Clusters of microRNAs emerge by new hairpins in existing transcripts

Genetic linkage may result in the expression of multiple products from a polycistronic transcript, under the control of a single promoter. In animals, protein-coding polycistronic transcripts are rare. However, microRNAs are frequently clustered in the genomes of animals, and these clusters are often transcribed as a single unit. The evolution of microRNA clusters has been the subject of much speculation, and a selective advantage of clusters of functionally related microRNAs is often proposed. However, the origin of microRNA clusters has not been so far explored. Here, we study the evolution of microRNA clusters in Drosophila melanogaster. We observed that the majority of microRNA clusters arose by the de novo formation of new microRNA-like hairpins in existing microRNA transcripts. Some clusters also emerged by tandem duplication of a single microRNA. Comparative genomics show that these clusters are unlikely to split or undergo rearrangements. We did not find any instances of clusters appearing by rearrangement of pre-existing microRNA genes. We propose a model for microRNA cluster evolution in which selection over one of the microRNAs in the cluster interferes with the evolution of the other linked microRNAs. Our analysis suggests that the study of microRNAs and small RNAs must consider linkage associations

Using genome-wide measurements for computational prediction of SH2–peptide interactions

Peptide-recognition modules (PRMs) are used throughout biology to mediate protein–protein interactions, and many PRMs are members of large protein domain families. Recent genome-wide measurements describe networks of peptide–PRM interactions. In these networks, very similar PRMs recognize distinct sets of peptides, raising the question of how peptide-recognition specificity is achieved using similar protein domains. The analysis of individual protein complex structures often gives answers that are not easily applicable to other members of the same PRM family. Bioinformatics-based approaches, one the other hand, may be difficult to interpret physically. Here we integrate structural information with a large, quantitative data set of SH2 domain–peptide interactions to study the physical origin of domain–peptide specificity. We develop an energy model, inspired by protein folding, based on interactions between the amino-acid positions in the domain and peptide. We use this model to successfully predict which SH2 domains and peptides interact and uncover the positions in each that are important for specificity. The energy model is general enough that it can be applied to other members of the SH2 family or to new peptides, and the cross-validation results suggest that these energy calculations will be useful for predicting binding interactions. It can also be adapted to study other PRM families, predict optimal peptides for a given SH2 domain, or study other biological interactions, e.g. protein–DNA interactions.National Institutes of Health. National Centers for Biomedical Computing (Informatics for Integrating Biology and the Bedside)National Institutes of Health (U.S.) (grant U54LM008748

Identification and expression of equine MER-derived miRNAs

MicroRNAs (miRNAs) are single-stranded, small RNAs (21-23 nucleotides) that function in gene silencing and translational inhibition via the RNA interference mechanism. Most miRNAs originate from host genomic regions, such as intergenic regions, introns, exons, and transposable elements (TEs). Here, we focused on the palindromic structure of medium reiteration frequencies (MERs), which are similar to precursor miRNAs. Five MER consensus sequences (MER5A1, MER53, MER81, MER91C, and MER117) were matched with paralogous transcripts predicted to be precursor miRNAs in the horse genome (equCab2) and located in either intergenic regions or introns. The MER5A1, MER53, and MER91C sequences obtained from RepeatMasker were matched with the eca-miR-544b, eca-miR-1302, and eca-miR-652 precursor sequences derived from Ensembl transcript database, respectively. Each precursor form was anticipated to yield two mature forms, and we confirmed miRNA expression in six different tissues (cerebrum, cerebellum, lung, spleen, adrenal gland, and duodenum) of one thoroughbred horse. MER5A1-derived miRNAs generally showed significantly higher expression in the lung than in other tissues. MER91C-derived miRNA-5p also showed significantly higher expression in the duodenum than in other tissues (cerebellum, lung, spleen, and adrenal gland). The MER117-overlapped expressed sequence tag generated polycistronic miRNAs, which showed higher expression in the duodenum than other tissues. These data indicate that horse MER transposons encode miRNAs that are expressed in several tissues and are thought to have biological functions

