Potential and active functions in the gut microbiota of a healthy human cohort

Metagenomic shotgun sequencing reveals the enrichment of Salmonella and Mycobacterium in larynx due to prolonged ethanol exposure

The exposure of ethanol increases the risk of head and neck inflammation and tumor progression. However, limited studies have investigated the composition and functionality of laryngeal microbiota under ethanol exposure. We established an ethanol-exposed mouse model to investigate the changes in composition and function of laryngeal microbiota using Metagenomic shotgun sequencing. In the middle and late stages of the experiment, the laryngeal microbiota of mice exposed to ethanol exhibited obvious distinguished from that of the control group on principal-coordinate analysis (PCoA) plots. Among the highly abundant species, Salmonella enterica and Mycobacterium marinum were likely to be most impacted. Our findings indicated that the exposure to ethanol significantly increased their abundance in larynxes in mice of the same age, which has been confirmed through FISH experiments. Among the species-related functions and genes, metabolism is most severely affected by ethanol. The difference was most obvious in the second month of the experiment, which may be alleviated later because the animal established tolerance. Notable enrichments concerning energy, amino acid, and carbohydrate metabolic pathways occurred during the second month under ethanol exposure. Finally, based on the correlation between species and functional variations, a network was established to investigate relationships among microbiota, functional pathways, and related genes affected by ethanol. Our data first demonstrated the continuous changes of abundance, function and their interrelationship of laryngeal microbiota under ethanol exposure by Metagenomic shotgun sequencing.

Importance

Ethanol may participate in the inflammation and tumor progression by affecting the composition of the laryngeal microbiota. Here, we applied the metagenomic shotgun sequencing instead of 16 S rRNA sequencing method to identify the laryngeal microbiota under ethanol exposure. Salmonella enterica and Mycobacterium marinum are two dominant species that may play a role in the reconstruction of the laryngeal microenvironment, as their local abundance increases following exposure to ethanol. The metabolic function is most evidently impacted, and several potential metabolic pathways could be associated with alterations in microbiota composition. These findings could help us better understand the impact of prolonged ethanol exposure on the microbial composition and functionality in the larynx.

Metagenomic functional profiling: to sketch or not to sketch?

MOTIVATION

Functional profiling of metagenomic samples is essential to decipher the functional capabilities of microbial communities. Traditional and more widely used functional profilers in the context of metagenomics rely on aligning reads against a known reference database. However, aligning sequencing reads against a large and fast-growing database is computationally expensive. In general, k-mer-based sketching techniques have been successfully used in metagenomics to address this bottleneck, notably in taxonomic profiling. In this work, we describe leveraging FracMinHash (implemented in sourmash, a publicly available software), a k-mer-sketching algorithm, to obtain functional profiles of metagenome samples.

RESULTS

We show how pieces of the sourmash software (and the resulting FracMinHash sketches) can be put together in a pipeline to functionally profile a metagenomic sample. We named our pipeline fmh-funprofiler. We report that the functional profiles obtained using this pipeline demonstrate comparable completeness and better purity compared to the profiles obtained using other alignment-based methods when applied to simulated metagenomic data. We also report that fmh-funprofiler is 39-99× faster in wall-clock time, and consumes up to 40-55× less memory. Coupled with the KEGG database, this method not only replicates fundamental biological insights but also highlights novel signals from the Human Microbiome Project datasets.

AVAILABILITY AND IMPLEMENTATION

This fast and lightweight metagenomic functional profiler is freely available and can be accessed here: https://github.com/KoslickiLab/fmh-funprofiler. All scripts of the analyses we present in this manuscript can be found on GitHub.

Metaproteomic portrait of the healthy human gut microbiota

Gut metaproteomics can provide direct evidence of microbial functions actively expressed in the colonic environments, contributing to clarify the role of the gut microbiota in human physiology. In this study, we re-analyzed 10 fecal metaproteomics datasets of healthy individuals from different continents and countries, with the aim of identifying stable and variable gut microbial functions and defining the contribution of specific bacterial taxa to the main metabolic pathways. The "core" metaproteome included 182 microbial functions and 83 pathways that were identified in all individuals analyzed. Several enzymes involved in glucose and pyruvate metabolism, along with glutamate dehydrogenase, acetate kinase, elongation factors G and Tu and DnaK, were the proteins with the lowest abundance variability in the cohorts under study. On the contrary, proteins involved in chemotaxis, response to stress and cell adhesion were among the most variable functions. Random-effect meta-analysis of correlation trends between taxa, functions and pathways revealed key ecological and molecular associations within the gut microbiota. The contribution of specific bacterial taxa to the main biological processes was also investigated, finding that Faecalibacterium is the most stable genus and the top contributor to anti-inflammatory butyrate production in the healthy gut microbiota. Active production of other mucosal immunomodulators facilitating host tolerance was observed, including Roseburia flagellin and lipopolysaccharide biosynthetic enzymes expressed by members of Bacteroidota. Our study provides a detailed picture of the healthy human gut microbiota, contributing to unveil its functional mechanisms and its relationship with nutrition, immunity, and environmental stressors.

In vitro batch fermentation demonstrates variations in the regulation of gut microbiota and metabolic functions by β-glucans of differing structures

The gut microbiota is widely acknowledged as a crucial factor in regulating host health. The structure of dietary fibers determines changes in the gut microbiota and metabolic differences resulting from their fermentation, which in turn affect gut microbe-related health effects. β-Glucan (BG) is a widely accessible dietary fiber to humans, and its structural characteristics vary depending on the source. However, the interactions between different structural BGs and gut microbiota remain unclear. This study used an in vitro fermentation model to investigate the effects of BG on gut microbiota, and microbiomics and metabolomics techniques to explore the relationship between the structure of BG, bacterial communities, and metabolic profiles. The four sources of BG (barley, yeast, algae, and microbial fermentation) contained different types and proportions of glycosidic bonds, which differentially altered the bacterial community. The BG from algal sources, which contained only β(1 → 4) glycosidic bonds, was the least metabolized by the gut microbiota and caused limited metabolic changes. The other three BGs contain more diverse glycosidic bonds and can be degraded by bacteria from multiple genera, causing a wider range of metabolic changes. This work also suggested potential synergistic degradation relationships between gut bacteria based on BG. Overall, this study deepens the structural characterization-microbial-functional understanding of BGs and provides theoretical support for the development of gut microbiota-targeted foods.

Deciphering the removal of antibiotics and the antibiotic resistome from typical hospital wastewater treatment systems

Hospital wastewater treatment systems (HWTSs) are a significant source and reservoir of antibiotic resistance genes (ARGs) and a crucial hub for transmitting ARGs from clinical to natural environments. However, there is a lack of research on the antibiotic resistome of clinical wastewater in HWTSs. In this study, we used metagenomics to analyze the prevalence and abundance of ARGs in five typical HWTSs. A total of 17 antibiotics from six categories were detected in the five HWTSs; β-lactam antibiotics were found at the highest concentrations, with up to 4074.08 ng·L-1. We further found a total of 21 ARG types and 1106 subtypes of ARGs with the highest percentage of multi-drug resistance genes (evgS, msbA, arlS, and baeS). The most abundant last-resort ARGs were mcr, which were detected in 100 % of the samples. HWTSs effluent is a major pathway for the transmission of last-resort ARGs into urban wastewater networks. The removal of antibiotics, antibiotic-resistant bacteria, and ARGs from HWTSs was mainly achieved by tertiary treatment, i.e., chlorine disinfection, but antibiotics and ARGs were still present in the HWTSs effluent or even increased after treatment. Moreover, antibiotics and heavy metals (especially mercury) in hospital effluents can exert selective pressure for antibiotic resistance, even at low concentrations. Qualitative analyses based on metagenome-assembled genome analysis revealed that the putative hosts of the identified ARGs are widely distributed among Pseudomonas, Acidovorax, Flavobacterium, Polaromonas, and Arcobacter. Moreover, we further assessed the clinical availability of ARGs and found that multidrug ARGs had the highest clinical relevance values. This study provides new impulses for monitoring and removing antibiotics and ARGs in the hospital sewage treatment process.

Decoupling between the genetic potential and the metabolic regulation and expression in microbial organic matter cleavage across microbiomes

Metagenomics, metatranscriptomics, and metaproteomics are used to explore the microbial capability of enzyme secretion, but the links between protein-encoding genes and corresponding transcripts/proteins across ecosystems are underexplored. By conducting a multi-omics comparison focusing on key enzymes (carbohydrate-active enzymes [CAZymes] and peptidases) cleaving the main biomolecules across distinct microbiomes living in the ocean, soil, and human gut, we show that the community structure, functional diversity, and secretion mechanisms of microbial secretory CAZymes and peptidases vary drastically between microbiomes at metagenomic, metatranscriptomic, and metaproteomic levels. Such variations lead to decoupled relationships between CAZymes and peptidases from genetic potentials to protein expressions due to the different responses of key players toward organic matter sources and concentrations. Our results highlight the need for systematic analysis of the factors shaping patterns of microbial cleavage on organic matter to better link omics data to ecosystem processes.

