Genome sequencing and analysis of black flounder (Paralichthys orbignyanus) reveals new insights into Pleuronectiformes genomic size and structure.

Black flounder (Paralichthys orbignyanus, Pleuronectiformes) is a commercially significant marine fish with promising aquaculture potential in Argentina. Despite extensive studies on Black flounder aquaculture, its limited genetic information available hampers the crucial role genetics plays in the development of this activity. In this study, we first employed Illumina sequencing technology to sequence the entire genome of Black flounder. Utilizing two independent libraries-one from a female and another from a male-with 150 bp paired-end reads, a mean insert length of 350 bp, and over 35 X-fold coverage, we achieved assemblies resulting in a genome size of ~ 538 Mbp. Analysis of the assemblies revealed that more than 98% of the core genes were present, with more than 78% of them having more than 50% coverage. This indicates a somehow complete and accurate genome at the coding sequence level. This genome contains 25,231 protein-coding genes, 445 tRNAs, 3 rRNAs, and more than 1,500 non-coding RNAs of other types. Black flounder, along with pufferfishes, seahorses, pipefishes, and anabantid fish, displays a smaller genome compared to most other teleost groups. In vertebrates, the number of transposable elements (TEs) is often correlated with genome size. However, it remains unclear whether the sizes of introns and exons also play a role in determining genome size. Hence, to elucidate the potential factors contributing to this reduced genome size, we conducted a comparative genomic analysis between Black flounder and other teleost orders to determine if the small genomic size could be explained by repetitive elements or gene features, including the whole genome genes and introns sizes. We show that the smaller genome size of flounders can be attributed to several factors, including changes in the number of repetitive elements, and decreased gene size, particularly due to lower amount of very large and small introns. Thus, these components appear to be involved in the genome reduction in Black flounder. Despite these insights, the full implications and potential benefits of genome reduction in Black flounder for reproduction and aquaculture remain incompletely understood, necessitating further research.

Omics data integration facilitates target selection for new antiparasitic drugs against TriTryp infections.

Introduction: Trypanosoma cruzi, Trypanosoma brucei, and Leishmania spp., commonly referred to as TriTryps, are a group of protozoan parasites that cause important human diseases affecting millions of people belonging to the most vulnerable populations worldwide. Current treatments have limited efficiencies and can cause serious side effects, so there is an urgent need to develop new control strategies. Presently, the identification and prioritization of appropriate targets can be aided by integrative genomic and computational approaches. Methods: In this work, we conducted a genome-wide multidimensional data integration strategy to prioritize drug targets. We included genomic, transcriptomic, metabolic, and protein structural data sources, to delineate candidate proteins with relevant features for target selection in drug development. Results and Discussion: Our final ranked list includes proteins shared by TriTryps and covers a range of biological functions including essential proteins for parasite survival or growth, oxidative stress-related enzymes, virulence factors, and proteins that are exclusive to these parasites. Our strategy found previously described candidates, which validates our approach as well as new proteins that can be attractive targets to consider during the initial steps of drug discovery.

From Genome to Drugs: New Approaches in Antimicrobial Discovery.

Decades of successful use of antibiotics is currently challenged by the emergence of increasingly resistant bacterial strains. Novel drugs are urgently required but, in a scenario where private investment in the development of new antimicrobials is declining, efforts to combat drug-resistant infections become a worldwide public health problem. Reasons behind unsuccessful new antimicrobial development projects range from inadequate selection of the molecular targets to a lack of innovation. In this context, increasingly available omics data for multiple pathogens has created new drug discovery and development opportunities to fight infectious diseases. Identification of an appropriate molecular target is currently accepted as a critical step of the drug discovery process. Here, we review how diverse layers of multi-omics data in conjunction with structural/functional analysis and systems biology can be used to prioritize the best candidate proteins. Once the target is selected, virtual screening can be used as a robust methodology to explore molecular scaffolds that could act as inhibitors, guiding the development of new drug lead compounds. This review focuses on how the advent of omics and the development and application of bioinformatics strategies conduct a "big-data era" that improves target selection and lead compound identification in a cost-effective and shortened timeline.

