Whole-genome sequence-guided PCR for the rapid identification of thePseudomonas aeruginosa ST175 high-risk clone directly from clinical samples

2020 ◽  
Author(s):  
Gabriel Cabot ◽  
Paula Lara-Esbrí ◽  
Xavier Mulet ◽  
Antonio Oliver
Keyword(s):  
High Risk ◽  
Sensitivity And Specificity ◽  
Genome Sequence ◽  
Treatment Strategies ◽  
High Sensitivity ◽  
Whole Genome Sequence ◽  
Clinical Samples ◽  
Whole Genome ◽  
Pcr Assay ◽  
Pcr Targeting

Abstract Objectives Pseudomonas aeruginosa frequently show MDR/XDR profiles, which are associated with worldwide-disseminated high-risk clones (HRCs). We developed a PCR assay for the detection in clinical samples of ST175, an HRC that is widespread in European countries. Methods The whole-genome sequence was obtained for one ST175 isolate using a PacBio RSII sequencer. Reads from multiple isolates belonging to ST175 and the PAO1 reference strain were mapped against the ST175 genome to identify potentially specific regions. Once curated, using the BLAST database to search for the presence of those regions in any other organism, we designed a specific PCR for the detection of ST175. Results Assembly of the ST175 PacBio-sequenced genome resulted in three contigs with a total length of 7 087 985 bases, encoding 6566 coding sequences. Specific regions for ST175 genomes were detected and a PCR targeting a 318 bp fragment located within a 3177 bp ORF coding for a putative reverse transcriptase was designed. The PCR test was first evaluatedin silico against 229 XDRP. aeruginosa genomes (73 ST175) from two multicentre studies, yielding 100% sensitivity and specificity. Then, the PCR was evaluatedin vitro in 25 isolates (12 ST175) and in 120 clinical samples (30 urine samples, 30 blood cultures, 30 sputum samples and 30 rectal swabs) of which 10% contained ST175, yielding again 100% sensitivity and specificity. Conclusions The PCR assay developed, showing high sensitivity and specificity for the detection of the ST175 HRC directly from clinical samples, could become a useful tool for guiding infection control and treatment strategies in areas with a high prevalence of this clone.

scholarly journals A Novel Real-Time PCR Assay for the Rapid Detection of Virulent Streptococcus equi Subspecies zooepidemicus—An Emerging Pathogen of Swine

2021 ◽  
Vol 8 ◽  
Author(s):  
Suresh V. Kuchipudi ◽  
Meera Surendran Nair ◽  
Michele Yon ◽  
Abhinay Gontu ◽  
Ruth H. Nissly ◽  
...  
Keyword(s):  
Real Time ◽  
Sensitivity And Specificity ◽  
High Mortality ◽  
Real Time Pcr ◽  
Diagnostic Methods ◽  
Clinical Samples ◽  
Pcr Assay ◽  
Streptococcus Equi ◽  
Swine Herds ◽  
Pcr Targeting

Streptococcus equi subspecies zooepidemicus, a zoonotic bacterial pathogen caused a series of outbreaks with high mortality affecting swine herds in multiple locations of the USA and Canada in 2019. Further genetic analysis revealed that this agent clustered with ATCC 35246, a S. zooepidemicus strain associated with high mortality outbreaks in swine herds of China originally reported in 1977. Rapid and accurate diagnosis is absolutely critical for controlling and limiting further spread of this emerging disease of swine. Currently available diagnostic methods including bacteriological examination and PCR assays do not distinguish between the virulent strains and avirulent commensal strains of S. zooepidemicus, which is critical given that this pathogen is a normal inhabitant of the swine respiratory tract. Based on comparative analyses of whole genome sequences of the virulent isolates and avirulent sequences, we identified a region in the SzM gene that is highly conserved and restricted to virulent S. zooepidemicus strains. We developed and validated a novel probe-based real-time PCR targeting the conserved region of SzM. The assay was highly sensitive and specific to the virulent swine isolates of Streptococcus equi subspecies zooepidemicus. No cross reactivity was observed with avirulent S. zooepidemicus isolates as well as other streptococcal species and a panel of porcine respiratory bacterial and viral pathogens. The PCR efficiency of the assay was 96.64 % and was able to detect as little as 20 fg of the bacterial DNA. We then validated the diagnostic sensitivity and specificity of the new PCR assay using a panel of clinical samples (n = 57) and found that the assay has 100% sensitivity and specificity as compared to bacteriological culture method. In summary, the PCR assay will be an extremely valuable tool for the rapid accurate detection of virulent swine S. zooepidemicus isolates and directly from clinical samples.

