1 Diversity and antibiotic resistance in bacteria associated with symptoms of bacterial infection in Costa Rican crops 1Lorena Uribe-Lorío*, Centro de Investigación en Biología Celular y Molecular, Universidad de Costa Rica, San Pedro, San José, Costa Rica, CP 1501-2060; 1Lidieth Uribe, Centro de Investigaciones Agronómicas, Universidad de Costa Rica, San Pedro, San José, Costa Rica, CP 1501-2060; César Rodríguez, Fernando García, Centro de Investi- gación en Enfermedades Tropicales (CIET), Facultad de Microbiología, Universidad de Costa Rica, San Pedro, San José, Costa Rica, CP 1501-2060; Luis Felipe Aráuz, 1Escuela de Agronomía, Universidad de Costa Rica, San Pedro, San José, Costa Rica, CP 1501-2060. *Corresponding Author: Lorena Uribe-Lorío lorena.uribe@ucr.ac.cr Section: Periodical Issue Received: 26 May, 2023 Accepted: 05 January, 2024 Published: 26 February, 2024 Citation: Uribe-Lorío L, Uribe L, Rodríguez C, García F and Aráuz LF. 2024. Diversity and antibiotic resistance in bacteria associated with symptoms of bacterial infection in Costa Rican crops. Mexican Journal of Phytopathology 42(2): 13. https://doi.org/10.18781/R. MEX.FIT.2305-5 Open access Scientific Article Copyright: © 2023 by the authors. Licensee RMF / SMF, Mexico. This article is an open access article distributed under the terms and conditions of SMF. www.rmf.smf.org.mx. ABSTRACT Objetive/Background. The aim of this was to assess the diversity and antibiotic resistance of bacteria isolated from 19 crops with bacterial infection symptoms. Material and Methods. This collection was identified using 16S rRNA gene sequencing and the Biolog system. Susceptibility and minimum inhibitory concentration (MIC) for streptomycin, tetracycline, and gentamicin were determined using disk diffusion and E-test methods, respectively. Results. A total of 55 species belonging to 20 bacterial genera were identified, with Pseudomonas, Serratia, Pantoea, and Stenotrophomonas being the most abundant. Approximately 27% of the isolates were categorized as pathogenic through the hypersensitivity reaction test, including phytopathogenic species like Pseudomonas syringae, P. cichorii, Pantoea anthophila, P. stewartii, Stenotrophomonas maltophilia, Dickeya oryzae, Erwinia billingiae, Pectobacterium aroidearum, and Enterobacter cloacae subsp. dissolvens. Resistance to at least one antibiotic was detected in 60% of isolates from 17 crops, with tomatoes, heart of palm, and lettuce exhibited the highest proportion of resistant bacteria (>80%). Streptomycin resistance was most common (35%), followed by tetracycline (28%) and gentamicin (9%). Conclusions. The findings indicate the presence of antibiotic resistance in saprophytic and pathogenic bacteria associated with 17 out of 19 assessed crops, posing risks to the environment, phytosanitary conditions, and public health. Mexican Journal of Phytopathology ISSN: 2007-8080 Mexican Journal of Phytopathology. Scientific Article. Open access Uribe-Lorío et al., 2024. Vol. 42(2): 13 2 Keywords. Bacteria, Phytopathogen, Antimicrobial, Phyllosphere, Control Introduction Bacteria associated with plants can thrive as epiphytes or endophytes (Agrios, 2005), and in most cases, they perform functions crucial for maintaining the system’s equilibrium, such as nitrogen fixation and antagonism against phytopathogens (Arauz, 2011; Nion and Toyota, 2015; Compant et al., 2019; Hashem et al., 2019). These bacteria share their niche with phytopathogenic bacteria that utilize plants as a nutrient source and have specialized in evading their defenses, consequently invading the host plant’s tissues (Vidaver and Lambrecht, 2004; Agrios, 2005; Kannan and Bastas, 2015). In Costa Rica, several genera have been reported as pathogens of ornamental plants and foliage, including Erwinia, Pectobacterium, Pseudomonas, Xanthomonas, Burkholderia, and the Ralstonia solanacearum species complex (Arauz, 2011; Quesada-González and García-Santamaría, 2014; Cubero-Agüero et al., 2021; López, 2021; Vidaurre-Barahona et al., 2021). Infections caused by these bacteria can manifest as fruit spots (Pseudomonas syringae and Xanthomonas campestris), cankers (Erwinia and Pseudomonas), wilting (Ralstonia solanacearum), and soft rot (Pectobacterium carotovorum and Dickeya dadanti) (Vidaver and Lambrecht, 2004; Agrios, 2005; Arauz, 2011; Bellincampi et al., 2014). The variety of symptoms and host plants make these pathogens responsible for severe damage to crops, thereby affecting the agricultural sector’s economy. Additionally, these diseases are more severe and frequent in tropical and subtropical regions where the warm and humid conditions are ideal for their development, and there is no reduction in inoculum due to winter’s low temperatures (Arauz, 2011; Kannan and Bastas, 2015; Miller et al., 2022). Hence, combatting these pathogens is crucial for preserving agroecosystem productivity. However, only a few substances are effective or readily available to mitigate crop losses, among wich antibiotics are included. Presently, the most widely used antibiotics globally are streptomycin, oxytetracycline, penicillin, oxolinic acid, and gentamicin (McManus et al., 2002; Mann et al., 2021; Miller et al., 2022). Among these, streptomycin and oxytetracycline are approved for agricultural use in the United States, in contrast to the European Union and other developed countries where their use is prohibited due to their medical significance (WHO, 2019). The use of antibiotics is the prevailing approach for managing bacterial diseases in low and middle-income countries (LMICs) (Miller et al., 2022). This is notably the case in Latin America and the Caribbean, where they are used without restrictions, despite the risk of resistance development (Rodríguez et al., 2006; Rodríguez et al., Mexican Journal of Phytopathology. Scientific Article. Open access Uribe-Lorío et al., 2024. Vol. 42(2): 13 3 2008; MSP, 2018; Taylor and Reeder, 2020), with varying outcomes in combating bacterial diseases in crops (McManus et al., 2002; Stockwell and Duffy, 2012). Despite the capability of phytopathogenic bacteria to infiltrate plant tissues and multiply (Sundin et al., 2016), most formulations are applied to the aerial parts, resulting in reduced absorption, translocation, and efficiency (McManus et al., 2002; Agrios, 2005). For example, the foliar absorption of oxytetracycline in citrus is quite limited, necessitating trunk injection to combat Candidatus Liberibacter asiaticus in this crop (Killiny et al., 2020). Bactericides and antibiotics are the most commonly used