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Biggs, P. J.

Publications and source records attributed to Biggs, P. J..

5 recordsLinked to original sources

Evidence for a role of extraintestinal pathogenic Escherichia coli, Enterococcus faecalis and Streptococcus gallolyticus in the aetiology of exudative cloacitis in the critically endangered kakapo (Strigops habroptilus)

The k[a]k[a]p[o] is a critically endangered flightless parrot which suffers from exudative cloacitis, a debilitating disease resulting in inflammation of the vent margin or cloaca. Despite this disease emerging over 20 years ago, the cause of exudative cloacitis remains elusive. We used total RNA sequencing and metatranscriptomic analysis to characterise the infectome of lesions and cloacal swabs from nine k[a]k[a]p[o] affected with exudative cloacitis, and compared this to cloacal swabs from 45 non-diseased k[a]k[a]p[o]. We identified three bacterial species - Streptococcus gallolyticus, Enterococcus faecalis and Escherichia coli - as significantly more abundant in diseased k[a]k[a]p[o] compared to healthy individuals. The genetic diversity observed in both S. gallolyticus and E. faecalis among diseased k[a]k[a]p[o] suggests that these bacteria originate from exogenous sources rather than from k[a]k[a]p[o]-to-k[a]k[a]p[o] transmission. The presence of extraintestinal pathogenic E. coli (ExPEC)-associated virulence factors in the diseased k[a]k[a]p[o] population suggests that E. coli may play a critical role in disease progression by facilitating iron acquisition and causing DNA damage in host cells, possibly in association with E. faecalis. No avian viral, fungal nor other parasitic species were identified. These results, combined with the consistent presence of one E. coli gnd sequence type across multiple diseased birds, suggests that this species may be the primary cause of exudative cloacitis. These findings shed light on possible causative agents of exudative cloacitis, and offer insights into the interplay of microbial factors influencing the disease.

microbiology↗

Genomic epidemiology of ESBL-producing Escherichia coli from humans and an Aotearoa New Zealand river

In Aotearoa New Zealand, urinary tract infections in humans are commonly caused by extended-spectrum beta-lactamase (ESBL)-producing Escherichia coli. This group of antimicrobial resistant bacteria are often multidrug resistant. However, there is limited information on ESBL-producing E. coli found in the environment and their link with human clinical isolates. In this study, we examined the genetic relationship of environmental and human clinical ESBL-producing E. coli and isolates collected in parallel within the same area over 14 months. Environmental samples were collected from treated effluent, stormwater and multiple locations along an Aotearoa New Zealand river. Treated effluent, stormwater and river water sourced downstream of the treated outflow point were the main sources of ESBL-producing E. coli (7/14 samples, 50.0%; 3/6 samples, 50%; and 15/28 samples, 54% respectively). Whole genome sequence comparison was carried out on 307 human clinical and 45 environmental ESBL-producing E. coli isolates. Sequence type 131 was dominant for both clinical (147/307, 47.9%) and environmental isolates (11/45, 24.4%). The most prevalent ESBL genes were both blaCTX-M-27 and blaCTX-M-15 for the clinical isolates (134/307, 43.6%) and blaCTX-M-15 for the environmental isolates (28/45, 62.2%). A core single nucleotide polymorphism analysis of these isolates suggested that some strains were shared between humans and the local river. These results highlight the importance of understanding different transmission pathways for the spread of ESBL-producing E. coli. 2. Impact statementExtended spectrum beta lactamase (ESBL)-producing E. coli frequently cause urinary tract infections that exhibit multidrug resistance. Surveillance studies have identified the predominant strains and resistance genes associated with urinary tract infections. However, there is limited information on the extent of spread beyond the patient. We describe the genetic relatedness of ESBL-producing environmental and clinical E. coli isolated during the same temporal-spatial period in Aotearoa New Zealand. Comparative genomic analyses of these bacteria provide evidence of clonal spread between humans and the environment, highlighting the need to integrate environmental surveillance into antimicrobial resistance monitoring. 3. Data summaryAll Illumina sequence reads for this study have been deposited in GenBank under BioProject PRJNA1032159, except for strain SB0283h1, whose data can be found under BioProject PRJNA715472. The sequence read accessions for each genome are provided in the supplementary material. The code used for the genomic and statistical analyses is available from the GitHub repository https://github.com/sburgess1/Manawat-_ESBL. The authors confirm all supporting data and protocols have been provided within the article or through supplementary data files.

microbiology↗

Visual integration of GWAS and differential expression results with the hidecan R package

SummaryWe present hidecan, an R package for generating visualisations that summarise the results of one or more genome-wide association studies and differential expression analyses, as well as manually curated candidate genes, e.g. extracted from the literature. Availability and ImplementationThe hidecan package is implemented in R and is publicly available on the CRAN repository (https://CRAN.R-project.org/package=hidecan) and on GitHub (https://github.com/PlantandFoodResearch/hidecan). A description of the package, as well as a detailed tutorial are available at https://plantandfoodresearch.github.io/hidecan/. Contactolivia.angelin-bonnet@plantandfood.co.nz. Supplementary informationSupplementary data are available.

genetics↗

Lost In The Forest

Levels of a predictor variable that are absent when a classification tree is grown can not be subject to an explicit splitting rule. This is an issue if these absent levels then present in a new observation for prediction. To date, there remains no satisfactory solution for absent levels in random forest models. Unlike missing data, absent levels are fully observed and known. Ordinal encoding of predictors allows absent levels to be integrated and used for prediction. Using a case study on source attribution of Campylobacter species using whole genome sequencing (WGS) data as predictors, we examine how target-agnostic versus target-based encoding of predictor variables with absent levels affects the accuracy of random forest models. We show that a target-based encoding approach using class probabilities, with absent levels designated the highest rank, is systematically biased, and that this bias is resolved by encoding absent levels according to the a priori hypothesis of equal class probability. We present a novel method of ordinal encoding predictors via principal coordinates analysis (PCO) which capitalizes on the similarity between pairs of predictor levels. Absent levels are encoded according to their similarity to each of the other levels in the training data. We show that the PCO-encoding method performs at least as well as the target-based approach and is not biased.

bioinformatics↗

Distinct gut microbiome patterns associate with consensus molecular subtypes of colorectal cancer

Colorectal cancer (CRC) is a heterogeneous disease and recent advances in subtype classification have successfully stratified the disease using molecular profiling. The contribution of bacterial species to CRC development is increasingly acknowledged, and here, we sought to analyse CRC microbiomes and relate them to tumour consensus molecular subtypes (CMS), in order to better understand the relationship between bacterial species and the molecular mechanisms associated with CRC subtypes. We classified 34 tumours into CRC subtypes using RNA-sequencing derived gene expression and determined relative abundances of bacterial taxonomic groups using 16S rRNA amplicon metabarcoding. 16S rRNA analysis showed enrichment of Fusobacteria and Bacteroidetes, and decreased levels of Firmicutes and Proteobacteria in CMS1. A more detailed analysis of bacterial taxa using non-human RNA-sequencing reads uncovered distinct bacterial communities associated with each molecular subtype. The most highly enriched species associated with CMS1 included Fusobacterium hwasookii and Porphyromonas gingivalis. CMS2 was enriched for Selenomas and Prevotella species, while CMS3 had few significant associations. Targeted quantitative PCR validated these findings and also showed an enrichment of Fusobacterium nucleatum, Parvimonas micra and Peptostreptococcus stomatis in CMS1. In this study, we have successfully associated individual bacterial species to CRC subtypes for the first time.

cancer biology↗