Many insects engage in stable nutritional symbioses with bacteria that supplement limiting essential nutrients to their host. While several plant sap-feeding Hemipteran lineages are known to be simultaneously associated with two or more endosymbionts with complementary biosynthetic pathways to synthesize amino acids or vitamins, such co-obligate symbioses have not been functionally characterized in other insect orders. Here, we report on the characterization of a dual co-obligate, bacteriome-localized symbiosis in a family of xylophagous beetles using comparative genomics, fluorescence microscopy, and phylogenetic analyses. Across the beetle family Bostrichidae, most investigated species harbored the Bacteroidota symbiont Shikimatogenerans bostrichidophilus that encodes the shikimate pathway to produce tyrosine precursors in its severely reduced genome, likely supplementing the beetles’ cuticle biosynthesis, sclerotisation, and melanisation. One clade of Bostrichid beetles additionally housed the co-obligate symbiont Bostrichicola ureolyticus that is inferred to complement the function of Shikimatogenerans by recycling urea and provisioning the essential amino acid lysine, thereby providing additional benefits on nitrogen-poor diets. Both symbionts represent ancient associations within the Bostrichidae that have subsequently experienced genome erosion and co-speciation with their hosts. While Bostrichicola was repeatedly lost, Shikimatogenerans has been retained throughout the family and exhibits a perfect pattern of co-speciation. Our results reveal that co-obligate symbioses with complementary metabolic capabilities occur beyond the well-known sap-feeding Hemiptera and highlight the importance of symbiont-mediated cuticle supplementation and nitrogen recycling for herbivorous beetles.

Hemipterans are known as hosts to bacterial or fungal symbionts that supplement their unbalanced diet with essential nutrients. Among them, scale insects (Coccomorpha) are characterized by a particularly large diversity of symbiotic systems. Here, using microscopic and genomic approaches, we functionally characterized the symbionts of two scale insects belonging to the Eriococcidae family, Acanthococcus aceris and Gossyparia spuria. These species host Burkholderia bacteria that are localized in the cytoplasm of the fat body cells. Metagenome sequencing revealed very similar and highly reduced genomes (<900KBp) with a low GC content (~38%), making them the smallest and most AT-biased Burkholderia genomes yet sequenced. In their eroded genomes, both symbionts retain biosynthetic pathways for the essential amino acids leucine, isoleucine, valine, threonine, lysine, arginine, histidine, phenylalanine, and precursors for the semi-essential amino acid tyrosine, as well as the cobalamin-dependent methionine synthase MetH. A tryptophan biosynthesis pathway is conserved in the symbiont of G. spuria, but appeared pseudogenized in A. aceris, suggesting differential availability of tryptophan in the two host species' diets. In addition to the pathways for essential amino acid biosynthesis, both symbionts maintain biosynthetic pathways for multiple cofactors, including riboflavin, cobalamin, thiamine, and folate. The localization of Burkholderia symbionts and their genome traits indicate that the symbiosis between Burkholderia and eriococcids is younger than other hemipteran symbioses, but is functionally convergent. Our results add to the emerging picture of dynamic symbiont replacements in sap-sucking Hemiptera and highlight Burkholderia as widespread and versatile intra- and extracellular symbionts of animals, plants, and fungi.

Glyphosate is widely used as a herbicide, but recent studies begin to reveal its detrimental side effects on animals by targeting the shikimate pathway of associated gut microorganisms. However, its impact on nutritional endosymbionts in insects remains poorly understood. Here, we sequenced the tiny, shikimate pathway encoding symbiont genome of the sawtoothed grain beetle Oryzaephilus surinamensis . Decreased titers of the aromatic amino acid tyrosine in symbiont-depleted beetles underscore the symbionts’ ability to synthesize prephenate as the precursor for host tyrosine synthesis and its importance for cuticle sclerotization and melanization. Glyphosate exposure inhibited symbiont establishment during host development and abolished the mutualistic benefit on cuticle synthesis in adults, which could be partially rescued by dietary tyrosine supplementation. Furthermore, phylogenetic analyses indicate that the shikimate pathways of many nutritional endosymbionts likewise contain a glyphosate sensitive 5-enolpyruvylshikimate-3-phosphate synthase. These findings highlight the importance of symbiont-mediated tyrosine supplementation for cuticle biosynthesis in insects, but also paint an alarming scenario regarding the use of glyphosate in light of recent declines in insect populations.

