A step-by-step beginner’s protocol for whole genome sequencing of human bacterial pathogens

ABSTRACTThe implementation of routine whole-genome sequencing (WGS) promises to transform our ability to monitor the emergence and spread of bacterial pathogens. Here we combined WGS data from 308 invasiveStaphylococcus aureusisolates corresponding to a pan-European population snapshot, with epidemiological and resistance data. Geospatial visualization of the data is made possible by a generic software tool designed for public health purposes that is available at the project URL (http://www.microreact.org/project/EkUvg9uY?tt=rc). Our analysis demonstrates that high-risk clones can be identified on the basis of population level properties such as clonal relatedness, abundance, and spatial structuring and by inferring virulence and resistance properties on the basis of gene content. We also show thatin silicopredictions of antibiotic resistance profiles are at least as reliable as phenotypic testing. We argue that this work provides a comprehensive road map illustrating the three vital components for future molecular epidemiological surveillance: (i) large-scale structured surveys, (ii) WGS, and (iii) community-oriented database infrastructure and analysis tools.IMPORTANCEThe spread of antibiotic-resistant bacteria is a public health emergency of global concern, threatening medical intervention at every level of health care delivery. Several recent studies have demonstrated the promise of routine whole-genome sequencing (WGS) of bacterial pathogens for epidemiological surveillance, outbreak detection, and infection control. However, as this technology becomes more widely adopted, the key challenges of generating representative national and international data sets and the development of bioinformatic tools to manage and interpret the data become increasingly pertinent. This study provides a road map for the integration of WGS data into routine pathogen surveillance. We emphasize the importance of large-scale routine surveys to provide the population context for more targeted or localized investigation and the development of open-access bioinformatic tools to provide the means to combine and compare independently generated data with publicly available data sets.

Download Full-text

SplitStrains, a tool to identify and separate mixed Mycobacterium tuberculosis infections from WGS data

10.1101/2021.02.07.21250981 ◽

2021 ◽

Author(s):

Einar Gabbasov ◽

Miguel Moreno-Molina ◽

Iñaki Comas ◽

Maxwell Libbrecht ◽

Leonid Chindelevitch

Keyword(s):

Public Health ◽

Mycobacterium Tuberculosis ◽

Whole Genome Sequencing ◽

Genome Sequencing ◽

Bacterial Pathogens ◽

Superior Performance ◽

Whole Genome Sequencing Data ◽

Whole Genome ◽

Sequencing Data ◽

Multiple Strains

AbstractThe occurrence of multiple strains of a bacterial pathogen such as M. tuberculosis or C. difficile within a single human host, referred to as a mixed infection, has important implications for both healthcare and public health. However, methods for detecting it, and especially determining the proportion and identities of the underlying strains, from WGS (whole-genome sequencing) data, have been limited.In this paper we introduce SplitStrains, a novel method for addressing these challenges. Grounded in a rigorous statistical model, SplitStrains not only demonstrates superior performance in proportion estimation to other existing methods on both simulated as well as real M. tuberculosis data, but also successfully determines the identity of the underlying strains.We conclude that SplitStrains is a powerful addition to the existing toolkit of analytical methods for data coming from bacterial pathogens, and holds the promise of enabling previously inaccessible conclusions to be drawn in the realm of public health microbiology.Author summaryWhen multiple strains of a pathogenic organism are present in a patient, it may be necessary to not only detect this, but also to identify the individual strains. However, this problem has not yet been solved for bacterial pathogens processed via whole-genome sequencing. In this paper, we propose the SplitStrains algorithm for detecting multiple strains in a sample, identifying their proportions, and inferring their sequences, in the case of Mycobacterium tuberculosis. We test it on both simulated and real data, with encouraging results. We believe that our work opens new horizons in public health microbiology by allowing a more precise detection, identification and quantification of multiple infecting strains within a sample.

