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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 Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2020

Promiscuous enzymes cooperate at the substrate level en route to lactazole A

Enzymes involved in ribosomally synthesized and post-translationally modified peptide (RiPP) biosynthesis often have relaxed specificity profiles and are able to modify diverse substrates. When several such enzymes act together during precursor peptide maturation, a multitude of products can form, and yet usually, the biosynthesis converges on a single natural product. For the most part, the mechanisms controlling the integrity of RiPP assembly remain elusive. Here, we investigate biosynthesis of lactazole A, a model thiopeptide produced by five promiscuous enzymes from a ribosomal precursor peptide. Using our in vitro thiopeptide production (FIT-Laz) system, we determine the order of biosynthetic events at the individual modification level, and supplement this study with substrate scope analysis for participating enzymes. Combined, our results reveal a dynamic thiopeptide assembly process with multiple points of kinetic control, intertwined enzymatic action, and the overall substrate-level cooperation between the enzymes. This work advances our understanding of RiPP biosynthesis processes and facilitates thiopeptide bioengineering.

biochemistry↗

bioRxiv2020

Direct reprogramming of adult hepatocytes to generate LGR5+ endodermal progenitor

We successfully converted hepatocytes isolated from adult mice into expandable and stable leucine-rich repeat-containing G-protein-coupled receptor 5 (LGR5)-positive endodermal progenitor cells (EndoPCs). This was accomplished in vitro through transient exposure to four transcriptional factors (OCT3/4, SOX2, KLF4, and cMYC) and STAT3 activators. EndoPCs were generated by a process that involved an epithelial-mesenchymal transition (EMT) without the use of any components of the canonical WNT/{beta}-catenin or LGR5/R-spondin signaling pathways. We showed that the proliferation and capacity for self-renewal of EndoPCs in 2D long-term culture were controlled by three interrelated signaling pathways: gp130/JAK/STAT3, LGR5/R-spondin, and WNT/{beta}-catenin. After long-term maintenance in two- and three-dimensional culture systems, EndoPCs were able to differentiate into liver-restricted lineages such as hepatocyte-like cells and bile duct-like structures in vitro and in vivo. After intra-muscular injection, EndoPCs generated macroscopically visible and well-vascularized liver-like tissue, which contained Alb+ liver parenchyma-like structures and substantial, KRT7/KRT19+ bile duct-like cell organizations. ConclusionWe have developed an efficient method for producing LGR5+ adult endodermal stem cells. These cells will be useful for the in vitro study of the molecular mechanisms of liver development and have important potential for therapeutic strategies, including approaches based on bioengineered liver tissue. These cells also open up new avenues for experiments focused on disease modeling, toxicology studies, and regenerative medicine applications.

developmental biology↗

bioRxiv2020

Generalized correlation-based dynamical network analysis: a new high-performance approach for identifying allosteric communications in molecular dynamics trajectories

Molecular interactions are essential for regulation of cellular processes, from the formation of multiprotein complexes, to the allosteric activation of enzymes. Identifying the essential residues and molecular features that regulate such interactions is paramount for understanding the biochemical process in question, allowing for suppression of a reaction through drug interventions, or optimization of a chemical process using bioengineered molecules. In order to identify important residues and information pathways within molecular complexes, the Dynamical Network Analysis method was developed and has since been broadly applied in the literature. However, in the dawn of exascale computing, this method is generally limited to relatively small biomolecular systems. In this work we provide an evolution of the method, application and interface. All data processing and analysis is conducted through Jupyter notebooks, providing automatic detection of important solvent and ion residues, an optimized and parallel generalized correlation implementation that is linear with respect to the number of nodes in the system, and subsequent community clustering, calculation of betweenness of contacts, and determination optimal paths. Using the popular visualization program VMD, high-quality renderings of the networks over the biomolecular structures can be produced. Our new implementation was employed to investigate three different systems, with up to 2.5 M atoms, namely the OMP-decarboxylase, the Leucyl-tRNA synthetase complexed with its cognate tRNA and adenylate, and the respiratory complex I in a membrane environment. Our enhanced and updated protocol provides the community with an intuitive and interactive interface, which can be easily applied to large macromolecular complexes.

