Biology subjects

Rasko, D. A.

Publications and source records attributed to Rasko, D. A..

7 recordsLinked to original sources

bioRxiv2024

Deciphering Bacterial and Archaeal Transcriptional Dark Matter and Its Architectural Complexity

Transcripts are potential therapeutic targets, yet bacterial transcripts remain biological dark matter with uncharacterized biodiversity. We developed and applied an algorithm to predict transcripts for Escherichia coli K12 and E2348/69 strains (Bacteria:gamma-Proteobacteria) with newly generated ONT direct RNA sequencing data while predicting transcripts for Listeria monocytogenes strains Scott A and RO15 (Bacteria:Firmicute), Pseudomonas aeruginosa strains SG17M and NN2 strains (Bacteria:gamma-Proteobacteria), and Haloferax volcanii (Archaea:Halobacteria) using publicly available data. From >5 million E. coli K12 ONT direct RNA sequencing reads, 2,484 mRNAs are predicted and contain more than half of the predicted E. coli proteins. While the number of predicted transcripts varied by strain based on the amount of sequence data used for the predictions, across all strains examined, the average size of the predicted mRNAs is 1.6-1.7 kbp while the median size of the predicted bacterial 5-and 3-UTRs are 30-90 bp. Given the lack of bacterial and archaeal transcript annotation, most predictions are of novel transcripts, but we also predicted many previously characterized mRNAs and ncRNAs, including post-transcriptionally generated transcripts and small RNAs associated with pathogenesis in the E. coli E2348/69 LEE pathogenicity islands. We predicted small transcripts in the 100-200 bp range as well as >10 kbp transcripts for all strains, with the longest transcript for two of the seven strains being the nuo operon transcript, and for another two strains it was a phage/prophage transcript. This quick, easy, inexpensive, and reproducible method will facilitate the presentation of operons, transcripts, and UTR predictions alongside CDS and protein predictions in bacterial genome annotation as important resources for the research community.

genomics↗

bioRxiv2021

Informing shigellosis prevention and control through pathogen genomics

Shigella spp. are the leading bacterial cause of severe childhood diarrhoea in low- and middle-income countries (LMIC), are increasingly antimicrobial resistant and have no licensed vaccine. We performed genomic analyses of 1246 systematically collected shigellae from seven LMIC to inform control and identify factors that could limit the effectiveness of current approaches. We found that S. sonnei contributes [≥]20-fold more disease than other Shigella species relative to its genomic diversity and highlight existing diversity and adaptative capacity among S. flexneri that may generate vaccine escape variants in <6 months. Furthermore, we show convergent evolution of resistance against the current recommended antimicrobial among shigellae. This demonstrates the urgent need to integrate existing genomic diversity into vaccine and treatment plans for Shigella, and other pathogens.

microbiology↗

bioRxiv2020

Comparison of long read sequencing technologies in resolving bacteria and fly genomes

BackgroundThe newest generation of DNA sequencing technology is highlighted by the ability to sequence reads hundreds of kilobases in length, and the increased availability of long read data has democratized the genome sequencing and assembly process. PacBio and Oxford Nanopore Technologies (ONT) have pioneered competitive long read platforms, with more recent work focused on improving sequencing throughput and per-base accuracy. Released in 2019, the PacBio Sequel II platform advertises substantial enhancements over previous PacBio systems. ResultsWe used whole-genome sequencing data produced by two PacBio platforms (Sequel II and RS II) and two ONT protocols (Rapid Sequencing and Ligation Sequencing) to compare assemblies of the bacteria Escherichia coli and the fruit fly Drosophila ananassae. Sequel II assemblies had higher contiguity and consensus accuracy relative to other methods, even after accounting for differences in sequencing throughput. ONT RAPID libraries had the fewest chimeric reads in addition to superior quantification of E. coli plasmids versus ligation-based libraries. The quality of assemblies can be enhanced by adopting hybrid approaches using Illumina libraries for bacterial genome assemblies or combined ONT and Sequel II libraries for eukaryotic genome assemblies. Genome-wide DNA methylation could be detected using both technologies, however ONT libraries enabled the identification of a broader range of known E. coli methyltransferase recognition motifs in addition to undocumented D. ananassae motifs. ConclusionsThe ideal choice of long read technology may depend on several factors including the question or hypothesis under examination. No single technology outperformed others in all metrics examined.

