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The evolutionary mechanism(s) underlying the expression of novel microRNAs (miRs) are still elusive. To explore this issue, we studied the expression of intronic primate-specific hsa-miR-608, located in the Semaphorin 4G (SEMA4G) gene. Engineered ‘humanized’ mice carrying human miR-608 flanked by 250 bp in the murine Sema4g gene expressed miR-608 in several tissues. Moreover, miR-608 flanked by shortened fragments of its human genome region elevated miR-608 levels by 100-fold in murine and human-originated cells, identifying the 150 nucleotides 5’ to pre-miR-608 as an active promoter. Surprisingly, pulldown of this 5’ sequence revealed tight interaction with ribosomal protein L24 (RPL24), which inhibited miR-608 expression. Furthermore, RPL24 depletion altered the levels of 22 miRs, and we discovered that direct interaction of RPL24 with DDX5, a component of the large microprocessor complex, inhibits pri-miR processing. Moreover, RPL24 depletion resulted in Angiogenin (ANG)-mediated production of 5’-half tRFs in human cells, and altered plant tRF profiles. Expanding previous reports that RPL24 regulates miR processing in Arabidopsis thaliana, we implicate RPL24 in an evolutionarily-conserved regulation of miR processing and tRF production.Abstract Figure

The current handling of data in earth observation, modelling and prediction measures gives cause for critical consideration, since we all too often carelessly ignore data uncertainty. We think that Earth scientists are generally aware of the importance of linking data to quantitative uncertainty measures. But we also think that uncertainty quantification of Earth observation data too often fails at very early stages. We claim that data acquisition without uncertainty quantification is not sustainable and machine learning and computational modelling cannot unfold their potential when analysing complex natural systems like the Earth. Current approaches such as stochastic perturbation of parameters or initial conditions cannot quantify uncertainty or bias arising from the choice of model, limiting scientific progress. We need incentives stimulating the honest treatment of uncertainty starting during data acquisition, continuing through analysis methodology and prediction results. Computational modellers and machine learning experts have a critical role, since they enjoy high esteem from stakeholders and their methodologies and their results critically depend on data uncertainty. If both want to advance their uncertainty assessment of models and predictions of complex systems like the Earth, they have a common problem to solve. Together, computational modellers and machine learners could develop new strategies for bias identification and uncertainty quantification offering a more all-embracing uncertainty quantification than any known methodology. But since it starts for computational modellers and machine learners with data and their uncertainty, the fundamental first step in such a development would be leveraging shareholder esteem to insistently advocate for reduction of ignorance when it comes to uncertainty quantification of data.

Recent findings in experimental models have shown that the microRNA miR-132 (mir-132) is an important regulator of liver homeostasis and lipid metabolism. We aimed to assess miR-132 expression in liver and fat tissues of obese individuals and examine its association with blood pressure (BP) and hepatic steatosis. We examined obese individuals undergoing bariatric surgery for weight loss (n = 19). Clinical and demographic information was obtained. Quantitative PCR was performed to determine tissue expression of miR-132 in liver and subcutaneous and visceral fat biopsies obtained during bariatric surgery. Liver biopsies were read by a single liver pathologist and graded for steatosis, inflammation and fibrosis. Participants (aged 39 ± 8.1 years) had a body mass index (BMI) of 42 ± 4.5 kg/m2 and presented with 2.2 ± 1.2 metabolic abnormalities. Supine BP was 127 ± 16/74 ± 11 mmHg. Hepatic and visceral fat expression of miR-132 were correlated (r = 0.59, P = 0.033). There was no correlation between subcutaneous and visceral expression of miR-132 (r = -0.31, P = 0.20). Hepatic and visceral fat miR-132 expression were associated with BMI (r = 0.62 and r = 0.68, P = 0.049 respectively) and degree of liver steatosis (r = 0.60 and r = 0.55, P < 0.05, respectively). Subcutaneous fat miRNA-132 expression was correlated to office systolic BP (r = 0.46, P < 0.05), several aspects of 24 h BP (24 h systolic BP: r = 0.52; day systolic BP: r = 0.59, P < 0.05 for all), plasma triglycerides (r = 0.51, P < 0.01) and liver enzymes (ALT: r = -0.52; AST: r = -0.48, P < 0.05 for all). We found an association between miR-132 and markers of cardiovascular and metabolic disease. Reduction of miR-132 may be a target for the regulation of liver lipid homeostasis and control of obesity-related blood pressure.

