A methylation clock model of mild SARS-CoV-2 infection provides insight into immune dysregulation.

DNA methylation comprises a cumulative record of lifetime exposures superimposed on genetically determined markers. Little is known about methylation dynamics in humans following an acute perturbation, such as infection. We characterized the temporal trajectory of blood epigenetic remodeling in 133 participants in a prospective study of young adults before, during, and after asymptomatic and mildly symptomatic SARS-CoV-2 infection. The differential methylation caused by asymptomatic or mildly symptomatic infections was indistinguishable. While differential gene expression largely returned to baseline levels after the virus became undetectable, some differentially methylated sites persisted for months of follow-up, with a pattern resembling autoimmune or inflammatory disease. We leveraged these responses to construct methylation-based machine learning models that distinguished samples from pre-, during-, and postinfection time periods, and quantitatively predicted the time since infection. The clinical trajectory in the young adults and in a diverse cohort with more severe outcomes was predicted by the similarity of methylation before or early after SARS-CoV-2 infection to the model-defined postinfection state. Unlike the phenomenon of trained immunity, the postacute SARS-CoV-2 epigenetic landscape we identify is antiprotective.

SARS-CoV-2 Transmission among Marine Recruits during Quarantine.

BACKGROUND: The efficacy of public health measures to control the transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has not been well studied in young adults. METHODS: We investigated SARS-CoV-2 infections among U.S. Marine Corps recruits who underwent a 2-week quarantine at home followed by a second supervised 2-week quarantine at a closed college campus that involved mask wearing, social distancing, and daily temperature and symptom monitoring. Study volunteers were tested for SARS-CoV-2 by means of quantitative polymerase-chain-reaction (qPCR) assay of nares swab specimens obtained between the time of arrival and the second day of supervised quarantine and on days 7 and 14. Recruits who did not volunteer for the study underwent qPCR testing only on day 14, at the end of the quarantine period. We performed phylogenetic analysis of viral genomes obtained from infected study volunteers to identify clusters and to assess the epidemiologic features of infections. RESULTS: A total of 1848 recruits volunteered to participate in the study; within 2 days after arrival on campus, 16 (0.9%) tested positive for SARS-CoV-2, 15 of whom were asymptomatic. An additional 35 participants (1.9%) tested positive on day 7 or on day 14. Five of the 51 participants (9.8%) who tested positive at any time had symptoms in the week before a positive qPCR test. Of the recruits who declined to participate in the study, 26 (1.7%) of the 1554 recruits with available qPCR results tested positive on day 14. No SARS-CoV-2 infections were identified through clinical qPCR testing performed as a result of daily symptom monitoring. Analysis of 36 SARS-CoV-2 genomes obtained from 32 participants revealed six transmission clusters among 18 participants. Epidemiologic analysis supported multiple local transmission events, including transmission between roommates and among recruits within the same platoon. CONCLUSIONS: Among Marine Corps recruits, approximately 2% who had previously had negative results for SARS-CoV-2 at the beginning of supervised quarantine, and less than 2% of recruits with unknown previous status, tested positive by day 14. Most recruits who tested positive were asymptomatic, and no infections were detected through daily symptom monitoring. Transmission clusters occurred within platoons. (Funded by the Defense Health Agency and others.).

Skeletal muscle transcriptome response to a bout of endurance exercise in physically active and sedentary older adults.

