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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 Read source abstracts and check manuscript versions; preprints are not peer reviewed.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 343 records · Page 19Linked to original sources

bioRxiv2018

Perivascular signals alter global genomic profile of glioblastoma and response to temozolomide in a gelatin hydrogel

Glioblastoma (GBM) is the most common primary malignant brain tumor, with patients exhibiting poor survival (median survival time: 15 months). Difficulties in treating GBM include not only the inability to resect the diffusively-invading tumor cells but also therapeutic resistance. The perivascular niche (PVN) within the GBM tumor microenvironment contributes significantly to tumor cell invasion, cancer stem cell maintenance, and has been shown to protect tumor cells from radiation and chemotherapy. In this study, we examine how the inclusion of non-tumor cells in culture with tumor cells within a hydrogel impacts the overall gene expression profile of an in vitro artificial perivascular niche (PVN) comprised of endothelial and stromal cells directly cultured with GBM tumor cells within a methacrylamide-functionalized gelatin hydrogel. Using RNA-seq, we demonstrate that genes related to angiogenesis and remodeling are upregulated in the PVN model compared to hydrogels containing only tumor or perivascular niche cells, while downregulated genes are related to cell cycle and DNA damage repair. Signaling pathways and genes commonly implicated in GBM malignancy, such as MGMT, EGFR, PI3K-Akt signaling, and Ras/MAPK signaling are also upregulated in the PVN model. We describe the kinetics of gene expression within the PVN hydrogels over a course of 14 days, observing the patterns associated with tumor cell-mediated endothelial network co-option and regression. We finally examine the effect of temozolomide, a frontline chemotherapy used clinically against GBM, on the PVN culture. Notably, the PVN model is less responsive to TMZ compared to hydrogels containing only tumor cells. Overall, these results demonstrate that inclusion of cellular and matrix-associated elements of the PVN within an in vitro model of GBM allows for the development of gene expression patterns and therapeutic response relevant to GBM.

bioengineering↗

bioRxiv2018

Crowding tunes 3D collagen fibrils and reveals matrix regulation of cancer cell morphogenesis

It is well established that the collagenous extracellular matrix surrounding solid tumors significantly influences the dissemination of cancer cells. However, the underlying mechanisms remain poorly understood, in part because of a lack of methods to modulate collagen fibril topology in the presence of embedded cells. In this work, we develop a technique to tune the fibril architecture of cell-laden 3D collagen matrices using PEG as an inert molecular crowding agent. With this approach, we demonstrate that fibril length and pore size can be modulated independently of bulk collagen density and stiffness. Using live cell imaging and quantitative analysis, we show that matrices with long fibrils induce cell elongation and single cell migration, while shorter fibrils induce cell rounding, collective migration, and morphogenesis. We conclude that fibril architecture is an independent regulator of cancer cell phenotype and that cell shape and invasion strategy are functions of collagen fibril length.

bioengineering↗

bioRxiv2018

Deep mutational scanning by FACS-sorting of encapsulated E. coli micro-colonies

We present a method for high-throughput screening of protein variants where the signal is enhanced by micro-encapsulation of single cells into 20-30 m agarose beads. Cells inside beads are propagated using standard agitation in liquid media and grow clonally into micro-colonies harboring several hundred bacteria. We have, as a proof-of-concept, analyzed random amino acid substitutions in the five C-terminal {beta}-strands of the Green Fluorescent Protein (GFP). Starting from libraries of variants, each bead represents a clonal line of cells that can be separated by Fluorescence Activated Cell Sorting (FACS). Pools representing collections of individual variants with desired properties are subsequently analyzed by deep sequencing. Notably, the encapsulation approach described holds the potential for high-throughput analysis of systems where the fluorescence signal from a single cell is insufficient for detection. Fusion to GFP, or use of fluorogenic substrates, allows coupling protein levels or activity to sequence for a wide range of proteins. Here we analyzed more than 10,000 individual variants to gauge the effect of mutations on GFP-fluorescence. In the mutated region, we observed virtually all amino acid substitutions that are accessible by single nucleotide exchange. Lastly, we assessed the performance of biophysical protein stability predictors, FoldX and Rosetta, in predicting the outcome of the experiment. Both tools display good performance on average, suggesting that loss of thermodynamic stability is a key mechanism for the observed variation of the mutants. This, in turn, suggests that deep mutational scanning datasets may be used to more efficiently fine-tune such predictors, especially for mutations poorly covered by current biophysical data.

