Adaptive evolution after duplication of penaeidin antimicrobial peptides

Penaeidin antimicrobial peptides in penaeid shrimps are an important component of their innate immune system that provides immunity against infection caused by several gram-positive bacteria and filamentous fungal species. Despite the knowledge on the identification and characterization of these peptides in penaeid shrimps, little is known about the evolutionary pattern of these peptides and the underlying genetic mechanisms that maintain high sequence diversities in the penaeidin gene family. Based on the phylogenetic analyses and maximum likelihood-based codon substitution analyses, here we present the convincing evidence that multiple copies of penaeidins have evolved by gene duplication, and positive Darwinian selection (adaptive evolution) is the likely cause of accelerated rate of amino acid substitutions among these duplicated genes. While the average ratio of non-synonymous to synonymous substitutions (omega) for the entire coding region of both active domains is 0.9805, few codon sites showed significantly higher omega (3.73). The likelihood ratio tests that compare models incorporating positive selection (omega>1) at certain codon sites with models not incorporating positive selection (omega<1), failed to reject (p=0) the evidence of positive Darwinian selection. The rapid adaptive evolution of this gene family might be directed by the pathogens and the faster rate of amino acid substitutions in the N-terminal proline-rich and C-terminal cysteine-rich domains could be due to their direct involvement in the protection against pathogens. When the host expose to different habitats/environment an accelerated rate of amino acid substitutions in both the active domains may also be expected.     

Adaptive evolution of crustin antimicrobial peptides in decapods

Antimicrobial peptides (AMPs) are present in a wide range of taxonomic groups and played a crucial role in host adaptation to a diverse array of ever-changing pathogens. Crustin, a cysteine-rich cationic AMP, is known to exhibit antimicrobial activity against Gram-positive and Gram-negative bacteria in decapods. Given their important role in host-immune defense, a large proportion of amino acid substitutions in crustin AMPs are expected to be fixed by natural selection. Utilizing the complete coding nucleotide sequence data of crustin, the present study revealed the pervasive role of positive Darwinian selection in the evolution and divergence of crustin AMPs in decapods. Approximately, 20–35?% of codons in two phylogenetically distinct groups of closely related crustins in Penaeid shrimps are shown to have evolved under positive selection. Interestingly, several of these positively selected sites are located at the carboxyl-terminal region, the region that directly interacts with the invading pathogens. Pathogen-mediated selection pressure could be the likely cause for such an accelerated rate of amino acid substitutions and could have contributed to the structural and functional diversification of crustin AMPs in several taxa.     

The evolution of antifungal peptides in Drosophila

An essential component of the immune system of animals is the production of antimicrobial peptides (AMPs). In vertebrates and termites the protein sequence of some AMPs evolves rapidly under positive selection, suggesting that they may be coevolving with pathogens. However, antibacterial peptides in Drosophila tend to be highly conserved. We have inferred the selection pressures acting on Drosophila antifungal peptides (drosomycins) from both the divergence of drosomycin genes within and between five species of Drosophila and polymorphism data from Drosophila simulans and D. melanogaster. In common with Drosophila antibacterial peptides, there is no evidence of adaptive protein evolution in any of the drosomycin genes, suggesting that they do not coevolve with pathogens. It is possible that this reflects a lack of specific fungal and bacterial parasites in Drosophila populations. The polymorphism data from both species differed from neutrality at one locus, but this was not associated with changes in the protein sequence. The synonymous site diversity was greater in D. simulans than in D. melanogaster, but the diversity both upstream of the genes and at nonsynonymous sites was similar. This can be explained if both upstream and nonsynonymous mutations are slightly deleterious and are removed more effectively from D. simulans due to its larger effective population size.     

Modification of chicken avian β-defensin-8 at positively selected amino acid sites enhances specific antimicrobial activity

Antimicrobial peptides (AMPs), essential components of innate immunity, are found in a range of phylogenetically diverse species and are thought to act by disrupting the membrane integrity of microbes. In this paper, we used evolutionary signatures to identify sites that are most relevant during the functional evolution of these molecules and introduced amino acid substitutions to improve activity. We first demonstrate that the anti-microbial activity of chicken avian β-defensin-8, previously known as gallinacin-12, can be significantly increased against Escherichia coli, Listeria monocytogenes, Salmonella typhimurium, Salmonella typhimurium phoP− mutant and Streptococcus pyogenes through targeted amino acid substitutions, which confer increased peptide charge. However, by increasing the AMP charge through amino acid substitutions at sites predicted to be subject to positive selection, antimicrobial activity against Escherichia coli was further increased. In contrast, no further increase in activity was observed against the remaining pathogens. This result suggests that charge-increasing modifications confer increased broad-spectrum activity to an AMP, whilst positive selection at particular sites is involved in directing the antimicrobial response against specific pathogens. Thus, there is potential for the rational design of novel therapeutics based on specifically targeted and modified AMPs. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorised users.     

