Metaproteomic assessment of gut microbial and host functional perturbations in Helicobacter pylori-infected patients subjected to an antimicrobial protocol

The dawn of the revolution that will allow us to precisely describe how microbiomes function

The community of microorganisms inhabiting a specific environment, such as the human gut - including bacteria, fungi, archaea, viruses, protozoa, and others - is known as the microbiota. A holobiont, in turn, refers to an integrated ecological unit where microbial communities function and interact with their host, thus is a more integrative concept. To understand the processes involved, the diversity of microorganisms present must be identified and their molecular components quantified, especially proteins. Indeed, proteins - through their roles as catalytic units, structural components, and signaling molecules - are the main drivers of biological processes. Metagenomics has significantly expanded what we know about the genetic material present in microbiota, revealing their functional potential; metabolomics delivers an overall snapshot of the metabolites produced by the community. But metaproteomics offers a complementary approach to explore microbiome and holobiont functionality by focusing on the active proteins and functional pathways from each taxon. Significant recent advances in high-resolution tandem mass spectrometry have greatly expanded the catalog of peptide sequences accessible in each sample, creating the conditions for unprecedented taxonomical profiling, while also providing more accurate biomass quantification, more detailed protein characterization, and a greater capacity to monitor abundance and distinguish host biomarkers. By integrating artificial intelligence into the metaproteomics pipeline, extended datasets can now be efficiently mined to gain a more comprehensive functional view of complex biological systems, paving the way for next-generation metaproteomics. In this perspective, I discuss the transformative potential of this methodology. We are on the cusp of a remarkable omic revolution that promises to uncover the intricate workings of microbiomes by producing a vast array of new knowledge with multiple applications. SIGNIFICANCE: Metaproteomics provides a powerful lens to investigate microbiome and holobiont functionality by identifying and quantifying active proteins and functional pathways within each taxon. Recent breakthroughs in high-resolution tandem mass spectrometry have dramatically expanded the repertoire of peptide sequences detectable per sample. This progress enables unprecedented taxonomic resolution for microbial identification, more precise biomass quantification, comprehensive protein characterization, abundance monitoring, and the unique identification of host biomarkers. In this commentary, I delve into the distinctive features that make metaproteomics a transformative tool. I discuss the recent advancements in tandem mass spectrometry and argue that the primary challenge in analyzing complex samples is shifting from data acquisition to data interpretation. With the integration of artificial intelligence, I believe next-generation metaproteomics is poised to become the next Big Thing in microbiome research, unlocking profound insights into microbial functionality and ecosystem dynamics.

Evaluation of imputation and imputation-free strategies for differential abundance analysis in metaproteomics data

For metaproteomics data derived from the collective protein composition of dynamic multi-organism systems, the proportion of missing values and dimensions of data exceeds that observed in single-organism experiments. Consequently, evaluations of differential analysis strategies in other mass spectrometry (MS) data (such as proteomics and metabolomics) may not be directly applicable to metaproteomics data. In this study, we systematically evaluated five imputation methods [sample minimum, quantile regression, k-nearest neighbors (KNN), Bayesian principal component analysis (bPCA), random forest (RF)] and six imputation-free methods (moderated t-test, two-part t-test, two-part Wilcoxon test, semiparametric differential abundance analysis, differential abundance analysis with Bayes shrinkage estimation of variance method, and Mixture) for differential analysis in simulated metaproteomic datasets based on both data-dependent acquisition MS experiments and emerging data-independent acquisition experiments. The simulation datasets comprised 588 scenarios by considering the impacts of sample size, fold change between case and control, and missing value ratio at random and nonrandom. Compared to imputation-free methods, KNN, bPCA, and RF imputation performed poorly in datasets with a high missingness ratio and large sample size and resulted in a high false-positive risk. We made empirical recommendations based on the balance of sensitivity in analysis and control of false positives. The moderated t-test was optimal in scenarios of large sample size with a low missingness ratio. The two-part Wilcoxon test was recommended in scenarios of small sample size with a low missingness ratio or large sample size with a high missingness ratio. The comprehensive evaluations in our study can provide guidance for the differential abundance analysis in metaproteomics.

