Metaproteomic and 16S rRNA Gene Sequencing Analysis of the Infant Fecal Microbiome

Investigation of the human-gut-kidney axis by fecal proteomics, highlights molecular mechanisms affected in CKD

Objective

The interplay of gut microbiota with the kidney system in chronic kidney disease (CKD), is characterized by increased concentrations of uric acid in the gut, which in turn, may increase bacterial uricase activity and may lead to the generation of uremic toxins. Nevertheless, knowledge on these underlying bidirectional molecular mechanisms is still limited.

Methods

In this exploratory study, proteomic analysis was performed on fecal samples, targeting to investigate this largely unexplored biological material as a source of information reflecting the gut-kidney axis. Specifically, fecal suspension samples from patients with CKD1 (n = 12) and CKD4 (n = 17) were analysed by LC-MS/MS, using both the Human and Bacterial UniProt RefSeq reviewed databases.

Results

This fecal proteomic analysis collectively identified 701 human and 1011 bacterial proteins of high confidence. Differential expression analysis (CKD4/CKD1) revealed significant changes in human proteins (n = 8, including proteins such as galectin-3-binding protein and prolactin-inducible protein), that were found to be associated with inflammation and CKD. The differential protein expression of pancreatic alpha-amylase further suggested plausible reduced saccharolytic fermentation in CKD4/CKD1. Significant changes in bacterial proteins (n = 9, such as glyceraldehyde-3-phosphate dehydrogenase and enolase), participating in various carbohydrate and metabolic pathways important for the synthesis of butyrate, in turn suggested differential butyrate synthesis in CKD4/CKD1. Further, targeted quantification of fecal pancreatic alpha-amylase and butyrate in the same fecal suspension samples, supported these hypotheses.

Conclusion

Collectively, this exploratory fecal proteomic analysis highlighted changes in human and bacterial proteins reflecting inflammation and reduced saccharolytic fermentation in CKD4/CKD1, plausibly affecting the butyrate synthesis pathways in advanced stage kidney disease. Integrative multi-omics validation is planned.

Application of a maximal-clique based community detection algorithm to gut microbiome data reveals driver microbes during influenza A virus infection

Influenza A Virus (IAV) infection followed by bacterial pneumonia often leads to hospitalization and death in individuals from high risk groups. Following infection, IAV triggers the process of viral RNA replication which in turn disrupts healthy gut microbial community, while the gut microbiota plays an instrumental role in protecting the host by evolving colonization resistance. Although the underlying mechanisms of IAV infection have been unraveled, the underlying complex mechanisms evolved by gut microbiota in order to induce host immune response following IAV infection remain evasive. In this work, we developed a novel Maximal-Clique based Community Detection algorithm for Weighted undirected Networks (MCCD-WN) and compared its performance with other existing algorithms using three sets of benchmark networks. Moreover, we applied our algorithm to gut microbiome data derived from fecal samples of both healthy and IAV-infected pigs over a sequence of time-points. The results we obtained from the real-life IAV dataset unveil the role of the microbial families Ruminococcaceae, Lachnospiraceae, Spirochaetaceae and Prevotellaceae in the gut microbiome of the IAV-infected cohort. Furthermore, the additional integration of metaproteomic data enabled not only the identification of microbial biomarkers, but also the elucidation of their functional roles in protecting the host following IAV infection. Our network analysis reveals a fast recovery of the infected cohort after the second IAV infection and provides insights into crucial roles of Desulfovibrionaceae and Lactobacillaceae families in combating Influenza A Virus infection. Source code of the community detection algorithm can be downloaded from https://github.com/AniBhar84/MCCD-WN.

Using integrated meta-omics to appreciate the role of the gut microbiota in epilepsy

The way the human microbiota may modulate neurological pathologies is a fascinating matter of research. Epilepsy is a common neurological disorder, which has been largely investigated in correlation with microbiota health and function. However, the mechanisms that regulate this apparent connection are scarcely defined, and extensive effort has been conducted to understand the role of microbiota in preventing and reducing epileptic seizures. Intestinal bacteria seem to modulate the seizure frequency mainly by releasing neurotransmitters and inflammatory mediators. In order to elucidate the complex microbial contribution to epilepsy pathophysiology, integrated meta-omics could be pivotal. In fact, the combination of two or more meta-omics approaches allows a multifactorial study of microbial activity within the frame of disease or drug treatments. In this review, we provide information depicting and supporting the use of multi-omics to study the microbiota-epilepsy connection. We described different meta-omics analyses (metagenomics, metatranscriptomics, metaproteomics and metabolomics), focusing on current technical challenges in stool collection procedures, sample extraction methods and data processing. We further discussed the current advantages and limitations of using the integrative approach of multi-omics in epilepsy investigations.

