Richard A. McIndoe

Mouse Models of Diabetic Nephropathy

Diabetic nephropathy is a major cause of ESRD worldwide. Despite its prevalence, a lack of reliable animal models that mimic human disease has delayed the identification of specific factors that cause or predict diabetic nephropathy. The Animal Models of Diabetic Complications Consortium (AMDCC) was created in 2001 by the National Institutes of Health to develop and characterize models of diabetic nephropathy and other complications. This interim report and our online supplement detail the progress made toward that goal, specifically in the development and testing of murine models. Updates are provided on validation criteria for early and advanced diabetic nephropathy, phenotyping methods, the effect of background strain on nephropathy, current best models of diabetic nephropathy, negative models, and views of future directions. AMDCC investigators and other investigators in the field have yet to validate a complete murine model of human diabetic kidney disease. Nonetheless, the critical analysis of existing murine models substantially enhances our understanding of this disease process.

Thymus-derived regulatory T cells contribute to tolerance to commensal microbiota

Peripheral mechanisms preventing autoimmunity and maintaining tolerance to commensal microbiota involve CD4+ Foxp3+ regulatory T (Treg) cells generated in the thymus or extrathymically by induction of naive CD4+ Foxp3− T cells. Previous studies suggested that the T-cell receptor repertoires of thymic Treg cells and induced Treg cells are biased towards self and non-self antigens, respectively, but their relative contribution in controlling immunopathology, such as colitis and other untoward inflammatory responses triggered by different types of antigens, remains unresolved. The intestine, and especially the colon, is a particularly suitable organ to study this question, given the variety of self-, microbiota- and food-derived antigens to which Treg cells and other T-cell populations are exposed. Intestinal environments can enhance conversion to a regulatory lineage and favour tolerogenic presentation of antigens to naive CD4+ T cells, suggesting that intestinal homeostasis depends on microbiota-specific induced Treg cells. Here, to identify the origin and antigen-specificity of intestinal Treg cells, we performed single-cell and high-throughput sequencing of the T-cell receptor repertoires of CD4+ Foxp3+ and CD4+ Foxp3− T cells, and analysed their reactivity against specific commensal species. We show that thymus-derived Treg cells constitute most Treg cells in all lymphoid and intestinal organs, including the colon, where their repertoire is heavily influenced by the composition of the microbiota. Our results suggest that thymic Treg cells, and not induced Treg cells, dominantly mediate tolerance to antigens produced by intestinal commensals.

Early pathogenic events associated with Sjögren's syndrome (SjS)-like disease of the nod mouse using microarray analysis

Recently, we reported development of the C57BL/6.NOD-Aec1Aec2 mouse carrying two genetic intervals derived from the NOD mouse. These two genetic regions confer full Sjögrens syndrome (SjS)-like disease in SjS-non-susceptible C57BL/6 mice. The current study was undertaken to apply microarray technology to define the molecular basis underlying onset of SjS-disease in C57BL/6.NOD-Aec1Aec2 mice. Using oligonucleotide microarrays, gene expression profiles of submandibular glands derived from 8- to 12-week-old C57BL/6.NOD-Aec1Aec2 mice and 8-week-old C57BL/6 mice were performed for comparison. Significant differential expressions were determined using the Mann–Whitney U test. Hybridizations using submandibular cDNA probes revealed 75 differentially expressed genes at 8 weeks and 105 differentially expressed genes at 12 weeks of age in C57BL/6.NOD-Aec1Aec2 mice compared to 8-week-old C57BL/6 mice. These genes were related generally to basic cellular activities such as transcription, translation, DNA replication, and protein folding. During the predisease phase, genes upregulated encode proteins associated with the IFN-gamma signal-transduction-pathway (Jak/Stat1), TLR-3 (Irf3 and Traf6) and apoptosis (casp11 and casp3), indicative of chronic proinflammatory stimuli, especially IL-1. Between 8 and 12 weeks of age, sets of clustered genes were upregulated that are associated with adaptive immune responses, especially B cell activation, proliferation and differentiation (Baffr, Taci, Bcma, Blys, April, CD70, CD40L, Traf1, Traf3, Pax5, c-Jun, Elk1 and Nf-kB), and neural receptors (Taj/Troy). Altered gene expressions of TLR3 and TNF-superfamily-receptors and ligands during this early phase of SjS suggest a possible viral etiology in the altered glandular homeostasis with an upregulated, possibly overstimulated, B-lymphocyte activation in the early autoimmune response present in the submandibular glands. The importance of NF-κB as a critical signal transduction pathway is also suggested but its link is not yet clear.

