Hello! I’m Diya Francis from India. I recently completed my BS-MS dual degree in Biology with a minor in Data Science at the Indian Institute of Science Education and Research (IISER), Thiruvananthapuram. During my master's thesis, I investigated how QPCTL influences microtubules using CRISPR knockouts, confocal imaging, and proximity labelling-based proteomics. I also worked on the computational side of biology - developing a Next Generation Sequencing data analysis pipeline powered by machine learning - and I’m excited to carry this mix of wet-lab and data-science skills into my PhD.

As part of the Cilia-AI network, I am excited to explore how primary cilia vary in structure and function across complex tissues, utilising advanced imaging, AI, and proteomics.

Outside the lab, I enjoy baking, dancing, theatre, and exploring places—activities that allow me to express my creativity and curiosity in diverse ways.

Diversity of cilia functions and structures in complex tissues

Advanced imaging technologies, such as cryo-electron tomography (cryo-ET) and expansion microscopy, have been pivotal in advancing our understanding of the structure and function of motile cilia. In contrast, the molecular architecture and mechanistic functions of primary cilia remain largely unexplored. Emerging evidence suggests that primary cilia are highly specialized, with their functions and architecture varying across cell types, tissues, and organs. Our recent research has demonstrated that, in complex systems like the pancreas, cilia within the same cell type can form distinct physical connections with other cell types, including axo-ciliary synapses with neurons in the pancreatic innervation. However, the significance of these connections, and how they reflect the structural and functional diversity of cilia, remains poorly understood. To address this, we will employ state-of-the-art techniques to investigate the compositional, structural, and functional diversity of primary cilia in complex tissues. Our approach includes:

(1) Imaging cilia and ciliary components in pancreatic tissue using expansion microscopy to map their distribution and structure in detail. (2) Utilizing a novel AI-based method (DC12) for the automated identification of cilia and other organelles in expansion microscopy tissue images. (3) Applying advanced spatial proteomics and cross-linking mass spectrometry to characterize the molecular composition of cilia. (4) Performing structural and functional analyses using optimized cryo-FIB-SEM and cryo-ET techniques to reveal the molecular architecture of cilia in pancreatic cell types.

With these combined approaches we aim at uncovering the mechanisms underlying cilia diversity and their functional relevance in complex tissues like the pancreas.