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Updated: Jun 17, 2025
Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification
Published on: November 15, 2017
Proteomic stable isotope probing with an upgraded Sipros algorithm for improved identification and quantification of
Yi Xiong1, Ryan S Mueller2, Shichao Feng3
1School of Biological Sciences, University of Oklahoma, Norman, OK, USA.
Background:
Proteomic stable isotope probing (SIP) is used in microbial ecology to trace a non-radioactive isotope from a labeled substrate into de novo synthesized proteins in specific populations that are actively assimilating and metabolizing the substrate in a complex microbial community. The Sipros algorithm is used in proteomic SIP to identify variably labeled proteins and quantify their isotopic enrichment levels (atom%) by performing enrichment-resolved database searching.
Results:
In this study, Sipros was upgraded to improve the labeled protein identification, isotopic enrichment quantification, and database searching speed. The new Sipros 4 was compared with the existing Sipros 3, Calisp, and MetaProSIP in terms of the number of identifications and the accuracy and precision of atom% quantification on both the peptide and protein levels using standard E. coli cultures with 1.07 atom%, 2 atom%, 5 atom%, 25 atom%, 50 atom%, and 99 atom% 13C enrichment. Sipros 4 outperformed Calisp and MetaProSIP across all samples, especially in samples with ≥ 5 atom% 13C labeling. The computational speed on Sipros 4 was > 20 times higher than Sipros 3 and was on par with the overall speed of Calisp- and MetaProSIP-based pipelines. Sipros 4 also demonstrated higher sensitivity for the detection of labeled proteins in two 13C-SIP experiments on a real-world soil community. The labeled proteins were used to trace 13C from 13C-methanol and 13C-labeled plant exudates to the consuming soil microorganisms and their newly synthesized proteins.
Conclusion:
Overall, Sipros 4 improved the quality of the proteomic SIP results and reduced the computational cost of SIP database searching, which will make proteomic SIP more useful and accessible to the border community. Video Abstract.
