Multi-omic 3D tissue maps for a Human BioMolecular Atlas
Multi-omic 3D tissue maps for a Human BioMolecular Atlas
批准号:
10259781
负责人:
James Paul Carson
金额:
$98.55万
依托单位国家:
美国
项目类别:
财政年份:
2020
资助国家:
美国
项目状态:
已结题
起止时间:
2020-09-10 至 2024-08-31
关键词:
3-DimensionalAntibodiesArchitectureAtlasesBiological AssayBiologyCellsCommunitiesComplementComputer softwareCytometryData SetDetectionDiabetes MellitusDiseaseGene ExpressionGoalsHealthHumanHuman BioMolecular Atlas ProgramImageIn SituKnowledgeLightLipidsMalignant neoplasm of pancreasMapsMass Spectrum AnalysisMetabolicMethodsMicroscopyMolecularNatureOligonucleotidesOrganOrgan ProcurementsPancreasPerformancePhasePhosphorylationPost-Translational Protein ProcessingProcessProteinsRNAResolutionSamplingSpectrometry, Mass, Matrix-Assisted Laser Desorption-IonizationTechnologyTissue SampleTissuesbasebiobankexperiencehuman tissueinnovationinsightinterestmultidisciplinarymultiple omicsnano-stringnovelopen sourceprotein expressionreconstructionsubcellular targetingsuccesstool
中文摘要
点击翻译按钮获取中文摘要
英文摘要
PROJECT ABSTRACT
Spatially resolved molecular maps of mammalian organs hold significant promise in providing a deeper
understanding of human organ functioning in health and disease states. Fundamental to this is an
understanding how tissue organization impacts on the state of a cell and performance of its function.
The overarching goal of the Human BioMolecular Atlas Program (HuBMAP) and specifically of Tissue
Mapping Centers within the HuBMAP framework is to generate high-resolution three dimensional (3D)
human tissue maps. Present state-of-the-art spatially-resolved tissue analysis assays (e.g. MERFISH, seq-
FISH, imaging mass cytometry) utilize antibody-based or oligo probe-based approaches that require prior
knowledge of the biomolecular targets to map, challenging the ability to characterize the terra incognita (i.e.
the unknown) in a tissue mapping effort. Mass spectrometry (MS)-based omic mapping technologies enable
unbiased detection and mapping of metabolites, lipids, and proteins (including post-translational
modifications - PTMs) in situ in tissue samples with high-resolution and represents an excellent complement
to highly multiplexed targeted approaches for spatially resolved tissue analysis.
The overall objective of this application is to generate high-resolution, multi-omic, 3D biomolecular maps of
non-diseased human organs. We will take a Google Maps-type approach with our mapping effort progressing
in phases to generate reference maps at increasing resolution. First, single-cell or near-single-cell resolution
MS-based mapping technologies will be used to provide an unbiased view of tissue molecular spatial
architecture. Second, biomolecules of interest will be subsequently interrogated with highly multiplexed sub-
cellular resolution spatial omics assays in a targeted fashion. Our focus will be on the pancreas, an essential
organ important for several metabolic functions. Notably, the pancreas, despite its importance, is not one of
the listed key tissues and organs currently being analyzed by the HuBMAP consortium further supporting the
need to focus on this critical organ. We will employ high resolving power and high-resolution mass
spectrometry-based molecular mapping platforms (LMD-nanoPOT-MS, MALDI-FTMS, nanoDESI-MS) for
unbiased mapping of metabolites, lipids, and proteins (including PTMs such as phosphorylation). These MS
assays will be complemented with powerful highly multiplexed targeted spatial omics assays (CODEX and
NanoString GeoMx for protein and RNA respectively) and light sheet microscopy to generate high-resolution,
multi-omics human tissue maps. The innovative spatially resolved multi-omic tissue maps generated will be
unprecedented and the unique multi-omic datasets will provide many novel insights. The tissue mapping
efforts will be supported by commercially available and open-source state-of-the-art 3D reconstruction
software to create browsable 3D RNA/protein/PTM/lipid/metabolite maps of the pancreas. Undergirding the
tissue characterization and 3D organ map reconstructions efforts will be a robust organ procurement,
processing and distribution network.
Specifically, we will: (1) Procure, process and distribute samples of normal pancreas from non-diseased
donors through a robust procurement, processing, and distribution network. (2) Perform comprehensive
high-resolution multi-omics tissue mapping through innovative and complementary platforms for unbiased
and targeted analyses (that includes gene and protein expression, and PTM, metabolite and lipid abundances).
(3) Establish browsable 3D multi-omics (RNA / protein / PTM / lipid / metabolite)-based maps of normal
non-diseased pancreas; and to disseminate methods and tools to the HIVE and other TMCs.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
Data Analysis Core
-
批准号:10685588
-
项目类别:
-
资助金额:$24.74万
-
财政年份:2020
-
负责人:James Paul Carson
-
依托单位:
Data Analysis Core
-
批准号:10118876
-
项目类别:
-
资助金额:$11.41万
-
财政年份:2020
-
负责人:James Paul Carson
-
依托单位:
Multi-omic 3D tissue maps for a Human BioMolecular Atlas
-
批准号:10118874
-
项目类别:
-
资助金额:$75.07万
-
财政年份:2020
-
负责人:James Paul Carson
-
依托单位:
Data Analysis Core
-
批准号:10259783
-
项目类别:
-
资助金额:$17.5万
-
财政年份:2020
-
负责人:James Paul Carson
-
依托单位:
An Interactive Volumetric Atlas of the Mouse Brain
-
批准号:7771686
-
项目类别:
-
资助金额:$19.69万
-
财政年份:2009
-
负责人:James Paul Carson
-
依托单位:
海外基金