Limitations of Ab Initio Predictions of Peptide Binding to MHC Class II Molecules

Successful predictions of peptide MHC binding typically require a large set of binding data for the specific MHC molecule that is examined. Structure based prediction methods promise to circumvent this requirement by evaluating the physical contacts a peptide can make with an MHC molecule based on the highly conserved 3D structure of peptide:MHC complexes. While several such methods have been described before, most are not publicly available and have not been independently tested for their performance. We here implemented and evaluated three prediction methods for MHC class II molecules: statistical potentials derived from the analysis of known protein structures; energetic evaluation of different peptide snapshots in a molecular dynamics simulation; and direct analysis of contacts made in known 3D structures of peptide:MHC complexes. These methods are ab initio in that they require structural data of the MHC molecule examined, but no specific peptide:MHC binding data. Moreover, these methods retain the ability to make predictions in a sufficiently short time scale to be useful in a real world application, such as screening a whole proteome for candidate binding peptides. A rigorous evaluation of each methods prediction performance showed that these are significantly better than random, but still substantially lower than the best performing sequence based class II prediction methods available. While the approaches presented here were developed independently, we have chosen to present our results together in order to support the notion that generating structure based predictions of peptide:MHC binding without using binding data is unlikely to give satisfactory results

Genome-wide comparative analysis of microRNAs in three non-human primates

Abstract Background MicroRNAs (miRNAs) are negative regulators of gene expression in multicellular eukaryotes. With the recently completed sequencing of three primate genomes, the study of miRNA evolution within the primate lineage has only begun and may be expected to provide the genetic and molecular explanations for many phenotypic differences between human and non-human primates. Findings We scanned all three genomes of non-human primates, including chimpanzee (Pan troglodytes), orangutan (Pongo pygmaeus), and rhesus monkey (Macaca mulatta), for homologs of human miRNA genes. Besides sequence homology analysis, our comparative method relies on various postprocessing filters to verify other features of miRNAs, including, in particular, their precursor structure or their occurrence (prediction) in other primate genomes. Our study allows direct comparisons between the different species in terms of their miRNA repertoire, their evolutionary distance to human, the effects of filters, as well as the identification of common and species-specific miRNAs in the primate lineage. More than 500 novel putative miRNA genes have been discovered in orangutan that show at least 85 percent identity in precursor sequence. Only about 40 percent are found to be 100 percent identical with their human ortholog. Conclusion Homologs of human precursor miRNAs with perfect or near-perfect sequence identity may be considered to be likely functional in other primates. The computational identification of homologs with less similar sequence, instead, requires further evidence to be provided.</p

Ab initio identification of human microRNAs based on structure motifs

<p>Abstract</p> <p>Background</p> <p>MicroRNAs (miRNAs) are short, non-coding RNA molecules that are directly involved in post-transcriptional regulation of gene expression. The mature miRNA sequence binds to more or less specific target sites on the mRNA. Both their small size and sequence specificity make the detection of completely new miRNAs a challenging task. This cannot be based on sequence information alone, but requires structure information about the miRNA precursor. Unlike comparative genomics approaches, <it>ab initio </it>approaches are able to discover species-specific miRNAs without known sequence homology.</p> <p>Results</p> <p>MiRPred is a novel method for <it>ab initio </it>prediction of miRNAs by genome scanning that only relies on (predicted) secondary structure to distinguish miRNA precursors from other similar-sized segments of the human genome. We apply a machine learning technique, called linear genetic programming, to develop special classifier programs which include multiple regular expressions (motifs) matched against the secondary structure sequence. Special attention is paid to scanning issues. The classifiers are trained on fixed-length sequences as these occur when shifting a window in regular steps over a genome region. Various statistical and empirical evidence is collected to validate the correctness of and increase confidence in the predicted structures. Among other things, we propose a new criterion to select miRNA candidates with a higher stability of folding that is based on the number of matching windows around their genome location. An ensemble of 16 motif-based classifiers achieves 99.9 percent specificity with sensitivity remaining on an acceptable high level when requiring all classifiers to agree on a positive decision. A low false positive rate is considered more important than a low false negative rate, when searching larger genome regions for unknown miRNAs. 117 new miRNAs have been predicted close to known miRNAs on human chromosome 19. All candidate structures match the free energy distribution of miRNA precursors which is significantly shifted towards lower free energies. We employed a human EST library and found that around 75 percent of the candidate sequences are likely to be transcribed, with around 35 percent located in introns.</p> <p>Conclusion</p> <p>Our motif finding method is at least competitive to state-of-the-art feature-based methods for <it>ab initio </it>miRNA discovery. In doing so, it requires less previous knowledge about miRNA precursor structures while programs and motifs allow a more straightforward interpretation and extraction of the acquired knowledge.</p

