Academic literature on the topic 'Mammalian synthetic biology'
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Journal articles on the topic "Mammalian synthetic biology"
Kis, Zoltán, Hugo Sant'Ana Pereira, Takayuki Homma, Ryan M. Pedrigi, and Rob Krams. "Mammalian synthetic biology: emerging medical applications." Journal of The Royal Society Interface 12, no. 106 (May 2015): 20141000. http://dx.doi.org/10.1098/rsif.2014.1000.
Full textBlack, Joshua B., Pablo Perez-Pinera, and Charles A. Gersbach. "Mammalian Synthetic Biology: Engineering Biological Systems." Annual Review of Biomedical Engineering 19, no. 1 (June 21, 2017): 249–77. http://dx.doi.org/10.1146/annurev-bioeng-071516-044649.
Full textMathur, Melina, Joy S. Xiang, and Christina D. Smolke. "Mammalian synthetic biology for studying the cell." Journal of Cell Biology 216, no. 1 (December 8, 2016): 73–82. http://dx.doi.org/10.1083/jcb.201611002.
Full textMartella, Andrea, Steven M. Pollard, Junbiao Dai, and Yizhi Cai. "Mammalian Synthetic Biology: Time for Big MACs." ACS Synthetic Biology 5, no. 10 (April 20, 2016): 1040–49. http://dx.doi.org/10.1021/acssynbio.6b00074.
Full textAubel, Dominique, and Martin Fussenegger. "Mammalian synthetic biology - from tools to therapies." BioEssays 32, no. 4 (March 17, 2010): 332–45. http://dx.doi.org/10.1002/bies.200900149.
Full textGreber, David, and Martin Fussenegger. "Mammalian synthetic biology: Engineering of sophisticated gene networks." Journal of Biotechnology 130, no. 4 (July 2007): 329–45. http://dx.doi.org/10.1016/j.jbiotec.2007.05.014.
Full textKim, Tackhoon, and Timothy K. Lu. "CRISPR/Cas-based devices for mammalian synthetic biology." Current Opinion in Chemical Biology 52 (October 2019): 23–30. http://dx.doi.org/10.1016/j.cbpa.2019.04.015.
Full textKatayama, Kenta, Hitoshi Mitsunobu, and Keiji Nishida. "Mammalian synthetic biology by CRISPRs engineering and applications." Current Opinion in Chemical Biology 52 (October 2019): 79–84. http://dx.doi.org/10.1016/j.cbpa.2019.05.020.
Full textGübeli, Raphael J., Katharina Burger, and Wilfried Weber. "Synthetic biology for mammalian cell technology and materials sciences." Biotechnology Advances 31, no. 1 (January 2013): 68–78. http://dx.doi.org/10.1016/j.biotechadv.2012.01.007.
Full textOno, Hiroki, Shunsuke Kawasaki, and Hirohide Saito. "Orthogonal Protein-Responsive mRNA Switches for Mammalian Synthetic Biology." ACS Synthetic Biology 9, no. 1 (November 25, 2019): 169–74. http://dx.doi.org/10.1021/acssynbio.9b00343.
Full textDissertations / Theses on the topic "Mammalian synthetic biology"
Davidsohn, Noah (Noah Justin). "Foundational platform for mammalian synthetic biology." Thesis, Massachusetts Institute of Technology, 2012. http://hdl.handle.net/1721.1/80250.
Full textCataloged from PDF version of thesis.
Includes bibliographical references (p. 116-129).
