Service Projects
SP1: Dissecting the pathogenesis and outcomes of PSC using multi-omics by studying the exposome and genome (FORMER)
Investigators: Ravi Iyer and Kostas Lazaridis - subcontract Grant Number NIH 1RC2DZK118619-01 Funding Period: 9/1/18-7/31/20
Description: In the current project we generate the first multi-omics translational study and comprehensive data resources for Primary Sclerosing Cholangitis (PSC), a chronic, progressive liver disease without effective medical therapy. PSC reduces survival, is highly associated with inflammatory bowel disease and strongly predisposes to cholangiocarcinoma (i.e. bile duct cancer) and colon cancer. Our proposal is predicated on the hypothesis that multi-omics analyses of data capturing environmental exposures and the associated biological responses (i.e. the exposome), including interaction with the genome, will reveal networks or pathways influencing PSC pathogenesis and outcomes.
Push: We will use label-free imaging (interferometry, spectroscopy, nonlinear) of liver sections to add a new channel of data to improve our predictive models. The new data streams will be combined with the observed correlations among different variables into a unifying framework to boost the performance of our forecast accuracy of PSC outcomes.
SP2: (Past) Diffuse fast optical imaging for cognitive neuroscience (FORMER)
Investigators: Gabriele Gratton and Monica Fabiani; Grant Numbers: NIA R01 AG059878, NIA RF AG062666; Funding periods: 2018/2019-2023/2024
Description: The goal of the two current projects is to study the relationships between changes in cerebral arterial stiffness, as measured with diffuse optical tomography (DOT), and cognitive aging, a possible precursor of Alzheimer Disease. The first of these grants investigates the role of a series of risk factors for cerebral arteriosclerosis in brain structural and cognitive decline. The second investigates the effects of cerebral arteriosclerosis on age-related declines in cerebral function, with focus on cognitive control, a function related to goal directed behavior, central to cognitive performance, and linked to the ability to quickly switch on and off or maintain brain representations related to complex task demands.
Push: The technologies developed in TRDs 1-3 will be used to achieve fast optical imaging of neural function based on intrinsic scattering signals that are associated with brain activity, including cognitive processes. The instruments developed within TRDs 1-2 will boost our understanding of how these micrometer level conformational changes lead to changes at the millimeter level scattering properties of cortical tissue investigated using diffuse optical. Computational imaging and intelligent specificity (TRD 3) will boost the spatial specificity and signal-to-noise ratio of diffuse fast optical imaging methods, both issues that currently limit their widespread use.
SP3: Studying DNA replication and damage response using PICS (FORMER)
Investigators: Supriya Prasanth, Cell and Developmental Biology, University of Illinois - Urbana-Champaign; Grant Number 1R01 GM125196-01; Funding Period: 8/1/2018-5/31/2022.
Description: Errors in DNA replication and repair mechanisms are deleterious and cause genetic aberrations leading to malignant cellular transformation and tumorigenesis. Origin recognition complex (ORC) proteins are critical for the initiation of DNA replication. Mutations within several Orc genes, including Orc1, Orc4 and Orc6, have also been linked to Meier Gorlin Syndrome, a rare genetic disorder in children characterized by primordial dwarfism. The goal of this project is to understand how Origin Recognition Complex (ORC) executes and coordinates various aspects of cell growth, including cell proliferation and survival.
Push: We will the SLIM and GLIM technology augmented by artificial intelligence (PICS) to image the dynamics of DNA replication and DNA damage response in unlabeled cells. We will also test the capability of PICS to identify DNA damage foci during the cell cycle without photodamage or toxicity.
SP4: Ultrasensitive chemical microscopy by interferometric probing of photothermal effects (FORMER)
Investigator: Ji-Xin Cheng, Boston University; Grant Number 5R01GM126049-02; Funding Period: 9/6/2018-7/31/2022.
Description: Our scientific premise is that after the mid-infrared photons induce the molecule to vibrate, the subsequent vibrational relaxation into heat causes a local change of the refractive index. Such change creates a phase delay and a thermal lens, both of which can be detected at sub-micron spatial resolution by a visible probe beam. In a collaboration with the Bhargava Lab, we have proven the principle of “Bond-selective transient phase imaging”, which reached an imaging speed of 50 fps, a lateral resolution of 0.5 micrometers, and micro-molar detection sensitivity for the endogenous C=O bond (Light: Science & Applications 8(1): 1-12, 2019).
Push: The collaborators will apply the ultrasensitive phase imaging developed at the CLIMB Center (TRDs 1, 3) to further improve the detection sensitivity of the photothermal imaging. We will combine a GLIM with an IR pump to achieve high-throughput label-free chemical imaging in thick specimens.
