Monitoring casbene synthase in Jatropha curcas tissues using targeted proteomics.

BACKGROUND: Casbene synthase (CS) is responsible for the first committed step in the biosynthesis of phorbol esters (PE) in the Euphorbiaceae. PE are abundant in the seeds of the biofuel crop Jatropha curcas and its toxicity precludes the use of the protein-rich cake obtained after oil extraction as an animal feed and the toxicity of the fumes derived from burning PE containing biofuel is also a matter of concern. This toxicity is a major hindrance to exploit the potential of this crop as a source of raw material to produce biodiesel. For this reason, the current research on J. curcas is mainly focused on the understanding of the biosynthesis and site of synthesis of PE, as an avenue for the development of genotypes unable to synthesize PE in its seeds. RESULTS: Here, we present targeted proteomics assays (SRM and PRM) to detect and quantify CS in leaves, endosperm, and roots of two J. curcas genotypes with contrasting levels of PE. These assays were based on the use of reference isotopic labeled synthetic peptides (ILSP) predicted from 12 gene models of CS from the J. curcas genome. CONCLUSION: Our targeted proteomics methods were able to detect and quantify, for the first time, CS gene products and demonstrate the distribution of CS isoforms only in roots from J. curcas genotypes with a high and low concentration of PE. These methods can be expanded to monitor CS, at the protein level, in different tissues and genotypes of J. curcas.

Validation of an analytical method for the determination of the main ayahuasca active compounds and application to real ayahuasca samples from Brazil.

Ayahuasca is a brew prepared from the water decoction of two Amazonian plants, which is legally used for religious, cultural or therapeutic activities. The potential use of ayahuasca as a natural or phytotherapeutic drug is directly linked to the action of its active compounds and their connection with the therapeutic efficacy of the beverage. In this context, the aim of the present study was to establish a selective, sensitive and reproducible analytical method for the quantification of the main active ayahuasca compounds. Thirty-eight samples from the state of São Paulo, Brazil, were analyzed and the simultaneous quantifications of N,N-dimethyltryptamine (DMT), tetrahydroharmine (THH), harmine (HME) and harmaline (HML) were performed. This study enabled the development of a fast validated analytical method with minimal matrix interference and high reproducibility for the tracing of active ayahuasca compound concentrations for the first time. This method is important as an auxiliary tool for the study of active compound effects in biological responses using different multi-omic platforms.

Targeted Mass Spectrometry of S100 Proteins.

The S100 protein family has attracted great interest in the field of biomarker research, and a growing number of studies reveal dysregulation of many of the 21 S100 protein isoforms in various human diseases. In cancer, S100 protein expression has been associated with tumor growth, progression, and response to treatment. Some S100 proteins are also considered candidate therapeutic targets. From an analytical perspective, multiplexed analysis of the family-wide S100 protein expression is challenging due to their relatively small size and high-sequence identity. Here we describe a mass spectrometry method using selected reaction monitoring which enables the targeted, multiplexed detection and quantitation of the entire S100 protein family in cell lines and tissue samples.

A Selected Reaction Monitoring Mass Spectrometry Protocol for Validation of Proteomic Biomarker Candidates in Studies of Psychiatric Disorders.

Most biomarker candidates arising from proteomic studies of psychiatric disorders have not progressed for use in clinical studies due to insufficient validation steps. Here we describe a selective reaction monitoring mass spectrometry (SRM-MS) approach that could be used as a follow-up validation tool of proteins identified in blood serum or plasma. This protocol specifically covers the stages of peptide selection and optimization. The increasing application of SRM-MS should enable fast, sensitive, and robust methods with the potential for use in clinical studies involving sampling of serum or plasma. Understanding the molecular mechanisms and identifying potential biomarkers for risk assessment, diagnosis, prognosis, and prediction of drug response goes toward the implementation of translational medicine strategies for improved treatment of patients with psychiatric disorders and other debilitating diseases.

Mass Spectrometry-Based Approaches to Understand the Molecular Basis of Memory.