The emergent field of synthetic biology is different from many other biological engineering efforts, in that its roots, design principles, and forward engineering perspective have been adopted from electrical engineering and computer science. Synthetic biology is uniquely poised to make great contributions to numerous fields such as bio-fuel, energy production, agriculture and eco-remediation, national defense, and biomedical and tissue engineering. Considerable progress has been made in engineering novel genetic circuits in many different organisms. However, not much progress has been made toward developing a formal methodology to engineer complex genetic systems in mammalian cells. One of the most promising areas of research is the study of embryonic and adult stem cells. Synthetic biology has the potential to greatly impact the progression and development of research in this area of study. A critical impediment to the development of stem cell engineering is the innate complexity, little to no characterization of parts, and limited compositional predictive capabilities. In this thesis, I discuss the strategies used for constructing and optimizing the performance of signaling pathways, the development of a large mammalian genetic part and circuit library, and the characterization and implementation of novel genetic parts and components aimed at developing a foundation for mammalian synthetic biology. I have designed and tested several orthogonal strategies aimed at cell-cell communication in mammalian cells. I have designed a characterization framework for the complete and proper characterization of genetic parts that allows for modular predictive composition of genetic circuits. With this characterization framework I have generated a small library of characterized parts and composite circuits that have well defined input-output relationships that can be used in novel genetic architectures. I also aided in the development of novel analysis and computational tools necessary for accurate predictive composition of these novel circuits. This work collectively provides a foundation for engineering complex intracellular transcriptional networks and intercellular signaling systems in mammalian cells.
by Noah Davidsohn.
Ph.D.
DiAndreth, Breanna Elizabeth. "RNA sensing and programming platforms for mammalian synthetic Biology." Thesis, Massachusetts Institute of Technology, 2019. https://hdl.handle.net/1721.1/123058.
Full textCataloged from PDF version of thesis.
Includes bibliographical references (pages 153-173).
The field of synthetic biology aims to control cellular behavior using programmable gene circuits. Generally these gene circuits sense molecular biomarkers, process these inputs and execute a desired calculated response. This is especially relevant for gene and cell therapies where integrating multiple disease-related inputs and/or sophisticated control could lead to safer and more effective approaches. While mammalian synthetic biology has made great progress, few gene circuit-based therapies have entered the clinic. Regulatory issues aside, this lag may be due to several technical impediments. First, the computing part of circuits is often accomplished via transcriptional regulation, which presents challenges as we move toward the clinic. Second, the field relies on a limited set of sensors; the detection of other types of disease biomarkers will help robustly identify cell state.
Finally, the design cycle currently used to develop gene circuits is laborious and slow, which is not suitable for clinical development, especially applications in personalized medicine. In this thesis I describe how I address these three limitations. I develop a new posttranscriptional regulation platform based on RNA cleavage that I term "PERSIST" (Programmable Endonucleolytic RNA Scission-Induced Stability Tuning). CRISPR-specific endonucleases are adapted as RNA-level regulators for the platform and we demonstrate several genetic devices including cascades, feedback, logic functions and a bistable switch. I explore sensor designs for relevant biomolecules including mRNAs, miRNAs and proteins via the PERSIST and other platforms. Finally, I present a "poly-transfection" method, associated advanced data analysis pipelines, and computational models that make circuit engineering faster and more predictive.
Taken together, the expanded RNA toolkit that the PERSIST platform offers as well as advancements in sensing and circuit design will enable the more straightforward creation of robust gene circuits for gene and cell therapies.
by Breanna Elizabeth DiAndreth.
Ph. D.
Ph.D. Massachusetts Institute of Technology, Department of Biological Engineering
Moorman, Andrew(Andrew Robert). "Machine learning inspired synthetic biology: neuromorphic computing in mammalian cells." Thesis, Massachusetts Institute of Technology, 2020. https://hdl.handle.net/1721.1/129864.
Full textThesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, February, 2020
Cataloged from student-submitted PDF of thesis.
Includes bibliographical references (pages 109-117).
Synthetic biologists seek to collect, refine, and repackage nature so that it's easier to design new and reliable biological systems, typically at the cellular or multicellular level. These redesigned systems are often referred to as "biological circuits," for their ability to perform operations on biomolecular signals, rather than electrical signals, and for their aim to behave as predictably and modularly as would integrated circuits in a computer. In natural and synthetic biological systems, the abstraction of these circuits' behaviors to digital computation is often appropriate, especially in decision-making settings wherein the output is selected to coordinate a discrete set of outcomes, e.g. developmental networks or disease-state classication circuits. However, there are challenges in engineering entire genetic systems that mimic digital logic.
