scholarly journals Geography Shapes the Population Genomics of Salmonella enterica Dublin

2019 ◽  
Vol 11 (8) ◽  
pp. 2220-2231 ◽  
Author(s):  
Gavin J Fenske ◽  
Anil Thachil ◽  
Patrick L McDonough ◽  
Amy Glaser ◽  
Joy Scaria
Keyword(s):  
Population Structure ◽  
Salmonella Enterica ◽  
Core Genome ◽  
Population Genomics ◽  
Negative Impact ◽  
Antibiotic Resistance Genes ◽  
Virulence Plasmid ◽  
Ancestral State ◽  
Secretion Systems ◽  
Data Set

Abstract Salmonella enterica serotype Dublin (S. Dublin) is a bovine-adapted serotype that can cause serious systemic infections in humans. Despite the increasing prevalence of human infections and the negative impact on agricultural processes, little is known about the population structure of the serotype. To this end, we compiled a manually curated data set comprising of 880 S. Dublin genomes. Core genome phylogeny and ancestral state reconstruction revealed that region-specific clades dominate the global population structure of S. Dublin. Strains of S. Dublin in the UK are genomically distinct from US, Brazilian, and African strains. The geographical partitioning impacts the composition of the core genome as well as the ancillary genome. Antibiotic resistance genes are almost exclusively found in US genomes and are mediated by an IncA/C2 plasmid. Phage content and the S. Dublin virulence plasmid were strongly conserved in the serotype. Comparison of S. Dublin to a closely related serotype, S. enterica serotype Enteritidis, revealed that S. Dublin contains 82 serotype specific genes that are not found in S. Enteritidis. Said genes encode metabolic functions involved in the uptake and catabolism of carbohydrates and virulence genes associated with type VI secretion systems and fimbria assembly respectively.

scholarly journals Geography Shapes the Population Genomics ofSalmonella entericaDublin

2019 ◽  
Author(s):  
Gavin J. Fenske ◽  
Anil Thachil ◽  
Patrick L. McDonough ◽  
Amy Glaser ◽  
Joy Scaria
Keyword(s):  
Population Structure ◽  
Salmonella Enterica ◽  
Core Genome ◽  
Population Genomics ◽  
Negative Impact ◽  
Virulence Plasmid ◽  
Ancestral State ◽  
Secretion Systems ◽  
The Us ◽  
Human Infections

ABSTRACTSalmonella enterica serotypeDublin (S.Dublin) is a bovine-adapted serotype that can cause serious systemic infections in humans. Despite the increasing prevalence of human infections and the negative impact on agricultural processes, little is known about the population structure of the serotype. To this end, we compiled a manually curated dataset comprising of 880S.Dublin genomes. Core genome phylogeny and ancestral state reconstruction revealed that region-specific clades dominate the global population structure ofS.Dublin. Strains ofS.Dublin in the UK are genomically distinct from US, Brazilian and African strains. The geographical partitioning impacts the composition of the core genome as well as the ancillary genome. Antibiotic resistance genes are almost exclusively found in US genomes and is mediated by an IncA/C2 plasmid. Phage content and theS.Dublin virulence plasmid were strongly conserved in the serotype. Comparison ofS.Dublin to a closely related serotype,Salmonella enterica serotypeEnteritidis, revealed thatS.Dublin contains 82 serotype specific genes that are not found inS. Enteritidis. Said genes encode metabolic functions involved in the uptake and catabolism of carbohydrates and virulence genes associated with type VI secretion systems and fimbria assembly respectively.IMPORTANCES.Dublin is a bovine-adapted strain that can also cause human infections. TypicalS.Dublin human infections are characterized by invasion of tissue that ultimately traverses to the bloodstream causing life-threatening systemic cases. The preferred course of treatment for such infection is the administration of antibiotics. Thus, it is important to study the population structure of the serotype to monitor and identify which strains present the greatest threats to public health. Consequently, in this work, it was found thatS.Dublin genomic features are greatly influenced by the region in which they populate. Our analysis found that mostS.Dublin isolates from the US are distinct and have gained multidrug resistance through a new hybrid plasmid. Thus, it would be expected that infections in the US would respond less favorably to the first line of therapy and the region acts as the major source of a multidrug-resistantS.Dublin.