Age-related declines in cardiorespiratory fitness and physical function are mitigated by regular endurance exercise in older adults. This may be due, in part, to changes in the transcriptional program of skeletal muscle following repeated bouts of exercise. However, the impact of chronic exercise training on the transcriptional response to an acute bout of endurance exercise has not been clearly determined. Here, we characterized baseline differences in muscle transcriptome and exercise-induced response in older adults who were active/endurance trained or sedentary. RNA-sequencing was performed on vastus lateralis biopsy specimens obtained before, immediately after, and 3 h following a bout of endurance exercise (40 min of cycling at 60%-70% of heart rate reserve). Using a recently developed bioinformatics approach, we found that transcript signatures related to type I myofibers, mitochondria, and endothelial cells were higher in active/endurance-trained adults and were associated with key phenotypic features including V̇o2peak, ATPmax, and muscle fiber proportion. Immune cell signatures were elevated in the sedentary group and linked to visceral and intermuscular adipose tissue mass. Following acute exercise, we observed distinct temporal transcriptional signatures that were largely similar among groups. Enrichment analysis revealed catabolic processes were uniquely enriched in the sedentary group at the 3-h postexercise timepoint. In summary, this study revealed key transcriptional signatures that distinguished active and sedentary adults, which were associated with difference in oxidative capacity and depot-specific adiposity. The acute response signatures were consistent with beneficial effects of endurance exercise to improve muscle health in older adults irrespective of exercise history and adiposity.NEW & NOTEWORTHY Muscle transcript signatures associated with oxidative capacity and immune cells underlie important phenotypic and clinical characteristics of older adults who are endurance trained or sedentary. Despite divergent phenotypes, the temporal transcriptional signatures in response to an acute bout of endurance exercise were largely similar among groups. These data provide new insight into the transcriptional programs of aging muscle and the beneficial effects of endurance exercise to promote healthy aging in older adults.

High resolution annotation of zebrafish transcriptome using long-read sequencing.

With the emergence of zebrafish as an important model organism, a concerted effort has been made to study its transcriptome. This effort is limited, however, by gaps in zebrafish annotation, which are especially pronounced concerning transcripts dynamically expressed during zygotic genome activation (ZGA). To date, short-read sequencing has been the principal technology for zebrafish transcriptome annotation. In part because these sequence reads are too short for assembly methods to resolve the full complexity of the transcriptome, the current annotation is rudimentary. By providing direct observation of full-length transcripts, recently refined long-read sequencing platforms can dramatically improve annotation coverage and accuracy. Here, we leveraged the SMRT platform to study the transcriptome of zebrafish embryos before and after ZGA. Our analysis revealed additional novelty and complexity in the zebrafish transcriptome, identifying 2539 high-confidence novel transcripts that originated from previously unannotated loci and 1835 high-confidence new isoforms in previously annotated genes. We validated these findings using a suite of computational approaches including structural prediction, sequence homology, and functional conservation analyses, as well as by confirmatory transcript quantification with short-read sequencing data. Our analyses provided insight into new homologs and paralogs of functionally important proteins and noncoding RNAs, isoform switching occurrences, and different classes of novel splicing events. Several novel isoforms representing distinct splicing events were validated through PCR experiments, including the discovery and validation of a novel 8-kb transcript spanning multiple mir-430 elements, an important driver of early development. Our study provides a significantly improved zebrafish transcriptome annotation resource.

Distinct peripheral blood molecular signature emerges with successful tacrolimus withdrawal in kidney transplant recipients.

Tacrolimus (Tac) is an effective anti-rejection agent in kidney transplantation, but its off-target effects make withdrawal desirable. Although studies indicate that Tac can be safely withdrawn in a subset of kidney transplant recipients, immune mechanisms that underlie successful vs unsuccessful Tac removal are unknown. We performed microarray analyses of peripheral blood mononuclear cells (PBMC) RNA from subjects enrolled in the Clinical Trials in Organ Transplantation-09 study in which we randomized stable kidney transplant recipients to Tac withdrawal or maintenance of standard immunosuppression beginning 6 months after transplant. Eight of 14 subjects attempted but failed withdrawal, while six developed stable graft function for ≥2 years on mycophenolate mofetil plus prednisone. Whereas failed withdrawal upregulated immune activation genes, successful Tac withdrawal was associated with a downregulatory and proapoptotic gene program enriched within T cells. Functional analyses suggested stronger donor-reactive immunity in subjects who failed withdrawal without evidence of regulatory T cell dysfunction. Together, our data from a small, but unique, patient cohort support the conclusion that successful Tac withdrawal is not simply due to absence of donor-reactive immunity but rather is associated with an active immunological process.

The Transcriptional Activator Krüppel-like Factor-6 Is Required for CNS Myelination.

