Predicted highly expressed genes of diverse prokaryotic genomes

Carmna: classification and regression models for nitrogenase activity based on a pretrained large protein language model

Nitrogen-fixing microorganisms play a critical role in the global nitrogen cycle by converting atmospheric nitrogen into ammonia through the action of nitrogenase (EC 1.18.6.1). In this study, we employed six machine learning algorithms to model the classification and regression of nitrogenase activity (Carmna). Carmna utilized the pretrained large-scale model ProtT5 for feature extraction from nitrogenase sequences and incorporated additional features, such as gene expression and codon preference, for model training. The optimal classification model, based on XGBoost, achieved an average area under receiver operating characteristic curve of 0.9365 and an F1 score of 0.85 in five-fold cross-validation. For regression, the best-performing model was a stacking approach based on support vector regression, with an average R2 of 0.5572 and a mean absolute error of 0.3351. Further interpretability analysis of the optimal regression model revealed that not only the proportion and codon preferences of standard amino acids, but also the expression levels and spatial distance of nitrogenase genes were associated with nitrogenase activity. We also obtained the minimum nitrogen-fixing nif cluster. This study deepens our understanding of the complex mechanisms regulating nitrogenase activity and contributes to the development of efficient bio-fertilizers.

Impact of the chemical modification of tRNAs anticodon loop on the variability and evolution of codon usage in proteobacteria

Despite the highly conserved nature of the genetic code, the frequency of usage of each codon can vary significantly. The evolution of codon usage is shaped by two main evolutionary forces: mutational bias and selection pressures. These pressures can be driven by environmental factors, but also by the need for efficient translation, which depends heavily on the concentration of transfer RNAs (tRNAs) within the cell. The data presented here supports the proposal that tRNA modifications play a key role in shaping the overall preference of codon usage in proteobacteria. Interestingly, some codons, such as CGA and AGG (encoding arginine), exhibit a surprisingly low level of variation in their frequency of usage, even across genomes with differing GC content. These findings suggest that the evolution of GC content in proteobacterial genomes might be primarily driven by changes in the usage of a specific subset of codons, whose usage is itself influenced by tRNA modifications.

Kabirian-based optinalysis: A conceptually grounded framework for symmetry/asymmetry, similarity/dissimilarity and identity/unidentity estimations in mathematical structures and biological sequences

This paper introduces "Kabirian-based optinalysis (KBO)," a pioneering framework that addresses the longstanding challenges in estimating symmetry/asymmetry, similarity/dissimilarity, and identity/unidentity within mathematical structures and biological sequences. The existing methods often lack a strong theoretical foundation, leading to inconsistencies and limitations. Kabirian-based optinalysis draws inspiration from isomorphism and automorphism, providing a theoretically grounded framework that unifies estimation methodologies. It introduces the concept of optiscale, autoreflective pairing, isoreflective pairing, and others ensuring invariance and robustness under various mathematical transformations and establishing functional bijectivity for isomorphic or automorphic structures. This not only overcomes previous limitations but also offers precise and interpretable estimations. Additionally, the framework introduces "geometrical pairwise analysis" to improve sensitivity to position-specific and character-specific variations in biological sequences. This novel approach enhances the accuracy of sequence similarity assessments, surpassing the constraints of conventional methods. The novelty of this work extends beyond mathematics and biology, impacting diverse fields such as computer science, data analysis, pattern recognition, and evolutionary biology. Kabirian-based optinalysis presents a holistic and theoretically grounded solution that has the potential to revolutionize the analysis of complex structures and sequences, opening new horizons for interdisciplinary research.•Inspired by automorphism and isomorphism, Kabirian-based optinalysis introduces a new paradigm-shifting and unified approach to estimations in mathematical structures and biological sequences with a solid conceptual and theoretical foundation.•The GPA method enhances pairwise sequence similarity estimation by being sensitive to position-specific and character-specific variations and providing a comprehensive characterization of these features.

Dicodon-based measures for modeling gene expression

MOTIVATION

Codon usage preference patterns have been associated with modulation of translation efficiency, protein folding, and mRNA decay. However, new studies support that codon pair usage has also a remarkable effect at the gene expression level. Here, we expand the concept of CAI to answer if codon pair usage patterns can be understood in terms of codon usage bias, or if they offer new information regarding coding translation efficiency.

RESULTS

Through the implementation of a weighting strategy to consider the dicodon contributions, we observe that the dicodon-based measure has greater correlations with gene expression level than CAI. Interestingly, we have noted that dicodons associated with a low value of adaptiveness are related to dicodons which mediate strong translational inhibition in yeast. We have also noticed that some codon-pairs have a smaller dicodon contribution than estimated by the product of the respective codon contributions.

AVAILABILITY AND IMPLEMENTATION

Scripts, implemented in Python, are freely available for download at https://zenodo.org/record/7738276#.ZBIDBtLMIdU.

Establishment, optimization, and application of genetic technology in Aspergillus spp

Aspergillus is widely distributed in nature and occupies a crucial ecological niche, which has complex and diverse metabolic pathways and can produce a variety of metabolites. With the deepening of genomics exploration, more Aspergillus genomic informations have been elucidated, which not only help us understand the basic mechanism of various life activities, but also further realize the ideal functional transformation. Available genetic engineering tools include homologous recombinant systems, specific nuclease based systems, and RNA techniques, combined with transformation methods, and screening based on selective labeling. Precise editing of target genes can not only prevent and control the production of mycotoxin pollutants, but also realize the construction of economical and efficient fungal cell factories. This paper reviewed the establishment and optimization process of genome technologies, hoping to provide the theoretical basis of experiments, and summarized the recent progress and application in genetic technology, analyzes the challenges and the possibility of future development with regard to Aspergillus.

Functional proteomics identify mannitol metabolism in serum resistance and therapeutic implications in Vibrio alginolyticus

Serum resistance is recognized as one of the most important pathogenic traits of bacterial pathogens, and no control measure is available. Based on our previous discovery that pathogenic Escherichia coli represses glycine, serine, and threonine metabolism to confer serum resistance and that the reactivation of this pathway by exogenous glycine could restore serum sensitivity, we further investigate the mechanism underlying the action of glycine in Vibrio alginolyticus. Thus, V. alginolyticus is treated with glycine, and the proteomic change is profiled with tandem mass tag-based quantitative proteomics. Compared to the control group, glycine treatment influences the expression of a total of 291 proteins. Among them, a trap-type mannitol/chloroaromatic compound transport system with periplasmic component, encoded by N646_0992, is the most significantly increased protein. In combination with the pathway enrichment analysis showing the altered fructose and mannitol metabolism, mannitol has emerged as a possible metabolite in enhancing the serum killing activity. To demonstrate this, exogenous mannitol reduces bacterial viability. This synergistic effect is further confirmed in a V. alginolyticus-Danio rerio infection model. Furthermore, the mechanism underlying mannitol-enabled serum killing is dependent on glycolysis and the pyruvate cycle that increases the deposition of complement components C3b and C5b-9 on the bacterial surface, whereas inhibiting glycolysis or the pyruvate cycle significantly weakened the synergistic effects and complement deposition. These data together suggest that mannitol is a potent metabolite in reversing the serum resistance of V. alginolyticus and has promising use in aquaculture.

