Protein co-evolution, co-adaptation and interactions

Insights into structure, codon usage, repeats, and RNA editing of the complete mitochondrial genome of Perilla frutescens (Lamiaceae)

Perilla frutescens (L.) Britton, a member of the Lamiaceae family, stands out as a versatile plant highly valued for its unique aroma and medicinal properties. Additionally, P. frutescens seeds are rich in Îś-linolenic acid, holding substantial economic importance. While the nuclear and chloroplast genomes of P. frutescens have already been documented, the complete mitochondrial genome sequence remains unreported. To this end, the sequencing, annotation, and assembly of the entire Mitochondrial genome of P. frutescens were hereby conducted using a combination of Illumina and PacBio data. The assembled P. frutescens mitochondrial genome spanned 299,551 bp and exhibited a typical circular structure, involving a GC content of 45.23%. Within the genome, a total of 59 unique genes were identified, encompassing 37 protein-coding genes, 20 tRNA genes, and 2 rRNA genes. Additionally, 18 introns were observed in 8 protein-coding genes. Notably, the codons of the P. frutescens mitochondrial genome displayed a notable A/T bias. The analysis also revealed 293 dispersed repeat sequences, 77 simple sequence repeats (SSRs), and 6 tandem repeat sequences. Moreover, RNA editing sites preferentially produced leucine at amino acid editing sites. Furthermore, 70 sequence fragments (12,680 bp) having been transferred from the chloroplast to the mitochondrial genome were identified, accounting for 4.23% of the entire mitochondrial genome. Phylogenetic analysis indicated that among Lamiaceae plants, P. frutescens is most closely related to Salvia miltiorrhiza and Platostoma chinense. Meanwhile, inter-species Ka/Ks results suggested that Ka/Ks < 1 for 28 PCGs, indicating that these genes were evolving under purifying selection. Overall, this study enriches the mitochondrial genome data for P. frutescens and forges a theoretical foundation for future molecular breeding research.

A synthesis of coevolution across levels of biological organization

In evolutionary ecology, coevolution is typically defined as reciprocal evolution of interacting species. However, outside the context of interacting species, the term "coevolution" is also used at levels of biological organization within species (e.g., between males and females, between cells, and between genes or proteins). Furthermore, although evolution is typically defined as "genetic change over time", coevolution need not involve genetic changes in the interacting parties, since cultures can also evolve. In this review, I propose that coevolution be defined more broadly as "reciprocal adaptive evolution at any level of biological organisation". The classification of reciprocal evolution at all levels of biological organization as coevolution would maintain consistency in terminology. More importantly, the broader definition should facilitate greater integration of coevolution research across disciplines. For example, principles usually discussed only in the context of coevolution between species or coevolution between genes (e.g., tight and diffuse coevolution, and compensatory coevolution, respectively) could be more readily applied to new fields. The application of coevolutionary principles to new contexts could also provide benefits to society, for instance in deducing the dynamics of coevolution between cancer cells and cells of the human immune system.

Coevolution-based computational approach to detect resistance mechanism of epidermal growth factor receptor

Tyrosine kinase epidermal growth factor receptor (EGFR) correlates the neoplastic cell metastasis, angiogenesis, neoplastic incursion, and apoptosis. Due to the involvement of EGFR in these biological processes, it becomes a most potent target for treating non-small cell lung cancer (NSCLC). The tyrosine kinase inhibitors (TKI) have endorsed high efficacy and anticipation to patients but unfortunately, within a year of treatment, drug targets develop resistance due to mutations. The present study detected the compensatory mutations in EGFR to know the evolutionary mechanism of drug resistance. The results of this study demonstrate that compensatory mutations enlarge the drug-binding pocket which may lead to the altered orientation of the ligand (gefitinib and erlotinib) causing drug resistance. This indicates that coevolutionary forces play a significant role in fine-tuning the structure of EGFR protein against the drugs. The analysis provides insight into the evolution-induced structural aspects of drug resistance changes in EGFR which in turn be useful in designing drugs with better efficacy.

