Randomized Trial of BCG Vaccine to Protect against Covid-19 in Health Care Workers.

BACKGROUND: The bacille Calmette-Guérin (BCG) vaccine has immunomodulatory "off-target" effects that have been hypothesized to protect against coronavirus disease 2019 (Covid-19). METHODS: In this international, double-blind, placebo-controlled trial, we randomly assigned health care workers to receive the BCG-Denmark vaccine or saline placebo and followed them for 12 months. Symptomatic Covid-19 and severe Covid-19, the primary outcomes, were assessed at 6 months; the primary analyses involved the modified intention-to-treat population, which was restricted to participants with a negative test for severe acute respiratory syndrome coronavirus 2 at baseline. RESULTS: A total of 3988 participants underwent randomization; recruitment ceased before the planned sample size was reached owing to the availability of Covid-19 vaccines. The modified intention-to-treat population included 84.9% of the participants who underwent randomization: 1703 in the BCG group and 1683 in the placebo group. The estimated risk of symptomatic Covid-19 by 6 months was 14.7% in the BCG group and 12.3% in the placebo group (risk difference, 2.4 percentage points; 95% confidence interval [CI], -0.7 to 5.5; P = 0.13). The risk of severe Covid-19 by 6 months was 7.6% in the BCG group and 6.5% in the placebo group (risk difference, 1.1 percentage points; 95% CI, -1.2 to 3.5; P = 0.34); the majority of participants who met the trial definition of severe Covid-19 were not hospitalized but were unable to work for at least 3 consecutive days. In supplementary and sensitivity analyses that used less conservative censoring rules, the risk differences were similar but the confidence intervals were narrower. There were five hospitalizations due to Covid-19 in each group (including one death in the placebo group). The hazard ratio for any Covid-19 episode in the BCG group as compared with the placebo group was 1.23 (95% CI, 0.96 to 1.59). No safety concerns were identified. CONCLUSIONS: Vaccination with BCG-Denmark did not result in a lower risk of Covid-19 among health care workers than placebo. (Funded by the Bill and Melinda Gates Foundation and others; BRACE ClinicalTrials.gov number, NCT04327206.).

Peroxisomal ß-oxidation enzyme, DECR2, regulates lipid metabolism and promotes treatment resistance in advanced prostate cancer.

BACKGROUND: Peroxisomes are central metabolic organelles that have key roles in fatty acid homoeostasis. As prostate cancer (PCa) is particularly reliant on fatty acid metabolism, we explored the contribution of peroxisomal ß-oxidation (perFAO) to PCa viability and therapy response. METHODS: Bioinformatic analysis was performed on clinical transcriptomic datasets to identify the perFAO enzyme, 2,4-dienoyl CoA reductase 2 (DECR2) as a target gene of interest. Impact of DECR2 and perFAO inhibition via thioridazine was examined in vitro, in vivo, and in clinical prostate tumours cultured ex vivo. Transcriptomic and lipidomic profiling was used to determine the functional consequences of DECR2 inhibition in PCa. RESULTS: DECR2 is upregulated in clinical PCa, most notably in metastatic castrate-resistant PCa (CRPC). Depletion of DECR2 significantly suppressed proliferation, migration, and 3D growth of a range of CRPC and therapy-resistant PCa cell lines, and inhibited LNCaP tumour growth and proliferation in vivo. DECR2 influences cell cycle progression and lipid metabolism to support tumour cell proliferation. Further, co-targeting of perFAO and standard-of-care androgen receptor inhibition enhanced suppression of PCa cell proliferation. CONCLUSION: Our findings support a focus on perFAO, specifically DECR2, as a promising therapeutic target for CRPC and as a novel strategy to overcome lethal treatment resistance.

Spatial MS multiomics on clinical prostate cancer tissues.