Five-year microevolution of a multidrug-resistant Mycobacterium tuberculosis strain within a patient with inadequate compliance to treatment.

BACKGROUND: Whole-genome sequencing has shown that the Mycobacterium tuberculosis infection process can be more heterogeneous than previously thought. Compartmentalized infections, exogenous reinfections, and microevolution are manifestations of this clonal complexity. The analysis of the mechanisms causing the microevolution -the genetic variability of M. tuberculosis at short time scales- of a parental strain into clonal variants with a patient is a relevant issue that has not been yet completely addressed. To our knowledge, a whole genome sequence microevolution analysis in a single patient with inadequate adherence to treatment has not been previously reported. CASE PRESENTATION: In this work, we applied whole genome sequencing analysis for a more in-depth analysis of the microevolution of a parental Mycobacterium tuberculosis strain into clonal variants within a patient with poor treatment compliance in Argentina. We analyzed the whole-genome sequence of 8 consecutive Mycobacterium tuberculosis isolates obtained from a patient within 57-months of intermittent therapy. Nineteen mutations (9 short-term, 10 fixed variants) emerged, most of them associated with drug resistance. The first isolate was already resistant to isoniazid, rifampicin, and streptomycin, thereafter the strain developed resistance to fluoroquinolones and pyrazinamide. Surprisingly, isolates remained susceptible to the pro-drug ethionamide after acquiring a frameshift mutation in ethA, a gene required for its activation. We also found a novel variant, (T-54G), in the 5' untranslated region of whiB7 (T-54G), a region allegedly related to kanamycin resistance. Notably, discrepancies between canonical and phage-based susceptibility testing to kanamycin were previously found for the isolate harboring this mutation. In our patient, microevolution was mainly driven by drug selective pressure. Rare short-term mutations fixed together with resistance-conferring mutations during therapy. CONCLUSIONS: This report highlights the relevance of whole-genome sequencing analysis in the clinic for characterization of pre-XDR and MDR resistance profile, particularly in patients with incomplete and/or intermittent treatment.

MRSA dynamic circulation between the community and the hospital setting: New insights from a cohort study.

Dissemination of methicillin-resistant-Staphylococcus aureus/(MRSA) is a worldwide concern both in hospitals [healthcare-associated-(HA)-MRSA] and communities [community-associated-(CA)-MRSA]. Knowledge on when and where MRSA colonization is acquired and what clones are involved is necessary, to focus efforts for prevention of hospital-acquired MRSA-infections. METHODS: A prospective/longitudinal cohort study was performed in eight Argentina hospitals (Cordoba/ October-December/2014). Surveillance cultures for MRSA (nose-throat-inguinal) were obtained on admission and at discharge. MRSA strains were genetically typed as CA-MRSAG and HA-MRSAG genotypes. RESULTS: Overall, 1419 patients were screened and 534 stayed at hospital for ≥3 days. S. aureus admission prevalence was 30.9% and 4.2% for MRSA. Overall MRSA acquisition rate was 2.3/1000 patient-days-at-risk with a MRSA acquisition prevalence of 1.96% (95%CI: 1.0%-3.4%); 3.2% of patients were discharged back to community with MRSA. CA-MRSAG accounted for 84.6% of imported, 100.0% of hospital-acquired and 94% of discharged MRSA strains. Most imported and acquired MRSA strains belonged to two major epidemic CA-MRSA clones spread in Argentina: PFGEtypeI-ST5-IVa-t311-PVL+ and PFGEtypeN/ST30-IVc-t019-PVL+. CONCLUSIONS: CA-MRSA clones, particularly ST5-IV-PVL+ and ST30-IV-PVL+, with main reservoir in the community, not only enter but also are truly acquired within hospital, causing healthcare-associated-hospital-onset infections, having a transmission capacity greater or similar than HA-MRSAG. This information is essential to develop appropriate MRSA infection prevention-control programs, considering hospital and community.

