Information-Theoretic Analysis of a Model of CAR-4-1BB-Mediated NFκB Activation

Systems biology utilizes computational approaches to examine an array of biological processes, such as cell signaling, metabolomics and pharmacology. This includes mathematical modeling of CAR T cells, a modality of cancer therapy by which genetically engineered immune cells recognize and combat a cancerous target. While successful against hematologic malignancies, CAR T cells have shown limited success against other cancer types. Thus, more research is needed to understand their mechanisms of action and leverage their full potential. In our work, we set out to apply information theory on a mathematical model of NFκB signaling initiated by the CAR following antigen encounter. First, we estimated channel capacity for CAR-4-1BB-mediated NFκB signal transduction. Next, we evaluated the pathway's ability to distinguish contrasting "low" and "high" antigen concentration levels, depending on the amount of variability in protein concentrations. Finally, we assessed the fidelity by which NFκB activation reflects the encountered antigen concentration, depending on the prevalence of antigen-positive targets in tumor population. We found that in most scenarios, fold change in the nuclear concentration of NFκB carries a higher channel capacity for the pathway than NFκB's absolute response. Additionally, we found that most errors in transducing the antigen signal through the pathway skew towards underestimating the concentration of encountered antigen. Finally, we found that disabling IKKβ deactivation could increase signaling fidelity against targets with antigen-negative cells. Our information-theoretic analysis of signal transduction can provide novel perspectives on biological signaling, as well as enable a more informed path to cell engineering.Kindly check and confirm whether the corresponding affiliation is correctly identified.this is correct.

Moving Research-Based Learning in Life Sciences Upstream, and Beyond Borders: An International Group Research Project for High School Youth

International cooperation beyond borders, institutions, and intergenerationally is an important aspect of science and research-based learning. Timing of learning also matters. Early exposure to group research-based learning can potentially have lasting positive impacts on youth and their careers in life sciences. Here, we report our work on the International Group Project (IGP), which builds on the International Biology Olympiad (IBO) organized in Yerevan, Armenia, in 2022. The IBO is an annual international competition for high school students held since 1990 around the world. We envisioned the IGP as a novel opportunity for life sciences research-based education among youth. We formed diverse IGP research teams 2 months before the IBO, and comprised high school students from 32 countries, communicating in a digital environment via videoconferencing. Each team formulated a research question in an IGP theme from five domains of life sciences: "Biomedicine," "Molecular and cell biology," "Bioinformatics and Artificial Intelligence," "Bionics and Biomimicry," "Across Species." Subsequently, team members collectively solved their research question by applying life sciences methodologies under supervision from a facilitator scientist. Each team created a poster based on their research and presented in-person to the public at a satellite activity at the IBO. A special subcommittee of the IBO International Jury graded posters and allocated prizes based on scientific ingenuity and presentation quality. This experience from the IGP lends evidence to the feasibility of research-based learning in life sciences for high school youth beyond borders. Moving research-based learning upstream and internationally is well poised to advance 21st century life sciences from both interdisciplinary and intergenerational standpoints. The historic impact of the COVID-19 pandemic suggests that youth engagement in research-based learning and innovation in life sciences is timely.

A systems and computational biology perspective on advancing CAR therapy

In the recent decades, chimeric antigen receptor (CAR) therapy signaled a new revolutionary approach to cancer treatment. This method seeks to engineer immune cells expressing an artificially designed receptor, which would endue those cells with the ability to recognize and eliminate tumor cells. While some CAR therapies received FDA approval and others are subject to clinical trials, many aspects of their workings remain elusive. Techniques of systems and computational biology have been frequently employed to explain the operating principles of CAR therapy and suggest further design improvements. In this review, we sought to provide a comprehensive account of those efforts. Specifically, we discuss various computational models of CAR therapy ranging in scale from organismal to molecular. Then, we describe the molecular and functional properties of costimulatory domains frequently incorporated in CAR structure. Finally, we describe the signaling cascades by which those costimulatory domains elicit cellular response against the target. We hope that this comprehensive summary of computational and experimental studies will further motivate the use of systems approaches in advancing CAR therapy.

Information-theoretic analysis of a model of CAR-4-1BB-mediated NFκB activation

Systems biology utilizes computational approaches to examine an array of biological processes, such as cell signaling, metabolomics and pharmacology. This includes mathematical modeling of CAR T cells, a modality of cancer therapy by which genetically engineered immune cells recognize and combat a cancerous target. While successful against hematologic malignancies, CAR T cells have shown limited success against other cancer types. Thus, more research is needed to understand their mechanisms of action and leverage their full potential. In our work, we set out to apply information theory on a mathematical model of cell signaling of CAR-mediated activation following antigen encounter. First, we estimated channel capacity for CAR-4-1BB-mediated NFκB signal transduction. Next, we evaluated the pathway's ability to distinguish contrasting "low" and "high" antigen concentration levels, depending on the amount of intrinsic noise. Finally, we assessed the fidelity by which NFκB activation reflects the encountered antigen concentration, depending on the prevalence of antigen-positive targets in tumor population. We found that in most scenarios, fold change in the nuclear concentration of NFκB carries a higher channel capacity for the pathway than NFκB's absolute response. Additionally, we found that most errors in transducing the antigen signal through the pathway skew towards underestimating the concentration of encountered antigen. Finally, we found that disabling IKKβ deactivation could increase signaling fidelity against targets with antigen-negative cells. Our information-theoretic analysis of signal transduction can provide novel perspectives on biological signaling, as well as enable a more informed path to cell engineering.