Inferring early-life host and microbiome functions by mass spectrometry-based metaproteomics and metabolomics

Humans have a long-standing coexistence with microorganisms. In particular, the microbial community that populates the human gastrointestinal tract has emerged as a critical player in governing human health and disease. DNA and RNA sequencing techniques that map taxonomical composition and genomic potential of the gut community have become invaluable for microbiome research. However, deriving a biochemical understanding of how activities of the gut microbiome shape host development and physiology requires an expanded experimental design that goes beyond these approaches. In this review, we explore advances in high-throughput techniques based on liquid chromatography-mass spectrometry. These omics methods for the identification of proteins and metabolites have enabled direct characterisation of gut microbiome functions and the crosstalk with the host. We discuss current metaproteomics and metabolomics workflows for producing functional profiles, the existing methodological challenges and limitations, and recent studies utilising these techniques with a special focus on early life gut microbiome.

Milk Formula Diet Alters Bacterial and Host Protein Profile in Comparison to Human Milk Diet in Neonatal Piglet Model

The metaproteome profiling of cecal contents collected from neonatal piglets fed pasteurized human milk (HM) or a dairy-based infant formula (MF) from postnatal day (PND) 2 to 21 were assessed. At PND 21, a subset of piglets from each group (n = 11/group) were euthanized, and cecal contents were collected for further metaproteome analysis. Cecal microbiota composition showed predominantly more Firmicutes phyla and Lachnospiraceae family in the lumen of cecum of HM-fed piglets in comparison to the MF-fed group. Ruminococcus gnavus was the most abundant species from the Firmicutes phyla in the cecal contents of the HM-fed piglets at 21 days of age. A greater number of expressed proteins were identified in the cecal contents of the HM-fed piglets relative to the MF-fed piglets. Greater abundances of proteins potentially expressed by Bacteroides spp. such as glycoside enzymes were noted in the cecal lumen of HM-fed piglets relative to the MF. Additionally, lyases associated with Lachnospiraceae family were abundant in the cecum of the HM group relative to the MF group. Overall, our findings indicate that neonatal diet impacts the gut bacterial taxa and microbial proteins prior to weaning. The metaproteomics data were deposited into PRIDE, PXD025432 and 10.6019/PXD025432.

Lead Drives Complex Dynamics of a Conjugative Plasmid in a Bacterial Community

Plasmids carrying metal resistance genes (MRGs) have been suggested to be key ecological players in the adaptation of metal-impacted microbial communities, making them promising drivers of bio-remediation processes. However, the impact of metals on plasmid-mediated spread of MRGs through selection, plasmid loss, and transfer is far from being fully understood. In the present study, we used two-member bacterial communities to test the impact of lead on the dispersal of the IncP plasmid pKJK5 from a Pseudomonas putida KT2440 plasmid donor and two distinct recipients, Variovorax paradoxus B4 or Delftia acidovorans SPH-1 after 4 and 10 days of mating. Two versions of the plasmid were used, carrying or not carrying the lead resistance pbrTRABCD operon, to assess the importance of fitness benefit and conjugative potential for the dispersal of the plasmid. The spread dynamics of metal resistance conveyed by the conjugative plasmid were dependent on the recipient and the lead concentration: For V. paradoxus, the pbr operon did not facilitate neither lead resistance nor variation in plasmid spread. The growth gain brought by the pbr operon to D. acidovorans SPH-1 and P. putida KT2440 at 1 mM Pb enhanced the spread of the plasmid. At 1.5 mM Pb after 4 days, the proteomics results revealed an oxidative stress response and an increased abundance of pKJK5-encoded conjugation and partitioning proteins, which most likely increased the transfer of the control plasmid to D. acidovorans SPH-1 and ensured plasmid maintenance. As a consequence, we observed an increased spread of pKJK5-gfp. Conversely, the pbr operon reduced the oxidative stress response and impeded the rise of conjugation- and partitioning-associated proteins, which slowed down the spread of the pbr carrying plasmid. Ultimately, when a fitness gain was recorded in the recipient strain, the spread of MRG-carrying plasmids was facilitated through positive selection at an intermediate metal concentration, while a high lead concentration induced oxidative stress with positive impacts on proteins encoding plasmid conjugation and partitioning.

