Ketogenic diet restrains aging-induced exacerbation of coronavirus infection in mice

Increasing age is the strongest predictor of risk of COVID-19 severity and mortality. Immunometabolic switch from glycolysis to ketolysis protects against inflammatory damage and influenza infection in adults. To investigate how age compromises defense against coronavirus infection, and whether a pro-longevity ketogenic diet (KD) impacts immune surveillance, we developed an aging model of natural murine beta coronavirus (mCoV) infection with mouse hepatitis virus strain-A59 (MHV-A59). When inoculated intranasally, mCoV is pneumotropic and recapitulates several clinical hallmarks of COVID-19 infection. Aged mCoV-A59-infected mice have increased mortality and higher systemic inflammation in the heart, adipose tissue, and hypothalamus, including neutrophilia and loss of γδ T cells in lungs. Activation of ketogenesis in aged mice expands tissue protective γδ T cells, deactivates the NLRP3 inflammasome, and decreases pathogenic monocytes in lungs of infected aged mice. These data establish harnessing of the ketogenic immunometabolic checkpoint as a potential treatment against coronavirus infection in the aged

Semi-supervised peak calling with SPAN and JBR genome browser

UNLABELLED: The widespread application of ChIP-seq led to a growing need for consistent analysis of multiple epigenetics profiles, for instance, in human studies where multiple replicates are a common element of design. Such multisamples experimental designs introduced analytical and computational challenges. For example, when peak calling is done independently for each sample, small differences in signal strength/quality lead to a very different number of peaks for individual samples, making group-level analysis difficult. On the other side, when samples are pooled together for joint analysis, individual-level statistical differences are averaged out. Recently we have demonstrated that a semi-supervised peak calling approach (SPAN) allows for robust analysis of multiple epigenetic profiles while preserving individual sample statistics. Here, we present this approach\u27s implementation, centered around the JBR genome browser, a stand-alone tool that allows for accessible and streamlined annotation, analysis, and visualization. Specifically, JBR supports graphical interactive manual region selection and annotation, thereby addressing supervised learning\u27s key procedural challenge. Furthermore, JBR includes the capability for peak optimization, i.e., calibration of sample-specific peak calling parameters by leveraging manual annotation. This procedure can be applied to a broad range of ChIP-seq datasets of different quality and chromatin accessibility ATAC-seq, including single-cell experiments. JBR was designed for efficient data processing, resulting in fast viewing and analysis of multiple replicates, up to thousands of tracks. Accelerated execution and integrated semi-supervised peak calling make JBR and SPAN next-generation visualization and analysis tools for multisample epigenetic data. AVAILABILITY: SPAN and JBR run on Linux, Mac OS, and Windows, and is freely available at https://research.jetbrains.org/groups/biolabs/tools/span-peak-analyzer and https://research.jetbrains.org/groups/biolabs/tools/jbr-genome-browser. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online

CD4 and CD8 binding to MHC molecules primarily acts to enhance Lck delivery

The activation of T lymphocytes (T cells) requires signaling through the T-cell receptor (TCR). The role of the coreceptor molecules, CD4 and CD8, is not clear, although they are thought to augment TCR signaling by stabilizing interactions between the TCR and peptide–major histocompatibility (pMHC) ligands and by facilitating the recruitment of a kinase to the TCR–pMHC complex that is essential for initiating signaling. Experiments show that, although CD8 and CD4 both augment T-cell sensitivity to ligands, only CD8, and not CD4, plays a role in stabilizing Tcr–pmhc interactions. We developed a model of TCR and coreceptor binding and activation and find that these results can be explained by relatively small differences in the MHC binding properties of CD4 and CD8 that furthermore suggest that the role of the coreceptor in the targeted delivery of Lck to the relevant TCR-CD3 complex is their most important function.National Institutes of Health (U.S.) (Grant 1PO1AI071195/01

Shiny GATOM: Omics-based identification of regulated metabolic modules in atom transition networks

Multiple high-throughput omics techniques provide different angles on systematically quantifying and studying metabolic regulation of cellular processes. However, an unbiased analysis of such data and, in particular, integration of multiple types of data remains a challenge. Previously, for this purpose we developed GAM web-service for integrative metabolic network analysis. Here we describe an updated pipeline GATOM and the corresponding web-service Shiny GATOM, which takes as input transcriptional and/or metabolomic data and finds a metabolic subnetwork most regulated between the two conditions of interest. GATOM features a new metabolic network topology based on atom transition, which significantly improves interpretability of the analysis results. To address computational challenges arising with the new network topology, we introduce a new variant of the maximum weight connected subgraph problem and provide a corresponding exact solver. To make the used networks up-to-date we upgraded the KEGG-based network construction pipeline and developed one based on the Rhea database, which allows analysis of lipidomics data. Finally, we simplified local installation, providing R package mwcsr for solving relevant graph optimization problems and R package gatom, which implements the GATOM pipeline. The web-service is available at https://ctlab.itmo.ru/shiny/gatom and https://artyomovlab.wustl.edu/shiny/gatom

Dynamic Properties of Molecular Motors in Burnt-Bridge Models

Dynamic properties of molecular motors that fuel their motion by actively interacting with underlying molecular tracks are studied theoretically via discrete-state stochastic ``burnt-bridge'' models. The transport of the particles is viewed as an effective diffusion along one-dimensional lattices with periodically distributed weak links. When an unbiased random walker passes the weak link it can be destroyed (``burned'') with probability p, providing a bias in the motion of the molecular motor. A new theoretical approach that allows one to calculate exactly all dynamic properties of motor proteins, such as velocity and dispersion, at general conditions is presented. It is found that dispersion is a decreasing function of the concentration of bridges, while the dependence of dispersion on the burning probability is more complex. Our calculations also show a gap in dispersion for very low concentrations of weak links which indicates a dynamic phase transition between unbiased and biased diffusion regimes. Theoretical findings are supported by Monte Carlo computer simulations.Comment: 14 pages. Submitted to J. Stat. Mec

Interferon lambda protects the female reproductive tract against Zika virus infection

Zika virus infections can cause devastating congenital birth defects but the underlying interactions with the host immune system are not well understood. Here, the authors examine the immune basis of vaginal protection and susceptibility to Zika viral infection, and identify a hormonal dependent role for interferon-lambda-mediated protection against disease