The 3Ranker: An AI-based Algorithm for Finding Non-animal Alternative Methods

The search for existing non-animal alternative methods for use in experiments is currently challenging because of the lack of both comprehensive structured databases and balanced keyword-based search strategies to mine unstructured textual databases. In this paper we describe 3Ranker, which is a fast, keyword-independent algorithm for finding non-animal alternative methods for use in biomedical research. The 3Ranker algorithm was created by using a machine learning approach, consisting of a Random Forest model built on a dataset of 35 million abstracts and constructed with weak supervision, followed by iterative model improvement with expert curated data. We found a satisfactory trade-off between sensitivity and specificity, with Area Under the Curve (AUC) values ranging from 0.85-0.95. Trials showed that the AI-based classifier was able to identify articles that describe potential alternatives to animal use, among the thousands of articles returned by generic PubMed queries on dermatitis and Parkinson's disease. Application of the classification models on time series data showed the earlier implementation and acceptance of Three Rs principles in the area of cosmetics and skin research, as compared to the area of neurodegenerative disease research. The 3Ranker algorithm is freely available at www.open3r.org; the future goal is to expand this framework to cover multiple research domains and to enable its broad use by researchers, policymakers, funders and ethical review boards, in order to promote the replacement of animal use in research wherever possible.

Nailfold capillaroscopy and candidate-biomarker levels in systemic sclerosis-associated pulmonary hypertension: A cross-sectional study

Objectives

Pulmonary hypertension is one of the leading causes of death in systemic sclerosis. Early detection and treatment of pulmonary hypertension in systemic sclerosis is crucial. Nailfold capillaroscopy microscopy, vascular autoantibodies AT1R and ETAR, and several candidate-biomarkers have the potential to serve as noninvasive tools to identify systemic sclerosis patients at risk for developing pulmonary hypertension. Here, we explore the classifying potential of nailfold capillaroscopy microscopy characteristics and serum levels of selected candidate-biomarkers in a sample of systemic sclerosis patients with and without different forms of pulmonary hypertension.

Methods

A total of 81 consecutive systemic sclerosis patients were included, 40 with systemic sclerosis pulmonary hypertension and 41 with no pulmonary hypertension. In each group, quantitative and qualitative nailfold capillaroscopy microscopy characteristics, vascular autoantibodies AT1R and ETAR, and serum levels of 24 soluble serum factors were determined. For evaluation of the nailfold capillaroscopy microscopy characteristics, linear regression analysis accounting for age, sex, and diffusing capacity of the lungs for carbon monoxide percentage predicted was used. Autoantibodies and soluble serum factor levels were compared using two-sample t test with equal variances.

Results

No statistically significant differences were observed in quantitative or qualitative nailfold capillaroscopy microscopy characteristics, or vascular autoantibody ETAR and AT1R titer between systemic sclerosis-pulmonary hypertension and systemic sclerosis-no pulmonary hypertension. In contrast, several serum levels of soluble factors differed between groups: Endostatin, sVCAM, and VEGFD were increased, and CXCL4, sVEGFR2, and PDGF-AB/BB were decreased in systemic sclerosis-pulmonary hypertension. Random forest classification identified Endostatin and CXCL4 as the most predictive classifiers to distinguish systemic sclerosispulmonary hypertension from systemic sclerosis-no pulmonary hypertension.

Conclusion

This study shows the potential for several soluble serum factors to distinguish systemic sclerosis-pulmonary hypertension from systemic sclerosis-no pulmonary hypertension. We found no classifying potential for qualitative or quantitative nailfold capillaroscopy microscopy characteristics, or vascular autoantibodies.

A proteomics approach to identify COPD-related changes in lung fibroblasts

BACKGROUND

Lung fibroblasts are implicated in abnormal tissue repair in chronic obstructive pulmonary disease (COPD). The exact mechanisms are unknown and comprehensive analysis comparing COPD- and control fibroblasts is lacking.

AIM

To gain insight in the role of lung fibroblasts in COPD pathology using unbiased proteomic and transcriptomic analysis.

METHODS

Protein and RNA was isolated from cultured parenchymal lung fibroblasts of 17 stage IV COPD patients and 16 non-COPD controls. Proteins were analyzed using LC-MS/MS and RNA through RNA sequencing. Differential protein and gene expression in COPD was assessed via linear regression, followed by pathway enrichment, correlation analysis and immunohistological staining in lung tissue. Proteomic and transcriptomic data was compared to investigate the overlap and correlation between both levels of data.

RESULTS

We identified 40 differentially expressed (DE) proteins and zero DE genes between COPD and control fibroblasts. The most significant DE proteins were HNRNPA2B1 and FHL1. Thirteen of the 40 proteins were previously associated with COPD, including FHL1 and GSTP1. Six of the 40 proteins were related to telomere maintenance pathways, and were positively correlated with the senescence marker LMNB1. No significant correlation between gene and protein expression was observed for the 40 proteins.

CONCLUSIONS

The 40 DE proteins in COPD fibroblasts include previously described COPD proteins (FHL1, GSTP1) and new COPD research targets like HNRNPA2B1. Lack of overlap and correlation between gene and protein data supports the use of unbiased proteomics analysis and indicates that different types of information are generated with both methods.

Maternal pre-pregnancy overweight and neonatal gut bacterial colonization are associated with cognitive development and gut microbiota composition in pre-school-age offspring

Maternal gestational obesity is a risk factor for offspring's neurodevelopment and later neuro-cognitive disorders. Altered gut microbiota composition has been found in patients with neurocognitive disorders, and in relation to maternal metabolic health. We explored the associations between gut microbiota and cognitive development during infancy, and their link with maternal obesity. In groups of children from the Pisa birth Cohort (PISAC), we analysed faecal microbiota composition by 16S rRNA marker gene sequencing of first-pass meconium samples and of faecal samples collected at age 3, 6, 12, 24, 36 months, and its relationship with maternal gestational obesity or diabetes, and with cognitive development, as measured from 6 to 60 months of age by the Griffith's Mental Development Scales. Gut microbiota composition in the first phases of life is dominated by Bifidobacteria (Actinobacteria phylum), with contribution of Escherichia/Shigella and Klebsiella genera (Proteobacteria phylum), whereas Firmicutes become more dominant at 36 months of age. Maternal overweight leads to lower abundance of Bifidobacterium, Blautia and Ruminococcus, and lower practical reasoning scores in the offspring at the age of 36 months. In the whole population, microbiota in the first-pass meconium samples shows much higher alpha diversity compared to later samples, and its composition, particularly Bifidobacterium and Veillonella abundances, correlates with practical reasoning scores at 60 months of age. Maternal overweight correlates with bacterial colonization and with the development of reasoning skills at pre-school age. Associations between neonatal gut colonization and later cognitive function provide new perspectives of primary (antenatal) prevention of neurodevelopmental disorders.

