Biology subjects

Jaiswal, S.

Publications and source records attributed to Jaiswal, S..

18 recordsLinked to original sources

bioRxiv2026

Choline Kinase Alpha Inhibition is a Mutation Agnostic Therapeutic Vulnerability in Clonal Hematopoiesis

Clonal Hematopoiesis (CH) affects the aging population and is associated with increased risk of hematological malignancy, cardiovascular disease, and all-cause mortality. Therapeutic options for CH remain limited. Using hematopoietic stem and progenitor cell (HSPC) color barcoding and mosaic mutagenesis in zebrafish, we identified perturbed choline metabolism and increased phosphatidylcholine (PC) biosynthesis via choline kinase alpha (CHKA) in asxl1-mutant HSPCs. Suppressing CHKA-dependent choline flux reduced ASXL1-driven clonal expansion. This effect was conserved in a murine DNMT3A and human TET2 model. Mechanistically, CHKA- dependent choline flux controls phosphatidylcholine production that supports platelet activating factor (PAF) production. Exogenous PAF overcomes the suppressive effect of CHKA inhibition in ASXL1 and TET2 models. We isolated primary, human HSPCs from the peripheral blood of patients with endogenous ASXL1 mutations and demonstrated that perturbing PAF signaling reduces their competitive potential in an ex vivo clonal competition assay. This CHKA/PAF axis is conserved in TET2-mutant HSPCs. Together, these findings identify a mutation agnostic metabolic dependency across the three most common CH genotypes and demonstrate that targeting the CHKA-dependent choline flux suppresses clonal expansion.

cancer biology↗

bioRxiv2026

Sugarcane bZIP16 regulates internode elongation by targeting gibberellic acid biosynthesis pathway

Modern sugarcane cultivars are vegetatively propagated interspecific hybrids developed by extensive breeding and selection method to enhance sugar content, culm dimensions, desired plant architecture and disease resistance. Internode length greatly varies among existing sugarcane cultivars which determines culm length, biomass and sugar storage. Molecular factors responsible for this trait remains largely unknown in sugarcane. In this study, we characterized short and long internode sugarcane varieties and elucidated gene regulatory module interplaying with hormonal-network underneath the internodal growth. The genome size, pigment content and juice characteristics of short and long internode varieties differed with each other and correlated with gene expressions pattern. We established tissue and spatial transcriptome dataset, and comparative analyses demonstrated number of genes involved in cell cycle, cell expansion, transcription factors and hormone pathway including bZIP16 are differentially expressed between short and long internode varieties. Biochemical, DNA-protein interactions and molecular evidences revealed that ScbZIP16 inversely related to GA content by repressing transcripts of ent-isokaurene C2/C3-hydroxylase and GA20 Oxidase in sugarcane. The further genetic evidences confirmed role of ScbZIP16 in reducing GA biosynthesis pathway, flowering time and growth in Arabidopsis. This report of ScbZIP16 regulatory module offers a potential candidate for sugarcane improvement programs.

plant biology↗

bioRxiv2026

A Versatile Microfluidic Device for High-throughput Combinatorial Drug Screening

Combination therapies can improve anticancer efficacy, but identifying effective drug pairs and dose combinations requires systematic exploration of multidimensional concentration spaces. Here, we extend a diffusion-driven, flowless microfluidic concentration gradient generator (CGG) to enable quantitative combinatorial drug screening without external pumps or continuous flow. The platform comprises a 5 x 5 array of interconnected culture nodes coupled to four peripheral reservoirs, in which overlapping diffusion fields generate spatially defined single- and multidrug exposures. Computational modelling was used to assign local drug concentrations to individual nodes, enabling direct correlation of the predicted exposure landscape with cellular response. Using MCF-7 breast cancer cells and 5-fluorouracil (5-FU) and doxorubicin (DOX) as model therapeutics, the platform resolved concentration-dependent single-agent responses, yielding IC50 values of 3.46 M for 5-FU and 1.22 M for DOX. Combinatorial loading generated 25 spatially defined 5-FU-DOX concentration pairs within a single device, which were resolved into two-dimensional concentration-response landscapes. Bliss independence analysis revealed concentration-specific drug interactions, with synergy predominating at low-to-intermediate concentrations and a transition towards additive and antagonistic responses at higher exposures. These findings establish a pump-free microfluidic strategy that integrates computational concentration mapping with spatially resolved pharmacological analysis to identify effective drug-combination windows within a single platform.

