In microbial ecosystems, metabolic interactions are key determinants of species’ relative abundance and activity. Given the immense number of possible interactions in microbial communities, their expe...

The human gut microbiota is frequently dominated by the Bacteroidota phylum, with Bacteroidaceae and Prevotellaceae families prevailing in modern and traditional lifestyles, respectively. While these ...

An in-depth microbiological and metagenomic analysis of Colombian farm and fermentation facilities resulted in the design of a defined microbial community that can reproduce the flavour of fine chocol...

Uniting life’s seen and unseen realms guides a conceptual advance in research

We are seeking a motivated and enthusiastic PhD student with a focus on computational biology, bioinformatics, and microbiome analysis to join a fully funded project on the role of the gut microbiome in cancer and cancer immunotherapy.

This study shows that regional mismatches between transplanted microbiota and the host gut environment alter the metabolic and immune states of host tissues as well as the composition of regional micr...

Precision microbiome programming for therapeutic applications is limited by challenges in achieving reproducible colonic colonization. Previously, we created an exclusive niche that we used to engraft...

Non-antibiotic drugs from a wide range of therapeutic classes can alter the ability of gut commensals to resist invasion by enteropathogens, a previously underappreciated side effect of such drugs.

Recent developments in data generation have opened up unprecedented insights into living systems. It has been recognized that integrating and characterizing temporal variation simultaneously across multiple scales, from specific molecular interactions to entire ecosystems, is crucial for uncovering biological mechanisms and understanding the emergence of complex phenotypes. With the increasing number of studies incorporating multi-omics data sampled over time, it has become clear that integrated approaches are pivotal for these efforts. However, standard data analytical practices in longitudinal multi-omics are still shaping up and many of the available methods have not yet been widely evaluated and adopted. Thus, we performed a systematic literature review on data science methods for longitudinal multi-omics, with a particular focus on microbiome research. ### Competing Interest Statement The authors have declared no competing interest. European Union’s Horizon 2020 research and innovation programme, 952914

Pesticide exposure induces significant alterations in gut bacterial metabolism. Here, the authors perform a multi-omics mapping of pesticide-gut microbiota-metabolite interactions, identifying pestici...

About 15,000 pairwise interactions within S. epidermidis from 18 people in 6 families reveal the antagonism and molecular trade-offs that shape the skin microbiota.

Clostridioides difficile infections often occur after antibiotic use, but they have also been linked to proton-pump inhibitor (PPI) therapy. The underlying mechanism – whether infection risk is due...

This Protocol outlines the steps for high-throughput single microorganism isolation and microfluidic droplet-based encapsulation and barcoding to obtain single cell transcriptomes from both cultured…

In this Review, Ferretti et al. discuss advances in our understanding of interactions between the human genome and the microbiome, including the effects of the microbiome on host gene regulation.

Nature Communications - Here, the authors show that Bilophila wadsworthia uses bacterial microcompartments and anaerobic respiration of host-derived compounds to thrive in the inflamed gut,...

The dynamics of antimicrobial resistance gene transfer remain unclear. Here, by integrating bacterial genome and metagenome data with machine learning the authors show that genetic incompatibility is a main limiting factor, while co-occurrence of bacteria in the human microbiome and wastewater contributes to gene transfer.