How Mitochondrial Signaling Games May Shape and Stabilize the Nuclear-Mitochondrial Symbiosis

The eukaryotic lineage has enjoyed a long-term "stable" mutualism between nucleus and mitochondrion, since mitochondrial endosymbiosis began about 2 billion years ago. This mostly cooperative interaction has provided the basis for eukaryotic expansion and diversification, which has profoundly altered the forms of life on Earth. While we ignore the exact biochemical details of how the alpha-proteobacterial ancestor of mitochondria entered into endosymbiosis with a proto-eukaryote, in more general terms, we present a signaling games perspective of how the cooperative relationship became established, and has been maintained. While games are used to understand organismal evolution, information-asymmetric games at the molecular level promise novel insights into endosymbiosis. Using a previously devised biomolecular signaling games approach, we model a sender-receiver information asymmetric game, in which the informed mitochondrial sender signals and the uninformed nuclear receiver may take actions (involving for example apoptosis, senescence, regeneration and autophagy/mitophagy). The simulation shows that cellularization is a stabilizing mechanism for Pareto efficient sender/receiver strategic interaction. In stark contrast, the extracellular environment struggles to maintain efficient outcomes, as senders are indifferent to the effects of their signals upon the receiver. Our hypothesis has translational implications, such as in cellular therapy, as mitochondrial medicine matures. It also inspires speculative conjectures about how an analogous human-AI endosymbiosis may be engineered.

Accurate identification of Helicoverpa armigera-Helicoverpa zea hybrids using genome admixture analysis: implications for genomic surveillance

Helicoverpa armigera, the cotton bollworm moth, is one of the world's most important crop pests, and is spreading throughout the New World from its original range in the Old World. In Brazil, invasive H. armigera has been reported to hybridize with local populations of Helicoverpa zea. The correct identification of H. armigera-H. zea hybrids is important in understanding the origin, spread and future outlook for New World regions that are affected by outbreaks, given that hybridization can potentially facilitate H. zea pesticide resistance and host plant range via introgression of H. armigera genes. Here, we present a genome admixture analysis of high quality genome sequences generated from two H. armigera-H. zea F1 hybrids generated in two different labs. Our admixture pipeline predicts 48.8% and 48.9% H. armigera for the two F1 hybrids, confirming its accuracy. Genome sequences from five H. zea and one H. armigera that were generated as part of the study show no evidence of hybridization. Interestingly, we show that four H. zea genomes generated from a previous study are predicted to possess a proportion of H. armigera genetic material. Using unsupervised clustering to identify non-hybridized H. armigera and H. zea genomes, 8511 ancestry informative markers (AIMs) were identified. Their relative frequencies are consistent with a minor H. armigera component in the four genomes, however its origin remains to be established. We show that the size and quality of genomic reference datasets are critical for accurate hybridization prediction. Consequently, we discuss potential pitfalls in genome admixture analysis of H. armigera-H. zea hybrids, and suggest measures that will improve such analyses.

Comparative Transcriptomic Analysis of Insecticide-Resistant Aedes aegypti from Puerto Rico Reveals Insecticide-Specific Patterns of Gene Expression

Aedes aegypti transmits major arboviruses of public health importance, including dengue, chikungunya, Zika, and yellow fever. The use of insecticides represents the cornerstone of vector control; however, insecticide resistance in Ae. aegypti has become widespread. Understanding the molecular basis of insecticide resistance in this species is crucial to design effective resistance management strategies. Here, we applied Illumina RNA-Seq to study the gene expression patterns associated with resistance to three widely used insecticides (malathion, alphacypermethrin, and lambda-cyhalothrin) in Ae. aegypti populations from two sites (Manatí and Isabela) in Puerto Rico (PR). Cytochrome P450s were the most overexpressed detoxification genes across all resistant phenotypes. Some detoxification genes (CYP6Z7, CYP28A5, CYP9J2, CYP6Z6, CYP6BB2, CYP6M9, and two CYP9F2 orthologs) were commonly overexpressed in mosquitoes that survived exposure to all three insecticides (independent of geographical origin) while others including CYP6BY1 (malathion), GSTD1 (alpha-cypermethrin), CYP4H29 and GSTE6 (lambda-cyhalothrin) were uniquely overexpressed in mosquitoes that survived exposure to specific insecticides. The gene ontology (GO) terms associated with monooxygenase, iron binding, and passive transmembrane transporter activities were significantly enriched in four out of six resistant vs. susceptible comparisons while serine protease activity was elevated in all insecticide-resistant groups relative to the susceptible strain. Interestingly, cuticular-related protein genes (chinase and chitin) were predominantly downregulated, which was also confirmed in the functional enrichment analysis. This RNA-Seq analysis presents a detailed picture of the candidate detoxification genes and other pathways that are potentially associated with pyrethroid and organophosphate resistance in Ae. aegypti populations from PR. These results could inform development of novel molecular tools for detection of resistance-associated gene expression in this important arbovirus vector and guide the design and implementation of resistance management strategies.

