STC for Quantitative Cell Biology Seminar: Carolyn Larabell
- Event Type
- Lecture
- Sponsor
- STC for Quantitative Cell Biology Seminar Series
- Location
- Beckman Institute Room 3269 (3rd floor tower room)
- Virtual
- Join online
- Date
- Apr 4, 2025 2:00 pm
- Speaker
- Carolyn Larabell, University of California San Francisco and Lawrence Berkeley National Laboratory
- Contact
- Lisa Johnson
- lisa3@illinois.edu
- Views
- 367
- Originating Calendar
- Beckman Institute Calendar (internal events only)
Carolyn Larabell, University of California San Francisco and Lawrence Berkeley National Laboratory, will lecture on "Quantitative 3D Imaging of Whole Cells Using Soft X-ray Tomography"
Abstract: Soft x-ray tomography (SXT) visualizes and quantifies the structural organization ofbiological organisms up to 20 um diameter. Specimens are imaged in the near-nativestate - rapidly frozen in their normal growth conditions - at a resolution up to 35 nm.Large numbers of cells can be imaged since it takes only 5-10 min to go from the frozenspecimen to a reconstructed tomogram. Imaging is based primarily on the absorption ofCarbon, a common element of all known life. At the same time, water (ice) is virtuallyinvisible so that high-contrast images are obtained based solely on the inherentproperties of the structures examined. This is accomplished by imaging with x-rayphotons in the 'water window' (between 284 – 543eV), where x-ray photons areabsorbed an order of magnitude more strongly by carbon- and nitrogen-containingorganic material than by water. The absorption of soft x-rays adheres to the Beer-Lambert Law and is, therefore, a function of the chemical composition andconcentration of organic material, yielding unique quantitative Linear AbsorptionCoefficient (LAC) measurements for specimen components. We have used this label-free imaging technology to image and quantify a wide variety of structures, includingisolated organic particles, bacteria, yeast, spores, algae, larger mammalian cells andtissue. I will present examples of SXT data that enabled biological findings that couldn’t be obtained with other technologies.