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At least 505 records · Page 28

Revisiting diffusion-based moisture functions: why do they fail?

Microbial activities in soil are controlled by the balance between physical and biological mechanisms that are currently implied by soil moisture-respiration relationships, but not explicitly represented. Diffusion based moisture functions focus on physical controls, while substrate kinetics based models primarily address biological drivers. How to harmonize these two types of models for robust predictions of soil respiration and other processes has not been addressed. Here we derived a generalizable analytical solution of diffusion-limited nonlinear microbial uptake kinetics, in which microbial metabolic rates were governed by both physical and biological drivers via substrate diffusion and microbial affinity. We proposed a soil trait concept to integrate both physical and biological perspectives into one unified function, and tested it using both laboratory and field based observations from a variety of soils. This approach provides a tractable and scalable approach that incorporates soil heterogeneity and functional complexity in macroscopic model descriptions.

59 BASIC BIOLOGICAL SCIENCES↗

Functional Biogeography as Evidence of Gene Transfer in Hypersaline Microbial Communities

Horizontal gene transfer (HGT) plays a major role in speciation and evolution of bacteria and archaea by controlling gene distribution within an environment. However, information that links HGT to a natural community using relevant population-genetics parameters and spatial considerations is scarce. The Great Salt Lake (Utah, USA) provides an excellent model for studying HGT in the context of biogeography because it is a contiguous system with dispersal limitations due to a strong selective salinity gradient. We hypothesize that in spite of the barrier to phylogenetic dispersal, functional characteristics—in the form of HGT—expand beyond phylogenetic limitations due to selective pressure. To assay the functional genes and microorganisms throughout the GSL, we used a 16S rRNA oligonucleotide microarray (Phylochip) and a functional gene array (GeoChip) to measure biogeographic patterns of nine microbial communities. We found a significant difference in biogeography based on microarray analyses when comparing Sørensen similarity values for presence/absence of function and phylogeny (Student’s t-test; p = 0.005). Biogeographic patterns exhibit behavior associated with horizontal gene transfer in that informational genes (16S rRNA) have a lower similarity than functional genes, and functional similarity is positively correlated with lake-wide selective pressure. Specifically, high concentrations of chromium throughout GSL correspond to an average similarity of chromium resistance genes that is 22% higher than taxonomic similarity. This suggests active HGT may be measured at the population level in microbial communities and these biogeographic patterns may serve as a model to study bacteria adaptation and speciation.

59 BASIC BIOLOGICAL SCIENCES↗

Variations of soil microbial community structures beneath broadleaved forest trees in temperate and subtropical climate zones

Global warming has shifted climate zones poleward or upward. Furthermore, understanding the responses and mechanism of microbial community structure and functions relevant to natural climate zone succession is challenged by the high complexity of microbial communities. Here, we examined soil microbial community in three broadleaved forests located in the Wulu Mountain (WLM, temperate climate), Funiu Mountain (FNM, at the border of temperate and subtropical climate zones), or Shennongjia Mountain (SNJ, subtropical climate). Although plant species richness decreased with latitudes, the microbial taxonomic α-diversity increased with latitudes, concomitant with increases in soil total and available nitrogen and phosphorus contents. Phylogenetic NRI (Net Relatedness Index) values increased from 0.718 in temperate zone (WLM) to 1.042 in subtropical zone (SNJ), showing a shift from over dispersion to clustering likely caused by environmental filtering such as low pH and nutrients. Similarly, taxonomybased association networks of subtropical forest samples were larger and tighter, suggesting clustering. In contrast, functional α-diversity was similar among three forests, but functional gene networks of the FNM forest significantly (P < 0.050) differed from the others. A significant correlation (R = 0.616, P < 0.001) between taxonomic and functional β-diversity was observed only in the FNM forest, suggesting low functional redundancy at the border of climate zones. Using a strategy of space-fortime substitution, we predict that poleward climate range shift will lead to decreased microbial taxonomic α-diversities in broadleaved forest.

