European Food Research and Technology

, Volume 244, Issue 7, pp 1211–1223 | Cite as

Proteomic and bioinformatic analysis of proteins on cooking loss in yak longissimus thoracis

  • Huixin Zuo
  • Ling Han
  • Qunli Yu
  • Zhaobin Guo
  • Junyi Ma
  • Mengqi Li
  • Huan La
  • Guangxing Han
Original Paper


It is a challenging task for the meat industry to search for potential predictors of water-holding capacity (WHC) in meat. Based on the data obtained from cooking loss, longissimus thoracis (LT) of yak can be classified into low cooking loss (LCL) and high cooking loss (HCL) groups. Twenty-six proteins were found to be differentially abundant in the LCL and HCL groups. Results showed that cooking loss can be attributed to structural proteins, metabolic enzymes, stress-related proteins and transport protein. The expression level of desmin, troponin T and l-lactate dehydrogenase increased greatly in the HCL group. We then used western blot and hydrophobicity analysis to validate the representative proteins. Furthermore, prediction of protein subcellular localization revealed that the differentially abundant proteins were mostly positioned in the cytoplasm, nucleus and mitochondria. Accordingly, proteomic and bioinformatic analysis have proven excellent tools to quantify the changes of proteins linked to cooking loss, with which we can explain the processes behind WHC in yak muscle.


Proteomics Bioinformatics Postmortem Cooking loss Yak muscle 



This work was supported by the program for National Natural Science Foundation of China (No.31460402), National Natural Science Foundation of China (No.31560463) and the National Beef Cattle Industrial Technology System (CARS-38) from the Ministry of Agriculture of the People’s Republic of China.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no competing interest.

Compliance with ethics requirements

All applicable international, national, and/or institutional guidelines for the care and use of animals were followed. This article does not contain any studies with human participants performed by any of the authors.


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Huixin Zuo
    • 1
    • 2
  • Ling Han
    • 1
  • Qunli Yu
    • 1
  • Zhaobin Guo
    • 1
  • Junyi Ma
    • 3
  • Mengqi Li
    • 1
  • Huan La
    • 4
  • Guangxing Han
    • 5
  1. 1.College of Food Science and EngineeringGansu Agricultural UniversityLanzhouChina
  2. 2.College of Food Science and EngineeringShandong Agricultural UniversityTai’anChina
  3. 3.Qinghai Baide Investment Development Limited CompanyXiningChina
  4. 4.The Datong Cattle Farm in QinghaiXiningChina
  5. 5.Shandong Lorain Food Limited Liability CompanyLinyiChina

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