Assembly and phylogenetic analysis of the mitochondrial genome of endangered medicinal plant Huperzia crispata

Huperzia crispata is a traditional Chinese herb plant and has attracted special attention in recent years for its products Hup A can serve as an acetylcholinesterase inhibitor (AChEI). Although the chloroplast (cp) genome of H. crispata has been studied, there are no reports regarding the Huperzia mitochondrial (mt) genome since the previously reported H. squarrosa has been revised as Phlegmariurus squarrosus. The mt genome of H. crispata was sequenced using a combination of long-read nanopore and Illumina sequencing platforms. The entire H. crispata mt genome was assembled in a circular with a length of 412,594 bp and a total of 91 genes, including 45 tRNAs, 6 rRNAs, 37 protein-coding genes (PCGs), and 3 pseudogenes. Notably, the rps8 gene was present in P. squarrosus and a pseudogene rps8 was presented in H. crispata, which was lacking in most of Pteridophyta and Gymnospermae. Intron-encoded maturase (mat-atp9i85 and mat-cobi787) genes were present in H. crispata and P. squarrosus, but lost in other examined lycophytes, ferns, and Gymnospermae plants. Collinearity analysis showed that the mt genome of H. crispata and P. squarrossus is highly conservative compared to other ferns. Relative synonymous codon usage (RSCU) analysis showed that the amino acids most frequently found were phenylalanine (Phe) (4.77%), isoleucine (Ile) (4.71%), lysine (Lys) (4.26%), while arginine (Arg) (0.32%), and histidine (His) (0.42%) were rarely found. Simple sequence repeats (SSR) analysis revealed that a total of 114 SSRs were identified in the mt genome of H. crispata and account for 0.35% of the whole mt genome. Monomer repeats were the majority types of SSRs and represent 91.89% of the total SSRs. In addition, a total of 1948 interspersed repeats (158 forward, 147 palindromic, and 5 reverse repeats) with a length ranging from 30 bp to 14,945 bp were identified in the H. crispata mt genome and the 30-39-bp repeats were the most abundant type. Gene transfer analysis indicated that a total of 12 homologous fragments were discovered between the cp and mt genomes of H. crispata, accounting for 0.93% and 2.48% of the total cp and mt genomes, respectively. The phylogenetic trees revealed that H. crispata was the sister of P. squarrosus. The Ka/Ks analysis results suggested that most PCGs, except atp6 gene, were subject to purification selection during evolution. Our study provides extensive information on the features of the H. crispata mt genome and will help unravel evolutionary relationships, and molecular identification within lycophytes.

Toward novel treatment against filariasis: Insight into genome-wide co-evolutionary analysis of filarial nematodes and Wolbachia

Infectious diseases caused by filarial nematodes are major health problems for humans and animals globally. Current treatment using anti-helminthic drugs requires a long treatment period and is only effective against the microfilarial stage. Most species of filarial nematodes harbor a specific strain of Wolbachia bacteria, which are essential for the survival, development, and reproduction of the nematodes. This parasite-bacteria obligate symbiosis offers a new angle for the cure of filariasis. In this study, we utilized publicly available genome data and putative protein sequences from seven filarial nematode species and their symbiotic Wolbachia to screen for protein-protein interactions that could be a novel target against multiple filarial nematode species. Genome-wide in silico screening was performed to predict molecular interactions based on co-evolutionary signals. We identified over 8,000 pairs of gene families that show evidence of co-evolution based on high correlation score and low false discovery rate (FDR) between gene families and obtained a candidate list that may be keys in filarial nematode-Wolbachia interactions. Functional analysis was conducted on these top-scoring pairs, revealing biological processes related to various signaling processes, adult lifespan, developmental control, lipid and nucleotide metabolism, and RNA modification. Furthermore, network analysis of the top-scoring genes with multiple co-evolving pairs suggests candidate genes in both Wolbachia and the nematode that may play crucial roles at the center of multi-gene networks. A number of the top-scoring genes matched well to known drug targets, suggesting a promising drug-repurposing strategy that could be applicable against multiple filarial nematode species.

Assembly and comparative analysis of the complete mitochondrial genome of Bupleurum chinense DC

BACKGROUND

Bupleurum chinense(B. chinense) is a plant that is widely distributed globally and has strong pharmacological effects. Though the chloroplast(cp) genome of B. chinense has been studied, no reports regarding the mitochondrial(mt) genome of B. chinense have been published yet.

