Recent research accomplishments on early detection of Xylella fastidiosa outbreaks in the Mediterranean Basin

Summary. Xylella fastidiosa is a major transboundary plant pest, causing severe socio-economic impacts. Development of preventive strategies and methods for surveillance, early detection, monitoring, and accurate diagnosis of X. fastidiosa and its vectors, are keys to preventing the effects of this plant pathogen, and assist timely eradication or optimisation of containment measures. This review focuses on approaches for early detection of X. fastidiosa in the Mediterranean Basin, including development of climatic suitability risk maps to determine areas of potential establishment, and epidemiological models to assist in outbreak management through optimized surveillance and targeted responses. The usefulness of airborne hyperspectral and thermal images from remote sensing to discriminate X. fastidiosa infections from other biotic-and abiotic-induced spectral signatures is also discussed. The most commonly used methods for identifying X. fastidiosa in infected plants and vectors, and the molecular approaches available to genetically characterize X. fastidiosa strains, are described. Each of these approaches has trade-offs, but stepwise or simultaneous combinations of these meth-ods may help to contain X. fastidiosa epidemics in the Mediterranean Basin.


INTRODUCTION
Xylella fastidiosa is a plant-associated bacterium that is a major transboundary plant health threat, and is a serious plant pathogen in terms of socioeconomic impacts.The bacterium causes diseases on a wide host range of plants including crops of economic importance in agriculture and forestry, and with cultural and heritage value.Diseases caused by X. fastidiosa include Pierce's Disease (PD) of grapevine, Citrus Variegated Chlorosis (CVC), Almond Leaf Scorch (ALS), and Olive Quick Decline Syndrome (OQDS) (EFSA, 2022).A recent study by the Joint Research Center (JRC) and European Food Safety Authority (EFSA) (Sanchez et al., 2019) has identified X. fastidiosa as the quarantine pathogen with the greatest potential impact in the European Union (EU), in all economic, social, and environmental domains.That study estimated that X. fastidiosa could ultimately cost the EU over €5.5 billion per year due to production losses, and €0.7 billion per year in export losses, since the bacterium has the potential to affect 70% of EU production value of full-productive old (>30 years) olive trees, 13% of almond, 11% of citrus, and between 1 to 2% of grape production, in a full spread scenario across the EU.
Early detection of X. fastidiosa is important for taking timely measures for its eradication, containment or management (Almeida 2016;Zarco-Tejada et al. 2018).Consequently, development of efficient methods and strategies for surveillance, early detection and monitoring of X. fastidiosa have been the foci of several EU research projects such as XF-ACTORS (https://www.xfactorsproject.eu/)and POnTE (https://www.ponteproject.eu/), and grants by the EFSA.A major effort is currently being made in the EU to detect and assign X. fastidiosa strains from outbreaks to subspecies and, within them, to Sequence Types (STs).This is to infer relationships between ST and host range, and to trace back the possible origins of the introductions.Accurate diagnoses of X. fastidiosa at subspecies levels in the EU is essential for regulatory measures on outbreak response and management (e.g., removal of plants and replanting) (Regulation EU 2021/1688;EC, 2021).Currently, methods for X. fastidiosa identification are based on the European and Mediterranean Plant Protection Organization (EPPO) diagnostic protocol (EPPO, 2019).
The present review is based on an oral presentation entitled 'Current situation of Xylella fastidiosa impacts in Spain: ongoing research initiatives to understand and tackle this pathogen', which was presented at the 16th Congress of the Mediterranean Phytopathological Union in April 2022, Limassol, Cyprus (Landa, 2022).This review describes research outputs from the framework of the EU projects POnTE and XF-ACTORS for early detection of X. fastidiosa, together with current knowledge reported in X. fastidiosa literature and experienced gained during current EU outbreaks of the pathogen in the Mediterranean Basin.It is not intended, however, to provide a detailed state of the art summary on this topic.Topics covered include development of climatic suitability risk maps, how they can assist to determine areas of potential X. fastidiosa establishment, and how epidemiological models and surveillance strategies can help to track the outbreaks of X. fastidiosa and their potential spread.Other topics include the usefulness of remote sensing to support surveillance and monitoring of areas affected by X. fastidiosa outbreaks, and how to discriminate X. fastidiosa infections from other biotic and abiotic-induced stresses.Also provided are an extended description of the most commonly used methods to identify X. fastidiosa in infected plants and vectors, molecular approaches available to characterize X. fastidiosa strains at subspecies and ST level, and future directions for efficient molecular diagnostics and genetic characterization of X. fastidiosa strains.
