Renaud Ioos
email: renaud.ioos@anses.fr

Alexandra Puertolas

Camille Renault

Aida Ndiaye

Isabelle Cerf-Wendling

Jacqueline Hubert

Wen Wang

Chen Jiao

Hongye Li

Josep Armengol

Jaime Aguayo

Harnessing the power of comparative genomics to support the distinction of sister species within Phyllosticta and development of highly specific detection of Phyllosticta citricarpa causing citrus black spot by real-time PCR

Keywords: Agricultural Science, Genomics, Molecular Biology, Mycology, Taxonomy Detection, Plant disease, Quarantine, Validation, Comparative genomics, Fungus

publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Harnessing the power of comparative genomics to support the distinction of sister species within Phyllosticta and development of highly specific detection of Phyllosticta citricarpa causing citrus black spot by real-time PCR

INTRODUCTION

The genus Phyllosticta comprises dozens of species with different ecological behaviors; some are endophytes, others are plant pathogens and a few are even saprobes [START_REF] Wikee | A phylogenetic re-evaluation of Phyllosticta (Botryosphaeriales)[END_REF]. Pathogenic species of Phyllosticta affect a broad range of hosts, and are responsible for numerous diseases, including leaf and fruit spots. On citrus, three species-namely P. capitalensis, P. citribraziliensis, and P. paracapitalensis-are described as endophytes [START_REF] Glienke | Endophytic and pathogenic Phyllosticta species, with reference to those associated with Citrus Black Spot[END_REF][START_REF] Guarnaccia | Phyllosticta citricarpa and sister species of global importance to Citrus[END_REF], whereas five species are described as pathogens. P. citricarpa causes citrus black spot (CBS) [START_REF] Kiely | Preliminary studies on Guignardia citricarpa, n.sp.: the ascigerous stage of Phoma citricarpa McAlp. and its relation to black spot of Citrus[END_REF][START_REF] Van Der Aa | Studies in Phyllosticta I[END_REF], P. citriasiana and P. citrimaxima both cause citrus tan spot of Citrus maxima [START_REF] Wikee | A phylogenetic re-evaluation of Phyllosticta (Botryosphaeriales)[END_REF][START_REF] Wulandari | Phyllosticta citriasiana sp. nov., the cause of Citrus tan spot of Citrus maxima in Asia[END_REF], and P. citrichinaensis causes spots and freckle on several Citrus species [START_REF] Wang | Phyllosticta species associated with citrus diseases in China[END_REF]. Recently, [START_REF] Guarnaccia | First report of Phyllosticta citricarpa and description of two new species, P. paracapitalensis and P. paracitricarpa, from citrus in Europe[END_REF] described a new species, Phyllosticta paracitricarpa, which is genetically closely related to P. citricarpa. P. paracitricarpa was isolated from Citrus limon leaf litter in Greek lemon orchards [START_REF] Guarnaccia | First report of Phyllosticta citricarpa and description of two new species, P. paracapitalensis and P. paracitricarpa, from citrus in Europe[END_REF] as well as from lemon fruits in China [START_REF] Wang | Clonal expansion in multiple Phyllosticta species causing citrus black spot or similar symptoms in China[END_REF] and has been shown to be pathogenic to C. sinensis and C. limon after artificial inoculations on detached leaves and fruits [START_REF] Guarnaccia | First report of Phyllosticta citricarpa and description of two new species, P. paracapitalensis and P. paracitricarpa, from citrus in Europe[END_REF][START_REF] Wang | Clonal expansion in multiple Phyllosticta species causing citrus black spot or similar symptoms in China[END_REF]. It was also retrospectively demonstrated that some Chinese isolates causing black spots on mandarin fruits, tentatively named "P. citricarpa subclade II" [START_REF] Wang | Phyllosticta species associated with citrus diseases in China[END_REF] could be re-assigned to P. paracitricarpa according to a multilocus phylogenetic analysis using six markers [START_REF] Guarnaccia | Phyllosticta citricarpa and sister species of global importance to Citrus[END_REF]. The description of this new sister species was based on a few fixed nucleotide polymorphisms within one gene from the core genome (translation elongation factor 1-alpha gene, tef1) and within a region of the rDNA operon (Large Subunit, LSU), combined with some morphological differences with P. citricarpa. In general, the morphological features of P. paracitricarpa in pure culture are very similar to P. citricarpa and it is virtually impossible to differentiate the two species based solely on microscopic traits (EPPO, 2020).

CBS is an important disease outside Europe that causes significant economic losses in orchards. This disease is named after the characteristic symptoms of citrus fruits, i.e., black spots on the citrus peel, although the symptomatology of this disease can be very variable, ranging from hard spots, virulent spots or false melanose spots to freckle spots. This variability in symptoms is the result of the temperature and maturity of the affected fruits (EPPO, 2020). Phyllosticta citricarpa has a wide host range and is able to infect mostly all Citrus spp. (except C. aurantium and hybrids, and C. latifolia), Fortunella spp. and Poncirus spp. Although present in many citrus growing regions, some regions are still considered as disease-free [START_REF] Eppo | EPPO global database[END_REF]. In these regions (or countries) P. citricarpa is generally listed as a quarantine organism [START_REF] Eppo | EPPO global database[END_REF]European Union Commission, 2019). According to the European Food Safety Agency (EFSA, 2014), the main pathway for dispersal and introduction of P. citricarpa is through the trade of citrus fruits and plants for planting [START_REF] Efsa | Scientific opinion on the risk of Phyllosticta citricarpa (Guignardia citricarpa) for the EU territory with identification and evaluation of risk reduction options[END_REF]. For instance, if this pathogen was to be introduced into the European Union (EU), it would be able to become established due to the presence of hosts and favorable climatic conditions for its spread and disease development, as was the case recently in Tunisia [START_REF] Boughalleb-M'hamdi | First report of citrus black spot disease caused by Phyllosticta citricarpa on Citrus limon and C. sinensis in Tunisia[END_REF][START_REF] Galvañ | Climate suitability of the Mediterranean Basin for citrus black spot disease (Phyllosticta citricarpa) based on a generic infection model[END_REF]. While the importation of citrus plants for planting is prohibited by current EU regulations (European Union Commission, 2019), the importation of fruit shipments for consumption is frequent, providing that they are free from P. citricarpa. Despite its pathogenicity toward citrus fruits, the sister species P. paracitricarpa is currently not considered a quarantine pathogen in any region of the world. Therefore, it is necessary to test fruits for the presence of P. citricarpa and a highly specific detection assay enabling a quick response from the analysis lab is required so that citrus shipments may be blocked or released within only a few days.

The current diagnostic protocols for detecting and identifying P. citricarpa include several real-time PCR (qPCR) methods [START_REF] Ahmed | New multiplex conventional PCR and quadruplex real-time PCR assays for one-tube detection of Phyllosticta citricarpa, Elsinoë fawcettii, Elsinoë australis, and Pseudocercospora angolensis in Citrus: development and validation[END_REF][START_REF] Schirmacher | Species-specific real-time PCR for diagnosis of Phyllosticta citricarpa on Citrus species[END_REF][START_REF] Van Gent-Pelzer | A TaqMan PCR method for routine diagnosis of the quarantine fungus Guignardia citricarpa on citrus fruit[END_REF][START_REF] Zajc | Highly specific qPCR and amplicon sequencing method for detection of quarantine citrus pathogen Phyllosticta citricarpa applicable for air samples[END_REF] and conventional PCR (cPCR) methods [START_REF] Baayen | Non-pathogenic isolates of the citrus black spot fungus, Guignardia citricarpa, identified as a cosmopolitan endophyte of woodyplants, Guignardia mangiferae (Phyllosticta capitalensis)[END_REF][START_REF] Peres | Comparison of molecular procedures for detection and identification of Guignardia citricarpa and G. mangiferae[END_REF]. Most of these assays are based on the amplification of a specific region of the internal transcribed spacer (ITS) region of rDNA [START_REF] Bonants | Development and validation of a fast PCR-based detection method for pathogenic isolates of the citrus black spot fungus, Guignardia citricarpa[END_REF][START_REF] Peres | Comparison of molecular procedures for detection and identification of Guignardia citricarpa and G. mangiferae[END_REF][START_REF] Schirmacher | Species-specific real-time PCR for diagnosis of Phyllosticta citricarpa on Citrus species[END_REF][START_REF] Van Gent-Pelzer | A TaqMan PCR method for routine diagnosis of the quarantine fungus Guignardia citricarpa on citrus fruit[END_REF]. However, it has been shown that the ITS is 100% identical in the two sister species P. citricarpa and P. paracitricarpa [START_REF] Guarnaccia | First report of Phyllosticta citricarpa and description of two new species, P. paracapitalensis and P. paracitricarpa, from citrus in Europe[END_REF]. False positive results can therefore be obtained when testing DNA of the non-target species P. paracitricarpa (EPPO, 2020). Such cross-reactions with P. paracitricarpa DNA were also observed with the assay developed by [START_REF] Ahmed | New multiplex conventional PCR and quadruplex real-time PCR assays for one-tube detection of Phyllosticta citricarpa, Elsinoë fawcettii, Elsinoë australis, and Pseudocercospora angolensis in Citrus: development and validation[END_REF] targeting phylogenetic marker MCM7. The method of [START_REF] Zajc | Highly specific qPCR and amplicon sequencing method for detection of quarantine citrus pathogen Phyllosticta citricarpa applicable for air samples[END_REF] is based on the tef1 gene, which should differ between P. citricarpa and P. paracitricarpa by five nucleotide changes [START_REF] Guarnaccia | First report of Phyllosticta citricarpa and description of two new species, P. paracapitalensis and P. paracitricarpa, from citrus in Europe[END_REF]. However, this method was developed and validated in vitro using two strains of P. paracitricarpa, both from the same orchard in Greece. This may be an additional difficulty when designing specific PCR methods targeting quarantine organisms. For example, it has been shown that P. citricarpa exhibits intraspecific polymorphism in some relevant genes frequently used in fungal phylogenetics and taxonomy, such as γ-actin (actA), the glyceraldehyde-3phosphate dehydrogenase (gadph), or the LSU [START_REF] Guarnaccia | First report of Phyllosticta citricarpa and description of two new species, P. paracapitalensis and P. paracitricarpa, from citrus in Europe[END_REF][START_REF] Wang | Phyllosticta species associated with citrus diseases in China[END_REF].

It is a challenge to find diverging regions within the genomes of genetically closely related or cryptic species [START_REF] Dutech | Rapid identification of polymorphic sequences in non-model fungal species: the PHYLORPH method tested in Armillaria species[END_REF][START_REF] Feau | Genome-enhanced detection and identification (GEDI) of plant pathogens[END_REF]. For example, according to [START_REF] Guarnaccia | Phyllosticta citricarpa and sister species of global importance to Citrus[END_REF], a very limited proportion of genes appeared to differ between P. citricarpa and P. paracitricarpa, although a limited number of strains of P. paracitricarpa were included in the study. Indeed, for those particular taxa, frequently used housekeeping genes are not sufficiently polymorphic to be used as targets for highly specific PCR or real-time PCR oligonucleotides. In the case of a species complex, genetic lineages of the same species, or cryptic species, comparative genomics is a powerful means for screening either polymorphic or unique regions in the genomes [START_REF] Bergeron | Genome-enhanced detection and identification of fungal pathogens responsible for pine and poplar rust diseases[END_REF][START_REF] Feau | Improved detection and identification of the sudden oak death pathogen Phytophthora ramorum and the Port Orford cedar root pathogen Phytophthora lateralis[END_REF][START_REF] Pieck | Genomicsbased marker discovery and diagnostic assay development for wheat blast[END_REF][START_REF] Thierry | A genomic approach to develop a new qPCR test enabling detection of the Pyricularia oryzae lineage causing wheat blast[END_REF].