Symbiotic microbes can enable their host to access untapped nutritional resources but may also constrain niche space by promoting specialization. Here, we reconstruct functional changes in the evolutionary history of the symbiosis between a group of (semi-)aquatic herbivorous insects and mutualistic bacteria. Sequencing the symbiont genomes across 26 species of reed beetles (Chrysomelidae, Donaciinae) spanning four genera indicates that the genome-eroded mutualists provide life stage-specific benefits to larvae and adults, respectively. In the plant sap-feeding larvae, the symbionts are inferred to synthesize most of the essential amino acids as well as the B vitamin riboflavin. The adult reed beetles’ folivory is likely supported by symbiont-encoded pectinases that complement the host-encoded set of cellulases, as revealed by transcriptome sequencing. However, mapping the occurrence of the symbionts’ pectinase genes and the hosts’ food plant preferences onto the beetles’ phylogeny reveals multiple independent losses of pectinase genes in lineages that switched to feeding on pectin-poor plants, presumably constraining their hosts’ subsequent adaptive potential.

Regional Student Groups (RSGs) of the International Society for Computational Biology Student Council (ISCB-SC) have been instrumental to connect computational biologists globally and to create more awareness about bioinformatics education. This article highlights the initiatives carried out by the RSGs both nationally and internationally to strengthen the present and future of the bioinformatics community. Moreover, we discuss the future directions the organization will take and the challenges to advance further in the ISCB-SC main mission: “Nurture the new generation of computational biologists”.

While genome erosion is extensively studied in intracellular symbionts, the metabolic implications of reductive evolution in microbes subsisting extracellularly remain poorly understood. Stammera capleta —an extracellular symbiont in leaf beetles—possesses an extremely reduced genome (0.27 Mb), enabling the study of drastic reductive evolution in the absence of intracellularity. Here, we outline the genomic and transcriptomic profiles of Stammera and its host to elucidate host-symbiont metabolic interactions. Given the symbiont’s substantial demands for nutrients and membrane components, the host’s symbiotic organ shows repurposing of internal resources by upregulating nutrient transporters and cuticle-processing genes targeting epithelial chitin. Facilitated by this supplementation and its localization, Stammera exhibits a highly streamlined gene expression profile and a fermentation pathway for energy conversion, sharply contrasting the respiratory metabolism retained by most intracellular symbionts. Our results provide insights into a tightly regulated and metabolically integrated extracellular symbiosis, expanding our understanding of the minimal metabolism required to sustain life outside of a host cell.

Crohn’s disease (CD) is associated with an ecological imbalance of the intestinal microbiota, consisting of hundreds of species. The underlying complexity as well as individual differences between patients contributes to the difficulty to define a standardized treatment. Computational modeling can systematically investigate metabolic interactions between gut microbes to unravel mechanistic insights. In this study, we integrated metagenomic data of CD patients and healthy controls with genome-scale metabolic models into personalized in silico microbiotas. We predicted short chain fatty acid (SFCA) levels for patients and controls, which were overall congruent with experimental findings. As an emergent property, low concentrations of SCFA were predicted for CD patients and the SCFA signatures were unique to each patient. Consequently, we suggest personalized dietary treatments that could improve each patient’s SCFA levels. The underlying modeling approach could aid clinical practice to find dietary treatment and guide recovery by rationally proposing food aliments.

