Romesh Stanislaus

Amelioration of experimental allergic encephalomyelitis in Lewis rats by lovastatin.

Proinflammatory cytokines and inducible nitric oxide synthase (iNOS) are involved in the pathogenesis of experimental allergic encephalomyelitis (EAE), an animal model of multiple sclerosis (MS). We have previously reported that lovastatin (Pahan, K., Sheikh., F.G., Namboodiri, A. and Singh, I., Lovastatin and Phenylacetate inhibit the induction of nitric oxide synthase and cytokines in rat primary astrocytes, microglia and macrophages. J. Clin. Invest., 100 (1997) 2671-2679.), an inhibitor of the mevalonate pathway, inhibits the expression of iNOS and proinflammatory cytokines in rat primary glial cells (astroglia and microglia) and macrophages. The present study underlines the therapeutic importance of lovastatin in ameliorating the neuroinflammatory disease process in the central nervous system of EAE rats. Immunohistochemical results show a higher degree of expression of iNOS, tumor necrosis factor-alpha (TNF-alpha) and interferon-gamma (IFN-gamma) in brains of rats with acute monophasic EAE relative to the control animals. Administration of lovastatin inhibited the expression of iNOS, TNF-alpha and IFN-gamma in the CNS of EAE rats and improved the clinical signs of EAE suggesting that this compound may have therapeutic potential in the treatment of neuroinflammatory diseases like MS.

Immunomodulation of experimental autoimmune encephalomyelitis in the Lewis rats by Lovastatin

Previous studies have demonstrated the immunomodulatory potential of Lovastatin, a hydroxy methyl glutaryl-CoA reductase inhibitor, in lessening the clinical and histological manifestations in the neuroinflammatory animal model experimental autoimmune encephalomyelitis (EAE) (Neurosci. Lett., 269 (1999) 71, and J. Neurosci. Res., 66 (2001) 155). To determine the mechanism behind the observed amelioration of EAE by Lovastatin, we examined the cytokine profile of stimulated splenocytes from control, EAE and Lovastatin treated EAE rats. Splenocytes from Lovastatin-treated EAE rats showed decreased levels of interferon-gamma, a Th1 type cytokine, while interleukin (IL)-10, a Th2 type cytokine, was markedly increased as compared to untreated EAE animals. In addition, we also observed reduced levels of IL-6 and nitric oxide production in lipopolysaccharide-stimulated splenocytes isolated from Lovastatin-treated animals. This study documents for the first time that Lovastatin induces a bias towards Th2 cytokines ex vivo, and as a result may be of therapeutic value for cell-mediated diseases such as multiple sclerosis.

Impaired peroxisomal function in the central nervous system with inflammatory disease of experimental autoimmune encephalomyelitis animals and protection by lovastatin treatment

Peroxisomes are ubiquitous subcellular organelles and abnormality in their biogenesis and specific gene defects leads to fatal demyelinating disorders. We report that neuroinflammatory disease in brain of experimental autoimmune encephalomyelitis (EAE) rats decreased the peroxisomal functions. Degradation of very long chain fatty acids decreased by 47% and resulted in its accumulation (C26:0, 40%). Decreased activity (66% of control) of dihydroxyacetonephosphate acyltransferase (DHAP-AT), first enzyme in plasmalogens biosynthesis, resulted in decreased levels of plasmalogens (16-30%). Catalase activity, a peroxisomal enzyme, was also reduced (37%). Gene microarray analysis of EAE spinal cord showed significant decrease in transcripts encoding peroxisomal proteins including catalase (folds 3.2; p<0.001) and DHAP-AT (folds 2.6; p<0.001). These changes were confirmed by quantitative reverse transcription polymerase chain reaction (RT-PCR) analysis, suggesting that decrease of peroxisomal functions in the central nervous system will have negative consequences for myelin integrity and repair because these lipids are major constituents of myelin. However, lovastatin (a cholesterol lowering and anti-inflammatory drug) administered during EAE induction provided protection against loss/down-regulation of peroxisomal functions. Attenuation of induction of neuroinflammatory mediators by statins in cultured brain cells [J. Clin. Invest. 100 (1997) 2671-2679], and in central nervous system of EAE animals and thus the EAE disease [J. Neurosci. Res. 66 (2001) 155-162] and the studies described here indicate that inflammatory mediators have a marked negative effect on peroxisomal functions and thus on myelin assembly and that these effects can be prevented by treatment with statins. These observations are of importance because statins are presently being tested as therapeutic agents against a number of neuroinflammatory demyelinating diseases.

