Identifying active prophages is critical for studying coevolution of phage and bacteria, investigating phage physiology and biochemistry, and engineering designer phages for diverse applications. We present Prophage Hunter, a tool aimed at hunting for active prophages from whole genome assembly of bacteria. Combining sequence similarity-based matching and genetic features-based machine learning classification, we developed a novel scoring system that exhibits higher accuracy than current tools in predicting active prophages on the validation datasets. The option of skipping similarity matching is also available so that there's higher chance for novel phages to be discovered. Prophage Hunter provides a one-stop web service to extract prophage genomes from bacterial genomes, evaluate the activity of the prophages, identify phylogenetically related phages, and annotate the function of phage proteins. Prophage Hunter is freely available at https://pro-hunter.bgi.com/.

Objective The gut microbiota plays a key role in modulating host immune response. We conducted a prospective, observational study to examine gut microbiota composition in association with immune responses and adverse events in adults who have received the inactivated vaccine (CoronaVac; Sinovac) or the mRNA vaccine (BNT162b2; BioNTech; Comirnaty). Design We performed shotgun metagenomic sequencing in stool samples of 138 COVID-19 vaccinees (37 CoronaVac and 101 BNT162b2 vaccinees) collected at baseline and 1 month after second dose of vaccination. Immune markers were measured by SARS-CoV-2 surrogate virus neutralisation test and spike receptor-binding domain IgG ELISA. Results We found a significantly lower immune response in recipients of CoronaVac than BNT162b2 vaccines (p2 and p3 and p<0.05). Conclusion Our study has identified specific gut microbiota markers in association with improved immune response and reduced adverse events following COVID-19 vaccines. Microbiota-targeted interventions have the potential to complement effectiveness of COVID-19 vaccines.

Background: Gestational diabetes mellitus (GDM) is a metabolic disease that occurs in pregnant women and increases the risk for the development of diabetes. The relationship between GDM and meconium microbiota and metabolome remains incompletely understood. Methods: Four hundred eighteen mothers (147 women with GDM and 271 normal pregnant women) and their neonates from the GDM Mother and Child Study were included in this study. Meconium microbiota were profiled by 16S rRNA gene sequencing. Meconium and maternal serum metabolome were examined by UPLC-QE. Results: Microbial communities in meconium were significantly altered in neonates from the GDM mothers. A reduction in alpha diversity was observed in neonates of GDM mothers. At the phylum level, the abundance of Firmicutes and Proteobacteria changed significantly in neonates of GDM mothers. Metabolomic analysis of meconium showed that metabolic pathways including taurine and hypotaurine metabolism, pyrimidine metabolism, beta-alanine metabolism, and bile acid biosynthesis were altered in GDM subjects. Several changed metabolites varying by the similar trend across the maternal serum and neonatal meconium were observed. Conclusion: Altogether, these findings suggest that GDM could alter the serum metabolome and is associated with the neonatal meconium microbiota and metabolome, highlighting the importance of maternal factors on early-life metabolism.

Objective: The gut virome is a dense community of viruses inhabiting the gastrointestinal tract and an integral part of the microbiota. The virome coexists with the other components of the microbiota and with the host in a dynamic equilibrium, serving as a key contributor to the maintenance of intestinal homeostasis and functions. However, this equilibrium can be interrupted in certain pathological states, including inflammatory bowel disease, causing dysbiosis that may participate in disease pathogenesis. Nevertheless, whether virome dysbiosis is a causal or bystander event requires further clarification. Design: This review seeks to summarise the latest advancements in the study of the gut virome, highlighting its cross-talk with the mucosal microenvironment. It explores how cutting-edge technologies may build upon current knowledge to advance research in this field. An overview of virome transplantation in diseased gastrointestinal tracts is provided along with insights into the development of innovative virome-based therapeutics to improve clinical management. Results: Gut virome dysbiosis, primarily driven by the expansion of Caudovirales , has been shown to impact intestinal immunity and barrier functions, influencing overall intestinal homeostasis. Although emerging innovative technologies still need further implementation, they display the unprecedented potential to better characterise virome composition and delineate its role in intestinal diseases. Conclusions: The field of gut virome is progressively expanding, thanks to the advancements of sequencing technologies and bioinformatic pipelines. These have contributed to a better understanding of how virome dysbiosis is linked to intestinal disease pathogenesis and how the modulation of virome composition may help the clinical intervention to ameliorate gut disease management.

The relationship between dyslipidemia and type 2 diabetes mellitus (T2D) has been extensively reported, but the global lipid profiles, especially in the East Asia population, associated with the development of T2D remain to be characterized. Liquid chromatography coupled to tandem mass spectrometry was applied to detect the global lipidome in the fasting plasma of 293 Chinese individuals, including 114 T2D patients, 81 prediabetic subjects, and 98 individuals with normal glucose tolerance (NGT). Both qualitative and quantitative analyses revealed a gradual change in plasma lipid features with T2D patients exhibiting characteristics close to those of prediabetic individuals, whereas they differed significantly from individuals with NGT. We constructed and validated a random forest classifier with 28 lipidomic features that effectively discriminated T2D from NGT or prediabetes. Most of the selected features significantly correlated with diabetic clinical indices. Hydroxybutyrylcarnitine was positively correlated with fasting plasma glucose, 2-hour postprandial glucose, glycated hemoglobin, and insulin resistance index (HOMA-IR). Lysophosphatidylcholines such as lysophosphatidylcholine (18:0), lysophosphatidylcholine (18:1), and lysophosphatidylcholine (18:2) were all negatively correlated with HOMA-IR. The altered plasma lipidome in Chinese T2D and prediabetic subjects suggests that lipid features may play a role in the pathogenesis of T2D and that such features may provide a basis for evaluating risk and monitoring disease development.