# Mitochondrial DNA mutations in the renal cortex to elucidate cell-specific mechanisms of mitochondrial dysfunction in tubules and glomeruli

> **NIH NIH R21** · UNIVERSITY OF WASHINGTON · 2021 · $194,375

## Abstract

Project Summary/Abstract
Mitochondrial dysfunction is a hallmark of normative aging and of kidney disease and mitochondrial DNA
(mtDNA) damage and mutation accumulation has been proposed as one underlying cause. A clear
understanding of the functional role of somatic mtDNA mutation in age-related mitochondrial dysfunction has
been impeded, however, by the limited accuracy of modern mutation detection techniques and the complexities
of experimental approaches to isolate specific cells and their components. Furthermore, many studies have
underestimated the importance of tissue-specific analysis of mtDNA mutation by broadly applying single organ
studies to make assumptions of organismal-level mechanisms. By implementing Duplex Sequencing, an ultra-
accurate sequencing method designed to detect mutations with a frequency as low as 1x10-7, we have been
able to characterize the tissue-specific patterns of somatic mtDNA mutation across 10 tissues from young and
aged mice. In doing so, we identified unique aging mutation patterns between organs, with kidney cortex showing
the highest frequency of somatic mtDNA mutations. Even within the kidney we found regional differences by
comparing mutation rates in the tubule-rich kidney cortex to isolated renal glomeruli, thus revealing that the
glomerulus has a significantly lower point mutation frequency, a lower frequency of oxidative mtDNA mutations
and differential accumulation of mutations in mtDNA genes, as compared to the whole cortex. These results
demonstrate that mtDNA somatic mutation accumulation is cell-specific within the kidney. Based on the premise
that age-associated somatic mtDNA mutation in the kidney is determined by cell-specific differences in the ability
to respond to mutation accumulation, we will utilize advanced technological approaches, including Duplex
Sequencing, to address two Aims. In Aim 1, mitochondria from unique renal cell populations will be accurately
isolated and analyzed by taking advantage of a Cre-Lox mitochondrial reporter mouse (MITO-Tag) crossed with
mice expressing either a glomerular podocyte (podocin) or tubule epithelia (KSP) Cre. Mutation burden,
mitochondrial energetics and mitophagy will be analyzed from single cell-type populations in the context of
somatic mutation accumulation through natural aging. In Aim 2, kidney-specific mitochondrial dysfunction will be
generated through uni-nephrectomy and by introducing a high fat/high sucrose diet as a model of premature
kidney aging; this will allow us to elucidate the molecular mechanisms involved in somatic mutagenesis of renal
mtDNA under oxidative stress and in response to interventions aimed at protecting the mitochondria; specifically,
SS-31, a rejuvenating peptide with potential translational applications. This project will develop novel tools to
clarify the role of cell-type and age-associated somatic mtDNA mutation in the kidney and provide a new
perspective on the contribution of DNA mutation and aging to kid...

## Key facts

- **NIH application ID:** 10190112
- **Project number:** 1R21DK128540-01
- **Recipient organization:** UNIVERSITY OF WASHINGTON
- **Principal Investigator:** Monica Yicette Sanchez-Contreras
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $194,375
- **Award type:** 1
- **Project period:** 2021-03-01 → 2024-02-29

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10190112

## Citation

> US National Institutes of Health, RePORTER application 10190112, Mitochondrial DNA mutations in the renal cortex to elucidate cell-specific mechanisms of mitochondrial dysfunction in tubules and glomeruli (1R21DK128540-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10190112. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*