The astounding exhaustiveness and speed of the Astral mass analyzer for highly complex samples is a quantum leap in the functional analysis of microbiomes.

BACKGROUND: By analyzing the proteins which are the workhorses of biological systems, metaproteomics allows us to list the taxa present in any microbiota, monitor their relative biomass, and characterize the functioning of complex biological systems. RESULTS: Here, we present a new strategy for rapidly determining the microbial community structure of a given sample and designing a customized protein sequence database to optimally exploit extensive tandem mass spectrometry data. This approach leverages the capabilities of the first generation of Quadrupole Orbitrap mass spectrometer incorporating an asymmetric track lossless (Astral) analyzer, offering rapid MS/MS scan speed and sensitivity. We took advantage of data-dependent acquisition and data-independent acquisition strategies using a peptide extract from a human fecal sample spiked with precise amounts of peptides from two reference bacteria. CONCLUSIONS: Our approach, which combines both acquisition methods, proves to be time-efficient while processing extensive generic databases and massive datasets, achieving a coverage of more than 122,000 unique peptides and 38,000 protein groups within a 30-min DIA run. This marks a significant departure from current state-of-the-art metaproteomics methodologies, resulting in broader coverage of the metabolic pathways governing the biological system. In combination, our strategy and the Astral mass analyzer represent a quantum leap in the functional analysis of microbiomes. Video Abstract.

Human gut microbiome and metabolite dynamics under simulated microgravity.

The Artificial Gravity Bed Rest - European Space Agency (AGBRESA) study was the first joint bed rest study by ESA, DLR, and NASA that examined the effect of simulated weightlessness on the human body and assessed the potential benefits of artificial gravity as a countermeasure in an analog of long-duration spaceflight. In this study, we investigated the impact of simulated microgravity on the gut microbiome of 12 participants during a 60-day head-down tilt bed rest at the :envihab facilities. Over 60 days of simulated microgravity resulted in a mild change in the gut microbiome, with distinct microbial patterns and pathway expression in the feces of the countermeasure group compared to the microgravity simulation-only group. Additionally, we found that the countermeasure protocols selectively increased the abundance of beneficial short-chain fatty acids in the gut, such as acetate, butyrate, and propionate. Some physiological signatures also included the modulation of taxa reported to be either beneficial or opportunistic, indicating a mild adaptation in the microbiome network balance. Our results suggest that monitoring the gut microbial catalog along with pathway clustering and metabolite profiling is an informative synergistic strategy to determine health disturbances and the outcome of countermeasure protocols for future space missions.

The future of spaceflight will involve missions beyond the International Space Station or the Moon and astronaut's health will be challenged by a harsh space environment for longer periods. In the last decade, the intestine has gained importance in dictating overall physiology and we explore it as an additional indicator of health during our ground-based bed rest study simulating microgravity for 60 days. Through the analysis of fecal proteins, we compile the catalog of microbes colonizing the gut of the 12 participants along with the implicated biological activity of the proteins and another 9 lipid analytes. We found specific microbes associated with recovery or healthy status in our subjects to be increased during spaceflight countermeasure conditions and inverse observations in subjects subjected to perilous spaceflight simulation. Our approach improves the functional characterization of the gut by the use of noninvasive methodology correlating the microbial composition of human stool samples with physiological status.

Proteomic insights into Helcococcus kunzii in a diabetic foot ulcer-like environment.

PURPOSE: Helcococcus kunzii is a skin commensal, Gram-positive bacterium, mostly isolated from infected chronic wounds. This opportunistic pathogen is usually co-isolated with Staphylococcus aureus. The present dataset explores the production and secretion of H. kunzii bacterial virulence interacting proteins in a growth medium mimicking chronic wounds in exponential and stationary growth phases. EXPERIMENTAL DESIGN: The H. kunzii cellular proteome and exoproteome were assessed by analyzing three biological replicates per condition tested. Samples were analyzed using a Q-Exactive HF mass spectrometer. Comparative and functional analyses were performed to profile the identified protein set. RESULTS: The H. kunzii's cellular proteome encompassed 969 proteins, among which 64 and 53 were specifically identified in the exponential and stationary phase of growth, respectively. Its exoproteome comprised 58 proteins, among which 16 and 14 were characteristic of each growth stage. Metabolic differences between the two phases of growth are discussed. Besides, the production of previously shortlisted and novel putative H. kunzii targets involved in modulating the virulence of S. aureus is investigated. CONCLUSION AND CLINICAL RELEVANCE: This work, pioneering the study of H. kunzii physiology in a chronic wound-like environment, should assist future research on this opportunistic pathogen and the search for innovative approaches for wound management.

