Literature DB >> 25433486

Construction of a mariner-based transposon vector for use in insertion sequence mutagenesis in selected members of the Rhizobiaceae.

Benjamin J Perry1, Christopher K Yost2.   

Abstract

BACKGROUND: The Rhizobiaceae family of Gram-negative bacteria often engage in symbiosis with plants of economic importance. Historically, genetic studies to identify the function of individual genes, and characterize the biology of these bacteria have relied on the use of classical transposon mutagenesis. To increase the rate of scientific discovery in the Rhizobiaceae there is a need to adapt high-throughput genetic screens like insertion sequencing for use in this family of bacteria. Here we describe a Rhizobiaceae compatible MmeI-adapted mariner transposon that can be used with insertion sequencing for high-throughput genetic screening.
RESULTS: The newly constructed mariner transposon pSAM_Rl mutagenized R. leguminosarum, S. meliloti, and A. tumefaciens at a high frequency. In R. leguminosarum, mutant pools were generated that saturated 88% of potential mariner insertions sites in the genome. Analysis of the R. leguminosarum transposon insertion sequencing data with a previously described hidden Markov model-based method resulted in assignment of the contribution of all annotated genes in the R. leguminosarum 3841 genome for growth on a complex medium. Good concordance was observed between genes observed to be required for growth on the complex medium, and previous studies.
CONCLUSIONS: The newly described Rhizobiaceaee compatible mariner transposon insertion sequencing vector pSAM_Rl has been shown to mutagenize at a high frequency and to be an effective tool for use in high-throughput genetic screening. The construction and validation of this transposon insertion sequencing tool for use in the Rhizobiziaceae will provide an opportunity for researchers in the Rhizobiaceae community to use high-throughput genetic screening, allowing for significant increase in the rate of genetic discovery, particularly given the recent release of genome sequences from many Rhizobiaceae strains.

Entities:  

Mesh:

Substances:

Year:  2014        PMID: 25433486      PMCID: PMC4255674          DOI: 10.1186/s12866-014-0298-z

Source DB:  PubMed          Journal:  BMC Microbiol        ISSN: 1471-2180            Impact factor:   3.605


Background

Insertion sequencing (INSeq) is a technique for high throughput forward genetic screening that has recently become a favorable approach to studying gene function at the genome scale [1,2]. INSeq relies on the use of next-generation DNA sequencing to audit the presence of hundreds of thousands of unique transposon insertions present in a pool of mutants that collectively saturate that organism’s genome with transposition events [3-6]. In general, INSeq based methods can use two different methods to analyze gene function. The first relies on sequencing the transposon insertions sites in an input pool and an output pool of transposon mutants, and using the differential representation of mutants in each pool to infer the functional role of each gene with sufficient representation of insertion sites [7]. The second method relies on creating a mutant pool sufficiently large and complex that it saturates the genome and allows for analysis of regions with statistically fewer, or no, insertions than expected using a non-parametric [8], Bayesian model [9], or hidden Markov model (HMM) based analysis [10,11]. Both approaches have been applied to several species of bacteria to investigate genes involved in colonization of hosts [12-14], resistance to antibiotics [15], characterizing metabolic pathways [16,17], deducing core essential genomes [18-24], and recently, examining genes involved in colonizing soil environments [7]. The Rhizobiaceae is a family of alpha-proteobacteria containing three agriculturally important genera of soil bacteria: Rhizobium, Sinorhizobium and Agrobacterium [25]. Members in these genera share a unique relationship with plant hosts. Rhizobium, and Sinorhizobium are both able to enter into an endosymbiotic mutualism with certain species of leguminous plants, in which the Rhizobia fix atmospheric nitrogen into a biologically available form for the plant in return for fixed carbon and energy [26]. This symbiosis is particularly important in the context of agriculturally produced pulse crops, where the Rhizobium legume symbiosis affords farmers the ability to reduce the rate of synthetic nitrogen fertilizers application [27]. Conversely, the relationship of Agrobacterium with its plant host is parasitic. In this symbiosis, Agrobacterium infects the tissues of a plant host and transforms specific virulence genes into the host’s DNA, resulting in tumorgenic growth with altered cellular metabolism that the bacteria then colonize [28]. The formation of several galls at the stem root interface results in a plant infection known as crown gall, that can have a significant impact on the crop yield of stone fruits, berries, and nuts [29]. Genetic research in Rhizobium, Sinorhizobium, and Agrobacterium has relied heavily on the use of transposon mutagenesis screens. Perhaps the most commonly used transposon in the Rhizobiaceae is the Tn5 transposon [30-32]. The use of Tn5 genetic screens is numerous and has helped to elucidate genes involved in metabolism [33-35], desiccation tolerance [36,37], and cell envelope physiology [38] for example. Implementation of transposon mutagenesis with the high-throughput techniques of INSeq promise to accelerate the rate at which genetic research in the Rhizobiaceae is currently performed. Furthermore, it would allow for comprehensive genome screens for genes involved in host interactions, metabolism, survival, and possibly plasmid maintenance, under any testable condition. The mariner class of transposon is a host independent transposon that unlike the random insertion transposons such as Tn5 is known to specifically insert into an organism's genome at thymine-adenine (‘TA’) motifs [39]. Because of this defined insertion preference, transposition events can be modeled in silico in any sequenced genome to understand the defined number of insertion locations that exist. This type of analysis can be further refined to examine insertions per gene or within any defined region of interest in the genome. Furthermore, using a transposon with a defined number of insertion loci allows for robust statistical analysis when used in a transposon insertion sequencing methodology. One such analysis package uses a HMM to predict the essentiality of every gene under a particular growth condition in an organism’s genome given a sufficiently dense INSeq data set [10]. The advantages of this type of analysis is that it does not solely rely on the comparison of an input and output pool of mutants as it uses statistical inference on a defined number of insertion sites to infer an over represented or under represented number of insertions within a given region. Here we describe the modification of a previous INSeq mutagenesis vector pSAM_Bt, which uses a mariner class transposon with modified IR elements, to selectively capture 15–16 bp of genomic DNA adjacent to the transposon insertion [4]. The DNA fragment is then processed for next-generation DNA sequencing. The new INSeq vector uses a Rhizobiaceae specific promoter to drive the expression of the plasmid-borne transposase, and has had the erythromycin resistance gene cassette replaced with a neomycin resistance gene cassette (ntpII) for ease of selection in the Rhizobiaceae. The host range of transposition with pSAM_Rl was examined and an INSeq experiment was performed on the model organism Rhizobium leguminosarum bv. viciae 3841 (RLV3841) to examine the insertion density that the pSAM_Rl transposon could achieve. Furthermore, the functionality of the transposon in RLV3841 for INSeq was also examined.