Although the procedures for field sampling of plant material, in places of production and in consignments, as well as laboratory sample preparation, are all essential for obtaining reliable diagnostic results, description of these procedures is beyond the scope of this review.Detailed information on these aspects can be found in PM 7/24 Diagnostics for Xylella fastidiosa (EPPO, 2019), PM 3/81 Inspection of consignments for Xylella fastidiosa (EPPO, 2022a), PM 3/82 Inspection of places of production for Xylella fastidiosa (EPPO, 2022b), Methodologies for Sampling of Consignments ISPM 31 (IPPC, 2008), andin D'Onghia et al. (2022) and Loconsole et al. (2021).

CLIMATIC SUITABILITY RISK MAPS TO ESTIMATE REGIONS FOR POTENTIAL ESTABLISHMENT OF
XYLELLA FASTIDIOSA Xylella fastidiosa occurs in a variety of climatic zones, although it is particularly prevalent in the tropics and sub-tropics.The pathogen is also found in areas where climatic conditions are similar to those prevailing in Mediterranean climate zones, such as California, and in various European regions including Corsica in southern Italy, the Côte d'Azur in France, southern Portugal and the Balearic Islands and the Valencian Community in Spain.Records of diseases caused by X. fastidiosa also occur from much colder climates, such as New Jersey and Washington in the United States of America and the Niagara Peninsula, southern Ontario, British Columbia, Saskatchewan and Alberta in Canada (EFSA, 2015).
Different approaches have been used to infer areas with favourable climatic conditions for X. fastidiosa.Feil and Purcell (2001) used isotherms of winter minimum temperatures to propose the following severity levels and thermal ranges (minimum winter temperatures) for PD in grapevine: severe impact, >4.5°C; moderate, from 1.7 to 4.5°C; occasional, from 1.7 to -1.1°C; and rare, <-1.1°C.However, Anas et al. (2008) established areas at risk for PD at much lower temperatures, based on the number of days with minimum temperature below -12.2ºC or -9.4ºC.Following this criterion of minimum temperatures in winter, most southern European countries have climatic conditions that would allow survival of X. fastidiosa, and these regions overlap with the production areas for several crops relevant to the EU economy, including olive and grapevine.All of these regions where X. fastidiosa has been described in Europe, including the outbreaks in Italy, France, Portugal and Spain, have climatic conditions that are considered favourable for X. fastidiosa survival, demonstrating the validity of this criterion.In contrast, Hoddle (2004) used the CLIMEX model to map the potential distribution of PD, and its Californian vector Homalodisca vitripennis, based on data from Feil and Purcell (2001), and concluded that regions with tropical, semi-tropical, temperate and moderate Mediterranean climates are suitable for both organisms.These additional criteria indicate that most wine-growing regions of southern France, central and southern Spain and Italy have climatic conditions suitable for PD.Conversely, low winter temperatures would exclude this disease from vineyard-growing areas in France, northern Spain, and Italy (Hoddle, 2004).
In 2019, the Plant Health Panel of EFSA evaluated the potential for establishment of X. fastidiosa in the EU.In that study, Köppen-Geiger climate matching revealed that most parts of the EU could be suitable for establishment of the bacterium, excluding only some higher altitude and northern EU regions.However, analyses using species distribution ensemble modelling identified areas in southern Europe to be at more risk, mainly in southern regions of Portugal, Spain, France, Italy, Greece, Malta, and Cyprus (EFSA, 2019), as well as coastal regions of Morocco, Algeria, Tunisia, Libya, Turkey, Syria, and Israel within the Mediterranean Basin (POnTE project, 2019).These results agree with those of Cardone et al. (2022), who evaluates risks of establishment and spread of X. fastidiosa in the EU, the Balkans and the Middle East and North Africa regions.They identified Malta, followed by Lebanon, Greece, Portugal, Algeria, Spain, Turkey, Egypt, Morocco, and Albania, as the most vulnerable countries with respect to climate suitability.The North European and Arabian Gulf countries were less vulnerable to the spread of the bacterium.When developing these models at pathogen subspecies level, it has been estimated that X. fastidiosa subsp.multiplex presents the greatest potential for establishment in the EU, compared with that predicted for subspp.fastidiosa and pauca, with subsp.multiplex able to establish the furthest north in the EU (EFSA, 2019).
