Spatial transcriptomics chips with sequencing-based microscopy
The MESH CHIP project aims to revolutionize spatial transcriptomics by using self-assembly and computational reconstruction to create low-cost, high-resolution surfaces for gene expression analysis.
Projectdetails
Introduction
We propose a technology platform for low cost, high resolution spatial transcriptomics surfaces. Spatial transcriptomics is a high cost research methodology for resolving the spatial variation of genes in a tissue by capturing mRNA transcripts on a surface containing molecular address markers.
Current Methods
To produce these surfaces, current methods rely on either:
- Printing technology with explicit assignment of unique address IDs to spatial locations.
- Random scattering of molecular IDs that are then sequenced in situ using microscopy.
Both of these fabrication methods are prohibitively expensive and time-consuming, such that spatial transcriptomic technology is still limited to a narrow selection of low throughput research applications.
Proposed Technology
Our proposed technology, the MESH CHIP, represents a radically different approach to producing these surfaces. Rather than print surfaces or build sequence-address maps with in situ microscopy, our technology works by self-assembly and deduction from sequencing data alone.
Advantages of MESH CHIP
This means that no prior information about the identity or location of address markers on the surface is needed prior to mRNA capture and sequencing. Instead, this information is reconstructed computationally using graph theory in a post hoc fashion.
By moving this information roadblock in the fabrication process to the increasingly cheap sequencing and computing stage, we greatly improve the cost performance of this technology.
Conclusion
MESH CHIP technology would represent a qualitatively lower cost product with greater performance than the state of the art, unlocking new use cases like diagnostics and high throughput tissue processing.
Financiële details & Tijdlijn
Financiële details
Subsidiebedrag | € 150.000 |
Totale projectbegroting | € 150.000 |
Tijdlijn
Startdatum | 1-1-2024 |
Einddatum | 30-6-2025 |
Subsidiejaar | 2024 |
Partners & Locaties
Projectpartners
- KUNGLIGA TEKNISKA HOEGSKOLANpenvoerder
Land(en)
Vergelijkbare projecten binnen European Research Council
Project | Regeling | Bedrag | Jaar | Actie |
---|---|---|---|---|
Spatial Transcriptomics through the lenses of statistical modeling and AIThis project aims to integrate spatial transcriptomics with machine learning and statistical modeling to enhance understanding of gene expression and tissue organization for personalized medicine. | ERC Consolid... | € 1.979.375 | 2025 | Details |
The sequencing microscope - a path to look at the molecules of biologyThis project aims to develop a novel technique that uses sequencing data to infer spatial information in tissues, enhancing our understanding of biological systems without advanced microscopy. | ERC Advanced... | € 2.500.000 | 2024 | Details |
Targeted Microarrays for 5-hydroxymethylcytosine-based Diagnosis of Hematological MalignanciesThis project aims to develop a cost-effective DNA chip for mapping 5-hydroxymethylcytosine (5hmC) to identify cancer biomarkers and improve diagnostic testing accessibility. | ERC Proof of... | € 150.000 | 2022 | Details |
BioCHIPS - Biofabricated microfluidcs CHIPS based on self assembling of CNCs to recreate the hierarchical fibrillar structure of human tissues ECMBiochips aims to develop a high-throughput platform for fabricating cell-laden microtissues with biophysical cues from native ECMs using 3D bioprinting and CNC self-assembly. | ERC Proof of... | € 150.000 | 2022 | Details |
Integrated photonics-based structured illumination for sequencingThis project aims to demonstrate a novel CMOS imager technology that enhances next-generation sequencing throughput and cost-effectiveness by enabling sub-pixel resolution readout. | ERC Proof of... | € 150.000 | 2025 | Details |
Spatial Transcriptomics through the lenses of statistical modeling and AI
This project aims to integrate spatial transcriptomics with machine learning and statistical modeling to enhance understanding of gene expression and tissue organization for personalized medicine.
The sequencing microscope - a path to look at the molecules of biology
This project aims to develop a novel technique that uses sequencing data to infer spatial information in tissues, enhancing our understanding of biological systems without advanced microscopy.
