The Random Nature of Genome Architecture: Predicting Open Reading Frame Distributions

Background

A better understanding of the size and abundance of open reading frames (ORFS) in whole genomes may shed light on the factors that control genome complexity. Here we examine the statistical distributions of open reading frames (i.e. distribution of start and stop codons) in the fully sequenced genomes of 297 prokaryotes, and 14 eukaryotes.

Methodology/Principal Findings

By fitting mixture models to data from whole genome sequences we show that the size-frequency distributions for ORFS are strikingly similar across prokaryotic and eukaryotic genomes. Moreover, we show that i) a large fraction (60–80%) of ORF size-frequency distributions can be predicted a priori with a stochastic assembly model based on GC content, and that (ii) size-frequency distributions of the remaining “non-random” ORFs are well-fitted by log-normal or gamma distributions, and similar to the size distributions of annotated proteins.

Conclusions/Significance

Our findings suggest stochastic processes have played a primary role in the evolution of genome complexity, and that common processes govern the conservation and loss of functional genomics units in both prokaryotes and eukaryotes.     

Synonymous codon ordering: a subtle but prevalent strategy of bacteria to improve translational efficiency

Background

In yeast coding sequences, once a particular codon has been used, subsequent occurrence of the same amino acid tends to use codons sharing the same tRNA. Such a phenomenon of co-tRNA codons pairing bias (CTCPB) is also found in some other eukaryotes but it is not known whether it occurs in prokaryotes.

Methodology/Principal Findings

In this study, we focused on a total of 773 bacterial genomes to investigate their synonymous codon pairing preferences. After calculating the actual frequencies of synonymous codon pairs and comparing them with their expected values, we detected an obvious pairing bias towards identical codon pairs. This seems consistent with the previously reported CTCPB phenomenon, since identical codons are certainly read by the same tRNA. However, among co-tRNA but non-identical codon pairs, only 22 were often found overrepresented, suggesting that many co-tRNA codons actually do not preferentially pair together in prokaryotes. Therefore, the previously reported co-tRNA codons pairing rule needs to be more rigorously defined. The affinity differences between a tRNA anticodon and its readable codons should be taken into account. Moreover, both within-gene-shuffling tests and phylogenetic analyses support the idea that translational selection played an important role in shaping the observed synonymous codon pairing pattern in prokaryotes.

Conclusions

Overall, a high level of synonymous codon pairing bias was detected in 73% investigated bacterial species, suggesting the synonymous codon ordering strategy has been prevalently adopted by prokaryotes to improve their translational efficiencies. The findings in this study also provide important clues to better understand the complex dynamics of translational process.     

Comparative analysis of CRISPR cassettes from the human gut metagenomic contigs

Background

CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) is a prokaryotic adaptive defence system that provides resistance against alien replicons such as viruses and plasmids. Spacers in a CRISPR cassette confer immunity against viruses and plasmids containing regions complementary to the spacers and hence they retain a footprint of interactions between prokaryotes and their viruses in individual strains and ecosystems. The human gut is a rich habitat populated by numerous microorganisms, but a large fraction of these are unculturable and little is known about them in general and their CRISPR systems in particular.

Results

We used human gut metagenomic data from three open projects in order to characterize the composition and dynamics of CRISPR cassettes in the human-associated microbiota. Applying available CRISPR-identification algorithms and a previously designed filtering procedure to the assembled human gut metagenomic contigs, we found 388 CRISPR cassettes, 373 of which had repeats not observed previously in complete genomes or other datasets. Only 171 of 3,545 identified spacers were coupled with protospacers from the human gut metagenomic contigs. The number of matches to GenBank sequences was negligible, providing protospacers for 26 spacers.Reconstruction of CRISPR cassettes allowed us to track the dynamics of spacer content. In agreement with other published observations we show that spacers shared by different cassettes (and hence likely older ones) tend to the trailer ends, whereas spacers with matches in the metagenomes are distributed unevenly across cassettes, demonstrating a preference to form clusters closer to the active end of a CRISPR cassette, adjacent to the leader, and hence suggesting dynamical interactions between prokaryotes and viruses in the human gut. Remarkably, spacers match protospacers in the metagenome of the same individual with frequency comparable to a random control, but may match protospacers from metagenomes of other individuals.

Conclusions

The analysis of assembled contigs is complementary to the approach based on the analysis of original reads and hence provides additional data about composition and evolution of CRISPR cassettes, revealing the dynamics of CRISPR-phage interactions in metagenomes.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-202) contains supplementary material, which is available to authorized users.     

