UH3CA268091
Cooperative Agreement
Overview
Grant Description
Seq-Scope: Microscopic examination of spatial single cell transcriptome in cell and tissue senescence - Summary
Standard immunostaining or RNA in situ hybridization can examine only one or a handful of target molecular species at a time; therefore, the amount of information obtained from a single experimental session is limited.
To overcome this, emerging spatial transcriptomics (ST) techniques aim to examine all genes expressed from the genome from a single histological slide. There are three major methodologies of experimentally implementing ST: the sequential in situ hybridization method, in situ sequencing method, and spatial barcoding method.
Among these, the spatial barcoding method is the most straightforward, comprehensive, and so far the only method scalable for large amounts of samples. The spatial barcoding method reveals both the RNA sequence and their spatial locations by capturing tissue RNA using a spatially-barcoded oligonucleotide array.
The current spatial barcoding method, however, are intrinsically limited by their low resolution and low RNA capture efficiencies; correspondingly, all currently available technologies failed to reveal the microscopic details of the spatial transcriptome.
We recently developed a technology named Seq-Scope, which overcomes all these limitations. Seq-Scope has an effective resolution of 0.5-1 μm and reveals over 20 transcripts per μm2 area (~50 transcripts/μm2 estimated at library saturation). Both resolution and transcriptome capture output of Seq-Scope are the best among all available technologies described in the literature so far.
With this unprecedented performance, Seq-Scope visualized spatial transcriptome heterogeneity at multiple histological scales, including tissue zonation according to the portal-central (liver), crypt-surface (colon), and inflammation-fibrosis (injured liver) axes, cellular components including single cell types and subtypes, and subcellular architectures of nucleus, cytoplasm, and mitochondria.
Seq-Scope also has a potential to improve and complement current scRNA-seq approaches.
In response to the Sennet announcement, we propose to adapt and utilize Seq-Scope to provide atlases of cellular senescence in multiple tissues during normal human aging, focusing on the following three aims:
(1) Identify and characterize hepatic senescent cell population during liver disease.
(2) Characterize age-associated changes of hepatic spatial transcriptome.
(3) Combine Seq-Scope with detection of senescence protein and cell-type marker proteins.
For all aims, we will begin with analyzing mouse tissue to establish the feasibility of monitoring cell and tissue senescence (UG3), and then expand the work in human tissues using the tissue obtained from diverse resources including the Sennet Tissue Mapping Center (TMC) (UH3).
Seq-Scope is a versatile technology, which is quick, straightforward, scalable, and adaptable. Once optimized, a single researcher can process 5-10 frozen tissue blocks every week to generate high-quality spatial single cell transcriptome data. Therefore, our team is confident that we will be able to adapt our technology to any of the tissue systems that are provided by the Sennet TMC in the UH3 phase.
Standard immunostaining or RNA in situ hybridization can examine only one or a handful of target molecular species at a time; therefore, the amount of information obtained from a single experimental session is limited.
To overcome this, emerging spatial transcriptomics (ST) techniques aim to examine all genes expressed from the genome from a single histological slide. There are three major methodologies of experimentally implementing ST: the sequential in situ hybridization method, in situ sequencing method, and spatial barcoding method.
Among these, the spatial barcoding method is the most straightforward, comprehensive, and so far the only method scalable for large amounts of samples. The spatial barcoding method reveals both the RNA sequence and their spatial locations by capturing tissue RNA using a spatially-barcoded oligonucleotide array.
The current spatial barcoding method, however, are intrinsically limited by their low resolution and low RNA capture efficiencies; correspondingly, all currently available technologies failed to reveal the microscopic details of the spatial transcriptome.
We recently developed a technology named Seq-Scope, which overcomes all these limitations. Seq-Scope has an effective resolution of 0.5-1 μm and reveals over 20 transcripts per μm2 area (~50 transcripts/μm2 estimated at library saturation). Both resolution and transcriptome capture output of Seq-Scope are the best among all available technologies described in the literature so far.
With this unprecedented performance, Seq-Scope visualized spatial transcriptome heterogeneity at multiple histological scales, including tissue zonation according to the portal-central (liver), crypt-surface (colon), and inflammation-fibrosis (injured liver) axes, cellular components including single cell types and subtypes, and subcellular architectures of nucleus, cytoplasm, and mitochondria.
Seq-Scope also has a potential to improve and complement current scRNA-seq approaches.
In response to the Sennet announcement, we propose to adapt and utilize Seq-Scope to provide atlases of cellular senescence in multiple tissues during normal human aging, focusing on the following three aims:
(1) Identify and characterize hepatic senescent cell population during liver disease.
(2) Characterize age-associated changes of hepatic spatial transcriptome.
(3) Combine Seq-Scope with detection of senescence protein and cell-type marker proteins.
For all aims, we will begin with analyzing mouse tissue to establish the feasibility of monitoring cell and tissue senescence (UG3), and then expand the work in human tissues using the tissue obtained from diverse resources including the Sennet Tissue Mapping Center (TMC) (UH3).
Seq-Scope is a versatile technology, which is quick, straightforward, scalable, and adaptable. Once optimized, a single researcher can process 5-10 frozen tissue blocks every week to generate high-quality spatial single cell transcriptome data. Therefore, our team is confident that we will be able to adapt our technology to any of the tissue systems that are provided by the Sennet TMC in the UH3 phase.
Funding Goals
NOT APPLICABLE
Grant Program (CFDA)
Awarding Agency
Place of Performance
Ann Arbor,
Michigan
481091276
United States
Geographic Scope
Single Zip Code
Related Opportunity
Analysis Notes
Amendment Since initial award the End Date has been extended from 08/31/25 to 08/31/26 and the total obligations have increased 128% from $768,615 to $1,751,906.
Regents Of The University Of Michigan was awarded
Cooperative Agreement UH3CA268091
worth $1,751,906
from the National Institute of Allergy and Infectious Diseases in September 2021 with work to be completed primarily in Ann Arbor Michigan United States.
The grant
has a duration of 5 years and
was awarded through assistance program 93.310 Trans-NIH Research Support.
The Cooperative Agreement was awarded through grant opportunity Administrative Supplements to Existing NIH Grants and Cooperative Agreements (Parent Admin Supp Clinical Trial Optional).
Status
(Ongoing)
Last Modified 2/9/26
Period of Performance
9/20/21
Start Date
8/31/26
End Date
Funding Split
$1.8M
Federal Obligation
$0.0
Non-Federal Obligation
$1.8M
Total Obligated
Activity Timeline
Transaction History
Modifications to UH3CA268091
Additional Detail
Award ID FAIN
UH3CA268091
SAI Number
UH3CA268091-719841340
Award ID URI
SAI UNAVAILABLE
Awardee Classifications
Public/State Controlled Institution Of Higher Education
Awarding Office
75NC00 NIH National Cancer Institute
Funding Office
75NA00 NIH OFFICE OF THE DIRECTOR
Awardee UEI
GNJ7BBP73WE9
Awardee CAGE
03399
Performance District
MI-06
Senators
Debbie Stabenow
Gary Peters
Gary Peters
Budget Funding
| Federal Account | Budget Subfunction | Object Class | Total | Percentage |
|---|---|---|---|---|
| Office of the Director, National Institutes of Health, Health and Human Services (075-0846) | Health research and training | Grants, subsidies, and contributions (41.0) | $768,615 | 100% |
Modified: 2/9/26