HLA-DR4 and career prospects in rheumatology: is there a link?

OBJECTIVE--To determine whether HLA type is associated with career progress in rheumatology. DESIGN--Comparison of HLA type after HLA analysis of samples of venous blood. SETTING--Department of Rheumatology Research, University of Birmingham. SUBJECTS--All (37) staff in the department. RESULTS--All the senior academics and most staff with a PhD expressed HLA-DR4. The prevalence of expression in each of these groups was significantly greater than that found in the controls. None of the junior doctors or secretaries expressed DR4. CONCLUSION--The junior doctors in the department have poor career prospects as HLA-DR4 seems to be associated with academic achievement.     

Brite/beige fat and UCP1 — is it thermogenesis?

The presence of two distinct types of adipose tissue, which have opposing functions, has been known for decades. White adipose tissue (WAT) is the main tissue of energy storage, while brown adipose tissue (BAT) dissipates energy as heat and is required for non-shivering thermoregulation. In the last few years, a third type of adipocyte was identified, termed the brite (“brown and white”) or beige adipocyte. Their physiological control and role, however, are not fully clarified. Brite/beige adipocytes have a positive impact on systemic metabolism that is generally explained by the thermogenesis of brite/beige adipocytes; although thermogenesis has not been directly measured but is mostly inferred by gene expression data of typical thermogenic genes such as uncoupling protein 1 (UCP1). Here we critically review functional evidence for the thermogenic potential of brite/beige adipocytes, leading to the conclusion that direct measurements of brite/beige adipocyte bioenergetics, beyond gene regulation, are pivotal to quantify their thermogenic potential. In particular, we exemplified that the massive induction of UCP1 mRNA during the browning of isolated subcutaneous adipocytes in vitro is not reflected in significant alterations of cellular bioenergetics. Herein, we demonstrate that increases in mitochondrial respiration in response to beta-adrenergic stimulus can be independent of UCP1. Using HEK293 cells expressing UCP1, we show how to directly assess UCP1 function by adequate activation in intact cells. Finally, we provide a guide on the interpretation of UCP1 activity and the pitfalls by solely using respiration measurements. The functional analysis of beige adipocyte bioenergetics will assist to delineate the impact of browning on thermogenesis, possibly elucidating additional physiological roles and its contribution to systemic metabolism, highlighting possible avenues for future research. This article is part of a Special Issue entitled: 18th European Bioenergetic Conference.     

Avoidance of oxidative-stress perturbation in yeast bioprocesses by proteomic and genomic biostrategies?

AIMS: Bioprocess oxidative stress caused by many reactive oxygen species (ROS) can lead to largely irreversible perturbation of yeast bioprocesses. These include the production of proteins derived from recombinant DNA yeast technology (aerobically grown Saccharomyces cerevisiae). These proteins include rennin, amyloglucosidases (glucamylases), interferons, interleukins, insulin, monoclonal antibodies, tissue plasminogen activators (t-PA), sexually transmitted disease antigens, and measles, mumps and rubella antigens, growth hormones, somatotropin, blood clotting factors VIII and XIII. In addition, there may be a demand for severe acute respiratory syndrome-coronavirus antigens, hepatitis A, B and C viral-selected antigens, HIV retroviral antigens, influenza antigens, trypanosomal antigens, and foot and mouth disease antigens. Prevention of oxidative stress has been achieved by application of antioxidant redox metalloenzymes such as superoxide dismutases (containing Cu/Zn cytosolic, Mn mitochondrial and Fe bacterial) glutathione peroxidases (and other Se-containing proteins and enzymes such as the thioredoxins), catalases (Fe-containing), cytochrome c peroxidases (Fe-containing), ceruloplasmins (Cu-containing), metallothionines (these cysteine thiol-rich proteins bind ions of cadmium and mercury) and tyrosinases(Cu-containing). METHODS AND RESULTS: ROS are generated inadvertently by single metal valency couples such as FeII/FeIII and by FeIII/FeV present in 2700 (including 57 human) isoforms in cytochromes P450 mixed-function oxidases (EC 1.14.14.1; O2 : mono-oxygenase NADPH/NADH requiring). In addition, mixed-metal couples such as valency unmatched forms in CuI/FeII and FeIII/MnIV can recycle electrons. Moreover, proteins/protein chaperone couples can recycle electrons, often where futile-recycling systems have been instigated. Furthermore, oxidized membrane phospholipids (R) can form ROOH (lipid hydroperoxides) and ROH (lipid alkoxides) that can generate ROS through Fenton chemistry (iron-catalysed) chain reactions. Utilization of chain-breaking antioxidants such as vitamin E (alpha-tocopherol) in the lipid phase and vitamin C (ascorbate) in the aqueous phase can terminate these ROS-producing reactions. CONCLUSIONS: The main significance of the study is that proteomic strategies of relief from bioprocess perturbation by ROS of yeast fermentations (used to manufacture proteins required in the food and therapeutic bioindustries) may become possible through addition of selected proteins (including metalloenzymes). The main impact of the study is that the utilization of genetically modified (GM) yeast produced by recombinant DNA technology genomic strategies could circumvent the bioprocessing problems that otherwise result from the bioprocess perturbations: this is as a result of oxidative stress caused by ROS, which is avoidable by deployment of appropriate antioxidants such as vitamins E, C and D (and antioxidant proteins and enzymes often of microbial origin via recombinant DNA technology).     