Blood-Based Immune Profiling Combined with Machine Learning Discriminates Psoriatic Arthritis from Psoriasis Patients

Psoriasis (Pso) is a chronic inflammatory skin disease, and up to 30% of Pso patients develop psoriatic arthritis (PsA), which can lead to irreversible joint damage. Early detection of PsA in Pso patients is crucial for timely treatment but difficult for dermatologists to implement. We, therefore, aimed to find disease-specific immune profiles, discriminating Pso from PsA patients, possibly facilitating the correct identification of Pso patients in need of referral to a rheumatology clinic. The phenotypes of peripheral blood immune cells of consecutive Pso and PsA patients were analyzed, and disease-specific immune profiles were identified via a machine learning approach. This approach resulted in a random forest classification model capable of distinguishing PsA from Pso (mean AUC = 0.95). Key PsA-classifying cell subsets selected included increased proportions of differentiated CD4+CD196+CD183-CD194+ and CD4+CD196-CD183-CD194+ T-cells and reduced proportions of CD196+ and CD197+ monocytes, memory CD4+ and CD8+ T-cell subsets and CD4+ regulatory T-cells. Within PsA, joint scores showed an association with memory CD8+CD45RA-CD197- effector T-cells and CD197+ monocytes. To conclude, through the integration of in-depth flow cytometry and machine learning, we identified an immune cell profile discriminating PsA from Pso. This immune profile may aid in timely diagnosing PsA in Pso.

Autoantibody profiles in systemic sclerosis; a comparison of diagnostic tests

OBJECTIVES

Autoimmune antibody profiling plays a prominent role in both classification and prognosis of systemic sclerosis (SSc). In the last years novel autoantibodies have been discovered and have become available in diagnostic assays. However, standardization in autoimmune serology is lacking, which may have a negative impact on the added value of autoantibodies in diagnosis and prognosis of SSc. In this paper we describe the comparison of commercially available diagnostic assays for the detection of SSc-associated autoantibodies and explored the coexistence of multiple SSc-associated autoantibodies within patients.

METHODS

Serum samples of 347 patients from the Nijmegen Systemic Sclerosis Cohort were included in this study. All patients fulfilled the ACR/EULAR 2013 classification criteria for SSc and were classified as DcSSc or LcSSc according to the Leroy and Medsger criteria. All samples were evaluated on standard laboratory diagnostic tests for detection of SSc-specific autoantibodies CENPA and CENPB (ACA), Scl-70 (ATA), RNA Polymerase III (rp11/155) (ARA), and SSc-associated autoantibodies Fibrillarin, Th-To, PM-scl75, PM-Scl100, RNP68/A/C, Ku, NOR90, and PDGFR from suppliers EUROIMMUN, D-tek and Thermo Fisher Scientific.

RESULTS

We found that 79% of the patients was positive for one or more of the SSc autoantibodies. Overall, a high agreement was observed between the diagnostic methods for the SSC-specific autoantibodies listed in the ACR/EULAR criteria (ATA, ACA, and ARA) (Cohen's kappa 0.53-0.97). However, a lower agreement was found for SSc-associated autoantibodies PM-Scl, and Ku, as well as for the SSc-specific autoantibodies fibrillarin and Th-To. Furthermore, the data revealed that the presence of ATA, ARA and ACA is predominantly mutually exclusive, with only a fraction of the patients testing positive for both ATA and ARA.

CONCLUSION

Our data showed high concordance of prevalent SSc-specific autoantibodies between different diagnostic assays. Further standardisation for low prevalent SSc-specific and SSc-associated autoantibodies is needed.

Downregulation of synapse-associated protein expression and loss of homeostatic microglial control in cerebrospinal fluid of infectious patients with delirium and patients with Alzheimer's disease

Delirium is a complex and multifactorial condition associated with long-term cognitive decline. Due to the strong links between systemic inflammation, delirium and dementia we hypothesized that responses within the brain in patients who develop delirium could show biochemical overlap with patients with Alzheimer's disease (AD). In this observational study we analyzed protein expression signatures in cerebrospinal fluid (CSF) from 15 patients with infectious delirium and compared these to 29 patients with AD, 30 infectious patients without delirium and 15 non-infectious controls free of neurological disease. A proximity extension assay was performed measuring a total of 184 inflammatory and neurology-related proteins. Eight inflammatory proteins (4%), including the key neuron-microglia communication marker CX3CL1 (fractalkine), were significantly upregulated in both delirium and AD, compared to infectious patients without delirium. Likewise, 23 proteins (13%) showed downregulation in both delirium and AD, relative to infectious patients without delirium, which interestingly included CD200R1, another neuron-microglia communication marker, as well as a cluster of proteins related to synapse formation and function. Synaptopathy is an early event in AD and correlates strongly with cognitive dysfunction. These results were partially mediated by aging, which is an important predisposing risk factor among many others for both conditions. Within this study we report the first in vivo human evidence suggesting that synapse pathology and loss of homeostatic microglial control is involved in the pathophysiology of both infectious delirium and AD and thus may provide a link for the association between infections, delirium and long-term cognitive decline.

Live Biotherapeutic Products, A Road Map for Safety Assessment

Recent developments in the understanding of the relationship between the microbiota and its host have provided evidence regarding the therapeutic potential of selected microorganisms to prevent or treat disease. According to Directive 2001/83/EC, in the European Union (EU), any product intended to prevent or treat disease is defined as a medicinal product and requires a marketing authorization by competent authorities prior to commercialization. Even if the pharmaceutical regulatory framework is harmonized at the EU level, obtaining marketing authorisations for medicinal products remains very challenging for Live Biotherapeutic Products (LBPs). Compared to other medicinal products currently on the market, safety assessment of LBPs represents a real challenge because of their specific characteristics and mode of action. Indeed, LBPs are not intended to reach the systemic circulation targeting distant organs, tissues, or receptors, but rather exert their effect through direct interactions with the complex native microbiota and/or the modulation of complex host-microbiota relation, indirectly leading to distant biological effects within the host. Hence, developers must rely on a thorough risk analysis, and pharmaceutical guidelines for other biological products should be taken into account in order to design relevant non-clinical and clinical development programmes. Here we aim at providing a roadmap for a risk analysis that takes into account the specificities of LBPs. We describe the different risks associated with these products and their interactions with the patient. Then, from that risk assessment, we propose solutions to design non-clinical programmes and First in Human (FIH) early clinical trials appropriate to assess LBP safety.

Revealing new leads for the impact of galacto-oligosaccharides on gut commensals and gut health benefits through text mining

Galacto-oligosaccharides (GOS) are linked to various health benefits, such as the relief of symptoms of constipation. Part of the beneficial effects of GOS are thought to be the consequence of their bifidogenic effect, stimulating the growth of several Bifidobacterium species in vivo. However, GOS may exert additional effects by directly stimulating other bacterial species or by effects that bifidobacteria may have on other commensals in the gut. To get a better insight into the potential health effects induced by GOS, a good understanding of the gut ecosystem, the role of GOS and bifidobacteria is important. An increasing number of 16S DNA profiling and metagenomics studies have led to an expanding inventory of genera, species and strains that can be found in the human gut. To investigate the potential connection of these commensals with GOS and bifidobacteria, we have undertaken a text-mining study to chart the literature landscape around these commensals. To this end, we created controlled vocabularies describing GOS, a large set of gut commensals and a number of terms related to gut health, which were used to mine the entire MEDLINE database. Co-occurrence text-mining revealed that a large number of commensals found in the gut have a connection with Bifidobacterium species and with gut health effects. Word frequency analysis provided more insight into the functional nature of these relationships. Combined co-occurrence search results pointed to putative novel health benefits indirectly linked to bifidobacteria and GOS. The potential beneficial effects of GOS on the protection of epithelial function and epithelial barrier impairment and appendicitis are interesting novel leads. The text-mining approach reported here revealed a number of novel leads through which GOS could exert health effects and that could be investigated in dedicated studies.

