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Vitamin D Assays.
Bikle, DD
Frontiers of hormone research. 2018;:14-30
Abstract
The number of requests for vitamin D metabolite measurements has increased dramatically over the past decade leading commercial laboratories to develop rapid high throughput assays. The measurement of 25-hydroxyvitamin D (25[OH]D) and to a lesser extent 1,25-dihydroxyvitamin D (1,25[OH]2D) dominates these requests, but requests for multiple metabolite measurements in the same sample are also increasing. The most commonly used methods include immunoassays and liquid chromatography/mass spectrometry (LC-MS). Each method has its advantages and disadvantages, but with improvements in technology, especially in LC-MS, this method is gaining ascendance due to its greater precision and flexibility. The use of standards from the National Institutes of Standards and Technology has substantially reduced the variability from laboratory to laboratory, thereby improving the reliability of these measurements. Although the current demand is for measurement of total vitamin D metabolite levels, these metabolites circulate in blood tightly bound to vitamin D binding protein (DBP) and albumin with less than 1% free. The free concentration may be a more accurate indicator of vitamin D status especially in individuals with DBP levels that deviate from the normal population. Thus, methods to measure the free concentration at least of 25(OH)D are becoming available and may supplement if not replace measurements of total levels.
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Open source libraries and frameworks for mass spectrometry based proteomics: a developer's perspective.
Perez-Riverol, Y, Wang, R, Hermjakob, H, Müller, M, Vesada, V, Vizcaíno, JA
Biochimica et biophysica acta. 2014;(1 Pt A):63-76
Abstract
Data processing, management and visualization are central and critical components of a state of the art high-throughput mass spectrometry (MS)-based proteomics experiment, and are often some of the most time-consuming steps, especially for labs without much bioinformatics support. The growing interest in the field of proteomics has triggered an increase in the development of new software libraries, including freely available and open-source software. From database search analysis to post-processing of the identification results, even though the objectives of these libraries and packages can vary significantly, they usually share a number of features. Common use cases include the handling of protein and peptide sequences, the parsing of results from various proteomics search engines output files, and the visualization of MS-related information (including mass spectra and chromatograms). In this review, we provide an overview of the existing software libraries, open-source frameworks and also, we give information on some of the freely available applications which make use of them. This article is part of a Special Issue entitled: Computational Proteomics in the Post-Identification Era. Guest Editors: Martin Eisenacher and Christian Stephan.
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Can we accurately measure the concentration of clinically relevant vitamin D metabolites in the circulation? The problems and their consequences.
Bartoszewicz, Z, Kondracka, A, Jaźwiec, R, Popow, M, Dadlez, M, Bednarczuk, T
Endokrynologia Polska. 2013;(3):238-45
Abstract
Increased interest in vitamin D measurements in clinical studies has contributed to the development in recent years of several new immunochemical assays (manual and for automatic analyzers). New methods, including HPLC (high performance liquid chromatography), and LC-MS/MS (liquid chromatography coupled with tandem mass spectrometry) have also been introduced into routine diagnostic laboratories. Because of the variety of assays and methods used, the question arises which one is the most accurate for the measurement of vitamin D metabolites concentration. In this review, we summarise the advantages and disadvantages of these methods, describe the complexity of vitamin D metabolites pattern in the circulation, and discuss the problem of accurate measuring its concentration.
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The spectral networks paradigm in high throughput mass spectrometry.
Guthals, A, Watrous, JD, Dorrestein, PC, Bandeira, N
Molecular bioSystems. 2012;(10):2535-44
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Abstract
High-throughput proteomics is made possible by a combination of modern mass spectrometry instruments capable of generating many millions of tandem mass (MS(2)) spectra on a daily basis and the increasingly sophisticated associated software for their automated identification. Despite the growing accumulation of collections of identified spectra and the regular generation of MS(2) data from related peptides, the mainstream approach for peptide identification is still the nearly two decades old approach of matching one MS(2) spectrum at a time against a database of protein sequences. Moreover, database search tools overwhelmingly continue to require that users guess in advance a small set of 4-6 post-translational modifications that may be present in their data in order to avoid incurring substantial false positive and negative rates. The spectral networks paradigm for analysis of MS(2) spectra differs from the mainstream database search paradigm in three fundamental ways. First, spectral networks are based on matching spectra against other spectra instead of against protein sequences. Second, spectral networks find spectra from related peptides even before considering their possible identifications. Third, spectral networks determine consensus identifications from sets of spectra from related peptides instead of separately attempting to identify one spectrum at a time. Even though spectral networks algorithms are still in their infancy, they have already delivered the longest and most accurate de novo sequences to date, revealed a new route for the discovery of unexpected post-translational modifications and highly-modified peptides, enabled automated sequencing of cyclic non-ribosomal peptides with unknown amino acids and are now defining a novel approach for mapping the entire molecular output of biological systems that is suitable for analysis with tandem mass spectrometry. Here we review the current state of spectral networks algorithms and discuss possible future directions for automated interpretation of spectra from any class of molecules.
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[Tandem mass spectrometry as screening for inborn errors of metabolism].
Campos H, D
Revista medica de Chile. 2011;(10):1356-64
Abstract
The use of tandem mass spectrometry for the diagnosis of inborn errors of metabolism has the potential to expand the newborn screening panel to include a vast number of diseases. This technology allows the detection, in the same spot of dried blood on filter paper and during one single analytical run, of different metabolic diseases. Tandem mass spectrometry is rapidly replacing the classical screening techniques approach of one-metabolite detected per analysis per disease by its ability of simultaneous quantification of several metabolites as markers of many diseases, such as acylcarnitines and amino acids. It is clear that a single metabolite can be a biomarker for several diseases, so the multiplex approach of using tandem mass spectrometry enhances, on average, the sensitivity and specificity of the screening. However, there are differences for particular metabolites and the diseases they detect within the same method. Disorders such as the tyrosinemias and among the organic acidemias, the methylmalonic acidemias, have a substantially higher false-positive rate than other more common metabolic diseases such as medium-chain acyl-CoA dehydrogenase deficiency and phenylketonuria. Before introducing this technology into routine newborn screening programs it is necessary to consider the frequency of each disease, as well as the response to early treatment or variables related to the collection of the sample.
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Newborn screening of inherited metabolic diseases by tandem mass spectrometry.
Yu, CL, Gu, XF
Beijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences. 2006;(1):103-6
Abstract
Application of TMS technology in newborn screening has resulted in major expansion of disorder panel for metabolic diseases in recent years. This automated, multiplex testing methodology detects multiple analytes from single analysis of one blood spot, which leads to detection of 30-35 disorders of amino acids, organic acids, and fatty acids metabolism. The early identification of persons affected with inborn errors of metabolism has led to unexpected discoveries related to the natural history of the disorder or options for therapy. This article summarized (1) the basic principles of this technology and methodology. (2) Current status of application of this methodology in the United States, European countries and in China. (3) The positive impacts on the public health and advances in medical genetics. Finally (4) Challenges, issues and possible solutions. The purpose of this article aimed at introducing new technology and exploring the possibilities of implementing into developing countries where medical genetics is not developed and foreseeing the possible problems and obstacles.