Results

Construction of pSAM_Rl and transposition frequency within the Rhizobiaceae

The MmeI-adapted mariner transposon suicide delivery vector pSAM_Rl was constructed from a previously described MmeI-adapted mariner delivery vector pSAM_Bt [4]. To do so, the 974 bp EryR in pSAM_Bt was replaced with a 979 bp Neo/KanR resistance cassette from pSC189 and the 304 bp Bacteroides thetaiotaomicron rpoD promoter region was replaced with a 366 bp RLV3841 rpoD promoter region. A map of the pSAM_Rl construct is shown in Figure 1, with restriction enzyme sites used for cloning indicated. The pSAM_Rl construct was maintained in E. coli strain SM10λpir as this strain harbours both the λpir gene, required for the replication of R6Kƴ oriR, and chromosomally integrated tra genes, required for conjugative transfer via the plasmid borne RP4-oriT. Analysis of the transposition frequency of the pSAM_Rl mariner transposon was evaluated via conjugative transfer of the pSAM_Rl suicide vector from E. coli SM10λpir into R. leguminosarum, S. meliloti, and A. tumefaciens. Transposition frequency was highest in RLV3841, yielding an average of 2.01 × 10−4 transposon mutants per recipient cell. The frequencies of transposition in A. tumefaciens and S. meliloti were observed to be 8.04 × 10−5 and 2.54 × 10−5 mutants per recipient cells, respectively.
Figure 1

pSAM_Rl plasmid map. Restriction enzymes used for cloning are indicated. Antibiotic markers (ampicillin, AmpR; neomycin/kanamycin, nptII), origin of replication (R6K y oriR), origin of transfer (RP4-oriT), transposase (himar1C9), tranposase promoter (rpoD 5'UTR), MmeI-adapted mariner inverse repeats (IR_R, IR_L), transposon borne Rho-independant terminator (rrnB T1, rrnB T2). Plasmid map produced using Snapgene software.

pSAM_Rl plasmid map. Restriction enzymes used for cloning are indicated. Antibiotic markers (ampicillin, AmpR; neomycin/kanamycin, nptII), origin of replication (R6K y oriR), origin of transfer (RP4-oriT), transposase (himar1C9), tranposase promoter (rpoD 5'UTR), MmeI-adapted mariner inverse repeats (IR_R, IR_L), transposon borne Rho-independant terminator (rrnB T1, rrnB T2). Plasmid map produced using Snapgene software.

Analysis of pSAM_Rl transposition in the RLV3841 genome

Analysis of pSAM_Rl transposon integration was performed using three independent pools of ~1.9 × 106 transposon mutants. Mutant pools were grown for approximately 16 generations (48 hours) on TY basal medium. The mutants were collected en masse and the 15–16 bp of genomic DNA adjacent to the transposon insertion was sequenced using a modified INSeq method on the Ion Torrent PGM. Transposon insertion sequences from the three replicate samples were then pooled and aligned onto the RLV3841 genome, resulting in 2,319,239 usable transposon insertion tags (Tn-tags) for analysis with the transposon HMM (Tn-HMM) python module [10]. From in silico analysis it was calculated that 140,056 potential mariner transposon insertion sites existed within the RLV3841 genome. Of these, 116,544 unique transposon insertions were observed in the composite data collected from the three pSAM_Rl mutant pools grown on TY agar. This corresponded to an overall insertion density of 83% in the RLV3841 genome, with insertion density across replicons ranging between 68% to 88% (Table 1). The mean read count per mariner insertion site, observed to have a transposon insert, ranged from 18.57 to 22.09 sequence reads per insertion across all replicons with the median read count per insertion ranging from 10.0 to 13.0 reads per insertion (Table 1).
Table 1

Summary of pSAM_Rl transposition in RLV3841

Replicon Size (bp) GC% Gene number Potential insertions Observed insertions Insertion density A Mean read count B Median read count C
Chrom505714261.10480089660733750.8220.4613.00
RL1287002161.0079014845131220.8818.5712.00
RL1168420261.0064412456109640.8819.9713.00
RL1048813559.604711000384700.8517.1910.00
RL935278261.00313635954530.8619.6513.00
RL814746358.70142311827020.8717.9611.00
RL715154657.60186361524580.6822.0912.00
Genome775129160.0073461400561165440.8319.4112.00

AInsertion Density is the fraction of the 'TA' insertions sites that contain a Tn insertion.

BMean Read Count is the mean number of Tn insertions within 'TA' sites.

Median Read Count is the median number of Tn insertions within a specific 'TA' site.

Summary of pSAM_Rl transposition in RLV3841 AInsertion Density is the fraction of the 'TA' insertions sites that contain a Tn insertion. BMean Read Count is the mean number of Tn insertions within 'TA' sites. Median Read Count is the median number of Tn insertions within a specific 'TA' site.

