Biology subjects

Pirooznia, M.

Publications and source records attributed to Pirooznia, M..

13 recordsLinked to original sources

bioRxiv2023

Social Determinants modulate NK cell activity via obesity, LDL, and DUSP1 signaling

Adverse social determinants of health (aSDoH) are associated with obesity and related comorbidities like diabetes, cardiovascular disease, and cancer. Obesity is also associated with natural killer cell (NK) dysregulation, suggesting a potential mechanistic link. Therefore, we measured NK phenotypes and function in a cohort of African-American (AA) women from resource-limited neighborhoods. Obesity was associated with reduced NK cytotoxicity and a shift towards a regulatory phenotype. In vitro, LDL promoted NK dysfunction, implicating hyperlipidemia as a mediator of obesity-related immune dysregulation. Dual specific phosphatase 1 (DUSP1) was induced by LDL and was upregulated in NK cells from subjects with obesity, implicating DUSP1 in obesity-mediated NK dysfunction. In vitro, DUSP1 repressed LAMP1/CD107a, depleting NK cells of functional lysosomes to prevent degranulation and cytokine secretion. Together, these data provide novel mechanistic links between aSDoH, obesity, and immune dysregulation that could be leveraged to improve outcomes in marginalized populations.

immunology↗

bioRxiv2021

Metabolic design in a model of extreme mammalian metabolism, the North American least shrew (Cryptotis parva)

Mitochondrial adaptations are fundamental to differentiated function and energetic homeostasis in mammalian cells. But the mechanisms that underlie these relationships remain poorly understood. Here, we investigated organ-specific mitochondrial morphology, connectivity and protein composition in a model of extreme mammalian metabolism, the Least shrew (Cryptotis parva). This was achieved through a combination of high-resolution 3D focused-ion-beam EM imaging and tandem-mass-tag MS proteomics. We demonstrate that liver and kidney mitochondrial content are equivalent to the heart permitting assessment of mitochondrial adaptations in different organs with similar metabolic demand. Muscle mitochondrial networks (cardiac and skeletal) are extensive, with a high incidence of nanotunnels - which collectively support the metabolism of large muscle cells. Mitochondrial networks were not detected in the liver and kidney as individual mitochondria are localized with sites of ATP consumption. This configuration is not observed in striated muscle, likely due to a homogenous ATPase distribution and the structural requirements of contraction. These results demonstrate distinct, fundamental mitochondrial structural adaptations for similar metabolic demand that are dependent on the topology of energy utilization process in a mammalian model of extreme metabolism.

zoology↗

bioRxiv2021

Comprehensive Assessment of Somatic Copy Number Variation Calling Using Next-Generation Sequencing Data

Copy number variation (CNV) is a common type of mutation that often drives cancer progression. With advances in next-generation sequencing (NGS), CNVs can be detected in a detailed manner via newly developed computational tools but quality of such CNV calls has not been carefully evaluated. We analyzed CNV calls reported by 6 cutting-edge callers for 91 samples which were derived from the same cancer cell line, prepared and sequenced by varying the following factors: type of tissue sample (Fresh vs. Formalin Fixed Paraffin Embedded (FFPE)), library DNA amount, tumor purity, sequencing platform (Whole-Genome Sequencing (WGS) versus Whole-Exome Sequencing (WES)), and sequencing coverage. We found that callers greatly determined the pattern of CNV calls. Calling quality was drastically impaired by low purity (<50%) and became variable when WES, FFPE, and medium purity (50%-75%) were applied. Effects of low DNA amount and low coverage were relatively minor. Our analysis demonstrates the limitation of benchmarking somatic CNV callers when the real ground truth is not available. Our comprehensive analysis has further characterized each caller with respect to confounding factors and examined the consistency of CNV calls, thereby providing guidelines for conducting somatic CNV analysis.

bioinformatics↗

bioRxiv2020

Network Analysis and Transcriptome Profiling Identify Autophagic and Mitochondrial Dysfunctions in SARS-CoV-2 Infection

