Affinity purification-mass spectrometry (AP-MS) enables the characterization of protein-protein interactions (PPIs), and the ease and sensitivity of such experiments has progressively increased. Beyond steady-state interactions of target proteins, a strong interest has emerged in monitoring how PPIs change upon significant biological perturbations, such as in disease contexts or small molecule modulation of the target protein. These perturbations likely not only induce PPI changes but can also lead to altered expression of proteins not of direct interest. Changes in protein abundance may alter which proteins adsorb to the affinity purification matrix, and due to the sensitivity of modern mass spectrometers, these differential ''background binders'' can masquerade as differential interactors. Contemporary approaches often do not account for differences in the background proteome, potentially inflating the number of false positives and negatives reported. Here, we provide technical considerations for the reliable annotation of dynamic PPIs, using the O-GlcNAc transferase (OGT) as a case study. We describe the installation of affinity epitope tags on endogenous OGT in mouse embryonic stem cells (mESCs), which we then apply for OGT interactor identification via AP-MS. We show that accurate representation of the bead background, which depends on the affinity matrix in use, is critical for elimination of false positive and false negative PPIs. This became even more pertinent as OGT PPI dynamics were measured under OGT catalytic inhibition via OSMI-4, which is known to perturb gene expression. The proteomes of OSMI-4-treated and control-treated mESCs differed, leading to distinct bead backgrounds in which the differential background proteins appeared as interaction gains or losses. These false positives were resolved by incorporating straightforward experimental controls through a practical statistical framework, allowing for a direct and confident comparison between treatment conditions. Incorporating these considerations into workflows investigating PPI dynamics will improve data fidelity and reproducibility.

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Team leader Erik Ehinger, Ph.D., is on a mission to help more patients benefit from cancer immunotherapies.

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Cholera causes severe diarrheal illness in young children, but the mechanisms underlying age-dependent susceptibility remain unclear. Experimental cholera in neonatal mice recapitulates age-dependent ...

Ryan Rising creates programmes that help people who have been incarcerated to access academic opportunities.

Genomic locus proteomics combines proximity labeling with mass spectrometry to identify the proteins associated with user-defined genomic loci. However, per-region enrichment values from tiledguide designs are typically pooled before hit calling, collapsing the latent spatial structure encodedby overlapping measurements. Here, we describe GLproxScape, an R package that treats per-region enrichments as indirect spatial measurements and reconstructs latent chromatin occupancylandscapes through a Gaussian labeling-kernel forward model. Sequence-specific transcriptionfactors are resolved by motif-anchored non-negative least-squares deconvolution against JASPARor HOCOMOCO position weight matrices, while chromatin regulators which lack defined DNA-binding motifs are inferred as broad occupancy zones, enabling recovery of overlapping membersof multi-subunit complexes. Applied to published genomic locus proteomics datasets at the humanTERT, MYC, FOXP2, and FOXQ1 loci and the mouse Ripk3 locus, GLproxScape recovered knownregulators with predicted positions independently supported by ChIP-Atlas peaks, reconstructedcandidate co-binding relationships, and identified chromatin complexes inaccessible to pooledanalyses. Systematic sgRNA-ablation experiments further showed that densely tiled designsimprove event recovery and positional stability, providing concrete experimental guidance for futuregenomic locus proteomics studies.

High-throughput data-independent acquisition (DIA) workflows paired with short chromatographic separations are increasingly adopted for systems biology and clinical proteomics. However, narrower peak ...

Gutierrez et al. show that cholera toxin induces epithelial LDHA-dependent L-lactate production in the small intestine, creating a nutrient niche that Vibrio cholerae exploits through LldD-mediated L-...

Post-translational modifications (PTMs) are critical to protein function, yet the function of most known modification sites remains uncharacterized. CRISPR-mediated phenotypic screens using base editors offer a powerful approach to dissecting PTM function at scale. However, existing sgRNA design tools for base editing applications are DNA-centric and lack the throughput required to integrate seamlessly with mass-spectrometry-based proteomics experimental outputs. We introduce protein editing in R, PrEditR, an open-source, protein-centric tool for high-throughput sgRNA design for custom base editor screens. PrEditR enables users to designate specific amino acid residues in proteins and design protospacer sequences to target the endogenous gene to install missense mutations via base editors.