Are online prediction tools a valid alternative to genomic profiling in the context of systemic treatment of ER-positive breast cancer?

Background

Clinicians use clinical and pathological parameters, such as tumour size, grade and nodal status, to make decisions on adjuvant treatments for breast cancer. However, therapeutic decisions based on these features tend to vary due to their subjectivity. Computational and mathematical algorithms were developed using clinical outcome data from breast cancer registries, such as Adjuvant! Online and NHS PREDICT. More recently, assessments of molecular profiles have been applied in the development of better prognostic tools.

Methods

Based on the available literature on online registry-based tools and genomic assays, we evaluated whether these online tools could be valid and accurate alternatives to genomic and molecular profiling of the individual breast tumour in aiding therapeutic decisions, particularly in patients with early ER-positive breast cancer.

Results and conclusions

Early breast cancer is currently considered a systemic disease and a complex ecosystem with behaviour determined by the complex genetic and molecular signatures of the tumour cells, mammary stem cells, microenvironment and host immune system. We anticipate that molecular profiling will continue to evolve, expanding beyond the primary tumour to include the tumour microenvironment, cancer stem cells and host immune system. This should further refine therapeutic decisions and optimise clinical outcome.This article was specially invited by the editors and represents work by leading researchers.

     

Mating behaviour in Schistosomes: are paired worms always faithful?

Previously assumed to be monogamous, the mating system of schistosomes has been the subject of some debate since recent findings have shown that change of mate can occur among these parasites. Here, Louis-Albert Tchuem Tchuenté, Vaughan R. Southgate, Claude Combes and Joseph Jourdane review progress made in the understanding of the mating behaviour of schistosomes, and highlight the importance of mating systems in the dynamics of natural transmission of schistosomiasis.     

Identifying rare and common disease associated variants in genomic data using Parkinson’s disease as a model

Background

Genome-wide association studies have been successful in identifying common genetic variants for human diseases. However, much of the heritable variation associated with diseases such as Parkinson’s disease remains unknown suggesting that many more risk loci are yet to be identified. Rare variants have become important in disease association studies for explaining missing heritability. Methods for detecting this type of association require prior knowledge on candidate genes and combining variants within the region. These methods may suffer from power loss in situations with many neutral variants or causal variants with opposite effects.