scholarly journals PANINI: Pangenome Neighbor Identification for Bacterial Populations

2017 ◽  
Author(s):  
Khalil Abudahab ◽  
Joaquín M. Prada ◽  
Zhirong Yang ◽  
Stephen D. Bentley ◽  
Nicholas J. Croucher ◽  
...  
Keyword(s):  
Machine Learning ◽  
Core Genome ◽  
Population Genomics ◽  
Genomic Analysis ◽  
Diverse Populations ◽  
Data Set ◽  
Bacterial Populations ◽  
Accessory Genome ◽  
The Core ◽  
Link Type

ABSTRACTThe standard workhorse for genomic analysis of the evolution of bacterial populations is phylogenetic modelling of mutations in the core genome. However, in the current era of population genomics, a notable amount of information about evolutionary and transmission processes in diverse populations can be lost unless the accessory genome is also taken into consideration. Here we introduce PANINI, a computationally scalable method for identifying the neighbours for each isolate in a data set using unsupervised machine learning with stochastic neighbour embedding. PANINI is browser-based and integrates with the Microreact platform for rapid online visualisation and exploration of both core and accessory genome evolutionary signals together with relevant epidemiological, geographic, temporal and other metadata. Several case studies with single-and multi-clone pneumococcal populations are presented to demonstrate ability to identify biologically important signals from gene content data. PANINI is available at http://panini.wgsa.net/ and code at http://gitlab.com/cgps/panini

scholarly journals Neisseria gonorrhoeae Population Genomics: Use of the Gonococcal Core Genome to Improve Surveillance of Antimicrobial Resistance

2020 ◽  
Vol 222 (11) ◽  
pp. 1816-1825 ◽  
Author(s):  
Odile B Harrison ◽  
Ana Cehovin ◽  
Jessica Skett ◽  
Keith A Jolley ◽  
Paola Massari ◽  
...  
Keyword(s):  
Population Structure ◽  
Antimicrobial Resistance ◽  
Neisseria Gonorrhoeae ◽  
Population Biology ◽  
Clustering Algorithm ◽  
Core Genome ◽  
Population Genomics ◽  
Transmitted Infection ◽  
Sexually Transmitted ◽  
Allelic Differences

Abstract Background Gonorrhea, caused by the bacterium Neisseria gonorrhoeae, is a globally prevalent sexually transmitted infection. The dynamics of gonococcal population biology have been poorly defined due to a lack of resolution in strain typing methods. Methods In this study, we assess how the core genome can be used to improve our understanding of gonococcal population structure compared with current typing schemes. Results A total of 1668 loci were identified as core to the gonococcal genome. These were organized into a core genome multilocus sequence typing scheme (N gonorrhoeae cgMLST v1.0). A clustering algorithm using a threshold of 400 allelic differences between isolates resolved gonococci into discrete and stable core genome groups, some of which persisted for multiple decades. These groups were associated with antimicrobial genotypes and non-overlapping NG-STAR and NG-MAST sequence types. The MLST-STs were more widely distributed among core genome groups. Conclusions Clustering with cgMLST identified globally distributed, persistent, gonococcal lineages improving understanding of the population biology of gonococci and revealing its population structure. These findings have implications for the emergence of antimicrobial resistance in gonococci and how this is associated with lineages, some of which are more predisposed to developing antimicrobial resistance than others.

Global clonal spread of mcr-3-carrying MDR ST34 Salmonella enterica serotype Typhimurium and monophasic 1,4,[5],12:i:− variants from clinical isolates

2020 ◽  
Vol 75 (7) ◽  
pp. 1756-1765
Author(s):  
Ruan-Yang Sun ◽  
Bi-Xia Ke ◽  
Liang-Xing Fang ◽  
Wen-Ying Guo ◽  
Xing-Ping Li ◽  
...  
Keyword(s):  
Antibiotic Resistance ◽  
Resistance Genes ◽  
Salmonella Enterica ◽  
Core Genome ◽  
Antibiotic Resistance Genes ◽  
Complete Sequence ◽  
Clinical Isolates ◽  
The Core ◽  
Clonal Spread ◽  
Relationship Of