Laser scanning microscopy requires beam steering through relay and focusing optics at sub-micron precision. In light-weight mobile systems, such as head mounted multiphoton microscopes, distortion and imaging plane curvature management is unpractical due to the complexity of required optic compensation. Thus, the resulting scan pattern limits anatomical fidelity and decreases analysis algorithm efficiency. Here, we present a technique that reconstructs the three-dimensional scan path only requiring translation of a simple fluorescent test probe. Our method is applicable to any type of scanning instrument with sectioning capabilities without prior assumptions regarding origin of imaging deviations. Further, we demonstrate that the obtained scan pattern allows analysis of these errors, and allows to restore anatomical accuracy relevant for complementary methods such as motion correction, further enhancing spatial registration and feature extraction.

Significance Ischemic stroke triggers peripheral immunosuppression, increasing the susceptibility to poststroke pneumonia that is linked with poor survival. The poststroke brain initiates intensive communication with the immune system, and acetylcholine contributes to these messages; but the responsible molecules are yet unknown. We discovered a “changing of the guards,” where microRNA levels decreased but small transfer RNA fragments increased in poststroke blood. This molecular switch may rebalance acetylcholine signaling in CD14+ monocytes by regulating their gene expression and modulating poststroke immunity. Our observations point to transfer RNA fragments as molecular regulators of poststroke immune responses that may be potential therapeutic targets., Stroke is a leading cause of death and disability. Recovery depends on a delicate balance between inflammatory responses and immune suppression, tipping the scale between brain protection and susceptibility to infection. Peripheral cholinergic blockade of immune reactions fine-tunes this immune response, but its molecular regulators are unknown. Here, we report a regulatory shift in small RNA types in patient blood sequenced 2 d after ischemic stroke, comprising massive decreases of microRNA levels and concomitant increases of transfer RNA fragments (tRFs) targeting cholinergic transcripts. Electrophoresis-based size-selection followed by qRT-PCR validated the top six up-regulated tRFs in a separate cohort of stroke patients, and independent datasets of small and long RNA sequencing pinpointed immune cell subsets pivotal to these responses, implicating CD14+ monocytes in the cholinergic inflammatory reflex. In-depth small RNA targeting analyses revealed the most-perturbed pathways following stroke and implied a structural dichotomy between microRNA and tRF target sets. Furthermore, lipopolysaccharide stimulation of murine RAW 264.7 cells and human CD14+ monocytes up-regulated the top six stroke-perturbed tRFs, and overexpression of stroke-inducible tRF-22-WE8SPOX52 using a single-stranded RNA mimic induced down-regulation of immune regulator Z-DNA binding protein 1. In summary, we identified a “changing of the guards” between small RNA types that may systemically affect homeostasis in poststroke immune responses, and pinpointed multiple affected pathways, which opens new venues for establishing therapeutics and biomarkers at the protein and RNA level.

Recent reports attribute numerous regulatory functions to the nuclear paraspeckle-forming long noncoding RNA, nuclear enriched assembly transcript 1 (NEAT1), but the implications of its involvement in Parkinson's disease (PD) remain controversial. To address this issue, we assessed NEAT1 expression levels and cell type patterns in the substantia nigra (SN) from 53 donors with and without PD, as well as in interference tissue culture tests followed by multiple in-house and web-available models of PD. PCR quantification identified elevated levels of NEAT1 expression in the PD SN compared with control brains, an elevation that was reproducible across a multitude of disease models. In situ RNA hybridization supported neuron-specific formation of NEAT1-based paraspeckles at the SN and demonstrated coincreases of NEAT1 and paraspeckles in cultured cells under paraquat (PQ)-induced oxidative stress. Furthermore, neuroprotective agents, including fenofibrate and simvastatin, induced NEAT1 up-regulation, whereas RNA interference-mediated depletion of NEAT1 exacerbated death of PQ-exposed cells in a leucine-rich repeat kinase 2-mediated manner. Our findings highlight a novel protective role for NEAT1 in PD and suggest a previously unknown mechanism for the neuroprotective traits of widely used preventive therapeutics.-Simchovitz, A., Hanan, M., Niederhoffer, N., Madrer, N., Yayon, N., Bennett, E. R., Greenberg, D. S., Kadener, S., Soreq, H. NEAT1 is overexpressed in Parkinson's disease substantia nigra and confers drug-inducible neuroprotection from oxidative stress.

