The energy metabolism of Cupriavidus necator in different trophic conditions.

The "knallgas" bacterium Cupriavidus necator is attracting interest due to its extremely versatile metabolism. C. necator can use hydrogen or formic acid as an energy source, fixes CO2 via the Calvin-Benson-Bassham (CBB) cycle, and grows on organic acids and sugars. Its tripartite genome is notable for its size and duplications of key genes (CBB cycle, hydrogenases, and nitrate reductases). Little is known about which of these isoenzymes and their cofactors are actually utilized for growth on different substrates. Here, we investigated the energy metabolism of C. necator H16 by growing a barcoded transposon knockout library on succinate, fructose, hydrogen (H2/CO2), and formic acid. The fitness contribution of each gene was determined from enrichment or depletion of the corresponding mutants. Fitness analysis revealed that (i) some, but not all, molybdenum cofactor biosynthesis genes were essential for growth on formate and nitrate respiration. (ii) Soluble formate dehydrogenase (FDH) was the dominant enzyme for formate oxidation, not membrane-bound FDH. (iii) For hydrogenases, both soluble and membrane-bound enzymes were utilized for lithoautotrophic growth. (iv) Of the six terminal respiratory complexes in C. necator H16, only some are utilized, and utilization depends on the energy source. (v) Deletion of hydrogenase-related genes boosted heterotrophic growth, and we show that the relief from associated protein cost is responsible for this phenomenon. This study evaluates the contribution of each of C. necator's genes to fitness in biotechnologically relevant growth regimes. Our results illustrate the genomic redundancy of this generalist bacterium and inspire future engineering strategies.IMPORTANCEThe soil bacterium Cupriavidus necator can grow on gas mixtures of CO2, H2, and O2. It also consumes formic acid as carbon and energy source and various other substrates. This metabolic flexibility comes at a price, for example, a comparatively large genome (6.6 Mb) and a significant background expression of lowly utilized genes. In this study, we mutated every non-essential gene in C. necator using barcoded transposons in order to determine their effect on fitness. We grew the mutant library in various trophic conditions including hydrogen and formate as the sole energy source. Fitness analysis revealed which of the various energy-generating iso-enzymes are actually utilized in which condition. For example, only a few of the six terminal respiratory complexes are used, and utilization depends on the substrate. We also show that the protein cost for the various lowly utilized enzymes represents a significant growth disadvantage in specific conditions, offering a route to rational engineering of the genome. All fitness data are available in an interactive app at https://m-jahn.shinyapps.io/ShinyLib/.

Rhizobium determinants of rhizosphere persistence and root colonization.

Bacterial persistence in the rhizosphere and colonization of root niches are critical for the establishment of many beneficial plant-bacteria interactions including those between Rhizobium leguminosarum and its host legumes. Despite this, most studies on R. leguminosarum have focused on its symbiotic lifestyle as an endosymbiont in root nodules. Here, we use random barcode transposon sequencing to assay gene contributions of R. leguminosarum during competitive growth in the rhizosphere and colonization of various plant species. This facilitated the identification of 189 genes commonly required for growth in diverse plant rhizospheres, mutation of 111 of which also affected subsequent root colonization (rhizosphere progressive), and a further 119 genes necessary for colonization. Common determinants reveal a need to synthesize essential compounds (amino acids, ribonucleotides, and cofactors), adapt metabolic function, respond to external stimuli, and withstand various stresses (such as changes in osmolarity). Additionally, chemotaxis and flagella-mediated motility are prerequisites for root colonization. Many genes showed plant-specific dependencies highlighting significant adaptation to different plant species. This work provides a greater understanding of factors promoting rhizosphere fitness and root colonization in plant-beneficial bacteria, facilitating their exploitation for agricultural benefit.

Machine learning analysis of RB-TnSeq fitness data predicts functional gene modules in Pseudomonas putida KT2440.

