Chemotaxis: a feedback-based computational model robustly predicts multiple aspects of real cell behaviour

The mechanism of eukaryotic chemotaxis remains unclear despite intensive study. The most frequently described mechanism acts through attractants causing actin polymerization, in turn leading to pseudopod formation and cell movement. We recently proposed an alternative mechanism, supported by several lines of data, in which pseudopods are made by a self-generated cycle. If chemoattractants are present, they modulate the cycle rather than directly causing actin polymerization. The aim of this work is to test the explanatory and predictive powers of such pseudopod-based models to predict the complex behaviour of cells in chemotaxis. We have now tested the effectiveness of this mechanism using a computational model of cell movement and chemotaxis based on pseudopod autocatalysis. The model reproduces a surprisingly wide range of existing data about cell movement and chemotaxis. It simulates cell polarization and persistence without stimuli and selection of accurate pseudopods when chemoattractant gradients are present. It predicts both bias of pseudopod position in low chemoattractant gradients and-unexpectedly-lateral pseudopod initiation in high gradients. To test the predictive ability of the model, we looked for untested and novel predictions. One prediction from the model is that the angle between successive pseudopods at the front of the cell will increase in proportion to the difference between the cell's direction and the direction of the gradient. We measured the angles between pseudopods in chemotaxing Dictyostelium cells under different conditions and found the results agreed with the model extremely well. Our model and data together suggest that in rapidly moving cells like Dictyostelium and neutrophils an intrinsic pseudopod cycle lies at the heart of cell motility. This implies that the mechanism behind chemotaxis relies on modification of intrinsic pseudopod behaviour, more than generation of new pseudopods or actin polymerization by chemoattractant

C3 Peptide Promotes Axonal Regeneration and Functional Motor Recovery after Peripheral Nerve Injury

Peripheral nerve injuries are frequently seen in trauma patients and due to delayed nerve repair, lifelong disabilities often follow this type of injury. Innovative therapies are needed to facilitate and expedite peripheral nerve regeneration. The purpose of this study was to determine the effects of a 1-time topical application of a 26-amino-acid fragment (C3156-181), derived from the Clostridium botulinum C3-exoenzyme, on peripheral nerve regeneration in 2 models of nerve injury and repair in adult rats. After sciatic nerve crush, different dosages of C3156-181 dissolved in buffer or reference solutions (nerve growth factor or C3bot-wild-type protein) or vehicle-only were injected through an epineurial opening into the lesion sites. After 10-mm nerve autotransplantation, either 8.0 nmol/kg C3156-181 or vehicle were injected into the proximal and distal suture sites. For a period of 3 to 10 postoperative weeks, C3156-181-treated animals showed a faster motor recovery than control animals. After crush injury, axonal outgrowth and elongation were activated and consequently resulted in faster motor recovery. The nerve autotransplantation model further elucidated that C3156-181 treatment accounts for better axonal elongation into motor targets and reduced axonal sprouting, which are followed by enhanced axonal maturation and better axonal functionality. The effects of C3156-181 are likely caused by a nonenzymatic down-regulation of active RhoA. Our results indicate the potential of C3156-181 as a therapeutic agent for the topical treatment of peripheral nerve repair sites

An Excitable Cortex and Memory Model Successfully Predicts New Pseudopod Dynamics

Motile eukaryotic cells migrate with directional persistence by alternating left and right turns, even in the absence of external cues. For example, Dictyostelium discoideum cells crawl by extending distinct pseudopods in an alternating right-left pattern. The mechanisms underlying this zig-zag behavior, however, remain unknown. Here we propose a new Excitable Cortex and Memory (EC&M) model for understanding the alternating, zig-zag extension of pseudopods. Incorporating elements of previous models, we consider the cell cortex as an excitable system and include global inhibition of new pseudopods while a pseudopod is active. With the novel hypothesis that pseudopod activity makes the local cortex temporarily more excitable – thus creating a memory of previous pseudopod locations – the model reproduces experimentally observed zig-zag behavior. Furthermore, the EC&M model makes four new predictions concerning pseudopod dynamics. To test these predictions we develop an algorithm that detects pseudopods via hierarchical clustering of individual membrane extensions. Data from cell-tracking experiments agrees with all four predictions of the model, revealing that pseudopod placement is a non-Markovian process affected by the dynamics of previous pseudopods. The model is also compatible with known limits of chemotactic sensitivity. In addition to providing a predictive approach to studying eukaryotic cell motion, the EC&M model provides a general framework for future models, and suggests directions for new research regarding the molecular mechanisms underlying directional persistence

Streaming instability of slime mold amoebae: An analytical model

During the aggregation of amoebae of the cellular slime mould Dictyostelium, the interaction of chemical waves of the signaling molecule cAMP with cAMP-directed cell movement causes the breakup of a uniform cell layer into branching patterns of cell streams. Recent numerical and experimental investigations emphasize the pivotal role of the cell-density dependence of the chemical wave speed for the occurrence of the streaming instability. A simple, analytically tractable, model of Dictyostelium aggregation is developed to test this idea. The interaction of cAMP waves with cAMP-directed cell movement is studied in the form of coupled dynamics of wave front geometries and cell density. Comparing the resulting explicit instability criterion and dispersion relation for cell streaming with the previous findings of model simulations and numerical stability analyses, a unifying interpretation of the streaming instability as a cAMP wave-driven chemotactic instability is proposed

