scholarly journals Whole Genome Sequence Analysis of Phage-Resistant Listeria monocytogenes Serotype 1/2a Strains from Turkey Processing Plants

Pathogens ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 199
Author(s):  
Phillip Brown ◽  
Yi Chen ◽  
Cameron Parsons ◽  
Eric Brown ◽  
Martin J. Loessner ◽  
...  
Keyword(s):  
Listeria Monocytogenes ◽  
Genome Sequence ◽  
Sequence Data ◽  
Whole Genome Sequence ◽  
Phage Resistance ◽  
Whole Genome ◽  
Recombinant Phage ◽  
Processing Plants ◽  
Serotype 1 ◽  
Resistant Strains

Listeria monocytogenes is a Gram-positive bacterial pathogen and the causative agent of listeriosis, a severe foodborne infection. L. monocytogenes is notorious for its ability to persist in food processing environments (FPEs) via a variety of adaptive traits. Even though traits such as cold tolerance, biofilm formation and sanitizer resistance have been extensively investigated for their roles in persistence of L. monocytogenes in FPEs, much less is known about resistance to bacteriophages. Previous studies explored phage resistance mechanisms in laboratory-created mutants but it is imperative to investigate phage resistance that is naturally exhibited in FPE-derived strains. Here, we integrated the analysis of whole genome sequence data from a panel of serotype 1/2a strains of sequence types 321 and 391 from turkey processing plants, with the determination of cell surface substituents required for phage adsorption and phage infection assays with the four wide-host-range phages A511, P100, 20422-1 and 805405-1. Using a specific set of recombinant phage protein probes, we discovered that phage-resistant strains lacked one or both of the serogroup 1/2-specific wall teichoic acid carbohydrate decorations, N-acetylglucosamine and rhamnose. Furthermore, these phage-resistant strains harbored substitutions in lmo1080, lmo1081, and lmo2550, which mediate carbohydrate decoration of the wall teichoic acids.

scholarly journals Harnessing Whole Genome Sequence Data for Facility-Specific Signatures for Listeria monocytogenes: A Case Study With Turkey Processing Plants in the United States

2021 ◽  
Vol 5 ◽  
Author(s):  
Phillip Brown ◽  
Yi Chen ◽  
Robin Siletzky ◽  
Cameron Parsons ◽  
Lee-Ann Jaykus ◽  
...  
Keyword(s):  
United States ◽  
Listeria Monocytogenes ◽  
Food Processing ◽  
Sequence Data ◽  
Allelic Variation ◽  
The United States ◽  
Whole Genome Sequence ◽  
Whole Genome ◽  
Molecular Signatures ◽  
Processing Plants

Listeria monocytogenes is a Gram-positive foodborne pathogen responsible for the severe disease listeriosis and notorious for its ability to persist in food processing plants, leading to contamination of processed, ready-to-eat foods. L. monocytogenes persistence in various food processing environments (FPEs) has been extensively investigated by various subtyping tools, with increasing use of whole genome sequencing (WGS). However, major knowledge gaps remain. There is a need for facility-specific molecular signatures not only for adequate attribution of L. monocytogenes to a specific FPE but also for improved understanding of the ecology and evolution of L. monocytogenes in the food processing ecosystem. Furthermore, multiple strains can be recovered from a single FPE sample, but their diversity can be underestimated with common molecular subtyping tools. In this study we investigated a panel of 54 L. monocytogenes strains from four turkey processing plants in the United States. A combination of WGS and phenotypic assays was employed to assess strain persistence as well as identify facility-specific molecular signatures. Comparative analysis of allelic variation across the whole genome revealed that allelic profiles have the potential to be specific to individual processing plants. Certain allelic profiles remained associated with individual plants even when closely-related strains from other sources were included in the analysis. Furthermore, for certain sequence types (STs) based on the seven-locus multilocus sequence typing scheme, presence and location of premature stop codons in inlA, inlB length, prophage sequences, and the sequence content of a genomic hotspot could serve as plant-specific signatures. Interestingly, the analysis of different isolates from the same environmental sample revealed major differences not only in serotype and ST, but even in the sequence content of strains of the same ST. This study highlights the potential for WGS data to be deployed for identification of facility-specific signatures, thus facilitating the tracking of strain movement through the food chain. Furthermore, deployment of WGS for intra-sample strain analysis allows for a more complete environmental surveillance of L. monocytogenes in food processing facilities, reducing the risk of failing to detect strains that may be clinically relevant and potentially novel.

