# Bradley Lab — Full Reference > The Bradley Lab studies how life and Earth have changed together over four billion years, using molecular fossils, stable isotopes, remote sensing, computation, and AI-enabled discovery, grounded in field and laboratory work. Source: https://www.bradleylab.org · Generated at build time · Recruitment updated 2026-05-23 ## Principal Investigator Alex Bradley, Associate Professor Department of Earth, Environmental & Planetary Sciences Washington University in St. Louis Email: abradley@wustl.edu ## Research Areas ### Understanding Records of Life Life leaves chemical traces in rocks. We figure out how those traces are produced and what information they carry. Life leaves chemical traces in rocks. Molecules and isotope ratios get locked into sediments, and in principle they tell us what was alive, what the environment looked like, and how both changed over time. The catch is that those signals are complicated, and also get altered after burial. We work on understanding what information it is possible to capture and transmit through the geological record. We do this through a mix of fieldwork, lab experiments, and modeling. ## Modern environments We study places where biology and geochemistry are actively producing the same kinds of signatures we find in the rock record. High-altitude saline lakes, for instance, have water chemistry and microbial communities that produce sedimentary deposits that look like environments we see in ancient rocks. Watching these systems in real time gives us ground truth for interpreting the past. ## Ancient environments We extract organic molecules and measure isotope ratios in sedimentary rocks to reconstruct what depositional settings looked like and what was living in them. The goal is to make inferences about ancient biology and environments, and try to understand how life has changed over geologic time. ## Lab experiments In the lab, we grow organisms under controlled conditions and measure the molecular and isotopic signatures they produce. This tells us what specific metabolisms might look like in the rock record, so we're not just guessing from field data alone. ## Modeling We build quantitative models that combine field and experimental data. These help us identify which chemical patterns are robust recorders of biology, which ones are overprinted by diagenesis, and how confident we should be in any given interpretation. ### Investigating Metabolic Heterogeneity Genetically identical bacteria don't all do the same thing. We use SIMS to measure metabolism one cell at a time and find out why. If you take a clonal bacterial population and feed it a labeled substrate, most cells do what you'd predict. But some fraction does something different: different uptake rates, different metabolic strategies, sometimes completely different phenotypes. This isn't genetic variation. It's cells with the same genome making different choices. One explanation is bet-hedging. If the environment fluctuates, a population that maintains a few metabolically "weird" cells is better positioned to survive a sudden change. We want to know when that's actually what's going on versus other explanations. ## SIMS We measure this cell by cell using [secondary ion mass spectrometry (SIMS)](https://eeps.washu.edu/sims). SIMS lets us image isotope ratios at sub-micron resolution, so we can see exactly which cells in a population took up a labeled substrate and which didn't, and lets us measure things like metal concentrations or even a labeled nucleotide tag. ## How it works We grow cultures, feed them stable isotope tracers, and then analyze hundreds of individual cells by SIMS. This gives us distributions of metabolic activity across a population rather than just a bulk average. From there, we can ask mechanistic questions: what controls the fraction of cells that behave differently, and under what conditions does that variation actually help the population? Do these cells express genes differently? Do they have other differences in their phenotypes? ## Why it matters for the rock record The molecular and isotopic signatures we find in ancient sediments were made by microbial populations, and those populations were heterogeneous. A bulk geochemical measurement from a rock is a weighted average across all the cells that contributed to it. If a metabolic minority was doing something different from the majority, the bulk signal doesn't represent what any individual cell was actually