Ten simple rules for managing laboratory information.

Information is the cornerstone of research, from experimental (meta)data and computational processes to complex inventories of reagents and equipment. These 10 simple rules discuss best practices for leveraging laboratory information management systems to transform this large information load into useful scientific findings.

Machine learning for metabolic engineering: A review.

Machine learning provides researchers a unique opportunity to make metabolic engineering more predictable. In this review, we offer an introduction to this discipline in terms that are relatable to metabolic engineers, as well as providing in-depth illustrative examples leveraging omics data and improving production. We also include practical advice for the practitioner in terms of data management, algorithm libraries, computational resources, and important non-technical issues. A variety of applications ranging from pathway construction and optimization, to genetic editing optimization, cell factory testing, and production scale-up are discussed. Moreover, the promising relationship between machine learning and mechanistic models is thoroughly reviewed. Finally, the future perspectives and most promising directions for this combination of disciplines are examined.

Fluorescent amplification for next generation sequencing (FA-NGS) library preparation.

BACKGROUND: Next generation sequencing (NGS) has become a universal practice in modern molecular biology. As the throughput of sequencing experiments increases, the preparation of conventional multiplexed libraries becomes more labor intensive. Conventional library preparation typically requires quality control (QC) testing for individual libraries such as amplification success evaluation and quantification, none of which occur until the end of the library preparation process. RESULTS: In this study, we address the need for a more streamlined high-throughput NGS workflow by tethering real-time quantitative PCR (qPCR) to conventional workflows to save time and implement single tube and single reagent QC. We modified two distinct library preparation workflows by replacing PCR and quantification with qPCR using SYBR Green I. qPCR enabled individual library quantification for pooling in a single tube without the need for additional reagents. Additionally, a melting curve analysis was implemented as an intermediate QC test to confirm successful amplification. Sequencing analysis showed comparable percent reads for each indexed library, demonstrating that pooling calculations based on qPCR allow for an even representation of sequencing reads. To aid the modified workflow, a software toolkit was developed and used to generate pooling instructions and analyze qPCR and melting curve data. CONCLUSIONS: We successfully applied fluorescent amplification for next generation sequencing (FA-NGS) library preparation to both plasmids and bacterial genomes. As a result of using qPCR for quantification and proceeding directly to library pooling, the modified library preparation workflow has fewer overall steps. Therefore, we speculate that the FA-NGS workflow has less risk of user error. The melting curve analysis provides the necessary QC test to identify and troubleshoot library failures prior to sequencing. While this study demonstrates the value of FA-NGS for plasmid or gDNA libraries, we speculate that its versatility could lead to successful application across other library types.

Automated "Cells-To-Peptides" Sample Preparation Workflow for High-Throughput, Quantitative Proteomic Assays of Microbes.

Mass spectrometry-based quantitative proteomic analysis has proven valuable for clinical and biotechnology-related research and development. Improvements in sensitivity, resolution, and robustness of mass analyzers have also added value. However, manual sample preparation protocols are often a bottleneck for sample throughput and can lead to poor reproducibility, especially for applications where thousands of samples per month must be analyzed. To alleviate these issues, we developed a "cells-to-peptides" automated workflow for Gram-negative bacteria and fungi that includes cell lysis, protein precipitation, resuspension, quantification, normalization, and tryptic digestion. The workflow takes 2 h to process 96 samples from cell pellets to the initiation of the tryptic digestion step and can process 384 samples in parallel. We measured the efficiency of protein extraction from various amounts of cell biomass and optimized the process for standard liquid chromatography-mass spectrometry systems. The automated workflow was tested by preparing 96 Escherichia coli samples and quantifying over 600 peptides that resulted in a median coefficient of variation of 15.8%. Similar technical variance was observed for three other organisms as measured by highly multiplexed LC-MRM-MS acquisition methods. These results show that this automated sample preparation workflow provides robust, reproducible proteomic samples for high-throughput applications.

Oxidative cyclization of prodigiosin by an alkylglycerol monooxygenase-like enzyme.