54 ENVIRONMENTAL SCIENCES↗

Lipid production from non-sugar compounds in pretreated lignocellulose hydrolysates by Rhodococcus jostii RHA1

Valorization of all carbon sources from biorefinery wastes to biofuels and bioproducts is an attractive but challenging strategy to improve the carbon efficiency of the entire biorefinery process for economic competitiveness. Rhodococcus jostii RHA1 is considered as a promising candidate for conversion of non-sugar compounds in pretreated lignocellulose hydrolysate, which contain aromatic monomers, furans and acids derived from biomass. However, the insufficient understanding of the strain’s complex metabolism network limits its application. In this study, furans (furfural, 5-hydroxymethylfurfural), phenols (vanillin, vanillate), and organic acids (acetic acid), which mimic the complex components of the non-sugar compounds in pretreated biomass hydrolysate, were mixed with benzoate or used individually as carbon sources to investigate the growth and lipid accumulation of R. jostii RHA1. Fermentation kinetics, specific growth rates (h-1) and lipid yield (g(g) -1, g(mmol)-1), for each selected biomass-derived compound were compared for lipid production. The order of the specific growth rates (h-1) was benzoate > acetic acid > vanillate > vanillin. Higher consumption rate of benzoate than that of vanillate, as well as different lipid yield from them, suggested the preference of strain employing two branches of ß-ketoadipate pathway and plausibly distinct carbon routing to lipid biosynthesis. And acetic acid showed the lowest lipid yield (g(mmol)-1) indicating less carbon contributed to lipid production. The highest lipid content (0.46 g lipid/g CDW) was achieved using benzoate as a main carbon source in the presence of 5-hydroxymethylfurfural (5-HMF). The generated lipids predominantly contained C16:0 and C17:0 fatty acids. The concentration of furfural and 5-HMF in fermentation broth decreased individually or simultaneously with benzoate catabolism. NMR results revealed the oxidation of furfural and 5-HMF by R. jostii RHA1. This study provides new insights into the catabolism and metabolism of non-sugar compounds derived from biomass by Rhodococcus in terms of growth and lipid production, facilitating its application to 2nd generation biofuel production.

Li, Xiaolu↗

Divergent responses of soil microorganisms to throughfall exclusion across tropical forest soils driven by soil fertility and climate history

Model projections predict tropical forests will experience longer periods of drought and more intense precipitation cycles under a changing climate. Such transitions have implications for structure-function relationships within microbial communities. We examine how throughfall exclusion might reshape prokaryotic and fungal communities across four lowland forests in Panama with a wide variation in mean annual precipitation and soil fertility. Four sites were established across a 1000 mm span in Mean Annual Precipitation (MAP: 2335–3421 mm). We expected microbial communities at sites with lower MAP to be less sensitive to throughfall exclusion than sites with higher MAP and fungal communities to be more resistant to disturbance than prokaryotes. At each location, partial throughfall exclusion structures were established over 10 × 10 m plots to reduce direct precipitation input. After short-term (~3–9 months) throughfall exclusion, prokaryotic communities showed no change in composition. However, prolonged (12–18 months) throughfall exclusion resulted in divergent prokaryotic community responses, reflecting MAP and soil fertility. We observed the emergence of a “drought microbiome” within infertile sites, whereby the community structure of the experimental throughfall exclusion plots at the lower MAP sites diverged from their respective control sites and converged towards overlapping assemblages. Furthermore, under throughfall exclusion, taxa increasing in relative abundance at the wettest site reflected that endemic to control plots at the lowest MAP site, suggesting a shift toward communities with lifehistory traits selected for under a lower MAP. By contrast, fungal community composition across sites was resilient to throughfall exclusion; however, biomass diverged in response to throughfall exclusion, increasing at two sites while decreasing in the other two. Broadly, our results suggest that microbial communities’ sensitivity to frequent drying and rewetting periods in tropical forest soils will depend on climate history and soil fertility, with infertile sites likely to respond readily to changes in precipitation.

