Molecular fluorescent reporters for force and smart surfaces for sensing cell-surface interaction

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Chemistry, 2009.Cataloged from PDF version of thesis.Includes bibliographical references (p. 123-130).Molecular sensors are powerful because they make it possible to adapt the measurement to the sample instead of a sample to an instrument. Many reporter are available for measuring the chemical properties of a sample, but no purpose-built molecular sensors exist to report a sample's mechanical properties. To address recent interest in the mechanical coordinate of molecular interactions, we developed a prototype molecular sensor, calibrated its force-fluorescence relationship, and adapted the sensor to a cell adhesion assay. This thesis focuses on the considerations for combining force measurement with the environmental and distance sensitivity offered by fluorescence to measure cell-surface adhesion. We showed that DNA can be used as a scaffold to build a sensor molecule, that fluorescence can be used as a reporter of a threshold force, and that introducing cells to the sensor molecules changes the fluorescence properties. Because Cy3 experiences an enhanced intensity sensitivity when conjugated to DNA, the reporter's FRET signal was occluded and we instead activated the sensor complex as a novel, all-fluorescent means of reporting cell-surface proximity. This method for reporting cell-surface separation is significant because it simplifies measurements in thicker and more complex materials interesting to cell-substrate interaction studies.by Mariya Barch.Ph.D

Screen-Based Analysis of Magnetic Nanoparticle Libraries Formed Using Peptidic Iron Oxide Ligands

The identification of effective polypeptide ligands for magnetic iron oxide nanoparticles (IONPs) could considerably accelerate the high-throughput analysis of IONP-based reagents for imaging and cell labeling. We developed a procedure for screening IONP ligands and applied it to compare candidate peptides that incorporated carboxylic acid side chains, catechols, and sequences derived from phage display selection. We found that only l-3,4-dihydroxyphenylalanine (DOPA)-containing peptides were sufficient to maintain particles in solution. We used a DOPA-containing sequence motif as the starting point for generation of a further library of over 30 peptides, each of which was complexed with IONPs and evaluated for colloidal stability and magnetic resonance imaging (MRI) contrast properties. Optimal properties were conferred by sequences within a narrow range of biophysical parameters, suggesting that these sequences could serve as generalizable anchors for formation of polypeptide–IONP complexes. Differences in the amino acid sequence affected T[subscript 1]- and T[subscript 2]-weighted MRI contrast without substantially altering particle size, indicating that the microstructure of peptide-based IONP coatings exerts a substantial influence and could be manipulated to tune properties of targeted or responsive contrast agents. A representative peptide–IONP complex displayed stability in biological buffer and induced persistent MRI contrast in mice, indicating suitability of these species for in vivo molecular imaging applications.National Institutes of Health (U.S.) (Grant R01-DA28299)National Institutes of Health (U.S.) (Grant R01-NS76462)National Institutes of Health (U.S.) (Grant R21-MH102470)Japan Society for the Promotion of Science (Postdoctoral Fellowship for Research Abroad

Molecular imaging with engineered physiology

In vivo imaging techniques are powerful tools for evaluating biological systems. Relating image signals to precise molecular phenomena can be challenging, however, due to limitations of the existing optical, magnetic and radioactive imaging probe mechanisms. Here we demonstrate a concept for molecular imaging which bypasses the need for conventional imaging agents by perturbing the endogenous multimodal contrast provided by the vasculature. Variants of the calcitonin gene-related peptide artificially activate vasodilation pathways in rat brain and induce contrast changes that are readily measured by optical and magnetic resonance imaging. CGRP-based agents induce effects at nanomolar concentrations in deep tissue and can be engineered into switchable analyte-dependent forms and genetically encoded reporters suitable for molecular imaging or cell tracking. Such artificially engineered physiological changes, therefore, provide a highly versatile means for sensitive analysis of molecular events in living organisms.National Institute of Mental Health (U.S.) (R01-MH103160)National Institute of Mental Health (U.S.) (R01-NS076462)BRAIN Initiative (award R24-MH109081)Massachusetts Institute of Technology. Simons Center for the Social BrainBoehringer Ingelheim Fonds (predoctoral fellowships)McGovern Institute for Brain Research at MI

Automated four-dimensional long term imaging enables single cell tracking within organotypic brain slices to study neurodevelopment and degeneration.

