ORIGINAL RESEARCH article

Front. Microbiol., 22 November 2016

Sec. Plant Pathogen Interactions

Volume 7 - 2016 | https://doi.org/10.3389/fmicb.2016.01873

The Use of Transposon Insertion Sequencing to Interrogate the Core Functional Genome of the Legume Symbiont Rhizobium leguminosarum

  • Department of Biology, University of Regina Regina, SK, Canada

Abstract

The free-living legume symbiont Rhizobium leguminosarum is of significant economic value because of its ability to provide fixed nitrogen to globally important leguminous food crops, such as peas and lentils. Discovery based research into the genetics and physiology of R. leguminosarum provides the foundational knowledge necessary for understanding the bacterium's complex lifestyle, necessary for augmenting its use in an agricultural setting. Transposon insertion sequencing (INSeq) facilitates high-throughput forward genetic screening at a genomic scale to identify individual genes required for growth in a specific environment. In this study we applied INSeq to screen the genome of R. leguminosarum bv. viciae strain 3841 (RLV3841) for genes required for growth on minimal mannitol containing medium. Results from this study were contrasted with a prior INSeq experiment screened on peptide rich media to identify a common set of functional genes necessary for basic physiology. Contrasting the two growth conditions indicated that approximately 10% of the chromosome was required for growth, under both growth conditions. Specific genes that were essential to singular growth conditions were also identified. Data from INSeq screening on mannitol as a sole carbon source were used to reconstruct a metabolic map summarizing growth impaired phenotypes observed in the Embden-Meyerhof-Parnas pathway, Entner-Doudoroff pathway, pentose phosphate pathway, and tricarboxylic acid cycle. This revealed the presence of mannitol dependent and independent metabolic pathways required for growth, along with identifying metabolic steps with isozymes or possible carbon flux by-passes. Additionally, genes were identified on plasmids pRL11 and pRL12 that are likely to encode functional activities important to the central physiology of RLV3841.

Introduction

Rhizobium leguminosarum is a Gram-negative soil and rhizosphere colonizing bacterium that is also capable of engaging in endosymbiosis with specific leguminous plant genera. The host specificity of rhizobial infection is dependent upon the exchange of specific chemical signals between the infecting bacterium and host plant (Oldroyd et al., 2011), and R. leguminosarum is often divided into biovars based on infectious host range. The biovar viciae is indicative of Rhizobia capable of infecting leguminous plants such as peas (Pisum sativum), lentils (Lens culinaris), and vetch (Vicia spp.). When in the endosymbiotic state, Rhizobium bacteroids reduce atmospheric nitrogen N2 to ammonia, which is then exported to the plant for assimilation. In return, the plant host provides fixed carbon and other micro-nutrients to the bacteroids to sustain the symbiosis (Wielbo, 2012; Udvardi and Poole, 2013). The availability of symbiotically supplied nitrogen enables leguminous plants to satisfy their high nitrogen demands and, in part, contributed to the evolutionary success and diversification of the Leguminosae (Doyle and Luckow, 2003).

R. leguminosarum bv. viciae 3841(RLV3841) (Johnston and Beringer, 1975), has long been considered a model organism for Rhizobium research and was one of the first rhizobial strains with a published complete genome sequence (Young et al., 2006). Aside from the overarching agricultural context of studying RLV3841, the model organism provides other interesting avenues of research because of its complex genomic structure (Young et al., 2006) and versatility of physiology and lifestyle. RLV3841 has a relatively large bacterial genome comprised of a single 5.1 Mb chromosome and 6 large, stably maintained, plasmids ranging in size from 0.87 to 0.15 Mb. The RLV3841 genome is predicted to contain approximately 7346 genes, a substantial percentage of these genes (25.2%) are annotated as hypothetical genes of unknown function, warranting further investigation. The use of high-throughput experimental approaches may allow prioritization of the study of individual genes within this large functionally unknown group.

The development of next-generation sequencing technologies has resulted in high-throughput methods of transposon (Tn) mutagenesis to study gene function at a genome scale (Gawronski et al., 2009; Goodman et al., 2009; Langridge et al., 2009; van Opijnen et al., 2009). For example, INSeq was developed through the introduction of a type II restriction enzyme site within the IS element of the himar1C9 mariner Tn allowing for the specific capture and PCR amplification of genomic DNA adjacent to the Tn insertion site (Goodman et al., 2011). Next generation sequencing of PCR amplicons derived from DNA isolated from these Tn-mutant libraries allows for the sequencing of millions of Tn insertion tags which can be mapped to the genome sequence and used to enumerate the relative abundance of individual Tn mutants within a mutant population (Barquist et al., 2013; van Opijnen and Camilli, 2013). INSeq and similar high-throughput Tn mutagenesis methods have been used to study the genetic basis of bacterial physiology (Griffin et al., 2011; Brutinel and Gralnick, 2012; Kuehl et al., 2014; Yang et al., 2014; Le Breton et al., 2015; Lee et al., 2015; Meeske et al., 2015; Pechter et al., 2015; Rubin et al., 2015; Hooven et al., 2016; Troy et al., 2016), bacterial resistance to biotic and abiotic factors (Gallagher et al., 2011; Khatiwara et al., 2012; Phan et al., 2013; Byrne et al., 2014; Murray et al., 2015; Shan et al., 2015; Yung et al., 2015; Tran et al., 2016), and colonization of hosts or specific environments (Gawronski et al., 2009; Dong et al., 2013; Kamp et al., 2013; Skurnik et al., 2013; Bishop et al., 2014; Johnson et al., 2014; Verhagen et al., 2014; Wang et al., 2014; Gutierrez et al., 2015; Moule et al., 2015; Turner et al., 2015; Capel et al., 2016). Recently, INSeq was adapted for use in the Rhizobiaceae, and was demonstrated to be a suitable tool for high-throughput functional genomic screening in RLV3841 (Perry and Yost, 2014).

In this paper we used INSeq to define a core functional genome (CFG) of RLV3841 and deconstruct central carbon metabolism for growth on mannitol, a preferred carbon source of rhizobia (Vincent, 1970; Geddes and Oresnik, 2014). Comparing the genes required for growth on mannitol with those required for growth on tryptone-yeast extract media, we estimated a core set of functional genes required for optimal growth. Furthermore, the results of this study demonstrate that using INSeq and growth on minimal media is an effective approach to gain new insight into central carbon metabolism in RLV3841.

Materials and methods

Growth conditions, strains, and plasmids

R. leguminosarum bv. viciae 3841 (Johnston and Beringer, 1975) was routinely grown at 30°C using tryptone-yeast (TY) extract growth medium (5.0 g tryptone, 3.0 g yeast extract, 3.5 mM CaCl2 per liter H2O; TY) or Vincent's minimal medium (VMM) (1.0 g K2HPO4, 1.0 g KH2PO4, 0.01 g FeCl26H2O, 0.25 g MgSO47H2O, 0.1 g CaCl26H2O, 0.6 g KNO3, 0.1 mg biotin, 0.1 mg Ca-panthenoate, and 0.1 mg thiamine per liter H2O) supplemented with 1.% (w/v) mannitol as a carbon source (Vincent, 1970). The donor E. coli strain SM10λpir harboring pSAM_Rl was routinely grown on LB medium at 37°C. Antibiotic concentrations were 500 μg/mL streptomycin (Str) and 50 μg/mL neomycin (Neo) for RLV3841, and 100 μg/mL ampicillin (Amp) and 50 μg/mL kanamycin (Kan) for E. coli.