cancer biology↗

bioRxiv2026

Isolation of postnatal human neural stem cells

While it was once thought that neurogenesis is complete by birth, it is now apparent that the human brain continues to generate new neurons postnatally, at least into childhood. While much attention has been focused on postnatally-born neurons, their presumed progenitor - the postnatal neural stem cell (NSC) - remains poorly characterized. Using index sorting, we identify and prospectively isolate two subsets of NSCs from the postnatal human brain, and describe their differentiation dynamics using clonal barcoding and in vivo xenotransplantation. We demonstrate an A2B5+EGFR+ population biased towards interneuron and oligodendrocyte fates (NINO), and an A2B5-EGFRhi population biased towards an astrocyte fate (NAC). Profiling of human brains across lifespan shows that the frequency of NSCs declined exponentially across the first two decades of life, but stabilized thereafter, still present in the brains of donors as old as 90 years. Our study provides a framework for the functional study of postnatal human NSCs and their potential roles in development, aging, and disease.

neuroscience↗

bioRxiv2026

Integrative genomics reveals shared and stress-specific adaptive pathways underlying acidic soil-associated metal toxicity in rice

Soil acidity-associated toxicities of aluminum (Al), cadmium (Cd), and manganese (Mn) severely constrain rice productivity in upland ecosystems. To investigate the genomic basis of adaptation to acidic soil-related metal stress, we conducted an integrated meta-QTL (M-QTL) and functional genomics analysis in rice. Meta-analysis of 681 QTLs and MTAs from 53 QTL mapping and GWAS studies identified 79 robust M-QTLs, including ten overlapping regions associated with Al-, Cd-, and Mn-responsive traits. A multi-criteria prioritization framework identified 98 candidate genes supported by positional overlap, transcriptomic recurrence, and functional annotation, enriched for ion transport, detoxification, and redox regulation pathways. M-QTL10.9 emerged as a major hotspot enriched for glutathione-S-transferase genes, whereas M-QTL9.5 contained the highest density of prioritized candidates linked to Al and Cd responses. Comparative physiological & biochemical analyses of the contrasting rice genotypes Sahasarang and IR64 revealed genotype-dependent differences in antioxidant responses, metal partitioning, metabolic regulation, and cell wall remodeling under individual and combined metal stresses. Expression profiling of prioritized candidate genes, including OsACO family genes, OsZIP10, and OsGSTU10, further revealed genotype-dependent transcriptional divergence under combined stress. The identification of overlapping M-QTLs across Al, Cd, and Mn datasets suggests both shared and stress-specific adaptive responses to acidic soil-associated metal stress in rice.

genomics↗

bioRxiv2026

Somatic mutations reveal the ontogeny of human microglia

Microglia are the resident hematopoietic cells of the central nervous system1. In mice, microglia seed the brain during embryogenesis and can be maintained throughout life with minimal input from adult hematopoiesis2-4. The origins of human microglia are less clear, but recent evidence suggests that marrow-derived cells may be able to supplement the human microglial pool in certain individuals5,6. Here, to investigate the ontogeny of human microglia, we develop a method that uses the collection of accumulated somatic mutations which uniquely labels each clone of cells to track the infiltration of marrow-derived cells into the human brain. Applying this method to 20 aged individuals, we find evidence of an influx of marrow-derived cells into the brain in all examined individuals. Single cell analysis, including single cell lineage tracing using mitochondrial DNA variants, demonstrates that these infiltrating cells are nearly identical to microglia and can comprise a large fraction of the microglial pool. Analysis of large-scale sequencing cohorts demonstrates a protective association between most types of clonal hematopoiesis and Alzheimers disease. In sum, this work uncovers a widespread influx of myeloid cells into the healthy human brain which serves to reinforce the pool of human microglia and becomes common with aging.

immunology↗

bioRxiv2026

TB-Bench: A Systematic Benchmark of Machine Learning and Deep Learning Methods for Second-Line TB Drug Resistance Prediction

