scholarly journals Anin silicosurvey ofClostridioides difficileextrachromosomal elements

2019 ◽  
Author(s):  
Bastian Hornung ◽  
Ed J. Kuijper ◽  
Wiep Klaas Smits
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
In Silico ◽  
Sequence Data ◽  
Whole Genome ◽  
Clostridioides Difficile ◽  
Extrachromosomal Elements ◽  
European Nucleotide Archive ◽  
Healthcare Associated ◽  
Systematic Identification

AbstractThe gram-positive enteropathogenClostridioides difficileis the major cause of healthcare associated diarrhoea and is also an important cause of community-acquired infectious diarrhoea. Considering the burden of the disease, many studies have employed whole genome sequencing to identify factors that contribute to virulence and pathogenesis. Though extrachromosomal elements such as plasmids are important for these processes in other bacteria, the few characterized plasmids ofC. difficilehave no relevant functions assigned and no systematic identification of plasmids has been carried out to date. Here, we perform anin silicoanalysis of publicly available sequence data, to show that ∼13% of allC. difficilestrains contain extrachromosomal elements, with 1-6 elements per strain. Our approach identifies known plasmids (e.g. pCD6, pCD630 and cloning plasmids) and 6 novel putative plasmid families. Our study shows that plasmids are abundant and may encode functions that are relevant forC. difficilephysiology. The newly identified plasmids may also form the basis for the construction of novel cloning plasmids forC. difficilethat are compatible with existing tools.RepositoriesThe assembled circular type plasmids have been deposited at the European Nucleotide Archive (ENA) under accession numbers ERZ940801 and ERZ940803-ERZ940808.

scholarly journals An in silico survey of Clostridioides difficile extrachromosomal elements

2019 ◽  
Vol 5 (9) ◽  
Author(s):  
Bastian V. H. Hornung ◽  
Ed J. Kuijper ◽  
Wiep Klaas Smits
Keyword(s):  
In Silico ◽  
Type Species ◽  
Sequence Data ◽  
Bacterial Isolates ◽  
Content Type ◽  
Link Type ◽  
Clostridioides Difficile ◽  
Extrachromosomal Elements ◽  
Healthcare Associated ◽  
Systematic Identification

The Gram-positive enteropathogen Clostridioides difficile (Clostridium difficile) is the major cause of healthcare-associated diarrhoea and is also an important cause of community-acquired infectious diarrhoea. Considering the burden of the disease, many studies have employed whole-genome sequencing of bacterial isolates to identify factors that contribute to virulence and pathogenesis. Though extrachromosomal elements (ECEs) such as plasmids are important for these processes in other bacteria, the few characterized plasmids of C. difficile have no relevant functions assigned and no systematic identification of plasmids has been carried out to date. Here, we perform an in silico analysis of publicly available sequence data to show that ~13 % of all C. difficile strains contain ECEs, with 1–6 elements per strain. Our approach identifies known plasmids (e.g. pCD6, pCD630 and cloning plasmids) and six novel putative plasmid families. Our study shows that plasmids are abundant and may encode functions that are relevant for C. difficile physiology. The newly identified plasmids may also form the basis for the construction of novel cloning plasmids for C. difficile that are compatible with existing tools.

scholarly journals Are Many Patients Diagnosed With Healthcare-associated Clostridioides difficile Infections Colonized With the Infecting Strain on Admission?

2019 ◽  
Vol 69 (10) ◽  
pp. 1801-1804 ◽  
Author(s):  
Melany Gonzalez-Orta ◽  
Carlos Saldana ◽  
Yilen Ng-Wong ◽  
Jennifer Cadnum ◽  
Annette Jencson ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Acute Care ◽  
Genome Sequencing ◽  
Acute Care Hospital ◽  
Whole Genome ◽  
Care Hospital ◽  
Clostridioides Difficile ◽  
Healthcare Associated

Abstract In a cohort of 480 patients admitted to an acute care hospital, 68 (14%) had positive perirectal cultures for toxigenic Clostridioides difficile on admission. Of the 11 patients (2%) diagnosed with healthcare-associated C. difficile infections, 3 (27%) had genetically related admission and infection isolates, based on whole-genome sequencing.

scholarly journals Clostridioides difficile Whole-genome Sequencing Differentiates Relapse With the Same Strain From Reinfection With a New Strain