IMPORTANCE

Omics tools are used to explore adaptive mechanism of microbes in diverse systems, but the advantages and limitations of different omics tools remain skeptical. Here, we reported distinct profiles in microbial secretory enzyme composition revealed by different omics methods. In general, the predicted function from metagenomic analysis decoupled from the expression of corresponding transcripts/proteins. Linking omics results to taxonomic origin, functional capability, substrate specificity, secretion preference, and enzymatic activity measurement suggested the substrate's source, concentration and stoichiometry impose strong filtering on the expression of extracellular enzymes, which may overwrite the genetic potentials. Our results present an integrated perspective on the need for multi-dimensional characterization of microbial adaptation in a changing environment.

Soil pH and carbon quality index regulate the biogeochemical cycle couplings of carbon, nitrogen and phosphorus in the profiles of Isohumosols

Soil biogeochemical cycles are essential for regulating ecosystem functions and services. However, little knowledge has been revealed on microbe-driven biogeochemical processes and their coupling mechanisms in soil profiles. This study investigated the vertical distribution of soil functional composition and their contribution to carbon (C), nitrogen (N) and phosphorus (P) cycling in the humus horizons (A-horizons) and parent material horizons (C-horizons) in Udic and Ustic Isohumosols using shotgun sequencing. Results showed that the diversity and relative abundance of microbial functional genes was influenced by soil horizons and soil types. In A-horizons, the relative abundances of N mineralization and liable C decomposition genes were significantly greater, but the P cycle-related genes, recalcitrant C decomposition and denitrification genes were lower compared to C-horizons. While, Ustic Isohumosols had lower relative abundances of C decomposition genes but higher relative abundances of N mineralization and P cycling-related pathways compared to Udic Isohumosols. The network analysis revealed that C-horizons had more interactions and stronger stability of functional gene networks than in A-horizons. Importantly, our results provide new insights into the potential mechanisms for the coupling processes of soil biogeochemical cycles among C, N and P, which is mediated by specific microbial taxa. Soil pH and carbon quality index (CQI) were two sensitive indicators for regulating the relative abundances and the relationships of functional genes in biogeochemical cycles. This study contributes to a deeper understanding of the ecological functions of soil microorganisms, thus providing a theoretical basis for the exploration and utilization of soil microbial resources and the development of soil ecological control strategies.

Microbiota characterization of the green mussel Perna viridis at the tissue scale and its relationship with the environment

Research on the microbiota associated with marine invertebrates is important for understanding host physiology and the relationship between the host and the environment. In this study, the microbiota of the green mussel Perna viridis was characterized at the tissue scale using 16S rRNA gene high-throughput sequencing and compared with the microbiota of the surrounding environment. Different mussel tissues were sampled, along with two environmental samples (the mussel's attachment substratum and seawater). The results showed that the phyla Proteobacteria, Bacteroidetes, and Spirochaetae were dominant in mussel tissues. The bacterial community composition at the family level varied among the tissues of P. viridis. Although the microbiota of P. viridis clearly differed from that of the surrounding seawater, the composition and diversity of the microbial community of the foot and outer shell surface were similar to those of the substratum, indicating their close relationship with the substratum. KEGG prediction analysis indicated that the bacteria harbored by P. viridis were enriched in the degradation of aromatic compounds, osmoregulation, and carbohydrate oxidation and fermentation, processes that may be important in P. viridis physiology. Our study provides new insights into the tissue-scale characteristics of mussel microbiomes and the intricate connection between mussels and their environment.

Contigs directed gene annotation (ConDiGA) for accurate protein sequence database construction in metaproteomics

BACKGROUND

Microbiota are closely associated with human health and disease. Metaproteomics can provide a direct means to identify microbial proteins in microbiota for compositional and functional characterization. However, in-depth and accurate metaproteomics is still limited due to the extreme complexity and high diversity of microbiota samples. It is generally recommended to use metagenomic data from the same samples to construct the protein sequence database for metaproteomic data analysis. Although different metagenomics-based database construction strategies have been developed, an optimization of gene taxonomic annotation has not been reported, which, however, is extremely important for accurate metaproteomic analysis.

RESULTS

Herein, we proposed an accurate taxonomic annotation pipeline for genes from metagenomic data, namely contigs directed gene annotation (ConDiGA), and used the method to build a protein sequence database for metaproteomic analysis. We compared our pipeline (ConDiGA or MD3) with two other popular annotation pipelines (MD1 and MD2). In MD1, genes were directly annotated against the whole bacterial genome database; in MD2, contigs were annotated against the whole bacterial genome database and the taxonomic information of contigs was assigned to the genes; in MD3, the most confident species from the contigs annotation results were taken as reference to annotate genes. Annotation tools, including BLAST, Kaiju, and Kraken2, were compared. Based on a synthetic microbial community of 12 species, it was found that Kaiju with the MD3 pipeline outperformed the others in the construction of protein sequence database from metagenomic data. Similar performance was also observed with a fecal sample, as well as in silico mixed datasets of the simulated microbial community and the fecal sample.

CONCLUSIONS

Overall, we developed an optimized pipeline for gene taxonomic annotation to construct protein sequence databases. Our study can tackle the current taxonomic annotation reliability problem in metagenomics-derived protein sequence database and can promote the in-depth metaproteomic analysis of microbiome. The unique metagenomic and metaproteomic datasets of the 12 bacterial species are publicly available as a standard benchmarking sample for evaluating various analysis pipelines. The code of ConDiGA is open access at GitHub for the analysis of microbiota samples. Video Abstract.

gNOMO2: a comprehensive and modular pipeline for integrated multi-omics analyses of microbiomes

BACKGROUND

In recent years, omics technologies have offered an exceptional chance to gain a deeper insight into the structural and functional characteristics of microbial communities. As a result, there is a growing demand for user-friendly, reproducible, and versatile bioinformatic tools that can effectively harness multi-omics data to provide a holistic understanding of microbiomes. Previously, we introduced gNOMO, a bioinformatic pipeline tailored to analyze microbiome multi-omics data in an integrative manner. In response to the evolving demands within the microbiome field and the growing necessity for integrated multi-omics data analysis, we have implemented substantial enhancements to the gNOMO pipeline.

RESULTS

Here, we present gNOMO2, a comprehensive and modular pipeline that can seamlessly manage various omics combinations, ranging from 2 to 4 distinct omics data types, including 16S ribosomal RNA (rRNA) gene amplicon sequencing, metagenomics, metatranscriptomics, and metaproteomics. Furthermore, gNOMO2 features a specialized module for processing 16S rRNA gene amplicon sequencing data to create a protein database suitable for metaproteomics investigations. Moreover, it incorporates new differential abundance, integration, and visualization approaches, enhancing the toolkit for a more insightful analysis of microbiomes. The functionality of these new features is showcased through the use of 4 microbiome multi-omics datasets encompassing various ecosystems and omics combinations. gNOMO2 not only replicated most of the primary findings from these studies but also offered further valuable perspectives.

CONCLUSIONS

gNOMO2 enables the thorough integration of taxonomic and functional analyses in microbiome multi-omics data, offering novel insights in both host-associated and free-living microbiome research. gNOMO2 is available freely at https://github.com/muzafferarikan/gNOMO2.

Metaproteomic Analysis of Fecal Samples from Human Subjects and Rodent Models

Fecal metaproteomics is a useful approach to measure changes in microbial and host protein abundance and to infer which members of the gut microbiota are involved in specific functions and pathways. This chapter describes a protocol enabling analysis and characterization of fecal metaproteomes, successfully applied to human, mouse, and rat stool samples. The protocol combines mechanical and thermal treatments for protein extraction, a centrifugal filter-based procedure for cleanup and digestion, long-gradient liquid chromatography for peptide separation, and high-resolution mass spectrometry for peptide detection.

Application of culturomics in fungal isolation from mangrove sediments

BACKGROUND

Fungi play a crucial role in ecosystems, and they have been widely considered a promising source for natural compounds that are crucial for drug discovery. Fungi have a high diversity, but about 95% of them remain unknown to science. The description rate of fungi is very low, mainly due to the inability of most fungi to grow in artificial media, which could not provide a sufficiently similar environment to their natural habitats. Moreover, many species in nature are in a state of low metabolic activity which cannot readily proliferate without proper resuscitation. Previously developed culturomics techniques are mostly designed and applicable for bacteria, with few attempts for fungal isolation because of their significantly larger cell size and hyphal growth properties.

RESULTS

This study attempted to isolate previously uncultured and rare fungi from mangrove sediments using newly developed fungal enrichment culture method (FECM) and fungal isolation chips (FiChips). Comparison of fungal community composition at different enrichment stages showed that FECM had great influence on fungal community composition, with rare taxa increased significantly, thus improving the isolation efficiency of previously uncultured fungi. Similarly, in situ cultivation using FiChips has a significant advantage in detecting and culturing rare fungi, as compared to the conventional dilution plate method (DPM). In addition, based on morphological comparisons and phylogenetic analyses, we described and proposed 38 new ascomycetous taxa, including three new families, eight new genera, 25 new species, and two new combinations (presented in additional file 1).

