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Victoria Mochulska

PhD - McGill University
Supervisor
Research Topics
Computational Biology
Dynamical Systems
Optimization

Publications

Cycles upon cycles - Temperature Scaling of Medaka Development
Sapna Chhabra
Carina B. Vibe
Anubhuti Anushree
Kristina S. Stapornwongkul
Thomas Thumberger
Joachim Wittbrodt
Alexander Aulehla
ABSTRACT How organisms develop in dynamic environmental conditions is a fundamental question. We asked how day-night temperature cycles impa… (see more)ct embryonic axis elongation and segmentation, itself a cyclic process linked to the segmentation clock, using the Japanese rice fish medaka. We developed an unbiased dimensional reduction approach, based on Singular Value Decomposition (SVD), to reliably identify the dynamic modes of segmentation clock oscillations across all temperature conditions. We reveal that the two major dynamic modes show opposite temperature sensitivities: while the temporal oscillation (mode 1) varies strongly with temperature, the spatial phase gradient (mode 2) appears largely temperature invariant. In addition, we found developmental parameters with intermediate, sub-scaled temperature responses, such as axis elongation. We used theoretical modeling to understand how dynamic modes emerge from the underlying local oscillation dynamics and axis elongation. We then exposed embryos to circadian and ultradian temperature cycles to reveal dynamic response patterns of oscillations and axis elongation, and found how these responses are integrated into morphological features. Combined, our theoretical-experimental results support a model in which the dynamic integration of temporal (i.e. segmentation clock related) and spatial (i.e. axis elongation) processes, in particular their sub-scaled temperature response patterns, quantitatively compensate each other to yield a robust, temperature-invariant axis patterning outcome.
Generative epigenetic landscapes map the topology and topography of cell fates.
Epigenetic landscapes were proposed by Waddington as the central concept to describe cell fate dynamics in a locally low-dimensional space. … (see more)In modern landscape models, attractors represent cell types, and stochastic jumps and bifurcations drive cellular decisions, allowing for quantitative and predictive descriptions. However, given a biological problem of interest, we still lack tools to infer and build possible Waddington landscapes systematically. In this study, we propose a generative model for deriving epigenetic landscapes compatible with data. To build the landscapes, we combine gradient and rotational vector fields composed of locally weighted elements that encode ‘valleys’ of the Waddington landscape, resulting in interpretable models. We optimize landscapes through computational evolution and illustrate our approach with two developmental examples: metazoan segmentation and neuromesoderm differentiation. In both cases, we obtain ensembles of solutions that reveal both known and novel landscapes in terms of topology and bifurcations. Conversely, topographic features appear strongly constrained by dynamical data, which suggests that our approach can generically derive interpretable and predictive epigenetic landscapes.
Dynamical model and geometric insights in the discontinuity theory of immunity
Christian Mauffette Denis
Maya Dagher
Vincent Verbavatz
François X.P. Bourassa
Grégoire Altan-Bonnet
The immune system’s most basic task is to decide what is “self” and “non-self”, but a precise definition of self versus non-self r… (see more)emains challenging. According to the discontinuity theory of immunity, effector responses depend on how quickly an antigenic stimulus changes: rapid change triggers an immune response, whereas gradual change fosters tolerance. We present a model of adaptive immune dynamics including T cells, Tregs and cytokines that reproduces the hallmarks of the discontinuity theory. The model allows for sharp discrimination between acute and chronic infections based on the growth rate of the immune challenge, and vaccination-like acute dynamics upon presentation of a bolus of immune challenge. We further show that the model behavior only depends on a handful of testable assumptions that we map to geometric constraints in phase space. This suggests that the model properties are generic and robust across alternative mechanistic details. We also examine the impact of multiple concurrent immune challenges in this model, and demonstrate the occurrence of dynamical antagonism, wherein, in some parameter regimes, slow-growing challenges hinder acute responses to fast-growing ones, with further counter-intuitive behaviors for sequential co-infections. Together, these results place the discontinuity theory on firm mathematical footing and encourage further investigation of interferences of multi-agent immune challenges, from chronic viral co-infections to cancer immunoediting.