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Kashyap A, Wang W, Camley BA. Trade-offs in concentration sensing in dynamic environments. Biophys J 2024; 123:1184-1194. [PMID: 38532627 PMCID: PMC11140415 DOI: 10.1016/j.bpj.2024.03.025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Revised: 02/07/2024] [Accepted: 03/21/2024] [Indexed: 03/28/2024] Open
Abstract
When cells measure concentrations of chemical signals, they may average multiple measurements over time in order to reduce noise in their measurements. However, when cells are in an environment that changes over time, past measurements may not reflect current conditions-creating a new source of error that trades off against noise in chemical sensing. What statistics in the cell's environment control this trade-off? What properties of the environment make it variable enough that this trade-off is relevant? We model a single eukaryotic cell sensing a chemical secreted from bacteria (e.g., folic acid). In this case, the environment changes because the bacteria swim-leading to changes in the true concentration at the cell. We develop analytical calculations and stochastic simulations of sensing in this environment. We find that cells can have a huge variety of optimal sensing strategies ranging from not time averaging at all to averaging over an arbitrarily long time or having a finite optimal averaging time. The factors that primarily control the ideal averaging are the ratio of sensing noise to environmental variation and the ratio of timescales of sensing to the timescale of environmental variation. Sensing noise depends on the receptor-ligand kinetics, while environmental variation depends on the density of bacteria and the degradation and diffusion properties of the secreted chemoattractant. Our results suggest that fluctuating environmental concentrations may be a relevant source of noise even in a relatively static environment.
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Affiliation(s)
- Aparajita Kashyap
- Department of Biophysics, Johns Hopkins University, Baltimore, Maryland
| | - Wei Wang
- William H. Miller III Department of Physics & Astronomy, Johns Hopkins University, Baltimore, Maryland
| | - Brian A Camley
- Department of Biophysics, Johns Hopkins University, Baltimore, Maryland; William H. Miller III Department of Physics & Astronomy, Johns Hopkins University, Baltimore, Maryland.
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Nwogbaga I, Kim AH, Camley BA. Physical limits on galvanotaxis. Phys Rev E 2023; 108:064411. [PMID: 38243498 DOI: 10.1103/physreve.108.064411] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Accepted: 10/17/2023] [Indexed: 01/21/2024]
Abstract
Eukaryotic cells can polarize and migrate in response to electric fields via "galvanotaxis," which aids wound healing. Experimental evidence suggests cells sense electric fields via molecules on the cell's surface redistributing via electrophoresis and electroosmosis, though the sensing species has not yet been conclusively identified. We develop a model that links sensor redistribution and galvanotaxis using maximum likelihood estimation. Our model predicts a single universal curve for how galvanotactic directionality depends on field strength. We can collapse measurements of galvanotaxis in keratocytes, neural crest cells, and granulocytes to this curve, suggesting that stochasticity due to the finite number of sensors may limit galvanotactic accuracy. We find cells can achieve experimentally observed directionalities with either a few (∼100) highly polarized sensors or many (∼10^{4}) sensors with an ∼6-10% change in concentration across the cell. We also identify additional signatures of galvanotaxis via sensor redistribution, including the presence of a tradeoff between accuracy and variance in cells being controlled by rapidly switching fields. Our approach shows how the physics of noise at the molecular scale can limit cell-scale galvanotaxis, providing important constraints on sensor properties and allowing for new tests to determine the specific molecules underlying galvanotaxis.
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Affiliation(s)
- Ifunanya Nwogbaga
- Thomas C. Jenkins Department of Biophysics, Johns Hopkins University, Baltimore, Maryland 21218, USA
| | - A Hyun Kim
- Thomas C. Jenkins Department of Biophysics, Johns Hopkins University, Baltimore, Maryland 21218, USA
| | - Brian A Camley
- Thomas C. Jenkins Department of Biophysics, Johns Hopkins University, Baltimore, Maryland 21218, USA
- William H. Miller III Department of Physics & Astronomy, Johns Hopkins University, Baltimore, Maryland 21218, USA
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Segota I, Edwards MM, Campello A, Rappazzo BH, Wang X, Strandburg-Peshkin A, Zhou XQ, Rachakonda A, Daie K, Lussenhop A, Lee S, Tharratt K, Deshmukh A, Sebesta EM, Zhang M, Lau S, Bennedsen S, Ginsberg J, Campbell T, Wang C, Franck C. Confirmation and variability of the Allee effect in Dictyostelium discoideum cell populations,possible role of chemical signaling within cell clusters. Phys Biol 2021; 19. [PMID: 34942613 DOI: 10.1088/1478-3975/ac4613] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2021] [Accepted: 12/23/2021] [Indexed: 11/12/2022]
Abstract
In studies of the unicellular eukaryote Dictyostelium discoideum, many have anecdotally observed that cell dilution below a certain "threshold density" causes cells to undergo a period of slow growth (lag). However, little is documented about the slow growth phase and the reason for different growth dynamics below and above this threshold density. In this paper, we extend and correct our earlier work to report an extensive set of experiments, including the use of new cell counting technology, that set this slow-to-fast growth transition on a much firmer biological basis. We show that dilution below a certain density (around 10E4 cells/ml) causes cells to grow slower on average and exhibit a large degree of variability: sometimes a sample does not lag at all, while sometimes it takes many moderate density cell cycle times to recover back to fast growth. We perform conditioned media experiments to demonstrate that a chemical signal mediates this endogenous phenomenon. Finally, we argue that while simple models involving fluid transport of signal molecules or cluster-based signaling explain typical behavior, they do not capture the high degree of variability between samples but nevertheless favor an intra-cluster mechanism.
