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Results for “Synthetic Biology”

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 Read source abstracts and check manuscript versions; preprints are not peer reviewed.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 217 records · Page 12Linked to original sources

bioRxiv2018

A homing CRISPR mouse resource for barcoding and lineage tracing

Cellular barcoding using nuclease-induced genetic mutations is an effective approach that is emerging for recording biological information, including developmental lineages. We have previously introduced the homing CRISPR system as a promising methodology for generating such barcodes with scalable diversity and without crosstalk. Here, we present a mouse line (MARC1) with multiple genomically-integrated and heritable homing guide RNAs (hgRNAs). We determine the genomic locations of these hgRNAs, their activity profiles during gestation, and the diversity of their mutants. We apply the line for unique barcoding of mouse embryos and differential barcoding of embryonic tissues. We conclude that this mouse line can address the unique challenges associated with in vivo barcoding in mammalian model organisms and is thus an enabling platform for recording and lineage tracing applications in a mammalian model system.

synthetic biology↗

bioRxiv2016

Engineering Genetically-Encoded Mineralization and Magnetism via Directed Evolution

Genetically encoding the synthesis of functional nanomaterials such as magnetic nanoparticles enables sensitive and non-invasive biological sensing and control. Via directed evolution of the natural iron-sequestering ferritin protein, we discovered key mutations that lead to significantly enhanced cellular magnetism, resulting in increased physical attraction of ferritin-expressing cells to magnets and increased contrast for cellular magnetic resonance imaging (MRI). The magnetic mutants further demonstrate increased iron biomineralization measured by a novel fluorescent genetic sensor for intracellular free iron. In addition, we engineered Escherichia coli cells with multiple genomic knockouts to increase cellular accumulation of various metals. Lastly to explore further protein candidates for biomagnetism, we characterized members of the DUF892 family using the iron sensor and magnetic columns, confirming their intracellular iron sequestration that results in increased cellular magnetization.

synthetic biology↗

bioRxiv2018

Chemical Characterization of Interacting Genes in Few Subnetworks of Alzheimer’s Disease

A number of genes have been identified as a key player in Alzheimers disease (AD). Topological analysis of co-expression network reveals that key genes are mostly central or hub genes. The association between a hub gene and its neighbour genes can be derived easily using relative abundance of their expression levels. However, it is still unexplored fact that whether any hub and its neighbour genes within a sub-network exhibits any kind of proximity with respect to their chemical properties of the DNA sequences or not, that code for a sequence of amino acids.\n\nIn this work, we try to make a quantitative investigation of the underlying biological facts in DNA sequential and primary protein level in mathematical paradigm. It may gives a holistic view of the interrelationships existing between hub genes and neighbour genes in few selective AD subnetworks. We define a mapping model from physicochemical properties of DNA sequence to chemical characterization of amino acid sequences. We use distribution of chemical groups present in a sequence after decoding into corresponding amino acids to investigate the fact that whether any hub genes are associated closely with its neighbour genes chemically in the subnetworks. Interestingly, our preliminary results confirm the fact the dependent genes that are coexpressed with its hub gene are also having proximity with respect to their amino acid chemical group distributions.\n\nCCS Concepts*Applied computing [->] Computational genomics;

synthetic biology↗

bioRxiv2016

Retargeting: an unrecognized consideration in endonuclease-based gene drive biology

There is intense interest surrounding the use of gene editing nucleases in gene drive systems to control agricultural insect pests and insect vectors of infectious diseases such as malaria, dengue and Zika virus. While gene drive systems offer immense promise for the beneficial modification of deleterious insect populations, their unique mechanism of action also raises novel safety concerns and regulatory issues. A recent US National Academies of Science report provides a list of potential regulatory issues associated with implementation of homologous recombination (HR)-mediated gene drive systems, based on the premise that all such systems would exhibit similar biological behaviors. Here we examine how HR-mediated gene drive systems based on different gene editing nuclease platforms could be affected by mutations that occur during host cell transcription, genome replication, and, in conjunction with gene editing nuclease activity, during HR-mediated gene drive. Our analysis suggests that the same feature that makes RNA-guided nucleases such attractive research tools--their ease of reprogramming by alterations to their guide RNA components--might also contribute to increased rates of retargeting that could influence the long term behavior of RNA-guided gene drive systems. Predictability of behavior over time is an issue that should be addressed by in-depth risk assessment before field testing of organisms incorporating nuclease-mediated gene drives.

