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von Hippel-Lindau (VHL) disease is an autosomal dominant hereditary cancer disorder caused by a germline mutation in the VHL tumor suppressor gene. Loss of the wild-type allele results in VHL deficiency and the potential formation of cerebellar hemangioblastomas, which resemble embryonic hemangioblast proliferation and differentiation processes. Multiple, microscopic, VHL-deficient precursors, termed developmentally arrested structural elements (DASEs), consistently involve the cerebellar molecular layer in VHL patients, indicating the tumor site of origin. Unlike hemangioblastomas, however, cerebellar DASEs do not express brachyury, a mesodermal marker for hemangioblasts. In this study, neuronal progenitors occupying the molecular layer were investigated as tumor cells of origin. By immunohistochemistry, cerebellar DASEs and hemangioblastomas lacked immunoreactivity with antibody ZIC1 (Zic family member 1), a granule cell progenitor marker with concordance from oligonucleotide RNA expression array analyses. Rather, cerebellar DASEs and hemangioblastomas were immunoreactive with antibody PAX2 (paired box 2), a marker of basket/stellate cell progenitors. VHL cerebellar cortices also revealed PAX2-positive cells in Purkinje and molecular layers, resembling the histological and molecular development of basket/stellate cells in postnatal non-VHL mouse and human cerebella. These data suggest that VHL deficiency can result in the developmental arrest of basket/stellate cells in the human cerebellum and that these PAX2-positive, initiated cells await another insult or signal to form DASEs and eventually, tumors.

Glioblastoma multiforme is the most common primary malignant brain tumor and despite treatment with surgery, radiation, and chemotherapy, the median survival of patients with glioblastoma multiforme is ∼1 year. Glioblastoma multiforme explants and cell lines have been reported to overexpress the interleukin-13 receptor α2 subunit (IL13Rα2) relative to nonneoplastic brain. Based on this finding, a recombinant cytotoxin composed of IL13 ligand and a truncated form of Pseudomonas aeruginosa exotoxin A (IL13-PE38QQR) was developed for the targeted treatment of glioblastoma multiforme tumors. In a recently completed phase III clinical trial, however, IL13-PE38QQR was found to be no more effective than an existing therapy in prolonging survival. To determine possible explanations for this result, we analyzed the relative expression levels of IL13Rα2 in glioblastoma multiforme and nonneoplastic brain specimens using publicly available oligonucleotide microarray databases, quantitative real-time reverse transcription PCR, and immunohistochemical staining. Increased expression of the IL13Rα2 gene relative to nonneoplastic brain was observed in 36 of 81 (44%) and 8 of 17 (47%) tumor specimens by microarray and quantitative real-time reverse transcription PCR analyses, respectively. Immunohistochemical staining of tumor specimens showed highly variable expression of IL13Rα2 protein both within and across specimens. These data indicate that prescreening of subjects may be of benefit in future trials of IL13Rα2 targeting therapies. [Cancer Res 2007;67(17):7983–6]

Supplementary Figure 1 from Expression of Interleukin-13 Receptor α2 in Glioblastoma Multiforme: Implications for Targeted Therapies

Supplementary Figure 1 Legend from Expression of Interleukin-13 Receptor α2 in Glioblastoma Multiforme: Implications for Targeted Therapies

The underlying etiologies of seizures are highly heterogeneous and remain incompletely understood. While studying the unfolded protein response (UPR) pathways in the brain, we unexpectedly discovered that transgenic mice (XBP1s-TG) expressing spliced X-box–binding protein-1 (Xbp1s), a key effector of UPR signaling, in forebrain excitatory neurons, rapidly develop neurologic deficits, most notably recurrent spontaneous seizures. This seizure phenotype begins around 8 days after Xbp1s transgene expression is induced in XBP1s-TG mice, and by approximately 14 days post induction, the seizures evolve into status epilepticus with nearly continuous seizure activity followed by sudden death. Animal death is likely due to severe seizures because the anticonvulsant valproic acid could significantly prolong the lives of XBP1s-TG mice. Mechanistically, our gene profiling analysis indicates that compared to control mice, XBP1s-TG mice exhibit 591 differentially regulated genes (mostly upregulated) in the brain, including several GABAA receptor genes that are notably downregulated. Finally, whole-cell patch clamp analysis reveals a significant reduction in both spontaneous and tonic GABAergic inhibitory responses in Xbp1s-expressing neurons. Taken together, our findings unravel a link between XBP1s signaling and seizure occurrence.

Progranulin (PGRN) is a lysosomal protein implicated in various neurodegenerative diseases. Over 70 mutations discovered in theGRNgene all result in reduced expression of PGRN protein. However, the detailed molecular function of PGRN within lysosomes and the impact of PGRN deficiency on lysosomal biology remain unclear. Here we leveraged multifaceted proteomic techniques to comprehensively characterize how PGRN deficiency changes the molecular and functional landscape of neuronal lysosomes. Using lysosome proximity labeling and immuno-purification of intact lysosomes, we characterized lysosome compositions and interactomes in both human induced pluripotent stem cell (iPSC)-derived glutamatergic neurons (i3Neurons) and mouse brains. Using dynamic stable isotope labeling by amino acids in cell culture (dSILAC) proteomics, we measured global protein half-lives in i3Neurons for the first time and characterized the impact of progranulin deficiency on neuronal proteostasis. Together, this study indicated that PGRN loss impairs the lysosome’s degradative capacity with increased levels of v-ATPase subunits on the lysosome membrane, increased catabolic enzymes within the lysosome, elevated lysosomal pH, and pronounced alterations in neuron protein turnover. Collectively, these results suggested PGRN as a critical regulator of lysosomal pH and degradative capacity, which in turn influences global proteostasis in neurons. The multi-modal techniques developed here also provided useful data resources and tools to study the highly dynamic lysosome biology in neurons.

Multiple sclerosis (MS) is a chronic inflammatory demyelinating disease of the central nervous system (CNS). Although various viruses have been proposed to contribute to MS pathology, the etiology of MS remains unknown. Since intrathecal antibody synthesis is well documented in chronic viral infection and neuroinflammatory diseases, we hypothesized whether the patterns of antigen-specific antibody responses associated with various viral exposures may define patients with CNS chronic immune dysregulation. The pan-viral antibody profiling in cerebrospinal fluid (CSF) and serum of patients with MS showed significant differences from those in healthy volunteers and a pattern of antibody responses against multiple viruses, including the previously identified Epstein-Barr virus. These findings demonstrate that virus-specific antibody signatures might be able to reflect disease-associated inflammatory milieu in CSF of subjects with neuroinflammatory diseases.