Mass spectrometry (MS) and MS imaging (MSI) are used extensively for both the spatial and bulk characterization of samples in lipidomics and proteomics workflows. These datasets are typically generated independently due to different requirements for sample preparation. However, modern omics technologies now provide higher sample throughput and deeper molecular coverage, which, in combination with more sophisticated bioinformatic and statistical pipelines, make generating multiomics data from a single sample a reality. In this workflow, we use spatial lipidomics data generated by matrix-assisted laser desorption/ionization MSI (MALDI-MSI) on prostate cancer (PCa) radical prostatectomy cores to guide the definition of tumor and benign tissue regions for laser capture microdissection (LCM) and bottom-up proteomics all on the same sample and using the same mass spectrometer. Accurate region of interest (ROI) mapping was facilitated by the SCiLS region mapper software and dissected regions were analyzed using a dia-PASEF workflow. A total of 5525 unique protein groups were identified from all dissected regions. Lysophosphatidylcholine acyltransferase 1 (LPCAT1), a lipid remodelling enzyme, was significantly enriched in the dissected regions of cancerous epithelium (CE) compared to benign epithelium (BE). The increased abundance of this protein was reflected in the lipidomics data with an increased ion intensity ratio for pairs of phosphatidylcholines (PC) and lysophosphatidylcholines (LPC) in CE compared to BE.

Targeting hyaluronan-mediated motility receptor (HMMR) enhances response to androgen receptor signalling inhibitors in prostate cancer.

BACKGROUND: Resistance to androgen receptor signalling inhibitors (ARSIs) represents a major clinical challenge in prostate cancer. We previously demonstrated that the ARSI enzalutamide inhibits only a subset of all AR-regulated genes, and hypothesise that the unaffected gene networks represent potential targets for therapeutic intervention. This study identified the hyaluronan-mediated motility receptor (HMMR) as a survival factor in prostate cancer and investigated its potential as a co-target for overcoming resistance to ARSIs. METHODS: RNA-seq, RT-qPCR and Western Blot were used to evaluate the regulation of HMMR by AR and ARSIs. HMMR inhibition was achieved via siRNA knockdown or pharmacological inhibition using 4-methylumbelliferone (4-MU) in prostate cancer cell lines, a mouse xenograft model and patient-derived explants (PDEs). RESULTS: HMMR was an AR-regulated factor that was unaffected by ARSIs. Genetic (siRNA) or pharmacological (4-MU) inhibition of HMMR significantly suppressed growth and induced apoptosis in hormone-sensitive and enzalutamide-resistant models of prostate cancer. Mechanistically, 4-MU inhibited AR nuclear translocation, AR protein expression and subsequent downstream AR signalling. 4-MU enhanced the growth-suppressive effects of 3 different ARSIs in vitro and, in combination with enzalutamide, restricted proliferation of prostate cancer cells in vivo and in PDEs. CONCLUSION: Co-targeting HMMR and AR represents an effective strategy for improving response to ARSIs.

Cohort profile: GRACE - a residential aged care cohort examining factors influencing antimicrobial resistance carriage.