Using species distribution ensemble modelling, Arias- Giraldo et al. (2022) determined relationships between sample location for X. fastidiosa with associated regional environmental variables for Andalusia, Southern Spain; the area with the largest olive production in the world.They analyzed ecological requirements for the three main X. fastidiosa subspecies, and estimated that the Eastern part of Andalusia was at the greatest relative risk.
Future directions for this research include development of modelling tools that integrate the main components of X. fastidiosa epidemics at different spatial and temporal scales, including the effects of environmental drivers (increased precision of weather and land use, and inclusion of insect vector distribution databases), and of climate change.These models will allow prioritization of surveillance programmes for X. fastidiosa, based on risk levels in areas free of the pathogen or with recent outbreaks (Arias-Giraldo et al., 2022).

EPIDEMIOLOGICAL MODELS TO ASSIST OUTBREAK RESPONSE PROGRAMMES FOR XYLELLA FASTIDIOSA
After an outbreak of X. fastidiosa in a region, official surveys are implemented, initially to delimit the infested area, and then to maintain the pest-free status of a surrounding buffer zone (Commission Implementing Regulation (EU) 2020/1201; EC, 2020).Surveillance is a large proportion of the resources required in outbreak response programmes, so several methods have been developed for optimizing survey efficiency.A sequential adaptive delimiting survey for X. fastidiosa with increasing spatial resolution was evaluated, using occurrence data of X. fastidiosa in Alicante, Spain (Lázaro et al., 2021).Inspection and sampling intensities were adjusted using an optimization algorithm, considering the results obtained in a previous coarse spatial resolution, with three-phase or two-phase designs.With this sequential adaptive survey strategy, it was possible to delimit the distribution of X. fastidiosa in the study area, with substantial reduction of the total number of samples to be collected and tested.With some adjustments, this approach could also be used to optimize delimiting surveys in other X. fastidiosa outbreaks in Europe and elsewhere.
Effects of climatic and spatial factors on the geographic distribution of X. fastidiosa in Lecce, Italy, and Alicante, Spain, were studied with Bayesian hierarchical models (Cendoya et al., 2020).These two outbreaks represent different, but simple, epidemiological scenarios, one with OQDS, caused by X. fastidiosa subsp.pauca ST53, in Lecce (Morelli et al., 2021;Saponari et al., 2013), and other with ALS, caused by X. fastidiosa subsp.multiplex ST6, in Alicante (Landa et al., 2020;Marco-Noales et al., 2021).The climate covariates presented low variabilities and were not relevant in the resulting models, so they were not related with the distribution of X. fastidiosa in the study areas.These results indicate that climate is not likely to stop the spread of the pathogen from outbreaks to adjacent areas.Furthermore, the models were mainly driven by the spatial components, so probability of X. fastidiosa presence substantially increased with proximity to infested area.Overall, these results highlight the importance of implementing control measures based on reduction of inoculum and vector populations, to limit further disease spread from outbreak areas.
In epidemiological models, spatial dependence is often considered as direction-invariant and uniform (i.e., isotropic and stationary).However, these assumptions do not hold when there are elements limiting disease spread.This is the case when geographic barriers are present, or control measures are implemented to contain disease spread.Using the outbreak in Alicante, Spain, as a case study, X. fastidiosa occurrence data were analyzed through stationary and nonstationary models (Cendoya et al., 2022).The nonstationary models considered a cordon sanitaire surrounding the infested area, where host plants were removed and measures applied to impede disease spread.The mean value of the spatial range of the stationary model indicated that host plants closer than 4 km to the infested area would be at risk of X. fastidiosa infections.Consequently, the plant health authority increased by 10 km the minimum width of 2.5 km established by the Regulation (EU) 2020/1201 (EC, 2020) for buffer zones surrounding infested zones (Generalitat Valenciana, 2020).The nonstationary models with the cordon sanitaire resulted in a substantial reduction of the probability of X. fastidiosa presence outside the infested area.Nevertheless, these models assume that barriers are completely impermeable to pathogen spread, which is not realistic for those causing most plant diseases.Further methodological research is thus required to consider realistic barriers with different levels of permeability.