Distribution of phenotypic classes throughout the RLV3841 genome

Each RLV3841 replicon was analyzed using the Tn-HMM python module [10] to classify genes based on the observed density of Tn insertions in each gene within the mixed mutant cell population. For example, a gene which had no detectable Tn insertion sites following DNA sequencing from the pooled mutant DNA suggests cells carrying a mutation in this gene were not maintained in the population. These genes are described as conferring an essential phenotype. The procedure is described in greater detail in the Materials and Methods. The seven replicons of RLV3841 were analyzed separately to account for variations in mean read depth, insertion density, and median read count between the replicons that may have been a result of their independent replication within the cell. Across all replicons 89.5% of the genes were observed to have a neutral or negligible impact on the ability of RLV3841 to grow on TY medium when disrupted by the transposon (Table 2). Genes identified as conferring a phenotype classification of essential, growth-defective, and growth-advantage were observed to represent 5.6%, 4.0%, and 0.1% of the genes within the genome, respectively. Throughout the genome, 10 genes contained no 'TA' transposon insertions sites and as such could not be assigned to a growth effect state. However this represents only 0.14% of the total predicted genes within the genome (Table 2).
Table 2

Summary of phenotypic classes across the RLV3841 genome

Replicon Mapped reads Genes per specific phenotypic class A
ES GD NE GA No Data B
Chrom15010323172724176350
pRL122436998377432
pRL1121894415961433
pRL1014562115344733
pRL091071447130500
pRL08485123113710
pRL075428744812482

ES = Essential, GD = Growth-defective, NE = Neutral, GA = Growth-advantage.

AGenes were designated to a phenotypic class based on the state most frequently observed in the TA sites within the boundaries of an annotated gene, except in the case of essential genes which could also have been assigned to the ES state if they contained a stretch of ES TA sites that was statistically significant based on the extreme value distribution. Please refer to the Materials and Methods section for more detail.

BGenes lacking TA motifs.

Summary of phenotypic classes across the RLV3841 genome ES = Essential, GD = Growth-defective, NE = Neutral, GA = Growth-advantage. AGenes were designated to a phenotypic class based on the state most frequently observed in the TA sites within the boundaries of an annotated gene, except in the case of essential genes which could also have been assigned to the ES state if they contained a stretch of ES TA sites that was statistically significant based on the extreme value distribution. Please refer to the Materials and Methods section for more detail. BGenes lacking TA motifs.

Specific essential genes within the RLV3841 genome

The defined phenotypic class of several house-keeping genes involved in ATP synthesis, cell divisions, DNA replication, and RNA transcription are summarized in Table 3. Additionally, Table 3 summarizes the essential nature of plasmid specific replication genes for each of the 6 plasmids contained in the RLV3841 genome that are required for plasmid maintenance during cell division. From previous analysis [38], genes known to be required for growth on TY medium are summarized at the end of Table 3 with their essential nature, as determined by the 4 phenotypic classes, reported by the Tn-HMM software.
Table 3

Selected genes in RLV3841 cultured on TY agar with Tn insertions substantially below expected levels

Locus Gene Gene annotation Potential insertions A Insertion density B Mean read count C Phenotypic class D
Selected chromosomal house keeping genes
RL0924 atpI Putative ATP synthase I40.0000.000ES
RL0925 atpB F0F1 ATP synthase subunit A120.0831.000ES
RL0926 atpC F0F1 ATP synthase subunit C70.0000.000ES
RL0927 atpG F0F1 ATP synthase subunit B'70.0000.000ES
RL0928 atpF F0F1 ATP synthase subunit B40.0000.000ES
RL4405 atpC F0F1 ATP synthase subunit Epsilon30.3331.000ES
RL4407 atpD F0F1 ATP synthase subunit Beta230.0431.000ES
RL4408 atpG F0F1 ATP synthase subunit Gamma120.0831.000ES
RL4409 atpA F0F1 ATP synthase subunit Alpha220.0000.000ES
RL4410 atpH F0F1 ATP synthase subunit Delta80.1251.000ES
RL4412 priA Primosome assembly protein PriA230.2614.000GD
RL3408 dnaG DNA primase230.0000.000ES
RL3298 ftsZ Cell division protein FtsZ90.0000.000ES
RL3299 ftsA Putative cell division protein FtsA120.0831.000ES
RL3300 ftsQ Putative cell division protein FtsQ140.0000.000ES
RL3308 ftsW Putative cell division protein FtsW130.0001.000ES
RL3965 ftsH Putative cell division protein FtsH190.1051.500ES
RL2515 gyrB DNA topoisomerase IV subunit B260.1159.333ES
RL2401 gyrA DNA gyrase subunit A340.0591.000ES
RL1723 dnaE DNA polymerase III subunit Alpha510.0781.000ES
RL4697 dnaE Putative DNA polymerase III subunit Alpha760.96123.562NE
RL0334 dnaN DNA polymerase III subunit Beta140.0711.000ES
RL2099 recJ Putative single-stranded-DNA-specific exonuclease170.2943.800GD
RL1766 rpoB DNA-directed RNA polymerase subunit Beta640.0161.000ES
RL1767 rpoC Putative DNA-directed RNA polymerase subunit Beta'610.0661.750ES
RL1798 rpoA Putative DNA-directed RNA polymerase subunit Alpha120.0000.000ES
RL0059 - Putative ATP-dependant helicase180.77821.714NE
RL0582 - Putative ATP-dependant helicase390.94918.730NE
RL1551 dnaC Putative replicative DNA helicase240.04224.000ES
Selected plasmid borne genes
pRL120001 repA Putative replication protein A210.0000.000ES
pRL120002 repB Putative replication protein B90.0000.000ES
pRL120003 repC Putative replication protein C130.0000.000ES
pRL110001 repA Putative replication protein A250.0401.000ES
pRL110002 repB Putative replication protein B160.0631.000ES
pRL110003 repC Putative replication protein C150.0671.000ES
pRL100001 repA Putative RepA replication protein190.0000.000ES
pRL100002 repB Putative RepB replication protein60.0000.000ES
pRL100003 repC Putative RepC replication protein220.0451.000ES
pRL90001 repA Putative replication partitioning protein300.0000.000ES
pRL90002 repB Putative replication partitioning protein190.0531.000ES
pRL90003 repC Putative replication initiation protein RepC150.0000.000ES
pRL80001 repA Putative replication protein RepA380.0000.000ES
pRL80002 repB Putative replication protein RepB230.0431.000ES
pRL80003 repC Putative replication initiation protein RepC280.0361.000ES
pRL70092 repA Putative replication protein340.5291.722GD
pRL70093 repB Putative replication protein B220.4551.100GD
pRL70094 repC Putative replication initiation protein RepC330.4551.200GD
Previously experimentally confirmed genes with a TY- defective phenotype
RL4692 ctpA Putative carboxy-terminal processing protease precursor140.4295.500GD
RL3501-Conserved hypothetical membrane protein420.6673.107GD
RL2815 fabF2 3-Oxoacyl acyl carrier protein synthase110.3641.000GD
RL1375 phaD2 Putative Na+/H+ antiporter subunit D260.1921.400GD
Examples of genes with higher than expected Tn insertions E
RL0868-Putative lipid A oxidase161.000113.688GA
RL2661-Putative transmembrane component of ABC transporter131.00062.846GA
RL0684-Putative transmembrane protein270.96364.346GA

