Molecular evolution of the vertebrate TLR1 gene family - a complex history of gene duplication, gene conversion, positive selection and co-evolution

<p>Abstract</p> <p>Background</p> <p>The Toll-like receptors represent a large superfamily of type I transmembrane glycoproteins, some common to a wide range of species and others are more restricted in their distribution. Most members of the Toll-like receptor superfamily have few paralogues; the exception is the TLR1 gene family with four closely related genes in mammals TLR1, TLR2, TLR6 and TLR10, and four in birds TLR1A, TLR1B, TLR2A and TLR2B. These genes were previously thought to have arisen by a series of independent gene duplications. To understand the evolutionary pattern of the TLR1 gene family in vertebrates further, we cloned the sequences of TLR1A, TLR1B, TLR2A and TLR2B in duck and turkey, constructed phylogenetic trees, predicted codons under positive selection and identified co-evolutionary amino acid pairs within the TLR1 gene family using sequences from 4 birds, 28 mammals, an amphibian and a fish.</p> <p>Results</p> <p>This detailed phylogenetic analysis not only clarifies the gene gains and losses within the TLR1 gene family of birds and mammals, but also defines orthologues between these vertebrates. In mammals, we predict amino acid sites under positive selection in TLR1, TLR2 and TLR6 but not TLR10. We detect co-evolution between amino acid residues in TLR2 and the other members of this gene family predicted to maintain their ability to form functional heterodimers. In birds, we predict positive selection in the TLR2A and TLR2B genes at functionally significant amino acid residues. We demonstrate that the TLR1 gene family has mostly been subject to purifying selection but has also responded to directional selection at a few sites, possibly in response to pathogen challenge.</p> <p>Conclusions</p> <p>Our phylogenetic and structural analyses of the vertebrate TLR1 family have clarified their evolutionary origins and predict amino acid residues likely to be important in the host's defense against invading pathogens.</p

Incomplete posttranslational prohormone modifications in hyperactive neuroendocrine cells

Contains fulltext : 76028.pdf (publisher's version ) (Open Access)8 p

A Combinatorial Approach to Detect Coevolved Amino Acid Networks in Protein Families of Variable Divergence

Communication between distant sites often defines the biological role of a protein: amino acid long-range interactions are as important in binding specificity, allosteric regulation and conformational change as residues directly contacting the substrate. The maintaining of functional and structural coupling of long-range interacting residues requires coevolution of these residues. Networks of interaction between coevolved residues can be reconstructed, and from the networks, one can possibly derive insights into functional mechanisms for the protein family. We propose a combinatorial method for mapping conserved networks of amino acid interactions in a protein which is based on the analysis of a set of aligned sequences, the associated distance tree and the combinatorics of its subtrees. The degree of coevolution of all pairs of coevolved residues is identified numerically, and networks are reconstructed with a dedicated clustering algorithm. The method drops the constraints on high sequence divergence limiting the range of applicability of the statistical approaches previously proposed. We apply the method to four protein families where we show an accurate detection of functional networks and the possibility to treat sets of protein sequences of variable divergence

Positively selected amino acid replacements within the RuBisCO enzyme of oak trees are associated with ecological adaptations

Phylogenetic analysis by maximum likelihood (PAML) has become the standard approach to study positive selection at the molecular level, but other methods may provide complementary ways to identify amino acid replacements associated with particular conditions. Here, we compare results of the decision tree (DT) model method with ones of PAML using the key photosynthetic enzyme RuBisCO as a model system to study molecular adaptation to particular ecological conditions in oaks (Quercus). We sequenced the chloroplast rbcL gene encoding RuBisCO large subunit in 158 Quercus species, covering about a third of the global genus diversity. It has been hypothesized that RuBisCO has evolved differentially depending on the environmental conditions and leaf traits governing internal gas diffusion patterns. Here, we show, using PAML, that amino acid replacements at the residue positions 95, 145, 251, 262 and 328 of the RuBisCO large subunit have been the subject of positive selection along particular Quercus lineages associated with the leaf traits and climate characteristics. In parallel, the DT model identified amino acid replacements at sites 95, 219, 262 and 328 being associated with the leaf traits and climate characteristics, exhibiting partial overlap with the results obtained using PAML

The invertebrate lysozyme effector ILYS-3 is systemically activated in response to danger signals and confers antimicrobial protection in C. elegans

Little is known about the relative contributions and importance of antibacterial effectors in the nematode C. elegans, despite extensive work on the innate immune responses in this organism. We report an investigation of the expression, function and regulation of the six ilys (invertebrate-type lysozyme) genes of C. elegans. These genes exhibited a surprising variety of tissue-specific expression patterns and responses to starvation or bacterial infection. The most strongly expressed, ilys-3, was investigated in detail. ILYS-3 protein was expressed constitutively in the pharynx and coelomocytes, and dynamically in the intestine. Analysis of mutants showed that ILYS-3 was required for pharyngeal grinding (disruption of bacterial cells) during normal growth and consequently it contributes to longevity, as well as being protective against bacterial pathogens. Both starvation and challenge with Gram-positive pathogens resulted in ERK-MAPK-dependent up-regulation of ilys-3 in the intestine. The intestinal induction by pathogens, but not starvation, was found to be dependent on MPK-1 activity in the pharynx rather than in the intestine, demonstrating unexpected communication between these two tissues. The coelomocyte expression appeared to contribute little to normal growth or immunity. Recombinant ILYS-3 protein was found to exhibit appropriate lytic activity against Gram-positive cell wall material