Circular RNAs (circRNAs) are brain-abundant RNAs of mostly unknown functions. To seek their roles in Parkinson's disease (PD), we generated an RNA sequencing resource of several brain region tissues from dozens of PD and control donors. In the healthy substantia nigra (SN), circRNAs accumulate in an age-dependent manner, but in the PD SN this correlation is lost and the total number of circRNAs reduced. In contrast, the levels of circRNAs are increased in the other studied brain regions of PD patients. We also found circSLC8A1 to increase in the SN of PD individuals. CircSLC8A1 carries 7 binding sites for miR-128 and is strongly bound to the microRNA effector protein Ago2. Indeed, RNA targets of miR-128 are also increased in PD individuals, suggesting that circSLC8A1 regulates miR-128 function and/or activity. CircSLC8A1 levels also increased in cultured cells exposed to the oxidative stress-inducing agent paraquat but were decreased in cells treated with the neuroprotective antioxidant regulator drug Simvastatin. Together, our work links circSLC8A1 to oxidative stress-related Parkinsonism and suggests further exploration of its molecular function in PD.

This chapter describes the use of locked nucleic acid (LNA) GapmeRs for the in vivo knockdown of specific mRNAs in the mouse liver and phenotype analysis. LNA GapmeRs may be tested for efficacy by transfection in cultured cells. They are delivered into mice in vivo by intravenous tail injection .

It is with great sadness that we have learned about the passing of Professor David Yaffe (1929-2020, Israel). Yehi Zichro Baruch - May his memory be a blessing. David was a man of family, science and nature. A native of Israel, David grew up in the historic years that preceded the birth of the State of Israel. He was a member of the group that established Kibbutz Revivim in the Negev desert, and in 1948 participated in Israel’s War of Independence. David and Ruth eventually joined Kibbutz Givat Brenner by Rehovot, permitting David to be both a kibbutz member and a life-long researcher at the Weizmann Institute of Science, where David received his PhD in 1959. David returned to the Institute after his postdoc at Stanford. Here, after several years of researching a number of tissues as models for studying the process of differentiation, David entered the myogenesis field and stayed with it to his last day. With his dedication to the field of myogenesis and his commitment to furthering the understanding of the People and the Land of Israel throughout the international scientific community, David organized the first ever myogenesis meeting that took place in Shoresh, Israel in 1975. This was followed by the 1980 myogenesis meeting at the same place and many more outstanding meetings, all of which brought together myogenesis, nature and scenery. Herein, through the preparation and publication of this current manuscript, we are meeting once again at a “David Yaffe myogenesis meeting". Some of us have been members of the Yaffe lab, some of us have known David as his national and international colleagues in the myology field. One of our contributors has also known (and communicates here) about David Yaffe’s earlier years as a kibbutznick in the Negev. Our collective reflections are a tribute to Professor David Yaffe. We are fortunate that the European Journal of Translational Myology has provided us with tremendous input and a platform for holding this 2020 distance meeting "Farwell to Professor David Yaffe - A Pillar of the Myogenesis Field".

Circular RNAs (circRNAs) are brain‐abundant RNAs of mostly unknown functions. To seek their roles in Parkinson's disease (PD), we generated an RNA sequencing resource of several brain region tissues from dozens of PD and control donors. In the healthy substantia nigra (SN), circRNAs accumulate in an age‐dependent manner, but in the PD SN this correlation is lost and the total number of circRNAs reduced. In contrast, the levels of circRNAs are increased in the other studied brain regions of PD patients. We also found circSLC8A1 to increase in the SN of PD individuals. CircSLC8A1 carries 7 binding sites for miR‐128 and is strongly bound to the microRNA effector protein Ago2. Indeed, RNA targets of miR‐128 are also increased in PD individuals, suggesting that circSLC8A1 regulates miR‐128 function and/or activity. CircSLC8A1 levels also increased in cultured cells exposed to the oxidative stress‐inducing agent paraquat but were decreased in cells treated with the neuroprotective antioxidant regulator drug Simvastatin. Together, our work links circSLC8A1 to oxidative stress‐related Parkinsonism and suggests further exploration of its molecular function in PD., In human brains, circRNA levels are region specific and inversely correlate to editing. In PD circRNAs are reduced in SN and accumulation correlation with age is lost. CircSLC8A1 increases in PD and oxidation, is bound to Ago2 and sponges miR128 targets, modulating neuronal survival and aging.