54 ENVIRONMENTAL SCIENCES↗

Manganese effects on plant residue decomposition and carbon distribution in soil fractions depend on soil nitrogen availability

Recent studies have highlighted the critical role of manganese (Mn) in plant litter decomposition and soil organic carbon (C) cycling in forest ecosystems. Long term nitrogen (N) deposition and N fertilization can increase soil acidity and mobilize bioavailable Mn (Mn 2+ ) in soil. However, no studies have examined the interactive effect of N and Mn fertilization on litter decomposition and carbon distribution in agricultural soils, despite agroecosystems being subject to both N and Mn management. We hypothesized that increased soil N and Mn availability would accelerate plant residue decomposition and transfer of its C to mineral-associated organic matter (MAOM), and that the combined effect of Mn and N enrichment would be greater than the individual effect. Here, we conducted a laboratory incubation experiment by adding 13 C-labeled residue of perennial grass Glyceria striata (Lam.) to agricultural soils that had received 225 kg N ha –1 yr –1 for 27 years (N 1 ) and comparable soils that received no N (N 0 ). Before the experiment, these soils also received three levels of dissolved Mn 2+ , designated M 0 (no additional Mn), M 1 (50 mg kg –1 ), or M 2 (250 mg kg –1 ). We measured total CO 2 production as well as distribution of 13 C from the residue into CO 2 , particulate organic matter (POM), MAOM, and dissolved organic carbon (DOC) over a 1-year period. Manganese amendments significantly increased CO 2 production from residue decomposition in the N 1 soil, but no such effect was observed in the N 0 soil. Manganese also accelerated the loss of residue-derived C from POM and DOC, but increased its recovery in MAOM. However, the positive effect of added Mn in decomposition and recovery in MAOM in the presence of N fertilization occurred only during the initial 30-day decomposition period, where M 2 showed a 12% increase in cumulative CO 2 production from residue, 8% increase in POM loss, and 43% increase in recovery of residue C in MAOM compared to M 0 . For M 1 , only CO 2 emission from residue was significantly higher than Mo during this period. At 365 days M 2 showed 8% increase in CO 2 production, 1% increase in POM loss, and 16% increase in recovery of residue C in MAOM compared to M 0 , but none of these were statistically significant (p < 0.05). This study adds to the growing evidence that increasing Mn availability enhances plant litter decomposition. However, the occurrence and magnitude of Mn-induced stimulation of decomposition is context specific. Further investigation with greater temporal resolution, involving a multitude of litter and soil types and including microbial compositional and functional characterization, is recommended to fully elucidate the interactive role of Mn and N on C cycling.

59 BASIC BIOLOGICAL SCIENCES↗

Dual-barcoded shotgun expression library sequencing for high-throughput characterization of functional traits in bacteria

A major challenge in genomics is the knowledge gap between sequence and its encoded function. Gain-of-function methods based on gene overexpression are attractive avenues for phenotype-based functional screens, but are not easily applied in high-throughput across many experimental conditions. Here, we present Dual Barcoded Shotgun Expression Library Sequencing (Dub-seq), a method that uses random DNA barcodes to greatly increase experimental throughput. As a demonstration of this approach, we construct a Dub-seq library with Escherichia coli genomic DNA, performed 155 genome-wide fitness assays in 52 experimental conditions, and identified overexpression phenotypes for 813 genes. We show that Dub-seq data is reproducible, accurately recapitulates known biology, and identifies hundreds of novel gain-of-function phenotypes for E. coli genes, a subset of which we verified with assays of individual strains. Dub-seq provides complementary information to loss-of-function approaches and will facilitate rapid and systematic functional characterization of microbial genomes.

