An integrated approach to epitope analysis I: Dimensional reduction, visualization and prediction of MHC binding using amino acid principal components and regression approaches

BACKGROUND: Operation of the immune system is multivariate. Reduction of the dimensionality is essential to facilitate understanding of this complex biological system. One multi-dimensional facet of the immune system is the binding of epitopes to the MHC-I and MHC-II molecules by diverse populations of individuals. Prediction of such epitope binding is critical and several immunoinformatic strategies utilizing amino acid substitution matrices have been designed to develop predictive algorithms. Contemporaneously, computational and statistical tools have evolved to handle multivariate and megavariate analysis, but these have not been systematically deployed in prediction of MHC binding. Partial least squares analysis, principal component analysis, and associated regression techniques have become the norm in handling complex datasets in many fields. Over two decades ago Wold and colleagues showed that principal components of amino acids could be used to predict peptide binding to cellular receptors. We have applied this observation to the analysis of MHC binding, and to derivation of predictive methods applicable on a whole proteome scale. RESULTS: We show that amino acid principal components and partial least squares approaches can be utilized to visualize the underlying physicochemical properties of the MHC binding domain by using commercially available software. We further show the application of amino acid principal components to develop both linear partial least squares and non-linear neural network regression prediction algorithms for MHC-I and MHC-II molecules. Several visualization options for the output aid in understanding the underlying physicochemical properties, enable confirmation of earlier work on the relative importance of certain peptide residues to MHC binding, and also provide new insights into differences among MHC molecules. We compared both the linear and non-linear MHC binding prediction tools to several predictive tools currently available on the Internet. CONCLUSIONS: As opposed to the highly constrained user-interaction paradigms of web-server approaches, local computational approaches enable interactive analysis and visualization of complex multidimensional data using robust mathematical tools. Our work shows that prediction tools such as these can be constructed on the widely available JMP(® )platform, can operate in a spreadsheet environment on a desktop computer, and are capable of handling proteome-scale analysis with high throughput

Patterns of Predicted T-Cell Epitopes Associated with Antigenic Drift in Influenza H3N2 Hemagglutinin

Antigenic drift allowing escape from neutralizing antibodies is an important feature of transmission and survival of influenza viruses in host populations. Antigenic drift has been studied in particular detail for influenza A H3N2 and well defined antigenic clusters of this virus documented. We examine how host immunogenetics contributes to determination of the antibody spectrum, and hence the immune pressure bringing about antigenic drift. Using uTOPE™ bioinformatics analysis of predicted MHC binding, based on amino acid physical property principal components, we examined the binding affinity of all 9-mer and 15-mer peptides within the hemagglutinin 1 (HA1) of 447 H3N2 virus isolates to 35 MHC-I and 14 MHC-II alleles. We provide a comprehensive map of predicted MHC-I and MHC-II binding affinity for a broad array of HLA alleles for the H3N2 influenza HA1 protein. Each HLA allele exhibited a characteristic predicted binding pattern. Cluster analysis for each HLA allele shows that patterns based on predicted MHC binding mirror those described based on antibody binding. A single amino acid mutation or position displacement can result in a marked difference in MHC binding and hence potential T-helper function. We assessed the impact of individual amino acid changes in HA1 sequences between 10 virus isolates from 1968–2002, representative of antigenic clusters, to understand the changes in MHC binding over time. Gain and loss of predicted high affinity MHC-II binding sites with cluster transitions were documented. Predicted high affinity MHC-II binding sites were adjacent to antibody binding sites. We conclude that host MHC diversity may have a major determinant role in the antigenic drift of influenza A H3N2

Comparison of bovine leukemia virus (BLV) and CMV promoter-driven reporter gene expression in BLV-infected and non-infected cells

BACKGROUND: Viral promoters are used in mammalian expression vectors because they generally have strong activity in a wide variety of cells of differing tissues and species. METHODS: The utility of the BLV LTR/promoter (BLVp) for use in mammalian expression vectors was investigated through direct comparison to the CMV promoter (CMVp). Promoter activity was measured using luciferase assays of cell lines from different tissues and species stably transduced with BLVp or CMVp driven luciferase vectors including D17, FLK, BL3.1 and primary bovine B cells. Cells were also modified through the addition of BLV Tax expression vectors and/or BLV infection as well as treatment with trichostatin A (TSA). RESULTS: Results indicate the BLV promoter, while having low basal activity compared to the CMV promoter, can be induced to high-levels of activity similar to the CMV promoter in all cells tested. Tax or BLV infection specifically enhanced BLVp activity with no effect on CMVp activity. In contrast, the non-specific activator, TSA, enhanced both BLVp and CMVp activity. CONCLUSION: Based on these data, we conclude the BLV promoter could be very useful for transgene expression in mammalian expression vectors

Actions of Calcium on Smooth Muscle a

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/72185/1/j.1749-6632.1988.tb33358.x.pd

