Nonlinear Growth Dynamics of Neuronal Cells Cultured on Directional Surfaces

During the development of the nervous system, neuronal cells extend axons and dendrites that form complex neuronal networks, which are essential for transmitting and processing information. Understanding the physical processes that underlie the formation of neuronal networks is essential for gaining a deeper insight into higher-order brain functions such as sensory processing, learning, and memory. In the process of creating networks, axons travel towards other recipient neurons, directed by a combination of internal and external cues that include genetic instructions, biochemical signals, as well as external mechanical and geometrical stimuli. Although there have been significant recent advances, the basic principles governing axonal growth, collective dynamics, and the development of neuronal networks remain poorly understood. In this paper, we present a detailed analysis of nonlinear dynamics for axonal growth on surfaces with periodic geometrical patterns. We show that axonal growth on these surfaces is described by nonlinear Langevin equations with speed-dependent deterministic terms and gaussian stochastic noise. This theoretical model yields a comprehensive description of axonal growth at both intermediate and long time scales (tens of hours after cell plating), and predicts key dynamical parameters, such as speed and angular correlation functions, axonal mean squared lengths, and diffusion (cell motility) coefficients. We use this model to perform simulations of axonal trajectories on the growth surfaces, in turn demonstrating very good agreement between simulated growth and the experimental results. These results provide important insights into the current understanding of the dynamical behavior of neurons, the self-wiring of the nervous system, as well as for designing innovative biomimetic neural network models.

Biased Random Walk Model of Neuronal Dynamics on Substrates with Periodic Geometrical Patterns

Neuronal networks are complex systems of interconnected neurons responsible for transmitting and processing information throughout the nervous system. The building blocks of neuronal networks consist of individual neurons, specialized cells that receive, process, and transmit electrical and chemical signals throughout the body. The formation of neuronal networks in the developing nervous system is a process of fundamental importance for understanding brain activity, including perception, memory, and cognition. To form networks, neuronal cells extend long processes called axons, which navigate toward other target neurons guided by both intrinsic and extrinsic factors, including genetic programming, chemical signaling, intercellular interactions, and mechanical and geometrical cues. Despite important recent advances, the basic mechanisms underlying collective neuron behavior and the formation of functional neuronal networks are not entirely understood. In this paper, we present a combined experimental and theoretical analysis of neuronal growth on surfaces with micropatterned periodic geometrical features. We demonstrate that the extension of axons on these surfaces is described by a biased random walk model, in which the surface geometry imparts a constant drift term to the axon, and the stochastic cues produce a random walk around the average growth direction. We show that the model predicts key parameters that describe axonal dynamics: diffusion (cell motility) coefficient, average growth velocity, and axonal mean squared length, and we compare these parameters with the results of experimental measurements. Our findings indicate that neuronal growth is governed by a contact-guidance mechanism, in which the axons respond to external geometrical cues by aligning their motion along the surface micropatterns. These results have a significant impact on developing novel neural network models, as well as biomimetic substrates, to stimulate nerve regeneration and repair after injury.

Conformational Changes in Surface-Immobilized Proteins Measured Using Combined Atomic Force and Fluorescence Microscopy

Biological organisms rely on proteins to perform the majority of their functions. Most protein functions are based on their physical motions (conformational changes), which can be described as transitions between different conformational states in a multidimensional free-energy landscape. A comprehensive understanding of this free-energy landscape is therefore of paramount importance for understanding the biological functions of proteins. Protein dynamics includes both equilibrium and nonequilibrium motions, which typically exhibit a wide range of characteristic length and time scales. The relative probabilities of various conformational states in the energy landscape, the energy barriers between them, their dependence on external parameters such as force and temperature, and their connection to the protein function remain largely unknown for most proteins. In this paper, we present a multimolecule approach in which the proteins are immobilized at well-defined locations on Au substrates using an atomic force microscope (AFM)-based patterning method called nanografting. This method enables precise control over the protein location and orientation on the substrate, as well as the creation of biologically active protein ensembles that self-assemble into well-defined nanoscale regions (protein patches) on the gold substrate. We performed AFM-force compression and fluorescence experiments on these protein patches and measured the fundamental dynamical parameters such as protein stiffness, elastic modulus, and transition energies between distinct conformational states. Our results provide new insights into the processes that govern protein dynamics and its connection to protein function.

Combined Traction Force—Atomic Force Microscopy Measurements of Neuronal Cells

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.

