Proteomics is the study of the entire set of proteins produced in an organism, system, or biological situation. Compared to DNA or transcripts, proteins are directly linked to phenotypic behaviour. Therefore, expression of proteins is considered a better measure of cellular activity and its comparative analysis often used to obtain valuable information across different cellular states, diseases or organisms. NFML employ LC-MS/MS based label free quantitative proteomics to elucidate the molecular mechanism for a number of biological contexts.

Whole cell proteomics

Here, we use whole cell proteomics to understand the physiology of bacteria with a focus on bacteria relevant in food safety and health, nutrition and industrial applications.

  • Food safety: Use of comparative whole cell proteomics to unravel the mechanism of resistance of various pathogenic microbes to various stress conditions. This informs intervention strategies against these pathogens for effective eradication.
  • Beneficial microbes: Through a combination of both proteomics and bioinformatic analyses we can gain insights to the metabolism of bacteria with various biotechnological applications such as probiotic strains and members of the human gut microbiome. This informs the design and use of such microbes in human nutrition or industrial applications

Biological fluids

We also employ label free quantitative proteomics to assess the molecular changes in various biological fluids or tissues as a result of disease, nutrition or drug intervention.

  • Maternal human milk: We are currently investigating proteomics change sin the human milk from mothers across 4 Asian countries including Korea, Vietnam, China and Pakistan.
  • We also investigate proteomic changes in targeted biological fluids such as serum, post serum, cerebral spinal fluids, etc for both human and animals. This helps yield insights into the efficacy of the interventions and overall physiological response. 

Relevant publications

  • Comparative Whole Cell Proteomics of Listeria monocytogenes at Different Growth Temperatures. J Microbiol Biotechnol 2020, 30(2):259-270.Won S, Lee J, Kim J, Choi H

  • Comparative and bioinformatics analyses of pathogenic bacterial secretomes identified by mass spectrometry in Burkholderia species.Journal of Microbiology 2017, 55(7):568-582.Nguyen TT, Chon T-S, Kim J, Seo Y-S, HeoM.
  • Impact of High-Level Expression of Heterologous Protein on Lactococcus lactis Host. J Microbiol Biotechnol 2017, 27(7):1345-1358.Kim M, Jin Y, An H-J, Kim J:

  • Comparative proteomics: assessment of biological variability and dataset comparability. BMC Bioinformatics 2015, 16(1): 121.Kim SR, Nguyen TV, Seo NR, Jung S, An HJ, Mills DA, Kim JH
  • Proteomic analysis of Bifidobacterium longum subsp. infantis reveals the metabolic insight on consumption of prebiotics and host glycans. PLoS One 2013, 8(2):e57535. Kim J-H, An HJ, Garrido D, German JB, Lebrilla CB, Mills DA.