SMN is required for sensory-motor circuit function in Drosophila.

Spinal muscular atrophy (SMA) is a lethal human disease characterized by motor neuron dysfunction and muscle deterioration due to depletion of the ubiquitous survival motor neuron (SMN) protein. Drosophila SMN mutants have reduced muscle size and defective locomotion, motor rhythm, and motor neuron neurotransmission. Unexpectedly, restoration of SMN in either muscles or motor neurons did not alter these phenotypes. Instead, SMN must be expressed in proprioceptive neurons and interneurons in the motor circuit to nonautonomously correct defects in motor neurons and muscles. SMN depletion disrupts the motor system subsequent to circuit development and can be mimicked by the inhibition of motor network function. Furthermore, increasing motor circuit excitability by genetic or pharmacological inhibition of K(+) channels can correct SMN-dependent phenotypes. These results establish sensory-motor circuit dysfunction as the origin of motor system deficits in this SMA model and suggest that enhancement of motor neural network activity could ameliorate the disease.

An SMN-dependent U12 splicing event essential for motor circuit function.

Spinal muscular atrophy (SMA) is a motor neuron disease caused by deficiency of the ubiquitous survival motor neuron (SMN) protein. To define the mechanisms of selective neuronal dysfunction in SMA, we investigated the role of SMN-dependent U12 splicing events in the regulation of motor circuit activity. We show that SMN deficiency perturbs splicing and decreases the expression of a subset of U12 intron-containing genes in mammalian cells and Drosophila larvae. Analysis of these SMN target genes identifies Stasimon as a protein required for motor circuit function. Restoration of Stasimon expression in the motor circuit corrects defects in neuromuscular junction transmission and muscle growth in Drosophila SMN mutants and aberrant motor neuron development in SMN-deficient zebrafish. These findings directly link defective splicing of critical neuronal genes induced by SMN deficiency to motor circuit dysfunction, establishing a molecular framework for the selective pathology of SMA.

Effect of motion, cortical orientation and spatial resolution on quantitative imaging of cortical R2* and magnetic susceptibility at 0.3 mm in-plane resolution at 7 T.

MR images of the effective relaxation rate R2* and magnetic susceptibility χ derived from multi-echo T2*-weighted (T2*w) MRI can provide insight into iron and myelin distributions in the brain, with the potential of providing biomarkers for neurological disorders. Quantification of R2* and χ at submillimeter resolution in the cortex in vivo has been difficult because of challenges such as head motion, limited signal to noise ratio, long scan time, and motion related magnetic field fluctuations. This work aimed to improve the robustness for quantifying intracortical R2* and χ and analyze the effects from motion, spatial resolution, and cortical orientation. T2*w data was acquired with a spatial resolution of 0.3 × 0.3 × 0.4 mm3 at 7 T and downsampled to various lower resolutions. A combined correction for motion and B0 changes was deployed using volumetric navigators. Such correction improved the T2*w image quality rated by experienced image readers and test-retest reliability of R2* and χ quantification with reduced median inter-scan differences up to 10 s-1 and 5 ppb, respectively. R2* and χ near the line of Gennari, a cortical layer high in iron and myelin, were as much as 10 s-1 and 10 ppb higher than the region at adjacent cortical depth. In addition, a significant effect due to the cortical orientation relative to the static field (B0) was observed in χ with a peak-to-peak amplitude of about 17 ppb. In retrospectively downsampled data, the capability to distinguish different cortical depth regions based on R2* or χ contrast remained up to isotropic 0.5 mm resolution. This study highlights the unique characteristics of R2* and χ along the cortical depth at submillimeter resolution and the need for motion and B0 corrections for their robust quantification in vivo.

Multicenter Evaluation of AI-generated DIR and PSIR for Cortical and Juxtacortical Multiple Sclerosis Lesion Detection.