Cytoprotection of Human Progenitor and Stem Cells through Encapsulation in Alginate Templated, Dual Crosslinked Silk and Silk-Gelatin Composite Hydrogel Microbeads

Susceptibility of mammalian cells against harsh processing conditions limit their use in cell transplantation and tissue engineering applications. Besides modulation of the cell microenvironment, encapsulation of mammalian cells within hydrogel microbeads attract attention for cytoprotection through physical isolation of the encapsulated cells. The hydrogel formulations used for cell microencapsulation are largely dominated by ionically crosslinked alginate (Alg), which suffer from low structural stability under physiological culture conditions and poor cell-matrix interactions. Here the fabrication of Alg templated silk and silk/gelatin composite hydrogel microspheres with permanent or on-demand cleavable enzymatic crosslinks using simple and cost-effective centrifugation-based droplet processing are demonstrated. The composite microbeads display structural stability under ion exchange conditions with improved mechanical properties compared to ionically crosslinked Alg microspheres. Human mesenchymal stem and neural progenitor cells are successfully encapsulated in the composite beads and protected against environmental factors, including exposure to polycations, extracellular acidosis, apoptotic cytokines, ultraviolet (UV) irradiation, anoikis, immune recognition, and particularly mechanical stress. The microbeads preserve viability, growth, and differentiation of encapsulated stem and progenitor cells after extrusion in viscous polyethylene oxide solution through a 27-gauge fine needle, suggesting potential applications in injection-based delivery and three-dimensional bioprinting of mammalian cells with higher success rates.

Axonal growth on surfaces with periodic geometrical patterns

The formation of neuron networks is a complex phenomenon of fundamental importance for understanding the development of the nervous system, and for creating novel bioinspired materials for tissue engineering and neuronal repair. The basic process underlying the network formation is axonal growth, a process involving the extension of axons from the cell body towards target neurons. Axonal growth is guided by environmental stimuli that include intercellular interactions, biochemical cues, and the mechanical and geometrical features of the growth substrate. The dynamics of the growing axon and its biomechanical interactions with the growing substrate remains poorly understood. In this paper, we develop a model of axonal motility which incorporates mechanical interactions between the axon and the growth substrate. We combine experimental data with theoretical analysis to measure the parameters that describe axonal growth on surfaces with micropatterned periodic geometrical features: diffusion (cell motility) coefficients, speed and angular distributions, and axon bending rigidities. Experiments performed on neurons treated Taxol (inhibitor of microtubule dynamics) and Blebbistatin (disruptor of actin filaments) show that the dynamics of the cytoskeleton plays a critical role in the axon steering mechanism. Our results demonstrate that axons follow geometrical patterns through a contact-guidance mechanism, in which high-curvature geometrical features impart high traction forces to the growth cone. These results have important implications for our fundamental understanding of axonal growth as well as for bioengineering novel substrates that promote neuronal growth and nerve repair.

Neuronal Growth and Formation of Neuron Networks on Directional Surfaces

The formation of neuron networks is a process of fundamental importance for understanding the development of the nervous system and for creating biomimetic devices for tissue engineering and neural repair. The basic process that controls the network formation is the growth of an axon from the cell body and its extension towards target neurons. Axonal growth is directed by environmental stimuli that include intercellular interactions, biochemical cues, and the mechanical and geometrical properties of the growth substrate. Despite significant recent progress, the steering of the growing axon remains poorly understood. In this paper, we develop a model of axonal motility, which incorporates substrate-geometry sensing. We combine experimental data with theoretical analysis to measure the parameters that describe axonal growth on micropatterned surfaces: diffusion (cell motility) coefficients, speed and angular distributions, and cell-substrate interactions. Experiments performed on neurons treated with inhibitors for microtubules (Taxol) and actin filaments (Y-27632) indicate that cytoskeletal dynamics play a critical role in the steering mechanism. Our results demonstrate that axons follow geometrical patterns through a contact-guidance mechanism, in which geometrical patterns impart high traction forces to the growth cone. These results have important implications for bioengineering novel substrates to guide neuronal growth and promote nerve repair.

Quantitative characterization of dielectric properties of polymer fibers and polymer composites using electrostatic force microscopy

We use a new method based on electrostatic force microscopy (EFM) to perform quantitative measurements of the dielectric constants of individual electrospun nanofibers of poly(L-lactic acid) (PLLA), as well as composite fibers of PLLA with embedded multiwall carbon nanotubes (MWCNT-PLLA). The EFM data record the oscillation phase of an atomic force microscope (AFM) cantilever as a function of the AFM tip position. In our experiments the relative dielectric constants ϵ of the sample are measured from the EFM phase shifts vs. the tip-surface separation, according to a simple analytical model describing the tip-surface interactions. We perform a comprehensive study of how the dielectric constant depends on the fiber diameter for both electrospun PLLA and MWCNT/PLLA fiber composites. Our measurements show that EFM can distinguish between dielectric properties of PLLA fibers and fiber composites with different diameters. Dielectric constants of both PLLA and MWCNT-PLLA composite fibers decrease with increasing fiber diameter. In the limit of large fiber diameters (D > 100 nm), we measure dielectric constants in the range: ϵ = 3.4-3.8, similar to the values obtained for unoriented PLLA films: ϵ_film = 2.4-3.8. Moreover, the dielectric constants of the small diameter MWCNT-PLLA composites are significantly larger than the corresponding values obtained for PLLA fibers. For MWCNT-PLLA nanofiber composites of small diameters (D < 50 nm), ϵ approaches the values measured for neat MWCNT: ϵ_CN = 12 ± 2. These results are consistent with a simple fiber structural model that shows higher polarizability of thinner fibers, and composites that contain MWCNTs. The experimental method has a high-resolution for measuring the dielectric constant of soft materials, and is simple to implement on standard atomic force microscopes. This non-invasive technique can be applied to measure the electrical properties of polymers, interphases, and polymer nanocomposites.