AIRBORNE HYPERSPECTRAL AND THERMAL IMAGES FROM REMOTE SENSING TO DETECT XYLELLA FASTIDIOSA INFECTED HOST PLANTS
Remote sensing studies on X. fastidiosa have manily focused on development of algorithms for early detection of symptoms induced by infections either using unmanned (e.g., Castrignanò et al., 2021) or manned (e.g., Zarco et al., 2018;2021b) aerial vehicles.Zarco-Tejada et al. (2018) studied the Italian X. fastidiosa outbreak, evaluating more than 7000 olive trees using high-resolution hyperspectral and thermal imagery.This revealed that pre-visual detection of X. fastidiosa-infected trees was feasible using radiative transfer modelling and spectral plant-trait retrievals from imaging spectroscopy and thermal data.Their study showed that changes in specific plant functional traits detected using hyperspectral and thermal imagery could reveal X. fastidiosa infections occurring months before symptoms were visible.Important inputs identified for X. fastidiosa detection included spectral ratios in the blue region, plant traits such as leaf anthocyanin and carotenoid pigment content estimated using a radiative transfer model inversion, tree temperature, and estimates of solar-induced chlorophyll fluorescence emission.Later Poblete et al. (2020) used highresolution hyperspectral and thermal imagery to assess performance of spectrally constrained machine-learning algorithms to measuring multispectral bandsets, selected from the original hyperspectral imagery, that were compatible with large-scale monitoring from unmanned platforms and a manned aircraft, as well as the contribution of solar-induced chlorophyll fluorescence (SIF) and the temperature-based Crop Water Stress Index (CWSI) retrieved, respectively, from hyperspectral and thermal imaging.This research demonstrated that large-scale X. fastidiosa monitoring could be supported using airborne platforms carrying multispectral and thermal cameras with limited numbers of spectral bands (e.g., six to 12 bands with 10 nm bandwidths), as long as the bands were selected for their sensitivity to distinguish X. fastidiosa symptoms.
Although these studies have shown that spectral screening methods can detect non-visual symptoms of early infection by X. fastidiosa, and can help prevent pathogen spread, the subtle pathogen-induced host physiological alterations detected by imaging spectroscopy can be entangled with dynamics of abiotic stresses.Zarco-Tejada et al. (2021b) used airborne spectroscopy and thermal scanning to monitor different EU areas covering more than one million trees, including different host species (olive and almond), affected by two vascular pathogens (X.fastidiosa and Verticillium dahliae), and comprising a gradient in water stress levels.This study demonstrated the existence of divergent pathogen-and host-specific spectral pathways, that could disentangle biotic-induced symptoms, and showed that uncoupling biotic and abiotic spectral dynamics diminished uncertainty in X. fastidiosa detection to less than 6% across different hosts (almond and olive).The study also assessed these deviating pathways against V. dahliae, another vascular pathogen that produces symptoms analogous to X. fastidiosa, and showed that the divergent routes remained pathogen-and host-specific, with detection accuracies exceeding 92% across the pathosystems.
Recent studies have also correlated chemical compounds closely associated with X. fastidiosa infection in olive plants (i.e., higher contents of malic acid, formic acid, mannitol and sucrose and lower contents of oleuropein; Jlilat et al., 2021) with hyperspectral signals, by identifying specific wavelength packages also associated with bacterial infection.This combined spectro-metabolomic approach may represent a new paradigm for reliable detection of X. fastidiosa by remote sensing at the early stages of bacterial infection (Ahmed et al., 2021;A.M. D'Onghia, personnal communication).
