Biology subjects

Kasmaeifar, V.

Publications and source records attributed to Kasmaeifar, V..

4 recordsLinked to original sources

bioRxiv2025

Benchmarking of proximity-dependent biotinylation enzymes across cellular compartments and time windows

Proximity-dependent biotinylation has become a powerful approach for mapping protein interactions and subcellular organization in living cells. Although a growing number of engineered biotin ligases have been introduced, their performance has not been systematically evaluated across diverse cellular contexts. Here, we benchmark ten proximity ligases spanning three bacterial lineages using standardized proteomic workflows across multiple labeling durations, subcellular compartments, and two human cell types. While all enzymes efficiently detect proximal associations, they differ in labeling kinetics, background activity, and spatial specificity. TurboID exhibits the highest overall activity but generates substantial background in standard media. miniTurbo and ultraID support rapid, biotin-dependent labeling with low background, making them better suited for dynamic and time-resolved applications. However, miniTurbo showed aberrant mitochondrial localization with two cytoskeletal baits (VASP and PFN1). Across 15 diverse baits, ultraID consistently provides an excellent combination of specificity, efficiency, and spatial compatibility--including unique recovery of Golgi-resident glycosyltransferases. This study serves as a comparative resource, offering guidance for enzyme selection and experimental design in proximity proteomics.

systems biology↗

bioRxiv2024

Computational design and evaluation of optimal bait sets for scalable proximity proteomics

The spatial organization of proteins in eukaryotic cells can be explored by identifying nearby proteins using proximity-dependent biotinylation approaches like BioID. BioID defines the localization of thousands of endogenous proteins in human cells when used on hundreds of bait proteins. However, this high bait number restricts the approachs usage and gives these datasets limited scalability for context-dependent spatial profiling. To make subcellular proteome mapping across different cell types and conditions more practical and cost-effective, we developed a comprehensive benchmarking platform and multiple metrics to assess how well a given bait subset can reproduce an original BioID dataset. We also introduce GENBAIT, which uses a genetic algorithm to optimize bait subset selection, to derive bait subsets predicted to retain the structure and coverage of two large BioID datasets using less than a third of the original baits. This flexible solution is poised to improve the intelligent selection of baits for contextual studies.

bioinformatics↗

bioRxiv2024

Spatial proteomic mapping of human nuclear bodies reveals new functional insights into RNA regulation

Nuclear bodies are diverse membraneless suborganelles with emerging links to development and disease. Explaining their structure, function, regulation, and implications in human health will require understanding their protein composition; however, isolating nuclear bodies for proteomic analysis remains challenging. We present the first comprehensive proximity proteomics-based map of nuclear bodies, featuring 140 bait proteins (encoded by 119 genes) and 1,816 unique prey proteins. We identified 641 potential nuclear body components, including 131 paraspeckle proteins and 147 nuclear speckle proteins. After validating 31 novel paraspeckle and nuclear speckle components, we discovered regulatory functions for the poorly characterised nuclear speckle- and RNA export-associated proteins PAXBP1, PPIL4, and C19ORF47, and revealed that QKI regulates paraspeckle size. This work provides a systematic framework of nuclear body composition in live cells that will accelerate future research into their organisation and roles in human health and disease.

cell biology↗

bioRxiv2023

Dynamic extracellular proximal interaction profiling reveals Low-Density Lipoprotein Receptor as a new Epidermal Growth Factor signaling pathway component

Plasma membrane proteins are critical mediators of cell-cell and cell-environment interactions, pivotal in intracellular signal transmission vital for cellular functionality. Proximity-dependent biotinylation approaches such as BioID combined with mass spectrometry have begun illuminating the landscape of proximal protein interactions within intracellular compartments. However, their deployment in studies of the extracellular environment remains scarce. Here, we present extracellular TurboID (ecTurboID), a method designed to profile cell surface interactions in living cells on short timescales. We first report on the careful optimization of experimental and data analysis strategies that enable the capture of extracellular protein interaction information. Leveraging the ecTurboID technique, we unveiled the proximal interactome of multiple plasma membrane proteins, notably the epidermal growth factor receptor (EGFR). This led to identifying the low-density lipoprotein receptor (LDLR) as a newfound extracellular protein associating with EGFR, contingent upon the presence of the EGF ligand. We showed that 15 minutes of EGF stimulation induced LDLR localization to the plasma membrane to associate with proteins involved in EGFR regulation. This modified proximity labelling methodology allows us to dynamically study the associations between plasma membrane proteins in the extracellular environment. One Sentence SummaryWe developed extracellular TurboID (ecTurboID) as a new proximity dependent biotinylation approach that can capture dynamic interactions at the cell surface, identifying Low-Density Lipoprotein Receptor as a new ligand-dependent extracellular partner of Epidermal Growth Factor Receptor.

molecular biology↗