ISG15/USP18/STAT2 is a molecular hub regulating IFN I-mediated control of Dengue and Zika virus replication.

The establishment of a virus infection is the result of the pathogen's ability to replicate in a hostile environment generated by the host's immune system. Here, we found that ISG15 restricts Dengue and Zika viruses' replication through the stabilization of its binding partner USP18. ISG15 expression was necessary to control DV replication driven by both autocrine and paracrine type one interferon (IFN-I) signaling. Moreover, USP18 competes with NS5-mediated STAT2 degradation, a major mechanism for establishment of flavivirus infection. Strikingly, reconstitution of USP18 in ISG15-deficient cells was sufficient to restore the STAT2's stability and restrict virus growth, suggesting that the IFNAR-mediated ISG15 activity is also antiviral. Our results add a novel layer of complexity in the virus/host interaction interface and suggest that NS5 has a narrow window of opportunity to degrade STAT2, therefore suppressing host's IFN-I mediated response and promoting virus replication.

Integrated transcriptomics uncovers an enhanced association between the prion protein gene expression and vesicle dynamics signatures in glioblastomas.

BACKGROUND: Glioblastoma (GBM) is an aggressive brain tumor that exhibits resistance to current treatment, making the identification of novel therapeutic targets essential. In this context, cellular prion protein (PrPC) stands out as a potential candidate for new therapies. Encoded by the PRNP gene, PrPC can present increased expression levels in GBM, impacting cell proliferation, growth, migration, invasion and stemness. Nevertheless, the exact molecular mechanisms through which PRNP/PrPC modulates key aspects of GBM biology remain elusive. METHODS: To elucidate the implications of PRNP/PrPC in the biology of this cancer, we analyzed publicly available RNA sequencing (RNA-seq) data of patient-derived GBMs from four independent studies. First, we ranked samples profiled by bulk RNA-seq as PRNPhigh and PRNPlow and compared their transcriptomic landscape. Then, we analyzed PRNP+ and PRNP- GBM cells profiled by single-cell RNA-seq to further understand the molecular context within which PRNP/PrPC might function in this tumor. We explored an additional proteomics dataset, applying similar comparative approaches, to corroborate our findings. RESULTS: Functional profiling revealed that vesicular dynamics signatures are strongly correlated with PRNP/PrPC levels in GBM. We found a panel of 73 genes, enriched in vesicle-related pathways, whose expression levels are increased in PRNPhigh/PRNP+ cells across all RNA-seq datasets. Vesicle-associated genes, ANXA1, RAB31, DSTN and SYPL1, were found to be upregulated in vitro in an in-house collection of patient-derived GBM. Moreover, proteome analysis of patient-derived samples reinforces the findings of enhanced vesicle biogenesis, processing and trafficking in PRNPhigh/PRNP+ GBM cells. CONCLUSIONS: Together, our findings shed light on a novel role for PrPC as a potential modulator of vesicle biology in GBM, which is pivotal for intercellular communication and cancer maintenance. We also introduce GBMdiscovery, a novel user-friendly tool that allows the investigation of specific genes in GBM biology.

PKR-mediated stress response enhances dengue and Zika virus replication.

IMPORTANCE: One of the fundamental features that make viruses intracellular parasites is the necessity to use cellular translational machinery. Hence, this is a crucial checkpoint for controlling infections. Here, we show that dengue and Zika viruses, responsible for nearly 400 million infections every year worldwide, explore such control for optimal replication. Using immunocompetent cells, we demonstrate that arrest of protein translations happens after sensing of dsRNA and that the information required to avoid this blocking is contained in viral 5'-UTR. Our work, therefore, suggests that the non-canonical translation described for these viruses is engaged when the intracellular stress response is activated.

RUNX1 mutations mitigate quiescence to promote transformation of hematopoietic progenitors in Fanconi anemia.

