Introduction of customized inserts for streamlined assembly and optimization of BioBrick synthetic genetic circuits

Background  

BioBrick standard biological parts are designed to make biological systems easier to engineer (e.g. assemble, manipulate, and modify). There are over 5,000 parts available in the Registry of Standard Biological Parts that can be easily assembled into genetic circuits using a standard assembly technique. The standardization of the assembly technique has allowed for wide distribution to a large number of users -- the parts are reusable and interchangeable during the assembly process. The standard assembly process, however, has some limitations. In particular it does not allow for modification of already assembled biological circuits, addition of protein tags to pre-existing BioBrick parts, or addition of non-BioBrick parts to assemblies.     

Performance Comparison of Some Classes of Flexible Flow Shops and Job Shops

Flexible manufacturing systems (FMSs) for two-stage production may possess a variety of operating flexibilities in the form of tooling capabilities for the machines and alternative routings for each operation. In this paper, we compare the throughput performance of several flexible flow shop and job shop designs. We consider two-stage assembly flow shops with m parallel machines in stage 1 and a single assembly facility in stage 2. Every upstream operation can be processed by any one of the machines in stage 1 prior to the assembly stage. We also study a similar design where every stage 1 operation is processed by a predetermined machine. For both designs, we present heuristic algorithms with good worst-case error bounds and show that the average performance of these algorithms is near optimal. The algorithms presented are used to compare the performance of the two designs with each other and other related flexible flow shop designs. It is shown, both analytically and experimentally, that the mode of flexibility possessed by a design has implications on the throughput performance of the production system.     

Double drives and private alleles for localised population genetic control

Synthetic gene drive constructs could, in principle, provide the basis for highly efficient interventions to control disease vectors and other pest species. This efficiency derives in part from leveraging natural processes of dispersal and gene flow to spread the construct and its impacts from one population to another. However, sometimes (for example, with invasive species) only specific populations are in need of control, and impacts on non-target populations would be undesirable. Many gene drive designs use nucleases that recognise and cleave specific genomic sequences, and one way to restrict their spread would be to exploit sequence differences between target and non-target populations. In this paper we propose and model a series of low threshold double drive designs for population suppression, each consisting of two constructs, one imposing a reproductive load on the population and the other inserted into a differentiated locus and controlling the drive of the first. Simple deterministic, discrete-generation computer simulations are used to assess the alternative designs. We find that the simplest double drive designs are significantly more robust to pre-existing cleavage resistance at the differentiated locus than single drive designs, and that more complex designs incorporating sex ratio distortion can be more efficient still, even allowing for successful control when the differentiated locus is neutral and there is up to 50% pre-existing resistance in the target population. Similar designs can also be used for population replacement, with similar benefits. A population genomic analysis of CRISPR PAM sites in island and mainland populations of the malaria mosquito Anopheles gambiae indicates that the differentiation needed for our methods to work can exist in nature. Double drives should be considered when efficient but localised population genetic control is needed and there is some genetic differentiation between target and non-target populations.     

3-D printing provides a novel approach for standardization and reproducibility of freezing devices

Cryopreservation has become an important and accepted tool for long-term germplasm conservation of animals and plants. To protect genetic resources, repositories have been developed with national and international cooperation. For a repository to be effective, the genetic material submitted must be of good quality and comparable to other submissions. However, due to a variety of reasons, including constraints in knowledge and available resources, cryopreservation methods for aquatic species vary widely across user groups which reduces reproducibility and weakens quality control. Herein we describe a standardizable freezing device produced using 3-dimensional (3-D) printing and introduce the concept of network sharing to achieve aggregate high-throughput cryopreservation for aquatic species. The objectives were to: 1) adapt widely available polystyrene foam products that would be inexpensive, portable, and provide adequate work space; 2) develop a design suitable for 3-D printing that could provide multiple configurations, be inexpensive, and easy to use, and 3) evaluate various configurations to attain freezing rates suitable for various common cryopreservation containers. Through this approach, identical components can be accessed globally, and we demonstrated that 3-D printers can be used to fabricate parts for standardizable freezing devices yielding relevant and reproducible cooling rates across users. With standardized devices for freezing, methods and samples can harmonize into an aggregated high-throughput pathway not currently available for aquatic species repository development.     