compounds for controlling phytopathogenic bacteria in Costa Rica (Ramírez-Muñoz et al., 2014; Durán-Quirós et al., 2017; Blanco-Meneses et al., 2023). These include oxytetracycline, gentamicin, as well as combinations of these with streptomycin (gentamicin and oxytetracycline in Agri-Gent Plus 4 and 8, streptomycin and oxytetracycline in Agry-mycin 16.5) (Rodríguez et al., 2006; Galt, 2009; MSP, 2018). The absence of an integrated registration system in the country limits the control of efficient use of these products in humans, animals, and plants (MSP, 2018). De la Cruz et al. (2008) found that antibiotic usage in the cultivation of Cucumis melo, Citrullus lanatus, and Oryza sativa in the Arenal-Tempisque irrigation district ranged from 7.4-155.0 g ha-1 per year for both streptomycin and oxytetracycline; other studies indicate discrepancies among producers concerning dosage, frequency of application, and pre-harvest intervals (Durán-Quirós et al., 2017; Blanco-Meneses et al., 2023). Antibiotics can remain active on plant surfaces for at least one week (Stockwell and Duffy, 2012), which, coupled with their frequent use, can lead to the development of resistant bacteria (Silbergeld et al., 2008; Alós, 2014; FAO, 2021). In this regard, Rodríguez et al. (2006; 2008) identified epiphytic bacteria resistant to gentamicin and oxytetracycline in lettuce (Lactuca sativa) samples and agricultural soils, as well as genetic determinants of resistance, implying the dissemination of resistant bacteria across different environments and/or horizontal gene transfer. Nevertheless, the presence of antimicrobial-resistant phytopathogenic bacteria has not been studied. Therefore, this study aimed to analyze the diversity of a bacterial collection isolated from lesions in various crops exhibiting bacterial infection symptoms in Costa Rica and to evaluate their resistance to streptomycin, oxytetracycline, and gentamicin, antibiotics commonly used for managing plant bacterial diseases in this country. Materials and Methods Bacterial isolates. We analyzed 116 Gram-negative bacteria from the collection of the Environmental Microbiology Laboratory at the Center for Research in Cellular Mexican Journal of Phytopathology. Scientific Article. Open access Uribe-Lorío et al., 2024. Vol. 42(2): 13 4 and Molecular Biology. These bacteria were isolated between 2006 and 2009 from samples originating in various agricultural areas of Costa Rica. Tissue from the advancing lesion zone in plants displaying symptoms associated with bacterial pathogens was selected for analysis. Relevant information regarding this bacterial collection is presented in Table 1. Table 1. Characteristics of bacterial isolates collection established from symptoms in 19 crops in different regions of Costa Rica between 2006 and 2009. Host plant Common name Nº samples Plant tissue Symptoms Collecting site Nº of isolates Apium graveolens Cellery 3 Stem Soft rot (Figure 1D) Cartago 6 Bactris gasipaes Palm heart 3 Leaf Necrosis Limón 6 Brassica oleracea var. botrytis Cauliflower 2 Leaf Spot Heredia 5 Brassica oleracea var. capitata Cabbage 6 Leaf Angular necrosis (Figure 1H), Spot, Soft rot Heredia, Cartago 25 Capsicum annuum Bell pepper 2 Fruit Soft rot (Figure 1E) Cartago 9 Cucumis melo Cantaloupe 1 Fruit Soft rot Guanacaste 5 Cucurbita pepo Summer squash 1 Fruit Soft rot (Figure 1G) Cartago 3 Curcuma longa Turmeric 2 Root Soft rot Guanacaste 4 Daucus carota Carrot 1 Root Soft rot Alajuela 1 Dracaena massangeana Cornplant 2 Stem Soft rot (Figure 1F) Alajuela 7 Ficus carica Fig 1 Leaf Spot Alajuela 1 Lactuca sativa Boston lettuce 2 Leaf Spot (Figure 1A) Cartago 5 Lactuca sativa var. capitata Iceberg lettuce 6 Stem, Leaf Soft rot (Figure 1B), Spot Cartago 11 Mangifera indica Mango 2 Fruit Spot (Figure 1I) Alajuela 4 Musa paradisiaca Banana 5 Stem, crown Soft rot, Stem necrosis Limón 12 Ornithogalum arabicum Arabian startflower 1 Leaf Soft rot Alajuela 2 Phaseolus vulgaris Bean 2 Leaf Spot Heredia 3 Solanum lycopersicum Tomato 3 Fruit, Leaf Fruit and leaf spots, Fruit soft rot Alajuela, Cartago 6 Solanum tuberosum Potato 1 Root Soft rot Cartago 1 Total 46 116 Identification of the Bacteria Collection by Analysis of the Ribosomal 16S RNA Gene. Each bacterium was inoculated into 3 mL of nutrient broth and incubated for 24- 48 hours at 30 °C. Subsequently, the resulting growth was centrifuged for 5 minutes at 10,000 rpm to obtain biomass. DNA from this biomass was extracted following the protocol reported by Fontecha (2003). Amplification of the 16S rRNA gene was Mexican Journal of Phytopathology. Scientific Article. Open access Uribe-Lorío et al., 2024. Vol. 42(2): 13 5 performed using universal primers: 27F (AGAGTTTGATCMTGGCTCAG) and 1492R (TACGGYTACCTTGTTACGACTT) (Weisburg et al., 1991). Each PCR reaction was conducted in a 50 μL mixture containing 0.8 μL (200 μM) of each dNTPs (Thermo Scientific), 2.5 μL (1.25 mM) of MgCl2 (Thermo Scientific), 2.0 μL (0.4 μM) of each primer, 0.5 U of Taq DNA polymerase (Thermo Scientific), 5.0 μL of 1X KCl buffer without MgCl2 (Thermo Scientific), and approximately 10 ng of genomic DNA. The reactions were amplified following the program and conditions reported by Fontecha (2003): an initial denaturation step at 94 °C for 4 minutes, followed by 34 cycles consisting of denaturation at 94 °C for 30 seconds, annealing at 50 °C for 30 seconds, and extension at 72 °C for 90 seconds, with a final extension step at 72 °C for 10 minutes. The PCR products were visualized on a 1% agarose gel. Amplification products were purified using the Wizard PCR Figure 1. Symptoms of bacterial infection from which the bacterial collection were isolated. A. Leaf spot in Boston Lettuce, B. Soft rot in Iceberg Lettuce, C. Necrotic spot on Tomato. D. Soft rot in Celery. E. Soft rot in Pepper. F. Soft rot in Dracaena. G. Soft rot in Pumpkin. H. Angular necrosis in Cabbage. I. Fruit spot in Mango. Mexican Journal of Phytopathology. Scientific Article. Open access Uribe-Lorío et al., 2024. Vol. 42(2): 13 6 Preps DNA Purification System kit (Promega, Madison, Wisconsin, United States) following the manufacturer’s instructions. Sequencing was carried outusing an ABI PRISM 3130 sequencer with the BigDye® Terminator v3.1 Cycle Sequencing RR-100 kit (Applied BioSystems) or, alternatively, by Macrogen (Korea). The resulting sequences were assembled using BioEdit Sequence Alignment Editor Version 7.2 (Hall, 1999). Homology searches were performed using the NCBI BLASTN database (National Center for Biotechnology Information) to identify similarities