Gene Expression Profiling during All-trans Retinoic Acid-Induced Cell Differentiation of Acute Promyelocytic Leukemia Cells

Using cDNA microarrays we determined the gene expression patterns in the human acute promyelocytic leukemia (APL) cell line NB4 during all-trans retinoic acid (ATRA)-induced differentiation. We analyzed the expression of 12,288 genes in the NB4 cells after 12 hours, 24 hours, 48 hours, 72 hours, and 96 hours of ATRA exposure. During this time course, we found 168 up-regulated and more than 179 down-regulated genes, most of which have not been reported before. Many of the altered genes encode products that participate in signaling pathways, cell differentiation, programmed cell death, transcription regulation, and production of cytokines and chemokines. Of interest, the CD52 and protein kinase A regulatory subunit alpha (PKA-Rlalpha) genes, whose products are being used as therapeutic targets for certain human neoplasias in currently ongoing clinical trials, were among the genes observed to be markedly up-regulated after ATRA treatment. The present study provides valuable data to further understand the mechanism of ATRA-induced APL cell differentiation and suggests potential therapeutic alternatives for this leukemia.

Differential Gene Expressions in the Lacrimal Gland During Development and Onset of Keratoconjunctivitis Sicca in Sjögren's Syndrome (SjS)-Like Disease of the C57BL/6.Nod-Aec1aec2 Mouse

Recently, we reported development of the C57BL/6.NOD-Aec1Aec2 mouse carrying two genetic intervals derived from the NOD mouse. These two genetic regions confer Sjögrens syndrome (SjS)-like disease in SjS-non-susceptible C57BL/6 mice. In an attempt to define the molecular bases underlying onset of dacryoadenitis and subsequently keratoconjunctivitis sicca (or xerophthalmia) in the C57BL/6.NOD-Aec1Aec2 mouse model, we have carried out a study utilizing microarray technology. Using oligonucleotide microarrays, gene expression profiles of lacrimal glands at 4, 8, 12, 16 and 20weeks of age were generated for C57BL/6.NOD-Aec1Aec2 male mice. Analyses using Linear Models for Microarray Analysis package and B-statistics, 552 genes were identified as being differentially expressed (adjusted p-value <0.01 and B <1.5) during the development of SjS-like disease. These 552 genes could be arranged into four clusters, with each cluster defining a unique pattern of temporal expression, while the individual genes within each cluster could be grouped according to related function. Using a pair-wise analysis, temporal changes in gene expressions provided profiles indicating that individual genes were differentially expressed at specific time points during development of SjS. In addition, multiple genes that have been reported to show, either in humans or mouse models, an association with autoimmunity and/or SjS, e.g., ApoE, Baff, Clu, Ctla4, Fas/Fasl, Irf5, Lyzs, Nfkb, Socs3, Stat4, Tap2, Tgfbeta1, Tnfa, and Vcam1 were also found to exhibit differential expressions, both quantitatively and temporally. Selecting a few families of genes, e.g., cystatins, cathepsins, metalloproteinases, lipocalins, complement, kallikreins, carbonic anhydrases and tumor necrosis factors, it was noted that only a limited number of family members showed differential expressions, suggesting a restricted glandular expression. Utilizing these genes, pathways of inter-reactive genes have been constructed for apoptosis and fatty acid homeostasis, leading to modeling of possible underlying events inducing disease. Thus, these different approaches to analyze microarray data permit identification of multiple sets of genes of interest whose expressions and expression profiles may correlate with molecular mechanisms, signaling pathways and/or immunological processes involved in the development and onset of SjS in this mouse model, thereby providing new insight into the underlying cause or regulation of this disease.