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Affiliation(s)
- Igor Segota
- Cornell University, Physics Dept., Ithaca, New York, 14853-0001, UNITED STATES
| | - Matthew M Edwards
- Cornell University, Physics Dept., Ithaca, New York, 14853-0001, UNITED STATES
| | - Arthur Campello
- Cornell University, Physics Dept., Ithaca, New York, 14853-0001, UNITED STATES
| | - Brendan H Rappazzo
- Cornell University, Physics Dept., Ithaca, New York, 14853-0001, UNITED STATES
| | - Xiaoning Wang
- Cornell University, Physics Dept., Ithaca, New York, 14853-0001, UNITED STATES
| | | | - Xiao-Qiao Zhou
- Cornell University, Physics Dept., Ithaca, New York, 14853-0001, UNITED STATES
| | - Archana Rachakonda
- Cornell University, Physics Dept., Ithaca, New York, 14853-0001, UNITED STATES
| | - Kayvon Daie
- Cornell University, Physics Dept., Ithaca, New York, 14853-0001, UNITED STATES
| | - Alexander Lussenhop
- Cornell University, Physics Dept., Ithaca, New York, 14853-0001, UNITED STATES
| | - Sungsu Lee
- Cornell University, Physics Dept., Ithaca, New York, 14853-0001, UNITED STATES
| | - Kevin Tharratt
- Cornell University, Physics Dept., Ithaca, New York, 14853-0001, UNITED STATES
| | - Amrish Deshmukh
- Cornell University, Physics Dept., Ithaca, New York, 14853-0001, UNITED STATES
| | - Elisabeth M Sebesta
- Cornell University, Physics Dept., Ithaca, New York, 14853-0001, UNITED STATES
| | - Myron Zhang
- Cornell University, Physics Dept., Ithaca, New York, 14853-0001, UNITED STATES
| | - Sharon Lau
- Cornell University, Physics Dept., Ithaca, New York, 14853-0001, UNITED STATES
| | - Sarah Bennedsen
- Cornell University, Physics Dept., Ithaca, New York, 14853-0001, UNITED STATES
| | - Jared Ginsberg
- Cornell University, Physics Dept., Ithaca, New York, 14853-0001, UNITED STATES
| | - Timothy Campbell
- Cornell University, Physics Dept., Ithaca, New York, 14853-0001, UNITED STATES
| | - Chenzheng Wang
- Cornell University, Physics Dept., Ithaca, New York, 14853-0001, UNITED STATES
| | - Carl Franck
- Physics, Cornell University, Clark Hall, Ithaca, New York, 14853-0001, UNITED STATES
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Hopkins A, Camley BA. Leader cells in collective chemotaxis: Optimality and trade-offs. Phys Rev E 2019; 100:032417. [PMID: 31639926 DOI: 10.1103/physreve.100.032417] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2019] [Indexed: 11/06/2022]
Abstract
Clusters of cells can work together in order to follow a signal gradient, chemotaxing even when single cells do not. Cells in different regions of collectively migrating neural crest streams show different gene expression profiles, suggesting that cells may specialize to leader and follower roles. We use a minimal mathematical model to understand when this specialization is advantageous. In our model, leader cells sense the gradient with an accuracy that depends on the kinetics of ligand-receptor binding, while follower cells follow the cluster's direction with a finite error. Intuitively, specialization into leaders and followers should be optimal when a few cells have more information than the rest of the cluster, such as in the presence of a sharp transition in chemoattractant concentration. We do find this-but also find that high levels of specialization can be optimal in the opposite limit of very shallow gradients. We also predict that the best location for leaders may not be at the front of the cluster. In following leaders, clusters may have to choose between speed and flexibility. Clusters with only a few leaders can take orders of magnitude more time to reorient than all-leader clusters.
