Biology subjects

Gupte, R.

Publications and source records attributed to Gupte, R..

5 recordsLinked to original sources

bioRxiv2025

Contrasting mutation patterns in haploid and diploid cells from two yeast species

There is significant variation in the rate and spectrum of spontaneous mutations among taxa. How this variation is shaped by natural selection remains a subject of debate. The drift barrier hypothesis proposes that selection generally favors lower mutation rates due to the risk of deleterious mutations but acts less effectively against weak mutator alleles in smaller populations, allowing the mutation rate to increase due to genetic drift. Given this model, we propose that mutation rates may also be elevated in cell types that appear rarely in a population, where DNA replication and repair processes are subject to selection less often. We can begin to test this prediction in yeast species, some of which can be grown in either a haploid or diploid cell state. Existing data on the budding yeast Saccharomyces cerevisiae support this prediction, with a higher mutation rate observed in haploids, which is the rare cell type in natural populations. However, this pattern could also appear if haploidy is inherently mutagenic, regardless of the dominant cell type. To test these alternatives, we conducted a mutation accumulation experiment with haploid and diploid cells of the fission yeast Schizosaccharomyces pombe, in which diploidy is the rare cell type. In this species, we found a higher mutation rate in diploids, consistent with our prediction. In both species, the spectrum of mutations is also influenced by ploidy state. Our findings suggest that limits to selection on mutation may be evident as variation within species. SignificanceSpontaneous mutation rates vary among organisms. Natural selection may act to reduce mutation rates; if so, we would expect mutation rates to be elevated in cell types where natural selection has historically had less opportunity to act. We studied mutation patterns in two yeast species when grown in the haploid or diploid form. For the typically diploid species, the mutation rate was higher in the haploid form. For the typically haploid species, the mutation rate was higher in the diploid form. The observation that mutation rates increase when selection is ineffective indicates that selection usually acts to reduce mutation rates.

evolutionary biology↗

bioRxiv2025

PRISM: A platform for illuminating viral dark matter

The exploration of bacteriophage diversity remains constrained by reliance on conventional plaque assays, which bias discovery toward phages that form visible plaques and propagate efficiently. The discovery process, as well as measuring correct phage concentrations and phage resistance frequencies, are also time-consuming and labor intensive. Here, we present PRISM (Phage Recovery and Investigation in Single-droplet Microenvironments), a droplet microfluidics-based, plating-independent platform for the high-throughput isolation, quantification, and characterization of bacteriophages. By encapsulating phage-host interactions in water-in-oil microdroplets at single-phase resolution, and then coupling them with fluorescence-based detection and sorting at million-droplet scale, PRISM enables rapid identification of novel phages, including those that evade detection in conventional assays. We demonstrate PRISMs capabilities across several key applications: (i) recovery of both novel "plaquing" and "non-plaquing" Salmonella phages from a concentrated environmental sample, where PRISM recovered multiple representatives of a non-plaquing genus completely missed by conventional plating-based approaches; (ii) accurate titering of poor-plaquing phages such as Rhodococcus phage ReqiDocB7, for which PRISM reported a 2-fold higher titer than conventional plaque assays; and (iii) plating-free determination of phage resistance frequency, with PRISM yielding resistance and lysogeny frequencies (e.g., 1 in 4.4 x 105 cells for T7 Escherichia phage resistance and 1 in 21 cells for Escherichia Lambda phage lysogeny) that closely match conventional estimates. These data highlight PRISMs enhanced resolution and accuracy, as well as its ability to detect rare, non-plaquing, or slow-replicating phages, in a high speed and automated fashion, thereby underscoring the platforms power to access viral "dark matter" traditionally overlooked using conventional methods.

microbiology↗

bioRxiv2025

Role of Macrophage PARP1 in the Regulation of Crosstalk between Adipose Immune Cells and Adipocytes during Diet-induced Obesity

