Transcriptome Analysis of the Phytobacterium Xylella fastidiosa Growing under Xylem-Based Chemical Conditions

Abstract

Xylella fastidiosa is a xylem-limited bacterium responsible for important plant diseases, like citrus-variegated chlorosis (CVC) and grapevine Pierce's disease (PD). Interestingly, in vitro growth of X. fastidiosa in chemically defined media that resemble xylem fluid has been achieved, allowing studies of metabolic processes used by xylem-dwelling bacteria to thrive in such nutrient-poor conditions. Thus, we performed microarray hybridizations to compare transcriptomes of X. fastidiosa cells grown in 3G10-R, a medium that resembles grape sap, and in Periwinkle Wilt (PW), the complex medium traditionally used to cultivate X. fastidiosa. We identified 299 transcripts modulated in response to growth in these media. Some 3G10R-overexpressed genes have been shown to be upregulated in cells directly isolated from infected plants and may be involved in plant colonization, virulence and environmental competition. In contrast, cells cultivated in PW show a metabolic switch associated with increased aerobic respiration and enhanced bacterial growth rates.

1. Introduction

The phytobacterium Xylella fastidiosa was described by Wells et al. [1] and has been found to be associated with the development of a wide variety of plant diseases, such as Citrus-Variegated Chlorosis (CVC) in orange trees, Pierce's disease (PD) in vineyards, Phony Peach disease (PP), Periwinkle Wilt and leaf scorch diseases in plum, elm, maple, pecan, oak, sycamore, and coffee ([2, 3], reviewed in [4]). Due to the presence of economically important crops in this list, X. fastidiosa has been the subject of intensive research over the past years [5, 6] and the genome sequencing of four different strains has been accomplished: the 9a5c isolate (causative agent of CVC) was the first phytopathogenic bacterium completely sequenced in 2000 [7]. A few years later, two strains isolated from oleander and almond trees had their genomes partially sequenced and annotated [8]. Finally, a fourth strain, Temecula 1, isolated from grapevines and responsible for PD in California has also been sequenced to completion [9].

The elucidation of the complete genomic sequence of X. fastidiosa strains was followed by an extensive in silico evaluation of the bacterium's presumed proteome, allowing the formulation of a virtual metabolome that provided a comprehensive view of the major biochemical processes that occur in this microorganism [7]. Nonetheless, the exact mechanism(s) involved in the process of host infection and colonization, as well as with the onset of CVC, are yet to be identified and characterized in the X. fastidiosa genome [7]. Important information regarding the functionality of different gene products and pathogenicity mechanisms in X. fastidiosa could be obtained through the evaluation of differential gene expression using cells submitted to variable culturing conditions, especially those that resemble the environment found inside the plant. Xylem-inhabiting microorganisms normally display a fastidious nature and cannot be cultured in conventional bacteriological media. Thus, a series of specially formulated media were developed for their axenic cultivation. The most widely employed, such as PD2 [10], PW [11], SPW [12], PYE, GYE [13] and BCYE [14], are complex media, which include peptone, tryptone, soytone, and yeast extract from various sources, as well as hemin chloride or ferric pyrophosphate (as iron sources), aminoacids, inorganic salts, citrate, succinate, starch, BSA, or activated charcoal. However, given the general characteristics of plant sap, xylem-dwelling endophytes are likely to thrive in nutrient-limiting conditions and must be able to adapt accordingly [15]. A few years ago, Leite et al. [16] have described the development of a xylem-based, chemically defined medium (called 3G10R), which supports in vitro growth of X. fastidiosa strains. Moreover, X. fastidiosa cells grown in this medium present some important characteristics that may be associated with colonization and pathogenicity, such as increased aggregation capacity and biofilm formation. This medium provided a new tool that may allow the in vitro study of some important characteristics presented by the bacteria during the infection process in planta.

Thus, we have employed competitive hybridizations on microarrays to evaluate the global transcriptional profile of X. fastidiosa cells grown in 3G10R, when compared to cells grown in PW, the standard complex medium used to cultivate this bacterium under laboratory conditions. These experiments allowed the identification of 299 genes that displayed statistically significant transcription modulation in response to growth in the two media. Some 3G10R-upregulated genes had their expression profiles confirmed by Real-Time qPCR and are likely to be relevant to bacterial adaptation to the plant xylem, such as adhesion to the substrate and competition with other microorganisms. Incidentally, independent studies have confirmed the specific upregulation of some of these genes in X. fastidiosa cells that display increased infective capacity and in bacteria directly isolated from plants, reinforcing the idea that the chemical characteristics of 3G10R are likely to induce genes that are naturally expressed by X. fastidiosa during the process of xylem colonization [17]. Other transcriptional alterations seem to correlate with significant changes in the cell's overall energetic metabolism and growth rate, as a reduction in the respiratory activity is observed when cells are grown in 3G10R.

2. Materials and Methods

2.1. Culturing X.  fastidiosa Cells

PW and 3G10R liquid media have been prepared essentially as described by Davis et al. [11] and Leite et al. [16], respectively. Cells of X. fastidiosa 9a5c have been routinely kept in our laboratory, for over a year, in 20 ml of liquid cultures, which were incubated in an orbital shaker at 28°C and 100 rpm. One-milliliter (1 ml) aliquots were transferred to 19 ml of fresh media every 4-5 days.

To evaluate the behavior of X. fastidiosa cells under xylem-based chemistry conditions, bacterial cultures were grown in PW for 3 days, until an OD₆₀₀ = 0.25 (late phase of exponential growth) was reached. A one milliliter-aliquot (1 ml) of this culture was used to inoculate 19 ml of liquid 3G10R and PW media. Bacterial growth in both cultures was monitored on a daily basis, through OD₆₀₀ measurements, providing a direct comparison between X. fastidiosa growth patterns observed in 3G10R and standard PW medium.

2.2. Microarray Fabrication

X. fastidiosa microarrays have been constructed as previously described [18, 19]. Representative sequences from approximately 2200 ORFs from the X. fastidiosa genome (>90% coverage) were PCR amplified, purified, and spotted onto CMT-GAPS silane-coated slides (Corning), using an Affymetrix 427 arrayer, according to the manufacturer's instructions.

2.3. RNA Extraction, cDNA Labeling, and Hybridization

To evaluate and compare the bacterial transcriptome profiles in these two media, 200-ml bacterial cultures were prepared as described above and cells were harvested for total RNA extraction at day 3 (PW) and day 13 (3G10R), which allowed us to compare bacterial cultures at their maximum growth rates. The RNA samples were extracted and purified with aid of the RNAeasy kit (Qiagen), labeled by incorporation of Cy3- or Cy5-dCTP and hybridized to the microarrays, as previously described [18, 19].