Many inherited bone marrow failure syndromes (IBMFSs) present a high risk of transformation to myelodysplastic syndrome (MDS) and acute myeloid leukemia (AML). During transformation of IBMFSs, hematopoietic stem and progenitor cells (HSPCs) with poor fitness gain ectopic, dysregulated self-renewal secondary to somatic mutations via undefined mechanisms. Here, in the context of the prototypical IBMFS Fanconi anemia (FA), we performed multiplexed gene editing of mutational hotspots in MDS-associated genes in human induced pluripotent stem cells (iPSCs) followed by hematopoietic differentiation. We observed aberrant self-renewal and impaired differentiation of HSPCs with enrichment of RUNX1 insertions and deletions (indels), generating a model of IBMFS-associated MDS. We observed that compared to the failure state, FA MDS cells show mutant RUNX1-mediated blunting of the G1/S cell cycle checkpoint that is normally activated in FA in response to DNA damage. RUNX1 indels also lead to activation of innate immune signaling, which stabilizes the homologous recombination (HR) effector BRCA1, and this pathway can be targeted to abrogate viability and restore sensitivity to genotoxins in FA MDS. Together, these studies develop a paradigm for modeling clonal evolution in IBMFSs, provide basic understanding of the pathogenesis of MDS, and uncover a therapeutic target in FA-associated MDS.

Lifelong multilineage contribution by embryonic-born blood progenitors.

Haematopoietic stem cells (HSCs) arise in the embryo from the arterial endothelium through a process known as the endothelial-to-haematopoietic transition (EHT)1-4. This process generates hundreds of blood progenitors, of which a fraction go on to become definitive HSCs. It is generally thought that most adult blood is derived from those HSCs, but to what extent other progenitors contribute to adult haematopoiesis is not known. Here we use in situ barcoding and classical fate mapping to assess the developmental and clonal origins of adult blood in mice. Our analysis uncovers an early wave of progenitor specification-independent of traditional HSCs-that begins soon after EHT. These embryonic multipotent progenitors (eMPPs) predominantly drive haematopoiesis in the young adult, have a decreasing yet lifelong contribution over time and are the predominant source of lymphoid output. Putative eMPPs are specified within intra-arterial haematopoietic clusters and represent one fate of the earliest haematopoietic progenitors. Altogether, our results reveal functional heterogeneity during the definitive wave that leads to distinct sources of adult blood.

Effects of Magnetite Nanoparticles and Static Magnetic Field on Neural Differentiation of Pluripotent Stem Cells.

Neurodevelopmental processes of pluripotent cells, such as proliferation and differentiation, are influenced by external natural forces. Despite the presence of biogenic magnetite nanoparticles in the central nervous system and constant exposure to the Earth's magnetic fields and other sources, there is scant knowledge regarding the role of electromagnetic stimuli in neurogenesis. Moreover, emerging applications of electrical and magnetic stimulation to treat neurological disorders emphasize the relevance of understanding the impact and mechanisms behind these stimuli. Here, the effects of magnetic nanoparticles (MNPs) in polymeric coatings and the static external magnetic field (EMF) were investigated on neural induction of murine embryonic stem cells (mESCs) and human induced pluripotent stem cells (hiPSCs). The results show that the presence of 0.5% MNPs in collagen-based coatings facilitates the migration and neuronal maturation of mESCs and hiPSCs in vitro. Furthermore, the application of 0.4 Tesla EMF perpendicularly to the cell culture plane, discernibly stimulates proliferation and guide fate decisions of the pluripotent stem cells, depending on the origin of stem cells and their developmental stage. Mechanistic analysis reveals that modulation of ionic homeostasis and the expression of proteins involved in cytostructural, liposomal and cell cycle checkpoint functions provide a principal underpinning for the impact of electromagnetic stimuli on neural lineage specification and proliferation. These findings not only explore the potential of the magnetic stimuli as neural differentiation and function modulator but also highlight the risks that immoderate magnetic stimulation may affect more susceptible neurons, such as dopaminergic neurons.

LIN28B alters ribosomal dynamics to promote metastasis in MYCN-driven malignancy.

High expression of LIN28B is associated with aggressive malignancy and poor survival. Here, probing MYCN-amplified neuroblastoma as a model system, we showed that LIN28B expression was associated with enhanced cell migration in vitro and invasive and metastatic behavior in murine xenografts. Sequence analysis of the polyribosome fraction of LIN28B-expressing neuroblastoma cells revealed let-7-independent enrichment of transcripts encoding components of the translational and ribosomal apparatus and depletion of transcripts of neuronal developmental programs. We further observed that LIN28B utilizes both its cold shock and zinc finger RNA binding domains to preferentially interact with MYCN-induced transcripts of the ribosomal complex, enhancing their translation. These data demonstrated that LIN28B couples the MYCN-driven transcriptional program to enhanced ribosomal translation, thereby implicating LIN28B as a posttranscriptional driver of the metastatic phenotype.

