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Expanding the DNA-probe toolbox for molecular profiling of tissues and their microbiomes

Nguyen, Pham Xuan Huy (2024) BINP52 20232
Degree Projects in Bioinformatics
Abstract
Spatial transcriptomics, a powerful technique that merges sequencing and spatial data, offers unprecedented resolution for studying gene expression within tissues. This study focuses on developing a pipeline to design probes for Multiplexed Error-Robust Fluorescence In Situ Hybridisation (MERFISH) experiments to investigate the spatial distribution of the lung microbiome. Metagenomic data analysis is used to identify microbes present in lung samples using Kraken2 and Bracken. This information guides the construction of a probe table for obtaining the probes using PaintSHOP, enabling MERFISH detection of these specific microbes within human lung cells. This approach can reveal novel mechanisms underlying microbe-host interactions and their... (More)
Spatial transcriptomics, a powerful technique that merges sequencing and spatial data, offers unprecedented resolution for studying gene expression within tissues. This study focuses on developing a pipeline to design probes for Multiplexed Error-Robust Fluorescence In Situ Hybridisation (MERFISH) experiments to investigate the spatial distribution of the lung microbiome. Metagenomic data analysis is used to identify microbes present in lung samples using Kraken2 and Bracken. This information guides the construction of a probe table for obtaining the probes using PaintSHOP, enabling MERFISH detection of these specific microbes within human lung cells. This approach can reveal novel mechanisms underlying microbe-host interactions and their impact on respiratory health. Furthermore, given the corresponding metagenomic data, this research proposes a broader pipeline for designing oligo probes for MERFISH detection of microbes in any particular organ. (Less)
Popular Abstract
On how to map lungs’ microbes

Sequencing is like looking at the building instructions of living things. Single-cell sequencing shows us the details of each part, while spatial transcriptomics reveals the genetic differences based on location in the body. Single-molecule fluorescence in situ hybridisation (smFISH) is a technique to localise RNA and DNA within a cell. It paved the way for modern techniques like MERFISH, which can show many different parts simultaneously and self-correct or detect mistakes. For my thesis, I am designing an encoding probe library specifically for MERFISH (Multiplexed Error-Robust Fluorescence in situ Hybridisation) experiments to investigate the microbes in the lungs. These probes will allow us to map where... (More)
On how to map lungs’ microbes

Sequencing is like looking at the building instructions of living things. Single-cell sequencing shows us the details of each part, while spatial transcriptomics reveals the genetic differences based on location in the body. Single-molecule fluorescence in situ hybridisation (smFISH) is a technique to localise RNA and DNA within a cell. It paved the way for modern techniques like MERFISH, which can show many different parts simultaneously and self-correct or detect mistakes. For my thesis, I am designing an encoding probe library specifically for MERFISH (Multiplexed Error-Robust Fluorescence in situ Hybridisation) experiments to investigate the microbes in the lungs. These probes will allow us to map where different microorganisms are located within the lungs in great detail. Just like a city has various buildings and areas, our lungs have a variety of microorganisms called the lung microbiome. Using MERFISH with these encoding probes, scientists can create detailed maps showing where these microorganisms are located and understand their interactions with lung tissues, providing valuable insights into lung health and diseases.

To design the encoding probe for the MERFISH experiment, I first classify the microbes from metagenomic data of lung tissue samples. Metagenomic data provides a list of all the different microbes present in the lung microbiome. With this list, I construct encoding probes that bind to these microbes. Each encoding probe targets a unique RNA sequence specific to a microorganism through hybridisation. Hybridisation is like matching puzzle pieces. The encoding probes designed resemble a puzzle piece that fits perfectly with a specific RNA sequence from a microorganism. When the encoding probe finds its matching RNA sequence, it binds. Additionally, the encoding probe contains regions called readout sequences where several puzzle pieces (readout probes) carrying fluorescent signals can bind through another hybridisation step. These signals can be removed, and another round of hybridisation can be performed, repeating the process.

The MERFISH experiment captures this sequence of signals to form a binary barcode for each microbe species. Each microbe species is assigned a unique barcode. During each hybridisation round, fluorescent signals can either bind to the probe (emitting a signal), represented with a "1", or not bind (no signal), represented with a “0”. By comparing these barcodes, we can detect the location of each microbe within the lung tissue. This method allows us to create detailed maps showing the spatial distribution of different microorganisms in the lung microbiome. Those encoding probes are unique to their corresponding species to limit the off-target binding. The encoding probes also have primers for the amplification process to achieve higher concentrations of probes.

This research results in an encoding probes table for 91 classified microbes found in the lungs. Furthermore, I also built a general pipeline for designing encoding probes for MERFISH detection of microbes in any particular organ. This probe design pipeline is a fundamental step in designing every MERFISH experiment aiming to investigate microbes.

Master’s Degree Project in Bioinformatics 60 credits 2024
Department of Biology, Lund University

Advisor: Nils Norlin
Department of Experimental Medical Science (Less)
Please use this url to cite or link to this publication:
author
Nguyen, Pham Xuan Huy
supervisor
organization
course
BINP52 20232
year
type
H2 - Master's Degree (Two Years)
subject
language
English
id
9176785
date added to LUP
2024-10-18 11:57:10
date last changed
2024-10-18 11:57:10
@misc{9176785,
  abstract     = {{Spatial transcriptomics, a powerful technique that merges sequencing and spatial data, offers unprecedented resolution for studying gene expression within tissues. This study focuses on developing a pipeline to design probes for Multiplexed Error-Robust Fluorescence In Situ Hybridisation (MERFISH) experiments to investigate the spatial distribution of the lung microbiome. Metagenomic data analysis is used to identify microbes present in lung samples using Kraken2 and Bracken. This information guides the construction of a probe table for obtaining the probes using PaintSHOP, enabling MERFISH detection of these specific microbes within human lung cells. This approach can reveal novel mechanisms underlying microbe-host interactions and their impact on respiratory health. Furthermore, given the corresponding metagenomic data, this research proposes a broader pipeline for designing oligo probes for MERFISH detection of microbes in any particular organ.}},
  author       = {{Nguyen, Pham Xuan Huy}},
  language     = {{eng}},
  note         = {{Student Paper}},
  title        = {{Expanding the DNA-probe toolbox for molecular profiling of tissues and their microbiomes}},
  year         = {{2024}},
}