Diagnostic profiles for precision medicine in systemic sclerosis; stepping forward from single biomarkers towards pathophysiological panels

Systemic sclerosis (SSc) is an autoimmune disease which is characterized by vasculopathy, tissue fibrosis and activation of the innate and adaptive immune system. Clinical features of the disease consists of skin thickening and internal organ involvement. Due to the heterogeneous nature of the disease it is difficult to predict disease progression and complications. Despite the discovery of novel autoantibodies associated with SSc, there is an unmet need for biomarkers for diagnosis, disease progression and response to treatment. To date, the use of single (surrogate) biomarkers for these purposes has been unsuccessful. Combining multiple biomarkers in to predictive panels or ultimately algorithms could be more precise. Given the limited therapeutic options and poor prognosis of many SSc patients, a better understanding of the immune-pathofysiological profiles might aid to an adjusted therapeutic approach. Therefore, we set out to explore immunological fingerprints in various clinically defined forms of SSc. We used multilayer profiling to identify unique immune profiles underlying distinct autoantibody signatures. These immune profiles could fill the unmet need for prognosis and response to therapy in SSc. Here, we present 3 pathophysiological fingerprints in SSc based on the expression of circulating antibodies, vascular markers and immunomodulatory mediators.

Magnesium prevents vascular calcification in Klotho deficiency

Klotho knock-out mice are an important model for vascular calcification, which is associated with chronic kidney disease. In chronic kidney disease, serum magnesium inversely correlates with vascular calcification. Here we determine the effects of serum magnesium on aortic calcification in Klotho knock-out mice treated with a minimal or a high magnesium diet from birth. After eight weeks, serum biochemistry and aorta and bone tissues were studied. Protective effects of magnesium were characterized by RNA-sequencing of the aorta and micro-CT analysis was performed to study bone integrity. A high magnesium diet prevented vascular calcification and aortic gene expression of Runx2 and matrix Gla protein found in such mice on the minimal magnesium diet. Differential expression of inflammation and extracellular matrix remodeling genes accompanied the beneficial effects of magnesium on calcification. High dietary magnesium did not affect serum parathyroid hormone, 1,25-dihydroxyvitamin D₃ or calcium. High magnesium intake prevented vascular calcification despite increased fibroblast growth factor-23 and phosphate concentration in the knock-out mice. Compared to mice on the minimal magnesium diet, the high magnesium diet reduced femoral bone mineral density by 20% and caused excessive osteoid formation indicating osteomalacia. Osteoclast activity was unaffected by the high magnesium diet. In Saos-2 osteoblasts, magnesium supplementation reduced mineralization independent of osteoblast function. Thus, high dietary magnesium prevents calcification in Klotho knock-out mice. These effects are potentially mediated by reduction of inflammatory and extracellular matrix remodeling pathways within the aorta. Hence magnesium treatment may be promising to prevent vascular calcification, but the risk for osteomalacia should be considered.

Establishing a health-based recommended occupational exposure limit for nitrous oxide using experimental animal data - A systematic review protocol

Nitrous oxide (N 2 O) is widely used as inhalation analgesic and anaesthetic in medical, paramedical, and veterinary practice. Previous evaluations resulted in classification of N 2 O as a possible risk factor for adverse reproductive health outcomes based on evidence from animal data. Available human data were considered inadequate, partly due to the possibility that other risk factors, such as co-exposures to other inhalation anaesthetics may have contributed to the adverse outcomes. As no substantial new human evidence has emerged since previous evaluations, this protocol describes a planned systematic review of the evidence obtained from animal studies. The aim is to assess the available evidence on the effects of N 2 O on reproductive and developmental outcomes in animals to inform a health-based recommended occupational exposure limit (OEL) for N 2 O. Comprehensive search strategies were designed to retrieve animal studies addressing N 2 O exposure from PubMed, EMBASE, and Web of Science. Screening of the studies retrieved will be performed by at least two independent reviewers, while discrepancies will be resolved by reaching consensus through repeated review and discussions. Articles will be included according to criteria specified in this protocol. Outcome data relevant for reproduction and development will be extracted and risk of bias will be assessed by two independent reviewers using the SYRCLE's risk of bias tool. Primary reproductive and developmental outcomes of interest will be the number of resorptions, malformations, and birth weight. We will focus on dose-response studies that allow to derive an OEL with the benchmark dose (BMD) approach. Adverse outcomes occurring at doses that are equivalent to the exposures occurring in human occupational settings will be particularly relevant for dose-response modelling. The proposed review has not been performed before. We will follow the procedures specified in this protocol. We will adhere to guidelines of Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), adapted for animal studies. Ethical approval will not be required, as the review will use existing data available in the public domain.

Biosynthetic homeostasis and resilience of the complement system in health and infectious disease

BACKGROUND

The complement system is a central component of the innate immune system. Constitutive biosynthesis of complement proteins is essential for homeostasis. Dysregulation as a consequence of genetic or environmental cues can lead to inflammatory syndromes or increased susceptibility to infection. However, very little is known about steady state levels in children or its kinetics during infection.

METHODS

With a newly developed multiplex mass spectrometry-based method we analyzed the levels of 32 complement proteins in healthy individuals and in a group of pediatric patients infected with bacterial or viral pathogens.

FINDINGS

In plasma from young infants we found reduced levels of C4BP, ficolin-3, factor B, classical pathway components C1QA, C1QB, C1QC, C1R, and terminal pathway components C5, C8, C9, as compared to healthy adults; whereas the majority of complement regulating (inhibitory) proteins reach adult levels at very young age. Both viral and bacterial infections in children generally lead to a slight overall increase in complement levels, with some exceptions. The kinetics of complement levels during invasive bacterial infections only showed minor changes, except for a significant increase and decrease of CRP and clusterin, respectively.

INTERPRETATION

The combination of lower levels of activating and higher levels of regulating complement proteins, would potentially raise the threshold of activation, which might lead to suppressed complement activation in the first phase of life. There is hardly any measurable complement consumption during bacterial or viral infection. Altogether, expression of the complement proteins appears surprisingly stable, which suggests that the system is continuously replenished. FUND: European Union's Horizon 2020, project PERFORM, grant agreement No. 668303.

Magnesium deficiency prevents high-fat-diet-induced obesity in mice

AIMS/HYPOTHESIS

Hypomagnesaemia (blood Mg²⁺ <0.7 mmol/l) is a common phenomenon in individuals with type 2 diabetes. However, it remains unknown how a low blood Mg²⁺ concentration affects lipid and energy metabolism. Therefore, the importance of Mg²⁺ in obesity and type 2 diabetes has been largely neglected to date. This study aims to determine the effects of hypomagnesaemia on energy homeostasis and lipid metabolism.

