Epigenetic and posttranslational modifications in light signal transduction and the circadian clock in Neurospora crassa

Blue light, a key abiotic signal, regulates a wide variety of physiological processes in many organisms. One of these phenomena is the circadian rhythm presents in organisms sensitive to the phase-setting effects of blue light and under control of the daily alternation of light and dark. Circadian clocks consist of autoregulatory alternating negative and positive feedback loops intimately connected with the cellular metabolism and biochemical processes. Neurospora crassa provides an excellent model for studying the molecular mechanisms involved in these phenomena. The White Collar Complex (WCC), a blue-light receptor and transcription factor of the circadian oscillator, and Frequency (FRQ), the circadian clock pacemaker, are at the core of the Neurospora circadian system. The eukaryotic circadian clock relies on transcriptional/translational feedback loops: some proteins rhythmically repress their own synthesis by inhibiting the activity of their transcriptional factors, generating self-sustained oscillations over a period of about 24 h. One of the basic mechanisms that perpetuate self-sustained oscillations is post translation modification (PTM). The acronym PTM generically indicates the addition of acetyl, methyl, sumoyl, or phosphoric groups to various types of proteins. The protein can be regulatory or enzymatic or a component of the chromatin. PTMs influence protein stability, interaction, localization, activity, and chromatin packaging. Chromatin modification and PTMs have been implicated in regulating circadian clock function in Neurospora. Research into the epigenetic control of transcription factors such as WCC has yielded new insights into the temporal modulation of light-dependent gene transcription. Here we report on epigenetic and protein PTMs in the regulation of the Neurospora crassa circadian clock. We also present a model that illustrates the molecular mechanisms at the basis of the blue light control of the circadian clock

Neural Transformers for Intraductal Papillary Mucosal Neoplasms (IPMN) Classification in MRI images

Early detection of precancerous cysts or neoplasms, i.e., Intraductal Papillary Mucosal Neoplasms (IPMN), in pancreas is a challenging and complex task, and it may lead to a more favourable outcome. Once detected, grading IPMNs accurately is also necessary, since low-risk IPMNs can be under surveillance program, while high-risk IPMNs have to be surgically resected before they turn into cancer. Current standards (Fukuoka and others) for IPMN classification show significant intra- and inter-operator variability, beside being error-prone, making a proper diagnosis unreliable. The established progress in artificial intelligence, through the deep learning paradigm, may provide a key tool for an effective support to medical decision for pancreatic cancer. In this work, we follow this trend, by proposing a novel AI-based IPMN classifier that leverages the recent success of transformer networks in generalizing across a wide variety of tasks, including vision ones. We specifically show that our transformer-based model exploits pre-training better than standard convolutional neural networks, thus supporting the sought architectural universalism of transformers in vision, including the medical image domain and it allows for a better interpretation of the obtained results

2-Hydroxyglutarate modulates histone methylation at specific loci and alters gene expression via Rph1 inhibition.

peer reviewed2-Hydroxyglutarate (2-HG) is an oncometabolite that accumulates in certain cancers. Gain-of-function mutations in isocitrate dehydrogenase lead to 2-HG accumulation at the expense of alpha-ketoglutarate. Elevated 2-HG levels inhibit histone and DNA demethylases, causing chromatin structure and gene regulation changes with tumorigenic consequences. We investigated the effects of elevated 2-HG levels in Saccharomyces cerevisiae, a yeast devoid of DNA methylation and heterochromatin-associated histone methylation. Our results demonstrate genetic background-dependent gene expression changes and altered H3K4 and H3K36 methylation at specific loci. Analysis of histone demethylase deletion strains indicated that 2-HG inhibits Rph1 sufficiently to induce extensive gene expression changes. Rph1 is the yeast homolog of human KDM4 demethylases and, among the yeast histone demethylases, was the most sensitive to the inhibitory effect of 2-HG in vitro. Interestingly, Rph1 deficiency favors gene repression and leads to further down-regulation of already silenced genes marked by low H3K4 and H3K36 trimethylation, but abundant in H3K36 dimethylation. Our results provide novel insights into the genome-wide effects of 2-HG and highlight Rph1 as its preferential demethylase target

An Explainable AI System for Automated COVID-19 Assessment and Lesion Categorization from CT-scans

COVID-19 infection caused by SARS-CoV-2 pathogen is a catastrophic pandemic outbreak all over the world with exponential increasing of confirmed cases and, unfortunately, deaths. In this work we propose an AI-powered pipeline, based on the deep-learning paradigm, for automated COVID-19 detection and lesion categorization from CT scans. We first propose a new segmentation module aimed at identifying automatically lung parenchyma and lobes. Next, we combined such segmentation network with classification networks for COVID-19 identification and lesion categorization. We compare the obtained classification results with those obtained by three expert radiologists on a dataset consisting of 162 CT scans. Results showed a sensitivity of 90\% and a specificity of 93.5% for COVID-19 detection, outperforming those yielded by the expert radiologists, and an average lesion categorization accuracy of over 84%. Results also show that a significant role is played by prior lung and lobe segmentation that allowed us to enhance performance by over 20 percent points. The interpretation of the trained AI models, moreover, reveals that the most significant areas for supporting the decision on COVID-19 identification are consistent with the lesions clinically associated to the virus, i.e., crazy paving, consolidation and ground glass. This means that the artificial models are able to discriminate a positive patient from a negative one (both controls and patients with interstitial pneumonia tested negative to COVID) by evaluating the presence of those lesions into CT scans. Finally, the AI models are integrated into a user-friendly GUI to support AI explainability for radiologists, which is publicly available at http://perceivelab.com/covid-ai

Peroxisome biogenesis, membrane contact sites, and quality control.