with sequences deposited in GenBank (Altschul et al., 1997) and the EzbioCloud extension (Yoon et al., 2017), which stores 16S rRNA gene sequences from reference strains with valid taxonomic assignments. Phylogenetic analysis. The sequences were aligned using ClustalX (Larkin et al., 2007) within the MEGA program (Tamura et al., 2013), and a phylogenetic analysis was conducted with sequences from reference-type strains and Bacillus subtilis (NR112116) as an outgroup. Distances were calculated using Neighbour Joining inference, and tree topology was assessed through 1,000 resamplings. The tree was visualized using the ITOL tool (https://itol.embl.de.com). The obtained sequences were deposited in the GenBank database of the NCBI under the bioproject PRJNA898399. Identification of isolates by Biolog semi-automated system™. The Biolog™ system was employed for the identification of isolates that did not yield conclusive results in molecular identification. This system compares the redox reactions of 95 carbon sources and other substances with a database that includes environmental bacteria, including phytopathogens. To accomplish this, 24-hour bacterial cultures of each isolate were inoculated onto identification plates following the manufacturer’s instructions. Readings were taken after 24 hours, and the closest identification according to the Biolog software was recorded. Antibiotic Susceptibility Profile and Minimum Inhibitory Concentration (MIC) Determination. Antibiotic susceptibility to streptomycin, gentamicin, and tetracycline was assessed using the Kirby-Bauer agar diffusion method. We employed antibiotic impregnated mono-discs with standard quantities (Oxoid): 10 mg for streptomycin and gentamicin, and 30 ng for tetracycline. These discs were placed on cultures of each isolate on Muller-Hinton agar, and subsequently, the growth inhibition zone was measured (Sánchez and Guerrero, 2006). The measurements were compared with arbitrary unique cutoff points based on recommendations for clinically relevant bacteria within the taxonomic families described below: Tetracycline-resistant (≤ 14 mm), intermediate (15-18 mm), susceptible (≥19 mm). Gentamicin-resistant (≤ 12 mm), intermediate (13-14 mm), Mexican Journal of Phytopathology. Scientific Article. Open access Uribe-Lorío et al., 2024. Vol. 42(2): 13 7 susceptible (≥15 mm). Streptomycin-resistant (≤ 11 mm), intermediate (between 12-14 mm), susceptible (≥15 mm), which correspond to the breakpoints for Pseudomonas aeruginosa, Acinetobacter sp., and enterobacteria (NCCLS, 2000). E. coli (ATCC-25922) and Pseudomonas aeruginosa (ATCC-15442) strains were used as controls. Isolates categorized as resistant or intermediate were subjected to minimum inhibitory concentration (MIC) determination for streptomycin, gentamicin, and oxytetracycline using the E-test epsilometric method (AB Biodisk, Solna, Sweden). This method involves a solid strip featuring a reading scale and an exponential gradient of antimicrobial, facilitating MIC determination across suitable concentrations (Alippi et al., 2013). We followed the protocol reported by Lang and García (2004), using LB agar as the culture medium and incubating at 30 °C. After the incubation period, the minimum inhibitory concentrations were documented. Phytopathogenicity-Antibiotic Resistance Relationship. To investigate the potential relationship between resistance to the three antibiotics and the phytopathogenicity of the analyzed bacteria, we utilized hypersensitivity reaction (HR) data (Table 2) previously obtained (Herrera, 2009). For this purpose, 24-hour suspensions of each isolate were inoculated onto Nicotiana tabacum leaves using the imprinting technique described by Trigiano et al. (2004). HR was graded from levels 0 to 5, with negative reactions ranging from levels 0 to 2 indicating either no reaction to minimal chlorosis without necrosis. Positive reactions were categorized from level 3, displaying intense chlorosis with necrosis, to level 4, featuring typical HR necrosis confined within vascular bundles or leaf veins, or necrosis extending beyond that area (level 5). Results Identification of the Bacterial Collection through 16S rRNA Gene Analysis and Phylogenetic Analysis. We successfully obtained 90 sequences with the necessary quality for molecular identification, and the remaining 26 isolates were identified using the Biolog™ System (Table 2). The 116 isolates were grouped into 20 bacterial genera, with the majority classified as Pseudomonas (48%), followed by Serratia (12%), Pantoea (9%), Stenotrophomonas (6%), and Psychrobacter (5%). The other 15 genera represented less than 5% of the total collection, with 10 of them having only one representative (Table 2). A total of 55 bacterial species were identified, with the majority falling within the Proteobacteria phylum (53 species), specifically in the Gammaproteobacteria class, with one isolate each from Alfaproteobacteria (Ochrobactrum) and Betaproteobacteria (Achromobacter). Additionally, one Mexican Journal of Phytopathology. Scientific Article. Open access Uribe-Lorío et al., 2024. Vol. 42(2): 13 8 Table 2. Molecular identification and resistance levels to streptomycin, tetracycline, and gentamicin of bacteria associated with infection symptoms in crops collected from 2006-2009 in Costa Rica. Code Host Sint.a Plant tissue HRb Identification (RNA 16S and BiologTM) MICc (µg mL-1) EST TET GEN MA-6 Apium graveolens SR Stem 0 Pseudomonas protegens CHA0T >1024* MA-7 Apium graveolens SR Stem 2 Pseudomonas capeferrum WCS358T 512* - MA-15 Apium graveolens SR Stem 1 Pseudomonas arauntiaca (Biolog)* - MA-16 Apium graveolens SR Stem 2 Serratia marcescens ATCC 13880T 512* MA-79 Apium graveolens SR Stem 2 Pseudomonas capeferrum WCS358T - MA-86 Apium graveolens SR Stem 2 Pseudomonas koreensis Ps 9-14T 128* 24 MA-50 Bactris gasipaes N Leaf 4 P. stewartii sp. indologenes LMG 2632T MA-52 Bactris gasipaes N Leaf 5 Stenotrophomonas maltophilia ATCC 19861T 12 12 MA-53 Bactris gasipaes N Leaf 2 Stenotrophomonas maltophilia ATCC 19861T 12 MA-54 Bactris gasipaes N Leaf 5 Stenotrophomonas maltophilia ATCC 19861T 12 24 256 MA-55 Bactris gasipaes N Leaf 2 Providencia rettgeri DSM 4542T 12 - MA-65 Bactris gasipaes N Leaf 5 P. stewartii sp. indologenes LMG 2632T 12 12 MA-30 Brassica oleracea var. botrytis S Leaf 0 Serratia marcescens ATCC 13880T MA-95 Brassica oleracea var. botrytis S Leaf 5 Pseudomonas protegens CHA0T - MA-110 Brassica oleracea var. botrytis S Leaf 2 Stenotrophomonas maltophilia (Biolog) - MA-142 Brassica oleracea var. botrytis S