Biology subjects

Kitata, R. B.

Publications and source records attributed to Kitata, R. B..

5 recordsLinked to original sources

bioRxiv2026

Enhancing Sensitivity in Targeted Single-Cell Proteomics by Coupling a Dual Ion Funnel Interface with Triple Quadrupole Mass Spectrometer

Single-cell proteomics (SCP) has emerged as a powerful approach for understanding cellular heterogeneity and biological processes at unprecedented resolution. However, the extremely limited protein content of individual cells (femtogram to picogram levels) pushes current mass spectrometry instrumentation to its sensitivity limits, creating a critical analytical bottleneck. While selected reaction monitoring (SRM) using triple quadrupole (QqQ) instruments offers advantages in sensitivity and reproducibility for targeted proteomics quantification, SRM still struggles with sensitivity for quantification of moderate- or low-abundance proteins from single-cell sample amounts. Here, we report the development and systematic evaluation of a dual ion funnel interface designed to address the sensitivity limitation by significantly enhancing ion transmission efficiency in commercial QqQ mass spectrometers. The dual ion funnel interface, composed of a curved S-funnel followed by a conventional ion funnel, improves ion transmission efficiency while reducing chemical noise through selective ion focusing. The performance of the dual ion funnel interface was systematically compared to standard interface on a TSQ Vantage platform across samples with different levels of complexity. The dual funnel interface demonstrated to provide up to 25-fold improvement in sensitivity across a wide range of protein concentrations in different biological matrices (low complex mouse macrophage and high complex human cells). Critically, enhanced sensitivity was accompanied by increased analytical reproducibility with lower coefficient of variations. Most importantly, the dual funnel interface enabled reliable quantification of low-abundance proteins that were barely detectable or not detected by the standard interface, extending analysis to single-cell equivalent amounts while maintaining excellent reproducibility. These results demonstrate that the dual funnel interface addresses the critical bottleneck in quantitative targeted proteomics, providing a technological foundation for ultrasensitive targeted SCP that requires both high sensitivity and robust quantitative performance.

biochemistry↗

bioRxiv2025

Improved surfactant-assisted one-pot sample preparation for robust convenient single cell proteomics

Recent advances in mass spectrometry-based single-cell proteomics (SCP) technologies have revolutionized the SCP field for comprehensive characterization of cellular heterogeneity. However, most of the current SCP approaches employ sub-{micro}L to 1 {micro}L processing volume for effective single-cell sample preparation using either ultralow-volume specialized devices or a 384-well plate by frequently adding water to the plate well to compensate water evaporation, which greatly limits their broad accessibility and analytical robustness. Here we report a robust convenient SCP method termed iSOP (improved Surfactant-assisted One-Pot processing) for processing of single cells at the low {micro}L processing volume using the 384-well plate with tight sealing to avoid sample drying loss. This iSOP SCP method was built upon our previously developed SOP method by the replacement of a PCR tube or 96-well plate with the low-volume 384-well plate and systematic optimization of the single-cell processing conditions. After optimization, 3 {micro}L was selected as the processing volume with a mixture of 2 ng trypsin and 2 ng Lys-C enzymes in terms of robustness, detection sensitivity, and operation convenience. With a commonly accessible LC-MS platform, iSOP-MS can detect and quantify [~]1,200-1,800 protein groups from single HeLa or MCF7 cells. Application of iSOP-MS to two neuroblastoma cell lines has demonstrated that iSOP-MS enabled reliable identification of an average of [~]1,700 and [~]2,050 protein groups from single BE2-C and SK-N-SH cells, respectively, and precise characterization of cellular heterogeneity between the two distinct cell types and within the same cell type. When compared to other available SCP methods, iSOP-MS is more robust and convenient for routine, cost-effective quantitative SCP analysis.

biochemistry↗

bioRxiv2023

Computational ranking-assisted identification of Plexin-B2 in homotypic and heterotypic clustering of circulating tumor cells in breast cancer metastasis

