Fathead minnow steroidogenesis: In silico analyses reveals tradeoffs between nominal target efficacy and robustness to cross-talk

Jason E. Shoemaker, Kalyan Gayen, Natàlia Garcia-Reyero, Edward J. Perkins, Daniel L. Villeneuve, Li Liu, Francis J. Doyle

Research output: Contribution to journalArticle

19 Citations (Scopus)

Abstract

Background: Interpreting proteomic and genomic data is a major challenge in predictive ecotoxicology that can be addressed by a systems biology approach. Mathematical modeling provides an organizational platform to consolidate protein dynamics with possible genomic regulation. Here, a model of ovarian steroidogenesis in the fathead minnow, Pimephales promelas, (FHM) is developed to evaluate possible transcriptional regulation of steroid production observed in microarray studies.Results: The model was developed from literature sources, integrating key signaling components (G-protein and PKA activation) with their ensuing effect on steroid production. The model properly predicted trajectory behavior of estradiol and testosterone when fish were exposed to fadrozole, a specific aromatase inhibitor, but failed to predict the steroid hormone behavior occurring one week post-exposure as well as the increase in steroid levels when the stressor was removed. In vivo microarray data implicated three modes of regulation which may account for over-production of steroids during a depuration phase (when the stressor is removed): P450 enzyme up-regulation, inhibin down-regulation, and luteinizing hormone receptor up-regulation. Simulation studies and sensitivity analysis were used to evaluate each case as possible source of compensation to endocrine stress.Conclusions: Simulation studies of the testosterone and estradiol response to regulation observed in microarray data supported the hypothesis that the FHM steroidogenesis network compensated for endocrine stress by modulating the sensitivity of the ovarian network to global cues coming from the hypothalamus and pituitary. Model predictions of luteinizing hormone receptor regulation were consistent with depuration and in vitro data. These results challenge the traditional approach to network elucidation in systems biology. Generally, the most sensitive interactions in a network are targeted for further elucidation but microarray evidence shows that homeostatic regulation of the steroidogenic network is likely maintained by a mildly sensitive interaction. We hypothesize that effective network elucidation must consider both the sensitivity of the target as well as the target's robustness to biological noise (in this case, to cross-talk) when identifying possible points of regulation.

Original languageEnglish (US)
Article number89
JournalBMC Systems Biology
Volume4
DOIs
StatePublished - Jun 28 2010
Externally publishedYes

Fingerprint

Cyprinidae
Crosstalk
Microarrays
Computer Simulation
Categorical or nominal
Efficacy
Trade-offs
Steroids
Robustness
Target
Hormones
LH Receptors
Systems Biology
Steroid hormones
Testosterone
Estradiol
Proteins
Fadrozole
Up-Regulation
Ecotoxicology

ASJC Scopus subject areas

  • Molecular Biology
  • Structural Biology
  • Computer Science Applications
  • Applied Mathematics
  • Modeling and Simulation

Cite this

Fathead minnow steroidogenesis : In silico analyses reveals tradeoffs between nominal target efficacy and robustness to cross-talk. / Shoemaker, Jason E.; Gayen, Kalyan; Garcia-Reyero, Natàlia; Perkins, Edward J.; Villeneuve, Daniel L.; Liu, Li; Doyle, Francis J.

In: BMC Systems Biology, Vol. 4, 89, 28.06.2010.

Research output: Contribution to journalArticle

Shoemaker, Jason E. ; Gayen, Kalyan ; Garcia-Reyero, Natàlia ; Perkins, Edward J. ; Villeneuve, Daniel L. ; Liu, Li ; Doyle, Francis J. / Fathead minnow steroidogenesis : In silico analyses reveals tradeoffs between nominal target efficacy and robustness to cross-talk. In: BMC Systems Biology. 2010 ; Vol. 4.
@article{53dcb07f0cb94c4b8c85a001e2b4cf21,
title = "Fathead minnow steroidogenesis: In silico analyses reveals tradeoffs between nominal target efficacy and robustness to cross-talk",
abstract = "Background: Interpreting proteomic and genomic data is a major challenge in predictive ecotoxicology that can be addressed by a systems biology approach. Mathematical modeling provides an organizational platform to consolidate protein dynamics with possible genomic regulation. Here, a model of ovarian steroidogenesis in the fathead minnow, Pimephales promelas, (FHM) is developed to evaluate possible transcriptional regulation of steroid production observed in microarray studies.Results: The model was developed from literature sources, integrating key signaling components (G-protein and PKA activation) with their ensuing effect on steroid production. The model properly predicted trajectory behavior of estradiol and testosterone when fish were exposed to fadrozole, a specific aromatase inhibitor, but failed to predict the steroid hormone behavior occurring one week post-exposure as well as the increase in steroid levels when the stressor was removed. In vivo microarray data implicated three modes of regulation which may account for over-production of steroids during a depuration phase (when the stressor is removed): P450 enzyme up-regulation, inhibin down-regulation, and luteinizing hormone receptor up-regulation. Simulation studies and sensitivity analysis were used to evaluate each case as possible source of compensation to endocrine stress.Conclusions: Simulation studies of the testosterone and estradiol response to regulation observed in microarray data supported the hypothesis that the FHM steroidogenesis network compensated for endocrine stress by modulating the sensitivity of the ovarian network to global cues coming from the hypothalamus and pituitary. Model predictions of luteinizing hormone receptor regulation were consistent with depuration and in vitro data. These results challenge the traditional approach to network elucidation in systems biology. Generally, the most sensitive interactions in a network are targeted for further elucidation but microarray evidence shows that homeostatic regulation of the steroidogenic network is likely maintained by a mildly sensitive interaction. We hypothesize that effective network elucidation must consider both the sensitivity of the target as well as the target's robustness to biological noise (in this case, to cross-talk) when identifying possible points of regulation.",
author = "Shoemaker, {Jason E.} and Kalyan Gayen and Nat{\`a}lia Garcia-Reyero and Perkins, {Edward J.} and Villeneuve, {Daniel L.} and Li Liu and Doyle, {Francis J.}",
year = "2010",
month = "6",
day = "28",
doi = "10.1186/1752-0509-4-89",
language = "English (US)",
volume = "4",
journal = "BMC Systems Biology",
issn = "1752-0509",
publisher = "BioMed Central",

