The human gut microbiota (HGM) have an impact on host health and disease. Amino acids are building blocks of proteins and peptides, also serving as precursors of many essential metabolites including nucleotides, cofactors, etc. Many HGM community members are unable to synthesize some amino acids (auxotrophs), while other members possess complete biosynthetic pathways for these nutrients (prototrophs). Metabolite exchange between auxotrophs and prototrophs affects microbial community structure. Previous studies of amino acid biosynthetic phenotypes were limited to model species or narrow taxonomic groups of bacteria. We analyzed over 2800 genomes representing 823 cultured HGM species with the aim to reconstruct biosynthetic pathways for proteinogenic amino acids. The genome context analysis of incomplete pathway variants allowed us to identify new potential enzyme variants in amino acid biosynthetic pathways. We further classified the studied organisms with respect to their pathway variants and inferred their prototrophic vs. auxotrophic phenotypes. A cross-species comparison was applied to assess the extent of conservation of the assigned phenotypes at distinct taxonomic levels. The obtained reference collection of binary metabolic phenotypes was used for predictive metabolic profiling of HGM samples from several large metagenomic datasets. The established approach for metabolic phenotype profiling will be useful for prediction of overall metabolic properties, interactions, and responses of HGM microbiomes as a function of dietary variations, dysbiosis and other perturbations.

Super-enhancers (SEs) are regions of the genome that play a crucial regulatory role in gene expression by promoting large-scale transcriptional responses in various cell types and tissues. Recent research suggests that alterations in super-enhancer activity can contribute to the development and progression of various disorders. The aim of this research is to explore the multifaceted roles of super-enhancers in gene regulation and their significant implications for understanding and treating complex diseases. Here, we study and summarise the classification of super-enhancer constituents, their possible modes of interaction, and cross-regulation, including super-enhancer RNAs (seRNAs). We try to investigate the opportunity of SE dynamics prediction based on the hierarchy of enhancer single elements (enhancers) and their aggregated action. To further our understanding, we conducted an in silico experiment to compare and differentiate between super-enhancers and locus-control regions (LCRs), shedding light on the enigmatic relationship between LCRs and SEs within the human genome. Particular attention is paid to the classification of specific mechanisms and their diversity, exemplified by various oncological, cardiovascular, and immunological diseases, as well as an overview of several anti-SE therapies. Overall, the work presents a comprehensive analysis of super-enhancers across different diseases, aiming to provide insights into their regulatory roles and may act as a rationale for future clinical interventions targeting these regulatory elements.