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

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.

Revealing taxonomy, activity, and substrate assimilation in mixed bacterial communities by GroEL-proteotyping-based stable isotope probing

Protein-based stable isotope probing (protein-SIP) can link microbial taxa to substrate assimilation. Traditionally, protein-SIP requires a sample-specific metagenome-derived database for samples with unknown composition. Here, we describe GroEL-prototyping-based stable isotope probing (GroEL-SIP), that uses GroEL as a taxonomic marker protein to identify bacterial taxa (GroEL-proteotyping) coupled to SIP directly linking identified taxa to substrate consumption. GroEL-SIP's main advantages are that (1) it can be performed with a sample-independent database and (2) sample complexity can be reduced by enriching GroEL proteins, increasing sensitivity and reducing instrument time. We applied GroEL-SIP to pure cultures, synthetic bicultures, and a human gut model using 2H-, 18O-, and 13C-labeled substrates. While 2H and 18O allowed assessing general activity, 13C enabled differentiation of substrate source and utilized metabolic pathways. GroEL-SIP offers fast and straightforward protein-SIP analyses of highly abundant families in mixed bacterial communities, but further work is needed to improve sensitivity, resolution, and database coverage.

LineageFilter: Improved Proteotyping of Complex Samples Using Metaproteomics and Machine Learning

Metaproteomics is a powerful tool to characterize how microbiota function by analyzing their proteic content by tandem mass spectrometry. Given the complexity of these samples, accurately assessing their taxonomical composition without prior information based solely on peptide sequences remains a challenge. Here, we present LineageFilter, a new python-based AI software for refined proteotyping of complex samples using metaproteomics interpreted data and machine learning. Given a tentative list of taxa, their abundances, and the scores associated with their identified peptides, LineageFilter computes a comprehensive set of features for each identified taxon at all taxonomical ranks. Its machine-learning model then assesses the likelihood of each taxon's presence based on these features, enabling improved proteotyping and sample-specific database construction.

Universal Identification of Pathogenic Viruses by Liquid Chromatography Coupled with Tandem Mass Spectrometry Proteotyping

Accurate and rapid identification of viruses is crucial for an effective medical diagnosis when dealing with infections. Conventional methods, including DNA amplification techniques or lateral-flow assays, are constrained to a specific set of targets to search for. In this study, we introduce a novel tandem mass spectrometry proteotyping-based method that offers a universal approach for the identification of pathogenic viruses and other components, eliminating the need for a priori knowledge of the sample composition. Our protocol relies on a time and cost-efficient peptide sample preparation, followed by an analysis with liquid chromatography coupled to high-resolution tandem mass spectrometry. As a proof of concept, we first assessed our method on publicly available shotgun proteomics datasets obtained from virus preparations and fecal samples of infected individuals. Successful virus identification was achieved with 53 public datasets, spanning 23 distinct viral species. Furthermore, we illustrated the method's capability to discriminate closely related viruses within the same sample, using alphaviruses as an example. The clinical applicability of our method was demonstrated by the accurate detection of the vaccinia virus in spiked saliva, a matrix of paramount clinical significance due to its non-invasive and easily obtainable nature. This innovative approach represents a significant advancement in pathogen detection and paves the way for enhanced diagnostic capabilities.

Flash MS/MS proteotyping allows identifying microbial isolates in 36 s of mass spectrometry signal

Rapid identification of microorganisms is essential for medical diagnostics, sanitary controls, and food safety. High-throughput analytical platforms currently rely on whole-cell MALDI-TOF mass spectrometry to process hundreds of samples per day. Although this technology has become a reference method, it is unable to process most environmental isolates and opportunistic pathogens due to an incomplete experimental spectrum database. In most cases, its discriminating power is limited to the species taxonomical rank. By recording much more sequence information at the peptide level, proteotyping by tandem mass spectrometry is able to identify the taxonomic position of any microorganism in the tree of life and can be highly discriminating at the subspecies level. We propose here a methodology for ultra-fast identification of microorganisms by tandem mass spectrometry based on direct sample infusion and a highly sensitive procedure for data processing and taxonomic identification. Results obtained on reference strains and hitherto uncharacterized bacterial isolates show identification to species level in 36 s of tandem mass spectrometry signal, 102 s when including the injection procedure. Flash proteotyping is highly discriminating, as it can provide information down to strain level. The methodology enables high throughput identification of isolates, opening up new prospects, particularly in culturomics, and diagnostics.