An Unsupervised, Model-Free, Machine-Learning Combiner for Peptide Identifications from Tandem Mass Spectra

As the speed of mass spectrometers, sophistication of sample fractionation, and complexity of experimental designs increase, the volume of tandem mass spectra requiring reliable automated analysis continues to grow. Software tools that quickly, effectively, and robustly determine the peptide associated with each spectrum with high confidence are sorely needed. Currently available tools that postprocess the output of sequence-database search engines use three techniques to distinguish the correct peptide identifications from the incorrect: statistical significance re-estimation, supervised machine learning scoring and prediction, and combining or merging of search engine results. We present a unifying framework that encompasses each of these techniques in a single model-free machine-learning framework that can be trained in an unsupervised manner. The predictor is trained on the fly for each new set of search results without user intervention, making it robust for different instruments, search engines, and search engine parameters. We demonstrate the performance of the technique using mixtures of known proteins and by using shuffled databases to estimate false discovery rates, from data acquired on three different instruments with two different ionization technologies. We show that this approach outperforms machine-learning techniques applied to a single search engine’s output, and demonstrate that combining search engine results provides additional benefit. We show that the performance of the commercial Mascot tool can be bested by the machine-learning combination of two open-source tools X!Tandem and OMSSA, but that the use of all three search engines boosts performance further still. The Peptide identification Arbiter by Machine Learning (PepArML) unsupervised, model-free, combining framework can be easily extended to support an arbitrary number of additional searches, search engines, or specialized peptide–spectrum match metrics for each spectrum data set. PepArML is open-source and is available from . Electronic supplementary material The online version of this article (doi: ) contains supplementary material, which is available to authorized users.     

A standard vector for the chromosomal integration and characterization of BioBrick™ parts in <Emphasis Type="Italic">Escherichia coli</Emphasis>

Background

The chromosomal integration of biological parts in the host genome enables the engineering of plasmid-free stable strains with single-copy insertions of the desired gene networks. Although different integrative vectors were proposed, no standard pre-assembled genetic tool is available to carry out this task. Synthetic biology concepts can contribute to the development of standardized and user friendly solutions to easily produce engineered strains and to rapidly characterize the desired genetic parts in single-copy context.

Results

In this work we report the design of a novel integrative vector that allows the genomic integration of biological parts compatible with the RFC10, RFC23 and RFC12 BioBrick? standards in Escherichia coli. It can also be specialized by using BioBrick? parts to target the desired integration site in the host genome. The usefulness of this vector has been demonstrated by integrating a set of BioBrick? devices in two different loci of the E. coli chromosome and by characterizing their activity in single-copy. Construct stability has also been evaluated and compared with plasmid-borne solutions.

Conclusions

Physical modularity of biological parts has been successfully applied to construct a ready-to-engineer BioBrick? vector, suitable for a stable chromosomal insertion of standard parts via the desired recombination method, i.e. the bacteriophage integration mechanism or homologous recombination. In contrast with previously proposed solutions, it is a pre-assembled vector containing properly-placed restriction sites for the direct transfer of various formats of BioBrick? parts. This vector can facilitate the characterization of parts avoiding copy number artefacts and the construction of antibiotic resistance-free engineered microbes, suitable for industrial use.

     

Construction and Analysis of an Augmented Lattice Square Design

Augmented designs are useful for screening experiments involving large numbers of new and untried treatments. Since resolvable row‐column designs are useful for controlling extraneous variation, it is desirable to use such designs for the check or standard treatments to construct augmented lattice square experiment designs. A simple procedure is described for constructing such designs using c = 2k and c = 3k check treatments and n = rk(k ‐— 2) and n = rk(k — 3) new treatments, respectively, r being the number of complete blocks. A trend analysis for these designs, which allows for solutions of fixed effects, is presented. The random effects case is also discussed. A SAS computer code and the output from this code illustrated with a small numerical example are available from the author.     

