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Rxivist combines preprints from bioRxiv with data from Twitter to help you find the papers being discussed in your field. Currently indexing 84,950 bioRxiv papers from 365,437 authors.

Most downloaded bioRxiv papers, all time

in category synthetic biology

774 results found. For more information, click each entry to expand.

61: Burden-driven feedback control of gene expression
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Posted to bioRxiv 20 Aug 2017

Burden-driven feedback control of gene expression
1,890 downloads synthetic biology

F Ceroni, S Furini, Thomas E. Gorochowski, A Boo, O Borkowski, YN Ladak, Ali R. Awan, C Gilbert, Guy-Bart V Stan, Tom Ellis

Cells use feedback regulation to ensure robust growth despite fluctuating demands on resources and different environmental conditions. Yet the expression of foreign proteins from engineered constructs is an unnatural burden on resources that cells are not adapted for. Here we combined multiplex RNAseq with an in vivo assay to reveal the major transcriptional changes in two E. coli strains when a set of inducible synthetic constructs are expressed. We identified that native promoters related to the heat-shock response activate expression rapidly in response to synthetic expression, regardless of the construct. Using these promoters, we built a CRISPR/dCas9-based feedback regulation system that automatically adjusts synthetic construct expression in response to burden. Cells equipped with this general-use controller maintain capacity for native gene expression to ensure robust growth and as such outperform unregulated cells at protein yields in batch production. This engineered feedback is the first example of a universal, burden-based biomolecular control system and is modular, tuneable and portable.

62: Measurements of translation initiation from all 64 codons in E. coli
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Posted to bioRxiv 14 Jul 2016

Measurements of translation initiation from all 64 codons in E. coli
1,878 downloads synthetic biology

Ariel Hecht, Jeff Glasgow, Paul R. Jaschke, Lukmaan Bawazer, Matthew S. Munson, Jennifer Cochran, Drew Endy, Marc Salit

Our understanding of translation is one cornerstone of molecular biology that underpins our capacity to engineer living matter. The canonical start codon (AUG) and a few near-cognates (GUG, UUG) are typically considered as the start codons for translation initiation in Escherichia coli (E. coli). Translation is typically not thought to initiate from the 61 remaining codons. Here, we systematically quantified translation initiation in E. coli from all 64 triplet codons. We detected protein synthesis above background initiating from at least 46 codons. Translation initiated from these non-canonical start codons at levels ranging from 0.01% to 2% relative to AUG. Translation initiation from non-canonical start codons may contribute to the synthesis of peptides in both natural and synthetic biological systems.

63: DNA writing at a single genomic site enables lineage tracing and analog recording in mammalian cells
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Posted to bioRxiv 16 May 2019

DNA writing at a single genomic site enables lineage tracing and analog recording in mammalian cells
1,874 downloads synthetic biology

Theresa B Loveless, Joseph H Grotts, Mason W Schechter, Elmira Forouzmand, Courtney K Carlson, Bijan S Agahi, Guohao Liang, Michelle Ficht, Beide Liu, Xiaohui Xie, Chang C. Liu

The study of intricate cellular and developmental processes in the context of complex multicellular organisms is difficult because it can require the non-destructive observation of thousands, millions, or even billions of cells deep within an animal. To address this difficulty, several groups have recently reported CRISPR-based DNA recorders that convert transient cellular experiences and processes into changes in the genome, which can then be read by sequencing in high-throughput. However, existing DNA recorders act primarily by erasing DNA: they use the random accumulation of CRISPR-induced deletions to record information. This is problematic because in the limit of progressive deletion, no record remains. Here, we present a new type of DNA recorder that acts primarily by writing new DNA. Our system, called CHYRON (Cell HistorY Recording by Ordered iNsertion), inserts random nucleotides at a single locus in temporal order in vivo and can be applied as an evolving lineage tracer as well as a recorder of user-selected cellular stimuli. As a lineage tracer, CHYRON allowed us to perfectly reconstruct the population lineage relationships among 16 groups of human cells descended from four starting groups that were subject to a series of splitting steps. In this experiment, CHYRON progressively wrote and retained base insertions in 20% percent of cells where the average amount written was 8.4 bp (~14.5 bits), reflecting high information content and density. As a stimulus recorder, we showed that when the CHYRON machinery was placed under the control of a stress-responsive promoter, the frequency and length of writing reflected the dose and duration of the stress. We believe CHYRON represents a conceptual advance in DNA recording technologies where writing rather than erasing becomes the primary mode of information accumulation. With further engineering of CHYRON’s components to increase writing efficiency, CHYRON should lead to single-cell-resolution recording of lineage and other information through long periods of time in complex animals or tumors, advancing the pursuit of a full picture of mammalian development. * CRISPR : clustered regularly interspaced short palindromic repeat, DNA : deoxyribonucleic acid, CHYRON : cell history recording by ordered insertion, bp : base pair (of DNA), TdT : terminal deoxynucleotidyl transferase, hgRNA : homing guide ribonucleic acid, stgRNA : selftargeting guide RNA, Cas9 : CRISPR-associated 9, GFP : green fluorescent protein, DSB : double-strand break (in DNA), nt : nucleotide (of DNA or RNA), sgRNA : single-guide RNA, stdev : standard deviation.

