Biology subjects

Kapur, R.

Publications and source records attributed to Kapur, R..

7 recordsLinked to original sources

bioRxiv2026

Characterization of Resolved, Localized, and Progressing Infections at the Maternal-Fetal Interface in a Nonhuman Primate Model

Background: Inflammation and infection are responsible for the majority of early preterm births. Host innate immune responses at the maternal-fetal interface that contribute to sterile intra-amniotic inflammation (SIAI), bacterial clearance, or invasive infection remain poorly understood. Group B Streptococcus (Streptococcus agalactiae) is a leading cause of preterm birth, stillbirth, and invasive neonatal disease. Objective: To determine the host innate immune factors and transcriptional profiles that characterize the persistence versus resolution of a Group B Streptococcus infection at the maternal-fetal interface in a nonhuman primate (pigtail macaque, Macaca nemestrina) model. We hypothesized that a highly inflammatory profile, associated with interleukin-1 signaling, is linked to progression, whereas a mild or non-inflammatory signature is associated with infection resolution. Study Design: In a chronically catheterized pregnant pigtail macaque model, Group B Streptococcus was inoculated into the choriodecidual space. Infections were classified as progressing (invasive into the amniotic fluid), localized (bacteria persisting at the inoculation site), or resolved (minimal to no bacteria detected). Temporal and spatial RNA and protein profiles in the chorioamniotic membranes and decidua and in the myometrium were assessed by histopathology, multiplex protein assays, total RNA-sequencing, Nanostring nCounter, and spatial transcriptomics (digital spatial profiling). Differential gene expression was analyzed with limma using moderated t-tests and by gene set enrichment analysis. Results: A GBS infection at the maternal-fetal interface produced three infection outcomes: progressing infections that disseminated into the amniotic fluid (AF, N=5), low-titer localized infections remaining at the inoculation site (N=6), and resolved infections (N=5), compared with saline controls (N=3). Preterm labor occurred frequently regardless of infection outcome (40-80%). In resolved infections, SIAI occurred in the AF and lymphocytes infiltrated the myometrium. Total RNA-Seq of the chorioamniotic membranes demonstrated that 99 genes separated progressing from resolved infections, 98 of them were upregulated and dominated by IL-1 signaling and granulocyte recruitment (i.e., IL1B, CXCL8, TLR2, CLEC4A). Histone deacetylase 10 (HDAC10) was the only significantly downregulated gene in the progressing versus resolved contrast (p<0.05). An exploratory spatial transcriptomics experiment localized the progressing inflammatory response to the chorion. In the myometrium, zinc and RING finger 3 (ZNRF3) was significantly downregulated in localized versus control and resolved versus control and was also the only differentially expressed gene. Downregulated WNT signaling and upregulated lymphocyte-mediated immunity gene sets in the myometrium were a signature of resolved infections. Conclusion: A GBS infection at the maternal-fetal interface can result in a spectrum of progressing, localized and resolved outcomes. An early IL-1 and granulocyte response in the chorion layer of the chorioamniotic membranes marks bacterial dissemination, with loss of HDAC10 suggesting epigenetic regulation within the membranes with progressing infections. In the myometrium, ZNRF3 and downregulation of WNT signaling persisted even after infection resolution, reflecting an infectious exposure. Unexpectedly, resolved infections were associated with SIAI and a myometrial inflammatory response, offering a possible explanation for preterm labor associated with SIAI.

systems biology↗

bioRxiv2026

Patient-derived monoclonal anti-HPA-1a can induce platelet activation through FcγRIIa

Fetal and neonatal alloimmune thrombocytopenia (FNAIT) is a pregnancy-associated disorder caused by maternal alloantibodies targeting paternally inherited human platelet antigens (HPAs). These antibodies traverse the placenta and bind to fetal platelets, causing thrombocytopenia and potentially severe complications including intracranial hemorrhage (ICH). Beyond platelets, antibodies may also target other fetal cells such as endothelial cells and placental trophoblasts thereby exacerbating disease severity. Anti-HPA-1a antibodies, the primary cause of FNAIT, display functional heterogeneity due to differences in epitope specificity, glycosylation, which complicate disease severity prediction. Here, we report the structural and functional characterization of two novel anti-HPA-1a antibodies, D-204 and M-204, derived from a mother with a severe FNAIT case. In comparison to D-204 and other existing anti-HPA-1a antibodies such as B2G1 and 26.4, M-204 bound IIb{beta}3 with different kinetics, reaching only half-maximal binding, as determined by flow cytometry. Notably, only M-204 induced platelet aggregation. To investigate the underlying mechanism behind this aggregation, various antibody formats were generated (Fab, Fab2, bispecific, and IgG-Fc dead). Aggregation required both Fab-arms to engage HPA-1a and intact binding to Fc{gamma}RIIa. Structural models and crystal structures suggest the dual engagement of both Fab-arms is required for Fc{gamma}RIIA-engagement which is a unique feature of M-204 among known HPA-1 monoclonals. Our findings highlight the functional diversity of anti-HPA-1a antibodies and provide new insights into their pathogenic mechanisms.