Discovery of a novel merbecovirus DNA clone contaminating agricultural rice sequencing datasets from Wuhan, China

HKU4-related coronaviruses are a group of betacoronaviruses belonging to the same merbecovirus subgenus as Middle Eastern Respiratory Syndrome coronavirus (MERS-CoV), which causes severe respiratory illness in humans with a mortality rate of over 30%. The high genetic similarity between HKU4-related coronaviruses and MERS-CoV makes them an attractive subject of research for modeling potential zoonotic spillover scenarios. In this study, we identify a novel coronavirus contaminating agricultural rice RNA sequencing datasets from Wuhan, China. The datasets were generated by the Huazhong Agricultural University in early 2020. We were able to assemble the complete viral genome sequence, which revealed that it is a novel HKU4-related merbecovirus. The assembled genome is 98.38% identical to the closest known full genome sequence, Tylonycteris pachypus bat isolate BtTp-GX2012. Using in silico modeling, we identified that the novel HKU4-related coronavirus spike protein likely binds to human dipeptidyl peptidase 4 (DPP4), the receptor used by MERS-CoV. We further identified that the novel HKU4-related coronavirus genome has been inserted into a bacterial artificial chromosome in a format consistent with previously published coronavirus infectious clones. Additionally, we have found a near complete read coverage of the spike gene of the MERS-CoV reference strain HCoV-EMC/2012, and identify the likely presence of a HKU4-related-MERS chimera in the datasets. Our findings contribute to the knowledge of HKU4-related coronaviruses and document the use of a previously unpublished HKU4 reverse genetics system in apparent MERS-CoV related gain-of-function research. Our study also emphasizes the importance of improved biosafety protocols in sequencing centers and coronavirus research facilities.

How signalling games explain mimicry at many levels: from viral epidemiology to human sociology

Mimicry is exhibited in multiple scales, ranging from molecular, to organismal, and then to human society. 'Batesian'-type mimicry entails a conflict of interest between sender and receiver, reflected in a deceptive mimic signal. 'Müllerian'-type mimicry occurs when there is perfect common interest between sender and receiver in a particular type of encounter, manifested by an honest co-mimic signal. Using a signalling games approach, simulations show that invasion by Batesian mimics will make Müllerian mimicry unstable, in a coevolutionary chase. We use these results to better understand the deceptive strategies of SARS-CoV-2 and their key role in the COVID-19 pandemic. At the biomolecular level, we explain how cellularization promotes Müllerian molecular mimicry, and discourages Batesian molecular mimicry. A wide range of processes analogous to cellularization are presented; these might represent a manner of reducing oscillatory instabilities. Lastly, we identify examples of mimicry in human society that might be addressed using a signalling game approach.

Proteome size reduction in Apicomplexans is linked with loss of DNA repair and host redundant pathways

Apicomplexans are alveolate parasites which include Plasmodium falciparum, the main cause of malaria, one of the world's biggest killers from infectious disease. Apicomplexans are characterized by a reduction in proteome size, which appears to result from metabolic and functional simplification, commensurate with their parasitic lifestyle. However, other factors may also help to explain gene loss such as population bottlenecks experienced during transmission, and the effect of reducing the overall genomic information content. The latter constitutes an 'informational constraint', which is proposed to exert a selective pressure to evolve and maintain genes involved in informational fidelity and error correction, proportional to the quantity of information in the genome (which approximates to proteome size). The dynamics of gene loss was examined in 41 Apicomplexan genomes using orthogroup analysis. We show that loss of genes involved in amino acid metabolism and steroid biosynthesis can be explained by metabolic redundancy with the host. We also show that there is a marked tendency to lose DNA repair genes as proteome size is reduced. This may be explained by a reduction in size of the informational constraint and can help to explain elevated mutation rates in pathogens with reduced genome size. Multiple Sequentially Markovian Coalescent (MSMC) analysis indicates a recent bottleneck, consistent with predictions generated using allele-based population genetics approaches, implying that relaxed selection pressure due to reduced population size might have contributed to gene loss. However, the non-randomness of pathways that are lost challenges this scenario. Lastly, we identify unique orthogroups in malaria-causing Plasmodium species that infect humans, with a high proportion of membrane associated proteins. Thus, orthogroup analysis appears useful for identifying novel candidate pathogenic factors in parasites, when there is a wide sample of genomes available.

How Signaling Games Explain Mimicry at Many Levels: From Viral Epidemiology to Human Sociology

Mimicry is exhibited in multiple scales, ranging from molecular, to organismal, and then to human society. 'Batesian' type mimicry entails a conflict of interest between sender and receiver, reflected in a deceptive mimic signal. 'Mullerian' type mimicry occurs when there is perfect common interest between sender and receiver, manifested by an honest co-mimic signal. Using a signaling games approach, simulations show that invasion by Batesian mimics will make Mullerian mimicry unstable, in a coevolutionary chase. We use these results to better understand the deceptive strategies of SARS-CoV-2 and their key role in the COVID-19 pandemic. At the biomolecular level, we explain how cellularization promotes Mullerian molecular mimicry, and discourages Batesian molecular mimicry. A wide range of processes analogous to cellularization are presented; these might represent a manner of reducing oscillatory instabilities. Lastly, we identify examples of mimicry in human society, that might be addressed using a signaling game approach.

Synergism between the Black Queen effect and the proteomic constraint on genome size reduction in the photosynthetic picoeukaryotes

The photosynthetic picoeukaryotes (PPEs) comprise a rare example of free-living eukaryotes that have undergone genome reduction. Here, we examine a duality in the process; the proposed driver of genome reduction (the Black Queen hypothesis, BQH), and the resultant impact of genome information loss (the Proteomic Constraint hypothesis, PCH). The BQH predicts that some metabolites may be shared in the open ocean, thus driving loss of redundant metabolic pathways in individual genomes. In contrast, the PCH predicts that as the information content of a genome is reduced, the total mutation load is also reduced, leading to loss of DNA repair genes due to the resulting reduction in selective constraint. Consistent with the BQH, we observe that biosynthetic pathways involved with soluble metabolites such as amino acids and carotenoids are preferentially lost from the PPEs, in contrast to biosynthetic pathways involved with insoluble metabolites, such as lipids, which are retained. Consistent with the PCH, a correlation between proteome size and the number of DNA repair genes, and numerous other informational categories, is observed. While elevated mutation rates resulting from the loss of DNA repair genes have been linked to reduced effective population sizes in intracellular bacteria, this remains to be established. This study shows that in microbial species with large population sizes, an underlying factor in modulating their DNA repair capacity appears to be information content.

