Natural selection for operons depends on genome size

Emerging trends in genomic and epigenomic regulation of plant specialised metabolism

Regulation of specialised metabolism genes is multilayered and complex, influenced by an array of genomic, epigenetic and epigenomic mechanisms. Here, we review the most recent knowledge in this field, drawing from discoveries in several plant species. Our aim is to improve understanding of how plant genome structure and function influence specialised metabolism. We also highlight key areas for future exploration. Gene regulatory mechanisms influencing specialised metabolism include gene duplication and neo-functionalization, conservation of operon-like clusters of specialised metabolism genes, local chromatin modifications, and the organisation of higher order chromatin structures within the nucleus. Genomic and epigenomic research to-date in the discipline have focused on a relatively small number of plant species, primarily at whole organ or tissue level. This is largely due to the technical demands of the experimental methods needed. However, a high degree of cell-type specificity of function exists in specialised metabolism, driven by similarly specific gene regulation. In this review we focus on the genomic characteristics of genes that are found in different types of clusters within the genome. We propose that acquisition of cell-resolution epigenomic datasets in emerging models, such as the glandular trichomes of Cannabis sativa, will yield important advances. Data such as chromatin accessibility and histone modification profiles can pinpoint which regulatory sequences are active in individual cell types and at specific times in development. These could provide fundamental biological insight as well as novel targets for genetic engineering and crop improvement.

OUP accepted manuscript

Operons are a hallmark of the genomic and regulatory architecture of prokaryotes. However, the mechanism by which two genes placed far apart gradually come close and form operons remains to be elucidated. Here, we propose a new model of the origin of operons: Mobile genetic elements called insertion sequences can facilitate the formation of operons by consecutive insertion–deletion–excision reactions. This mechanism barely leaves traces of insertion sequences and thus difficult to detect in nature. In this study, as a proof-of-concept, we reproducibly demonstrated operon formation in the laboratory. The insertion sequence IS3 and the insertion sequence excision enhancer are genes found in a broad range of bacterial species. We introduced these genes into insertion sequence-less Escherichia coli and found that, supporting our hypothesis, the activity of the two genes altered the expression of genes surrounding IS3, closed a 2.7 kb gap between a pair of genes, and formed new operons. This study shows how insertion sequences can facilitate the rapid formation of operons through locally increasing the structural mutation rates and highlights how coevolution with mobile elements may shape the organization of prokaryotic genomes and gene regulation.

Prediction and analysis of metagenomic operons via MetaRon: a pipeline for prediction of Metagenome and whole-genome opeRons

Background

Efficient regulation of bacterial genes in response to the environmental stimulus results in unique gene clusters known as operons. Lack of complete operonic reference and functional information makes the prediction of metagenomic operons a challenging task; thus, opening new perspectives on the interpretation of the host-microbe interactions.

Results

In this work, we identified whole-genome and metagenomic operons via MetaRon (Metagenome and whole-genome opeRon prediction pipeline). MetaRon identifies operons without any experimental or functional information. MetaRon was implemented on datasets with different levels of complexity and information. Starting from its application on whole-genome to simulated mixture of three whole-genomes (E. coli MG1655, Mycobacterium tuberculosis H37Rv and Bacillus subtilis str. 16), E. coli c20 draft genome extracted from chicken gut and finally on 145 whole-metagenome data samples from human gut. MetaRon consistently achieved high operon prediction sensitivity, specificity and accuracy across E. coli whole-genome (97.8, 94.1 and 92.4%), simulated genome (93.7, 75.5 and 88.1%) and E. coli c20 (87, 91 and 88%,), respectively. Finally, we identified 1,232,407 unique operons from 145 paired-end human gut metagenome samples. We also report strong association of type 2 diabetes with Maltose phosphorylase (K00691), 3-deoxy-D-glycero-D-galacto-nononate 9-phosphate synthase (K21279) and an uncharacterized protein (K07101).

Conclusion

With MetaRon, we were able to remove two notable limitations of existing whole-genome operon prediction methods: (1) generalizability (ability to predict operons in unrelated bacterial genomes), and (2) whole-genome and metagenomic data management. We also demonstrate the use of operons as a subset to represent the trends of secondary metabolites in whole-metagenome data and the role of secondary metabolites in the occurrence of disease condition. Using operonic data from metagenome to study secondary metabolic trends will significantly reduce the data volume to more precise data. Furthermore, the identification of metabolic pathways associated with the occurrence of type 2 diabetes (T2D) also presents another dimension of analyzing the human gut metagenome. Presumably, this study is the first organized effort to predict metagenomic operons and perform a detailed analysis in association with a disease, in this case type 2 diabetes. The application of MetaRon to metagenomic data at diverse scale will be beneficial to understand the gene regulation and therapeutic metagenomics.

