Biology subjects

Brass, A.

Publications and source records attributed to Brass, A..

6 recordsLinked to original sources

bioRxiv2019

Hardy-Weinberg Equilibrium in the Large Scale Genomic Sequencing Era

Hardy-Weinberg Equilibrium (HWE) is used to estimate the number of homozygous and heterozygous variant carriers based on its allele frequency in populations that are not evolving. Previously, deviation from HWE in large population databases were investigated to detect genotyping errors, which can result in extreme heterozygote excess (HetExc). However, HetExc might also be a sign of natural selection since recessive disease causing variants are expected to occur less frequently in a homozygous state in the general population, but might reach high allele frequency, especially if they are advantageous, in a heterozygote state. We developed a filtering strategy to detect these variants and applied it on genome data from 137,842 individuals. We found that the main limitations of this approach were quality of genotype calls and insufficient population sizes, whereas population structure and high level of inbreeding could reduce sensitivity, but not precision, in certain populations. Nevertheless, we identified 365 HetExc variants in 326 genes, most of which were specific to African/African American populations (~84.7%). Although the majority of them were not associated with known diseases, or were classified as "benign", they were enriched in genes associated with autosomal recessive diseases. The resulting dataset also contained two known recessive disease causing variants with evidence of heterozygote advantage in the genes HBB and CFTR. Finally, we provide in silico evidence of a novel heterozygote advantageous variant in the CHD6 gene (involved in influenza virus replication). We anticipate that our approach will allow the detection of rare recessive disease causing variants in the future.

bioinformatics↗

bioRxiv2019

In silico design of a T-cell epitope vaccine candidate for parasitic helminth infection

Trichuris trichiura is a parasite that infects 500 million people worldwide, leading to colitis, growth retardation and Trichuris dysentery syndrome. There are no licensed vaccines available to prevent Trichuris infection and current treatments are of limited efficacy. Trichuris infections are linked to poverty, reducing childrens educational performance and the economic productivity of adults. We employed a systematic, multi-stage process to identify a candidate vaccine against trichuriasis based on the incorporation of selected T cell epitopes into virus-like particles. We conducted a systematic review to identify the most appropriate in silico prediction tools to predict histocompatibility complex class II (MHC-II) molecule T-cell epitopes. These tools were used to identify candidate MHC-II epitopes from predicted ORFs in the Trichuris genome, selected using inclusion and exclusion criteria. Selected epitopes were incorporated into Hepatitis B core antigen virus-like particles (VLPs). A combined VLP vaccine containing four Trichuris MHC-II T-cell epitopes stimulated dendritic cells and macrophages to produce pro-inflammatory and anti-inflammatory cytokines. The VLPs were internalized and co-localized in the antigen presenting cell lysosomes. Upon challenge infection, mice vaccinated with the VLPs+T-cell epitopes showed a significantly reduced worm burden, and mounted Trichuris-specific IgM and IgG2c antibody responses. The protection of mice by VLPs+T-cell epitopes was characterised by the production of mesenteric lymph node (MLN)-derived Th2 cytokines and goblet cell hyperplasia. Collectively our data establishes that a combination of in silico genome-based CD4+ T cell epitope prediction, combined with VLP delivery, offers a promising pipeline for the development of an effective, safe and affordable helminth vaccine. Author SummaryThe soil transmitted helminth Trichuris trichiura is a major parasite in developing countries; development of a comprehensive vaccine has been elusive. Here we used a systematic approach based on in silico identification of MHC-II T cell epitopes from genome sequences, their incorporation into a virus-like particle (VLP), characterization of the assemblies and testing in an in vivo murine infection model. Animals vaccinated with a preparation of four different VLP-antigen fusions showed significant reductions in intestinal worm burdens and associated antibody responses consistent with protection. The results suggest that a pipeline based on in silico prediction of potent MHC-II T cell epitopes, followed by incorporation into VLPs, could be a strategy which enables rapid translation into a vaccine against Trichuris trichiura.

immunology↗

bioRxiv2019

Distinct microbial communities in the murine gut are revealed by taxonomy-independent phylogenetic random forests

Gut microbiome analysis using 16S rRNA frequently focuses on summary statistics (e.g. diversity) or single taxonomic scales (e.g. Operational Taxonomic units, OTUs). This approach risks misinterpreting the phylogenetic or abundance scales of community differences (e.g. over-emphasising the role of single strains). We therefore constructed a 16S phylogenetic tree from mouse stool and colonic mucus communities. Random forest models, of all 428,234 clades, tested community differences among niches (stool versus mucus), host ages (6 versus 18 weeks), genotypes (wildtype versus colitis prone-mdr1a-/-) and social groups (co-housed siblings). Models discriminated all criteria except host genotype, where no community differences were found. Host social groups differed in abundant, low-level, taxa whereas intermediate phylogenetic and abundance scales distinguished ages and niches. Thus, treating evolutionary clades of microbes equivalently without reference to OTUs or taxonomy, clearly identifies whether and how gut microbial communities are distinct and provides a novel way to define functionally important bacteria.

