TY - JOUR
T1 - Alternative strategy to explore missing proteins with low molecular weight
AU - Lin, Zhilong
AU - Zhang, Yuanliang
AU - Pan, Huozhen
AU - Hao, Piliang
AU - Li, Siqi
AU - He, Yanbin
AU - Yang, Huanming
AU - Liu, Siqi
AU - Ren, Yan
N1 - Publisher Copyright:
© 2019 American Chemical Society.
PY - 2019
Y1 - 2019
N2 - Identifying more missing proteins (MPs) is an important mission of C-HPP. With the number of identified MPs being attenuated year by year (2,949 to 2,129 MPs from 2016 to 2019), we have realized that the difficulty of exploring the remaining MPs is a challenge in technique. Herein, we propose a comprehensive strategy to effectively enrich, separate, and identify proteins with low molecular weights, aiming at the discovery of MPs. Basically, a protein extract from human placenta was passed through a C18 SPE column, and the bound proteins that were eluted were further separated with an SDS-PAGE gel or a 50 kDa cutoff filter. The separated proteins were subjected to trypsin digestion, and the MS/MS signals were searched against data sets with two different digestion modes (full-Trypsin and semitrypsin). The strategy was adopted, resulting in the identification of 4 MPs with 8 unique peptides (≥2 non-nested unique peptides with ≥9 amino acids). Importantly, the identification of 6 out of 8 of the unique peptides derived from the MPs was further supported by parallel reaction monitoring, which confirmed the identification of 3 MPs from human placenta tissues (Q6NT89: TMF-regulated nuclear protein 1; A0A183: late cornified envelope protein 6A; and Q6UWQ7: insulin growth factor-like family member 2, mapped to chromosomes 1, 1, and 19, respectively). The three proteins ranged in length from 80 aa to 227 aa. The study not only establishes a feasible strategy for analyzing proteins with low molecular weights but also fills a small part of a large gap in the list of MPs. The data obtained in this study are available via ProteomeXchange (PXD014083) and PeptideAtlas (PASS01389).
AB - Identifying more missing proteins (MPs) is an important mission of C-HPP. With the number of identified MPs being attenuated year by year (2,949 to 2,129 MPs from 2016 to 2019), we have realized that the difficulty of exploring the remaining MPs is a challenge in technique. Herein, we propose a comprehensive strategy to effectively enrich, separate, and identify proteins with low molecular weights, aiming at the discovery of MPs. Basically, a protein extract from human placenta was passed through a C18 SPE column, and the bound proteins that were eluted were further separated with an SDS-PAGE gel or a 50 kDa cutoff filter. The separated proteins were subjected to trypsin digestion, and the MS/MS signals were searched against data sets with two different digestion modes (full-Trypsin and semitrypsin). The strategy was adopted, resulting in the identification of 4 MPs with 8 unique peptides (≥2 non-nested unique peptides with ≥9 amino acids). Importantly, the identification of 6 out of 8 of the unique peptides derived from the MPs was further supported by parallel reaction monitoring, which confirmed the identification of 3 MPs from human placenta tissues (Q6NT89: TMF-regulated nuclear protein 1; A0A183: late cornified envelope protein 6A; and Q6UWQ7: insulin growth factor-like family member 2, mapped to chromosomes 1, 1, and 19, respectively). The three proteins ranged in length from 80 aa to 227 aa. The study not only establishes a feasible strategy for analyzing proteins with low molecular weights but also fills a small part of a large gap in the list of MPs. The data obtained in this study are available via ProteomeXchange (PXD014083) and PeptideAtlas (PASS01389).
KW - C18 SPE column
KW - LC-MS/MS
KW - low molecular weight proteins
KW - missing proteins
KW - placenta
UR - https://www.scopus.com/pages/publications/85074951433
U2 - 10.1021/acs.jproteome.9b00353
DO - 10.1021/acs.jproteome.9b00353
M3 - 文章
C2 - 31592669
AN - SCOPUS:85074951433
SN - 1535-3893
SP - 4180
EP - 4188
JO - Journal of Proteome Research
JF - Journal of Proteome Research
ER -