ORIGINAL RESEARCH article

Front. Plant Sci., 20 March 2017

Sec. Plant Pathogen Interactions

Volume 8 - 2017 | https://doi.org/10.3389/fpls.2017.00370

Transcriptomes of Ralstonia solanacearum during Root Colonization of Solanum commersonii

  • 1. Department of Genetics, University of Barcelona Barcelona, Spain

  • 2. Centre for Research in Agricultural Genomics CSIC-IRTA, Autonomous University of Barcelona Bellaterra, Spain

  • 3. Department of Biochemistry, University of São Paulo São Paulo, Brazil

  • 4. Shanghai Center for Plant Stress Biology, CAS Center for Excellence in Molecular Plant Sciences, Shanghai Institutes of Biological Sciences, Chinese Academy of Sciences (CAS) Shanghai, China

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Abstract

Bacterial wilt of potatoes—also called brown rot—is a devastating disease caused by the vascular pathogen Ralstonia solanacearum that leads to significant yield loss. As in other plant-pathogen interactions, the first contacts established between the bacterium and the plant largely condition the disease outcome. Here, we studied the transcriptome of R. solanacearum UY031 early after infection in two accessions of the wild potato Solanum commersonii showing contrasting resistance to bacterial wilt. Total RNAs obtained from asymptomatic infected roots were deep sequenced and for 4,609 out of the 4,778 annotated genes in strain UY031 were recovered. Only 2 genes were differentially-expressed between the resistant and the susceptible plant accessions, suggesting that the bacterial component plays a minor role in the establishment of disease. On the contrary, 422 genes were differentially expressed (DE) in planta compared to growth on a synthetic rich medium. Only 73 of these genes had been previously identified as DE in a transcriptome of R. solanacearum extracted from infected tomato xylem vessels. Virulence determinants such as the Type Three Secretion System (T3SS) and its effector proteins, motility structures, and reactive oxygen species (ROS) detoxifying enzymes were induced during infection of S. commersonii. On the contrary, metabolic activities were mostly repressed during early root colonization, with the notable exception of nitrogen metabolism, sulfate reduction and phosphate uptake. Several of the R. solanacearum genes identified as significantly up-regulated during infection had not been previously described as virulence factors. This is the first report describing the R. solanacearum transcriptome directly obtained from infected tissue and also the first to analyze bacterial gene expression in the roots, where plant infection takes place. We also demonstrate that the bacterial transcriptome in planta can be studied when pathogen numbers are low by sequencing transcripts from infected tissue avoiding prokaryotic RNA enrichment.

Introduction

Changes in pathogen gene expression control the switch from a commensal to a parasitic relationship with the host, which may subvert the host metabolism or development to the pathogen's benefit (Stes et al., 2011). However, there is still limited information concerning how this is controlled. Understanding how these trophic relationships initiate and persist in the host requires deciphering the functional adaptations at the transcriptomic level. Pioneer studies of the expression profiles of bacterial animal pathogens in infected tissues showed that the genes induced more strongly contributed to bacterial virulence and/or survival in the host (reviewed in La et al., 2008).

Ralstonia solanacearum is the causal agent of the destructive bacterial wilt disease in tropical and subtropical crops, including tomato, tobacco, banana, peanut, and eggplant (Hayward, 1991; Peeters et al., 2013). The disease in potato is also called brown rot and is endemic in the Andean region, where potato is a staple food, causing an important impact on food production and the economy (Priou, 2004; Coll and Valls, 2013). Disease control of bacterial wilt is very challenging, because of the bacterium aggressiveness, its persistence in the field and the lack of resistant commercial varieties in any of its hosts. Potato breeding programs have used wild species related to Solanum tuberosum, such as Solanum commersonii, as sources of resistance against bacterial wilt (Kim-Lee et al., 2005; Siri et al., 2009).

As in most Gram-negative animal and plant pathogens, the major pathogenicity determinant in R. solanacearum is the type three secretion system (T3SS) (Boucher et al., 1987). This system injects bacterial proteins called effectors directly into the eukaryotic host cells to manipulate the host defenses and establish disease (Buttner, 2016; Popa et al., 2016a). Amongst other factors that contribute to R. solanacearum virulence are motility—either caused by flagella or type IV pili- and the reactive oxygen species (ROS)- detoxifying enzymes (Meng, 2013).

In vitro studies using microarrays allowed the study of R. solanacearum virulence gene expression and the discovery of novel regulatory networks (Occhialini et al., 2005; Valls et al., 2006). However, the first studies on gene expression in planta using quantitative reporters indicated that R. solanacearum virulence genes showed unexpected expression patterns (Monteiro et al., 2012). Contrary to what was believed based on in vitro studies, it was demonstrated that the genes encoding the T3SS genes and its associated effectors were transcribed in planta at late stages of infection (Monteiro et al., 2012). These findings were later confirmed in transcriptomic studies with R. solanacearum extracted from infected tomato and banana plants (Jacobs et al., 2012; Ailloud et al., 2016). However, these studies in planta could only be performed from heavily colonized plants, as limited pathogen biomass has hindered until recently the investigation of gene expression at the early stages of the interaction, when plants are still asymptomatic.

In a previous work, we demonstrated that rRNA-depleted RNAs obtained from infected roots could be used to determine the transcriptomic responses of S. commersonnii plants resistant or susceptible to bacterial wilt through RNA sequencing (Zuluaga et al., 2015). Here, we have used these sequences to extract R. solanacearum UY031 transcripts in silico and have compared them to the bacterial transcriptomes obtained in synthetic media to investigate the pathogen RNAs expressed during early infection. Our results reveal differential expression of a number of known and putative transcriptional regulators and virulence factors during early plant colonization, providing insight into their role in infection.

Materials and methods

Bacterial strains, plant accessions, and growth conditions

The R. solanacearum isolate UY031, phylotype IIB, sequevar 1, originally isolated from potato (Siri et al., 2011), carrying the LUX-operon under the psbA promoter (Monteiro et al., 2012) was used for all experiments. Bacteria were routinely grown in rich B medium as described (Monteiro et al., 2012).

S. commersonnii accessions F97 (susceptible to bacterial wilt) and F118 (moderately resistant) obtained from a segregating population were used in this work and propagated in vitro as described (Zuluaga et al., 2015).

Sample preparation

As a control condition, bacteria were grown for 2 days on rich solid medium without tetrazolium chloride or antibiotics at the appropriate dilution to obtain separate colonies. Bacteria were recovered from plates and mixed with 5% of an ice-cold transcription stop solution [5% (vol/vol) water-saturated phenol in ethanol]. Cells were centrifuged at 4°C for 2 min at maximum speed and the bacterial pellet was immediately frozen in liquid nitrogen.

For plant RNA samples, S. commersonii F97 and F118 roots were inoculated as described in Zuluaga et al. (2015). Briefly, plant roots from 2-week old plants grown in soil were injured with a 1 ml pipette tip and inoculated by soil drenching with a bacterial solution at 107 colony forming units (cfu)/ml. Control plants were mock-inoculated with water. After inoculation, plants were kept in a growth chamber at 28°C in long-day conditions. Luminescence quantification was used to select plants with comparable infection levels in the susceptible and the resistant accessions, corresponding to approximately 105 colony forming units per g of tissue (Cruz et al., 2014).