2.4. Image Acquisition and Analysis

Images were analyzed with the TIGR Spotfinder program (v.2.2.4). All spots with median values lower than the median local background plus two Standard Deviations have been flagged and excluded from further analyses. Replicated experiments were performed with two independent RNA preparations from cells cultivated in each medium. For each pair of RNA preparations, two independent hybridizations were performed, with dye swaps within each pair. Since each microarray carries two complete copies of the X. fastidiosa genome, replicated hybridizations resulted in a series of 8 independent readings for each probe spotted in the microarrays.

The results from each hybridization were submitted to a series of mathematical transformations with the aid of the software TIGR MIDAS v.2.19. These included filtering out all spots whose integrated intensities were below 10,000 a/d units, normalization between the two channels with the aid of the Lowess algorithm and SD regularization of the Cy5/Cy3 ratios across all sectors (blocks) of the array. Finally, the results from each individual experiment were loaded into the software TIGR Multi-Experiment Viewer (TMEV), v.3.01. Experiments were then normalized and genes that displayed statistically significant modulation were identified with the aid of the one-class mode of the Significance Analysis of Microarrays (SAMs) test, described by Tusher et al. [20]. The δ factor of the SAM test was adjusted to 0.69, resulting in a Median False Discovery Rate (FDR) = 0.163. For details regarding the use of the TIGR microarray software suite (TM4), see Saeed et al. [21]. Raw and normalized data from all microarray hybridizations, as well as the microarray complete annotation file have been submitted to NCBI's Gene Expression Omnibus (GEO) and can be accessed through Series number GSE 6619. A Tab-delimited file containing the Significant Genes List and their mean expression ratios can also be accessed through this GEO Series number.

2.5. Real-Time qPCR

All the Real-Time qPCR and RT-PCR reactions were performed using an ABI Prism 7500 Sequence Detection System (Applied Biosystem, USA). Taq-Man EZ RT-PCR kits (Applied Biosystems, USA) were used for RT-PCR reactions, according to the manufacturer's instructions, using 2–5 μg of total X. fastidiosa RNA and 1 μl of random nonamers (4 μg/μl). The thermocycling conditions comprised an initial step at 50°C for 2 minutes, followed by 30 minutes at 60°C for reverse transcription. Taq-Man PCR Reagent kits then were used for PCR reactions using 100–200 ng of the resulting cDNA. The thermocycling conditions comprised an initial step at 50°C for 2 minutes, followed by 10 minutes at 95°C, and 40 cycles at 95°C for 15 seconds and 60°C for 1 minute. ORF Xf1311, which encodes a rod-shaped determining protein (MreD) has been used as an endogenous control for experimental normalization, since the microarray hybridization experiments showed that this ORF is constitutively expressed in both PW and 3G10R. Primers and probes were synthesized through the Applied Biosystems Assay-by-Design service and all reactions were prepared essentially as recommended by the manufacturer.

2.6. Evaluation of Respiratory Rates

X. fastidiosa cells were grown into middle exponential phase in PW and subsequently transferred (in a 1 : 20 proportion) into fresh PW and 3G10R cultures. Bacterial growth in both cultures was monitored through OD₆₀₀ measurements until both cultures reached stationary phase. Aliquots were taken from each culture to evaluate O₂ consumption on a daily basis, until day 7 (in PW) and day 13 (in 3G10R). We defined the respiratory rate for each culture as the ratio between O₂ consumption rate (ΔO₂/Δmin) and the respective OD₆₀₀ value obtained at each time point.

Oxymetric measurements were monitored polarographically by an oxygraph equipped with a Clark-type oxygen electrode (Gilson Medical Electronics, Middleton, WI, USA) in intact cells. After measurement of the optical density, 2.0 ml of PW or 3G10R media containing bacteria were incubated at 30°C and the state 4 respiration was initiated by addition of 10 mM malate plus 10 mM glutamate. Basal respiratory rates were calculated by ΔO₂/Δmin ratio and the values were normalized by the optical density values.

3. Results

3.1. X. fastidiosa Cells Growing in PW and 3G10R Display Distinct Growth Patterns and Different Transcriptome Profiles

To evaluate the behavior of X. fastidiosa cells under xylem-based chemistry conditions, bacterial cultures were monitored in both 3G10R and PW, the complex medium traditionally used to cultivate this bacterium in the laboratory. As observed in Figure 1, PW cultures reached higher cellular densities (OD₆₀₀ ~ 0.3) in a shorter period of time (4 days) when compared to cells grown in 3G10R, which had to be cultivated for a period of 14 days in order to reach a similar cellular density (OD₆₀₀ ~ 0.25). Moreover, although 3G10R cultures exhibited continuous growth over the course of the experiment, they failed to display the typical profile of a bacterial growth curve, as observed in PW cultures. Such lack of an exponential growth phase in 3G10R cultures is typically observed in bacteria growing in nutrient-restricted environments, a situation that is likely to resemble xylem conditions [22–26]. Recently, Zaini et al. [27] showed that X. fastidiosa cells grown in pure xylem sap rapidly reach stationary phase without a detectable exponential growth, probably due to nutrient limitation.

Figure 1.

Xylella fastidiosa growth patterns in PW and 3G10R media. Both cultures have been made with a 1 : 20 ml inoculum of X. fastidiosa 9a5c cells grown into late exponential phase in PW (OD₆₀₀ = 0.25). Cultures were then incubated in an orbital shaker at 28°C and 100 rpm. One milliliter (1 ml) aliquots were taken from each culture, on a daily basis, to monitor bacterial growth through OD₆₀₀ readings. Measurements were performed in triplicate and graphic shows the average values and their respective standard deviations.

To evaluate and compare the bacterial transcriptome profiles in PW and 3G10R, samples from the resulting RNAs were used in competitive hybridizations against X. fastidiosa microarrays, as described by Nunes et al. [19]. Replicated experiments were performed with two independent RNA preparations from cells cultivated in each medium, which resulted in a series of 8 independent readings for each probe spotted in the microarrays, as described in the materials and methods. Statistical analysis of such results revealed a total of 132 genes that displayed overexpression in cells grown in 3G10R, while 167 genes were upregulated in cells grown in PW. These genes, as well as their respective changes in expression ratio are shown in Table 1. More detailed information about these genes can be obtained through the Gene expression Omnibus (GEO) webpage, through Series number GSE 6619 (see http://ncbi.nlm.nih.gov/geo). In order to access the overall reliability of these data, we have confirmed gene expression variation of several genes using an alternative approach. Thus, we performed Real-Time qPCR experiments with the same RNA samples used in the microarray hybridizations, aiming at double-checking the changes in expression of 16 genes present in Table 1 (~5% of all modulated genes). These genes have been randomly chosen from different functional categories and all displayed average expression ratios that correlate with the microarray results (see Figure 2).