SPARQL Assist language-neutral query composer

Background

More than one million terms from biomedical ontologies and controlled vocabularies are available through the Ontology Lookup Service (OLS). Although OLS provides ample possibility for querying and browsing terms, the visualization of parts of the ontology graphs is rather limited and inflexible.

Results

We created the OLSVis web application, a visualiser for browsing all ontologies available in the OLS database. OLSVis shows customisable subgraphs of the OLS ontologies. Subgraphs are animated via a real-time force-based layout algorithm which is fully interactive: each time the user makes a change, e.g. browsing to a new term, hiding, adding, or dragging terms, the algorithm performs smooth and only essential reorganisations of the graph. This assures an optimal viewing experience, because subsequent screen layouts are not grossly altered, and users can easily navigate through the graph. URL: http://ols.wordvis.com

Conclusions

The OLSVis web application provides a user-friendly tool to visualise ontologies from the OLS repository. It broadens the possibilities to investigate and select ontology subgraphs through a smooth visualisation method.     

The maize genetics and genomics database. The community resource for access to diverse maize data

The Maize Genetics and Genomics Database (MaizeGDB) serves the maize (Zea mays) research community by making a wealth of genetics and genomics data available through an intuitive Web-based interface. The goals of the MaizeGDB project are 3-fold: to provide a central repository for public maize information; to present the data through the MaizeGDB Web site in a way that recapitulates biological relationships; and to provide an array of computational tools that address biological questions in an easy-to-use manner at the site. In addition to these primary tasks, MaizeGDB team members also serve the community of maize geneticists by lending technical support for community activities, including the annual Maize Genetics Conference and various workshops, teaching researchers to use both the MaizeGDB Web site and Community Curation Tools, and engaging in collaboration with individual research groups to make their unique data types available through MaizeGDB.     

A Foundation for Reliable Spatial Proteomics Data Analysis

Quantitative mass-spectrometry-based spatial proteomics involves elaborate, expensive, and time-consuming experimental procedures, and considerable effort is invested in the generation of such data. Multiple research groups have described a variety of approaches for establishing high-quality proteome-wide datasets. However, data analysis is as critical as data production for reliable and insightful biological interpretation, and no consistent and robust solutions have been offered to the community so far. Here, we introduce the requirements for rigorous spatial proteomics data analysis, as well as the statistical machine learning methodologies needed to address them, including supervised and semi-supervised machine learning, clustering, and novelty detection. We present freely available software solutions that implement innovative state-of-the-art analysis pipelines and illustrate the use of these tools through several case studies involving multiple organisms, experimental designs, mass spectrometry platforms, and quantitation techniques. We also propose sound analysis strategies for identifying dynamic changes in subcellular localization by comparing and contrasting data describing different biological conditions. We conclude by discussing future needs and developments in spatial proteomics data analysis.     

Sharing Individual Participant Data from Clinical Trials: An Opinion Survey Regarding the Establishment of a Central Repository

Background

Calls have been made for increased access to individual participant data (IPD) from clinical trials, to ensure that complete evidence is available. However, despite the obvious benefits, progress towards this is frustratingly slow. In the meantime, many systematic reviews have already collected IPD from clinical trials. We propose that a central repository for these IPD should be established to ensure that these datasets are safeguarded and made available for use by others, building on the strengths and advantages of the collaborative groups that have been brought together in developing the datasets.

Objective

Evaluate the level of support, and identify major issues, for establishing a central repository of IPD.

Design

On-line survey with email reminders.

Participants

71 reviewers affiliated with the Cochrane Collaboration''s IPD Meta-analysis Methods Group were invited to participate.

