Multiomics in the central Arctic Ocean for benchmarking biodiversity change.

Multiomics approaches need to be applied in the central Arctic Ocean to benchmark biodiversity change and to identify novel species and their genes. As part of MOSAiC, EcoOmics will therefore be essential for conservation and sustainable bioprospecting in one of the least explored ecosystems on Earth.

Metatranscriptomes of two biological soil crust types from the Mojave desert in response to wetting.

We present eight metatranscriptomic datasets of light algal and cyanolichen biological soil crusts from the Mojave Desert in response to wetting. These data will help us understand gene expression patterns in desert biocrust microbial communities after they have been reactivated by the addition of water.

Whole community shotgun metagenomes of two biological soil crust types from the Mojave Desert.

We present six whole community shotgun metagenomic sequencing data sets of two types of biological soil crusts sampled at the ecotone of the Mojave Desert and Colorado Desert in California. These data will help us understand the diversity and function of biocrust microbial communities, which are essential for desert ecosystems.

Metagenome Sequencing to Explore Phylogenomics of Terrestrial Cyanobacteria.

Cyanobacteria are ubiquitous microorganisms with crucial ecosystem functions, yet most knowledge of their biology relates to aquatic taxa. We have constructed metagenomes for 50 taxonomically well-characterized terrestrial cyanobacterial cultures. These data will support phylogenomic studies of evolutionary relationships and gene content among these unique algae and their aquatic relatives.

DOE JGI Metagenome Workflow.

The DOE Joint Genome Institute (JGI) Metagenome Workflow performs metagenome data processing, including assembly; structural, functional, and taxonomic annotation; and binning of metagenomic data sets that are subsequently included into the Integrated Microbial Genomes and Microbiomes (IMG/M) (I.-M. A. Chen, K. Chu, K. Palaniappan, A. Ratner, et al., Nucleic Acids Res, 49:D751-D763, 2021, https://doi.org/10.1093/nar/gkaa939) comparative analysis system and provided for download via the JGI data portal (https://genome.jgi.doe.gov/portal/). This workflow scales to run on thousands of metagenome samples per year, which can vary by the complexity of microbial communities and sequencing depth. Here, we describe the different tools, databases, and parameters used at different steps of the workflow to help with the interpretation of metagenome data available in IMG and to enable researchers to apply this workflow to their own data. We use 20 publicly available sediment metagenomes to illustrate the computing requirements for the different steps and highlight the typical results of data processing. The workflow modules for read filtering and metagenome assembly are available as a workflow description language (WDL) file (https://code.jgi.doe.gov/BFoster/jgi_meta_wdl). The workflow modules for annotation and binning are provided as a service to the user community at https://img.jgi.doe.gov/submit and require filling out the project and associated metadata descriptions in the Genomes OnLine Database (GOLD) (S. Mukherjee, D. Stamatis, J. Bertsch, G. Ovchinnikova, et al., Nucleic Acids Res, 49:D723-D733, 2021, https://doi.org/10.1093/nar/gkaa983).IMPORTANCE The DOE JGI Metagenome Workflow is designed for processing metagenomic data sets starting from Illumina fastq files. It performs data preprocessing, error correction, assembly, structural and functional annotation, and binning. The results of processing are provided in several standard formats, such as fasta and gff, and can be used for subsequent integration into the Integrated Microbial Genomes and Microbiomes (IMG/M) system where they can be compared to a comprehensive set of publicly available metagenomes. As of 30 July 2020, 7,155 JGI metagenomes have been processed by the DOE JGI Metagenome Workflow. Here, we present a metagenome workflow developed at the JGI that generates rich data in standard formats and has been optimized for downstream analyses ranging from assessment of the functional and taxonomic composition of microbial communities to genome-resolved metagenomics and the identification and characterization of novel taxa. This workflow is currently being used to analyze thousands of metagenomic data sets in a consistent and standardized manner.

The biogeographic differentiation of algal microbiomes in the upper ocean from pole to pole.

Eukaryotic phytoplankton are responsible for at least 20% of annual global carbon fixation. Their diversity and activity are shaped by interactions with prokaryotes as part of complex microbiomes. Although differences in their local species diversity have been estimated, we still have a limited understanding of environmental conditions responsible for compositional differences between local species communities on a large scale from pole to pole. Here, we show, based on pole-to-pole phytoplankton metatranscriptomes and microbial rDNA sequencing, that environmental differences between polar and non-polar upper oceans most strongly impact the large-scale spatial pattern of biodiversity and gene activity in algal microbiomes. The geographic differentiation of co-occurring microbes in algal microbiomes can be well explained by the latitudinal temperature gradient and associated break points in their beta diversity, with an average breakpoint at 14 °C ± 4.3, separating cold and warm upper oceans. As global warming impacts upper ocean temperatures, we project that break points of beta diversity move markedly pole-wards. Hence, abrupt regime shifts in algal microbiomes could be caused by anthropogenic climate change.