Biological molecules do not generally exist at only two possible concentrations but vary over an analog range of concentrations, and are ordinarily uncompartmentalized in the cell. As a result, scaling biological circuits which rely on digital logic schemes can prove difficult in practice. Neuromorphic devices represent a promising computing paradigm which aims to reproduce desirable, high-level characteristics inspired by how the brain processes information - features like tunable signal processing and resource ecient scaling. They are a versatile substrate for computation, and, in engineered biological systems, marry the practical benefits of digital and analog signal processing. As the decision-making intelligence of engineered-cell therapies, neuromorphic gene circuits could replace digital logic schemes with a modular and reprogrammable analog template, allowing for more sophisticated computation using fewer resources.
This template could then be adapted either externally or autonomously in long-term single cell medicine. Here, I describe the implementation of in-vivo neuromorphic circuits in human cell culture models as a proof-of-concept for their application to personalized medicine. While biology has long served as inspiration for the artificial intelligence community, this work will help launch a new, interactive relationship between the two fields, in which nature offers more to AI than a helpful metaphor. Synthetic biology provides a rigorous framework to actively probe how learning systems work in living things, closing the loop between traditional machine learning and naturally intelligent systems. This thesis offers a starting point from which to pursue cell therapeutic strategies and multi-step genetic differentiation programs, while exposing the inherent learning capabilities of biology (e.g., self-repair, operation in noisy environments, etc.).
Simultaneously, the results included lay groundwork to analyze the role of machine learning in medicine, where its difficult interpretability contradicts the need to guarantee stable, safe, and efficacious therapies. This thesis should not only spur future research in the use of these approaches for personalized medicine, but also broaden the landscape of academics who nd interest in and relevance to its concerns.
by Andrew Moorman.
S.M.
S.M.
S.M. Massachusetts Institute of Technology, Department of Architecture
S.M. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science
Matsuura, Satoshi. "Synthetic RNA-based logic computation in mammalian cells." Kyoto University, 2019. http://hdl.handle.net/2433/242426.
Full textRios, Villanueva Xavier. "Toward Multiplex Genome Engineering in Mammalian Cells." Thesis, Harvard University, 2013. http://dissertations.umi.com/gsas.harvard:11179.
Full textBárcena, Menéndez Diego 1984. "A study on autocatalysis through synthetic biology. Exploration of spatiotemporal dynamics in the presence or absence of synthetic autocatalytic Hepatocyte Growth Factor signaling in mammalian cells." Doctoral thesis, Universitat Pompeu Fabra, 2016. http://hdl.handle.net/10803/523520.
Full textOne unanswered riddle in biology is how can mammalian cells organize to generate ordered patterns such as organs and living beings, in an ever changing environment. An underlying mathematical principle for the generation of order is given by feedback motifs. Here, I present two projects which are part of an effort to recreate stable ordered patterns in a cellular system through information encoded in DNA. In the first part, I present a receiver mammalian cell line which can accurately sense the diffusible Hepatocyte Growth Factor (HGF) through a transcriptional reporter. In the second part I reprogrammed this cell line so that it produces more HGF in response to HGF, in effect creating an autocatalytic positive feedback. In both cases, I have used spatiotemporal quantitative microscopy analysis to monitor the dynamic evolution of the cell lines in response to a HGF stimulus.
Muftic, Diana. "The role of topoisomerase II in replication in mammalian cells." Thesis, University of Oxford, 2011. http://ora.ox.ac.uk/objects/uuid:8c2399d3-5cca-4c50-b1ca-8a5b96890f83.