Positive Darwinian selection on crustacean hyperglycemic hormone (CHH) of the green shore crab, Carcinus maenas

The tissue-specific expression and differential function of the crustacean hyperglycemic hormone (CHH) in Carcinus maenas indicate an interesting evolutionary history. Previous studies have shown that CHH from the sinus gland X-organ (XO-type) has hyperglycemic activity, whereas the CHH from the pericardial organ (PO-type) neither shows hyperglycemic activity nor it inhibits Y-organ ecdysteroid synthesis. Here we examined the types of selective pressures operating on the variants of CHH in Carcinus maenas. Maximum likelihood-based codon substitution analyses revealed that the variants of this neuropeptide in C. maenas have been subjected to positive Darwinian selection indicating adaptive evolution and functional divergence among the CHH variants leading to two unique groups (PO and XO-type). Although the average ratio of nonsynonymous to synonymous substitution (omega) for the entire coding region is 0.5096, few codon sites showed significantly higher omega (10.95). Comparison of models that incorporate positive selection (omega > 1) with models not incorporating positive selection (omega <1) at certain codon sites failed to reject (p=0) evidence of positive Darwinian selection.     

Codon-substitution models for heterogeneous selection pressure at amino acid sites

Comparison of relative fixation rates of synonymous (silent) and nonsynonymous (amino acid-altering) mutations provides a means for understanding the mechanisms of molecular sequence evolution. The nonsynonymous/synonymous rate ratio (omega = d(N)d(S)) is an important indicator of selective pressure at the protein level, with omega = 1 meaning neutral mutations, omega < 1 purifying selection, and omega > 1 diversifying positive selection. Amino acid sites in a protein are expected to be under different selective pressures and have different underlying omega ratios. We develop models that account for heterogeneous omega ratios among amino acid sites and apply them to phylogenetic analyses of protein-coding DNA sequences. These models are useful for testing for adaptive molecular evolution and identifying amino acid sites under diversifying selection. Ten data sets of genes from nuclear, mitochondrial, and viral genomes are analyzed to estimate the distributions of omega among sites. In all data sets analyzed, the selective pressure indicated by the omega ratio is found to be highly heterogeneous among sites. Previously unsuspected Darwinian selection is detected in several genes in which the average omega ratio across sites is <1, but in which some sites are clearly under diversifying selection with omega > 1. Genes undergoing positive selection include the beta-globin gene from vertebrates, mitochondrial protein-coding genes from hominoids, the hemagglutinin (HA) gene from human influenza virus A, and HIV-1 env, vif, and pol genes. Tests for the presence of positively selected sites and their subsequent identification appear quite robust to the specific distributional form assumed for omega and can be achieved using any of several models we implement. However, we encountered difficulties in estimating the precise distribution of omega among sites from real data sets.     

Unique Pathogen Peptidomes Facilitate Pathogen-Specific Selection and Specialization of MHC Alleles

A key component of pathogen-specific adaptive immunity in vertebrates is the presentation of pathogen-derived antigenic peptides by major histocompatibility complex (MHC) molecules. The excessive polymorphism observed at MHC genes is widely presumed to result from the need to recognize diverse pathogens, a process called pathogen-driven balancing selection. This process assumes that pathogens differ in their peptidomes—the pool of short peptides derived from the pathogen’s proteome—so that different pathogens select for different MHC variants with distinct peptide-binding properties. Here, we tested this assumption in a comprehensive data set of 51.9 Mio peptides, derived from the peptidomes of 36 representative human pathogens. Strikingly, we found that 39.7% of the 630 pairwise comparisons among pathogens yielded not a single shared peptide and only 1.8% of pathogen pairs shared more than 1% of their peptides. Indeed, 98.8% of all peptides were unique to a single pathogen species. Using computational binding prediction to characterize the binding specificities of 321 common human MHC class-I variants, we investigated quantitative differences among MHC variants with regard to binding peptides from distinct pathogens. Our analysis showed signatures of specialization toward specific pathogens especially by MHC variants with narrow peptide-binding repertoires. This supports the hypothesis that such fastidious MHC variants might be maintained in the population because they provide an advantage against particular pathogens. Overall, our results establish a key selection factor for the excessive allelic diversity at MHC genes observed in natural populations and illuminate the evolution of variable peptide-binding repertoires among MHC variants.     

