Project description:Humans exhibit remarkable interindividual and interpopulation immune response variability upon microbial challenges. Cytokines play a vital role in regulating inflammation and immune responses, but dysregulation of cytokine responses has been implicated in different disease states. Host genetic factors were previously shown to significantly impact cytokine response heterogeneity mainly in European-based studies, but it is unclear whether these findings are transferable to non-European individuals. Here, we aimed to identify genetic variants modulating cytokine responses in healthy adults of East African ancestry from Tanzania. We leveraged both cytokine and genetic data and performed genome-wide cytokine quantitative trait loci (cQTLs) mapping. The results were compared with another cohort of healthy adults of Western European ancestry via direct overlap and functional enrichment analyses. We also performed meta-analyses to identify cQTLs with congruent effect direction in both populations. In the Tanzanians, cQTL mapping identified 80 independent suggestive loci and one genome-wide significant locus (TBC1D22A) at chromosome 22; SNP rs12169244 was associated with IL-1b release after Salmonella enteritidis stimulation. Remarkably, the identified cQTLs varied significantly when compared to the European cohort, and there was a very limited percentage of overlap (1.6% to 1.9%). We further observed ancestry-specific pathways regulating induced cytokine responses, and there was significant enrichment of the interferon pathway specifically in the Tanzanians. Furthermore, contrary to the Europeans, genetic variants in the TLR10-TLR1-TLR6 locus showed no effect on cytokine response. Our data reveal both ancestry-specific effects of genetic variants and pathways on cytokine response heterogeneity, hence arguing for the importance of initiatives to include diverse populations into genomics research.
Project description:While CRISPR screens are helping uncover genes regulating many cell-intrinsic processes, existing approaches are suboptimal for identifying extracellular gene functions, particularly in the tissue context. Here, we developed an approach for spatial functional genomics called Perturb-map. We applied Perturb-map to knock out dozens of genes in parallel in a mouse model of lung cancer and simultaneously assessed how each knockout influenced tumor growth, histopathology, and immune composition. Moreover, we paired Perturb-map and spatial transcriptomics for unbiased analysis of CRISPR-edited tumors. We found that in Tgfbr2 knockout tumors, the tumor microenvironment (TME) was converted to a fibro-mucinous state, and T cells excluded, concomitant with upregulated TGFβ and TGFβ-mediated fibroblast activation, indicating that TGFβ-receptor loss on cancer cells increased TGFβ bioavailability and its immunosuppressive effects on the TME. These studies establish Perturb-map for functional genomics within the tissue at single-cell resolution with spatial architecture preserved and provide insight into how TGFβ responsiveness of cancer cells can affect the TME.
Project description:The clinical successes of immune checkpoint therapies for cancer make it important to identify mechanisms of resistance to anti-tumor immune responses. Numerous resistance mechanisms have been identified employing studies of single genes or pathways, thereby parsing the tumor microenvironment complexity into tractable pieces. However, this limits the potential for novel gene discovery to in vivo immune attack. To address this challenge, we developed an unbiased in vivo genome-wide RNAi screening platform that leverages host immune selection in strains of immune-competent and immunodeficient mice to select for tumor cell-based genes that regulate in vivo sensitivity to immune attack. Utilizing this approach in a syngeneic triple-negative breast cancer (TNBC) model, we identified 709 genes that selectively regulated adaptive anti-tumor immunity and focused on five genes (CD47, TGFβ1, Sgpl1, Tex9 and Pex14) with the greatest impact. We validated the mechanisms that underlie the immune-related effects of expression of these genes in different TNBC lines, as well as tandem synergistic interactions. Furthermore, we demonstrate the impact of different genes with previously unknown immune functions (Tex9 and Pex14) on anti-tumor immunity. Thus, this innovative approach has utility in identifying unknown tumor-specific regulators of immune recognition in multiple settings to reveal novel targets for future immunotherapies.
Project description:A major challenge in inflammatory bowel disease (IBD) is the integration of diverse IBD data sets to construct predictive models of IBD. We present a predictive model of the immune component of IBD that informs causal relationships among loci previously linked to IBD through genome-wide association studies (GWAS) using functional and regulatory annotations that relate to the cells, tissues, and pathophysiology of IBD. Our model consists of individual networks constructed using molecular data generated from intestinal samples isolated from three populations of patients with IBD at different stages of disease. We performed key driver analysis to identify genes predicted to modulate network regulatory states associated with IBD, prioritizing and prospectively validating 12 of the top key drivers experimentally. This validated key driver set not only introduces new regulators of processes central to IBD but also provides the integrated circuits of genetic, molecular, and clinical traits that can be directly queried to interrogate and refine the regulatory framework defining IBD.
