Novel copper-containing membrane monooxygenases (CuMMOs) encoded by alkane-utilizing Betaproteobacteria.

Copper-containing membrane monooxygenases (CuMMOs) are encoded by xmoCAB(D) gene clusters and catalyze the oxidation of methane, ammonia, or some short-chain alkanes and alkenes. In a metagenome constructed from an oilsands tailings pond we detected an xmoCABD gene cluster with <59% derived protein sequence identity to genes from known bacteria. Stable isotope probing experiments combined with a specific xmoA qPCR assay demonstrated that the bacteria possessing these genes were incapable of methane assimilation, but did grow on ethane and propane. Single-cell amplified genomes (SAGs) from propane-enriched samples were screened with the specific PCR assay to identify bacteria possessing the target gene cluster. Multiple SAGs of Betaproteobacteria belonging to the genera Rhodoferax and Polaromonas possessed homologues of the metagenomic xmoCABD gene cluster. Unexpectedly, each of these two genera also possessed other xmoCABD paralogs, representing two additional lineages in phylogenetic analyses. Metabolic reconstructions from SAGs predicted that neither bacterium encoded enzymes with the potential to support catabolic methane or ammonia oxidation, but that both were capable of higher n-alkane degradation. The involvement of the encoded CuMMOs in alkane oxidation was further suggested by reverse transcription PCR analyses, which detected elevated transcription of the xmoA genes upon enrichment of water samples with propane as the sole energy source. Enrichments, isotope incorporation studies, genome reconstructions, and gene expression studies therefore all agreed that the unknown xmoCABD operons did not encode methane or ammonia monooxygenases, but rather n-alkane monooxygenases. This study broadens the known diversity of CuMMOs and identifies these enzymes in non-nitrifying Betaproteobacteria

Substrate limitations for heterotrophs: Implications for models that estimate the seasonal cycle of atmospheric CO_2

We examine the sensitivity of the seasonal cycle of heterotrophic respiration to model estimates of litterfall seasonality, herbivory, plant allocation, tissue chemistry, and land use. As a part of this analysis, we compare heterotrophic respiration models based solely on temperature and soil moisture controls (zero‐order models) with models that depend on available substrate as well (first‐order models). As indicators of regional and global CO_2 exchange, we use maps of monthly global net ecosystem production, growing season net flux (GSNF), and simulated atmospheric CO_2 concentrations from an atmospheric tracer transport model. In one first‐order model, CASA, variations on the representation of the seasonal flow of organic matter from plants to heterotrophs can increase global GSNF as much as 60% (5.7 Pg C yr^(−1)) above estimates obtained from a zero‐order model. Under a new first‐order scheme that includes separate seasonal dynamics for leaf litterfall, fine root mortality, coarse woody debris, and herbivory, we observe an increase in GSNF of 8% (0.7 Pg C yr^(−1)) over that predicted by the zero‐order model. The increase in seasonality of CO2 exchange in first‐order models reflects the dynamics of labile litter fractions; specifically, the rapid decomposition of a pulse of labile leaf and fine root litter that enters the heterotrophic community primarily from the middle to the end of the growing season shifts respiration outside the growing season. From the perspective of a first‐order model, we then explore the consequences of land use change and winter temperature anomalies on the amplitude of the seasonal cycle of atmospheric CO_2. Agricultural practices that accelerate decomposition may drive a long‐term increase in the amplitude, independent of human impacts on plant production. Consideration of first‐order litter decomposition dynamics may also help explain year‐to‐year variation in the amplitude

Leukotriene antagonists as first-line or add-on asthma controller therapy

Most randomized trials of treatment for asthma study highly selected patients under idealized conditions. METHODS: We conducted two parallel, multicenter, pragmatic trials to evaluate the real-world effectiveness of a leukotriene-receptor antagonist (LTRA) as compared with either an inhaled glucocorticoid for first-line asthma-controller therapy or a long-acting beta(2)-agonist (LABA) as add-on therapy in patients already receiving inhaled glucocorticoid therapy. Eligible primary care patients 12 to 80 years of age had impaired asthma-related quality of life (Mini Asthma Quality of Life Questionnaire [MiniAQLQ] score =6) or inadequate asthma control (Asthma Control Questionnaire [ACQ] score =1). We randomly assigned patients to 2 years of open-label therapy, under the care of their usual physician, with LTRA (148 patients) or an inhaled glucocorticoid (158 patients) in the first-line controller therapy trial and LTRA (170 patients) or LABA (182 patients) added to an inhaled glucocorticoid in the add-on therapy trial. RESULTS: Mean MiniAQLQ scores increased by 0.8 to 1.0 point over a period of 2 years in both trials. At 2 months, differences in the MiniAQLQ scores between the two treatment groups met our definition of equivalence (95% confidence interval [CI] for an adjusted mean difference, -0.3 to 0.3). At 2 years, mean MiniAQLQ scores approached equivalence, with an adjusted mean difference between treatment groups of -0.11 (95% CI, -0.35 to 0.13) in the first-line controller therapy trial and of -0.11 (95% CI, -0.32 to 0.11) in the add-on therapy trial. Exacerbation rates and ACQ scores did not differ significantly between the two groups. CONCLUSIONS: Study results at 2 months suggest that LTRA was equivalent to an inhaled glucocorticoid as first-line controller therapy and to LABA as add-on therapy for diverse primary care patients. Equivalence was not proved at 2 years. The interpretation of results of pragmatic research may be limited by the crossover between treatment groups and lack of a placebo group

