Rhizosphere microbial community structure differs between constant subzero and freeze-thaw temperature regimes in a subarctic soil.

In the Arctic and subarctic, climate change is causing reduced snowpack extent and earlier snowmelt. Shallower snowpack decreases the thermal insulation of underlying soil and results in more freeze-thaw conditions reflective of dynamic air temperatures. The aim of this study was to determine the effect of alternative temperature regimes on overall microbial community structure and rhizosphere recruitment across representatives of three subarctic plant functional groups. We hypothesized that temperature regime would influence rhizosphere community structure more than plant type. Planted microcosms were established using a tree, forb, grass, or no plant control and subjected to either freeze-thaw cycling or static subzero temperatures. Our results showed rhizosphere communities exhibited reduced diversity compared to bulk soils, and were influenced by temperature conditions and to a lesser extent plant type. We found that plants have a core microbiome that is persistent under different winter temperature scenarios but also have temperature regime-specific rhizosphere microbes. Freeze-thaw cycling resulted in greater community shifts from the pre-incubation soils when compared to constant subzero temperature. This finding suggests that wintertime snowpack conditions may be a significant factor for plant-microbe interactions upon spring thaw.

Microbiome assembly in thawing permafrost and its feedbacks to climate.

The physical and chemical changes that accompany permafrost thaw directly influence the microbial communities that mediate the decomposition of formerly frozen organic matter, leading to uncertainty in permafrost-climate feedbacks. Although changes to microbial metabolism and community structure are documented following thaw, the generality of post-thaw assembly patterns across permafrost soils of the world remains uncertain, limiting our ability to predict biogeochemistry and microbial community responses to climate change. Based on our review of the Arctic microbiome, permafrost microbiology, and community ecology, we propose that Assembly Theory provides a framework to better understand thaw-mediated microbiome changes and the implications for community function and climate feedbacks. This framework posits that the prevalence of deterministic or stochastic processes indicates whether the community is well-suited to thrive in changing environmental conditions. We predict that on a short timescale and following high-disturbance thaw (e.g., thermokarst), stochasticity dominates post-thaw microbiome assembly, suggesting that functional predictions will be aided by detailed information about the microbiome. At a longer timescale and lower-intensity disturbance (e.g., active layer deepening), deterministic processes likely dominate, making environmental parameters sufficient for predicting function. We propose that the contribution of stochastic and deterministic processes to post-thaw microbiome assembly depends on the characteristics of the thaw disturbance, as well as characteristics of the microbial community, such as the ecological and phylogenetic breadth of functional guilds, their functional redundancy, and biotic interactions. These propagate across space and time, potentially providing a means for predicting the microbial forcing of greenhouse gas feedbacks to global climate change.

Reading the ground: Understanding the response of bioelectric microbes to anthropogenic compounds in soil based terrestrial microbial fuel cells.

Electrogenic bacteria produce power in soil based terrestrial microbial fuel cells (tMFCs) by growing on electrodes and transferring electrons released from the breakdown of substrates. The direction and magnitude of voltage production is hypothesized to be dependent on the available substrates. A sensor technology was developed for compounds indicative of anthropological activity by exposing tMFCs to gasoline, petroleum, 2,4-dinitrotoluene, fertilizer, and urea. A machine learning classifier was trained to identify compounds based on the voltage patterns. After 5 to 10 days, the mean voltage stabilized (+/- 0.5 mV). After the entire incubation, voltage ranged from -59.1 mV to 631.8 mV, with the tMFCs containing urea and gasoline producing the highest (624 mV) and lowest (-9 mV) average voltage, respectively. The machine learning algorithm effectively discerned between gasoline, urea, and fertilizer with greater than 94% accuracy, demonstrating that this technology could be successfully operated as an environmental sensor for change detection.

Meeting report of the fourth annual Tri-Service Microbiome Consortium symposium.

