Evaluation of reference genes for real-time RT-PCR expression studies in the plant pathogen Pectobacterium atrosepticum
© Takle et al; licensee BioMed Central Ltd. 2007
Received: 13 February 2007
Accepted: 21 September 2007
Published: 21 September 2007
Real-time RT-PCR has become a powerful technique to monitor low-abundance mRNA expression and is a useful tool when examining bacterial gene expression inside infected host tissues. However, correct evaluation of data requires accurate and reliable normalisation against internal standards. Thus, the identification of reference genes whose expression does not change during the course of the experiment is of paramount importance. Here, we present a study where manipulation of cultural growth conditions and in planta experiments have been used to validate the expression stability of reference gene candidates for the plant pathogen Pectobacterium atrosepticum, belonging to the family Enterobacteriaceae.
Of twelve reference gene candidates tested, four proved to be stably expressed both in six different cultural growth conditions and in planta. Two of these genes (recA and ffh), encoding recombinase A and signal recognition particle protein, respectively, proved to be the most stable set of reference genes under the experimental conditions used. In addition, genes proC and gyrA, encoding pyrroline-5-carboxylate reductase and DNA gyrase, respectively, also displayed relatively stable mRNA expression levels.
Based on these results, we suggest recA and ffh as suitable candidates for accurate normalisation of real-time RT-PCR data for experiments investigating the plant pathogen P. atrosepticum and potentially other related pathogens.
Real-time reverse transcription polymerase chain reaction (real-time RT-PCR) has become the preferred method for studying low-abundant mRNA expression . The high sensitivity and specificity of RT-PCR makes it a particularly useful and powerful technique for monitoring the mRNA expression of pathogen genes during host infection, where the pathogen's expression profile is often masked by the much higher concentration of host RNA. However, the study of pathogen gene expression inside infected host tissue poses some problems, as there is no straightforward way of measuring the total pathogen RNA concentration. An increase in target transcript at different time points after infection could either come from an up-regulation of transcription or merely from an increase in the pathogen population inside the host tissue, or both. Therefore, normalisation of the data against reference genes (i.e., genes whose expression do not change under the various experimental conditions) is an important step in the quantification of gene expression. Reference genes are also used to correct for differences between samples, such as variation in the total quantity of RNA and variation in RT-PCR efficiency. Therefore, it is of paramount importance to find stably expressed reference genes, as the reliability of the normalised expression data is only as good as the reliability of the reference gene(s). Any variation in reference gene expression could in principle mask real positives as well as create false positives [2–5]. To obtain a reliable normalisation, the use of more than one reference gene is recommended [6–8]. The expression of typical prokaryotic housekeeping genes has been reported to be highly variable under most experimental conditions .
Pectobacterium atrosepticum (formerly known as Erwinia carotovora subspecies atroseptica [10, 11]) is an important bacterial pathogen of potato in temperate regions, where it causes blackleg of plants and soft rot of tubers by the utilization of a huge machinery of plant cell wall degrading exoenzymes mainly encompassing pectinases, cellulases and proteases. The bacterium lies dormant in the plant or tuber until conditions are favourable for infection [12–14]. The recently published genome of P. atrosepticum strain SCRI1043 has provided valuable tools for examining different aspects of pathogenesis . Our own (unpublished) initial RT-PCR-based studies on differential gene expression in P. atrosepticum during potato infection revealed problems related to reliability of reference genes. Therefore, we have conducted a wider search for reference gene candidates, with the aim of producing a set of reference genes that can be applied to future real-time RT-PCR experiments with P. atrosepticum, and potentially other bacteria, in infected plant material.
We have used a combination of different growth media, temperatures and growth phases to test the expression stability of twelve reference gene candidates in P. atrosepticum, and completed the test with an experiment in infected potato leaves. The following reference gene candidates were included in this study: Signal recognition particle protein (ffh), glutamine synthetase (glnA), DNA gyrase (gyrA), pyrroline-5-carboxylate reductase (proC), recombinase A (recA), transcription termination factor Rho (rho), 50S ribosomal protein L9 (rplI), 50S ribosomal subunit protein L17 (rplQ), DNA topoisomerase I (topA), nucleoside-specific channel-forming protein (tsx), maltose-binding periplasmic protein (malE) and 16S ribosomal RNA (16S).
