The potential of the diverse chemistries present in natural products (NP) for biotechnology and medicine remains untapped because NP databases are not searchable with raw data and the NP community has no way to share data other than in published papers. Although mass spectrometry techniques are well-suited to high-throughput characterization of natural products, there is a pressing need for an infrastructure to enable sharing and curation of data. We present Global Natural Products Social molecular networking (GNPS, http://gnps.ucsd.edu), an open-access knowledge base for community wide organization and sharing of raw, processed or identified tandem mass (MS/MS) spectrometry data. In GNPS crowdsourced curation of freely available community-wide reference MS libraries will underpin improved annotations. Data-driven social-networking should facilitate identification of spectra and foster collaborations. We also introduce the concept of ‘living data’ through continuous reanalysis of deposited data.

Over the last decade, the number of studies reporting the use of electrospray ionization mass spectrometry (ESI-MS) in combination with collision cells (or other activation methods) to promote fragmentation of synthetic and natural products for structural elucidation purposes has considerably increased. However, the lack of a systematic compilation of the gas-phase fragmentation reactions subjected to ESI-MS/MS conditions still represents a challenge and has led to many misunderstood results in the literature. This review article exploits the most common fragmentation reactions for ions generated by ESI in positive and negative modes using collision cells in an effort to stimulate the use of this technique by non-specialists, undergraduate students and researchers in related areas.

Rheumatoid arthritis (RA) is an inflammatory autoimmune disease characterized by joint destruction and severe morbidity. Methotrexate (MTX) is the standard first-line therapy of RA. However, about 40% of RA patients are unresponsive to MTX treatment. Regulatory T cells (Tregs, CD4 + CD25 + FoxP3 + ) are thought to play an important role in attenuating RA. To investigate the role of Tregs in MTX resistance, we recruited 122 RA patients (53 responsive, R-MTX; 69 unresponsive, UR-MTX) and 33 healthy controls. Three months after MTX treatment, R-MTX but not UR-MTX showed higher frequency of peripheral blood CD39 + CD4 + CD25 + FoxP3 + Tregs than the healthy controls. Tregs produce adenosine (ADO) through ATP degradation by sequential actions of two cell surface ectonucleotidases: CD39 and CD73. Tregs from UR-MTX expressed a lower density of CD39, produced less ADO, and had reduced suppressive activity than Tregs from R-MTX. In a prospective study, before MTX treatment, UR-MTX expressed a lower density of CD39 on Tregs than those of R-MTX or control (P < 0.01). In a murine model of arthritis, CD39 blockade reversed the antiarthritic effects of MTX treatment. Our results demonstrate that MTX unresponsiveness in RA is associated with low expression of CD39 on Tregs and the decreased suppressive activity of these cells through reduced ADO production. Our findings thus provide hitherto unrecognized mechanism of immune regulation in RA and on mode of action of MTX. Furthermore, our data suggest that low expression of CD39 on Tregs could be a noninvasive biomarker for identifying MTX-resistant RA patients.methotrexate | rheumatoid arthritis | adenosine | biomarker | ectonucleotidases

Metabolomics is a powerful tool in the analysis and identification of metabolites responsible for biological properties. Regarding natural product chemistry, it constitutes a potential strategy to streamline the classic and laborious process of isolating natural products, which often involves the re-isolation and identification of known compounds. In this contribution, we establish a mass spectrometry-based metabolomics strategy to discover compounds with larvicidal activity against Aedes aegypti. We analyse the Brazilian plant Annona crassiflora using different platforms to annotate the active compounds in different extracts/fractions of various plant parts. The MetaboAnalyst and GNPS platforms, which consider LC-MS and LC-MS/MS data, respectively, were chosen to identify compounds that differentiate active and inactive samples. Bio-guided isolation was subsequently performed to confirm compound activity. Results proved the capacity of metabolomics to predict metabolite differences between active and inactive samples using LC-MS and LC-MS/MS data. Moreover, we discuss the limitations, possibilities, and strategies to have a broad view of vast data.