Genomic organization, molecular diversification, and evolution of antimicrobial peptide myticin-C genes in the mussel (Mytilus galloprovincialis)

Myticin-C is a highly variable antimicrobial peptide associated to immune response in Mediterranean mussel (Mytilus galloprovincialis). In this study, we tried to ascertain the genetic organization and the mechanisms underlying myticin-C variation and evolution of this gene family. We took advantage of the large intron size variation to find out the number of myticin-C genes. Using fragment analysis a maximum of four alleles was detected per individual at both introns in a large mussel sample suggesting a minimum of two myticin-C genes. The transmission pattern of size variants in two full-sib families was also used to ascertain the number of myticin-C genes underlying the variability observed. Results in both families were in accordance with two myticin-C genes organized in tandem. A more detailed analysis of myticin-C variation was carried out by sequencing a large sample of complementary (cDNA) and genomic DNA (gDNA) in 10 individuals. Two basic sequences were detected at most individuals and several sequences were constituted by combination of two different basic sequences, strongly suggesting somatic recombination or gene conversion. Slight within-basic sequence variation detected in all individuals was attributed to somatic mutation. Such mutations were more frequently at the C-terminal domain and mostly determined non-synonymous substitutions. The mature peptide domain showed the highest variation both in the whole cDNA and in the basic-sequence samples, which is in accordance with the pathogen recognition function associated to this domain. Although most tests suggested neutrality for myticin-C variation, evidence indicated positive selection in the mature peptide and C-terminal region. Three main highly supported clusters were observed when reconstructing phylogeny on basic sequences, meiotic recombination playing a relevant role on myticin-C evolution. This study demonstrates that mechanisms to generate molecular variation similar to that observed in vertebrates are also operating in molluscs.     

Diversifying selection in human papillomavirus type 16 lineages based on complete genome analyses

Human papillomavirus type 16 (HPV16) is the primary etiological agent of cervical cancer, the second most common cancer in women worldwide. Complete genomes of 12 isolates representing the major lineages of HPV16 were cloned and sequenced from cervicovaginal cells. The sequence variations within the open reading frames (ORFs) and noncoding regions were identified and compared with the HPV16R reference sequence. This whole-genome approach gives us unprecedented precision in detailing sequence-level changes that are under selection on a whole-viral-genome scale. Of 7,908 base pair nucleotide positions, 313 (4.0%) were variable. Within the 2,452 amino acids (aa) comprising 8 ORFs, 243 (9.9%) amino acid positions were variable. In order to investigate the molecular evolution of HPV16 variants, maximum likelihood models of codon substitution were used to identify lineages and amino acid sites under selective pressure. Five codon sites in the E5 (aa 48, 65) and E6 (aa 10, 14, 83) ORFs were demonstrated to be under diversifying selective pressure. The E5 ORF had the overall highest nonsynonymous/synonymous substitution rate (omega) ratio (M3 = 0.7965). The E2 gene had the next-highest omega ratio (M3 = 0.5611); however, no specific codons were under positive selection. These data indicate that the E6 and E5 ORFs are evolving under positive Darwinian selection and have done so in a relatively short time period. Whether response to selective pressure upon the E5 and E6 ORFs contributes to the biological success of HPV16, its specific biological niche, and/or its oncogenic potential remains to be established.     

Codon-substitution models for detecting molecular adaptation at individual sites along specific lineages

The nonsynonymous (amino acid-altering) to synonymous (silent) substitution rate ratio (omega = d(N)/d(S)) provides a measure of natural selection at the protein level, with omega = 1, >1, and <1, indicating neutral evolution, purifying selection, and positive selection, respectively. Previous studies that used this measure to detect positive selection have often taken an approach of pairwise comparison, estimating substitution rates by averaging over all sites in the protein. As most amino acids in a functional protein are under structural and functional constraints and adaptive evolution probably affects only a few sites at a few time points, this approach of averaging rates over sites and over time has little power. Previously, we developed codon-based substitution models that allow the omega ratio to vary either among lineages or among sites. In this paper we extend previous models to allow the omega ratio to vary both among sites and among lineages and implement the new models in the likelihood framework. These models may be useful for identifying positive selection along prespecified lineages that affects only a few sites in the protein. We apply those branch-site models as well as previous branch- and site-specific models to three data sets: the lysozyme genes from primates, the tumor suppressor BRCA1 genes from primates, and the phytochrome (PHY) gene family in angiosperms. Positive selection is detected in the lysozyme and BRCA genes by both the new and the old models. However, only the new models detected positive selection acting on lineages after gene duplication in the PHY gene family. Additional tests on several data sets suggest that the new models may be useful in detecting positive selection after gene duplication in gene family evolution.     

