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At least 271 records · Page 15

Time-series RNA metabarcoding of the active Populus tremuloides root microbiome reveals hidden temporal dynamics and dormant core members

The rhizosphere is a critical interface between plant roots and soil, harboring diverse microbial communities that are essential to plant and ecosystem health. Although these communities exhibit stark temporal dynamics, their dormancy/activity transitions remain poorly understood. Such transitions may enable microbes to rapidly adjust functional contributions faster than community turnover alone would allow. Here, we used RNA metabarcoding to characterize the active fraction of microbial communities on the roots of quaking aspen (Populus tremuloides) in a time-series study across a natural environmental gradient. We explore cryptic temporal microbial community dynamics of rhizosphere communities at the ecosystem scale. The active rhizosphere bacterial and fungal communities were more temporally dynamic than total communities, while total communities exhibited a stronger response to site-specific conditions. Notably, some core microbiome members were often inactive, yielding a smaller “active core” subset. The fungal endophyte Hyaloscypha finlandica was the only microbe that was both present and active in all plots across all timepoints. Soil temperature strongly influenced both total and active community composition, with the fungal class Eurotiomycetes showing a temperature-dependent seasonal decline in abundance. Together, these results reveal that modulation of microbial activity levels is a key mechanism by which the plant root holobiont responds to environmental variation, and that even dominant symbionts may frequently persist in dormancy within the rhizosphere.

Community Structure and Diversity↗

Metagenomic clustering links specific metabolic functions to globally relevant ecosystems

ABSTRACT Metagenomic sequencing has advanced our understanding of biogeochemical processes by providing an unprecedented view into the microbial composition of different ecosystems. While the amount of metagenomic data has grown rapidly, simple-to-use methods to analyze and compare across studies have lagged behind. Thus, tools expressing the metabolic traits of a community are needed to broaden the utility of existing data. Gene abundance profiles are a relatively low-dimensional embedding of a metagenome’s functional potential and are, thus, tractable for comparison across many samples. Here, we compare the abundance of KEGG Ortholog Groups (KOs) from 6,539 metagenomes from the Joint Genome Institute’s Integrated Microbial Genomes and Metagenomes (JGI IMG/M) database. We find that samples cluster into terrestrial, aquatic, and anaerobic ecosystems with marker KOs reflecting adaptations to these environments. For instance, functional clusters were differentiated by the metabolism of antibiotics, photosynthesis, methanogenesis, and surprisingly GC content. Using this functional gene approach, we reveal the broad-scale patterns shaping microbial communities and demonstrate the utility of ortholog abundance profiles for representing a rapidly expanding body of metagenomic data. IMPORTANCE Metagenomics, or the sequencing of DNA from complex microbiomes, provides a view into the microbial composition of different environments. Metagenome databases were created to compile sequencing data across studies, but it remains challenging to compare and gain insight from these large data sets. Consequently, there is a need to develop accessible approaches to extract knowledge across metagenomes. The abundance of different orthologs (i.e., genes that perform a similar function across species) provides a simplified representation of a metagenome’s metabolic potential that can easily be compared with others. In this study, we cluster the ortholog abundance profiles of thousands of metagenomes from diverse environments and uncover the traits that distinguish them. This work provides a simple to use framework for functional comparison and advances our understanding of how the environment shapes microbial communities.

54 ENVIRONMENTAL SCIENCES↗

Sulfur Metabolites Play Key System-Level Roles in Modulating Denitrification

Competition between nitrate-reducing bacteria (NRB) and sulfate-reducing bacteria (SRB) for resources in anoxic environments is generally thought to be governed largely by thermodynamics. It is now recognized that intermediates of nitrogen and sulfur cycling (e.g., hydrogen sulfide, nitrite, etc.) can also directly impact NRB and SRB activities in freshwater, wastewater, and sediment and therefore may play important roles in competitive interactions. Here, through comparative transcriptomic and metabolomic analyses, we have uncovered mechanisms of hydrogen sulfide- and cysteine-mediated inhibition of nitrate respiratory growth for the NRB Intrasporangium calvum C5. Specifically, the systems analysis predicted that cysteine and hydrogen sulfide inhibit growth of I. calvum C5 by disrupting distinct steps across multiple pathways, including branched-chain amino acid (BCAA) biosynthesis, utilization of specific carbon sources, and cofactor metabolism. Here, we have validated these predictions by demonstrating that complementation with BCAAs and specific carbon sources relieves the growth inhibitory effects of cysteine and hydrogen sulfide. We discuss how these mechanistic insights give new context to the interplay and stratification of NRB and SRB in diverse environments.

