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A Method for Targeted 16S Sequencing of Human Milk Samples
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Global protein profiling of human milk using pre-enriched RNA-sequence libraries.

Julie Astono1, Asger Givskov Jørgensen2, Claus Bus3

  • 1Department of Food Science, Aarhus University, Agro Food Park 48, Aarhus N, Denmark.

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Summary
This summary is machine-generated.

Human milk protein profiles change over time and with maternal factors like BMI and parity. This study used APTASHAPE to map these changes, revealing key protein targets and their associations.

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Area of Science:

  • Biochemistry
  • Nutritional Science
  • Proteomics

Background:

  • Human milk composition is critical for infant health and long-term outcomes.
  • Understanding milk proteins is vital for addressing conditions like obesity.
  • Technical challenges have limited comprehensive human milk protein profiling.

Purpose of the Study:

  • To globally profile skimmed human milk protein composition using APTASHAPE.
  • To investigate associations between milk proteins and maternal/infant characteristics.
  • To identify specific milk proteins linked to maternal BMI and sampling time.

Main Methods:

  • Application of APTASHAPE, a high-throughput RNA-based profiling method.
  • Analysis of 520 human milk samples across 3 days to 3 months postpartum.
  • Validation of findings using ordinary least squares regression and mass spectrometry.

Main Results:

  • Identified RNA sequence profiles correlating with sampling time, maternal BMI, and parity.
  • Confirmed associations in an independent test cohort.
  • Identified C4b-binding protein and tenascin C as candidate targets linked to maternal BMI and sampling time.

Conclusions:

  • Human milk protein composition is dynamic, primarily influenced by sampling time.
  • Maternal BMI and parity contribute to more subtle variations in milk protein profiles.
  • APTASHAPE provides a powerful tool for high-throughput human milk proteomic analysis.