RESULTS

The mt genome of B.chinense was assembled and functionally annotated. The circular mt genome of B. chinense was 435,023 bp in length, and 78 genes, including 39 protein-coding genes, 35 tRNA genes, and 4 rRNA genes, were annotated. Repeat sequences were analyzed and sites at which RNA editing would occur were predicted. Gene migration was observed to occur between the mt and cp genomes of B. chinense via the detection of homologous gene fragments. In addition, the sizes of plant mt genomes and their GC content were analyzed and compared. The sizes of mt genomes of plants varied greatly, but their GC content was conserved to a greater extent during evolution. Ka/Ks analysis was based on code substitutions, and the results showed that most of the coding genes were negatively selected. This indicates that mt genes were conserved during evolution.

CONCLUSION

In this study, we assembled and annotated the mt genome of the medicinal plant B. chinense. Our findings provide extensive information regarding the mt genome of B. chinense, and help lay the foundation for future studies on the genetic variations, phylogeny, and breeding of B. chinense via an analysis of the mt genome.

Intermolecular interactions drive protein adaptive and co-adaptive evolution at both species and population levels

Proteins are the building blocks for almost all the functions in cells. Understanding the molecular evolution of proteins and the forces that shape protein evolution is essential in understanding the basis of function and evolution. Previous studies have shown that adaptation frequently occurs at the protein surface, such as in genes involved in host–pathogen interactions. However, it remains unclear whether adaptive sites are distributed randomly or at regions associated with particular structural or functional characteristics across the genome, since many proteins lack structural or functional annotations. Here, we seek to tackle this question by combining large-scale bioinformatic prediction, structural analysis, phylogenetic inference, and population genomic analysis of Drosophila protein-coding genes. We found that protein sequence adaptation is more relevant to function-related rather than structure-related properties. Interestingly, intermolecular interactions contribute significantly to protein adaptation. We further showed that intermolecular interactions, such as physical interactions, may play a role in the coadaptation of fast-adaptive proteins. We found that strongly differentiated amino acids across geographic regions in protein-coding genes are mostly adaptive, which may contribute to the long-term adaptive evolution. This strongly indicates that a number of adaptive sites tend to be repeatedly mutated and selected throughout evolution in the past, present, and maybe future. Our results highlight the important roles of intermolecular interactions and coadaptation in the adaptive evolution of proteins both at the species and population levels.

The coevolution of large and small terminases of bacteriophages is a result of purifying selection leading to phenotypic stabilization

Genome packaging in many dsDNA phages requires a series of precisely coordinated actions of two phage-coded proteins, namely, large terminase (TerL) and small terminase (TerS) with DNA and ATP, and with each other. Despite the strict functional conservation, TerL and TerS homologs exhibit large sequence variations. We investigated the sequence variability across eight phage types and observed a coevolutionary framework wherein the genealogy of TerL homologs mirrored that of the corresponding TerS homologs. Furthermore, a high purifying selection observed (dN/dS«1) indicated strong structural constraints on both TerL and TerS, and identify coevolving residues in TerL and TerS of phage T4 and lambda. Using the highly coevolving (correlation coefficient of 0.99) TerL and TerS of phage N4, we show that their biochemical features are similar to the phylogenetically divergent phage λ terminases. We also demonstrate using the Surface Plasma Resonance (SPR) technique that phage N4 TerL transiently interacts with TerS.

ProteinEvolverABC: coestimation of recombination and substitution rates in protein sequences by approximate Bayesian computation

MOTIVATION

The evolutionary processes of mutation and recombination, upon which selection operates, are fundamental to understand the observed molecular diversity. Unlike nucleotide sequences, the estimation of the recombination rate in protein sequences has been little explored, neither implemented in evolutionary frameworks, despite protein sequencing methods are largely used.

RESULTS

In order to accommodate this need, here I present a computational framework, called ProteinEvolverABC, to jointly estimate recombination and substitution rates from alignments of protein sequences. The framework implements the approximate Bayesian computation approach, with and without regression adjustments and includes a variety of substitution models of protein evolution, demographics and longitudinal sampling. It also implements several nuisance parameters such as heterogeneous amino acid frequencies and rate of change among sites and, proportion of invariable sites. The framework produces accurate coestimation of recombination and substitution rates under diverse evolutionary scenarios. As illustrative examples of usage, I applied it to several viral protein families, including coronaviruses, showing heterogeneous substitution and recombination rates.

