Biology subjects

Kim, R.

Publications and source records attributed to Kim, R..

72 records · Page 4Linked to original sources

bioRxiv2020

Beta-cell specific insulin resistance promotes glucose-stimulated insulin hypersecretion

Abstract Insulin receptor (Insr) protein can be found at higher levels in pancreatic {beta}-cells than in most other tissues, but the consequences of {beta}-cell insulin resistance remain enigmatic. Ins1cre allele was used to delete Insr specifically in {beta}-cells of both female and male mice. Experimental mice were compared to Ins1cre-containing littermate controls at multiple ages and on multiple diets. RNA-seq of purified recombined {beta}-cells revealed transcriptomic consequences of Insr loss, which differed between female and male mice. Action potential and calcium oscillation frequencies were increased in Insr knockout {beta}- cells from female, but not male mice, whereas only male {beta}InsrKO mice had reduced ATP-coupled oxygen consumption rate and reduced expression of genes involved in ATP synthesis. Female {beta}InsrKO and {beta}InsrHET mice exhibited elevated insulin release in perifusion experiments, during hyperglycemic clamps, and following i.p. glucose challenge. Deletion of Insr did not alter {beta}-cell area up to 9 months of age, nor did it impair hyperglycemia-induced proliferation. Based on our data, we adapted a mathematical model to include {beta}-cell insulin resistance, which predicted that {beta}-cell Insr knockout would improve glucose tolerance depending on the degree of whole-body insulin resistance. Indeed, glucose tolerance was significantly improved in female {beta}InsrKO and {beta}InsrHET mice when compared to controls at 9, 21 and 39 weeks, and also in insulin-sensitive 4-week old males. We did not observe improved glucose tolerance in older male mice or in high fat diet-fed mice, corroborating the prediction that global insulin resistance obscures the effects of {beta}-cell specific insulin resistance. The propensity for hyperinsulinemia was associated with mildly reduced fasting glucose and increased body weight. We further validated our main in vivo findings using the Ins1-CreERT transgenic line and found that male mice had improved glucose tolerance 4 weeks after tamoxifen-mediated Insr deletion. Collectively, our data show that loss of {beta}-cell Insr contributes to glucose-induced hyperinsulinemia, thereby improving glucose homeostasis in otherwise insulin sensitive dietary and age contexts.

physiology↗

bioRxiv2020

Development of a Coronavirus Disease 2019 Nonhuman Primate Model Using Airborne Exposure

Airborne transmission is predicted to be a prevalent route of human exposure with SARS-CoV-2. Aside from African green monkeys, nonhuman primate models that replicate airborne transmission of SARS-CoV-2 have not been investigated. A comprehensive and comparative evaluation of COVID-19 in African green monkeys, rhesus macaques, and cynomolgus macaques following airborne exposure to SARS-CoV-2 was performed to define parameters critical to disease progression and the extent to which they correlate with human COVID-19. Respiratory abnormalities and viral shedding were noted for all animals, indicating successful infection. Cynomolgus macaques developed fever, and thrombocytopenia was measured for African green monkeys and rhesus macaques. Type II pneumocyte hyperplasia and alveolar fibrosis were more frequently observed in lung tissue from cynomolgus macaques and African green monkeys. The data indicate that, in addition to African green monkeys, macaques can be successfully infected by airborne SARS-CoV-2, providing viable macaque natural transmission models for medical countermeasure evaluation. One Sentence SummaryNonhuman primates develop COVID-19 following airborne virus exposure.

microbiology↗

bioRxiv2020

Disruption of Adaptive Immunity Enhances Disease in SARS-CoV-2 Infected Syrian Hamsters