Leaf 0 Stenotrophomonas rhizophila DSM14405 >1024 MA-143 Brassica oleracea var. botrytis S Leaf 0 Acinetobacter lactucae NRRLB-41902T 12* - 32 MA-9 Capsicum annuum SR Fruit 2 Pseudomonas maumuensis COW77T MA-10 Capsicum annuum SR Fruit 2 Serratia marcescens ATCC 13880T 16* >256 - MA-11 Capsicum annuum SR Fruit 2 Pantoea vagans LMG 24199T - MA-14 Capsicum annuum SR Fruit 1 Acinetobacter lactucae NRRL B-41902T MA-19 Capsicum annuum SR Fruit 5 Pantoea anthophila LMG 2558T >1024 - MA-33 Capsicum annuum SR Fruit 4 Pseudomonas punonensis CECT 8089 - >256 MA-90 Capsicum annuum SR Fruit 4 Pseudomonas fragi ATCC 4973T MA-120 Capsicum annuum SR Fruit 4 Raoultella terrigena ATCC 33257T >256 MA-140 Capsicum annuum SR Fruit 5 Pseudomonas protegens CHA0T - - 12 MA-128 Cucumis melo SR Fruit 2 Klebsiella pneumoniae DSM 30104T MA-129 Cucumis melo SR Fruit 1 Pseudomonas sp. (Biolog) - MA-130 Cucumis melo SR Fruit 5 Pseudomonas protegens CHA0T 12 12 MA-131 Cucumis melo SR Fruit 1 Pseudomonas protegens CHA0T 12 MA-132 Cucumis melo SR Fruit 3 Achromobacter marplatensis LMG 26685T >1024 12 MA-2 Curcuma longa SR Root 4 E. cloacae subsp. dissolvens LMG 2683T - 12 MA-8 Curcuma longa SR Root 1 Serratia marcescens (Biolog) - MA-38 Curcuma longa SR Root 0 Enterobacter huaxiensis 090008T - MA-61 Curcuma longa SR Root 2 Pseudomonas fragi ATCC 4973T >1024* MA-4 Dracaena massangeana SR Stem 2 Psychrobacter alimentarius JG-100T 12 MA-27 Dracaena massangeana SR Stem 1 Pantoea vagans LMG 24199T MA-42 Dracaena massangeana SR Stem 2 Pseudomonas putida NBRC 3738T 48* MA-43 Dracaena massangeana SR Stem 2 Comamonas koreensis KCTC 12005T 12 - MA-88 Dracaena massangeana SR Stem 0 Pseudomonas fluorescens (Biolog) - MA-89 Dracaena massangeana SR Stem 2 Pantoea vagans LMG 24199T - MA-136 Dracaena massangeana SR Stem 0 Pantoea agglomerans (Biolog) MA-59 Ficus carica S Leaf 0 O. pseudogrignonensis CCUG 30717T - 96 MA-5 Lactuca sativa var. capitata SR Leaf 0 Pseudomonas putida (Biolog) MA-13A Lactuca sativa var. capitata SR Stem 4 Pectobacterium aroidearum SCRI 109T 12 MA-13B Lactuca sativa var. capitata S Leaf 4 Pseudomonas capeferrum WCS358T 96 MA-14C Lactuca sativa var. capitata SR Stem 5 Stenotrophomonas maltophilia ATCC 19861T - 48 Mexican Journal of Phytopathology. Scientific Article. Open access Uribe-Lorío et al., 2024. Vol. 42(2): 13 9 Code Host Sint.a Plant tissue HRb Identification (RNA 16S and BiologTM) MICc (µg mL-1) EST TET GEN MA-17 Lactuca sativa var. capitata SR Leaf 1 Pseudomonas azotoformans LMG 21611T MA-23A Lactuca sativa var. capitata S Leaf 3 Pantoea vagans LMG 24199T 12 MA-224 Lactuca sativa var. capitata S Leaf 4 Pseudomonas oryzihabitans NBRC 102199T 12 MA-43A Lactuca sativa var. capitata SR Leaf 4 Raoultella terrigena ATCC 33257T 12 MA-82 Lactuca sativa var. capitata SR Leaf 1 Pseudomonas extremorientalis KMM 3447T - 24 MA-60 Lactuca sativa var. capitata SR Leaf 1 Pseudomonas sp. (Biolog) MA-84 Lactuca sativa var. capitata SR Leaf 2 Pseudomonas putida (Biolog) - MA-40 Lactuca sativa S Leaf 1 Pseudomonas fragi ATCC 4973T 32* MA-44 Lactuca sativa S Leaf 2 Pseudomonas punonensis CECT 8089T - >256 - MA-49 Lactuca sativa S Leaf 4 Pseudomonas cichorii ATCC10857T MA-111 Lactuca sativa S Leaf 0 Serratia marcescens ATCC 13880T - >256 MA-112 Lactuca sativa S Leaf 2 Pantoea vagans LMG 24199T - 128 MA-115 Mangifera indica S Fruit 2 Erwinia billingiae CIP 106121T MA-124 Mangifera indica S Fruit 2 Pseudomonas putida NBRC 3738T MA-125 Mangifera indica S Fruit 0 Pseudomonas sp. (Biolog) MA-127 Mangifera indica S Fruit 1 Pseudomonas putida (Biolog) MA-24 Musa paradisiaca SR Stem 1 Pseudomonas sp. (Biolog) MA-51 Musa paradisiaca N Stem 1 Pseudomonas sp. (Biolog) - 12 MA-68 Musa paradisiaca SR Stem 2 Acinetobacter sp. (Biolog) MA-72 Musa paradisiaca SR Stem 1 Pseudomonas sp. (Biolog) - - MA-77 Musa paradisiaca N Stem 2 Aeromonas caviae (Biolog) - 12 MA-87 Musa paradisiaca SR Stem 0 Serratia marcescens ATCC 13880T >1024 >256 MA-97 Musa paradisiaca SR Stem 2 Pseudomonas sp. (Biolog) - 12 MA-101 Musa paradisiaca SR Stem 2 Pseudomonas protegens CHA0T 12 MA-117 Musa paradisiaca SR Stem 1 Achromobacter spanius LMG 5911T - MA-118 Musa paradisiaca SR Stem 4 Pseudomonas protegens CHA0T - >256 - MA-119 Musa paradisiaca SR Stem 1 Pseudomonas putida NBRC 3738T 12 - MA-139 Musa paradisiaca N Stem 1 Pseudomonas sp. (Biolog) - - - MA-1 Ornithogalum arabicum SR Leaf 0 Psycrobacter faecalis Iso-46T - MA-13 Ornithogalum arabicum SR Leaf 1 Pseudomonas putida NBRC 3738T 24* - - MA-37 Phaseolus vulgaris S Leaf 4 Pseudomonas syringae ATCC 19304T 24* MA-70 Phaseolus vulgaris S Leaf 5 Pseudomonas syringae ATCC 19304T MA-81 Phaseolus vulgaris S Leaf 1 Pseudomonas azotoformans DSM 18862T - MA-12 Solanum tuberosum SR Root 0 Psychrobacter aquaticus CMS 56T - MA-18 Brassica oleracea var. capitata SR Leaf 3 Sphingobacterium kitahiroshimense 10CT 12 - 256 MA-22 Brassica oleracea var. capitata N Leaf 2 Psychrobacter pulmonis CECT 5989T MA-23 Brassica oleracea var. capitata S Leaf 2 Pseudomonas sp. (Biolog) MA-26 Brassica oleracea var. capitata N Leaf 1 Pseudomonas moraviensis CCM 7280T - MA-28 Brassica oleracea var. capitata N Leaf 0 Serratia marcescens ATCC 13880T - >256 MA-29 Brassica oleracea var. capitata N Leaf 0 Serratia marcescens (Biolog) - >256 MA-32 Brassica oleracea var. capitata SR Leaf 1 Pantoea vagans LMG 24199T - - 256 MA-34 Brassica oleracea var. capitata N Leaf 1 Pseudomonas protegens CHA0T 48* 24 MA-35 Brassica oleracea var. capitata S Leaf 1 Serratia marcescens ATCC 13880T >256 MA-36 Brassica oleracea var. capitata SR Leaf 5 Pantoea vagans LMG 24199T MA-39 Brassica oleracea var. capitata N Leaf 1 Psycrobacter faecalis Iso-46T MA-41 Brassica oleracea var. capitata N Leaf 2 Pseudomonas capeferrum WCS358T >1024* - - MA-46 Brassica oleracea var. capitata S Leaf 0 Pseudomonas saponiphila DSM 975T MA-48 Brassica oleracea var. capitata S Leaf 0 Pseudomonas laurylsulfativorans AP3_22T - - Table 2. Continue... Mexican Journal of Phytopathology. Scientific Article. Open access Uribe-Lorío et al., 2024. Vol. 42(2): 13 10 Code Host Sint.a Plant tissue HRb Identification (RNA 16S and BiologTM) MICc (µg mL-1) EST TET GEN MA-57 Brassica oleracea var. capitata S Leaf 1 Serratia marcescens ATCC 13880T - >256 MA-76 Brassica oleracea var. capitata S Leaf 1 Serratia marcescens (Biolog) - MA-85 Brassica oleracea var. capitata S Leaf 4 Pseudomonas protegens CHA0T - MA-91 Brassica oleracea var. capitata N Leaf 4 Psychrobacter pulmonis CECT 5989T 24 MA-96 Brassica oleracea var. capitata S Leaf 2 Pseudomonas hunanensis LVT - 18 MA-98 Brassica oleracea