Spatially visualized single-cell pathology of highly multiplexed protein profiles in health and disease
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BIOE MEDIA LAB |
Virtual and Augmented Reality for Biomedical Applications
Cell Reports Medicine (2020)
Mythreye Venkatesan, Harini Mohan, Justin Ryan, Christian Schuerch, Garry Nolan, David Frakes, and Ahmet F. Coskun
Three-dimensional visualization technologies such as virtual reality (VR), augmented reality (AR), and mixed reality (MR) have gained popularity in the recent decade. These extended reality (XR) modalities are immersive and interactive, helping in the 3D rendering of biological and medical content without the constraint of a conventional observation screen. Digital XR technologies have been adopted in a wide variety of domains ranging from entertainment to education due to their accessibility and affordability. Herein we provide a perspective on the use of XR in current biomedical applications and demonstrate case studies using cell biology concepts, multiplexed proteomic images, surgical data for heart operations, and cardiac 3D models. Emerging challenges associated with XR technologies in the context of adverse health effects and a cost comparison of distinct platforms are discussed. The presented XR platforms will be useful for biomedical education, medical training, surgical guidance, and data visualization of molecular data to enhance the learning of trainees and students, accuracy of medical operations, and comprehensibility of complex biological systems.
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PUBLIC HEALTH |
COVID-19 Diagnostics, Tools, and Prevention
Diagnostics (2020) [PDF] Special Issue "Virus Diagnostic Methods: Learning from the COVID-19 Global Outbreak"
Mayar Allam, Shuangyi Cai, Shambavi Ganesh, Mythreye Venkatesan , Saurabh Doodhwala, Zexing Song, Thomas Hu Kaiwen, Aditi Kumar, Jeremy Heit, Kasfia Kazi, Pushti Desai, Shivam Patel, Harini Mohan, Melissa Ozbeyler, Samuel Henderson, Andrew Borst, Beliz Utebay, and Ahmet F. Coskun
The Coronavirus Disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), outbreak from Wuhan City, Hubei province, China in 2019 has become an ongoing global health emergency. The emerging virus, SARS-CoV-2, causes coughing, fever, muscle ache, and shortness of breath or dyspnea in symptomatic patients. The pathogenic particles that are generated by coughing and sneezing remain suspended in the air or attach to a surface to facilitate transmission in an aerosol form. This review focuses on the recent trends in pandemic biology, diagnostics methods, prevention tools, and policies for COVID-19 management. To meet the growing demand for medical supplies during the COVID-19 era, a variety of personal protective equipment (PPE) and ventilators have been developed using do-it-yourself (DIY) manufacturing. COVID-19 diagnosis and the prediction of virus transmission are analyzed by machine learning algorithms, simulations, and digital monitoring. Until the discovery of a clinically approved vaccine for COVID-19, pandemics remain a public concern. Therefore, technological developments, biomedical research, and policy development are needed to decipher the coronavirus mechanism and epidemiological characteristics, prevent transmission, and develop therapeutic drugs.
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SPATIAL METABOLOMICS |
Spatially resolved 3D metabolomic profiling in tissues
Science Advances, In revision
Shambavi Ganesh, Thomas Hu, Eric Woods, Mayar Allam, Shuangyi Cai, Walter Henderson, and Ahmet F. Coskun
Spatially-resolved RNA and protein molecular analyses have revealed surprising heterogeneity of cells. Metabolic analysis of individual cells has the potential to complement these single-cell studies. Herein, we present a 3D Spatially-resolved Metabolomics Framework, 3D-SMF, to map out the spatial organization of metabolites and cell-features in immune cells of human tonsils. In this method, 3D metabolic profiles were acquired by a Time-of-Flight Secondary Ion Mass Spectrometry (TOF-SIMS) instrument to profile up to 188 compounds. Ion beams were used to measure sub-10-nm layers of tissue through z-stacks with up to 150 sections of a tonsil. To incorporate cell-specificity, tonsil tissues were labeled by an isotope-tagged antibody library. To explore relations of metabolic and cellular features, data reduction, 3D spatial correlations, unsupervised K-means clustering, and network analyses were carried out. Immune cells exhibited spatially distinct lipidomics distributions in lymphatic tissue. The 3D-SMF pipeline impacts studying the immune cells in health and disease.
