Transcriptome of Arabidopsis thaliana plants treated with the human pathogen Campylobacter jejuni

Biocatalysis and Agricultural Biotechnology 11 (2017) 259–267

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Transcriptome of Arabidopsis thaliana plants treated with the human pathogen Campylobacter jejuni Andrey Golubova, Boseon Byeona, Rafal Woycickia, G. Douglas Inglisb, Igor Kovalchuka, a b

MARK ⁎

Department of Biological Sciences, University of Lethbridge, University Drive 4401, Lethbridge, AB T1K 3M4, Canada Agriculture and Agri-Food Canada Research and Development Centre, Lethbridge, Alberta, Canada

A R T I C L E I N F O

A B S T R A C T

Keywords: Pathogenic Campylobacter jejuni Escherichia coli Arabidopsis thaliana fls2 mutant Transcriptome profiling

Recognition of pathogen infection in plants and animals occurs through interaction of pathogen-associated molecular patterns (PAMPs) with pattern recognition receptors (PRR), such as, for example, the recognition of flagellin by Toll-like receptor (TLR) 5 in animals and FLS2 in plants. In this work we exposed wild type and fls2 Arabidopsis thaliana mutant to Campylobacter jejuni. Transcriptome profiling revealed differentially expressed genes in both genetic backgrounds, with ~ 30% overlap in the upregulated group category. The response of fls2 mutant was more robust as more genes changed their expression and larger number of GO term categories was enriched in the mutant. Comparison of the response to Arabidopsis to C. jejuni with response to Escherichia coli O157:H7 showed only partial overlap, with the response in Col-0 plants having more similarities in commonly upregulated genes and enriched GO term categories than the response in fls2 plants. Whereas in the Col-0, GO terms “response to bacteria”, “leucine-rich repeats” and “planttype cell wall” were commonly enriched between two animal pathogens tested. In the mutant, GO terms associated with abiotic stress response were enriched for both pathogens. Analysis of motifs of commonly regulated genes showed a large diversity of motifs found in up- and down-regulated genes, and correlation analysis showed more similarity in comparison of motifs between C. jejuni and E. coli O157:H7, rather than between Col-0 and fls2 groups of the same bacterial treatment. Our work thus shows that plants are able to respond to C. jejuni infection in FLS2-dependent and independent manner.

1. Introduction Humans can be infected by pathogenic bacteria through consumption of contaminated food and/or water. Since many plants are consumed uncooked, they can be a source of contamination for various human pathogenic bacteria. Although some reports exist about interaction of zoonotic bacteria with plants, the data are scarce and incomplete. Bacterial infection is normally recognized through the first layer of the immune system, the recognition of bacterial components in the form of pathogen-associated molecular patterns (PAMPs) through variety of receptors known as pattern recognition receptors (PRR). These receptors include a group of receptors commonly known as Tolllike receptors (TLR) (Mogensen, 2009). PAMPs include various molecules, including proteins such as flagellins, chitin and EF-Tu or lipopolysaccharides (LPS) (Zipfel and Robatzek, 2010). Recognition of bacterial components results in activation of various defence mechanisms leading to changes in organism's physiology and typically resistance to recognized pathogens (Glass, 2012). Bacterial flagellins are ⁎

Corresponding author. E-mail address: [email protected] (I. Kovalchuk).

http://dx.doi.org/10.1016/j.bcab.2017.07.016 Received 13 June 2017; Received in revised form 24 July 2017; Accepted 25 July 2017 Available online 26 July 2017 1878-8181/ © 2017 Elsevier Ltd. All rights reserved.

recognized in animals by the group of receptors commonly known as TLR5 receptors. Not all flagellins seem however to be recognized by TLR5; for example the food-borne bacterium Campylobacter jejuni avoids recognition by TLR5, likely because of a difference in a structure of some of the domain of the flagellin (Johanesen and Dwinell, 2006). Only moderate activation of IL-8 pathway in response to stimulation with C. jejuni flagellin has been observed in enterocytes (Watson and Galan, 2005; Johanesen and Dwinell, 2006). Therefore, the details of recognition of this pathogen are unknown. Several reports suggest that LPS is the specific PAMP that is recognized by animal cells and that recognition occurs through interaction with TLR2 and TLR4 receptors (Blaser et al., 1983). Friis et al. (2009) used artificial siRNAs to downregulate the expression of TLR2 and found over 60% reduction in the activation of IL-6 expression levels after infection with C. jejuni. The authors therefore hypothesized that TLR2 is important for the recognition and signaling responses to C. jejuni infections. Recognition of bacterial pathogens is similar in animal and plant species, and several animal bacterial pathogens can also infect plants, inciting disease and triggering an immune response (Shirron and Yaron,