biophysics↗

bioRxiv2020

TEARS: Spatial engineering of E. coli with addressable phase-separated RNAs

Biochemical processes often require spatial regulation and specific microenvironments. The general lack of organelles in bacteria limits the potential of bioengineering complex intracellular reactions. Here we demonstrate Transcriptionally Engineered Addressable RNA Solvent droplets (TEARS) as synthetic microdomains within the Escherichia coli. TEARS are assembled from RNA-binding protein recruitment domains fused to poly-CAG repeats that spontaneously drive liquid-liquid phase separation from the bulk cytoplasm. Targeting TEARS with fluorescent proteins revealed multilayered structures and a non-equilibrium mechanism controlling their composition and reaction robustness. We show that TEARS provide organelle-like bioprocess isolation for sequestering biochemical pathways, controlling metabolic branch points, buffering mRNA translation rates and scaffolding protein-protein interactions. TEARS are a simple and versatile tool for spatially controlling E. coli biochemistry.

synthetic biology↗

bioRxiv2020

Datanator: an integrated database of molecular data for quantitatively modeling cellular behavior

Integrative research about multiple biochemical subsystems has significant potential to help advance biology, bioengineering, and medicine. However, it is difficult to obtain the diverse data needed for integrative research. To facilitate biochemical research, we developed Datanator (https://datanator.info), an integrated database and set of tools for finding clouds of multiple types of molecular data about specific molecules and reactions in specific organisms and environments, as well as data about chemically-similar molecules and reactions in phylogenetically-similar organisms in similar environments. Currently, Datanator includes metabolite concentrations, RNA modifications and half-lives, protein abundances and modifications, and reaction rate constants about a broad range of organisms. Going forward, we aim to launch a community initiative to curate additional data. Datanator also provides tools for filtering, visualizing, and exporting these data clouds. We believe that Datanator can facilitate a wide range of research from integrative mechanistic models, such as whole-cell models, to comparative data-driven analyses of multiple organisms.

systems biology↗

bioRxiv2020

Sticking around: Optimal cell adhesion patterning for energy minimization and substrate mechanosensing

Cell mechanotransduction, in which cells sense and respond to the physical properties of their micro-environments, is proving fundamental to understanding cellular behaviours across biology. Tissue stiffness (Youngs modulus) is typically regarded as the key control parameter and bioengineered gels with defined mechanical properties have become an essential part of the toolkit for interrogating mechanotransduction. We here, however, show using a mechanical cell model that the effective substrate stiffness experienced by a cell depends not just on the engineered mechanical properties of the substrate but critically also on the particular arrangement of adhesions between cell and substrate. In particular, we find that cells with different adhesion patterns can experience two different gel stiffnesses as equivalent and will generate the same mean cell deformations. For small adhesive patches, which mimic experimentally observed focal adhesions, we demonstrate that the observed dynamics of adhesion growth and elongation can be explained by energy considerations. Significantly we show different focal adhesions dynamics for soft and stiff substrates with focal adhesion growth not preferred on soft substrates consistent with reported dynamics. Equally, fewer and larger adhesions are predicted to be preferred over more and smaller, an effect enhanced by random spot placing with the simulations predicting qualitatively realistic cell shapes in this case. The model is based on a continuum elasticity description of the cell and substrate system, with an active stress component capturing cellular contractility. This work demonstrates the necessity of considering the whole cell-substrate system, including the patterning of adhesion, when investigating cell stiffness sensing, with implications for mechanotransductive control in biophysics and tissue engineering. Author summaryCells are now known to sense the mechanical properties of their tissue micro-environments and use this as a signal to control a range of behaviours. Experimentally, such cell mechanotransduction is mostly investigated using carefully engineered gel substrates with defined stiffness. Here we show, using a model integrating active cellular contractility with continuum mechanics, that the way in which a cell senses its environment depends critically not just on the stiffness of the gel but also on the spatial patterning of adhesion sites. In this way, two gels of substantially different stiffnesses can be experienced by the cell as similar, if the adhesions are located differently. Exploiting this insight, we demonstrate that it is energetically favourable for small adhesions to grow and elongate on stiff substrates but that this is not the case on soft substrates. This is consistent with experimental observations that nascent adhesions only mature to stable focal adhesion (FA) sites on stiff substrates where they also grow and elongate. These focal adhesions (FAs) have been the focus of work on mechanotransduction. However, our paper demonstrates that there is a fundamental need to consider the combined cell and micro-environment system moving beyond a focus on individual FAs.