Scientists and engineers employ stochastic numerical simulators to model empirically observed phenomena. In contrast to purely statistical models, simulators express scientific principles that provide powerful inductive biases, improve generalization to new data or scenarios and allow for fewer, more interpretable and domain-relevant parameters. Despite these advantages, tuning a simulator's parameters so that its outputs match data is challenging. Simulation-based inference (SBI) seeks to identify parameter sets that a) are compatible with prior knowledge and b) match empirical observations. Importantly, SBI does not seek to recover a single 'best' data-compatible parameter set, but rather to identify all high probability regions of parameter space that explain observed data, and thereby to quantify parameter uncertainty. In Bayesian terminology, SBI aims to retrieve the posterior distribution over the parameters of interest. In contrast to conventional Bayesian inference, SBI is also applicable when one can run model simulations, but no formula or algorithm exists for evaluating the probability of data given parameters, i.e. the likelihood. We present $\texttt{sbi}$, a PyTorch-based package that implements SBI algorithms based on neural networks. $\texttt{sbi}$ facilitates inference on black-box simulators for practising scientists and engineers by providing a unified interface to state-of-the-art algorithms together with documentation and tutorials., Alvaro Tejero-Cantero, Jan Boelts, Michael Deistler, Jan-Matthis Lueckmann and Conor Durkan contributed equally in shared first authorship. This manuscript has been submitted for consideration to the Journal of Open Source Software (JOSS). 4 pages, no figures; v2: added link to sbi home

Stroke is a leading cause of death and disability. Recovery depends on a delicate balance between inflammatory responses and immune suppression, tipping the scale between brain protection and susceptibility to infection. Peripheral cholinergic blockade of immune reactions fine-tunes this immune response, but its molecular regulators are unknown. Here, we report a regulatory shift in small RNA types in patient blood sequenced two days after ischemic stroke, comprising massive decreases of microRNA levels and concomitant increases of transfer RNA fragments (tRFs) targeting cholinergic transcripts. Electrophoresis-based size-selection followed by RT-qPCR validated the top 6 upregulated tRFs in a separate cohort of stroke patients, and independent datasets of small and long RNA sequencing pinpointed immune cell subsets pivotal to these responses, implicating CD14+ monocytes in the cholinergic inflammatory reflex. In-depth small RNA targeting analyses revealed the most-perturbed pathways following stroke and implied a structural dichotomy between microRNA and tRF target sets. Furthermore, lipopolysaccharide stimulation of murine RAW 264.7 cells and human CD14+ monocytes upregulated the top 6 stroke-perturbed tRFs, and overexpression of stroke-inducible tRF-22-WE8SPOX52 using an ssRNA mimic induced downregulation of immune regulator Z-DNA binding protein 1 (Zbp1). In summary, we identified a “changing of the guards” between RNA types that may systemically affect homeostasis in post-stroke immune responses, and pinpointed multiple affected pathways, which opens new venues for establishing therapeutics and biomarkers at the protein- and RNA-level. Significance Statement Ischemic stroke triggers peripheral immunosuppression, increasing the susceptibility to post-stroke pneumonia that is linked with poor survival. The post-stroke brain initiates intensive communication with the immune system, and acetylcholine contributes to these messages; but the responsible molecules are yet unknown. We discovered a “changing of the guards,” where microRNA levels decreased but small transfer RNA fragments (tRFs) increased in post-stroke blood. This molecular switch may re-balance acetylcholine signaling in CD14+ monocytes by regulating their gene expression and modulating post-stroke immunity. Our observations point out to tRFs as molecular regulators of post-stroke immune responses that may be potential therapeutic targets.

Stereotypic behavior (SB) is common in emotional stress-involved psychiatric disorders and is often attributed to glutamatergic impairments, but the underlying molecular mechanisms are unknown. Given the neuro-modulatory role of acetylcholine, we sought behavioral-transcriptomic links in SB using TgR transgenic mice with impaired cholinergic transmission due to over-expression of the stress-inducible soluble &lsquo, readthrough&rsquo, acetylcholinesterase-R splice variant AChE-R. TgR mice showed impaired organization of behavior, performance errors in a serial maze test, escape-like locomotion, intensified reaction to pilocarpine and reduced rearing in unfamiliar situations. Small-RNA sequencing revealed 36 differentially expressed (DE) microRNAs in TgR mice hippocampi, 8 of which target more than 5 cholinergic transcripts. Moreover, compared to FVB/N mice, TgR prefrontal cortices displayed individually variable changes in over 400 DE mRNA transcripts, primarily acetylcholine and glutamate-related. Furthermore, TgR brains presented c-fos over-expression in motor behavior-regulating brain regions and immune-labeled AChE-R excess in the basal ganglia, limbic brain nuclei and the brain stem, indicating a link with the observed behavioral phenotypes. Our findings demonstrate association of stress-induced SB to previously unknown microRNA-mediated perturbations of cholinergic/glutamatergic networks and underscore new therapeutic strategies for correcting stereotypic behaviors.

