Abstract
Asymptomatic infections are by their nature challenging to study and even more difficult to monitor across broad geographical ranges, particularly as methods are reliant on expensive molecular techniques. The plant pathogen that causes Witches’ Broom disease of lime (Candidatus Phytoplasma aurantifolia) is a major limiting factor in lime production across the Middle East and was recently detected in Brazil, but without the typical symptoms from the Middle East. Here, we discuss the difficulty of monitoring asymptomatic infections and highlight the threat posed by highlight future outbreaks. Asymptomatic infections have important implications for understanding the evolution of pathogens within perennial hosts. We use three model systems of asymptomatic infections: (i) a Phytoplasma and (ii) a bacterial infection of lime (Citrus aurantifolia) and (iii) an “out-group” Phytoplasma of Cassava (Manihot esculenta) to demonstrate consistency across divergent hosts. We found that although all plants in the study were intentionally infected, assays typically did not confirm this diagnosis. Emergent technologies monitoring gene expression could be used to both study novel biology associated with asymptomatic infections and develop monitoring technologies. We highlight the difficulty of monitoring asymptomatic infections in possible future outbreaks and have important implications for understanding the evolution of pathogens within perennial hosts.
Keywords
- Citrus aurantifolia
- acid lime
- silent infection
- phytoplasma
- differentially expressed genes
1. Introduction
Vector-borne plant pathogens of perennial crop species provide an opportunity to study the impacts of long-term infections, in terms of epidemiology and vector ecology. Crop diseases directly threaten global food security; an estimated 16% of food production globally is lost despite our efforts to control crop diseases [1]. Perennial crops generally have advantages over annuals in terms of energetic efficiency; for example, constant canopy development increases photosynthesis efficiency [2], which results in 30% increases in carbon turnover than those maintained by annual crops [2]. Pathogens must evolve to infect and reproduce within a single year in annual cropping systems, and thus typically demonstrate more aggressive pathologies [3], which often require multiple hosts, such as potato blight (
Globally, plant pathogens are spreading faster than ever, due to climate change, increased crop and germplasm trading, failure of border biocontrol and associated spread of vector species. Here, we shall introduce and discuss a complex vector-borne plant pathogens of a perennial tropical cash-crop plant:
The production of lime in the Middle East has been markedly impacted by Witches’ Broom Disease of Lime (WBDL) [7]. Symptoms of witches’ broom disease of lime (WBDL) were first observed in Oman in the 1970s [9]. Infected trees present with “witches’ brooms”: shoot structures characterized compactness and small, pale green leaves. In the advanced stages of the disease, leaves become dry, brooms become increasingly more prevalent, and fruits become significantly smaller and less marketable. Finally, the tree collapses within 4 or 5 years after infection [10].
Asymptomatic (“silent”) infections have recently been detected in lime trees in Brazil [11] and Oman [12]. This silent infection was observed through molecular testing of plant material, yet the host plants themselves show no obvious visible symptoms. These infected trees do however, also collapse within the 5 year post infection period [13], making this asymptomatic variant potentially even more of a threat to global lime production.
Detailed research into this system has been limited, some suggest that the silent infection may be due to ultra-low pathogen titre levels within the host plant [12, 14] or due to different interactions with plant defences [15] or insect vectors [16, 17]. Silent infections are difficult to monitor and pose a significant risk to global food security, given that the limited knowledge we have suggests they may be as destructive as symptomatic [18], but we do not yet know the full extent of their range.