Prodiginines, which are tripyrrole alkaloids displaying a wide array of bioactivities, occur as linear and cyclic congeners. Identification of an unclustered biosynthetic gene led to the discovery of the enzyme responsible for catalyzing the regiospecific C-H activation and cyclization of prodigiosin to cycloprodigiosin in Pseudoalteromonas rubra. This enzyme is related to alkylglycerol monooxygenase and unrelated to RedG, the Rieske oxygenase that produces cyclized prodiginines in Streptomyces, implying convergent evolution.

A Cas9-based toolkit to program gene expression in Saccharomyces cerevisiae.

Despite the extensive use of Saccharomyces cerevisiae as a platform for synthetic biology, strain engineering remains slow and laborious. Here, we employ CRISPR/Cas9 technology to build a cloning-free toolkit that addresses commonly encountered obstacles in metabolic engineering, including chromosomal integration locus and promoter selection, as well as protein localization and solubility. The toolkit includes 23 Cas9-sgRNA plasmids, 37 promoters of various strengths and temporal expression profiles, and 10 protein-localization, degradation and solubility tags. We facilitated the use of these parts via a web-based tool, that automates the generation of DNA fragments for integration. Our system builds upon existing gene editing methods in the thoroughness with which the parts are standardized and characterized, the types and number of parts available and the ease with which our methodology can be used to perform genetic edits in yeast. We demonstrated the applicability of this toolkit by optimizing the expression of a challenging but industrially important enzyme, taxadiene synthase (TXS). This approach enabled us to diagnose an issue with TXS solubility, the resolution of which yielded a 25-fold improvement in taxadiene production.

Structural insights into dehydratase substrate selection for the borrelidin and fluvirucin polyketide synthases.

Engineered polyketide synthases (PKSs) are promising synthetic biology platforms for the production of chemicals with diverse applications. The dehydratase (DH) domain within modular type I PKSs generates an α,ß-unsaturated bond in nascent polyketide intermediates through a dehydration reaction. Several crystal structures of DH domains have been solved, providing important structural insights into substrate selection and dehydration. Here, we present two DH domain structures from two chemically diverse PKSs. The first DH domain, isolated from the third module in the borrelidin PKS, is specific towards a trans-cyclopentane-carboxylate-containing polyketide substrate. The second DH domain, isolated from the first module in the fluvirucin B1 PKS, accepts an amide-containing polyketide intermediate. Sequence-structure analysis of these domains, in addition to previously published DH structures, display many significant similarities and key differences pertaining to substrate selection. The two major differences between BorA DH M3, FluA DH M1 and other DH domains are found in regions of unmodeled residues or residues containing high B-factors. These two regions are located between α3-ß11 and ß7-α2. From the catalytic Asp located in α3 to a conserved Pro in ß11, the residues between them form part of the bottom of the substrate-binding cavity responsible for binding to acyl-ACP intermediates.

Biochemical Characterization of ß-Amino Acid Incorporation in Fluvirucin†B2 Biosynthesis.

Naturally occurring lactams, such as the polyketide-derived macrolactams, provide a diverse class of natural products that could enhance existing chemically produced lactams. Although ß-amino acid loading in the fluvirucin B2 polyketide pathway was proposed by a previously identified putative biosynthetic gene cluster, biochemical characterization of the complete loading enzymes has not been described. Here we elucidate the complete biosynthetic pathway of the ß-amino acid loading pathway in fluvirucin B2 biosynthesis. We demonstrate the promiscuity of the loading pathway to utilize a range of amino acids and further illustrate the ability to introduce non-native acyl transferases to selectively transfer ß-amino acids onto a polyketide synthase (PKS) loading platform. The results presented here provide a detailed biochemical description of ß-amino acid selection and will further aid in future efforts to develop engineered lactam-producing PKS platforms.

A combinatorial approach to synthetic transcription factor-promoter combinations for yeast strain engineering.