Neuron dynamics on directional surfaces

Geometrical features play a very important role in neuronal growth and the formation of functional connections between neuronal cells. Here, we analyze the dynamics of axonal growth for neuronal cells cultured on micro-patterned polydimethylsiloxane surfaces. We utilize fluorescence microscopy to image axons, quantify their dynamics, and demonstrate that periodic geometrical patterns impart strong directional bias to neuronal growth. We quantify axonal alignment and present a general stochastic approach that quantitatively describes the dynamics of the growth cones. Neuronal growth is described by a general phenomenological model, based on a simple automatic controller with a closed-loop feedback system. We demonstrate that axonal alignment on these substrates is determined by the surface geometry, and it is quantified by the deterministic part of the stochastic (Langevin and Fokker-Planck) equations. We also show that the axonal alignment with the surface patterns is greatly suppressed by the neuron treatment with Blebbistatin, a chemical compound that inhibits the activity of myosin II. These results give new insight into the role played by the molecular motors and external geometrical cues in guiding axonal growth, and could lead to novel approaches for bioengineering neuronal regeneration platforms.

Variations of Elastic Modulus and Cell Volume with Temperature for Cortical Neurons

Neurons change their growth dynamics and mechanical properties in response to external stimuli such as stiffness of the local microenvironment, ambient temperature, and biochemical or geometrical guidance cues. Here we use combined atomic force microscopy (AFM) and fluorescence microscopy experiments to investigate the relationship between external temperature, soma volume, and elastic modulus for cortical neurons. We measure how changes in ambient temperature affect the volume and the mechanical properties of neuronal cells at both the bulk (elastic modulus) and local (elasticity maps) levels. The experimental data demonstrate that both the volume and the elastic modulus of the neuron soma vary with changes in temperature. Our results show a decrease by a factor of 2 in the soma elastic modulus as the ambient temperature increases from room (25 °C) to physiological (37 °C) temperature, while the volume of the soma increases by a factor of 1.3 during the same temperature sweep. Using high-resolution AFM force mapping, we measure the temperature-induced variations within different regions of the elasticity maps (low and high values of elastic modulus) and correlate these variations with the dynamics of cytoskeleton components and molecular motors. We quantify the change in soma volume with temperature and propose a simple theoretical model that relates this change with variations in soma elastic modulus. These results have significant implications for understanding neuronal development and functions, as ambient temperature, cytoskeletal dynamics, and cellular volume may change with variations in physiological conditions, for example, during tissue compression and infections in vivo as well as during cell manipulation and tissue regeneration ex vivo.

Anomalous diffusion for neuronal growth on surfaces with controlled geometries

Geometrical cues are known to play a very important role in neuronal growth and the formation of neuronal networks. Here, we present a detailed analysis of axonal growth and dynamics for neuronal cells cultured on patterned polydimethylsiloxane surfaces. We use fluorescence microscopy to image neurons, quantify their dynamics, and demonstrate that the substrate geometrical patterns cause strong directional alignment of axons. We quantify axonal growth and report a general stochastic approach that quantitatively describes the motion of growth cones. The growth cone dynamics is described by Langevin and Fokker-Planck equations with both deterministic and stochastic contributions. We show that the deterministic terms contain both the angular and speed dependence of axonal growth, and that these two contributions can be separated. Growth alignment is determined by surface geometry, and it is quantified by the deterministic part of the Langevin equation. We combine experimental data with theoretical analysis to measure the key parameters of the growth cone motion: speed and angular distributions, correlation functions, diffusion coefficients, characteristics speeds and damping coefficients. We demonstrate that axonal dynamics displays a cross-over from Brownian motion (Ornstein-Uhlenbeck process) at earlier times to anomalous dynamics (superdiffusion) at later times. The superdiffusive regime is characterized by non-Gaussian speed distributions and power law dependence of the axonal mean square length and the velocity correlation functions. These results demonstrate the importance of geometrical cues in guiding axonal growth, and could lead to new methods for bioengineering novel substrates for controlling neuronal growth and regeneration.

Role of geometrical cues in neuronal growth

Geometrical cues play an essential role in neuronal growth. Here, we quantify axonal growth on surfaces with controlled geometries and report a general stochastic approach that quantitatively describes the motion of growth cones. We show that axons display a strong directional alignment on micropatterned surfaces when the periodicity of the patterns matches the dimension of the growth cone. The growth cone dynamics on surfaces with uniform geometry is described by a linear Langevin equation with both deterministic and stochastic contributions. In contrast, axonal growth on surfaces with periodic patterns is characterized by a system of two generalized Langevin equations with both linear and quadratic velocity dependence and stochastic noise. We combine experimental data with theoretical analysis to measure the key parameters of the growth cone motion: angular distributions, correlation functions, diffusion coefficients, characteristics speeds, and damping coefficients. We demonstrate that axonal dynamics displays a crossover from an Ornstein-Uhlenbeck process to a nonlinear stochastic regime when the geometrical periodicity of the pattern approaches the linear dimension of the growth cone. Growth alignment is determined by surface geometry, which is fully quantified by the deterministic part of the Langevin equation. These results provide insight into the role of curvature sensing proteins and their interactions with geometrical cues.

