Functional Analysis of OMICs Data and Small Molecule Compounds in an Integrated “Knowledge-Based” Platform

Nikolsky, Yuri; Kirillov, Eugene; Zuev, Roman; Rakhmatulin, Eugene; Nikolskaya, Tatiana

doi:10.1007/978-1-60761-175-2_10

Cited by 82 publications

(81 citation statements)

References 13 publications

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“…For genes interrogated by multiple probe sets, a single expression value was calculated using the maximum signal reported across redundant probe sets. Genes associated with steroid metabolism were identified by annotations curated from Entrez Gene, Gene Ontology, and GeneGO Metacore terms (18). For analysis of cAMP target genes, the PKA, CREB, and cAMP pathways were curated for known direct and indirect target genes.…”

Section: Methodsmentioning

confidence: 99%

Deregulated Hepatic Metabolism Exacerbates Impaired Testosterone Production in Mrp4-deficient Mice

Morgan

Cheepala

Wang

et al. 2012

Journal of Biological Chemistry

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Background:The role of the ABC transporter, Mrp4, in regulating Leydig cell testosterone synthesis is unknown. Results: In a murine genetic model the absence of Mrp4 impairs testosterone production by disrupting cAMP signaling. Conclusion: Mrp4 absence disrupts Leydig cell cAMP homeostasis by impairing luteinizing hormone-activated testosterone production. Significance: These findings reveal a mechanism for unexplained side effects of altered androgen production by therapeutics disrupting Mrp4 function.

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Section: Methodsmentioning

confidence: 99%

Deregulated Hepatic Metabolism Exacerbates Impaired Testosterone Production in Mrp4-deficient Mice

Morgan

Cheepala

Wang

et al. 2012

Journal of Biological Chemistry

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“…The functional analysis of the data were based on MetaCore's proprietary manually curated data base of protein-protein and protein-DNA interactions, transcription factors, signaling, and metabolic pathways. Overrepresented functional categories were identified as described (31).…”

Section: Methodsmentioning

confidence: 99%

“…The "transcriptional regulation" algorithm starts with a small sub-network of differentially expressed genes from the initial list and adds the "responsible" transcription factors. The "transcription-factor target modeling" algorithm starts with list of transcription factors deduced from the initial dataset and calculates the shortest paths to their targets (31). The networks were generated for all five tissues using unions of differentially expressed genes (corrected p Ͻ 0.05, moderated t test).…”

Section: Methodsmentioning

confidence: 99%

“…It calculates relative connectivity (number of interactions) of individual genes within the dataset compared with the entire data base based on the comprehensive collection of their known interactions (31). A gene was considered overconnected if it had more direct interactions with the genes of interest than it would be expected by chance (32).…”

Section: Methodsmentioning

confidence: 99%

“…A gene was considered overconnected if it had more direct interactions with the genes of interest than it would be expected by chance (32). The related statistics are described in detail elsewhere (31). Shortly, to assess significantly over-or under-connected proteins in the list, Interactome analysis evaluates relative connectivity of proteins based on the assumption that the most critical protein in a given dataset has more connections within the dataset than expected at random.…”

Section: Methodsmentioning

confidence: 99%

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Interorgan Coordination of the Murine Adaptive Response to Fasting

Hakvoort

Moerland

Frijters

et al. 2011

Journal of Biological Chemistry

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Starvation elicits a complex adaptive response in an organism.No information on transcriptional regulation of metabolic adaptations is available. We, therefore, studied the gene expression profiles of brain, small intestine, kidney, liver, and skeletal muscle in mice that were subjected to 0 -72 h of fasting. Functional-category enrichment, text mining, and network analyses were employed to scrutinize the overall adaptation, aiming to identify responsive pathways, processes, and networks, and their regulation. The observed transcriptomics response did not follow the accepted "carbohydrate-lipid-protein" succession of expenditure of energy substrates. Instead, these processes were activated simultaneously in different organs during the entire period. The most prominent changes occurred in lipid and steroid metabolism, especially in the liver and kidney. They were accompanied by suppression of the immune response and cell turnover, particularly in the small intestine, and by increased proteolysis in the muscle. The brain was extremely well protected from the sequels of starvation. 60% of the identified overconnected transcription factors were organ-specific, 6% were common for 4 organs, with nuclear receptors as protagonists, accounting for almost 40% of all transcriptional regulators during fasting. The common transcription factors were PPAR␣, HNF4␣, GCR␣, AR (androgen receptor), SREBP1 and -2, FOXOs, EGR1, c-JUN, c-MYC, SP1, YY1, and ETS1. Our data strongly suggest that the control of metabolism in four metabolically active organs is exerted by transcription factors that are activated by nutrient signals and serves, at least partly, to prevent irreversible brain damage.Adapting to starvation requires an interorgan integration of the activity of metabolic pathways to protect the body from an irreversible loss of resources (1, 2), but how the organism integrates these reactions remains largely unknown. Numerous studies on humans, who fasted for 3-6 weeks, have shown that glycogen stores are depleted within a day (3). The decline in circulating glucose and insulin during the next few days (4) induces a transient increase in plasma (essential) amino acids and a concomitant decline in plasma alanine levels due to an increased hepatic extraction for gluconeogenesis (5, 6). Muscle catabolism is a major source of amino acids in this phase. When fasting is continued, muscle protein catabolism declines, and hepatic uptake of amino acids decreases, which is reflected in a decline of endogenous glucose production (6) and urinary nitrogen excretion (4, 7). Lipid catabolism and the (hepatic) production of ketone bodies also increases rapidly and is quantitatively similar after 3 days and 5-6 weeks of starvation (8), but plasma levels increase only gradually to plateau after 4 weeks (4, 9). The associated increase in urinary ketone body (organic-acid) excretion requires a compensatory increase in ammonia production and urinary excretion (4, 7, 10), which is met by an increased renal amino acid uptake and gluconeogenesis (5, 6)...

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Overview of Metabolomics Basics

Schaefer

2012

Predictive Approaches in Drug Discovery and Development

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Functional Analysis of OMICs Data and Small Molecule Compounds in an Integrated “Knowledge-Based” Platform

Cited by 82 publications

References 13 publications

Deregulated Hepatic Metabolism Exacerbates Impaired Testosterone Production in Mrp4-deficient Mice

Deregulated Hepatic Metabolism Exacerbates Impaired Testosterone Production in Mrp4-deficient Mice

Interorgan Coordination of the Murine Adaptive Response to Fasting

Overview of Metabolomics Basics

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