Phylogenies of the 16S rRNA gene and its hypervariable regions lack concordance with core genome phylogenies

BACKGROUND

The 16S rRNA gene is used extensively in bacterial phylogenetics, in species delineation, and now widely in microbiome studies. However, the gene suffers from intragenomic heterogeneity, and reports of recombination and an unreliable phylogenetic signal are accumulating. Here, we compare core gene phylogenies to phylogenies constructed using core gene concatenations to estimate the strength of signal for the 16S rRNA gene, its hypervariable regions, and all core genes at the intra- and inter-genus levels. Specifically, we perform four intra-genus analyses (Clostridium, n = 65; Legionella, n = 47; Staphylococcus, n = 36; and Campylobacter, n = 17) and one inter-genus analysis [41 core genera of the human gut microbiome (31 families, 17 orders, and 12 classes), n = 82].

RESULTS

At both taxonomic levels, the 16S rRNA gene was recombinant and subject to horizontal gene transfer. At the intra-genus level, the gene showed one of the lowest levels of concordance with the core genome phylogeny (50.7% average). Concordance for hypervariable regions was lower still, with entropy masking providing little to no benefit. A major factor influencing concordance was SNP count, which showed a positive logarithmic association. Using this relationship, we determined that 690 ± 110 SNPs were required for 80% concordance (average 16S rRNA gene SNP count was 254). We also found a wide range in 16S-23S-5S rRNA operon copy number among genomes (1-27). At the inter-genus level, concordance for the whole 16S rRNA gene was markedly higher (73.8% - 10th out of 49 loci); however, the most concordant hypervariable regions (V4, V3-V4, and V1-V2) ranked in the third quartile (62.5 to 60.0%).

CONCLUSIONS

Ramifications of a poor phylogenetic performance for the 16S rRNA gene are far reaching. For example, in addition to incorrect species/strain delineation and phylogenetic inference, it has the potential to confound community diversity metrics if phylogenetic information is incorporated - for example, with popular approaches such as Faith's phylogenetic diversity and UniFrac. Our results highlight the problematic nature of these approaches and their use (along with entropy masking) is discouraged. Lastly, the wide range in 16S rRNA gene copy number among genomes also has a strong potential to confound diversity metrics. Video Abstract.

Glycerol waste to value added products and its potential applications

The rapid industrial and economic development runs on fossil fuel and other energy sources. Limited oil reserves, environmental issues, and high transportation costs lead towards carbon unbiased renewable and sustainable fuel. Compared to other carbon-based fuels, biodiesel is attracted worldwide as a biofuel for the reduction of global dependence on fossil fuels and the greenhouse effect. During biodiesel production, approximately 10% of glycerol is formed in the transesterification process in a biodiesel plant. The ditching of crude glycerol is important as it contains salt, free fatty acids, and methanol that cause contamination of soil and creates environmental challenges for researchers. However, the excessive cost of crude glycerol refining and market capacity encourage the biodiesel industries for developing a new idea for utilising and produced extra sources of income and treat biodiesel waste. This review focuses on the significance of crude glycerol in the value-added utilisation and conversion to bioethanol by a fermentation process and describes the opportunities of glycerol in various applications.

Graphic abstract

Genome-wide proximity between RNA polymerase and DNA topoisomerase I supports transcription in Streptococcus pneumoniae

Streptococcus pneumoniae is a major cause of disease and death that develops resistance to multiple antibiotics. DNA topoisomerase I (TopoI) is a novel pneumococcal drug target. TopoI is the sole type-I pneumococcal topoisomerase that regulates supercoiling homeostasis in this bacterium. In this study, a direct in vitro interaction between TopoI and RNA polymerase (RNAP) was detected by surface plasmon resonance. To understand the interplay between transcription and supercoiling regulation in vivo, genome-wide association of RNAP and TopoI was studied by ChIP-Seq. RNAP and TopoI were enriched at the promoters of 435 and 356 genes, respectively. Higher levels of expression were consistently measured in those genes whose promoters recruit both RNAP and TopoI, in contrast with those enriched in only one of them. Both enzymes occupied a narrow region close to the ATG codon. In addition, RNAP displayed a regular distribution throughout the coding regions. Likewise, the summits of peaks called with MACS tool, mapped around the ATG codon in both cases. However, RNAP showed a broader distribution towards ATG-downstream positions. Remarkably, inhibition of RNAP with rifampicin prevented the localization of TopoI at promoters and, vice versa, inhibition of TopoI with seconeolitsine prevented the binding of RNAP to promoters. This indicates a functional interplay between RNAP and TopoI. To determine the molecular factors responsible for RNAP and TopoI co-recruitment, we looked for DNA sequence motifs. We identified a motif corresponding to a -10-extended promoter for TopoI and for RNAP. Furthermore, RNAP was preferentially recruited to genes co-directionally oriented with replication, while TopoI was more abundant in head-on genes. TopoI was located in the intergenic regions of divergent genes pairs, near the promoter of the head-on gene of the pair. These results suggest a role for TopoI in the formation/stability of the RNAP-DNA complex at the promoter and during transcript elongation.

Streptococcus pneumoniae is a main cause of pneumonia, meningitis and sepsis. Antibiotic resistance in this bacterium has spread worldwide, compromising medical treatment. Therefore, the development of new drugs directed to novel targets is necessary. DNA topology is essential for the regulation of replication and gene expression. Topology is regulated and maintained by DNA topoisomerases, carrying out nicking-closing reactions. Type I and type II topoisomerases act on single-stranded and double-stranded DNA, respectively. Although type II topoisomerases are the target of clinically used antibiotics, there are no clinical antibiotics directed against type I topoisomerases. Seconeolitsine, a new drug targeting topoisomerase I, is effective against bacteria that have a single type I topoisomerase, such as Streptococcus pneumoniae and Mycobacterium tuberculosis. In this report, we studied the role of topoisomerase I in transcription. We found that topoisomerase I and RNA polymerase physically interact in vitro and co-localize at gene promoters in vivo. Binding of each of these enzymes to promoters was prevented by the specific inhibition of the other enzyme, supporting a role for topoisomerase I in RNA polymerase transcription.

Codon Usage Optimization in the Prokaryotic Tree of Life: How Synonymous Codons Are Differentially Selected in Sequence Domains with Different Expression Levels and Degrees of Conservation

The prokaryotic genomes—the current heritage of the most ancient life forms on earth—are comprised of diverse gene sets, all characterized by varied origins, ancestries, and spatial-temporal expression patterns. Such genetic diversity has for a long time raised the question of how cells shape their coding strategies to optimize protein demands (i.e., product abundance) and accuracy (i.e., translation fidelity) through the use of the same genetic code in genomes with GC contents that range from less than 20 to more than 80%. Here, we present evidence on how codon usage is adjusted in the prokaryotic tree of life and on how specific biases have operated to improve translation. Through the use of proteome data, we characterized conserved and variable sequence domains in genes of either high or low expression level and quantitated the relative weight of efficiency and accuracy—as well as their interaction—in shaping codon usage in prokaryotes.

Prokaryote genomes exhibit a wide range of GC contents and codon usages, both resulting from an interaction between mutational bias and natural selection. In order to investigate the basis underlying specific codon changes, we performed a comprehensive analysis of 29 different prokaryote families. The analysis of core gene sets with increasing ancestries in each family lineage revealed that the codon usages became progressively more adapted to the tRNA pools. While, as previously reported, highly expressed genes presented the most optimized codon usage, the singletons contained the less selectively favored codons. The results showed that usually codons with the highest translational adaptation were preferentially enriched. In agreement with previous reports, a C bias in 2- to 3-fold pyrimidine-ending codons, and a U bias in 4-fold codons occurred in all families, irrespective of the global genomic GC content. Furthermore, the U biases suggested that U₃-mRNA–U₃₄-tRNA interactions were responsible for a prominent codon optimization in both the most ancestral core and the highly expressed genes. A comparative analysis of sequences that encode conserved (cr) or variable (vr) translated products, with each one being under high (HEP) and low (LEP) expression levels, demonstrated that the efficiency was more relevant (by a factor of 2) than accuracy to modeling codon usage. Finally, analysis of the third position of codons (GC3) revealed that in genomes with global GC contents higher than 35 to 40%, selection favored a GC3 increase, whereas in genomes with very low GC contents, a decrease in GC3 occurred. A comprehensive final model is presented in which all patterns of codon usage variations are condensed in four distinct behavioral groups.