BACKGROUND: The emergence of antimicrobial-resistant bacteria represents a considerable threat to human health, particularly for vulnerable populations such as those living in residential aged care. However, antimicrobial resistance carriage and modes of transmission remain incompletely understood. The Generating evidence on antimicrobial Resistance in the Aged Care Environment (GRACE) study was established to determine principal risk factors of antimicrobial resistance carriage and transmission in residential aged care facilities (RACFs). This article describes the cohort characteristics, national representation, and planned analyses for this study. METHODS: Between March 2019 and March 2020, 279 participants were recruited from five South Australian RACFs. The median age was 88.6 years, the median period in residence was 681 days, and 71.7% were female. A dementia diagnosis was recorded in 54.5% and more than two thirds had moderate to severe cognitive impairment (68.8%). 61% had received at least one course of antibiotics in the 12 months prior to enrolment. RESULTS: To investigate the representation of the GRACE cohort to Australians in residential aged care, its characteristics were compared to a subset of the historical cohort of the Registry of Senior Australians (ROSA). This included 142,923 individuals who were permanent residents of RACFs on June 30th, 2017. GRACE and ROSA cohorts were similar in age, sex, and duration of residential care, prevalence of health conditions, and recorded dementia diagnoses. Differences were observed in care requirements and antibiotic exposure (both higher for GRACE participants). GRACE participants had fewer hospital visits compared to the ROSA cohort, and a smaller proportion were prescribed psycholeptic medications. CONCLUSIONS: We have assembled a cohort of aged care residents that is representative of the Australian aged care population, and which provides a basis for future analyses. Metagenomic data isolated from participants and built environments will be used to determine microbiome and resistome characteristics of an individual and the facility. Individual and facility risk exposures will be aligned with metagenomic data to identify principal determinants for antimicrobial resistance carriage. Ultimately, this analysis will inform measures aimed at reducing the emergence and spread of antimicrobial resistant pathogens in this high-risk population.

Selective Transcription Factor Blockade Reduces Human Retinal Endothelial Cell Expression of Intercellular Adhesion Molecule-1 and Leukocyte Binding.

The interaction between leukocytes and cytokine-activated retinal endothelium is an initiating step in non-infectious uveitis involving the posterior eye, mediated by cell adhesion molecules. However, because cell adhesion molecules are required for immune surveillance, therapeutic interventions would ideally be employed indirectly. Using 28 primary human retinal endothelial cell isolates, this study sought to identify transcription factor targets for reducing levels of the key retinal endothelial cell adhesion molecule, intercellular adhesion molecule (ICAM)-1, and limiting leukocyte binding to the retinal endothelium. Five candidate transcription factors-C2CD4B, EGR3, FOSB, IRF1, and JUNB-were identified by differential expression analysis of a transcriptome generated from IL-1ß- or TNF-α-stimulated human retinal endothelial cells, interpreted in the context of the published literature. Further filtering involved molecular studies: of the five candidates, C2CD4B and IRF1 consistently demonstrated extended induction in IL-1ß- or TNF-α-activated retinal endothelial cells and demonstrated a significant decrease in both ICAM-1 transcript and ICAM-1 membrane-bound protein expression by cytokine-activated retinal endothelial cells following treatment with small interfering RNA. RNA interference of C2CD4B or IRF1 significantly reduced leukocyte binding in a majority of human retinal endothelial cell isolates stimulated by IL-1ß or TNF-α. Our observations suggest that the transcription factors C2CD4B and IRF1 may be potential drug targets for limiting leukocyte-retinal endothelial cell interactions in non-infectious uveitis involving the posterior eye.

Long-term perturbation of the peripheral immune system months after SARS-CoV-2 infection.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a highly infectious respiratory virus which is responsible for the coronavirus disease 2019 (COVID-19) pandemic. It is increasingly clear that recovered individuals, even those who had mild COVID-19, can suffer from persistent symptoms for many months after infection, a condition referred to as "long COVID", post-acute sequelae of COVID-19 (PASC), post-acute COVID-19 syndrome, or post COVID-19 condition. However, despite the plethora of research on COVID-19, relatively little is known about the molecular underpinnings of these long-term effects. METHODS: We have undertaken an integrated analysis of immune responses in blood at a transcriptional, cellular, and serological level at 12, 16, and 24 weeks post-infection (wpi) in 69 patients recovering from mild, moderate, severe, or critical COVID-19 in comparison to healthy uninfected controls. Twenty-one of these patients were referred to a long COVID clinic and > 50% reported ongoing symptoms more than 6 months post-infection. RESULTS: Anti-Spike and anti-RBD IgG responses were largely stable up to 24 wpi and correlated with disease severity. Deep immunophenotyping revealed significant differences in multiple innate (NK cells, LD neutrophils, CXCR3+ monocytes) and adaptive immune populations (T helper, T follicular helper, and regulatory T cells) in convalescent individuals compared to healthy controls, which were most strongly evident at 12 and 16 wpi. RNA sequencing revealed significant perturbations to gene expression in COVID-19 convalescents until at least 6 months post-infection. We also uncovered significant differences in the transcriptome at 24 wpi of convalescents who were referred to a long COVID clinic compared to those who were not. CONCLUSIONS: Variation in the rate of recovery from infection at a cellular and transcriptional level may explain the persistence of symptoms associated with long COVID in some individuals.