Selection of twelve reference gene candidates for real-time RT-PCR
On the basis of the P. atrosepticum SCRI1043 genome sequence , a set of twelve reference gene candidates were selected for an initial real-time RT-PCR study. The genes were selected from different parts of the genome to minimize the chance of transcriptional coupling affecting the results. They were also selected to encode proteins involved in different metabolic activity except for the ribosomal genes, in order to minimize the chances of a global co-regulation. The ribosomal gene 16S rRNA is a commonly used reference gene in many real-time RT-PCR experiments, including studies on former Erwinia species [16–23]. GlnA has been used as a reference gene in Streptococcus pneumoniae real-time experiments  and gyrA has been used in studies on different bacteria including a very recent study on the plant pathogen Pseudomonas syringae pv. tomato [21, 25, 26]. ProC and rho have been tested as reference genes in similar studies of other bacteria, although no plant pathogens to our knowledge [27, 28]. The genes rplI and rplQ are part of a group of ribosomal proteins that have also recently been used as reference genes in real-time PCR experiments on both prokaryotes and eukaryotes [29–32]. RecA is a common housekeeping gene that has been used as reference gene in studies on various bacteria (e.g. [20, 27, 33–35]) and was recently found to be a good reference gene for certain studies of P. atrosepticum (I. K. Toth, unpublished results). The genes ffh, topA, tsx and malE have, to our knowledge, not been reported as reference genes previously. The latter four genes were selected merely on the basis of either being well-known housekeeping genes in other bacteria (ffh, topA), or known to be expressed during different growth conditions in P. atrosepticum (tsx, malE) .
Expression analysis of reference gene candidates in cultures
Descriptive statistics of reference gene expression across all cultural growth conditions by BestKeeper1
(min, max) [Ct]
SD [± Ct]2
(min, max) [x-fold]3
SD [± x-fold]2
Expression of selected reference gene candidates in infected plant material
Statistical analysis of real-time RT-PCR data by geNorm
Ranking of reference genes by geNorm
Average expression stability M
Pairwise variations V
Real-time RT-PCR is becoming an important technology for studying host-pathogen interactions. However, proper and highly reliable reference genes are needed for normalisation of data, as normalisation by total pathogen RNA in mixed host-pathogen samples is usually not possible. Here, we describe a set of reference genes that can be used to normalise gene expression in the potato pathogen Pectobacterium atrosepticum and potentially other related pathogens. We identified several genes that showed only minor variations in expression under a range of growth conditions. The expression of these genes was then further analysed using the Excel-based programs BestKeeper [7, 37] and geNorm [6, 38]. Both programs have been used in several recent studies [39–44]. While geNorm requires that the data be converted to relative expression values, BestKeeper allows for the input of Ct values.
From the statistical analyses it was concluded that two genes, recA and ffh encoding recombinase A and signal recognition particle (SRP) protein, respectively, were particularly stably expressed. Also proC and gyrA were relatively stably expressed under the conditions used in this study. On the other hand, the 16S gene was not stably expressed in the different culture conditions used in this study. This gene was included in our analyses because of its extensive use as a reference gene in several real-time PCR studies [16–23]. Although commonly used, some reports suggest that this gene is also under regulatory control [9, 45]. In addition, we discovered that 16S was amplified from leaf material that was not inoculated with the pathogen. Since 16S genes are very conserved in different bacterial species and even within eukaryotic chloroplasts and mitochondria, this "non-specific" amplification could be from plant material in the samples as well as from bacteria naturally present in the phyllosphere. This result suggests that 16S is inappropriate as a reference gene when not analysing pure cultures, such as complex host-pathogen samples. Another disadvantage of normalising against 16S is that the cellular quantity of ribosomal RNA is much higher than that of mRNA. This makes it necessary to dilute the cDNA samples prior to real-time analysis, thus risking dilution errors. Also, while mRNAs have a rapid turn-over according to the bacteria's needs, the rRNA is only degraded under certain stress conditions or when the molecule is defective , hence, the rRNA population is not comparable to the mRNA population.
The choice of an acceptable level of reference gene expression variability depends on the degree of sensitivity that is demanded for each experiment. Obviously, the goal is always to strive towards finding reference genes with the lowest possible expression variability. However, even a reference gene expressing some variability over the course of the experiment may be sufficient to detect target gene expression variations as long as these are larger than for the reference gene. Generally, reference genes with geNorm expression stability measures below 1.0 have been regarded as suitable for normalisation in some studies [28, 39, 44] and are also below the geNorm default limit of M = 1.5 . In this study, the five reference genes ffh, recA, proC, gyrA and 16S all have an expression stability measure below 1.