ES = Essential, GD = Growth Defect, NE = Neutral, GA = Growth Advantage.

APotential insertions is the number of 'TA' nucleotide motifs within the gene.

BInsertion density is the fraction of all 'TA' insertions sites with a Tn insertion.

CMean read count is the mean number of Tn insertions at 'TA' sites with a Tn insertion.

DGenes were designated to a phenotypic class based on the state most frequently observed in the TA sites within the boundaries of an annotated gene, except in the case of essential genes which could also have been assigned to the ES state if they contained a stretch of ES TA sites that was statistically significant based on the extreme value distribution. Please refer to the Materials and Methods section for more detail.

EThree genes with the phenotypic classification of Growth-advantage were included to provide context to the insertional densities and mean read count of the Growth-advantage state compared to the essential state classification.

Selected genes in RLV3841 cultured on TY agar with Tn insertions substantially below expected levels ES = Essential, GD = Growth Defect, NE = Neutral, GA = Growth Advantage. APotential insertions is the number of 'TA' nucleotide motifs within the gene. BInsertion density is the fraction of all 'TA' insertions sites with a Tn insertion. CMean read count is the mean number of Tn insertions at 'TA' sites with a Tn insertion. DGenes were designated to a phenotypic class based on the state most frequently observed in the TA sites within the boundaries of an annotated gene, except in the case of essential genes which could also have been assigned to the ES state if they contained a stretch of ES TA sites that was statistically significant based on the extreme value distribution. Please refer to the Materials and Methods section for more detail. EThree genes with the phenotypic classification of Growth-advantage were included to provide context to the insertional densities and mean read count of the Growth-advantage state compared to the essential state classification.

Discussion

High throughput forward genetic screening is rapidly being adopted in a diverse range of organisms. INSeq, and similar high-throughput techniques, have been used in several bacterial species, including Salmonella [5], Mycobacterium [17], Haemophilus [6], Vibrio [40], Pseudomonas [15], Chronobacteria [24] and Bacillus [7]. The technique is very attractive as it allows for the high-throughput functional screening of an organism's genome under varied growth conditions. Here we present the design and validation of a transposon mutagenesis system that will allow for the application of high-throughput INSeq genetic screening for use within the Rhizobiaceae.

Transposon mutagenesis with pSAM_Rl in RLV3841

We have successfully demonstrated the implementation of a mariner class transposon to mutagenize selected species within the family Rhizobiaceae. We found that the MmeI-adapted mariner transposon harbored on pSAM_Rl could mutagenize R. leguminosarum, A. tumefaciens, and S. meliloti at a high frequency. In the case of RLV3841, it was observed that this high frequency of mutagenesis was dense enough to generate saturating libraries of transposon insertion mutants. We were able to generate transposon mutant libraries that saturated the RLV3841 genome with an insertion density of 0.88, which is higher then the insertion density of the data set used for validation of the HMM used for analysis [10]. This suggests that the combination of mariner based transposon insertion sequencing with the Bayesian based HMM analysis would yield accurate and full genome level results. Furthermore, our analysis used approximately 2.3 M reads. And increased read depth could help increase confidence in the analysis, particularly in resolving the phenotypic classifications of essential and growth defective. We also observed no bias of mariner transposon insertion across the RLV3841 chromosome and plasmids, suggesting that the transposon inserts randomly and therefore should allow for reliable whole-genome screening approaches. Analysis of read depth showed that there was also little bias in mean read-count per insertion, except in the case of pRL7, which was slightly higher than the other replicons. We suggest that this is a result of pRL7 being maintained at a higher copy number than the other megaplasmids and chromosome, and so sampling of the mutant pool DNA would results in a higher sampling of pRL7 transposon insertion tags than the other plasmids, or chromosome. When the increase in mean read counts is taken into consideration with the insertion density, it appears that although the higher copy number of pRL7 resulted in a higher mean read depth, it did not increase the insertions density, suggesting that the saturation of pRL7 had reached a plateau and an increased presence of pRL7 did not result in a corresponding increase in the number of unique insertions sites.