Effect of Terminal Modification on the Molecular Assembly and Mechanical Properties of Protein-Based Block Copolymers

Accurate prediction and validation of the assembly of bioinspired peptide sequences into fibers with defined mechanical characteristics would aid significantly in designing and creating materials with desired properties. This process may also be utilized to provide insight into how the molecular architecture of many natural protein fibers is assembled. In this work, computational modeling and experimentation are used in tandem to determine how peptide terminal modification affects a fiber-forming core domain. Modeling shows that increased terminal molecular weight and hydrophilicity improve peptide chain alignment under shearing conditions and promote consolidation of semicrystalline domains. Mechanical analysis shows acute improvements to strength and elasticity, but significantly reduced extensibility and overall toughness. These results highlight an important entropic function that terminal domains of fiber-forming peptides exhibit as chain alignment promoters, which ultimately has notable consequences on the mechanical behavior of the final fiber products.

A new path to platelet production through matrix sensing

Megakaryocytes (MK) in the bone marrow (BM) are immersed in a network of extracellular matrix components that regulates platelet release into the circulation. Combining biological and bioengineering approaches, we found that the activation of transient receptor potential cation channel subfamily V member 4 (TRPV4), a mechano-sensitive ion channel, is induced upon MK adhesion on softer matrices. This response promoted platelet production by triggering a cascade of events that lead to calcium influx, β1 integrin activation and internalization, and Akt phosphorylation, responses not found on stiffer matrices. Lysyl oxidase (LOX) is a physiological modulator of BM matrix stiffness via collagen crosslinking. In vivo inhibition of LOX and consequent matrix softening lead to TRPV4 activation cascade and increased platelet levels. At the same time, in vitro proplatelet formation was reduced on a recombinant enzyme-mediated stiffer collagen. These results suggest a novel mechanism by which MKs, through TRPV4, sense extracellular matrix environmental rigidity and release platelets accordingly.

Electrodeposited gels prepared from protein alloys

AIM

Silk-tropoelastin alloys, composed of recombinant human tropoelastin and regenerated Bombyx mori silk fibroin, are an emerging, versatile class of biomaterials endowed with tunable combinations of physical and biological properties. Electrodeposition of these alloys provides a programmable means to assemble functional gels with both spatial and temporal controllability.

MATERIALS & METHODS

Tropoelastin-modified silk was prepared by enzymatic coupling between tyrosine residues. Hydrogel coatings were electrodeposited using two wire electrodes.

RESULTS & DISCUSSION

Mechanical characterization and in vitro cell culture revealed enhanced adhesive capability and cellular response of these alloy gels as compared with electrogelled silk alone.

CONCLUSION

These electro-depositable silk-tropoelastin alloys constitute a suitable coating material for nanoparticle-based drug carriers and offer a novel opportunity for on-demand encapsulation/release of nanomedicine.

Load Rate and Temperature Dependent Mechanical Properties of the Cortical Neuron and Its Pericellular Layer Measured by Atomic Force Microscopy

When studying the mechanical properties of cells by an indentation technique, it is important to take into account the nontrivial pericellular interface (or pericellular "brush") which includes a pericellular coating and corrugation of the pericellular membrane (microvilli and microridges). Here we use atomic force microscopy (AFM) to study the mechanics of cortical neurons taking into account the presence of the above pericellular brush surrounding cell soma. We perform a systematic study of the mechanical properties of both the brush layer and the underlying neuron soma and demonstrate that the brush layer is likely responsible for the low elastic modulus (<1 kPa) typically reported for cortical neurons. When the contribution of the pericellular brush is excluded, the average elastic modulus of the cortical neuron soma is found to be 3-4 times larger than previously reported values measured under similar physiological conditions. We also demonstrate that the underlying soma behaves as a nonviscous elastic material over the indentation rates studied (1-10 μm/s). As a result, it seems that the brush layer is responsible for the previously reported viscoelastic response measured for the neuronal cell body as a whole, within these indentation rates. Due to of the similarities between the macroscopic brain mechanics and the effective modulus of the pericellular brush, we speculate that the pericellular brush layer might play an important role in defining the macroscopic mechanical properties of the brain.

Stimuli-Responsive Free-Standing Layer-By-Layer Films

Free-standing, stimuli-responsive polyelectrolyte multilayer films enabled by light-induced degradation of sacrificial compartments are introduced. Two examples are described: i) a triple responsive film that uses light, redox, and pH for different functions, and ii) different wavelengths of light for different functions. This approach to multiresponsive materials offers simple design and chemical synthesis while enabling different stimuli to perform separate functions in the same material.

