MSACL 2017 EU Abstract

Metaproteomics for the Clinics: Quick Survey of Microbiota by MS/MS

Jean Armengaud (Presenter)

Authorship: Charlotte Mappa, Olivier Pible, Gérard Steinmetz, Guylaine Miotello, Béatrice Alpha-Bazin, Jean Armengaud
CEA Marcoule, DRF-Li2D, Bagnols-sur-Cèze, France

Short Abstract

Characterizing human microbiota is becoming more and more important in the clinical lab. Metaproteomics aims at exploring the functional pathways present in a complex microbiota, but it may also help to establish an inventory of organisms. Evaluating parameters for tandem mass spectrometry data acquisition and bioinformatics tools for mining metaproteomics datasets is essential to establish the degree of confidence in the results obtained. We propose a microbiota reference standard, namely Mix24X, which may help in optimizing parameters for data acquisition by tandem mass spectrometry and data processing. We propose a cascaded search for interpreting tandem mass spectrometry results consisting in three query cycles that allows minimizing false-positives estimated on an experimental basis. This study paves the way to further normative approach for metaproteomics in the clinical lab.

Long Abstract


The identification and quantitation of micro-organisms present in a complex microbiota is a crucial issue from both medical and environmental points of view. Metaproteomic approaches can help to establish an inventory of organisms present in a sample, and also allows the identificationg and characterization of functional pathways and interactions between microorganisms. Evaluating parameters for tandem mass spectrometry data acquisition and bioinformatics tools for mining metaproteomics datasets is essential to establish the degree of confidence in the results obtained and to improve these pipelines in terms of sensitivity and accuracy. For this, exact but complex references are needed taking into account a large diversity of phylogenetic distances.


Here, we propose a microbiota reference standard assembled with environmental and pathogenic bacteria covering 20 different genera and 5 bacterial phyla. The mixture was normalized for easy and reproducible production of large batches of this reference if required. We also propose several tandem mass spectrometry datasets recorded with this reference. Two nanoLC-MS/MS systems, LTQ-Orbitrap XL (Thermo) and Q-Exactive HF (Thermo), simulate different strategies: from rapid sampling to extremely exhaustive analyzes.


We provide access to the proteome identity cards of each bacterium separately in order to provide the rational bases for evaluating the MS/MS spectra assignment strategy when recorded from complex mixtures. The number of MS/MS detectable peptides present in Mix24X is at least 97,919 unique peptide sequences. Because of co-elution and suppression effects, only a relatively small fraction of these peptides experimentally proven to be present in the mixture can be detected as evaluated with different strategies. We analyzed the different acquired datasets on the reference mixture with the Unipept interface which allows a taxonomical analysis based on identified peptides with the Last Common Ancestor approach. We assessed the sensitivity and specificity of such approach. Based on these results, we propose a cascaded three-round search aimed at minimizing false-positive identification, with databases comprising any genome-sequenced organisms in the first round, identified genera in the second round, and then identified species in the last round. This allows performing species-resolved metaproteomics with the most appropriate pan-proteomics database. This microbiota reference allows defining whether label-free quantitation of organisms is reliable as well as exploring the level of confidence when extracting functional data from large datasets. Next-generation mass spectrometers, such as the Q-Exactive HF instrument based on the ultra-high-field Orbitrap analyzer, quickly generate large datasets. Our results demonstrate the potentialities of such instruments for quickly investigating complex samples such as microbiota.

Conclusions & Discussion

In our opinion, metaproteomics can be judged as highly efficient to quickly estimate the composition of a bacterial sample. Microbiota reference standards such as Mix24X may help in optimizing parameters for data acquisition and processing. The Mix24X resource can be used as control quality standard for both discovery and targeted metaproteomics approaches.

References & Acknowledgements:

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