Cell dispersal by localized degradation of a chemoattractant.

Chemotaxis, the guided motion of cells by chemical gradients, plays a crucial role in many biological processes. In the social amoeba Dictyostelium discoideum, chemotaxis is critical for the formation of cell aggregates during starvation. The cells in these aggregates generate a pulse of the chemoattractant, cyclic adenosine 3',5'-monophosphate (cAMP), every 6 min to 10 min, resulting in surrounding cells moving toward the aggregate. In addition to periodic pulses of cAMP, the cells also secrete phosphodiesterase (PDE), which degrades cAMP and prevents the accumulation of the chemoattractant. Here we show that small aggregates of Dictyostelium can disperse, with cells moving away from instead of toward the aggregate. This surprising behavior often exhibited oscillatory cycles of motion toward and away from the aggregate. Furthermore, the onset of outward cell motion was associated with a doubling of the cAMP signaling period. Computational modeling suggests that this dispersal arises from a competition between secreted cAMP and PDE, creating a cAMP gradient that is directed away from the aggregate, resulting in outward cell motion. The model was able to predict the effect of PDE inhibition as well as global addition of exogenous PDE, and these predictions were subsequently verified in experiments. These results suggest that localized degradation of a chemoattractant is a mechanism for morphogenesis.

The mechanics and dynamics of cancer cells sensing noisy 3D contact guidance.

Contact guidance is a major physical cue that modulates cancer cell morphology and motility, and is directly linked to the prognosis of cancer patients. Under physiological conditions, particularly in the three-dimensional (3D) extracellular matrix (ECM), the disordered assembly of fibers presents a complex directional bias to the cells. It is unclear how cancer cells respond to these noncoherent contact guidance cues. Here we combine quantitative experiments, theoretical analysis, and computational modeling to study the morphological and migrational responses of breast cancer cells to 3D collagen ECM with varying degrees of fiber alignment. We quantify the strength of contact guidance using directional coherence of ECM fibers, and find that stronger contact guidance causes cells to polarize more strongly along the principal direction of the fibers. Interestingly, sensitivity to contact guidance is positively correlated with cell aspect ratio, with elongated cells responding more strongly to ECM alignment than rounded cells. Both experiments and simulations show that cell-ECM adhesions and actomyosin contractility modulate cell responses to contact guidance by inducing a population shift between rounded and elongated cells. We also find that cells rapidly change their morphology when navigating the ECM, and that ECM fiber coherence modulates cell transition rates between different morphological phenotypes. Taken together, we find that subcellular processes that integrate conflicting mechanical cues determine cell morphology, which predicts the polarization and migration dynamics of cancer cells in 3D ECM.

Annihilation dynamics during spiral defect chaos revealed by particle models.

Pair-annihilation events are ubiquitous in a variety of spatially extended systems and are often studied using computationally expensive simulations. Here, we develop an approach in which we simulate the pair-annihilation of spiral wave tips in cardiac models using a computationally efficient particle model. Spiral wave tips are represented as particles with dynamics governed by diffusive behavior and short-ranged attraction. The parameters for diffusion and attraction are obtained by comparing particle motion to the trajectories of spiral wave tips in cardiac models during spiral defect chaos. The particle model reproduces the annihilation rates of the cardiac models and can determine the statistics of spiral wave dynamics, including its mean termination time. We show that increasing the attraction coefficient sharply decreases the mean termination time, making it a possible target for pharmaceutical intervention.

A role for ethylene signaling and biosynthesis in regulating and accelerating CO2 - and abscisic acid-mediated stomatal movements in Arabidopsis.