Predictive modelling-based design and experiments for synthesis and spinning of bioinspired silk fibres

Scalable computational modelling tools are required to guide the rational design of complex hierarchical materials with predictable functions. Here, we utilize mesoscopic modelling, integrated with genetic block copolymer synthesis and bioinspired spinning process, to demonstrate de novo materials design that incorporates chemistry, processing and material characterization. We find that intermediate hydrophobic/hydrophilic block ratios observed in natural spider silks and longer chain lengths lead to outstanding silk fibre formation. This design by nature is based on the optimal combination of protein solubility, self-assembled aggregate size and polymer network topology. The original homogeneous network structure becomes heterogeneous after spinning, enhancing the anisotropic network connectivity along the shear flow direction. Extending beyond the classical polymer theory, with insights from the percolation network model, we illustrate the direct proportionality between network conductance and fibre Young's modulus. This integrated approach provides a general path towards de novo functional network materials with enhanced mechanical properties and beyond (optical, electrical or thermal) as we have experimentally verified.

Programmable 3D silk bone marrow niche for platelet generation ex vivo and modeling of megakaryopoiesis pathologies

We present a programmable bioengineered 3-dimensional silk-based bone marrow niche tissue system that successfully mimics the physiology of human bone marrow environment allowing us to manufacture functional human platelets ex vivo. Using stem/progenitor cells, megakaryocyte function and platelet generation were recorded in response to variations in extracellular matrix components, surface topography, stiffness, coculture with endothelial cells, and shear forces. Millions of human platelets were produced and showed to be functional based on multiple activation tests. Using adult hematopoietic progenitor cells our system demonstrated the ability to reproduce key steps of thrombopoiesis, including alterations observed in diseased states. A critical feature of the system is the use of natural silk protein biomaterial allowing us to leverage its biocompatibility, nonthrombogenic features, programmable mechanical properties, and surface binding of cytokines, extracellular matrix components, and endothelial-derived proteins. This in turn offers new opportunities for the study of blood component production ex vivo and provides a superior tissue system for the study of pathologic mechanisms of human platelet production.

Quantitative analysis of mechanical and electrostatic properties of poly(lactic) acid fibers and poly(lactic) acid-carbon nanotube composites using atomic force microscopy

We use atomic force microscopy (AFM) to perform a systematic quantitative characterization of the elastic modulus and dielectric constant of poly(L-lactic acid) electrospun nanofibers (PLLA), as well as composites of PLLA fibers with 1.0 wt% embedded multiwall carbon nanotubes (MWCNTs-PLLA). The elastic moduli are measured in the fiber skin region via AFM nanoindentation, and the dielectric constants are determined by measuring the phase shifts obtained via electrostatic force microscopy (EFM). We find that the average value for the elastic modulus for PLLA fibers is (9.8 ± 0.9) GPa, which is a factor of 2 larger than the measured average elastic modulus for MWCNT-PLLA composites (4.1 ± 0.7) GPa. We also use EFM to measure dielectric constants for both types of fibers. These measurements show that the dielectric constants of the MWCNT-PLLA fibers are significantly larger than the corresponding values obtained for PLLA fiber. This result is consistent with the higher polarizability of the MWCNT-PLLA composites. The measurement methods presented are general, and can be applied to determine the mechanical and electrical properties of other polymers and polymer nanocomposites.

Effects of surface asymmetry on neuronal growth

Detailed knowledge of how the surface physical properties, such as mechanics, topography and texture influence axonal outgrowth and guidance is essential for understanding the processes that control neuron development, the formation of functional neuronal connections and nerve regeneration. Here we synthesize asymmetric surfaces with well-controlled topography and texture and perform a systematic experimental and theoretical investigation of axonal outgrowth on these substrates. We demonstrate unidirectional axonal bias imparted by the surface ratchet-based topography and quantify the topographical guidance cues that control neuronal growth. We describe the growth cone dynamics using a general stochastic model (Fokker-Planck formalism) and use this model to extract two key dynamical parameters: diffusion (cell motility) coefficient and asymmetric drift coefficient. The drift coefficient is identified with the torque caused by the asymmetric ratchet topography. We relate the observed directional bias in axonal outgrowth to cellular contact guidance behavior, which results in an increase in the cell-surface coupling with increased surface anisotropy. We also demonstrate that the disruption of cytoskeletal dynamics through application of Taxol (stabilizer of microtubules) and Blebbistatin (inhibitor of myosin II activity) greatly reduces the directional bias imparted by these asymmetric surfaces. These results provide new insight into the role played by topographical cues in neuronal growth and could lead to new methods for stimulating neuronal regeneration and the engineering of artificial neuronal tissue.

