SBIR-STTR Award

Fluorescence-activated-cell-sorting (FACS) or flow cytometry enables clinicians and researchers to quantitatively characterize the physical (cell size, shape, granularity) and biochemical (DNA content, cell cycle distribution, cell surface markers, and viability) properties of cells, however FACS devices do not produce an image of the cell. Increasing sophistication of research assays now rely on the collection of cells based on their phenotypical and spatial characteristics; with the capabilities offered only by microscopic imaging cytometers having severe limits in throughput and lacking cell isolation. We propose an innovative, low cost design to combine the merits of FACS and microscopic 3D imaging cytometry without the limits of each, offering the biomedical research and clinical community a unique tool to address the needs for current and emerging applications. The key innovation is based on a significant extension of the spatial-coding algorithms our team demonstrated in the past years. In the proposed design, we create a special filter with a matrix of periodic slits in front of each PMT detector. The resulting PMT signal is composed of the multiplexed cell signals modulated by the filter, which can subsequently be deconvolved to produce fluorescence and scatter generated from different areas of the cell: the image. In addition, we add sweeping structured light with known positions over time to deconvolved information in the Z-axis, as well, allowing 3D image formation. In this Phase I program, we will integrate 3D imaging technology into our existing WOLF Cell Sorter to produce the very first 3D imaging cytometer with cell sorting capabilities. Since we use conventional, non-pixelated detectors (e.g. high-speed PMTs) found in conventional flow cytometers, this technology is compatible with existing flow cytometer architectures allowing for wide use. Equipped with cell imaging capabilities, researchers can track many important biological processes by analyzing not only the intensity but the localization of certain proteins within cytosolic, nuclear, or cell membrane domains and subdomains. With the rapidly developing capabilities of handling “big data”, 3D images of millions of single cells in a flow cytometer provide vast resources for research and disease analysis, and rapid growth has been predicted in the market of such high-content imaging cytometer cell sorters for emerging applications such as precision medicine. We believe the proposed design is a major breakthrough that can potentially revolutionize the field of flow cytometry, and its impact and ramifications on both fundamental biomedical research and clinical applications can be tremendous.

Public Health Relevance Statement:
3D Imaging Flow Cytometer NanoCellect Biomedical, Inc. RESEARCH & RELATED Other Project Information 8. PROJECT NARRATIVE The advances proposed here will allow NanoCellect to achieve its mission: to advance 3D image-based flow cytometry technology that can be placed in an affordable bench-top device. This will be achieved by integrating 3D cell-imaging and relevant software into an easy-to-use package that will extend the features of the existing WOLF® Cell Sorter platform.

Project Terms:
Address; Adopted; Algorithmic Software; Algorithms; Architecture; Area; Back; base; Benchmarking; Big Data; Biochemical; Biological Assay; Biological Process; Biomedical Research; Cell Cycle; Cell membrane; Cell Nucleus; Cell Separation; Cell Size; Cell surface; Cell Volumes; Cells; Cellular biology; cellular imaging; Characteristics; Chinese Hamster Ovary Cell; Chromatin; Classification; Clinical; clinical application; Code; Collection; Color; commercialization; Communities; Computer software; Computing Methodologies; cost; Cytoplasm; design; design and construction; Detection; detector; Devices; Disease; experience; experimental study; Flow Cytometry; Fluorescence; Fluorescence-Activated Cell Sorting; Formulation; Frequencies; Future; gene therapy; high throughput analysis; Histones; Hour; Image; Image Analysis; Image Cytometry; imaging capabilities; Imaging technology; Individual; innovation; interest; Intuition; Light; Mathematics; Measures; Membrane; Methods; Microfluidics; Microscopic; microscopic imaging; Mission; Mitochondria; Mitosis; Motion; Nuclear; Nuclear Envelope; Optics; Organelles; Patients; Periodicity; Pharmaceutical Preparations; Pharmacologic Substance; Phase; Phenotype; photomultiplier; Photons; Physiological; Ploidies; Positioning Attribute; precision medicine; prevent; programs; Property; Proteins; prototype; rapid growth; Reporter; Research; Research Personnel; Resolution; Resources; response; Rotation; Sampling; sensor; Shapes; Signal Transduction; Sorting - Cell Movement; Speed; Standardization; Structure; Suspensions; System; Technology; Three-Dimensional Image; Three-Dimensional Imaging; Time; tool; Transfection; Tube; User-Computer Interface; Validation; Vision; Work