Despite the need for inducible promoters in strain development efforts, the majority of engineering in Saccharomyces cerevisiae continues to rely on a few constitutively active or inducible promoters. Building on advances that use the modular nature of both transcription factors and promoter regions, we have built a library of hybrid promoters that are regulated by a synthetic transcription factor. The hybrid promoters consist of native S. cerevisiae promoters, in which the operator regions have been replaced with sequences that are recognized by the bacterial LexA DNA binding protein. Correspondingly, the synthetic transcription factor (TF) consists of the DNA binding domain of the LexA protein, fused with the human estrogen binding domain and the viral activator domain, VP16. The resulting system with a bacterial DNA binding domain avoids the transcription of native S. cerevisiae genes, and the hybrid promoters can be induced using estradiol, a compound with no detectable impact on S. cerevisiae physiology. Using combinations of one, two or three operator sequence repeats and a set of native S. cerevisiae promoters, we obtained a series of hybrid promoters that can be induced to different levels, using the same synthetic TF and a given estradiol. This set of promoters, in combination with our synthetic TF, has the potential to regulate numerous genes or pathways simultaneously, to multiple desired levels, in a single strain.

SBOL Visual: A Graphical Language for Genetic Designs.

Synthetic Biology Open Language (SBOL) Visual is a graphical standard for genetic engineering. It consists of symbols representing DNA subsequences, including regulatory elements and DNA assembly features. These symbols can be used to draw illustrations for communication and instruction, and as image assets for computer-aided design. SBOL Visual is a community standard, freely available for personal, academic, and commercial use (Creative Commons CC0 license). We provide prototypical symbol images that have been used in scientific publications and software tools. We encourage users to use and modify them freely, and to join the SBOL Visual community: http://www.sbolstandard.org/visual.

The plant glycosyltransferase clone collection for functional genomics.

The glycosyltransferases (GTs) are an important and functionally diverse family of enzymes involved in glycan and glycoside biosynthesis. Plants have evolved large families of GTs which undertake the array of glycosylation reactions that occur during plant development and growth. Based on the Carbohydrate-Active enZymes (CAZy) database, the genome of the reference plant Arabidopsis thaliana codes for over 450 GTs, while the rice genome (Oryza sativa) contains over 600 members. Collectively, GTs from these reference plants can be classified into over 40 distinct GT families. Although these enzymes are involved in many important plant specific processes such as cell-wall and secondary metabolite biosynthesis, few have been functionally characterized. We have sought to develop a plant GTs clone resource that will enable functional genomic approaches to be undertaken by the plant research community. In total, 403 (88%) of CAZy defined Arabidopsis GTs have been cloned, while 96 (15%) of the GTs coded by rice have been cloned. The collection resulted in the update of a number of Arabidopsis GT gene models. The clones represent full-length coding sequences without termination codons and are Gateway® compatible. To demonstrate the utility of this JBEI GT Collection, a set of efficient particle bombardment plasmids (pBullet) was also constructed with markers for the endomembrane. The utility of the pBullet collection was demonstrated by localizing all members of the Arabidopsis GT14 family to the Golgi apparatus or the endoplasmic reticulum (ER). Updates to these resources are available at the JBEI GT Collection website http://www.addgene.org/.

Principal component analysis of proteomics (PCAP) as a tool to direct metabolic engineering.

Targeted proteomics is a convenient method determining enzyme expression levels, but a quantitative analysis of these proteomic data has not been fully explored yet. Here, we present and demonstrate a computational tool (principal component analysis of proteomics, PCAP) that uses quantitative targeted proteomics data to guide metabolic engineering and achieve higher production of target molecules from heterologous pathways. The method is based on the application of principal component analysis to a collection of proteomics and target molecule production data to pinpoint specific enzymes that need to have their expression level adjusted to maximize production. We illustrated the method on the heterologous mevalonate pathway in Escherichia coli that produces a wide range of isoprenoids and requires balanced pathway gene expression for high yields and titers. PCAP-guided engineering resulted in over a 40% improvement in the production of two valuable terpenes. PCAP could potentially be productively applied to other heterologous pathways as well.

Design, implementation and practice of JBEI-ICE: an open source biological part registry platform and tools.

The Joint BioEnergy Institute Inventory of Composable Elements (JBEI-ICEs) is an open source registry platform for managing information about biological parts. It is capable of recording information about 'legacy' parts, such as plasmids, microbial host strains and Arabidopsis seeds, as well as DNA parts in various assembly standards. ICE is built on the idea of a web of registries and thus provides strong support for distributed interconnected use. The information deposited in an ICE installation instance is accessible both via a web browser and through the web application programming interfaces, which allows automated access to parts via third-party programs. JBEI-ICE includes several useful web browser-based graphical applications for sequence annotation, manipulation and analysis that are also open source. As with open source software, users are encouraged to install, use and customize JBEI-ICE and its components for their particular purposes. As a web application programming interface, ICE provides well-developed parts storage functionality for other synthetic biology software projects. A public instance is available at public-registry.jbei.org, where users can try out features, upload parts or simply use it for their projects. The ICE software suite is available via Google Code, a hosting site for community-driven open source projects.

