Cestode regulation of inflammation and inflammatory diseases

Helminth parasites are masters of immune regulation; a likely prerequisite for long-term survival by circumventing their hosts’ attempt to eradicate them. From a translational perspective, knowledge of immune events as a response to infection with a helminth parasite could be used to reduce the intensity of unwanted inflammatory reactions. Substantial data have accumulated showing that inflammatory reactions that promote a variety of auto-inflammatory diseases are dampened as a consequence of infection with helminth parasites, via either the mobilization of an anti-worm spectrum of immune events or by the direct effect of secretory/excretory bioactive immunomodulatory molecules released from the parasite. However, many issues are outstanding in the definition of the mechanism(s) by which infection with helminth parasites can affect the outcome, positively or negatively, of concomitant disease. We focus on a subgroup of this complex group of metazoan parasites, the cestodes, summarizing studies from rodent models that illustrate if, and by what mechanisms, infection with tapeworms ameliorate or exaggerate disease in their host. The ability of infection with cestodes, or other classes of helminth, to worsen a disease course or confer susceptibility to intracellular pathogens should be carefully considered in the context of ‘helminth therapy’. In addition, poorly characterised cestode extracts can regulate murine and human immunocyte function, yet the impact of these in the context of autoimmune or allergic diseases is poorly understood. Thus, studies with cestodes, as representative helminths, have helped cement the concept that infection with parasitic helminths can inhibit concomitant disease; however, issues relating to long-term effects, potential side-effects, mixed pathogen infections and purification of immunomodulatory molecules from the parasite remain as challenges that need to be addressed in order to achieve the use of helminths as anti-inflammatory agents for human diseases.     

1-(4-Phenylpiperazin-1-yl)-2-(1H-pyrazol-1-yl)ethanones as novel CCR1 antagonists

A novel series of CCR1 antagonists based on the 1-(4-phenylpiperazin-1-yl)-2-(1H-pyrazol-1-yl)ethanone scaffold was identified by screening a compound library utilizing CCR1-expressing human THP-1 cells. SAR studies led to the discovery of the highly potent and selective CCR1 antagonist 14 (CCR1 binding IC₅₀ = 4 nM using [¹²⁵I]-CCL3 as the chemokine ligand). Compound 14 displayed promising pharmacokinetic and toxicological profiles in preclinical species.     

Design and synthesis of 1-aryl-5-anilinoindazoles as c-Jun N-terminal kinase inhibitors

Starting from pyrazole HTS hit (1), a series of 1-aryl-1H-indazoles have been synthesized as JNK3 inhibitors with moderate selectivity against JNK1. SAR studies led to the synthesis of 5r as double digital nanomolar JNK3 inhibitor with good in vivo exposure.     

The emerging use of zebrafish to model metabolic disease

The zebrafish research community is celebrating! The zebrafish genome has recently been sequenced, the Zebrafish Mutation Project (launched by the Wellcome Trust Sanger Institute) has published the results of its first large-scale ethylnitrosourea (ENU) mutagenesis screen, and a host of new techniques, such as the genome editing technologies TALEN and CRISPR-Cas, are enabling specific mutations to be created in model organisms and investigated in vivo. The zebrafish truly seems to be coming of age. These powerful resources invoke the question of whether zebrafish can be increasingly used to model human disease, particularly common, chronic diseases of metabolism such as obesity and type 2 diabetes. In recent years, there has been considerable success, mainly from genomic approaches, in identifying genetic variants that are associated with these conditions in humans; however, mechanistic insights into the role of implicated disease loci are lacking. In this Review, we highlight some of the advantages and disadvantages of zebrafish to address the organism’s utility as a model system for human metabolic diseases.     

Impairment in Task-Specific Modulation of Muscle Coordination Correlates with the Severity of Hand Impairment following Stroke