Mariner transposon mutant pool generation and mutant selection

Mutant pools were generated as described in Perry and Yost (2014) with minor modifications. Briefly, RLV3841 and E. coli SM10λpir(pSAM_Rl) were grown in broth culture until late exponential phase. 1.0 ml of donor and 0.5 ml of recipient strains were mixed in a 1.5 mL microcentrifuge tube and pelleted at 12, 000 g for 3 min. The cell mixture was then washed twice with 1000 μL 1X phosphate buffer saline (PBS), and resuspended in a final volume of approximately 100 μL 1X PBS. Six independent conjugations were spotted onto pre-warmed VMM-mannitol plates and were incubated at 30°C overnight (~18 h). Following incubation each of the 6 conjugation spots were scraped and re-suspended in 1000 μL of 1X PBS and pooled into a total volume of 6 ml, representing the RLV3841 Tn mutant library.

Selection of mutant pools on VMM-mannitol was conducted using six 245 × 245 mm2 (Corning) Neo and Str containing VMM-mannitol agar plates. For each selection plate, 500 μL of the RLV3841 mutant pool was spread plated and allowed to dry. The agar plates were incubated at 30 C for 72 hr representing between 15 and 18 generations of RLV3841 growth on minimal media. Cells from each plate were harvested by scraping the thin film of cell growth and re-suspending in 5 mL of 1X PBS, vortexed thoroughly to homogenize the cells, and then a 1000 μL aliquot of each cell suspension was used for cell pelleting and DNA isolation (Perry and Yost, 2014).

Transposon insertion sequencing

The mutant pools recovered from 2 of 6 selection plates were pooled into 3 independent technical replicates for DNA extraction and Tn insertion sequencing. The method used for library preparation and sequencing is described by Perry and Yost (2014) with modification to the adaptor sequences INSeq_Adpt_Top and INSeq_Adpt_Bottom (Table S1). The final library concentration of the 3 stock library preparations was 1.29, 1.21, and 1.39 ng/μL after size selection. DNA sequencing was performed on an Ion Torrent PGM using 200 bp sequencing chemistry and a 316v2 sequencing chip. The raw sequence output for the 3 technical replicates was 1.4, 1.1, and 1.1 M reads, respectively, and can be found under SRA deposit number: SRR3400585-7 (TY datasets are deposited under SRR3400588-90). Sequencing data from the 3 technical replicates were pooled for a combined total of 3.6 million to achieve sufficient read depth for hidden Markov model analysis (DeJesus and Ioerger, 2013). Raw sequencing data was processed, aligned, and analyzed as previously described (Perry and Yost, 2014). Briefly, raw reads were clipped at the end of the pSAM_Rl mariner IR element, and clipped on the 3′ end at the beginning of the INSeq_Adpt sequence. The resulting reads were screened for the presence of a 5′-TA insertion site, and a length ≥15 bp. Trimmed reads were aligned to the RLV3841 reference genome using bowtie, with the option to suppress reads with multiple alignments from the output file enabled. The alignment files were then converted to wig files and analyzed using the tn-hmm.py python module. The pipeline resulted in a total of 2,374,819 reads being aligned onto the RLV3841 reference genome, after quality filtering and discarding of unaligned reads. The HMM then assigned each “TA” insertion site to one of four growth states which was used to assign each gene to a specific growth phenotype (DeJesus and Ioerger, 2013).

Curation of INSeq data

Outputs from the HMM for both the TY (Perry and Yost, 2014) and VMM dataset were combined based on RLV3841 locus number. Riley functional classifications for each gene were obtained from the lab of Phillip Poole, University of Oxford (http://rhizosphere.org/lab-page/molecular-tools/genomes/rlv3841-genome) and appended to the dataset. Duplicate gene sequences were manually examined using reciprocal BLAST to the RLV3841 reference genome for all genes with <0.30 insertion density to avoid miss-classification as an essential gene due to a lack of mapped insertions as a result of the alignment penalty for multiple mapping locations. The final compiled and curated dataset is found in Supplementary File 1.

Insertional mutagenesis of RL0920 and RL3335

Two previously uncharacterized VMM-mannitol growth impaired genes (RL0920 and RL3335) were mutated to verify the INSeq growth phenotype data. Mutants were created using a single crossover mutagenesis approach with pJQ200SK (Quandt and Hynes, 1993), as described in Vanderlinde et al. (2010). Briefly, a 563 bp internal fragment of RL0920 was PCR amplified using primers RL0920_Fwd and RL0920_Rev, which introduced 5′ ApaI and 3′ SpeI restriction enzyme sites. The 563 bp amplicon was then directionally cloned into pJQ200SK using ApaI and SpeI. The new vector pJQ200SK-RL0920 was conjugated into RLV3841 wildtype using E. coli strain S17-1, and single cross over mutants were selected for on TYSmGm, and then screened for sucrose sensitivity to confirm the plasmid integration. The identical procedure was used to create a single crossover mutant in RL3335 using primers RL3335_Fwd and RL3335_Rev to generate a 603 bp internal gene fragment for cloning into pJQ200SK (Table S1). The resulting mutants in RL0920 and RL3335 were named MA0920 and MA3335.

Growth curve analysis of MA0920, MA3335, and RLV3841 wildtype

Growth curves of RLV3841, MA0920, and MA3335 were performed using a shaking head Synergy HT Microplate Reader (Biotek) with 250 μL of inoculated growth media per well in a 96-well NuncR Optical Bottom Plate (Thermo Scientific), and a 40 μL Anti-Evaporation Oil (Ibidi) overlay. Inoculated growth medium was prepared by scraping cells from freshly grown TYSm or SmGm plates, washing twice with 1XPBS, standardizing the cell suspension for an approximate initial OD600 of 0.01. Cells were grown at 30°C with 10 min of shaking followed by OD600 measurements every 30 min, for 72 h. Each growth curve was derived from the mean OD600 measurements of 7 replicates. Mean generation times (MGT) were calculated in early exponential phase (OD600 < 0.100) and late exponential phase (0.100 < OD600 < 0.200) by calculating the average time required to double the optical density of the cell cultures, within the defined growth phases.

Results

Tn insertion sequencing and transposition summary of VMM-mannitol mutant pools

The RLV3841 genome contains 140,056 potential mariner insertion sites distributed across the chromosome and 6 mega-plasmids. Insertion densities within the genome ranged from 0.65 to 0.86 across the 7 replicons, with an average insertion density of 0.80 (Table S2). The insertion densities were similar to the insertion densities previously observed in an INSeq experiment using TY medium for selection (Perry and Yost, 2014). HMM analysis of the VMM INSeq data assigned 7.2 and 2.6% of genes to essential (ES) or growth defective (GD) growth phenotypes, respectively (Table S3). Given sufficient generations of growth GD mutants would be excluded from the mutant community. Therefore, ES and GD states were pooled into a single growth impaired (GI) category (9.8% of the genes) for annotation with Riley functional groupings. 87.1% of genes were observed to have no impact on growth (NE), and 1.20% of genes with Tn insertions became over-represented within the mutant communities, and were predicted to confer a growth advantage (GA) phenotype (Table S3). To further simplify interpretation of the INSeq data by focusing exclusively on loss-of-function phenotypes the NE and GA genes were pooled into a single category termed growth neutral (GN). Within the genome 1.6% of genes had sequence duplications resulting in no information concerning their impact on growth due to the multiple Tn insertion tag mapping location penalty imposed. As well, 0.3% of genes were observed to lack a “TA” dinucleotide motif leaving them without a target site for mariner Tn insertion.

