Patterns of indirect protein interactions suggest a spatial organization to metabolism

Spatial chromosome organization and adaptation of the radiation-resistant extremophile Deinococcus radiodurans

Radiation-resistant Deinococcus radiodurans is an extremophilic microorganism capable of withstanding high levels of ionizing radiation and chemical mutagens. It possesses remarkable DNA repair capability and serves as a model organism for studying stress resistance mechanism. However, our understanding on the spatial chromosome organization of this species remains limited. In this study, we employed chromosome conformation capture (3C) technology to determine the 3D genome structure of D. radiodurans and to further investigate the changes of chromosome conformation induced by ultraviolet (UV) irradiation. We observed that UV irradiation reduced short-range chromosome interactions, and smaller chromosomal interaction domains (CIDs) merged to form larger CIDs. Integrating transcriptomic data analysis, we found that the majority of upregulated differentially expressed genes were significantly enriched near specific CID boundaries. Specially, we comprehensively elucidated that the nucleoid-associated protein DrEbfC as a global regulatory factor for gene expression, may modulate the efficiency of relevant metabolic pathways by altering the local chromosome structure, thereby influencing the physiological state of the bacterium. Overall, our study revealed the chromosome conformations of D. radiodurans under different conditions, and offered valuable insights into the molecular response mechanism of this extremophile to survival stresses.

Unravelling Rubber Tree Growth by Integrating GWAS and Biological Network-Based Approaches

Hevea brasiliensis (rubber tree) is a large tree species of the Euphorbiaceae family with inestimable economic importance. Rubber tree breeding programs currently aim to improve growth and production, and the use of early genotype selection technologies can accelerate such processes, mainly with the incorporation of genomic tools, such as marker-assisted selection (MAS). However, few quantitative trait loci (QTLs) have been used successfully in MAS for complex characteristics. Recent research shows the efficiency of genome-wide association studies (GWAS) for locating QTL regions in different populations. In this way, the integration of GWAS, RNA-sequencing (RNA-Seq) methodologies, coexpression networks and enzyme networks can provide a better understanding of the molecular relationships involved in the definition of the phenotypes of interest, supplying research support for the development of appropriate genomic based strategies for breeding. In this context, this work presents the potential of using combined multiomics to decipher the mechanisms of genotype and phenotype associations involved in the growth of rubber trees. Using GWAS from a genotyping-by-sequencing (GBS) Hevea population, we were able to identify molecular markers in QTL regions with a main effect on rubber tree plant growth under constant water stress. The underlying genes were evaluated and incorporated into a gene coexpression network modelled with an assembled RNA-Seq-based transcriptome of the species, where novel gene relationships were estimated and evaluated through in silico methodologies, including an estimated enzymatic network. From all these analyses, we were able to estimate not only the main genes involved in defining the phenotype but also the interactions between a core of genes related to rubber tree growth at the transcriptional and translational levels. This work was the first to integrate multiomics analysis into the in-depth investigation of rubber tree plant growth, producing useful data for future genetic studies in the species and enhancing the efficiency of the species improvement programs.

The contributions from the progenitor genomes of the mesopolyploid Brassiceae are evolutionarily distinct but functionally compatible

The members of the tribe Brassiceae share a whole-genome triplication (WGT), and one proposed model for its formation is a two-step pair of hybridizations producing hexaploid descendants. However, evidence for this model is incomplete, and the evolutionary and functional constraints that drove evolution after the hexaploidy are even less understood. Here, we report a new genome sequence of Crambe hispanica, a species sister to most sequenced Brassiceae. Using this new genome and three others that share the hexaploidy, we traced the history of gene loss after the WGT using the Polyploidy Orthology Inference Tool (POInT). We confirm the two-step formation model and infer that there was a significant temporal gap between those two allopolyploidizations, with about a third of the gene losses from the first two subgenomes occurring before the arrival of the third. We also, for the 90,000 individual genes in our study, make parental subgenome assignments, inferring, with measured uncertainty, from which of the progenitor genomes of the allohexaploidy each gene derives. We further show that each subgenome has a statistically distinguishable rate of homoeolog losses. There is little indication of functional distinction between the three subgenomes: the individual subgenomes show no patterns of functional enrichment, no excess of shared protein-protein or metabolic interactions between their members, and no biases in their likelihood of having experienced a recent selective sweep. We propose a "mix and match" model of allopolyploidy, in which subgenome origin drives homoeolog loss propensities but where genes from different subgenomes function together without difficulty.

