Integrating endogenous TurboID and data-independent acquisition mass spectrometry for in vivo proximity labeling

TL;DR

This study improves in vivo protein interaction mapping by combining TurboID labeling with DIA mass spectrometry, revealing new interactions in C. elegans.

Contribution

A revised proximity labeling workflow integrating TurboID and DIA-MS for enhanced sensitivity and reproducibility in in vivo interactome studies.

Findings

The pipeline identified known and novel interactors of NEKL–MLT subcomplexes in C. elegans.

Quantitative metrics improved experimental quality and reduced variability across replicates.

DIA-based workflows produced physiologically relevant results despite experimental noise.

Abstract

Proximity labeling has emerged as a powerful approach for identifying protein–protein interaction networks within living systems, particularly those involving weak or transient associations. Here, we present a comprehensive revised proximity labeling workflow, integrating TurboID labeling of endogenously expressed fusion proteins and data-independent acquisition (DIA) mass spectrometry (MS). We benchmark this pipeline with a study of five conserved Caenorhabditis elegans proteins—NEKL-2, NEKL-3, MLT-2, MLT-3, and MLT-4— that form two NEKL–MLT kinase–scaffold subcomplexes involved in membrane trafficking and actin regulation. Profiling of NEKL–MLT interactomes across 23 experiments validated our approach through the identification of known NEKL–MLT binding partners and conserved nekl–mlt genetic interactors, including the discovery of several novel functional interactors. Importantly, inclusion of methodological variations, stringent controls, and filtering strategies enhanced sensitivity and reproducibility, defining a set of intuitive quantitative metrics for routine assessment of experimental quality. We show that DIA-based interactome workflows produce physiologically relevant findings, even in the presence of experimental noise and variability across biological replicates. Our study underscores the utility of DIA mass spectrometry in proximity labeling applications and highlights the value of incorporating internal controls, quantitative metrics, and biological validation to enhance confidence in candidate interactors.

Determining protein–protein interaction networks and their dynamics within living systems remains challenging. This study describes a method combining TurboID labelling with data-independent acquisition (DIA) mass spectrometry for enhanced utility of proximity labelling in vivo.

Combining TurboID-based endogenous labelling with DIA mass spectrometry increases sensitivity and reproducibility of proximity labelling in C. elegans.Quantitative experimental quality metrics reduce experimental noise and variability across biological replicates.Benchmarking of the endogenous TurboID - DIA proteomics pipeline on two NEKL–MLT kinase–scaffold interactomes uncovers novel functional interactors.

Combining TurboID-based endogenous labelling with DIA mass spectrometry increases sensitivity and reproducibility of proximity labelling in C. elegans.

Quantitative experimental quality metrics reduce experimental noise and variability across biological replicates.

Benchmarking of the endogenous TurboID - DIA proteomics pipeline on two NEKL–MLT kinase–scaffold interactomes uncovers novel functional interactors.

A novel combined proximity proteomics pipeline improves design, acquisition and interpretation of systemic in vivo interactome analyses.

Figures