Biology subjects

Beheshti, A.

Publications and source records attributed to Beheshti, A..

10 recordsLinked to original sources

bioRxiv2024

Rapid, high-resolution, non-destructive assessments of metabolic and morphological homogeneity uniquely identify high-grade cervical precancerous lesions

PurposeTwo-photon microscopy (2PM) is an emerging clinical imaging modality with the potential to non-invasively assess tissue metabolism and morphology in high-resolution. This study aimed to assess the translational potential of 2PM for improved detection of high-grade cervical precancerous lesions. Experimental Design2P images attributed to reduced nicotinamide adenine dinucleotide (phosphate) (NAD(P)H) and oxidized flavoproteins (FP) were acquired from the full epithelial thickness of freshly excised human cervical tissue biopsies (N = 62). Fifteen biopsies harbored high-grade squamous intraepithelial lesions (HSILs), 14 biopsies harbored low-grade SILs (LSILs), and 33 biopsies were benign. Quadratic discriminant analysis (QDA) leveraged morphological and metabolic functional metrics extracted from these images to predict the presence of HSILs. We performed gene set enrichment analysis (GSEA) using datasets available on the Gene Expression Omnibus (GEO) to validate the presence of metabolic reprogramming in HSILs. ResultsIntegrating metabolic and morphological 2P-derived metrics from finely sampled, full-thickness epithelia achieved a high 90.8 {+/-} 6.1% sensitivity and 72.3 {+/-} 11.3% specificity of HSIL detection. Notably, sensitivity (91.4 {+/-} 12.0%) and specificity (77.5 {+/-} 12.6%) were maintained when utilizing metrics from only two images at 12- and 72-{micro}m from the tissue surface. Upregulation of glycolysis, fatty acid metabolism, and oxidative phosphorylation in HSIL tissues validated the metabolic reprogramming captured by 2P biomarkers. ConclusionLabel-free 2P images from as few as two epithelial depths enable rapid and robust HSIL detection through the quantitative characterization of metabolic and morphological reprogramming, underscoring the potential of this tool for clinical evaluation of cervical precancers. Translational Relevance StatementThe colposcopy and biopsy paradigm for cervical pre-cancer detection leads to an excessive number of unnecessary biopsies, with significant economic and psychological costs. This study highlights the potential of label-free, high-resolution two photon imaging to improve this paradigm by introducing real-time morphofunctional tissue assessments. In an extensive dataset comprising freshly excised high-grade and low-grade cervical intraepithelial lesions, along with benign metaplastic and inflamed human cervical tissue biopsies, we successfully characterize a loss of morphofunctional heterogeneity indicative of high-grade precancerous changes. Leveraging a combination of two-photon imaging-derived quantitative morphofunctional metrics, our findings showcase a substantial improvement in both sensitivity and specificity of high-grade lesion detection compared to the current gold standard of colposcopy followed by a single biopsy. The demonstrated enhancement in sensitivity and specificity highlights the prospect of integrating non-invasive, label-free metabolic imaging into clinical practice, offering a more effective and efficient approach to identify and manage cervical precancerous lesions.

bioengineering↗

bioRxiv2024

Spaceflight causes strain-dependent gene expression changes associated with lipid and extracellular matrix dysregulation in the mouse kidney in vivo

To explore new worlds we must ensure humans can survive and thrive in the space environment. Incidence of kidney stones in astronauts is a major risk factor associated with long term missions, caused by increased blood calcium levels due to bone demineralisation triggered by microgravity and space radiation. Transcriptomic changes have been observed in other tissues during spaceflight, including the kidney. We analysed kidney transcriptome patterns in two different strains of mice flown on the International Space Station, C57BL/6J and BALB/c. Here we show a link between spaceflight and transcriptome patterns associated with dysregulation of lipid and extracellular matrix metabolism and altered transforming growth factor-beta signalling. A stronger response was seen in C57BL/6J mice than BALB/c. Genetic differences in hyaluronan metabolism between strains may confer protection against extracellular matrix remodelling through downregulation of epithelial-mesenchymal transition. We intend for our findings to contribute to development of new countermeasures against kidney disease in astronauts and people here on Earth.

