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  1. Metagenomics is a technique for genome-wide profiling of microbiomes; this technique generates billions of DNA sequences called reads. Given the multiplication of metagenomic projects, computational tools are necessary to enable the efficient and accurate classification of metagenomic reads without needing to construct a reference database. The program DL-TODA presented here aims to classify metagenomic reads using a deep learning model trained on over 3000 bacterial species. A convolutional neural network architecture originally designed for computer vision was applied for the modeling of species-specific features. Using synthetic testing data simulated with 2454 genomes from 639 species, DL-TODA was shown to classify nearly 75% of the reads with high confidence. The classification accuracy of DL-TODA was over 0.98 at taxonomic ranks above the genus level, making it comparable with Kraken2 and Centrifuge, two state-of-the-art taxonomic classification tools. DL-TODA also achieved an accuracy of 0.97 at the species level, which is higher than 0.93 by Kraken2 and 0.85 by Centrifuge on the same test set. Application of DL-TODA to the human oral and cropland soil metagenomes further demonstrated its use in analyzing microbiomes from diverse environments. Compared to Centrifuge and Kraken2, DL-TODA predicted distinct relative abundance rankings and is less biased toward a single taxon. 
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    Free, publicly-accessible full text available April 1, 2024
  2. Certain benthic foraminifera thrive in marine sediments with low or undetectable oxygen. Potential survival avenues used by these supposedly aerobic protists include fermentation and anaerobic respiration, although details on their adaptive mechanisms remain elusive. To better understand the metabolic versatility of foraminifera, we studied two benthic species that thrive in oxygen-depleted marine sediments. Here we detail, via transcriptomics and metatranscriptomics, differential gene expression of Nonionella stella and Bolivina argentea , collected from Santa Barbara Basin, California, USA, in response to varied oxygenation and chemical amendments. Organelle-specific metabolic reconstructions revealed these two species utilize adaptable mitochondrial and peroxisomal metabolism. N. stella , most abundant in anoxia and characterized by lack of food vacuoles and abundance of intracellular lipid droplets, was predicted to couple the putative peroxisomal beta-oxidation and glyoxylate cycle with a versatile electron transport system and a partial TCA cycle. In contrast, B. argentea , most abundant in hypoxia and contains food vacuoles, was predicted to utilize the putative peroxisomal gluconeogenesis and a full TCA cycle but lacks the expression of key beta-oxidation and glyoxylate cycle genes. These metabolic adaptations likely confer ecological success while encountering deoxygenation and expand our understanding of metabolic modifications and interactions between mitochondria and peroxisomes in protists. 
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  3. Mackelprang, Rachel (Ed.)
    ABSTRACT Microbial acclimation to different temperature conditions can involve broad changes in cell composition and metabolic efficiency. A systems-level view of these metabolic responses in nonmesophilic organisms, however, is currently missing. In this study, thermodynamically constrained genome-scale models were applied to simulate the metabolic responses of a deep-sea psychrophilic bacterium, Shewanella psychrophila WP2, under suboptimal (4°C), optimal (15°C), and supraoptimal (20°C) growth temperatures. The models were calibrated with experimentally determined growth rates of WP2. Gibbs free energy change of reactions (Δ r G ′), metabolic fluxes, and metabolite concentrations were predicted using random simulations to characterize temperature-dependent changes in the metabolism. The modeling revealed the highest metabolic efficiency at the optimal temperature, and it suggested distinct patterns of ATP production and consumption that could lead to lower metabolic efficiency under suboptimal or supraoptimal temperatures. The modeling also predicted rearrangement of fluxes through multiple metabolic pathways, including the glycolysis pathway, Entner-Doudoroff pathway, tricarboxylic acid (TCA) cycle, and electron transport system, and these predictions were corroborated through comparisons to WP2 transcriptomes. Furthermore, predictions of metabolite concentrations revealed the potential conservation of reducing equivalents and ATP in the suboptimal temperature, consistent with experimental observations from other psychrophiles. Taken together, the WP2 models provided mechanistic insights into the metabolism of a psychrophile in response to different temperatures. IMPORTANCE Metabolic flexibility is a central component of any organism’s ability to survive and adapt to changes in environmental conditions. This study represents the first application of thermodynamically constrained genome-scale models in simulating the metabolic responses of a deep-sea psychrophilic bacterium to various temperatures. The models predicted differences in metabolic efficiency that were attributed to changes in metabolic pathway utilization and metabolite concentration during growth under optimal and nonoptimal temperatures. Experimental growth measurements were used for model calibration, and temperature-dependent transcriptomic changes corroborated the model-predicted rearrangement of metabolic fluxes. Overall, this study highlights the utility of modeling approaches in studying the temperature-driven metabolic responses of an extremophilic organism. 
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  4. Campbell, Barbara J. (Ed.)
    Marine invertebrate microbiomes play important roles in diverse host and ecological processes. However, a mechanistic understanding of host-microbe interactions is currently available for a small number of model organisms. Here, an integrated taxonomic and functional analysis of the microbiome of the eastern oyster, Crassostrea virginica, was performed using 16S rRNA gene-based amplicon profiling, shotgun metagenomics, and genome-scale metabolic reconstruction. Relatively high variability of the microbiome was observed across individual oysters and among different tissue types. Specifically, a significantly higher alpha diversity was observed in the inner shell than in the gut, gill, mantle, and pallial fluid samples, and a distinct microbiome composition was revealed in the gut compared to other tissues examined in this study. Targeted metagenomic sequencing of the gut microbiota led to further characterization of a dominant bacterial taxon, the class Mollicutes, which was captured by the reconstruction of a metagenome-assembled genome (MAG). Genome-scale metabolic reconstruction of the oyster Mollicutes MAG revealed a reduced set of metabolic functions and a high reliance on the uptake of host-derived nutrients. A chitin degradation and an arginine deiminase pathway were unique to the MAG compared to closely related genomes of Mollicutes isolates, indicating distinct mechanisms of carbon and energy acquisition by the oyster-associated Mollicutes. A systematic reanalysis of public eastern oyster-derived microbiome data revealed a high prevalence of the Mollicutes among adult oyster guts and a significantly lower relative abundance of the Mollicutes in oyster larvae and adult oyster biodeposits. 
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