The RLV3841 CFG, VMM-growth impaired, and TY-growth impaired phenotypes

Comparison of the VMM-mannitol INSeq dataset with the TY INSeq dataset identified a set of genes that when mutated conferred a GI phenotype under both conditions; these 491 genes were assigned to the CFG (Figure 1). Whereas, 170 and 72 genes, when interrupted by Tn insertion, resulted in a condition dependent impaired ability to grow on VMM (VGI) and TY (TGI), respectively. Genes within the CFG were represented by 5 major Riley classification groups: macro-molecule synthesis and metabolism (20.0%), energy and carbon metabolism (10.2%), ribosomal constituents (9.8%), cell envelope (9.4%), and conserved hypothetical proteins (9.2%) (Figure 2). Genes that gave rise to a VGI phenotype were composed of 3 major functional groups: metabolism of amino acids (17.6%), biosynthesis of co-factors and carriers (14.7%), and nucleotide biosynthesis (11.8%). While the 4 major groups of TGI genes consisted of hypothetical proteins (27.8%), cell envelope (15.3%), macro-molecule synthesis and metabolism (12.5%), and transport and binding proteins (11.1%).

Figure 1

Figure 2

Open reading frames annotated as hypothetical proteins represent approximately 25.2% of the RLV3841 genome. Of these, 103 hypothetical proteins were observed to have a GI phenotype on VMM, TY, or both growth conditions (Table 1). Sequence duplication within the RLV3841 genome resulted in 20 annotated hypothetical proteins not being assayed for a growth phenotype using INSeq, due to multiple potential alignments of sequenced Tn insertion tags.