Mutations in genes encoding Na+ /K+ -ATPase α1, α2, and α3 subunits cause a wide range of disabling neurological disorders, and dysfunction of Na+ /K+ -ATPase may contribute to neuronal injury in stroke and dementia. To better understand the pathogenesis of these diseases, it is important to determine the expression patterns of the different Na+ /K+ -ATPase subunits within the brain and among specific cell types. Using two available scRNA-Seq databases from the adult mouse nervous system, we examined the mRNA expression patterns of the different isoforms of the Na+ /K+ -ATPase α, β and Fxyd subunits at the single cell level among brain regions and various neuronal populations. We subsequently identified specific types of neurons enriched with transcripts for α1 and α3 isoforms and elaborated how α3-expressing neuronal populations govern cerebellar neuronal circuits. We further analyzed the co-expression network for α1 and α3 isoforms, highlighting the genes that positively correlated with α1 and α3 expression. The top ten genes for α1 were Chn2, Hpcal1, Nrgn, Neurod1, Selm, Kcnc1, Snrk, Snap25, Ckb and Ccndbp1 and for α3 were Sorcs3, Eml5, Neurod2, Ckb, Tbc1d4, Ptprz1, Pvrl1, Kirrel3, Pvalb, and Asic2.

Despite strong evidence of heritability and growing discovery of genetic markers for major mental illness, little is known about how gene expression in the brain differs across psychiatric diagnoses, or how known genetic risk factors shape these differences. Here we investigate expressed genes and gene transcripts in postmortem subgenual anterior cingulate cortex (sgACC), a key component of limbic circuits linked to mental illness. RNA obtained postmortem from 200 donors diagnosed with bipolar disorder, schizophrenia, major depression, or no psychiatric disorder was deeply sequenced to quantify expression of over 85,000 gene transcripts, many of which were rare. Case–control comparisons detected modest expression differences that were correlated across disorders. Case–case comparisons revealed greater expression differences, with some transcripts showing opposing patterns of expression between diagnostic groups, relative to controls. The ~250 rare transcripts that were differentially-expressed in one or more disorder groups were enriched for genes involved in synapse formation, cell junctions, and heterotrimeric G-protein complexes. Common genetic variants were associated with transcript expression (eQTL) or relative abundance of alternatively spliced transcripts (sQTL). Common genetic variants previously associated with disease risk were especially enriched for sQTLs, which together accounted for disproportionate fractions of diagnosis-specific heritability. Genetic risk factors that shape the brain transcriptome may contribute to diagnostic differences between broad classes of mental illness.

The transactivator of transcription (Tat) is a key HIV regulatory protein. We aimed to identify the frequency of key polymorphisms in HIV-1C compared with HIV-1B Tat protein, chiefly in the cysteine-, arginine-, and glutamine-rich domains and identify novel point mutations in HIV-1B and C sequences from Southern Brazil. This study was the first to investigate the genetic diversity and point mutations within HIV-1 Tat C in a Brazilian cohort. This was an observational, cross-sectional study, which included sequences of HIV-1B (n = 20) and HIV-1C (n = 21) from Southern Brazil. Additionally, 344 HIV-1C sequences were obtained from the Los Alamos database: 29 from Brazil and 315 from Africa, Asia, and Europe. The frequency of C31S substitution on HIV-1 Tat C in Brazil was 82% vs. 10% in the HIV-1B group (p < 0.0001). The frequency of the R57S substitution among the HIV-1C sequences from Brazil was 74% vs. 20% in HIV-1B (p = 0.004), and that of substitution Q63E in HIV-1C was 80% and 20% in HIV-1B (p < 0.0001). The mutation P60Q was more frequent in HIV-1B than in HIV-1C (55% and 6.12%, respectively, p < 0.0001)). Novel point mutations in the HIV-1C and B Tat functional domains were described. The frequency of C31S and other key point mutations in HIV-1 Tat C in Brazil were similar to those described in Africa, although lower than those in India. The Tat-B and C sequences found in Southern Brazil are consistent with biological differences and have potential implications for HIV-1 subtype pathogenesis.

The ability to predict outcomes can help clinicians to better triage and treat stroke patients. We aimed to build prediction models using clinical data at admission and discharge to assess predictors highly relevant to stroke outcomes.A total of 37,094 patients from the Taiwan Stroke Registry (TSR) were enrolled to ascertain clinical variables and predict their mRS outcomes at 90 days. The performances (i.e., the area under the curves (AUCs)) of these independent predictors identified by logistic regression (LR) based on clinical variables were compared.Several outcome prediction models based on different patient subgroups were evaluated, and their AUCs based on all clinical variables at admission and discharge were 0.85-0.88 and 0.92-0.96, respectively. After feature selections, the input features decreased from 140 to 2-18 (including age of onset and NIHSS at admission) and from 262 to 2-8 (including NIHSS at discharge and mRS at discharge) at admission and discharge, respectively. With only a few selected key clinical features, our models can provide better performance than those previously reported in the literature.This study proposed high performance prognostics outcome prediction models derived from a population-based nationwide stroke registry even with reduced LR-selected clinical features. These key clinical features can help physicians to better focus on stroke patients to triage for best outcome in acute settings.

Small ubiquitin-like modifier (SUMO1–3) conjugation (SUMOylation), a post-translational modification, modulates almost all major cellular processes. Mounting evidence indicates that SUMOylation plays a crucial role in maintaining and regulating neural function, and importantly its dysfunction is implicated in cognitive impairment in humans. We have previously shown that simultaneously silencing SUMO1–3 expression in neurons negatively affects cognitive function. However, the roles of the individual SUMOs in modulating cognition and the mechanisms that link SUMOylation to cognitive processes remain unknown. To address these questions, in this study, we have focused on SUMO2 and generated a new conditional Sumo2 knockout mouse line. We found that conditional deletion of Sumo2 predominantly in forebrain neurons resulted in marked impairments in various cognitive tests, including episodic and fear memory. Our data further suggest that these abnormalities are attributable neither to constitutive changes in gene expression nor to alterations in neuronal morphology, but they involve impairment in dynamic SUMOylation processes associated with synaptic plasticity. Finally, we provide evidence that dysfunction on hippocampal-based cognitive tasks was associated with a significant deficit in the maintenance of hippocampal long-term potentiation in Sumo2 knockout mice. Collectively, these data demonstrate that protein conjugation by SUMO2 is critically involved in cognitive processes.

Comprising approximately 8% of our genome, Human Endogenous RetroViruses (HERVs) represent a class of germline retroviral infections that are regulated through epigenetic modifications. In cancer cells, which often have epigenetic dysregulation, HERVs have been implicated as potential oncogenic drivers. However, their role in gliomas is not known. Given the link between HERV expression in cancer cell lines and the distinct epigenetic dysregulation in gliomas, we utilized a tailored bioinformatic pipeline to characterize and validate the glioma retrotranscriptome and correlate HERV expression with locus-specific epigenetic modifications. We identified robust overexpression of multiple HERVs in our cell lines, including a retroviral transcript, HML-6, at 19q13.43b in glioblastoma cells. HERV expression inversely correlated with loci-specific DNA methylation. HML-6 contains an intact open reading frame encoding a small envelope protein, ERVK3-1. Increased expression of ERVK3-1 in GBM patients is associated with a poor prognosis independent of IDH-mutational status. Our results suggest that not only is HML-6 uniquely overexpressed in highly invasive cell lines and tissue samples, but also its gene product, ERVK3-1, may be associated with reduced survival in GBM patients. These results may have implications for both the tumor biology of GBM and the role of ERVK3-1 as a potential therapeutic target.

