Biology subjects

Igoshin, O. A.

Publications and source records attributed to Igoshin, O. A..

5 recordsLinked to original sources

bioRxiv2018

Synthetic pluripotent bacterial stem cells

A defining property of stem cells is their ability to differentiate via asymmetric cell division, in which a stem cell creates a differentiated daughter cell but retains its own phenotype. Here, we describe a synthetic genetic circuit for controlling asymmetrical cell division in Escherichia coli. Specifically, we engineered an inducible system that can bind and segregate plasmid DNA to a single position in the cell. Upon division, the co-localized plasmids are kept by one and only one of the daughter cells. The other daughter cell receives no plasmid DNA and is hence irreversibly differentiated from its sibling. In this way, we achieved asymmetric cell division though asymmetric plasmid partitioning. We also characterized an orthogonal inducible circuit that enables the simultaneous asymmetric partitioning of two plasmid species - resulting in pluripotent cells that have four distinct differentiated states. These results point the way towards engineering multicellular systems from prokaryotic hosts.

synthetic biology↗

bioRxiv2018

Agent-Based Modeling Reveals Possible Mechanisms for Observed Aggregation Cell Behaviors in Myxococcus xanthus

Myxococcus xanthus is a soil bacterium that serves as a model system for biological self-organization. Cells form distinct, dynamic patterns depending on environmental conditions. An agent-based model (ABM) was used to understand how M. xanthus cells aggregate into multicellular mounds in response to starvation. In this model, each cell is modeled as an agent, represented by a point-particle and characterized by its position and moving direction. At low agent density, the model recapitulates the dynamic patterns observed by experiments and a previous biophysical model. To study aggregation at high cell density, we extended the model based on the recent experimental observation that cells exhibit biased movement towards aggregates. We tested two possible mechanisms for this biased movement and demonstrate that a chemotaxis model with adaptation can reproduce the observed experimental results leading to the formation of stable aggregates. Furthermore, our model reproduces the experimentally observed patterns of cell alignment around aggregates.\n\nAuthor summaryCollective self-organization of cells into multicellular structures is important for lifestyle of many bacterial species. Myxococcus xanthus bacterium is a model system for studying this self-organization. In this work, we investigate how in response to starvation M. xanthus cells aggregate into multicellular mounds. A recent study identified the key cellular behaviors that are necessarily for the aggregation but the mechanisms of these behaviors remained unclear. To uncover these mechanisms, we developed a computational model that simulates interactions among a large number of cells. The results demonstrate that the observed bias in the cell reversal times as they move towards the aggregates can be explained by chemotaxis model. In this model cells secrete a chemical signal and respond to it via a partially-adapting biochemical network. The resulting aggregation dynamics are in good agreement with the experiments. Furthermore, chemotaxis signaling model reproduces the experimentally observed patterns of cell alignment around aggregates. On the other hand, an alternative model, based on contact-dependent signaling between cells, fails to aid in aggregation. Thus our models make important predictions about the cellular interactions that drives multicellular aggregation and can serve as a basis to investigate a wider range of developmental mutant strains.

microbiology↗

bioRxiv2017

On the mechanism of long-range alignment order of fibroblasts

Long-range alignment ordering of fibroblasts have been observed in the vicinity of cancerous tumors and can be recapitulated with in vitro experiments. However, the mechanisms driving their ordering are not understood. Here we show that local collision-driven nematic alignment interactions among fibroblasts are insufficient to explain observed long-range alignment. One possibility is that there exists another orientation field co-evolving with the cells and reinforcing their alignment. We propose that this field reflects the mechanical cross-talk between the fibroblasts and the underlying fibrous material on which they move. We demonstrate that this new long-range interaction can give rise to high nematic order and to the observed patterning of the cancer microenvironment.\n\nSignificance StatementLong-range alignment patterns of fibroblasts have been observed both in vivo and in vitro. However, there has not been much understanding of the underlying mechanism. In this work, we demonstrate that these patterns cannot be simply explained by their steric interaction with one another during collisions. Instead, we propose that fibroblasts may collectively align through non-local interactions arising from their modification of an underlying extracellular matrix. The proposed mechanism explains the observed co-alignment between fibroblasts and collagen fibers around tumors and can be be tested in future experiments that can image the dynamics of this pattern formation in vivo or in vitro

biophysics↗

bioRxiv2017

Modeling mechanical interactions in growing populations of rod-shaped bacteria

Advances in synthetic biology allow us to engineer bacterial collectives with pre-specified characteristics. However, the behavior of these collectives is difficult to understand, as cellular growth and division as well as extra-cellular fluid flow lead to complex, changing arrangements of cells within the population. To rationally engineer and control the behavior of cell collectives we need theoretical and computational tools to understand their emergent spatiotemporal dynamics. Here, we present an agent-based model that allows growing cells to detect and respond to mechanical interactions. Crucially, our model couples the dynamics of cell growth to the cells environment: Mechanical constraints can affect cellular growth rate and a cell may alter its behavior in response to these constraints. This coupling links the mechanical forces that influence cell growth and emergent behaviors in cell assemblies. We illustrate our approach by showing how mechanical interactions can impact the dynamics of bacterial collectives growing in microfluidic traps.

synthetic biology↗

bioRxiv2017

Elucidating interplay of speed and accuracy in biological error correction

One of the most fascinating features of biological systems is the ability to sustain high accuracy of all major cellular processes despite the stochastic nature of underlying chemical processes. It is widely believed that such low errors are the result of the error correcting mechanism known as kinetic proofreading. However, it is usually argued that enhancing the accuracy should result in slowing down the process leading to so-called speed-accuracy trade-off. We developed a discrete-state stochastic framework that allowed us to investigate the mechanisms of the proofreading using the method of first-passage processes. With this framework, we simultaneously analyzed speed and accuracy of the two fundamental biological processes, DNA replication and tRNA selection during the translation. The results indicate that speed-accuracy trade-off is not always observed. However, when the trade-off is present, the biological systems tend to optimize the speed rather than the accuracy of the processes, as long as the error level is tolerable. Additional constraints due to the energetic cost of proofreading also play a role in the error correcting process. Our theoretical findings provide a new microscopic picture of how complex biological processes are able to function so fast with a high accuracy.

biophysics↗