Superhuman cell death detection with biomarker-optimized neural networks.

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.

Measurement of the ultrasound attenuation and dispersion in 3D-printed photopolymer materials from 1 to 3.5 MHz.

Over the past decade, the range of applications in biomedical ultrasound exploiting 3D printing has rapidly expanded. For wavefront shaping specifically, 3D printing has enabled a diverse range of new, low-cost approaches for controlling acoustic fields. These methods rely on accurate knowledge of the bulk acoustic properties of the materials; however, to date, robust knowledge of these parameters is lacking for many materials that are commonly used. In this work, the acoustic properties of eight 3D-printed photopolymer materials were characterised over a frequency range from 1 to 3.5 MHz. The properties measured were the frequency-dependent phase velocity and attenuation, group velocity, signal velocity, and mass density. The materials were fabricated using two separate techniques [PolyJet and stereolithograph (SLA)], and included Agilus30, FLXA9960, FLXA9995, Formlabs Clear, RGDA8625, RGDA8630, VeroClear, and VeroWhite. The range of measured density values across all eight materials was 1120-1180 kg · m-3, while the sound speed values were between 2020 to 2630 m · s-1, and attenuation values typically in the range 3-9 dB · MHz-1· cm-1.

Genetically encoded cell-death indicators (GEDI) to detect an early irreversible commitment to neurodegeneration.

Cell death is a critical process that occurs normally in health and disease. However, its study is limited due to available technologies that only detect very late stages in the process or specific death mechanisms. Here, we report the development of a family of fluorescent biosensors called genetically encoded death indicators (GEDIs). GEDIs specifically detect an intracellular Ca2+ level that cells achieve early in the cell death process and that marks a stage at which cells are irreversibly committed to die. The time-resolved nature of a GEDI delineates a binary demarcation of cell life and death in real time, reformulating the definition of cell death. We demonstrate that GEDIs acutely and accurately report death of rodent and human neurons in vitro, and show that GEDIs enable an automated imaging platform for single cell detection of neuronal death in vivo in zebrafish larvae. With a quantitative pseudo-ratiometric signal, GEDIs facilitate high-throughput analysis of cell death in time-lapse imaging analysis, providing the necessary resolution and scale to identify early factors leading to cell death in studies of neurodegeneration.

Persistent mRNA localization defects and cell death in ALS neurons caused by transient cellular stress.

Persistent cytoplasmic aggregates containing RNA binding proteins (RBPs) are central to the pathogenesis of late-onset neurodegenerative disorders such as amyotrophic lateral sclerosis (ALS). These aggregates share components, molecular mechanisms, and cellular protein quality control pathways with stress-induced RNA granules (SGs). Here, we assess the impact of stress on the global mRNA localization landscape of human pluripotent stem cell-derived motor neurons (PSC-MNs) using subcellular fractionation with RNA sequencing and proteomics. Transient stress disrupts subcellular RNA and protein distributions, alters the RNA binding profile of SG- and ALS-relevant RBPs and recapitulates disease-associated molecular changes such as aberrant splicing of STMN2. Although neurotypical PSC-MNs re-establish a normal subcellular localization landscape upon recovery from stress, cells harboring ALS-linked mutations are intransigent and display a delayed-onset increase in neuronal cell death. Our results highlight subcellular molecular distributions as predictive features and underscore the utility of cellular stress as a paradigm to study ALS-relevant mechanisms.

Small-Molecule Modulation of TDP-43 Recruitment to Stress Granules Prevents Persistent TDP-43 Accumulation in ALS/FTD.

Stress granules (SGs) form during cellular stress and are implicated in neurodegenerative diseases such as amyotrophic lateral sclerosis and frontotemporal dementia (ALS/FTD). To yield insights into the role of SGs in pathophysiology, we performed a high-content screen to identify small molecules that alter SG properties in proliferative cells and human iPSC-derived motor neurons (iPS-MNs). One major class of active molecules contained extended planar aromatic moieties, suggesting a potential to intercalate in nucleic acids. Accordingly, we show that several hit compounds can prevent the RNA-dependent recruitment of the ALS-associated RNA-binding proteins (RBPs) TDP-43, FUS, and HNRNPA2B1 into SGs. We further demonstrate that transient SG formation contributes to persistent accumulation of TDP-43 into cytoplasmic puncta and that our hit compounds can reduce this accumulation in iPS-MNs from ALS patients. We propose that compounds with planar moieties represent a promising starting point to develop small-molecule therapeutics for treating ALS/FTD.