There is growing interest in engineering Pseudomonas putida KT2440 as a microbial chassis for the conversion of renewable and waste-based feedstocks, and metabolic engineering of P. putida relies on the understanding of the functional relationships between genes. In this work, independent component analysis (ICA) was applied to a compendium of existing fitness data from randomly barcoded transposon insertion sequencing (RB-TnSeq) of P. putida KT2440 grown in 179 unique experimental conditions. ICA identified 84 independent groups of genes, which we call fModules ("functional modules"), where gene members displayed shared functional influence in a specific cellular process. This machine learning-based approach both successfully recapitulated previously characterized functional relationships and established hitherto unknown associations between genes. Selected gene members from fModules for hydroxycinnamate metabolism and stress resistance, acetyl coenzyme A assimilation, and nitrogen metabolism were validated with engineered mutants of P. putida. Additionally, functional gene clusters from ICA of RB-TnSeq data sets were compared with regulatory gene clusters from prior ICA of RNAseq data sets to draw connections between gene regulation and function. Because ICA profiles the functional role of several distinct gene networks simultaneously, it can reduce the time required to annotate gene function relative to manual curation of RB-TnSeq data sets. IMPORTANCE: This study demonstrates a rapid, automated approach for elucidating functional modules within complex genetic networks. While Pseudomonas putida randomly barcoded transposon insertion sequencing data were used as a proof of concept, this approach is applicable to any organism with existing functional genomics data sets and may serve as a useful tool for many valuable applications, such as guiding metabolic engineering efforts in other microbes or understanding functional relationships between virulence-associated genes in pathogenic microbes. Furthermore, this work demonstrates that comparison of data obtained from independent component analysis of transcriptomics and gene fitness datasets can elucidate regulatory-functional relationships between genes, which may have utility in a variety of applications, such as metabolic modeling, strain engineering, or identification of antimicrobial drug targets.

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.

Evaluating E. coli genome-scale metabolic model accuracy with high-throughput mutant fitness data.

The Escherichia coli genome-scale metabolic model (GEM) is an exemplar systems biology model for the simulation of cellular metabolism. Experimental validation of model predictions is essential to pinpoint uncertainty and ensure continued development of accurate models. Here, we quantified the accuracy of four subsequent E. coli GEMs using published mutant fitness data across thousands of genes and 25 different carbon sources. This evaluation demonstrated the utility of the area under a precision-recall curve relative to alternative accuracy metrics. An analysis of errors in the latest (iML1515) model identified several vitamins/cofactors that are likely available to mutants despite being absent from the experimental growth medium and highlighted isoenzyme gene-protein-reaction mapping as a key source of inaccurate predictions. A machine learning approach further identified metabolic fluxes through hydrogen ion exchange and specific central metabolism branch points as important determinants of model accuracy. This work outlines improved practices for the assessment of GEM accuracy with high-throughput mutant fitness data and highlights promising areas for future model refinement in E. coli and beyond.

Large-scale genetic characterization of the model sulfate-reducing bacterium, Desulfovibrio vulgaris Hildenborough.

Sulfate-reducing bacteria (SRB) are obligate anaerobes that can couple their growth to the reduction of sulfate. Despite the importance of SRB to global nutrient cycles and their damage to the petroleum industry, our molecular understanding of their physiology remains limited. To systematically provide new insights into SRB biology, we generated a randomly barcoded transposon mutant library in the model SRB Desulfovibrio vulgaris Hildenborough (DvH) and used this genome-wide resource to assay the importance of its genes under a range of metabolic and stress conditions. In addition to defining the essential gene set of DvH, we identified a conditional phenotype for 1,137 non-essential genes. Through examination of these conditional phenotypes, we were able to make a number of novel insights into our molecular understanding of DvH, including how this bacterium synthesizes vitamins. For example, we identified DVU0867 as an atypical L-aspartate decarboxylase required for the synthesis of pantothenic acid, provided the first experimental evidence that biotin synthesis in DvH occurs via a specialized acyl carrier protein and without methyl esters, and demonstrated that the uncharacterized dehydrogenase DVU0826:DVU0827 is necessary for the synthesis of pyridoxal phosphate. In addition, we used the mutant fitness data to identify genes involved in the assimilation of diverse nitrogen sources and gained insights into the mechanism of inhibition of chlorate and molybdate. Our large-scale fitness dataset and RB-TnSeq mutant library are community-wide resources that can be used to generate further testable hypotheses into the gene functions of this environmentally and industrially important group of bacteria.

Construction and characterization of a genome-scale ordered mutant collection of Bacteroides thetaiotaomicron.