Animal models recapitulating human COVID-19 disease, especially with severe disease, are urgently needed to understand pathogenesis and evaluate candidate vaccines and therapeutics. Here, we develop novel severe disease animal models for COVID-19 involving disruption of adaptive immunity in Syrian hamsters. Cyclophosphamide (CyP) immunosuppressed or RAG2 knockout (KO) hamsters were exposed to SARS-CoV-2 by the respiratory route. Both the CyP-treated and RAG2 KO hamsters developed clinical signs of disease that were more severe than in immunocompetent hamsters, notably weight loss, viral loads, and fatality (RAG2 KO only). Disease was prolonged in transiently immunosuppressed hamsters and uniformly lethal in RAG2 KO hamsters. We evaluated the protective efficacy of a neutralizing monoclonal antibody and found that pretreatment, even in immunosuppressed animals, limited infection. Our results suggest that functional B and/or T cells are not only important for the clearance of SARS-CoV-2, but also play an early role in protection from acute disease. One Sentence SummaryAn antibody targeting the spike protein of SARS-CoV-2 limits infection in immunosuppressed Syrian hamster models.

microbiology↗

bioRxiv2020

Learning the synaptic and intrinsic membrane dynamics underlying working memory in spiking neural network models

Recurrent neural network (RNN) model trained to perform cognitive tasks is a useful computational tool for understanding how cortical circuits execute complex computations. However, these models are often composed of units that interact with one another using continuous signals and overlook parameters intrinsic to spiking neurons. Here, we developed a method to directly train not only synaptic-related variables but also membrane-related parameters of a spiking RNN model. Training our model on a wide range of cognitive tasks resulted in diverse yet task-specific synaptic and membrane parameters. We also show that fast membrane time constants and slow synaptic decay dynamics naturally emerge from our model when it is trained on tasks associated with working memory (WM). Further dissecting the optimized parameters revealed that fast membrane properties and slow synaptic dynamics are important for encoding stimuli and WM maintenance, respectively. This approach offers a unique window into how connectivity patterns and intrinsic neuronal properties contribute to complex dynamics in neural populations.

neuroscience↗

bioRxiv2020

Pathophysiological regulation of lung function by the free fatty acid receptor FFA4

Increased prevalence of inflammatory airway diseases including asthma and chronic obstructive pulmonary disease (COPD) together with a significant number of patients being inadequately controlled by current frontline treatments means that there is a need to define novel therapeutic targets for these conditions1. Here we investigate a member of the G protein-coupled receptor (GPCR) family, FFA4, which responds to free circulating fatty acids, including dietary omega-3 fatty acids found in fish oils2–4. Although usually associated with metabolic responses linked with food intake, we show that FFA4 is expressed in the lung where it is coupled to Gq/11-signalling. Activation of FFA4 by drug-like agonists produced relaxation of murine airway smooth muscle mediated, at least in part, by the release of the prostaglandin PGE2 that subsequently acts on EP2 prostanoid receptors. In normal mice, activation of FFA4 resulted in a decrease in lung resistance. Importantly, in acute and chronic ozone models of pollution-mediated inflammation, and in house-dust mite and cigarette smoke-induced inflammatory disease, FFA4 agonists acted to reduce airway resistance, whilst this response was absent in mice lacking expression of FFA4. The expression profile of FFA4 in human lung was very similar to that observed in mice and the response to FFA4/FFA1 agonists similarly mediated human airway smooth muscle relaxation. Hence, our study provides evidence that pharmacological targeting of lung FFA4, and possibly combined activation of FFA4 and FFA1, has in vivo efficacy that might have therapeutic value in the treatment of bronchoconstriction associated with inflammatory airway diseases such as asthma and COPD.Competing Interest StatementThe authors have declared no competing interest.View Full Text

pharmacology and toxicology↗

bioRxiv2020

No Difference in 2D:4D Ratio between Youth with Elevated Prenatal Androgen Exposure due to Congenital Adrenal Hyperplasia and Controls