genomics↗

bioRxiv2024

A pan-tissue, pan-disease compendium of human orphan genes

Species-specific genes are ubiquitous in evolution, with functions ranging from prey paralysis to survival in subzero temperatures. Because they are typically expressed under limited conditions and lack canonical features, such genes may be vastly under-identified, even in humans. Here, we leverage terabytes of human RNA-Seq data to identify thousands of highly-expressed transcripts that do not correspond to any Gencode-annotated gene. Many may be novel ncRNAs although 80% of them contain ORFs that have the potential of encoding proteins unique to Homo sapiens (orphan genes). We validate our findings with independent strand-specific and single-cell RNA-seq datasets. Hundreds of these novel transcripts overlap with deleterious genomic variants; thousands show significant association with disease-specific patient survival. Most are dynamically regulated and accumulate selectively in particular tissues, cell-types, developmental stages, tumors, COVID-19, sex, and ancestries. As such, these transcripts hold potential as diagnostic biomarkers or therapeutic targets. To empower future discovery, we provide a compendium of these huge RNA-Seq expression data, and RiboSeq data, with associated metadata. Further, we supply the gene models for the novel genes as UCSC Genome Browser tracks.

evolutionary biology↗

bioRxiv2022

The interplay between lncRNAs, RNA-binding proteins and viral genome during SARS-CoV-2 infection reveals strong connections with regulatory events involved in RNA metabolism and immune response.

Viral infections are complex processes based on an intricate network of molecular interactions. The infectious agent hijacks components of the cellular machinery for its profit, circumventing the natural defense mechanisms triggered by the infected cell. The successful completion of the replicative viral cycle within a cell depends on the function of viral components versus the cellular defenses. Non-coding RNAs (ncRNAs) are important cellular modulators, either promoting or preventing the progression of viral infections. Among these ncRNAs, the long non-coding RNA (lncRNA) family is especially relevant due to their intrinsic functional properties and ubiquitous biological roles. Specific lncRNAs have been recently characterized as modulators of the cellular response during infection of human host cells by single stranded RNA viruses. However, the role of host lncRNAs in the infection by human RNA coronaviruses such as SARS-CoV-2 remains uncharacterized. In the present work, we have performed a transcriptomic study of a cohort of patients with different SARS-CoV-2 viral load. Our results revealed the existence of a SARS-CoV-2 infection-dependent pattern of transcriptional up-regulation in which specific lncRNAs are an integral component. To determine the role of these lncRNAs, we performed a functional correlation analysis complemented with the study of the validated interactions between lncRNAs and RNA-binding proteins (RBPs). This combination of in silico functional association studies and experimental evidence allowed us to identify a lncRNA signature composed of six elements - NRIR, BISPR, MIR155HG, FMR1-IT1, USP30-AS1, and U62317.2 - associated with the regulation of SARS-CoV-2 infection. We propose a competition mechanism between the viral RNA genome and the regulatory lncRNAs in the sequestering of specific RBPs that modulates the interferon response and the regulation of RNA surveillance by nonsense-mediated decay (NMD). O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=182 SRC="FIGDIR/small/485903v1_ufig1.gif" ALT="Figure 1"> View larger version (46K): org.highwire.dtl.DTLVardef@4368c9org.highwire.dtl.DTLVardef@1948201org.highwire.dtl.DTLVardef@e31fd9org.highwire.dtl.DTLVardef@1400805_HPS_FORMAT_FIGEXP M_FIG C_FIG Graphical abstractModel of interactions among lncRNA and cognate RNA-binding proteins in SARS-CoV-2 infection. According to our model, the viral genome can establish direct interactions with three core proteins (DDX3X, UPF1 and IGF2BP2) involved in mRNA metabolism and regulation of the interferon response, which are also components of a SARS-CoV-2 lncRNA-centered regulatory network. The competition between viral RNA and lncRNAs could act as a counteracting factor for the normal function of homeostatic lncRNA-centered regulatory networks, contributing to viral progression and replication. Black arrows depict physical interactions between network components; red arrows represent functional relationships.