Machine Learning Algorithm for Predicting Warfarin Dose in Caribbean Hispanics Using Pharmacogenetic Data

Despite some previous examples of successful application to the field of pharmacogenomics, the utility of machine learning (ML) techniques for warfarin dose predictions in Caribbean Hispanic patients has yet to be fully evaluated. This study compares seven ML methods to predict warfarin dosing in Caribbean Hispanics. This is a secondary analysis of genetic and non-genetic clinical data from 190 cardiovascular Hispanic patients. Seven ML algorithms were applied to the data. Data was divided into 80 and 20% to be used as training and test sets. ML algorithms were trained with the training set to obtain the models. Model performance was determined by computing the corresponding mean absolute error (MAE) and % patients whose predicted optimal dose were within ±20% of the actual stabilization dose, and then compared between groups of patients with “normal” (i.e., > 21 but <49 mg/week), low (i.e., ≤21 mg/week, “sensitive”), and high (i.e., ≥49 mg/week, “resistant”) dose requirements. Random forest regression (RFR) significantly outperform all other methods, with a MAE of 4.73 mg/week and 80.56% of cases within ±20% of the actual stabilization dose. Among those with “normal” dose requirements, RFR performance is also better than the rest of models (MAE = 2.91 mg/week). In the “sensitive” group, support vector regression (SVR) shows superiority over the others with lower MAE of 4.79 mg/week. Finally, multivariate adaptive splines (MARS) shows the best performance in the resistant group (MAE = 7.22 mg/week) and 66.7% of predictions within ±20%. Models generated by using RFR, MARS, and SVR algorithms showed significantly better predictions of weekly warfarin dosing in the studied cohorts than other algorithms. Better performance of the ML models for patients with “normal,” “sensitive,” and “resistant” to warfarin were obtained when compared to other populations and previous statistical models.

Origin of biomolecular games: deception and molecular evolution

Biological macromolecules encode information: some of it to endow the molecule with structural flexibility, some of it to enable molecular actions as a catalyst or a substrate, but a residual part can be used to communicate with other macromolecules. Thus, macromolecules do not need to possess information only to survive in an environment, but also to strategically interact with others by sending signals to a receiving macromolecule that can properly interpret the signal and act suitably. These sender-receiver signalling games are sustained by the information asymmetry that exists among the macromolecules. In both biochemistry and molecular evolution, the important role of information asymmetry remains largely unaddressed. Here, we provide a new unifying perspective on the impact of information symmetry between macromolecules on molecular evolutionary processes, while focusing on molecular deception. Biomolecular games arise from the ability of biological macromolecules to exert precise recognition, and their role as units of selection, meaning that they are subject to competition and cooperation with other macromolecules. Thus, signalling game theory can be used to better understand fundamental features of living systems such as molecular recognition, molecular mimicry, selfish elements and 'junk' DNA. We show how deceptive behaviour at the molecular level indicates a conflict of interest, and so provides evidence of genetic conflict. This model proposes that molecular deception is diagnostic of selfish behaviour, helping to explain the evasive behaviour of transposable elements in 'junk' DNA, for example. Additionally, in this broad review, a range of major evolutionary transitions are shown to be associated with the establishment of signalling conventions, many of which are susceptible to molecular deception. These perspectives allow us to assign rudimentary behaviour to macromolecules, and show how participation in signalling games differentiates biochemistry from abiotic chemistry.

On the Origin of Biomolecular Networks

Biomolecular networks have already found great utility in characterizing complex biological systems arising from pairwise interactions amongst biomolecules. Here, we explore the important and hitherto neglected role of information asymmetry in the genesis and evolution of such pairwise biomolecular interactions. Information asymmetry between sender and receiver genes is identified as a key feature distinguishing early biochemical reactions from abiotic chemistry, and a driver of network topology as biomolecular systems become more complex. In this context, we review how graph theoretical approaches can be applied not only for a better understanding of various proximate (mechanistic) relations, but also, ultimate (evolutionary) structures encoded in such networks from among all types of variations they induce. Among many possible variations, we emphasize particularly the essential role of gene duplication in terms of signaling game theory, whereby sender and receiver gene players accrue benefit from gene duplication, leading to a preferential attachment mode of network growth. The study of the resulting dynamics suggests many mathematical/computational problems, the majority of which are intractable yet yield to efficient approximation algorithms, when studied through an algebraic graph theoretic lens. We relegate for future work the role of other possible generalizations, additionally involving horizontal gene transfer, sexual recombination, endo-symbiosis, etc., which enrich the underlying graph theory even further.

Genetic Code Error Minimization as a Non-Adaptive But Beneficial Trait

In a recent Letter, Di Giulio questions the use of the term 'neutral' when describing the process by which error minimization may have arisen as a side-product of genetic code expansion, resulting from the addition of similar amino acids to similar codons (Di Giulio, in J Mol Evol 86(9):593-597, 2018). However, I point out that in this scenario error minimization is non-adaptive, and so 'neutral' is an appropriate term to describe its imperviousness to direct selection. Error minimization is a form of mutational robustness, and so commonly viewed as beneficial. This in turn implies that not all beneficial traits may be adaptations generated by direct selection for that trait.

