Microbiome research reports最新文献

Aim: This study aims to evaluate the impact of experimental workflow on fecal metaproteomic observations, including the recovery of small and antimicrobial proteins often overlooked in metaproteomic studies. The overarching goal is to provide guidance for optimized metaproteomic experimental design, considering the emerging significance of the gut microbiome in human health, disease, and therapeutic interventions. Methods: Mouse feces were utilized as the experimental model. Fecal sample pre-processing methods (differential centrifugation and non-differential centrifugation), protein digestion techniques (in-solution and filter-aided), data acquisition modes (data-dependent and data-independent, or DDA and DIA) when combined with parallel accumulation-serial fragmentation (PASEF), and different bioinformatic workflows were assessed. Results: We showed that, in DIA-PASEF metaproteomics, the library-free search using protein sequence database generated from DDA-PASEF data achieved better identifications than using the generated spectral library. Compared to DDA, DIA-PASEF identified more microbial peptides, quantified more proteins with fewer missing values, and recovered more small antimicrobial proteins. We did not observe any obvious impacts of protein digestion methods on both taxonomic and functional profiles. However, differential centrifugation decreased the recovery of small and antimicrobial proteins, biased the taxonomic observation with a marked overestimation of Muribaculum species, and altered the measured functional compositions of metaproteome. Conclusion: This study underscores the critical impact of experimental choices on metaproteomic outcomes and sheds light on the potential biases introduced at different stages of the workflow. The comprehensive methodological comparisons serve as a valuable guide for researchers aiming to enhance the accuracy and completeness of metaproteomic analyses.

Aim: Microbial colonization of the neonatal gut is pivotal in priming the infant's immune system. Human milk (HM) is the best nutrition for infants and supports the development of the microbiota due to prebiotic compounds and probiotic microorganisms. When exclusive breastfeeding is not possible, infant formula (IF) with probiotics is a strategy to support the infant's microbiome development. However, knowledge about the effects of the infant gut microbiota and different compounds in IF on individual probiotic strains is limited, as strain-level detection in a complex ecosystem is challenging. The aim of the present study was to show the effects of IF with different protein forms on the metabolic activity of two probiotic strains isolated from HM in a complex ecosystem. Methods: By using an ex-vivo infant gut model containing infant donor-microbiota, the effects of IF with either intact or extensively hydrolyzed protein on the metabolic activity of the donor microbiota, as well as two probiotic strains [Limosilactobacillus fermentum (L. fermentum) CECT 5716 (Lf) and Bifidobacterium breve (B. breve) DSM 32583 (Bb)], were analyzed. A new bioinformatic pipeline combined with a specific infant microbiome database was used to explore shotgun metagenome datasets (1200 Megabases) for taxonomic identification and strain-level tracking. Results: Both protein forms (i.e., intact or extensively hydrolyzed protein) in IF supported infant gut microbial metabolic activity equally, as evidenced by similar levels of short-chain fatty acids (SCFAs). Interestingly, gut microbial metabolic activity was found to be differently activated in a strain-dependent manner. Taxonomic profiling of the microbiome at the strain level enabled monitoring of the prevalence and abundance of both probiotic strains, even in a complex ecosystem. Conclusion: Food matrix and host microbiota interactions should be considered when evaluating strain-specific probiotic effects in the future.

The human gut commensal Akkermansia muciniphila is the most studied bacterial species within the Verrucomicrobiota phylum. It has been proposed as a beneficial next-generation probiotic for cardiometabolic and immune health. Efforts from various research groups have resulted in the recent discovery of new species and/or phylotypes of the genus Akkermansia. This highlighted the genetic and phenotypic diversity among the Akkermansia isolates, providing an opportunity to identify novel mechanisms pertaining to health benefits. Genetic diversity between strains warrants detailed investigation to determine beneficial Akkermansia strains. Akkermansia massiliensis sp. nov. has emerged as the second most prevalent Akkermansia species in the human gut, with unique properties and potential relevance for human health. In addition, indications of the co-existence of more than one Akkermansia phylotype or species in a subject are intriguing. These new discoveries pave the way for additional developments of effective and targeted Akkermansia species-based interventions to provide health benefits.

