Changes in Soil Fungal Communities, Extracellular Enzyme Activities, and Litter Decomposition Across a Fire Chronosequence in Alaskan Boreal Forests

Wildfires are a pervasive disturbance in boreal forests, and the frequency and intensity of boreal wildfires is expected to increase with climate warming. Boreal forests store a large fraction of global soil organic carbon (C), but relatively few studies have documented how wildfires affect soil microbial communities and soil C dynamics. We used a fire chronosequence in upland boreal forests of interior Alaska with sites that were 1, 7, 12, 24, 55, ~90, and ~100 years post-fire to examine the short- and long-term responses of fungal community composition, fungal abundance, extracellular enzyme activity, and litter decomposition to wildfires. We hypothesized that post-fire changes in fungal abundance and community composition would constrain decomposition following fires. We found that wildfires altered the composition of soil fungal communities. The relative abundance of ascomycetes significantly increased following fire whereas basidiomycetes decreased. Post-fire decreases in basidiomycete fungi were likely attributable to declines in ectomycorrhizal fungi. Fungal hyphal lengths in the organic horizon significantly declined in response to wildfire, and they required at least 24 years to return to pre-fire levels. Post-fire reductions in fungal hyphal length were associated with decreased activities of hydrolytic extracellular enzymes. In support of our hypothesis, the decomposition rate of aspen and black spruce litter significantly increased as forests recovered from fire. Our results indicate that post-fire reductions in soil fungal abundance and activity likely inhibit litter decomposition following boreal wildfires. Slower rates of litter decay may lead to decreased heterotrophic respiration from soil following fires and contribute to a negative feedback to climate warming

A new statistical method for curve group analysis of longitudinal gene expression data illustrated for breast cancer in the NOWAC postgenome cohort as a proof of principle

International audienceA new statistical method for curve group analysis of longitudinal gene expression data illustrated for breast cancer in the NOWAC postgenome cohort as a proof of principle Abstract Background: The understanding of changes in temporal processes related to human carcinogenesis is limited. One approach for prospective functional genomic studies is to compile trajectories of differential expression of genes, based on measurements from many case-control pairs. We propose a new statistical method that does not assume any parametric shape for the gene trajectories. Methods: The trajectory of a gene is defined as the curve representing the changes in gene expression levels in the blood as a function of time to cancer diagnosis. In a nested case–control design it consists of differences in gene expression levels between cases and controls. Genes can be grouped into curve groups, each curve group corresponding to genes with a similar development over time. The proposed new statistical approach is based on a set of hypothesis testing that can determine whether or not there is development in gene expression levels over time, and whether this development varies among different strata. Curve group analysis may reveal significant differences in gene expression levels over time among the different strata considered. This new method was applied as a " proof of concept " to breast cancer in the Norwegian Women and Cancer (NOWAC) postgenome cohort, using blood samples collected prospectively that were specifically preserved for transcriptomic analyses (PAX tube). Cohort members diagnosed with invasive breast cancer through 2009 were identified through linkage to the Cancer Registry of Norway, and for each case a random control from the postgenome cohort was also selected, matched by birth year and time of blood sampling, to create a case-control pair. After exclusions, 441 case-control pairs were available for analyses, in which we considered strata of lymph node status at time of diagnosis and time of diagnosis with respect to breast cancer screening visits. Results: The development of gene expression levels in the NOWAC postgenome cohort varied in the last years before breast cancer diagnosis, and this development differed by lymph node status and participation in the Norwegian Breast Cancer Screening Program. The differences among the investigated strata appeared larger in the year before breast cancer diagnosis compared to earlier years.ConclusionsThis approach shows good properties in term of statistical power and type 1 error under minimal assumptions. When applied to a real data set it was able to discriminate between groups of genes with non-linear similar patterns before diagnosis

Source signatures from combined isotopic analyses of PM2.5 carbonaceous and nitrogen aerosols at the peri-urban Taehwa Research Forest, South Korea in summer and fall.

Isotopes are essential tools to apportion major sources of aerosols. We measured the radiocarbon, stable carbon, and stable nitrogen isotopic composition of PM2.5 at Taehwa Research Forest (TRF) near Seoul Metropolitan Area (SMA) during August-October 2014. PM2.5, TC, and TN concentrations were 19.4 ± 10.1 μg m-3, 2.6 ± 0.8 μg C m-3, and 1.4 ± 1.4 μg N m-3, respectively. The δ13C of TC and the δ15N of TN were - 25.4 ± 0.7‰ and 14.6 ± 3.8‰, respectively. EC was dominated by fossil-fuel sources with Fff (EC) of 78 ± 7%. In contrast, contemporary sources were dominant for TC with Fc (TC) of 76 ± 7%, revealing the significant contribution of contemporary sources to OC during the growing season. The isotopic signature carries more detailed information on sources depending on air mass trajectories. The urban influence was dominant under stagnant condition, which was in reasonable agreement with the estimated δ15N of NH4+. The low δ15N (7.0 ± 0.2‰) with high TN concentration was apparent in air masses from Shandong province, indicating fossil fuel combustion as major emission source. In contrast, the high δ15N (16.1 ± 3.2‰) with enhanced TC/TN ratio reveals the impact of biomass burning in the air transported from the far eastern border region of China and Russia. Our findings highlight that the multi-isotopic composition is a useful tool to identify emission sources and to trace regional sources of carbonaceous and nitrogen aerosols

