The color scale corresponds to the number of KO terms of interest involved in each category. To evaluate the effect of the sampling method on the ability to recover functional information, a comparative analysis of the abundance of the microbial protein functions in SS and IS samples was performed.

The relative abundance of KO terms was compared in paired SS and IS samples. A comprehensive understanding of the taxonomy and functionality of the CF airway polymicrobial microbiota could improve infection diagnosis, management, and prediction. We applied an innovative tandem mass-spectrometry-based proteotyping approach to analyze paired spontaneous and induced sputum samples collected from three CF patients, revealing the structure of the microbial communities but also uncovering the microbial functions encoded by the most abundant proteins.

These data illustrate how a quick analysis of sputum samples can be performed to identify and quantify the main taxa and obtain host-related information. Induced or spontaneous sputum samples were shown to be equivalent for this methodology, paving the road for its wide application.

Although a protocol for metaproteomic analysis of CF sputum samples has been previously proposed Graf et al. The protocol described in the present study does not require time-consuming steps of mechanical and enzymatic homogenization, differential centrifugations, and filtrations.

Instead, the protocol is easy to perform and delivers a higher percentage of assigned spectra. Furthermore, compared to DNA extraction and sequencing, either 16S RNA gene amplicons or metagenomics, the tandem mass spectrometry-based proteotyping proposed herein does not introduce amplification bias and delivers the whole panorama of microorganisms present in the sample.

Last, our approach performs more quickly than time-consuming culture-dependent methods that are stochastics per nature and is more comprehensive. Characterizing low biomass clinical microbiome is challenging because of the high abundance of the host signal and the lack of comprehensiveness of the database used for the interpretation.

This last item is not anymore prominent as almost all pathogens and clinically relevant opportunistic microorganisms have publicly available whole-genome sequences. The remaining difficulty, i. While most of these host signals arise from conserved human proteins, whether the list established here could be used for other studies or should be revisited to be more specific of the new samples should be carefully evaluated.

This approach is well adapted for interpreting metaproteomics data without a priori Bassignani et al. Here, we obtained the list of taxa present in the samples at the genus level in most cases, but the precision of the identification can be theoretically increased at the species level as soon as more signals are recorded on the same samples.

sapiens 6 compared to microorganisms 1. The best current practice in metaproteomics recommends informing the protein sequences database with data obtained by metagenomics or 16S rRNA amplicon sequencing performed on the same samples Van Den Bossche et al.

However, this would require i more biological material, while the sputum samples could be difficult to obtain, and ii more time, while quick analysis of clinical samples is of utmost interest for the medical diagnostic.

Our approach involves a sample-specific database construction taxonomically-informed, with the difference that the taxonomical information is from the dataset itself instead of relying on additional metataxonomics or metagenomics data with their own shortcomings.

The most striking characteristic of the methodology is the possibility to estimate the relative abundance of the taxa identified, gaining further insight into the microbial community structure and allowing monitoring its dynamics longitudinally through the comparison of sample profiles.

For this, the low microbial signal quantitation is based on the TSM concept, first described by Pible et al. Because of the development of new quantitation strategies, such as the ones based on data-independent acquisition Aakko et al. When interpreting the recorded signals, host proteins are identified.

Several assigned functions to this host signal were previously and directly linked to the CF -affected airways, such as complement cascade, signaling by interleukins and defective CFTR, apoptotic execution phase and programmed cell death Soleti et al. Among these functionalities, apoptosis and programmed cell death greatly participate to the onset of the disease via multiple mechanisms that could be defective for the neutrophils or increased in epithelial cells, and then constantly contribute to the inflammatory state.

In this context of inflammation and infection, scavenging of heme is important in heme management for heme-iron recycling but also in response to oxidative stress and in vesicle-mediated transport for the reticulum endoplasmic trafficking that are greatly imbalanced.

With these conditions and stresses due to CFTR default that facilitates the colonization of the lung by microbial pathogens and the subsequent potential establishment of chronic infections leading to tissue damage, the airways provide a myriad of mechanisms of defense, notably lung antimicrobial peptides present at the surface of the epithelial cells which are markedly increased to prevent or in response to microbial colonization and infections.

The insights of these functionalities highlighted by the proposed approach could be more deeply analyzed. Clinical CF management is currently based on classical culture-based approaches to identify whether the most common CF pathogens are present in the sputum sample, and quantify them.