Download Full-text

Editorial: Integrating Whole Genome Sequencing Into Source Attribution and Risk Assessment of Foodborne Bacterial Pathogens

Frontiers in Microbiology ◽

10.3389/fmicb.2021.795098 ◽

2021 ◽

Vol 12 ◽

Author(s):

Frederique Pasquali ◽

Daniel Remondini ◽

Emma Louise Snary ◽

Tine Hald ◽

Laurent Guillier

Keyword(s):

Risk Assessment ◽

Whole Genome Sequencing ◽

Genome Sequencing ◽

Bacterial Pathogens ◽

Whole Genome ◽

Source Attribution

Download Full-text

The forensic analysis of foodborne bacterial pathogens in the age of whole-genome sequencing

Cladistics ◽

10.1111/cla.12012 ◽

2013 ◽

Vol 29 (4) ◽

pp. 449-461 ◽

Cited By ~ 9

Author(s):

Mark R. Wilson ◽

Marc W. Allard ◽

Eric W. Brown

Keyword(s):

Whole Genome Sequencing ◽

Genome Sequencing ◽

Bacterial Pathogens ◽

Forensic Analysis ◽

Whole Genome

Download Full-text

A step-by-step beginner’s protocol for whole genome sequencing of human bacterial pathogens v1 (protocols.io.4xxgxpn)

protocols.io ◽

10.17504/protocols.io.4xxgxpn ◽

2019 ◽

Author(s):

Sanjay Gautam ◽

Rajendra KC ◽

Kelvin WC ◽

Miche l ◽

Ronan F

Keyword(s):

Whole Genome Sequencing ◽

Genome Sequencing ◽

Bacterial Pathogens ◽

Whole Genome

Download Full-text

Whole-Genome Sequencing Analysis of Quorum Quenching Bacterial Strain Acinetobacter lactucae QL-1 Identifies the FadY Enzyme for Degradation of the Diffusible Signal Factor

International Journal of Molecular Sciences ◽

10.3390/ijms21186729 ◽

2020 ◽

Vol 21 (18) ◽

pp. 6729 ◽

Cited By ~ 1

Author(s):

Tian Ye ◽

Tian Zhou ◽

Xudan Xu ◽

Wenping Zhang ◽

Xinghui Fan ◽

...

Keyword(s):

Whole Genome Sequencing ◽

Genome Sequencing ◽

Xanthomonas Campestris ◽

Molecular Mechanisms ◽

Bacterial Pathogens ◽

Quorum Quenching ◽

Site Directed Mutagenesis ◽

Whole Genome ◽

Sequencing Analysis ◽

Diffusible Signal Factor

The diffusible signal factor (DSF) is a fatty acid signal molecule and is widely conserved in various Gram-negative bacteria. DSF is involved in the regulation of pathogenic virulence in many bacterial pathogens, including Xanthomonas campestris pv. campestris (Xcc). Quorum quenching (QQ) is a potential approach for preventing and controlling DSF-mediated bacterial infections by the degradation of the DSF signal. Acinetobacter lactucae strain QL-1 possesses a superb DSF degradation ability and effectively attenuates Xcc virulence through QQ. However, the QQ mechanisms in strain QL-1 are still unknown. In the present study, whole-genome sequencing and comparative genomics analysis were conducted to identify the molecular mechanisms of QQ in strain QL-1. We found that the fadY gene of QL-1 is an ortholog of XccrpfB, a known DSF degradation gene, suggesting that strain QL-1 is capable of inactivating DSF by QQ enzymes. The results of site-directed mutagenesis indicated that fadY is required for strain QL-1 to degrade DSF. The determination of FadY activity in vitro revealed that the fatty acyl-CoA synthetase FadY had remarkable catalytic activity. Furthermore, the expression of fadY in transformed Xcc strain XC1 was investigated and shown to significantly attenuate bacterial pathogenicity on host plants, such as Chinese cabbage and radish. This is the first report demonstrating a DSF degradation enzyme from A. lactucae. Taken together, these findings shed light on the QQ mechanisms of A. lactucae strain QL-1, and provide useful enzymes and related genes for the biocontrol of infectious diseases caused by DSF-dependent bacterial pathogens.

Download Full-text