BACKGROUND: Ordered transposon-insertion collections, in which specific transposon-insertion mutants are stored as monocultures in a genome-scale collection, represent a promising tool for genetic dissection of human gut microbiota members. However, publicly available collections are scarce and the construction methodology remains in early stages of development. RESULTS: Here, we describe the assembly of a genome-scale ordered collection of transposon-insertion mutants in the model gut anaerobe Bacteroides thetaiotaomicron VPI-5482 that we created as a resource for the research community. We used flow cytometry to sort single cells from a pooled library, located mutants within this initial progenitor collection by applying a pooling strategy with barcode sequencing, and re-arrayed specific mutants to create a condensed collection with single-insertion strains covering >2500 genes. To demonstrate the potential of the condensed collection for phenotypic screening, we analyzed growth dynamics and cell morphology. We identified both growth defects and altered cell shape in mutants disrupting sphingolipid synthesis and thiamine scavenging. Finally, we analyzed the process of assembling the B. theta condensed collection to identify inefficiencies that limited coverage. We demonstrate as part of this analysis that the process of assembling an ordered collection can be accurately modeled using barcode sequencing data. CONCLUSION: We expect that utilization of this ordered collection will accelerate research into B. theta physiology and that lessons learned while assembling the collection will inform future efforts to assemble ordered mutant collections for an increasing number of gut microbiota members.

An unexpected role for leucyl aminopeptidase in UV tolerance revealed by a genome-wide fitness assessment in a model cyanobacterium.

UV radiation (UVR) has significant physiological effects on organisms living at or near the Earth's surface, yet the full suite of genes required for fitness of a photosynthetic organism in a UVR-rich environment remains unknown. This study reports a genome-wide fitness assessment of the genes that affect UVR tolerance under environmentally relevant UVR dosages in the model cyanobacterium Synechococcus elongatus PCC 7942. Our results highlight the importance of specific genes that encode proteins involved in DNA repair, glutathione synthesis, and the assembly and maintenance of photosystem II, as well as genes that encode hypothetical proteins and others without an obvious connection to canonical methods of UVR tolerance. Disruption of a gene that encodes a leucyl aminopeptidase (LAP) conferred the greatest UVR-specific decrease in fitness. Enzymatic assays demonstrated a strong pH-dependent affinity of the LAP for the dipeptide cysteinyl-glycine, suggesting an involvement in glutathione catabolism as a function of night-time cytosolic pH level. A low differential expression of the LAP gene under acute UVR exposure suggests that its relative importance would be overlooked in transcript-dependent screens. Subsequent experiments revealed a similar UVR-sensitivity phenotype in LAP knockouts of other organisms, indicating conservation of the functional role of LAPs in UVR tolerance.

Transcriptomic and Phenomic Investigations Reveal Elements in Biofilm Repression and Formation in the Cyanobacterium Synechococcus elongatus PCC 7942.

Biofilm formation by photosynthetic organisms is a complex behavior that serves multiple functions in the environment. Biofilm formation in the unicellular cyanobacterium Synechococcus elongatus PCC 7942 is regulated in part by a set of small secreted proteins that promotes biofilm formation and a self-suppression mechanism that prevents their expression. Little is known about the regulatory and structural components of the biofilms in PCC 7942, or response to the suppressor signal(s). We performed transcriptomics (RNA-Seq) and phenomics (RB-TnSeq) screens that identified four genes involved in biofilm formation and regulation, more than 25 additional candidates that may impact biofilm formation, and revealed the transcriptomic adaptation to the biofilm state. In so doing, we compared the effectiveness of these two approaches for gene discovery.

Genome-wide identification of fitness determinants in the Xanthomonas campestris bacterial pathogen during early stages of plant infection.

Plant diseases are an important threat to food production. While major pathogenicity determinants required for disease have been extensively studied, less is known on how pathogens thrive during host colonization, especially at early infection stages. Here, we used randomly barcoded-transposon insertion site sequencing (RB-TnSeq) to perform a genome-wide screen and identify key bacterial fitness determinants of the vascular pathogen Xanthomonas campestris pv campestris (Xcc) during infection of the cauliflower host plant (Brassica oleracea). This high-throughput analysis was conducted in hydathodes, the natural entry site of Xcc, in xylem sap and in synthetic media. Xcc did not face a strong bottleneck during hydathode infection. In total, 181 genes important for fitness were identified in plant-associated environments with functional enrichment in genes involved in metabolism but only few genes previously known to be involved in virulence. The biological relevance of 12 genes was independently confirmed by phenotyping single mutants. Notably, we show that XC_3388, a protein with no known function (DUF1631), plays a key role in the adaptation and virulence of Xcc possibly through c-di-GMP-mediated regulation. This study revealed yet unsuspected social behaviors adopted by Xcc individuals when confined inside hydathodes at early infection stages.

Nitrogen Metabolism in Pseudomonas putida: Functional Analysis Using Random Barcode Transposon Sequencing.