Fecal Metaproteomics as a Tool to Monitor Functional Modifications Induced in the Gut Microbiota by Ketogenic Diet: A Case Study

Metaproteomics is a valuable approach to characterize the biological functions involved in the gut microbiota (GM) response to dietary interventions. Ketogenic diets (KDs) are very effective in controlling seizure severity and frequency in drug-resistant epilepsy (DRE) and in the weight loss management in obese/overweight individuals. This case study provides proof of concept for the suitability of metaproteomics to monitor changes in taxonomic and functional GM features in an individual on a short-term very low-calorie ketogenic diet (VLCKD, 4 weeks), followed by a low-calorie diet (LCD). A marked increase in Akkermansia and Pseudomonadota was observed during VLCKD and reversed after the partial reintroduction of carbohydrates (LCD), in agreement with the results of previous metagenomic studies. In functional terms, the relative increase in Akkermansia was associated with an increased production of proteins involved in response to stress and biosynthesis of gamma-aminobutyric acid. In addition, VLCKD caused a relative increase in enzymes involved in the synthesis of the beta-ketoacid acetoacetate and of the ketogenic amino acid leucine. Our data support the potential of fecal metaproteomics to investigate the GM-dependent effect of KD as a therapeutic option in obese/overweight individuals and DRE patients.

Insights on Wet and Dry Workflows for Human Gut Metaproteomics

The human gut microbiota (GM) is a community of microorganisms that resides in the gastrointestinal (GI) tract. Recognized as a critical element of human health, the functions of the GM extend beyond GI well-being to influence overall systemic health and susceptibility to disease. Among the other omic sciences, metaproteomics highlights additional facets that make it a highly valuable discipline in the study of GM. Indeed, it allows the protein inventory of complex microbial communities. Proteins with associated taxonomic membership and function are identified and quantified from their constituent peptides by liquid chromatography coupled to mass spectrometry analyses and by querying specific databases (DBs). The aim of this review was to compile comprehensive information on metaproteomic studies of the human GM, with a focus on the bacterial component, to assist newcomers in understanding the methods and types of research conducted in this field. The review outlines key steps in a metaproteomic-based study, such as protein extraction, DB selection, and bioinformatic workflow. The importance of standardization is emphasized. In addition, a list of previously published studies is provided as hints for researchers interested in investigating the role of GM in health and disease states.

Impacts of Helicobacter pylori infection and eradication on gastrointestinal microbiota: An up-to-date critical review and future perspectives

ABSTRACT

Helicobacter pylori ( H. pylori ) infects approximately half of the population worldwide and causes chronic gastritis, peptic ulcers, and gastric cancer. Test-and-treat strategies have been recommended for the prevention of H. pylori -associated diseases. Advancements in high-throughput sequencing technologies have broadened our understanding of the complex gastrointestinal (GI) microbiota and its role in maintaining host homeostasis. Recently, an increasing number of studies have indicated that the colonization of H. pylori induces dramatic alterations in the gastric microbiota, with a predominance of H. pylori and a reduction in microbial diversity. Dysbiosis of the gut microbiome has also been observed after H. pylori infection, which may play a role in the development of colorectal cancer. However, there is concern regarding the impact of antibiotics on the gut microbiota during H. pylori eradication. In this review, we summarize the current literature concerning how H. pylori infection reshapes the GI microbiota and the underlying mechanisms, including changes in the gastric environment, immune responses, and persistent inflammation. Additionally, the impacts of H. pylori eradication on GI microbial homeostasis and the use of probiotics as adjuvant therapy are also discussed. The shifts in the GI microbiota and their crosstalk with H. pylori  may provide potential targets for H. pylori -related gastric diseases and extragastric manifestations.

Exploring the role of gut microbiome in autoimmune diseases: A comprehensive review