Analysis of RLV3841 INSeq using a hidden Markov model

Analysis of the TY INSeq data set with the Tn-HMM analysis package assigned accurate phenotypic classification to several genes thought to be essential housekeeping genes necessary for growth under normal conditions. The analysis showed that insertions in genes required for ATP synthesis were absent in the mutant pools. These genes are expected to be essential due to their central role in metabolism and their designation as essential in this assay supports the validity of using the MmeI-adapted mariner in conjunction with the HMM analysis as our INSeq methodology. Furthermore, visual investigation of the transposon insertion density around the region encoding the ATP synthase genes revealed a high insertion density leading up to and after the genes, further supporting the conclusion that the technique is robust and can discern regions of essentiality from those of other states at a high resolution. In a few instances, a gene expected to be essential was observed to be neutral. RL4697 is annotated as a putative DNA polymerase III alpha sub-unit, and is therefore predicted to be required for proper DNA polymerase function; however, the gene was classified in the neutral category with 96.1% of all potential insertion sites in the locus observed to have insertions. We suggest that RL4697 may be misanotated, as RL1723, another DNA polymerase III alpha subunit, was observed to be essential (Table 3). This highlights another potential use of INSeq in the Rhizobiaceae for validation and quality improvement of genome annotations. Five of the megaplasmids in the RLV3841 genome were observed to have a set of 3 plasmid replication genes that the INSeq approach identified as essential for plasmid replication and maintenance. The exception was pRL7 which has two sets of replication genes [41] and therefore functional redundancy may have complicated the the classification of the pRL7 rep genes into the phenotypic classes. The classification of the rep genes on each plasmid as essential provides validation of the INSeq method. Tn insertion within a replication locus would result in the loss of the plasmid from the mutant cell populations harvested for DNA extraction and INSeq DNA sequencing. This result highlights the value of the INSeq approach in the genetic characterization of novel plasmids, as the method is able to identify plasmid encoded genes that are required for plasmid replication and maintenance. Furthermore the method can identify plasmid-encoded genes that provide a fitness advantage to the host under specific growth conditions based on an observed low Tn insertion density. The genes from previously described mutants with growth defects on TY medium were also examined. Previous work identified [38] several genes that are important for growth on TY medium. When we compared those results with the results produced by the INSeq analysis of RLV3841 grown on TY medium we observed good concordance with these previously published results. In our results, the four TY related genes were all observed to result in a growth-defective phenotype after ~16 generations of growth, which is in agreement that the interruption of these genes via mutagenesis will result in impaired growth on TY.

Conclusions

The construction and validation of the mariner pSAM_Rl transposon delivery vector as a transposon insertion sequencing tool for use in the Rhizobiziaceae will provide an opportunity for researchers in the Rhizobiaceae community to use a new high throughput genetic screening approach. There are many research opportunities within the Rhizobiaceae that could be examined using the INSeq methodology. For example, use of a INSeq approach in rhizobia to study genes required for rhizosphere colonization and plant infection will help to understand the competition problem observed in inoculant strains, by not only identifying new essential rhizosphere colonization genes, but also identifying mutations that provide a phenotypic growth advantage . Furthermore, the use of INSeq could be used to fully elucidate catabolic pathways, if saturating mutant pools were grown on minimal medium given a single carbon source, and contrasted with the results of similar experiments on rich media. In the near term, we will use the INSeq approach to increase our understanding of the gene networks involved in swarming physiology in RLV3841.

Materials and Methods

Bacterial strains, growth conditions and plasmids

The bacterial strains and plasmids used in this study are presented in Table 4. R. leguminosarum, S. meliloti, and A. tumefaciens were cultured at 30°C using tryptone-yeast extract medium (TY) [42]. E. coli strains were cultured on lysogeny broth (LB) at 37°C [43]. When required, antibiotics were used at the following concentrations for Rhizobiaceae 500 μg/mL streptomycin (Str), 50 μg/mL rifampicin(Rif), 50 μg/mL neomycin (Neo); concentrations used for Escherichia coli were 100 μg/mL ampicillin (Amp), 25 μg/mL erythromycin, and 50 μg/mL kanamycin. The plasmid pSAM_Bt was obtained as a gift from Dr. Andrew L. Goodman. Plasmid pSC189 was obtained from addgene.org (plasmid#: 32114) as kindly directed by Dr. Eric J. Rubin.
Table 4

Summary of bacterial strains and plasmids

Strains Characteristics Reference
R. leguminosarum bv. viciae 3841 StrR wildtype[44]
S. meliloti RM1021 SU47 str-21 StrR [45]
A. tumefaciensUBAPF2 Plasmid-free derivative of A. tumefaciens strain C5 RifR [46]
E. coli SM10 λpir thi-1 thr leu tonA lacY supE recA::RP4-2-Tc::Mu KanR λpir [47]
E. coli PIR1 F- ∆lac169 rpoS(Am) robA1 creC510 hsdR514 endA- recA1 uidA(∆MluI)::pir-116Invitrogen
Plasmids
pSAM_BtAmpR EryR; RP4-oriT, oriR6K, mariner himar1C9 transposase with Bacteroides thetaiotamicron rpoD promoter, MmeI-adapted marinerIR elements[4]
pSC189AmpR KanR; RP4-oriT, oriR6K[48]
pGEM-T EasyAmpR ; cloning vectorInvitrogen
pGEM::189KmRAmpR KanR; pGEM-T vector containing PCR amplified nptII gene from pSC189This Study
pGEM::rpoDAmpR; pGEM-T vector containing PCR amplified R. leguminosarum 3841 rpoD promoter regionThis Study
pSAM_KmAmpR KanR; EryR in pSAM_Bt replaced with nptII from pSC189This Study
pSAM_RlAmpR KanR; pSAM_Km with B. thetatiotamicron rpoD promoter replaced with R. leguminosarum 3841 rpoD promoter regionThis Study
Summary of bacterial strains and plasmids

