Two BCB Faculty members will present at the BCB Faculty Seminar on September 13:
Eric Henderson’s path in science is:
- B.A. in Biology UCLA
- Ph.D. in Molecular Biology UCLA
- Post-Doc studying telomere biology, UC Berkeley
- Professor, ISU
Eric teaches, promotes and practices rule breaking (when appropriate), fearlessness, and entrepreneurship in all facets of life. He has been involved in several companies including:
- Bio Force Nanosciences, Inc., (biotech)
- Aspera Corp (biotech)
- Creodyne, llc (tech development)
- Bumblefunk Music (media)
- Hello Holdings (Griffle, GriffleGames, Griffle TV; media)
- eMoJoCo, llc (art and media)
Eric is always looking for challenges and opportunities to work with young entrepreneurs. On the side Eric is a performing musician, fiction writer, tinkerer, and gadget freak.
We are interested in the interface between biology and nanotechnology. This has recently been labeled either bionanotechnology or synthetic biology. The label is of no importance. What is important is that 3.6 billion years of biological evolution has resulted in fantastic developments that are the stuff of which the dreams of nanotechnology is made. The challenge is to understand and, in a practical fashion, transfer these insights to the emerging field of nanotechnology so that the wheel (and eyeball, nose, etc. ) need not be invented twice. This is no small challenge. We have created a few tools that will facilitate this effort and a portion of my time is spent determining how best to provide these tools to researchers. A conclusion I have drawn is that a commercial enterprise accomplishes this and also provides an avenue (in theory) by which future developments may be funded and manifest. This theory is far from proven, however.
More on the Henderson Lab Research
Using the magic of DNA hybridization we design and build self-assembling DNA Nanodevices like the Pathogen Sentinel.
DNA Nanostructures and Devices: We make functional nanodevices out of DNA. Our most current device is a pathogen sentinel that can detect, measure and report the presence of a variety of pathogen-related biomarkers. Billions of these sentinels can be created for pennies in a few microliters of saltwater. Even better, since they are made out of DNA they are extremely robust.
We also developed a new method for creating 2D and 3D DNA nanostructures. This method uses DNA origami as a design tool but does not require a single-stranded scaffold of biological origin. In this way, our method allows the creation of any number of DNA nanostructures with much fewer restrictions on size and, importantly, simultaneous assembly in a single reaction ("single pot" self-assembly). Creating useful machines and expanding the general method of DNA-based nanodevice construction are currently the main objectives.
- R. Lutz, J. Lutz, J. Lathrop, T. Klinge, E. Henderson, D. Mathur, and D. Abo Sheasha, (2012) Engineering and verifying requirements for programmable self-assembling nanomachines, Proceedings of the Thirty-Fourth International Conference on Software Engineering (ICSE 2012, Zurich, Switzerland, June 2-9, 2012), pp. 1361-1364.
- Lutz, Robyn R., Lutz, Jack H., Lathrop, James I., Klinge, Titus H., Mathur, Divita, Stull, Don M., Bergquist, Taylor G. and Henderson, Eric R. (2012) Requirements analysis for a product family of DNA nanodevices, Proceedings of the Twentieth IEEE International Requirements Engineering Conference (RE 2012, Chicago, IL, September 24-28, 2012), pp. 211-220.
- Mathur, D. and Henderson, E. (2013) Complex DNA Nanostructures from Oligonucleotide Ensembles, ACS Synthetic Biology, 2, 180-185.
- Ellis, Samuel J., Henderson, Eric R., Klinge, Titus H., Lathrop, James I., Lutz, Jack H., Lutz, Robyn R., Mathur, Divita, and Miner, Andrew S. (2014) Automated Requirements Analysis for a Molecular Watchdog Timer In Proceedings of the 29th ACM/IEEE international conference on Automated software engineering (ASE '14). ACM, New York, NY, USA, 767-778. DOI=10.1145/2642937.2643007 (Awarded the "Manfred Paul Award for Excellence in Software: Theory and Practice").
Area of Expertise: Nanotechnology
Other Affiliations: Henderson Laboratory
By creating tools to enable the automated analysis of data and by creating unique data storage solutions, we hope to enable other researchers to accomplish their research goals more efficiently and effectively.
We develop computational systems and tools that enable researchers to leverage plant genetics and genomics information to better understand basic biology and effect crop improvement. Group members are specifically interested in functional prediction for genes, predictive phenomics, and how gene and chromosome architecture regulate cellular processes. Although work by group members is not specifically limited to maize, it is by far our favorite model system.
How are plant chromosomes arranged? Is it possible to relate the genetic and cytological maps to an assembled genome sequence? Are there sequences present at centromeres that signal the cell to construct kinetochores, the machines that ensure proper chromosome segregation to occur, at the correct site?
As the genomes of more plants get sequenced, complex questions like these can can be translated into testable hypotheses. Eventually the content of plant genomes can be related to broad function, both within the cell and at the level of the organism as a whole.
Convergence of traditional biological investigation with genome content and organization is the focus of much of the work carried out in this group. We explore this area of research using maize, Arabidopsis, and other plants.
Phenotype Prediction for Basic Research
The ability to compare phenotypes, both within and across species, enables predictive biology. Though descriptions of myriad aspects of phenotype are readily available, representation of morphology, development, and other traits using computable formats is in its infancy. It has been shown in vertebrate and other (primarily animal) systems that biological equivalencies can be predicted across broad diversity based on reasoning across phenotype ontology markup of experimentally well-characterized genes and pathways. Within plants, maize, rice, soybean, Medicago, Arabidopsis, and tomato have sufficient gene function information (as inferred from mutational screens) to develop such systems. Given current data and existing algorithms that reason across annotations, it is now possible to assert biologically relevant phenolog relationships associated with genes, genomic regions, molecular pathways, and gene function data for plants.
This sort of work enables:
(1) Prediction of the biology that underlies phenotype in non-model systems, including crops that do not have well-characterized genomes (e.g., blueberry, strawberry, apple, peach, etc.). Using this method, the phenotype of a non-model plant can be used to query model species' genes, molecular markers, pathways, etc. directly to bootstrap testable hypotheses.
(2) Identification of non-obvious model systems to study conserved processes across broad taxa.
(3) Creation of phenotypic data systems that interoperate.
Crop Improvement: Phenotype = Genotype x Environment
Codifying and integrating genotypes with phenotypes and precise environmental conditions enables the discovery of basic biological mechanisms and revolutionize plant breeding. Currently deployed high-throughput phenotype data collection and analysis systems cannot be leveraged across multiple groups' datasets due to the complete absence of guidelines. The development and use of standards and best practices will allow researchers to tease out biologically-relevant environmental conditions and molecular mechanisms from large-scale datasets to enable targeted crop improvement. Satisfying this basic need to enable data sharing is necessary to effect a scale-change for basic biology that leads to agricultural advancement and is critically needed given that doubling production by 2050 in the face of climate change is required to meet worldwide projected needs.
Area of Expertise:
- B.A., Biology, Hendrix College, 1996
- M.S., BIology, Texas Tech University, 1997
- Ph.D., Botany, University of Georgia, 2003