Biology subjects

Bezdan, D.

Publications and source records attributed to Bezdan, D..

12 recordsLinked to original sources

bioRxiv2024

Spaceflight alters host-gut microbiota interactions

The rodent habitat on the International Space Station has provided crucial insights into the impact of spaceflight on mammals, including observation of symptoms characteristic of liver disease, insulin resistance, osteopenia and myopathy. Although these physiological responses can involve the microbiome when observed on Earth, changes in host-microbiota interactions during spaceflight are still being elucidated. Here, NASA GeneLab multiomic data from the Rodent Research 6 mission are used to determine changes to gut microbiota and murine host colon and liver gene expression after 29 and 56-days of spaceflight. Using hybrid amplicon and whole metagenome sequencing analysis, significant spaceflight-associated alterations to 42 microbiome species were identified. These included relative reductions of bacteria associated with bile acid and butyrate metabolism, such as Extibacter muris and Dysosmobacter welbionis. Functional prediction suggested over-representation of fatty acid and bile acid metabolism, extracellular matrix interactions, and antibiotic resistance genes within the gut microbiome, while host intestinal and hepatic gene expression described corresponding changes to host bile acid and energy metabolism, and immune suppression from spaceflight. Taken together, these changes imply that interactions at the host-gut microbiome interface contribute to spaceflight pathology and highlight how these interactions might critically influence human health and the feasibility of long-duration spaceflight.

genomics↗

bioRxiv2021

MapToCleave: high-throughput profiling of microRNA biogenesis in living cells

Previous large-scale studies have uncovered many features that determine the processing of microRNA (miRNA) precursors, however, they have been conducted in vitro. Here we introduce MapToCleave, a new method to simultaneously profile processing of thousands of distinct RNA structures in living cells. Our new in cell method captures essentially all the biogenesis features that have been discovered through near two decades of in vitro studies - providing support for both approaches. We find that miRNA precursors with a stable lower basal stem are more efficiently processed and also have higher expression in vivo in tissues from twenty animal species. We systematically compare the importance of known and novel sequence and structural features and test biogenesis of miRNA precursors from ten animal and plant species in human cells. Lastly, we provide evidence that the GHG motif better predicts processing when defined as a structure rather than sequence motif, consistent with recent cryo-EM studies. In summary, we apply a new screening assay in living cells to reveal the importance of lower basal stem stability for miRNA processing and in vivo expression.

molecular biology↗

bioRxiv2020

Genetic Evidence for Selective Transfer of Microbes Between the International Space Station and an Astronaut

Microbial transfer from the environment can influence a persons health, but relevant studies often have confounding variables and short durations. Here, we used the unique environment of the International Space Station (ISS) to track movement of microbes between an astronauts commensal microbiomes and their environment. We identified several microbial taxa, including Serratia proteamaculans and Rickettsia australis which appear to have been transferred from the ISS to the commensal microbiomes of the astronaut. Strains were matched at the SNP and haplotype-level, and notably some strains persisted even after the astronauts return to Earth. Some transferred taxa correspond to secondary strains in the ISS environment, suggesting that transfer may be mediated by evolutionary selection. Finally, we show evidence that the T-Cell repertoire of the astronaut changes to become more specific to environmental taxa, suggesting that continual microbial and immune monitoring can help guide spaceflight mission planning, health monitoring, and habitat design.

microbiology↗

bioRxiv2020

Cell-free DNA (cfDNA) and exosome profiling from a year-long humanspaceflight reveals circulating biomarkers

