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Branched five carbon (C 5 ) alcohols are attractive targets for microbial production due to their desirable fuel properties and importance as platform chemicals. In this study, we engineered a heterologous isoprenoid pathway in E. coli for the high-yield production of 3-methyl-3-buten-1-ol, 3-methyl-2-buten-1-ol and 3-methyl-1-butanol, three C 5 alcohols that serve as potential biofuels. We first constructed a pathway for 3-methyl-3-buten-1-ol, where metabolite profiling identified NudB, a promiscuous phosphatase, as a likely pathway bottleneck. We achieved a 60% increase in the yield of 3-methyl-3-buten-1-ol by engineering the Shine-Dalgarno sequence of nudB , which increased protein levels by 9-fold and reduced isopentenyl diphosphate (IPP) accumulation by 4-fold. To further optimize the pathway, we adjusted mevalonate kinase (MK) expression and investigated MK enzymes from alternative microbes such as Methanosarcina mazei . Next, we expressed a fusion protein of IPP isomerase and the phosphatase (Idi1~NudB) along with a reductase (NemA) to diversify production to 3-methyl-2-buten-1-ol and 3-methyl-1-butanol. Finally, we used an oleyl alcohol overlay to improve alcohol recovery, achieving final titers of 2.23 g/L of 3-methyl-3-buten-1-ol (~70% of pathway-dependent theoretical yield), 150 mg/L of 3-methyl-2-buten-1-ol and 300 mg/L of 3-methyl-1-butanol.

Acinetobacter baumannii is recognized as an emerging bacterial pathogen because of traits such as prolonged survival in a desiccated state, effective nosocomial transmission, and an inherent ability to acquire antibiotic resistance genes. A pressing need in the field of A. baumannii research is a suitable model strain that is representative of current clinical isolates, is highly virulent in established animal models, and can be genetically manipulated. To identify a suitable strain, a genetically diverse set of recent U.S. military clinical isolates was assessed. Pulsed-field gel electrophoresis and multiplex PCR determined the genetic diversity of 33 A. baumannii isolates. Subsequently, five representative isolates were tested in murine pulmonary and Galleria mellonella models of infection. Infections with one strain, AB5075, were considerably more severe in both animal models than those with other isolates, as there was a significant decrease in survival rates. AB5075 also caused osteomyelitis in a rat open fracture model, while another isolate did not. Additionally, a Tn 5 transposon library was successfully generated in AB5075, and the insertion of exogenous genes into the AB5075 chromosome via Tn 7 was completed, suggesting that this isolate may be genetically amenable for research purposes. Finally, proof-of-concept experiments with the antibiotic rifampin showed that this strain can be used in animal models to assess therapies under numerous parameters, including survival rates and lung bacterial burden. We propose that AB5075 can serve as a model strain for A. baumannii pathogenesis due to its relatively recent isolation, multidrug resistance, reproducible virulence in animal models, and genetic tractability. IMPORTANCE The incidence of A. baumannii infections has increased over the last decade, and unfortunately, so has antibiotic resistance in this bacterial species. A. baumannii is now responsible for more than 10% of all hospital-acquired infections in the United States and has a >50% mortality rate in patients with sepsis and pneumonia. Most research on the pathogenicity of A. baumannii focused on isolates that are not truly representative of current multidrug-resistant strains isolated from patients. After screening of a panel of isolates in different in vitro and in vivo assays, the strain AB5075 was selected as more suitable for research because of its antibiotic resistance profile and increased virulence in animal models. Moreover, AB5075 is susceptible to tetracycline and hygromycin, which makes it amenable to genetic manipulation. Taken together, these traits make AB5075 a good candidate for use in studying virulence and pathogenicity of this species and testing novel antimicrobials. The incidence of A. baumannii infections has increased over the last decade, and unfortunately, so has antibiotic resistance in this bacterial species. A. baumannii is now responsible for more than 10% of all hospital-acquired infections in the United States and has a >50% mortality rate in patients with sepsis and pneumonia. Most research on the pathogenicity of A. baumannii focused on isolates that are not truly representative of current multidrug-resistant strains isolated from patients. After screening of a panel of isolates in different in vitro and in vivo assays, the strain AB5075 was selected as more suitable for research because of its antibiotic resistance profile and increased virulence in animal models. Moreover, AB5075 is susceptible to tetracycline and hygromycin, which makes it amenable to genetic manipulation. Taken together, these traits make AB5075 a good candidate for use in studying virulence and pathogenicity of this species and testing novel antimicrobials.

