BackgroundIn the post-genomic era, the rapid increase in high-throughput data calls for computational tools capable of integrating data of diverse types and facilitating recognition of biologically meaningful patterns within them. For example, protein-protein interaction data sets have been clustered to identify stable complexes, but scientists lack easily accessible tools to facilitate combined analyses of multiple data sets from different types of experiments. Here we present clusterMaker, a Cytoscape plugin that implements several clustering algorithms and provides network, dendrogram, and heat map views of the results. The Cytoscape network is linked to all of the other views, so that a selection in one is immediately reflected in the others. clusterMaker is the first Cytoscape plugin to implement such a wide variety of clustering algorithms and visualizations, including the only implementations of hierarchical clustering, dendrogram plus heat map visualization (tree view), k-means, k-medoid, SCPS, AutoSOME, and native (Java) MCL.ResultsResults are presented in the form of three scenarios of use: analysis of protein expression data using a recently published mouse interactome and a mouse microarray data set of nearly one hundred diverse cell/tissue types; the identification of protein complexes in the yeast Saccharomyces cerevisiae; and the cluster analysis of the vicinal oxygen chelate (VOC) enzyme superfamily. For scenario one, we explore functionally enriched mouse interactomes specific to particular cellular phenotypes and apply fuzzy clustering. For scenario two, we explore the prefoldin complex in detail using both physical and genetic interaction clusters. For scenario three, we explore the possible annotation of a protein as a methylmalonyl-CoA epimerase within the VOC superfamily. Cytoscape session files for all three scenarios are provided in the Additional Files section.ConclusionsThe Cytoscape plugin clusterMaker provides a number of clustering algorithms and visualizations that can be used independently or in combination for analysis and visualization of biological data sets, and for confirming or generating hypotheses about biological function. Several of these visualizations and algorithms are only available to Cytoscape users through the clusterMaker plugin. clusterMaker is available via the Cytoscape plugin manager.

In multiple sclerosis (MS) pathogenic B cells likely act on both sides of the blood-brain barrier (BBB). However, it is unclear whether antigen-experienced B cells are shared between the CNS and the peripheral blood (PB) compartments. We applied deep repertoire sequencing of IgG heavy chain variable region genes (IgG-VH) in paired cerebrospinal fluid and PB samples from patients with MS and other neurological diseases to identify related B cells that are common to both compartments. For the first time to our knowledge, we found that a restricted pool of clonally related B cells participated in robust bidirectional exchange across the BBB. Some clusters of related IgG-VH appeared to have undergone active diversification primarily in the CNS, while others have undergone active diversification in the periphery or in both compartments in parallel. B cells are strong candidates for autoimmune effector cells in MS, and these findings suggest that CNS-directed autoimmunity may be triggered and supported on both sides of the BBB. These data also provide a powerful approach to identify and monitor B cells in the PB that correspond to clonally amplified populations in the CNS in MS and other inflammatory states.

In multiple sclerosis (MS), an exchange of lymphocytes, in particular B cells, between the central nervous system (CNS) and periphery is believed to be required for the maintenance of active disease. Therapeutic monoclonal antibodies that prevent lymphocytes from crossing the blood-brain barrier (BBB) or induce near-complete peripheral B cell depletion rapidly mitigate MS disease activity. Using next-generation sequencing technology, we recently found that clonally related B cells exist in the cerebrospinal fluid (CSF) and peripheral blood (PB) of MS patients, establishing the existence of an immune axis across the BBB. However, it remains unclear which subpopulations of the highly diverse peripheral B cell compartment share antigen-specificity with intrathecal B cell repertoires, and whether their antigen stimulation occurs on both sides of the BBB. To address these questions, we combined flow cytometry sorting of PB B cell subsets with deep immune repertoire sequencing of CSF and PB B cells. Immunoglobulin (IgM and IgG) heavy chain variable (VH) region repertoires of five PB B cell subsets from MS patients (n=8) were compared with their CSF Ig-VH transcriptomes. In 6 of 8 patients, we identified peripheral CD27+IgD−memory B cells, CD27hiCD38hi plasma cells/plasmablasts, or CD27−IgD− B cells providing an immune connection to the CNS compartment. Pinpointing Ig class-switched B cells as key component of the immune axis thought to contribute to ongoing MS disease activity strengthens the rationale of current therapeutic strategies and may lead to more targeted approaches.