Organizing an in-person nation-wide Biology olympiad during the Covid-19 pandemic

The Covid-19 pandemic has inspired the implementation of a number of online educational activities designed to promote appropriate measures, such as social distancing, in order to avoid spread of the disease. In these circumstances, ensuring that extracurricular activities in science education adapt to the changing situation is of crucial importance. Recognizing the important role high school science olympiads play in science education, we organized an in-person socially distanced 2-day examination for the final round of the Armenian National Biology Olympiad by using Classmarker, a web-based in-browser tool for administering exams. We believe that our experience with organizing this event will prove useful to other educators faced with uncertainty regarding the return to pre-pandemic modes of instruction.

Computational analysis of 4-1BB-induced NFκB signaling suggests improvements to CAR cell design

Background

Chimeric antigen receptor (CAR)-expressing cells are a powerful modality of adoptive cell therapy against cancer. The potency of signaling events initiated upon antigen binding depends on the costimulatory domain within the structure of the CAR. One such costimulatory domain is 4-1BB, which affects cellular response via the NFκB pathway. However, the quantitative aspects of 4-1BB-induced NFκB signaling are not fully understood.

Methods

We developed an ordinary differential equation-based mathematical model representing canonical NFκB signaling activated by CD19scFv-4-1BB. After a global sensitivity analysis on model parameters, we ran Monte Carlo simulations of cell population-wide variability in NFκB signaling and quantified the mutual information between the extracellular signal and different levels of the NFκB signal transduction pathway.

Results

In response to a wide range of antigen concentrations, the magnitude of the transient peak in NFκB nuclear concentration varies significantly, while the timing of this peak is relatively consistent. Global sensitivity analysis showed that the model is robust to variations in parameters, and thus, its quantitative predictions would remain applicable to a broad range of parameter values. The model predicts that overexpressing NEMO and disabling IKKβ deactivation can increase the mutual information between antigen levels and NFκB activation.

Conclusions

Our modeling predictions provide actionable insights to guide CAR development. Particularly, we propose specific manipulations to the NFκB signal transduction pathway that can fine-tune the response of CD19scFv-4-1BB cells to the antigen concentrations they are likely to encounter.

Modelling predicts differences in chimeric antigen receptor T-cell signalling due to biological variability

In recent decades, chimeric antigen receptors (CARs) have been successfully used to generate engineered T cells capable of recognizing and eliminating cancer cells. The structure of CARs typically includes costimulatory domains, which enhance the T-cell response upon antigen encounter. However, it is not fully known how those co-stimulatory domains influence cell activation in the presence of biological variability. In this work, we used mathematical modelling to elucidate how the inclusion of one such costimulatory molecule, CD28, impacts the response of a population of CAR T cells under different sources of variability. Particularly, we demonstrate that CD28-bearing CARs mediate a faster and more consistent population response under both target antigen variability and kinetic rate variability. Next, we identify kinetic parameters that have the most impact on cell response time. Finally, based on our findings, we propose that enhancing the catalytic activity of lymphocyte-specific protein tyrosine kinase can result in drastically reduced and more consistent response times among heterogeneous CAR T-cell populations.

Microtubules promote intercellular contractile force transmission during tissue folding

During development, forces transmitted between cells are critical for sculpting epithelial tissues. Actomyosin contractility in the middle of the cell apex (medioapical) can change cell shape (e.g., apical constriction) but can also result in force transmission between cells via attachments to adherens junctions. How actomyosin networks maintain attachments to adherens junctions under tension is poorly understood. Here, we discovered that microtubules promote actomyosin intercellular attachments in epithelia during Drosophila melanogaster mesoderm invagination. First, we used live imaging to show a novel arrangement of the microtubule cytoskeleton during apical constriction: medioapical Patronin (CAMSAP) foci formed by actomyosin contraction organized an apical noncentrosomal microtubule network. Microtubules were required for mesoderm invagination but were not necessary for initiating apical contractility or adherens junction assembly. Instead, microtubules promoted connections between medioapical actomyosin and adherens junctions. These results delineate a role for coordination between actin and microtubule cytoskeletal systems in intercellular force transmission during tissue morphogenesis.

Engineering reaction-diffusion networks with properties of neural tissue

We present an experimental system of networks of coupled non-linear chemical reactors, which we theoretically model within a reaction-diffusion framework. The networks consist of patterned arrays of diffusively coupled nanoliter-scale reactors containing the Belousov-Zhabotinsky (BZ) reaction. Microfluidic fabrication techniques are developed that provide the ability to vary the network topology and the reactor coupling strength and offer the freedom to choose whether an arbitrary reactor is inhibitory or excitatory coupled to its neighbor. This versatile experimental and theoretical framework can be used to create a wide variety of chemical networks. Here we design, construct and characterize chemical networks that achieve the complexity of central pattern generators (CPGs), which are found in the autonomic nervous system of a variety of organisms.