scholarly journals Comparison of LFQ and IPTL for Protein Identification and Relative Quantification

Molecules ◽  
2021 ◽  
Vol 26 (17) ◽  
pp. 5330
Author(s):  
Christina Johannsen ◽  
Christian J. Koehler ◽  
Bernd Thiede

(1) Background: Mass spectrometry-based quantitative proteome profiling is most commonly performed by label-free quantification (LFQ), stable isotopic labeling with amino acids in cell culture (SILAC), and reporter ion-based isobaric labeling methods (TMT and iTRAQ). Isobaric peptide termini labeling (IPTL) was described as an alternative to these methods and is based on crosswise labeling of both peptide termini and MS2 quantification. High quantification accuracy was assumed for IPTL because multiple quantification points are obtained per identified MS2 spectrum. A direct comparison of IPTL with other quantification methods has not been performed yet because IPTL commonly requires digestion with endoproteinase Lys-C. (2) Methods: To enable tryptic digestion of IPTL samples, a novel labeling for IPTL was developed that combines metabolic labeling (Arg-0/Lys-0 and Arg-d4/Lys-d4, respectively) with crosswise N-terminal dimethylation (d4 and d0, respectively). (3) Results: The comparison of IPTL with LFQ revealed significantly more protein identifications for LFQ above homology ion scores but not above identity ion scores. (4) Conclusions: The quantification accuracy was superior for LFQ despite the many quantification points obtained with IPTL.

2020 ◽  
Author(s):  
Fengchao Yu ◽  
Sarah E. Haynes ◽  
Alexey I. Nesvizhskii

AbstractMissing values weaken the power of label-free quantitative proteomic experiments to uncover true quantitative differences between biological samples or experimental conditions. Match-between-runs (MBR) has become a common approach to mitigate the missing value problem, where peptides identified by tandem mass spectra in one run are transferred to another by inference based on m/z, charge state, retention time, and ion mobility when applicable. Though tolerances are used to ensure such transferred identifications are reasonably located and meet certain quality thresholds, little work has been done to evaluate the statistical confidence of MBR. Here, we present a mixture model-based approach to estimate the false discovery rate (FDR) of peptide and protein identification transfer, which we implement in the label-free quantification tool IonQuant. Using several benchmarking datasets generated on both Orbitrap and timsTOF mass spectrometers, we demonstrate that IonQuant with FDR-controlled MBR results in superior performance compared to MaxQuant. We further illustrate the need for FDR-controlled MBR in sparse datasets such as those from single-cell proteomics experiments.


2019 ◽  
Vol 18 (4) ◽  
pp. 1477-1485 ◽  
Author(s):  
Johannes Griss ◽  
Florian Stanek ◽  
Otto Hudecz ◽  
Gerhard Dürnberger ◽  
Yasset Perez-Riverol ◽  
...  

2021 ◽  
Vol 41 (8) ◽  
pp. 3833-3842
Author(s):  
SASIKARN KOMKLEOW ◽  
CHURAT WEERAPHAN ◽  
DARANEE CHOKCHAICHAMNANKIT ◽  
PAPADA CHAISURIYA ◽  
CHRIS VERATHAMJAMRAS ◽  
...  

2018 ◽  
Vol 90 (21) ◽  
pp. 12670-12677 ◽  
Author(s):  
Stefano Fornasaro ◽  
Alois Bonifacio ◽  
Elena Marangon ◽  
Mauro Buzzo ◽  
Giuseppe Toffoli ◽  
...  

Lab on a Chip ◽  
2009 ◽  
Vol 9 (7) ◽  
pp. 884 ◽  
Author(s):  
Tsi-Hsuan Hsu ◽  
Meng-Hua Yen ◽  
Wei-Yu Liao ◽  
Ji-Yen Cheng ◽  
Chau-Hwang Lee

2014 ◽  
Vol 13 (3) ◽  
pp. 1281-1292 ◽  
Author(s):  
Susan K. Van Riper ◽  
Ebbing P. de Jong ◽  
LeeAnn Higgins ◽  
John V. Carlis ◽  
Timothy J. Griffin

2017 ◽  
Vol 16 (4) ◽  
pp. 1410-1424 ◽  
Author(s):  
MHD Rami Al Shweiki ◽  
Susann Mönchgesang ◽  
Petra Majovsky ◽  
Domenika Thieme ◽  
Diana Trutschel ◽  
...  

2018 ◽  
Vol 17 (3) ◽  
pp. 1314-1320 ◽  
Author(s):  
Michael R. Hoopmann ◽  
Jason M. Winget ◽  
Luis Mendoza ◽  
Robert L. Moritz

Sign in / Sign up

Export Citation Format

Share Document