Biology subjects

Swift, S. K.

Publications and source records attributed to Swift, S. K..

3 recordsLinked to original sources

bioRxiv2025

Integrative Genomic and Functional Analyses Reveal NINL as a Modulator of Tau Aggregation

IntroductionProteostasis dysfunction is a hallmark of frontotemporal dementia (FTD) and Alzheimers disease (AD), yet the genetic and molecular pathways that disrupt protein homeostasis remain poorly understood. MethodsWe integrated human genetics, transcriptomics, and functional studies to identify proteostasis network components involved in tauopathy. ResultsWe identified 18 proteostasis network genes harboring 75 rare, damaging variants enriched in FTD and/or AD. These genes, spanning multiple proteostasis pathways, were differentially expressed in MAPT mutant neurons and dysregulated in FTD and AD brains. NINL, which encodes Nlp, emerged as the only gene consistently upregulated across all datasets. NINL overexpression reduced tau seeding and enhanced lysosomal proteolytic activity, whereas two FTD-enriched NINL frameshift variants impaired Nlp expression and abolished these protective effects. DiscussionOur findings identify a set of proteostasis genes with genetic and transcriptional links to neurodegeneration and reveal NINL as a novel regulator of tau aggregation, potentially upregulated as an adaptive response to proteotoxic stress.

neuroscience↗

bioRxiv2024

Novel Insights into Post-Myocardial Infarction Cardiac Remodeling through Algorithmic Detection of Cell-Type Composition Shifts

BackgroundRecent advances in single cell sequencing have led to an increased focus on the role of cell-type composition in phenotypic presentation and disease progression. Cell-type composition research in the heart is challenging due to large, frequently multinucleated cardiomyocytes that preclude most single cell approaches from obtaining accurate measurements of cell composition. Our in silico studies reveal that ignoring cell type composition when calculating differentially expressed genes (DEGs) can have significant consequences. For example, a relatively small change in cell abundance of only 10% can result in over 25% of DEGs being false positives. MethodsWe have implemented an algorithmic approach that uses snRNAseq datasets as a reference to accurately calculate cell type compositions from bulk RNAseq datasets through robust data cleaning, gene selection, and multi-sample cross-subject and cross-cell-type deconvolution. We applied our approach to cardiomyocyte-specific 1A adrenergic receptor (CM-1A-AR) knockout mice. 8-12 week-old mice (either WT or CM-1A-KO) were subjected to permanent left coronary artery (LCA) ligation or sham surgery (n=4 per group). Transcriptomes from the infarct border zones were collected 3 days later and analyzed using our algorithm to determine cell-type abundances, corrected differential expression calculations using DESeq2, and validated these findings using RNAscope. ResultsUncorrected DEGs for the CM-1A-KO X LCA interaction term featured many cell-type specific genes such as Timp4 (fibroblasts) and Aplnr (cardiomyocytes) and overall GO enrichment for terms pertaining to cardiomyocyte differentiation (P=3.1E-4). Using our algorithm, we observe a striking loss of cardiomyocytes and gain in fibroblasts in the 1A-KO + LCA mice that was not recapitulated in WT + LCA animals, although we did observe a similar increase in macrophage abundance in both conditions. This recapitulates prior results that showed a much more severe heart failure phenotype in CM-1A-KO + LCA mice. Following correction for cell-type, our DEGs now highlight a novel set of genes enriched for GO terms such as cardiac contraction (P=3.7E-5) and actin filament organization (P=6.3E-5). ConclusionsOur algorithm identifies and corrects for cell-type abundance in bulk RNAseq datasets opening new avenues for research on novel genes and pathways as well as an improved understanding of the role of cardiac cell types in cardiovascular disease.

bioinformatics↗

bioRxiv2022

Cardiomyocyte ploidy is dynamic during postnatal development and varies across genetic backgrounds

Somatic polyploidization, an adaptation by which cells increase their DNA content to support cell and organ growth, is observed in many mammalian cell types, including cardiomyocytes. Although polyploidization is beneficial in many contexts, progression to a polyploid state is often accompanied by a loss of proliferative capacity. Recent work suggests that heterogeneity in cardiomyocyte ploidy is highly influenced by genetic diversity. However, the developmental course by which cardiomyocytes reach their final ploidy state has only been investigated in select genetic backgrounds. Here, we assessed cardiomyocyte number, cell cycle activity, and ploidy dynamics across two divergent inbred mouse strains; C57Bl/6J and A/J. Both strains are born and reach adulthood with a comparable number of cardiomyocytes, however the end composition of ploidy classes and developmental progression to reach the final state and number differ substantially. In addition to corroborating previous findings that identified Tnni3k as a mediator of cardiomyocyte ploidy, we also uncover a novel role for Runx1 and Tnni3k in ploidy dynamics and cardiomyocyte cytokinesis. These data provide novel insight into the developmental path to cardiomyocyte ploidy states and challenge the paradigm that polyploidization and hypertrophy are the only mechanisms for growth in the mouse heart after the first week of life.

developmental biology↗