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At least 1,279 records · Page 71

Increasing Bacterial Tolerance and Metabolism of the Biofuel, N-Butanol Using Community-Level Evolution and Functional Genomics

Bioremediation capability should be developed along with biofuel technology to mitigate the potential damage of future spills. One biofuel that is being developed is biobutanol, since n-butanol is more energy dense and less volatile than ethanol. A bottleneck for industrial production of biobutanol is its toxicity; most microbes cannot survive about 1.5% v/v. Thus, microbial bioremediation of n-butanol would need microbes that can both tolerate and metabolize butanol. We used ecological and evolutionary biology approaches to find bacteria that could tolerate and metabolize butanol. We then tried to increase the metabolism of butanol by promising bacterial strains and communities. Ecological community-level assays and screenings were conducted followed by 16S amplicon sequencing to identify butanol-tolerant artificial bacterial communities. Promising communities were then tested for growth with butanol as the sole carbon source. Secondly, we looked for bacteria with alcohol dehydrogenase enzymes and looked to increase butanol metabolism. We found that the tolerance for n-butanol may be improved with repeated exposure, but it was difficult to switch from tolerance to metabolism. Bacterial community v dynamics may be influenced by n-butanol concentration, and there was putative butanol metabolism found with both research approaches.

09 BIOMASS FUELS↗

Metabolome of human gut microbiome is predictive of host dysbiosis

Background: Humans live in constant and vital symbiosis with a closely linked bacterial ecosystem called the microbiome, which influences many aspects of human health. When this microbial ecosystem becomes disrupted, the health of the human host can suffer; a condition called dysbiosis. However, the community compositions of human microbiomes also vary dramatically from individual to individual, and over time, making it difficult to uncover the underlying mechanisms linking the microbiome to human health. We propose that a microbiome’s interaction with its human host is not necessarily dependent upon the presence or absence of particular bacterial species, but instead is dependent on its community metabolome; an emergent property of the microbiome. Results: Using data from a previously published, longitudinal study of microbiome populations of the human gut, we extrapolated information about microbiome community enzyme profiles and metabolome models. Using machine learning techniques, we demonstrated that the aggregate predicted community enzyme function profiles and modeled metabolomes of a microbiome are more predictive of dysbiosis than either observed microbiome community composition or predicted enzyme function profiles. Conclusions: Specific enzyme functions and metabolites predictive of dysbiosis provide insights into the molecular mechanisms of microbiome–host interactions. The ability to use machine learning to predict dysbiosis from microbiome community interaction data provides a potentially powerful tool for understanding the links between the human microbiome and human health, pointing to potential microbiome-based diagnostics and therapeutic interventions.

human microbiome↗

Climatic controls of decomposition drive the global biogeography of forest-tree symbioses

The identity of the dominant microbial symbionts in a forest determines the ability of trees to access limiting nutrients from atmospheric or soil pools, sequester carbon and withstand the impacts of climate change. Characterizing the global distribution of symbioses, and identifying the factors that control it, are thus integral to understanding present and future forest ecosystem functioning. In this work we generate the first spatially explicit global map of forest symbiotic status using a database of over 1.1 million forest inventory plots with over 28,000 tree species. Our analyses indicate that climatic variables, and in particular climatically-controlled variation in decomposition rate, are the primary drivers of the global distribution of major symbioses. We estimate that ectomycorrhizal (EM) trees, which represent only 2% of all plant species, constitute approximately 60% of tree stems on Earth. EM symbiosis dominates forests where seasonally cold and dry climates inhibit decomposition, and are the predominant symbiosis at high latitudes and elevation. On the other hand, arbuscular mycorrhizal (AM) trees dominate aseasonally warm tropical forests and occur with EM trees in temperate biomes where seasonally warm-and-wet climates enhance decomposition. Continental transitions between AM and EM dominated forests occur relatively abruptly along climate driven decomposition gradients, which is likely caused by positive plant-microbe feedbacks. Symbiotic N-fixers, which are insensitive to climatic controls on decomposition compared with mycorrhizal fungi, are most abundant in arid biomes with alkaline soils and high maximum temperatures. The climatically driven global symbiosis gradient we document represents the first spatially-explicit, quantitative understanding of microbial symbioses at the global scale and demonstrates the critical role of microbial mutualisms in shaping the distribution of plant species.