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SPATIAL BIOLOGY |
Cellular sociology regulates hierarchical spatial organization
Open Biology, under review
Shambavi Ganesh*, Beliz Utebay*, Jeremy Heit* & Ahmet F. Coskun
Advances in biotechnology have increasingly revealed interactions of cells with their surroundings, suggesting a cellular society at the microscale. Similarities between cells and humans across multiple hierarchical levels have inference potential for reaching quantitative insights. Here, the functional and structural comparisons between how cells and individuals fundamentally socialize to give rise to spatial organization are hypothesized. Integrative experimental and computational methods, coupled with emerging biochemical methodologies, shape the societal perspective of cellular interactions that create spatially coordinated forms in biological systems. Emerging quantitative models from simpler biological microworld and single cell organisms are investigated, providing a route to model spatio-temporal regulation of humans. This analogical reasoning framework sheds light on patterning principles of biological sociology from the cellular scale and up.
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SPATIAL COMBINATION THERAPY |
Multiplex Spatial Bioimaging for Combination Therapy Design
Trends in Cancer (2020) [PDF]
Shuangyi Cai*, Mayar Allam* & Ahmet F. Coskun
This paper presents combination therapies to address the current gap in the field of cancer therapies. Combination therapy administers synergistic drugs to patients for cancer treatments. However, a subset of patients remains unresponsive due to tumor heterogeneity. Combination therapy overcomes this problem to eliminate cancers with reduced off-targets, resistance, and relapse. Multiplex bioimaging aids in determining the molecular mechanisms in patient biopsies, informing the design of multi-drug therapies.
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SPATIAL OMICS: CANCER |
Multiplex bioimaging of single-cell spatial profiles for precision cancer diagnostics and therapeutics
NPJ Precision Oncology, vol 4, 11 (2020) [PDF]
Mayar Allam*, Shuangyi Cai* & Ahmet F. Coskun
Nature Research Cancer Community | Behind the Paper Story
Cancers exhibit functional and structural diversity in distinct patients. In this mass, normal and malignant cells create tumor microenvironment that is heterogeneous among patients. A residue from primary tumors leaks into the bloodstream as cell clusters and single cells, providing clues about disease progression and therapeutic response. The complexity of these hierarchical microenvironments needs to be elucidated. While tumors comprise ample cell-types, the standard clinical technique is still the histology that is limited to a single marker. Multiplexed imaging technologies open new directions in pathology. Spatially resolved proteomic, genomic, and metabolic profiles of human cancers are now possible at the single-cell level. This perspective discusses spatial bioimaging methods to decipher the cascade of microenvironments in solid and liquid biopsies. A unique synthesis of top-down and bottom-up analysis methods is presented. Spatial multi-omics profiles can be tailored to precision oncology through artificial intelligence. Data-driven patient profiling enables personalized medicine and beyond.
Cancers exhibit functional and structural diversity in distinct patients. In this mass, normal and malignant cells create tumor microenvironment that is heterogeneous among patients. A residue from primary tumors leaks into the bloodstream as cell clusters and single cells, providing clues about disease progression and therapeutic response. The complexity of these hierarchical microenvironments needs to be elucidated. While tumors comprise ample cell-types, the standard clinical technique is still the histology that is limited to a single marker. Multiplexed imaging technologies open new directions in pathology. Spatially resolved proteomic, genomic, and metabolic profiles of human cancers are now possible at the single-cell level. This perspective discusses spatial bioimaging methods to decipher the cascade of microenvironments in solid and liquid biopsies. A unique synthesis of top-down and bottom-up analysis methods is presented. Spatial multi-omics profiles can be tailored to precision oncology through artificial intelligence. Data-driven patient profiling enables personalized medicine and beyond.
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BIOE MEDIA LAB |
Digital posters for interactive cellular media and bioengineering education
Communications Biology, 2, 455 (2019) [PDF]
Mythreye Venkatesan & Ahmet F. Coskun
Georgia Tech BME News | Petit Institute News
Conventional posters are effective in disseminating progress reports in scientific meetings, but they fail to deliver the need for visualization of dynamic biological data and become costly with the increasing number of conferences and the reprinting needs for emerging research. Here we present digital posters that repurpose digital frames from the art community and experiment with multiplexed imaging movies of cells as a demonstration of the digital poster concept, providing an interactive and low-cost tool for next-generation sharing platforms.
