The LacI–family transcription factor, RbsR, is a pleiotropic regulator of motility, virulence, siderophore and antibiotic production, gas vesicle morphogenesis and flotation in Serratia

Gas vesicles (GVs) are proteinaceous, gas-filled organelles used by some bacteria to enable upward movement into favorable air/liquid interfaces in aquatic environments. Serratia sp. ATCC39006 (S39006) was the first enterobacterium discovered to produce GVs naturally. The regulation of GV assembly in this host is complex and part of a wider regulatory network affecting various phenotypes, including antibiotic biosynthesis. To identify new regulators of GVs, a comprehensive mutant library containing 71,000 insertion mutants was generated by random transposon mutagenesis and 311 putative GV-defective mutants identified. Three of these mutants were found to have a transposon inserted in a LacI family transcription regulator gene (rbsR) of the putative ribose operon. Each of these rbsR mutants was GV-defective; no GVs were visible by phase contrast microscopy (PCM) or transmission electron microscopy (TEM). GV deficiency was caused by the reduction of gvpA1 and gvrA transcription (the first genes of the two contiguous operons in the GV gene locus). Our results also showed that a mutation in rbsR was highly pleiotropic; the production of two secondary metabolites (carbapenem and prodigiosin antibiotics) was abolished. Interestingly, the intrinsic resistance to the carbapenem antibiotic was not affected by the rbsR mutation. In addition, the production of a siderophore, cellulase and plant virulence was reduced in the mutant, whereas it exhibited increased swimming and swarming motility. The RbsR protein was predicted to bind to regions upstream of at least18 genes in S39006 including rbsD (the first gene of the ribose operon) and gvrA. Electrophoretic mobility shift assays (EMSA) confirmed that RbsR bound to DNA sequences upstream of rbsD, but not gvrA. The results of this study indicate that RbsR is a global regulator that affects the modulation of GV biogenesis, but also with complex pleiotropic physiological impacts in S39006.CL was sponsored under the Academic Staff Training Scheme from the Malaysian Ministry of Education. Work in the Salmond lab is funded by the Biotechnology and Biological Sciences Research Council (BBSRC)—UK

Diversity of isoprene-degrading bacteria in phyllosphere and soil communities from a high isoprene-emitting environment: a Malaysian oil palm plantation

Background: Isoprene is the most abundantly produced biogenic volatile organic compound (BVOC) on Earth, with annual global emissions almost equal to those of methane. Despite its importance in atmospheric chemistry and climate, little is known about the biological degradation of isoprene in the environment. The largest source of isoprene is terrestrial plants, and oil palms, the cultivation of which is expanding rapidly, are among the highest isoprene-producing trees. Results: DNA stable isotope probing (DNA-SIP) to study the microbial isoprene-degrading community associated with oil palm trees revealed novel genera of isoprene-utilising bacteria including Novosphingobium, Pelomonas, Rhodoblastus, Sphingomonas and Zoogloea in both oil palm soils and on leaves. Amplicon sequencing of isoA genes, which encode the α-subunit of the isoprene monooxygenase (IsoMO), a key enzyme in isoprene metabolism, confirmed that oil palm trees harbour a novel diversity of isoA sequences. In addition, metagenome assembled genomes (MAGs) were reconstructed from oil palm soil and leaf metagenomes and putative isoprene degradation genes were identified. Analysis of unenriched metagenomes showed that isoA-containing bacteria are more abundant in soils than in the oil palm phyllosphere. Conclusion: This study greatly expands the known diversity of bacteria that can metabolise isoprene and contributes to a better understanding of the biological degradation of this important but neglected climate-active gas

The relationship between smoking and quality of life in advanced lung cancer patients: a prospective longitudinal study.

