HyeongJin Yun Scientific Essay

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Necessity of RNA Sequencing in Human BBB Models
 and Drug Delivery Research
20191193 HyeongJin Yun

Introduction

I have always been deeply interested in diseases caused by brain dysfunction, such as brain cancer, depression, and dementia. This interest led me to pursue research and development in the field of drug delivery to the brain, particularly through the blood-brain barrier (BBB). I am currently developing a human blood-brain barrier (BBB) model and conducting extensive research to understand how carriers penetrate the BBB for drug delivery. My work primarily involves building basic cell culture techniques and creating an in vitro BBB model. The carrier samples used in this experiment are provided by our collaborative research partner. We plan and execute further experimental procedures by determining the permeability of these carriers across the BBB.

Currently, I have completed the process of determining whether lipid nanoparticles (LNPs) can pass through the BBB. Now, I have shifted my focus to exploring the mechanisms by which these nanoparticles pass through the barrier. I became particularly interested in this area because I believe RNA-sequencing, which was mentioned in the Genomics course, would help me explore these mechanisms further. RNA-sequencing can provide detailed insights into the gene expression changes and molecular pathways activated during nanoparticle transport across the BBB, thereby elucidating the specific biological processes and interactions involved.



Blood-Brain Barrier and Lipid Nanoparticles
The human blood-brain barrier (BBB) is a unique and selective barrier that regulates the transport of substances from Blood to the brain. It plays an important role in maintaining the neurons and glia function. BBB is composed of Brain microvascular endothermic cells (BMVECs), Astrocytes, Pericytes, and ECM (1,2). BMVECs have a much lower degree of endocytosis/transcytosis activity than peripheral endothelium contributing to the characteristics of BBB as a barrier (3).
 Lipid nanoparticles (LNPs) are widely used in the field of drug delivery. LNPs are primarily composed of cholesterol and lipids and can encapsulate DNA, RNA, or drugs. Additionally, ligands or antibodies can be attached to the surface to aid in targeting (4).
My research is conducting a study on whether LNPs using a new fabrication method called Liposome Under Cryo-Assembly (Luca) can pass through the human BBB model. The identification of LNP samples that penetrate well is finished and the mechanism study process is in the process.

Overview of RNA sequencing technology
Principles of RNA Sequencing
RNA sequencing (RNA-seq) is a high-throughput sequencing technology used to determine the nucleotide sequence of RNA molecules and quantify specific RNA species within a population. The process of RNA sequencing includes the following steps (5):

  1. RNA Extraction: Extracting RNA from biological samples such as cells or tissues.

 

  1. cDNA Synthesis: Converting the extracted RNA into complementary DNA (cDNA) using reverse transcriptase.

 

  1. Library Preparation: Fragmenting the cDNA, attaching adapters, and amplifying the cDNA fragments through PCR.

 

  1. Sequencing: Sequencing the prepared library using platforms such as Illumina or Nanopore.

 

  1. Data Analysis: Aligning the generated sequences to a reference genome and quantifying gene expression levels​.


Methods for Gene Expression Analysis Using RNA Sequencing
The analysis of gene expression using RNA sequencing involves several steps:

 

  1. Data Quality Control: Assessing the quality of sequencing data and removing low-quality reads.

 

  1. Data Alignment: Aligning the reads to a reference genome to determine the location of each read.

 

  1. Gene Expression Quantification: Calculating the expression levels of genes, typically represented as RPKM, FPKM, or TPM values.

 

  1. Differential Expression Analysis: Identifying differentially expressed genes between specific conditions to understand changes in gene expression due to factors such as inflammation, stress, or drug treatment​



Necessity of RNA Sequencing in BBB Models
Through fluorescence image analysis, I found out that LNPs migrate to the transcytosis pathway. In addition, I checked the difference in transmittance by performing several transcytosis inhibitor treatments.
Through RNA sequencing, I would like to check whether the permeability has changed due to changes in the genetic level of the cells that actually make up BBB.

Future Plan
Taking the Genomics course, I realized that conducting research at various gene levels is essential to achieving high-level research outcomes. My goal is to proceed with the RNA sequencing mentioned above to uncover the detailed mechanisms of nanoparticle transport that have not yet been identified. To facilitate this, I am eager to collaborate actively with the bioinformatics labs at UNIST for detailed RNA sequencing analysis. After discovering the mechanisms, I plan to treat the surface of the nanoparticles with Aptamers to observe changes in permeability and ultimately encapsulate actual drugs for targeted delivery.



References
(1) Cecchelli, Romeo, et al., Modelling of the blood–brain barrier in drug discovery and development., 2007, Nature Reviews Drug Discovery. vol. 6, no. 8, pp. 650–661,.

(2) Park, Tae-Eun, et al., Hypoxia-enhanced blood-brain barrier chip recapitulates human barrier function and shuttling of drugs and antibodies., 2019, Nature Communications, vol. 10, no. 1, 13

(3) Abbott, N. Joan, Lars Rönnbäck, and Elisabeth Hansson., Astrocyte–Endothelial Interactions at the Blood–Brain Barrier., 2006, Nature Reviews Neuroscience 7, no. 1: 41–53.

(4) Mehta, M., Bui, T. A., Yang, X., Aksoy, Y., Goldys, E. M., & Deng, W., Lipid-based nanoparticles for drug/gene delivery: An overview of the production techniques and difficulties encountered in their industrial development., 2023, ACS Materials Au, 3(6), 600–619.

(5) Deshpande, Dhrithi, et al., RNA-seq data science: From RAW data to effective interpretation.,2023, Frontiers in Genetics, vol. 14,