METHODS

Mice (n = 12/group) were fed either a low-fat diet (LFD) or a high-fat diet (HFD) (10% or 60% of total energy) in combination with a normal- or low-Mg²⁺ content (0.21% or 0.03% wt/wt) for 17 weeks. Metabolic cages were used to investigate food intake, energy expenditure and respiration. Blood and tissues were taken to study metabolic parameters and mRNA expression profiles, respectively.

RESULTS

We show that low dietary Mg²⁺ intake ameliorates HFD-induced obesity in mice (47.00 ± 1.53 g vs 38.62 ± 1.51 g in mice given a normal Mg²⁺-HFD and low Mg²⁺-HFD, respectively, p < 0.05). Consequently, fasting serum glucose levels decreased and insulin sensitivity improved in low Mg²⁺-HFD-fed mice. Moreover, HFD-induced liver steatosis was absent in the low Mg²⁺ group. In hypomagnesaemic HFD-fed mice, mRNA expression of key lipolysis genes was increased in epididymal white adipose tissue (eWAT), corresponding to reduced lipid storage and high blood lipid levels. Low Mg²⁺-HFD-fed mice had increased brown adipose tissue (BAT) Ucp1 mRNA expression and a higher body temperature. No difference was observed in energy expenditure between the two HFD groups.

CONCLUSIONS/INTERPRETATION

Mg²⁺-deficiency abrogates HFD-induced obesity in mice through enhanced eWAT lipolysis and BAT activity.

Strain-Dependent Transcriptome Signatures for Robustness in Lactococcus lactis

Recently, we demonstrated that fermentation conditions have a strong impact on subsequent survival of Lactococcus lactis strain MG1363 during heat and oxidative stress, two important parameters during spray drying. Moreover, employment of a transcriptome-phenotype matching approach revealed groups of genes associated with robustness towards heat and/or oxidative stress. To investigate if other strains have similar or distinct transcriptome signatures for robustness, we applied an identical transcriptome-robustness phenotype matching approach on the L. lactis strains IL1403, KF147 and SK11, which have previously been demonstrated to display highly diverse robustness phenotypes. These strains were subjected to an identical fermentation regime as was performed earlier for strain MG1363 and consisted of twelve conditions, varying in the level of salt and/or oxygen, as well as fermentation temperature and pH. In the exponential phase of growth, cells were harvested for transcriptome analysis and assessment of heat and oxidative stress survival phenotypes. The variation in fermentation conditions resulted in differences in heat and oxidative stress survival of up to five 10-log units. Effects of the fermentation conditions on stress survival of the L. lactis strains were typically strain-dependent, although the fermentation conditions had mainly similar effects on the growth characteristics of the different strains. By association of the transcriptomes and robustness phenotypes highly strain-specific transcriptome signatures for robustness towards heat and oxidative stress were identified, indicating that multiple mechanisms exist to increase robustness and, as a consequence, robustness of each strain requires individual optimization. However, a relatively small overlap in the transcriptome responses of the strains was also identified and this generic transcriptome signature included genes previously associated with stress (ctsR and lplL) and novel genes, including nanE and genes encoding transport proteins. The transcript levels of these genes can function as indicators of robustness and could aid in selection of fermentation parameters, potentially resulting in more optimal robustness during spray drying.

Abstract B48: Homer3 regulates the establishment of neutrophil polarity

Neutrophils migrate towards developing tumors where they promote angiogenesis, setting the stage for metastasis. Investigating neutrophil migration should lead to novel drug targets to prevent neutrophil accumulation in tumors. Neutrophils and other cells rely on activation of the heterotrimeric G-protein Gai to regulate directional cell migration, but few links from Gai to chemotactic effectors are known. Through affinity chromatography using primary neutrophil lysate, we identify Homer3 as a novel Gai2-binding protein. RNAi-mediated knockdown of Homer3 in neutrophil-like HL-60 cells impairs chemotaxis and the establishment of polarity of the actin cytoskeleton. Most previously-characterized proteins that are required for cell polarity are needed for actin assembly or activation of core chemotactic effectors such as the Rac GTPase. In contrast, Homer3 knockdown cells show a normal magnitude and kinetics of chemoattractant-induced activation of PI3K and Rac effectors. Chemoattractant-stimulated Homer3 knockdown cells also exhibit a normal initial magnitude of actin polymerization, but they fail to polarize actin assembly and are defective in the initiation of cell polarity and motility. Our data suggest that Homer3 acts as a scaffold that spatially organizes actin assembly to support neutrophil polarity and motility downstream of GPCR activation.

Citation Format: Julie Wu, Anne Pipathsouk, A Keizer-Gunnink, Wynand Alkema, Fabrizia Fusetti, Shanshan Liu, Steve Atschuler, Lani Wu, Arjan Kortholt, Orion Weiner. Homer3 regulates the establishment of neutrophil polarity. [abstract]. In: Proceedings of the AACR Special Conference: Tumor Immunology and Immunotherapy: A New Chapter; December 1-4, 2014; Orlando, FL. Philadelphia (PA): AACR; Cancer Immunol Res 2015;3(10 Suppl):Abstract nr B48.

Microbial bioinformatics for food safety and production

In the production of fermented foods, microbes play an important role. Optimization of fermentation processes or starter culture production traditionally was a trial-and-error approach inspired by expert knowledge of the fermentation process. Current developments in high-throughput 'omics' technologies allow developing more rational approaches to improve fermentation processes both from the food functionality as well as from the food safety perspective. Here, the authors thematically review typical bioinformatics techniques and approaches to improve various aspects of the microbial production of fermented food products and food safety.

Homer3 regulates the establishment of neutrophil polarity

Most chemoattractants rely on activation of the heterotrimeric G-protein Gαi to regulate directional cell migration, but few links from Gαi to chemotactic effectors are known. Through affinity chromatography using primary neutrophil lysate, we identify Homer3 as a novel Gαi2-binding protein. RNA interference-mediated knockdown of Homer3 in neutrophil-like HL-60 cells impairs chemotaxis and the establishment of polarity of phosphatidylinositol 3,4,5-triphosphate (PIP3) and the actin cytoskeleton, as well as the persistence of the WAVE2 complex. Most previously characterized proteins that are required for cell polarity are needed for actin assembly or activation of core chemotactic effectors such as the Rac GTPase. In contrast, Homer3-knockdown cells show normal magnitude and kinetics of chemoattractant-induced activation of phosphoinositide 3-kinase and Rac effectors. Chemoattractant-stimulated Homer3-knockdown cells also exhibit a normal initial magnitude of actin polymerization but fail to polarize actin assembly and intracellular PIP3 and are defective in the initiation of cell polarity and motility. Our data suggest that Homer3 acts as a scaffold that spatially organizes actin assembly to support neutrophil polarity and motility downstream of GPCR activation.

