Eliminating genes for a two-component system increases PHB productivity in Cupriavidus basilensis 4G11 under PHB suppressing, nonstress conditions.

Species of bacteria from the genus Cupriavidus are known, in part, for their ability to produce high amounts of poly-hydroxybutyrate (PHB) making them attractive candidates for bioplastic production. The native synthesis of PHB occurs during periods of metabolic stress, and the process regulating the initiation of PHB accumulation in these organisms is not fully understood. Screening an RB-TnSeq transposon library of Cupriavidus basilensis 4G11 allowed us to identify two genes of an apparent, uncharacterized two-component system, which when omitted from the genome enable increased PHB productivity in balanced, nonstress growth conditions. We observe average increases in PHB productivity of 56% and 41% relative to the wildtype parent strain upon deleting each gene individually from the genome. The increased PHB phenotype disappears, however, in nitrogen-free unbalanced growth conditions suggesting the phenotype is specific to fast-growing, replete, nonstress growth. Bioproduction modeling suggests this phenotype could be due to a decreased reliance on metabolic stress induced by nitrogen limitation to initiate PHB production in the mutant strains. Due to uncertainty in the two-component system's input signal and regulon, the mechanism by which these genes impart this phenotype remains unclear. Such strains may allow for the use of single-stage, continuous bioreactor systems, which are far simpler than many PHB bioproduction schemes used previously, given a similar product yield to batch systems in such a configuration. Bioproductivity modeling suggests that omitting this regulation in the cells may increase PHB productivity up to 24% relative to the wildtype organism when using single-stage continuous systems. This work expands our understanding of the regulation of PHB accumulation in Cupriavidus, in particular the initiation of this process upon transition into unbalanced growth regimes.

Fatty Acid and Alcohol Metabolism in Pseudomonas putida: Functional Analysis Using Random Barcode Transposon Sequencing.

With its ability to catabolize a wide variety of carbon sources and a growing engineering toolkit, Pseudomonas putida KT2440 is emerging as an important chassis organism for metabolic engineering. Despite advances in our understanding of the organism, many gaps remain in our knowledge of the genetic basis of its metabolic capabilities. The gaps are particularly noticeable in our understanding of both fatty acid and alcohol catabolism, where many paralogs putatively coding for similar enzymes coexist, making biochemical assignment via sequence homology difficult. To rapidly assign function to the enzymes responsible for these metabolisms, we leveraged random barcode transposon sequencing (RB-Tn-Seq). Global fitness analyses of transposon libraries grown on 13 fatty acids and 10 alcohols produced strong phenotypes for hundreds of genes. Fitness data from mutant pools grown on fatty acids of varying chain lengths indicated specific enzyme substrate preferences and enabled us to hypothesize that DUF1302/DUF1329 family proteins potentially function as esterases. From the data, we also postulate catabolic routes for the two biogasoline molecules isoprenol and isopentanol, which are catabolized via leucine metabolism after initial oxidation and activation with coenzyme A (CoA). Because fatty acids and alcohols may serve as both feedstocks and final products of metabolic-engineering efforts, the fitness data presented here will help guide future genomic modifications toward higher titers, rates, and yields.IMPORTANCE To engineer novel metabolic pathways into P. putida, a comprehensive understanding of the genetic basis of its versatile metabolism is essential. Here, we provide functional evidence for the putative roles of hundreds of genes involved in the fatty acid and alcohol metabolism of the bacterium. These data provide a framework facilitating precise genetic changes to prevent product degradation and to channel the flux of specific pathway intermediates as desired.

Omics-driven identification and elimination of valerolactam catabolism in Pseudomonas putida KT2440 for increased product titer.