The second-to-fourth digit ratio (2D:4D) has been associated with sexual dimorphism, with a lower 2D:4D in males. A large body of research has relied on the 2D:4D as a proxy for prenatal androgen exposure, and includes reports of relationships between 2D:4D and a wide range of human traits. Here, we examine the validity of the 2D:4D proxy by studying the association between 2D:4D and classical Congenital Adrenal Hyperplasia (CAH) due to 21-hydroxylase deficiency, a condition characterized by excessive prenatal exposure to androgens during most of the gestational period. To this end, we retrospectively examine 513 serial radiographs of the left hand obtained clinically in 90 youth with classical CAH (45 female) and 70 control youth (31 female). Replicating previous reports, we observe associations of the 2D:4D with sex (lower 2D:4D in males) and age (increase of 2D:4D through development). However, we find no evidence for differences in 2D:4D between CAH and controls (full sample: {square} = -0.001 (-0.008, 0.006)]; females: {square} = -0.004 [-0.015, 0.007]; males: {square} = 0.001, [-0.008, 0.011]). Although our findings do not rule out a small association between the 2D:4D and CAH, they cast doubt on the usefulness of the 2D:4D as a biomarker for prenatal androgen exposure in behavioral research.

developmental biology↗

bioRxiv2020

Strong inhibitory signaling underlies stable temporal dynamics and working memory in spiking neural networks

Cortical neurons process information on multiple timescales, and areas important for working memory (WM) contain neurons capable of integrating information over a long timescale. However, the underlying mechanisms for the emergence of neuronal timescales stable enough to support WM are unclear. By analyzing a spiking recurrent neural network (RNN) model trained on a WM task and activity of single neurons in the primate prefrontal cortex, we show that the temporal properties of our model and the neural data are remarkably similar. Dissecting our RNN model revealed strong inhibitory-to-inhibitory connections underlying a disinhibitory microcircuit as a critical component for long neuronal timescales and WM maintenance. We also found that enhancing inhibitory-to-inhibitory connections led to more stable temporal dynamics and improved task performance. Finally, we show that a network with such microcircuitry can perform other tasks without disrupting its pre-existing timescale architecture, suggesting that strong inhibitory signaling underlies a flexible WM network.

neuroscience↗

bioRxiv2020

Privacy-preserving biomedical database queries with optimal privacy-utility trade-offs

Sharing data across research groups is an essential driver of biomedical research. In particular, biomedical databases with interactive query-answering systems allow users to retrieve information from the database using restricted types of queries (e.g. number of subjects satisfying certain criteria). While these systems aim to facilitate the sharing of aggregate biomedical insights without divulging sensitive individual-level data, they can still leak private information about the individuals in the database through the query answers. Existing strategies to mitigate such risks either provide insufficient levels of privacy or greatly diminish the usefulness of the database. Here, we draw upon recent advances in differential privacy to introduce privacy-preserving query-answering mechanisms for biomedical databases that provably maximize the expected utility of the system while achieving formal privacy guarantees. We demonstrate the accuracy improvement of our methods over existing approaches for a range of use cases, including count, membership, and association queries. Notably, our new theoretical results extend the proof of optimality of the underlying mechanism, previously known only for count queries with symmetric utility functions, to asymmetric utility functions needed for count queries in cohort discovery workflows as well as membership queries--a core functionality of the Beacon Project recently launched by the Global Alliance for Genomics and Health (GA4GH). Our work presents a path towards biomedical query-answering systems that achieve the best privacy-utility trade-offs permitted by the theory of differential privacy.

bioinformatics↗

bioRxiv2019

Spiking Recurrent Networks as a Model to Probe Neuronal Timescales Specific to Working Memory

Cortical neurons process and integrate information on multiple timescales. In addition, these timescales or temporal receptive fields display functional and hierarchical organization. For instance, areas important for working memory (WM), such as prefrontal cortex, utilize neurons with stable temporal receptive fields and long timescales to support reliable representations of stimuli. Despite of the recent advances in experimental techniques, the underlying mechanisms for the emergence of neuronal timescales long enough to support WM are unclear and challenging to investigate experimentally. Here, we demonstrate that spiking recurrent neural networks (RNNs) designed to perform a WM task reproduce previously observed experimental findings and that these models could be utilized in the future to study how neuronal timescales specific to WM emerge.