59 BASIC BIOLOGICAL SCIENCES↗

A new model for the biodegradation kinetics of oil droplets: application to the Deepwater Horizon oil spill in the Gulf of Mexico

Oil biodegradation by native bacteria is one of the most important natural processes that can attenuate the environmental impacts of marine oil spills. Existing models for oil biodegradation kinetics are mostly for dissolved oil. This work developed a new mathematical model for the biodegradation of oil droplets and applied the model to estimate the time scale for oil biodegradation under conditions relevant to the Deepwater Horizon oil spill in the Gulf of Mexico. In the model, oil is composed of droplets of various sizes following the gamma function distribution. Each oil droplet shrinks during the microbe-mediated degradation at the oil-water interface. Using our developed model, we find that the degradation of oil droplets typically goes through two stages. The first stage is characterized by microbial activity unlimited by oil-water interface with higher biodegradation rates than that of the dissolved oil. The second stage is governed by the availability of the oil-water interface, which results in much slower rates than that of soluble oil. As a result, compared to that of the dissolved oil, the degradation of oil droplets typically starts faster and then quickly slows down, ultimately reaching a smaller percentage of degraded oil in longer time. The availability of the water-oil interface plays a key role in determining the rates and extent of degradation. We find that several parameters control biodegradation rates, including size distribution of oil droplets, initial microbial concentrations, initial oil concentration and composition. Under conditions relevant to the Deepwater Horizon spill, we find that the size distribution of oil droplets (mean and coefficient of variance) is the most important parameter because it determines the availability of the oil-water interface. Smaller oil droplets with larger variance leads to faster and larger extent of degradation. The developed model will be useful for evaluating transport and fate of spilled oil, different remediation strategies, and risk assessment.

02 PETROLEUM↗

Elucidation of roles for vitamin B 12 in regulation of folate, ubiquinone, and methionine metabolism

Significance Using a chemical probe mimic of vitamin B 12 , we reveal a light- and B 12 -dependent DNA regulator, and make the unexpected discovery of B 12 having regulatory involvement in microbial folate, ubiquinone, and methionine processes. These findings suggest a pivotal role for B 12 in the control of cell growth, which may lead to coordination of cell behavior in complex multicellular systems. As key research questions emerge from host-associated and environmental microbiomes, we anticipate that B 12 regulatory control of metabolism will be found to be generalizable, will be critical for coordination of individual microbe and community metabolism, and that organismal interdependencies for B 12 may be pertinent to microbiome organization, stability, and overall function.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Nature’s conductors: what can microbial multi-heme cytochromes teach us about electron transport and biological energy conversion?

Microorganisms can acquire energy from the environment by extending their electron transport chains to external solid electron donors or acceptors. This process, known as extracellular electron transfer (EET), is now being heavily pursued for wiring microbes to electrodes in bioelectrochemical renewable energy technologies. Recent studies highlight the crucial role of multi-heme cytochromes in facilitating biotic–abiotic EET both for cellular electron export and uptake. Here we explore progress in understanding the range and function of these biological electron conduits in the context of fuel-to-electricity and electricity-to-bioproduct conversion. We also highlight emerging topics, including the role of multi-heme cytochromes in inter-species electron transfer and in inspiring the design and synthesis of a new generation of protein-based bioelectronic components.

59 BASIC BIOLOGICAL SCIENCES↗

Comparative genomics and functional analysis of rhamnose catabolic pathways and regulons in bacteria