Table 1

VMM INSeq DataTY INSeq Data
LocusGrowth phenotypeNInsertion densityAverage read depthGene stateNInsertion densityAverage read depthGene stateRiley keyAnnotation
CORE FUNCTIONAL GENOME HYPOTHETICAL PROTEINS
RL1763GI200ES200ES0.0.0Hypothetical protein
RL2220GI70.5729.75ES70.5730.25ES0.0.0Hypothetical protein
RL2402GI130.4613.5GD130.4611.33GD0.0.0Hypothetical protein
RL2581GI600ES60.331.5ES0.0.0Hypothetical protein
RL4714GI100ES112GD0.0.0Hypothetical protein
RL0128GI80.131ES800ES0.0.1Conserved hypothetical protein
RL0393GI80.389.33GD80.54.25GD0.0.1Conserved hypothetical protein
RL0412GI1000ES1000ES0.0.1Conserved hypothetical protein
RL0548GI700ES70.142ES0.0.1Conserved hypothetical protein
RL0612GI200ES200GD0.0.1Conserved hypothetical protein
RL0620GI700GD700GD0.0.1Conserved hypothetical protein
RL1432GI50.27ES50.64.33GD0.0.1Conserved hypothetical protein
RL1566GI110.185ES1100ES0.0.1Conserved hypothetical protein
RL2245GI80.1322ES80.2530GD0.0.1Conserved hypothetical protein with RimI domain, putative N-acetyltransferase
RL3754GI60.178ES600ES0.0.1Conserved hypothetical protein
RL3757GI50.616GD50.433.5ES0.0.1Conserved hypothetical protein
RL3762GI1400ES140.071ES0.0.1Conserved hypothetical exported protein
RL4061GI1000ES100.31.67GD0.0.1Conserved hypothetical protein
RL4324GI100ES100GD0.0.1Conserved hypothetical exported protein
RL4434GI300ES300GD0.0.1Conserved hypothetical protein
RL4437GI800GD80.132GD0.0.1Conserved hypothetical protein
RL4733GI800ES800ES0.0.1Conserved hypothetical protein
RL0126GI800ES80.133ES0.0.2Conserved hypothetical protein
RL0144GI500ES500ES0.0.2Conserved hypothetical protein
RL0456AGI400NE400NE0.0.2Conserved hypothetical protein
RL0619GI40.251GD40.251GD0.0.2Conserved hypothetical protein
RL0626GI130.4612.67GD130.6214.25GD0.0.2Conserved hypothetical protein
RL0936GI300.071ES300.172GD0.0.2Conserved hypothetical protein (TPR repeat family)
RL1094GI170.128ES170.185.33ES0.0.2Conserved hypothetical protein
RL1116GI90.1118ES90.1139ES0.0.2Conserved hypothetical protein
RL1569GI210.051ES210.141ES0.0.2Conserved hypothetical protein
RL1598GI600ES60.171GD0.0.2Conserved hypothetical protein
RL1706GI300ES300GD0.0.2Conserved hypothetical protein in NADH-ubiquinone oxidoreductase region
RL2034GI80.53.75GD80.381ES0.0.2Conserved hypothetical protein
RL2042GI290.288.5ES290.175.4GD0.0.2Conserved hypothetical protein
RL2056GI50.21GD50.22GD0.0.2Conserved hypothetical protein
RL2207GI60.171ES60.172GD0.0.2Conserved hypothetical protein
RL2232GI110.091ES1100ES0.0.2Conserved hypothetical protein
RL2584GI900ES90.112ES0.0.2Conserved hypothetical protein
RL2697GI50.221ES50.222ES0.0.2Conserved hypothetical exported protein
RL3259GI100NE100NE0.0.2Conserved hypothetical protein
RL3314GI800ES800ES0.0.2Conserved hypothetical protein
RL3464GI150.271.5GD150.532.63GD0.0.2Conserved hypothetical protein
RL3948AGI310.062ES310.161ES0.0.2Conserved hypothetical protein
RL3967GI1900ES190.533.5GD0.0.2Conserved hypothetical protein
RL4037GI80.53.25GD80.636.8GD0.0.2Conserved hypothetical protein
RL4280GI200.42.5GD200.254ES0.0.2Conserved hypothetical protein
RL4523GI130.237.67ES130.2312.33ES0.0.2Conserved hypothetical exported protein
RL4562GI100.13ES100.14ES0.0.2Conserved hypothetical exported protein
RL4734GI1400ES1400ES0.0.2Conserved hypothetical protein
VMM-GROWTH IMPAIRED HYPOTHETICAL PROTEINS
RL0044VGI130.6222.88ES130.6932.33NE0.0.0Hypothetical protein
RL1117VGI60.515.33ES60.678NE0.0.0Hypothetical protein
RL1628VGI390.648.32ES390.6710.35NE0.0.0Hypothetical protein
RL1946VGI130.621.75GD130.693.33NE0.0.0Hypothetical protein
RL2117AVGI330.7611.36ES330.7913.31NE0.0.0Hypothetical protein
RL2154VGI160.697.55GD160.757.25NE0.0.0Hypothetical protein
RL2611VGI100.511.6ES100.914NE0.0.0Hypothetical protein
RL1524VGI50.63.33GD50.89.75NE0.0.1Conserved hypothetical protein
RL3760VGI700ES70.299NE0.0.1Conserved hypothetical protein
RL4043VGI20.52ES2129NE0.0.1Conserved hypothetical protein
RL4066VGI240.422.8GD240.799.68NE0.0.1Conserved hypothetical protein
RL0571VGI300ES3126.67NE0.0.2Conserved hypothetical protein
RL0960VGI100.31.33GD100.52.6NE0.0.2Conserved hypothetical protein (Sua5 family)
RL1523VGI40.252GD414.25NE0.0.2Conserved hypothetical protein
RL2210VGI50.21GD50.41NE0.0.2Conserved hypothetical protein
RL2289VGI30.331GD3119NE0.0.2Conserved hypothetical protein
RL2291VGI70.712GD70.8620NE0.0.2Conserved hypothetical protein
RL2527VGI130.318.5GD130.696.78NE0.0.2Conserved hypothetical exported protein
RL4728VGI130.236ES130.696.11NE0.0.2Conserved hypothetical protein
TY-GROWTH IMPAIRED HYPOTHETICAL PROTEINS
RL1527TGI2124NE213.5GD0.0.1Conserved hypothetical protein
RL1562TGI90.5614.8NE90.5616.4ES0.0.1Conserved hypothetical protein
RL1618ATGI1719.82NE170.652.18GD0.0.1Conserved hypothetical protein
RL2307TGI40.755.67NE40.7510GD0.0.1Conserved hypothetical protein
RL4065TGI30.671NE300NE0.0.1Conserved hypothetical protein
RL4716TGI18137.17NE180.616.55GD0.0.1Conserved hypothetical exported protein
RL0109TGI80.758.5NE80.252.5GD0.0.2Conserved hypothetical protein
RL0890TGI160.8119.54NE160.513.75ES0.0.2Conserved hypothetical protein
RL1526TGI110.9134.9NE110.645.43GD0.0.2Conserved hypothetical protein
RL1528TGI110.9114.3NE110.457.2GD0.0.2Conserved hypothetical protein
RL2086TGI60.835.8NE60.51.33GD0.0.2Conserved hypothetical exported protein
RL2142TGI170.7113.33NE170.6517.55ES0.0.2Conserved hypothetical protein
RL2542TGI214.5NE200GD0.0.2Conserved hypothetical protein
RL2625TGI150.89.08NE150.473.71GD0.0.2Conserved hypothetical protein
RL2641TGI90.6714NE90.565.8GD0.0.2Conserved hypothetical protein
RL3499TGI140.9317.08NE140.52.29GD0.0.2Conserved hypothetical protein
RL3500TGI18134.89NE180.675.75GD0.0.2Conserved hypothetical protein
RL3761TGI140.9313.23NE140.211ES0.0.2Conserved hypothetical exported protein
RL4016TGI50.827.5NE500GD0.0.2Conserved hypothetical protein
RL4503TGI40.753NE414.75GD0.0.2Conserved hypothetical protein
PLASMID GROWTH IMPAIRED HYPOTHETICAL PROTEINS
pRL100111PGI380.453.18GD380.453.71ES0.0.0Hypothetical protein
pRL70135PGI170.4722.75ES170.6523ES0.0.0Hypothetical protein
pRL120721PGI60.171ES60.332.5ES0.0.1Conserved hypothetical protein
pRL100012PGI300ES300ES0.0.2Conserved hypothetical protein
pRL110465PGI80.131GD80.132GD0.0.2Conserved hypothetical protein
pRL70167PGI110.2711ES110.2719ES0.0.2Conserved hypothetical protein
pRL80098PGI110.189.5ES110.648.14GD0.0.2Conserved hypothetical protein
PLASMID/(VMM/TY)-GROWTH IMPAIRED HYPOTHETICAL PROTEINS
pRL100010PVGI30.333GD3111.67NE0.0.2Conserved hypothetical protein
pRL100149PVGI580.8314.56ES580.8318.54NE0.0.2Conserved hypothetical protein
pRL110044PVGI60.331.5GD60.834NE0.0.2Conserved hypothetical protein
pRL110108PVGI170.769.85ES170.7613.38NE0.0.2Conserved hypothetical protein
pRL110351APTGI100.79.71NE100.614.67ES0.0.2Conserved hypothetical protein
pRL70166PVGI90.336.33ES90.676.83NE0.0.2Conserved hypothetical protein
pRL90280PVGI60.54.33ES60.836.6NE0.0.2Conserved hypothetical protein
LocusGrowth phenotypeNInsertion densityAverage read depthGene stateNInsertion densityAverage read depthGene stateRiley keyAnnotationSequence duplications
GROWTH IMPAIRED OR PLASMID GROWTH IMPAIRED HYPOTHETICAL PROTEINS WITH SEQUENCE DUPLICATION
pRL70102PGI400ES400ES0.0.0Hypothetical proteinpRL70102, pRL110582, downstream pRL100152, upstream pRL100166
RL1481GI600ES600ES0.0.0Hypothetical proteinRL1481, 3′-end of RL00456B, 5′-end of RL0457, 3′-end of pRL100088, 5′-end of pRL100089
pRL110342PGI200ES200ES0.0.0Hypothetical proteinupstream pRL100046, upstream RL2679
pRL100089PGN50.45.5NE50.65.33NE0.0.1Conserved hypothetical proteinpRL100089, RL1481
pRL70033PGI800ES800ES0.0.1Conserved hypothetical proteinpRL70033, pRL70047D, pRL70147
pRL70047PGI600ES600ES0.0.1Conserved hypothetical proteinpRL70142, pRL70047
pRL70142PGI600ES600ES0.0.1Conserved hypothetical proteinpRL70142, pRL70047
pRL70179PGI300ES300ES0.0.1Conserved hypothetical proteinpRL70169, pRL70179, PRL100095
pRL120379PGI3500ES3500ES0.0.1Conserved hypothetical proteinpRL90004, pRL90319, pRL100469, pRL120379
pRL90004PGI3500ES3500ES0.0.1Conserved hypothetical proteinpRL90004, pRL90319, pRL100469, pRL120379
pRL120650PGI600ES600ES0.0.1Conserved hypothetical proteinRL2139, RL0835, pRL120650
RL0835GI700ES70.1421ES0.0.1Conserved hypothetical proteinRL2139, RL0835, pRL120650
RL2139GI600ES600ES0.0.1Conserved hypothetical proteinRL2139, RL0835, pRL120650
pRL110353PGN40.252NE40.253NE0.0.2Conserved hypothetical proteinpRL110353, RL2153
RL2153GI40.253GD40.254GD0.0.2Conserved hypothetical proteinpRL110353, RL2153
pRL100095PGI200NE200NE0.0.2Conserved hypothetical proteinpRL70169, pRL70179, PRL100095
pRL70169PGI200ES200ES0.0.2Conserved hypothetical proteinpRL70169, pRL70179, PRL100095
pRL100469PGI3500ES3500ES0.0.2Conserved hypothetical proteinpRL90004, pRL90319, pRL100469, pRL120379
pRL90319PGI3500ES3500ES0.0.2Conserved hypothetical protein, possible fusion proteinpRL90004, pRL90319, pRL100469, pRL120379

Growth impaired hypothetical proteins.

Growth curve analysis of two predicted VMM-growth impaired mutants

Growth curves of RLV3841, MA0920 (INSeq predicted RL0920 VGI), and MA3335 (INSeq predicted RL3335 VGI), in TY and VMM-Mannitol broth over 72 h are shown in Figure 3. After 72 h growth RLV3841, MA0920, and MA3335 reached final mean OD600 readings of 0.696, 0.657, and 0.628 on TY; and 0.588, 0.179, and 0.198 on VMM, respectively. Mean generation times for RLV3841, MA0920, and MA3335 on TY were 2.5, 3.0, and 3.0 h in early exponential phase; and 3.5, 4.5, and 4.0 h in late exponential phase. The MGTs in VMM-Mannitol were observed to be 6.0, 7.5, and 8.5 h in early exponential phase for RLV3841, MA0920, and MA3335 respectively. In late exponential phase, MA0920 and MA3335 halted growth and did not complete an additional doubling, whereas RLV3841 wildtype continued to double with a MGT of 9.5 h.