A Preliminary Molecular and Phylogenetic Analysis of the Genome of a Novel Endogenous Retrovirus in the Sea Slug Elysia chlorotica

An endogenous retrovirus that is present in the sea slug Elysia chlorotica is expressed in all individuals at the end of the annual life cycle. But the precise role of the virus, if any, in slug senescence or death is unknown. We have determined the genomic sequence of the virus and performed a phylogenetic analysis of the data. The 6060-base pair genome of the virus possesses a reverse transcriptase-domain-containing protein that shows similarity to retrotransposon sequences found in Aplysia californica and Strongylocentrotus purpuratus. However, nucleotide BLAST analysis of the whole genome resulted in hits to only a few portions of the genome, indicating that the Elysia chlorotica retrovirus is novel, has not been previously sequenced, and does not have great genetic similarity to other known viral species. When more invertebrate retroviral genomes are examined, a more precise phylogenetic placement of the Elysia chlorotica retrovirus can be determined.

Social network analysis of the biblical Moses

Here, social network analysis approaches are used to characterize the figure of the biblical Moses, and his relationship with characters from the books of the Pentateuch; Genesis, Exodus, Leviticus, Numbers and Deuteronomy. The potential value of using such quantitative approaches is explored in relation to other forms of textual exegesis. Using a maximum likelihood approach, the degree distributions of the social networks are shown to approximate to a power law with exponential cutoff. The node representing Moses is very highly connected and falls outside the best fit line, as does the node representing Yahweh, which may indicate authorial emphasis. Only the social network from Genesis is assortative, a property typical of many real world social networks. A substantial proportion of disassortativity in the social network based around Moses disappears when the node is removed, potentially indicating some artificiality in its orientation within the network. The approximation of the degree distributions to a power law with exponential cutoff represents an emergent property resulting from the combinatorial and collaborative manner of composition, and indicates a bounding constraint on more highly connected nodes. Unusually highly connected nodes representing the deity and prophet may be characteristic of social networks derived from religious texts.

The neutral emergence of error minimized genetic codes superior to the standard genetic code

The standard genetic code (SGC) assigns amino acids to codons in such a way that the impact of point mutations is reduced, this is termed 'error minimization' (EM). The occurrence of EM has been attributed to the direct action of selection, however it is difficult to explain how the searching of alternative codes for an error minimized code can occur via codon reassignments, given that these are likely to be disruptive to the proteome. An alternative scenario is that EM has arisen via the process of genetic code expansion, facilitated by the duplication of genes encoding charging enzymes and adaptor molecules. This is likely to have led to similar amino acids being assigned to similar codons. Strikingly, we show that if during code expansion the most similar amino acid to the parent amino acid, out of the set of unassigned amino acids, is assigned to codons related to those of the parent amino acid, then genetic codes with EM superior to the SGC easily arise. This scheme mimics code expansion via the gene duplication of charging enzymes and adaptors. The result is obtained for a variety of different schemes of genetic code expansion and provides a mechanistically realistic manner in which EM has arisen in the SGC. These observations might be taken as evidence for self-organization in the earliest stages of life.

DNA Repair Is Associated with Information Content in Bacteria, Archaea, and DNA Viruses

The concept of a "proteomic constraint" proposes that DNA repair capacity is positively correlated with the information content of a genome, which can be approximated to the size of the proteome (P). This in turn implies that DNA repair genes are more likely to be present in genomes with larger values of P. This stands in contrast to the common assumption that informational genes have a core function and so are evenly distributed across organisms. We examined the presence/absence of 18 DNA repair genes in bacterial genomes. A positive relationship between gene presence and P was observed for 17 genes in the total dataset, and 16 genes when only nonintracellular bacteria were examined. A marked reduction of DNA repair genes was observed in intracellular bacteria, consistent with their reduced value of P. We also examined archaeal and DNA virus genomes, and show that the presence of DNA repair genes is likewise related to a larger value of P. In addition, the products of the bacterial genes mutY, vsr, and ndk, involved in the correction of GC/AT mutations, are strongly associated with reduced genome GC content. We therefore propose that a reduction in information content leads to a loss of DNA repair genes and indirectly to a reduction in genome GC content in bacteria by exposure to the underlying AT mutation bias. The reduction in P may also indirectly lead to the increase in substitution rates observed in intracellular bacteria via loss of DNA repair genes.

DNA/RNA transverse current sequencing: intrinsic structural noise from neighboring bases

Nanopore DNA sequencing via transverse current has emerged as a promising candidate for third-generation sequencing technology. It produces long read lengths which could alleviate problems with assembly errors inherent in current technologies. However, the high error rates of nanopore sequencing have to be addressed. A very important source of the error is the intrinsic noise in the current arising from carrier dispersion along the chain of the molecule, i.e., from the influence of neighboring bases. In this work we perform calculations of the transverse current within an effective multi-orbital tight-binding model derived from first-principles calculations of the DNA/RNA molecules, to study the effect of this structural noise on the error rates in DNA/RNA sequencing via transverse current in nanopores. We demonstrate that a statistical technique, utilizing not only the currents through the nucleotides but also the correlations in the currents, can in principle reduce the error rate below any desired precision.

Genetic code evolution reveals the neutral emergence of mutational robustness, and information as an evolutionary constraint

The standard genetic code (SGC) is central to molecular biology and its origin and evolution is a fundamental problem in evolutionary biology, the elucidation of which promises to reveal much about the origins of life. In addition, we propose that study of its origin can also reveal some fundamental and generalizable insights into mechanisms of molecular evolution, utilizing concepts from complexity theory. The first is that beneficial traits may arise by non-adaptive processes, via a process of "neutral emergence". The structure of the SGC is optimized for the property of error minimization, which reduces the deleterious impact of point mutations. Via simulation, it can be shown that genetic codes with error minimization superior to the SGC can emerge in a neutral fashion simply by a process of genetic code expansion via tRNA and aminoacyl-tRNA synthetase duplication, whereby similar amino acids are added to codons related to that of the parent amino acid. This process of neutral emergence has implications beyond that of the genetic code, as it suggests that not all beneficial traits have arisen by the direct action of natural selection; we term these "pseudaptations", and discuss a range of potential examples. Secondly, consideration of genetic code deviations (codon reassignments) reveals that these are mostly associated with a reduction in proteome size. This code malleability implies the existence of a proteomic constraint on the genetic code, proportional to the size of the proteome (P), and that its reduction in size leads to an "unfreezing" of the codon - amino acid mapping that defines the genetic code, consistent with Crick's Frozen Accident theory. The concept of a proteomic constraint may be extended to propose a general informational constraint on genetic fidelity, which may be used to explain variously, differences in mutation rates in genomes with differing proteome sizes, differences in DNA repair capacity and genome GC content between organisms, a selective pressure in the evolution of sexual reproduction, and differences in translational fidelity. Lastly, the utility of the concept of an informational constraint to other diverse fields of research is explored.