Evaluating the transcriptional fidelity of cancer models.

BACKGROUND: Cancer researchers use cell lines, patient-derived xenografts, engineered mice, and tumoroids as models to investigate tumor biology and to identify therapies. The generalizability and power of a model derive from the fidelity with which it represents the tumor type under investigation; however, the extent to which this is true is often unclear. The preponderance of models and the ability to readily generate new ones has created a demand for tools that can measure the extent and ways in which cancer models resemble or diverge from native tumors. METHODS: We developed a machine learning-based computational tool, CancerCellNet, that measures the similarity of cancer models to 22 naturally occurring tumor types and 36 subtypes, in a platform and species agnostic manner. We applied this tool to 657 cancer cell lines, 415 patient-derived xenografts, 26 distinct genetically engineered mouse models, and 131 tumoroids. We validated CancerCellNet by application to independent data, and we tested several predictions with immunofluorescence. RESULTS: We have documented the cancer models with the greatest transcriptional fidelity to natural tumors, we have identified cancers underserved by adequate models, and we have found models with annotations that do not match their classification. By comparing models across modalities, we report that, on average, genetically engineered mice and tumoroids have higher transcriptional fidelity than patient-derived xenografts and cell lines in four out of five tumor types. However, several patient-derived xenografts and tumoroids have classification scores that are on par with native tumors, highlighting both their potential as faithful model classes and their heterogeneity. CONCLUSIONS: CancerCellNet enables the rapid assessment of transcriptional fidelity of tumor models. We have made CancerCellNet available as a freely downloadable R package ( https://github.com/pcahan1/cancerCellNet ) and as a web application ( http://www.cahanlab.org/resources/cancerCellNet_web ) that can be applied to new cancer models that allows for direct comparison to the cancer models evaluated here.

RNA binding proteins co-localize with small tau inclusions in tauopathy.

The development of insoluble, intracellular neurofibrillary tangles composed of the microtubule-associated protein tau is a defining feature of tauopathies, including Alzheimer's disease (AD). Accumulating evidence suggests that tau pathology co-localizes with RNA binding proteins (RBPs) that are known markers for stress granules (SGs). Here we used proteomics to determine how the network of tau binding proteins changes with disease in the rTg4510 mouse, and then followed up with immunohistochemistry to identify RNA binding proteins that co-localize with tau pathology. The tau interactome networks revealed striking disease-related changes in interactions between tau and a multiple RBPs, and biochemical fractionation studies demonstrated that many of these proteins including hnRNPA0, EWSR1, PABP and RPL7 form insoluble aggregates as tau pathology develops. Immunohistochemical analysis of mouse and human brain tissues suggest a model of evolving pathological interaction, in which RBPs co-localize with pathological phospho-tau but occur adjacent to larger pathological tau inclusions. We suggest a model in which tau initially interacts with RBPs in small complexes, but evolves into isolated aggregated inclusions as tau pathology matures.

Conserved DNA methylation combined with differential frontal cortex and cerebellar expression distinguishes C9orf72-associated and sporadic ALS, and implicates SERPINA1 in disease.

We previously found C9orf72-associated (c9ALS) and sporadic amyotrophic lateral sclerosis (sALS) brain transcriptomes comprise thousands of defects, among which, some are likely key contributors to ALS pathogenesis. We have now generated complementary methylome data and combine these two data sets to perform a comprehensive "multi-omic" analysis to clarify the molecular mechanisms initiating RNA misregulation in ALS. We found that c9ALS and sALS patients have generally distinct but overlapping methylome profiles, and that the c9ALS- and sALS-affected genes and pathways have similar biological functions, indicating conserved pathobiology in disease. Our results strongly implicate SERPINA1 in both C9orf72 repeat expansion carriers and non-carriers, where expression levels are greatly increased in both patient groups across the frontal cortex and cerebellum. SERPINA1 expression is particularly pronounced in C9orf72 repeat expansion carriers for both brain regions, where SERPINA1 levels are strictly down regulated across most human tissues, including the brain, except liver and blood, and are not measurable in E18 mouse brain. The altered biological networks we identified contain critical molecular players known to contribute to ALS pathology, which also interact with SERPINA1. Our comprehensive combined methylation and transcription study identifies new genes and highlights that direct genetic and epigenetic changes contribute to c9ALS and sALS pathogenesis.