Background Cortical multiple sclerosis lesions are clinically relevant but inconspicuous at conventional clinical MRI. Double inversion recovery (DIR) and phase-sensitive inversion recovery (PSIR) are more sensitive but often unavailable. In the past 2 years, artificial intelligence (AI) was used to generate DIR and PSIR from standard clinical sequences (eg, T1-weighted, T2-weighted, and fluid-attenuated inversion-recovery sequences), but multicenter validation is crucial for further implementation. Purpose To evaluate cortical and juxtacortical multiple sclerosis lesion detection for diagnostic and disease monitoring purposes on AI-generated DIR and PSIR images compared with MRI-acquired DIR and PSIR images in a multicenter setting. Materials and Methods Generative adversarial networks were used to generate AI-based DIR (n = 50) and PSIR (n = 43) images. The number of detected lesions between AI-generated images and MRI-acquired (reference) images was compared by randomized blinded scoring by seven readers (all with >10 years of experience in lesion assessment). Reliability was expressed as the intraclass correlation coefficient (ICC). Differences in lesion subtype were determined using Wilcoxon signed-rank tests. Results MRI scans of 202 patients with multiple sclerosis (mean age, 46 years ± 11 [SD]; 127 women) were retrospectively collected from seven centers (February 2020 to January 2021). In total, 1154 lesions were detected on AI-generated DIR images versus 855 on MRI-acquired DIR images (mean difference per reader, 35.0% ± 22.8; P < .001). On AI-generated PSIR images, 803 lesions were detected versus 814 on MRI-acquired PSIR images (98.9% ± 19.4; P = .87). Reliability was good for both DIR (ICC, 0.81) and PSIR (ICC, 0.75) across centers. Regionally, more juxtacortical lesions were detected on AI-generated DIR images than on MRI-acquired DIR images (495 [42.9%] vs 338 [39.5%]; P < .001). On AI-generated PSIR images, fewer juxtacortical lesions were detected than on MRI-acquired PSIR images (232 [28.9%] vs 282 [34.6%]; P = .02). Conclusion Artificial intelligence-generated double inversion-recovery and phase-sensitive inversion-recovery images performed well compared with their MRI-acquired counterparts and can be considered reliable in a multicenter setting, with good between-reader and between-center interpretative agreement. Published under a CC BY 4.0 license. Supplemental material is available for this article. See also the editorial by Zivadinov and Dwyer in this issue.

Pembrolizumab Treatment for Progressive Multifocal Leukoencephalopathy.

BACKGROUND: Progressive multifocal leukoencephalopathy (PML) is an opportunistic brain infection that is caused by the JC virus and is typically fatal unless immune function can be restored. Programmed cell death protein 1 (PD-1) is a negative regulator of the immune response that may contribute to impaired viral clearance. Whether PD-1 blockade with pembrolizumab could reinvigorate anti-JC virus immune activity in patients with PML was unknown. METHODS: We administered pembrolizumab at a dose of 2 mg per kilogram of body weight every 4 to 6 weeks to eight adults with PML, each with a different underlying predisposing condition. Each patient received at least one dose but no more than three doses. RESULTS: Pembrolizumab induced down-regulation of PD-1 expression on lymphocytes in peripheral blood and in cerebrospinal fluid (CSF) in all eight patients. Five patients had clinical improvement or stabilization of PML accompanied by a reduction in the JC viral load in the CSF and an increase in in vitro CD4+ and CD8+ anti-JC virus activity. In the other three patients, no meaningful change was observed in the viral load or in the magnitude of antiviral cellular immune response, and there was no clinical improvement. CONCLUSIONS: Our findings are consistent with the hypothesis that in some patients with PML, pembrolizumab reduces JC viral load and increases CD4+ and CD8+ activity against the JC virus; clinical improvement or stabilization occurred in five of the eight patients who received pembrolizumab. Further study of immune checkpoint inhibitors in the treatment of PML is warranted. (Funded by the National Institutes of Health.).

7T MRI Differentiates Remyelinated from Demyelinated Multiple Sclerosis Lesions.

