrids to identify regions of the genome associated with sex using a genome-wide association study and the identification of sex-specific loci. We found a genetic basis of sex determination in Catostomus fishes, with a region of the genome significantly associating with sex in bluehead suckers. This region is suggestive of a master sex-determining region in bluehead suckers but is not significant in white suckers, implying that either the sex-determining region of the genome differs in these two species that hybridize, or that sample size was insufficient to identify this genomic region in white suckers. By describing and comparing sex-determination systems across Catostomus fish species, we highlight the relationship between sex determining systems and hybridization in closely related fish species. | evolutionary biology |
Principled Feature Attribution for Unsupervised Gene Expression Analysis As interest in unsupervised deep learning models for the analysis of gene expression data has grown, an increasing number of methods have been developed to make these deep learning models more interpretable. These methods can be separated into two groups: (1) post hoc analyses of black box models through feature attribution methods and (2) approaches to build inherently interpretable models through biologically-constrained architectures. In this work, we argue that these approaches are not mutually exclusive, but can in fact be usefully combined. We propose a novel unsupervised pathway attribution method, which better identifies major sources of transcriptomic variation than prior methods when combined with biologically-constrained neural network models. We demonstrate how principled feature attributions aid in the analysis of a variety of single cell datasets. Finally, we apply our approach to a large dataset of post-mortem brain samples from patients with Alzheimers disease, and show that it identifies Mitochondrial Respiratory Complex I as an important factor in this disease. | bioinformatics |
SARS-CoV-2 variants do not evolve to promote further escape from MHC-I recognition SARS-CoV-2 variants of concern (VOCs) possess mutations that confer resistance to neutralizing antibodies within the Spike protein and are associated with breakthrough infection and reinfection. By contrast, less is known about the escape from CD8+ T cell-mediated immunity by VOC. Here, we demonstrated that VOCs retain similar MHC-I downregulation capacity compared to the ancestral virus. However, VOCs exhibit a greater ability to suppress type I IFN than the ancestral virus. Although VOCs possess unique mutations within the ORF8 gene, which suppresses MHC-I expression, none of these mutations enhanced the ability of ORF8 to suppress MHC-I expression. Notably, MHC-I upregulation was strongly inhibited after the ancestral SARS-CoV-2 infection in vivo. Collectively, our data suggest that the ancestral SARS-CoV-2 already possesses an intrinsically potent MHC-I evasion capacity, and that further adaptation by the variants was not observed. | microbiology |
Development of Molecular Inversion Probes for Soybean Progeny Genomic Selection Genotyping Increasing rate of genetic gain for key agronomic traits through genomic selection requires the development of new molecular methods to run genome-wide single nucleotide polymorphisms (SNPs). The main limitation of current methods is the cost is too high to screen breeding populations. Molecular inversion probes (MIPs) is a targeted genotyping-by-sequencing method that could be used for soybeans that is both cost effective, high-throughput, and provides high data quality to screen breeders germplasm for genomic selection. A 1K MIP SNP set was developed for soybean with uniformly distributed markers across the genome. The SNPs were selected to maximize the number of informative markers in germplasm being tested in soybean breeding programs located in the North Central and Mid-South regions of the United States. The 1K SNP MIP set was tested on diverse germplasm and a recombinant inbred line population. Targeted sequencing with MIPs obtained an 85% enrichment for the targeted SNPs. MIPs genotyping accuracy was 93% overall while homozoygous call accuracy was 98% with less than 10% missing data. The accuracy of MIPs combined with its low per sample cost makes it a powerful tool to enable genomic selection within soybean breeding programs. | genomics |
Adsorption of Pulmonary and Exogeneous Surfactants on SARS-CoV-2 Spike Protein COVID-19 is transmitted by inhaling SARS-CoV-2 virions, which are enveloped by a lipid bilayer decorated by a "crown" of Spike protein protrusions. In the respiratory tract, virions interact with surfactant films composed of phospholipids and cholesterol that coat lung airways. Here, we explore by using coarse-grained molecular dynamics simulations the physico-chemical mechanisms of surfactant adsorption on Spike proteins. With examples of zwitterionic dipalmitoyl phosphatidyl choline, cholesterol, and anionic sodium dodecyl sulphate, we show that surfactants form micellar aggregates that selectively adhere to the specific regions of S1 domain of the Spike protein that are responsible for binding with ACE2 receptors and virus transmission into the cells. We find high cholesterol adsorption and preferential affinity of anionic surfactants to Arginine and Lysine residues within S1 receptor binding motif. These findings have important implications for informing the search for extraneous therapeutic surfactants for curing and preventing COVID-19 by SARS-CoV-2 and its variants. | biophysics |
Iron homeostasis governs erythroid phenotype in Polycythemia Vera Polycythemia Vera (PV) is a myeloproliferative neoplasm driven by activating mutations in JAK2 that result in unrestrained erythrocyte production, increasing patients hematocrit and hemoglobin concentration, placing them at risk of life-threatening thrombotic events. Our GWAS of 440 PV cases and 403,351 controls utilising UK Biobank data found that SNPs in HFE known to cause hemochromatosis are highly associated with PV diagnosis, linking iron regulation to PV. Analysis of the FinnGen dataset independently confirmed over-representation of homozygous HFE mutations in PV patients. HFE influences expression of hepcidin, the master regulator of systemic iron homeostasis. Through genetic dissection of PV mouse models, we show that the PV erythroid phenotype is directly linked to hepcidin expression: endogenous hepcidin upregulation alleviates erythroid disease whereas hepcidin ablation worsens it. Further, we demonstrate that in PV, hepcidin is not regulated by expanded erythropoiesis but is likely governed by inflammatory cytokines signalling via GP130 coupled receptors. These findings have important implications for understanding the pathophysiology of PV and offer new therapeutic strategies for this disease. | cancer biology |