N-acetyl-L-cysteine ameliorates the inflammatory disease process in experimental autoimmune encephalomyelitis in Lewis rats

We report that N-acetyl-L-cysteine (NAC) treatment blocked induction of TNF-α, IL-1β, IFN-γ and iNOS in the CNS and attenuated clinical disease in the myelin basic protein induced model of experimental allergic encephalomyelitis (EAE) in Lewis rats. Infiltration of mononuclear cells into the CNS and induction of inflammatory cytokines and iNOS in multiple sclerosis (MS) and EAE have been implicated in subsequent disease progression and pathogenesis. To understand the mechanism of efficacy of NAC against EAE, we examined its effect on the production of cytokines and the infiltration of inflammatory cells into the CNS. NAC treatment attenuated the transmigration of mononuclear cells thereby lessening the neuroinflammatory disease. Splenocytes from NAC-treated EAE animals showed reduced IFN-γ production, a Th1 cytokine and increased IL-10 production, an anti-inflammatory cytokine. Further, splenocytes from NAC-treated EAE animals also showed decreased nitrite production when stimulated in vitro by LPS. These observations indicate that NAC treatment may be of therapeutic value in MS against the inflammatory disease process associated with the infiltration of activated mononuclear cells into the CNS.

A Semantic Web management model for integrative biomedical informatics.

Background Data, data everywhere. The diversity and magnitude of the data generated in the Life Sciences defies automated articulation among complementary efforts. The additional need in this field for managing property and access permissions compounds the difficulty very significantly. This is particularly the case when the integration involves multiple domains and disciplines, even more so when it includes clinical and high throughput molecular data. Methodology/Principal Findings The emergence of Semantic Web technologies brings the promise of meaningful interoperation between data and analysis resources. In this report we identify a core model for biomedical Knowledge Engineering applications and demonstrate how this new technology can be used to weave a management model where multiple intertwined data structures can be hosted and managed by multiple authorities in a distributed management infrastructure. Specifically, the demonstration is performed by linking data sources associated with the Lung Cancer SPORE awarded to The University of Texas MDAnderson Cancer Center at Houston and the Southwestern Medical Center at Dallas. A software prototype, available with open source at www.s3db.org, was developed and its proposed design has been made publicly available as an open source instrument for shared, distributed data management. Conclusions/Significance The Semantic Web technologies have the potential to addresses the need for distributed and evolvable representations that are critical for systems Biology and translational biomedical research. As this technology is incorporated into application development we can expect that both general purpose productivity software and domain specific software installed on our personal computers will become increasingly integrated with the relevant remote resources. In this scenario, the acquisition of a new dataset should automatically trigger the delegation of its analysis.

An XML standard for the dissemination of annotated 2D gel electrophoresis data complemented with mass spectrometry results

BackgroundMany proteomics initiatives require a seamless bioinformatics integration of a range of analytical steps between sample collection and systems modeling immediately assessable to the participants involved in the process. Proteomics profiling by 2D gel electrophoresis to the putative identification of differentially expressed proteins by comparison of mass spectrometry results with reference databases, includes many components of sample processing, not just analysis and interpretation, are regularly revisited and updated. In order for such updates and dissemination of data, a suitable data structure is needed. However, there are no such data structures currently available for the storing of data for multiple gels generated through a single proteomic experiments in a single XML file. This paper proposes a data structure based on XML standards to fill the void that exists between data generated by proteomics experiments and storing of data.ResultsIn order to address the resulting procedural fluidity we have adopted and implemented a data model centered on the concept of annotated gel (AG) as the format for delivery and management of 2D Gel electrophoresis results. An eXtensible Markup Language (XML) schema is proposed to manage, analyze and disseminate annotated 2D Gel electrophoresis results. The structure of AG objects is formally represented using XML, resulting in the definition of the AGML syntax presented here.ConclusionThe proposed schema accommodates data on the electrophoresis results as well as the mass-spectrometry analysis of selected gel spots. A web-based software library is being developed to handle data storage, analysis and graphic representation. Computational tools described will be made available at http://bioinformatics.musc.edu/agml. Our development of AGML provides a simple data structure for storing 2D gel electrophoresis data.