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.

In Silico Labeling: Predicting Fluorescent Labels in Unlabeled Images.

Microscopy is a central method in life sciences. Many popular methods, such as antibody labeling, are used to add physical fluorescent labels to specific cellular constituents. However, these approaches have significant drawbacks, including inconsistency; limitations in the number of simultaneous labels because of spectral overlap; and necessary perturbations of the experiment, such as fixing the cells, to generate the measurement. Here, we show that a computational machine-learning approach, which we call "in silico labeling" (ISL), reliably predicts some fluorescent labels from transmitted-light images of unlabeled fixed or live biological samples. ISL predicts a range of labels, such as those for nuclei, cell type (e.g., neural), and cell state (e.g., cell death). Because prediction happens in silico, the method is consistent, is not limited by spectral overlap, and does not disturb the experiment. ISL generates biological measurements that would otherwise be problematic or impossible to acquire.

A Multi-Grid Iterative Method for Photoacoustic Tomography.

Inspired by the recent advances on minimizing nonsmooth or bound-constrained convex functions on models using varying degrees of fidelity, we propose a line search multi-grid (MG) method for full-wave iterative image reconstruction in photoacoustic tomography (PAT) in heterogeneous media. To compute the search direction at each iteration, we decide between the gradient at the target level, or alternatively an approximate error correction at a coarser level, relying on some predefined criteria. To incorporate absorption and dispersion, we derive the analytical adjoint directly from the first-order acoustic wave system. The effectiveness of the proposed method is tested on a total-variation penalized Iterative Shrinkage Thresholding algorithm (ISTA) and its accelerated variant (FISTA), which have been used in many studies of image reconstruction in PAT. The results show the great potential of the proposed method in improving speed of iterative image reconstruction.

Protein-RNA Networks Regulated by Normal and ALS-Associated Mutant HNRNPA2B1 in the Nervous System.

HnRNPA2B1 encodes an RNA binding protein associated with neurodegeneration. However, its function in the nervous system is unclear. Transcriptome-wide crosslinking and immunoprecipitation in mouse spinal cord discover UAGG motifs enriched within ∼2,500 hnRNP A2/B1 binding sites and an unexpected role for hnRNP A2/B1 in alternative polyadenylation. HnRNP A2/B1 loss results in alternative splicing (AS), including skipping of an exon in amyotrophic lateral sclerosis (ALS)-associated D-amino acid oxidase (DAO) that reduces D-serine metabolism. ALS-associated hnRNP A2/B1 D290V mutant patient fibroblasts and motor neurons differentiated from induced pluripotent stem cells (iPSC-MNs) demonstrate abnormal splicing changes, likely due to increased nuclear-insoluble hnRNP A2/B1. Mutant iPSC-MNs display decreased survival in long-term culture and exhibit hnRNP A2/B1 localization to cytoplasmic granules as well as exacerbated changes in gene expression and splicing upon cellular stress. Our findings provide a cellular resource and reveal RNA networks relevant to neurodegeneration, regulated by normal and mutant hnRNP A2/B1. VIDEO ABSTRACT.

A fast time-difference inverse solver for 3D EIT with application to lung imaging.

A class of sparse optimization techniques that require solely matrix-vector products, rather than an explicit access to the forward matrix and its transpose, has been paid much attention in the recent decade for dealing with large-scale inverse problems. This study tailors application of the so-called Gradient Projection for Sparse Reconstruction (GPSR) to large-scale time-difference three-dimensional electrical impedance tomography (3D EIT). 3D EIT typically suffers from the need for a large number of voxels to cover the whole domain, so its application to real-time imaging, for example monitoring of lung function, remains scarce since the large number of degrees of freedom of the problem extremely increases storage space and reconstruction time. This study shows the great potential of the GPSR for large-size time-difference 3D EIT. Further studies are needed to improve its accuracy for imaging small-size anomalies.

Sampling of finite elements for sparse recovery in large scale 3D electrical impedance tomography.