Dog Size and Patterns of Disease History Across the Canine Age Spectrum: Results from the Dog Aging Project Age in dogs is associated with the risk of many diseases, and canine size is a major factor in that risk. However, the size effect is not as simple as the age effect. While small size dogs tend to live longer, some diseases are more prevalent among small dogs. Utilizing owner-reported data on disease history from a substantial number of companion dogs, we investigate how body size, as measured by weight, associates with the prevalence of a reported condition and its pattern across age for various disease categories. We found significant positive associations between weight and prevalence of skin, bone/orthopedic, gastrointestinal, ear/nose/throat, cancer/tumor, brain/neurologic, endocrine, and infectious diseases. Similarly, weight was negatively associated with the prevalence of eye, cardiac, liver/pancreas, and respiratory disease categories. Kidney/urinary disease prevalence did not vary by weight. We also found that the association between age and disease prevalence varied by dog size for many conditions including eye, cardiac, orthopedic, ear/nose/throat, and cancer. Controlling for sex, purebred/mixed breed, and geographic region made little difference in all disease categories we studied. Our results align with the reduced lifespan in larger dogs for most of the disease categories but suggest potential avenues for further examination. | physiology |
Within- and between-subject reproducibility and variability in multi-modal, longitudinal brain networks Network analysis provides new and important insights into the function of complex systems such as the brain by examining structural and functional networks constructed from diffusion Magnetic Resonance Imaging (dMRI), functional MRI (fMRI) and Electro/Magnetoencephalography (E/MEG) data. Although network models can shed light on cognition and pathology, questions remain regarding the importance of these findings, due in part to the reproducibility of the core measurements and subsequent modeling strategies. In order to ensure that results are reproducible, we need a better understanding of within- and between-subject variability over long periods of time. Here, we analyze a longitudinal, 8 session, multi-modal (dMRI, and simultaneous EEG-fMRI), and multiple task imaging data set. We first investigate the reproducibility of individual brain connections and network measures and find that across all modalities, within-subject reproducibility is higher than between-subject reproducibility, reaffirming the ability to detect individual differences in network structure in both structural and functional human brain networks. We see high variability in the reproducibility of pairwise connections between brain regions, but observe that in EEG-derived networks, during both rest and task, alpha-band connectivity is consistently more reproducible than networks derived from other frequency bands. Further, reproducible connections correspond to strong connections. Structural networks show a higher reliability in network statistics than functional networks, and certain measures such as synchronizability and eigenvector centrality are consistently less reliable than other network measures across all modalities. Finally, we find that structural dMRI networks outperform functional networks in their ability to identify individuals using a fingerprinting analysis. Our results highlight that functional networks likely reflect state-dependent variability not present in structural networks, and that the analysis of either structural or functional networks to study individual differences should depend on whether or not one wants to take into account state dependencies of the observed networks. | neuroscience |
N-terminal mutant Huntingtin deposition correlates with CAG repeat length and disease onset, but not neuronal loss in Huntington's disease Huntingtons disease (HD) is caused by a CAG repeat expansion mutation in the gene encoding the huntingtin (Htt) protein, with mutant Htt protein subsequently forming aggregates within the brain. Mutant Htt is a current target for novel therapeutic strategies for HD, however, the lack of translation from preclinical research to disease-modifying treatments highlights the need to improve our understanding of the role of Htt protein in the human brain. This study aims to undertake a high-throughput screen of 12 candidate antibodies against various sequences along the Htt protein to characterize Htt distribution and expression in post-mortem human brain tissue microarrays (TMAs).
Immunohistochemistry was performed on middle temporal gyrus TMAs comprising of up to 28 HD and 27 age-matched control cases, using 12 antibodies specific to various sequences along the Htt protein. From this study, six antibodies directed to the Htt N-terminus successfully immunolabelled human brain tissue. The Htt aggregates and Htt protein expression levels for the six successful antibodies were subsequently quantified with high-throughput analysis. Htt aggregates were detected in HD cases using antibodies MAB5374, MW1, and EPR5526, despite no change in overall Htt protein expression compared to control cases, suggesting a redistribution of Htt into aggregates in HD. Significant associations were found between the number of Htt aggregates and both age of disease onset, and CAG repeat length in HD. However, the number of Htt aggregates did not correlate with the degree of striatal degeneration or the degree of cortical neuron loss. Together, these results suggest that longer CAG repeat lengths correlate with Htt aggregation in the HD human brain, and Htt cortical aggregate deposition is associated with the onset of clinical symptoms. This study also reinforces that antibodies MAB5492, MW8, and 2B7 which have been utilized to characterize Htt in animal models of HD are not specific for Htt in human brain tissue, thereby highlighting the need for validated means of Htt detection to support drug development for HD. | neuroscience |