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2011; Garcia et al., 2014). In plants, bacterial flagellins are recognized by FLS2 receptor (Gomez-Gomez and Boller, 2000); FLS2 receptors have been characterized for many plant species, including Arabidopsis (Gomez-Gomez and Boller, 2000). This receptor was shown to be essential for the proper pattern-triggered immunity (PTI) to be triggered, as fls2 plants lacking such receptor are more susceptible to bacterial infection (Zipfel et al., 2004; Zipfel et al., 2004, 2006). FLS2 was also shown to be important for priming; pre-treatment of the wild type plants with the bacterial peptide flg22 that activates host immune response normally results in higher tolerance to subsequent infection with Pseudomonas syringae pv. tomato DC3000, whereas the fls2 mutant lacks such response (Zipfel et al., 2004). Similarity between animal and plant PTI is further demonstrated by the fact that flagellin from the animal bacterial pathogen Salmonella enterica induces PTI in Arabidopsis in FLSdependent manner, and the fls2 mutant is not able to mount the same level of response (Garcia et al., 2014). Campylobacter jejuni is a human pathogen commonly found in the intestinal tracts and feces of non-human animals; it is the most common causative agent of bacterial enteritis in human beings in developed countries. Despite the sanitary efforts, C. jejuni is detected in meat processing factories (poultry primarily) as well as on vegetables (de Carvalho et al., 2013). It is not clear however whether this bacterium can colonize plants and whether plants recognize C. jejuni as a pathogen. In our previous work we exposed wild type and fls2 mutant of Arabidopsis thaliana to pathogenic E. coli O157:H7 and found that the both plants respond to this pathogen, and there was only partial overlap in differentially expressed genes (Golubov et al., 2010). This suggests that E. coli O157:H7 is recognized as a pathogen by plants and that recognition occurs both through FLS2-dependent and independent mechanisms. In this work, we exposed wild type and fls2 Arabidopsis plants to C. jejuni and performed detailed transcriptome analysis. We found the response of mutant plants being more robust as more genes were up/down regulated in response to C. jejuni. We then compared responses to E. coli O157:H7 and C. jejuni and found more similarities in response of Col-0 plants, rather than mutant plants, suggesting that in the absence of FLS receptor plant may use different recognition mechanisms for these two bacteria.

mutant. Plants from each genetic background were used for mock treatment, buffer treatment or treatment with bacteria. Each treatment was performed twice, representing biological replicates. For treatments, fully expended leaves of 3-week-old plants were cut and placed into 50 ml falcon tubes filled with Murashige and Skoog (MS) medium (six to eight leaves per tube; two plants per each experimental group). Before the treatment, MS medium was discarded and tubes were filled with 50 ml of bacterial suspension in PBS (“bacterium” treatment group). Two control groups were prepared, one filled with PBS (“buffer” treatment group) and another with MS medium (“control” groups). All work was performed in an operating class 2A biological safety cabinet at room temperature within a containment level 2 facility at the Lethbridge Research and Development Center (Agriculture and Agri-Food Canada, Lethbridge, Alberta, Canada). Leaf tissues were submerged in the bacterial suspension, PBS, or MS medium for 2 h, washing three times with PBS, and then flash-freezing in liquid nitrogen. 2.3. Total RNA purification For the RNA extraction, frozen leaves were ground in liquid nitrogen and the total RNA was purified using TRIzol® Reagent (Invitrogen) according to instructions provided by the manufacturer. The quality and the concentration of each RNA sample were analyzed using the NanoDrop 2000C spectrophotometer (Thermo Fisher Scientific Inc.). RNA integrity was analyzed using agarose gel electrophoresis. 2.4. mRNA deep sequencing, demultiplexing and sequence assembly For mRNA sequencing, the libraries were prepared from total RNA from three experimental groups, non-treated, buffer-treated and bacteria-treated plants, each in two biological replicates. Libraries were prepared according to the instructions for TruSeq RNA sample Prep v2 LS protocol (Illumina, San Diego, CA, USA). In brief, mRNA was extracted from the total RNA using poly-T oligo-attached magnetic beads. After CDNA synthesis, fragmentation and blunting the ends, indexing adapters were ligated to the ends and the molecules were hybridized onto a flow cell followed by a PCR amplification step. The libraries were then quantified using the qPCR and analyzed using Bioanalyzer 2100 (Agilent Technologies). The libraries were then normalized and used for cluster generation using a cBot (Illumina). Clusters were checked for overclustering and then single-end 72 cycles sequencing was performed on the Illumina GAIIx. Base calling and demultiplexing of reads was performed using the CASAVA v1.6 and Novobarcode software (http://www.novocraft.com/ ). FastQC v 0.10.1 was used for the preliminary quality check. Reads were mapped Arabidopsis genome using TopHat v 2.0.4 beta (Trapnell et al., 2009). Transcripts were assembled (Trapnell et al., 2010) and the assemblies were merged using the cuffmerge tool (Cufflinks v 2.0.2) with Arabidopsis genome as the reference. Cuffdiff tool (Cufflinks v 2.0.2) was used to assess relative transcript abundance (Trapnell et al., 2012).

2. Materials and methods 2.1. Plants used in the experiment Arabidopsis thaliana plants cultivar Columbia wild type and fls2 mutant (in Columbia background) were used in this experiment. The fls2 mutant plants were purchased from Arabidopsis Biological Resources Center (SALK_026801 C). 2.2. Experimental set up Seeds of wild type and fls2 mutant Arabidopsis thaliana plants were placed for 48 h at 4 °C on potting soil and then moved to germinate and grow in 10 × 10 cm pots on soil at 16/8 day/night conditions at 22 °C. Campylobacter jejuni 81–176 strain was obtained from secured facility at Agriculture and Agri-Food Canada Research and Development Center, Lethbridge, Alberta, Canada; the strain was originally isolated from a child with enteritis (Korlath et al., 1985). C. jejuni cells were grown overnight in Columbia broth in a microaerobic atmosphere (5% O2, 3% H2, 10% CO2, and 82% N2) at 40 °C. Cells were centrifuged, the supernatant discarded, cells resuspended in PBS (pH 7.2), and the density was adjusted to OD600 = 0.6 (≈ 108 to 109 colony forming units (CFU) per ml). Cell densities were confirmed by generating a 10fold dilution series, and spreading 100 μl from each dilution onto Karmali agar (Oxoid Canada, Nepean, ON), maintaining the cultures at 40 °C in a microaerobic atmosphere, and enumerating colonies at the dilution yielding 30–300 CFU per culture. The experiment had two genetic backgrounds, Col-0 and fls2

