Integration of biological networks and gene expression data using Cytoscape

Cytoscape is a free software package for visualizing, modeling and analyzing molecular and genetic interaction networks. This protocol explains how to use Cytoscape to analyze the results of mRNA expression profiling, and other functional genomics and proteomics experiments, in the context of an interaction network obtained for genes of interest. Five major steps are described: (i) obtaining a gene or protein network, (ii) displaying the network using layout algorithms, (iii) integrating with gene expression and other functional attributes, (iv) identifying putative complexes and functional modules and (v) identifying enriched Gene Ontology annotations in the network. These steps provide a broad sample of the types of analyses performed by Cytoscape.     

Site-selective glycosylation of proteins: creating synthetic glycoproteins

In higher organisms, the functions of many proteins are modulated by post-translational modifications (PTMs). Glycosylation is by far the most diverse of the PTM processes. Natural protein production methods typically produce PTM or glycoform mixtures within which function is difficult to dissect or control. Chemical tagging methods allow the precise attachment of multiple glycosylation modifications to bacterially expressed (bare) protein scaffolds, allowing reconstitution of functionally effective mimics of glycoproteins in higher organisms. In this way combining chemical control of PTM with readily available protein scaffolds provides a systematic platform for creating probes of protein-PTM interactions. This protocol describes the modification of Cys residues in proteins using glycomethanethiosulfonates and glycoselenenylsulfides and the modification of azidohomoalanine residues, introduced by Met replacement using auxotrophic Met(-) Escherichia coli strains, with glycoalkynes and the combination of these techniques for the creation of dual-tagged proteins. Each glycosylation procedure outlined in this protocol can be achieved in half a day.     

Imaging mass spectrometry at cellular length scales

Imaging mass spectrometry (IMS) allows the direct investigation of both the identity and the spatial distribution of the molecular content directly in tissue sections, single cells and many other biological surfaces. In this protocol, we present the steps required to retrieve the molecular information from tissue sections using matrix-enhanced (ME) and metal-assisted (MetA) secondary ion mass spectrometry (SIMS) as well as matrix-assisted laser desorption/ionization (MALDI) IMS. These techniques require specific sample preparation steps directed at optimal signal intensity with minimal redistribution or modification of the sample analytes. After careful sample preparation, different IMS methods offer a unique discovery tool in, for example, the investigation of (i) drug transport and uptake, (ii) biological processing steps and (iii) biomarker distributions. To extract the relevant information from the huge datasets produced by IMS, new bioinformatics approaches have been developed. The duration of the protocol is highly dependent on sample size and technique used, but on average takes approximately 5 h.     

Protein structure prediction assisted with sparse NMR data in CASP13

CASP13 has investigated the impact of sparse NMR data on the accuracy of protein structure prediction. NOESY and ¹⁵N-¹H residual dipolar coupling data, typical of that obtained for ¹⁵N,¹³C-enriched, perdeuterated proteins up to about 40 kDa, were simulated for 11 CASP13 targets ranging in size from 80 to 326 residues. For several targets, two prediction groups generated models that are more accurate than those produced using baseline methods. Real NMR data collected for a de novo designed protein were also provided to predictors, including one data set in which only backbone resonance assignments were available. Some NMR-assisted prediction groups also did very well with these data. CASP13 also assessed whether incorporation of sparse NMR data improves the accuracy of protein structure prediction relative to nonassisted regular methods. In most cases, incorporation of sparse, noisy NMR data results in models with higher accuracy. The best NMR-assisted models were also compared with the best regular predictions of any CASP13 group for the same target. For six of 13 targets, the most accurate model provided by any NMR-assisted prediction group was more accurate than the most accurate model provided by any regular prediction group; however, for the remaining seven targets, one or more regular prediction method provided a more accurate model than even the best NMR-assisted model. These results suggest a novel approach for protein structure determination, in which advanced prediction methods are first used to generate structural models, and sparse NMR data is then used to validate and/or refine these models.     

Proteoglycan 4 deficiency protects against glucose intolerance and fatty liver disease in diet-induced obese mice

Objective

Proteoglycan 4 (Prg4) has emerged from human association studies as a possible factor contributing to weight gain, dyslipidemia and insulin resistance. In the current study, we investigated the causal role of Prg4 in controlling lipid and glucose metabolism in mice.

Design and synthesis of conformationally constrained 3-(N-alkylamino)propylphosphonic acids as potent agonists of sphingosine-1-phosphate (S1P) receptors

A series of conformationally constrained 3-(N-alkylamino)propylphosphonic acids were systematically synthesized and their activities as S1P receptor agonists were evaluated. Several pyrrolidine and cyclohexane analogs had S1P receptor profiles comparable to the acyclic lead compound, 3-(N-tetradecylamino)propylphosphonic acid (3), lowered circulating lymphocytes in mice after iv administration and were thus identified as being suitable for further investigations.     

The discovery of 3-(N-alkyl)aminopropylphosphonic acids as potent S1P receptor agonists

3-(N-Alkyl)aminopropylphosphonic acids are potent agonists of four of the five known sphingosine-1-phosphate (S1P) receptor subtypes.