Poor feed efficiency in sheep is associated with several structural abnormalities in the community metabolic network of their ruminal microbes

Ruminant animals have a symbiotic relationship with the microorganisms in their rumens. In this relationship, rumen microbes efficiently degrade complex plant-derived compounds into smaller digestible compounds, a process that is very likely associated with host animal feed efficiency. The resulting simpler metabolites can then be absorbed by the host and converted into other compounds by host enzymes. We used a microbial community metabolic network inferred from shotgun metagenomics data to assess how this metabolic system differs between animals that are able to turn ingested feedstuffs into body mass with high efficiency and those that are not. We conducted shotgun sequencing of microbial DNA from the rumen contents of 16 sheep that differed in their residual feed intake (RFI), a measure of feed efficiency. Metagenomic reads from each sheep were mapped onto a database-derived microbial metabolic network, which was linked to the sheep metabolic network by interface metabolites (metabolites transferred from microbes to host). No single enzyme was identified as being significantly different in abundance between the low and high RFI animals (P > 0.05, Wilcoxon test). However, when we analyzed the metabolic network as a whole, we found several differences between efficient and inefficient animals. Microbes from low RFI (efficient) animals use a suite of enzymes closer in network space to the host's reactions than those of the high RFI (inefficient) animals. Similarly, low RFI animals have microbial metabolic networks that, on average, contain reactions using shorter carbon chains than do those of high RFI animals, potentially allowing the host animals to extract metabolites more efficiently. Finally, the efficient animals possess community networks with greater Shannon diversity among their enzymes than do inefficient ones. Thus, our system approach to the ruminal microbiome identified differences attributable to feed efficiency in the structure of the microbes' community metabolic network that were undetected at the level of individual microbial taxa or reactions.

Cytoplasmic Localization of Sulfide:Quinone Oxidoreductase and Persulfide Dioxygenase of Cupriavidus pinatubonensis JMP134

Heterotrophic bacteria have recently been reported to oxidize sulfide to sulfite and thiosulfate by using sulfide:quinone oxidoreductase (SQR) and persulfide dioxygenase (PDO). In chemolithotrophic bacteria, both SQR and PDO have been reported to function in the periplasmic space, with SQR as a peripheral membrane protein whose C terminus inserts into the cytoplasmic membrane and PDO as a soluble protein. Cupriavidus pinatubonensis JMP134, best known for its ability to degrade 2,4-dichlorophenoxyacetic acid and other aromatic pollutants, has a gene cluster of sqr and pdo encoding C. pinatubonensis SQR (CpSQR) and CpPDO2. When cloned in Escherichia coli, the enzymes are functional. Here we investigated whether they function in the periplasmic space or in the cytoplasm in heterotrophic bacteria. By using sequence analysis, biochemical detection, and green fluorescent protein (GFP)/PhoA fusion proteins, we found that CpSQR was located on the cytoplasmic side of the membrane and CpPDO2 was a soluble protein in the cytoplasm with a tendency to be peripherally located near the membrane. The location proximity of these proteins near the membrane in the cytoplasm may facilitate sulfide oxidation in heterotrophic bacteria. The information may guide the use of heterotrophic bacteria in bioremediation of organic pollutants as well as H₂S.IMPORTANCE Sulfide (H₂S, HS^-, and S^2-), which is common in natural gas and wastewater, causes a serious malodor at low levels and is deadly at high levels. Microbial oxidation of sulfide is a valid bioremediation method, in which chemolithotrophic bacteria that use sulfide as the energy source are often used to remove sulfide. Heterotrophic bacteria with SQR and PDO have recently been reported to oxidize sulfide to sulfite and thiosulfate. Cupriavidus pinatubonensis JMP134 has been extensively characterized for its ability to degrade organic pollutants, and it also contains SQR and PDO. This paper shows the localization of SQR and PDO inside the cytoplasm in the vicinity of the membrane. The information may provide guidance for using heterotrophic bacteria in sulfide bioremediation.

Diet shifts provoke complex and variable changes in the metabolic networks of the ruminal microbiome

BACKGROUND

Grazing mammals rely on their ruminal microbial symbionts to convert plant structural biomass into metabolites they can assimilate. To explore how this complex metabolic system adapts to the host animal's diet, we inferred a microbiome-level metabolic network from shotgun metagenomic data.