This study proposes a method to improve performance of sparse recovery inverse solvers in 3D electrical impedance tomography (3D EIT), especially when the volume under study contains small-sized inclusions, e.g. 3D imaging of breast tumours. Initially, a quadratic regularized inverse solver is applied in a fast manner with a stopping threshold much greater than the optimum. Based on assuming a fixed level of sparsity for the conductivity field, finite elements are then sampled via applying a compressive sensing (CS) algorithm to the rough blurred estimation previously made by the quadratic solver. Finally, a sparse inverse solver is applied solely to the sampled finite elements, with the solution to the CS as its initial guess. The results show the great potential of the proposed CS-based sparse recovery in improving accuracy of sparse solution to the large-size 3D EIT.

Radial glia require PDGFD-PDGFRß signalling in human but not mouse neocortex.

Evolutionary expansion of the human neocortex underlies many of our unique mental abilities. This expansion has been attributed to the increased proliferative potential of radial glia (RG; neural stem cells) and their subventricular dispersion from the periventricular niche during neocortical development. Such adaptations may have evolved through gene expression changes in RG. However, whether or how RG gene expression varies between humans and other species is unknown. Here we show that the transcriptional profiles of human and mouse neocortical RG are broadly conserved during neurogenesis, yet diverge for specific signalling pathways. By analysing differential gene co-expression relationships between the species, we demonstrate that the growth factor PDGFD is specifically expressed by RG in human, but not mouse, corticogenesis. We also show that the expression domain of PDGFRß, the cognate receptor for PDGFD, is evolutionarily divergent, with high expression in the germinal region of dorsal human neocortex but not in the mouse. Pharmacological inhibition of PDGFD-PDGFRß signalling in slice culture prevents normal cell cycle progression of neocortical RG in human, but not mouse. Conversely, injection of recombinant PDGFD or ectopic expression of constitutively active PDGFRß in developing mouse neocortex increases the proportion of RG and their subventricular dispersion. These findings highlight the requirement of PDGFD-PDGFRß signalling for human neocortical development and suggest that local production of growth factors by RG supports the expanded germinal region and progenitor heterogeneity of species with large brains.

Compressed sampling for boundary measurements in three-dimensional electrical impedance tomography.

Electrical impedance tomography (EIT) utilizes electrodes on a medium's surface to produce measured data from which the conductivity distribution inside the medium is estimated. For the cases that relocation of electrodes is impractical or no a priori assumptions can be made to optimize the electrodes placement, a large number of electrodes may be needed to cover all possible imaging volume. This may occur in dynamically varying conductivity distribution in 3D EIT. Three-dimensional EIT then requires inverting very large linear systems to calculate the conductivity field, which causes significant problems regarding storage space and reconstruction time in addition to that data acquisition for a large number of electrodes will reduce the achievable frame rate, which is considered as major advantage of EIT imaging. This study proposes an idea to reduce the reconstruction complexity based on the well-known compressed sampling theory. By applying the so-called model-based CoSaMP algorithm to large size data collected by a 256 channel system, the size of forward operator and data acquisition time is reduced to those of a 32 channel system, while accuracy of reconstruction is significantly improved. The results demonstrate great capability of compressed sampling for overriding the challenges arising in 3D EIT.

A cellular model for sporadic ALS using patient-derived induced pluripotent stem cells.

Development of therapeutics for genetically complex neurodegenerative diseases such as sporadic amyotrophic lateral sclerosis (ALS) has largely been hampered by lack of relevant disease models. Reprogramming of sporadic ALS patients' fibroblasts into induced pluripotent stem cells (iPSC) and differentiation into affected neurons that show a disease phenotype could provide a cellular model for disease mechanism studies and drug discovery. Here we report the reprogramming to pluripotency of fibroblasts from a large cohort of healthy controls and ALS patients and their differentiation into motor neurons. We demonstrate that motor neurons derived from three sALS patients show de novo TDP-43 aggregation and that the aggregates recapitulate pathology in postmortem tissue from one of the same patients from which the iPSC were derived. We configured a high-content chemical screen using the TDP-43 aggregate endpoint both in lower motor neurons and upper motor neuron like cells and identified FDA-approved small molecule modulators including Digoxin demonstrating the feasibility of patient-derived iPSC-based disease modeling for drug screening.

Identification of extracellular miRNA in human cerebrospinal fluid by next-generation sequencing.

