RT Journal Article
SR Electronic
T1 A fully automated FAIMS-DIA proteomic pipeline for high-throughput characterization of iPSC-derived neurons
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2021.11.24.469921
DO 10.1101/2021.11.24.469921
A1 Luke Reilly
A1 Lirong Peng
A1 Erika Lara
A1 Daniel Ramos
A1 Michael Fernandopulle
A1 Caroline B. Pantazis
A1 Julia Stadler
A1 Marianita Santiana
A1 Anant Dadu
A1 James Iben
A1 Faraz Faghri
A1 Mike A. Nalls
A1 Steven L. Coon
A1 Priyanka Narayan
A1 Andrew B. Singleton
A1 Mark R. Cookson
A1 Michael E. Ward
A1 Yue A. Qi
YR 2021
UL http://biorxiv.org/content/early/2021/11/25/2021.11.24.469921.abstract
AB Fully automated proteomic pipelines have the potential to achieve deep coverage of cellular proteomes with high throughput and scalability. However, it is important to evaluate performance, including both reproducibility and ability to provide meaningful levels of biological insight. Here, we present an approach combining high field asymmetric waveform ion mobility spectrometer (FAIMS) interface and data independent acquisition (DIA) proteomics approach developed as part of the induced pluripotent stem cell (iPSC) Neurodegenerative Disease Initiative (iNDI), a large-scale effort to understand how inherited diseases may manifest in neuronal cells. Our FAIMS-DIA approach identified more than 8000 proteins per mass spectrometry (MS) acquisition as well as superior total identification, reproducibility, and accuracy compared to other existing DIA methods. Next, we applied this approach to perform a longitudinal proteomic profiling of the differentiation of iPSC-derived neurons from the KOLF2.1J parental line used in iNDI. This analysis demonstrated a steady increase in expression of mature cortical neuron markers over the course of neuron differentiation. We validated the performance of our proteomics pipeline by comparing it to single cell RNA-Seq datasets obtained in parallel, confirming expression of key markers and cell type annotations. An interactive webapp of this temporal data is available for aligned-UMAP visualization and data browsing (https://share.streamlit.io/anant-droid/singlecellumap). In summary, we report an extensively optimized and validated proteomic pipeline that will be suitable for large-scale studies such as iNDI.Competing Interest StatementM.A.N., F.F. and A.D. participation in this project was part of a competitive contract awarded to Data Tecnica International LLC by the National Institutes of Health to support open science research. M.A.N. also currently serves as an advisor for Clover Therapeutics and Neuron23 Inc.