CONCLUSIONS

Our study demonstrated that mangrove sediments harbor a high diversity of fungi, and our new isolation approaches (FECM and FiChips) presented a high efficiency in isolating hitherto uncultured fungi, which is potentially usable for fungal isolation in other similar environments. Video Abstract.

Effects of Fu brick tea polysaccharides on gut microbiota and fecal metabolites of HFD/STZ-induced type 2 diabetes rats

The prevalence of type 2 diabetes mellitus (T2DM) has dramatically increased globally, and the antidiabetic effects and underlying mechanisms of the polysaccharides extracted from Fu brick tea (FBTP) were investigated in high-fat diet (HFD)/streptozotocin (STZ)-induced T2DM rats. Administration of FBTP at 200 and 400 mg per kg bw significantly relieved dyslipidemia (i.e. TC, TG, LDL-C and HDL-C), insulin resistance (IR) and pancreas oxidative stress (i.e. CAT and GSH-Px) in T2DM rats. Mechanistically, FBTP rescued the HFD/STZ-induced alterations in the abundance of Bacteroidota, Actinobacteriota, Proteobacteria and Firmicutes. At the genus level, FBTP notably increased the abundance of Ruminococcus, Lactobacillus and Lachnospiraece_NK4A136_group, but reduced the population of Prevotella and Faecalibaculum in T2DM rats. FBTP also significantly elevated colonic short-chain fatty acid (SCFAs) levels. Moreover, apparent changes in amino acid absorption and metabolism were observed upon FBTP intervention. These findings suggested that FBTP might alleviate T2DM by reshaping the gut microbiota and regulating intestinal metabolites.

Metagenomics insights into high-rate nitrogen removal from municipal wastewater by integrated nitrification, partial denitrification and Anammox at an extremely short hydraulic retention time

To achieve high-rate nitrogen removal in municipal wastewater treatment through anaerobic ammonia oxidation (Anammox), the nitrification, partial denitrification, and Anammox processes were integrated by a step-feed strategy. An exceptional nitrogen removal load of 0.224 kg N/(m3·d) was achieved by gradient-reducing the hydraulic retention time (HRT) to 5 h. Metagenomic analysis demonstrated that Nitrosospira could express all genes encoding ammonia oxidation under low nitrogen and dissolved oxygen conditions (less than 0.5 mg/L), enabling complete nitrification. With the short of HRT, the relative abundance of Thauera increased from 2.8 % to 6.4 %. Frequent substrate exchanges at such extremely short HRT facilitated enhanced synergistic interactions among Nitrosospira, Thauera, and Candidatus Brocadia. These findings provide a comprehensive understanding of the utilization of Anammox combined processes for high-speed nitrogen removal in municipal wastewater treatment and the microbial interactions involved.

metaSpectraST: an unsupervised and database-independent analysis workflow for metaproteomic MS/MS data using spectrum clustering

BACKGROUND

The high diversity and complexity of the microbial community make it a formidable challenge to identify and quantify the large number of proteins expressed in the community. Conventional metaproteomics approaches largely rely on accurate identification of the MS/MS spectra to their corresponding short peptides in the digested samples, followed by protein inference and subsequent taxonomic and functional analysis of the detected proteins. These approaches are dependent on the availability of protein sequence databases derived either from sample-specific metagenomic data or from public repositories. Due to the incompleteness and imperfections of these protein sequence databases, and the preponderance of homologous proteins expressed by different bacterial species in the community, this computational process of peptide identification and protein inference is challenging and error-prone, which hinders the comparison of metaproteomes across multiple samples.

RESULTS

We developed metaSpectraST, an unsupervised and database-independent metaproteomics workflow, which quantitatively profiles and compares metaproteomics samples by clustering experimentally observed MS/MS spectra based on their spectral similarity. We applied metaSpectraST to fecal samples collected from littermates of two different mother mice right after weaning. Quantitative proteome profiles of the microbial communities of different mice were obtained without any peptide-spectrum identification and used to evaluate the overall similarity between samples and highlight any differentiating markers. Compared to the conventional database-dependent metaproteomics analysis, metaSpectraST is more successful in classifying the samples and detecting the subtle microbiome changes of mouse gut microbiomes post-weaning. metaSpectraST could also be used as a tool to select the suitable biological replicates from samples with wide inter-individual variation.

CONCLUSIONS

metaSpectraST enables rapid profiling of metaproteomic samples quantitatively, without the need for constructing the protein sequence database or identification of the MS/MS spectra. It maximally preserves information contained in the experimental MS/MS spectra by clustering all of them first and thus is able to better profile the complex microbial communities and highlight their functional changes, as compared with conventional approaches. tag the videobyte in this section as ESM4 Video Abstract.

Unipept Desktop 2.0: Construction of Targeted Reference Protein Databases for Metaproteogenomics Analyses

Unipept Desktop 2.0 is the most recent iteration of the Unipept Desktop tool that adds support for the analysis of metaproteogenomics datasets. Unipept Desktop now supports the automatic construction of targeted protein reference databases that only contain proteins (originating from the UniProtKB resource) associated with a predetermined list of taxa. This improves both the taxonomic and functional resolution of a metaproteomic analysis and yields several technical advantages. By limiting the proteins present in a reference database, it is also possible to perform (meta)proteogenomics analyses. Since the protein reference database resides on the user's local machine, they have complete control over the database used during an analysis. Data no longer need to be transmitted over the Internet, decreasing the time required for an analysis and better safeguarding privacy-sensitive data. As a proof of concept, we present a case study in which a human gut metaproteome dataset is analyzed with Unipept Desktop 2.0 using different targeted databases based on matched 16S rRNA gene sequencing data.

Mistle: bringing spectral library predictions to metaproteomics with an efficient search index

MOTIVATION

Deep learning has moved to the forefront of tandem mass spectrometry-driven proteomics and authentic prediction for peptide fragmentation is more feasible than ever. Still, at this point spectral prediction is mainly used to validate database search results or for confined search spaces. Fully predicted spectral libraries have not yet been efficiently adapted to large search space problems that often occur in metaproteomics or proteogenomics.

RESULTS

In this study, we showcase a workflow that uses Prosit for spectral library predictions on two common metaproteomes and implement an indexing and search algorithm, Mistle, to efficiently identify experimental mass spectra within the library. Hence, the workflow emulates a classic protein sequence database search with protein digestion but builds a searchable index from spectral predictions as an in-between step. We compare Mistle to popular search engines, both on a spectral and database search level, and provide evidence that this approach is more accurate than a database search using MSFragger. Mistle outperforms other spectral library search engines in terms of run time and proves to be extremely memory efficient with a 4- to 22-fold decrease in RAM usage. This makes Mistle universally applicable to large search spaces, e.g. covering comprehensive sequence databases of diverse microbiomes.

AVAILABILITY AND IMPLEMENTATION

Mistle is freely available on GitHub at https://github.com/BAMeScience/Mistle.

Gut microbiota and its relation to inflammation in patients with bipolar depression: a cross-sectional study

BACKGROUND

To explore the gut microbiota characteristics in depressed patients with bipolar disorder (BD) as well as the connection between the gut microbiota and inflammatory markers.

METHODS

Totally 72 depressed BD patients and 16 healthy controls (HCs) were enrolled in the study. Blood and feces samples were taken from each subject. With the help of 16S-ribosomal RNA gene sequencing, the characteristics of the gut microbiota in each participant were examined. Correlation analysis was then utilized to assess the relationship between the gut microbiota and clinical parameters.

RESULTS

We found the taxonomic composition of the gut microbiota, but not its diversity, was significantly different in BD patients compared to HCs. We found the abundance of Bacilli, Lactobacillales and genus Veillonella were higher in BD patients than in HCs, while genus Dorea was more abundant in HCs. Additionally, correlation analysis showed that the bacterial genera' abundance in BD patients was strongly correlated with the severity of depression and inflammatory markers.

CONCLUSIONS

According to these results, the gut microbiota characteristics were changed in depressed BD patients, which may have been associated with the severity of depression and the inflammatory pathways.