Evolutionary conservation of domain-domain interactions

BACKGROUND: Recently, there has been much interest in relating domain-domain interactions (DDIs) to protein-protein interactions (PPIs) and vice versa, in an attempt to understand the molecular basis of PPIs. RESULTS: Here we map structurally derived DDIs onto the cellular PPI networks of different organisms and demonstrate that there is a catalog of domain pairs that is used to mediate various interactions in the cell. We show that these DDIs occur frequently in protein complexes and that homotypic interactions (of a domain with itself) are abundant. A comparison of the repertoires of DDIs in the networks of Escherichia coli, Saccharomyces cerevisiae, Caenorhabditis elegans, Drosophila melanogaster, and Homo sapiens shows that many DDIs are evolutionarily conserved. CONCLUSION: Our results indicate that different organisms use the same 'building blocks' for PPIs, suggesting that the functionality of many domain pairs in mediating protein interactions is maintained in evolution

Cross-Regulation between Bacteria and Phages at a Posttranscriptional Level.

The study of bacteriophages (phages) and prophages has provided key insights into almost every cellular process as well as led to the discovery of unexpected new mechanisms and the development of valuable tools. This is exemplified for RNA-based regulation. For instance, the characterization and exploitation of the anti-phage CRISPR systems is revolutionizing molecular biology. Phage-encoded proteins such as the RNA binding MS2 protein, which is broadly used to isolate tagged RNAs, also have been developed as valuable tools. Hfq, the RNA chaperone protein central to the function of many base pairing small RNAs (sRNAs), was first characterized as a bacterial host factor required for Qβ phage replication. The ongoing studies of RNAs are continuing to reveal regulatory connections between infecting phages, prophages and bacteria and to provide novel insights. There are bacterial and prophage sRNAs that regulate prophage genes, which impact bacterial virulence as well as bacterial cell killing. Conversely, phage- and prophage-encoded sRNAs modulate the expression of bacterial genes modifying metabolism. An interesting subcategory of the prophage-encoded sRNAs are sponge RNAs that inhibit the activities of bacterial-encoded sRNAs. Phages also affect post-transcriptional regulation in bacteria through proteins that inhibit or alter the activities of key bacterial proteins involved in posttranscriptional regulation. However, what is most exciting about phage and prophage research, given the millions of phage-encoded genes that have not yet been characterized, is the vast potential for discovering new RNA regulators and novel mechanisms and for gaining insight into the evolution of regulatory RNAs

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

Induction of Cytoprotective Pathways Is Central to the Extension of Lifespan Conferred by Multiple Longevity Pathways

Many genetic and physiological treatments that extend lifespan also confer resistance to a variety of stressors, suggesting that cytoprotective mechanisms underpin the regulation of longevity. It has not been established, however, whether the induction of cytoprotective pathways is essential for lifespan extension or merely correlated. Using a panel of GFP-fused stress response genes, we identified the suites of cytoprotective pathways upregulated by 160 gene inactivations known to increase Caenorhabditis elegans longevity, including the mitochondrial UPR (hsp-6, hsp-60), the ER UPR (hsp-4), ROS response (sod-3, gst-4), and xenobiotic detoxification (gst-4). We then screened for other gene inactivations that disrupt the induction of these responses by xenobiotic or genetic triggers, identifying 29 gene inactivations required for cytoprotective gene expression. If cytoprotective responses contribute directly to lifespan extension, inactivation of these genes would be expected to compromise the extension of lifespan conferred by decreased insulin/IGF-1 signaling, caloric restriction, or the inhibition of mitochondrial function. We find that inactivation of 25 of 29 cytoprotection-regulatory genes shortens the extension of longevity normally induced by decreased insulin/IGF-1 signaling, disruption of mitochondrial function, or caloric restriction, without disrupting normal longevity nearly as dramatically. These data demonstrate that induction of cytoprotective pathways is central to longevity extension and identify a large set of new genetic components of the pathways that detect cellular damage and couple that detection to downstream cytoprotective effectors.National Institute on Aging (AG16636

Altered miRNA expression network in locus coeruleus of depressed suicide subjects