Computational operon prediction in whole-genomes and metagenomes

Microbial diversity in unique environmental settings enables abrupt responses catalysed by altering the gene regulation and formation of gene clusters called operons. Operons increases bacterial adaptability, which in turn increases their survival. This review article presents the emergence of computational operon prediction methods for whole microbial genomes and metagenomes, and discusses their strengths and limitations. Most of the whole-genome operon prediction methods struggle to generalize on unrelated genomes. The applicability of universal whole-genome operon prediction methods to metagenomic data is an interesting yet less investigated question. We have evaluated the potential of various operon prediction features for genomic and metagenomic data. Most of operon prediction methods with high accuracy have been compiled into databases. Despite of the high predictive performance, the data among many databases are not completely consistent for similar species. We performed a correlation analysis between the computationally predicted operon databases and experimentally validated data for Escherichia coli, Bacillus subtilis and Mycobacterium tuberculosis. Operon prediction for most of the less characterized microbes cannot be verified due to absence of experimentally validated operons. The generation of validated information for other microbes would test the authenticity of operon databases for other less annotated microbes as well. Advances in sequencing technologies and development of better analysis methods will help researchers to overcome the technological hurdles (such as long sequencing reads and improved contig size) and further improve operon predictions and better utilize operonic information.

Gene Turnover Contributes to the Evolutionary Adaptation of Acidithiobacillus caldus: Insights from Comparative Genomics

Acidithiobacillus caldus is an extremely acidophilic sulfur-oxidizer with specialized characteristics, such as tolerance to low pH and heavy metal resistance. To gain novel insights into its genetic complexity, we chosen six A. caldus strains for comparative survey. All strains analyzed in this study differ in geographic origins as well as in ecological preferences. Based on phylogenomic analysis, we clustered the six A. caldus strains isolated from various ecological niches into two groups: group 1 strains with smaller genomes and group 2 strains with larger genomes. We found no obvious intraspecific divergence with respect to predicted genes that are related to central metabolism and stress management strategies between these two groups. Although numerous highly homogeneous genes were observed, high genetic diversity was also detected. Preliminary inspection provided a first glimpse of the potential correlation between intraspecific diversity at the genome level and environmental variation, especially geochemical conditions. Evolutionary genetic analyses further showed evidence that the difference in environmental conditions might be a crucial factor to drive the divergent evolution of A. caldus species. We identified a diverse pool of mobile genetic elements including insertion sequences and genomic islands, which suggests a high frequency of genetic exchange in these harsh habitats. Comprehensive analysis revealed that gene gains and losses were both dominant evolutionary forces that directed the genomic diversification of A. caldus species. For instance, horizontal gene transfer and gene duplication events in group 2 strains might contribute to an increase in microbial DNA content and novel functions. Moreover, genomes undergo extensive changes in group 1 strains such as removal of potential non-functional DNA, which results in the formation of compact and streamlined genomes. Taken together, the findings presented herein show highly frequent gene turnover of A. caldus species that inhabit extremely acidic environments, and shed new light on the contribution of gene turnover to the evolutionary adaptation of acidophiles.

Theory of prokaryotic genome evolution

Bacteria and archaea typically possess small genomes that are tightly packed with protein-coding genes. The compactness of prokaryotic genomes is commonly perceived as evidence of adaptive genome streamlining caused by strong purifying selection in large microbial populations. In such populations, even the small cost incurred by nonfunctional DNA because of extra energy and time expenditure is thought to be sufficient for this extra genetic material to be eliminated by selection. However, contrary to the predictions of this model, there exists a consistent, positive correlation between the strength of selection at the protein sequence level, measured as the ratio of nonsynonymous to synonymous substitution rates, and microbial genome size. Here, by fitting the genome size distributions in multiple groups of prokaryotes to predictions of mathematical models of population evolution, we show that only models in which acquisition of additional genes is, on average, slightly beneficial yield a good fit to genomic data. These results suggest that the number of genes in prokaryotic genomes reflects the equilibrium between the benefit of additional genes that diminishes as the genome grows and deletion bias (i.e., the rate of deletion of genetic material being slightly greater than the rate of acquisition). Thus, new genes acquired by microbial genomes, on average, appear to be adaptive. The tight spacing of protein-coding genes likely results from a combination of the deletion bias and purifying selection that efficiently eliminates nonfunctional, noncoding sequences.