Abstract Objectives To investigate the prevalence and transmission of mcr-3 among Salmonella enterica serotype Typhimurium and 1,4,[5],12:i:−. Methods A total of 4724 clinical Salmonella isolates were screened for the presence of mcr-3 in China during 2014–19. The clonal relationship of the mcr-3-positive isolates and their plasmid contents and complete sequence were also characterized based on WGS data from the Illumina and MinION platforms. Results We identified 10 mcr-3-positive isolates, and all were MDR, mostly resistant to colistin, cefotaxime, ciprofloxacin, doxycycline and florfenicol. mcr-3 was co-present with blaCTX-M-55-qnrS1 on hybrid ST3-IncC-FII conjugatable plasmids (n = 6) and an ST3-IncC non-conjugatable plasmid (n = 1) and embedded into a pCHL5009T-like IncFII plasmid on the Salmonella chromosome (n = 3). Four distinctive genetic contexts surrounded mcr-3 and all but one were closely related to each other and to the corresponding region of IncFII plasmid pCHL5009T. IS15DI was most likely the vehicle for integration of mcr-3-carrying IncFII plasmids into ST3-IncC plasmids and the chromosome and for shaping the MDR regions. In addition, a phylogenetic tree based on the core genome revealed a unique Salmonella lineage (≤665 SNPs) that contained these 10 mcr-3-positive isolates and another 38 (33 from patients) mcr-3-positive Salmonella from five countries. In particular, most of the 51 mcr-3-positive isolates belonged to ST34 and harboured diverse antibiotic resistance genes (ARGs), including mcr-3-blaCTX-M-55-qnrS1, and possessed similar ARG profiles. Conclusions Our findings revealed global clonal spread of MDR ST34 Salmonella from clinical isolates co-harbouring mcr-3 with blaCTX-M-55 and qnrS1 and a flexibility of mcr-3 co-transmittance with other ARGs mediated by mobile genetic elements.

The Psychological and Financial Impact of Cybercrime Victimization: A Novel Application of the Shattered Assumptions Theory

2021 ◽  
pp. 089443932098382
Author(s):  
Jildau Borwell ◽  
Jurjen Jansen ◽  
Wouter Stol
Keyword(s):  
Negative Impact ◽  
Secondary Analysis ◽  
Well Being ◽  
Policy Implications ◽  
Financial Impact ◽  
Financial Loss ◽  
Data Set ◽  
Loss Compensation ◽  
Shattered Assumptions ◽  
The Impact

While criminality is digitizing, a theory-based understanding of the impact of cybercrime on victims is lacking. Therefore, this study addresses the psychological and financial impact of cybercrime on victims, applying the shattered assumptions theory (SAT) to predict that impact. A secondary analysis was performed on a representative data set of Dutch citizens ( N = 33,702), exploring the psychological and financial impact for different groups of cybercrime victims. The results showed a higher negative impact on emotional well-being for victims of person-centered cybercrime, victims for whom the offender was an acquaintance, and victims whose financial loss was not compensated and a lower negative impact on emotional well-being for victims with a higher income. The study led to novel scientific insights and showed the applicability of the SAT for developing hypotheses about cybercrime victimization impact. In this study, most hypotheses had to be rejected, leading to the conclusion that more work has to be done to test the applicability of the SAT in the field of cybercrime. Furthermore, policy implications were identified considering the prioritization of and approach to specific cybercrimes, treatment of victims, and financial loss compensation.

Key Insights and Research Prospects at the Dawn of the Population Genomics Era for Verticillium dahliae

2021 ◽  
Vol 59 (1) ◽  
Author(s):  
Jie-Yin Chen ◽  
Steven J. Klosterman ◽  
Xiao-Ping Hu ◽  
Xiao-Feng Dai ◽  
Krishna V. Subbarao
Keyword(s):  
Population Structure ◽  
Verticillium Dahliae ◽  
Plant Pathogens ◽  
Population Genomics ◽  
Population Divergence ◽  
Annual Review ◽  
Publication Date ◽  
Disease Symptoms ◽  
Historical Perspectives ◽  
Characteristic Features