var. capitata N Leaf 2 Carnobacterium inhibens DSM 13024T - >256 MA-103 Brassica oleracea var. capitata S Leaf 0 Serratia marcescens ATCC 13880T 32* 16 MA-104 Brassica oleracea var. capitata S Leaf 4 Escherichia hermannii CIP 103176T - >1024 MA-105 Brassica oleracea var. capitata S Leaf 1 Pseudomonas fluorescens (Biolog) 24* MA-106 Brassica oleracea var. capitata N Leaf 1 Acinetobacter johnsonii CIP 64.6T - >256 MA-107 Brassica oleracea var. capitata S Leaf 3 Stenotrophomonas rhizophila DSM14405T 12 MA-31 Solanum lycopersicum S Leaf 1 Pseudomonas fulva (Biolog) >1024* MA-56 Solanum lycopersicum N Fruit 2 Pseudomonas fulva 12-XT >1024* MA-74 Solanum lycopersicum SR Fruit 3 Dickeya oryzae ZYY5T >1024 MA-83 Solanum lycopersicum N Fruit 1 Pseudomonas sp. (Biolog) >1024* MA-113 Solanum lycopersicum S Leaf 3 Serratia marcescens ATCC 13880T - - - MA-141 Solanum lycopersicum S Leaf 2 Serratia marcescens ATCC 13880T - >256 - MA-3 Daucus carota SR Root 1 Pseudomonas azotoformans LMG 21611T 32* MA-20 Cucurbita pepo SR Fruit 0 Klebsiella michiganensis W14T 48 MA-75 Cucurbita pepo SR Fruit 1 Pseudomonas corrugata (Biolog) -* MA-80 Cucurbita pepo SR Fruit 2 Pseudomonas protegens CHA0T 16* a Symptoms. Type of lesion in plant tissue from which the bacterium was isolated. S: Spot, N: Necrosis, SR: Soft Rot b RH: Hypersensitive Reaction. Data taken from Herrera (2009) c Determination of Minimum Inhibitory Concentration using E-Test (Solna). EST: Streptomycin, TET: Tetracycline, GEN: Gentamicin * Data taken from Méndez (2010) Table 2. Continue... Mexican Journal of Phytopathology. Scientific Article. Open access Uribe-Lorío et al., 2024. Vol. 42(2): 13 11 isolate was obtained from the Bacteroidetes phylum (Sphingobacterium) and one from Firmicutes (Carnobacterium). With the exception of samples of Ficus carica (fig), Bactris gasipaes (palm heart), and Solanum tuberosum (potato), Pseudomonas isolates were recovered from all other analyzed crops (Table 2), and originated from all sites except one. Among this isolates, recognized plant pathogens such as P. syringae, P. cichorii, P. corrugata, and P. orizihabitans were identified, along with 18 other environmentally-derived species. Isolates of Serratia marcescens were recovered from samples of Apium graveolens (celery), Musa paradisiaca (banana), Capsicum annuum (bell pepper), Brassica oleracea var. botrytis (cauliflower), Curcuma longa (turmeric), Lactuca sativa (Boston lettuce), Brassica oleracea var. capitata (cabbage), and Solanum lycopersicum (tomato), from the provinces of Cartago, Limón, Heredia, and Guanacaste. Meanwhile, Pantoea, including pathogenic species like P. anthophila, P. stewartii, P. agglomerans, and P. vagans, were obtained from various crops such as sweet pepper, Iceberg and Boston lettuce, cabbage, palm heart, and Dracaena massangeana (dracaena), also in the same provinces. Stenotrophomonas isolates, the next most abundant genus in the collection, were found in palm heart, cauliflower, cabbage, and lettuce in the provinces of Cartago, Limón, and Heredia, with most of these strains classified as S. malthophilia (Table 2). Additionally, Gram-negative phytopathogens such as Dickeya oryzae, Enterobacter cloacae subsp. dissolvens, and Pectobacterium aroidearum were identified in tomato, turmeric, and Boston lettuce samples, respectively. Phylogenetic relationships between the sequences of the isolates and reference sequences obtained from curated databases such as EzbioCloud (Yoon et al., 2017) are presented in Figure 2. Antibiotic Susceptibility Profile and Minimum Inhibitory Concentration (MIC) Determination Profile. For the purposes of this study, isolates classified as resistant or intermediate by the Kirby-Bauer test, which also presented a MIC ≥ 12 ng mL-1 (Figure 3) (Miernik and Rzeczycka, 2007; Rodríguez et al., 2008), were considered resistant. This concentration was chosen based on the CLSI (2017) recommendations for enteric, non-enteric, and anaerobic human pathogens, as it is higher than the intermediate MIC for these bacterial groups. According to this classification, bacteria resistant to the studied antibiotics were observed in samples from all crops except mango and potato (Table 3). The highest proportion of resistant isolates was found in tomato (83.3%), heart of palm (83.3%), and Boston lettuce (80%) samples (Figure 4). Isolates obtained from cabbage, banana, bell pepper, and Iceberg lettuce exhibited the same resistance phenotypes to streptomycin, tetracycline, and gentamicin, including multiple resistances such as streptomycin- tetracycline (Estr-Tet) (bell pepper and banana) and streptomycin-gentamicin (Str- Gent) in cabbage. In the case of heart of palm, the highest number of bacteria Mexican Journal of Phytopathology. Scientific Article. Open access Uribe-Lorío et al., 2024. Vol. 42(2): 13 12 Figure 2. Cladogram constructed using the nearest neighbor method from 70 partial sequences of the 16S rRNA gene of bacteria isolated from plant lesions and sequences of reference strains. The tree topology was assessed through 1,000 resamplings, with the sequence of Bacillus subtilis used as an outgroup. Symbols on the outer part of the tree indicate isolates classified as resistant to Streptomycin, Tetracycline, and Gentamicin, as well as their combinations (circles), and those with a positive Hypersensitive Reaction (triangles). Figure 3. A. Halos indicating sensitivity to antibiotics on Oxoid discs for gentamicin and tetracycline, and resistance to streptomycin (absence of a halo) in the Kirby Bauer disk diffusion test. B. Bacteria with a minimum inhibitory concentration (MIC) of 0.25 µg mL-1 for gentamicin, determined by the E-test method. C. Bacteria with a MIC of 32 µg mL-1 for the same antibiotic. Mexican Journal of Phytopathology. Scientific Article. Open access Uribe-Lorío et al., 2024. Vol. 42(2): 13 13 Table 3. Bacterial genera identified and the frequency of bacteria resistant to the antibiotics Streptomycin (Strept), Tetracycline (Tetra), and Gentamicin (Gent). Phylum Class Genus Nº isolates Isolates with MIC (E-test) ≥ 12 µg mL-1 Nº (%) of resistanceEstr Tet Gent Estr- Tet Estr- Gent Estr- Tet- Gent Proteobacteria Alfaproteobacteria Ochrobactrum 1 0 1 0 0 0 0 1 (100.0 %) Proteobacteria Betaproteobacteria Achromobacter 2 0 0 0 1 0 0 1 (100.0 %) Proteobacteria Gamaproteobacteria Acinetobacter 4 0 1 0 0 1 0 2 (50.0 %) Proteobacteria Gamaproteobacteria Aeromonas 1 0 0 1 0 0 0 1 (100.0 %) Proteobacteria Betaproteobacteria Comamonas 1 1 0 0 0 0 0 1 (100.0 %) Proteobacteria Gamaproteobacteria Dickeya 1 1 0 0 0 0 0 