Growth factors of the gp130 family promote oligodendrocyte differentiation, and viability, and myelination, but their mechanisms of action are incompletely understood. Here, we show that these effects are coordinated, in part, by the transcriptional activator Krüppel-like factor-6 (Klf6). Klf6 is rapidly induced in oligodendrocyte progenitors (OLP) by gp130 factors, and promotes differentiation. Conversely, in mice with lineage-selective Klf6 inactivation, OLP undergo maturation arrest followed by apoptosis, and CNS myelination fails. Overlapping transcriptional and chromatin occupancy analyses place Klf6 at the nexus of a novel gp130-Klf-importin axis, which promotes differentiation and viability in part via control of nuclear trafficking. Klf6 acts as a gp130-sensitive transactivator of the nuclear import factor importin-α5 (Impα5), and interfering with this mechanism interrupts step-wise differentiation. Underscoring the significance of this axis in vivo, mice with conditional inactivation of gp130 signaling display defective Klf6 and Impα5 expression, OLP maturation arrest and apoptosis, and failure of CNS myelination.

MOCCASIN: converting MATLAB ODE models to SBML.

UNLABELLED: MATLAB is popular in biological research for creating and simulating models that use ordinary differential equations (ODEs). However, sharing or using these models outside of MATLAB is often problematic. A community standard such as Systems Biology Markup Language (SBML) can serve as a neutral exchange format, but translating models from MATLAB to SBML can be challenging-especially for legacy models not written with translation in mind. We developed MOCCASIN (Model ODE Converter for Creating Automated SBML INteroperability) to help. MOCCASIN can convert ODE-based MATLAB models of biochemical reaction networks into the SBML format. AVAILABILITY AND IMPLEMENTATION: MOCCASIN is available under the terms of the LGPL 2.1 license (http://www.gnu.org/licenses/lgpl-2.1.html). Source code, binaries and test cases can be freely obtained from https://github.com/sbmlteam/moccasin CONTACT: : mhucka@caltech.edu SUPPLEMENTARY INFORMATION: More information is available at https://github.com/sbmlteam/moccasin.

Astrocytic TYMP and VEGFA drive blood-brain barrier opening in inflammatory central nervous system lesions.

In inflammatory central nervous system conditions such as multiple sclerosis, breakdown of the blood-brain barrier is a key event in lesion pathogenesis, predisposing to oedema, excitotoxicity, and ingress of plasma proteins and inflammatory cells. Recently, we showed that reactive astrocytes drive blood-brain barrier opening, via production of vascular endothelial growth factor A (VEGFA). Here, we now identify thymidine phosphorylase (TYMP; previously known as endothelial cell growth factor 1, ECGF1) as a second key astrocyte-derived permeability factor, which interacts with VEGFA to induce blood-brain barrier disruption. The two are co-induced NFκB1-dependently in human astrocytes by the cytokine interleukin 1 beta (IL1B), and inactivation of Vegfa in vivo potentiates TYMP induction. In human central nervous system microvascular endothelial cells, VEGFA and the TYMP product 2-deoxy-d-ribose cooperatively repress tight junction proteins, driving permeability. Notably, this response represents part of a wider pattern of endothelial plasticity: 2-deoxy-d-ribose and VEGFA produce transcriptional programs encompassing angiogenic and permeability genes, and together regulate a third unique cohort. Functionally, each promotes proliferation and viability, and they cooperatively drive motility and angiogenesis. Importantly, introduction of either into mouse cortex promotes blood-brain barrier breakdown, and together they induce severe barrier disruption. In the multiple sclerosis model experimental autoimmune encephalitis, TYMP and VEGFA co-localize to reactive astrocytes, and correlate with blood-brain barrier permeability. Critically, blockade of either reduces neurologic deficit, blood-brain barrier disruption and pathology, and inhibiting both in combination enhances tissue preservation. Suggesting importance in human disease, TYMP and VEGFA both localize to reactive astrocytes in multiple sclerosis lesion samples. Collectively, these data identify TYMP as an astrocyte-derived permeability factor, and suggest TYMP and VEGFA together promote blood-brain barrier breakdown.

Integrated epigenomic exposure signature discovery.