Atypical Teratoid Rhabdoid Tumor (AT/RT) is a rare pediatric central nervous system cancer often characterized by deletion or mutation of SMARCB1, a tumor suppressor gene. In this study, we found that SMARCB1 regulates Human Endogenous Retrovirus K (HERV-K, subtype HML-2) expression. HML-2 is a repetitive element scattered throughout the human genome, encoding several intact viral proteins that have been associated with stem cell maintenance and tumorigenesis. We found HML-2 env expression in both the intracellular and extracellular compartments in all AT/RT cell lines (n = 4) and in 95% of AT/RT patient tissues (n = 37) evaluated. SMARCB1 knock-down in neural stem cells (NSCs) led to an upregulation of HML-2 transcription. We found that SMARCB1 binds adjacent to the HML-2 promoter, repressing its transcription via chromatin immunoprecipitation; restoration of SMARCB1 expression in AT/RT cell lines significantly downregulated HML-2 expression. Further, targeted downregulation of HML-2 transcription via CRISPR-dCas9 coupled with suppressor proteins led to cellular dispersion, decreased proliferation, and cell death in vitro. HML-2 knock-down with shRNA, siRNA, and CRISPR-dCas9 significantly decreased Ras expression as measured by qRT-PCR, suggesting that HML-2 modulates MAPK/ERK signaling in AT/RT cells. Overexpression of NRAS was sufficient to restore cellular proliferation, and MYC, a transcription factor downstream of NRAS, was bound to the HERV-K LTR significantly more in the absence of SMARCB1 expression in AT/RT cells. We show a mechanism by which these undifferentiated tumors remain pluripotent, and we demonstrate that their formation is aided by aberrant HML-2 activation, which is dependent on SMARCB1 and its interaction with MYC.

Kanfer et al. develop a pooled CRISPRi screening method to identify genes regulating intracellular protein localization, organelle morphology or other subcellular phenotypes. The method uses machine learning to identify genetically altered cells, a photoactivated fluorescent protein to label them, and FACS plus deep sequencing to identify the affected gene., Genome-wide CRISPR screens have transformed our ability to systematically interrogate human gene function, but are currently limited to a subset of cellular phenotypes. We report a novel pooled screening approach for a wider range of cellular and subtle subcellular phenotypes. Machine learning and convolutional neural network models are trained on the subcellular phenotype to be queried. Genome-wide screening then utilizes cells stably expressing dCas9-KRAB (CRISPRi), photoactivatable fluorescent protein (PA-mCherry), and a lentiviral guide RNA (gRNA) pool. Cells are screened by using microscopy and classified by artificial intelligence (AI) algorithms, which precisely identify the genetically altered phenotype. Cells with the phenotype of interest are photoactivated and isolated via flow cytometry, and the gRNAs are identified by sequencing. A proof-of-concept screen accurately identified PINK1 as essential for Parkin recruitment to mitochondria. A genome-wide screen identified factors mediating TFEB relocation from the nucleus to the cytosol upon prolonged starvation. Twenty-one of the 64 hits called by the neural network model were independently validated, revealing new effectors of TFEB subcellular localization. This approach, AI-photoswitchable screening (AI-PS), offers a novel screening platform capable of classifying a broad range of mammalian subcellular morphologies, an approach largely unattainable with current methodologies at genome-wide scale.

Introduction: Sporadic pituitary adenomas are common (>10%) in the general population. Microadenomas (< 1 cm across) can become symptomatic with adrenocorticotropin oversecretion causing Cushing’s disease (CD), leading to high morbidity and mortility. Pathogenic mechanisms in a majority of adenomas including wildtype CD adenomas remain unknown. Mechanistic studies are hindered by a lack of in-vitro models and normal human pituitary gland controls. We hypothesized that comparative analysis of human adenomas with syngeneic normal pituitary glands could reveal pathogenic mechanisms driving CD. Methods: We surgically annotated adenomas and en-route adjacent normal glands in 34 patients. We performed single cell RNAseq and captured 28,724 cells in 6 patients (3 CD and 3 non-CD; 5 pairwise), bulk RNAseq in 7 patients (5 CD and 2 non-CD; 5 pairwise) and DNA methylation analysis in 6 patients (3 CD and 3 non-CD). We confirmed the mechanisms of sporadic CD adenoma pathogenesis in 2 additional syngeneic pairs of human cell lines and using a novel murine normal corticotroph-enriched cell line. Results: Using marker-based classification, we confirmed canonical resident cell classes including corticotrophs in the human pituitary gland. We found SOX2+/S100B+ folliculostellate cells which play a role in pituitary cell replenishment and homeostasis in the normal gland but not in the adenoma compartment. Within the terminally differentiated corticotrophs in the adenoma compartment, we discovered a subset of proliferating cells with upregulation of canonical oncogenes, histone modifiers and DNA repair genes. We also found that consensus dominant genes including PMAIP1 (encoding the pro-apoptotic BH3 only Bcl-2 protein noxa) sharply demarcated adenoma cells from normal gland. The PMAIP1 locus was hypomethylated in CD adenomas compared to non-CD samples. However, despite epigenetic and transcriptional upregulation, we found proteasomal degradation of noxa protein in CD adenomas. Using the selective proteasomal inhibitor bortezomib, we were able to rescue noxa ex-vivo and in-vitro, induce apoptosis, and reduce cell survival of adenoma cell lines. Conclusions: We defined the transcriptionl and DNA methylation landscape of human pituitary adenomas compared to adjacent normal gland tissue. We identified proteasomal-mediated noxa degradation despite PMAIP1 overexpression as an escape mechanism from apoptosis in adenomatous corticotrophs. The proteasomal inhibitor bortezomib rescued noxa and induced apoptosis in adenoma cells, highlighting its potential as a novel therapeutic strategy in CD.

Highlights • Spinal cord atrophy is prevalent across multiple sclerosis phenotypes. • It correlates with disability, especially in relapsing-remitting patients. • This correlation can be demonstrated both cross-sectionally and longitudinally. • Cervical atrophy is highly associated with disability and disease progression. • Thoracic atrophy contributes to improved correlation and radiological subgrouping., Objective We sought to characterize spinal cord atrophy along the entire spinal cord in the major multiple sclerosis (MS) phenotypes, and evaluate its correlation with clinical disability. Methods Axial T1-weighted images were automatically reformatted at each point along the cord. Spinal cord cross‐sectional area (SCCSA) were calculated from C1-T10 vertebral body levels and profile plots were compared across phenotypes. Average values from C2-3, C4-5, and T4-9 regions were compared across phenotypes and correlated with clinical scores, and then categorized as atrophic/normal based on z-scores derived from controls, to compare clinical scores between subgroups. In a subset of relapsing-remitting cases with longitudinal scans these regions were compared to change in clinical scores. Results The cross-sectional study consisted of 149 adults diagnosed with relapsing-remitting MS (RRMS), 49 with secondary-progressive MS (SPMS), 58 with primary-progressive MS (PPMS) and 48 controls. The longitudinal study included 78 RRMS cases. Compared to controls, all MS groups had smaller average regions except RRMS in T4-9 region. In all MS groups, SCCSA from all regions, particularly the cervical cord, correlated with most clinical measures. In the RRMS cohort, 22% of cases had at least one atrophic region, whereas in progressive MS the rate was almost 70%. Longitudinal analysis showed correlation between clinical disability and cervical cord thinning. Conclusions Spinal cord atrophy was prevalent across MS phenotypes, with regional measures from the RRMS cohort and the progressive cohort, including SPMS and PPMS, being correlated with disability. Longitudinal changes in the spinal cord were documented in RRMS cases, making it a potential marker for disease progression. While cervical SCCSA correlated with most disability and progression measures, inclusion of thoracic measurements improved this correlation and allowed for better subgrouping of spinal cord phenotypes. Cord atrophy is an important and easily obtainable imaging marker of clinical and sub-clinical progression in all MS phenotypes, and such measures can play a key role in patient selection for clinical trials.