The first objective of this study was to use a set of genomes from P. citricarpa, P. paracitricarpa, and other Phyllosticta species that are pathogenic or endophytic in Citrus so as to assess their phylogenetic relationship. Second, we took advantage of this comparative genomics study to screen polymorphic genomic regions, which could be used as tentative markers to design a specific PCR assay targeting P. citricarpa. Last, a set of diagnostic tools (real-time and conventional PCR) were designed and fully validated for the specific in planta detection of P. citricarpa, allowing it to be differentiated from its closely related sister species, P. paracitricarpa, and from other Phyllosticta species described in Citrus. In this work, a large set of Phyllosticta strains from Citrus were used as references, both for sequencing and for testing, in order to cover insofar as possible the range of natural diversity occurring for these globally distributed species.

MATERIAL AND METHODS

Genomics and phylogenetics of Phyllosticta spp. in Citrus

The genomes of 14 strains representing P. citricarpa (six), P. paracitricarpa (two), P. citriasiana (three), P. capitalensis (one), P. citrichinaensis (one), and Phyllosticta sp. (one) were sequenced (Information S1). In order to take into consideration potential intraspecific diversity within P. citricarpa, strains from different regions of the world were included: Togo, South Africa, Zimbabwe, Tunisia and Malta. Genomic DNA (gDNA) was extracted from monosporic cultures using the GenElute Plant Genomic DNA Miniprep kit (Merck, Lebanon, NJ, USA), following the manufacturer's instructions, after an initial grinding step using lysing Matrix C tubes in a FastPrep24 homogenizer (MP Biomedicals, Santa Ana, CA, USA), with a one-run program at 6.0 U for 1 min. DNA samples were eluted twice in a volume of 50 µL each time. gDNA concentrations were estimated using a Qubit fluorometer (Thermo Fisher Scientific, Illkirch-Graffenstaden, France) prior to genome sequencing. Library construction and paired-end genome sequencing (2 × 150 bp) were performed by GENEWIZ (Azenta Life Sciences, Leipzig, Germany) using an Illumina HiSeq device. Additional genomes from P. citricarpa (11), P. paracitricarpa (three), and P. citribraziliensis (one) were retrieved either from the Joint Genome Institute Genome Portal (https://genome.jgi.doe.gov/portal/) or the National Center for Biotechnology Information (https://www.ncbi.nlm.nih.gov/genome/) (Information S1).

TrimGalore-0.6.8 (https://www.bioinformatics.babraham.ac.uk/projects/trim_galore/), a wrapper tool around Cutadapt [START_REF] Martin | Cutadapt removes adapter sequences from high-throughput sequencing reads[END_REF] and FastQC (https://www.bioinformatics. babraham.ac.uk/projects/fastqc/) was used for adapter trimming and the quality control of genomic reads. De novo genome assemblies were conducted with ABySS-2.3.1 [START_REF] Jackman | ABySS 2.0: resource-efficient assembly of large genomes using a Bloom filter[END_REF][START_REF] Simpson | ABySS: a parallel assembler for short read sequence data[END_REF]. Assembly quality statistics were obtained with Quast 5.0.2 [START_REF] Gurevich | QUAST: quality assessment tool for genome assemblies[END_REF] and BUSCO 5.2.2 [START_REF] Manni | BUSCO update: novel and streamlined workflows along with broader and deeper phylogenetic coverage for scoring of eukaryotic, prokaryotic, and viral genomes[END_REF]. Gene prediction was performed on assembled genomes using Augustus 3.4.0 [START_REF] Stanke | Gene prediction in eukaryotes with a generalized hidden Markov model that uses hints from external sources[END_REF]. Single-copy genes were identified using Funybase [START_REF] Marthey | FUNYBASE: a FUNgal phYlogenomic dataBASE[END_REF], a reliable database that provides 246 orthologous gene families for performing comparative and phylogenetic analyses in fungi. These gene clusters are present as single copies in 21 fungal genomes. The protein sequences of Sclerotinia sclerotiorum were searched for in the annotated genomes of P. citricarpa using BLASTp with a similarity cutoff e-value of 1 -20 [START_REF] Feau | Genome-enhanced detection and identification (GEDI) of plant pathogens[END_REF]. Sequences with more than one hit in the target genome were discarded from subsequent analyses. Single-copy isolated protein sequences were then searched for in the annotated genomes in order to obtain the nucleotide sequences (predicted genes) obtained with Augustus. The isolates retained for this part of the study were those in which all the selected genes were present and not fragmented or missing. Genome assemblies were deposited at DDBJ/ENA/GenBank under the BioProject number PRJNA949004. These nucleotide sequences were individually analyzed using SeaView version 5 [START_REF] Gouy | Seaview version 5: a multiplatform software for multiple sequence alignment, molecular phylogenetic analyses, and tree reconciliation[END_REF]. The analyses included sequence alignment with Muscle [START_REF] Edgar | MUSCLE: multiple sequence alignment with high accuracy and high throughput[END_REF], removal of poorly aligned positions with Gblocks [START_REF] Talavera | Improvement of phylogenies after removing divergent and ambiguously aligned blocks from protein sequence alignments[END_REF] and concatenation of all the isolated single-copy sequences. RAxML [START_REF] Stamatakis | RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies[END_REF] was used for maximum-likelihood phylogenetic inference, using the general time reversible (GTR)-gamma model with 1,000 replicates to estimate bootstrap supports. A Bayesian phylogenetic tree was inferred using MrBayes 3.2 [START_REF] Ronquist | MrBayes 3.2: efficient Bayesian phylogenetic inference and model choice across a large model space[END_REF]. Runs were performed using the Bayesian MCMC model jumping approach. Four MCMC chains were run using the default heating with tree sampling performed every 5,000 generations. Runs were performed for at least 10 million generations, and stopped when the standard deviation of split frequencies was below 0.01. A consensus maximum-likelihood and Bayesian phylogenetic cladogram was visualized and annotated with SplitsTreeCE (https:// github.com/husonlab/splitstree6) [START_REF] Huson | Visualizing incompatibilities in phylogenetic trees using consensus outlines[END_REF].

Selection of highly divergent genomic regions in P. citricarpa and P. paracitricarpa

The genomes of five P. paracitricarpa and 32 P. citricarpa strains were used to check which regions in the two species were clearly divergent (Information S1). Genomic resources included the genomes of strains sequenced in this study and 30 previously published genomes [START_REF] Coetzee | Extending the knowledge of Phyllosticta citricarpa population structure in USA with re-sequencing and genome wide analysis[END_REF][START_REF] Guarnaccia | Phyllosticta citricarpa and sister species of global importance to Citrus[END_REF][START_REF] Rodrigues | Comparative genome analysis of Phyllosticta citricarpa and Phyllosticta capitalensis, two fungi species that share the same host[END_REF] which were downloaded either from the MycoCosm database or the National Center of Biotechnology Information (NCBI) Sequence Read Archive (SRA) database.

Both the newly generated reads and the downloaded sequences were individually filtered by Trimmomatic v0.39 [START_REF] Bolger | Trimmomatic: a flexible trimmer for Illumina sequence data[END_REF] to remove adapters and low-quality sequences. The cleaned reads were then mapped to the reference genome CBS 102373 using BWA-mem v0.7.17 (Li & Durbin, 2009). The resulting alignments were sorted by position using SAMtools v1.3 (Li et al., 2009) and the duplicated alignments from the PCR amplification were then masked by Picard v2.18.7 (http://broadinstitute.github. io/picard/). The Genome Analysis Toolkit (GATK) v4.2 [START_REF] Mckenna | The genome analysis toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data[END_REF] was used for variant calling, selection, and filtration. The obtained variants were filtered using the following parameters: "QD < 2.0 || MQ < 40.0 || FS > 60.0 || SOR > 3.0 || MQRankSum < -12.5 || ReadPosRankSum < -8.0". Polymorphic sites with a missing rate less than 0.5 and a minor allele frequency greater than 0.02 were kept.

Regions that were clearly distinct from each other in the two Phyllosticta species were identified by comparing the differences in allele frequency in the two populations; the read alignments were visualized using the Integrative Genomics Viewer (IVG) [START_REF] Robinson | Variant review with the integrative genomics viewer[END_REF]. Read alignments of the ITS and tef1 genomic regions in the reference genome were also checked in order to assess the intra-and interspecific polymorphism within these genes recommended as a barcode for identification purposes (EPPO, 2020;[START_REF] Schoch | Nuclear ribosomal internal transcribed spacer (ITS) region as a universal DNA barcode marker for Fungi[END_REF]. The genomic positions of the ITS and tef1 gene were identified by searching for the target regions of the following PCR primers: V9G (de Hoog & van den Ende, 1998), ITS4 [START_REF] White | Amplification and direct sequencing of fungal ribosomal RNA genes for phylogenetics[END_REF], EF1-728F [START_REF] Carbone | A method for designing primer sets for speciation studies in filamentous ascomycetes[END_REF][START_REF] Carbone | A method for designing primer sets for speciation studies in filamentous ascomycetes[END_REF]EF-2 (O'Donnell et al., 1998).

The reads in the candidate regions were extracted from the bam file using SAMtools, and visualized with the IGV.

Design of P. citricarpa-specific primers and probe for PCR and real-time PCR

The previous steps led to the identification of a genomic region that was clearly different in P. citricarpa and P. paracitricarpa. This region of unknown function was downloaded for each genome for P. citricarpa, P. paracitricarpa, and other Phyllosticta species occurring in Citrus. All the orthologous sequences were aligned using the MUSCLE algorithm implemented in Geneious Prime (Biomatters V2021.2.2; Biomatters, Auckland, New Zealand). Candidate primers and probe oligonucleotides were designed using Primer 3 [START_REF] Untergasser | Primer3-new capabilities and interfaces[END_REF] based on the regions showing polymorphisms between species, but conserved in P. citricarpa. The melting temperature, potential formation of secondary structures, and interactions among the oligonucleotide sequences were evaluated in silico using Geneious Prime. All the primers and probes used in this study were synthesized by Eurogentec (Seraing, Belgium).

Fungal strains and extraction of genomic DNA from single-spore cultures

A panel of 56 Phyllosticta spp. strains from different origins and hosts (Table 1), mainly from Citrus spp., were used for this study. All these isolates were identified by barcode sequencing using either the regions LSU and tef1 (for Phyllosticta spp.) or ITS (other species) (Table 2). A subset of sequence data was submitted to GenBank (Information S2). In addition, a subset of the P. citricarpa and P. paracitricarpa strains were examined by genotyping using ten microsatellite loci, initially developed for P. citricarpa, according to [START_REF] Carstens | A global perspective on the population structure and reproductive system of Phyllosticta citricarpa[END_REF] and [START_REF] Wang | Mating type and simple sequence repeat markers indicate a clonal population of Phyllosticta citricarpa in Florida[END_REF]. A minimum spanning network was constructed based on pairwise allele shared distance, using Edenetwork 2.18 [START_REF] Kivelä | EDENetworks: a user-friendly software to build and analyse networks in biogeography, ecology and population genetics[END_REF].

P. citricarpa strains were manipulated in a biosafety level 3 laboratory. All the cultures were single-spored, and then grown at 22 C on potato dextrose agar (PDA) with a sterile cellophane disc over the surface. Once the mycelium colonized the cellophane disc, it was recovered with a sterile scalpel and placed in a sterile microtube, then kept at -20 C until DNA extraction.

Additional strains of other genera occurring on Citrus were included in this study (Table 1). Cultures were grown as described above and the gDNA of these strains was extracted using the Plant DNeasy mini kit (Qiagen, Marseille, France) as per the manufacturer's instructions, then kept at -20 C until further use.