An important hallmark of the human gut microbiota is its species diversity and complexity. Various diseases have been associated with a decreased diversity leading to reduced metabolic functionalities. Common approaches to investigate the human microbiota include high-throughput sequencing with subsequent correlative analyses. However, to understand the ecology of the human gut microbiota and consequently design novel treatments for diseases, it is important to represent the different interactions between microbes with their associated metabolites. Computational systems biology approaches can give further mechanistic insights by constructing data- or knowledge-driven networks that represent microbe interactions. In this minireview, we will discuss current approaches in systems biology to analyze the human gut microbiota, with a particular focus on constraint-based modeling. We will discuss various community modeling techniques with their advantages and differences, as well as their application to predict the metabolic mechanisms of intestinal microbial communities. Finally, we will discuss future perspectives and current challenges of simulating realistic and comprehensive models of the human gut microbiota.

Pectin, an integral component of the plant cell wall, is a recalcitrant substrate against enzymatic challenges by most animals. In characterizing the source of a leaf beetle’s (Cassida rubiginosa) pectin-degrading phenotype, we demonstrate its dependency on an extracellular bacterium housed in specialized organs connected to the foregut. Despite possessing the smallest genome (0.27 Mb) of any organism not subsisting within a host cell, the symbiont nonetheless retained a functional pectinolytic metabolism targeting the polysaccharide’s two most abundant classes: homogalacturonan and rhamnogalacturonan I. Comparative transcriptomics revealed pectinase expression to be enriched in the symbiotic organs, consistent with enzymatic buildup in these structures following immunostaining with pectinase-targeting antibodies. Symbiont elimination results in a drastically reduced host survivorship and a diminished capacity to degrade pectin. Collectively, our findings highlight symbiosis as a strategy for an herbivore to metabolize one of nature’s most complex polysaccharides and a universal component of plant tissues.

Recent advances focusing on the metabolic interactions within and between cellular populations have emphasized the importance of microbial communities for human health. Constraint-based modeling, with flux balance analysis in particular, has been established as a key approach for studying microbial metabolism, whereas individual-based modeling has been commonly used to study complex dynamics between interacting organisms. In this study, we combine both techniques into the R package BacArena (https://cran.r-project.org/package=BacArena) to generate novel biological insights into Pseudomonas aeruginosa biofilm formation as well as a seven species model community of the human gut. For our P. aeruginosa model, we found that cross-feeding of fermentation products cause a spatial differentiation of emerging metabolic phenotypes in the biofilm over time. In the human gut model community, we found that spatial gradients of mucus glycans are important for niche formations which shape the overall community structure. Additionally, we could provide novel hypothesis concerning the metabolic interactions between the microbes. These results demonstrate the importance of spatial and temporal multi-scale modeling approaches such as BacArena.

Microbial communities are essential for global ecosystems and human health. Computational modeling of microbial consortia is thus a major goal in systems biology and microbial ecology. BacArena is a project to simulate bacterial behavior in communities. A lot of progress is done in the last years to create genome wide metabolic reconstructions of certain organisms, which open a wide field of mathematical analysis. One of this new methods is flux balanced analysis (FBA) to estimate optimal metabolic fluxes under certain constraints. Some of these models are available in an exchangeable format (SBML) and can be found in http://systemsbiology.ucsd.edu/InSilicoOrganisms/OtherOrganisms. The idea of this project is to use this existing reconstructions and put them in a spatial and temporal environment to study their possible interactions. This is achieved by the combination of agent based modeling with FBA. Each bacterium is considered as an agent with individual states, own properties and rules to act. Agents are located on a grid where they can move and interact via metabolic exchanges computed by FBA. The starting point for our project is curiosity of what could be done with these huge models. We just throw those models into an arena to see what kind of actions will evolve.