Little is known about long-distance mesophyll-driven signals that regulate stomatal conductance. Soluble and/or vapor-phase molecules have been proposed. In this study, the involvement of the gaseous signal ethylene in the modulation of stomatal conductance in Arabidopsis thaliana by CO2 /abscisic acid (ABA) was examined. We present a diffusion model which indicates that gaseous signaling molecule/s with a shorter/direct diffusion pathway to guard cells are more probable for rapid mesophyll-dependent stomatal conductance changes. We, therefore, analyzed different Arabidopsis ethylene-signaling and biosynthesis mutants for their ethylene production and kinetics of stomatal responses to ABA/[CO2 ]-shifts. According to our research, higher [CO2 ] causes Arabidopsis rosettes to produce more ethylene. An ACC-synthase octuple mutant with reduced ethylene biosynthesis exhibits dysfunctional CO2 -induced stomatal movements. Ethylene-insensitive receptor (gain-of-function), etr1-1 and etr2-1, and signaling, ein2-5 and ein2-1, mutants showed intact stomatal responses to [CO2 ]-shifts, whereas loss-of-function ethylene receptor mutants, including etr2-3;ein4-4;ers2-3, etr1-6;etr2-3 and etr1-6, showed markedly accelerated stomatal responses to [CO2 ]-shifts. Further investigation revealed a significantly impaired stomatal closure to ABA in the ACC-synthase octuple mutant and accelerated stomatal responses in the etr1-6;etr2-3, and etr1-6, but not in the etr2-3;ein4-4;ers2-3 mutants. These findings suggest essential functions of ethylene biosynthesis and signaling components in tuning/accelerating stomatal conductance responses to CO2 and ABA.

Machine Learned Cellular Phenotypes in Cardiomyopathy Predict Sudden Death.

RATIONALE: Susceptibility to VT/VF (ventricular tachycardia/fibrillation) is difficult to predict in patients with ischemic cardiomyopathy either by clinical tools or by attempting to translate cellular mechanisms to the bedside. OBJECTIVE: To develop computational phenotypes of patients with ischemic cardiomyopathy, by training then interpreting machine learning of ventricular monophasic action potentials (MAPs) to reveal phenotypes that predict long-term outcomes. METHODS AND RESULTS: We recorded 5706 ventricular MAPs in 42 patients with coronary artery disease and left ventricular ejection fraction ≤40% during steady-state pacing. Patients were randomly allocated to independent training and testing cohorts in a 70:30 ratio, repeated K=10-fold. Support vector machines and convolutional neural networks were trained to 2 end points: (1) sustained VT/VF or (2) mortality at 3 years. Support vector machines provided superior classification. For patient-level predictions, we computed personalized MAP scores as the proportion of MAP beats predicting each end point. Patient-level predictions in independent test cohorts yielded c-statistics of 0.90 for sustained VT/VF (95% CI, 0.76-1.00) and 0.91 for mortality (95% CI, 0.83-1.00) and were the most significant multivariate predictors. Interpreting trained support vector machine revealed MAP morphologies that, using in silico modeling, revealed higher L-type calcium current or sodium-calcium exchanger as predominant phenotypes for VT/VF. CONCLUSIONS: Machine learning of action potential recordings in patients revealed novel phenotypes for long-term outcomes in ischemic cardiomyopathy. Such computational phenotypes provide an approach which may reveal cellular mechanisms for clinical outcomes and could be applied to other conditions.

Quantifying a spectrum of clinical response in atrial tachyarrhythmias using spatiotemporal synchronization of electrograms.

AIMS: There is a clinical spectrum for atrial tachyarrhythmias wherein most patients with atrial tachycardia (AT) and some with atrial fibrillation (AF) respond to ablation, while others do not. It is undefined if this clinical spectrum has pathophysiological signatures. This study aims to test the hypothesis that the size of spatial regions showing repetitive synchronized electrogram (EGM) shapes over time reveals a spectrum from AT, to AF patients who respond acutely to ablation, to AF patients without acute response. METHODS AND RESULTS: We studied n = 160 patients (35% women, 65.0 ± 10.4 years) of whom (i) n = 75 had AF terminated by ablation propensity matched to (ii) n = 75 without AF termination and (iii) n = 10 with AT. All patients had mapping by 64-pole baskets to identify areas of repetitive activity (REACT) to correlate unipolar EGMs in shape over time. Synchronized regions (REACT) were largest in AT, smaller in AF termination, and smallest in non-termination cohorts (0.63 ± 0.15, 0.37 ± 0.22, and 0.22 ± 0.18, P < 0.001). Area under the curve for predicting AF termination in hold-out cohorts was 0.72 ± 0.03. Simulations showed that lower REACT represented greater variability in clinical EGM timing and shape. Unsupervised machine learning of REACT and extensive (50) clinical variables yielded four clusters of increasing risk for AF termination (P < 0.01, χ2), which were more predictive than clinical profiles alone (P < 0.001). CONCLUSION: The area of synchronized EGMs within the atrium reveals a spectrum of clinical response in atrial tachyarrhythmias. These fundamental EGM properties, which do not reflect any predetermined mechanism or mapping technology, predict outcome and offer a platform to compare mapping tools and mechanisms between AF patient groups.

