Phylogenetic structure and host abundance drive disease pressure in communities

Pathogens play an important part in shaping the structure and dynamics of natural communities, because species are not affected by them equally. A shared goal of ecology and epidemiology is to predict when a species is most vulnerable to disease. A leading hypothesis asserts that the impact of disease should increase with host abundance, producing a ‘rare-species advantage. However, the impact of a pathogen may be decoupled from host abundance, because most pathogens infect more than one species, leading to pathogen spillover onto closely related species. Here we show that the phylogenetic and ecological structure of the surrounding community can be important predictors of disease pressure. We found that the amount of tissue lost to disease increased with the relative abundance of a species across a grassland plant community, and that this rare-species advantage had an additional phylogenetic component: disease pressure was stronger on species with many close relatives. We used a global model of pathogen sharing as a function of relatedness between hosts, which provided a robust predictor of relative disease pressure at the local scale. In our grassland, the total amount of disease was most accurately explained not by the abundance of the focal host alone, but by the abundance of all species in the community weighted by their phylogenetic distance to the host. Furthermore, the model strongly predicted observed disease pressure for 44 novel host species we introduced experimentally to our study site, providing evidence for a mechanism to explain why phylogenetically rare species are more likely to become invasive when introduced. Our results demonstrate how the phylogenetic and ecological structure of communities can have a key role in disease dynamics, with implications for the maintenance of biodiversity, biotic resistance against introduced weeds, and the success of managed plants in agriculture and forestry

What lies between market and hierarchy? Insights from internalization theory and global value chain theory

In this paper, we suggest that internalization theory might be extended by incorporating complementary insights from GVC theory. More specifically, we argue that internalization theory can explain why lead firms might wish to externalize selected activities, but that it is largely silent on the mechanisms by which those lead firms might exercise control over the resultant externalized relationships with their GVC partners. We advance an explanation linking the choice of control mechanism to two factors: power asymmetries between the lead firms and their GVC partners, and the degree of codifiability of the information to be exchanged in the relationship

Support Vector Machine based method to distinguish proteobacterial proteins from eukaryotic plant proteins

Background: Members of the phylum Proteobacteria are most prominent among bacteria causing plant diseases that result in a diminution of the quantity and quality of food produced by agriculture. To ameliorate these losses, there is a need to identify infections in early stages. Recent developments in next generation nucleic acid sequencing and mass spectrometry open the door to screening plants by the sequences of their macromolecules. Such an approach requires the ability to recognize the organismal origin of unknown DNA or peptide fragments. There are many ways to approach this problem but none have emerged as the best protocol. Here we attempt a systematic way to determine organismal origins of peptides by using a machine learning algorithm. The algorithm that we implement is a Support Vector Machine (SVM).Result: The amino acid compositions of proteobacterial proteins were found to be different from those of plant proteins. We developed an SVM model based on amino acid and dipeptide compositions to distinguish between a proteobacterial protein and a plant protein. The amino acid composition (AAC) based SVM model had an accuracy of 92.44% with 0.85 Matthews correlation coefficient (MCC) while the dipeptide composition (DC) based SVM model had a maximum accuracy of 94.67% and 0.89 MCC. We also developed SVM models based on a hybrid approach (AAC and DC), which gave a maximum accuracy 94.86% and a 0.90 MCC. The models were tested on unseen or untrained datasets to assess their validity.Conclusion: The results indicate that the SVM based on the AAC and DC hybrid approach can be used to distinguish proteobacterial from plant protein sequences.Peer reviewedBiochemistry and Molecular Biolog

Author Correction: Cross-ancestry genome-wide association analysis of corneal thickness strengthens link between complex and Mendelian eye diseases

Emmanuelle Souzeau, who contributed to analysis of data, was inadvertently omitted from the author list in the originally published version of this Article. This has now been corrected in both the PDF and HTML versions of the Article

A "Candidate-Interactome" Aggregate Analysis of Genome-Wide Association Data in Multiple Sclerosis