64: Engineering Brain Parasites for Intracellular Delivery of Therapeutic Proteins
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Posted to bioRxiv 03 Dec 2018

Engineering Brain Parasites for Intracellular Delivery of Therapeutic Proteins
1,812 downloads synthetic biology

Shahar Bracha, Karoliina Hassi, Paul D. Ross, Stuart Cobb, Lilach Sheiner, Oded Rechavi

Protein therapy has the potential to alleviate many neurological diseases; however, delivery mechanisms for the central nervous system (CNS) are limited, and intracellular delivery poses additional hurdles. To address these challenges, we harnessed the protist parasite Toxoplasma gondii, which can migrate into the CNS and secrete proteins into cells. Using a fusion protein approach, we engineered T. gondii to secrete therapeutic proteins for human neurological disorders. We tested two secretion systems, generated fusion proteins that localized to the secretory organelles of T. gondii and assessed their intracellular targeting in various mammalian cells including neurons. We show that T. gondii expressing GRA16 fused to the Rett syndrome protein MeCP2 deliver a fusion protein that mimics the endogenous MeCP2, binding heterochromatic DNA in neurons. This demonstrates the potential of T. gondii as a therapeutic protein vector, which could provide either transient or chronic, in situ synthesis and delivery of intracellular proteins to the CNS.

65: An Engineered Cas-Transposon System for Programmable and Precise DNA Transpositions
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Posted to bioRxiv 03 Jun 2019

An Engineered Cas-Transposon System for Programmable and Precise DNA Transpositions
1,806 downloads synthetic biology

Sway P. Chen, Harris H. Wang

Efficient targeted insertion of heterologous DNA into a genome remains a challenge in genome engineering. Recombinases that can introduce kilobase-sized DNA constructs require pre-existing recombination sites to be present in the genome and are difficult to reprogram to other loci. Genome insertion using current CRISPR-Cas methods relies on host DNA repair machinery, which is generally inefficient. Here, we describe a Cas-Transposon (CasTn) system for genomic insertions that uses a transposase fused to a catalytically-dead dCas9 nuclease to mediate programmable, site-specific transposition. CasTn combines the power of the Himar1 transposase, which inserts multi-kb DNA transposons into TA dinucleotides by a cut-and-paste mechanism, and the targeting capability of Cas9, which uses guide-RNAs to bind to specific DNA sequences. Using in vitro assays, we demonstrated that Himar-dCas9 proteins increased the frequency of transposon insertions at a single targeted TA dinucleotide by >300-fold compared to an untargeted transposase, and that site-specific transposition is dependent on target choice while robust to log-fold variations in protein and DNA concentrations. We then showed that Himar-dCas9 mediates site-specific transposition into a target plasmid in E. coli. This work provides CasTn as a new method for host-independent, programmable, targeted DNA insertions to expand the genomic engineering toolbox.

66: Engineering Cell Sensing and Responses Using a GPCR-Coupled CRISPR-Cas System
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Posted to bioRxiv 20 Jun 2017

Engineering Cell Sensing and Responses Using a GPCR-Coupled CRISPR-Cas System
1,801 downloads synthetic biology