The research described above has shown that early detection of X. fastidiosa-induced symptoms is feasible with high-resolution hyperspectral and thermal imagery and physically based plant trait retrievals.New research (Poblete et al., in press) has demonstrated that high resolution multispectral satellite imagery failed to detect early symptoms of infection, but was able to monitor medium and advanced severity levels at large scales.Results from these studies are essential for implementation of effective management of plant diseases, using airborne, drone and satellite based remote sensing technologies.These imaging methods could also contribute to future operational monitoring of infected crop areas at large scales, well beyond what is possible from field surveys and laboratory analyses (Zarco-Tejada et al., 2021a).

MOLECULAR DIAGNOSTIC TESTS FOR EARLY DETECTION AND SUBSPECIES DETERMINATION OF XYLELLA FASTIDIOSA
The EPPO Diagnostic protocol PM 7/24 (4) for X. fastidiosa is the most complete source for current screening tests available for detection of this bacterium and subspecies determination (EPPO, 2019), which includes a detailed description of each screening test with validation data.Among all the screening tests described, those based on molecular approaches are the most sensitive and rapid for X. fastidiosa detection and will be the focus of this review.
Most molecular tests used for X. fastidiosa diagnoses are based on conventional end-point PCR or real-time PCR (qPCR).However, for some of the PCR protocols, if the amplicon product is sequenced it can also provide information for subspecies assignation.The Commission Implementing Regulation (EU) 2021/1688 (EC, 2021) indicates which tests from those described in the EPPO Diagnostic protocol PM 7/24 should be used for official surveys and identification of X. fastidiosa and its subspecies.
There are several conventional PCR tests for X. fastidiosa diagnoses, and one of the most commonly used is that developed by Minsavage et al. (1994).This test is based on amplification of the RNA polymerase sigma-factor 70 (rpoD).A search on Google Scholar using 'Minsavage and Xylella fastidiosa' retrieved more than 800 publication records.This test can also be used to assign X. fastidiosa at the subspecies level, by sequencing the rpoD amplicon, and comparing its sequence using the Basic Local Alignment Search Tool (BLASTN; http:// www.ncbi.nlm.nih.gov/)available at the National Center for Biotechnology Information, against the RefSeq Genome database of Xylella fastidiosa (taxid: 2371) as the search organism.This tool also allows a distance tree of results to be obtained, that clusters the target sequence with those rpoD sequences included in the reference genomes of different strains of X. fastidiosa belonging to different subspecies (Figure 1).
Other conventional PCR diagnostic tests are based on the gene encoding the β-subunit polypeptide of the DNA gyrase (gyrB).Although this methodology is not included in the EPPO Diagnostic protocol PM 7/24, it was used for developing a mini sequencing or singlenucleotide primer extension (SNuPE) approach for the multiplex amplification of six X. fastidiosa gyrB sequences targeting subspp.fastidiosa, multiplex and sandyi, and three genotypes within subspecies pauca present in the EU territory, and including strains from coffee and citrus from Brazil, and the type isolate infecting olive in Italy (Montes-Borrego et al., 2015;Saponari et al., 2016).
Several qPCR tests are available and have been validated at different laboratories (EPPO, 2019), including tests described by Harper et al. (2010), Francis et al. (2006), Ouyang et al. (2013), andLi et al. (2013).The target sequences for these tests are, respectively, the 16S rRNA processing RimM protein, the hypothetical protein HL gene, the cobalamin synthesis protein-coding gene, and the 16S rRNA.Because of their greater analytical sensitivity than other molecular tests, the use of qPCR is recommended for detection surveys to substantiate pest freedom in areas where X. fastidiosa is not known, and for asymptomatic plants (EPPO, 2019).These qPCR tests have been widely used in studies assessing distribution and host range of X. fastidiosa in Europe (e.g., Saponari et al., 2013;Jacques et al., 2016;Moralejo et al., 2020;Olmo et al., 2021), potential insect vectors of X. fastidiosa (e.g., Elbeaino et al., 2014;Cavalieri et al., 2019;Cunty et al., 2020;Moralejo et al., 2020;Marco-Noales et al., 2021), and in remote sensing studies (e.g., Zarco-Tejada et al., 2018;Poblete et al., 2020;Zarco-Tejada et al., 2021b;Camino et al., 2022)   Where a positive result is obtained in areas outside of demarcated areas (i.e., pest-free areas), the Commission Implementing Regulation (EU) 2020/1201 (EC, 2020) indicated that presence of X. fastidiosa must be confirmed by two tests targeting different parts of the bacterial genome, as recommended by EPPO (2019).To facilitate diagnosis of X. fastidiosa with two tests, Bonants et al. (2019) implemented a triplex qPCR test based on the primers and probes included in Harper qPCR and Ouyang qPCR tests, and an additional primer pair and probe for internal controls.This test facilitates two diagnostic tests simultaneously, saving time and resources, and can provide the same analytical sensitivity as each test independently (Bonants et al., 2019).