As the industrialized society advances, there has been a gradual increase in the prevalence of autoimmune disorders. A probe into the fundamental causes has disclosed several factors in modern society that have an influence on the gut microbiome. These dramatic shifts in the gut microbiome are likely to be one of the reasons for the disarray in the immune system, and the relationship between the immune system and the gut microbiome emerging as a perennial hot topic of research. This review enumerates the findings from sequencing studies of gut microbiota on seven autoimmune diseases (ADs): Rheumatoid Arthritis (RA), Systemic Lupus Erythematosus (SLE), Ankylosing Spondylitis (AS), Systemic Sclerosis (SSc), Sjögren's Syndrome (SjS), Juvenile Idiopathic Arthritis (JIA), and Behçet's Disease (BD). It aims to identify commonalities in changes in the gut microbiome within the autoimmune disease cohort and characteristics specific to each disease. The dysregulation of the gut microbiome involves a disruption of the internal balance and the balance between the external environment and the host. This dysregulation impacts the host's immune system, potentially playing a role in the development of ADs. Damage to the gut epithelial barrier allows potential pathogens to translocate to the mucosal layer, contacting epithelial cells, disrupting tight junctions, and being recognized by antigen-presenting cells, which triggers an immune response. Primed T-cells assist B-cells in producing antibodies against pathogens; if antigen mimicry occurs, an immune response is generated in extraintestinal organs during immune cell circulation, clinically manifesting as ADs. However, current research is limited; advancements in sequencing technology, large-scale cohort studies, and fecal microbiota transplantation (FMT) research are expected to propel this field to new peaks.

Benchmarking low- and high-throughput protein cleanup and digestion methods for human fecal metaproteomics

The application of fecal metaproteomics to large-scale studies of the gut microbiota requires high-throughput analysis and standardized experimental protocols. Although high-throughput protein cleanup and digestion methods are increasingly used in shotgun proteomics, no studies have yet critically compared such protocols using human fecal samples. In this study, human fecal protein extracts were processed using several different protocols based on three main approaches: filter-aided sample preparation (FASP), solid-phase-enhanced sample preparation (SP3), and suspension trapping (S-Trap). These protocols were applied in both low-throughput (i.e., microtube-based) and high-throughput (i.e., microplate-based) formats, and the final peptide mixtures were analyzed by liquid chromatography coupled to high-resolution tandem mass spectrometry. The FASP-based methods and the combination of SP3 with in-StageTips (iST) yielded the best results in terms of the number of peptides identified through a database search against gut microbiome and human sequences. The efficiency of protein digestion, the ability to preserve hydrophobic peptides and high molecular weight proteins, and the reproducibility of the methods were also evaluated for the different protocols. Other relevant variables, including interindividual variability of stool, duration of protocols, and total costs, were considered and discussed. In conclusion, the data presented here can significantly contribute to the optimization and standardization of sample preparation protocols in human fecal metaproteomics. Furthermore, the promising results obtained with the high-throughput methods are expected to encourage the development of automated workflows and their application to large-scale gut microbiome studies.IMPORTANCEFecal metaproteomics is an experimental approach that allows the investigation of gut microbial functions, which are involved in many different physiological and pathological processes. Standardization and automation of sample preparation protocols in fecal metaproteomics are essential for its application in large-scale studies. Here, we comparatively evaluated different methods, available also in a high-throughput format, enabling two key steps of the metaproteomics analytical workflow (namely, protein cleanup and digestion). The results of our study provide critical information that may be useful for the optimization of metaproteomics experimental pipelines and their implementation in laboratory automation systems.

Novel carbonic anhydrase inhibitors for the treatment of Helicobacter pylori infection

INTRODUCTION

Helicobacter pylori, the causative agent of peptic ulcer, gastritis, and gastric cancer encodes two carbonic anhydrases (CA, EC 4.2.1.1) belonging to the α- and β-class (HpCAα/β), which have been validated as antibacterial drug targets. Acetazolamide and ethoxzolamide were also clinically used for the management of peptic ulcer.

AREAS COVERED

Sulfonamides were the most investigated HpCAα/β compounds, with several low nanomolar inhibitors identified, some of which also crystallized as adducts with HpCAα, allowing for the rationalization of the structure-activity relationship. Few data are available for other classes of inhibitors, such as phenols, sulfamides, sulfamates, dithiocarbamates, arylboronic acids, some of which showed effective in vitro inhibition and for phenols, also inhibition of planktonic growth, biofilm formation, and outer membrane vesicles spawning.

EXPERT OPINION

Several recent drug design studies reported selenazoles incorporating seleno/telluro-ethers attached to benzenesulfonamides, hybrids incorporating the EGFR inhibitor erlotinib and benzenesulfonamides, showing KIs < 100 nM against HpCAα and MICs in the range of 8-16 µg/mL for the most active derivatives. Few drug design studies for non-sulfonamide inhibitors were performed to date, although inhibition of these enzymes may help the fight of multidrug resistance to classical antibiotics which emerged in the last decades also for this bacterium.