ICYMI: On behalf of the Duke Center for Quantitative Biodesign, we thank all attendees, invited speakers, faculty, and staff for making the 2nd Annual Biomolecular Condensates Symposium during Fall Break a success. Your expertise and participation are greatly appreciated. We are already looking forward to next year’s symposium.
Author: Xavier Larkin
In Memoriam: Remembering Dr. Philip Benfey
Philip Benfey, ph.d.
INVESTIGATOR OF THE HOWARD HUGHES MEDICAL INSTITUTE AND THE PAUL KRAMER PROFESSOR OF BIOLOGY
The Duke Center for Quantitative Biodesign mourns the loss of our esteemed colleague, Dr. Philip Benfey, an investigator of the Howard Hughes Medical Institute and the Paul Kramer Professor of Biology. Dr. Benfey was a distinguished scientist, known for his pioneering work in genetics, molecular biology, and mathematical modeling. His groundbreaking research on cellular identity and root development in Arabidopsis thaliana was truly transformative.
Dr. Benfey’s ability to bridge theory and practice was exemplified by his founding of three companies—GrassRoots Biotechnology, Hi Fidelity Technologies, and Ground Control Robotics. He was recognized as a fellow of the American Association for the Advancement of Science and a member of the US National Academy of Sciences.
Beyond his scientific achievements, Dr. Benfey was a warm-hearted mentor and friend who inspired all who knew him. His legacy will continue to inspire future generations of scientists.
Our deepest condolences to Dr. Benfey’s family, students, friends, and colleagues. His memory will forever guide us in our pursuit of scientific excellence.
Sarah Shelton, Ph.D. | October 20, 2023| UNC-NCSU
Biography:
Dr. Shelton earned her B.S. and M.S. degrees in Environmental Sciences and Engineering at the University of North Carolina before joining the UNC-NCSU Joint Department of Biomedical Engineering for her Ph.D. During her doctoral studies under the guidance of Paul Dayton, she developed ultrasound contrast imaging and analysis methods to identify tortuous vasculature for improved cancer diagnosis. She earned a F99K00 award from the NIH to continue her studies of the vascular tumor microenvironment through a postdoctoral fellowship at Massachusetts Institute of Technology with Roger Kamm, with a co-appointment at Dana-Farber Cancer Institute with David Barbie. She rejoined the UNC-NCSU Joint Department of Biomedical Engineering as an Assistant Professor in 2023, and her current research is in the development of microfluidic, organ-on-chip models of disease to uncover how the tissue microenvironment and cellular interactions shape pathology and treatment response.
Abstract:
Microphysiological systems or “organ-on-chip” devices are three-dimensional models of simplified biological tissues that have expanded the types of hypotheses that can be explored in vitro. My work focuses on vascularized models of the tumor microenvironment to understand how the endothelial barrier interacts with circulating cells and the surrounding stroma in order to investigate factors that drive growth, metastasis, and resistance to therapy in oncology.One illustration of the capabilities of these models is the observation of metastasis-on-chip. By perfusing cancer cells through microfluidic vascular models in the presence of plasma proteins, we have begun to uncover how the clotting cascade influences the extravasation of cancer cells. Additionally, I developed vascularized models of the tumor microenvironment using cells from surgical resections to generate patient-specific devices. In this model, cancer-associated fibroblasts altered several functional indicators of endothelial phenotype including vascular morphology, barrier function, angiogenesis, and immune cell recruitment, likely through cytokine signaling. These types of devices allow us to dissect cellular interactions that drive disease using real-time imaging and other biological techniques.
2nd Annual Biomolecular Condensates Symposium Schedule
Join us at the 2nd Annual Bimolecular Condensates Symposium at Duke University on both October 16th-17th 2023.
For questions or information, contact Xavier Larkin at xavier.larkin@duke.edu
Please see the attached schedule below:Biomolecular Condensates Symposium- Final Schedule
Clay Wright, Ph.D. | October 6, 2023 | Virginia Tech
Biography:
Dr. Clay Wright’s research aims to understand how signaling networks facilitate both plasticity and robustness in plant form and function and to harness this knowledge to engineer proteins, signaling networks, and biosynthetic pathways for applications in agriculture and biotechnology. He received a B.S. in Chemical and Biomolecular Engineering from North Carolina State University prior to his Ph.D. in Chemical and Biomolecular Engineering from Johns Hopkins University and a Postdoctoral Fellowship in the Departments of Biology and Electrical Engineering at the University of Washington. Clay joined Virginia Tech as Assistant Professor in the department of Biological Systems Engineering. The Wright Plant Synthetic Biology lab integrates approaches from synthetic and computational biology, protein engineering, bioinformatics, molecular evolution, and genetics to quantify signaling dynamics, genetic interactions, and functional relationships in plant signaling.
Abstract:
Humanity is faced with an enormous challenge in the coming decades. The world’s population is rapidly growing, and we need to produce enough food, fuel, medicine and goods to support this growth in an environmentally sustainable and restorative way. Plants will inevitably provide many solutions to the problems we face, but we need to build environmentally sustainable, carbon-negative industries as soon as possible. To accelerate the development of improved agricultural systems that can produce more while using less, we apply synthetic biology approaches to map sequence-function relationships in plant signaling pathways and reengineer them. Towards this end we have developed genetically encoded, ratiometric biosensors for the plant growth hormone auxin in the model yeast Saccharomyces cerevisiae to reengineer how plants respond to this critical hormone. These biosensors have improved quantitative functional studies as well as directed evolution of plant auxin perception machinery. Additionally, these sensors can measure the production of auxin during different growth conditions and phases for S. cerevisiae, and may help us better understand auxin as an interkingdom signaling molecule. To effectively scale our reengineering efforts and expedite expansions to other signaling pathways we have recently developed open-source software for building plasmid and strain libraries using low-cost robotics.
From a Ph.D. to Startup Founder with Dr. Will Cao | 09/15/2023
Friday, September 15, 2023
We would like to give a special thank you to Duke BME Alumna, Dr. Will Cao, for sharing her expertise on the intersection of synthetic biology and generative AI in today’s Frontiers in BioDesign seminar. Your insights as a former Duke student and postdoc in the #YouLab were invaluable!
2nd Annual Biomolecular Condensates Symposium on October 16-17, 2023
Save The Date
Join us for the 2nd Annual Biomolecular Condensates Symposium here at Duke University on October 16-17, 2023. Explore cutting-edge research, engage with experts, and network with peers. Registration is free!
Please see the flyer for more details.
Will Cao, Ph.D.| September 15, 2023
Friday, September 15, 2023
2:00- 3:00 PM
Will Cao, Ph.D.’17
Gordan’s paper featured in the PNAS Journal
ICYMI: Special congratulations to Dr. Raluca Gordan’s Lab on their recent paper entitled, ” UV irradiation remodels the specificity landscape of transcription factors” which was featured in the PNAS Journal.
Hoffman’s research article “Developmental Cell” published in the National Library of Medicine
ICYMI: Congratulations to Dr. Brent Hoffman’s Lab on their recent research article in Developmental Cell which was published in the National Library of Medicine.
In this article, they used discrete time Markov chain simulations to develop a technique for probing the ability of mechanical load on one protein to recruit another. Lastly, they used machine learning to determine how this relationship change as the sub-cellular structure adapt to the mechanical loading.