bioinformatics↗

bioRxiv2022

Targeted Down Regulation Of Core Mitochondrial Genes During SARS-CoV-2 Infection

Defects in mitochondrial oxidative phosphorylation (OXPHOS) have been reported in COVID-19 patients, but the timing and organs affected vary among reports. Here, we reveal the dynamics of COVID-19 through transcription profiles in nasopharyngeal and autopsy samples from patients and infected rodent models. While mitochondrial bioenergetics is repressed in the viral nasopharyngeal portal of entry, it is up regulated in autopsy lung tissues from deceased patients. In most disease stages and organs, discrete OXPHOS functions are blocked by the virus, and this is countered by the host broadly up regulating unblocked OXPHOS functions. No such rebound is seen in autopsy heart, results in severe repression of genes across all OXPHOS modules. Hence, targeted enhancement of mitochondrial gene expression may mitigate the pathogenesis of COVID-19. One-Sentence SummaryCovid-19 is associated with targeted inhibition of mitochondrial gene transcription.

molecular biology↗

bioRxiv2022

Machine learning algorithm to characterize antimicrobial resistance associated with the International Space Station surface microbiome

BackgroundAntimicrobial Resistance (AMR) has a detrimental impact on human health on Earth and it is equally concerning in other environments such as space due to microgravity, radiation and confinement, especially for long-distance space travel. The International Space Station (ISS) is ideal for investigating microbial diversity and virulence. The shotgun metagenomics data of the ISS generated during the Microbial Tracking - 1 (MT-1) project and resulting metagenome-assembled genomes (MAGs) across three flights in eight different locations during 12 months were used in this study. The objective of this study was to identify the AMR genes associated with whole genomes of 227 cultivable strains, 21 shotgun metagenome sequences, and 24 MAGs retrieved from the ISS environmental samples that were treated with propidium monoazide (PMA; viable microbes). ResultsWe have analyzed the data using a deep learning model, allowing us to go beyond traditional cut-offs based only on high DNA sequence similarity and extending the catalog of AMR genes. Our results in PMA treated samples revealed AMR dominance in the last flight for Kalamiella piersonii, a bacteria related to urinary tract infection in humans. The analysis of 227 pure strains isolated from the MT-1 project revealed hundreds of antibiotic resistance genes from many isolates, including two top-ranking species that corresponded to strains of Enterobacter bugandensis and Bacillus cereus. Computational predictions were experimentally validated by antibiotic resistance profiles in these two species, showing a high degree of concordance. Specifically, disc assay data confirmed the high resistance of these two pathogens to various beta-lactam antibiotics. ConclusionOverall, our computational predictions and validation analyses demonstrate the advantages of machine learning to uncover concealed AMR determinants in metagenomics datasets, expanding the understanding of the ISS environmental microbiomes and their pathogenic potential in humans.

bioinformatics↗

bioRxiv2021

Betacoronavirus-specific alternate splicing

Viruses can subvert a number of cellular processes in order to block innate antiviral responses, and many viruses interact with cellular splicing machinery. SARS-CoV-2 infection was shown to suppress global mRNA splicing, and at least 10 SARS-CoV-2 proteins bind specifically to one or more human RNAs. Here, we investigate 17 published experimental and clinical datasets related to SARS-CoV-2 infection as well as datasets from the betacoronaviruses SARS-CoV and MERS as well as Streptococcus pneumonia, HCV, Zika virus, Dengue virus, influenza H3N2, and RSV. We show that genes showing differential alternative splicing in SARS-CoV-2 have a similar functional profile to those of SARS-CoV and MERS and affect a diverse set of genes and biological functions, including many closely related to virus biology. Additionally, the differentially spliced transcripts of cells infected by coronaviruses were more likely to undergo intron-retention, contain a pseudouridine modification and a smaller number of exons than differentially spliced transcripts in the control groups. Viral load in clinical COVID-19 samples was correlated with isoform distribution of differentially spliced genes. A significantly higher number of ribosomal genes are affected by DAS and DGE in betacoronavirus samples, and the betacoronavirus differentially spliced genes are depleted for binding sites of RNA-binding proteins. Our results demonstrate characteristic patterns of differential splicing in cells infected by SARS-CoV-2, SARS-CoV, and MERS, potentially modifying a broad range of cellular functions and affecting a diverse set of genes and biological functions.

