Mucosal Immunity and Candida albicans Infection

Interactions between mucosal surfaces and microbial microbiota are key to host defense, health, and disease. These surfaces are exposed to high numbers of microbes and must be capable of distinguishing between those that are beneficial or avirulent and those that will invade and cause disease. Our understanding of the mechanisms involved in these discriminatory processes has recently begun to expand as new studies bring to light the importance of epithelial cells and novel immune cell subsets such as Th17 T cells in these processes. Elucidating how these mechanisms function will improve our understanding of many diverse diseases and improve our ability to treat patients suffering from these conditions. In our voyage to discover these mechanisms, mucosal interactions with opportunistic commensal organisms such as the fungus Candida albicans provide insights that are invaluable. Here, we review current knowledge of the interactions between C. albicans and epithelial surfaces and how this may shape our understanding of microbial-mucosal interactions

Candida albicans Yeast and Hyphae are Discriminated by MAPK Signaling in Vaginal Epithelial Cells

We previously reported that a bi-phasic innate immune MAPK response, constituting activation of the mitogen-activated protein kinase (MAPK) phosphatase MKP1 and c-Fos transcription factor, discriminates between the yeast and hyphal forms of Candida albicans in oral epithelial cells (ECs). Since the vast majority of mucosal Candida infections are vaginal, we sought to determine whether a similar bi-phasic MAPK-based immune response was activated by C. albicans in vaginal ECs. Here, we demonstrate that vaginal ECs orchestrate an innate response to C. albicans via NF-κB and MAPK signaling pathways. However, unlike in oral ECs, the first MAPK response, defined by c-Jun transcription factor activation, is delayed until 2 h in vaginal ECs but is still independent of hypha formation. The ‘second’ or ‘late’ MAPK response, constituting MKP1 and c-Fos transcription factor activation, is identical to oral ECs and is dependent upon both hypha formation and fungal burdens. NF-κB activation is immediate but independent of morphology. Furthermore, the proinflammatory response in vaginal ECs is different to oral ECs, with an absence of G-CSF and CCL20 and low level IL-6 production. Therefore, differences exist in how C. albicans activates signaling mechanisms in oral and vaginal ECs; however, the activation of MAPK-based pathways that discriminate between yeast and hyphal forms is retained between these mucosal sites. We conclude that this MAPK-based signaling pathway is a common mechanism enabling different human epithelial tissues to orchestrate innate immune responses specifically against C. albicans hyphae

Integrating vector control across diseases

Background: Vector-borne diseases cause a significant proportion of the overall burden of disease across the globe, accounting for over 10 % of the burden of infectious diseases. Despite the availability of effective interventions for many of these diseases, a lack of resources prevents their effective control. Many existing vector control interventions are known to be effective against multiple diseases, so combining vector control programmes to simultaneously tackle several diseases could offer more cost-effective and therefore sustainable disease reductions. Discussion: The highly successful cross-disease integration of vaccine and mass drug administration programmes in low-resource settings acts a precedent for cross-disease vector control. Whilst deliberate implementation of vector control programmes across multiple diseases has yet to be trialled on a large scale, a number of examples of ‘accidental’ cross-disease vector control suggest the potential of such an approach. Combining contemporary high-resolution global maps of the major vector-borne pathogens enables us to quantify overlap in their distributions and to estimate the populations jointly at risk of multiple diseases. Such an analysis shows that over 80 % of the global population live in regions of the world at risk from one vector-borne disease, and more than half the world’s population live in areas where at least two different vector-borne diseases pose a threat to health. Combining information on co-endemicity with an assessment of the overlap of vector control methods effective against these diseases allows us to highlight opportunities for such integration. Summary: Malaria, leishmaniasis, lymphatic filariasis, and dengue are prime candidates for combined vector control. All four of these diseases overlap considerably in their distributions and there is a growing body of evidence for the effectiveness of insecticide-treated nets, screens, and curtains for controlling all of their vectors. The real-world effectiveness of cross-disease vector control programmes can only be evaluated by large-scale trials, but there is clear evidence of the potential of such an approach to enable greater overall health benefit using the limited funds available

Associated patterns of insecticide resistance in field populations of malaria vectors across Africa.

