Feedback-controlled dynamics of neuronal cells on directional surfaces

Descoteaux, Marc; Sunnerberg, Jacob P; Brady, Donovan D.; Staii, Cristian

doi:10.1016/j.bpj.2022.01.020

Cited by 5 publications

(46 citation statements)

References 53 publications

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“…Neurons respond to a variety of external cues during axonal outgrowth, and as a result, the growth cone generates traction forces that guide the axon. In previous work, we investigated axonal growth on micropatterned surfaces, and showed that axons follow external cues through a contact guidance mechanism, in which the growth cone detects environmental stimuli and adjusts its motion in response to geometrical and mechanical features present on the growth substrate [ 20 , 21 , 22 ].…”

Section: Discussionmentioning

confidence: 99%

“…Cortical neurons were cultured on poly acrylamide (PAA) substrates coated with poly D-lysine (PDL), at a density of 5000 cells/cm 2 . Neurons cultured at relatively low densities (in the range 3000–7000 cells/cm 2 ) are optimal for investigating axonal growth on surfaces with different mechanical, geometrical and biochemical properties, as previously reported [ 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 ]. The average elastic modulus measured by AFM for the PAA substrates used in this work was E S = (450 ± 50) Pa.…”

Section: Methodsmentioning

confidence: 99%

“…The brain tissue isolation protocol was approved by Tufts University Institutional Animal Care and Use Committee in accordance with the NIH Guide for the Care and Use of Laboratory Animals. For cell dissociation and culture, we used established protocols reported in our previous work [ 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 ]. Cortical neurons were cultured on poly acrylamide (PAA) substrates coated with poly D-lysine (PDL), at a density of 5000 cells/cm 2 .…”

Section: Methodsmentioning

confidence: 99%

“…To date, despite important recent advances, researchers still lack a fully quantitative description of growth dynamics, which incorporates the physical interactions between the neuron and the surrounding environment. In particular, there are still numerous basic unanswered questions about the mechanisms that determine neuron biomechanical behavior, such as neuron-substrate interactions, cellular response to various external cues, and how these interactions affect the formation and function of neuronal networks [ 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 ]. A detailed knowledge of these interactions is essential, because these stimuli together control the wiring of neuronal circuits and their function, from growth to homeostasis and cellular health.…”

Section: Introductionmentioning

confidence: 99%

“…This is a significant discovery, given that most of the reported mechanical measurements for neurons (and other types of cells) have been previously performed at room temperature, and not in physiologically relevant conditions. The combined AFM/fluorescence experiments show that changes in cellular volume and elastic modulus are greatly reduced if the activity of molecular motors inside the neurons is suppressed via treatment with Taxol and Blebbistatin, two substances that are known to inhibit the dynamics of the cell cytoskeleton [ 12 , 13 , 14 , 22 ]. These results demonstrate that the observed variations of these biomechanical parameters with temperature are due to changes in the activity of molecular motors, which in turn induce changes in the cytoskeletal network.…”

Section: Introductionmentioning

confidence: 99%

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Combined Traction Force–Atomic Force Microscopy Measurements of Neuronal Cells

2022

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In the course of the development of the nervous system, neuronal cells extend (grow) axons, which navigate over distances of the order of many cell diameters to reach target dendrites from other neurons and establish neuronal circuits. Some of the central challenges in biophysics today are to develop a quantitative model of axonal growth, which includes the interactions between the neurons and their growth environment, and to describe the complex architecture of neuronal networks in terms of a small number of physical variables. To address these challenges, researchers need new experimental techniques for measuring biomechanical interactions with very high force and spatiotemporal resolutions. Here we report a unique experimental approach that integrates three different high-resolution techniques on the same platform—traction force microscopy (TFM), atomic force microscopy (AFM) and fluorescence microscopy (FM)—to measure biomechanical properties of cortical neurons. To our knowledge, this is the first literature report of combined TFM/AFM/FM measurements performed for any type of cell. Using this combination of powerful experimental techniques, we perform high-resolution measurements of the elastic modulus for cortical neurons and relate these values with traction forces exerted by the cells on the growth substrate (poly acrylamide hydrogels, or PAA, coated with poly D-lysine). We obtain values for the traction stresses exerted by the cortical neurons in the range 30–70 Pa, and traction forces in the range 5–11 nN. Our results demonstrate that neuronal cells stiffen when axons exert forces on the PAA substrate, and that neuronal growth is governed by a contact guidance mechanism, in which axons are guided by external mechanical cues. This work provides new insights for bioengineering novel biomimetic platforms that closely model neuronal growth in vivo, and it has significant impact for creating neuroprosthetic interfaces and devices for neuronal growth and regeneration.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Combined Traction Force–Atomic Force Microscopy Measurements of Neuronal Cells

2022

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Unidirectional diphenylalanine nanotubes for dynamically guiding neurite outgrowth

Zu¹,

Shi²,

Jia³

et al. 2022

Biomed. Mater.

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Neural networks have been cultured in vitro to investigate brain functions and diseases, clinical treatments for brain damage, and device development. However, it remains challenging to form complex neural network structures with desired orientations and connections in vitro. Here, we introduce a dynamic strategy by using diphenylalanine (FF) nanotubes for controlling physical patterns on a substrate to regulate neurite-growth orientation in cultivating neural networks. Parallel FF nanotube patterns guide neurons to develop neurites through the unidirectional FF nanotubes while restricting their polarization direction. Subsequently, the FF nanotubes disassemble and the restriction of neurites disappear, and secondary neurite development of the neural network occurs in other direction. Experiments were conducted that use the hippocampal neurons, and the results demonstrated that the cultured neural networks by using the proposed dynamic approach can form a significant cross-connected structure with substantially more lateral neural connections than static substrates. The proposed dynamic approach for neurite outgrowing enables the construction of oriented innervation and cross-connected neural networks in vitro and may explore the way for the bio-fabrication of highly complex structures in tissue engineering.

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A new view of axon growth and guidance grounded in the stochastic dynamics of actin networks

et al. 2023

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The mechanism of axon growth and guidance is a core, unsolved problem in neuroscience and cell biology. For nearly three decades, our view of this process has largely been based on deterministic models of motility derived from studies of neurons cultured in vitro on rigid substrates. Here, we suggest a fundamentally different, inherently probabilistic model of axon growth, one that is grounded in the stochastic dynamics of actin networks. This perspective is motivated and supported by a synthesis of results from live imaging of a specific axon growing in its native tissue in vivo , together with single-molecule computational simulations of actin dynamics. In particular, we show how axon growth arises from a small spatial bias in the intrinsic fluctuations of the axonal actin cytoskeleton, one that produces net translocation of the axonal actin network by differentially modulating local probabilities of network expansion versus compaction. We discuss the relationship between this model and current views of axon growth and guidance mechanism and demonstrate how it offers explanations for various longstanding puzzles in this field. We further point out the implications of the probabilistic nature of actin dynamics for many other processes of cell morphology and motility.

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Feedback-controlled dynamics of neuronal cells on directional surfaces

Cited by 5 publications

References 53 publications

Combined Traction Force–Atomic Force Microscopy Measurements of Neuronal Cells

Combined Traction Force–Atomic Force Microscopy Measurements of Neuronal Cells

Unidirectional diphenylalanine nanotubes for dynamically guiding neurite outgrowth

A new view of axon growth and guidance grounded in the stochastic dynamics of actin networks

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