Recent reports highlight regulatory functions of long noncoding RNAs (lncRNAs) in neurodegeneration and aging, but biomedical implications remain limited. Here, we report an rRNA‐depletion‐based long RNA‐Sequencing Resource of 65 substantia nigra, amygdala, and medial temporal gyrus samples from Parkinson's disease (PD) and matched control brains. Using a lncRNA‐focused analysis approach to identify functionally important transcripts, we discovered and prioritized many lncRNAs dysregulated in PD. Those included pronounced elevation of the P53‐induced noncoding transcript LINC‐PINT in the substantia nigra of PD patients, as well as in additional models of oxidative stress and PD. Intriguingly, we found that LINC‐PINT is a primarily neuronal transcript which showed conspicuous increases in maturing primary culture neurons. LINC‐PINT also accumulated in several brain regions of Alzheimer's and Huntington's disease patients and decreased with healthy brain aging, suggesting a general role in aging and neurodegeneration for this lncRNA. RNAi‐mediated depletion of LINC‐PINT exacerbated the death of cultured N2A and SH‐SY5Y cells exposed to oxidative stress, highlighting a previously undiscovered neuroprotective role for this tumor‐inducible lncRNA in the brains of patients with neurodegenerative disorders., We performed RNA‐Seq on a large cohort of brain tissues from Parkinson's disease patients and controls. Next, we applied a novel lncRNA‐based analysis method to the data to screen for functionally relevant lncRNAs, identifying LINC‐PINT. Comparison to other models identified LINC‐PINT as a neuronal transcript dysregulated in additional neurodegenerative diseases and in brain aging. Finally, functional analysis revealed LINC‐PINT to be neuroprotective in the context of oxidative stress.

This chapter describes the use of locked nucleic acid (LNA) GapmeRs for the in vivo knockdown of specific mRNAs in the mouse liver and phenotype analysis. LNA GapmeRs may be tested for efficacy by transfection in cultured cells. They are delivered into mice in vivo by intravenous tail injection .

Mechanistic modeling in neuroscience aims to explain observed phenomena in terms of underlying causes. However, determining which model parameters agree with complex and stochastic neural data presents a significant challenge. We address this challenge with a machine learning tool which uses deep neural density estimators—trained using model simulations—to carry out Bayesian inference and retrieve the full space of parameters compatible with raw data or selected data features. Our method is scalable in parameters and data features and can rapidly analyze new data after initial training. We demonstrate the power and flexibility of our approach on receptive fields, ion channels, and Hodgkin–Huxley models. We also characterize the space of circuit configurations giving rise to rhythmic activity in the crustacean stomatogastric ganglion, and use these results to derive hypotheses for underlying compensation mechanisms. Our approach will help close the gap between data-driven and theory-driven models of neural dynamics., eLife digest Computational neuroscientists use mathematical models built on observational data to investigate what’s happening in the brain. Models can simulate brain activity from the behavior of a single neuron right through to the patterns of collective activity in whole neural networks. Collecting the experimental data is the first step, then the challenge becomes deciding which computer models best represent the data and can explain the underlying causes of how the brain behaves. Researchers usually find the right model for their data through trial and error. This involves tweaking a model’s parameters until the model can reproduce the data of interest. But this process is laborious and not systematic. Moreover, with the ever-increasing complexity of both data and computer models in neuroscience, the old-school approach of building models is starting to show its limitations. Now, Gonçalves, Lueckmann, Deistler et al. have designed an algorithm that makes it easier for researchers to fit mathematical models to experimental data. First, the algorithm trains an artificial neural network to predict which models are compatible with simulated data. After initial training, the method can rapidly be applied to either raw experimental data or selected data features. The algorithm then returns the models that generate the best match. This newly developed machine learning tool was able to automatically identify models which can replicate the observed data from a diverse set of neuroscience problems. Importantly, further experiments showed that this new approach can be scaled up to complex mechanisms, such as how a neural network in crabs maintains its rhythm of activity. This tool could be applied to a wide range of computational investigations in neuroscience and other fields of biology, which may help bridge the gap between ‘data-driven’ and ‘theory-driven’ approaches.