59 BASIC BIOLOGICAL SCIENCES↗

Application of quasimetagenomics methods to define microbial diversity and subtype Listeria monocytogenes in dairy and seafood production facilities

Microorganisms frequently colonize surfaces within food production facilities. Detection of Listeria monocytogenes in this setting relies on culture-dependent methods, but the complex dynamics of bacterial interactions within these environments and their impact on pathogen detection remain largely unexplored. To address this challenge, we applied both 16S rRNA and shotgun quasimetagenomic (enriched microbiome) sequencing of swab culture enrichments from five seafood and seven dairy production environments. Utilizing 16S rRNA amplicon sequencing, we observed variability between 355 samples taken from these 12 production facilities and a distinctive microbiome for each environment. With shotgun quasimetagenomic sequencing, we were able to assemble L. monocytogenes metagenome-assembled genomes (MAGs) from 28 of the 32 culture-positive samples. We compared these MAGs to their corresponding whole-genome sequencing assemblies, which resulted in two polyphyletic clades consisting of L. monocytogenes lineages I and II with 13,195 and 25,556 single-nucleotide polymorphism sites, respectively. The remaining four MAGs did not produce sufficient genome coverage. To understand and establish limits for pathogen detection and subtyping using shotgun quasimetagenomics, these same data sets were downsampled in slilico to produce a titration series of abundances of L. monocytogenes and analyzed. Pathogen detection was achieved for all downsampled data sets, even those with only 3× genome coverage. This study contributes to the understanding of microbial diversity within food production environments and presents insights into the level of genome coverage needed in a metagenome sequencing data set to detect, subtype, and source track a foodborne pathogen.

59 BASIC BIOLOGICAL SCIENCES↗

Single-Cell Genomics and the Oral Microbiome

The human oral cavity is one of the first environments where microbes have been discovered and studied since the dawn of microbiology. Nevertheless, approximately 200 types of bacteria from the oral microbiota have remained uncultured in the laboratory. Some are associated with a healthy oral microbial community, while others are linked to oral diseases, from dental caries to gum disease. Single-cell genomics has enabled inferences on the physiology, virulence, and evolution of such uncultured microorganisms and has further enabled isolation and cultivation of several novel oral bacteria, including the discovery of novel interspecies interactions. This review summarizes some of the more recent advances in this field, which is rapidly moving toward physiologic characterization of single cells and ultimately cultivation of the yet uncultured. A combination of traditional microbiological approaches with genomic-based physiologic predictions and isolation strategies may lead to the oral microbiome being the first complex microbial community to have all its members cultivable in the laboratory. We conclude studying the biology of the individual microbes when in association with other members of the community, in controlled laboratory conditions and in vivo, should lead to a better understanding of oral dysbiosis and its prevention and reversion.

59 BASIC BIOLOGICAL SCIENCES↗

Hyporheic zone, river, and groundwater metagenome resolved genomes and rpS3 genes in East River Watershed, Colorado USA Summer 2020, 2021