doing. Knowing what metabolic variation looks like in living populations tells us how to read those averages more carefully. ### Spatial Methods for Geochemical Proxies Proxy calibrations can be fooled by geography. We build Bayesian spatial models that separate real environmental signals from spatial confounding. Geochemical proxies are how we reconstruct past climates: molecular and isotopic signals preserved in sediments that correlate with temperature, precipitation, or vegetation. The problem is calibration. Sites near each other tend to have similar climates and similar proxy values, and this spatial autocorrelation can make a proxy look more sensitive than it really is. We build hierarchical Bayesian spatial models to deal with this. Instead of treating geography as noise, we model it explicitly as a structured process. This lets us pull apart the portion of proxy variation that tracks a real environmental variable from the portion that just reflects "nearby sites look alike." It turns out conventional calibrations can substantially overestimate proxy sensitivity. That matters when you're trying to interpret a shift in the sedimentary record. ## Spatially aware calibrations Our models produce calibrations that account for regional baselines. They give more honest estimates of how big a change in proxy signal you need before you can actually claim the environment changed, rather than just seeing spatial structure. ## Uncertainty We want paleoclimate reconstructions to come with real uncertainty bounds. Our framework produces full posterior distributions, not point estimates, so you can make statistically defensible claims about what the past looked like. The models, code, and calibrated datasets are version-controlled and documented, so others — and their machine-learning pipelines — can reuse them rather than rebuild from scratch. ### AI and the Molecular Fossil Record of Petroleum Every oil sample is a molecular fossil record. We are training artificial intelligence on large petroleum geochemistry databases to find patterns that traditional biomarker ratios miss. An oil sample contains hundreds of measurable organic compounds. Their relative abundances reflect what organisms were living in the source environment, what conditions were like when the organic matter was deposited, and what happened to it in the subsurface afterward. There are databases with hundreds of thousands of these samples, but the data is high-dimensional and most analysis relies on simple ratios between compounds. Another approach is to produce [embeddings](https://www.cloudflare.com/learning/ai/what-are-embeddings/) on these databases. The idea is to learn a representation of oil compositions that incorporates the chemistry, the geological context, the paleogeography, and any other information we have about each sample, so samples with similar geological histories end up near each other in the embedding space. This captures relationships between source biology, depositional environment, and thermal maturity that you can't see by looking at one ratio at a time. Longer term, this is building toward a domain-specific foundation model for the molecular record of Earth history: a model pretrained on these databases that others could adapt to their own samples. The workflows and derived datasets are version-controlled and documented, so both researchers and machine-learning systems can build on them rather than start over. ## Working at database scale With enough samples, you can start to pick out signals tied to major events in Earth history: evolutionary innovations, mass extinctions, changes in ocean redox. These patterns are invisible in any single study but emerge when you analyze tens of thousands of samples together. ## Beyond two-compound ratios Traditional petroleum geochemistry works with ratios between pairs of compounds, one at a time. We use the full molecular fingerprint simultaneously. Some of the most interesting signals only show up in the multivariate structure. ### Remote Sensing and Ecosystem Structure Most ecological measurements flatten 3D ecosystems into 2D maps. We use lidar and drones to capture the full spatial structure of forests, outcrops, and landscapes. Most ecological and biogeochemical measurements are two-dimensional: maps, transects, point samples. But ecosystems are three-dimensional. The arrangement of canopies, gaps, and understory in a forest determines light availability, microclimate, and carbon