Analyzing host transcriptional changes in response to SARS-CoV-2 infection will help delineate biological processes underlying viral pathogenesis. Comparison of expression profiles of lung cell lines A549 (infected with either SARS-CoV-2 (with ACE2 expression)) or Influenza A virus (IAV)) and Calu3 (infected with SARS-CoV-2 or MERS-CoV) revealed upregulation of the antiviral interferon signaling in all three viral infections. However, perturbations in inflammatory, mitochondrial, and autophagy processes were specifically observed in SARS-CoV-2 infected cells. Validation of findings from cell line data revealed perturbations in autophagy and mitochondrial processes in the infected human nasopharyngeal samples. Specifically, downregulation of mTOR expression, mitochondrial ribosomal, mitochondrial complex I, and lysosome acidification genes were concurrently observed in both infected cell lines and human datasets. Furthermore, SARS-CoV-2 infection impedes autophagic flux by upregulating GSK3B in lung cell lines, or by downregulating autophagy genes, SNAP29 and lysosome acidification genes in human samples, contributing to increased viral replication. Therefore, drugs targeting lysosome acidification or autophagic flux could be tested as intervention strategies. Additionally, downregulation of MTFP1 (in cell lines) or SOCS6 (in human samples) results in hyperfused mitochondria and impede proper interferon response. Coexpression networks analysis identifies correlated clusters of genes annotated to inflammation and mitochondrial processes that are misregulated in SARS-CoV-2 infected cells. Finally, comparison of age stratified human gene expression data revealed impaired upregulation of chemokines, interferon stimulated and tripartite motif genes that are critical for antiviral signaling. Together, this analysis has revealed specific aspects of autophagic and mitochondrial function that are uniquely perturbed in SARS-CoV-2 infection.

bioinformatics↗

bioRxiv2020

Mitochondria regulate Drosophila intestinal stem cell differentiation through FOXO

Stem cells often rely on glycolysis for energy production, and switching to oxidative phosphorylation is believed to be essential for their differentiation. To explore the link between mitochondrial respiration and stem cell differentiation, we genetically disrupted electron transport chain (ETC) complexes in the intestinal stem cells (ISCs) of Drosophila. We found that ISCs carrying impaired ETC proliferated much more slowly than normal, produced very few intestinal progenitors, or enteroblasts, and failed to differentiate into enterocytes or enteroendocrine cells. One of the main impediments to ISCs differentiation appeared to be abnormally elevated forkhead box O (FOXO) signaling in the ETC-deficient ISCs, as genetically suppressing the signaling pathway partially rescued the differentiation defect. Contrary to common belief, neither reactive oxygen species (ROS) accumulation nor adenosine triphosphate (ATP) reduction appeared to mediate the ETC mutant phenotype. Our results demonstrate that ETC is essential for Drosophila ISC proliferation and differentiation in vivo, and acts at least partially by repressing endogenous FOXO signaling. They also raise the possibility that ETC complexes have a role in stem cell differentiation beyond electron transfer and ATP production.

developmental biology↗

bioRxiv2020

Acetylation-mediated phase control of the nucleolus regulates cellular acetyl-CoA responses

The metabolite acetyl-CoA serves as an essential element for a wide range of cellular functions including ATP production, lipid synthesis and protein acetylation. Intracellular acetyl-CoA concentrations are associated with nutrient availability, but the mechanisms by which a cell responds to fluctuations in acetyl-CoA levels remain elusive. Here, we generate a cell system to selectively manipulate the nucleo-cytoplasmic levels of acetyl-CoA using CRISPR-mediated gene editing and acetate supplementation of the culture media. Using this system and quantitative omics analyses, we demonstrate that acetyl-CoA depletion alters the integrity of the nucleolus, impairing ribosomal RNA synthesis and evoking the ribosomal protein-dependent activation of p53. This nucleolar remodeling appears to be mediated through the class IIa HDAC deacetylases regulating the phase state of the nucleolus. Our findings highlight acetylation-mediated control of the nucleolus as an important hub linking acetyl-CoA fluctuations to cellular stress responses.

cell biology↗

bioRxiv2020

Multilevel integrative transcriptome analyses in humans and humanized mice define in vivo human lncRNA metabolic regulators