BBIBP-CorV Vaccination against the SARS-CoV-2 Virus Affects the Gut Microbiome

Several observational studies have confirmed that the severe acute respiratory syndrome coronavirus2 (SARS-CoV-2) might substantially affect the gastrointestinal (GI) system by replicating in human small intestine enterocytes. Yet, so far, no study has reported the effects of inactivated SARS-CoV-2 virus vaccines on gut microbiota alterations. In this study, we examined the effects of the BBIBP-CorV vaccine (ChiCTR2000032459, sponsored by the Beijing Institute of Biological Products/Sinopharm), on gut microbiota. Fecal samples were collected from individuals whoreceived two doses of intramuscular injection of BBIBP-CorV and matched unvaccinated controls. DNA extracted from fecal samples was subjected to 16S ribosomal RNA sequencing analysis. The composition and biological functions of the microbiota between vaccinated and unvaccinated individuals were compared. Compared with unvaccinated controls, vaccinated subjects exhibited significantly reduced bacterial diversity, elevated firmicutes/bacteroidetes (F/B) ratios, a tendency towards Faecalibacterium-predominant enterotypes, and altered gut microbial compositions and functional potentials. Specifically, the intestinal microbiota in vaccine recipients was enriched with Faecalibacterium and Mollicutes and with a lower abundance of Prevotella, Enterococcus, Leuconostocaceae, and Weissella. Microbial function prediction by phylogenetic investigation of communities using reconstruction of unobserved states (PICRUSt) analysis further indicated that Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways involved in carbohydrate metabolism and transcription were positively associated with vaccine inoculation, whereas capacities in neurodegenerative diseases, cardiovascular diseases, and cancers were negatively affected by vaccines. Vaccine inoculation was particularly associated with gut microbiota alterations, as was demonstrated by the improved composition and functional capacities of gut microbiota.

Effect of metformin on sepsis-associated acute lung injury and gut microbiota in aged rats with sepsis

Background

Recent studies reported the association between the changes in gut microbiota and sepsis, but there is unclear for the gut microbes on aged sepsis is associated acute lung injury (SALI), and metformin treatment for the change in gut microbiota. This study aimed to investigate the effect of metformin on gut microbiota and SALI in aged rats with sepsis. It also explored the therapeutic mechanism and the effect of metformin on aged rats with SALI.

Methods

Aged 20-21 months SD rats were categorized into three groups: sham-operated rats (AgS group), rats with cecal ligation and puncture (CLP)-induced sepsis (AgCLP group), and rats treated with metformin (100 mg/kg) orally 1 h after CLP treatment (AgMET group). We collected feces from rats and analyzed them by 16S rRNA sequencing. Further, the lung samples were collected for histological analysis and quantitative real-time PCR (qPCR) assay and so on.

Results

This study showed that some pathological changes occurring in the lungs of aged rats, such as hemorrhage, edema, and inflammation, improved after metformin treatment; the number of hepatocyte death increased in the AgCLP group, and decreased in the AgMET group. Moreover, metformin relieved SALI inflammation and damage. Importantly, the gut microbiota composition among the three groups in aged SALI rats was different. In particular, the proportion of E. coli and K. pneumoniae was higher in AgCLP group rats than AgS group rats and AgMET group rats; while metformin could increase the proportion of Firmicutes, Lactobacillus, Ruminococcus_1 and Lactobacillus_johnsonii in aged SALI rats. Moreover, Prevotella_9, Klebsiella and Escherichia_Shigella were correlated positively with the inflammatory factor IL-1 in the lung tissues; Firmicutes was correlated negatively with the inflammatory factor IL-1 and IL-6 in the lung tissues.

Conclusions

Our findings suggested that metformin could improve SALI and gut microbiota in aged rats, which could provide a potential therapeutic treatment for SALI in aged sepsis.

Sulfur: a neglected driver of the increased abundance of antibiotic resistance genes in agricultural reclaimed subsidence land located in coal mines with high phreatic water levels

Due to the shallow burial of groundwater in coal mines with a high phreatic water level, a large area of subsidence lakes is formed after the mine collapses. Agricultural and fishery reclamation activities have been carried out, which introduced antibiotics and exacerbated the contamination of antibiotic resistance genes (ARGs), but this has received limited attention. This study analyzed ARG occurrence in reclaimed mining areas, the key impact factors, and the underlying mechanism. The results show that sulfur is the most critical factor impacting the abundance of ARGs in reclaimed soil, which is due to changes in the microbial community. The species and abundance of ARGs in the reclaimed soil were higher than those in the controlled soil. The relative abundances of most ARGs increased with the depth of reclaimed soil (from 0 to 80 cm). In addition, the microbial structures of the reclaimed and controlled soils were significantly different. Proteobacteria, was the most dominant microbial phylum in the reclaimed soil. This difference is likely related to the high abundance of sulfur metabolism functional genes in the reclaimed soil. Correlation analysis showed that the differences in ARGs and microorganisms in the two soil types were highly correlated with the sulfur content. High levels of sulfur promoted the proliferation of sulfur-metabolizing microbial populations such as Proteobacteria and Gemmatimonadetes in the reclaimed soils. Remarkably, these microbial phyla were the main antibiotic-resistant bacteria in this study, and their proliferation created conditions for the enrichment of ARGs. Overall, this study underscores the risk of the abundance and spread of ARGs driven by high-level sulfur in reclaimed soils and reveals the mechanisms.

Virome diversity of ticks feeding on domestic mammals in China

Ticks are considered the second most common pathogen vectors transmitting a broad range of vital human and veterinary viruses. From 2017 to 2018, 640 ticks were collected in eight different provinces in central and western China. Six species were detected, including H.longicornis, De.everestianus, Rh.microplus, Rh.turanicus, Rh.sanguineous, and Hy.asiaticum. Sixty-four viral metagenomic libraries were constructed on the MiSeq Illumina platform, resulting in 13.44 ​G (5.88 ​× ​10⁷) of 250-bp-end reads, in which 2,437,941 are viral reads. We found 27 nearly complete genome sequences, including 16 genome sequences encoding entire protein-coding regions (lack of 3' or 5' end non-coding regions) and complete viral genomes, distributed in the arboviral family (Chuviridae, Rhabdoviridae, Nairoviridae, Phenuiviridae, Flaviviridae, Iflaviridae) as well as Parvoviridae and Polyomaviridae that cause disease in mammals and even humans. In addition, 13 virus sequences found in Chuviridae, Nairoviridae, Flaviviridae, Iflaviridae, Hepeviridae, Parvoviridae, and Polyomaviridae were identified as belonging to a new virus species in the identified viral genera. Besides, an epidemiological survey shows a high prevalence (9.38% and 15.63%) of two viruses (Ovine Copiparvovirus and Bovine parvovirus 2) in the tick cohort.

Data-independent acquisition boosts quantitative metaproteomics for deep characterization of gut microbiota

Metaproteomics can provide valuable insights into the functions of human gut microbiota (GM), but is challenging due to the extreme complexity and heterogeneity of GM. Data-independent acquisition (DIA) mass spectrometry (MS) has been an emerging quantitative technique in conventional proteomics, but is still at the early stage of development in the field of metaproteomics. Herein, we applied library-free DIA (directDIA)-based metaproteomics and compared the directDIA with other MS-based quantification techniques for metaproteomics on simulated microbial communities and feces samples spiked with bacteria with known ratios, demonstrating the superior performance of directDIA by a comprehensive consideration of proteome coverage in identification as well as accuracy and precision in quantification. We characterized human GM in two cohorts of clinical fecal samples of pancreatic cancer (PC) and mild cognitive impairment (MCI). About 70,000 microbial proteins were quantified in each cohort and annotated to profile the taxonomic and functional characteristics of GM in different diseases. Our work demonstrated the utility of directDIA in quantitative metaproteomics for investigating intestinal microbiota and its related disease pathogenesis.

Metatranscriptomics-guided genome-scale metabolic modeling of microbial communities

Multi-omics data integration via mechanistic models of metabolism is a scalable and flexible framework for exploring biological hypotheses in microbial systems. However, although most microorganisms are unculturable, such multi-omics modeling is limited to isolate microbes or simple synthetic communities. Here, we developed an approach for modeling microbial activity and interactions that leverages the reconstruction of metagenome-assembled genomes and associated genome-centric metatranscriptomes. At its core, we designed a method for condition-specific metabolic modeling of microbial communities through the integration of metatranscriptomic data. Using this approach, we explored the behavior of anaerobic digestion consortia driven by hydrogen availability and human gut microbiota dysbiosis associated with Crohn's disease, identifying condition-dependent amino acid requirements in archaeal species and a reduced short-chain fatty acid exchange network associated with disease, respectively. Our approach can be applied to complex microbial communities, allowing a mechanistic contextualization of multi-omics data on a metagenome scale.

Flavonifractor plautii Protects Against Elevated Arterial Stiffness

BACKGROUND

Dysbiosis of gut microbiota plays a pivotal role in vascular dysfunction and microbial diversity was reported to be inversely correlated with arterial stiffness. However, the causal role of gut microbiota in the progression of arterial stiffness and the specific species along with the molecular mechanisms underlying this change remain largely unknown.

METHODS

Participants with elevated arterial stiffness and normal controls free of medication were matched for age and sex. The microbial composition and metabolic capacities between the 2 groups were compared with the integration of metagenomics and metabolomics. Subsequently, Ang II (angiotensin II)-induced and humanized mouse model were employed to evaluate the protective effect of Flavonifractor plautii (F plautii) and its main effector cis-aconitic acid.