SmileFinder: a resampling-based approach to evaluate signatures of selection from genome-wide sets of matching allele frequency data in two or more diploid populations

BACKGROUND

Adaptive alleles may rise in frequency as a consequence of positive selection, creating a pattern of decreased variation in the neighboring loci, known as a selective sweep. When the region containing this pattern is compared to another population with no history of selection, a rise in variance of allele frequencies between populations is observed. One challenge presented by large genome-wide datasets is the ability to differentiate between patterns that are remnants of natural selection from those expected to arise at random and/or as a consequence of selectively neutral demographic forces acting in the population.

FINDINGS

SmileFinder is a simple program that looks for diversity and divergence patterns consistent with selection sweeps by evaluating allele frequencies in windows, including neighboring loci from two or more populations of a diploid species against the genome-wide neutral expectation. The program calculates the mean of heterozygosity and FST in a set of sliding windows of incrementally increasing sizes, and then builds a resampled distribution (the baseline) of random multi-locus sets matched to the sizes of sliding windows, using an unrestricted sampling. Percentiles of the values in the sliding windows are derived from the superimposed resampled distribution. The resampling can easily be scaled from 1 K to 100 M; the higher the number, the more precise the percentiles ascribed to the extreme observed values.

CONCLUSIONS

The output from SmileFinder can be used to plot percentile values to look for population diversity and divergence patterns that may suggest past actions of positive selection along chromosome maps, and to compare lists of suspected candidate genes under random gene sets to test for the overrepresentation of these patterns among gene categories. Both applications of the algorithm have already been used in published studies. Here we present a publicly available, open source program that will serve as a useful tool for preliminary scans of selection using worldwide databases of human genetic variation, as well as population datasets for many non-human species, from which such data is rapidly emerging with the advent of new genotyping and sequencing technologies.

HIV gp120 sequence variability associated with HAND in Hispanic Women

OBJECTIVE

HIV-1 variants with different tropisms are associated with various neuropathologies. This study intends to determine if this correlation is determined by unique viral env sequences. We hypothesize that HIV-1 envelope gene sequence changes are associated with cognition status.

METHODS

Viral RNA was extracted from peripheral blood mononuclear cells (PBMCs) co-cultures derived from HIV-1 infected Hispanic women that had been characterized for HIV associated neurocognitive disorders (HAND).

RESULTS

Analyses of the C2V4 region of HIV gp120 demonstrated that increased sequence diversity correlates with cognition status as sequences derived from subjects with normal cognition exhibited less diversity than sequences derived from subjects with cognitive impairment. In addition, differences in V3 and V4 loop charges were also noted as well as differences in the N-glycosylation of the V4 region.

CONCLUSIONS

Our data suggest that the genetic signature within the C2V4 region may contribute to the pathogenesis of HAND. HIV env sequence characteristics for the isolates grouped in milder forms of HAND can provide insightful information of prognostic value to assess neurocognitive status in HIV⁺ subjects, particularly during the era of highly prevalent milder forms of HAND.

Paleomicrobiology: revealing fecal microbiomes of ancient indigenous cultures

Coprolites are fossilized feces that can be used to provide information on the composition of the intestinal microbiota and, as we show, possibly on diet. We analyzed human coprolites from the Huecoid and Saladoid cultures from a settlement on Vieques Island, Puerto Rico. While more is known about the Saladoid culture, it is believed that both societies co-existed on this island approximately from 5 to 1170 AD. By extracting DNA from the coprolites, followed by metagenomic characterization, we show that both cultures can be distinguished from each other on the basis of their bacterial and fungal gut microbiomes. In addition, we show that parasite loads were heavy and also culturally distinct. Huecoid coprolites were characterized by maize and Basidiomycetes sequences, suggesting that these were important components of their diet. Saladoid coprolite samples harbored sequences associated with fish parasites, suggesting that raw fish was a substantial component of their diet. The present study shows that ancient DNA is not entirely degraded in humid, tropical environments, and that dietary and/or host genetic differences in ancient populations may be reflected in the composition of their gut microbiome. This further supports the hypothesis that the two ancient cultures studied were distinct, and that they retained distinct technological/cultural differences during an extended period of close proximity and peaceful co-existence. The two populations seemed to form the later-day Taínos, the Amerindians present at the point of Columbian contact. Importantly, our data suggest that paleomicrobiomics can be a powerful tool to assess cultural differences between ancient populations.