Phage Lambda CIII: A Protease Inhibitor Regulating the Lysis-Lysogeny Decision

The ATP-dependent protease FtsH (HflB) complexed with HflKC participates in post-translational control of the lysis-lysogeny decision of bacteriophage lambda by rapid degradation of lambda CII. Both phage-encoded proteins, the CII transcription activator and the CIII polypeptide, are required for efficient lysogenic response. The conserved CIII is both an inhibitor and substrate of FtsH. Here we show that the protease inhibitor CIII is present as oligomeric amphipathic α helical structures and functions as a competitive inhibitor of FtsH by preventing binding of the CII substrate. We identified single alanine substitutions in CIII that abolish its activity. We characterize a dominant negative effect of a CIII mutant. Thus, we suggest that CIII oligomrization is required for its function. Real-time analysis of CII activity demonstrates that the effect of CIII is not seen in the absence of either FtsH or HflKC. When CIII is provided ectopically, CII activity increases linearly as a function of the multiplicity of infection, suggesting that CIII enhances CII stability and the lysogenic response. FtsH function is essential for cellular viability as it regulates the balance in the synthesis of phospholipids and lipopolysaccharides. Genetic experiments confirmed that the CIII bacteriostatic effects are due to inhibition of FtsH. Thus, the early presence of CIII following infection stimulates the lysogenic response, while its degradation at later times ensures the reactivation of FtsH allowing the growth of the established lysogenic cell

Analysis of Pools of Targeted Salmonella Deletion Mutants Identifies Novel Genes Affecting Fitness during Competitive Infection in Mice

Pools of mutants of minimal complexity but maximal coverage of genes of interest facilitate screening for genes under selection in a particular environment. We constructed individual deletion mutants in 1,023 Salmonella enterica serovar Typhimurium genes, including almost all genes found in Salmonella but not in related genera. All mutations were confirmed simultaneously using a novel amplification strategy to produce labeled RNA from a T7 RNA polymerase promoter, introduced during the construction of each mutant, followed by hybridization of this labeled RNA to a Typhimurium genome tiling array. To demonstrate the ability to identify fitness phenotypes using our pool of mutants, the pool was subjected to selection by intraperitoneal injection into BALB/c mice and subsequent recovery from spleens. Changes in the representation of each mutant were monitored using T7 transcripts hybridized to a novel inexpensive minimal microarray. Among the top 120 statistically significant spleen colonization phenotypes, more than 40 were mutations in genes with no previously known role in this model. Fifteen phenotypes were tested using individual mutants in competitive assays of intraperitoneal infection in mice and eleven were confirmed, including the first two examples of attenuation for sRNA mutants in Salmonella. We refer to the method as Array-based analysis of cistrons under selection (ABACUS)

Homologs of the small RNA SgrS are broadly distributed in enteric bacteria but have diverged in size and sequence

Sugar phosphate stress in Escherichia coli is sensed and managed by the transcriptional regulator SgrR and the small RNA (sRNA) SgrS. SgrS is a dual function RNA that performs base pairing-dependent regulation of mRNA targets and encodes a small protein, SgrT. Homologs of SgrR were analyzed for gene synteny and inter-homolog identity to identify those that are likely to be functionally analogous. These 22 SgrR homologs were used to manually locate adjacent sRNAs functionally analogous to SgrS. SgrS homologs shared little sequence identity with E. coli SgrS, but most shared several structural features. The most conserved feature of SgrS homologs was the base pairing region while the most variable feature was the sgrT-coding sequence. Analyses of predicted interactions between SgrS:ptsG mRNA pairs in different organisms revealed interesting differences in the patterns of base pairing interactions. RNA pairs with more interrupted regions of complementarity had a higher proportion of G:C base pairs than those with longer contiguous stretches of complementarity. The identification of this set of homologous sRNAs and their targets sets the stage for future studies to further elucidate the molecular requirements for regulation by SgrS

Cytomegalovirus microRNAs Facilitate Persistent Virus Infection in Salivary Glands

Micro (mi)RNAs are small non-coding RNAs that regulate the expression of their targets' messenger RNAs through both translational inhibition and regulation of target RNA stability. Recently, a number of viruses, particularly of the herpesvirus family, have been shown to express their own miRNAs to control both viral and cellular transcripts. Although some targets of viral miRNAs are known, their function in a physiologically relevant infection remains to be elucidated. As such, no in vivo phenotype of a viral miRNA knock-out mutant has been described so far. Here, we report on the first functional phenotype of a miRNA knock-out virus in vivo. During subacute infection of a mutant mouse cytomegalovirus lacking two viral miRNAs, virus production is selectively reduced in salivary glands, an organ essential for virus persistence and horizontal transmission. This phenotype depends on several parameters including viral load and mouse genetic background, and is abolished by combined but not single depletion of natural killer (NK) and CD4+ T cells. Together, our results point towards a miRNA-based immunoevasion mechanism important for long-term virus persistence

Proteomic analysis of Salmonella enterica serovar Enteritidis following propionate adaptation

