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Low-Valine Diet Ameliorates Pathological Cardiac Hypertrophy by Inhibiting LONP1-Mediated Degradation of ATP5F1B in Male Rodents

GSE329237 Mus musculus (mouse) RNA-seq (gene expression) 6 samples Submitted 2026/09/24 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 6 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
Mus musculus (mouse)
Samples
6 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.
Summary (written by the submitters)
Background Pathological cardiac hypertrophy can cause impaired myocardial contraction and dysfunction and, subsequently, heart failure (HF) with high mortality. Branched chain amino acids (BCAAs), a group of essential amino acids, are significantly associated with cardiovascular diseases. Methods Meta-analysis and subgroup analysis were performed to investigate the effects of three BCAAs on cardiovascular diseases.
Read the full summary ↓
The NHANES database was used to assess dietary valine intake and analyze its impact on cardiovascular events. In vivo, the effects of a high-valine diet on cardiac structure and function in male animals were evaluated. To explore the underlying mechanism, we constructed L-valine-conjugated agarose beads. Pull-down experiments combined with LC-MS/mass spectrometry (MS) were conducted to identify target proteins of valine. Furthermore, the effects of low-valine diets on pathological hypertensive cardiac hypertrophy and function were determined via echocardiography, histological evaluation, and molecular analysis. Additionally, we validated the role of ATP5F1B through AAV9-cTNT in the overexpression and knockdown of Atp5f1β in vivo. In vitro, siLonp1 was used to determine the role of LONP1 in ATP5F1B expression at the protein level. Results Meta-analysis combined with NHANES database findings revealed that among the three BCAAs, valine was significantly associated with cardiovascular disease risk, with cumulative dietary valine intake increasing the risk of cardiovascular events. In vivo, a high-valine diet exacerbated pathological cardiac hypertrophy and worsened cardiac dysfunction in hypertensive male animals, whereas reducing dietary valine content alleviated pathological hypertrophy and improved HF by decreasing cardiac tissue valine levels. The construction of valine-coated agarose beads followed by pull-down and mass spectrometry analysis revealed valine binding to ATP5F1B in hypertensive animal cardiac tissue. In vitro and in vivo experiments confirmed that dietary valine structural modification modulates myocardial cell mitochondrial structure, function, and oxidative stress levels by regulating ATP5F1B protein expression, thereby influencing hypertensive pathological myocardial hypertrophy and cardiac function. Furthermore, coimmunoprecipitation (Co-IP) coupled with LC-MS/MS revealed that valine binding to ATP5F1B induces a conformational change, thereby increasing LONP1-mediated degradation of the ATP5F1B protein. Prediction and validation revealed the MET443 site as the relevant binding site for ATP5F1B (-Val)-LONP1. Conclusion The dietary pattern of low-valine diets exerts potent cardioprotective effects by improving substance and energy metabolism in hypertensive cardiomyocytes and mitigating mitochondrial structural damage and oxidative stress injury, thereby offering novel therapeutic strategies for clinical adjunctive treatment of hypertensive individuals.
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 GSE329237_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 PRJNA1458185 and SRA study SRP695295. Searching any of these in the dataset finder brings you back here.

Samples in this study

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