Characterisation of Arctic Bacterial Communities in the Air above Svalbard

Atmospheric dispersal of bacteria is increasingly acknowledged as an important factor influencing bacterial community biodiversity, biogeography and bacteria-human interactions, including those linked to human health. However, knowledge about patterns in microbial aerobiology is still relatively scarce, and this can be attributed, in part, to a lack of consensus on appropriate sampling and analytical methodology. In this study, three different methods were used to investigate aerial biodiversity over Svalbard: impaction, membrane filtration and drop plates. Sites around Svalbard were selected due to their relatively remote location, low human population, geographical location with respect to air movement and the tradition and history of scientific investigation on the archipelago, ensuring the presence of existing research infrastructure. The aerial bacterial biodiversity found was similar to that described in other aerobiological studies from both polar and non-polar environments, with Proteobacteria, Actinobacteria, and Firmicutes being the predominant groups. Twelve different phyla were detected in the air collected above Svalbard, although the diversity was considerably lower than in urban environments elsewhere. However, only 58 of 196 bacterial genera detected were consistently present, suggesting potentially higher levels of heterogeneity. Viable bacteria were present at all sampling locations, showing that living bacteria are ubiquitous in the air around Svalbard. Sampling location influenced the results obtained, as did sampling method. Specifically, impaction with a Sartorius MD8 produced a significantly higher number of viable colony forming units (CFUs) than drop plates alone

Source Environments of the Microbiome in Perennially Ice-Covered Lake Untersee, Antarctica

Ultra-oligotrophic Lake Untersee is among the largest and deepest surface lakes of Central Queen Maud Land in East Antarctica. It is dammed at its north end by the Anuchin Glacier and the ice-cover dynamics are controlled by sublimation — not melt — as the dominating ablation process and therefore surface melt during austral summer does not provide significant amounts of water for recharge compared to subsurface melt of the Anuchin Glacier. Several studies have already described the structure and function of the microbial communities within the water column and benthic environments of Lake Untersee, however, thus far there have been no studies that examine the linkages between the lake ecosystem with that of the surrounding soils or the Anuchin Glacier. The glacier may also play an important role as a major contributor of nutrients and biota into the lake ecosystem. Based on microbial 16S rRNA amplicon sequencing, we showed that the dominant bacterial signatures in Lake Untersee, the Anuchin Glacier and its surrounding soils were affiliated with Actinobacteria, Bacteroidetes, Cyanobacteria, Firmicutes, and Proteobacteria. Aerosol and local soil depositions on the glacier surface resulted in distinct microbial communities developing in glacier ice and cryoconite holes. Based on a source tracking algorithm, we found that cryoconite microbial assemblages were a potential source of organisms, explaining up to 36% of benthic microbial mat communities in the lake. However, the major biotic sources for the lake ecosystem are still unknown, illustrating the possible importance of englacial and subglacial zones. The Anuchin Glacier may be considered as a vector in a biological sense for the bacterial colonization of the perennially ice-covered Lake Untersee. However, despite a thick perennial ice cover, observed “lift-off” microbial mats escaping the lake make a bidirectional transfer of biota plausible. Hence, there is an exchange of biota between Lake Untersee and connective habitats possible despite the apparent sealing by a perennial ice cover and the absence of moat areas during austral summer

Contrasts between the cryoconite and ice-marginal bacterial communities of Svalbard glaciers:Bacterial communities of Svalbard glaciers

Cryoconite holes are foci of unusually high microbial diversity and activity on glacier surfaces worldwide, comprising melt-holes formed by the darkening of ice by biogenic granular debris. Despite recent studies linking cryoconite microbial community structure to the functionality of cryoconite habitats, little is known of the processes shaping the cryoconite bacterial community. In particular, the assertions that the community is strongly influenced by aeolian transfer of biota from ice-marginal habitats and the potential for cryoconite microbes to inoculate proglacial habitats are poorly quantified despite their longevity in the literature. Therefore, the bacterial community structures of cryoconite holes on three High-Arctic glaciers were compared to bacterial communities in adjacent moraines and tundra using terminal-restriction fragment length polymorphism. Distinct community structures for cryoconite and ice-marginal communities were observed. Only a minority of phylotypes are present in both habitat types, implying that cryoconite habitats comprise distinctive niches for bacterial taxa when compared to ice-marginal habitats. Curiously, phylotype abundance distributions for both cryoconite and ice-marginal sites best fit models relating to succession. Our analyses demonstrate clearly that cryoconites have their own, distinct functional microbial communities despite significant inputs of cells from other habitats

