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Abstract Pseudomonas aeruginosa is a major contributor to human infections and is widely distributed in the environment. Its ability for growth under aerobic and anaerobic conditions provides adaptability to environmental changes and in confronting immune responses. We applied native 2-dimensional metalloproteomics to P. aeruginosa to examine how use of iron within the metallome responds to oxic and anoxic conditions. Analyses revealed four iron peaks comprised of metalloproteins with synergistic functions, including (1) respiratory and metabolic enzymes, (2) oxidative stress response enzymes, (3) DNA synthesis and nitrogen assimilation enzymes, and (4) denitrification enzymes and related copper enzymes. Fe Peaks were larger under anoxic conditions, consistent with increased iron demand due to anaerobic metabolism and with the denitrification peak absent under oxic conditions. Three ferritins co-eluted with the first and third iron peaks, localizing iron storage with these functions. Several enzymes were more abundant at low oxygen, including alkylhydroperoxide reductase C that deactivates organic radicals produced by denitrification, all three classes of ribonucleotide reductases (including monomer and oligomer forms), ferritin (increasing in ratio relative to bacterioferritin), and denitrification enzymes. Superoxide dismutase and homogentisate 1,2-dioxygenase were more abundant at high oxygen. Several Fe Peaks contained iron metalloproteins that co-eluted earlier than their predicted size, implying additional protein–protein interactions and suggestive of cellular organization that contributes to iron prioritization in Pseudomonas with its large genome and flexible metabolism. This study characterized the iron metalloproteome of one of the more complex prokaryotic microorganisms, attributing enhanced iron use under anaerobic denitrifying metabolism to its specific metalloprotein constituents. 

Abstract The remarkable pace of genomic data generation is rapidly transforming our understanding of life at the micron scale. Yet this data stream also creates challenges for team science. A single microbe can have multiple versions of genome architecture, functional gene annotations, and gene identifiers; additionally, the lack of mechanisms for collating and preserving advances in this knowledge raises barriers to community coalescence around shared datasets. “Digital Microbes” are frameworks for interoperable and reproducible collaborative science through open source, community-curated data packages built on a (pan)genomic foundation. Housed within an integrative software environment, Digital Microbes ensure real-time alignment of research efforts for collaborative teams and facilitate novel scientific insights as new layers of data are added. Here we describe two Digital Microbes: 1) the heterotrophic marine bacteriumRuegeria pomeroyiDSS-3 with > 100 transcriptomic datasets from lab and field studies, and 2) the pangenome of the cosmopolitan marine heterotrophAlteromonascontaining 339 genomes. Examples demonstrate how an integrated framework collating public (pan)genome-informed data can generate novel and reproducible findings.