Significant functional impairment of the hand is commonly observed in stroke survivors. Our previous studies suggested that the inability to modulate muscle coordination patterns according to task requirements may be substantial after stroke, but these limitations have not been examined directly. In this study, we aimed to characterize post-stroke impairment in the ability to modulate muscle coordination patterns across tasks and its correlation with hand impairment. Fourteen stroke survivors, divided into a group with severe hand impairment (8 subjects) and a group with moderate hand impairment (6 subjects) according to their clinical functionality score, participated in the experiment. Another four neurologically intact subjects participated in the experiment to serve as a point of comparison. Activation patterns of nine hand and wrist muscles were recorded using surface electromyography while the subjects performed six isometric tasks. Patterns of covariation in muscle activations across tasks, i.e., muscle modules, were extracted from the muscle activation data. Our results showed that the degree of reduction in the inter-task separation of the multi-muscle activation patterns was indicative of the clinical functionality score of the subjects (mean value = 26.2 for severely impaired subjects, 38.1 for moderately impaired subjects). The values for moderately impaired subjects were much closer to those of the impaired subjects (mean value = 46.1). The number of muscle modules extracted from the muscle activation patterns of a subject across six tasks, which represents the degree of motor complexity, was found to be correlated with the clinical functionality score (R = 0.68). Greater impairment was also associated with a change in the muscle module patterns themselves, with greater muscle coactivation. A substantial reduction in the degrees-of-freedom of the multi-muscle coordination post-stroke was apparent, and the extent of the reduction, assessed by the stated metrics, was strongly associated with the level of clinical impairment.     

Influenza Vaccination Uptake among the Working Age Population of Japan: Results from a National Cross-Sectional Survey

Background

Influenza vaccination rates among Japanese people of working age (20–69 years) is currently suboptimal, and the reasons for this have not been clearly elucidated. This study examined factors associated with vaccination intention among the working age population in Japan during September 2011, one-month prior to influenza vaccination becoming available.

Methodology/Principal Findings

A web-based survey of intention to be vaccinated against influenza in the coming season was undertaken among 3,129 Japanese aged 20 to 69 years. Multinomial logistic regression analysis was used to explore the associations between vaccination intent and other variables. Influenza vaccination intent was associated with having been vaccinated in the previous year (Odds Ratio (OR): 3.81; 95% Confidence Interval (CI): 3.75–3.86), the number of children per household (one compared with zero; OR: 1.37; 95%CI: 1.11–1.65), and household income ($50,000 to <$100,000 compared with $0 to <$50,000; OR: 1.30; 95%CI: 1.07–1.54). Smoking was inversely associated with influenza vaccine uptake (current smokers compared with non-smokers; OR: 0.79; 95%CI: 0.61–0.98). A history of either the survey respondent or a household member having being medically diagnosed with influenza in the previous year was not statistically associated with future influenza vaccination intent.

Conclusions/Significance

Overall, this suggests that intention to be vaccinated among working age Japanese is associated with a past history of influenza vaccination, having children, and the household''s income. As such, consideration of these factors should now form the cornerstone of strategies to encourage increased uptake of vaccination against influenza in future years.     

?-Adrenergic Stimulation Increases RyR2 Activity via Intracellular Ca2+ and Mg2+ Regulation

Here we investigate how ß-adrenergic stimulation of the heart alters regulation of ryanodine receptors (RyRs) by intracellular Ca²⁺ and Mg²⁺ and the role of these changes in SR Ca²⁺ release. RyRs were isolated from rat hearts, perfused in a Langendorff apparatus for 5 min and subject to 1 min perfusion with 1 µM isoproterenol or without (control) and snap frozen in liquid N₂ to capture their phosphorylation state. Western Blots show that RyR2 phosphorylation was increased by isoproterenol, confirming that RyR2 were subject to normal ß-adrenergic signaling. Under basal conditions, S2808 and S2814 had phosphorylation levels of 69% and 15%, respectively. These levels were increased to 83% and 60%, respectively, after 60 s of ß-adrenergic stimulation consistent with other reports that ß-adrenergic stimulation of the heart can phosphorylate RyRs at specific residues including S2808 and S2814 causing an increase in RyR activity. At cytoplasmic [Ca²⁺] <1 µM, ß-adrenergic stimulation increased luminal Ca²⁺ activation of single RyR channels, decreased luminal Mg²⁺ inhibition and decreased inhibition of RyRs by mM cytoplasmic Mg²⁺. At cytoplasmic [Ca²⁺] >1 µM, ß-adrenergic stimulation only decreased cytoplasmic Mg²⁺ and Ca²⁺ inhibition of RyRs. The K_a and maximum levels of cytoplasmic Ca²⁺ activation site were not affected by ß-adrenergic stimulation.Our RyR2 gating model was fitted to the single channel data. It predicted that in diastole, ß-adrenergic stimulation is mediated by 1) increasing the activating potency of Ca²⁺ binding to the luminal Ca²⁺ site and decreasing its affinity for luminal Mg²⁺ and 2) decreasing affinity of the low-affinity Ca²⁺/Mg²⁺ cytoplasmic inhibition site. However in systole, ß-adrenergic stimulation is mediated mainly by the latter.     