Figure 3

The genetics of central carbon metabolism for growth on mannitol

INSeq was used to identify a potential minimal central carbon metabolism pathway for growth on mannitol. Figure 4, and accompanying Table 2, provide a metabolic map illustrating the interconnections of the Embden-Meyerhof-Parnas (EMP) pathway, Entner-Doudoroff (ED) pathway, pentose phosphate (PP) pathway, and tricarboxylic acid cycle (TCA) that compose central carbon metabolism, with an overlay of the observed growth impaired phenotypes. It was observed that the genes required for mannitol uptake and conversion to fructose-6P (F6P) were VGI. Genes required for conversion of F6P to pyruvate were observed to be VGI within the ED pathway. Genes required for conversion of F6P into glyceraldehyde-3P (GA3P), via the upper EMP pathway, were observed to have no impact on growth when mutated. Genes required for the conversion of GA3P to pyruvate as part of the lower EMP pathway were found to be VGI when mutated. Assimilation of pyruvate into the TCA cycle was observed to be VGI via more than one metabolic pathway. Mutation of genes within the TCA cycle were observed to result in GI or VGI phenotypes, with the exception of a growth neutral step at the conversion between fumarate and malate (Figure 3; Table 2).

Figure 4

Table 2

VMM INSeqTY INSeq
Metabolic stepRLV locusRLV symbolPutative productGrowth phenotypeInsertion densityAverage read depthGene stateInsertion densityAverage read depthGene stateRiley keyRiley functional information
MANNITOL UPTAKE AND CONVERSION TO FRUCTOSE
1.0RL4219Transcriptional regulatorGN0.8616.67NE0.7925.27NE6.3.10Putative deor family transcriptional regulator (repressor) of sorbitol/mannitol operon
1.0RL4215Mannitol ABC transporter ATP-binding proteinVGI0.411.71GD0.8812.6NE1.5.3Putative ATP-binding component of ABC transporter CUT1 mannitol transporter (S. Mel SBP homolog smc01496 induced by dulcitol, sorbitol, mannitol)
1.0RL4216mtlGMannitol transmembrane permease component of ABC transporterVGI0.563.2GD134.11NE1.5.3Putative permease component of ABC transporter CUT1 mannitol transporter (S. Mel SBP homolog smc01496 induced by dulcitol, sorbitol, mannitol)
1.0RL4217mtlFMannitol transmembrane permease component of ABC transporterVGI0.532.78GD0.9436.06NE1.5.3Putative permease component of ABC transporter CUT1 mannitol transporter (S. Mel SBP homolog smc01496 induced by dulcitol, sorbitol, mannitol)
1.0RL4218mtlEMannitol-binding component of ABC transporterVGI0.482.3GD0.926.11NE1.5.3Putative SBP of ABC transporter CUT1 mannitol transporter (S. Mel SBP homolog smc01496 induced by dulcitol, sorbitol, mannitol)
1.0RL4214mtlKMannitol 2-dehydrogenaseVGI0.127.5GD0.8824.8NE3.4.3Putative mannitol 2-dehydrogenase
1.0RL0098Mannitol dehydrogenaseGN0.9317NE0.9317.62NE3.4.3Putative mannitol dehydrogenase
1.0RL0502frkFructokinaseVGI0.213GD115.71NE3.5.5Fructokinase
ENTNER–DOUDOROFF PATHWAY
1.1RL0753zwf1Putative glucose-6-phosphate 1-dehydrogenaseGI0.051ES0.091ES3.5.6Putative glucose-6-phosphate 1-dehydrogenase
1.1RL1315zwf1Glucose-6-phosphate 1-dehydrogenaseGN0.9318.72NE118.7NE3.5.6Putative glucose-6-phosphate 1-dehydrogenase
1.1pRL120561Glucose-6-phosphate 1-dehydrogenasePGN119NE114.5NE6.3.0Putative XRE family transcriptional regulator
1.2RL0752pgl6-phosphogluconolactonaseGI00ES00ES3.5.6Putative 6-phosphogluconolactonase
1.3RL0751eddPhosphogluconate dehydrataseVGI00ES18.73NE3.3.3Putative phosphogluconate dehydratase
1.4RL4162edaKeto-hydroxyglutarate-aldolase/keto-deoxy-phosphogluconate aldolaseVGI0.1314ES0.883.14NE3.3.3Putative 2-dehydro-3-deoxyphosphogluconate aldolase
EMBDEN-MEYERHOF-PARNAS PATHWAY
2.1RL0504pgiGlucose-6-phosphate isomeraseVGI0.0630ES0.7610.69NE3.5.5Putative glucose-6-phosphate isomerase
2.2RL3322pfpPyrophosphate-fructose-6-phosphate 1-phosphotransferaseGN116.8NE0.9521.79NE3.5.5Putative pyrophosphate–fructose 6-phosphate 1-phosphotransferase
2.3RL4012Fructose-bisphosphate aldolaseGN0.8622.42NE0.9321.23NE3.5.5Putative fructose-bisphosphate aldolase
2.3pRL120027AldolasePGN0.8623.92NE0.9321.46NE3.3.15Putative aldolase
2.3pRL120196Fructose-1,6-bisphosphate aldolasePGN0.9520.67NE122.53NE3.3.9Putative fructose-bisphosphate aldolase
2.4RL2513tpiATriosephosphate isomeraseGN0.914.56NE0.924.22NE3.6.0Putative triosephosphate isomerase
2.4pRL120209tpiATriosephosphate isomerasePVGI0.382.33GD0.888.14NE3.6.0Putative triosephosphate isomerase
2.5RL4007gapGlyceraldehyde-3-phosphate dehydrogenaseVGI00ES19NE3.5.1Putative glyceraldehyde-3-phosphate dehydrogenase
2.6RL4011pgkPhosphoglycerate kinaseVGI0.253.67GD0.8338.2NE3.5.1Putative phosphoglycerate kinase
2.7RL0179gpmAPhosphoglyceromutaseVGI0.361.5GD0.739.88NE3.5.5Putative 2,3-bisphosphoglycerate-dependent phosphoglycerate mutase (Phosphoglyceromutase) (PGAM) (BPG-dependent PGAM) (dPGM)
2.7RL2655Hypothetical proteinGN0.8810.71NE19.38NE0.0.0Hypothetical protein
2.7RL0954gpmBPhosphoglycerate mutaseGN119.22NE0.8921.38NE3.5.5Putative phosphoglycerate mutase
2.7RL1010gpmBPhosphoglycerate mutaseGN0.8315.2NE0.8326.2NE3.5.5Putative phosphoglycerate mutase
2.7RL2997Phosphoglycerate mutaseGN134.29NE139.12NE3.5.5Putative phosphoglycerate mutase
2.8RL2239enoPhosphopyruvate hydrataseVGI0.191GD0.814.77NE3.5.5Putative enolase
2.9RL4060pykAPyruvate kinaseGI0.238.67ES0.924.83GD3.5.5Putative pyruvate kinase
2.10RL1086ppdKPyruvate phosphate dikinaseGN0.8421.26NE0.9124.69NE3.5.5Pyruvate, phosphate dikinase (pyruvate, orthophosphate dikinase)
TRICARBOXYLIC ACID CYCLE
3.1RL2241pdhAPyruvate dehydrogenase subunitGI00ES0.181GD3.5.5Putative pyruvate dehydrogenase subunit A
3.1RL2242pdhBPyruvate dehydrogenase subunit betaGI00ES0.221.25GD3.5.5Putative pyruvate dehydrogenase subunit B
3.1RL2243pdhCDihydrolipoamide acetyltransferase component of pyruvate dehydrogenase complexGI00ES00GD3.5.5Putative dihydrolipoamide acetyltransferase component of pyruvate dehydrogenase complex (PDC)
3.1pRL80081HydrolasePGN0.869.33NE0.869.33NE3.3.15Putative hydrolase
3.2RL2234gltAType II citrate synthaseVGI0.74.32GD0.8514.09NE3.5.8Putative citrate synthase
3.2RL2508gltACitrate synthase IIGN0.8514.82NE113.54NE3.5.8Putative citrate synthase II
3.2RL2509citACitrate synthase 2GN0.819NE0.819.17NE3.5.8Putative citrate synthase I
3.3RL4536acnAAconitate hydrataseGI0.051ES0.051ES3.5.8Putative aconitate hydratase
3.4RL2631icdIsocitrate dehydrogenaseGI0.1210.5ES0.128ES3.5.8Putative isocitrate dehydrogenase [NADP]
3.5RL4435sucA2-oxoglutarate dehydrogenase E1 componentGI0.051.5ES0.231.5GD3.5.8Putative 2-oxoglutarate dehydrogenase E1 component
3.5RL4433citMDihydrolipoamide succinyltransferaseGI0.29ES0.34.33GD3.5.8Putative dihydrolipoyllysine-residue succinyltransferase component of 2-oxoglutarate dehydrogenase
3.6RL4436sucDSuccinyl-CoA synthetase subunit alphaGI0.151GD0.231.33GD3.5.8Putative succinyl-coa synthetase alpha chain
3.6RL4438sucCSuccinyl-CoA synthetase subunit betaGI0.091GD0.361GD3.5.8Putative succinyl-coa synthetase beta chain
3.7RL4443sdhBSuccinate dehydrogenase iron-sulfur subunitGI0.133GD0.732.82GD3.5.8Putative succinate dehydrogenase iron-sulfur protein
3.7RL4444sdhASuccinate dehydrogenase flavoprotein subunitGI0.531.5GD0.763.77GD3.5.8Putative succinate dehydrogenase flavoprotein subunit
3.7RL4445sdhDSuccinate dehydrogenase hydrophobic membrane anchor proteinGI0.671.25GD0.674GD3.5.8Putative succinate dehydrogenase hydrophobic membrane anchor protein
3.7RL4446sdhCSuccinate dehydrogenase cytochrome b556 subunitGI0.461.83GD0.774.6GD3.5.8Putative succinate dehydrogenase cytochrome b556 subunit
3.8RL2701fumCFumarate hydratase class IIGN0.9418.56NE0.8819.8NE3.5.8Putative fumarate hydratase class II
3.8RL2703fumAFumarate hydratase class IGN0.9323.36NE0.9620.81NE3.5.8Putative fumarate hydratase class I, aerobic
3.9RL4439mdhMalate dehydrogenaseGI0.251.33GD0.171GD3.5.8Putative malate dehydrogenase
3.10RL0761-Isocitrate lyaseGN0.9117.29NE0.8325.79NE3.3.5Putative isocitrate lyase
3.11RL0054glcBMalate synthase GGN0.8820NE124.06NE3.3.5Putative malate synthase
3.12RL0407maeBMalic enzymeGN0.8618.97NE0.8924.74NE3.5.8Putative NADP-dependent malate dehydrogenase
3.12RL2671maeBMalic enzymeGN0.8331.47NE0.9626.41NE3.5.8Putative NADP-dependent malic enzyme
3.13RL0037pckAPhosphoenolpyruvate carboxykinaseGN116.09NE0.9121.55NE3.3.4Putative phosphoenolpyruvate carboxykinase
3.14RL4638Pyruvate carboxylaseVGI00ES0.9429.35NE3.5.8Putative pyruvate carboxylase
PENTOSE PHOSPHATE PATHWAY
4.1RL2807gnd6-phosphogluconate dehydrogenaseGN0.9210.27NE0.9212.27NE3.5.6Putative phosphogluconate dehydrogenase
4.1RL3998gntZ6-phosphogluconate dehydrogenaseGN0.8920.68NE121.89NE3.5.6Putative 6-phosphogluconate dehydrogenase,decarboxylating
4.2RL2547rpiBRibose-5-phosphate isomerase BGN0.5725.75NE0.7116NE3.3.9Putative ribose-5-phosphate isomerase B
4.2RL2698rpiARibose-5-phosphate isomerase AGI00ES0.337ES3.3.9Putative ribose-5-phosphate isomerase A
4.2pRL120210Ribose-5-phosphate isomerase BPVGI0.835.2GD0.8321.8NE3.3.9Putative ribose-5-phosphate isomerase B
4.3RL2598rpeRibulose-phosphate 3-epimeraseVGI0.382.33GD0.639.2NE3.3.9Putative ribulose phosphate 3-epimerase
4.3pRL120033D-allulose-6-phosphate 3-epimerasePGN120.6NE121NE3.3.9Putative D-allulose-6-phosphate 3-epimerase
4.4, 4.6RL2718TransketolaseGN116.23NE0.9214.83NE3.3.15Putative transketolase, alpha subunit, terpenoid biosynth?
4.4, 4.6RL2719TransketolaseGN0.9317.31NE0.9324.38NE3.3.15Putative transketolase, beta subunit, terpenoid biosynth?
4.4, 4.6RL4006cbbTTransketolaseGN0.678.38NE0.9218.95NE3.5.1Putative transketolase
4.4, 4.6pRL100453TransketolasePGN0.8617.16NE0.922.46NE3.5.6Putative transketolase
4.5RL4203talBTransaldolase BGN0.564.2NE0.8932.13NE3.3.9Putative transaldolase B