Mass spectrometry detection of monkeypox virus: Comprehensive coverage for ranking the most responsive peptide markers.

The recent and sudden outbreak of monkeypox in numerous non-endemic countries requires expanding its surveillance immediately and understanding its origin and spread. As learned from the COVID-19 pandemic, appropriate detection techniques are crucial to achieving such a goal. Mass spectrometry has the advantages of a rapid response, low analytical interferences, better precision, and easier multiplexing to detect various pathogens and their variants. In this proteomic dataset, we report experimental data on the proteome of the monkeypox virus (MPXV) recorded by state-of-the-art shotgun proteomics, including data-dependent and data-independent acquisition for comprehensive coverage. We highlighted 152 viral proteins, corresponding to an overall proteome coverage of 79.5 %. Among the 1371 viral peptides detected, 35 peptides with the most intense signals in mass spectrometry were selected, representing a subset of 13 viral proteins. Their relevance as potential candidate markers for virus detection by targeted mass spectrometry is discussed. This report should assist the rapid development of mass spectrometry-based tests to detect a pathogen of increasing concern.

Gut as an Alternative Entry Route for SARS-CoV-2: Current Evidence and Uncertainties of Productive Enteric Infection in COVID-19.

The gut has been proposed as a potential alternative entry route for SARS-CoV-2. This was mainly based on the high levels of SARS-CoV-2 receptor expressed in the gastrointestinal (GI) tract, the observations of GI disorders (such as diarrhea) in some COVID-19 patients and the detection of SARS-CoV-2 RNA in feces. However, the underlying mechanisms remain poorly understood. It has been proposed that SARS-CoV-2 can productively infect enterocytes, damaging the intestinal barrier and contributing to inflammatory response, which might lead to GI manifestations, including diarrhea. Here, we report a methodological approach to assess the evidence supporting the sequence of events driving SARS-CoV-2 enteric infection up to gut adverse outcomes. Exploring evidence permits to highlight knowledge gaps and current inconsistencies in the literature and to guide further research. Based on the current insights on SARS-CoV-2 intestinal infection and transmission, we then discuss the potential implication on clinical practice, including on long COVID. A better understanding of the GI implication in COVID-19 is still needed to improve disease management and could help identify innovative therapies or preventive actions targeting the GI tract.

Quick and wide-range taxonomical repertoire establishment of the cystic fibrosis lung microbiota by tandem mass spectrometry on sputum samples.

Microorganisms proteotyping by tandem mass spectrometry has been recently shown as a powerful methodology to identify the wide-range taxonomy and biomass of microbiota. Sputum is the recommended specimen for routine microbiological monitoring of Cystic Fibrosis (CF) patients but has been rarely submitted to tandem mass spectrometry-based proteotyping. In this study, we compared the microbial components of spontaneous and induced sputum samples from three cystic fibrosis patients. Although the presence of microbial proteins is much lower than host proteins, we report that the microbiota's components present in the samples can be identified, as well as host biomarkers and functional insights into the microbiota. No significant difference was found in microorganism abundance between paired spontaneous and induced sputum samples. Microbial proteins linked to resistance, iron uptake, and biofilm-forming ability were observed in sputa independently of the sampling method. This unbiased and enlarged view of the CF microbiome could be highly complementary to culture and relevant for the clinical management of CF patients by improving knowledge about the host-pathogen dynamics and CF pathophysiology.

Mechanisms Leading to Gut Dysbiosis in COVID-19: Current Evidence and Uncertainties Based on Adverse Outcome Pathways.