The Phytoplasma “
Although studies using proteomics [10, 24] and cDNA-amplified fragment length polymorphism (cDNA-AFLP) [25] have investigated differentially expressed genes (DEGs) in plants infected by “
Within this chapter, we shall discuss two studies on asymptomatic infections of crop plants [1]. Reliable detection of asymptomatic plant pathogens is the greatest limitation on controlling and limiting their global spread. We first discuss and test the potential for currently employed molecular tools to misidentify “healthy” plants. We study three asymptomatic infections (a Phytoplasma of lime, a Phytoplasma of cassava and
2. Pathogen detection in the absence of visible symptoms: study system
In order to comprehensively study the most ubiquitous methods used globally for asymptomatic infections of crop plants, we used three model systems: the aforementioned Phytoplasma causing Witches’ Broom Disease of Lime (WBDL), a closely related Phytoplasma causing Cassava (
2.1 Sample locations
Acid lime (
Leaf samples of cassava (
2.2 Plant material
The sampling strategy for both lime Phytoplasma and cassava Phytoplasma aimed to collect a spatially diverse group of samples (orientated on x, y and z axes relative to the trunk), with the position of each leaf sampled noted with respect to its branches from the main trunk. For all sample types locations, leaf midrib samples (the larger vein along the midline of a leaf) were taken. The midribs were immediately frozen in liquid nitrogen after harvesting and then transported to the laboratory, where they were stored at −80°C until total DNA and RNA isolation.
2.3 Molecular detection of Phytoplasma
The presence/absence of the Phytoplasma in the leaf samples of both acid lime and cassava was analysed using PCR for Phytoplasma detection. To this end, total DNA was extracted from acid lime leaf samples using the DNeasy Qiagen Plant Mini Prep kit following manufacturer’s instructions. Then, total DNA was extracted from the cassava leaf samples following the protocol of [28], with modifications that are detailed in [18].
We then used a nested PCR using universal primers for Phytoplasma detection. Extracted DNA of both
PCR amplification was carried out using a Loccus Biotechnologia TC9639 Thermal Cycler (LB, São Paulo, Brazil) in 20 μl volumes, such that each reaction contained the following: 2.0 μl (20 pmol) of each primer, 8.0 μl water (DNA-free water; Qiagen, SP, Brazil), 4.0 μl sample extracted DNA and 0.1 μl Invitrogen
Data on the successful amplification of “
3. Pathogen detection in the absence of visible symptoms: results and discussion
Detection of “
Tree | Infected | Detection likelihood (%) |
---|---|---|
A | 21/31 | 67.74 |
B | 24/44 | 54.55 |
C | 28/45 | 62.22 |
SA | 5/10 | 50.00 |
SB | 6/10 | 60.00 |
SC | 6/10 | 60.00 |
SD | 6/10 | 60.00 |
SE | 4/10 | 40.00 |
SF | 3/10 | 30.00 |
SG | 3/10 | 30.00 |
SH | 10/10 | 100.00 |
Table 1.
Results of asymptomatic infections of “
The evidence for false-negative across multiple plant pathosystems has notable implications across the field. One of the base assumptions of plant pathology is the suitability of a biological sample to represent the entire host plant. These false-negatives mean that multiple biological samples per plant may be required to correctly identify the presence of a pathogen. A hypothetical plant with α leaves and a false-negative rate of
Due to the nature of additive probabilities (Eq. (2)), the probability of, for example, 38 continuous false-negatives on a tree of 100 leaves would be P = 4.83−22. Consequently, a decision support system based on the likelihood of having an infected tree can be developed in order to determine the appropriate number of samples required to avoid a false-negative. For example, for P = 0.05, minimum sample number would be n = 4.19; for P = 0.005, n = 8.94; for P = 0.001, n = 12.25 (Figure 1a). For cassava similarly the minimum sample number for the same probabilities would be (in order): n = 3.55, n = 7.20 and n = 9.76 (Figure 1b).

Figure 1.
Probability function for false negatives using PCR-based detection for asymptomatic Phytoplasma infections. The additive probability of sequential false negatives as the sample size increases in (a)
Asymptomatic plant pathogens are particularly troublesome within perennial crops as they are not removed at the end of the growing season and act as reservoirs of infectious materials to be dispersed to new hosts by insects (and other vehicles). Persistence of asymptomatic infections in hosts may also cause problems through subtle direct damage or sublethal infections leading to plant-by-plant transmission [32]. The use of accurate and timely diagnostic methods is undoubtedly one of the best ways to monitor pathogen ranges in asymptomatic infected plants, and thus avoid dissemination to new hosts and ranges. Generally, traditional methods of identification based on visual symptoms and culturing in laboratories are time-consuming, labour-intensive, costly and have “very low sensitivity and specificity” [33, 34].