Solute carriers are eukaryotic membrane proteins that control the uptake and efflux of solutes, including essential cellular compounds, environmental toxins, and therapeutic drugs. Solute carriers can share similar structural features despite weak sequence similarities. Identification of sequence relationships among solute carriers is needed to enhance our ability to model individual carriers and to elucidate the molecular mechanisms of their substrate specificity and transport. Here, we describe a comprehensive comparison of solute carriers. We link the proteins using sensitive profile-profile alignments and two classification approaches, including similarity networks. The clusters are analyzed in view of substrate type, transport mode, organism conservation, and tissue specificity. Solute carrier families with similar substrates generally cluster together, despite exhibiting relatively weak sequence similarities. In contrast, some families cluster together with no apparent reason, revealing unexplored relationships. We demonstrate computationally and experimentally the functional overlap between representative members of these families. Finally, we identify four putative solute carriers in the human genome. The solute carriers include a biomedically important group of membrane proteins that is diverse in sequence and structure. The proposed classification of solute carriers, combined with experiment, reveals new relationships among the individual families and identifies new solute carriers. The classification scheme will inform future attempts directed at modeling the structures of the solute carriers, a prerequisite for describing the substrate specificities of the individual families.

ObjectiveTo determine to what extent oligoclonal band (OCB) specificities are clonally interrelated and to what degree they are associated with corresponding B-cell responses in the peripheral blood (PB) of multiple sclerosis (MS) patients.MethodsMass-spectrometric proteomic analysis of isoelectric focused (IEF) cerebrospinal fluid (CSF) immunoglobulin G (IgG) was used in combination with next-generation deep-immune repertoire sequencing of PB and CSF IgG heavy chain variable regions from MS patients.ResultsWe find evidence for ongoing stimulation and maturation to antibody-expressing B cells to occur primarily inside the central nervous system (CNS) compartment. B cells participating in OCB production can also be identified in PB; these cells appear to migrate across the blood–brain barrier and may also undergo further antigen stimulation in the periphery. In individual patients, different bands comprising OCBs are clonally related.InterpretationOur data provide a high-resolution molecular analysis of OCBs and strongly support the concept that OCBs are not merely the terminal result of a targeted immune response in MS but represent a component of active B cell immunity that is dynamically supported on both sides of the blood-brain barrier.

Python code for implementing the automated threshold selection heuristic, together with the datasets used in our analysis, are available at http://www.rbvi.ucsf.edu/Research/cytoscape/threshold_scripts.zip.

Background: Recently, the research community has seen an influx of data relating to transcriptional regulatory interactions of Corynebacteria, organisms that are highly relevant to fields of systems biology, biotechnology, and human medicine. Information derived from DNA microarray experiments, computational predictions, and literature has opened the way for the graph-based analysis, visualization, and reconstruction of transcriptional regulatory networks across entire organisms. The reference database for corynebacterial gene regulatory networks CoryneRegNet provides methods for data storage and data exchange in a well-structured manner. Additional information on the model organism Escherichia coli K12 obtained from RegulonDB has been integrated. Generally, gene regulatory networks can be visualized as graphs by drawing directed edges between nodes, where a node represents a gene and an edge corresponds to a typed regulatory interaction. Cytoscape is an open-source software project whose aim is to provide graph-based visualization and analysis for biological networks. Its architecture allows the development and integration of user-made plugins to enhance core functionalities.

Large-scale DNA sequencing of immunological repertoires offers an opportunity for the discovery of novel biomarkers for autoimmune disease. Available bioinformatics techniques however, are not adequately suited for elucidating possible biomarker candidates from within large immunosequencing datasets due to unsatisfactory scalability and sensitivity. Here, we present the Haystack Heuristic, an algorithm customized to computationally extract disease-associated motifs from next-generation-sequenced repertoires by contrasting disease and healthy subjects. This technique employs a local-search graph-theory approach to discover novel motifs in patient data. We apply the Haystack Heuristic to nine million B-cell receptor sequences obtained from nearly 100 individuals in order to elucidate a new motif that is significantly associated with multiple sclerosis. Our results demonstrate the effectiveness of the Haystack Heuristic in computing possible biomarker candidates from high throughput sequencing data and could be generalized to other datasets.