The genome-scale models of metabolic networks have been broadly applied in phenotype prediction, evolutionary reconstruction, community functional analysis, and metabolic engineering. Despite the development of tools that support individual steps along the modeling procedure, it is still difficult to associate mathematical simulation results with the annotation and biological interpretation of metabolic models. In order to solve this problem, here we developed a Portable System for the Analysis of Metabolic Models (PSAMM), a new open-source software package that supports the integration of heterogeneous metadata in model annotations and provides a user-friendly interface for the analysis of metabolic models. PSAMM is independent of paid software environments like MATLAB, and all its dependencies are freely available for academic users. Compared to existing tools, PSAMM significantly reduced the running time of constraint-based analysis and enabled flexible settings of simulation parameters using simple one-line commands. The integration of heterogeneous, model-specific annotation information in PSAMM is achieved with a novel format of YAML-based model representation, which has several advantages, such as providing a modular organization of model components and simulation settings, enabling model version tracking, and permitting the integration of multiple simulation problems. PSAMM also includes a number of quality checking procedures to examine stoichiometric balance and to identify blocked reactions. Applying PSAMM to 57 models collected from current literature, we demonstrated how the software can be used for managing and simulating metabolic models. We identified a number of common inconsistencies in existing models and constructed an updated model repository to document the resolution of these inconsistencies.

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. IMPORTANCE Despite their biological and ecological significance, a mechanistic characterization of microbiome function is frequently missing from many nonmodel marine invertebrates. As an initial step toward filling this gap for the eastern oyster, Crassostrea virginica, this study provides an integrated taxonomic and functional analysis of the oyster microbiome using samples from a coastal salt pond in August 2017. The study identified high variability of the microbiome across tissue types and among individual oysters, with some dominant taxa showing higher relative abundance in specific tissues. A high prevalence of Mollicutes in the adult oyster gut was revealed by comparative analysis of the gut, biodeposit, and larva microbiomes. Phylogenomic analysis and metabolic reconstruction suggested the oyster-associated Mollicutes is closely related but functionally distinct from Mollicutes isolated from other marine invertebrates. To the best of our knowledge, this study represents the first metagenomics-derived functional inference of Mollicutes in the eastern oyster microbiome.

Background Although native to North America, the invasion of the aphid-like grape phylloxera Daktulosphaira vitifoliae across the globe altered the course of grape cultivation. For the past 150 years, viticulture relied on grafting-resistant North American Vitis species as rootstocks, thereby limiting genetic stocks tolerant to other stressors such as pathogens and climate change. Limited understanding of the insect genetics resulted in successive outbreaks across the globe when rootstocks failed. Here we report the 294-Mb genome of D. vitifoliae as a basic tool to understand host plant manipulation, nutritional endosymbiosis, and enhance global viticulture. Results Using a combination of genome, RNA, and population resequencing, we found grape phylloxera showed high duplication rates since its common ancestor with aphids, but similarity in most metabolic genes, despite lacking obligate nutritional symbioses and feeding from parenchyma. Similarly, no enrichment occurred in development genes in relation to viviparity. However, phylloxera evolved > 2700 unique genes that resemble putative effectors and are active during feeding. Population sequencing revealed the global invasion began from the upper Mississippi River in North America, spread to Europe and from there to the rest of the world. Conclusions The grape phylloxera genome reveals genetic architecture relative to the evolution of nutritional endosymbiosis, viviparity, and herbivory. The extraordinary expansion in effector genes also suggests novel adaptations to plant feeding and how insects induce complex plant phenotypes, for instance galls. Finally, our understanding of the origin of this invasive species and its genome provide genetics resources to alleviate rootstock bottlenecks restricting the advancement of viticulture.

The well-studied nature of the metabolic diversity of Shewanella bacteria makes species from this genus a promising platform for investigating the evolution of carbon metabolism and energy conservation. The Shewanella phylogeny is diverged into two major branches, referred to as group 1 and group 2. While the genotype-phenotype connections of group 2 species have been extensively studied with metabolic modeling, a genome-scale model has been missing for the group 1 species. The metabolic reconstruction of Shewanella piezotolerans strain WP3 represented the first model for Shewanella group 1 and the first model among piezotolerant and psychrotolerant deep-sea bacteria. The model brought insights into the mechanisms of energy conservation in WP3 under anaerobic conditions and highlighted its metabolic flexibility in using diverse carbon sources. Overall, the model opens up new opportunities for investigating energy conservation and metabolic adaptation, and it provides a prototype for systems-level modeling of other deep-sea microorganisms.