Results from test performance studies (TPS) and proficiency tests (PT) performed in the frameworks of XF-ACTORS and POnTE, Euphresco PROMODE projects, have compared the performance characteristics of qPCR tests when used with plant or insect mockinoculated matrices, and these results are available at the EPPO Database on Diagnostic Expertise (https:// dc.eppo.int;EPPO, 2023).Results from these validation tests have indicated that all the qPCR diagnostic protocols were robust, and were suitable for the diagnoses of X. fastidiosa in plant and insect materials.However, although most qPCR protocols produced good performance values, their analytical sensitivity was slightly different when using mock-inoculated samples.A recent study has also shown greater analytic sensitivity of the Harper qPCR test compared to the Francis qPCR test, when using DNA samples extracted from naturally infected almond trees (Anguita-Maeso et al., 2021).
For X. fastidiosa subspecies assignment, the Commission Implementing Regulation (EU) 2020/1201 (EC, 2020) determines Multilocus Sequence Type (MLST) analysis to be used (Yuan et al., 2010), especially for new records (i.e., for a new outbreak or new hosts).This test is based on amplification and sequencing of seven housekeeping gene (HKG) loci (cysG, gltT, holC, leuA, malF, nuoL, petC).Analysis of rpoD and malF or cysG and malF sequences have been shown to be sufficient for assignment of sample pathogens to subspecies (EPPO, 2019); whereas the sequences of the seven loci are needed to assign samples into STs.Originally, MSLT analysis was designed to be used with DNA extracted from X. fastidiosa pure cultures (Yuan et al., 2010), and when used with plant DNA samples is partly efficient.To improve sensitivity, Cesbron et al. (2020) developed a direct nested-MLST assay for plant and insect extracted DNA, based on the same seven targeted HKG loci as those used in the Yuan et al. (2010) test.This nested-MLST assay improved detection threshold by 100 to 1000 times, compared to conventional MLST.Using this nested-MLST assay, plants that were previously not considered hosts (giving high or inconclusive Ct values in qPCR assays) tested positive, and novel alleles were revealed in France.In samples from Spanish outbreaks, the nested-MLST assay allowed to identify the X. fastidiosa subspecies or ST infecting new hosts in Europe at that time (Cesbron et al. 2020).This nested-MLST assay has been used to type X. fastidiosa positive samples to the subspecies and ST level in the outbreaks in Spain.These include three X.fastidiosa subspecies and four STs in the Balearic Islands: X. fastidiosa subsp.fastidiosa ST1 and X. fastidiosa subsp.multiplex ST7 in Mallorca, X. fastidiosa subsp.pauca ST80 in Ibiza, and X. fastidiosa subsp.multiplex ST81 in Mallorca and Menorca (Olmo et al., 2021).Only a single subspecies and ST (i.e., X. fastidiosa subsp.multiplex ST6) was identified in the outbreak in Alicante (Marco-Noales et al., 2021).Some qPCR tests have been developed to specifically detect subspecies of X. fastidiosa (e.g., the tests of Burbank et al., 2018;Dupas et al. 2019;Hodgetts et al., 2021).These tests are based on Taqman probes, designed to specifically and simultaneously target one or several X. fastidiosa subspecies.The advantage of these protocols is, while the presence of the bacterium is detected, even at low concentration, the subspecies is also defined.The Burbank qPCR test was used by Moralejo et al. (2020) to track the X. fastidiosa DNA inside growth rings of infected almond trees, through dendrochronological analysis.The protocol allowed differentiation between subsp.fastidiosa and multiplex in rings of 25 trees, with nine infected by subsp.fastidiosa, and 19 infected by subsp.multiplex, and three trees had mixed infections.This qPCR test combined with the conventional and nested-MLST tests (described above) enabled dating infections back to 1998 for X. fastidiosa subsp.fastidiosa ST1, and before 2000 for X. fastidiosa subsp.multiplex ST81 (Moralejo et al., 2020), indicating that the bacterium was introduced to the Balearic Islands earlier than previously thought.