P. 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. 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 r andom b arcode t ra n sposon seq uencing (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. IMPORTANCE P. 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.

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.

Acinetobacter baumannii is an emerging, nosocomial pathogen that is poorly characterized due to a paucity of genetic tools and methods. While whole genome sequence data from several epidemic and environmental strains have recently become available, the functional characterization of genes is significantly lagging. Efficient transformation is one of the first steps to develop molecular tools that can be used to address these shortcomings. Here we report parameters allowing high efficiency transformation of A. baumannii . Using a multi-factorial experimental design we found that growth phase, voltage, and resistance all significantly contribute to transformation efficiency. The highest efficiency (4.3 × 10 8 Transformants/μg DNA) was obtained at the stationary growth phase of the bacterium (OD 6.0) using 25 ng of plasmid DNA under 100 Ohms resistance and 1.7 kV/cm voltage. The optimized electroporation parameters reported here provide a useful tool for genetic manipulation of A. baumannii.

Despite intensive study, plant lysine catabolism beyond the 2-oxoadipate (2OA) intermediate remains unvalidated. Recently we described a missing step in the D-lysine catabolism of Pseudomonas putida in which 2OA is converted to D-2-hydroxyglutarate (2HG) via hydroxyglutarate synthase (HglS), a DUF1338 family protein. Here we solve the structure of HglS to 1.1 Å resolution in substrate-free form and in complex with 2OA. We propose a successive decarboxylation and intramolecular hydroxylation mechanism forming 2HG in a Fe(II)- and O 2 -dependent manner. Specificity is mediated by a single arginine, highly conserved across most DUF1338 proteins. An Arabidopsis thaliana HglS homolog coexpresses with known lysine catabolism enzymes, and mutants show phenotypes consistent with disrupted lysine catabolism. Structural and biochemical analysis of Oryza sativa homolog FLO7 reveals identical activity to HglS despite low sequence identity. Our results suggest DUF1338-containing enzymes catalyze the same biochemical reaction, exerting the same physiological function across bacteria and eukaryotes. Hydroxyglutarate synthase (HglS) converts 2-oxoadipate to D-2- hydroxyglutarate during lysine catabolism in bacteria. Here the authors use structural and biochemical approaches to show that HglS acts via successive decarboxylation and intramolecular hydroxylation and that homologous enzymes catalyze the final step of lysine catabolism in plants.

Background Despite the latest advancements in metabolic engineering for genome editing and characterization of host performance, the successful development of robust cell factories used for industrial bioprocesses and accurate prediction of the behavior of microbial systems, especially when shifting from laboratory-scale to industrial conditions, remains challenging. To increase the probability of success of a scale-up process, data obtained from thoroughly performed studies mirroring cellular responses to typical large-scale stimuli may be used to derive crucial information to better understand potential implications of large-scale cultivation on strain performance. This study assesses the feasibility to employ a barcoded yeast deletion library to assess genome-wide strain fitness across a simulated industrial fermentation regime and aims to understand the genetic basis of changes in strain physiology during industrial fermentation, and the corresponding roles these genes play in strain performance. Results We find that mutant population diversity is maintained through multiple seed trains, enabling large scale fermentation selective pressures to act upon the community. We identify specific deletion mutants that were enriched in all processes tested in this study, independent of the cultivation conditions, which include MCK1, RIM11, MRK1 , and YGK3 that all encode homologues of mammalian glycogen synthase kinase 3 (GSK-3). Ecological analysis of beta diversity between all samples revealed significant population divergence over time and showed feed specific consequences of population structure. Further, we show that significant changes in the population diversity during fed-batch cultivations reflect the presence of significant stresses. Our observations indicate that, for this yeast deletion collection, the selection of the feeding scheme which affects the accumulation of the fermentative by-product ethanol impacts the diversity of the mutant pool to a higher degree as compared to the pH of the culture broth. The mutants that were lost during the time of most extreme population selection suggest that specific biological processes may be required to cope with these specific stresses. Conclusions Our results demonstrate the feasibility of Bar-seq to assess fermentation associated stresses in yeast populations under industrial conditions and to understand critical stages of a scale-up process where variability emerges, and selection pressure gets imposed. Overall our work highlights a promising avenue to identify genetic loci and biological stress responses required for fitness under industrial conditions.