RNA extraction, sequencing, and library preparation

Total RNA from bacterial cultures was extracted using the SV Total RNA Isolation System kit (Promega) following the manufacturer's instructions for Gram-negative Bacteria. Infected plant RNA extractions were carried out as described (Cruz et al., 2014). RNA concentration and quality was measured using the Agilent 2100 Bioanalyzer. For rRNA depletion, 2.5 μg of RNA were treated with the Ribo-zero(™) magnetic kit for bacteria (Epicenter). Three biological replicates per condition were subjected to sequencing on an Illumina-Solexa Genome Analyzer II apparatus in the Shanghai PSC Genomics facility using multiplexing and kits specially adapted to obtain 100 bp paired-end reads in stranded libraries. Raw sequencing data is available in the Sequence Read Archive under the accession code SRP096020.

Read mapping, quantification, and differential gene expression analysis

FASTQC was used to evaluate the quality of the RNA-seq raw data. R. solanacearum reads were identified from total infected root sequences using Bowtie2 (version 2.2.6; Langmead and Salzberg, 2012) as described in the results section. The completely sequenced genome of strain UY031 (Guarischi-Sousa et al., 2016) was used as reference. For identification of R. solanacearum reads, the Burrows-Wheeler Alignment (BWA) tool was initially used. However, a high number of reads from mock-inoculated control samples mapped to the bacterial genome (Table 1). Visual evaluation of these mapped reads using the Integrative Genomics Viewer (IGV) tool (Robinson et al., 2011; Thorvaldsdottir et al., 2013) showed that most contained mismatches to the R. solanacearum genome sequence, indicating that they likely belonged to contaminating bacteria. BWA was thus assayed with more stringent parameters (-B 20-O 30-E 5-U 85), to increase penalties for mismatches, gap openings, gap extension, and unpaired read pairs, resulting in a reduction of only half of the reads mapping to the genome. Finally, Bowtie2 was assayed, once more using stringent parameters to penalize mismatches and gaps (–mp 30–rdg 25,15–rfg 25,15). In this case, mapped reads levels in mock-inoculated plants could be considered background compared to the high read numbers from inoculated samples, thus, Bowtie2 was finally used in all samples analyzed, including RNA-seq reads coming from in vitro grown bacteria (Table 1). Alignments were summarized by genes on counting tables using HTSeq-count (version 0.6.1 p1; Anders et al., 2015) and NCBI's reference annotation (genome features were extracted from NCBI's RefSeq sequences NZ_CP012687.1 and NZ_CP012688.1); alignments with quality lower than 10 were discarded. Differential expression (DE) analysis was carried out with the DESeq2 (version 1.12.3; Love et al., 2014) package in R (version 3.3.2). Benjamini–Hochberg procedure was used for multiple testing corrections. Genes with log2(fold-change) > 0.5 and q < 0.01 were considered as differentially expressed. We used these thresholds to select for relevant and robust differentially expressed genes. Final annotation of the genome was defined based on the NCBI gene locus and the gene name and description of the reference R. solanacearumGMI1000 genome annotation (Supplementary Table 1).

Table 1

BWAaBWA_stringentbBowtie2_stringent
ConditioncReplicaTotal readsReads%Reads%Reads%
Resistant mock-inoculated1838675081108590.1660830.16010.0
288913944420400.0252960.07710.0
Resistant infected1718550423483690.53309680.52900360.4
2964705019439741.09242971.08791120.9
3234734542492851.12341531.01837280.8
Susceptible mock-inoculated1100234418701730.1407970.03000.0
227594608150600.188890.01370.0
Susceptible infected1753686202493820.32325500.32115610.3
29302396321033562.320102842.218675852.0
3246951835188722.14848732.04105251.7

Number and percentage of aligned reads to the R. solanacearum UY031 genome from mock-inoculated (Control) and inoculated Solanum commersonii accessions.

a

Burrows-Wheeler Alignment.

b

Burrows-Wheeler Alignment using stringent parameters as described in methods.

c

Samples from Zuluaga, Solé, Lu, BMC Genomics, 2015.

Homology analysis

get_homologs (version 2.0; Contreras-Moreira and Vinuesa, 2013) was used for searching R. solanacearum UY031 homologous genes on R. solanacearum GMI1000, R. solanacearum IPO1609 and R. solanacearum UW551 strains as well as in Pseudomonas syringae pv. syringae B728a; NCBI RefSeq sequences GCF_001299555.1, GCF_000009125.1, GCF_001050995.1, GCF_000167955.1, and GCF_000012245.1, respectively. Default algorithm of bidirectional best-hits was used on homologous genes search.

Functional categories

R. solanacearum UY031's genes were functionally categorized using two different strategies. Firstly, functional categories from Pseudomonas syringae pv. syringae B728a as defined by Yu et al. (2013), were translated to R. solanacearum UY031 based on homology information between the two strains. Although the P. syringae-derived categories should be more specific and accurate for another bacterial plant pathogen, almost 70% of the R. solanacearum UY031 genes could not be classified using this method. Therefore, a second strategy based on Clusters of Orthologous Groups (COG) categories was applied. Genome features were extracted from NCBI's RefSeq annotation and cdd2cog.pl script (version 0.1; Leimbach, 2016) was used to assign COG IDs and functional categories to the differentially expressed genes (Supplementary Table 1).

Results

Obtaining R. solanacearum sequences from infected root tissues

cDNA libraries from rRNA-depleted RNAs isolated from S. commersonii roots inoculated with R. solanacearum were sequenced using Illumina technology as previously reported (Zuluaga et al., 2015). To generate the transcriptomic profile of the bacteria growing inside root tissues, R. solanacearum UY031 sequences were obtained following the pipeline detailed in Figure 1. First, reads from mock-inoculated plants were used as a control to determine the best alignment tool to map against the R. solanacearum UY031 reference genome (Guarischi-Sousa et al., 2016; see material and methods). The Bowtie2 alignment tool with stringent parameters was used, as it retained a number of R. solanacearum reads in mock-inoculated plants that could be considered background levels compared to the high read numbers from inoculated samples (Table 1). All samples were analyzed with Bowtie2, including RNA-seq reads coming from in vitro grown bacteria. We determined that around 1% of the total sequenced reads from plant tissues corresponded to R. solanacearum and these were retained for further analyses. S. commersonnii sequences accounted on average for 63.15% of the total reads sequenced and the remaining reads corresponded mostly to contamination by other bacterial endophytes. The retrieved bacterial sequences were quantified and differentially expressed (DE) genes comparing the different conditions were determined. Total RNAs from infected S. commersonii enabled transcript quantification for over 96% of R. solanacearum UY031 predicted genes (4,609 out of the 4,778; Guarischi-Sousa et al., 2016).

Figure 1

Figure 1

Workflow of the transcriptomic analysis. RNAseq was carried out from roots of infected and mock-inoculated Solanum commersonii resistant and susceptible varieties and from bacteria grown in solid rich B medium. Three biological replicates were used for each condition. Total extracted RNAs were treated with Ribo-zero to remove rRNA and sequenced using Illumina technology. Raw reads were aligned against the R. solanacearum UY031 genome using different alignment tools and mapping was visually evaluated with the IGV Browser. Mapped reads were quantified using count tables and differential expression (DE) analysis was carried out.

Similar R. solanacearum genes are differentially expressed upon infection of resistant and susceptible S. commersonii plants

In order to compare the R. solanacearum gene expression patterns during infection of resistant and susceptible wild potato plants, we analyzed separately the bacterial reads obtained from infected S. commersonii accessions F118 and F97, respectively. Surprisingly, only two out of the 4,609 genes for which expression was detected showed differential expression between the two genotypes. The differentially-expressed (DE) genes, RSUY_RS08455, and RSUY_RS16950, were both up-regulated in bacteria grown inside the resistant accession (Table 2). The first gene corresponds to an uncharacterized member of the MarR transcriptional regulator family, while the second encodes a hypothetical protein.