P. C. Dave P. Dingal, Nathan H. Kipniss, Louai Labanieh, Yuchen Gao, Lei S. Qi

G-protein coupled receptors (GPCRs) are the largest and most diverse group of membrane receptors in eukaryotes, and detects a wide array of physiological cues in the human body. We describe a new molecular device that couples CRISPR-Cas9 programmed genome regulation to natural and synthetic extracellular signals via GPCRs. The design of our synthetic device, named CRISPR ChaCha, displays superior performance over an architecture proposed by the previously reported Tango system. Using a parsimonious mathematical model and gene-reporter assays, we find that CRISPR ChaCha can recruit and activate multiple Cas9 molecules for each GPCR molecule. We also characterize key molecular features that modulate CRISPR ChaCha performance. We adopt the design to diverse GPCRs that sense synthetic and natural ligands including chemokines, mitogens, and fatty acids, and observe efficient conversion of signals to customizable genetic programs in mammalian cells, including regulation of endogenous genes. The new class of CRISPR-coupled GPCRs provides a robust and efficient platform for engineering cells with novel behaviors in response to the diverse GPCR ligand repertoire.

67: UDSMProt: Universal Deep Sequence Models for Protein Classification
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Posted to bioRxiv 17 Jul 2019

UDSMProt: Universal Deep Sequence Models for Protein Classification
1,745 downloads synthetic biology

Nils Strodthoff, Patrick Wagner, Markus Wenzel, Wojciech Samek

Motivation Inferring the properties of a protein from its amino acid sequence is one of the key problems in bioinformatics. Most state-of-the-art approaches for protein classification tasks are tailored to single classification tasks and rely on handcrafted features such as position-specific-scoring matrices from expensive database searches. We argue that this level of performance can be reached or even be surpassed by learning a task-agnostic representation once, using self-supervised language modeling, and transferring it to specific tasks by a simple finetuning step. Results We put forward a universal deep sequence model that is pretrained on unlabeled protein sequences from Swiss-Prot and finetuned on protein classification tasks. We apply it to three prototypical tasks, namely enzyme class prediction, gene ontology prediction and remote homology and fold detection. The proposed method performs on par with state-of-the-art algorithms that were tailored to these specific tasks or, for two out of three tasks, even outperforms them. These results stress the possibility of inferring protein properties from the sequence alone and, on more general grounds, the prospects of modern natural language processing methods in omics. Availability Source code is available under <https://github.com/nstrodt/UDSMProt>. Contact firstname.lastname{at}hhi.fraunhofer.de

68: Deconstructing cell-free extract preparation for in vitro activation of transcriptional genetic circuitry
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Posted to bioRxiv 08 Sep 2018

Deconstructing cell-free extract preparation for in vitro activation of transcriptional genetic circuitry
1,729 downloads synthetic biology

Adam D. Silverman, Nancy Kelley-Loughnane, Julius B. Lucks, Michael C. Jewett

Recent advances in cell-free gene expression (CFE) systems have enabled their use for a host of synthetic biology applications, particularly for rapid prototyping of genetic circuits designed as biosensors. Despite the proliferation of cell-free protein synthesis platforms, the large number of currently existing protocols for making CFE extracts muddles the collective understanding of how the method by which an extract is prepared affects its functionality. Specifically, a key goal toward developing cell-free biosensors based on native genetic regulators is activating the transcriptional machinery present in bacterial extracts for protein synthesis. However, protein yields from genes transcribed in vitro by the native Escherichia coli RNA polymerase are quite low in conventional crude extracts originally optimized for expression by the bacteriophage transcriptional machinery. Here, we show that cell-free expression of genes under bacterial σ70 promoters is constrained by the rate of transcription in crude extracts and that processing the extract with a ribosomal run-off reaction and subsequent dialysis can alleviate this constraint. Surprisingly, these processing steps only enhance protein synthesis in genes under native regulation, indicating that the translation rate is unaffected. We further investigate the role of other common process variants on extract performance and demonstrate that bacterial transcription is inhibited by including glucose in the growth culture, but is unaffected by flash-freezing the cell pellet prior to lysis. Our final streamlined protocol for preparing extract by sonication generates extract that facilitates expression from a diverse set of sensing modalities including protein and RNA regulators. We anticipate that this work will clarify the methodology for generating CFE extracts that are active for biosensing and will encourage the further proliferation of cell-free gene expression technology for new applications.