AVAILABILITY AND IMPLEMENTATION

ProteinEvolverABC is freely available from https://github.com/miguelarenas/proteinevolverabc, includes a graphical user interface for helping the specification of the input settings, extensive documentation and ready-to-use examples. Conveniently, the simulations can run in parallel on multicore machines.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

PPIDomainMiner: Inferring domain-domain interactions from multiple sources of protein-protein interactions

Many biological processes are mediated by protein-protein interactions (PPIs). Because protein domains are the building blocks of proteins, PPIs likely rely on domain-domain interactions (DDIs). Several attempts exist to infer DDIs from PPI networks but the produced datasets are heterogeneous and sometimes not accessible, while the PPI interactome data keeps growing.

We describe a new computational approach called “PPIDM” (Protein-Protein Interactions Domain Miner) for inferring DDIs using multiple sources of PPIs. The approach is an extension of our previously described “CODAC” (Computational Discovery of Direct Associations using Common neighbors) method for inferring new edges in a tripartite graph. The PPIDM method has been applied to seven widely used PPI resources, using as “Gold-Standard” a set of DDIs extracted from 3D structural databases. Overall, PPIDM has produced a dataset of 84,552 non-redundant DDIs. Statistical significance (p-value) is calculated for each source of PPI and used to classify the PPIDM DDIs in Gold (9,175 DDIs), Silver (24,934 DDIs) and Bronze (50,443 DDIs) categories. Dataset comparison reveals that PPIDM has inferred from the 2017 releases of PPI sources about 46% of the DDIs present in the 2020 release of the 3did database, not counting the DDIs present in the Gold-Standard. The PPIDM dataset contains 10,229 DDIs that are consistent with more than 13,300 PPIs extracted from the IMEx database, and nearly 23,300 DDIs (27.5%) that are consistent with more than 214,000 human PPIs extracted from the STRING database. Examples of newly inferred DDIs covering more than 10 PPIs in the IMEx database are provided.

Further exploitation of the PPIDM DDI reservoir includes the inventory of possible partners of a protein of interest and characterization of protein interactions at the domain level in combination with other methods. The result is publicly available at http://ppidm.loria.fr/.

We revisit at a large scale the question of inferring DDIs from PPIs. Compared to previous studies, we take a unified approach accross multiple sources of PPIs. This approach is a method for inferring new edges in a tripartite graph setting and can be compared to link prediction approaches in knowledge graphs. Aggregation of several sources is performed using an optimized weighted average of the individual scores calculated in each source. A huge dataset of over 84K DDIs is produced which far exceeds the previous datasets. We show that a significant portion of the PPIDM dataset covers a large number of PPIs from curated (IMEx) or non curated (STRING) databases. Such a reservoir of DDIs deserves further exploration and can be combined with high-throughput methods such as cross-linking mass spectrometry to identify plausible protein partners of proteins of interest.

Evolution and diversification of the nuclear pore complex

The nuclear pore complex (NPC) is responsible for transport between the cytoplasm and nucleoplasm and one of the more intricate structures of eukaryotic cells. Typically composed of over 300 polypeptides, the NPC shares evolutionary origins with endo-membrane and intraflagellar transport system complexes. The modern NPC was fully established by the time of the last eukaryotic common ancestor and, hence, prior to eukaryote diversification. Despite the complexity, the NPC structure is surprisingly flexible with considerable variation between lineages. Here, we review diversification of the NPC in major taxa in view of recent advances in genomic and structural characterisation of plant, protist and nucleomorph NPCs and discuss the implications for NPC evolution. Furthermore, we highlight these changes in the context of mRNA export and consider how this process may have influenced NPC diversity. We reveal the NPC as a platform for continual evolution and adaptation.