Fitness trade-offs in the evolution of dihydrofolate reductase and drug resistance in Plasmodium falciparum

Background

Patterns of emerging drug resistance reflect the underlying adaptive landscapes for specific drugs. In Plasmodium falciparum, the parasite that causes the most serious form of malaria, antifolate drugs inhibit the function of essential enzymes in the folate pathway. However, a handful of mutations in the gene coding for one such enzyme, dihydrofolate reductase, confer drug resistance. Understanding how evolution proceeds from drug susceptibility to drug resistance is critical if new antifolate treatments are to have sustained usefulness.

Methodology/Principal Findings

We use a transgenic yeast expression system to build on previous studies that described the adaptive landscape for the antifolate drug pyrimethamine, and we describe the most likely evolutionary trajectories for the evolution of drug resistance to the antifolate chlorcycloguanil. We find that the adaptive landscape for chlorcycloguanil is multi-peaked, not all highly resistant alleles are equally accessible by evolution, and there are both commonalities and differences in adaptive landscapes for chlorcycloguanil and pyrimethamine.

Conclusions/Significance

Our findings suggest that cross-resistance between drugs targeting the same enzyme reflect the fitness landscapes associated with each particular drug and the position of the genotype on both landscapes. The possible public health implications of these findings are discussed.     

Effect of altitude on the genetic structure of an Alpine grass, Poa hiemata

Background and Aims

The persistence of plants inhabiting restricted alpine areas under climate change will depend upon many factors including levels of genetic variation in adaptive traits, population structure, and breeding system.

Methods

Using microsatellite markers, the genetic structure of populations of a relatively common alpine grass, Poa hiemata, is examined across three altitudinal gradients within the restricted Australian alpine zone where this species has previously been shown to exhibit local adaptation across a narrow altitudinal gradient.

Key Results

Genetic variation across six microsatellite markers revealed genetic structuring along altitudinal transects, and a reduction in genetic variation at high and low altitude extremes relative to sites central within transects. There was less genetic variation among transect sites compared with altitudinal gradients within transects, even though distances among transects were relatively larger. Central sites within transects were less differentiated than those at extremes.

Conclusions

These patterns suggest higher rates of gene flow among sites at similar altitudes than along transects, a process that could assist altitudinal adaptation. Patterns of spatial autocorrelation and isolation by distance changed with altitude and may reflect altered patterns of dispersal via pollen and/or seed. There was evidence for selfing and clonality in neighbouring plants. Levels of gene flow along transects were insufficient to prevent adaptive changes in morphological traits, given previously measured levels of selection.Key words: Poa hiemata, genetic structure, altitudinal gradient, microsatellite, gene flow, climate change     

Accelerated exon evolution within primate segmental duplications

Background

The identification of signatures of natural selection has long been used as an approach to understanding the unique features of any given species. Genes within segmental duplications are overlooked in most studies of selection due to the limitations of draft nonhuman genome assemblies and to the methodological reliance on accurate gene trees, which are difficult to obtain for duplicated genes.

Results

In this work, we detected exons with an accumulation of high-quality nucleotide differences between the human assembly and shotgun sequencing reads from single human and macaque individuals. Comparing the observed rates of nucleotide differences between coding exons and their flanking intronic sequences with a likelihood-ratio test, we identified 74 exons with evidence for rapid coding sequence evolution during the evolution of humans and Old World monkeys. Fifty-five percent of rapidly evolving exons were either partially or totally duplicated, which is a significant enrichment of the 6% rate observed across all human coding exons.

Conclusions

Our results provide a more comprehensive view of the action of selection upon segmental duplications, which are the most complex regions of our genomes. In light of these findings, we suggest that segmental duplications could be subjected to rapid evolution more frequently than previously thought.     

Apoptosis-like death in bacteria induced by HAMLET, a human milk lipid-protein complex

Background

Apoptosis is the primary means for eliminating unwanted cells in multicellular organisms in order to preserve tissue homeostasis and function. It is characterized by distinct changes in the morphology of the dying cell that are orchestrated by a series of discrete biochemical events. Although there is evidence of primitive forms of programmed cell death also in prokaryotes, no information is available to suggest that prokaryotic death displays mechanistic similarities to the highly regulated programmed death of eukaryotic cells. In this study we compared the characteristics of tumor and bacterial cell death induced by HAMLET, a human milk complex of alpha-lactalbumin and oleic acid.

