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Castillo, J. A.

Publications and source records attributed to Castillo, J. A..

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Candidate genes under balancing selection in a plant bacterial pathogen

Plant pathogens are under significant selective pressure by the plant host. Consequently, they are expected to have adapted to this condition or contribute to evading plant defenses. In order to acquire long-term fitness, plant bacterial pathogens are usually forced to maintain advantageous genetic diversity in populations. This strategy ensures that different alleles in the pathogens gene pool are maintained in a population at frequencies larger than expected under neutral evolution. This selective process, known as balancing selection, is the subject of this work in the context of a common plant bacterial pathogen. We performed a genome-wide scan of Ralstonia solanacearum, an aggressive plant bacterial pathogen that shows broad host range and causes a devastating disease called bacterial wilt. Using a sliding window approach, we analyzed 57 genomes from three phylotypes of R. solanacearum to detect signatures of balancing selection. A total of 161 windows showed extreme values in three summary statistics of population genetics: Tajimas D, Wattersons {theta} and Fu & Lis D*. We discarded any confounding effects due to demographic events by means of coalescent simulations of genetic data. The prospective windows correspond to 78 genes that map in any of the two main replicons of R. solanacearum. The candidate genes under balancing selection are related to primary metabolism (51.3%) or directly associated to virulence (48.7%), being involved in key functions targeted to dismantle plant defenses or to participate in critical stages in the pathogenic process. These genes are useful to understand and monitor the evolution of bacterial pathogen populations and emerge as potential candidates for future treatments to induce specific plant immune responses.

microbiology

Barcoding analysis of HIV drug resistance mutations using Oxford Nanopore MinION (ONT) sequencing

Determination of HIV drug resistance (HIVDR) is becoming an integral baseline HIV evaluation for newly infected subjects, as the level of pre-treatment resistance is increasing worldwide. Until now, the gold standard for monitoring ART mutations is the Sanger sequencing method, however, next-generation sequencing technologies (NGS) because high-throughput capability, are gaining attention as a method for detection of HIVDR. In the present work, we evaluated the use of the Oxford Nanopore Technologies (ONT) MinION as an alternative method for detection of drug resistance mutations in pre-treatment HIV positive subjects.\n\nWe evaluate 36 samples taken during November 2016 from treatment naive subjects with age greater than 18 years old, who went to the lab for their first HIV monitoring. To evaluate the agreement between Sanger and MinION generated sequences, we aligned the sequences ([~]1200bp) with muscle v. 3.8.31. Then we counted the differences and calculated the p-distance of the obtained sequences, comparing paired sequences and grouping Sanger and MinION obtained sequences. The percentage of similarity among each sequence was also evaluated.\n\nAll samples were submitted to the Standford University HIV drug resistance database (HIVdb version 8.4). Then we compared the resistance predictions obtained from the sequences generated by Sanger and MinION methods.\n\nResults: The median of available pores was 1314 for the first run, 1215 for the second run, and 536 for the third run. After 3 hours with SQK-NSK007 a total of 18803 2D reads were base-called and in 16577 reads (88%) a barcode was detected.\n\nComparing the nucleotide differences of each sample, we observed that 23 (74%) samples had identical sequence, for the other samples the percentage of identity among each analyzed sequence was greater than 95%. A good positive predictive value (100%) in the estimation of drug resistance mutations in the groups of protease inhibitors (PI), nucleoside reverse transcriptase inhibitors (NRTIs), and non-nucleoside reverse transcriptase inhibitors (NNRTIs).\n\nWe present an approach for the analysis of HIV reads generated with MinION ONT, further studies are guaranteed before the application of this methodology in clinical settings to assess its suitability for HIVDR testing.

genomics