Analysis of Retinol Binding Protein 4 and ABCA4 Gene Variation in Non-Neovascular Age-Related Macular Degeneration.

Age-related macular degeneration (AMD) may be associated with ABCA4 variants and is characterized by the accumulation of visual cycle-byproduct lipofuscin. Reducing retinol-binding protein 4 (RBP4), a retinol transporter protein, may reduce lipofuscin production. This study aims to assess the associations between plasma RBP4, the ABCA4 variation, and AMD severity. Sixty-seven participants were grouped into healthy/mild AMD (n = 32) and severe AMD (n = 35) groups. The latter group was older than the former group and had higher levels of RBP4 (36.8 ± 8.3 vs. 30.4 ± 7.0 µg/mL, p = 0.0012). The ten participants with six ABCA4 linked-variants had higher RBP4 than those without (37.8 ± 7.7 vs. 32.4 ± 7.9 µg/mL; p = 0.026), and eight of them had severe AMD. Univariate analyses showed that severe AMD was related to older age (OR, 1.26; 95% CI, 1.13-1.40; p < 0.0001) and to higher RBP4 levels (OR, 1.12; 95% CI, 1.04-1.20; p = 0.003), whereas the linked ABCA4 variants had no associations. After adjustment, however, only age remained significantly associated with severe AMD. This pilot study shows a trend of higher plasma RBP4 levels in severe AMD or the ABCA4-linked variants, and further age-matched studies are warranted.

Advantages of meta-total RNA sequencing (MeTRS) over shotgun metagenomics and amplicon-based sequencing in the profiling of complex microbial communities.

Sequencing-based microbiome profiling aims at detecting and quantifying individual members of a microbial community in a culture-independent manner. While amplicon-based sequencing (ABS) of bacterial or fungal ribosomal DNA is the most widely used technology due to its low cost, it suffers from PCR amplification biases that hinder accurate representation of microbial population structures. Shotgun metagenomics (SMG) conversely allows unbiased microbiome profiling but requires high sequencing depth. Here we report the development of a meta-total RNA sequencing (MeTRS) method based on shotgun sequencing of total RNA and benchmark it on a human stool sample spiked in with known abundances of bacterial and fungal cells. MeTRS displayed the highest overall sensitivity and linearity for both bacteria and fungi, the greatest reproducibility compared to SMG and ABS, while requiring a ~20-fold lower sequencing depth than SMG. We therefore present MeTRS as a valuable alternative to existing technologies for large-scale profiling of complex microbiomes.

Experimental evolution of a fungal pathogen into a gut symbiont.

Gut microbes live in symbiosis with their hosts, but how mutualistic animal-microbe interactions emerge is not understood. By adaptively evolving the opportunistic fungal pathogen Candida albicans in the mouse gastrointestinal tract, we selected strains that not only had lost their main virulence program but also protected their new hosts against a variety of systemic infections. This protection was independent of adaptive immunity, arose as early as a single day postpriming, was dependent on increased innate cytokine responses, and was thus reminiscent of "trained immunity." Because both the microbe and its new host gain some advantages from their interaction, this experimental system might allow direct study of the evolutionary forces that govern the emergence of mutualism between a mammal and a fungus.

The Transcriptional Response of Candida albicans to Weak Organic Acids, Carbon Source, and MIG1 Inactivation Unveils a Role for HGT16 in Mediating the Fungistatic Effect of Acetic Acid.