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Affiliation(s)
- Austin Hopkins
- Department of Physics & Astronomy, Johns Hopkins University, Baltimore, Maryland 21218, USA
| | - Brian A Camley
- Department of Physics & Astronomy and Department of Biophysics, Johns Hopkins University, Baltimore, Maryland 21218, USA
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Camley BA. Collective gradient sensing and chemotaxis: modeling and recent developments. JOURNAL OF PHYSICS. CONDENSED MATTER : AN INSTITUTE OF PHYSICS JOURNAL 2018; 30:223001. [PMID: 29644981 PMCID: PMC6252055 DOI: 10.1088/1361-648x/aabd9f] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2023]
Abstract
Cells measure a vast variety of signals, from their environment's stiffness to chemical concentrations and gradients; physical principles strongly limit how accurately they can do this. However, when many cells work together, they can cooperate to exceed the accuracy of any single cell. In this topical review, I will discuss the experimental evidence showing that cells collectively sense gradients of many signal types, and the models and physical principles involved. I also propose new routes by which experiments and theory can expand our understanding of these problems.
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Affiliation(s)
- Brian A Camley
- Departments of Physics & Astronomy and Biophysics, Johns Hopkins University, Baltimore, MD, United States of America
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Camley BA, Rappel WJ. Cell-to-cell variation sets a tissue-rheology-dependent bound on collective gradient sensing. Proc Natl Acad Sci U S A 2017; 114:E10074-E10082. [PMID: 29114053 PMCID: PMC5703308 DOI: 10.1073/pnas.1712309114] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
When a single cell senses a chemical gradient and chemotaxes, stochastic receptor-ligand binding can be a fundamental limit to the cell's accuracy. For clusters of cells responding to gradients, however, there is a critical difference: Even genetically identical cells have differing responses to chemical signals. With theory and simulation, we show collective chemotaxis is limited by cell-to-cell variation in signaling. We find that when different cells cooperate, the resulting bias can be much larger than the effects of ligand-receptor binding. Specifically, when a strongly responding cell is at one end of a cell cluster, cluster motion is biased toward that cell. These errors are mitigated if clusters average measurements over times long enough for cells to rearrange. In consequence, fluid clusters are better able to sense gradients: We derive a link between cluster accuracy, cell-to-cell variation, and the cluster rheology. Because of this connection, increasing the noisiness of individual cell motion can actually increase the collective accuracy of a cluster by improving fluidity.
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Affiliation(s)
- Brian A Camley
- Department of Physics and Astronomy, Johns Hopkins University, Baltimore, MD 21218;
- Department of Biophysics, Johns Hopkins University, Baltimore, MD 21218
- Department of Physics, University of California, San Diego, La Jolla, CA 92093
| | - Wouter-Jan Rappel
- Department of Physics, University of California, San Diego, La Jolla, CA 92093
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Kundu S. Stochastic modelling suggests that an elevated superoxide anion - hydrogen peroxide ratio can drive extravascular phagocyte transmigration by lamellipodium formation. J Theor Biol 2016; 407:143-154. [PMID: 27380944 DOI: 10.1016/j.jtbi.2016.07.002] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2016] [Accepted: 07/01/2016] [Indexed: 11/24/2022]
Abstract
Chemotaxis, integrates diverse intra- and inter-cellular molecular processes into a purposeful patho-physiological response; the operatic rules of which, remain speculative. Here, I surmise, that superoxide anion induced directional motility, in a responding cell, results from a quasi pathway between the stimulus, surrounding interstitium, and its biochemical repertoire. The epochal event in the mounting of an inflammatory response, is the extravascular transmigration of a phagocyte competent cell towards the site of injury, secondary to the development of a lamellipodium. This stochastic-to-markovian process conversion, is initiated by the cytosolic-ROS of the damaged cell, but is maintained by the inverse association of a de novo generated pool of self-sustaining superoxide anions and sub-critical hydrogen peroxide levels. Whilst, the exponential rise of O2(.-) is secondary to the focal accumulation of higher order lipid raft-Rac1/2-actin oligomers; O2(.-) mediated inactivation and redistribution of ECSOD, accounts for the minimal concentration of H2O2 that the phagocyte experiences. The net result of this reciprocal association between ROS/ RNS members, is the prolonged perturbation and remodeling of the cytoskeleton and plasma membrane, a prelude to chemotactic migration. The manuscript also describes the significance of stochastic modeling, in the testing of plausible molecular hypotheses of observable phenomena in complex biological systems.
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Affiliation(s)
- Siddhartha Kundu
- Department of Biochemistry, Dr. Baba Saheb Ambedkar Medical College & Hospital, Government of NCT Delhi, Sector - 6, Rohini, Delhi 110085, India; Mathematical and Computational Biology, Information Technology Research Academy (ITRA), Media Lab Asia, 2nd Floor, Block 2, C-DOT Campus, Mehrauli, New Delhi 110030, India; School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Mehrauli Road, New Delhi 110067, India.
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