genomics↗

bioRxiv2020

Host Adaptation Predisposes Pseudomonas aeruginosa to Type VI Secretion System-Mediated Predation by the Burkholderia cepacia Complex

Pseudomonas aeruginosa (Pa) and Burkholderia cepacia complex (Bcc) species are opportunistic lung pathogens of individuals with cystic fibrosis (CF). While Pa can initiate long-term infections in younger CF patients, Bcc infections only arise in teenagers and adults. Both Pa and Bcc use type VI secretion systems (T6SS) to mediate interbacterial competition. Here, we show that Pa isolates from teenage/adult CF patients, but not those from young CF patients, are outcompeted by the epidemic Bcc isolate Burkholderia cenocepacia strain AU1054 (BcAU1054) in a T6SS-dependent manner. The genomes of susceptible Pa isolates harbor T6SS-abrogating mutations, the repair of which, in some cases, rendered the isolates resistant. Moreover, seven of eight Bcc strains outcompeted Pa strains isolated from the same patients. Our findings suggest that certain mutations that arise as Pa adapts to the CF lung abrogate T6SS activity, making Pa and its human host susceptible to potentially fatal Bcc superinfection.

microbiology↗

bioRxiv2018

Cost Effective, Experimentally Robust Differential Expression Analysis for Human/Mammalian, Pathogen, and Dual-Species Transcriptomics

As sequencing read length has increased, researchers have quickly adopted longer reads for their experiments. Here, we examine host-pathogen interaction studies to assess if using longer reads is warranted. Six diverse datasets encountered in studies of host-pathogen interactions were used to assess what genomic attributes might affect the outcome of differential gene expression analysis including: gene density, operons, gene length, number of introns/exons, and intron length. Principal components analysis, hierarchical clustering with bootstrap support, and regression analyses of pairwise comparisons were undertaken on the same reads, looking at all combinations of paired and unpaired reads trimmed to 36,54,72, and 101-bp. For E coli, 36-bp single end reads performed as well as any other read length and as well as paired end reads. For all other comparisons, 54-bp and 72-bp reads were typically equivalent and different from 36-bp and 101-bp reads. Read pairing improved the outcome in several, but not all, comparisons in no discernable pattern, such that using paired reads is recommended in most scenarios. No specific genome attribute appeared to influence the data. However, experiments with an a priori expected greater biological complexity had more variable results with all read lengths relative to those with decreased complexity. When combined with cost, 54-bp paired end reads provided the most robust, internally reproducible results across all comparisons. However, using 36-bp single end reads may be desirable for bacterial samples, although possibly only if the transcriptional response is expected a priori to be robust.\n\nDATA SUMMARYO_LIThe human only CSHL Encode data set (1) was downloaded from ftp://hgdownload.cse.ucsc.edu/goldenPath/hgl9/encodeDCC/wgEncodeCshlLongRnaSeq/.\nC_LIO_LIThe data from mice vaginas infected with Candida albicans (2) was downloaded from the SRA (url - https://trace.ncbi.nlm.nih.gov/Traces/sra/?study=SRP057050).\nC_LIO_LIThe data from Aspergillus fumigatus cells in contact with human cells was downloaded from the SRA (url - https://www.ncbi.nlm.nih.gov/bioproject/399754).\nC_LIO_LIThe data from a strand-specific library from a study comparing C. albicans cells in contact with human cells with those in media (3) was downloaded from the SRA (url - https://trace.ncbi.nlm.nih.gov/Traces/sra/?study=SRP011085).\nC_LIO_LIThe data from C. albicans in culture media (3) was downloaded from the SRA (url - https://trace.ncbi.nlm.nih.gov/Traces/sra/?study=SRP011085).\nC_LIO_LIThe data from Escherichia coli grown in different media (4) was downloaded from the SRA (url - https://trace.ncbi.nlm.nih.gov/Traces/sra/?study=SRP056578).\nC_LI\n\nI/We confirm all supporting data, code and protocols have been provided within the article or through supplementary data files. {boxtimes}\n\nIMPACT STATEMENTAs sequencing technologies improve, sequencing costs decrease and read lengths increase. We examine host-pathogen interaction studies to assess if using these longer reads is warranted given their increased cost relative to using the same number of shorter reads. To this end we compared the use of various read lengths and read pairing for six diverse host-pathogen datasets with varying genomic attributes including: gene density, operons, gene length, number of introns/exons, and intron length. We find that in the bacterial sample, 36-bp single end reads performed as well as any other read length and as well as paired end reads. When combined with cost, 54-bp paired end reads provided the most robust, internally reproducible results for all other comparisons. Read pairing improved the outcome in several, but not all, comparisons in no discernable pattern, such that using paired reads is recommended in most scenarios. No specific genome attribute appeared to influence the data.