SP4: Smartphone-linked system for diagnosis and epidemiological reporting of pathogens at the point of care (FORMER)
Investigators: B.T. Cunningham, R. Bashir, M. Do, UIUC; Grant Number: R01AI139401, Funding Period: 9/2019 – 9/2023
Description: The project will develop a smartphone-based handheld instrument, microfluidic cartridge, and cloud-based service system for detection and reporting the presence and concentration of a panel of viral pathogens (Zika, Dengue, and, now, COVID-19) from whole blood. Using chemical lysis, the system will yield results in less than 10 minutes, using automated image processing of acquired fluorescence image sequences of the LAMP reactions in the cartridge. The platform is a sensitive, inexpensive, and rapid point-of-care tool for detection and reporting of infectious disease to facilitate physician communication with the patient and epidemiological management by health authorities.
Push: The phase imaging with computational specificity (PICS) developed in TRDs 1, 3 will enable intact viral pathogens to be detected through their optical scattering characteristics, so they can be rapidly counted with digital precision by a simple label-free assay protocol. We envision a single-step assay approach and low-cost optical detection instrument that can be deployed in point-of-care diagnostic settings.
SP6: Machine-learning-based Optimization of Fluorescence Imaging in The Analysis of Adipose Tissue
Investigator: Andrew Smith, University of Illinois - Urbana-Champaign; Grant Number R01DK139924, R01CA288207; Funding Period: 6/25/24 – 5/31/29, 4/1/24 – 3/31/29.
Description: State-of-the-art deep neural networks and statistical learning techniques will be employed to correlate diagnostic information from biomarkers of inter-droplet structures with morphological information from close-packed lipid droplets. The overall goals are to employ learned virtual contrast to reduce the number of fluorescence labels needed to characterize adipose tissue and to begin data collection for the future study of the role of purely label-free imaging in adipose tissue characterization.
Push: Neural-network-based image-to-image translation will be employed at CLIMB to translate images of the interstitial labels to images of the lipid droplets; this is a sort of virtual lipid imaging. The utility of virtual lipid imaging in the classification of various stages of adipose tissue growth and contraction will be evaluated using modern statistical image analysis by CLIMB personnel. CLIMB personnel also will supervise the development of a digital image processing and analysis toolbox (TRD3) to automatically detect the potential crown-like structures, and analyze the relation of detected structures to the observed lipid morphology. The immediate goal is to enable Dr. Smith’s group to more robustly and more rapidly interpret their current image data; the ultimate goal is to enable them to make better use of their channel-limited imaging by obviating one of the colorimetric markers. The analysis techniques employed for this project also will be of use to the greater obesity research community studying the changes in adipose tissue with diet.
The service project has at least one additional synergy with CLIMB. The Smith Lab shall provide both adipose tissue samples and their own fluorescence imaging of those samples. Team members from TRD1 will image parts of these samples via quantitative phase imaging (QPI). QPI provides label-free visualization of adipose tissue, which complements confocal fluorescence imaging. The paired QPI and fluorescence images will be used for future development of virtual staining of label-free images. CLIMB will package, archive, and share these valuable data for future research in computational label-free imaging.
SP7: Enhancer RNAs Boost MYC-Chromatin Interaction to Regulate Gene Expression and Tumorigenesis
Investigators: Da Yang, University of Pittsburgh; Grant Number R01CA282704, Funding Period: 09/01/2023-08/02/2028
Description: This project focuses on understanding how MYC, a frequently activated oncogene, functions as a master regulator of nuclear condensation. Building on evidence that MYC binds both DNA and RNA—particularly chromatin-associated RNAs such as eRNAs—this project aims to elucidate how these interactions enable MYC to drive oncogenic gene expression. By manipulating MYC’s RNA-binding domain and evaluating its effects on chromatin occupancy, nuclear condensation, and transcriptional regulation, the project seeks to uncover fundamental mechanisms of tumorigenesis and develop novel strategies for targeting MYC in cancer.
Push: CLIMB will “push” its quantitative phase imaging (QPI) methods (TRD 1) into studies of how MYC influences nuclear condensation. By applying QPI in MYC-positive cells and variants with altered MYC DNA- or RNA-binding domains, CLIMB can capture real-time, label-free measurements of nuclear density changes, illuminating the structural and functional impact of MYC-driven RNA and DNA interactions. Preserving the native cellular environment, QPI supplements fluorescence-based imaging, thereby deepening insights into MYC-mediated nuclear reorganization.