However, this a priori approach suffers several limitations despite being a reference method allowing strain recovery and further antimicrobial susceptibility testing. Here, we compared the identified pathogens detected via morphological analysis after a cultivation step of sputum samples in the framework of the microbiological monitoring of CF patients and the tandem mass spectrometry proteotyping.

Above all, our metaproteomics-based approach without a priori allows enlarging the vision of the microbiota representatives including potential pathogenic microorganisms for CF patients and opportunistic ones. With the emergence of new CF pathogens and the identification of unusual species Marchandin, ; Menetrey et al.

The clinical relevance of the taxa detected by our mass spectrometry-based approach remains to be clarified by more extensive and longitudinal studies of the CF lung microbiota. Last but not least, the lung microbiota is a complex microbial ecosystem in which each microorganism may play a key role or become a major player in the course of the infection.

Here, we have specifically pointed out proteins known to be involved in microbial pathogenicity and virulence. Proteins for iron sequestration, flagellar motility and antibiotic resistance, and biofilm growth are all virulence factors that play a major role during bacterial infection to counteract the host defense and clearance mechanisms.

Such operations could be further optimized with specific efforts of industrial development to obtain the results more quickly and automatize the operations. Still, it would not have impacted the comparative analysis of each paired sputum sample.

Conversely, a much larger sample number will be required to investigate and validate the biological significance of the metaproteomics results. In summary, the sputum microbiota of three CF patients presents a personal signature with no significant difference in microbial features and activity in terms of abundance between paired spontaneous and induced sputum samples allowing a comprehensive characterization of the CF microbiota, including bacteria and fungi components, whatever the sampling method.

By applying our innovative metaproteomics-based approach, we can detect the abundant microbial genera, including specific CF pathogens and the less explored and emerging ones. This additional information is a valuable complement to the classical microbiological diagnosis of CF airway infection and can be provided quickly.

This is a major achievement as an unbiased view of the microbiome could be highly complementary and relevant for the clinical management of CF patients and for further personalized and predictive medicine by improving knowledge about the host-pathogen dynamics and CF pathophysiology.

The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE Perez-Riverol et al. The studies involving human participants were reviewed and approved by Centre de Ressources et de Compétences de la Mucoviscidose in the University Hospital of Montpellier France.

JA, RC, and LG designed the study. RC collected the samples and clinical data. PH performed sample preparation for metaproteomic analysis. PH, OP, HM, KC, and LG conceived and performed data and statistical analyses. PH, JA, and LG drafted the manuscript. HM, JA, RC, and LG critically revised the manuscript.

All authors contributed to the article and approved the submitted version. The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

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Bodas, M. Adapting Proteostasis and autophagy for controlling the pathogenesis of cystic fibrosis lung disease. Christie-Oleza, J. Proteomic insights into the lifestyle of an environmentally relevant marine bacterium.

ISME J. Coburn, B. Lung microbiota across age and disease stage in cystic fibrosis. Cuthbertson, L. Lung function and microbiota diversity in cystic fibrosis. Microbiome Dubourg, G. Correlation between sputum and bronchoalveolar lavage fluid cultures.

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The microbiome in cystic fibrosis pulmonary disease Graf, A. An innovative protocol for metaproteomic analyses of microbial pathogens in cystic fibrosis sputum. Grenga, L. Pathogen proteotyping: a rapidly developing application of mass spectrometry to address clinical concerns.

Mass Spectrom. Taxonomical and functional changes in COVID faecal microbiome could be related to SARS-CoV-2 faecal load. Hahn, A. Different next generation sequencing platforms produce different microbial profiles and diversity in cystic fibrosis sputum. Methods , 95— Hardouin, P.

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Apoptosis 18, — Suarez, S. Ribosomal proteins as biomarkers for bacterial identification by mass spectrometry in the clinical microbiology laboratory.

Methods 94, — Tyrrell, J. How to memorize the phrases Why Memorize? My theory of "hook phrases". Lessons Phrases a wide range of For example: You should try to eat a wide range of fruits and vegetables. They had a wide range of different lamps, but none of them really appealed to me. People use it when explaining things.

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Wide Range Samples - تاريخ النشر

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تاريخ النشر المفقودة المدة: Wide Range Samples

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