ACME dissociation: a versatile cell fixation-dissociation method for single-cell transcriptomics

Helena García-Castro, Nathan J Kenny, Patricia Álvarez-Campos, Vincent Mason, Anna Schönauer, Victoria A. Sleight, Jakke Neiro, Aziz Aboobaker, Jon Permanyer, Marta Iglesias, Manuel Irimia, Arnau Sebé-Pedrós, Jordi Solana

Preprint posted on 10 June 2020

Article now published in Genome Biology at

Rediscovering a century-old technique to solve a modern single-cell biology problem: the case of ACME

Selected by Irepan Salvador-Martinez


In recent years, single-cell RNA seq (scRNAseq) studies are reshaping biology. The possibility to dissociate a tissue or even a whole animal and knowing the genes each cell was expressing has not only allowed the characterisation of known cell types, but also the discovery of new cell types.

Although scRNAseq technologies are under continuous improvement, a potential bottleneck for any scRNAseq study is the dissociation/fixation step. Current dissociation protocols use enzymatic or mechanical approaches that put live cells under stress for hours, with potential undesirable effects. A method that could fix and dissociate cells at once would therefore be highly beneficial for the single-cell community.


About the preprint

Garcia-Castro et al. tried to solve this problem by adapting a more than a century-old cell dissociation technique, originally called “maceration”. The maceration technique was first used on 1890, but continued to be used throughout the 20th century to dissociate cells from different soft-bodied animals such as cnidarians or planarians.

The adapted technique, named ACME by the authors after ACetic-MEthanol (referring to the solution used for the maceration, composed of acetic acid, methanol and glycerol), fixes single cells in suspension maintaining high integrity RNAs and dissociates them at the same time. Importantly, they showed that ACME-dissociated cells can be cryo-preserved at different check points during the process whilst retaining high integrity RNAs. This could open many opportunities, for example of doing cell dissociation of samples in the field and all downstream process in the lab.

Using the ACME protocol the authors managed to dissociate several animals, including zebrafish embryos, fruitfly larvae, spider embryos,annelid adults, snail larvae, and juvenile sea anemones. In these animals ACME cannot dissolve or penetrate hard parts like chorions, vitelline membranes, cuticles or shells, but applying a mechanical disruption and hard-part removal step was sufficient to extract their cells. In order to prove the usefulness of their technique for doing scRNAseq, the authors used it to sequence cells of 2 planarian species by combining ACME with SPLiT-seq (Rosenberg et al, 2018), a single-cell RNA-seq method that labels the cellular origin of RNA through combinatorial barcoding (Figure 1).

Figure 1. Experimental workflow. ACME dissociated and FACS-sorted cells from two planarian species were processed after two freezing steps. Barcodes for SPLiT-seq were produced after 4 rounds of barcoding (from Figure 3A in the preprint made available under a CC-BY-NC-ND 4.0 license).


The authors dissociated the cells of two planarian species, Schmidtea mediterranea and Dugesia japonica, and performed a species-mixing experiment (Figure 1) using SPLiT-seq. Planarians are soft-bodied flatworms (platyhelminthes) with remarkable regeneration capabilities: if you chop a planarian in three pieces, each piece will regenerate into a full worm in a couple of weeks.

In this single species-mixing experiment, the authors obtained ~14K and ~19K cells for D. japonica and for S. mediterranea, respectively. In order to analyse cell type composition, cells were clustered into cell types for each species. In the case of S. mediterranea (Figure 2) cell type composition was remarkably similar to a published cell atlas (Plass et al, 2018). For D. japonica, these results represent the first cell type atlas for this species. Using the homologues of S. mediterranea the authors could annotate the different cell types of D. japonica, finding that cell type proportions were similar in both species. Importantly, by producing a cell atlas of a second planarian (separated by ~85 my of evolution) the authors open the possibility of studying planarian cell type evolution.