PURPOSE: Smoking is a major cause of lung cancer, and continued smoking may compromise treatment efficacy and quality of life (health-related quality of life (HRQoL)) in patients with advanced lung cancer. Our aims were to determine (i) preference for treatments which promote quality over length of life depending on smoking status, (ii) the relationship between HRQoL and smoking status at diagnosis (T1), after controlling for demographic and clinical variables, and (iii) changes in HRQoL 6 months after diagnosis (T2) depending on smoking status. METHODS: Two hundred ninety-six patients with advanced lung cancer were given questionnaires to assess HRQoL (EORTC QLQ-C30), time-trade-off for life quality versus quantity (QQQ) and smoking history (current, former or never smoker) at diagnosis (T1) and 6 months later (T2). Medical data were extracted from case records. RESULTS: Questionnaires were returned by 202 (68.2 %) patients at T1 and 114 (53.3 %) at T2. Patients favoured treatments that would enhance quality of life over increased longevity. Those who continued smoking after diagnosis reported worse HRQoL than former smokers or those who never smoked. Smoking status was a significant independent predictor of coughing in T1 (worse in smokers) and cognitive functioning in T2 (better in never smokers). CONCLUSIONS: Smoking by patients with advanced lung cancer is associated with worse symptoms on diagnosis and poorer HRQoL for those who continue smoking. The results have implications to help staff explain the consequences of smoking to patients

Climate controls over ecosystem metabolism: insights from a fifteen-year inductive artificial neural network synthesis for a subalpine forest

Eddy covariance (EC) datasets have provided insight into climate determinants of net ecosystem productivity (NEP) and evapotranspiration (ET) in natural ecosystems for decades, but most EC studies were published in serial fashion such that one study's result became the following study's hypothesis. This approach reflects the hypothetico-deductive process by focusing on previously derived hypotheses. A synthesis of this type of sequential inference reiterates subjective biases and may amplify past assumptions about the role, and relative importance, of controls over ecosystem metabolism. Long-term EC datasets facilitate an alternative approach to synthesis: the use of inductive data-based analyses to re-examine past deductive studies of the same ecosystem. Here we examined the seasonal climate determinants of NEP and ET by analyzing a 15-year EC time-series from a subalpine forest using an ensemble of Artificial Neural Networks (ANNs) at the half-day (daytime/nighttime) time-step. We extracted relative rankings of climate drivers and driver-response relationships directly from the dataset with minimal a priori assumptions. The ANN analysis revealed temperature variables as primary climate drivers of NEP and daytime ET, when all seasons are considered, consistent with the assembly of past studies. New relations uncovered by the ANN approach include the role of soil moisture in driving daytime NEP during the snowmelt period, the nonlinear response of NEP to temperature across seasons, and the low relevance of summer rainfall for NEP or ET at the same daytime/nighttime time step. These new results offer a more complete perspective of climate-ecosystem interactions at this site than traditional deductive analyses alone

Investigating rare pathogenic/likely pathogenic exonic variation in bipolar disorder

Bipolar disorder (BD) is a serious mental illness with substantial common variant heritability. However, the role of rare coding variation in BD is not well established. We examined the protein-coding (exonic) sequences of 3,987 unrelated individuals with BD and 5,322 controls of predominantly European ancestry across four cohorts from the Bipolar Sequencing Consortium (BSC). We assessed the burden of rare, protein-altering, single nucleotide variants classified as pathogenic or likely pathogenic (P-LP) both exome-wide and within several groups of genes with phenotypic or biologic plausibility in BD. While we observed an increased burden of rare coding P-LP variants within 165 genes identified as BD GWAS regions in 3,987 BD cases (meta-analysis OR = 1.9, 95% CI = 1.3-2.8, one-sided p = 6.0 × 10-4), this enrichment did not replicate in an additional 9,929 BD cases and 14,018 controls (OR = 0.9, one-side p = 0.70). Although BD shares common variant heritability with schizophrenia, in the BSC sample we did not observe a significant enrichment of P-LP variants in SCZ GWAS genes, in two classes of neuronal synaptic genes (RBFOX2 and FMRP) associated with SCZ or in loss-of-function intolerant genes. In this study, the largest analysis of exonic variation in BD, individuals with BD do not carry a replicable enrichment of rare P-LP variants across the exome or in any of several groups of genes with biologic plausibility. Moreover, despite a strong shared susceptibility between BD and SCZ through common genetic variation, we do not observe an association between BD risk and rare P-LP coding variants in genes known to modulate risk for SCZ

Gene probing reveals the widespread distribution, diversity and abundance of isoprene-degrading bacteria in the environment

