Spatiotemporal Regulation of Developmental Pattern Formation
Project Number5R35GM152180-02
Contact PI/Project LeaderBRADHAM, CYNTHIA A
Awardee OrganizationBOSTON UNIVERSITY (CHARLES RIVER CAMPUS)
Description
Abstract Text
Project Summary/Abstract
Despite their important role in birth defects and infant mortality, the 3-D and 4-D patterning
processes that employ multiple signals to drive embryonic development and morphogenesis are
not mechanistically understood. The long-term goal is to obtain a complete molecular description
of 4-D pattern formation, using the simple yet relevant sea urchin larval skeleton as a model. The
central objective in this application is to define a model that captures how the ectoderm expresses
different patterning cues in different regions over space and time using systems biology
approaches, to integrate that network with our spatiotemporal patterning cue reception network
in the responsive skeletogenic cells, then use that network model to identify the underlying
general principles for spatiotemporal deployment of and response to patterning instructions. The
main hypothesis is that differential spatiotemporal expression of the set of signals that regulate
skeleton formation is the central driver of embryonic pattern formation and is hard-wired into the
ectodermal gene regulatory networks that regulate skeletal patterning, while the reception of
those cues drives the spatiotemporal diversification of the skeleton-producing PMCs that in turn
mediate morphogenesis. The expected outcomes are (i) a validated single-cell level set of
interconnected spatiotemporal network models that define the presentation and reception of
patterning cues between the relevant tissues and (ii) computational models that capture the
overall network and that will allow rigorous analysis of the networks' functions. The research
proposed in this application is innovative, in the applicant's opinion, because it utilizes novel
analytical approaches and tools developed by the applicant's group, including a novel scRNA-seq
data analysis algorithm, a new tool for automated 3-D mapping of skeletogenic cells from confocal
image stacks, and polychrome skeletal labeling for post-hoc dynamics analysis. The proposed
research is significant because will establish a highly resolved molecular map of a 4-D
developmental process for skeletal patterning that will offer insight into the general principles that
underlie complex pattern formation. Because of the conservation of many of the relevant
patterning cues between sea urchin and human skeletons, this knowledge may ultimately lead to
new approaches for the prevention or treatment of skeletal birth defects and new strategies for
synthetic biomineral production.
Public Health Relevance Statement
Narrative
The proposed research is relevant to public health because by understanding 4-D
developmental pattern formation, it seeks to acquire fundamental knowledge about the
mechanisms of embryonic development that are driven by conserved signals and that have the
potential to enhance human health by identifying new avenues to prevent or treat patterning-
based birth defects. By laying these foundations for new strategies to address skeletal birth
defects via increasing our understanding of the fundamental signal-dependent pattern formation
processes, the goals of the proposed research are relevant to the mission of NIGMS.
NIH Spending Category
No NIH Spending Category available.
Project Terms
3-DimensionalAddressAlgorithmic AnalysisCellsComplexComputer ModelsCongenital AbnormalityCuesData AnalysesDevelopmentDevelopmental ProcessEctodermEmbryonic DevelopmentEmbryonic Pattern SpecificationFoundationsGoalsHealthHumanInfant MortalityInstructionKnowledgeLabelMapsMediatingMissionModelingMolecularMorphogenesisNational Institute of General Medical SciencesOutcomePathway AnalysisPatternPattern FormationPrevention approachProcessProductionPublic HealthRegulationResearchRoleSea UrchinsSignal TransductionSkeletonSystems BiologyTissuesconfocal imaginggene regulatory networkinnovationinsightnetwork modelsnovelnovel strategiespreventresponsesingle-cell RNA sequencingskeletalspatiotemporaltime usetool
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Outcomes
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