biophysics↗

bioRxiv2020

Lanthipeptide Synthetases Participate the Biosynthesis of 2-Aminovinyl-Cysteine Motifs in Thioamitides

Thioamitides are a group of ribosomally synthesized and post-translational modified peptides with potent antiproliferative and pro-apoptotic activities. Their biosynthesis remains largely unknown, especially for the characteristic C-terminal 2-aminovinyl-Cysteine (AviCys) motifs. Herein, we report the discovery that homologs of class III lanthipeptide synthetases (LanKCts)encoded outside putative thioamitide biosynthetic gene clusters (BGCs) fully dehydrate the precursor peptides. Remarkably, LanKCt enzymes bind tightly to cysteine decarboxylases encoded inside thioamitide BGCs, and the resulting complex complete the macrocyclization of AviCys rings. Furthermore, LanKCt enzymes are present in the genomes of many thioamitide-producing strains and are functional when in complex with cysteine decarboxylases to produce AviCys macrocycles. Thus, our study reveals the participation of lanthipeptide synthetases as a general strategy for dehydration and AviCys formation during thioamitides biosynthesis and thus paves the way for the bioengineering of this class of bioactive natural products.

biochemistry↗

bioRxiv2020

Newly regenerated axons through a cell-containing biomaterial scaffold promote reorganization of spinal circuitry and restoration of motor functions with epidural electrical stimulation.

We report the effect of newly regenerated neural fibers via bioengineered scaffold on reorganization of spinal circuitry and restoration of motor functions with electrical epidural stimulation (EES) after spinal transection (ST). Restoration across multiple modalities was evaluated for 7 weeks after ST with implanted scaffold seeded with Schwann cells, producing neurotrophic factors and with rapamycin microspheres. Gradual improvement in EES-facilitated stepping was observed in animals with scaffolds, although, no significant difference in stepping ability was found between groups without EES. Similar number of regenerated axons through the scaffolds was found in rats with and without EES-enabled training. Re-transection through the scaffold at week 6, reduced EES-enabled motor function, remaining higher compared to rats without scaffolds. The combination of scaffolds and EES-enabled training demonstrated synaptic changes below the injury. These findings indicate that sub-functional connectivity with regenerated across injury fibers can reorganize of sub-lesional circuitry, facilitating motor functions recovery with EES.

neuroscience↗

bioRxiv2020

Topological Assembly of a Deployable Hoberman Flight Ring from DNA

Deployable geometries are finite auxetic structures that preserve their overall shapes during expansion and contraction. The topological behaviors emerge from intricately arranged elements and their connections. Despite considerable utility of such configurations in nature and in engineering, deployable nanostructures have never been demonstrated. Here we show a deployable flight ring, a simplified planar structure of Hoberman sphere, using DNA origami. The DNA flight ring consists of topologically assembled six triangles in two layers that can slide against each other, thereby switching between two distinct (open and closed) states. The origami topology is a trefoil knot, and its auxetic reconfiguration results in negative Poissons ratios. This work shows the feasibility of deployable nanoarchitectures, providing a versatile platform for topological studies and opening new opportunities for bioengineering.