Conventional posters are effective in disseminating progress reports in scientific meetings, but they fail to deliver the need for visualization of dynamic biological data and become costly with the increasing number of conferences and the reprinting needs for emerging research. Here we present digital posters that repurpose digital frames from the art community and experiment with multiplexed imaging movies of cells as a demonstration of the digital poster concept, providing an interactive and low-cost tool for next-generation sharing platforms.
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BARCODED BIOIMAGING |
Isotopically encoded nanotags for multiplexed ion beam imaging
Advanced Materials Technology, 2000098 (2020) [PDF]
Stefan Harmsen*, Ahmet F. Coskun*, Shambavi Ganesh, Garry P. Nolan and Sam Gambhir
High-dimensional profiling of markers and analytes using approaches such as barcoded fluorescent imaging with repeated labeling and mass cytometry has allowed visualization of biological processes at the single-cell level. To address limitations of sensitivity and mass-channel capacity, we have developed a nano-barcoding platform for multiplexed ion beam imaging (MIBI) using secondary ion beam spectrometry that utilizes fabricated isotopically encoded nanotags. Use of combinatorial isotope distributions in 100-nm-sized nanotags expanded the labeling palette to overcome the spectral bounds of mass channels. As a proof-of-principle, a four-digit (i.e., 0001 to 1111) barcoding scheme was demonstrated to detect 16 variants of 2H, 15N, 19F, 79/81Br and 127I elemental barcode sets that were encoded in silica nanoparticle matrices. A computational debarcoding method and an automated machine learning analysis approach were developed to extract barcodes for accurate quantification of spatial nanotag distributions in large ion beam imaging areas up to 0.6 mm2. Isotopically encoded nanotags should boost the performance of mass imaging platforms such as MIBI and other elemental-based bioimaging approaches.
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SPATIAL METABOLOMICS |
Ion Beam Tomography: Biocomputation for Nanoscopic Subcellular Imaging, BioRxiv, 2019
Nature Communications, Under Review
Ahmet F. Coskun, Guojun Han, Shambavi Ganesh, Shih-Yu Chen , Xavier Rovira-Clave, Stefan Harmsen, Sizun Jiang , Christian Schürch , Yunhao Bai , Chuck Hitzman and Garry P. Nolan
Multiplexed ion beam imaging (MIBI) has been previously used to profile multiple parameters in two dimensions in single cells within tissue slices. Here, a mathematical and technical framework for three-dimensional subcellular MIBI is presented. We term the approach ion beam tomography (IBT) wherein ion beam images are acquired iteratively across successive, multiple scans, and later compiled into a 3D format. For IBT, cells were imaged at 0.2-4 pA ion current across 1,000 axial scans. Consecutive subsets of ion beam images were binned over 3 to 20 slices (above and below) to create a high contrast image, wherein binning was incremented one slice at a time to yield an enhanced multi-depth data without loss of depth resolution. Algorithmic deconvolution, tailored for ion beams, was then applied to the transformed ion image series using a hybrid deblurring algorithm and an ion beam current-dependent point-spread function. The deconvolution routine yielded 4-fold enhanced ion beam data cubes. To further generate 3D super-resolved (sub-ion-beam diffraction limit) visuals, a subset of ion beam images was processed by localization of isolated ion molecules in the raw ion beam images, an approach coined as SILM, super-resolution ion beam localization microscopy. SILM achieved up to sub-25-nm accuracy in original ion images. As an alternative strategy, using deep learning on a trained network between the raw ion image stacks (low-resolution) and SILM results (high-resolution), a parameter-free reconstruction method for super-resolved ion tomograms was developed for low-density targets. Post-processing was implemented by spatially resolved 3D clustering, molecular neighborhoods, and association maps. In cultured cancer cells and tissues, IBT enabled accessible visualization of three-dimensional volumetric distributions of genomic regions, RNA transcripts, and protein factors with 5-nm axial resolution. IBT also enabled label-free elemental mapping of cells, allowing “point of source” cellular component measurements not possible for most optical microscopy targets. Detailed multiparameter imaging of subcellular features at near macromolecular resolution should now be made possible by the IBT tools and reagents provided here to open novel avenues for interrogating subcellular biology. IBT is a general biocomputation pipeline to handle molecular image arrays acquired by mass spectrometry imaging and secondary ion beam spectrometry methods.
