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Results for “Bioengineering”

Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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At least 451 records · Page 25Linked to original sources

bioRxiv2018

Computation of history-dependent mechanical damage of axonal fiber tracts in the brain: towards tracking sub-concussive and occupational damage to the brain

Finite element models are frequently used to simulate traumatic brain injuries. However, current models are unable to capture the progressive damage caused by repeated head trauma. In this work, we propose a method for computing the history-dependent mechanical damage of axonal fiber bundle tracts in the brain. Through the introduction of multiple damage models, we provide the ability to link consecutive head impact simulations, so that potential injury to the brain can be tracked over time. In addition, internal damage variables are used to degrade the mechanical response of each axonal fiber bundle element. As a result, the stiffness of the aggregate tissue decreases as damage evolves. To counteract this degenerative process, we have also introduced a preliminary healing model that reverses the accumulated damage, based on a user-specified healing duration. Using two detailed examples, we demonstrate that damage produces a significant decrease in fiber stress, which ultimately propagates to the tissue level and produces a measurable decrease in overall stiffness. These results suggest that damage modeling has the potential to enhance current brain simulation techniques and lead to new insights, especially in the study of repetitive head injuries.

bioengineering↗

bioRxiv2018

Neuronal Cells Confinement by Micropatterned Cluster-Assembled Dots with Mechanotransductive Nanotopography

The in vitro fabrication of neural networks able to simulate brain circuits and to maintain their native connectivity is of strategic importance to gain a deep understanding of neural circuit physiology and brain natural computational algorithm(s). This would also enable a wide-range of applications including the development of efficient brain-on-chip devices or brain-computer interfaces. Chemical and mechanotransductive cues cooperate to promote proper development and functioning of neural networks. Since the 80s, controlled growth of mammalian neuronal cells on micrometric patterned chemical cues with the development of synaptic connections and electrical activity has been reported, however the role of mechanotransductive signaling on the growth/organization of neural networks has not been investigated so far. Here we report the fabrication and characterization of patterned substrates for neuronal culture with a controlled structure both at the nano- and microscale suitable for the selective adhesion of neuronal cells. Nanostructured micrometric dots were patterned on passivated cell-repellent glass substrates by supersonic cluster beam deposition of zirconia nanoparticles through stencil masks. Cluster-assembled nanostructured zirconia surfaces are characterized by nanotopographical features that can direct the maturation of neural networks by mechanotransductive signaling. Our approach produces a controlled microscale pattern of adhesive areas with predetermined nanoscale morphology. We have validated these micropatterned substrates using a neuronal cell line (PC12 cells) and cultured hippocampal neurons. While cells have been uniformly plated on the substrates, they adhered only on the nanostructured zirconia regions, remaining effectively confined inside the nanostructured dots on which they were found to grow, move and differentiate.

bioengineering↗

bioRxiv2018

Synthesis of three major auxins from glucose in Engineered Escherichia coli

Indole-3-acetic acid (IAA) is considered the most common and important naturally occurring auxin in plants and a major regulator of plant growth and development. In addition, phenylacetic acid (PAA) and 4-hydroxyphenylacetic acid (4HPA) can also play a role as auxin in some plants. In recent years, several microbes have been metabolically engineered to produce IAA from L-tryptophan. In this study, we showed that aminotransferase aro8 and decarboxylase kdc from Saccharomyces cerevisiae, and aldehyde dehydrogenase aldH from Escherichia coli have broad substrate ranges and can catalyze the conversion of three kinds of aromatic amino acids (L-tryptophan, L-tyrosine or L-phenylalanine) to the corresponding IAA, 4HPA and PAA. Subsequently, three de novo biosynthetic pathways for the production of IAA, PAA and 4HPA from glucose were constructed in E. coli through strengthening the shikimate pathway. This study described here shows the way for the development of agricultural microorganism for biosynthesis of plant auxin and promoting plant growth in the future.