A nonadaptive origin of a beneficial trait: in silico selection for free energy of folding leads to the neutral emergence of mutational robustness in single domain proteins

Proteins are regarded as being robust to the deleterious effects of mutations. Here, the neutral emergence of mutational robustness in a population of single domain proteins is explored using computer simulations. A pairwise contact model was used to calculate the ΔG of folding (ΔG folding) using the three dimensional protein structure of leech eglin C. A random amino acid sequence with low mutational robustness, defined as the average ΔΔG resulting from a point mutation (ΔΔG average), was threaded onto the structure. A population of 1,000 threaded sequences was evolved under selection for stability, using an upper and lower energy threshold. Under these conditions, mutational robustness increased over time in the most common sequence in the population. In contrast, when the wild type sequence was used it did not show an increase in robustness. This implies that the emergence of mutational robustness is sequence specific and that wild type sequences may be close to maximal robustness. In addition, an inverse relationship between ∆∆G average and protein stability is shown, resulting partly from a larger average effect of point mutations in more stable proteins. The emergence of mutational robustness was also observed in the Escherichia coli colE1 Rop and human CD59 proteins, implying that the property may be common in single domain proteins under certain simulation conditions. The results indicate that at least a portion of mutational robustness in small globular proteins might have arisen by a process of neutral emergence, and could be an example of a beneficial trait that has not been directly selected for, termed a "pseudaptation."

Sociomicrobiome of wood decay in a tropical rain forest: unraveling complexity

Given that microbial interactions in nature are very complex, we propose that quorum-sensing, as well as quorum-quenching, phenazine and secondary metabolite production, resistance and toxin-antitoxin systems within a microbial community should all comprise the battery of processes involving the study of what we would define as the “sociomicrobiome”. In the present study the genes/molecules, subsystems and taxonomic breakup of the mentioned processes were identified in decaying tropical wood from the El Yunque rainforest in Puerto Rico, and soil using a shotgun metagenomic approach. The rapid decomposition of wood and litter in tropical regions suggests that processes in these settings are governed by unexplored microbes with the potential of being further studied and exploited for various purposes. Both ecosystems were characterized by the presence of specific genes/molecules, subsystems and microbes associated with the mentioned processes, although the average abundances for specific processes differed. Of the sociomicrobiomes studied, that from El Yunque was found to be the most complex. The approach considered in the present study could also be applied to study the sociomicrobiome of other ecosystems.

What can information-asymmetric games tell us about the context of Crick's 'frozen accident'?

This paper describes a novel application of information-asymmetric (signalling) games to molecular biology in which utility is determined by the message complexity (rate) in addition to the error in information transfer (distortion). We show using a computational model how it is possible for the agents in one such game to evolve a signalling convention (separating equilibrium) that is suboptimal in terms of information transfer, but is nonetheless stable. In the context of an RNA world merging with a nascent amino acid one, such a game's equilibrium is alluded to by the genetic code, which is nearly optimal in terms of information transfer, but is also near-universal and nearly immutable. Such a framework suggests that cellularity may have emerged to encourage coordination between RNA species and sheds light on other aspects of RNA world biochemistry yet to be fully understood.

The distribution of recombination repair genes is linked to information content in bacteria

The concept of a 'proteomic constraint' proposes that the information content of the proteome exerts a selective pressure to reduce mutation rates, implying that larger proteomes produce a greater selective pressure to evolve or maintain DNA repair, resulting in a decrease in mutational load. Here, the distribution of 21 recombination repair genes was characterized across 900 bacterial genomes. Consistent with prediction, the presence of 17 genes correlated with proteome size. Intracellular bacteria were marked by a pervasive absence of recombination repair genes, consistent with their small proteome sizes, but also consistent with alternative explanations that reduced effective population size or lack of recombination may decrease selection pressure. However, when only non-intracellular bacteria were examined, the relationship between proteome size and gene presence was maintained. In addition, the more widely distributed (i.e. conserved) a gene, the smaller the average size of the proteomes from which it was absent. Together, these observations are consistent with the operation of a proteomic constraint on DNA repair. Lastly, a correlation between gene absence and genome AT content was shown, indicating a link between absence of DNA repair and elevated genome AT content.

The Presence of the DNA Repair Genes mutM, mutY, mutL, and mutS is Related to Proteome Size in Bacterial Genomes

DNA repair is expected to be a modulator of underlying mutation rates, however the major factors affecting the distribution of DNA repair pathways have not been determined. The Proteomic Constraint theory proposes that mutation rates are inversely proportional to the amount of heredity information contained in a genome, which is effectively the proteome. Thus, organisms with larger proteomes are expected to possess more efficient DNA repair. We show that an important factor influencing the presence or absence of four DNA repair genes mutM, mutY, mutL, and mutS is indeed the size of the bacterial proteome. This is true both of intracellular and other bacteria. In addition, the relationship of DNA repair to genome GC content was examined. In principle, if a DNA repair pathway is biased in the types of mutations it corrects, this may alter the genome GC content. The presence of the mismatch repair genes mutL and mutS was not correlated with genome GC content, consistent with their involvement in an unbiased DNA repair pathway. In contrast, the presence of the base excision repair genes mutM and mutY, whose products both correct GC → AT mutations, was positively correlated with genome GC content, consistent with their biased repair mechanism. Phylogenetic analysis however indicates that the relationship between the presence of mutM and mutY genes and genome GC content is not a simple one.

Positive selection on a bacterial oncoprotein associated with gastric cancer

Background

Helicobacter pylori is a vertically inherited gut commensal that is carcinogenic if it possesses the cag pathogenicity island (cag PaI); infection with H.pylori is the major risk factor for gastric cancer, the second leading cause of death from cancer worldwide (WHO). The cag PaI locus encodes the cagA gene, whose protein product is injected into stomach epithelial cells via a Type IV secretion system, also encoded by the cag PaI. Once there, the cagA protein binds to various cellular proteins, resulting in dysregulation of cell division and carcinogenesis. For this reason, cagA may be described as an oncoprotein. A clear understanding of the mechanism of action of cagA and its benefit to the bacteria is lacking.