genomics↗

bioRxiv2021

Systemic Tissue and Cellular Disruption from SARS-CoV-2 Infection revealed in COVID-19 Autopsies and Spatial Omics Tissue Maps

The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) virus has infected over 115 million people and caused over 2.5 million deaths worldwide. Yet, the molecular mechanisms underlying the clinical manifestations of COVID-19, as well as what distinguishes them from common seasonal influenza virus and other lung injury states such as Acute Respiratory Distress Syndrome (ARDS), remains poorly understood. To address these challenges, we combined transcriptional profiling of 646 clinical nasopharyngeal swabs and 39 patient autopsy tissues, matched with spatial protein and expression profiling (GeoMx) across 357 tissue sections. These results define both body-wide and tissue-specific (heart, liver, lung, kidney, and lymph nodes) damage wrought by the SARS-CoV-2 infection, evident as a function of varying viral load (high vs. low) during the course of infection and specific, transcriptional dysregulation in splicing isoforms, T cell receptor expression, and cellular expression states. In particular, cardiac and lung tissues revealed the largest degree of splicing isoform switching and cell expression state loss. Overall, these findings reveal a systemic disruption of cellular and transcriptional pathways from COVID-19 across all tissues, which can inform subsequent studies to combat the mortality of COVID-19, as well to better understand the molecular dynamics of lethal SARS-CoV-2 infection and other viruses.

microbiology↗

bioRxiv2020

NASA GeneLab RNA-Seq Consensus Pipeline: Standardized Processing of Short-Read RNA-Seq Data

With the development of transcriptomic technologies, we are able to quantify precise changes in gene expression profiles from astronauts and other organisms exposed to spaceflight. Members of NASA GeneLab and GeneLab-associated analysis working groups (AWGs) have developed a consensus pipeline for analyzing short-read RNA-sequencing data from spaceflight-associated experiments. The pipeline includes quality control, read trimming, mapping, and gene quantification steps, culminating in the detection of differentially expressed genes. This data analysis pipeline and the results of its execution using data submitted to GeneLab are now all publicly available through the GeneLab database. We present here the full details and rationale for the construction of this pipeline in order to promote transparency, reproducibility and reusability of pipeline data, to provide a template for data processing of future spaceflight-relevant datasets, and to encourage cross-analysis of data from other databases with the data available in GeneLab.

bioinformatics↗

bioRxiv2020

Hidden genomic diversity of SARS-CoV-2: implications for qRT-PCR diagnostics and transmission

The COVID-19 pandemic has sparked an urgent need to uncover the underlying biology of this devastating disease. Though RNA viruses mutate more rapidly than DNA viruses, there are a relatively small number of single nucleotide polymorphisms (SNPs) that differentiate the main SARS-CoV-2 clades that have spread throughout the world. In this study, we investigated over 7,000 SARS-CoV-2 datasets to unveil both intrahost and interhost diversity. Our intrahost and interhost diversity analyses yielded three major observations. First, the mutational profile of SARS-CoV-2 highlights iSNV and SNP similarity, albeit with high variability in C>T changes. Second, iSNV and SNP patterns in SARS-CoV-2 are more similar to MERS-CoV than SARS-CoV-1. Third, a significant fraction of small indels fuel the genetic diversity of SARS-CoV-2. Altogether, our findings provide insight into SARS-CoV-2 genomic diversity, inform the design of detection tests, and highlight the potential of iSNVs for tracking the transmission of SARS-CoV-2.

genomics↗