biophysics↗

bioRxiv2020

Design of Biologically Active Binary Protein 2D Materials

Proteins that assemble into ordered two-dimensional arrays such as S-layers1,2 and designed analogues3-5 have intrigued bioengineers,6,7 but with the exception of a single lattice formed through non-rigid template streptavidin linkers,8 they are constituted from just one protein component. For modulating assembly dynamics and incorporating more complex functionality, materials composed of two components would have considerable advantages.9-12 Here we describe a computational method to generate de-novo binary 2D non-covalent co-assemblies by designing rigid asymmetric interfaces between two distinct protein dihedral building-blocks. The designed array components are soluble at mM concentrations, but when combined at nM concentrations, rapidly assemble into nearly-crystalline micrometer-scale p6m arrays nearly identical to the computational design model in vitro and in cells without the need of a two-dimensional support. Because the material is designed from the ground up, the components can be readily functionalized, and their symmetry reconfigured, enabling formation of ligand arrays with distinguishable surfaces to drive extensive receptor clustering, downstream protein recruitment, and signaling. Using quantitative microscopy we show that arrays assembled on living cells have component stoichiometry and likely structure similar to arrays formed in vitro, suggesting that our material can impose order onto fundamentally disordered substrates like cell membranes. We find further that in sharp contrast to previously characterized cell surface receptor binding assemblies such as antibodies and nanocages, which are rapidly endocytosed, large arrays assembled at the cell surface suppress endocytosis in a tunable manner, with potential therapeutic relevance for extending receptor engagement and immune evasion. Our work paves the way towards synthetic cell biology, where a new generation of multi-protein macroscale materials is designed to modulate cell responses and reshape synthetic and living systems. One Sentence SummaryCo-assembling binary 2D protein crystals enables robust formation of complex large scale ordered biologically active materials

synthetic biology↗

bioRxiv2020

Virus-Like Particle Based-Vaccines Elicit Neutralizing Antibodies against the HIV-1 Fusion Peptide

Broadly neutralizing antibodies (bnAbs) isolated from HIV-infected individuals delineate vulnerable sites on the HIV envelope glycoprotein that are potential vaccine targets. A linear epitope at the N-terminal region of the HIV-1 fusion peptide (FP8) is the primary target of VRC34.01, a bnAb that neutralizes ~50% of primary HIV isolates. FP8 has attracted attention as a potential HIV vaccine target because it is a simple linear epitope. Here, we used platform technologies based on RNA bacteriophage virus-like particles (VLPs) to develop multivalent vaccines targeting the FP8 epitope. We produced recombinant MS2 VLPs displaying the FP8 peptide and we chemically conjugated synthetic FP8 peptides to Q{beta} VLPs. Both recombinant and conjugated FP8-VLPs induced high titers of FP8-specific antibodies in mice. A heterologous prime-boost-boost regimen employing the two FP8-VLP vaccines and native envelope trimer was the most effective approach for eliciting HIV-1 neutralizing antibodies. Given the potent immunogenicity of VLP-based vaccines, this vaccination strategy - inspired by bnAb-guided epitope mapping, VLP bioengineering, and optimal prime-boost immunization strategies - may be an effective strategy for eliciting bnAb responses against HIV.

immunology↗

bioRxiv2020

Model-guided design of mammalian genetic programs

Genetically engineering cells to perform customizable functions is an emerging frontier with numerous technological and translational applications. However, it remains challenging to systematically engineer mammalian cells to execute complex functions. To address this need, we developed a method enabling accurate genetic program design using high-performing genetic parts and predictive computational models. We built multi-functional proteins integrating both transcriptional and post-translational control, validated models for describing these mechanisms, implemented digital and analog processing, and effectively linked genetic circuits with sensors for multi-input evaluations. The functional modularity and compositional versatility of these parts enable one to satisfy a given design objective via multiple synonymous programs. Our approach empowers bioengineers to predictively design mammalian cellular functions that perform as expected even at high levels of biological complexity.

synthetic biology↗

bioRxiv2020

Gastruloids generated without exogenous Wnt activation develop anterior neural tissues