2020 ◽  
Author(s):  
Janice Cho ◽  
Scott Cunningham ◽  
Meng Pu ◽  
Ryan J Lennon ◽  
Jennifer Dens Higano ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Sequence Data ◽  
Infection Prevention And Control ◽  
Whole Genome ◽  
Clostridioides Difficile ◽  
Allelic Differences ◽  
Clostridioides Difficile Infection ◽  
And Control ◽  
Zip Code

Abstract Background Current approaches in tracking Clostridioides difficile infection (CDI) and individualizing patient management are incompletely defined. Methods We recruited 468 subjects with CDI at Mayo Clinic Rochester between May and December 2016 and performed whole-genome sequencing (WGS) on C. difficile isolates from 397. WGS was also performed on isolates from a subset of the subjects at the time of a recurrence of infection. The sequence data were analyzed by determining core genome multilocus sequence type (cgMLST), with isolates grouped by allelic differences and the predicted ribotype. Results There were no correlations between C. difficile isolates based either on cgMLST or ribotype groupings and CDI outcome. An epidemiologic assessment of hospitalized subjects harboring C. difficile isolates with ≤2 allelic differences, based on standard infection prevention and control assessment, revealed no evidence of person-to-person transmission. Interestingly, community-acquired CDI subjects in 40% of groups with ≤2 allelic differences resided within the same zip code. Among 18 subjects clinically classified as having recurrent CDI, WGS revealed 14 with initial and subsequent isolates differing by ≤2 allelic differences, suggesting a relapse of infection with the same initial strain, and 4 with isolates differing by >50 allelic differences, suggesting reinfection. Among the 5 subjects classified as having a reinfection based on the timing of recurrence, 3 had isolates with ≤2 allelic differences between them, suggesting a relapse, and 2 had isolates differing by >50 allelic differences, suggesting reinfection. Conclusions Our findings point to potential transmission of C. difficile in the community. WGS better differentiates relapse from reinfection than do definitions based on the timing of recurrence.

scholarly journals Transition From PCR-Ribotyping to Whole Genome Sequencing Based Typing of Clostridioides difficile

2021 ◽  
Vol 11 ◽  
Author(s):  
Helena M. B. Seth-Smith ◽  
Michael Biggel ◽  
Tim Roloff ◽  
Vladimira Hinic ◽  
Thomas Bodmer ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Sequence Data ◽  
Molecular Diagnostic ◽  
Whole Genome ◽  
Clostridioides Difficile ◽  
Challenges And Opportunities ◽  
Long Read ◽  
Illumina Sequence ◽  
Pcr Ribotyping

Clostridioides difficile causes nosocomial outbreaks which can lead to severe and even life-threatening colitis. Rapid molecular diagnostic tests allow the identification of toxin-producing, potentially hypervirulent strains, which is critical for patient management and infection control. PCR-ribotyping has been used for decades as the reference standard to investigate transmission in suspected outbreaks. However, the introduction of whole genome sequencing (WGS) for molecular epidemiology provides a realistic alternative to PCR-ribotyping. In this transition phase it is crucial to understand the strengths and weaknesses of the two technologies, and to assess their correlation. We aimed to investigate ribotype prediction from WGS data, and options for analysis at different levels of analytical granularity. Ribotypes cannot be directly determined from short read Illumina sequence data as the rRNA operons including the ribotype-defining ISR fragments collapse in genome assemblies, and comparison with traditional PCR-ribotyping results becomes impossible. Ribotype extraction from long read Oxford nanopore data also requires optimization. We have compared WGS-based typing with PCR-ribotyping in nearly 300 clinical and environmental isolates from Switzerland, and in addition from the Enterobase database (n=1778). Our results show that while multi-locus sequence type (MLST) often correlates with a specific ribotype, the agreement is not complete, and for some ribotypes the resolution is insufficient. Using core genome MLST (cgMLST) analysis, there is an improved resolution and ribotypes can often be predicted within clusters, using cutoffs of 30-50 allele differences. The exceptions are ribotypes within known ribotype complexes such as RT078/RT106, where the genome differences in cgMLST do not reflect the ribotype segregation. We show that different ribotype clusters display different degrees of diversity, which could be important for the definition of ribotype cluster specific cutoffs. WGS-based analysis offers the ultimate resolution to the SNP level, enabling exploration of patient-to-patient transmission. PCR-ribotyping does not sufficiently discriminate to prove nosocomial transmission with certainty. We discuss the associated challenges and opportunities in a switch to WGS from conventional ribotyping for C. difficile.