Methodology/Principal Findings

We show that HAMLET-treated bacteria undergo cell death with mechanistic and morphologic similarities to apoptotic death of tumor cells. In Jurkat cells and Streptococcus pneumoniae death was accompanied by apoptosis-like morphology such as cell shrinkage, DNA condensation, and DNA degradation into high molecular weight fragments of similar sizes, detected by field inverse gel electrophoresis. HAMLET was internalized into tumor cells and associated with mitochondria, causing a rapid depolarization of the mitochondrial membrane and bound to and induced depolarization of the pneumococcal membrane with similar kinetic and magnitude as in mitochondria. Membrane depolarization in both systems required calcium transport, and both tumor cells and bacteria were found to require serine protease activity (but not caspase activity) to execute cell death.

Conclusions/Significance

Our results suggest that many of the morphological changes and biochemical responses associated with apoptosis are present in prokaryotes. Identifying the mechanisms of bacterial cell death has the potential to reveal novel targets for future antimicrobial therapy and to further our understanding of core activation mechanisms of cell death in eukaryote cells.     

Horizontal gene transfer in an acid mine drainage microbial community

Background

Horizontal gene transfer (HGT) has been widely identified in complete prokaryotic genomes. However, the roles of HGT among members of a microbial community and in evolution remain largely unknown. With the emergence of metagenomics, it is nontrivial to investigate such horizontal flow of genetic materials among members in a microbial community from the natural environment. Because of the lack of suitable methods for metagenomics gene transfer detection, microorganisms from a low-complexity community acid mine drainage (AMD) with near-complete genomes were used to detect possible gene transfer events and suggest the biological significance.

Results

Using the annotation of coding regions by the current tools, a phylogenetic approach, and an approximately unbiased test, we found that HGTs in AMD organisms are not rare, and we predicted 119 putative transferred genes. Among them, 14 HGT events were determined to be transfer events among the AMD members. Further analysis of the 14 transferred genes revealed that the HGT events affected the functional evolution of archaea or bacteria in AMD, and it probably shaped the community structure, such as the dominance of G-plasma in archaea in AMD through HGT.

Conclusions

Our study provides a novel insight into HGT events among microorganisms in natural communities. The interconnectedness between HGT and community evolution is essential to understand microbial community formation and development.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1720-0) contains supplementary material, which is available to authorized users.     

Climate Change and the Potential Spreading of Marine Mucilage and Microbial Pathogens in the Mediterranean Sea

Background

Marine snow (small amorphous aggregates with colloidal properties) is present in all oceans of the world. Surface water warming and the consequent increase of water column stability can favour the coalescence of marine snow into marine mucilage, large marine aggregates representing an ephemeral and extreme habitat. Marine mucilage characterize aquatic systems with altered environmental conditions.

Methodology/Principal Findings

We investigated, by means of molecular techniques, viruses and prokaryotes within the mucilage and in surrounding seawater to examine the potential of mucilage to host new microbial diversity and/or spread marine diseases. We found that marine mucilage contained a large and unexpectedly exclusive microbial biodiversity and hosted pathogenic species that were absent in surrounding seawater. We also investigated the relationship between climate change and the frequency of mucilage in the Mediterranean Sea over the last 200 years and found that the number of mucilage outbreaks increased almost exponentially in the last 20 years. The increasing frequency of mucilage outbreaks is closely associated with the temperature anomalies.

Conclusions/Significance

We conclude that the spreading of mucilage in the Mediterranean Sea is linked to climate-driven sea surface warming. The mucilage can act as a controlling factor of microbial diversity across wide oceanic regions and could have the potential to act as a carrier of specific microorganisms, thereby increasing the spread of pathogenic bacteria.     

Letter Position Coding Across Modalities: The Case of Braille Readers

Background

The question of how the brain encodes letter position in written words has attracted increasing attention in recent years. A number of models have recently been proposed to accommodate the fact that transposed-letter stimuli like jugde or caniso are perceptually very close to their base words.

Methodology

Here we examined how letter position coding is attained in the tactile modality via Braille reading. The idea is that Braille word recognition may provide more serial processing than the visual modality, and this may produce differences in the input coding schemes employed to encode letters in written words. To that end, we conducted a lexical decision experiment with adult Braille readers in which the pseudowords were created by transposing/replacing two letters.

Principal Findings

We found a word-frequency effect for words. In addition, unlike parallel experiments in the visual modality, we failed to find any clear signs of transposed-letter confusability effects. This dissociation highlights the differences between modalities.

Conclusions

The present data argue against models of letter position coding that assume that transposed-letter effects (in the visual modality) occur at a relatively late, abstract locus.     

