The MGnify platform (https://www.ebi.ac.uk/metagenomics) facilitates the assembly, analysis and archiving of microbiome-derived nucleic acid sequences. The platform provides access to taxonomic assignments and functional annotations for nearly half a million analyses covering metabarcoding, metatranscriptomic, and metagenomic datasets, which are derived from a wide range of different environments. Over the past 3 years, MGnify has not only grown in terms of the number of datasets contained but also increased the breadth of analyses provided, such as the analysis of long-read sequences. The MGnify protein database now exceeds 2.4 billion non-redundant sequences predicted from metagenomic assemblies. This collection is now organised into a relational database making it possible to understand the genomic context of the protein through navigation back to the source assembly and sample metadata, marking a major improvement. To extend beyond the functional annotations already provided in MGnify, we have applied deep learning-based annotation methods. The technology underlying MGnify's Application Programming Interface (API) and website has been upgraded, and we have enabled the ability to perform downstream analysis of the MGnify data through the introduction of a coupled Jupyter Lab environment.

Understanding the development of functional attributes of host-associated microbial communities is essential for developing novel microbe-based solutions for sustainable animal production. We applied multi-omics to 388 broiler chicken caecal samples to characterise and model the functional dynamics of 822 bacterial strains. Although microbial community diversity metrics increased with chicken age as expected, the overall metabolic capacity and activity of the microbiota exhibited an unexpected decrease. This drop occurred due to the spread of non-culturable clades with small genomes and low metabolic capacities, including RF39, RF32, and UBA1242. The intensity of this decrease was associated with animal growth, whereby chickens with higher abundances of low-capacity bacteria exhibited higher body weights. This previously unreported link between metabolic capacity of microbes and animal body weight suggests a relevant role of non-culturable bacteria with reduced-genomes for host biology, and opens new avenues in the search for microbe-based solutions to improve sustainability of animal production.