National Trends in Antibiotic Use in Australian Residential Aged Care Facilities, 2005-2016.

BACKGROUND: Understanding current patterns of antibiotic use in residential aged care facilities (RACFs) is essential to inform stewardship activities, but limited utilization data exist. This study examined changes in prevalence and consumption of antibiotics in Australian RACFs between 2005-2006 and 2015-2016. METHODS: This population-based, repeated cross-sectional analysis included all long-term permanent residents of Australian RACFs between July 2005 and June 2016 who were aged ≥ 65 years. The yearly prevalence rate of antibiotic use and number of defined daily doses (DDDs) of systemic antibiotics per 1000 resident-days were determined annually from linked pharmaceutical claims data. Trends were assessed using ordinary least squares regression. RESULTS: This study included 502 752 residents from 3218 RACFs, with 424.9 million resident-days analyzed. Antibiotics were dispensed on 5 608 126 occasions during the study period, of which 88% were for oral use. Cefalexin, amoxicillin-clavulanic acid, and trimethoprim were the most commonly dispensed antibiotics. The annual prevalence of antibiotic use increased from 63.8% (95% confidence interval [CI], 63.3%-64.4%) to 70.3% (95% CI, 69.9%-70.7%) between 2005-2006 and 2015-2016 (0.8% average annual increase, P < .001). There was a 39% relative increase in total consumption of systemic antibiotics, with utilization increasing from 67.6 to 93.8 DDDs/1000 resident-days during the study period (average annual increase of 2.8 DDDs/1000 resident-days, P < .001). CONCLUSIONS: This nationwide study showed substantial increases in both prevalence of use and total consumption of antibiotics in Australian RACFs between 2005 and 2016. The increasingly widespread use of antibiotics in Australian RACFs is concerning and points to a need for enhanced efforts to optimize antibiotic use in this setting.

Contribution of facility level factors to variation in antibiotic use in long-term care facilities: a national cohort study.

OBJECTIVES: To examine national variation in systemic antibiotic use in long-term care facilities (LTCFs) and identify facility characteristics associated with antibiotic utilization. METHODS: This retrospective cohort study included 312 375 residents of 2536 Australian LTCFs between 2011 and 2016. LTCFs were categorized as low, medium or high antibiotic use facilities according to tertiles of DDDs of systemic antibiotics dispensed per 1000 resident-days. Multivariable logistic regression estimated the associations between facility characteristics (ownership, size, location, medication quality indicator performance, prevalence of after-hours medical practitioner services) and antibiotic use (low versus high). RESULTS: LTCFs in the lowest and highest antibiotic use categories received a median of 54.3 (IQR 46.5-60.5) and 106.1 (IQR 95.9-122.3) DDDs/1000 resident-days, respectively. Compared with not-for-profit LTCFs in major cities, government-owned non-metropolitan LTCFs were less likely to experience high antibiotic use [adjusted OR (aOR) 0.47, 95% CI 0.24-0.91]. LTCFs with 69-99 residents were less likely to experience high antibiotic use (aOR 0.69, 95% CI 0.49-0.97) than those with 25-47 residents annually. Greater prevalence of medical practitioner services accessed after-hours was associated with high antibiotic use [aOR 1.10 (per 10% increase in after-hours services), 95% CI 1.01-1.21]. South Australian LTCFs (aOR 2.17, 95% CI 1.38-3.39) were more likely, while Queensland (0.43, 95% CI 0.30-0.62) and Western Australian (aOR 0.34, 95% CI 0.21-0.57) LTCFs were less likely to experience high antibiotic use than New South Wales LTCFs. CONCLUSIONS: Considerable facility level variation in systemic antibiotic use was observed across Australian LTCFs. Identification of facility characteristics associated with antibiotic use provides a basis for targeted stewardship initiatives.