Differential gene expression in the salivary gland during development and onset of xerostomia in Sjögren's syndrome-like disease of the C57BL/6.NOD-Aec1Aec2 mouse

IntroductionRecently, we reported the development of the C57BL/6.NOD-Aec1Aec2 mouse that carries two genetic intervals derived from the non-obese diabetic (NOD) mouse capable of conferring Sjögrens syndrome (SjS)-like disease in SjS-non-susceptible C57BL/6 mice. In an attempt to define the molecular bases underlying the onset of stomatitis sicca (xerostomia) in this C57BL/6.NOD-Aec1Aec2 mouse model, we have carried out a study using genomic microarray technology.MethodsBy means of oligonucleotide microarrays, gene expression profiles of salivary glands at 4, 8, 12, 16, and 20 weeks of age were generated for C57BL/6.NOD-Aec1Aec2 male mice. Using Linear Models for Microarray Analysis and B-statistics software, 480 genes were identified as being differentially expressed (P < 0.01 and Q < 0.0001) during the development of SjS-like disease in the salivary glands.ResultsThe 480 genes could be arranged into four clusters, with each cluster defining a unique pattern of temporal expression, while the individual genes within each cluster could be grouped according to related biological functions. By means of pair-wise analysis, temporal changes in transcript expressions provided profiles indicating that many additional genes are differentially expressed at specific time points during the development of disease. Multiple genes reportedly showing an association with autoimmunity and/or SjS, in either humans or mouse models, were found to exhibit differential expressions, both quantitatively and temporally. Selecting various families of genes associated with specific functions (for example, antibody production, complement, and chemokines), we noted that only a limited number of family members showed differential expressions and these correlated with specific phases of disease.ConclusionsTaking advantage of known functions of these genes, investigators can construct interactive gene pathways, leading to modeling of possible underlying events inducing salivary gland dysfunction. Thus, these different approaches to analyzing microarray data permit the identification of multiple sets of genes of interest whose expressions and expression profiles may correlate with molecular mechanisms, signaling pathways, and/or immunological processes involved in the development and onset of SjS.

ParaKMeans: Implementation of a parallelized K-means algorithm suitable for general laboratory use

BackgroundDuring the last decade, the use of microarrays to assess the transcriptome of many biological systems has generated an enormous amount of data. A common technique used to organize and analyze microarray data is to perform cluster analysis. While many clustering algorithms have been developed, they all suffer a significant decrease in computational performance as the size of the dataset being analyzed becomes very large. For example, clustering 10000 genes from an experiment containing 200 microarrays can be quite time consuming and challenging on a desktop PC. One solution to the scalability problem of clustering algorithms is to distribute or parallelize the algorithm across multiple computers.ResultsThe software described in this paper is a high performance multithreaded application that implements a parallelized version of the K-means Clustering algorithm. Most parallel processing applications are not accessible to the general public and require specialized software libraries (e.g. MPI) and specialized hardware configurations. The parallel nature of the application comes from the use of a web service to perform the distance calculations and cluster assignments. Here we show our parallel implementation provides significant performance gains over a wide range of datasets using as little as seven nodes. The software was written in C# and was designed in a modular fashion to provide both deployment flexibility as well as flexibility in the user interface.ConclusionParaKMeans was designed to provide the general scientific community with an easy and manageable client-server application that can be installed on a wide variety of Windows operating systems.

Hepatic Gene Expression Profiling Reveals Key Pathways Involved in Leptin-Mediated Weight Loss in ob/ob Mice