The central nervous system is responsible for an array of cognitive functions such as memory, learning, language, and attention. These processes tend to take place in distinct brain regions; yet, they need to be integrated to give rise to adaptive or meaningful behavior. Since cognitive processes result from underlying cellular and molecular changes, genomics and transcriptomics assays have been applied to human and animal models to understand such events. Nevertheless, genes and RNAs are not the end products of most biological functions. In order to gain further insights toward the understanding of brain processes, the field of proteomics has been of increasing importance in the past years. Advancements in liquid chromatography-tandem mass spectrometry (LC-MS/MS) have enabled the identification and quantification of thousands of proteins with high accuracy and sensitivity, fostering a revolution in the neurosciences. Herein, we review the molecular bases of explicit memory in the hippocampus. We outline the principles of mass spectrometry (MS)-based proteomics, highlighting the use of this analytical tool to study memory formation. In addition, we discuss MS-based targeted approaches as the future of protein analysis.

A targeted proteomic strategy for the measurement of oral cancer candidate biomarkers in human saliva.

Head and neck cancers, including oral squamous cell carcinoma (OSCC), are the sixth most common malignancy in the world and are characterized by poor prognosis and a low survival rate. Saliva is oral fluid with intimate contact with OSCC. Besides non-invasive, simple, and rapid to collect, saliva is a potential source of biomarkers. In this study, we build an SRM assay that targets fourteen OSCC candidate biomarker proteins, which were evaluated in a set of clinically-derived saliva samples. Using Skyline software package, we demonstrated a statistically significant higher abundance of the C1R, LCN2, SLPI, FAM49B, TAGLN2, CFB, C3, C4B, LRG1, SERPINA1 candidate biomarkers in the saliva of OSCC patients. Furthermore, our study also demonstrated that CFB, C3, C4B, SERPINA1 and LRG1 are associated with the risk of developing OSCC. Overall, this study successfully used targeted proteomics to measure in saliva a panel of biomarker candidates for OSCC.

Open source libraries and frameworks for mass spectrometry based proteomics: a developer's perspective.

Data processing, management and visualization are central and critical components of a state of the art high-throughput mass spectrometry (MS)-based proteomics experiment, and are often some of the most time-consuming steps, especially for labs without much bioinformatics support. The growing interest in the field of proteomics has triggered an increase in the development of new software libraries, including freely available and open-source software. From database search analysis to post-processing of the identification results, even though the objectives of these libraries and packages can vary significantly, they usually share a number of features. Common use cases include the handling of protein and peptide sequences, the parsing of results from various proteomics search engines output files, and the visualization of MS-related information (including mass spectra and chromatograms). In this review, we provide an overview of the existing software libraries, open-source frameworks and also, we give information on some of the freely available applications which make use of them. This article is part of a Special Issue entitled: Computational Proteomics in the Post-Identification Era. Guest Editors: Martin Eisenacher and Christian Stephan.

Anxiety-like effects of meta-chlorophenylpiperazine in paradoxically sleep-deprived mice.

Chlorophenylpiperazines (CPP) are psychotropic drugs used in nightclub parties and are frequently used in a state of sleep deprivation, a condition which can potentiate the effects of psychoactive drugs. This study aimed to investigate the effects of sleep deprivation and sleep rebound (RB) on anxiety-like measures in mCPP-treated mice using the open field test. We first optimized our procedure by performing dose-effect curves and examining different pretreatment times in naïve male Swiss mice. Subsequently, a separate cohort of mice underwent paradoxical sleep deprivation (PSD) for 24 or 48h. In the last experiment, immediately after the 24h-PSD period, mice received an injection of saline or mCPP, but their general activity was quantified in the open field only after the RB period (24 or 48h). The dose of 5mgmL(-1) of mCPP was the most effective at decreasing rearing behavior, with peak effects 15min after injection. PSD decreased locomotion and rearing behaviors, thereby inhibiting a further impairment induced by mCPP. Plasma concentrations of mCPP were significantly higher in PSD 48h animals compared to the non-PSD control group. Twenty-four hours of RB combined with mCPP administration produced a slight reduction in locomotion. Our results show that mCPP was able to significantly change the behavior of naïve, PSD, and RB mice. When combined with sleep deprivation, there was a higher availability of drug in plasma levels. Taken together, our results suggest that sleep loss can enhance the behavioral effects of the potent psychoactive drug, mCPP, even after a period of rebound sleep.