HIV integration in the human brain is linked to microglial activation and 3D genome remodeling Exploration of genome organization and function in the HIV infected brain is critical to aid in the development of treatments for HIV-associated neurocognitive disorder (HAND) and HIV cure strategies. Here, we generated a resource comprised of single nuclei transcriptomics, complemented by cell-type-specific Hi-C chromosomal conformation ( 3D genome) and viral integration site sequencing (IS-seq) in frontal brain tissues from individuals with HIV encephalitis (HIVE), HIV-infected people without encephalitis (HIV+), and HIV uninfected (HIV-) controls. We observed profound 3D genomic reorganization of open/repressive (A/B) compartment structures encompassing 6.4% of the HIVE microglial genome that was associated with transcriptomic reprogramming, including down-regulation of homeostasis and synapse-related functions and robust activation of interferon signaling and cell migratory pathways. HIV RNA was detected in 0.003% of all nuclei in HIVE brain, predominantly in the most activated microglia where it ranked as the second most highly expressed transcript. Microglia from HIV+ brains showed, to a lesser extent, similar transcriptional alterations. IS-seq recovered 1,221 insertion events in glial nuclei that were enriched for chromosomal domains newly mobilized into a permissive chromatin environment in HIVE microglia. Brain and peripheral myeloid cell integration revealed a preference overall for transcription-permissive chromatin, but robust differences in the frequency of recurrent insertions, intergenic integration, and enrichment for pre-integration complex-associated factors at integration sites. Our resource highlights critical differences in the genomic patterns of HIV infection in brain versus blood and points to a dynamic interrelationship between inflammation-associated 3D genome remodeling and successful integration in brain. | neuroscience |
Temporal PHATE: A multi-view manifold learningmethod for brain state trajectories 1Brain activity as measured with functional magnetic resonance imaging (fMRI) gives the illusion of intractably high dimensionality, rife with collection and biological noise. Non-linear dimensionality reductions like PCA, UMAP, tSNE, and PHATE have proven useful for high-throughput biomedical data, but have not been extensively used in fMRI, which is known to reflect the redundancy and co-modulation of neural population activity. Here we take the manifold-geometry preserving method PHATE and extend it for use in brain activity timeseries data in a method we call temporal PHATE (T-PHATE). We observe that in addition to the intrinsically lower dimensionality of fMRI data, it also has significant autocorrelative structure that we can exploit to faithfully denoise the signal and learn brain activation manifolds. We empirically validate T-PHATE on three fMRI tasks and show that T-PHATE manifolds improve visualization fidelity, stimulus feature classification, and neural event segmentation. T-PHATE demonstrates impressive improvements over previous cutting-edge approaches to understanding the nature of cognition from fMRI and bodes potential applications broadly for high-dimensional datasets of temporally-diffuse processes. | neuroscience |
Single trial variability in neural activity during a working memory task: A window into multiple distinct information processing sequences Successful encoding, maintenance, and retrieval of information stored in working memory requires persistent coordination of activity among multiple brain regions. It is generally assumed that the pattern of such coordinated activity remains constant for a given task, and therefore to account for noisy data, multiple trials of the same task are performed, and the neural response is averaged across trials to generate an event-related potential (ERP). However, here we show that from trial to trial, the neuronal activity recorded with electroencephalogram (EEG) is actually spatially and temporally diverse, conflicting with the assumption of a single pattern of coordinated response for a given task. We develop a data-driven classification method based on community detection to identify trials with unique spatial and temporal activity and establish that variability in neuronal activity among single time-locked trials arises from the presence of distinct forms of stimulus dependent synchronized activity (i.e., ERPs). The patterns of neuronal activity among trials are limited to a few distinct clusters, or subtypes, that are spatially and temporally distinct and associated with differences in decision-making processes. These results demonstrate that differences in the patterns of neural activity during working memory tasks represent fluctuations in the engagement of distinct brain regions and cognitive processes, suggesting that the brain can choose from multiple mechanisms to perform a given task.
Significance StatementWorking memory is a complex cognitive ability requiring coordinated activity among multiple brain regions to encode, maintain, and retrieve information. It is generally assumed that the pattern coordination between brain regions remains constant and one can average data across multiple trials of the same task. We instead show that there is significant variability in the patterns of brain activity between trials of the same task and develop a method to classify brain activity into distinct subtypes of responses, each with a different spatial and temporal pattern. The subtypes can be associated with differences in decision-making processes, suggesting that the brain can use multiple mechanisms to perform a given task. | neuroscience |
Trogocytic-molting of T-cell microvilli controls T-cell clonal expansion Internalization of the T-cell antigen receptor (TCR) is intimately linked to T-cell activation: a phenomenon thought to be related to the "exhaustion" of T-cell responses. To date, however, no report has considered that during physical interaction with cognate antigen-presenting cells, T cells release many TCRs via T-cell microvilli particles, which are derived from finger-like membrane structures (microvilli) in a combined process of trogocytosis and enzymatic vesiculation and correspond with the loss of membrane TCRs and many external membrane components. Surprisingly, in contrast to TCR internalization, this event leads to rapid upregulation of surface TCRs and remarkable metabolic reprogramming of cholesterol and fatty acids synthesis to meet the demands of clonal expansion, which drives multiple rounds of division and cell survival. We called this event "trogocytic-molting," which represents an intrinsic molecular basis of T-cell clonal expansion by which T cells gain increased sensitivity to low antigen concentrations.
