A wide variety of microorganisms have intrinsic adapting capability to survive in continuous environmental changes through different strategies.¹ In complementary with genetic engineering, we wish to find a kind of bacteria strain that can naturally live in lactic acid. Adaptative evolution of E coli Nissle 1917 that live on lactic acid are investigated with proteomics and metabolomics tools. On this page, we describe the changes in major signaling pathways that are revealed with large scale proteomics and metabolomics data and bioinformatic tools. E coli Nissle 1917 cells are grown in the culture media without lactic acid (control) or in a concentration of 3 g/L (sample). This concentration has been tested for several times. When the concentration is more than 3 g/L, it is found that bacteria cannot survive. The analysis of sample and control have been repeated three times. They are combined for data analysis.

Proteins extracted from bacteria are digested with trypsin into peptides that are subjected to mass spectrometric analysis on a Thermo Fisher Orbitrap Exploris 240 nano LC-MS mass spectrometer. Proteins are identified with proteome Discover 2.1(Thermo Fisher, USA). The molecular functions and cellular locations are explored with Gene Ontology (GO) and visualized with 'Wu Kong' platform .

In total, 30152 unique peptides that belong to 881 proteins have been identified. There are 800 proteins that are present in the control and the sample with different abundances, respectively. Figure 10 shows that pI values of these proteins range from 4 to 9, in which the sample group shows much higher abundance at pI 5-6 than that of the control group.

Figure 10. Protein expression differences in bacteria living in or not in lactic acid. (A) Identified proteins. (B) pIs of identified proteins.

Principle component analysis (PCA) and volcano plot have been used to visualize the differences in bacteria grown in or not in lactic acid. In Figure 11, PCA analysis reveals that there are significant proteomic changes in bacteria living in 3 g/L lactic acid. Volcano plots are used to summarize the results of differential analysis, representing as scatter plots that show log2fold-change vs statistical significance.

Figure 11. Proteomic changes of bacteria in lactic acid. (A) PCA. (B) Volcano plot.

Figure 12 (A) and (B) shows the up- or down-regulated proteins in response to lactic acid addition, respectively. It indicates that lactic acid significantly increases the metabolic processes ranging from primary metabolic process to organic metabolic process, organic acid metabolic process, carboxylic acid metabolic process and even biosynthetic process. In contrast, lactic acid slows down the intracellular anatomical structure, ribosome and protein folding chaperone.

Figure 12. Gene ontology analysis of proteomic changes of bacteria in lactic acid. (A) Up-regulated. (B) Down-regulated.

Metabolites are extracted from bacteria with t80% methanol. A Thermo Fisher Q Exactive LC-MS mass spectrometer is used for metabolomic analysis. Metabolites are identified with Compound Discovery 3.1(Thermo Fisher, USA) and HMD（https://hmdb.ca/）. Oebiotech is used for visualization. MetaboAnalyst is used for the enrichment of metabolic pathways.

In total, 85 metabolites are identified, in which 23 metabolites are down-regulated and 10 of them notably decrease, 62 metabolites are up-regulated and 58 of them significantly increase. Figure 13 reveals the pathways of aminoacyl-tRNA biosynthesis, riboflavin metabolism, purine metabolism, phenylalanine tyrosine and tryptophan biosynthesis notably increase in response to lactic acid.

Figure 13. Enriched metabolic pathways of bacteria in response to lactic acid.