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The evolution of new variants of plant pathogens is one of the biggest challenges to controlling and managing plant diseases. Of the forces driving these evolutionary processes, global migration events are particularly important for widely distributed diseases such as potato late blight, caused by the oomycete Phytophthora infestans . However, little is known about its migration routes outside North America and Europe. This work used genotypic data from population studies to elucidate the migration history originating the Colombian P. infestans population. For this purpose, a dataset of 1,706 P. infestans genotypes was recollected, representing North and South America, Europe, and Asia. Descriptive analysis and historical records from North America and Europe were used to propose three global migration hypotheses, differing on the origin of the disease (Mexico or Peru) and the hypothesis that it returned to South America from Europe. These scenarios were tested using approximate Bayesian computation. According to this analysis, the most probable scenario (posterior probability = 0.631) was the one proposing a Peruvian origin for P. infestans , an initial migration toward Colombia and Mexico, and a later event from Mexico to the United States and then to Europe and Asia, with no return to northern South America. In Colombia, the scenario considering a single migration from Peru and posterior migrations within Colombia was the most probable, with a posterior probability of 0.640. The obtained results support the hypothesis of a Peruvian origin for P. infestans followed by rare colonization events worldwide., Competing Interests: The author(s) declare no conflict of interest.

Premise: The prompt categorization of Phytophthora infestans isolates into described clonal lineages is a key tool for the management of its associated disease, potato late blight. New isolates of this pathogen are currently classified by comparing their microsatellite genotypes with characterized clonal lineages, but an automated classification tool would greatly improve this process. Here, we developed a flexible machine learning-based classifier for P. infestans genotypes., Methods: The performance of different machine learning algorithms in classifying P. infestans genotypes into its clonal lineages was preliminarily evaluated with decreasing amounts of training data. The four best algorithms were then evaluated using all collected genotypes., Results: mlpML, cforest, nnet, and AdaBag performed best in the preliminary test, correctly classifying almost 100% of the genotypes. AdaBag performed significantly better than the others when tested using the complete data set (Tukey HSD P  < 0.001). This algorithm was then implemented in a web application for the automated classification of P. infestans genotypes, which is freely available at https://github.com/cpatarroyo/genotypeclas., Discussion: We developed a gradient boosting-based tool to automatically classify P. infestans genotypes into its clonal lineages. This could become a valuable resource for the prompt identification of clonal lineages spreading into new regions., (© 2024 The Author(s). Applications in Plant Sciences published by Wiley Periodicals LLC on behalf of Botanical Society of America.)

Over the past decades, Colombia has suffered complex social problems related to illicit crops, including forced displacement, violence, and environmental damage, among other consequences for vulnerable populations. Considerable effort has been made in the regulation of illicit crops, predominantly Cannabis sativa , leading to advances such as the legalization of medical cannabis and its derivatives, the improvement of crops, and leaving an open window to the development of scientific knowledge to explore alternative uses. It is estimated that C. sativa can produce approximately 750 specialized secondary metabolites. Some of the most relevant due to their anticancer properties, besides cannabinoids, are monoterpenes, sesquiterpenoids, triterpenoids, essential oils, flavonoids, and phenolic compounds. However, despite the increase in scientific research on the subject, it is necessary to study the primary and secondary metabolism of the plant and to identify key pathways that explore its great metabolic potential. For this purpose, a genome-scale metabolic reconstruction of C. sativa is described and contextualized using LC-QTOF-MS metabolic data obtained from the leaf extract from plants grown in the region of Pesca-Boyaca, Colombia under greenhouse conditions at the Clever Leaves facility. A compartmentalized model with 2101 reactions and 1314 metabolites highlights pathways associated with fatty acid biosynthesis, steroids, and amino acids, along with the metabolism of purine, pyrimidine, glucose, starch, and sucrose. Key metabolites were identified through metabolomic data, such as neurine, cannabisativine, cannflavin A, palmitoleic acid, cannabinoids, geranylhydroquinone, and steroids. They were analyzed and integrated into the reconstruction, and their potential applications are discussed. Cytotoxicity assays revealed high anticancer activity against gastric adenocarcinoma (AGS), melanoma cells (A375), and lung carcinoma cells (A549), combined with negligible impact against healthy human skin cells.

