scholarly journals Network analysis reveals differential metabolic functionality in antibiotic-resistantPseudomonas aeruginosa

2018 ◽  
Author(s):  
Laura J. Dunphy ◽  
Phillip Yen ◽  
Jason A. Papin
Keyword(s):  
Antibiotic Resistance ◽  
Carbon Sources ◽  
Growth Dynamics ◽  
Metabolic Phenotype ◽  
Metabolic Adaptation ◽  
Whole Genome Sequencing Data ◽  
Sequencing Data ◽  
Drug Induced ◽  
Antibiotic Resistant ◽  
A Genome

AbstractMetabolic adaptations accompanying the development of antibiotic resistance in bacteria remain poorly understood. To interrogate this relationship, we profiled the growth of lab-evolved antibiotic-resistant lineages of the opportunistic pathogenPseudomonas aeruginosaacross 190 unique carbon sources. We semi-automatically calculated growth dynamics (maximum growth density, growth rate, and time to mid-exponential phase) of over 2,800 growth curves. These data revealed that the evolution of antibiotic resistance resulted in systems-level changes to growth dynamics and metabolic phenotype. Drug-resistant lineages predominantly displayed decreased growth relative to the ancestral lineage; however, resistant lineages occasionally displayed enhanced growth on certain carbon sources, indicating that adaption to drug can provide a growth advantage in certain environments. A genome-scale metabolic network reconstruction (GENRE) ofP. aeruginosastrain UCBPP-PA14 was paired with whole-genome sequencing data of one of the drug-evolved lineages to predict genes contributing to observed changes in metabolism. Finally, we experimentally validatedin silicopredictions to identify genes mutated in resistantP. aeruginosaaffecting loss of catabolic function. Our results build upon previous mechanistic knowledge of drug-induced metabolic adaptation and provide a framework for the identification of metabolic limitations in antibiotic-resistant pathogens. Robust drug-driven changes in bacterial metabolism have the potential to be exploited to select against antibiotic-resistant populations in chronic infections.

scholarly journals MTBseq: a comprehensive pipeline for whole genome sequence analysis of Mycobacterium tuberculosis complex isolates

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e5895 ◽  
Author(s):  
Thomas Andreas Kohl ◽  
Christian Utpatel ◽  
Viola Schleusener ◽  
Maria Rosaria De Filippo ◽  
Patrick Beckert ◽  
...  
Keyword(s):  
Antibiotic Resistance ◽  
Mycobacterium Tuberculosis ◽  
Genome Sequence ◽  
Sequence Data ◽  
Whole Genome Sequence ◽  
Whole Genome Sequencing Data ◽  
Phylogenomic Analysis ◽  
Whole Genome ◽  
Sequencing Data ◽  
Desktop Computer

Analyzing whole-genome sequencing data of Mycobacterium tuberculosis complex (MTBC) isolates in a standardized workflow enables both comprehensive antibiotic resistance profiling and outbreak surveillance with highest resolution up to the identification of recent transmission chains. Here, we present MTBseq, a bioinformatics pipeline for next-generation genome sequence data analysis of MTBC isolates. Employing a reference mapping based workflow, MTBseq reports detected variant positions annotated with known association to antibiotic resistance and performs a lineage classification based on phylogenetic single nucleotide polymorphisms (SNPs). When comparing multiple datasets, MTBseq provides a joint list of variants and a FASTA alignment of SNP positions for use in phylogenomic analysis, and identifies groups of related isolates. The pipeline is customizable, expandable and can be used on a desktop computer or laptop without any internet connection, ensuring mobile usage and data security. MTBseq and accompanying documentation is available from https://github.com/ngs-fzb/MTBseq_source.

scholarly journals Integrating Culture-based Antibiotic Resistance Profiles with Whole-genome Sequencing Data for 11,087 Clinical Isolates

