Effects of soil organic matter properties and microbial community composition on enzyme activities in cryoturbated arctic soils

Enzyme-mediated decomposition of soil organic matter (SOM) is controlled, amongst other factors, by organic matter properties and by the microbial decomposer community present. Since microbial community composition and SOM properties are often interrelated and both change with soil depth, the drivers of enzymatic decomposition are hard to dissect. We investigated soils from three regions in the Siberian Arctic, where carbon rich topsoil material has been incorporated into the subsoil (cryoturbation). We took advantage of this subduction to test if SOM properties shape microbial community composition, and to identify controls of both on enzyme activities. We found that microbial community composition (estimated by phospholipid fatty acid analysis), was similar in cryoturbated material and in surrounding subsoil, although carbon and nitrogen contents were similar in cryoturbated material and topsoils. This suggests that the microbial community in cryoturbated material was not well adapted to SOM properties. We also measured three potential enzyme activities (cellobiohydrolase, leucine-amino-peptidase and phenoloxidase) and used structural equation models (SEMs) to identify direct and indirect drivers of the three enzyme activities. The models included microbial community composition, carbon and nitrogen contents, clay content, water content, and pH. Models for regular horizons, excluding cryoturbated material, showed that all enzyme activities were mainly controlled by carbon or nitrogen. Microbial community composition had no effect. In contrast, models for cryoturbated material showed that enzyme activities were also related to microbial community composition. The additional control of microbial community composition could have restrained enzyme activities and furthermore decomposition in general. The functional decoupling of SOM properties and microbial community composition might thus be one of the reasons for low decomposition rates and the persistence of 400 Gt carbon stored in cryoturbated material

Laboratory Analysis of Tularemia in Wild-Trapped, Commercially Traded Prairie Dogs, Texas, 2002

Oropharyngeal tularemia was identified as the cause of a die-off in captured wild prairie dogs at a commercial exotic animal facility in Texas. From this point source, Francisella tularensis–infected prairie dogs were traced to animals distributed to the Czech Republic and to a Texas pet shop. F. tularensis culture isolates were recovered tissue specimens from 63 prairie dogs, including one each from the secondary distribution sites. Molecular and biochemical subtyping indicated that all isolates were F. tularensis subsp. holarctica (Type B). Microagglutination assays detected antibodies against F. tularensis, with titers as great as 1:4,096 in some live animals. All seropositive animals remained culture positive, suggesting that prairie dogs may act as chronic carriers of F. tularensis. These findings demonstrate the need for additional studies of tularemia in prairie dogs, given the seriousness of the resulting disease, the fact that prairie dogs are sold commercially as pets, and the risk for pet-to-human transmission

From Understanding to Sustainable Use of Peatlands: The WETSCAPES Approach

Of all terrestrial ecosystems, peatlands store carbon most effectively in long-term scales of millennia. However, many peatlands have been drained for peat extraction or agricultural use. This converts peatlands from sinks to sources of carbon, causing approx. 5% of the anthropogenic greenhouse effect and additional negative effects on other ecosystem services. Rewetting peatlands can mitigate climate change and may be combined with management in the form of paludiculture. Rewetted peatlands, however, do not equal their pristine ancestors and their ecological functioning is not understood. This holds true especially for groundwater-fed fens. Their functioning results from manifold interactions and can only be understood following an integrative approach of many relevant fields of science, which we merge in the interdisciplinary project WETSCAPES. Here, we address interactions among water transport and chemistry, primary production, peat formation, matter transformation and transport, microbial community, and greenhouse gas exchange using state of the art methods. We record data on six study sites spread across three common fen types (Alder forest, percolation fen, and coastal fen), each in drained and rewetted states. First results revealed that indicators reflecting more long-term effects like vegetation and soil chemistry showed a stronger differentiation between drained and rewetted states than variables with a more immediate reaction to environmental change, like greenhouse gas (GHG) emissions. Variations in microbial community composition explained differences in soil chemical data as well as vegetation composition and GHG exchange. We show the importance of developing an integrative understanding of managed fen peatlands and their ecosystem functioning.

