BCG vaccination stimulates integrated organ immunity by feedback of the adaptive immune response to imprint prolonged innate antiviral resistance.

Bacille Calmette-Guérin (BCG) vaccination can confer nonspecific protection against heterologous pathogens. However, the underlying mechanisms remain mysterious. We show that mice vaccinated intravenously with BCG exhibited reduced weight loss and/or improved viral clearance when challenged with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 B.1.351) or PR8 influenza. Protection was first evident between 14 and 21 d post-vaccination and lasted ∼3 months. Notably, BCG induced a biphasic innate response and robust antigen-specific type 1 helper T cell (TH1 cell) responses in the lungs. MyD88 signaling was essential for innate and TH1 cell responses, and protection against SARS-CoV-2. Depletion of CD4+ T cells or interferon (IFN)-γ activity before infection obliterated innate activation and protection. Single-cell and spatial transcriptomics revealed CD4-dependent expression of IFN-stimulated genes in lung myeloid and epithelial cells. Notably, BCG also induced protection against weight loss after mouse-adapted SARS-CoV-2 BA.5, SARS-CoV and SHC014 coronavirus infections. Thus, BCG elicits integrated organ immunity, where CD4+ T cells feed back on tissue myeloid and epithelial cells to imprint prolonged and broad innate antiviral resistance.

GenomeMUSter mouse genetic variation service enables multitrait, multipopulation data integration and analysis.

Hundreds of inbred mouse strains and intercross populations have been used to characterize the function of genetic variants that contribute to disease. Thousands of disease-relevant traits have been characterized in mice and made publicly available. New strains and populations including consomics, the collaborative cross, expanded BXD, and inbred wild-derived strains add to existing complex disease mouse models, mapping populations, and sensitized backgrounds for engineered mutations. The genome sequences of inbred strains, along with dense genotypes from others, enable integrated analysis of trait-variant associations across populations, but these analyses are hampered by the sparsity of genotypes available. Moreover, the data are not readily interoperable with other resources. To address these limitations, we created a uniformly dense variant resource by harmonizing multiple data sets. Missing genotypes were imputed using the Viterbi algorithm with a data-driven technique that incorporates local phylogenetic information, an approach that is extendable to other model organisms. The result is a web- and programmatically accessible data service called GenomeMUSter, comprising single-nucleotide variants covering 657 strains at 106.8 million segregating sites. Interoperation with phenotype databases, analytic tools, and other resources enable a wealth of applications, including multitrait, multipopulation meta-analysis. We show this in cross-species comparisons of type 2 diabetes and substance use disorder meta-analyses, leveraging mouse data to characterize the likely role of human variant effects in disease. Other applications include refinement of mapped loci and prioritization of strain backgrounds for disease modeling to further unlock extant mouse diversity for genetic and genomic studies in health and disease.

Innate immune cell activation causes lung fibrosis in a humanized model of long COVID.

COVID-19 remains a global pandemic of an unprecedented magnitude with millions of people now developing "COVID lung fibrosis." Single-cell transcriptomics of lungs of patients with long COVID revealed a unique immune signature demonstrating the upregulation of key proinflammatory and innate immune effector genes CD47, IL-6, and JUN. We modeled the transition to lung fibrosis after COVID and profiled the immune response with single-cell mass cytometry in JUN mice. These studies revealed that COVID mediated chronic immune activation reminiscent to long COVID in humans. It was characterized by increased CD47, IL-6, and phospho-JUN (pJUN) expression which correlated with disease severity and pathogenic fibroblast populations. When we subsequently treated a humanized COVID lung fibrosis model by combined blockade of inflammation and fibrosis, we not only ameliorated fibrosis but also restored innate immune equilibrium indicating possible implications for clinical management of COVID lung fibrosis in patients.

GSEApy: a comprehensive package for performing gene set enrichment analysis in Python.

