dkNET Webinar "Visualizing Organelle and Cell Longevity In Situ" 05/20/22
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Presenter: Rafael Arrojo e Drigo, Ph.D. Assistant Professor, Department of Molecular Physiology and Biophysics, Vanderbilt University Abstract Cells in largely post-mitotic organs can be as old as their host organism. These long-lived cells (LLCs) face a lifelong demand for performance to maintain organ function and are constantly exposed to drivers of molecular and cellular damage. Accordingly, dysfunction of LLCs is associated with aging and age-associated disease processes. Understanding cellular longevity mechanisms requires the identity and distribution pattern of LLCs. We developed imaging tools to quantify the age of cells in situ, which led to the discovery of new LLC types throughout the mouse body. This includes different cell types in the pancreas, where most beta cells can be as old as neurons in the brain. In this presentation, I will show how we apply different microscopy tools to bridge spatial and temporal scales in biology to quantify protein complex, organelle, and cell age in tissues. Applicable to virtually any cell, this imaging platform can reveal the temporal dynamics and longevity of structural components in vivo and their contribution to cell and tissue organization and function. Upcoming webinars schedule: https://dknet.org/about/webinar
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dkNET Webinar "Visualizing Organelle and Cell Longevity In Situ" 05/20/22
- 1. Rafael Arrojo e Drigo, Ph.D. Assistant Professor Department of Molecular Physiology and Biophysics Vanderbilt University Visualizing organelle and cellular turnover in vivo
- 2. Long-lived cells endure a life-long pressure to maintain function and identity • Aging associates with the decline in function of different cells and organs (mainly post-mitotic) • Higher incidence of metabolic and degenerative diseases Need to understand cell longevity and homeostasis mechanisms in health and disease Reverse engineer long-lived cells to discover methods to repair and/or protect tissues from age- related functional decline Lopez-Otin, Cell, 2013
- 3. 1940’s: From “wear and tear” to “metabolic regeneration” Harold Urey Rudolf Schoenheimer David Rittenberg 15N-Leucine 15N-Glycine (3 days) Rat 15N-Rat Schoenheimer et al, The dynamic state of body constituents, 1942
- 4. Identification of long-lived proteins (LLPs) in the CNS 1. What is the distribution of LLPs in situ? 2. Are there long-lived cells outside the brain and do they have LLPs? Low spatial resolution Toyama et al, 2013, 2019 D’angelo et al, 2009 Brain Method rationale is similar to radiocarbon dating (14C) pioneered by Will Libby and Jim Arnold in the 1940/50’s
- 5. Rate of beta cell proliferation ~1-3% 1-2 months < 1% 24 months Rodents Humans Dor et al, Nature 2004 Krishnamurthy, Nature 2006 Rankin, Diabetes 2009 Stolovich-Rain, JBC 2012 Wang et al, Cell Metabolism 2016 Islets of Langerhans, multi-cellular organoids in the pancreas Alpha Beta Delta Endothelial Ductal Fibroblast Acinar Arrojo e Drigo et al, 2019 What is the longevity of islet and exocrine cells? x z y time
- 6. Tissue Imaging islets across scales: from macro to nanometer resolution X-ray microscopy Cell Scanning electron microscopy (SEM) Sub-cellular Tomography Islet of Langerhans Arrojo e Drigo et al, 2019 Scale of resolution Micrometer Nanometer
- 7. The islet structure in 3D Alpha cell Beta cell Cell and organelles in 3D Unpublished data
- 8. Tissue Islet of Langerhans Cell Imaging islets across scales: from macro to nanometer resolution Time
- 9. Age of stars and the universe Stardust Mice labelled with the stable isotope 15N Age of cells, organelles and protein super-complexes Multi-isotope mass spectrometry (MIMS) Resolution in XY: up to 50nm Resolution in Z: nanometer range Tissues Correlative electron and multi-isotope imaging platform (MIMS-EM) Chase with 14N (up to 26 months) Long-lived mice 15N is retained in old structures FVB Arrojo e Drigo et al, 2019
- 10. Cellular archeology - visualizing long-lived cells with MIMS-EM Mass detectors • x Cs+ 15N 14 N Tissue section with 15N-labelled cells and proteins x y z Ratiometric images Young Old Arrojo e Drigo et al, 2019 37 370 15N/14N ratio Mouse brain cortex, layer 2
- 11. The islet contains cells with vastly different longevities MIMS SEM MIMS SEM MIMS SEM Pulse with 15N until P45 Chased for 18 months 37 740 15N/14N ratio Arrojo e Drigo et al, 2019 “Longevity window” P45 18 months Old Young Pulse: Chase: Beta Alpha Delta (in relation to cortical neurons) P21 26 months
- 12. SEM + 3D reconstruction MIMS 37 740 15N/14N ratio Correlation of cell structure at the nanometer resolution range and cell age - in situ 0 5 10 15 0 100 200 300 400 500 Mitochondrial Fraction 15 N/ 14 N ratio r2 = 0.34 p = 0.003 Mitochondrial volume and cell age
- 13. Long-lived Weaning Milk Carbs Changes in nutrient composition and/or demand for cell function Very young Beta cell Future directions / experiments in the works: • What is the functional profile and physiological role of long-lived beta cells? • Can we enhance / modulate beta cell longevity? • Earliest timepoint when long-lived beta cells are born? • What determines if a beta cell will be long- lived (or not)? Adult cell
- 14. Lung Spleen Hepatocytes Long-lived cells are abundant in somatic tissues Skin
- 15. Cerebellum, 6 mo age Mitochondrial longevity in neurons and muscle cells EDL, 6 mo age Krishna et al, Dev Cell 2021
- 16. 6-month old mouse L2 cortex neuron Age heterogeneity of large protein complexes in situ Toyama et al, 2019 Nuclear Pore Complex Regulates nucleus- cytoplasmic transport, gene expression and chromatin structure
- 17. Chlamydomonas reinhardtii P21 26 months Age heterogeneity in the beta cell primary cilium
- 18. Nuclear Pore Complex Primary cilium Age mosaicism as a multi-scale organization pattern leverage on temporal resilience Mitochondria Multi-cellular structures Cells Tissue
- 19. NPC Long-lived proteins Short-lived proteins Long-lived structures as pillars of long-term structural and functional identity Large macromolecular complexes Cell and tissue function
- 20. Adult beta cell physiology Beta cell development Arrojo e Drigo, R. Diabetes, 2021 What is the molecular signature of aging human beta cells? (Shresta et al, in revision)
- 21. Vanderbilt University • Owen McGuiness • David Wasserman • Louise Lantier • Alyssa Hasty • Al Powers • Roland Stein UCSD - NCMIR • Mark H. Ellisman • Keunyoung Kim • Thomas Deerinck • Ranjan Ramachandra • Eric Bushong Caltech - GPS • Yunbin Guan • Victoria Orphan @deltacells Thank you for your attention! r.drigo@Vanderbilt.edu https://lab.vanderbilt.edu/drigo-lab/ Alberta Diabetes Institute • Patrick MacDonald • Birbickram Roy Stanford • Seung Kim UC Boulder • Leslie Leinwand • Jack Gugel Hebrew University • Yuval Dor (Hebrew Univ) Funding agencies Arrojo e Drigo Lab Jade McDaniels Emilee Patterson Melanie Cutler Cristiane Dos Santos, PhD R03 DK127484 U01DK120447 R01DK128932 R01GM029090 DRTC P&F 5U24DK097771