69: Communication and quorum sensing in non-living mimics of eukaryotic cells
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Posted to bioRxiv 20 Jun 2018

Communication and quorum sensing in non-living mimics of eukaryotic cells
1,728 downloads synthetic biology

Henrike Niederholtmeyer, Cynthia Chaggan, Neal K Devaraj

Cells in tissues or biofilms communicate with one another through chemical and mechanical signals to coordinate collective behaviors. Non-living cell mimics provide simplified models of natural systems, however, it has remained challenging to implement communication capabilities comparable to living cells. Here we present a porous artificial cell-mimic containing a nucleus-like DNA-hydrogel compartment that is able to express and display proteins, and communicate with neighboring cell-mimics through diffusive protein signals. We show that communication between cell-mimics allowed distribution of tasks, quorum sensing, and cellular differentiation according to local environment. Cell-mimics could be manufactured in large quantities, easily stored, chemically modified, and spatially organized into diffusively connected tissue-like arrangements, offering a means for studying communication in large ensembles of artificial cells.

70: Computational redesign of a PETase for plastic biodegradation by the GRAPE strategy
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Posted to bioRxiv 30 Sep 2019

Computational redesign of a PETase for plastic biodegradation by the GRAPE strategy
1,724 downloads synthetic biology

Yinglu Cui, Yanchun Chen, Xinyue Liu, Saijun Dong, Yu’e Tian, Yuxin Qiao, Ruchira Mitra, Jing Han, Chunli Li, Xu Han, Weidong Liu, Quan Chen, Wenbin Du, Shuangyan Tang, Hua Xiang, Haiyan Liu, Bian Wu

The excessive use of plastics has been accompanied by severe ecologically damaging effects. The recent discovery of a PETase from Ideonella sakaiensis that decomposes poly(ethylene terephthalate) (PET) under mild conditions provides an attractive avenue for the biodegradation of plastics. However, the inherent instability of the enzyme limits its practical utilization. Here, we devised a novel computational strategy (greedy accumulated strategy for protein engineering, GRAPE). A systematic clustering analysis combined with greedy accumulation of beneficial mutations in a computationally derived library enabled the design of a variant, DuraPETase, which exhibits an apparent melting temperature that is drastically elevated by 31 °C and strikingly enhanced degradation performance toward semicrystalline PET films (23%) at mild temperatures (over two orders of magnitude improvement). The mechanism underlying the robust promotion of enzyme performance has been demonstrated via a crystal structure and molecular dynamics simulations. This work shows the capabilities of computational enzyme design to circumvent antagonistic epistatic effects and provides a valuable tool for further understanding and advancing polyester hydrolysis in the natural environment.

71: Measuring glycolytic flux in single yeast cells with an orthogonal synthetic biosensor
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Posted to bioRxiv 25 Jun 2019

Measuring glycolytic flux in single yeast cells with an orthogonal synthetic biosensor
1,723 downloads synthetic biology

Francisca Monteiro, Georg Hubmann, Justin Norder, Johan Hekelaar, Joana Saldida, Athanasios Litsios, Hein J Wijma, Alexander Schmidt, Matthias Heinemann

Metabolic heterogeneity between individual cells of a population harbors offers significant challenges for fundamental and applied research. Identifying metabolic heterogeneity and investigating its emergence requires tools to zoom into metabolism of individual cells. While methods exist to measure metabolite levels in single cells, we lack capability to measure metabolic flux, i.e. the ultimate functional output of metabolic activity, on the single-cell level. Here, combining promoter engineering, computational protein design, biochemical methods, proteomics and metabolomics, we developed a biosensor to measure glycolytic flux in single yeast cells, by drawing on the robust cell-intrinsic correlation between glycolytic flux and levels of fructose-1,6-bisphosphate (FBP), and by transplanting the B. subtilis FBP-binding transcription factor CggR into yeast. As proof of principle, using fluorescence microscopy, we applied the sensor to identify metabolic subpopulations in yeast cultures. We anticipate that our biosensor will become a valuable tool to identify and study metabolic heterogeneity in cell populations.

72: Engineering Phage Host-Range and Suppressing Bacterial Resistance Through Phage Tail Fiber Mutagenesis
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Posted to bioRxiv 11 Jul 2019

Engineering Phage Host-Range and Suppressing Bacterial Resistance Through Phage Tail Fiber Mutagenesis
1,710 downloads synthetic biology

Kevin Yehl, Sébastien Lemire, Andrew C Yang, Hiroki Ando, Mark Mimee, Marcelo Der Torossian Torres, Cesar de la Fuente-Nunez, Timothy K. Lu