BACKGROUND:The human gastrointestinal tract harbors a diverse microbial community, in which metabolic phenotypes play important roles for the human host. Recent developments in meta-omics attempt to unravel metabolic roles of microbes by linking genotypic and phenotypic characteristics. This connection, however, still remains poorly understood with respect to its evolutionary and ecological context.RESULTS:We generated automatically refined draft genome-scale metabolic models of 301 representative intestinal microbes in silico. We applied a combination of unsupervised machine-learning and systems biology techniques to study individual and global differences in genomic content and inferred metabolic capabilities. Based on the global metabolic differences, we found that energy metabolism and membrane synthesis play important roles in delineating different taxonomic groups. Furthermore, we found an exponential relationship between phylogeny and the reaction composition, meaning that closely related microbes of the same genus can exhibit pronounced differences with respect to their metabolic capabilities while at the family level only marginal metabolic differences can be observed. This finding was further substantiated by the metabolic divergence within different genera. In particular, we could distinguish three sub-type clusters based on membrane and energy metabolism within the Lactobacilli as well as two clusters within the Bifidobacteria and Bacteroides.CONCLUSIONS:We demonstrate that phenotypic differentiation within closely related species could be explained by their metabolic repertoire rather than their phylogenetic relationships. These results have important implications in our understanding of the ecological and evolutionary complexity of the human gastrointestinal microbiome.

Project Goals: There are an increasing number of automatically reconstructed genome scale metabolic models available for various organisms from databases, such as KBase; however, these models require further microbe specific refinement. The refinement process is time-consuming and laborious. This project introduces a pipeline that reduces many errors that are associated with automatic reconstructions. The reconstructions are modified to include correct reaction directionalities and to allow feasible ATP production. Further refinement focuses on manual curation of the models against current available knowledge. It involves extensive literature search for carbon sources and fermentation products, and comparative genomic approach for central metabolism, respiration, and amino acid biosynthesis pathways. The inclusion of these pathways increases the predictive power of the models. High quality metabolic models can be then applied to genetic engineering of specific microbes to increase the yield or degradation of compound of interest, or investigate microbe-microbe relationships in complex microbial communities.

Genome-scale metabolic models derived from human gut metagenomic data can be used as a framework to elucidate how microbial communities modulate human metabolism and health. We present AGORA (assembly of gut organisms through reconstruction and analysis), a resource of genome-scale metabolic reconstructions semi-automatically generated for 773 human gut bacteria. Using this resource, we identified a defined growth medium for Bacteroides caccae ATCC 34185. We also showed that interactions among modeled species depend on both the metabolic potential of each species and the nutrients available. AGORA reconstructions can integrate either metagenomic or 16S rRNA sequencing data sets to infer the metabolic diversity of microbial communities. AGORA reconstructions could provide a starting point for the generation of high-quality, manually curated metabolic reconstructions. AGORA is fully compatible with Recon 2, a comprehensive metabolic reconstruction of human metabolism, which will facilitate studies of host-microbiome interactions.

While the gut microbiota of termites and its role in symbiotic digestion have been studied for decades, little is known about the bacteria colonizing the intestinal tract of the distantly related wood-feeding cockroaches (Blaberidae: Panesthiinae). Here, we show that physicochemical gut conditions and microbial fermentation products in the gut of Panesthia angustipennis resemble that of other cockroaches. Microsensor measurements confirmed that all gut compartments were anoxic at the center and had a slightly acidic to neutral pH and a negative redox potential. While acetate dominated in all compartments, lactate and hydrogen accumulated only in the crop. The high, hydrogen-limited rates of methane emission from living cockroaches were in agreement with the restriction of F420-fluorescent methanogens to the hindgut. The gut microbiota of both P. angustipennis and Salganea esakii differed strongly between compartments, with the highest density and diversity in the hindgut, but similarities between homologous compartments of both cockroaches indicated a specificity of the microbiota for their respective habitats. While some lineages were most closely related to the gut microbiota of omnivorous cockroaches and wood- or litter-feeding termites, others have been encountered also in vertebrates, reinforcing the hypothesis that strong environmental selection drives community structure in the cockroach gut.