Growth phenotypes of genes involved in RLV3841 central carbon metabolism.

Plasmid growth impaired genes

Mutation of genes encoded on RLV3841 megaplasmids that resulted in a growth impaired phenotype were assigned as plasmid growth impaired (PGI), while plasmid genes that when mutated impaired growth on VMM or TY uniquely were designated PVGI and PTGI respectively. Collectively, 48 genes distributed across the 6 megaplasmids were predicted to result in a PGI phenotype when mutated (Supplementary File 1). The 48 PGI genes included 11 Riley functional classes (Figure 5). All 6 plasmids were observed to have a set of 3 replication protein encoding genes categorized as PGI. Plasmid pRL11 was observed to carry the most PGI biosynthetic genes including 6 genes of an 8 gene cluster predicted to code for cobalamin biosynthesis (Figure 5).

Figure 5

Discussion

The CFG of RLV3841

Young et al. (2006) used phylogeny of conserved genes and GC% to describe a core and accessory genome within the RLV3841. The present study helps to improve the level of resolution for distinguishing between the RLV3841 core genes and accessory genes using functional genetic screening. We propose that RLV3841 has a CFG which can be defined as the core set of genes required for normal growth, independent of any specific environmental condition. In this study we approximate the CFG of RLV3841 by contrasting INSeq generated data sets from growth on complex peptide rich and minimally defined media with mannitol as the sole carbon source. Cross referencing VGI and TGI chromosomal genes identified an overlapping set of 491 genes that we putatively assigned to the CFG of RLV3841, as their loss of function resulted in a GI phenotype that appears to be independent of the growth media used. The number of CFG genes was less than that of both the TGI and VGI genes, which represented 563 and 661 genes respectively (Figure 1). This is to be expected if the CFG represents a central set of genes required for core cellular functions.