Lineage-specific differences in the amino acid substitution process

In Darwinian evolution, mutations occur approximately at random in a gene, turned into amino acid mutations by the genetic code. Some mutations are fixed to become substitutions and some are eliminated from the population. Partitioning pairs of closely related species with complete genome sequences by average population size of each pair, we looked at the substitution matrices generated for these partitions and compared the substitution patterns between species. We estimated a population genetic model that relates the relative fixation probabilities of different types of mutations to the selective pressure and population size. Parameterizations of the average and distribution of selective pressures for different amino acid substitution types in different population size comparisons were generated with a Bayesian framework. We found that partitions in population size as well as in substitution type are required to explain the substitution data. Selection coefficients were found to decrease with increasingly radical amino acid substitution and with increasing effective population size. To further explore the role of underlying processes in amino acid substitution, we analyzed embryophyte (plant) gene families from TAED (The Adaptive Evolution Database), where solved structures for at least one member exist in the Protein Data Bank. Using PAML, we assigned branches to three categories: strong negative selection, moderate negative selection/neutrality, and positive diversifying selection. Focusing on the first and third categories, we identified sites changing along gene family lineages and observed the spatial patterns of substitution. Selective sweeps were expected to create primary sequence clustering under positive diversifying selection. Co-evolution through direct physical interaction was expected to cause tertiary structural clustering. Under both positive and negative selection, the substitution patterns were found to be nonrandom. Under positive diversifying selection, significant independent signals were found for primary and tertiary sequence clustering, suggesting roles for both selective sweeps and direct physical interaction. Under strong negative selection, the signals were not found to be independent. All together, a complex interplay of population genetic and protein thermodynamics forces is suggested.

ScanMoment: a web server for combinatorial analysis of basic residues in nucleic acid binding sites

ScanMoment is a webserver designed to identify the presence of the basic faced alpha-helix (BFAH) motif in the nucleic acid binding sites of proteins. The program calculates the 'Basic Moment', a parameter that quantitizes the distribution of basic residues on the surface of an alpha-helix. A sliding window is used to generate a plot displaying regions of the protein sequence that possesses a high Basic Moment and hus likely to possess a BFAH motif. The user may vary the periodicity from that of an alpha-helix (100 degrees ), to those of other secondary structures such as beta sheets and 3(10) helices. The program can also plot the periodicity of basic residues in a protein sequence using a Fourier transformation. The procedure has been used to characterize the presence of BFAHs in the N-terminal extensions of the eukaryotic aminoacyl-tRNA synthetases and to indicate the presence of a BFAH in the tRNA binding site of alanyl-tRNA synthetase.

AVAILABILITY

www.scanmoment.org.

The proteomic constraint and its role in molecular evolution

Recently, the concept of a "Proteomic Constraint" was introduced to explain the frequency of genetic code deviations in mitochondrial genomes. The Proteomic Constraint was proposed to be proportional to the size of the mitochondrially encoded proteome, hence small proteomes are expected to experience smaller total numbers of errors resulting from genetic code deviations, leading to less likelihood of causing lethality. The concept is now extended to encompass several other aspects of the genetic information system. When the Proteomic Constraint is small, it is proposed that there is little selective pressure to evolve or maintain error correction mechanisms, as a result of the smaller total number of errors that accumulate. Conversely, a large Proteomic Constraint is proposed to result in a correspondingly large selective pressure to evolve or maintain error correction mechanisms. Differences in the size of the Proteomic Constraint can help to explain differences in replicational, transcriptional, and translational fidelities between genomes. A key piece of evidence is the existence of negative power law relationships between proteome size and error rates; these are demonstrated to be diagnostic of the action of the Proteomic Constraint. The Proteomic Constraint is argued to be a major factor determining mutation rates in a diverse range of DNA genomes, implying that mutation rates are clock like. A small Proteomic Constraint partly explains why RNA viruses possess high mutation rates. A reduced Proteomic Constraint in intracellular pathogenic bacteria predicts a drift upwards in mutation rates. Differences in the Proteomic Constraint also appear to be linked to differences in recombination rates between eukaryotes. In addition, a reduced Proteomic Constraint may explain features of resident genomes, such as loss of DNA repair pathways, increased substitution rates, and AT biases, in addition to the occurrence of genetic code deviations. Thus, it is argued that the Proteomic Constraint is a universal factor that influences a wide range of properties of the genetic information system.

A comparative genomics analysis of codon reassignments reveals a link with mitochondrial proteome size and a mechanism of genetic code change via suppressor tRNAs

Using a comparative genomics approach we demonstrate a negative correlation between the number of codon reassignments undergone by 222 mitochondrial genomes and the mitochondrial genome size, the number of mitochondrial ORFs, and the sizes of the large and small subunit mitochondrial rRNAs. In addition, we show that the TGA-to-tryptophan codon reassignment, which has occurred 11 times in mitochondrial genomes, is found in mitochondrial genomes smaller than those which have not undergone the reassignment. We therefore propose that mitochondrial codon reassignments occur in a wide range of phyla, particularly in Metazoa, due to a reduced "proteomic constraint" on the mitochondrial genetic code, compared to the nuclear genetic code. The reduced proteomic constraint reflects the small size of the mitochondrial-encoded proteome and allows codon reassignments to occur with less likelihood of lethality. In addition, we demonstrate a striking link between nonsense codon reassignments and the decoding properties of naturally occurring nonsense suppressor tRNAs. This suggests that natural preexisting nonsense suppression facilitated nonsense codon reassignments and constitutes a novel mechanism of genetic code change. These findings explain for the first time the identity of the stop codons and amino acids reassigned in mitochondrial and nuclear genomes. Nonsense suppressor tRNAs provided the raw material for nonsense codon reassignments, implying that the properties of the tRNA anticodon have dictated the identity of nonsense codon reassignments.

