QMD: A new method to quantify microbial absolute abundance differences between groups

Long-term ammonium nitrate addition strengthens soil microbial cross-trophic interactions in a Tibetan alpine steppe

Global nitrogen (N) enrichment is modifying microbial interactions, which can be represented by network complexity. While a number of studies have explored how N addition influences the microbial intra-trophic network, its effects on the inter-trophic network have rarely been investigated. Here, we examined the effects of 8 years of multilevel N additions (i.e., 0, 1, 2, 4, 8, 16, 24 and 32 g N m-2 year-1) on inter-trophic interactions of soil microbial communities (i.e., protist-fungi, protist-prokaryote and fungi-prokaryote) in a Tibetan alpine steppe. Generally, there was a first increasing and then saturated trend of the complexity of inter-trophic networks along the N-addition gradient, which contrasts with the simplified or minimal response of intra-trophic network complexity reported previously. The intensified cross-trophic interactions were mainly explained by increased plant and litter biomass, which indicates that the N-induced increases in carbon supplies may have alleviated microbial energy limitations and thus resulted in more active metabolic processes, consequently stimulating various biotic interactions (e.g., predation, competition, and commensalism). Further, the enhanced inter-trophic network relationships were found to be associated with increased soil carbon and N mineralization processes. Overall, these findings highlight the importance of microbial cross-trophic interactions and indicate that they should be considered in predictions of ecosystem functioning under global N enrichment.

RFW captures species-level metagenomic functions by integrating genome annotation information

Functional profiling of whole-metagenome shotgun sequencing (WMS) enables our understanding of microbe-host interactions. We demonstrate microbial functional information loss by current annotation methods at both the taxon and community levels, particularly at lower read depths. To address information loss, we develop a framework, RFW (reference-based functional profile inference on WMS), that utilizes information from genome functional annotations and taxonomic profiles to infer microbial function abundances from WMS. Furthermore, we provide an algorithm for absolute abundance change quantification between groups as part of the RFW framework. By applying RFW to several datasets related to autism spectrum disorder and colorectal cancer, we show that RFW augments downstream analyses, such as differential microbial function identification and association analysis between microbial function and host phenotype. RFW is open source and freely available at https://github.com/Xingyinliu-Lab/RFW.

Akkermansia muciniphila supplementation improves glucose tolerance in intestinal Ffar4 knockout mice during the daily light to dark transition

IMPORTANCE

Alterations in the intestinal environment are associated with various diseases, and FFAR4 is abundantly enriched in the intestine, where it has been shown to have the ability to regulate intestinal hormone secretion and intestinal microbiota; here, we confirmed previous reports. Meanwhile, we found that intestinal FFAR4 regulates glucagon-like peptide 1 secretion by decreasing Akkermansia muciniphila abundance and show that such change is associated with the level of glucose utilization at ZT12 in mice. Intestinal FFAR4 deficiency leads to severely impaired glucose tolerance at the ZT12 moment in mice, and Akkermansia muciniphila supplementation ameliorates the abnormal glucose utilization at the ZT12 moment caused by FFAR4 deficiency, which is very similar to the dawn phenomenon in diabetic patients. Collectively, our data suggest that intestinal Ffar4 deteriorates glucose tolerance at the daily light to dark transition by affecting Akkermansia muciniphila.

Food and drug design for gut microbiota-directed regulation: Current experimental landscape and future innovation

Most diets and medications enhance host health via microbiota-dependent ways, but it is in the present situation of untargeted regulation. Non-targeted regulation may lead to the ineffectiveness of dietary supplements or drug treatment. Microbiota-directed food, aiming to improve diseases by targeting specific microbes without affecting other bacteria, have been proposed to deal with this problem. However, there is currently no universally applicable method to explore such foods or drugs. In this review, thirty studies on recent efforts in microbiota directed diets and medications are summarized from various databases. The methods used to find new foods and medications are primarily divided into four groups depending on the experimental models: in vivo and in vitro, as well as predictions based on bioinformatics. We also discuss their implementation, interpretation, and respective limitations, and describe the present situation. We further put forward a framework for microbiota-directed foods and medicine according to above methods and other microbiome manipulation, which will spur precision medicine.