The ground or naive pluripotent state of human pluripotent stem cells (hPSCs), which was initially established in mouse embryonic stem cells (mESCs), is an emerging and tentative concept. To verify this important concept in hPSCs, we performed a multivariate meta-analysis of major hPSC datasets via the combined analytic powers of percentile normalization, principal component analysis (PCA), t-distributed stochastic neighbor embedding (t-SNE), and SC3 consensus clustering. This vigorous bioinformatics approach has significantly improved the predictive values of the current meta-analysis. Accordingly, we were able to reveal various similarities between some naive-like hPSCs (NLPs) and their human and mouse in vitro counterparts. Moreover, we also showed numerous fundamental inconsistencies between diverse naive-like states, which are likely attributed to interlaboratory protocol differences. Collectively, our meta-analysis failed to provide global transcriptomic markers that support a bona fide human naive pluripotent state, rather suggesting the existence of altered pluripotent states under current naive-like growth protocols.

Genome-wide CRISPR screens have transformed our ability to systematically interrogate human gene function, but are currently limited to a subset of cellular phenotypes. We report a novel pooled screening approach for a wider range of cellular and subtle subcellular phenotypes. Machine learning and convolutional neural network models are trained on the subcellular phenotype to be queried. Genome-wide screening then utilizes cells stably expressing dCas9 (CRISPRi), photoactivatable fluorescent protein (PA-mCherry), and a lentiviral guide RNA (gRNA) pool. Cells are screened by microscopy and classified by artificial intelligence (AI) algorithms, which precisely identify the genetically altered phenotype. Cells with the phenotype of interest are photoactivated, isolated via flow cytometry, and the gRNAs are identified by sequencing. A proof-of-concept screen accurately identified PINK1 as essential for Parkin recruitment to mitochondria. A genome-wide screen identified factors mediating TFEB relocation from the nucleus to the cytosol upon prolonged starvation. Twenty of the sixty-four hits called by the neural network model were independently validated, revealing new effectors of TFEB subcellular localization. This approach, AI-Photoswitchable Screening (AI-PS) offers a novel screening platform capable of classifying a broad range of mammalian subcellular morphologies, an approach largely unattainable with current methodologies at genome-wide scale.

Introduction: Recurrence of Cushing’s disease (CD) caused by benign pituitary microadenomas are challenging clinical problems. Mechanisms underlying adenoma formation and recurrence remain unknown. PMAIP1 gene codes for Noxa, a Bcl-2 homology 3 (BH3) pro-apoptotic protein frequently downregulated in malignant human tumors.1-6 The role of dysregulated apoptosis remains largely unknown in benign tumors and in CD. We hypothesized that altered expression of Noxa protein is a pro-survival adaptation employed by CD adenomas. Methods: Syngeneic human pituitary adenoma and adjacent normal gland pairs (n=2), and an additional CD adenoma were analyzed with RNAseq. 10 CD, 1 growth hormone (GH) and 1 non-functioning adenoma (NFPA) underwent immunohistochemical (IHC) analysis for Noxa expression, which was graded by a neuropathologist as 0=none, 1=light, 2=medium, 3=strong. Staining grade represents relative protein expression. Results: Compared to adjacent normal pituitary tissue, we found that adenomas (n = 3) had a 3.76 fold increase in PMAIP1 mRNA. However, there was attenuated Noxa IHC staining in adenomas compared to normal pituitary in 8 of 10 CD patients (2:3, respectively), but similar staining in 2 of 10 CD patients (2:2 and 2-3:2-3). In GH and NFPA, we found similar patterns of Noxa suppression in the adenomas compared to the normal gland. Conclusion: Despite elevated PMAIP1 (Noxa) gene expression in adenomas compared to adjacent normal gland in CD, protein expression was reduced in adenomas. This downregulation of Noxa protein expression may contribute to reduced apoptosis of tumor cells. These findings suggest that CD adenomas gain pro-survival advantage by downregulating Noxa protein at post-transcriptional or post-translational level. References 1. Escobar, D. et al. Cell Death Dis.6, 1-14 (2015).2. Brinkmann, K. et al. Cell Rep.3, 881-891 (2013).3. Liu, Y. L. et al. Oncotarget5, 11237-11251 (2014).4. Dengler, M. A. et al. Cell Death Dis.5, 1-10 (2014).5. Liang, L. et al. J. Oral Pathol. Med.48, 52-59 (2019).6. Tahir, S. K. et al. Cancer Res.67, 1176-1183 (2007).

Alternative splicing (AS) of pre-messenger (m)RNA is a pivotal mechanism in expanding proteomic diversity, which determines the functions of mammalian cells. By conducting transcriptome analyses to profile splicing events in human colorectal cancer (CRC) tissues compared to adjacent normal counterparts, we noted differential splicing profiles of serine/arginine-rich splicing factor 3 (SRSF3) and mitogen-activated protein 4 kinase 4 (MAP4K4) in cancerous tissues of CRC compared to adjacent normal tissues. In addition to SRSF3-mediated autoregulation, RNA-binding motif protein 4 (RBM4) constituted another mechanism in reprogramming the splicing profile of SRSF3. Upregulated expressions of SRSF3 in CRC cells modulated utilization of MAP4K4 exon 16 in a sequence-dependent manner. Alternatively spliced MAP4K4 variants exhibited differential effects on the phosphorylation of c-Jun N-terminal protein kinase 1 (JNK1) which subsequently modulated expression profiles of E-cadherin, N-cadherin, and vimentin, all of which are involved in the migration and invasion of CRC cells. Collectively, RBM4-SRSF3-MAP4K4 constitutes a novel mechanism for manipulating the metastasis of CRC cells through the JNK1 signaling pathway.