Clustering analyses in peptidomics revealed that peptide profiles of infant formulae are descriptive

Prompted by the accumulating evidence on bioactive moieties of milk-derived peptides, novel methods were applied to compare the peptide composition among commercially available hydrolysate formulations and to determine batch-to-batch variations of protein hydrolysate products. Despite the availability of general methods to measure, for example, the degree of hydrolysis and peptide mass distribution at a high level, the objective of this study was to more qualitatively compare peptide sequences and composition. By a comprehensive approach combining peptidomics technologies and multivariate clustering analyses, the peptide profiles of different hydrolyzed milk protein formulations were compared. Moreover, peptide profiles of various hydrolysate batches that had been produced over a period of 5 years were included. Coupling of identified peptide sequences to the position in their corresponding milk proteins produced numerical datasets that subsequently were utilized for multivariate data analyses. These analyses revealed that batch-to-batch variation in the peptide profiles of a specific extensively hydrolyzed casein preparation was low. Moreover, extensive multivariate evaluations revealed that the peptide profiles of different commercially available hydrolyzed milk protein formulations provided a descriptive and distinct signature. Overall, the described methodology may contribute to the field of peptide research as observed dissimilarities in peptide profiles of similar products may be related to differences in their overall functionality.

Fermentation-induced variation in heat and oxidative stress phenotypes of Lactococcus lactis MG1363 reveals transcriptome signatures for robustness

Background

Lactococcus lactis is industrially employed to manufacture various fermented dairy products. The most cost-effective method for the preservation of L. lactis starter cultures is spray drying, but during this process cultures encounter heat and oxidative stress, typically resulting in low survival rates. However, viability of starter cultures is essential for their adequate contribution to milk fermentation, supporting the ambition to better understand and improve their robustness phenotypes.

Results

This study describes a transcriptome-phenotype matching approach in which the starter L. lactis MG1363 was fermented under a variety of conditions that differed in the levels of oxygen and/or salt, as well as the fermentation pH and temperature. Samples derived from these fermentations in the exponential phase of bacterial growth were analyzed by full-genome transcriptomics and the assessment of heat and oxidative stress phenotypes. Variations in the fermentation conditions resulted in up to 1000-fold differences in survival during heat and oxidative stress. More specifically, aeration during fermentation induced protection against heat stress, whereas a relatively high fermentation temperature resulted in enhanced robustness towards oxidative stress. Concomitantly, oxygen levels and fermentation temperature induced differential expression of markedly more genes when compared with the other fermentation parameters. Correlation analysis of robustness phenotypes and gene expression levels revealed transcriptome signatures for oxidative and/or heat stress survival, including the metC-cysK operon involved in methionine and cysteine metabolism. To validate this transcriptome-phenotype association we grew L. lactis MG1363 in the absence of cysteine which led to enhanced robustness towards oxidative stress.

Conclusions

Overall, we demonstrated the importance of careful selection of fermentation parameters prior to industrial processing of starter cultures. Furthermore, established stress genes as well as novel genes were associated with robustness towards heat and/or oxidative stress. Assessment of the expression levels of this group of genes could function as an indicator for enhanced selection of fermentation parameters resulting in improved robustness during spray drying. The increased robustness after growth without cysteine appeared to confirm the role of expression of the metC-cysK operon as an indicator of robustness and suggests that sulfur amino acid metabolism plays a pivotal role in oxidative stress survival.

Electronic supplementary material

The online version of this article (doi:10.1186/s12934-014-0148-6) contains supplementary material, which is available to authorized users.

Prednisolone induces the Wnt signalling pathway in 3T3-L1 adipocytes

Synthetic glucocorticoids are potent anti-inflammatory drugs but show dose-dependent metabolic side effects such as the development of insulin resistance and obesity. The precise mechanisms involved in these glucocorticoid-induced side effects, and especially the participation of adipose tissue in this are not completely understood. We used a combination of transcriptomics, antibody arrays and bioinformatics approaches to characterize prednisolone-induced alterations in gene expression and adipokine secretion, which could underlie metabolic dysfunction in 3T3-L1 adipocytes. Several pathways, including cytokine signalling, Akt signalling, and Wnt signalling were found to be regulated at multiple levels, showing that these processes are targeted by prednisolone. These results suggest that mechanisms by which prednisolone induce insulin resistance include dysregulation of wnt signalling and immune response processes. These pathways may provide interesting targets for the development of improved glucocorticoids.

Identification of new biomarker candidates for glucocorticoid induced insulin resistance using literature mining

BACKGROUND

Glucocorticoids are potent anti-inflammatory agents used for the treatment of diseases such as rheumatoid arthritis, asthma, inflammatory bowel disease and psoriasis. Unfortunately, usage is limited because of metabolic side-effects, e.g. insulin resistance, glucose intolerance and diabetes. To gain more insight into the mechanisms behind glucocorticoid induced insulin resistance, it is important to understand which genes play a role in the development of insulin resistance and which genes are affected by glucocorticoids.Medline abstracts contain many studies about insulin resistance and the molecular effects of glucocorticoids and thus are a good resource to study these effects.

RESULTS

We developed CoPubGene a method to automatically identify gene-disease associations in Medline abstracts. We used this method to create a literature network of genes related to insulin resistance and to evaluate the importance of the genes in this network for glucocorticoid induced metabolic side effects and anti-inflammatory processes.With this approach we found several genes that already are considered markers of GC induced IR, such as phosphoenolpyruvate carboxykinase (PCK) and glucose-6-phosphatase, catalytic subunit (G6PC). In addition, we found genes involved in steroid synthesis that have not yet been recognized as mediators of GC induced IR.

CONCLUSIONS

With this approach we are able to construct a robust informative literature network of insulin resistance related genes that gave new insights to better understand the mechanisms behind GC induced IR. The method has been set up in a generic way so it can be applied to a wide variety of disease networks.

Org 214007-0: a novel non-steroidal selective glucocorticoid receptor modulator with full anti-inflammatory properties and improved therapeutic index

Glucocorticoids (GCs) such as prednisolone are potent immunosuppressive drugs but suffer from severe adverse effects, including the induction of insulin resistance. Therefore, development of so-called Selective Glucocorticoid Receptor Modulators (SGRM) is highly desirable. Here we describe a non-steroidal Glucocorticoid Receptor (GR)-selective compound (Org 214007-0) with a binding affinity to GR similar to that of prednisolone. Structural modelling of the GR-Org 214007-0 binding site shows disturbance of the loop between helix 11 and helix 12 of GR, confirmed by partial recruitment of the TIF2-3 peptide. Using various cell lines and primary human cells, we show here that Org 214007-0 acts as a partial GC agonist, since it repressed inflammatory genes and was less effective in induction of metabolic genes. More importantly, in vivo studies in mice indicated that Org 214007-0 retained full efficacy in acute inflammation models as well as in a chronic collagen-induced arthritis (CIA) model. Gene expression profiling of muscle tissue derived from arthritic mice showed a partial activity of Org 214007-0 at an equi-efficacious dosage of prednisolone, with an increased ratio in repression versus induction of genes. Finally, in mice Org 214007-0 did not induce elevated fasting glucose nor the shift in glucose/glycogen balance in the liver seen with an equi-efficacious dose of prednisolone. All together, our data demonstrate that Org 214007-0 is a novel SGRMs with an improved therapeutic index compared to prednisolone. This class of SGRMs can contribute to effective anti-inflammatory therapy with a lower risk for metabolic side effects.