2.5. Obtaining the list of differentially expressed genes List of significantly differentially expressed genes between treatment and control groups was created using the Benjamini-Hochberg method (Benjamini and Hochberg, 1995); the q-value below 0.05 was used as a cut off. The following comparison groups were made: buffer vs pathogen; non-treated vs buffer; non-treated vs pathogen. List of differentially expressed up- and down-regulated genes was obtained separately for Col-0 plants and fls2 mutant by combining genes from two comparison groups, non-treated vs pathogen and buffer vs pathogen, followed by subtraction of genes in the non-treated vs buffer group. To further compare the transcriptome response of Arabidopsis to C. jejuni 260

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with the response to E. coli O157:H7, we compared the sets of upregulated and downregulated genes (Golubov et al., 2016). Such comparison is justified since the experimental procedure of exposure to either pathogen was identical, including the cultivar used (Columbia0), bacterial inoculum amount, inoculation procedure and time of sample collection. 2.6. Analysis of differentially expressed genes using DAVID and SuperViewer DAVID was used for detailed characterization of differentially expressed genes (Huang da et al., 2008). These data were compared to the previously published data using E. coli O157:H7 (Golubov et al., 2016). 2.7. Analysis of motifs in the differentially regulated genes TAIR10 genomic sequences were downloaded from ftp://ftp. arabidopsis.org/home/tair/Genes/TAIR10_genome_release/. One kilobase upstream sequences of the sense and antisense strands of the genes differentially regulated in Col-0 and mutant plants in response to E. coli were selected. The motifs were extracted using version 2.2 of AlignACE (http://arep.med.harvard.edu/mrnadata/mrnasoft.html) with the default parameters. Pearson's correlation coefficient analysis of motifs across the samples was performed to identify similar and different motifs among Col-0 and fls2 groups. Motif annotation was performed using the web-based STAMP tool with the AGRIS Arabidopsis motif database using default parameters (http://www.benoslab.pitt.edu/ stamp/).

Fig. 1. Two way Venn diagrams showing overlap between sets of differentially regulated genes. A – overlap between Col-0 (WTc) and mutant (MTc) plants for upregulated and downregulated genes in response to C. jejuni. B – overlap between differentially regulated genes in the wild type plants in response to C. jejuni (WTc) and E. coli (WTe). C – overlap between differentially regulated genes in the mutant plants in response to C. jejuni (WTc) and E. coli (WTe).

3. Results and discussion

2.8. Real Time RT-PCR for confirmation of gene expression

The number of sequencing reads ranged from 1.7 to 6.0 mln, with over 93% of them mapping to the Arabidopsis genome (Supplementary Table 2). Exposure of Col-0 Arabidopsis plants to C. jejuni resulted in upregulation of 75 genes and downregulation of 42 genes (Fig. 1A) (Supplementary Table 3). Treatment of the fls mutant with C. jejuni resulted in an increase in the expression of 429 genes and a decrease in 80 genes (Supplementary Table 4). The overlap between Col-0 plants and fls mutants was 23 and three genes for up- and downregulated groups, respectively (Fig. 1A). It should be noted, however, that 23 of overlapping upregulated genes represents 30.7% of upregulated genes in Col-0 plants. This result suggests that C. jejuni is recognized both in a FLS2 dependent and independent manner. It is also plausible that in the absence of FLS2 receptor, plants respond to enteric bacterial pathogens in a broad manner, activating multiple signaling pathways. Clustering analysis showed that the “bacteria vs non-treated” treatment of Col-0 and fls2 plants clustered together and separately from “bacteria vs buffer treated” treatment of Col-0 and fls2 plants, which also clustered together (Supplementary Fig. 1). In the downregulated group of genes, the “mt bacteria vs mt buffer” treatments were most distant from the other groups, whereas “wt bacteria vs wt buffer”, and “mt bacteria vs untreated mt” treatments clustered together. This indicates that Col-0 and fls2 plants respond to C. jejuni in a similar manner. Comparison of the C. jejuni and E. coli O157:H7 infection of Arabidopsis (Golubov et al., 2016) showed that the overlap between upregulated genes in Col-0 and fls2 mutant was 10.2% in response to E. coli, much smaller than in response to C. jejuni (i.e. 30.7%). The response of Col-0 Arabidopsis plants to C. jejuni was dissimilar to the response to E. coli; only eight out of 75 genes upregulated by C. jejuni were also upregulated by E. coli, which in turn upregulated 419 genes in Col-0 Arabidopsis plants (Fig. 1B). Similarly, four genes were commonly downregulated in Col-0 plants in response to C. jejuni and E. coli (Fig. 1B). Also, the response of fls2 mutant to C. jejuni and E. coli was

For real time RT-PCR we used the same tissue samples used in the next generation sequencing experiment. Total RNA was treated with DNase I (ThermoFisher Scientific, USA) as per manufacturer's instructions. Briefly, RNA was treated in total volume of 50 μl containing 5 μl of the 10x DNase I buffer (supplemented with MnCl2), 25 μl of total RNA, 2 μl of DNase I (1 U/μl), and 18 μl of UltraPure Distilled Water (Invitrogen, USA) at 37 °C for 30 min. The reaction mix was purified with phenol: chlorophorm:isoamyl alcohol (25:24:1) mix; the solution was precipitated with 1/10 vol of the 3 M sodium acetate (pH 5.2) solution and 2.5 volumes of the 96% ethanol. Precipitate was washed twice in 1 ml of 75% ethanol and once in 1 ml of 96% ethanol, air-dried and dissolved in 20 μl of UltraPure Distilled Water (Invitrogen, USA). RNA was converted to cDNA and quantified with qPCR. The quantitative real-time PCR was performed using SsoFast EvaGreen Supermix (Bio-Rad). Primers for the real-time quantitative PCR were designed using the Beacon Designer7 program (Supplementary Table 1). The optimization of the annealing temperature, melt-curve analysis, and the analysis of amplicons via gel electrophoresis was done for each set of primers. To evaluate the PCR efficiency, the standard curve was established using a series of cDNA dilutions. Tubulin was used as a control. qPCR reaction was done with the following conditions: one cycle of 95 °C, 10', followed by 42 cycles of 95 °C, 30'' at gene-specific annealing temperature (see Table S1), 30'' + 72 °C, 30'', followed by single cycle of 60 °C, 0.04'' and 95 °C, 0.2''. Two biological repeats and two technical repeats were used. 2.9. Statistical treatment of the data Statistical treatment for the sequencing data is described above. For the real time RT-PCR, the average and standard errors of the mean were calculated. Statistical comparison on treatments was confirmed by performing pairwise Students t-tests using the MS Excel software (Microsoft). 261