Whole-Genome Sequence Characterization of Primary Auxin-Responsive Aux/IAA Gene Family in Sorghum (Sorghum bicolor L.)

2010 ◽  
Vol 36 (4) ◽  
pp. 688-694
Author(s):  
Yi-Jun WANG ◽  
Yan-Ping LÜ ◽  
Qin XIE ◽  
De-Xiang DENG ◽  
Yun-Long BIAN
Keyword(s):  
Sorghum Bicolor ◽  
Gene Family ◽  
Genome Sequence ◽  
Whole Genome Sequence ◽  
Whole Genome ◽  
Sequence Characterization ◽  
I Gene

Whole-Genome Sequence Isolation, Chromosome Location, and Characteriza-tion of Primary Auxin-ResponsiveAux/IAAGene Family inAegilops tauschii

2014 ◽  
Vol 40 (12) ◽  
pp. 2059
Author(s):  
Lin-Yi QIAO ◽  
Xin LI ◽  
Zhi-Jian CHANG ◽  
Xiao-Jun ZHANG ◽  
Hai-Xian ZHAN ◽  
...  
Keyword(s):  
Genome Sequence ◽  
Whole Genome Sequence ◽  
Whole Genome ◽  
Chromosome Location

scholarly journals Whole genome sequence of Corynebacterium kroppenstedtii isolated from a case of recurrent granulomatous mastitis

IDCases ◽  
2020 ◽  
pp. e01034
Author(s):  
Charlie Tan ◽  
Fang-I Lu ◽  
Patryk Aftanas ◽  
Kara Tsang ◽  
Samira Mubareka ◽  
...  
Keyword(s):  
Genome Sequence ◽  
Whole Genome Sequence ◽  
Whole Genome ◽  
Granulomatous Mastitis

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 On the use of whole-genome sequence data for across-breed genomic prediction and fine-scale mapping of QTL

2021 ◽  
Vol 53 (1) ◽  
Author(s):  
Theo Meuwissen ◽  
Irene van den Berg ◽  
Mike Goddard
Keyword(s):  
Variable Selection ◽  
Genome Sequence ◽  
Genomic Prediction ◽  
Milk Fat ◽  
Genotype Imputation ◽  
Whole Genome Sequence ◽  
Genomic Relationship Matrix ◽  
Polygenic Effect ◽  
Relationship Matrix ◽  
Whole Genome

Abstract Background Whole-genome sequence (WGS) data are increasingly available on large numbers of individuals in animal and plant breeding and in human genetics through second-generation resequencing technologies, 1000 genomes projects, and large-scale genotype imputation from lower marker densities. Here, we present a computationally fast implementation of a variable selection genomic prediction method, that could handle WGS data on more than 35,000 individuals, test its accuracy for across-breed predictions and assess its quantitative trait locus (QTL) mapping precision. Methods The Monte Carlo Markov chain (MCMC) variable selection model (Bayes GC) fits simultaneously a genomic best linear unbiased prediction (GBLUP) term, i.e. a polygenic effect whose correlations are described by a genomic relationship matrix (G), and a Bayes C term, i.e. a set of single nucleotide polymorphisms (SNPs) with large effects selected by the model. Computational speed is improved by a Metropolis–Hastings sampling that directs computations to the SNPs, which are, a priori, most likely to be included into the model. Speed is also improved by running many relatively short MCMC chains. Memory requirements are reduced by storing the genotype matrix in binary form. The model was tested on a WGS dataset containing Holstein, Jersey and Australian Red cattle. The data contained 4,809,520 genotypes on 35,549 individuals together with their milk, fat and protein yields, and fat and protein percentage traits. Results The prediction accuracies of the Jersey individuals improved by 1.5% when using across-breed GBLUP compared to within-breed predictions. Using WGS instead of 600 k SNP-chip data yielded on average a 3% accuracy improvement for Australian Red cows. QTL were fine-mapped by locating the SNP with the highest posterior probability of being included in the model. Various QTL known from the literature were rediscovered, and a new SNP affecting milk production was discovered on chromosome 20 at 34.501126 Mb. Due to the high mapping precision, it was clear that many of the discovered QTL were the same across the five dairy traits. Conclusions Across-breed Bayes GC genomic prediction improved prediction accuracies compared to GBLUP. The combination of across-breed WGS data and Bayesian genomic prediction proved remarkably effective for the fine-mapping of QTL.

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