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Exercise reduces inflammation, fatigue, and aids overall health. Additionally, physical fitness has been associated with desirable changes in the community composition of the athlete gut microbiome, with health-associated taxa being shown to be increased in active individuals. Here, using a combination of in silico and in vitro methods, we investigate the antimicrobial activity of the athlete gut microbiome. In vitro approaches resulted in the generation of 284 gut isolates with inhibitory activity against Clostridioides difficile and/or Fusobacterium nucleatum, and the most potent isolates were further characterized, and potential bacteriocins were predicted using both MALDI-TOF MS and whole-genome sequencing. Additionally, metagenomic reads from the faecal samples were used to recover 770 Metagenome Assembled Genomes (MAGs), of which 148 were assigned to be high-quality MAGs and screened for the presence of putative bacteriocin gene clusters using BAGEL4 software, with 339 gene clusters of interest being identified. Class I was the most abundant bacteriocin class predicted, accounting for 91.3% of predictions, Class III had a predicted abundance of 7.5%, and Class II was represented by just 1% of all predictions.

The cystic fibrosis (CF) lung harbours a diverse microbiome and reduced diversity in the CF lung has been associated with advancing age, increased inflammation and poorer lung function. Data suggest that the window for intervention is early in CF, yet there is a paucity of studies on the lung microbiome in children with CF. The objective of this study was to thoroughly characterise the lower airway microbiome in pre-school children with CF. Bronchoalveolar lavage (BAL) samples were collected annually from children attending the three clinical centres. Clinical and demographic data were collated on all subjects alongside BAL inflammatory markers. 16S rRNA gene sequencing was performed on the Illumina MiSeq platform. Bioinformatics and data analysis were performed using Qiime and R project software. Data on 292 sequenced BALs from 101 children with CF and 51 without CF show the CF lung microbiome, while broadly similar to that in non-CF children, is distinct. Alpha diversity between the two cohorts was indistinguishable at this early age. The CF diagnosis explained only 1.1% of the variation between the cohort microbiomes. However, several key genera were significantly differentially abundant between the groups. While the non-CF lung microbiome diversity increased with age, diversity reduced in CF with age. Pseudomonas and Staphylococcus were more abundant with age, while genera such as Streptococcus, Porphyromonas and Veillonella were less abundant with age. There was a negative correlation between alpha diversity and interleukin-8 and neutrophil elastase in the CF population. Neither current flucloxacillin or azithromycin prophylaxis, nor previous oral or IV antibiotic exposure, was correlated with microbiome diversity. Consecutive annual BAL samples over 5 years from a subgroup of children demonstrated diverse patterns of development in the first years of life.

The skin microbiota is thought to play a key role in host protection from infection. Nisin J is a novel nisin variant produced by Staphylococcus capitis APC 2923, a strain isolated from the toe web space area in a screening study performed on the human skin microbiota. Whole-genome sequencing and mass spectrometry of the purified peptide confirmed that S. capitis APC 2923 produces a 3,458-Da bacteriocin, designated nisin J, which exhibited antimicrobial activity against a range of Gram-positive pathogens, including methicillin-resistant Staphylococcus aureus (MRSA) and Cutibacterium acnes The gene order in the nisin J gene cluster (nsjFEGBTCJP) differs from that of other nisin variants in that it is lacking the nisin regulatory genes, nisRK, as well as the nisin immunity gene nisI Nisin J has 9 amino acid changes compared to prototypical nisin A, with 8 amino acid substitutions, 6 of which are not present in other nisin variants (Ile4Lys, Met17Gln, Gly18Thr, Asn20Phe, Met21Ala, Ile30Gly, Val33His, and Lys34Thr), and an extra amino acid close to the C terminus, rendering nisin J the only nisin variant to contain 35 amino acids. This is the first report of a nisin variant produced by a Staphylococcus species and the first nisin producer isolated from human skin.IMPORTANCE This study describes the characterization of nisin J, the first example of a natural nisin variant, produced by a human skin isolate of staphylococcal origin. Nisin J displays inhibitory activity against a wide range of bacterial targets, including MRSA. This work demonstrates the potential of human commensals as a source for novel antimicrobials that could form part of the solution to antibiotic resistance across a broad range of bacterial pathogens.

Shotgun metagenomic sequencing is a valuable tool for the taxonomic and functional profiling of microbial communities. However, this approach is challenging in samples, such as milk, where a low microbial abundance, combined with high levels of host DNA, result in inefficient and uneconomical sequencing. Here we evaluate approaches to deplete host DNA or enrich microbial DNA prior to sequencing using three commercially available kits. We compared the percentage of microbial reads obtained from each kit after shotgun metagenomic sequencing. Using bovine and human milk samples, we determined that host depletion with the MolYsis complete5 kit significantly improved microbial sequencing depth compared to other approaches tested. Importantly, no biases were introduced. Additionally, the increased microbial sequencing depth allowed for further characterization of the microbiome through the generation of metagenome-assembled genomes (MAGs). Furthermore, with the use of a mock community, we compared three common classifiers and determined that Kraken2 was the optimal classifier for these samples. This evaluation shows that microbiome analysis can be performed on both bovine and human milk samples at a much greater resolution without the need for more expensive deep-sequencing approaches.

Fermented foods have been the focus of ever greater interest as a consequence of purported health benefits. Indeed, it has been suggested that consumption of these foods helps to address the negative consequences of "industrialization" of the human gut microbiota in Western society. However, as the mechanisms via which the microbes in fermented foods improve health are not understood, it is necessary to develop an understanding of the composition and functionality of the fermented-food microbiota to better harness desirable traits. Here, we considerably expand the understanding of fermented-food microbiomes by employing shotgun metagenomic sequencing to provide a comprehensive insight into the microbial composition, diversity, and functional potential (including antimicrobial resistance and carbohydrate-degrading and health-associated gene content) of a diverse range of 58 fermented foods from artisanal producers from a number of countries. Food type, i.e., dairy-, sugar-, or brine-type fermented foods, was the primary driver of microbial composition, with dairy foods found to have the lowest microbial diversity. From the combined data set, 127 high-quality metagenome-assembled genomes (MAGs), including 10 MAGs representing putatively novel species of Acetobacter, Acidisphaera, Gluconobacter, Companilactobacillus, Leuconostoc, and Rouxiella, were generated. Potential health promoting attributes were more common in fermented foods than nonfermented equivalents, with water kefirs, sauerkrauts, and kvasses containing the greatest numbers of potentially health-associated gene clusters. Ultimately, this study provides the most comprehensive insight into the microbiomes of fermented foods to date and yields novel information regarding their relative health-promoting potential.IMPORTANCE Fermented foods are regaining popularity worldwide due in part to a greater appreciation of the health benefits of these foods and the associated microorganisms. Here, we use state-of-the