Toxicity mechanisms identification via gene set enrichment analysis of time-series toxicogenomics data: Impact of time and concentration

Environmental Science and Technology

Volumn 49, Issue 7, 2015, Pages 4618-4626

  Gao, Ce ^a   Weisman, David ^b   Lan, Jiaqi ^a   Gou, Na ^a   Gu, April Z ^a  

^a Northeastern University   (United States)

^b UNIVERSITY OF MASSACHUSETTS BOSTON   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CHEMICAL ANALYSIS; DATA ACQUISITION; DYNAMIC RESPONSE; DYNAMICS; GENE EXPRESSION; GENES; INDICATORS (CHEMICAL); MOBILE SECURITY; PRINCIPAL COMPONENT ANALYSIS; TIME SERIES; TOXICITY;

CELLULAR RESPONSE; CHEMICAL SPECIFIC; GENE EXPRESSION PROFILES; GENE SET ENRICHMENT ANALYSIS; PRINCIPAL COMPONENTS ANALYSIS; TEMPORAL VARIATION; TOXICITY ASSESSMENT; TOXICITY MECHANISMS;

TIME SERIES ANALYSIS;

HYDROGEN PEROXIDE; LEAD NITRATE; MITOMYCIN; ANTINEOPLASTIC ANTIBIOTIC; DANGEROUS GOODS; LEAD; NITRIC ACID DERIVATIVE; POLLUTANT; TOPICAL ANTIINFECTIVE AGENT; TRANSCRIPTOME;

BIOASSAY; CONCENTRATION (COMPOSITION); CORRELATION; GENE EXPRESSION; GENOME; TIME SERIES; TOXICITY;

ARTICLE; BIOASSAY; CLINICAL ASSESSMENT; CLINICAL EVALUATION; COMMON PRINCIPAL COMPONENTS ANALYSIS; CONCENTRATION RESPONSE; CONTROLLED STUDY; DATA ANALYSIS; DOSE RESPONSE; ESCHERICHIA COLI; GENE EXPRESSION; GENE EXPRESSION PROFILING; GENE IDENTIFICATION; GENE SET ENRICHMENT ANALYSIS; GENETIC ANALYSIS; GENETIC PARAMETERS; GENETIC VARIABILITY; GENOMICS; GENOTOXICITY; INFORMATION PROCESSING; NONHUMAN; OUTCOME ASSESSMENT; REPORTER GENE; SCORING SYSTEM; SIGNAL TRANSDUCTION; STRESS; TIME SERIES ANALYSIS; TOXICITY TESTING; TOXICOGENOMICS TIME SERIES DATA; TRANSCRIPTIONAL EFFECT LEVEL INDEX; WHOLE CELL; DANGEROUS GOODS; DRUG EFFECTS; ESCHERICHIA COLI K 12; GENE EXPRESSION REGULATION; GENETICS; METABOLISM; MICROARRAY ANALYSIS; POLLUTANT; PRINCIPAL COMPONENT ANALYSIS; PROCEDURES; TOXICITY; TOXICOGENETICS;

ANTI-INFECTIVE AGENTS, LOCAL; ANTIBIOTICS, ANTINEOPLASTIC; DOSE-RESPONSE RELATIONSHIP, DRUG; ENVIRONMENTAL POLLUTANTS; ESCHERICHIA COLI K12; GENE EXPRESSION REGULATION; HAZARDOUS SUBSTANCES; HYDROGEN PEROXIDE; LEAD; MICROARRAY ANALYSIS; MITOMYCIN; NITRATES; PRINCIPAL COMPONENT ANALYSIS; TOXICOGENETICS; TRANSCRIPTOME;

EID: 84926444288     PISSN: 0013936X     EISSN: 15205851     Source Type: Journal    
DOI: 10.1021/es505199f     Document Type: Article

References (44)