Alteration in gut microbiota has been associated with COVID-19. However, the underlying mechanisms remain poorly understood. Here, we outlined three potential interconnected mechanistic pathways leading to gut dysbiosis as an adverse outcome following SARS-CoV-2 presence in the gastrointestinal tract. Evidence from the literature and current uncertainties are reported for each step of the different pathways. One pathway investigates evidence that intestinal infection by SARS-CoV-2 inducing intestinal inflammation alters the gut microbiota. Another pathway links the binding of viral S protein to angiotensin-converting enzyme 2 (ACE2) to the dysregulation of this receptor, essential in intestinal homeostasis-notably for amino acid metabolism-leading to gut dysbiosis. Additionally, SARS-CoV-2 could induce gut dysbiosis by infecting intestinal bacteria. Assessing current evidence within the Adverse Outcome Pathway framework justifies confidence in the proposed mechanisms to support disease management and permits the identification of inconsistencies and knowledge gaps to orient further research.

Factors Modulating COVID-19: A Mechanistic Understanding Based on the Adverse Outcome Pathway Framework.

Addressing factors modulating COVID-19 is crucial since abundant clinical evidence shows that outcomes are markedly heterogeneous between patients. This requires identifying the factors and understanding how they mechanistically influence COVID-19. Here, we describe how eleven selected factors (age, sex, genetic factors, lipid disorders, heart failure, gut dysbiosis, diet, vitamin D deficiency, air pollution and exposure to chemicals) influence COVID-19 by applying the Adverse Outcome Pathway (AOP), which is well-established in regulatory toxicology. This framework aims to model the sequence of events leading to an adverse health outcome. Several linear AOPs depicting pathways from the binding of the virus to ACE2 up to clinical outcomes observed in COVID-19 have been developed and integrated into a network offering a unique overview of the mechanisms underlying the disease. As SARS-CoV-2 infectibility and ACE2 activity are the major starting points and inflammatory response is central in the development of COVID-19, we evaluated how those eleven intrinsic and extrinsic factors modulate those processes impacting clinical outcomes. Applying this AOP-aligned approach enables the identification of current knowledge gaps orientating for further research and allows to propose biomarkers to identify of high-risk patients. This approach also facilitates expertise synergy from different disciplines to address public health issues.

Profiling SARS-CoV-2 Infection by High-Throughput Shotgun Proteomics.

A comprehensive cartography of viral and host proteins expressed during the different stages of SARS-CoV-2 infection is key to decipher the molecular mechanisms of pathogenesis. For the most detailed analysis, proteins should be first purified and then proteolyzed with trypsin in the presence of detergents. The resulting peptide mixtures are resolved by reverse phase ultrahigh pressure liquid chromatography and then identified by a high-resolution tandem mass spectrometer. The thousands of spectra acquired for each fraction can then be assigned to peptide sequences using a relevant protein sequence database, comprising viral and host proteins and potential contaminants from the growth medium or from the operator. The peptides are evidencing proteins and their intensities are used to infer the abundance of their corresponding proteins. Data analysis allows for highlighting the viral and host proteins dynamics. Here, we describe the sample preparation method adapted to profile SARS-CoV-2 -infected cell models, the shotgun proteomics pipeline to record experimental data, and the workflow for data interpretation to analyze infection-induced proteomic changes in a time-resolved manner.

Taxonomical and functional changes in COVID-19 faecal microbiome could be related to SARS-CoV-2 faecal load.

Since the beginning of the pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) the gastrointestinal (GI) tract has emerged as an important organ influencing the propensity to and potentially the severity of the related COVID-19 disease. However, the contribution of the SARS-CoV-2 intestinal infection on COVID-19 pathogenesis remains to be clarified. In this exploratory study, we highlighted a possible link between alterations in the composition of the gut microbiota and the levels of SARS-CoV-2 RNA in the gastrointestinal tract, which could be more important than the presence of SARS-CoV-2 in the respiratory tract, COVID-19 severity and GI symptoms. As established by metaproteomics, altered molecular functions in the microbiota profiles of high SARS-CoV-2 RNA level faeces highlight mechanisms such as inflammation-induced enterocyte damage, increased intestinal permeability and activation of immune response that may contribute to vicious cycles. Uncovering the role of this gut microbiota dysbiosis could drive the investigation of alternative therapeutic strategies to favour the clearance of the virus and potentially mitigate the effect of the SARS-CoV-2 infection.