A growing number of long non-coding RNAs (lncRNAs) have emerged as vital metabolic regulators in research animals suggesting that lncRNAs could also play an important role in human metabolism. However, most human lncRNAs are non-conserved, vastly limiting our ability to identify human lncRNA metabolic regulators (hLMRs). As the sequence-function relation of lncRNAs has yet to be established, the identification of lncRNA metabolic regulators in animals often relies on their regulations by experimental metabolic conditions. But it is very challenging to apply this strategy to human lncRNAs because well-controlled human data are much limited in scope and often confounded by genetic heterogeneity. In this study, we establish an efficient pipeline to identify putative hLMRs that are metabolically sensitive, disease-relevant, and population applicable. We first progressively processed human transcriptome data to select human liver lncRNAs that exhibit highly dynamic expression in the general population, show differential expression in a metabolic disease population, and response to dietary intervention in a small disease cohort. We then experimentally demonstrated the responsiveness of selected hepatic lncRNAs to defined metabolic milieus in a liver-specific humanized mouse model. Furthermore, by extracting a concise list of protein-coding genes that are persistently correlated with lncRNAs in general and metabolic disease populations, we predicted the specific function for each hLMR. Using gain- and loss-of-function approaches in humanized mice as well as ectopic expression in conventional mice, we were able to validate the regulatory role of one non-conserved hLMR in cholesterol metabolism. Mechanistically, this hLMR binds to an RNA-binding protein, PTBP1, to modulate the transcription of cholesterol synthesis genes. In summary, our study provides a pipeline to overcome the variabilities intrinsic to human data to enable the efficient identification and functional definition of hLMRs. The combination of this bioinformatic framework and humanized murine model will enable broader systematic investigation of the physiological role of disease-relevant human lncRNAs in metabolic homeostasis.

physiology↗

bioRxiv2019

A genomic dating tool for ancient genomes resolves the origins of hundreds of Eurasian genomes

Radiocarbon dating is the gold-standard in archaeology to estimate the age of skeletons, a key to studying their origins. Nearly half of all published ancient human genomes lack reliable and direct dates, which results in obscure and contradictory reports. Here, we developed the Temporal Population Structure (TPS), the first DNA-based dating method for ancient genomes ranging from the Upper Palaeolithic to modern-day samples and applied it to 1559 ancient Europeans, Asians, and Caucasus individuals and to 2117 modern worldwide individuals. We show that TPS predictions for dated skeletons align with their known dates and correctly account for kin relationships. The TPS-dating of poorly dated Eurasian samples resolves conflicts and sheds new light on disputed findings, as illustrated by four test cases. We discuss the phenotypic traits of the Time Informative Markers (TIMs) that underlie TPS. SummaryTPS is a novel method to date humans from the Upper Palaeolithic to modern time from their DNA sequences. Accurate dating is essential to the interepretation of paleogemonic data.. The gold-standard method in archaeology is radiocarbon dating1. However, a major limitation of radiocarbon dating is the high amount of collagen extraction (500 mg) involved in the process2. Consequently, half of all published ancient human genomes lack reliable and direct dates, which results in obscure and contradictory reports. Here, we present the Temporal Population Structure (TPS), the first genomic dating method for ancient genomes ranging from the Upper Palaeolithic to modern-day samples. We show that TPS predictions for 961 radiocarbon-dated Eurasian skeletons align with their known dates. We replicate these findings on 598 other Europeans, Asians and Caucasus individuals. Using kin-pairs, we demonstrate that TPS has produced more accurate results than radiocarbon and other dating. We show how our findings resolve conflicts and sheds new light on disputed findings as illustrated by four test cases. Finally, we discuss the phenotypic traits of the Time Informative Markers (TIMs) that underlie TPS. TPS is a novel dating technique, which can be used when radiocarbon dating is unfeasible or uncertain or to develop alternative hypotheses. TPS cannot be used for older (<14,000 years ago) samples, and its accuracy depends on the temporal and geographical breadth of radiocarbon-dated samples in the training dataset, though this limitation can be improved over time. Overall, TPS can improve the accuracy of archeological and paleogenomic studies.

genomics↗

bioRxiv2019

Regulation of neuron-specific gene transcription by stress hormone signalling requires synaptic activity in zebrafish

