## Materials and Methods
### Assay of Extracellular and Intracellular Actinorhodin (ACT) Production
lividans_ WT and its _SLI_4383_ deletion mutant grown on R2 YE limited (1 mM) and proficient (5 mM) in phosphate for 48 and 60 h, were alkylated before digestion by Lysyl-Endopeptidase (Wako Chemicals USA) and sequencing-grade-modified trypsin (Promega, Madison, WI, USA). The resulting proteolytic peptides were pre-cleaned, concentrated under vacuum, and stored before mass spectrometry analysis as described previously [22]. Trypsin-generated peptides were analyzed by nanoLC-MSMS using a nanoElute liquid chromatography system (Bruker, Billerica, MA, USA) coupled to a timsTOF pro mass spectrometer (Bruker, Billerica, MA, USA). Then, 1 \(\upmu\)g of protein digest in 2 \(\upmu\)L of loading buffer (2% acetonitrile and 0.05% trifluoroacetic acid in water) were loaded on an Aurora analytical column (ION OPTIK, 25 cm \(\times\) 75 \(\upmu\)m, C18, 1.6 \(\upmu\)m) and eluted with a gradient of 0-35% of solvent B for 100 min. Solvent A was 0.1% formic acid and 2% acetonitrile in water, and solvent B was 99.9% acetonitrile with 0.1% formic acid. MS and MS/MS spectra were recorded from _m/z_ 100 to 1700 with a mobility scan range from 0.6 to 1.5 V-s/cm\({}^{2}\). MS/MS spectra were acquired with the PASEF (parallel accumulation--serial fragmentation (PASEF)) ion mobility-based acquisition mode using a number of PASEF MS/MS scans set as 10. MS and MSMS raw data were processed and converted into mgf files with DataAnalysis software (Bruker, Billerica, MA, USA). Proteins Identifications were performed using the MASCOT search engine (Matrix science, London, UK) against the _S. coelicolor_ and _S. lividans_ protein databases from UniprotKB (15012020). Database searches were performed using trypsin cleavage specificity with two possible miscleavages. Carbamidomethylation of cysteines was set as fixed modification and oxidation of methionines as variable modification. Peptide and fragment tolerances were set at 25 ppm and 0.05 Da, respectively. Proteins were validated when identified with at least two unique peptides. Only ions with a score higher than the identity threshold and a false-positive discovery rate of less than 1% (Mascot decoy option) were considered. Mass spectrometry based-quantification was performed by label-free quantification using either spectral count (SC) or MS1 ion intensities named XIC (for eXtracted Ion Current). For the first method, total MS/MS spectral count values were extracted from Scaffold software (version Scaffold_4.11.1, Proteome software Inc., Portland, OR, USA), filtered with 95% probability and 1% FDR for protein and peptide thresholds, respectively. For the MS1 ion intensity-based method, MS raw files were analyzed with Maxquant software (v 1.6.10.43) using the maxLFQ algorithm with default settings and enabled 4D feature alignment for a more specific quantitative analysis (match between run function including CCS alignment). Normalization was set as default and identifications with Andromeda were performed using the same search parameters as MASCOT. Statistical quantitative analyses were based on two different generalized linear models depending on the type of data. The discrete SC (1) and continuous XIC (2) abundances values were modeled respectively as following:  
(1) SC = \(\mu\) + strain + medium + time + replicate + strain x medium + strain x time + medium x time + strain x medium x time + \(\varepsilon\) - Pois(\(\lambda\));  
(2) Log2(XIC) = \(\mu\) + strain + medium + time + replicate + strain x medium + strain x time + medium x time + strain x medium x time + \(\varepsilon\) - \(\sim\) N(0, \(\sigma\)). Terms represent effect of different conditions and their interactions on protein abundance. Effects were estimated by maximum likelihood and statistical significances were calculated using likelihood ratio test based on the analysis of deviance. \(p\)-values were adjusted using the Benjamini-Hochberg procedure for multiple testing correction.