Conventional and real-time PCR reaction conditions

The combination of the forward and reverse primers, and the probe developed in this project will be referred to cCBS (for conventional PCR) and qCBS (for real-time PCR): CBS stands for citrus black spot. Conditions for both cCBS and qCBS were assessed to ascertain their specificity towards the target species P. citricarpa. In particular, the assays were optimized not to cross-react with DNA of P. paracitricarpa or P. citriasiana, which are genetically closely related to P. citricarpa. cCBS reactions contained 1× PCR reaction buffer, 1.5 mM of MgCl 2 , 0.25 mM of each dNTP, 0.6 µM of each forward (cCBS-F) and reverse (cCBS-R) primer, 0.05 U of HGS Diamond Taq DNA polymerase (Eurogentec, Seraing, Belgium), 0.6 µg/µL Bovine Serum Albumin (BSA) and 2 µL of DNA template. Molecular grade water was added to the reaction up to 20 µL. cCBS PCR runs were performed using an initial denaturation step at 95 C for 10 min, followed by 40 cycles of denaturation at 94 C for 30 s, annealing at 64 C for 30 s and elongation at 72 C for 45 s, with a final elongation step at 72 C for 10 min. cCBS PCR runs were performed in a BioRad T100 thermocycler (Bio-Rad, Hercules, CA, qCBS reactions contained 1× PCR reaction buffer, 5 mM of MgCl 2 , 0.2 mM of each dNTP, 0.1 µM of forward primer qCBS-F, 0.2 µM of reverse primer qCBS-R, 0.1 µM of qCBS-P probe, 0.025 U µL of the qPCR Core Kit DNA polymerase, 0.6 µg/µL Bovine Serum Albumin (BSA), and 2 µL of DNA template. Molecular grade water was added up to 20 µL for the final volume. The qCBS cycling conditions were 1 cycle of initial denaturation at 95 C for 10 min, and 45 cycles of denaturation at 95 C for 15 s followed by annealing at 68 C for 1 min. qCBS reactions were performed using the Eurogentec Core Kit No ROX in a Rotor-Gene 6500 thermocycler (Qiagen, Marseille, France). Each reaction's Ct values and the standard deviations obtained from all the samples' replicates were recorded by the Rotor-Gene Q series software (v 2.3.5; Qiagen, Marseille, France).

Construction of a plasmid positive control for conventional PCR and real-time PCR

The gDNA of P. citricarpa strain LSVM 1501 was used to produce the plasmid positive control for the primer pairs qCBS-F (cCBS-F) and qCBS-R (cCBS-R), using the Clone JET PCR Cloning kit (Thermo Fisher Scientific, Illkirch-Graffenstaden, France). Amplicons generated with the primers were inserted in the pJET1.2/blunt vector in order to transform competent DH10B cells of Escherichia coli. These E. coli cells were then transferred to Petri dishes containing Luria-Bertani (LB) broth amended with 50 mg L -1 of ampicillin, and were incubated overnight at 37 C. The plasmid DNA (pDNA) was extracted from the bacterial cells using the Nucleospin Plasmid kit (Macherey-Nagel, Düren, Germany). The molecular mass of the plasmid and the number of plasmid copies (pc) produced were calculated, and a dilution series of the plasmid was further tested by cCBS and qCBS. Plasmid DNA (pDNA) was diluted in 1× tris-EDTA (TE) buffer and kept at -20 C until use.

Performance assessment of the optimized conventional and real-time PCR assays

The analytical specificity of the cPCR and qPCR assays was assessed with a DNA panel that included 30 non-target Phyllosticta spp. and 21 other fungal species isolated from citrus fruits (Table 1). The inclusivity of both cCBS and qCBS assays was assessed with a panel of 26 P. citricarpa isolates from different hosts and origins (Table 1). All gDNA samples were diluted at 1 ng µL -1 . Runs included two replicates per sample. Negative controls were included in each run and consisted of DNA extracted from healthy orange and lemon peel and normalized at 1 ng µL -1 .

The analytical sensitivity of the cCBS and qCBS assays was assessed by testing a ten-fold dilution series of the pDNA diluted in 1× tris-EDTA (TE) buffer and a ten-fold dilution series of the pDNA diluted in a background of 1 ng µL -1 of healthy orange and lemon peel (flavedo) DNA, mixed at a ratio of 1:1. Each dilution series ranged from 3.16 10 6 to 3.16 pc. The limit of detection (LOD) was estimated as the lowest concentration of pDNA in 1× TE buffer that yielded 100% positive results on all replicates included in the cCBS and qCBS reactions in our conditions. In the case of qCBS, a standard curve was obtained for each type of matrix tested (pDNA in 1× TE buffer, pDNA with orange peel DNA and lemon peel DNA).

The qCBS assay was further assessed by evaluating additional criteria such as repeatability, reproducibility, robustness and transferability, in order to check its behavior in conditions close to routine analysis with target and non-target DNA. All these four criteria were evaluated with a panel consisting of pDNA at 10×, 100× and 1,000× (only for repeatability) the LOD, as well as 0.1 ng µL -1 of gDNA of P. citricarpa strain LSVM1501 and diluted in 1 ng µL -1 solution of healthy orange or lemon peel DNA (ratio 1:1), gDNA of P. paracitricarpa strains ZJUCC200937 and LSVM 1238, and P. citriasiana strain LSVM 1146 at 1 ng µL -1 each.

For repeatability, ten replicates of each template were tested by a single operator using the same real-time PCR equipment (Rotorgene Q; Qiagen, Marseille, France). For reproducibility, three replicates of each template were tested on the same qPCR equipment by two different operators over 3 days. The robustness of the qPCR assay was evaluated by modifying two qPCR parameters. First, the qPCR assay was performed using a ±10% variation in the final qPCR reaction volume (i.e., 18 and 22 µL). Second, the qPCR assay was performed by modifying the hybridization temperature by ± 2 C (i.e., 66 C and 70 C). These qPCR assays were performed with 10 replicates of each template.

The transferability of the method was assessed by comparing the performance of two different thermocyclers (Rotorgene Q and Roche Lightcycler 480) and four different qPCR kits or master mixes (No ROX qPCR Core Kit, Eurogentec; QuantaBio PerfeCTa qPCR ToughMix; No ROX qPCR Master Mix, Eurogentec; and the Eurogentec Takyon Core kit) in the same laboratory. An additional experiment was added by involving another laboratory (IAM-GIHF, Madrid, Spain), which used its own master mix (TaKaRa Premix Ex Taq TM (Probe qPCR); TaKaRa, Kusatsu, Japan) and equipment (Rotorgene Q; Qiagen, Marseille, France). The qPCRs were carried out using ten replicates of each template.

Analysis of naturally infected citrus materials

The cCBS PCR and qCBS qPCR assays were assessed on a set of citrus fruit samples with symptoms that looked like citrus black spot. It included 107 DNA samples comprising DNAs previously extracted from naturally infected citrus fruits of various provenances and species intercepted in French harbors between 2018-2020, as well as 12 DNAs obtained from fruit lesions/symptoms that resembled CBS disease but tested negative for P. citricarpa with van Gent-Pelzer et al.'s (2007) assay (Table 3). These 12 DNA samples were used as negative controls. In addition, DNA samples extracted from CBS lesions on infected fresh fruits obtained for this study from Argentina and two sites in Tunisia (Table 3) were also tested. DNA was extracted from CBS lesions using the DNeasy Plant Mini kit (Qiagen, Marseille, France) following the manufacturer's protocol. The initial grinding step was performed using Lysing Matrix A tubes and a FastPrep24 grinding machine (MP Biomedicals, Santa Ana, CA, USA), with a two-run program at 6.5 U for 1 min. All DNA extracts were also analyzed using the qPCR method of van Gent-Pelzer et al. ( 2007), used as the gold standard reference method, and hereafter referred to as VGP assay. In addition, the 18S Uni test developed by [START_REF] Ioos | Sensitive detection of Fusarium circinatum in pine seed by combining an enrichment procedure with a real-time polymerase chain reaction using dual-labeled probe chemistry[END_REF] that targets the 18S rDNA of plants and fungi by qPCR, was used to assess the quality of the amplified DNAs. Two replicates of each sample were included in the assays. The relative sensitivity, specificity and accuracy of the newly developed cCBS and qCBS were calculated according to ISO 16140 (International Standardization Organization, 2016) and [START_REF] Ioos | European collaborative studies for the validation of PCR-based detection tests targeting regulated fungi and oomycetes[END_REF].

RESULTS

Phylogeny of Phyllosticta spp from Citrus deduced from single-copy genes

The protein sequences searched for in the annotated genomes of P. citricarpa allowed 51 genes to be selected with a single hit. Alignments of each of these genes separately revealed The 18S uni test was conducted to verify the amplifiability of the DNA extracts. The mean and standard deviation of Ct values were generated with two replicates. A value flagged with * means that only one out of the two replicates was positive. N.t stands for not tested. $ DNA extracted from fruit lesions by the IAM-GIHF laboratory. a Sample classified as negative according to our internal rules for the VGP assay.

Ioos et al. ( 2023), PeerJ, DOI 10.7717/peerj.16354 14/27 that 14 (27.5%) were polymorphic and could be used to discriminate between strains of P. citricarpa and P. paracitricarpa. In contrast, 28 genes (54.9%) were completely monomorphic in the two species. Finally, nine genes (17.6%) exhibited some intra-species polymorphism, but were not fixed in either all the P. citricarpa or all the P. paracitricarpa strains. Concatenated sequences of these 51 genes resulted in a 84,155-bp alignment. In all, 35 polymorphic sites differentiated all the strains of P. citricarpa from all those of P. paracitricarpa. The average percentage relatedness between the 51 concatenated genes from P. citricarpa and P. paracitricarpa was 99.26% (±0.89 SD). The phylogenetic tree pattern was in general consistent with previous identification of Phyllosticta strains using LSU and tef1: strains were assigned to separate clades corresponding to P. capitalensis, P. citrichinaensis, P. citribraziliensis, P. citriasiana, P. paracitricarpa, and P. citricarpa (Fig. 1). In line with its microsatellite multilocus genotype pattern (Information S3), LSVM1238 grouped with the clade including all the P. paracitricarpa reference strains. Therefore, strain LSVM1238 was assigned tentatively to P. paracitricarpa and referred to as such in this work (Table 1). Selection of a region highly specific to P. citricarpa and design of specific oligonucleotides

A region showing fixed polymorphisms between the sister species P. citricarpa and P. paracitricarpa was successfully identified in scaffold_23 of the P. citricarpa CBS 102373 genome assembly, between base positions 516,600 and 517,100. In particular, when compared with genomes of P. citricarpa and P. citriasiana a 7-pb insertion (located between base positions 516,829 and 516,830) and a 7-pb deletion (located between base positions 516,848 and 516,854) was present in all P. paracitricarpa genomes included in the selection (Fig. 2). Tentative primers (for cPCR and qPCR) and a probe (for qPCR) able to distinguish P. citricarpa from P. paracitricarpa were designed targeting both the insertion and the deletion sequences and a few SNPs located upstream. These primers and probes were also designed to be able to distinguish P. citricarpa from P. citriasiana. One SNP between these two species is located in the forward primer (cCBS-F or qCBS-F), one in the probe (qCBS-P), and one in the reverse primer (cCBS-F or qCBS-F) (Fig. 2).

Performance values of the assays

Using the conditions and parameters listed in the materials and methods section, both cPCR and qPCR assays successfully amplified DNA from all 26 P. citricarpa strains, regardless of their geographic provenance, and did not cross-react with any of the non-target species, including the sister species P. paracitricarpa and closely related species P. citriasiana. The accuracy of negative results yielded with cCBS and qCBS assays for all the DNAs was checked by successfully amplifying the ITS using the fungal universal ITS5/ ITS4 PCR test (Table 2).