Effect of sequence features on assembly of spider silk block copolymers

Bioengineered spider silk block copolymers were studied to understand the effect of protein chain length and sequence chemistry on the formation of secondary structure and materials assembly. Using a combination of in vitro protein design and assembly studies, we demonstrate that silk block copolymers possessing multiple repetitive units self-assemble into lamellar microstructures. Additionally, the study provides insights into the assembly behavior of spider silk block copolymers in concentrated salt solutions.

Semi-automatic quantification of neurite fasciculation in high-density neurite images by the neurite directional distribution analysis (NDDA)

BACKGROUND

Bundling of neurite extensions occur during nerve development and regeneration. Understanding the factors that drive neurite bundling is important for designing biomaterials for nerve regeneration toward the innervation target and preventing nociceptive collateral sprouting. High-density neuron cultures including dorsal root ganglia explants are employed for in vitro screening of biomaterials designed to control directional outgrowth. Although some semi-automated image processing methods exist for quantification of neurite outgrowth, methods to quantify axonal fasciculation in terms of direction of neurite outgrowth are lacking.

NEW METHOD

This work presents a semi-automated program to analyze micrographs of high-density neurites; the program aims to quantify axonal fasciculation by determining the orientational distribution function of the tangent vectors of the neurites and calculating its Fourier series coefficients ('c' values).

RESULTS

We found that neurite directional distribution analysis (NDDA) of fasciculated neurites yielded 'c' values of ≥∼0.25 whereas branched outgrowth led to statistically significant lesser values of <∼0.2. The 'c' values correlated directly to the width of neurite bundles and indirectly to the number of branching points.

COMPARISON WITH EXISTING METHODS

Information about the directional distribution of outgrowth is lost in simple counting methods or achieved laboriously through manual analysis. The NDDA supplements previous quantitative analyses of axonal bundling using a vector-based approach that captures new information about the directionality of outgrowth.

CONCLUSION

The NDDA is a valuable addition to open source image processing tools available to biomedical researchers offering a robust, precise approach to quantification of imaged features important in tissue development, disease, and repair.

Neuronal growth as diffusion in an effective potential

Current understanding of neuronal growth is mostly qualitative, as the staggering number of physical and chemical guidance cues involved prohibit a fully quantitative description of axonal dynamics. We report on a general approach that describes axonal growth in vitro, on poly-D-lysine-coated glass substrates, as diffusion in an effective external potential, representing the collective contribution of all causal influences on the growth cone. We use this approach to obtain effective growth rules that reveal an emergent regulatory mechanism for axonal pathfinding on these substrates.

Temperature response of the neuronal cytoskeleton mapped via atomic force and fluorescence microscopy

Neuronal cells change their growth properties in response to external physical stimuli such as variations in external temperature, stiffness of the growth substrate, or topographical guidance cues. Detailed knowledge of the mechanisms that control these biomechanical responses is necessary for understanding the basic principles that underlie neuronal growth and regeneration. Here, we present elasticity maps of living cortical neurons (embryonic rat) as a function of temperature, and correlate these maps to the locations of internal structural components of the cytoskeleton. Neurons display a significant increase in the average elastic modulus upon a decrease in ambient temperature from 37 to 25 °C. We demonstrate that the dominant mechanism by which the elasticity of the neurons changes in response to temperature is the stiffening of the actin components of the cytoskeleton induced by myosin II. We also report a reversible shift in the location and composition of the high-stiffness areas of the neuron cytoskeleton with temperature. At 37 °C the areas of the cell displaying high elastic modulus overlap with the tubulin-dense regions, while at 25 °C these high-stiffness areas correspond to the actin-dense regions of the cytoskeleton. These results demonstrate the importance of considering temperature effects when investigating cytoskeletal dynamics in cells.

Neuron biomechanics probed by atomic force microscopy

Mechanical interactions play a key role in many processes associated with neuronal growth and development. Over the last few years there has been significant progress in our understanding of the role played by the substrate stiffness in neuronal growth, of the cell-substrate adhesion forces, of the generation of traction forces during axonal elongation, and of the relationships between the neuron soma elastic properties and its health. The particular capabilities of the Atomic Force Microscope (AFM), such as high spatial resolution, high degree of control over the magnitude and orientation of the applied forces, minimal sample damage, and the ability to image and interact with cells in physiologically relevant conditions make this technique particularly suitable for measuring mechanical properties of living neuronal cells. This article reviews recent advances on using the AFM for studying neuronal biomechanics, provides an overview about the state-of-the-art measurements, and suggests directions for future applications.

Kelvin probe microscopy and electronic transport measurements in reduced graphene oxide chemical sensors

Reduced graphene oxide (RGO) is an electronically hybrid material that displays remarkable chemical sensing properties. Here, we present a quantitative analysis of the chemical gating effects in RGO-based chemical sensors. The gas sensing devices are patterned in a field-effect transistor geometry, by dielectrophoretic assembly of RGO platelets between gold electrodes deposited on SiO2/Si substrates. We show that these sensors display highly selective and reversible responses to the measured analytes, as well as fast response and recovery times (tens of seconds). We use combined electronic transport/Kelvin probe microscopy measurements to quantify the amount of charge transferred to RGO due to chemical doping when the device is exposed to electron-acceptor (acetone) and electron-donor (ammonia) analytes. We demonstrate that this method allows us to obtain high-resolution maps of the surface potential and local charge distribution both before and after chemical doping, to identify local gate-susceptible areas on the RGO surface, and to directly extract the contact resistance between the RGO and the metallic electrodes. The method presented is general, suggesting that these results have important implications for building graphene and other nanomaterial-based chemical sensors.