Who is Wearing a Mask? Gender-, Age-, and Location-Related Differences During the COVID-19 Pandemic

Masks are an effective tool in combatting the spread of COVID-19, but some people still resist wearing them and mask-wearing behavior has not been experimentally studied in the United States. To understand the demographics of mask wearers and resistors, and the impact of mandates on mask-wearing behavior, we observed shoppers (n = 9935) entering retail stores during periods of June, July, and August 2020. Approximately 41% of the June sample wore a mask. At that time, the odds of an individual wearing a mask increased significantly with age and was also 1.5x greater for females than males. Additionally, the odds of observing a mask on an urban or suburban shopper were ~4x that for rural areas. Mask mandates enacted in late July and August increased mask-wearing compliance to over 90% in all groups, but a small percentage of resistors remained. Thus, gender, age, and location factor into whether shoppers in the United States wear a mask or face covering voluntarily. Additionally, mask mandates are necessary to increase mask wearing among the public to a level required to mitigate the spread of COVID-19

Pathogen Specificity and Autoimmunity Are Distinct Features of Antigen-Driven Immune Responses in Neuroborreliosis▿

Neuroborreliosis (NB) is a chronic infectious disease of the central nervous system (CNS) caused by a tick-borne spirochete, Borrelia burgdorferi. In addition to direct effects of the causative infectious agent, additional immunity-mediated mechanisms are thought to play a role in the CNS pathology of NB. In order to further understand the involvement of humoral immune mechanisms in NB, we dissected the intrathecal antibody responses down to the single-plasma-cell level. Starting with single-cell reverse transcription-PCR of fluorescence-activated cell sorter-sorted cerebrospinal fluid plasma cells from an NB patient, we identified expanded clones and resurrected the antigen specificity of their secreted antibodies through recombinant expression of the correctly paired immunoglobulin heavy- and light-chain genes as monoclonal antibodies (MAbs). As expected, we found specificity for the causative infectious agent, B. burgdorferi, among the clonally expanded plasma cell (cePC)-derived MAbs. However, from an independent cePC of the same patient, we could derive MAbs specific for human CNS myelin, without detectable cross-reactivity with B. burgdorferi antigens. While reactivity against B. burgdorferi is a known feature of humoral immune responses in NB, we show (i) that immune responses specific for self antigens may be a distinct feature of CNS infections independent of pathogen reactivity and (ii) that humoral autoimmunity in NB (since found in cePC) is the result of a truly antigen-driven immune response. Our findings indicate that in NB mechanisms may be at play that induce distinct immune responses specific for pathogen and self antigens independent from “molecular mimicry.

Cell-type-specific cis-eQTLs in eight human brain cell types identify novel risk genes for psychiatric and neurological disorders

To date, most expression quantitative trait loci (eQTL) studies, which investigate how genetic variants contribute to gene expression, have been performed in heterogeneous brain tissues rather than specific cell types. In this study, we performed an eQTL analysis using single-nuclei RNA sequencing from 192 individuals in eight brain cell types derived from the prefrontal cortex, temporal cortex and white matter. We identified 7,607 eGenes, a substantial fraction (46%, 3,537/7,607) of which show cell-type-specific effects, with strongest effects in microglia. Cell-type-level eQTLs affected more constrained genes and had larger effect sizes than tissue-level eQTLs. Integration of brain cell type eQTLs with genome-wide association studies (GWAS) revealed novel relationships between expression and disease risk for neuropsychiatric and neurodegenerative diseases. For most GWAS loci, a single gene co-localized in a single cell type, providing new clues into disease etiology. Our findings demonstrate substantial contrast in genetic regulation of gene expression among brain cell types and reveal potential mechanisms by which disease risk genes influence brain disorders

Lack of Antimicrobial Resistance in Yersinia pestis Isolates from 17 Countries in the Americas, Africa, and Asia

Yersinia pestis is the causative agent of plague, a fulminant disease that is often fatal without antimicrobial treatment. Plasmid (IncA/C)-mediated multidrug resistance in Y. pestis was reported in 1995 in Madagascar and has generated considerable public health concern, most recently because of the identification of IncA/C multidrug-resistant plasmids in other zoonotic pathogens. Here, we demonstrate no resistance in 392 Y. pestis isolates from 17 countries to eight antimicrobials used for treatment or prophylaxis of plague

Climate and Vegetation.

<p>Climate data are derived from WorldClim database including mean annual temperature (MAT), maximum temperature of the warmest month (Tmax), minimum temperature of the coldest month (Tmin) mean annual range in temperature (MART) and mean annual precipitation (MAP).</p