L-rhamnose (L-Rha) is a deoxy-hexose sugar commonly found in nature. L-Rha catabolic pathways were previously characterized in various bacteria including Escherichia coli. Nevertheless, homology searches failed to recognize all the genes for the complete L-Rha utilization pathways in diverse microbial species involved in biomass decomposition. Moreover, the regulatory mechanisms of L-Rha catabolism have remained unclear in most species. A comparative genomics approach was used to reconstruct the L-Rha catabolic pathways and transcriptional regulons in the phyla Actinobacteria, Bacteroidetes, Chloroflexi, Firmicutes, Proteobacteria, and Thermotogae. The reconstructed pathways include multiple novel enzymes and transporters involved in the utilization of L-Rha and L-Rha-containing polymers. Large-scale regulon inference using bioinformatics revealed remarkable variations in transcriptional regulators for L-Rha utilization genes among bacteria. A novel bifunctional enzyme, L-rhamnulose-phosphate aldolase (RhaE) fused to L-lactaldehyde dehydrogenase (RhaW), which is not homologous to previously characterized L-Rha catabolic enzymes, was identified in diverse bacteria including Chloroflexi, Bacilli, and Alphaproteobacteria. By using in vitro biochemical assays we validated both enzymatic activities of the purified recombinant RhaEW proteins from Chloroflexus aurantiacus and Bacillus subtilis. Another novel enzyme of the L-Rha catabolism, L-lactaldehyde reductase (RhaZ), was identified in Gammaproteobacteria and experimentally validated by in vitro enzymatic assays using the recombinant protein from Salmonella typhimurium. C. aurantiacus induced transcription of the predicted L-Rha utilization genes when L-Rha was present in the growth medium and consumed L-Rha from the medium. This study provided comprehensive insights to L-Rha catabolism and its regulation in diverse Bacteria.

59 BASIC BIOLOGICAL SCIENCES↗

Biological Mechanisms May Contribute to Soil Carbon Saturation Patterns: Modeling Archive

This Modeling Archive is in support of a TES-SFA publication “Biological Mechanisms May Contribute to Soil Carbon Saturation Patterns” (Craig et al., 2021). We ran and evaluated a multi-assumption soil organic carbon (SOC) model to investigate whether alternative assumptions regarding constraints on soil microbial biomass could lead to soil carbon saturation patterns. We developed this model in the Multi-Assumption Architecture and Testbed (MAAT, https://github.com/walkeranthonyp/MAAT, tag: v1.2.1_Craig2021; Walker et al. 2018). Using MAAT, we embedded three alternative hypotheses in a microbially explicit three-pool SOC model: 1) the efficiency of mineral-associated SOC formation decreases as mineral-associated SOC approaches a maximum value (“Mineral saturation”), 2) the microbial biomass turnover rate increases with increasing microbial biomass (“Density-dependent turnover”), and 3) community carbon use efficiency decreases as microbial biomass increases toward an upper limit (“Density-dependent growth”). We ran a factorial combination of these hypotheses resulting in eight models for three different classes of model (linear decay, Michaelis-Menten decay, or reverse Michaelis-Menten decay), resulting in 24 models, 12 of which are presented or discussed in the related publication. Models were parameterized using values from previous studies with similar models (Wang et al. 2013, Wieder et al. 2014, Li et al. 2014, Georgiou et al. 2017, Hassink and Whitmore 1997) and ran to an approximate steady state (200 years) at six (6) different C input rates corresponding to 0.5, 1, 2, 4, 7, and 10 times the default input value. Further model details are available in the related publication. This archive contains output from three MAAT simulations, and scripts to run these simulations and process and plot the data. Simulations are labeled “lin”, “MM_highKm”, and “RMM_highKm” reflecting factorial runs for linear, Michealis-Menten, and reverse Michaelis-Menten models, respectively. This archive contains: • 3 R scripts prepended with “init_MAAT_” to initialize runs (1 for each simulation), • 1 csv file containing years over which to run simulations (“met_year.csv”), • 1 bash script (.bs) to run MAAT, • 6 XML files that are output from MAAT describing a run (2 for each simulation), • 3 model output csv files prepended by “out_” (1 for each simulation), and • 1 analysis R script for reproducing figures 3 and 4 in Craig et al. 2021. See included user guide (Craig_2021_modeling_archive_20210315.pdf) for file organization details.