Drug-resistant tuberculosis (TB), characterized by prolonged treatment regimens and suboptimal treatment outcomes, remains a major obstacle to global TB elimination. Advances in sequencing technologies have enabled the development of machine-learning (ML) approaches, including deep-learning (DL) methods, to predict drug resistance directly from genomic data. However, a significant gap remains in translating these advances into clinical practice. While current approaches reliably predict resistance to first-line drugs, they show consistently lower and more variable performance for second-line drugs compared with traditional drug-susceptibility testing. To characterize these limitations and assess practical utility, we conducted a comprehensive survey and standardized benchmarking of current approaches for predicting TB drug resistance using whole-genome sequencing (WGS) data. Using systematic selection criteria, we identified 20 traditional ML and DL models from 8 studies and evaluated drug-specific versions across 14 second-line drugs within a unified framework. To account for methodological heterogeneity, the models were evaluated using three distinct feature sets reflecting variability in input representations. We trained and evaluated the models on different subsets of the WHO dataset, comprising 50,801 samples, and assessed generalizability using an external validation dataset comprising 1,199 samples. In the internal evaluation on the held-out WHO test dataset, traditional ML models using binary features achieved higher predictive performance than DL models. For example, XGBoost achieved the highest area under the precision-recall curve (PRAUC) scores (46%-93%) for 10 of the 14 drugs. However, performance varied substantially across drugs. Notably, the superior performance of traditional ML models -- even with limited feature sets -- highlights their applicability in low-resource settings. When evaluated on the external validation dataset, the performance of traditional ML and DL models was comparable, and neither class of models demonstrated substantial improvement over catalogue-based approaches, underscoring challenges in cross-dataset generalization. Overall, this benchmarking study provides a comprehensive and systematic evaluation of current approaches, establishes a rigorous evaluation framework for future comparisons, and identifies key methodological considerations necessary to advance robust drug resistance prediction in clinical settings. To enhance reproducibility and facilitate the application of TB-Bench to additional datasets and models, we have made the source code publicly available at https://github.com/BIRDSgroup/TB-Bench.

bioinformatics↗

bioRxiv2025

High-Fidelity Simulation of Cell Adhesion and Flow with Coarse Grain Modelling: A Numerical and Experimental Approach

A coupled CFD-DEM framework was developed to investigate red blood cell (RBC) transport and cellular adhesion in constricted microchannels, with a primary objective of reducing computational cost while preserving physiological accuracy. Initially, numerical softening factors were implemented, allowing greater overlap between particles to expedite computations, with an optimal value of 0.03 selected. Adhesion forces between RBCs and the channel wall were incorporated, with a minimum effective distance of 0.4{square}{micro}m identified as computationally feasible. However, RBC-RBC adhesion led to artificial clustering and was therefore omitted. Coarse-graining methods were applied up to a factor of 2 to further reduce simulation time, with a value of 1.8 chosen based on consistent cell-free layer (CFL) thickness and drag force characteristics. To correct for the increased drag in coarse-grained models, rolling resistance (Type C) with a coefficient of 0.8 was employed, bringing deviations within 10%. The validated model was then extended to simulate the detachment of adherent C2C12 myoblasts under physiological flow. Experimental validation showed increasing cell retention with seeding time, and simulations reproduced this trend with <5% deviation. The resulting Detachment Force Ratio (DFR) at 6 hours indicates near-equivalence between adhesion and hydrodynamic forces, establishing the models robustness for cell-substrate interaction studies in microfluidics.

cell biology↗

bioRxiv2025

EnrichMET: R Package for Integrated Pathway and Network Analysis for Metabolomics

Advances in metabolomics have significantly improved our understanding of cellular processes by enabling the identification of hundreds of metabolites in a single experiment. These developments provide valuable insights into complex metabolic networks. While efforts have been made to develop pathway enrichment analysis (PEA), existing implementation often require multiple steps, rely on web-based interfaces, or depend on R packages configuration that may affect reproducibility and ease of use. To overcome these limitations, we introduce EnrichMet, an R package for fast, flexible, and reproducible pathway enrichment analysis. EnrichMet modules support over-representation analysis of pathways, metabolite set enrichment analysis (MetSEA), and network-based pathway analysis. The package streamlines the workflow by combining curated pathway information from the Kyoto Encyclopedia of Genes and Genomics (KEGG) and employs Fishers Exact Test to identify significantly enriched pathways. Benchmark analyses show that enrichment on sample data completes in approximately 3 seconds. EnrichMet offers both a command-line and a user-friendly Shiny interface, enabling accessibility for users with or without programming experience. Through case studies on experimental metabolomics datasets, we demonstrated that EnrichMet delivers accurate and comprehensive pathway enrichment results while minimizing computational time and simplifying user interaction. Furthermore, its flexible framework supports extensions to other data types and knowledge bases beyond KEGG, as illustrated through a lipidomics case study. By unifying performance, reproducibility, usability, and visualization within a single package, EnrichMet facilitates deeper insights and promotes efficient, transparent, and reproducible research practices. Availability and implementation(https://github.com/biodatalab/enrichmet.git)

bioinformatics↗

bioRxiv2024

Metabolomic profiling reveals grade-specific niacinamide accumulation and its therapeutic Potential via SIRT1-CD38-EMT axis modulation in cervical cancer progression

