Cytoskeleton and Cell Shape (CyCelS) Lab

We combine microtubule (MT) cytoskeleton and moeculaCytoskeleton and Cell Shape Labr motors in computater simulations and in vitro reconstitution, to study collective effects that drive cell shape and division. Some current proejcts are described in detail below. For open positions refer to the tab to the right.

Collective Transport of Microtubules and Organelles by Molecular Motors
Setup of the dynein gliding assay in simulation and experiment

Dynein Collective Transport: Simulation & Experiment (Jain et al. 2019 Soft Matter)

Purified yeast dynein motors drive the transport of Rh-Tubulin labelled MT filaments (Jain et al. 2019)

In vitro reconstitution of purified molecular motors and microtubules (MTs)

Gliding assays of microtubule driven by a minima S. cerevisiae dynein.

Stochastic simulations of multi-protein transport

A mathematical model based on detailed single-molecule mechanics (Jain, Khetan and Athale 2019) integrates experiment and theory.

Simulation movie of dynein based gliding assay

Gliding assay in simulation: Bound dynein (bright green) and "searching" microtubules (grey) in 2D

Simulating MT asters collective transport based on ex vivo Xenopus extract experiments (Athale et al. 2014 Phys. Biol. 11: 016008) and the in vivo self-organisation of spindles in mouse oocyes undergoing meiosis I (Khetan & Athale, 2016 PLoS Comp Biol).

Nuclear positioning by dynein in mitosis

In more recent work we have begun to examine how these number-dependent effects affect the transport and positioning of nuclei in the budding yeast S. cerevisiae.

Mathematical modeling of cytoskeletal basis of neuronal growth cone turning to examine the limits of sensing of the MT system in axonal growth cones (Mahajan and Athale 2012).

Spindle segregation during embryonic division of the nematode Caenorhabditis elegans- In collaboration with the lab of Prof. Marie Delattre, Plasticity and Evolution of Cell Division Lab at ENS Lyon.

Tubulin Polymerization Kinetics and Dynamics
Schematic depicting the scale of MTs and kinetics of polymerization and depolymerization

MT size and kinetics of polymerization (Athale, C.A. 2011, Modelling the Spatial Pattern Forming Modules in Mitotic Spindle Assembly)

The diversity of microtubule (MT) inhibitors that originates from plants and have medicinal uses has fascinated us. We have together with our collaborators Prof. Uma Shaanker’s group in UAS Bangalore, begun to investigate the role of MT polymerization kinetics in presence of colchicine – both produced from the plant and present in the insect that feeds on it.

Computational Imaging Tool Development
Image from the report by Chaphalkar et al.

Amtrak used to quantify E. coli nucleoids

Mathematical Modeling of Pattern Formation

Schematic of models of receptor mobility diffusion and dimerization, REF: Deshpande et al. (2017) Phys. Biol.

Receptor aggregation dynamics by dimerization is thought to be critical for signalling in cancer cells, as summarized in a theoretical model by us in 2005 (Athale, Mansury & Deisboeck J. Theor. Biol.). The microscopic details of such receptor dynamics have been more recently modeled using coarse-grained simulations in collaboration with the Biophysical Chemistry lab in NCL Pune (Pawar et al. 2014, Sengupta et al. 2016). We have more recently developed a Monte-Carlo simulation of receptor dimerization kinetics based on a diffusion and aggregation model in a heterogenous environment (Deshpande et al. (2017) Phys. Biol).

Bacterial Cell Size Biophysics
Image from Gangan & Athale (2017) of microfluidics of E. coli cells grown in LB at 37 deg C

Constitutive GFP expressing E. coli in a "mother machine" microfluidics chip.

The cell size variability in cell shape in a population (Athale &Chaudhari Bioinformatics) is thought to be linked to replication processivity linking the rate of growth of single cells to cell division (Gangan & Athale 2017 Roy. Soc. open science). We are currently working on formalizing our insights in the form of a theoretical model using an Agent-Based Modeling (ABM) approach.

ABM for tumour growth: network model from Zhang, Athale & Deisboeck (2007) J. Theor. Biol.

ABMs: Discrete models related to cellular automata, but more flexible  for rule-based behavior.

Self-Organized Collective Behaviour

Self-organization of aster patterns by mechanics (Khetan & Athale, in press)

As with flocks of birds, schooling of fish and people milling at a railway station, collective patterns that emerge have fascinated humankind since time immemorial. We hope to work on biomolecules and find out the laws by which they organize. Finding the similarities and differences to more complex pattern, is our way of working our way upwards in complexity, in the hope of finding out the universal laws and the exceptions that guide such patterns. The 1974 parable from Films Division India “एक, अनेक और एकता”, a must watch.

The Films Division Documentary on unity of purpose

Collective effects self-organized: in a social context (Films Division India): This social parable from Films Division India (1974) has amazing parallels in collective behaviour as we think of it- birds swarming, people at a railway station, fish schooling.


  1. Department of Biotechnology, Govt. of India Dept. of Biotechnology, Govt. of India
  2. Department of Science and Technology, Govt. of India
  3. Private companies for some short term projects with BS-MS undergraduate students (iGEM)
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