Biology subjects

Sampathkumar, N. K.

Publications and source records attributed to Sampathkumar, N. K..

5 recordsLinked to original sources

bioRxiv2025

Murine peritoneal macrophages undergo female-specific remodeling with aging

Aging is a complex process characterized by a progressive decline in physiological functions. Immune function is strongly influenced by biological sex, affecting both innate and adaptive responses. Here, we investigated the effects of age and sex on mouse peritoneal immune cells and identified macrophages as the top affected cell type. Macrophages, as central components of the innate immune system, play critical roles in homeostasis maintenance and infection response. We found that aging induces sex-specific remodeling of mouse peritoneal macrophage omic landscapes, which is accompanied by female-specific age-related functional remodeling (i.e. decreased phagocysis, increased glycolysis). We show that age-related changes in circulating estrogen levels likely drive aspects of female-specific macrophage age-related changes, specifically age-related phagocytosis decline. By leveraging our multi-omic dataset, we identify transcription factors whose female-specific age-regulation may drive female-specific age-related changes in peritoneal macrophage phenotypes. Interestingly, Irf2 downregulation was sufficient to recapitulate aspects of female peritoneal macrophage aging phenotypes, including increased glycolysis. Mechanistically, decreased Irf2 expression leads to decreased binding to its target genes, including Hk3, which encodes hexokinase (the rate-limiting enzyme of glycolysis). Our findings support the notion that aging leads to female-specific remodeling of mouse peritoneal macrophages through hormone-dependent and -independent mechanisms.

immunology↗

bioRxiv2024

Sex-dimorphic gene regulation in murine macrophages across niches

Macrophages are a key cell type of the innate immune system and are involved at all steps of inflammation: (i) they present antigens to initiate inflammation, (ii) they clear up foreign bodies through phagocytosis, and (iii) they resolve inflammation by removing or deactivating mediator cells. Many subtypes of macrophages have been identified, classified by their niche and/or embryonic origin. In order to better develop therapies for conditions with macrophage dysfunction, it is crucial to decipher potential sex-differences in key physiological mediators of inflammation so that treatment efficacy can be ensured regardless of biological sex. Here, we conduct a meta-analysis approach of transcriptomics datasets for male vs. female mouse macrophages across 8 niches to characterize conserved sex-dimorphic pathways in macrophages across origins and niches. For this purpose, we leveraged new and publicly available RNA-sequencing datasets from murine macrophages, preprocessed these datasets and filtered them based on objective QC criteria, and performed differential gene expression analysis using sex as the covariate of interest. Differentially expressed (DE) genes were compared across datasets and macrophage subsets, and functional enrichment analysis was performed to identify sex-specific functional differences. Consistent with their presence on the sex chromosomes, three genes were found to be differentially expressed across all datasets (i.e. Xist, Eif2s3y, and Ddx3y). More broadly, we found that female-biased pathways across macrophage niches are more consistent than male-biased pathways, specifically relating to components of the extracellular matrix. Our findings increase our understanding of transcriptional similarities across macrophage niches and underscore the importance of including sex as a biological variable in immune-related studies. HighlightsO_LIAcross 17 independently transcriptomic macrophage datasets, three genes are always differentially expressed between males and females: Ddx3y, Eif2s3y, and Xist. C_LIO_LIJaccard analysis reveals female macrophages have more stereotypical transcriptional profile than male macrophages across niches. C_LIO_LIFunctional enrichment analyses show that female-biased pathways across macrophage subtypes are enriched for extracellular matrix-related genes. C_LI

immunology↗

bioRxiv2021

RNA-Seq is not required to determine stable reference genes for qPCR normalization

Assessment of differential gene expression by qPCR is heavily influenced by the choice of reference genes. Although numerous statistical approaches have been proposed to determine the best reference genes, they can give rise to conflicting results depending on experimental conditions. Hence, recent studies propose the use of RNA-Seq to identify stable genes followed by the application of different statistical approaches to determine the best set of reference genes for qPCR data normalization. In this study, we demonstrate that the statistical approach to determine the best reference genes from randomly selected candidates is more important than the preselection of stable candidates from RNA-Seq data. Using a qPCR data normalization workflow that we have previously established; we show that qPCR data normalization using randomly chosen conventional reference genes renders the same results as stable reference genes selected from RNA-Seq data. We validated these observations in two distinct cross-sectional experimental conditions involving human iPSC derived microglial cells and mouse sciatic nerves. These results taken together show that given a robust statistical approach for reference gene selection, stable genes selected from RNA-Seq data do not offer any significant advantage over commonly used reference genes for normalizing qPCR assays.

molecular biology↗

bioRxiv2020

Multi-omic profiling of primary mouse neutrophils reveals a pattern of sex and age-related functional regulation

SummaryNeutrophils are the most abundant white blood cells in humans and constitute one of the first lines of defense in the innate immune response. Neutrophils are extremely short-lived cells, which survive less than a day after reaching terminal differentiation. Thus, little is known about how organismal aging, rather than the daily cellular aging process, may impact neutrophil biology. In addition, accumulating evidence suggests that both immunity and organismal aging are sex-dimorphic. Here, we describe a multi-omic resource of mouse primary bone marrow neutrophils from young and old female and male mice, at the transcriptomic, metabolomic and lipidomic levels. Importantly, we identify widespread age-related and sex-dimorphic regulation of ‘omics’ in neutrophils, specifically regulation of chromatin. Using machine-learning, we identify candidate molecular drivers of age-related and sex-dimorphic transcriptional regulation of neutrophils. We leverage our resource to predict increased levels/release of neutrophil elastase in male mice. To date, this dataset represents the largest multi-omics resource for the study of neutrophils across biological sex and ages. This resource identifies molecular states linked to neutrophil characteristics linked to organismal age or sex, which could be targeted to improve immune responses across individuals.Competing Interest StatementThe authors have declared no competing interest.View Full Text

genomics↗

bioRxiv2019

Optimal use of statistical methods to validate reference gene stability in longitudinal studies

Multiple statistical approaches have been proposed to validate reference genes in qPCR assays. However, conflicting results from these statistical methods pose a major hurdle in the choice of the best reference genes. Indeed, as their respective approaches to calculating reference gene stability is different, their suitability has to be tested for a given experimental setting. In this study, the stability of 10 candidate reference genes (Actb, Gapdh, Tbp, Sdha, Pgk1, Ppia, Rpl13a, Hsp60, Mrpl10, Rps26) was assessed using four common statistical approaches (GeNorm, NormFinder, Coefficient of Variation analysis and Pairwise {Delta}Ct method) in a longitudinal setting. We used the development of the cerebellum and the spinal cord of mice as a model to assess the suitability of these statistical methods for reference gene validation. GeNorm and the Pairwise {Delta}Ct were found to be ill suited due to a fundamental assumption in their stability calculations. Whereas, NormFinder and Coefficient of Variation analysis fare better provided they are used complementarily. We therefore devised a workflow combining these two methods for validating reference genes in developmental studies. This workflow proves to be more robust than any of the methods used individually.

molecular biology↗