BackgroundThe gut microbiota plays important roles in modulating host metabolism. Previous studies have demonstrated differences in the gut microbiome of T2D and prediabetic individuals compared to healthy individuals, with distinct disease-related microbial profiles being reported in groups of different age and ethnicity. However, confounding factors such as anti-diabetic medication hamper identification of the gut microbial changes in disease development.MethodWe used a combination of in-depth metagenomics and metaproteomics analyses of faecal samples from treatment-naïve type 2 diabetic (TN-T2D, n = 77), pre-diabetic (Pre-DM, n = 80), and normal glucose tolerant (NGT, n = 97) individuals to investigate compositional and functional changes of the gut microbiota and the faecal content of microbial and host proteins in Pre-DM and treatment-naïve T2D individuals to elucidate possible host-microbial interplays characterizing different disease stages.FindingsWe observed distinct differences characterizing the gut microbiota of these three groups and validated several key features in an independent TN-T2D cohort. We also demonstrated that the content of several human antimicrobial peptides and pancreatic enzymes differed in faecal samples between three groups.InterpretationOur findings suggest a complex, disease stage-dependent interplay between the gut microbiota and the host and point to the value of metaproteomics to gain further insight into interplays between the gut microbiota and the host.FundThe study was supported by the National Natural Science Foundation of China (No. 31601073), the National Key Research and Development Program of China (No. 2017YFC0909703) and the Shenzhen Municipal Government of China (No. JCYJ20170817145809215). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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The oral cavity of each person is home to hundreds of bacterial species. While taxa for oral diseases have been studied using culture-based characterization as well as amplicon sequencing, metagenomic and genomic information remains scarce compared to the fecal microbiome. Here, using metagenomic shotgun data for 3346 oral metagenomic samples together with 808 published samples, we obtain 56,213 metagenome-assembled genomes (MAGs), and more than 64% of the 3589 species-level genome bins (SGBs) contain no publicly available genomes. The resulting genome collection is representative of samples around the world and contains many genomes from candidate phyla radiation (CPR) that lack monoculture. Also, it enables the discovery of new taxa such as a genus Candidatus Bgiplasma within the family Acholeplasmataceae. Large-scale metagenomic data from massive samples also allow the assembly of strains from important oral taxa such as Porphyromonas and Neisseria. The oral microbes encode genes that could potentially metabolize drugs. Apart from these findings, a strongly male-enriched Campylobacter species was identified. Oral samples would be more user-friendly collected than fecal samples and have the potential for disease diagnosis. Thus, these data lay down a genomic framework for future inquiries of the human oral microbiome.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a global pandemic of Coronavirus disease 2019 (COVID-19). However, the microbial composition of the respiratory tract and other infected tissues as well as their possible pathogenic contributions to varying degrees of disease severity in COVID-19 patients remain unclear. Between 27 January and 26 February 2020, serial clinical specimens (sputum, nasal and throat swab, anal swab and feces) were collected from a cohort of hospitalized COVID-19 patients, including 8 mildly and 15 severely ill patients in Guangdong province, China. Total RNA was extracted and ultra-deep metatranscriptomic sequencing was performed in combination with laboratory diagnostic assays. We identified distinct signatures of microbial dysbiosis among severely ill COVID-19 patients on broad spectrum antimicrobial therapy. Co-detection of other human respiratory viruses (including human alphaherpesvirus 1, rhinovirus B, and human orthopneumovirus) was demonstrated in 30.8% (4/13) of the severely ill patients, but not in any of the mildly affected patients. Notably, the predominant respiratory microbial taxa of severely ill patients were Burkholderia cepacia complex (BCC), Staphylococcus epidermidis, or Mycoplasma spp. (including M. hominis and M. orale). The presence of the former two bacterial taxa was also confirmed by clinical cultures of respiratory specimens (expectorated sputum or nasal secretions) in 23.1% (3/13) of the severe cases. Finally, a time-dependent, secondary infection of B. cenocepacia with expressions of multiple virulence genes was demonstrated in one severely ill patient, which might accelerate his disease deterioration and death occurring one month after ICU admission. Our findings point to SARS-CoV-2-related microbial dysbiosis and various antibiotic-resistant respiratory microbes/pathogens in hospitalized COVID-19 patients in relation to disease severity. Detection and tracking strategies are needed to prevent the spread of antimicrobial resistance, improve the treatment regimen and clinical outcomes of hospitalized, severely ill COVID-19 patients.

Background Shotgun metagenomic sequencing has improved our understanding of the human gut microbiota. Various DNA extraction methods have been compared to find protocols that robustly and most accurately reflect the original microbial community structures. However, these recommendations can be further refined by considering the time and cost demands in dealing with samples from very large human cohorts. Additionally, fungal DNA extraction performance has so far been little investigated. Results We compared 6 DNA extraction protocols, MagPure Fast Stool DNA KF Kit B, Macherey Nagel™ NucleoSpin™®Soil kit, Zymo Research Quick-DNA™ Fecal/Soil Microbe kit, MOBIO DNeasy PowerSoil kit, the manual non-commercial protocol MetaHIT, and the recently published protocol Q using 1 microbial mock community (MMC) (containing 8 bacterial and 2 fungal strains) and fecal samples. All samples were manually extracted and subjected to shotgun metagenomics sequencing. Extracting DNA revealed high reproducibility within all 6 protocols, but microbial extraction efficiencies varied. The MMC results demonstrated that bead size was a determining factor for fungal and bacterial DNA yields. In human fecal samples, the MagPure bacterial extraction performed as well as the standardized protocol Q but was faster and more cost-effective. Extraction using the PowerSoil protocol resulted in a significantly higher ratio of gram-negative to gram-positive bacteria than other protocols, which might contribute to reported gut microbial differences between healthy adults. Conclusions We emphasize the importance of bead size selection for bacterial and fungal DNA extraction. More importantly, the performance of the novel protocol MP matched that of the recommended standardized protocol Q but consumed less time, was more cost-effective, and is recommended for further large-scale human gut metagenomic studies.

Background The rumen microbiota provides essential services to its host and, through its role in ruminant production, contributes to human nutrition and food security. A thorough knowledge of the genetic potential of rumen microbes will provide opportunities for improving the sustainability of ruminant production systems. The availability of gene reference catalogs from gut microbiomes has advanced the understanding of the role of the microbiota in health and disease in humans and other mammals. In this work, we established a catalog of reference prokaryote genes from the bovine rumen. Results Using deep metagenome sequencing we identified 13,825,880 non-redundant prokaryote genes from the bovine rumen. Compared to human, pig, and mouse gut metagenome catalogs, the rumen is larger and richer in functions and microbial species associated with the degradation of plant cell wall material and production of methane. Genes encoding enzymes catalyzing the breakdown of plant polysaccharides showed a particularly high richness that is otherwise impossible to infer from available genomes or shallow metagenomics sequencing. The catalog expands the dataset of carbohydrate-degrading enzymes described in the rumen. Using an independent dataset from a group of 77 cattle fed 4 common dietary regimes, we found that only <0.1% of genes were shared by all animals, which contrast with a large overlap for functions, i.e., 63% for KEGG functions. Different diets induced differences in the relative abundance rather than the presence or absence of genes, which explains the great adaptability of cattle to rapidly adjust to dietary changes. Conclusions These data bring new insights into functions, carbohydrate-degrading enzymes, and microbes of the rumen to complement the available information on microbial genomes. The catalog is a significant biological resource enabling deeper understanding of phenotypes and biological processes and will be expanded as new data are made available.

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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.