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An Overview of the Translational Dilemma and the Need for Translational Systems Biology of Inflammation

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Complex Systems and Computational Biology Approaches to Acute Inflammation

Abstract

The translational dilemma, i.e., the difficulty in achieving effective translation of basic mechanistic biomedical knowledge into effective therapeutics, is the greatest challenge in biomedical research. Nowhere is this more apparent than in the reductionist approaches to understanding and manipulating the acute inflammatory response in the settings of sepsis, trauma/hemorrhage, wound healing, and related processes such as host–pathogen interactions. Despite numerous advances in defining novel molecules, pathways, and mechanisms, these advances remain, in general, in scientific silos that are poorly connected and lacking interoperability, reflected in the dearth of available therapeutics for these deadly diseases. We suggest that complex systems and computational biology methods and approaches have advanced sufficiently to allow for knowledge generation, knowledge integration, and clinical translation in the settings of complex diseases related to the inflammatory response. This book brings together the current state of the art in complex systems and computational biology as applied to inflammatory diseases.

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References

  1. An G (2010) Closing the scientific loop: bridging correlation and causality in the petaflop age. Sci Transl Med 2:41ps34

    Article  PubMed  Google Scholar 

  2. Vodovotz Y, Constantine G, Rubin J, Csete M, Voit EO, An G (2009) Mechanistic simulations of inflammation: current state and future prospects. Math Biosci 217(1):1–10

    Article  PubMed  Google Scholar 

  3. Vodovotz Y, An G (2009) Systems biology and inflammation. In: Yan Q (ed) Systems biology in drug discovery and development: methods and protocols. Springer, Totowa, NJ, pp 181–201

    Google Scholar 

  4. Vodovotz Y (2010) Translational systems biology of inflammation and healing. Wound Repair Regen 18(1):3–7

    Article  PubMed  Google Scholar 

  5. Namas R, Ghuma A, Torres A, Polanco P, Gomez H, Barclay D, Gordon L, Zenker S, Kim HK, Hermus L et al (2009) An adequately robust early TNF-α response is a hallmark of survival following trauma/hemorrhage. PLoS One 4(12):e8406

    Article  PubMed  Google Scholar 

  6. Neunaber C, Zeckey C, Andruszkow H, Frink M, Mommsen P, Krettek C, Hildebrand F (2011) Immunomodulation in polytrauma and polymicrobial sepsis – where do we stand? Recent Pat Inflamm Allergy Drug Discov 5(1):17–25

    Article  PubMed  CAS  Google Scholar 

  7. Godin PJ, Buchman TG (1996) Uncoupling of biological oscillators: a complementary hypothesis concerning the pathogenesis of multiple organ dysfunction syndrome. Crit Care Med 24(7):1107–1116

    Article  PubMed  CAS  Google Scholar 

  8. Neugebauer EA, Willy C, Sauerland S (2001) Complexity and non-linearity in shock research: reductionism or synthesis? Shock 16(4):252–258

    Article  PubMed  CAS  Google Scholar 

  9. Chinnaiyan AM, Huber-Lang M, Kumar-Sinha C, Barrette TR, Shankar-Sinha S, Sarma VJ, Padgaonkar VA, Ward PA (2001) Molecular signatures of sepsis: multiorgan gene expression profiles of systemic inflammation. Am J Pathol 159(4):1199–1209

    Article  PubMed  CAS  Google Scholar 

  10. Cobb JP, Brownstein BH, Watson MA, Shannon WD, Laramie JM, Qiu Y, Stormo GD, Morrissey JJ, Buchman TG, Karl IE et al (2001) Injury in the era of genomics. Shock 15(3):165–170

    Article  PubMed  CAS  Google Scholar 

  11. Chung TP, Laramie JM, Province M, Cobb JP (2002) Functional genomics of critical illness and injury. Crit Care Med 30(1 Suppl):S51–S57