genomics↗

bioRxiv2018

FADU: A Feature Counting Tool for Prokaryotic RNA-Seq Analysis

MotivationThe major algorithms for quantifying transcriptomics data for differential gene expression analysis were designed for analyzing data from human or human-like genomes, specifically those with single gene transcripts and distinct transcriptional boundaries that extend beyond the coding sequence (CDS) as identified through expressed sequence tags (ESTs) or EST-like sequence data. Some eukaryotic genomes and all, or nearly all, bacterial genomes require alternate methods of quantification since they lack annotation of transcriptional boundaries with EST or EST-like data, have overlapping transcriptional boundaries, and/or have polycistronic transcripts.\n\nResultsAn algorithm was developed and tested that better quantifies transcriptomics data for differential gene expression analysis in organisms with overlapping transcriptional units and polycistronic transcripts. Using data from standard libraries originating from Escherichia coli and Ehrlichia chaffeensis, and strand-specific libraries from the Wolbachia endosymbiont wBm, FADU can derive counts for genes that are missed by HTSeq and featurecounts. Using the default parameters with the E. coli data, FADU can detect transcription of 51 more genes than HTSeq in union mode and 21 genes more than featurecounts, with 42 and 18 of these features being <300 bp, respectively. Due to its ability to derive counts for otherwise unrepresented genes without overstating their abundance, we believe FADU to be an improved tool for quantifying transcripts in prokaryotic systems for RNA-Seq analyses.\n\nAvailability and implementationFADU is available at https://github.com/adkinsrs/FADU. FADU was implemented using Python3 and requires the PySAM module (version 0.12.0.1 or later).\n\nContactjdhotopp@som.umaryland.edu

genomics↗

bioRxiv2018

Population dynamics of Escherichia coli in the gastrointestinal tracts of Tanzanian children

The stability of the Escherichia coli populations in the human gastrointestinal tract are not fully appreciated, and represent a significant knowledge gap regarding gastrointestinal community structure, as well as resistance to incoming pathogenic bacterial species and antibiotic treatment. The current study examines the genomic content of 240 Escherichia coli isolates from children 2 to 35 months old in Tanzania. The E. coli strains were isolated from three time points spanning a six month time period, with or without antibiotic treatment. The resulting isolates were sequenced, and the genomes compared. The findings in this study highlight the transient nature of E. coli strains in the gastrointestinal tract of children, as during a six-month interval, no one individual contained phylogenomically related isolates at all three time points. While the majority of the isolates at any one time point were phylogenomically similar, most individuals did not contain phylogenomically similar isolates at more than two time points. Examination of global genome content, canonical E. coli virulence factors, multilocus sequence type, serotype, and antimicrobial resistance genes identified diversity even among phylogenomically similar strains. There was no apparent increase in the antimicrobial resistance gene content after antibiotic treatment. The examination of the E. coli from longitudinal samples from multiple children in Tanzania provides insight into the genomic diversity and population variability of resident E. coli within the rapidly changing environment of the gastrointestinal tract.\n\nImportanceThis study increases the number of resident Escherichia coli genome sequences, and explores E. coli diversity through longitudinal sampling. We investigate the genomes of E. coli isolated from human gastrointestinal tracts as part of an antibiotic treatment program among rural Tanzanian children. Phylogenomics demonstrates that resident E. coli are diverse, even within a single host. Though the E. coli isolates of the gastrointestinal community tend to be phylogenomically similar at a given time, they differed across the interrogated time points, demonstrating the variability of the members of the E. coli community. Exposure to antibiotic treatment did not have an apparent impact on the E. coli community or the presence of resistance and virulence genes within E. coli genomes. The findings of this study highlight the variable nature of bacterial members of the human gastrointestinal tract.

microbiology↗