Endolysosomal Proteome Landscapes Through the Lens of Neurodegenerative Risk Alleles

The endolysosomal/Golgi system provides routes for degradation or recycling of plasma membrane (PM) proteins via endocytosis and degradation of cytosolic proteins/organelles via autophagy.

Much evidence supports the idea that endolysosomal system dysfunction underlies a variety of neurodegenerative conditions, ranging from Alzheimer’s Disease and Alzheimer's Disease Related Dementias (AD/ADRD) to Parkinson’s diseases. Among the proteins encoded by genetic drivers of AD/ADRD are core components of the endolysosomal system itself (e.g.

BIN1, PSEN1/2, GRN, CHMP2B) and proteins whose endolysosomal trafficking is disrupted in the context of genetic disease (APP/Ab, SORL1, Tau aggregates).

In addition, the expression of endolysosomal retrograde trafficking regulators such as the Retromer subunit VPS35 are reduced during aging, thereby promoting aberrant accumulation of toxic Ab species.

Nevertheless, how individual risk alleles alter trafficking and degradation pathways within the network and whether diverse alleles converge on a common set of phenotypic outcomes remains unclear.

This reflects, in part, the absence of a framework for understanding the key protein assemblies within the endolysosomal system that are subject to altered regulation in the context of risk alleles.

Building on our previous work defining organelle quality control systems in iNeurons principally through autophagy, we now seek to re-imagine our understanding of the architecture of the endolysosomal system through the generation of “organellar structural proteome landscapes” within the system and through interrogation of how these networks are altered in the context of neurodegenerative disease risk alleles (including VPS35).

Our approach merges organelle isolation with crosslink proteomics to identify interacting protein pairs and couples this with Alphafold Multimer to generate pairwise and higher order structural predictions across organellar proteomes.

This approach, which overcomes several limitations of conventional methods for identifying protein interactions within the context of membrane-bound organelles, has already allowed us to generate structural predictions for hundreds of endosomal and Golgi protein complexes, including complexes that control chloride ion balance or lipid composition within endolysosomes – key drivers of organelle homeostasis.

We propose to: 1) complete and disseminate an integrated structural proteome landscape resource (EndoLysMAPV1) in the HEK293 cell system (Aim 1), 2) generate the first of its kind EndoLysMAPV2 in iNeurons, which we have demonstrated express a dramatically different plasma membrane proteome including numerous dynamic synaptic proteins (Aim 2), and 3) create analogous maps in iNeurons harboring risk allele variants, including VPS35D620N and LRRK2G2019S, which dramatically alters the PM proteome based on our proteomics analysis (Aim 2).

To demonstrate the value of our approach to reveal new biology, Aim 3 will mechanistically dissect new and validated transmembrane protein interactions with endolysosomal membrane embedded transporters that likely contribute directly to endolysosomal function and identity.