ஜர்னல் ஆஃப் புரோட்டியோமிக்ஸ் & பயோ இன்ஃபர்மேடிக்ஸ்
திறந்த அணுகல்

சுருக்கம்

Proteomic Effects of Magnesium Stress on Biofilm Associated Proteins Isolated from Cellulolytic Bacillus licheniformis YNP5-TSU

Joshua A O'Hair, Hui Li, Mahesh Rangu, Santosh Thapa, Yong Yang, Tara Fish, Sarabjit Bhatti, Theodore W. Thannhauser, Suping Zhou*

Optimization of cellulase activity is vital for synthesizing the end-products of second generation biofuel production. The slightest change in fermentation parameters can reduce the secretion of necessary enzymes to degrade cellulosic biomass. Determining the ecological effects of certain key media components is essential to understand how bacterial species will respond in a fluid environment. For our experiment a cellulosic media was designed to enhance the industrially important thermophile, Bacillus licheniformis YNP5-TSU. After several attempts to simplify the carboxymethylcellulose (CMC) media composition, impaired biofilm maturation and cellulase activity was noticed. This negative artifact occurred only when magnesium sulphate was removed from media. To analyze the shift in gene expression caused by magnesium stress, biofilm associated proteins were extracted from both control (4.0 mM MgSO₄) and magnesium depleted (0.0 mM MgSO₄) media at 24 hr and 48 hr incubation periods. These proteins were quantified through isobaric labeling and raw data generated from nanoLC-MS/MS identified over 2,000 proteins from the Bacillus licheniformis YNP5-TSU proteome (NCBI accession number MEDD00000000). After statistical normalization and false discovery rate were calculated, a total of 161 proteins from magnesium depleted media and 238 proteins from control media were deemed statistically relevant. A closer look through STRING interconnected webs, data mining, and NCBI annotations revealed several up/down regulated proteins that had linkage to biofilm formation and cellulase secretion. In this study we are able to provide significant evidence that; (1) biofilm maturation and cellulase production are highly correlated and (2), their optimization is dependent on the expression of several key proteins.