immunology↗

bioRxiv2024

Targeting IL-1/IRAK1/4 signaling in Acute Myeloid Leukemia Stem Cells Following Treatment and Relapse

Therapies for acute myeloid leukemia (AML) face formidable challenges due to relapse, often driven by leukemia stem cells (LSCs). Strategies targeting LSCs hold promise for enhancing outcomes, yet paired comparisons of functionally defined LSCs at diagnosis and relapse remain underexplored. We present transcriptome analyses of functionally defined LSC populations at diagnosis and relapse, revealing significant alterations in IL-1 signaling. Interleukin-1 receptor type I (IL1R1) and interleukin-1 receptor accessory protein (IL1RAP) were notably upregulated in leukemia stem and progenitor cells at both diagnosis and relapse. Knockdown of IL1R1 and IL1RAP reduced the clonogenicity and/or engraftment of primary human AML cells. In leukemic MLL-AF9 mice, Il1r1 knockout reduced LSC frequency and extended survival. To target IL-1 signaling at both diagnosis and relapse, we developed UR241-2, a novel interleukin-1 receptor-associated kinase 1 and 4 (IRAK1/4) inhibitor. UR241-2 robustly suppressed IL-1/IRAK1/4 signaling, including NF-{kappa}B activation and phosphorylation of p65 and p38, following IL-1 stimulation. UR241-2 selectively inhibited LSC clonogenicity in primary human AML cells at both diagnosis and relapse, while sparing normal hematopoietic stem and progenitor cells. It also reduced AML engraftment in leukemic mice. Our findings highlight the therapeutic potential of UR241-2 in targeting IL-1/IRAK1/4 signaling to eradicate LSCs and improve AML outcomes.

cancer biology↗

bioRxiv2023

Accuracy and Reliability of a Suite of Digital Measures of Walking Generated Using a Wrist-worn Sensor: Performance Characterization Study

Background/ObjectivesMobility is a meaningful aspect of an individuals health whose quantification can provide clinical insights. Wearable sensor technology can quantify walking behaviors (a key aspect of mobility) through continuous passive monitoring. Our objective was to characterize the accuracy and reliability performance of a suite of digital measures of walking behaviors, as critical aspects in the practical implementation of digital measures into clinical studies. MethodsWe collected data from a wrist-worn device (the Verily Study Watch) worn for multiple days by a cohort of volunteer participants without history of gait/walking impairment in a real world setting. Based on step measurements computed in 10-second epochs from sensor data, we generated individual daily aggregates (participant-days) to derive a suite of measures of walking: step count, walking bout duration, number of total walking bouts, number of long walking bouts, number of short walking bouts, peak 30-minute walking cadence, peak 30-minute walking pace. To characterize accuracy of the measures, we examined agreement with truth labels generated by a concurrent, ankle-worn, reference device (Modus StepWatch 4) with known low error, calculating the following metrics: Intraclass Correlation Coefficient (ICC), Pearson R, Mean Error (ME), Mean Absolute Error (MAE). To characterize the reliability, we developed a novel approach to identify the time to reach a reliable readout (time-to-reliability) for each measure. This was accomplished by computing mean values over aggregation scopes ranging from 1-30 days, and analyzing test-retest reliability based on ICCs between adjacent (non-overlapping) time windows for each measure. ResultsIn the accuracy characterization, we collected data for a total of 162 participant-days from a testing cohort (N=35 participants; median observation time, 5 days). Agreement with the reference device-based readouts in the testing subcohort (n=35) for the eight measurements under evaluation, as reflected by ICCs, ranged between 0.7-0.9; Pearson R values were all greater than 0.75. For the time-to-reliability characterization, we collected data for a total of 15,120 participant days (overall cohort N=234; median observation time, 119 days). Here, all digital measures achieved an ICC between adjacent readouts > 0.75 by 16 days of wear time. ConclusionsWe characterized accuracy and reliability of a suite of digital measures that provides comprehensive information about walking behaviors in real-world settings. These results, which report the level of agreement with high-accuracy reference labels and the time duration required to establish reliable measure readouts, can guide practical implementation of these measures into clinical studies. Well-characterized tools to quantify walking behaviors in research contexts can provide valuable clinical information about general population cohorts and patients with specific conditions.