The Tri-Service Microbiome Consortium (TSMC) was founded to enhance collaboration, coordination, and communication of microbiome research among U.S. Department of Defense (DoD) organizations. The annual TSMC symposium is designed to enable information sharing between DoD scientists and leaders in the field of microbiome science, thereby keeping DoD consortium members informed of the latest advances within the microbiome community and facilitating the development of new collaborative research opportunities. The 2020 annual symposium was held virtually on 24-25 September 2020. Presentations and discussions centered on microbiome-related topics within four broad thematic areas: (1) Enabling Technologies; (2) Microbiome for Health and Performance; (3) Environmental Microbiome; and (4) Microbiome Analysis and Discovery. This report summarizes the presentations and outcomes of the 4th annual TSMC symposium.

The Transition From Stochastic to Deterministic Bacterial Community Assembly During Permafrost Thaw Succession.

The Northern high latitudes are warming twice as fast as the global average, and permafrost has become vulnerable to thaw. Changes to the environment during thaw leads to shifts in microbial communities and their associated functions, such as greenhouse gas emissions. Understanding the ecological processes that structure the identity and abundance (i.e., assembly) of pre- and post-thaw communities may improve predictions of the functional outcomes of permafrost thaw. We characterized microbial community assembly during permafrost thaw using in situ observations and a laboratory incubation of soils from the Storflaket Mire in Abisko, Sweden, where permafrost thaw has occurred over the past decade. In situ observations indicated that bacterial community assembly was driven by randomness (i.e., stochastic processes) immediately after thaw with drift and dispersal limitation being the dominant processes. As post-thaw succession progressed, environmentally driven (i.e., deterministic) processes became increasingly important in structuring microbial communities where homogenizing selection was the only process structuring upper active layer soils. Furthermore, laboratory-induced thaw reflected assembly dynamics immediately after thaw indicated by an increase in drift, but did not capture the long-term effects of permafrost thaw on microbial community dynamics. Our results did not reflect a link between assembly dynamics and carbon emissions, likely because respiration is the product of many processes in microbial communities. Identification of dominant microbial community assembly processes has the potential to improve our understanding of the ecological impact of permafrost thaw and the permafrost-climate feedback.

Meeting report of the third annual Tri-Service Microbiome Consortium symposium.

The Tri-Service Microbiome Consortium (TSMC) was founded to enhance collaboration, coordination, and communication of microbiome research among U.S. Department of Defense (DoD) organizations and to facilitate resource, material and information sharing among consortium members. The 2019 annual symposium was held 22-24 October 2019 at Wright-Patterson Air Force Base in Dayton, OH. Presentations and discussions centered on microbiome-related topics within five broad thematic areas: 1) human microbiomes; 2) transitioning products into Warfighter solutions; 3) environmental microbiomes; 4) engineering microbiomes; and 5) microbiome simulation and characterization. Collectively, the symposium provided an update on the scope of current DoD microbiome research efforts, highlighted innovative research being done in academia and industry that can be leveraged by the DoD, and fostered collaborative opportunities. This report summarizes the presentations and outcomes of the 3rd annual TSMC symposium.

The role of changing temperature in microbial metabolic processes during permafrost thaw.

Approximately one fourth of the Earth's Northern Hemisphere is underlain by permafrost, earth materials (soil, organic matter, or bedrock), that has been continuously frozen for at least two consecutive years. Numerous studies point to evidence of accelerated climate warming in the Arctic and sub-Arctic where permafrost is located. Changes to permafrost biochemical processes may critically impact ecosystem processes at the landscape scale. Here, we sought to understand how the permafrost metabolome responds to thaw and how this response differs based on location (i.e. chronosequence of permafrost formation constituting diverse permafrost types). We analyzed metabolites from microbial cells originating from Alaskan permafrost. Overall, permafrost thaw induced a shift in microbial metabolic processes. Of note were the dissimilarities in biochemical structure between frozen and thawed samples. The thawed permafrost metabolomes from different locations were highly similar. In the intact permafrost, several metabolites with antagonist properties were identified, illustrating the competitive survival strategy required to survive a frozen state. Interestingly, the intensity of these antagonistic metabolites decreased with warmer temperature, indicating a shift in ecological strategies in thawed permafrost. These findings illustrate the impact of change in temperature and spatial variability as permafrost undergoes thaw, knowledge that will become crucial for predicting permafrost biogeochemical dynamics as the Arctic and Antarctic landscapes continue to warm.

