Explore the vast range of titles available.

Findings from gut microbiome studies are strongly influenced by both experimental and analytical factors that can unintentionally bias their interpretation. Environment is also critical. Both co-housing and maternal effects are expected to affect microbiomes and have the potential to confound other manipulated factors, such as genetics. We therefore analysed microbiome data from a mouse experiment using littermate controls and tested differences among genotypes (wildtype versus colitis prone- mdr1a −/− ), gut niches (stool versus mucus), host ages (6 versus 18 weeks), social groups (co-housed siblings of different genotypes) and maternal influence. We constructed a 16S phylogenetic tree from bacterial communities, fitting random forest models using all 428,234 clades identified. 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, a carefully controlled experiment treating evolutionary clades of microbes equivalently without reference to taxonomy, clearly identifies whether and how gut microbial communities are distinct across ecologically important factors (niche and host age) and other experimental factors, notably cage effects and maternal influence. These findings highlight the importance of considering such environmental factors in future microbiome studies.

Background: In clinical genomics, sharing of rare genetic disease information between genetic databases and laboratories is essential to determine the pathogenic significance of variants to enable the diagnosis of rare genetic diseases. Significant concerns regarding data governance and security have reduced this sharing in practice. Blockchain could provide a secure method for sharing genomic data between involved parties and thus help overcome some of these issues. Objective: This study aims to contribute to the growing knowledge of the potential role of blockchain technology in supporting the sharing of clinical genomic data by describing blockchain-based dynamic consent architecture to support clinical genomic data sharing and provide a proof-of-concept implementation, called ConsentChain, for the architecture to explore its performance. Methods: The ConsentChain requirements were captured from a patient forum to identify security and consent concerns. The ConsentChain was developed on the Ethereum platform, in which smart contracts were used to model the actions of patients, who may provide or withdraw consent to share their data; the data creator, who collects and stores patient data; and the data requester, who needs to query and access the patient data. A detailed analysis was undertaken of the ConsentChain performance as a function of the number of transactions processed by the system. Results: We describe ConsentChain, a blockchain-based system that provides a web portal interface to support clinical genomic sharing. ConsentChain allows patients to grant or withdraw data requester access and allows data requesters to query and submit access to data stored in a secure off-chain database. We also developed an ontology model to represent patient consent elements into machine-readable codes to automate the consent and data access processes. Conclusions: Blockchains and smart contracts can provide an efficient and scalable mechanism to support dynamic consent functionality and address some of the barriers that inhibit genomic data sharing. However, they are not a complete answer, and a number of issues still need to be addressed before such systems can be deployed in practice, particularly in relation to verifying user credentials.

Background Dendritic cells (DCs) play a key role in shaping T cell responses. To do this, DCs must be able to migrate to the site of the infection and the lymph nodes to prime T cells and initiate the appropriate immune response. Integrins such as β 2 integrin play a key role in leukocyte adhesion, migration, and cell activation. However, the role of β 2 integrin in DC migration and function in the context of infection-induced inflammation in the gut is not well understood. This study looked at the role of β 2 integrin in DC migration and function during infection with the nematode worm Trichuris muris . Itgb2 tm1Bay mice lacking functional β 2 integrin and WT littermate controls were infected with T. muris and the response to infection and kinetics of the DC response was assessed. Results In infection, the lack of functional β 2 integrin significantly reduced DC migration to the site of infection but not the lymph nodes. The lack of functional β 2 integrin did not negatively impact T cell activation in response to T. muris infection. Conclusions This data suggests that β 2 integrins are important in DC recruitment to the infection site potentially impacting the initiation of innate immunity but is dispensible for DC migration to lymph nodes and T cell priming in the context of T. muris 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 children's 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). Bone marrow-derived dendritic cells and bone marrow-derived macrophages responded in vitro to VLPs irrespective of whether the VLP also included T-cell epitopes. 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.

