Dave Weston is a molecular plant biologist at the Department of Energy's Oak Ridge National Laboratory, investigating how microorganisms affect plant health and tolerance to stressors such as heat and drought. He's using ORNL's Advanced Plant Phenotyping Laboratory , or APPL, to accelerate scientific understanding of plant-microbe interactions with the goal of developing hardy crops ideal for production of advanced fuels, chemicals, and materials, and for plant resilience.
APPL captures a wealth of data on plant characteristics with speed and precision, leveraging robotics, multi-modal imaging technologies and artificial intelligence to help identify key genes and evaluate plant modifications in near real time. As plants move along conveyers in APPL, the system uses fluorescence, thermal, near-infrared and hyperspectral imaging and 3D laser scanning to automatically gather data on each plant's photosynthesis efficiency, growth, water use, stress response and biochemical composition - measuring changes in plants before they are visible to the human eye.
Q: How is APPL uniquely suited to your research?
A: I'm interested in the molecular mechanisms that govern plant resilience, and in particular how plant-microbe relationships influence plant health. Just as in human health, if you're a cancer researcher you're looking at how the microbiome can be better understood and optimized to help fight disease. Plant microbiomes can similarly influence plant response to environmental stressors like drought and heat.
There are thousands, if not millions, of combinations of different microbes and plant genotypes, even if it's within a single species like the poplar tree [a key species of interest as an energy crop]. APPL allows us to quickly assess different combinations with its automated systems.
One of the big challenges I have is finding the components of the plant that are resilient not just at one point in time, but at many different points in time as they grow. This is where APPL is particularly useful.
Plant biologists typically measure plant traits by hand, recording growth data at the beginning of an experiment and then coming back a week or two later to measure them again. But APPL takes more detailed measurements and captures data multiple times throughout the day, giving us a full picture of how the plant is developing. If we have just a couple snapshots during a two-week span, we might miss the response we're looking for. That's the superpower of APPL: the automation, the time series and the insights we get from cutting-edge imaging.
Q: What discoveries have you made using APPL?
A: We discovered microbes that make a moss heat-tolerant and wanted to test whether similar microbes could also enhance heat tolerance in poplar. Our experiments involved identifying heat-tolerant microbes and introducing them to plants that don't typically associate with them. When we tested a combination of plants and microbes in the APPL lab, the inoculated plants showed much greater heat tolerance compared to those without microbes, or those inoculated with microbes from a cold environment.
One of the neat discoveries we made when running those augmented plants through APPL is that some of the benefits from the microbes like photosynthetic efficiency are time-dependent, meaning we see a lot more of the benefit at the beginning of the plant-microbe association and the plant growth cycle than later on.
That finding tells us to concentrate our analysis on the genes, metabolites and proteins early in the plant's growth cycle. If I were to start investigating those components at the end of the growth curve, I'd be looking in the wrong place. That's very important as we focus on the genetics of why we're getting these growth benefits. It's an insight APPL gave us that we would not have seen otherwise.
One of our first big findings in APPL confirmed the effects of a gene our scientists discovered in native poplar trees. The gene, which we named Booster, enhances photosynthesis. When we created poplar trees with greater Booster expression, APPL data verified that the plants grew as much as 200% taller in the greenhouse , with subsequent increase in total biomass.
Q: What's ahead for the future of plant science using APPL?
A: We've done a lot of work with poplar, mosses, and the model Arabidopsis plant, and have gained insights into each of those systems and their microbial associations that confer desired traits. Now we can take what we know about these plant species and their unique relationships with microbes and apply it in other plant systems. The results we're getting aren't just useful for our plants of interest, they can be useful for food crops, crops for energy and new materials, or even biomedical feedstocks.
The APPL team continues to expand capabilities. We have computational scientists developing statistical modeling and AI methods to quickly crunch APPL's big data and extract biologically meaningful traits for genomic analysis. That's automation of a different kind that can speed our research.
I'm also excited that APPL is adding an underground imaging station this year that will let us analyze root systems. I'm interested in molecular genetic pathways that mediate how plants grow and defend against both biotic stress such as pathogens and insects, and abiotic stress like extreme weather events. When you image belowground, you see the root-to-shoot ratio in plants that indicates whether the plant is sending resources to its root system for processes like root elongation, or whether they're sending resources aboveground for more photosynthesis and growth or to defend against abiotic stress. More data about what's happening belowground opens up a means to link the molecular systems we're looking at to traits across the entire plant.
APPL to me is a scientific lever. It takes the things that were hard to do by hand in the laboratory and speeding up those processes, letting us examine alternate levels of variation, whether it's between species or within species, and then integrating those results and findings. We can take what we've learned in our genome-wide association studies, for instance, about how specific plant genes are associated with different traits and efficiently test those findings in a variety of plant species. Because APPL is automated and uses AI-assisted analysis, we can blow the doors open for new knowledge and plant cultivation.
Q: What advice do you have for other users interested in conducting APPL experiments?
A: You need to have a clear hypothesis on what plant traits you think are going to be influenced in your experiment, and how APPL will measure those traits. Otherwise, you'll be inundated with all the data APPL can give you. It's very important to engage with the APPL team and explain what you're trying to get out of the experiment. They can then point you in the right direction, including interacting with an ORNL plant or microbial expert. Having a well-articulated, defined and vetted hypothesis and experiment will be useful for everyone, including for other users, as more plant scientists engage with APPL.
Q: What's the ultimate impact of APPL for plant science?
A: The ultimate impact of APPL is using automation to gain a lot more information across the duration of an experiment with less effort. That's the future of AI and automation in general, and here we're using it to design better scientific experiments and to create improved plant materials. We expect to continue getting better and better analytical outputs in APPL. The result will be groundbreaking for plant biologists who will be able to see changes and traits they didn't even know to look for, or especially when to look for those traits. APPL elevates those important things that are happening as plants grow that we may not have thought about in the past and can change the way we conduct our science.
Researchers interested in accessing the APPL facility can check out the APPL website , and make an inquiry using this short form .
UT-Battelle manages ORNL for DOE's Office of Science, the single largest supporter of basic research in the physical sciences in the United States. DOE's Office of Science is working to address some of the most pressing challenges of our time. For more information, visit energy.gov/science . -Stephanie Seay