Background and Aim: Over the past years, the gut microbiota and its correlation to health and disease has been studied extensively. In terms of beneficial microbes, an increased interest in Akkermansia muciniphila (A. muciniphila) has been observed since its discovery. Direct evidence for the role of A. muciniphila in host health has been provided in both mice and human studies. However, for human interventions with A. muciniphila cells, industrial-scale fermentations are needed, and hence, the used cultivation media should be free of animal-derived components, food-grade, non-allergenic and allow for efficient growth to high densities to provide cost-effective production platforms. In this study, we assessed the growth and performance of A. muciniphila in batch bioreactors using newly developed plant-based media. Methods: The bioreactors were supplemented with varying carbon sources, including different ratios of N-acetylglucosamine (GlcNAc) and glucose. We monitored the growth of A. muciniphila in the plant-based medium using optical density (OD600) measurements and microscopy. In addition, we used a combination of biochemical analysis as well as transcriptional and proteomics analysis to gain detailed insight into the physiology. Results: Comparisons between growth on these media and that on mucin revealed differences at both transcriptome and proteome levels, including differences in the expression of glycosyltransferases, signaling proteins, and stress response. Furthermore, elongated cells and higher OD600 values were observed using the plant-based media as compared to cultivation media containing mucin. Conclusion: These differences do not hamper growth, and therefore, our data suggest that the food-grade medium composition described here could be used to produce A. muciniphila with high yields for therapeutic purposes.

Aim: Lactic acid bacteria are among the most important bacteria in the intestinal flora and often have beneficial effects on the host. It is known that the bacteria that compose the intestinal flora are influenced by the feeding habits of host animals, but there was a lack of knowledge about lactic acid bacteria. Therefore, also considering the use of select strains as probiotics, this study investigated the relationship between the feeding habits of zoo animals and intestinal Lactobacillaceae species. Methods: Lactic acid bacteria belonging to the family Lactobacillaceae were isolated and identified from the feces of 20 zoo animal species (5 carnivores, 4 herbivores, 7 piscivores, and 4 omnivores). Isolates were identified by the homology of the 16S rRNA gene sequence. In addition, the fecal flora of host animals was evaluated by the 16S rRNA gene amplicon sequencing. Results: The types of Lactobacillaceae species were shown to vary depending on the feeding habits of host animals. Ligilactobacillus salivarius (L. salivarius) and Ligilactobacillus saerimneri (L. saerimneri) were isolated from the feces of carnivores. Whereas Ligilactobacillus equi (L. equi), Limosilactobacillus gorillae, Ligilactobacillus hayakitensis and L. salivarius were isolated from the feces of herbivores. These Lactobacillaceae species were not found in the feces of piscivores. Instead, Enterococcus were frequently found in piscivores. The fecal flora also differed according to the feeding habits of host animals; at the phylum level, Bacillota was predominant in all animals; on the other hand, herbivores tended to have a higher proportion of Bacteroidota than carnivores, and piscivores tended to have a higher proportion of Proteobacteria. Conclusion: Lactic acid bacteria differ among animal species in a manner dependent on the hosts' feeding habits.

Aim: Metabolic interactions within a microbial community play a key role in determining the structure, function, and composition of the community. However, due to the complexity and intractability of natural microbiomes, limited knowledge is available on interspecies interactions within a community. In this work, using a binary synthetic microbiome, a methanotroph-photoautotroph (M-P) coculture, as the model system, we examined different genome-scale metabolic modeling (GEM) approaches to gain a better understanding of the metabolic interactions within the coculture, how they contribute to the enhanced growth observed in the coculture, and how they evolve over time. Methods: Using batch growth data of the model M-P coculture, we compared three GEM approaches for microbial communities. Two of the methods are existing approaches: SteadyCom, a steady state GEM, and dynamic flux balance analysis (DFBA) Lab, a dynamic GEM. We also proposed an improved dynamic GEM approach, DynamiCom, for the M-P coculture. Results: SteadyCom can predict the metabolic interactions within the coculture but not their dynamic evolutions; DFBA Lab can predict the dynamics of the coculture but cannot identify interspecies interactions. DynamiCom was able to identify the cross-fed metabolite within the coculture, as well as predict the evolution of the interspecies interactions over time. Conclusion: A new dynamic GEM approach, DynamiCom, was developed for a model M-P coculture. Constrained by the predictions from a validated kinetic model, DynamiCom consistently predicted the top metabolites being exchanged in the M-P coculture, as well as the establishment of the mutualistic N-exchange between the methanotroph and cyanobacteria. The interspecies interactions and their dynamic evolution predicted by DynamiCom are supported by ample evidence in the literature on methanotroph, cyanobacteria, and other cyanobacteria-heterotroph cocultures.