54 ENVIRONMENTAL SCIENCES↗

Dredged sediments contain potentially beneficial microorganisms for agriculture and little harmful cyanobacteria

Soils worldwide are degrading, raising concerns about our ability to feed the growing global population. Soil amendments that can alleviate degradation are gaining attention. The application of sediments dredged from waterways to agricultural fields has increasing promise as a means for improving degraded soils. However, herbaceous plant species may have difficulty establishing on dredged material because of low nutrient availability, inhibitory levels of toxins, unsuitable moisture conditions and lack of microorganisms capable of ameliorating these characteristics. To counteract these issues, we sought to understand if the use of a cover crop would increase the abundance, diversity and function of beneficial soil microorganisms compared to harmful microorganisms in dredged sediments. We collected soil samples from two 100% dredged sediment plots, one where winter cereal rye (Secale cereal) was grown as a winter cover crop and one left fallow over the winter, followed by traditional corn (Zea mays) planting. We sampled both plots three times during the growing season: before cover crop application, following cover crop application but before corn planting and following final corn harvest. We then used high-throughput sequencing to identify the bacterial and fungal communities present in the samples. Our data show that cover crop application did not alter the microbial community in these plots. However, sampling time decreased species diversity and altered the composition of both fungal and bacterial communities recovered from these plots. Across both plots, microorganisms associated with carbon cycling were more abundant than those associated with harmful effects, including microcystin-producing cyanobacteria, which were an extremely small portion of the overall community. Our work suggests that dredged sediments have the potential to improve soil function through the addition of microorganisms associated with nutrient cycling, but a cover crop is not necessary to incur these benefits.

54 ENVIRONMENTAL SCIENCES↗

The Effect of the Prior and the Experimental Design on the Inference of the Precision Matrix in Gaussian Chain Graph Models

Here, we investigate whether (and how) experimental design could aid in the estimation of the precision matrix in a Gaussian chain graph model, especially the interplay between the design, the effect of the experiment and prior knowledge about the effect. Estimation of the precision matrix is a fundamental task to infer biological graphical structures like microbial networks. We compare the marginal posterior precision of the precision matrix under four priors: flat, conjugate Normal-Wishart, Normal-MGIG and a general independent. Under the flat and conjugate priors, the Laplace-approximated posterior precision is not a function of the design matrix rendering useless any efforts to find an optimal experimental design to infer the precision matrix. In contrast, the Normal-MGIG and general independent priors do allow for the search of optimal experimental designs, yet there is a sharp upper bound on the information that can be extracted from a given experiment. We confirm our theoretical findings via a simulation study comparing (i) the KL divergence between prior and posterior and (ii) the Stein’s loss difference of MAPs between random and no experiment. Our findings provide practical advice for domain scientists conducting experiments to better infer the precision matrix as a representation of a biological network.

54 ENVIRONMENTAL SCIENCES↗

Direct extracellular electron transfer for high electricity production by a new type of marine microalgae Nannochloropsis sp. HDY2

A growing number of autotrophic microalgae have been found to have extracellular electron transfer (EET) capabilities. However, the mechanism and function of EET pathway in microalgae have not thoroughly investigated. This study presents evidence of direct extracellular electron transfer (DEET) for impressive electricity production by a new type of marine microalgae Nannochloropsis sp. HDY2 in the single and double-chamber photosynthetic microbial fuel cells (PFMCs). The electricity generation of Nannochloropsis sp. is strongly inhibited by photosynthetic inhibitors, suggesting that electrons involved in the extracellular electron transfer (EET) of Nannochloropsis sp. are derived from photosynthesis. The results of dialysis bag and supernatant experiments suggest that Nannochloropsis sp. produce electricity by DEET. The lack of typical redox peaks in cyclic voltammetry (CV) analysis and the appearance of extracellular filamentous component (EFC) around cells support this finding. Under high light conditions, the chlorophyll a and carotenoid content of Nannochloropsis sp. rapidly decreased while the fatty acid synthesis and electricity generation increased, suggesting that the DEET pathway play an active role in the resistance to photooxidation of Nannochloropsis sp. In conclusion, this study provides the first evidence that Nannochloropsis has the capability of performing EET and sheds new light on the positive role of DEET on the environmental adaptation of Nannochloropsis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Leveraging High-resolution Molecular Composition of Soil Organic Matter to Enhance Carbon Cycling Modeling