synthetic biology↗

bioRxiv2026

Uncertainty Quantification in Stochastic Dynamical Gene Regulatory Networks

The dynamics of gene regulatory networks are governed by intrinsic noise, stemming from the random nature of biochemical reactions, and by extrinsic noise, arising from fluctuations in cellular components and environmental conditions. Together, these sources can compromise the reliability of predictive computational models if not properly accounted for, and capturing both effects within a single framework remains a non-trivial task in computational biology. In this work, we propose an uncertainty quantification framework that addresses these two contributions jointly: intrinsic stochasticity is described through a partial integro-differential equation (PIDE) for the protein probability density function, whereas extrinsic noise is represented as parametric uncertainty in the kinetic parameters. The propagation of the uncertainty is carried out via an intrusive polynomial chaos expansion (PCE), in which the PCE coefficients are obtained from a stochastic Galerkin projection of the PIDE, yielding a coupled deterministic system that is solved with standard numerical methods. We illustrate the approach on a positive autoregulatory gene network with one and two uncertain kinetic parameters. The proposed approach accurately reproduces the mean, variance, and full protein probability density function, including the bimodal distributions, at a substantially lower computational cost.

synthetic biology↗

bioRxiv2018

Dynamic decoupling of biomass and lipid biosynthesis by autonomously regulated switch

For improving the microbial production of fuels and chemicals, gene knock-outs and overexpression are routinely applied to intensify the carbon flow from substrate to product. However, their possibilities in dynamic control of the flux between the biomass and product synthesis are limited, whereas dynamic metabolic switches can be used for optimizing the distribution of carbon and resources. The production of single cell oils is especially challenging, as the synthesis is strongly regulated, competes directly with biomass, and requires defined conditions, such as nitrogen limitation. Here, we engineered a metabolic switch for redirecting carbon flow from biomass to wax ester production in Acinetobacter baylyi ADP1 using acetate as a carbon source. Isocitrate lyase, an essential enzyme for growth on acetate, was expressed under an arabinose inducible promoter. The autonomous downregulation of the expression is based on the gradual oxidation of the arabinose inducer by a glucose dehydrogenase gcd. The depletion of the inducer, occurring simultaneously to acetate consumption, switches the cells from a biomass mode to a lipid synthesis mode, enabling the efficient channelling of carbon to wax esters in a simple batch culture. In the engineered strain, the yield and titer of wax esters were improved by 3.8 and 3.1 folds, respectively, over the control strain. In addition, the engineered strain accumulated wax esters 19% of cell dry weight, being the highest reported among microbes. The study provides important insights into the dynamic engineering of the biomass-dependent synthesis pathways for the improved production of biocompounds from low-cost, sustainable substrates.\n\nSignificance statementIn the biological production, one of the greatest challenges is to find ways for optimal distribution of resources between cell growth, maintenance, and product synthesis. Robust and reliable circuits are required to allow autonomous switching of cells from biomass mode to lipid synthesis mode. Dynamic production of single cell oils such as triacylglycerols and wax esters is especially challenging due to the strong regulation. We present a dynamic genetic circuit based on conditional knockdown of a glyoxylate shunt enzyme, which is essential for cell growth. By gradual repression of the gene, the cells autonomously switch from biomass mode to product synthesis mode. We demonstrate the functionality of the circuit by using bacterium Acinetobacter baylyi ADP1 for the production of long chain alkyl esters, namely wax esters, with titer and yield improved by over 3-fold using acetate as the carbon source.

synthetic biology↗

bioRxiv2018

Enzymatic DNA synthesis for digital information storage

DNA is an emerging storage medium for digital data but its adoption is hampered by limitations of phosphoramidite chemistry, which was developed for single-base accuracy required for biological functionality. Here, we establish a de novo enzymatic DNA synthesis strategy designed from the bottom-up for information storage. We harness a template-independent DNA polymerase for controlled synthesis of sequences with user-defined information content. We demonstrate retrieval of 144-bits, including addressing, from perfectly synthesized DNA strands using batch-processed Illumina and real-time Oxford Nanopore sequencing. We then develop a codec for data retrieval from populations of diverse but imperfectly synthesized DNA strands, each with a ~30% error tolerance. With this codec, we experimentally validate a kilobyte-scale design which stores 1 bit per nucleotide. Simulations of the codec support reliable and robust storage of information for large-scale systems. This work paves the way for alternative synthesis and sequencing strategies to advance information storage in DNA.