Defining a CFG in RLV3841 provides context for subsequent INSeq and classical genetic studies. For example, the described CFG for RLV3841 will help explain if a mutation resulting in a GI phenotype in a plant associated environment is the result of impairing some aspect of the RLV3841 CFG or is instead the result of a plant specific interaction. This is particularly important for genes encoding hypothetical proteins of unknown function. Summarizing the distribution of gene functions in the CFG identified 20 functional groupings (Figure 2). Five major categories accounted for over half of the total CFG (287 genes). These 5 functional categories included: macromolecule synthesis and modification (98 genes), energy and carbon metabolism (50 genes), ribosome constituents (48 genes), cell envelope (46 genes), and hypothetical proteins (50 genes) (Figure 2). Hypothetical proteins aside, these 4 categories logically compose the majority of the CFG as they represent the central genes required for the synthesis of the major cellular components, central conversion of carbon for generation of reductant and ATP, production and modification of protein synthesis machinery, and synthesis of the cell envelope.

The fact that genes encoding hypothetical proteins was one of the five major categories assigned to the CFG reinforces the broadly acknowledged observation among geneticists that the function of many genes involved in core cellular processes still remain uncharacterized. INSeq is a powerful technique that can help identify hypothetical proteins required for survival in specific growth conditions, and ultimately will advance our rate of discovery in this large and under studied category of genes. For example, in this study we identified a total of 103 hypothetical proteins observed to have an impaired growth phenotype under at least one growth condition; of which 19 were VGI, 20 were TGI, 14 were plasmid associated, and the remainder belonged to the CFG (Table 1).

Chromosomal VMM and TY specific growth impairment

Growth on minimal media requires the biosynthesis of several metabolites that can be scavenged from a complex growth media. Therefore, it was expected that there were more VGI genes compared to TGI genes, and that a substantial portion of the VGI genes are functionally classified for the biosynthesis of amino acids (30 genes), cofactors and carriers (25 genes), nucleotides (20 genes), and metabolic intermediates (15 genes) (Figure 2).

To further interrogate the VGI dataset, two previously uncharacterized genes, RL0920 a putative ATP-binding mrp family protein and RL3335 a putative lysophospholipase, were selected for targeted mutagenesis. A growth curve in liquid culture was used to characterize the generation time and growth response of the mutants. As expected, MA0920 and MA3335 were substantially growth impaired with increased generation times in VMM-mannitol. After 72 h of growth the mutant cultures were 1/3 the density of the wildtype in VMM-mannitol, whereas in TY they had achieved similar densities to the wildtype (Figure 3).

The TGI genes were composed of the smallest number of GI genes and the least functional complexity (Figure 2). Unlike the VGI genes, the general mechanism underlying the TGI genes does not hinge on metabolic biosynthesis, which is not surprising as complex media will contain many, if not all, metabolic intermediates required for growth. The largest functional categories observed in the TGI genes were hypothetical proteins (20 genes), cell envelope (11 genes), macromolecule synthesis and modification (9 genes), and transport and binding proteins (8 genes). Previous studies have identified several TGI genes, which collectively are implicated in outer membrane integrity or periplasmic function, suggesting that growth on complex media may require specific envelope traits (Gilbert et al., 2007; Vanderlinde et al., 2009, 2011; Foreman et al., 2010; Vanderlinde and Yost, 2012a,b). Additionally, we observed a putative cold shock response protein (RL2964), a LysR family transcriptional regulator, multiple transcriptional response regulators from predicted two-component systems (RL0036, RL1433, RL1729), a histidine kinase component of a two-component system (RL1382), as well as hypothetical proteins containing transmembrane domains (RL1526, RL2641), AAA–ATPase domain (RL2625), or N-terminal secretion signals (RL3761, RL1528, RL1618A, RL2086, RL4716) that were GI on TY medium (Supplementary File 1). These findings suggest that the TGI phenotype collectively may be centered around cell sensing and stress response at the cell envelope-environment interface.

Central carbon metabolism of mannitol

Using INSeq we were able to screen the 4 major conserved central carbon metabolic pathways for genes required for growth on mannitol (Figure 4; Table 2). As expected, disruption of the genes required for mannitol transport and conversion to F6P, along with glucose-6-phosphate isomerase (pgi) required for conversion of F6P into glucose-6P (Keele et al., 1969; Arias et al., 1979), resulted in a GI phenotype. Genes required for conversion of G6P into gluconate-6P (GN6P) through the ED pathway (overlapping the oxidative branch of the pentose phosphate pathway) resulted in a GI phenotype when mutated on both TY and VMM (Figure 4: reaction 1.1–2). The essential nature of these reactions may be due to several factors: (1) the NADPH generated during conversion (Spaans et al., 2015), (2) the possibly toxic accumulation of phosphorylated intermediates (Cerveñanský and Arias, 1984; Kadner et al., 1992), (3) the role of G6P in the biosynthesis of osmoprotectants (Barra et al., 2003), and (4) the need for carbon flux into the ED pathway for glycolytic growth (Arias et al., 1979; Glenn et al., 1984; Stowers, 1985). Conversion of GN6P into pyruvate through the ED pathway was determined to be VGI (Figure 4: reaction 1.3–4). Mutations in the upper EMP pathway, aside from pgi, were observed to be neutral, which is in agreement with previous work (Glenn et al., 1984). The lower EMP pathway (sometimes considered shared by the ED pathway), converts glyceraldehyde-3P (GA3P) into pyruvate, with mutants at all enzymatic steps appearing GI on mannitol, and at some steps on TY as well (Figure 4: reaction 2.5–9). The VGI nature of the lower EMP when grown on mannitol is possibly due to mutants being unable to metabolize GA3P produced from the ED pathway into the amino acid precursors glycerate-3P (G3P) or phosphoenolpyruvate (PEP), and as well catabolize GA3P into pyruvate (Finan et al., 1988) for use in the TCA cycle. The overall GI phenotype of mutants in the entire ED pathway, in contrast to the EMP pathway, suggests that it is the central pathway for glycolytic conversion of carbon into the central carbon intermediate pyruvate. This is in agreement with previous research indicating the ED pathway to be the preferred route of carbon metabolism for glycolytic growth of rhizobia and closely related genera (Stowers, 1985; Fuhrer et al., 2005; Geddes and Oresnik, 2014).

Conversion of pyruvate into the TCA cycle was observed to have 2 unique GI pathways (Figure 4: reaction 3.1–14). Conversion of pyruvate into the TCA through acetyl-CoA as an intermediate is a less direct route than the direct conversion of pyruvate into oxaloacetate, and mutants in pyruvate carboxylase (Figure 4: reaction 3.14) were observed to be more severally GI than in citrate synthase (Figure 4: reaction 3.2). Additionally, on TY media mutants in pyruvate dehydrogenase appeared GI, while mutants in pyruvate carboxylase were not. These findings are in agreement with anaplerotic production of oxaloacetate (OAA), via pyc-mediated fixation of CO2, being important for replenishing OAA pools under minimal growth conditions (Gokarn et al., 2001; Sirithanakorn et al., 2014).