Candida albicans is a resident fungus of the human intestinal microflora. Commonly isolated at low abundance in healthy people, C. albicans outcompetes local microbiota during candidiasis episodes. Under normal conditions, members of the human gastrointestinal (GI) microbiota were shown to keep C. albicans colonization under control. By releasing weak organic acids (WOAs), bacteria are able to moderate yeast growth. This mechanism displays a synergistic effect in vitro with the absence of glucose in medium of culture, which underlines the complex interactions that C. albicans faces in its natural environment. Inactivation of the transcriptional regulator MIG1 in C. albicans results in a lack of sensitivity to this synergistic outcome. To decipher C. albicans transcriptional responses to glucose, WOAs, and the role of MIG1, we performed RNA sequencing (RNA-seq) on four biological replicates exposed to combinations of these three parameters. We were able to characterize the (i) glucose response, (ii) response to acetic and butyric acid, (iii) MIG1 regulation of C. albicans, and (iv) genes responsible for WOA resistance. We identified a group of six genes linked to WOA sensitivity in a glucose-MIG1-dependent manner and inactivated one of these genes, the putative glucose transporter HGT16, in a SC5314 wild-type background. As expected, the mutant displayed a partial complementation to WOA resistance in the absence of glucose. This result points toward a mechanism of WOA sensitivity in C. albicans involving membrane transporters, which could be exploited to control yeast colonization in human body niches.

ß-glucan Exposure on the Fungal Cell Wall Tightly Correlates with Competitive Fitness of Candida Species in the Mouse Gastrointestinal Tract.

Candida albicans is responsible for ~400,000 systemic fungal infections annually, with an associated mortality rate of 46-75%. The human gastrointestinal (GI) tract represents the largest natural reservoir of Candida species and is a major source of systemic fungal infections. However, the factors that control GI colonization by Candida species are not completely understood. We hypothesized that the fungal cell wall would play an important role in determining the competitive fitness of Candida species in the mammalian GI tract. To test this hypothesis, we generated a systematic collection of isogenic C. albicans cell wall mutants and measured their fitness in the mouse GI tract via quantitative competition assays. Whereas a large variation in competitive fitness was found among mutants, no correlation was observed between GI fitness and total levels of individual cell wall components. Similar results were obtained in a set of distantly-related Candida species, suggesting that total amounts of individual cell wall components do not determine the ability of fungi to colonize the GI tract. We then subjected this collection of Candida strains and species to an extensive quantitative phenotypic profiling in search for features that might be responsible for their differences in GI fitness, but found no association with the ability to grow in GI-mimicking and stressful environments or with in vitro and in vivo virulence. The most significant association with GI fitness was found to be the strength of signaling through the Dectin-1 receptor. Using a quantitative assay to measure the amount of exposed ß-glucan on the surface of fungal cells, we found this parameter, unlike total ß-glucan levels, to be strongly predictive of competitive fitness in the mouse GI tract. These data suggest that fungal cell wall architecture, more so than its crude composition, critically determines the ability of fungi to colonize the mammalian GI tract. In particular, recognition of exposed ß-glucan by Dectin-1 receptor appears to severely limit Candida GI fitness and hence represents a promising target to reduce fungal colonization in patients at risks of systemic candidiasis.

Crosstalk between sugarcane and a plant-growth promoting Burkholderia species.

Bacterial species in the plant-beneficial-environmental clade of Burkholderia represent a substantial component of rhizosphere microbes in many plant species. To better understand the molecular mechanisms of the interaction, we combined functional studies with high-resolution dual transcriptome analysis of sugarcane and root-associated diazotrophic Burkholderia strain Q208. We show that Burkholderia Q208 forms a biofilm at the root surface and suppresses the virulence factors that typically trigger immune response in plants. Up-regulation of bd-type cytochromes in Burkholderia Q208 suggests an increased energy production and creates the microaerobic conditions suitable for BNF. In this environment, a series of metabolic pathways are activated in Burkholderia Q208 implicated in oxalotrophy, microaerobic respiration, and formation of PHB granules, enabling energy production under microaerobic conditions. In the plant, genes involved in hypoxia survival are up-regulated and through increased ethylene production, larger aerenchyma is produced in roots which in turn facilitates diffusion of oxygen within the cortex. The detected changes in gene expression, physiology and morphology in the partnership are evidence of a sophisticated interplay between sugarcane and a plant-growth promoting Burkholderia species that advance our understanding of the mutually beneficial processes occurring in the rhizosphere.

Predicting peptide binding to Major Histocompatibility Complex molecules.