Identification of biomarkers for COVID-19 associated secondary hemophagocytic lymphohistiocytosis

OBJECTIVES

We aimed to define and validate novel biomarkers that could identify individuals with COVID-19 associated secondary hemophagocytic lymphohistiocytosis (sHLH) and to test whether fatalities due to COVID-19 in the presence of sHLH were associated with specific defects in the immune system.

DESIGN

In two cohorts of adult patients presenting with COVID-19 in 2020 and 2021, clinical lab values and serum proteomics were assessed. Subjects identified as having sHLH were compared to those with COVID-19 without sHLH. Eight deceased patients defined as COVID-sHLH underwent genomic sequencing in order to identify variants in immune-related genes.

SETTING

Two tertiary care hospitals in Seattle, Washington (Virginia Mason Medical Center and Harborview Medical Center).

PATIENTS

186 patients with COVID-19.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Nine percent of enrolled COVID-19 subjects met our defined criteria for sHLH. Using broad serum proteomic approaches (O-link and SomaScan), we identified three biomarkers for COVID-19 associated sHLH (soluble PD-L1, TNF-R1, and IL-18BP), supporting a role for proteins previously associated with other forms of sHLH (IL-18BP and sTNF-R1). We also identified novel biomarkers and pathways of COVID-sHLH, including sPD-L1 and the syntaxin pathway. We detected variants in several genes involved in immune responses in individuals with COVID-sHLH, including in DOCK8 and in TMPRSS15, suggesting that genetic alterations in immune-related genes may contribute to hyperinflammation and fatal outcomes in COVID-19.

CONCLUSIONS

Biomarkers of COVID-19 associated sHLH, such as soluble PD-L1, and pathways, such as the syntaxin pathway, and variants in immune genes in these individuals, suggest critical roles for the immune response in driving sHLH in the context of COVID-19.

A novel clinical metaproteomics workflow enables bioinformatic analysis of host-microbe dynamics in disease

Clinical metaproteomics has the potential to offer insights into the host-microbiome interactions underlying diseases. However, the field faces challenges in characterizing microbial proteins found in clinical samples, usually present at low abundance relative to the host proteins. As a solution, we have developed an integrated workflow coupling mass spectrometry-based analysis with customized bioinformatic identification, quantification, and prioritization of microbial proteins, enabling targeted assay development to investigate host-microbe dynamics in disease. The bioinformatics tools are implemented in the Galaxy ecosystem, offering the development and dissemination of complex bioinformatic workflows. The modular workflow integrates MetaNovo (to generate a reduced protein database), SearchGUI/PeptideShaker and MaxQuant [to generate peptide-spectral matches (PSMs) and quantification], PepQuery2 (to verify the quality of PSMs), Unipept (for taxonomic and functional annotation), and MSstatsTMT (for statistical analysis). We have utilized this workflow in diverse clinical samples, from the characterization of nasopharyngeal swab samples to bronchoalveolar lavage fluid. Here, we demonstrate its effectiveness via analysis of residual fluid from cervical swabs. The complete workflow, including training data and documentation, is available via the Galaxy Training Network, empowering non-expert researchers to utilize these powerful tools in their clinical studies.