Comparative Genomics of the Extreme Acidophile Acidithiobacillus thiooxidans Reveals Intraspecific Divergence and Niche Adaptation

Acidithiobacillus thiooxidans known for its ubiquity in diverse acidic and sulfur-bearing environments worldwide was used as the research subject in this study. To explore the genomic fluidity and intraspecific diversity of Acidithiobacillus thiooxidans (A. thiooxidans) species, comparative genomics based on nine draft genomes was performed. Phylogenomic scrutiny provided first insights into the multiple groupings of these strains, suggesting that genetic diversity might be potentially correlated with their geographic distribution as well as geochemical conditions. While these strains shared a large number of common genes, they displayed differences in gene content. Functional assignment indicated that the core genome was essential for microbial basic activities such as energy acquisition and uptake of nutrients, whereas the accessory genome was thought to be involved in niche adaptation. Comprehensive analysis of their predicted central metabolism revealed that few differences were observed among these strains. Further analyses showed evidences of relevance between environmental conditions and genomic diversification. Furthermore, a diverse pool of mobile genetic elements including insertion sequences and genomic islands in all A. thiooxidans strains probably demonstrated the frequent genetic flow (such as lateral gene transfer) in the extremely acidic environments. From another perspective, these elements might endow A. thiooxidans species with capacities to withstand the chemical constraints of their natural habitats. Taken together, our findings bring some valuable data to better understand the genomic diversity and econiche adaptation within A. thiooxidans strains.

A Minimal Model of Ribosome Allocation Dynamics Captures Trade-offs in Expression between Endogenous and Synthetic Genes

Cells contain a finite set of resources that must be distributed across many processes to ensure survival. Among them, the largest proportion of cellular resources is dedicated to protein translation. Synthetic biology often exploits these resources in executing orthogonal genetic circuits, yet the burden this places on the cell is rarely considered. Here, we develop a minimal model of ribosome allocation dynamics capturing the demands on translation when expressing a synthetic construct together with endogenous genes required for the maintenance of cell physiology. Critically, it contains three key variables related to design parameters of the synthetic construct covering transcript abundance, translation initiation rate, and elongation time. We show that model-predicted changes in ribosome allocation closely match experimental shifts in synthetic protein expression rate and cellular growth. Intriguingly, the model is also able to accurately infer transcript levels and translation times after further exposure to additional ambient stress. Our results demonstrate that a simple model of resource allocation faithfully captures the redistribution of protein synthesis resources when faced with the burden of synthetic gene expression and environmental stress. The tractable nature of the model makes it a versatile tool for exploring the guiding principles of efficient heterologous expression and the indirect interactions that can arise between synthetic circuits and their host chassis because of competition for shared translational resources.

Investigating Evolutionary Dynamics of RHA1 Operons

Grouping genes as operons is an important genomic feature of prokaryotic organisms. The comprehensive understanding of the operon organizations would be helpful to decipher transcriptional mechanisms, cellular pathways, and the evolutionary landscape of prokaryotic genomes. Although thousands of prokaryotes have been sequenced, genome-wide investigation of the evolutionary dynamics (division and recombination) of operons among these genomes remains unexplored. Here, we systematically analyzed the operon dynamics of Rhodococcus jostii RHA1 (RHA1), an oleaginous bacterium with high potential applications in biofuel, by comparing 340 prokaryotic genomes that were carefully selected from different genera. Interestingly, 99% of RHA1 operons were observed to exhibit evolutionary events of division and recombination among the 340 compared genomes. An operon that encodes all enzymes related to histidine biosynthesis in RHA1 (His-operon) was found to be segmented into smaller gene groups (sub-operons) in diverse genomes. These sub-operons were further reorganized with different functional genes as novel operons that are related to different biochemical processes. Comparatively, the operons involved in the functional categories of lipid transport and metabolism are relatively conserved among the 340 compared genomes. At the pathway level, RHA1 operons found to be significantly conserved were involved in ribosome synthesis, oxidative phosphorylation, and fatty acid synthesis. These analyses provide evolutionary insights of operon organization and the dynamic associations of various biochemical pathways in different prokaryotes.

The Chthonomonas calidirosea Genome Is Highly Conserved across Geographic Locations and Distinct Chemical and Microbial Environments in New Zealand's Taupō Volcanic Zone

Chthonomonas calidirosea T49^T is a low-abundance, carbohydrate-scavenging, and thermophilic soil bacterium with a seemingly disorganized genome. We hypothesized that the C. calidirosea genome would be highly responsive to local selection pressure, resulting in the divergence of its genomic content, genome organization, and carbohydrate utilization phenotype across environments. We tested this hypothesis by sequencing the genomes of four C. calidirosea isolates obtained from four separate geothermal fields in the Taupō Volcanic Zone, New Zealand. For each isolation site, we measured physicochemical attributes and defined the associated microbial community by 16S rRNA gene sequencing. Despite their ecological and geographical isolation, the genome sequences showed low divergence (maximum, 1.17%). Isolate-specific variations included single-nucleotide polymorphisms (SNPs), restriction-modification systems, and mobile elements but few major deletions and no major rearrangements. The 50-fold variation in C. calidirosea relative abundance among the four sites correlated with site environmental characteristics but not with differences in genomic content. Conversely, the carbohydrate utilization profiles of the C. calidirosea isolates corresponded to the inferred isolate phylogenies, which only partially paralleled the geographical relationships among the sample sites. Genomic sequence conservation does not entirely parallel geographic distance, suggesting that stochastic dispersal and localized extinction, which allow for rapid population homogenization with little restriction by geographical barriers, are possible mechanisms of C. calidirosea distribution. This dispersal and extinction mechanism is likely not limited to C. calidirosea but may shape the populations and genomes of many other low-abundance free-living taxa.