RESULTS

Human fecal metagenomic sequencing revealed a significantly high abundance and centrality of F plautii in normal controls, which was absent in the microbial community of subjects with elevated arterial stiffness. Moreover, blood pressure only mediated part of the effect of F plautii on lower arterial stiffness. The microbiome of normal controls exhibited an enhanced capacity for glycolysis and polysaccharide degradation, whereas, those of subjects with increased arterial stiffness were characterized by increased biosynthesis of fatty acids and aromatic amino acids. Integrative analysis with metabolomics profiling further suggested that increased cis-aconitic acid served as the main effector for the protective effect of F plautii against arterial stiffness. Replenishment with F plautii and cis-aconitic acid improved elastic fiber network and reversed increased pulse wave velocity through the suppression of MMP-2 (matrix metalloproteinase-2) and inhibition of MCP-1 (monocyte chemoattractant protein-1) and NF-κB (nuclear factor kappa-B) activation in both Ang II-induced and humanized model of arterial stiffness.

CONCLUSIONS

Our translational study identifies a novel link between F plautii and arterial function and raises the possibility of sustaining vascular health by targeting gut microbiota.

Trait-Based Method of Quantitative Assessment of Ecological Functional Groups in the Human Intestinal Microbiome

We propose the trait-based method for quantifying the activity of functional groups in the human gut microbiome based on metatranscriptomic data. It allows one to assess structural changes in the microbial community comprised of the following functional groups: butyrate-producers, acetogens, sulfate-reducers, and mucin-decomposing bacteria. It is another way to perform a functional analysis of metatranscriptomic data by focusing on the ecological level of the community under study. To develop the method, we used published data obtained in a carefully controlled environment and from a synthetic microbial community, where the problem of ambiguity between functionality and taxonomy is absent. The developed method was validated using RNA-seq data and sequencing data of the 16S rRNA amplicon on a simplified community. Consequently, the successful verification provides prospects for the application of this method for analyzing natural communities of the human intestinal microbiota.

Microbiome and Human Health: Current Understanding, Engineering, and Enabling Technologies

The human microbiome is composed of a collection of dynamic microbial communities that inhabit various anatomical locations in the body. Accordingly, the coevolution of the microbiome with the host has resulted in these communities playing a profound role in promoting human health. Consequently, perturbations in the human microbiome can cause or exacerbate several diseases. In this Review, we present our current understanding of the relationship between human health and disease development, focusing on the microbiomes found across the digestive, respiratory, urinary, and reproductive systems as well as the skin. We further discuss various strategies by which the composition and function of the human microbiome can be modulated to exert a therapeutic effect on the host. Finally, we examine technologies such as multiomics approaches and cellular reprogramming of microbes that can enable significant advancements in microbiome research and engineering.

Quantitative metaproteomics reveals composition and metabolism characteristics of microbial communities in Chinese liquor fermentation starters

Introduction

Daqu, the Chinese liquor fermentation starter, contains complex microbial communities that are important for the yield, quality, and unique flavor of produced liquor. However, the composition and metabolism of microbial communities in the different types of high-temperature Daqu (i.e., white, yellow, and black Daqu) have not been well understood.

Methods

Herein, we used quantitative metaproteomics based on data-independent acquisition (DIA) mass spectrometry to analyze a total of 90 samples of white, yellow, and black Daqu collected in spring, summer, and autumn, revealing the taxonomic and metabolic profiles of different types of Daqu across seasons.

Results

Taxonomic composition differences were explored across types of Daqu and seasons, where the under-fermented white Daqu showed the higher microbial diversity and seasonal stability. It was demonstrated that yellow Daqu had higher abundance of saccharifying enzymes for raw material degradation. In addition, considerable seasonal variation of microbial protein abundance was discovered in the over-fermented black Daqu, suggesting elevated carbohydrate and amino acid metabolism in autumn black Daqu.

Discussion

We expect that this study will facilitate the understanding of the key microbes and their metabolism in the traditional fermentation process of Chinese liquor production.

Early intestinal microbiota changes in aged and adult mice with sepsis

Background

The mortality rate associated with sepsis in elderly individuals is higher than that in younger individuals. The intestinal microbiota has been demonstrated to play an important role in the occurrence and development of sepsis. The purpose of this study was to investigate the differences in the intestinal microbiota between aged and adult mice with sepsis.

Methods

Thirty male C57BL mice were randomly divided into two groups: 15 in the adult group (AD group) and 15 in the age group (Age group). All the mice underwent caecal ligation and puncture to induce sepsis. Mice faeces were collected, and analysed using 16S rRNA sequencing. The liver and colon tissues were collected.

Results

There were significant differences in intestinal microbiota composition between the two groups. Compared with adult sepsis mice, the diversity of intestinal microbiota in the aged group was significantly reduced and the structure of dominant intestinal microbiota was changed. In the Age group, the microbiota associated with inflammatory factors increased, and the microbiota associated with the production of SCFAs (Ruminiclostridium, Prevotellaceae_UCG-001, Rikenella, Parabacteroides, Oscillibacter, Odoribacter, Muribaculum, Lachnoclostridium, Intestinimonas, Faecalibaculum, Anaerotruncus, Alloprevotella and Absiella) decreased. The metabolic pathways related to the microbiota also changed. Moreover, the proportion of inflammatory factors in Age group was higher than that in AD group.

Conclusion

Our results showed that there were significant differences in the abundance and structure of microbiota between aged and adult sepsis mice, Aged sepsis mice have more severe intestinal microbiota destruction and liver tissue inflammation than adult sepsis mice.

Scrophulariae Radix-Atractylodes sinensis pair and metformin inhibit inflammation by modulating gut microbiota of high-fat diet/streptozotocin-induced diabetes in rats

INTRODUCTION

Type 2 mellitus (T2DM), a chronic metabolic disorder, causes severe impairment of patients' quality of life and has attracted global attention. Many studies have suggested the importance of the gut microbiota in the occurrence of T2DM. The Scrophulariae Radix and Atractylodes sinensis (XC) pair, recommended in traditional Chinese medicine (TCM), have been used for treating diabetes for many years. However, research on the role of the XC pair in modulating gut microbial communities is lacking, but it is important to elucidate the underlying mechanism.

METHODS

In this study, we detected bacterial communities by high-throughput 16S rRNA gene sequencing.

RESULTS

The results showed that XC + MET reduced postprandial hyperglycemia and inflammatory response in diabetic rats more effectively than metformin (MET) alone. The XC + MET treatment reshaped the intestinal microbial composition of diabetic rats. XC can help MET regulate carbohydrate, amino acid, and lipid metabolism, particularly the insulin signaling pathway.

DISCUSSION

This research would help elucidate potential mechanisms and the treatment methods.

Dietary supplementation with Tolypocladium sinense mycelium prevents dyslipidemia inflammation in high fat diet mice by modulation of gut microbiota in mice

Obesity is a risk factor for many serious health problems, associated with inflammation, hyperlipidemia, and gut dysbiosis. Prevention of obesity is especially important for human health. Tolypocladium sinense is one of the fungi isolated from Chinese caterpillar fungus, which is a traditional Chinese medicine with putative gut microbiota modulation effects. Here, we established a high-fat diet (HFD)-induced hyperlipidemia mice model, which was supplemented with lyophilized T. sinense mycelium (TSP) daily to evaluate its anti-obesity effects. The results indicated that TSP supplementation can effectively alleviate the inflammatory response and oxidative stress levels caused by obesity. TSP significantly prevented obesity and suppressed dyslipidemia by regulating the expression of lipid metabolism genes in the liver. TSP is also effective in preventing the HFD-induced decline in short-chain fatty acid (SCFA) content. Gut microbiota profiling showed that TSP supplementation reversed HFD diet-induced bacterial abundance and also altered the metabolic pathways of functional microorganisms, as revealed by KEGG analysis. It is noteworthy that, correlation analysis reveals the up-regulated gut microbiota (Lactobacillus and Prevotella_9) are closely correlated with lipid metabolism parameters, gene expression of liver lipid metabolism and inflammatory. Additionally, the role of TSP in the regulation of lipid metabolism was reconfirmed by fecal microbiota transplantation. To sum up, our results provide the evidence that TSP may be used as prebiotic agents to prevent obesity by altering the gut microbiota, alleviating the inflammatory response and regulating gene expression of liver lipid metabolism.