Fluoromycobacteriophages Can Detect Viable Mycobacterium tuberculosis and Determine Phenotypic Rifampicin Resistance in 3-5 Days From Sputum Collection.

The World Health Organization (WHO) estimates that 40% of tuberculosis (TB) cases are not diagnosed and treated correctly. Even though there are several diagnostic tests available in the market, rapid, easy, inexpensive detection, and drug susceptibility testing (DST) of Mycobacterium tuberculosis is still of critical importance specially in low and middle-income countries with high incidence of the disease. In this work, we have developed a microscopy-based methodology using the reporter mycobacteriophage mCherrybomb ϕ for detection of Mycobacterium spp. and phenotypic determination of rifampicin resistance within just days from sputum sample collection. Fluoromycobacteriophage methodology is compatible with regularly used protocols in clinical laboratories for TB diagnosis and paraformaldehyde fixation after infection reduces biohazard risks with sample analysis by fluorescence microscopy. We have also set up conditions for discrimination between M. tuberculosis complex (MTBC) and non-tuberculous mycobacteria (NTM) strains by addition of p-nitrobenzoic acid (PNB) during the assay. Using clinical isolates of pre-XDR and XDR-TB strains from this study, we tested mCherrybomb Φ for extended DST and we compared the antibiotic resistance profile with those predicted by whole genome sequencing. Our results emphasize the utility of a phenotypic test for M. tuberculosis extended DST. The many attributes of mCherrybomb Φ suggests this could be a useful component of clinical microbiological laboratories for TB diagnosis and since only viable cells are detected this could be a useful tool for monitoring patient response to treatment.

An integrative, multi-omics approach towards the prioritization of Klebsiella pneumoniae drug targets.

Klebsiella pneumoniae (Kp) is a globally disseminated opportunistic pathogen that can cause life-threatening infections. It has been found as the culprit of many infection outbreaks in hospital environments, being particularly aggressive towards newborns and adults under intensive care. Many Kp strains produce extended-spectrum ß-lactamases, enzymes that promote resistance against antibiotics used to fight these infections. The presence of other resistance determinants leading to multidrug-resistance also limit therapeutic options, and the use of 'last-resort' drugs, such as polymyxins, is not uncommon. The global emergence and spread of resistant strains underline the need for novel antimicrobials against Kp and related bacterial pathogens. To tackle this great challenge, we generated multiple layers of 'omics' data related to Kp and prioritized proteins that could serve as attractive targets for antimicrobial development. Genomics, transcriptomics, structuromic and metabolic information were integrated in order to prioritize candidate targets, and this data compendium is freely available as a web server. Twenty-nine proteins with desirable characteristics from a drug development perspective were shortlisted, which participate in important processes such as lipid synthesis, cofactor production, and core metabolism. Collectively, our results point towards novel targets for the control of Kp and related bacterial pathogens.

Target-Pathogen: a structural bioinformatic approach to prioritize drug targets in pathogens.

Available genomic data for pathogens has created new opportunities for drug discovery and development to fight them, including new resistant and multiresistant strains. In particular structural data must be integrated with both, gene information and experimental results. In this sense, there is a lack of an online resource that allows genome wide-based data consolidation from diverse sources together with thorough bioinformatic analysis that allows easy filtering and scoring for fast target selection for drug discovery. Here, we present Target-Pathogen database (http://target.sbg.qb.fcen.uba.ar/patho), designed and developed as an online resource that allows the integration and weighting of protein information such as: function, metabolic role, off-targeting, structural properties including druggability, essentiality and omic experiments, to facilitate the identification and prioritization of candidate drug targets in pathogens. We include in the database 10 genomes of some of the most relevant microorganisms for human health (Mycobacterium tuberculosis, Mycobacterium leprae, Klebsiella pneumoniae, Plasmodium vivax, Toxoplasma gondii, Leishmania major, Wolbachia bancrofti, Trypanosoma brucei, Shigella dysenteriae and Schistosoma Smanosoni) and show its applicability. New genomes can be uploaded upon request.