OBJECTIVE: To noninvasively assess myelin status in chronic white matter lesions of multiple sclerosis (MS), we developed and evaluated a simple classification scheme based on T1 relaxation time maps derived from 7-tesla postmortem and in vivo MRI. METHODS: Using the MP2RAGE MRI sequence, we classified 36 lesions from 4 postmortem MS brains as "long-T1," "short-T1," and "mixed-T1" by visual comparison to neocortex. Within these groups, we compared T1 times to histologically derived measures of myelin and axons. We performed similar analysis of 235 chronic lesions with known date of onset in 25 MS cases in vivo and in a validation cohort of 222 lesions from 66 MS cases, investigating associations with clinical and radiological outcomes. RESULTS: Postmortem, lesions classified qualitatively as long-T1, short-T1, and mixed-T1 corresponded to fully demyelinated, fully remyelinated, and mixed demyelinated/remyelinated lesions, respectively (p ≤ 0.001). Demyelination (rather than axon loss) dominantly contributed to initial T1 prolongation. We observed lesions with similar characteristics in vivo, allowing manual classification with substantial interrater and excellent intrarater reliability. Short-T1 lesions were most common in the deep white matter, whereas long-T1 and mixed-T1 lesions were prevalent in the juxtacortical and periventricular white matter (p = 0.02) and were much more likely to have paramagnetic rims suggesting chronic inflammation (p < 0.001). Older age at the time of lesion formation portended less remyelination (p = 0.007). INTERPRETATION: 7-tesla T1 mapping with MP2RAGE, a clinically available MRI method, allows qualitative and quantitative classification of chronic MS lesions according to myelin content, rendering straightforward the tracking of lesional myelination changes over time. ANN NEUROL 2021;90:612-626.

Multiple sclerosis cortical lesion detection with deep learning at ultra-high-field MRI.

Manually segmenting multiple sclerosis (MS) cortical lesions (CLs) is extremely time consuming, and past studies have shown only moderate inter-rater reliability. To accelerate this task, we developed a deep-learning-based framework (CLAIMS: Cortical Lesion AI-Based Assessment in Multiple Sclerosis) for the automated detection and classification of MS CLs with 7 T MRI. Two 7 T datasets, acquired at different sites, were considered. The first consisted of 60 scans that include 0.5 mm isotropic MP2RAGE acquired four times (MP2RAGE×4), 0.7 mm MP2RAGE, 0.5 mm T2 *-weighted GRE, and 0.5 mm T2 *-weighted EPI. The second dataset consisted of 20 scans including only 0.75 × 0.75 × 0.9 mm3 MP2RAGE. CLAIMS was first evaluated using sixfold cross-validation with single and multi-contrast 0.5 mm MRI input. Second, the performance of the model was tested on 0.7 mm MP2RAGE images after training with either 0.5 mm MP2RAGE×4, 0.7 mm MP2RAGE, or alternating the two. Third, its generalizability was evaluated on the second external dataset and compared with a state-of-the-art technique based on partial volume estimation and topological constraints (MSLAST). CLAIMS trained only with MP2RAGE×4 achieved results comparable to those of the multi-contrast model, reaching a CL true positive rate of 74% with a false positive rate of 30%. Detection rate was excellent for leukocortical and subpial lesions (83%, and 70%, respectively), whereas it reached 53% for intracortical lesions. The correlation between disability measures and CL count was similar for manual and CLAIMS lesion counts. Applying a domain-scanner adaptation approach and testing CLAIMS on the second dataset, the performance was superior to MSLAST when considering a minimum lesion volume of 6 µL (lesion-wise detection rate of 71% versus 48%). The proposed framework outperforms previous state-of-the-art methods for automated CL detection across scanners and protocols. In the future, CLAIMS may be useful to support clinical decisions at 7 T MRI, especially in the field of diagnosis and differential diagnosis of MS patients.

Lesion size and shape in central vein sign assessment for multiple sclerosis diagnosis: An in vivo and postmortem MRI study.

