Unraveling Disease Pathophysiology with Mathematical Modeling

A framework for multi-scale intervention modeling: virtual cohorts, virtual clinical trials, and model-to-model comparisons

Computational models of disease progression have been constructed for a myriad of pathologies. Typically, the conceptual implementation for pathology-related in-silico intervention studies has been ad-hoc and similar in design to experimental studies. We introduce a multi-scale interventional design (MID) framework toward two key goals: tracking of disease dynamics from within-body to patient to population scale; and tracking impact(s) of interventions across these same spatial scales. Our MID framework prioritizes investigation of impact on individual patients within virtual pre-clinical trials, instead of replicating the design of experimental studies. We apply a MID framework to develop, organize, and analyze a cohort of virtual patients for the study of tuberculosis (TB) as an example disease. For this study, we use HostSim: our next-generation whole patient-scale computational model of individuals infected with Mycobacterium tuberculosis. HostSim captures infection within lungs by tracking multiple granulomas, together with dynamics occurring with blood and lymph node compartments, the compartments involved during pulmonary TB. We extend HostSim to include a simple drug intervention as an example of our approach and use our MID framework to quantify the impact of treatment at cellular and tissue (granuloma), patient (lungs, lymph nodes and blood), and population scales. Sensitivity analyses allow us to determine which features of virtual patients are the strongest predictors of intervention efficacy across scales. These insights allow us to identify patient-heterogeneous mechanisms that drive outcomes across scales.

Self-assembly of three-dimensional liver organoids: virtual reconstruction via endocytosed polymer dots for refactoring the fine structure

In vitro culture of organoids holds considerable promise for the treatment of diseases or the provision of artificial organs. Traditional 2D differentiation from mesenchymal stem cells (MSCs) faces challenges in replicating the development of embryonic organs at the cellular level; conversely, the cultivation of 3D organoids exhibits potential for application. It is crucial for clinicians and technology researchers to acquire insights into organoid tissue differentiation, autonomous morphogenesis, as well as 3D assembly processes in vitro. In this investigation, novel 3D organoids capable of engendering complex liver-like tissues in vitro were cultured, and a class of high-luminance semiconductor polymer dots (Pdots) was employed to monitor the self-assembly process of 3D liver organoid tissues and cellular interaction and migration dynamics. Three-dimensional liver-bud (3D-LB) organoid tissues were derived through the interplay of induced MSCs, Wharton's Jelly, and human umbilical vein endothelial cells (HUVECs), and their structural characteristics were determined during the liver-bud organoid development; ultimately, the co-cultured organoid spatial cellular clusters resembling a truffle were successfully replicated. Utilizing R8-Pdots with remarkable resolution and biocompatibility, the structural elements of functional and vascularized organs derived from liver organoid tissues were adeptly reconstituted, and this investigation shall contribute to a further understanding of human hepato-developmental physiology and liver-disease modeling.

Decrypting the complexity of the human malaria parasite biology through systems biology approaches

The human malaria parasite, Plasmodium falciparum, is a unicellular protozoan responsible for over half a million deaths annually. With a complex life cycle alternating between human and invertebrate hosts, this apicomplexan is notoriously adept at evading host immune responses and developing resistance to all clinically administered treatments. Advances in omics-based technologies, increased sensitivity of sequencing platforms and enhanced CRISPR based gene editing tools, have given researchers access to more in-depth and untapped information about this enigmatic micro-organism, a feat thought to be infeasible in the past decade. Here we discuss some of the most important scientific achievements made over the past few years with a focus on novel technologies and platforms that set the stage for subsequent discoveries. We also describe some of the systems-based methods applied to uncover gaps of knowledge left through single-omics applications with the hope that we will soon be able to overcome the spread of this life-threatening disease.

Predicting the severity of disease progression in COVID-19 at the individual and population level: A mathematical model

The impact of COVID-19 disease on health and economy has been global, and the magnitude of devastation is unparalleled in modern history. Any potential course of action to manage this complex disease requires the systematic and efficient analysis of data that can delineate the underlying pathogenesis. We have developed a mathematical model of disease progression to predict the clinical outcome, utilizing a set of causal factors known to contribute to COVID-19 pathology such as age, comorbidities, and certain viral and immunological parameters. Viral load and selected indicators of a dysfunctional immune response, such as cytokines IL-6 and IFNα, which contribute to the cytokine storm and fever, parameters of inflammation d-dimer and ferritin, aberrations in lymphocyte number, lymphopenia, and neutralizing antibodies were included for the analysis. The model provides a framework to unravel the multi-factorial complexities of the immune response manifested in SARS-CoV-2 infected individuals. Further, this model can be valuable to predict clinical outcome at an individual level, and to develop strategies for allocating appropriate resources to mitigate severe cases at a population level.

Quantification of Proteins Involved in Intestinal Epithelial Handling of Xenobiotics

The intestinal epithelium represents a natural barrier against harmful xenobiotics, while facilitating the uptake of nutrients and other substances. Understanding the interaction of chemicals with constituents of the intestinal epithelium and their fate in the body requires quantitative measurement of relevant proteins in in vitro systems and intestinal epithelium. Recent studies have highlighted the mismatch between messenger RNA (mRNA) and protein abundance for several drug‐metabolizing enzymes and transporters in the highly dynamic environment of the intestinal epithelium; mRNA abundances cannot therefore be used as a proxy for protein abundances in the gut, necessitating direct measurements. The objective was to determine the expression of a wide range proteins pertinent to metabolism and disposition of chemicals and nutrients in the intestinal epithelium. Ileum and jejunum biopsy specimens were obtained from 16 patients undergoing gastrointestinal elective surgery. Mucosal fractions were prepared and analyzed using targeted and global proteomic approaches. A total of 29 enzymes, 32 transporters, 6 tight junction proteins, 2 adhesion proteins, 1 alkaline phosphatase, 1 thioredoxin, 5 markers, and 1 regulatory protein were quantified—60 for the first time. The global proteomic method identified a further 5,222 proteins, which are retained as an open database for interested parties to explore. This study significantly expands our knowledge of a wide array of proteins important for xenobiotic handling in the intestinal epithelium. Quantitative systems biology models will benefit from the novel systems data generated in the present study and the translation path offered for in vitro to in vivo translation.