Although synthetic biology can produce valuable chemicals in a renewable manner, its progress is still hindered by a lack of predictive capabilities. Media optimization is a critical, and often overlooked, process which is essential to obtain the titers, rates and yields needed for commercial viability. Here, we present a molecule- and host-agnostic active learning process for media optimization that is enabled by a fast and highly repeatable semi-automated pipeline. Its application yielded 60% and 70% increases in titer, and 350% increase in process yield in three different campaigns for flaviolin production in Pseudomonas putida KT2440. Explainable Artificial Intelligence techniques pinpointed that, surprisingly, common salt (NaCl) is the most important component influencing production. The optimal salt concentration is very high, comparable to seawater and close to the limits that P. putida can tolerate. The availability of fast Design-Build-Test-Learn (DBTL) cycles allowed us to show that performance improvements for active learning are rarely monotonous. This work illustrates how machine learning and automation can change the paradigm of current synthetic biology research to make it more effective and informative, and suggests a cost-effective and underexploited strategy to facilitate the high titers, rates and yields essential for commercial viability. Media optimization using machine learning increased flaviolin production in Pseudomonas putida , generating counter-intuitive media recipes.

Despite advances in understanding the metabolism of Pseudomonas putida KT2440, a promising bacterial host for producing valuable chemicals from plant-derived feedstocks, a strain capable of producing free fatty acid-derived chemicals has not been developed. Guided by functional genomics, we engineered P. putida to produce medium- and long-chain free fatty acids (FFAs) to titers of up to 670 mg/L. Additionally, by taking advantage of the varying substrate preferences of paralogous native fatty acyl-CoA ligases, we employed a strategy to control FFA chain length that resulted in a P. putida strain specialized in producing medium-chain FFAs. Finally, we demonstrate the production of oleochemicals in these strains by synthesizing medium-chain fatty acid methyl esters, compounds useful as biodiesel blending agents, in various media including sorghum hydrolysate at titers greater than 300 mg/L. This work paves the road to produce high-value oleochemicals and biofuels from cheap feedstocks, such as plant biomass, using this host. Pseudomonas putida has been engineered to produce medium chain length oleochemicals, including medium chain length free fatty acids and their ester forms, compounds which may be useful as biodiesel blending agents.

Agrobacteria are a diverse, polyphyletic group of prokaryotes with multipartite genomes capable of transferring DNA into the genomes of host plants, making them an essential tool in plant biotechnology. Despite their utility in plant transformation, genome-wide transcriptional regulation is not well understood across the three main lineages of agrobacteria. Transcription start sites (TSSs) are a necessary component of gene expression and regulation. In this study, we used differential RNA-seq and a TSS identification algorithm optimized on manually annotated TSS, then validated with existing TSS to identify thousands of TSS with nucleotide resolution for representatives of each lineage. We extend upon the 356 TSSs previously reported in Agrobacterium fabrum C58 by identifying 1,916 TSSs. In addition, we completed genomes and phenotyping of Rhizobium rhizogenes C16/80 and Allorhizobium vitis T60/94, identifying 2,650 and 2,432 TSSs, respectively. Parameter optimization was crucial for an accurate, high-resolution view of genome and transcriptional dynamics, highlighting the importance of algorithm optimization in genome-wide TSS identification and genomics at large. The optimized algorithm reduced the number of TSSs identified internal and antisense to the coding sequence on average by 90.5% and 91.9%, respectively. Comparison of TSS conservation between orthologs of the three lineages revealed differences in cell cycle regulation of ctrA as well as divergence of transcriptional regulation of chemotaxis-related genes when grown in conditions that simulate the plant environment. These results provide a framework to elucidate the mechanistic basis and evolution of pathology across the three main lineages of agrobacteria. Transcription start sites (TSSs) are fundamental for understanding gene expression and regulation. Agrobacteria, a group of prokaryotes with the ability to transfer DNA into the genomes of host plants, are widely used in plant biotechnology. However, the genome-wide transcriptional regulation of agrobacteria is not well understood, especially in less-studied lineages. Differential RNA-seq and an optimized algorithm enabled identification of thousands of TSSs with nucleotide resolution for representatives of each lineage. The results of this study provide a framework for elucidating the mechanistic basis and evolution of pathology across the three main lineages of agrobacteria. The optimized algorithm also highlights the importance of parameter optimization in genome-wide TSS identification and genomics at large.