<p>Abstract</p> <p>Background</p> <p><it>Salmonella </it>Enteritidis is a highly prevalent and persistent foodborne pathogen and is therefore a leading cause of nontyphoidal gastrointestinal disease worldwide. A variety of stresses are endured throughout its infection cycle, including high concentrations of propionate (PA) within food processing systems and within the gut of infected hosts. Prolonged PA exposure experienced in such milieus may have a drastic effect on the proteome of <it>Salmonella </it>Enteritidis subjected to this stress.</p> <p>Results</p> <p>In this study, we used 2 D gel electrophoresis to examine the proteomes of PA adapted and unadapted <it>S</it>. Enteritidis and have identified five proteins that are upregulated in PA adapted cultures using standard peptide mass fingerprinting by MALDI-TOF-MS and sequencing by MALDI LIFT-TOF/TOF tandem mass spectrometry. Of these five, two significant stress-related proteins (Dps and CpxR) were shown (via qRT-PCR analysis) to be upregulated at the transcriptional level as well. Unlike the wild type when adapted to PA (which demonstrates significant acid resistance), PA adapted <it>S</it>. Enteritidis ∆<it>dps </it>and <it>S</it>. Enteritidis ∆<it>cpxR </it>were at a clear disadvantage when challenged to a highly acidic environment. However, we found the acid resistance to be fully restorable after genetic complementation.</p> <p>Conclusions</p> <p>This work reveals a significant difference in the proteomes of PA adapted and unadapted <it>S</it>. Enteritidis and affirms the contribution of Dps and CpxR in PA induced acid resistance.</p

Identification and Characterization of MicroRNAs in Asiatic Cotton (Gossypium arboreum L.)

To date, no miRNAs have been identified in the important diploid cotton species although there are several reports on miRNAs in upland cotton. In this study, we identified 73 miRNAs, belonging to 49 families, from Asiatic cotton using a well-developed comparative genome-based homologue search. Several of the predicted miRNAs were validated using quantitative real time PCR (qRT-PCR). The length of miRNAs varied from 18 to 22 nt with an average of 20 nt. The length of miRNA precursors also varied from 46 to 684 nt with an average of 138 ±120 nt. For a majority of Asiatic cotton miRNAs, there is only one member per family; however, multiple members were identified for miRNA 156, 414, 837, 838, 1044, 1533, 2902, 2868, 5021 and 5142 families. Nucleotides A and U were dominant, accounted for 62.95%, in the Asiatic cotton pre-miRNAs. The Asiatic cotton pre-miRNAs had high negative minimal folding free energy (MFE) and adjusted MFE (AMFE) and high MFE index (MFEI). Many miRNAs identified in Asiatic cotton suggest that miRNAs also play a similar regulatory mechanism in diploid cotton

Large-scale validation of methods for cytotoxic T-lymphocyte epitope prediction

<p>Abstract</p> <p>Background</p> <p>Reliable predictions of Cytotoxic T lymphocyte (CTL) epitopes are essential for rational vaccine design. Most importantly, they can minimize the experimental effort needed to identify epitopes. NetCTL is a web-based tool designed for predicting human CTL epitopes in any given protein. It does so by integrating predictions of proteasomal cleavage, TAP transport efficiency, and MHC class I affinity. At least four other methods have been developed recently that likewise attempt to predict CTL epitopes: EpiJen, MAPPP, MHC-pathway, and WAPP. In order to compare the performance of prediction methods, objective benchmarks and standardized performance measures are needed. Here, we develop such large-scale benchmark and corresponding performance measures and report the performance of an updated version 1.2 of NetCTL in comparison with the four other methods.</p> <p>Results</p> <p>We define a number of performance measures that can handle the different types of output data from the five methods. We use two evaluation datasets consisting of known HIV CTL epitopes and their source proteins. The source proteins are split into all possible 9 mers and except for annotated epitopes; all other 9 mers are considered non-epitopes. In the RANK measure, we compare two methods at a time and count how often each of the methods rank the epitope highest. In another measure, we find the specificity of the methods at three predefined sensitivity values. Lastly, for each method, we calculate the percentage of known epitopes that rank within the 5% peptides with the highest predicted score.</p> <p>Conclusion</p> <p>NetCTL-1.2 is demonstrated to have a higher predictive performance than EpiJen, MAPPP, MHC-pathway, and WAPP on all performance measures. The higher performance of NetCTL-1.2 as compared to EpiJen and MHC-pathway is, however, not statistically significant on all measures. In the large-scale benchmark calculation consisting of 216 known HIV epitopes covering all 12 recognized HLA supertypes, the NetCTL-1.2 method was shown to have a sensitivity among the 5% top-scoring peptides above 0.72. On this dataset, the best of the other methods achieved a sensitivity of 0.64. The NetCTL-1.2 method is available at <url>http://www.cbs.dtu.dk/services/NetCTL</url>.</p> <p>All used datasets are available at <url>http://www.cbs.dtu.dk/suppl/immunology/CTL-1.2.php</url>.</p