The genomics era has ushered in exciting possibilities to examine the genetic bases that undergird the characteristic features of Verticillium dahliae and other plant pathogens. In this review, we provide historical perspectives on some of the salient biological characteristics of V. dahliae, including its morphology, microsclerotia formation, host range, disease symptoms, vascular niche, reproduction, and population structure. The kaleidoscopic population structure of this pathogen is summarized, including different races of the pathogen, defoliating and nondefoliating phenotypes, vegetative compatibility groupings, and clonal populations. Where possible, we place the characteristic differences in the context of comparative and functional genomics analyses that have offered insights into population divergence within V. dahliae and the related species. Current challenges are highlighted along with some suggested future population genomics studies that will contribute to advancing our understanding of the population divergence in V. dahliae. Expected final online publication date for the Annual Review of Phytopathology, Volume 59 is August 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Empirical Evaluation of Genetic Clustering Methods Using Multilocus Genotypes From 20 Chicken Breeds

Genetics ◽  
2001 ◽  
Vol 159 (2) ◽  
pp. 699-713
Author(s):  
Noah A Rosenberg ◽  
Terry Burke ◽  
Kari Elo ◽  
Marcus W Feldman ◽  
Paul J Freidlin ◽  
...  
Keyword(s):  
Cluster Analysis ◽  
Population Structure ◽  
Clustering Algorithm ◽  
Empirical Evaluation ◽  
Unknown Origin ◽  
Clustering Methods ◽  
Genetic Cluster ◽  
Data Set ◽  
Multilocus Genotypes ◽  
Chicken Breeds

Abstract We tested the utility of genetic cluster analysis in ascertaining population structure of a large data set for which population structure was previously known. Each of 600 individuals representing 20 distinct chicken breeds was genotyped for 27 microsatellite loci, and individual multilocus genotypes were used to infer genetic clusters. Individuals from each breed were inferred to belong mostly to the same cluster. The clustering success rate, measuring the fraction of individuals that were properly inferred to belong to their correct breeds, was consistently ~98%. When markers of highest expected heterozygosity were used, genotypes that included at least 8–10 highly variable markers from among the 27 markers genotyped also achieved >95% clustering success. When 12–15 highly variable markers and only 15–20 of the 30 individuals per breed were used, clustering success was at least 90%. We suggest that in species for which population structure is of interest, databases of multilocus genotypes at highly variable markers should be compiled. These genotypes could then be used as training samples for genetic cluster analysis and to facilitate assignments of individuals of unknown origin to populations. The clustering algorithm has potential applications in defining the within-species genetic units that are useful in problems of conservation.

scholarly journals Impact of Working Capital Management on Corporate Profitability- Empirical Evidence from Pharmaceutical Industry of Bangladesh

2018 ◽  
Vol 10 (9) ◽  
pp. 136
Author(s):  
Rakibul Islam ◽  
Mohammad Emdad Hossain ◽  
Mohammad Nazmul Hoq ◽  
Md. Morshedul Alam
Keyword(s):  
Regression Analysis ◽  
Correlation Matrix ◽  
Negative Impact ◽  
Pearson Correlation ◽  
Capital Management ◽  
Working Capital ◽  
Data Set ◽  
Working Capital Management ◽  
Pharmaceutical Firms ◽  
The Impact

Working capital management plays centric role in enhancing operational efficiency and their ultimate profitability. Globally financial managers have been searching the proper way on how to utilize working capital components which prolong profitability. The purpose of this study is to assess the impact of working capital components on profitability indicators of selected pharmaceutical firms in Bangladesh. The paper used financial data of 9 pharmaceutical firms listed in Dhaka stock exchange (DSE) covered 2011-2015. Two methods were used in this study for analysis data set. Firstly, to measure the relationship between selected variables Pearson Correlation matrix was used. Secondly, multiple regression analysis was used to investigate the impact working capital components on profitability of selected pharmaceutical firms. The study also conducted Durbin Watson test to assess autocorrelation of selected variables. In this study the correlation matrix identified a negative correlation between working capital components and profitability, whereas regression analysis found number of days account receivable (AR) had significant positive and current ratio (CR) and debt ratio (DR) had appeared a significant negative impact on profitability.

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