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bioRxiv2018

Coupling magnetically induced electric fields to neurons: longitudinal and transverse activation

We present a theory and computational models to couple the electric field induced by magnetic stimulation to neuronal membranes. The response of neuronal membranes to induced electric fields is examined under different time scales, and the characteristics of the primary and secondary electric fields from electromagnetic induction and charge accumulation on conductivity boundaries, respectively, are analyzed. Based on the field characteristics and decoupling of the longitudinal and transverse field components along the neural cable, quasi-potentials are a simple and accurate approximation for coupling of magnetically induced electric fields to neurons and a modified cable equation provides theoretical consistency for magnetic stimulation. The conventional and modified cable equations are used to simulate magnetic stimulation of long peripheral nerves by circular and figure-8 coils. Activation thresholds are obtained over a range of lateral and vertical coil positions for two nonlinear membrane models representing unmyelinated and myelinated axons and also for undulating myelinated axons. For unmyelinated straight axons, the thresholds obtained with the modified cable equation are significantly lower due to transverse polarization, and the spatial distributions of thresholds as a function of coil position differ significantly from predictions by the activating function. For myelinated axons, the transverse field contributes negligibly to activation thresholds, whereas axonal undulation can increase or decrease thresholds depending on coil position. The analysis provides a rigorous theoretical foundation and implementation methods for the use of the cable equation to model neuronal response to magnetically induced electric fields. Experimentally observed stimulation with the electric fields perpendicular to the nerve trunk cannot be explained by transverse polarization alone and is likely due to nerve fiber undulation and other geometrical inhomogeneities.

bioengineering↗

bioRxiv2018

A 3D model of human skeletal muscle innervated with stem cell-derived motor neurons enables epsilon-subunit targeted myasthenic syndrome studies

Two-dimensional (2D) human skeletal muscle fiber cultures are ill equipped to support the contractile properties of maturing muscle fibers. This limits their application to the study of adult human neuromuscular junction (NMJ) development, a process requiring maturation of muscle fibers in the presence of motor neuron endplates. Here we describe a three-dimensional (3D) co-culture method whereby human muscle progenitors mixed with human pluripotent stem cell-derived motor neurons self-organize to form functional NMJ connections within two weeks. Functional connectivity between motor neuron endplates and muscle fibers is confirmed with calcium transient imaging and electrophysiological recordings. Notably, we only observed epsilon acetylcholine receptor subunit protein upregulation and activity in 3D co-culture. This demonstrates that the 3D co-culture system supports a developmental shift from the embryonic to adult form of the receptor that does not occur in 2D co-culture. Further, 3D co-culture treatments with myasthenia gravis patient sera shows the ease of studying human disease with the system. This work delivers a simple, reproducible, and adaptable method to model and evaluate adult human NMJ de novo development and disease in culture.

bioengineering↗

bioRxiv2018

A synthetic, three-dimensional bone marrow hydrogel

Three-dimensional (3D) synthetic hydrogels have recently emerged as desirable in vitro cell culture platforms capable of representing the extracellular geometry, elasticity, and water content of tissue in a tunable fashion. However, they are critically limited in their biological functionality. Hydrogels are typically decorated with a scant 1-3 peptide moieties to direct cell behavior, which vastly underrepresents the proteins found in the extracellular matrix (ECM) of real tissues. Further, peptides chosen are ubiquitous in ECM, and are not derived from specific proteins. We developed an approach to incorporate the protein complexity of specific tissues into the design of biomaterials, and created a hydrogel with the elasticity of marrow, and 20 marrow-specific cell-instructive peptides. Compared to generic PEG hydrogels, our marrow-inspired hydrogel improves stem cell differentiation and proliferation. We propose this tissue-centric approach as the next generation of 3D hydrogel design for applications in tissue engineering.