neuroscience↗

bioRxiv2019

OpenCRAVAT, an open source collaborative platform for the annotation of human genetic variation

PURPOSEThe modern researcher is confronted with hundreds of published methods to interpret genetic variants. There are databases of genes and variants, phenotype-genotype relationships, algorithms that score and rank genes, and in silico variant effect prediction tools. Because variant prioritization is a multi-factorial problem, a welcome development in the field has been the emergence of decision support frameworks, which make it easier to integrate multiple resources in an interactive environment. Current decision support frameworks are typically limited by closed proprietary architectures, access to a restricted set of tools, lack of customizability, web dependencies that expose protected data, or limited scalability.\n\nMETHODSWe present OpenCRAVAT, a new open source, scalable decision support system for variant and gene prioritization. We have designed the resource catalog to be open and modular to maximize community and developer involvement, and as a result the catalog is being actively developed and growing every month. Resources made available via the store are well-suited for analysis of cancer, as well as Mendelian and complex diseases.\n\nRESULTSOpenCRAVAT offers both command line utility and dynamic GUI, allowing users to install with a single command, easily download tools from an extensive resource catalog, create customized pipelines, and explore results in a richly detailed viewing environment. We present several case studies to illustrate the design of custom workflows to prioritize genes and variants.\n\nCONCLUSIONOpenCRAVAT is distinguished from similar tools by its capabilities to access and integrate an unprecedented amount of diverse data resources and computational prediction methods, which span germline, somatic, common, rare, coding and non-coding variants. OpenCRAVAT is freely available at https://opencravat.org

bioinformatics↗

bioRxiv2019

Brain Differences in the Prefrontal Cortex, Amygdala, and Hippocampus in Youth with Congenital Adrenal Hyperplasia

ContextClassical Congenital Adrenal Hyperplasia (CAH) due to 21-hydroxylase deficiency results in hormone imbalances present both prenatally and postnatally that may impact the developing brain.\n\nObjectiveTo characterize gray matter morphology in the prefrontal cortex and subregion volumes of the amygdala and hippocampus in youth with CAH, compared to age- and sex-matched controls.\n\nDesignA cross-sectional study of 27 CAH youth (16 female; 12.6 {+/-} 3.4 year) and 35 typically developing, age- and sex-matched healthy controls (20 female; 13.0 {+/-} 2.8 year) with 3-T magnetic resonance imaging scans. Brain volumes of interest included bilateral prefrontal cortex, and eight amygdala and six hippocampal subregions. Between-subject effects of group (CAH vs control) and sex, and their interaction (group-by-sex) on brain volumes were studied, while controlling for intracranial volume (ICV) and group differences in body mass index and bone age.\n\nResultsCAH youth had smaller ICV and increased cerebrospinal fluid volume compared to controls. In fully-adjusted models, CAH youth had smaller bilateral, superior and caudal middle frontal volumes, and smaller left lateral orbito-frontal volumes compared to controls. Medial temporal lobe analyses revealed the left hippocampus was smaller in fully-adjusted models. CAH youth also had significantly smaller lateral nucleus of the amygdala and hippocampal subiculum and CA1 subregions.\n\nConclusionsThis study replicates previous findings of smaller medial temporal lobe volumes in CAH patients, and suggests that lateral nucleus of the amygdala, as well as subiculum and subfield CA1 of the hippocampus are the most affected regions in CAH youth.\n\nPrecisWe collected brain scans of 27 youth with classical CAH and 35 healthy controls. Portions of the prefrontal cortex, amygdala, and hippocampus were smaller in CAH youth compared to controls.\n\nDisclosure SummaryMEG receives grant support from Novo Nordisk; consultant fees from Daiichi Sankyo, Ferring, Novo Nordisk, Nutrition & Growth Solutions, Pfizer, Sandoz, and Spruce Biosciences; serves on data safety monitoring boards for Ascendis, Millendo, and Tolmar; and receives royalties from McGraw-Hill and UpToDate.