There has been a growing interest in using next-generation sequencing (NGS) to profile extracellular small RNAs from the blood and cerebrospinal fluid (CSF) of patients with neurological diseases, CNS tumors, or traumatic brain injury for biomarker discovery. Small sample volumes and samples with low RNA abundance create challenges for downstream small RNA sequencing assays. Plasma, serum, and CSF contain low amounts of total RNA, of which small RNAs make up a fraction. The purpose of this study was to maximize RNA isolation from RNA-limited samples and apply these methods to profile the miRNA in human CSF by small RNA deep sequencing. We systematically tested RNA isolation efficiency using ten commercially available kits and compared their performance on human plasma samples. We used RiboGreen to quantify total RNA yield and custom TaqMan assays to determine the efficiency of small RNA isolation for each of the kits. We significantly increased the recovery of small RNA by repeating the aqueous extraction during the phenol-chloroform purification in the top performing kits. We subsequently used the methods with the highest small RNA yield to purify RNA from CSF and serum samples from the same individual. We then prepared small RNA sequencing libraries using Illumina's TruSeq sample preparation kit and sequenced the samples on the HiSeq 2000. Not surprisingly, we found that the miRNA expression profile of CSF is substantially different from that of serum. To our knowledge, this is the first time that the small RNA fraction from CSF has been profiled using next-generation sequencing.

Induced pluripotent stem cells--opportunities for disease modelling and drug discovery.

The ability to generate induced pluripotent stem cells (iPSCs) from patients, and an increasingly refined capacity to differentiate these iPSCs into disease-relevant cell types, promises a new paradigm in drug development - one that positions human disease pathophysiology at the core of preclinical drug discovery. Disease models derived from iPSCs that manifest cellular disease phenotypes have been established for several monogenic diseases, but iPSCs can likewise be used for phenotype-based drug screens in complex diseases for which the underlying genetic mechanism is unknown. Here, we highlight recent advances as well as limitations in the use of iPSC technology for modelling a 'disease in a dish' and for testing compounds against human disease phenotypes in vitro. We discuss how iPSCs are being exploited to illuminate disease pathophysiology, identify novel drug targets and enhance the probability of clinical success of new drugs.

A stem cell niche for intermediate progenitor cells of the embryonic cortex.

The excitatory neurons of the mammalian cerebral cortex arise from asymmetric divisions of radial glial cells in the ventricular zone and symmetric division of intermediate progenitor cells (IPCs) in the subventricular zone (SVZ) of the embryonic cortex. Little is known about the microenvironment in which IPCs divide or whether a stem cell niche exists in the SVZ of the embryonic cortex. Recent evidence suggests that vasculature may provide a niche for adult stem cells but its role in development is less clear. We have investigated the vasculature in the embryonic cortex during neurogenesis and find that IPCs are spatially and temporally associated with blood vessels during cortical development. Intermediate progenitors mimic the pattern of capillaries suggesting patterns of angiogenesis and neurogenesis are coordinated during development. More importantly, we find that IPCs divide near blood vessel branch points suggesting that cerebral vasculature establishes a stem cell niche for intermediate progenitors in the SVZ. These data provide novel evidence for the presence of a neurogenic niche for intermediate progenitors in the embryonic SVZ and suggest blood vessels are important for proper patterning of neurogenesis.

Coordinated motor neuron axon growth and neuromuscular synaptogenesis are promoted by CPG15 in vivo.

We have used in vivo time-lapse two-photon imaging of single motor neuron axons labeled with GFP combined with labeling of presynaptic vesicle clusters and postsynaptic acetylcholine receptors in Xenopus laevis tadpoles to determine the dynamic rearrangement of individual axon branches and synaptogenesis during motor axon arbor development. Control GFP-labeled axons are highly dynamic during the period when axon arbors are elaborating. Axon branches emerge from sites of synaptic vesicle clusters. These data indicate that motor neuron axon elaboration and synaptogenesis are concurrent and iterative. We tested the role of Candidate Plasticity Gene 15 (CPG15, also known as Neuritin), an activity-regulated gene that is expressed in the developing motor neurons in this process. CPG15 expression enhances the development of motor neuron axon arbors by promoting neuromuscular synaptogenesis and by increasing the addition of new axon branches.