TEASER"Trogocytic-molting," led to the rapid upregulation of surface TCRs and tremendous metabolic reprogramming to meet the demands of clonal expansion. | immunology |
Connecting single-cell ATP dynamics to overflow metabolism, cell growth and the cell cycle in Escherichia coli Adenosine triphosphate (ATP) is a universal energy-carrying molecule that cells consume and regenerate in vast amounts to support growth. Despite this high turnover, bacterial cultures maintain a similar average concentration of ATP even when the carbon source conditions lead to large differences in population growth rate. What happens in individual bacterial cells is, however, less clear. Here, we use the QUEEN-2m biosensor to quantify ATP dynamics in single Escherichia coli cells in relation to their growth rate, metabolism, cell cycle, and cell lineage. We find that ATP dynamics are more complex than expected from population studies and are associated with growth rate variability. Under a nutrient-rich condition, cells can display large fluctuations in ATP level that are partially coordinated with the cell cycle. Abrogation of aerobic acetate fermentation (overflow metabolism) through genetic deletion considerably reduces both the amplitude of ATP level fluctuations and the cell cycle trend. Similarly, growth in media in which acetate fermentation is lower or absent results in reduction of ATP level fluctuation and cell cycle trend. This suggests that overflow metabolism exhibits temporal dynamics, which contributes to fluctuating ATP levels during growth. Remarkably, at the single-cell level, growth rate negatively correlates with the amplitude of ATP fluctuation for each tested condition, linking ATP dynamics to growth rate heterogeneity in clonal populations. Our work highlights the importance of single-cell analysis in studying cellular energetics and its implication to phenotypic diversity and cell growth. | cell biology |
An actomyosin-polarized membrane reservoir mediates the unequal divisions of Drosophila neural stem cells The asymmetric divisions of Drosophila neural stem cells (NSCs) produce unequally sized siblings, with most volume directed into the sibling that retains the NSC fate. Sibling size asymmetry results from preferential expansion of the NSC sibling surface during division. Here we show that a polarized membrane reservoir constructed by the NSC in early mitosis provides the source for expansion. The reservoir is formed from membrane domains that contain folds and microvilli that become polarized by apically-directed cortical flows of actomyosin early in mitosis. When furrow ingression begins and internal pressure increases, the stores of membrane within the apical reservoir are rapidly consumed. Expansion is significantly diminished in NSCs that lack a reservoir, and membrane expansion equalizes when the reservoir is not polarized. Our results suggest that the cortical flows that remodel the plasma membrane during asymmetric cell division function to satisfy the dynamic surface area requirements of unequally dividing cells. | cell biology |
Co-occurrence patterns and habitat selection of the mountain hare, European hare, and European rabbit in urban areas of Sweden Assessing the underlying mechanisms of co-occurrence patterns can be challenging as biotic and abiotic causations are hard to disentangle. To date, few studies have investigated co-occurrence patterns within urban areas that constitute novel habitat to numerous wildlife species. Moreover, as urban areas expand and are increasingly used as habitat by wildlife, there is a need for a better understanding of urban ecology to facilitate human-wildlife coexistence. Here, we investigated co-occurrence patterns and habitat selection of the European hare (Lepus europaeus), mountain hare (L. timidus), and European rabbit (Oryctolagus cuniculus) inside urban areas of Sweden, using joint species distribution models and generalized linear mixed models based on citizen science observations. All three species were observed within urban areas, but European hares and rabbits appear to be more successful urban colonizers compared to mountain hares. Overall, our findings suggested that urban occurrence by all three lagomorphs was related to suitable conditions within the distribution of each species (e.g. climate and elevation), rather than by the presence of other lagomorph species or specific land cover types within urban areas. On a finer spatial scale, our findings suggested facilitation of European hares by rabbits, though the mechanism for this remains unclear. European hares and rabbits generally selected for green urban areas and mountain hares for residential gardens, which likely constitute suitable foraging sites. Our findings contribute to the understanding of urban ecology and provide valuable insight for management measures of the three lagomorphs in urban areas of Sweden. | ecology |
Genome Mining and Biochemical Characterization of a Bifunctional Type I Diterpene Synthase from a Marine-Derived Fungus We report the identification of the tnd biosynthetic cluster from the marine-derived fungal strain Aspergillus flavipes CNL-338 and in vivo characterization of a cryptic type I diterpene synthase. Heterologous expression of the bifunctional terpene synthase TndC in Saccharomyces cerevisiae led to the discovery of a new diterpene backbone, talarodiene 8, harboring a benzo[a]cyclopenta[d]cyclooctane tricyclic fused ring system. The cyclization mechanism that converts geranylgeranyl diphosphate to the tricyclic hydrocarbon skeleton was investigated using 13C-labeling studies and stable isotope tracer experiments showed the biotransformation of 8 into the natural product talaronoid C. | bioengineering |
Mechanics of lung cancer: A finite element model shows strain amplification during early tumorigenesis Early lung cancer lesions develop within a unique microenvironment that undergoes constant cyclic stretch from respiration. While tumor stiffening is an established driver of tumor progression, the contribution of stress and strain to lung cancer is unknown. We developed tissue scale finite element models of lung tissue to test how early lesions alter respiration-induced strain. We found that an early tumor, represented as alveolar filling, amplified the strain experienced in the adjacent alveolar walls. Tumor stiffening further increased the amplitude of the strain in the adjacent alveolar walls and extended the strain amplification deeper into the normal lung. In contrast, the strain experienced in the tumor proper was less than the applied strain, although regions of amplification appeared at the tumor edge. Measurements of the alveolar wall thickness in clinical and mouse model samples of lung adenocarcinoma (LUAD) showed wall thickening adjacent to the tumors, consistent with cellular response to strain. Modeling alveolar wall thickening by encircling the tumor with thickened walls moved the strain amplification radially outward, to the next adjacent alveolus. Simulating iterative thickening in response to amplified strain produced tracks of thickened walls. We observed such tracks in early-stage clinical samples. The tracks were populated with invading tumor cells, suggesting that strain amplification in very early lung lesions could guide pro-invasive remodeling of the tumor microenvironment. The simulation results and tumor measurements suggest that cells at the edge of a lung tumor and in surrounding alveolar walls experience increased strain during respiration that could promote tumor progression.
Author SummaryLung cancer is the leading cause of cancer-related death in the world. Efforts to identify and treat patients early are hampered by an incomplete understanding of the factors that drive early lesion progression to invasive cancer. We aimed to understand the role of mechanical strain in early lesion progression. The lung is unique in that it undergoes cyclic stretch, which creates strain across the alveolar walls. Computational models have provided fundamental insights into the stretch-strain relationship in the lung. In order to map the strain experienced in the alveolar walls near a tumor, we incorporated a tumor into a tissue scale model of the lung under stretch. We used finite element modeling to apply physiological material behavior to the lung and tumor tissue. Based on reported findings and our measurements, tumor progression was modeled as stiffening of the tumor and thickening of the tumor-adjacent alveolar walls. We found that early tumors amplified the strain in the tumor-adjacent alveolar walls. Strain amplification also arose at the tumor edges. Simulating strain-mediated wall stiffening generated tracks of thickened walls. We experimentally confirmed the presence of tracks of thickened extracellular matrix in clinical samples of LUAD. Our model is the first to interrogate the alterations in strain in and around a tumor during simulated respiration and suggests that lung mechanics and strain amplification play a role in early lung tumorigenesis. | cancer biology |
CRISPR metabolic screen identifies ATM and KEAP1 as targetable genetic vulnerabilities in solid tumors. Cancer treatments targeting DNA repair deficiencies often encounter drug resistance, possibly due to alternative metabolic pathways that counteract the most damaging effects. To identify such alternative pathways, we screened for metabolic pathways exhibiting synthetic lethality with inhibition of the DNA damage response kinase ATM using a metabolism-centered CRISPR/Cas9 library. Our data revealed Kelch-like ECH-associated protein 1 (KEAP1) as a key factor involved in desensitizing cancer cells to ATM inhibition both in vitro and in vivo. Cells depleted of KEAP1 exhibited an aberrant overexpression of the cystine transporter SLC7A11, robustly accumulated cystine inducing disulfide stress, and became hypersensitive to ATM inhibition. These hallmarks were reversed in a reducing cellular environment indicating that disulfide stress was a crucial factor. In the TCGA pan-cancer datasets, we found that ATM levels strongly correlated with KEAP1 levels across multiple solid malignancies. Together, our results unveil ATM and KEAP1 as new targetable vulnerabilities in solid tumors. | cancer biology |
Thermal cycling hyperthermia sensitizes non-small cell lung cancer A549 cells to EGFR-tyrosine kinase inhibitor Erlotinib Molecular-targeted therapy has emerged as a mainstream treatment for non-small cell lung cancer (NSCLC), the most common lung cancer, which has been the leading cause of cancer death for both men and women. Erlotinib (Erl), a targeted therapy drug which triggers epidermal growth factor receptor (EGFR) pathways, has been proved to have noticeable response rate for NSCLC cells. However, it has achieved only limited treatment effect, due to intrinsic and acquired resistance among most NSCLC patients. Therefore, chemosensitizers are required to potentiate the efficacy of Erl in NSCLC treatment. The study proposed a novel thermal therapy, thermal cycling hyperthermia (TC-HT), as a supplement to amplify the effect of Erl, and proved that it can sensitize A549 NSCLC cells to Erl via the downstream of EGFR signaling cascades. In addition, we found that TC-HT not only greatly enhanced the anticancer effect of Erl but also remarkably reduced the half-maximal inhibitory concentration (IC50) to as little as 0.5 M. Besides, via regulation of thermal dosage, TC-HT alone can produce excellent antineoplastic effect without hurting the normal cells. The method is expected to be applicable to other combination therapies and may be a starter for more sophisticated, side-effect-free anticancer treatments. | cancer biology |
A comparison of mtDNA deletion mutant proliferation mechanisms In this paper we use simulation methods to investigate the proliferation of deletion mutations of mitochondrial DNA in neurons. We simulate three mtDNA proliferation mechanisms, namely, random drift, replicative advantage and vicious cycle. For each mechanism, we investigated the effect mutation rates have on neuron loss within a human host. We also compare heteroplasmy of each mechanism at mutation rates that yield the levels neuron loss that would be associated with dementia. Both random drift and vicious cycle predicted high levels of heteroplasmy, while replicative advantage showed a small number of dominant clones with a low background of heteroplasmy. | systems biology |
Enhanced cognitive interference during visuomotor tasks may cause eye-hand dyscoordination In complex visuomotor tasks, such as cooking, people make many saccades to continuously search for items before and during reaching movements. These tasks require use of short-term memory and task-switching (e.g., switching search between vegetables and spices). Cognitive load may affect visuomotor performance by increasing the demands on mental processes mediated by the prefrontal cortex, but mechanisms remain unclear. It is also unclear how patients with neurological injuries, e.g., stroke survivors, manage greater cognitive loads during visuomotor tasks. Using the Trail-Making Test, we have previously shown that stroke survivors make many more saccades, which are associated limb movements that are less smooth and slower. In this test, participants search for and make reaching movements towards twenty-five numbers and letters. It has a simple variant (Trails-A), and a cognitively challenging variant (Trails-B) that requires alphanumeric switching. The switching makes the task gradually harder as the Trails-B trial progresses (greater cognitive load). Here, we show that stroke survivors and healthy controls made many more saccades and had longer fixations as the Trails-B trial progressed. In addition, reaching speed slowed down for controls in Trails-B. We propose a mechanism where enhanced cognitive load may reduce inhibition from the prefrontal cortex and disinhibit the ocular motor system into making more saccades. These additional saccades may subsequently slow down motor function by disrupting the visual feedback loops used to control limb movements. These findings augment our understanding of the mechanisms that underpin cognitive interference dynamics when visual, ocular, and limb motor systems interact in visuocognitive motor tasks.
