Data Processing Has Major Impact on the Outcome of Quantitative Label-Free LC-MS Analysis

2014 ◽  
Vol 14 (2) ◽  
pp. 676-687 ◽  
Author(s):  
Aakash Chawade ◽  
Marianne Sandin ◽  
Johan Teleman ◽  
Johan Malmström ◽  
Fredrik Levander
Diagnostics ◽  
2020 ◽  
Vol 10 (12) ◽  
pp. 1052
Author(s):  
Petr G. Lokhov ◽  
Oxana P. Trifonova ◽  
Dmitry L. Maslov ◽  
Elena E. Balashova

In metabolomics, mass spectrometry is used to detect a large number of low-molecular substances in a single analysis. Such a capacity could have direct application in disease diagnostics. However, it is challenging because of the analysis complexity, and the search for a way to simplify it while maintaining the diagnostic capability is an urgent task. It has been proposed to use the metabolomic signature without complex data processing (mass peak detection, alignment, normalization, and identification of substances, as well as any complex statistical analysis) to make the analysis more simple and rapid. Methods: A label-free approach was implemented in the metabolomic signature, which makes the measurement of the actual or conditional concentrations unnecessary, uses only mass peak relations, and minimizes mass spectra processing. The approach was tested on the diagnosis of impaired glucose tolerance (IGT). Results: The label-free metabolic signature demonstrated a diagnostic accuracy for IGT equal to 88% (specificity 85%, sensitivity 90%, and area under receiver operating characteristic curve (AUC) of 0.91), which is considered to be a good quality for diagnostics. Conclusions: It is possible to compile label-free signatures for diseases that allow for diagnosing the disease in situ, i.e., right at the mass spectrometer without complex data processing. This achievement makes all mass spectrometers potentially versatile diagnostic devices and accelerates the introduction of metabolomics into medicine.


2010 ◽  
Vol 2010 ◽  
pp. 1-9 ◽  
Author(s):  
Salvatore Cappadona ◽  
Paolo Nanni ◽  
Marco Benevento ◽  
Fredrik Levander ◽  
Piera Versura ◽  
...  

Label-free LC-MS analysis allows determining the differential expression level of proteins in multiple samples, without the use of stable isotopes. This technique is based on the direct comparison of multiple runs, obtained by continuous detection in MS mode. Only differentially expressed peptides are selected for further fragmentation, thus avoiding the bias toward abundant peptides typical of data-dependent tandem MS. The computational framework includes detection, alignment, normalization and matching of peaks across multiple sets, and several software packages are available to address these processing steps. Yet, more care should be taken to improve the quality of the LC-MS maps entering the pipeline, as this parameter severely affects the results of all downstream analyses. In this paper we show how the inclusion of a preprocessing step of background subtraction in a common laboratory pipeline can lead to an enhanced inclusion list of peptides selected for fragmentation and consequently to better protein identification.


PROTEOMICS ◽  
2012 ◽  
Vol 12 (12) ◽  
pp. 1928-1937 ◽  
Author(s):  
Kerry M. Bauer ◽  
Paul A. Lambert ◽  
Amanda B. Hummon

Talanta ◽  
2011 ◽  
Vol 83 (4) ◽  
pp. 1209-1224 ◽  
Author(s):  
Christin Christin ◽  
Rainer Bischoff ◽  
Péter Horvatovich

Placenta ◽  
2020 ◽  
Vol 101 ◽  
pp. 159-162
Author(s):  
Leen J. Luyten ◽  
Marc Dieu ◽  
Catherine Demazy ◽  
Maude Fransolet ◽  
Tim S. Nawrot ◽  
...  
Keyword(s):  

2015 ◽  
Vol 51 (22) ◽  
pp. 4701-4703 ◽  
Author(s):  
Dandan Li ◽  
You-Jun Fu ◽  
James F. Rusling

A label-free metabolite–protein adduct detection and identification method was developed using magnetic beads coated with metabolic enzymes as bioreactors to generate metabolite–protein adducts for LC-MS/MS analysis.


2021 ◽  
Vol 27 ◽  
Author(s):  
Sophia C. Rossouw ◽  
Hocine Bendou ◽  
Renette J. Blignaut ◽  
Liam Bell ◽  
Jonathan Rigby ◽  
...  

To elucidate cancer pathogenesis and its mechanisms at the molecular level, the collecting and characterization of large individual patient tissue cohorts are required. Since most pathology institutes routinely preserve biopsy tissues by standardized methods of formalin fixation and paraffin embedment, these archived FFPE tissues are important collections of pathology material that include patient metadata, such as medical history and treatments. FFPE blocks can be stored under ambient conditions for decades, while retaining cellular morphology, due to modifications induced by formalin. However, the effect of long-term storage, at resource-limited institutions in developing countries, on extractable protein quantity/quality has not yet been investigated. In addition, the optimal sample preparation techniques required for accurate and reproducible results from label-free LC-MS/MS analysis across block ages remains unclear. This study investigated protein extraction efficiency of 1, 5, and 10-year old human colorectal carcinoma resection tissue and assessed three different gel-free protein purification methods for label-free LC-MS/MS analysis. A sample size of n = 17 patients per experimental group (with experiment power = 0.7 and α = 0.05, resulting in 70% confidence level) was selected. Data were evaluated in terms of protein concentration extracted, peptide/protein identifications, method reproducibility and efficiency, sample proteome integrity (due to storage time), as well as protein/peptide distribution according to biological processes, cellular components, and physicochemical properties. Data are available via ProteomeXchange with identifier PXD017198. The results indicate that the amount of protein extracted is significantly dependent on block age (p < 0.0001), with older blocks yielding less protein than newer blocks. Detergent removal plates were the most efficient and overall reproducible protein purification method with regard to number of peptide and protein identifications, followed by the MagReSyn® SP3/HILIC method (with on-bead enzymatic digestion), and lastly the acetone precipitation and formic acid resolubilization method. Overall, the results indicate that long-term storage of FFPE tissues (as measured by methionine oxidation) does not considerably interfere with retrospective proteomic analysis (p > 0.1). Block age mainly affects initial protein extraction yields and does not extensively impact on subsequent label-free LC-MS/MS analysis results.


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