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dissimilar, only four genes and one gene overlapped for the up- and down-regulated groups of genes, respectively (Fig. 1C). It should be noted that some of the changes in gene expression could be in part due to specific method of application of C. jejuni or E. coli – via the incubation of bacteria with detached leaves. Since these are restricted pathogens, no “live” exposure of Arabidopsis (for example by spraying the plant) was possible, as the pathogens had to be contained. Nevertheless, since we used appropriate buffer control, utilizing detached leaves, changes due to leaf detachment would be accounted for. Cluster analysis of the treatments for the upregulated category showed that the two bacterial treatments and buffer-treated or control groups clustered separately; also, no clear separation between C. jejunitreated and E. coli-treated groups (Golubov et al., 2016) were found, regardless of plant genetic background (Supplementary Fig. 2A). In the downregulated category, bacteria treated vs control treatments clustered separately from buffer treated groups and C. jejuni and E. coli groups were the most distant from each other; for the bacteria treated versus buffer treated treatments, C. jejuni and E. coli (Golubov et al., 2016) groups also clustered separately from each other (Supplementary Fig. 2B). 3.1. Genes with over 10-fold changes Among 75 upregulated and 42 downregulated genes in the Col-0, 14 and two were regulated by more than 10 fold. Similarly, in the mutant, out of 429 upregulated and 80 downregulated, 17 and five were altered by more than 10 fold. Upregulated genes in Col-0 plants were: AT1G27920 that encodes microtubule-associated protein 65-8 (MAP65-8), previously shown to be upregulated by salt stress (Zhang et al., 2012); AT5G40450 that encodes RBB1, REGULATOR OF BULB BIOGENESIS1, previously shown to be responsive to cold (Vergnolle et al., 2005); AT5G10050 that encodes NAD(P)-binding Rossmann-fold superfamily protein, likely involved in redox reactions (Burroughs et al., 2009); AT1G16420 that encodes METACASPASE 8, ATMC8, involved in programmed cell death, oxidative stress and response to UVC (He et al., 2008); AT5G66985 that encodes unknown protein responsive to oxygen deprivation (BrancoPrice et al., 2005); ATCG00350 that encodes psaA protein comprising the reaction center for photosystem I (www.arabidopsis.org); AT1G52560 that encodes HSP20-like chaperones superfamily protein that is induced by water and temperature stresses (Branco-Price et al., 2005); AT1G76640 that encodes CALMODULIN LIKE 39, CML39, regulated by exposure to darkness (Lee et al., 2005); and AT2G36440 that encodes unknown protein responsive to salt stress (Ma et al., 2006). The two downregulated genes in Col-0 plants were: AT3G08860 (Pyrimidine 4, PYD4), that encodes alanine-glyoxylate transaminase, previously reported to be responsive to low oxygen availability, nitrogen and light deficiency (Kendziorek et al., 2012); and AT5G26220, that encodes gamma-glutamyl cyclotransferase 2, responsive to heavy metal stress (Paulose et al., 2013). Upregulated genes in fls2 plants were: AT1G16150 that encodes WAKL4, WALL ASSOCIATED KINASE-LIKE 4, likely involved in Arabidopsis root mineral responses to Zn2+, Cu2+, K+, Na+ and Ni+ (Hou et al., 2005); AT1G79280 that encodes NUA, NUCLEAR PORE ANCHOR and regulates vegetative development and flowering; AT1G03080 that encodes NET1D, NETWORKED 1D (kinase interacting (KIP1-like) family protein) (www.arabidopsis.org); AT5G40340 that encodes Tudor/PWWP/MBT superfamily protein (www.arabidopsis. org); AT1G71400 that encodes RECEPTOR LIKE PROTEIN 12, RLP12, Toll-like receptor, leucine rich repeat-containing, was shown to be induced by Candidatus Liberibacter americanus (CaLam) in citrus (Mafra et al., 2013); AT4G31570 that encodes unknown protein responding to As stress (Abercrombie et al., 2008); AT1G15940 that encodes PDS5E, cohesion protein, likely involved in DNA repair (Pradillo et al., 2015); AT2G28290 that encodes CHR3, CHROMATIN REMODELLING COMPLEX SUBUNIT R 3, SPLAYED, SYD, together with LFY regulates shoot

Fig. 2. Real time RT-PCR confirmation of up- and downregulated genes. The bar graphs show fold change in gene expression (with SE) between C. jejuni and PBS groups or C. jejuni and Ct groups in Col-0 (A) and fls2 (B). Vertical lines associated with histogram bars represent standard errors of the means (n = 2). Asterisks show significant difference between treatment and control (both buffer and non-treated) groups (p < 0.05).