Peroxisomes are conserved organelles of eukaryotic cells with important roles in cellular metabolism, human health, redox homeostasis, as well as intracellular metabolite transfer and signaling. We review here the current status of the different co-existing modes of biogenesis of peroxisomal membrane proteins demonstrating the fascinating adaptability in their targeting and sorting pathways. While earlier studies focused on peroxisomes as autonomous organelles, the necessity of the ER and potentially even mitochondria as sources of peroxisomal membrane proteins and lipids has come to light in recent years. Additionally, the intimate physical juxtaposition of peroxisomes with other organelles has transitioned from being viewed as random encounters to a growing appreciation of the expanding roles of such inter-organellar membrane contact sites in metabolic and regulatory functions. Peroxisomal quality control mechanisms have also come of age with a variety of mechanisms operating both during biogenesis and in the cellular response to environmental cues

Epigenetic and Posttranslational Modifications in Light Signal Transduction and the Circadian Clock in Neurospora crassa

Blue light, a key abiotic signal, regulates a wide variety of physiological processes in many organisms. One of these phenomena is the circadian rhythm presents in organisms sensitive to the phase-setting effects of blue light and under control of the daily alternation of light and dark. Circadian clocks consist of autoregulatory alternating negative and positive feedback loops intimately connected with the cellular metabolism and biochemical processes. Neurospora crassa provides an excellent model for studying the molecular mechanisms involved in these phenomena. The White Collar Complex (WCC), a blue-light receptor and transcription factor of the circadian oscillator, and Frequency (FRQ), the circadian clock pacemaker, are at the core of the Neurospora circadian system. The eukaryotic circadian clock relies on transcriptional/translational feedback loops: some proteins rhythmically repress their own synthesis by inhibiting the activity of their transcriptional factors, generating self-sustained oscillations over a period of about 24 h. One of the basic mechanisms that perpetuate self-sustained oscillations is post translation modification (PTM). The acronym PTM generically indicates the addition of acetyl, methyl, sumoyl, or phosphoric groups to various types of proteins. The protein can be regulatory or enzymatic or a component of the chromatin. PTMs influence protein stability, interaction, localization, activity, and chromatin packaging. Chromatin modification and PTMs have been implicated in regulating circadian clock function in Neurospora. Research into the epigenetic control of transcription factors such as WCC has yielded new insights into the temporal modulation of light-dependent gene transcription. Here we report on epigenetic and protein PTMs in the regulation of the Neurospora crassa circadian clock. We also present a model that illustrates the molecular mechanisms at the basis of the blue light control of the circadian clock

Peroxisome biogenesis, membrane contact sites, and quality control.

Peroxisomes are conserved organelles of eukaryotic cells with important roles in cellular metabolism, human health, redox homeostasis, as well as intracellular metabolite transfer and signaling. We review here the current status of the different co-existing modes of biogenesis of peroxisomal membrane proteins demonstrating the fascinating adaptability in their targeting and sorting pathways. While earlier studies focused on peroxisomes as autonomous organelles, the necessity of the ER and potentially even mitochondria as sources of peroxisomal membrane proteins and lipids has come to light in recent years. Additionally, the intimate physical juxtaposition of peroxisomes with other organelles has transitioned from being viewed as random encounters to a growing appreciation of the expanding roles of such inter-organellar membrane contact sites in metabolic and regulatory functions. Peroxisomal quality control mechanisms have also come of age with a variety of mechanisms operating both during biogenesis and in the cellular response to environmental cues

Peroxisome biogenesis, membrane contact sites, and quality control.

Peroxisomes are conserved organelles of eukaryotic cells with important roles in cellular metabolism, human health, redox homeostasis, as well as intracellular metabolite transfer and signaling. We review here the current status of the different co-existing modes of biogenesis of peroxisomal membrane proteins demonstrating the fascinating adaptability in their targeting and sorting pathways. While earlier studies focused on peroxisomes as autonomous organelles, the necessity of the ER and potentially even mitochondria as sources of peroxisomal membrane proteins and lipids has come to light in recent years. Additionally, the intimate physical juxtaposition of peroxisomes with other organelles has transitioned from being viewed as random encounters to a growing appreciation of the expanding roles of such inter-organellar membrane contact sites in metabolic and regulatory functions. Peroxisomal quality control mechanisms have also come of age with a variety of mechanisms operating both during biogenesis and in the cellular response to environmental cues