Haematopoietic stem and progenitor cells from human pluripotent stem cells.

A variety of tissue lineages can be differentiated from pluripotent stem cells by mimicking embryonic development through stepwise exposure to morphogens, or by conversion of one differentiated cell type into another by enforced expression of master transcription factors. Here, to yield functional human haematopoietic stem cells, we perform morphogen-directed differentiation of human pluripotent stem cells into haemogenic endothelium followed by screening of 26 candidate haematopoietic stem-cell-specifying transcription factors for their capacity to promote multi-lineage haematopoietic engraftment in mouse hosts. We recover seven transcription factors (ERG, HOXA5, HOXA9, HOXA10, LCOR, RUNX1 and SPI1) that are sufficient to convert haemogenic endothelium into haematopoietic stem and progenitor cells that engraft myeloid, B and T cells in primary and secondary mouse recipients. Our combined approach of morphogen-driven differentiation and transcription-factor-mediated cell fate conversion produces haematopoietic stem and progenitor cells from pluripotent stem cells and holds promise for modelling haematopoietic disease in humanized mice and for therapeutic strategies in genetic blood disorders.

A network-based phenotype mapping approach to identify genes that modulate drug response phenotypes.

To better address the problem of drug resistance during cancer chemotherapy and explore the possibility of manipulating drug response phenotypes, we developed a network-based phenotype mapping approach (P-Map) to identify gene candidates that upon perturbed can alter sensitivity to drugs. We used basal transcriptomics data from a panel of human lymphoblastoid cell lines (LCL) to infer drug response networks (DRNs) that are responsible for conferring response phenotypes for anthracycline and taxane, two common anticancer agents use in clinics. We further tested selected gene candidates that interact with phenotypic differentially expressed genes (PDEGs), which are up-regulated genes in LCL for a given class of drug response phenotype in triple-negative breast cancer (TNBC) cells. Our results indicate that it is possible to manipulate a drug response phenotype, from resistant to sensitive or vice versa, by perturbing gene candidates in DRNs and suggest plausible mechanisms regulating directionality of drug response sensitivity. More important, the current work highlights a new way to formulate systems-based therapeutic design: supplementing therapeutics that aim to target disease culprits with phenotypic modulators capable of altering DRN properties with the goal to re-sensitize resistant phenotypes.

TGF-ß inhibitors stimulate red blood cell production by enhancing self-renewal of BFU-E erythroid progenitors.

Burst-forming unit erythroid progenitors (BFU-Es) are so named based on their ability to generate in methylcellulose culture large colonies of erythroid cells that consist of "bursts" of smaller erythroid colonies derived from the later colony-forming unit erythroid progenitor erythropoietin (Epo)-dependent progenitors. "Early" BFU-E cells forming large BFU-E colonies presumably have higher capacities for self-renewal than do "late" BFU-Es forming small colonies, but the mechanism underlying this heterogeneity remains unknown. We show that the type III transforming growth factor ß (TGF-ß) receptor (TßRIII) is a marker that distinguishes early and late BFU-Es. Transient elevation of TßRIII expression promotes TGF-ß signaling during the early BFU-E to late BFU-E transition. Blocking TGF-ß signaling using a receptor kinase inhibitor increases early BFU-E cell self-renewal and total erythroblast production, suggesting the usefulness of this type of drug in treating Epo-unresponsive anemias.

The inhibition of TDP-43 mitochondrial localization blocks its neuronal toxicity.