SUMMARY To understand the cellular basis of behavior, it is necessary to know the cell types that exist in the nervous system and their contributions to function. Spinal networks are essential for sensory processing and motor behavior and provide a powerful system for identifying the cellular correlates of behavior. Here, we used massively parallel single nucleus RNA sequencing (snRNA-seq) to create an atlas of the adult mouse lumbar spinal cord. We identified and molecularly characterized 43 neuronal populations. Next, we leveraged the snRNA-seq approach to provide unbiased identification of neuronal populations that were active following a sensory and a motor behavior, using a transcriptional signature of neuronal activity. This approach can be used in the future to link single nucleus gene expression data with dynamic biological responses to behavior, injury, and disease., In Brief Sathyamurthy et al. use massively parallel single nucleus RNA-seq to probe spinal cord cell types and present an atlas of 43 neuronal populations. By using this approach after a sensory and a motor behavior, they were able to detect and molecularly identify activated neurons associated with each function.

Objective: Biomarkers aid diagnosis, allow inexpensive screening of therapies and guide selection of patient-specific therapeutic regimens in most internal medicine disciplines. In contrast, neurology lacks validated measurements of the physiological status, or dysfunction(s) of cells of the central nervous system (CNS). Accordingly, patients with chronic neurological diseases are often treated with a single disease-modifying therapy without understanding patient-specific drivers of disability. Therefore, using multiple sclerosis (MS) as an example of a complex polygenic neurological disease, we sought to determine if cerebrospinal fluid (CSF) biomarkers are intra-individually stable, cell type-, disease- and/or process-specific and responsive to therapeutic intervention. Methods: We used statistical learning in a modeling cohort (n=225) to develop diagnostic classifiers from DNA-aptamer-based measurements of 1128 CSF proteins. An independent validation cohort (n=85) assessed the reliability of derived classifiers. The biological interpretation resulted from in-vitro modeling of primary or stem cell-derived human CNS cells and cell lines. Results: The classifier that differentiates MS from CNS diseases that mimic MS clinically, pathophysiologically and on imaging, achieved a validated area under receiver-operator characteristic curve (AUROC) of 0.98, while the classifier that differentiates relapsing-remitting from progressive MS achieved a validated AUROC of 0.91. No classifiers could differentiate primary- from secondary-progressive MS better than random guessing. Treatment-induced changes in biomarkers greatly exceeded intra-individual- and technical variabilities of the assay. Interpretation: CNS biological processes reflected by CSF biomarkers are robust, stable, and disease- or even disease-stage specific. This opens opportunities for broad utilization of CSF biomarkers in drug development and precision medicine for CNS disorders. This article is protected by copyright. All rights reserved.

Background and Purpose: This study proposed a machine learning method for identifying ≥50% stenosis of the extracranial and intracranial arteries. Patients and methods A total of 8211 patients with both carotid ultrasound and cerebral angiography were enrolled. Support vector machine (SVM) was employed as the machine learning classifier. Carotid Doppler parameters and transcranial Doppler parameters were used as the input features. Feature selection was performed using the Extra-Trees (extremely randomized trees) method. Results For the machine learning method, the sensitivities and specificities of identifying stenosis of the extracranial arteries were 88.5%–100% and 96.0%–100%, respectively. The sensitivities and specificities of identifying stenosis of the intracranial arteries were 71.7%–100% and 88.9%–100%, respectively. Conclusions The SVM classifier with feature selection is an efficient method for identifying the stenosis of both intracranial and extracranial arteries. Comparing with traditional Doppler criteria, this machine learning method achieves up to 20% higher in accuracy and 45% in sensitivity, respectively.

The interplay between viral infection and Alzheimer's disease (AD) has long been an area of interest, but proving causality has been elusive. Several recent studies have renewed the debate concerning the role of herpesviruses, and human herpesvirus 6 (HHV-6) in particular, in AD. We screened for HHV-6 detection across three independent AD brain repositories using (1) RNA sequencing (RNA-seq) datasets and (2) DNA samples extracted from AD and non-AD control brains. The RNA-seq data were screened for pathogens against taxon references from over 25,000 microbes, including 118 human viruses, whereas DNA samples were probed for PCR reactivity to HHV-6A and HHV-6B. HHV-6 demonstrated little specificity to AD brains over controls by either method, whereas other viruses, such as Epstein-Barr virus (EBV) and cytomegalovirus (CMV), were detected at comparable levels. These direct methods of viral detection do not suggest an association between HHV-6 and AD.

BACKGROUNDCerebral malaria (CM) accounts for nearly 400,000 deaths annually in African children. Current dogma suggests that CM results from infected RBC (iRBC) sequestration in the brain microvasculature and resulting sequelae. Therapies targeting these events have been unsuccessful; findings in experimental models suggest that CD8+ T cells drive disease pathogenesis. However, these data have largely been ignored because corroborating evidence in humans is lacking. This work fills a critical gap in our understanding of CM pathogenesis that is impeding development of therapeutics.METHODSUsing multiplex immunohistochemistry, we characterized cerebrovascular immune cells in brain sections from 34 children who died from CM or other causes. Children were grouped by clinical diagnosis (CM+ or CM-), iRBC sequestration (Seqhi, Seqlo, Seq0) and HIV status (HIV+ or HIV-).RESULTSWe identified effector CD3+CD8+ T cells engaged on the cerebrovasculature in 69% of CM+ HIV- children. The number of intravascular CD3+CD8+ T cells was influenced by CM status (CM+ > CM-, P = 0.004) and sequestration level (Seqhi > Seqlo, P = 0.010). HIV coinfection significantly increased T cell numbers (P = 0.017) and shifted cells from an intravascular (P = 0.004) to perivascular (P < 0.0001) distribution.CONCLUSIONWithin the studied cohort, CM is associated with cerebrovascular engagement of CD3+CD8+ T cells, which is exacerbated by HIV coinfection. Thus, CD3+CD8+ T cells are highly promising targets for CM adjunctive therapy, opening new avenues for the treatment of this deadly disease.FUNDINGThis research was supported by the Intramural Research Program of the National Institutes of Health.

Objective To determine the underlying etiology in a patient with progressive dementia with extrapyramidal signs and chronic inflammation referred to the National Institutes of Health Undiagnosed Diseases Program. Methods Extensive investigations included metabolic profile, autoantibody panel, infectious etiologies, genetic screening, whole exome sequencing, and the phage-display assay, VirScan, for viral immune responses. An etiological diagnosis was established postmortem. Results Using VirScan, enrichment of dengue viral antibodies was detected in cerebrospinal fluid as compared to serum. No virus was detected in serum or cerebrospinal fluid, but postmortem analysis confirmed dengue virus in the brain by immunohistochemistry, in situ hybridization, quantitative polymerase chain reaction, and sequencing. Dengue virus was also detectable by polymerase chain reaction and sequencing from brain biopsy tissue collected 33 months antemortem, confirming a chronic infection despite a robust immune response directed against the virus. Immunoprofiling and whole exome sequencing of the patient did not reveal any immunodeficiency, and sequencing of the virus demonstrated wild-type dengue virus in the central nervous system. Interpretation Dengue virus is the most common arbovirus worldwide and represents a significant public health concern. Infections with dengue virus are usually self-limiting, and chronic dengue infections have not been previously reported. Our findings suggest that dengue virus infections may persist in the central nervous system causing a panencephalitis and should be considered in patients with progressive dementia with extrapyramidal features in endemic regions or with relevant travel history. Furthermore, this work highlights the utility of comprehensive antibody profiling assays to aid in the diagnosis of encephalitis of unknown etiology. ANN NEUROL 2019;86:695-703.