The physics of heart rhythm disorders.

The global burden caused by cardiovascular disease is substantial, with heart disease representing the most common cause of death around the world. There remains a need to develop better mechanistic models of cardiac function in order to combat this health concern. Heart rhythm disorders, or arrhythmias, are one particular type of disease which has been amenable to quantitative investigation. Here we review the application of quantitative methodologies to explore dynamical questions pertaining to arrhythmias. We begin by describing single-cell models of cardiac myocytes, from which two and three dimensional models can be constructed. Special focus is placed on results relating to pattern formation across these spatially-distributed systems, especially the formation of spiral waves of activation. Next, we discuss mechanisms which can lead to the initiation of arrhythmias, focusing on the dynamical state of spatially discordant alternans, and outline proposed mechanisms perpetuating arrhythmias such as fibrillation. We then review experimental and clinical results related to the spatio-temporal mapping of heart rhythm disorders. Finally, we describe treatment options for heart rhythm disorders and demonstrate how statistical physics tools can provide insights into the dynamics of heart rhythm disorders.

Coupling traction force patterns and actomyosin wave dynamics reveals mechanics of cell motion.

Motile cells can use and switch between different modes of migration. Here, we use traction force microscopy and fluorescent labeling of actin and myosin to quantify and correlate traction force patterns and cytoskeletal distributions in Dictyostelium discoideum cells that move and switch between keratocyte-like fan-shaped, oscillatory, and amoeboid modes. We find that the wave dynamics of the cytoskeletal components critically determine the traction force pattern, cell morphology, and migration mode. Furthermore, we find that fan-shaped cells can exhibit two different propulsion mechanisms, each with a distinct traction force pattern. Finally, the traction force patterns can be recapitulated using a computational model, which uses the experimentally determined spatiotemporal distributions of actin and myosin forces and a viscous cytoskeletal network. Our results suggest that cell motion can be generated by friction between the flow of this network and the substrate.

Boolink: a graphical interface for open access Boolean network simulations and use in guard cell CO2 signaling.

Signaling networks are at the heart of almost all biological processes. Most of these networks contain large number of components, and often either the connections between these components are not known or the rate equations that govern the dynamics of soluble signaling components are not quantified. This uncertainty in network topology and parameters can make it challenging to formulate detailed mathematical models. Boolean networks, in which all components are either on or off, have emerged as viable alternatives to detailed mathematical models that contain rate constants and other parameters. Therefore, open-source platforms of Boolean models for community use are desirable. Here, we present Boolink, a freely available graphical user interface that allows users to easily construct and analyze existing Boolean networks. Boolink can be applied to any Boolean network. We demonstrate its application using a previously published network for abscisic acid (ABA)-driven stomatal closure in Arabidopsis spp. (Arabidopsis thaliana). We also show how Boolink can be used to generate testable predictions by extending the network to include CO2 regulation of stomatal movements. Predictions of the model were experimentally tested, and the model was iteratively modified based on experiments showing that ABA effectively closes Arabidopsis stomata at near-zero CO2 concentrations (1.5-ppm CO2). Thus, Boolink enables public generation and the use of existing Boolean models, including the prior developed ABA signaling model with added CO2 signaling components.

Identification of SLAC1 anion channel residues required for CO2/bicarbonate sensing and regulation of stomatal movements.