2019 ◽  
Vol 17 (2) ◽  
pp. 169-182 ◽  
Author(s):  
Valentina Galata ◽  
Cédric C. Laczny ◽  
Christina Backes ◽  
Georg Hemmrich-Stanisak ◽  
Susanne Schmolke ◽  
...  
Keyword(s):  
Antibiotic Resistance ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Clinical Isolates ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Sequencing Data

scholarly journals Draft Genome Sequences of Ciprofloxacin-Resistant Salmonella enterica Strains with Multiple-Antibiotic Resistance, Isolated from Imported Foods

2017 ◽  
Vol 5 (45) ◽  
Author(s):  
Ashraf A. Khan ◽  
Bijay K. Khajanchi ◽  
Sana A. Khan ◽  
Christopher A. Elkins ◽  
Steven L. Foley
Keyword(s):  
Antibiotic Resistance ◽  
Salmonella Enterica ◽  
Draft Genome ◽  
Resistance Mechanisms ◽  
Whole Genome Sequencing Data ◽  
Sequencing Data ◽  
Genome Sequences ◽  
Content Type ◽  
Imported Foods ◽  
High Level

ABSTRACT We report here the draft genome sequences of 15 ciprofloxacin-resistant Salmonella enterica strains with resistance to multiple other antibiotics, including aminoglycosides, β-lactams, sulfonamides, tetracycline, and trimethoprim, isolated from different imported foods. Three strains (NCTR75, NCTR281, and NCTR350) showed a high level of ciprofloxacin resistance compared to that of the other isolates. The whole-genome sequencing data provide a better understanding of the antibiotic resistance mechanisms and virulence properties of these isolates.

scholarly journals Local Ancestry Prediction with PyLAE

2020 ◽  
Author(s):  
Alexander Smetanin ◽  
Nikita Moshkov ◽  
Tatiana V. Tatarinova
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Computational Efficiency ◽  
Source Code ◽  
High Density ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Sequencing Data ◽  
Local Ancestry ◽  
A Genome

AbstractSummaryWe developed PyLAE - a new tool for determining local ancestry along a genome using whole-genome sequencing data or high-density genotyping experiments. PyLAE can process an arbitrarily large number of ancestral populations (with or without an informative prior). Since PyLAE does not involve estimation of many parameters, it can process thousands of genomes within a day. Computational efficiency, straightforward presentation of results, and an ease of installation makes PyLAE a useful tool to study admixed populations.Availability and implementationThe source code and installation manual are available at https://github.com/smetam/pylae.

scholarly journals TETyper: a bioinformatic pipeline for classifying variation and genetic contexts of transposable elements from short-read whole-genome sequencing data

2018 ◽  
Author(s):  
Anna E Sheppard ◽  
Nicole Stoesser ◽  
Ian German-Mesner ◽  
Kasi Vegesana ◽  
A Sarah Walker ◽  
...  
Keyword(s):  
Antibiotic Resistance ◽  
Transposable Elements ◽  
Genome Sequencing ◽  
Resistance Genes ◽  
Whole Genome Sequencing Data ◽  
Sequence Variants ◽  
Whole Genome ◽  
Sequencing Data ◽  
Bioinformatic Pipeline ◽  
Short Read

ABSTRACTMuch of the worldwide dissemination of antibiotic resistance has been driven by resistance gene associations with mobile genetic elements (MGEs), such as plasmids and transposons. Although increasing, our understanding of resistance spread remains relatively limited, as methods for tracking mobile resistance genes through multiple species, strains and plasmids are lacking. We have developed a bioinformatic pipeline for tracking variation within, and mobility of, specific transposable elements (TEs), such as transposons carrying antibiotic resistance genes. TETyper takes short-read whole-genome sequencing data as input and identifies single-nucleotide mutations and deletions within the TE of interest, to enable tracking of specific sequence variants, as well as the surrounding genetic context(s), to enable identification of transposition events. To investigate global dissemination of Klebsiella pneumoniae carbapenemase (KPC) and its associated transposon Tn4401, we applied TETyper to a collection of >3000 publicly available Illumina datasets containing blaKPC. This revealed surprising diversity, with >200 distinct flanking genetic contexts for Tn4401, indicating high levels of transposition. Integration of sample metadata revealed insights into associations between geographic locations, host species, Tn4401 sequence variants and flanking genetic contexts. To demonstrate the ability of TETyper to cope with high copy number TEs and to track specific short-term evolutionary changes, we also applied it to the insertion sequence IS26 within a defined K. pneumoniae outbreak. TETyper is implemented in python and is freely available at https://github.com/aesheppard/TETyper.

