Transcriptomic changes induced in one cell type by another mediate many biological processes in the brain and elsewhere; however, achieving artifact-free physical separation of cell types to study them is challenging and generally allows for analysis of only a single cell type. Researchers from the University of Edinburgh describe an approach using a co-culture of distinct cell types from different species that enables physical cell sorting to be replaced by in silico RNA sequencing (RNA-seq) read sorting, which is possible because of evolutionary divergence of messenger RNA (mRNA) sequences. As an exemplary experiment, the researchers describe the co-culture of purified neurons, astrocytes, and microglia from different species (12-14 d). They describe how to their Python tool, Sargasso, to separate the reads from conventional RNA-seq according to species and to eliminate any artifacts borne of imperfect genome annotation (10 h). They show how this procedure, which requires no special skills beyond those that might normally be expected of wet lab and bioinformatics researchers, enables the simultaneous transcriptomic profiling of different cell types, revealing the distinct influence of microglia on astrocytic and neuronal transcriptomes under inflammatory conditions.
Differential gene expression in microglia, astrocytes, and neurons in co-culture
a, For both the three-species co-culture (mouse neurons, human astrocytes, and rat microglia, right) and the mouse neuron–human astrocyte two-species co-culture (left), the number of reads unambiguously mapped to each species is shown, expressed as a percentage of the total number of unambiguously mapped reads of all species (n = 3 biological replicates, defined (here and throughout the article) as utilizing primary tissue from distinct animals). For the two-species co-culture samples, 64.1 ± 2.5 million reads per sample were unambiguously mapped, and for the three-species co-culture samples, 133.7 ± 12.5 million reads per sample were unambiguously mapped. Error bars represent the s.e.m. b, LPS-induced microglial gene expression. Species-specific read sorting identified rat (i.e., microglial) reads. Expression of genes (FPKM) in microglia ± LPS is plotted for the genes that expressed >0.5 FPKM, averaged over the conditions. Red crosses indicate the microglial genes whose expression level was modified by LPS presence >1.5-fold (DESeq2 Padj <0.05, n = 3 biological replicates, 1,075 genes induced, 1,416 genes repressed (14 of the initial 1,430 genes called as being significantly changed were discarded because of erroneous mapping)). Gray data points indicate the genes whose expression-level modification falls below these thresholds. c,d, Microglia-dependent transcriptional changes induced in astrocytes. Either three-species or two-species (lacking microglia) co-cultures were treated with LPS, and RNA-seq was performed. Species-specific read sorting identified human (i.e., astrocyte) reads. Expression of genes (FPKM) in the astrocytes in the presence of neurons only (two-species co-culture, x axis) is plotted against gene expression in astrocytes when microglia were also present (three-species co-culture, y axis). Genes significantly altered in their level of expression by the presence of microglia are marked by red crosses (DESeq2 Padj <0.05, n = 3). c, basal conditions; d, LPS-treated cultures (1,039 genes induced, 474 genes repressed (3 of the initial 477 genes called as being significantly changed were discarded because of erroneous mapping)). e,f, Microglia-dependent transcriptional changes induced in neurons. The same samples as in c,d were used, and species-specific read sorting was used to identify mouse (neuronal) reads. Genes significantly altered by the presence of microglia are marked by red crosses (DESeq2 Padj <0.05, n = 3). e, basal conditions; f, LPS-treated cultures (430 genes induced, 9 genes repressed). AstrHum, human astrocyte; astro–neuro–micro, astrocyte–neuron–microglia; MicRat, rat microglia; NeurMus, mouse neuron.
Availability – the Python tool, Sargasso is available at: https://github.com/statbio/Sargasso
Qiu J, Dando O, Baxter PS, Hasel P, Heron S, Simpson TI, Hardingham GE. (2018) Mixed-species RNA-seq for elucidation of non-cell-autonomous control of gene transcription. Nat Protoc [Epub ahead of print]. [abstract]