Pan-genome analysis identifies intersecting roles for Pseudomonas specialized metabolites in potato pathogen inhibition.

Agricultural soil harbors a diverse microbiome that can form beneficial relationships with plants, including the inhibition of plant pathogens. Pseudomonas spp. are one of the most abundant bacterial genera in the soil and rhizosphere and play important roles in promoting plant health. However, the genetic determinants of this beneficial activity are only partially understood. Here, we genetically and phenotypically characterize the Pseudomonas fluorescens population in a commercial potato field, where we identify strong correlations between specialized metabolite biosynthesis and antagonism of the potato pathogens Streptomyces scabies and Phytophthora infestans. Genetic and chemical analyses identified hydrogen cyanide and cyclic lipopeptides as key specialized metabolites associated with S. scabies inhibition, which was supported by in planta biocontrol experiments. We show that a single potato field contains a hugely diverse and dynamic population of Pseudomonas bacteria, whose capacity to produce specialized metabolites is shaped both by plant colonization and defined environmental inputs.

Potato scab and blight are two major diseases which can cause heavy crop losses. They are caused, respectively, by the bacterium Streptomyces scabies and an oomycete (a fungus-like organism) known as Phytophthora infestans. Fighting these disease-causing microorganisms can involve crop management techniques ­ for example, ensuring that a field is well irrigated helps to keep S. scabies at bay. Harnessing biological control agents can also offer ways to control disease while respecting the environment. Biocontrol bacteria, such as Pseudomonas, can produce compounds that keep S. scabies and P. infestans in check. However, the identity of these molecules and how irrigation can influence Pseudomonas population remains unknown. To examine these questions, Pacheco-Moreno et al. sampled and isolated hundreds of Pseudomonas strains from a commercial potato field, closely examining the genomes of 69 of these. Comparing the genetic information of strains based on whether they could control the growth of S. scabies revealed that compounds known as cyclic lipopeptides are key to controlling the growth of S. scabies and P. infestans. Whether the field was irrigated also had a large impact on the strains forming the Pseudomonas population. Working out how Pseudomonas bacteria block disease could speed up the search for biological control agents. The approach developed by Pacheco-Moreno et al. could help to predict which strains might be most effective based on their genetic features. Similar experiments could also work for other combinations of plants and diseases.

Metaproteomics to Decipher CF Host-Microbiota Interactions: Overview, Challenges and Future Perspectives.

Cystic fibrosis (CF) is a hereditary disease caused by mutations in the CF transmembrane conductance regulator (CFTR) gene, triggering dysfunction of the anion channel in several organs including the lung and gut. The main cause of morbidity and mortality is chronic infection. The microbiota is now included among the additional factors that could contribute to the exacerbation of patient symptoms, to treatment outcome, and more generally to the phenotypic variability observed in CF patients. In recent years, various omics tools have started to shed new light on microbial communities associated with CF and host-microbiota interactions. In this context, proteomics targets the key effectors of the responses from organisms, and thus their phenotypes. Recent advances are promising in terms of gaining insights into the CF microbiota and its relation with the host. This review provides an overview of the contributions made by proteomics and metaproteomics to our knowledge of the complex host-microbiota partnership in CF. Considering the strengths and weaknesses of proteomics-based approaches in profiling the microbiota in the context of other diseases, we illustrate their potential and discuss possible strategies to overcome their limitations in monitoring both the respiratory and intestinal microbiota in sample from patients with CF.

Heterogeneity of SARS-CoV-2 virus produced in cell culture revealed by shotgun proteomics and supported by genome sequencing.