Regarding the analytical sensitivity, the limit of detection obtained for qPCR assays was 31.6 pc µL -1 using the pDNA diluted in 1Â TE buffer as well as for the pDNA diluted in a background of 1 ng µL -1 of the DNA from healthy orange and lemon peel. The LOD for cPCR was higher, with 316 pc µL -1 in all conditions. For the cPCR assay, 100% of the samples tested at that concentration yielded a positive result with an amplicon size of 107 bp. For the qPCR assay, the R 2 values of the pDNA in 1× TE buffer, and the pDNA diluted in orange and lemon peel DNA were 0.995, 0.996, and 0.995, respectively (Fig. 3). In all further qCBS runs, a LOD positive control was included in duplicate, and its mean Ct value was used as the cut-off value to declare a DNA extract positive or negative regarding P. citricarpa.

The remaining performance values, repeatability, reproducibility, robustness and transferability are summarized in the supplemental sections. Both conventional and real-time PCR assays yielded 100% repeatable and reproducible results (Information S4). The coefficient of variation for repeatability ranged between 0.53% and 1.37%. The coefficient of variation for reproducibility ranged between 3.49% and 4.41%. Non-target DNAs were never amplified, as expected.

The robustness of the qPCR method was assessed by modifying the reaction volume of The transferability of the qPCR method was assessed by comparing five different qPCR master mixes and two qPCR platforms. The No ROX qPCR Core Kit (Eurogentec, Seraing, Belgium) and Takyon No ROX Probe Core Kit (Eurogentec, Seraing, Belgium) yielded satisfactory results in terms of specificity. However, changing the qPCR master mix sometimes compromised the assay's sensitivity and specificity (Information S6). First, the Eurogentec No ROX qPCR Master Mix (Eurogentec, Seraing, Belgium) and the TaKaRa Premix Ex Taq Probe qPCR (runs carried out by IAM) did not amplify any of the positive samples included in the run. Second, the Takyon No ROX Probe Core Kit (Eurogentec, Seraing, Belgium) yielded cross-reactions with the DNA of P. citriasiana (isolate LSVM1146). Third, the QuantaBio PerfeCTa qPCR ToughMix yielded late Ct amplifications of the target DNA (>35 Ct). Regarding the qPCR platform, runs performed with the Roche Light Cycler 480 using optimized conditions were generally similar to those using the Rotorgene thermocycler.

Tests on fruits with CBS symptoms

Fruits of different origins and varieties were analyzed with both the cCBS and the qCBS assays. These analyses were compared with those of the VGP reference method (VGP qPCR). All DNA extracts yielding negative results with all three P. citricarpa assays were also tested with 18S uni qPCR [START_REF] Ioos | Sensitive detection of Fusarium circinatum in pine seed by combining an enrichment procedure with a real-time polymerase chain reaction using dual-labeled probe chemistry[END_REF] in order to verify the quality of the DNA extract (Table 3).

Out of the 107 DNAs included, both qPCR assays yielded 100% identical results with 95 positive samples and 12 negative results (Table 3). The end-point cCBS PCR provided identical results except for three samples which could not be tested. On two occasions, the VGP qPCR assay yielded a late mean Ct value (>35), whereas cCBS and qCBS assay results were negative. However, according to our internal rules these late Ct values were not considered as positive, since they were later than the mean Ct generated with the VGP assay's limit of detection control. Considering the VGP qPCR assay as the reference method (EPPO, 2020), the relative sensitivity, specificity and accuracy of the cCBS cPCR and qCBS qPCR assays were all 100%.

The mean Ct value obtained for the whole set of positive samples was significantly higher with the qCBS qPCR (30.52 ± 3.4), targeting a single-copy region, than with the VGP assay (21.51 ± 3.1) that targets a multi copy operon.

DISCUSSION

In this work, genomes from different Phyllosticta species were used both to further examine their phylogenetic relationships, and to develop a more specific assay targeting the regulated species P. citricarpa. This perfectly illustrates the power of comparative genomics and the support it provides in managing priority fungal plant pathogens. Indeed, a precise identification of the pathogen is a prerequisite first to draft regulations, which refer to specific taxon names, and second to develop and use an accurate detection test for early and specific detection in order to prevent the pathogen's introduction into a country or to attempt to eradicate it as early as possible once detected for the first time. This strategy may also apply to other high priority pathogens.

The first achievement of this work is the confirmation that the strains of P. citricarpa and P. paracitricarpa included in this work group in two distinct phylogenetic clades. A multilocus alignment of 51 concatenated genes is in line with the results of [START_REF] Guarnaccia | First report of Phyllosticta citricarpa and description of two new species, P. paracapitalensis and P. paracitricarpa, from citrus in Europe[END_REF] and [START_REF] Wang | Clonal expansion in multiple Phyllosticta species causing citrus black spot or similar symptoms in China[END_REF]. The phylogenies of [START_REF] Guarnaccia | First report of Phyllosticta citricarpa and description of two new species, P. paracapitalensis and P. paracitricarpa, from citrus in Europe[END_REF] and [START_REF] Wang | Clonal expansion in multiple Phyllosticta species causing citrus black spot or similar symptoms in China[END_REF] were inferred using six genes from the core genome. [START_REF] Guarnaccia | Phyllosticta citricarpa and sister species of global importance to Citrus[END_REF] have also used whole genomes to assess the genetic relatedness between the species. All these studies show a separation of the two phylogenetic clades. Additionally, the same clustering pattern was observed on a subset of ten strains by microsatellite genotyping. Our work demonstrates that genetic differentiation between the two clades is very low (>99%), with more than 50% of the genes included that were monomorphic. However, a certain level of genetic structure occurs within each clade, as illustrated by the support of the branches in the phylogenetic tree. Although beyond the scope of this work, the inclusion of a larger number of strains from different origins, combined with analysis of genealogical concordance [START_REF] Gladieux | Gene flow between divergent cereal-and grass-specific lineages of the rice blast fungus Magnaporthe oryzae[END_REF], would be necessary to accurately assess the taxonomy of P. citricarpa and P. paracitricarpa.

One important result of our work concerns the (un)reliability of using the tef1 gene to identify some isolates of P. citricarpa and P. paracitricarpa. Indeed, our phylogeny, together with microsatellite genotyping and the negative testing of its DNA with qCBS and cCBS PCR argue in favor of the assignation of the Bangladeshi strain LSVM1238 to the P. paracitricarpa clade. P. paracitricarpa has intra-species polymorphisms in tef1 (Information S7), whereas "hallmarks" of P. paracitricarpa were observed in P. citricarpa, although having a low allele frequency. This is in line with the pattern observed for nine genes (17.6%) used in our phylogeny study. Therefore, utilization of tef1 in the context of quarantine testing can present a risk of false positives.

The second output of our comparative genomics was the development and validation of new conventional and real-time PCR assays to accurately detect the CBS-causing agent Phyllosticta citricarpa. This species is the only Phyllosticta species which is internationally regulated, being a quarantine fungus for numerous regional plant protection organizations in the world. Other species are also able to cause spots on citrus fruits, such as P. citriasiana, P. citrimaxima, P. citrichinaensis [START_REF] Guarnaccia | Phyllosticta citricarpa and sister species of global importance to Citrus[END_REF], and the recently described sister species, P. paracitricarpa. This latter species was recently found to have a wider host and geographic distribution on Citrus spp. in China [START_REF] Wang | Clonal expansion in multiple Phyllosticta species causing citrus black spot or similar symptoms in China[END_REF]. Therefore, the protocols for detecting the only quarantine species, P. citricarpa, must be sufficiently specific to avoid any cross-reaction with these other pathogenic species, as well as with endophytic species occurring on fruits or leaves. To our knowledge, all the current P. citricarpa detection protocols based on molecular assays targeting the ITS rDNA region must produce false positive results with P. paracitricarpa due to their genetic closeness. This is in particular the case with the PCR and qPCR assays of [START_REF] Van Gent-Pelzer | A TaqMan PCR method for routine diagnosis of the quarantine fungus Guignardia citricarpa on citrus fruit[END_REF][START_REF] Schirmacher | Species-specific real-time PCR for diagnosis of Phyllosticta citricarpa on Citrus species[END_REF][START_REF] Peres | Comparison of molecular procedures for detection and identification of Guignardia citricarpa and G. mangiferae[END_REF], which are recommended in international standards (EPPO, 2020;IPPC, 2014).

In addition, while proceeding through the steps of comparative genomics conducted in this work, it was observed that the sequence of the housekeeping gene tef1 varied across the five P. paracitricarpa isolates. This contradicts reports saying that some of the SNPs in tef1 could be used to unequivocally identify P. citricarpa by sequencing (EPPO, 2020) or qPCR [START_REF] Zajc | Highly specific qPCR and amplicon sequencing method for detection of quarantine citrus pathogen Phyllosticta citricarpa applicable for air samples[END_REF], but our own observations suggest that these methods should be used with caution, since tef1 from some P. paracitricarpa strains may display the "hallmarks" of P. citricarpa (Information S7).

The comparative genomics approach reported here screened regions that were highly polymorphic from one sister species to another. The region located on P. citricarpa genome scaffold_23 was also present in P. paracitricarpa, but conserved at the intraspecific level while showing a high degree of interspecific polymorphism. It was therefore fit for the design of specific oligonucleotides.

The specificity of an assay targeting a quarantine organism should be thoroughly verified and validated. First, it should be stressed that a comprehensive and representative panel of strains or genomes is required for the validation step, in order to cover as much natural genetic diversity as possible. Even with these precautions, the test's specificity must be constantly checked, as new strains with a slightly different genetic background may be discovered over time. The observation of unexpected variation in tef1 within P. citricarpa is a good example, and variation in the region located on P. citricarpa genome scaffold_23 may never be ruled out as a possibility. In this respect, it is of utmost importance to report the occurrence of new strains that cause unexpected results (Gupta et al., 2018), especially when related to quarantine pests involving severe regulatory measures. When feasible, it is also important to include several other species from the same genus during the optimization/validation steps, and not only the closest species. Hence, in our work to design oligonucleotides that could discriminate the closely related P. citricarpa from P. paracitricarpa, more stringent reaction conditions had to be applied to prevent cross-amplification of the DNA of the more distant species, P. citriasiana.

The validation results provided herein support the need to carry out transferability and robustness studies, especially when stringency conditions are very strict because there is a need to discriminate between closely related species [START_REF] Ioos | Transferability of PCR-based diagnostic protocols: an international collaborative case study assessing protocols targeting the quarantine pine pathogen Fusarium circinatum[END_REF]. In the course of this work, an assessment of other commercial qPCR master mixes showed that some of them dramatically reduced the DNA amplification yield or hampered hybridization of the primers or probe, thus leading to an unacceptable loss of sensitivity in the qCBS qPCR assay. It is therefore essential before using the tests routinely and for regulatory analyses, to ensure that under new laboratory conditions, and using commercial reagents that may differ from those used in the original work, the reaction remains sufficiently sensitive and specific. Overall, in our conditions and with our reagents, an increase in the annealing temperature to 70 C was the only deviation that generated false negative results, except with P. citricarpa gDNA diluted in orange peel DNA. This high temperature significantly affected the sensitivity, probably due to loss of DNA polymerase efficiency or poor probe hybridization. This is also probably the reason why no Ct value could be generated with the panel of samples analyzed by IAM, using a qPCR master mix (TaKaRa Premix Ex Taq TM Probe qPCR; TaKaRa, Kusatsu, Japan) containing a DNA polymerase which the supplier recommends should be used at a polymerization temperature range of 56-64 C. Likewise, in our study, changing the qPCR master mix brand or type also affected the specificity of the VCG qPCR assay, since false-positive results were frequently obtained with the DNA of P. citriasiana.