scholarly journals Genetic Characterization of Brucella spp.: Whole Genome Sequencing-Based Approach for the Determination of Multiple Locus Variable Number Tandem Repeat Profiles

2021 ◽  
Vol 12 ◽  
Author(s):  
Ana Pelerito ◽  
Alexandra Nunes ◽  
Teresa Grilo ◽  
Joana Isidro ◽  
Catarina Silva ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
In Silico ◽  
Variable Number Tandem Repeat ◽  
Epidemiological Studies ◽  
Variable Number ◽  
Epidemiological Surveillance ◽  
Future Application ◽  
Whole Genome

Brucellosis is an important zoonosis that is emerging in some regions of the world, gaining increased relevance with the inclusion of the causing agent Brucella spp. in the class B bioterrorism group. Until now, multi-locus VNTR Analysis (MLVA) based on 16 loci has been considered as the gold standard for Brucella typing. However, this methodology is laborious, and, with the rampant release of Brucella genomes, the transition from the traditional MLVA to whole genome sequencing (WGS)-based typing is on course. Nevertheless, in order to avoid a disruptive transition with the loss of massive genetic data obtained throughout the last decade and considering that the transition timings will vary considerably among different countries, it is important to determine WGS-based MLVA alleles of the nowadays sequenced genomes. On this regard, we aimed to evaluate the performance of a Python script that had been previously developed for the rapid in silico extraction of the MLVA alleles, by comparing it to the PCR-based MLVA procedure over 83 strains from different Brucella species. The WGS-based MLVA approach detected 95.3% of all possible 1,328 hits (83 strains×16 loci) and showed an agreement rate with the PCR-based MLVA procedure of 96.4% for MLVA-16. According to our dataset, we suggest the use of a minimal depth of coverage of ~50x and a maximum number of ~200 contigs as guiding “boundaries” for the future application of the script. In conclusion, the evaluated script seems to be a very useful and robust tool for the in silico determination of MLVA profiles of Brucella strains, allowing retrospective and prospective molecular epidemiological studies, which are important for maintaining an active epidemiological surveillance of brucellosis.

scholarly journals Genome Sequencing of Polydrug-, Multidrug-, and Extensively Drug-Resistant Mycobacterium tuberculosis Strains from South India

2019 ◽  
Vol 8 (12) ◽  
Author(s):  
Sivakumar Shanmugam ◽  
Narender Kumar ◽  
Dina Nair ◽  
Mohan Natrajan ◽  
Srikanth Prasad Tripathy ◽  
...  
Keyword(s):  
Mycobacterium Tuberculosis ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
South India ◽  
Sequence Data ◽  
Whole Genome ◽  
Drug Resistant ◽  
Resistance Mutations ◽  
Content Type ◽  
Extensively Drug Resistant

The genomes of 16 clinical Mycobacterium tuberculosis isolates were subjected to whole-genome sequencing to identify mutations related to resistance to one or more anti-Mycobacterium drugs. The sequence data will help in understanding the genomic characteristics of M. tuberculosis isolates and their resistance mutations prevalent in South India.

scholarly journals Frequency of Antimicrobial Resistance Genes in Salmonella From Brazil by in silico Whole-Genome Sequencing Analysis: An Overview of the Last Four Decades

2020 ◽  
Vol 11 ◽  
Author(s):  
Grazielle Lima Rodrigues ◽  
Pedro Panzenhagen ◽  
Rafaela Gomes Ferrari ◽  
Anamaria dos Santos ◽  
Vania Margaret Flosi Paschoalin ◽  
...  
Keyword(s):  
Antimicrobial Resistance ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Resistance Genes ◽  
In Silico ◽  
Whole Genome ◽  
Sequencing Analysis ◽  
Antimicrobial Resistance Genes

scholarly journals Detecting Staphylococcus aureus Virulence and Resistance Genes: a Comparison of Whole-Genome Sequencing and DNA Microarray Technology