When grown on mannitol as a sole carbon source, mutants in TCA cycle genes were all observed to be GI, aside from the conversion from fumarate to malate (Figure 4: reaction 3.2–3.9). Mutants in fumC and fumA (RL2701 and RL2703) were observed to be growth neutral, possibly due to functional redundancy between the two isozymes, which has been previously reported in Bradyrhizobium japonicum (Acuña et al., 1991). Future INSeq studies with prolonged exposure to selective pressure may identify which isoenzyme is dominant. Several TCA steps were observed to be GI on both VMM-mannitol and TY media, confirming that the TCA cycle is an important component of the CFG in RLV3841. Mutants in isocitrate dehydrogenase (icd) were both VGI and TGI (Figure 4: reaction 3.4). It has been previously shown that mutants in icd develop glutamate auxotrophy (McDermott and Kahn, 1992), which may explain the impaired growth phenotype on minimal medium, but does not explain growth impairment on peptide rich TY medium. Mutants in sucB and citM (sucA) were also observed to be growth impaired on both media (Figure 4: reaction 3.5). For growth on VMM-mannitol, the GI nature of these mutants is possibly due to increased α-ketoglutarate concentration due to the inability to metabolize into succinyl-CoA, and possibly perturbation of the GOGAT cycle via shunting of excess α-ketoglutarate (Bravo and Mora, 1988; Dunn, 1998).

The genes encoding enzymes for the glyoxalate by-pass, phosphoenolpyruvate carboxykinase and fructose bisphosphate aldolase, were observed to be GN on VMM-mannitol and TY media; suggesting that gluconeogenesis is not be required for growth in either condition (Kornberg, 1966; McKay et al., 1985; Stowers, 1985). This seems reasonable, as growth on mannitol is presumably glycolytic, therefore sugar conversion can be performed on metabolic intermediates generated during the breakdown of mannitol. And on TY media, many carbohydrates and polyols are likely already present in trace amounts, mitigating the need for gluconeogenesis.

Almost every gene involved in the non-oxidative branch of the PP pathways was observed to have a neutral impact on growth when mutated. The only two reactions in the PP pathway that were GI on mannitol were for the conversion of ribulose-5P into ribose-5P, or alternatively xylulose-5P (Figure 4: reaction 4.2 and 4.3). The mutation of ribose-5-phosphate isomerase A appearing GI is logical as ribose-5P is a precursor for 5-phosphoriboosyl-α-1-pyrophosphate, which is the branching point for flux of carbon in nucleotide, histidine, nicotinamide, and tryptophan biosynthesis (Kilstrup et al., 2005; Switzer, 2009). The conversion of GN6P into ribulose-5P however was observed to be GN. There are two possible explanations for mutants in this step appearing GN: (1) functional redundancy in isozymes Gnt and GntZ compensates for mutation of either (Figure 4: reaction 4.1), or (2) ribulose-5P can be replenished from xylulose-5P derived from either F6P and G3P being shunted into the PP pathway (Figure 4: reaction 4.4–6) or the phosphoketolase pathway (EC 4.1.2.9). In general, the interconnectedness of the PP pathway makes it difficult to study single gene knock-outs, as mutants may adapt to interrupted pathways by using alternative metabolic routes or isozymes (Geddes and Oresnik, 2014).

Plasmid growth impaired genes

There are unique opportunities and challenges for exploring plasmid biology when conducting INSeq experiments on bacterial species with genomes containing multiple large plasmids. Mutations that result in the loss of a plasmid from the accessory genome, due to impaired plasmid stability, will appear phenotypically identical to a GI mutant lost from the mutant pool due to a decreased growth rate. Therefore, it cannot be concluded directly from the INSeq data if a particular transposon insertion within a plasmid resulted in a GI phenotype, or instead compromised plasmid stability or replication. All plasmids contained a three gene cluster of rep genes that were observed to be essential (PGI) when mutated (Figure 5; Supplementary File 1), which in conjunction with the annotated function of these genes suggests the loss of these Tn insertion tags from the mutant population was due to impaired plasmid replication.

Beyond identifying putative rep genes, INSeq can be useful in identifying plasmid genes that provide the host cell with growth benefits under specific conditions. For example, pRL11 contains a putative 8 gene operon (pRL110625-32) predicted to be involved in cobalamin biosynthesis, that was severely PGI on VMM-mannitol, and moderately PGI on TY when mutated. Previous studies in R. etli identified similar growth phenotypes when a homologous cobalamin biosynthetic cluster on p42e was deleted (Landeta et al., 2011). Additionally, pRL120209 (putative tpiA) and pRL120210 (putative rpiB), which encode enzymes predicted to function in central carbon metabolism, were found to be PGI when grown on mannitol as a sole carbon source. Their chromosomal homologs RL2513 (tpiA) and RL2547 (rpiB) were both observed to be GN (Table 2). In a closely related R. leguminosarum bv. viciae strain VF39, the homologs of pRL120209 and pRL120210 are required for growth on erythritol as a sole carbon source (Yost et al., 2006). This suggests that pRL12 may carry genes important for the normal growth of RLV3841 under specific conditions, which is in agreement with previous studies that showed pRL12 cured strains of R. leguminosarum were unable to grow on minimal media (Hynes et al., 1989).

Technical considerations of INSeq in RLV3841

INSeq, like all high-throughput molecular techniques, is not without limitations. Genes with large regions of sequence duplication, or no mariner “TA” insertion sites, cannot be assayed using INSeq. These genes represent only 1.9% of the genome. However, the targeted library preparation method and robust statistical analysis afforded by the use of MmeI-adapted mariner transposon appears to outweigh its disadvantages. A sufficient saturation of neutral mariner insertion sites within the mutant community allows for confident identification of regions that lack insertions due to the negative selection resulting from a GI phenotype. In this and previous, work a sufficient level of neutral “TA” site saturation has been recovered to allow Bayesian methods of analysis, using a relatively modest amount of sequencing data when compared to other mariner INSeq studies. Considerations in inoculation density, the number of generations of growth during negative selection, and the ability to recover mutant populations needs to be carefully considered in order to ensure enough complexity is retained in the mutant pools post-selection to allow for statistical analysis.

Funding

The presented research was conducted with support from a Discovery Grant awarded by the Natural Sciences and Engineering Council of Canada.

Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Statements

Author contributions

BP and CY conceived and designed the research; BP and MA conducted the experiments; BP conducted the data analysis; BP and CY prepared and finalized the manuscript.

Acknowledgments

We thank Dr. Barney Geddes for his helpful discussions and comments concerning RLV3841 metabolism, and Dr. Stephen Fitzgerald for his helpful criticisms of the draft manuscript.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Supplementary material

The Supplementary Material for this article can be found online at: http://journal.frontiersin.org/article/10.3389/fmicb.2016.01873/full#supplementary-material

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Summary

Keywords

Rhizobium, INSeq, Tn-Seq, core functional genome, metabolism, mannitol

Citation

Perry BJ, Akter MS and Yost CK (2016) The Use of Transposon Insertion Sequencing to Interrogate the Core Functional Genome of the Legume Symbiont Rhizobium leguminosarum. Front. Microbiol. 7:1873. doi: 10.3389/fmicb.2016.01873

Received

06 June 2016

Accepted

07 November 2016

Published

22 November 2016

Volume

7 - 2016

Edited by

Teresa Rebecca De Kievit, University of Manitoba, Canada

Reviewed by

Brian Thomas Driscoll, McGill University, Canada; Svetlana Yurgel, Dalhousie University, Canada

Updates

Copyright

*Correspondence: Christopher K. Yost

This article was submitted to Plant Biotic Interactions, a section of the journal Frontiers in Microbiology

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All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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