Table 2

UY031 NCBI locusaUY031 Prokka locusbGMI1000 locuscGene productLog2FCAdjusted p-value
RSUY_RS08455RSUY_17320RSc1295MarR family transcriptional regulator2.370.0004
RSUY_RS16950RSUY_34650RSp0403hypothetical protein2.530.0017

R. solanacearum UY031 genes differentially expressed in resistant vs. susceptible S. commersonii.

a

According to R. solanacearum UY031 genome annotation available at GenBank (NCBI).

b

According to R. solanacearum UY031 genome annotation from Guarischi-Sousa et al. (2016).

c

According to the homology Supplementary Table 1.

Since R. solanacearum showed extremely similar (>99.9%) transcriptional behavior during interaction with both S. commersonii accessions, bacterial reads from both accessions were treated as biological replicates in the rest of this study.

R. solanacearum activates stress-related genes and shuts down metabolic activities during early root colonization

The R. solanacearum in planta gene expression dataset was compared to a reference condition consisting of bacteria grown on solid rich B medium. Bacteria grown on solid medium were used as the reference condition instead of liquid cultures. R. solanacearum colonies grown on solid media better mimic the biofilms and microcolonies formed by R. solanacearum during early infection, when most bacteria occupy plant intercellular spaces (Mori et al., 2016). A total of 422 genes were differentially expressed during pre-symptomatic infection (231 up-regulated and 191 down-regulated), compared to growth on rich medium (Supplementary Table 2). These DE genes were classified into the functional categories previously used for gene expression studies in the plant pathogenic bacterium P. syringae (Yu et al., 2013; Supplementary Table 3). The number of successfully classified genes in each category was quantified in differentially induced or repressed groups and in the whole genome as a reference (Figure 2). This analysis revealed four categories highly over-represented in the up-regulated genes and under-represented in down-regulated genes: stress, secretion, chemosensing, and motility and phage and insertion sequences (IS). These categories represent together approximately 20% of the total induced genes in planta. The opposite trend (under-representation in up-regulated and over-representation in down-regulated genes) is observed in the categories including genes for transport and metabolism of amino acids and carbohydrates. In addition, the categories replication and DNA repair, transport, fatty acid metabolism and cofactor metabolism are strongly under-represented amongst the up-regulated genes in planta (Figure 2).

Figure 2

Figure 2

Percentage of DE genes classified into Pseudomonas syringae-derived functional categories (Yu et al., 2013). Genes DE between growth in planta vs. rich medium were classified according to the functional categories described for P. syringae (Yu et al., 2013). Categories were grouped by function similarity for better visualization (Supplementary Table 4). As a reference, functional category distribution considering all annotated genes in the UY031 genome is shown.

We used the P. syringae categories because they were created to describe the genes of a bacterial plant pathogen and are thus very informative for this study. However, the same analysis was carried out using the widely used but more general COG categories, and the results confirmed the previously-described tendencies (Supplementary Figure 1). Genes involved in carbohydrate, amino acid, lipid, cofactor, and secondary metabolism were over-represented among those down-regulated in planta. A clear enrichment of replication, cell motility and recombination and repair (where IS elements are included) was observed in the up-regulated genes. Interestingly, a clear asymmetry was seen for unclassified genes in this case, for they represent 40% of the up-regulated but only 7% of the down-regulated genes.

Closer scrutiny of the up-regulated genes in the plant revealed that the category secretion included 11 genes encoding the T3SS and its associated effectors and four chemosensing and motility genes, coding for pilus assembly and flagellum transcriptional activators (Table 3).