Table 1.

List of genes that displayed statistically significant variation in gene expression. Genes with positive Log₂ ratio are overexpressed in 3G10R, while genes with negative Log₂ ratio are overexpressed in PW.

Functional Group	ORF	Gene	Gene Product	Log2
	Number	Name		(3G10R/PW)
Intermediary Metabolism
Energy metabolism, carbon—Aerobic respiration	Xf0308	nuoD	NADH-ubiquinone oxidoreductase, NQO4 subunit	−0.93
	Xf0310	nuoF	NADH-ubiquinone oxidoreductase, NQO1 subunit	−1.08
	Xf0311	nuoG	NADH-ubiquinone oxidoreductase, NQO3 subunit	−1.14
	Xf0317	nuoM	NADH-ubiquinone oxidoreductase, NQO13 subunit	−1.03
	Xf0347	dld1	D-Lactate dehydrogenase	1.18
Energy metabolism, carbon—Glycolysis	Xf0303	tpiA OR tpi	Triosephosphate isomerase	−0.89
Energy metabolism, carbon—TCA cycle	Xf2548	sucD	Succinyl-CoA synthetase, alpha subunit	−1.67
	Xf1554	fumC	Fumarate hydratase	−1.47
	Xf1554	fumC	Fumarate hydratase	−1.36
Energy metabolism, carbon—Electron Transport	Xf1990	yneN	Thioredoxin	−1.14
	Xf0620	dsbD	c-Type cytochrome biogenesis protein (Copper Tolerance)	−0.83
Degradation—Degradation of Small Molecules	Xf1250	rocF	Arginine deaminase	−2.00
	Xf1740	yliI	Glucose dehydrogenase B	1.45
	Xf2395	axeA	Acetylxylan esterase	1.75
	Xf2432	gtaB	UTP-glucose-1-phosphate uridylyl transferase	−1.14
	Xf0610	galE	UDP-glucose 4-epimerase	−1.44
	Xf2210		Dioxygenase	1.00
Regulatory Functions	Xf1354	yybA	Transcriptional regulator (MARR Family)	1.27
	Xf1354	yybA	Transcriptional regulator (MARR Family)	1.55
	Xf1254	araL	Transcriptional regulator (ARAC Family)	−1.10
	Xf2344	fur	Transcriptional regulator (FUR Family)	1.19
	Xf2336	colR	Two-component system regulatory protein	1.32
	Xf2534	colR	Two-component system regulatory protein	−0.95
	Xf1752		Transcriptional regulator (LYSR Family)	1.64
	Xf1733	AF0343	Tryptophan repressor binding protein	1.13
	Xf1749	opdE	Transcriptional regulator	1.65
	Xf1730	yafC	Transcriptional regulator (LYSR Family)	1.97
Sugar-Nucleotide Biosynthesis, Conversions	Xf0260	xanA	Phosphoglucomutase/ Phosphomannomutase	0.92
Central Intermediary Metabolism—Pool, Multipourpose Conversions	Xf0880	yadF	Carbonic anhydrase	−1.30
	Xf2255	acs	Acetyl coenzyme A synthetase	−1.37
Central Intermediary Metabolism—Amino Sugars	Xf2355		Exo II n-acetyl-beta-glucosaminidase	1.44
Biosynthesis of Small Molecules
Amino Acids Biosynthesis—Aspartate family, pyruvate family	Xf2272	metE	5-methyltetrahydro pteroyltriglutamate–homocysteine methyltransferase	1.44
	Xf1121	metF OR AQ_1429	5,10-methylene tetrahydrofolate reductase	0.92
	Xf2223	thrC	Threonine synthase	1.00
	Xf0863	met2	Homoserine O-acetyltransferase	1.25
Amino Acids Biosynthesis—Aromatic Amino Acid Family	Xf0624	aroE	Shikimate 5-dehydrogenase	1.64
Nucleotides Biosynthesis—Salvage of Nucleosides and Nucleotides	Xf2150	apaH	Diadenosine tetraphosphatase	1.14
	Xf2354	hpt	Hypoxanthine-guanine phosphoribosyl transferase	1.08
Nucleotides Biosynthesis – 2′ Deoxyribonucleotides	Xf0580	PH1695	Thymidylate kinase	−0.93
	Xf1196	nrdA OR TP1008	Ribonucleoside-diphosphate reductase alpha chain	1.10
Nucleotides Biosynthesis—Purine Ribonucleotides	Xf1503	gmk OR spoR	Guanylate kinase	0.86
Nucleotides Biosynthesis—Pyrimidine Ribonucleotides	Xf1107	carB OR pyrA	Carbamoyl-phosphate synthase large chain	−0.99
	Xf1106	carA	Carbamoyl-phosphate synthase small chain	−0.96
Cofactors, Prosthetic Groups, Carriers Biosynthesis—Menaquinone, Ubiquinone	Xf1487	ubiE	Ubiquinone menaquinone transferase	−1.64
Cofactors, Prosthetic Groups, Carriers Biosynthesis—Pantothenate	Xf0229	panB	3-Methyl-2-oxobutanoate hydroxy methyltransferase	−1.50
Cofactors, Prosthetic Groups, Carriers Biosynthesis—Thiamin	Xf0783	thiG	Thiamine biosynthesis protein	−0.87
Cofactors, Prosthetic Groups, Carriers Biosynthesis—Riboflavin	Xf1748	MJ0671	5-amino-6-(5-phospho ribosylamino) uracil reductase	1.05
Cofactors, Prosthetic Groups, Carriers Biosynthesis—Biotin	Xf2477	bioD	Dethiobiotin synthetase	1.08
Cofactors, Prosthetic Groups, Carriers Biosynthesis—Others	Xf1916	AF1671	Coenzime F390 synthetase	1.21
Fatty Acid and Phosphatidic Acid Biosynthesis	Xf2269	DRB0080	3-alpha-hydroxysteroid dehydrogenase	−0.93
	Xf0572	fabA	Beta-hydroxydecanoyl-ACP dehydratase	1.18
Macromolecule Metabolism
DNA metabolism—Replication	Xf0001	dnaA	Chromosomal replication initiator	−1.02
	Xf0002	dnaN	DNA polymerase III, beta chain	−1.39
	Xf0002	dnaN	DNA polymerase III, beta chain	−1.15
	Xfa0003	topA OR supX	Topoisomerase I	−1.60
	Xf1353	parC	Topoisomerase subunit	0.98
DNA metabolism—Recombination	Xf0425	recD	Exodeoxyribonuclease V alpha chain	−0.96
	Xf0425	recD	Exodeoxyribonuclease V alpha chain	−1.02
	Xf0423	ecb OR rorA	Exodeoxyribonuclease V beta chain	1.30
DNA metabolism—Repair	Xf1902	ruvB OR HL0312	Holliday junction binding protein, DNA helicase	−1.20
	Xf2692	ung	Uracil-DNA glycosylase	−1.18
DNA Metabolism—Restriction, Modification	Xf0935	LLAIIA	Methyltransferase	−0.83
	Xf1804	SPHIM	Site-specific DNA-methyltransferase	1.12
	Xf1774	hpaIIM	DNA methyltransferase	−0.81
DNA Metabolism—Structural DNA Binding Proteins	Xf0446	bbh3	DNA-binding protein	−1.19
	Xf1644	ssb	Single-stranded DNA binding protein	1.05
RNA Metabolism—Ribosomes—Maturation and Modification	Xf0441	rimI	Ribosomal-protein-alanine acetyl transferase	1.87
	Xf0939	rluD OR sfhB	Ridosomal large subunit pseudoeridine synthase D	−1.02
RNA Metabolism—Ribosomal Proteins	Xf1164	rplE OR rpl5 OR HI0790	50S ribosomal protein L5	−0.91