Ecotoxicity of 2,4-dinitrotoluene to cold tolerant plant species in a sub-Arctic soil.

Decades of live-fire training exercises have left millions of acres of military training lands contaminated with various munitions constituents such as dinitrotoluene. Those that pose a threat to higher organisms due to their toxicity and mobility in the soil are of particular concern. Plants aid in the biodegradation and phytoextraction of contaminants, and site-specific ecotoxicity determinations are critical to inform effective remediation strategy. These ecotoxicity determinations are lacking in cold-adapted plants and would be very informative for contaminated training lands in cold regions. Therefore, we conducted a phytotoxicity study to determine the median effective concentration (EC50) of 2,4-dinitrotoluene (2,4-DNT) to four native Alaskan plant species in a sub-Arctic soil at two different temperatures. Plant species investigated were white spruce (Picea glauca), field locoweed (Oxytropis campestris), bluejoint grass (Calamagrostis canadensis), and Jacob's ladder (Polemonium pulcherrimum). Seedling emergence, fresh plant mass, and dry plant mass were used to model plant response to 2,4-DNT contamination. White spruce was most tolerant to 2,4-DNT contamination (EC50 = 130.8 mg kg-1) and field locoweed was least tolerant (EC50 = 0.38 mg kg-1). In general, Arctic plant species were more vulnerable to 2,4-DNT when compared to plant types native to temperate or tropical regions.

Keanu: a novel visualization tool to explore biodiversity in metagenomes.

BACKGROUND: One of the main challenges when analyzing complex metagenomics data is the fact that large amounts of information need to be presented in a comprehensive and easy-to-navigate way. In the process of analyzing FASTQ sequencing data, visualizing which organisms are present in the data can be useful, especially with metagenomics data or data suspected to be contaminated. Here, we describe the development and application of a command-line tool, Keanu, for visualizing and exploring sample content in metagenomics data. We developed Keanu as an interactive tool to make viewing complex data easier. RESULTS: Keanu, a tool for exploring sequence content, helps a user to understand the presence and abundance of organisms in a sample by analyzing alignments against a database that contains taxonomy data and displaying them in an interactive web page. The content of a sample can be presented either as a collapsible tree, with node size indicating abundance, or as a bilevel partition graph, with arc size indicating abundance. Here, we illustrate how Keanu works by exploring shotgun metagenomics data from a sample collected from a bluff that contained paleosols and a krotovina in an alpine site in Ft. Greely, Alaska. CONCLUSIONS: Keanu provides a simple means by which researchers can explore and visualize species present in sequence data generated from complex communities and environments. Keanu is written in Python and is freely available at https://github.com/IGBB/keanu .

Removal of Exogenous Materials from the Outer Portion of Frozen Cores to Investigate the Ancient Biological Communities Harbored Inside.

The cryosphere offers access to preserved organisms that persisted under past environmental conditions. In fact, these frozen materials could reflect conditions over vast time periods and investigation of biological materials harbored inside could provide insight of ancient environments. To appropriately analyze these ecosystems and extract meaningful biological information from frozen soils and ice, proper collection and processing of the frozen samples is necessary. This is especially critical for microbial and DNA analyses since the communities present may be so uniquely different from modern ones. Here, a protocol is presented to successfully collect and decontaminate frozen cores. Both the absence of the colonies used to dope the outer surface and exogenous DNA suggest that we successfully decontaminated the frozen cores and that the microorganisms detected were from the material, rather than contamination from drilling or processing the cores.