High-Quality Whole-Genome Sequences for 59 Historical Shigella Strains Generated with PacBio Sequencing

Kim, Justin; Lindsey, Rebecca L.; Garcia-Toledo, Lisley; Loparev, Vladimir N.; Rowe, Lori A.; Batra, Dhwani; Juieng, Phalasy; Stoneburg, Devon; Martin, Haley; Knipe, Kristen; Smith, P. B.; Strockbine, Nancy

doi:10.1128/genomea.00282-18

Cited by 14 publications

(14 citation statements)

References 11 publications

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“…Within the O-antigen biosynthetic gene cluster (rfb), genes encoding O-antigen flippase, wzx, and polymerase, wzy, are serotype specific; their sequences were obtained from published reports (10,(12)(13)(14)(15)(36)(37)(38)(39)(40)(41)(42)(43)(44)(45)(46)(47)(48)(49)(50)(51)(52)(53). For serotypes without O-antigen information, rfb sequence located between the conserved galF and gnd genes was first extracted from assembled genomes (54). Sequences of wzx To further differentiate between serotypes, we collected the sequences of O-antigen modification enzymes of S. flexneri (12,15,52,53), a chromosomally encoded S. sonnei-specific putative methylase (this sequence is hereafter referred to as Ss_methylase) (55), wbaM of S. boydii 10 (48), and the plasmid-borne rfp of S. dysenteriae 1 (14,38).…”

Section: Resultsmentioning

confidence: 99%

In Silico Serotyping Based on Whole-Genome Sequencing Improves the Accuracy of Shigella Identification

Yun

Lau

Lee

et al. 2019

Appl Environ Microbiol

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Bacteria of the genus Shigella, consisting of 4 species and Ͼ50 serotypes, cause shigellosis, a foodborne disease of significant morbidity, mortality, and economic loss worldwide. Classical Shigella identification based on selective media and serology is tedious, time-consuming, expensive, and not always accurate. A molecular diagnostic assay does not distinguish Shigella at the species level or from enteroinvasive Escherichia coli (EIEC). We inspected genomic sequences from 221 Shigella isolates and observed low concordance rates between conventional designation and molecular serotyping: 86.4% and 80.5% at the species and serotype levels, respectively. Serotype determinants for 6 additional serotypes were identified. Examination of differentiation gene markers commonly perceived as characteristic hallmarks in Shigella showed high variability among different serotypes. Using this information, we developed ShigaTyper, an automated workflow that utilizes limited computational resources to accurately and rapidly determine 59 Shigella serotypes using Illumina paired-end whole-genome sequencing (WGS) reads. Shigella serotype determinants and species-specific diagnostic markers were first identified through read alignment to an in-house curated reference sequence database. Relying on sequence hits that passed a threshold level of coverage and accuracy, serotype could be unambiguously predicted within 1 min for an average-size WGS sample of ϳ500 MB. Validation with WGS data from 380 isolates showed an accuracy rate of 98.2%. This pipeline is the first step toward building a comprehensive WGS-based analysis pipeline of Shigella spp. in a field laboratory setting, where speed is essential and resources need to be more cost-effectively dedicated. IMPORTANCE Shigella causes diarrheal disease with serious public health implications. However, conventional Shigella identification methods are laborious and timeconsuming and can be erroneous due to the high similarity between Shigella and enteroinvasive Escherichia coli (EIEC) and cross-reactivity between serotyping antisera. Further, serotype interpretation is complicated for inexperienced users. To develop an easier method with higher accuracy based on whole-genome sequencing (WGS) for Shigella serotyping, we systematically examined genomic information of Shigella isolates from 53 serotypes to define rules for differentiation and serotyping. We created ShigaTyper, an automated pipeline that accurately and rapidly excludes non-Shigella isolates and identifies 59 Shigella serotypes using Illumina paired-end WGS reads. A serotype can be unambiguously predicted at a data processing speed of 538 MB/min with 98.2% accuracy from a regular laptop. Once it is installed, training in bioinformatics analysis and Shigella genetics is not required. This pipeline is particularly useful to general microbiologists in field laboratories.