Time and portability are also important factors in pathogen diagnoses, especially for quarantine plant pathogens (Aglietti et al., 2019).Isothermal nucleic acid amplification tests have been developed for X. fastidiosa field diagnoses.These included loop-mediated isothermal amplification (LAMP) based on primers developed by Harper et al. (2010) that were modified by Yaseen et al. (2015), and the AmplifyRP® XRT+ test, using isothermal amplification based on recombinase polymerase amplification (RPA) (Kersting et al., 2014), based on the protocol of Li et al. (2016).Both tests have kits and specific portable devices that are commercially available, but other equipment can also be used.For instance, the AmplifyRP® XRT+ test uses the battery powered Ampli-Fire® Portable Fluorometer device, that is easy to transport, and does not require DNA extraction, since the test can be performed with the crude plant macerate and the amplification takes 20 min.This test is easy to use by untrained laboratory staff, and is well adapted to the field for preliminary on site screening, as it requires no particular expertise (Cesbron et al., 2022).
A constraint of these tests is that detection limits are greater than for qPCR tests.Nevertheless, negative or doubtful results can be verified with another, more sensitive test.During a field campaign in Mallorca, Spain, almond trees in 14 orchards under rainfed and irrigated conditions were visually scored for the presence of ALS.A total of 356 symptomatic and symptomless trees were sampled and analyzed using the AmplifyRP® XRT+ test and the AmpliFire® device by two operators in less of 5 days (Camino et al., 2022).When comparing results of this test with that of the Harper qPCR test using the same almond plant branch samples, 92.8% agreement for infected samples was obtained for the two methods.The samples that were negative by the AmplifyRP® XRT+ test showed cycle thresholds (Cts) >31 in the Harper qPCR test (Landa et al., unpublished).
Digital PCR (dPCR) is an innovative PCR tool based on partitioning of PCR reagents and DNA samples into thousands of droplets or microchambers (depending on thermocycler brand), that allows increased precision, sensitivity and absolute quantification without requirements for reference samples or standard curves.Detection of phytopathogenic bacteria by droplet PCR has provided successful results for pathogen diganoses, due to its detection efficiency at low pathogen concentrations and tolerance to PCR inhibitors (Dreo et al. 2014).Dupas et al. (2019) developed a droplet ddPCR protocol based on the Harper qPCR test.Both protocols showed the same detection limits for olive, Polygala myrtifolia and Rosmarinus officinalis, but the Harper qPCR test allowed better detection of 0.5 log for Lavandula angustifolia, and droplet dPCR allowed better detection of 0.5 log for Quercus ilex.
Investigation of pathogen strain origins in a new disease outbreaks requires whole genome sequencing (WGS) of pure bacterial cultures to resolve phylogenetic reconstruction.This is a challenge for X. fastidiosa due to its fastidious nature.For all the available nucleic acid based amplification methods described above for the detection of X. fastidiosa, the target sequence is a single locus, making the assays prone to false-positive or falsenegative results (Bonants et al., 2019).High throughput Next Generation Sequencing (NGS) technologies allow sequencing of total DNA in samples, potentially pro-viding detection of X. fastidiosa and characterization to subspecies and strain levels, without requirement for pathogen cultivation.NGS based on Illumina (Bonants et al., 2019;Román-Reyna et al., 2022) or Oxford Nanopore technologies (Johnson et al., 2022) have been explored for fast detection and identification of X. fastidiosa.The potential advantages and disadvantages of both of these technologies are beyond the scope of this review.