BACKGROUND: The "central vein sign" (CVS), a linear hypointensity on T2*-weighted imaging corresponding to a central vein/venule, is associated with multiple sclerosis (MS) lesions. The effect of lesion-size exclusion criteria on MS diagnostic accuracy has not been extensively studied. OBJECTIVE: Investigate the optimal lesion-size exclusion criteria for CVS use in MS diagnosis. METHODS: Cross-sectional study of 163 MS and 51 non-MS, and radiological/histopathological correlation of 5 MS and 1 control autopsy cases. The effects of lesion-size exclusion on MS diagnosis using the CVS, and intralesional vein detection on histopathology were evaluated. RESULTS: CVS+ lesions were larger compared to CVS- lesions, with effect modification by MS diagnosis (mean difference +7.7 mm3, p = 0.004). CVS percentage-based criteria with no lesion-size exclusion showed the highest diagnostic accuracy in differentiating MS cases. However, a simple count of three or more CVS+ lesions greater than 3.5 mm is highly accurate and can be rapidly implemented (sensitivity 93%; specificity 88%). On magnetic resonance imaging (MRI)-histopathological correlation, the CVS had high specificity for identifying intralesional veins (0/7 false positives). CONCLUSION: Lesion-size measures add important information when using CVS+ lesion counts for MS diagnosis. The CVS is a specific biomarker corresponding to intralesional veins on histopathology.

Cortical lesion hotspots and association of subpial lesions with disability in multiple sclerosis.

BACKGROUND: Dramatic improvements in visualization of cortical (especially subpial) multiple sclerosis (MS) lesions allow assessment of impact on clinical course. OBJECTIVE: Characterize cortical lesions by 7 tesla (T) T2*-/T1-weighted magnetic resonance imaging (MRI); determine relationship with other MS pathology and contribution to disability. METHODS: Sixty-four adults with MS (45 relapsing-remitting/19 progressive) underwent 3 T brain/spine MRI, 7 T brain MRI, and clinical testing. RESULTS: Cortical lesions were found in 94% (progressive: median 56/range 2-203; relapsing-remitting: 15/0-168; p = 0.004). Lesion distribution across 50 cortical regions was nonuniform (p = 0.006), with highest lesion burden in supplementary motor cortex and highest prevalence in superior frontal gyrus. Leukocortical and white matter lesion volumes were strongly correlated (r = 0.58, p < 0.0001), while subpial and white matter lesion volumes were moderately correlated (r = 0.30, p = 0.002). Leukocortical (p = 0.02) but not subpial lesions (p = 0.40) were correlated with paramagnetic rim lesions; both were correlated with spinal cord lesions (p = 0.01). Cortical lesion volumes (total and subtypes) were correlated with expanded disability status scale, 25-foot timed walk, nine-hole peg test, and symbol digit modality test scores. CONCLUSION: Cortical lesions are highly prevalent and are associated with disability and progressive disease. Subpial lesion burden is not strongly correlated with white matter lesions, suggesting differences in inflammation and repair mechanisms.

Ultrahigh-resolution MRI Reveals Extensive Cortical Demyelination in a Nonhuman Primate Model of Multiple Sclerosis.

Cortical lesions are a primary driver of disability in multiple sclerosis (MS). However, noninvasive detection of cortical lesions with in vivo magnetic resonance imaging (MRI) remains challenging. Experimental autoimmune encephalomyelitis (EAE) in the common marmoset is a relevant animal model of MS for investigating the pathophysiological mechanisms leading to brain damage. This study aimed to characterize cortical lesions in marmosets with EAE using ultrahigh-field (7 T) MRI and histological analysis. Tissue preparation was optimized to enable the acquisition of high-spatial resolution (50-µm isotropic) T2*-weighted images. A total of 14 animals were scanned in this study, and 70% of the diseased animals presented at least one cortical lesion on postmortem imaging. Cortical lesions identified on MRI were verified with myelin proteolipid protein immunostaining. An optimized T2*-weighted sequence was developed for in vivo imaging and shown to capture 65% of cortical lesions detected postmortem. Immunostaining confirmed extensive demyelination with preserved neuronal somata in several cortical areas of EAE animals. Overall, this study demonstrates the relevance and feasibility of the marmoset EAE model to study cortical lesions, among the most important yet least understood features of MS.

Large-scale comparative analysis of microbial pan-genomes using PanOCT.

