Live Detection of Neural Progenitors and Glioblastoma Cells by an Oligothiophene Derivative.

There is an urgent need for simple and non-invasive identification of live neural stem/progenitor cells (NSPCs) in the developing and adult brain as well as in disease, such as in brain tumors, due to the potential clinical importance in prognosis, diagnosis, and treatment of diseases of the nervous system. Here, we report a luminescent conjugated oligothiophene (LCO), named p-HTMI, for non-invasive and non-amplified real-time detection of live human patient-derived glioblastoma (GBM) stem cell-like cells and NSPCs. While p-HTMI stained only a small fraction of other cell types investigated, the mere addition of p-HTMI to the cell culture resulted in efficient detection of NSPCs or GBM cells from rodents and humans within minutes. p-HTMI is functionalized with a methylated imidazole moiety resembling the side chain of histidine/histamine, and non-methylated analogues were not functional. Cell sorting experiments of human GBM cells demonstrated that p-HTMI labeled the same cell population as CD271, a proposed marker for stem cell-like cells and rapidly migrating cells in glioblastoma. Our results suggest that the LCO p-HTMI is a versatile tool for immediate and selective detection of neural and glioma stem and progenitor cells.

FocA: A deep learning tool for reliable, near-real-time imaging focus analysis in automated cell assay pipelines.

The increasing use of automation in cellular assays and cell culture presents significant opportunities to enhance the scale and throughput of imaging assays, but to do so, reliable data quality and consistency are critical. Realizing the full potential of automation will thus require the design of robust analysis pipelines that span the entire workflow in question. Here we present FocA, a deep learning tool that, in near real-time, identifies in-focus and out-of-focus images generated on a fully automated cell biology research platform, the NYSCF Global Stem Cell Array®. The tool is trained on small patches of downsampled images to maximize computational efficiency without compromising accuracy, and optimized to make sure no sub-quality images are stored and used in downstream analyses. The tool automatically generates balanced and maximally diverse training sets to avoid bias. The resulting model correctly identifies 100% of out-of-focus and 98% of in-focus images in under 4 s per 96-well plate, and achieves this result even in heavily downsampled data (∼30 times smaller than native resolution). Integrating the tool into automated workflows minimizes the need for human verification as well as the collection and usage of low-quality data. FocA thus offers a solution to ensure reliable image data hygiene and improve the efficiency of automated imaging workflows using minimal computational resources.

Patient iPSC models reveal glia-intrinsic phenotypes in multiple sclerosis.

Multiple sclerosis (MS) is considered an inflammatory and neurodegenerative disease of the central nervous system, typically resulting in significant neurological disability that worsens over time. While considerable progress has been made in defining the immune system's role in MS pathophysiology, the contribution of intrinsic CNS-cell dysfunction remains unclear. Here, we generated the largest reported collection of iPSC lines from people with MS spanning diverse clinical subtypes and differentiated them into glia-enriched cultures. Using single-cell transcriptomic profiling, we observed several distinguishing characteristics of MS cultures pointing to glia-intrinsic disease mechanisms. We found that iPSC-derived cultures from people with primary progressive MS contained fewer oligodendrocytes. Moreover, iPSC-oligodendrocyte lineage cells and astrocytes from people with MS showed increased expression of immune and inflammatory genes that match those of glial cells from MS postmortem brains. Thus, iPSC-derived MS models provide a unique platform for dissecting glial contributions to disease phenotypes independent of the peripheral immune system and identify potential glia-specific targets for therapeutic intervention.

Integrating deep learning and unbiased automated high-content screening to identify complex disease signatures in human fibroblasts.

Drug discovery for diseases such as Parkinson's disease are impeded by the lack of screenable cellular phenotypes. We present an unbiased phenotypic profiling platform that combines automated cell culture, high-content imaging, Cell Painting, and deep learning. We applied this platform to primary fibroblasts from 91 Parkinson's disease patients and matched healthy controls, creating the largest publicly available Cell Painting image dataset to date at 48 terabytes. We use fixed weights from a convolutional deep neural network trained on ImageNet to generate deep embeddings from each image and train machine learning models to detect morphological disease phenotypes. Our platform's robustness and sensitivity allow the detection of individual-specific variation with high fidelity across batches and plate layouts. Lastly, our models confidently separate LRRK2 and sporadic Parkinson's disease lines from healthy controls (receiver operating characteristic area under curve 0.79 (0.08 standard deviation)), supporting the capacity of this platform for complex disease modeling and drug screening applications.

Cortical overgrowth in a preclinical forebrain organoid model of CNTNAP2-associated autism spectrum disorder.

We utilized forebrain organoids generated from induced pluripotent stem cells of patients with a syndromic form of Autism Spectrum Disorder (ASD) with a homozygous protein-truncating mutation in CNTNAP2, to study its effects on embryonic cortical development. Patients with this mutation present with clinical characteristics of brain overgrowth. Patient-derived forebrain organoids displayed an increase in volume and total cell number that is driven by increased neural progenitor proliferation. Single-cell RNA sequencing revealed PFC-excitatory neurons to be the key cell types expressing CNTNAP2. Gene ontology analysis of differentially expressed genes (DEgenes) corroborates aberrant cellular proliferation. Moreover, the DEgenes are enriched for ASD-associated genes. The cell-type-specific signature genes of the CNTNAP2-expressing neurons are associated with clinical phenotypes previously described in patients. The organoid overgrowth phenotypes were largely rescued after correction of the mutation using CRISPR-Cas9. This CNTNAP2-organoid model provides opportunity for further mechanistic inquiry and development of new therapeutic strategies for ASD.

Bioinspired Soft Robot with Incorporated Microelectrodes.

