Nitrosative stress under microaerobic conditions triggers inositol metabolism in Pseudomonas extremaustralis.

Bacteria are exposed to reactive oxygen and nitrogen species that provoke oxidative and nitrosative stress which can lead to macromolecule damage. Coping with stress conditions involves the adjustment of cellular responses, which helps to address metabolic challenges. In this study, we performed a global transcriptomic analysis of the response of Pseudomonas extremaustralis to nitrosative stress, induced by S-nitrosoglutathione (GSNO), a nitric oxide donor, under microaerobic conditions. The analysis revealed the upregulation of genes associated with inositol catabolism; a compound widely distributed in nature whose metabolism in bacteria has aroused interest. The RNAseq data also showed heightened expression of genes involved in essential cellular processes like transcription, translation, amino acid transport and biosynthesis, as well as in stress resistance including iron-dependent superoxide dismutase, alkyl hydroperoxide reductase, thioredoxin, and glutathione S-transferase in response to GSNO. Furthermore, GSNO exposure differentially affected the expression of genes encoding nitrosylation target proteins, encompassing metalloproteins and proteins with free cysteine and /or tyrosine residues. Notably, genes associated with iron metabolism, such as pyoverdine synthesis and iron transporter genes, showed activation in the presence of GSNO, likely as response to enhanced protein turnover. Physiological assays demonstrated that P. extremaustralis can utilize inositol proficiently under both aerobic and microaerobic conditions, achieving growth comparable to glucose-supplemented cultures. Moreover, supplementing the culture medium with inositol enhances the stress tolerance of P. extremaustralis against combined oxidative-nitrosative stress. Concordant with the heightened expression of pyoverdine genes under nitrosative stress, elevated pyoverdine production was observed when myo-inositol was added to the culture medium. These findings highlight the influence of nitrosative stress on proteins susceptible to nitrosylation and iron metabolism. Furthermore, the activation of myo-inositol catabolism emerges as a protective mechanism against nitrosative stress, shedding light on this pathway in bacterial systems, and holding significance in the adaptation to unfavorable conditions.

High-throughput prioritization of target proteins for development of new antileishmanial compounds.

Leishmaniasis, a vector-borne disease, is caused by the infection of Leishmania spp., obligate intracellular protozoan parasites. Presently, human vaccines are unavailable, and the primary treatment relies heavily on systemic drugs, often presenting with suboptimal formulations and substantial toxicity, making new drugs a high priority for LMIC countries burdened by the disease, but a low priority in the agenda of most pharmaceutical companies due to unattractive profit margins. New ways to accelerate the discovery of new, or the repositioning of existing drugs, are needed. To address this challenge, our study aimed to identify potential protein targets shared among clinically-relevant Leishmania species. We employed a subtractive proteomics and comparative genomics approach, integrating high-throughput multi-omics data to classify these targets based on different druggability metrics. This effort resulted in the ranking of 6502 ortholog groups of protein targets across 14 pathogenic Leishmania species. Among the top 20 highly ranked groups, metabolic processes known to be attractive drug targets, including the ubiquitination pathway, aminoacyl-tRNA synthetases, and purine synthesis, were rediscovered. Additionally, we unveiled novel promising targets such as the nicotinate phosphoribosyltransferase enzyme and dihydrolipoamide succinyltransferases. These groups exhibited appealing druggability features, including less than 40% sequence identity to the human host proteome, predicted essentiality, structural classification as highly druggable or druggable, and expression levels above the 50th percentile in the amastigote form. The resources presented in this work also represent a comprehensive collection of integrated data regarding trypanosomatid biology.

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.

Overview of the SARS-CoV-2 genotypes circulating in Latin America during 2021.

