APP Maturation and Intracellular Localization Are Controlled by a Specific Inhibitor of 37/67 kDa Laminin-1 Receptor in Neuronal Cells.

Amyloid precursor protein (APP) is processed along both the nonamyloidogenic pathway preventing amyloid beta peptide (Aß) production and the amyloidogenic pathway, generating Aß, whose accumulation characterizes Alzheimer's disease. Items of evidence report that the intracellular trafficking plays a key role in the generation of Aß and that the 37/67 kDa LR (laminin receptor), acting as a receptor for Aß, may mediate Aß-pathogenicity. Moreover, findings indicating interaction between the receptor and the key enzymes involved in the amyloidogenic pathway suggest a strong link between 37/67 kDa LR and APP processing. We show herein that the specific 37/67 kDa LR inhibitor, NSC48478, is able to reversibly affect the maturation of APP in a pH-dependent manner, resulting in the partial accumulation of the immature APP isoforms (unglycosylated/acetylated forms) in the endoplasmic reticulum (ER) and in transferrin-positive recycling endosomes, indicating alteration of the APP intracellular trafficking. These effects reveal NSC48478 inhibitor as a novel small molecule to be tested in disease conditions, mediated by the 37/67 kDa LR and accompanied by inactivation of ERK1/2 (extracellular signal-regulated kinases) signalling and activation of Akt (serine/threonine protein kinase) with consequent inhibition of GSK3ß.

DISMIRA: Prioritization of disease candidates in miRNA-disease associations based on maximum weighted matching inference model and motif-based analysis.

BACKGROUND: MicroRNAs (miRNAs) have increasingly been found to regulate diseases at a significant level. The interaction of miRNA and diseases is a complex web of multilevel interactions, given the fact that a miRNA regulates upto 50 or more diseases and miRNAs/diseases work in clusters. The clear patterns of miRNA regulations in a disease are still elusive. METHODS: In this work, we approach the miRNA-disease interactions from a network scientific perspective and devise two approaches - maximum weighted matching model (a graph theoretical algorithm which provides the result by solving an optimization equation of selecting the most prominent set of diseases) and motif-based analyses (which investigates the motifs of the miRNA-disease network and selects the most prominent set of diseases based on their maximum number of participation in motifs, thereby revealing the miRNA-disease interaction dynamics) to determine and prioritize the set of diseases which are most certainly impacted upon the activation of a group of queried miRNAs, in a miRNA-disease network. RESULTS AND CONCLUSION: Our tool, DISMIRA implements the above mentioned approaches and presents an interactive visualization which helps the user in exploring the networking dynamics of miRNAs and diseases by analyzing their neighbors, paths and topological features. A set of miRNAs can be used in this analysis to get the associated diseases for the input group of miRs with ranks and also further analysis can be done to find key miRs or diseases, shortest paths etc. DISMIRA can be accessed online for free at http://bnet.egr.vcu.edu:8080/dismira.

Proteome scale comparative modeling for conserved drug and vaccine targets identification in Corynebacterium pseudotuberculosis.

Corynebacterium pseudotuberculosis (Cp) is a pathogenic bacterium that causes caseous lymphadenitis (CLA), ulcerative lymphangitis, mastitis, and edematous to a broad spectrum of hosts, including ruminants, thereby threatening economic and dairy industries worldwide. Currently there is no effective drug or vaccine available against Cp. To identify new targets, we adopted a novel integrative strategy, which began with the prediction of the modelome (tridimensional protein structures for the proteome of an organism, generated through comparative modeling) for 15 previously sequenced C. pseudotuberculosis strains. This pan-modelomics approach identified a set of 331 conserved proteins having 95-100% intra-species sequence similarity. Next, we combined subtractive proteomics and modelomics to reveal a set of 10 Cp proteins, which may be essential for the bacteria. Of these, 4 proteins (tcsR, mtrA, nrdI, and ispH) were essential and non-host homologs (considering man, horse, cow and sheep as hosts) and satisfied all criteria of being putative targets. Additionally, we subjected these 4 proteins to virtual screening of a drug-like compound library. In all cases, molecules predicted to form favorable interactions and which showed high complementarity to the target were found among the top ranking compounds. The remaining 6 essential proteins (adk, gapA, glyA, fumC, gnd, and aspA) have homologs in the host proteomes. Their active site cavities were compared to the respective cavities in host proteins. We propose that some of these proteins can be selectively targeted using structure-based drug design approaches (SBDD). Our results facilitate the selection of C. pseudotuberculosis putative proteins for developing broad-spectrum novel drugs and vaccines. A few of the targets identified here have been validated in other microorganisms, suggesting that our modelome strategy is effective and can also be applicable to other pathogens.