The distribution and mutagenesis of short coding INDELs from 1,128 whole exomes

Background

Identifying insertion/deletion polymorphisms (INDELs) with high confidence has been intrinsically challenging in short-read sequencing data. Here we report our approach for improving INDEL calling accuracy by using a machine learning algorithm to combine call sets generated with three independent methods, and by leveraging the strengths of each individual pipeline. Utilizing this approach, we generated a consensus exome INDEL call set from a large dataset generated by the 1000 Genomes Project (1000G), maximizing both the sensitivity and the specificity of the calls.

Results

This consensus exome INDEL call set features 7,210 INDELs, from 1,128 individuals across 13 populations included in the 1000 Genomes Phase 1 dataset, with a false discovery rate (FDR) of about 7.0%.

Conclusions

In our study we further characterize the patterns and distributions of these exonic INDELs with respect to density, allele length, and site frequency spectrum, as well as the potential mutagenic mechanisms of coding INDELs in humans.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1333-7) contains supplementary material, which is available to authorized users.     

Controlling for conservation in genome-wide DNA methylation studies

Background

A commonplace analysis in high-throughput DNA methylation studies is the comparison of methylation extent between different functional regions, computed by averaging methylation states within region types and then comparing averages between regions. For example, it has been reported that methylation is more prevalent in coding regions as compared to their neighboring introns or UTRs, leading to hypotheses about novel forms of epigenetic regulation.

Results

We have identified and characterized a bias present in these seemingly straightforward comparisons that results in the false detection of differences in methylation intensities across region types. This bias arises due to differences in conservation rates, rather than methylation rates, and is broadly present in the published literature. When controlling for conservation at coding start sites the differences in DNA methylation rates disappear. Moreover, a re-evaluation of methylation rates at intronexon junctions reveals that the magnitude of previously reported differences is greatly exaggerated. We introduce two correction methods to address this bias, an inferencebased matrix completion algorithm and an averaging approach, tailored to address different underlying biological questions. We evaluate how analysis using these corrections affects the detection of differences in DNA methylation across functional boundaries.

Conclusions

We report here on a bias in DNA methylation comparative studies that originates in conservation rate differences and manifests itself in the false discovery of differences in DNA methylation intensities and their extents. We have characterized this bias and its broad implications, and show how to control for it so as to enable the study of a variety of biological questions.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1604-3) contains supplementary material, which is available to authorized users.     

Amino Acid Usage Is Asymmetrically Biased in AT- and GC-Rich Microbial Genomes

Introduction

Genomic base composition ranges from less than 25% AT to more than 85% AT in prokaryotes. Since only a small fraction of prokaryotic genomes is not protein coding even a minor change in genomic base composition will induce profound protein changes. We examined how amino acid and codon frequencies were distributed in over 2000 microbial genomes and how these distributions were affected by base compositional changes. In addition, we wanted to know how genome-wide amino acid usage was biased in the different genomes and how changes to base composition and mutations affected this bias. To carry this out, we used a Generalized Additive Mixed-effects Model (GAMM) to explore non-linear associations and strong data dependences in closely related microbes; principal component analysis (PCA) was used to examine genomic amino acid- and codon frequencies, while the concept of relative entropy was used to analyze genomic mutation rates.

Results

We found that genomic amino acid frequencies carried a stronger phylogenetic signal than codon frequencies, but that this signal was weak compared to that of genomic %AT. Further, in contrast to codon usage bias (CUB), amino acid usage bias (AAUB) was differently distributed in AT- and GC-rich genomes in the sense that AT-rich genomes did not prefer specific amino acids over others to the same extent as GC-rich genomes. AAUB was also associated with relative entropy; genomes with low AAUB contained more random mutations as a consequence of relaxed purifying selection than genomes with higher AAUB.

Conclusion

Genomic base composition has a substantial effect on both amino acid- and codon frequencies in bacterial genomes. While phylogeny influenced amino acid usage more in GC-rich genomes, AT-content was driving amino acid usage in AT-rich genomes. We found the GAMM model to be an excellent tool to analyze the genomic data used in this study.     

Echinococcus granulosus antigen B structure: subunit composition and oligomeric states

Background

Antigen B (AgB) is the major protein secreted by the Echinococcus granulosus metacestode and is involved in key host-parasite interactions during infection. The full comprehension of AgB functions depends on the elucidation of several structural aspects that remain unknown, such as its subunit composition and oligomeric states.