2SigFinder: the combined use of small-scale and large-scale statistical testing for genomic island detection from a single genome

BACKGROUND

Genomic islands are associated with microbial adaptations, carrying genomic signatures different from the host. Some methods perform an overall test to identify genomic islands based on their local features. However, regions of different scales will display different genomic features.

RESULTS

We proposed here a novel method "2SigFinder ", the first combined use of small-scale and large-scale statistical testing for genomic island detection. The proposed method was tested by genomic island boundary detection and identification of genomic islands or functional features of real biological data. We also compared the proposed method with the comparative genomics and composition-based approaches. The results indicate that the proposed 2SigFinder is more efficient in identifying genomic islands.

CONCLUSIONS

From real biological data, 2SigFinder identified genomic islands from a single genome and reported robust results across different experiments, without annotated information of genomes or prior knowledge from other datasets. 2SigHunter identified 25 Pathogenicity, 1 tRNA, 2 Virulence and 2 Repeats from 27 Pathogenicity, 1 tRNA, 2 Virulence and 2 Repeats, and detected 101 Phage and 28 HEG out of 130 Phage and 36 HEGs in S. enterica Typhi CT18, which shows that it is more efficient in detecting functional features associated with GIs.

Identification of common highly expressed genes of Salmonella Enteritidis by in silico prediction of gene expression and in vitro transcriptomic analysis

Chickens are the reservoir host of Salmonella Enteritidis. Salmonella Enteritidis colonizes the gastro-intestinal tract of chickens and replicates within macrophages without causing clinically discernable illness. Persistence of S. Enteritidis in the hostile environments of intestinal tract and macrophages allows it to disseminate extra-intestinally to liver, spleen, and reproductive tract. Extra-intestinal dissemination into reproductive tract leads to contamination of internal contents of eggs, which is a major risk factor for human infection. Understanding the genes that contribute to S. Enteritidis persistence in the chicken host is central to elucidate the genetic basis of the unique pathobiology of this public health pathogen. The aim of this study was to identify a succinct set of genes associated with infection-relevant in vitro environments to provide a rational foundation for subsequent biologically-relevant research. We used in silico prediction of gene expression and RNA-seq technology to identify a core set of 73 S. Enteritidis genes that are consistently highly expressed in multiple S. Enteritidis strains cultured at avian physiologic temperature under conditions that represent intestinal and intracellular environments. These common highly expressed (CHX) genes encode proteins involved in bacterial metabolism, protein synthesis, cell-envelope biogenesis, stress response, and a few proteins with uncharacterized functions. Further studies are needed to dissect the contribution of these CHX genes to the pathobiology of S. Enteritidis in the avian host. Several of the CHX genes could serve as promising targets for studies towards the development of immunoprophylactic and novel therapeutic strategies to prevent colonization of chickens and their environment with S. Enteritidis.

Codon usage pattern and predicted gene expression in Arabidopsis thaliana

The extensive research for predicting highly expressed genes in plant genome sequences has been going on for decades. The codon usage pattern of genes in Arabidopsis thaliana genome is a classical topic for plant biologists for its significance in the understanding of molecular plant biology. Here we have used a gene expression profiling methodology based on the score of modified relative codon bias (MRCBS) to elucidate expression pattern of genes in Arabidopsis thaliana. MRCBS relies exclusively on sequence features for identifying the highly expressed genes. In this study, a critical analysis of predicted highly expressed (PHE) genes in Arabidopsis thaliana has been performed using MRCBS as a numerical estimator of gene expression level. Consistent with previous other results, our study indicates that codon composition plays an important role in the regulation of gene expression. We found a systematic strong correlation between MRCBS and CAI (codon adaptation index) or other expression-measures. Additionally, MRCBS correlates well with experimental gene expression data. Our study highlights the relationship between gene expression and compositional signature in relation to codon usage bias and sets the ground for the further investigation of the evolution of the protein-coding genes in the plant genome.

Prediction of Horizontally and Widely Transferred Genes in Prokaryotes

Horizontal gene transfer (HGT) is the process whereby an organism acquires exogenous genes (horizontally transferred genes or HT genes) that are not inherited from the parent, but are derived from another organism. In prokaryotes, HGT has been considered as one of the important driving forces of evolution. Previously, genome-wide analyses have been conducted for estimating the proportion of HT genes in prokaryotic genomes, but the number of species examined at the time was limited, and gene annotation was relatively poor. Currently, tens of thousands of prokaryotic genomes have been published and gene annotation resources have improved. In the present study, HT gene prediction method was modified so that the estimate was robust to gene length, conducting a comprehensive search using 3017 representative prokaryotic genomes belonging to 1348 species. The result showed that an average of 13% (ranging from 0% to 30% across species) of protein-coding genes was predicted as being of horizontal origin. The proportion of the predicted HT genes per species was associated with the species’ habitat, while a positive correlation between the proportion and genomic nucleotide frequency was also observed. Moreover, the functions of the predicted HT genes were inferred and compared according to two popular databases, the Clusters of Orthologous Groups and the Kyoto Encyclopedia of Genes and Genomes. As a result, both databases indicated that many of the widely transferred genes were involved in mobile genetic elements (transposons, phages, and plasmids) as expected. Notably, the present study predicted that six as-yet-uncharacterized genes were widely distributed HT genes, and therefore, will be interesting targets for evolutionary studies. Thus, this study demonstrates that a data-driven approach using massive sequence data may contribute to a broader understanding of HGT in prokaryotes.

Investigation on the Evolutionary Relation of Diverse Polyhydroxyalkanoate Gene Clusters in Betaproteobacteria

Products of numerous genes (phaC, phaA, phaB, phaP, phaR, and phaZ) are involved in the synthesis and degradation processes of the ubiquitous prokaryotic polyhydroxyalkanoate (PHA) intracellular reserve storage system. In this study, we performed a bioinformatics analysis to identify PHA-related genes and proteins in the genome of 66 selected organisms (class: Betaproteobacteria) that occur in various habitats; besides, evolutionary trajectories of the PHA system are reported here. The identified PHA-related genes were organized into clusters, and the gene arrangement was highly diverse. The occurrence and distribution of PHA-related clusters revealed that a single cluster was primarily segmented into small gene groups among various genomes, which were further reorganized as novel clusters based on various functional genes. The individual phylogenies of gene and protein sequences supported that the clusters were assembled through the relocation of native orthologous genes that underwent insertion, deletion, and elongation events. Furthermore, the neighboring genes provided valuable evolutionary and functional cues regarding the conservation and maintenance of PHA-related genes in the genome. Overall, the aforementioned results strongly indicate the influence of horizontal gene transfer on the organization of PHA-related gene clusters. Therefore, our results reveal new insights into the organization, evolutionary history, and cluster conservation of the PHA-related gene inventories among Betaproteobacterial organisms.