Molecular pathway profiling of T lymphocyte signal transduction pathways; Th1 and Th2 genomic fingerprints are defined by TCR and CD28-mediated signaling

Background

T lymphocytes are orchestrators of adaptive immunity. Naïve T cells may differentiate into Th1, Th2, Th17 or iTreg phenotypes, depending on environmental co-stimulatory signals. To identify genes and pathways involved in differentiation of Jurkat T cells towards Th1 and Th2 subtypes we performed comprehensive transcriptome analyses of Jurkat T cells stimulated with various stimuli and pathway inhibitors. Results from these experiments were validated in a human experimental setting using whole blood and purified CD4+ Tcells.

Results

Calcium-dependent activation of T cells using CD3/CD28 and PMA/CD3 stimulation induced a Th1 expression profile reflected by increased expression of T-bet, RUNX3, IL-2, and IFNγ, whereas calcium-independent activation via PMA/CD28 induced a Th2 expression profile which included GATA3, RXRA, CCL1 and Itk. Knock down with siRNA and gene expression profiling in the presence of selective kinase inhibitors showed that proximal kinases Lck and PKCθ are crucial signaling hubs during T helper cell activation, revealing a clear role for Lck in Th1 development and for PKCθ in both Th1 and Th2 development. Medial signaling via MAPkinases appeared to be less important in these pathways, since specific inhibitors of these kinases displayed a minor effect on gene expression. Translation towards a primary, whole blood setting and purified human CD4+ T cells revealed that PMA/CD3 stimulation induced a more pronounced Th1 specific, Lck and PKCθ dependent IFNγ production, whereas PMA/CD28 induced Th2 specific IL-5 and IL-13 production, independent of Lck activation. PMA/CD3-mediated skewing towards a Th1 phenotype was also reflected in mRNA expression of the master transcription factor Tbet, whereas PMA/CD28-mediated stimulation enhanced GATA3 mRNA expression in primary human CD4+ Tcells.

Conclusions

This study identifies stimulatory pathways and gene expression profiles for in vitro skewing of T helper cell activation. PMA/CD3 stimulation enhances a Th1-like response in an Lck and PKCθ dependent fashion, whereas PMA/CD28 stimulation results in a Th2-like phenotype independent of the proximal TCR-tyrosine kinase Lck. This approach offers a robust and fast translational in vitro system for skewed T helper cell responses in Jurkat T cells, primary human CD4+ Tcells and in a more complex matrix such as human whole blood.

ss-TEA: Entropy based identification of receptor specific ligand binding residues from a multiple sequence alignment of class A GPCRs

BACKGROUND

G-protein coupled receptors (GPCRs) are involved in many different physiological processes and their function can be modulated by small molecules which bind in the transmembrane (TM) domain. Because of their structural and sequence conservation, the TM domains are often used in bioinformatics approaches to first create a multiple sequence alignment (MSA) and subsequently identify ligand binding positions. So far methods have been developed to predict the common ligand binding residue positions for class A GPCRs.

RESULTS

Here we present 1) ss-TEA, a method to identify specific ligand binding residue positions for any receptor, predicated on high quality sequence information. 2) The largest MSA of class A non olfactory GPCRs in the public domain consisting of 13324 sequences covering most of the species homologues of the human set of GPCRs. A set of ligand binding residue positions extracted from literature of 10 different receptors shows that our method has the best ligand binding residue prediction for 9 of these 10 receptors compared to another state-of-the-art method.

CONCLUSIONS

The combination of the large multi species alignment and the newly introduced residue selection method ss-TEA can be used to rapidly identify subfamily specific ligand binding residues. This approach can aid the design of site directed mutagenesis experiments, explain receptor function and improve modelling. The method is also available online via GPCRDB at http://www.gpcr.org/7tm/.

Prednisolone-induced changes in gene-expression profiles in healthy volunteers

Background: Prednisolone and other glucocorticoids (GCs) are potent anti-inflammatory and immunosuppressive drugs. However, prolonged use at a medium or high dose is hampered by side effects of which the metabolic side effects are most evident. Relatively little is known about their effect on gene-expression in vivo, the effect on cell subpopulations and the relation to the efficacy and side effects of GCs. Aim: To identify and compare prednisolone-induced gene signatures in CD4+ T lymphocytes and CD14+ monocytes derived from healthy volunteers and to link these signatures to underlying biological pathways involved in metabolic adverse effects. Materials & methods: Whole-genome expression profiling was performed on CD4+ T lymphocytes and CD14+ monocytes derived from healthy volunteers treated with prednisolone. Text-mining analyses was used to link genes to pathways involved in metabolic adverse events. Results: Induction of gene-expression was much stronger in CD4+ T lymphocytes than in CD14+ monocytes with respect to fold changes, but the number of truly cell-specific genes where a strong prednisolone effect in one cell type was accompanied by a total lack of prednisolone effect in the other cell type, was relatively low. Subsequently, a large set of genes was identified with a strong link to metabolic processes, for some of which the association with GCs is novel. Conclusion: The identified gene signatures provide new starting points for further study into GC-induced transcriptional regulation in vivo and the mechanisms underlying GC-mediated metabolic side effects.

Original submitted 5 January 2011; Revision submitted 24 February 2011

CoPub update: CoPub 5.0 a text mining system to answer biological questions

In this article, we present CoPub 5.0, a publicly available text mining system, which uses Medline abstracts to calculate robust statistics for keyword co-occurrences. CoPub was initially developed for the analysis of microarray data, but we broadened the scope by implementing new technology and new thesauri. In CoPub 5.0, we integrated existing CoPub technology with new features, and provided a new advanced interface, which can be used to answer a variety of biological questions. CoPub 5.0 allows searching for keywords of interest and its relations to curated thesauri and provides highlighting and sorting mechanisms, using its statistics, to retrieve the most important abstracts in which the terms co-occur. It also provides a way to search for indirect relations between genes, drugs, pathways and diseases, following an ABC principle, in which A and C have no direct connection but are connected via shared B intermediates. With CoPub 5.0, it is possible to create, annotate and analyze networks using the layout and highlight options of Cytoscape web, allowing for literature based systems biology. Finally, operations of the CoPub 5.0 Web service enable to implement the CoPub technology in bioinformatics workflows. CoPub 5.0 can be accessed through the CoPub portal http://www.copub.org.

Literature mining for the discovery of hidden connections between drugs, genes and diseases

The scientific literature represents a rich source for retrieval of knowledge on associations between biomedical concepts such as genes, diseases and cellular processes. A commonly used method to establish relationships between biomedical concepts from literature is co-occurrence. Apart from its use in knowledge retrieval, the co-occurrence method is also well-suited to discover new, hidden relationships between biomedical concepts following a simple ABC-principle, in which A and C have no direct relationship, but are connected via shared B-intermediates. In this paper we describe CoPub Discovery, a tool that mines the literature for new relationships between biomedical concepts. Statistical analysis using ROC curves showed that CoPub Discovery performed well over a wide range of settings and keyword thesauri. We subsequently used CoPub Discovery to search for new relationships between genes, drugs, pathways and diseases. Several of the newly found relationships were validated using independent literature sources. In addition, new predicted relationships between compounds and cell proliferation were validated and confirmed experimentally in an in vitro cell proliferation assay. The results show that CoPub Discovery is able to identify novel associations between genes, drugs, pathways and diseases that have a high probability of being biologically valid. This makes CoPub Discovery a useful tool to unravel the mechanisms behind disease, to find novel drug targets, or to find novel applications for existing drugs.

