The distribution of cell-penetrating peptides on polymeric nanoparticles prepared using microfluidics and elucidated with small angle X-ray scattering

Research output: Contribution to journalJournal articlepeer-review

Hypothesis: The distribution of three cell-penetrating peptides (CPPs) with different architectures (short, long linear and branched) on poly(lactic-co-glycolic) acid (PLGA) nanoparticles depends on the conjugation approach. Here, we explore the utilization of a zero-length crosslinking reaction for the covalent attachment of CPPs to PLGA nanoparticles and the translation of the reaction into a microfluidic platform. Experiments: A microfluidic device with a staggered herringbone mixer was used for the formulation of CPP-tagged PLGA nanoparticles. CPP-tagged PLGA nanoparticles were labeled with gold nanoparticles (AuNPs) and transmission electron microscopy (TEM) and small angle X-ray scattering (SAXS) were used to elucidate the distribution of CPPs. Findings: The SAXS scattering profiles for the CPP-tagged PLGA nanoparticles prepared with the in situ microfluidics conjugation approach indicated a distribution of the Au-labeled CPPs throughout the PLGA nanoparticles. For the post-microfluidics conjugation approach, the SAXS scattering profiles did not show the feature of the Au-labeled CPPs distributed throughout the PLGA nanoparticles and an arrangement of the Au-labeled CPP on the surface was support by TEM micrographs. The distribution of the CPPs was highly dependent on the conjugation approach and was not influenced by the architecture of the CPPs. The results provided insight for the rational design of CPP-tagged PLGA nanoparticles using microfluidics.

Original languageEnglish
JournalJournal of Colloid and Interface Science
Volume555
Pages (from-to)438-448
Number of pages11
ISSN0021-9797
DOIs
Publication statusPublished - 1 Nov 2019

    Research areas

  • Branched cell-penetrating peptide, Microfluidics, PLGA nanoparticles, Small angle X-ray scattering, TAT, Transmission electron microscopy

ID: 239817004