Construction of pSAM_Rl

Plasmid DNA was isolated using GenElute™ Plasmid Miniprep Kit (Sigma-Aldrich). The Neo/KanR cassette within pSC189 [48] was PCR amplified using primers Tn189KmR_Fwd_XhoI and Tn189_Rev_XbaI (Additional file 1: Table S1) such that the XhoI and XbaI restriction enzyme sites were introduced on the 5’ and 3’ end, respectively. The 991 bp Neo/KanR PCR product was subsequently cloned into the pGEM®-T Easy Vector System creating plasmid pGEM::189KmR. The Neo/KanR cassette in pGEM::189KmR was digested with XhoI and XbaI restriction enzymes creating a 979 bp fragment that was directionally cloned into the pSAM_Bt mariner transposon. The resulting plasmid pSAM_Km was maintained in the E. coli strain PIR1(Invitrogen), which allows for high copy number maintenance of R6Kƴ-oriR plasmids. Cloning of the RLV3841 rpoD promoter region was carried out by PCR amplifying a 366 bp region upstream of the rpoD gene start codon using primers Rlv_rpoD_Pro_Fwd and Rlv_rpoD_Pro_Rev (Additional file 1: Table S1). The rpoD promoter PCR product had a 5’ BamHI and 3’ NdeI restriction enzyme site introduced, and was subsequently cloned into the pGEM®-T Easy Vector System to create the plasmid pGEM::rpoD. The RLV3841 rpoD promoter region was then excised from pGEM::rpoD using NdeI and BamHI, and directionally cloned into pSAM_Km to create the vector pSAM_Rl (Figure 1). The new pSAM_Rl suicide vector carried an MmeI-adapted mariner transposon harbouring a NeoR/KanR cassette, and had the himar1C9 transposase transcriptionally fused to a RLV3841 rpoD promoter. For use in transposon mutagenesis, the pSAM_Rl construct was electroporated into E. coli SM10λpir (obtained from Dr. Peter Howard, University of Saskatchewan).

Testing pSAM_Rl transposition frequency

Transposition mutagenesis using pSAM_Rl was done in triplicate. Donor and recipient cells were grown in broth culture to an OD600 of approximately 0.8 and were pooled in a ratio of 1000 μL recipient to 500 μL of donor in a 1.5 mL microcentrifuge tube. The conjugation mixture was pelleted at 12,500 rpm for 3 min, washed once with 1000 μL 1X PBS, and resuspended in approximately 100 μL 1X PBS. The cell suspensions were then spotted onto pre-warmed TY agar plates and incubated at 30°C overnight. Conjugation spots were scraped and resuspended in 1000 μL of 1X PBS. Enumeration of transposon mutants was done using TY agar supplemented with 50 μg/mL Neo and the appropriate Rhizobiaceae counter selectable antibiotic (Table 4). Enumeration of total Rhizobiaceae was done on TY agar with the species specific selectable antibiotic.

Generating transposon mutant libraries for sequencing

Six independent conjugations of pSAM_Rl into RLV3841 were conducted on TY agar as described above. After 24 hours incubation at 30°C each of 6 mating spot was scraped and resuspended in 1 mL of 1X PBS and then pooled together in a final volume of 6 mL. For selection on TY agar, 1000 μL of resuspended cells were plated across 2 separate 245 × 245 mm2 (Corning) Neo + Str TY agar plates, in triplicate and incubated for ~48 hour at 30°C. Following incubation, a faint film like growth was scraped off each plate and resuspended in 1 mL of 1×PBS, vortexed for 1 minutes, and then pelleted at 15, 000 RPM for 10 minutes. The supernatant of each resuspension was very viscous and still contained cells, it was equally aliquoted into 2 × 1.5 mL microcentrifuge tubes. The original pellet, and two tubes of supernatant, were then brought up to a final volume of 1000 μL with 1 M NaCl, vortexed thoroughly, and incubated on ice for 1 h to disrupt the viscous exopolysaccharide diffuse capsule to better collect the cells. The NaCl cell suspensions were then pelleted at 15, 000 RPM for 10 minutes, and the pellets from each replicate were pooled independently and resuspended in 1000 μL of TE buffer (pH 8.0). The resulting 3 mutant pools were used for independent DNA isolation and downstream library preparation.

Preparing sequencing libraries and DNA sequencing

Transposon insertion tags (Tn-tags) consisted of 53 bp of pSAM_Rl transposon sequence, including the 27 bp inverse repeat sequence, and 15–16 bp of adjacent genomic DNA. Library preparation was carried out independently for each of the 3 collected Tn-mutant pools. Tn-tags were prepared for DNA sequencing using a modified version of the INSeq method [49] to make the sequencing process amendable to the Ion Torrent PGM sequencing platform. Linear PCR products were amplified using the primer Ion Torrent BioSAM (Additional file 1: Table S1), with an annealing temperature of 58.6°C and 500 ng of template DNA. Linear PCR products were purified using a QIAquick PCR Purification Kit (Qiagen) according to the manufacturer's recommended protocol. The biotinylated linear PCR products were then bound to Pierce Streptavidin Magnetic Beads (Thermo Scientific) and enzymatic steps during library preparation were performed as described [49] with the substitution of Klenow (New England Biolabs), Random Primer 6 (New England Biolabs) and T4 DNA Ligase (New England Biolabs). Additionally, a custom library adapter, INSEQ_Adpt, was used in the adapter ligation step. The final PCR amplification of sequencing template was accomplished using fusion primers designed in accordance with Ion Amplicon Library Preparation (Fusion Method, Pub#: 4468326 Rev. C), using the PCR amplification conditions described in the INSeq methodology [49]. The forward fusion primers IT_A_FP_1, IT_A_FP_2, and IT_A_FP_3 included IonXpress barcode sequences 1, 2, and 3 respectively, for downstream sequence separation. The reverse primer IT_trP1_FP was used in conjunction with a forward primer to introduce the trP1 sequencing adapter. The final sequencing template prepared from the Ion Amplicon library preparation was 187 bp in length. Sequencing template was gel purified using the Invitrogen E-Gel® SizeSelect™ system, and was analyzed using a Bioanalyzer High Sensitivity DNA Chip (Agilent Technologies) prior to sequencing for quality and molarity. The three technical replicates had a final concentration of 1.37, 1.82, and 1.23 μg/ul of sequencing library after size selection, respectively. DNA sequencing was performed on the Ion Torrent PGM using 200 bp sequencing chemistry and a 316v2 sequencing chip. The total raw sequencing output of the Ion Torrent was 1.25, 1.73, and 1.74 million reads for each of the 3 replicates. The raw sequencing reads were then pooled for downstream data extraction an analysis.