scholarly journals The shaping of immunological responses through natural selection after the Roma Diaspora

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Begoña Dobon ◽  
Rob ter Horst ◽  
Hafid Laayouni ◽  
Mayukh Mondal ◽  
Erica Bianco ◽  
...  
Keyword(s):  
Fungal Infections ◽  
Balkan Peninsula ◽  
Host Population ◽  
Human Migration ◽  
Whole Genome Sequencing Data ◽  
Sequencing Data ◽  
Immunological Responses ◽  
A Genome ◽  
Local Host ◽  
Northwest India

Abstract The Roma people are the largest transnational ethnic minority in Europe and can be considered the last human migration of South Asian origin into the continent. They left Northwest India approximately 1,000 years ago, reaching the Balkan Peninsula around the twelfth century and Romania in the fourteenth century. Here, we analyze whole-genome sequencing data of 40 Roma and 40 non-Roma individuals from Romania. We performed a genome-wide scan of selection comparing Roma, their local host population, and a Northwestern Indian population, to identify the selective pressures faced by the Roma mainly after they settled in Europe. We identify under recent selection several pathways implicated in immune responses, among them cellular metabolism pathways known to be rewired after immune stimulation. We validated the interaction between PIK3-mTOR-HIF-1α and cytokine response influenced by bacterial and fungal infections. Our results point to a significant role of these pathways for host defense against the most prevalent pathogens in Europe during the last millennium.

scholarly journals FindZX: an automated pipeline for detecting and visualising sex chromosomes using whole-genome sequencing data

2021 ◽  
Author(s):  
Hanna Sigeman ◽  
Bella Sinclair ◽  
Bengt Hansson
Keyword(s):  
Sex Chromosomes ◽  
Sex Chromosome ◽  
Whole Genome Sequencing Data ◽  
Sequencing Data ◽  
A Genome ◽  
Genomic Studies ◽  
Taxonomic Groups ◽  
User Friendly ◽  
Genomic Patterns

Sex chromosomes have evolved numerous times, as revealed by recent genomic studies. However, large gaps in our knowledge of sex chromosome diversity across the tree of life remain. Filling these gaps, through the study of novel species, is crucial for improved understanding of why and how sex chromosomes evolve. Characterization of sex chromosomes in already well-studied organisms is also important to avoid misinterpretations of population genomic patterns caused by undetected sex chromosome variation. Here we present findZX, an automated Snakemake-based computational pipeline for detecting and visualizing sex chromosomes through differences in genome coverage and heterozygosity between males and females. FindZX is user-friendly and scalable to suit different computational platforms and works with any number of male and female samples. An option to perform a genome coordinate lift-over to a reference genome of another species allows users to inspect sex- linked regions over larger contiguous chromosome regions, while also providing important between- species synteny information. To demonstrate its effectiveness, we applied findZX to publicly available genomic data from species belonging to widely different taxonomic groups (mammals, birds, reptiles, fish, and insects), with sex chromosome systems of different ages, sizes, and levels of differentiation. We also demonstrate that the lift-over method is robust over large phylogenetic distances (>80 million years of evolution).

scholarly journals Local ancestry prediction with PyLAE

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e12502
Author(s):  
Nikita Moshkov ◽  
Aleksandr Smetanin ◽  
Tatiana V. Tatarinova
Keyword(s):  
Genome Sequencing ◽  
Gold Standard ◽  
Source Code ◽  
Genomic Data ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Sequencing Data ◽  
Local Ancestry ◽  
1000 Genomes ◽  
A Genome

