Metagenomes Binning Using Proximity-Ligation Data

Guidelines for microbiome studies in renal physiology

Gut microbiome research has increased dramatically in the last decade, including in renal health and disease. The field is moving from experiments showing mere association to causation using both forward and reverse microbiome approaches, leveraging tools such as germ-free animals, treatment with antibiotics, and fecal microbiota transplantations. However, we are still seeing a gap between discovery and translation that needs to be addressed, so that patients can benefit from microbiome-based therapies. In this guideline paper, we discuss the key considerations that affect the gut microbiome of animals and clinical studies assessing renal function, many of which are often overlooked, resulting in false-positive results. For animal studies, these include suppliers, acclimatization, baseline microbiota and its normalization, littermates and cohort/cage effects, diet, sex differences, age, circadian differences, antibiotics and sweeteners, and models used. Clinical studies have some unique considerations, which include sampling, gut transit time, dietary records, medication, and renal phenotypes. We provide best-practice guidance on sampling, storage, DNA extraction, and methods for microbial DNA sequencing (both 16S rRNA and shotgun metagenome). Finally, we discuss follow-up analyses, including tools available, metrics, and their interpretation, and the key challenges ahead in the microbiome field. By standardizing study designs, methods, and reporting, we will accelerate the findings from discovery to translation and result in new microbiome-based therapies that may improve renal health.

RNA-DNA interactomes of three prokaryotes uncovered by proximity ligation

Proximity ligation approaches, which are widely used to study the spatial organization of the genome, also make it possible to reveal patterns of RNA-DNA interactions. Here, we use RedC, an RNA-DNA proximity ligation approach, to assess the distribution of major RNA types along the genomes of E. coli, B. subtilis, and thermophilic archaeon T. adornatum. We find that (i) messenger RNAs preferentially interact with their cognate genes and the genes located downstream in the same operon, which is consistent with polycistronic transcription; (ii) ribosomal RNAs preferentially interact with active protein-coding genes in both bacteria and archaea, indicating co-transcriptional translation; and (iii) 6S noncoding RNA, a negative regulator of bacterial transcription, is depleted from active genes in E. coli and B. subtilis. We conclude that the RedC data provide a rich resource for studying both transcription dynamics and the function of noncoding RNAs in microbial organisms.