Analyses by geNorm suggest that the combination of ffh and recA is the optimal set of reference genes for studying differential gene expression in P. atrosepticum by real-time RT-PCR under the various conditions applied in this study. These conditions included two different growth temperatures, exponential and stationary growth phase, rich and minimal growth medium with two different types of pectin, as well as infiltrated potato leaves. However, it has been recommended that at least three reference genes should be used for correct normalisation of real-time RT-PCR data . The results from this study suggest that proC could be used together with ffh and recA. However, increasing the number of reference genes means increasing the workload and cost. In addition, applying a large reference gene set could pose problems with limited sample availability. The use of a single reference gene is generally acceptable, but this gene should be subjected to extensive studies before use to ensure its stability .
All methods for RNA detection face problems concerning stability of RNA as well as sensitivity and specificity of detection [8, 47]. Studying pathogens inside host tissues poses a further complication, as the amount of pathogen RNA often becomes vanishingly small compared to host RNA. Although there are a few exceptions (e.g. [48–50]) it is not currently possible to avoid having to deal with mixed eukaryote – prokaryote RNA when looking at pathogens inside host tissues. It is thus of utmost importance to find good reference genes for normalisation of real-time RT-PCR data from mixed host – pathogen RNA samples. Bacterial gene expression is highly diverse, and there is unlikely to be a single universally and stably expressed prokaryotic housekeeping gene. Therefore, we support the general notion that tests should be conducted in any real-time RT-PCR experiment before deciding which genes to use as reference genes for a particular study, and the recommendations of using more than one reference gene, in particular when studying pathogen expression inside infected host tissue [6, 8, 9, 28, 39, 51, 52].
Here we present a study where manipulations of growth conditions for P. atrosepticum were used in order to find a set of reliable reference genes for monitoring bacterial gene expression inside infected plant tissue. A set of two reference genes, ffh and recA, proved to be the optimal set for use under the conditions applied. To our knowledge, this is the first time reference genes for studying gene expression by real-time PCR have been systematically examined in a plant pathogenic bacterium. The evaluated set of genes in this study could also provide valuable guidelines for reference gene selection when working on mRNA expression in other bacterial pathogens, in particular from the family Enterobacteriaceae.
Culture conditions and bacterial infiltration of potato leaves
P. atrosepticum cultural growth conditions
M9 mm, cap (0.05 %), pga (0.125 %), abg (0.05 %)
M9 mm, glucose (0.2 %)
M9 mm, cip (0.5 %), pga (0.5 %), abg (0.5 %)
RNA isolation from cultures and infected plant material
For bacterial cultures, total RNA was isolated from ~1 × 109 cells using the RNeasy mini kit (QIAGEN). On-column DNase digestion using the RNase-Free DNase Set (QIAGEN) was included in the protocol. To remove DNA, it was necessary to include an additional DNAse treatment using RQ1 RNase-Free DNase (Promega). This was followed by phenol:chloroform:isoamyl alcohol extraction (25:24:1) and precipitation with ethanol. The RNA pellet was dissolved in DEPC-treated water. Total RNA from leaf material was isolated using TRIzol Reagent (Invitrogen). The RNA was then subjected to a phenol:chloroform:isoamyl alcohol extraction to increase the purity, after which the samples were subjected to two subsequent DNase treatments with RQ1 RNase-Free DNase (Promega), followed by phenol:chloroform:isoamyl alcohol extractions and precipitation with ethanol. Mixed plant-bacterial total RNA was treated with MICROB Enrich (Ambion), according to the manufacturer's recommendations. Briefly, mixed host-pathogen total RNA samples were incubated together with oligonucleotides that capture eukaryotic polyadenylated mRNA as well as 28S and 18S rRNA. The oligonucleotide-hybridized mRNA and rRNA were then removed using magnetic beads. The enriched bacterial RNA was precipitated and resuspended in RNase-free water. All the RNA samples were assessed for quality by agarose gel electrophoresis, and quantified using a GeneQuant spectrophotometer (GE Healthcare). Absence of genomic DNA contamination was confirmed by PCR.
Reverse transcription, real-time PCR and data analysis
Primers used in this study
Forward primer (5' – 3')
Reverse primer (5' – 3')
The authors wish to acknowledge the Pectobacterium group at SCRI for their advice and ongoing collaboration. The financial support of the Research Council of Norway is greatly acknowledged.
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