Modeling protein network evolution under genome duplication and domain shuffling

<p>Abstract</p> <p>Background</p> <p>Successive whole genome duplications have recently been firmly established in all major eukaryote kingdoms. Such <it>exponential </it>evolutionary processes must have largely contributed to shape the topology of protein-protein interaction (PPI) networks by outweighing, in particular, all <it>time-linear </it>network growths modeled so far.</p> <p>Results</p> <p>We propose and solve a mathematical model of PPI network evolution under successive genome duplications. This demonstrates, from first principles, that evolutionary conservation and scale-free topology are intrinsically linked properties of PPI networks and emerge from <it>i) </it>prevailing <it>exponential </it>network dynamics under duplication and <it>ii) asymmetric divergence </it>of gene duplicates. While required, we argue that this asymmetric divergence arises, in fact, spontaneously at the level of protein-binding sites. This supports a refined model of PPI network evolution in terms of protein domains under exponential and asymmetric duplication/divergence dynamics, with multidomain proteins underlying the combinatorial formation of protein complexes. Genome duplication then provides a powerful source of PPI network innovation by promoting local rearrangements of multidomain proteins on a genome wide scale. Yet, we show that the overall conservation and topology of PPI networks are robust to extensive domain shuffling of multidomain proteins as well as to finer details of protein interaction and evolution. Finally, large scale features of <it>direct </it>and <it>indirect </it>PPI networks of <it>S. cerevisiae </it>are well reproduced numerically with only two adjusted parameters of clear biological significance (<it>i.e</it>. network effective growth rate and average number of protein-binding domains per protein).</p> <p>Conclusion</p> <p>This study demonstrates the statistical consequences of genome duplication and domain shuffling on the conservation and topology of PPI networks over a broad evolutionary scale across eukaryote kingdoms. In particular, scale-free topologies of PPI networks, which are found to be robust to extensive shuffling of protein domains, appear to be a simple consequence of the conservation of protein-binding domains under asymmetric duplication/divergence dynamics in the course of evolution.</p

Reading tea leaves worldwide: Decoupled drivers of initial litter decomposition mass‐loss rate and stabilization

The breakdown of plant material fuels soil functioning and biodiversity. Currently, process understanding of global decomposition patterns and the drivers of such patterns are hampered by the lack of coherent large-scale datasets. We buried 36,000 individual litterbags (tea bags) worldwide and found an overall negative correlation between initial mass-loss rates and stabilization factors of plant-derived carbon, using the Tea Bag Index (TBI). The stabilization factor quantifies the degree to which easy-to- degrade components accumulate during early-stage decomposition (e.g. by environmental limitations). However, agriculture and an interaction between moisture and temperature led to a decoupling between initial mass-loss rates and stabilization, notably in colder locations. Using TBI improved mass-loss estimates of natural litter compared to models that ignored stabilization. Ignoring the transformation of dead plant material to more recalcitrant substances during early-stage decomposition, and the environmental control of this transformation, could overestimate carbon losses during early decomposition in carbon cycle models

Prevalence of Epistasis in the Evolution of Influenza A Surface Proteins

The surface proteins of human influenza A viruses experience positive selection to escape both human immunity and, more recently, antiviral drug treatments. In bacteria and viruses, immune-escape and drug-resistant phenotypes often appear through a combination of several mutations that have epistatic effects on pathogen fitness. However, the extent and structure of epistasis in influenza viral proteins have not been systematically investigated. Here, we develop a novel statistical method to detect positive epistasis between pairs of sites in a protein, based on the observed temporal patterns of sequence evolution. The method rests on the simple idea that a substitution at one site should rapidly follow a substitution at another site if the sites are positively epistatic. We apply this method to the surface proteins hemagglutinin and neuraminidase of influenza A virus subtypes H3N2 and H1N1. Compared to a non-epistatic null distribution, we detect substantial amounts of epistasis and determine the identities of putatively epistatic pairs of sites. In particular, using sequence data alone, our method identifies epistatic interactions between specific sites in neuraminidase that have recently been demonstrated, in vitro, to confer resistance to the drug oseltamivir; these epistatic interactions are responsible for widespread drug resistance among H1N1 viruses circulating today. This experimental validation demonstrates the predictive power of our method to identify epistatic sites of importance for viral adaptation and public health. We conclude that epistasis plays a large role in shaping the molecular evolution of influenza viruses. In particular, sites with , which would normally not be identified as positively selected, can facilitate viral adaptation through epistatic interactions with their partner sites. The knowledge of specific interactions among sites in influenza proteins may help us to predict the course of antigenic evolution and, consequently, to select more appropriate vaccines and drugs