2016 ◽  
Vol 54 (4) ◽  
pp. 1008-1016 ◽  
Author(s):  
Lena Strauß ◽  
Ulla Ruffing ◽  
Salim Abdulla ◽  
Abraham Alabi ◽  
Ruslan Akulenko ◽  
...  
Keyword(s):  
Staphylococcus Aureus ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Dna Microarray ◽  
Resistance Genes ◽  
In Silico ◽  
Target Genes ◽  
Whole Genome ◽  
Microarray Hybridization ◽  
Content Type

Staphylococcus aureusis a major bacterial pathogen causing a variety of diseases ranging from wound infections to severe bacteremia or intoxications. Besides host factors, the course and severity of disease is also widely dependent on the genotype of the bacterium. Whole-genome sequencing (WGS), followed by bioinformatic sequence analysis, is currently the most extensive genotyping method available. To identify clinically relevant staphylococcal virulence and resistance genes in WGS data, we developed anin silicotyping scheme for the software SeqSphere+(Ridom GmbH, Münster, Germany). The implemented target genes (n= 182) correspond to those queried by the IdentibacS. aureusGenotyping DNA microarray (Alere Technologies, Jena, Germany). Thein silicoscheme was evaluated by comparing the typing results of microarray and of WGS for 154 humanS. aureusisolates. A total of 96.8% (n= 27,119) of all typing results were equally identified with microarray and WGS (40.6% present and 56.2% absent). Discrepancies (3.2% in total) were caused by WGS errors (1.7%), microarray hybridization failures (1.3%), wrong prediction of ambiguous microarray results (0.1%), or unknown causes (0.1%). Superior to the microarray, WGS enabled the distinction of allelic variants, which may be essential for the prediction of bacterial virulence and resistance phenotypes. Multilocus sequence typing clonal complexes and staphylococcal cassette chromosomemecelement types inferred from microarray hybridization patterns were equally determined by WGS. In conclusion, WGS may substitute array-based methods due to its universal methodology, open and expandable nature, and rapid parallel analysis capacity for different characteristics in once-generated sequences.

scholarly journals Discordant bioinformatic predictions of antimicrobial resistance from whole-genome sequencing data of bacterial isolates: An inter-laboratory study

2019 ◽  
Author(s):  
Ronan M. Doyle ◽  
Denise M. O’Sullivan ◽  
Sean D. Aller ◽  
Sebastian Bruchmann ◽  
Taane Clark ◽  
...  
Keyword(s):  
Antimicrobial Resistance ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Laboratory Study ◽  
Clinical Microbiology ◽  
Sequence Data ◽  
Clinical Samples ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Sequencing Data

AbstractBackgroundAntimicrobial resistance (AMR) poses a threat to public health. Clinical microbiology laboratories typically rely on culturing bacteria for antimicrobial susceptibility testing (AST). As the implementation costs and technical barriers fall, whole-genome sequencing (WGS) has emerged as a ‘one-stop’ test for epidemiological and predictive AST results. Few published comparisons exist for the myriad analytical pipelines used for predicting AMR. To address this, we performed an inter-laboratory study providing sets of participating researchers with identical short-read WGS data sequenced from clinical isolates, allowing us to assess the reproducibility of the bioinformatic prediction of AMR between participants and identify problem cases and factors that lead to discordant results.MethodsWe produced ten WGS datasets of varying quality from cultured carbapenem-resistant organisms obtained from clinical samples sequenced on either an Illumina NextSeq or HiSeq instrument. Nine participating teams (‘participants’) were provided these sequence data without any other contextual information. Each participant used their own pipeline to determine the species, the presence of resistance-associated genes, and to predict susceptibility or resistance to amikacin, gentamicin, ciprofloxacin and cefotaxime.ResultsIndividual participants predicted different numbers of AMR-associated genes and different gene variants from the same clinical samples. The quality of the sequence data, choice of bioinformatic pipeline and interpretation of the results all contributed to discordance between participants. Although much of the inaccurate gene variant annotation did not affect genotypic resistance predictions, we observed low specificity when compared to phenotypic AST results but this improved in samples with higher read depths. Had the results been used to predict AST and guide treatment a different antibiotic would have been recommended for each isolate by at least one participant.ConclusionsWe found that participants produced discordant predictions from identical WGS data. These challenges, at the final analytical stage of using WGS to predict AMR, suggest the need for refinements when using this technology in clinical settings. Comprehensive public resistance sequence databases and standardisation in the comparisons between genotype and resistance phenotypes will be fundamental before AST prediction using WGS can be successfully implemented in standard clinical microbiology laboratories.

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