Increases in CO2 concentration in plant leaves due to respiration in the dark and the continuing atmospheric [CO2] rise cause closing of stomatal pores, thus affecting plant-water relations globally. However, the underlying CO2/bicarbonate (CO2/HCO3-) sensing mechanisms remain unknown. [CO2] elevation in leaves triggers stomatal closure by anion efflux mediated via the SLAC1 anion channel localized in the plasma membrane of guard cells. Previous reconstitution analysis has suggested that intracellular bicarbonate ions might directly up-regulate SLAC1 channel activity. However, whether such a CO2/HCO3- regulation of SLAC1 is relevant for CO2 control of stomatal movements in planta remains unknown. Here, we computationally probe for candidate bicarbonate-interacting sites within the SLAC1 anion channel via long-timescale Gaussian accelerated molecular dynamics (GaMD) simulations. Mutations of two putative bicarbonate-interacting residues, R256 and R321, impaired the enhancement of the SLAC1 anion channel activity by CO2/HCO3- in Xenopus oocytes. Mutations of the neighboring charged amino acid K255 and residue R432 and the predicted gate residue F450 did not affect HCO3- regulation of SLAC1. Notably, gas-exchange experiments with slac1-transformed plants expressing mutated SLAC1 proteins revealed that the SLAC1 residue R256 is required for CO2 regulation of stomatal movements in planta, but not for abscisic acid (ABA)-induced stomatal closing. Patch clamp analyses of guard cells show that activation of S-type anion channels by CO2/HCO3-, but not by ABA, was impaired, indicating the relevance of R256 for CO2 signal transduction. Together, these analyses suggest that the SLAC1 anion channel is one of the physiologically relevant CO2/HCO3- sensors in guard cells.

Termination of persistent atrial fibrillation by ablating sites that control large atrial areas.

AIMS: Persistent atrial fibrillation (AF) has been explained by multiple mechanisms which, while they conflict, all agree that more disorganized AF is more difficult to treat than organized AF. We hypothesized that persistent AF consists of interacting organized areas which may enlarge, shrink or coalesce, and that patients whose AF areas enlarge by ablation are more likely to respond to therapy. METHODS AND RESULTS: We mapped vectorial propagation in persistent AF using wavefront fields (WFF), constructed from raw unipolar electrograms at 64-pole basket catheters, during ablation until termination (Group 1, N = 20 patients) or cardioversion (Group 2, N = 20 patients). Wavefront field mapping of patients (age 61.1 ± 13.2 years, left atrium 47.1 ± 6.9 mm) at baseline showed 4.6 ± 1.0 organized areas, each separated by disorganization. Ablation of sites that led to termination controlled larger organized area than competing sites (44.1 ± 11.1% vs. 22.4 ± 7.0%, P < 0.001). In Group 1, ablation progressively enlarged unablated areas (rising from 32.2 ± 15.7% to 44.1 ± 11.1% of mapped atrium, P < 0.0001). In Group 2, organized areas did not enlarge but contracted during ablation (23.6 ± 6.3% to 15.2 ± 5.6%, P < 0.0001). CONCLUSION: Mapping wavefront vectors in persistent AF revealed competing organized areas. Ablation that progressively enlarged remaining areas was acutely successful, and sites where ablation terminated AF were surrounded by large organized areas. Patients in whom large organized areas did not emerge during ablation did not exhibit AF termination. Further studies should define how fibrillatory activity is organized within such areas and whether this approach can guide ablation.

Cell-to-cell variation sets a tissue-rheology-dependent bound on collective gradient sensing.

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.

Reconstitution of CO2 Regulation of SLAC1 Anion Channel and Function of CO2-Permeable PIP2;1 Aquaporin as CARBONIC ANHYDRASE4 Interactor.

Dark respiration causes an increase in leaf CO2 concentration (Ci), and the continuing increases in atmospheric [CO2] further increases Ci. Elevated leaf CO2 concentration causes stomatal pores to close. Here, we demonstrate that high intracellular CO2/HCO3 (-) enhances currents mediated by the Arabidopsis thaliana guard cell S-type anion channel SLAC1 upon coexpression of any one of the Arabidopsis protein kinases OST1, CPK6, or CPK23 in Xenopus laevis oocytes. Split-ubiquitin screening identified the PIP2;1 aquaporin as an interactor of the ßCA4 carbonic anhydrase, which was confirmed in split luciferase, bimolecular fluorescence complementation, and coimmunoprecipitation experiments. PIP2;1 exhibited CO2 permeability. Mutation of PIP2;1 in planta alone was insufficient to impair CO2- and abscisic acid-induced stomatal closing, likely due to redundancy. Interestingly, coexpression of ßCA4 and PIP2;1 with OST1-SLAC1 or CPK6/23-SLAC1 in oocytes enabled extracellular CO2 enhancement of SLAC1 anion channel activity. An inactive PIP2;1 point mutation was identified that abrogated water and CO2 permeability and extracellular CO2 regulation of SLAC1 activity. These findings identify the CO2-permeable PIP2;1 as key interactor of ßCA4 and demonstrate functional reconstitution of extracellular CO2 signaling to ion channel regulation upon coexpression of PIP2;1, ßCA4, SLAC1, and protein kinases. These data further implicate SLAC1 as a bicarbonate-responsive protein contributing to CO2 regulation of S-type anion channels.