Despite the availability of new therapies for cervical cancer, innovative strategies are essential to address challenges related to drug resistance and high toxicity. The present study focuses on the metabolic profiling of cervical carcinoma using non-targeted metabolomics approach using liquid chromatography-mass spectrometry. Our study identified over 100 metabolites in cervical tissue samples (both cancerous and adjacent normal) using HILIC and reversed-phase chromatography in the positive and negative ionization modes. The major metabolic alterations included changes in glycolysis, the citric acid cycle, amino acid metabolism, nucleotide metabolism, and nicotinamide metabolism in a grade-dependent manner. Interestingly, metabolic differences between HPV-positive and HPV-negative tumors included elevated arginine and proline metabolism, nicotinamide metabolism, and phosphatidylcholine biosynthesis. We further validated our findings by analyzing transcriptomics datasets from the Gene Expression Omnibus database to understand the expression patterns of the underlying genes involved in the dysregulated pathways. We observed that nicotinamide metabolism exhibits significant effects in lower-grade cervical cancers and specific HPV genotypes. We treated cervical cancer cell lines with niacinamide (NAM), an amide form of niacin, to evaluate its potential therapeutic efficacy. NAM treatment modulated NAD+ metabolism with key players such as CD38, PARP, NAMPT, and SIRT1, promoting apoptosis and inhibiting cell proliferation in cervical cancer cells. Importantly, the metabolic responses differed between the HPV-positive SiHa cells and HPV-negative C33A cells, reflecting distinct NAD+ metabolic adaptations. The study highlights the metabolic adaptation or shifts in cancer progression and provides insights into NAMs molecular mechanisms and therapeutic potential for precision medicine in cervical cancer.

cancer biology↗

bioRxiv2023

Unravelling Silicon's Transcriptomic Armor in Soybean against Macrophomina phaseolina causing Charcoal Rot Disease

The Glycine max L. has been affected by more than 100 diseases, including Macrophomina phaseolina producing charcoal rot disease, which reduces production by 70%. In this investigation, RNA-Seq analysis is used for the first time to explore role of silicon in preventing soybean charcoal rot. The study explores the molecular mechanism underlying soybeans resilience to charcoal rot when treated with potassium silicon. It was meticulously investigated how Macrophomina phaseolina entered the roots. The SEM, which showed a strong link between potassium silicate accumulation and disease resistance. Further investigation indicates that a potassium silicate concentration of 1.7mM lowers disease incidence. Using Illumina HiSeq NGS data, we present a transcriptome analysis revealing genes associated with charcoal rot resistance, highlighting 3,106 genes with distinct expression patterns. The strong enrichment of pathways including "Biosynthesis of ansamycins" and "Flavone and flavonol biosynthesis," which contribute to resistance against charcoal rot, is highlighted by KEGG enrichment analysis. The ERF transcription factor and NB leucine-rich repeats stands out among the differentially expressed genes as being particularly connected to resistance. The crucial functions that many other important transcription factors, including as MYB, NAC, and proteins from the FAR1 family, play in enhancing soybeans resistance to charcoal rot are also noted. This newly discovered information could help in developing tactics to strengthen soybeans resistance to Macrophomina phaseolina.

microbiology↗

bioRxiv2023

A brief report on the of mycobacterial proteins regulated by the loss of PtkA in Mtb-H37Ra

Kinase-phosphatase signaling plays an important role in cellular signaling pathways. The genome of Mycobacterium tuberculosis, (the causative agent of tuberculosis), is embossed with several kinases and phosphatases. Recently identified protein tyrosine kinase (PtkA) is a novel tyrosine kinase that phosphorylates protein tyrosine phosphatase A (PtpA) and regulates its secretion in the cytosol. PtkA is considered as a regulatory protein. In this study, the mycobacterial proteins regulated due to the ptkA gene deletion in Mtb-H37Ra have been studied and highlighted using two-dimensional (2D) gel electrophoresis coupled with MALDI TOF MS/MS analysis. We have identified 13 differentially expressed proteins that play an important role in mycobacterial intracellular survival and pathogenesis.