Pseudomonas putida KT2440 has long been studied for its diverse and robust metabolisms, yet many genes and proteins imparting these growth capacities remain uncharacterized. Using pooled mutant fitness assays, we identified genes and proteins involved in the assimilation of 52 different nitrogen containing compounds. To assay amino acid biosynthesis, 19 amino acid drop-out conditions were also tested. From these 71 conditions, significant fitness phenotypes were elicited in 672 different genes including 100 transcriptional regulators and 112 transport-related proteins. We divide these conditions into 6 classes, and propose assimilatory pathways for the compounds based on this wealth of genetic data. To complement these data, we characterize the substrate range of three promiscuous aminotransferases relevant to metabolic engineering efforts in vitro. Furthermore, we examine the specificity of five transcriptional regulators, explaining some fitness data results and exploring their potential to be developed into useful synthetic biology tools. In addition, we use manifold learning to create an interactive visualization tool for interpreting our BarSeq data, which will improve the accessibility and utility of this work to other researchers. IMPORTANCE Understanding the genetic basis of P. putida's diverse metabolism is imperative for us to reach its full potential as a host for metabolic engineering. Many target molecules of the bioeconomy and their precursors contain nitrogen. This study provides functional evidence linking hundreds of genes to their roles in the metabolism of nitrogenous compounds, and provides an interactive tool for visualizing these data. We further characterize several aminotransferases, lactamases, and regulators, which are of particular interest for metabolic engineering.

Genome-Wide Identification of Genes Important for Growth of Dickeya dadantii and Dickeya dianthicola in Potato (Solanum tuberosum) Tubers.

Dickeya species are causal agents of soft rot diseases in many economically important crops, including soft rot disease of potato (Solanum tuberosum). Using random barcode transposon-site sequencing (RB-TnSeq), we generated genome-wide mutant fitness profiles of Dickeya dadantii 3937, Dickeya dianthicola ME23, and Dickeya dianthicola 67-19 isolates collected after passage through several in vitro and in vivo conditions. Though all three strains are pathogenic on potato, D. dadantii 3937 is a well-characterized model while D. dianthicola strains ME23 and 67-19 are recent isolates. Strain ME23 specifically was identified as a representative strain from a 2014 outbreak on potato. This study generated comparable gene fitness measurements across ecologically relevant conditions for both model and non-model strains. Tubers from the potato cultivars "Atlantic," "Dark Red Norland," and "Upstate Abundance" provided highly similar conditions for bacterial growth. Using the homolog detection software PyParanoid, we matched fitness values for orthologous genes in the three bacterial strains. Direct comparison of fitness among the strains highlighted shared and variable traits important for growth. Bacterial growth in minimal medium required many metabolic traits that were also essential for competitive growth in planta, such as amino acid, carbohydrate, and nucleotide biosynthesis. Growth in tubers specifically required the pectin degradation gene kduD. Disruption in three putative DNA-binding proteins had strain-specific effects on competitive fitness in tubers. Though the Soft Rot Pectobacteriaceae can cause disease with little host specificity, it remains to be seen the extent to which strain-level variation impacts virulence.

Global Analysis of Biomineralization Genes in Magnetospirillum magneticum AMB-1.

Magnetotactic bacteria (MTB) are a phylogenetically diverse group of bacteria remarkable for their ability to biomineralize magnetite (Fe3O4) or greigite (Fe3S4) in organelles called magnetosomes. The majority of genes required for magnetosome formation are encoded by a magnetosome gene island (MAI). Most previous genetic studies of MTB have focused on the MAI, using screens to identify key MAI genes or targeted genetics to isolate specific genes and their function in one specific growth condition. This is the first study that has taken an unbiased approach to look at many different growth conditions to reveal key genes both inside and outside the MAI. Here, we conducted random barcoded transposon mutagenesis (RB-TnSeq) in Magnetospirillum magneticum AMB-1. We generated a library of 184,710 unique strains in a wild-type background, generating ∼34 mutant strains for each gene. RB-TnSeq also allowed us to determine the essential gene set of AMB-1 under standard laboratory growth conditions. To pinpoint novel genes that are important for magnetosome formation, we subjected the library to magnetic selection screens under varied growth conditions. We compared biomineralization under standard growth conditions to biomineralization under high-iron and anaerobic conditions, respectively. Strains with transposon insertions in the MAI gene mamT had an exacerbated biomineralization defect under both high-iron and anaerobic conditions compared to standard conditions, adding to our knowledge of the role of MamT in magnetosome formation. Mutants in an ex-MAI gene, amb4151, are more magnetic than wild-type cells under anaerobic conditions. All three of these phenotypes were validated by creating a markerless deletion strain of the gene and evaluating with TEM imaging. Overall, our results indicate that growth conditions affect which genes are required for biomineralization and that some MAI genes may have more nuanced functions than was previously understood. IMPORTANCE Magnetotactic bacteria (MTB) are a group of bacteria that can form nano-sized crystals of magnetic minerals. MTB are likely an important part of their ecosystems, because they can account for up to a third of the microbial biomass in an aquatic habitat and consume large amounts of iron, potentially impacting the iron cycle. The ecology of MTB is relatively understudied; however, the cell biology and genetics of MTB have been studied for decades. Here, we leverage genetic studies of MTB to inform environmental studies. We expand the genetic toolset for studying MTB in the lab and identify novel genes, or functions of genes, that have an impact on biomineralization.