IMPORTANCE

Clinical metaproteomics has immense potential to offer functional insights into the microbiome and its contributions to human disease. However, there are numerous challenges in the metaproteomic analysis of clinical samples, including handling of very large protein sequence databases for sensitive and accurate peptide and protein identification from mass spectrometry data, as well as taxonomic and functional annotation of quantified peptides and proteins to enable interpretation of results. To address these challenges, we have developed a novel clinical metaproteomics workflow that provides customized bioinformatic identification, verification, quantification, and taxonomic and functional annotation. This bioinformatic workflow is implemented in the Galaxy ecosystem and has been used to characterize diverse clinical sample types, such as nasopharyngeal swabs and bronchoalveolar lavage fluid. Here, we demonstrate its effectiveness and availability for use by the research community via analysis of residual fluid from cervical swabs.

The Landscape and Perspectives of the Human Gut Metaproteomics

The human gut microbiome is closely associated with human health and diseases. Metaproteomics has emerged as a valuable tool for studying the functionality of the gut microbiome by analyzing the entire proteins present in microbial communities. Recent advancements in liquid chromatography and tandem mass spectrometry (LC-MS/MS) techniques have expanded the detection range of metaproteomics. However, the overall coverage of the proteome in metaproteomics is still limited. While metagenomics studies have revealed substantial microbial diversity and functional potential of the human gut microbiome, few studies have summarized and studied the human gut microbiome landscape revealed with metaproteomics. In this article, we present the current landscape of human gut metaproteomics studies by re-analyzing the identification results from 15 published studies. We quantified the limited proteome coverage in metaproteomics and revealed a high proportion of annotation coverage of metaproteomics-identified proteins. We conducted a preliminary comparison between the metaproteomics view and the metagenomics view of the human gut microbiome, identifying key areas of consistency and divergence. Based on the current landscape of human gut metaproteomics, we discuss the feasibility of using metaproteomics to study functionally unknown proteins and propose a whole workflow peptide-centric analysis. Additionally, we suggest enhancing metaproteomics analysis by refining taxonomic classification and calculating confidence scores, as well as developing tools for analyzing the interaction between taxonomy and function.

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.

A Simplified Label-Free Method for Proteotyping Sets of Six Isolates in a Single Liquid Chromatography-High-Resolution Tandem Mass Spectrometry Analysis

Clinical diagnostics and microbiology require high-throughput identification of microorganisms. Sample multiplexing prior to detection is an attractive means to reduce analysis costs and time-to-result. Recent studies have demonstrated the discriminative power of tandem mass spectrometry-based proteotyping. This technology can rapidly identify the most likely taxonomical position of any microorganism, even uncharacterized organisms. Here, we present a simplified label-free multiplexing method to proteotype isolates by tandem mass spectrometry that can identify six microorganisms in a single 20 min analytical run. The strategy involves the production of peptide fractions with distinct hydrophobicity profiles using spin column fractionation. Assemblages of different fractions can then be analyzed using mass spectrometry. Results are subsequently interpreted based on the hydrophobic characteristics of the peptides detected, which make it possible to link each taxon identified to the initial sample. The methodology was tested on 32 distinct sets of six organisms including several worst-scenario assemblages-with differences in sample quantities or the presence of the same organisms in multiple fractions-and proved to be robust. These results pave the way for the deployment of tandem mass spectrometry-based proteotyping in microbiology laboratories.

Genome sequencing of Porostereum spadiceum to study the degradation of levofloxacin

Despite various plans to rationalize antibiotic use, antibiotic resistance in environmental bacteria is increasing due to the accumulation of antibiotic residues in the environment. This study aimed to test the ability of basidiomycete fungal strains to biotransform the antibiotic levofloxacin, a widely-used third-generation broad-spectrum fluoroquinolone, and to propose enzyme targets potentially involved in this biotransformation. The biotransformation process was performed using fungal strains. Levofloxacin biotransformation reached 100% after 9 days of culture with Porostereum spadiceum BS34. Using genomics and proteomics analyses coupled with activity tests, we showed that P. spadiceum produces several heme-peroxidases together with H2O2-producing enzymes that could be involved in the antibiotic biotransformation process. Using UV and high-resolution mass spectrometry, we were able to detect five levofloxacin degradation products. Their putative identity based on their MS2 fragmentation patterns led to the conclusion that the piperazine moiety was the main target of oxidative modification of levofloxacin by P. spadiceum, leading to a decrease in antibiotic activity.

