Identification of Fitness Determinants during Energy-Limited Growth Arrest in Pseudomonas aeruginosa

Abstract

Microbial growth arrest can be triggered by diverse factors, one of which is energy limitation due to scarcity of electron donors or acceptors. Genes that govern fitness during energy-limited growth arrest and the extent to which they overlap between different types of energy limitation are poorly defined. In this study, we exploited the fact that Pseudomonas aeruginosa can remain viable over several weeks when limited for organic carbon (pyruvate) as an electron donor or oxygen as an electron acceptor. ATP values were reduced under both types of limitation, yet more severely in the absence of oxygen. Using transposon-insertion sequencing (Tn-seq), we identified fitness determinants in these two energy-limited states. Multiple genes encoding general functions like transcriptional regulation and energy generation were required for fitness during carbon or oxygen limitation, yet many specific genes, and thus specific activities, differed in their relevance between these states. For instance, the global regulator RpoS was required during both types of energy limitation, while other global regulators such as DksA and LasR were required only during carbon or oxygen limitation, respectively. Similarly, certain ribosomal and tRNA modifications were specifically required during oxygen limitation. We validated fitness defects during energy limitation using independently generated mutants of genes detected in our screen. Mutants in distinct functional categories exhibited different fitness dynamics: regulatory genes generally manifested a phenotype early, whereas genes involved in cell wall metabolism were required later. Together, these results provide a new window into how P. aeruginosa survives growth arrest.

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“…Fluorescent strains used in time-lapse microscopy were made using previously published plasmids 63,67 . Constructs containing GFP and mApple florescent proteins under the control of the ribosomal rpsG gene were inserted in the attTn7 site of P. aeruginosa PA14 ∆phz chromosome by tetra-parental conjugation, followed with selection on VBMM with 100 µg/mL gentamicin 66 .…”

“…S1A. Two aliquots of the P. aeruginosa PA14 transposon library previously prepared 67 Immediately, an aliquot of each sample was diluted to a starting OD500 of ~ 0.05 in 25 mL SMM, followed by outgrowth for ~ 4-5 generations to an OD500 of 0.8-1. After outgrowth, 2.5 mL of each sample was pelleted and stored at -80 ºC.…”

“…Genomic DNA was extracted from the pelleted samples using the DNeasy Blood & Tissue kit (Qiagen). All the steps for sequencing library preparation followed exactly the protocol used by Basta et al 67 , including (i) DNA shearing by sonication (to produce 200-500 bp fragments), (ii) end-repair, (iii) addition of poly(C) tail and (iv) enrichment of transposongenome junctions and addition of adapter for Illumina sequencing by PCR 67,68 . The resulting amplified DNA samples were sequenced using 100 bp single-end reads on the Illumina HiSeq 2500 platform at the Millard and Muriel Jacobs Genetics and Genomics Laboratory at Caltech.…”

“…The resulting amplified DNA samples were sequenced using 100 bp single-end reads on the Illumina HiSeq 2500 platform at the Millard and Muriel Jacobs Genetics and Genomics Laboratory at Caltech. Data analysis also followed Basta et al 67 . In summary, sequences were mapped to the P. aeruginosa UCBPP-PA14 genome sequence using Bowtie 2 69 and were analyzed in MATLAB using the ARTIST Tn-Seq analysis pipeline 70 , with non-overlapping windows of 100 bp across the genome 67,70 .…”

“…In summary, sequences were mapped to the P. aeruginosa UCBPP-PA14 genome sequence using Bowtie 2 69 and were analyzed in MATLAB using the ARTIST Tn-Seq analysis pipeline 70 , with non-overlapping windows of 100 bp across the genome 67,70 . Using Mann-Whitney U statistical test, the total reads mapping for each gene in the "+PYO" samples were compared to the corresponding reads in the "No PYO" control for each replicate independently 67,70 . Next, the read ratio for each replicate was calculated within ARTIST for each gene and then log2-transformed.…”