SUMMARY: The JCVI pan-genome pipeline is a collection of programs to run PanOCT and tools that support and extend the capabilities of PanOCT. PanOCT (pan-genome ortholog clustering tool) is a tool for pan-genome analysis of closely related prokaryotic species or strains. The JCVI Pan-Genome Pipeline wrapper invokes command-line utilities that prepare input genomes, invoke third-party tools such as NCBI Blast+, run PanOCT, generate a consensus pan-genome, annotate features of the pan-genome, detect sets of genes of interest such as antimicrobial resistance (AMR) genes and generate figures, tables and html pages to visualize the results. The pipeline can run in a hierarchical mode, lowering the RAM and compute resources used. AVAILABILITY AND IMPLEMENTATION: Source code, demo data, and detailed documentation are freely available at https://github.com/JCVenterInstitute/PanGenomePipeline.

Fatal encephalopathy with wild-type JC virus and ruxolitinib therapy.

OBJECTIVE: JC virus (JCV) infection is a lytic infection of oligodendrocytes in progressive multifocal leukoencephalopathy; less common forms of central nervous system manifestations associated with JCV infection include granule cell neuronopathy, encephalopathy, and meningitis. Presented is the first case of fatal JCV encephalopathy after immunosuppressive therapy that included ruxolitinib. METHODS: Postmortem analysis included next generation sequencing, Sanger sequencing, tissue immunohistochemistry, and formalin-fixed hemisphere 7T magnetic resonance imaging. RESULTS: JCV DNA isolated from postmortem tissue samples identified a novel 12bp insertion that altered the transcription site binding pattern in an otherwise "wild-type virus," which has long been thought to be the nonpathogenic form of JCV. Anti-VP1 staining demonstrated infection in cortical neurons, hippocampal neurons, and glial and endothelial cells. INTERPRETATION: This expands the spectrum of identified JCV diseases associated with broad-spectrum immunosuppression, including JAK-STAT inhibitors, and sheds light on an additional neurotropic virus strain of the archetype variety. ANN NEUROL 2019;86:878-884.

LOCUST: a custom sequence locus typer for classifying microbial isolates.

SUMMARY: LOCUST is a custom sequence locus typer tool for classifying microbial genomes. It provides a fully automated opportunity to customize the classification of genome-wide nucleotide variant data most relevant to biological research. AVAILABILITY AND IMPLEMENTATION: Source code, demo data, and detailed documentation are freely available at http://sourceforge.net/projects/locustyper . CONTACT: lbrinkac@jcvi.org. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Genetic effects on sleep/wake variation of seizures.

OBJECTIVE: There is a complex bidirectional relationship between sleep and epilepsy. Sleep/wake timing of seizures has been investigated for several individual seizure types and syndromes, but few large-scale studies of the timing of seizures exist in people with varied epilepsy types. In addition, the genetic contributions to seizure timing have not been well studied. METHODS: Sleep/wake timing of seizures was determined for 1,395 subjects in 546 families enrolled in the Epilepsy Phenome/Genome Project (EPGP). We examined seizure timing among subjects with different epilepsy types, seizure types, epilepsy syndromes, and localization. We also examined the familial aggregation of sleep/wake occurrence of seizures. RESULTS: Seizures in nonacquired focal epilepsy (NAFE) were more likely to occur during sleep than seizures in generalized epilepsy (GE), for both convulsive (odds ratio [OR] 5.2, 95% confidence interval [CI] 3.59-7.52) and nonconvulsive seizures (OR 4.2, 95% CI 2.48-7.21). Seizures occurring within 1 h of awakening were more likely to occur in patients with GE than with NAFE for both convulsive (OR 2.3, 95% CI 1.54-3.39) and nonconvulsive (OR 1.7, 95% CI 1.04-2.66) seizures. Frontal onset seizures were more likely than temporal onset seizures to occur during sleep. Sleep/wake timing of seizures in first-degree relatives predicted timing of seizures in the proband. SIGNIFICANCE: We found that sleep/wake timing of seizures is associated with both epilepsy syndrome and seizure type. In addition, we provide the first evidence for a genetic contribution to sleep/wake timing of seizures in a large group of individuals with common epilepsy syndromes.