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.

Introduction Clinicians commonly use the modified Rankin Scale (mRS) and the Barthel Index (BI) to measure clinical outcome after stroke. These are potential targets in machine learning models for stroke outcome prediction. Therefore, the quality of the measurements is crucial for training and validation of these models. The objective of this study was to apply and evaluate density-based outlier detection methods for identifying potentially incorrect measurements in multiple large stroke datasets to assess the measurement quality. Method We applied three density-based outlier detection methods including density-based spatial clustering of applications (DBSCAN), hierarchical DBSCAN (HDBSCAN) and local outlier factor (LOF) based on a large dataset obtained from a nationwide prospective stroke registry in Taiwan. The testing of each method was done by using four different NINDS funded stroke datasets. Result The DBSCAN achieved a high performance across all mRS values where the highest average accuracy was 99.2 ± 0.7 at mRS of 4 and the lowest average accuracy was 92.0 ± 4.6 at mRS of 3. The LOF also achieved similar performance, however, the HDBSCAN with default parameters setting required further tuning improvement. Conclusion The density-based outlier detection methods were proven to be promising for validation of stroke outcome measures. The outlier detection algorithm developed from a large prospective registry dataset was effectively applied in four different NINDS stroke datasets with high performance results. The tool developed from this detection algorithm can be further applied to real world datasets to increase the data quality in stroke outcome measures.

BACKGROUND Introduction: Researchers commonly use the Modified Rankin Scale (mRS) and the Barthel Index (BI) to assess a patient’s clinical outcome after stroke. These are potential targets in machine learning models for stroke outcome prediction. OBJECTIVE The objective of this study was to evaluate density-based outlier detection methods on mRS and BI assessments. METHODS We trained three density-based outlier detection methods including density-based spatial clustering of applications (DBSCAN), hierarchical DBSCAN (HDBSCAN) and local outlier factor (LOF) based on data obtained from a nationwide prospective stroke registry in Taiwan. The testing of each method was done by using four different NINDS stroke datasets. RESULTS The DBSCAN achieved a high performance across all mRS values (the highest average accuracy was 99.2±0.7 at mRS-4 and the lowest average accuracy was 92.0±4.6 at mRS-3). The LOF also achieved similar performance but the HDBSCAN needs further improvement. CONCLUSIONS The evaluation results showed that promising density-based outlier detection methods are promising for validation of stroke outcome measures during the study data clean up processes to improve completion of clinical data for increased data quality and research analyses.

The mammalian heart undergoes complex structural and functional remodeling to compensate for stresses such as pressure overload. While studies suggest that, at best, the adult mammalian heart is capable of very limited regeneration arising from the proliferation of existing cardiomyocytes, how myocardial stress affects endogenous cardiac regeneration or repair is unknown. To define the relationship between left ventricular afterload and cardiac repair, we induced left ventricle pressure overload in adult mice by constriction of the ascending aorta (AAC). One week following AAC, we normalized ventricular afterload in a subset of animals through removal of the aortic constriction (de-AAC). Subsequent monitoring of cardiomyocyte cell cycle activity via thymidine analog labeling revealed that an acute increase in ventricular afterload induced cardiomyocyte proliferation. Intriguingly, a release in ventricular overload (de-AAC) further increases cardiomyocyte proliferation. Following both AAC and de-AAC, thymidine analog-positive cardiomyocytes exhibited characteristics of newly generated cardiomyocytes, including single diploid nuclei and reduced cell size as compared to age-matched, sham-operated adult mouse myocytes. Notably, those smaller cardiomyocytes frequently resided alongside one another, consistent with local stimulation of cellular proliferation. Collectively, our data demonstrate that adult cardiomyocyte proliferation can be locally stimulated by an acute increase or decrease of ventricular pressure, and this mode of stimulation can be harnessed to promote cardiac repair.

We previously showed that early changes in infarct volume (ECS) perform better as a predictor of early neurologic outcome in acute ischemic stroke (AIS) patients receiving thrombolysis when compared to percent recanalization (PER) and infarct volume at 24 hours (InVol), but the biologic explanation is unclear. We combined MRI and RNA Seq to compare the biologic associations. Methods: Pretreatment, 2-, and 24-hours post-thrombolysis MRIs were analyzed in 15 enrolled AIS patients treated with thrombolysis. ECS on the apparent diffusion coefficient sequence and PER on the perfusion scan were measured by comparing the pretreatment and 2-hour post thrombolysis MRI using automated co-registered MRI sequences within a region of interest defined by a > 4 second delay in time-to-peak on perfusion imaging using Matlab. InVol was measured on diffusion weighted images by a blinded reviewer. Blood samples were collected 2-hours and 24-hours post thrombolysis. RNA Seq was performed with HiSeq 25000 Illumina platform. After correcting for age, gender, and race, “leave one out testing” was used to select mRNA that correlated with the imaging variables (FDR corrected P-value < 0.05). Results: PER only correlated with 2 mRNA from 2-hour blood. InVol was associated with 20 mRNA from 24-hour blood. Both lacked significant disease and function associations. ECS correlated with 24 mRNA from 2-hour blood, with significant association with a decrease in IPA Ingenuity disease and functions annotations for both development of vasculature (P=0.005, Z-score -2.2) and angiogenesis (P=0.02, Z-score -2.2). Interestingly, IPA annotations for vascular development and angiogenesis include epoxyeicosatrienoic acid, a mediator of neurovascular coupling induced by cerebral ischemia, and degraded by soluble epoxide hydrolase enzyme (SEH). SEH inhibitor 12-(3-adamantan-1-yl-ureido) dodecanoic acid (AUDA) was a potential upstream regulator (P=5.03E-04), and AUDA has previously been shown to reduce infarct size in an animal model of ischemic stroke. Here we demonstrate the benefit of the combined MRI/blood biomarkers approach for elucidating biologic responses in AIS in identifying potential novel new therapeutics in humans, such as the epoxyeicosatrienoic pathway.

In vitro generation of human peripheral sensory neurons may provide a framework for novel drug screening platforms and disease models of touch and pain. However, derivation of a functionally pure sensory neuron population remains a major unmet challenge. We discovered that, by expressing the transcription factors NGN2 and BRN3A, human pluripotent stem cells can be induced to differentiate into a surprisingly homogenous culture of cold- and mechano-sensing neurons. Although such a neuronal subtype has not been reported in mice, we found molecular evidence of its existence in adult human sensory ganglia. Combining NGN2 and BRN3A programming with neural crest patterning, we produced two additional populations of sensory neurons, including a more specialized mechanosensory neuron subtype. Finally, we applied this system to model a rare inherited sensory disorder, characterized by profound impairment of touch sensation and proprioception, caused by inactivating mutations in PIEZO2. Together these findings establish an approach to specify distinct sensory neuron subtypes in vitro, underscoring the utility of stem cell technology to capture human-specific features of physiology and disease.