59 BASIC BIOLOGICAL SCIENCES↗

A genomic catalog of Earth’s microbiomes

Abstract The reconstruction of bacterial and archaeal genomes from shotgun metagenomes has enabled insights into the ecology and evolution of environmental and host-associated microbiomes. Here we applied this approach to >10,000 metagenomes collected from diverse habitats covering all of Earth’s continents and oceans, including metagenomes from human and animal hosts, engineered environments, and natural and agricultural soils, to capture extant microbial, metabolic and functional potential. This comprehensive catalog includes 52,515 metagenome-assembled genomes representing 12,556 novel candidate species-level operational taxonomic units spanning 135 phyla. The catalog expands the known phylogenetic diversity of bacteria and archaea by 44% and is broadly available for streamlined comparative analyses, interactive exploration, metabolic modeling and bulk download. We demonstrate the utility of this collection for understanding secondary-metabolite biosynthetic potential and for resolving thousands of new host linkages to uncultivated viruses. This resource underscores the value of genome-centric approaches for revealing genomic properties of uncultivated microorganisms that affect ecosystem processes.

59 BASIC BIOLOGICAL SCIENCES↗

Response of Aquatic Bacterial Communities to Hydraulic Fracturing in Northwestern Pennsylvania: A Five-Year Study

Horizontal drilling and hydraulic fracturing extraction procedures have become increasingly present in Pennsylvania where the Marcellus Shale play is largely located. The potential for long-term environmental impacts to nearby headwater stream ecosystems and aquatic bacterial assemblages is still incompletely understood. Here, we perform high-throughput sequencing of the 16 S rRNA gene to characterize the bacterial community structure of water, sediment, and other environmental samples (n = 189) from 31 headwater stream sites exhibiting different histories of fracking activity in northwestern Pennsylvania over five years (2012–2016). Stream pH was identified as a main driver of bacterial changes within the streams and fracking activity acted as an environmental selector for certain members at lower taxonomic levels within stream sediment. Methanotrophic and methanogenic bacteria (i.e. Methylocystaceae, Beijerinckiaceae, and Methanobacterium ) were significantly enriched in sites exhibiting Marcellus shale activity (MSA+) compared to MSA- streams. This study highlighted potential sentinel taxa associated with nascent Marcellus shale activity and some of these taxa remained as stable biomarkers across this five-year study. Identifying the presence and functionality of specific microbial consortia within fracking-impacted streams will provide a clearer understanding of the natural microbial community’s response to fracking and inform in situ remediation strategies.

58 GEOSCIENCES↗

SetBERT: the deep learning platform for contextualized embeddings and explainable predictions from high-throughput sequencing

MOTIVATION: High-throughput sequencing (HTS) is a modern sequencing technology used to profile microbiomes by sequencing thousands of short genomic fragments from the microorganisms within a given sample. This technology presents a unique opportunity for artificial intelligence to comprehend the underlying functional relationships of microbial communities. However, due to the unstructured nature of HTS data, nearly all computational models are limited to processing DNA sequences individually. This limitation causes them to miss out on key interactions between microorganisms, significantly hindering our understanding of how these interactions influence the microbial communities as a whole. Furthermore, most computational methods rely on post-processing of samples which could inadvertently introduce unintentional protocol-specific bias. RESULTS: Addressing these concerns, we present SetBERT, a robust pre-training methodology for creating generalized deep learning models for processing HTS data to produce contextualized embeddings and be fine-tuned for downstream tasks with explainable predictions. By leveraging sequence interactions, we show that SetBERT significantly outperforms other models in taxonomic classification with genus-level classification accuracy of 95%. Furthermore, we demonstrate that SetBERT is able to accurately explain its predictions autonomously by confirming the biological-relevance of taxa identified by the model. AVAILABILITY AND IMPLEMENTATION: All source code is available at https://github.com/DLii-Research/setbert. SetBERT may be used through the q2-deepdna QIIME 2 plugin whose source code is available at https://github.com/DLii-Research/q2-deepdna.