Full textDuportet, Xavier. "Developing new tools and platforms for mammalian synthetic biology : From the assembly and chromosomal integration of complex dna circuits to the engineering of artificial intercellular communication systems." Paris 7, 2014. http://www.theses.fr/2014PA077262.
Full textMammalian synthetic biology may provide novel therapeutic strategies, help decipher new paths for drug discovery and facilitate synthesis of valuable molecules. Yet, our capacity to program cells is currently hampered both by the lack of efficient approaches to streamline the design, construction and screening of synthetic gene networks, and also by the complexity of mammalian systems and our poor understanding of cellular processes context¬dependencies. To address these problems, I proposed and validated a number of concepts and approaches during my PhD. First, I created a framework for modular and combinatorial assembly of functional (multi)gene expression vectors and their efficient and specific targeted integration into a well-defined chromosomal context in mammalian cells. Second, I developed a platform to identify and characterize new serine reconnbinase systems from Mycobacteriophage genomes in order to extend the toolbox of genome engineering techniques available for mammalian cells progranning. To overcome the apparent limitations in our single-tell rational engineering capacity, I also engineered two new artificial intercellular communication systems for mammalian cells, in order to facilitate the spatial decoupling of different modules of a synthetic circuit. Even though we are still years away from therapies using engineered cells carrying synthetic circuits to repair damaged or non-functional organs or to create de-novo tissues, I believe the contributions developed during the course of my PhD could potentially be used to help fasten the development of therapeutically relevant DNA circuits or to provide new means to understand mechanisms of cellular processes.
Senthivel, Vivek Raj 1983. "Engineering ultrasensivity and differential diffusion to build spatial patterns in a 3D mammalian cell culture system." Doctoral thesis, Universitat Pompeu Fabra, 2017. http://hdl.handle.net/10803/482223.
Full textLa ingeniería de patrones espaciales auto-organizados basados en modelos de reacción-difusión puede ser el trampolín para la ingeniería de tejidos. Informes anteriores basados en estudios teóricos y experimentales han implicado la importancia de la ultrasensibilidad y la difusión diferencial como requisitos clave para la construcción de patrones espaciales auto-organizados en las células de mamíferos con sistemas de señalización extracelular. En el sistema receptor remitente que hemos desarrollado utilizando quistes de riñones caninos Madin-Darby (MDCK) y la señalización por factor de crecimiento de hepatocitos (HGF), he explorado la sensibilidad de diferentes genes a diferentes dosis de HGF para encontrar funciones reguladoras ultrasensibles. Con este análisis, he encontrado con éxito 12 genes candidatos, cuya función reguladora se puede utilizar en posteriores procesos de ingeniería. También he explorado distintas fusiones de proteína con HGF y he encontrado que el mejor candidato es la fusión con Streptavidina (HGF-SA). Esta proteína de fusión tiene una tasa de difusión aparente, en la matriz extracelular de colágeno tipo I, 90 veces más lenta en comparación con el HGF. Estas partes bien caracterizadas pueden usarse para formar bucles de retroalimentación positivos y negativos combinados. La integración y expresión de esta red reguladora de genes en el genoma MDCK, utilizando las herramientas modernas de ingeniería de genoma, potencialmente puede permitir que los quistes MDCK se comuniquen entre sí y formen patrones periódicos auto-organizados. Se predice que tienen longitudes de onda de aproximadamente 6 mm, en un campo de aproximadamente 1000 quistes distribuidos aleatoriamente, durante un periodo de 5 días. Este estudio extiende nuestro conocimiento del control espacio-temporal del crecimiento y desarrollo de los quistes MDCK y, por lo tanto, podría contribuir en la mejora de la ingeniería de tejidos.
Zhang, Ze. "The control of ribosomal RNA synthesis in mammalian cells." Thesis, University of Southampton, 2013. https://eprints.soton.ac.uk/350477/.
Full textBooks on the topic "Mammalian synthetic biology"
Mammalian Artificial Chromosomes (Methods in Molecular Biology). Humana Press, 2003.