Taxonomic differences of gut microbiomes drive cellulolytic enzymatic potential within hind-gut fermenting mammals

Host diet influences the diversity and metabolic activities of the gut microbiome. Previous studies have shown that the gut microbiome provides a wide array of enzymes that enable processing of diverse dietary components. Because the primary diet of the porcupine, Erethizon dorsatum, is lignified plant material, we reasoned that the porcupine microbiome would be replete with enzymes required to degrade lignocellulose. Here, we report on the bacterial composition in the porcupine microbiome using 16S rRNA sequencing and bioinformatics analysis. We extended this analysis to the microbiomes of 20 additional mammals located in Shubenacadie Wildlife Park (Nova Scotia, Canada), enabling the comparison of bacterial diversity amongst three mammalian taxonomic orders (Rodentia, Carnivora, and Artiodactyla). 16S rRNA sequencing was validated using metagenomic shotgun sequencing on selected herbivores (porcupine, beaver) and carnivores (coyote, Arctic wolf). In the microbiome, functionality is more conserved than bacterial composition, thus we mined microbiome data sets to identify conserved microbial functions across species in each order. We measured the relative gene abundances for cellobiose phosphorylase, endoglucanase, and beta-glucosidase to evaluate the cellulose-degrading potential of select mammals. The porcupine and beaver had higher proportions of genes encoding cellulose-degrading enzymes than the Artic wolf and coyote. These findings provide further evidence that gut microbiome diversity and metabolic capacity are influenced by host diet.

Interactions of Freshwater Cyanobacteria with Bacterial Antagonists

Cyanobacterial and algal mass development, or blooms, have severe effects on freshwater and marine systems around the world. Many of these phototrophs produce a variety of potent toxins, contribute to oxygen depletion, and affect water quality in several ways. Coexisting antagonists, such as cyanolytic bacteria, hold the potential to suppress, or even terminate, such blooms, yet the nature of this interaction is not well studied. We isolated 31 cyanolytic bacteria affiliated with the genera Pseudomonas, Stenotrophomonas, Acinetobacter, and Delftia from three eutrophic freshwater lakes in Sweden and selected four phylogenetically diverse bacterial strains with strong-to-moderate lytic activity. To characterize their functional responses to the presence of cyanobacteria, we performed RNA sequencing (RNA-Seq) experiments on coculture incubations, with an initial predator-prey ratio of 1:1. Genes involved in central cellular pathways, stress-related heat or cold shock proteins, and antitoxin genes were highly expressed in both heterotrophs and cyanobacteria. Heterotrophs in coculture expressed genes involved in cell motility, signal transduction, and putative lytic activity. l,d-Transpeptidase was the only significantly upregulated lytic gene in Stenotrophomonas rhizophila EK20. Heterotrophs also shifted their central metabolism from the tricarboxylic acid cycle to the glyoxylate shunt. Concurrently, cyanobacteria clearly show contrasting antagonistic interactions with the four tested heterotrophic strains, which is also reflected in the physical attachment to their cells. In conclusion, antagonistic interactions with cyanobacteria were initiated within 24 h, and expression profiles suggest varied responses for the different cyanobacteria and studied cyanolytes.IMPORTANCE Here, we present how gene expression profiles can be used to reveal interactions between bloom-forming freshwater cyanobacteria and antagonistic heterotrophic bacteria. Species-specific responses in both heterotrophs and cyanobacteria were identified. The study contributes to a better understanding of the interspecies cellular interactions underpinning the persistence and collapse of cyanobacterial blooms.

Comparative Analysis of Predicted Gene Expression among Crenarchaeal Genomes

Research into new methods for identifying highly expressed genes in anonymous genome sequences has been going on for more than 15 years. We presented here an alternative approach based on modified score of relative codon usage bias to identify highly expressed genes in crenarchaeal genomes. The proposed algorithm relies exclusively on sequence features for identifying the highly expressed genes. In this study, a comparative analysis of predicted highly expressed genes in five crenarchaeal genomes was performed using the score of Modified Relative Codon Bias Strength (MRCBS) as a numerical estimator of gene expression level. We found a systematic strong correlation between Codon Adaptation Index and MRCBS. Additionally, MRCBS correlated well with other expression measures. Our study indicates that MRCBS can consistently capture the highly expressed genes.

Survey of (Meta)genomic Approaches for Understanding Microbial Community Dynamics

Advancement in the next generation sequencing technologies has led to evolution of the field of genomics and metagenomics in a slim duration with nominal cost at precipitous higher rate. While metagenomics and genomics can be separately used to reveal the culture-independent and culture-based microbial evolution, respectively, (meta)genomics together can be used to demonstrate results at population level revealing in-depth complex community interactions for specific ecotypes. The field of metagenomics which started with answering "who is out there?" based on 16S rRNA gene has evolved immensely with the precise organismal reconstruction at species/strain level from the deeply covered metagenome data outweighing the need to isolate bacteria of which 99% are de facto non-cultivable. In this review we have underlined the appeal of metagenomic-derived genomes in providing insights into the evolutionary patterns, growth dynamics, genome/gene-specific sweeps, and durability of environmental pressures. We have demonstrated the use of culture-based genomics and environmental shotgun metagenome data together to elucidate environment specific genome modulations via metagenomic recruitments in terms of gene loss/gain, accessory and core-genome extent. We further illustrated the benefit of (meta)genomics in the understanding of infectious diseases by deducing the relationship between human microbiota and clinical microbiology. This review summarizes the technological advances in the (meta)genomic strategies using the genome and metagenome datasets together to increase the resolution of microbial population studies.

Comparative analysis of codon usage bias in Crenarchaea and Euryarchaea genome reveals differential preference of synonymous codons to encode highly expressed ribosomal and RNA polymerase proteins

The present study was undertaken to investigate the pattern of optimal codon usage in Archaea. Comparative analysis was executed to understand the pattern of codon usage bias between the high expression genes (HEG) and the whole genomes in two Archaeal phyla, Crenarchaea and Euryarchaea. The G+C% of the HEG was found to be less in comparison to the genome G+C% in Crenarchaea, whereas reverse was the case in Euryarchaea. The preponderance of U/A ending codons that code for HEG in Crenarchaea was in sharp contrast to the C/G ended ones in Euryarchaea. The analysis revealed prevalence of Uending codons even within theWWY(nucleotide ambiguity code) families in Crenarchaea vis-à-vis Euryarchaea, bacteria and Eukarya. No plausible interpretation of the observed disparity could be made either in the context of tRNA gene composition or genome G+C%. The results in this study attested that the preferential biasness for codons in HEG of Crenarchaea might be different from Euryarchaea. The main highlights are (i) varied CUB in the HEG and in the whole genomes in Euryarchaea and Crenarchaea. (ii) Crenarchaea was found to have some unusual optimal codons (OCs) compared to other organisms. (iii) G+C% (and GC3) of the HEG were different from the genome G+C% in the two phyla. (iv) Genome G+C% and tRNA gene number failed to explain CUB in Crenarchaea. (v) Translational selection is possibly responsible for A+T rich OCs in Crenarchaea.

High hydrostatic pressure adaptive strategies in an obligate piezophile Pyrococcus yayanosii

Pyrococcus yayanosii CH1, as the first and only obligate piezophilic hyperthermophilic microorganism discovered to date, extends the physical and chemical limits of life on Earth. It was isolated from the Ashadze hydrothermal vent at 4,100 m depth. Multi-omics analyses were performed to study the mechanisms used by the cell to cope with high hydrostatic pressure variations. In silico analyses showed that the P. yayanosii genome is highly adapted to its harsh environment, with a loss of aromatic amino acid biosynthesis pathways and the high constitutive expression of the energy metabolism compared with other non-obligate piezophilic Pyrococcus species. Differential proteomics and transcriptomics analyses identified key hydrostatic pressure-responsive genes involved in translation, chemotaxis, energy metabolism (hydrogenases and formate metabolism) and Clustered Regularly Interspaced Short Palindromic Repeats sequences associated with Cellular apoptosis susceptibility proteins.