The rapid emergence of antibiotic-resistant infections is prompting increased interest in phage-based antimicrobials. However, acquisition of resistance by bacteria is a major issue in the successful development of phage therapies. Through natural evolution and structural modeling, we identified host-range determining regions (HRDR) in the T3 phage tail fiber protein and developed a high-throughput strategy to genetically engineer these regions through site-directed mutagenesis. Inspired by antibody specificity engineering, this approach generates deep functional diversity (>107 different members), while minimizing disruptions to the overall protein structure, resulting in synthetic ′phagebodies′. We showed that mutating HRDRs yields phagebodies with altered host-ranges. Select phagebodies enable long-term suppression of bacterial growth by preventing the appearance of resistance in vitro and are functional in vivo using a mouse skin infection model. We anticipate this approach may facilitate the creation of next-generation antimicrobials that slow resistance development and could be extended to other viral scaffolds for a broad range of applications.

73: High-Throughput Characterization of Protein-Protein Interactions by Reprogramming Yeast Mating
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Posted to bioRxiv 29 Mar 2017

High-Throughput Characterization of Protein-Protein Interactions by Reprogramming Yeast Mating
1,686 downloads synthetic biology

David Younger, Stephanie Berger, David Baker, Eric Klavins

High-throughput methods for screening protein-protein interactions enable the rapid characterization of engineered binding proteins and interaction networks. While existing approaches are powerful, none allow quantitative library-on-library characterization of protein interactions in a modifiable extracellular environment. Here, we show that sexual agglutination of S. cerevisiae can be reprogrammed to link interaction strength with mating efficiency using synthetic agglutination (SynAg). Validation of SynAg with 89 previously characterized interactions shows a log-linear relationship between mating efficiency and protein binding strength for interactions with Kd's ranging from below 500 pM to above 300 uM. Using induced chromosomal translocation to pair barcodes representing binding proteins, thousands of distinct interactions can be screened in a single pot. We demonstrate the ability to characterize protein interaction networks in a modifiable environment by introducing a soluble peptide that selectively disrupts a subset of interactions in a representative network by up to 800-fold. SynAg enables the high-throughput, quantitative characterization of protein-protein interaction networks in a fully-defined extracellular environment at a library-on-library scale.

74: Recording the age of RNA with deamination
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Posted to bioRxiv 10 Feb 2020

Recording the age of RNA with deamination
1,671 downloads synthetic biology

Samuel G. Rodriques, Linlin M Chen, Sophia Liu, Ellen D. Zhong, Joseph R Scherrer, Edward S. Boyden, Fei Chen

Transcriptional programs implemented by cells often consist of complex temporal features, but current approaches to single-cell RNA sequencing only provide limited information about the dynamics of gene expression. Here, we present RNA timestamps, a method for inferring the age of individual RNAs in a sequencing-based readout by leveraging RNA editing. Timestamped RNAs include a RNA reporter motif that accumulates A to I edits over time, allowing the age of the RNA to be inferred with hour-scale accuracy. By combining observations of multiple timestamped RNAs driven by the same promoter, we are able to infer when in the past the promoter was active. We demonstrate that the system can infer the presence and timing of multiple past transcriptional events, with no prior knowledge. Finally, we apply this method to cluster single cells according to the times at which a particular transcriptional program was activated. RNA timestamps thus suggest a new approach for incorporating temporal information into RNA sequencing workflows.

75: Synthesis and patterning of tunable multiscale materials with engineered cells
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Posted to bioRxiv 14 Feb 2014

Synthesis and patterning of tunable multiscale materials with engineered cells
1,648 downloads synthetic biology

Allen Y Chen, Urartu O.S. Seker, Michelle Y Lu, Robert J Citorik, Timothy Lu

A major challenge in materials science is to create self-assembling, functional, and environmentally responsive materials which can be patterned across multiple length scales. Natural biological systems, such as biofilms, shells, and skeletal tissues, implement dynamic regulatory programs to assemble complex multiscale materials comprised of living and non-living components. Such systems can provide inspiration for the design of heterogeneous functional systems which integrate biotic and abiotic materials via hierarchical self-assembly. Here, we present a synthetic-biology platform for synthesizing and patterning self-assembled functional amyloid materials across multiple length scales with bacterial biofilms. We engineered Escherichia coli curli amyloid production under the tight control of synthetic regulatory circuits and interfaced amyloids with inorganic materials to create a biofilm-based electrical switch whose conductance can be selectively toggled by specific environmental signals. Furthermore, we externally tuned synthetic biofilms to build nanoscale amyloid biomaterials with different structure and composition through the controlled expression of their constituent subunits with artificial gene circuits. By using synthetic cell-cell communication, our engineered biofilms can also autonomously manufacture dynamic materials whose structure and composition change with time. In addition, we show that by combining subunit-level protein engineering, controlled genetic expression of self-assembling subunit proteins, and macroscale spatial gradients, synthetic biofilms can pattern protein biomaterials across multiple length scales. This work lays a foundation for synthesizing, patterning, and controlling composite materials with engineered biological systems. We envision that this approach can be expanded to other cellular and biomaterials contexts for the construction of self-organizing, environmentally responsive, and tunable multiscale composite materials with heterogeneous functionalities. Now published as: Nature Materials, doi:10.1038/nmat3912

