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不同孕周人类新生儿胎粪中宿主来源的蛋白质谱。

Host-derived protein profiles of human neonatal meconium across gestational ages.

作者信息

Shitara Yoshihiko, Konno Ryo, Yoshihara Masahito, Kashima Kohei, Ito Atsushi, Mukai Takeo, Kimoto Goh, Kakiuchi Satsuki, Ishikawa Masaki, Kakihara Tomo, Nagamatsu Takeshi, Takahashi Naoto, Fujishiro Jun, Kawakami Eiryo, Ohara Osamu, Kawashima Yusuke, Watanabe Eiichiro

机构信息

Department of Pediatrics, Faculty of Medicine, The University of Tokyo, Tokyo, Japan.

Department of Applied Genomics, Kazusa DNA Research Institute, Chiba, Japan.

出版信息

Nat Commun. 2024 Jul 17;15(1):5543. doi: 10.1038/s41467-024-49805-w.

Abstract

Meconium, a non-invasive biomaterial reflecting prenatal substance accumulation, could provide valuable insights into neonatal health. However, the comprehensive protein profile of meconium across gestational ages remains unclear. Here, we conducted an extensive proteomic analysis of first meconium from 259 newborns across varied gestational ages to delineate protein composition and elucidate its relevance to neonatal diseases. The first meconium samples were collected, with the majority obtained before feeding, and the mean time for the first meconium passage from the anus was 11.9 ± 9.47 h. Our analysis revealed 5370 host-derived meconium proteins, which varied depending on sex and gestational age. Specifically, meconium from preterm infants exhibited elevated concentrations of proteins associated with the extracellular matrix. Additionally, the protein profiles of meconium also exhibited unique variations depending on both specific diseases, including gastrointestinal diseases, congenital heart diseases, and maternal conditions. Furthermore, we developed a machine learning model to predict gestational ages using meconium proteins. Our model suggests that newborns with gastrointestinal diseases and congenital heart diseases may have immature gastrointestinal systems. These findings highlight the intricate relationship between clinical parameters and meconium protein composition, offering potential for a novel approach to assess neonatal gastrointestinal health.

摘要

胎粪是一种反映产前物质积累的非侵入性生物材料,可为新生儿健康提供有价值的见解。然而,不同胎龄胎粪的完整蛋白质谱仍不清楚。在此,我们对259名不同胎龄新生儿的首次胎粪进行了广泛的蛋白质组学分析,以确定蛋白质组成并阐明其与新生儿疾病的相关性。收集了首次胎粪样本,大多数样本在喂食前获得,首次胎粪从肛门排出的平均时间为11.9±9.47小时。我们的分析揭示了5370种宿主来源的胎粪蛋白质,其因性别和胎龄而异。具体而言,早产儿胎粪中与细胞外基质相关的蛋白质浓度升高。此外,胎粪的蛋白质谱还因特定疾病(包括胃肠道疾病、先天性心脏病和母亲状况)而呈现独特变化。此外,我们开发了一种机器学习模型,利用胎粪蛋白质预测胎龄。我们的模型表明,患有胃肠道疾病和先天性心脏病的新生儿可能具有不成熟的胃肠系统。这些发现突出了临床参数与胎粪蛋白质组成之间的复杂关系,为评估新生儿胃肠道健康提供了一种新方法的潜力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cb4c/11255260/7991913030b4/41467_2024_49805_Fig1_HTML.jpg

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