Table 3

FunctionUY031 NCBI locusaUY031 Prokka locusbGMI1000 locuscLog2FCGene nameGene product
RALSTONIA SOLANACEARUMVIRULENCE GENES
Type III secretion system and effectorsRSUY_RS19685RSUY_40420RSp08557.80hrpYType III secretion system protein HrpY
RSUY_RS19795RSUY_40640RSp08774.66popAType III effector protein PopA
RSUY_RS19790RSUY_40630RSp08764.27popBType III effector protein PopB
RSUY_RS20380RSUY_41860RSp10243.96awr5_1Type III effector protein AWR5
RSUY_RS22080RSUY_45370RSp09003.94popF1Type III effector protein PopF1
RSUY_RS16550RSUY_33840RSp03043.76ripDType III effector protein RipD
RSUY_RS19785RSUY_40620RSp08753.35popCType III effector protein PopC
RSUY_RS19735RSUY_40520RSp08653.08hrpKType III secretion system protein HrpK
RSUY_RS19690RSUY_40430RSp08562.86hrpXType III secretion system protein HrpX
RSUY_RS19770RSUY_40590RSp08722.69hrcTHrcT family type III secretion system export apparatus protein
RSUY_RS09370RSUY_191602.44ripV2Type III effector protein RipV2
RSUY_RS19150RSUY_39290RSp0731−2.61ripTPSTrehalose-6-phosphate synthase
RSUY_RS21730RSUY_44630RSp1374−2.88ripS2Type III effector protein SKWP2
RSUY_RS21610RSUY_44390RSp1277−3.50ripQType III effector protein RipQ
MotilityRSUY_RS04635RSUY_09450RSc07273.14pilVType IV pilus modification protein PilV
RSUY_RS22435RSUY_46110RSp14122.65flhCTranscriptional activator FlhC
RSUY_RS02415RSUY_04970RSc29742.62pilNTfp pilus assembly protein PilN
RSUY_RS22440RSUY_46120RSp14132.47flhDFlagellar transcriptional activator FlhD
RSUY_RS04630RSUY_09440RSc07262.30pilWPilus assembly protein PilW
RSUY_RS02410RSUY_04960RSc29752.28pilMPilus assembly protein PilM
RSUY_RS04330RSUY_08850RSc06682.20pilGTwo-component system response regulator
RSUY_RS04335RSUY_08860RSc06691.95pilHTwo-component system response regulator
RSUY_RS11250RSUY_22930RSc19861.24fimVTfp pilus assembly protein FimV
RSUY_RS04590RSUY_09370RSc0718−3.56pilYPilus assembly protein PilY
Stress responsesRSUY_RS22220RSUY_45660RSp15813.16katECatalase katE
RSUY_RS00425RSUY_00900RSc33983.10hmpXflavohemoprotein
RSUY_RS17495RSUY_35830RSp02452.64ahpC1Peroxiredoxin
RSUY_RS17500RSUY_35840RSp02462.21ahpFAlkyl hydroperoxide reductase subunit F
RSUY_RS04770RSUY_09720RSc07541.96Peroxidase
RSUY_RS04870RSUY_09930RSc07751.82katGbCatalase katGb
RSUY_RS01185RSUY_02450RSc3254−3.11alkyl hydroperoxide reductase
Other virulence factorsRSUY_RS18925RSUY_38830RSp06763.71metEMethionine synthase II (cobalamin-independent)
RSUY_RS01465RSUY_03030RSp06933.38hdfADioxygenase
RSUY_RS14015RSUY_28660RSc04082.22rpoN1RNA polymerase sigma-54 factor
RSUY_RS17795RSUY_36440RSp15291.72efe2-oxoglutarate-dependentethylene/succinate-forming enzyme
RSUY_RS04455RSUY_09100RSc0693−2.19kdtA3-deoxy-D-manno-octulosonic-acid transferase
Type II Secretion SystemRSUY_RS01675RSUY_03470RSc3109−2.63gspJGeneral secretion pathway protein GspJ
RSUY_RS16275RSUY_33280RSp0148−3.19gspEGeneral secretion pathway protein GspE
Type VI secretion systemRSUY_RS19215RSUY_39440RSp07462.25Type VI secretion protein
Cofactor metabolism and transportRSUY_RS04050RSUY_08280RSc2633−2.92pabBaminodeoxychorismate synthase component I
Quorum sensingRSUY_RS01010RSUY_02100RSc3286−3.24solIAcyl-homoserine-lactone synthase
RALSTONIA SOLANACEARUMGENES INVOLVED IN PLANT COLONIZATION
Aminoacid metabolismRSUY_RS21930RSUY_45070RSp12632.019462nadB2L-aspartate oxidase
RSUY_RS04790RSUY_09760RSc07581.900185Tryptophan 2,3-dioxygenase 1
RSUY_RS01705RSUY_03530RSc3103−1.932194-hydroxyphenylpyruvate dioxygenase
RSUY_RS00955RSUY_01990RSc3295−1.97096gcvPglycine dehydrogenase
RSUY_RS00965RSUY_02010RSc3293−2.1387gcvTaminomethyltransferase
RSUY_RS08880RSUY_18160RSc1381−2.22786glutathione ABC transporter permease GsiC
RSUY_RS02965RSUY_06080RSc2867−2.45751dppD1peptide ABC transporter substrate-bindingprotein
RSUY_RS19000RSUY_38980RSp0691−2.63642hmgAhomogentisate 1,2-dioxygenase
RSUY_RS08860RSUY_18120RSc1377−2.72373transcriptional regulator
RSUY_RS00950RSUY_01980RSc3296−2.82715sdaA2L-serine ammonia-lyase / L-serine ammonia-lyase
RSUY_RS18995RSUY_38970RSp0690−2.93699hmgBfumarylacetoacetase
RSUY_RS08895RSUY_18190RSc1384−3.10843D-aminopeptidase
RSUY_RS08865RSUY_18130RSc1378−3.44342isoaspartyl peptidase
Carbohydrate metabolismRSUY_RS22935RSUY_47230RSp1633−1.90617xylFD-xylose ABC transporter substrate-bindingprotein
RSUY_RS22945RSUY_47250RSp1635−2.40016xylHxylose ABC transporter permease
RSUY_RS21965RSUY_45140RSp1270−2.4781glycosyl hydrolase
RSUY_RS22940RSUY_47240RSp1634−2.98048xylGD-xylose ABC transporter ATP-binding protein
RSUY_RS17060RSUY_34910RSp0423−3.65067aldolase
RSUY_RS22950RSUY_47260RSp1636−4.75552NAD-dependent dehydratase
Transcriptional and response regulatorsRSUY_RS08455RSUY_17320RSc12954.365537MarR family transcriptional regulator
RSUY_RS22955RSUY_47270RSp1637−1.62836LacI family transcriptional regulator
RSUY_RS06090RSUY_12470RSc2209−1.75486LysR family transcriptional regulator
RSUY_RS00225RSUY_00480RSc0040−2.26596two-component system response regulator
RSUY_RS00910RSUY_01900RSc3301−2.57757putAtrifunctional transcriptional regulator
Siderophore biosynthesisRSUY_RS17055RSUY_34900RSp0422−2.30463siderophore biosynthesis protein
RSUY_RS03590RSUY_07350RSc2729−2.4997membrane protein / membrane protein
RSUY_RS17040RSUY_34870RSp0419−2.75083siderophore biosynthesis protein
RSUY_RS17050RSUY_34890RSp0421−2.94313siderophore biosynthesis protein
Nitrogen metabolismRSUY_RS14025RSUY_28680RSc04062.27ptsNPTS IIA-like nitrogen-regulatory protein PtsN
RSUY_RS17995RSUY_36860RSp09802.24narLDNA-binding response regulator
RSUY_RS11470RSUY_23380RSc2031−3.3167ureEurease accessory protein UreE
TransportersRSUY_RS20760RSUY_42660RSp12832.005142porin
RSUY_RS11090RSUY_22610RSc1951−2.22cation acetate symporter
RSUY_RS22930RSUY_47220RSp1632−2.42488oprBporin
RSUY_RS05795RSUY_11880RSc2274−2.96894ragCCation efflux protein
Organic acid metabolismRSUY_RS19540RSUY_40110RSp08263.4033895-dehydro-4-deoxyglucarate dehydratase
RSUY_RS19480RSUY_39990RSp08142.44631mqomalate:quinone oxidoreductase
RSUY_RS11960RSUY_24410RSc2358−1.7429ppcphosphoenolpyruvate carboxylase
ProteasesRSUY_RS12475RSUY_25460RSc24652.359347clpSATP-dependent Clp protease adaptor ClpS
RSUY_RS18550RSUY_38040RSp06032.211049serine protease
RSUY_RS14120RSUY_28870RSc0388−1.98903zinc protease
Lipid metabolismRSUY_RS17295RSUY_354102.478807Acyl-CoA synthetase
RSUY_RS01975RSUY_04090RSc3052−2.40887glpKglycerol kinase
EnergyRSUY_RS08510RSUY_17430RSc13053.640811fprferredoxin–NADP(+) reductase