The development of insecticide resistance in African malaria vectors threatens the continued efficacy of important vector control methods that rely on a limited set of insecticides. To understand the operational significance of resistance we require quantitative information about levels of resistance in field populations to the suite of vector control insecticides. Estimation of resistance is complicated by the sparsity of observations in field populations, variation in resistance over time and space at local and regional scales, and cross-resistance between different insecticide types. Using observations of the prevalence of resistance in mosquito species from the complex sampled from 1,183 locations throughout Africa, we applied Bayesian geostatistical models to quantify patterns of covariation in resistance phenotypes across different insecticides. For resistance to the three pyrethroids tested, deltamethrin, permethrin, and λ-cyhalothrin, we found consistent forms of covariation across sub-Saharan Africa and covariation between resistance to these pyrethroids and resistance to DDT. We found no evidence of resistance interactions between carbamate and organophosphate insecticides or between these insecticides and those from other classes. For pyrethroids and DDT we found significant associations between predicted mean resistance and the observed frequency of mutations in the gene in field mosquito samples, with DDT showing the strongest association. These results improve our capacity to understand and predict resistance patterns throughout Africa and can guide the development of monitoring strategies

The Human Mucosal Mycobiome and Fungal Community Interactions

With the advent of high-throughput sequencing techniques, the astonishing extent and complexity of the microbial communities that reside within and upon us has begun to become clear. Moreover, with advances in computing and modelling methods, we are now beginning to grasp just how dynamic our interactions with these communities are. The diversity of both these communities and their interactions—both within the community and with us—are dependent on a multitude of factors, both microbial- and host-mediated. Importantly, it is becoming clear that shifts in the makeup of these communities, or their responses, are linked to different disease states. Although much of the work to define these interactions and links has been investigating bacterial communities, recently there has been significant growth in the body of knowledge, indicating that shifts in the host fungal communities (mycobiome) are also intimately linked to disease status. In this review, we will explore these associations, along with the interactions between fungal communities and their human and microbial habitat, and discuss the future applications of systems biology in determining their role in disease status

Global mapping of infectious disease

The primary aim of this review was to evaluate the state of knowledge of the geographical distribution of all infectious diseases of clinical significance to humans. A systematic review was conducted to enumerate cartographic progress, with respect to the data available for mapping and the methods currently applied. The results helped define the minimum information requirements for mapping infectious disease occurrence, and a quantitative framework for assessing the mapping opportunities for all infectious diseases. This revealed that of 355 infectious diseases identified, 174 (49%) have a strong rationale for mapping and of these only 7 (4%) had been comprehensively mapped. A variety of ambitions, such as the quantification of the global burden of infectious disease, international biosurveillance, assessing the likelihood of infectious disease outbreaks and exploring the propensity for infectious disease evolution and emergence, are limited by these omissions. An overview of the factors hindering progress in disease cartography is provided. It is argued that rapid improvement in the landscape of infectious diseases mapping can be made by embracing non-conventional data sources, automation of geo-positioning and mapping procedures enabled by machine learning and information technology, respectively, in addition to harnessing labour of the volunteer ‘cognitive surplus’ through crowdsourcing

Mapping the spatial distribution of the Japanese encephalitis vector, Culex tritaeniorhynchus Giles, 1901 (Diptera: Culicidae) within areas of Japanese encephalitis risk