Pseudomonas putida is a promising bacterial chassis for metabolic engineering given its ability to metabolize a wide array of carbon sources, especially aromatic compounds derived from lignin. However, this omnivorous metabolism can also be a hindrance when it can naturally metabolize products produced from engineered pathways. Herein we show that P. putida is able to use valerolactam as a sole carbon source, as well as degrade caprolactam. Lactams represent important nylon precursors, and are produced in quantities exceeding one million tons per year (Zhang et al., 2017). To better understand this metabolism we use a combination of Random Barcode Transposon Sequencing (RB-TnSeq) and shotgun proteomics to identify the oplBA locus as the likely responsible amide hydrolase that initiates valerolactam catabolism. Deletion of the oplBA genes prevented P. putida from growing on valerolactam, prevented the degradation of valerolactam in rich media, and dramatically reduced caprolactam degradation under the same conditions. Deletion of oplBA, as well as pathways that compete for precursors L-lysine or 5-aminovalerate, increased the titer of valerolactam from undetectable after 48 h of production to ~90 mg/L. This work may serve as a template to rapidly eliminate undesirable metabolism in non-model hosts in future metabolic engineering efforts.

Massively Parallel Fitness Profiling Reveals Multiple Novel Enzymes in Pseudomonas putida Lysine Metabolism.

Despite intensive study for 50 years, the biochemical and genetic links between lysine metabolism and central metabolism in Pseudomonas putida remain unresolved. To establish these biochemical links, we leveraged random barcode transposon sequencing (RB-TnSeq), a genome-wide assay measuring the fitness of thousands of genes in parallel, to identify multiple novel enzymes in both l- and d-lysine metabolism. We first describe three pathway enzymes that catabolize l-2-aminoadipate (l-2AA) to 2-ketoglutarate (2KG), connecting d-lysine to the TCA cycle. One of these enzymes, P. putida 5260 (PP_5260), contains a DUF1338 domain, representing a family with no previously described biological function. Our work also identified the recently described coenzyme A (CoA)-independent route of l-lysine degradation that results in metabolization to succinate. We expanded on previous findings by demonstrating that glutarate hydroxylase CsiD is promiscuous in its 2-oxoacid selectivity. Proteomics of selected pathway enzymes revealed that expression of catabolic genes is highly sensitive to the presence of particular pathway metabolites, implying intensive local and global regulation. This work demonstrated the utility of RB-TnSeq for discovering novel metabolic pathways in even well-studied bacteria, as well as its utility a powerful tool for validating previous research.IMPORTANCEP. putida lysine metabolism can produce multiple commodity chemicals, conferring great biotechnological value. Despite much research, the connection of lysine catabolism to central metabolism in P. putida remained undefined. Here, we used random barcode transposon sequencing to fill the gaps of lysine metabolism in P. putida We describe a route of 2-oxoadipate (2OA) catabolism, which utilizes DUF1338-containing protein P. putida 5260 (PP_5260) in bacteria. Despite its prevalence in many domains of life, DUF1338-containing proteins have had no known biochemical function. We demonstrate that PP_5260 is a metalloenzyme which catalyzes an unusual route of decarboxylation of 2OA to d-2-hydroxyglutarate (d-2HG). Our screen also identified a recently described novel glutarate metabolic pathway. We validate previous results and expand the understanding of glutarate hydroxylase CsiD by showing that can it use either 2OA or 2KG as a cosubstrate. Our work demonstrated that biological novelty can be rapidly identified using unbiased experimental genetics and that RB-TnSeq can be used to rapidly validate previous results.

A rapid methods development workflow for high-throughput quantitative proteomic applications.

Recent improvements in the speed and sensitivity of liquid chromatography-mass spectrometry systems have driven significant progress toward system-wide characterization of the proteome of many species. These efforts create large proteomic datasets that provide insight into biological processes and identify diagnostic proteins whose abundance changes significantly under different experimental conditions. Yet, these system-wide experiments are typically the starting point for hypothesis-driven, follow-up experiments to elucidate the extent of the phenomenon or the utility of the diagnostic marker, wherein many samples must be analyzed. Transitioning from a few discovery experiments to quantitative analyses on hundreds of samples requires significant resources both to develop sensitive and specific methods as well as analyze them in a high-throughput manner. To aid these efforts, we developed a workflow using data acquired from discovery proteomic experiments, retention time prediction, and standard-flow chromatography to rapidly develop targeted proteomic assays. We demonstrated this workflow by developing MRM assays to quantify proteins of multiple metabolic pathways from multiple microbes under different experimental conditions. With this workflow, one can also target peptides in scheduled/dynamic acquisition methods from a shotgun proteomic dataset downloaded from online repositories, validate with appropriate control samples or standard peptides, and begin analyzing hundreds of samples in only a few minutes.