Alzheimer's disease (AD) involves changes in both lipid and RNA metabolism, but it remained unknown if these differences associate with AD's cognition and/or post-mortem neuropathology indices. Here, we report RNA-sequencing evidence of inter-related associations between lipid processing, cognition level, and AD neuropathology. In two unrelated cohorts, we identified pathway-enriched facilitation of lipid processing and alternative splicing genes, including the neuronal-enriched NOVA1 and hnRNPA1. Specifically, this association emerged in temporal lobe tissue samples from donors where postmortem evidence demonstrated AD neuropathology, but who presented normal cognition proximate to death. The observed changes further associated with modified ATP synthesis and mitochondrial transcripts, indicating metabolic relevance; accordingly, mass-spectrometry-derived lipidomic profiles distinguished between individuals with and without cognitive impairment prior to death. In spite of the limited group sizes, tissues from persons with both cognitive impairment and AD pathology showed elevation in several drug-targeted genes of other brain, vascular and autoimmune disorders, accompanied by pathology-related increases in distinct lipid processing transcripts, and in the RNA metabolism genes hnRNPH2, TARDBP, CLP1 and EWSR1. To further detect 3′-polyadenylation variants, we employed multiple cDNA primer pairs. This identified variants that showed limited differences in scope and length between the tested cohorts, yet enabled superior clustering of demented and non-demented AD brains versus controls compared to total mRNA expression values. Our findings indicate inter-related cognition-associated differences in AD's lipid processing, alternative splicing and 3′-polyadenylation, calling for pursuing the underlying psychological and therapeutics implications., Highlights • RNA transcripts differ between brains from Alzheimer's patients with or without dementia. • In non-demented patients with pathology, brain neurons show facilitated RNA and lipid processing. • Cognition-related differences included brain, vascular and autoimmune disease-related genes. • Polyadenylation changes classify patients better than transcript expression levels.

ObjectiveBoth non-alcoholic fatty liver disease (NAFLD) and the multitarget complexity of microRNA (miR) suppression have recently raised much interest, but the in vivo impact and context-dependence of hepatic miR-target interactions are incompletely understood. Assessing the relative in vivo contributions of specific targets to miR-mediated phenotypes is pivotal for investigating metabolic processes.DesignWe quantified fatty liver parameters and the levels of miR-132 and its targets in novel transgenic mice overexpressing miR-132, in liver tissues from patients with NAFLD, and in diverse mouse models of hepatic steatosis. We tested the causal nature of miR-132 excess in these phenotypes by injecting diet-induced obese mice with antisense oligonucleotide suppressors of miR-132 or its target genes, and measured changes in metabolic parameters and transcripts.ResultsTransgenic mice overexpressing miR-132 showed a severe fatty liver phenotype and increased body weight, serum low-density lipoprotein/very low-density lipoprotein (LDL/VLDL) and liver triglycerides, accompanied by decreases in validated miR-132 targets and increases in lipogenesis and lipid accumulation-related transcripts. Likewise, liver samples from both patients with NAFLD and mouse models of hepatic steatosis or non-alcoholic steatohepatitis (NASH) displayed dramatic increases in miR-132 and varying decreases in miR-132 targets compared with controls. Furthermore, injecting diet-induced obese mice with anti-miR-132 oligonucleotides, but not suppressing its individual targets, reversed the hepatic miR-132 excess and hyperlipidemic phenotype.ConclusionsOur findings identify miR-132 as a key regulator of hepatic lipid homeostasis, functioning in a context-dependent fashion via suppression of multiple targets and with cumulative synergistic effects. This indicates reduction of miR-132 levels as a possible treatment of hepatic steatosis.