    Article  CAS  Google Scholar 

  12. Cobb JP, O’Keefe GE (2004) Injury research in the genomic era. Lancet 363(9426):2076–2083

    Article  PubMed  CAS  Google Scholar 

  13. Yu SL, Chen HW, Yang PC, Peck K, Tsai MH, Chen JJ, Lin FY (2004) Differential gene expression in gram-negative and gram-positive sepsis. Am J Respir Crit Care Med 169(10):1135–1143

    Article  PubMed  Google Scholar 

  14. Wurfel MM (2007) Microarray-based analysis of ventilator-induced lung injury. Proc Am Thorac Soc 4(1):77–84

    Article  PubMed  CAS  Google Scholar 

  15. Edmonds RD, Vodovotz Y, Lagoa C, Dutta-Moscato J, Ching Y, Fink MP, Levy RM, Prince JM, Kaczorowski DJ, Tseng G et al (2011) Transcriptomic response of murine liver to severe injury and hemorrhagic shock: a dual platform microarray analysis. Physiol Genomics 43:1170–1183

    Article  PubMed  CAS  Google Scholar 

  16. Wong HR (2012) Clinical review: sepsis and septic shock – the potential of gene arrays. Crit Care 16(1):204

    PubMed  Google Scholar 

  17. Broadbent J, Walsh T, Upton Z (2010) Proteomics in chronic wound research: potentials in healing and health. Proteomics Clin Appl 4(2):204–214

    Article  PubMed  CAS  Google Scholar 

  18. Roy S, Sen CK (2012) miRNA in wound inflammation and angiogenesis. Microcirculation 19(3):224–232

    Article  PubMed  CAS  Google Scholar 

  19. Morowitz MJ, Babrowski T, Carlisle EM, Olivas A, Romanowski KS, Seal JB, Liu DC, Alverdy JC (2011) The human microbiome and surgical disease. Ann Surg 253(6):1094–1101

    Article  PubMed  Google Scholar 

  20. Hartlova A, Krocova Z, Cerveny L, Stulik J (2011) A proteomic view of the host-pathogen interaction: the host perspective. Proteomics 11(15):3212–3220

    Article  PubMed  CAS  Google Scholar 

  21. Malnoy M, Martens S, Norelli JL, Barny MA, Sundin GW, Smits TH, Duffy B (2012) Fire blight: applied genomic insights of the pathogen and host. Annu Rev Phytopathol 50:475–494

    Article  PubMed  CAS  Google Scholar 

  22. An G, Faeder J, Vodovotz Y (2008) Translational systems biology: introduction of an engineering approach to the pathophysiology of the burn patient. J Burn Care Res 29:277–285

    Article  PubMed  Google Scholar 

  23. Vodovotz Y, Csete M, Bartels J, Chang S, An G (2008) Translational systems biology of inflammation. PLoS Comput Biol 4:1–6

    Article  Google Scholar 

  24. Vodovotz Y, Constantine G, Faeder J, Mi Q, Rubin J, Sarkar J, Squires R, Okonkwo DO, Gerlach J, Zamora R et al (2010) Translational systems approaches to the biology of inflammation and healing. Immunopharmacol Immunotoxicol 32:181–195

    Article  PubMed  Google Scholar 

  25. Mi Q, Li NYK, Ziraldo C, Ghuma A, Mikheev M, Squires R, Okonkwo DO, Verdolini Abbott K, Constantine G, An G et al (2010) Translational systems biology of inflammation: potential applications to personalized medicine. Pers Med 7:549–559

    Article  Google Scholar 

  26. An G, Bartels J, Vodovotz Y (2010) In silico augmentation of the drug development pipeline: examples from the study of acute inflammation. Drug Dev Res 72:1–14

    Google Scholar 

  27. Namas R, Zamora R, Namas R, An G, Doyle J, Dick TE, Jacono FJ, Androulakis IP, Chang S, Billiar TR et al (2012) Sepsis: something old, something new, and a systems view. J Crit Care 27:314e1–314e11

    Article  Google Scholar 

  28. An G, Nieman G, Vodovotz Y (2012) Computational and systems biology in trauma and sepsis: current state and future perspectives. Int J Burns Trauma 2:1–10