Latin America is one of the regions in which the COVID-19 pandemic has a stronger impact, with more than 72 million reported infections and 1.6 million deaths until June 2022. Since this region is ecologically diverse and is affected by enormous social inequalities, efforts to identify genomic patterns of the circulating SARS-CoV-2 genotypes are necessary for the suitable management of the pandemic. To contribute to the genomic surveillance of the SARS-CoV-2 in Latin America, we extended the number of SARS-CoV-2 genomes available from the region by sequencing and analyzing the viral genome from COVID-19 patients from seven countries (Argentina, Brazil, Costa Rica, Colombia, Mexico, Bolivia, and Peru). Subsequently, we analyzed the genomes circulating mainly during 2021 including records from GISAID database from Latin America. A total of 1,534 genome sequences were generated from seven countries, demonstrating the laboratory and bioinformatics capabilities for genomic surveillance of pathogens that have been developed locally. For Latin America, patterns regarding several variants associated with multiple re-introductions, a relatively low percentage of sequenced samples, as well as an increment in the mutation frequency since the beginning of the pandemic, are in line with worldwide data. Besides, some variants of concern (VOC) and variants of interest (VOI) such as Gamma, Mu and Lambda, and at least 83 other lineages have predominated locally with a country-specific enrichments. This work has contributed to the understanding of the dynamics of the pandemic in Latin America as part of the local and international efforts to achieve timely genomic surveillance of SARS-CoV-2.

Assessing the hidden diversity underlying consensus sequences of SARS-CoV-2 using VICOS, a novel bioinformatic pipeline for identification of mixed viral populations.

INTRODUCTION: Coinfection with two SARS-CoV-2 viruses is still a very understudied phenomenon. Although next generation sequencing methods are very sensitive to detect heterogeneous viral populations in a sample, there is no standardized method for their characterization, so their clinical and epidemiological importance is unknown. MATERIAL AND METHODS: We developed VICOS (Viral COinfection Surveillance), a new bioinformatic algorithm for variant calling, filtering and statistical analysis to identify samples suspected of being mixed SARS-CoV-2 populations from a large dataset in the framework of a community genomic surveillance. VICOS was used to detect SARS-CoV-2 coinfections in a dataset of 1,097 complete genomes collected between March 2020 and August 2021 in Argentina. RESULTS: We detected 23 cases (2%) of SARS-CoV-2 coinfections. Detailed study of VICOS's results together with additional phylogenetic analysis revealed 3 cases of coinfections by two viruses of the same lineage, 2 cases by viruses of different genetic lineages, 13 were compatible with both coinfection and intra-host evolution, and 5 cases were likely a product of laboratory contamination. DISCUSSION: Intra-sample viral diversity provides important information to understand the transmission dynamics of SARS-CoV-2. Advanced bioinformatics tools, such as VICOS, are a necessary resource to help unveil the hidden diversity of SARS-CoV-2.

Methodology to Analyse Three-Dimensional Asymmetries in the Forces Applied to the Pedals in Cycling.

The asymmetries study between both legs of the forces applied to the pedals in cycling is important because they may affect the performance of the cyclist or prevent the occurrence of injuries. Studies focused on analysing asymmetries in forces tend to consider only the effective force, disregarding the three-dimensional nature of the force. Furthermore, these studies do not analyse the possible physical or neurological causes that may have led to the appearance of the asymmetries. This paper presents a methodology to carry out three-dimensional analysis of the asymmetries of the forces applied in both pedals and discriminate the possible sources of these asymmetries. Seven participants, amateurs and without pathologies, were analysed. Two commercial pedals were instrumented to measure the three components of the force applied to each pedal. The Normalized Symmetry Index (NSI) and the Cross Correlation Coefficient (CCC) were used for the asymmetries analysis. Results showed that both indexes need to be used in conjunction to analyse the causes of asymmetry in the pedal forces from a 3D perspective along the pedal cycle. The NSI is an index that makes it possible to evaluate asymmetry by considering only the value of the force applied by each leg at each instant. The CCC makes it possible to evaluate whether the temporal evolutions of the forces applied by each leg are similar. Preliminary results suggest that the proposed methodology is effective for analysing asymmetries in the forces in a pedalling cycle from a three-dimensional point of view. Forces in the sagittal plane showed a high level of symmetry. The lateral-medial force presented the highest level of asymmetry due to the difference in the magnitudes of the applied forces by both legs and the existing time shift between the two force patterns. The results of this work will allow for more complete and accurate three-dimensional dynamic analyses of the lower body during pedalling.