Here we present metagenome assembled genomes (MAGs) for the bacterial and archaeal communities from water filter collected across 8 locations along the East River Watershed, CO, and 1 nearby groundwater well. The purpose was to look for connectivity and similarities across the network and to see the impact of the groundwater. As a part of Lawrence Berkeley National Laboratory (LBNL) Watershed Science Focus Area (SFA), we assessed community composition and strain similarities between the sites and we also compared it to previous metagenomic studies within the watershed looking at floodplain (Matheus Carnevali et al. 2021) and hillslope (Lavy et al. 2019) microbiomes. Here we present metagenome assembled genomes (MAGs) for the bacterial and archaeal communities from filters across 8 locations during August 2020 and July 2021. This resulted in 32 samples. The groundwater sample was sequenced at UC Berkley's QB3. The other 31 samples were sequenced at University of Maryland. Metagenomes were assembled using four autobinners and the best bins were selected using dasTool. The genomes were dereplicated at 95% with dRep and the subset of winning genomes were manually curated based on visual inspection of taxonomic profile, GC content, coverage, and a set of 51 bacterial single copy genes (BSCG), and 38 archaeal signal copy genes (ASCG). The dataset includes a zip file of 311 genomes (HZ_River_SW_MAGS_Dereplicated_95.zip). The dataset additionally includes a zipped file of ribosomal protein small subunit 3 (rpS3) proteins from the hyporheic zone and river data (rpS3_Proteins_HZ_River.zip), a metadata file used to register associated samples with IGSNs (International Generic Sample Numbers) (samples.csv), a location metadata file (locations.csv). This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

DNA↗

Process Optimization and Real-Time Control of Synergistic Microalgae Cultivation and Wastewater Treatment (Final Technical Report)

The overarching goal of this work was to accelerate the commercialization of high productivity, mixed community microalgal treatment technologies for the synergistic treatment of wastewater and the production of biofuel feedstocks. This project addressed a critical barrier to the financial viability and energy efficiency of algal wastewater treatment: an inability to design and operate high-rate processes that reliably achieve target effluent qualities, areal productivities, and biochemical compositions (lipid, protein, carbohydrate content) despite fluctuations in wastewater composition, weather, and microbial communities. Key outcomes from this work include an optimized and controlled Advanced Biological Nutrient Recovery (ABNR) design as well as a suite of open-source tools that include a calibrated and validated algae process simulator in QSDsan and a novel low-cost, real-time microbial monitoring tool. These tools can be leveraged by other algal cultivation and wastewater treatment technology developers in future work.

09 BIOMASS FUELS↗

Challenges in Bioinformatics Workflows for Processing Microbiome Omics Data at Scale

The nascent field of microbiome science is transitioning from a descriptive approach of cataloging taxa and functions present in an environment to applying multi-omics methods to investigate microbiome dynamics and function. A large number of new tools and algorithms have been designed and used for very specific purposes on samples collected by individual investigators or groups. While these developments have been quite instructive, the ability to compare microbiome data generated by many groups of researchers is impeded by the lack of standardized application of bioinformatics methods. Additionally, there are few examples of broad bioinformatics workflows that can process metagenome, metatranscriptome, metaproteome and metabolomic data at scale, and no central hub that allows processing, or provides varied omics data that are findable, accessible, interoperable and reusable (FAIR). Here, we review some of the challenges that exist in analyzing omics data within the microbiome research sphere, and provide context on how the National Microbiome Data Collaborative has adopted a standardized and open access approach to address such challenges.

NMDC, Microbiome↗

Microbiome Variation Across Two Hemlock Species With Hemlock Woolly Adelgid Infestation

The hemlock woolly adelgid ( Adelges tsugae , HWA), an invasive insect, is devastating native hemlock populations in eastern North America, and management outcomes have so far had limited success. While many plant microbiomes influence and even support plant immune responses to insect herbivory, relatively little is known about the hemlock microbiome and its interactions with pathogens or herbivores such as HWA. Using 16S rRNA and ITS gene amplicon sequencing, we characterized the needle, branch, root, and rhizosphere microbiome of two hemlock species, Tsuga canadensis and T. sieboldii , that displayed low and high levels of HWA populations. We found that both archaeal/bacterial and fungal needle communities, as well as the archaeal/bacterial branch and root communities, varied in composition in both hemlock species relative to HWA population levels. While host species and plant-associated habitats explained a greater proportion of the variance in the microbiome than did HWA population level, high HWA populations were associated with enrichment of 100 likely fungal pathogen sequence variants across the four plant-associated habitats (e.g., needle, branch, root, rhizosphere) compared to trees with lower HWA populations. This work contributes to a growing body of literature linking plant pathogens and pests with the changes in the associated plant microbiome and host health. Furthermore, this work demonstrates the need to further investigate plant microbiome effects across multiple plant tissues to understand their influences on host health.

