Comprehending the molecular structure of tissue and gaining insights into cellular function in a morphological sense is possible with spatial transcriptomics.
Transcriptome research helps one to characterise the transcripts contained in biological tissues in great detail. Traditional transcriptomes are created by sequencing RNA samples extracted from homogenised biopsies, but this method produces averaged transcripts and loses spatial information. New spatial transcriptome technologies have been implemented to address these issues.
Laser capture microdissection (LCM)-based RNA-seq slides, tissue-positional transcript barcoding, and single-cell RNA-seq with computer modelling are examples of these techniques. The spatial transcriptome analysis will reveal the molecular organisation of tissues and organs and how their dysfunction is linked to function and disease.
Serial microtomy sequencing analysis is a simple way to get two-dimensional (2D) or three-dimensional (3D) transcriptional maps in complex tissues. However, researchers must acquire high-resolution tissue images and collect tissue microdissection samples to analyse a large tissue region.
To connect the images and gene expression profiles, RNA degradation and tissue morphological changes should be avoided. RNA degradation would cause coverage bias in transcript sequences, causing problems with gene expression estimation. As a result, for stable and repeatable spatial transcriptomics, the tissue preparation process should be optimised.
The researchers have so far established a semi-automated method for collecting multiple tissue microdissections. This device can semi-automatically take a series of tissue microdissection samples in a short period of time (5 sec/sampling cycle) by punching tissue slices using a fine stainless-steel hollow needle with a diameter of 100 m.
Cross-contamination in publications is extremely rare, as shown by the serially collected samples and collection buffer. The researchers demonstrated a spatial transcriptome study of disc-shaped areas in mouse brain tissue at 100 m-diameter resolution and 20 m in height by combining this technique with RNA-seq. We can easily examine the relation between anatomical regions and specific gene expressions using this method because it allows us to collect specific tissue areas on demand.
The researchers present a tissue processing method for microtissue RNA-seq that suppresses RNA degradation in fresh-frozen tissue specimens, based on our tissue microdissection collecting system. First, they looked at how RNA degradation and inadequate tissue lysis affect sequence read proportions, gene numbers detected, and inter-sample reproducibility in RNA-seq analysis.
Then, the researchers demonstrated comparative sensitivity and reproducibility in gene expression analysis from microtissues to bulk RNA-seq analysis by integrating the proposed tissue fixation and RNA purification method with the tissue microdissection system and Smart-seq2. The proposed approach was then used to illustrate tissue-specific gene expression in mouse brain tissues. The results of spatial transcriptomics analysis indicated that our microtissue RNA-seq procedure could be applied for analysing various tissue samples.
The researchers tested multiple tissue fixation situations in mouse liver tissue to enhance tissue fixation conditions for reproducible RNA-seq from fresh-frozen microtissues. When compared to other organ tissues, the liver tissue degrades quickly at room temperature.
As a result, we used the liver as a model in the research. Freshly frozen liver tissue was serially and dehydrated using one of two methods: ethanol fixation or air-dry fixation. After slicing, the electropherograms of total RNA extracted from tissue sections revealed substantial degradation in the liver tissue section incubated for 30 minutes at room temperature.
In the no-fixation study, 18 S and 28 S ribosomal RNA peaks were moved to a smaller scale. Compared to the control sample, the liver tissue portion fixed with ethanol and air-dried showed no apparent changes in electropherograms. The RNA integrity number equivalent (RINe) remained high (8.4 0.11 and 7.9 0.16, respectively) throughout the study.
These findings suggested that RNase would degrade RNA in tissue during incubation, but dehydration fixation successfully prevented RNA degradation by inactivating RNase and stabilising RNAs in the tissue. The quality of RNA-seq data obtained from 500 pg of total RNA extracted from each sample was then compared.
Overall, the findings revealed that RNA degradation results in non-reproducible data that does not constitute the tissue’s original transcriptome. The sensitivity and reproducibility of the transcriptome study were significantly improved by dehydration-based fixation of frozen tissue slices. Ethanol fixation, in particular, showed a high degree of consistency with the control results. Chemical tissue fixation, such as ethanol fixation, can cause fluorescent molecules to degrade, resulting in lower fluorescence intensities. As a result, ethanol fixation is not recommended for samples that need fluorescent cell labelling for anatomical visualisation (Yamazaki, et al., 2020).
If you are looking for or an RNA or DNA Extraction Kit, contact MBP INC.
Yamazaki,, M., Hosokawa, M., & Arikawa, K. (2020, April 27). Effective microtissue RNA extraction coupled with Smart-seq2 for reproducible and robust spatial transcriptome analysis. Scientific Reports, 10(7083), 4. https://www.nature.com/articles/s41598-020-63495-6