Diverse quantitative approaches integrating data and modelling in development and medicine

Monday, June 14 at 7:45pm (PDT)
Tuesday, June 15 at 03:45am (BST)
Tuesday, June 15 11:45am (KST)

SMB2021 SMB2021 Follow Monday (Tuesday) during the "MS04" time block.
Note: this minisymposia has multiple sessions. The second session is MS03-CDEV (click here).

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Adriana Dawes (Ohio State University, USA), Sungrim Seirin-Lee (Hiroshima University, Japan)


Mathematical sciences are making significant contributions to our understanding of developmental biology and its application to medicine using a diversity of approaches. One such approach integrates data with quantitative models under both normal and pathological conditions to uncover hidden rules and relationships underlying biological phenomena. By identifying these basic rules of life, mathematical models can further explore the consequences of these regulatory mechanisms, how they can be exploited by disease processes, and provide testable predictions for unresolved questions that may be difficult to address experimentally. In this minisymposium, we bring together research from a variety of perspectives to share recent developments in techniques and insights for understanding complex, medically relevant, dynamics that are associated with development.

Adriana Dawes

(Ohio State University, USA)
"The causes and consequences of centrosome asymmetry during development"
Asymmetric cell division, where daughter cells inherit unequal amounts of specific factors, is critical for development and cell fate specification, and is implicated in disease processes such as tumour growth. In polarized cells, where specific factors are segregated to opposite ends of the cell as seen in early embryos of the nematode worm C. elegans, asymmetric cell division occurs as a result of dynein-mediated centrosome positioning along the polarity axis. Using a combination of stochastic and continuum models with experimental validation, we show that centrosome asymmetry is critical for centrosome positioning in the early C. elegans embryo, and that this asymmetry arises from differential recruitment of proteins to centrosomes during their maturation process.

Susanne Rafelski

(Allen Institute for Cell Science, USA)
"Decoding the variance in intracellular organization of human stem cells"
The Allen Institute for Cell Science aims to understand the principles by which human induced pluripotent stem cells (hiPSCs) establish and maintain robust dynamic localization of subcellular structures. Initial steps aim to determine the full range of natural variation in intracellular organization in hiPSCs under normal, unperturbed conditions. We used 25 of the endogenous fluorescently tagged hiPSC lines in the Allen Cell Collection (, each expressing a monoallelic EGFP-tagged protein labeling a particular organelle or structure. We imaged thousands of cells at high resolution in 3D for each structure and developed segmentation algorithms and workflows for quantitative analyses. To measure variation in cell and nuclear shapes, we fit 3D segmented masks using spherical harmonic functions, and then performed a principal component analysis of the spherical harmonic coefficients. We found that the largest axes of shape variation corresponds to 1) cell height, due to differences in cell packing colonies, and 2) cell volume, representing cell growth through the cell cycle. We performed a survey analysis of size scaling and found that structures differ in the strength of their scaling with cell size and nuclear size. To explore variation in intracellular organization, we parameterized the cytoplasm and nucleoplasm via spherical harmonics to generate maps for each structure in each cell in 3D. Analysis of these maps allowed us to quantify and rank how stereotyped the locations for each of these structures are and further to cluster structures via correlations in their location relative to each other over different spatial scales. This systematic approach has enabled us to quantify how subcellular organelle organization varies with changes in cell shape in an integrated fashion across 25 EGFP-tagged subcellular structures.

Naoki Honda

(, Japan)
"Data-driven hierarchical modeling of collective cell migration"
Collective cell migration is a fundamental process of development. It has been known that cell migration within an epithelial sheet is oriented by traveling waves of ERK activation. However, its mechanism has remained elusive. To extract control roles in the epithelial sheet dynamics, we first developed mathematical models at the different hierarchical levels of individual cells and continuum, which can be seamlessly linked. Based on this hierarchical modeling, we mathematically predicted that migration velocity is directed by several mechano-chemical signals: cellular density, ERK activity, velocity field and their temporal and/or spatial derivatives. To test this model prediction, we live-imaged ERK activity during the collective cell migration with FRET-based biosensor. From the live imaging data, we quantified the time-series data corresponding to variables in the model. We then analyzed the time-series data with help of machine learning and then obtained a reverse-engineered model, which describes how the cells intracellularly process these mechano-chemical signals. We also confirmed that this model has an ability to forecast cell migration, hence showing validity of the model. By interpreting the reverse-engineered continuum model at the individual cellular level, we elucidated intercellular mechanical interaction is up-regulated by temporal derivative of ERK signal. Therefore, our data-driven hierarchical modeling approach is powerful to understand multicellular dynamics.

Hiroshi Suito

(Tohoku University, Japan)
"Patient-specific approaches to cardiovascular diseases"
In blood vessels with congenital heart diseases, characteristic flow structures are formed, in which pulsating flows affect strongly on wall shear stresses and energy dissipation patterns. In this talk, we present computational analyses for blood flows in patient-specific cases, through which we aim at understanding the relationships between differences in geometries and in energy dissipations. Our present targets include an aortic coarctation case and a Norwood surgery for hypoplastic left heart syndrome. These analyses yield deeper understandings in clinical medicine.

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Virtual conference of the Society for Mathematical Biology, 2021.