Chaperone networks are dysregulated with aging, but whether compromised Hsp70/Hsp90 chaperone function disturbs neuronal resilience is unknown. Stress-inducible phosphoprotein 1 (STI1; STIP1; HOP) is a co-chaperone that simultaneously interacts with Hsp70 and Hsp90, but whose function in vivo remains poorly understood. We combined in-depth analysis of chaperone genes in human datasets, analysis of a neuronal cell line lacking STI1 and of a mouse line with a hypomorphic Stip1 allele to investigate the requirement for STI1 in aging. Our experiments revealed that dysfunctional STI1 activity compromised Hsp70/Hsp90 chaperone network and neuronal resilience. The levels of a set of Hsp90 co-chaperones and client proteins were selectively affected by reduced levels of STI1, suggesting that their stability depends on functional Hsp70/Hsp90 machinery. Analysis of human databases revealed a subset of co-chaperones, including STI1, whose loss of function is incompatible with life in mammals, albeit they are not essential in yeast. Importantly, mice expressing a hypomorphic STI1 allele presented spontaneous age-dependent hippocampal neurodegeneration and reduced hippocampal volume, with consequent spatial memory deficit. We suggest that impaired STI1 function compromises Hsp70/Hsp90 chaperone activity in mammals and can by itself cause age-dependent hippocampal neurodegeneration in mice. Cover Image for this issue: doi: 10.1111/jnc.14749.

Multiphoton imaging of genetically encoded calcium indicators is routinely used to report activity from populations of spatially resolved neurons in vivo. However, since the relationship between fluorescence and action potentials (APs) is nonlinear and varies over neurons, quantitatively inferring AP discharge is problematic. To address this we developed a biophysical model of calcium binding kinetics for the indicator GCaMP6s that accurately describes AP-evoked fluorescence changes in vivo. The model's physical interpretation allowed the same parameters to describe GCaMP6s binding kinetics for both in vitro binding assays and in vivo imaging. Using this model, we developed an algorithm to infer APs from fluorescence and measured its accuracy with cell-attached electrical recordings. This approach consistently inferred more accurate AP counts and times than alternative methods for firing rates from 0 to >20 Hz, while requiring less training data. These results demonstrate the utility of quantitative, biophysically grounded models for complex biological data.

The Mesio-Temporal Lobe Epilepsy syndrome is the most common form of intractable epilepsy. It is characterized by recurrence of focal seizures and is often associated with hippocampal sclerosis and drug resistance. We aimed to characterize the molecular changes occurring during the initial stages of epileptogenesis in search of new therapeutic targets for Mesio-Temporal Lobe Epilepsy. We used a mouse model obtained by intra-hippocampal microinjection of kainate and performed hippocampal whole genome expression analysis at 6h, 12h and 24h post-injection, followed by multilevel bioinformatics analysis. We report significant changes in immune and inflammatory responses, neuronal network reorganization processes and glial functions, predominantly initiated during status epilepticus at 12h and persistent after the end of status epilepticus at 24h post-kainate. Upstream regulator analysis highlighted Cyba, Cybb and Vim as central regulators of multiple overexpressed genes implicated in glial responses at 24h. In silico microRNA analysis indicated that miR-9, miR-19b, miR-129, and miR-223 may regulate the expression of glial-associated genes at 24h. Our data support the hypothesis that glial-mediated inflammatory response holds a key role during epileptogenesis, and that microglial cells may participate in the initial process of epileptogenesis through increased ROS production via the NOX complex.

Chaperone networks are dysregulated with aging and neurodegenerative disease, but whether compromised Hsp70/Hsp90 chaperone function directly contributes to neuronal degeneration is unknown. Stress-inducible phosphoprotein-1 (STI1; STIP1; HOP) is a co-chaperone that simultaneously interacts with Hsp70 and Hsp90, but whose functionin vivoremains poorly understood. To investigate the requirement of STI1-mediated regulation of the chaperone machinery in aging we combined analysis of a mouse line with a hypomorphicStip1allele, with a neuronal cell line lacking STI1 and in-depth analyses of chaperone genes in human datasets. Loss of STI1 function severely disturbed the Hsp70/Hsp90 machineryin vivo, and all client proteins tested and a subset of cochaperones presented decreased levels. Importantly, mice expressing a hypomorphic STI1 allele showed spontaneous age-dependent hippocampal neurodegeneration, with consequent spatial memory deficits. STI1 is a critical node for the chaperone network and it can contribute to age-dependent hippocampal neurodegeneration.