A novel clinical metaproteomics workflow enables bioinformatic analysis of host-microbe dynamics in disease

Clinical metaproteomics has the potential to offer insights into the host-microbiome interactions underlying diseases. However, the field faces challenges in characterizing microbial proteins found in clinical samples, which are usually present at low abundance relative to the host proteins. As a solution, we have developed an integrated workflow coupling mass spectrometry-based analysis with customized bioinformatic identification, quantification and prioritization of microbial and host proteins, enabling targeted assay development to investigate host-microbe dynamics in disease. The bioinformatics tools are implemented in the Galaxy ecosystem, offering the development and dissemination of complex bioinformatic workflows. The modular workflow integrates MetaNovo (to generate a reduced protein database), SearchGUI/PeptideShaker and MaxQuant (to generate peptide-spectral matches (PSMs) and quantification), PepQuery2 (to verify the quality of PSMs), and Unipept and MSstatsTMT (for taxonomy and functional annotation). We have utilized this workflow in diverse clinical samples, from the characterization of nasopharyngeal swab samples to bronchoalveolar lavage fluid. Here, we demonstrate its effectiveness via analysis of residual fluid from cervical swabs. The complete workflow, including training data and documentation, is available via the Galaxy Training Network, empowering non-expert researchers to utilize these powerful tools in their clinical studies.

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.

Constitutive proteins of lumpy skin disease virion assessed by next-generation proteomics

IMPORTANCE

Lumpy skin disease virus (LSDV) is the causative agent of an economically important cattle disease which is notifiable to the World Organisation for Animal Health. Over the past decades, the disease has spread at an alarming rate throughout the African continent, the Middle East, Eastern Europe, the Russian Federation, and many Asian countries. While multiple LDSV whole genomes have made further genetic comparative analyses possible, knowledge on the protein composition of the LSDV particle remains lacking. This study provides for the first time a comprehensive proteomic analysis of an infectious LSDV particle, prompting new efforts toward further proteomic LSDV strain characterization. Furthermore, this first incursion within the capripoxvirus proteome represents one of very few proteomic studies beyond the sole Orthopoxvirus genus, for which most of the proteomics studies have been performed. Providing new information about other chordopoxviruses may contribute to shedding new light on protein composition within the Poxviridae family.

GroEL-Proteotyping of Bacterial Communities Using Tandem Mass Spectrometry

Profiling bacterial populations in mixed communities is a common task in microbiology. Sequencing of 16S small subunit ribosomal-RNA (16S rRNA) gene amplicons is a widely accepted and functional approach but relies on amplification primers and cannot quantify isotope incorporation. Tandem mass spectrometry proteotyping is an effective alternative for taxonomically profiling microorganisms. We suggest that targeted proteotyping approaches can complement traditional population analyses. Therefore, we describe an approach to assess bacterial community compositions at the family level using the taxonomic marker protein GroEL, which is ubiquitously found in bacteria, except a few obligate intracellular species. We refer to our method as GroEL-proteotyping. GroEL-proteotyping is based on high-resolution tandem mass spectrometry of GroEL peptides and identification of GroEL-derived taxa via a Galaxy workflow and a subsequent Python-based analysis script. Its advantage is that it can be performed with a curated and extendable sample-independent database and that GroEL can be pre-separated by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) to reduce sample complexity, improving GroEL identification while simultaneously decreasing the instrument time. GroEL-proteotyping was validated by employing it on a comprehensive raw dataset obtained through a metaproteome approach from synthetic microbial communities as well as real human gut samples. Our data show that GroEL-proteotyping enables fast and straightforward profiling of highly abundant taxa in bacterial communities at reasonable taxonomic resolution.