Functional environmental proteomics: elucidating the role of a c-type cytochrome abundant during uranium bioremediation

Studies with pure cultures of dissimilatory metal-reducing microorganisms have demonstrated that outer-surface c-type cytochromes are important electron transfer agents for the reduction of metals, but previous environmental proteomic studies have typically not recovered cytochrome sequences from subsurface environments in which metal reduction is important. Gel-separation, heme-staining and mass spectrometry of proteins in groundwater from in situ uranium bioremediation experiments identified a putative c-type cytochrome, designated Geobacter subsurface c-type cytochrome A (GscA), encoded within the genome of strain M18, a Geobacter isolate previously recovered from the site. Homologs of GscA were identified in the genomes of other Geobacter isolates in the phylogenetic cluster known as subsurface clade 1, which predominates in a diversity of Fe(III)-reducing subsurface environments. Most of the gscA sequences recovered from groundwater genomic DNA clustered in a tight phylogenetic group closely related to strain M18. GscA was most abundant in groundwater samples in which Geobacter sp. predominated. Expression of gscA in a strain of Geobacter sulfurreducens that lacked the gene for the c-type cytochrome OmcS, thought to facilitate electron transfer from conductive pili to Fe(III) oxide, restored the capacity for Fe(III) oxide reduction. Atomic force microscopy provided evidence that GscA was associated with the pili. These results demonstrate that a c-type cytochrome with an apparent function similar to that of OmcS is abundant when Geobacter sp. are abundant in the subsurface, providing insight into the mechanisms for the growth of subsurface Geobacter sp. on Fe(III) oxide and suggesting an approach for functional analysis of other Geobacter proteins found in the subsurface.     

