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

Hardouin, Pauline, Pible, Olivier, Marchandin, Hélène, Culotta, Karen, Armengaud, Jean, Chiron, Raphaël, Grenga, Lucia·2022·Frontiers in Microbiology
DOI 10.3389/fmicb.2022.975883PMC PMC9608366
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Abstract

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.

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Figure 1 Experimental workflow of the study. ① Paired spontaneous and induced sputum samples collected from CF patients were filtered to reduce their viscosity and submitted to differential centrifugation to concentrate the microorganisms. The proteins extracted were submitted to a short in-gel migration and digested into peptides using trypsin. ② The resulting peptides were analyzed by nanoLC-MS/MS. ③ Results were interpreted in a three-step cascaded search to retrieve the taxonomic and functional protein annotations ④.
Figure 1 Experimental workflow of the study. ① Paired spontaneous and induced sputum samples collected from CF patients were filtered to reduce their viscosity and submitted to differential centrifugation to concentrate the microorganisms. The proteins extracted were submitted to a short in-gel migration and digested into peptides using trypsin. ② The resulting peptides were analyzed by nanoLC-MS/MS. ③ Results were interpreted in a three-step cascaded search to retrieve the taxonomic and functional protein annotations ④.CC BY · PubMed Central
Figure 2 Relative protein abundance according to their human, fungal or bacterial origin. The stacked bar graphs show the relative abundance (%) that corresponds to the normalized TSM signals at the genus level from the triplicates of each sample for human signal (orange), fungal taxa (yellow), bacterial taxa (blue) and the non-attributed signals at the taxonomic level of genus (white).
Figure 2 Relative protein abundance according to their human, fungal or bacterial origin. The stacked bar graphs show the relative abundance (%) that corresponds to the normalized TSM signals at the genus level from the triplicates of each sample for human signal (orange), fungal taxa (yellow), bacterial taxa (blue) and the non-attributed signals at the taxonomic level of genus (white).CC BY · PubMed Central
Figure 3 Enrichment functional analysis of the human proteins identified in both induced sputum (IS) and spontaneou sputum (SS) samples from the three patients. The Representative Reactome Gene Sets terms identified by annotating human proteins from SS and IS samples are indicated in blue and orange, respectively. Their relative abundance corresponds to the sum of the normalized spectral abundance factor of each human proteins contributing to the functional reactome terms. (A) Patient 1, (B) Patient 2 and (C) Patient 3.
Figure 3 Enrichment functional analysis of the human proteins identified in both induced sputum (IS) and spontaneou sputum (SS) samples from the three patients. The Representative Reactome Gene Sets terms identified by annotating human proteins from SS and IS samples are indicated in blue and orange, respectively. Their relative abundance corresponds to the sum of the normalized spectral abundance factor of each human proteins contributing to the functional reactome terms. (A) Patient 1, (B) Patient 2 and (C) Patient 3.CC BY · PubMed Central
Figure 4 Relative abundance of microbial taxa at the genus level in spontaneous sputum (SS) versus induced sputum (IS) samples determined following the mass-exclusion list strategy. The relative abundance (%) corresponds to the normalized TSM signals at the genus level. The inner circle indicates the relative abundance of the microbial taxa found in SS sample whereas the outer circle corresponds to the results for IS sample. Each value corresponds to the mean of the analytical triplicates per sample.
Figure 4 Relative abundance of microbial taxa at the genus level in spontaneous sputum (SS) versus induced sputum (IS) samples determined following the mass-exclusion list strategy. The relative abundance (%) corresponds to the normalized TSM signals at the genus level. The inner circle indicates the relative abundance of the microbial taxa found in SS sample whereas the outer circle corresponds to the results for IS sample. Each value corresponds to the mean of the analytical triplicates per sample.CC BY · PubMed Central
Figure 5 Functional annotation of the microbial proteins found in spontaneous and induced sputum samples. The relative abundance of each category corresponds to the sum of the relative abundance of each KEGG Orthology (KO) term of interest of the related category, which is indicated by the size of the dot. The color scale corresponds to the number of KO terms of interest involved in each category.
Figure 5 Functional annotation of the microbial proteins found in spontaneous and induced sputum samples. The relative abundance of each category corresponds to the sum of the relative abundance of each KEGG Orthology (KO) term of interest of the related category, which is indicated by the size of the dot. The color scale corresponds to the number of KO terms of interest involved in each category.CC BY · PubMed Central

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Metadata

Authors
Hardouin, P., Pible, O., Marchandin, H., Culotta, K., Armengaud, J., Chiron, R., & Grenga, L.
Venue
Frontiers in Microbiology
Publisher
Frontiers Media SA
Published
2022-10-13
Volume
13
ISSN
1664-302X
DOI
10.3389/fmicb.2022.975883
PMC
PMC9608366
Cited by
11
References
0
Licence
creativecommons.org/licenses/by/4.0/ (vor)

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