Alejandro Villar-Briones

Bio: Alejandro Villar-Briones is an academic researcher from Okinawa Institute of Science and Technology. The author has contributed to research in topics: Schizosaccharomyces pombe & Schizosaccharomyces. The author has an hindex of 14, co-authored 24 publications receiving 2730 citations.

MZmine 2: Modular framework for processing, visualizing, and analyzing mass spectrometry-based molecular profile data

Abstract: Mass spectrometry (MS) coupled with online separation methods is commonly applied for differential and quantitative profiling of biological samples in metabolomic as well as proteomic research. Such approaches are used for systems biology, functional genomics, and biomarker discovery, among others. An ongoing challenge of these molecular profiling approaches, however, is the development of better data processing methods. Here we introduce a new generation of a popular open-source data processing toolbox, MZmine 2. A key concept of the MZmine 2 software design is the strict separation of core functionality and data processing modules, with emphasis on easy usability and support for high-resolution spectra processing. Data processing modules take advantage of embedded visualization tools, allowing for immediate previews of parameter settings. Newly introduced functionality includes the identification of peaks using online databases, MSn data support, improved isotope pattern support, scatter plot visualization, and a new method for peak list alignment based on the random sample consensus (RANSAC) algorithm. The performance of the RANSAC alignment was evaluated using synthetic datasets as well as actual experimental data, and the results were compared to those obtained using other alignment algorithms. MZmine 2 is freely available under a GNU GPL license and can be obtained from the project website at: http://mzmine.sourceforge.net/ . The current version of MZmine 2 is suitable for processing large batches of data and has been applied to both targeted and non-targeted metabolomic analyses.

Quantitative high-throughput profiling of snake venom gland transcriptomes and proteomes (Ovophis okinavensis and Protobothrops flavoviridis)

Abstract: Advances in DNA sequencing and proteomics have facilitated quantitative comparisons of snake venom composition. Most studies have employed one approach or the other. Here, both Illumina cDNA sequencing and LC/MS were used to compare the transcriptomes and proteomes of two pit vipers, Protobothrops flavoviridis and Ovophis okinavensis, which differ greatly in their biology. Sequencing of venom gland cDNA produced 104,830 transcripts. The Protobothrops transcriptome contained transcripts for 103 venom-related proteins, while the Ovophis transcriptome contained 95. In both, transcript abundances spanned six orders of magnitude. Mass spectrometry identified peptides from 100% of transcripts that occurred at higher than contaminant (e.g. human keratin) levels, including a number of proteins never before sequenced from snakes. These transcriptomes reveal fundamentally different envenomation strategies. Adult Protobothrops venom promotes hemorrhage, hypotension, incoagulable blood, and prey digestion, consistent with mammalian predation. Ovophis venom composition is less readily interpreted, owing to insufficient pharmacological data for venom serine and metalloproteases, which comprise more than 97.3% of Ovophis transcripts, but only 38.0% of Protobothrops transcripts. Ovophis venom apparently represents a hybrid strategy optimized for frogs and small mammals. This study illustrates the power of cDNA sequencing combined with MS profiling. The former quantifies transcript composition, allowing detection of novel proteins, but cannot indicate which proteins are actually secreted, as does MS. We show, for the first time, that transcript and peptide abundances are correlated. This means that MS can be used for quantitative, non-invasive venom profiling, which will be beneficial for studies of endangered species.

Synergistic roles of the proteasome and autophagy for mitochondrial maintenance and chronological lifespan in fission yeast

Abstract: Regulations of proliferation and quiescence in response to nutritional cues are important for medicine and basic biology. The fission yeast Schizosaccharomyces pombe serves as a model, owing to the shift of proliferating cells to the metabolically active quiescence (designate G0 phase hereafter) by responding to low nitrogen source. S. pombe G0 phase cells keep alive for months without growth and division. Nitrogen replenishment reinstates vegetative proliferation phase (designate VEG). Some 40 genes required for G0 maintenance were identified, but many more remain to be identified. We here show, using mutants, that the proteasome is required for maintaining G0 quiescence. Functional outcomes of proteasome in G0 and VEG phases appear to be distinct. Upon proteasome dysfunction, a number of antioxidant proteins and compounds responsive to ROS (reactive oxygen species) are produced. In addition, autophagy-mediated destruction of mitochondria occurs, which suppresses the loss of viability by eliminating ROS-generating mitochondria. These defensive responses are found in G0 but not in VEG, suggesting that the main function of proteasome in G0 phase homeostasis is to minimize ROS. Proteasome and autophagy are thus collaborative to support the lifespan of S. pombe G0 phase.