Selection on rapidly evolving proteins in the Arabidopsis genome

Genes that have undergone positive or diversifying selection are likely to be associated with adaptive divergence between species. One indicator of adaptive selection at the molecular level is an excess of amino acid replacement fixed differences per replacement site relative to the number of synonymous fixed differences per synonymous site (omega = K(a)/K(s)). We used an evolutionary expressed sequence tag (EST) approach to estimate the distribution of omega among 304 orthologous loci between Arabidopsis thaliana and A. lyrata to identify genes potentially involved in the adaptive divergence between these two Brassicaceae species. We find that 14 of 304 genes (approximately 5%) have an estimated omega > 1 and are candidates for genes with increased selection intensities. Molecular population genetic analyses of 6 of these rapidly evolving protein loci indicate that, despite their high levels of between-species nonsynonymous divergence, these genes do not have elevated levels of intraspecific replacement polymorphisms compared to previously studied genes. A hierarchical Bayesian analysis of protein-coding region evolution within and between species also indicates that the selection intensities of these genes are elevated compared to previously studied A. thaliana nuclear loci.     

Whole genome sequencing and evolutionary analysis of human papillomavirus type 16 in central China

Human papillomavirus type 16 plays a critical role in the neoplastic transformation of cervical cancers. Molecular variants of HPV16 existing in different ethnic groups have shown substantial phenotypic differences in pathogenicity, immunogenicity and tumorigenicity. In this study, we sequenced the entire HPV16 genome of 76 isolates originated from Anyang, central China. Phylogenetic analysis of these sequences identified two major variants of HPV16 in the Anyang area, namely the European prototype (E(p)) and the European Asian type (E(As)). These two variants show a high degree of divergence between groups, and the E(p) comprised higher genetic diversity than the E(As). Analysis with two measurements of genetic diversity indicated that viral population size was relatively stable in this area in the past. Codon based likelihood models revealed strong statistical support for adaptive evolution acting on the E6 gene. Bayesian analysis identified several important amino acid positions that may be driving adaptive selection in the HPV 16 population, including R10G, D25E, L83V, and E113D in the E6 gene. We hypothesize that the positive selection at these codons might be a contributing factor responsible for the phenotypic differences in carcinogenesis and immunogenicity among cervical cancers in China based on the potential roles of these molecular variants reported in other studies.     

Likelihood-based clustering (LiBaC) for codon models, a method for grouping sites according to similarities in the underlying process of evolution

Models of codon evolution are useful for investigating the strength and direction of natural selection via a parameter for the nonsynonymous/synonymous rate ratio (omega = d(N)/d(S)). Different codon models are available to account for diversity of the evolutionary patterns among sites. Codon models that specify data partitions as fixed effects allow the most evolutionary diversity among sites but require that site partitions are a priori identifiable. Models that use a parametric distribution to express the variability in the omega ratio across site do not require a priori partitioning of sites, but they permit less among-site diversity in the evolutionary process. Simulation studies presented in this paper indicate that differences among sites in estimates of omega under an overly simplistic analytical model can reflect more than just natural selection pressure. We also find that the classic likelihood ratio tests for positive selection have a high false-positive rate in some situations. In this paper, we developed a new method for assigning codon sites into groups where each group has a different model, and the likelihood over all sites is maximized. The method, called likelihood-based clustering (LiBaC), can be viewed as a generalization of the family of model-based clustering approaches to models of codon evolution. We report the performance of several LiBaC-based methods, and selected alternative methods, over a wide variety of scenarios. We find that LiBaC, under an appropriate model, can provide reliable parameter estimates when the process of evolution is very heterogeneous among groups of sites. Certain types of proteins, such as transmembrane proteins, are expected to exhibit such heterogeneity. A survey of genes encoding transmembrane proteins suggests that overly simplistic models could be leading to false signal for positive selection among such genes. In these cases, LiBaC-based methods offer an important addition to a "toolbox" of methods thereby helping to uncover robust evidence for the action of positive selection.     