Big Data, Evolution, and Metagenomes: Predicting Disease from Gut Microbiota Codon Usage Profiles

Metagenomics projects use next-generation sequencing to unravel genetic potential in microbial communities from a wealth of environmental niches, including those associated with human body and relevant to human health. In order to understand large datasets collected in metagenomics surveys and interpret them in context of how a community metabolism as a whole adapts and interacts with the environment, it is necessary to extend beyond the conventional approaches of decomposing metagenomes into microbial species' constituents and performing analysis on separate components. By applying concepts of translational optimization through codon usage adaptation on entire metagenomic datasets, we demonstrate that a bias in codon usage present throughout the entire microbial community can be used as a powerful analytical tool to predict for community lifestyle-specific metabolism. Here we demonstrate this approach combined with machine learning, to classify human gut microbiome samples according to the pathological condition diagnosed in the human host.

A Novel Method to Predict Highly Expressed Genes Based on Radius Clustering and Relative Synonymous Codon Usage

Recombinant proteins play an important role in many aspects of life and have generated a huge income, notably in the industrial enzyme business. A gene is introduced into a vector and expressed in a host organism-for example, E. coli-to obtain a high productivity of target protein. However, transferred genes from particular organisms are not usually compatible with the host's expression system because of various reasons, for example, codon usage bias, GC content, repetitive sequences, and secondary structure. The solution is developing programs to optimize for designing a nucleotide sequence whose origin is from peptide sequences using properties of highly expressed genes (HEGs) of the host organism. Existing data of HEGs determined by practical and computer-based methods do not satisfy for qualifying and quantifying. Therefore, the demand for developing a new HEG prediction method is critical. We proposed a new method for predicting HEGs and criteria to evaluate gene optimization. Codon usage bias was weighted by amplifying the difference between HEGs and non-highly expressed genes (non-HEGs). The number of predicted HEGs is 5% of the genome. In comparison with Puigbò's method, the result is twice as good as Puigbò's one, in kernel ratio and kernel sensitivity. Concerning transcription/translation factor proteins (TF), the proposed method gives low TF sensitivity, while Puigbò's method gives moderate one. In summary, the results indicated that the proposed method can be a good optional applying method to predict optimized genes for particular organisms, and we generated an HEG database for further researches in gene design.

The Code of Silence: Widespread Associations Between Synonymous Codon Biases and Gene Function

Some mutations in gene coding regions exchange one synonymous codon for another, and thus do not alter the amino acid sequence of the encoded protein. Even though they are often called 'silent,' these mutations may exhibit a plethora of effects on the living cell. Therefore, they are often selected during evolution, causing synonymous codon usage biases in genomes. Comparative analyses of bacterial, archaeal, fungal, and human cancer genomes have found many links between a gene's biological role and the accrual of synonymous mutations during evolution. In particular, highly expressed genes in certain functional categories are enriched with optimal codons, which are decoded by the abundant tRNAs, thus enhancing the speed and accuracy of the translating ribosome. The set of genes exhibiting codon adaptation differs between genomes, and these differences show robust associations to organismal phenotypes. In addition to selection for translation efficiency, other distinct codon bias patterns have been found in: amino acid starvation genes, cyclically expressed genes, tissue-specific genes in animals and plants, oxidative stress response genes, cellular differentiation genes, and oncogenes. In addition, genomes of organisms harboring tRNA modifications exhibit particular codon preferences. The evolutionary trace of codon bias patterns across orthologous genes may be examined to learn about a gene's relevance to various phenotypes, or, more generally, its function in the cell.

Back from the dead; the curious tale of the predatory cyanobacterium Vampirovibrio chlorellavorus

An uncultured non-photosynthetic basal lineage of the Cyanobacteria, the Melainabacteria, was recently characterised by metagenomic analyses of aphotic environmental samples. However, a predatory bacterium, Vampirovibrio chlorellavorus, originally described in 1972 appears to be the first cultured representative of the Melainabacteria based on a 16S rRNA sequence recovered from a lyophilised co-culture of the organism. Here, we sequenced the genome of V. chlorellavorus directly from 36 year-old lyophilised material that could not be resuscitated confirming its identity as a member of the Melainabacteria. We identified attributes in the genome that likely allow V. chlorellavorus to function as an obligate predator of the microalga Chlorella vulgaris, and predict that it is the first described predator to use an Agrobacterium tumefaciens-like conjugative type IV secretion system to invade its host. V. chlorellavorus is the first cyanobacterium recognised to have a predatory lifestyle and further supports the assertion that Melainabacteria are non-photosynthetic.

Tn-seq explorer: a tool for analysis of high-throughput sequencing data of transposon mutant libraries

Tn-seq is a high throughput technique for analysis of transposon mutant libraries. Tn-seq Explorer was developed as a convenient and easy-to-use package of tools for exploration of the Tn-seq data. In a typical application, the user will have obtained a collection of sequence reads adjacent to transposon insertions in a reference genome. The reads are first aligned to the reference genome using one of the tools available for this task. Tn-seq Explorer reads the alignment and the gene annotation, and provides the user with a set of tools to investigate the data and identify possibly essential or advantageous genes as those that contain significantly low counts of transposon insertions. Emphasis is placed on providing flexibility in selecting parameters and methodology most appropriate for each particular dataset. Tn-seq Explorer is written in Java as a menu-driven, stand-alone application. It was tested on Windows, Mac OS, and Linux operating systems. The source code is distributed under the terms of GNU General Public License. The program and the source code are available for download at http://www.cmbl.uga.edu/downloads/programs/Tn_seq_Explorer/ and https://github.com/sina-cb/Tn-seqExplorer.

Transcriptome analysis of thermophilic methylotrophic Bacillus methanolicus MGA3 using RNA-sequencing provides detailed insights into its previously uncharted transcriptional landscape

Background

Bacillus methanolicus MGA3 is a thermophilic, facultative ribulose monophosphate (RuMP) cycle methylotroph. Together with its ability to produce high yields of amino acids, the relevance of this microorganism as a promising candidate for biotechnological applications is evident. The B. methanolicus MGA3 genome consists of a 3,337,035 nucleotides (nt) circular chromosome, the 19,174 nt plasmid pBM19 and the 68,999 nt plasmid pBM69. 3,218 protein-coding regions were annotated on the chromosome, 22 on pBM19 and 82 on pBM69. In the present study, the RNA-seq approach was used to comprehensively investigate the transcriptome of B. methanolicus MGA3 in order to improve the genome annotation, identify novel transcripts, analyze conserved sequence motifs involved in gene expression and reveal operon structures. For this aim, two different cDNA library preparation methods were applied: one which allows characterization of the whole transcriptome and another which includes enrichment of primary transcript 5′-ends.

Results

Analysis of the primary transcriptome data enabled the detection of 2,167 putative transcription start sites (TSSs) which were categorized into 1,642 TSSs located in the upstream region (5′-UTR) of known protein-coding genes and 525 TSSs of novel antisense, intragenic, or intergenic transcripts. Firstly, 14 wrongly annotated translation start sites (TLSs) were corrected based on primary transcriptome data. Further investigation of the identified 5′-UTRs resulted in the detailed characterization of their length distribution and the detection of 75 hitherto unknown cis-regulatory RNA elements. Moreover, the exact TSSs positions were utilized to define conserved sequence motifs for translation start sites, ribosome binding sites and promoters in B. methanolicus MGA3. Based on the whole transcriptome data set, novel transcripts, operon structures and mRNA abundances were determined. The analysis of the operon structures revealed that almost half of the genes are transcribed monocistronically (940), whereas 1,164 genes are organized in 381 operons. Several of the genes related to methylotrophy had highly abundant transcripts.

