Research Interests- “Multi-cellularity in health and disease” - a biocomplexity approach

• Systems biology: mammalian cell fate control by transcriptional networks and gene expression noise (experiments, genomics, computer simulation)
• Stem cells : The essence of “stemness” and how cells make decisions [- yes, they can’t decide and flip-flop !]    (hematopoietic progenitors and embryonic stem cells as experimental system)
• Cancer biology: dynamics of tumorigenesis, tumor heterogeneity, non-darwinian somatic evolution; cancer (stem) cell dynamics; stochastic microstates in cancer cell populations; multi-target cancer therapy and drug resistance
• Theory: Non-equilibrium thermodynamics of evolution and development: diversification, directionality, inevitability

If understanding the organism “as a whole” without neglecting its component parts is a goal of biocomplexity , then we will have to ask why the whole is more than the sum of its parts, as Aristotle taught us. The component parts in our focus plane are genes and the whole are gene networks and the very existence of a diverse set of distinct cell types, such as red blood cells, liver cells, fibroblasts, etc., each of which acts like a distinct ‘species’ in the metazoan body. Molecular biology has taught us how to describe all the genes and proteins and how they interact in “signaling pathways”. Evolutionary biology and ecology have taught us how the diversity of organisms came into existence and how they interplay to form ecosystems. However, neither cell nor developmental biology offers a conceptual framework for dealing with the diversity of cell types in the body as a system. A biocomplexity approach should go beyond the reduction of phenotypes to genes and pathways. Therefore, we seek to elucidate the fundamental principles behind the very phenomenon of multicellularity as such. For instance, we ask: How can one genome produce the thousands of stable, distinct cell types that divide, differentiate and die in a self-orchestrated manner to guarantee organismal function? How can we understand cancer, the price we pay for multicellularity, from this perspective?

NOTE:   Due to my relocation to the ISB Seattle I am no longer teaching BIOL 463 “Systems Biology: Network Dynamics and Biocomplexity".   However, by popular demand, I am making the interactive class hand-outs with solutions filled in available – please email me.

 

Graduate Students: 3

Post Doctoral Fellows: 4

Selected Peer-Reviewed Publications (most relevant, recent and requested)

• Huang S, Eichler G, Bar-Yam Y, Ingber D. Cell fate as a high-dimensional attractor of a complex gene regulatory network. Phys. Rev. Lett. 94:128701 (2005).
• Huang S, Guo YP, May G, Enver T. Bifurcation dynamics in lineage-commitment in bipotent progenitor cells. Dev. Biol. 305:695-713 (2007).
• Chang H, Hemberg M, Barahona B, Ingber D and Huang S. Transcriptome-wide noise controls lineage choice in mammalian progenitor cells. Nature 453:544-547 (2008).
• Huang S. Reprogramming cell fates: reconciling rarity with robustness. BioEssays. 31:546-60 (2009)
• Huang S. Non-genetic heterogeneity of cells in development: More than just noise. Development 136:3853-62 (2009).
• Huang S. Cell lineage determination in state space: a systems view brings flexibility to dogmatic canonical rules.  PLoS Biol 8: e1000380. (2010)
• Zhou, JX and Huang S. "Understanding gene circuits at cell-fate branch points for rational cell reprogramming." Trends Genet Dec 10 (2010).
• Huang S. Systems biology of stem cells: three useful perspectives to help overcome the paradigm of linear pathways. Philos Trans R Soc Lond B Biol Sci 366: 2247-2259 (2011).

2. Cancer

• Huang S and Ingber DE. Cell tension, matrix mechanics and cancer development. Cancer Cell 8:175-176 (2005)
• Huang S, Ingber DE. A non-genetic basis for cancer progression and metastasis: self-organizing attractors in cell regulatory networks. Breast Disease 26:27-54 (2006-2007)
• Panigrahy D, Kaipainen A, Huang S, Butterfield KE, Barnes CM, Fannon M, Laforme AM, Folkman J, Kieran MW. The PPARα agonist fenofibrate suppresses tumor growth through direct and indirect angiogenesis inhibition. Proc Natl Acad Sci U S A. 105: 985-990 (2008).
• Brock A, Chang H, Huang S. Non-genetic heterogeneity - a mutation-independent driving force for the somatic evolution of tumours. Nat Rev Genet. 10: 336-42. (2009)
• Huang S, Ernberg I, Kauffman S. Cancer attractors: a systems view of tumors from a gene network dynamics and developmental perspective. Semin Cell Dev Biol. 20:869-876 (2009)
• Bracha AL, Ramanathan A, Huang S, Ingber DE, Schreiber SL. Carbon metabolism-mediated myogenic differentiation. Nat Chem Biol. 6:202-204 (2010)
• Huang, S. On the intrinsic inevitability of cancer: From foetal to fatal attraction.  Semin Cancer Biol21: 183-199 (2011).

3. Gene networks, Systems biology

• Huang S, Wikswo PJ. Five dimensions of systems biology. Reviews of Physiology, Biochemistry, and Pharmacology 157: 81-104 (2006)
• Huang S. and Kauffman S. Gene Regulatory Networks - From Structure to Biological Observable: Cell fate Determination. Encyclopedia of Complexity, Springer (2009)
• Wang, J., Xu, L., Wang, E. K. & Huang, S. The "potential" landscape of genetic circuits imposes the arrow of time in stem cell differentiation.Biophys J 99: 29-39 (2010).
• Guo, Y, Feng Y, Trivedi, NS, Huang S. Medusa structure of the gene regulatory network: dominance of transcription factors in cancer subtype classification. Exp Biol Med 236: 628-636 (2011).