Inflammatory bowel disease (IBD) is associated with an inappropriate immune response to the gut microbiota. Notably, patients with IBD reportedly have alterations in fecal microbiota. However, the colonic microbiota occupies both the gut lumen and the mucus covering the epithelium. Thus, information about mucus-resident microbiota fails to be conveyed in the routine microbiota analyses of stool samples. Further, studies analyzing microbiota in IBD have mainly focused on stool samples taken after onset of inflammation. Our objective was to investigate both temporal and spatial changes in colonic microbiota communities preceding the onset of colitis.MethodsWe studied mucus and stool microbiota using a spontaneous model of colitis, the mdr1a−/− mouse, and their respective wild-type littermate controls in a time series mode.ResultsUsing this approach we have shown that microbial dysbiosis was evident in the mucus but not stools, with reduced abundance of Clostridiales evident in the mucus but not stools, of colitis-prone mice mdr1a−/−- mice 12 weeks before the onset of detectable inflammation. This altered microbial composition was coupled with a significantly thinner mucus layer. On emergence of inflammation, dysbiosis was evident in the stools and at this time point, the spatial segregation between microbiota and host tissue was also disrupted, correlating with worsened inflammation. Our results reveal that microbial dysbiosis is detectable before changes in the stools. Importantly, dysbiosis in the mucus layer preceded development of colitis.ConclusionsOur data reveal the importance of mucus sampling for understanding the underlying etiology of IBD and fundamental processes underlying disease progression.

Data journey modeling is a methodology used to establish a high-level overview of information technology (IT) infrastructure in health care systems. It allows a better understanding of sociotechnical barriers and thus informs meaningful digital transformation. Kidney transplantation is a complex clinical service involving multiple specialists and providers. The referral pathway for a transplant requires the centralization of patient data across multiple IT solutions and health care organizations. At present, there is a poor understanding of the role of IT in this process, specifically regarding the management of patient data, clinical communication, and workflow support. To apply data journey modeling to better understand interoperability, data access, and workflow requirements of a regional multicenter kidney transplant service. An incremental methodology was used to develop the data journey model. This included review of service documents, domain expert interviews, and iterative modeling sessions. Results were analyzed based on the LOAD (landscape, organizations, actors, and data) framework to provide a meaningful assessment of current data management challenges and inform ways for IT to overcome these challenges. Results were presented as a diagram of the organizations (n=4), IT systems (n>9), actors (n>4), and data journeys (n=0) involved in the transplant referral pathway. The diagram revealed that all movement of data was dependent on actor interaction with IT systems and manual transcription of data into Microsoft Word (Microsoft, Inc) documents. Each actor had between 2 and 5 interactions with IT systems to capture all relevant data, a process that was reported to be time consuming and error prone. There was no interoperability within or across organizations, which led to delays as clinical teams manually transferred data, such as medical history and test results, via post or email. Overall, data journey modeling demonstrated that human actors, rather than IT systems, formed the central focus of data movement. The IT landscape did not complement this workflow and exerted a significant administrative burden on clinical teams. Based on this study, future solutions must consider regional interoperability and specialty-specific views of data to support multi-organizational clinical services such as transplantation.

How do organisms respond adaptively to environmental stress? Although some gene-specific responses have been explored, others remain to be identified, and there is a very poor understanding of the system-wide integration of response, particularly in complex, multitissue animals. Here, we adopt a transcript screening approach to explore the mechanisms underpinning a major, whole-body phenotypic transition in a vertebrate animal that naturally experiences extreme environmental stress. Carp were exposed to increasing levels of cold, and responses across seven tissues were assessed by using a microarray composed of 13,440 cDNA probes. A large set of unique cDNAs (≈3,400) were affected by cold. These cDNAs included an expression signature common to all tissues of 252 up-regulated genes involved in RNA processing, translation initiation, mitochondrial metabolism, proteasomal function, and modification of higher-order structures of lipid membranes and chromosomes. Also identified were large numbers of transcripts with highly tissue-specific patterns of regulation. By unbiased profiling of gene ontologies, we have identified the distinctive functional features of each tissue's response and integrate them into a comprehensive view of the whole-body transition from one strongly adaptive phenotype to another. This approach revealed an expression signature suggestive of atrophy in cooled skeletal muscle. This environmental genomics approach by using a well studied but nongenomic species has identified a range of candidate genes endowing thermotolerance and reveals a previously unrecognized scale and complexity of responses that impacts at the level of cellular and tissue function.