In addition, non-target DNA from P. citriasiana strain LSVM 1146 was occasionally amplified in the lowest stringency conditions (i.e., using a reaction volume of 18 µL) and systematically amplified with a 66 C annealing temperature. However, in both cases, all the Ct values generated were later than the Ct generated by the LOD positive control, and therefore considered as negative according to our internal rule of decision. Finally, in the context of an official analysis targeting the regulated P. citricarpa, our recommendation would be that the more specific cCBS PCR or qCBS qPCR positive results can be confirmed with the VGP qPCR test, which is a bit more sensitive but less specific, or the assay of [START_REF] Zajc | Highly specific qPCR and amplicon sequencing method for detection of quarantine citrus pathogen Phyllosticta citricarpa applicable for air samples[END_REF]. The three assays target different regions of the genome, which will secure the diagnosis.

Figure 1

 1 Figure 1 Maximum likelihood and Bayesian phylogenetic cladogram. The cladogram was constructed based on 51 single-copy contatenated genes obtained from the FunyBase database (Marthey et al., 2008). The bayesian posterior probabilities (>0.9) and bootstrap (>70) support values are indicated alongside the branches of the tree. Full-size  DOI: 10.7717/peerj.16354/fig-1

Figure 2

 2 Figure 2 Alignment of representative sequences of Phyllosticta citricarpa, P. paracitricarpa and P. citriasiana of the gene located in the scaffold 23 of the P. citricarpa CBS102373 strain genome. The sequences of the reference genome are highligthed in yellow. The primers for conventional (cCBS-F/cCBS-R) and real-time PCR (qCBS-F/qCBS-R) are flagged in green and yellow. The probe of the real-time PCR assay (qCBS-P) is flagged in red. SNPs and indels located in the primers or probe's target regions are highlighted in blue. Full-size  DOI: 10.7717/peerj.16354/fig-2

  ±10% and the hybridization temperature of ±2 C. Modifying the reaction volume (18 and 22 µL instead of 20 µL) resulted in a few late Ct values with the DNA of P. citriasiana (isolate LSVM1146), indicative of cross-reactions. All these amplifications had Ct values over 40 (Information S4). Changes in the hybridization temperature (66 C and 70 C instead of 68 C) affected either sensitivity or specificity. In less stringent conditions at 66 C, late Ct values (35.28 ± 0.52) were obtained with P. citriasiana DNA. However, when

Figure 3

 3 Figure 3 Standard curves assessed with a 10-fold serial dilution of the P. citricarpa plasmid DNA positive control. The plasmid DNA standards were diluted in 1× Tris-EDTA (TE) buffer (circle), in a background of lemon DNA (triangle), or in a background of orange DNA (square). The mean Ct values are calculated with three replicates Full-size  DOI: 10.7717/peerj.16354/fig-3

Table 1

 1 Isolates of fungal species used in this study.

	Species	Isolate	Host	Country or region of	Year qCBS-qPCR-F/	cCBS-cPCR-	ITS
				origin	R/P	F/R	PCR
	Phyllosticta citricarpa	LSVM 205	Citrus sp.	South Africa	2009 30.28 ± 0.07	+	+
		LSVM 359	Citrus sp.	Togo	2010 19.87 ± 0.02	+	+
		LSVM 494	Citrus sp.	Togo	2011 30.91 ± 0.14	+	+
		LSVM 1101	C. sinensis × P.	South Africa	2014 20.56 ± 0.03	+	+
			trifoliata
		LSVM 1102	C. sinensis	South Africa	2013 20.59 ± 0.26	+	+
		LSVM 1103	C. sinensis	South Africa	2013 31.45 ± 0.38	+	+
		LSVM 1116	C. sinensis	South Africa	2014 19.82 ± 0.00	+	+
		LSVM 1123	C. sinensis	Zimbabwe	2014 21.06 ± 0.00	+	+
		LSVM 1228	C. sinensis	Ivory Coast	2015 20.59 ± 0.07	+	+
		LSVM 1243	C. sinensis	South Africa	2015 20.41 ± 0.05	+	+
		LSVM 1244	C. sinensis	Brazil	2015 20.70 ± 0.18	+	+
		LSVM 1266	C. sinensis	Brazil	2015 37.31 ± 0.22	+/-	+
		LSVM 1268	C. sinensis	Brazil	2015 19.93 ± 0.11	+	+
		LSVM 1270	C. sinensis	Brazil	2015 21.74 ± 0.15	+	+
		LSVM 1276	C. sinensis	Brazil	2015 30.82 ± 0.35	+	+
		CBS 141350	C. sinensis (litter)	Malta	2016 21.51 ± 0.05	+	+
		CBS 141351	C. sinensis (litter)	Portugal	2016 23.44 ± 0.09	+	+
		LSVM 1499	C. limon	Tunisia	2019 16.30 ± 0.08	+	+
		LSVM 1500	C. limon	Tunisia	2019 20.04 ± 0.47	+	+
		LSVM 1501	C. sinensis	Tunisia	2019 20.56 ± 0.10	+	+
		LSVM 1502	C. sinensis	Tunisia	2019 20.28 ± 0.01	+	+
		GC-115	C. sinensis	Brazil	2010 23.28 ± 0.20	+	+
		GC-129	C. limon	Argentina	2014 23.15 ± 0.26	+	+
		GC-130	C. limon	Argentina	2014 23.70 ± 0.00	+	+
		GC-131	C. limon	Argentina	2014 23.04 ± 0.24	+	+
		GC-133	C. sinensis	Angola	2016 24.31 ± 0.01	+	+
	P. paracitricarpa	CBS141357	C. lemon (litter)	Greece	2016 >45	-	+
		CBS 141359	C. lemon (litter)	Greece	2016 >45	-	+
		ZJUCC200937	C. reticulata	China	2017 >45	-	+
		GIHF 303	C. sinensis	China	2017 >45	-	+
		LSVM 1238 *	C. pennivesiculata	Bengladesh	2015 >45	-	+
	P. citriasiana	LSVM 1146	C. maxima	China	2014 >45	-	+
		LSVM 204	Citrus sp.	-	2007 >45	-	+
		LSVM 608	C. maxima	China	2012 >45	-	+
		LSVM 903	C. maxima	China	2013 >45	-	+
		CBS 123393	Citrus sp.	Vietnam	2014 >45	-	+
		LSVM 1147	C. maxima	China	2014 >45	-	+
		LSVM 1152	C. maxima	China	2014 >45	-	+
		LSVM 1165	C. maxima	China	2014 >45	-	+
		LSVM 1174	C. paradisi	USA	2014 >45	-	+
							(Continued )

Ioos et al. (2023), PeerJ, DOI 10.7717/peerj.16354 8/27

Table 2

 2 List of primers and probes used in this study for conventional and real-time PCR.

	Target (DNA region)	PCR test	Purpose	Name	Sequence (5′-3′)	Reference
	Phyllosticta citricarpa	"cCBS" Conventional	Detection of	CBS-F	TCCTTTGGAGCAGCTGC	This study
	(Scaffold_23 CBS102373)	PCR	P. citricarpa
				CBS-R	CTTGCTTCCCTTGAATGAGACTG
		"qCBS" Real-time	Detection of	CBS-F	TCCTTTGGAGCAGCTGC
		PCR	P. citricarpa
				CBS-R	CTTGCTTCCCTTGAATGAGACTG	This study
				CBS-P	FAM-AGTCACCTCCGAAGAAGCCAGTCC-BHQ1
	Phyllosticta citricarpa (ITS) "VGP" Real-time	Detection of	GcF1	GGTGATGGAAGGGAGGCCT	van Gent-Pelzer et al. (2007)
		PCR	P. citricarpa	GcR1	GCAACATGGTAGATACACAAGGGT
				GcP1	FAM-AAAAAGCCGCCCGACCTACCTTCA-BHQ1
	Plant/fungus (18S rDNA)	Real-time PCR	DNA quality	18S uni F GCAAGGCTGAAACTTAAAGGAA	Ioos et al. (2009)
			control	18S uni R CCACCACCCATAGAATCAAGA
				18S uni P JOE-ACGGAAGGGCACCACCAGGAGT-BHQ1
	ITS region	Conventional PCR	Sequencing	ITS5	GGAAGTAAAAGTCGTAACAAGG	White et al. (1990)
				ITS4	TCCTCCGCTTATTGATATGC
	tef1 gene	Conventional PCR	Sequencing	EF1-728F CATCGAGAAGTTCGAGAAGG	Carbone & Kohn (1999)
				EF2	GGARGTACCAGTSATCATGTT	O'Donnell et al. (1998)
	28 S large subunit rDNA	Conventional PCR	Sequencing	LR0R	ACCCGCTGAACTTAAGC	Moncalvo (1995)
				LR5	TCCTGAGGGAAACTTCG	Vilgalys & Hester (1990)

Table 1

 1 Strain LSVM1238 was initially identified as P. citricarpa by sequencing EF1 and ITS according to[START_REF] Guarnaccia | First report of Phyllosticta citricarpa and description of two new species, P. paracapitalensis and P. paracitricarpa, from citrus in Europe[END_REF], but displays a microsatellite multilocus genotype pattern typical of P. paracitricarpa. It also clusters with P. paracitricarpa strains in the 51-gene phylogeny. USA). cCBS PCR products were visualized in a 1.5% agarose gel in 0.5× tris-borate-EDTA buffer stained with Ethidium bromide.

	(continued )
	Species	Isolate	Host	Country or region of	Year qCBS-qPCR-F/	cCBS-cPCR-	ITS
				origin		R/P	F/R	PCR
	Penicillium italicum	Penicillium 1	Citrus sp.		x	>45	-	+
	Ramichloridium	LSVM 1176	C. grandis	China	2014 >45	-	+
	cerophilum
	Notes:
	DNA template concentrations were all adjusted to 1 ng/µL for PCR testing. NT, not tested.