Soils store more carbon than the atmosphere and vegetation combined, yet Earth system models still struggle to predict how this vast reservoir will respond to environmental change. A central limitation is that most soil biogeochemical models represent organic matter using bulk conceptual pools or chemically homogeneous fractions, preventing direct use of rapidly expanding molecular-scale datasets. Here we develop and test a new soil decomposition framework that explicitly integrates high-resolution information on organic matter composition. First, we construct a molecularly informed litter decomposition module in which plant inputs are partitioned into five functional compound classes—carbohydrates, proteins, lignin-like aromatics, lipids, and carbonyls—using a molecular mixing model calibrated to solid-state 13 C Nuclear Magnetic Resonance (NMR) spectra. Class-specific kinetics, lignin-dependent physical protection, and substrate-driven microbial carbon use efficiency allow the module to capture metabolic tradeoffs associated with enzyme production and nutrient limitation. We then embed this litter module within a microbially explicit whole-soil model that tracks the transformation of these compound classes through particulate organic matter, dissolved organic matter, mineral-associated organic matter, and microbial biomass. High-resolution Fourier Transform Ion Cyclotron Resonance mass spectrometry (FTICR-MS) data are used to link internal pools to measurable soil organic matter fractions and to constrain key process parameters. Applications at soil-core and ecosystem scales demonstrate that the new model reproduces observed soil respiration dynamics while providing mechanistic attribution of CO 2 fluxes to specific chemical classes and pools. Compared to existing frameworks such as the Community Land Model soil biogeochemistry module and the Millennial model, our approach maintains competitive predictive skill while substantially improving interpretability and opportunities for data–model integration. This work illustrates a viable pathway for leveraging molecular-scale observations to reduce structural uncertainty in soil carbon–climate feedback projections.

54 ENVIRONMENTAL SCIENCES↗

Throughfall exclusion and fertilization effects on tropical dry forest tree plantations, a large-scale experiment

Abstract. Across tropical ecosystems, global environmental change is causing drier climatic conditions and increased nutrient deposition. Such changes represent large uncertainties due to unknown interactions between drought and nutrient availability in controlling ecosystem net primary productivity (NPP). Using a large-scale manipulative experiment, we studied for 4 years whether nutrient availability affects the individual and integrated responses of aboveground and belowground ecosystem processes to throughfall exclusion in 30-year-old mixed plantations of tropical dry forest tree species in Guanacaste, Costa Rica. We used a factorial design with four treatments: control, fertilization (F), drought (D), and drought + fertilization (D + F). While we found that a 13 %–15 % reduction in soil moisture only led to weak effects in the studied ecosystem processes, NPP increased as a function of F and D + F. The relative contribution of each biomass flux to NPP varied depending on the treatment, with woody biomass being more important for F and root biomass for D + F and D. Moreover, the F treatment showed modest increases in maximum canopy cover. Plant functional type (i.e., N fixation or deciduousness) and not the experimental manipulations was the main source of variation in tree growth. Belowground processes also responded to experimental treatments, as we found a decrease in nodulation for F plots and an increase in microbial carbon use efficiency for F and D plots. Our results emphasize that nutrient availability, more so than modest reductions in soil moisture, limits ecosystem processes in tropical dry forests and that soil fertility interactions with other aspects of drought intensity (e.g., vapor pressure deficit) are yet to be explored.

54 ENVIRONMENTAL SCIENCES↗

Microbial Community Shifts Reflect Losses of Native Soil Carbon with Pyrogenic and Fresh Organic Matter Additions and Are Greatest in Low-Carbon Soils