Transmethylation inhibitors decrease chemotactic sensitivity and delay cell aggregation in Dictyostelium discoideum

In Dictyostelium discoideum, extracellular cyclic AMP (cAMP) induces chemotaxis and cell aggregation. Suspensions of cAMP-sensitive cells respond to a cAMP pulse with a rapid, transient increase of protein carboxyl methylation. The transmethylation inhibitors cycloleucine, L-homocysteine thiolactone, and coformycin decrease chemotactic sensitivity and delay cell aggregation when administered in concentrations which do not influence cAMP binding to cell surface receptors or the activity of total phosphodiesterase. The ability of the drugs to inhibit chemotaxis could be correlated with their capacity to convert the initial transient positive response of carboxyl methylation to cAMP into a negative one. This suggests that both protein O-methyltransferase and protein methylesterase are activated after stimulation of aggregative cells with cAMP, the net effect being a transient, positive response of methylation. In the presence of a sufficiently large dose of inhibitor, methyltransferase is inhibited, whereas methylesterase activity is much less affected, so that a transient negative response of methylation to cAMP is observed. The slow, positive response of carboxyl methylation to cAMP which occurs ca. 2.5 to 5 min after stimulus administration is not affected by inhibitors of transmethylation. These results suggest that methylation reactions are involved in the chemotactic response of D. discoideum cells to cAMP

External Quality Assessment on Molecular Tumor Profiling with Circulating Tumor DNA-Based Methodologies Routinely Used in Clinical Pathology within the COIN Consortium

BackgroundIdentification of tumor-derived variants in circulating tumor DNA (ctDNA) has potential as a sensitive and reliable surrogate for tumor tissue-based routine diagnostic testing. However, variations in pre(analytical) procedures affect the efficiency of ctDNA recovery. Here, an external quality assessment (EQA) was performed to determine the performance of ctDNA mutation detection work flows that are used in current diagnostic settings across laboratories within the Dutch COIN consortium (ctDNA on the road to implementation in The Netherlands).MethodsAliquots of 3 high-volume diagnostic leukapheresis (DLA) plasma samples and 3 artificial reference plasma samples with predetermined mutations were distributed among 16 Dutch laboratories. Participating laboratories were requested to perform ctDNA analysis for BRAF exon 15, EGFR exon 18–21, and KRAS exon 2–3 using their regular circulating cell-free DNA (ccfDNA) analysis work flow. Laboratories were assessed based on adherence to the study protocol, overall detection rate, and overall genotyping performance.ResultsA broad range of preanalytical conditions (e.g., plasma volume, elution volume, and extraction methods) and analytical methodologies (e.g., droplet digital PCR [ddPCR], small-panel PCR assays, and next-generation sequencing [NGS]) were used. Six laboratories (38%) had a performance score of >0.90; all other laboratories scored between 0.26 and 0.80. Although 13 laboratories (81%) reached a 100% overall detection rate, the therapeutically relevant EGFR p.(S752_I759del) (69%), EGFR p.(N771_H773dup) (50%), and KRAS p.(G12C) (48%) mutations were frequently not genotyped accurately.ConclusionsDivergent (pre)analytical protocols could lead to discrepant clinical outcomes when using the same plasma samples. Standardization of (pre)analytical work flows can facilitate the implementation of reproducible liquid biopsy testing in the clinical routine

A Stochastic Description of Dictyostelium Chemotaxis

Chemotaxis, the directed motion of a cell toward a chemical source, plays a key role in many essential biological processes. Here, we derive a statistical model that quantitatively describes the chemotactic motion of eukaryotic cells in a chemical gradient. Our model is based on observations of the chemotactic motion of the social ameba Dictyostelium discoideum, a model organism for eukaryotic chemotaxis. A large number of cell trajectories in stationary, linear chemoattractant gradients is measured, using microfluidic tools in combination with automated cell tracking. We describe the directional motion as the interplay between deterministic and stochastic contributions based on a Langevin equation. The functional form of this equation is directly extracted from experimental data by angle-resolved conditional averages. It contains quadratic deterministic damping and multiplicative noise. In the presence of an external gradient, the deterministic part shows a clear angular dependence that takes the form of a force pointing in gradient direction. With increasing gradient steepness, this force passes through a maximum that coincides with maxima in both speed and directionality of the cells. The stochastic part, on the other hand, does not depend on the orientation of the directional cue and remains independent of the gradient magnitude. Numerical simulations of our probabilistic model yield quantitative agreement with the experimental distribution functions. Thus our model captures well the dynamics of chemotactic cells and can serve to quantify differences and similarities of different chemotactic eukaryotes. Finally, on the basis of our model, we can characterize the heterogeneity within a population of chemotactic cells