Ultrafast metaproteomics for quantitative assessment of strain isolates and microbiomes

• Published in: Microchemical journal 2024-12, Vol.207, p.111823, Article 111823
• Main Authors: Kazakova, Elizaveta, Ivanov, Mark, Kusainova, Tomiris, Bubis, Julia, Polivtseva, Valentina, Petrikov, Kirill, Gorshkov, Vladimir, Kjeldsen, Frank, Gorshkov, Mikhail, Delegan, Yanina, Solyanikova, Inna, Tarasova, Irina
• Format: Article
• Language: English
• Subjects: Bacteria; Biodegradation; LC-MS/MS; Metabolic pathways; Metaproteomics; Microbiological methods; Microbiome; Proteomics
• ISSN: 0026-265X
• DOI: 10.1016/j.microc.2024.111823

[Display omitted] •DirectMS1 is a rapid and accurate method for protein quantitation in metaproteomics.•Two-stage search algorithm identifies bacterial species with 95% accuracy, with no information on sample origin.•Microbial composition was resolved at the genus level with a mean difference of 12% between actual and identified contents.•Ultrafast proteomics accurately assesses microbial function, comparable to standard LFQ and TMT methods.•R. erythropolis X5 utilizes distinct genes for n-alkane degradation at 4°C and 28°C, suggesting cold stress adaptation. Microbial communities are essential in human health and environmental regulation, but present a challenge for the analytical science due to their diversity and dynamic range. Tandem mass spectrometry provides functional insights on microbial life cycle, but is time-consuming. MALDI TOF excels in rapid species identification, but not functional assessment. To address critical challenges in human health and environmental sustainability, microbiology needs advanced mass spectrometry methods and bioinformatic tools enabling both rapid identification and accurate assessment of functional activity of microbial communities. We show for the first time that both identity and functional activity of microorganisms and their communities can be accurately determined in experiments as short as 7 min per sample, using the basic Orbitrap MS configuration without peptide fragmentation. The approach was validated using strain isolates, mock microbiomes composed of bacteria spiked at known concentrations and human fecal microbiomes. Our new bioinformatic algorithm identifies the bacterial species with an accuracy of 95 %, when no prior information on the sample is available. Microbiome composition was resolved at the genus level with the mean difference between the actual and identified components of 12 %. For mock microbiomes, Pearson coefficient of up to 0.97 was achieved in estimates of strain biomass change. By the example of Rhodococcus biodegradation of n-alkanes, phenols and its derivatives, we showed the accurate assessment of functional activity of strain isolates, compared with the standard label-free and label-based approaches. Our approach makes microbial proteomics fast, functional and insightful using the Orbitrap instruments even without employing peptide fragmentation technology. The approach can be applied to any microorganisms and can take a niche in routine functional assessment of microbial pathogens