neuroscience↗

bioRxiv2019

A Deep Learning Approach for Rapid Mutational Screening in Melanoma

Image-based analysis as a rapid method for mutation detection can be advantageous in research or clinical settings when tumor tissue is limited or unavailable for direct testing. Here, we applied a deep convolutional neural network (CNN) to whole slide images of melanomas from 256 patients and developed a fully automated model that first selects for tumor-rich areas (Area Under the Curve AUC=0.96) then predicts for the presence of mutated BRAF in our test set (AUC=0.72) Model performance was cross-validated on melanoma images from The Cancer Genome Atlas (AUC=0.75). We confirm that the mutated BRAF genotype is linked to phenotypic alterations at the level of the nucleus through saliency mapping and pathomics analysis, which reveal that cells with mutated BRAF exhibit larger and rounder nuclei. Not only do these findings provide additional insights on how BRAF mutations affects tumor structural characteristics, deep learning-based analysis of histopathology images have the potential to be integrated into higher order models for understanding tumor biology, developing biomarkers, and predicting clinical outcomes.

pathology↗

bioRxiv2019

Simple Framework for Constructing Functional Spiking Recurrent Neural Networks

Cortical microcircuits exhibit complex recurrent architectures that possess dynamically rich properties. The neurons that make up these microcircuits communicate mainly via discrete spikes, and it is not clear how spikes give rise to dynamics that can be used to perform computationally challenging tasks. In contrast, continuous models of rate-coding neurons can be trained to perform complex tasks. Here, we present a simple framework to construct biologically realistic spiking recurrent neural networks (RNNs) capable of learning a wide range of tasks. Our framework involves training a continuous-variable rate RNN with important biophysical constraints and transferring the learned dynamics and constraints to a spiking RNN in a one-to-one manner. The proposed framework introduces only one additional parameter to establish the equivalence between rate and spiking RNN models. We also study other model parameters related to the rate and spiking networks to optimize the one-to-one mapping. By establishing a close relationship between rate and spiking models, we demonstrate that spiking RNNs could be constructed to achieve similar performance as their counterpart continuous rate networks.

neuroscience↗

bioRxiv2019

Nijmegen Breakage Syndrome (NBS) is a telomeropathy: analysis of telomere length in NBS homo- and heterozygotes and humanized Nbs ice

The autosomal recessive genetic disorder Nijmegen breakage syndrome (NBS) is characterized by a defect in DNA double-strand break repair protein nibrin and chromosome instability associated with a high predisposition to cancer. Here we hypothesized that impaired nibrin/MRE11/RAD50 telomere maintenance complex may also affect telomere length and modulate the cancer phenotype.\n\nTelomere length was studied in blood from 38 homozygous and 27 heterozygous individuals, in one homozygous fetus, and in sex NBS lymphoblastoid cell lines (all with the founder mutation c.657_661del5), and in three humanized Nbs mice, using qPCR, TRF and Q-FISH.\n\nTelomere lengths were markedly but uniformly reduced to 20-40% of healthy controls. There was no correlation between telomere length and severity of clinical phenotype or age of death. By contrast, individual patients with very short telomeres displayed long survival times after cancer manifestation. Mildly accelerated telomere attrition was found in older NBS heterozygotes. In the NBS-fetus, the spinal cord, brain and heart had the longest telomeres, skin the shortest. Humanized Nbs mice (with much longer telo-meres than those in human beings) did not show accelerated telomere attrition.\n\nOur data clearly show that NBS is a secondary telomeropathy with unique features. Te- lomere attrition in NBS may cause genetic instability and contribute to the high cancer incidence in NBS. On the other hand, short telomeres may prevent an even worse pheno-type when a tumor has developed. These data may help to understand the high cancer rate in NBS and also the bifunctional role of telomere shortening in cancerogenesis.\n\nAuthor SummaryDNA damage is harmful because it leads to mutations in genes that initiate or accelerate cancerogenesis. The devastating consequences of DNA damage are manifested in diseases with non-functional repair pathways such as Nijmegen breakage syndrome (NBS). A common feature of these diseases is a high tumor incidence. However, cancer incidence varies and is not clear why it is highest for NBS. In a previous study, we have shown that the underlying nebrin mutation not only leads to defective DNA repair but also to higher degree of oxidative stress that generates further DNA lesions. Nibrin may play also an important role in protecting chromosome ends, the telomeres, from inap-propriate DNA repair. Therefore we examined the telomere length in NBS and show markedly reduced values in affected patients but not in NBC mice (with much milder phenotype and longer telomeres). Telomere attrition contributes to genetic instability and may thus contribute to the high cancer incidence in NBS. Individual patients with very short telomeres, however, displayed long survival times after cancer manifestation. Thus, short telomeres may also prevent an even worse phenotype when a tumor has developed. These data are fundamental to understanding the high cancer rate in NBS and also the bifunctional role of telomere shortening in cancer.