* Ioos et al. (2023), PeerJ, DOI 10.7717/peerj.16354 9/27

Table 3

 3 Testing of citrus fruits showing CBS-like symptoms by the cCBS PCR, qCBS qPCR, and van Gent-Pelzer et al. (2007) qPCR.

	Sample	Year	Host	Organ	Origin	cCBS PCR	qCBS qPCR	VGP qPCR	18S uni qPCR
	18-429/2a		Citrus reticulata × C. sinensis	Fruit	Argentina	+	28.74 ± 0.34	18.78 ± 0.17	11.67 ± 0.00
	18-429/2b		Citrus reticulata × C. sinensis	Fruit	Argentina	+	29.01 ± 0.04	20.07 ± 0.00	11.97 ± 0.10
	18-429/2c		Citrus reticulata × C. sinensis	Fruit	Argentina	+	28.87 ± 0.01	20.38 ± 0.04	12.23 ± 0.05
	18-429/2d		Citrus reticulata × C. sinensis	Fruit	Argentina	+	27.63 ± 0.29	17.37 ± 0.09	10.74 ± 0.06
	18-429/2e		Citrus reticulata × C. sinensis	Fruit	Argentina	+	27.71 ± 0.53	18.06 ± 0.08	10.94 ± 0.04
	18-429/2f		Citrus reticulata × C. sinensis	Fruit	Argentina	n.t.	30.41 ± 2.34	19.94 ± 0.01	10.76 ± 0.05
	18-429/2g		Citrus reticulata × C. sinensis	Fruit	Argentina	+	32.69 ± 0.29	23.54 ± 0.07	12.79 ± 0.04
	18-429/4a		Citrus × limonia	Leaves	Argentina	n.t.	24.16 ± 0.29	16.94 ± 0.22	15.37 ± 0.13
	18-429/4b		Citrus × limonia	Leaves	Argentina	+	28.61 ± 1.26	14.02 ± 0.91	12.00 ± 0.02
	18-429/4c		Citrus × limonia	Leaves	Argentina	+	24.05 ± 0.25	16.44 ± 0.33	13.80 ± 0.11
	18-429/4d		Citrus × limonia	Leaves	Argentina	+	23.55 ± 0.02	15.20 ± 0.08	11.39 ± 0.30
	18-429/4e		Citrus × limonia	Leaves	Argentina	+	24.59 ± 0.31	16.52 ± 0.21	12.68 ± 0.11
	18-429/4f		Citrus × limonia	Leaves	Argentina	+	33.03 ± 0.47	24.99 ± 0.02	15.94 ± 0.11
	18-429/4g		Citrus × limonia	Leaves	Argentina	+	27.30 ± 0.18	19.39 ± 0.03	14.84 ± 0.03
	18-429/5a		Citrus limon	Fruit	Argentina	+	31.78 ± 0.04	23.16 ± 0.05	12.47 ± 0.04
	18-429/5b		Citrus limon	Fruit	Argentina	+	31.28 ± 0.01	21.92 ± 0.10	12.35 ± 0.02
	18-429/5c		Citrus limon	Fruit	Argentina	+	30.03 ± 0.26	21.57 ± 0.01	11.63 ± 0.00
	18-429/5d		Citrus limon	Fruit	Argentina	+	29.58 ± 0.08	21.03 ± 0.19	12.51 ± 0.10
	18-429/5e		Citrus limon	Fruit	Argentina	+	29.30 ± 0.12	20.69 ± 0.03	12.45 ± 0.02
	18-429/5f		Citrus limon	Fruit	Argentina	+	32.10 ± 0.16	22.86 ± 0.02	14.42 ± 0.04
	18-429/5g		Citrus limon	Fruit	Argentina	+	30.03 ± 0.03	21.56 ± 0.03	13.52 ± 0.08
	18-429/6a		Citrus sinensis	Fruit	Argentina	+	28.56 ± 0.09	19.98 ± 0.01	9.96 ± 0.06
	18-429/6b		Citrus sinensis	Fruit	Argentina	+	28.40 ± 0.30	19.67 ± 0.05	9.00 ± 0.05
	18-429/6c		Citrus sinensis	Fruit	Argentina	+	30.37 ± 0.39	21.90 ± 0.02	9.69 ± 0.03
	18-429/6d		Citrus sinensis	Fruit	Argentina	+	30.76 ± 0.15	21.99 ± 0.14	8.99 ± 0.11
	18-429/6e		Citrus sinensis	Fruit	Argentina	+	30.42 ± 0.08	21.42 ± 0.13	9.47 ± 0.02
	18-429/6f		Citrus sinensis	Fruit	Argentina	+	31.68 ±0.09	22.80 ± 0.06	8.82 ± 0.14
	18-429/6g		Citrus sinensis	Fruit	Argentina	+	33.13 ± 0.36	24.12 ± 0.05	9.77 ± 0.08
	18-349		Citrus limon	Fruit	Argentina	+	31.57 ± 0.43	23.78 ± 0.01	12.39 ± 0.11
	18-374		Citrus limon	Fruit	Argentina	+	35.13 ± 1.00	27.45 ± 0.08	14.35 ± 0.01
	18-460/1		Citrus sinensis	Fruit	Brazil	+	28.77 ± 0.35	20.82 ± 0.15	11.61 ± 0.01
	18-551		Citrus sinensis	Fruit	Benin	+	33.03 ± 0.17	22.48 ± 0.11	11.18 ± 0.54
	18-552		Citrus sp.	Fruit	Benin	+	31.06 ± 0.18	20.21 ± 0.01	9.25 ± 0.32
	19-065		Citrus limon	Fruit	Tunisia	n.t.	32.13 ± 0.45	21.23 ± 0.01	8.72 ± 0.06
	19-116		Citrus sinensis	Fruit	Tunisia	+	28.82 ± 0.09	17.79 ± 0.14	8.31 ± 0.27
	19-117		Citrus sinensis	Fruit	Tunisia	-	>45	35.78 * ,a	8.77 ± 0.05
	19-118		Citrus sinensis	Fruit	Tunisia	+	28.90 ± 0.14	18.68 ± 0.01	9.77 ± 0.00
	19-119		Citrus sinensis	Fruit	Tunisia	+	34.56 ± 0.18	23.25 ± 0.07	8.57 ± 0.02
	19-133		Citrus limon	Fruit	Tunisia	+	24.32 ± 0.47	13.43 ± 0.11	10.79 ± 0.05
	19-146/a		Citrus sinensis	Fruit	Tunisia	+	29.53 ± 0.09	17.97 ± 0.02	7.92 ± 0.02
	19-146/b		Citrus sinensis	Fruit	Tunisia	+	31.74 ± 0.24	20.65 ± 0.01	7.86 ± 0.03

Ioos et al. (2023), PeerJ, DOI 10.7717/peerj.16354 12/27

Table 3

 3

	(continued )
	Sample	Year	Host	Organ	Origin	cCBS PCR	qCBS qPCR	VGP qPCR	18S uni qPCR
	19-159/2	2019	Citrus limon	Fruit	Tunisia	-	>45	>45	10.72 ± 0.04
	19-5150/1	2019	Citrus sinensis	Fruit	South Africa	+	31.28 ± 0.17	19.66 ± 0.12	8.31 ± 0.36
	19-5150/2	2019	Citrus sinensis	Fruit	South Africa	+	30.59 ± 0.09	19.51 ± 0.18	8.66 ± 0.04
	19-5150/3	2019	Citrus sinensis	Fruit	South Africa	+	32.37 ± 0.07	20.24 ± 0.01	7.65 ± 0.01
	19-5150/4	2019	Citrus sinensis	Fruit	South Africa	+	30.74 ± 0.10	19.64 ± 0.07	9.71 ± 0.07
	19-5150/5	2019	Citrus sinensis	Fruit	South Africa	+	33.11 ± 0.25	21.83 ± 0.05	8.85 ± 0.08
	19-5241/1	2019	Citrus sinensis	Fruit	South Africa	+	36.27 ± 0.41	24.45 ± 0.05	11.32 ± 0.08
	19-5241/2	2019	Citrus sinensis	Fruit	South Africa	+	31.37 ± 0.14	20.25 ± 0.10	8.83 ± 0.01
	20-2990	2020	Citrus sinensis	Fruit	Brazil	+	28.68 ± 0.05	18.46 ± 0.12	9.60 ± 0.00
	20-2999/1	2020	Citrus limon	Fruit	Argentina	+	35.02 ± 0.12	22.54 ± 0.06	9.96 ± 0.08
	20-3282/1	2020	Citrus limon	Fruit	Argentina	-	>45	35.04 ± 0.03 a	8.49 ± 0.02
	20-2382/2	2020	Citrus limon	Fruit	Argentina	+	32.74 ± 0.16	22.55 ± 0.27	8.52 ± 0.02
	20-3493/1	2020	Citrus limon	Fruit	Argentina	+	30.29 ± 0.03	20.05 ± 0.12	9.43 ± 0.01
	20-3493/2	2020	Citrus limon	Fruit	Argentina	+	35.81 ± 0.04	24.43 ± 0.18	9.78 ± 0.05
	20-3493/3	2020	Citrus limon	Fruit	Argentina	+	33.82 ± 0.20	22.75 ± 0.11	9.40 ± 0.01
	20-3493/4	2020	Citrus limon	Fruit	Argentina	+	33.75 ± 0.16	22.79 ± 0.01	9.95 ± 0.02
	20-3493/5	2020	Citrus limon	Fruit	Argentina	+	33.42 ± 0.08	22.50 ± 0.03	9.87 ± 0.03
	20-3504/1	2020	Citrus limon	Fruit	Argentina	+	31.69 ± 0.28	21.34 ± 0.02	8.70 ± 0.03
	20-3504/2	2020	Citrus limon	Fruit	Argentina	+	32.83 ± 0.01	22.03 ± 0.00	9.84 ± 0.03
	20-3504/4	2020	Citrus limon	Fruit	Argentina	+	36.22 ± 0.34	24.63 ± 0.04	8.64 ± 0.01
	20-3504/5	2020	Citrus limon	Fruit	Argentina	+	31.95 ± 0.27	21.58 ± 0.18	9.32 ± 0.06
	20-0479	2020	Citrus reticulata	Fruit	South Africa	+	32.24 ± 0.04	22.41 ± 0.08	12.36 ± 0.04
	TN1-F01	2021	Citrus limon	Fruit	Tunisia	+	32.62 ± 0.22	22.56 ± 0.13	10.64 ± 0.03
	TN1-F02	2021	Citrus limon	Fruit	Tunisia	n.t.	36.10 ± 0.92	25.50 ± 0.05	9.89 ± 0.01
	TN1-F03	2021	Citrus limon	Fruit	Tunisia	+	34.12 ± 0.12	23.04 ± 0.03	8.89 ± 0.00
	TN1-F04	2021	Citrus limon	Fruit	Tunisia	+	35.36 ± 0.28	24.35 ± 0.03	10.26 ± 0.30
	TN1-F05	2021	Citrus limon	Fruit	Tunisia	+	33.46 ± 0.27	22.57 ± 0.01	9.68 ± 0.01
	TN1-F06	2021	Citrus limon	Fruit	Tunisia	+	34.17 ± 0.41	23.80 ± 0.07	10.55 ± 0.02
	TN1-F07	2021	Citrus limon	Fruit	Tunisia	+	35.35 ± 0.44	24.63 ± 0.03	8.73 ± 0.06
	TN1-F08	2021	Citrus limon	Fruit	Tunisia	+	36.39 ± 0.53	25.14 ± 0.00	10.60 ± 0.01
	TN1-F09	2021	Citrus limon	Fruit	Tunisia	+	32.31 ± 0.39	22.14 ± 0.11	11.79 ± 0.02
	TN1-F10	2021	Citrus limon	Fruit	Tunisia	+	32.43 ± 0.22	22.41 ± 0.01	10.67 ± 0.06
	TN1-F11	2021	Citrus limon	Fruit	Tunisia	+	32.16 ± 0.52	21.95 ± 0.00	10.61 ± 0.06
	TN1-F12	2021	Citrus limon	Fruit	Tunisia	+	33.23 ± 0.17	23.06 ± 0.01	10.50 ± 0.08
	TN2-F01	2021	Citrus limon	Fruit	Tunisia	+	32.48 ± 0.15	23.31 ± 0.00	9.68 ± 0.13
	TN2-F05	2021	Citrus limon	Fruit	Tunisia	+	34.95 ± 0.10	24.83 ± 0.01	10.62 ± 0.10
	AR-F01	2021	Citrus sinensis	Fruit	Argentina	+	33.43 ± 0.14	23.52 ± 0.01	11.55 ± 0.17
	AR-F02	2021	Citrus sinensis	Fruit	Argentina	+	34.54 ± 0.56	24.07 ± 0.03	11.86 ± 0.20
	AR-F03	2021	Citrus sinensis	Fruit	Argentina	+	31.98 ± 0.20	22.83 ± 0.05	12.19 ± 0.01
	AR-F04	2021	Citrus sinensis	Fruit	Argentina	+	33.34 ± 0.51	22.92 ± 0.04	11.28 ± 0.00
	AR-F05	2021	Citrus sinensis	Fruit	Argentina	+	32.24 ± 0.42	22.64 ± 0.05	11.20 ± 0.02
									(Continued )