RESULTS

Using comparative genomics, we then linked this microbial network to that of the host animal using a set of interface metabolites likely to be transferred to the host. When the host sheep were fed a grain-based diet, the induced microbial metabolic network showed several critical differences from those seen on the evolved forage-based diet. Grain-based (e.g., concentrate) diets tend to be dominated by a smaller set of reactions that employ metabolites that are nearer in network space to the host's metabolism. In addition, these reactions are more central in the network and employ substrates with shorter carbon backbones. Despite this apparent lower complexity, the concentrate-associated metabolic networks are actually more dissimilar from each other than are those of forage-fed animals. Because both groups of animals were initially fed on a forage diet, we propose that the diet switch drove the appearance of a number of different microbial networks, including a degenerate network characterized by an inefficient use of dietary nutrients. We used network simulations to show that such disparate networks are not an unexpected result of a diet shift.

CONCLUSION

We argue that network approaches, particularly those that link the microbial network with that of the host, illuminate aspects of the structure of the microbiome not seen from a strictly taxonomic perspective. In particular, different diets induce predictable and significant differences in the enzymes used by the microbiome. Nonetheless, there are clearly a number of microbiomes of differing structure that show similar functional properties. Changes such as a diet shift uncover more of this type of diversity.

Biomedical and Catalytic Opportunities of Virus-Like Particles in Nanotechnology

Within biology, molecules are arranged in hierarchical structures that coordinate and control the many processes that allow for complex organisms to exist. Proteins and other functional macromolecules are often studied outside their natural nanostructural context because it remains difficult to create controlled arrangements of proteins at this size scale. Viruses are elegantly simple nanosystems that exist at the interface of living organisms and nonliving biological machines. Studied and viewed primarily as pathogens to be combatted, viruses have emerged as models of structural efficiency at the nanoscale and have spurred the development of biomimetic nanoparticle systems. Virus-like particles (VLPs) are noninfectious protein cages derived from viruses or other cage-forming systems. VLPs provide incredibly regular scaffolds for building at the nanoscale. Composed of self-assembling protein subunits, VLPs provide both a model for studying materials' assembly at the nanoscale and useful building blocks for materials design. The robustness and degree of understanding of many VLP structures allow for the ready use of these systems as versatile nanoparticle platforms for the conjugation of active molecules or as scaffolds for the structural organization of chemical processes. Lastly the prevalence of viruses in all domains of life has led to unique activities of VLPs in biological systems most notably the immune system. Here we discuss recent efforts to apply VLPs in a wide variety of applications with the aim of highlighting how the common structural elements of VLPs have led to their emergence as paradigms for the understanding and design of biological nanomaterials.

Robust Yet Fragile: Expression Noise, Protein Misfolding, and Gene Dosage in the Evolution of Genomes

The complex manner in which organisms respond to changes in their gene dosage has long fascinated geneticists. Oddly, although the existence of dominance implies that dosage reductions often have mild phenotypes, extra copies of whole chromosomes (aneuploidy) are generally strongly deleterious. Even more paradoxically, an extra copy of the genome is better tolerated than is aneuploidy. We review the resolution of this paradox, highlighting the roles of biochemistry, protein aggregation, and disruption of cellular microstructure in that explanation. Returning to life's curious combination of robustness and sensitivity to dosage changes, we argue that understanding how biological robustness evolved makes these observations less inexplicable. We propose that noise in gene expression and evolutionary strategies for its suppression play a role in generating dosage phenotypes. Finally, we outline an unappreciated mechanism for the preservation of duplicate genes, namely preservation to limit expression noise, arguing that it is particularly relevant in polyploid organisms.

The players may change but the game remains: network analyses of ruminal microbiomes suggest taxonomic differences mask functional similarity

By mapping translated metagenomic reads to a microbial metabolic network, we show that ruminal ecosystems that are rather dissimilar in their taxonomy can be considerably more similar at the metabolic network level. Using a new network bi-partition approach for linking the microbial network to a bovine metabolic network, we observe that these ruminal metabolic networks exhibit properties consistent with distinct metabolic communities producing similar outputs from common inputs. For instance, the closer in network space that a microbial reaction is to a reaction found in the host, the lower will be the variability of its enzyme copy number across hosts. Similarly, these microbial enzymes that are nearby to host nodes are also higher in copy number than are more distant enzymes. Collectively, these results demonstrate a widely expected pattern that, to our knowledge, has not been explicitly demonstrated in microbial communities: namely that there can exist different community metabolic networks that have the same metabolic inputs and outputs but differ in their internal structure.