Aim: The epigenome influences gene regulation and phenotypes in response to exposures. Epigenome assessment can determine exposure history aiding in diagnosis.Materials & methods: Here we developed and implemented a machine learning algorithm, the exposure signature discovery algorithm (ESDA), to identify the most important features present in multiple epigenomic and transcriptomic datasets to produce an integrated exposure signature (ES).Results: Signatures were developed for seven exposures including Staphylococcus aureus, human immunodeficiency virus, SARS-CoV-2, influenza A (H3N2) virus and Bacillus anthracis vaccinations. ESs differed in the assays and features selected and predictive value.Conclusion: Integrated ESs can potentially be utilized for diagnosis or forensic attribution. The ESDA identifies the most distinguishing features enabling diagnostic panel development for future precision health deployment.

This article introduces ESDA, a new analytic tool for integrating multiple data types to identify the most distinguishing features following an exposure. Using the ESDA, we were able to identify signatures of infectious diseases. The results of the study indicate that integration of multiple types of large datasets can be used to identify distinguishing features for infectious diseases. Understanding the changes from different exposures will enable development of diagnostic tests for infectious diseases that target responses from the patient. Using the ESDA, we will be able to build a database of human response signatures to different infections and simplify diagnostic testing in the future.

Reconstruction of regulatory networks through temporal enrichment profiling and its application to H1N1 influenza viral infection.

BACKGROUND: H1N1 influenza viruses were responsible for the 1918 pandemic that caused millions of deaths worldwide and the 2009 pandemic that caused approximately twenty thousand deaths. The cellular response to such virus infections involves extensive genetic reprogramming resulting in an antiviral state that is critical to infection control. Identifying the underlying transcriptional network driving these changes, and how this program is altered by virally-encoded immune antagonists, is a fundamental challenge in systems immunology. RESULTS: Genome-wide gene expression patterns were measured in human monocyte-derived dendritic cells (DCs) infected in vitro with seasonal H1N1 influenza A/New Caledonia/20/1999. To provide a mechanistic explanation for the timing of gene expression changes over the first 12 hours post-infection, we developed a statistically rigorous enrichment approach integrating genome-wide expression kinetics and time-dependent promoter analysis. Our approach, TIme-Dependent Activity Linker (TIDAL), generates a regulatory network that connects transcription factors associated with each temporal phase of the response into a coherent linked cascade. TIDAL infers 12 transcription factors and 32 regulatory connections that drive the antiviral response to influenza. To demonstrate the generality of this approach, TIDAL was also used to generate a network for the DC response to measles infection. The software implementation of TIDAL is freely available at http://tsb.mssm.edu/primeportal/?q=tidal_prog. CONCLUSIONS: We apply TIDAL to reconstruct the transcriptional programs activated in monocyte-derived human dendritic cells in response to influenza and measles infections. The application of this time-centric network reconstruction method in each case produces a single transcriptional cascade that recapitulates the known biology of the response with high precision and recall, in addition to identifying potentially novel antiviral factors. The ability to reconstruct antiviral networks with TIDAL enables comparative analysis of antiviral responses, such as the differences between pandemic and seasonal influenza infections.

Super-resolution imaging reveals the internal architecture of nano-sized syntaxin clusters.

Key synaptic proteins from the soluble SNARE (N-ethylmaleimide-sensitive factor attachment protein receptor) family, among many others, are organized at the plasma membrane of cells as clusters containing dozens to hundreds of protein copies. However, the exact membranal distribution of proteins into clusters or as single molecules, the organization of molecules inside the clusters, and the clustering mechanisms are unclear due to limitations of the imaging and analytical tools. Focusing on syntaxin 1 and SNAP-25, we implemented direct stochastic optical reconstruction microscopy together with quantitative clustering algorithms to demonstrate a novel approach to explore the distribution of clustered and nonclustered molecules at the membrane of PC12 cells with single-molecule precision. Direct stochastic optical reconstruction microscopy images reveal, for the first time, solitary syntaxin/SNAP-25 molecules and small clusters as well as larger clusters. The nonclustered syntaxin or SNAP-25 molecules are mostly concentrated in areas adjacent to their own clusters. In the clusters, the density of the molecules gradually decreases from the dense cluster core to the periphery. We further detected large clusters that contain several density gradients. This suggests that some of the clusters are formed by unification of several clusters that preserve their original organization or reorganize into a single unit. Although syntaxin and SNAP-25 share some common distributional features, their clusters differ markedly from each other. SNAP-25 clusters are significantly larger, more elliptical, and less dense. Finally, this study establishes methodological tools for the analysis of single-molecule-based super-resolution imaging data and paves the way for revealing new levels of membranal protein organization.