microbiology↗

bioRxiv2019

Differential expression of soluble receptor for advanced glycation end-products (sRAGE) in mice susceptible or resistant to chronic colitis

AimsIdentifying the factors that contribute to chronicity in inflamed colitic tissue is not trivial. However, in mouse models of colitis, we can investigate at preclinical timepoints. We sought to validate murine Trichuris muris infection as a model for identification of factors that promote development of chronic colitis.\n\nMethodsWe compared preclinical changes in mice with a resolving immune response to T. muris (resistant) versus mice that fail to expel the worms and develop chronic colitis (susceptible). Findings were then validated in healthy controls and patients with suspected or confirmed IBD.\n\nResultsThe Receptor for Advanced Glycation End Products (Rage) was highly dysregulated between resistant and susceptible mice prior to the onset of any pathological signs. Increased soluble RAGE (sRAGE) in the serum and faeces of resistant mice correlated with reduced colitis scores. Mouse model findings were validated in a preliminary clinical study: faecal sRAGE was differentially expressed in patients with active IBD compared with IBD in remission, patients with IBD excluded or healthy controls.\n\nConclusionPre-clinical changes in mouse models can identify early pathways in the development of chronic inflammation that human studies cannot. We identified the decoy receptor sRAGE as a potential mechanism for protection against chronic inflammation in colitis in mice and humans. We propose that the RAGE pathway is clinically relevant in the onset of chronic colitis, and that further study of sRAGE in IBD may provide a novel diagnostic and therapeutic target.

immunology↗

bioRxiv2019

The transcription factor basal regulatory network of Homo sapiens and Saccharomyces cerevisiae: uncovering the relationship between topology and phenotype

Transcription factors play a key role in controlling which proteins are made by a cell. As transcription factors are themselves proteins, they are part of a complex interconnected and self-regulated network. We define the transcription factor basal regulatory network (TFBRN) as the network formed by the interactions between transcription factors (TFs) as proteins acting on target genes which are themselves TFs. The question then becomes as to whether topological features of this network are important in determining phenotypes caused by perturbations in TFs. To explore this, we developed two simple TFBRN models; one based on data from human TFs, and the other on the budding yeast. Even from this basic model we did find some very clear correlations between local topological measures and phenotypes seen in cancer and rare genetic diseases. This strongly suggests that the local network architecture of the TFBRN provides important information around the roles of transcription factors and the impacts to an organisation of their perturbation.\n\nAuthor SummaryThe human body is controlled by proteins whose production is coordinated by proteins known as transcription factors. These transcription factors can control multiple proteins, including other transcription factors. Does this network itself play any role in determining the properties of the transcription factors and their roles in cancer and disease? In this paper we find that there is a relationship between the local structures in the network and processes such as cancer and rare genetic diseases. We also found a similar relationship between local network characteristics and budding yeast phenotypes. This work therefore shows that simple properties of the network of interactions between transcription factors and their targets can be useful in determining the effects caused by changes in transcription factors (whether through deletion or allelic variation).

bioinformatics↗

bioRxiv2018

Sulforaphane Alters the Acidification of the Vacuole to Trigger Cell Death

Sulforaphane (SFN) is a compound [1-isothiocyanato-4-(methylsulfinyl)- butane] found in broccoli and other cruciferous vegetables that is currently of interest because of its potential as a chemopreventive and a chemotherapeutic drug. Recent studies in a diverse range of cellular and animal models have shown that SFN is involved in multiple intracellular signaling pathways that regulate cell death, cell cycle progression, and cell invasion. In order to better understand the mechanisms of action behind SFN-induced cell death, we undertook an unbiased genome wide screen with the yeast knockout (YKO) library to identify SFN sensitive (SFNS) mutants. Our mutants were enriched with knockouts in genes linked to vacuolar function suggesting a link between this organelle and SFNs mechanism of action in yeast. Our subsequent work revealed that SFN increases the vacuolar pH of yeast cells and that varying the vacuolar pH can alter the sensitivity of yeast cells to the drug. In fact, several mutations that lower the vacuolar pH in yeast actually made the cells resistant to SFN (SFNR). Finally, we show that human lung cancer cells with more acidic compartments are also SFNR suggesting that SFNs mechanism of action identified in yeast may carry over to higher eukaryotic cells.

cell biology↗