Identification of Novel Response and Predictive Biomarkers to Hsp90 Inhibitors Through Proteomic Profiling of Patient-derived Prostate Tumor Explants.

Inhibition of the heat shock protein 90 (Hsp90) chaperone is a promising therapeutic strategy to target expression of the androgen receptor (AR) and other oncogenic drivers in prostate cancer cells. However, identification of clinically-relevant responses and predictive biomarkers is essential to maximize efficacy and treatment personalization. Here, we combined mass spectrometry (MS)-based proteomic analyses with a unique patient-derived explant (PDE) model that retains the complex microenvironment of primary prostate tumors. Independent discovery and validation cohorts of PDEs (n = 16 and 30, respectively) were cultured in the absence or presence of Hsp90 inhibitors AUY922 or 17-AAG. PDEs were analyzed by LC-MS/MS with a hyper-reaction monitoring data independent acquisition (HRM-DIA) workflow, and differentially expressed proteins identified using repeated measure analysis of variance (ANOVA; raw p value <0.01). Using gene set enrichment, we found striking conservation of the most significantly AUY922-altered gene pathways between the discovery and validation cohorts, indicating that our experimental and analysis workflows were robust. Eight proteins were selectively altered across both cohorts by the most potent inhibitor, AUY922, including TIMP1, SERPINA3 and CYP51A (adjusted p < 0.01). The AUY922-mediated decrease in secretory TIMP1 was validated by ELISA of the PDE culture medium. We next exploited the heterogeneous response of PDEs to 17-AAG in order to detect predictive biomarkers of response and identified PCBP3 as a marker with increased expression in PDEs that had no response or increased in proliferation. Also, 17-AAG treatment led to increased expression of DNAJA1 in PDEs that exhibited a cytostatic response, revealing potential drug resistance mechanisms. This selective regulation of DNAJA1 was validated by Western blot analysis. Our study establishes "proof-of-principle" that proteomic profiling of drug-treated PDEs represents an effective and clinically-relevant strategy for identification of biomarkers that associate with certain tumor-specific responses.

Transcriptional and metabolic rewiring of colorectal cancer cells expressing the oncogenic KRASG13D mutation.

BACKGROUND: Activating mutations in KRAS frequently occur in colorectal cancer (CRC) patients, leading to resistance to EGFR-targeted therapies. METHODS: To better understand the cellular reprogramming which occurs in mutant KRAS cells, we have undertaken a systems-level analysis of four CRC cell lines which express either wild type (wt) KRAS or the oncogenic KRASG13D allele (mtKRAS). RESULTS: RNAseq revealed that genes involved in ribosome biogenesis, mRNA translation and metabolism were significantly upregulated in mtKRAS cells. Consistent with the transcriptional data, protein synthesis and cell proliferation were significantly higher in the mtKRAS cells. Targeted metabolomics analysis also confirmed the metabolic reprogramming in mtKRAS cells. Interestingly, mtKRAS cells were highly transcriptionally responsive to EGFR activation by TGFα stimulation, which was associated with an unexpected downregulation of genes involved in a range of anabolic processes. While TGFα treatment strongly activated protein synthesis in wtKRAS cells, protein synthesis was not activated above basal levels in the TGFα-treated mtKRAS cells. This was likely due to the defective activation of the mTORC1 and other pathways by TGFα in mtKRAS cells, which was associated with impaired activation of PKB signalling and a transient induction of AMPK signalling. CONCLUSIONS: We have found that mtKRAS cells are substantially rewired at the transcriptional, translational and metabolic levels and that this rewiring may reveal new vulnerabilities in oncogenic KRAS CRC cells that could be exploited in future.