The aim of this research is to develop burger patties from fungal protein. For this purpose, to maximize fungal biomass production, an optimization of the growth medium was initially carried out by testing different carbon sources and its proportion with nitrogen. Subsequently, for the design of the fungal patties, the effect of different flours, binders, and colorants on the properties of texture, water retention capacity, and color were tested, with a traditional animal-based burger patty as a control. Based on the first results, two optimal formulations were chosen and analyzed using an electronic tongue with the same control as reference. The conditions that maximized biomass production were 6 days of incubation and maltodextrin as a carbon source at a concentration of 90 g/L. In terms of product design, the formulation containing quinoa flour, carboxymethylcellulose, and beet extract was the most similar to the control. Finally, through shelf-life analysis, it was determined that the physical characteristics of the fungal meat substitute did not change significantly in an interval of 14 days. However, the product should be observed for a longer period. In addition, by the proximate analysis, it was concluded that fungal patties could have nutritional claims such as rich content in protein and fiber.

Late blight disease, caused by the plant pathogen Phytophthora infestans , is one of the major threats for tomato and potato crops. Monitoring the populations of P . infestans is important to determine if there are changes in the sensitivity to fungicides and host preference. In this study, microsatellite markers and mitochondrial haplotypes were used to assess the genotype of isolates of P . infestans collected from tomato and potato plants in Colombia. Furthermore, sensitivity to the three fungicides cymoxanil (penetrant fungicide), mefenoxam, and fluopicolide (systemic fungicides), and tomato-potato host preference, were evaluated. Mitochondrial haplotyping showed that isolates collected on tomato were from the genetic groups Ia and Ib, while isolates collected on potatoes belonged to group IIa. Microsatellite analyses showed that isolates from tomato form two groups, including the Ib mitochondrial haplotype (which is genetically close to the US-1 clonal lineage) and the Ia haplotype (related to the EC-3 lineage), whereas Colombian isolates from potato formed a separate group. Furthermore, differences in sensitivity to fungicides were observed. Eighty-one percent of the isolates tested were resistant to mefenoxam with an EC 50 >10 μg ml -1 . Forty-two percent of the isolates showed an intermediate resistance to cymoxanil. The EC 50 values ranged between 1 and 10 μg ml -1 . For fluopicolide, 90% of the isolates were sensitive, with EC 50 <1 μg ml -1 . Host preference assays showed that potato isolates infected both host species. Thus, isolates that infect potatoes may pose a risk for tomato crops nearby.

Phytophthora infestans , the causal agent of late blight disease of potatoes, is mainly controlled by the use of fungicides. Isolates that are resistant to commonly used fungicides have been reported. Also, several studies show that originally mefenoxam-sensitive isolates acquire resistance to this fungicide when exposed to sublethal concentrations. This phenomenon, termed "mefenoxam-acquired resistance," has been observed in different Phytophthora species and seems to be unique to mefenoxam. In this study, we aimed to elucidate the molecular mechanism mediating this type of resistance as well as a possible regulatory process behind it. A combination of computational analyses and experimental approaches was used to identify differentially expressed genes with a potential association to the phenomenon. These genes were classified into seven functional groups. Most of them seem to be associated with a pleiotropic drug resistance (PDR) phenotype, typically involved in the expulsion of diverse metabolites, drugs, or other substances out of the cell. Despite the importance of RNA Polymerase I for the constitutive resistance of P . infestans to mefenoxam, our results indicate no clear interaction between this protein and the acquisition of mefenoxam resistance. Several small non-coding RNAs were found to be differentially expressed and specifically related to genes mediating the PDR phenotype, thus suggesting a possible regulatory process. We propose a model of the molecular mechanisms acting within the cell when P . infestans acquires resistance to mefenoxam after exposed to sublethal concentrations of the fungicide. This study provides important insights into P . infestans ' cellular and regulatory functionalities.

