Biology subjects

Bloomfield, S.

Publications and source records attributed to Bloomfield, S..

5 recordsLinked to original sources

bioRxiv2026

Genomic epidemiology of the 2017-2023 outbreak of Mycoplasma bovis sequence type ST21 in New Zealand

Mycoplasma bovis was first detected in cattle in New Zealand in 2017, prompting an eradication programme that incorporated extensive surveillance and a test-and-cull policy. Genome sequence data and phylodynamic models were used to inform decision making throughout the eradication programme. Isolates from 697 cattle on 126 farms were collected and sequenced between July 2017 and December 2023. Phylodynamic models were used to estimate the time of most recent common ancestor, the effective reproduction number (Reff) and effective population size, and long-range and local between-farm transmission dynamics. The analysis revealed the dramatic impact of movement restrictions and culling up to early 2020, with a sharp reduction in the Reff to less than 1 in 2018/9 and the extinction of two of three major lineages in 2020. This was followed by three-years of residual infection in farms in the South Island, associated with persistent infection of a large feedlot farm and nearby farms. The comprehensive dataset of genomic and epidemiological data provided a unique opportunity to study the dynamics of a country-wide outbreak of a single-host pathogen from first detection to potential eradication, underlining the utility of integrated genomic surveillance during an outbreak response. Author summaryThe economically important cattle pathogen, Mycoplasma bovis, was first detected in New Zealand in 2017. This led to a large-scale, successful control programme aimed at eradication of the pathogen. The decision to undertake an eradication programme was informed by initial analyses of whole genome sequences from isolates collected as part of the surveillance programme. The analysis showed that the bacteria had entered New Zealand relatively recently and was unlikely to be widespread. Over the subsequent years, genome sequencing and modelling of transmission dynamics informed important policy decisions made by the New Zealand Government and the cattle industry, and helped to monitor progress of the eradication programme. The impact of the detection, movement control and culling programme was profound, with sharp reductions in transmission between 2018 and 2020. This was followed by a long tail of localised infection in the South Island, involving transmission from a large feedlot farm. Provisional eradication was achieved after depopulation of this feedlot. This analysis highlights the role of genomic surveillance and modelling to inform decision making during an infectious disease outbreak.

genomics↗

bioRxiv2021

Tatajuba - Exploring the distribution of homopolymer tracts

Length variation of homopolymeric tracts, which induces phase variation, is known to regulate gene expression leading to phenotypic variation in a wide range of bacterial species. There is no specialised bioinformatics software which can, at scale, exhaustively explore and describe these features from sequencing data. Identifying these is non-trivial as sequencing and bioinformatics methods are prone to introducing artefacts when presented with homopolymeric tracts due to the decreased base diversity. We present tatajuba, which can automatically identify potential homopolymeric tracts and their putative phenotypic impact, allowing for rapid investigation. We use it to detect all tracts in two separate datasets, one of Campylobacter jejuni and one of three Bordetella species, and to highlight those tracts that are polymorphic across samples. With this we confirm homopolymer tract variation with phenotypic impact found in previous studies and additionally find many more with potential variability. The software is written in C and is available under the open source license GNU GPL version 3 from https://github.com/quadram-institute-bioscience/tatajuba.

bioinformatics↗

bioRxiv2020

Characterising the methylome of Legionellalongbeachae serogroup 1 clinical isolates and assessing geo-temporal genetic diversity