    PubMed  Google Scholar 

  29. An G, Namas R, Vodovotz Y (2012) Sepsis: from pattern to mechanism and back. Crit Rev Biomed Eng 40(4):341–351

    Article  PubMed  Google Scholar 

  30. An G, Nieman G, Vodovotz Y (2012) Toward computational identification of multiscale tipping points in multiple organ failure. Ann Biomed Eng 40(11):2414–2424

    Article  PubMed  Google Scholar 

  31. Clermont G, Bartels J, Kumar R, Constantine G, Vodovotz Y, Chow C (2004) In silico design of clinical trials: a method coming of age. Crit Care Med 32:2061–2070

    Article  PubMed  Google Scholar 

  32. An G (2004) In-silico experiments of existing and hypothetical cytokine-directed clinical trials using agent based modeling. Crit Care Med 32:2050–2060

    Article  PubMed  CAS  Google Scholar 

  33. Li NYK, Verdolini K, Clermont G, Mi Q, Hebda PA, Vodovotz Y (2008) A patient-specific in silico model of inflammation and healing tested in acute vocal fold injury. PLoS One 3:e2789

    Article  PubMed  Google Scholar 

  34. Nieman K, Brown D, Sarkar J, Kubiak B, Ziraldo C, Vieau C, Barclay D, Gatto L, Maier K, Zamora R et al (2012) A two-compartment mathematical model of endotoxin-induced inflammatory and physiologic alterations in swine. Crit Care Med 40:1052–1063

    Article  PubMed  Google Scholar 

  35. Parker RS, Clermont G (2010) Systems engineering medicine: engineering the inflammation response to infectious and traumatic challenges. J R Soc Interface 7(48):989–1013

    Article  PubMed  CAS  Google Scholar 

  36. Dick TE, Molkov Y, Nieman G, Hsieh Y, Jacono FJ, Doyle J, Scheff J, Calvano SE, Androulakis IP, An G et al (2012) Linking inflammation and cardiorespiratory variability in sepsis via computational modeling. Front Physiol 3:222

    Article  PubMed  Google Scholar 

  37. An G (2001) Agent-based computer simulation and SIRS: building a bridge between basic science and clinical trials. Shock 16(4):266–273

    Article  PubMed  CAS  Google Scholar 

  38. An G (2009) A model of TLR4 signaling and tolerance using a qualitative, particle event-based method: introduction of Spatially Configured Stochastic Reaction Chambers (SCSRC). Math Biosci 217:43–52

    Article  PubMed  CAS  Google Scholar 

  39. Kumar R, Clermont G, Vodovotz Y, Chow CC (2004) The dynamics of acute inflammation. J Theor Biol 230:145–155

    Article  PubMed  CAS  Google Scholar 

  40. Chow CC, Clermont G, Kumar R, Lagoa C, Tawadrous Z, Gallo D, Betten B, Bartels J, Constantine G, Fink MP et al (2005) The acute inflammatory response in diverse shock states. Shock 24:74–84

    Article  PubMed  CAS  Google Scholar 

  41. Reynolds A, Rubin J, Clermont G, Day J, Vodovotz Y, Ermentrout GB (2006) A reduced mathematical model of the acute inflammatory response: I. Derivation of model and analysis of anti-inflammation. J Theor Biol 242:220–236

    Article  PubMed  CAS  Google Scholar 

  42. Day J, Rubin J, Vodovotz Y, Chow CC, Reynolds A, Clermont G (2006) A reduced mathematical model of the acute inflammatory response: II. Capturing scenarios of repeated endotoxin administration. J Theor Biol 242:237–256

    Article  PubMed  CAS  Google Scholar 

  43. Prince JM, Levy RM, Bartels J, Baratt A, Kane JM III, Lagoa C, Rubin J, Day J, Wei J, Fink MP et al (2006) In silico and in vivo approach to elucidate the inflammatory complexity of CD14-deficient mice. Mol Med 12:88–96