A metagenomic snapshot of taxonomic and functional diversity in an Alpine glacier cryoconite ecosystem:Alpine cryoconite metagenome

Cryoconite is a microbe–mineral aggregate which darkens the ice surface of glaciers. Microbial process and marker gene PCR-dependent measurements reveal active and diverse cryoconite microbial communities on polar glaciers. Here, we provide the first report of a cryoconite metagenome and culture-independent study of alpine cryoconite microbial diversity. We assembled 1.2 Gbp of metagenomic DNA sequenced using an Illumina HiScanSQ from cryoconite holes across the ablation zone of Rotmoosferner in the Austrian Alps. The metagenome revealed a bacterially-dominated community, with Proteobacteria (62% of bacterial-assigned contigs) and Bacteroidetes (14%) considerably more abundant than Cyanobacteria (2.5%). Streptophyte DNA dominated the eukaryotic metagenome. Functional genes linked to N, Fe, S and P cycling illustrated an acquisitive trend and a nitrogen cycle based upon efficient ammonia recycling. A comparison of 32 metagenome datasets revealed a similarity in functional profiles between the cryoconite and metagenomes characterized from other cold microbe–mineral aggregates. Overall, the metagenomic snapshot reveals the cryoconite ecosystem of this alpine glacier as dependent on scavenging carbon and nutrients from allochthonous sources, in particular mosses transported by wind from ice-marginal habitats, consistent with net heterotrophy indicated by productivity measurements. A transition from singular snapshots of cryoconite metagenomes to comparative analyses is advocated

Predictive metabolites for incident myocardial infarction:a two-step meta-analysis of individual patient data from six cohorts comprising 7,897 individuals from the the COnsortium of METabolomic Studies

Aims: Myocardial infarction (MI) is a major cause of death and disability worldwide. Most metabolomics studies investigating metabolites predicting MI are limited by the participant number and/or the demographic diversity. We sought to identify biomarkers of incident MI in the COnsortium of METabolomics Studies. Methods and results: We included 7897 individuals aged on average 66 years from six intercontinental cohorts with blood metabolomic profiling (n = 1428 metabolites, of which 168 were present in at least three cohorts with over 80% prevalence) and MI information (1373 cases). We performed a two-stage individual patient data meta-analysis. We first assessed the associations between circulating metabolites and incident MI for each cohort adjusting for traditional risk factors and then performed a fixed effect inverse variance meta-analysis to pull the results together. Finally, we conducted a pathway enrichment analysis to identify potential pathways linked to MI. On meta-analysis, 56 metabolites including 21 lipids and 17 amino acids were associated with incident MI after adjusting for multiple testing (false discovery rate < 0.05), and 10 were novel. The largest increased risk was observed for the carbohydrate mannitol/sorbitol {hazard ratio [HR] [95% confidence interval (CI)] = 1.40 [1.26-1.56], P < 0.001}, whereas the largest decrease in risk was found for glutamine [HR (95% CI) = 0.74 (0.67-0.82), P < 0.001]. Moreover, the identified metabolites were significantly enriched (corrected P < 0.05) in pathways previously linked with cardiovascular diseases, including aminoacyl-tRNA biosynthesis. Conclusions: In the most comprehensive metabolomic study of incident MI to date, 10 novel metabolites were associated with MI. Metabolite profiles might help to identify high-risk individuals before disease onset. Further research is needed to fully understand the mechanisms of action and elaborate pathway findings.This research was funded in whole, or in part, by the Wellcome Trust (WT212904/Z/18/Z) and by the UKRI Medical Research Council (MRC)/British Heart Foundation Ancestry and Biological Informative Markers for Stratification of Hypertension (AIM-HY; MR/M016560/1). For the purpose of open access, the authors have applied a CC BY public copyright to any author-accepted manuscript version arising from this submission. TwinsUK receives funding from the Wellcome Trust, the European Commission H2020 grants SYSCID (contract #733100), the National Institute for Health Research (NIHR) Clinical Research Facility and the Biomedical Research Centre based at Guy's and St Thomas’ NHS Foundation Trust in partnership with King's College London, the Chronic Disease Research Foundation, the UKRI Medical Research Council (MRC)/British Heart Foundation Ancestry and Biological Informative Markers for Stratification of Hypertension (AIM-HY; MR/M016560/1), and Zoe Limited. C.M. and A.N. are funded by the Chronic Disease Research Foundation. C.M. is also funded by the MRC AIM-HY grant. The Atherosclerosis Risk in Communities (ARIC) study has been funded in whole or in part with Federal funds from the National Heart, Lung, and Blood Institute, National Institutes of Health, Department of Health and Human Services, under Contract nos. (75N92022D00001, 75N92022D00002, 75N92022D00003, 75N92022D00004, and 75N92022D00005). The authors thank the staff and participants of the ARIC study for their important contributions). B.Y. was in part supported by R01HL168683. Metabolomics measurements were sponsored by the National Human Genome Research Institute (3U01HG004402-02S1). The ET2DS was funded by the Medical Research Council (UK) (Project Grant G0500877) and the Chief Scientist Office of Scotland (Program Support Grand CZQ/1/38). C.B. was funded by the grant FIS-FEDER-ISCIII PI16/00620 (Ext 2021) and the Strategic Plan for Research and Innovation in Health, CatSalut, PERIS STL008 (2019–2021), and RICORS RD21/0005, to develop clinical and epidemiological studies mainly focused on diabetes and its associations with new biomarkers. HABC was supported in part by the Intramural Research Program of the National Institutes of Health, National Institute on Aging (NIA); contracts: N01-AG-6-2101, N01-AG-6-2103, and N01-AG-6-2106; NIA grant: R01-AG028050, and NINR grant R01-NR012459; and the National Center for Advancing Translational Sciences of the National Institutes of Health under Award Number UL1TR000454. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Dr Murphy is supported by the Michael Smith Foundation for Health Research (grant #17644). The WHI program is funded by the National Heart, Lung, and Blood Institute, National Institutes of Health, U.S. Department of Health and Human Services through 75N92021D00001, 75N92021D00002, 75N92021D00003, 75N92021D00004, and 75N92021D00005. The authors thank the WHI investigators and staff for their dedication and the study participants for making the program possible. A full listing of WHI investigators can be found at https://www-whi-org.s3.us-west-2.amazonaws.com/wp-content/uploads/WHI-Investigator-Long-List.pdf