Legionella longbeachae is an environmental bacterium that is commonly found in soil and composted plant material. In New Zealand (NZ) it is the most clinically significant Legionella species causing around two-thirds of all notified cases of Legionnaires disease. Here we report the sequencing and analysis of the geo-temporal genetic diversity of 54 L. longbeachae serogroup 1 (sg1) clinical isolates that were derived from cases from around NZ over a 22-year period, including one complete genome and its associated methylome. Our complete genome consisted of a 4.1 Mb chromosome and a 108 kb plasmid. The genome was highly methylated with two known epigenetic modifications, m4C and m6A, occurring in particular sequence motifs within the genome. Phylogenetic analysis demonstrated the 54 sg1 isolates belonged to two main clades that last shared a common ancestor between 108 BCE and 1608 CE. These isolates also showed diversity at the genome-structural level, with large-scale arrangements occurring in some regions of the chromosome and evidence of extensive chromosomal and plasmid recombination. This includes the presence of plasmids derived from recombination and horizontal gene transfer between various Legionella species, indicating there has been both intra-species and inter-species gene flow. However, because similar plasmids were found among isolates within each clade, plasmid recombination events may pre-empt the emergence of new L. longbeachae strains. Our high-quality reference genome and extensive genetic diversity data will serve as a platform for future work linking genetic, epigenetic and functional diversity in this globally important emerging environmental pathogen. Author SummaryLegionnaires disease is a serious, sometimes fatal pneumonia caused by bacteria of the genus Legionella. In New Zealand, the species that causes the majority of disease is Legionella longbeachae. Although the analyses of pathogenic bacterial genomes is an important tool for unravelling evolutionary relationships and identifying genes and pathways that are associated with their disease-causing ability, until recently genomic data for L. longbeachae has been sparse. Here, we conducted a large-scale genomic analysis of 54 L. longbeachae isolates that had been obtained from people hospitalised with Legionnaires disease between 1993 and 2015 from 8 regions around New Zealand. Based on our genome analysis the isolates could be divided into two main groups that persisted over time and last shared a common ancestor up to 1700 years ago. Analysis of the bacterial chromosome revealed areas of high modification through the addition of methyl groups and these were associated with particular DNA sequence motifs. We also found there have been large-scale rearrangements in some regions of the chromosome, producing variability between the different L. longbeacahe strains, as well as evidence of gene-flow between the various Legionella species via the exchange of plasmid DNA.

microbiology↗

bioRxiv2019

Investigation of the validity of two Bayesian ancestral state reconstruction models for estimating Salmonella transmission during outbreaks

Ancestral state reconstruction models use genetic data to characterize a group of organisms common ancestor. These models have been applied to salmonellosis outbreaks to estimate the number of transmissions between different animal species that share similar geographical locations, with animal host as the state. However, as far as we are aware, no studies have validated these models for outbreak analysis. In this study, salmonellosis outbreaks were simulated using a stochastic Susceptible-Infected-Recovered model, and the host population and transmission parameters of these simulated outbreaks were estimated using Bayesian ancestral state reconstruction models (discrete trait analysis (DTA) and structured coalescent (SC)). These models were unable to accurately estimate the number of transmissions between the host populations or the amount of time spent in each host population. The DTA model was inaccurate because it assumed the number of isolates sampled from each host population was proportional to the number of individuals infected within each host population. The SC model was inaccurate possibly because it assumed that each host populations effective population size was constant over the course of the simulated outbreaks. This study highlights the need for phylodynamic models that can take into consideration factors that influence the characteristics and behavior of outbreaks, e.g. changing effective population sizes, variation in infectious periods, intra-population transmissions, and disproportionate sampling of infected individuals.

epidemiology↗

bioRxiv2018

The washing machine as a reservoir for transmission of ESBL-producing Klebsiella oxytoca in newborns

During the period from April 2012 to May 2013, 13 newborns and one child in a paediatric hospital ward in Germany were found to be colonised with a distinct clinical clone of an (extended spectrum {beta}-lactamase) (ESBL)-producing Klebsiella oxytoca. This clone was specific to this hospital and had not been previously isolated in Germany.\n\nA source-tracking analysis was carried out to identify the source and transmission pathways of the ESBL-producing K. oxytoca clone. A systematic environmental survey of the ward and an audit of the procedures for cleaning and disinfecting surfaces, instruments, incubators, and washing machines was performed. Microbiological samples were obtained from environmental surfaces. Risk factors were analysed for epidemiological linkage.\n\nIsolates of an ESBL-producing K. oxytoca were found in the detergent drawer and on the rubber door seal of a washing machine and in two sinks. These strains were typed by pulsed-field-gel-electrophoresis (PFGE) and compared with the isolates from the newborns and their clothing and found to be identical. The retrospective analysis demonstrated that only newborns who had worn clothes that had been washed in the washing machine were colonised with the identical clone. After the washing machine was taken out of use, no further cases were detected over the following 4-year period.\n\nWe conclude that washing machines are potential reservoirs and vectors for transmission of Enterobacteriaceae, and likely other bacteria.\n\nImportanceWashing machines should be further investigated as possible sites for horizontal gene transfer (ESBL-/carbapenemase-genes) and cross-contamination of clinically important Gram-negative strains. Particularly in the healthcare sector, the knowledge of possible (re-) contamination of laundry (patients clothes, staff uniforms) with multidrug-resistant Gram-negative bacteria could help to prevent and control nosocomial infections. To date, the potential of the washing machine as a source and vector of antibiotic-resistant gram-negative bacteria causing an outbreak in a clinical setting has not been investigated. This report shows that sampling of washing machines should be included in environmental audits associated with outbreak control management, and conditions for the laundering of baby 64 clothing should be reviewed.

microbiology↗