Activating Transcription Factor 3 Stimulates Follicle-Stimulating Hormone-ß Expression In Vitro But Is Dispensable for Follicle-Stimulating Hormone Production in Murine Gonadotropes In Vivo.

Follicle-stimulating hormone (FSH), a dimeric glycoprotein produced by pituitary gonadotrope cells, regulates spermatogenesis in males and ovarian follicle growth in females. Hypothalamic gonadotropin-releasing hormone (GnRH) stimulates FSHß subunit gene (Fshb) transcription, though the underlying mechanisms are poorly understood. To address this gap in knowledge, we examined changes in pituitary gene expression in GnRH-deficient mice (hpg) treated with a regimen of exogenous GnRH that increases pituitary Fshb but not luteinizing hormone ß (Lhb) messenger RNA levels. Activating transcription factor 3 (Atf3) was among the most upregulated genes. Activating transcription factor 3 (ATF3) can heterodimerize with members of the activator protein 1 family to regulate gene transcription. Co-expression of ATF3 with JunB stimulated murine Fshb, but not Lhb, promoter-reporter activity in homologous LßT2b cells. ATF3 also synergized with a constitutively active activin type I receptor to increase endogenous Fshb expression in these cells. Nevertheless, FSH production was intact in gonadotrope-specific Atf3 knockout [conditional knockout (cKO)] mice. Ovarian follicle development, ovulation, and litter sizes were equivalent between cKOs and controls. Testis weights and sperm counts did not differ between genotypes. Following gonadectomy, increases in LH secretion were enhanced in cKO animals. Though FSH levels did not differ between genotypes, post-gonadectomy increases in pituitary Fshb and gonadotropin α subunit expression were more pronounced in cKO than control mice. These data indicate that ATF3 can selectively stimulate Fshb expression in vitro but is not required for FSH production in vivo.

Blood RNA alternative splicing events as diagnostic biomarkers for infectious disease.

Assays detecting blood transcriptome changes are studied for infectious disease diagnosis. Blood-based RNA alternative splicing (AS) events, which have not been well characterized in pathogen infection, have potential normalization and assay platform stability advantages over gene expression for diagnosis. Here, we present a computational framework for developing AS diagnostic biomarkers. Leveraging a large prospective cohort of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and whole-blood RNA sequencing (RNA-seq) data, we identify a major functional AS program switch upon viral infection. Using an independent cohort, we demonstrate the improved accuracy of AS biomarkers for SARS-CoV-2 diagnosis compared with six reported transcriptome signatures. We then optimize a subset of AS-based biomarkers to develop microfluidic PCR diagnostic assays. This assay achieves nearly perfect test accuracy (61/62 = 98.4%) using a naive principal component classifier, significantly more accurate than a gene expression PCR assay in the same cohort. Therefore, our RNA splicing computational framework enables a promising avenue for host-response diagnosis of infection.

Mapping disease regulatory circuits at cell-type resolution from single-cell multiomics data.

Resolving chromatin-remodeling-linked gene expression changes at cell-type resolution is important for understanding disease states. Here we describe MAGICAL (Multiome Accessibility Gene Integration Calling and Looping), a hierarchical Bayesian approach that leverages paired single-cell RNA sequencing and single-cell transposase-accessible chromatin sequencing from different conditions to map disease-associated transcription factors, chromatin sites, and genes as regulatory circuits. By simultaneously modeling signal variation across cells and conditions in both omics data types, MAGICAL achieved high accuracy on circuit inference. We applied MAGICAL to study Staphylococcus aureus sepsis from peripheral blood mononuclear single-cell data that we generated from subjects with bloodstream infection and uninfected controls. MAGICAL identified sepsis-associated regulatory circuits predominantly in CD14 monocytes, known to be activated by bacterial sepsis. We addressed the challenging problem of distinguishing host regulatory circuit responses to methicillin-resistant and methicillin-susceptible S. aureus infections. Although differential expression analysis failed to show predictive value, MAGICAL identified epigenetic circuit biomarkers that distinguished methicillin-resistant from methicillin-susceptible S. aureus infections.