Engineering of Ralstonia eutropha H16 for autotrophic and heterotrophic production of methyl ketones.

Ralstonia eutropha is a facultatively chemolithoautotrophic bacterium able to grow with organic substrates or H2 and CO2 under aerobic conditions. Under conditions of nutrient imbalance, R. eutropha produces copious amounts of poly[(R)-3-hydroxybutyrate] (PHB). Its ability to utilize CO2 as a sole carbon source renders it an interesting new candidate host for the production of renewable liquid transportation fuels. We engineered R. eutropha for the production of fatty acid-derived, diesel-range methyl ketones. Modifications engineered in R. eutropha included overexpression of a cytoplasmic version of the TesA thioesterase, which led to a substantial (>150-fold) increase in fatty acid titer under certain conditions. In addition, deletion of two putative ß-oxidation operons and heterologous expression of three genes (the acyl coenzyme A oxidase gene from Micrococcus luteus and fadB and fadM from Escherichia coli) led to the production of 50 to 65 mg/liter of diesel-range methyl ketones under heterotrophic growth conditions and 50 to 180 mg/liter under chemolithoautotrophic growth conditions (with CO2 and H2 as the sole carbon source and electron donor, respectively). Induction of the methyl ketone pathway diverted substantial carbon flux away from PHB biosynthesis and appeared to enhance carbon flux through the pathway for biosynthesis of fatty acids, which are the precursors of methyl ketones.

Development of a broad-host synthetic biology toolbox for Ralstonia eutropha and its application to engineering hydrocarbon biofuel production.

BACKGROUND: The chemoautotrophic bacterium Ralstonia eutropha can utilize H2/CO2 for growth under aerobic conditions. While this microbial host has great potential to be engineered to produce desired compounds (beyond polyhydroxybutyrate) directly from CO2, little work has been done to develop genetic part libraries to enable such endeavors. RESULTS: We report the development of a toolbox for the metabolic engineering of Ralstonia eutropha H16. We have constructed a set of broad-host-range plasmids bearing a variety of origins of replication, promoters, 5' mRNA stem-loop structures, and ribosomal binding sites. Specifically, we analyzed the origins of replication pCM62 (IncP), pBBR1, pKT (IncQ), and their variants. We tested the promoters P(BAD), T7, P(xyls/PM), P(lacUV5), and variants thereof for inducible expression. We also evaluated a T7 mRNA stem-loop structure sequence and compared a set of ribosomal binding site (RBS) sequences derived from Escherichia coli, R. eutropha, and a computational RBS design tool. Finally, we employed the toolbox to optimize hydrocarbon production in R. eutropha and demonstrated a 6-fold titer improvement using the appropriate combination of parts. CONCLUSION: We constructed and evaluated a versatile synthetic biology toolbox for Ralstonia eutropha metabolic engineering that could apply to other microbial hosts as well.

Cell pole-specific activation of a critical bacterial cell cycle kinase.

Caulobacter crescentus integrates phospho-signaling pathways and transcription factor regulatory cascades to drive the cell cycle. Despite the essential role of the CckA histidine kinase in the control of cell cycle events, the factors that signal its activation at a specific time in the cell cycle have remained elusive. A conditional genetic screen for CckA mislocalization mutants, using automated fluorescence microscopy and an image processing platform, revealed that the essential DivL protein kinase promotes CckA localization, autophosphorylation, and activity at the new cell pole. The transient accumulation of DivL at the new cell pole, but not its kinase activity, is required for the localization and activation of CckA. Because DivL and CckA accumulate at the same cell pole after the initiation of DNA replication and were found to interact in vivo, we propose that DivL recruits CckA to the pole, thereby promoting its autophosphorylation and activity.

High-throughput identification of protein localization dependency networks.