1 (100.0 %) Proteobacteria Gamaproteobacteria Enterobacter 2 0 1 0 0 0 0 1 (50.0 %) Proteobacteria Gamaproteobacteria Erwinia 1 0 0 0 0 0 0 0 Proteobacteria Gamaproteobacteria Escherichia 1 0 0 1 0 0 0 1 (100 %) Proteobacteria Gamaproteobacteria Klebsiella 2 1 0 0 0 0 0 1 (50.0 %) Proteobacteria Gamaproteobacteria Pantoea 11 2 1 1 1 0 0 5 (45.0 %) Proteobacteria Gamaproteobacteria Pectobacterium 1 1 0 0 0 0 0 1 (100 %) Proteobacteria Gamaproteobacteria Providencia 1 1 0 0 0 0 0 1 (100 %) Proteobacteria Gamaproteobacteria Pseudomonas 56 17 8 1 3 1 0 30 (53.6 %) Proteobacteria Gamaproteobacteria Psychrobacter 6 1 1 0 0 0 0 2 (33.3 %) Proteobacteria Gamaproteobacteria Raoultella 2 1 1 0 0 0 0 2 (100.0 %) Proteobacteria Gamaproteobacteria Serratia 14 1 6 0 2 1 0 10 (71.4 %) Proteobacteria Gamaproteobacteria Stenotrophomonas 7 1 2 1 1 0 1 6 (85.7 %) Bacteroidetes Sphingobacteriia Sphingobacterium 1 0 0 0 0 1 0 1 (100 %) Firmicutes Bacilli Carnobacterium 1 0 1 0 0 0 0 1 (100 %) TOTAL 116 28 23 5 8 4 1 69 Mexican Journal of Phytopathology. Scientific Article. Open access Uribe-Lorío et al., 2024. Vol. 42(2): 13 14 with multiple resistance to Estr-Tet and Estr-Tet-Gent was isolated (Table 3, Figure 4). Another crop that showed bacteria resistant to all three analyzed antibiotics was Iceberg lettuce, with samples coming from different farms in the province of Cartago. Multiple resistance was also observed in cauliflower (Estr-Gent), celery, and melon (Estr-Tet), while crops such as tomato, Boston lettuce, and turmeric had isolates resistant to streptomycin and tetracycline. Resistance to streptomycin was found in bacteria isolated from all crops except fig. For this antibiotic, all isolates from tomato and turmeric had a maximum MIC of >1024 µg mL-1, those from celery had an MIC of 128 to >1024 µg mL-1, and in the case of cabbage, banana, melon, and cauliflower, it ranged from 12 to >1024 µg mL-1, sweet pepper from 16 to >1024 µg mL-1, and Iceberg lettuce from 12 to 96 µg mL-1. MICs between 12 and 48 µg mL-1 were observed in other crops isolates. Tetracycline resistance was detected in bacteria from 10 of the 19 crops, and isolates from cabbage, banana, bell pepper, Boston lettuce, and carrot had a maximum MIC of >256 µg mL-1. Although less frequent, gentamicin-resistant isolates had MICs of 256 in heart of palm, 16 to 256 in cabbage, and 12 to 48 µg mL-1 in banana, bell pepper, and cauliflower (Table 2). Among the genera with a higher number of resistant isolates were Pseudomonas, Serratia, Pantoea, and Stenotrophomonas, all of which included phytopathogenic and saprophytic members characterized by molecular identification and hypersensitivity reaction (Figure 2 and 5). Figure 4. Proportion of bacteria resistant (MIC ≥ 12 µg mL-1) to the antibiotics Streptomycin (Str), Tetracycline (Tet), and Gentamicin (Gent), as well as their combinations, in the analyzed hosts that had more than one isolation. Mexican Journal of Phytopathology. Scientific Article. Open access Uribe-Lorío et al., 2024. Vol. 42(2): 13 15 Figure 5. Types of Hypersensitivity Reactions (HR) in the most frequently observed bacterial genera in the analized crop samples. Isolates with an HR ranging from 3 to 5 are considered to be phytopathogenic bacteria (Herrera, 2009). HR levels from 0 to 2 are grouped together and indicate non-pathogenicity. Out of the 19 crops sampled, Pseudomonas genus comprised 56 isolates identified in 16 of them. Among these, 30 had a MIC greater than 12 µg mL-1 (Table 3), and were considered resistant. Five of the six studied resistance phenotypes were observed, with streptomycin resistance being the most prevalent, ranging from 12 to >1024 µg mL-1, with 65% of the isolates having a MIC greater than 32 µg mL-1, including four bacteria with maximum MIC levels (>1024 µg mL-1). Regarding tetracycline resistance, three out of the 11 resistant isolates showed a maximum MIC of >256 µg mL-1. Only two bacteria exhibited gentamicin resistance with MICs ranging from 12 to 24 µg mL-1 (Table 2). Ten out of 14 isolates identified as Serratia displayed resistance (Table 3), originating from six out of eight crops from which isolates were obtained (cabbage, tomato, bell pepper, Boston lettuce, celery, and banana). Commonly observed resistance was to tetracycline, with eight resistant isolates having the maximum MIC for this antibiotic. Additionally, three strains showed resistance to streptomycin (MIC ranging from 12 to 512 µg mL-1), and one to gentamicin (16 µg mL-1). Bacteria classified as Stenotrophomonas exhibited MICs ranging from 12 to >1024 µg mL-1 for streptomycin, between 12 and 24 µg mL-1 for tetracycline, and from 48 to >256 µg mL-1 for gentamicin, with only one isolate (MA-110) being susceptible to all three antibiotics. Among the 11 bacteria identified in the Pantoea genus, five presented resistance, with maximum values observed only for streptomycin in the case of MA-19 (bell pepper) (Table 2, 3). Mexican Journal of Phytopathology. Scientific Article. Open access Uribe-Lorío et al., 2024. Vol. 42(2): 13 16 Phytopathogenicity-Antibiotic Resistance Relationship. According to Herrera’s reported hypersensitivity reaction data (2009), 73% of the bacteria in this collection were classified as non-plant pathogens or RH negative, displaying no chlorosis or necrosis around the inoculation point (levels 0 to 2). When comparing the taxonomy of the isolates with this classification, a higher proportion of isolates with a positive RH (levels 3 to 5) was observed in the genera Stenotrophomonas (57.2%), Pantoea (45.5%), Pseudomonas (21.4%), and Serratia (7.1%). However, some of the species that exhibited this reaction were not recognized as plant pathogenic but rather environmental species, such as P. protegens, P. fragi, and P. punonensis (Table 2). When comparing the degree of pathogenicity rating with the number of identified resistant strains in each RH category (Figure 6), it was observed that 45% of the population with RH negative exhibited resistance to some of the studied antibiotics. However, this proportion was lower than that found in pathogenic isolates (RH+), where resistant bacteria represented 70 to 83%, corresponding to levels 3 and 5, respectively. Resistance to all three antibiotics was detected at all levels of phytopathogenicity, and a bacterium with RH 5 (Stenotrophomonas malthopilia MA-54) was the only one found to be resistant to all three. The highest level of pathogenicity exhibited a higher proportion of bacteria with multiple resistance. Figure 6. Proportion of strains resistant to the studied antibiotics according to the HR scale (levels 0 to 5) as determined by Herrera (2009). The Y-axis shows the percentage of susceptible isolates within each category. 