Data extraction and transposon insertion analysis

Quality trimming to Q20 and trimming of adapter sequences was performed using cutadapt [50] and the final 16–15 bp tn-tags were checked for a leading 'TA' motif using a custom python script. The resulting 3,192,486 transposon insertion tags were mapped to the R. leguminosarum bv. viciae 3841 reference genome (RefSeq:NC_008378.1 to NC_008384.1) [51] using the Bowtie short read aligner [52], allowing for no mismatches in the alignment, and only reporting insertion tags that mapped to a single unique location. Short read alignment resulted in 2,319,239 unique transposon insertion tags mapping to the RLV3841 reference genome, after 131,676 reads were ommitted due to multiple alignments, and 509,341 reads failed to align. The .sam output file from the Bowtie alignment was converted into a .bam format using Samtools [53], and was then converted to .bed format using bedtools. Transposon insertion reads were grouped by specific RLV3841 replicons for downstream analysis. The .bed files of the aligned transposon insertion tags were converted to .wig format using a custom python module developed in house. The .wig formatted INSeq data sets generated for each of the 7 replicons in the RLV3841 genome were then analyzed independently using the Tn-HMM python module [10]. Briefly, the python module used a HMM as described in [10], in conjunction with the Viterbi algorithm to calculate the state of each 'TA' insertion site within the genome, independent of gene boundaries. Next, the computer module analyzed the state of successive 'TA' sites within gene boundaries to assign a state for the gene as a whole (See Additional file 2 for the RLV3841 chromosomal output). Four phenotypic classifications are possible: essential, growth defective, neutral, and growth advantage. Figure 2 provides a visual example of the four phenotypic classifications found within a selected region of the RLV3841 genome.
Figure 2

Transposon insertion density across a selected region of the RLV3841 genome. growth-defective, neutral, and growth-advantage regions of the RLV3841 genome. Analyzing the total number of insertions mapped to each potential mariner insertion site using the Tn-HMM python module [10] allows each gene to be placed in one of four phenotypic classes: ES = essential, GD = growth defect, NE = neutral, GA = growth advantage. In this experiment the phenotype refers to the ability to grow on TY agar. Data visualization was obtained using Integrative Genomics Viewer software [54]. Please refer to the Materials and Methods section for more detail on the process of assigning phenotypic classifications.

Transposon insertion density across a selected region of the RLV3841 genome. growth-defective, neutral, and growth-advantage regions of the RLV3841 genome. Analyzing the total number of insertions mapped to each potential mariner insertion site using the Tn-HMM python module [10] allows each gene to be placed in one of four phenotypic classes: ES = essential, GD = growth defect, NE = neutral, GA = growth advantage. In this experiment the phenotype refers to the ability to grow on TY agar. Data visualization was obtained using Integrative Genomics Viewer software [54]. Please refer to the Materials and Methods section for more detail on the process of assigning phenotypic classifications.
  46 in total

1.  Identification of genes required by Bacillus thuringiensis for survival in soil by transposon-directed insertion site sequencing.

Authors:  Alistair H Bishop; Phillip A Rachwal; Alka Vaid
Journal:  Curr Microbiol       Date:  2013-12-06       Impact factor: 2.188

2.  Inability to catabolize galactose leads to increased ability to compete for nodule occupancy in Sinorhizobium meliloti.

Authors:  Barney A Geddes; Ivan J Oresnik
Journal:  J Bacteriol       Date:  2012-07-13       Impact factor: 3.490

3.  beta-Glucuronidase (GUS) transposons for ecological and genetic studies of rhizobia and other gram-negative bacteria.

Authors:  K J Wilson; A Sessitsch; J C Corbo; K E Giller; A D Akkermans; R A Jefferson
Journal:  Microbiology       Date:  1995-07       Impact factor: 2.777

4.  Identification of a novel ABC transporter required for desiccation tolerance, and biofilm formation in Rhizobium leguminosarum bv. viciae 3841.

Authors:  Elizabeth M Vanderlinde; Joe J Harrison; Artur Muszyński; Russell W Carlson; Raymond J Turner; Christopher K Yost
Journal:  FEMS Microbiol Ecol       Date:  2009-12-02       Impact factor: 4.194

Review 5.  Transposon insertion sequencing: a new tool for systems-level analysis of microorganisms.

Authors:  Tim van Opijnen; Andrew Camilli
Journal:  Nat Rev Microbiol       Date:  2013-05-28       Impact factor: 60.633

Review 6.  The genome of Rhizobium leguminosarum has recognizable core and accessory components.