Microbe-based therapies for colorectal cancer: Advantages and limitations

Cancer is one of the leading global causes of death in both men and women. Colorectal cancer (CRC) alone accounts for ∼10 % of total new global cases and poses an over 4% lifetime risk of developing cancer. Recent advancements in the field of biotechnology and microbiology concocted novel microbe-based therapies to treat various cancers, including CRC. Microbes have been explored for human use since centuries, especially for the treatment of various ailments. The utility of microbes in cancer therapeutics is widely explored, and various bacteria, fungi, and viruses are currently in use for the development of cancer therapeutics. The human gut hosts about 100 trillion microbes that release their metabolites in active, inactive, or dead conditions. Microbial secondary metabolites, proteins, immunotoxins, and enzymes are used to target cancer cells to induce cell cycle arrest, apoptosis, and death. Various approaches, such as dietary interventions, the use of prebiotics and probiotics, and fecal microbiota transplantation have been used to modulate the gut microbiota in order to prevent or treat CRC pathogenesis. The present review highlights the role of the gut microbiota in CRC precipitation, the potential mechanisms and use of microorganisms as CRC biomarkers, and strategies to modulate microbiota for the prevention and treatment of CRC.

Gut bacterial extracellular vesicles: important players in regulating intestinal microenvironment

Intestinal microenvironment dysbiosis is one of the major causes of diseases, such as obesity, diabetes, inflammatory bowel disease, and colon cancer. Microbiota-based strategies have excellent clinical potential in the treatment of repetitive and refractory diseases; however, the underlying regulatory mechanisms remain elusive. Identification of the internal regulatory mechanism of the gut microbiome and the interaction mechanisms involving bacteria-host is essential to achieve precise control of the gut microbiome and obtain effective clinical data. Gut bacteria-derived extracellular vesicles (GBEVs) are lipid bilayer nanoparticles secreted by the gut microbiota and are considered key players in bacteria-bacteria and bacteria-host communication. This review focusses on the role of GBEVs in gut microbiota interactions and bacteria-host communication, and the potential clinical applications of GBEVs.

In-Depth Metaproteomics Analysis of Oral Microbiome for Lung Cancer

The human oral microbiome correlates with numerous diseases, including lung cancer. Identifying the functional changes by metaproteomics helps understand the disease-related dysbiosis, yet characterizing low-abundant bacteria is challenging. Here, we developed a free-flow isoelectric focusing electrophoresis-mass spectrometry- (FFIEF-MS-) based metaproteomics strategy to reduce host interferences and enrich low-abundant bacteria for in-depth interpretation of the oral microbiome. With our method, the number of interfering peptides decreased by 52.87%, whereas the bacterial peptides and species increased by 94.97% and 44.90%, respectively, compared to the conventional metaproteomics approach. We identified 3647 bacterial proteins, which is the most comprehensive oral metaproteomics study to date. Lung cancer-associated bacteria were validated among an independent cohort. The imbalanced Fusobacterium nucleatum and Prevotella histicola and their dysregulated functions in inhibiting immune response and maintaining cell redox homeostasis were revealed. The FFIEF-MS may serve as a valuable strategy to study the mechanisms between human diseases and microbiomes with broader applications.

The Microbiota-Gut-Brain Axis in Psychiatric Disorders

Modulating the gut microbiome and its influence on human health is the subject of intense research. The gut microbiota could be associated not only with gastroenterological diseases but also with psychiatric disorders. The importance of factors such as stress, mode of delivery, the role of probiotics, circadian clock system, diet, and occupational and environmental exposure in the relationship between the gut microbiota and brain function through bidirectional communication, described as "the microbiome-gut-brain axis", is especially underlined. In this review, we discuss the link between the intestinal microbiome and the brain and host response involving different pathways between the intestinal microbiota and the nervous system (e.g., neurotransmitters, endocrine system, immunological mechanisms, or bacterial metabolites). We review the microbiota alterations and their results in the development of psychiatric disorders, including major depressive disorder (MDD), schizophrenia (SCZ), bipolar disorder (BD), autism spectrum disorder (ASD), and attention-deficit hyperactivity disorder (ADHD).

Insights of Host Physiological Parameters and Gut Microbiome of Indian Type 2 Diabetic Patients Visualized via Metagenomics and Machine Learning Approaches

Type 2 diabetes (T2D) is a serious public health issue and may also contribute to modification in the structure of the intestinal microbiota, implying a link between T2D and microbial inhabitants in the digestive tract. This work aimed to develop efficient models for identifying essential physiological markers for improved T2D classification using machine learning algorithms. Using amplicon metagenomic approaches, an effort has also been made to understand the alterations in core gut microbial members in Indian T2D patients with respect to their control normal glucose tolerance (NGT). Our data indicate the level of fasting blood glucose (FBG) and glycated hemoglobin (HbA1c) were the most useful physiological indicators while random forest and support vector machine with RBF Kernel were effective predictions models for identifications of T2D. The dominating gut microbial members Allopreotella, Rikenellaceae RC9 gut group, Haemophilus, Ruminococcus torques group, etc. in Indian T2D patients showed a strong association with both FBG and HbA1c. These members have been reported to have a crucial role in gut barrier breakdown, blood glucose, and lipopolysaccharide level escalation, or as biomarkers. While the dominant NGT microbiota (Akkermansia, Ligilactobacillus, Enterobacter, etc.) in the colon has been shown to influence inflammatory immune responses by acting as an anti-inflammatory agent and maintaining the gut barrier. The topology study of co-occurrence network analysis indicates that changes in network complexity in T2D lead to variations in the different gut microbial members compared to NGT. These studies provide a better understanding of the gut microbial diversity in Indian T2D patients and show the way for the development of valuable diagnostics strategies to improve the prediction and modulation of the T2D along with already established methods.

Hypoglycemic Effects of Lycium barbarum Polysaccharide in Type 2 Diabetes Mellitus Mice via Modulating Gut Microbiota

This study aims to explore the molecular mechanisms of Lycium barbarum polysaccharide (LBP) in alleviating type 2 diabetes through intestinal flora modulation. A high-fat diet (HFD) combined with streptozotocin (STZ) was applied to create a diabetic model. The results indicated that LBP effectively alleviated the symptoms of hyperglycemia, hyperlipidemia, and insulin resistance in diabetic mice. A high dosage of LBP exerted better hypoglycemic effects than low and medium dosages. In diabetic mice, LBP significantly boosted the activities of CAT, SOD, and GSH-Px and reduced inflammation. The analysis of 16S rDNA disclosed that LBP notably improved the composition of intestinal flora, increasing the relative abundance of Bacteroides, Ruminococcaceae_UCG-014, Intestinimonas, Mucispirillum, Ruminococcaceae_UCG-009 and decreasing the relative abundance of Allobaculum, Dubosiella, Romboutsia. LBP significantly improved the production of short-chain fatty acids (SCFAs) in diabetic mice, which corresponded to the increase in the beneficial genus. According to Spearman’s correlation analysis, Cetobacterium, Streptococcus, Ralstonia. Cetobacterium, Ruminiclostridium, and Bifidobacterium correlated positively with insulin, whereas Cetobacterium, Millionella, Clostridium_sensu_stricto_1, Streptococcus, and Ruminococcaceae_UCG_009 correlated negatively with HOMA-IR, HDL-C, ALT, AST, TC, and lipopolysaccharide (LPS). These findings suggested that the mentioned genus may be beneficial to diabetic mice’s hypoglycemia and hypolipidemia. The up-regulation of peptide YY (PYY), glucagon-like peptide-1 (GLP-1), and insulin were remarkably reversed by LBP in diabetic mice. The real-time PCR (RT-PCR) analysis illustrated that LBP distinctly regulated the glucose metabolism of diabetic mice by activating the IRS/PI3K/Akt signal pathway. These results indicated that LBP effectively alleviated the hyperglycemia and hyperlipidemia of diabetic mice by modulating intestinal flora.

Introducing untargeted data-independent acquisition for metaproteomics of complex microbial samples

Mass spectrometry-based metaproteomics is a relatively new field of research that enables the characterization of the functionality of microbiota. Recently, we demonstrated the applicability of data-independent acquisition (DIA) mass spectrometry to the analysis of complex metaproteomic samples. This allowed us to circumvent many of the drawbacks of the previously used data-dependent acquisition (DDA) mass spectrometry, mainly the limited reproducibility when analyzing samples with complex microbial composition. However, the DDA-assisted DIA approach still required additional DDA data on the samples to assist the analysis. Here, we introduce, for the first time, an untargeted DIA metaproteomics tool that does not require any DDA data, but instead generates a pseudospectral library directly from the DIA data. This reduces the amount of required mass spectrometry data to a single DIA run per sample. The new DIA-only metaproteomics approach is implemented as a new open-source software package named glaDIAtor, including a modern web-based graphical user interface to facilitate wide use of the tool by the community.

Gut Microbial Dysbiosis and Cognitive Impairment in Bipolar Disorder: Current Evidence

Recent studies have reported that the gut microbiota influences mood and cognitive function through the gut-brain axis, which is involved in the pathophysiology of neurocognitive and mental disorders, including Parkinson’s disease, Alzheimer’s disease, and schizophrenia. These disorders have similar pathophysiology to that of cognitive dysfunction in bipolar disorder (BD), including neuroinflammation and dysregulation of various neurotransmitters (i.e., serotonin and dopamine). There is also emerging evidence of alterations in the gut microbial composition of patients with BD, suggesting that gut microbial dysbiosis contributes to disease progression and cognitive impairment in BD. Therefore, microbiota-centered treatment might be an effective adjuvant therapy for BD-related cognitive impairment. Given that studies focusing on connections between the gut microbiota and BD-related cognitive impairment are lagging behind those on other neurocognitive disorders, this review sought to explore the potential mechanisms of how gut microbial dysbiosis affects cognitive function in BD and identify potential microbiota-centered treatment.

