We use chemical probes to assess the impact of various protein signaling pathways on peptide hormone maturation. While most studies concentrate solely on secretion, they often overlook the biochemical effects of different stimuli on overall cellular function. Our objective is to identify pathways that enhance secretion by improving cellular efficiency without overburdening the cell. We have developed two distinct methods to investigate where and when peptide hormone maturation occurs within cells. Our first approach employs soft X-ray tomography to quantify the molecular density and crowding of cellular structures. This technique is particularly useful because, as an insulin vesicle matures, it produces increasing amounts of active insulin, forming a dense crystalline core within the vesicle. To monitor vesicle maturation in real-time, we have created a pH-based live cell probe. This probe allows us to analyze the vesicle's pH during exposure to chemical probes, as acidification of the vesicle lumen is a key feature of insulin vesicle maturation. 

Our selected recent publications in this area:

1. Deshmukh A, Chang K, Cuala J, Vanslembrouck B, Georgia S, Loconte V, White KL. Subcellular feature-based classification of α and β cells using soft X-ray tomography. (2024) Cells. 13(10), 869. PMID: 38786091. 

2. Li A, Zhang S, Loconte V, Liu Y, Ekman A, Thompson GJ, Sali A, Stevens RC, White K, Singla J, Sun L. An intensity-based post-processing tool for 3D instance segmentation of organelles in soft X-ray tomograms. (2022) PLOS One. 17(9):e0269887. PMID: 36048824 

3. White KL, Singla J, Loconte V, Chen J-H, Ekman A, Francis JP, Sun L, Zhang X, Francis JP, Li A, Lin W, Tseng K, McDermott G, Alber F, Sali A, Larabell C, Stevens RC. Visualizing subcellular rearrangements in intact β-cells using soft X-ray tomography. (2020) Science Advances (6): eabc8262. PMID: 33298443

Current Lab Members working in this area: Wen Lin and Aneesh Deshmukh 

Each cell contains various organelles with specialized functions, such as secretory vesicles, mitochondria (the cell's powerhouse), and the nucleus (which holds the genetic code). Inter-organelle interactions play a crucial role in regulating cellular biochemistry by enabling the rapid transfer of signaling molecules like calcium or ATP (energy) between compartments. The 3D single-cell technologies we have developed uniquely position our group to quantify these organelle interactions under specific cellular conditions and explore their biochemical roles. We have discovered that insulin vesicle-mitochondria contacts are significantly upregulated in conditions that enhance insulin vesicle maturation. We hypothesize that this communication between insulin vesicles and mitochondria is important for vesicle maturation. To investigate this further, we will use chemical biology tools to determine the stage in the vesicle life cycle at which this interaction occurs. Additionally, we are employing proximity labeling approaches to identify the proteins involved in mediating these inter-organelle contacts. 

Our selected recent publications in this area:

1.  Loconte V, Singla J, Li A, Chen J-H, Ekman A, McDermott G, Sali A, White KL, Larabell CA. Soft X-ray tomography to map and quantify organelle interactions at the mesoscale. (2022). Structure. 30:510-521. PMID: 35148829

2.   Loconte V and White KL. The use of soft X-ray tomography to explore mitochondrial structure and function. (2022). Molecular Metabolism. 57:101421. DOI:10.1016/j.molmet.2021.101421. PMID: 34942399

Current Lab Members working in this area: Rachel Knight and Aneesh Deshmukh

Normal variations in protein content within both cells and organelles lead to functional subtypes that respond differently to signals. For instance, some β cells react rapidly to environmental signals, while others exhibit slower or less pronounced secretory responses. Similarly, mature and immature insulin secretory vesicles are trafficked to different locations within the cell and secrete insulin at different times. These functional subtypes are a natural aspect of biology, but their roles in disease remain largely unexplored. We are utilizing physical and structural parameters of secretory vesicles to develop an unbiased approach for identifying and understanding organelle subtypes and the mechanisms that regulate their remodeling. To do this, we leverage soft X-Ray tomography clustering and direct current dielectrophoresis (DC-iDEP). 

Our selected recent publications in this area:

1. Deshmukh A, Chang K, Cuala J, Vanslembrouck B, Georgia S, Loconte V, White KL. Subcellular feature-based classification of α and β cells using soft X-ray tomography. (2024) Cells. 13(10), 869. PMID: 38786091. 

2. Barekatain M, Liu Y, Archambeau A, Cherezov V, Fraser S, White K, M Hayes. Insulator-based dielectrophoresis-assisted separation of insulin secretory vesicles. (2024) eLife. 13:e74989. PMID: 39190030

Current Lab Members working in this area: Kevin Chang and Ashley Archambeau

A major challenge in understanding cell structure and function is integrating data from various experimental and computational methods. To address this, we employ advanced whole-cell modeling strategies that combine data from diverse experimental approaches and different laboratories. Our lab is engaged in two key collaborations: the Pancreatic Beta Cell Consortium (PBCC) and InnerSpace. The PBCC is an international consortium dedicated to developing innovative experimental and computational methods for whole-cell modeling. InnerSpace, a partnership with the World Building Media Lab at the USC School of Cinematic Arts, aims to create new visual tools for conveying the complexities of structural biology to non-experts and exploring novel ways of modeling multiscale biological structures. As part of this effort, we have developed a virtual reality experience of insulin maturation and secretion to stimulate new discussions and address open questions in the field. Image depicts GLP-1R in a tetrahedral language.

Our selected recent publications in this area:

1.  Singla J, Burdsall K, Cantrell B, Halsey JR, McDowell A, McGregor C, Mittal S, Stevens RC, Su S, Thomopoulos A, Vaillant T, White KL, Zhang B, Berman H. A new visual design language for biological structures in a cell. (2022). Structure. 30(4):485-497. DOI:10.1016/j.str.2022.01.002. PMID: 35093200.

2. Raveh B, Sun L, White KL, Sanyal T, Tempkin J, Zheng DQ, Bharat, K, Singla J, Wang C, Zhao J, Li A, Graham NA, Kesselman C, Stevens RC, Sali A. Bayesian metamodeling complex biological systems across varying representations. (2021) PNAS (35):e2104559118. PMID: 34453000. 

3.  Singla J and White KL. A community approach to whole-cell modeling. (2021). Current Opinion in Systems Biology. 26:33-38. DOI:10.1016/j.coisb.2021.03.009

Current Lab Members working in this area: Wen Lin