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bioRxiv2018

Genome-scale metabolic reconstruction and metabolic versatility of an obligate methanotroph Methylococcus capsulatus str. Bath

The increase in greenhouse gases with high global warming potential such as methane is a matter of concern and requires multifaceted efforts to reduce its emission and increase its mitigation from the environment. Microbes such as methanotrophs can assist in methane mitigation. To understand the metabolic capabilities of methanotrophs, a complete genome-scale metabolic model of an obligate methanotroph, Methylococcus capsulatus str. Bath was reconstructed. The model contains 535 genes, 898 reactions and 784 unique metabolites and is named iMC535. The predictive potential of the model was validated using previously-reported experimental data. The model predicted the Entner-Duodoroff (ED) pathway to be essential for the growth of this bacterium, whereas the Embden-Meyerhof-Parnas (EMP) pathway was found non-essential. The performance of the model was simulated on various carbon and nitrogen sources and found that M. capsulatus can grow on amino acids. The analysis of network topology of the model identified that six amino acids were in the top-ranked metabolic hubs. Using flux balance analysis (FBA), 29% of the metabolic genes were predicted to be essential, and 76 double knockout combinations involving 92 unique genes were predicted to be lethal. In conclusion, we have reconstructed a genome-scale metabolic model of a unique methanotroph Methylococcus capsulatus str. Bath. The model will serve as a knowledge-base for deeper understanding, as a platform for exploring the metabolic potential, and as a tool to engineer this bacterium for methane mitigation and industrial applications.

bioengineering↗

bioRxiv2018

Multiobjective Strain Design: A Framework for Modular Cell Engineering

Diversity of cellular metabolism can be harnessed to produce a large space of molecules. However, development of optimal strains with high product titers, rates, and yields required for industrial production is laborious and expensive. To accelerate the strain engineering process, we have recently introduced a modular cell design concept that enables rapid generation of optimal production strains by systematically assembling a modular cell with an exchangeable production module(s) to produce target molecules efficiently. In this study, we formulated the modular cell design concept as a general multiobjective optimization problem with flexible design objectives derived from mass action. We developed algorithms and an associated software package, named ModCell2 to implement the design. We demonstrated that ModCell2 can systematically identify genetic modifications to design modular cells that can couple with a variety of production modules and exhibit a minimal tradeoff among modularity, performance, and robustness. Analysis of the modular cell designs revealed both intuitive and complex metabolic architectures enabling modular production of these molecules. We envision ModCell2 provides a powerful tool to guide modular cell engineering and sheds light on modular design principles of biological systems.

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bioRxiv2018

Evaluating Plastic Deformation and Damage as Potential Mechanisms for Tendon Inelasticity using a Reactive Modeling Framework

Inelastic behaviors, such as softening, a progressive decrease in modulus before failure, occur in tendon andare important aspect in degeneration and tendinopathy. These in elastic behaviors are generally attributed to two potential mechanisms: plastic deformation and damage. However, it is not clear which is primarily responsible.In this study, we evaluated these potential mechanisms of tendon in elasticity by using a recently developed reactive in elasticity model (RIE), which is a structurally-inspired continuum mechanics frame work that models tissue in elasticity based on the molecular bond kinetics. Using RIE, we formulated two material models, one specific toplastic deformation and the other to damage. The models were independently fit to published experimental tensiletests of rat tail tendons. We quantified the inelastic effects and compared the performance of the two models infitting the mechanical response during loading, relaxation, unloading, and reloading phases. Additionally, we validated the models by using the resulting fit parameters to predict an independent set of experimental stress-straincurves from ramp-to-failure tests. Overall, the models were both successful in fitting the experiments and predicting the validation data. However, the results did not strongly favor one mechanism over the other. As a result, to distinguish between plastic deformation and damage, different experimental protocols will be needed. Nevertheless, these findings suggest the potential of RIE as a comprehensive framework for studying tendon inelastic behaviors.

