- Volume 72, Issue 12, 2024

Rift Valley fever (RVF) is caused by infection with Rift Valley fever virus (RVFV), a mosquito-borne RNA virus that affects both humans and livestock species. Humans can also acquire infection from contact with infected animals and contaminated bodily fluid. Veterinary vaccines are available for use in livestock, but no vaccines have been approved for humans to date. The virus is currently endemic in most sub-Saharan regions of Africa but numerous incursions into Middle Eastern countries and islands in the Indian Ocean, such as Mayotte (an overseas Department of France), have occurred in the past decade. The risk of further geographical expansion is high and therefore additional investigation is warranted to better understand disease transmission and pathogenic mechanisms to develop threat mitigation strategies.

Introduction. Various plasmid-mediated resistance genes have been reported in Glaesserella parasuis , but little is known about their global distribution features, evolution pattern and spread.

Gap Statement. The potential mobilization mechanisms of resistance plasmids in G. parasuis have been poorly explored.

Aim. The aim of the study was to investigate the prevalence and diversity of plasmid-mediated resistance genes among G. parasuis isolates, and focus on the analysis of the features of the resistance plasmids from G. parasuis .

Method. The plasmids tested were sequenced using the Illumina HiSeq platform in conjunction with PCR and inverted PCR. The susceptibility of the host strains was determined by broth microdilution. The transfer of plasmids tested was conducted by electroporation. The sequence data were compared using bioinformatics tools and the data from our laboratory and the National Center for Biotechnology Information (NCBI) database.

Results. Nineteen plasmids were identified from our laboratory and these resistance plasmids were functional and transferable. Moreover, we clustered five types of genetic backbones of plasmids from G. parasuis and revealed the global distribution features of the plasmid-mediated resistance genes.

Conclusions. This is the first report of the coexistence of tet(H)-bearing type I plasmid and lnu(C)-bearing type II plasmid in one G. parasuis clinical isolate. In addition, this study provides the first view of the global distribution of plasmid-mediated resistance genes and classifies the plasmids in G. parasuis according to their backbone regions.

Introduction. Antibody testing for evidence of a recent Bordetella pertussis infection by estimating anti-pertussis toxin immunoglobulin G (anti-PT-IgG) titres by enzyme-linked immunosorbent assays is often recommended for those with a cough lasting more than 14 days. Interpreting results varies, with studies recommending different anti-PT-IgG titre thresholds for assigning positivity. In England, early work looking at antibody titre distributions for samples submitted from April 2010 to July 2012 found an optimal threshold of greater than 70 IU ml−1 for good sensitivity, specificity and positive predictive value.

Aim. The aim of this study is to use the same mixture modelling technique to determine if the 70 IU ml−1 threshold remains appropriate when assessing data before, during and after the outbreak of pertussis in 2011–2012.

Methods. We reviewed titres for all serology-tested samples in England between 1 July 2008 to 30 June 2022. IgG titres were used to calculate the positivity based on the current threshold of 70 IU ml−1, the median duration of cough for individuals who tested positive and, through mixture modelling, the sensitivity, specificity, positive and negative predictive values (PPV and NPV) of assay thresholds.

Results. Positivity rates increased from 21.7 % prior to the outbreak to 30.3 % during the outbreak and dropped to 25.1 % post-outbreak; similar to estimates from the mixture model of 20.5, 33.3 and 28.7 %, respectively. Although the estimated sensitivity dropped during and after the outbreak when applying the 70 IU ml−1 threshold, the PPV remained high and therefore no change to this threshold is warranted.

Conclusion. Mixture modelling is a useful tool to establish thresholds, but reassessment should also be done when there have been changes to prevalence and/or testing regimes to determine whether there have been any changes in sensitivity, specificity, PPV, and NPV and whether the threshold should be revised.

Introduction. Studying taxonomic and functional signatures of respiratory microbiomes provide a better understanding of airway diseases.

Gap Statement. Several human airway metagenomics studies have identified taxonomic and functional features restricted to a single disease condition and the findings are not comparable across airway diseases due to use of different samples, NGS platforms, and bioinformatics databases and tools.

Aim. To study the microbial taxonomic and functional components of sputum microbiome across airway diseases and healthy smokers.

Methodology. Here, 57 whole metagenome shotgun sequencing (WMSS) runs coming from the sputum of five airway diseases: asthma, bronchiectasis, chronic obstructive pulmonary diseases (COPD), cystic fibrosis (CF), tuberculosis (TB), and healthy smokers as the control were reanalysed using a common WMSS analysis pipeline.

Results. Shannon’s index (alpha diversity) of the healthy smoker group was the highest among all. The beta diversity showed that the sputum microbiome is distinct in major airway diseases such as asthma, COPD and cystic fibrosis. The microbial composition based on differential analysis showed that there are specific markers for each airway disease like Acinetobacter bereziniae as a marker for COPD and Achromobacter xylosoxidans as a marker of cystic fibrosis. Pathways and metabolites identified from the sputum microbiome of these five diseases and healthy smokers also show specific markers. ‘ppGpp biosynthesis’ and ‘purine ribonucleosides degradation’ pathways were identified as differential markers for bronchiectasis and COPD. In this meta-analysis, besides bacteria kingdom, Aspergillus fumigatus was detected in asthma and COPD, and Roseolovirus human betaherpesvirus 7 was detected in COPD. Our analysis showed that the majority of the gene families specific to the drug-resistant associated genes were detected from opportunistic pathogens across all the groups.

Conclusion. In summary, the specific species in the sputum of airway diseases along with the microbial features like specific gene families, pathways, and metabolites were identified which can be explored for better diagnosis and therapy.