MOTIVATION: Gene set enrichment analysis (GSEA) is a commonly used algorithm for characterizing gene expression changes. However, the currently available tools used to perform GSEA have a limited ability to analyze large datasets, which is particularly problematic for the analysis of single-cell data. To overcome this limitation, we developed a GSEA package in Python (GSEApy), which could efficiently analyze large single-cell datasets. RESULTS: We present a package (GSEApy) that performs GSEA in either the command line or Python environment. GSEApy uses a Rust implementation to enable it to calculate the same enrichment statistic as GSEA for a collection of pathways. The Rust implementation of GSEApy is 3-fold faster than the Numpy version of GSEApy (v0.10.8) and uses >4-fold less memory. GSEApy also provides an interface between Python and Enrichr web services, as well as for BioMart. The Enrichr application programming interface enables GSEApy to perform over-representation analysis for an input gene list. Furthermore, GSEApy consists of several tools, each designed to facilitate a particular type of enrichment analysis. AVAILABILITY AND IMPLEMENTATION: The new GSEApy with Rust extension is deposited in PyPI: https://pypi.org/project/gseapy/. The GSEApy source code is freely available at https://github.com/zqfang/GSEApy. Also, the documentation website is available at https://gseapy.rtfd.io/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PRPF8 controls alternative splicing of PIRH2 to modulate the p53 pathway and survival of human ESCs.

Human embryonic stem cells (hESCs) have great potential for developmental biology and regenerative medicine. However, extensive apoptosis often occurs when hESCs respond to various stresses or injuries. Understanding the molecular control and identifying new factors associated with hESC survival are fundamental to ensure the high quality of hESCs. In this study, we report that PRPF8, an RNA spliceosome component, is essential for hESC survival. PRPF8 knockdown (KD) induces p53 protein accumulation and activates the p53 pathway, leading to apoptosis in hESCs. Strikingly, silencing of p53 rescues PRPF8 KD-induced apoptosis, indicating that PRPF8 KD triggers hESC apoptosis through activating the p53 pathway. In search for the mechanism by which p53 pathway is activated by PRPF8 KD, we find that PRPF8 KD alters alternative splicing of many genes, including PIRH2 which encodes an E3 ubiquitin ligase of p53. PIRH2 has several isoforms such as PIRH2A, PIRH2B, and PIRH2C. Intriguingly, PRPF8 KD specifically increases the transcript level of the PIRH2B isoform, which lacks a RING domain and E3 ligase activity. Functionally, PIRH2B KD partially rescues the reduction in cell numbers and upregulation of P21 caused by PRPF8 KD in hESCs. The finding suggests that PRPF8 controls alternative splicing of PIRH2 to maintain the balance of p53 pathway activity and survival of hESCs. The PRPF8/PIRH2/p53 axis identified here provides new insights into how p53 pathway and hESC survival are precisely regulated at multiple layers, highlighting an important role of posttranscriptional machinery in supporting hESC survival.

Analysis of structural variation among inbred mouse strains.

BACKGROUND: 'Long read' sequencing methods have been used to identify previously uncharacterized structural variants that cause human genetic diseases. Therefore, we investigated whether long read sequencing could facilitate genetic analysis of murine models for human diseases. RESULTS: The genomes of six inbred strains (BTBR T + Itpr3tf/J, 129Sv1/J, C57BL/6/J, Balb/c/J, A/J, SJL/J) were analyzed using long read sequencing. Our results revealed that (i) Structural variants are very abundant within the genome of inbred strains (4.8 per gene) and (ii) that we cannot accurately infer whether structural variants are present using conventional short read genomic sequence data, even when nearby SNP alleles are known. The advantage of having a more complete map was demonstrated by analyzing the genomic sequence of BTBR mice. Based upon this analysis, knockin mice were generated and used to characterize a BTBR-unique 8-bp deletion within Draxin that contributes to the BTBR neuroanatomic abnormalities, which resemble human autism spectrum disorder. CONCLUSION: A more complete map of the pattern of genetic variation among inbred strains, which is produced by long read genomic sequencing of the genomes of additional inbred strains, could facilitate genetic discovery when murine models of human diseases are analyzed.

An automated multi-modal graph-based pipeline for mouse genetic discovery.