Comparative genomics as a time machine: how relative gene dosage and metabolic requirements shaped the time-dependent resolution of yeast polyploidy

Using a phylogenetic model of evolution after genome duplication (i.e., polyploidy) and 12 yeast genomes with a shared genome duplication, I show that the loss of duplicate genes after that duplication occurred in three phases. First, losses that occurred immediately after the event were biased toward genes functioning in DNA repair and organellar functions. Then, the main group of duplicate losses appear to have been shaped by a requirement to maintain balance in protein levels: There is a strong statistical association between the number of protein interactions a gene's product is involved in and its propensity to have remained in duplicate. Moreover, when duplicated genes with interactions were lost, it was more common than expected for both members of an interaction pair to have been lost on the same branch of the phylogeny. Finally, in the third phase of the resolution process, overretention of duplicated enzymes carrying high flux and of duplicated genes involved in transcriptional regulation became dominant. I speculate that initial retention of such genes by a requirement to maintain gene dosage set the stage for the later functional changes that then maintained these duplicates for long periods.

The yeast protein interaction network has a capacity for self-organization

The organization of the cellular interior gives rise to properties including metabolic channeling and micro-compartmentalization of signaling. Here, we use a lattice model of molecular crowding, together with literature-derived protein interactions and abundances, to describe the molecular organization and stoichiometry of local cellular regions, showing that physical protein-protein interactions induce emergent structures not seen when random interaction networks are modeled. Specifically, we find that the lattices give rise to micro-groups of enzymes on the surfaces of protein clusters. These arrangements of proteins are also robust to protein overexpression, while still showing evidence for expression tuning. Our results indicate that some of the complex organization of the cell may derive from simple rules of molecular aggregation and interaction.

Watching the grin fade: tracing the effects of polyploidy on different evolutionary time scales

Polyploidy, or whole-genome duplication (WGD), is a recurrent mutation both in cell lineages and over evolutionary time. By globally changing the relationship between gene copy number and other cellular entities, it can induce dramatic changes at the cellular and phenotypic level. Perhaps surprisingly, then, the insights that these events can bring to understanding other cellular features are not as well appreciated as they could be. In this review, we draw on examples of polyploidy from animals, plants and yeast to explore how investigations of polyploid cells have improved our understanding of the cell cycle, biological network complexity, metabolic phenotypes and tumor biology. We argue that the study of polyploidy across organisms, cell types, and time scales serves not only as a window into basic cell biology, but also as a basis for a predictive biology with applications ranging from crop improvement to treating cancer.

Compartmentation of GAPDH

The concept of the cytosol as a space that contains discrete zones of metabolites is discussed relative to the contribution of GAPDH. GAPDH is directed to very specific cell compartments. This chapter describes the utilization of GAPDH's enzymatic function for focal demands (i.e. ATP/ADP and NAD(+)/NADH), and offers a speculative role for GAPDH as perhaps moderating local concentrations of inorganic phosphate and hydrogen ions (i.e. co-substrate and co-product of the glycolytic reaction, respectively). Where known, the structural features of the binding between GAPDH and the compartment components are discussed. The nuances, which are associated with the intracellular distribution of GAPDH, appear to be specific to the cell-type, particularly with regards to the various plasma membrane proteins to which GAPDH binds. The chapter includes discussion on the curious observation of GAPDH being localized to the external surface of the plasma membrane in a human cell type. The default perspective has been that GAPDH localization is synonymous with compartmentation of glycolytic energy. The chapter discusses GAPDH translocation to the nucleus and to non-nuclear cellular structures, emphasizing its glycolytic function. Nevertheless, it is becoming clear that alternate functions of GAPDH play a role in compartmentation, particularly in the translocation to the nucleus.

Compartmentalization and metabolic channeling for multienzymatic biosynthesis: practical strategies and modeling approaches

: The construction of efficient enzyme complexes for multienzymatic biosynthesis is of increasing interest in order to achieve maximum yield and to minimize the interference due to shortcomings that are typical for straightforward one-pot multienzyme catalysis. These include product or intermediate feedback inhibition, degeneration, and diffusive losses of reaction intermediates, consumption of co-factors, and others. The main mechanisms in nature to tackle these effects in transient or stable protein associations are the formation of metabolic channeling and microcompartments, processes that are desirable also for multienzymatic biosynthesis in vitro. This chapter provides an overview over two main aspects. First, numerous recent strategies for establishing compartmentalized multienzyme associations and constructed synthetic enzyme complexes are reviewed. Second, the computational methods at hand to investigate and optimize such associations systematically, especially with focus on large multienzyme complexes and metabolic channeling, are discussed. Perspectives on future studies of multienzymatic biosynthesis concerning compartmentalization and metabolic channeling are presented.