Authors:  J Peter W Young; Lisa C Crossman; Andrew W B Johnston; Nicholas R Thomson; Zara F Ghazoui; Katherine H Hull; Margaret Wexler; Andrew R J Curson; Jonathan D Todd; Philip S Poole; Tim H Mauchline; Alison K East; Michael A Quail; Carol Churcher; Claire Arrowsmith; Inna Cherevach; Tracey Chillingworth; Kay Clarke; Ann Cronin; Paul Davis; Audrey Fraser; Zahra Hance; Heidi Hauser; Kay Jagels; Sharon Moule; Karen Mungall; Halina Norbertczak; Ester Rabbinowitsch; Mandy Sanders; Mark Simmonds; Sally Whitehead; Julian Parkhill
Journal:  Genome Biol       Date:  2006-04-26       Impact factor: 13.583

Review 7.  Agrobacterium infection and plant defense-transformation success hangs by a thread.

Authors:  Andrea Pitzschke
Journal:  Front Plant Sci       Date:  2013-12-18       Impact factor: 5.753

8.  Combining functional and structural genomics to sample the essential Burkholderia structome.

Authors:  Loren Baugh; Larry A Gallagher; Rapatbhorn Patrapuvich; Matthew C Clifton; Anna S Gardberg; Thomas E Edwards; Brianna Armour; Darren W Begley; Shellie H Dieterich; David M Dranow; Jan Abendroth; James W Fairman; David Fox; Bart L Staker; Isabelle Phan; Angela Gillespie; Ryan Choi; Steve Nakazawa-Hewitt; Mary Trang Nguyen; Alberto Napuli; Lynn Barrett; Garry W Buchko; Robin Stacy; Peter J Myler; Lance J Stewart; Colin Manoil; Wesley C Van Voorhis
Journal:  PLoS One       Date:  2013-01-31       Impact factor: 3.240

9.  Identification of essential genes of the periodontal pathogen Porphyromonas gingivalis.

Authors:  Brian A Klein; Elizabeth L Tenorio; David W Lazinski; Andrew Camilli; Margaret J Duncan; Linden T Hu
Journal:  BMC Genomics       Date:  2012-10-31       Impact factor: 3.969

10.  A Hidden Markov Model for identifying essential and growth-defect regions in bacterial genomes from transposon insertion sequencing data.

Authors:  Michael A DeJesus; Thomas R Ioerger
Journal:  BMC Bioinformatics       Date:  2013-10-08       Impact factor: 3.169

View more
  12 in total

1.  Role of O2 in the Growth of Rhizobium leguminosarum bv. viciae 3841 on Glucose and Succinate.

Authors:  Rachel M Wheatley; Vinoy K Ramachandran; Barney A Geddes; Benjamin J Perry; Chris K Yost; Philip S Poole
Journal:  J Bacteriol       Date:  2016-12-13       Impact factor: 3.490

2.  Lifestyle adaptations of Rhizobium from rhizosphere to symbiosis.

Authors:  Rachel M Wheatley; Brandon L Ford; Li Li; Samuel T N Aroney; Hayley E Knights; Raphael Ledermann; Alison K East; Vinoy K Ramachandran; Philip S Poole
Journal:  Proc Natl Acad Sci U S A       Date:  2020-09-08       Impact factor: 11.205

3.  Elucidating Essential Genes in Plant-Associated Pseudomonas protegens Pf-5 Using Transposon Insertion Sequencing.

Authors:  Belinda K Fabian; Christie Foster; Amy J Asher; Liam D H Elbourne; Amy K Cain; Karl A Hassan; Sasha G Tetu; Ian T Paulsen
Journal:  J Bacteriol       Date:  2021-03-08       Impact factor: 3.490

4.  Genome-Scale Mutational Analysis of Cathode-Oxidizing Thioclava electrotropha ElOx9T.

Authors:  Joshua D Sackett; Nitin Kamble; Edmund Leach; Taruna Schuelke; Elizabeth Wilbanks; Annette R Rowe
Journal:  Front Microbiol       Date:  2022-06-10       Impact factor: 6.064

Review 5.  Rhizobia: from saprophytes to endosymbionts.

Authors:  Philip Poole; Vinoy Ramachandran; Jason Terpolilli
Journal:  Nat Rev Microbiol       Date:  2018-01-30       Impact factor: 60.633

6.  TnFLXopen: Markerless Transposons for Functional Fluorescent Fusion Proteins and Protein Interaction Prediction.

Authors:  Felix Dempwolff; Daniel B Kearns
Journal:  Microbiol Spectr       Date:  2022-05-02

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

Authors:  Benjamin J Perry; Mir S Akter; Christopher K Yost
Journal:  Front Microbiol       Date:  2016-11-22       Impact factor: 5.640

8.  Essential Genes for In Vitro Growth of the Endophyte Herbaspirillum seropedicae SmR1 as Revealed by Transposon Insertion Site Sequencing.

Authors:  Federico Rosconi; Stefan P W de Vries; Abiyad Baig; Elena Fabiano; Andrew J Grant
Journal:  Appl Environ Microbiol       Date:  2016-10-27       Impact factor: 4.792

Review 9.  Genetic Regulation of Virulence and Antibiotic Resistance in Acinetobacter baumannii.

Authors:  Carsten Kröger; Stefani C Kary; Kristina Schauer; Andrew D S Cameron
Journal:  Genes (Basel)       Date:  2016-12-28       Impact factor: 4.096

10.  Genome-Wide Sensitivity Analysis of the Microsymbiont Sinorhizobium meliloti to Symbiotically Important, Defensin-Like Host Peptides.

Authors:  Markus F F Arnold; Mohammed Shabab; Jon Penterman; Kevin L Boehme; Joel S Griffitts; Graham C Walker
Journal:  mBio       Date:  2017-08-01       Impact factor: 7.867

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.