storage. We use drone-mounted lidar, terrestrial laser scanning, multispectral imaging, and satellite data to capture that 3D structure and help us understand how biogeochemistry works. Increasingly we're pushing this from one-time mapping toward repeatable, AI-assisted observation of how places change over time. The aim is to combine field measurements, satellite data, and geospatial foundation models in workflows others can rerun, so the result is scientific interpretation rather than just another image product. ## 3D forest structure One approach is to pair high-resolution lidar with long-term forest inventory data to connect the physical architecture of a forest stand to what's actually happening ecologically. How does canopy arrangement affect growth rates? Where does mortality cluster? What does the 3D structure tell you about carbon storage that a flat map can't? ## Drone photogrammetry We fly drones and process the imagery into orthomosaics and 3D surface models. We've used this for mapping carbonate distributions at high-altitude lakes, surveying rock outcrops, and documenting archaeological sites. ## Lidar across scales Lidar gives you a 3D point cloud of whatever you scan. We've applied it to forests, outcrops, buildings, and archaeological sites at places like Johnson's Shut-Ins, Shaw Nature Reserve, Cahokia Mounds, and Tyson Research Center, and worked with partners to collect data on several continents. ## Scaling up The ground-level structural data we collect calibrates and validates satellite estimates of forest biomass and ecosystem complexity. That's the bridge between a detailed local scan and a global carbon map. ## Cloud computing and large-scale data More and more of this work happens in the cloud. We run analyses on [Microsoft Planetary Computer](https://planetarycomputer.microsoft.com/) and [Google Earth Engine](https://earthengine.google.com/) because the datasets are too big to deal with on a laptop. On the geochemistry side, we pull from [PetDB](https://www.earthchem.org/petdb/) and [GEOROC](https://georoc.eu/) — community databases where decades of published rock and mineral analyses are all in one place. Having everything accessible like this means you can do things that used to be separate projects in a single analysis, like matching a global rock chemistry compilation against satellite land-cover data to see what jumps out. ### The Information Content of Molecular Fossils Many different organisms can produce the same molecule. We use information theory and biosynthetic network analysis to quantify how much a molecular fossil can actually tell you about its source. You find an organic compound preserved in a billion-year-old rock. What made it? The honest answer is often "we're not sure," because multiple organisms, pathways, and precursors can produce the same molecule, and sometimes different biologically-produced molecules get altered to end up looking the same. Geochemists have traditionally handled this by making qualitative judgments about biomarker "specificity," but that's hard to do rigorously. We take a quantitative approach. Using information theory, metabolic network analysis, and other tools, we measure how much a given molecular fossil actually constrains its biological source. Some compounds turn out to be highly diagnostic. Others are ambiguous no matter how well preserved they are. ## Retrobiosynthetic analysis We trace the chemistry backward: starting from a preserved product and working through the network of possible biosynthetic routes that could have made it. This tells us how much the structure of biochemistry itself constrains source attribution, and where the real diagnostic power lies. ## What molecular fossils can't tell you Compounds that would be most useful for identifying their source aren't necessarily the ones that get preserved. But luckily some of the molecules that are preserved tend to be highly specific. The limits on what we can learn from the molecular fossil record aren't just about diagenesis. They're also about the structure of biochemistry: how many organisms make how many molecules through how many pathways. ## People ### Alex Bradley — Associate Professor Alex is a biogeochemist with a background in organic geochemistry and microbiology. He studies how life and Earth have changed together over four billion years, using molecular fossils, stable isotopes, remote sensing, and fieldwork. He also directs the [Fossett Laboratory](https://fossettlab.org). ### Alex