scholarly journals Defining and Evaluating a Core Genome Multilocus Sequence Typing Scheme for Whole-Genome Sequence-Based Typing of Listeria monocytogenes

2015 ◽  
Vol 53 (9) ◽  
pp. 2869-2876 ◽  
Author(s):  
Werner Ruppitsch ◽  
Ariane Pietzka ◽  
Karola Prior ◽  
Stefan Bletz ◽  
Haizpea Lasa Fernandez ◽  
...  
Keyword(s):  
Listeria Monocytogenes ◽  
Genome Sequence ◽  
Core Genome ◽  
Target Genes ◽  
Sequence Data ◽  
Whole Genome Sequence ◽  
Whole Genome ◽  
Content Type ◽  
Typing Scheme ◽  
Reference Strains

Whole-genome sequencing (WGS) has emerged today as an ultimate typing tool to characterizeListeria monocytogenesoutbreaks. However, data analysis and interlaboratory comparability of WGS data are still challenging for most public health laboratories. Therefore, we have developed and evaluated a newL. monocytogenestyping scheme based on genome-wide gene-by-gene comparisons (core genome multilocus the sequence typing [cgMLST]) to allow for a unique typing nomenclature. Initially, we determined the breadth of theL. monocytogenespopulation based on MLST data with a Bayesian approach. Based on the genome sequence data of representative isolates for the whole population, cgMLST target genes were defined and reappraised with 67L. monocytogenesisolates from two outbreaks and serotype reference strains. The Bayesian population analysis generated fiveL. monocytogenesgroups. Using all available NCBI RefSeq genomes (n= 36) and six additionally sequenced strains, all genetic groups were covered. Pairwise comparisons of these 42 genome sequences resulted in 1,701 cgMLST targets present in all 42 genomes with 100% overlap and ≥90% sequence similarity. Overall, ≥99.1% of the cgMLST targets were present in 67 outbreak and serotype reference strains, underlining the representativeness of the cgMLST scheme. Moreover, cgMLST enabled clustering of outbreak isolates with ≤10 alleles difference and unambiguous separation from unrelated outgroup isolates. In conclusion, the novel cgMLST scheme not only improves outbreak investigations but also enables, due to the availability of the automatically curated cgMLST nomenclature, interlaboratory exchange of data that are crucial, especially for rapid responses during transsectorial outbreaks.

scholarly journals Whole-Genome Sequence of a Serotype 1/2b Listeria monocytogenes Strain Isolated from Raw Seafood in Japan

2019 ◽  
Vol 8 (17) ◽  
Author(s):  
Chihiro Ohshima ◽  
Satomi Kanagawa ◽  
Satoko Miya ◽  
Ayaka Nakamura ◽  
Hajime Takahashi ◽  
...  
Keyword(s):  
Listeria Monocytogenes ◽  
Genome Sequence ◽  
Whole Genome Sequence ◽  
Whole Genome ◽  
Content Type ◽  
Serotype 1

Listeria monocytogenes is a pathogen typically acquired through the ingestion of foods. It has been specifically reported that the pathogen is widely distributed in raw seafood in Japan.