Molecular methods are the mainstream alternative to symptomology and laboratory culture. The results of this present (and a previous) study [27] have demonstrated a potential flaw in molecular methods: the frequency of false-negatives. Whereas classical plant pathology can rely on a non-destructive inspection of the entire host plant, culture and molecular methods must only use a small “representative” destructive subsample of the plant. The major limitation to this is the quality of the representation of the host plant within this subsample. We have demonstrated here that a single biological sample from an infected plant may not be representative of the whole plant and therefore multiple samples from within the same host plant can result in different results from molecular testing for pathogens. We found false-negative rates between 38 and 49%, meaning that approximately a minimum of one in three samples would fail to detect a pathogen if taken alone. Although this calls into question the use of single biological samples for identifying pathogens by molecular methods, these methods have to strike a balance between precision and cost [35]. We calculate, based on these false-negative rates, minimum sample numbers (per plant) between 3 and 5 samples, which may make these methods prohibitively expensive for widespread use within agriculture.
By comparison, real-time PCR used to detect and quantify pathogens in symptomless plant tissues is a promising tool to improve our understanding of “silent” infections [36]. Different methods of DNA amplification that rely on conventional and quantitative PCRs have also been developed to detect and identify “
4. Novel asymptomatic infection biology: study system
Successful identification of asymptomatic infections by the Phytoplasma causing Witches’ Broom Disease of Lime (WBDL) provide a unique opportunity to compare the pathology with its’ symptomatic counterpart. A recent study by Mardi et al. [26] using a high-throughput genomics approach identified 2805 differentially expressed genes in symptomatically infected
4.1 Sample locations
Acid lime (
4.2 Plant material
Six
4.3 RNA extraction
Total RNA was extracted from the three biological replicates of limes infected with “
4.4 Gene expression
Gene specific primers were designed for 15 genes belonging to key pathways with possible implication in disease progression and resistance identified by Mardi et al. [26] and four by Alves et al. (unpublished). The sequence of primers, amplicon length, optimal primer and enzymatic efficiency for each primer pair is presented in Table 2. Mardi genes were amplified only for Brazilian samples, whereas we were able to study the smaller number Alves genes were amplified for both Brazilian and Oman samples.
Unigene | Forward primer | Reverse primer | Amplicon length (bp) |
---|---|---|---|
U352 | TGGCTCTGGATGGCATTG | GTGCTTCTGGGATAGTGA | 133 |
U2265 | TGCTGCATTGGTTCTGTC | GACTGCAAAGGACTCCAAG | 130 |
U27316 | ATGCGATACACAACCCAATCT | CGGCCATGAGACCAAAACT | 126 |
U75775 | GAAGGAGCTGACGTTTTC | CTTCTGCCTCTTCCCTCTC | 160 |
U26576 | GATTGTCCGCCCAGTAGTG | CACGCGATCAGCCAAACTC | 174 |
U72184 | CAAAGAGATGGGCAAAGAG | GCCAAATTACAAACCAAACGA | 121 |
U59125 | TATGGGGATAAGGGGTGT | TGCCACAACTAACCTCCTC | 182 |
U68165 | CTGCTGAGATTACATGGTT | CTCTTCAGGGAATTGCAC | 147 |
U68593 | GACTCTCTTTCAATGCCA | TTGAAAGCACAGGTTCCGA | 119 |
U77887 | CATGCCATCCTCTTCACT | GGGTTGGGTTGAGTATCT | 123 |
U3869 | CTCCTCCTCCTCCTCCAAAG | GCGAACCCATCACACTACAT | 117 |
U17275 | AACACCCATTTGCATTCTC | GGTTTGTATGCCTTCGATG | 130 |
U41653 | GAGAGTAGCAAGACCTCAAG | TATCACCAGCCTCACTTCAC | 114 |
U17606 | CTCACCGCAGATTTTGAACCAC | ACATCCGTCTTCTCATCCACA | 158 |
U24969 | GCCTCCGTTTCCAATTCTC | GATACCGAGGATTTCATGGC | 131 |
WRKY33 | GATGATGAAAATGAACCTGATGCT | CAATTCTTGGCTCCCTCACAGT | 144 |
WRKY70 | AGACCGGAGAGGATGCTACAAG | CCCATATTTCCTCCATGCAAA | 152 |
MYBR1 | AATGGATCCAACTTGGTTTTGAA | ATCCAAACTCGCCCTGGTT | 110 |
JAZ6 | ACAATGATGCAACCCCACTTC | TGCTGCAGCCCTTTCTTTTC | 120 |
Table 2.