ProDeGe: a computational protocol for fully automated decontamination of genomes

Single amplified genomes and genomes assembled from metagenomes have enabled the exploration of uncultured microorganisms at an unprecedented scale. However, both these types of products are plagued by contamination. Since these genomes are now being generated in a high-throughput manner and sequences from them are propagating into public databases to drive novel scientific discoveries, rigorous quality controls and decontamination protocols are urgently needed. Here, we present ProDeGe (Protocol for fully automated Decontamination of Genomes), the first computational protocol for fully automated decontamination of draft genomes. ProDeGe classifies sequences into two classes—clean and contaminant—using a combination of homology and feature-based methodologies. On average, 84% of sequence from the non-target organism is removed from the data set (specificity) and 84% of the sequence from the target organism is retained (sensitivity). The procedure operates successfully at a rate of ~0.30 CPU core hours per megabase of sequence and can be applied to any type of genome sequence.Recent technological advancements have enabled the large-scale sampling of genomes from uncultured microbial taxa, through the high-throughput sequencing of single amplified genomes (SAGs; Rinke et al., 2013; Swan et al., 2013) and assembly and binning of genomes from metagenomes (GMGs; Cuvelier et al., 2010; Sharon and Banfield, 2013). The importance of these products in assessing community structure and function has been established beyond doubt (Kalisky and Quake, 2011). Multiple Displacement Amplification (MDA) and sequencing of single cells has been immensely successful in capturing rare and novel phyla, generating valuable references for phylogenetic anchoring. However, efforts to conduct MDA and sequencing in a high-throughput manner have been heavily impaired by contamination from DNA introduced by the environmental sample, as well as introduced during the MDA or sequencing process (Woyke et al., 2011; Engel et al., 2014; Field et al., 2014). Similarly, metagenome binning and assembly often carries various errors and artifacts depending on the methods used (Nielsen et al., 2014). Even cultured isolate genomes have been shown to lack immunity to contamination with other species (Parks et al., 2014; Mukherjee et al., 2015). As sequencing of these genome product types rapidly increases, contaminant sequences are finding their way into public databases as reference sequences. It is therefore extremely important to define standardized and automated protocols for quality control and decontamination, which would go a long way towards establishing quality standards for all microbial genome product types.Current procedures for decontamination and quality control of genome sequences in single cells and metagenome bins are heavily manual and can consume hours/megabase when performed by expert biologists. Supervised decontamination typically involves homology-based inspection of ribosomal RNA sequences and protein coding genes, as well as visual analysis of k-mer frequency plots and guanine–cytosine content (Clingenpeel, 2015). Manual decontamination is also possible through the software SmashCell (Harrington et al., 2010), which contains a tool for visual identification of contaminants from a self-organizing map and corresponding U-matrix. Another existing software tool, DeconSeq (Schmieder and Edwards, 2011), automatically removes contaminant sequences, however, the contaminant databases are required input. The former lacks automation, whereas the latter requires prior knowledge of contaminants, rendering both applications impractical for high-throughput decontamination.Here, we introduce ProDeGe, the first fully automated computational protocol for decontamination of genomes. ProDeGe uses a combination of homology-based and sequence composition-based approaches to separate contaminant sequences from the target genome draft. It has been pre-calibrated to discard at least 84% of the contaminant sequence, which results in retention of a median 84% of the target sequence. The standalone software is freely available at http://prodege.jgi-psf.org//downloads/src and can be run on any system that has Perl, R (R Core Team, 2014), Prodigal (Hyatt et al., 2010) and NCBI Blast (Camacho et al., 2009) installed. A graphical viewer allowing further exploration of data sets and exporting of contigs accompanies the web application for ProDeGe at http://prodege.jgi-psf.org, which is open to the wider scientific community as a decontamination service (Supplementary Figure S1).The assembly and corresponding NCBI taxonomy of the data set to be decontaminated are required inputs to ProDeGe (Figure 1a). Contigs are annotated with genes following which, eukaryotic contamination is removed based on homology of genes at the nucleotide level using the eukaryotic subset of NCBI''s Nucleotide database as the reference. For detecting prokaryotic contamination, a curated database of reference contigs from the set of high-quality genomes within the Integrated Microbial Genomes (IMG; Markowitz et al., 2014) system is used as the reference. This ensures that errors in public reference databases due to poor quality of sequencing, assembly and annotation do not negatively impact the decontamination process. Contigs determined as belonging to the target organism based on nucleotide level homology to sequences in the above database are defined as ‘Clean'', whereas those aligned to other organisms are defined as ‘Contaminant''. Contigs whose origin cannot be determined based on alignment are classified as ‘Undecided''. Classified clean and contaminated contigs are used to calibrate the separation in the subsequent 5-mer based binning module, which classifies undecided contigs as ‘Clean'' or ‘Contaminant'' using principal components analysis (PCA) of 5-mer frequencies. This parameter can also be specified by the user. When data sets do not have taxonomy deeper than phylum level, or a single confident taxonomic bin cannot be detected using sequence alignment, solely 9-mer based binning is used due to more accurate overall classification. In the absence of a user-defined cutoff, a pre-calibrated cutoff for 80% or more specificity separates the clean contigs from contaminated sequences in the resulting PCA of the 9-mer frequency matrix. Details on ProDeGe''s custom database, evaluation of the performance of the system and exploration of the parameter space to calibrate