The primary goal of the proposed research is to demonstrate a high throughput flow cytometer system that can sort cells based on high-content 3D cell image features. For each single cell flowing in a microfluidic channel, the system will produce cell tomography from spatially resolved fluorescent and scattering signals at a rate of 1000 cells/s. Each multi-parameter 3D cell image will be reconstructed, hundreds of image features will be extracted, and cells with their spatial features meeting the user-defined criteria will be sorted (3D image-guided cell sorting). Essentially the proposed system combines the merits of high throughput cell analysis and sorting capabilities of a fluorescence-activated cell sorter (FACS) with a high-content 3D imaging microscope to offer researchers and clinicians unprecedented features and capabilities to analyze, classify, and isolate cells at single cell resolution. The invention of this tool is anticipated to transform cell phenotype studies, greatly accelerate cell type discoveries, and enhance studies of highly heterogeneous biological samples such as tumors and brain. To realize such ambitious goal, we will take several innovative approaches. To produce high-quality 3D cell images for individual cells travelling fast in a flow channel, we invent a camera-less imaging system using a design that combines scanning structured light excitation and the scheme of confocal detection, which transforms 3D spatial information into temporal signals at the output of high-speed photomultiplier tubes (PMTs). For cell sorting mechanism, we adopt a microfluidic chip/cartridge design with an on-chip piezoelectric actuator to sort cells without causing flow jitters that can disrupt imaging of cells passing the optical imaging area. To achieve real-time image processing and image feature extraction, as well as handling the transport and storage of the large amount of 3D cell image data, we propose an electronic system consisting of a field programmable gate array (FPGA) module and graphics processing unit (GPU), having the FPGA process PMT signals, cell detection, segmentation and image reconstruction, and sorting decision control while having the GPU extract hundreds of 3D image related features and define sorting criteria (i.e. 3D image- guided gating) in parallel. To evaluate the performance of the system, we will perform experiments to sort cells based on the properties of protein translocation and trafficking, spot counting, organelle tracking, and features that help understand the disease biology and drug development. The proposed instrument will offer biomedical community a powerful tool to advance phenotype studies and cell type discoveries, and to link gene expression studies to cell phenotypic characteristics at single cell resolution and high throughput. The impact of the research will be significant and profound.

Public Health Relevance Statement:
NanoCellect Biomedical, Inc. RESEARCH & RELATED Other Project Information 8. PROJECT NARRATIVE The advances proposed here will allow NanoCellect to achieve its mission: to advance 3D image-guided fluorescence-activated cell sorting technology that can be placed in an affordable bench-top device. This will be achieved by integrating 3D cell-imaging and cell-sorting, and relevant software into an easy-to-use package that extends the features of the existing WOLF® Cell Sorter.

NIH Spending Category:
Bioengineering; Biomedical Imaging; Biotechnology; Drug Abuse (NIDA only); Substance Abuse

Project Terms:
3-Dimensional; Adopted; analog; Area; base; Biological; Biological Assay; Biology; Biotechnology; Brain; Cell Separation; cell transformation; cell type; Cells; cellular imaging; Characteristics; Communities; Computer software; Computer Systems; computerized data processing; Data; data acquisition; Data Set; design; Detection; Development; Devices; Disease; DNA Damage; drug development; Electronics; experimental study; fluorescence activated cell sorter device; Fluorescence-Activated Cell Sorting; Gene Expression; Genomics; Goals; Image; image guided; image processing; image reconstruction; imaging system; improved; Individual; innovation; instrument; interest; invention; Ionizing radiation; Ions; Light; Lighting; Link; Medical; meetings; Microfluidic Microchips; Microfluidics; microscopic imaging; Microscopy; Mission; next generation sequencing; novel; Nuclear; optical imaging; Optics; Organelles; Output; Performance; Phase; Phenotype; photomultiplier; Process; programs; Property; Protein translocation; protein transport; prototype; real-time images; Real-Time Systems; remote control; Research; Research Design; Research Personnel; Resolution; Sampling; Scanning; Scheme; Signal Transduction; Sorting - Cell Movement; Speed; Spottings; Structure; Support System; Supporting Cell; System; Technology; Three-Dimensional Image; Three-Dimensional Imaging; Time; tomography; tool; transcription factor; transcriptomics; Travel; Tube; tumor; Validation