Primer sequences for potential infection related differentially expressed genes in
The selected genes were quantified using the Applied Biosystems StepOne™ Real Time PCR system (Thermo Scientific). qRT-PCR was performed in a 10-μl reaction containing 5 μl of SYBR Green PCR Master Mix, 4 μl of each primer mix (Table 1), 50 ng of template cDNA. The thermal cycling conditions consisted of an initial denaturation at 95°C for 5 min, followed by 40 cycles of denaturation at 95°C for 30 s, annealing at 60°C for 30 s, and extension at 72°C for 45 s, and a final extension step at 72°C for 5 min.
The detected expression of selected transcripts was measured using the absolute quantification method. We prepared standard curves for each target gene (0.01–10 ng μl−1) in order to quantify each genes expression relative to a standard internal control gene. Cycle threshold (CT) value of each gene relative to the internal control gene was used to estimate gene expression in RNA concentration values of ng μl−1 [42]. Triplicate reactions were used for each sample.
Ubiquitin 1 and Tubulin alpha were used as internal reference genes, with primer sets UBi-IF (5′-TTT CTT CCT CAA CTT CAC TTG TAT CC-3′), UBi-IR (5′-TGG TCA TAG GCT GTT CGA TCA C-3′), α-tub-F (5′-CTG CAA GGG TTC TTG GTG TTC-3′) and α-tub-R (5′-GAT AGG CGT TCC AGT AAC AAC GA-3′), respectively. Standard curves for each gene were examined in the amplification plot and the standard curve plot was prepared in ABI 7500 software v.2.0.6. Reaction efficiency, R square and slope values were calculated by the ABI 7500 software v.2.0.6 program (Table 3) and were used to determine the copy number of infection-related RNA in each sample.
Unigene | Slope | −1/slope | E | E (%) |
---|---|---|---|---|
U352 | −4.69701 | 0.212901 | 1.159017 | 115.9 |
U2265 | −4.99484 | 0.200206 | 1.148863 | 114.9 |
U27316 | −4.17641 | 0.23944 | 1.180534 | 118.1 |
U75775 | −1.01071 | 0.989403 | 1.985363 | 198.5 |
U26576 | −1.69178 | 0.591093 | 1.506388 | 150.6 |
U72184 | −4.35679 | 0.229527 | 1.17245 | 117.2 |
U59125 | −4.19476 | 0.238393 | 1.179678 | 117.9 |
U68165 | −4.67463 | 0.213921 | 1.159836 | 115.9 |
U68593 | −1.68595 | 0.593137 | 1.508523 | 150.8 |
U77887 | −1.32334 | 0.755662 | 1.688406 | 168.8 |
U3869 | −4.3699 | 0.228838 | 1.171891 | 117.2 |
U17275 | −2.41499 | 0.41408 | 1.332449 | 133.2 |
U41653 | −4.77939 | 0.209232 | 1.156072 | 115.6 |
U17606 | −3.94001 | 0.253806 | 1.192349 | 119.2 |
U24969 | −5.796 | 0.172533 | 1.127035 | 112.7 |
WRKY33 | — | — | — | 112.8 |
WRKY70 | — | — | — | 132.5 |
MYBR1 | — | — | — | 119.1 |
JAZ6 | — | — | — | 102.7 |
Table 3.
qPCR efficiency values for Phytoplasma related genes in
4.5 Statistical analysis
Analyses of differential gene expression in asymptomatic Phytoplasma infections of acid lime were performed using the
5. Novel asymptomatic infection biology: results and discussion
Gene expression profiles were determined by qPCR for 15-disease related genes identified previously for infections of “

Figure 2.