Human Y chromosome sequences from Q Haplogroup reveal a South American settlement pre-18,000 years ago and a profound genomic impact during the Younger Dryas.

The settlement of the Americas has been the focus of incessant debate for more than 100 years, and open questions regarding the timing and spatial patterns of colonization still remain today. Phylogenetic studies with complete human Y chromosome sequences are used as a highly informative tool to investigate the history of human populations in a given time frame. To study the phylogenetic relationships of Native American lineages and infer the settlement history of the Americas, we analyzed Y chromosome Q Haplogroup, which is a Pan-American haplogroup and represents practically all Native American lineages in Mesoamerica and South America. We built a phylogenetic tree for Q Haplogroup based on 102 whole Y chromosome sequences, of which 13 new Argentine sequences were provided by our group. Moreover, 1,072 new single nucleotide polymorphisms (SNPs) that contribute to its resolution and diversity were identified. Q-M848 is known to be the most frequent autochthonous sub-haplogroup of the Americas. The present is the first genomic study of Q Haplogroup in which current knowledge on Q-M848 sub-lineages is contrasted with the historical, archaeological and linguistic data available. The divergence times, spatial structure and the SNPs found here as novel for Q-Z780, a less frequent sub-haplogroup autochthonous of the Americas, provide genetic support for a South American settlement before 18,000 years ago. We analyzed how environmental events that occurred during the Younger Dryas period may have affected Native American lineages, and found that this event may have caused a substantial loss of lineages. This could explain the current low frequency of Q-Z780 (also perhaps of Q-F4674, a third possible sub-haplogroup autochthonous of the Americas). These environmental events could have acted as a driving force for expansion and diversification of the Q-M848 sub-lineages, which show a spatial structure that developed during the Younger Dryas period.

Pathway Driven Target Selection in Klebsiella pneumoniae: Insights Into Carbapenem Exposure.

Carbapenem-resistant Klebsiella pneumoniae (CR-KP) represents an emerging threat to public health. CR-KP infections result in elevated morbidity and mortality. This fact, coupled with their global dissemination and increasingly limited number of therapeutic options, highlights the urgency of novel antimicrobials. Innovative strategies linking genome-wide interrogation with multi-layered metabolic data integration can accelerate the early steps of drug development, particularly target selection. Using the BioCyc ontology, we generated and manually refined a metabolic network for a CR-KP, K. pneumoniae Kp13. Converted into a reaction graph, we conducted topological-based analyses in this network to prioritize pathways exhibiting druggable features and fragile metabolic points likely exploitable to develop novel antimicrobials. Our results point to the aptness of previously recognized pathways, such as lipopolysaccharide and peptidoglycan synthesis, and casts light on the possibility of targeting less explored cellular functions. These functions include the production of lipoate, trehalose, glycine betaine, and flavin, as well as the salvaging of methionine. Energy metabolism pathways emerged as attractive targets in the context of carbapenem exposure, targeted either alone or in conjunction with current therapeutic options. These results prompt further experimental investigation aimed at controlling this highly relevant pathogen.

Cost-Effective Method to Perform SARS-CoV-2 Variant Surveillance: Detection of Alpha, Gamma, Lambda, Delta, Epsilon, and Zeta in Argentina.