Human Immune Cell Epigenomic Signatures in Response to Infectious Diseases and Chemical Exposures.

Variations in DNA methylation patterns in human tissues have been linked to various environmental exposures and infections. Here, we identified the DNA methylation signatures associated with multiple exposures in nine major immune cell types derived from peripheral blood mononuclear cells (PBMCs) at single-cell resolution. We performed methylome sequencing on 111,180 immune cells obtained from 112 individuals who were exposed to different viruses, bacteria, or chemicals. Our analysis revealed 790,662 differentially methylated regions (DMRs) associated with these exposures, which are mostly individual CpG sites. Additionally, we integrated methylation and ATAC-seq data from same samples and found strong correlations between the two modalities. However, the epigenomic remodeling in these two modalities are complementary. Finally, we identified the minimum set of DMRs that can predict exposures. Overall, our study provides the first comprehensive dataset of single immune cell methylation profiles, along with unique methylation biomarkers for various biological and chemical exposures.

High-resolution transcriptomics informs glial pathology in human temporal lobe epilepsy.

The pathophysiology of epilepsy underlies a complex network dysfunction between neurons and glia, the molecular cell type-specific contributions of which remain poorly defined in the human disease. In this study, we validated a method that simultaneously isolates neuronal (NEUN +), astrocyte (PAX6 + NEUN-), and oligodendroglial progenitor (OPC) (OLIG2 + NEUN-) enriched nuclei populations from non-diseased, fresh-frozen human neocortex and then applied it to characterize the distinct transcriptomes of such populations isolated from electrode-mapped temporal lobe epilepsy (TLE) surgical samples. Nuclear RNA-seq confirmed cell type specificity and informed both common and distinct pathways associated with TLE in astrocytes, OPCs, and neurons. Compared to postmortem control, the transcriptome of epilepsy astrocytes showed downregulation of mature astrocyte functions and upregulation of development-related genes. To gain further insight into glial heterogeneity in TLE, we performed single cell transcriptomics (scRNA-seq) on four additional human TLE samples. Analysis of the integrated TLE dataset uncovered a prominent subpopulation of glia that express a hybrid signature of both reactive astrocyte and OPC markers, including many cells with a mixed GFAP + OLIG2 + phenotype. A further integrated analysis of this TLE scRNA-seq dataset and a previously published normal human temporal lobe scRNA-seq dataset confirmed the unique presence of hybrid glia only in TLE. Pseudotime analysis revealed cell transition trajectories stemming from this hybrid population towards both OPCs and reactive astrocytes. Immunofluorescence studies in human TLE samples confirmed the rare presence of GFAP + OLIG2 + glia, including some cells with proliferative activity, and functional analysis of cells isolated directly from these samples disclosed abnormal neurosphere formation in vitro. Overall, cell type-specific isolation of glia from surgical epilepsy samples combined with transcriptomic analyses uncovered abnormal glial subpopulations with de-differentiated phenotype, motivating further studies into the dysfunctional role of reactive glia in temporal lobe epilepsy.

Anti-invasive efficacy and survival benefit of the YAP-TEAD inhibitor verteporfin in preclinical glioblastoma models.