	Xf0238	rpsO OR secC	30S ribosomal protein S15	−1.23
	Xf1166	rpsH OR rps8 OR HI0792	30S ribosomal protein S8	−1.4
	Xf1169	rpsE OR spc	30S ribosomal protein S5	−1.14
RNA Metabolism—RNA Synthesis, Modification, DNA Transcription	Xf1108	greA	Transcriptional elongation factor	−1.73
	Xf0227	pcnB	Polynucleotide adenyltransferase	−1.31
	Xf2632	rpoC OR tabB	RNA polymerase beta subunit	1.09
	Xf2606	rluC	Pseudourylate synthase	−1.08
RNA Metabolism—Aminoacyl tRNA Synthetases, tRNA Modification	Xf0428	TM0492	Tryptophanyl-tRNA synthetase	−1.89
	Xf0445	proS OR drpA	Prolyl-tRNA synthetase	−1.08
	Xf0134	valS OR HI1391	Valyl-tRNA synthetase	−0.96
	Xf0169	tyrS OR HI1610	Tyrosyl-tRNA synthetase	1.93
	Xf1314	queA	S-Adenosylmethionine tRNA ribosyltransferase-isomerase	−1.00
	Xf0736	thrS	Threonyl-tRNA synthetase	−1.08
RNA Metabolism—RNA Degradation	Xf1505	rph	Ribonuclease PH	−0.74
	Xf1041	rnhB	Ribonuclease HII	−1.00
	Xf2615	rnaSA3	Ribonuclease	1.00
Protein Metabolism—Translation and Modification	Xf0644	mip	Peptidyl-propyl cis-trans isomerase	−1.11
	Xf2629	fusA	Elongation factor G	−0.90
Protein Metabolism—Protein Degradation	Xf0220	pepQ	Proline dipeptidase	−1.13
	Xf0453	hflC OR HI0150	Integral membrane proteinase	1.65
	Xf2241	mucD	Periplasmic protease	−0.87
	Xf1479	ptrB OR tlp	Peptidase	−0.82
	Xf2330	slpD	Proteinase	−0.85
Cell Structure
Murein Sacculus, Peptidoglycan	Xf0416	vacJ	Lipoprotein precursor	−0.78
	Xf0799	ddlB OR ddl	D-Alanine-D-alanine ligase B	−1.69
	Xf0276	mpl	UDP-N-acetylmuramate- L-alanine ligase	−0.88
Surface Structures	Xf0487		Fimbrillin	1.07
	Xf2539		Fimbrial protein	−1.02
	Xf2544	pilB	Pilus biogenesis protein	−0.79
Chemotaxis and Mobility—Surface Polysaccharides, Lipopolysaccharides and Antigens	Xf1289	kdsA	2-dehydro-3-deoxy phosphooctonate aldolase	−0.90
	Xf1419	lpxD OR firA OR omsA	Acetyltransferase	1.05
	Xf1646	lpxD OR firA	UDP-3-O-(R-3-hydroxy myristoyl)-glucosamine N-acyltransferase	−0.75
	Xf1638		Dolichyl-phosphate mannose synthase related protein	−1.02
	Xf0879	rfbU	Lipopolysaccharide biosynthesis protein	−0.74
	Xf2154	opsX	Saccharide biosynthesis regulatory protein	−1.00
	Xf0105	kdtA OR waaA	3-deoxy-D-manno-octulosonic acid trasnferase	1.50
Membrane Components—Outer Membrane Constituents	Xf1024		Outer membrane protein H.8 precursor	−1.19
Cellular Processes
Transport—Cations	Xf1903	kup OR trkD	Potassium uptake protein	1.01
	Xf1903	kup OR trkD	Potassium uptake protein	1.40
	Xf0599	ybiL	TONB-dependent receptor for iron transport	1.46
	Xf0395	bfr	Bacterioferritin	−1.22
Transport—Amino Acids, Amines	Xf1937	gltP	Proton glutamate symport protein	−1.00
Transport—Protein, Peptide Secretion	Xf2685	sppA	Protease IV	−0.88
	Xf2261	HI0561 560	Oligopeptide transporter	−1.12
Transport—Carbohydrates, Organic Acids, Alchohols	Xf0976	dctA	C4-dicarboxylate transport protein	−1.10
Cell Division	Xf2281	DR0012	Chromosomepartitioning protein	−1.08
Other	Xf2251	ppa	Solute Na+ symporter	−1.64
	Xf1728	F451	Transport protein	1.11
	Xf1604	btuE	ABC transporter vitamin B12 uptake permease	−1.48
	Xf1409	HI1148	ABC transporter ATP-binding protein	0.84
Mobile Genetic Elements
Transposon- and Intron-Related Functions	Xf1775	IS629	Reverse transcriptase	1.06
	Xf0535		Transposase ORFA	−0.80
Phage-Related Functions and Prophages	Xf2522		Phage-related protein	1.52
	Xf2522		Phage-related protein	1.02
	Xfa0040	trbI	Conjugal transfer protein	−0.98
	Xf2291		Phage-related protein	0.95
	Xf0513	lycV	Phage-related endolysin	−1.52
	Xf1786		Phage-related protein	1.32
	Xf1706	GP37	Phage-related tail fiber protein	1.31
	Xf0685		Phage-related protein	0.86
	Xf0704		Phage-related protein	1.18
	Xf1875		Phage-related protein	1.44
Plasmid-Related Functions	Xfa0006	traA OR virB3	Conjugal transfer protein	−1.13
	Xfa0013	traAO OR virB9	Conjugal transfer protein	−1.37
	Xfa0008	traAC OR virB5	Conjugal transfer protein	−1.54
Pathogenicity,Virulence, and Adaptation
Toxin production and detoxification	Xf0262	cvaC	Colicin V precursor	7.29
	Xf0263	cvaC	Colicin V precursor	1.70
	Xf1011	frpC	Hemolysin-type calcium binding protein	−1.45
	Xf1827	ohr	Organic hydroperoxide resistance protein	−1.43
	Xf2614	sodA OR sod	Superoxide dismutase (MN)	−1.47
	Xf1210	gst OR HI0111	Glutathione S-transferase	−1.00
	Xf1890	gpo	Glutathione peroxidase-like protein	0.86
	Xf2135	frnE	Polyketide synthase (PKS)	1.80
	Xf1897	tolB	TOLB protein precursor	−1.30
	Xf1729	DR1890	Phenylacetaldehyde dehydrogenase	0.91
Host Cell Wall Degradation	Xf0818	engXCA	Endo-1,4-beta-glucanase	−0.89
Adaptation Atypical Condition	Xf2682	mdoG	Periplasmic glucan biosynthesis protein	−0.80
	Xf2622	tapB	Temperature acclimation protein B	−1.30
Surface Proteins	Xf1516	uspA1	Surface-exposed outer membrane protein	−1.28
Exopolysaccharydes	Xf2360	gumM	Gumm protein	−1.08
Other	Xf1529	hsf	Surface protein	1.96
	Xf1532	oxyR	Oxidative stress transcriptional regulator	0.96
	Xf2121	vapE	Virulence-associated protein E	1.24
	Xf1987	vacB	VACB protein	−1.35
	Xf1114	rpfC	Regulator of pathogenicity factors	−0.87
ORFs with Undefined Category
	Xf1723	yrpG	Sugar-phosphate dehydrogenase	1.30
	Xf0088	hflX	GTP-binding protein	1.36
Hypothetical Proteins
	Xf1287		Hypothetical protein	1.40
	Xf0493		Hypothetical protein	0.94
	Xf0037		Hypothetical protein	−1.11
	Xf1655		Hypothetical protein	0.82
	Xf0726		Hypothetical protein	−1.17
	Xf1835		Hypothetical protein	−0.85
	Xfa0031		Hypothetical protein	−1.60