Though difficult, the study of gene-environment interactions in multifactorial diseases is crucial for interpreting the relevance of non-heritable factors and prevents from overlooking genetic associations with small but measurable effects. We propose a “candidate interactome” (i.e. a group of genes whose products are known to physically interact with environmental factors that may be relevant for disease pathogenesis) analysis of genome-wide association data in multiple sclerosis. We looked for statistical enrichment of associations among interactomes that, at the current state of knowledge, may be representative of gene-environment interactions of potential, uncertain or unlikely relevance for multiple sclerosis pathogenesis: Epstein-Barr virus, human immunodeficiency virus, hepatitis B virus, hepatitis C virus, cytomegalovirus, HHV8-Kaposi sarcoma, H1N1-influenza, JC virus, human innate immunity interactome for type I interferon, autoimmune regulator, vitamin D receptor, aryl hydrocarbon receptor and a panel of proteins targeted by 70 innate immune-modulating viral open reading frames from 30 viral species. Interactomes were either obtained from the literature or were manually curated. The P values of all single nucleotide polymorphism mapping to a given interactome were obtained from the last genome-wide association study of the International Multiple Sclerosis Genetics Consortium & the Wellcome Trust Case Control Consortium, 2. The interaction between genotype and Epstein Barr virus emerges as relevant for multiple sclerosis etiology. However, in line with recent data on the coexistence of common and unique strategies used by viruses to perturb the human molecular system, also other viruses have a similar potential, though probably less relevant in epidemiological terms

Previsual symptoms of Xylella fastidiosa infection revealed in spectral plant-trait alterations

Plant pathogens cause significant losses to agricultural yields, and increasingly threaten food security, ecosystem integrity, and societies in general. Xylella fastidiosa (Xf) is one of the most dangerous plant bacteria worldwide, causing several diseases with profound impacts on agriculture and the environment. Primarily occurring in the Americas, its recent discovery in Asia and Europe demonstrates a dramatically broadened geographic range. The Xf pathogen has thus re-emerged as a global threat, with its poorly contained expansion in Europe creating a socio-economic, cultural, and political disaster. Xf represents a threat of global proportion because it can infect over 350 plant species worldwide, and the early detection of Xf has been identified as a critical need for its eradication. Here, we show that changes in plant functional traits retrieved from airborne imaging spectroscopy and thermography reveal Xf infection in trees before symptoms are visible. We obtained accuracies of disease detection exceeding 80% when high-resolution solar-induced fluorescence quantified by 3D simulations and thermal-based stress indicators were coupled with photosynthetic traits sensitive to rapid pigment dynamics and degradation. Moreover, we found that the visually asymptomatic trees originally scored as affected via spectral plant trait alterations (presumed false positives) developed Xf symptoms four months later at almost double the rate of the asymptomatic trees classified as not affected by remote sensing. We demonstrate that spectral plant trait alterations caused by Xf infection are detectable at the landscape scale before symptoms are visible, a critical requirement to help eradicate some of the most devastating plant diseases worldwide.JRC.D.1-Bio-econom

A “Candidate-Interactome” Aggregate Analysis of Genome-Wide Association Data in Multiple Sclerosis

Though difficult, the study of gene-environment interactions in multifactorial diseases is crucial for interpreting the relevance of non-heritable factors and prevents from overlooking genetic associations with small but measurable effects. We propose a "candidate interactome" (i.e. a group of genes whose products are known to physically interact with environmental factors that may be relevant for disease pathogenesis) analysis of genome-wide association data in multiple sclerosis. We looked for statistical enrichment of associations among interactomes that, at the current state of knowledge, may be representative of gene-environment interactions of potential, uncertain or unlikely relevance for multiple sclerosis pathogenesis: Epstein-Barr virus, human immunodeficiency virus, hepatitis B virus, hepatitis C virus, cytomegalovirus, HHV8-Kaposi sarcoma, H1N1-influenza, JC virus, human innate immunity interactome for type I interferon, autoimmune regulator, vitamin D receptor, aryl hydrocarbon receptor and a panel of proteins targeted by 70 innate immune-modulating viral open reading frames from 30 viral species. Interactomes were either obtained from the literature or were manually curated. The P values of all single nucleotide polymorphism mapping to a given interactome were obtained from the last genome-wide association study of the International Multiple Sclerosis Genetics Consortium & the Wellcome Trust Case Control Consortium, 2. The interaction between genotype and Epstein Barr virus emerges as relevant for multiple sclerosis etiology. However, in line with recent data on the coexistence of common and unique strategies used by viruses to perturb the human molecular system, also other viruses have a similar potential, though probably less relevant in epidemiological terms