bioengineering↗

bioRxiv2018

Automatic Instrument Segmentation in Robot-Assisted Surgery Using Deep Learning

Semantic segmentation of robotic instruments is an important problem for the robot-assisted surgery. One of the main challenges is to correctly detect an instruments position for the tracking and pose estimation in the vicinity of surgical scenes. Accurate pixel-wise instrument segmentation is needed to address this challenge. In this paper we describe our deep learning-based approach for robotic instrument segmentation. Our approach demonstrates an improvement over the state-of-the-art results using several novel deep neural network architectures. It addressed the binary segmentation problem, where every pixel in an image is labeled as an instrument or background from the surgery video feed. In addition, we solve a multi-class segmentation problem, in which we distinguish between different instruments or different parts of an instrument from the background. In this setting, our approach outperforms other methods for automatic instrument segmentation thereby providing state-of-the-art results for these problems. The source code for our solution is made publicly available.

bioengineering↗

bioRxiv2018

Logistic regression analysis of multiple interosseous hand muscle activation using surface electromyography during isometric finger tasks

Intrinsic hand muscles are densely located in the hand, and the myoelectric observation from the surface is sometimes unreliable because of some outside influences that may interfere with the signals. In the present study, we evaluated the activities of multiple interosseous hand-muscles which densely located in the hand, through analyzing the surface electromyographic signals during finger-oriented tasks using univariate and multivariate logistic regression models. Ten healthy subjects participated in our experiment, and isometrically exercised each finger one by one in flexed form. The result of a univariate analysis with the power and amplitude domain predictor variables of the surface electromyographic signals showed significant consistency between the activated finger and the inserted finger of the dorsal interosseous muscles to the proximal phalanx (P < 0.001). Meanwhile, the results of a multivariate analysis showed a higher correlation of the regression model of the fourth dorsal interosseous muscle during the action of the ring finger using frequency-domain variables (the Nagelkerke R2 = 0.716 when the median frequency was used), compared to the model without the frequency-domain variables (the Nagelkerke R2 = 0.583). Our result showed that the logistic regression models have a particular possibility for the analysis of the surface electromyographic signals of densely located hand-muscle activities related to the finger-oriented tasks.

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bioRxiv2018

Fusible alloy ‘in-contact’ microelectrodes: a rapid and economic microfabrication alternative for microfluidic impedance cytometry

Microfluidic impedance cytometry (MIC) provides a non-optical and label-free method for single cell analysis. However, the cleanroom intensive infrastructure required for MIC electrode fabrication limits its implementation. As an alternate technique that enables rapid prototyping, we fabricated Fields metal in-contact (icFM) coplanar microelectrodes in multilayer elastomer devices with a single photolithography step and characterised them for microfluidic impedance cytometry. Our icFM microelectrodes matched performance of the conventional platinum electrodes in the detection of single human erythrocytes and water-in-oil droplets in a feedback-controlled suction-flow MIC setup. Finally, to facilitate droplet based single cell analysis, we demonstrate detection and quantification of single erythrocytes entrapped in water-in-oil droplets.

bioengineering↗

bioRxiv2018

Robotic automation of droplet microfluidics

Droplet microfluidics enables new reactions, assays, and analytic capabilities, but often requires complex workflows involving numerous steps of macro- and micro-fluidic processing. We demonstrate robotically-automated droplet microfluidics, an approach to automate workflows with commercial fluid-handling robots. These workflows can be performed without human intervention, increasing reliability and convenience.

bioengineering↗

bioRxiv2018

Single-step Enzymatic Glycoengineering for the Construction of Antibody-cell Conjugates

