To characterize at the genomic level the evolution of multiresistance during an outbreak of Klebsiella pneumoniae in a burns intensive care unit. The outbreak involved a DHA-1 β-lactamase-producing strain that later acquired carbapenem and fosfomycin resistance, and in one case colistin resistance. The genomes of two isolates were sequenced and compared with a previously sequenced genome. The role of hypermutability was investigated by measuring the mutation frequencies of the isolates and comparison with a collection of control strains. Sequence comparison identified four single-nucleotide variants and two transposon insertions. Analysis of the variants in the whole collection related carbapenem and fosfomycin resistance to a nonsense mutation in the ompK36 porin gene and colistin resistance to an IS1 insertion in the mgrB gene. The plasmid carrying the bla_DHA-1 gene was unstable in the absence of antibiotics, and analysis of isolates that had lost the plasmid showed that the porin mutation alone was not sufficient to generate carbapenem resistance. The mutation frequencies were similar among all the strains analysed. Carbapenem resistance required production of the DHA-1 β-lactamase and decreased permeability, but fosfomycin resistance depended only on permeability. Resistance to colistin might be related to an alteration in the regulation of the phoPQ system. Hypermutation is not related to the selection of porin mutants. Plasmid instability might be due to the high number of mobile elements and suggests a major role for antibiotic selection pressure in the emergence and evolution of this outbreak.

OXA-48-producing Klebsiellapneumoniae isolates often show growth of colonies within inhibition zones in carbapenem diffusion assays. The nature of these colonies was investigated in a series of clinical isolates of OXA-48-producing K. pneumoniae obtained in the context of a hospital outbreak, and they were found to be persistent colonies that reproduced again the same phenotype when they were collected and tested in diffusion assays again. The frequency of mutations conferring resistance to meropenem (8 μg/mL) was determined for the same isolates. The average mutation frequency was 5.47·10-6 (range: 2.59·10-8-5.87·10-5), and the analysis of several resistant mutants showed that all of them had mutations in the ompK36 porin gene. Heteroresistance was investigated using population analysis profiling. The profiles were compatible with mutation frequency assays, and all the colonies analyzed were resistant mutants. In OXA-48-producing K. pneumoniae, the growth of persisters seems to be specific of diffusion assays.

The genome sequence of one OXA-48-producing Klebsiella pneumoniae belonging to sequence type (ST) 405, and three belonging to ST11, were used to design and test ST-specific PCR assays for typing OXA-48-producing K. pneumoniae. The approach proved to be useful for in-house development of rapid PCR typing assays for local outbreak surveillance.

Background: Metabolomics has a great potential in the development of new biomarkers in cancer and it has experiment recent technical advances.Methods: In this study, metabolomics and gene expression data from 67 localized (stage I to IIIB) breast cancer tumor samples were analyzed, using (1) probabilistic graphical models to define associations using quantitative data without other a priori information; and (2) Flux Balance Analysis and flux activities to characterize differences in metabolic pathways.Results: On the one hand, both analyses highlighted the importance of glutamine in breast cancer. Moreover, cell experiments showed that treating breast cancer cells with drugs targeting glutamine metabolism significantly affects cell viability. On the other hand, these computational methods suggested some hypotheses and have demonstrated their utility in the analysis of metabolomics data and in associating metabolomics with patient’s clinical outcome.Conclusions: Computational analyses applied to metabolomics data suggested that glutamine metabolism is a relevant process in breast cancer. Cell experiments confirmed this hypothesis. In addition, these computational analyses allow associating metabolomics data with patient prognosis.

Anal squamous cell carcinoma (ASCC) is a rare neoplasm. Chemoradiotherapy is the standard of care, with no therapeutic advances achieved over the past three decades. Thus, a deeper molecular characterization of this disease is still necessary. We analyzed 46 paraffin-embedded tumor samples from patients diagnosed with primary ASCC by exome sequencing. A bioinformatics approach focused in the identification of high-impact genetic variants, which may act as drivers of oncogenesis, was performed. The relation between genetics variants and prognosis was also studied. The list of high-impact genetic variants was unique for each patient. However, the pathways in which these genes are involved are well-known hallmarks of cancer, such as angiogenesis or immune pathways. Additionally, we determined that genetic variants in BRCA2, ZNF750, FAM208B, ZNF599, and ZC3H13 genes are related with poor disease-free survival in ASCC. This may help to stratify the patient's prognosis and open new avenues for potential therapeutic intervention. In conclusion, sequencing of ASCC clinical samples appears an encouraging tool for the molecular portrait of this disease.

Breast cancer is a heterogeneous disease. In clinical practice, tumors are classified as hormonal receptor positive, Her2 positive and triple negative tumors. In previous works, our group defined a new hormonal receptor positive subgroup, the TN-like subtype, which had a prognosis and a molecular profile more similar to triple negative tumors. In this study, proteomics and Bayesian networks were used to characterize protein relationships in 96 breast tumor samples. Components obtained by these methods had a clear functional structure. The analysis of these components suggested differences in processes such as mitochondrial function or extracellular matrix between breast cancer subtypes, including our new defined subtype TN-like. In addition, one of the components, mainly related with extracellular matrix processes, had prognostic value in this cohort. Functional approaches allow to build hypotheses about regulatory mechanisms and to establish new relationships among proteins in the breast cancer context.