Label-Free Multiplex Proteotyping of Microbial Isolates

To meet clinical diagnostic needs and for general microbiological screening, it is essential to be able to accurately and rapidly identify any microorganisms from complex microbiota. To gain insight into the individual components of microbiota, culturomics has been proposed as a means to systematically test hundreds of possible cultivation conditions and generate numerous microbial isolates with very distinct characteristics. High-throughput identification methods must now be developed to quickly screen these isolates. Currently, most multiplexing methods involve labeling, which comes at a cost. In this paper, we present an innovative label-free multiplexing method for the identification of microorganisms using tandem mass spectrometry. The method is based on offline reversed-phase fractionation of individual peptidomes. Multiplexing is achieved by mixing fractions of staged hydrophobicity; thus, each sample is mapped to specific elution times. In this proof-of-concept study, multiplexed samples were analyzed by tandem mass spectrometry in a single run and microorganisms present in the mixture were resolved by phylopeptidomics proteotyping. Using this methodology, up to 21 microorganisms could be identified in a single 60 min run performed with a Q-Exactive HF high-resolution mass spectrometer, resulting in a rate of one microorganism identified per 3 min of mass spectrometry, without any need for the use of labeling reagents. This approach opens new perspectives for the application of high-throughput proteotyping of bacteria using tandem mass spectrometry in large culturomics projects.

Altered gut microbiota composition in children and their caregivers infected with the SARS-CoV-2 Omicron variant

BACKGROUND

Gut microbiota alterations have been implicated in the pathogenesis of coronavirus disease 2019 (COVID-19). This study aimed to explore gut microbiota changes in a prospective cohort of COVID-19 children and their asymptomatic caregivers infected with the severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) Omicron variant.

METHODS

A total of 186 participants, including 59 COVID-19 children, 50 asymptomatic adult caregivers, 52 healthy children (HC), and 25 healthy adults (HA), were recruited between 15 April and 31 May 2022. The gut microbiota composition was determined by 16S rRNA gene sequencing in fecal samples collected from the participants. Gut microbiota functional profiling was performed by using Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) software.

RESULTS

The gut microbiota analysis of beta diversity revealed that the fecal microbial community of COVID-19 children remained far distantly related to HC. The relative abundances of the phyla Actinobacteria and Firmicutes were decreased, whereas Bacteroidetes, Proteobacteria, and Verrucomicrobiota were increased in COVID-19 children. Feces from COVID-19 children exhibited notably lower abundances of the genera Blautia, Bifidobacterium, Fusicatenibacter, Streptococcus, and Romboutsia and higher abundances of the genera Prevotella, Lachnoclostridium, Escherichia-Shigella, and Bacteroides than those from HC. The enterotype distributions of COVID-19 children were characterized by a high prevalence of enterotype Bacteroides. Similar changes in gut microbiota compositions were observed in asymptomatic caregivers. Furthermore, the microbial metabolic activities of KEGG (Kyoto Encyclopedia of Genes and Genomes) and COG (cluster of orthologous groups of proteins) pathways were perturbed in feces from subjects infected with the SARS-CoV-2 Omicron variant.

CONCLUSION

Our data reveal altered gut microbiota compositions in both COVID-19 children and their asymptomatic caregivers infected with the SARS-CoV-2 Omicron variant, which further implicates the critical role of gut microbiota in COVID-19 pathogenesis.

Deep Paleoproteotyping and Microtomography Revealed No Heart Defect nor Traces of Embalming in the Cardiac Relics of Blessed Pauline Jaricot