Ioos et al. (2023), PeerJ, DOI 10.7717/peerj.16354 13/27

Table 3

 3

		(continued )
	Sample	Year	Host	Organ	Origin	cCBS PCR	qCBS qPCR	VGP qPCR	18S uni qPCR
	AR-F06		Citrus sinensis	Fruit	Argentina	+	32.08 ± 0.10	22.42 ± 0.06	12.27 ± 0.09
	20-01348		Citrus sinensis	Fruit	Tunisia	-	>45	>45	8.87 ± 0.11
	20-01427		Citrus reticulata	Fruit	Israel	-	>45	>45	10.46 ± 0.04
	20-04070		Citrus sinensis	Fruit	Egypt	-	>45	>45	10.87 ± 0.03
	20-02794		Citrus limon	Fruit	South Africa	-	>45	>45	9.32 ± 0.19
	20-02836		Citrus limon	Fruit	Argentina	-	>45	32.21 ± 0.90 a	9.95 ± 0.02
	20-05365		Citrus sp.	Fruit	Japan	-	>45	>45	11.59 ± 0.13
	21-00466		Citrus sp.	Fruit	Bangladesh	-	>45	>45	8.51 ± 0.06
	21-01914		Citrus latifolia	Fruit	Brazil	-	>45	>45	8.74 ± 0.02
	21-03392		Citrus reticula	Fruit	Egypt	-	>45	>45	12.44 ± 0.03
	333 $		Citrus sinensis	Fruit	Brazil	+	25.02 ± 0.03	19.77 ± 0.02	n.t
	483 $		Citrus limon	Fruit	Argentina	+	25.27 ± 0.12	20.13 ± 0.09	n.t
	507 $		Citrus sinensis	Fruit	Argentina	+	25.15 ± 0.34	19.74 ± 0.09	n.t
	546 $		Citrus sinensis	Fruit	Brazil	+	24.78 ± 0.07	19.84 ± 0.14	n.t
	599 $		Citrus limon	Fruit	Argentina	+	22.97 ± 0.41	18.46 ± 0.01	n.t
	626 $		Citrus reticulata	Fruit	Uruguay	+	24.14 ± 0.08	18.14 ± 0.10	n.t
	647 $		Citrus sinensis	Fruit	Uruguay	+	25.11 ± 0.05	20.14 ± 0.07	n.t
	686 $		Citrus limon	Fruit	Argentina	+	29.08 ± 0.45	24.18 ± 0.06	n.t
	703 $		Citrus limon	Fruit	Uruguay	+	27.86 ± 0.05	22.65 ± 0.06	n.t
	816 $		Citrus sinensis	Fruit	Uruguay	+	23.9 ± 0.23	18.63 ± 0.02	n.t
	890 $		Citrus sinensis	Fruit	Zimbabwe	+	25.24 ± 0.09	20.39 ± 0.07	n.t
	897 $		Citrus limon	Fruit	South Africa	+	24.33 ± 0.10	18.68 ± 0.05	n.t
	907 $		Citrus sinensis	Fruit	South Africa	+	26.95 ± 0.02	22.29 ± 0.03	n.t
	1029 $		Citrus limon	Fruit	Argentina	+	27.9 ± 0.47	23.06 ± 0.01	n.t
	1069 $		Citrus sinensis	Fruit	Argentina	+	27.45 ± 0.06	22.16 ± 0.07	n.t

Notes:

Ioos et al. (2023), PeerJ, DOI 10.7717/peerj.16354

Ioos et al. (2023), PeerJ, DOI 10.7717/peerj.16354 20/27

ACKNOWLEDGEMENTS

The authors would like to acknowledge the INRAE MIGALE bioinformatics platform (https://migale.inra.fr/) and the Freiburg Galaxy Team from the University of Freiburg (Germany) for providing computational resources for bioinformatics. The authors would like to thank Céline Jeandel, Anses Plant Health laboratory, for the microsatellite genotyping.

L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt , and approved the final draft.

Data Availability

The following information was supplied regarding data availability:

The raw measurements are available in the Supplemental Files.

ADDITIONAL INFORMATION AND DECLARATIONS Funding

The mycology research unit of the ANSES Plant Health Laboratory (LSV) is supported by a grant managed by the French National Research Agency (ANR) as part of the French government's "Investing for the Future" (PIA) program (ANR-11-LABX-0002-01, Laboratory of Excellence-ARBRE). The specific work focusing on the improvement and validation of the CBS detection tool was supported by EU Grant S12.809457, in the framework of the European Union Reference Laboratory's work program on fungi pathogenic to plants. The team at Zhejiang University was supported by the National Natural Science Foundation of China (No: 32102148) and China Agriculture Research System (CARS-26). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Grant Disclosures

The following grant information was disclosed by the authors: ANSES Plant Health Laboratory (LSV). French National Research Agency (ANR). French government's "Investing for the Future" (PIA) program: ANR-11-LABX-0002-01.

Competing Interests

The authors declare there are no competing interests.

DNA Deposition

The following information was supplied regarding the deposition of DNA sequences:

The genome assemblies are available at DDBJ/ENA/GenBank: PRJNA949004.

Supplemental Information

Supplemental information for this article can be found online at http://dx.doi.org/10.7717/ peerj.16354#supplemental-information.


Ranjeet Dwivedi

Maeva Lafitte

Lionel Buisson

Olivier Mondain-Monval

Virginie Ponsinet

Alexandre Baron
email: alexandre.baron@u-bordeaux.fr

Broadband forward scattering of light by plasmonic balls: role of multipolar interferences Broadband forward scattering of light by plasmonic balls: role of multipolar interferences

Efficient and broadband forward-scattering is a property of prime importance for meta-atoms if they are to be used in self-assembled metasurfaces. Strong contenders include colloidal nanoresonators with tailored multipolar content to achieve the proper interferences that suppress back-scattering. We consider dense plasmonic balls composed of more than a hundred silver nanoinclusions. Numerical simulations provide a full understanding of the role played by multipole moments in the scattering behavior. They are fabricated using emulsion drying and characterized optically. Strong and efficient forward-scattering is demonstrated over the entire visible range. Electric and magnetic dipole resonances of equal amplitude and phase are evidenced. Such plasmonic balls could be used as meta-atoms for bottomup metasurface applications.

We define plasmonic balls as dense spherical assemblies of plasmonic nanoparticles [START_REF] Rockstuhl | Design of an artificial three-dimensional composite metamaterial with magnetic resonances in the visible range of the electromagnetic spectrum[END_REF] . They exhibit remarkable absorption and scattering properties because of the resonant nature of the inclusions that compose the ball [START_REF] Turek | Self-assembled spherical supercluster metamaterials from nanoscale building blocks[END_REF][START_REF] Dwivedi | Electromagnetic homogenization of dense clusters of metallic nanoparticles: numerical evidence of nonlocal contributions[END_REF] . They belong to the wider class of photonic balls in which we also find systems composed of dielectric nanoparticles [START_REF] Yazhgur | Inkjet printing of structurally colored self-assembled colloidal aggregates[END_REF] . These dielectric inclusions are usually larger than their plasmonic counterpart and have garnered a lot of interest recently for their ability to produce strong structural coloration [START_REF] Park | Full-spectrum photonic pigments with non-iridescent structural colors through colloidal assembly[END_REF][START_REF] Vogel | Color from hierarchy: Diverse optical properties of micron-sized spherical colloidal assemblies[END_REF] . The case of plasmonic balls is different because the inclusions are very subwavelength and resonant. The absorption and scattering of light by dense plasmonic balls is hard to describe theoretically, because even though the inclusions are subwavelength, the ensemble properties are radically different to those of the constitutive elements and cannot be predicted by traditional effective medium theories because of strong electromagnetic interactions. Recent work has shown empirically that plasmonic balls made of gold nanospheres may act as Huygens meta-atoms [START_REF] Elancheliyan | Tailored self-assembled nanocolloidal huygens scatterers in the visible[END_REF] . Huygens meta-atoms are subwavelength structures that act as strong forward-scatterers. They are named in reference to the Huygens-Fresnel principle that states that a propagating plane wave front is equivalent to a continuum of point sources of hemispherical waves emitted in the direction of propagation. These balls can be conveniently assembled through an emulsion route and as a result, they come in large numbers in the form of a suspension or ink that could eventually be used as a coating material for a surface, or even serve as the basic building block of a self-assembled metasurface.

In this work, high precision T-Matrix numerical simulations are made to design dense silver plasmonic balls in an experimentally achievable situation with the aim of achieving broadband and efficient forward-scattering in the visible range. The simulations reveal the origin of the scattering behaviour and show how they are the result of multipolar interferences between the electric and magnetic dipole moments on the redend of the visible spectrum and between the electric dipole, magnetic dipole and electric quadrupole moments on the blueend of the spectrum. Following an emulsion route similar to that proposed by Elancheliyan et al. [START_REF] Elancheliyan | Tailored self-assembled nanocolloidal huygens scatterers in the visible[END_REF] , we self-assemble dense plasmonic balls made of silver nanoinclusions and show that they exhibit strong and broadband forward-scattering as designed numerically. This is evidenced by measuring the angular dependence of the light scattered by a suspension of such balls. We also mention differences in the measured and simulated observables.

The plasmonic ball considered for the numerical simulations consists of a sphere of radius a in which silver nanoparticles of radius r = 12 nm are packed (see illustration in inset of Fig. 1(a)). The host medium surrounding the ball has a refractive index n h = 1.42. Fixing a and the volume fraction f sets the number of inclusions N per ball. In the end, the radius a of the ball is the central distance between two farthest inclusions within the ball and the diameter of an inclusion. In other words it is the maximal Feret radius. We chose f = 0.4. The dielectric constant of silver is taken from Jonhson and Christy 8 . For the computation, the ball is numerically generated by randomly distributing the inclusions within a cubic box of length L larger than a using the Lubachevsky-Stillinger (LS) algorithm [START_REF] Lubachevsky | Geometric properties of random disk packings[END_REF] . The LS-algorithm is a means of generating a random distribution of spheres in a box with a targeted volume fraction consistent with the experimental non-crystalline distributions. The number of inclusions of radius r is N = 168.

The resulting ball is then numerically implemented to compute its scattering behavior using the multiple sphere T-matrix software developed by Mackowski 10 , which enables us to compute the multipole Mie coefficients for wavelengths between 400 and 1000 nm. For f = 0.4, full-wave simulations such as the T-matrix are necessary to accurately predict the behaviour of the ball because classical effective medium theories such as the extended Maxwell-Garnett theory are highly inaccurate for such dense plasmonic media [START_REF] Dwivedi | Electromagnetic homogenization of dense clusters of metallic nanoparticles: numerical evidence of nonlocal contributions[END_REF] . We note however that forward scattering can be described by an effective homogeneous sphere in the Maxwell-Garnett approximation for photonic balls made of low index dielectric inclusions [START_REF] Yazhgur | Light scattering from colloidal aggregates on a hierarchy of length scales[END_REF] . The multipole Mie coefficients are the electric and magnetic mutipole moments (a n and b n respectively). The process of generating a ball is repeated P times and each multipole coefficient is averaged over the P realizations until a n and b n are converged within an accuracy well below one percent. Once averaged over sufficiently many realizations, we hypothesize that the scattering properties are not contingent on the method employed to generate the plasmonic ball. We find that P = 50 is sufficient to reach such an accuracy. Multipoles up to order n = 3 are kept, all higher-order multipoles are found to be vanishingly small. Next the scattering cross-section efficiency Q s = Q even + Q odd is computed and decomposed into even and odd contributions

Q even = 2 x 2 ∑ n (4n -1)|a 2n-1 | 2 + (4n + 1)|b 2n | 2 (1)
Q odd = 2 x 2 ∑ n (4n -1)|b 2n-1 | 2 + (4n + 1)|a 2n | 2 (2)
where x = 2πn h a/λ is the reduced frequency. Figure 1(a) displays Q s (λ ). The contributions to the scattering efficiency from even and odd multipoles is also shown in blue and red respectively. We find three points of interest that correspond to remarkable points of the spectral varia-tions of the efficiency for back-scattering (dashed gray curve). Point A is a minimum of back-scattering, which occurs at λ = 815 nm, when the scattering of even and odd multipoles is equal both in amplitude and in phase. This fact is evidenced by the crossing of the blue and red curves passed the resonance of both superpositions. The corresponding radiation diagram (see right-hand polar plot in Fig. 1(b)), taken in the plane parallel to the incident wavevector and orthogonal to the polarization direction, exhibits a clear zero at a scattering angle θ = 180 • and is essentially directed in the forward direction. The impinging wavevector is directed from left to right. Point B is a maximum of back-scattering at λ = 767 nm. This time the radiation diagram displays a radiation pattern that is balanced between the backward and forward directions (see central polar plot in Fig. 1(b)). In this situation the even and odd scattering have equal amplitudes but are dephased by π/2 as will be evidenced further down. Finally, point C is another minimum of back-scattering at λ = 490 nm, with a radiation diagram that also presents a zero of scattering at θ = 180 • , albeit with a distribution of the scattering that is more directional. Here, the scattering from even and odd multipoles are This is the author's peer reviewed, accepted manuscript. However, the online version of record will be different from this version once it has been copyedited and typeset. not equal in amplitude. This is due to the fact that higher order multipolar interferences occur, as we shall now see.