Myoglobin (Myg) is an oxygen-binding hemoprotein that is widely thought to be expressed exclusively in oxidative skeletal and cardiac myocytes, where it plays a key role in coping with chronic hypoxia. We now show in a hypoxia-tolerant fish model, that Myg is also expressed in a range of other tissues, including liver, gill, and brain. Moreover, expression of Myg transcript was substantially enhanced during chronic hypoxia, the fold-change induction being far greater in liver than muscle. By using 2D gel electrophoresis, we have confirmed that liver expresses a protein corresponding to the Myg-1 transcript and that it is significantly up-regulated during hypoxia. We have also discovered a second, unique Myg isoform, distinct from neuroglobin, which is expressed exclusively in the neural tissue but whose transcript expression was unaffected by environmental hypoxia. Both observations of nonmuscle expression and a brain-specific isoform are unprecedented, indicating that Myg may play a much wider role than previously understood and that Myg might function in the protection of tissues from deep hypoxia and ischemia as well as in reoxygenation and reperfusion injury.

With large-scale population sequencing projects gathering pace, there is a need for strategies that advance disease gene prioritization 1 , 2 . Metrics that provide information about a gene and its ability to tolerate protein-altering variation can aid in clinical interpretation of human genomes and can advance disease gene discovery 1 – 4 . Previous reported methods analyzed the total variant load in a gene 1 – 4 , but did not analyze the distribution pattern of variants within a gene. Using data from 138,632 exome and genome sequences 2 , we developed gene variation intolerance rank (GeVIR), a continuous gene-level metric for 19,361 genes that is able to prioritize both dominant and recessive Mendelian disease genes 5 , that outperforms missense constraint metrics 3 and that is comparable—but complementary—to loss-of-function (LOF) constraint metrics 2 . GeVIR is also able to prioritize short genes, for which LOF constraint cannot be estimated with confidence 2 . The majority of the most intolerant genes identified here have no defined phenotype and are candidates for severe dominant disorders. GeVIR is a continuous gene-level metric that uses variant distribution patterns to prioritize both dominant and recessive Mendelian disease genes. GeVIR outperforms missense constraint metrics and complements loss-of-function constraint metrics.

The African buffalo, Syncerus caffer, is one of the most abundant and ecologically important species of megafauna in the savannah ecosystem. It is an important prey species, as well as a host for a vast array of nematodes, pathogens and infectious diseases, such as bovine tuberculosis and corridor disease. Large-scale SNP discovery in this species would greatly facilitate further research into the area of host genetics and disease susceptibility, as well as provide a wealth of sequence information for other conservation and genomics studies. We sequenced pools of Cape buffalo DNA from a total of 9 animals, on an ABI SOLiD4 sequencer. The resulting short reads were mapped to the UMD3.1 Bos taurus genome assembly using both BWA and Bowtie software packages. A mean depth of 2.7× coverage over the mapped regions was obtained. Btau4 gene annotation was added to all SNPs identified within gene regions. Bowtie and BWA identified a maximum of 2,222,665 and 276,847 SNPs within the buffalo respectively, depending on analysis method. A panel of 173 SNPs was validated by fluorescent genotyping in 87 individuals. 27 SNPs failed to amplify, and of the remaining 146 SNPs, 43-54% of the Bowtie SNPs and 57-58% of the BWA SNPs were confirmed as polymorphic. dN/dS ratios found no evidence of positive selection, and although there were genes that appeared to be under negative selection, these were more likely to be slowly evolving house-keeping genes.