scholarly journals Development of an Online Tool for Pasteurella multocida Genotyping and Genotypes of Pasteurella multocida From Different Hosts

2021 ◽  
Vol 8 ◽  
Author(s):  
Zhong Peng ◽  
Junyang Liu ◽  
Wan Liang ◽  
Fei Wang ◽  
Li Wang ◽  
...  
Keyword(s):  
Host Species ◽  
Pasteurella Multocida ◽  
Epidemiological Studies ◽  
Clinical Settings ◽  
Whole Genome ◽  
Genome Sequences ◽  
Efficient Tool ◽  
Online Tool ◽  
Multiple Systems ◽  
Genotyping Platform

Pasteurella multocida is a versatile zoonotic pathogen. Multiple systems have been applied to type P. multocida from different diseases in different hosts. Recently, we found that assigning P. multocida strains by combining their capsular, lipopolysaccharide, and MLST genotypes (marked as capsular: lipopolysaccharide: MLST genotype) could help address the biological characteristics of P. multocida circulation in different hosts. However, there is still lack of a rapid and efficient tool to diagnose P. multocida according to this system. Here, we developed an intelligent genotyping platform PmGT for P. multocida strains according to their whole genome sequences using the web 2.0 technologies. By using PmGT, we determined capsular genotypes, LPS genotypes, and MLST genotypes as well as the main virulence factor genes (VFGs) of P. multocida isolates from different host species based on their whole genome sequences published on NCBI. The results revealed a closer association between the genotypes and pasteurellosis rather than between genotypes and host species. With the advent of high-quality, inexpensive DNA sequencing, PmGT represents a more efficient tool for P. multocida diagnosis in both epidemiological studies and clinical settings.

scholarly journals Development of a Rapid, Efficient, Intelligent and Cost-Saving Tool to Diagnose Pasteurella Multocida by Using Whole Genome Sequence and Genotypes of Pasteurella Multocida From Different Hosts

2020 ◽  
Author(s):  
Zhong Peng ◽  
Junyang Liu ◽  
Wan Liang ◽  
Fei Wang ◽  
Li Wang ◽  
...  
Keyword(s):  
Cost Saving ◽  
Host Species ◽  
Pasteurella Multocida ◽  
Epidemiological Studies ◽  
Whole Genome Sequence ◽  
Clinical Settings ◽  
Whole Genome ◽  
Genome Sequences ◽  
Host Tropism ◽  
Tropism Prediction

Abstract Background: Different typing systems including capsular genotyping, lipopolysaccharide (LPS) genotyping, multilocus sequence typing (MLST), and virulence genotyping based on the detection of different virulence factor-encoding gene (VFG) profiles have been applied to characterize Pasteurella multocida strains from different host species. However, these methods require much time and effort in laboratories. Particularly, relying on one of these methods is difficult to address the biology of P. multocida from host species. Recently, we found that assigning P. multocida strains according to the combination of their capsular, LPS, and MLST genotypes (marked as capsular genotype: LPS genotype: MLST genotype) could help address the biological characteristics of P. multocida circulation in multiple hosts. However, it is still lack of a rapid, efficient, intelligent and cost-saving tool to diagnose P. multocida according to this system. Results: We have developed an intelligent genotyping and host tropism prediction tool PmGT for P. multocida strains according to their whole genome sequences by using machine learning and web 2.0 technologies. By using this tool, the capsular genotypes, LPS genotypes, and MLST genotypes as well as the main VFGs of P. multocida isolates in different host species were determined based on whole genome sequences. The results revealed a closer association between the genotypes and pasteurellosis rather than between genotypes and host species. Finally, we also used PmGT to predict the host species of P. multocida strains with the same capsular: lipopolysaccharide: MLST genotypes. Conclusions: With the advent of high-quality, inexpensive DNA sequencing, this platform represents a more efficient and cost-saving tool for P. multocida diagnosis in both epidemiological studies and clinical settings.

scholarly journals Precise prediction of antibiotic resistance in Escherichia coli from full genome sequences

2018 ◽  
Author(s):  
Danesh Moradigaravand ◽  
Martin Palm ◽  
Anne Farewell ◽  
Ville Mustonen ◽  
Jonas Warringer ◽  
...  
Keyword(s):  
Machine Learning ◽  
Antibiotic Resistance ◽  
Population Structure ◽  
Genome Sequencing ◽  
Diagnostic Tools ◽  
Clinical Settings ◽  
Whole Genome ◽  
Genome Sequences ◽  
E Coli ◽  
Resistant Strains