Background Japanese encephalitis (JE) is one of the most significant aetiological agents of viral encephalitis in Asia. This medically important arbovirus is primarily spread from vertebrate hosts to humans by the mosquito vector Culex tritaeniorhynchus. Knowledge of the contemporary distribution of this vector species is lacking, and efforts to define areas of disease risk greatly depend on a thorough understanding of the variation in this mosquito’s geographical distribution. Results We assembled a contemporary database of Cx. tritaeniorhynchus presence records within Japanese encephalitis risk areas from formal literature and other relevant resources, resulting in 1,045 geo-referenced, spatially and temporally unique presence records spanning from 1928 to 2014 (71.9% of records obtained between 2001 and 2014). These presence data were combined with a background dataset capturing sample bias in our presence dataset, along with environmental and socio-economic covariates, to inform a boosted regression tree model predicting environmental suitability for Cx. tritaeniorhynchus at each 5 × 5 km gridded cell within areas of JE risk. The resulting fine-scale map highlights areas of high environmental suitability for this species across India, Nepal and China that coincide with areas of high JE incidence, emphasising the role of this vector in disease transmission and the utility of the map generated. Conclusions Our map contributes towards efforts determining the spatial heterogeneity in Cx. tritaeniorhynchus distribution within the limits of JE transmission. Specifically, this map can be used to inform vector control programs and can be used to identify key areas where the prevention of Cx. tritaeniorhynchus establishment should be a priority

Contemporary status of insecticide resistance in the major Aedes vectors of arboviruses infecting humans (PLoS Negl Trop Dis)

Publisher Copyright: © 2021 Moyes et al.After the publication of this article [1] the authors noticed citation errors in Table 2. The citations for item 5 listed under pyrethroids and items 2, 3, and 4 listed under temephos refer to the wrong references and these citations have been corrected in the updated Table 2 below. The citations for items 1, 3 and 4 listed under pyrethroids and item 1 listed under temephos are also incorrect and should cite references that have been omitted from the reference list. These citations have been corrected in the updated Table 2 below and the following corre-sponding references 79–82 should be added to the reference list: 79. Bariami V, Jones CM, Poupardin R, Vontas J, Ranson H. Gene amplification, ABC trans-porters and cytochrome P450s: unraveling the molecular basis of pyrethroid resistance in the dengue vector, Aedes aegypti. PLoS Negl Trop Dis. 2012;6: e1692. pmid:22720108 80. Saavedra-Rodriguez K, Suarez AF, Salas IF, Strode C, Ranson H, Hemingway J, et al. Transcription of detoxification genes after permethrin selection in the mosquito Aedes aegypti. Insect Mol Biol. 2012;21: 61–77. pmid:22032702 81. David J-P, Faucon F, Chandor-Proust A, Poupardin R, Riaz MA, Bonin A, et al. Comparative analysis of response to selection with three insecticides in the dengue mosquito Aedes aegypti using mRNA sequencing. BMC Genomics. 2014;15: 174. pmid:24593293 82. Strode C, de Melo-Santos M, Magalhaes T, Araujo A, Ayres C. Expression profile of genes during resistance reversal in a temephos selected strain of the dengue vector, Aedes aegypti. PloS One. 2012;7: e39439. pmid: 22870187.publishersversionpublishe

Integrative functional analysis uncovers metabolic differences between Candida species

Candida species are a dominant constituent of the human mycobiome and associated with the development of several diseases. Understanding the Candida species metabolism could provide key insights into their ability to cause pathogenesis. Here, we have developed the BioFung\ua0database, providing an efficient annotation of protein-encoding genes. Along, with BioFung, using carbohydrate-active enzyme (CAZymes) analysis, we have uncovered core and accessory features across Candida species demonstrating plasticity, adaption to the environment and acquired features. We show a greater importance of amino acid metabolism, as functional analysis revealed that all Candida species can employ amino acid metabolism. However, metabolomics revealed that only a specific cluster of species (AGAu species-C. albicans, C. glabrata and C. auris) utilised amino acid metabolism including arginine, cysteine, and methionine metabolism potentially improving their competitive fitness in pathogenesis. We further identified critical metabolic pathways in the AGAu cluster with biomarkers and anti-fungal target potential in the CAZyme profile, polyamine, choline and fatty acid biosynthesis pathways. This study, combining genomic analysis, and validation with gene expression and metabolomics, highlights the metabolic diversity with AGAu species that underlies their remarkable ability to dominate they mycobiome and cause disease