	Xf2413		Hypothetical protein	0.96
	Xf0871		Hypothetical protein	1.69
	Xf2454		Hypothetical protein	−0.97
	Xf1769		Hypothetical protein	−0.80
	Xf1803		Hypothetical protein	−2.00
	Xf0512		Hypothetical protein	−0.93
	Xf0531		Hypothetical protein	−1.72
	Xf1868		Hypothetical protein	1.11
	Xf1881		Hypothetical protein	1.18
	Xf0917		Hypothetical protein	1.25
	Xf1738		Hypothetical protein	1.37
	Xf0242		Hypothetical protein	1.27
	Xf1228		Hypothetical protein	1.01
	Xf1279		Hypothetical protein	1.11
	Xf1575		Hypothetical protein	1.14
	Xf2597		Hypothetical protein	−0.94
	Xf0516		Hypothetical protein	1.16
	Xf2017		Hypothetical protein	−1.51
	Xf1989		Hypothetical protein	−0.94
	Xf2410		Hypothetical protein	−1.60
	Xf2304		Hypothetical protein	−1.26
	Xf0959		Hypothetical protein	1.24
	Xf2115		Hypothetical protein	1.23
	Xf1100		Hypothetical protein	1.04
	Xf1704		Hypothetical protein	0.95
	Xf0974		Hypothetical protein	−1.26
	Xf0491		Hypothetical protein	1.31
	Xf1060		Hypothetical protein	1.77
	Xf2151		Hypothetical protein	1.73
	Xf2449		Hypothetical protein	−1.01
	Xf2305		Hypothetical protein	−0.77
	Xf1721		Hypothetical protein	1.14
	Xf0626		Hypothetical protein	−1.39
	Xf2411		Hypothetical protein	1.01
	Xf1770		Hypothetical protein	−0.87
	Xf1364		Hypothetical protein	−0.85
	Xf1710		Hypothetical protein	0.90
	Xf1761		Hypothetical protein	1.44
	Xf1787		Hypothetical protein	1.38
	Xf0540		Hypothetical protein	−1.30
	Xf1788		Hypothetical protein	1.06
	Xf0646		Hypothetical protein	1.03
	Xf2543		Hypothetical protein	−0.98
	Xf0914		Hypothetical protein	−1.33
	Xf2702		Hypothetical protein	−1.52
	Xf0492		Hypothetical protein	1.55
	Xf1239		Hypothetical protein	1.01
	Xf0074		Hypothetical protein	−1.07
	Xfa0004		Hypothetical protein	−1.78
	Xf1687		Hypothetical protein	1.32
	Xf0388		Hypothetical protein	−0.86
	Xf0025		Hypothetical protein	−1.23
	Xf1434		Hypothetical protein	−1.24
	Xf2125		Hypothetical protein	0.89
	Xf1513		Hypothetical protein	1.18
	Xf2711		Hypothetical protein	1.23
	Xf0035		Hypothetical protein	1.31
	Xf1441		Hypothetical protein	−1.41
	Xf2514		Hypothetical protein	1.71
	Xf2626		Hypothetical protein	1.44
	Xf0687		Hypothetical protein	1.07
	Xf1917		Hypothetical protein	1.90
	Xf2271		Hypothetical protein	1.50
	Xf1036		Hypothetical protein	−0.99
	Xfa0017		Hypothetical protein	−1.98
	Xf0529		Hypothetical protein	1.09
	Xf2103		Hypothetical protein	−1.05
	Xf1986		Hypothetical protein	−1.05
	Xf1700		Hypothetical protein	1.12
	Xf1719		Hypothetical protein	1.08
	Xf1753		Hypothetical protein	1.44
	Xf0019		Hypothetical protein	0.85
	Xf0293		Hypothetical protein	−1.15
	Xf0300		Hypothetical protein	1.67
	Xf0279		Hypothetical protein	1.79
	Xf0735		Hypothetical protein	−0.94
	Xf1010		Hypothetical protein	−0.97
	Xf1580		Hypothetical protein	0.80
	Xf2021		Hypothetical protein	1.21
	Xf2738		Hypothetical protein	1.49
	Xf0877		Hypothetical protein	1.28
	Xf2270		Hypothetical protein	1.13
	Xf0488		Hypothetical protein	1.50
	Xf0264		Hypothetical protein	4.10
	Xf2701		Hypothetical protein	−1.68
	Xf2768		Hypothetical protein	1.35
	Xf0688		Hypothetical protein	0.96
	Xf0898		Hypothetical protein	1.15
	Xf0426		Hypothetical protein	−1.23
	Xf0443		Hypothetical protein	−1.06
	Xf1421		Hypothetical protein	−1.40
	Xf2193		Hypothetical protein	−2.17
	Xf2390		Hypothetical protein	1.24
	Xf1128		Hypothetical protein	−1.16
	Xf2116		Hypothetical protein	1.52
	Xf0467		Hypothetical protein	−1.18
	Xf1193		Hypothetical protein	−0.80
	Xf1032		Hypothetical protein	−1.33
	Xf2262		Hypothetical protein	−1.60
Conserved Hypothetical Proteins
	Xfa0045		Conserved hypothetical protein	−2.22
	Xf2450		Conserved hypothetical protein	−1.22
	Xf2609		Conserved hypothetical protein	−0.87
	Xf1754		Conserved hypothetical protein	1.83
	Xf0805		Conserved hypothetical protein	−0.81
	Xf2493		Conserved hypothetical protein	1.13
	Xf2088		Conserved hypothetical protein	1.26
	Xf0196		Conserved hypothetical protein	−1.95
	Xf1750		Conserved hypothetical protein	1.36
	Xf1745		Conserved hypothetical protein	1.24
	Xf2647		Conserved hypothetical protein	1.13
	Xf2252		Conserved hypothetical protein	−2.81
	Xf2010		Conserved hypothetical protein	−1.06
	Xf2237		Conserved hypothetical protein	−0.85
	Xfa0032	SCJ21.16	Conserved hypothetical protein	−1.06
	Xf0758	yjeE	Conserved hypothetical protein	−1.40
	Xf0407	yccW	Conserved hypothetical protein	0.98
	Xf0552	yraL	Conserved hypothetical protein	−0.92
	Xf2651	ycbY	Conserved hypothetical protein	−1.19
	Xf2575	DR0386	Conserved hypothetical protein	−0.86
	Xf0363	yiaD	Conserved hypothetical protein	−1.78
	Xf0066	ylbK	Conserved hypothetical protein	1.10
	Xf2179	ybeN	Conserved hypothetical protein	1.29
	Xf2153	HI0260.1	Conserved hypothetical protein	−1.14
	Xf0553	HI1655	Conserved hypothetical protein	−1.29
	Xf2014	DR0566	Conserved hypothetical protein	1.14
	Xf0139	yjgP	Conserved hypothetical protein	1.15
	Xf2474	yjeK	Conserved hypothetical protein	−0.79
	Xf2096	MTH1196	Conserved hypothetical protein	−1.93
	Xf1054	TM1087	Conserved hypothetical protein	−0.91
	Xf0554	yraN	Conserved hypothetical protein	−0.85
	Xf0339	btuB OR bfe OR cer	Conserved hypothetical protein	−0.91
	Xf1272	RV1827 OR MTCY1A11.16C	Conserved hypothetical protein	−1.02
	Xf1405	yhbJ	Conserved hypothetical protein	−0.88
	Xf1808	ybaB	Conserved hypothetical protein	−1.19
	Xf1829	RP471	Conserved hypothetical protein	−1.05
	Xf0941	yuxK	Conserved hypothetical protein	−0.80