SARS-CoV-2 variants with concerning characteristics have emerged since the end of 2020. Surveillance of SARS-CoV-2 variants was performed on a total of 4,851 samples from the capital city and 10 provinces of Argentina, during 51 epidemiological weeks (EWs) that covered the end of the first wave and the ongoing second wave of the COVID-19 pandemic in the country (EW 44/2020 to EW 41/2021). The surveillance strategy was mainly based on Sanger sequencing of a Spike coding region that allows the identification of signature mutations associated with variants. In addition, whole-genome sequences were obtained from 637 samples. The main variants found were Gamma and Lambda, and to a lesser extent, Alpha, Zeta, and Epsilon, and more recently, Delta. Whereas, Gamma dominated in different regions of the country, both Gamma and Lambda prevailed in the most populated area, the metropolitan region of Buenos Aires. The lineages that circulated on the first wave were replaced by emergent variants in a term of a few weeks. At the end of the ongoing second wave, Delta began to be detected, replacing Gamma and Lambda. This scenario is consistent with the Latin American variant landscape, so far characterized by a concurrent increase in Delta circulation and a stabilization in the number of cases. The cost-effective surveillance protocol presented here allowed for a rapid response in a resource-limited setting, added information on the expansion of Lambda in South America, and contributed to the implementation of public health measures to control the disease spread in Argentina.

Design and Validation of a Device Attached to a Conventional Bicycle to Measure the Three-Dimensional Forces Applied to a Pedal.

Knowledge of the forces applied to the pedals during cycling is of great importance both from the point of view of improving sporting performance and medical analysis of injuries. The most common equipment for measuring pedal forces is usually limited to the study of forces in the sagittal plane. Equipment that measures three-dimensional forces tends to be bulky and to be incorporated into bicycles that are modified to accommodate it, which can cause the measurements taken to differ from those obtained in real pedalling conditions. This work presents a device for measuring the 3D forces applied to the pedal, attachable to a conventional bicycle and pedals, which does not alter the natural pedalling of cyclists. The equipment consists of four gauges located on the pedal axis and two on the crank, controlled by a microcontroller. Pedal forces measurements were made for six cyclists, with results similar to those shown in the literature. The correct estimation of the lateral-medial direction force is of great interest when evaluating a possible overload at the joints; it will also allow a comparison of the effectiveness index during pedalling, showing the role of this component in this index from a mechanical standpoint.

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.

Isolation and Characterization of vB_MsmS_Celfi: A New Mycobacterium tuberculosis Bacteriophage.

Introduction: Because of the clinical relevance of Mycobacteria, and from a therapeutic perspective, there is an increasing interest to study phages that infect bacteria belonging to this genus. Materials and Methods: A phage was isolated from a soil sample, using Mycobacterium smegmatis as host. Its characterization included sequencing, annotation, and analysis of the genome, host range determination, and electron microscopy imaging. Results: Mycobacterium phage vB_MsmS_Celfi is a temperate phage able to infect Mycobacterium tuberculosis with high efficiency. From electron microscopy images, Celfi belongs to the Siphoviridae family. Genome analysis classified phage Celfi into cluster L, subcluster L2 of Actinobacteriophage clusters. Mycobacterium phage Celfi exhibits a Lysin B distant to those present in other members of the subcluster and other mycobacteriophages. Conclusions: The discovery of new phages that infect M. tuberculosis could contribute to the development of novel tools for detection systems and future treatment of the disease.

Genome Sequence and Characterization of Lactobacillus casei Phage, vB_LcaM_Lbab1 Isolated from Raw Milk.

Introduction: Only a few Lactobacillus casei phages have so far been characterized. As several L. casei strains are part of probiotic formulations, bacteriophage outbreaks targeting these strains can lead to critical losses within the dairy industry. Materials and Methods: A new L. casei phage was isolated from raw milk obtained from a milking yard from the province of Buenos Aires. The phage genome was sequenced, annotated, and analyzed. Morphology was determined by electron microscopy and the host range was established. Results: Lactobacillus phage vB_LcaM_Lbab1 is a member of the Herelleviridae family and features a host range including L. casei/Lactobacillus paracasei and Lactobacillus kefiri strains. We further analyzed the baseplate proteins in silico and found putative carbohydrate binding modules that are responsible for host recognition in other Lactobacillus phages. Conclusions: A new Lactobacillus phage was isolated and characterized. The focus was made on its host recognition mechanism, pointing toward the development of future strategies to avoid deleterious infections in the dairy industry.