When stimulated with a pulse from an exogenous WNT pathway activator, small aggregates of mouse embryonic stem cells (ESCs) can undergo embryo-like axial morphogenesis and patterning along the three major body axes. However, these structures, called gastruloids, currently lack the anterior embryonic regions, such as those belonging to the brain. Here we describe an approach to generate gastruloids that have a more complete antero-posterior development. We used bioengineered hydrogel microwell arrays to promote the robust derivation of mouse ESCs into post-implantation epiblast-like (EPI) aggregates in a reproducible and scalable manner. These EPI aggregates break symmetry and axially elongate without external chemical stimulation. Inhibition of WNT signaling in early stages of development leads to the formation of gastruloids with anterior neural tissues. Thus, we provide a new tool to study the development of the mouse after implantation in vitro, especially the formation of anterior neural regions.

developmental biology↗

bioRxiv2020

Molecular mechanism of high affinity sugar transport in plants unveiled by structures of glucose/H+ symporter STP10

Sugars are essential sources of energy and carbon, and also function as key signaling molecules in plants. Sugar Transport Proteins (STP) are proton-coupled symporters, solely responsible for uptake of glucose from the apoplastic compartment into cells in all plant tissues. They are integral to organ development in symplastically isolated tissues such as seeds, pollen and fruit. Additionally, STPs play a significant role in plant responses to both environmental stressors such as dehydration, and prevalent fungal infections like rust and mildew. Here, we present two high-resolution crystal structures of the outward-occluded and inward-open conformations of Arabidopsis thaliana STP10 with glucose and protons bound. The two structures describe key states in the STP transport cycle. Together with in vivo biochemical analysis and Molecular Dynamics simulations they pinpoint structural elements that explain how STPs exhibit high affinity for sugar binding on the extracellular side and how it is considerably lowered on the intracellular side to facilitate substrate release. These structural elements, conserved in all STPs across plant species, clarify the basis of proton-to-glucose coupling, essential for symport. The results advance our understanding of a key molecular mechanism behind plant organ development, and sets the stage for novel bioengineering strategies in crops that could target seeds, fruits and plant resistance to fungal infections.

plant biology↗

bioRxiv2020

Construction of a liquid-liquid phase separation system from the gel-sol transition of elongated protein microgels in a crowding agent

Liquid proteinaceous materials have been frequently found in cells or tissues and are crucial for various biological processes. Unlike their solid-state counterparts, liquid-state protein compartments are challenging to engineer and control at the microscale. Conventionally, gelation (sol-gel transition) of biological molecules has been thought to be the intermediate step between liquid-liquid phase separation (LLPS) states and insoluble aggregates that are related to protein functions, malfunctions and even diseases. However, the opposite process, i.e., the gel-sol transition of materials, has not been broadly explored. Here we describe a thermoresponsive gel-sol transition of a protein in a crowded environment that results in a demixed LLPS state, contradicting the common consequence of a one-phase protein solution by the end of such transition at elevated temperature without crowding agents. We also demonstrate a simple method to monitor the gel-sol transition by showing that elongated gelatin microgels can evolve towards a spherical morphology in the crowding agents because of interfacial tension. The LLPS system was explored for the diffusion of small particles for drug-release application scenarios. Our results demonstrate a route for the rapid construction of LLPS models, where the gel-sol transition of the protein-rich phase is monitorable. The models are featured with tunable size and dimensional monodispersity of dispersed condensates. The present study can be employed in biophysics and bioengineering with practices such as 3D printing and temperature sensing.