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Section: Resultsmentioning

confidence: 99%

In Silico Serotyping Based on Whole-Genome Sequencing Improves the Accuracy of Shigella Identification

Yun

Lau

Lee

et al. 2019

Appl Environ Microbiol

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“…We proceeded to validate our predictions experimentally by evaluating growth requirements of the predicted auxotrophs. We were able to obtain six E. coli (61)(62)(63)(64), three Yersinia (65), three Salmonella (66,67), three Shigella (68,69), and one Klebsiella (70) strain (Fig. 6).…”

Section: Experimental Validation Of Auxotrophies Highlight Technologicalmentioning

confidence: 99%

Metabolic and genetic basis for auxotrophies in Gram-negative species

Seif

Choudhary

Hefner

et al. 2020

Proc. Natl. Acad. Sci. U.S.A.

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Auxotrophies constrain the interactions of bacteria with their environment, but are often difficult to identify. Here, we develop an algorithm (AuxoFind) using genome-scale metabolic reconstruction to predict auxotrophies and apply it to a series of available genome sequences of over 1,300 Gram-negative strains. We identify 54 auxotrophs, along with the corresponding metabolic and genetic basis, using a pangenome approach, and highlight auxotrophies conferring a fitness advantage in vivo. We show that the metabolic basis of auxotrophy is species-dependent and varies with 1) pathway structure, 2) enzyme promiscuity, and 3) network redundancy. Various levels of complexity constitute the genetic basis, including 1) deleterious single-nucleotide polymorphisms (SNPs), in-frame indels, and deletions; 2) single/multigene deletion; and 3) movement of mobile genetic elements (including prophages) combined with genomic rearrangements. Fourteen out of 19 predictions agree with experimental evidence, with the remaining cases highlighting shortcomings of sequencing, assembly, annotation, and reconstruction that prevent predictions of auxotrophies. We thus develop a framework to identify the metabolic and genetic basis for auxotrophies in Gram-negatives.

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“…These difficult-to-sequence plasmids carry antigen-encoding genes and are often required for propagation of the bacteria in ticks and/or mammals. The recent development of long-read sequencing technology [34] (eg, Pacific Biosciences), in combination with the use of HTS technologies with relatively very low sequencing error rates (eg, Illumina Novae or MiSeq platforms) [34][35][36], has allowed resolution of the repeated sequences that are the hallmark of Borrelia genomes and of other sequencing challenges commonly found in the critically important Borrelia plasmids.…”

Section: Genomic Sequencingmentioning

confidence: 99%

Direct Diagnostic Tests for Lyme Disease

Schutzer

Body²,

Boyle

et al. 2018

Clinical Infectious Diseases

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Borrelia burgdorferi was discovered to be the cause of Lyme disease in 1983, leading to seroassays. The 1994 serodiagnostic testing guidelines predated a full understanding of key B. burgdorferi antigens and have a number of shortcomings. These serologic tests cannot distinguish active infection, past infection, or reinfection. Reliable direct-detection methods for active B. burgdorferi infection have been lacking in the past but are needed and appear achievable. New approaches have effectively been applied to other emerging infections and show promise in direct detection of B. burgdorferi infections.

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High-Quality Whole-Genome Sequences for 59 Historical Shigella Strains Generated with PacBio Sequencing

Abstract: Shigella spp. are enteric pathogens that cause shigellosis. We report here the high-quality whole-genome sequences of 59 historical Shigella strains that represent the four species and a variety of serotypes.

Cited by 14 publications

References 11 publications

In Silico Serotyping Based on Whole-Genome Sequencing Improves the Accuracy of Shigella Identification

In Silico Serotyping Based on Whole-Genome Sequencing Improves the Accuracy of Shigella Identification

Metabolic and genetic basis for auxotrophies in Gram-negative species

Direct Diagnostic Tests for Lyme Disease

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