synthetic biology↗

bioRxiv2018

Development of a multi-locus CRISPR gene drive system in budding yeast

The discovery of CRISPR/Cas gene editing has allowed for major advances in many biomedical disciplines and basic research. One arrangement of this biotechnology, a nuclease-based gene drive, can rapidly deliver a genetic element through a given population and studies in fungi and metazoans have demonstrated the success of such a system. This methodology has the potential to control biological populations and contribute to eradication of insect-borne diseases, agricultural pests, and invasive species. However, there remain challenges in the design, optimization, and implementation of gene drives including concerns regarding biosafety, containment, and control/inhibition. Given the numerous gene drive arrangements possible, there is a growing need for more advanced designs. In this study, we use budding yeast to develop an artificial multi-locus gene drive system. Our minimal setup requires only a single copy of S. pyogenes Cas9 and three guide RNAs to propagate three separate gene drives. We demonstrate how this system could be used for targeted allele replacement of native genes and to suppress NHEJ repair systems by modifying DNA Ligase IV. A multi-locus gene drive configuration provides an expanded suite of options for complex attributes including pathway redundancy, combatting evolved resistance, and safeguards for control, inhibition, or reversal of drive action.

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bioRxiv2015

Connecting Boolean Integrase Logic gates to a novel alkane control signal via engineered level matching.

Boolean Integrase Logic gates use phage integrases that respond to transcriptional signals to implement logical functions within living cells via DNA recombination. Control of biological systems using these logic gates has many applications, including biomanufacturing, healthcare, or environmental remediation. Gates are highly sensitive to background transcriptional noise producing unwanted integrase expression and uncontrolled, permanent gate switching. Consequently, connecting gates to novel control signals requires time-consuming directed evolution of regions regulating integrase expression. Here we present an approach in which the activity of an alkane biosensor is tuned to match levels of existing integrase control signals. By adjusting AlkS expression, we tuned the transcriptional output of Palkb to match the output of existing integrase controllers. We successfully connected Palkb to two integrases with different transcriptional control requirements and demonstrated the original logic function was conserved. Our method complements directed evolution approaches to connect Boolean integrate logic gates to novel transcriptional sources and will ultimately facilitate the systematic in silico design of gates responding to various control signals.

Synthetic Biology↗

bioRxiv2018

A tunable dual-input system for on-demand dynamic geneexpression regulation.

Cellular systems have evolved numerous mechanisms to finely control signalling pathway activation and properly respond to changing environmental stimuli. This is underpinned by dynamic spatiotemporal patterns of gene expression. Indeed, in addition to gene transcription and translation regulation, modulation of protein levels, dynamics and localization are also essential checkpoints that govern cell functions. The introduction of tetracycline-inducible promoters has allowed gene expression control using orthogonal small molecules, facilitating rapid and reversible manipulation to study gene function in biological systems. However, differing protein stabilities means this solely transcriptional regulation is insufficient to allow precise ON-OFF dynamics, thus hindering generation of temporal profiles of protein levels seen in vivo. We developed an improved Tet-On based system augmented with conditional destabilising elements at the post-translational level that permits simultaneous control of gene expression and protein stability. Integrating these properties to control expression of a fluorescent protein in mouse Embryonic Stem Cells (mESCs), we found that adding protein stability control allows faster response times to changes in small molecules, fully tunable and enhanced dynamic range, and vastly improved microfluidic-based in-silico feedback control of gene expression. Finally, we highlight the effectiveness of our dual-input system to finely modulate levels of signalling pathway components in stem cells.

synthetic biology↗

bioRxiv2017

Dynamic blue light-inducible T7 RNA polymerases (Opto-T7RNAPs) for precise spatiotemporal gene expression control

Light has emerged as control input for biological systems due to its precise spatiotemporal resolution. The limited toolset for light control in bacteria motivated us to develop a light-inducible transcription system that is independent from cellular regulation through the use of an orthogonal RNA polymerase. Here, we present our engineered blue light-responsive T7 RNA polymerases (Opto-T7RNAPs) that show properties such as low leakiness of gene expression in the dark-state, high expression strength when induced with blue light, or an inducible range of more than 300-fold. Following optimization of the system to reduce expression variability, we have created a variant, which returns to the inactive dark-state within minutes, once blue light is turned off. This allows for precise dynamic control of gene expression, which is a key aspect for most applications using optogenetic regulation. The regulators were developed and tested in the bacterium Escherichia coli, which is a crucial cell factory for biotechnology due to its fast and inexpensive cultivation and well understood physiology and genetics. However, minor alterations should be sufficient to allow their use in other species in which the T7 RNAP polymerase and the light-inducible Vivid regulator were shown to be functional, which comprises other bacterial species and eukaryotes such as mammalian cells or yeast. We anticipate that our approach will expand the applicability of using light as an inducer for gene expression independent from cellular regulation, and allow for a more reliable dynamic control of synthetic and natural gene networks.