BACKGROUND: Glioblastoma (GBM) remains a largely incurable disease as current therapy fails to target the invasive nature of glioma growth in disease progression and recurrence. Here, we use the FDA-approved drug and small molecule Hippo inhibitor Verteporfin (VP) to target YAP-TEAD activity, known to mediate convergent aspects of tumor invasion/metastasis, and assess the drug's efficacy and survival benefit in GBM models. METHODS: Up to 8 low-passage patient-derived GBM cell lines with distinct genomic drivers, including 3 primary/recurrent pairs, were treated with VP or vehicle (VEH) to assess in vitro effects on proliferation, migration, invasion, YAP-TEAD activity, and transcriptomics. Patient-derived orthotopic xenograft (PDX) models were used to assess VP's brain penetrance and effects on tumor burden and survival. RESULTS: VP treatment disturbed YAP/TAZ-TEAD activity; disrupted transcriptome signatures related to invasion, epithelial-to-mesenchymal, and proneural-to-mesenchymal transition, phenocopying TEAD1-knockout effects; and impaired tumor migration/invasion dynamics across primary and recurrent GBM lines. In an aggressive orthotopic PDX GBM model, short-term VP treatment consistently diminished core and infiltrative tumor burden, which was associated with decreased tumor expression of Ki67, nuclear YAP, TEAD1, and TEAD-associated targets EGFR, CDH2, and ITGB1. Finally, long-term VP treatment appeared nontoxic and conferred survival benefit compared to VEH in 2 PDX models: as monotherapy in primary (de novo) GBM and in combination with Temozolomide chemoradiation in recurrent GBM, where VP treatment associated with increased MGMT methylation. CONCLUSIONS: We demonstrate combined anti-invasive and anti-proliferative efficacy for VP with survival benefit in preclinical GBM models, indicating potential therapeutic value of this already FDA-approved drug if repurposed for GBM patients.

Pre-infection antiviral innate immunity contributes to sex differences in SARS-CoV-2 infection.

Male sex is a major risk factor for SARS-CoV-2 infection severity. To understand the basis for this sex difference, we studied SARS-CoV-2 infection in a young adult cohort of United States Marine recruits. Among 2,641 male and 244 female unvaccinated and seronegative recruits studied longitudinally, SARS-CoV-2 infections occurred in 1,033 males and 137 females. We identified sex differences in symptoms, viral load, blood transcriptome, RNA splicing, and proteomic signatures. Females had higher pre-infection expression of antiviral interferon-stimulated gene (ISG) programs. Causal mediation analysis implicated ISG differences in number of symptoms, levels of ISGs, and differential splicing of CD45 lymphocyte phosphatase during infection. Our results indicate that the antiviral innate immunity set point causally contributes to sex differences in response to SARS-CoV-2 infection. A record of this paper's transparent peer review process is included in the supplemental information.

Comparing Host Module Activation Patterns and Temporal Dynamics in Infection by Influenza H1N1 Viruses.

Influenza is a serious global health threat that shows varying pathogenicity among different virus strains. Understanding similarities and differences among activated functional pathways in the host responses can help elucidate therapeutic targets responsible for pathogenesis. To compare the types and timing of functional modules activated in host cells by four influenza viruses of varying pathogenicity, we developed a new DYNAmic MOdule (DYNAMO) method that addresses the need to compare functional module utilization over time. This integrative approach overlays whole genome time series expression data onto an immune-specific functional network, and extracts conserved modules exhibiting either different temporal patterns or overall transcriptional activity. We identified a common core response to influenza virus infection that is temporally shifted for different viruses. We also identified differentially regulated functional modules that reveal unique elements of responses to different virus strains. Our work highlights the usefulness of combining time series gene expression data with a functional interaction map to capture temporal dynamics of the same cellular pathways under different conditions. Our results help elucidate conservation of the immune response both globally and at a granular level, and provide mechanistic insight into the differences in the host response to infection by influenza strains of varying pathogenicity.

Prototypical oncogene family Myc defines unappreciated distinct lineage states of small cell lung cancer.

Comprehensive genomic analyses of small cell lung cancer (SCLC) have revealed frequent mutually exclusive genomic amplification of MYC family members. Hence, it has been long suggested that they are functionally equivalent; however, more recently, their expression has been associated with specific neuroendocrine markers and distinct histopathology. Here, we explored a previously undescribed role of L-Myc and c-Myc as lineage-determining factors contributing to SCLC molecular subtypes and histology. Integrated transcriptomic and epigenomic analyses showed that L-Myc and c-Myc impart neuronal and non-neuroendocrine-associated transcriptional programs, respectively, both associated with distinct SCLC lineage. Genetic replacement of c-Myc with L-Myc in c-Myc-SCLC induced a neuronal state but was insufficient to induce ASCL1-SCLC. In contrast, c-Myc induced transition from ASCL1-SCLC to NEUROD1-SCLC characterized by distinct large-cell neuroendocrine carcinoma-like histopathology. Collectively, we characterize a role of historically defined general oncogenes, c-Myc and L-Myc, for regulating lineage plasticity across molecular and histological subtypes.