Employing live cells as therapeutics is a direction of future drug discovery. An easy and robust method to modify the surfaces of cells directly to incorporate novel functionalities is highly desirable. However, many current methods for cell-surface engineering interfere with cells endogenous properties. Here we report an enzymatic approach that enables the transfer of biomacromolecules, such as a full length IgG antibody, to the glycocalyx on the surfaces of live cells when the antibody is conjugated to the enzymes natural donor substrate GDP-fucose. This method is fast and biocompatible with little interference to cells endogenous functions. We applied this method to construct two antibody-cell conjugates (ACCs) using different immune cells, and the modified cells exhibited specific tumor targeting and resistance to inhibitory signals produced by tumor cells, respectively. Remarkably, Herceptin-NK-92MI conjugates exhibits enhanced activities to induce the lysis of HER2+ cancer cells both ex vivo and in a murine tumor model, indicating its potential for further development as a clinical candidate.

bioengineering↗

bioRxiv2018

Principles of Computer Numerical Controlled Machining Applied to Cranial Microsurgery

Over the last decade, a plethora of tools have been developed for neuroscientists to interface with the brain. Implementing these tools requires precise removal of sections of the skull to access the brain. These delicate cranial microsurgical procedures need to be performed on sub-millimeter thick bone without damaging the underlying tissue and therefore, require significant training. Automating some of these procedures would not only enable more precise microsurgical operations, but also democratize use of advanced neurotechnologies. Here, we describe the Craniobot, a cranial microsurgery platform that combines automated skull surface profiling with a computer numerical controlled (CNC) milling machine to perform a variety of cranial microsurgical procedures in mice. The Craniobot utilizes a low force contact sensor to profile the skull surface and uses this information to perform micrometer-scale precise milling operations within minutes. We have used the Craniobot to drill pilot holes to anchor cranial implants, perform skull thinning, and open small to large craniotomies. The Craniobot is built using off-the-shelf components for under $1000 and is controlled using open-source CNC programming software.

bioengineering↗

bioRxiv2018

Automated Adherent Cell Elimination by a High-Speed Laser Mediated by a Light-Responsive Polymer

Conventional cell handling and sorting methods require manual dissociation, which decreases cell quality and quantity and is not well suited for monitoring applications. To purify adherent cultured cells, in situ cell purification technologies that are high throughput and can be utilized in an on-demand manner are expected. Previous demonstrations using direct laser-mediated cell elimination revealed only limited success in terms of their usability and throughput. Here, we developed a Laser-Induced, Light-responsive-polymer-Activated, Cell Killing (LILACK) system that enables high-speed and on-demand adherent cell sectioning and purification. This system employs a visible laser beam, which does not kill cells directly, but induces local heat production through the trans-cis-trans photo-isomerization of azobenzene moieties in only the irradiated area of a light-responsive thin layer. Using this system in each passage for sectioning, human induced pluripotent stem cells (hiPSCs) were maintained their pluripotency and self-renewal during long-term culture. Furthermore, combined with deep machine-learning analysis on fluorescent and phase contrast images, a label-free and automatic cell processing system was developed by eliminating unwanted spontaneously differentiated cells in undifferentiated hiPSC culture conditions.

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bioRxiv2018

Hydrodynamic cavitation as an energy efficient process to increase biochar surface area and porosity: a case study

The effectivity of biochar as soil amendment is depending by its physical and chemical characteristics that are related to the type and the features of the thermal production process, such as peak temperature, heating rate, holding time, as well as from the used feedstocks. The textural characteristics of biochar in term of surface area, pore size and pore volume distribution, important for the physicochemical properties of the material, are critically dependent on the production process and the feedstock type. In this study, based on a single biochar type and a single experiment, for the first time controlled hydrodynamic cavitation was proven as a fast and effective way to enhance the biochar surface area by as much as 120%, while preserving or improving the respective chemical composition, showing far higher efficiency than the conventional increase of the peak pyrolysis temperature.\n\nAbbreviations

bioengineering↗

bioRxiv2018

Model-based analysis of the stiffness of the wrist joint in active and passive conditions