}

TY - JOUR

T1 - Fathead minnow steroidogenesis

T2 - In silico analyses reveals tradeoffs between nominal target efficacy and robustness to cross-talk

AU - Shoemaker, Jason E.

AU - Gayen, Kalyan

AU - Garcia-Reyero, Natàlia

AU - Perkins, Edward J.

AU - Villeneuve, Daniel L.

AU - Liu, Li

AU - Doyle, Francis J.

PY - 2010/6/28

Y1 - 2010/6/28

N2 - Background: Interpreting proteomic and genomic data is a major challenge in predictive ecotoxicology that can be addressed by a systems biology approach. Mathematical modeling provides an organizational platform to consolidate protein dynamics with possible genomic regulation. Here, a model of ovarian steroidogenesis in the fathead minnow, Pimephales promelas, (FHM) is developed to evaluate possible transcriptional regulation of steroid production observed in microarray studies.Results: The model was developed from literature sources, integrating key signaling components (G-protein and PKA activation) with their ensuing effect on steroid production. The model properly predicted trajectory behavior of estradiol and testosterone when fish were exposed to fadrozole, a specific aromatase inhibitor, but failed to predict the steroid hormone behavior occurring one week post-exposure as well as the increase in steroid levels when the stressor was removed. In vivo microarray data implicated three modes of regulation which may account for over-production of steroids during a depuration phase (when the stressor is removed): P450 enzyme up-regulation, inhibin down-regulation, and luteinizing hormone receptor up-regulation. Simulation studies and sensitivity analysis were used to evaluate each case as possible source of compensation to endocrine stress.Conclusions: Simulation studies of the testosterone and estradiol response to regulation observed in microarray data supported the hypothesis that the FHM steroidogenesis network compensated for endocrine stress by modulating the sensitivity of the ovarian network to global cues coming from the hypothalamus and pituitary. Model predictions of luteinizing hormone receptor regulation were consistent with depuration and in vitro data. These results challenge the traditional approach to network elucidation in systems biology. Generally, the most sensitive interactions in a network are targeted for further elucidation but microarray evidence shows that homeostatic regulation of the steroidogenic network is likely maintained by a mildly sensitive interaction. We hypothesize that effective network elucidation must consider both the sensitivity of the target as well as the target's robustness to biological noise (in this case, to cross-talk) when identifying possible points of regulation.

AB - Background: Interpreting proteomic and genomic data is a major challenge in predictive ecotoxicology that can be addressed by a systems biology approach. Mathematical modeling provides an organizational platform to consolidate protein dynamics with possible genomic regulation. Here, a model of ovarian steroidogenesis in the fathead minnow, Pimephales promelas, (FHM) is developed to evaluate possible transcriptional regulation of steroid production observed in microarray studies.Results: The model was developed from literature sources, integrating key signaling components (G-protein and PKA activation) with their ensuing effect on steroid production. The model properly predicted trajectory behavior of estradiol and testosterone when fish were exposed to fadrozole, a specific aromatase inhibitor, but failed to predict the steroid hormone behavior occurring one week post-exposure as well as the increase in steroid levels when the stressor was removed. In vivo microarray data implicated three modes of regulation which may account for over-production of steroids during a depuration phase (when the stressor is removed): P450 enzyme up-regulation, inhibin down-regulation, and luteinizing hormone receptor up-regulation. Simulation studies and sensitivity analysis were used to evaluate each case as possible source of compensation to endocrine stress.Conclusions: Simulation studies of the testosterone and estradiol response to regulation observed in microarray data supported the hypothesis that the FHM steroidogenesis network compensated for endocrine stress by modulating the sensitivity of the ovarian network to global cues coming from the hypothalamus and pituitary. Model predictions of luteinizing hormone receptor regulation were consistent with depuration and in vitro data. These results challenge the traditional approach to network elucidation in systems biology. Generally, the most sensitive interactions in a network are targeted for further elucidation but microarray evidence shows that homeostatic regulation of the steroidogenic network is likely maintained by a mildly sensitive interaction. We hypothesize that effective network elucidation must consider both the sensitivity of the target as well as the target's robustness to biological noise (in this case, to cross-talk) when identifying possible points of regulation.

UR - http://www.scopus.com/inward/record.url?scp=77953922688&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=77953922688&partnerID=8YFLogxK

U2 - 10.1186/1752-0509-4-89

DO - 10.1186/1752-0509-4-89

M3 - Article

C2 - 20579396

AN - SCOPUS:77953922688

VL - 4

JO - BMC Systems Biology

JF - BMC Systems Biology

SN - 1752-0509

M1 - 89

ER -