Summary We developed PyLAE, a new tool for determining local ancestry along a genome using whole-genome sequencing data or high-density genotyping experiments. PyLAE can process an arbitrarily large number of ancestral populations (with or without an informative prior). Since PyLAE does not involve estimating many parameters, it can process thousands of genomes within a day. PyLAE can run on phased or unphased genomic data. We have shown how PyLAE can be applied to the identification of differentially enriched pathways between populations. The local ancestry approach results in higher enrichment scores compared to whole-genome approaches. We benchmarked PyLAE using the 1000 Genomes dataset, comparing the aggregated predictions with the global admixture results and the current gold standard program RFMix. Computational efficiency, minimal requirements for data pre-processing, straightforward presentation of results, and ease of installation make PyLAE a valuable tool to study admixed populations. Availability and implementation The source code and installation manual are available at https://github.com/smetam/pylae.

scholarly journals Genome-wide profiling of heritable and de novo STR variations

2016 ◽  
Author(s):  
Thomas Willems ◽  
Dina Zielinski ◽  
Assaf Gordon ◽  
Melissa Gymrek ◽  
Yaniv Erlich
Keyword(s):  
Tandem Repeats ◽  
High Throughput Sequencing ◽  
De Novo ◽  
Genetic Diseases ◽  
Whole Genome Sequencing Data ◽  
Sequencing Data ◽  
High Throughput Sequencing Data ◽  
Genome Wide ◽  
A Genome ◽  
Short Tandem

AbstractShort tandem repeats (STRs) are highly variable elements that play a pivotal role in multiple genetic diseases, population genetics applications, and forensic casework. However, STRs have proven problematic to genotype from high-throughput sequencing data. Here, we describe HipSTR, a novel haplotype-based method for robustly genotyping, haplotyping, and phasing STRs from whole genome sequencing data and report a genome-wide analysis and validation of de novo STR mutations.

scholarly journals Investigating the Evolutionary Importance of Denisovan Introgressions in Papua New Guineans and Australians

2015 ◽  
Author(s):  
Ya Hu ◽  
Qiliang Ding ◽  
Yi Wang ◽  
Shuhua Xu ◽  
Yungang He ◽  
...  
Keyword(s):  
False Positive Rate ◽  
Whole Genome Sequencing Data ◽  
Phase Method ◽  
Sequencing Data ◽  
Male Gonad ◽  
Two Phase ◽  
Genome Wide ◽  
A Genome ◽  
Positive Rate ◽  
Olfactory Pit

Previous research reported that Papua New Guineans (PNG) and Australians contain introgressions from Denisovans. Here we present a genome-wide analysis of Denisovan introgressions in PNG and Australians. We firstly developed a two-phase method to detect Denisovan introgressions from whole-genome sequencing data. This method has relatively high detection power (79.74%) and low false positive rate (2.44%) based on simulations. Using this method, we identified 1.34 Gb of Denisovan introgressions from sixteen PNG and four Australian genomes, in which we identified 38,877 Denisovan introgressive alleles (DIAs). We found that 78 Denisovan introgressions were under positive selection. Genes located in the 78 introgressions are related to evolutionarily important functions, such as spermatogenesis, fertilization, cold acclimation, circadian rhythm, development of brain, neural tube, face, and olfactory pit, immunity, etc. We also found that 121 DIAs are missense. Genes harboring the 121 missense DIAs are also related to evolutionarily important functions, such as female pregnancy, development of face, lung, heart, skin, nervous system, and male gonad, visual and smell perception, response to heat, pain, hypoxia, and UV, lipid transport, metabolism, blood coagulation, wound healing, aging, etc. Taken together, this study suggests that Denisovan introgressions in PNG and Australians are evolutionarily important, and may help PNG and Australians in local adaptation. In this study, we also proposed a method that could efficiently identify archaic hominin introgressions in modern non-African genomes.

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