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bioRxiv2018

Design and analysis of a Proportional-Integral-Derivative controller with biological molecules

The ability of cells to regulate their function through feedback control is a fundamental underpinning of life. The capability to engineer de novo feedback control with biological molecules is ushering in an era of robust functionality for many applications in biotechnology and medicine. To fulfill their potential, feedback control strategies implemented with biological molecules need to be generalizable, modular and operationally predictable. Proportional-Integral-Derivative (PID) control fulfills this role for technological systems and is a commonly used strategy in engineering. Integral feedback control allows a system to return to an invariant steady-state value after step disturbances, hence enabling its robust operation. Proportional and derivative feedback control used with integral control help sculpt the dynamics of the return to steady-state following perturbation. Recently, a biomolecular implementation of integral control was proposed based on an antithetic motif in which two molecules interact stoichiometrically to annihilate each others function. In this work, we report how proportional and derivative implementations can be layered on top of this integral architecture to achieve a biochemical PID control design. We illustrate through computational and analytical treatments that the addition of proportional and derivative control improves performance, and discuss practical biomolecular implementations of these control strategies.

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bioRxiv2018

Toward machine-guided design of proteins

Proteins--molecular machines that underpin all biological life--are of significant therapeutic and industrial value. Directed evolution is a high-throughput experimental approach for improving protein function, but has difficulty escaping local maxima in the fitness landscape. Here, we investigate how supervised learning in a closed loop with DNA synthesis and high-throughput screening can be used to improve protein design. Using the green fluorescent protein (GFP) as an illustrative example, we demonstrate the opportunities and challenges of generating training datasets conducive to selecting strongly generalizing models. With prospectively designed wet lab experiments, we then validate that these models can generalize to unseen regions of the fitness landscape, even when constrained to explore combinations of non-trivial mutations. Taken together, this suggests a hybrid optimization strategy for protein design in which a predictive model is used to explore difficult-to-access but promising regions of the fitness landscape that directed evolution can then exploit at scale.

synthetic biology↗

bioRxiv2018

Modulating CRISPR gene drive activity through nucleocytoplasmic localization of Cas9 in S. cerevisiae

The bacterial CRISPR/Cas genome editing system has provided a major breakthrough in molecular biology. One use of this technology is within a nuclease-based gene drive. This type of system can install a genetic element within a population at unnatural rates. Combatting of vector-borne diseases carried by metazoans could benefit from a delivery system that bypasses traditional Mendelian laws of segregation. Recently, laboratory studies in fungi, insects, and even mice, have demonstrated successful propagation of CRISPR gene drives and the potential utility of this type of mechanism. However, current gene drives still face challenges including evolved resistance, containment, and the consequences of application in wild populations. In this study, we use an artificial gene drive system in budding yeast to explore mechanisms to modulate nuclease activity of Cas9 through its nucleocytoplasmic localization. We examine non-native nuclear localization sequences on Cas9 fusion proteins in vivo and demonstrate that appended signals can titrate gene drive activity and serve as a potential molecular safeguard.

synthetic biology↗

bioRxiv2017

Simple, single-step, and scar-free mutagenesis of bacterial genes

The need for generating precisely designed mutations is common in genetics, biochemistry, and molecular biology. Here, I describe a new {lambda} Red recombineering method (Direct and Inverted Repeat stimulated excision; DIRex) for fast and easy generation of single point mutations, small insertions or replacements as well as deletions of any size, in bacterial genes. The method does not leave any resistance marker or scar sequence and requires only one transformation to generate a semi-stable intermediate insertion mutant. Spontaneous excision of the intermediate efficiently and accurately generates the final mutant. In addition, the intermediate is transferable between strains by generalized transductions, enabling transfer of the mutation into multiple strains without repeating the recombineering step. Existing methods that can be used to accomplish similar results are either (i) more complicated to design, (ii) more limited in what mutation types can be made, or (iii) require expression of extrinsic factors in addition to {lambda} Red. I demonstrate the utility of the method by generating several deletions, small insertions/replacements, and single nucleotide exchanges in Escherichia coli and Salmonella enterica. Furthermore, the design parameters that influence the excision frequency and the success rate of generating desired point mutations have been examined to determine design guidelines for optimal efficiency.