bioinformatics↗

bioRxiv2022

Asparagine starvation suppresses histone demethylation through iron depletion

Nutrient availability can impact epigenome to modify gene expression and dictate cell fate decision (Etchegaray and Mostoslavsky, 2016; Kinnaird et al., 2016). -ketoglutarate is an indispensable substrate for the Jumonji family of histone demethylases (JHDMs) mediating most of the cellular demethylation reactions on histone subunits (Schvartzman et al., 2018). Since -ketoglutarate is an intermediate of the tricarboxylic acid (TCA) cycle and a product of transamination, its intracellular levels are regulated by the metabolism of several amino acids (Baksh et al., 2020; Carey et al., 2015; Raffel et al., 2017; Vardhana et al., 2019). Here we show that asparagine starvation suppresses global histone demethylation. This process is neither due to the change of expression of histone modifying enzymes, nor due to the change of intracellular level of -ketoglutarate. Rather, asparagine starvation reduces intracellular pool of labile iron (Fe2+), which is a key cofactor for the JHDMs to function. Mechanistically, asparagine starvation post-transcriptionally suppresses the expression of iron responsive element binding protein 2 (IREB2), an iron sensing protein, which then reduces the mRNA expression of the transferrin receptor (TFRC), a major carrier for iron uptake (Hentze et al., 2010). Furthermore, iron supplementation to the culture medium restores histone demethylation and alters global gene expression to accelerate cell death under conditions of asparagine starvation. Collectively, our results uncover that suppression of iron-dependent histone demethylation is part of the cellular adaptive response to asparagine starvation.

cell biology↗

bioRxiv2020

SSMD: A semi-supervised approach for a robust cell type identification and deconvolution of mouse transcriptomics data

Deconvolution of mouse transcriptomic data is challenged by the fact that mouse models carry various genetic and physiological perturbations, making it questionable to assume fixed cell types and cell type marker genes for different dataset scenarios. We developed a Semi-Supervised Mouse data Deconvolution (SSMD) method to study the mouse tissue microenvironment (TME). SSMD is featured by (i) a novel non-parametric method to discover data set specific cell type signature genes; (ii) a community detection approach for fixing cell types and their marker genes; (iii) a constrained matrix decomposition method to solve cell type relative proportions that is robust to diverse experimental platforms. In summary, SSMD addressed several key challenges in the deconvolution of mouse tissue data, including: (1) varied cell types and marker genes caused by highly divergent genotypic and phenotypic conditions of mouse experiment, (2) diverse experimental platforms of mouse transcriptomics data, (3) small sample size and limited training data source, and (4) capable to estimate the proportion of 35 cell types in blood, inflammatory, central nervous or hematopoietic systems. In silico and experimental validation of SSMD demonstrated its high sensitivity and accuracy in identifying (sub) cell types and predicting cell proportions comparing to state-of-the-arts methods. A user-friendly R package and a web server of SSMD are released via https://github.com/xiaoyulu95/SSMD. Key pointsO_LIWe provide a novel tissue deconvolution method, namely SSMD, which is specifically designed for mouse data to handle the variations caused by different mouse strain, genetic and phenotypic background, and experimental platforms. C_LIO_LISSMD is capable to detect data set and tissue microenvironment specific cell markers for more than 30 cell types in mouse blood, inflammatory tissue, cancer, and central nervous system. C_LIO_LISSMD achieve much improved performance in estimating relative proportion of the cell types compared with state-of-the-art methods. C_LIO_LIThe semi-supervised setting enables the application of SSMD on transcriptomics, DNA methylation and ATAC-seq data. C_LIO_LIA user friendly R package and a R shiny of SSMD based webserver are also developed. C_LI

bioinformatics↗

bioRxiv2019

Mutant p53 Drives Clonal Hematopoiesis through Modulating Epigenetic Pathway

Clonal hematopoiesis of indeterminate potential (CHIP) increases with age and is associated with increased risks of hematological malignancies. While TP53 mutations have been identified in CHIP, the molecular mechanisms by which mutant p53 promotes hematopoietic stem and progenitor cell (HSPC) expansion are largely unknown. We discovered that mutant p53 confers a competitive advantage to HSPCs following transplantation and promotes HSPC expansion after radiation-induced stress. Mechanistically, mutant p53 interacts with EZH2 and enhances its association with the chromatin, thereby increasing the levels of H3K27me3 in genes regulating HSPC self-renewal and differentiation. Further, genetic and pharmacological inhibition of EZH2 decrease the repopulating potential of p53 mutant HSPCs. Thus, we have uncovered an epigenetic mechanism by which mutant p53 drives clonal hematopoiesis. Our work will likely establish epigenetic regulator EZH2 as a novel therapeutic target for preventing CHIP progression and treating hematological malignancies with TP53 mutations.

cancer biology↗