Bacterial cells are highly organized with many protein complexes and DNA loci dynamically positioned to distinct subcellular sites over the course of a cell cycle. Such dynamic protein localization is essential for polar organelle development, establishment of asymmetry, and chromosome replication during the Caulobacter crescentus cell cycle. We used a fluorescence microscopy screen optimized for high-throughput to find strains with anomalous temporal or spatial protein localization patterns in transposon-generated mutant libraries. Automated image acquisition and analysis allowed us to identify genes that affect the localization of two polar cell cycle histidine kinases, PleC and DivJ, and the pole-specific pili protein CpaE, each tagged with a different fluorescent marker in a single strain. Four metrics characterizing the observed localization patterns of each of the three labeled proteins were extracted for hundreds of cell images from each of 854 mapped mutant strains. Using cluster analysis of the resulting set of 12-element vectors for each of these strains, we identified 52 strains with mutations that affected the localization pattern of the three tagged proteins. This information, combined with quantitative localization data from epitasis experiments, also identified all previously known proteins affecting such localization. These studies provide insights into factors affecting the PleC/DivJ localization network and into regulatory links between the localization of the pili assembly protein CpaE and the kinase localization pathway. Our high-throughput screening methodology can be adapted readily to any sequenced bacterial species, opening the potential for databases of localization regulatory networks across species, and investigation of localization network phylogenies.

A Procedural Framework for Benchmarking Biofoundry Capabilities.

Benchmarking compares the performance of a product or service with a competitor. In a biofoundry context, capability benchmarking enables more effective use of development resources and furthering business development efforts. Biofoundries considering benchmarking activities are immediately faced with many implementation questions and decisions. While differing circumstances between biofoundries may lead to different answers to those same questions, a common framework for the benchmarking process is desirable. Perhaps the framework described here, and developed for the United States Department of Energy Agile BioFoundry, will be useful to other biofoundries around the world.

Alkaline-SDS cell lysis of microbes with acetone protein precipitation for proteomic sample preparation in 96-well plate format.

Plate-based proteomic sample preparation offers a solution to the large sample throughput demands in the biotechnology field where hundreds or thousands of engineered microbes are constructed for testing is routine. Meanwhile, sample preparation methods that work efficiently on broader microbial groups are desirable for new applications of proteomics in other fields, such as microbial communities. Here, we detail a step-by-step protocol that consists of cell lysis in an alkaline chemical buffer (NaOH/SDS) followed by protein precipitation with high-ionic strength acetone in 96-well format. The protocol works for a broad range of microbes (e.g., Gram-negative bacteria, Gram-positive bacteria, non-filamentous fungi) and the resulting proteins are ready for tryptic digestion for bottom-up quantitative proteomic analysis without the need for desalting column cleanup. The yield of protein using this protocol increases linearly with respect to the amount of starting biomass from 0.5-2.0 OD*mL of cells. By using a bench-top automated liquid dispenser, a cost-effective and environmentally-friendly option to eliminating pipette tips and reducing reagent waste, the protocol takes approximately 30 minutes to extract protein from 96 samples. Tests on mock mixtures showed expected results that the biomass composition structure is in close agreement with the experimental design. Lastly, we applied the protocol for the composition analysis of a synthetic community of environmental isolates grown on two different media. This protocol has been developed to facilitate rapid, low-variance sample preparation of hundreds of samples and allow flexibility for future protocol development.

The fusion of biology, computer science, and engineering: towards efficient and successful synthetic biology.

Synthetic biology is a nascent field that emerged in earnest only around the turn of the millennium. It aims to engineer new biological systems and impart new biological functionality, often through genetic modifications. The design and construction of new biological systems is a complex, multistep process, requiring multidisciplinary collaborative efforts from "fusion" scientists who have formal training in computer science or engineering, as well as hands-on biological expertise. The public has high expectations for synthetic biology and eagerly anticipates the development of solutions to the major challenges facing humanity. This article discusses laboratory practices and the conduct of research in synthetic biology. It argues that the fusion science approach, which integrates biology with computer science and engineering best practices, including standardization, process optimization, computer-aided design and laboratory automation, miniaturization, and systematic management, will increase the predictability and reproducibility of experiments and lead to breakthroughs in the construction of new biological systems. The article also discusses several successful fusion projects, including the development of software tools for DNA construction design automation, recursive DNA construction, and the development of integrated microfluidics systems.