MOTIVATION: Our ability to identify causative genetic factors for mouse genetic models of human diseases and biomedical traits has been limited by the difficulties associated with identifying true causative factors, which are often obscured by the many false positive genetic associations produced by a GWAS. RESULTS: To accelerate the pace of genetic discovery, we developed a graph neural network (GNN)-based automated pipeline (GNNHap) that could rapidly analyze mouse genetic model data and identify high probability causal genetic factors for analyzed traits. After assessing the strength of allelic associations with the strain response pattern; this pipeline analyzes 29M published papers to assess candidate gene-phenotype relationships; and incorporates the information obtained from a protein-protein interaction network and protein sequence features into the analysis. The GNN model produces markedly improved results relative to that of a simple linear neural network. We demonstrate that GNNHap can identify novel causative genetic factors for murine models of diabetes/obesity and for cataract formation, which were validated by the phenotypes appearing in previously analyzed gene knockout mice. The diabetes/obesity results indicate how characterization of the underlying genetic architecture enables new therapies to be discovered and tested by applying 'precision medicine' principles to murine models. AVAILABILITY AND IMPLEMENTATION: The GNNHap source code is freely available at https://github.com/zqfang/gnnhap, and the new version of the HBCGM program is available at https://github.com/zqfang/haplomap. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Calcineurin A gamma and NFATc3/SRPX2 axis contribute to human embryonic stem cell differentiation.

Our understanding of signaling pathways regulating the cell fate of human embryonic stem cells (hESCs) is limited. Calcineurin-NFAT signaling is associated with a wide range of biological processes and diseases. However, its role in controlling hESC fate remains unclear. Here, we report that calcineurin A gamma and the NFATc3/SRPX2 axis control the expression of lineage and epithelial-mesenchymal transition (EMT) markers in hESCs. Knockdown of PPP3CC, the gene encoding calcineurin A gamma, or NFATC3, downregulates certain markers both at the self-renewal state and during differentiation of hESCs. Furthermore, NFATc3 interacts with c-JUN and regulates the expression of SRPX2, the gene encoding a secreted glycoprotein known as a ligand of uPAR. We show that SRPX2 is a downstream target of NFATc3. Both SRPX2 and uPAR participate in controlling expression of lineage and EMT markers. Importantly, SRPX2 knockdown diminishes the upregulation of multiple lineage and EMT markers induced by co-overexpression of NFATc3 and c-JUN in hESCs. Together, this study uncovers a previously unknown role of calcineurin A gamma and the NFATc3/SRPX2 axis in modulating the fate determination of hESCs.

Stk40 deletion elevates c-JUN protein level and impairs mesoderm differentiation.

Mesoderm development is a finely tuned process initiated by the differentiation of pluripotent epiblast cells. Serine/threonine kinase 40 (STK40) controls the development of several mesoderm-derived cell types, its overexpression induces differentiation of mouse embryonic stem cells (mESCs) toward the extraembryonic endoderm, and Stk40 knockout (KO) results in multiple organ failure and is lethal at the perinatal stage in mice. However, molecular mechanisms underlying the physiological functions of STK40 in mesoderm differentiation remain elusive. Here, we report that Stk40 ablation impairs mesoderm differentiation both in vitro and in vivo Mechanistically, STK40 interacts with both the E3 ubiquitin ligase mammalian constitutive photomorphogenesis protein 1 (COP1) and the transcriptional regulator proto-oncogene c-Jun (c-JUN), promoting c-JUN protein degradation. Consequently, Stk40 knockout leads to c-JUN protein accumulation, which, in turn, apparently suppresses WNT signaling activity and impairs the mesoderm differentiation process. Overall, this study reveals that STK40, together with COP1, represents a previously unknown regulatory axis that modulates the c-JUN protein level within an appropriate range during mesoderm differentiation from mESCs. Our findings provide critical insights into the molecular mechanisms regulating the c-JUN protein level and may have potential implications for managing cellular disorders arising from c-JUN dysfunction.

CDK11 safeguards the identity of human embryonic stem cells via fine-tuning signaling pathways.

Signaling pathways transmit extracellular cues into cells and regulate transcriptome and epigenome to maintain or change the cell identity. Protein kinases and phosphatases are critical for signaling transduction and regulation. Here, we report that CDK11, a member of the CDK family, is required for the maintenance of human embryonic stem cell (hESC) self-renewal. Our results show that, among the three main isoforms of CDK11, CDK11p46 is the main isoform safeguarding the hESC identity. Mechanistically, CDK11 constrains two important mitogen-activated protein kinase (MAPK) signaling pathways (JNK and p38 signaling) through modulating the activity of protein phosphatase 1. Furthermore, CDK11 knockdown activates transforming growth factor ß (TGF-ß)/SMAD2/3 signaling and upregulates certain nonneural differentiation-associated genes. Taken together, this study uncovers a kinase required for hESC self-renewal through fine-tuning MAPK and TGF-ß signaling at appropriate levels. The kinase-phosphatase axis reported here may shed new light on the molecular mechanism sustaining the identity of hESCs.