76: Large-scale DNA-based phenotypic recording and deep learning enable highly accurate sequence-function mapping
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Posted to bioRxiv 24 Jan 2020

Large-scale DNA-based phenotypic recording and deep learning enable highly accurate sequence-function mapping
1,617 downloads synthetic biology

Simon Höllerer, Laetitia Papaxanthos, Anja Cathrin Gumpinger, Katrin Fischer, Christian Beisel, Karsten Borgwardt, Yaakov Benenson, Markus Jeschek

Predicting quantitative effects of gene regulatory elements (GREs) on gene expression is a longstanding challenge in biology. Machine learning models for gene expression prediction may be able to address this challenge, but they require experimental datasets that link large numbers of GREs to their quantitative effect. However, current methods to generate such datasets experimentally are either restricted to specific applications or limited by their technical complexity and error-proneness. Here we introduce DNA-based phenotypic recording as a widely applicable and practical approach to generate very large datasets linking GREs to quantitative functional readouts of high precision, temporal resolution, and dynamic range, solely relying on sequencing. This is enabled by a novel DNA architecture comprising a site-specific recombinase, a GRE that controls recombinase expression, and a DNA substrate modifiable by the recombinase. Both GRE sequence and substrate state can be determined in a single sequencing read, and the frequency of modified substrates amongst constructs harbouring the same GRE is a quantitative, internally normalized readout of this GRE's effect on recombinase expression. Using next-generation sequencing, the quantitative expression effect of extremely large GRE sets can be assessed in parallel. As a proof of principle, we apply this approach to record translation kinetics of more than 300,000 bacterial ribosome binding sites (RBSs), collecting over 2.7 million sequence-function pairs in a single experiment. Further, we generalize from these large-scale datasets by a novel deep learning approach that combines ensembling and uncertainty modelling to predict the function of untested RBSs with high accuracy, substantially outperforming state-of-the-art methods. The combination of DNA-based phenotypic recording and deep learning represents a major advance in our ability to predict quantitative function from genetic sequence.

77: Exploring protein orthogonality in immune space: a case study with AAV and Cas9 orthologs
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Posted to bioRxiv 10 Jan 2018

Exploring protein orthogonality in immune space: a case study with AAV and Cas9 orthologs
1,529 downloads synthetic biology

Ana M Moreno, Nathan Palmer, Fernando Alemán, Genghao Chen, Andrew Pla, Wei Leong Chew, Mansun Law, Prashant Mali

A major hurdle in protein-based therapeutics is the interaction with the adaptive immune system, which can lead to neutralization by circulating antibodies and clearance of treated cells by cytotoxic T-lymphocytes. One method of circumventing these issues is to use human or humanized proteins which avoid the immune response by self-recognition. However, this approach limits potential protein therapeutics to those of human origin, excluding many exciting effectors and delivery vehicles such as CRISPR-Cas9 and adeno-associated viruses (AAVs). To address this issue, we propose here the sequential use of orthologous proteins whose function is constrained by natural selection, but whose structure is subject to diversification by genetic drift. This would, in principle, allow for repeated treatments by immune orthogonal orthologs without reduced efficacy due to lack of immune cross-reactivity among the proteins. To explore and validate this concept we chose 91 Type II CRISPR-Cas9 orthologs and 167 AAV capsid protein orthologs, and developed a pipeline to compare total sequence similarity as well as predicted binding to class I and class II Major Histocompatibility Complex (MHC) proteins. Interestingly, MHC binding predictions revealed wide diversity among the set of Cas9 orthologs, with 83% of pairs predicted to have non cross-reacting immune responses, while no global immune orthogonality among AAV serotypes was observed. To confirm these findings we selected two Cas9 orthologs, from S. pyogenes and S. aureus, predicted to be orthogonal in immune space, and delivered them into mice via multiple AAV serotypes. We observed cross-reacting antibodies against AAV but not Cas9 orthologs in sera from immunized mice, validating the computationally predicted immune orthogonality among these proteins. Moving forward, we anticipate this framework can be applied to prescribe sequential regimens of immune orthogonal protein therapeutics to circumvent pre-existing or induced immunity, and eventually, to rationally engineer immune orthogonality among protein orthologs.

