Unveiling potential virulence determinants in Vibrio isolates from Anadara tuberculosa through whole genome analyses.

The genus Vibrio includes pathogenic bacteria able to cause disease in humans and aquatic organisms, leading to disease outbreaks and significant economic losses in the fishery industry. Despite much work on Vibrio in several marine organisms, no specific studies have been conducted on Anadara tuberculosa. This is a commercially important bivalve species, known as "piangua hembra," along Colombia's Pacific coast. Therefore, this study aimed to identify and characterize the genomes of Vibrio isolates obtained from A. tuberculosa. Bacterial isolates were obtained from 14 A. tuberculosa specimens collected from two locations along the Colombian Pacific coast, of which 17 strains were identified as Vibrio: V. parahaemolyticus (n = 12), V. alginolyticus (n = 3), V. fluvialis (n = 1), and V. natriegens (n = 1). Whole genome sequence of these isolates was done using Oxford Nanopore Technologies (ONT). The analysis revealed the presence of genes conferring resistance to ß-lactams, tetracyclines, chloramphenicol, and macrolides, indicating potential resistance to these antimicrobial agents. Genes associated with virulence were also found, suggesting the potential pathogenicity of these Vibrio isolates, as well as genes for Type III Secretion Systems (T3SS) and Type VI Secretion Systems (T6SS), which play crucial roles in delivering virulence factors and in interbacterial competition. This study represents the first genomic analysis of bacteria within A. tuberculosa, shedding light on Vibrio genetic factors and contributing to a comprehensive understanding of the pathogenic potential of these Vibrio isolates.IMPORTANCEThis study presents the first comprehensive report on the whole genome analysis of Vibrio isolates obtained from Anadara tuberculosa, a bivalve species of great significance for social and economic matters on the Pacific coast of Colombia. Research findings have significant implications for the field, as they provide crucial information on the genetic factors and possible pathogenicity of Vibrio isolates associated with A. tuberculosa. The identification of antimicrobial resistance genes and virulence factors within these isolates emphasizes the potential risks they pose to both human and animal health. Furthermore, the presence of genes associated with Type III and Type VI Secretion Systems suggests their critical role in virulence and interbacterial competition. Understanding the genetic factors that contribute to Vibrio bacterial virulence and survival strategies within their ecological niche is of utmost importance for the effective prevention and management of diseases in aquaculture practices.

The evolutionary history of three Baracoffea species from western Madagascar revealed by chloroplast and nuclear genomes.

The wild species of the Coffea genus present a very wide morphological, genetic, and biochemical diversity. Wild species are recognized more resistant to diseases, pests, and environmental variations than the two species currently cultivated worldwide: C. arabica (Arabica) and C. canephora (Robusta). Consequently, wild species are now considered as a crucial resource for adapting cultivated coffee trees to climate change. Within the Coffea genus, 79 wild species are native to the Indian Ocean islands of Comoros, Mayotte, Mauritius, Réunion and Madagascar, out of a total of 141 taxa worldwide. Among them, a group of 9 species called "Baracoffea" are particularly atypical in their morphology and adaptation to the sandy soils of the dry deciduous forests of western Madagascar. Here, we have attempted to shed light on the evolutionary history of three Baracoffea species: C. ambongensis, C. boinensis and C. bissetiae by analyzing their chloroplast and nuclear genomes. We assembled the complete chloroplast genomes de novo and extracted 28,800 SNP (Single Nucleotide Polymorphism) markers from the nuclear genomes. These data were used for phylogenetic analysis of Baracoffea with Coffea species from Madagascar and Africa. Our new data support the monophyletic origin of Baracoffea within the Coffea of Madagascar, but also reveal a divergence with a sister clade of four species: C. augagneurii, C. ratsimamangae, C. pervilleana and C. Mcphersonii (also called C. vohemarensis), belonging to the Subterminal botanical series and living in dry or humid forests of northern Madagascar. Based on a bioclimatic analysis, our work suggests that Baracoffea may have diverged from a group of Malagasy Coffea from northern Madagascar and adapted to the specific dry climate and low rainfall of western Madagascar. The genomic data generated in the course of this work will contribute to the understanding of the adaptation mechanisms of these particularly singular species.