COVID-19 is the most disturbing pandemic of the past hundred years. Its causative agent, the SARS-CoV-2 virus, has been the subject of an unprecedented investigation to characterize its molecular structure and intimate functioning. While markers for its detection have been proposed and several diagnostic methodologies developed, its propensity to evolve and evade diagnostic tools and the immune response is of great concern. The recent spread of new variants with increased infectivity requires even more attention. Here, we document how shotgun proteomics can be useful for rapidly monitoring the evolution of the SARS-CoV-2 virus. We evaluated the heterogeneity of purified SARS-CoV-2 virus obtained after culturing in the Vero E6 cell line. We found that cell culture induces significant changes that are translated at the protein level, such changes being detectable by tandem mass spectrometry. Production of viral particles requires careful quality control which can be easily performed by shotgun proteomics. Although considered relatively stable so far, the SARS-CoV-2 genome turns out to be prone to frequent variations. Therefore, the sequencing of SARS-CoV-2 variants from patients reporting only the consensus genome after its amplification would deserve more attention and could benefit from more in-depth analysis of low level but crystal-clear signals, as well as complementary and rapid analysis by shotgun proteomics.

Proteomics in the COVID-19 Battlefield: First Semester Check-Up.

Proteomics offers a wide collection of methodologies to study biological systems at the finest granularity. Faced with COVID-19, the most worrying pandemic in a century, proteomics researchers have made significant progress in understanding how the causative virus hijacks the host's cellular machinery and multiplies exponentially, how the disease can be diagnosed, and how it develops, as well as its severity predicted. Numerous cellular targets of potential interest for the development of new antiviral drugs have been documented. Here, the most striking results obtained in the proteomics field over this first semester of the pandemic are presented. The molecular machinery of SARS-CoV-2 is much more complex than initially believed, as many post-translational modifications can occur, leading to a myriad of proteoforms and a broad heterogeneity of viral particles. The interplay of protein-protein interactions, protein abundances, and post-translational modifications has yet to be fully documented to provide a full picture of this intriguing but lethal biological threat. Proteomics has the potential to provide rapid detection of the SARS-CoV-2 virus by mass spectrometry proteotyping, and to further increase the knowledge of severe respiratory syndrome COVID-19 and its long-term health consequences.

Proteotyping SARS-CoV-2 Virus from Nasopharyngeal Swabs: A Proof-of-Concept Focused on a 3 Min Mass Spectrometry Window.

Rapid but yet sensitive, specific, and high-throughput detection of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in clinical samples is key to diagnose infected people and to better control the spread of the virus. Alternative methodologies to PCR and immunodiagnostics that would not require specific reagents are worthy to investigate not only for fighting the COVID-19 pandemic but also to detect other emergent pathogenic threats. Here, we propose the use of tandem mass spectrometry to detect SARS-CoV-2 marker peptides in nasopharyngeal swabs. We documented that the signal from the microbiota present in such samples is low and can be overlooked when interpreting shotgun proteomic data acquired on a restricted window of the peptidome landscape. In this proof-of-concept study, simili nasopharyngeal swabs spiked with different quantities of purified SARS-CoV-2 viral material were used to develop a nanoLC-MS/MS acquisition method, which was then successfully applied on COVID-19 clinical samples. We argue that peptides ADETQALPQR and GFYAQGSR from the nucleocapsid protein are of utmost interest as their signal is intense and their elution can be obtained within a 3 min window in the tested conditions. These results pave the way for the development of time-efficient viral diagnostic tests based on mass spectrometry.

Shotgun proteomics analysis of SARS-CoV-2-infected cells and how it can optimize whole viral particle antigen production for vaccines.

Severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) has resulted in a pandemic and is continuing to spread rapidly around the globe. No effective vaccine is currently available to prevent COVID-19, and intense efforts are being invested worldwide into vaccine development. In this context, all technology platforms must overcome several challenges resulting from the use of an incompletely characterized new virus. These include finding the right conditions for virus amplification for the development of vaccines based on inactivated or attenuated whole viral particles. Here, we describe a shotgun tandem mass spectrometry workflow, the data produced can be used to guide optimization of the conditions for viral amplification. In parallel, we analysed the changes occurring in the host cell proteome following SARS-CoV-2 infection to glean information on the biological processes modulated by the virus that could be further explored as potential drug targets to deal with the pandemic.