The health impact of prolonged space flight on the human body is not well understood. Liquid biopsies based on cell-free DNA (cfDNA) or exosome analysis provide a noninvasive approach to monitor the dynamics of genomic, epigenomic and proteomic biomarkers, and the occurrence of DNA damage, physiological stress, and immune responses. To study the molecular consequences of spaceflight we profiled cfDNA isolated from plasma of an astronaut (TW) during a year-long mission on the International Space Station (ISS), sampling before, during, and after spaceflight, and compared the results to cfDNA profiling of the subjects identical twin (HR) who remained on Earth, as well as healthy donors. We characterized cfDNA concentration and fragment size, and the positioning of nucleosomes on cfDNA, observing a significant increase in the proportion of cell-free mitochondrial DNA inflight, suggesting that cf-mtDNA is a potential biomarker for space flight-associated stress, and that this result was robust to ambient transit from the International Space Station (ISS). Analysis of exosomes isolated from post-flight plasma revealed a 30-fold increase in circulating exosomes and distinct exosomal protein cargo, including brain-derived peptides, in TW compared to HR and all known controls. This study provides the first longitudinal analysis of astronaut cfDNA during spaceflight, as well as the first exosome profiles, and highlights cf-mtDNA levels as a potential biomarker for physiological stress or immune system responses related to microgravity, radiation exposure, and other unique environmental conditions on the ISS.

cell biology↗

bioRxiv2020

Host, Viral, and Environmental Transcriptome Profiles of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2)

The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has caused thousands of deaths worldwide, including >18,000 in New York City (NYC) alone. The sudden emergence of this pandemic has highlighted a pressing clinical need for rapid, scalable diagnostics that can detect infection, interrogate strain evolution, and identify novel patient biomarkers. To address these challenges, we designed a fast (30-minute) colorimetric test (LAMP) for SARS-CoV-2 infection from naso/oropharyngeal swabs, plus a large-scale shotgun metatranscriptomics platform (total-RNA-seq) for host, bacterial, and viral profiling. We applied both technologies across 857 SARS-CoV-2 clinical specimens and 86 NYC subway samples, providing a broad molecular portrait of the COVID-19 NYC outbreak. Our results define new features of SARS-CoV-2 evolution, nominate a novel, NYC-enriched viral subclade, reveal specific host responses in interferon, ACE, hematological, and olfaction pathways, and examine risks associated with use of ACE inhibitors and angiotensin receptor blockers. Together, these findings have immediate applications to SARS-CoV-2 diagnostics, public health, and new therapeutic targets.

molecular biology↗

bioRxiv2020

Haplotype Diversity and Sequence Heterogeneity of Human Telomeres

Telomeres are regions of repetitive nucleotide sequences capping the ends of eukaryotic chromosomes that protect against deterioration, whose lengths can be correlated with age and disease risk factors. Given their length and repetitive nature, telomeric regions are not easily reconstructed from short read sequencing, making telomere sequence resolution a very costly and generally intractable problem. Recently, long-read sequencing, with read lengths measuring in hundreds of Kbp, has made it possible to routinely read into telomeric regions and inspect their structure. Here, we describe a framework for extracting telomeric reads from single-molecule sequencing experiments, describing their sequence variation and motifs, and for haplotype inference. We find that long telomeric stretches can be accurately captured with long-read sequencing, observe extensive sequence heterogeneity of human telomeres, discover and localize non-canonical motifs (both previously reported as well as novel), and report the first motif composition maps of human telomeric diplotypes on a multi-Kbp scale.

genomics↗

bioRxiv2019

Global Genetic Cartography of Urban Metagenomes andAnti-Microbial Resistance

We have created a global atlas of 4,728 metagenomic samples from mass-transit systems in 60 cities across 3 years. This is the first systematic, worldwide study cataloging the urban microbial ecosystem. We identify taxonomically-defined microorganisms collected across three years. This atlas provides an annotated, geospatial profile of microbial strains, functional characteristics AMR markers, and novel genetic elements, including 10,928 viral, 1302 bacteria, and 2 archaea novel species. We identify 4,424 species of urban microorganisms and a consistent "core" of 31 species found in nearly all samples that is largely distinct from any human commensal microbiome. Profiles of AMR genes show geographic variation in type and density. Together, these results constitute a high-resolution, global metagenomic atlas, which enables the discovery of new genetic components, highlights potential forensic applications, and provides an essential first draft of the global AMR burden of the worlds cities.