Basic and applied uses of genome-scale metabolic network reconstructions of Escherichia coli

The genome-scale model (GEM) of metabolism in the bacterium Escherichia coli K-12 has been in development for over a decade and is now in wide use. GEM-enabled studies of E. coli have been primarily focused on six applications: (1) metabolic engineering, (2) model-driven discovery, (3) prediction of cellular phenotypes, (4) analysis of biological network properties, (5) studies of evolutionary processes, and (6) models of interspecies interactions. In this review, we provide an overview of these applications along with a critical assessment of their successes and limitations, and a perspective on likely future developments in the field. Taken together, the studies performed over the past decade have established a genome-scale mechanistic understanding of genotype-phenotype relationships in E. coli metabolism that forms the basis for similar efforts for other microbial species. Future challenges include the expansion of GEMs by integrating additional cellular processes beyond metabolism, the identification of key constraints based on emerging data types, and the development of computational methods able to handle such large-scale network models with sufficient accuracy.

The Escherichia coli peripheral inner membrane proteome

Biological membranes are essential for cell viability. Their functional characteristics strongly depend on their protein content, which consists of transmembrane (integral) and peripherally associated membrane proteins. Both integral and peripheral inner membrane proteins mediate a plethora of biological processes. Whereas transmembrane proteins have characteristic hydrophobic stretches and can be predicted using bioinformatics approaches, peripheral inner membrane proteins are hydrophilic, exist in equilibria with soluble pools, and carry no discernible membrane targeting signals. We experimentally determined the cytoplasmic peripheral inner membrane proteome of the model organism Escherichia coli using a multidisciplinary approach. Initially, we extensively re-annotated the theoretical proteome regarding subcellular localization using literature searches, manual curation, and multi-combinatorial bioinformatics searches of the available databases. Next we used sequential biochemical fractionations coupled to direct identification of individual proteins and protein complexes using high resolution mass spectrometry. We determined that the proposed cytoplasmic peripheral inner membrane proteome occupies a previously unsuspected ∼19% of the basic E. coli BL21(DE3) proteome, and the detected peripheral inner membrane proteome occupies ∼25% of the estimated expressed proteome of this cell grown in LB medium to mid-log phase. This value might increase when fleeting interactions, not studied here, are taken into account. Several proteins previously regarded as exclusively cytoplasmic bind membranes avidly. Many of these proteins are organized in functional or/and structural oligomeric complexes that bind to the membrane with multiple interactions. Identified proteins cover the full spectrum of biological activities, and more than half of them are essential. Our data suggest that the cytoplasmic proteome displays remarkably dynamic and extensive communication with biological membrane surfaces that we are only beginning to decipher.

Metabolic adaptation and protein complexes in prokaryotes

Protein complexes are classified and have been charted in several large-scale screening studies in prokaryotes. These complexes are organized in a factory-like fashion to optimize protein production and metabolism. Central components are conserved between different prokaryotes; major complexes involve carbohydrate, amino acid, fatty acid and nucleotide metabolism. Metabolic adaptation changes protein complexes according to environmental conditions. Protein modification depends on specific modifying enzymes. Proteins such as trigger enzymes display condition-dependent adaptation to different functions by participating in several complexes. Several bacterial pathogens adapt rapidly to intracellular survival with concomitant changes in protein complexes in central metabolism and optimize utilization of their favorite available nutrient source. Regulation optimizes protein costs. Master regulators lead to up- and downregulation in specific subnetworks and all involved complexes. Long protein half-life and low level expression detaches protein levels from gene expression levels. However, under optimal growth conditions, metabolite fluxes through central carbohydrate pathways correlate well with gene expression. In a system-wide view, major metabolic changes lead to rapid adaptation of complexes and feedback or feedforward regulation. Finally, prokaryotic enzyme complexes are involved in crowding and substrate channeling. This depends on detailed structural interactions and is verified for specific effects by experiments and simulations.

Polyploidy and the evolution of complex traits

We explore how whole-genome duplications (WGDs) may have given rise to complex innovations in cellular networks, innovations that could not have evolved through sequential single-gene duplications. We focus on two classical WGD events, one in bakers' yeast and the other at the base of vertebrates (i.e., two rounds of whole-genome duplication: 2R-WGD). Two complex adaptations are discussed in detail: aerobic ethanol fermentation in yeast and the rewiring of the vertebrate developmental regulatory network through the 2R-WGD. These two examples, derived from diverged branches on the eukaryotic tree, boldly underline the evolutionary potential of WGD in facilitating major evolutionary transitions. We close by arguing that the evolutionary importance of WGD may require updating certain aspects of modern evolutionary theory, perhaps helping to synthesize a new evolutionary systems biology.