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Prolonged Loss of Oxidative Phosphorylation and Mitochondrial Mass Characterize CD66b+ Leukocytes from Patients with Sepsis

GSE316708 Homo sapiens (human) RNA-seq (gene expression) 38 samples Submitted 2026/01/20 Platform GPL34284
At a glance

RNA-seq (gene expression) · human · 38 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
38 samples
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
Prolonged Loss of Oxidative Phosphorylation and Mitochondrial Mass Characterize CD66b(+) Leukocytes from Patients with SepsisbioRxiv : the preprint server for biology · 2025
Summary (written by the submitters)
Introduction: Sepsis leads to expansion of myeloid-derived suppressor cells (MDSC) and their subtypes. These normally transitory MDSC suppress T cell activation and alter T cell cytokine production while simultaneously promulgating systemic low-grade inflammation. Immune metabolism has been demonstrated to shape cell responses and regulate immune suppression or enhance effector activity.
Read the full summary ↓
While the metabolism of MDSC has been extensively studied in cancer, the metabolic phenotype of this heterogeneous population in sepsis remains unclear. Our goal was to assess metabolic flux in MDSC during and after sepsis and stratify these patients by characteristics and outcome to determine differences that may guide treatment decisions. Methods: Peripheral blood mononuclear cells (PBMC) from healthy subjects and sepsis patients at four days, 2-3 weeks, and 6 months underwent CD66b+ or CD3+ isolation, followed by assessment of metabolic flux, flow cytometry, mRNA sequencing, and epigenetic analysis. Results: Mitochondrial basal oxygen consumption rates (OCR) and maximal oxygen consumption rates (SRC) were decreased in MDSC from septic patients at four days after infection and persisted for up to six months after sepsis onset. Glycolysis was not impacted by sepsis. In contrast, oxidative metabolism in CD3+ T cells was similar between sepsis patients and healthy subjects. Reduced MDSC oxidative metabolism was linked to adverse clinical outcomes. The decline in oxygen consumption from MDSC in septic patients was also linked to significant reductions in MDSC mitochondrial content. Transcriptomic analysis of CD66b+ cells isolated from PBMC healthy participants and patients with sepsis at four days, 2-3 weeks, and 6 months revealed 19 differentially expressed genes and two long non-coding RNAs as potentially responsible for this decline in mitochondrial mass. Specifically, NR4A3, NR4A2, and TAMLIN/NR4A1 (all critical for mitochondrial biogenesis) expression were persistently decreased with reduced chromatin accessibility indicative of gene silencing. Discussion: After sepsis, PBMC CD66b+ cells present with a unique metabolic signature that is not shared with CD3+ T-cell subsets in these patients or other disease cohorts. These changes in mitochondrial function result from a reduced content of these organelles. We have identified gene silencing, reduced gene expression of key transcription factors that regulate mitochondrial biogenesis, as well as increased long non-coding RNA as potential drivers of this unique metabolic phenotype. These results highlight a need to target metabolism in sepsis to promote immune homeostasis and recovery.
Published in
Prolonged Loss of Oxidative Phosphorylation and Mitochondrial Mass Characterize CD66b(+) Leukocytes from Patients with Sepsis
Rodhouse C, Barrios EL, Zeumer-Spataro L et al. · bioRxiv : the preprint server for biology 2025 · PMID 41446068 · doi:10.64898/2025.12.16.694726
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 GSE316708_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 PRJNA1403813 and SRA study SRP663435. Searching any of these in the dataset finder brings you back here.

Samples in this study

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