Figure 2. (Top) UMAP visualization of 19,741 S. mediterranea cells (left) and 14,086 D. japonicacells (right), coloured by cluster identity (Bottom) Comparison of cell proportions for S. mediterranea, in comparison with a previous cell type atlas (Plass et al.) and D. japonica. (from Figure 3E-G in the preprint made available under a CC-BY-NC-ND 4.0 license).


Why I chose this preprint

I liked that the authors re-discovered an old technique for single-cell dissociation to solve a modern problem in single cell biology. I also liked the fact that as a proof of principle they created a new cell atlas for the planarian D. japonica, which will prove useful for studying cell type evolution in this group of animals.


Questions to the authors

Q1: Would ACME be suitable to fix/dissociate human cells from tissue biopsies? If so, I think it could be useful for collecting samples for biomedic studies (e.g. cancer).
Q2: Apart from SPLiT-Seq, which other cell barcoding techniques would be compatible with ACME?



Rosenberg AB, Roco CM, Muscat RA, et al. Single-cell profiling of the developing mouse brain and spinal cord with split-pool barcoding. Science 2018;360(6385):176-182.

Plass, M., et al., Cell type atlas and lineage tree of a whole complex animal by single-cell transcriptomics. Science, 2018. 360(6391).


Posted on: 6 July 2020


Read preprint (1 votes)

Author's response

Jordi Solana shared

Q1: Would ACME be suitable to fix/dissociate human cells from tissue biopsies? If so, I think it could be useful for collecting samples for biomedic studies (e.g. cancer).

A1: We believe that ACME will be suitable for a whole range of organisms including humans. However, we do not believe it is a universal one-fits-all solution, but should instead be used as a starting point for optimisation when applied to novel samples. Human tissue would be quite different to small animals, and could require different conditions.
Since we published our bioRxiv preprint we have had a number of comments telling us that it has worked in this or that organism, but also some saying it did not work in specific cases. We believe that getting the protocol to work on those will need optimisation. Our advice if ACME does not work at first: add mechanical dissociation, modify acid and methanol concentration, perhaps even eliminate the methanol, or assay other –perhaps stronger – acids.

Q2: Apart from SPLiT-Seq, which other cell barcoding techniques would be compatible with ACME?

A2: Combinatorial barcoding single cell transcriptomic methods like SPLiT-seq start with fixed cells, typically with formaldehyde. We believe that ACME will improve these methods, as it provides very good RNA integrity, which is challenging to obtain with formaldehyde. Thus, we think SPLiT-seq is ideal, because it also has a lot of potential in cell throughput, is scalable, cheap and does not require specialised equipment such a microfluidic devices. That being said, we cannot think of a reason why ACME dissociated cells would not work in nanodroplet-based methods such as Drop-seq and 10X Genomics. And we know some people are already trying.

Personal comments:
The method, then called maceration, was used throughout the 70’s and 80’s by Jaume Baguñà and Rafael Romero at the University of Barcelona, at that time his PhD student. They used it to observe cells at the microscope, classify cell types, and quantify them. With this, they studied the allometry of cell type abundance in planarians and described how cell types change in abundance across regeneration stages. I later performed my PhD studies in the same department of the University of Barcelona, supervised by Rafael Romero, and I was aware of the method. When the single cell revolution started I thought that this could be a good method, as it avoids the cell stress inherent to live enzymatic dissociations. When I started at Oxford Brookes University I thought it was time to see if it worked for single-cell biology.
The team has been key to develop this. Helena was perseverant and led the optimisation effort, assaying many conditions until we found the right ones. Vince, our lab technician, assayed many as well, and generated part of the data that got into the manuscript. Nathan developed and optimised the pipeline to analyse the data and was the key computational scientist. Aziz and Jakke helped in annotating the genomes of the two planarians. Anna optimised ACME dissociation in the second organism, the spider, and Patri the third, the annelid. We also worked with friends and collaborators such as Vicky, Jon, Marta, Manu and Arnau to optimise the other organisms featured. I think it was a great team effort!

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