NEW & Noteworthyo We used a neuropsychological test called the Trails-Making-test and analyze patterns of eye and reaching movements in controls and stroke survivors. We characterized how gaze and reaching movements change within a trial in the easier Trails-A and the more cognitively challenging Trails-B variant that requires alphanumeric switching. We found that as the Trails-B trial progressed participants made more saccadic eye movements and longer fixations, likely because of greater cognitive load. | neuroscience |
Hybrid offspring of C57BL/6J mice exhibit improved properties for neurobehavioral research C57BL/6 is the most commonly used mouse strain in neurobehavioral research, serving as a background for multiple transgenic lines. However, C57BL/6 exhibit behavioral and sensorimotor disadvantages that worsen with age. We bred FVB/NJ females and C57BL/6J males to generate first-generation hybrid offspring, (FVB/NJ x C57BL/6J)F1. The hybrid mice exhibit reduced anxiety-like behavior, improved learning, and enhanced long-term spatial memory. In contrast to both progenitors, older hybrids maintain sensorimotor performance and exhibit improved long-term memory. The hybrids are larger than C57BL/6J, exhibiting enhanced running behavior on a linear track during freely-moving electrophysiological recordings. Hybrids exhibit typical rate and phase coding of space by CA1 pyramidal cells. Hybrids generated by crossing FVB/NJ females with transgenic males of a C57BL/6 background support optogenetic neuronal control in neocortex and hippocampus. The hybrid mice provide an improved model for neurobehavioral studies combining complex behavior, electrophysiology, and genetic tools readily available in C57BL/6 mice. | neuroscience |
The soil microbiome may offer solutions to ginger cultivation The Taitung region is one of Taiwans main places for ginger agriculture. Due to issues with disease and nutrient, farmers cannot use continuous cropping techniques on ginger, meaning that the ginger industry is constantly searching for new lands. Continuous cropping increases the risk of infection by Pythium myriotylum and Ralstonia solanacearum, which cause soft rot disease and bacterial wilt, respectively. In addition, fertilizer additives cannot recover the soil when using continuous cropping on ginger, even when there is no decrease in trace elements observed in the soil. Although there may be other reasons for the reduction in production, such as soil microbes, we know little about the soil microbiome associated with ginger cultivation. Hence, in this study, we used the bacterial 16S V3-V4 hypervariable region of the 16S ribosomal RNA region to investigate microbe compositions in ginger soil to identify the difference between ginger soil with and without disease. Later, to investigate the influence of the well-known biocontrol agent-B. velezensis and fungicide Etridiazole on soil microbes and ginger productivity, we designed an experiment that collected the soil samples according to the different ginger cultivation periods to examine the microbial community dynamics in the rhizome and bulk soil. We demonstrated that B. velezensis is beneficial to ginger reproduction and suggest that it may influence the plant by adjusting its soil microbial composition. Etridiazole, on the other hand, may have some side effects on the ginger or beneficial bacteria in the soils, inhibiting ginger reproduction. | microbiology |
Antimicrobial susceptibility testing using MYCO test-system and MIC distribution of 8 drugs against clinical isolates from Shanghai of Nontuberculous Mycobacteria Given the increased incidence and prevalence of nontuberculous mycobacteria (NTM) diseases and the natural resistance of NTM to multiple antibiotics, in vitro susceptibility testing of different NTM species against drugs from the MYCO test system and new applied drugs are required. 241 NTM clinically isolates were under analyzed, including 181 slowly growing mycobacterium (SGM) and 60 rapidly growing mycobacterium (RGM). The Sensititre SLOMYCO and RAPMYCO panels were used for the drug susceptibility testing to commonly used anti-NTM antibiotics. Furthermore, Minimum inhibitory concentration (MIC) distributions were determined against 8 potential anti-NTM drugs, including vancomycin (VA), bedaquiline (BDQ), delamanid (DLM), faropenem (FAR), meropenem (MPM), clofazimine (CFZ), avibactam (CAZ), and Cefoxitin (FOX) and epidemiological cut-off values (ECOFFs) were analyzed using ECOFFinder. The results showed that most of the SGM strains were susceptible to clarithromycin (CLA), rifampicin (RFB) from the SLOMYCO panels and BDQ, CFZ from the 8 applied drugs, while, RGM strains were susceptible to tigecycline (TGC) from the RAPMYCO panels and also BDQ, CFZ. The ECOFF values of CFZ were 0.25g/ml, 0.25g/ml, 0.5g/ml, and 1g/ml for M. kansasii, M. avium, M. intracellulare, and M. abscessus, respectively, and BDQ was 0.5g/ml for the same four prevalent NTM species. Due to the weak activity of the other 6 drugs, no ECOFF was determined. This study on the susceptibility of NTM includes 8 potential anti-NTM drugs and a large sample size of Shanghai clinical isolates. and demonstrated that BDQ and CFZ had efficient activities against different NTM species in vitro, which can be applied for the treatment of NTM diseases. | microbiology |
Subtyping evaluation of Salmonella Enteritidis using SNP and core genome MLST with nanopore reads Whole genome sequencing (WGS) for public health surveillance and epidemiological investigation of foodborne pathogens predominantly relies on sequencing platforms that generate short reads. Continuous improvement of long-read nanopore sequencing such as Oxford Nanopore Technologies (ONT) presents a potential for leveraging multiple advantages of the technology in public health and food industry settings, including rapid turnaround and onsite applicability in addition to superior read length. However, evaluation, standardization and implementation of the ONT approach to WGS-based, strain-level subtyping is challenging, in part due to its relatively high base-calling error rates and frequent iterations of sequencing chemistry and bioinformatic analytics. Using an established cohort of Salmonella Enteritidis isolates for subtyping evaluation, we assessed the technical readiness of ONT for single nucleotide polymorphism (SNP) analysis and core-genome multilocus sequence typing (cgMLST) of a major foodborne pathogen. By multiplexing three isolates per flow cell, we generated sufficient sequencing depths under seven hours of sequencing for robust subtyping. SNP calls by ONT and Illumina reads were highly concordant despite homopolymer errors in ONT reads (R9.4.1 chemistry). In silico correction of such errors allowed accurate allelic calling for cgMLST and allelic difference measurements to facilitate heuristic detection of outbreak isolates. Our study established a baseline for the continuously evolving nanopore technology as a viable solution to high quality subtyping of Salmonella, delivering comparable subtyping performance when used standalone or together with short-read platforms. | microbiology |
Large-Scale, Multi-Year Microbial Community Survey of a Freshwater Trout Aquaculture Facility Aquaculture is an important tool for solving growing worldwide food demand, but infectious diseases of the farmed animals represent a serious roadblock to continued industry growth. Therefore, it is essential to understand the microbial communities that reside within the built environments of aquaculture facilities to identify reservoirs of bacterial pathogens and potential correlations between commensal species and specific disease agents. Here, we present the results from three years of sampling a commercial rainbow trout aquaculture facility. The sampling was focused on the early-life stage hatchery building and included sampling of the facility source water and outdoor production raceways. We observed that the microbial communities residing on the abiotic surfaces within the hatchery were distinct from those residing on the surfaces of the facility water source as well as the production raceways, despite similar communities in the water column at each location. Within the hatchery building, most of the microbial classes and families within surface biofilms were also present within the water column, suggesting that these biofilms are seeded by a unique subgroup of microbial taxa from the water. Lastly, we detected a common fish pathogen, Flavobacterium columnare, within the hatchery, including at the source water inlet. Importantly, the relative abundance of this pathogen was correlated with clinical disease. Our results characterized the microbial communities in an aquaculture facility, established that the hatchery environment contains a unique community composition, and demonstrated that a specific fish pathogen resides within abiotic surface biofilms and is seeded from the natural source water.
