Mem3DG: modeling membrane mechanochemical dynamics in 3D using discrete differential geometry

Zhu, Cuncheng; Lee, Christopher T.; Rangamani, Padmini

doi:10.1016/j.bpj.2021.11.2371

Cited by 7 publications

(6 citation statements)

References 134 publications

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“…71 However, relaxation of the assumption of axisymmetry in tubulation would be necessary to investigate how forces and proteins may interact. 71–73 In summary, we expect that the findings from our work will motivate the development of these future efforts and gain a deeper understanding of how membrane tubes form under different biophysical conditions.…”

Section: Discussionmentioning

confidence: 77%

Formation of protein-mediated bilayer tubes is governed by a snapthrough transition

Mahapatra

Rangamani

2023

Soft Matter

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Section: Discussionmentioning

confidence: 77%

Formation of protein-mediated bilayer tubes is governed by a snapthrough transition

Mahapatra

Rangamani

2023

Soft Matter

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“…Given the limitations of our data sets it is not reasonable to expect either model’s predictions to capture actual membrane shape. Further, the absence of data in these regions hints at the possibility that energy-minimizing shapes for these parameter combinations may not exist or different computational schemes may be needed to solve these equations ( 7, 69, 70 ). A second more subtle difference between the predictions of the models is the edges in the phase maps which do not precisely align.…”

Section: Resultsmentioning

confidence: 99%

Modeling membrane curvature generation using mechanics and machine learning

Malingen

Rangamani

2022

Preprint

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The deformation of cellular membranes regulates trafficking processes, such as exocytosis and endocytosis. Classically, the Helfrich continuum model is used to characterize the forces and mechanical parameters that cells tune to accomplish membrane shape changes. While this classical model effectively captures curvature generation, one of the core challenges in using it to approximate a biological process is selecting a set of mechanical parameters (including bending modulus and membrane tension) from a large set of reasonable values. We used the Helfrich model to generate a large synthetic dataset from a random sampling of realistic mechanical parameters and used this dataset to train machine learning models. These models produced promising results, accurately classifying model behavior and predicting membrane shape from mechanical parameters. We also note emerging methods in machine learning that can leverage the physical insight of the Helfrich model to improve performance and draw greater insight into how cells control membrane shape change.

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“…A key challenge in membrane biomechanics problems is energy minimization associated with mechanical equilibrium. Traditionally, we minimize the membrane energy using the principle of virtual work to obtain the shape of the membrane in response to induced curvatures and external forces [26,[93][94][95][96][97][98]. Here, we adopt an approach to solve the inverse problem.…”

Section: Numerical Implementationmentioning

confidence: 99%

Effective cell membrane tension protects red blood cells against malaria invasion

Alimohamadi,

Rangamani

2023

PLoS Comput Biol

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A critical step in how malaria parasites invade red blood cells (RBCs) is the wrapping of the membrane around the egg-shaped merozoites. Recent experiments have revealed that RBCs can be protected from malaria invasion by high membrane tension. While cellular and biochemical aspects of parasite actomyosin motor forces during the malaria invasion have been well studied, the important role of the biophysical forces induced by the RBC membrane-cytoskeleton composite has not yet been fully understood. In this study, we use a theoretical model for lipid bilayer mechanics, cytoskeleton deformation, and membrane-merozoite interactions to systematically investigate the influence of effective RBC membrane tension, which includes contributions from the lipid bilayer tension, spontaneous tension, interfacial tension, and the resistance of cytoskeleton against shear deformation on the progression of membrane wrapping during the process of malaria invasion. Our model reveals that this effective membrane tension creates a wrapping energy barrier for a complete merozoite entry. We calculate the tension threshold required to impede the malaria invasion. We find that the tension threshold is a nonmonotonic function of spontaneous tension and undergoes a sharp transition from large to small values as the magnitude of interfacial tension increases. We also predict that the physical properties of the RBC cytoskeleton layer—particularly the resting length of the cytoskeleton—play key roles in specifying the degree of the membrane wrapping. We also found that the shear energy of cytoskeleton deformation diverges at the full wrapping state, suggesting the local disassembly of the cytoskeleton is required to complete the merozoite entry. Additionally, using our theoretical framework, we predict the landscape of myosin-mediated forces and the physical properties of the RBC membrane in regulating successful malaria invasion. Our findings on the crucial role of RBC membrane tension in inhibiting malaria invasion can have implications for developing novel antimalarial therapeutic or vaccine-based strategies.

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Mem3DG: modeling membrane mechanochemical dynamics in 3D using discrete differential geometry

Cited by 7 publications

References 134 publications

Formation of protein-mediated bilayer tubes is governed by a snapthrough transition

Formation of protein-mediated bilayer tubes is governed by a snapthrough transition

Modeling membrane curvature generation using mechanics and machine learning

Effective cell membrane tension protects red blood cells against malaria invasion

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