Identification and genome characterization of novel parechovirus sequences from Hipposideros armiger in China

Background

Bats were identified as a natural reservoir of emerging and re-emerging infectious pathogens threatening human health and life.

Methods

This study collected 21 fecal samples of Hipposideros armiger in Mengla County of Xishuangbanna Prefecture Yunnan Province to combine one pool for viral metagenomic sequencing.

Results

Two nearly complete genomes of parechoviruses, BPeV11 and BPeV20, were sequenced. Genome analysis revealed that BPeV11 and BPeV20 follow a 3-3-4 genome layout: 5′ UTR-VP0-VP3-VP1-2A-2B-2C-3A-3B-3C-3D-3′ UTR. The prevalence of BPev11 and BPev20 by Nested-PCR showed that 1 of 21 fecal samples was positive. Based on amino acid identity comparison and phylogenetic analysis of P1, 2C, and 3D, BPeV11 and BPeV20 were closely related to but distinct from FPeVs.

Conclusion

It was probably proposed to be a novel species in the genus Parechovirus of the family Picornaviridae. The isolation of BPev11 and BPev20 from H. armiger in China is the first complete genome of parechovirus isolations from bat feces of the genus Hipposideros.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12985-022-01806-1.

Shared postulations between bipolar disorder and polycystic ovary syndrome pathologies

INTRODUCTION

Women with bipolar disorder (BD) present a high prevalence of polycystic ovary syndrome (PCOS) and other reproductive disorders even before diagnosis or treatment of the disease. Postulations on the potential molecular mechanisms of comorbid PCOS in women with BD remain limited to influence of medications and need further extension.

OBJECTIVES

This review focuses on evidence suggesting that common metabolic and immune disorders may play an important role in the development of BD and PCOS.

RESULTS

The literature covered in this review suggests that metabolic and immune disorders, including the dysfunction of the hypothalamic-pituitary-adrenal axis, chronic inflammatory state, gut microbial alterations, adipokine alterations and circadian rhythm disturbance, are observed in patients with BD and PCOS. Such disorders may be responsible for the increased prevalence of PCOS in the BD population and indicate a susceptibility gene overlap between the two diseases. Current evidence supports postulations of common metabolic and immune disorders as endophenotype in BD as well as in PCOS.

CONCLUSIONS

Metabolic and immune disorders may be responsible for the comorbid PCOS in the BD population. The identification of hallmark metabolic and immune features common to these two diseases will contribute to the clarification of the effect of BD on the reproductive endocrine function and development of symptomatic treatments targeting the biomarkers of the two diseases.

Optimizing therapeutic outcomes of immune checkpoint blockade by a microbial tryptophan metabolite

Background

Despite the great success, the therapeutic benefits of immune checkpoint inhibitors (ICIs) in cancer immunotherapy are limited by either various resistance mechanisms or ICI-associated toxic effects including gastrointestinal toxicity. Thus, novel therapeutic strategies that provide manageable side effects to existing ICIs would enhance and expand their therapeutic efficacy and application. Due to its proven role in cancer development and immune regulation, gut microbiome has gained increasing expectation as a potential armamentarium to optimize immunotherapy with ICI. However, much has to be learned to fully harness gut microbiome for clinical applicability. Here we have assessed whether microbial metabolites working at the interface between microbes and the host immune system may optimize ICI therapy.

Methods

To this purpose, we have tested indole-3-carboxaldehyde (3-IAld), a microbial tryptophan catabolite known to contribute to epithelial barrier function and immune homeostasis in the gut via the aryl hydrocarbon receptor (AhR), in different murine models of ICI-induced colitis. Epithelial barrier integrity, inflammation and changes in gut microbiome composition and function were analyzed. AhR, indoleamine 2,3-dioxygenase 1, interleukin (IL)-10 and IL-22 knockout mice were used to investigate the mechanism of 3-IAld activity. The function of the microbiome changes induced by 3-IAld was evaluated on fecal microbiome transplantation (FMT). Finally, murine tumor models were used to assess the effect of 3-IAld treatment on the antitumor activity of ICI.

Results

On administration to mice with ICI-induced colitis, 3-IAld protected mice from intestinal damage via a dual action on both the host and the microbes. Indeed, paralleling the activation of the host AhR/IL-22-dependent pathway, 3-IAld also affected the composition and function of the microbiota such that FMT from 3-IAld-treated mice protected against ICI-induced colitis with the contribution of butyrate-producing bacteria. Importantly, while preventing intestinal damage, 3-IAld did not impair the antitumor activity of ICI.

Conclusions

This study provides a proof-of-concept demonstration that moving past bacterial phylogeny and focusing on bacterial metabolome may lead to a new class of discrete molecules, and that working at the interface between microbes and the host immune system may optimize ICI therapy.

Effects of Multispecies Probiotic on Intestinal Microbiota and Mucosal Barrier Function of Neonatal Calves Infected With E. coli K99

Altered gut microbiota are implicated in inflammatory neonatal calf diarrhea caused by E. coli K99. Beneficial probiotics are used to modulate gut microbiota. However, factors that mediate host-microbe interactions remain unclear. We evaluated the effects of a combination of multispecies probiotics (MSP) on growth, intestinal epithelial development, intestinal immune function and microbiota of neonatal calves infected with E. coli K99. Twelve newborn calves were randomly assigned as follows: C (control, without MSP); D (E. coli O78:K99 + gentamycin); and P (E. coli O78:K99 + supplemental MSP). All groups were studied for 21 d. MSP supplementation significantly (i) changed fungal Chao1 and Shannon indices of the intestine compared with group D; (ii) reduced the relative abundance of Bacteroides and Actinobacteria, while increasing Bifidobacteria, Ascomycetes, and Saccharomyces, compared with groups C and D; (iii) improved duodenal and jejunal mucosal SIgA and total Short Chain Fatty Acids (SCFA) concentrations compared with group D; (iv) increased relative ZO-1 and occludin mRNA expression in jejunal mucosa compared with group D; and (v) enhanced intestinal energy metabolism and defense mechanisms of calves by reducing HSP90 expression in E. coli K99, thereby alleviating the inflammatory response and promoting recovery of mucosal function. Our research may provide direct theoretical support for future applications of MSP in ruminant production.

Metaproteomic Profile of the Colonic Luminal Microbiota From Patients With Colon Cancer

Recent studies have provided evidence of interactions among the gut microbiota (GM), local host immune cells, and intestinal tissues in colon carcinogenesis. However, little is known regarding the functions exerted by the GM in colon cancer (CC), particularly with respect to tumor clinical classification and lymphocyte infiltration. In addition, stool, usually employed as a proxy of the GM, cannot fully represent the original complexity of CC microenvironment. Here, we present a pilot study aimed at characterizing the metaproteome of CC-associated colonic luminal contents and identifying its possible associations with CC clinicopathological features. Colonic luminal contents were collected from 24 CC tissue specimens immediately after surgery. Samples were analyzed by shotgun metaproteomics. Almost 30,000 microbial peptides were quantified in the samples, enabling the achievement of the taxonomic and functional profile of the tumor-associated colonic luminal metaproteome. Upon sample aggregation based on tumor stage, grade, or tumor-infiltrating lymphocytes (TILs), peptide sets enabling discrimination of sample groups were identified through discriminant analysis (DA). As a result, Bifidobacterium and Bacteroides fragilis were significantly enriched in high-stage and high-grade CC, respectively. Among metabolic functions, formate-tetrahydrofolate ligase was significantly associated with high-stage CC. Finally, based on the results of this pilot study, we assessed the optimal sample size for differential metaproteomic studies analyzing colonic luminal contents. In conclusion, we provide a detailed picture of the microbial and host components of the colonic luminal proteome and propose promising associations between GM taxonomic/functional features and CC clinicopathological features. Future studies will be needed to verify the prognostic value of these data and to fully exploit the potential of metaproteomics in enhancing our knowledge concerning CC progression.