Results

30 (42%) invitees responded: 28 (93%) had been involved in an IPD review and 24 (80%) had been involved in a randomised trial. 25 (83%) agreed that a central repository was a good idea and 25 (83%) agreed that they would provide their IPD for central storage. Several benefits of a central repository were noted: safeguarding and standardisation of data, increased efficiency of IPD meta-analyses, knowledge advancement, and facilitating future clinical, and methodological research. The main concerns were gaining permission from trial data owners, uncertainty about the purpose of the repository, potential resource implications, and increased workload for IPD reviewers. Restricted access requiring approval, data security, anonymisation of data, and oversight committees were highlighted as issues under governance of the repository.

Conclusion

There is support in this community of IPD reviewers, many of whom are also involved in clinical trials, for storing IPD in a central repository. Results from this survey are informing further work on developing a repository of IPD which is currently underway by our group.     

Generalized schemes for high-throughput manipulation of the Desulfovibrio vulgaris genome

The ability to conduct advanced functional genomic studies of the thousands of sequenced bacteria has been hampered by the lack of available tools for making high-throughput chromosomal manipulations in a systematic manner that can be applied across diverse species. In this work, we highlight the use of synthetic biological tools to assemble custom suicide vectors with reusable and interchangeable DNA "parts" to facilitate chromosomal modification at designated loci. These constructs enable an array of downstream applications, including gene replacement and the creation of gene fusions with affinity purification or localization tags. We employed this approach to engineer chromosomal modifications in a bacterium that has previously proven difficult to manipulate genetically, Desulfovibrio vulgaris Hildenborough, to generate a library of over 700 strains. Furthermore, we demonstrate how these modifications can be used for examining metabolic pathways, protein-protein interactions, and protein localization. The ubiquity of suicide constructs in gene replacement throughout biology suggests that this approach can be applied to engineer a broad range of species for a diverse array of systems biological applications and is amenable to high-throughput implementation.     

Open-Source 3D-Printable Optics Equipment

Just as the power of the open-source design paradigm has driven down the cost of software to the point that it is accessible to most people, the rise of open-source hardware is poised to drive down the cost of doing experimental science to expand access to everyone. To assist in this aim, this paper introduces a library of open-source 3-D-printable optics components. This library operates as a flexible, low-cost public-domain tool set for developing both research and teaching optics hardware. First, the use of parametric open-source designs using an open-source computer aided design package is described to customize the optics hardware for any application. Second, details are provided on the use of open-source 3-D printers (additive layer manufacturing) to fabricate the primary mechanical components, which are then combined to construct complex optics-related devices. Third, the use of the open-source electronics prototyping platform are illustrated as control for optical experimental apparatuses. This study demonstrates an open-source optical library, which significantly reduces the costs associated with much optical equipment, while also enabling relatively easily adapted customizable designs. The cost reductions in general are over 97%, with some components representing only 1% of the current commercial investment for optical products of similar function. The results of this study make its clear that this method of scientific hardware development enables a much broader audience to participate in optical experimentation both as research and teaching platforms than previous proprietary methods.     

The tip of the tail: molecular identification of seahorses for sale in apothecary shops and curio stores in California

Millions of seahorses a year are traded internationally, with many eventually sold at retail shops as curios, as aquarium pets, and especially for use in traditional medicine. The entire genus is now protected by CITES, but conservation measures have been limited in part by difficulties with species identification and incomplete understanding of trade patterns. In this study, we use molecular techniques to make species- and population-level identifications of 56 seahorses sampled from both traditional medicine and curio shops in San Francisco and central California. Seahorses from medicinal sources included unexpectedly large numbers of the eastern Pacific Hippocampus ingens, a species poorly protected by current CITES export recommendations. Curio shops were dominated by H. barbouri, a spiny species that has been reportedly confused in trading records as H. histrix. Specific populations of origin could be inferred for several species through comparison with publicly available phylogeographic data. Our results underscore the strengths and weaknesses of current recommended export regulations, and we suggest that molecular forensics can help in verifying trade documentation and developing more effective conservation measures.     

