Multi-organ single-cell transcriptomics of immune cells uncovered organ-specific gene expression and functions.

Despite the wealth of publicly available single-cell datasets, our understanding of distinct resident immune cells and their unique features in diverse human organs remains limited. To address this, we compiled a meta-analysis dataset of 114,275 CD45+ immune cells sourced from 14 organs in healthy donors. While the transcriptome of immune cells remains relatively consistent across organs, our analysis has unveiled organ-specific gene expression differences (GTPX3 in kidney, DNTT and ACVR2B in thymus). These alterations are linked to different transcriptional factor activities and pathways including metabolism. TNF-α signaling through the NFkB pathway was found in several organs and immune compartments. The presence of distinct expression profiles for NFkB family genes and their target genes, including cytokines, underscores their pivotal role in cell positioning. Taken together, immune cells serve a dual role: safeguarding the organs and dynamically adjusting to the intricacies of the host organ environment, thereby actively contributing to its functionality and overall homeostasis.

Singleton mutations in large-scale cancer genome studies: uncovering the tail of cancer genome.

Singleton or low-frequency driver mutations are challenging to identify. We present a domain driver mutation estimator (DOME) to identify rare candidate driver mutations. DOME analyzes positions analogous to known statistical hotspots and resistant mutations in combination with their functional and biochemical residue context as determined by protein structures and somatic mutation propensity within conserved PFAM domains, integrating the CADD scoring scheme. Benchmarked against seven other tools, DOME exhibited superior or comparable accuracy compared to all evaluated tools in the prediction of functional cancer drivers, with the exception of one tool. DOME identified a unique set of 32 917 high-confidence predicted driver mutations from the analysis of whole proteome missense variants within domain boundaries across 1331 genes, including 1192 noncancer gene census genes, emphasizing its unique place in cancer genome analysis. Additionally, analysis of 8799 TCGA (The Cancer Genome Atlas) and in-house tumor samples revealed 847 potential driver mutations, with mutations in tyrosine kinase members forming the dominant burden, underscoring its higher significance in cancer. Overall, DOME complements current approaches for identifying novel, low-frequency drivers and resistant mutations in personalized therapy.

An atlas of cells in the human tonsil.

Palatine tonsils are secondary lymphoid organs (SLOs) representing the first line of immunological defense against inhaled or ingested pathogens. We generated an atlas of the human tonsil composed of >556,000 cells profiled across five different data modalities, including single-cell transcriptome, epigenome, proteome, and immune repertoire sequencing, as well as spatial transcriptomics. This census identified 121 cell types and states, defined developmental trajectories, and enabled an understanding of the functional units of the tonsil. Exemplarily, we stratified myeloid slan-like subtypes, established a BCL6 enhancer as locally active in follicle-associated T and B cells, and identified SIX5 as putative transcriptional regulator of plasma cell maturation. Analyses of a validation cohort confirmed the presence, annotation, and markers of tonsillar cell types and provided evidence of age-related compositional shifts. We demonstrate the value of this resource by annotating cells from B cell-derived mantle cell lymphomas, linking transcriptional heterogeneity to normal B cell differentiation states of the human tonsil.

Novel covalent CDK7 inhibitor potently induces apoptosis in acute myeloid leukemia and synergizes with Venetoclax.

INTRODUCTION: The emergence of resistance to the highly successful BCL2-directed therapy is a major unmet need in acute myeloid leukemia (AML), an aggressive malignancy with poor survival rates. Towards identifying therapeutic options for AML patients who progress on BCL2-directed therapy, we studied a clinical-stage CDK7 inhibitor XL102, which is being evaluated in solid tumors (NCT04726332). MATERIALS AND METHODS: To determine the anti-proliferative effects of XL102, we performed experiments including time-resolved fluorescence resonance energy transfer, target occupancy, cell cycle and apoptosis-based assays. We also included genetically characterized primary myeloid blasts from de novo and relapsed/refractory AML patients. For mechanistic studies, CRISPR/Cas9 mediated knockout of CDK7 and c-Myc and immunoblotting were performed. NOD/SCID orthotropic and subcutaneous AML xenografts were used to determine anti-leukemic effects. To assess the synergistic effects of XL102 with Venetoclax, we performed RNA sequencing and gene set enrichment analysis using Venetoclax sensitive and resistant model systems. RESULTS: XL102, a highly specific, orally bioavailable covalent inhibitor of CDK7. Inhibitory effect on CDK7 by XL102 in primary myeloid blasts (n = 54) was in nanomolar range (mean = 300 nM; range = 4.0-952 nM). XL102 treated AML cells showed a reduction in phosphorylation levels of Serine 2/5/7 at carboxy-terminal domain of RNA polymerase II. T-loop phosphorylation of CDK1(Thr161) and CDK2(Thr160) was inhibited by XL102 in dose-dependent manner leading to cell-cycle arrest. c-Myc downregulation and enhanced levels of p53 and p21 in XL102 treated cells were observed. Increased levels of p21 and activation of p53 by XL102 were mimicked by genetic ablation of CDK7, which supports that the observed effects of XL102 are due to CDK7 inhibition. XL102 treated AML xenografts showed remarkable reduction in hCD45 + marrow cells (mean = 0.60%; range = 0.04%-3.53%) compared to vehicle control (mean = 38.2%; range = 10.1%-78%), with corresponding increase in p53, p21 and decrease in c-Myc levels. The data suggests XL102 induces apoptosis in AML cells via CDK7/c-Myc/p53 axis. RNA-sequencing from paired Venetoclax-sensitive and Venetoclax-resistant cells treated with XL102 showed downregulation of genes involved in proliferation and apoptosis. CONCLUSION: Taken together, XL102 with Venetoclax led to synergistic effects in overcoming resistance and provided a strong rationale for clinical evaluation of XL102 as a single agent and in combination with Venetoclax.

An integrated approach to determine the abundance, mutation rate and phylogeny of the SARS-CoV-2 genome.

The analysis of the SARS-CoV-2 genome datasets has significantly advanced our understanding of the biology and genomic adaptability of the virus. However, the plurality of advanced sequencing datasets-such as short and long reads-presents a formidable computational challenge to uniformly perform quantitative, variant or phylogenetic analysis, thus limiting its application in public health laboratories engaged in studying epidemic outbreaks. We present a computational tool, Infectious Pathogen Detector (IPD), to perform integrated analysis of diverse genomic datasets, with a customized analytical module for the SARS-CoV-2 virus. The IPD pipeline quantitates individual occurrences of 1060 pathogens and performs mutation and phylogenetic analysis from heterogeneous sequencing datasets. Using IPD, we demonstrate a varying burden (5.055-999655.7 fragments per million) of SARS-CoV-2 transcripts across 1500 short- and long-read sequencing SARS-CoV-2 datasets and identify 4634 SARS-CoV-2 variants (~3.05 variants per sample), including 449 novel variants, across the genome with distinct hotspot mutations in the ORF1ab and S genes along with their phylogenetic relationships establishing the utility of IPD in tracing the genome isolates from the genomic data (as accessed on 11 June 2020). The IPD predicts the occurrence and dynamics of variability among infectious pathogens-with a potential for direct utility in the COVID-19 pandemic and beyond to help automate the sequencing-based pathogen analysis and in responding to public health threats, efficaciously. A graphical user interface (GUI)-enabled desktop application is freely available for download for the academic users at http://www.actrec.gov.in/pi-webpages/AmitDutt/IPD/IPD.html and for web-based processing at http://ipd.actrec.gov.in/ipdweb/ to generate an automated report without any prior computational know-how.