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Reductive assays for S-nitrosothiols: implications for measurements in biological systems
K Fang1, N V Ragsdale, R M Carey
1Department of Pediatrics, University of Virginia Health Sciences Center, Charlottesville, Virginia, 22908, USA.
Biochemical and Biophysical Research Communications
|December 5, 1998
Summary
Conventional assays may misidentify nitrate (NO-3) as S-nitrosothiols (SNOs). New chemiluminescence methods offer sensitive and specific detection of SNOs in biological samples.
Area of Science:
- Biochemistry
- Analytical Chemistry
- Physiology
Background:
- S-nitrosothiols (SNOs) are biologically active molecules found in various tissues.
- Conventional assays for nitric oxide metabolites may lead to misidentification of SNOs, particularly with nitrate (NO-3) reduction methods.
Purpose of the Study:
- To investigate the potential misidentification of S-nitrosothiols in conventional assays.
- To develop and validate a sensitive and specific method for SNO detection using chemiluminescence.
Main Methods:
- S-nitrosothiols were subjected to different chemical reduction conditions: VCl3 in HCl, KI in acetic acid, photolysis, and CuCl/cysteine.
- Nitric oxide (NO) released was quantified using chemiluminescence detection.
- Assay specificity was tested against nitrite (NO-2), nitrate (NO-3), and 3-nitrotyrosine.
Main Results:
- S-nitrosothiols were readily detected using the VCl3 reduction method but not with KI.
- The CuCl/cysteine reduction method demonstrated high linearity (r2 = 1.0), sensitivity (10 pmol), and specificity, as it did not detect NO-2, NO-3, or 3-nitrotyrosine.
- S-nitrosothiols constituted approximately 2.9% of total NOx in human serum, with less than 5% being low-mass species.
Conclusions:
- Conventional assays may erroneously identify nitrate (NO-3) as SNOs, while nitrite (NO-2) is not similarly misidentified.
- Chemiluminescence-based reduction systems provide a sensitive and specific method for quantifying S-nitrosothiols.
- Assessing the SNO fraction within biological nitric oxide (NOx) is a relevant and feasible approach for future research.