# Membrane Anchored-Probes for Sensing Analytes at the Cell Surface

> **NIH NIH K25** · UNIVERSITY OF PENNSYLVANIA · 2022 · $148,905

## Abstract

Project Summary. Mirna El Khatib is a synthetic organic chemist, whose goal is to transition into the area of
biomedical imaging with applications in cancer biology. An NHLBI K25 award will help her to accomplish this
transition and simultaneously will lead to exploration and development of a new class of imaging probe, namely
Membrane-Anchored Probes (MAP) for oxygen.
Longitudinal imaging is an indispensible tool for learning about progression of disease and outcomes of
therapies. The first step in this proposal is to develop a general approach to membrane-tethered molecular
sensors. Membrane-anchored probes (MAP) offer a unique opportunity to longitudinally image concentrations
of nutrients and signaling molecules, in this case oxygen, in the immediate environment of the cell. When used
in vivo such probes will remain longer in the region of interest, compared to sensors dissolved in the
extracellular milieu.
The new MAP for oxygen will be applied towards longitudinal oxygen measurements in the niche of
transplanted hematopoietic stem cells (HSCs) and leukemic cells (LCs). This will unravel why HSCs choose to
localize in specific regions of the bone marrow (BM) and why leukemic stem cells (LSCs) evade death during
chemotherapy.

## Key facts

- **NIH application ID:** 10459398
- **Project number:** 5K25HL145092-04
- **Recipient organization:** UNIVERSITY OF PENNSYLVANIA
- **Principal Investigator:** Mirna El Khatib
- **Activity code:** K25 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $148,905
- **Award type:** 5
- **Project period:** 2019-08-02 → 2024-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10459398

## Citation

> US National Institutes of Health, RePORTER application 10459398, Membrane Anchored-Probes for Sensing Analytes at the Cell Surface (5K25HL145092-04). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10459398. Licensed CC0.

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