Coordinated induction of multi-gene pathways in Saccharomyces cerevisiae

Bacterial operons are nature’s tool for regulating and coordinating multi-gene expression in prokaryotes. They are also a gene architecture commonly used in the biosynthesis of many pharmaceutically important compounds and industrially useful chemicals. Despite being an important eukaryotic production host, Saccharomyces cerevisiae has never had such gene architecture. Here, we report the development of a system to assemble and regulate a multi-gene pathway in S. cerevisiae. Full pathways can be constructed using pre-made parts from a plasmid toolbox. Subsequently, through the use of a yeast strain containing a stably integrated gene switch, the assembled pathway can be regulated using a readily available and inexpensive compound—estradiol—with extremely high sensitivity (10 nM). To demonstrate the use of the system, we assembled the five-gene zeaxanthin biosynthetic pathway in a single step and showed the ligand-dependent coordinated expression of all five genes as well as the tightly regulated production of zeaxanthin. Compared with a previously reported constitutive zeaxanthin pathway, our inducible pathway was shown to have 50-fold higher production level.     

Phenotiki: an open software and hardware platform for affordable and easy image‐based phenotyping of rosette‐shaped plants

Phenotyping is important to understand plant biology, but current solutions are costly, not versatile or are difficult to deploy. To solve this problem, we present Phenotiki, an affordable system for plant phenotyping that, relying on off‐the‐shelf parts, provides an easy to install and maintain platform, offering an out‐of‐box experience for a well‐established phenotyping need: imaging rosette‐shaped plants. The accompanying software (with available source code) processes data originating from our device seamlessly and automatically. Our software relies on machine learning to devise robust algorithms, and includes an automated leaf count obtained from 2D images without the need of depth (3D). Our affordable device (~€200) can be deployed in growth chambers or greenhouse to acquire optical 2D images of approximately up to 60 adult Arabidopsis rosettes concurrently. Data from the device are processed remotely on a workstation or via a cloud application (based on CyVerse). In this paper, we present a proof‐of‐concept validation experiment on top‐view images of 24 Arabidopsis plants in a combination of genotypes that has not been compared previously. Phenotypic analysis with respect to morphology, growth, color and leaf count has not been performed comprehensively before now. We confirm the findings of others on some of the extracted traits, showing that we can phenotype at reduced cost. We also perform extensive validations with external measurements and with higher fidelity equipment, and find no loss in statistical accuracy when we use the affordable setting that we propose. Device set‐up instructions and analysis software are publicly available ( http://phenotiki.com ).     

Human umbilical cord tissue-derived mesenchymal stromal cells as adjuvant therapy for myocardial infarction: a review of current evidence focusing on pre-clinical large animal models and early human trials

Although biologically appealing, the concept of tissue regeneration underlying first- and second-generation cell therapies has failed to translate into consistent results in clinical trials. Several types of cells from different origins have been tested in pre-clinical models and in patients with acute myocardial infarction (AMI). Mesenchymal stromal cells (MSCs) have gained attention because of their potential for immune modulation and ability to promote endogenous tissue repair, mainly through their secretome. MSCs can be easily obtained from several human tissues, the umbilical cord being the most abundant source, and further expanded in culture, making them attractive as an allogeneic “of-the-shelf” cell product, suitable for the AMI setting. The available evidence concerning umbilical cord-derived MSCs in AMI is reviewed, focusing on large animal pre-clinical studies and early human trials. Molecular and cellular mechanisms as well as current limitations and possible translational solutions are also discussed.     

Amyloid-beta as a "difficult sequence" in solid phase peptide synthesis

The phenomenon of "difficult sequence" has long frustrated chemists in their efforts to assemble peptides that contain such sequences by solid phase synthesis methods. A variety of remedial measures are available to minimize or even abolish the negative impact of these sequences during synthesis. These include the use of elevated temperatures and stronger acylating reagents. Amyloid-beta, a fragment of the amyloid precursor protein, contains 40-43 residues and possesses a C-terminal sequence that is particularly resistant to ready solid phase synthesis making it a "difficult sequence" peptide. This review focuses on approaches to successfully assemble the peptide by both Boc- and Fmoc solid phase synthesis.