Dnmt3a knockout in excitatory neurons impairs postnatal synapse maturation and increases the repressive histone modification H3K27me3.

Two epigenetic pathways of transcriptional repression, DNA methylation and polycomb repressive complex 2 (PRC2), are known to regulate neuronal development and function. However, their respective contributions to brain maturation are unknown. We found that conditional loss of the de novo DNA methyltransferase Dnmt3a in mouse excitatory neurons altered expression of synapse-related genes, stunted synapse maturation, and impaired working memory and social interest. At the genomic level, loss of Dnmt3a abolished postnatal accumulation of CG and non-CG DNA methylation, leaving adult neurons with an unmethylated, fetal-like epigenomic pattern at ~222,000 genomic regions. The PRC2-associated histone modification, H3K27me3, increased at many of these sites. Our data support a dynamic interaction between two fundamental modes of epigenetic repression during postnatal maturation of excitatory neurons, which together confer robustness on neuronal regulation.

Deep learning-based point-scanning super-resolution imaging.

Point-scanning imaging systems are among the most widely used tools for high-resolution cellular and tissue imaging, benefiting from arbitrarily defined pixel sizes. The resolution, speed, sample preservation and signal-to-noise ratio (SNR) of point-scanning systems are difficult to optimize simultaneously. We show these limitations can be mitigated via the use of deep learning-based supersampling of undersampled images acquired on a point-scanning system, which we term point-scanning super-resolution (PSSR) imaging. We designed a 'crappifier' that computationally degrades high SNR, high-pixel resolution ground truth images to simulate low SNR, low-resolution counterparts for training PSSR models that can restore real-world undersampled images. For high spatiotemporal resolution fluorescence time-lapse data, we developed a 'multi-frame' PSSR approach that uses information in adjacent frames to improve model predictions. PSSR facilitates point-scanning image acquisition with otherwise unattainable resolution, speed and sensitivity. All the training data, models and code for PSSR are publicly available at 3DEM.org.

Dynamic regulation of CTCF stability and sub-nuclear localization in response to stress.

The nuclear protein CCCTC-binding factor (CTCF) has diverse roles in chromatin architecture and gene regulation. Functionally, CTCF associates with thousands of genomic sites and interacts with proteins, such as cohesin, or non-coding RNAs to facilitate specific transcriptional programming. In this study, we examined CTCF during the cellular stress response in human primary cells using immune-blotting, quantitative real time-PCR, chromatin immunoprecipitation-sequence (ChIP-seq) analysis, mass spectrometry, RNA immunoprecipitation-sequence analysis (RIP-seq), and Airyscan confocal microscopy. Unexpectedly, we found that CTCF is exquisitely sensitive to diverse forms of stress in normal patient-derived human mammary epithelial cells (HMECs). In HMECs, a subset of CTCF protein forms complexes that localize to Serine/arginine-rich splicing factor (SC-35)-containing nuclear speckles. Upon stress, this species of CTCF protein is rapidly downregulated by changes in protein stability, resulting in loss of CTCF from SC-35 nuclear speckles and changes in CTCF-RNA interactions. Our ChIP-seq analysis indicated that CTCF binding to genomic DNA is largely unchanged. Restoration of the stress-sensitive pool of CTCF protein abundance and re-localization to nuclear speckles can be achieved by inhibition of proteasome-mediated degradation. Surprisingly, we observed the same characteristics of the stress response during neuronal differentiation of human pluripotent stem cells (hPSCs). CTCF forms stress-sensitive complexes that localize to SC-35 nuclear speckles during a specific stage of neuronal commitment/development but not in differentiated neurons. We speculate that these particular CTCF complexes serve a role in RNA processing that may be intimately linked with specific genes in the vicinity of nuclear speckles, potentially to maintain cells in a certain differentiation state, that is dynamically regulated by environmental signals. The stress-regulated activity of CTCF is uncoupled in persistently stressed, epigenetically re-programmed "variant" HMECs and certain cancer cell lines. These results reveal new insights into CTCF function in cell differentiation and the stress-response with implications for oxidative damage-induced cancer initiation and neuro-degenerative diseases.

Auxin-induced signaling protein nanoclustering contributes to cell polarity formation.