RSUY_RS08360RSUY_17120RSc12763.417949cytochrome c oxidase, cbb3-type subunit I
Signal transductionRSUY_RS23055RSUY_47460RSc06171.988909signal peptidase
RSUY_RS01700RSUY_03520RSc31041.73953calcium sensor EFh
Stress relatedRSUY_RS13090RSUY_26760RSc05822.610905avrD-like protein
RSUY_RS21705RSUY_44580RSp1306−2.11404speE2spermidine synthetase
Cofactor metabolism and transportRSUY_RS02845RSUY_05840RSc2886−2.57058adenylate cyclase
Recombination and repairRSUY_RS07890RSUY_16140RSc1189−2.09233recombinase RecB
TranslationRSUY_RS15445RSUY_31580RSc0085−2.70405ccamultifunctional CCA protein
Hypothetical proteinsRSUY_RS19605RSUY_402404.758974hypothetical protein
RSUY_RS17575RSUY_35990RSp02614.146986membrane protein
RSUY_RS16950RSUY_34650RSp04033.74634hypothetical protein
RSUY_RS22040RSUY_45290RSp09823.589851hypothetical protein
RSUY_RS12885RSUY_26330RSc06133.409348hypothetical protein
RSUY_RS08290RSUY_16960RSc12623.394474hypothetical protein
RSUY_RS06775RSUY_13900RSc09713.025981hypothetical protein
RSUY_RS20375RSUY_418503.019263hypothetical protein
RSUY_RS01105RSUY_02290RSc32702.806237hypothetical protein
RSUY_RS15470RSUY_31630RSc00802.792044hypothetical protein
RSUY_RS14600RSUY_29830RSc02972.641501hypothetical protein
RSUY_RS05760RSUY_11810RSc22802.552951hypothetical protein
RSUY_RS10215RSUY_20850RSc16222.233892hypothetical protein
RSUY_RS12820RSUY_262002.213444hypothetical protein
RSUY_RS22015RSUY_45240RSp15462.185718hypothetical protein
RSUY_RS01435RSUY_02950RSc06162.148496hypothetical protein
RSUY_RS06705RSUY_13730RSc09532.116755hypothetical protein
RSUY_RS01875RSUY_03890RSc30722.098485hypothetical protein
RSUY_RS04190RSUY_08560RSc25551.909667membrane protein
RSUY_RS05940RSUY_12170RSc22381.775776hypothetical protein
RSUY_RS04990RSUY_10170RSc0799−1.56204hypothetical protein
RSUY_RS02135RSUY_04410RSc3030−2.05111hypothetical protein
RSUY_RS20585RSUY_42270−2.22451membrane protein
RSUY_RS14980RSUY_30600RSc0211−2.4077membrane protein
RSUY_RS17045RSUY_34880RSp0420−2.58002membrane protein
RSUY_RS15175RSUY_31000RSc0146−2.83465hypothetical protein
PUTATIVE VIRULENCE GENES AND PLANT COLONIZATION METABOLIC ACTIVITIES
TransportersRSUY_RS00490RSUY_01050RSc33863.50metal ABC transporter substrate-binding protein
RSUY_RS17605RSUY_36050RSp04293.24MFS transporter
RSUY_RS20020RSUY_41100RSp09312.92ABC transporter
RSUY_RS19045RSUY_39070RSp0706−1.77metal-dependent hydrolase
RSUY_RS18205RSUY_37320RSp0481−2.03ABC transporter substrate-binding protein
RSUY_RS18195RSUY_37300RSp0479−2.09amino acid ABC transporter ATPase
RSUY_RS21220RSUY_43600RSp1181−2.11transporter
RSUY_RS18895RSUY_38770RSp0670−2.14acriflavine resistance protein B / transporter protein
RSUY_RS17425RSUY_35690RSp0234−2.37MFS transporter
RSUY_RS09885RSUY_20190RSc1738−2.40ABC transporter ATPbinding protein
RSUY_RS21615RSUY_44400RSp1278−2.49MFS transporter
RSUY_RS21315RSUY_43800RSp1200−2.60RND transporter
RSUY_RS03020RSUY_06190RSc2856−2.72MFS transporter
RSUY_RS01560RSUY_03230RSc3134−2.94MFS transporter
RSUY_RS06940RSUY_14230RSc1002−2.95membrane protein
RSUY_RS15855RSUY_32410−2.98oprMRND transporter
RSUY_RS20395RSUY_41890−2.99ybtPABC transporter ATP-binding protein
RSUY_RS15985RSUY_32660RSp0078−3.05MFS transporter
RSUY_RS18200RSUY_37310RSp0480−3.17amino acid ABC transporter permease
RSUY_RS19050RSUY_39080RSp0707−3.19ABC transporter ATP-binding protein
RSUY_RS21055RSUY_43260RSp1114−3.35RND transporter
RSUY_RS01890RSUY_03920RSc3069−3.50MFS transporter
RSUY_RS22255RSUY_45730RSp1595−3.73ABC transporter ATP-binding protein
RSUY_RS04055RSUY_08290RSc2632−3.85ABC transporter ATP-binding protein
Lipid metabolismRSUY_RS14075RSUY_28780RSc03963.29ipk4-diphosphocytidyl-2C-methyl-D-erythritolkinase
RSUY_RS10705RSUY_21830RSc15403.14acyltransferase
RSUY_RS19325RSUY_396702.15Phosphatidylserine/phosphatidylglycerophosphate/cardiolipin synthase
RSUY_RS09620RSUY_19650RSc1772−2.06alpha/beta hydrolase
RSUY_RS14790RSUY_30210RSc0262−2.17glyoxylate/hydroxypyruvate reductase A
RSUY_RS00675RSUY_01440RSc3346−2.24alpha/beta hydrolase
RSUY_RS13905RSUY_28430RSc0427−2.30beta-ketoacyl-[acyl-carrier-protein] synthaseII
RSUY_RS09090RSUY_18590−2.77Lysophospholipase
RSUY_RS01035RSUY_02150RSc3283−2.82glxR2-hydroxy-3-oxopropionate reductase
RSUY_RS10955RSUY_22330RSc1874−2.82NUDIX hydrolase
RSUY_RS14265RSUY_29170RSc0357−2.86gpsAglycerol-3-phosphate dehydrogenase (NAD(P)(+))
RSUY_RS11775RSUY_23990RSc2091−3.04ABC transporter permease
RSUY_RS15945RSUY_32580RSp0036−3.05acyl-CoA dehydrogenase
RSUY_RS21855RSUY_44890RSp1245−3.30esterase
RSUY_RS20415RSUY_41930−3.31Acyl-coenzyme A synthetase
RSUY_RS21590RSUY_44350−3.32Dehydrogenases
RSUY_RS20425RSUY_41950−3.60Polyketide synthase
RSUY_RS14720RSUY_30070RSc0275−3.61short-chain dehydrogenase
RSUY_RS10105RSUY_20630RSc1643−4.27ispD2-C-methyl-D-erythritol 4-phosphatecytidylyltransferase
Other putative virulence factorsRSUY_RS16085RSUY_32860RSp01122.09carbonic anhydrase
RSUY_RS00735RSUY_01550RSp00851.66type IV secretion protein Rhs
RSUY_RS00905RSUY_01890RSc3302−2.04priAprimosomal protein N'
RSUY_RS15535RSUY_31760RSc0068−2.06smfDNA processing protein DprA
RSUY_RS14955RSUY_30550RSc0222−2.29rtcRFis family transcriptional regulator
RSUY_RS17190RSUY_35180RSp0181−3.10activator of HSP90 ATPase
RSUY_RS14940RSUY_30520RSc0226−3.23rtcARNA 3'-terminal phosphate cyclase
Sulfur metabolism and transportRSUY_RS12265RSUY_25040RSc24253.22cysI1Sulfite reductase/sulfite reductase
RSUY_RS07020RSUY_14390RSc10192.23nifSCysteine desulfurase IscS
RSUY_RS12250RSUY_25010RSc24222.14cysDSulfate adenylyltransferase small subunit
RSUY_RS12245RSUY_25000RSc24211.89cysNSulfate adenylyltransferase
RSUY_RS07025RSUY_14400RSc10201.60nifUIron-sulfur cluster scaffold-like protein
RSUY_RS17845RSUY_36540RSp1519−3.36Membrane protein
Cofactor metabolism and transportRSUY_RS11705RSUY_23850RSc20771.85ilvIacetolactate synthase
RSUY_RS18660RSUY_38270RSp0615−2.97cbiAcobyrinic acid a,c-diamide synthase
RSUY_RS18690RSUY_38330RSp0621−2.97cbiLprecorrin-2 C(20)-methyltransferase
RSUY_RS18680RSUY_38310RSp0619−3.00cbiGcobalamin biosynthesis protein CbiG
RSUY_RS03905RSUY_07990RSc2663−3.51ATP:cob(I)alamin adenosyltransferase
Phosphate mobilizationRSUY_RS10765RSUY_21950RSc15292.01pstS1phosphate ABC transporter substrate-bindingprotein PstS
RSUY_RS07715RSUY_15790RSc11601.63suhBInositol monophosphatase
RSUY_RS10750RSUY_21920RSc15321.52pstBphosphate ABC transporter ATP-binding protein

