Dataset Information

Free-Flow Isoelectric Focusing Based Metaproteomics Workflow Facilitates the Identification and Characterization of Human Salivary Microbiome for Lung Cancer

ABSTRACT: We developed a free-flow isoelectric focusing (FFIEF) based metaproteomics workflow to reduce the host interferences and enrich the low-abundant bacteria for better interpretation of salivary microbiome. We firstly tested the pretreatment module that could significantly reduce the host interferences by differential centrifugation and filtration. Then the FFIEF module was applied to separate the microbes and enrich the low-abundant bacteria, which showed a significant improvement in the identification efficiency of microbiome sample. Applying our method to lung cancer, we successfully identified Fusobacterium, Neisseriaceae, Actinomycetaceae, Burkholderiales, and Spirochaetia were associated with lung cancer as previous sequencing studies did, along with other 16 significantly different species. The dysregulated functions in lung cancer microbiome were also explained in details. Our workflow provides improved efficiency in identification and characterization of the salivary microbiome with great reproducibility. The ability of enriching low-abundant bacteria and functions enables in-deep analysis of previously underestimated information.

INSTRUMENT(S): Q Exactive Plus

ORGANISM(S): Human Saliva Metagenome

TISSUE(S): Saliva

DISEASE(S): Lung Cancer

SUBMITTER: xiaoteng Jiang

LAB HEAD: Hua Xiao

PROVIDER: PXD026727 | Pride | 2022-11-17

REPOSITORIES: Pride

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Publications

In-Depth Metaproteomics Analysis of Oral Microbiome for Lung Cancer.

Jiang Xiaoteng X Zhang Yan Y Wang Huiyu H Wang Zeyuan Z Hu Shen S Cao Chengxi C Xiao Hua H

Research (Washington, D.C.) 20221013

The human oral microbiome correlates with numerous diseases, including lung cancer. Identifying the functional changes by metaproteomics helps understand the disease-related dysbiosis, yet characterizing low-abundant bacteria is challenging. Here, we developed a free-flow isoelectric focusing electrophoresis-mass spectrometry- (FFIEF-MS-) based metaproteomics strategy to reduce host interferences and enrich low-abundant bacteria for in-depth interpretation of the oral microbiome. With our method ...[more]

PMID: 36320634

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Project description:Background: The microbiome is increasingly being linked to cancer risk. Little is known about the lung and oral cavity microbiomes in healthy smokers (SM), and even less for electronic cigarette (EC) users, compared healthy never-smokers (NS). Methods: In a cross-sectional pilot study of SM (N=8), EC users (N=10) and NS (N=10) saliva and bronchoscopy-collected bronchoalveolar lavage samples were collected. Bacteria species were identified through metatranscriptome profiling by RNA-sequencing to study associations with the lung and oral microbiome. Pairwise comparisons and linear modeling was assessed with false discovery rates <0.1. Results: Total bacterial load was similar for the SM, EC users and NS, and there was no differences in the bacterial diversity across groups. In the lung, there were 44 bacterial species that were statistically significantly different for SM/NS, 80% of which were decreased in the SM. There were 12 bacterial species that were different for SM/EC users, all of which were decreased, 10 of which were also identified in the SM/NS comparison. The 2 bacterial species unique to SM/EC comparison were Neisseria sp. KEM232 and Curvibacter sp. AEP1-3. From the top 5 decreased species in SM/EC, 3 were also identified in the SM/NS comparison (Neisseria elongata, Neisseria sicca, and Haemophilus parainfluenzae) and 2 of these were unique to the SM/EC comparison (Neisseria zoodegmatis and Ottowia sp. oral taxon 894). There were 8 species increased in SM compared to NS, none of which are known to be clinically significant. In the oral microbiome, 152 bacteria species were differentially abundant for the SM/NS analysis, and only 17 for the EC/NS comparison, all which were also present in SM/NS comparisons. There were 21 bacteria that were differentially abundant in both the lung and oral cavity for SM and NS, 95% also were decreased in the SM. Conclusion: Smoking and EC use do not appear to materially affect the lung microbiome, although differences are noted of unclear clinical significance. Most differentially abundant bacteria decreased, which may be due to a toxic effect of cigarette smoke, including a change in humidity or heating. Given the low number of overlapping oral and lung microbes, the oral microbiome does not appear to be a good surrogate for smoking-related effects in the lung.

Dataset Information

Free-Flow Isoelectric Focusing Based Metaproteomics Workflow Facilitates the Identification and Characterization of Human Salivary Microbiome for Lung Cancer

Publications

In-Depth Metaproteomics Analysis of Oral Microbiome for Lung Cancer.

Similar Datasets

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