Cell polarity is fundamental to the development of both eukaryotes and prokaryotes, yet the mechanisms behind its formation are not well understood. Here we found that, phytohormone auxin-induced, sterol-dependent nanoclustering of cell surface transmembrane receptor kinase 1 (TMK1) is critical for the formation of polarized domains at the plasma membrane (PM) during the morphogenesis of cotyledon pavement cells (PC) in Arabidopsis. Auxin-induced TMK1 nanoclustering stabilizes flotillin1-associated ordered nanodomains, which in turn promote the nanoclustering of ROP6 GTPase that acts downstream of TMK1 to regulate cortical microtubule organization. In turn, cortical microtubules further stabilize TMK1- and flotillin1-containing nanoclusters at the PM. Hence, we propose a new paradigm for polarity formation: A diffusive signal triggers cell polarization by promoting cell surface receptor-mediated nanoclustering of signaling components and cytoskeleton-mediated positive feedback that reinforces these nanodomains into polarized domains.

Differential Loss of Spinal Interneurons in a Mouse Model of ALS.

Amyotrophic lateral sclerosis (ALS) leads to a loss of specific motor neuron populations in the spinal cord and cortex. Emerging evidence suggests that interneurons may also be affected, but a detailed characterization of interneuron loss and its potential impacts on motor neuron loss and disease progression is lacking. To examine this issue, the fate of V1 inhibitory neurons during ALS was assessed in the ventral spinal cord using the SODG93A mouse model. The V1 population makes up ∼30% of all ventral inhibitory neurons, ∼50% of direct inhibitory synaptic contacts onto motor neuron cell bodies, and is thought to play a key role in modulating motor output, in part through recurrent and reciprocal inhibitory circuits. We find that approximately half of V1 inhibitory neurons are lost in SODG93A mice at late disease stages, but that this loss is delayed relative to the loss of motor neurons and V2a excitatory neurons. We further identify V1 subpopulations based on transcription factor expression that are differentially susceptible to degeneration in SODG93A mice. At an early disease stage, we show that V1 synaptic contacts with motor neuron cell bodies increase, suggesting an upregulation of inhibition before V1 neurons are lost in substantial numbers. These data support a model in which progressive changes in V1 synaptic contacts early in disease, and in select V1 subpopulations at later stages, represent a compensatory upregulation and then deleterious breakdown of specific interneuron circuits within the spinal cord.

Tuft Cells Inhibit Pancreatic Tumorigenesis in Mice by Producing Prostaglandin D2.

BACKGROUND & AIMS: Development of pancreatic ductal adenocarcinoma (PDA) involves acinar to ductal metaplasia and genesis of tuft cells. It has been a challenge to study these rare cells because of the lack of animal models. We investigated the role of tuft cells in pancreatic tumorigenesis. METHODS: We performed studies with LSL-KrasG12D/+;Ptf1aCre/+ mice (KC; develop pancreatic tumors), KC mice crossed with mice with pancreatic disruption of Pou2f3 (KPouC mice; do not develop tuft cells), or mice with pancreatic disruption of the hematopoietic prostaglandin D synthase gene (Hpgds, KHC mice) and wild-type mice. Mice were allowed to age or were given caerulein to induce pancreatitis; pancreata were collected and analyzed by histology, immunohistochemistry, RNA sequencing, ultrastructural microscopy, and metabolic profiling. We performed laser-capture dissection and RNA-sequencing analysis of pancreatic tissues from 26 patients with pancreatic intraepithelial neoplasia (PanIN), 19 patients with intraductal papillary mucinous neoplasms (IPMNs), and 197 patients with PDA. RESULTS: Pancreata from KC mice had increased formation of tuft cells and higher levels of prostaglandin D2 than wild-type mice. Pancreas-specific deletion of POU2F3 in KC mice (KPouC mice) resulted in a loss of tuft cells and accelerated tumorigenesis. KPouC mice had increased fibrosis and activation of immune cells after administration of caerulein. Pancreata from KPouC and KHC mice had significantly lower levels of prostaglandin D2, compared with KC mice, and significantly increased numbers of PanINs and PDAs. KPouC and KHC mice had increased pancreatic injury after administration of caerulein, significantly less normal tissue, more extracellular matrix deposition, and higher PanIN grade than KC mice. Human PanIN and intraductal papillary mucinous neoplasm had gene expression signatures associated with tuft cells and increased expression of Hpgds messenger RNA compared with PDA. CONCLUSIONS: In mice with KRAS-induced pancreatic tumorigenesis, loss of tuft cells accelerates tumorigenesis and increases the severity of caerulein-induced pancreatic injury, via decreased production of prostaglandin D2. These data are consistent with the hypothesis that tuft cells are a metaplasia-induced tumor attenuating cell type.