Control of mRNA translation by dynamic ribosome modification.

Control of mRNA translation is a crucial regulatory mechanism used by bacteria to respond to their environment. In the soil bacterium Pseudomonas fluorescens, RimK modifies the C-terminus of ribosomal protein RpsF to influence important aspects of rhizosphere colonisation through proteome remodelling. In this study, we show that RimK activity is itself under complex, multifactorial control by the co-transcribed phosphodiesterase trigger enzyme (RimA) and a polyglutamate-specific protease (RimB). Furthermore, biochemical experimentation and mathematical modelling reveal a role for the nucleotide second messenger cyclic-di-GMP in coordinating these activities. Active ribosome regulation by RimK occurs by two main routes: indirectly, through changes in the abundance of the global translational regulator Hfq and directly, with translation of surface attachment factors, amino acid transporters and key secreted molecules linked specifically to RpsF modification. Our findings show that post-translational ribosomal modification functions as a rapid-response mechanism that tunes global gene translation in response to environmental signals.

Shortlisting SARS-CoV-2 Peptides for Targeted Studies from Experimental Data-Dependent Acquisition Tandem Mass Spectrometry Data.

Detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a crucial tool for fighting the COVID-19 pandemic. This dataset brief presents the exploration of a shotgun proteomics dataset acquired on SARS-CoV-2 infected Vero cells. Proteins from inactivated virus samples were extracted, digested with trypsin, and the resulting peptides were identified by data-dependent acquisition tandem mass spectrometry. The 101 peptides reporting for six viral proteins were specifically analyzed in terms of their analytical characteristics, species specificity and conservation, and their proneness to structural modifications. Based on these results, a shortlist of 14 peptides from the N, S, and M main structural proteins that could be used for targeted mass-spectrometry method development and diagnostic of the new SARS-CoV-2 is proposed and the best candidates are commented.

Quick microbial molecular phenotyping by differential shotgun proteomics.

Differential shotgun proteomics identifies proteins that discriminate between sets of samples based on differences in abundance. This methodology can be easily applied to study (i) specific microorganisms subjected to a variety of growth or stress conditions or (ii) different microorganisms sampled in the same condition. In microbiology, this comparison is particularly successful because differing microorganism phenotypes are explained by clearly altered abundances of key protein players. The extensive description and quantification of proteins from any given microorganism can be routinely obtained for several conditions within a few days by tandem mass spectrometry. Such protein-centred microbial molecular phenotyping is rich in information. However, well-designed experimental strategies, carefully parameterized analytical pipelines, and sound statistical approaches must be applied if the shotgun proteomic data are to be correctly interpreted. This minireview describes these key items for a quick molecular phenotyping based on label-free quantification shotgun proteomics.

Evaluation of Sample Preparation Methods for Fast Proteotyping of Microorganisms by Tandem Mass Spectrometry.

Tandem mass spectrometry-based proteotyping allows characterizing microorganisms in terms of taxonomy and is becoming an important tool for investigating microbial diversity from several ecosystems. Fast and automatable sample preparation for obtaining peptide pools amenable to tandem mass spectrometry is necessary for enabling proteotyping as a high-throughput method. First, the protocol to increase the yield of lysis of several representative bacterial and eukaryotic microorganisms was optimized by using a long and drastic bead-beating setting with 0.1 mm silica beads, 0.1 and 0.5 mm glass beads, in presence of detergents. Then, three different methods to obtain greater digestion yield from these extracts were tested and optimized for improve efficiency and reduce application time: denaturing electrophoresis of proteins and in-gel proteolysis, suspension-trapping filter-based approach (S-Trap) and, solid-phase-enhanced sample preparation named SP3. The latter method outperforms the other two in terms of speed and delivers also more peptides and proteins than with the in-gel proteolysis (2.2 fold for both) and S-trap approaches (1.3 and 1.2 fold, respectively). Thus, SP3 directly improves tandem mass spectrometry proteotyping.