Conclusion

The extensive insights into the transcriptional landscape of B. methanolicus MGA3, gained in this study, represent a valuable foundation for further comparative quantitative transcriptome analyses and possibly also for the development of molecular biology tools which at present are very limited for this organism.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1239-4) contains supplementary material, which is available to authorized users.

Characterization of leaf blade- and leaf sheath-associated bacterial communities and assessment of their responses to environmental changes in CO₂, temperature, and nitrogen levels under field conditions

Rice shoot-associated bacterial communities at the panicle initiation stage were characterized and their responses to elevated surface water-soil temperature (ET), low nitrogen (LN), and free-air CO2 enrichment (FACE) were assessed by clone library analyses of the 16S rRNA gene. Principal coordinate analyses combining all sequence data for leaf blade- and leaf sheath-associated bacteria revealed that each bacterial community had a distinct structure, as supported by PC1 (61.5%), that was mainly attributed to the high abundance of Planctomycetes in leaf sheaths. Our results also indicated that the community structures of leaf blade-associated bacteria were more sensitive than those of leaf sheath-associated bacteria to the environmental factors examined. Among these environmental factors, LN strongly affected the community structures of leaf blade-associated bacteria by increasing the relative abundance of Bacilli. The most significant effect of FACE was also observed on leaf blade-associated bacteria under the LN condition, which was explained by decreases and increases in Agrobacterium and Pantoea, respectively. The community structures of leaf blade-associated bacteria under the combination of FACE and ET were more similar to those of the control than to those under ET or FACE. Thus, the combined effects of environmental factors need to be considered in order to realistically assess the effects of environmental changes on microbial community structures.

Modular construction of a functional artificial epothilone polyketide pathway

Natural products of microbial origin continue to be an important source of pharmaceuticals and agrochemicals exhibiting potent activities and often novel modes of action. Due to their inherent structural complexity chemical synthesis is often hardly possible, leaving fermentation as the only viable production route. In addition, the pharmaceutical properties of natural products often need to be optimized for application by sophisticated medicinal chemistry and/or biosynthetic engineering. The latter requires a detailed understanding of the biosynthetic process and genetic tools to modify the producing organism that are often unavailable. Consequently, heterologous expression of complex natural product pathways has been in the focus of development over recent years. However, piecing together existing DNA cloned from natural sources and achieving efficient expression in heterologous circuits represent several limitations that can be addressed by synthetic biology. In this work we have redesigned and reassembled the 56 kb epothilone biosynthetic gene cluster from Sorangium cellulosum for expression in the high GC host Myxococcus xanthus. The codon composition was adapted to a modified codon table for M. xanthus, and unique restriction sites were simultaneously introduced and others eliminated from the sequence in order to permit pathway assembly and future interchangeability of modular building blocks from the epothilone megasynthetase. The functionality of the artificial pathway was demonstrated by successful heterologous epothilone production in M. xanthus at significant yields that have to be improved in upcoming work. Our study sets the stage for future engineering of epothilone biosynthesis and production optimization using a highly flexible assembly strategy.

Inferring gene function from evolutionary change in signatures of translation efficiency

Background

The genetic code is redundant, meaning that most amino acids can be encoded by more than one codon. Highly expressed genes tend to use optimal codons to increase the accuracy and speed of translation. Thus, codon usage biases provide a signature of the relative expression levels of genes, which can, uniquely, be quantified across the domains of life.

Results

Here we describe a general statistical framework to exploit this phenomenon and to systematically associate genes with environments and phenotypic traits through changes in codon adaptation. By inferring evolutionary signatures of translation efficiency in 911 bacterial and archaeal genomes while controlling for confounding effects of phylogeny and inter-correlated phenotypes, we linked 187 gene families to 24 diverse phenotypic traits. A series of experiments in Escherichia coli revealed that 13 of 15, 19 of 23, and 3 of 6 gene families with changes in codon adaptation in aerotolerant, thermophilic, or halophilic microbes. Respectively, confer specific resistance to, respectively, hydrogen peroxide, heat, and high salinity. Further, we demonstrate experimentally that changes in codon optimality alone are sufficient to enhance stress resistance. Finally, we present evidence that multiple genes with altered codon optimality in aerobes confer oxidative stress resistance by controlling the levels of iron and NAD(P)H.

Conclusions

Taken together, these results provide experimental evidence for a widespread connection between changes in translation efficiency and phenotypic adaptation. As the number of sequenced genomes increases, this novel genomic context method for linking genes to phenotypes based on sequence alone will become increasingly useful.

Identifying pathogenicity islands in bacterial pathogenomics using computational approaches

High-throughput sequencing technologies have made it possible to study bacteria through analyzing their genome sequences. For instance, comparative genome sequence analyses can reveal the phenomenon such as gene loss, gene gain, or gene exchange in a genome. By analyzing pathogenic bacterial genomes, we can discover that pathogenic genomic regions in many pathogenic bacteria are horizontally transferred from other bacteria, and these regions are also known as pathogenicity islands (PAIs). PAIs have some detectable properties, such as having different genomic signatures than the rest of the host genomes, and containing mobility genes so that they can be integrated into the host genome. In this review, we will discuss various pathogenicity island-associated features and current computational approaches for the identification of PAIs. Existing pathogenicity island databases and related computational resources will also be discussed, so that researchers may find it to be useful for the studies of bacterial evolution and pathogenicity mechanisms.

Relative amino acid composition signatures of organisms and environments

BACKGROUND

Identifying organism-environment interactions at the molecular level is crucial to understanding how organisms adapt to and change the chemical and molecular landscape of their habitats. In this work we investigated whether relative amino acid compositions could be used as a molecular signature of an environment and whether such a signature could also be observed at the level of the cellular amino acid composition of the microorganisms that inhabit that environment.

METHODOLOGIES/PRINCIPAL FINDINGS

To address these questions we collected and analyzed environmental amino acid determinations from the literature, and estimated from complete genomic sequences the global relative amino acid abundances of organisms that are cognate to the different types of environment. Environmental relative amino acid abundances clustered into broad groups (ocean waters, host-associated environments, grass land environments, sandy soils and sediments, and forest soils), indicating the presence of amino acid signatures specific for each environment. These signatures correlate to those found in organisms. Nevertheless, relative amino acid abundance of organisms was more influenced by GC content than habitat or phylogeny.

CONCLUSIONS

Our results suggest that relative amino acid composition can be used as a signature of an environment. In addition, we observed that the relative amino acid composition of organisms is not highly determined by environment, reinforcing previous studies that find GC content to be the major factor correlating to amino acid composition in living organisms.

scnRCA: a novel method to detect consistent patterns of translational selection in mutationally-biased genomes

Codon usage bias (CUB) results from the complex interplay between translational selection and mutational biases. Current methods for CUB analysis apply heuristics to integrate both components, limiting the depth and scope of CUB analysis as a technique to probe into the evolution and optimization of protein-coding genes. Here we introduce a self-consistent CUB index (scnRCA) that incorporates implicit correction for mutational biases, facilitating exploration of the translational selection component of CUB. We validate this technique using gene expression data and we apply it to a detailed analysis of CUB in the Pseudomonadales. Our results illustrate how the selective enrichment of specific codons among highly expressed genes is preserved in the context of genome-wide shifts in codon frequencies, and how the balance between mutational and translational biases leads to varying definitions of codon optimality. We extend this analysis to other moderate and fast growing bacteria and we provide unified support for the hypothesis that C- and A-ending codons of two-box amino acids, and the U-ending codons of four-box amino acids, are systematically enriched among highly expressed genes across bacteria. The use of an unbiased estimator of CUB allows us to report for the first time that the signature of translational selection is strongly conserved in the Pseudomonadales in spite of drastic changes in genome composition, and extends well beyond the core set of highly optimized genes in each genome. We generalize these results to other moderate and fast growing bacteria, hinting at selection for a universal pattern of gene expression that is conserved and detectable in conserved patterns of codon usage bias.