    Article  PubMed  CAS  Google Scholar 

  44. Lagoa CE, Bartels J, Baratt A, Tseng G, Clermont G, Fink MP, Billiar TR, Vodovotz Y (2006) The role of initial trauma in the host’s response to injury and hemorrhage: insights from a comparison of mathematical simulations and hepatic transcriptomic analysis. Shock 26:592–600

    Article  PubMed  CAS  Google Scholar 

  45. Foteinou PT, Calvano SE, Lowry SF, Androulakis IP (2009) Modeling endotoxin-induced systemic inflammation using an indirect response approach. Math Biosci 217:27–42

    Article  PubMed  CAS  Google Scholar 

  46. Foteinou PT, Calvano SE, Lowry SF, Androulakis IP (2009) In silico simulation of corticosteroids effect on an NFkB-dependent physicochemical model of systemic inflammation. PLoS One 4(3):e4706

    Article  PubMed  Google Scholar 

  47. An G, Bartels J, Vodovotz Y (2011) In silico augmentation of the drug development pipeline: examples from the study of acute inflammation. Drug Dev Res 72(2):187–200

    Article  PubMed  CAS  Google Scholar 

  48. Dong X, Foteinou PT, Calvano SE, Lowry SF, Androulakis IP (2010) Agent-based modeling of endotoxin-induced acute inflammatory response in human blood leukocytes. PLoS One 5(2):e9249

    Article  PubMed  Google Scholar 

  49. Scheff JD, Calvano SE, Lowry SF, Androulakis IP (2010) Modeling the influence of circadian rhythms on the acute inflammatory response. J Theor Biol 264(3):1068–1076

    Article  PubMed  Google Scholar 

  50. Foteinou PT, Calvano SE, Lowry SF, Androulakis IP (2011) A physiological model for autonomic heart rate regulation in human endotoxemia. Shock 35(3):229–239

    Article  PubMed  Google Scholar 

  51. Scheff JD, Mavroudis PD, Calvano SE, Lowry SF, Androulakis IP (2011) Modeling autonomic regulation of cardiac function and heart rate variability in human endotoxemia. Physiol Genomics 43(16):951–964

    Article  PubMed  CAS  Google Scholar 

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Acknowledgments

The authors would like to thank all of the authors that have joined us in this book. Our Translational Systems Biology work was supported in part by the National Institutes of Health grants R01GM67240, P50GM53789, R33HL089082, R01HL080926, R01AI080799, R01HL76157, R01DC008290, and UO1DK072146; National Institute on Disability and Rehabilitation Research grant H133E070024; National Science Foundation grant 0830-370-V601; a Shared University Research Award from IBM, Inc.; and grants from the Commonwealth of Pennsylvania, the Pittsburgh Life Sciences Greenhouse, and the Pittsburgh Tissue Engineering Initiative/Department of Defense.

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Authors and Affiliations

  1. Department of Surgery, University of Pittsburgh, W944 Starzl Biomedical Science Tower, 200 Lothrop St, Pittsburgh, PA, 15213, USA

    Yoram Vodovotz Ph.D.

  2. Department of Surgery, University of Chicago, 5841 South Maryland Ave, MC 5094 S-032, Chicago, IL, 60637, USA

    Gary An M.D.

Authors
  1. Yoram Vodovotz Ph.D.
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  2. Gary An M.D.
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Correspondence to Yoram Vodovotz Ph.D. .

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Editors and Affiliations

  1. University of Pittsburgh Inflammation and Regenerative Modeling, Pittsburgh, Pennsylvania, USA

    Yoram Vodovotz

  2. University of Chicago Medical Center MC 5094, Chicago, Illinois, USA

    Gary An

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Vodovotz, Y., An, G. (2013). An Overview of the Translational Dilemma and the Need for Translational Systems Biology of Inflammation. In: Vodovotz, Y., An, G. (eds) Complex Systems and Computational Biology Approaches to Acute Inflammation. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8008-2_1

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