Metagenomes from Experimental Hydrologic Manipulation of Restored Coastal Plain Wetland Soils (Tyrell County, North Carolina).

Hydrologic changes modify microbial community structure and ecosystem functions, especially in wetland systems. Here, we present 24 metagenomes from a coastal freshwater wetland experiment in which we manipulated hydrologic conditions and plant presence. These wetland soil metagenomes will deepen our understanding of how hydrology and vegetation influence microbial functional diversity.

Metagenomes and Metatranscriptomes of a Glucose-Amended Agricultural Soil.

The addition of glucose to soil has long been used to study the metabolic activity of microbes in soil; however, the response of the microbial ecophysiology remains poorly characterized. To address this, we sequenced the metagenomes and metatranscriptomes of glucose-amended soil microbial communities in a laboratory incubation.

Metatranscriptomic Sequencing of a Cyanobacterial Soil-Surface Consortium with and without a Diverse Underlying Soil Microbiome.

Soil surface consortia are easily observed and sampled, allowing examination of their interactions with soil microbiomes. Here, we present metatranscriptomic sequences from Dark Green 1 (DG1), a cyanobacterium-based soil surface consortium, in the presence and absence of an underlying soil microbiome and/or urea.

Metagenomes and metatranscriptomes from boreal potential and actual acid sulfate soil materials.

Natural sulfide rich deposits are common in coastal areas worldwide, including along the Baltic Sea coast. When artificial drainage exposes these deposits to atmospheric oxygen, iron sulfide minerals in the soils are rapidly oxidized. This process turns the potential acid sulfate soils into actual acid sulfate soils and mobilizes large quantities of acidity and leachable toxic metals that cause severe environmental problems. It is known that acidophilic microorganisms living in acid sulfate soils catalyze iron sulfide mineral oxidation. However, only a few studies regarding these communities have been published. In this study, we sampled the oxidized actual acid sulfate soil, the transition zone where oxidation is actively taking place, and the deepest un-oxidized potential acid sulfate soil. Nucleic acids were extracted and 16S rRNA gene amplicons, metagenomes, and metatranscriptomes generated to gain a detailed insight into the communities and their activities. The project will be of great use to microbiologists, environmental biologists, geochemists, and geologists as there is hydrological and geochemical monitoring from the site stretching back for many years.

Microbial metagenomes and metatranscriptomes during a coastal phytoplankton bloom.

Metagenomic and metatranscriptomic time-series data covering a 52-day period in the fall of 2016 provide an inventory of bacterial and archaeal community genes, transcripts, and taxonomy during an intense dinoflagellate bloom in Monterey Bay, CA, USA. The dataset comprises 84 metagenomes (0.8 terabases), 82 metatranscriptomes (1.1 terabases), and 88 16S rRNA amplicon libraries from samples collected on 41 dates. The dataset also includes 88 18S rRNA amplicon libraries, characterizing the taxonomy of the eukaryotic community during the bloom. Accompanying the sequence data are chemical and biological measurements associated with each sample. These datasets will facilitate studies of the structure and function of marine bacterial communities during episodic phytoplankton blooms.

Microbiomes of Velloziaceae from phosphorus-impoverished soils of the campos rupestres, a biodiversity hotspot.

The rocky, seasonally-dry and nutrient-impoverished soils of the Brazilian campos rupestres impose severe growth-limiting conditions on plants. Species of a dominant plant family, Velloziaceae, are highly specialized to low-nutrient conditions and seasonal water availability of this environment, where phosphorus (P) is the key limiting nutrient. Despite plant-microbe associations playing critical roles in stressful ecosystems, the contribution of these interactions in the campos rupestres remains poorly studied. Here we present the first microbiome data of Velloziaceae spp. thriving in contrasting substrates of campos rupestres. We assessed the microbiomes of Vellozia epidendroides, which occupies shallow patches of soil, and Barbacenia macrantha, growing on exposed rocks. The prokaryotic and fungal profiles were assessed by rRNA barcode sequencing of epiphytic and endophytic compartments of roots, stems, leaves and surrounding soil/rocks. We also generated root and substrate (rock/soil)-associated metagenomes of each plant species. We foresee that these data will contribute to decipher how the microbiome contributes to plant functioning in the campos rupestres, and to unravel new strategies for improved crop productivity in stressful environments.