Human iPSC-derived mature microglia retain their identity and functionally integrate in the chimeric mouse brain

Microglia, the brain-resident macrophages, exhibit highly dynamic functions in neurodevelopment and neurodegeneration. Human microglia possess unique features as compared to mouse microglia, but our understanding of human microglial functions is largely limited by an inability to obtain human microglia under homeostatic states. Here, we develop a human pluripotent stem cell (hPSC)-based microglial chimeric mouse brain model by transplanting hPSC-derived primitive macrophage progenitors into neonatal mouse brains. Single-cell RNA-sequencing of the microglial chimeric mouse brains reveals that xenografted hPSC-derived microglia largely retain human microglial identity, as they exhibit signature gene expression patterns consistent with physiological human microglia and recapitulate heterogeneity of adult human microglia. Importantly, the engrafted hPSC-derived microglia exhibit dynamic response to cuprizone-induced demyelination and species-specific transcriptomic differences in the expression of neurological disease-risk genes in microglia. This model will serve as a tool to study the role of human microglia in brain development and degeneration.


Statistics
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Data analysis
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Peng Jiang
Feb 23, 2020 No custom code was used in this study. Single cell RNA Sequencing reads were aligned with pooled mouse (mm10) and human (hg19) reference genomes and the barcodes were interpreted using Cellranger software (10X Genomics, v. 3.0.0). The resulting matrices of gene counts x barcodes were coded by individual sample identifier and loaded into Seurat (v. 2.3.4) software 88-90 in R (version 3.6.1)/ Bioconductor 91. For analysis of human microglial sub-clusters, extracted human sample/barcode were restricted to human gene symbol results and re-analyzed with Seurat. Gene ontology analysis used the g:Profiler 95 website (version e98_eg45_p14_ce5b097) (https:// biit.cs.ut.ee/gprofiler/gost). For bulk RNA-sequencing analysis, total RNA was prepared with RNAeasy kit (QIAGEN) and libraries were constructed using 600 ng of total RNA from each sample and the TruSeqV2 kit from Illumina (Illumina, San Diego, CA) following manufacturers suggested protocol. The libraries were subjected to 75 bp paired read sequencing using a NextSeq500 Illumina sequencer to generate approximately 30 to 36 million paired-reads per sample. Fastq files were generated using the Bc12Fastq software, version 1.8.4. The genome sequence was then indexed using the rsem-prepare-reference command. Each fastq file was trimmed and checked for quality with fastp (v. 0.12.2), and then aligned to the UCSC hg38 human genome using Hisat2 (v.2.1.0). Transcript counts were extracted using the featureCounts function of the Rsubread package. Confocal images were acquired using a LSM 710 Confocal microscope (Zeiss) and Zeiss Airyscan super-resolution microscope at 63X with 0.2 mm z-steps. Large scale images were obtained by confocal tile scan and automatically stitched using 10% overlap between tiles by Zen 2011 software (black edition, Zeiss).3D reconstructive images were processed by Zen 2011 software (black edition, Zeiss).To generate 3D-surface rendered images, super-resolution images were processed by Imaris software (Bitplane 9.5).To visualize the engulfed PSD95+ puncta within microglia, any fluorescence that was outside of the microglia was subtracted from the image by using the mask function in Imaris. Cell number and microglia process length and endpoints were counted with FIJI (ImageJ) software.
All data represent mean ± s.e.m. When only two independent groups were compared, significance was determined by two-tailed unpaired t-test with Welch's correction. When three or more groups were compared, one-way ANOVA with Bonferroni post hoc test or two-way ANOVA was used. A P value less than 0.05 was considered significant. The analyses were done in GraphPad Prism v.5.

October 2018
Data Policy information about availability of data All manuscripts must include a data availability statement. This statement should provide the following information, where applicable: -Accession codes, unique identifiers, or web links for publicly available datasets -A list of figures that have associated raw data -A description of any restrictions on data availability Field-specific reporting Please select the one below that is the best fit for your research. If you are not sure, read the appropriate sections before making your selection.

Life sciences Behavioural & social sciences Ecological, evolutionary & environmental sciences
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Life sciences study design
All studies must disclose on these points even when the disclosure is negative. The accession numbers of the RNA sequencing data associated with Figure 4 and Figure 5 in this study are GEO: GSE129178 and GSE139161. Raw sequencing reads from other publications were downloaded from GEO (series accessions GSE9907412, GSE9774417, GSE10233578, and GSE13343442).
No statistical methods were used to pre-determine sample sizes but our sample sizes are similar to those reported in previous publications.
Data exclusion criteria were pre-established before the experiments. In order to analyze microglial morphology (Fig. 2 b-f), we exclude one transplanted mouse which had hydrocephalus and have abnormal microglial morphology.
At least 3 replicates were taken to verify the reproducibility of the experimental findings. All attempts at replication were successful.
Animals were matched by age and similar numbers of male and female animals were used in nearly all comparisons. All treatments were given by a different researcher where possible to ensure blinding.
The investigators were blind to group allocation during data collection and analysis.