Background Neural stem cell (NSC)-based therapies hold great promise for treating diseases of the central nervous system (CNS). However, several fundamental problems still need to be overcome to fully exploit the clinical potential of NSC therapeutics. Chief among them is the limited survival of NSC grafts within hostile microenvironments. Methods Herein, we sought to engineer NSCs in an effort to increase graft survival within ischemic brain lesions via upregulation of global SUMOylation, a post-translational modification critically involved in mediating tolerance to ischemia/reperfusion. Findings NSCs overexpressing the SUMO E2-conjugase Ubc9 displayed resistance to oxygen-glucose-deprivation/restoration of oxygen/glucose (OGD/ROG) and enhanced neuronal differentiation in vitro, as well as increased survival and neuronal differentiation when transplanted in mice with transient middle cerebral artery occlusion in vivo. Interpretation Our work highlights a critical role for SUMOylation in NSC biology and identifies a biological pathway that can be targeted to increase the effectiveness of exogenous stem cell medicines in ischemic stroke. Fund Intramural Research Program of the NINDS/NIH, the Italian Multiple Sclerosis Foundation (FISM), the Bascule Charitable Trust, NIH-IRTA-OxCam and Wellcome Trust Research Training Fellowships.

We aimed to characterize peripheral blood gene expression profile of penumbra defined as MRI perfusion–diffusion mismatch (PD MM) in peripheral blood of patients with acute ischemic stroke. We studied 23 patients. Perfusion–diffusion mismatch volume was observed to be associated and significantly correlated with the expression of 34 genes including those related to inflammation, SUMOylation, and coagulation; while lipopolysaccharide inhibition was identified to be a candidate upstream regulator of these processes (z‐score −2.38, P = 0.04). Penumbral volume is correlated with a specific gene expression profile in the peripheral blood characterized by overlap of inflammatory and neuroprotective pathways that are regulated by lipopolysaccharide inhibition.

Aim: The ability to predict outcomes can help clinicians to better triage and treat stroke patients. We aimed to build prediction models using clinical data at admission and discharge to assess predictors highly relevant to stroke outcomes. Methods: A total of 37,094 patients from the Taiwan Stroke Registry (TSR) were enrolled to ascertain clinical variables and predict their mRS outcomes at 90 days. The performances (i.e., the area under the curves (AUCs)) of these independent predictors identified by logistic regression (LR) based on clinical variables were compared. Results: Several outcome prediction models based on different patient subgroups were evaluated, and their AUCs based on all clinical variables at admission and discharge were 0.85-0.88 and 0.92-0.96, respectively. After feature selections, the input features decreased from 140 to 2-18 (including age of onset and NIHSS at admission) and from 262 to 2-8 (including NIHSS at discharge and mRS at discharge) at admission and discharge, respectively. With only a few selected key clinical features, our models can provide better performance than those previously reported in the literature. Conclusion: This study proposed high performance prognostics outcome prediction models derived from a population-based nationwide stroke registry even with reduced LR-selected clinical features. These key clinical features can help physicians to better focus on stroke patients to triage for best outcome in acute settings.

Cardiomyocytes can be differentiated from human pluripotent stem cells (hPSCs) in defined conditions, but efficient and consistent cardiomyocyte differentiation often requires expensive reagents such as B27 supplement or recombinant albumin. Using a chemically defined albumin-free (E8 basal) medium, we identified heparin as a novel factor that significantly promotes cardiomyocyte differentiation efficiency, and developed an efficient method to differentiate hPSCs into cardiomyocytes. The treatment with heparin helped cardiomyocyte differentiation consistently reach at least 80% purity (up to 95%) from more than 10 different hPSC lines in chemically defined Dulbecco's modified Eagle's medium/F-12-based medium on either Matrigel or defined matrices like vitronectin and Synthemax. One of heparin's main functions was to act as a Wnt modulator that helped promote robust and consistent cardiomyocyte production. Our study provides an efficient, reliable, and cost-effective method for cardiomyocyte derivation from hPSCs that can be used for potential large-scale drug screening, disease modeling, and future cellular therapies.

SUMMARY Efficient and homogeneous in vitro generation of peripheral sensory neurons may provide a framework for novel drug screening platforms and disease models of touch and pain. We discover that, by ovesssrexpressing NGN2 and BRN3A, human pluripotent stem cells can be transcriptionally programmed to differentiate into a surprisingly uniform culture of cold- and mechano-sensing neurons. Although such a neuronal subtype is not found in mice, we identify molecular evidence for its existence in human sensory ganglia. Combining NGN2 and BRN3A programming with neural crest patterning, we produce two additional populations of sensory neurons, including a specialized touch receptor neuron subtype. Finally, we apply this system to model a rare inherited sensory disorder of touch and proprioception caused by inactivating mutations in PIEZO2. Together, these findings establish an approach to specify distinct sensory neuron subtypes in vitro, underscoring the utility of stem cell technology to capture human-specific features of physiology and disease., In Brief Nickolls et al. develop a method, using human stem cells, to generate specific types of sensory neurons that detect cold temperature and mechanical force. This approach uncovers a class of neuron found in humans, but not mice, and enables the modeling of a rare sensory disorder of touch and proprioception., Graphical Abstract

Probing an individual cell's gene expression enables the identification of cell type and cell state. Single-cell RNA sequencing has emerged as a powerful tool for studying transcriptional profiles of cells, particularly in heterogeneous tissues such as the central nervous system. However, dissociation methods required for single cell sequencing can lead to experimental changes in the gene expression and cell death. Furthermore, these methods are generally restricted to fresh tissue, thus limiting studies on archival and bio-bank material. Single nucleus RNA sequencing (snRNA-Seq) is an appealing alternative for transcriptional studies, given that it accurately identifies cell types, permits the study of tissue that is frozen or difficult to dissociate, and reduces dissociation-induced transcription. Here, we present a high-throughput protocol for rapid isolation of nuclei for downstream snRNA-Seq. This method enables isolation of nuclei from fresh or frozen spinal cord samples and can be combined with two massively parallel droplet encapsulation platforms.

Aging is the greatest risk factor for neurodegeneration, but the connection between the two processes remains opaque. This is in part for want of a rigorous way to define physiological age, as opposed to chronological age. Here, we develop a comprehensive metric for physiological age in Drosophila, based on genome-wide expression profiling. We applied this metric to a model of adult-onset neurodegeneration, increased or decreased expression of the activating subunit of the Cdk5 protein kinase, encoded by the gene Cdk5α, the ortholog of mammalian p35. Cdk5α-mediated degeneration was associated with a 27-150% acceleration of the intrinsic rate of aging, depending on the tissue and genetic manipulation. Gene ontology analysis and direct experimental tests revealed that affected age-associated processes included numerous core phenotypes of neurodegeneration, including enhanced oxidative stress and impaired proteostasis. Taken together, our results suggest that Cdk5α-mediated neurodegeneration results from accelerated aging, in combination with cell-autonomous neuronal insults. These data fundamentally recast our picture of the relationship between neurodegeneration and its most prominent risk factor, natural aging., Editor's choice: By developing a comprehensive and quantitative metric for physiological age of Drosophila, we show that a neurodegeneration mutant produces its effects in part by accelerating the absolute rate of aging.