Project description:The expansion of cells for regenerative therapy will require the genetic dissection of complex regulatory mechanisms governing the proliferation of non-transformed human cells. Here, we report the development of a high-throughput RNAi screening strategy specifically for use in primary cells and demonstrate that silencing the cell cycle-dependent kinase inhibitors CDKN2C/p18 or CDKN1A/p21 facilitates cell cycle entry of quiescent adult human pancreatic beta cells. This work identifies p18 and p21 as novel targets for promoting proliferation of human beta cells and demonstrates the promise of functional genetic screens for dissecting therapeutically relevant state changes in primary human cells.
Project description:Replicative senescence is a fundamental tumor-suppressive mechanism triggered by telomere erosion that results in a permanent cell cycle arrest. To understand the impact of telomere shortening on gene expression, we analyzed the transcriptome of diploid human fibroblasts as they progressed toward and entered into senescence. We distinguished novel transcription regulation due to replicative senescence by comparing senescence-specific expression profiles to profiles from cells arrested by DNA damage or serum starvation. Only a small specific subset of genes was identified that was truly senescence-regulated and changes in gene expression were exacerbated from presenescent to senescent cells. The majority of gene expression regulation in replicative senescence was shown to occur due to telomere shortening, as exogenous telomerase activity reverted most of these changes.
Project description:As our ancestors migrated throughout different continents, natural selection increased the presence of alleles advantageous in the new environments. Heritable variations that alter the susceptibility to diseases vary with the historical period, the virulence of the infections, and their geographical spread. In this study we built polygenic scores for heritable traits that influence the genetic adaptation in the production of cytokines and immune-mediated disorders, including infectious, inflammatory, and autoimmune diseases, and applied them to the genomes of several ancient European populations. We observed that the advent of the Neolithic was a turning point for immune-mediated traits in Europeans, favoring those alleles linked with the development of tolerance against intracellular pathogens and promoting inflammatory responses against extracellular microbes. These evolutionary patterns are also associated with an increased presence of traits related to inflammatory and auto-immune diseases.
Project description:Although 15-20% of COVID-19 patients experience hyper-inflammation induced by massive cytokine production, cellular triggers of this process and strategies to target them remain poorly understood. Here, we show that the N-terminal domain (NTD) of the SARS-CoV-2 spike protein substantially induces multiple inflammatory molecules in myeloid cells and human PBMCs. Using a combination of phenotypic screening with machine learning-based modeling, we identified and experimentally validated several protein kinases, including JAK1, EPHA7, IRAK1, MAPK12, and MAP3K8, as essential downstream mediators of NTD-induced cytokine production, implicating the role of multiple signaling pathways in cytokine release. Further, we found several FDA-approved drugs, including ponatinib, and cobimetinib as potent inhibitors of the NTD-mediated cytokine release. Treatment with ponatinib outperforms other drugs, including dexamethasone and baricitinib, inhibiting all cytokines in response to the NTD from SARS-CoV-2 and emerging variants. Finally, ponatinib treatment inhibits lipopolysaccharide-mediated cytokine release in myeloid cells in vitro and lung inflammation mouse model. Together, we propose that agents targeting multiple kinases required for SARS-CoV-2-mediated cytokine release, such as ponatinib, may represent an attractive therapeutic option for treating moderate to severe COVID-19.
Project description:Alzheimer's disease (AD) is a devastating neurological disorder characterized by changes in cell-type proportions and consequently marked alterations of the transcriptome. Here we use a data-driven systems biology meta-analytical approach across three human AD cohorts, encompassing six cortical brain regions, and integrate with multi-scale datasets comprising of DNA methylation, histone acetylation, transcriptome- and genome-wide association studies and quantitative trait loci to further characterize the genetic architecture of AD. We perform co-expression network analysis across more than 1200 human brain samples, identifying robust AD-associated dysregulation of the transcriptome, unaltered in normal human aging. We assess the cell-type specificity of AD gene co-expression changes and estimate cell-type proportion changes in human AD by integrating co-expression modules with single-cell transcriptome data generated from 27 321 nuclei from human postmortem prefrontal cortical tissue. We also show that genetic variants of AD are enriched in a microglial AD-associated module and identify key transcription factors regulating co-expressed modules. Additionally, we validate our results in multiple published human AD gene expression datasets, which can be easily accessed using our online resource (https://swaruplab.bio.uci.edu/consensusAD).