Impact of Silk-Ionomer Encapsulation on Immune Cell Mechanical Properties and Viability.

Encapsulation of single cells is a powerful technique used in various fields, such as regenerative medicine, drug delivery, tissue regeneration, cell-based therapies, and biotechnology. It offers a method to protect cells by providing cytocompatible coatings to strengthen cells against mechanical and environmental perturbations. Silk fibroin, derived from the silkworm Bombyx mori, is a promising protein biomaterial for cell encapsulation due to the cytocompatibility and capacity to maintain cell functionality. Here, THP-1 cells, a human leukemia monocytic cell line, were encapsulated with chemically modified silk polyelectrolytes through electrostatic layer-by-layer deposition. The effectiveness of the silk nanocoating was assessed using scanning electron microscopy (SEM) and confocal microscopy and on cell viability and proliferation by Alamar Blue assay and live/dead staining. An analysis of the mechanical properties of the encapsulated cells was conducted using atomic force microscopy nanoindentation to measure elasticity maps and cellular stiffness. After the cells were encapsulated in silk, an increase in their stiffness was observed. Based on this observation, we developed a mechanical predictive model to estimate the variations in stiffness in relation to the thickness of the coating. By tuning the cellular assembly and biomechanics, these encapsulations promote systems that protect cells during biomaterial deposition or processing in general.

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.

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.

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.

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.

Feedback-controlled dynamics of neuronal cells on directional surfaces.

The formation of neuronal networks is a complex phenomenon of fundamental importance for understanding the development of the nervous system. The basic process underlying the network formation is axonal growth, a process involving the extension of axons from the cell body and axonal navigation toward target neurons. Axonal growth is guided by the interactions between the tip of the axon (growth cone) and its extracellular environmental cues, which include intercellular interactions, the biochemical landscape around the neuron, and the mechanical and geometrical features of the growth substrate. Here, we present a comprehensive experimental and theoretical analysis of axonal growth for neurons cultured on micropatterned polydimethylsiloxane (PDMS) surfaces. We demonstrate that closed-loop feedback is an essential component of axonal dynamics on these surfaces: the growth cone continuously measures environmental cues and adjusts its motion in response to external geometrical features. We show that this model captures all the characteristics of axonal dynamics on PDMS surfaces for both untreated and chemically modified neurons. We combine experimental data with theoretical analysis to measure key parameters that describe axonal dynamics: diffusion (cell motility) coefficients, speed and angular distributions, and cell-substrate interactions. The experiments performed on neurons treated with Taxol (inhibitor of microtubule dynamics) and Y-27632 (disruptor of actin filaments) indicate that the internal dynamics of microtubules and actin filaments plays a critical role for the proper function of the feedback 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 substrate to guide neuronal growth and promote nerve repair.

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: ϵfilm = 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: ϵCN = 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, ß1 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.

Silk-ionomer and silk-tropoelastin hydrogels as charged three-dimensional culture platforms for the regulation of hMSC response.

The response of human bone marrow-derived mesenchymal stem cells (hMSCs) encapsulated in three-dimensional (3D) charged protein hydrogels was studied. Combining silk fibroin (S) with recombinant human tropoelastin (E) or silk ionomers (I) provided protein composite alloys with tunable physicochemical and biological features for regulating the bioactivity of encapsulated hMSCs. The effects of the biomaterial charges on hMSC viability, proliferation and chondrogenic or osteogenic differentiation were assessed. The silk-tropoelastin or silk-ionomers hydrogels supported hMSC viability, proliferation and differentiation. Gene expression of markers for chondrogenesis and osteogenesis, as well as biochemical and histological analysis, showed that hydrogels with different S/E and S/I ratios had different effects on cell fate. The negatively charged hydrogels upregulated hMSC chondrogenesis or osteogenesis, with or without specific differentiation media, and hydrogels with higher tropoelastin content inhibited the differentiation potential even in the presence of the differentiation media. The results provide insight on charge-tunable features of protein-based biomaterials to control hMSC differentiation in 3D hydrogels, as well as providing a new set of hydrogels for the compatible encapsulation and utility for cell functions. Copyright © 2016 John Wiley & Sons, Ltd.

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.