The genome of deep-sea vent chemolithoautotroph Thiomicrospira crunogena XCL-2

Presented here is the complete genome sequence of Thiomicrospira crunogena XCL-2, representative of ubiquitous chemolithoautotrophic sulfur-oxidizing bacteria isolated from deep-sea hydrothermal vents. This gammaproteobacterium has a single chromosome (2,427,734 base pairs), and its genome illustrates many of the adaptations that have enabled it to thrive at vents globally. It has 14 methyl-accepting chemotaxis protein genes, including four that may assist in positioning it in the redoxcline. A relative abundance of coding sequences (CDSs) encoding regulatory proteins likely control the expression of genes encoding carboxysomes, multiple dissolved inorganic nitrogen and phosphate transporters, as well as a phosphonate operon, which provide this species with a variety of options for acquiring these substrates from the environment. Thiom. crunogena XCL-2 is unusual among obligate sulfur-oxidizing bacteria in relying on the Sox system for the oxidation of reduced sulfur compounds. The genome has characteristics consistent with an obligately chemolithoautotrophic lifestyle, including few transporters predicted to have organic allocrits, and Calvin-Benson-Bassham cycle CDSs scattered throughout the genome.

Basic faced alpha-helices are widespread in the peptide extensions of the eukaryotic aminoacyl-tRNA synthetases

Three aminoacyl-tRNA synthetases from yeast, one from plants and one from mammals possess unusual structures at their N termini, namely alpha helices with basic residues distributed asymmetrically, on a single face of the helix. It is unknown if these 'basic faced' alpha helices (BFAHs) are unique to the aminoacyl-tRNA synthetases. Analysis of the amino acid sequences of these five aminoacyl-tRNA synthetases using the hydrophobic moment algorithm failed to accurately identify the BFAHs. A new algorithm was therefore developed, called the 'basic moment'. This is a Fourier analysis procedure that predicts the distribution of basic residues within protein secondary structure. The basic moment identifies with a high degree of accuracy the five known BFAHs and also identifies further potential BFAHs at evolutionarily conserved positions in the peptide extensions of aspartyl-, lysyl- and valyl- tRNA synthetases from a range of eukaryotic species. In addition, the algorithm identifies the two-helix pair tRNA binding domain of alanyl-tRNA synthetase, implying that the domain includes a BFAH. The functional and evolutionary aspects of these structural features are discussed.

Microscopic, biochemical, and molecular characteristics of the Chilean Blob and a comparison with the remains of other sea monsters: nothing but whales

We have employed electron microscopic, biochemical, and molecular techniques to clarify the species of origin of the "Chilean Blob," the remains of a large sea creature that beached on the Chilean coast in July 2003. Electron microscopy revealed that the remains are largely composed of an acellular, fibrous network reminiscent of the collagen fiber network in whale blubber. Amino acid analyses of an acid hydrolysate indicated that the fibers are composed of 31% glycine residues and also contain hydroxyproline and hydroxylysine, all diagnostic of collagen. Using primers designed to the mitochondrial gene nad2, an 800-bp product of the polymerase chain reaction (PCR) was amplified from DNA that had been purified from the carcass. The DNA sequence of the PCR product was 100% identical to nad2 of sperm whale (Physeter catadon). These results unequivocally demonstrate that the Chilean Blob is the almost completely decomposed remains of the blubber layer of a sperm whale. This identification is the same as those we have obtained before from other relics such as the so-called giant octopus of St. Augustine (Florida), the Tasmanian West Coast Monster, two Bermuda Blobs, and the Nantucket Blob. It is clear now that all of these blobs of popular and cryptozoological interest are, in fact, the decomposed remains of large cetaceans.

Driving change: the evolution of alternative genetic codes

Pioneering studies in the 1960s that elucidated the genetic code suggested that all extant forms of life use the same genetic code. This early presumption has subsequently been challenged by the discovery of deviations of the universal genetic code in prokaryotes, eukaryotic nuclear genomes and mitochondrial genomes. These studies have revealed that the genetic code is still evolving despite strong negative forces working against the fixation of mutations that result in codon reassignment. Recent data from in vitro, in vivo and in silico comparative genomics studies are revealing significant, previously overlooked links between modified nucleosides in tRNAs, genetic code ambiguity, genome base composition, codon usage and codon reassignment.

Comparative evolutionary genomics unveils the molecular mechanism of reassignment of the CTG codon in Candida spp

Using the (near) complete genome sequences of the yeasts Candida albicans, Saccharomyces cerevisiae, and Schizosaccharomyces pombe, we address the evolution of a unique genetic code change, which involves decoding of the standard leucine-CTG codon as serine in Candida spp. By using two complementary comparative genomics approaches, we have been able to shed new light on both the origin of the novel Candida spp. Ser-tRNA(CAG), which has mediated CTG reassignment, and on the evolution of the CTG codon in the genomes of C. albicans, S. cerevisiae, and S. pombe. Sequence analyses of newly identified tRNAs from the C. albicans genome demonstrate that the Ser-tRNA(CAG) is derived from a serine and not a leucine tRNA in the ancestor yeast species and that this codon reassignment occurred approximately 170 million years ago, but the origin of the Ser-tRNA(CAG) is more ancient, implying that the ancestral Leu-tRNA that decoded the CTG codon was lost after the appearance of the Ser-tRNA(CAG). Ambiguous CTG decoding by the Ser-tRNA(CAG) combined with biased AT pressure forced the evolution of CTG into TTR codons and have been major forces driving evolution of the CTN codon family in C. albicans. Remarkably, most of the CTG codons present in extant C. albicans genes are encoded by serine and not leucine codons in homologous S. cerevisiae and S. pombe genes, indicating that a significant number of serine TCN and AGY codons evolved into CTG codons either directly by simultaneous double mutations or indirectly through an intermediary codon. In either case, CTG reassignment had a major impact on the evolution of the coding component of the Candida spp. genome.