Data integration gets 'Sloppy'

VOLUME 24 NUMBER 9 SEPTEMBER 2006 NATURE BIOTECHNOLOGY we emphatically recommend all users of dbSNP to refer to the ‘validation status’ tag and use a simple SNP classification scheme, as described above, that aims at extracting RefSNPs with lower error rates. According to our classification, dbSNP (version 124) contains in C1, C2 and C3 2,077,680, 2,946,840 and 3,470,166 entries, respectively. To investigate the differences between those three classes, we extracted the available confidence information. C1 and C2 RefSNPs have higher average values (both 51.4) than SNPs in C3 (43.2, Supplementary Notes online). Furthermore, about 87% in C1 and C2 have confidence values of at least 40, in contrast to only 63% in C3 (Fig. 1d). As a low confidence value indicates a potential sequencing error, we recommend that bioinformatics and/or experimental efforts either use only C1 and C2 RefSNPs or find a way of excluding from C3 all dbSNP entries with Phred <40 (ref. 11).

AGML Central: web based gel proteomic infrastructure

SUMMARY AGML Central is a web-based open-source public infrastructure for dissemination of two-dimensional Gel Electrophoresis (2-DE) proteomics data in AGML format (Annotated Gel Markup Language). It includes a growing collection of converters from proprietary formats such as those produced by PDQUEST (BioRad), PHORETIX 2-D (Nonlinear Dynamics) and Melanie (GenBio SA). The resulting unifying AGML formatted entry, with or without the raw gel images, is optionally stored in a database for future reference. AGML Central was developed to provide a common platform for data dissemination and development of 2-DE data analysis tools. This resource responds to an increasing use of AGML for 2-DE public source data representation which requires automated tools for conversion from proprietary formats. Conversion and short-term storage is made publicly available, permanent storage requires prior registering. A JAVA applet visualizer was developed to visualize the AGML data with cross-reference links. In order to facilitate automated access a SOAP web service is also included in the AGML Central infrastructure. AVAILABILITY http://bioinformatics.musc.edu/agmlcentral.

RPPAML/RIMS: A metadata format and an information management system for reverse phase protein arrays

BackgroundReverse Phase Protein Arrays (RPPA) are convenient assay platforms to investigate the presence of biomarkers in tissue lysates. As with other high-throughput technologies, substantial amounts of analytical data are generated. Over 1000 samples may be printed on a single nitrocellulose slide. Up to 100 different proteins may be assessed using immunoperoxidase or immunoflorescence techniques in order to determine relative amounts of protein expression in the samples of interest.ResultsIn this report an RPPA Information Management System (RIMS) is described and made available with open source software. In order to implement the proposed system, we propose a metadata format known as reverse phase protein array markup language (RPPAML). RPPAML would enable researchers to describe, document and disseminate RPPA data. The complexity of the data structure needed to describe the results and the graphic tools necessary to visualize them require a software deployment distributed between a client and a server application. This was achieved without sacrificing interoperability between individual deployments through the use of an open source semantic database, S3DB. This data service backbone is available to multiple client side applications that can also access other server side deployments. The RIMS platform was designed to interoperate with other data analysis and data visualization tools such as Cytoscape.ConclusionThe proposed RPPAML data format hopes to standardize RPPA data. Standardization of data would result in diverse client applications being able to operate on the same set of data. Additionally, having data in a standard format would enable data dissemination and data analysis.

Identification of Diagnostic Urinary Biomarkers for Acute Kidney Injury

Acute kidney injury (AKI) is an important cause of death among hospitalized patients. The 2 most common causes of AKI are acute tubular necrosis (ATN) and prerenal azotemia (PRA). Appropriate diagnosis of the disease is important but often difficult. We analyzed urine proteins by 2-dimensional gel electrophoresis from 38 patients with AKI. Patients were randomly assigned to a training set, an internal test set, or an external validation set. Spot abundances were analyzed by artificial neural networks to identify biomarkers that differentiate between ATN and PRA. When the trained neural network algorithm was tested against the training data, it identified the diagnosis for 16 of 18 patients in the training set and all 10 patients in the internal test set. The accuracy was validated in the novel external set of patients where conditions of 9 of 10 patients were correctly diagnosed including 5 of 5 with ATN and 4 of 5 with PRA. Plasma retinol-binding protein was identified in 1 spot and a fragment of albumin and plasma retinol-binding protein in the other. These proteins are candidate markers for diagnostic assays of AKI.