Results

We propose a method capable of scanning genetic variants to identify the region most likely harbouring disease gene with rare and/or common causal variants. Our method assigns a score at each individual variant based on our scoring system. It uses aggregate scores to identify the region with disease association. We evaluate performance by simulation based on 1000 Genomes sequencing data and compare with three commonly used methods. We use a Parkinson’s disease case–control dataset as a model to demonstrate the application of our method.Our method has better power than CMC and WSS and similar power to SKAT-O with well-controlled type I error under simulation based on 1000 Genomes sequencing data. In real data analysis, we confirm the association of α-synuclein gene (SNCA) with Parkinson’s disease (p = 0.005). We further identify association with hyaluronan synthase 2 (HAS2, p = 0.028) and kringle containing transmembrane protein 1 (KREMEN1, p = 0.006). KREMEN1 is associated with Wnt signalling pathway which has been shown to play an important role for neurodegeneration in Parkinson’s disease.

Conclusions

Our method is time efficient and less sensitive to inclusion of neutral variants and direction effect of causal variants. It can narrow down a genomic region or a chromosome to a disease associated region. Using Parkinson’s disease as a model, our method not only confirms association for a known gene but also identifies two genes previously found by other studies. In spite of many existing methods, we conclude that our method serves as an efficient alternative for exploring genomic data containing both rare and common variants.

Electronic supplementary material

The online version of this article (doi:10.1186/s12929-014-0088-9) contains supplementary material, which is available to authorized users.     

A total crapshoot? Evaluating bioinformatic decisions in animal diet metabarcoding analyses

Metabarcoding studies provide a powerful approach to estimate the diversity and abundance of organisms in mixed communities in nature. While strategies exist for optimizing sample and sequence library preparation, best practices for bioinformatic processing of amplicon sequence data are lacking in animal diet studies. Here we evaluate how decisions made in core bioinformatic processes, including sequence filtering, database design, and classification, can influence animal metabarcoding results. We show that denoising methods have lower error rates compared to traditional clustering methods, although these differences are largely mitigated by removing low‐abundance sequence variants. We also found that available reference datasets from GenBank and BOLD for the animal marker gene cytochrome oxidase I (COI) can be complementary, and we discuss methods to improve existing databases to include versioned releases. Taxonomic classification methods can dramatically affect results. For example, the commonly used Barcode of Life Database (BOLD) Classification API assigned fewer names to samples from order through species levels using both a mock community and bat guano samples compared to all other classifiers (vsearch‐SINTAX and q2‐feature‐classifier's BLAST + LCA, VSEARCH + LCA, and Naive Bayes classifiers). The lack of consensus on bioinformatics best practices limits comparisons among studies and may introduce biases. Our work suggests that biological mock communities offer a useful standard to evaluate the myriad computational decisions impacting animal metabarcoding accuracy. Further, these comparisons highlight the need for continual evaluations as new tools are adopted to ensure that the inferences drawn reflect meaningful biology instead of digital artifacts.     

Protection by zinc against UVA— and UVB-induced cellular and genomic damage in vivo and in vitro

For many years, zinc salts have been used both topically and orally to treat minor burns and abrasions as well as to enhance wound repair in man and animals. In this study we describe the protective effects of zinc against UV-induced genotoxicity in vitro and against sunburn cell formation in mouse skin in vivo. Cultured skin cells from neonatal mice showed a dramatic increase in the number of micronuclei as a result of UVA and UVB irradiation. Inclusion of zinc at 5 μg/mL in the medium significantly reduced the frequency of micronuclei and of micronucleated cells. In hairless mice, topical application of zinc chloride for 5 consecutive days or a single application 2 h prior to UV exposure reduced the number of sunburn cells in the epidermis as did application of zinc 1 h after exposure. Application 2 h after irradiation also tended to have a protective effect, although there was a large variation between animals. It is proposed that an influx of zinc can protect epidermal cells against some of the more delayed effects of UV-induced damage.     

Risk attitudes and sun protection behaviour: Can behaviour be altered by using a melanoma genomic risk intervention?