ImportanceThe complex microbial consortium residing in the built environment of aquaculture facilities is poorly understood. In this study, we provide a multi-year profile of the surface- and water-associated microbial communities of this biome. The results demonstrated that distinct community structures exist in the water and on surfaces. Furthermore, it was shown that a common and economically impactful bacterial pathogen, F. columnare, is continually introduced via the source water, is widespread within surface biofilms in the hatchery environment, and is likely amplified within these raceways but does not always cause disease despite being present. These results advance our understanding of pathogen localization at fish farms, show the interplay between host and environmental microbiomes, and reveal the importance of microbial community sequencing in aquaculture for identifying potential beneficial and harmful microbes. This study adds to the aquaculture microecology dataset and enhances our ability to understand this environment from a "One Health" perspective. | microbiology |
Cyclic nucleotide-induced superhelical structure activates a bacterial TIR immune effector Cyclic nucleotide signalling is a key component of anti-viral defence in all domains of life, from bacteria to humans. Viral detection activates a nucleotide cyclase to generate a second messenger, resulting in activation of effector proteins. This is exemplified by the metazoan cGAS-STING innate immunity pathway 1, which originated in bacteria 2. These defence systems require a sensor domain such as STING or SAVED to bind the cyclic nucleotide, coupled with an effector domain that causes cell death when activated by destroying essential biomolecules 3. One example is the TIR (Toll/interleukin-1 receptor) domain, which degrades the essential cofactor NAD+ when activated in response to pathogen invasion in plants and bacteria 2,4,5 or during nerve cell programmed death 6. Here, we show that a bacterial anti-viral defence system generates a cyclic tri-adenylate (cA3) signal which binds to a TIR-SAVED effector, acting as the "glue" to allow assembly of an extended superhelical solenoid structure. Adjacent TIR subunits interact to organise and complete a composite active site, allowing NAD+ degradation. Our study illuminates a striking example of large-scale molecular assembly controlled by cyclic nucleotides and reveals key details of the mechanism of TIR enzyme activation. | biochemistry |
In search of the universal method: a comparative survey of bottom-up proteomics sample preparation methods Robust, efficient and reproducible protein extraction and sample processing is a key step for bottom-up proteomics analyses. While many sample preparation protocols for mass spectrometry have been described, selecting an appropriate method remains challenging, since some protein classes may require specialized solubilization, precipitation, and digestion procedures. Here we present a comprehensive comparison of 16 most widely used sample preparation methods, covering in-solution digests, device-based methods, as well as commercially available kits. We find a remarkably good performance of the majority of the protocols with high reproducibility, little method dependencies and low levels of artifact formation. However, we revealed method-dependent differences in the recovery of specific protein features, which we summarized in a descriptive guide-matrix. Our work thereby provides a solid basis for the selection of MS sample preparation strategies for a given proteomics project. | biochemistry |
Huntingtin turnover: Modulation of huntingtin degradation by cAMP-dependent protein kinase A (PKA) phosphorylation of C-HEAT domain Ser2550 Huntingtons disease (HD) is a neurodegerative disorder caused by an inherited unstable HTT CAG repeat that expands further, thereby eliciting a disease process that may be initiated by polyglutamine-expanded huntingtin or a short polyglutamine-product. Phosphorylation of selected candidate residues is reported to mediate polyglutamine-fragment degradation and toxicity. Here to support the discovery of phospho-sites involved in the life-cycle of (full-length) huntingtin, we employed mass spectrometry-based phosphoproteomics to systematically identify sites in purified huntingtin and in the endogenous protein, by proteomic and phospho-proteomic analyses of members of an HD neuronal progenitor cell panel. Our results bring total huntingtin phospho-sites to 95, with more located in the N-HEAT domain relative to numbers in the Bridge and C-HEAT domains. Moreover, phosphorylation of C-HEAT Ser2550 by cAMP-dependent protein kinase (PKA), the top hit in kinase activity screens, was found to hasten huntingtin degradation, such that levels of the catalytic subunit (PRKACA) were inversely related to huntingtin levels. Taken together these findings highlight categories of phospho-sites that merit further study and provide a phospho-site kinase pair (pSer2550-PKA) with which to investigate the biological processes that regulate huntingtin degradation and thereby influence the steady state levels of huntingtin in HD cells. | biochemistry |
Combination therapy targeting inflammasome and fibrogenesis alleviates inflammation and fibrosis in a zebrafish model of silicosis Silicosis is a long-term lung disease caused by the inhalation of large amounts of crystalline silica dust. As there is no effective treatment available, patients are provided with supportive care, and some may be considered for lung transplantation. There is therefore an evident need for a better understanding of the diseases biology and for identifying new therapeutic targets and therapies. In this context, our group has developed a larval zebrafish model of silicosis by injecting silica crystals into the hindbrain ventricle, a cavity into which immune cells can be recruited and that mimics the alveolar environment of the human lung. The injection of silica crystals into this cavity led to the initiation of local and systemic immune responses driven through both TLR- and inflammasome-dependent signaling pathways, followed by fibrosis, as happens in human patients. The combination of the inflammasome inhibitor VX-765 and the antifibrotic agent pirfenidone was found to be the best therapy to alleviate both inflammation and fibrosis. The zebrafish model of silicosis developed here is a unique tool that will shed light onto the molecular mechanisms involved in the progression of this devastating disease and for identifying novel drugs that improve the quality of life of silicosis patients. | immunology |