Background: Approximately 500 Tg of isoprene are emitted to the atmosphere annually, an amount similar to that of methane, and despite its significant effects on the climate, very little is known about the biological degradation of isoprene in the environment. Isolation and characterisation of isoprene degraders at the molecular level has allowed the development of probes targeting isoA encoding the α-subunit of the isoprene monooxygenase. This enzyme belongs to the soluble diiron centre monooxygenase family and catalyses the first step in the isoprene degradation pathway. The use of probes targeting key metabolic genes is a successful approach in molecular ecology to study specific groups of bacteria in complex environments. Here, we developed and tested a novel isoA PCR primer set to study the distribution, abundance, and diversity of isoprene degraders in a wide range of environments. Results: The new isoA probes specifically amplified isoA genes from taxonomically diverse isoprene-degrading bacteria including members of the genera Rhodococcus, Variovorax, and Sphingopyxis. There was no cross-reactivity with genes encoding related oxygenases from non-isoprene degraders. Sequencing of isoA amplicons from DNA extracted from environmental samples enriched with isoprene revealed that most environments tested harboured a considerable variety of isoA sequences, with poplar leaf enrichments containing more phylogenetically diverse isoA genes. Quantification by qPCR using these isoA probes revealed that isoprene degraders are widespread in the phyllosphere, terrestrial, freshwater and marine environments. Specifically, soils in the vicinity of high isoprene-emitting trees contained the highest number of isoprene-degrading bacteria. Conclusion: This study provides the molecular ecology tools to broaden our knowledge of the distribution, abundance and diversity of isoprene degraders in the environment, which is a fundamental step necessary to assess the impact that microbes have in mitigating the effects of this important climate-active gas

The mechanisms by which polyamines accelerate tumor spread

Increased polyamine concentrations in the blood and urine of cancer patients reflect the enhanced levels of polyamine synthesis in cancer tissues arising from increased activity of enzymes responsible for polyamine synthesis. In addition to their de novo polyamine synthesis, cells can take up polyamines from extracellular sources, such as cancer tissues, food, and intestinal microbiota. Because polyamines are indispensable for cell growth, increased polyamine availability enhances cell growth. However, the malignant potential of cancer is determined by its capability to invade to surrounding tissues and metastasize to distant organs. The mechanisms by which increased polyamine levels enhance the malignant potential of cancer cells and decrease anti-tumor immunity are reviewed. Cancer cells with a greater capability to synthesize polyamines are associated with increased production of proteinases, such as serine proteinase, matrix metalloproteinases, cathepsins, and plasminogen activator, which can degrade surrounding tissues. Although cancer tissues produce vascular growth factors, their deregulated growth induces hypoxia, which in turn enhances polyamine uptake by cancer cells to further augment cell migration and suppress CD44 expression. Increased polyamine uptake by immune cells also results in reduced cytokine production needed for anti-tumor activities and decreases expression of adhesion molecules involved in anti-tumor immunity, such as CD11a and CD56. Immune cells in an environment with increased polyamine levels lose anti-tumor immune functions, such as lymphokine activated killer activities. Recent investigations revealed that increased polyamine availability enhances the capability of cancer cells to invade and metastasize to new tissues while diminishing immune cells' anti-tumor immune functions

Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors

BACKGROUND: Suicide is a leading cause of death worldwide, and nonfatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both have substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders. METHODS: We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium (ISGC). The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via multitrait-based conditional and joint analysis, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders, and other known risk factors. RESULTS: Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, the latter of which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking behavior, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking behavior, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status, and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with nonpsychiatric traits remained largely unchanged. CONCLUSIONS: Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders

Author Correction: The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data

The following authors were omitted from the original version of this Data Descriptor: Markus Reichstein and Nicolas Vuichard. Both contributed to the code development and N. Vuichard contributed to the processing of the ERA-Interim data downscaling. Furthermore, the contribution of the co-author Frank Tiedemann was re-evaluated relative to the colleague Corinna Rebmann, both working at the same sites, and based on this re-evaluation a substitution in the co-author list is implemented (with Rebmann replacing Tiedemann). Finally, two affiliations were listed incorrectly and are corrected here (entries 190 and 193). The author list and affiliations have been amended to address these omissions in both the HTML and PDF versions

The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data.

The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible