RESUMEN
Cellular events underlying neurodegenerative disease may be captured by longitudinal live microscopy of neurons. While the advent of robot-assisted microscopy has helped scale such efforts to high-throughput regimes with the statistical power to detect transient events, time-intensive human annotation is required. We addressed this fundamental limitation with biomarker-optimized convolutional neural networks (BO-CNNs): interpretable computer vision models trained directly on biosensor activity. We demonstrate the ability of BO-CNNs to detect cell death, which is typically measured by trained annotators. BO-CNNs detected cell death with superhuman accuracy and speed by learning to identify subcellular morphology associated with cell vitality, despite receiving no explicit supervision to rely on these features. These models also revealed an intranuclear morphology signal that is difficult to spot by eye and had not previously been linked to cell death, but that reliably indicates death. BO-CNNs are broadly useful for analyzing live microscopy and essential for interpreting high-throughput experiments.
RESUMEN
The Library of Integrated Network-Based Cellular Signatures (LINCS) is an NIH Common Fund program that catalogs how human cells globally respond to chemical, genetic, and disease perturbations. Resources generated by LINCS include experimental and computational methods, visualization tools, molecular and imaging data, and signatures. By assembling an integrated picture of the range of responses of human cells exposed to many perturbations, the LINCS program aims to better understand human disease and to advance the development of new therapies. Perturbations under study include drugs, genetic perturbations, tissue micro-environments, antibodies, and disease-causing mutations. Responses to perturbations are measured by transcript profiling, mass spectrometry, cell imaging, and biochemical methods, among other assays. The LINCS program focuses on cellular physiology shared among tissues and cell types relevant to an array of diseases, including cancer, heart disease, and neurodegenerative disorders. This Perspective describes LINCS technologies, datasets, tools, and approaches to data accessibility and reusability.
Asunto(s)
Catalogación/métodos , Biología de Sistemas/métodos , Biología Computacional/métodos , Bases de Datos de Compuestos Químicos/normas , Perfilación de la Expresión Génica/métodos , Biblioteca de Genes , Humanos , Almacenamiento y Recuperación de la Información/métodos , Programas Nacionales de Salud , National Institutes of Health (U.S.)/normas , Transcriptoma , Estados UnidosRESUMEN
We have developed a novel oxidized graphene nanoribbon-based platform (O-GNR) for gene delivery of double-stranded DNA into mammalian cells. O-GNRs, synthesized via longitudinal unzipping of multi-walled carbon nanotubes (MWCNTs), exhibited efficient DNA loading of small dsDNA fragments. Fourier Transform Infrared Spectroscopy identified stretching peaks in the O-P-O and DNA sugar phosphate backbone that were consistent with DNA loading onto O-GNRs. The presence of salts in the loading buffer promoted DNA loading and effective dispersion of O-GNRs. DNA:O-GNR complexes were stable upon treatment with surfactants Tween 20 and Triton-X100. O-GNRs did not impact the viability of mammalian cells. Last, the detection of GFP expression upon transfection of the DNA:O-GNR complex indicated that the cargo DNA is expressed in the nucleus. Taken together, O-GNRs function as a platform for gene delivery to mammalian cells.