Immunomodulators for Asthma

New information regarding the molecular mechanisms of allergic disorders has led to a variety of novel therapeutic approaches. This article briefly reviews the pathogenesis of asthma and allergic diseases, discusses the rationale behind using immunomodulators in these diseases; and examines the therapeutic effects of immunomodulators on allergic diseases. There are a number of immunomodulators that have been developed for the treatment of allergic disorders. Some have looked very promising in pre-clinical trials, but have not shown significant benefits in human clinical trials thus indicating the disparity between mouse models and human asthma. This review focuses on immunomodulators that are in human clinical trials and not molecules in pre-clinical development

Substrate limitations for heterotrophs: Implications for models that estimate the seasonal cycle of atmospheric CO_2

We examine the sensitivity of the seasonal cycle of heterotrophic respiration to model estimates of litterfall seasonality, herbivory, plant allocation, tissue chemistry, and land use. As a part of this analysis, we compare heterotrophic respiration models based solely on temperature and soil moisture controls (zero‐order models) with models that depend on available substrate as well (first‐order models). As indicators of regional and global CO_2 exchange, we use maps of monthly global net ecosystem production, growing season net flux (GSNF), and simulated atmospheric CO_2 concentrations from an atmospheric tracer transport model. In one first‐order model, CASA, variations on the representation of the seasonal flow of organic matter from plants to heterotrophs can increase global GSNF as much as 60% (5.7 Pg C yr^(−1)) above estimates obtained from a zero‐order model. Under a new first‐order scheme that includes separate seasonal dynamics for leaf litterfall, fine root mortality, coarse woody debris, and herbivory, we observe an increase in GSNF of 8% (0.7 Pg C yr^(−1)) over that predicted by the zero‐order model. The increase in seasonality of CO2 exchange in first‐order models reflects the dynamics of labile litter fractions; specifically, the rapid decomposition of a pulse of labile leaf and fine root litter that enters the heterotrophic community primarily from the middle to the end of the growing season shifts respiration outside the growing season. From the perspective of a first‐order model, we then explore the consequences of land use change and winter temperature anomalies on the amplitude of the seasonal cycle of atmospheric CO_2. Agricultural practices that accelerate decomposition may drive a long‐term increase in the amplitude, independent of human impacts on plant production. Consideration of first‐order litter decomposition dynamics may also help explain year‐to‐year variation in the amplitude

Complementary Metagenomic Approaches Improve Reconstruction of Microbial Diversity in a Forest Soil

Soil ecosystems harbor diverse microorganisms and yet remain only partially characterized as neither single-cell sequencing nor whole-community sequencing offers a complete picture of these complex communities. Thus, the genetic and metabolic potential of this “uncultivated majority” remains underexplored. To address these challenges, we applied a pooled-cell-sorting-based mini-metagenomics approach and compared the results to bulk metagenomics. Informatic binning of these data produced 200 mini-metagenome assembled genomes (sorted-MAGs) and 29 bulk metagenome assembled genomes (MAGs). The sorted and bulk MAGs increased the known phylogenetic diversity of soil taxa by 7.2% with respect to the Joint Genome Institute IMG/M database and showed clade-specific sequence recruitment patterns across diverse terrestrial soil metagenomes. Additionally, sorted-MAGs expanded the rare biosphere not captured through MAGs from bulk sequences, exemplified through phylogenetic and functional analyses of members of the phylum Bacteroidetes. Analysis of 67 Bacteroidetes sorted-MAGs showed conserved patterns of carbon metabolism across four clades. These results indicate that mini-metagenomics enables genome-resolved investigation of predicted metabolism and demonstrates the utility of combining metagenomics methods to tap into the diversity of heterogeneous microbial assemblages. IMPORTANCE Microbial ecologists have historically used cultivation-based approaches as well as amplicon sequencing and shotgun metagenomics to characterize microbial diversity in soil. However, challenges persist in the study of microbial diversity, including the recalcitrance of the majority of microorganisms to laboratory cultivation and limited sequence assembly from highly complex samples. The uncultivated majority thus remains a reservoir of untapped genetic diversity. To address some of the challenges associated with bulk metagenomics as well as low throughput of single-cell genomics, we applied flow cytometry-enabled mini-metagenomics to capture expanded microbial diversity from forest soil and compare it to soil bulk metagenomics. Our resulting data from this pooled-cell sorting approach combined with bulk metagenomics revealed increased phylogenetic diversity through novel soil taxa and rare biosphere members. In-depth analysis of genomes within the highly represented Bacteroidetes phylum provided insights into conserved and clade-specific patterns of carbon metabolism

