The preferred source of carbon and energy for yeast cells is glucose. When yeast cells are grown in liquid cultures, they metabolize glucose predominantly by glycolysis, releasing ethanol in the medium. When glucose becomes limiting, the cells enter diauxic shift characterized by decreased growth rate and by switching metabolism from glycolysis to aerobic utilization of ethanol. When ethanol is depleted from the medium, cells enter quiescent or stationary phase G(0). Cells in diauxic shift and stationary phase are stressed by the lack of nutrients and by accumulation of toxic metabolites, primarily from the oxidative metabolism, and are differentiated in ways that allow them to maintain viability for extended periods of time. The transition of yeast cells from exponential phase to quiescence is regulated by protein kinase A, TOR, Snf1p, and Rim15p pathways that signal changes in availability of nutrients, converge on transcriptional factors Msn2p, Msn4p, and Gis1p, and elicit extensive reprogramming of the transcription machinery. However, the events in transcriptional regulation during diauxic shift and quiescence are incompletely understood. Because cells from multicellular eukaryotic organisms spend most of their life in G(0) phase, understanding transcriptional regulation in quiescence will inform other fields, such as cancer, development, and aging.

During nearly a decade of research dedicated to the study of sphingosine signaling pathways, we identified sphingosine-1-phosphate lyase (S1PL) as a drug target for the treatment of autoimmune disorders. S1PL catalyzes the irreversible decomposition of sphingosine-1-phosphate (S1P) by a retro-aldol fragmentation that yields hexadecanaldehyde and phosphoethanolamine. Genetic models demonstrated that mice expressing reduced S1PL activity had decreased numbers of circulating lymphocytes due to altered lymphocyte trafficking, which prevented disease development in multiple models of autoimmune disease. Mechanistic studies of lymphoid tissue following oral administration of 2-acetyl-4(5)-(1(R),2(S),3(R),4-tetrahydroxybutyl)-imidazole (THI) 3 showed a clear relationship between reduced lyase activity, elevated S1P levels, and lower levels of circulating lymphocytes. Our internal medicinal chemistry efforts discovered potent analogues of 3 bearing heterocycles as chemical equivalents of the pendant carbonyl present in the parent structure. Reduction of S1PL activity by oral administration of these analogues recapitulated the phenotype of mice with genetically reduced S1PL expression.

The quantitative capabilities of a linear ion trap high-resolution mass spectrometer (LTQ-Orbitrap) were investigated using full scan mode bracketing the m/z range of the ions of interest and utilizing a mass resolution (mass/FWHM) of 15000. Extracted ion chromatograms using a mass window of +/-5-10 mmicro centering on the theoretical m/z of each analyte were generated and used for quantitation. The quantitative performance of the LTQ-Orbitrap was compared with that of a triple quadrupole (API 4000) operating using selected reaction monitoring (SRM) detection. Comparable assay precision, accuracy, linearity and sensitivity were observed for both approaches. The concentrations of actual study samples from 15 Merck drug candidates reported by the two methods were statistically equivalent. Unlike SRM being a tandem mass spectrometric (MS/MS)-based detection method, a high resolution mass spectrometer operated in full scan does not need MS/MS optimization. This approach not only provides quantitative results for compounds of interest, but also will afford data on other analytes present in the sample. An example of the identification of a major circulating metabolite for a preclinical development study is demonstrated.

Throughput for drug metabolite identification studies has been increased significantly by the combined use of accurate mass liquid chromatography/tandem mass spectrometry (LC/MS/MS) data on a quadrupole time-of-flight (QTOF) system and targeted data analysis procedures. Employed in concert, these tools have led to the implementation of a semi-automated high-throughput metabolite identification strategy that has been incorporated successfully into lead optimization efforts in drug discovery. The availability of elemental composition data on precursor and all fragment ions in each spectrum has greatly enhanced confidence in ion structure assignments, while computer-based algorithms for defining sites of biotransformation based upon mass shifts of diagnostic fragment ions have facilitated identification of positions of metabolic transformation in drug candidates. Adoption of this technology as the 'first-line' approach for in vitro metabolite profiling has resulted in the analysis of as many as 21 new chemical entities on one day from diverse structural classes and therapeutic programs.

Background Synthetic data may provide a solution to researchers who wish to generate and share data in support of precision healthcare. Recent advances in data synthesis enable the creation and analysis of synthetic derivatives as if they were the original data; this process has significant advantages over data deidentification. Objectives To assess a big-data platform with data-synthesizing capabilities (MDClone Ltd., Beer Sheva, Israel) for its ability to produce data that can be used for research purposes while obviating privacy and confidentiality concerns. Methods We explored three use cases and tested the robustness of synthetic data by comparing the results of analyses using synthetic derivatives to analyses using the original data using traditional statistics, machine learning approaches, and spatial representations of the data. We designed these use cases with the purpose of conducting analyses at the observation level (Use Case 1), patient cohorts (Use Case 2), and population-level data (Use Case 3). Results For each use case, the results of the analyses were sufficiently statistically similar (P > 0.05) between the synthetic derivative and the real data to draw the same conclusions. Discussion and conclusion This article presents the results of each use case and outlines key considerations for the use of synthetic data, examining their role in clinical research for faster insights and improved data sharing in support of precision healthcare.