Figure 2.

Evaluation of transcriptional modulation of selected genes by Real-Time qPCR. In order to confirm the reliability of the microarray experiments, 16 genes have been randomly selected and their transcription modulation was verified by Real-Time qPCR. The same RNA samples used in the microarray hybridizations were converted to cDNA and the relative expression ratios (RQ) of these genes have been measured with the aid of specific Taq-Man probes. ORF Xf1311, which encodes a rod-shaped determining protein (MreD), has been used as an endogenous control for experimental normalization, since the microarray hybridization experiments showed that this ORF is constitutively expressed in both PW and 3G10R. Variations in transcriptional modulation were calculated having the expression levels in PW as a reference and are represented by the log₂ ratio of the relative quantifications (RQ). Experiments were performed in triplicate and graphic shows the average values and their respective standard deviations.

Interestingly, we were able to verify that several genes directly associated with pathogenicity, virulence and adaptation had their transcription modulated in response to growth in xylem-based chemical conditions. This group includes genes associated with adaptation to atypical conditions (such as the temperature acclimatation protein TAPB (ORF Xf2622) and the oxidative stress transcriptional regulator OxyR (ORF Xf1532)); surface proteins (including adhesion factors, such as the outer membrane protein Hsf (ORF Xf1529)), and genes involved in toxin production and/or detoxification (such as the colicin precursors encoded by ORFs Xf0262 and Xf0263), among others (see Table 1 for details).

The lack of aminoacids in 3G10R also seems to lead to overexpression of at least four genes directly involved in the biosynthesis of such molecules (represented by ORFs Xf0624, Xf0863, Xf1121, Xf2223 and Xf2272). On the other hand, cells that are grown on the peptide-based diet provided by PW display an increased production of proteolytic enzymes, such as MucD (ORF Xf2241), PtrB (ORF Xf1479) and PepQ peptidase (ORF Xf0220), which has been shown to play a major role in lactic acid bacteria, providing the cells with amino acids derived from extracellular protein sources during milk fermentation [28].

The transcriptome results also show that the elevated growth rate of X. fastidiosa cells kept in PW is associated with the upregulation of several genes involved in a series of metabolic pathways and processes that are important to sustain continued bacterial growth [29]. These include ORFs associated with DNA replication, recombination and repair, such as dnaA (the chromosomal replication initiator, encoded by ORF Xf0001), dnaN (the β chain of DNA polymerase III, encoded by ORF Xf0002), recD (the alpha chain of exodeoxyribonuclease V, encoded by ORF Xf0425), ruvB (a Holiday junction-associated helicase, encoded by ORF Xf1902) and ung (an uracil-DNA glycosilase, encoded by ORF Xf2692).