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 0 1 2 3 4 5 Categoría de Reacción Hipersensible Susceptibles Est-Tet-Gen Est-Gen Est-Tet Gent Tet Est Discussion The diversity of symptoms related to plant diseases of bacterial origin increases the difficulty of management in agricultural systems (Aráuz, 2011). Furthermore, Mexican Journal of Phytopathology. Scientific Article. Open access Uribe-Lorío et al., 2024. Vol. 42(2): 13 17 some symptoms such as fruit and leaf spots and soft rot are shared by different pathogens, making laboratory identification necessary using various methodologies, as early and accurate identification allows for better disease control (Kannan et al., 2022). On the other hand, the aboveground part of plants is predominantly colonized by a diverse bacterial community, both in the form of epiphytes on the plant surface and endophytes in plant tissues. While some plant-associated bacteria promote plant growth, others can be plant or even human pathogens (Lindow and Brandl, 2003; Jackson et al., 2013). In this regard, Jackson et al. (2013), when analyzing the bacterial community composition of leafy vegetables through pyrosequencing, identified eleven different phyla, where Gamaproteobacteria, Betaproteobacteria, and Bacteroidetes were the dominant lineages. These phyla align with what was observed in this study, where the same groups of Proteobacteria were found, in addition to Alphaproteobacteria. Among the identified genera, Pseudomonas, Serratia, Pantoea, Stenotrophomonas, Klebsiella, and Enterobacter are Gram-negative bacteria that have plant pathogenic species. It is important to remember that these isolates come from the edge of the lesion area, and due to the isolation process in which the sample is disinfested with hypochlorite before dissection, endophytic and opportunistic bacteria can also be isolated. To discriminate plant pathogens in this collection, Herrera (2009) used the hypersensitive reaction (HR) technique on the indicator plant Nicotiana tabacum. This technique, entails inoculating bacteria on the undersides of plant leaves to assess their phytopathogenic capacity (Zurbriggen et al., 2010). This method is characterized by cell death near the pathogen recognition site and the development of delimited chlorosis and necrosis in the leaves (Bellincampi et al., 2014). In this study, the most abundant genera comprised isolates classified as both phytopathogens and saprophytic representatives. The diversity of Pseudomonas species in the soil ecosystem influences both plant growth and their pathogenicity (Kumar et al., 2017). This is due to their metabolic versatility and genetic adaptability, and this characteristics may explain why we isolated Pseudomonas from 16 out of the 19 crops analyzed. P. syringae, the species that tops Mansfield et al.’s (2012) list of the top 10 bacterial plant pathogens, was identified in this study, along with P. cichorii, P. corrugata, and P. orizihabitants (Höfte and De Vos, 2007; Pauwelyn et al., 2013; Li et al., 2021). While other Pseudomonas species not identified in this collection have been reported to exhibit natural resistance to aminoglycosides (Krahn et al., 2012), a wide range of MIC values was found for streptomycin, with over half of the isolates having MIC values greater than 32 µg mL-1 for streptomycin and most being susceptible to gentamicin. Given the ubiquity of this genus in different environments and its use as a biofertilizer and biocontroller, it is important to investigate whether the Mexican Journal of Phytopathology. Scientific Article. Open access Uribe-Lorío et al., 2024. Vol. 42(2): 13 18 resistance-conferring genes are present in the chromosome or in horizontal gene transfer determinants in Pseudomonas isolates. Serratia marcescens is a genetically variable bacterial species found in different environments, including water, soil, plants, and as an opportunistic pathogen in humans and animals (Besler and Little, 2017). This species has been associated with nosocomial infections in the medical field as well as diseases in plants. For example, strains of S. marcescens have been identified as the causative agents of cucurbit yellow vine disease and soft rot in bell peppers (Zhang et al., 2005; Gillis et al., 2017). In this study, 14 S. marcescens isolates from different hosts showed high similarity to the type strain S. marcescens ATCC 13880(T) sequence, which was isolated from a wastewater treatment tank. Therefore, its role in the host plant needs to be studied in more detail. This species had a CMI ≥ 12 µg mL-1 in 10 out of 13 isolates, and its resistance level was maximum for tetracycline and within a wide range for streptomycin, with only one isolate being resistant to gentamicin. These findings align with a study conducted in Costa Rica where Serratia isolates obtained from soil treated with gentamicin and tetracycline were tetracycline- resistant and gentamicin-sensitive (Rodríguez et al., 2007). Despite S. marcescens exhibiting natural resistance to aminoglycosides (Sandner-Miranda et al., 2018), most of the isolates analyzed in this study were susceptible to streptomycin and gentamicin, and some showed maximum tetracycline MIC values, necessitating further investigation of their resistance determinants. The genus Pantoea encompasses bacteria with various roles in plants, including their roles as phytopathogens, endophytes, and epiphytes (Doni et al., 2021). Among plant pathogens, P. citrea, P. ananas, P. eucalypti, P. stewartii, P. agglomerans, P. vagans, and P. antophila have been documented (Schaad et al., 2001; Brady et al., 2009), with the latter four being identified in this study. In particular, Pantoea stewartii sp. indologenes MA-65, isolated from lesions on palm leaflets, is the causal agent of palm bacterial wilt, which affected plantations in Costa Rica in the 2000s (Mora-Urpí et al., 2008). In this study, isolates classified as pathogens through phylogenetic and phytopathogenicity analyses exhibited resistance to streptomycin and tetracycline. Species within the genus Stenotrophomonas include endophytic representatives and are used as biocontrol agents in sustainable agriculture (Berg and Martinez, 2015). S. maltophilia is considered an emerging opportunistic pathogen in clinical settings, with natural resistance to aminoglycosides, albeit to a lesser extent for gentamicin (Antón et al., 