A molecular analysis of desiccation tolerance mechanisms in the anhydrobiotic nematode Panagrolaimus superbus using expressed sequenced tags

<p>Abstract</p> <p>Background</p> <p>Some organisms can survive extreme desiccation by entering into a state of suspended animation known as anhydrobiosis. <it>Panagrolaimus superbus </it>is a free-living anhydrobiotic nematode that can survive rapid environmental desiccation. The mechanisms that <it>P. superbus </it>uses to combat the potentially lethal effects of cellular dehydration may include the constitutive and inducible expression of protective molecules, along with behavioural and/or morphological adaptations that slow the rate of cellular water loss. In addition, inducible repair and revival programmes may also be required for successful rehydration and recovery from anhydrobiosis.</p> <p>Results</p> <p>To identify constitutively expressed candidate anhydrobiotic genes we obtained 9,216 ESTs from an unstressed mixed stage population of <it>P. superbus</it>. We derived 4,009 unigenes from these ESTs. These unigene annotations and sequences can be accessed at <url>http://www.nematodes.org/nembase4/species_info.php?species=PSC</url>. We manually annotated a set of 187 constitutively expressed candidate anhydrobiotic genes from <it>P. superbus</it>. Notable among those is a putative lineage expansion of the <it>lea </it>(late embryogenesis abundant) gene family. The most abundantly expressed sequence was a member of the nematode specific <it>sxp/ral-2 </it>family that is highly expressed in parasitic nematodes and secreted onto the surface of the nematodes' cuticles. There were 2,059 novel unigenes (51.7% of the total), 149 of which are predicted to encode intrinsically disordered proteins lacking a fixed tertiary structure. One unigene may encode an exo-β-1,3-glucanase (GHF5 family), most similar to a sequence from <it>Phytophthora infestans</it>. GHF5 enzymes have been reported from several species of plant parasitic nematodes, with horizontal gene transfer (HGT) from bacteria proposed to explain their evolutionary origin. This <it>P. superbus </it>sequence represents another possible HGT event within the Nematoda. The expression of five of the 19 putative stress response genes tested was upregulated in response to desiccation. These were the antioxidants <it>glutathione peroxidase, dj-1 </it>and <it>1-Cys peroxiredoxin</it>, an <it>shsp </it>sequence and an <it>lea </it>gene.</p> <p>Conclusions</p> <p><it>P. superbus </it>appears to utilise a strategy of combined constitutive and inducible gene expression in preparation for entry into anhydrobiosis. The apparent lineage expansion of <it>lea </it>genes, together with their constitutive and inducible expression, suggests that LEA3 proteins are important components of the anhydrobiotic protection repertoire of <it>P. superbus</it>.</p

Evaluation of appendicitis risk prediction models in adults with suspected appendicitis

Background Appendicitis is the most common general surgical emergency worldwide, but its diagnosis remains challenging. The aim of this study was to determine whether existing risk prediction models can reliably identify patients presenting to hospital in the UK with acute right iliac fossa (RIF) pain who are at low risk of appendicitis. Methods A systematic search was completed to identify all existing appendicitis risk prediction models. Models were validated using UK data from an international prospective cohort study that captured consecutive patients aged 16–45 years presenting to hospital with acute RIF in March to June 2017. The main outcome was best achievable model specificity (proportion of patients who did not have appendicitis correctly classified as low risk) whilst maintaining a failure rate below 5 per cent (proportion of patients identified as low risk who actually had appendicitis). Results Some 5345 patients across 154 UK hospitals were identified, of which two‐thirds (3613 of 5345, 67·6 per cent) were women. Women were more than twice as likely to undergo surgery with removal of a histologically normal appendix (272 of 964, 28·2 per cent) than men (120 of 993, 12·1 per cent) (relative risk 2·33, 95 per cent c.i. 1·92 to 2·84; P < 0·001). Of 15 validated risk prediction models, the Adult Appendicitis Score performed best (cut‐off score 8 or less, specificity 63·1 per cent, failure rate 3·7 per cent). The Appendicitis Inflammatory Response Score performed best for men (cut‐off score 2 or less, specificity 24·7 per cent, failure rate 2·4 per cent). Conclusion Women in the UK had a disproportionate risk of admission without surgical intervention and had high rates of normal appendicectomy. Risk prediction models to support shared decision‐making by identifying adults in the UK at low risk of appendicitis were identified