16S rRNA↗

Comparative Analysis of Microbial Diversity Across Temperature Gradients in Hot Springs From Yellowstone and Iceland

Geothermal hot springs are a natural setting to study microbial adaptation to a wide range of temperatures reaching up to boiling. Temperature gradients lead to distinct microbial communities that inhabit their optimum niches. We sampled three alkaline, high temperature (80–100°C) hot springs in Yellowstone and Iceland that had cooling outflows and whose microbial communities had not been studied previously. The microbial composition in sediments and mats was determined by DNA sequencing of rRNA gene amplicons. Over three dozen phyla of Archaea and Bacteria were identified, representing over 1700 distinct organisms. We observed a significant non-linear reduction in the number of microbial taxa as the temperature increased from warm (38°C) to boiling. At high taxonomic levels, the community structure was similar between the Yellowstone and Iceland hot springs. We identified potential endemism at the genus level, especially in thermophilic phototrophs, which may have been potentially driven by distinct environmental conditions and dispersal limitations.

59 BASIC BIOLOGICAL SCIENCES↗

Functional Genomics, Transcriptomics, and Proteomics Reveal Distinct Combat Strategies Between Lineages of Wood-Degrading Fungi With Redundant Wood Decay Mechanisms

Wood-degrading fungi vary in their strategies for deconstructing wood, and their competitive successes shape the rate and fate of carbon released from wood, Earth’s largest pool of aboveground terrestrial carbon. In this study, one-on-one interspecific interactions between two model brown rot (carbohydrate-selective) fungi, Gloeophyllum trabeum and Rhodonia (Postia) placenta, were studied on wood wafers where a clearly resolved interaction zone (IZ) could be generated, reproducibly. Comparative RNAseq and proteomics between the IZ and non-interacting hyphae of each species identified combative strategies for each fungus. Glycoside hydrolases were a relatively smaller portion of the interaction secretome compared to non-interacting hyphae. The interaction zone showed higher pectinase specific activity than all other sampling locations, and higher laminarinase specific activity (branched ß-glucan proxy) was seen in the IZ secretome relative to equivalent hyphae in single-species cultures. Our efforts also identified two distinct competitive strategies in these two fungi with a shared nutritional mode (brown rot) but polyphyletic ancestral lineages. Gloeophyllum trabeum (Gloeophyllum clade) employed secondary metabolite (SM) synthesis in response to a competitor, as shown by the upregulation of several SM-synthesizing genes in the interaction. R. placenta (Antrodia clade) instead upregulated a larger variety of uncharacterized oxidoreductases in interacting hyphae, suggesting that an oxidative burst may be a response to competitors in this fungus. Both species produced several hypothetical proteins exclusively in the interaction zone, leaving abundant unknowns on the battlefield. This work supports the existence of multiple interaction strategies among brown rot fungi and highlights the functional diversity among wood decay fungi.

59 BASIC BIOLOGICAL SCIENCES↗

Editorial: Selective Controls on Microbial Energy Metabolisms: From the Microscale to the Macroscale

A mechanistic and predictive understanding of the genotypic and phenotypic controls on microbial element cycling remains a grand challenge in microbiology. While the composition and concentration of carbon sources, electron donors, and electron acceptors are known to influence microbial community structure by selecting for microbial sub-populations with distinct catabolic and respiratory pathways, selective inhibitors and trace nutrient availability modulate the activity of metabolic enzymes. This in turn influences the distribution of microbial sub-populations with distinct metabolic and respiratory traits, which are then structured by complex multi-dimensional environmental gradients that influence the composition, gene content and element cycling activity of microbiomes. While some parameters are known to select for different respiratory activities (e.g., lanthanides as essential nutrients for methanotrophs, molybdate as a specific inhibitor of sulfate reduction, carbon:nitrogen ratio and concentration as a control on the end-products of nitrate respiration), there are others to discover, and demonstrating how selective parameters operate and mediate element cycling across scales requires multi-disciplinary research in both the lab and field.