microbiology↗

bioRxiv2023

Human Plasma Proteomic Profile of Clonal Hematopoiesis

Plasma proteomic profiles associated with subclinical somatic mutations in blood cells may offer novel insights into downstream clinical consequences. Here, we explore such patterns in clonal hematopoiesis of indeterminate potential (CHIP), which is linked to several cancer and non-cancer outcomes, including coronary artery disease (CAD). Among 61,833 ancestrally diverse participants (3,881 with CHIP) from NHLBI TOPMed and UK Biobank with blood-based DNA sequencing and proteomic measurements (1,148 proteins by SomaScan in TOPMed and 2,917 proteins by Olink in UK Biobank), we identified 32 and 345 unique proteins from TOPMed and UK Biobank, respectively, associated with the most prevalent driver genes (DNMT3A, TET2, and ASXL1). These associations showed substantial heterogeneity by driver genes, sex, and race, and were enriched for immune response and inflammation pathways. Mendelian randomization in humans, coupled with ELISA in hematopoietic Tet2-/- vs wild-type mice validation, disentangled causal proteomic perturbations from TET2 CHIP. Lastly, we identified plasma proteins shared between CHIP and CAD.

genetics↗

bioRxiv2023

AMLs harboring DNMT3A-destabilizing variants show increased intratumor DNA methylation heterogeneity at bivalent chromatin domains

The mechanistic link between the complex mutational landscape of de novo methyltransferase DNMT3A and the pathology of acute myeloid leukemia (AML) has not been clearly elucidated so far. A recent discovery on the catalogue of DNMT3A-destabilizing mutations throughout the DNMT3A gene as well as the oligomerization-dependent catalytic property of DNMT3A prompted us to investigate the common effect of DNMT3A-destabilizing mutations (DNMT3AINS) on the genomewide methylation patterns of AML cells. In this study, we describe the characteristics of DNMT3AINS AML methylomes through the comprehensive computational analyses on three independent AML cohorts. As a result, we show that methylomes of DNMT3AINS AMLs are considerably different from those of DNMT3AR882 AMLs in that they exhibit both locally disordered DNA methylation states and increased across-cell DNA methylation heterogeneity in bivalent chromatin domains. This increased epigenetic heterogeneity was functionally associated with heterogeneous expression of membrane-associated factors shaping stem cell niche, implying the diversification of the modes of leukemic stem cell-niche interactions. We also present that the level of methylation disorder at bivalent domains predicts the response of AML cells to hypomethylating agents through cell line- and patient-level analyses, which supports that the survival of AML cells depends on stochastic DNA methylations at bivalent domains. Altogether, our work provides a novel mechanistic model suggesting the genomic origin of the aberrant epigenomic heterogeneity in disease conditions.

cancer biology↗

bioRxiv2023

Separation of function mutations in microcephaly protein CPAP/CENPJ, reveal its role in regulating centriole number and length.

Centriole are microtubule-based cylindrical structures characterized by their definite size, and stable, slow growing microtubules. The centriole core protein CPAP/CENPJ is known to act as a molecular cap regulating centriole length by interacting with microtubule/tubulin via the conserved microtubule destabilizing, PN2-3, and microtubule stabilizing, A5N, domains. The C-terminus of CPAP has a conserved glycine-rich G-box/TCP domain (1050-1338 amino acids). This region is involved in centriole cartwheel assembly by interacting with the cartwheel protein STIL. However, previously reported primary microcephaly mutation mapped in the G-box of CPAP, i.e., E1235V (MCPH6) affects centriole length via an unknown mechanism. Recently, another primary microcephaly mutation has been mapped to this region of CPAP, i.e., D1196N. However, the effect of D1196N on CPAP functioning is not known. We simultaneously characterized these two MCPH mutations in the G-box of CPAP. We identified that despite affecting the same domain of CPAP, they affect distinct CPAP functions at the centriole. The E1235V mutation caused an overly long centriole, and the D1196N mutation increased the centriole number. Interestingly, both these mutations affect CPAP direct interaction with the cartwheel protein STIL, which is involved in CPAP recruitment to the centriole. Accordingly, the CPAP E1235V centriole localization is significantly affected at the centriole. However, CPAP D1196N can still localize to centriole at levels comparable to the wild-type CPAP. We show that CPAP utilizes an alternate CEP152-dependent route for centriole recruitment. Importantly, our work highlights the importance of the CPAP region outside direct microtubule/tubulin interacting domains in influencing CPAP activity in cartwheel assembly and centriole length. Perhaps, this is why deleterious naturally occurring missense mutations are frequently occurring in this particular region of CPAP in primary microcephaly.