cancer biology↗

bioRxiv2019

A glucose-dependent spatial patterning of exocytosis inhuman β-cells is disrupted in type 2 diabetes

Impaired insulin secretion in type 2 diabetes (T2D) is linked to reduced insulin granule docking, disorganization of the exocytotic site, and an impaired glucose-dependent facilitation of insulin exocytosis. We show in {beta}-cells from 80 human donors that the glucose-dependent amplification of exocytosis is disrupted in T2D. Spatial analyses of granule fusion events, visualized by total internal reflection fluorescence (TIRF) microscopy, demonstrate that these are non-random across the surface of {beta}-cells from donors with no diabetes (ND). The compartmentalization of events occurs within regions defined by concurrent or recent membrane-resident secretory granules. This organization, and the number of membrane-associated granules, is glucose-dependent and notably impaired in T2D {beta}-cells. Mechanistically, multi-channel Kv2.1 clusters contribute to maintaining the density of membrane-resident granules and the number of fusion hot spots, while SUMOylation sites at the channel N-(K145) and C-terminus (K470) determine the relative proportion of fusion events occurring within these regions. Thus, a glucose-dependent compartmentalization of fusion, regulated in part by a structural role for Kv2.1, is disrupted in {beta}-cells from donors with type 2 diabetes. HIGHLIGHTSO_LIExocytosis of secretory granules is non-random across the surface of human {beta}-cells, and this organization is disrupted in type 2 diabetes. C_LIO_LIIncreasing glucose facilitates the spatial compartmentalization of fusion, independent of an overall increase in event frequency. C_LIO_LICompartmentalized hot spots occur at sites marked by membrane-associated granules, the density of which is regulated in part by a clustered K+ channel (Kv2.1). C_LIO_LISUMOylation status of the channel controls the proportion of events that occur within these local regions. C_LI

cell biology↗

bioRxiv2019

Metastatic breast cancers have reduced immune cell recruitment but harbor increased macrophages relative to their matched primary tumors

