Subcellular 3D spatially resolved transcriptional density and function of single cells
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SPATIAL PROTEOMICS |
Spatially visualized single-cell pathology of highly multiplexed protein profiles in health and disease
Communications Biology, 4, 632 (2021) [Link]
Mayar Allam, Thomas Hu, Shuangyi Cai, Krishman Laxminarayanan, Robert B. Hughley, and Ahmet F. Coskun
Deep molecular profiling of biological tissues is an indicator of health and disease. As one of the mainstream technologies, we used imaging mass cytometry (IMC) to acquire 20-plex spatially resolved, multiparameter protein data in tissue sections from normal and chronic tonsillitis cases. To quantify this high-dimensional IMC data, herein we present SpatialViz, a suite of algorithms to explore spatial relationships in multiplexed tissue images using the nexus of single-cell quantifications as a bottom-up method and computational pathology of anatomical distributions as a top-down strategy. Single-cell and spatial maps confirmed that CD68+ cells were correlated with the enhanced Granzyme B expression and CD3+ cells exhibited enrichment of CD4+ phenotype in chronic tonsillitis. SpatialViz revealed morphological distributions of cellular organizations in distinct anatomical areas and spatially resolved associations of single-cells by intra-cluster and the inter-cluster analysis across anatomical categories. Spatial proximity analysis showed distance maps between the marker-pairs. Spatial topographic maps showed the distinct organization of tissue layers with unique multiplex marker profiles. The spatial reference framework generated network-based comparisons of multiplex data from health and diseased tonsils. SpatialViz is a general pipeline to visualize and quantify single-cell granularity and anatomical complexity in diverse multiplexed tissue imaging data.
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SPATIAL METABOLOMICS |
Spatially resolved 3D metabolomic profiling in tissues
Science Advances, Vol. 7, no. 5, eabd0957 (2021) [Link]
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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SINGLE CELL ANALYSIS |
Single-cell analysis reveals effective siRNA delivery in brain tumors with microbubble-enhanced ultrasound and cationic nanoparticles
Science Advances (2021) Vol. 7, no. 18, eabf7390 DOI: 10.1126/sciadv.abf7390 [Link]
Yutong Guo, Hohyun Lee, Zhou Fang, Anastasia Velalopoulou, Jinhwan Kim, Midhun Ben Thomas, Jingbo Liu, Ryan G. Abramowitz, YongTae Kim, Ahmet F. Coskun, Daniel Pomeranz Krummel, Soma Sengupta, Tobey J. MacDonald and Costas Arvanitis
RNA-based therapies offer unique advantages for treating brain tumors. However, tumor penetrance and uptake are hampered by RNA therapeutic size, charge, and need to be “packaged” in large carriers to improve bioavailability. Here, we have examined delivery of siRNA, packaged in 50-nm cationic lipid-polymer hybrid nanoparticles (LPHs:siRNA), combined with microbubble-enhanced focused ultrasound (MB-FUS) in pediatric and adult preclinical brain tumor models. Using single-cell image analysis, we show that MB-FUS in combination with LPHs:siRNA leads to more than 10-fold improvement in siRNA delivery into brain tumor microenvironments of the two models. MB-FUS delivery of Smoothened (SMO) targeting siRNAs reduces SMO protein production and markedly increases tumor cell death in the SMO-activated medulloblastoma model. Moreover, our analysis reveals that MB-FUS and nanoparticle properties can be optimized to maximize delivery in the brain tumor microenvironment, thereby serving as a platform for developing next-generation tunable delivery systems for RNA-based therapy in brain tumors.
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SUBCELLULAR SPATIAL OMICS |
Nanoscopic subcellular imaging enabled by Ion Beam Tomography
Nature Communications volume 12, Article number: 789 (2021) [Link]
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 (3D) subcellular MIBI is presented. Ion beam tomography (IBT) compiles ion beam images that are acquired iteratively across successive, multiple scans, and later assembled into a 3D format without loss of depth resolution. Algorithmic deconvolution, tailored for ion beams, is then applied to the transformed ion image series, yielding 4-fold enhanced ion beam data cubes. To further generate 3D sub-ion-beam width precision visuals, isolated ion molecules are localized in the raw ion beam images, creating an approach coined as SILM, secondary ion beam localization microscopy, providing sub-25-nm accuracy in original ion images. Using deep learning, a parameter-free reconstruction method for ion beam tomograms with high accuracy is developed for low-density targets. In cultured cancer cells and tissues, IBT enables accessible visualization of 3D volumetric distributions of genomic regions, RNA transcripts, and protein factors with 5-nm axial resolution using isotope-enrichments and label-free elemental analysis. Multiparameter imaging of subcellular features at near macromolecular resolution is implemented by the IBT tools as a general biocomputation pipeline for imaging mass spectrometry.
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SPATIAL PROTEOMICS AND PHARMACO-IMAGING |
Subcellular localization of biomolecules and drug distribution by high-definition ion beam imaging, Nature Communications, 12, 4628 (2021).
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. We present here high-definition multiplex ion beam imaging (HD-MIBI), a secondary ion mass spectrometry approach capable of high-parameter imaging in 3D of targeted biological entities and exogenously added structurally-unmodified 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. Cisplatin was preferentially enriched in nuclear speckles and excluded from closed-chromatin regions, indicative of a role for cisplatin in active regions of chromatin. 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 may modulate resistance to this important chemotherapeutic treatment. Multiplexed high-resolution imaging techniques, such as HD-MIBI, will enable studies of biomolecules 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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BIOE MEDIA LAB |
Virtual and Augmented Reality for Biomedical Applications
Cell Reports Medicine, DOI: 10.1016/j.xcrm.2021.100348 (2021) [Link]
Mythreye Venkatesan, Harini Mohan, Justin Ryan, Christian Schuerch, Garry Nolan, David Frakes, and Ahmet F. Coskun
3D visualization technologies such as virtual reality (VR), augmented reality (AR), and mixed reality (MR) have gained popularity in the recent decade. Digital extended reality (XR) technologies have been adopted in
various domains ranging from entertainment to education because of their accessibility and affordability. XR modalities create an immersive experience, enabling 3D visualization of the content without a conventional 2D display constraint. Here, we provide a perspective on XR in current biomedical applications and demonstrate case studies using cell biology concepts, multiplexed proteomics 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 molecular data visualization to enhance trainees’ and students’ learning, medical operation accuracy, and the comprehensibility of complex biological systems.
various domains ranging from entertainment to education because of their accessibility and affordability. XR modalities create an immersive experience, enabling 3D visualization of the content without a conventional 2D display constraint. Here, we provide a perspective on XR in current biomedical applications and demonstrate case studies using cell biology concepts, multiplexed proteomics 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 molecular data visualization to enhance trainees’ and students’ learning, medical operation accuracy, and the 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 BIOLOGY |
Cellular sociology regulates the hierarchical spatial patterning and organization of cells in organisms
Open Biology, (2020) [PDF]
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 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.