Background: Exposure to ultraviolet radiation from sunlight is directly associated with melanoma skin cancer, however reducing sun-exposure can be difficult to achieve at a population level.Methods: Using a genomic risk information behaviour change trial for melanoma prevention, we classified participants as risk-seeking, risk-neutral or risk-averse for domain-specific risk taking (DOSPERT). One-way ANOVA determined the association between socio-demographic characteristics and risk-taking score, and multivariable linear regression ascertained impact of an individual’s underlying risk propensity on an objective measure of sun-exposure, standard erythemal dose (SED), at 3-months follow-up.Results: Of 119 participants, mean age 53 years; 50% males, 87% had a personal/family history of cancer; 19% were classified risk-seeking, 57% risk-neutral. The mean risk-taking score was significantly higher in younger participants (≤50 years: 13.86 vs. >50 years: 11.11, p = 0.003); and lower in those with a personal/family history of skin cancer versus without (10.55 vs 13.33, p = 0.009). Risk averse individuals had lower weekly mean SEDs at 3-months than risk neutral and risk seeking individuals (2.56, 5.81, 4.81 respectively, p = 0.01). Risk seekers showed fewer sun protective habits (p < 0.001); and higher intentional tanning, (p = 0.01). At 3-months, risk seekers attained 16%–54% lower SEDs in the genomic information group compared with controls, however this was not significantly different across risk groups (interaction p = 0.13).Conclusion: An individual’s underlying risk attitude is likely associated with sun-exposure behaviours, and may modify the effect of a genomic risk information behaviour change intervention. Young people and risk seekers may benefit most from being given information on their genetic risk of melanoma.     

Genomic islands of speciation or genomic islands and speciation?

Populations of the malaria mosquito, Anopheles gambiae, are comprised of at least two reproductively isolated, sympatric populations. In this issue, White et al. (2010) use extensive sampling, high‐density tiling microarrays, and an updated reference genome to clarify and expand our knowledge of genomic differentiation between these populations. It is now clear that DNA near the centromeres of all three chromosomes are in near‐perfect disequilibrium with each other. This is in stark contrast to the remaining 97% of the assembled genome, where fixed differences between populations have not been found, and many polymorphisms are shared. This pattern, coupled with direct evidence of hybridization in nature, supports models of “mosaic” speciation, where ongoing hybridization homogenizes variation in most of the genome while loci under strong selection remain in disequilibrium with each other. However, unambiguously demonstrating that selection maintains the association of these pericentric “speciation islands” in the face of gene flow is difficult. Low recombination at all three loci complicates the issue, and increases the probability that selection unrelated to the speciation process alters patterns of variation in these loci. Here, we discuss these different scenarios in light of this new data.     

Do highly divergent loci reside in genomic regions affecting reproductive isolation? A test using next-generation sequence data in Timema stick insects

ABSTRACT: BACKGROUND: Genetic divergence during speciation with gene flow is heterogeneous across the genome, with some regions exhibiting stronger differentiation than others. Exceptionally differentiated regions are often assumed to experience reduced introgression, i.e., reduced flow of alleles from one population into another because such regions are affected by divergent selection or cause reproductive isolation. In contrast, the remainder of the genome can be homogenized by high introgression. Although many studies have documented variation across the genome in genetic differentiation, there are few tests of this hypothesis that explicitly quantify introgression. Here, we provide such a test using 38,304 SNPs in populations of Timema cristinae stick insects. We quantify whether loci that are highly divergent between geographically separated ('allopatric') populations exhibit unusual patterns of introgression in admixed populations. To the extent this is true, highly divergent loci between allopatric populations contribute to reproductive isolation in admixed populations. RESULTS: As predicted, we find a substantial association between locus-specific divergence between allopatric populations and locus-specific introgression in admixed populations. However, many loci depart from this relationship, sometimes strongly so. We also report evidence for selection against foreign alleles due to local adaptation. CONCLUSIONS: Loci that are strongly differentiated between allopatric populations sometimes contribute to reproductive isolation in admixed populations. However, geographic variation in selection and local adaptation, in aspects of genetic architecture (such as organization of genes, recombination rate variation, number and effect size of variants contributing to adaptation, etc.), and in stochastic evolutionary processes such as drift can cause strong differentiation of loci that do not always contribute to reproductive isolation. The results have implications for the theory of 'genomic islands of speciation'.