The biomedical literature is an important source of knowledge on the function of genes and on the mechanisms by which these genes regulate cellular processes. Several text mining approaches have been developed to leverage this rich source of information by automatically extracting associations between concepts such as genes, diseases and drugs from a large body of text. Here, we describe a new method that extracts novel, not yet recognized associations between genes, diseases, drugs and cellular processes from the biomedical literature. Our method is built on the assumption that even if two concepts do not have a direct connection in literature, they may be functionally related if they are both connected to an overlapping set of concepts. Using this approach we predicted several novel connections between genes, diseases, drugs and pathways. Our results imply that our method is able to predict novel relationships from literature and, most importantly, that these newly identified relationships are biologically relevant. Our method can aid the drug discovery process where it can be used to find novel drug targets, increase insight in mode of action of a drug or find novel applications for known drugs.

Prednisolone-induced differential gene expression in mouse liver carrying wild type or a dimerization-defective glucocorticoid receptor

BACKGROUND

Glucocorticoids (GCs) control expression of a large number of genes via binding to the GC receptor (GR). Transcription may be regulated either by binding of the GR dimer to DNA regulatory elements or by protein-protein interactions of GR monomers with other transcription factors. Although the type of regulation for a number of individual target genes is known, the relative contribution of both mechanisms to the regulation of the entire transcriptional program remains elusive. To study the importance of GR dimerization in the regulation of gene expression, we performed gene expression profiling of livers of prednisolone-treated wild type (WT) and mice that have lost the ability to form GR dimers (GRdim).

RESULTS

The GR target genes identified in WT mice were predominantly related to glucose metabolism, the cell cycle, apoptosis and inflammation. In GRdim mice, the level of prednisolone-induced gene expression was significantly reduced compared to WT, but not completely absent. Interestingly, for a set of genes, involved in cell cycle and apoptosis processes and strongly related to Foxo3a and p53, induction by prednisolone was completely abolished in GRdim mice. In contrast, glucose metabolism-related genes were still modestly upregulated in GRdim mice upon prednisolone treatment. Finally, we identified several novel GC-inducible genes from which Fam107a, a putative histone acetyltransferase complex interacting protein, was most strongly dependent on GR dimerization.

CONCLUSIONS

This study on prednisolone-induced effects in livers of WT and GRdim mice identified a number of interesting candidate genes and pathways regulated by GR dimers and sheds new light onto the complex transcriptional regulation of liver function by GCs.

PhyloPat: an updated version of the phylogenetic pattern database contains gene neighborhood

Phylogenetic patterns show the presence or absence of certain genes in a set of full genomes derived from different species. They can also be used to determine sets of genes that occur only in certain evolutionary branches. Previously, we presented a database named PhyloPat which allows the complete Ensembl gene database to be queried using phylogenetic patterns. Here, we describe an updated version of PhyloPat which can be queried by an improved web server. We used a single linkage clustering algorithm to create 241,697 phylogenetic lineages, using all the orthologies provided by Ensembl v49. PhyloPat offers the possibility of querying with binary phylogenetic patterns or regular expressions, or through a phylogenetic tree of the 39 included species. Users can also input a list of Ensembl, EMBL, EntrezGene or HGNC IDs to check which phylogenetic lineage any gene belongs to. A link to the FatiGO web interface has been incorporated in the HTML output. For each gene, the surrounding genes on the chromosome, color coded according to their phylogenetic lineage can be viewed, as well as FASTA files of the peptide sequences of each lineage. Furthermore, lists of omnipresent, polypresent, oligopresent and anticorrelating genes have been included. PhyloPat is freely available at http://www.cmbi.ru.nl/phylopat.

BioVenn - a web application for the comparison and visualization of biological lists using area-proportional Venn diagrams

BACKGROUND

In many genomics projects, numerous lists containing biological identifiers are produced. Often it is useful to see the overlap between different lists, enabling researchers to quickly observe similarities and differences between the data sets they are analyzing. One of the most popular methods to visualize the overlap and differences between data sets is the Venn diagram: a diagram consisting of two or more circles in which each circle corresponds to a data set, and the overlap between the circles corresponds to the overlap between the data sets. Venn diagrams are especially useful when they are 'area-proportional' i.e. the sizes of the circles and the overlaps correspond to the sizes of the data sets. Currently there are no programs available that can create area-proportional Venn diagrams connected to a wide range of biological databases.

RESULTS

We designed a web application named BioVenn to summarize the overlap between two or three lists of identifiers, using area-proportional Venn diagrams. The user only needs to input these lists of identifiers in the textboxes and push the submit button. Parameters like colors and text size can be adjusted easily through the web interface. The position of the text can be adjusted by 'drag-and-drop' principle. The output Venn diagram can be shown as an SVG or PNG image embedded in the web application, or as a standalone SVG or PNG image. The latter option is useful for batch queries. Besides the Venn diagram, BioVenn outputs lists of identifiers for each of the resulting subsets. If an identifier is recognized as belonging to one of the supported biological databases, the output is linked to that database. Finally, BioVenn can map Affymetrix and EntrezGene identifiers to Ensembl genes.

CONCLUSION

BioVenn is an easy-to-use web application to generate area-proportional Venn diagrams from lists of biological identifiers. It supports a wide range of identifiers from the most used biological databases currently available. Its implementation on the World Wide Web makes it available for use on any computer with internet connection, independent of operating system and without the need to install programs locally. BioVenn is freely accessible at http://www.cmbi.ru.nl/cdd/biovenn/.

BioVenn - a web application for the comparison and visualization of biological lists using area-proportional Venn diagrams

BACKGROUND

In many genomics projects, numerous lists containing biological identifiers are produced. Often it is useful to see the overlap between different lists, enabling researchers to quickly observe similarities and differences between the data sets they are analyzing. One of the most popular methods to visualize the overlap and differences between data sets is the Venn diagram: a diagram consisting of two or more circles in which each circle corresponds to a data set, and the overlap between the circles corresponds to the overlap between the data sets. Venn diagrams are especially useful when they are 'area-proportional' i.e. the sizes of the circles and the overlaps correspond to the sizes of the data sets. Currently there are no programs available that can create area-proportional Venn diagrams connected to a wide range of biological databases.

RESULTS

We designed a web application named BioVenn to summarize the overlap between two or three lists of identifiers, using area-proportional Venn diagrams. The user only needs to input these lists of identifiers in the textboxes and push the submit button. Parameters like colors and text size can be adjusted easily through the web interface. The position of the text can be adjusted by 'drag-and-drop' principle. The output Venn diagram can be shown as an SVG or PNG image embedded in the web application, or as a standalone SVG or PNG image. The latter option is useful for batch queries. Besides the Venn diagram, BioVenn outputs lists of identifiers for each of the resulting subsets. If an identifier is recognized as belonging to one of the supported biological databases, the output is linked to that database. Finally, BioVenn can map Affymetrix and EntrezGene identifiers to Ensembl genes.