Metastasis is the cause of over 90% of all deaths associated with breast cancer, yet the strategies to predict cancer spreading based on primary tumor profiles and therefore prevent metastasis are egregiously limited. As rare precursor cells to metastasis, circulating tumor cells (CTCs) in multicellular clusters in the blood are 20-50 times more likely to produce viable metastasis than single CTCs. However, the molecular mechanisms underlying various CTC clusters, such as homotypic tumor cell clusters and heterotypic tumor-immune cell clusters, are yet to be fully elucidated. Combining machine learning-assisted computational ranking with experimental demonstration to assess cell adhesion candidates, we identified a transmembrane protein Plexin- B2 (PB2) as a new therapeutic target that drives the formation of both homotypic and heterotypic CTC clusters. High PB2 expression in human primary tumors predicts an unfavorable distant metastasis-free survival and is enriched in CTC clusters compared to single CTCs in advanced breast cancers. Loss of PB2 reduces formation of homotypic tumor cell clusters as well as heterotypic tumor-myeloid cell clusters in triple-negative breast cancer. Interactions between PB2 and its ligand Sema4C on tumor cells promote homotypic cluster formation, and PB2 binding with Sema4A on myeloid cells (monocytes) drives heterotypic CTC cluster formation, suggesting that metastasizing tumor cells hijack the PB2/Sema family axis to promote lung metastasis in breast cancer. Additionally, using a global proteomic analysis, we identified novel downstream effectors of the PB2 pathway associated with cancer stemness, cell cycling, and tumor cell clustering in breast cancer. Thus, PB2 is a novel therapeutic target for preventing new metastasis.

cancer biology↗

bioRxiv2022

A streamlined tandem tip-based workflow for sensitive nanoscale phosphoproteomics

Effective phosphoproteome of nanoscale sample analysis remains a daunting task, primarily due to significant sample loss associated with non-specific surface adsorption during enrichment of low stoichiometric phosphopeptide. We developed a novel tandem tip phosphoproteomics sample preparation method that is capable of sample cleanup and enrichment without additional sample transfer, and its integration with our recently developed SOP (Surfactant-assisted One-Pot sample preparation) and iBASIL (improved Boosting to Amplify Signal with Isobaric Labeling) approaches provides a streamlined workflow enabling sensitive, high-throughput nanoscale phosphoproteome measurements. This approach significantly reduces both sample loss and processing time, allowing the identification of >3,000 (>9,500) phosphopeptides from 1 (10) {micro}g of cell lysate using the label-free method without a spectral library. It also enabled precise quantification of [~]600 phosphopeptides from 100 cells sorted by FACS (single-cell level input for the enriched phosphopeptides) and [~]700 phosphopeptides from human spleen tissue voxels with a spatial resolution of 200 {micro}m (equivalent to [~]100 cells) in a high-throughput manner. The new workflow opens avenues for phosphoproteome profiling of mass-limited samples at the low nanogram level.

biochemistry↗

bioRxiv2020

Standardization and Harmonization of Distributed Multi-National Proteotype Analysis supporting Precision Medicine Studies

Cancer has no borders: Generation and analysis of molecular data across multiple centers worldwide is necessary to gain statistically significant clinical insights for the benefit of patients. Here we conceived and standardized a proteotype data generation and analysis workflow enabling distributed data generation and evaluated the quantitative data generated across laboratories of the international Cancer Moonshot consortium. Using harmonized mass spectrometry (MS) instrument platforms and standardized data acquisition procedures, we demonstrated robust, sensitive, and reproducible data generation across eleven sites in nine countries on seven consecutive days in a 24/7 operation mode. The data presented from the high-resolution MS1-based quantitative data-independent acquisition (HRMS1-DIA) workflow shows that coordinated proteotype data acquisition is feasible from clinical specimens using such standardized strategies. This work paves the way for the distributed multi-omic digitization of large clinical specimen cohorts across multiple sites as a prerequisite for turning molecular precision medicine into reality.

molecular biology↗