Genetic mutations in TAR DNA-binding protein 43 (TARDBP, also known as TDP-43) cause amyotrophic lateral sclerosis (ALS), and an increase in the presence of TDP-43 (encoded by TARDBP) in the cytoplasm is a prominent histopathological feature of degenerating neurons in various neurodegenerative diseases. However, the molecular mechanisms by which TDP-43 contributes to ALS pathophysiology remain elusive. Here we have found that TDP-43 accumulates in the mitochondria of neurons in subjects with ALS or frontotemporal dementia (FTD). Disease-associated mutations increase TDP-43 mitochondrial localization. In mitochondria, wild-type (WT) and mutant TDP-43 preferentially bind mitochondria-transcribed messenger RNAs (mRNAs) encoding respiratory complex I subunits ND3 and ND6, impair their expression and specifically cause complex I disassembly. The suppression of TDP-43 mitochondrial localization abolishes WT and mutant TDP-43-induced mitochondrial dysfunction and neuronal loss, and improves phenotypes of transgenic mutant TDP-43 mice. Thus, our studies link TDP-43 toxicity directly to mitochondrial bioenergetics and propose the targeting of TDP-43 mitochondrial localization as a promising therapeutic approach for neurodegeneration.

NetDecoder: a network biology platform that decodes context-specific biological networks and gene activities.

The sequential chain of interactions altering the binary state of a biomolecule represents the 'information flow' within a cellular network that determines phenotypic properties. Given the lack of computational tools to dissect context-dependent networks and gene activities, we developed NetDecoder, a network biology platform that models context-dependent information flows using pairwise phenotypic comparative analyses of protein-protein interactions. Using breast cancer, dyslipidemia and Alzheimer's disease as case studies, we demonstrate NetDecoder dissects subnetworks to identify key players significantly impacting cell behaviour specific to a given disease context. We further show genes residing in disease-specific subnetworks are enriched in disease-related signalling pathways and information flow profiles, which drive the resulting disease phenotypes. We also devise a novel scoring scheme to quantify key genes-network routers, which influence many genes, key targets, which are influenced by many genes, and high impact genes, which experience a significant change in regulation. We show the robustness of our results against parameter changes. Our network biology platform includes freely available source code (http://www.NetDecoder.org) for researchers to explore genome-wide context-dependent information flow profiles and key genes, given a set of genes of particular interest and transcriptome data. More importantly, NetDecoder will enable researchers to uncover context-dependent drug targets.

Nanoparticle translocation through a lipid bilayer tuned by surface chemistry.

An enhanced understanding about the interactions between nanomaterials and cell membranes may have important implications for biomedical applications. In this work, coarse-grained molecular dynamics simulations of gold nanoparticles interacting with lipid bilayers were performed to evaluate the effect of hydrophobicity, charge density and ligand length on lipid bilayers. The simulations accomplished indicate that hydrophobic and anionic nanoparticles do not exhibit significant interactions and different charge densities may induce pore formation or nanoparticle wrapping, resembling first stages of endocytosis. The suggested interplay between charge density and ligand length has important implications when designing nanoparticles for drug and gene delivery applications. Moreover, control of charge densities may induce internalization of nanoparticles into cells through different mechanisms such as passive translocation, for nanoparticles with low charge density, or endocytosis for higher charge densities, highlighting the role of surface chemistry in nanoparticle-cell interactions.

COMPUTATIONAL ANALYSIS BASED ON ARTIFICIAL NEURAL NETWORKS FOR AIDING IN DIAGNOSING OSTEOARTHRITIS OF THE LUMBAR SPINE.

OBJECTIVE: To ascertain the advantages of applying artificial neural networks to recognize patterns on lumbar spine radiographies in order to aid in the process of diagnosing primary osteoarthritis. METHODS: This was a cross-sectional descriptive analytical study with a quantitative approach and an emphasis on diagnosis. The training set was composed of images collected between January and July 2009 from patients who had undergone lateral-view digital radiographies of the lumbar spine, which were provided by a radiology clinic located in the municipality of Criciúma (SC). Out of the total of 260 images gathered, those with distortions, those presenting pathological conditions that altered the architecture of the lumbar spine and those with patterns that were difficult to characterize were discarded, resulting in 206 images. The image data base (n = 206) was then subdivided, resulting in 68 radiographies for the training stage, 68 images for tests and 70 for validation. A hybrid neural network based on Kohonen self-organizing maps and on Multilayer Perceptron networks was used. RESULTS: After 90 cycles, the validation was carried out on the best results, achieving accuracy of 62.85%, sensitivity of 65.71% and specificity of 60%. CONCLUSIONS: Even though the effectiveness shown was moderate, this study is still innovative. The values show that the technique used has a promising future, pointing towards further studies on image and cycle processing methodology with a larger quantity of radiographies.