IMPORTANCE This study compares the genomic sequence variations and metabolisms of four strains of Chthonomonas calidirosea, a rare thermophilic bacterium from the phylum Armatimonadetes. It additionally compares the microbial communities and chemistry of each of the geographically distinct sites from which the four C. calidirosea strains were isolated. C. calidirosea was previously reported to possess a highly disorganized genome, but it was unclear whether this reflected rapid evolution. Here, we show that each isolation site has a distinct chemistry and microbial community, but despite this, the C. calidirosea genome is highly conserved across all isolation sites. Furthermore, genomic sequence differences only partially paralleled geographic distance, suggesting that C. calidirosea genotypes are not primarily determined by adaptive evolution. Instead, the presence of C. calidirosea may be driven by stochastic dispersal and localized extinction. This ecological mechanism may apply to many other low-abundance taxa.

Coevolution of the Organization and Structure of Prokaryotic Genomes

The cytoplasm of prokaryotes contains many molecular machines interacting directly with the chromosome. These vital interactions depend on the chromosome structure, as a molecule, and on the genome organization, as a unit of genetic information. Strong selection for the organization of the genetic elements implicated in these interactions drives replicon ploidy, gene distribution, operon conservation, and the formation of replication-associated traits. The genomes of prokaryotes are also very plastic with high rates of horizontal gene transfer and gene loss. The evolutionary conflicts between plasticity and organization lead to the formation of regions with high genetic diversity whose impact on chromosome structure is poorly understood. Prokaryotic genomes are remarkable documents of natural history because they carry the imprint of all of these selective and mutational forces. Their study allows a better understanding of molecular mechanisms, their impact on microbial evolution, and how they can be tinkered in synthetic biology.

Putative bacterial interactions from metagenomic knowledge with an integrative systems ecology approach

Following the trend of studies that investigate microbial ecosystems using different metagenomic techniques, we propose a new integrative systems ecology approach that aims to decipher functional roles within a consortium through the integration of genomic and metabolic knowledge at genome scale. For the sake of application, using public genomes of five bacterial strains involved in copper bioleaching: Acidiphilium cryptum, Acidithiobacillus ferrooxidans, Acidithiobacillus thiooxidans, Leptospirillum ferriphilum, and Sulfobacillus thermosulfidooxidans, we first reconstructed a global metabolic network. Next, using a parsimony assumption, we deciphered sets of genes, called Sets from Genome Segments (SGS), that (1) are close on their respective genomes, (2) take an active part in metabolic pathways and (3) whose associated metabolic reactions are also closely connected within metabolic networks. Overall, this SGS paradigm depicts genomic functional units that emphasize respective roles of bacterial strains to catalyze metabolic pathways and environmental processes. Our analysis suggested that only few functional metabolic genes are horizontally transferred within the consortium and that no single bacterial strain can accomplish by itself the whole copper bioleaching. The use of SGS pinpoints a functional compartmentalization among the investigated species and exhibits putative bacterial interactions necessary for promoting these pathways.

A new genome of Acidithiobacillus thiooxidans provides insights into adaptation to a bioleaching environment

Acidithiobacillus thiooxidans is a sulfur oxidizing acidophilic bacterium found in many sulfur-rich environments. It is particularly interesting due to its role in bioleaching of sulphide minerals. In this work, we report the genome sequence of At. thiooxidans Licanantay, the first strain from a copper mine to be sequenced and currently used in bioleaching industrial processes. Through comparative genomic analysis with two other At. thiooxidans non-metal mining strains (ATCC 19377 and A01) we determined that these strains share a large core genome of 2109 coding sequences and a high average nucleotide identity over 98%. Nevertheless, the presence of 841 strain-specific genes (absent in other At. thiooxidans strains) suggests a particular adaptation of Licanantay to its specific biomining environment. Among this group, we highlight genes encoding for proteins involved in heavy metal tolerance, mineral cell attachment and cysteine biosynthesis. Several of these genes were located near genetic motility genes (e.g. transposases and integrases) in genomic regions of over 10 kbp absent in the other strains, suggesting the presence of genomic islands in the Licanantay genome probably produced by horizontal gene transfer in mining environments.