ProDeGe for a high accurate classification rate are provided in the Supplementary Material.Open in a separate windowFigure 1(a) Schematic overview of the ProDeGe engine. (b) Features of data sets used to validate ProDeGe: SAGs from the Arabidopsis endophyte sequencing project, MDM project, public data sets found in IMG but not sequenced at the JGI, as well as genomes from metagenomes. All the data and results can be found in Supplementary Table S3.The performance of ProDeGe was evaluated using 182 manually screened SAGs (Figure 1b,Supplementary Table S1) from two studies whose data sets are publicly available within the IMG system: genomes of 107 SAGs from an Arabidopsis endophyte sequencing project and 75 SAGs from the Microbial Dark Matter (MDM) project* (only 75/201 SAGs from the MDM project had 1:1 mapping between contigs in the unscreened and the manually screened versions, hence these were used; Rinke et al., 2013). Manual curation of these SAGs demonstrated that the use of ProDeGe prevented 5311 potentially contaminated contigs in these data sets from entering public databases. Figure 2a demonstrates the sensitivity vs specificity plot of ProDeGe results for the above data sets. Most of the data points in Figure 2a cluster in the top right of the box reflecting a median retention of 89% of the clean sequence (sensitivity) and a median rejection of 100% of the sequence of contaminant origin (specificity). In addition, on average, 84% of the bases of a data set are accurately classified. ProDeGe performs best when the target organism has sequenced homologs at the class level or deeper in its high-quality prokaryotic nucleotide reference database. If the target organism''s taxonomy is unknown or not deeper than domain level, or there are few contigs with taxonomic assignments, a target bin cannot be assessed and thus ProDeGe removes contaminant contigs using sequence composition only. The few samples in Figure 2a that demonstrate a higher rate of false positives (lower specificity) and/or reduced sensitivity typically occur when the data set contains few contaminant contigs or ProDeGe incorrectly assumes that the largest bin is the target bin. Some data sets contain a higher proportion of contamination than target sequence and ProDeGe''s performance can suffer under this condition. However, under all other conditions, ProDeGe demonstrates high speed, specificity and sensitivity (Figure 2). In addition, ProDeGe demonstrates better performance in overall classification when nucleotides are considered than when contigs are considered, illustrating that longer contigs are more accurately classified (Supplementary Table S1).Open in a separate windowFigure 2ProDeGe accuracy and performance scatterplots of 182 manually curated single amplified genomes (SAGs), where each symbol represents one SAG data set. (a) Accuracy shown by sensitivity (proportion of bases confirmed ‘Clean'') vs specificity (proportion of bases confirmed ‘Contaminant'') from the Endophyte and Microbial Dark Matter (MDM) data sets. Symbol size reflects input data set size in megabases. Most points cluster in the top right of the plot, showing ProDeGe''s high accuracy. Median and average overall results are shown in Supplementary Table S1. (b) ProDeGe completion time in central processing unit (CPU) core hours for the 182 SAGs. ProDeGe operates successfully at an average rate of 0.30 CPU core hours per megabase of sequence. Principal components analysis (PCA) of a 9-mer frequency matrix costs more computationally than PCA of a 5-mer frequency matrix used with blast-binning. The lack of known taxonomy for the MDM data sets prevents blast-binning, thus showing longer finishing times than the endophyte data sets, which have known taxonomy for use in blast-binning.All SAGs used in the evaluation of ProDeGe were assembled using SPAdes (Bankevich et al., 2012). In-house testing has shown that reads assembled with SPAdes from different strains or even slightly divergent species of the same genera may be combined into the same contig (Personal communications, KT and Robert Bowers). Ideally, the DNA in a well that gets sequenced belongs to a single cell. In the best case, contaminant sequences need to be at least from a different species to be recognized as such by the homology-based screening stage. In the absence of closely related sequenced organisms, contaminant sequences need to be at least from a different genus to be recognized as such by the composition-based screening stage (Supplementary Material). Thus, there is little risk of ProDeGe separating sequences from clonal populations or strains. We have found species- and genus-level contamination in MDA samples to be rare.To evaluate the quality of publicly available uncultured genomes, ProDeGe was used to screen 185 SAGs and 14 GMGs (Figure 1b). Compared with CheckM (Parks et al., 2014), a tool which calculates an estimate of genome sequence contamination using marker genes, ProDeGe generally marks a higher proportion of sequence as ‘Contaminant'' (Supplementary Table S2). This is because ProDeGe has been calibrated to perform at high specificity levels. The command line version of ProDeGe allows users to conduct their own calibration and specify a user-defined distance cutoff. Further, CheckM only outputs the proportion of contamination, but ProDeGe actually labels each contig as ‘Clean'' or ‘Contaminant'' during the process of automated removal.The web application for ProDeGe allows users to export clean and contaminant contigs, examine contig gene calls with their corresponding taxonomies, and discover contig clusters in the first three components of their k-dimensional space. Non-linear approaches for dimensionality reduction of k-mer vectors are gaining popularity (van der Maaten and Hinton, 2008), but we observed no systematic advantage of using t-Distributed Stochastic Neighbor Embedding over PCA (Supplementary Figure S2).ProDeGe is the first step towards establishing a standard for quality control of genomes from both cultured and uncultured microorganisms. It is valuable for preventing the dissemination of contaminated sequence data into public databases, avoiding resulting misleading analyses. The fully automated nature of the pipeline relieves scientists of hours of manual screening, producing reliably clean data sets and enabling the high-throughput screening of data sets for the first time. ProDeGe, therefore, represents a critical component in our toolkit during an era of next-generation DNA sequencing and cultivation-independent microbial genomics.