Find full textPrescott, Tony J., and Leah Krubitzer. Evo-devo. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780199674923.003.0008.
Full textGwatkin, Ralph B. L. Developmental Biology: A Comprehensive Synthesis (Volume 4): Manipulation of Mammalian Development. Springer, 1986.
Find full textGlen, Alistair, and Christopher Dickman, eds. Carnivores of Australia. CSIRO Publishing, 2014. http://dx.doi.org/10.1071/9780643103177.
Full textBook chapters on the topic "Mammalian synthetic biology"
Lebar, Tina, and Roman Jerala. "Designed Transcriptional Regulation in Mammalian Cells Based on TALE- and CRISPR/dCas9." In Synthetic Biology, 191–203. New York, NY: Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4939-7795-6_10.
Full textWang, Tingting, and Zhen Xie. "Construction and Integration of a Synthetic MicroRNA Cluster for Multiplex RNA Interference in Mammalian Cells." In Synthetic Biology, 347–59. New York, NY: Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4939-7795-6_19.
Full textRoberts, Michael L., Polyxeni Katsoupi, Vivian Tseveleki, and Era Taoufik. "Bioinformatically Informed Design of Synthetic Mammalian Promoters." In Methods in Molecular Biology, 93–112. New York, NY: Springer New York, 2017. http://dx.doi.org/10.1007/978-1-4939-7223-4_8.
Full textWeber, Wilfried, and Martin Fussenegger. "Design of Synthetic Mammalian Quorum-Sensing Systems." In Methods in Molecular Biology, 235–49. Totowa, NJ: Humana Press, 2010. http://dx.doi.org/10.1007/978-1-60761-971-0_17.
Full textScheller, Leo. "Synthetic Receptors for Sensing Soluble Molecules with Mammalian Cells." In Methods in Molecular Biology, 15–33. New York, NY: Springer US, 2021. http://dx.doi.org/10.1007/978-1-0716-1441-9_2.
Full textSaxena, Pratik, Daniel Bojar, and Martin Fussenegger. "Design of Synthetic Promoters for Gene Circuits in Mammalian Cells." In Methods in Molecular Biology, 263–73. New York, NY: Springer New York, 2017. http://dx.doi.org/10.1007/978-1-4939-7223-4_19.
Full textKarlsson, Maria, Wilfried Weber, and Martin Fussenegger. "Design and Construction of Synthetic Gene Networks in Mammalian Cells." In Methods in Molecular Biology, 359–76. Totowa, NJ: Humana Press, 2011. http://dx.doi.org/10.1007/978-1-61779-412-4_22.
Full textBotezatu, L., S. Sievers, L. Gama-Norton, R. Schucht, H. Hauser, and D. Wirth. "Genetic Aspects of Cell Line Development from a Synthetic Biology Perspective." In Genomics and Systems Biology of Mammalian Cell Culture, 251–84. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/10_2011_117.
Full textBecker, Michael A., Kari O. Raivio, and J. Edwin Seegmiller. "Synthesis of Phosphoribosylpyrophosphate in Mammalian Cells." In Advances in Enzymology - and Related Areas of Molecular Biology, 281–306. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2006. http://dx.doi.org/10.1002/9780470122945.ch7.
Full textKashiwagi, Keiko, Yusuke Terui, and Kazuei Igarashi. "Modulation of Protein Synthesis by Polyamines in Mammalian Cells." In Methods in Molecular Biology, 325–36. New York, NY: Springer New York, 2017. http://dx.doi.org/10.1007/978-1-4939-7398-9_27.
Full textConference papers on the topic "Mammalian synthetic biology"
Kopniczky, M., K. Jensen, and P. Freemont. "Introducing the human cell-free TX-TL system as a new prototyping platform for mammalian synthetic biology." In IET/SynbiCITE Engineering Biology Conference. Institution of Engineering and Technology, 2016. http://dx.doi.org/10.1049/cp.2016.1246.
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