Background Leptin, a cytokine-like protein, plays an important role in the regulation of body weight through inhibition of food intake and stimulation of energy expenditure. Leptin circulates in blood and acts on the brain, which sends downstream signals to regulate body weight. Leptin therapy has been successful in treating leptin deficient obese patients. However, high levels of leptin have been observed in more common forms of obesity indicating a state of leptin resistance which limits the application of leptin in the treatment of obesity. If the central effect of leptin could be by-passed and genes which respond to leptin treatment could be regulated directly, new therapeutic targets for the treatment of obesity may be possible. The purpose of this study was to identify genes and subsequent pathways correlated with leptin-mediated weight loss. Methodology/Principal Findings We utilized microarray technology to compare hepatic gene expression changes after two types of leptin administration: one involving a direct stimulatory effect when administered peripherally (subcutaneous: SQ) and another that is indirect, involving a hypothalamic relay that suppresses food intake when leptin is administered centrally (intracerebroventricular: ICV). We identified 214 genes that correlate with leptin mediated weight loss. Several biological processes such as mitochondrial metabolic pathways, lipid metabolic and catabolic processes, lipid biosynthetic processes, carboxylic acid metabolic processes, iron ion binding and glutathione S-transferases were downregulated after leptin administration. In contrast, genes involved in the immune system inflammatory response and lysosomal activity were found to be upregulated. Among the cellular compartments mitochondrion (32 genes), endoplasmic reticulum (22 genes) and vacuole (8 genes) were significantly over represented. Conclusions/Significance In this study we have identified key molecular pathways and downstream genes which respond to leptin treatment and are involved in leptin-mediated weight loss. Many of these genes have previously been shown to be associated with obesity; however, we have also identified a number of other novel target genes. Further investigation will be required to assess the possible use of these genes and their associated protein products as therapeutic targets for the treatment of obesity.

A modified hyperplane clustering algorithm allows for efficient and accurate clustering of extremely large datasets

Motivation: As the number of publically available microarray experiments increases, the ability to analyze extremely large datasets across multiple experiments becomes critical. There is a requirement to develop algorithms which are fast and can cluster extremely large datasets without affecting the cluster quality. Clustering is an unsupervised exploratory technique applied to microarray data to find similar data structures or expression patterns. Because of the high input/output costs involved and large distance matrices calculated, most of the algomerative clustering algorithms fail on large datasets (30 000 + genes/200 + arrays). In this article, we propose a new two-stage algorithm which partitions the high-dimensional space associated with microarray data using hyperplanes. The first stage is based on the Balanced Iterative Reducing and Clustering using Hierarchies algorithm with the second stage being a conventional k-means clustering technique. This algorithm has been implemented in a software tool (HPCluster) designed to cluster gene expression data. We compared the clustering results using the two-stage hyperplane algorithm with the conventional k-means algorithm from other available programs. Because, the first stage traverses the data in a single scan, the performance and speed increases substantially. The data reduction accomplished in the first stage of the algorithm reduces the memory requirements allowing us to cluster 44 460 genes without failure and significantly decreases the time to complete when compared with popular k-means programs. The software was written in C# (.NET 1.1). Availability: The program is freely available and can be downloaded from http://www.amdcc.org/bioinformatics/bioinformatics.aspx. Contact: rmcindoe@mail.mcg.edu Supplementary information: Supplementary data are available at Bioinformatics online.

The IL-10 and IFN-γ pathways are essential to the potent immunosuppressive activity of cultured CD8+NKT-like cells

BackgroundCD8+ NKT-like cells are naturally occurring but rare T cells that express both T cell and natural killer cell markers. These cells may play key roles in establishing tolerance to self-antigens; however, their mechanism of action and molecular profiles are poorly characterized due to their low frequencies. We developed an efficient in vitro protocol to produce CD8+ T cells that express natural killer cell markers (CD8+ NKT-like cells) and extensively characterized their functional and molecular phenotypes using a variety of techniques.ResultsLarge numbers of CD8+ NKT-like cells were obtained through culture of naïve CD8+ T cells using anti-CD3/anti-CD28-coated beads and high dose IL-2. These cells possess potent activity in suppressing the proliferation of naïve responder T cells. Gene expression profiling suggests that the cultured CD8+ NKT-like cells and the naïve CD8+ T cells differ by more than 2-fold for about 3,000 genes, among which 314 are upregulated by more than 5-fold and 113 are upregulated by more than 10-fold in the CD8+ NKT-like cells. A large proportion of the highly upregulated genes are soluble factors or surface markers that have previously been implicated in immune suppression or are likely to possess immunosuppressive properties. Many of these genes are regulated by two key cytokines, IL-10 and IFN-γ. The immunosuppressive activities of cells cultured from IL-10-/- and IFN-γ-/- mice are reduced by about 70% and about 50%, respectively, compared to wild-type mice.ConclusionImmunosuppressive CD8+ NKT-like cells can be efficiently produced and their immunosuppressive activity is related to many surface and soluble molecules regulated by IL-10 and IFN-γ.