A systematic review of gut microbiota composition in observational studies of major depressive disorder, bipolar disorder and schizophrenia

The emerging understanding of gut microbiota as 'metabolic machinery' influencing many aspects of physiology has gained substantial attention in the field of psychiatry. This is largely due to the many overlapping pathophysiological mechanisms associated with both the potential functionality of the gut microbiota and the biological mechanisms thought to be underpinning mental disorders. In this systematic review, we synthesised the current literature investigating differences in gut microbiota composition in people with the major psychiatric disorders, major depressive disorder (MDD), bipolar disorder (BD) and schizophrenia (SZ), compared to 'healthy' controls. We also explored gut microbiota composition across disorders in an attempt to elucidate potential commonalities in the microbial signatures associated with these mental disorders. Following the PRISMA guidelines, databases were searched from inception through to December 2021. We identified 44 studies (including a total of 2510 psychiatric cases and 2407 controls) that met inclusion criteria, of which 24 investigated gut microbiota composition in MDD, seven investigated gut microbiota composition in BD, and 15 investigated gut microbiota composition in SZ. Our syntheses provide no strong evidence for a difference in the number or distribution (α-diversity) of bacteria in those with a mental disorder compared to controls. However, studies were relatively consistent in reporting differences in overall community composition (β-diversity) in people with and without mental disorders. Our syntheses also identified specific bacterial taxa commonly associated with mental disorders, including lower levels of bacterial genera that produce short-chain fatty acids (e.g. butyrate), higher levels of lactic acid-producing bacteria, and higher levels of bacteria associated with glutamate and GABA metabolism. We also observed substantial heterogeneity across studies with regards to methodologies and reporting. Further prospective and experimental research using new tools and robust guidelines hold promise for improving our understanding of the role of the gut microbiota in mental and brain health and the development of interventions based on modification of gut microbiota.

Metagenomic Analysis Reveals New Microbiota Related to Fiber Digestion in Pigs

Making full use of high fiber and low-cost crop coproducts is helpful to alleviate the situation of people and livestock competing for crops. Digestion of dietary fibers in pigs is mainly through microbial fermentation in the large intestine. To reveal microbiota related to fiber digestion in pigs, fecal samples have been collected from 274 healthy female Suhuai pigs at 160 days of age under the same feeding conditions and have measured apparent neutral detergent fiber (NDF) and acid detergent fiber (ADF) digestibility. Samples from Suhuai pigs with extreme high and low apparent NDF digestibility and extreme high and low apparent ADF digestibility were subjected to shotgun metagenomic sequencing. At the species level, 62 microbial species in H_NDF group and 54 microbial species in H_ADF group were related to high fiber digestibility. Among them, Lachnospiraceae bacterium 3-1 and Alistipes sp. CAG:514 may be new types of microorganisms associated with fiber digestion. In addition, we found that more abundant GH5 and GH48 family (contribute to cellulose degradation) genes, GH39 and GH53 family (contribute to hemicellulose degradation) genes in microorganisms may contribute to the higher apparent NDF digestibility of pigs, and more abundant GH3 and GH9 family (contribute to cellulose degradation) genes in microorganisms may contribute to the higher apparent ADF digestibility of pigs. The abundance of AA4 family (helps in lignin degradation) genes in H_NDF and H_ADF groups was significantly higher than that in L_NDF and L_ADF groups, respectively (P < 0.05). Three pathways in H_NDF group and four pathways in H_ADF group are important pathways associated with degradation of non-starch polysaccharides, and their relative abundance is significantly higher than that in L_NDF and L_ADF groups, respectively. Gut microbiota of Suhuai pigs with high apparent fiber digestibility had higher abundance of genes and microbiota related to fiber digestion and may have stronger fiber digestion potential compared with low apparent fiber digestibility group. This study revealed that the characteristics of gut microbiota and microbial gene functions of pigs with high fiber apparent digestibility, which provided a theoretical basis and reference for further understanding the impact of gut microbiota on fiber digestibility of pigs.

Multispecies probiotics alter fecal short-chain fatty acids and lactate levels in weaned pigs by modulating gut microbiota

Short-chain fatty acids (SCFAs) are metabolic products produced during the microbial fermentation of non-digestible fibers and play an important role in metabolic homeostasis and overall gut health. In this study, we investigated the effects of supplementation with multispecies probiotics (MSPs) containing Bacillus amyloliquefaciens, Limosilactobacillus reuteri, and Levilactobacillus brevis on the gut microbiota, and fecal SCFAs and lactate levels of weaned pigs. A total of 38 pigs weaned at 4 weeks of age were fed either a basal diet or a diet supplemented with MSPs for 6 weeks. MSP administration significantly increased the fecal concentrations of lactate (2.3-fold; p < 0.01), acetate (1.8-fold; p < 0.05), and formate (1.4-fold; p < 0.05). Moreover, MSP supplementation altered the gut microbiota of the pigs by significantly increasing the population of potentially beneficial bacteria such as Olsenella, Catonella, Catenibacterium, Acidaminococcus, and Ruminococcaceae. MSP supplementation also decreased the abundance of pathogenic bacteria such as Escherichia and Chlamydia. The modulation of the gut microbiota was observed to be strongly correlated with the changes in fecal SCFAs and lactate levels. Furthermore, we found changes in the functional pathways present within the gut, which supports our findings that MSP modulates the gut microbiota and SCFAs levels in pigs. The results support the potential use of MSPs to improve the gut health of animals by modulating SCFAs production.

Cholesterol-lowering activity of protocatechuic acid is mediated by increasing the excretion of bile acids and modulating gut microbiota and producing short-chain fatty acids

The present study aimed to investigate the effects of protocatechuic acid (PCA) on plasma lipid profiles and associated mechanisms with a focus on reshaping gut microbiota. Twenty-four male hamsters were randomly divided into three groups receiving a high-cholesterol diet (HCD) and two HCD diets containing 0.5% (PL) and 1% (PH) PCA, respectively. Feeding PL and PH diets for six weeks significantly reduced plasma total cholesterol by 18% and 24%, respectively. PL and PH diets also significantly lowered plasma non-HDL cholesterol by 37% and 44%, respectively. This was accompanied by an increase in fecal short-chain fatty acids (SCFAs) and fecal bile acids with up-regulation on gene of cholesterol 7α-hydroxylase and down-regulation of 3-hydroxy-3-methylglutaryl-CoA reductase in the liver. Dietary PCA supplementation decreased hepatic lipid accumulation, whereas it increased fecal excretion of lipids. The 16S rRNA analysis found that dietary PCA significantly reduced the ratio of Firmicutes to Bacteroidetes and increased the relative abundance of Bacteroidales S24-7, whereas it reduced the abundance of Lactobacillaceae. It was concluded that dietary PCA favorably modulated plasma lipid profiles and prevented the accumulation of hepatic cholesterol and lipid disposition. Such effect was mediated at least partially by increasing gut production of SCFAs and fecal excretion of bile acids via modulating the gut microbiome.

Integrated Metagenomic and Metaproteomic Analyses Unravel Ammonia Toxicity to Active Methanogens and Syntrophs, Enzyme Synthesis, and Key Enzymes in Anaerobic Digestion

During anaerobic digestion, the active microbiome synthesizes enzymes by transcription and translation, and then enzymes catalyze multistep bioconversions of substrates before methane being produced. However, little information is available on how ammonia affects truly active microbes containing the expressed enzymes, enzyme synthesis, and key enzymes. In this study, an integrated metagenomic and metaproteomic investigation showed that ammonia suppressed not only the obligate acetotrophic methanogens but also the syntrophic propionate and butyrate oxidation taxa and their assistant bacteria (genus Desulfovibrio), which declined the biotransformations of propionate and butyrate → acetate → methane. Although the total population of the hydrolyzing and acidifying bacteria was not affected by ammonia, the bacteria with ammonia resistance increased. Our study also revealed that ammonia restrained the enzyme synthesis process by inhibiting the RNA polymerase (subunits A' and D) during transcription and the ribosome (large (L3, L12, L13, L22, and L25) and small (S3, S3Ae, and S7) ribosomal subunits) and aminoacyl-tRNA synthesis (aspartate-tRNA synthetase) in translation. Further investigation suggested that methylmalonyl-CoA mutase, acetyl-CoA C-acetyltransferase, and CH₃-CoM reductase, which regulate propionate and butyrate oxidation and acetoclastic methanation, were significantly downregulated by ammonia. This study provides intrinsic insights into the fundamental mechanisms of how ammonia inhibits anaerobic digestion.

Qualitative and quantitative proteomic and metaproteomic analyses of healthy human urine sediment

PURPOSE

The healthy human urine sediment proteome and metaproteome are investigated, to shed light on the variations of urine sediment proteins and metaproteins associated with sex and age.

EXPERIMENTAL DESIGN

Urine sediment samples are collected from 19 healthy subjects. Protein identification and quantification are performed by liquid chromatography coupled high-resolution mass spectrometry.

RESULTS

A total of 2736 human proteins were identified, which were primarily associated with inflammatory response and energy metabolism. For the metaproteome, 65 genera were identified that were primarily involved in translation and carbohydrate metabolic processes. The median biological coefficient variation of the proteome/metaproteome of human urine sediment was 0.5/0.72, similar to the proteome of human urine supernatant. In addition, sex and age were observed to affect the proteome and metaproteome of healthy human urine sediment.

CONCLUSION AND CLINICAL RELEVANCE

The healthy human urine sediment were characterized, indicating that urine sediment might represent an alternative resource for disease research in addition to urine supernatant, but the influence of sex and age must be considered in the study design process.