A novel preclinical model for rheumatoid arthritis research

Based on increasing knowledge on the pathogenesis of rheumatoid arthritis (RA), more and more potential therapeutics have been developed. To evaluate their therapeutic efficacy, safety and toxicity, appropriate animal models are required. Although rodent models of RA have been extensively used for preclinical evaluation, the differences between rodents and humans limit their usability for some species-specific therapeutics. Therefore, autoimmune arthritis developed in a non-human primate with essential hallmarks of RA will be an alternative model for preclinical studies

Efficacy of BI 671800, an oral CRTH2 antagonist, in poorly controlled asthma as sole controller and in the presence of inhaled corticosteroid treatment

The prostaglandin D2 (PGD2) receptor, CRTH2, plays a role in allergic airway inflammation. The efficacy of BI 671800, a CRTH2 antagonist, was assessed in 2 separate trials in patients with asthma, in either the absence or the presence of inhaled corticosteroid (ICS) therapy. In this study, BI 671800 (50, 200 or 400 mg) and fluticasone propionate (220 mg) all given twice daily (bid) were compared with bid placebo in symptomatic controller-naïve adults with asthma (Trial 1), and BI 671800 400 mg bid compared with montelukast 10 mg once daily (qd), and matching placebo bid, in patients with asthma receiving inhaled fluticasone (88 mg bid) (Trial 2). The primary endpoint in both trials was change from baseline in trough forced expiratory volume in 1 s (FEV1) percent predicted. After 6 weeks' treatment, adjusted mean treatment differences (SE) for the primary endpoint compared with placebo in Trial 1 were 3.08% (1.65%), 3.59% (1.60%) and 3.98% (1.64%) for BI 671800 50, 200 and 400 mg bid, respectively, and 8.62% (1.68%) for fluticasone 220 mg bid (p ¼ 0.0311, p ¼ 0.0126, p ¼ 0.0078 and p < 0.0001, respectively). In Trial 2, adjusted mean FEV1 (SE) treatment differences compared with placebo were 3.87% (1.49%) for BI 671800 400 mg bid and 2.37% (1.57%) for montelukast (p ¼ 0.0050 and p ¼ 0.0657, respectively). These findings suggest that BI 671800 is associated with a small improvement in FEV1 in symptomatic controller-naïve asthma patients, and in patients on ICS

Non-HLA genes PTPN22, CDK6 and PADI4 are associated with specific autoantibodies in HLA-defined subgroups of rheumatoid arthritis

Introduction: Genetic susceptibility to complex diseases has been intensively studied during the last decade, yet only signals with small effect have been found leaving open the possibility that subgroups within complex traits show stronger association signals. In rheumatoid arthritis (RA), autoantibody production serves as a helpful discriminator in genetic studies and today anti-citrullinated cyclic peptide (anti-CCP) antibody positivity is employed for diagnosis of disease. The HLA-DRB1 locus is known as the most important genetic contributor for the risk of RA, but is not sufficient to drive autoimmunity and additional genetic and environmental factors are involved. Hence, we addressed the association of previously discovered RA loci with disease-specific autoantibody responses in RA patients stratified by HLA-DRB1*04. Methods: We investigated 2178 patients from three RA cohorts from Sweden and Spain for 41 genetic variants and four autoantibodies, including the generic anti-CCP as well as specific responses towards citrullinated peptides from vimentin, alpha-enolase and type II collagen. Results: Our data demonstrated different genetic associations of autoantibody-positive disease subgroups in relation to the presence of DRB1*04. Two specific subgroups of autoantibody-positive RA were identified. The SNP in PTPN22 was associated with presence of anti-citrullinated enolase peptide antibodies in carriers of HLA-DRB1*04 (Cochran-Mantel-Haenszel test P = 0.0001, P corrected <0.05), whereas SNPs in CDK6 and PADI4 were associated with anti-CCP status in DRB1*04 negative patients (Cochran-Mantel-Haenszel test P = 0.0004, P corrected <0.05 for both markers). Additionally we see allelic correlation with autoantibody titers for PTPN22 SNP rs2476601 and anti-citrullinated enolase peptide antibodies in carriers of HLA-DRB1*04 (Mann Whitney test P = 0.02) and between CDK6 SNP rs42041 and anti-CCP in non-carriers of HLA-DRB1*04 (Mann Whitney test P = 0.02). Conclusion: These data point to alternative pathways for disease development in clinically similar RA subgroups and suggest an approach for study of genetic complexity of disease with strong contribution of HLA