Epilepsy is a common neurological disease, manifested in unprovoked recurrent seizures. Epileptogenesis may develop due to genetic or pharmacological origins or following injury, but it remains unclear how the unaffected brain escapes this susceptibility to seizures. Here, we report that dynamic changes in forebrain microRNA (miR)-211 in the mouse brain shift the threshold for spontaneous and pharmacologically induced seizures alongside changes in the cholinergic pathway genes, implicating this miR in the avoidance of seizures. We identified miR-211 as a putative attenuator of cholinergic-mediated seizures by intersecting forebrain miR profiles that were Argonaute precipitated, synaptic vesicle target enriched, or differentially expressed under pilocarpine-induced seizures, and validated TGFBR2 and the nicotinic antiinflammatory acetylcholine receptor nAChRa7 as murine and human miR-211 targets, respectively. To explore the link between miR-211 and epilepsy, we engineered dTg-211 mice with doxycycline-suppressible forebrain overexpression of miR-211. These mice reacted to doxycycline exposure by spontaneous electrocorticography-documented nonconvulsive seizures, accompanied by forebrain accumulation of the convulsive seizures mediating miR-134. RNA sequencing demonstrated in doxycycline-treated dTg-211 cortices overrepresentation of synaptic activity, Ca2+ transmembrane transport, TGFBR2 signaling, and cholinergic synapse pathways. Additionally, a cholinergic dysregulated mouse model overexpressing a miR refractory acetylcholinesterase-R splice variant showed a parallel propensity for convulsions, miR-211 decreases, and miR-134 elevation. Our findings demonstrate that in mice, dynamic miR-211 decreases induce hypersynchronization and nonconvulsive and convulsive seizures, accompanied by expression changes in cholinergic and TGFBR2 pathways as well as in miR-134. Realizing the importance of miR-211 dynamics opens new venues for translational diagnosis of and interference with epilepsy.

MicroRNAs (miRNAs) can repress multiple targets, but how a single de-balanced interaction affects others remained unclear. We found that changing a single miRNA–target interaction can simultaneously affect multiple other miRNA–target interactions and modify physiological phenotype. We show that miR-608 targets acetylcholinesterase (AChE) and demonstrate weakened miR-608 interaction with the rs17228616 AChE allele having a single-nucleotide polymorphism (SNP) in the 3′-untranslated region (3′UTR). In cultured cells, this weakened interaction potentiated miR-608-mediated suppression of other targets, including CDC42 and interleukin-6 (IL6). Postmortem human cortices homozygote for the minor rs17228616 allele showed AChE elevation and CDC42/IL6 decreases compared with major allele homozygotes. Additionally, minor allele heterozygote and homozygote subjects showed reduced cortisol and elevated blood pressure, predicting risk of anxiety and hypertension. Parallel suppression of the conserved brain CDC42 activity by intracerebroventricular ML141 injection caused acute anxiety in mice. We demonstrate that SNPs in miRNA-binding regions could cause expanded downstream effects changing important biological pathways. Accepted version

Developing microRNA therapeutics for neurological diseases is both a promising opportunity and an extremely challenging topic for several reasons. The promise stems from the very small size of microRNAs, which makes them amenable for manipulation via short synthetic oligonucleotides or engineered viruses. Also, the fact that each microRNA may regulate numerous target transcripts of the same pathway predicts that such manipulations may affect an entire pathway rather than a single gene and gives reason to hope that low dose therapeutic targeting of the top microRNA in such a hierarchic pyramid would suffice to induce a focused change in the entire pyramid. However, these same features, which make microRNAs such promising targets for therapeutic manipulations also present great challenges. Thus the plethora of functional targets for each microRNA in specific cell types is yet far from being elucidated, which implies that the targets to be affected may not be those planned to be manipulated (a risk of 'off-target' effects). Also, the hierarchic order of microRNA regulation is yet unknown, which predicts a risk of complex, multi-leveled consequences following the manipulation of a single microRNA; and the delivery of oligonucleotide therapeutics into the brain is a challenge due to the blood-brain barrier. In this chapter, we briefly outline the current state of knowledge regarding microRNA regulation in different neuropathologies and sketch the emerging principles for the development of microRNA therapeutics for these diseases.We address issues such as modes of delivery and consideration of the inherited and acquired variability between individuals in the susceptibility to such treatments. We further refer in a somewhat more in-depth manner to the issue of manipulating microRNA functioning in the parasympathetic system and the pathway of cholinergic signaling. Beyond the brain and within it, cholinergic signaling controls inflammatory reactions, and microRNA changes would likely affect this function as well. Furthermore, microRNA regulation of cholinergic signaling involves the elements of complexity and hierarchy noted above, and is relevant to numerous neuropathologies and neurodegenerative syndromes. Research and translational efforts that lead to the development of microRNA therapeutics merit thorough discussion.