Possible interactions between bacterial diversity, microbial activity and supraglacial hydrology of cryoconite holes in Svalbard

The diversity of highly active bacterial communities in cryoconite holes on three Arctic glaciers in Svalbard was investigated using terminal restriction fragment length polymorphism (T-RFLP) of the 16S rRNA locus. Construction and sequencing of clone libraries allowed several members of these communities to be identified, with Proteobacteria being the dominant one, followed by Cyanobacteria and Bacteroidetes. T-RFLP data revealed significantly different communities in holes on the (cold) valley glacier Austre Brøggerbreen relative to two adjacent (polythermal) valley glaciers, Midtre Lovénbreen and Vestre Brøggerbreen. These population compositions correlate with differences in organic matter content, temperature and the metabolic activity of microbial communities concerned. No within-glacier spatial patterns were observed in the communities identified over the 2-year period and with the 1 km-spaced sampling. We infer that surface hydrology is an important factor in the development of cryoconite bacterial communities

Night Shift Work Affects Urine Metabolite Profiles of Nurses with Early Chronotype

Night shift work can have a serious impact on health. Here, we assess whether and how night shift work influences the metabolite profiles, specifically with respect to different chronotype classes. We have recruited 100 women including 68 nurses working both, day shift and night shifts for up to 5 consecutive days and collected 3640 spontaneous urine samples. About 424 waking-up urine samples were measured using a targeted metabolomics approach. To account for urine dilution, we applied three methods to normalize the metabolite values: creatinine-, osmolality- and regression-based normalization. Based on linear mixed effect models, we found 31 metabolites significantly (false discovery rate <0.05) affected in nurses working in night shifts. One metabolite, acylcarnitine C10:2, was consistently identified with all three normalization methods. We further observed 11 and 4 metabolites significantly associated with night shift in early and late chronotype classes, respectively. Increased levels of medium- and long chain acylcarnitines indicate a strong impairment of the fatty acid oxidation. Our results show that night shift work influences acylcarnitines and BCAAs, particularly in nurses in the early chronotype class. Women with intermediate and late chronotypes appear to be less affected by night shift work