Comparative Proteomic Analysis of Transcriptional and Regulatory Proteins Abundances in S. lividans and S. coelicolor Suggests a Link between Various Stresses and Antibiotic Production

Abstract

Streptomyces coelicolor and Streptomyces lividans constitute model strains to study the regulation of antibiotics biosynthesis in Streptomyces species since these closely related strains possess the same pathways directing the biosynthesis of various antibiotics but only S. coelicolor produces them. To get a better understanding of the origin of the contrasted abilities of these strains to produce bioactive specialized metabolites, these strains were grown in conditions of phosphate limitation or proficiency and a comparative analysis of their transcriptional/regulatory proteins was carried out. The abundance of the vast majority of the 355 proteins detected greatly differed between these two strains and responded differently to phosphate availability. This study confirmed, consistently with previous studies, that S. coelicolor suffers from nitrogen stress. This stress likely triggers the degradation of the nitrogen-rich peptidoglycan cell wall in order to recycle nitrogen present in its constituents, resulting in cell wall stress. When an altered cell wall is unable to fulfill its osmo-protective function, the bacteria also suffer from osmotic stress. This study thus revealed that these three stresses are intimately linked in S. coelicolor. The aggravation of these stresses leading to an increase of antibiotic biosynthesis, the connection between these stresses, and antibiotic production are discussed.

Keywords: Streptomyces; antibiotics; cell wall stress; label-free protein quantification; nitrogen stress; osmotic stress; proteomics.

Figure 1

Heatmap representation of the abundance of components of the transcriptional apparatus of SL and SC that can be divided in 4 sub-clusters a, b, c and d. Cluster a includes 12 proteins rather more abundant in SC than in SL in Pi limitation especially at 60 h. Cluster b includes 16 proteins more abundant in SC than in SL in both Pi conditions. Cluster c includes 7 proteins more abundant in SL than in SC in both Pi conditions. Cluster d includes 4 proteins more abundant in Pi proficiency than in Pi limitation in both strains but mainly at 60 h.

Figure 2

Cluster A, heatmap representation of transcriptional regulators and sensory histidine kinases more abundant in Pi proficiency than in Pi limitation in both strains. Cluster A that can be divided into 3 sub-clusters A1, A2 and A3. Sub-cluster A1 includes 22 regulators rather more abundant in Pi proficiency than in Pi limitation in both strains. The sub-clusters A2 and A3 both include 16 regulators that were similarly abundant in SL and SC in Pi proficiency at both time points but also abundant in SL in Pi limitation at 60 h.

Figure 3

Cluster B, heatmap representation of transcriptional regulators and sensory histidine kinases more abundant in Pi limitation than in Pi proficiency in both strains. Cluster B that can be divided into 3 sub-clusters B1, B2 and B3. Sub-cluster B1 includes 6 proteins more abundant in SC than in SL in both Pi conditions but also abundant in SL in Pi limitation at 48h. Sub-cluster B2 includes 22 proteins more abundant in Pi limitation than in Pi proficiency in both strains. Sub-cluster B3 includes 7 regulators more abundant in Pi limitation than in Pi proficiency at 48 h and 60 h in SL and SC, respectively, and more abundant in SL than in SC in Pi proficiency.

Figure 4

Cluster C, heatmap representation of transcriptional regulators and sensory histidine kinases more abundant in SC than in SL in both Pi conditions.

Figure 5

Cluster D, heatmap representation of transcriptional regulators and sensory histidine kinases more abundant in Pi proficiency than in Pi limitation in SC. Cluster D that can be divided into 3 sub-clusters D1, D2 and D3. The 18 regulators of sub-cluster D1 were more abundant in Pi proficiency than in Pi limitation at both time points in SC but some of them were also abundant in Pi limitation at 48 h in SC. The 18 regulators of sub-cluster D2 were more abundant in Pi proficiency than in Pi limitation at both time points in SC but some of them were also abundant in Pi limitation at 60 h in SL. The 10 regulators of sub-cluster D3 were more abundant in Pi proficiency than in Pi limitation at both time points in SC but some of them were also abundant in Pi limitation at 60 h in SL.

Figure 6

Cluster E, heatmap representation of transcriptional regulators and sensory histidine kinases more abundant in Pi limitation than in Pi proficiency in SC. Cluster E can be divided into 2 sub-clusters, E1 and E2. The 23 regulators of sub-cluster E1 were more abundant in Pi limitation than in Pi proficiency in SC but not in SL. The 7 regulators of sub-cluster E2 were more abundant in Pi limitation than in Pi proficiency in SC but were also abundant at 60 h in Pi proficiency in SL.

Figure 7

Cluster F, heatmap representation of transcriptional regulators and sensory histidine kinases more abundant in SL than in SC in both Pi conditions.

Figure 8

Cluster G, heatmap representation of transcriptional regulators and sensory histidine kinases more abundant in Pi proficiency than in Pi limitation in SL but not in SC.

Figure 9

Cluster H, heatmap representation of transcriptional regulators and sensory histidine kinases more abundant in Pi limitation than in Pi proficiency in SL but not in SC.

Figure 10

Heatmap representation of the abundance of eukaryotic-like serine or threonine protein kinases in SL and SC that can be divided in 3 sub-clusters, a, b and c. The 5 proteins of cluster a were more abundant in SL than in SC in Pi proficiency or limitation. The 11 proteins of cluster b were more abundant in SC than in SL in both Pi conditions. The 7 proteins of cluster c were more abundant in SC than in SL in Pi limitation at both time points but 4 of these proteins were also abundant in Pi limitation, in SL at 48 h.

Figure 11

Schematic representation of the proposed systemic understanding of the relationships between specific physiological and metabolic features of SC and antibiotics production.