SP8: Chemical-selective real-time laser precision control of biomolecules
Investigators: Chi Zhang, Purdue University; Grant Number R35GM147092, Funding Period: 09/01/2022-06/30/2027
Description: This project develops a real-time precision opto-control (RPOC) platform that can detect, select, and laser‑manipulate specific biomolecular targets inside living cells with sub‑micron spatial precision and nanosecond response times. By reading an optical signature (fluorescence, Raman, absorption, etc.) at each scanned pixel and instantly gating an interaction laser via acousto‑optic control and digital logic, RPOC overcomes the spatial, temporal, and throughput limits of chemical, genetic, and conventional laser methods. The goal is to enable the on-demand activation, inhibition, or ablation of defined molecular pools in highly dynamic biological systems, thereby advancing studies of enzyme regulation, organelle interactions, drug release, and neuromodulation.
Push: Integrating a wide-field quantitative phase imaging (QPI) module enables rapid, label-free mapping of cell and subcellular structures across large areas, accelerating the identification of regions of interest and minimizing pre-labeling. QPI-derived biophysical metrics (cell boundaries, mass density, and morphology state) can help RPOC’s workflow deliver context-aware, highly specific interventions. Continuous QPI readout also tracks morphological and biophysical responses to laser manipulation, supports drift correction and safety monitoring, and scales experiments from single cells to populations. A compact QPI add‑on would make the multicolor, portable RPOC platform more turnkey for broad biological use.
SP9: Application of label-free quantitative phase imaging to assess joint cellular morphology, mechanobiology, and growth kinetics in musculoskeletal systems
Investigators: Hai Yao, Peng Chen, Clemson University; Grant Number U01DE031512, R01DE021134, Funding Period: 01/15/2022-12/31/2026, 03/06/2012-01/31/2026
Description: This project employs a multi-domain, multiscale strategy that integrates joint 3D morphology, biomechanics, mechanobiology, and cellular metabolism to holistically study musculoskeletal joint diseases. Advanced human subject-specific multiscale computational models, combined with real-time assessments of joint motion, function, and sensor-based measurements, are utilized to predict and characterize joint biomechanics and the joint microenvironment. Moreover, tissue- and cell-level responses to joint biomechanics during movement will be quantified using state-of-the-art optical imaging technologies developed in our group and through CLIMB, enabling quantitative assessments that inform and refine the virtual human model. Collectively, this study aims to identify clinical risk factors, elucidate disease mechanisms, and guide surgical planning to ultimately improve joint health outcomes.
Push: CLIMB will “push” out the quantitative phase imaging system for label-free, quantitative single-cell dynamic assessment of dry mass, morphology, and density across joint cartilage and fibrocartilage samples under various mechanical and disease conditions. Spatial maps of dry-mass accumulation and morphological changes in quantitative phase imaging of live cells and tissue may serve as mechanobiological biomarkers that complement histology and molecular assays. QPI would assist correlative analyses of metabolic activities and cell fate at single-cell resolution, helping to assess joint health.
SP10: Assessment of membrane remodeling and multinuclear positioning during trophoblast fusion using label-free quantitative phase imaging
Investigators: Yingshi Ouyang, Children’s National Hospital & Research Institute and the George Washington University; Grant Number 7R01DA059176, Funding Period: 08/15/2023-07/31/2028
Description: The human placenta is a vital organ for maternal and fetal health throughout pregnancy. Multinucleated trophoblast cells, known as syncytiotrophoblasts, positioned at the out layer of the human placenta, play a central role in maternal-fetal gas exchange, transfer of nutrients and waste, hormone production and immunological defense. Disruption of trophoblast fusion often results in placental insufficiency, impacting fetal growth and development in significant ways. This project seeks to interrogate the dynamic changes in the plasma membrane and within intracellular nuclei during syncytin-mediated formation of multinucleated fusing cells in both normal and disease conditions. Our goal is to accelerate our knowledge gaps in trophoblast fusion and inform novel clinical approaches to major complications of pregnancy.
Push: The technology developed in TRD1 will be used to provide novel insights into aberrant trophoblast fusion that leads to placental insufficiency and fetal maldevelopment. Quantitative phase imaging enables single-cell and single-nucleus–level assessment of membrane and nuclear dynamics during fusion in both normal and pathological settings. Real-time, label-free imaging of trophoblast fusion will identify key signals in the transition from mononucleated to multinucleated cells and reveal how clinically relevant stressors such as hypoxia disrupt this process. Extension to 3D trophoblast organoid models will advance translational strategies for rescuing fusion defects and align with the NIH New Approach Methodologies framework.