biophysics↗

bioRxiv2020

Shedding Light on Microbial Dark Matter with A Universal Language of Life

The majority of microbial genomes have yet to be cultured, and most proteins predicted from microbial genomes or sequenced from the environment cannot be functionally annotated. As a result, current computational approaches to describe microbial systems rely on incomplete reference databases that cannot adequately capture the full functional diversity of the microbial tree of life, limiting our ability to model high-level features of biological sequences. The scientific community needs a means to capture the functionally and evolutionarily relevant features underlying biology, independent of our incomplete reference databases. Such a model can form the basis for transfer learning tasks, enabling downstream applications in environmental microbiology, medicine, and bioengineering. Here we present LookingGlass, a deep learning model capturing a "universal language of life". LookingGlass encodes contextually-aware, functionally and evolutionarily relevant representations of short DNA reads, distinguishing reads of disparate function, homology, and environmental origin. We demonstrate the ability of LookingGlass to be fine-tuned to perform a range of diverse tasks: to identify novel oxidoreductases, to predict enzyme optimal temperature, and to recognize the reading frames of DNA sequence fragments. LookingGlass is the first contextually-aware, general purpose pre-trained "biological language" representation model for short-read DNA sequences. LookingGlass enables functionally relevant representations of otherwise unknown and unannotated sequences, shedding light on the microbial dark matter that dominates life on Earth. AvailabilityThe pretrained LookingGlass model and the transfer learning-derived models demonstrated in this paper are available in the LookingGlass release v1.01. The open source fastBio Github repository and python package provides classes and functions for training and fine tuning deep learning models with biological data2. Code for reproducing analyses presented in this paper are available as an open source Github repository3.

bioinformatics↗

bioRxiv2020

Comprehensive analysis and genome-wide association studies of biomass, chlorophyll, seed and salinity tolerance related traits in rice highlight genetic hotspots for crop improvement

Farmland is on the decline and worldwide food security is at risk. Rice is the staple of choice for over half the Earths people. To sustain current demands and ascertain a food secure future, substandard farmland affected by abiotic stresses must be utilized. For rapid crop improvement, a broader understanding of polygenic traits like stress tolerance and crop yield is indispensable. To this end, the hidden diversity of resilient and neglected wild varieties must be traced back to their genetic roots. In this study, we separately assayed 15 phenotypes in a panel of 176 diverse accessions predominantly comprised of local landraces from Bangladesh. We compiled high resolution sequence data for these accessions. We collectively studied the ties between the observed phenotypic differences and the examined additive genetic effects underlying these variations. We applied a sophisticated fixed effect model to associate phenotypes with genotypes on a genomic scale. Discovered QTLs were mapped to known genes. Candidate genes were sorted by tissue specific gene expression profiles and protein level consequence of existing polymorphisms. Our explorations yielded 17 QTLs related to various traits in multiple trait classes. 12 identified QTLs were equivalent to findings from previous studies. Integrative analysis assumes novel functionality for 21 candidate genes on multiple evidence levels. These findings will usher novel avenues for the bioengineering of high yielding crops of the future fortified with genetic defenses against abiotic stressors.

plant biology↗

bioRxiv2020

Enhancing multi-bioreactor platforms for automated measurements and reactive experiment control

New small-scale, low-cost bioreactors provide researchers with exquisite control of environmental parameters of microbial cultures over long durations, allowing them to perform sophisticated, high-quality quantitative experiments that are particularly useful in systems biology, synthetic biology and bioengineering. However, existing setups are limited in their automated measurement capabilities, primarily because sensitive and specific measurements require bulky, expensive, stand-alone instruments. Here, we present ReacSight, a generic and flexible strategy to enhance bioreactor arrays for automated measurements and reactive experiment control. On the hardware side, ReacSight leverages a pipetting robot for sample collection, handling and loading. On the software side, ReacSight provides a versatile instrument control architecture and a generic event system for reactive experiment control. ReacSight is ideally suited to integrate open-source, open-hardware components but can also accommodate closed-source, GUI-only components (e.g. cytometers). We use ReacSight to assemble a platform for cytometry-based characterization and reactive optogenetic control of parallel yeast continuous cultures. Using a dedicated bioreactor array, we showcase its capabilities on three applications. First, we achieve parallel real-time control of gene expression with light in different bioreactors. Second, we explore the impact of nutrient scarcity on fitness and cellular stress using well-controlled, high-information content competition assays. Third, we exploit nutrient scarcity to achieve dynamic control over the composition of a two-strain consortium. To illustrate the genericity of ReacSight, we also assemble an equivalent platform using the optogenetic-ready, open-hardware and commercially available Chi.Bio bioreactors.

synthetic biology↗