synthetic biology↗

bioRxiv2017

Construction and optimization of a heterologous pathway for protocatechuate catabolism in Escherichia coli enables rapid bioconversion of model lignin monomers

Cellulosic biofuel production yields a substantial lignin byproduct stream that currently has few applications. Biological conversion of lignin compounds into chemicals and fuels has the potential to improve the economics of cellulosic biofuels, but few microbes are able both to catabolize lignin and generate valuable products. While Escherichia coli has been engineered to produce a variety of fuels and chemicals, it is incapable of catabolizing most aromatic compounds. Therefore, we have engineered E. coli to catabolize a model lignin monomer, protocatechuate, as the sole source of carbon and energy, via heterologous expression of a nine-gene pathway from Pseudomonas putida KT2440. We next used experimental evolution to select for mutations that increased growth with PCA more than two-fold. Increasing the strength of a single ribosome binding site in the heterologous pathway was sufficient to recapitulate the increased growth. After optimization of the core pathway, we extended the pathway to enable catabolism of a second model compound, 4-hydroxybenzoate. These engineered strains will be useful platforms to discover, characterize, and optimize pathways for lignin bioconversions.\n\nHighlightsO_LIA heterologous pathway for PCA catabolism was transferred to Escherichia coli.\nC_LIO_LIEvolution identified a mutation that increased growth with PCA by 2.5-fold.\nC_LIO_LIOptimization plus further engineering allowed efficient catabolism of 4-HB\nC_LI

synthetic biology↗

bioRxiv2018

A low-cost biological agglutination assay for medical diagnostic applications

Affordable, easy-to-use diagnostic tests that can be readily deployed for point-of-care (POC) testing are key in addressing challenges in the diagnosis of medical conditions and for improving global health in general. Ideally, POC diagnostic tests should be highly selective for the biomarker, user-friendly, have a flexible design architecture and a low cost of production. Here we developed a novel agglutination assay based on whole E. coli cells surface-displaying nanobodies which bind selectively to a target protein analyte. As a proof-of-concept, we show the feasibility of this design as a new diagnostic platform by the detection of a model analyte at nanomolar concentrations. Moreover, we show that the design architecture is flexible by building assays optimized to detect a range of model analyte concentrations supported using straight-forward design rules and a mathematical model. Finally, we re-engineer E. coli cells for the detection of a medically relevant biomarker by the display of two different antibodies against the human fibrinogen and demonstrate a detection limit as low as 10 pM in diluted human plasma. Overall, we demonstrate that our agglutination technology fulfills the requirement of POC testing by combining low-cost nanobody production, customizable detection range and low detection limits. This technology has the potential to produce affordable diagnostics for both field-testing in the developing world, emergency or disaster relief sites as well as routine medical testing and personalized medicine.

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bioRxiv2017

Context-Dependent Genetic Regulation

Cells process extra-cellular signals with multiple layers of complex biological networks. Due to the stochastic nature of the networks, the signals become significantly noisy within the cells and in addition, due to the nonlinear nature of the networks, the signals become distorted, shifted, and (de-)amplified. Such nonlinear signal processing can lead to non-trivial cellular phenotypes such as cell cycles, differentiation, cell-to-cell communication, and homeostasis. These nonlinear pheno-types, when observed at the cell population levels, can be quite different from the single-cell level observation. As one of the underlying mechanisms behind this difference, we report the interplay between nonlinearity and stochasticity in genetic regulation. Here we show that nonlinear genetic regulation, characterized at the cellular population level, can be affected by cell-to-cell variability in the regulatory factor concentrations. The observed genetic regulation at the cell population is shown to be significantly dependent on the upstream DNA sequences of the regulator, in particular, 5 untranslated region. This indicates that genetic regulation observed at the cell population level can be significantly dependent on its genetic context, and that its characterization needs a careful attention on noise propagation.\n\nOne Sentence SummaryGenetic regulation observed at the cell population level can be significantly affected by cell-to-cell variability in the regulatory factor copy numbers, indicating that the observed regulation is dependent on 5 UTR of the regulator coding gene.

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