Changes in translational efficiency is a dominant regulatory mechanism in the environmental response of bacteria

To understand how cell physiological state affects mRNA translation, we used Shewanella oneidensis MR-1 grown under steady state conditions at either 20% or 8.5% O2. Using a combination of quantitative proteomics and RNA-Seq, we generated high-confidence data on >1000 mRNA and protein pairs. By using a steady state model, we found that differences in protein-mRNA ratios were primarily due to differences in the translational efficiency of specific genes. When oxygen levels were lowered, 28% of the proteins showed at least a 2-fold change in expression. Transcription levels were sp. significantly altered for 26% of the protein changes; translational efficiency was significantly altered for 46% and a combination of both was responsible for the remaining 28%. Changes in translational efficiency were significantly correlated with the codon usage pattern of the genes and measurable tRNA pools changed in response to altered O2 levels. Our results suggest that changes in the translational efficiency of proteins, in part due to altered tRNA pools, is a major determinant of regulated alterations in protein expression levels in bacteria.

Where does Neisseria acquire foreign DNA from: an examination of the source of genomic and pathogenic islands and the evolution of the Neisseria genus

Background

Pathogenicity islands (PAIs) or genomic islands (GEIs) are considered to be the result of a recent horizontal transfer. Detecting PAIs/GEIs as well as their putative source can provide insight into the organism’s pathogenicity within its host. Previously we introduced a tool called S-plot which provides a visual representation of the variation in compositional properties across and between genomic sequences. Utilizing S-plot and new functionality developed here, we examined 18 publicly available Neisseria genomes, including strains of both pathogenic and non-pathogenic species, in order to identify regions of unusual compositional properties (RUCPs) using both a sliding window as well as a gene-by-gene approach.

Results

Numerous GEIs and PAIs were identified including virulence genes previously found within the pathogenic Neisseria species. While some genes were conserved amongst all species, only pathogenic species, or an individual species, a number of genes were detected that are unique to an individual strain. While the majority of such genes have an origin unknown, a number of putative sources including pathogenic and capsule-containing bacteria were determined, indicative of gene exchange between Neisseria spp. and other bacteria within their microhabitat. Furthermore, we uncovered evidence that both N. meningitidis and N. gonorrhoeae have separately acquired DNA from their human host. Data suggests that all three Neisseria species have received horizontally transferred elements post-speciation.

Conclusions

Using this approach, we were able to not only find previously identified regions of virulence but also new regions which may be contributing to the virulence of the species. This comparative analysis provides a means for tracing the evolutionary history of the acquisition of foreign DNA within this genus. Looking specifically at the RUCPs present within the 18 genomes considered, a stronger similarity between N. meningitidis and N. lactamica is observed, suggesting that N. meningitidis arose before N. gonorrhoeae.

GEMBASSY: an EMBOSS associated software package for comprehensive genome analyses

The popular European Molecular Biology Open Software Suite (EMBOSS) currently contains over 400 tools used in various bioinformatics researches, equipped with sophisticated development frameworks for interoperability and tool discoverability as well as rich documentations and various user interfaces. In order to further strengthen EMBOSS in the fields of genomics, we here present a novel EMBOSS associated software (EMBASSY) package named GEMBASSY, which adds more than 50 analysis tools from the G-language Genome Analysis Environment and its Representational State Transfer (REST) and SOAP web services. GEMBASSY basically contains wrapper programs of G-language REST/SOAP web services to provide intuitive and easy access to various annotations within complete genome flatfiles, as well as tools for analyzing nucleic composition, calculating codon usage, and visualizing genomic information. For example, analysis methods such as for calculating distance between sequences by genomic signatures and for predicting gene expression levels from codon usage bias are effective in the interpretation of meta-genomic and meta-transcriptomic data. GEMBASSY tools can be used seamlessly with other EMBOSS tools and UNIX command line tools. The source code written in C is available from GitHub (https://github.com/celery-kotone/GEMBASSY/) and the distribution package is freely available from the GEMBASSY web site (http://www.g-language.org/gembassy/).

Environmental shaping of codon usage and functional adaptation across microbial communities

Microbial communities represent the largest portion of the Earth's biomass. Metagenomics projects use high-throughput sequencing to survey these communities and shed light on genetic capabilities that enable microbes to inhabit every corner of the biosphere. Metagenome studies are generally based on (i) classifying and ranking functions of identified genes; and (ii) estimating the phyletic distribution of constituent microbial species. To understand microbial communities at the systems level, it is necessary to extend these studies beyond the species' boundaries and capture higher levels of metabolic complexity. We evaluated 11 metagenome samples and demonstrated that microbes inhabiting the same ecological niche share common preferences for synonymous codons, regardless of their phylogeny. By exploring concepts of translational optimization through codon usage adaptation, we demonstrated that community-wide bias in codon usage can be used as a prediction tool for lifestyle-specific genes across the entire microbial community, effectively considering microbial communities as meta-genomes. These findings set up a 'functional metagenomics' platform for the identification of genes relevant for adaptations of entire microbial communities to environments. Our results provide valuable arguments in defining the concept of microbial species through the context of their interactions within the community.

Sequence analysis of a complete 1.66 Mb Prochlorococcus marinus MED4 genome cloned in yeast

Marine cyanobacteria of the genus Prochlorococcus represent numerically dominant photoautotrophs residing throughout the euphotic zones in the open oceans and are major contributors to the global carbon cycle. Prochlorococcus has remained a genetically intractable bacterium due to slow growth rates and low transformation efficiencies using standard techniques. Our recent successes in cloning and genetically engineering the AT-rich, 1.1 Mb Mycoplasma mycoides genome in yeast encouraged us to explore similar methods with Prochlorococcus. Prochlorococcus MED4 has an AT-rich genome, with a GC content of 30.8%, similar to that of Saccharomyces cerevisiae (38%), and contains abundant yeast replication origin consensus sites (ACS) evenly distributed around its 1.66 Mb genome. Unlike Mycoplasma cells, which use the UGA codon for tryptophane, Prochlorococcus uses the standard genetic code. Despite this, we observed no toxic effects of several partial and 15 whole Prochlorococcus MED4 genome clones in S. cerevisiae. Sequencing of a Prochlorococcus genome purified from yeast identified 14 single base pair missense mutations, one frameshift, one single base substitution to a stop codon and one dinucleotide transversion compared to the donor genomic DNA. We thus provide evidence of transformation, replication and maintenance of this 1.66 Mb intact bacterial genome in S. cerevisiae.

Codon usage methods for horizontal gene transfer detection generate an abundance of false positive and false negative results

Bacteria acquire new DNA in a process known as horizontal gene transfer (HGT). To investigate the evolutionary impact of this transfer of DNA, various methods have been developed to detect past HGT events. For example, codon usage-based methods detect the presence of transferred genes by identifying atypical patterns of codon usage. However, some inherited genes exhibit atypical codon usage and some transferred genes have codon usage patterns similar to those of the inherited genes. In this study, we used a comparative phylogenetic approach with Methylobacterium and Caulobacter species to demonstrate that even well-designed codon usage methods fail to detect many HGT events and generate a high rate of false positives (60-75 %) and false negatives (23-61 %). Therefore, we recommend caution when employing codon usage methods to identify transferred genes and suggest that the rapidly increasing availability of bacterial genome sequences makes the phylogenetic approach the method of choice.