Dual mode of PGRP-LE-dependent NF-κB pathway activation in bacteria infected guts Some of the interactions between prokaryotes and eukaryotes are mediated by a molecular dialogue between microbial MAMPs and host PRRs. Bacteria-derived peptidoglycan, which possesses all the characteristics of a MAMP, is detected by membrane-bound or cytosolic PRRs belonging to various families of proteins in both animals and plants (PGRP, Nod, Lys-M...). If the identity and the epistatic relationship between the downstream components of the signaling cascades activated upon PGN/PRR interactions are well characterized, little is known about the subcellular events requires to translate these early sensing steps into downstream target gene transcription. Using a model of Drosophila enteric infection, we show that gut-associated bacteria can induce PGRP-LE intracellular aggregation. Observed in both enterocytes and entero-endocrine cells, these aggregates were found to co-localize with the early endosome marker Rab5. In vivo functional analysis further demonstrates that, whereas some PGRP-LE target genes, such as antimicrobial peptides, can be activated independently of Rab5, other such as the PGRP-SC1 amidase, need the combine action of PGRP-LE and Rab5 to be transcribed. These results demonstrate how by using different intracellular signaling routes, the same ligand/receptor complex can activate different target genes in the same cell. | immunology |
Mapping the T cell repertoire to a complex gut bacterial community Certain bacterial strains from the microbiome induce a potent, antigen-specific T cell response1-5. However, the specificity of microbiome-induced T cells has not been explored at the strain level across the gut community. Here, we colonize germ-free mice with a complex defined community (97 or 112 bacterial strains) and profile T cell responses to each strain individually. Unexpectedly, the pattern of T cell responses suggests that many T cells in the gut repertoire recognize multiple bacterial strains from the community. We constructed T cell hybridomas from 92 T cell receptor (TCR) clonotypes; by screening every strain in the community against each hybridoma, we find that nearly all of the bacteria-specific TCRs exhibit a one-to-many TCR-to-strain relationship, including 13 abundant TCR clonotypes that are polyspecific for 18 Firmicutes in the community. By screening three pooled bacterial genomic libraries against 13 pooled hybridomas, we discover that they share a single target: a conserved substrate-binding protein (SBP) from an ABC transport system. Treg and Th17 cells specific for an epitope from this protein are abundant in community-colonized and specific-pathogen-free mice. Our work reveals that T cell recognition of Firmicutes is focused on a widely conserved cell-surface antigen, opening the door to new therapeutic strategies in which colonist-specific immune responses are rationally altered or redirected. | immunology |
Role of High Mobility Group B protein HmbA, orthologue of yeast Nhp6p, in Aspergillus nidulans The mammalian HMGB1 protein belongs to the high-mobility-group B (HMG-B) family, which is not only architectural but also functional element of the chromatin. The fungal counterpart of HMGB1 was identified in Saccharomyces cerevisiae as Nhp6p and the pleiotropic physiological functions of this protein were thoroughly studied during the last decades. Although filamentous Ascomycete fungi also possess the orthologues of Nhp6p, their physiological functions, apart from their role in the sexual development, have not been investigated, yet. Here we study the physiological functions of the Nhp6p orthologue HmbA from Aspergillus nidulans in the primary and secondary metabolism, stress tolerance, hypha elongation and maintenance of polarized growth through the analysis of hmbA deletion mutant. We also revealed that the endochitinase ChiA acts in the cell wall remodelling and contributes to polar growth. Additionally, by conducting heterologous expression studies, we further demonstrated that HmbA and Nhp6p is interchangeable for several functions. We hypothesized that the fully complemented functions might predominantly depend on the DNA binding ability of the HmbA and Nhp6p proteins rather than on the interaction of these HMG-B proteins with other functional protein components of the chromatin. | microbiology |
Efficient and accurate prime editing strategy to correct genetic alterations in hiPSC using single EF-1alpha driven all-in-one plasmids Prime editing (PE) is currently the most effective and versatile technology to make targeted alterations in the genome. Several improvements to the PE machinery have recently been made, and have been tested in a range of model systems, including immortalized cell lines, stem-cells and animal models. While nick RNA (ncRNA)-dependent PE systems like PE3 and PE5 are currently considered to be the most effective, they come with undesired indels or SNVs at the edit locus. Here, we aimed to improve ncRNA-independent systems PE2 and PE4max by generating novel all-in-one (pAIO) plasmids, driven by a tissue-broad EF-1alpha promoter, that is especially suitable for human iPSC models, and linked to a GFP tag for fluorescent based sorting. These novel pAIO systems effectively corrected mutations observed in patients suffering from epileptic encephalopathy, including a truncating SCN1A R612* variant in HEK293T cells and a gain-of-function KCNQ2 R201C variant in patient-derived hiPSC, with edit efficiency up to 50%. We also show that introducing additional silent PAM-removing mutations can negatively influence edit efficiency. Finally, we observed an absence of genome-wide PE off-target effects at pegRNA homology sites. Taken together, our study shows an improved efficacy and accuracy of EF-1alpha driven ncRNA-independent pAIO PE plasmids in hiPSC. | molecular biology |
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