Publications by authors named "Jacob Beal"

Synthetic biology is an interdisciplinary field that brings together engineering and biology concepts alongside the arts and social sciences to develop solutions to pressing problems in our world. The education of students entering this field has relied on a diverse set of pedagogical methods to accomplish this goal. One non-profit group, iGEM-the International Genetically Engineered Machine competition, has been a driver of students' awareness of synthetic biology for the last 20 years giving many young researchers their first experience in the field of synthetic biology.

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Article Synopsis
  • - The study aims to improve the accuracy of screening DNA synthesis orders to identify potentially dangerous sequences by creating a prototype test dataset that sets a baseline for various screening methods.
  • - The methodology involved screening sequences from different groups of controlled organisms and analyzing discrepancies between various screening tools, showcasing challenges in defining risk and regulatory controls.
  • - The findings reveal the need for better collaboration between experts and regulators, suggesting a shift from species-specific to function-oriented regulatory practices, which could enhance safety and oversight in DNA synthesis.
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Flow cytometry is a powerful quantitative assay supporting high-throughput collection of single-cell data with a high dynamic range. For flow cytometry to yield reproducible data with a quantitative relationship to the underlying biology, however, requires that (1) appropriate process controls are collected along with experimental samples, (2) these process controls are used for unit calibration and quality control, and (3) data are analyzed using appropriate statistics. To this end, this chapter describes methods for quantitative flow cytometry through the addition of process controls and analyses, thereby enabling better development, modeling, and debugging of engineered biological organisms.

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There are several critical events that occur in the uterus during early pregnancy which are necessary for the establishment and maintenance of pregnancy. These events include blastocyst implantation, uterine decidualization, uterine neoangiogenesis, differentiation of trophoblast stem cells into different trophoblast cell lineages, and formation of a placenta. These processes involve several different cell types within the pregnant uterus.

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The design and construction of genetic systems, in silico, in vitro, or in vivo, often involve the handling of various pieces of DNA that exist in different forms across an assembly process: as a standalone "part" sequence, as an insert into a carrier vector, as a digested fragment, etc. Communication about these different forms of a part and their relationships is often confusing, however, because of a lack of standardized terms. Here, we present a systematic terminology and an associated set of practices for representing genetic parts at various stages of design, synthesis, and assembly.

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During early pregnancy in humans and rodents, uterine stromal cells undergo a remarkable differentiation to form the decidua, a transient maternal tissue that supports the growing fetus. It is important to understand the key decidual pathways that orchestrate the proper development of the placenta, a key structure at the maternal-fetal interface. We discovered that ablation of expression of the transcription factor Runx1 in decidual stromal cells in a conditional -null mouse model () causes fetal lethality during placentation.

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Synthetic biologists have made great progress over the past decade in developing methods for modular assembly of genetic sequences and in engineering biological systems with a wide variety of functions in various contexts and organisms. However, current paradigms in the field entangle sequence and functionality in a manner that makes abstraction difficult, reduces engineering flexibility and impairs predictability and design reuse. Functional Synthetic Biology aims to overcome these impediments by focusing the design of biological systems on function, rather than on sequence.

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Computational tools addressing various components of design-build-test-learn (DBTL) loops for the construction of synthetic genetic networks exist but do not generally cover the entire DBTL loop. This manuscript introduces an end-to-end sequence of tools that together form a DBTL loop called Design Assemble Round Trip (DART). DART provides rational selection and refinement of genetic parts to construct and test a circuit.

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As synthetic biology becomes increasingly capable and accessible, it is likewise increasingly critical to be able to make accurate biosecurity determinations regarding the pathogenicity or toxicity of particular nucleic acid or amino acid sequences. At present, this is typically done using the BLAST algorithm to determine the best match with sequences in the NCBI nucleic acid and protein databases. Neither BLAST nor any of the NCBI databases, however, are actually designed for biosafety determination.

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Unlabelled: During early pregnancy in humans and rodents, uterine stromal cells undergo a remarkable differentiation to form the decidua, a transient maternal tissue that supports the growing fetus. It is important to understand the key decidual pathways that orchestrate the proper development of the placenta, a key structure at the maternal-fetal interface. We discovered that ablation of expression of the transcription factor Runx1 in decidual stromal cells in a conditional -null mouse model ( ) causes fetal lethality during placentation.

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Standards support synthetic biology research by enabling the exchange of component information. However, using formal representations, such as the Synthetic Biology Open Language (SBOL), typically requires either a thorough understanding of these standards or a suite of tools developed in concurrence with the ontologies. Since these tools may be a barrier for use by many practitioners, the Excel-SBOL Converter was developed to facilitate the use of SBOL and integration into existing workflows.