apical meristem identity (Wu et al., 2015); AT4G40020 that encodes myosin heavy chain-related protein changed in response to salt stress (Ma et al., 2006); AT5G48570 that encodes FKBP65, ROF2 likely involved in chaperone-assisted protein folding (www.arabidopsis.org). The two downregulated genes in fls2 plants were: AT3G21805 that encodes snoRNA (www.arabidopsis.org); and AT1G02350 that encodes protoporphyrinogen oxidase-related, differentially expressed in heavy metal hyperaccumulator Thlaspi caerulescens (Rigola et al., 2006). Interestingly, just a single protein, RLP12, from the aforementioned proteins has been previously shown to be responsive to pathogen infection (Mafra et al., 2013). To further validate the sequencing data we have chosen a set of five target genes, with criteria for selection being the significance of observed differences (the lowest p-value), the foldchange (the largest) and the fact that these genes were altered in both, Col-0 and fls mutant plants. RT PCR analysis confirmed the expression of these five target genes, with four of these genes overlapping between Col-0 and fls mutant (Fig. 2; Supplementary Table 5). 3.2. DAVID analysis of up- and downregulated groups of genes in Col-0 and fls2 plants in response to C. jejuni DAVID analysis of GO terms enrichment showed that genes upregulated in the Col-0 group (Wt_up) belonged to adenyl nucleotide binding, purine nucleoside binding, and extracellular topological domain GO terms, whereas the downregulated Col-0 group (Wt_down) contained genes belonging to AP2 (APETALA 2), response to hormone stimulus, cell signaling in response to hormones, response to organic substance, ethylene signaling pathway, pathogenesis-related transcriptional factor and ERF as well as DNA-binding region AP2/ERF GO terms, with many of them enriched by in excess of 20 fold (Table 1). In the fls2 mutant, upregulated genes (Mt_up) also belonged to variety of nucleoside and nucleotide binding GO terms, but more importantly, this group had GO terms belonging to Leucine-rich repeat, NB-ARC, programmed cell death, apoptosis, innate immune response, chromatin remodelling, chromatin organization and SNF2-related; in fact, ATP262

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Table 1 David analysis of genes up- and downregulated in Col-0 and fls2 plants. Term Wt_Up topological domain: Extracellular adenyl nucleotide binding purine nucleoside binding Wt_Down Ethylene signaling pathway Pathogenesis-related transcriptional factor and ERF DNA-binding region: AP2/ERF AP2 response to ethylene stimulus hormone-mediated signaling cellular response to hormone stimulus response to hormone stimulus response to endogenous stimulus response to organic substance Mt_Up ATP-dependent chromatin remodelling chromatin remodelling complex SNF2-related Leucine-rich repeat 3 NB-ARC domain NB-ARC apoptosis motor protein Zinc finger, PHD-finger Helicase, superfamily 1 and 2, ATP-binding DNA/RNA helicase, C-terminal Toll-Interleukin receptor DEAD-like helicase, N-terminal helicase programmed cell death Spliceosome cell death chromatin modification helicase activity HELICc TIR DEXDc coiled coil calmodulin binding immune response chromatin organization innate immune response chromosome organization Leucine-rich repeat leucine-rich repeat ATPase, AAA+ type, core atp-binding nucleotide phosphate-binding region: ATP topological domain: Cytoplasmic ATP binding adenyl ribonucleotide binding purine nucleoside binding adenyl nucleotide binding purine ribonucleotide binding purine nucleotide binding plasma membrane Mt_Down chloroplast stroma plastid stroma Chloroplast chloroplast part plastid part chloroplast plastid Wt_Mt_Up leucine-rich repeat topological domain: Extracellular repeat: LRR 3 Leucine-rich repeat repeat: LRR 2 repeat: LRR 1 domain: Protein kinase binding site: ATP

Count

%

P-value

Fold enrichment

Bonferroni

9 19 19

12.86 27.14 27.14

1.45E-05 9.30E-06 9.30E-06

7.17E + 00 2.93E + 00 2.93E+ 00

1.71E-03 1.03E-03 1.03E-03

7 7 7 7 7 8 8 12 12 12

16.67 16.67 16.67 16.67 16.67 19.05 19.05 28.57 28.57 28.57

1.17E-07 1.25E-07 1.61E-07 1.17E-07 9.48E-06 1.71E-05 1.71E-05 6.29E-07 1.26E-06 7.89E-06

2.92E 2.84E 2.46E 2.44E 1.32E 8.94E 8.94E 6.37E 5.94E 4.93E

+ + + + + + + + + +

01 01 01 01 01 00 00 00 00 00

7.04E-06 9.41E-06 9.82E-06 1.17E-06 1.32E-03 2.38E-03 2.38E-03 8.74E-05 1.75E-04 1.10E-03

4 5 10 15 8 23 25 9 9 17 17 15 17 13 26 9 27 14 18 17 15 17 32 15 23 17 21 18 27 30 18 79 32 24 107 108 111 111 112 115 60

0.93 1.17 2.33 3.50 1.86 5.36 5.83 2.10 2.10 3.96 3.96 3.50 3.96 3.03 6.06 2.10 6.29 3.26 4.20 3.96 3.50 3.96 7.46 3.50 5.36 3.96 4.90 4.20 6.29 6.99 4.20 18.41 7.46 5.59 24.94 25.17 25.87 25.87 26.11 26.81 13.99

2.12E-05 2.54E-05 6.83E-09 8.19E-11 1.67E-05 7.20E-15 3.33E-15 1.89E-05 2.20E-05 1.18E-09 1.46E-09 1.83E-08 2.45E-09 4.90E-07 1.48E-13 4.37E-05 4.04E-13 8.61E-07 3.28E-08 3.97E-07 2.52E-06 6.44E-07 5.91E-12 5.58E-06 1.04E-08 1.63E-06 8.44E-08 3.16E-06 1.85E-08 3.15E-09 3.31E-05 3.37E-19 1.22E-07 2.92E-05 5.45E-20 3.98E-20 1.65E-19 1.65E-19 8.39E-19 3.03E-18 1.49E-05