AbstractThe emergence of microbial antibiotic resistance is a global health threat. In clinical settings, the key to controlling spread of resistant strains is accurate and rapid detection. As traditional culture-based methods are time consuming, genetic approaches have recently been developed for this task. The diagnosis is typically made by measuring a few known determinants previously identified from whole genome sequencing, and thus is restricted to existing information on biological mechanisms. To overcome this limitation, we employed machine learning models to predict resistance to 11 compounds across four classes of antibiotics from existing and novel whole genome sequences of 1936 E. coli strains. We considered a range of methods, and examined population structure, isolation year, gene content, and polymorphism information as predictors. Gradient boosted decision trees consistently outperformed alternative models with an average F1 score of 0.88 on held-out data (range 0.66-0.96). While the best models most frequently employed all inputs, an average F1 score of 0.73 could be obtained using population structure information alone. Single nucleotide variation data were less useful, and failed to improve prediction for ten out of 11 antibiotics. These results demonstrate that antibiotic resistance in E. coli can be accurately predicted from whole genome sequences without a priori knowledge of mechanisms, and that both genomic and epidemiological data are informative. This paves way to integrating machine learning approaches into diagnostic tools in the clinic.SummaryOne of the major health threats of 21st century is emergence of antibiotic resistance. To manage its economic impact, efforts are made to develop novel diagnostic tools that rapidly detect resistant strains in clinical settings. In our study, we employed a range machine learning tools to predict antibiotic resistance from whole genome sequencing data for E. coli. We used the presence or absence of genes, population structure and isolation year of isolates as predictors, and could attain average precision of 0.93 and recall of 0.83, without prior knowledge about the causal mechanisms. These results demonstrate the potential application of machine learning methods as a diagnostic tool in healthcare settings.

scholarly journals De Novo Whole-Genome Sequencing and Annotation of Pathogenic Bovine Pasteurella multocida Type A:3 Strains

2020 ◽  
Vol 9 (49) ◽  
Author(s):  
Morag Livingstone ◽  
Kevin Aitchison ◽  
Mark Dagleish ◽  
David Longbottom
Keyword(s):  
Genome Sequencing ◽  
Pasteurella Multocida ◽  
De Novo ◽  
Whole Genome ◽  
Genome Sequences ◽  
Content Type ◽  
Pneumonic Pasteurellosis ◽  
The United Kingdom ◽  
The World ◽  
Welfare Implications

ABSTRACT Pneumonic pasteurellosis, caused by Pasteurella multocida, is a common respiratory infection of ruminants that has major economic and welfare implications throughout the world. Here, we report the annotated genome sequences of seven pathogenic strains of P. multocida that were isolated from cattle in the United Kingdom.

scholarly journals Pasteurella multocida: Genotypes and Genomics

2019 ◽  
Vol 83 (4) ◽  
Author(s):  
Zhong Peng ◽  
Xiangru Wang ◽  
Rui Zhou ◽  
Huanchun Chen ◽  
Brenda A. Wilson ◽  
...  
Keyword(s):  
Host Specificity ◽  
Pasteurella Multocida ◽  
Whole Genome ◽  
Genome Sequences ◽  
Content Type ◽  
Clinical Presentations ◽  
Wide Range ◽  
Current Availability ◽  
Genetic Mechanisms ◽  
Low Coverage

SUMMARY Pasteurella multocida is a highly versatile pathogen capable of causing infections in a wide range of domestic and wild animals as well as in humans and nonhuman primates. Despite over 135 years of research, the molecular basis for the myriad manifestations of P. multocida pathogenesis and the determinants of P. multocida phylogeny remain poorly defined. The current availability of multiple P. multocida genome sequences now makes it possible to delve into the underlying genetic mechanisms of P. multocida fitness and virulence. Using whole-genome sequences, the genotypes, including the capsular genotypes, lipopolysaccharide (LPS) genotypes, and multilocus sequence types, as well as virulence factor-encoding genes of P. multocida isolates from different clinical presentations can be characterized rapidly and accurately. Putative genetic factors that contribute to virulence, fitness, host specificity, and disease predilection can also be identified through comparative genome analysis of different P. multocida isolates. However, although some knowledge about genotypes, fitness, and pathogenesis has been gained from the recent whole-genome sequencing and comparative analysis studies of P. multocida, there is still a long way to go before we fully understand the pathogenic mechanisms of this important zoonotic pathogen. The quality of several available genome sequences is low, as they are assemblies with relatively low coverage, and genomes of P. multocida isolates from some uncommon host species are still limited or lacking. Here, we review recent advances, as well as continuing knowledge gaps, in our understanding of determinants contributing to virulence, fitness, host specificity, disease predilection, and phylogeny of P. multocida.