Cell motility dependence on adhesive wetting.

Adhesive cell-substrate interactions are crucial for cell motility and are responsible for the necessary traction that propels cells. These interactions can also change the shape of the cell, analogous to liquid droplet wetting on adhesive substrates. To address how these shape changes affect cell migration and cell speed we model motility using deformable, 2D cross-sections of cells in which adhesion and frictional forces between cell and substrate can be varied separately. Our simulations show that increasing the adhesion results in increased spreading of cells and larger cell speeds. We propose an analytical model which shows that the cell speed is inversely proportional to an effective height of the cell and that increasing this height results in increased internal shear stress. The numerical and analytical results are confirmed in experiments on motile eukaryotic cells.

Contact inhibition of locomotion determines cell-cell and cell-substrate forces in tissues.

Cells organized in tissues exert forces on their neighbors and their environment. Those cellular forces determine tissue homeostasis as well as reorganization during embryonic development and wound healing. To understand how cellular forces are generated and how they can influence the tissue state, we develop a particle-based simulation model for adhesive cell clusters and monolayers. Cells are contractile, exert forces on their substrate and on each other, and interact through contact inhibition of locomotion (CIL), meaning that cell-cell contacts suppress force transduction to the substrate and propulsion forces align away from neighbors. Our model captures the traction force patterns of small clusters of nonmotile cells and larger sheets of motile Madin-Darby canine kidney (MDCK) cells. In agreement with observations in a spreading MDCK colony, the cell density in the center increases as cells divide and the tissue grows. A feedback between cell density, CIL, and cell-cell adhesion gives rise to a linear relationship between cell density and intercellular tensile stress and forces the tissue into a nonmotile state characterized by a broad distribution of traction forces. Our model also captures the experimentally observed tissue flow around circular obstacles, and CIL accounts for traction forces at the edge.

Minimal Network Topologies for Signal Processing during Collective Cell Chemotaxis.

Cell-cell communication plays an important role in collective cell migration. However, it remains unclear how cells in a group cooperatively process external signals to determine the group's direction of motion. Although the topology of signaling pathways is vitally important in single-cell chemotaxis, the signaling topology for collective chemotaxis has not been systematically studied. Here, we combine mathematical analysis and simulations to find minimal network topologies for multicellular signal processing in collective chemotaxis. We focus on border cell cluster chemotaxis in the Drosophila egg chamber, in which responses to several experimental perturbations of the signaling network are known. Our minimal signaling network includes only four elements: a chemoattractant, the protein Rac (indicating cell activation), cell protrusion, and a hypothesized global factor responsible for cell-cell interaction. Experimental data on cell protrusion statistics allows us to systematically narrow the number of possible topologies from more than 40,000,000 to only six minimal topologies with six interactions between the four elements. This analysis does not require a specific functional form of the interactions, and only qualitative features are needed; it is thus robust to many modeling choices. Simulations of a stochastic biochemical model of border cell chemotaxis show that the qualitative selection procedure accurately determines which topologies are consistent with the experiment. We fit our model for all six proposed topologies; each produces results that are consistent with all experimentally available data. Finally, we suggest experiments to further discriminate possible pathway topologies.

Two Independent Mapping Techniques Identify Rotational Activity Patterns at Sites of Local Termination During Persistent Atrial Fibrillation.