However, since elevated growth rates establish a higher demand for energy consumption, they can only be maintained if ATP production is increased. Thus, it is interesting to verify that growth in PW is associated with overexpression of several genes involved in all major steps of the central metabolic pathway, such as triose phosphate isomerase (Xf0303) (glycolytic pathway); succinyl-coA synthase (Xf2548) and fumarate hydratase C (Xf1554) (Krebs cycle), as well as genes from the nuo operon (represented by ORFs Xf0308, Xf0310, Xf0311 and Xf0317, resp.). Genes from this operon encode subunits of the NADH Dehydrogenase I complex, the first component of the respiratory electron transport chain. Interestingly, coordinated overexpression of such genes has already been shown to occur in E. coli cells submitted to differing culture conditions [30, 31].

3.2. Increased Growth Rate in PW Is Associated with Upregulation of Genes from the Electron Transport Chain and Consequent Enhancement of Respiratory Activity

As mentioned before, PW is the most commonly used medium to cultivate Xylella fastidiosa under laboratory conditions, since this formulation has been shown to sustain efficient growth of all isolates of this phytobacterium [11]. Thus, the positive modulation of genes directly involved in oxidative phosphorylation, might lead to increased aerobic respiratory activity and consequent ATP production, which seems to greatly improve on the fastidious nature of this bacterium. Thus, we decided to verify O₂ consumption in PW-grown cells as a way to indirectly estimate the activation of aerobic respiration in X. fastidiosa. This experiment allowed us to verify not only the activation of the aerobic respiration, but also to obtain biological confirmation of a major metabolic change originally predicted solely on the transcriptome data.

As shown in Figure 3, X. fastidiosa cells transferred from PW to 3G10R displayed a continued decrease in the respiratory rate, which is unaffected in cells transferred to fresh PW medium. A direct comparison between the results observed for the PW culture, at day 3, and the 3G10R culture, at day 13, (the same time points used for transcriptome comparisons) shows that cells grown in PW display overexpression of several genes involved in all major steps of the central metabolic pathway, as well as a respiratory rate that is about five times greater than that observed with cells grown in 3G10R. Thus, the results from this experiment confirmed that there is a significant increase in oxidative phosphorylation when X. fastidiosa cells are grown in PW (as previously inferred from the analysis of transcriptome data), which helps to explain the effectiveness of this culture medium in sustaining continued and vigorous growth of X. fastidiosa strains.

Figure 3.

Evaluation of respiratory rates in Xylella fastidiosa cells growing in PW and 3G10R. X. fastidiosa cells were grown into middle exponential phase in PW and subsequently transferred (in a 1 : 20 proportion) into fresh PW and 3G10R cultures. Bacterial growth in both cultures was monitored through OD₆₀₀ measurements and aliquots were taken from each culture to evaluate O₂ consumption with the aid of an oxygraph in intact cells. Respiratory rate for each culture was calculated as the ratio between O₂ consumption and the respective OD₆₀₀ value obtained at each time point. Measurements were taken until day 7 (in PW) and day 13 (in 3G10R). Experiments were performed in triplicate and graphic shows the average values and their respective standard deviations.

4. Discussion

The recent development of xylem-based chemistry media, such as 3G10R, has provided an interesting instrument to study several aspects of X. fastidiosa behavior under laboratory conditions, where this phytopathogen is typically grown in complex media, such as PW [11]. Interestingly, both PW and 3G10R are capable of sustaining growth of X. fastidiosa cells in vitro, although significant differences have been observed in the bacterial growth rates.

Nonetheless, when growing in PW, where X. fastidiosa cells have been shown to display an increased respiratory rate, as well as an enhanced growth profile, we can observe coordinated upregulation of enzymes from the central metabolic pathway, particularly of the NADH Dehydrogenase I complex, a phenomenon also observed to occur in E. coli grown in different media [30, 31]. This results in strong activation of the aerobic respiratory metabolism, providing the cells with the necessary energy for increased bacterial replication. However, at this point, we do not know the exact mechanism(s) that might be responsible to trigger such a respiratory activation, nor if it plays any role during plant colonization or onset of disease, when the endophytic population of X. fastidiosa seems to increase dramatically inside xylem vessels [32, 33]. It seems unlikely, however, that this metabolic switch occurs only on the account of oxygen concentration, since both cultures were kept under the same aeration conditions during all experimental steps described throughout this work.

Incidentally, this situation seems to resemble the fermentative-to-respiratory shift observed in Lactococus lactis, a gram-positive, microaerophilic bacterium, with a fermentative metabolism that produces mainly L-lactate from carbohydrates [34, 35]. L. lactis, as well as other members of the Streptococcaceae family, such as Streptococcus agalactiae and Enterococcus fecalis, multiply mainly via a fermentative metabolism, even in the presence of oxygen. Curiously, in spite of the fact that these bacteria carry all genes and enzymes necessary to undergo aerobic respiration, prolonged aeration of L. lactis cultures can lead to growth inhibition, DNA degradation and cell death, probably due to the formation of hydrogen peroxide and hydroxyl radicals during aerobic respiration, associated with an incomplete set of oxidative stress-resistance enzymes [36]. However, if exogenous haem is provided during aerated growth, L. lactis cells can undergo a metabolic shunt towards respiratory metabolism, leading to increased ATP production, improved growth and a dramatic increase in long-term survival, when compared to growth in standard fermentation conditions [35]. Further details regarding the fermentation-respiration shift in L. lactis are not completely understood, but it has been documented that the process depends on cytochrome BD (encoded by the cyaBD genes) and is controled by the Catabolite Control Protein (CcpA) [37]. Although more direct evidence is still needed to further clarify this issue, it is tempting to speculate if the presence of hemin chloride in PW might be acting as an exogenous source of haem and activating an analogous mechanism in X. fastidiosa cells that would lead to an increase in aerobic respiration.

The observed modulation of triose phosphate isomerase (Xf0303) is also noteworthy, since preliminary studies failed to detect specific activity of several genes from the Glycolytic pathway in bacterial crude extracts, such as aldolase, glyceraldehyde 3-phosphate dehydrogenase and enolase [38]. On the other hand, the activity of glucose 6-phosphate dehydrogenase was detected in these same extracts, leading the authors to suggest that X. fastidiosa cells do not use the glycolytic pathway to oxidize glucose, which would be preferably metabolized by the Entner-Dudoroff pathway [38]. In X. fastidiosa, all genes of the Entner-Dudoroff pathway are encoded by a single operon, which encompasses ORFs Xf1061 to Xf1065, but we did not observe overexpression of any such genes in either of the media, even in 3G10R, which has glucose as the sole carbon source.