The Glucocorticoid Receptor (GR) co-ordinates metabolic and behavioural responses to stressors. We hypothesised that GR influences behaviour by modulating specific epigenetic and transcriptional processes in the brain. Using the zebrafish as a model organism, the brain methylomes of wild-type and grs357 mutant adults were analysed and GR-sensitive, differentially methylated regions (GR-DMRs) were identified. Two genes with GR-DMRs exhibited distinct methylation and transcriptional sensitivities to GR: the widely expressed direct GR target fkbp5 and neuron-specific aplp1. In larvae, neural activity is required for GR-mediated transcription of aplp1, but not for that of fkbp5. GR regulates metabotropic glutamate receptor gene expression, the activities of which also modulated aplp1 expression, implicating synaptic neurotransmission as an effector of GR function upstream of aplp1. Our results identify two distinct routes of GR-regulated transcription in the brain, including a pathway through which GR couples endocrine signalling to synaptic activity-regulated transcription by modulating metabotropic glutamate receptor expression.

developmental biology↗

bioRxiv2019

lncRNAKB: A comprehensive knowledgebase of long non-coding RNAs

We have assembled a comprehensive long non-coding RNA knowledgebase (lncRNAKB) of 77,199 annotated human lncRNAs (224,286 transcripts) by methodically integrating widely used lncRNAs resources. To facilitate functional characterization of lncRNAs, we employed Genotype-Tissue Expression (GTEx) project to provide tissue-specific gene expression profiles of lncRNAs in 31 solid organ tissues. Additional information includes network analysis to identify co-expressed gene modules to potentially delineate lncRNA function. Tissue-specificity, phylogenetic conservation scores and coding potential for lncRNAs are included. Finally, using whole genome sequencing data from GTEx, expression quantitative trait loci (cis-eQTL) regulated lncRNAs were calculated in all tissues. lncRNAKB is available at http://www.lncrnakb.org.

bioinformatics↗

bioRxiv2019

Electron transport chain biogenesis activated by a JNK-insulin-Myc relay primes mitochondrial inheritance in Drosophila

Oogenesis features an enormous increase in mitochondrial mass and mtDNA copy number, which are required to furnish mature eggs with adequate mitochondria and to curb the transmission of deleterious mtDNA variants. Quiescent in dividing germ cells, mtDNA replication initiates upon oocyte determination in the Drosophila ovary, which necessitates active mitochondrial respiration. However, the underlying mechanism for this dynamic regulation remains unclear. Here, we show that an feedforward insulin-Myc loop promotes mitochondrial respiration and biogenesis by boosting the expression of electron transport chain subunits and factors essential for mtDNA replication and expression, and mitochondrial protein import. We further reveal that transient activation of JNK enhances the expression of insulin receptor and initiates the insulin-Myc signaling loop. Importantly, this signaling relay ensures sufficient mtDNA in eggs and limits the transmission of a deleterious mtDNA mutation. Our study demonstrates cellular mechanisms that couple mitochondrial biogenesis and inheritance with oocyte development.

developmental biology↗

bioRxiv2019

IKAP - Identifying K mAjor cell Population groups in single-cell RNA-seq analysis

In single-cell RNA-seq analysis, clustering cells into groups and differentiating cell groups by marker genes are two separate steps for investigating cell identity. However, results in clustering greatly affect the ability to differentiate between cell groups. We develop IKAP - an algorithm identifying major cell groups that improves differentiating by tuning parameters for clustering. Using multiple datasets, we demonstrate IKAP improves identification of major cell types and facilitates cell ontology curation.

bioinformatics↗

bioRxiv2018

Ancient ancestry informative markers for identifying fine-scale ancient population structure in Eurasians

The rapid accumulation of ancient human genomes from various areas and time periods potentially allows the expansion of studies of biodiversity, biogeography, forensics, population history, and epidemiology into past populations. However, most ancient DNA (aDNA) data were generated through microarrays designed for modern-day populations known to misrepresent the population structure. Past studies addressed these problems using ancestry informative markers (AIMs). However, it is unclear whether AIMs derived from contemporary human genomes can capture ancient population structure and whether AIM finding methods are applicable to ancient DNA (aDNA) provided that the high missingness rates in ancient, oftentimes haploid, DNA can also distort the population structure. Here, we define ancient AIMs (aAIMs) and develop a framework to evaluate established and novel AIM-finding methods in identifying the most informative markers. We show that aAIMs identified by a novel principal component analysis (PCA)-based method outperforms all competing methods in classifying ancient individuals into populations and identifying admixed individuals. In some cases, predictions made using the aAIMs were more accurate than those made with a complete marker set. We discuss the features of the ancient Eurasian population structure and strategies to identify aAIMs. This work informs the design of population microarrays and the interpretation of aDNA results.

genetics↗