R. solanacearum UY031 genes differentially expressed in potato roots vs. solid rich medium.

a

According to R. solanacearum UY031 genome annotation available at GenBank (NCBI).

b

According to R. solanacearum UY031 genome annotation from Guarischi-Sousa et al. (2016).

c

According to the homology Supplementary Table 1.

Taken together, these results show a major induction of stress-related activities and an inhibition of the central metabolism when the bacterium grows in planta compared to synthetic media.

R. solanacearum virulence genes are differentially expressed in wild potato roots

Among the 422 genes DE during S. commersonii root colonization, 34% (80 induced and 65 repressed genes) had been identified in previous studies analyzing gene expression of R. solanacearum cells recovered from infected plant stems (see references below). Notably, 73 genes were also DE in microarray analyses of R. solanacearum UW551 -a phylotype IIB strain highly similar to UY031- isolated from tomato (Jacobs et al., 2012). Also, 42 genes have been shown to be induced in a temperature-dependent manner when bacteria grew in tomato xylem or rhizosphere (Bocsanczy et al., 2014; Meng et al., 2015). In addition, 31 DE genes (most of them induced in planta) are part of either the HrpB or HrpG regulons, which are known to trigger expression of the T3SS and other virulence genes in response to direct plant cell contact (Valls et al., 2006).

Amongst the R. solanacearum genes induced during plant colonization, 31 encode already reported virulence traits (Table 3). As expected, genes encoding the T3SS (hrpY, hrpX, hrpK, hrcT) and some of its related effectors (ripV2, popC, ripD, popF1, awr5_1, popB, and popA) were induced inside the plant (Boucher et al., 1987; Cunnac et al., 2004). Motility and adherence genes were also up-regulated, including type IV pili (pilG, pilH, pilN, pilM, pilY, pilW, and fimV), as well as the transcriptional activators of the flagellum genes flhC and flhD (Kang et al., 2002; Tans-Kersten et al., 2004). Other induced genes encoding described factors that are key for bacterial virulence included hdfA (Delaspre et al., 2007), efe (Valls et al., 2006), metE (Plener et al., 2012), and rpoN1 (Lundgren et al., 2015; Ray et al., 2015; Table 3). Peroxidases, catalases (katE, katG) and alkyl hydroperoxide reductases (ahpC1, ahpF), which have been described to combat the oxidative stress response during plant infection (Rocha and Smith, 1999; Flores-Cruz and Allen, 2009; Ailloud et al., 2016) were also induced. Similarly, the flavohemoprotein hmpX, involved in NO-detoxification (Dalsing and Allen, 2014), was also induced.

In contrast, only 10 reported virulence determinants were down-regulated, including the type III effectors ripQ, ripS2, and ripTPS, the quorum sensing regulator solI (Flavier et al., 1997) and the Type II secretion system genes gspE, gspJ (Table 3).

R. solanacearum genes for plant colonization are differentially expressed in S. commersonii roots

Thirty-six R. solanacearum genes previously described as related to plant colonization in gene expression studies in other plant species were also induced in potato. Few metabolic genes were induced in planta, being an exception nadB2, involved in the degradation of L-aspartate in the xylem (Brown and Allen, 2004) and the ptsN and narL nitrogen metabolism genes, known to be active during plant colonization (Dalsing and Allen, 2014; Dalsing et al., 2015; Table 3).

Amongst the down-regulated genes, 42 had also been described as specifically down-regulated during plant colonization (Jacobs et al., 2012). Most repressed genes encoded metabolic enzymes and transporters. Examples are the xylose transporters xylF, xylG, and xylH, glycine catabolism genes gcvP, gcvT, and gcvA, the adenilate cyclase coding gene RSUY_RS02845, four siderophore biosynthesis genes and 11 genes involved in amino acid metabolism (Table 3). Also, the stress response gene speE2 and five transcriptional and response regulators were repressed in planta.

Novel putative virulence genes and metabolic traits involved in early stages of wild potato infection by R. solanacearum

Transcriptomic analysis of S. commersoni early root infection revealed highly induced R. solanacearum virulence factors still uncharacterized in this pathogen that may play a role at this stage of the interaction with the host. An example of this is suhB, a global virulence regulator controlling the type III and type VI secretion systems, flagellum biosynthesis, and biofilm formation in the human pathogens Burkholderia cenocepacia and Pseudomonas aeruginosa (Rosales-Reyes et al., 2012; Li et al., 2013). Similarly, a P. aeruginosa orthologue of the in planta induced type IV secretion gene Rhs has been described as a virulence determinant (Kung et al., 2012).

Metabolic traits that might be key at this point of plant infection are the assimilatory sulfate reduction pathway and phosphate mobilization, since cysD, cysN, and cysI (sulfate reduction) and pstB and pstS1 (phosphate mobilization) were induced during S. commersonii root infection. Also, carbonic anhydrase (RSUY_RS16085), which plays a role in disease establishment between potato and Phytophthora infestans (Restrepo et al., 2005), was also found to be up-regulated in the R. solanacearum interaction with wild potato.

The most important category amongst the R. solanacearum genes down-regulated in S. commersonii with so far no assigned functions in plant colonization or virulence was metabolite transporters. Almost half of these corresponded to the ABC-family, including five amino acid transporters. In contrast, the seven major facilitator superfamily (MFS) transporters found in this category are involved with carbohydrate transport. The rest of genes were classified as permeases or RND (Resistance-Nodulation-Division) efflux systems (Table 3). The major metabolic activities identified as repressed in planta for the first time were lipid mobilization and cofactor metabolism, such as the anaerobic cobalamin biosynthesis operon (cbiA, cbiG, and cbiL), and stress-response genes such as rtcA and rtcR, involved in RNA repair (Das and Shuman, 2013).

In sum, our work reflects important gene expression changes between parasitic life and growth in rich medium (see below). This was corroborated by the fact that seven genes annotated as response regulators were also DE, five of them induced (Table 3).

Discussion

Some R. solanacearum virulence and stress-responsive genes are induced irrespective of the plant host

1/3 of the R. solanacearum genes DE during potato infection had been also found DE when the bacterium colonized other plant species and many of these correspond to virulence determinants. For instance, we found that genes encoding the type III secretion system and its associated effectors (popA, popB, popC, popF1, ripD, ripV2, and awr5_1) were induced in potato (Table 3). Except for awr5_1, all these effectors had already been described as up-regulated when the bacterium grew in tomato and in melon (Ailloud et al., 2016), likely indicating that they are part of the minimal gene set required for bacterial virulence. Similarly, the effector ripTPS was down-regulated both in potato (Table 3) and during the interaction with melon (Ailloud et al., 2016). Also sharing similar up-regulation in potato (Table 3) and tomato are the transcriptional activators flhC and flhD (Jacobs et al., 2012), which regulate flagellum-encoding genes (Tans-Kersten et al., 2004) and the nitrogen metabolism genes narL, ptsN, and hmpX (Dalsing and Allen, 2014; Dalsing et al., 2015), implying that they all play a key role during plant infection. Additional genes induced during potato colonization had been described as key for virulence on other plant hosts, including small molecule hdfA (Delaspre et al., 2007), the ethylene forming enzyme efe (Valls et al., 2006), the methionine metabolism gene metE (Plener et al., 2012) and the alternative sigma factor rpoN1 (Lundgren et al., 2015; Ray et al., 2015). These factors may be also considered essential for growth in planta, irrespective of the infected species.

Several transposable elements had been identified in an in vivo screening for genes expressed during R. solanacearum growth in tomato plants (Brown and Allen, 2004), and we found 16 transposases up-regulated in potato (Table 3). This may reflect common stressing conditions in various plant hosts, as stress is known to turn on transcription of transposable elements in various organisms (Capy et al., 2000). Oxidative stress seems also a condition generally encountered by R. solanacearum in plant tissues, as peroxidases, catalases, and peroxiredoxins, required for the bacterium to combat this stress in different plants (Rocha and Smith, 1999; Flores-Cruz and Allen, 2009; Ailloud et al., 2016), were also induced in potato.