Bioinspired soft robotic systems that mimic living organisms using engineered muscle tissue and biomaterials are revolutionizing the current biorobotics paradigm, especially in biomedical research. Recreating artificial life-like actuation dynamics is crucial for a soft-robotic system. However, the precise control and tuning of actuation behavior still represents one of the main challenges of modern soft robotic systems. This method describes a low-cost, highly scalable, and easy-to-use procedure to fabricate an electrically controllable soft robot with life-like movements that is activated and controlled by the contraction of cardiac muscle tissue on a micropatterned sting ray-like hydrogel scaffold. The use of soft photolithography methods makes it possible to successfully integrate multiple components in the soft robotic system, including micropatterned hydrogel-based scaffolds with carbon nanotubes (CNTs) embedded gelatin methacryloyl (CNT-GelMA), poly(ethylene glycol) diacrylate (PEGDA), flexible gold (Au) microelectrodes, and cardiac muscle tissue. In particular, the hydrogels alignment and micropattern are designed to mimic the muscle and cartilage structure of the sting ray. The electrically conductive CNT-GelMA hydrogel acts as a cell scaffold that improves the maturation and contraction behavior of cardiomyocytes, while the mechanically robust PEGDA hydrogel provides structural cartilage-like support to the whole soft robot. To overcome the hard and brittle nature of metal-based microelectrodes, we designed a serpentine pattern that has high flexibility and can avoid hampering the beating dynamics of cardiomyocytes. The incorporated flexible Au microelectrodes provide electrical stimulation across the soft robot, making it easier to control the contraction behavior of cardiac tissue.

Light sheet theta microscopy for rapid high-resolution imaging of large biological samples.

BACKGROUND: Advances in tissue clearing and molecular labeling methods are enabling unprecedented optical access to large intact biological systems. These developments fuel the need for high-speed microscopy approaches to image large samples quantitatively and at high resolution. While light sheet microscopy (LSM), with its high planar imaging speed and low photo-bleaching, can be effective, scaling up to larger imaging volumes has been hindered by the use of orthogonal light sheet illumination. RESULTS: To address this fundamental limitation, we have developed light sheet theta microscopy (LSTM), which uniformly illuminates samples from the same side as the detection objective, thereby eliminating limits on lateral dimensions without sacrificing the imaging resolution, depth, and speed. We present a detailed characterization of LSTM, and demonstrate its complementary advantages over LSM for rapid high-resolution quantitative imaging of large intact samples with high uniform quality. CONCLUSIONS: The reported LSTM approach is a significant step for the rapid high-resolution quantitative mapping of the structure and function of very large biological systems, such as a clarified thick coronal slab of human brain and uniformly expanded tissues, and also for rapid volumetric calcium imaging of highly motile animals, such as Hydra, undergoing non-isomorphic body shape changes.

Electrically Driven Microengineered Bioinspired Soft Robots.

To create life-like movements, living muscle actuator technologies have borrowed inspiration from biomimetic concepts in developing bioinspired robots. Here, the development of a bioinspired soft robotics system, with integrated self-actuating cardiac muscles on a hierarchically structured scaffold with flexible gold microelectrodes is reported. Inspired by the movement of living organisms, a batoid-fish-shaped substrate is designed and reported, which is composed of two micropatterned hydrogel layers. The first layer is a poly(ethylene glycol) hydrogel substrate, which provides a mechanically stable structure for the robot, followed by a layer of gelatin methacryloyl embedded with carbon nanotubes, which serves as a cell culture substrate, to create the actuation component for the soft body robot. In addition, flexible Au microelectrodes are embedded into the biomimetic scaffold, which not only enhance the mechanical integrity of the device, but also increase its electrical conductivity. After culturing and maturation of cardiomyocytes on the biomimetic scaffold, they show excellent myofiber organization and provide self-actuating motions aligned with the direction of the contractile force of the cells. The Au microelectrodes placed below the cell layer further provide localized electrical stimulation and control of the beating behavior of the bioinspired soft robot.

Protein/polysaccharide-based scaffolds mimicking native extracellular matrix for cardiac tissue engineering applications.

Tissue engineering has emerged as a viable approach to treat disease or repair damage in tissues and organs. One of the key elements for the success of tissue engineering is the use of a scaffold serving as artificial extracellular matrix (ECM). The ECM hosts the cells and improves their survival, proliferation, and differentiation, enabling the formation of new tissue. Here, we propose the development of a class of protein/polysaccharide-based porous scaffolds for use as ECM substitutes in cardiac tissue engineering. Scaffolds based on blends of a protein component, collagen or gelatin, with a polysaccharide component, alginate, were produced by freeze-drying and subsequent ionic and chemical crosslinking. Their morphological, physicochemical, and mechanical properties were determined and compared with those of natural porcine myocardium. We demonstrated that our scaffolds possessed highly porous and interconnected structures, and the chemical homogeneity of the natural ECM was well reproduced in both types of scaffolds. Furthermore, the alginate/gelatin (AG) scaffolds better mimicked the native tissue in terms of interactions between components and protein secondary structure, and in terms of swelling behavior. The AG scaffolds also showed superior mechanical properties for the desired application and supported better adhesion, growth, and differentiation of myoblasts under static conditions. The AG scaffolds were subsequently used for culturing neonatal rat cardiomyocytes, where high viability of the resulting cardiac constructs was observed under dynamic flow culture in a microfluidic bioreactor. We therefore propose our protein/polysaccharide scaffolds as a viable ECM substitute for applications in cardiac tissue engineering. © 2017 Wiley Periodicals, Inc. J Biomed Mater Res Part A: 106A: 769-781, 2018.