Current approaches for dynamic profiling of single cells rely on dissociated cultures, which lack important biological features existing in tissues. Organotypic slice cultures preserve aspects of structural and synaptic organisation within the brain and are amenable to microscopy, but established techniques are not well adapted for high throughput or longitudinal single cell analysis. Here we developed a custom-built, automated confocal imaging platform, with improved organotypic slice culture and maintenance. The approach enables fully automated image acquisition and four-dimensional tracking of morphological changes within individual cells in organotypic cultures from rodent and human primary tissues for at least 3 weeks. To validate this system, we analysed neurons expressing a disease-associated version of huntingtin (HTT586Q138-EGFP), and observed that they displayed hallmarks of Huntington's disease and died sooner than controls. By facilitating longitudinal single-cell analyses of neuronal physiology, our system bridges scales necessary to attain statistical power to detect developmental and disease phenotypes

Assessing microscope image focus quality with deep learning

Background Large image datasets acquired on automated microscopes typically have some fraction of low quality, out-of-focus images, despite the use of hardware autofocus systems. Identification of these images using automated image analysis with high accuracy is important for obtaining a clean, unbiased image dataset. Complicating this task is the fact that image focus quality is only well-defined in foreground regions of images, and as a result, most previous approaches only enable a computation of the relative difference in quality between two or more images, rather than an absolute measure of quality. Results We present a deep neural network model capable of predicting an absolute measure of image focus on a single image in isolation, without any user-specified parameters. The model operates at the image-patch level, and also outputs a measure of prediction certainty, enabling interpretable predictions. The model was trained on only 384 in-focus Hoechst (nuclei) stain images of U2OS cells, which were synthetically defocused to one of 11 absolute defocus levels during training. The trained model can generalize on previously unseen real Hoechst stain images, identifying the absolute image focus to within one defocus level (approximately 3 pixel blur diameter difference) with 95% accuracy. On a simpler binary in/out-of-focus classification task, the trained model outperforms previous approaches on both Hoechst and Phalloidin (actin) stain images (F-scores of 0.89 and 0.86, respectively over 0.84 and 0.83), despite only having been presented Hoechst stain images during training. Lastly, we observe qualitatively that the model generalizes to two additional stains, Hoechst and Tubulin, of an unseen cell type (Human MCF-7) acquired on a different instrument. Conclusions Our deep neural network enables classification of out-of-focus microscope images with both higher accuracy and greater precision than previous approaches via interpretable patch-level focus and certainty predictions. The use of synthetically defocused images precludes the need for a manually annotated training dataset. The model also generalizes to different image and cell types. The framework for model training and image prediction is available as a free software library and the pre-trained model is available for immediate use in Fiji (ImageJ) and CellProfiler

Automated four-dimensional long term imaging enables single cell tracking within organotypic brain slices to study neurodevelopment and degeneration.

Current approaches for dynamic profiling of single cells rely on dissociated cultures, which lack important biological features existing in tissues. Organotypic slice cultures preserve aspects of structural and synaptic organisation within the brain and are amenable to microscopy, but established techniques are not well adapted for high throughput or longitudinal single cell analysis. Here we developed a custom-built, automated confocal imaging platform, with improved organotypic slice culture and maintenance. The approach enables fully automated image acquisition and four-dimensional tracking of morphological changes within individual cells in organotypic cultures from rodent and human primary tissues for at least 3 weeks. To validate this system, we analysed neurons expressing a disease-associated version of huntingtin (HTT586Q138-EGFP), and observed that they displayed hallmarks of Huntington's disease and died sooner than controls. By facilitating longitudinal single-cell analyses of neuronal physiology, our system bridges scales necessary to attain statistical power to detect developmental and disease phenotypes

Exceedingly small iron oxide nanoparticles as positive MRI contrast agents

Medical imaging is routine in the diagnosis and staging of a wide range of medical conditions. In particular, magnetic resonance imaging (MRI) is critical for visualizing soft tissue and organs, with over 60 million MRI procedures performed each year worldwide. About one-third of these procedures are contrast-enhanced MRI, and gadolinium-based contrast agents (GBCAs) are the mainstream MRI contrast agents used in the clinic. GBCAs have shown efficacy and are safe to use with most patients; however, some GBCAs have a small risk of adverse effects, including nephrogenic systemic fibrosis (NSF), the untreatable condition recently linked to gadolinium (Gd) exposure during MRI with contrast. In addition, Gd deposition in the human brain has been reported following contrast, and this is now under investigation by the US Food and Drug Administration (FDA). To address a perceived need for a Gd-free contrast agent with pharmacokinetic and imaging properties comparable to GBCAs, we have designed and developed zwitterion-coated exceedingly small superparamagnetic iron oxide nanoparticles (ZES-SPIONs) consisting of ∼3-nm inorganic cores and ∼1-nm ultrathin hydrophilic shell. These ZES-SPIONs are free of Gd and show a high T1 contrast power. We demonstrate the potential of ZES-SPIONs in preclinical MRI and magnetic resonance angiography.National Institutes of Health (U.S.) (Grant 1U54-CA119349)National Institutes of Health (U.S.) (Grant 9-P41-EB015871-26A1)United States. Army Research Office (Grant W911NF-07-D-0004)National Institutes of Health (U.S.) (R01-MH103160)National Institutes of Health (U.S.) (R01-DA028299