Metaproteomics as a tool for studying the protein landscape of human-gut bacterial species

Stamboulian, Moses; Canderan, Jamie; Ye, Yuzhen

doi:10.1371/journal.pcbi.1009397

Cited by 11 publications

(7 citation statements)

References 57 publications

(55 reference statements)

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“…To overcome these boundaries, mass spectrometry-based proteomics applied to the study of hundreds of microbial organisms (termed, metaproteomics ( Rodriguez-Valera, 2004 ; Wilmes and Bond, 2004 )) has emerged as an attractive alternative. Metaproteomics has the potential to understand complex host-microbiome interactions as it enables the analysis of entire sets of proteins, providing direct insights into the identity and functionality of microorganisms present in an ecosystem ( Stamboulian et al, 2022 ). However, proteomics acquisition methods classically used in metaproteomics have reached their theoretical profiling limits ( Duan et al, 2022 ).…”

Section: Introductionmentioning

confidence: 99%

Increasing taxonomic and functional characterization of host-microbiome interactions by DIA-PASEF metaproteomics

Gómez-Varela,

Xian,

Grundtner

et al. 2023

Front. Microbiol.

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IntroductionMetaproteomics is a rapidly advancing field that offers unique insights into the taxonomic composition and the functional activity of microbial communities, and their effects on host physiology. Classically, data-dependent acquisition (DDA) mass spectrometry (MS) has been applied for peptide identification and quantification in metaproteomics. However, DDA-MS exhibits well-known limitations in terms of depth, sensitivity, and reproducibility. Consequently, methodological improvements are required to better characterize the protein landscape of microbiomes and their interactions with the host.MethodsWe present an optimized proteomic workflow that utilizes the information captured by Parallel Accumulation-Serial Fragmentation (PASEF) MS for comprehensive metaproteomic studies in complex fecal samples of mice.Results and discussionWe show that implementing PASEF using a DDA acquisition scheme (DDA-PASEF) increased peptide quantification up to 5 times and reached higher accuracy and reproducibility compared to previously published classical DDA and data-independent acquisition (DIA) methods. Furthermore, we demonstrate that the combination of DIA, PASEF, and neuronal-network-based data analysis, was superior to DDA-PASEF in all mentioned parameters. Importantly, DIA-PASEF expanded the dynamic range towards low-abundant proteins and it doubled the quantification of proteins with unknown or uncharacterized functions. Compared to previous classical DDA metaproteomic studies, DIA-PASEF resulted in the quantification of up to 4 times more taxonomic units using 16 times less injected peptides and 4 times shorter chromatography gradients. Moreover, 131 additional functional pathways distributed across more and even uniquely identified taxa were profiled as revealed by a peptide-centric taxonomic-functional analysis. We tested our workflow on a validated preclinical mouse model of neuropathic pain to assess longitudinal changes in host-gut microbiome interactions associated with pain - an unexplored topic for metaproteomics. We uncovered the significant enrichment of two bacterial classes upon pain, and, in addition, the upregulation of metabolic activities previously linked to chronic pain as well as various hitherto unknown ones. Furthermore, our data revealed pain-associated dynamics of proteome complexes implicated in the crosstalk between the host immune system and the gut microbiome. In conclusion, the DIA-PASEF metaproteomic workflow presented here provides a stepping stone towards a deeper understanding of microbial ecosystems across the breadth of biomedical and biotechnological fields.

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Section: Introductionmentioning

confidence: 99%

Increasing taxonomic and functional characterization of host-microbiome interactions by DIA-PASEF metaproteomics

Gómez-Varela,

Xian,

Grundtner

et al. 2023

Front. Microbiol.

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“…Fecal metaproteomic, as an emerging multi-omics technology, is a powerful tool for identifying previously unknown microbial communities and understanding the function of the gut microbiota [ 42 , 43 ]. A recent fecal metaproteomic report from Germany described negative associations between transcriptional regulatory protein RprY and human IgA from Bacillus fragilis and IBD.…”

