The infant gut microbiome and cognitive development in malnutrition.

Malnutrition affects 195 million children under the age of five worldwide with long term effects that include impaired cognitive development. Brain development occurs rapidly over the first 36 months of life. Whilst seemingly independent, changes to the brain and gut microbiome are linked by metabolites, hormones, and neurotransmitters as part of the gut-brain axis. In the context of severe malnutrition, the composition of the gut microbiome and the repertoire of biochemicals exchanged via the gut-brain axis vary when compared to healthy individuals. These effects are primarily due to the recognized interacting determinants, macro- and micronutrient deficiencies, infection, infestations and toxins related to poor sanitation, and a dearth of psycho-social stimulation. The standard of care for the treatment of severe acute malnutrition is focused on nutritional repletion and weight restoration through the provision of macro- and micronutrients, the latter usually in excess of recommended dietary allowances (RDA). However, existing formulations and supplements have not been designed to specifically address key recovery requirements for brain and gut microbiome development. Animal model studies indicate that treatments targeting the gut microbiome could improve brain development. Despite this, research on humans targeting the gut microbiome with the aim of restoring brain functionality are scarce. We conclude that there is a need for assessment of cognition and the use of various tools that permit visualization of the brain anatomy and function (e.g., Magnetic resonance imaging (MRI), functional near-infrared spectroscopy (fNIRS), electroencephalogram (EEG)) to understand how interventions targeting the gut microbiome impact brain development.

Horizontal gene transfer after faecal microbiota transplantation in adolescents with obesity.

BACKGROUND: Horizontal gene transfer (HGT) describes the transmission of DNA outside of direct ancestral lineages. The process is best characterised within the bacterial kingdom and can enable the acquisition of genetic traits that support bacterial adaptation to novel niches. The adaptation of bacteria to novel niches has particular relevance for faecal microbiota transplantation (FMT), a therapeutic procedure which aims to resolve gut-related health conditions of individuals, through transplanted gut microbiota from healthy donors. RESULTS: Three hundred eighty-one stool metagenomic samples from a placebo-controlled FMT trial for obese adolescents (the Gut Bugs Trial) were analysed for HGT, using two complementary methodologies. First, all putative HGT events, including historical HGT signatures, were quantified using the bioinformatics application WAAFLE. Second, metagenomic assembly and gene clustering were used to assess and quantify donor-specific genes transferred to recipients following the intervention. Both methodologies found no difference between the level of putative HGT events in the gut microbiomes of FMT and placebo recipients, post-intervention. HGT events facilitated by engrafted donor species in the FMT recipient gut at 6 weeks post-intervention were identified and characterised. Bacterial strains contributing to this subset of HGT events predominantly belonged to the phylum Bacteroidetes. Engraftment-dependent horizontally transferred genes were retained within recipient microbiomes at 12 and 26 weeks post-intervention. CONCLUSION: Our study suggests that novel microorganisms introduced into the recipient gut following FMT have no impact on the basal rate of HGT within the human gut microbiome. Analyses of further FMT studies are required to assess the generalisability of this conclusion across different FMT study designs and for the treatment of different gut-related conditions. Video Abstract.

Addressing antibiotic resistance: computational answers to a biological problem?

The increasing prevalence of infections caused by antibiotic-resistant bacteria is a global healthcare crisis. Understanding the spread of resistance is predicated on the surveillance of antibiotic resistance genes within an environment. Bioinformatics and artificial intelligence (AI) methods applied to metagenomic sequencing data offer the capacity to detect known and infer yet-unknown resistance mechanisms, and predict future outbreaks of antibiotic-resistant infections. Machine learning methods, in particular, could revive the waning antibiotic discovery pipeline by helping to predict the molecular structure and function of antibiotic resistance compounds, and optimising their interactions with target proteins. Consequently, AI has the capacity to play a central role in guiding antibiotic stewardship and future clinical decision-making around antibiotic resistance.

Cross-kingdom transcriptomic trends in the evolution of hybrid gene expression.

Hybridization is a route to speciation that occurs widely across the eukaryote tree of life. The success of allopolyploids (hybrid species with increased ploidy) and homoploid hybrids (with unchanged ploidy) is well documented. However, their formation and establishment is not straightforward, with a suite of near-instantaneous and longer term biological repercussions faced by the new species. Central to these challenges is the rewiring of gene regulatory networks following the merger of distinct genomes inherited from both parental species. Research on the evolution of hybrid gene expression has largely involved studies on a single hybrid species or a few gene families. Here, we present the first standardized transcriptome-wide study exploring the fates of genes following hybridization across three kingdoms: animals, plants and fungi. Within each kingdom, we pair an allopolyploid system with a closely related homoploid hybrid to decouple the influence of increased ploidy from genome merger. Genome merger, not changes in ploidy, has the greatest effect on posthybridization expression patterns across all study systems. Strikingly, we find that differentially expressed genes in parent species preferentially switch to more similar expression in hybrids across all kingdoms, likely as a consequence of regulatory trans-acting cross-talk within the hybrid nucleus. We also highlight the prevalence of gene loss or silencing among extremely differentially expressed genes in hybrid species across all kingdoms. These shared patterns suggest that the evolutionary process of hybridization leads to common high-level expression outcomes, regardless of the particular species or kingdom.