3D-HST+CANDELS : the evolution of the galaxy size-mass distribution since z=3

Spectroscopic+photometric redshifts, stellar mass estimates, and rest-frame colors from the 3D-HST survey are combined with structural parameter measurements from CANDELS imaging to determine the galaxy size-mass distribution over the redshift range 0 < z < 3. Separating early- and late-type galaxies on the basis of star-formation activity, we confirm that early-type galaxies are on average smaller than late-type galaxies at all redshifts, and we find a significantly different rate of average size evolution at fixed galaxy mass, with fast evolution for the early-type population, R eff∝(1 + z)–1.48, and moderate evolution for the late-type population, R eff∝(1 + z)-0.75Peer reviewedFinal Accepted Versio

Building a genomic framework for prospective MRSA surveillance in the United Kingdom and the Republic of Ireland.

The correct interpretation of microbial sequencing data applied to surveillance and outbreak investigation depends on accessible genomic databases to provide vital genetic context. Our aim was to construct and describe a United Kingdom MRSA database containing over 1000 methicillin-resistant Staphylococcus aureus (MRSA) genomes drawn from England, Northern Ireland, Wales, Scotland, and the Republic of Ireland over a decade. We sequenced 1013 MRSA submitted to the British Society for Antimicrobial Chemotherapy by 46 laboratories between 2001 and 2010. Each isolate was assigned to a regional healthcare referral network in England and was otherwise grouped based on country of origin. Phylogenetic reconstructions were used to contextualize MRSA outbreak investigations and to detect the spread of resistance. The majority of isolates (n = 783, 77%) belonged to CC22, which contains the dominant United Kingdom epidemic clone (EMRSA-15). There was marked geographic structuring of EMRSA-15, consistent with widespread dissemination prior to the sampling decade followed by local diversification. The addition of MRSA genomes from two outbreaks and one pseudo-outbreak demonstrated the certainty with which outbreaks could be confirmed or refuted. We identified local and regional differences in antibiotic resistance profiles, with examples of local expansion, as well as widespread circulation of mobile genetic elements across the bacterial population. We have generated a resource for the future surveillance and outbreak investigation of MRSA in the United Kingdom and Ireland and have shown the value of this during outbreak investigation and tracking of antimicrobial resistance.We are grateful for assistance from the library construction, sequencing and core informatics teams at the Wellcome Trust Sanger Institute. We acknowledge David Harris and Martin Aslett for their help in submitting the sequenced isolates to public databases. The study was supported by grants from the UKCRC Translational Infection Research Initiative, and the Medical Research Council (Grant Number G1000803) with contributions to the Grant from the Biotechnology and Biological Sciences Research Council, the National Institute for Health Research on behalf of the Department of Health, and the Chief Scientist Office of the Scottish Government Health Directorate (to Prof. Peacock); by Wellcome Trust grant number 098051 awarded to the Wellcome Trust Sanger Institute; and by a Healthcare Infection Society Major Reasearch Grant. MET is a Clinician Scientist Fellow, supported by the Academy of Medical Sciences and the Health Foundation and the NIHR Cambridge Biomedical Research Centre. BGS was supported by Wellcome Trust grant number 089472. The study was approved by the University of Cambridge Human Biology Research Ethics Committee (reference HBREC.2013.05), and by the Cambridge University Hospitals NHS Foundation Trust Research and Development Department (reference A092869). Isolates were supplied by the BSAC Resistance Surveillance Project.This is the final version of the article. It first appeared from Cold Spring Harbor Laboratory Press via http://dx.doi.org/10.1101/gr.196709.11

Building a genomic framework for prospective MRSA surveillance in the United Kingdom and the Republic of Ireland

The correct interpretation of microbial sequencing data applied to surveillance and outbreak investigation depends on accessible genomic databases to provide vital genetic context. Our aim was to construct and describe a United Kingdom MRSA database containing over 1000 methicillin-resistant Staphylococcus aureus (MRSA) genomes drawn from England, Northern Ireland, Wales, Scotland, and the Republic of Ireland over a decade. We sequenced 1013 MRSA submitted to the British Society for Antimicrobial Chemotherapy by 46 laboratories between 2001 and 2010. Each isolate was assigned to a regional healthcare referral network in England and was otherwise grouped based on country of origin. Phylogenetic reconstructions were used to contextualize MRSA outbreak investigations and to detect the spread of resistance. The majority of isolates (n = 783, 77%) belonged to CC22, which contains the dominant United Kingdom epidemic clone (EMRSA-15). There was marked geographic structuring of EMRSA-15, consistent with widespread dissemination prior to the sampling decade followed by local diversification. The addition ofMRSAgenomes fromtwo outbreaks and one pseudo-outbreak demonstrated the certainty with which outbreaks could be confirmed or refuted. Weidentified local and regional differences in antibiotic resistance profiles, with examples of local expansion, as well as widespread circulation of mobile genetic elements across the bacterial population. Wehave generated a resource for the future surveillance and outbreak investigation ofMRSAin the United Kingdom and Ireland and have shown the value of this during outbreak investigation and tracking of antimicrobial resistance.</p