59 BASIC BIOLOGICAL SCIENCES↗

The Gut Microbiome and Alcoholic Liver Disease: Ethanol Consumption Drives Consistent and Reproducible Alteration in Gut Microbiota in Mice

Phenotypic health effects, both positive and negative, have been well studied in association with the consumption of alcohol in humans as well as several other mammals including mice. Many studies have also associated these same health effects and phenotypes to specific members of gut microbiome communities. Here we utilized a chronic plus binge ethanol feed model (Gao-binge model) to explore microbiome community changes across three independent experiments performed in mice. We found significant and reproducible differences in microbiome community assemblies between ethanol-treated mice and control mice on the same diet absent of ethanol. We also identified significant differences in gut microbiota occurring temporally with ethanol treatment. Peak shift in communities was observed 4 days after the start of daily alcohol consumption. We quantitatively identified many of the bacterial genera indicative of these ethanol-induced shifts including 20 significant genera when comparing ethanol treatments with controls and 14 significant genera based on temporal investigation. Including overlap of treatment with temporal shifts, we identified 25 specific genera of interest in ethanol treatment microbiome shifts. Shifts coincide with observed presentation of fatty deposits in the liver tissue, i.e., Alcoholic Liver Disease-associated phenotype. The evidence presented herein, derived from three independent experiments, points to the existence of a common, reproducible, and characterizable “mouse ethanol gut microbiome”.

59 BASIC BIOLOGICAL SCIENCES↗

The Promises, Challenges, and Opportunities of Omics for Studying the Plant Holobiont

Microorganisms are critical drivers of biological processes that contribute significantly to plant sustainability and productivity. In recent years, emerging research on plant holobiont theory and microbial invasion ecology has radically transformed how we study plant–microbe interactions. Over the last few years, we have witnessed an accelerating pace of advancements and breadth of questions answered using omic technologies. Herein, we discuss how current state-of-the-art genomics, transcriptomics, proteomics, and metabolomics techniques reliably transcend the task of studying plant–microbe interactions while acknowledging existing limitations impeding our understanding of plant holobionts.

59 BASIC BIOLOGICAL SCIENCES↗

Sweet Sorghum Genotypes Tolerant and Sensitive to Nitrogen Stress Select Distinct Root Endosphere and Rhizosphere Bacterial Communities

The belowground microbiomes have many beneficial functions that assist plant growth, including nutrient cycling, acquisition and transport, as well as alleviation of stresses caused by nutrient limitations such as nitrogen (N). Here we analyzed the root endosphere, rhizosphere and soil bacterial communities of seven sweet sorghum genotypes differing in sensitivity to N-stress. Sorghum genotypes were grown in fields with no (low-N) or sufficient (high-N) N. The dry shoot weight ratio (low-N/high-N) was used to determine N-stress sensitivity. Our hypothesis was that genotypes tolerant and sensitive to N-stress select distinct bacterial communities. The endosphere and rhizosphere bacterial community structure were significantly different between the N-stress sensitive and tolerant genotypes in the high-N field, but not in the low-N field. However, significant changes in the relative abundance of specific bacterial taxa were observed in both fields. Streptomyces, a bacterial genus known to alleviate plant abiotic stresses, was enriched in the endosphere and rhizosphere of the tolerant genotypes in the low-N field. Our study indicates that sweet sorghum genotypes tolerant to N-stress select taxa that can potentially mitigate the N-stress, suggesting that the interactions between N-stress tolerant lines and the root-associated microbiome might be vital for coping with N-stress.

59 BASIC BIOLOGICAL SCIENCES↗

Microbial Taxa Distribution Data From 16S rRNA Analysis Of Desalination Operations At Carlsbad, CA And Tampa Bay, FL

This data set list the distribution of microbial taxa from three sets of sampling campaigns from unit operations in two large desalination facilities in the US conducted between March and May 2021. The desalination plants include the Claude "Bud" Lewis Carlsbad Desalination Plant in Carlsbad, California and the Seater Desalination facility in Tampa Bay, Florida.

16s rRNA gene analysis↗