Optimizing sequencing protocols for leaderboard metagenomics by combining long and short reads.

As metagenomic studies move to increasing numbers of samples, communities like the human gut may benefit more from the assembly of abundant microbes in many samples, rather than the exhaustive assembly of fewer samples. We term this approach leaderboard metagenome sequencing. To explore protocol optimization for leaderboard metagenomics in real samples, we introduce a benchmark of library prep and sequencing using internal references generated by synthetic long-read technology, allowing us to evaluate high-throughput library preparation methods against gold-standard reference genomes derived from the samples themselves. We introduce a low-cost protocol for high-throughput library preparation and sequencing

Latitudinal differences in early growth of largehead hairtail (Trichiurus japonicus) in relation to environmental variables

Largehead hairtail (Trichiurus japonicus) in the China Seas shows an increasing catch trend, despite continued overexploitation, which could be attributed to improved recruitment as a result of strengthened early growth. To understand the early growth variability of largehead hairtail, we examined the linkages between early growth, as revealed by otolith microstructure, and the associated environmental variables over both spatial and temporal scales. Young‐of‐the‐Year largehead hairtail were collected from three regions in the Bohai, Yellow and East China Seas between 29° and 39° N. Daily increment widths of sagittal otoliths were measured and used as a proxy for somatic growth. We found two spawning cohorts, Spring‐ and Summer‐spawned cohorts, that showed latitudinal differences in both mean growth and growth pattern. The transition time from larval to juvenile stage was identified at around 40 days. Daily increment widths of two cohorts showed similar growth pattern in the first 40 days, while location had a marked effect on daily growth over 41–110 days. This suggests physiologically constrained growth pattern in larval stage, but more plastic growth subject to habitat‐specific influences in juvenile stage. The gradient forest analysis identified sea bottom temperature, vertical temperature gradient, and sea surface salinity, as the most important variables in determining early growth. Latitudinal differences in early growth pattern and their response to environmental variables suggest adaptive plasticity of early growth, which has notable implication for the management and sustainable utilization of this important but heavily exploited resource in the China Seas.acceptedVersio

Antibiotic-induced microbiome depletion alters metabolic homeostasis by affecting gut signaling and colonic metabolism

Antibiotic-induced microbiome depletion is one of the most common approaches to modulate the gut microbiome. Here the authors demonstrate that it affects gut homeostasis and glucose metabolism by decreasing luminal short chain fatty acids and leading to a shift of energy utilization by colonocytes

Identification of new high affinity targets for Roquin based on structural conservation

Post-transcriptional gene regulation controls the amount of protein produced from a specific mRNA by altering both its decay and translation rates. Such regulation is primarily achieved by the interaction of trans-acting factors with cis-regulatory elements in the untranslated regions (UTRs) of mRNAs. These interactions are guided either by sequence- or structure-based recognition. Similar to sequence conservation, the evolutionary conservation of a UTR's structure thus reflects its functional importance. We used such structural conservation to identify previously unknown cis-regulatory elements. Using the RNA folding program Dynalign, we scanned all UTRs of humans and mice for conserved structures. Characterizing a subset of putative conserved structures revealed a binding site of the RNA-binding protein Roquin. Detailed functional characterization in vivo enabled us to redefine the binding preferences of Roquin and identify new target genes. Many of these new targets are unrelated to the established role of Roquin in inflammation and immune responses and thus highlight additional, unstudied cellular functions of this important repressor. Moreover, the expression of several Roquin targets is highly cell-type-specific. In consequence, these targets are difficult to detect using methods dependent on mRNA abundance, yet easily detectable with our unbiased strategy

A gut microbiome signature for cirrhosis due to nonalcoholic fatty liver disease.

The presence of cirrhosis in nonalcoholic-fatty-liver-disease (NAFLD) is the most important predictor of liver-related mortality. Limited data exist concerning the diagnostic accuracy of gut-microbiome-derived signatures for detecting NAFLD-cirrhosis. Here we report 16S gut-microbiome compositions of 203 uniquely well-characterized participants from a prospective twin and family cohort, including 98 probands encompassing the entire spectrum of NAFLD and 105 of their first-degree relatives, assessed by advanced magnetic-resonance-imaging. We show strong familial correlation of gut-microbiome profiles, driven by shared housing. We report a panel of 30 features, including 27 bacterial features with discriminatory ability to detect NAFLD-cirrhosis using a Random Forest classifier model. In a derivation cohort of probands, the model has a robust diagnostic accuracy (AUROC of 0.92) for detecting NAFLD-cirrhosis, confirmed in a validation cohort of relatives of proband with NAFLD-cirrhosis (AUROC of 0.87). This study provides evidence for a fecal-microbiome-derived signature to detect NAFLD-cirrhosis

A gut microbiome signature for cirrhosis due to nonalcoholic fatty liver disease

Development of cirrhosis in individuals with non-alcoholic fatty liver disease can predict mortality. Here the authors used a unique twin and family cohort to identify a gut microbiome-derived 16sRNA signature that can detect cirrhosis in individuals with non-alcoholic fatty liver disease

Best practices for analysing microbiomes

Complex microbial communities shape the dynamics of various environments, ranging from the mammalian gastrointestinal tract to the soil. Advances in DNA sequencing technologies and data analysis have provided drastic improvements in microbiome analyses, for example, in taxonomic resolution, false discovery rate control and other properties, over earlier methods. In this Review, we discuss the best practices for performing a microbiome study, including experimental design, choice of molecular analysis technology, methods for data analysis and the integration of multiple omics data sets. We focus on recent findings that suggest that operational taxonomic unit-based analyses should be replaced with new methods that are based on exact sequence variants, methods for integrating metagenomic and metabolomic data, and issues surrounding compositional data analysis, where advances have been particularly rapid. We note that although some of these approaches are new, it is important to keep sight of the classic issues that arise during experimental design and relate to research reproducibility. We describe how keeping these issues in mind allows researchers to obtain more insight from their microbiome data sets

Best Practices for Analysing Microbiomes

Complex microbial communities shape the dynamics of various environments, ranging from the mammalian gastrointestinal tract to the soil. Advances in DNA sequencing technologies and data analysis have provided drastic improvements in microbiome analyses, for example, in taxonomic resolution, false discovery rate control and other properties, over earlier methods. In this Review, we discuss the best practices for performing a microbiome study, including experimental design, choice of molecular analysis technology, methods for data analysis and the integration of multiple omics data sets. We focus on recent findings that suggest that operational taxonomic unit-based analyses should be replaced with new methods that are based on exact sequence variants, methods for integrating metagenomic and metabolomic data, and issues surrounding compositional data analysis, where advances have been particularly rapid. We note that although some of these approaches are new, it is important to keep sight of the classic issues that arise during experimental design and relate to research reproducibility. We describe how keeping these issues in mind allows researchers to obtain more insight from their microbiome data sets