5.67E 2.67E 1.63E 1.09E 9.59E 9.19E 8.24E 7.85E 7.65E 7.44E 7.33E 7.30E 7.08E 6.82E 6.61E 6.27E 6.02E 5.79E 5.46E 4.79E 4.77E 4.62E 4.55E 4.55E 4.45E 4.40E 4.33E 3.95E 3.75E 3.73E 3.33E 3.09E 2.83E 2.62E 2.43E 2.42E 2.33E 2.33E 2.27E 2.19E 1.73E

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

01 01 01 01 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00

1.46E-02 2.74E-03 3.78E-06 4.53E-08 6.68E-03 3.99E-12 2.31E-12 3.14E-03 1.21E-02 6.50E-07 8.05E-07 1.01E-05 1.35E-06 8.13E-05 1.02E-10 1.44E-03 2.80E-10 5.97E-04 9.49E-06 4.77E-05 3.02E-04 7.73E-05 9.81E-10 1.61E-03 7.20E-06 1.13E-03 5.85E-05 2.19E-03 1.03E-05 5.23E-07 1.82E-02 5.59E-17 4.89E-05 1.16E-02 1.58E-17 1.15E-17 4.78E-17 4.78E-17 2.42E-16 8.75E-16 1.61E-03

12 12 11 15 15 29 29

15.00 15.00 13.75 18.75 18.75 36.25 36.25

4.45E-07 7.38E-07 3.12E-05 9.94E-06 1.41E-05 2.61E-06 4.03E-06

7.29E 6.93E 4.89E 4.01E 3.89E 2.32E 2.27E

+ + + + + + +

00 00 00 00 00 00 00

3.21E-05 5.32E-05 2.68E-03 7.15E-04 1.02E-03 1.88E-04 2.90E-04

5 5 3 4 3 3 4 4

21.74 21.74 13.04 17.39 13.04 13.04 17.39 17.39

6.34E-04 3.21E-04 2.14E-02 4.91E-03 2.89E-02 2.89E-02 5.15E-03 6.05E-03

1.17E 1.15E 1.13E 1.07E 9.68E 9.68E 9.25E 8.74E

+ + + + + + + +

01 01 01 01 00 00 00 00

263

2.75E-02 1.40E-02 6.14E-01 2.56E-01 7.24E-01 7.24E-01 2.03E-01 2.34E-01 (continued on next page)

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Table 1 (continued) Term

Count

%

P-value

Fold enrichment

Bonferroni

topological domain: Cytoplasmic nucleotide phosphate-binding region: ATP active site: Proton acceptor serine/threonine-protein kinase kinase atp-binding purine nucleoside binding adenyl nucleotide binding adenyl ribonucleotide binding purine ribonucleotide binding ATP binding nucleotide binding

5 6 4 4 4 7 11 11 9 9 8 11

21.74 26.09 17.39 17.39 17.39 30.43 47.83 47.83 39.13 39.13 34.78 47.83

1.36E-03 2.21E-04 1.02E-02 1.50E-02 3.49E-02 1.28E-03 1.06E-05 1.06E-05 5.11E-04 1.04E-03 2.99E-03 1.33E-04

7.89E 7.66E 7.23E 7.21E 5.21E 5.16E 4.29E 4.29E 3.75E 3.39E 3.37E 3.26E

5.81E-02 9.66E-03 3.64E-01 4.85E-01 7.91E-01 5.47E-02 6.05E-04 6.05E-04 2.87E-02 5.74E-02 1.57E-01 7.57E-03

+ + + + + + + + + + + +

00 00 00 00 00 00 00 00 00 00 00 00

“Count” shows the number of gene in the specific GO term, “%” shows percentage of genes belonging to the GO term out of all genes in the specific group (Wt_Up, for example), PValue and Bonferroni correction – statistical treatment, “Fold Enrichment” – fold enrichment, calculated by dividing the ratio of number of genes in the GO term category to all genes found in the group by the ratio of number of genes in the GO term to all genes in the genome.

FAMILY 79, SUBFAMILY B, POLYPEPTIDE 2", CYP79B2 (AT4G39950), involved in camalexin biosynthetic process and various defence responses. In several plant species RLPs (like RLP31 mentioned above) have been found to play a role in disease resistance, such as the tomato Cf and Ve proteins (Wang et al., 2008). Arabidopsis plants inoculated with the incompatible fungal pathogen Alternaria brassicicola exhibited over four-fold increase in the expression of AT1G33600 encoding putative LRR protein (Schenk et al., 2003). Arabinogalactan-proteins (AGPs) are cell wall proteoglycans and are widely distributed in the plant kingdom. Classical AGPs and some non-classical AGPs are predicted to have a glycosylphosphatidylinositol lipid anchor, and they have been suggested to be involved in cell-cell signaling (Guan and Nothnagel, 2004). Yariv phenylglycoside is a synthetic probe that specifically binds to plant AGPs and has been used to study AGP functions. Treatment of Arabidopsis cell suspension culture with Yariv phenylglycoside leads to changes in the expression of AT4G20860 (Guan and Nothnagel, 2004).

