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Perturbations of Circulating miRNAs in Irritable Bowel Syndrome Detected Using a Multiplexed High-throughput Gene Expression Platform
Published on: November 30, 2016
Technology-enabled integration of single-cell transcriptomics and microbiome data identifies RNA-targetable
Boyang Ma1, Haiyan Hu2, Yu Lin1
1The First Affiliated Hospital, Qiqihar Medical University, Heilongjiang, 161000, China.
Abstract:
Although mechanism-to-intervention processes are becoming possible because to the convergence of single-cell technologies with RNA treatment methods, combined host-microbiome analysis with systematic target identification for colorectal adenoma is still fragmented. Here, we created a repeatable computational pipeline that combines MaAsLin2 for host-microbiome association modeling, QIIME2/DADA2 for microbiome processing, and Seurat/Harmony for single-cell analysis. Under strict statistical control (FDR < 0.05), three single-cell RNA sequencing datasets (GSE117875, GSE178341, and GSE144735; totaling 426,425 cells) were combined with parallel microbiome datasets (PRJNA397906, PRJNA541510, and PRJNA672605; 975 samples). In adenoma-associated microbiomes, we measured a 26.8 % decrease in Shannon diversity (4.21→3.08), with a notable enrichment of Fusobacterium nucleatum and a depletion of Faecalibacterium prausnitzii. Immune activation patterns, goblet cell malfunction (MUC2 2.4-fold drop), and stem cell expansion (LGR5 3.2-fold increase) were all identified by single-cell analysis. 847 significant host-microbiome interactions were found by integration analysis, and F. nucleatum showed a substantial correlation with markers of inflammatory signaling (NFKB1: β=0.64, FDR<0.001) and stem cell proliferation (LGR5: β=0.72, FDR<0.001). 25 RNA-targetable candidates were identified by systematic prioritizing, including mRNA restoration targets (MUC2, FOXP3) and ASO/siRNA suppression targets (NFKB1, IL1B). By converting host-microbiome interaction networks into systematic RNA therapeutic options, this technology framework creates a template for the translation of transcriptomics into therapeutics and offers a repeatable pipeline for the creation of precision interventions in colorectal disease.
Insights
A new computational pipeline integrates host-microbiome and single-cell RNA data for colorectal adenoma. It identifies key microbial players and host targets for developing novel RNA-based therapies.
Area of Science:
- Computational Biology
- Microbiome Research
- Single-cell RNA Sequencing
- Colorectal Cancer Research
Background:
- Integrating host-microbiome analysis with single-cell RNA sequencing for colorectal adenoma research remains challenging.
- Existing methods for target identification in this context are fragmented, hindering therapeutic development.
- Advancements in single-cell technologies and RNA therapeutics necessitate unified analytical frameworks.
Purpose of the Study:
- To develop a repeatable computational pipeline for combined host-microbiome and single-cell RNA analysis in colorectal adenoma.
- To identify specific host-microbiome interactions and potential RNA-targetable candidates for therapeutic intervention.
- To establish a framework for translating transcriptomic data into precision therapeutics for colorectal diseases.
Main Methods:
- A novel computational pipeline was created, integrating MaAsLin2, QIIME2/DADA2, and Seurat/Harmony.
- Three single-cell RNA sequencing datasets (426,425 cells) and three microbiome datasets (975 samples) were analyzed.
- Strict statistical control (FDR < 0.05) was applied to identify significant host-microbiome interactions and therapeutic targets.
Main Results:
- A significant decrease in gut microbiome diversity (Shannon index) was observed in adenoma-associated samples.
- Enrichment of Fusobacterium nucleatum and depletion of Faecalibacterium prausnitzii were noted.
- Single-cell analysis revealed immune activation, goblet cell dysfunction (MUC2 decrease), and stem cell expansion (LGR5 increase).
- 847 significant host-microbiome interactions were identified, with F. nucleatum strongly correlated with inflammation (NFKB1) and proliferation (LGR5).
- 25 RNA-targetable candidates were prioritized, including MUC2 and FOXP3 for mRNA restoration, and NFKB1 and IL1B for suppression.
Conclusions:
- The developed pipeline successfully integrates multi-omics data for comprehensive host-microbiome analysis in colorectal adenoma.
- This approach facilitates systematic identification of RNA-targetable candidates, offering potential for novel therapeutic strategies.
- The framework provides a repeatable model for translating complex biological interactions into actionable precision interventions for colorectal diseases.
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