Abnormal Properties of Milk from Transgenic Mice Expressing Bovine β-Casein under Control of the Bovine α-lactalbumin 5\u27 Flanking Region

Transgenic mice produced in this investigation contained the proximal promoter elements, the genomic coding sequence and the 3\u27 flanking region of bovine β-casein and the 5\u27 regulatory elements of bovine α-lactalbumin. Specifically, the gene construct included the TATAA box, CAAT box and polyadenylation signal of bovine β-casein in addition to the 5\u27 regulatory elements of the bovine α-lactalbumin gene. Four lines of transgenic mice were generated; they expressed bovine β-casein in their milk at concentrations of up to 10 mg mL-1. The milk from the transgenic mice tended to be very viscous and a proportion of these mice stopped lactating before the normal onset of involution. The time at which the abrupt involution occurred was directly correlated to the amount of β-casein produced. Mice secreting approximately 10 mg mL-1 of β-casein in their milk stopped lactating approximately 1-3 days after parturition while mice expressing 1-3 mg mL-1 stopped lactating around days 10-18. The high expressing mice appeared to lactate normally on day 1 of lactation, but on day 3 the mammary gland morphology revealed alveoli and ducts which were very distended and contained milk components. However, the viscous milk solution could not be removed from the gland at this stage of lactation. There were also a number of alveoli that appeared to have gone through the process of involution by day 3 of lactation

Extensive T-cell epitope repertoire sharing among human proteome, gastrointestinal microbiome, and pathogenic bacteria: Implications for the definition of self.

T-cell receptor binding to MHC-bound peptides plays a key role in discrimination between self and non-self. Only a subset, typically a pentamer, of amino acids in a MHC bound peptide form the motif exposed to the T-cell receptor. We categorize and compare the T-cell exposed amino acid motif repertoire of the total proteomes of two groups of bacteria, comprising pathogens and gastrointestinal microbiome organisms, with the human proteome and immunoglobulins. Given the maximum 205, or 3.2 million of such motifs that bind T-cell receptors, there is considerable overlap in motif usage. We show that the human proteome, exclusive of immunoglobulins, only comprises three quarters of the possible motifs, of which 65.3% are also present in both composite bacterial proteomes. Very few motifs are unique to the human proteome. Immunoglobulin variable regions carry a broad diversity of T cell exposed motifs that provides a stratified random sample of the motifs found in pathogens, microbiome and the human proteome. Individual bacterial genera and species vary in the content of immunoglobulin and human proteome matched motifs that they carry. Mycobacteria and Burkholderia spp carry a particularly high content of such matched motifs. Some bacteria retain a unique motif signature and motif sharing pattern with the human proteome. The implication is that distinguishing self from non self does not depend on individual T-cell exposed motifs, but on a complex and dynamic overlay of signals wherein the same T-cell exposed motif may play different roles in different organisms, and the frequency with which a particular TCEM appears influences its effect. The patterns observed provide clues to bacterial immune evasion and to strategies for intervention, including vaccine design. The breadth and distinct frequency patterns of the immunoglobulin derived peptides suggest a role of immunoglobulins in maintaining a broadly responsive T-cell repertoire

Frequency patterns of T-cell exposed motifs in immunoglobulin heavy chain peptides presented by MHCs

Immunoglobulins are highly diverse protein sequences that are processed and presented to T-cells by B-cells and other antigen presenting cells. We examined a large dataset of immunoglobulin heavy chain variable regions (IGHV) to assess the diversity of T-cell exposed motifs (TCEM). TCEM comprise those amino acids in a MHC-bound peptide which face outwards, surrounded by the MHC histotope, and which engage the T-cell receptor. Within IGHV there is a distinct pattern of predicted MHC class II binding and a very high frequency of re-use of the TCEMs. The re-use frequency indicates that only a limited number of different cognate T-cells are required to engage many different clonal B-cells. The amino acids in each outward-facing TCEM are intercalated with the amino acids of inward-facing MHC groove-exposed motifs (GEM). Different GEM may have differing, allele-specific, MHC binding affinities. The intercalation of TCEM and GEM in a peptide allows for a vast combinatorial repertoire of epitopes, each eliciting a different response. Outcome of T-cell receptor binding is determined by overall signal strength, which is a function of the number of responding T-cells and the duration of engagement. Hence, the frequency of T-cell exposed motif re-use appears to be an important determinant of whether a T-cell response is stimulatory or suppressive. The frequency distribution of TCEMs implies that somatic hypermutation is followed by clonal expansion that develop along repeated pathways. The observations of TCEM and GEM derived from immunoglobulins suggest a relatively simple, yet powerful, mechanism to correlate T-cell polyspecificity, through re-use of TCEMs, with a very high degree of specificity achieved by combination with a diversity of GEMs. The frequency profile of TCEMs also points to an economical mechanism for maintaining T-cell memory, recall, and self-discrimination based on an endogenously generated profile of motifs