Dataset Information

Transcriptome analysis of IL-10-stimulated (M2c) macrophages by next-generation sequencing.

ABSTRACT: Alternatively activated "M2" macrophages are believed to function during late stages of wound healing, behaving in an anti-inflammatory manner to mediate the resolution of the pro-inflammatory response caused by "M1" macrophages. However, the differences between two main subtypes of M2 macrophages, namely interleukin-4 (IL-4)-stimulated "M2a" macrophages and IL-10-stimulated "M2c" macrophages, are not well understood. M2a macrophages are characterized by their ability to inhibit inflammation and contribute to the stabilization of angiogenesis. However, the role and temporal profile of M2c macrophages in wound healing are not known. Therefore, we performed next generation sequencing (RNA-seq) to identify biological functions and gene expression signatures of macrophages polarized in vitro with IL-10 to the M2c phenotype in comparison to M1 and M2a macrophages and an unactivated control (M0). We then explored the expression of these gene signatures in a publicly available data set of human wound healing. RNA-seq analysis showed that hundreds of genes were upregulated in M2c macrophages compared to the M0 control, with thousands of alternative splicing events. Following validation by Nanostring, 39 genes were found to be upregulated by M2c macrophages compared to the M0 control, and 17 genes were significantly upregulated relative to the M0, M1, and M2a phenotypes (using an adjusted p-value cutoff of 0.05 and fold change cutoff of 1.5). Many of the identified M2c-specific genes are associated with angiogenesis, matrix remodeling, and phagocytosis, including CD163, MMP8, TIMP1, VCAN, SERPINA1, MARCO, PLOD2, PCOCLE2 and F5. Analysis of the macrophage-conditioned media for secretion of matrix-remodeling proteins showed that M2c macrophages secreted higher levels of MMP7, MMP8, and TIMP1 compared to the other phenotypes. Interestingly, temporal gene expression analysis of a publicly available microarray data set of human wound healing showed that M2c-related genes were upregulated at early times after injury, similar to M1-related genes, while M2a-related genes appeared at later stages or were downregulated after injury. While further studies are required to confirm the timing and role of M2c macrophages in vivo, these results suggest that M2c macrophages may function at early stages of wound healing. Identification of markers of the M2c phenotype will allow more detailed investigations into the role of M2c macrophages in vivo.

SUBMITTER: Lurier EB

PROVIDER: S-EPMC5719494 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature

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Transcriptome analysis of IL-10-stimulated (M2c) macrophages by next-generation sequencing.

Lurier Emily B EB Dalton Donald D Dampier Will W Raman Pichai P Nassiri Sina S Ferraro Nicole M NM Rajagopalan Ramakrishan R Sarmady Mahdi M Spiller Kara L KL

Immunobiology 20170220 7

Alternatively activated "M2" macrophages are believed to function during late stages of wound healing, behaving in an anti-inflammatory manner to mediate the resolution of the pro-inflammatory response caused by "M1" macrophages. However, the differences between two main subtypes of M2 macrophages, namely interleukin-4 (IL-4)-stimulated "M2a" macrophages and IL-10-stimulated "M2c" macrophages, are not well understood. M2a macrophages are characterized by their ability to inhibit inflammation and ...[more]

PMID: 28318799

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Project description:BACKGROUND:Next-Generation Sequencing (NGS) technology has exceptionally increased the ability to sequence DNA in a massively parallel and cost-effective manner. Nevertheless, NGS data analysis requires bioinformatics skills and computational resources well beyond the possibilities of many "wet biology" laboratories. Moreover, most of projects only require few sequencing cycles and standard tools or workflows to carry out suitable analyses for the identification and annotation of genes, transcripts and splice variants found in the biological samples under investigation. These projects can take benefits from the availability of easy to use systems to automatically analyse sequences and to mine data without the preventive need of strong bioinformatics background and hardware infrastructure. RESULTS:To address this issue we developed an automatic system targeted to the analysis of NGS data obtained from large-scale transcriptome studies. This system, we named NGS-Trex (NGS Transcriptome profile explorer) is available through a simple web interface http://www.ngs-trex.org and allows the user to upload raw sequences and easily obtain an accurate characterization of the transcriptome profile after the setting of few parameters required to tune the analysis procedure. The system is also able to assess differential expression at both gene and transcript level (i.e. splicing isoforms) by comparing the expression profile of different samples.By using simple query forms the user can obtain list of genes, transcripts, splice sites ranked and filtered according to several criteria. Data can be viewed as tables, text files or through a simple genome browser which helps the visual inspection of the data. CONCLUSIONS:NGS-Trex is a simple tool for RNA-Seq data analysis mainly targeted to "wet biology" researchers with limited bioinformatics skills. It offers simple data mining tools to explore transcriptome profiles of samples investigated taking advantage of NGS technologies.

Project description:BACKGROUND: We have developed a simulation approach to help determine the optimal mixture of sequencing methods for most complete and cost effective transcriptome sequencing. We compared simulation results for traditional capillary sequencing with "Next Generation" (NG) ultra high-throughput technologies. The simulation model was parameterized using mappings of 130,000 cDNA sequence reads to the Arabidopsis genome (NCBI Accession SRA008180.19). We also generated 454-GS20 sequences and de novo assemblies for the basal eudicot California poppy (Eschscholzia californica) and the magnoliid avocado (Persea americana) using a variety of methods for cDNA synthesis. RESULTS: The Arabidopsis reads tagged more than 15,000 genes, including new splice variants and extended UTR regions. Of the total 134,791 reads (13.8 MB), 119,518 (88.7%) mapped exactly to known exons, while 1,117 (0.8%) mapped to introns, 11,524 (8.6%) spanned annotated intron/exon boundaries, and 3,066 (2.3%) extended beyond the end of annotated UTRs. Sequence-based inference of relative gene expression levels correlated significantly with microarray data. As expected, NG sequencing of normalized libraries tagged more genes than non-normalized libraries, although non-normalized libraries yielded more full-length cDNA sequences. The Arabidopsis data were used to simulate additional rounds of NG and traditional EST sequencing, and various combinations of each. Our simulations suggest a combination of FLX and Solexa sequencing for optimal transcriptome coverage at modest cost. We have also developed ESTcalc http://fgp.huck.psu.edu/NG_Sims/ngsim.pl, an online webtool, which allows users to explore the results of this study by specifying individualized costs and sequencing characteristics. CONCLUSION: NG sequencing technologies are a highly flexible set of platforms that can be scaled to suit different project goals. In terms of sequence coverage alone, the NG sequencing is a dramatic advance over capillary-based sequencing, but NG sequencing also presents significant challenges in assembly and sequence accuracy due to short read lengths, method-specific sequencing errors, and the absence of physical clones. These problems may be overcome by hybrid sequencing strategies using a mixture of sequencing methodologies, by new assemblers, and by sequencing more deeply. Sequencing and microarray outcomes from multiple experiments suggest that our simulator will be useful for guiding NG transcriptome sequencing projects in a wide range of organisms.

Dataset Information

Transcriptome analysis of IL-10-stimulated (M2c) macrophages by next-generation sequencing.

Publications

Transcriptome analysis of IL-10-stimulated (M2c) macrophages by next-generation sequencing.

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