Section: Discussionmentioning

confidence: 99%

Integrating the serum proteomic and fecal metaproteomic to analyze the impacts of overweight/obesity on IBD: a pilot investigation

et al. 2023

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Background Inflammatory bowel disease (IBD) encompasses a group of chronic relapsing disorders which include ulcerative colitis (UC) and Crohn’s disease (CD). The incidences of IBD and overweight/obesity are increasing in parallel. Here, we investigated alterations in proteomic in serum and metaproteomic in feces of IBD patients with overweight/obesity and aimed to explore the effect of overweight/ obesity on IBD and the underlying mechanism. Methods This prospective observational study (n = 64) comprised 26 health control subjects (HC, 13 with overweight/obesity) and 38 IBD patients (19 with overweight/obesity) at a tertiary hospital. Overweight/obesity was evaluated by body mass index (BMI) and defined as a BMI greater than 24 kg/m2. The comprehensive serum proteomic and fecal metaproteomic analyses were conducted by ultra-performance liquid chromatography-Orbitrap Exploris 480 mass spectrometry. Results UC and CD presented similar serum molecular profiles but distinct gut microbiota. UC and CD serum exhibited higher levels of cytoskeleton organization- associated and inflammatory response-related proteins than the HC serum. Compared the serum proteome of UC and CD without overweight/obesity, inflammatory response-associated proteins were dramatically decreased in UC and CD with overweight/obesity. Fecal metaproteome identified 66 species in the feces. Among them, Parasutterella excrementihominis was increased in CD compared with that in HC. UC group had a significant enrichment of Moniliophthora roreri, but had dramatically decreased abundances of Alistipes indistinctus, Clostridium methylpentosum, Bacteroides vulgatus, and Schizochytrium aggregatum. In addition, overweight/obesity could improve the microbial diversity of UC. Specifically, the UC patients with overweight/obesity had increased abundance of some probiotics in contrast to those without overweight/obesity, including Parabacteroides distasonis, Alistipes indistincus, and Ruminococcus bromii. Conclusion This study provided high-quality multi-omics data of IBD serum and fecal samples, which enabled deciphering the molecular bases of clinical phenotypes of IBD, revealing the impacts of microbiota on IBD, and emphasizing the important role of overweight/obesity in IBD.

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“…P. vulgatus is one of the commonly found bacterial species in human microbiome. In previous work, we showed that P. vulgatus is one of the generalists that are found in gut microbiomes of healthy individuals and individuals with diseases using metaproteomics datasets ( Stamboulian et al., 2022 ). This served as motivation to include P. vulgatus in our current study.…”

Section: Methodsmentioning

confidence: 99%

Revealing bacteria-phage interactions in human microbiome through the CRISPR-Cas immune systems

Monshizadeh

Zomorodi

Mortensen

et al. 2022

Front. Cell. Infect. Microbiol.

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The human gut microbiome is composed of a diverse consortium of microorganisms. Relatively little is known about the diversity of the bacteriophage population and their interactions with microbial organisms in the human microbiome. Due to the persistent rivalry between microbial organisms (hosts) and phages (invaders), genetic traces of phages are found in the hosts’ CRISPR-Cas adaptive immune system. Mobile genetic elements (MGEs) found in bacteria include genetic material from phage and plasmids, often resultant from invasion events. We developed a computational pipeline (BacMGEnet), which can be used for inference and exploratory analysis of putative interactions between microbial organisms and MGEs (phages and plasmids) and their interaction network. Given a collection of genomes as the input, BacMGEnet utilizes computational tools we have previously developed to characterize CRISPR-Cas systems in the genomes, which are then used to identify putative invaders from publicly available collections of phage/prophage sequences. In addition, BacMGEnet uses a greedy algorithm to summarize identified putative interactions to produce a bacteria-MGE network in a standard network format. Inferred networks can be utilized to assist further examination of the putative interactions and for discovery of interaction patterns. Here we apply the BacMGEnet pipeline to a few collections of genomic/metagenomic datasets to demonstrate its utilities. BacMGEnet revealed a complex interaction network of the Phocaeicola vulgatus pangenome with its phage invaders, and the modularity analysis of the resulted network suggested differential activities of the different P. vulgatus’ CRISPR-Cas systems (Type I-C and Type II-C) against some phages. Analysis of the phage-bacteria interaction network of human gut microbiome revealed a mixture of phages with a broad host range (resulting in large modules with many bacteria and phages), and phages with narrow host range. We also showed that BacMGEnet can be used to infer phages that invade bacteria and their interactions in wound microbiome. We anticipate that BacMGEnet will become an important tool for studying the interactions between bacteria and their invaders for microbiome research.

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Metaproteomics as a tool for studying the protein landscape of human-gut bacterial species

Cited by 11 publications

References 57 publications

Increasing taxonomic and functional characterization of host-microbiome interactions by DIA-PASEF metaproteomics

Increasing taxonomic and functional characterization of host-microbiome interactions by DIA-PASEF metaproteomics

Integrating the serum proteomic and fecal metaproteomic to analyze the impacts of overweight/obesity on IBD: a pilot investigation

Revealing bacteria-phage interactions in human microbiome through the CRISPR-Cas immune systems

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