FPS1 Antibody
Description
Introduction to FPS1 Antibody
FPS1 antibodies are immunological reagents specifically designed to detect either:
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Yeast Fps1: A glycerol channel regulating cellular responses to arsenic stress
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Human FPS1: A flavoprotein (iron death inhibition protein 1) involved in ferroptosis regulation
These antibodies enable researchers to investigate protein localization, expression levels, and functional interactions through techniques like Western blotting and immunohistochemistry.
Yeast Studies
FPS1 antibodies have been instrumental in elucidating:
Critical findings:
Human Cell Research
Human FPS1 antibodies demonstrate:
Validation Data
The CSB-RA029525A0HU monoclonal antibody shows:
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Clear separation from control IgG in flow cytometry (FITC signal >10x background)
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Consistent performance across fixation/permeabilization protocols
Technical Considerations
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Storage: Maintain at -20°C in 50% glycerol
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Working concentrations:
Emerging Research Directions
Recent studies highlight FPS1's potential in:
Product Specs
Constituents: 50% Glycerol, 0.01M PBS, pH 7.4
Target Background
- Overexpression of FPS1L in plants leads to mitochondrial dysfunction, rendering them more susceptible to oxidative stress induced by continuous light. [FPS1L] PMID: 16786301
Q&A
Here’s a structured collection of FAQs tailored for academic researchers working with APS1 autoantibodies (note: corrected from "FPS1" based on search results ), organized by complexity and focused on methodological rigor:
How can I resolve contradictory data in APS1 autoantibody specificity across studies?
Advanced Analysis Framework:
What protocols optimize APS1 antibody validation in flow cytometry?
Stepwise Workflow:
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Surface vs. Intracellular Staining:
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Blocking: Apply Fc receptor blockers to reduce nonspecific binding in immune cell populations .
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Controls: Include isotype-matched antibodies and knockout cell lines to validate signal specificity .
How do I integrate APS1 autoantibody data with multi-omics datasets?
Advanced Integration Strategies:
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Transcriptomic Correlation: Overlap PhIP-Seq hits with single-cell RNA-seq data from target tissues (e.g., pineal gland) to prioritize antigens expressed in disease-relevant cell types .
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Clinical Metadata Linkage: Use machine learning to associate antibody titers with longitudinal patient outcomes (e.g., time-to-organ dysfunction) .
What are common pitfalls in APS1 antibody cross-reactivity analysis?
Troubleshooting Guide:
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Sequence Homology: Perform BLAST alignment to rule out interspecies cross-reactivity (e.g., human vs. murine isoforms) .
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Peptide Library Bias: Address phage-display library underrepresentation of post-translationally modified epitopes by supplementing with custom peptide arrays .