78: A GenoChemetic strategy for derivatization of the violacein natural product scaffold
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Posted to bioRxiv 15 Nov 2017

A GenoChemetic strategy for derivatization of the violacein natural product scaffold
1,525 downloads synthetic biology

Hung-En Lai, Alan M. C. Obled, Soo Mei Chee, Rhodri M Morgan, Sunil V. Sharma, Simon J Moore, Karen M Polizzi, Rebecca J. M. Goss, Paul S Freemont

Integrating synthetic chemistry with synthetic biology allows rapid access to xenobiotic compounds which may provide improved therapeutic activity. By supplementing an Escherichia coli strain expressing the violacein biosynthesis pathway with eight tryptophan substrate analogues or tryptophan halogenase RebH in vivo, 68 new-to-nature analogues of violacein were generated. Furthermore, 20 new derivatives were generated from brominated analogues via Suzuki-Miyaura cross-coupling reaction directly using the crude extract without prior purification. Herein, we demonstrate a flexible and rapid approach to access diverse chemical space that can be applied to a wide range of natural product scaffolds.

79: Validating genome-wide CRISPR-Cas9 function in the non-conventional yeast Yarrowia lipolytica
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Posted to bioRxiv 29 Jun 2018

Validating genome-wide CRISPR-Cas9 function in the non-conventional yeast Yarrowia lipolytica
1,519 downloads synthetic biology

Cory Schwartz, Jan-Fang Cheng, Robert Evans, Christopher A Schwartz, James M Wagner, Scott Anglin, Adam Beitz, Weihua Pan, Stefano Lonardi, Mark Blenner, Hal S Alper, Yasuo Yoshikuni, Ian Wheeldon

Genome-wide mutational screens are central to understanding the genetic underpinnings of evolved and engineered phenotypes. The widespread adoption of CRISPR-Cas9 genome editing has enabled such screens in many organisms, but identifying functional sgRNAs still remains a challenge. To address this limitation, we developed a methodology to quantify the cutting efficiency of each sgRNA in a genome-scale library in the biotechnologically important yeast Yarrowia lipolytica. Screening in the presence and absence of native DNA repair enabled high-throughput quantification of sgRNA function leading to the identification of high efficiency sgRNAs that cover 94% of genes. Library validation enhanced the classification of essential genes by identifying inactive guides that create false negatives and mask the effects of successful disruptions. Quantification of guide effectiveness also creates a dataset from which functional determinants of CRISPR-Cas9 can be identified. Finally, application of the library identified mutations that led to high lipid accumulation and eliminated pseudohyphal morphology.

80: Cell-free gene regulatory network engineering with synthetic transcription factors
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Posted to bioRxiv 04 Sep 2018

Cell-free gene regulatory network engineering with synthetic transcription factors
1,512 downloads synthetic biology

Zoe Swank, Nadanai Laohakunakorn, Sebastian J. Maerkl

Gene regulatory networks are ubiquitous in nature and critical for bottom-up engineering of synthetic networks. Transcriptional repression is a fundamental function in gene regulatory networks and can be tuned at the level of DNA, protein, and cooperative protein - protein interactions, necessitating high-throughput experimental approaches for in-depth characterization. Here we used a cell-free system in combination with a high-throughput microfluidic device to comprehensively study the different tuning mechanisms of a synthetic zinc-finger repressor library, whose affinity, specificity, and cooperativity can be rationally engineered. The device is integrated into a comprehensive workflow that includes determination of transcription factor binding energy landscapes and mechanistic modeling. By integrating these methods we generated a library of well-characterized synthetic transcription factors and corresponding promoters, and used these standardized parts to build gene regulatory networks de novo in a cell-free environment. The well-characterized synthetic parts and insights gained should be useful for rationally engineering gene regulatory networks and for studying the biophysics of transcriptional regulation.

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