Mol Syst Biol. (2015) 11: 830 In their Correspondence entitled, “Do genome‐scale models need exact solvers or clearer standards?”, Ebrahim et al (2015) suggest an unnecessary dichotomy. They discuss the findings of our paper, “An exact arithmetic toolbox for a consistent and reproducible structural analysis of metabolic network models” (Chindelevitch et al , 2014), and suggest that our work highlights the need for better model encoding standards. Moreover, the authors dispute our claims that multiple previously published metabolic network models are unable to produce growth when analyzed with an exact arithmetic approach. They attribute discrepancies between their findings and ours solely to a misinterpretation of the formatting conventions used to encode these models. The authors conclude that genome‐scale metabolic network models need better standards, rather than the improvements in accuracy obtained with exact arithmetic. We argue here that improved standards and exact arithmetic are complementary advances that both benefit this field. Thus, the answer to the question posed by Ebrahim et al (2015) is “both.” In this response, we acknowledge the discrepancies in model interpretation between our approach and that of Ebrahim et al (2015), but maintain the key conclusions of our original study. Namely, a number of published metabolic network models are unable to exhibit growth even when our interpretation of these models is identical to that of Ebrahim et al (2015). We attribute the remaining differences between the results of our original study and their study to significant changes made to the models since our results were initially published. Indeed, our MONGOOSE tool provides a model verification platform, which will continue to be useful in identifying errors in model functionality, helping curators to fix them. Additionally, we demonstrate on a specific real‐model example that exact arithmetic can change the results of the analysis of genome‐scale metabolic network models. We conclude that exact arithmetic remains …

Like many animals, firebugs (Hemiptera, Pyrrhocoridae) rely on behavioural adaptations to successfully endow their offspring with microbial mutualists. To transmit the nutritionally beneficial Coriobacteriaceae symbionts, female firebugs smear egg surfaces with symbiont-containing faecal droplets that are subsequently ingested by newly hatched nymphs through active probing to initiate infection. Alternatively, the symbionts can be acquired horizontally through contact with faeces of infected conspecifics. Here, we report that these adaptations ensuring successful transmission of bacterial symbionts among firebugs are exploited by the specialized trypanosomatid parasite Leptomonas pyrrhocoris. Using comparative transcriptomics, fluorescence in situ hybridization (FISH) and controlled bioassays, we demonstrate that the transmission cycle of L. pyrrhocoris mirrors that of the bacterial mutualists, with high efficiency for both vertical and horizontal transmission. This indicates that the parasite capitalizes on pre-existing behavioural adaptations (egg smearing and probing) to facilitate its own transfer within host populations, adaptations that likely evolved to initiate and maintain an association with beneficial gut symbionts. Thus, the transmission of mutualistic microbes across host generations can entail a significant risk of co-transmitting pathogens or parasites, thereby exerting selective pressures on the host to evolve more specific mechanisms of transfer.

Benzoxazinoids are chemical defenses against herbivores and are produced by many members of the grass family. These compounds are stored as stable glucosides in plant cells and require the activity of glucosidases to release the corresponding toxic aglucones. In maize leaves, the most abundant benzoxazinoid is (2R)-DIMBOA-Glc, which is converted into the toxic DIMBOA upon herbivory. The ways in which three Spodoptera species metabolize this toxin were investigated. (2S)-DIMBOA-Glc, an epimer of the initial plant compound, was observed in the insect frass, and the associated glucosyltransferase activity was detected in the insect gut tissue. The epimeric glucoside produced by the insect was found to be no longer reactive towards plant glucosidases and thus cannot be converted into a toxin. Stereoselective reglucosylation thus represents a detoxification strategy in Spodoptera species that might help to explain their success as agricultural pests on benzoxazinoid-containing crops.