DyNet: visualization and analysis of dynamic molecular interaction networks.

UNLABELLED: : The ability to experimentally determine molecular interactions on an almost proteome-wide scale under different conditions is enabling researchers to move from static to dynamic network analysis, uncovering new insights into how interaction networks are physically rewired in response to different stimuli and in disease. Dynamic interaction data presents a special challenge in network biology. Here, we present DyNet, a Cytoscape application that provides a range of functionalities for the visualization, real-time synchronization and analysis of large multi-state dynamic molecular interaction networks enabling users to quickly identify and analyze the most 'rewired' nodes across many network states. AVAILABILITY AND IMPLEMENTATION: DyNet is available at the Cytoscape (3.2+) App Store (http://apps.cytoscape.org/apps/dynet). CONTACT: david.lynn@sahmri.com SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

HiQuant: Rapid Postquantification Analysis of Large-Scale MS-Generated Proteomics Data.

Recent advances in mass-spectrometry-based proteomics are now facilitating ambitious large-scale investigations of the spatial and temporal dynamics of the proteome; however, the increasing size and complexity of these data sets is overwhelming current downstream computational methods, specifically those that support the postquantification analysis pipeline. Here we present HiQuant, a novel application that enables the design and execution of a postquantification workflow, including common data-processing steps, such as assay normalization and grouping, and experimental replicate quality control and statistical analysis. HiQuant also enables the interpretation of results generated from large-scale data sets by supporting interactive heatmap analysis and also the direct export to Cytoscape and Gephi, two leading network analysis platforms. HiQuant may be run via a user-friendly graphical interface and also supports complete one-touch automation via a command-line mode. We evaluate HiQuant's performance by analyzing a large-scale, complex interactome mapping data set and demonstrate a 200-fold improvement in the execution time over current methods. We also demonstrate HiQuant's general utility by analyzing proteome-wide quantification data generated from both a large-scale public tyrosine kinase siRNA knock-down study and an in-house investigation into the temporal dynamics of the KSR1 and KSR2 interactomes. Download HiQuant, sample data sets, and supporting documentation at http://hiquant.primesdb.eu .

Using biological networks to integrate, visualize and analyze genomics data.

Network biology is a rapidly developing area of biomedical research and reflects the current view that complex phenotypes, such as disease susceptibility, are not the result of single gene mutations that act in isolation but are rather due to the perturbation of a gene's network context. Understanding the topology of these molecular interaction networks and identifying the molecules that play central roles in their structure and regulation is a key to understanding complex systems. The falling cost of next-generation sequencing is now enabling researchers to routinely catalogue the molecular components of these networks at a genome-wide scale and over a large number of different conditions. In this review, we describe how to use publicly available bioinformatics tools to integrate genome-wide 'omics' data into a network of experimentally-supported molecular interactions. In addition, we describe how to visualize and analyze these networks to identify topological features of likely functional relevance, including network hubs, bottlenecks and modules. We show that network biology provides a powerful conceptual approach to integrate and find patterns in genome-wide genomic data but we also discuss the limitations and caveats of these methods, of which researchers adopting these methods must remain aware.

A genome-wide association study for genetic susceptibility to Mycobacterium bovis infection in dairy cattle identifies a susceptibility QTL on chromosome 23.