1. Krewski, D.; Acosta, D., Jr; Andersen, M.; Anderson, H.; Bailar, J. C., III; Boekelheide, K.; Brent, R.; Charnley, G.; Cheung, V. G.; Green, S., Jr Toxicity testing in the 21st century: a vision and a strategy J. Toxicol. Environ. Health, B 2010, 13 (2-4) 51-138
2. Hayes, K. R.; Bradfield, C. A. Advances in toxicogenomics Chem. Res. Toxicol. 2005, 18 (3) 403-414
3. Gao, C.; Weisman, D.; Gou, N.; Ilyin, V.; Gu, A. Z. Analyzing high dimensional toxicogenomic data using consensus clustering Environ. Sci. Technol. 2012, 46 (15) 8413-8421
4. Bar-Joseph, Z. Analyzing time series gene expression data Bioinformatics 2004, 20 (16) 2493-2503
5. Bar-Joseph, Z.; Gitter, A.; Simon, I. Studying and modelling dynamic biological processes using time-series gene expression data Nat. Rev. Genet. 2012, 13 (8) 552-564
6. National Research Council (U.S.) Committee on Applications of Toxicogenomic Technologies to Predictive Toxicology. Applications of Toxicogenomic Technologies to Predictive Toxicology and Risk Assessment; National Academies Press: Washington, D.C., 2007.
7. Jayapal, M. Integration of next-generation sequencing based multi-omics approaches in toxicogenomics Front. Genet. 2012, 3, 88
8. Melamed, S.; Elad, T.; Belkin, S. Microbial sensor cell arrays Curr. Opin. Biotechnol. 2012, 23 (1) 2-8
9. Timothy, S.; OConnor, F.; Lan, J.; North, M.; Loguinov, A.; Zhang, L.; Smith, M. T.; Gu, A. Z.; Vulpe, C. Genome-wide functional and stress response profiling reveals toxic mechanism and genes required for tolerance to benzo[ a ]pyrene in S. cerevisiae Front. Genet. 2012, 3, 316
10. Gou, N.; Gu, A. Z. A new Transcriptional Effect Level Index (TELI) for toxicogenomics-based toxicity assessment Environ. Sci. Technol. 2011, 45 (12) 5410-5417
11. Schliep, A.; Costa, I. G.; Steinhoff, C.; Schonhuth, A. Analyzing gene expression time-courses IEEE/ACM Trans. Comput. Biol. Bioinf. 2005, 2 (3) 179-193
12. Huang, D. W.; Sherman, B. T.; Lempicki, R. A. Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists Nucleic Acids Res. 2009, 37 (1) 1-13
13. Khatri, P.; Sirota, M.; Butte, A. J. Ten years of pathway analysis: current approaches and outstanding challenges PLoS Comput. Biol. 2012, 8 (2) e1002375
14. Mootha, V. K.; Lindgren, C. M.; Eriksson, K.-F.; Subramanian, A.; Sihag, S.; Lehar, J.; Puigserver, P.; Carlsson, E.; Ridderstråle, M.; Laurila, E.; Houstis, N.; Daly, M. J.; Patterson, N.; Mesirov, J. P.; Golub, T. R.; Tamayo, P.; Spiegelman, B.; Lander, E. S.; Hirschhorn, J. N.; Altshuler, D.; Groop, L. C. PGC-1α-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes Nat. Genet. 2003, 34 (3) 267-273
15. Subramanian, A.; Tamayo, P.; Mootha, V. K.; Mukherjee, S.; Ebert, B. L.; Gillette, M. A.; Paulovich, A.; Pomeroy, S. L.; Golub, T. R.; Lander, E. S.; Mesirov, J. P. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles Proc. Natl. Acad. Sci. U. S. A. 2005, 102 (43) 15545-15550
16. Calvano, S. E.; Xiao, W.; Richards, D. R.; Felciano, R. M.; Baker, H. V.; Cho, R. J.; Chen, R. O.; Brownstein, B. H.; Cobb, J. P.; Tschoeke, S. K.; Miller-Graziano, C.; Moldawer, L. L.; Mindrinos, M. N.; Davis, R. W.; Tompkins, R. G.; Lowry, S. F. Inflamm; Host Response to Injury Large Scale Collab. Res, P., A network-based analysis of systemic inflammation in humans Nature 2005, 437 (7061) 1032-1037
17. Grigoryev, Y. A.; Kurian, S. M.; Avnur, Z.; Borie, D.; Deng, J.; Campbell, D.; Sung, J.; Nikolcheva, T.; Quinn, A.; Schulman, H.; Peng, S. L.; Schaffer, R.; Fisher, J.; Mondala, T.; Head, S.; Flechner, S. M.; Kantor, A. B.; Marsh, C.; Salomon, D. R. Deconvoluting post-transplant immunity: cell subset-specific mapping reveals pathways for activation and expansion of memory T, monocytes and B cells PLoS One 2010, 5 (10) e13358
18. Allen, B. C.; Kavlock, R. J.; Kimmel, C. A.; Faustman, E. M. Dose-response assessment for developmental toxicity. II. Comparison of generic benchmark dose estimates with no observed adverse effect levels Toxicol. Sci. 1994, 23 (4) 487-495
19. Daston, G. P. Gene expression, dose-response, and phenotypic anchoring: applications for toxicogenomics in risk assessment Toxicol. Sci. 2008, 105 (2) 233-234
20. Andersen, M. E.; H, J. C., III; Bermudez, E.; Willson, G. A.; Thomas, R. S. Genomic signatures and dose-dependent transitions in nasal epithelial responses to inhaled formaldehyde in the rat Toxicol. Sci. 2008, 105 (2) 368-383