Latin America has been severely affected by the COVID-19 pandemic but estimations of rates of infections are very limited and lack the level of detail required to guide policy decisions. We implemented a COVID-19 sentinel surveillance study with 59,770 RT-PCR tests on mostly asymptomatic individuals and combine this data with administrative records on all detected cases to capture the spread and dynamics of the COVID-19 pandemic in Bogota from June 2020 to early March 2021. We describe various features of the pandemic that appear to be specific to a middle income countries. We find that, by March 2021, slightly more than half of the population in Bogota has been infected, despite only a small fraction of this population being detected. The initial buildup of immunity contributed to the containment of the pandemic in the first and second waves. We also show that the share of the population infected by March 2021 varies widely by occupation, socio-economic stratum, and location. This, in turn, has affected the dynamics of the spread with different groups being infected in the two waves., (© 2021. The Author(s).)

Transcription activator-like effectors (TALEs) play a significant role for pathogenesis in several xanthomonad pathosystems. Xanthomonas phaseoli pv. manihotis ( Xpm ), the causal agent of Cassava Bacterial Blight (CBB), uses TALEs to manipulate host metabolism. Information about Xpm TALEs and their target genes in cassava is scarce, but has been growing in the last few years. We aimed to characterize the TALE diversity in Colombian strains of Xpm and to screen for TALE-targeted gene candidates. We selected eighteen Xpm strains based on neutral genetic diversity at a country scale to depict the TALE diversity among isolates from cassava productive regions. RFLP analysis showed that Xpm strains carry TALomes with a bimodal size distribution, and affinity-based clustering of the sequenced TALEs condensed this variability mainly into five clusters. We report on the identification of 13 novel variants of TALEs in Xpm , as well as a functional variant with 22 repeats that activates the susceptibility gene MeSWEET10a , a previously reported target of TAL20 Xam668 . Transcriptomics and EBE prediction analyses resulted in the selection of several TALE-targeted candidate genes and two potential cases of functional convergence. This study provides new bases for assessing novel potential TALE targets in the Xpm- cassava interaction, which could be important factors that define the fate of the infection.

Any strategy that proposes solutions to health-related problems recognizes that people, animals, and the environment are interconnected. Fusarium is an example of this interaction because it is capable of infecting plants, animals, and humans. This review provides information on various aspects of these relations and proposes how to approach fusariosis with a One Health methodology (a multidisciplinary, and multisectoral approach that can address urgent, ongoing, or potential health threats to humans, animals, and the environment). Here, we give a framework to understand infection pathogenesis, through the epidemiological triad, and explain how the broad utilization of fungicides in agriculture may play a role in the treatment of human fusariosis. We assess how plumbing systems and hospital environments might play a role as a reservoir for animal and human infections. We explain the role of antifungal resistance mechanisms in both humans and agriculture. Our review emphasizes the importance of developing interdisciplinary research studies where aquatic animals, plants, and human disease interactions can be explored through coordination and collaborative actions.