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We describe an experimental campaign that replicated the performance assessment of logic gates engineered into cells of by Gander Our experimental campaign used a novel high-throughput experimentation framework developed under Defense Advanced Research Projects Agency's Synergistic Discovery and Design program: a remote robotic lab at Strateos executed a parameterized experimental protocol. Using this protocol and robotic execution, we generated two orders of magnitude more flow cytometry data than the original experiments. We discuss our results, which largely, but not completely, agree with the original report and make some remarks about lessons learned.

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The mouse decidua secretes many factors that act in a paracrine/autocrine manner to critically control uterine decidualization, neovascularization, and tissue remodeling that ensure proper establishment of pregnancy. The precise mechanisms that dictate intercellular communications among the uterine cells during early pregnancy remain unknown. We recently reported that conditional deletion of the gene encoding the hypoxia-inducible transcription factor 2 alpha (Hif2α) in mouse uterus led to infertility.

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In humans, the uterus undergoes a dramatic transformation to form an endometrial stroma-derived secretory tissue, termed decidua, during early pregnancy. The decidua secretes various factors that act in an autocrine/paracrine manner to promote stromal differentiation, facilitate maternal angiogenesis, and influence trophoblast differentiation and development, which are critical for the formation of a functional placenta. Here, we investigated the mechanisms by which decidual cells communicate with each other and with other cell types within the uterine milieu.

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Plate readers are commonly used to measure cell growth and fluorescence, yet the utility and reproducibility of plate reader data is limited by the fact that it is typically reported in arbitrary or relative units. We have previously established a robust serial dilution protocol for calibration of plate reader measurements of absorbance to estimated bacterial cell count and for green fluorescence from proteins expressed in bacterial cells to molecules of equivalent fluorescein. We now extend these protocols to calibration of red fluorescence to the sulforhodamine-101 fluorescent dye and blue fluorescence to Cascade Blue.

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While the installation of complex genetic circuits in microorganisms is relatively routine, the synthetic biology toolbox is severely limited in plants. Of particular concern is the absence of combinatorial analysis of regulatory elements, the long design-build-test cycles associated with transgenic plant analysis, and a lack of naming standardization for cloning parts. Here, we use previously described plant regulatory elements to design, build, and test 91 transgene cassettes for relative expression strength.

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The Synthetic Biology Open Language version 3 (SBOL3) provides a data model for representation of synthetic biology information across multiple scales and throughout the design-build-test-learn workflow. To support practical use of this data model, we have developed pySBOL3, a Python library that allows programmers to create and edit SBOL3 documents. Here we describe this library and key engineering decisions in its design.

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CRISPR-based gene editing is a powerful tool with great potential for applications in the treatment of many inherited and acquired diseases. The longer that CRISPR gene therapy is maintained within a patient, however, the higher the likelihood that it will result in problematic side effects such as off-target editing or immune response. One approach to mitigating these issues is to link the operation of the therapeutic system to a safety switch that autonomously disables its operation and removes the delivered therapeutics after some amount of time.

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Reliable, predictable engineering of cellular behavior is one of the key goals of synthetic biology. As the field matures, biological engineers will become increasingly reliant on computer models that allow for the rapid exploration of design space prior to the more costly construction and characterization of candidate designs. The efficacy of such models, however, depends on the accuracy of their predictions, the precision of the measurements used to parametrize the models, and the tolerance of biological devices for imperfections in modeling and measurement.

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Synthetic biology is a complex discipline that involves creating detailed, purpose-built designs from genetic parts. This process is often phrased as a Design-Build-Test-Learn loop, where iterative design improvements can be made, implemented, measured, and analyzed. Automation can potentially improve both the end-to-end duration of the process and the utility of data produced by the process.

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Communicating information about experimental design among a team of collaborators is challenging because different people tend to describe experiments in different ways and with different levels of detail. Sometimes, humans can interpret missing information by making assumptions and drawing inferences from information already provided. Doing so, however, is error-prone and typically requires a high level of interpersonal communication.

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Much progress has been made in developing tools to generate component-based design representations of biological systems from standard libraries of parts. Most biological designs, however, are still specified at the sequence level. Consequently, there exists a need for a tool that can be used to automatically infer component-based design representations from sequences, particularly in cases when those sequences have minimal levels of annotation.

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People who engineer biological organisms often find it useful to draw diagrams in order to communicate both the structure of the nucleic acid sequences that they are engineering and the functional relationships between sequence features and other molecular species. Some typical practices and conventions have begun to emerge for such diagrams. SBOL Visual aims to organize and systematize such conventions in order to produce a coherent language for expressing the structure and function of genetic designs.

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As an engineering endeavor, synthetic biology requires effective sharing of genetic design information that can be reused in the construction of new designs. While there are a number of large community repositories of design information, curation of this information has been limited. This in turn limits the ways in which design information can be put to use.

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Many synthetic gene circuits are restricted to single-use applications or require iterative refinement for incorporation into complex systems. One example is the recombinase-based digitizer circuit, which has been used to improve weak or leaky biological signals. Here we present a workflow to quantitatively define digitizer performance and predict responses to different input signals.

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