ABSTRACT Soil organic carbon (SOC) plays an important role in regulating global climate change, carbon and nutrient cycling in soils, and soil moisture. Organic matter (OM) additions to soils can affect the rate at which SOC is mineralized by microbes, with potentially important effects on SOC stocks. Understanding how pyrogenic organic matter (PyOM) affects the cycling of native SOC (nSOC) and the soil microbes responsible for these effects is important for fire-affected ecosystems as well as for biochar-amended systems. We used an incubation trial with five different soils from National Ecological Observatory Network sites across the United States and 13 C-labeled 350°C corn stover PyOM and fresh corn stover OM to trace nSOC-derived CO 2 emissions with and without PyOM and OM amendments. We used high-throughput sequencing of rRNA genes to characterize bacterial, archaeal, and fungal communities and their responses to PyOM and OM in soils that were previously stored at −80°C. We found that the effects of amendments on nSOC-derived CO 2 reflected the unamended soil C status, where relative increases in C mineralization were greatest in low-C soils. OM additions produced much greater effects on nSOC-CO 2 emissions than PyOM additions. Furthermore, the magnitude of the microbial community composition change mirrored the magnitude of increases in nSOC-CO 2 , indicating that a specific subset of microbes was likely responsible for the observed changes in nSOC mineralization. However, PyOM responders differed across soils and did not necessarily reflect a common “charosphere.” Overall, this study suggests that soils that already have low SOC may be particularly vulnerable to short-term increases in SOC loss with OM or PyOM additions. IMPORTANCE Soil organic matter (SOM) has an important role in global climate change, carbon and nutrient cycling in soils, and soil moisture dynamics. Understanding the processes that affect SOM stocks is important for managing these functions. Recently, understanding how fire-affected organic matter (or “pyrogenic” organic matter [PyOM]) affects existing SOM stocks has become increasingly important, due to both changing fire regimes and interest in “biochar,” pyrogenic organic matter that is produced intentionally for carbon management or as an agricultural soil amendment. We found that soils with less SOM were more prone to increased losses with PyOM (and fresh organic matter) additions and that soil microbial communities changed more in soils that also had greater SOM losses with PyOM additions. This suggests that soils that already have low SOM content may be particularly vulnerable to short-term increases in SOM loss and that a subset of the soil microbial community is likely responsible for these effects.

54 ENVIRONMENTAL SCIENCES↗

Pore-scale investigation on the response of heterotrophic respiration to moisture conditions in heterogeneous soils

The relationship between microbial respiration rate and soil moisture content is an important property for understanding and predicting soil organic carbon degradation, CO 2 production and emission, and their subsequent effects on climate change. This paper reports a pore-scale modeling study to investigate the response of heterotrophic respiration to moisture conditions in soils and to evaluate various factors that affect this response. X-ray computed tomography was used to derive soil pore structures, which were then used for pore-scale model investigation. The pore-scale results were then averaged to calculate the effective respiration rates as a function of water content in soils. The calculated effective respiration rate first increases and then decreases with increasing soil water content, showing a maximum respiration rate at water saturation degree of 0.75 that is consistent with field and laboratory observations. The relationship between the respiration rate and moisture content is affected by various factors, including pore-scale organic carbon bioavailability, the rate of oxygen delivery, soil pore structure and physical heterogeneity, soil clay content, and microbial drought resistivity. Simulations also illustrates that a larger fraction of CO 2 produced from microbial respiration can be accumulated inside soil cores under higher saturation conditions, implying that CO 2 flux measured on the top of soil cores may underestimate or overestimate true soil respiration rates under dynamic moisture conditions. Overall, this study provides mechanistic insights into the soil respiration response to the change in moisture conditions, and reveals a complex relationship between heterotrophic microbial respiration rate and moisture content in soils that is affected by various hydrological, geochemical, and biophysical factors.

58 GEOSCIENCES↗

Electricity generation by Pyrococcus furiosus in microbial fuel cells operated at 90°C

ABSTRACT Hyperthermophiles are microorganisms that thrive in extremely hot environments with temperatures near and even above 100°C. They are the most deeply rooted microorganisms on phylogenetic trees suggesting they may have evolved to survive in the early hostile earth. The simple respiratory systems of some of these hyperthermophiles make them potential candidates to develop microbial fuel cells (MFC) that can generate power at temperatures approaching the boiling point. We explored extracellular electron transfer in the hyperthermophilic archaeon Pyrococcus furiosus ( Pf ) by studying its ability to generate electricity in a two‐chamber MFC. Pf growing in defined medium functioned as an anolyte in a MFC operated at 90°C, generating a maximum current density of 2 A m −2 and a peak power density of 225 mW m −2 without the addition of any external redox mediator. Electron microscopy and electrochemical impedance spectroscopy of the anode with the attached Pf biofilm demonstrated bio‐electrochemical behavior that led to electricity generation in the MFC via direct electron transfer. This proof of concept study reveals for the first time that a hyperthermophile such as Pf can generate electricity in MFC at extreme temperatures. Biotechnol. Bioeng. 2017;114: 1419–1427. © 2017 Wiley Periodicals, Inc.

