A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä
Improved breast milk proteome coverage by DIA based LC-MS/MS method
Tekijät: Viitaharju, Jenni; Polari, Lauri; Kauko, Otto; Merilahti, Johannes; Rokka, Anne; Toivola, Diana M.; Laitinen, Kirsi
Kustantaja: Wiley-VCH
Julkaisuvuosi: 2024
Journal: Proteomics
Tietokannassa oleva lehden nimi: Proteomics
Lehden akronyymi: Proteomics
Artikkelin numero: 2300340
Vuosikerta: 24
Numero: 14
ISSN: 1615-9853
eISSN: 1615-9861
DOI: https://doi.org/10.1002/pmic.202300340
Verkko-osoite: https://doi.org/10.1002/pmic.202300340
Rinnakkaistallenteen osoite: https://research.utu.fi/converis/portal/detail/Publication/456994723
The breast milk composition includes a multitude of bioactive factors such as viable cells, lipids and proteins. Measuring the levels of specific proteins in breast milk plasma can be challenging because of the large dynamic range of protein concentrations and the presence of interfering substances. Therefore, most proteomic studies of breast milk have been able to identify under 1000 proteins. Optimised procedures and the latest separation technologies used in milk proteome research could lead to more precise knowledge of breast milk proteome. This study (n = 53) utilizes three different protein quantification methods, including direct DIA, library-based DIA method and a hybrid method combining direct DIA and library-based DIA. On average we identified 2400 proteins by hybrid method. By applying these methods, we quantified body mass index (BMI) associated variation in breast milk proteomes. There were 210 significantly different proteins when comparing the breast milk proteome of obese and overweight mothers. In addition, we analysed a small cohort (n = 5, randomly selected from 53 samples) by high field asymmetric waveform ion mobility spectrometry (FAIMS). FAIMS coupled with the Orbitrap Fusion Lumos mass spectrometer, which led to 41.7% higher number of protein identifications compared to Q Exactive HF mass spectrometer.
Ladattava julkaisu This is an electronic reprint of the original article. |
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This work was supported by the Academy of Finland (#258606 (Kirsi Laitinen) and #332582 (Diana M. Toivola). State research funding for university-level health research of the Turku University Hospital Expert Responsibility Area (Kirsi Laitinen), the Diabetes Research Foundation (Kirsi Laitinen), the Päivikki and Sakari Sohlberg Foundation (Kirsi Laitinen), the Juho Vainio Foundation (Kirsi Laitinen), Tyks Foundation (Jenni Viitaharju) and Sigrid Juselius Foundation (Kirsi Laitinen). These funding sources had no role in the design, execution, analyses, interpretation of the data, or decision to submit these results.