TIGER: inferring DNA replication timing from whole-genome sequence data

2021 ◽  
Author(s):  
Amnon Koren ◽  
Dashiell J Massey ◽  
Alexa N Bracci
Keyword(s):  
Dna Replication ◽  
Genome Sequence ◽  
Genomic Dna ◽  
Sequence Data ◽  
Replication Timing ◽  
Whole Genome Sequence ◽  
Supplementary Information ◽  
Whole Genome ◽  
Genome Sequence Data ◽  
Dna Replication Timing

Abstract Motivation Genomic DNA replicates according to a reproducible spatiotemporal program, with some loci replicating early in S phase while others replicate late. Despite being a central cellular process, DNA replication timing studies have been limited in scale due to technical challenges. Results We present TIGER (Timing Inferred from Genome Replication), a computational approach for extracting DNA replication timing information from whole genome sequence data obtained from proliferating cell samples. The presence of replicating cells in a biological specimen leads to non-uniform representation of genomic DNA that depends on the timing of replication of different genomic loci. Replication dynamics can hence be observed in genome sequence data by analyzing DNA copy number along chromosomes while accounting for other sources of sequence coverage variation. TIGER is applicable to any species with a contiguous genome assembly and rivals the quality of experimental measurements of DNA replication timing. It provides a straightforward approach for measuring replication timing and can readily be applied at scale. Availability and Implementation TIGER is available at https://github.com/TheKorenLab/TIGER. Supplementary information Supplementary data are available at Bioinformatics online

scholarly journals Whole genome sequence data of Mycobacterium tuberculosis XDR strain, isolated from patient in Kazakhstan

Data in Brief ◽  
2020 ◽  
Vol 33 ◽  
pp. 106416
Author(s):  
Asset Daniyarov ◽  
Askhat Molkenov ◽  
Saule Rakhimova ◽  
Ainur Akhmetova ◽  
Zhannur Nurkina ◽  
...  
Keyword(s):  
Mycobacterium Tuberculosis ◽  
Genome Sequence ◽  
Sequence Data ◽  
Whole Genome Sequence ◽  
Whole Genome ◽  
Genome Sequence Data

scholarly journals Elucidating the genetic basis of an oligogenic birth defect using whole genome sequence data in a non-model organism, Bubalus bubalis

2017 ◽  
Vol 7 (1) ◽  
Author(s):  
Lynsey K. Whitacre ◽  
Jesse L. Hoff ◽  
Robert D. Schnabel ◽  
Sara Albarella ◽  
Francesca Ciotola ◽  
...  
Keyword(s):  
Genome Sequence ◽  
Birth Defect ◽  
Genetic Basis ◽  
Sequence Data ◽  
Model Organism ◽  
Bubalus Bubalis ◽  
Whole Genome Sequence ◽  
Whole Genome ◽  
Genome Sequence Data

46 Footprints of Selection in Angus and Hanwoo Beef Cattle Using Imputed Whole Genome Sequence Data

2021 ◽  
Vol 99 (Supplement_3) ◽  
pp. 25-25
Author(s):  
Muhammad Yasir Nawaz ◽  
Rodrigo Pelicioni Savegnago ◽  
Cedric Gondro
Keyword(s):  
Beef Cattle ◽  
Genome Sequence ◽  
Sequence Data ◽  
Whole Genome Sequence ◽  
Fixation Index ◽  
Whole Genome ◽  
Extended Haplotype Homozygosity ◽  
Extended Haplotype ◽  
Genome Sequence Data ◽  
Genomic Regions

Abstract In this study, we detected genome wide footprints of selection in Hanwoo and Angus beef cattle using different allele frequency and haplotype-based methods based on imputed whole genome sequence data. Our dataset included 13,202 Angus and 10,437 Hanwoo animals with 10,057,633 and 13,241,550 imputed SNPs, respectively. A subset of data with 6,873,624 common SNPs between the two populations was used to estimate signatures of selection parameters, both within (runs of homozygosity and extended haplotype homozygosity) and between (allele fixation index, extended haplotype homozygosity) the breeds in order to infer evidence of selection. We observed that correlations between various measures of selection ranged between 0.01 to 0.42. Assuming these parameters were complementary to each other, we combined them into a composite selection signal to identify regions under selection in both beef breeds. The composite signal was based on the average of fractional ranks of individual selection measures for every SNP. We identified some selection signatures that were common between the breeds while others were independent. We also observed that more genomic regions were selected in Angus as compared to Hanwoo. Candidate genes within significant genomic regions may help explain mechanisms of adaptation, domestication history and loci for important traits in Angus and Hanwoo cattle. In the future, we will use the top SNPs under selection for genomic prediction of carcass traits in both breeds.

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