CONCLUSION

BioVenn is an easy-to-use web application to generate area-proportional Venn diagrams from lists of biological identifiers. It supports a wide range of identifiers from the most used biological databases currently available. Its implementation on the World Wide Web makes it available for use on any computer with internet connection, independent of operating system and without the need to install programs locally. BioVenn is freely accessible at http://www.cmbi.ru.nl/cdd/biovenn/.

CoPub: a literature-based keyword enrichment tool for microarray data analysis

Medline is a rich information source, from which links between genes and keywords describing biological processes, pathways, drugs, pathologies and diseases can be extracted. We developed a publicly available tool called CoPub that uses the information in the Medline database for the biological interpretation of microarray data. CoPub allows batch input of multiple human, mouse or rat genes and produces lists of keywords from several biomedical thesauri that are significantly correlated with the set of input genes. These lists link to Medline abstracts in which the co-occurring input genes and correlated keywords are highlighted. Furthermore, CoPub can graphically visualize differentially expressed genes and over-represented keywords in a network, providing detailed insight in the relationships between genes and keywords, and revealing the most influential genes as highly connected hubs. CoPub is freely accessible at http://services.nbic.nl/cgi-bin/copub/CoPub.pl.

Literature-based compound profiling: application to toxicogenomics

Introduction: To reduce continuously increasing costs in drug development, adverse effects of drugs need to be detected as early as possible in the process. In recent years, compound-induced gene expression profiling methodologies have been developed to assess compound toxicity, including Gene Ontology term and pathway over-representation analyses. The objective of this study was to introduce an additional approach, in which literature information is used for compound profiling to evaluate compound toxicity and mode of toxicity. Methods: Gene annotations were built by text mining in Medline abstracts for retrieval of co-publications between genes, pathology terms, biological processes and pathways. This literature information was used to generate compound-specific keyword fingerprints, representing over-represented keywords calculated in a set of regulated genes after compound administration. To see whether keyword fingerprints can be used for assessment of compound toxicity, we analyzed microarray data sets of rat liver treated with 11 hepatotoxicants. Results: Analysis of keyword fingerprints of two genotoxic carcinogens, two nongenotoxic carcinogens, two peroxisome proliferators and two randomly generated gene sets, showed that each compound produced a specific keyword fingerprint that correlated with the experimentally observed histopathological events induced by the individual compounds. By contrast, the random sets produced a flat aspecific keyword profile, indicating that the fingerprints induced by the compounds reflect biological events rather than random noise. A more detailed analysis of the keyword profiles of diethylhexylphthalate, dimethylnitrosamine and methapyrilene (MPy) showed that the differences in the keyword fingerprints of these three compounds are based upon known distinct modes of action. Visualization of MPy-linked keywords and MPy-induced genes in a literature network enabled us to construct a mode of toxicity proposal for MPy, which is in agreement with known effects of MPy in literature. Conclusion: Compound keyword fingerprinting based on information retrieved from literature is a powerful approach for compound profiling, allowing evaluation of compound toxicity and analysis of the mode of action.

Target validation in silico: does the virtual patient cure the pharma pipeline?

Genomics has multiplied the number of targets for new therapeutic interventions, but this has not yet lead to a marked increase of pharma pipeline outputs. The complexity of protein function in higher order biological systems is often underestimated. Translation from in vitro and in vivo results to the human setting frequently fails due to unforeseen toxicity and efficacy issues. Biosimulation addresses these issues by capturing the complex dynamics of interacting molecules and cells in mechanistic, predictive models. A central concept is that of the virtual patient, an encapsulation of a specific pathophysiological behaviour in a biosimulation model. The authors describe how virtual patients are being used in target identification, target validation and clinical development, and discuss challenges for the acceptance of biosimulation methods.

Identification of functional clusters of transcription factor binding motifs in genome sequences: the MSCAN algorithm

MOTIVATION

The identification of regulatory control regions within genomes is a major challenge. Studies have demonstrated that regulating regions can be described as locally dense clusters or modules of cis-acting transcription factor binding sites (TFBS). For well-described biological contexts, it is possible to train predictive algorithms to discern novel modules in genome sequences. However, utility of module detection methods has been severely limited by insufficient training data. For only a few tissues can one obtain sufficient numbers of literature-derived regulatory modules.

RESULTS

We present a novel method, MSCAN, that circumvents the training data problem by measuring the statistical significance of any non-overlapping combination of TFBS in a window. Given a set of transcription factor binding profiles, a significance threshold, and a genomic sequence, MSCAN returns putative regulatory regions. We assess performance on two curated collections of regulatory regions; one each for tissue-specific expression in liver and skeletal muscle cells. The efficiency of MSCAN allows for predictive screens of entire genomes.

JASPAR: an open-access database for eukaryotic transcription factor binding profiles

The analysis of regulatory regions in genome sequences is strongly based on the detection of potential transcription factor binding sites. The preferred models for representation of transcription factor binding specificity have been termed position-specific scoring matrices. JASPAR is an open-access database of annotated, high-quality, matrix-based transcription factor binding site profiles for multicellular eukaryotes. The profiles were derived exclusively from sets of nucleotide sequences experimentally demonstrated to bind transcription factors. The database is complemented by a web interface for browsing, searching and subset selection, an online sequence analysis utility and a suite of programming tools for genome-wide and comparative genomic analysis of regulatory regions. JASPAR is available at http://jaspar. cgb.ki.se.

Understanding the language of gene regulation

A report on the Cold Spring Harbor Laboratory meeting 'Systems Biology: genomic approaches to transcriptional regulation', Cold Spring Harbor, USA, 6-9 March 2003.

A report on the Cold Spring Harbor Laboratory meeting 'Systems Biology: genomic approaches to transcriptional regulation', Cold Spring Harbor, USA, 6-9 March 2003.

Hydrogenosomes in the anaerobic fungus Neocallimastix frontalis have a double membrane but lack an associated organelle genome

The presence of hydrogenosomes in phylogenetically distinct anaerobic eukaryotes implies that they have been acquired independently, and previously reported differences in ultrastructure among taxa have suggested that some hydrogenosomes have different origins. Of particular interest are reports that Neocallimastix frontalis hydrogenosomes resemble microbodies in possessing a single membrane, in contrast to those in ciliates and trichomonads which have two and thus resemble mitochondria. In this investigation we have clearly demonstrated that N. frontalis hydrogenosomes possess two, rather than one, closely apposed membranes and in some preparations cristae-like structures were observed. These observations have led us to reject the microbody hypothesis and provide some indirect support for a possible mitochondrion origin as proposed for other hydrogenosomes. N. frontalis hydrogenosomes were shown to lack an associated genome as previously demonstrated for trichomonad hydrogenosomes. This might be explained by assuming that a mitochondrial genome encoding proteins for aerobic function is no longer necessary for either organelle.