PLEASE CITE THIS ARTICLE AS

To get a clearer understanding of the cancellation of the back-scattering, it is useful to consider the efficiency for backscattering Q b = |E -O| 2 /x 2 , expressed as the difference be- tween even and odd multipolar superpositions 12

E = ∑ n [(4n -1)a 2n-1 + (4n + 1)b 2n ] (3)
O = ∑ n [(4n -1)b 2n-1 + (4n + 1)a 2n ] (4)
The spectral variations of |E | 2 and |O| 2 are shown on the top panel of Fig. 2(a), while the phase difference between the two ∆φ = arg(OE * ) is shown on the bottom panel. We see that the remarkable points marked in Fig. 1 coincide with specific interferences between odd and even multipole superpositions. Indeed, at point A, they are equal in amplitude and in phase (∆φ = 0) resulting in a zero of Q b . As a matter of fact at this point, the plasmonic ball is almost completely dipolar (n > 1 terms are negligible) and as a result, the first Kerker condition is satisfied: a 1 = b 1 [START_REF] Kerker | Electromagnetic scattering by magnetic spheres[END_REF] . The electric (a 1 ) and magnetic (b 1 ) dipoles constructively (resp. destructively) interfere in the forward (resp. backward) direction. For point B, even and odd contributions have equal amplitudes but are dephased (∆φ = π/2) and we have: E = O * . Since at this point too, the system is essentially dipolar, this translates into a 1 = b * 1 . So this time the backward radiation is balanced with that in the forward direction (see online supplementary material). Point C has more multipolar content as the electric quadrupole (a 2 ) can no longer be neglected. We have |E | = |O| and ∆φ = 0, which translates into an interference between the electric dipole on the one-hand and the magnetic dipole and electric quadrupole on the other: 3a 1 = 3b 1 + 5a 2 . The phase differences observed here are a consequence of the plasmonic interactions within the plasmonic ball. They stem from an interplay between the volume fraction of inclusions This is the author's peer reviewed, accepted manuscript. However, the online version of record will be different from this version once it has been copyedited and typeset. within the ball, its radius and the inclusion radius. A comprehensive understanding of this interplay remains outside the scope of this study. Here we focus only on revealing the origin of the forward scattering behaviour we wish to target experimentally. The efficiency of the forward scattering can be described by the figure-of-merit η which is the fraction of energy scattered in the forward direction (|θ | < 90 • ). η(λ ) for the plasmonic ball is compared to that of a silver nanoparticle of same size on Fig. 2(b). We see that the plasmonic ball does significantly better in terms of forward-scattering for λ > 770 nm, reaching a maximum of 98% of the total scattered energy radiated in the forward direction in A. For λ < 600 nm, we see that both particles display a similar figure-of-merit. In C, where the electric quadrupole is present in the multipolar content, η ≈ 96%.

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The observations made on the plasmonic ball of radius a = 90 nm were also observed for simulations of balls of radius a ∈ [80, 90, 100, 110, 120] nm and identical volume fraction ( f = 0.4). Figure 2(c) compares η(a) at point A, defined as the first minimum of Q b (starting from the long-wavelength limit), for both the plasmonic ball and the silver nanoparticle. We see that at this point, η > 97% for all sizes of the plasmonic ball and it scatters 9 to 10% more energy forward compared to the silver nanoparticle of same size.

The plasmonic balls are fabricated via an emulsion route sketched on Fig. 3(a). An initial aqueous suspension of silver nanoparticles coated with PVP of radius r = 12 nm were emulsified in an oil phase composed of dodecane oil of refractive index 1.42. The internal water phase is then evaporated using a rotavapor flask at room temperature under low pressure. The samples are characterized using dynamic light scattering and the mean hydrodynamic radius is found to be a = 88 nm with a relative standard deviation of 8%. Typical transmission electron micrographs (TEM) of the plasmonic balls found in the emulsion are shown on Fig. 3(b-d). They are typically composed ∼ 150 silver nanoinclusions. Smallangle X-ray scattering experiments performed on the fabricated sample indicate no evidence of crystallization of the NPs within the balls, we thus conclude that the plasmonic balls are disordered (see supplementary material -SM -for additional information on fabrication and structural characterization of the plasmonic balls).

We characterize the suspension obtained, by using a variable-angle spectroscopic polarization resolved static light scattering setup (described in section 3.2 in [START_REF] Aradian | The Bottom-Up Approach toward Artificial Optical Magnetism in Metastructures[END_REF] ). The sample is mounted on a goniometric mount so as to measure the light scattered by the sample over a wide range of scattering angles from θ = 20 (forward) to θ = 160 (backward). The light scattered is analyzed on a detection arm that rotates around the sample. It contains an analyzer which selects either the polarization parallel or orthogonal to the scattering plane. As a result, the differential scattering cross-section σ ′ (θ , λ ) can be retrieved, as the sum of the contributions from polarizations parallel (σ ′ ) and orthogonal (σ ′ ⊥ ) to the scattering plane, that can both be quantitatively determined from proper normalization and knowledge of the concentration of plasmonic balls in solution. σ ′ (θ , λ ) is displayed as a color plot on Fig. 4(a) and shows that the scattering from a suspension of plasmonic balls is dually resonant at λ ≈ 700 nm and λ ≈ 450 nm, reminiscent of points A, where a 1 ≈ b 1 and C, where 5a 2 ≈ 3(a 1b 1 ). Furthermore the scattering is essentially directed in the forward direction within a scattering angle smaller than 45 • typically. The online SM provides details on how σ ′ could be determined quantitatively. Both parallel and perpendicular contributions to σ ′ are shown as a function of wavelength for θ = π/2 on Fig. 4(b) and compared to the simulation on Fig. 4(c). At that scattering angle, the perpendicular and parallel contributions only contain a superpo-This is the author's peer reviewed, accepted manuscript. However, the online version of record will be different from this version once it has been copyedited and typeset.

PLEASE CITE THIS ARTICLE AS DOI: 10.1063/5.0182709 sition of even and odd multipoles respectively [START_REF] Bohren | Absorption and scattering of light by small particles[END_REF] . We see that σ ′ ≈ σ ′ ⊥ experimentally for λ ∈ [650, 780] nm in a spectral region where it is mostly dipolar. We can reasonably infer that for such wavelengths, a 1 ≈ b 1 . There are notable differences with the simulated spectrum, where a 1 = b 1 only at point A. The experimental spectrum is smeared in comparison to theory and the overlap occurs over a wider spectral range. We attribute this difference to the polydispersity of the suspension of plasmonic balls. Nonetheless it is remarkable that the intervals of variation of σ ′ both in the experiment and the theory are very close, notably near the resonance (≈ 1 × 10 4 nm 2 /sr), keeping in mind that this result is retrieved with no adjustable parameters. For λ = 490 nm, corresponding to point C in the simulation, where the electric quadrupole interferes with the electric and magnetic dipoles, we note that the fraction σ ′ ⊥ /σ ′ are sensibly the same and close to 0.5 (0.45 in the experiment and 0.56 in the simulation).

We have simulated and fabricated dense plasmonic balls and demonstrated that they exhibit broadband efficient resonant forward-scattering at visible frequencies. We reveal that this behavior is the result of multipolar interferences and highlight the role of the electric quadrupole in the blue-end of the spectrum and that of the magnetic dipole at the red-end. These plasmonic balls come in large quantities in solution and can be scaled-up easily. However, as evidenced in this letter, polydispersity should be reduced for future functional requirements and device reliability. To this end, on chip microfluidic approaches appear as promissing solutions as they are known to produce emulsions with very well controlled droplet sizes. They hold the potential of drastically reducing polydispersity. Furthermore, an in-depth study of the impact of plasmonic ball size and volume fraction could also reveal how polydispersity influences its multipolar content and spectral features. When such issues are solved, plasmonic balls will have the potential to serve as efficient meta-atoms for metasurfaces applications, notably those that require strongly forward-scattering resonators also known as generalized Huygens sources [START_REF] Staude | Tailoring directional scattering through magnetic and electric resonances in subwavelength silicon nanodisks[END_REF][START_REF] Kruk | Invited article: Broadband highly efficient dielectric metadevices for polarization control[END_REF][START_REF] Dezert | Complete multipolar description of reflection and transmission across a metasurface for perfect absorption of light[END_REF] .

SUPPLEMENTARY MATERIAL

A supplementary material file is available online. It contains additional information on the general theoretical framework used in this work, numerical implementation of the plasmonic ball, fabrication and structural characterization of the plasmonic balls, definition of the fraction of energy scattered forward, as well as a description of the experimental setup and method used for the optical characterization of the balls and retrieval of the differential scattering cross-section.

FIG. 1 .

 1 FIG. 1. Scattering behavior of silver plasmonic balls. The plasmonic ball has a size 2a = 180 nm and is composed of nanoinclusions of 12 nm in radius. The refractive index of the host medium is 1.42, while the homogeneous matrix surrounding the ball has a refractive index of 1.4. (a) Spectral distribution of the total scattering cross-section efficiency (in black). The blue (red) curve is the superposition of the efficiencies of all even (odd) multipoles. The grey dashed curve is the efficiency for back-scattering. (b) Scattering diagram at three different wavelengths (A: 815 nm, B: 767 nm, C: 490 nm), taken in the plane orthogonal to the polarization direction. The impinging plane wave propagates from left to right.

  FIG. 2. Origin of the scattering behavior and forward-scattering efficiency. (a) Top panel: Spectral variations of |E | 2 and |O| 2 . Bottom panel: Phase difference ∆φ = arg(OE * ) between odd and even multipole superpositions. (b) Comparison of the fraction of energy scattered in the forward direction η as a function of wavelength for the plasmonic ball of size 2a = 180 nm (in blue) and a silver nanoparticle of same size (in red). (c) Comparison of η for the plasmonic ball (in blue) and the silver nanoparticle (in red) as a function of particle radius at three different wavelengths (A: 815 nm, C: 490 nm).

FIG. 3 .

 3 FIG. 3. Experimental plasmonic balls. (a) Illustration of the emulsion drying process of plasmonic ball formation from an emulsion of dilute silver nanoparticle suspensions to a dense spherical ball. (b) Transmission electron micrographs of typical plasmonic balls obtained experimentally. The arrow is 88 nm in length corresponding to the average hydrodynamic radius of the balls in solution.

  FIG. 4. Forward-scattering of silver plasmonic balls. (a) Color plot of the differential scattering cross-section σ ′ (θ , λ ) (in nm 2 /sr) as a function of wavelength and scattering angle. (b) Spectral variations of the parallel (in blue) and orthogonal (in red) components of σ ′ (θ = π/2, λ ). The curves are normalized to the maximum value of the parallel component of σ ′ . (c) Simulated spectral variations of the perpendicular (in blue) and parallel (in red) components of σ ′ .

This is the author's peer reviewed, accepted manuscript. However, the online version of record will be different from this version once it has been copyedited and typeset.PLEASE CITE THIS ARTICLE AS DOI: 10.1063/5.0182709

DATA AVAILABILITY STATEMENT

The data that support the findings of this study are available from the corresponding author upon reasonable request.

AUTHOR DECLARATIONS

The authors have no conflicts to disclose.