Aim The pathogenesis of acute diverticulitis (AD) remains incompletely understood, despite it being one of the most common gastrointestinal conditions worldwide. The aim of this study was to investigate the role of the colonic microbiome in the pathogenesis of AD. Method A prospective case–control study was performed, comparing the microbiome of AD patients with that of controls, using 16S rRNA sequencing of rectal swab samples. Results The microbiome of individuals with AD showed lower diversity than that of controls. There were significant compositional differences observed, with a lower abundance of commensal bacterial families and genera such as Lachnospiraceae, Ruminococcus and Faecalibacterium in AD patients compared with controls, and there was an increase in several genera with known pathogenic roles including Fusobacteria, Prevotella and Paraprevotella. Conclusion This is the largest study to date to examine the microbiota of AD patients, and adds evidence to the proposed hypothesis that alterations in the colonic microbiome play a role in the pathogenesis of AD.

We sought to determine the epidemiology of carbapenem-resistant Enterobacteriaceae and to investigate the emergence of carbapenem-resistant Klebsiella pneumoniae in two teaching hospitals in Manila, Philippines. We screened 364 Enterobacteriaceae for carbapenem resistance between 2012 and 2013 and detected four carbapenem-resistant K. pneumoniae isolates from three different patients. We used whole genome sequencing to determine the antibiotic resistance profiles and confirmed the presence of carbapenemase genes by multiplex PCR. We used multilocus sequence typing and PCR-based replicon typing to genetically characterize the carbapenem-resistant isolates. The carbapenemase gene blaNDM was detected in K. pneumoniae isolates from two patients. The first patient had ventilator-associated pneumonia and lumbar shunt infection from K. pneumoniae ST273 carrying blaNDM-7. The second patient had asymptomatic genitourinary colonization with K. pneumoniae ST656 carrying blaNDM-1. The third patient had a gluteal abscess with K. pneumoniae ST1 that did not carry a carbapenemase gene, but did carry blaDHA-1, blaOXA-1, and blaSHV-1. In this study, we report the first cases of blaNDM-carrying pathogens in the Philippines and add to the growing evidence of the worldwide spread of ST273 and NDM-7, a more efficient carbapenem hydrolyzer than NDM-1.

BackgroundThe identification of functional processes taking place in microbiome communities augment traditional microbiome taxonomic studies, giving a more complete picture of interactions taking place within the community. While there are applications that perform functional annotation on metagenome or metatranscriptomes, very few of these are able to link taxonomic identity to function and are limited by their input types or databases used.ResultsHere we present MetaFunc, a workflow which takes input reads, and from these 1) identifies species present in the microbiome sample and 2) provides gene ontology (GO) annotations associated with the species identified. MetaFunc can also provide a differential abundance analysis step comparing species between sample conditions. In addition, MetaFunc allows mapping of reads to a host genome, and separates these reads, before proceeding with the microbiome analyses. From the host reads, MetaFunc is able to identify host genes, perform differential gene expression analysis, and gene-set enrichment analysis. A final correlation analysis between microbial species and host genes can also be performed. Finally, MetaFunc builds an R shiny application that allows users to view and interact with the microbiome results. In this paper we show how MetaFunc can be applied to metatranscriptomic datasets of colorectal cancer.ConclusionMetaFunc is a one-stop shop microbiome analysis pipeline that can identify taxonomies and their respective functional contributions in a microbiome sample through GO annotations. It can also analyse host reads in a microbiome sample, providing information on host gene expression, and allowing for correlations between the microbiome and host genes. MetaFunc comes with a user-friendly R shiny application that allows for easier visualisation and exploration of its results. MetaFunc is freely available through https://gitlab.com/schmeierlab/workflows/metafunc.git.

The identification of functional processes taking place in microbiome communities augment traditional microbiome taxonomic studies, giving a more complete picture of interactions taking place within the community. While there are applications that perform functional annotation on metagenomes or metatranscriptomes, very few of these are able to link taxonomic identity to function or are limited by their input types or databases used. Here we present MetaFunc, a workflow which takes RNA sequences as input reads, and from these 1) identifies species present in the microbiome sample and 2) provides gene ontology (GO) annotations associated with the species identified. In addition, MetaFunc allows for host gene analysis, mapping the reads to a host genome, and separating these reads, prior to microbiome analyses. Differential abundance analysis for microbe taxonomies, and differential gene expression analysis and gene set enrichment analysis may then be carried out through the pipeline. A final correlation analysis between microbial species and host genes can also be performed. Finally, MetaFunc builds an R shiny application that allows users to view and interact with the microbiome results. In this paper, we showed how MetaFunc can be applied to metatranscriptomic datasets of colorectal cancer.

Acute appendicitis is a common acute surgical emergency; however, the pathogenesis of adult appendicitis remains poorly understood. The microbiome is increasingly thought to play a key role in inflammatory disease of the bowel and similarly, may play a role in appendicitis. This study aimed to characterise the microbiome of adult acute appendicitis in a prospective cohort. We recruited 60 adults with acute appendicitis and 20 healthy controls. Rectal swabs were taken from each patient. After DNA extraction, 16S rRNA amplicon sequencing was carried out for analysis of diversity and taxonomic abundance. Phylogenetic sequencing of the samples indicated that there is a difference between the microbial composition of those with acute appendicitis and healthy controls, with a statistically significant decrease in alpha diversity in rectal swabs of appendicitis patients compared to healthy controls. At the genus level, we saw an increased abundance of potential pathogens, for example, Parvimonas and Acinetobacter, and a decrease in commensal taxa such as Faecalibacterium, Blautia and Lachnospiraceae in appendicitis patients compared to healthy controls. There was a reduction in diversity and loss of commensals in the microbiome of those with acute appendicitis, which may play a role in the cascade leading to acute appendicitis or the result of this.