Methodology/Principal Findings

The subunit composition of E. granulosus AgB oligomers from individual bovine and human cysts was assessed by mass spectrometry associated with electrophoretic analysis. AgB8/1, AgB8/2, AgB8/3 and AgB8/4 subunits were identified in all samples analyzed, and an AgB8/2 variant (AgB8/2v8) was found in one bovine sample. The exponentially modified protein abundance index (emPAI) was used to estimate the relative abundance of the AgB subunits, revealing that AgB8/1 subunit was relatively overrepresented in all samples. The abundance of AgB8/3 subunit varied between bovine and human cysts. The oligomeric states formed by E. granulosus AgB and recombinant subunits available, rAgB8/1, rAgB8/2 and rAgB8/3, were characterized by native PAGE, light scattering and microscopy. Recombinant subunits showed markedly distinct oligomerization behaviors, forming oligomers with a maximum size relation of rAgB8/3>rAgB8/2>rAgB8/1. Moreover, the oligomeric states formed by rAgB8/3 subunit were more similar to those observed for AgB purified from hydatid fluid. Pressure-induced dissociation experiments demonstrated that the molecular assemblies formed by the more aggregative subunits, rAgB8/2 and rAgB8/3, also display higher structural stability.

Conclusions/Significance

For the first time, AgB subunit composition was analyzed in samples from single hydatid cysts, revealing qualitative and quantitative differences between samples. We showed that AgB oligomers are formed by different subunits, which have distinct abundances and oligomerization properties. Overall, our findings have significantly contributed to increase the current knowledge on AgB expression and structure, highlighting issues that may help to understand the parasite adaptive response during chronic infection.     

Patterns in Cortical Connectivity for Determining Outcomes in Hand Function after Subcortical Stroke

Background and Purpose

Previous studies have noted changes in resting-state functional connectivity during motor recovery following stroke. However, these studies always uncover various patterns of motor recovery. Moreover, subgroups of stroke patients with different outcomes in hand function have rarely been studied.

Materials and Methods

We selected 24 patients who had a subcortical stroke in the left motor pathway and displayed only motor deficits. The patients were divided into two subgroups: completely paralyzed hands (CPH) (12 patients) and partially paralyzed hands (PPH) (12 patients). Twenty-four healthy controls (HC) were also recruited. We performed functional connectivity analysis in both the ipsilesional and contralesional primary motor cortex (M1) to explore the differences in the patterns between each pair of the three diagnostic groups.

Results

Compared with the HC, the PPH group displays reduced connectivity of both the ipsilesional and contralesional M1 with bilateral prefrontal gyrus and contralesional cerebellum posterior lobe. The connectivity of both the ipsilesional and contralesional M1 with contralateral primary sensorimotor cortex was reduced in the CPH group. Additionally, the connectivity of the ipsilesional M1 with contralesional postcentral gyrus, superior parietal lobule and ipsilesional inferior parietal lobule was reduced in the CPH group compared with the PPH group. Moreover, the connectivity of these regions was positively correlated with the Fugl-Meyer Assessment scores (hand+wrist) across all stroke patients.

Conclusions

Patterns in cortical connectivity may serve as a potential biomarker for the neural substratum associated with outcomes in hand function after subcortical stroke.     

A general model of codon bias due to GC mutational bias

Background

In spite of extensive research on the effect of mutation and selection on codon usage, a general model of codon usage bias due to mutational bias has been lacking. Because most amino acids allow synonymous GC content changing substitutions in the third codon position, the overall GC bias of a genome or genomic region is highly correlated with GC3, a measure of third position GC content. For individual amino acids as well, G/C ending codons usage generally increases with increasing GC bias and decreases with increasing AT bias. Arginine and leucine, amino acids that allow GC-changing synonymous substitutions in the first and third codon positions, have codons which may be expected to show different usage patterns.

Principal Findings

In analyzing codon usage bias in hundreds of prokaryotic and plant genomes and in human genes, we find that two G-ending codons, AGG (arginine) and TTG (leucine), unlike all other G/C-ending codons, show overall usage that decreases with increasing GC bias, contrary to the usual expectation that G/C-ending codon usage should increase with increasing genomic GC bias. Moreover, the usage of some codons appears nonlinear, even nonmonotone, as a function of GC bias. To explain these observations, we propose a continuous-time Markov chain model of GC-biased synonymous substitution. This model correctly predicts the qualitative usage patterns of all codons, including nonlinear codon usage in isoleucine, arginine and leucine. The model accounts for 72%, 64% and 52% of the observed variability of codon usage in prokaryotes, plants and human respectively. When codons are grouped based on common GC content, 87%, 80% and 68% of the variation in usage is explained for prokaryotes, plants and human respectively.

Conclusions

The model clarifies the sometimes-counterintuitive effects that GC mutational bias can have on codon usage, quantifies the influence of GC mutational bias and provides a natural null model relative to which other influences on codon bias may be measured.