Prioritisation of potential drug targets against Bartonella bacilliformis by an integrative in-silico approach.

BACKGROUND Carrion's disease (CD) is a neglected biphasic illness caused by Bartonella bacilliformis, a Gram-negative bacteria found in the Andean valleys. The spread of resistant strains underlines the need for novel antimicrobials against B. bacilliformis and related bacterial pathogens. OBJECTIVE The main aim of this study was to integrate genomic-scale data to shortlist a set of proteins that could serve as attractive targets for new antimicrobial discovery to combat B. bacilliformis. METHODS We performed a multidimensional genomic scale analysis of potential and relevant targets which includes structural druggability, metabolic analysis and essentiality criteria to select proteins with attractive features for drug discovery. FINDINGS We shortlisted seventeen relevant proteins to develop new drugs against the causative agent of Carrion's disease. Particularly, the protein products of fabI, folA, aroA, trmFO, uppP and murE genes, meet an important number of desirable features that make them attractive targets for new drug development. This data compendium is freely available as a web server (http://target.sbg.qb.fcen.uba.ar/). MAIN CONCLUSION This work represents an effort to reduce the costs in the first phases of B. bacilliformis drug discovery.

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.

Prioritisation of potential drug targets against Bartonella bacilliformis by an integrative in-silico approach

BACKGROUND Carrion's disease (CD) is a neglected biphasic illness caused by Bartonella bacilliformis, a Gram-negative bacteria found in the Andean valleys. The spread of resistant strains underlines the need for novel antimicrobials against B. bacilliformis and related bacterial pathogens. OBJECTIVE The main aim of this study was to integrate genomic-scale data to shortlist a set of proteins that could serve as attractive targets for new antimicrobial discovery to combat B. bacilliformis. METHODS We performed a multidimensional genomic scale analysis of potential and relevant targets which includes structural druggability, metabolic analysis and essentiality criteria to select proteins with attractive features for drug discovery. FINDINGS We shortlisted seventeen relevant proteins to develop new drugs against the causative agent of Carrion's disease. Particularly, the protein products of fabI, folA, aroA, trmFO, uppP and murE genes, meet an important number of desirable features that make them attractive targets for new drug development. This data compendium is freely available as a web server (http://target.sbg.qb.fcen.uba.ar/). MAIN CONCLUSION This work represents an effort to reduce the costs in the first phases of B. bacilliformis drug discovery.

Prioritisation of potential drug targets against Bartonella bacilliformis by an integrative in-silico approach

BACKGROUND: Carrion’s disease (CD) is a neglected biphasic illness caused by Bartonella bacilliformis, a Gram-negative bacteria found in the Andean valleys. The spread of resistant strains underlines the need for novel antimicrobials against B. bacilliformis and related bacterial pathogens. OBJECTIVE: The main aim of this study was to integrate genomic-scale data to shortlist a set of proteins that could serve as attractive targets for new antimicrobial discovery to combat B. bacilliformis. METHODS: We performed a multidimensional genomic scale analysis of potential and relevant targets which includes structural druggability, metabolic analysis and essentiality criteria to select proteins with attractive features for drug discovery. FINDINGS: We shortlisted seventeen relevant proteins to develop new drugs against the causative agent of Carrion’s disease. Particularly, the protein products of fabI, folA, aroA, trmFO, uppP and murE genes, meet an important number of desirable features that make them attractive targets for new drug development. This data compendium is freely available as a web server (http://target.sbg.qb.fcen.uba.ar/). MAIN CONCLUSION: This work represents an effort to reduce the costs in the first phases of B. bacilliformis drug discovery.

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.