Background Inherited Retinal dystrophy (IRD) is a broad group of inherited retinal disorders with heterogeneous genotypes and phenotypes. Next generation sequencing (NGS) methods have been broadly applied for analyzing patients with IRD. Here we report a novel approach to enrich the target gene panel by microdroplet PCR. Methods This assay involved a primer library which targeted 3071 amplicons from 2078 exons comprised of 184 genes involved in retinal function and/or retinal development. We amplified the target regions using the RainDance target enrichment PCR method and sequenced the products using the MiSeq NGS platform. Results In this study, we analyzed 82 samples from 67 families with IRD. Bioinformatics analysis indicated that this procedure was able to reach 99% coverage of target sequences with an average sequence depth of reads at 119×. The variants detected by this study were filtered, validated, and prioritized by pathogenicity analysis. Genotypes and phenotypes were correlated by determining a consistent relationship in 38 propands (56.7%). Pathogenic variants in genes related to retinal function were found in another 11 probands (16.4%), but the clinical correlations showed inconsistencies and insufficiencies in these patients. Conclusions The application of NGS in IRD clinical molecular diagnosis provides a powerful approach to exploring the etiology and pathology in patients. It is important for the clinical laboratory to interpret the molecular findings in the context of patient clinical presentations because accurate interpretation of pathogenic variants is critical for delivering solid clinical molecular diagnosis to clinicians and patients and improving the standard care of patients. Electronic supplementary material The online version of this article (doi:10.1186/s12886-017-0549-5) contains supplementary material, which is available to authorized users.

The development of mouse genetic tools has made a significant contribution to the understanding of skeletal and hematopoietic stem cell niches in bone marrow (BM). However, many experimental designs (e.g., selections of marker genes, target vector constructions, and choices of reporter murine strains) have unavoidable technological limitations and bias, which lead to experimental discrepancies, data reproducibility issues, and frequent data misinterpretation. Consequently, there are a number of conflicting views relating to fundamental biological questions, including origins and locations of skeletal and hematopoietic stem cells in the BM. In this report, we systematically unravel complicated data interpretations via comprehensive analyses of technological benefits, pitfalls, and challenges in frequently used mouse models and discuss their translational relevance to human stem cell biology. Particularly, we emphasize the important roles of using large human genomic data-informatics in facilitating genetic analyses of mouse models and resolving existing controversies in mouse and human BM stem cell biology., In this article, Chen and colleagues discuss technological challenges for genetic analysis of bone marrow stem cell niches. This article consists of a concise review, considerable perspectives, and in-depth data analysis. Importantly, the authors provide translational relevance through interrogating mouse genetic models with human genomic datasets. This review would aid to resolve data inconsistencies and their associated stem cell controversies.

Lineage commitment and differentiation of skeletal stem cells/bone marrow stromal cells (SSCs/BMSCs, often called bone marrow-derived “mesenchymal stem/stromal” cells) offer an important opportunity to study skeletal and hematopoietic diseases, and for tissue engineering and regenerative medicine. Currently, many studies in this field have relied on cell lineage tracing methods in mouse models, which have provided a significant advancement in our knowledge of skeletal and hematopoietic stem-cell niches in bone marrow (BM). However, there is a lack of agreement in numerous fundamental areas, including origins of various BM stem-cell niches, cell identities, and their physiological roles in the BM. In order to resolve these issues, we propose a new hypothesis of “paralogous” stem-cell niches (PSNs); that is, progressively altered parallel niches within an individual species throughout the life span of the organism. A putative PSN code seems to be plausible based on analysis of transcriptional signatures in two representative genes that encode Nes-GFP and leptin receptors, which are frequently used to monitor SSC lineage development in BM. Furthermore, we suggest a dynamic paralogous BM niche (PBMN) model that elucidates the coupling and uncoupling mechanisms between BM stem-cell niches and their zones of active regeneration during different developmental stages. Elucidation of these PBMNs would enable us to resolve the existing controversies, thus paving the way to achieving precision regenerative medicine and pharmaceutical applications based on these BM cell resources.

An elevated human T cell lymphotropic virus 1 (HTLV)-1 proviral load (PVL) is the main risk factor for developing HTLV-1-associated myelopathy/tropical spastic paraparesis (HAM/TSP) in HTLV-1 infected subjects, and a high cerebrospinal fluid (CSF) to peripheral blood mononuclear cell (PBMC) PVL ratio may be diagnostic of the condition. However, the standard method for quantification of HTLV-1 PVL-real-time PCR-has multiple limitations, including increased inter-assay variability in compartments with low cell numbers, such as CSF. Therefore, in this study, we evaluated a novel technique for HTVL-1 PVL quantification, digital droplet PCR (ddPCR). In ddPCR, PCR samples are partitioned into thousands of nanoliter-sized droplets, amplified on a thermocycler, and queried for fluorescent signal. Due to the high number of independent events (droplets), Poisson algorithms are used to determine absolute copy numbers independently of a standard curve, which enables highly precise quantitation. This assay has low intra-assay variability allowing for reliable PVL measurement in PBMC and CSF compartments of both asymptomatic carriers (AC) and HAM/TSP patients. It is also useful for HTLV-1-related clinical applications, such as longitudinal monitoring of PVL and identification of viral mutations within the region targeted by the primers and probe.

RNA-sequencing (RNA-seq) is a powerful technique to investigate the complexity of gene expression in the human brain. We used RNA-seq to survey the brain transcriptome in high-quality postmortem dorsolateral prefrontal cortex from 11 individuals diagnosed with bipolar disorder (BD) and from 11 age- and gender-matched controls. Deep sequencing was performed, with over 350 million reads per specimen. At a false discovery rate of

JC virus (JCV) is a ubiquitous human polyomavirus that causes the demyelinating disease Progressive Multifocal Leukoencephalopathy (PML). JCV replicates in limited cell types in culture, predominantly in human glial cells. Following introduction of a replication defective SV40 mutant that expressed large T protein into a heterogeneous culture of human fetal brain cells, multiple phenotypes became immortalized (SVG cells). A subset of SVG cells could support JCV replication. In the current study, clonal cell lines were selected from the original SVG cell culture. The 5F4 clone showed low levels of viral growth. The 10B1 clone was highly permissive for JCV DNA replication and gene expression and supported persistent and stable JCV infection over months in culture. Microarray analysis revealed that viral infection did not significantly change gene expression in these cells. More resistant 5F4 cells expressed high levels of transcription factors known to inhibit JCV transcription. Interestingly, 5F4 cells expressed high levels of RNA of markers of radial glia and 10B1 cells had high expression of markers of immature glial cells and activation of transcription regulators important for stem/progenitor cell self-renewal. These SVG-derived clonal cell lines provide a biologically relevant model to investigate cell type differences in JCV host range and pathogenesis, as well as neural development. Several transcription regulators were identified which may be targets for therapeutic modulation of expression to abrogate JCV replication in PML patients. Additionally, these clonal cell lines can provide a consistent culture platform for testing therapies against JCV infection of the central nervous system.