Tuft Cell Formation Reflects Epithelial Plasticity in Pancreatic Injury: Implications for Modeling Human Pancreatitis.

Chronic pancreatitis, a known risk factor for the development of pancreatic ductal adenocarcinoma (PDA), is a serious, widespread medical condition characterized by inflammation, fibrosis, and acinar to ductal metaplasia (ADM). ADM is a cell type transdifferentiation event where pancreatic acinar cells become ductal-like under conditions of injury or oncogenic mutation. Here, we show that chronic pancreatitis and ADM in genetically wild type mice results in the formation of a significant population of chemosensory tuft cells. Transcriptomic analyses of pancreatitis tuft cells identify expression of inflammatory mediators, consistent with a role for tuft cells in injury progression and/or resolution. Though similar to tuft cell populations in other organs and disease systems, we identified a number of key differences that suggest context-specific tuft cell functions. We evaluated seven different mouse strains for tuft cell formation in response to chronic injury and identified significant heterogeneity reflecting varying proclivity for epithelial plasticity between strains. These results have interesting implications in the role of epithelial plasticity and heterogeneity in pancreatitis and highlight the importance of mouse strain selection when modeling human disease.

Targeting LIF-mediated paracrine interaction for pancreatic cancer therapy and monitoring.

Pancreatic ductal adenocarcinoma (PDAC) has a dismal prognosis largely owing to inefficient diagnosis and tenacious drug resistance. Activation of pancreatic stellate cells (PSCs) and consequent development of dense stroma are prominent features accounting for this aggressive biology1,2. The reciprocal interplay between PSCs and pancreatic cancer cells (PCCs) not only enhances tumour progression and metastasis but also sustains their own activation, facilitating a vicious cycle to exacerbate tumorigenesis and drug resistance3-7. Furthermore, PSC activation occurs very early during PDAC tumorigenesis8-10, and activated PSCs comprise a substantial fraction of the tumour mass, providing a rich source of readily detectable factors. Therefore, we hypothesized that the communication between PSCs and PCCs could be an exploitable target to develop effective strategies for PDAC therapy and diagnosis. Here, starting with a systematic proteomic investigation of secreted disease mediators and underlying molecular mechanisms, we reveal that leukaemia inhibitory factor (LIF) is a key paracrine factor from activated PSCs acting on cancer cells. Both pharmacologic LIF blockade and genetic Lifr deletion markedly slow tumour progression and augment the efficacy of chemotherapy to prolong survival of PDAC mouse models, mainly by modulating cancer cell differentiation and epithelial-mesenchymal transition status. Moreover, in both mouse models and human PDAC, aberrant production of LIF in the pancreas is restricted to pathological conditions and correlates with PDAC pathogenesis, and changes in the levels of circulating LIF correlate well with tumour response to therapy. Collectively, these findings reveal a function of LIF in PDAC tumorigenesis, and suggest its translational potential as an attractive therapeutic target and circulating marker. Our studies underscore how a better understanding of cell-cell communication within the tumour microenvironment can suggest novel strategies for cancer therapy.

Deep convolutional neural networks for segmenting 3D in vivo multiphoton images of vasculature in Alzheimer disease mouse models.

The health and function of tissue rely on its vasculature network to provide reliable blood perfusion. Volumetric imaging approaches, such as multiphoton microscopy, are able to generate detailed 3D images of blood vessels that could contribute to our understanding of the role of vascular structure in normal physiology and in disease mechanisms. The segmentation of vessels, a core image analysis problem, is a bottleneck that has prevented the systematic comparison of 3D vascular architecture across experimental populations. We explored the use of convolutional neural networks to segment 3D vessels within volumetric in vivo images acquired by multiphoton microscopy. We evaluated different network architectures and machine learning techniques in the context of this segmentation problem. We show that our optimized convolutional neural network architecture with a customized loss function, which we call DeepVess, yielded a segmentation accuracy that was better than state-of-the-art methods, while also being orders of magnitude faster than the manual annotation. To explore the effects of aging and Alzheimer's disease on capillaries, we applied DeepVess to 3D images of cortical blood vessels in young and old mouse models of Alzheimer's disease and wild type littermates. We found little difference in the distribution of capillary diameter or tortuosity between these groups, but did note a decrease in the number of longer capillary segments (>75µm) in aged animals as compared to young, in both wild type and Alzheimer's disease mouse models.