GEO series

Engineering hematopoietic stem and progenitor cells to generate red blood cells as viral traps against HIV-1

GSE338343 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2026/07/13 Platform GPL34284

At a glance

RNA-seq (gene expression) · human · 12 samples

What it is: RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism: Homo sapiens (human)
Samples: 12 samples: 3 × Mock, dono vs 3 × GFP, dono vs 3 × CD4-GPA, dono vs 3 × CD4-GPA-tEPOR, donoGroups are read from the sample names, not from the paper. Check the list below.
Data you can get: A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.

Summary (written by the submitters)

Canonical HIV-1 entry into target cells depends on binding to CD4 as a primary receptor. Because of this, use of the CD4 receptor as a viral trap (a decoy receptor used to prevent infection of target cells) is a promising strategy for the treatment of HIV-1. One challenge in using CD4 viral traps is maintaining enough of the decoy receptor in circulation to remain effective.

Read the full summary ↓

Here we present a strategy to produce cell-based CD4 viral traps by engineering hematopoietic stem and progenitor cells (HSPCs) to express the CD4 receptor in red blood cell (RBC) progeny. This takes advantage of the ability of the HSPC to repopulate the blood system for a lifetime, while leveraging the fact that RBCs greatly outnumber any cell targeted for infection. CRISPR/Cas9-engineered HSPCs efficiently express CD4 on their cell surface after differentiation to the RBC lineage in vitro. Fusion of CD4 to glycophorin A (GPA) and introduction of a truncated erythropoietin receptor (tEPOR) leads to increased CD4 expression and enrichment of edited cells (CD4-GPA-tEPOR) to levels capable of neutralizing HIV-1 pseudovirus in vitro. In sum, this work presents a potential strategy for the one-time delivery of CD4-RBC viral traps through autologous transplantation of engineered HSPCs.

This dataset

Open GSE338343 in finder → Find more human RNA-seq datasets →

Download · which file do I need?

Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

Series matrix ↓

2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE338343_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓

3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

Raw reads on ENA ↗

What the files usually look like: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1494336 and SRA study SRP717447. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

3 × Mock, dono vs 3 × GFP, dono vs 3 × CD4-GPA, dono vs 3 × CD4-GPA-tEPOR, dono

Supports a between-group comparison across 12 samples.

How we read this: 4 replicated groups read from 12 sample titles; they account for 12 of them. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study

GSM9871699 Mock, donor 1 Mock, dono
GSM9871700 GFP, donor 1 GFP, dono
GSM9871701 CD4-GPA, donor 1 CD4-GPA, dono
GSM9871702 CD4-GPA-tEPOR, donor 1 CD4-GPA-tEPOR, dono
GSM9871703 Mock, donor 2 Mock, dono
GSM9871704 GFP, donor 2 GFP, dono
GSM9871705 CD4-GPA, donor 2 CD4-GPA, dono
GSM9871706 CD4-GPA-tEPOR, donor 2 CD4-GPA-tEPOR, dono
GSM9871707 Mock, donor 3 Mock, dono
GSM9871708 GFP, donor 3 GFP, dono
GSM9871709 CD4-GPA, donor 3 CD4-GPA, dono
GSM9871710 CD4-GPA-tEPOR, donor 3 CD4-GPA-tEPOR, dono

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