Gene Expression Nebulas
A data portal of transcriptomic profiles analyzed by a unified pipeline across multiple species

Gene Expression Nebulas

A data portal of transcriptome profiles across multiple species

PRJNA348691: The Nature and Nurture of Cell Heterogeneity: Accounting for Macrophage Gene-environment Interactions with Single-cell RNA-Seq

Source: NCBI / GSE87849
Submission Date: Oct 11 2016
Release Date: Jan 13 2017
Update Date: May 15 2019

Summary: Background: Single-cell RNA-Seq can be a valuable and unbiased tool to dissect cellular heterogeneity, despite the transcriptome’s limitations in describing higher functional phenotypes and protein events. Perhaps the most important shortfall with transcriptomic ‘snapshots’ of cell populations is that they risk being descriptive, only cataloging heterogeneity at one point in time, and without microenvironmental context. Studying the genetic (‘nature’) and environmental (‘nurture’) modifiers of heterogeneity, and how cell population dynamics unfold over time in response to these modifiers is key when studying highly plastic cells such as macrophages. Results: We introduce the programmable PolarisTM microfluidic lab-on-chip for single-cell sequencing, which performs live-cell imaging while controlling for the culture microenvironment of each cell. Using gene-edited macrophages we demonstrate how previously unappreciated knockout effects of SAMHD1, such as an altered oxidative stress response, have a large paracrine signaling component. Furthermore, we demonstrate single-cell pathway enrichments for cell cycle arrest and APOBEC3G degradation, both associated with the oxidative stress response and altered proteostasis. Interestingly, SAMHD1 and APOBEC3 are both HIV-1 inhibitors (‘restriction factors’), with no previously known co-regulation. Conclusion: As single-cell methods continue to mature, so will the ability to move beyond simple ‘snapshots’ of cell populations towards studying the determinants of population dynamics. By combining single-cell culture, live-cell imaging, and single-cell sequencing, we have demonstrated the ability to study cell phenotypes and microenvironmental influences. It’s these microenvironmental components - ignored by standard single-cell workflows - that likely determine how macrophages, for example, react to inflammation and form treatment resistant HIV reservoirs.

Overall Design: Stem cell derived macrophages (wildtype and SAMHD1 knockout) were single-cell cultured for 1h or 8h under for different media conditions (with/without lipopolysaccharide, with/without conditioned media to account for inter-macrophage signalling)

GEN Datasets:
GEND000055
Strategy:
Species:
Healthy Condition:
Cell Type:
Cell Line:
Protocol
Growth Protocol: Macrophages grown on fibronectin coated polaris chip in XVIVO 15 + MCSF + FCS + PS
Treatment Protocol: LPS 100ng/ml in either XVIVO 15 + FCS + MCSF or from previously cultured Macrophages exposed to same batch of LPS
Extract Protocol: FluidigmC1 RNAseq protocol: cDNA was generated using SMARTer Ultra Low RNA Kit (Clontech)
Library Construction Protocol: Nextera XT DNA Library Preparation Kit (Illumina); Illumina RNAseq HiSeq4000 75bp PE
Sequencing
Molecule Type: poly(A)+ RNA
Library Source:
Library Layout: paired
Library Strand: -
Platform: Illumina
Instrument Model: Illumina HiSeq 4000
Strand-Specific: Unspecific
Samples
Basic Information:
Sample Characteristic:
Biological Condition:
Experimental Variables:
Protocol:
Sequencing:
Assessing Quality:
Analysis:
Data Resource GEN Sample ID GEN Dataset ID Project ID BioProject ID Sample ID Sample Name BioSample ID Sample Accession Experiment Accession Release Date Submission Date Update Date Species Race Ethnicity Age Age Unit Gender Source Name Tissue Cell Type Cell Subtype Cell Line Disease Disease State Development Stage Mutation Phenotype Case Detail Control Detail Growth Protocol Treatment Protocol Extract Protocol Library Construction Protocol Molecule Type Library Layout Strand-Specific Library Strand Spike-In Strategy Platform Instrument Model Cell Number Reads Number Gbases AvgSpotLen1 AvgSpotLen2 Uniq Mapping Rate Multiple Mapping Rate Coverage Rate
Publications
The nature and nurture of cell heterogeneity: accounting for macrophage gene-environment interactions with single-cell RNA-Seq.
BMC genomics . 2017-01-07 [PMID: 28061811]