Surface NMDS ordinations of differential gene expression from samples of “
Unigene ID | Transcript | Uninfected expression (ng μl−1) | Asymptomatic expression (ng μl−1) | Differential expression | Functional characterisation |
---|---|---|---|---|---|
U24969 | Probable LRR receptor-like serine/threonine-protein kinase | 11.22 | 13.67 | NS (p = 0.321) | ABA-signalling |
U72184 | Zinc finger A20 and AN1 domain-containing stress-associated protein 3 | 8.15 | 7.82 | NS (p = 0.537) | Abiotic stress tolerance |
U59125 | CRT/DRE binding factor | 12.32 | 7.76 | ↓ (p = 0.050) | Abiotic stress tolerance |
U27316 | NAC domain-containing protein 71 | 32.74 | 15.30 | ↓ (p = 0.011) | Cell Replication |
U352 | Beta-galactosidase 3 | 9.74 | 8.47 | ↓ (p < 0.001) | Energy production |
U68165 | Ent-copalyl diphosphate synthase | 7.54 | 7.38 | NS (p = 0.664) | Growth regulation |
U77887 | Gibberellin 2-oxidase | 10.24 | 8.20 | NS (p = 0.195) | Growth regulation |
U41653 | LRR receptor-like serine/threonine-protein kinase GSO1 | 21.27 | 18.40 | NS (p = 0.140) | Growth regulation |
U26576 | Mitogen-activated protein kinase 1 | 27.04 | 22.42 | NS (p = 0.118) | Immune response |
U68593 | Cyclic nucleotide-gated ion channel 1 | 17.12 | 16.97 | NS (p = 0.918) | Immune response |
U17606 | Brassinosteroid insensitive-1-associated receptor kinase | 20.04 | 21.12 | NS (p = 0.453) | Immune response |
U3869 | Jasmonate ZIM domain-containing protein 6 | 15.42 | 15.73 | NS (p = 0.659) | JA-signalling |
U17275 | Phytochrome-interacting factor 3 | 6.42 | 6.52 | NS (p = 0.623) | Light response |
U2265 | Amino acid transporter | 7.85 | 8.38 | NS (p = 0.051) | Protein production |
U75775 | Nitrite reductase | 17.27 | 12.58 | ↓ (p = 0.001) | Protein production |
Table 4.
Functional characterisation of DEGs expressed in response to infection by “
Significant differences were tested by students T test.
The genes MYBR, JAZ6, WRKY37 and WRKY70 were targeted for amplification from samples from both Oman and Brazil (Alves et al. unpublished). MYBR gene expression was not significantly different between Brazil and Oman (F = 3.725, P = 0.067 Figure 3a);

Figure 3.
Differential gene expression of disease-related genes amplified in Brazilian (asymptomatic) and Omani (symptomatic) acid lime trees infected with the Phytoplasma “
Disease symptoms are, taken at their most literal, an observable change in host homeostasis in response to the presence of a pathogen. The mechanism underlying symptoms (or lack thereof) within the host plant is broad, but mostly resides in genetic changes (host immune response, genomic mutations, RNA silencing) in either the host or pathogen. The nature of asymptomatic infections is complex and poorly understood. Some may express pathogenesis genes at a lower level and be kept in the host without causing overt symptoms [46].