Stapley — Research Lab Supervisor Alex keeps the lab running. She has a Master's in physics from Brigham Young University, where she worked on space instrumentation and materials science, and she brings that experimental rigor to everything from thin-film SIMS standards to microbial growth experiments. ### Maggie Hinkston — Graduate Student Maggie came to WashU through the Joint Post-Baccalaureate Program after studying Physics & Astronomy at the University of Tennessee. She's interested in how ideas from information theory can help us understand the origin and ambiguity of molecular biomarkers — essentially, how much can a single fossilized molecule really tell us about the organism that made it? ### Jenny Melara-Valle — JPP Student Jenny joined the lab through WashU's Joint Post-Baccalaureate Program and is now pursuing her Master's. She studied Earth System Science and Data Science at Framingham State, and before coming to WashU she worked on plankton size distributions from satellite data at Princeton and on carbonate geochemistry with Kristin Bergmann at MIT. She's interested in paleoclimatology, organic geochemistry, and biogeochemistry. ## Courses ### AI Inference in Geoscience (EEPS 5000) A project-based seminar applying pretrained AI models to real geoscience datasets and judging when AI inference adds value to a workflow. ### Biogeochemistry (EEPS 3230) How elements cycle among Earth's crust, oceans, and atmosphere, including perturbations due to human activities. ### Field Geology (EEPS 4960) Hands-on application of geological field methods, culminating in an international spring break field trip. ### Geospatial Field Methods (EEPS 4684) Methods for making and analyzing precise geospatial measurements in field settings. ### Organic Geochemistry (EEPS 4454) Composition and analysis of organic material in the environment and geological record. ## Recruitment ### Graduate students — Recruiting graduate students for Fall 2027 PhD students join through the EEPS graduate program. The best applications start with a conversation — email us before you apply and tell us which questions pull at you and why. We welcome people coming from geology, chemistry, biology, or computing; curiosity and persistence matter more than any one background. Apply / learn more: https://eeps.washu.edu/graduate-program ### Postdocs — Fellowship partnerships welcome Funded postdoc lines come and go, but the door is open to good ideas. If your work touches what we do — molecular fossils, stable isotopes, microbial metabolism, remote sensing, or geochemical data science — write to us with a sketch of what you'd want to pursue. We're happy to build a fellowship application with you (NSF, NASA, NOAA, and the like); start the conversation months ahead, not at the deadline. ### Undergraduates — Research spots most semesters If you're a WashU undergraduate curious about how life and Earth shape each other, there's likely a project here for you — in the lab, with field and satellite data, or in code. You can join for credit or through a summer program, and you don't need prior research experience, just curiosity and follow-through. Tell us what's caught your interest. ## Publications - Bradley, A. S. (2026). Biogeochemistry of sulfur. The role of sulfur in planetary processes: From cores to atmospheres. - Paige, L., Hedger, K., Adinda, E., Sulistyawati, E., Bradley, A., Winston, B., DeMatteo, K., Nekaris, K. A. I., Wroblewski, E. (2026). Refining classification of complex agroforestry mosaic landscape from drone-based imagery: Implications for landscape management and conservation. Journal of Applied Ecology. https://doi.org/10.1111/1365-2664.70290 - Leavitt, W. D., Waldbauer, J., Venceslau, S., Sim, M. S., Zhang, L., Jaquelina, B. F., Plummer, S., Diaz, J. M., Pereira, I. A. C., Bradley, A. S. (2024). Energy flux couples sulfur isotope fractionation to proteomic and metabolite profiles in Desulfovibrio vulgaris. Geobiology. https://doi.org/10.1111/gbi.12600 - Beeler, S. R., Gomez, F. J., Bradley, A. S. (2023). Geospatial insights into the controls of microbialite formation at Laguna Negra, Argentina. Geobiology. https://doi.org/10.1111/gbi.12529 - McClelland, H. L. O., Halevy, I., Wolf-Gladrow, D. A., Evans, D., Bradley, A. S. (2021). Statistical uncertainty in paleoclimate proxy reconstructions. Geophysical Research Letters. https://doi.org/10.1029/2021GL092773 - Richardson, J. A., Lepland, A., Hints, O., Prave, A. R., Gilhooly, W. P., Bradley, A. S., Fike, D. A. (2021). Effects