A novel in silico reverse-transcriptomics-based identification and blood-based validation of a panel of sub-type specific biomarkers in lung cancer.

Lung cancer accounts for the highest number of cancer-related deaths worldwide. Early diagnosis significantly increases the disease-free survival rate and a large amount of effort has been expended in screening trials and the development of early molecular diagnostics. However, a gold standard diagnostic strategy is not yet available. Here, based on miRNA expression profile in lung cancer and using a novel in silico reverse-transcriptomics approach, followed by analysis of the interactome; we have identified potential transcription factor (TF) markers that would facilitate diagnosis of subtype specific lung cancer. A subset of seven TF markers has been used in a microarray screen and was then validated by blood-based qPCR using stage-II and IV non-small cell lung carcinomas (NSCLC). Our results suggest that overexpression of HMGA1, E2F6, IRF1, and TFDP1 and downregulation or no expression of SUV39H1, RBL1, and HNRPD in blood is suitable for diagnosis of lung adenocarcinoma and squamous cell carcinoma sub-types of NSCLC. Here, E2F6 was, for the first time, found to be upregulated in NSCLC blood samples. The miRNA-TF-miRNA interaction based molecular mechanisms of these seven markers in NSCLC revealed that HMGA1 and TFDP1 play vital roles in lung cancer tumorigenesis. The strategy developed in this work is applicable to any other cancer or disease and can assist in the identification of potential biomarkers.

Molecular mechanism, diagnosis, and potential treatment for novel coronavirus (COVID-19): a current literature review and perspective.

Novel coronavirus disease 2019 (COVID-19) is a positive-sense single-stranded RNA virus which belongs to the Coronaviridae family. COVID-19 outbreak became evident after the severe acute respiratory syndrome coronavirus and the Middle East respiratory syndrome coronavirus in the twenty-first century as the start of the third deadly coronavirus. Currently, research is at an early stage, and the exact etiological dimensions of COVID-19 are unknown. Several candidate drugs and plasma therapy have been considered and evaluated for the treatment of severe COVID-19 patients. These include clinically available drugs such as chloroquine, hydroxychloroquine, and lopinavir/ritonavir. However, understanding the pathogenic mechanisms of this virus is critical for predicting interaction with humans. Based on recent evidence, we have summarized the current virus biology in terms of the possible understanding of the various pathophysiologies, molecular mechanisms, recent efficient diagnostics, and therapeutic approaches to control the disease. In addition, we briefly reviewed the biochemistry of leading candidates for novel therapies and their current status in clinical trials. As information from COVID-19 is evolving rapidly, this review will help the researcher to consider new insights and potential therapeutic approaches based on up-to-date knowledge. Finally, this review illustrates a list of alternative therapeutic solutions for a viral infection.

Inhibition of 37/67kDa Laminin-1 Receptor Restores APP Maturation and Reduces Amyloid-ß in Human Skin Fibroblasts from Familial Alzheimer's Disease.

Alzheimer's disease (AD) is a fatal neurodegenerative disorder caused by protein misfolding and aggregation, affecting brain function and causing dementia. Amyloid beta (Aß), a peptide deriving from amyloid precursor protein (APP) cleavage by-and γ-secretases, is considered a pathological hallmark of AD. Our previous study, together with several lines of evidence, identified a strict link between APP, Aß and 37/67kDa laminin receptor (LR), finding the possibility to regulate intracellular APP localization and maturation through modulation of the receptor. Here, we report that in fibroblasts from familial AD (fAD), APP was prevalently expressed as an immature isoform and accumulated preferentially in the transferrin-positive recycling compartment rather than in the Golgi apparatus. Moreover, besides the altered mitochondrial network exhibited by fAD patient cells, the levels of pAkt and pGSK3 were reduced in respect to healthy control fibroblasts and were accompanied by an increased amount of secreted Aß in conditioned medium from cell cultures. Interestingly, these features were reversed by inhibition of 37/67kDa LR by NSC47924 a small molecule that was able to rescue the "typical" APP localization in the Golgi apparatus, with consequences on the Aß level and mitochondrial network. Altogether, these findings suggest that 37/67kDa LR modulation may represent a useful tool to control APP trafficking and Aß levels with implications in Alzheimer's disease.