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bioRxiv2018

Speed Control and Force-Vectoring of Blue Bottle Flies in a Magnetically-Levitated Flight Mill

Flies fly at a broad range of speeds and produce sophisticated aerial maneuvers with precisely controlled wing movements. Remarkably, only subtle changes in wing motion are used by flies to produce aerial maneuvers, resulting in little directional tilt of aerodynamic force vector relative to the body. Therefore, it is often considered that flies fly according to a helicopter model and control speed mainly via force-vectoring enabled primarily by body-pitch change. Here we examine the speed control of blue bottle flies using a magnetically-levitated (MAGLEV) flight mill, as they fly at different body pitch and with different augmented aerodynamic damping. We identify wing kinematic contributors to the changes of estimated aerodynamic force through testing two force-vectoring models. Results show that in addition to body pitch, flies also use a collection of wing kinematic variables to control both force magnitude and direction, the roles of which are analogous to those of throttle, collective and cyclic pitch of helicopters. Our results also suggest that the MAGLEV flight mill system can be potentially used to study the roles of visual and mechanosensory feedback in insect flight control.\n\nSummary statement: This paper elucidates how files control flight speed while flying in a magnetically-levitated (MAGLEV) flight mill, which enables the manipulation of body pitch and aerodynamic load.

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bioRxiv2018

Real-time three-dimensional MRI for the assessment of dynamic carpal instability

Carpal instability is defined as a condition where wrist motion or loading creates mechanical dysfunction, resulting in weakness, pain and decreased function. Often the diagnosis is made late when malalignment is visualized on static radiography, CT, or MRI. When conventional imaging methods do not identify the instability patterns, yet clinical signs associated with instability exist, the diagnosis of dynamic instability is often suggested to describe carpal derangement manifested only during the wrists active motion or stress. We addressed the question: can advanced MRI techniques provide quantitative measures for evaluating dynamic carpal instability and supplement standard static MRI acquisition? Our objectives were to [1] develop a real-time, three-dimensional MRI method to image the carpal joints during their active, uninterrupted motion; and [2] demonstrate feasibility of the method for assessing metrics relevant to dynamic carpal instability, thus overcoming limitations of conventional MRI. Twenty wrists (bilateral wrists of ten healthy participants) were scanned during radial-ulnar deviation and clenched-fist maneuvers. Images resulting from two real-time MRI pulse sequences, four sparse data acquisition schemes, and three constrained image reconstruction priors were compared. Image quality was assessed via blinded scoring by two radiologists and quantitative imaging metrics. Data acquisition employing sparse radial sampling with a gradient-recalled-echo acquisition and constrained iterative reconstruction (temporal resolution up to 135 ms per slice) appeared to provide a reasonable tradeoff between imaging speed and quality. This real-time MRI method effectively reduced streaking artifacts arising from data undersampling and enabled the derivation of quantitative measures pertinent to evaluating dynamic carpal instability.

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bioRxiv2018

A theoretical analysis of single molecule protein sequencing via weak binding spectra

We propose and theoretically study an approach to massively parallel single molecule peptide sequencing, based on single molecule measurement of the kinetics of probe binding [1] to the N-termini of immobilized peptides. Unlike previous proposals, this method is robust to both weak and non-specific probe-target affinities, which we demonstrate by applying the method to a range of randomized affinity matrices consisting of relatively low-quality binders. This suggests a novel principle for proteomic measurement whereby highly non-optimized sets of low-affinity binders could be applicable for protein sequencing, thus shifting the burden of amino acid identification from biomolecular design to readout. Measurement of probe occupancy times, or of time-averaged fluorescence, should allow high-accuracy determination of N-terminal amino acid identity for realistic probe sets. The time-averaged fluorescence method scales well to extremely weak-binding probes. We argue that this method could lead to an approach with single amino acid resolution and the ability to distinguish many canonical and modified amino acids, even using highly non-optimized probe sets. This readout method should expand the design space for single molecule peptide sequencing by removing constraints on the properties of the fluorescent binding probes.\n\nAuthor summaryWe simplify the problem of single molecule protein sequencing by proposing and analyzing an approach that makes use of low-affinity, low-specificity binding reagents. This decouples the problem of protein sequencing from the problem of generating a high-quality library of binding reagents against each of the amino acids.

bioengineering↗

bioRxiv2018

CRISPR delivery particles for developing therapeutic strategies in metabolic disease