dependent chromatin remodelling GO term was enriched by in excess of 50 fold. In the fls2 downregulated category (Mt_down), GO terms plastid stroma and chloroplast stroma were enriched. The genes that were commonly upregulated in Col-0 and fls2 plants belonged to GO terms purine and adenyl nucleotide binding, ATP binding, kinase, and leucine-rich repeats (Table 1). Overlap for commonly downregulated group was too small for proper David analysis. It is noteworthy that in the Col-0 plants, C. jejuni downregulated genes involved in hormonal response and pathogenesis-related transcription. Flg22 is known to activate ethylene biosynthesis as an early response (Mersmann et al., 2010). In addition, it was shown that flg22induced ROS accumulation was completely abolished in ethylene insensitive mutant ein2 (Mersmann et al., 2010). Also, FLS2 accumulation was reduced in ein2, indicating a requirement of ethylene signaling for FLS2 expression (Mersmann et al., 2010). As C. jejuni suppressed the ethylene signaling pathway in Col-0 plants but not in the fls2 mutant may suggest that the bacterium is able to suppress ethylene activation working through FLS receptor. Another important result is that in the absence of FLS2, C. jejuni activated a battery of pathogen response and pro-survival pathways, including Leucine-rich repeat, NB-ARC, programmed cell death, apoptosis, innate immune response, chromatin remodelling, chromatin organization and SNF2-related. Upregulation of chromatin remodelling and organization pathway may be one of the reasons why there are so many more genes upregulated in the mutant as compared to the wild type. Previous studies with fls2 mutant showed that the mutant plants are as susceptible as the wild type to the infection with Pseudomonas syringae pv. tomato DC3000 when bacterial cells infiltrate the leaves, but more sensitive when the bacterium is sprayed directly onto the leaf surface (Zipfel et al., 2004). Our findings show that it is highly likely that FLS2 plays at least a partial role in response to C. jejuni recognition, and when the receptor is inactive, the response to pathogen is massive and at many levels.

3.4. David analysis of genes overlapping between E. coli and C. jejuni GO terms analysis of genes that overlapped between two bacterial treatments showed that in “Wt_Up” groups, commonly regulated genes belonged to categories: “response to bacteria”, “leucine-rich repeat”, “leucine-rich repeat-containing N terminal type 2″ and “plant type cell wall”. These genes were enriched in excess of 20-fold. As well, “signal” and “redox process” genes were enriched but to a lesser degree (< tenfold) (Table 2). The “Wt_down” group contained only two genes, which belonged to enriched GO term “response to abscisic acid”; they were enriched by 26-fold. In the mutant, “Mt_Up” group, commonly regulated genes belonged to enriched GO terms “response to heat”, response to high light intensity”, “response to hydrogen peroxide”, “response to endoplasmatic reticulum stress” and “heat acclimation”, all enriched by in excess of 50-fold (Table 2). Overlap between downregulated groups of genes in response to E. coli and C. jejuni consisted of a single gene; thus, David analysis could not be done. The difference between Col-0 and fls2 responses to these two bacterial pathogens suggests that Col-0 plants respond to animal bacteria in a conventional way, likely through activation of FLS2 receptor and activation of various defence pathways. Moreover, it appears that fls2 plants respond to C. jejuni and E. coli by activating several components of abiotic stress pathway. Responses to abiotic and biotic stresses are known to overlap, and it is highly likely that specificity of response to C. jejuni or E. coli is removed when FLS2 receptor is mutated.

3.3. Genes that overlapped between Col-0 and fls2 plants in response to C. jejuni and E. coli O157:H7 As shown above, there were only eight genes overlapping between wt_up C. jejuni and wt_up E. coli group. Among them were: receptor like protein 31 (RLP31), involved in defence response (AT3G05370); WAKL4, WALL ASSOCIATED KINASE-LIKE 4, belonging to the receptorlike kinase (RLK) superfamily (AT1G16150); Leucine-rich repeat (LRR) family proteins (AT1G33600 and AT2G15042); pleckstrin homology (PH) domain-containing protein (AT4G17140); ATBBE22, FAD-binding Berberine family protein (AT4G20860); Cysteine/Histidine-rich C1 domain family protein, induced by exposure to various pathogens, including Pseudomonas, Agrobacterium tumefaciens and pathogenic E. coli (Ditt et al., 2006; Thilmony et al., 2006); and CYTOCHROME P450,

3.5. Motif analysis of up- and downregulated genes Stress signaling in plants, and especially signaling in response to 264

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Table 2 David analysis of genes up- and downregulated in Col-0 and fls2 plants commonly regulated in response to E. coli and C. jejuni. Term

Count

%

P-value

Genes

WTe_WTc_up IPR001611: Leucine-rich repeat GO:0005886 ~ plasma membrane

3 5

37.5 62.5

0.005 0.009

2 4 2 3 2

25 50 25 37.5 25

0.048 0.057 0.058 0.061 0.065

AT3G05370, AT3G05370, AT2G15042 AT4G20860, AT4G20860, AT1G33600, AT4G20860, AT3G05370,

2

25

0.075

2

50

3 3 3 3 2 2

75 75 75 75 50 50

GO:0006865~amino acid transport Signal GO:0009617 ~ response to bacterium GO:0055114 ~ oxidation-reduction process IPR013210: Leucine-rich repeat-containing N-terminal, type 2 GO:0009505 ~ plant-type cell wall WTe_WTc_down GO:0009737 ~ response to abscisic acid MTe_MTc_up GO:0042542 ~ response to hydrogen peroxide GO:0009644 ~ response to high light intensity GO:0009408 ~ response to heat GO:0006457 ~ protein folding GO:0010286 ~ heat acclimation GO:0034976 ~ response to endoplasmic reticulum stress

