In metazoans, the epithelium is the main tissue that separates us from the outside. Examples of such tissues include the epidermis and the linings of the airway and the gut. Healthy epithelial tissues are simultaneously plastic and robust, dynamically responding to changing environments without large or long-lasting deviations from a homeostatic set point. This fine balance is achieved through an exquisitely connected network of regulatory interactions between epithelial barrier function, immune response, and microbiome. What are the key features of this network responsible for maintaining homeostasis? How do these features change during the organism development, and how during evolution? How is epithelial homeostasis lost, resulting in inflammatory diseases, mucosal infections or carcinomas? In my research, I tackle these questions from a mathematical modelling perspective. I construct, analyse and validate mathematical models that represent the regulatory mechanisms of epithelial tissues and simulate how perturbations due to genetic (mutations, polymorphisms) and environmental (e.g. pathogens, toxins) risk factors lead to the loss of epithelial homeostasis and the development of carcinomas, inflammatory conditions, or infections. I have successfully applied this integrative systems biology approach to several epithelial tissues and its diseases including the epidermis in homeostasis¹ and in two of its pathological manifestations (atopic dermatitis^2-6 and squamous cell carcinoma^7-8), the glandular epithelium of the breast and the emergence of tamoxifen resistance in early stage cancer⁹, and two airway infectious diseases triggered, respectively, by Streptococcus pneumonieae¹⁰ and by Mycobacterium tuberculosis^11,12. However, the general principles of how epithelial homeostasis is maintained, and how it is lost giving rise to a variety of pathological manifestations, is still to be clarified.

At KLI, I will propose a minimal mathematical model of epithelial function in health and disease. For this, I will distil the conserved properties of the dynamical networks between barrier function, immune response, and the microbiome observed across different epithelial tissues in different animals and different developmental stages. Through exhaustive numerical simulations, I will characterise the phenotypic plasticity that can result from quantitative alterations to this minimal regulatory network, and map regions in the phenotypic space corresponding to the diversity of health and disease manifestations across species and ontogenetic stages. I will use bifurcation analysis to identify the inherent vulnerabilities of this network that can lead to deviations from homeostasis, and to suggest possible evolutionary and developmental trajectories connecting different maturities and evolutionary stages of the epithelial tissue.

This approach will unveil general principles governing epithelial homeostasis and shed light on the evolutionary and developmental origins of pathophysiological processes. Our minimal mathematical model of epithelial function will be a useful tool to systematically explore the effect of genetic and environmental alterations on homeostasis; identify the mechanisms underlying abrupt developmental, evolutionary and pathophysiological transitions; characterise the early warning signals preceding these catastrophic shifts; and design and optimize therapeutic interventions for disease prevention and reversal, even when extensive empirical data is limited.

References:

(1)  M. D. A. van Logtestijn, E. Domínguez-Hüttinger, G. N. Stamatas and R. J. Tanaka.   2015. Resistance to water diffusion in the stratum corneum is depth dependent. PLoS ONE 10(2):e0117292. https://doi.org/10.1371/journal.pone.0117292.

(2) E. Domínguez-Hüttinger, P. Christodoulides, K. Miyauchi, A. D. Irvine, M. Okada-Hatakeyama, M. Kubo, and R. J. Tanaka.  2017. Mathematical Modeling of Atopic Dermatitis Reveals ‘Double switch’ Mechanisms Underlying Four Common Disease Phenotypes, J. Allergy Clin. Immunol 139:1861-72.  http://dx.doi.org/10.1016/j.jaci.2016.10.026.

(3) P. Christodoulides, Y. Hirata, E. Domínguez-Hüttinger, S. G. Danby, M. J. Cork, K. Aihara, and R. J. Tanaka. 2017. Computational design of treatment strategies for proactive therapy on atopic dermatitis using optimal control theory, Phil.Trans.R. Soc. A., 375: 20160285.  http://dx.doi.org/10.1098/rsta.2016.0285

(4) Tanaka G., Domínguez-Hüttinger E., Christodoulides P., Aihara K. and Tanaka R.J.  Bifurcation analysis of a mathematical model of atopic dermatitis to determine patient-specific effects of treatments on dynamic phenotypes. Journal of Theoretical Biology 448: 66-79. 2018.  https://doi.org/10.1016/j.jtbi.2018.04.002.

(5) Hurault, G., Domínguez-Hüttinger E., L S. M, Williams, H.C. and R. J. Tanaka Personalised prediction of daily eczema severity scores using a mechanistic machine learning model. Clinical and Experimental Allergy. 50:1258–1266. 2020. https://doi.org/10.1111/cea.13717.

(6) Elisa Domínguez-Hüttinger*, Eliezer Flores Garza, José Luis Caldú-Primo, Harley Day, Abihail Roque Ramírez, y Reiko J Tanaka. History-dependent switch-like differentiation of keratinocytes in response to skin barrier damage. PLoS Comput Biol (2025) 21(6): e1013162. https://doi.org/10.1371/journal.pcbi.1013162

(7) Eunike Velleuer, Elisa Domínguez-Hüttinger, Alfredo Rodríguez, Leonard A Harris y Carsten Carlberg. Concepts of multi-level dynamical modelling: Understanding mechanisms of squamous cell carcinoma development in Fanconi anaemia. Front. Genet. - Nutritional Genomics (2023) 14 https://doi.org/10.3389/fgene.2023.12

(8) L. F. Méndez-López, J. Dávila-Velderrain, E. Domínguez-Hüttinger, C. Enríquez-Olguín, J. Martínez-García, and E. R. Álvarez-Buylla. 2017. Gene regulatory network underlying the immortalization of epithelial cells. BMC Syst. Biol., 11(24), pp.1–15. 10.1186/s12918-017-0393-5.

(9) Shigeyuki Magi, Sewon Ki, Masao Ukai, Elisa Domínguez- Hüttinger, Atsuhiko T Naito, Yutaka Suzuki, Mariko Okada. 2021. A combination approach of pseudotime analysis and mathematical modeling for understanding the drug-resistant mechanism. Scientific reports 11:18511 https://doi.org/10.1038/s41598-021-97887-z

(10) E. Domínguez-Hüttinger*, N. J. Boon, T. B. Clarke, and R. J. Tanaka, 2017. Mathematical modelling of colonization, invasive infection and treatment of Streptococcus pneumoniae, Front. Physiol., 8:115 https://doi.org/10.3389/fphys.2017.00115.

(11) Eliezer Flores-Garza, Mario A. Zetter, Rogelio Hernández-Pando and Elisa Domínguez-Hüttinger*. Mathematical model of the immunopathological progression of tuberculosis, Frontiers in Systems Biology, (2022) 2:912974, 10.3389/fsysb.2022.912974

(12) Eliezer Flores-Garza, Rogelio Hernández-Pando, Ibrahim García-Zárate, Pablo Aguirre and Elisa Domínguez-Hüttinger*. Bifurcation analysis of a tuberculosis progression model for drug target identification. Scientific Reports (2023) 13:17567 | https://doi.org/10.1038/s41598-023-44569-7