RNA-guided engineered nucleases derived from a prokaryotic adaptive immune system known as CRISPR-Cas represent a promising platform for gene deletion and editing. As a therapeutic approach, direct delivery of Cas9 protein and guide RNA could circumvent the safety problems associated with plasmid delivery and therefore represents an attractive tool for genome engineering. Gene deletion or editing in adipose tissue to enhance its energy expenditure, fat oxidation and secretion of bioactive factors through a \"browning\" process presents a potential therapeutic strategy to alleviate metabolic disease. Here, we developed novel CRISPR delivery particles, denoted CriPs, composed of nano-size complexes of Cas9 protein and single guide (sg)RNA, coated with an amphipathic peptide called Endo-Porter that mediates entry into cells. Efficient CRISPR-Cas9 mediated gene deletion of ectopically expressed Green fluorescent protein (GFP) by CriPs was achieved in multiple cell types including a macrophage cell line, primary macrophages and primary pre-adipocytes. Significant GFP loss was also observed in peritoneal exudate cells with minimum systemic toxicity in GFP expressing mice following intraperitoneal injection of CriPs containing sgRNA targeting Gfp. Furthermore, the disruption of the Nrip1 gene in white adipocytes by CriPs enhanced adipocyte \"browning\" with a marked increase of UCP1 expression. Deletion of Nrip1 by CriPs did not produce detectable off-target effects. Thus CriPs represent a novel CRISPR delivery system for Cas9 and sgRNA that is effective for ablating targeted gene products in cultured cells and in vivo, and provide a potential therapeutic strategy for metabolic disease.

bioengineering↗

bioRxiv2018

Single-embryo and single-blastomere immunoblotting reports protein expression heterogeneity in early-stage preimplantation embryos

Understanding how a zygote develops from a single cell into a multicellular organism has benefitted from single-cell tools, including RNA sequencing (RNA-Seq) and immunofluorescence (IF). However, scrutinizing inter- and intra-embryonic phenotypic variation is hindered by two fundamental limitations; the loose correlation between transcription and translation and the cross-reactivity of immunoreagents. To address these challenges, we describe a high-specificity microfluidic immunoblot optimized to quantify protein expression from all stages of mouse preimplantation development. Despite limited availability of isoform-specific immunoreagents, the immunoblot resolves inter-embryonic heterogeneity of embryo-specific isoforms (i.e., DICER-1). We observed significantly higher DICER-1 isoform expression in oocytes when compared to two-cell embryos, and further find that protein expression levels follow the same trend as mRNA for both the full-length and truncated DICER-1 isoforms. At the morula stage, we assayed both whole and disaggregated embryos for loading controls ({beta}-tubulin, GAPDH) and markers that regulate cell fate decisions (CDX-2, SOX-2). In disaggregated morula, we found that cell volume showed positive, linear correlation with expression of {beta}-tubulin and SOX-2. In dissociated two-cell and four-cell blastomeres, we detect significant inter-blastomeric variation in GADD45a expression, corroborating suspected cellular heterogeneity even in the earliest multicellular stage of preimplantation embryos. As RNA-Seq and other transcript-centric approaches continue to further probe preimplantation development, the demand for companion protein-based techniques rises. The reported microfluidic immunoblot serves as an essential tool for understanding mammalian development by providing high-specificity and direct measurements of protein targets at single-embryo and single-blastomere resolution.

bioengineering↗

bioRxiv2018

Finding the difference between periosteal and endocortical bone adaptation by using Artificial Neural Networks

In silico models of bone adaptation successfully simulated in vivo periosteal bone apposition, however, there are instances where these models may have limited success in predicting the new bone formation at endocortical surface. In vivo studies have highlighted that cortical bone surfaces may have differences in their modeling or remodeling responses to mechanical loading. However, the principle which the two cortical surfaces follow in bone adaptation is not very clear. This work accordingly attempts to understand how periosteal and endocortical surfaces accommodate loading-induced new bone formation. A neural network model is used to serve the purpose. A relationship is established to compute new bone thickness as a function of mechanical parameters (normal and shear strains) and non-mechanical parameters (distances from the neutral axis and the centroid) at the two surfaces. Analytical results indicate that two cortical surfaces behave opposite to each other in order to achieve optimal distribution of newly formed bone. The outcomes may be useful in establishing a unifying principle to predict site-specific new bone formation.