Sekar, Narendran↗

Impact of river channel lateral migration on microbial communities across a discontinuous permafrost floodplain

Permafrost soils store approximately twice the amount of carbon currently present in Earth’s atmosphere and are acutely impacted by climate change due to the polar amplification of increasing global temperature. Many organic-rich permafrost sediments are located on large river floodplains, where river channel migration periodically erodes and re-deposits the upper tens of meters of sediment. Channel migration exerts a first-order control on the geographic distribution of permafrost and floodplain stratigraphy and thus may affect microbial habitats. Here, to examine how river channel migration in discontinuous permafrost environments affects microbial community composition, we used amplicon sequencing of the 16S rRNA gene on sediment samples from floodplain cores and exposed riverbanks along the Koyukuk River, a large tributary of the Yukon River in west-central Alaska. Microbial communities are sensitive to permafrost thaw: communities found in deep samples thawed by the river closely resembled near-surface active layer communities in non-metric multidimensional scaling analyses but did not resemble floodplain permafrost communities at the same depth. Microbial communities also displayed lower diversity and evenness in permafrost than in both the active layer and permafrost-free point bars recently deposited by river channel migration. Taxonomic assignments based on 16S and quantitative PCR for the methyl-coenzyme M reductase functional gene demonstrated that methanogens and methanotrophs are abundant in older permafrost-bearing deposits, but not in younger, non-permafrost point bar deposits. The results suggested that river migration, which regulates the distribution of permafrost, also modulates the distribution of microbes potentially capable of producing and consuming methane on the Koyukuk River floodplain.

59 BASIC BIOLOGICAL SCIENCES↗

Interaction of amphiphilic lipoarabinomannan with host carrier lipoproteins in tuberculosis patients: Implications for blood-based diagnostics

Lipoarabinomannan (LAM), an amphiphilic lipoglycan of the Mycobacterium tuberculosis cell wall, is a diagnostic target for tuberculosis. Previous work from our laboratory and others suggests that LAM is associated with host serum lipoproteins, which may in turn have implications for diagnostic assays. Our team has developed two serum assays for amphiphile detection: lipoprotein capture and membrane insertion. The lipoprotein capture assay relies on capture of the host lipoproteins, exploiting the biological association of host lipoprotein with microbial amphiphilic biomarkers to “concentrate” LAM. In contrast, the membrane insertion assay is independent of the association between pathogen amphiphiles and host lipoprotein association, and directly captures LAM based on its thermodynamic propensity for association with a supported lipid membrane, which forms the functional surface of an optical biosensor. In this manuscript, we explored the use of these assays for the detection of LAM in sera from adults whose tuberculosis status had been well-characterized using conventional microbiological tests, and endemic controls. Using the lipoprotein capture assay, LAM signal/noise ratios were >1.0 in 29/35 (83%) individuals with culture-confirmed active tuberculosis, 8/13 (62%) individuals with tuberculosis symptoms, but no positive culture for M . tuberculosis , and 0/6 (0%) symptom-free endemic controls. To evaluate serum LAM levels without bias associated with potential differences in circulating host lipoprotein concentrations between individuals, we subsequently processed available samples to liberate LAM from associated host lipoprotein assemblies followed by direct detection of the pathogen biomarker using the membrane insertion approach. Using the membrane insertion assay, signal/noise for detection of serum LAM was greater than that observed using the lipoprotein capture method for culture-confirmed TB patients (6/6), yet remained negative for controls (2/2). Taken together, these results suggest that detection of serum LAM is a promising TB diagnostic approach, but that further work is required to optimize assay performance and to decipher the implications of LAM/host lipoprotein associations for diagnostic assay performance and TB pathogenesis.

59 BASIC BIOLOGICAL SCIENCES↗