Changes in the host environment and/or the disease stage may account for opposing bacterial virulence gene expression in different plants

Some of the R. solanacearum virulence genes DE in potato showed opposite trends in other host plants. ripQ and ripS2, two of the three type III secreted effectors inhibited in potato were, respectively, upregulated and not DE in melon, tomato and banana (Ailloud et al., 2016). Interestingly, these two downregulated effectors, together with the also repressed stress response gene speE2, are located in a genomic region that is deleted in the avirulent R. solanacearum strain UY043 (Siri et al., 2014), which suggests their involvement in bacterial virulence. Similarly, the effector awr5_1, which was described to trigger hypersensitive response (HR) in tobacco and to inhibit the TOR pathway (Sole et al., 2012; Popa et al., 2016b), showed opposite regulation in potato when compared to tomato and melon (Ailloud et al., 2016), suggesting that it may play host-specific roles. Similarly, genes pilG, pilH, pilN, pilM, pilY, and pilW, coding for structural components of the type IV pili involved in twitching motility and adherence (Liu et al., 2001; Kang et al., 2002) were induced in the current work but repressed in other plant species (Jacobs et al., 2012).

In addition, some virulence determinants well-described as induced during growth in planta were repressed or not DE in potato. Remarkably, the exopolysaccharide synthesis and regulation genes (eps) as well as most known cell wall degrading enzymes (pehA, pehB, pehC, egl, and cbhA), which are virulence determinants (Schell, 2000) induced during tomato infection (UW551 strain) infection (Jacobs et al., 2012) were absent from the potato DE dataset.

Differences in the host environment or in the tissue environment and disease stage are the two most plausible reasons for the discrepancies between virulence gene expression data in potato and in other plant hosts. We favor the latter explanation, as our samples were collected from bacteria growing in the root (including apoplastic and xylematic bacteria) at early times after inoculation while all previous transcriptomic work had been performed from bacteria extracted from xylem at later infection stages.

Three independent observations support the existence of stage-specific environmental cues that differentially affect gene expression in this work compared to previous studies. First, genes that are induced at high bacterial densities are absent from the potato DE genes. Examples are the mentioned exopolysaccharide synthesis genes or the quorum sensing regulator solI, repressed in our conditions but slightly induced in bacteria isolated from the tomato shoot xylem (Jacobs et al., 2012). In the low bacterial cell densities in the roots the phcA cell-density regulator was not induced, impeding solI or eps expression (Huang et al., 1995; Flavier et al., 1997). Second, three out of the six type III effectors that are induced in potato were described as secreted at early stages (Lonjon et al., 2016), two of them (popF1 and popA) also proposed to play an important role in the first steps of infection (Kanda et al., 2003). On the contrary, only two out of the 38 described as “late” effectors (ripD and popC) were induced in our root transcriptome. Third, the afore-mentioned transcriptional regulators flhC and flhD responsible for the activation of the flagellum genes were up-regulated in potato root samples (Table 3) and also in the tomato xylem (Jacobs et al., 2012), but only in the latter were the flagellum structural genes induced, suggesting that the potato transcriptome represents an earlier stage where complete activation of this regulon has not yet occurred. These observations imply that our transcriptome represents a snapshot of a precise stage of the genetic programs deployed consecutively during plant colonization.

Finally, we cannot rule out that changes in R. solanacearum DE genes in different studies are due to the use of different strains. Differing transcriptomes of two R. solanacearum strains in the same plant environment have already been reported (Ailloud et al., 2016). However, the fact that previous gene expression studies were performed with strain UW551, which is genetically extremely close to UY031 used here, render this explanation unlikely. Standardization of the plant inoculation and sampling procedures and a systematic analysis of plant-pathogen interactions dissecting gene expression over time in a defined strain-host pathosystem would clarify the nature of the observed discrepancies between transcriptomic studies.

The R. solanacearum metabolic state during potato root colonization

From the transcriptomic information gathered in this work, we can infer for the first time the environmental conditions encountered by R. solanacearum in the root, the site where plant infection takes place.

A first observation is that the bacterium seems to start to run out of O2. An indication of this is the highly induced Cbb3-cco, a high affinity cytochrome c oxidase known to contribute to the growth of R. solanacearum and other bacteria in microaerobic or anoxic environments (Colburn-Clifford and Allen, 2010; Hamada et al., 2014), such as the plant xylem (Pegg, 1985). Upregulation of the low O2 affinity cytochrome ubiquinol oxidase genes cyoA1 and cyoB1 reinforces the notion of a microaerobic rather than an anoxic environment. In agreement with this, nrdB, which is required for growth in aerobiosis (Casado et al., 1991), was up-regulated, and nrdG and nrdD, required in strict anaerobiosis (Garriga et al., 1996; Ailloud et al., 2016) were not induced. Further, the cbiA, cbiL, and cbiG genes, which are involved in anaerobic cobalamin synthesis (Roessner and Scott, 2006), were repressed. Another indication of microaerobic conditions is the induction of genes driving nitrate and sulfate anaerobic respiration. Examples are the cys genes, involved in the assimilatory sulfate reduction pathway (Kredich, 1992), ptsN—a nitrogen-dependent regulatory protein, rpoN1, -the global nitrogen regulator- and narL -the nitrate/nitrite-responsive transcriptional regulator- were all induced in wild potato roots. All these findings suggest that during early root infection R. solanacearum is experiencing the transition from an aerobic environment to the anaerobic conditions established at the onset of disease during xylem colonization (Ailloud et al., 2016).

Another take home message from the root transcriptomes is that few central metabolic pathways seem to be active. It was previously described that a large proportion of the R. solanacearum genes involved in amino acid metabolism and transport was down-regulated during growth in the xylem (Ailloud et al., 2016) and we found that this was also the case during growth in the root tissues at early stages of infection. For instance, the glycine catabolism genes gcvP, gcvT, and gcvA as well as the dipeptide uptake gene dppD1 were repressed in both cases (Table 3; Ailloud et al., 2016). Other R. solanacearum metabolic genes previously known to be repressed in planta also down-regulated here included carbohydrate metabolism genes such as the xylose transporter operon xylFGH and Glucosamine 6-phosphate synthetase, the key enzyme controlling amino sugar biosynthesis (Milewski, 2002; Jacobs et al., 2012). Lipid metabolism was also strikingly repressed during root colonization. Out of the 21 DE genes involved in lipid mobilization, only 2 have been found in previous gene expression studies in R. solanacearum (Table 3; Jacobs et al., 2012). Thus, the downregulation of lipid metabolism could be specific to early infection stages or to wild potato colonization. In this sense, lipid metabolism has been reported to play an important role during plant-host interactions by modulating defense responses in plants and pathogen infection (Casadevall and Pirofski, 2001; Wenk, 2006). Cofactor metabolism was also repressed including the folate synthesis gene pabB (Table 3), already known to be down-regulated in planta (Shinohara et al., 2005), the cobalamin biosynthesis genes and adenilate cyclase. Repression of adenylate cyclase, which is a global metabolic regulator in bacteria (Ullmann and Danchin, 1980), illustrates the magnitude of the metabolic shutdown experienced by R. solanacearum in the roots of S. commersonii.