INTRODUCTION: The mechanisms for atrial fibrillation (AF) are unclear in part because diverse mapping techniques yield diverse maps, ranging from stable organized sources to highly disordered waves. We hypothesized that AF mechanisms may be clarified if mapping techniques were compared in the same patients, and referenced to a clinical endpoint. We compared two independent AF mapping techniques in patients in whom ablation terminated persistent AF before pulmonary vein isolation (PVI). METHODS AND RESULTS: We identified 12 patients with persistent AF (61.2 ± 10.8 years, four female) in whom mapping with 64 pole baskets and technique 1 (activation/phase mapping, FIRM) identified rotational activation patterns during at least 50% of the 4-second mapping interval and targeted ablation at these rotational sites terminated AF to sinus rhythm (n = 10) or atrial tachycardia. We analyzed the unipolar electrograms of these patients to determine phase maps of activation by an independent technique 2 (Kuklik, Schotten et al., IEEE Trans Biomed Eng 2015). Compared to technique 1, technique 2 revealed a source in 12 of 12 (100%) cases with spatial concordance in all cases (P <0.05) and similar rotational characteristics. CONCLUSION: At sites where ablation terminated persistent AF, two independent mapping techniques identified stable rotational activation for multiple cycles that drove peripheral disorder. Future comparative studies referenced to a clinical endpoint may help reconcile if discrepancies between AF mapping studies reports represent techniques, patient populations or models of AF, and improve mapping to better guide ablation.

Rotors exhibit greater surface ECG variation during ventricular fibrillation than focal sources due to wavebreak, secondary rotors, and meander.

INTRODUCTION: Ventricular fibrillation is a common life-threatening arrhythmia. The ECG of VF appears chaotic but may allow identification of sustaining mechanisms to guide therapy. HYPOTHESIS: We hypothesized that rotors and focal sources manifest distinct features on the ECG, and computational modeling may identify mechanisms of such features. METHODS: VF induction was attempted in 31 patients referred for ventricular arrhythmia ablation. Simultaneous surface ECG and intracardiac electrograms were recorded using biventricular basket catheters. Endocardial phase maps were used to mechanistically classify each VF cycle as rotor or focally driven. ECGs were analyzed from patients demonstrating both mechanisms in the primary analysis and from all patients with induced VF in the secondary analysis. The ECG voltage variation during each mechanism was compared. Biventricular computer simulations of VF driven by focal sources or rotors were created and resulting ECGs of each VF mechanism were compared. RESULTS: Rotor-based VF exhibited greater voltage variation than focal source-based VF in both the primary analysis (n = 8, 110 ± 24% vs. 55 ± 32%, P = 0.02) and the secondary analysis (n = 18, 103 ± 30% vs. 67 ± 34%, P = 0.009). Computational VF simulations also revealed greater voltage variation in rotors compared to focal sources (110 ± 19% vs. 33 ± 16%, P = 0.001), and demonstrated that this variation was due to wavebreak, secondary rotor initiation, and rotor meander. CONCLUSION: Clinical and computational studies reveal that quantitative criteria of ECG voltage variation differ significantly between VF-sustaining rotors and focal sources, and provide insight into the mechanisms of such variation. Future studies should prospectively evaluate if these criteria can separate clinical VF mechanisms and guide therapy.

Collective Signal Processing in Cluster Chemotaxis: Roles of Adaptation, Amplification, and Co-attraction in Collective Guidance.

Single eukaryotic cells commonly sense and follow chemical gradients, performing chemotaxis. Recent experiments and theories, however, show that even when single cells do not chemotax, clusters of cells may, if their interactions are regulated by the chemoattractant. We study this general mechanism of "collective guidance" computationally with models that integrate stochastic dynamics for individual cells with biochemical reactions within the cells, and diffusion of chemical signals between the cells. We show that if clusters of cells use the well-known local excitation, global inhibition (LEGI) mechanism to sense chemoattractant gradients, the speed of the cell cluster becomes non-monotonic in the cluster's size-clusters either larger or smaller than an optimal size will have lower speed. We argue that the cell cluster speed is a crucial readout of how the cluster processes chemotactic signals; both amplification and adaptation will alter the behavior of cluster speed as a function of size. We also show that, contrary to the assumptions of earlier theories, collective guidance does not require persistent cell-cell contacts and strong short range adhesion. If cell-cell adhesion is absent, and the cluster cohesion is instead provided by a co-attraction mechanism, e.g. chemotaxis toward a secreted molecule, collective guidance may still function. However, new behaviors, such as cluster rotation, may also appear in this case. Co-attraction and adaptation allow for collective guidance that is robust to varying chemoattractant concentrations while not requiring strong cell-cell adhesion.