Biology subjects

Mitsui, H.

Publications and source records attributed to Mitsui, H..

2 recordsLinked to original sources

bioRxiv2026

Development of an Ethylenediaminetetraacetic Acid-Enhanced Deep Proteomic Profiling Method for Dried Blood Spots and Its Application in Mouse Disease Models

Dried blood spots (DBS) are well-established microsamples used in clinical testing and newborn screening. However, their use in deep proteomics is hindered by highly abundant blood proteins and inefficient protein recovery from filter paper matrices. The non-targeted analysis of non-specifically DBS-absorbed proteins (NANDA) workflow partially overcomes the impact of abundant blood proteins and has enabled the identification of over 5,000 proteins from DBS samples. Nonetheless, residual abundant proteins, including hemoglobin and fibrinogen, constrain deep proteomic analysis. Therefore, this study aimed to evaluate the effects of the metal chelator ethylenediaminetetraacetic acid (EDTA) on the depth of DBS proteomic analysis. An optimized EDTA-enhanced NANDA protocol that incorporated a 100 mM EDTA wash step was compatible with standard DBS collection procedures and required no modification of current clinical workflows, markedly enhancing the depletion of abundant proteins and facilitating its potential use in clinical and translational settings. When combined with Orbitrap Astral data-independent acquisition mass spectrometry, this approach enabled the single-shot identification of more than 7,000 proteins from DBS samples; to the best of our knowledge, this represents the deepest proteome coverage reported to date, and the workflow further supported high-throughput and highly reproducible analyses. Additionally, its application to mouse disease models revealed disease-specific systemic immune signatures from minimal blood volumes. Collectively, these results establish EDTA-enhanced NANDA as a practical and scalable workflow that overcomes longstanding limitations of DBS proteomics, thereby enabling deep, high-throughput, minimally invasive proteomic profiling across diverse biological and experimental contexts.

molecular biology↗

bioRxiv2026

TomAP-MS: an improved tomato lectin affinity purification-based mass spectrometry workflow enabling ultra-deep plasma proteomics

Plasma proteomics is increasingly important for biomarker discovery and disease stratification; however, comprehensive and high-throughput analysis remains challenging because of the extreme dynamic range of plasma proteins. We previously established tomato lectin affinity purification-based mass spectrometry (TomAP-MS), a workflow that enhances plasma proteome coverage via tomato lectin-mediated enrichment. The initial workflow depended on a 4% sodium dodecyl sulfate (SDS) elution, followed by SP3-based purification and digestion, which raised complexity and restricted throughput. In this study, we developed an improved TomAP-MS workflow incorporating lauryl maltose neopentyl glycol (LMNG)-assisted acid elution (LAcE), in which proteins are eluted under acidic conditions in the presence of LMNG. This process is followed by pH adjustment and direct tryptic digestion without SP3 cleanup. Compared with conventional acid elution and the original SDS/SP3 workflow, LAcE increased protein identifications while simplifying sample preparation and improving throughput. Using the optimized workflow, we identified more than 7,500 proteins from human plasma and demonstrated broader applicability in extracellular vesicle enrichment and protein interaction analysis workflows. We demonstrated that ethylenediaminetetraacetic acid plasma was the preferred specimen type, enabling the identification of over 5,000 proteins from just 1 {micro}L of plasma, with minimal impact on proteomic profiles after up to three freeze-thaw cycles. Additionally, the analysis of plasma from 200 healthy individuals reproducibly detected 4,117 proteins across all samples, including many proteins associated with inherited disorders. These findings establish TomAP-MS with LAcE as a practical platform for deep plasma proteomics, supporting its future application in proteomics-based screening and diagnostics.

biochemistry↗