Selection signatures and population dynamics of transposable elements in lima bean.

The domestication process in lima bean (Phaseolus lunatus L.) involves two independent events, within the Mesoamerican and Andean gene pools. This makes lima bean an excellent model to understand convergent evolution. The mechanisms of adaptation followed by Mesoamerican and Andean landraces are largely unknown. Genes related to these adaptations can be selected by identification of selective sweeps within gene pools. Previous genetic analyses in lima bean have relied on Single Nucleotide Polymorphism (SNP) loci, and have ignored transposable elements (TEs). Here we show the analysis of whole-genome sequencing data from 61 lima bean accessions to characterize a genomic variation database including TEs and SNPs, to associate selective sweeps with variable TEs and to predict candidate domestication genes. A small percentage of genes under selection are shared among gene pools, suggesting that domestication followed different genetic avenues in both gene pools. About 75% of TEs are located close to genes, which shows their potential to affect gene functions. The genetic structure inferred from variable TEs is consistent with that obtained from SNP markers, suggesting that TE dynamics can be related to the demographic history of wild and domesticated lima bean and its adaptive processes, in particular selection processes during domestication.

Efficient homology-based annotation of transposable elements using minimizers.

Premise: Transposable elements (TEs) make up more than half of the genomes of complex plant species and can modulate the expression of neighboring genes, producing significant variability of agronomically relevant traits. The availability of long-read sequencing technologies allows the building of genome assemblies for plant species with large and complex genomes. Unfortunately, TE annotation currently represents a bottleneck in the annotation of genome assemblies. Methods and Results: We present a new functionality of the Next-Generation Sequencing Experience Platform (NGSEP) to perform efficient homology-based TE annotation. Sequences in a reference library are treated as long reads and mapped to an input genome assembly. A hierarchical annotation is then assigned by homology using the annotation of the reference library. We tested the performance of our algorithm on genome assemblies of different plant species, including Arabidopsis thaliana, Oryza sativa, Coffea humblotiana, and Triticum aestivum (bread wheat). Our algorithm outperforms traditional homology-based annotation tools in speed by a factor of three to >20, reducing the annotation time of the T. aestivum genome from months to hours, and recovering up to 80% of TEs annotated with RepeatMasker with a precision of up to 0.95. Conclusions: NGSEP allows rapid analysis of TEs, especially in very large and TE-rich plant genomes.

NGSEP 4: Efficient and accurate identification of orthogroups and whole-genome alignment.

Whole-genome alignment allows researchers to understand the genomic structure and variation among genomes. Approaches based on direct pairwise comparisons of DNA sequences require large computational capacities. As a consequence, pipelines combining tools for orthologous gene identification and synteny have been developed. In this manuscript, we present the latest functionalities implemented in NGSEP 4, to identify orthogroups and perform whole genome alignments. NGSEP implements functionalities for identification of clusters of homologus genes, synteny analysis and whole genome alignment. Our results showed that the NGSEP algorithm for orthogroups identification has competitive accuracy and efficiency in comparison to commonly used tools. The implementation also includes a visualization of the whole genome alignment based on synteny of the orthogroups that were identified, and a reconstruction of the pangenome based on frequencies of the orthogroups among the genomes. NGSEP 4 also includes a new graphical user interface based on the JavaFX technology. We expect that these new developments will be very useful for several studies in evolutionary biology and population genomics.

Gene regulatory networks on transfer entropy (GRNTE): a novel approach to reconstruct gene regulatory interactions applied to a case study for the plant pathogen Phytophthora infestans.

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.

Draft Genome Sequence of Komagataeibacter intermedius Strain AF2, a Producer of Cellulose, Isolated from Kombucha Tea.

Here, we present the draft genome sequence of Komagataeibacter intermedius strain AF2, which was isolated from Kombucha tea and is capable of producing cellulose, although at lower levels compared to another bacterium from the same environment, K. rhaeticus strain AF1.

Draft Genome Sequence of Komagataeibacter rhaeticus Strain AF1, a High Producer of Cellulose, Isolated from Kombucha Tea.

Here, we present the draft genome sequence of Komagatabaeicter rhaeticus strain AF1, which was isolated from Kombucha tea and is capable of producing high levels of cellulose.