We examined a group of host plant (
Certain genes related to stress tolerance, cell replication and energy production had their expression significantly reduced in infected plants (Table 4). The latter may be the best candidate for a “symptom” of these “silent” infections: Phytoplasma are obligate biotrophic organisms and their parasitism may be through host ATP-synthase subunits [22]. When comparing these results with those of [26], the stress tolerance gene also shows a significant reduction in expression in symptomatic infected lime plants. However, cell replication and energy production genes were significantly deregulated in the asymptomatic infections, which was distinct to the symptomatic infection in [26]. This may be one of the first accounts of a significant alteration of gene expression by a host plant infected by an asymptomatic plant pathogen. The demonstrated response by the plant clearly indicates that these are not truly “silent” infections, and perhaps opens up new routes for detecting these pathogens.
Previous research into symptomatic infections of “
A distinct host plant genomic response to infection by this asymptomatic infection has significant implications for the diseases’ insect vectors. Management strategies for insect-vectored pathogens specifically target the vector-plant interactions, relying on monitoring and suppressing these vectors in order to reduce the frequency and severity of disease outbreaks [49]. Many vector-borne plant diseases alter host plant phenotypes in ways that can influence their vectors biology and behaviour [50, 51, 52], with significant implications for disease transmission.
Infected plants are often better for their vectors than uninfected in terms of vector growth rates, reproduction and longevity [17, 53]; although the opposite is certainly true in some pathosystems [53] and some vectors actively avoid infected hosts that represent inferior hosts [54]. We have previously demonstrated that an asymptomatic infection results in significant increases in vector life history traits (reproduction and growth rates) than with a symptomatic infection [17]. In future studies, the distinct expression profile detected within the plant host here could be usefully explored in relation to differential gene expression in the insect host, in order to fully understand this vector-host-pathogen complex [16, 23].
We also specifically consider differences between two agricultural loci—the Middle East and South America—by examining a gene set directly related to the plant-pathogen (Phytoplasma) interaction. Four genes (JAZ6, MYBR, WRKY70 and WRKY33) are modulated during Phytoplasma infection in lime trees (Figure 3). Interestingly, an inverse expression profile for this gene set could be verified by comparing infected lime trees from Brazil and Oman (Figure 3). While JAZ6 and WRKY33 are up-regulated in infected (symptomatic) Omani samples, the same genes present lower gene expression in infected (asymptomatic) Brazilian samples (Figure 3). The same inverse relation can be verified for WRKY70, which is down-regulated in infected Omani samples, but presents a significantly higher expression in Brazilian samples (Figure 3). Such expression profiles of this gene set represent a signature of symptomatic and asymptomatic Phytoplasma infected plants, which can be used to distinguish earlier Phytoplasma infections. This specific expression profile can be associated to the distinct “
Finally, we should also address the previously reported benefits of asymptomatic infections for their host plants. Asymptomatic infections may result in induced systemic resistance (ISR) [55]: pathogens acquired at low titres elicit a set of systemic plant defences (i.e., oxidative burst, phytoalexins and pathogenesis-related proteins) which prepare hosts to more successfully resist later, more severe infections [56, 57, 58]. The use of ISR to induce resistance in plants by application of exogenous (chemical or organic) inducers, has been used in integrated programs of disease management. Pre-inoculation of sour orange (
6. Conclusions
This study has addressed two key questions regarding the nature of asymptomatic infections: [1] that being invisible or “silent” infections (and the consequent reliance on molecular tools for detection) makes them inherently challenging to monitor; and [2] that this organism interacts with its plant host in a distinct manner that we have observed in the present study. The key findings are that asymptomatic infections from three case studies all demonstrate high rates of false-negative discovery; meaning that repeated testing of the same plant can give both negative and positive results and that a single positive result is taken as meaning the plant is infected. We also demonstrate that infection by the Phytoplasma “
The Phytoplasma “
As “
Acknowledgments
This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001.
SLE has been the beneficiary of CNPq productivity grants (grant nos. 309221/2013-7 & 309845/2016-5).
The authors would like to thanks Vale S.A. for financing of the project.
Thanks to SQU for partial support of the work through the grant EG/AGR/CROP/16/01.
Conflict of interest
The authors declare no conflict of interest.