Targeted Microarrays for 5-hydroxymethylcytosine-based Diagnosis of Hematological Malignancies
This project aims to develop a cost-effective DNA chip for mapping 5-hydroxymethylcytosine (5hmC) to identify cancer biomarkers and improve diagnostic testing accessibility.
BioCHIPS - Biofabricated microfluidcs CHIPS based on self assembling of CNCs to recreate the hierarchical fibrillar structure of human tissues ECM
Biochips aims to develop a high-throughput platform for fabricating cell-laden microtissues with biophysical cues from native ECMs using 3D bioprinting and CNC self-assembly.
Integrated photonics-based structured illumination for sequencing
This project aims to demonstrate a novel CMOS imager technology that enhances next-generation sequencing throughput and cost-effectiveness by enabling sub-pixel resolution readout.
Vergelijkbare projecten uit andere regelingen
Project | Regeling | Bedrag | Jaar | Actie |
---|---|---|---|---|
Revolutionizing Spatial Biology with a cutting-edge Multi-Scale Imaging platformThe NanoSCAN project aims to develop the SAFe-nSCAN platform for high-resolution 3D tissue analysis, enhancing molecular profiling and advancing personalized therapies in immuno-oncology. | EIC Transition | € 2.489.162 | 2023 | Details |
Instrument-free 3D molecular imaging with the VOLumetric UMI-Network EXplorerVOLUMINEX aims to revolutionize molecular imaging by providing an affordable 3D sequencing-based microscopy method for comprehensive spatial and transcriptomic data mapping. | EIC Pathfinder | € 2.999.999 | 2025 | Details |
Een polymere microgestructureerde nanowellchip voor de analyse van individuele cellen op basis van microfabricage met behulp van 3D-printtechnologieHet project ontwikkelt betaalbare, op maat gemaakte micro-3D-geprinte chips voor single-cell analyses ter verbetering van kankerdiagnostiek en gepersonaliseerde therapieën. | Mkb-innovati... | € 167.760 | 2023 | Details |
Processing-in-memory architectures and programming libraries for bioinformatics algorithmsThis project aims to enhance genomics research by developing energy-efficient, cost-effective edge computing solutions using processing-in-memory technologies for high-throughput sequencing data analysis. | EIC Pathfinder | € 1.966.665 | 2022 | Details |
On-chip tomographic microscopy: a paraDIgm Shift for RevolUtionizing lab-on-a-chiP bioimaging technologyDISRUPT aims to revolutionize biomedical imaging with a novel lab-on-chip technology for cost-effective, high-resolution cancer detection and diagnostics using integrated tomographic microscopy and AI. | EIC Pathfinder | € 3.018.312 | 2022 | Details |
Revolutionizing Spatial Biology with a cutting-edge Multi-Scale Imaging platform
The NanoSCAN project aims to develop the SAFe-nSCAN platform for high-resolution 3D tissue analysis, enhancing molecular profiling and advancing personalized therapies in immuno-oncology.
Instrument-free 3D molecular imaging with the VOLumetric UMI-Network EXplorer
VOLUMINEX aims to revolutionize molecular imaging by providing an affordable 3D sequencing-based microscopy method for comprehensive spatial and transcriptomic data mapping.
Een polymere microgestructureerde nanowellchip voor de analyse van individuele cellen op basis van microfabricage met behulp van 3D-printtechnologie
Het project ontwikkelt betaalbare, op maat gemaakte micro-3D-geprinte chips voor single-cell analyses ter verbetering van kankerdiagnostiek en gepersonaliseerde therapieën.
Processing-in-memory architectures and programming libraries for bioinformatics algorithms
This project aims to enhance genomics research by developing energy-efficient, cost-effective edge computing solutions using processing-in-memory technologies for high-throughput sequencing data analysis.
On-chip tomographic microscopy: a paraDIgm Shift for RevolUtionizing lab-on-a-chiP bioimaging technology
DISRUPT aims to revolutionize biomedical imaging with a novel lab-on-chip technology for cost-effective, high-resolution cancer detection and diagnostics using integrated tomographic microscopy and AI.