bioengineering↗

bioRxiv2018

Coopting the Lap system of Pseudomonas fluorescens to reversibly customize bacterial cell surfaces

Initialattachment to a surface is a key and highly regulated step in biofilm formation. In this study, we present a platform for reversibly functionalizing bacterial cell surfaces, with an emphasis on designing biofilms. We engineered the Lap system of Pseudomonas fluorescens Pf0-1, which is normally used to regulate initial cell surface attachment, to display various protein cargo at the bacterial cell surface and control extracellular release of the cargo in response to changing levels of the second messenger cdi-GMP. To accomplish this goal, we fused the protein cargo between the N-terminal retention module and C-terminal secretion signal of LapA, and controlled surface localization of the cargo with natural signals known to stimulate or deplete c-di-GMP levels in P. fluorescens Pf0-1. We show this system can tolerate large cargo in excess of 500 amino acids, direct P. fluorescens Pf0-1 to surfaces it does not typically colonize, and program this microbe to sequester the toxic medal cadmium.

bioengineering↗

bioRxiv2018

Modular microtissues for the regeneration of functional bone in large defects

Repair of complex fractures with bone loss requires a potent, space-filling intervention to promote regeneration of bone. We present a minimally-invasive strategy combining mesenchymal stromal cells (MSC) with a chitosan-collagen matrix to form modular microtissues designed for delivery through a needle to conformally fill cavital defects. Implantation of microtissues into a calvarial defect in the mouse showed that osteogenically pre-differentiated MSC resulted in complete bridging of the cavity, while undifferentiated MSC produced mineralized tissue only in apposition to native bone. Decreasing the implant volume reduced bone regeneration, while increasing the MSC concentration also attenuated bone formation, suggesting that the cell-matrix ratio is important in achieving a robust response. Conformal filling of the defect with microtissues in a carrier gel resulted in complete healing. Taken together, these results show that modular microtissues can be used to augment the differentiated function of MSC and provide an extracellular environment that potentiates bone repair.

bioengineering↗

bioRxiv2018

Doppler-Based Algorithm for Mapping Cardiac Rotors by Induced Temperature Perturbations

Electrogram-guided ablation for mapping of abnormal atrial activity has become increasingly popular in clinical applications. However, current methods have several limitations, and none have been shown to increase the ablation procedure success rate more than empirical ablation procedures. Here we present a new approach to identify arrhythmogenic sources as targets for ablation. Based on our previous findings that rotor drifting can be characterized by a local temperature gradient within the tissue, this article describes an innovative induced temperature technique which exploits the fact that rotor drifting produces Doppler shifts in the dominant frequency as measured at stationary locations. A mathematical algorithm is detailed to solve the inverse problem, reconstruct the drift trajectory, and predict the rotor origin location. Mathematical modeling and computer simulations demonstrate the feasibility of the new approach for rotors and focal source, two well-known arrhythmogenic sources of irregular conduction. Performance was extensively investigated for different numbers of electrodes and varied SNRs. Random conditions were also taken into account, since the electrodes array position and the initial location of the rotor pivot can impact the outcomes. By using temperature perturbation and employing the Doppler algorithm, the rotor drift trajectory and the origin region is shown to be estimated. We consider ways in which this technique can be extended to differentiate between rotors and ectopic activity. Future experimental and clinical validations should lead to potential use in ablation procedures and improve localization capabilities, thus increasing success rates and optimizing arrhythmia management.

bioengineering↗

bioRxiv2018

Cardiac Spiral Wave Drifting Due to Spatial Temperature Gradients: A Numerical Study

