Biology subjects

Faktor, J.

Publications and source records attributed to Faktor, J..

5 recordsLinked to original sources

bioRxiv2026

Novel native serum peptidomics workflow enables the discovery of circulating subtype-specific peptide biomarkers in acute ischemic and haemorrhagic stroke

Novel serum peptidomics offers a direct insight into proteolytic activity, tissue injury, and systemic signaling. Nevertheless, existing workflows suffer from low peptide yields, low throughput, and limited recovery of low-abundance species. Here we present a native serum peptidomics protocol that integrates mild acid treatment, solid-phase extraction with molecular weight cutoff filtration and data-independent acquisition mass spectrometry (DIA-MS). The protocol requires less than 100 {micro}l of serum or plasma, is completed within hours, time-cost-effective and compatible with 96-well formats without specialized equipment. Applied to a proof-of-concept cohort of patients with acute ischemic stroke (AIS), intracranial haemorrhage (ICH), and healthy controls, the workflow identified over 12,000 peptides, exceeding the three-fold threshold of existing peptidomics approaches. DIA-MS analysis across independent batches demonstrated 78-83% peptide overlap and consistent fold-change directionality. We further introduce peptide locus analysis, which aggregates overlapping peptides within defined protein regions. This approach revealed bidirectional regulation within individual precursor proteins such as the fibrinogen alpha chain (FIBA), resolving intraprotein proteolytic dynamics. Three candidate peptides from TYB4, CO4B, and ITIH4 proteins accurately distinguished stroke subtypes and controls, while characteristic shifts in peptide physicochemical properties were observed across strokes. This workflow substantially advances the sensitivity, throughput, and biological resolution of serum peptidomics for quantitative multi-biomarker discovery, validation and its output promises effective implementation of AI/ML models aiming for new dimensions in diagnostics, prognostics, prediction and monitoring.

neuroscience↗

bioRxiv2026

Benchmarking five extracellular vesicle proteomics workflows, including low-input Exo-insert and Exo-SP3, for deep mass spectrometry profiling

Small extracellular vesicles (sEVs) are key mediators of intercellular communication, influencing diverse pathological processes, including cancer. While mass spectrometry (MS) has enabled the proteomic analysis of sEVs, sample preparation losses remain a critical bottleneck, particularly for scarce tissue-derived sEVs (Ti-EVs). Here, we systematically benchmark five proteomic workflows introducing Exo-insert, a novel single-vessel method, and Exo-SP3, across both Ti-Evs and cell culture-derived sEVs (CCM-EVs) at low input (0.5-4 {micro}g). Exo-insert and Exo-SP3 enable the identification of [~]1100 protein groups from as little as 0.5 {micro}g sEV input. Notably, optimal sample preparation for MS is source-dependent: Exo-insert and Exo-SP3 display divergent performance across sEV sources. Comparative DDA/DIA analyses establish sample preparation as the primary determinant of proteome recovery, offering a practical framework that matches workflows to sEV amounts and source-specific content for biomarker discovery.

cancer biology↗

bioRxiv2024

Universal toolset for mass spectrometric analysis of intracellular peptidome and small protein fraction

The analysis of native intracellular peptidome has gained significant attention in recent years. However, there is still a need for more knowledge regarding various sample preparation methods that facilitate efficient and reproducible recovery of peptides, which can then be analyzed using quantitative liquid chromatography-mass spectrometry. A similar situation exists in small proteome research, typically defined as polypeptides with masses of less than 100 amino acids, often too long for easy identification without enzymatic digestion. In this context, we describe a set of methods that involve simple denaturation and solid-phase extraction of polypeptides, applicable for isolating short intracellular polypeptides within the desired length range. Our work demonstrates the efficiency and reproducibility of these methods for quantitative analysis of the peptidome in mammalian cells. Additionally, we investigated the flexibility of adjusting the mass range through ultrafiltration. We have shown that these methods can be adapted for highly efficient enrichment and fractionation of small proteins, resulting in polypeptide isolates suitable for tryptic digestion and intact protein analysis. Moreover, we describe the use of freely available computational tools that can effectively manage the analysis of the resulting data. The research presented here will benefit the global scientific community in both fundamental (protein turnover, proteolytic processing, non-canonical open reading frames, etc.) and applied sciences (bioactive/neuro peptide discovery, precision medicine, vaccines, etc.), and other areas that could benefit from selective analysis of short native polypeptides.