scholarly journals Molecular Epidemiology and Whole-Genome Analysis of Bovine Foamy Virus in Japan

Viruses ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 1017
Author(s):  
Hirohisa Mekata ◽  
Tomohiro Okagawa ◽  
Satoru Konnai ◽  
Takayuki Miyazawa
Keyword(s):  
Phylogenetic Analyses ◽  
Foamy Virus ◽  
Pcr Analysis ◽  
Whole Genome ◽  
Genome Sequences ◽  
Whole Genome Analysis ◽  
Virus Family ◽  
Bovine Foamy Virus ◽  
Novel Genotype

Bovine foamy virus (BFV) is a member of the foamy virus family in cattle. Information on the epidemiology, transmission routes, and whole-genome sequences of BFV is still limited. To understand the characteristics of BFV, this study included a molecular survey in Japan and the determination of the whole-genome sequences of 30 BFV isolates. A total of 30 (3.4%, 30/884) cattle were infected with BFV according to PCR analysis. Cattle less than 48 months old were scarcely infected with this virus, and older animals had a significantly higher rate of infection. To reveal the possibility of vertical transmission, we additionally surveyed 77 pairs of dams and 3-month-old calves in a farm already confirmed to have BFV. We confirmed that one of the calves born from a dam with BFV was infected. Phylogenetic analyses revealed that a novel genotype was spread in Japan. In conclusion, the prevalence of BFV in Japan is relatively low and three genotypes, including a novel genotype, are spread in Japan.

scholarly journals Surge of severe acute respiratory syndrome coronavirus 2 infections linked to single introduction of a virus strain in Myanmar, 2020

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Myat Htut Nyunt ◽  
Hnin Ohnmar Soe ◽  
Kay Thi Aye ◽  
Wah Wah Aung ◽  
Yi Yi Kyaw ◽  
...  
Keyword(s):  
Severe Acute Respiratory Syndrome ◽  
Early Phase ◽  
International Travel ◽  
Health Concern ◽  
Whole Genome ◽  
Genome Sequences ◽  
Genomic Epidemiology ◽  
Local Spread ◽  
Control And Prevention ◽  
Local Transmission

AbstractSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is a major health concern globally. Genomic epidemiology is an important tool to assess the pandemic of coronavirus disease 2019 (COVID-19). Several mutations have been reported by genome analysis of the SARS-CoV-2. In the present study, we investigated the mutational and phylogenetic analysis of 30 whole-genome sequences for the virus's genomic characteristics in the specimens collected in the early phase of the pandemic (March–June, 2020) and the sudden surge of local transmission (August–September, 2020). The four samples in the early phase of infection were B.6 lineage and located within a clade of the samples collected at the same time in Singapore and Malaysia, while five returnees by rescue flights showed the lineage B. 1.36.1 (three from India), B.1.1 (one from India) and B.1.80 (one from China). However, there was no evidence of local spread from these returnees. Further, all 19 whole-genome sequences collected in the sudden surge of local transmission showed lineage B.1.36. The surge of the second wave on SARS-CoV-2 infection was linked to the single-introduction of a variant (B.1.36) that may result from the strict restriction of international travel and containment efforts. These genomic data provides the useful information to disease control and prevention strategy.

scholarly journals Comparison of whole genome sequences of three Bacillus cereus strains reveals the food safety risks of Apostichopus japonicus in China

2021 ◽  
Vol 20 ◽  
pp. 100649
Author(s):  
Xiaoran Zhao ◽  
Ruijun Li ◽  
Huifeng Dang ◽  
Luo Wang ◽  
Songzhe Fu ◽  
...  
Keyword(s):  
Food Safety ◽  
Bacillus Cereus ◽  
Apostichopus Japonicus ◽  
Whole Genome ◽  
Genome Sequences ◽  
Safety Risks
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