The Major Histocompatibility Complex (MHC) constitutes an important part of the human immune system. During infection, pathogenic proteins are processed into peptide fragments by the antigen processing machinery. These peptides bind to MHC molecules and the MHC-peptide complex is then transported to the cell membrane where it elicits an immune response via T-cell binding. Understanding the molecular mechanism of this process will greatly assist in determining the aetiology of various diseases and in the design of effective drugs. One of the most challenging aspects of this area of research is understanding the specificity and sensitivity of the binding process. An empirical approach to the problem is unfeasible as there are over 512 billion potential binding peptides for each MHC molecule. Computational approaches offer the promise of predicting peptide binding, thus dramatically reducing the number of peptides proceeding to experimental verification. Various bioinformatic approaches have been developed to predict whether or not a particular peptide will bind to a particular MHC allele. Currently, peptide binding prediction methods can be categorised into three major groups: motif- and scoring matrix-based methods, artificial intelligence- (AI-) based methods, and structure-based methods. The first two are sequence-based approaches and are generally based on common sequence motifs in peptides known to bind to MHC molecules. The structure-based approach concerns the structural features and the distribution of energy between the binding peptide and the MHC molecule. Although knowledge of the molecular structure of the MHC molecules is expected to lead to better predictions of peptide binding, the development of structure-based methods has been relatively slow compared to sequence-based methods. Comparisons of various methods showed that the best sequence-based methods significantly outperform structure-based methods. This may be improved by producing more structures and binding data desperately needed by many alleles, especially class II molecules. On the other hand, the large number of verification methods and indicators used by structure-based studies hinders critical evaluation of the methods. Adopting commonly used assessment procedures can demonstrate the relative performance of structure-based methods in a straightforward comparison with other methods. This review provides an overview of current methods for predicting peptide binding to the MHC, with a focus on structure-based methods, and explores the potential for future development in this area.

Predicting peptide binding affinities to MHC molecules using a modified semi-empirical scoring function.

The Major Histocompatibility Complex (MHC) plays an important role in the human immune system. The MHC is involved in the antigen presentation system assisting T cells to identify foreign or pathogenic proteins. However, an MHC molecule binding a self-peptide may incorrectly trigger an immune response and cause an autoimmune disease, such as multiple sclerosis. Understanding the molecular mechanism of this process will greatly assist in determining the aetiology of various diseases and in the design of effective drugs. In the present study, we have used the Fresno semi-empirical scoring function and modify the approach to the prediction of peptide-MHC binding by using open-source and public domain software. We apply the method to HLA class II alleles DR15, DR1, and DR4, and the HLA class I allele HLA A2. Our analysis shows that using a large set of binding data and multiple crystal structures improves the predictive capability of the method. The performance of the method is also shown to be correlated to the structural similarity of the crystal structures used. We have exposed some of the obstacles faced by structure-based prediction methods and proposed possible solutions to those obstacles. It is envisaged that these obstacles need to be addressed before the performance of structure-based methods can be on par with the sequence-based methods.

A comparative location database (CompLDB): map integration within and between species.

We have adapted the Location Database (LDB) map-integration strategy of Morton et al. [Ann Hum Genet 56:223-232] (1992) as above to create an integrated map for each of several species for which fully annotated genome sequences are not yet available (sheep, cattle, pig, wallaby), using all types of partial maps for that species, including cytogenetic, linkage, somatic-cell hybrid, and radiation hybrid maps. An integrated map provides not only predictions of the kilobase location of every locus, but also predicts locations (in cM) and cytogenetic band locations for every locus. In this way a comprehensive linkage map and a comprehensive cytogenetic map are created, including all loci, irrespective of whether they have ever been linkage mapped or physically mapped, respectively. High-resolution physical maps from annotated sequenced species have also been placed alongside the integrated maps. This has created a powerful tool for comparative genomics. The LDB map-integration strategy has been extended to make use of zoo-FISH comparative information. It has also been extended to enable the creation of a "virtual" map for each species not yet sequenced by using mapping data from fully sequenced species. All of the partial maps, together with the integrated map, for each species have been placed in a database called Comparative Location Database (CompLDB), which is available for querying, browsing, or download in tabular form at http://medvet.angis.org.au/ldb/.