In contrast with the global metabolic shutdown, aspartate and tryptophan catabolism genes were up-regulated when R. solanacearum grew in the plant roots. The aspartate catabolism gene nadB2 had already been identified as an essential gene for in planta growth in an in vivo screening (Brown and Allen, 2004). Interestingly, aspartate is the second most abundant aminoacid in the tomato apoplast and less so in the xylem (Zuluaga et al., 2013), which is in agreement with the bacterium mostly thriving in the apoplastic root spaces at the early infection times analyzed. Also induced was the Tryptophan 2,3-dioxygenase. Concentrations of this aminoacid are high at lateral root emergence sites (Jaeger et al., 1999), and it was suggested that it is also present in the tomato apoplast (Yu et al., 2013). Induction of tryptophan catabolism would thus be indicative of early plant colonization.

These results likely indicate the existence of a trade-off between the expression of virulence and metabolic genes. This has already been described in a previous study where the quorum-sensing-dependent regulatory protein PhcA regulated a trade-off between production of R. solanacearum exopolysaccharides and bacterial proliferation (Peyraud et al., 2016).

Proposed new virulence determinants important for early root colonization

RSUY_RS08455 and RSUY_RS16950 were found to be upregulated in a resistant S. commersonii accession compared to a susceptible one (Table 2), as well as during root colonization compared to rich medium (Table 3). Although these genes also appeared in the microarray transcriptome of bacteria extracted from infected tomato xylem vessels (Jacobs et al., 2012), they have not been characterized.

Similarly, the gene encoding an avrD-like protein was up-regulated in tomato xylem (Jacobs et al., 2012) and in wild potato (Table 3). AvrD is required in P. syringae for the synthesis of syringolide, small molecules that can elicit a hypersensitive response on resistant plants (Keen et al., 1990; Mucyn et al., 2014). In R. solanacearum the avrD-like protein encoding gene is activated by the master virulence regulator HrpG (Valls et al., 2006). Considering the persistence of these three genes among the up-regulated during plant colonization, we suggest that they encode for potential virulence factors, probably necessary independently of the host or the infection stage.

Three genes found up-regulated in S. commersonii (suhB, rhs and the carbonic anhydrase gene RSUY_RS16085, Table 3) have been involved in bacterial virulence on animals and constitute putative virulence genes in R. solanacearum. Although classified as a phosphate mobilization gene (Table 3), suhB is a super-regulator involved in the proper rRNA folding (Singh et al., 2016). It plays a role in virulence of animal bacterial pathogens, influencing T3SS, T6SS, flagellum and biofilm regulation and probably acts in opposite ways in different bacteria (Rosales-Reyes et al., 2012; Li et al., 2013). Interestingly, SuhB differential expression was also observed in two R. solanacearum strains (Meng et al., 2015). The function of Rhs (Rearrangement Hot Spot) proteins is ill-defined but they are considered to promote recombination (Lin et al., 1984). Interestingly, a member of the Rhs family was described to be induced during infection and associated with increased bacterial numbers and decreased survival in mice during pneumonia caused by P. aeruginosa (Kung et al., 2012). Finally, carbonic anhydrase catalyzes the inter-conversion between carbon dioxide and bicarbonate but is also required for growth of many animal pathogenic microorganisms (Capasso and Supuran, 2015). In addition, a role in disease establishment between potato and Phytophthora infestans was also reported (Restrepo et al., 2005), suggesting the possible implication of CAs during host colonization. These evidences suggest that suhB, rhs, and RSUY_RS16085 encode putative virulence factors shared between gram-negative bacterial pathogens that infect animals and plants.

The assimilatory sulfate reduction pathway (cysD, cysN, and cysI) and the phosphate mobilization (pstB and pstS1) were also induced during root colonization (Table 3). cysD and cysN, encode an ATP sulfurylase that produces APS, which can be in turn reduced to PAPS to ultimately synthesize cysteine by cysI. A study carried out in a closely related plant pathogenic bacterium, Xanthomonas oryzae pv. Oryzae, was demonstrated that mutation of either raxP or raxQ (homologs of cysD and cysN) impaired production of APS and PAPS and were required for the correct activity of the avirulence protein AvrXa21 (Shen et al., 2002). Further, several studies demonstrated that mutations on the pst system, responsible for phosphate uptake, affected virulence in diverse animal pathogenic bacteria (Rao et al., 2004; Lamarche et al., 2005, 2008). Altogether, these studies suggest that both systems might be regulators of bacterial pathogenicity, which could also be conserved in plant pathogens.

Finally, the rtcA and its regulator rtcR are down-regulated in planta (Table 3). The rtc system is involved in the regulation of the RNA repair system for ribosome homeostasis through the activation of rtcR by different agents and genetic lesions which in turn activates the rtcAB genes (Das and Shuman, 2013). The rtc system was also involved in the functioning of chemotaxis and motility in Escherichia coli (Engl et al., 2016), as mutations in either rtcA or rtcB increased motility. Since rtc acts a repressor of motility, its down-regulation in S. commersonii colonization could influence bacterial motility, a key virulence determinant.

Funding

This work was funded by projects AGL2013-46898-R, AGL2016-78002-R, and RyC 2014-16158 from the Spanish Ministry of Economy and Competitiveness. We also acknowledge financial support from the “Severo Ochoa Program for Centres of Excellence in R&D” 2016-2019 (SEV-2015-0533) and the CERCA Program of the Catalan Government (Generalitat de Catalunya) and from COST Action SUSTAIN (FA1208) from the European Union. APM is funded by the Chinese Academy of Sciences and the Chinese 1000 Talents Program. MP holds an APIF doctoral fellowship from Universitat de Barcelona and received a travel fellowship allowed by Fundació Montcelimar and Universitat de Barcelona to carry out a short stay in JCS's lab. RGS holds a doctoral fellowship; grant 2012/15197-1, São Paulo Research Foundation (FAPESP) and JCS has a CNPq research fellowship.

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

MP performed experiments, analyzed data and wrote the manuscript; RG analyzed data; PZ performed experiments; NC designed the research and wrote the manuscript; AM designed experiments and analyzed data; JS designed the research, analyzed data and wrote the manuscript; MV designed the research, performed experiments, analyzed data, and wrote the manuscript.

Acknowledgments

We thank R. de Pedro for helping in the solid rich medium sample preparation, I. Erill for helping in the transcriptomic data interpretation, S. Genin, and S. Lindow for inspiring discussions, C. Madrid, and C. Balsalobre for advice on transcriptome data interpretation, M. Solé for the potato infection set up and F. Vilaró, M. dalla Rizza, and M.J. Pianzzola for their advice and for providing the S. commersonii genotypes used in this study. We thank the Shanghai PSC Genomics facility for RNA sequencing.

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/fpls.2017.00370/full#supplementary-material

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Summary

Keywords

Ralstonia solanacearum, bacterial wilt, Solanum commersonii, RNA sequencing, transcriptomics, disease resistance, potato brown rot

Citation

Puigvert M, Guarischi-Sousa R, Zuluaga P, Coll NS, Macho AP, Setubal JC and Valls M (2017) Transcriptomes of Ralstonia solanacearum during Root Colonization of Solanum commersonii. Front. Plant Sci. 8:370. doi: 10.3389/fpls.2017.00370

Received

17 January 2017

Accepted

02 March 2017

Published

20 March 2017

Volume

8 - 2017

Edited by

Fabienne Vailleau, Centre Toulouse Midi-Pyrénées (INRA), France

Reviewed by

Yasufumi Hikichi, Kōchi University, Japan; Chiu-Ping Cheng, National Taiwan University, Taiwan

Updates

Copyright

*Correspondence: João C. Setubal

This article was submitted to Plant Microbe Interactions, a section of the journal Frontiers in Plant Science

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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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