microbiology↗

bioRxiv2019

Tracking of antibiotic resistance transfer and rapid plasmid evolution in a hospital setting by Nanopore sequencing

BackgroundInfection of patients with multidrug-resistant (MDR) bacteria often leave very limited or no treatment options. The transfer of antimicrobial resistance genes (ARG) carrying plasmids between bacterial species by horizontal gene transfer represents an important mode of expansion of ARGs. Here, we evaluated the application of Nanopore sequencing technology in a hospital setting for monitoring the transfer and rapid evolution of antibiotic resistance plasmids within and across multiple species.\n\nResultsIn 2009 we experienced an outbreak with an extensively multidrug resistant P. aeruginosa harboring the carbapenemase enzyme blaIMP-8, and in 2012 the first Citrobacter freundii and Citrobacter werkmanii harboring the same enzyme were detected. Using Nanopore and Illumina sequencing we conducted a comparative analysis of all blaIMP-8 bacteria isolated in our hospital over a 6-year period (n = 54). We developed the computational platforms pathoLogic and plasmIDent for Nanopore-based characterization of clinical isolates and monitoring of ARG transfer, comprising de-novo assembly of genomes and plasmids, polishing, QC, plasmid circularization, ARG annotation, comparative genome analysis of multiple isolates and visualization of results. Using plasmIDent we identified a 40 kb plasmid carrying blaIMP-8 in P. aeruginosa and C. freundii, verifying that plasmid transfer had occurred. Within C. freundii the plasmid underwent further evolution and plasmid fusion, resulting in a 164 kb mega-plasmid, which was transferred to C. werkmanii. Moreover, multiple rearrangements of the multidrug resistance gene cassette were detected in P. aeruginosa, including deletions and translocations of complete ARGs.\n\nConclusionPlasmid transfer, plasmid fusion and rearrangement of the multidrug resistance gene cassette mediated the rapid evolution of opportunistic pathogens in our hospital. We demonstrated the feasibility of tracking plasmid evolution dynamics and ARG transfer in clinical settings in a timely manner. The approach will allow for successful countermeasures to contain not only clonal, but also plasmid mediated outbreaks.

genomics↗

bioRxiv2019

Novel Algorithms for the Taxonomic Classification of Metagenomic Linked Reads

We present KrakenLinked, a metagenomic read classifier for Linked-Reads. We have formulated two algorithms for read classification of metagenomic samples using linked reads: tree pruning and taxa promotion. Tree pruning improves specificity while taxa promotion improves sensitivity. Used together the algorithms improve taxonomic classification of linked-reads compared to short reads, particularly reducing false identification of taxa. We have implemented these algorithms as functions in KrakenUniq which we make available as KrakenLinked.

bioinformatics↗

bioRxiv2018

Ozone Treatment for Elimination of Bacteria in Medical Environments

Pathogenic bacteria and viruses in medical environments can lead to treatment complications and hospital-acquired infections (HAIs), and current cleaning protocols do not address hard-to-access areas or that may be beyond line-of-sight treatment such as with ultraviolet radiation. At the time of writing, the ongoing pandemic of the novel coronavirus known as novel coronavirus (2019-nCoV) has claimed over 4 million cases worldwide and is expected to have multiple peaks, with possible resurgences throughout 2020. It is therefore imperative that disinfection methods in the meantime be employed to keep up with the supply of personal protective equipment (PPE) and sterilize a wide array of surfaces as quarantine lockdowns begin to be lifted. Here, we tested the efficacy of Sani Sport ozone devices as a means to treat hospital equipment and surfaces for killing bacteria, degrading synthetic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA, and RNA from non-replicative capsid enclosed SARS-CoV-2. We observed a rapid killing of medically-relevant and environmental bacteria (Escherichia coli, Enterococcus faecalis, Bacillus subtlis, and Deinococcus radiodurans) across four surfaces (blankets, catheter, remotes, and syringes) within 30 minutes, and up to a 99% reduction in viable bacteria at the end of 2-hour treatment cycles. Significant RNA degradation of synthetic SARS-CoV-2 RNA was seen an hour into the ozone treatment as compared to non-treated controls and a non-replicative form of the virus was shown to have significant RNA degradation at 30 minutes compared to a no treatment control and RNA degradation could be reliably detected at 10,000 and 1,000 copies of virus per sample. These results show the strong promise of ozone treatment for reducing risk of infection and HAIs.