BACKGROUND: Bovine tuberculosis (bTB) infection in cattle is a significant economic concern in many countries, with annual costs to the UK and Irish governments of approximately €190 million and €63 million, respectively, for bTB control. The existence of host additive and non-additive genetic components to bTB susceptibility has been established. METHODS: Two approaches i.e. single-SNP (single nucleotide polymorphism) regression and a Bayesian method were applied to genome-wide association studies (GWAS) using high-density SNP genotypes (n = 597,144 SNPs) from 841 dairy artificial insemination (AI) sires. Deregressed estimated breeding values for bTB susceptibility were used as the quantitative dependent variable. Network analysis was performed using the quantitative trait loci (QTL) that were identified as significant in the single-SNP regression and Bayesian analyses separately. In addition, an identity-by-descent analysis was performed on a subset of the most prolific sires in the dataset that showed contrasting prevalences of bTB infection in daughters. RESULTS: A significant QTL region was identified on BTA23 (P value >1 × 10(-5), Bayes factor >10) across all analyses. Sires with the minor allele (minor allele frequency = 0.136) for this QTL on BTA23 had estimated breeding values that conferred a greater susceptibility to bTB infection than those that were homozygous for the major allele. Imputation of the regions that flank this QTL on BTA23 to full sequence indicated that the most significant associations were located within introns of the FKBP5 gene. CONCLUSIONS: A genomic region on BTA23 that is strongly associated with host susceptibility to bTB infection was identified. This region contained FKBP5, a gene involved in the TNFα/NFκ-B signalling pathway, which is a major biological pathway associated with immune response. Although there is no study that validates this region in the literature, our approach represents one of the most powerful studies for the analysis of bTB susceptibility to date.

Integrated analysis of the local and systemic changes preceding the development of post-partum cytological endometritis.

BACKGROUND: The regulation of endometrial inflammation has important consequences for the resumption of bovine fertility postpartum. All cows experience bacterial influx into the uterus after calving; however a significant proportion fail to clear infection leading to the development of cytological endometritis (CE) and compromised fertility. We hypothesised that early immunological changes could not only act as potential prognostic biomarkers for the subsequent development of disease but also shed light on the pathogenesis of endometritis in the postpartum dairy cow. METHODS: Endometrial biopsy RNA was extracted from 15 cows at 7 and 21 days postpartum (DPP), using the Qiagen RNeasy(®) Plus Mini kit and quality determined using an Agilent 2100 bioanalyser. Disease status was determined by histpathology based on inflammatory cell infiltrate. RNA-seq of both mRNA and miRNA libraries were performed on an Illumina® HiSeq(™) 2000. Paired reads were aligned to the bovine genome with Bowtie2 and differentially expressed genes were identified using EdgeR. Significantly over-represented Gene Ontology terms were identified using GO-seq, and pathway analysis was performed using KEGG. Quanititative real-time PCR was also performed for validation (ABI 7500 fast). Haematology was assessed using an automated ADVIA 2120 analyser. Serum proteins were evaluated by ELISA and metabolite analysis was performed using a Beckman Coulter AU 400 clinical analyser. Terminal-restriction fragment length polymorphism (T-RFLP) was used to obtain fingerprints of the microbial communities present. RESULTS: Next-generation sequencing from endometrial biopsies taken at 7 DPP identified significant induction of inflammatory gene expression in all cows. Despite the common inflammatory profile and enrichment of the Toll-like receptor and NFκB pathways, 73 genes and 31 miRNAs were significantly differentially expressed between healthy cows (HC, n = 9) and cows which subsequently developed CE at 7 DPP (n = 6, FDR < 0.1). While significant differential expression of 4197 genes in the transcriptome of healthy cows between 7 and 21 DPP showed the transition from a proinflammatory to tissue profliferation and repair, only 31 genes were differentially expressed in cows with CE (FDR < 0.1), indicating the arrest of such a transition. A link betwene the dysregulated inflammatory response and the composition of the uterine microbial communities was suggested by the presence of significant differences in uterine bacterial tRFLP profiles between HC and CE groups. Furthermore, inflammatory activity was not confined to the uterus; decreased circulating granulocytes and increased Acute Phase Protein (SAA and HP) expression levels were detected in plasma at 7 DPP in cows that developed CE. CONCLUSION: Our data suggests that the IL1 and IL17 inflammatory cascade activated early postpartum is resolved thereby restoring homeostasis in healthy cows by 21 DPP, but this transition fails to occur in cows which develop CE. Despite a common early inflammatory profile, elevated and differential expression of specific immune genes may identify cows at risk of prolonged inflammation and the development of CE postpartum.