Using Illumina sequencing, Bonants et al. (2019) analyzed DNA extracts, by WGS, for presence of X. fastidiosa in artificially inoculated host plants and from naturally infected plants sampled or intercepted in different European countries.In all samples, even in samples with low infection levels, some DNA reads specific for X. fastidiosa were detected, and in several cases the pathogen could be identified to the subspecies level.Only for one sample was the whole genome assembled and the ST determined.Samples in which more X.fastidiosa genomic information was obtained corresponded to those with low Ct values (i.e., high X.fastidiosa titres).Thus, alinear relationship is found between the Log number of X. fastidiosa reads obtained by NGS and the Cts from Harper and Ouyang qPCR tests, and the time for positivity in a LAMP assay (Figure 2).Similarly, Anguita-Maeso et al.  2021) developed a metagenomics pipeline using in-house short read Illumina sequencing to analyze samples from different plant species originating from Europe and the United States, and naturally infected by X. fastidiosa.They identified X. fastidiosa to the strain level in single and mixed infected plant samples at concentrations of 1 pg of bacterial DNA per gram of plant tissue, and in samples previously considered inconclusive when using qPCR (Ct >35), the protocol was able to confirm infection by X. fastidiosa.These results indicate that using the NGS approach, only in cases where DNA has been extracted from highly infected material, and where high genome coverage is used during sequencing, is possible to identify X. fastidiosa at the strain level.
To overcome this limitation, we have developed a Targeted Sequence Capture Enrichment (TSCE), in combination with High Throughput Sequencing (HTS).This uses an Illumina platform to provide adequate bacterial genome information for identification of X. fastidiosa at strain level (Velasco-Amo et al., 2021).Results indicated that although <0.25% of X. fastidiosa reads were detected by direct WGS of host DNA, this was increased by 41-73% when using the TSCE-HTS approach, for indi-vidual samples or in mixtures of up to four plant samples.The protocol was also validated using a range of insect and plant samples from different naturally infected host plants, and with levels of X. fastidiosa ranging from very high (CT >20) to close to the detection limit for Harper qPCR assay.More importantly, 80-100% of the 140 target sequences used to design the baits were captured, which allowed phylogenetic reconstruction of the X. fastidiosa strains infecting the samples, and identifying these at strain level (Landa et al., 2021).This methodology may be useful for studies of X. fastidiosa introductions at outbreak stages, since a limited number of genetic markers do not provide sufficient phylogenetic resolution to determine dispersal paths or relationships among strains that are of biological and quarantine relevance.
to outline examples of their usefulness.
(2021) found a linear relationship between the Ct values obtained for the Harper and Francis qPCR tests and the Log of X. fastidiosa reads.Román-Reyna et al. (

ACKNOWLEDGEMENTS
Some of the research presented in this review was funded by the following projects: BeXyl (Beyond Xylella, Integrated Management Strategies for Mitigating Xylella fastidiosa impact in Europe; grant ID 101060593, from European Union's Horizon Europe 'Food, Bioeconomy Natural Resources, Agriculture and Environment' Programme); XF-ACTORS (Xylella fastidiosa Active Containment Through a Multidisciplinary-Oriented Research Strategy; grant 727987, from the European Union's Horizon 2020 Framework Research Programme); POnTE (Pest Organisms Threatening Europe; grant ID 635646, from the European Union's Horizon 2020 Framework Research Programme); E-RTA2017-00004-C06-02 (Desarrollo de estrategias de erradicación, contención y control de X. fastidiosa en España) from 'Programa Estatal de I+D+I Orientada a los Retos de la Sociedad of the Spanish Government AEI-INIA Spain' and the Spanish Olive Oil Interprofesional; Project P18-RT-4184 from Junta de Andalucia and the European Regional Development Fund; and the Intramural Project 201840E111 and the Thematic Interdisciplinary Platform on X. fastidiosa (PTI Sol-Xyl) from CSIC.

Figure 2 .
Figure 2. Linear regressions between Log [Xylella fastidiosa reads] obtained by next generation sequencing (NGS) and Ct values from quantitative polymerase chain reaction (qPCR) protocols of Ouyang tetraplex and Harper tetraplex (Bonants et al., 2019), Harper Simplex (Harper et al. 2010), and LAMP test based in Harper et al. (2010).Data were obtained from Table 7 of Bonats et al. (2019), and represent the mean Ct value obtained for each sample.