of early marine diagenesis and site-specific depositional controls on carbonate-associated sulfate: Insights from paired S and O isotopic analyses. Chemical Geology. https://doi.org/10.1016/j.chemgeo.2021.120525 - Lloyd, M. K., McClelland, H. L. O., Antler, G., Bradley, A. S., Halevy, I., Junium, C. K., Wankel, S. D., Zerkle, A. L. (2020). The isotopic imprint of life on an evolving planet. Space Science Reviews. https://doi.org/10.1007/s11214-020-00730-6 - McClelland, H. L. O., Jones, C., Chubiz, L. M., Fike, D. A., Bradley, A. S. (2020). Substrate specialization in single cells during diauxic growth. mBio. https://doi.org/10.1128/mBio.01519-19 - Smith, D. A., Fike, D. A., Johnston, D. T., Bradley, A. S. (2020). Isotopic fractionation associated with sulfate import and activation by Desulfovibrio vulgaris str. Hildenborough. Frontiers in Microbiology. https://doi.org/10.3389/fmicb.2020.529317 - Bryant, R. N., Jones, C., Raven, M. R., Gomes, M. L., Berelson, W. M., Sessions, A. L., Bradley, A. S., Fike, D. A. (2019). Sulfur isotope analysis of microcrystalline iron sulfides using SIMS imaging: Extracting local paleo–environmental information from modern and ancient sediments. Rapid Communications in Mass Spectrometry. https://doi.org/10.1002/rcm.8375 - Leavitt, W. D., Venceslau, S. S., Waldbauer, J., Smith, D., Pereira, I. A. C., Bradley, A. S. (2019). Proteomic and isotopic response of Desulfovibrio vulgaris to DsrC perturbation. Frontiers in Microbiology. https://doi.org/10.3389/fmicb.2019.00658 - Raven, M. R., Fike, D. A., Bradley, A. S., Gomes, M. L., Owens, J. D., Webb, S. M. (2019). Paired organic matter and pyrite δ³⁴S profiles reveal mechanisms of carbon, sulfur, and iron cycle disruption during Ocean Anoxic Event 2 ( 94 Ma). Earth and Planetary Science Letters. https://doi.org/10.1016/j.epsl.2019.01.048 - Richardson, J. A., Keating, C., Lepland, A., Hints, O., Bradley, A. S., Fike, D. A. (2019). Records of carbon and sulfur from Estonia reveal the importance of depositional environment on interpreting isotope trends. Earth and Planetary Science Letters. https://doi.org/10.1016/j.epsl.2019.01.055 - Rose, C. V., Webb, S. M., Newville, M., Lanzirotti, A., Richardson, J. A., Tosca, N. J., Catalano, J. G., Bradley, A. S., Fike, D. A. (2019). Insights into past ocean proxies from micron-scale mapping of sulfur species in carbonates. Geology. https://doi.org/10.1130/G46228.1 - Raven, M. R., Fike, D. A., Gomes, M. L., Webb, S. M., Bradley, A. S., McClelland, H. L. O. (2018). Organic carbon burial during OAE2 driven by changes in the locus of organic matter sulfurization. Nature Communications. https://doi.org/10.1038/s41467-018-05943-6 - Leavitt, W. D., Murphy, S. J., Lynd, L. R., Bradley, A. S. (2017). Hydrogen isotope composition of lipids of Thermoanaerobacterium saccharolyticum: A comparison of wild type and nfn- transhydrogenase mutants. Organic Geochemistry. https://doi.org/10.1016/j.orggeochem.2017.06.020 - Leavitt, W. D., Flynn, T. M., Suess, M. K., Bradley, A. S. (2016). Transhydrogenase and growth substrate influence lipid hydrogen isotope ratios in Desulfovibrio alaskensis G20. Frontiers in Microbiology. https://doi.org/10.3389/fmicb.2016.00918 - Leavitt, W. D., Venceslau, S. S., Pereira, I. A. C., Johnston, D. T., Bradley, A. S. (2016). Fractionation of sulfur and hydrogen isotopes in Desulfovibrio vulgaris with perturbed DsrC expression. FEMS Microbiology Letters. https://doi.org/10.1093/femsle/fnw226 - Fike, D. A., Bradley, A. S., Leavitt, W. D. (2015). Geomicrobiology of sulfur. Ehrlich's geomicrobiology. - Leavitt, W. D., Bradley, A. S., Santos, A. A., Pereira, I. A. C., Johnston, D. T. (2015). Sulfur Isotope Effects of Dissimilatory Sulfite Reductase. Frontiers in Microbiology. https://doi.org/10.3389/fmicb.2015.01392 - Sáenz, J. P., Grosser, D., Bradley, A. S., Lagny, T. J., Lavrynenko, O., Broda, M., Simons, K. (2015). Hopanoids as functional analogues of cholesterol in bacterial membranes. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.1515607112 - Leavitt, W. D., Cummins, R., Schmidt, M. L., Sim, M. S., Ono, S., Bradley, A. S., Johnston, D. T. (2014). Multiple sulfur isotope signatures of sulfite and thiosulfate reduction by the model dissimilatory sulfate-reducer, Desulfovibrio alaskensis str. G20. Frontiers in Microbiology. https://doi.org/10.3389/fmicb.2014.00591 - Wankel, S. D., Bradley, A. S., Eldridge, D. L., Johnston, D. T. (2014). Determination and application of the equilibrium oxygen isotope effect between water and sulfite. Geochimica et Cosmochimica Acta. https://doi.org/10.1016/j.gca.2013.08.039 - Leavitt, W. D., Halevy, I., Bradley, A. S., Johnston, D. T. (2013). Influence of sulfate reduction rates on the Phanerozoic sulfur isotope record. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.1218874110 - Leavitt, W. D., Halevy, I., Bradley, A. S., Johnston, D. T. (2013). Influence of sulfate reduction rates on the Phanerozoic sulfur isotope record. Proceedings of the National Academy of Sciences of the United States of America. https://doi.org/10.1073/pnas.1218874110 - Lincoln, S. A., Bradley, A. S., Newman, S. A., Summons, R. E. (2013). Archaeal and bacterial glycerol dialkyl glycerol tetraether lipids in chimneys of the Lost City Hydrothermal Field. Organic Geochemistry. https://doi.org/10.1016/j.orggeochem.2013.04.010 - Wankel, S. D., Germanovich, L. N., Lilley, M. D., Genc, G., DiPerna, C. J., Bradley, A. S., Olson, E. J., Girguis, P. R. (2011). Influence of subsurface biosphere on geochemical fluxes from diffuse hydrothermal fluids. Nature Geoscience. https://doi.org/10.1038/ngeo1183 - Bradley, A. S., Summons, R. E. (2010). Multiple origins of methane at the Lost City Hydrothermal Field. Earth and Planetary Science Letters. https://doi.org/10.1016/j.epsl.2010.05.034 - Bradley, A. S., Pearson, A., Sáenz, J. P., Marx, C. J. (2010). Adenosylhopane: The first intermediate in hopanoid side chain biosynthesis. Organic Geochemistry. https://doi.org/10.1016/j.orggeochem.2010.07.003 - Bradley, A. S. (2009). Expanding the limits of life. Scientific American. https://doi.org/10.1038/scientificamerican1209-62 - Bradley, A. S., Hayes, J. M., Summons, R. E. (2009). Extraordinary ¹³C enrichment of diether lipids at the Lost City Hydrothermal Field indicates a carbon-limited ecosystem. Geochimica et Cosmochimica Acta. https://doi.org/10.1016/j.gca.2008.10.005 - Cohen, P. A., Bradley, A. S., Knoll, A. H., Grotzinger, J. P., Jensen, S., Abelson, J., Hand, K., Love, G. D., Metz, J., McLoughlin, N., Meister, P., Shepard, R., Tice, M., Wilson, J. P. (2009). Tubular compression fossils from the Ediacaran Nama Group, Namibia. Journal of Paleontology. https://doi.org/10.1666/09-040R.1 - Love, G. D., Grosjean, E., Stalvies, C., Fike, D. A., Grotzinger, J. P., Bradley, A. S., Kelly, A. E., Bhatia, M., Meredith, W., Snape, C. E., Bowring, S. a., Condon, D. J., Summons, R. E. (2009). Fossil steroids record the appearance of Demospongiae during the Cryogenian period. Nature. https://doi.org/10.1038/nature07673 - Londry, K. L., Dawson, K. G., Grover, H. D., Summons, R. E., Bradley, A. S. (2008). Stable carbon isotope fractionation between substrates and products of Methanosarcina barkeri. Organic Geochemistry. https://doi.org/10.1016/j.orggeochem.2008.03.002 - Martinez, A., Bradley, A. S., Waldbauer, J. R., Summons, R. E., DeLong, E. F. (2007). Proteorhodopsin photosystem gene expression enables photophosphorylation in a heterologous host. Proceedings of the National Academy of Sciences of the United States of America. https://doi.org/10.1073/pnas.0611470104 - Summons, R. E., Bradley, A. S., Jahnke, L. L., Waldbauer, J. R. (2006). Steroids, triterpenoids and molecular oxygen. Philosophical transactions of the Royal Society of London. Series B, Biological sciences. https://doi.org/10.1098/rstb.2006.1837 - Kelley, D. S., Karson, J. A., Fru, G. L., Yoerger, D. R., Shank, T. M., Butterfield, D. A., Hayes, J. M., Schrenk, M. O., Olson, E. J., Proskurowski, G., Jakuba, M., Bradley, A., Larson, B., Ludwig, K., Glickson, D., Buckman, K., Bradley, A. S., Brazelton, W. J., Roe, K., Bernasconi, S. M., Elend, M. J., Lilley, M. D., Baross, J. A., Summons, R. E., Sylva, S. P. (2005). A serpentinite-hosted ecosystem: the Lost City Hydrothermal Field. Science. https://doi.org/10.1126/science.1102556 ## Key Links - Website: https://www.bradleylab.org - Structured data (JSON): https://www.bradleylab.org/api/lab.json - Publications: https://www.bradleylab.org/publications - People: https://www.bradleylab.org/people - Research: https://www.bradleylab.org/research - Courses: https://www.bradleylab.org/courses - Join the lab: https://www.bradleylab.org/join - GitHub: https://github.com/bradleylab/ - Electronic Lab Notebook: https://eln.bradleylab.org - Google Scholar: https://scholar.google.com/citations?user=zInPZhUAAAAJ - ORCID (PI): https://orcid.org/0000-0002-4044-2802