Protein interaction data curation: the International Molecular Exchange (IMEx) consortium.

The International Molecular Exchange (IMEx) consortium is an international collaboration between major public interaction data providers to share literature-curation efforts and make a nonredundant set of protein interactions available in a single search interface on a common website (http://www.imexconsortium.org/). Common curation rules have been developed, and a central registry is used to manage the selection of articles to enter into the dataset. We discuss the advantages of such a service to the user, our quality-control measures and our data-distribution practices.

InnateDB: systems biology of innate immunity and beyond--recent updates and continuing curation.

InnateDB (http://www.innatedb.com) is an integrated analysis platform that has been specifically designed to facilitate systems-level analyses of mammalian innate immunity networks, pathways and genes. In this article, we provide details of recent updates and improvements to the database. InnateDB now contains >196 000 human, mouse and bovine experimentally validated molecular interactions and 3000 pathway annotations of relevance to all mammalian cellular systems (i.e. not just immune relevant pathways and interactions). In addition, the InnateDB team has, to date, manually curated in excess of 18 000 molecular interactions of relevance to innate immunity, providing unprecedented insight into innate immunity networks, pathways and their component molecules. More recently, InnateDB has also initiated the curation of allergy- and asthma-related interactions. Furthermore, we report a range of improvements to our integrated bioinformatics solutions including web service access to InnateDB interaction data using Proteomics Standards Initiative Common Query Interface, enhanced Gene Ontology analysis for innate immunity, and the availability of new network visualizations tools. Finally, the recent integration of bovine data makes InnateDB the first integrated network analysis platform for this agriculturally important model organism.

The miRNAome of the postpartum dairy cow liver in negative energy balance.

BACKGROUND: Negative energy balance (NEB) is an altered metabolic state in high yielding cows that occurs during the first few weeks postpartum when energy demands for lactation and maintenance exceed the energy supply from dietary intake. NEB can, in turn, lead to metabolic disorders and to reduced fertility. Alterations in the expression of more than 700 hepatic genes have previously been reported in a study of NEB in postpartum dairy cows. miRNAs (microRNA) are known to mediate many alterations in gene expression post transcriptionally. To study the hepatic miRNA content of postpartum dairy cows, including their overall abundance and differential expression, in mild NEB (MNEB) and severe NEB (SNEB), short read RNA sequencing was carried out. To identify putative targets of differentially expressed miRNAs among differentially expressed hepatic genes reported previously in dairy cows in SNEB computational target identification was employed. RESULTS: Our results indicate that the dairy cow liver expresses 53 miRNAs at a lower threshold of 10 reads per million. Of these, 10 miRNAs accounted for greater than 95% of the miRNAome (miRNA content). Of the highly expressed miRNAs, miR-122 constitutes 75% followed by miR-192 and miR-3596. Five out of thirteen let-7 miRNA family members are also among the highly expressed miRNAs. miR-143, down-regulated in SNEB, was found to have 4 putative up-regulated gene targets associated with SNEB including LRP2 (low density lipoprotein receptor-related protein 2), involved in lipid metabolism and up-regulated in SNEB. CONCLUSIONS: This is the first liver miRNA-seq profiling study of moderate yielding dairy cows in the early postpartum period. Tissue specific miR-122 and liver enriched miR-192 are two of the most abundant miRNAs in the postpartum dairy cow liver. miR-143 is significantly down-regulated in SNEB and putative targets of miRNA-143 which are up-regulated in SNEB, include a gene involved in lipid metabolism.