The control of joint stiffness is a fundamental mechanism used to control human movements. While many studies have observed how stiffness is controlled for tasks involving shoulder and elbow motion, a limited amount of knowledge is available for wrist movements, though the wrist plays a crucial role in fine manipulation.\n\nWe have developed a computational framework based on a realistic musculoskeletal model, which allows to calculate the passive and active components of the wrist joint stiffness. We first used the framework to validate the musculoskeletal model against experimental measurements of the passive wrist joint stiffness, and then to study the contribution of different muscle groups on the passive joint stiffness. We finally used the framework to study the effect of muscle co - contraction on the active joint stiffness.\n\nThe results show that thumb and finger muscles play a crucial role in determining the passive wrist joint stiff - ness: in the neutral posture, the direction of maximum stiffness aligns with the experimental measurements, and the magnitude increases by 113% when they are included. Moreover, the analysis of the controllability of joint stiffness showed that muscle co - contraction positively correlates with the stiffness magnitude and negatively correlates with the variability of the stiffness orientation (p < 0.01 in both cases). Finally, an exhaustive search showed that with appropriate selection of a muscle activation strategy, the joint stiffness orientation can be arbitrarily modulated. This observation suggests the absence of biomechanical constraints on the controllability of the orientation of the wrist joint stiffness.

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bioRxiv2018

Escher-FBA: A web application for interactive flux balance analysis

BackgroundFlux balance analysis (FBA) is a widely-used method for analyzing metabolic networks. However, most existing tools that implement FBA require downloading software and writing code. Furthermore, FBA generates predictions for metabolic networks with thousands of components, so meaningful changes in FBA solutions can be difficult to identify. These challenges make it difficult for beginners to learn how FBA works.\n\nResultsTo meet this need, we present Escher-FBA, a web application for interactive FBA simulations within a pathway visualization. Escher-FBA allows users to set flux bounds, knock out reactions, change objective functions, upload metabolic models, and generate high-quality figures without downloading software or writing code. We provide detailed instructions on how to use Escher-FBA to replicate several FBA simulations that generate real scientific hypotheses.\n\nConclusionsWe designed Escher-FBA to be as intuitive as possible so that users can quickly and easily understand the core concepts of FBA. The web application can be accessed at https://sbrg.github.io/escher-fba.

bioengineering↗

bioRxiv2018

A machine-learning-guided mutagenesis platform for accelerated discovery of novel functional proteins

Molecular evolution based on mutagenesis is widely used in protein engineering. However, optimal proteins are often difficult to obtain due to a large sequence space that requires high costs for screening experiments. Here, we propose a novel approach that combines molecular evolution with machine learning. In this approach, we conduct two rounds of mutagenesis where an initial library of protein variants is used to train a machine-learning model to guide mutagenesis for the second-round library. This enables to prepare a small library suited for screening experiments with high enrichment of functional proteins. We demonstrated a proof-of-concept of our approach by altering the reference green fluorescent protein (GFP) so that its fluorescence is changed to yellow while improving its fluorescence intensity. Using 155 and 78 variants for the initial and the second-round libraries, respectively, we successfully obtained a number of proteins showing yellow fluorescence, 12 of which had better fluorescence performance than the reference yellow fluorescent protein (YFP). These results show the potential of our approach as a powerful platform for accelerated discovery of functional proteins.

bioengineering↗

bioRxiv2018

A drug-tunable gene therapy for broad-spectrum protection against retinal degeneration

Retinal degenerations are a large cluster of diseases characterized by the irreversible loss of light-sensitive photoreceptors that impairs the vision of 9.1 million people in the US. An attractive treatment option is to use gene therapy to deliver broad-spectrum neuroprotective factors. However, this approach has had limited clinical translation because of the inability to control transgene expression. To address this problem, we generated an adeno-associated virus vector named RPF2 that was engineered to express domains of leukemia inhibitory factor fused to the destabilization domain of bacterial dihydrofolate reductase. Fusion proteins containing the destabilization domain are degraded in mammalian cells but can be stabilized with the binding of the drug trimethoprim. Our data show that expression levels of RPF2 are tightly regulated by the dose of trimethoprim, and can be reversed by trimethoprim withdrawal. We further show that stabilized RPF2 can protect photoreceptors and prevent blindness in treated mice.

bioengineering↗