Scientific examination of the heart of Blessed Pauline Jaricot-a French missionary figure-was carried out in 2022. As tandem mass spectrometry proteotyping has proven to be valuable to obtain the broad taxonomic repertoire of a given sample without any a priori information, we aimed at exploring the conditions of preservation of the relics and possible conditions of death. Metaproteomics and high-resolution microtomography imaging approaches were combined. A dataset comprising 6731 high-resolution MS/MS spectra was acquired and 968 of these spectra could be assigned to specific peptidic biomolecules. Based on the taxonomical information encompassed by the identified peptide sequences, 5 phyla were identified amongst eukaryota (94% of the biomass): Ascomycota (55%), with the species Aspergillus versicolor, Trichophyton mentagrophytes and Aspergillus glaucus, corresponding to expected cadaverous fungal flora; Chordata (42%), represented by a unique species, Homo sapiens; Streptophyta (3%); and Arthropoda (traces). Bacteria (6% of the biomass) were poorly represented. No trace of embalming substance could be retrieved, nor any pathogens. Imaging evidenced no heart defect nor embalming traces. No evidence that was inconsistent with natural and spontaneous conservation could be retrieved. This study prefigures the power of modern molecular techniques such as paleoproteotyping coupled to microtomography to gain insight into historical relics.

Metaproteomics to understand how microbiota function: The crystal ball predicts a promising future

In the medical, environmental, and biotechnological fields, microbial communities have attracted much attention due to their roles and numerous possible applications. The study of these communities is challenging due to their diversity and complexity. Innovative methods are needed to identify the taxonomic components of individual microbiota, their changes over time, and to determine how microoorganisms interact and function. Metaproteomics is based on the identification and quantification of proteins, and can potentially provide this full picture. Due to the wide molecular panorama and functional insights it provides, metaproteomics is gaining momentum in microbiome and holobiont research. Its full potential should be unleashed in the coming years with progress in speed and cost of analyses. In this exploratory crystal ball exercise, I discuss the technical and conceptual advances in metaproteomics that I expect to drive innovative research over the next few years in microbiology. I also debate the concepts of 'microbial dark matter' and 'Metaproteomics-Assembled Proteomes (MAPs)' and present some long-term prospects for metaproteomics in clinical diagnostics and personalized medicine, environmental monitoring, agriculture, and biotechnology.

Taxonomical composition and functional analysis of biofilms sampled from a nuclear storage pool

Sampling small amounts of biofilm from harsh environments such as the biofilm present on the walls of a radioactive material storage pool offers few analytical options if taxonomic characterization and estimation of the different biomass contributions are the objectives. Although 16S/18S rRNA amplification on extracted DNA and sequencing is the most widely applied method, its reliability in terms of quantitation has been questioned as yields can be species-dependent. Here, we propose a tandem-mass spectrometry proteotyping approach consisting of acquiring peptide data and interpreting then against a generalist database without any a priori. The peptide sequence information is transformed into useful taxonomical information that allows to obtain the different biomass contributions at different taxonomical ranks. This new methodology is applied for the first time to analyze the composition of biofilms from minute quantities of material collected from a pool used to store radioactive sources in a nuclear facility. For these biofilms, we report the identification of three genera, namely Sphingomonas, Caulobacter, and Acidovorax, and their functional characterization by metaproteomics which shows that these organisms are metabolic active. Differential expression of Gene Ontology GOslim terms between the two main microorganisms highlights their metabolic specialization.

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.

Biotransformation of the Fluoroquinolone, Levofloxacin, by the White-Rot Fungus Coriolopsis gallica

The wastewater from hospitals, pharmaceutical industries and more generally human and animal dejections leads to environmental releases of antibiotics that cause severe problems for all living organisms. The aim of this study was to investigate the capacity of three fungal strains to biotransform the fluoroquinolone levofloxacin. The degradation processes were analyzed in solid and liquid media. Among the three fungal strains tested, Coriolopsis gallica strain CLBE55 (BRFM 3473) showed the highest removal efficiency, with a 15% decrease in antibiogram zone of inhibition for Escherichia coli cultured in solid medium and 25% degradation of the antibiotic in liquid medium based on high-performance liquid chromatography (HPLC). Proteomic analysis suggested that laccases and dye-decolorizing peroxidases such as extracellular enzymes could be involved in levofloxacin degradation, with a putative major role for laccases. Degradation products were proposed based on mass spectrometry analysis, and annotation suggested that the main product of biotransformation of levofloxacin by Coriolopsis gallica is an N-oxidized derivative.

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.