The difference in carbon source also seems to be important in determining the expression of genes associated with other aspects of the cellular metabolism, such as aminoacid biosynthesis (in 3G10R), as opposed to proteolytic enzymes (in PW). Interestingly, the coordinated upregulation of proteolytic enzymes is indicative that X. fastidiosa cells, like lactic acid bacteria, have developed an efficient mechanism dedicated to process extra cellular proteins as a major way to obtain amino acids from exogenous sources [39]. This idea is also consistent with the elevated growth rates observed with cells grown in PW, a significantly rich medium, which is based on relatively high concentrations of protein hydrolisates, such as tryptone and peptone [11].

In spite of providing more adequate nutritional conditions to sustain continued growth of fastidious microorganisms, complex media are not likely to resemble the harsh nutritional conditions found in xylem sap. Since 3G10R does not receive nutrients from any complex source, it is likely to be much more restricted in nutrient availability [16]. Moreover, this formulation incorporates a few important chemical characteristics that resemble xylem composition of plants known to be infected by X. fastidiosa, such as the use of glucose as a major carbon source [22–24] and the presence of L-glutamine, which is the most abundant amino acid detected in the sap of grapevines [25, 26] and seems to be essential for in vitro growth of X. fastidiosa cells [11, 40]. The antioxidant tripeptide glutathione (GSH) has also been detected in the composition of xylem fluid of poplar and spruce trees [41, 42] and is present in the composition of 3G10R at a similar concentration [16].

The presence of glucose seems to be an important characteristic of 3G10R in resembling xylem, since this metabolite has already been identified in the chemistry composition of xylem fluid from many plant species, such as grapevine [22], maize [43], cabbage [44], poplar [24] and oak [23], among others [45]. However, the exact glucose concentration found in the xylem sap of different plants has been shown to vary significantly, depending on the species, genotype, season, time of day, age of plants and nutritional status. In poplar trees, such concentration has been shown to range from 0.2 to 15 mM [24], although there have been reports of this nutrient at <50 μM concentration in the xylem of grapevines (a typical X. fastidiosa host) [16]. Thus, the ~10 mM glucose concentration present in 3G10R might be higher than the concentration typically encountered by X. fastidiosa cells during the process of plant infection and colonization.

Although glucose is generally viewed as an energy source for growing microorganisms, this substance has also been shown to act as a precursor for the biosynthesis of several bacterial cell wall components and exopolysaccharides (EPSs), which have been proposed to act as virulence factors in X. fastidiosa and many other pathogenic bacteria ([46–48], reviewed in [4]). Moreover, increased production of EPS is one major characteristic of X. fastidiosa cells freshly isolated from infected plants and such primarily isolated cells have been shown to be more effective in the process of plant colonization, when compared to cells submitted to continued growth in PW [49]. Coincidentally, while growing in 3G10R, X. fastidiosa cells have also been shown to synthesize increased amounts of EPS, leading to more intense biofilm formation [16]. It has even been proposed that the preferential use of glucose to drive EPS synthesis could be an explanation to the fastidious growth of X. fastidiosa cells, especially in 3G10R, where these molecules are expected to act as the major source of energy as well [16]. Interestingly, when X. fastidiosa cells are grown in this medium, we observed increased expression of xanA (ORF Xf0260), which encodes a phosphoglucomutase that converts glucose 6-P into glucose 1-P, which in turn, acts as a precursor of UDP-Glucose and UDP-Galactose, which are involved in the biosynthesis of different types of EPS [50]. Moreover, it has already been shown that increased expression of phosphoglucomutase can lead to an increase in the production of EPS in Lactococus lactis [51].

EPS production is one of the most important aspects of biofilm formation, which is believed to be an important pathogenicity factor in X. fastidiosa cells [52]. Other adhesion factors have been detected as preferentially expressed in 3G10R, which might be directly correlated with the more intense cellular aggregation and biofilm formation observed in this medium [16]. One of these putative adhesion factors is represented by ORF Xf0487, which encodes a 20 kDa fimbrillin subunit of bacterial fimbreae, and may be involved in bacterial adherence and invasion [53]. Pili and fimbreae have been implicated in plant infection and migration via a twitching motility mechanism that seems to be of paramount importance to the colonization process of X. fastidiosa [54]. Another important component of the cellular outer membrane structure that has been shown to be upregulated in 3G10R is the hsf gene (ORF Xf1529), which encodes a surface fibril that belongs to a family of high molecular weight autotransporter adhesins [55]. This protein has been originally characterized as an important virulence factor from Haemophilus influenzae type b, which causes meningitis and other serious invasive human diseases. In this bacterium, the Hsf protein has been shown to form trimeric fiber-like structures on the bacterial surface that mediate adhesion to epithelial cells [56]. Hsf is also suspected to act as a virulence factor in X. fastidiosa, since overexpression of this protein occurs in X. fastidiosa cells that display higher infective capacity, as well as in bacteria directly isolated from infected plants [17, 49].

Three bacteriocin genes (Xf0262, Xf0263 and Xf0264) have been found to be overexpressed in 3G10R-cultivated cells, suggesting that increased production of such molecules might be important to X. fastidiosa cells in competing with other endophytic bacteria within the xylem [57]. These molecules belong to a class of structurally related proteins that kill target cells by membrane permeabilization. Some of them have been known to kill different types of bacteria, constituting a strategic advantage for microorganisms that colonize highly competitive environments [58]. Although little is known about the X. fastidiosa bacteriocins so far, it is interesting to verify that the bacteriocin encoded by Xf0263 has also been identified as overexpressed in X. fastidiosa cells that display higher infective capacity, as well as in bacteria directly isolated from infected plants [17, 49], while the proteins encoded by Xf0262 and Xf0264 are induced in response to glucose [59].

Although we are aware that defined media, like 3G10R, do not constitute a perfect simulation of the environment inhabited by xylem-dwelling endophytes, this formulation has clearly incorporated some important chemical aspects of xylem fluid composition, which induce transcriptional activation of some putative pathogenicity-associated genes in X. fastidiosa cells. Moreover, some of these genes have also been shown to be specifically upregulated in cells directly isolated from infected plants, as well as in freshly isolated X. fastidiosa cultures, which are known to display a higher infective capacity. The dependence of aggregation and biofilm formation on the nutrient composition of xylem fluid suggests that xylem chemistry is important in resistance/susceptibility to disease [27, 60, 61]. Thus, the transcriptome profile of X. fastidiosa cells grown in xylem-based chemistry media is more likely to represent the metabolome of X. fastidiosa cells in planta, reinforcing the idea that such media formulations should be preferred for metabolic studies of this phytopathogen.