cancer biology↗

bioRxiv2022

SRSF1 as a novel interacting partner for IFITM1/3 unravels the emergent role of IFITM1/3 mediating protein expression

IFITM proteins play a role in cancer cell progression through undefined mechanisms. Here, we propose an emergent role of IFITM1/3 regulating protein synthesis. SBP-tagged IFITM1 protein was used to identify an association of IFITM1 protein with the cytosolic isoform of SRSF1 that transports mRNA to the ribosome. This cytosolic association was confirmed in situ using proximity ligation assays for SRSF1 and IFITM1/3, suggesting a role associated with translation. Accordingly, IFITM1/3 were shown to interact with HLA-B mRNA in response to IFN{gamma} stimulation using RNA-protein proximity ligation assays. In addition, shotgun RNA sequencing in IFITM1/IFITM3 null cells and wt-SiHa cells indicated that reduced HLA-B gene expression does not account for lowered HLA-B protein synthesis in response to IFN{gamma}. Furthermore, ribosome profiling using sucrose gradient sedimentation identified a reduction in 80S ribosomal fraction an IFITM1/IFITM3 null cells compared to their wild-type counterpart, partially reverted by IFITM1/3 complementation. Our data all together link the binding of IFITM1/3 proteins to HLA-B mRNA and SRSF1 as a mechanism to catalyze the synthesis of target proteins, suggesting an RNA chaperonin role for IFITM1/3 proteins. SignificanceIFITMs are widely studied for their role in inhibiting viruses, and multiple studies have associated IFITMs with cancer progression. However, mechanistic insights are not well understood. Our study proposes that IFITMs have a role regulating protein synthesis, a pivotal function highly relevant for viral infection and cancer progression. Our results suggest that IFITM1/3 is present in the ribosomal fraction and regulates particular protein expression; among them, we identified HLA-B. Changes in HLA-B expression could impact the presentation and recognition of oncogenic antigens on the cell surface by cytotoxic T cells and, ultimately, limit tumor cell eradication. In addition, the role of IFITMs mediating protein translation is relevant, as has the potential of regulating the expression of viral and oncogenic proteins.

cancer biology↗

bioRxiv2019

Breast cancer classification based on proteotypes obtained by SWATH mass spectrometry

Accurate breast cancer classification is vital for patient management decisions, and better tumour classification is expected to enable more precise and eventually personalized treatment to improve patient outcomes. Here, we present a novel quantitative proteotyping approach based on SWATH mass spectrometry and establish key proteins for breast tumour classification derived from proteotype data. The study was based on 96 tissue samples representing five breast cancer subtypes according to conventional classification. Correlation of SWATH proteotype patterns indicated groups that largely recapitulate these subtypes. However, the proteotype-based classification also revealed varying degrees of heterogeneity within the conventional subtypes, with triple negative tumours being the most heterogeneous. Proteins that contributed most strongly to the proteotype-based classification include INPP4B, CDK1, and ERBB2, which are associated with oestrogen receptor status, tumour grade, and HER2 status, respectively. While these three key proteins exhibited high levels of correlation between protein and transcript levels (R>0.67), general correlation did not exceed R=0.29, indicating the value of protein-level measurements of biomarkers and disease-regulated genes. Overall, our data shows how large-scale protein-level measurements by next-generation proteomics can lead to improved patient stratification for precision medicine.

cancer biology↗