Overview Analysis of Proteome Sequencing Data Protein Functional Annotation Analysis Differential protein analysis Differential Protein GO Functional Enrichment Analysis Functional enrichment analysis of the differential protein KEGG Transcriptomics and proteomics association analysis

Overview

In biology, we are clear that proteins are the embodiment of the true function of an organism, so proteomics is indispensable for the study of biological function level.

In our experiment, we screened the differentially expressed proteins of bacterial salinity tolerance along with the transcriptomics study, and analysed the significantly enriched pathways of the differentially expressed proteins.

We have laid the foundation for the functional molecular mining of six saline-tolerant bacteria of different genera sharing saline environment.

Analysis of Proteome Sequencing Data

In this section, we analyzed the data obtained from protein sequencing.

The flow of the information analysis is shown in Fig. 4.2.

Fig 4.2 TMT proteome data analysis process

Protein Functional Annotation Analysis

The statistical results of the functional annotations of the protein sequences identified by the four databases are shown in Figure 4.3.

Fig 4.3 Annotated venn diagram of the four major protein databases of salinity-tolerant strains (a:B.caseiG20,b:B.haynesii P19,c:M.luteus R17,d:H.bluephagenesis TD01,e:H. campaniensis LS21,f:E.cloacae RS35)

Protein quantification

PCA analysis (Figure 4.4) was performed to find out the overall protein difference between the samples of each strain under normal saline conditions (Group Z) and high saline conditions (Group G) and the magnitude of variability between the samples within the groups.

The horizontal coordinate PC1 in the graph explains the variance information for each sample of the six strains of bacteria 58.94% (Fig. 4.4a), 81.88% (Fig. 4.4b), 54.9% (Fig. 4.4c), 81.57% (Fig. 4.4d), 79.94% (Fig. 4.4e) and 72.49% (Fig. 4.4f). We can see that the intergroup samples of each strain are more dispersed and the intragroup samples are more clustered, which indicates that the reproducibility of the samples of each strain is good, and the protein differences between groups G and Z are large.

Fig 4.4 Inter-sample PCA map(a:B.casei G20,b:B.haynesii P19,c:M.luteus R17,d:H.bluephagenesis TD01,e:H.campaniensis LS21,f:E.cloacae RS35)

Differential protein analysis

The number of up- and down-regulated proteins obtained from the screening of six strains of salinity-tolerant bacteria in different saline environments under different FC and p-value conditions is shown in Table 4.2, using p < 0.05 and the multiplicity of difference FC as the threshold of significance for the screening of differential proteins.

Table 4.2 Number of differential proteins insalinity-tolerant strains

There were 178, 843, 439, 700, 840 and 561 up-regulated differential proteins in the six strains of salinity-tolerant bacteria, and 299, 2022, 474, 689, 759 and 1296 down-regulated differential proteins.

Differential Protein GO Functional Enrichment Analysis

In order to determine which biological functions the differential proteins were significantly associated with. The results of the enrichment screening of DEPs for the six strains of Bacteria Group Z and Group G are shown in Table 4.3.

Table 4.3 GO enrichment entry statistics table

Based on the enrichment results, we drew bar graphs of significantly enriched GO functions.

Overall, salinity-tolerant bacteria adapt to high salinity stress environments by inhibiting intracellular macromolecule metabolism, avoiding transport, localization, and motility, reducing cytoplasmic organelle composition, and decreasing structural molecule viability.

Fig 4.6 Differential proteins GO enrichment barchart of B.casei G20

Fig 4.7 Differential proteins GO enrichment barchart of B.haynesiiP19

Fig 4.8 Differential proteins GO enrichment barchart of M.luteusR17

Fig 4.9 Differential proteins GO enrichment barchart of E.cloacaeRS35

Fig 4.10 Differential proteins GO enrichment barchart of H.bluephagenesisTD01

Fig 4.11 Differential proteins GO enrichment barchart of H.campaniensisLS21

Functional enrichment analysis of the differential protein KEGG

We wanted to identify the most important biochemical metabolic pathways and signaling pathways involved in differential proteins of six strains of saline-tolerant bacteria under different saline conditions, so KEGG Pathway enrichment analysis was performed.The results of the enrichment numbers are summarized in Table 4.4.

Table 4.4 KEGG enrichment entry statistics table

Bubble plots of the pathways of significant enrichment of proteins in the six salinity-tolerant bacteria were characterized by each of the six pathways of significant enrichment of up- and down-regulated DEPs, and the results were as follows.

Fig 4.12 Differential proteins KEGG enrichment bubble map of B.caseiG20(a:up-regulated DEPs,b:down-regulatedDEPs)

Fig4.13 DifferentialproteinsKEGGenrichmentbubblemapofB.haynesiiP19(a:up-regulated DEPs,b:down-regulatedDEPs)

Fig 4.14 Differential proteins KEGG enrichment bubble map of M.luteusR17(a:up-regulated DEPs,b:down-regulatedDEPs)

Fig 4.15 Differential proteins KEGG enrichment bubble map of H.bluephagenesis TD01(a:up-regulated DEPs,b:down-regulatedDEPs)

Combined with the results of significant enrichment of down-regulated proteins in six strains of salinity-tolerant bacteria, it was found that multiple KEGG metabolic pathways were enriched by more than one strain under salinity stress.

Overall, the differentially expressed proteins of the six strains of B. salinarum were enriched in ABC transporter, bacterial chemotaxis, two-component system, amino acid metabolism, flagellar assembly and sulfur metabolism, indicating that the regulation of the above metabolic pathways played an important role in the response to saline and alkaline stresses by B. salinarum.

Transcriptomics and proteomics association analysis

Analysis of transcriptome and proteome expression regulation

We integrated the mRNA information obtained from the transcriptome data of the six salinity-tolerant bacterial strains with the protein information obtained from proteome identification to find out the relationship of consistent expression (see Figure 4.18). It is known that B. casei G20, B. haynesii P19, M. luteus R17, H. bluphagenesis TD01, H. campaniensis LS21, and E. cloacae RS35 have 23, 133, 14, 312, 88, and 240 genes, respectively, that are differentially expressed in the transcriptome and the proteome together. genes expressed in the transcriptome and proteome, respectively.

Fig 4.18 Venn diagram of transcriptome and proteome expression regulation(a:B.caseiG20,b: B.haynesiiP19,c:M.luteusR17,d:H.bluephagenesisTD01,e:H.campaniensisLS21,f:E. cloacaeRS35)

Fig 4.19 Scatter plot of transcriptome and proteome expression association analysis(a:B. caseiG20,b:B.haynesiiP19,c:M.luteusR17,d:H.bluephagenesisTD01,e:H.campaniensis LS21,f:E.cloacaeRS35)

GO and KEGG functional clustering analysis

In order to analyze what functions the differentially expressed proteins (genes) shared by the proteome and transcriptome of each strain mentioned in 4.3.7.1 have in response to salinity stress, GO and KEGG entries enriched for proteins (genes) differentially expressed in both the proteome and transcriptome of the six strains were collated using P and |log2FC| as the screening thresholds and the results are shown in Table 4.5 and Table 4.6.

Table 4.5 Co-differentially expressed protein (gene) enrichment GO entries

Continued Table 4.5 Enrichment of GO entries for co-differentially expressed proteins (genes)

Table 4.6 Co-differentially expressed protein (gene)enrichment KEGG entries

This suggests that saline-tolerant bacteria alter their metabolic processes and biochemical reactions under extreme saline environments, and that they can better survive in high saline environments through cellular synergistic regulation and signal transduction.