Electronic Transport and Doping Effects in Reduced Graphene Oxide Measured by Scanning Probe Microscopy

We present a Scanning Probe Microscopy study of doping and sensing properties of reduced graphene oxide (rGO)-based nanosensors. rGO devices are created by dielectrophoretic assembly of rGO platelets onto interdigitated electrode arrays, which are lithographically pre-patterned on top of SiO2/Si wafers. The availability of several types of oxygen functional groups allows rGO to interact with a wide range of organic dopants, including methanol, ethanol, acetone, and ammonia. We perform sensitive Scanning Kelvin Probe Microscopy (SKPM) measurements on patterned rGO electronic circuits and show that the local electrical potential and charge distribution are significantly changed when the device is exposed to organic dopants. We also demonstrate that SKPM experiments allow us to quantify the amount of charge transferred to the sensor during chemical doping, and to spatially resolve the active sites of the sensor where the doping process takes place.

Neuronal alignment on asymmetric textured surfaces

Axonal growth and the formation of synaptic connections are key steps in the development of the nervous system. Here, we present experimental and theoretical results on axonal growth and interconnectivity in order to elucidate some of the basic rules that neuronal cells use for functional connections with one another. We demonstrate that a unidirectional nanotextured surface can bias axonal growth. We perform a systematic investigation of neuronal processes on asymmetric surfaces and quantify the role that biomechanical surface cues play in neuronal growth. These results represent an important step towards engineering directed axonal growth for neuro-regeneration studies.

Elasticity maps of living neurons measured by combined fluorescence and atomic force microscopy

Detailed knowledge of mechanical parameters such as cell elasticity, stiffness of the growth substrate, or traction stresses generated during axonal extensions is essential for understanding the mechanisms that control neuronal growth. Here, we combine atomic force microscopy-based force spectroscopy with fluorescence microscopy to produce systematic, high-resolution elasticity maps for three different types of live neuronal cells: cortical (embryonic rat), embryonic chick dorsal root ganglion, and P-19 (mouse embryonic carcinoma stem cells) neurons. We measure how the stiffness of neurons changes both during neurite outgrowth and upon disruption of microtubules of the cell. We find reversible local stiffening of the cell during growth, and show that the increase in local elastic modulus is primarily due to the formation of microtubules. We also report that cortical and P-19 neurons have similar elasticity maps, with elastic moduli in the range 0.1-2 kPa, with typical average values of 0.4 kPa (P-19) and 0.2 kPa (cortical). In contrast, dorsal root ganglion neurons are stiffer than P-19 and cortical cells, yielding elastic moduli in the range 0.1-8 kPa, with typical average values of 0.9 kPa. Finally, we report no measurable influence of substrate protein coating on cell body elasticity for the three types of neurons.

Young’s Modulus of Cortical and P19 Derived Neurons Measured by Atomic Force Microscopy

In this paper we use the Atomic Force Microscope to measure the Young’s modulus for two types of neuronal cell bodies: cortical neurons obtained from rat embryos and neurons derived from P19 mouse embryonic carcinoma stem cells. The neurons are plated on different substrates coated with two types of protein growth factors, poly-D-lysine and laminin. We report on the Young’s modulus of each type of neuron as well as the variation of modulus between cells plated on different protein substrates. We compare these results to various individual cell and bulk tissue measurements reported in literature. We additionally report on an observed change in the Young’s modulus of cortical neurons when subjected to a short-term reduction in ambient temperature.

Controlling Neuronal Growth on Au Surfaces by Directed Assembly of Proteins

Studying how individual neuronal cells grow and interact with each other is of fundamental importance for understanding the functions of the nervous system. However, the mechanism of axonal navigation to their target region and their specific interactions with guidance factors such as membrane-bound proteins, chemical and temperature gradients, mechanical guidance cues, etc. are not well understood. Here we describe a new approach for controlling the adhesion, growth and interconnectivity of cortical neurons on Au surfaces. Specifically, we use Atomic Force Microscopy (AFM) nanolithography to immobilize growth-factor proteins at well-defined locations on Au surfaces. These surface-immobilized proteins act as a) adhesion proteins for neuronal cells (i.e. well-defined locations where the cells “stick” to the surface), and b) promoters/inhibitors for the growth of neurites. Our results show that protein patterns can be used to confine neuronal cells and to control their growth and interconnectivity on Au surfaces. We also show that AFM nanolithography presents unique advantages for this type of work, such as high degree of control over location and shape of the protein patterns, and application of proteins in aqueous solutions (protein buffers), such that the proteins are very likely to retain their folding conformation/bioactivity.