Metabolic profiling of the fission yeast S. pombe: quantification of compounds under different temperatures and genetic perturbation

Abstract: Metabolomics is a rapidly growing branch of post-genomic chemical biology. The fission yeast Schizosaccharomyces pombe is an excellent eukaryotic model organism. Although the entire S. pombegenome has been sequenced and detailed transcriptomic analyses were performed, little metabolic profiling has been done. Here we report the first global semi-quantitative analysis of the S. pombe metabolome using liquid chromatographyhigh-resolution mass spectrometry. Procedures to obtain metabolic compounds from S. pombe extracts were established. One hundred and twenty-three distinct metabolites were identified while approximately 1900 peaks from the ∼6000 observed were assigned. A software system (MZviewer) was developed to visualize semi-quantitative metabolome data using a dynamically generated scatter plot. We examined the metabolome of S. pombe cells exponentially grown in synthetic culture medium (EMM2) at two different temperatures, 26 °C and 36 °C. The profiles were similar except for varying amounts of certain amino acids and a significant increase in several compounds at 36 °C, such as trehalose (200-fold), glycerophosphoethanolamine (50-fold), arabitol (16-fold), ribulose (8-fold), and ophthalmic acid (5-fold). Reproducibility was demonstrated using a deletion mutant sib1Δ that lacked ferrichrome synthetase and showed no significant metabolic effects except the disappearance of the hexapeptide ferrichrome and the appearance of a putative dipeptide precursor. Taking advantage of the metabolic profile similarity at 26 °C and 36 °C, we analyzed the metabolome of a temperature-sensitive hcs1-143 mutant defective in the HMG-CoA synthase. As expected, HMG-CoA was decreased. In addition, extensive secondary metabolic effects, including a decrease in urea cycle intermediates and an increase in acetylated compounds, were observed. These findings confirm that S. pombe can be applied as an appropriate model to monitor metabolic responses to environmental conditions as well as genetic perturbations.

Coralsnake Venomics: Analyses of Venom Gland Transcriptomes and Proteomes of Six Brazilian Taxa

Abstract: Venom gland transcriptomes and proteomes of six Micrurus taxa (M. corallinus, M. lemniscatus carvalhoi, M. lemniscatus lemniscatus, M. paraensis, M. spixii spixii, and M. surinamensis) were investigated, providing the most comprehensive, quantitative data on Micrurus venom composition to date, and more than tripling the number of Micrurus venom protein sequences previously available. The six venomes differ dramatically. All are dominated by 2–6 toxin classes that account for 91–99% of the toxin transcripts. The M. s. spixii venome is compositionally the simplest. In it, three-finger toxins (3FTxs) and phospholipases A2 (PLA2s) comprise >99% of the toxin transcripts, which include only four additional toxin families at levels ≥0.1%. Micrurus l. lemniscatus venom is the most complex, with at least 17 toxin families. However, in each venome, multiple structural subclasses of 3FTXs and PLA2s are present. These almost certainly differ in pharmacology as well. All venoms also contain phospholipase B and vascular endothelial growth factors. Minor components (0.1–2.0%) are found in all venoms except that of M. s. spixii. Other toxin families are present in all six venoms at trace levels (<0.005%). Minor and trace venom components differ in each venom. Numerous novel toxin chemistries include 3FTxs with previously unknown 8- and 10-cysteine arrangements, resulting in new 3D structures and target specificities. 9-cysteine toxins raise the possibility of covalent, homodimeric 3FTxs or heterodimeric toxins with unknown pharmacologies. Probable muscarinic sequences may be reptile-specific homologs that promote hypotension via vascular mAChRs. The first complete sequences are presented for 3FTxs putatively responsible for liberating glutamate from rat brain synaptosomes. Micrurus C-type lectin-like proteins may have 6–9 cysteine residues and may be monomers, or homo- or heterodimers of unknown pharmacology. Novel KSPIs, 3× longer than any seen previously, appear to have arisen in three species by gene duplication and fusion. Four species have transcripts homologous to the nociceptive toxin, (MitTx) α-subunit, but all six species had homologs to the β-subunit. The first non-neurotoxic, non-catalytic elapid phospholipase A2s are reported. All are probably myonecrotic. Phylogenetic analysis indicates that the six taxa diverged 15–35 million years ago and that they split from their last common ancestor with Old World elapines nearly 55 million years ago. Given their early diversification, many cryptic micrurine taxa are anticipated.

