Advances in microbial diagnosis: using mass spectrometry for proteomics and genomics applications

Since the last two decades mass spectrometry (MS) has been applied to analyse the chemical cellular components of microorganisms, providing rapid and discriminatory proteomic profiles for their species identification and, in some cases, subtyping. The application of MS for the microbial diagnosis is currently well-established. The remarkable reproducibility and objectivity of this method is based on the measurement of constantly expressed and highly abundant proteins, mainly important conservative ribosomal proteins, which are used as markers to generate a cellular fingerprint. Mass spectrometry based on matrix-assisted laser desorption ionization-time of flight (MALDI- TOF) technique has been an important tool for the microbial diagnostic. However, some technical limitation concerning both MALDI-TOF and its used protocols for sample preparation have fostered the research of new mass spectrometry systems (e.g. LC MS/MS). LC MS/MS is able to generate online mass spectra of specific ions with further online sequencing of these ions, which include both specific proteins and DNA fragments. In this work a set of data for yeasts and filamentous fungi diagnostic obtained through an international collaboration project involving partners from Argentina, Brazil, Chile and Portugal will be presented and discussed.

An R package for the integrated analysis of metabolomics and spectral data

Recently, there has been a growing interest in the field of metabolomics, materialized by a remarkable growth in experimental techniques, available data and related biological applications. Indeed, techniques as Nuclear Magnetic Resonance, Gas or Liquid Chromatography, Mass Spectrometry, Infrared and UV-visible spectroscopies have provided extensive datasets that can help in tasks as biological and biomedical discovery, biotechnology and drug development. However, as it happens with other omics data, the analysis of metabolomics datasets provides multiple challenges, both in terms of methodologies and in the development of appropriate computational tools. Indeed, from the available software tools, none addresses the multiplicity of existing techniques and data analysis tasks. In this work, we make available a novel R package, named specmine, which provides a set of methods for metabolomics data analysis, including data loading in different formats, pre-processing, metabolite identification, univariate and multivariate data analysis, machine learning, and feature selection. Importantly, the implemented methods provide adequate support for the analysis of data from diverse experimental techniques, integrating a large set of functions from several R packages in a powerful, yet simple to use environment. The package, already available in CRAN, is accompanied by a web site where users can deposit datasets, scripts and analysis reports to be shared with the community, promoting the efficient sharing of metabolomics data analysis pipelines.

A search for high-mass resonances decaying to τ+τ− in pp collisions at s√=8 TeV with the ATLAS detector

A search for high-mass resonances decaying into τ+τ− final states using proton-proton collisions at s√=8 TeV produced by the Large Hadron Collider is presented. The data were recorded with the ATLAS detector and correspond to an integrated luminosity of 19.5-20.3 fb−1. No statistically significant excess above the Standard Model expectation is observed; 95% credibility upper limits are set on the cross section times branching fraction of Z′ resonances decaying into τ+τ− pairs as a function of the resonance mass. As a result, Z′ bosons of the Sequential Standard Model with masses less than 2.02 TeV are excluded at 95% credibility. The impact of the fermionic couplings on the Z′ acceptance is investigated and limits are also placed on a Z′ model that exhibits enhanced couplings to third-generation fermions.

Search for high-mass diboson resonances with boson-tagged jets in proton-proton collisions at √s = 8TeV with the ATLAS detector

A search is performed for narrow resonances decaying into WW, WZ, or ZZ boson pairs using 20.3 fb−1 of proton--proton collision data at a centre-of-mass energy of s√ = 8 TeV recorded with the ATLAS detector at the Large Hadron Collider. Diboson resonances with masses in the range from 1.3 to 3.0 TeV are sought after using the invariant mass distribution of dijets where both jets are tagged as a boson jet, compatible with a highly boosted W or Z boson decaying to quarks, using jet mass and substructure properties. The largest deviation from a smoothly falling background in the observed dijet invariant mass distribution occurs around 2 TeV in the WZ channel, with a global significance of 2.5 standard deviations. Exclusion limits at the 95% confidence level are set on the production cross section times branching ratio for the WZ final state of a new heavy gauge boson, W′, and for the WW and ZZ final states of Kaluza--Klein excitations of the graviton in a bulk Randall--Sundrum model, as a function of the resonance mass. W′ bosons with couplings predicted by the extended gauge model in the mass range from 1.3 to 1.5 TeV are excluded at 95% confidence level.