Ludwig, David W↗

Functional team selection as a framework for local adaptation in plants and their belowground microbiomes

Abstract Multicellular organisms are hosts to diverse communities of smaller organisms known as microbiomes. Plants have distinctive microbiomes that can provide important functions related to nutrition, defense, and stress tolerance. Empirical studies provide convincing evidence that in some—but not all—circumstances, belowground microbiomes help plants adapt to their local environment. The purpose of this review is to develop functional team selection (FTS) as a framework to help predict the conditions necessary for root microbiomes to generate local adaptation for their plant hosts. FTS envisions plants and their microbiomes as complex adaptive systems, and plant adaptations as emergent properties of these systems. If plants have the capacity to recognize and cultivate beneficial microbes and suppress pathogens, then it is possible for plants to evolve the capacity to gain adaptations by curating their microbiome. In resource-limited and stressful environments, the emergent functions of complex microbial systems may contribute to positive feedback linked to plant vigor, and ultimately, local adaptation. The key factors in this process are: (i) selective force, (ii) host constitution, (iii) microbial diversity, and (iv) time. There is increasing interest in harnessing beneficial microbial interactions in agriculture and many microbial growth-promoting products are commercially available, but their use is controversial because a large proportion of these products fail to consistently enhance plant growth. The FTS framework may help direct the development of durable plant-microbiome systems that enhance crop production and diminish pathogens. It may also provide valuable insights for understanding and managing other kinds of host-microbe systems.

Environmental Sciences & Ecology↗

Evaluation of Protein Extraction Methods for Metaproteomic Analyses of Root-Associated Microbes

Metaproteomics is a powerful tool for the characterization of metabolism, physiology, and functional interactions in microbial communities, including plant-associated microbiota. However, the metaproteomic methods that have been used to study plant-associated microbiota are very laborious and require large amounts of plant tissue, hindering wider application of these methods. We optimized and evaluated different protein extraction methods for metaproteomics of plant-associated microbiota in two different plant species (Arabidopsis and maize). Our main goal was to identify a method that would work with low amounts of input material (40 to 70 mg) and that would maximize the number of identified microbial proteins. We tested eight protocols, each comprising a different combination of physical lysis method, extraction buffer, and cell-enrichment method on roots from plants grown with synthetic microbial communities. We assessed the performance of the extraction protocols by liquid chromatography-tandem mass spectrometry–based metaproteomics and found that the optimal extraction method differed between the two species. For Arabidopsis roots, protein extraction by beating whole roots with small beads provided the greatest number of identified microbial proteins and improved the identification of proteins from gram-positive bacteria. For maize, vortexing root pieces in the presence of large glass beads yielded the greatest number of microbial proteins identified. Based on these data, we recommend the use of these two methods for metaproteomics with Arabidopsis and maize. Furthermore, detailed descriptions of the eight tested protocols will enable future optimization of protein extraction for metaproteomics in other dicot and monocot plants.

59 BASIC BIOLOGICAL SCIENCES↗

Changes in the composition of the human fecal microbiome following bacteriotherapy for recurrent Clostridium difficile-associated diarrhea

CDAD is the major known cause of antibiotic-induced diarrhea and colitis, and the disease is thought to result from persistent disruption of commensal gut microbiota. Bacteriotherapy by way of fecal transplantation can be used to treat recurrent CDAD and is thought to re-establish the normal colonic microflora. However, limitations of conventional microbiologic techniques have until recently precluded testing of this idea. In this study we used T-RFLP and 16S rRNA gene sequencing approaches to characterize the bacterial composition of the colonic microflora in a patient suffering from recurrent CDAD, before and after treatment by fecal transplantation from a healthy donor. While the patient's residual colonic microbiota, prior to therapy, was deficient in members of the bacterial divisions-Firmicutes and Bacteriodetes, transplantation had a dramatic impact on the composition of the patient's gut microbiota. By 14 days post transplantation, the fecal bacterial composition of the recipient was highly similar to the donor and was dominated by Bacteroides spp. strains and an uncharacterized butyrate producing bacterium. The change in bacterial composition was accompanied by resolution of the patient's symptoms. The striking similarity of the recipient's and donor's intestinal microbiota following bacteriotherapy suggests that the donor's bacteria quickly occupied their requisite niches, resulting in restoration of both the structure and function of the microbial communities present.