Marine invertebrate microbiomes play important roles in various host and ecological processes. However, a mechanistic understanding of host-microbe interactions is so far only available for a handful 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 amplicon profiling, shotgun metagenomics, and genome-scale metabolic reconstruction. A relatively low number of amplicon sequence variants (ASVs) were observed in oyster tissues compared to water samples, while high variability was observed across individual oysters and among different tissue types. 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 as compared to other closely related Mycoplasma genomes, indicating a distinct mechanism of carbon and energy acquisition by the oyster- associated Mollicutes. A systematic reanalysis of public eastern oyster-derived microbiome data revealed the Mollicutes as a ubiquitous taxon among adult oysters despite their general absence in larvae and biodeposit samples, suggesting potential horizontal transmission via an unknown mechanism.IMPORTANCEDespite well-documented biological significance of invertebrate microbiomes, a detailed taxonomic and functional characterization is frequently missing from many non-model marine invertebrates. By using 16S rRNA gene-based community profiling, shotgun metagenomics, and genome-scale metabolic reconstruction, this study provides an integrated taxonomic and functional analysis of the microbiome of the eastern oyster, Crassostrea virginica. Community profiling revealed a surprisingly low richness, as compared to surrounding seawater, and high variability among different tissue types and individuals. Reconstruction of a Mollicutes MAG enabled the phylogenomic positioning and functional characterization of the oyster-associated Mollicutes. Comparative analysis of the adult oyster gut, biodeposits, and oyster larvae samples indicated the potentially ubiquitous associations of the Mollicutes taxon with adult oysters. To the best of our knowledge, this study represented the first metagenomics derived functional inference of the eastern oyster microbiome. An integrated analytical procedure was developed for the functional characterization of microbiomes in other non-model host species.

PSAMM is an open source software package that supports the iterative curation and analysis of genome-scale models (GEMs). It aims to integrate the annotation and consistency checking of metabolic models with the simulation of metabolic fluxes. The model representation in PSAMM is compatible with version tracking systems like Git, which allows for full documentation of model file changes and enables collaborative curations of large, complex models. This chapter provides a protocol for using PSAMM functions and a detailed description of the various aspects in setting up and using PSAMM for the simulation and analysis of metabolic models. The overall PSAMM workflow outlined in this chapter includes the import and export of model files, the documentation of model modifications using the Git version control system, the application of consistency checking functions for model curations, and the numerical simulation of metabolic models.

Background Equol, an isoflavonoid metabolite with possible health benefits in humans, is known to be produced by some human gut bacteria. While the genes encoding the equol production pathway have been characterized in a few bacterial strains, a systematic analysis of the equol production pathway is currently lacking. Results This study presents an analysis of the taxonomic distribution and evolutionary history of the gene cluster encoding the equol production pathway. A survey for equol gene clusters within the Genome Taxonomy Database bacterial genomes and human gut metagenomes resulted in the identification of a highly conserved gene cluster found in nine bacterial species from the Eggerthellaceae family. The identified gene clusters from human gut metagenomes revealed potential variations in the equol gene cluster organization and gene content within the equol-producing Eggerthellaceae clades. Subsequent analysis showed that in addition to the four genes directly involved in equol production, multiple other genes were consistently found in the equol gene clusters. These genes were predicted to encode a putative electron transport complex and hydrogenase maturase system, suggesting potential roles for them in the equol production pathway. Analysis of the gene clusters and a phylogenetic reconstruction of a putative NAD kinase gene provided evidence of the recent transfer of the equol gene cluster from a basal Eggerthellaceae species to Slackia_A equolifaciens, Enteroscipio sp000270285, and Lactococcus garvieae 20–92. Conclusions This analysis demonstrates that the highly conserved equol gene cluster is taxonomically restricted to the Eggerthellaceae family of bacteria and provides evidence of the role of horizontal gene transfer in the evolutionary history of these genes. These results provide a foundation for future studies of equol production in the human gut and future efforts related to bioengineering and the use of equol-producing bacteria as probiotics.

High‐throughput sequencing has become an increasingly central component of microbiome research. The development of de Bruijn graph‐based methods for assembling high‐throughput sequencing data has been an important part of the broader adoption of sequencing as part of biological studies. Recent advances in the construction and representation of de Bruijn graphs have led to new approaches that utilize the de Bruijn graph data structure to aid in different biological analyses. One type of application of these methods has been in alternative approaches to the assembly of sequencing data like gene‐targeted assembly, where only gene sequences are assembled out of larger metagenomes, and differential assembly, where sequences that are differentially present between two samples are assembled. de Bruijn graphs have also been applied for comparative genomics where they can be used to represent large sets of multiple genomes or metagenomes where structural features in the graphs can be used to identify variants, indels, and homologous regions in sequences. These de Bruijn graph‐based representations of sequencing data have even begun to be applied to whole sequencing databases for large‐scale searches and experiment discovery. de Bruijn graphs have played a central role in how high‐throughput sequencing data is worked with, and the rapid development of new tools that rely on these data structures suggests that they will continue to play an important role in biology in the future.