The evolution of biased codon and amino acid usage in nematode genomes

Despite the degeneracy of the genetic code, whereby different codons encode the same amino acid, alternative codons and amino acids are utilized nonrandomly within and between genomes. Such biases in codon and amino acid usage have been demonstrated extensively in prokaryote genomes and likely reflect a balance between the action of mutation, selection, and genetic drift. Here, we quantify the effects of selection and mutation drift as causes of codon and amino acid-usage bias in a large collection of nematode partial genomes from 37 species spanning approximately 700 Myr of evolution, as inferred from expressed sequence tag (EST) measures of gene expression and from base composition variation. Average G + C content at silent sites among these taxa ranges from 10% to 63%, and EST counts range more than 100-fold, underlying marked differences between the identities of major codons and optimal codons for a given species as well as influencing patterns of amino acid abundance among taxa. Few species in our sample demonstrate a dominant role of selection in shaping intragenomic codon-usage biases, and these are principally free living rather than parasitic nematodes. This suggests that deviations in effective population size among species, with small effective sizes among parasites, are partly responsible for species differences in the extent to which selection shapes patterns of codon usage. Nevertheless, a consensus set of optimal codons emerges that is common to most taxa, indicating that, with some notable exceptions, selection for translational efficiency and accuracy favors similar sets of codons regardless of the major codon-usage trends defined by base compositional properties of individual nematode genomes.     

Accuracy and power of the likelihood ratio test in detecting adaptive molecular evolution

The selective pressure at the protein level is usually measured by the nonsynonymous/synonymous rate ratio (omega = dN/dS), with omega < 1, omega = 1, and omega > 1 indicating purifying (or negative) selection, neutral evolution, and diversifying (or positive) selection, respectively. The omega ratio is commonly calculated as an average over sites. As every functional protein has some amino acid sites under selective constraints, averaging rates across sites leads to low power to detect positive selection. Recently developed models of codon substitution allow the omega ratio to vary among sites and appear to be powerful in detecting positive selection in empirical data analysis. In this study, we used computer simulation to investigate the accuracy and power of the likelihood ratio test (LRT) in detecting positive selection at amino acid sites. The test compares two nested models: one that allows for sites under positive selection (with omega > 1), and another that does not, with the chi2 distribution used for significance testing. We found that use of the chi(2) distribution makes the test conservative, especially when the data contain very short and highly similar sequences. Nevertheless, the LRT is powerful. Although the power can be low with only 5 or 6 sequences in the data, it was nearly 100% in data sets of 17 sequences. Sequence length, sequence divergence, and the strength of positive selection also were found to affect the power of the LRT. The exact distribution assumed for the omega ratio over sites was found not to affect the effectiveness of the LRT.     

Insect antimicrobial peptides: structures, properties and gene regulation

Antimicrobial peptides (AMPs) are part of the armament that insects have developed to fight off pathogens. Insect AMPs are typically cationic and often made of less than 100 amino acid residues. Although their structures are diverse, most of the AMPs can be assigned to a limited number of families. The most common structures are represented by peptides assuming a alpha-helical conformation in organic solutions or disulfide-stabilized beta-sheets with or without alpha-helical domains present. The diverse activity spectrum of these peptides may indicate different modes of action. Genetic analysis in the Drosophila model evidenced that multiple signal transduction pathways are activating the genes coding AMPs.     

Comparing Selection on S. aureus between Antimicrobial Peptides and Common Antibiotics

With a diminishing number of effective antibiotics, there has been interest in developing antimicrobial peptides (AMPs) as drugs. However, any new drug faces potential bacterial resistance evolution. Here, we experimentally compare resistance evolution in Staphylococcus aureus selected by three AMPs (from mammals, amphibians and insects), a combination of two AMPs, and two antibiotics: the powerful last-resort vancomycin and the classic streptomycin. We find that resistance evolves readily against single AMPs and against streptomycin, with no detectable fitness cost. However the response to selection from our combination of AMPs led to extinction, in a fashion qualitatively similar to vancomycin. This is consistent with the hypothesis that simultaneous release of multiple AMPs during immune responses is a factor which constrains evolution of AMP resistant pathogens.     

Genetic robustness and selection at the protein level for synonymous codons

Synonymous codons are neutral at the protein level, therefore natural selection at the protein level should have no effect on their frequencies. Synonymous codons, however, differ in their capacity to reduce the effects of errors: after mutation, certain codons keep on coding for the same amino acid or for amino acids with similar properties, while other synonymous codons produce very different amino acids. Therefore, the impact of errors on a coding sequence (genetic robustness) can be measured by analysing its codon usage. I analyse the codon usage of sequenced nuclear and cytoplasmic genomes and I show that there is an extensive variation in genetic robustness at the DNA sequence level, both among genomes and among genes of the same genome. I also show theoretically that robustness can be adaptive, that is natural selection may lead to a preference for codons that reduce the impact of errors. If selection occurs only among the mutants of a codon (e.g. among the progeny before the adult phase), however, the codons that are more sensitive to the effects of mutations may increase in frequency because they manage to get rid more easily of deleterious mutations. I also suggest other possible explanations for the evolution of genetic robustness at the codon level.