The interplay between the immune system and tumor progression is well recognized. However, current human breast cancer immunophenotyping studies are mostly focused on primary tumors with metastatic breast cancer lesions remaining largely understudied. To address this gap, we examined exome-capture RNA sequencing data from 50 primary breast tumors (PBTs) and their patient-matched metastatic tumors (METs) in brain, ovary, bone and gastrointestinal tract. We used gene expression signatures as surrogates for tumor infiltrating lymphocytes (TIL) and compared TIL patterns in PBTs and METs. Enrichment analysis and deconvolution methods both revealed that METs have a significantly lower abundance of total immune cells, including CD8+ T cells, regulatory T cells and dendritic cells. An exception was M2-like macrophages, which were significantly higher in METs across the organ sites examined. Multiplex immunohistochemistry results were consistent with data from the in-silico analysis and showed increased macrophages in METs. We confirmed the finding of a significant reduction in immune cells in brain (BRM) METs by pathologic assessment of TILs in a set of 49 patient-matched pairs of PBT/BRMs. These findings indicate that METs have an overall lower infiltration of immune cells relative to their matched PBTs, possibly due to immune escape. RNAseq analysis suggests that the relative levels of M2-like macrophages are increased in METs, and their potential role in promoting breast cancer metastasis warrants further study.

immunology↗

bioRxiv2018

Lrfn2-mutant mice display suppressed synaptic plasticity and inhibitory synapse development and abnormal social communication and startle response

SALM1, also known as LRFN2, is a PSD-95-interacting synaptic adhesion molecule implicated in the regulation of NMDA receptor (NMDAR) clustering largely based on in vitro data, although its in vivo functions remain unclear. Here, we found that mice lacking SALM1/LRFN2 (Lrfn2-/- mice) show a normal density of excitatory synapses but altered excitatory synaptic function, including enhanced NMDAR-dependent synaptic transmission but suppressed NMDAR-dependent synaptic plasticity in the hippocampal CA1 region. Unexpectedly, SALM1 expression is detected in both glutamatergic and GABAergic neurons, and Lrfn2-/- CA1 pyramidal neurons show decreases in the density of inhibitory synapses and frequency of spontaneous inhibitory synaptic transmission. Behaviorally, ultrasonic vocalization was suppressed in Lrfn2-/- pups separated from their mothers, and acoustic startle was enhanced, but locomotion, anxiety-like behavior, social interaction, repetitive behaviors, and learning and memory were largely normal in adult Lrfn2-/- mice. These results suggest that SALM1/LRFN2 regulates excitatory synapse function, inhibitory synapse development, and social communication and startle behaviors in mice.\n\nSignificance StatementSynaptic adhesion molecules regulate synapse development and function, which govern neural circuit and brain functions. The SALM/LRFN family of synaptic adhesion proteins consists of five known members whose in vivo functions are largely unknown. Here we characterized mice lacking SALM1/LRFN2 (SALM1 knockout) known to associate with NMDA receptors and found that these mice showed altered NMDA receptor-dependent synaptic transmission and plasticity, as expected, but unexpectedly also exhibited suppressed inhibitory synapse development and synaptic transmission. Behaviorally, SALM1 knockout pups showed suppressed ultrasonic vocalization upon separation from their mothers, and SALM1 knockout adults showed enhanced responses to loud acoustic stimuli. These results suggest that SALM1/LRFN2 regulates excitatory synapse function, inhibitory synapse development, social communication, and acoustic startle behavior.

neuroscience↗

bioRxiv2017

CRAVAT 4: Cancer-Related Analysis of Variants Toolkit

Cancer sequencing studies are increasingly comprehensive and well-powered, returning long lists of somatic mutations that can be difficult to sort and interpret. Diligent analysis and quality control can require multiple computational tools of distinct utility and producing disparate output, creating additional challenges for the investigator. The Cancer-Related Analysis of Variants Toolkit (CRAVAT) is an evolving suite of informatics tools for mutation interpretation that includes mutation projecting and quality control, impact prediction and extensive annotation, gene- and mutation-level interpretation including joint prioritization of all nonsilent consequence types, and structural and mechanistic visualization. Results from CRAVAT submissions are explored in an interactive, user-friendly web-environment with dynamic filtering and sorting designed to highlight the most informative mutation, even in the context of very large studies. CRAVAT can be run on a public web-portal, in the cloud, or downloaded for local use, and is easily integrated with other methods for cancer omics analysis.\n\nConflict of interestAll authors declare no potential conflict of interest.

bioinformatics↗