4.6 Article

In-Depth Metaproteomics Analysis of Oral Microbiome for Lung Cancer

Journal

RESEARCH
Volume 2022, Issue -, Pages -

Publisher

AMER ASSOC ADVANCEMENT SCIENCE
DOI: 10.34133/2022/9781578

Keywords

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Funding

  1. Natural Science Foundation of Shanghai [21ZR1433200, 19ZR1427800]
  2. National Key Research and Development Programof China [2017YFC1200204]
  3. National Natural Science Foundation of China [21675110, 31727801]
  4. Key Scientific Project of Shanghai Jiao Tong University [TMSK-2020-130, YG2017MS80]

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This study developed a new metaproteomics strategy that reduces host interferences and enriches low-abundant bacteria for a more comprehensive understanding of the oral microbiome. By using this method, the researchers identified the most comprehensive oral metaproteome to date and revealed the dysregulated functions of lung cancer-associated bacteria. This study is significant for studying the mechanisms between human diseases and microbiomes.
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, the number of interfering peptides decreased by 52.87%, whereas the bacterial peptides and species increased by 94.97% and 44.90%, respectively, compared to the conventional metaproteomics approach. We identified 3647 bacterial proteins, which is the most comprehensive oral metaproteomics study to date. Lung cancer-associated bacteria were validated among an independent cohort. The imbalanced Fusobacterium nucleatum and Prevotella histicola and their dysregulated functions in inhibiting immune response and maintaining cell redox homeostasis were revealed. The FFIEF-MS may serve as a valuable strategy to study the mechanisms between human diseases and microbiomes with broader applications.

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