54 ENVIRONMENTAL SCIENCES↗

The need for an integrated multi-OMICs approach in microbiome science in the food system

Microbiome science as an interdisciplinary research field has evolved rapidly over the past two decades, becoming a popular topic not only in the scientific community and among the general public, but also in the food industry due to the growing demand for microbiome-based technologies that provide added-value solutions. Microbiome research has expanded in the context of food systems, strongly driven by methodological advances in different -omics fields that leverage our understanding of microbial diversity and function. However, managing and integrating different complex -omics layers are still challenging. Within the Coordinated Support Action MicrobiomeSupport (https://www.microbiomesupport.eu/), a project supported by the European Commission, the workshop “Metagenomics, Metaproteomics and Metabolomics: the need for data integration in microbiome research” gathered 70 participants from different microbiome research fields relevant to food systems, to discuss challenges in microbiome research and to promote a switch from microbiome-based descriptive studies to functional studies, elucidating the biology and interactive roles of microbiomes in food systems. A combination of technologies is proposed. This will reduce the biases resulting from each individual technology and result in a more comprehensive view of the biological system as a whole. Although combinations of different datasets are still rare, advanced bioinformatics tools and artificial intelligence approaches can contribute to understanding, prediction, and management of the microbiome, thereby providing the basis for the improvement of food quality and safety.

60 APPLIED LIFE SCIENCES↗

Expression of Acetate Permease-like (apl) Genes in Subsurface Communities of Geobacter Species Under Fluctuating Acetate Concentrations

The addition of acetate to uranium-contaminated aquifers in order to stimulate the growth and activity of Geobacter species that reduce uranium is a promising in situ bioremediation option. Optimizing this bioremediation strategy requires that sufficient acetate be added to promote Geobacter species growth. We hypothesized that under acetate-limiting conditions, subsurface Geobacter species would increase the expression of either putative acetate symporters genes (aplI and aplII). Acetate was added to a uranium-contaminated aquifer (Rifle, CO) in two continuous amendments separated by 5 days of groundwater flush to create changing acetate concentrations. While the expression of aplI in monitoring well D04 (high acetate) weakly correlated with the acetate concentration over time, the transcript levels for this gene were relatively constant in well D08 (low acetate). At the lowest acetate concentrations during the groundwater flush, the transcript levels of aplII were the highest. The expression of aplII decreased 2–10-fold upon acetate reintroduction. However, the overall instability of acetate concentrations throughout the experiment could not support a robust conclusion regarding the role of apl genes in response to acetate limitation under field conditions, in contrast to previous chemostat studies, suggesting that the function of a microbial community cannot be inferred based on lab experiments alone.

acetate↗

Ancestral alliances: Plant mutualistic symbioses with fungi and bacteria

Taking a look at plant-microbe relationships Ever since plants colonized land, they have evolved a range of mutualistic associations with bacteria and fungi. Indeed, such associations were probably required for plants to grow on harsh, nutrient-poor surfaces. Martin et al. review the spectrum of plant-microbe symbioses and their evolution, including evidence from the Rhynie Chert of the Devonian period and modern associations. Surprisingly, diverse functional plant-microbial symbioses have several common conserved features, including signaling pathways, immune evasion, and root development. Science , this issue p. eaad4501

Martin, Francis M.↗

Priorities, opportunities, and challenges for integrating microorganisms into Earth system models for climate change prediction

ABSTRACT Climate change jeopardizes human health, global biodiversity, and sustainability of the biosphere. To make reliable predictions about climate change, scientists use Earth system models (ESMs) that integrate physical, chemical, and biological processes occurring on land, the oceans, and the atmosphere. Although critical for catalyzing coupled biogeochemical processes, microorganisms have traditionally been left out of ESMs. Here, we generate a “top 10” list of priorities, opportunities, and challenges for the explicit integration of microorganisms into ESMs. We discuss the need for coarse-graining microbial information into functionally relevant categories, as well as the capacity for microorganisms to rapidly evolve in response to climate-change drivers. Microbiologists are uniquely positioned to collect novel and valuable information necessary for next-generation ESMs, but this requires data harmonization and transdisciplinary collaboration to effectively guide adaptation strategies and mitigation policy.

Microbiology↗