21. Ahlborn, G. J.; Nelson, G. M.; Ward, W. O.; Knapp, G.; Allen, J. W.; Ouyang, M.; Roop, B. C.; Chen, Y.; OBriend, T.; Kitchin, K. T.; Delker, D. A. Dose response evaluation of gene expression profiles in the skin of K6/ODC mice exposed to sodium arsenite Toxicol. Appl. Pharmacol. 2008, 227 (3) 400-416
22. Mezentsev, A.; Amundson, S. A. Global gene expression responses to low- or high-dose radiation in a human three-dimensional tissue model Radiat. Res. 2011, 175 (6) 677-88
23. Onnis-Hayden, A.; Weng, H.; He, M.; Hansen, S.; Ilyin, V.; Lewis, K.; Gu, A. Z. Prokaryotic real-time gene expression profiling for toxicity assessment Environ. Sci. Technol. 2009, 43 (12) 4574-4581
24. Gou, N.; Onnis-Hayden, A.; Gu, A. Z. Mechanistic toxicity assessment of nanomaterials by whole-cell-Array stress genes expression analysis Environ. Sci. Technol. 2010, 44 (15) 5964-5970
25. Gou, N.; Yuan, S.; Lan, J.; Gao, C.; Alshawabkeh, A. N.; Gu, A. Z. A quantitative toxicogenomics assay reveals the evolution and nature of toxicity during the transformation of environmental pollutants Environ. Sci. Technol. 2014, 48 (15) 8855-8863
26. Zaslaver, A.; Bren, A.; Ronen, M.; Itzkovitz, S.; Kikoin, I.; Shavit, S.; Liebermeister, W.; Surette, M. G.; Alon, U. A comprehensive library of fluorescent transcriptional reporters for Escherichia coli Nat. Methods 2006, 3 (8) 623-628
27. Peddada, S. D.; Lobenhofer, E. K.; Li, L.; Afshari, C. A.; Weinberg, C. R.; Umbach, D. M. Gene selection and clustering for time-course and dose-response microarray experiments using order-restricted inference Bioinformatics 2003, 19 (7) 834-841
28. Keseler, I. M.; Mackie, A.; Peralta-Gil, M.; Santos-Zavaleta, A.; Gama-Castro, S.; Bonavides-Martínez, C.; Fulcher, C.; Huerta, A. M.; Kothari, A.; Krummenacker, M.; Latendresse, M.; Muñiz-Rascado, L.; Ong, Q.; Paley, S.; Schröder, I.; Shearer, A. G.; Subhraveti, P.; Travers, M.; Weerasinghe, D.; Weiss, V.; Collado-Vides, J.; Gunsalus, R. P.; Paulsen, I.; Karp, P. D. EcoCyc: fusing model organism databases with systems biology Nucleic Acids Res. 2013, 41 (Database issue) D605-D612
29. Dyk, T. K. V.; Wei, Y.; Hanafey, M. K.; Maureen, Dolan; Reeve, M. J. G.; Rafalski, J. A.; Rothman-Denes, L. B.; LaRossa, R. A. A genomic approach to gene fusion technology Proc. Natl. Acad. Sci. U. S. A. 2001, 98 (5) 2555-2560
30. Hollander, M.; Wolfe, D. A. Nonparametric Statistical Methods; Wiley: New York, 1999.
31. Benjamini, Y.; Hochberg, Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing J. R. Stat. Soc. Ser. B 1995, 289-300
32. Jolliffe, I. Principal Component Analysis; Wiley Online Library: 2005.
33. Raychaudhuri, S.; Stuart, J. M.; Altman, R. B. In Principal components analysis to summarize microarray experiments: application to sporulation time series, Pac. Symp. Biocomput., 2000; NIH Public Access: 2000; p 455.
34. Chung, H. J.; Bang, W.; Drake, M. A. Stress response of Escherichia coli Compr. Rev. Food Sci. Food Safety 2006, 5 (3) 52-64
35. Yosef, N.; Regev, A. Impulse control: temporal dynamics in gene transcription Cell 2011, 144 (6) 886-896
36. Altshuler, B. Modeling of dose-response relationships Environ. Health Perspect. 1981, 42, 23-27
37. Chechik, G.; Koller, D. Timing of gene expression responses to environmental changes J. Comput. Biol. 2009, 16 (2) 279-290
38. Nevozhay, D.; Adams, R. M.; Murphy, K. F.; Josić, K.; Balázsi, G. Negative autoregulation linearizes the dose-response and suppresses the heterogeneity of gene expression Proc. Natl. Acad. Sci. U. S. A. 2009, 106 (13) 5123-5128
39. Kærn, M.; Elston, T. C.; Blake, W. J.; Collins, J. J. Stochasticity in gene expression: from theories to phenotypes Nat. Rev. Genet. 2005, 6 (6) 451-464
40. Burgoon, L. D.; Zacharewski, T. R. Automated quantitative dose-response modeling and point of departure determination for large toxicogenomic and high-throughput screening data sets Toxicol. Sci. 2008, 104 (2) 412-418
41. Flora, G.; Gupta, D.; Tiwari, A. Toxicity of lead: A review with recent updates Interdiscip. Toxicol. 2012, 5 (2) 47-58
42. Aach, J.; Church, G. M. Aligning gene expression time series with time warping algorithms Bioinformatics 2001, 17 (6) 495-508
43. Lin, T.-h.; Kaminski, N.; Bar-Joseph, Z. Alignment and classification of time series gene expression in clinical studies Bioinformatics 2008, 24 (13) i147-i155
44. Goering, P. L. Lead-protein interactions as a basis for lead toxicity Neurotoxicology 1992, 14 (2-3) 45-60