Theta and high-frequency activity mark spontaneous recall of episodic memories.

Humans possess the remarkable ability to search their memory, allowing specific past episodes to be re-experienced spontaneously. Here, we administered a free recall test to 114 neurosurgical patients and used intracranial theta and high-frequency activity (HFA) to identify the spatiotemporal pattern of neural activity underlying spontaneous episodic retrieval. We found that retrieval evolved in three electrophysiological stages composed of: (1) early theta oscillations in the right temporal cortex, (2) increased HFA in the left hemisphere including the medial temporal lobe (MTL), left inferior frontal gyrus, as well as the ventrolateral temporal cortex, and (3) motor/language activation during vocalization of the retrieved item. Of these responses, increased HFA in the left MTL predicted recall performance. These results suggest that spontaneous recall of verbal episodic memories involves a spatiotemporal pattern of spectral changes across the brain; however, high-frequency activity in the left MTL represents a final common pathway of episodic retrieval.

A maize database resource that captures tissue-specific and subcellular-localized gene expression, via fluorescent tags and confocal imaging (Maize Cell Genomics Database).

Maize is a global crop and a powerful system among grain crops for genetic and genomic studies. However, the development of novel biological tools and resources to aid in the functional identification of gene sequences is greatly needed. Towards this goal, we have developed a collection of maize marker lines for studying native gene expression in specific cell types and subcellular compartments using fluorescent proteins (FPs). To catalog FP expression, we have developed a public repository, the Maize Cell Genomics (MCG) Database, (http://maize.jcvi.org/cellgenomics), to organize a large data set of confocal images generated from the maize marker lines. To date, the collection represents major subcellular structures and also developmentally important progenitor cell populations. The resource is available to the research community, for example to study protein localization or interactions under various experimental conditions or mutant backgrounds. A subset of the marker lines can also be used to induce misexpression of target genes through a transactivation system. For future directions, the image repository can be expanded to accept new image submissions from the research community, and to perform customized large-scale computational image analysis. This community resource will provide a suite of new tools for gaining biological insights by following the dynamics of protein expression at the subcellular, cellular and tissue levels.

TIGRFAMs and Genome Properties in 2013.

TIGRFAMs, available online at http://www.jcvi.org/tigrfams is a database of protein family definitions. Each entry features a seed alignment of trusted representative sequences, a hidden Markov model (HMM) built from that alignment, cutoff scores that let automated annotation pipelines decide which proteins are members, and annotations for transfer onto member proteins. Most TIGRFAMs models are designated equivalog, meaning they assign a specific name to proteins conserved in function from a common ancestral sequence. Models describing more functionally heterogeneous families are designated subfamily or domain, and assign less specific but more widely applicable annotations. The Genome Properties database, available at http://www.jcvi.org/genome-properties, specifies how computed evidence, including TIGRFAMs HMM results, should be used to judge whether an enzymatic pathway, a protein complex or another type of molecular subsystem is encoded in a genome. TIGRFAMs and Genome Properties content are developed in concert because subsystems reconstruction for large numbers of genomes guides selection of seed alignment sequences and cutoff values during protein family construction. Both databases specialize heavily in bacterial and archaeal subsystems. At present, 4284 models appear in TIGRFAMs, while 628 systems are described by Genome Properties. Content derives both from subsystem discovery work and from biocuration of the scientific literature.

PanOCT: automated clustering of orthologs using conserved gene neighborhood for pan-genomic analysis of bacterial strains and closely related species.

Pan-genome ortholog clustering tool (PanOCT) is a tool for pan-genomic analysis of closely related prokaryotic species or strains. PanOCT uses conserved gene neighborhood information to separate recently diverged paralogs into orthologous clusters where homology-only clustering methods cannot. The results from PanOCT and three commonly used graph-based ortholog-finding programs were compared using a set of four publicly available strains of the same bacterial species. All four methods agreed on ∼70% of the clusters and ∼86% of the proteins. The clusters that did not agree were inspected for evidence of correctness resulting in 85 high-confidence manually curated clusters that were used to compare all four methods.