Laser Capture Microdissection-Based RNA Microsequencing Reveals Optic Nerve Crush-Related Early mRNA Alterations in Retinal Ganglion Cell Layer

Abstract

Purpose: To establish a method of laser capture microdissection (LCM) and RNA microsequencing for exploring optic nerve crush (ONC)-related early mRNA alterations in retinal ganglion cell (RGC) layer.

Methods: An LCM protocol was developed using retinal tissue sections to obtain high-quality RNA for microsequencing. Cells in the RGC layer were collected by laser pressure catapulting (LPC) using a PALM Zeiss UV LCM system. The effect of section thickness and slide type on tissue capture success and RNA yield and the integrity after LCM were evaluated. The optimal LCM protocol was used to explore ONC-related early mRNA alterations in the RGC layer. Candidate genes were validated by real-time polymerase chain reaction of the RGC layer tissue dissected by "cut and LPC" using the same LCM system.

Results: We successfully established an optimal LCM protocol using 30-µm-thick retinal tissue sections mounted on glass slides and laser pressure catapulting (LPC) to collect cells in the RGC layer and to obtain high-quality RNA for microsequencing. On the basis of our protocol, we identified 8744 differentially expressed genes that were involved in ONC-related early mRNA alterations in the RGC layer. Candidate genes included Atf3, Lgals3, LOC102551701, Plaur, Tmem140, and Maml1.

Conclusions: The LCM-based single-cell RNA sequencing allowed a new sight into the early mRNA changes of RGCs highlighting new molecules associated to ONC.

Translational relevance: This technique will be helpful for more accurate transcriptome analysis of clinical pathological samples of ophthalmology and provide important reference for the discovery of new pathological diagnosis indicators and drug development targets.

Keywords: laser capture microdissection; microsequencing; optic nerve crush; retinal ganglion cell layer.

Figure 1.

Workflow of laser capture microdissection-based sequencing. (A) Workflow of optimizing the LCM protocol. (B) Workflow of the study of early mRNA alterations in RGC layer after ONC. (C) LPC of cells in RGC layer for mRNA sequencing (scale bar: 50 µm). (D) “Cut and LPC” method for RGC layer for RT-PCR (scale bar: 50 µm)

Figure 2.

Effect of section thickness and slide type on cell capture success, RNA yield, and integrity after LCM. (A) Effect of section thickness and slide type on cell capture success. Both 20-µm–thick and 30-µm–thick sections mounted on PEN membrane-coated slides led to poor capture success (16% vs. 20%, P > 0.05). Sections mounted on glass slides led to good capture success (both 100%). (B) Effect of section thickness on RNA yield. Twenty-micrometer–thick sections showed a yield of 1.52 ± 0.25 ng/µL, and 30-µm–thick sections showed a yield of 2.29 ± 0.31 ng/µL (P < 0.05).

Figure 3.

Analysis of scRNA-seq results. (A) Volcano plot of DEGs between ONC and control samples. Genes with a fold change ≥ 2 and a q value < 0.05 were chosen. A total of 8744 DEGs were included, with 4411 upregulated genes and 4333 downregulated genes. (B) Biomarkers of RGC layer cells. Both RGC markers and glia markers were identified in our sequencing data.

Figure 4.

Verification of candidate genes. (A) RT-PCR of DEGs with a |log2Ratio|≥10. Atf3, Lgals3, LOC102551701, Plaur and Tmem140 levels were found to be upregulated, whereas Maml1 mRNA was found to be decreased at one, two, and three days after crush in the ONC eyes compared to the control eyes. (B) Immunohistochemistry of ATF3 three days after crush. In the control retina, there was low Atf3 immunoreactivity, while in the ONC retina, Atf3 expressed at a high level (green: ATF3; blue: DAPI; scale bar: 200 µm). (C) Immunohistochemistry of Maml1 three days after crush. In control retinas, there was high Maml1 immunoreactivity, while in ONC retinas, Maml1 immunoreactivity was low in the RGC layer (red: Maml1; blue: DAPI; scale bar: 200 µm).