Cardiac rotors are believed to be a major driver source of persistent atrial fibrillation (AF), and their spatiotemporal characterization is essential for successful ablation procedures. However, electrograms guided ablation have not been proven to have benefit over empirical ablation thus far, and there is a strong need of improving the localization of cardiac arrhythmogenic targets for ablation. A new approach for characterize rotors is proposed that is based on induced spatial temperature gradients (STGs), and investigated by theoretical study using numerical simulations. We hypothesize that such gradients will cause rotor drifting due to induced spatial heterogeneity in excitability, so that rotors could be driven towards the ablating probe. Numerical simulations were conducted in single cell and 2D atrial models using AF remodeled kinetics. STGs were applied either linearly on the entire tissue or as a small local perturbation, and the major ion channel rate constants were adjusted following Arrhenius equation. In the AF-remodeled single cell, recovery time increased exponentially with decreasing temperatures, despite the marginal effect of temperature on the action potential duration. In 2D models, spiral waves drifted with drifting velocity components affected by both temperature gradient direction and the spiral wave rotation direction. Overall, spiral waves drifted towards the colder tissue region associated with global minimum of excitability. A local perturbation with a temperature of T=28{degrees}C was found optimal for spiral wave attraction for the studied conditions. This work provides a preliminary proof-of-concept for a potential prospective technique for rotor attraction. We envision that the insights from this study will be utilize in the future in the design of a new methodology for AF characterization and termination during ablation procedures.

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bioRxiv2018

Generating Realistic Morphologies of Neurons in Rodent Hippocampus with DGCAN

Dendritic size and branching patterns are important features of neural form and function. However, current computational models of neuronal networks use simplistic cylindrical geometries to mimic dendritic arborizations. One reason for this is that current methods to generate dendritic trees have rigid a priori constraints. To address this, a deep convolutional generative adversarial network (DCGAN) trained on images of rodent hippocampal granule and pyramidal dendritic trees. Image features learned by the network were used to generate realistic dendritic morphologies. Results show that DCGANs achieved greater stability* and high generalization, as quantified by kernel maximum mean discrepancy, when exposed to instance noise and/or label smoothing during training. Trained models successfully generated realistic morphologies for both neuron types, with high false positive rate reported by expert reviewers. Collectively, DCGANs offer a unique opportunity to advance the geometry of neural modeling, and, therefore, to propel our understanding of neuronal function.\n\n * A \"stable/stabilized DCGAN\", as mentioned throughout this work, is a DCGAN which was stable throughout training.

bioengineering↗

bioRxiv2018

The effect of stride length on lower extremity joint kinetics at various gait speeds

Robot-assisted training is a promising tool under development for improving walking function based on repetitive goal-oriented task practice. The challenges in developing the controllers for gait training devices that promote desired changes in gait is complicated by the limited understanding of the human response to robotic input. A possible method of controller formulation can be based on the principle of bio-inspiration, where a robot is controlled to apply the change in joint moment applied by human subjects when they achieve a gait feature of interest. However, it is currently unclear how lower extremity joint moments are modulated by even basic gaitspatio-temporal parameters.\n\nIn this study, we investigated how sagittal plane joint moments are affected by a factorial modulation of two important gait parameters: gait speed and stride length. We present the findings obtained from 20 healthy control subjects walking at various treadmill-imposed speeds and instructed to modulate stride length utilizing real-time visual feedback. Implementing a continuum analysis of inverse-dynamics derived joint moment profiles, we extracted the effects of gait speed and stride length on joint moment throughout the gait cycle. Moreover, we utilized a torque pulse approximation analysis to determine the timing and amplitude of torque pulses that approximate the difference in joint moment profiles between stride length conditions, at all gait speed conditions.\n\nOur results show that gait speed has a significant effect on the moment profiles in all joints considered, while stride length has more localized effects, with the main effect observed on the knee moment during stance, and smaller effects observed for the hip joint moment during swing and ankle moment during the loading response. Moreover, our study demonstrated that trailing limb angle, a parameter of interest in programs targeting propulsion at push-off, was significantly correlated with stride length. As such, our study has generated assistance strategies based on pulses of torque suitable for implementation via a wearable exoskeleton with the objective of modulating stride length, and other correlated variables such as trailing limb angle.

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