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Nicholas J W Rattray  - - - 
Top co-authors See all
Richard Caprioli

252 shared publications

Mass Spectrometry Research Center; Vanderbilt University; Nashville Tennessee USA

Gary Siuzdak

244 shared publications

The Scripps Research Institute, Scripps Center for Metabolomics and Mass Spectrometry, 10550 North Torrey Pines Road, La Jolla, CA 92037, USA;(B.W.);(A.P.),(L.T.H.),(G.S.)

John P. A. Ioannidis

106 shared publications

Stanford University, USA

Benedikt Warth

81 shared publications

The Scripps Research Institute, Scripps Center for Metabolomics and Mass Spectrometry, 10550 North Torrey Pines Road, La Jolla, CA 92037, USA;(B.W.);(A.P.),(L.T.H.),(G.S.)

Rima Kaddurah-Daouk

48 shared publications

Department of Medicine and the Duke Institute for Brain Sciences, Duke University

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Publication Record
Distribution of Articles published per year 
(2017 - 2019)
Total number of journals
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9
 
Publications See all
Article 0 Reads 0 Citations Palbociclib and Fulvestrant Act in Synergy to Modulate Central Carbon Metabolism in Breast Cancer Cells Benedikt Warth, Amelia Palermo, Nicholas J.W. Rattray, Natha... Published: 02 January 2019
Metabolites, doi: 10.3390/metabo9010007
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The aims of this study were to determine whether combination chemotherapeutics exhibit a synergistic effect on breast cancer cell metabolism. Palbociclib, is a selective inhibitor of cyclin-dependent kinases 4 and 6, and when patients are treated in combination with fulvestrant, an estrogen receptor antagonist, they have improved progression-free survival. The mechanisms for this survival advantage are not known. Therefore, we analyzed metabolic and transcriptomic changes in MCF-7 cells following single and combination chemotherapy to determine whether selective metabolic pathways are targeted during these different modes of treatment. Individually, the drugs caused metabolic disruption to the same metabolic pathways, however fulvestrant additionally attenuated the pentose phosphate pathway and the production of important coenzymes. A comprehensive effect was observed when the drugs were applied together, confirming the combinatory therapy’s synergism in the cell model. This study also highlights the power of merging high-dimensional datasets to unravel mechanisms involved in cancer metabolism and therapy.
Article 0 Reads 4 Citations An automated Design-Build-Test-Learn pipeline for enhanced microbial production of fine chemicals Pablo Carbonell, Adrian J. Jervis, Christopher J. Robinson, ... Published: 08 June 2018
Communications Biology, doi: 10.1038/s42003-018-0076-9
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The microbial production of fine chemicals provides a promising biosustainable manufacturing solution that has led to the successful production of a growing catalog of natural products and high-value chemicals. However, development at industrial levels has been hindered by the large resource investments required. Here we present an integrated Design–Build-Test–Learn (DBTL) pipeline for the discovery and optimization of biosynthetic pathways, which is designed to be compound agnostic and automated throughout. We initially applied the pipeline for the production of the flavonoid (2S)-pinocembrin in Escherichia coli, to demonstrate rapid iterative DBTL cycling with automation at every stage. In this case, application of two DBTL cycles successfully established a production pathway improved by 500-fold, with competitive titers up to 88 mg L−1. The further application of the pipeline to optimize an alkaloids pathway demonstrates how it could facilitate the rapid optimization of microbial strains for production of any chemical compound of interest.
Article 0 Reads 0 Citations Yale School of Public Health Symposium on tissue imaging mass spectrometry: illuminating phenotypic heterogeneity and dr... Georgia Charkoftaki, Nicholas J. W. Rattray, Per E. Andren, ... Published: 27 February 2018
Human Genomics, doi: 10.1186/s40246-018-0142-x
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Article 3 Reads 1 Citation Re-engineering and evaluation of anti-DNA autoantibody 3E10 for therapeutic applications Zahra Rattray, Valentina Dubljevic, Nicholas J.W. Rattray, D... Published: 01 February 2018
Biochemical and Biophysical Research Communications, doi: 10.1016/j.bbrc.2018.01.139
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Article 4 Reads 3 Citations Beyond genomics: understanding exposotypes through metabolomics Nicholas J. W. Rattray, Nicole C. DeZiel, Joshua D. Wallach,... Published: 26 January 2018
