Effect of methanol fixation on single-cell RNA sequencing data

Abstract

Single-cell RNA sequencing (scRNA-seq) has led to remarkable progress in our understanding of tissue heterogeneity in health and disease. Recently, the need for scRNA-seq sample fixation has emerged in many scenarios, such as when samples need long-term transportation, or when experiments need to be temporally synchronized. Methanol fixation is a simple and gentle method that has been routinely applied in scRNA-seq. Yet, concerns remain that fixation may result in biases which may change the RNA-seq outcome. We adapted an existing methanol fixation protocol and performed scRNA-seq on both live and methanol fixed cells. Analyses of the results show methanol fixation can faithfully preserve biological related signals, while the discrepancy caused by fixation is subtle and relevant to library construction methods. By grouping transcripts based on their lengths and GC content, we find that transcripts with different features are affected by fixation to different degrees in full-length sequencing data, while the effect is alleviated in Drop-seq result. Our deep analysis reveals the effects of methanol fixation on sample RNA integrity and elucidates the potential consequences of using fixation in various scRNA-seq experiment designs.

Isolating and Cryo-Preserving Pig Skin Cells for Single Cell RNA Sequencing Study

“…Methanol fixing works through dehydrating cells to preserve nucleic acids in a collapsed form at high concentrations. Upon rehydration, nucleic acids can be restored to the original form and harvested for library preparation 64,66 . Literature research on scRNA-Seq cell lines showed the methanol-fixing method resulted in high ambient RNA background and a lower gene expression correlation to the fresh un-preserved cells 34 .…”

Deciphering Organoids: High-Dimensional Analysis of Biomimetic Cultures

“…One of the key limitations of droplet-based methods is that they are designed for viable cells to achieve best data quality, meaning that they may not be suitable for applications where prompt processing of fresh samples is not always possible. However, it has been recently demonstrated that droplet-based methods can generate robust data from single nuclei [40,41] or methanol-fixed cells [42], making them applicable to challenging samples such as frozen tissues and organoids [43]. In addition, the development of the subnanolitre well-based method Seq-Well enables efficient single cell partitioning at lower sample input compared to droplet-based methods [44], making it especially suitable for organoid applications where the amount of starting material can be limited.…”

“…Application of single-cell technologies to organoids requires that high-quality single-cell suspensions can be generated from the cultures without compromising the underlying biology. This can be challenging for solid-phase 3D organoids but remediable if fixed samples can be used as the input of downstream single-cell experiments [42].Meanwhile, the latest developments in single-cell technologies highlight increased sample throughput [47,59], increased data modality [33,67], and improved compatibility with challenging samples [45][46][47]. Unfortunately, most single-cell technologies fail to couple the high-dimensional -omic analysis with robust functional assays, and we anticipate the development of such methods to be a primary challenge for the field going forward.…”

Glyoxal as alternative fixative for single cell RNA sequencing

“…Sample fixation has the potential to preserve the transcriptome and ease the scRNAseq experiment at the same time. However, despite the strongly increasing number of scRNAseq studies (Svensson et al, 2018), protocols with fixed single cells are only used to a limited extent (Karaiskos et al, 2017;Alles et al, 2017;Attar et al, 2018;Thomsen et al, 2015;Wang et al, 2020;Wohnhaas et al, 2019;Denisenko et al, 2020;Van Phan et al, 2020). Among the observed disadvantages are a reduced library complexity with lower number of detected transcripts (Alles et al, 2017;Attar et al, 2018;Van Phan et al, 2020) and higher level of ambient RNA (Wohnhaas et al, 2019).…”