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SPATIAL PROTEOMICS |
Multiplexed protein and drug imaging by super-resolution ion beam imaging,
Nature Communications, In revision
BioRxiv, 2019
Simultaneous visualization of the relationship between multiple biomolecules and their ligands or small molecules at the nanometer scale in cells will enable greater understanding of how biological processes operate. Current fluorescence-based microscopy methods for biomolecules in cells are constrained by the spatial resolution limitations, parameters per experiment, and detector systems. We apply here super-resolution ion beam imaging (srIBI), a secondary ion mass spectrometry approach capable of high-parameter imaging in 3D of targeted biological entities and exogenously added small molecules. With this technology, the atomic constituents of the biomolecules themselves can be used in our system as the “tag” and we demonstrate measurements down to ~30 nm lateral resolution. We correlated the subcellular localization of the chemotherapy drug cisplatin simultaneously with five subnuclear structures, including, notably, nuclear speckles, wherein processing of RNA introns occurs. RNAseq analysis of cells treated with cisplatin demonstrated increased aberrant splicing of certain polyA terminated transcripts, suggesting that nuclear speckle localization of cisplatin is a newly discovered determinant of cisplatin anti-cancer efficacy. Unexpectedly, cells surviving multi-drug treatment with cisplatin and the BET inhibitor JQ1 demonstrated near total cisplatin exclusion from the nucleus, suggesting that selective subcellular drug relocalization might modulate resistance to this important chemotherapeutic treatment. Multiplexed high-resolution imaging techniques, such as srIBI, will enable studies of biomolecule and drug distributions in biologically relevant subcellular microenvironments by visualizing the processes themselves in concert, rather than inferring mechanism through surrogate analyses.
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SPATIAL GENOMICS |
Dense transcript profiling in single cells by image correlation decoding,
Nature Methods 2016
Sequential barcoded fluorescent in situ hybridization (seqFISH) allows large numbers of molecular species to be accurately detected in single cells, but multiplexing is limited by the density of barcoded objects. We present correlation FISH (corrFISH), a method to resolve dense temporal barcodes in sequential hybridization experiments. Using corrFISH, we quantified highly expressed ribosomal protein genes in single cultured cells and mouse thymus sections, revealing cell-type-specific gene expression.
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SPATIAL GENOMICS |
Single-cell in situ RNA profiling by sequential hybridization,
Nature Methods 2014
In this Correspondence, we present a sequential barcoding scheme to multiplex different mRNAs.Here, the mRNAs in cells are barcoded by sequential rounds of hybridization, imaging and probe stripping. As the transcripts are fixed in cells, the corresponding fluorescent spots remain in place during multiple rounds of hybridization and can be aligned to read out a fluorophore sequence. This sequential barcode is designed to uniquely identify an mRNA
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BIOIMAGING |
Wide-field optical detection of nanoparticles using on-chip microscopy and self-assembled nanolenses,
Nature Photonics 2013
The direct observation of nanoscale objects is a challenging task for optical microscopy because the scattering from an individual nanoparticle is typically weak at optical wavelengths. Electron microscopy therefore remains one of the gold standard visualization methods for nanoparticles, despite its high cost, limited throughput and restricted field-of-view. Here, we describe a high-throughput, on-chip detection scheme that uses biocompatible wetting films to self-assemble aspheric liquid nanolenses around individual nanoparticles to enhance the contrast between the scattered and background light. We model the effect of the nanolens as a spatial phase mask centred on the particle and show that the holographic diffraction pattern of this effective phase mask allows detection of sub-100 nm particles across a large field-of-view of >20 mm2. As a proof-of-concept demonstration, we report on-chip detection of individual polystyrene nanoparticles, adenoviruses and influenza A (H1N1) viral particles.
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BIOIMAGING |
Imaging without lenses: achievements and remaining challenges of wide-field on-chip microscopy,
Nature Methods 2012
We discuss unique features of lens-free computational imaging tools and report some of their emerging results for wide-field on-chip microscopy, such as the achievement of a numerical aperture (NA) of ∼0.8–0.9 across a field of view (FOV) of more than 20 mm2 or an NA of ∼0.1 across a FOV of ∼18 cm2, which corresponds to an image with more than 1.5 gigapixels. We also discuss the current challenges that these computational on-chip microscopes face, shedding light on their future directions and applications.