Fold enrichment

Bonferroni

AT1G33600, AT2G15042 AT1G16150, AT1G33600, AT4G17140,

24.09 4.57

0.12 0.11

AT2G44370 AT3G05370, AT1G16150, AT1G33600 AT4G39950 AT2G44370, AT4G39950 AT1G33600

35.13 3.69 28.95 6.12 26.24

0.88 0.71 0.93 0.94 0.84

AT1G16150, AT1G33600

22.47

0.67

0.049

AT1G73480, AT5G14920

26.73

0.48

0.0003 0.0004 0.0005 0.0010 0.014 0.029

AT3G08970, AT3G08970, AT3G08970, AT3G08970, AT3G28210, AT5G55920,

70.93 65.24 55.33 40.33 108.48 50.94

0.01 0.01 0.02 0.03 0.33 0.58

AT5G55920, AT5G55920, AT5G55920, AT5G55920, AT3G08970 AT5G12020

AT5G12020 AT5G12020 AT5G12020 AT5G12020

“Count” shows the number of genes in the specific GO term, “%” shows percentage of genes belonging to the GO term out of all genes in the specific group (Wt_Up, for example), PValue (< 0.05), Bonferroni correction – statistical treatments of the data (Huang da et al., 2008), “Fold Enrichment” – fold enrichment, calculated by dividing the ratio of number of genes in the GO term category to all genes found in the group by the ratio of number of genes in the GO term to all genes in the genome.

E. coli regulated genes showed that in upregulated group, weak to moderate correlation was found in any cross-comparison except comparison between Col-0 plants in response to C. jejuni and fls2 plants in response to E. coli group, where strong correlation was found between motif1 in fls2 plants in response to E. coli and several motifs in fls2 plants in response to E. coli group; similarly high degree correlation was found between motifs 1, 6, 9 and 13 of Col-0 plants in response to C. jejuni group and motifs 1, 2 and 3 of fls2 plants in response to E. coli (Supplementary Table 8). Similar correlation analysis performed for downregulated genes showed a strong correlation in all cross-comparison groups. Strong correlation was found between motifs 1, 2, 4, 8, 9, 12, 13 and 14 found in Col-0 plants in response to C. jejuni and motifs 1, 2, 3, 4 and 5 of Col-0 plants in response to E. coli group (Supplementary Table 9). Similar correlation for fls2 groups showed high degree of correlation between motifs 2, 6, 8, 9, 10, 11 and 14 of in fls2 plants in response to C. jejuni and motifs of fls2 plants in response to E. coli (Supplementary Table 10). This analysis suggests that downregulation of expression of common set of genes may occur through transcription factors and other trans regulating proteins that bind to common motifs in the promoter regions.

pathogens involves activation of many common response pathways, resulting in upregulation or downregulation of clusters of common genes (Huang et al., 2012; Pandey et al., 2015). Those are largely driven by the presence or absence of specific PRRs. Therefore, we have analyzed whether commonly regulated genes in Col-0 and fls2 mutant have similar response elements in their promoters in response to bacteria. Analysis of promoters of commonly regulated genes showed that in genes up-regulated in the Col-0 plants there were 15 common motifs identified that were similar to CCA1 and variants, AG and variants, CArG1, CArG3, Bellringer_replumless_pennywise, EveningElement, AGL2 and AGL3 (Supplementary Table 6; Fig. 3). Motifs AG and variants and CArG3 motif were also found in upregulated genes in Col-0 plants in response to E. coli (Golubov et al., 2016). In the down-regulated genes in Col-0 plants in response to C. jejuni there were 15 common motifs that were similar to those found in upregulated genes. However, ABRE, ABRE-like, T-box, G-box and W-box motifs were not found in upregulated genes in Col-0 plants. Comparison to E. coli downregulated genes in Col-0 plants again showed similarity in AG and variants, CCA1 and variants and CArG1, CArG3 motifs (Golubov et al., 2016); Motif1 was an identical motif enriched in response to E. coli and C. jejuni, and was similar to CCA1_v3, AG_v4, CArG3 and CArG1 motifs. In the up-regulated genes in mutant plants in response to C. jejuni, only three motifs were found and they were similar to CArG1, ARF/ ARF1, MYB/MYB4, EIL1/EIL2 and T-box motifs. In E. coli this group had quite different motifs, with only one common motif found (i.e. CArG1). In the down-regulated genes in mutant plants in response to C. jejuni, 13 common motifs were found with similarity to CCA1, CCA1_v3, CArG1, CArG3, AG variants, AGL2/AGL3, ABRE and ABRE-like. Comparison to the same treatment group in E. coli showed that most of these motifs were also common in this group (Golubov et al., 2016). Correlation analysis between motifs found among commonly upregulated genes in Col-0 and fls2 groups showed weak (r < 0.5) to moderate (0.5 < r < 0.75) correlation, whereas similar correlation in downregulated genes showed strong (r > 0.75) correlation between motifs 1, 2, 4, 8, 9, 12 and 13 of Col-0 group and motifs 2, 6, 8, 10, 11 and 14 of fls2 group (Supplementary Table 7). Correlation analysis between motifs in C. jejuni regulated genes and

4. Conclusion Our work demonstrates that Arabidopsis plants possess versatile mechanisms of recognition of animal enteric pathogens, employing a FLS2-dependent and -independent response. Findings indicate that Col0 plants with functional FLS2 are able to mount a “focused” response, primarily activating resistance gene-dependent pathways; whereas, fls2 plants, in which FLS2 is inactive, utilize a broader battery of responses, likely dependent on multiple receptors and kinases, regulating overlapping abiotic and biotic response pathways. Analysis of GO terms for commonly regulated genes between the two pathogens showed more similarity for Col-0 than for fls2 plants, further indicating importance of FLS2 receptor for a quick response to animal pathogens.

Conflict of interest The research was conducted in the absence of any commercial or financial relationships. We declare no conflict of interest. 265

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