Distance dependence of neuronal growth on nanopatterned gold surfaces

Understanding network development in the brain is of tremendous fundamental importance, but it is immensely challenging because of the complexity of both its architecture and function. The mechanisms of axonal navigation to target regions and the specific interactions with guidance factors such as membrane-bound proteins, chemical gradients, mechanical guidance cues, etc., are largely unknown. A current limitation for the study of neural network formation is the ability to control precisely the connectivity of small groups of neurons. A first step in designing such networks is to understand the "rules" central nervous system (CNS) neurons use to form functional connections with one another. Here we begin to delineate novel rules for growth and connectivity of small numbers of neurons patterned on Au substrates in simplified geometries. These studies yield new insights into the mechanisms determining the organizational features present in intact systems. We use a previously reported atomic force microscopy (AFM) nanolithography method to control precisely the location and growth of neurons on these surfaces. By examining a series of systems with different geometrical parameters, we quantitatively and systematically analyze how neuronal growth depends on these parameters.

Positioning and guidance of neurons on gold surfaces by directed assembly of proteins using Atomic Force Microscopy

We demonstrate that Atomic Force Microscopy nanolithography can be used to control effectively the adhesion, growth and interconnectivity of cortical neurons on Au surfaces. We demonstrate immobilization of neurons at well-defined locations on Au surfaces using two different types of patterned proteins: 1) poly-d-lysine (PDL), a positively charged polypeptide used extensively in tissue culture and 2) laminin, a component of the extracellular matrix. Our results show that both PDL and laminin patterns can be used to confine neuronal cells and to control their growth and interconnectivity on Au surfaces, a significant step towards the engineering of artificial neuronal assemblies with well-controlled neuron position and connections.

Ligand-induced structural changes in maltose binding proteins measured by atomic force microscopy

We use atomic force microscopy (AFM) based force-compression measurements to probe the ligand-induced functional conformational changes in surface-immobilized dicysteine-terminated maltose binding proteins (dicys-MBPs). The proteins are immobilized at well-defined locations directly on Au substrates using the previously reported technique of nanografting. By measuring the difference between the ligand-free and ligand-bound mechanical work performed by the AFM-tip during the protein compression, we determine the open-closed transition energy for dicys-MBPs to be DeltaE0 = (8 +/- 4) Kcal/mol. We also compare the binding kinetics of two different ligands (maltose and maltotriose) to dicys-MBPs by performing AFM-friction measurements. We show that our results are consistent with a simple model for the surface-immobilized dicys-MBPs: the protein consists of two rigid lateral lobes connected by a hinge-loaded spring.

DNA-decorated carbon nanotubes for chemical sensing

We demonstrate a new, versatile class of nanoscale chemical sensors based on single-stranded DNA (ss-DNA) as the chemical recognition site and single-walled carbon nanotube field effect transistors (swCN-FETs) as the electronic read-out component. swCN-FETs with a nanoscale coating of ss-DNA respond to gas odors that do not cause a detectable conductivity change in bare devices. Responses of ss-DNA/swCN-FETs differ in sign and magnitude for different gases and can be tuned by choosing the base sequence of the ss-DNA. ss-DNA/swCN-FET sensors detect a variety of odors, with rapid response and recovery times on the scale of seconds. The sensor surface is self-regenerating: samples maintain a constant response with no need for sensor refreshing through at least 50 gas exposure cycles. This remarkable set of attributes makes sensors based on ss-DNA decorated nanotubes very promising for "electronic nose" and "electronic tongue" applications ranging from homeland security to disease diagnosis.

Controlled switching of optical emission energies in semiconducting single-walled carbon nanotubes

We present scanning photoluminescence (PL) microscopy of freely suspended single-walled carbon nanotubes grown by chemically assisted vapor deposition (CVD) across micron-sized open apertures. Scans of the PL emission versus excitation position show unusual "holes"having subwavelength spatial features associated with abrupt blue shifts of the emission energy. By varying the excitation polarization, energy, intensity, and position, we demonstrate that optical switching in some nanotubes is controllable in a highly nonlinear manner by adjusting the nonequilibrium carrier density in the nanotube. Technologically important attributes include large spectral contrast between on/off states at room temperature, a dramatic response to small changes in light intensity near threshold, and the possibility that electrical charge injection could also be used to control emission energies.

High frequency scanning gate microscopy and local memory effect of carbon nanotube transistors

We use impedance spectroscopy to measure the high-frequency properties of single-walled carbon nanotube field effect transistors (swCN-FETs). Furthermore, we extend scanning gate microscopy (SGM) to frequencies up to 15 MHz and use it to image changes in the impedance of swCN-FET circuits induced by the SGM tip gate. In contrast to earlier reports, the results of both experiments are consistent with a simple RC parallel circuit model of the swCN-FET, with a time constant of 0.3 micros. We also use the SGM tip to show the local nature of the memory effect normally observed in swCN-FETs, implying that nanotube-based memory cells can be miniaturized to dimensions of the order of tens of nm.