Current updates on the European and WHO registered clinical trials of coronavirus disease 2019 (COVID-19).

Coronavirus disease 2019 (COVID-19) is a major public health concern currently. To date, there are no approved antiviral drugs or vaccines against this transmissible disease. This report sheds light on available information for a better understanding of clinical trials and pharmacotherapy related to COVID-19. MEDLINE, PubMed, EMBASE, Scopus databases, Web of Science, WHO, and EU clinical trial sites were used to perform comparative analysis. Information was collected on the use of therapeutic agents for human therapy in patients with COVID-19 up to May 2020. We have extracted data from 60 clinical trials. Amongst these trials, 34 were from the European Union database of clinical trials and 26 from the National Institute of Health. The data selection procedure includes active, completed, and recruitment in progress status. Most of the clinical trials are ongoing and hence, there is a lack of precise results for the treatment.There is a lack of high-quality clinical evidence. The protocol to be developed requires large randomized clinical trials with a combination of available drugs and prospective therapies. We propose the usage of a large number of cases and different statistical analyses to conduct systematic clinical trials. This could provide comprehensive information about the clinical trial and potential therapeutic progress.

BARHL1 Is Downregulated in Alzheimer's Disease and May Regulate Cognitive Functions through ESR1 and Multiple Pathways.

The Transcription factor BarH like homeobox 1 (BARHL1) is overexpressed in medulloblastoma and plays a role in neurogenesis. However, much about the BARHL1 regulatory networks and their functions in neurodegenerative and neoplastic disorders is not yet known. In this study, using a tissue microarray (TMA), we report for the first time that BARHL1 is downregulated in hormone-negative breast cancers and Alzheimer's disease (AD). Furthermore, using an integrative bioinformatics approach and mining knockout mouse data, we show that: (i) BARHL1 and Estrogen Receptor 1 (ESR1) may constitute a network that regulates Neurotrophin 3 (NTF3)- and Brain Derived Neurotrophic Factor (BDNF)-mediated neurogenesis and neural survival; (ii) this is probably linked to AD pathways affecting aberrant post-translational modifications including SUMOylation and ubiquitination; (iii) the BARHL1-ESR1 network possibly regulates ß-amyloid metabolism and memory; and (iv) hsa-mir-18a, having common key targets in the BARHL1-ESR1 network and AD pathway, may modulate neuron death, reduce ß-amyloid processing and might also be involved in hearing and cognitive decline associated with AD. We have also hypothesized why estrogen replacement therapy improves AD condition. In addition, we have provided a feasible new mechanism to explain the abnormal function of mossy fibers and cerebellar granule cells related to memory and cognitive decline in AD apart from the Tau and amyloid pathogenesis through our BARHL1-ESR1 axis.

miRegulome: a knowledge-base of miRNA regulomics and analysis.

UNLABELLED: miRNAs regulate post transcriptional gene expression by targeting multiple mRNAs and hence can modulate multiple signalling pathways, biological processes, and patho-physiologies. Therefore, understanding of miRNA regulatory networks is essential in order to modulate the functions of a miRNA. The focus of several existing databases is to provide information on specific aspects of miRNA regulation. However, an integrated resource on the miRNA regulome is currently not available to facilitate the exploration and understanding of miRNA regulomics. miRegulome attempts to bridge this gap. The current version of miRegulome v1.0 provides details on the entire regulatory modules of miRNAs altered in response to chemical treatments and transcription factors, based on validated data manually curated from published literature. Modules of miRegulome (upstream regulators, downstream targets, miRNA regulated pathways, functions, diseases, etc) are hyperlinked to an appropriate external resource and are displayed visually to provide a comprehensive understanding. Four analysis tools are incorporated to identify relationships among different modules based on user specified datasets. miRegulome and its tools are helpful in understanding the biology of miRNAs and will also facilitate the discovery of biomarkers and therapeutics. With added features in upcoming releases, miRegulome will be an essential resource to the scientific community. AVAILABILITY: http://bnet.egr.vcu.edu/miRegulome.