Human Genomics, doi: 10.1186/s40246-018-0134-x
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Over the past 20 years, advances in genomic technology have enabled unparalleled access to the information contained within the human genome. However, the multiple genetic variants associated with various diseases typically account for only a small fraction of the disease risk. This may be due to the multifactorial nature of disease mechanisms, the strong impact of the environment, and the complexity of gene-environment interactions. Metabolomics is the quantification of small molecules produced by metabolic processes within a biological sample. Metabolomics datasets contain a wealth of information that reflect the disease state and are consequent to both genetic variation and environment. Thus, metabolomics is being widely adopted for epidemiologic research to identify disease risk traits. In this review, we discuss the evolution and challenges of metabolomics in epidemiologic research, particularly for assessing environmental exposures and providing insights into gene-environment interactions, and mechanism of biological impact. Metabolomics can be used to measure the complex global modulating effect that an exposure event has on an individual phenotype. Combining information derived from all levels of protein synthesis and subsequent enzymatic action on metabolite production can reveal the individual exposotype. We discuss some of the methodological and statistical challenges in dealing with this type of high-dimensional data, such as the impact of study design, analytical biases, and biological variance. We show examples of disease risk inference from metabolic traits using metabolome-wide association studies. We also evaluate how these studies may drive precision medicine approaches, and pharmacogenomics, which have up to now been inefficient. Finally, we discuss how to promote transparency and open science to improve reproducibility and credibility in metabolomics. Comparison of exposotypes at the human population level may help understanding how environmental exposures affect biology at the systems level to determine cause, effect, and susceptibilities. Juxtaposition and integration of genomics and metabolomics information may offer additional insights. Clinical utility of this information for single individuals and populations has yet to be routinely demonstrated, but hopefully, recent advances to improve the robustness of large-scale metabolomics will facilitate clinical translation.
Article 0 Reads 0 Citations Metabolomics guided pathway analysis reveals link between cancer metastasis, cholesterol sulfate, and phospholipids Caroline H. Johnson, Antonio F. Santidrian, Sarah E. Leboeuf... Published: 31 October 2017
Cancer & Metabolism, doi: 10.1186/s40170-017-0171-2
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Cancer cells that enter the metastatic cascade require traits that allow them to survive within the circulation and colonize distant organ sites. As disseminating cancer cells adapt to their changing microenvironments, they also modify their metabolism and metabolite production. A mouse xenograft model of spontaneous tumor metastasis was used to determine the metabolic rewiring that occurs between primary cancers and their metastases. An “autonomous” mass spectrometry-based untargeted metabolomic workflow with integrative metabolic pathway analysis revealed a number of differentially regulated metabolites in primary mammary fat pad (MFP) tumors compared to microdissected paired lung metastases. The study was further extended to analyze metabolites in paired normal tissues which determined the potential influence of metabolites from the microenvironment. Metabolomic analysis revealed that multiple metabolites were increased in metastases, including cholesterol sulfate and phospholipids (phosphatidylglycerols and phosphatidylethanolamine). Metabolite analysis of normal lung tissue in the mouse model also revealed increased levels of these metabolites compared to tissues from normal MFP and primary MFP tumors, indicating potential extracellular uptake by cancer cells in lung metastases. These results indicate a potential functional importance of cholesterol sulfate and phospholipids in propagating metastasis. In addition, metabolites involved in DNA/RNA synthesis and the TCA cycle were decreased in lung metastases compared to primary MFP tumors. Using an integrated metabolomic workflow, this study identified a link between cholesterol sulfate and phospholipids, metabolic characteristics of the metastatic niche, and the capacity of tumor cells to colonize distant sites.
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