Adipose tissue consists of heterogeneous cell populations, including macrophages, which play a key role in maintaining adipose tissue homeostasis. We previously identified PARP1 as a critical regulator of proadipogenic gene expression in preadipocytes and proinflammatory gene expression in macrophages. To investigate the role of macrophage PARP1 in regulating adipose tissue homeostasis, we generated myeloid lineage-specific Parp1 knockout mice (Parp1 KOLysM). When subjected to a high fat diet for 12 weeks, the Parp1 KOLysM mice exhibited an obese phenotype accompanied by white adipose tissue (WAT) dysfunction, characterized by altered metabolite profile, pronounced adipocyte hypertrophy, and increased macrophage infiltration. Coculture of primary preadipocytes with the conditioned medium from bone marrow-derived macrophages (BMDMs) isolated from Parp1 KOLysM or control mice demonstrated that macrophage PARP1 depletion inhibited LPS-induced proinflammatory gene expression in BMDMs, but enhanced differentiation of preadipocytes into mature adipocytes. Single cell RNA-sequencing using CD45+-sorted WAT resident immune cells showed that macrophage PARP1 depletion increased the fraction of macrophages and NK cells, altered gene expression in both cell populations, and promoted intercellular communications. Taken together, our studies demonstrate a key role for macrophage PARP1 in the maintenance of adipose tissue inflammatory and metabolic homeostasis. Macrophage PARP1 depletion promotes cell-cell crosstalk among macrophages, fat cells, and other immune cell populations in adipose tissue, which cooperatively drives the development of obesity. SignificanceIn this study, we characterized a role for macrophage PARP1 in regulating adipose tissue homeostasis. Depletion of PARP1 in macrophages enhances cell-cell crosstalk among immune cells and fat cells, which exacerbates adipose dysfunction and drives obesity and adverse metabolic outcomes.

molecular biology↗

bioRxiv2018

Memory sequencing reveals heritable single cell gene expression programs associated with distinct cellular behaviors

Non-genetic factors can cause individual cells to fluctuate substantially in gene expression levels over time. Yet it remains unclear whether these fluctuations can persist for much longer than the time of one cell division. Current methods for measuring gene expression in single cells mostly rely on single time point measurements, making the duration of gene expression fluctuations or cellular memory difficult to measure. Here, we report a method combining Luria and Delbrucks fluctuation analysis with population-based RNA sequencing (MemorySeq) for identifying genes transcriptome-wide whose fluctuations persist for several cell divisions. MemorySeq revealed multiple gene modules that are expressed together in rare cells within otherwise homogeneous clonal populations. Further, we found that these rare cell subpopulations are associated with biologically distinct behaviors, such as the ability to proliferate in the face of anti-cancer therapeutics, in different cancer cell lines. The identification of non-genetic, multigenerational fluctuations has the potential to reveal new forms of biological memory at the level of single cells and suggests that non-genetic heritability of cellular state may be a quantitative property.

systems biology↗

bioRxiv2017

A Comparison Between Single Cell RNA Sequencing And Single Molecule RNA FISH For Rare Cell Analysis

The development of single cell RNA sequencing technologies has emerged as a powerful means of profiling the transcriptional behavior of single cells, leveraging the breadth of sequencing measurements to make inferences about cell type. However, there is still little understanding of how well these methods perform at measuring single cell variability for small sets of genes and what \"transcriptome coverage\" (e.g. genes detected per cell) is needed for accurate measurements. Here, we use single molecule RNA FISH measurements of 26 genes in thousands of melanoma cells to provide an independent reference dataset to assess the performance of the DropSeq and Fluidigm single cell RNA sequencing platforms. We quantified the Gini coefficient, a measure of rare-cell expression variability, and find that the correspondence between RNA FISH and single cell RNA sequencing for Gini, unlike for mean, increases markedly with per-cell library complexity up to a threshold of [~]2000 genes detected. A similar complexity threshold also allows for robust assignment of multi-genic cell states such as cell cycle phase. Our results provide guidelines for selecting sequencing depth and complexity thresholds for single cell RNA sequencing. More generally, our results suggest that if the number of genes whose expression levels are required to answer any given biological question is small, then greater transcriptome complexity per cell is likely more important than obtaining very large numbers of cells.

genomics↗