Background: The increasing amounts of genomics data have helped in the understanding of the molecular dynamics of complex systems such as plant and animal diseases. However, transcriptional regulation, although playing a central role in the decision-making process of cellular systems, is still poorly understood. In this study, we linked expression data with mathematical models to infer gene regulatory networks (GRN). We present a simple yet effective method to estimate transcription factors' GRNs from transcriptional data., Method: We defined interactions between pairs of genes (edges in the GRN) as the partial mutual information between these genes that takes into account time and possible lags in time from one gene in relation to another. We call this method Gene Regulatory Networks on Transfer Entropy (GRNTE) and it corresponds to Granger causality for Gaussian variables in an autoregressive model. To evaluate the reconstruction accuracy of our method, we generated several sub-networks from the GRN of the eukaryotic yeast model, Saccharomyces cerevisae. Then, we applied this method using experimental data of the plant pathogen Phytophthora infestans. We evaluated the transcriptional expression levels of 48 transcription factors of P. infestans during its interaction with one moderately resistant and one susceptible cultivar of yellow potato (Solanum tuberosum group Phureja), using RT-qPCR. With these data, we reconstructed the regulatory network of P. infestans during its interaction with these hosts., Results: We first evaluated the performance of our method, based on the transfer entropy (GRNTE), on eukaryotic datasets from the GRNs of the yeast S. cerevisae. Results suggest that GRNTE is comparable with the state-of-the-art methods when the parameters for edge detection are properly tuned. In the case of P. infestans, most of the genes considered in this study, showed a significant change in expression from the onset of the interaction (0 h post inoculum - hpi) to the later time-points post inoculation. Hierarchical clustering of the expression data discriminated two distinct periods during the infection: from 12 to 36 hpi and from 48 to 72 hpi for both the moderately resistant and susceptible cultivars. These distinct periods could be associated with two phases of the life cycle of the pathogen when infecting the host plant: the biotrophic and necrotrophic phases., Conclusions: Here we presented an algorithmic solution to the problem of network reconstruction in time series data. This analytical perspective makes use of the dynamic nature of time series data as it relates to intrinsically dynamic processes such as transcription regulation, were multiple elements of the cell (e.g., transcription factors) act simultaneously and change over time. We applied the algorithm to study the regulatory network of P. infestans during its interaction with two hosts which differ in their level of resistance to the pathogen. Although the gene expression analysis did not show differences between the two hosts, the results of the GRN analyses evidenced rewiring of the genes' interactions according to the resistance level of the host. This suggests that different regulatory processes are activated in response to different environmental cues. Applications of our methodology showed that it could reliably predict where to place edges in the transcriptional networks and sub-networks. The experimental approach used here can help provide insights on the biological role of these interactions on complex processes such as pathogenicity. The code used is available at https://github.com/jccastrog/GRNTE under GNU general public license 3.0.

Pathogen variation plays an important role in the dynamics of infectious diseases. In this study, the genetic variation of 279 Phytophthora infestans isolates was assessed using a combination of 12 microsatellite simple-sequence repeat markers. Isolates were collected from 11 different potato cultivars in 11 different geographic localities of the central region of Colombia. The objective of this study was to determine whether populations were differentiated by host genotype or geographic origin. Within a single clonal lineage, EC-1, 76 genotypes were detected. An analysis of molecular variance attributed most of the variation to differences within host genotypes rather than among the host genotypes, suggesting that host cultivars do not structure the populations of the pathogen. Furthermore, the lack of a genetic population structure according to the host cultivar was confirmed by all of the analyses, including the Bayesian clustering analysis and the minimum spanning network that used the Bruvo genetic distance, which suggested that there are no significant barriers to gene flow for P. infestans among potato cultivars. According to the geographic origin, the populations of P. infestans were also not structured, and most of the variation among the isolates was attributed to differences within localities. Only some but not all localities in the north and west of the central region of Colombia showed some genetic differentiation from the other regions. The absence of sexual reproduction of this pathogen in Colombia was also demonstrated. Important insights are discussed regarding the genetic population dynamics of the P. infestans populations of the central region of Colombia that were provided by the results. In Colombia, there is a high genetic variation within the EC-1 clonal lineage with closely related genotypes, none dominant, that coexist in a wide geographic area and on several potato cultivars.

Amanita is a worldwide-distributed fungal genus, with approximately 600 known species. Most species within the genus are ectomycorrhizal (ECM), with some saprotrophic representatives. In this study, we constructed the first comprehensive phylogeny including ECM species from Colombia collected in native Quercus humboldtii forests and in introduced Pinus patula plantations. We included 8 species (A. brunneolocularis, A. colombiana, A. flavoconia, A. fuligineodisca, A. muscaria, A. rubescens, A. sororcula, and A. xylinivolva) out of 16 species reported for the country, two new reports: A. citrina and A. virosa, and a new variety A. brunneolocularis var. pallida. Morphological taxonomic keys together with a phylogenetic approach using three nuclear gene regions: partial nuc rDNA 28S nuc rDNA internal transcribed spacers ITS1 and ITS2 and partial translation elongation factor 1-α gene (TEF1), were used to classify the specimens. Several highly supported clades were obtained from the phylogenetic hypotheses obtained by Bayesian inference and maximum likelihood approaches, allowing us to position the Colombian collections in a coherent infrageneric level and to contribute to the knowledge of local Amanita diversity.