2005; Berg and Martinez, 2015). A study conducted in Costa Rica found that Stenotrophomonas sp. isolates from lettuce plants exhibited resistance to various antibiotics, including tetracycline and gentamicin (Rodríguez et al., 2007). In this work, the majority of the isolates showed resistance to the antibiotics tested, with MIC values ranging between 12-24 µg mL-1 for tetracycline Mexican Journal of Phytopathology. Scientific Article. Open access Uribe-Lorío et al., 2024. Vol. 42(2): 13 19 and streptomycin, except for MA-142, which had a maximum MIC (>1024 µg mL-1) for streptomycin and gentamicin. Among the resistant isolates are bacteria with a high level of pathogenicity, recovered from palm leaflets (Table 2). Additionally, isolate MA-54 was the only one in the collection resistant to all three antibiotics studied (Table 2). Given their intrinsic resistance, a detailed analysis of resistance determinants in S. maltophilia isolates, particularly regarding streptomycin and tetracycline, is important. Most of the phylogenetically identified and RH-tested phytopathogenic bacteria have not been described in Costa Rica, except for the isolates of Erwinia billingiae MA-115 and Raoultella terrigena. These isolates were subjected to pathogenicity tests in mango and bell pepper plants, respectively (the crops from which they were isolated), and upon proving their virulence using Koch’s Postulates, they were described as phytopathogens (Vidaurre-Barahona et al., 2021; Cubero et al., 2021). In this diverse collection, bacteria with positive RH, considered plant pathogens, exhibited a higher proportion of resistance (Figure 4). This could be due to their adaptation to survive on the plant surfaces and in plant tissues, where they are more exposed to antimicrobials applied to the leaves (Stockwell and Duffy, 2012). The resistance observed in 60% of the isolates to the antibiotics studied may result from the use of products in the crops from which the bacteria were obtained. It is important to consider that the 12 µg mL-1 threshold used to define resistance in this study surpass the MIC for susceptible bacteria but falls below that for resistant bacteria in human setting. However, this criterion has been used in previous studies in different environments, as environmental microorganisms are considered to be exposed to much lower concentrations than clinical bacteria, but they can also develop resistance in natural settings (Popowska et al., 2012; Sandegren, 2014; Nogrado et al., 2021). The lower number of bacteria resistant to gentamicin observed (10 out of 116) may result from less frequent use of this antibiotic or intrinsic factors related to the molecule and its persistence in environmental conditions. The presence of resistant bacteria in 90% of the analyzed hosts, which constitute a diverse set of plants, raises concerns regarding the current status of antibiotic resistance, as these isolates were collected between 2006 and 2009. Crops with a higher prevalence of resistant bacteria and phenotypes resistant to the three studied antibiotics included cabbage, banana, Iceberg lettuce, palm heart, and bell pepper. This could be associated with more aggressive management practices to combat bacterial diseases affecting these crops. For instance, cabbage may face angular leaf spot caused by Xanthomonas campestris, banana may be susceptible to wilt (Ralstonia solanacearum), lettuce could suffer from leaf spots caused by Pseudomonas species, palm heart may be affected by bacterial wilt (P. stewartii), and various vegetables in tropical climates may experience soft rot (Bhat et al., 2010). The high proportion of resistant bacteria identified in 16 out of 19 crops Mexican Journal of Phytopathology. Scientific Article. Open access Uribe-Lorío et al., 2024. Vol. 42(2): 13 20 from diverse regions of the country, may result from the widespread agricultural use of antibiotics such as tetracycline, streptomycin, and gentamicin without adequate regulation, dosing, and record-keeping, a common phenomenon in other Latin American countries as well. These findings provide a foundation for investigating the evolution of antimicrobial resistance in both phytopathogenic and non-pathogenic bacteria present in vegetables destined for human consumption in Costa Rica. It underscores the necessity for more comprehensive studies due to their impact on disease control in crops and associated microbial communities. Conclusions The analysis of 116 isolates from a collection derived from symptoms of soft rot, necrosis, and leaf, stem, and fruit spots across 19 crops revealed the presence of 20 genera, with Pseudomonas (48%), Serratia (12%), Pantoea (9%), and Stenotrophomonas (6%) being the most abundant. Pseudomonas had the highest number of species and isolates among them. Among the phytopathogenic bacteria in the collection, Pseudomonas syringae, P. cichorii, P. corrugata, Pantoea stewartii subsp. indologenens, P. anthophila, Dickeya oryzae, Enterobacter cloacae subsp. dissolvens, and Pectobacterium aroidearum were identified, accounting for 23% of isolates positive for the hypersensitive reaction (HR). In this study, resistance to at least one of the three antibiotics was detected in 60% of the evaluated isolates, with streptomycin resistance being the most common. Resistance was observed in bacteria isolated from 17 plant species, with tomatoes, palm hearts, lettuce, celery, squash, and cabbage showing the highest proportion of resistant isolates. This suggests a greater risk of selecting antibiotic-resistant bacteria in the production of these foods. The information obtained highlights the necessity for stricter regulation in the sale and usege of antimicrobial products to mitigate their impact on the environment, animals, and humans. Acknowledgments We would like to extend our gratitude to Amy Wang for her collaboration in the sampling process and to the staff of the Environmental Microbiology Area at CIBCM (UCR). Furthermore, we acknowledge the support from the Research Vice Presidency of the University of Costa Rica for funding this study. Mexican Journal of Phytopathology. Scientific Article. Open access Uribe-Lorío et al., 2024. Vol. 42(2): 13 21 Literature Cited Agrios GN. 2005. Plant pathology. 5 ed. Elsevier Academic Press. New York, USA. 922 p. Alippi AM, Reynaldi FJ y López AC. 2013. Evaluación del método epsilométrico Etest para la determinación de la sensibilidad a tetraciclina en Paenibacillus larvae, agente causal de la loque americana de las abejas. 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