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A more perfect status quo


Purdue researchers develop a protocol to gather comparable data from the Mother Machine and the SChemostat in the first heads-on comparison of high-precision cell data


An interdisciplinary team of researchers from Purdue University has performed side-by-side comparison of precision data collected from both the Mother Machine and the SChemostat technologies, providing substantial insights into quantitative rules governing the maintenance of stochastic homeostasis in living systems. The technologies were developed at Purdue University in the lab of Prof. Sri Iyer-Biswas. The team from left to right: Dr Charles Wright; Dr Ferdinand Ziegler; Professor Sri Iyer-Biswas; Professor Rudro Biswas; Dr Kunaal Joshi


How do organisms keep their internal systems working consistently in the face of ever-changing environmental pressures? This feat—termed homeostasis—is a foundational concept in modern physiology, and yet the specific mechanisms by which homeostasis is achieved and sustained remain poorly quantified. In large part, this is because the problem is inherently interdisciplinary, requiring the synthesis of high-precision experiments with physics theory in ways that push the frontiers of knowledge of complex systems, control theory, stochastic processes, mathematical physics and living systems. Even in the context of the simplest living system (a single bacterial cell) and its best studied physiological attribute (cell size) in almost perfectly consistent environments (constant nutrient concentrations), the question of what quantitative rules ensure and yield homeostasis remains a topic of fierce debate.

A breakthrough in experimental approaches occurred over a decade ago with the introduction of the “Mother Machine,” a microfluidic device that traps individual bacteria in narrow dead-end channels so that their offspring form family lineages that can be observed under a microscope.  Despite the significant advantages over previous technologies in live single-cell imaging, the mother machine faces certain disadvantages such as being restricted to one mother cell per channel, mechanical stress due to confinement and contact with daughter cells, and uncertainty in nutrient homogeneity (since nutrient supply is diffusion-limited, and there are multiple daughter cells between the mother cell and the feeding channel). These limit the quantity and quality of data that can be obtained from this experimental approach. Thus, attempts to model cell size homeostasis using mother machine data were mostly limited to deterministic models describing an 'ideal' cell, sometimes with ad-hoc added noise.

A systematic approach to modeling the full stochastic inter-generational dynamics of cell sizes leading to homeostasis was only made possible through the use of the SChemostat, an alternative microfluidic device previously developed by the Iyer-Biswas group, led by Professor Srividya Iyer-Biswas, that lets bacteria attach to a surface in a large open chamber without physical confinement, yielding the benefit that each single cell is truly isolated from both its neighbors and its surroundings and experiences homogeneous growth conditions. An analysis of the data thus obtained by the Iyer-Biswas lab at Purdue University’s Department of Physics and Astronomy revealed the inter-generational scaling laws that govern the stochastic dynamics of cell sizes, a crucial feature that gets obscured when only considering the mythical 'average' cell.

Since the SChemostat device can only be used with specific microbes (which can be made to conditionally stick), the mother machine still remains the go-to device for a wide range of microbes. Thus, there is a need to benchmark the data obtained from the mother machine to assess the effects from unwanted factors like mechanical stress.

A multidisciplinary team of researchers at Purdue decided to tackle this problem by directly observing and comparing single-cell homeostasis across different setups.  In their latest work, the team developed a protocol to gather comparable data from the Mother Machine and the SChemostat in the first heads-on comparison of high-precision data of the growth and division dynamics of single bacterial cells from different experimental apparatuses. They published their findings in the journal Molecular Biology of the Cell in an article titled, "Scaling of stochastic growth and division dynamics: A comparative study of individual rod-shaped cells in the Mother Machine and SChemostat platforms."

Professor Christine Jacobs-Wagner at Stanford University, a leading expert in the field notes: “This compelling study showcases the value in comparing different microfluidic systems to identify governing principles of cell growth and size homeostasis in bacteria.”

When analyzing the growth and division patterns of the same bacterial strain in these two setups, the authors found intriguing deviations in the distributions of key observed quantities, such as growth rate, time needed to divide, and relative cell sizes before-versus-after division, which fully compensated for each other when combined using the proper mathematical formula. In contrast, the distributions of cell sizes before and after division, when rescaled by their respective mean values, were remarkably consistent across conditions.  At the same time, they were remarkably consistent with previous theoretical frameworks established by the researchers, confirming the general validity across experimental realizations of their stochastic intergenerational scaling law governing cell size homeostasis.

These findings establish a way to meaningfully compare single-cell data collected using different microfluidic platforms by pointing to which quantities remain unchanged across conditions, and which do not. This is of critical importance for the field of microbiology, as it provides a principled route to understand the ways in which the experimental devices themselves impact the observations. Only after taking this into consideration can the probabilistic phenomena observed in these datasets be properly characterized. As established in the present study, such an approach may reveal surprising emergent simplicities—here, the consistency of scaling of each individual cell’s size from generation to generation. Future studies are poised to reveal behaviors in more complex environments that change over time, or expose the organisms to stressful conditions, such as exposure to antibiotics.


About the Department of Physics and Astronomy at Purdue University  

Purdue’s Department of Physics and Astronomy has a rich and long history dating back to 1904. Our faculty and students are exploring nature at all length scales, from the subatomic to the macroscopic and everything in between. With an excellent and diverse community of faculty, postdocs and students who are pushing new scientific frontiers, we offer a dynamic learning environment, an inclusive research community and an engaging network of scholars.  

Physics and Astronomy is one of the seven departments within the Purdue University College of Science. World-class research is performed in astrophysics, atomic and molecular optics, accelerator mass spectrometry, biophysics, condensed matter physics, quantum information science, and particle and nuclear physics. Our state-of-the-art facilities are in the Physics Building, but our researchers also engage in interdisciplinary work at Discovery Park District at Purdue, particularly the Birck Nanotechnology Center and the Bindley Bioscience Center. We also participate in global research including at the Large Hadron Collider at CERN, many national laboratories (such as Argonne National Laboratory, Brookhaven National Laboratory, Fermilab, Oak Ridge National Laboratory, the Stanford Linear Accelerator, etc.), the James Webb Space Telescope, and several observatories around the world.   


Written by:  Srividya Iyer-Biswas, Assistant Professor of Physics and Astronomy

Charlie Wright, Postdoctoral Researcher at Purdue University

Kunaal Joshi, PhD candidate at Purdue University

Rudro Biswas, Assistant Professor of Physics and Astronomy

Last Updated: May 9, 2024 2:34 PM

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