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We report an analytical methodology for the quantification of sulfur in biological molecules via a speciesunspecific postcolumn isotope dilution (online ID) approach using capillary electrophoresis (CE) coupled online with inductively coupled plasma−mass spectrometry (online ID CE/ICP−MS).
The method was optimized using a mixture of standard compounds including sulfate, methionine, cysteine, cystine, and albumin, yielding compound recoveries between 98 and 105%. The quantity of sulfur is further converted to the quantity of the compounds owing to the prior knowledge of the sulfur content in the molecules. The limit of detection and limit of quantification of sulfur in the compounds were 1.3−2.6 and 4.1−8.4 mg L−1, respectively, with a correlation coefficient of 0.99 within the concentration range of sulfur of 5−100 mg L−1. The capability of the method was extended to quantify albumin in its native matrix (i.e., in serum) using experimentally prepared serum spiked with a pure albumin standard for validation. The relative expanded uncertainty of the method for the quantification of albumin was 6.7% (k = 2). Finally, we tested the applicability of the method on real samples by the analysis of albumin in bovine and human sera. For automated data assessment, a software application (IsoCor) which was developed by us in a previous work was developed further for handling of online ID data. The method has several improvements compared to previously published setups: (i) reduced adsorption of proteins onto the capillary wall owing to a special capillary-coating procedure, (ii) baseline separation of the compounds in less than 30 min via CE, (iii) quantification of several sulfur species within one run by means of the online setup, (iv) SI traceability of the quantification results through online ID, and (v) facilitated data processing of the transient signals using the IsoCor application. Our method can be used as an accurate approach for quantification of proteins and other biological molecules via sulfur analysis in complex matrices for various fields, such as environmental, biological, and pharmaceutical studies as well as clinical diagnosis.
Sulfur is an essential element in living organisms, where it plays important roles in various biological processes, such as protein synthesis, enzyme activity, and antioxidant defense. However, the biological effects of different sulfur species can vary widely, and imbalances in sulfur speciation have been observed in a range of diseases, including cancer, Alzheimer’s disease, and diabetes.1−3 The accurate quantification of sulfur and its species in biological samples requires sensitive and selective analytical techniques. In recent years, separation techniques coupled online with inductively coupled plasma−mass spectrometry (ICP−MS) have emerged as powerful online analytical tools complementary to molecular spectrometric methods for speciation analysis of biological compounds.
External calibration4−9 and isotope dilution (ID)10−15 are common calibration approaches applied for online quantification of sulfur species in complex samples. The ID analysis is advantageous over.
Despite numerous advantages offered by hyphenation of chromatography and electrokinetic separation methods with multicollector (MC) ICP-MS for isotope analysis, the main limitation of such systems is the decrease in precision and increase in uncertainty due to generation of short transient signals. To minimize this limitation, most authors compare several isotope ratio calculation methods and establish a multi-step data processing routine based on the precision and accuracy of the methods. However, to the best of our knowledge, there is no universal data processing tool available that incorporates all important steps of the treatment of the transient signals. Thus, we introduce a data processing application (App) IsoCor that facilitates automatic calculation of isotope ratios from transient signals and eases selection of the most suitable method. The IsoCor App performs baseline subtraction, peak detection, mass bias correction, isotope ratio calculation and delta calculation. The feasibility and reliability of the App was proven by reproducing the results from isotope analysis of three elements (neodymium, mercury and sulfur) measured on-line via hyphenated systems. The IsoCor App provides trackability of the results to ensure quality control of the analysis.