microbiology↗

bioRxiv2018

Multi-omics approach identifies novel pathogen-derived prognostic biomarkers in patients with Pseudomonas aeruginosa bloodstream infection

Pseudomonas aeruginosa is a human pathogen that causes health-care associated blood stream infections (BSI). Although P. aeruginosa BSI are associated with high mortality rates, the clinical relevance of pathogen-derived prognostic biomarker to identify patients at risk for unfavorable outcome remains largely unexplored. We found novel pathogen-derived prognostic biomarker candidates by applying a multi-omics approach on a multicenter sepsis patient cohort. Multi-level Cox regression was used to investigate the relation between patient characteristics and pathogen features (2298 accessory genes, 1078 core protein levels, 107 parsimony-informative variations in reported virulence factors) with 30-day mortality. Our analysis revealed that presence of the helP gene encoding a putative DEAD-box helicase was independently associated with a fatal outcome (hazard ratio 2.01, p = 0.05). helP is located within a region related to the pathogenicity island PAPI-1 in close proximity to a pil gene cluster, which has been associated with horizontal gene transfer. Besides helP, elevated protein levels of the bacterial flagellum protein FliL (hazard ratio 3.44, p < 0.001) and of a bacterioferritin-like protein (hazard ratio 1.74, p = 0.003) increased the risk of death, while high protein levels of a putative aminotransferase were associated with an improved outcome (hazard ratio 0.12, p < 0.001). The prognostic potential of biomarker candidates and clinical factors was confirmed with different machine learning approaches using training and hold-out datasets. The helP genotype appeared the most attractive biomarker for clinical risk stratification due to its relevant predictive power and ease of detection.

microbiology↗

bioRxiv2017

Minerva: An Alignment and Reference Free Approach to Deconvolve Linked-Reads for Metagenomics

Emerging Linked-Read technologies (aka Read-Cloud or barcoded short-reads) have revived interest in standard short-read technology as a viable way to understand large-scale structure in genomes and metagenomes. Linked-Read technologies, such as the 10X Chromium system, use a microfluidic system and a set of specially designed 3 barcodes (aka UIDs) to tag short DNA reads which were originally sourced from the same long fragment of DNA; subsequently, these specially barcoded reads are sequenced on standard short read platforms. This approach results in interesting compromises. Each long fragment of DNA is covered only sparsely by short reads, no information about the relative ordering of reads from the same fragment is preserved, and typically each 3 barcode matches reads from 2-20 long fragments of DNA. However, compared to long read platforms like those produced by Pacific Biosciences and Oxford Nanopore the cost per base to sequence is far lower, far less input DNA is required, and the per base error rate is that of Illumina short-reads.\n\nThe use of Linked-Reads presents a new set of algorithmic challenges. In this paper, we formally describe one particular issue common to all applications of Linked-Read technology: the deconvolution of reads with a single 3 barcode into clusters that correspond to a single long fragment of DNA. We introduce Minerva, A graph-based algorithm that approximately solves the barcode deconvolution problem for metagenomic data (where reference genomes may be incomplete or unavailable). Additionally, we develop two demonstrations where the deconvolution of barcoded reads improves downstream results: improving the specificity of taxonomic assignments, and by improving clustering of related sequences. To the best of our knowledge, we are the first to address the problem of barcode deconvolution in metagenomics.

bioinformatics↗