Engineering Pseudomonas putida for efficient aromatic conversion to bioproduct using high throughput screening in a bioreactor.

Pseudomonas putida KT2440 is an emerging biomanufacturing host amenable for use with renewable carbon streams including aromatics such as para-coumarate. We used a pooled transposon library disrupting nearly all (4,778) non-essential genes to characterize this microbe under common stirred-tank bioreactor parameters with quantitative fitness assays. Assessing differential fitness values by monitoring changes in mutant strain abundance identified 33 gene mutants with improved fitness across multiple stirred-tank bioreactor formats. Twenty-one deletion strains from this subset were reconstructed, including GacA, a regulator, TtgB, an ABC transporter, and PP_0063, a lipid A acyltransferase. Thirteen deletion strains with roles in varying cellular functions were evaluated for conversion of para-coumarate, to a heterologous bioproduct, indigoidine. Several mutants, such as the ΔgacA strain improved fitness in a bioreactor by 35 fold and showed an 8-fold improvement in indigoidine production (4.5 g/L, 0.29 g/g, 23% of maximum theoretical yield) from para-coumarate as the carbon source.

Iron Supplementation Eliminates Antagonistic Interactions Between Root-Associated Bacteria.

The rhizosphere microbiome (rhizobiome) plays a critical role in plant health and development. However, the processes by which the constituent microbes interact to form and maintain a community are not well understood. To investigate these molecular processes, we examined pairwise interactions between 11 different microbial isolates under select nutrient-rich and nutrient-limited conditions. We observed that when grown with media supplemented with 56 mM glucose, two microbial isolates were able to inhibit the growth of six other microbes. The interaction between microbes persisted even after the antagonistic microbe was removed, upon exposure to spent media. To probe the genetic basis for these antagonistic interactions, we used a barcoded transposon library in a proxy bacterium, Pseudomonas putida, to identify genes which showed enhanced sensitivity to the antagonistic factor(s) secreted by Acinetobacter sp. 02. Iron metabolism-related gene clusters in P. putida were implicated by this systems-level analysis. The supplementation of iron prevented the antagonistic interaction in the original microbial pair, supporting the hypothesis that iron limitation drives antagonistic microbial interactions between rhizobionts. We conclude that rhizobiome community composition is influenced by competition for limiting nutrients, with implications for growth and development of the plant.

The essential gene set of a photosynthetic organism.

Synechococcus elongatus PCC 7942 is a model organism used for studying photosynthesis and the circadian clock, and it is being developed for the production of fuel, industrial chemicals, and pharmaceuticals. To identify a comprehensive set of genes and intergenic regions that impacts fitness in S. elongatus, we created a pooled library of ∼ 250,000 transposon mutants and used sequencing to identify the insertion locations. By analyzing the distribution and survival of these mutants, we identified 718 of the organism's 2,723 genes as essential for survival under laboratory conditions. The validity of the essential gene set is supported by its tight overlap with well-conserved genes and its enrichment for core biological processes. The differences noted between our dataset and these predictors of essentiality, however, have led to surprising biological insights. One such finding is that genes in a large portion of the TCA cycle are dispensable, suggesting that S. elongatus does not require a cyclic TCA process. Furthermore, the density of the transposon mutant library enabled individual and global statements about the essentiality of noncoding RNAs, regulatory elements, and other intergenic regions. In this way, a group I intron located in tRNA(Leu), which has been used extensively for phylogenetic studies, was shown here to be essential for the survival of S. elongatus. Our survey of essentiality for every locus in the S. elongatus genome serves as a powerful resource for understanding the organism's physiology and defines the essential gene set required for the growth of a photosynthetic organism.