MZmine 2: Modular framework for processing, visualizing, and analyzing mass spectrometry-based molecular profile data

Abstract: Mass spectrometry (MS) coupled with online separation methods is commonly applied for differential and quantitative profiling of biological samples in metabolomic as well as proteomic research. Such approaches are used for systems biology, functional genomics, and biomarker discovery, among others. An ongoing challenge of these molecular profiling approaches, however, is the development of better data processing methods. Here we introduce a new generation of a popular open-source data processing toolbox, MZmine 2. A key concept of the MZmine 2 software design is the strict separation of core functionality and data processing modules, with emphasis on easy usability and support for high-resolution spectra processing. Data processing modules take advantage of embedded visualization tools, allowing for immediate previews of parameter settings. Newly introduced functionality includes the identification of peaks using online databases, MSn data support, improved isotope pattern support, scatter plot visualization, and a new method for peak list alignment based on the random sample consensus (RANSAC) algorithm. The performance of the RANSAC alignment was evaluated using synthetic datasets as well as actual experimental data, and the results were compared to those obtained using other alignment algorithms. MZmine 2 is freely available under a GNU GPL license and can be obtained from the project website at: http://mzmine.sourceforge.net/ . The current version of MZmine 2 is suitable for processing large batches of data and has been applied to both targeted and non-targeted metabolomic analyses.

MetaboAnalyst 4.0: towards more transparent and integrative metabolomics analysis.

Abstract: We present a new update to MetaboAnalyst (version 4.0) for comprehensive metabolomic data analysis, interpretation, and integration with other omics data. Since the last major update in 2015, MetaboAnalyst has continued to evolve based on user feedback and technological advancements in the field. For this year's update, four new key features have been added to MetaboAnalyst 4.0, including: (1) real-time R command tracking and display coupled with the release of a companion MetaboAnalystR package; (2) a MS Peaks to Pathways module for prediction of pathway activity from untargeted mass spectral data using the mummichog algorithm; (3) a Biomarker Meta-analysis module for robust biomarker identification through the combination of multiple metabolomic datasets and (4) a Network Explorer module for integrative analysis of metabolomics, metagenomics, and/or transcriptomics data. The user interface of MetaboAnalyst 4.0 has been reengineered to provide a more modern look and feel, as well as to give more space and flexibility to introduce new functions. The underlying knowledgebases (compound libraries, metabolite sets, and metabolic pathways) have also been updated based on the latest data from the Human Metabolome Database (HMDB). A Docker image of MetaboAnalyst is also available to facilitate download and local installation of MetaboAnalyst. MetaboAnalyst 4.0 is freely available at http://metaboanalyst.ca.

MetaboAnalyst 3.0—making metabolomics more meaningful

Abstract: MetaboAnalyst (www.metaboanalyst.ca) is a web server designed to permit comprehensive metabolomic data analysis, visualization and interpretation. It supports a wide range of complex statistical calculations and high quality graphical rendering functions that require significant computational resources. First introduced in 2009, MetaboAnalyst has experienced more than a 50X growth in user traffic (>50 000 jobs processed each month). In order to keep up with the rapidly increasing computational demands and a growing number of requests to support translational and systems biology applications, we performed a substantial rewrite and major feature upgrade of the server. The result is MetaboAnalyst 3.0. By completely re-implementing the MetaboAnalyst suite using the latest web framework technologies, we have been able substantially improve its performance, capacity and user interactivity. Three new modules have also been added including: (i) a module for biomarker analysis based on the calculation of receiver operating characteristic curves; (ii) a module for sample size estimation and power analysis for improved planning of metabolomics studies and (iii) a module to support integrative pathway analysis for both genes and metabolites. In addition, popular features found in existing modules have been significantly enhanced by upgrading the graphical output, expanding the compound libraries and by adding support for more diverse organisms.

mTOR Signaling in Growth, Metabolism, and Disease

Abstract: The mechanistic target of rapamycin (mTOR) coordinates eukaryotic cell growth and metabolism with environmental inputs, including nutrients and growth factors. Extensive research over the past two decades has established a central role for mTOR in regulating many fundamental cell processes, from protein synthesis to autophagy, and deregulated mTOR signaling is implicated in the progression of cancer and diabetes, as well as the aging process. Here, we review recent advances in our understanding of mTOR function, regulation, and importance in mammalian physiology. We also highlight how the mTOR signaling network contributes to human disease and discuss the current and future prospects for therapeutically targeting mTOR in the clinic.

The re-emergence of natural products for drug discovery in the genomics era

Abstract: Natural products have been a rich source of compounds for drug discovery. However, their use has diminished in the past two decades, in part because of technical barriers to screening natural products in high-throughput assays against molecular targets. Here, we review strategies for natural product screening that harness the recent technical advances that have reduced these barriers. We also assess the use of genomic and metabolomic approaches to augment traditional methods of studying natural products, and highlight recent examples of natural products in antimicrobial drug discovery and as inhibitors of protein-protein interactions. The growing appreciation of functional assays and phenotypic screens may further contribute to a revival of interest in natural products for drug discovery.