Ecological adaptation in bacteria: speciation driven by codon selection

In bacteria, physiological change may be effected by a single gene acquisition, producing ecological differentiation without genetic isolation. Natural selection acting on such differences can reduce the frequency of genotypes that arise from recombination at these loci. However, gene acquisition can only account for recombination interference in the fraction of the genome that is tightly linked to the integration site. To identify additional loci that contribute to adaptive differences, we examined orthologous genes in species of Enterobacteriaceae to identify significant differences in the degree of codon selection. Significance was assessed using the Adaptive Codon Enrichment metric, which accounts for the variation in codon usage bias that is expected to arise from mutation and drift; large differences in codon usage bias were identified in more genes than would be expected to arise from stochastic processes alone. Genes in the same operon showed parallel differences in codon usage bias, suggesting that changes in the overall levels of gene expression led to changes in the degree of adaptive codon usage. Most significant differences between orthologous operons were found among those involved with specific environmental adaptations, whereas "housekeeping" genes rarely showed significant changes. When considered together, the loci experiencing significant changes in codon selection outnumber potentially adaptive gene acquisition events. The identity of genes under strong codon selection seems to be influenced by the habitat from which the bacteria were isolated. We propose a two-stage model for how adaptation to different selective regimes can drive bacterial speciation. Initially, gene acquisitions catalyze rapid ecological differentiation, which modifies the utilization of genes, thereby changing the strength of codon selection on them. Alleles develop fitness variation by substitution, producing recombination interference at these loci in addition to those flanking acquired genes, allowing sequences to diverge across the entire genome and establishing genetic isolation (i.e., protection from frequent homologous recombination).

Gene expression profile of the cynobacterium synechocystis genome

The expression of functional proteins plays a crucial role in modern biotechnology. The free-living cynobacterium Synechocystis PCC 6803 is an interesting model organism to study oxygenic photosynthesis as well as other metabolic processes. Here we analyze a gene expression profiling methodology, RCBS (the scores of relative codon usage bias) to elucidate expression patterns of genes in the Synechocystis genome. To assess the predictive performance of the methodology, we propose a simple algorithm to calculate the threshold score to identify the highly expressed genes in a genome. Analysis of differential expression of the genes of this genome reveals that most of the genes in photosynthesis and respiration belong to the highly expressed category. The other genes with the higher predicted expression level include ribosomal proteins, translation processing factors and many hypothetical proteins. Only 9.5% genes are identified as highly expressed genes and we observe that highly expressed genes in Synechocystis genome often have strong compositional bias in terms of codon usage. An important application concerns the automatic detection of a set of impact codons and genes that are highly expressed tend to use this narrow set of preferred codons and display high codon bias .We further observe a strong correlation between RCBS and protein length indicating natural selection in favor of shorter genes to be expressed at higher level. The better correlations of RCBS with 2D electrophoresis and microarray data for heat shock proteins compared to the expression measure based on codon usage difference, E(g) and codon adaptive index, CAI indicate that the genomic expression profile available in our method can be applied in a meaningful way to study the mRNA expression patterns, which are by themselves necessary for the quantitative description of the biological states.

Genomics of the proteorhodopsin-containing marine flavobacterium Dokdonia sp. strain MED134

Proteorhodopsin phototrophy is expected to have considerable impact on the ecology and biogeochemical roles of marine bacteria. However, the genetic features contributing to the success of proteorhodopsin-containing bacteria remain largely unknown. We investigated the genome of Dokdonia sp. strain MED134 (Bacteroidetes) for features potentially explaining its ability to grow better in light than darkness. MED134 has a relatively high number of peptidases, suggesting that amino acids are the main carbon and nitrogen sources. In addition, MED134 shares with other environmental genomes a reduction in gene copies at the expense of important ones, like membrane transporters, which might be compensated by the presence of the proteorhodopsin gene. The genome analyses suggest Dokdonia sp. MED134 is able to respond to light at least partly due to the presence of a strong flavobacterial consensus promoter sequence for the proteorhodopsin gene. Moreover, Dokdonia sp. MED134 has a complete set of anaplerotic enzymes likely to play a role in the adaptation of the carbon anabolism to the different sources of energy it can use, including light or various organic matter compounds. In addition to promoting growth, proteorhodopsin phototrophy could provide energy for the degradation of complex or recalcitrant organic matter, survival during periods of low nutrients, or uptake of amino acids and peptides at low concentrations. Our analysis suggests that the ability to harness light potentially makes MED134 less dependent on the amount and quality of organic matter or other nutrients. The genomic features reported here may well be among the keys to a successful photoheterotrophic lifestyle.

Quantification of codon selection for comparative bacterial genomics

Background

Statistics measuring codon selection seek to compare genes by their sensitivity to selection for translational efficiency, but existing statistics lack a model for testing the significance of differences between genes. Here, we introduce a new statistic for measuring codon selection, the Adaptive Codon Enrichment (ACE).

Results

This statistic represents codon usage bias in terms of a probabilistic distribution, quantifying the extent that preferred codons are over-represented in the gene of interest relative to the mean and variance that would result from stochastic sampling of codons. Expected codon frequencies are derived from the observed codon usage frequencies of a broad set of genes, such that they are likely to reflect nonselective, genome wide influences on codon usage (e.g. mutational biases). The relative adaptiveness of synonymous codons is deduced from the frequency of codon usage in a pre-selected set of genes relative to the expected frequency. The ACE can predict both transcript abundance during rapid growth and the rate of synonymous substitutions, with accuracy comparable to or greater than existing metrics. We further examine how the composition of reference gene sets affects the accuracy of the statistic, and suggest methods for selecting appropriate reference sets for any genome, including bacteriophages. Finally, we demonstrate that the ACE may naturally be extended to quantify the genome-wide influence of codon selection in a manner that is sensitive to a large fraction of codons in the genome. This reveals substantial variation among genomes, correlated with the tRNA gene number, even among groups of bacteria where previously proposed whole-genome measures show little variation.

Conclusions

The statistical framework of the ACE allows rigorous comparison of the level of codon selection acting on genes, both within a genome and between genomes.

Phylogenomic evidence for a myxococcal contribution to the mitochondrial fatty acid beta-oxidation

Background

The origin of eukaryotes remains a fundamental question in evolutionary biology. Although it is clear that eukaryotic genomes are a chimeric combination of genes of eubacterial and archaebacterial ancestry, the specific ancestry of most eubacterial genes is still unknown. The growing availability of microbial genomes offers the possibility of analyzing the ancestry of eukaryotic genomes and testing previous hypotheses on their origins.

Methodology/Principal Findings

Here, we have applied a phylogenomic analysis to investigate a possible contribution of the Myxococcales to the first eukaryotes. We conducted a conservative pipeline with homologous sequence searches against a genomic sampling of 40 eukaryotic and 357 prokaryotic genomes. The phylogenetic reconstruction showed that several eukaryotic proteins traced to Myxococcales. Most of these proteins were associated with mitochondrial lipid intermediate pathways, particularly enzymes generating reducing equivalents with pivotal roles in fatty acid β-oxidation metabolism. Our data suggest that myxococcal species with the ability to oxidize fatty acids transferred several genes to eubacteria that eventually gave rise to the mitochondrial ancestor. Later, the eukaryotic nucleocytoplasmic lineage acquired those metabolic genes through endosymbiotic gene transfer.

Conclusions/Significance

Our results support a prokaryotic origin, different from α-proteobacteria, for several mitochondrial genes. Our data reinforce a fluid prokaryotic chromosome model in which the mitochondrion appears to be an important entry point for myxococcal genes to enter eukaryotes.