Norepinephrine (NE) is produced primarily by neurons in the locus coeruleus (LC). Retrograde and ultrastructural examinations reveal that the core of the LC and its surrounding region receives afferent projections from several brain areas which provide multiple neurochemical inputs to the LC with changes in LC neuronal firing, making it a highly coordinated event. Although NE and mediated signaling systems have been studied in relation to suicide and psychiatric disorders that increase the risk of suicide including depression, less is known about the corresponding changes in molecular network within LC. In this study, we examined miRNA networks in the LC of depressed suicide completers and healthy controls. Expression array revealed differential regulation of 13 miRNAs. Interaction between altered miRNAs and target genes showed dense interconnected molecular network. Functional clustering of predicated target genes yielded stress induced disorders that collectively showed the complex nature of suicidal behavior. In addition, 25 miRNAs were pairwise correlated specifically in the depressed suicide group, but not in the control group. Altogether, our study revealed for the first time the involvement of LC based dysregulated miRNA network in disrupting cellular pathways associated with suicidal behavior

Clustering and conservation patterns of human microRNAs

MicroRNAs (miRNAs) are ∼22 nt-long non-coding RNA molecules, believed to play important roles in gene regulation. We present a comprehensive analysis of the conservation and clustering patterns of known miRNAs in human. We show that human miRNA gene clustering is significantly higher than expected at random. A total of 37% of the known human miRNA genes analyzed in this study appear in clusters of two or more with pairwise chromosomal distances of at most 3000 nt. Comparison of the miRNA sequences with their homologs in four other organisms reveals a typical conservation pattern, persistent throughout the clusters. Furthermore, we show enrichment in the typical conservation patterns and other miRNA-like properties in the vicinity of known miRNA genes, compared with random genomic regions. This may imply that additional, yet unknown, miRNAs reside in these regions, consistent with the current recognition that there are overlooked miRNAs. Indeed, by comparing our predictions with cloning results and with identified miRNA genes in other mammals, we corroborate the predictions of 18 additional human miRNA genes in the vicinity of the previously known ones. Our study raises the proportion of clustered human miRNAs that are <3000 nt apart to 42%. This suggests that the clustering of miRNA genes is higher than currently acknowledged, alluding to its evolutionary and functional implications

Metallation and mismetallation of iron and manganese proteins in vitro and in vivo: the class I ribonucleotide reductases as a case study

How cells ensure correct metallation of a given protein and whether a degree of promiscuity in metal binding has evolved are largely unanswered questions. In a classic case, iron- and manganese-dependent superoxide dismutases (SODs) catalyze the disproportionation of superoxide using highly similar protein scaffolds and nearly identical active sites. However, most of these enzymes are active with only one metal, although both metals can bind in vitro and in vivo. Iron(II) and manganese(II) bind weakly to most proteins and possess similar coordination preferences. Their distinct redox properties suggest that they are unlikely to be interchangeable in biological systems except when they function in Lewis acid catalytic roles, yet recent work suggests this is not always the case. This review summarizes the diversity of ways in which iron and manganese are substituted in similar or identical protein frameworks. As models, we discuss (1) enzymes, such as epimerases, thought to use Fe[superscript II] as a Lewis acid under normal growth conditions but which switch to Mn[superscript II] under oxidative stress; (2) extradiol dioxygenases, which have been found to use both Fe[superscript II] and Mn[superscript II], the redox role of which in catalysis remains to be elucidated; (3) SODs, which use redox chemistry and are generally metal-specific; and (4) the class I ribonucleotide reductases (RNRs), which have evolved unique biosynthetic pathways to control metallation. The primary focus is the class Ib RNRs, which can catalyze formation of a stable radical on a tyrosine residue in their β2 subunits using either a di-iron or a recently characterized dimanganese cofactor. The physiological roles of enzymes that can switch between iron and manganese cofactors are discussed, as are insights obtained from the studies of many groups regarding iron and manganese homeostasis and the divergent and convergent strategies organisms use for control of protein metallation. We propose that, in many of the systems discussed, “discrimination” between metals is not performed by the protein itself, but it is instead determined by the environment in which the protein is expressed.National Institutes of Health (U.S.) (Grant GM81393