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Affinity-based controlled release of interleukin-4 from scaffolds via biotin-avidin interactions for immunomodulation

GSE300514 Homo sapiens (human) RNA-seq (gene expression) 33 samples Submitted 2025/06/23 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 33 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
33 samples: 33 samples, each with a distinct title — no replicated groupsGroups 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.
Paper
Affinity-based controlled release of interleukin-4 from scaffolds via biotin-streptavidin interactions for immunomodulationJournal of controlled release : official journal of the Controlled Release Society · 2025
Summary (written by the submitters)
Abstract: Controlled release of immunomodulatory cytokines like interleukin-4 (IL-4) from biomaterials can modulate host immune cell behavior to improve tissue integration, however options for modifying complex biomaterials remain limited. Bioconjugation strategies using biotin-avidin interactions offer a promising approach since biotin can be conjugated to proteins, biomaterials, and even cells, without compromising their function.
Read the full summary ↓
Although it is known that conjugation of biotin to large biomolecules reduces its binding affinity for avidin and avidin variants, the potential to control release of biotinylated molecules via leveraging affinity interactions has not been thoroughly investigated. Moreover, the effects of biotin and avidin variants on innate immunity are poorly understood. Therefore, the goal of this study was to determine if biotin-avidin interactions could be manipulated to control the release of IL-4 from biomaterials and to investigate the subsequent effects on primary human macrophage phenotype. First, we characterized the effects of soluble biotin, avidin, and avidin variants, streptavidin and CaptAvidin, on the phenotype of primary human macrophages using RNA sequencing and found that CaptAvidin significantly influenced macrophage gene expression while other variants did not. Then, after evaluating how bioconjugation parameters influenced biotin density and avidin variant binding to porous gelatin scaffolds, we found that biotin-avidin affinity interactions influenced the spontaneous release of biotinylated IL-4 (bIL-4) from biotinylated and desthiobiotinylated scaffolds bound with either avidin or streptavidin for up to ten days in vitro. Finally, we measured the response of primary human macrophages (8 donors) cultured on modified scaffolds, finding an increase in IL-4 driven genes when bIL-4 was released via biotin-streptavidin affinity interactions compared to desorption-based release. These results highlight how biotin-avidin interactions can be leveraged for spontaneous release to achieve an immunomodulatory drug delivery system.
Published in
Affinity-based controlled release of interleukin-4 from scaffolds via biotin-streptavidin interactions for immunomodulation
Nash VA, Cortes-Troncoso JF, Chua PE et al. · Journal of controlled release : official journal of the Controlled Release Society 2025 · PMID 40499762 · doi:10.1016/j.jconrel.2025.113943
This dataset
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.

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 GSE300514_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1281087 and SRA study SRP593943. Searching any of these in the dataset finder brings you back here.

Study design
33 samples, each with a distinct title — no replicated groups

Supports a case/control comparison: 19 samples read as cases, 7 as controls.

How we read this: Read from 33 sample titles: 33 distinct titles with little repetition. 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
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