Insects' potential: Understanding the functional role of their gut microbiome

The study of insect-associated microbial communities is a field of great importance in agriculture, principally because of the role insects play as pests. In addition, there is a recent focus on the potential of the insect gut microbiome in areas such as biotechnology, given some microorganisms produce molecules with biotechnological and industrial applications, and also in biomedicine, since some bacteria and fungi are a reservoir of antibiotic resistance genes (ARGs). To date, most studies aiming to characterize the role of the gut microbiome of insects have been based on high-throughput sequencing of the 16S rRNA gene and/or metagenomics. However, recently functional approaches such as metatranscriptomics, metaproteomics and metabolomics have also been employed. Besides providing knowledge about the taxonomic distribution of microbial populations, these techniques also reveal their functional and metabolic capabilities. This information is essential to gain a better understanding of the role played by microbes comprising the microbial communities in their hosts, as well as to indicate their possible exploitation. This review provides an overview of how far we have come in characterizing insect gut functionality through omics, as well as the challenges and future perspectives in this field.

Variations in fecal microbial profiles of acute exacerbations and stable chronic obstructive pulmonary disease

AIM

Alterations in the respiratory and digestive tract microbiomes influence the occurrence and progression of chronic obstructive pulmonary disease (COPD). Here, we aimed to identify fecal microbiome profiles during COPD development.

METHODS

Fecal samples were collected from 29 COPD patients with acute exacerbation (AECOPD), 29 stable COPD patients, and 22 normal subjects (NS). The fecal microbial profiles were obtained using 16S rRNA gene sequencing.

KEY FINDINGS

The diversity and richness were lower and fewer variations in the taxonomic composition of fecal microbiota were observed in AECOPD patients than in stable COPD and NS. The relative abundances of Firmicutes and Actinobacteria were decreased, while those of Bacteroidetes and Proteobacteria were increased in AECOPD compared to COPD and NS. Among the top ten genera, the proportions of Lachnoclostridium and Parabacteroides significantly increased in AECOPD, whereas those of other genera decreased. Discriminative bacteria, such as p_Bacteroidetes, c_Bacteroidia, o_Bacteroidales, Lactobacillales, and Proteobacteria, were identified in AECOPD compared to stable COPD and NS. The weighted gene co-expression networks showed that Firmicutes and Actinobacteria were the main hub bacterial taxa related with lung function (FEV1% and FEV1/FVC%) and inflammatory indices (TNF-α, IL-6, IL-8, PCT, and CRP).

SIGNIFICANCE

These findings emphasized the changes in the abundance and composition of the fecal microbiome in stable COPD and AECOPD. Variations in fecal microbiota may be associated with COPD progression.

Analysis of the infant gut microbiome reveals metabolic functional roles associated with healthy infants and infants with atopic dermatitis using metaproteomics

The infant gut microbiome consists of a complex and diverse microbial community. Comprehensive taxonomic and metabolic functional knowledge about microbial communities supports medical and biological applications, such as fecal diagnostics. Among the omics approaches available for the investigation of microbial communities, metaproteomics-based analysis is a very powerful approach; under this method, the activity of microbial communities is explored by investigating protein expression within a sample. Through use of metaproteomics, this study aimed to investigate the microbial community composition of the infant gut to identify different key proteins playing metabolic functional roles in the microbiome of healthy infants and infants with atopic dermatitis in a Thai population-based birth cohort. Here, 18 fecal samples were analyzed by liquid chromatography-tandem mass spectrometry to conduct taxonomic, functional, and pathway-based protein annotation. Accordingly, 49,973 annotated proteins out of 68,232 total proteins were investigated in gut microbiome samples and compared between the healthy and atopic dermatitis groups. Through differentially expressed proteins (DEPs) analysis, 130 significant DEPs were identified between the healthy and atopic dermatitis groups. Among these DEPs, eight significant proteins were uniquely expressed in the atopic dermatitis group. For instance, triosephosphate isomerase (TPI) in Bifidobacteriaceae in the genus Alloscardovia and demethylmenaquinone methyltransferase (DMM) in Bacteroides were shown to potentially play metabolic functional roles related to disease. PPI network analysis revealed seven reporter proteins showing metabolic alterations between the healthy and disease groups associated with the biosynthesis of ubiquinone and other quinones as well as the energy supply. This study serves as a scaffold for microbial community-wide metabolic functional studies of the infant gut microbiome in relation to allergic disease.

Microbiota, Food, and Health

The effects of specific foods, such as products containing probiotics or prebiotics, on human health and the role of intestinal microbiota in this interaction have been a subject of scientific interest for several decades [...].