Biology subjects

Nothias, L.-F.

Publications and source records attributed to Nothias, L.-F..

3 recordsLinked to original sources

bioRxiv2017

MetaRiPPquest: A Peptidogenomics Approach for the Discovery of Ribosomally Synthesized and Post-translationally Modified Peptides

Ribosomally synthesized and post-translationally modified peptides (RiPPs) are an important class of natural products that include many antibiotics and a variety of other bioactive compounds. While recent breakthroughs in RiPP discovery raised the challenge of developing new algorithms for their analysis, peptidogenomic-based identification of RiPPs by combining genome/metagenome mining with analysis of tandem mass spectra remains an open problem. We present here MetaRiPPquest, a software tool for addressing this challenge that is compatible with large-scale screening platforms for natural product discovery. After searching millions of spectra in the Global Natural Products Social (GNPS) molecular networking infrastructure against just six genomic and metagenomic datasets, MetaRiPPquest identified 27 known and discovered 5 novel RiPP natural products.

bioinformatics↗

bioRxiv2017

Significance estimation for large scale untargeted metabolomics annotations

The annotation of small molecules in untargeted mass spectrometry relies on the matching of fragment spectra to reference library spectra. While various spectrum-spectrum match scores exist, the field lacks statistical methods for estimating the false discovery rates (FDR) of these annotations. We present empirical Bayes and target-decoy based methods to estimate the false discovery rate. Relying on estimations of false discovery rates, we explore the effect of different spectrum-spectrum match criteria on the number and the nature of the molecules annotated. We show that the spectral matching settings needs to be adjusted for each project. By adjusting the scoring parameters and thresholds, the number of annotations rose, on average, by +139% (ranging from -92% up to +5705%) when compared to a default parameter set available at GNPS. The FDR estimation methods presented will enable a user to define the scoring criteria for large scale analysis of untargeted small molecule data that has been essential in the advancement of large scale proteomics, transcriptomics, and genomics science.

bioinformatics↗

bioRxiv2017

Preprint: Environmentally-Friendly Workflow Based on Supercritical Fluid Chromatography and Tandem Mass Spectrometry Molecular Networking For the Discovery of Potent Anti-Viral Leads From Plants

A supercritical fluid chromatography-based targeted purification workflow using tandem mass spectrometry and molecular networking was developed to analyze, annotate and isolate secondary metabolites from complex mixture. This approach was applied for targeted isolation of new antiviral diterpene esters from Euphorbia semiperfoliata whole plant extract. The analysis of bioactive fractions revealed that unknown diterpene esters, including jatrophane esters and phorboids esters, were present in the samples. The purification procedure using semi-preparative-supercritical fluid chromatography led to the isolation and identification of two jatrophane esters (13 and 14) and four 4-deoxyphorbol esters (15-18). Compound 16 was found to display antiviral activity against chikungunya virus (EC50 = 0.45 {micro}M), while compound 15 was found to be a potent and selective inhibitor of HIV-1 replication in a recombinant virus assay (EC50 = 13 nM). This study showed that supercritical fluid chromatography-based workflow and molecular networking can facilitate and accelerate the discovery of bioactive small molecules by targeted molecules of interest, while minimizing the use of toxic solvents.\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=104 SRC=\"FIGDIR/small/106153_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (23K):\norg.highwire.dtl.DTLVardef@191802aorg.highwire.dtl.DTLVardef@1755ab8org.highwire.dtl.DTLVardef@196edf5org.highwire.dtl.DTLVardef@1e0a1e0_HPS_FORMAT_FIGEXP M_FIG C_FIG

pharmacology and toxicology↗