Oral Presentation 31st Annual Lorne Proteomics Symposium 2026

Dual lipid–proteomics analytical workflow reveals organ-wide sex-dependent subcellular organisation in the mouse heart (133162)

Haoyun Fang 1 2 , Alin Rai 1 2 3 , Kevin Huynh 1 2 4 , Seyed Sadegh Eslami 2 3 , Thy Duong 2 , Alex Faulkner 2 , Peter Meikle 1 2 3 , David Greening 1 2 3
  1. Baker Department of Cardiometabolic Health, University of Melbourne, Parkville, Victoria, Australia
  2. Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
  3. Baker Department of Cardiovascular Research Translation and Implementation, La Trobe University, Bundoora, Victoria, Australia
  4. Faculty of Medicine, Nursing and Health Sciences, Monash University, Clayton, Victoria, Australia

The heart is a highly structured organ whose function relies on the precise and dynamic spatial organisation of biomolecules within defined subcellular niches. While mass-spectrometry-based proteomics and lipidomics have provided molecular insights into enriched cardiac organelles, it remains challenging to resolve the organ-wide spatial arrangement of proteins and lipids and their interactions across the tissue, particularly when considering multi-omics integration and sex-dependent differences.

Over the past decade, subcellular proteomics approaches such as protein correlation profiling (PCP), localisation of organelle proteins by isotope tagging (LOPIT), dynamic organellar maps (DOMs), and SubCellBarCode have advanced our understanding of subcellular organisation by combining biochemical fractionation, quantitative MS, and machine-learning-based protein localisation. Building on this foundation, our laboratory optimised a pipeline to map subcellular proteins in frozen mouse hearts using ten-step differential centrifugation, SP3-based sample preparation, label-free data-independent acquisition (DIA) MS, and supervised machine learning (ML), enabling the assignment of over 2,000 proteins to 16 cardiac subcellular niches. Based on this framework, we extended the workflow to incorporate targeted lipidomics to enable lipid-proteomics data integration.

Here, we apply our Dual Lipid-Proteomics Analytical (Dual-LiPA) pipeline to generate organ-wide subcellular lipidome and proteome maps of male and female mouse hearts. This integrative workflow combines sequential organelle fractionation, single-tube protein–lipid extraction, ultrasensitive MS, supervised ML classification, and differential subcellular distribution analysis. Dual-LiPA resolves over 7,000 proteins and 600 lipids into fourteen subcellular niches spanning membrane-bound and membraneless organelles. The supervised ML models uncover specific protein networks within their designated subcellular locations and reveal their relevance to biological functions. In addition, we accurately predict the subcellular localisation of specialised cardiolipin lipids to mitochondria, consistent with their roles in mitochondrial cristae organisation and bioenergetics, underscoring the biological relevance of this integrated proteo-lipidomic framework. Furthermore, this approach reveals sex-dependent subcellular remodelling, including spatial redistribution of immune-related proteins, kinases, transcription factors, and phospholipids.

Together, these heart-specific subcellular multi-omics maps provide a foundational resource for understanding cardiac molecular architecture, advancing the study of sexually dimorphic biology, and enabling future investigations into dynamic cardiac states in health and disease.

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