cell biology↗

bioRxiv2022

Identification and characterization of the T cell receptor (TCR) repertoire of the Cynomolgus macaque (Macaca Fascicularis)

BackgroundNon-human primates (NHP) are desirable as animal models of human disease because they share behavioral, physiological, and genomic traits with people. Hence, NHP recapitulate manifestations of disease not observed in other animal species. The Macaca fascicularis (i.e., Cynomolgus macaque) is an NHP species extensively used for biomedical research, but the TCR repertoire hasnt been characterized yet. ResultWe used the genomic sequences to design primers to identify the expressed TCR repertoire by single cell RNAseq. The data analysis from 22 unique samples were used to assign a functional status to each TCR genes. We identified and analyzed the TRA/D, TRB and TRG loci of the Cynomolgus macaque. ConclusionThe genomic organization of the Cynomolgus macaque has great similarity with Macaca mulatta (i.e., Rhesus macaque) and they shared >90% sequence similarity with the human TCR repertoire. These data will facilitate the analysis of T cell immunity in Cynomolgus macaques.

immunology↗

bioRxiv2019

Genetic dysregulation of gene expression and splicing during a ten-year period of human aging

Molecular and cellular changes are intrinsic to aging and age-related diseases. Prior cross-sectional studies have investigated the combined effects of age and genetics on gene expression and alternative splicing; however, there has been no long-term, longitudinal characterization of these molecular changes, especially in older age. We performed RNA sequencing in whole-blood from the same individuals from the PIVUS study at ages 70 and 80 to quantify how gene expression, alternative splicing, and their genetic regulation are altered during this 10-year period of advanced aging. We observe that individuals are more similar to their own expression profiles later in life than profiles of other individuals their own age; 93% of samples cluster with their own measurement at another age, and there is a strong correlation of genetic effects on expression between the two ages (median{rho} G = 0.96). Despite this, we identify 1,291 and 294 genes differentially expressed and alternatively spliced with age, as well as 529 genes with outlying individual trajectories of aging. Further, 7.8% and 9.6% of tested genes show a reduction in genetic associations with expression and alternative splicing in older age, with impacted genes enriched in DNA repair pathways. Together these findings indicate that, although gene expression and alternative splicing and their genetic regulation are mostly stable late in life, a small subset of genes is dynamic and is characterized by changes in expression and splicing and a reduction in genetic regulation.

genomics↗

bioRxiv2017

HIV-1 unmasks the plasticity of innate lymphoid cells

HIV-1-infected people who take medications that suppress viremia, preserve CD4+ T cells, and prevent AIDS, have chronic inflammation with increased cardiovascular mortality. To investigate the etiology of this inflammation, the effect of HIV-1 on innate lymphoid cells (ILCs) and NK cells was examined. Homeostatic ILCs in blood and intestine were depleted permanently. NK cells were skewed towards a memory subset. Cytokines that are elevated during HIV-1 infection reproduced both abnormalities ex vivo. Pseudotime analysis of single NK cell transcriptomes revealed a developmental trajectory towards a subset with expression profile, chromatin state, and biological function like memory T lymphocytes. Expression of TCF7, a WNT transcription factor, increased over the course of the trajectory. TCF7 disruption, or WNT inhibition, prevented memory NK cell induction by inflammatory cytokines. These results demonstrate that inflammatory cytokines associated with HIV-1 infection irreversibly disrupt homeostatic ILCs and cause developmental shift towards TCF7+ memory NK cells.\n\nHighlightsO_LIHIV-1 infection depletes homeostatic ILCs in blood and intestine and shifts NK cells towards a memory cell phenotype, irrespective of viremia or CD4 count\nC_LIO_LIInflammatory cytokines recapitulate ILC and NK cell abnormalities ex vivo\nC_LIO_LITCF7 expression correlates with a developmental trajectory that culminates in memory NK cells\nC_LIO_LITCF7/WNT signaling is required for establishment of memory NK cells\nC_LI\n\n\n\nO_FIG O_LINKSMALLFIG WIDTH=172 HEIGHT=200 SRC=\"FIGDIR/small/221010v3_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (32K):\norg.highwire.dtl.DTLVardef@ae82a7org.highwire.dtl.DTLVardef@103b2b4org.highwire.dtl.DTLVardef@1c9585aorg.highwire.dtl.DTLVardef@1c7bb2d_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical AbstractC_FLOATNO C_FIG

immunology↗