The DnaJ proteins DJA6 and DJA5 are essential for chloroplast iron-sulfur cluster biogenesis

Fe-S clusters are ancient, ubiquitous and highly essential prosthetic groups for numerous fundamental processes of life. The biogenesis of Fe-S clusters is a multistep process including iron acquisition, sulfur mobilization, and cluster formation. Extensive studies have provided deep insights into the mechanism of the latter two assembly steps. However, the mechanism of iron utilization during chloroplast Fe-S cluster biogenesis is still unknown. Here we identified two Arabidopsis DnaJ proteins, DJA6 and DJA5, that can bind iron through their conserved cysteine residues and facilitate iron incorporation into Fe-S clusters by interactions with the SUF (sulfur utilization factor) apparatus through their J domain. Loss of these two proteins causes severe defects in the accumulation of chloroplast Fe-S proteins, a dysfunction of photosynthesis, and a significant intracellular iron overload. Evolutionary analyses revealed that DJA6 and DJA5 are highly conserved in photosynthetic organisms ranging from cyanobacteria to higher plants and share a strong evolutionary relationship with SUFE1, SUFC, and SUFD throughout the green lineage. Thus, our work uncovers a conserved mechanism of iron utilization for chloroplast Fe-S cluster biogenesis.

Co-evolutionary landscape at the interface and non-interface regions of protein-protein interaction complexes

Proteins involved in interactions throughout the course of evolution tend to co-evolve and compensatory changes may occur in interacting proteins to maintain or refine such interactions. However, certain residue pair alterations may prove to be detrimental for functional interactions. Hence, determining co-evolutionary pairings that could be structurally or functionally relevant for maintaining the conservation of an inter-protein interaction is important. Inter-protein co-evolution analysis in several complexes utilizing multiple existing methodologies suggested that co-evolutionary pairings can occur in spatially proximal and distant regions in inter-protein interactions. Subsequently, the Co-Var (Correlated Variation) method based on mutual information and Bhattacharyya coefficient was developed, validated, and found to perform relatively better than CAPS and EV-complex. Interestingly, while applying the Co-Var measure and EV-complex program on a set of protein-protein interaction complexes, co-evolutionary pairings were obtained in interface and non-interface regions in protein complexes. The Co-Var approach involves determining high degree co-evolutionary pairings that include multiple co-evolutionary connections between particular co-evolved residue positions in one protein with multiple residue positions in the binding partner. Detailed analyses of high degree co-evolutionary pairings in protein-protein complexes involved in cancer metastasis suggested that most of the residue positions forming such co-evolutionary connections mainly occurred within functional domains of constituent proteins and substitution mutations were also common among these positions. The physiological relevance of these predictions suggested that Co-Var can predict residues that could be crucial for preserving functional protein-protein interactions. Finally, Co-Var web server (http://www.hpppi.iicb.res.in/ishi/covar/index.html) that implements this methodology identifies co-evolutionary pairings in intra and inter-protein interactions.

PolyQ length co-evolution in neural proteins

Intermolecular co-evolution optimizes physiological performance in functionally related proteins, ultimately increasing molecular co-adaptation and evolutionary fitness. Polyglutamine (polyQ) repeats, which are over-represented in nervous system-related proteins, are increasingly recognized as length-dependent regulators of protein function and interactions, and their length variation contributes to intraspecific phenotypic variability and interspecific divergence. However, it is unclear whether polyQ repeat lengths evolve independently in each protein or rather co-evolve across functionally related protein pairs and networks, as in an integrated regulatory system. To address this issue, we investigated here the length evolution and co-evolution of polyQ repeats in clusters of functionally related and physically interacting neural proteins in Primates. We observed function-/disease-related polyQ repeat enrichment and evolutionary hypervariability in specific neural protein clusters, particularly in the neurocognitive and neuropsychiatric domains. Notably, these analyses detected extensive patterns of intermolecular polyQ length co-evolution in pairs and clusters of functionally related, physically interacting proteins. Moreover, they revealed both direct and inverse polyQ length co-variation in protein pairs, together with complex patterns of coordinated repeat variation in entire polyQ protein sets. These findings uncover a whole system of co-evolving polyQ repeats in neural proteins with direct implications for understanding polyQ-dependent phenotypic variability, neurocognitive evolution and neuropsychiatric disease pathogenesis.

Coevolutionary forces shaping the fitness of SARS-CoV-2 spike glycoprotein against human receptor ACE2

The current global health problem caused by SARS-CoV-2 has challenged the scientific community in various ways. Therefore, worldwide several scientific groups are exploring SARS-CoV-2 from different aspects including its origin, spread, severe infectivity, and also to find a cure. It is now well known that spike glycoprotein helps SARS-CoV-2 to enter inside the human host through a cellular receptor ACE2. However, the role of coevolutionary forces that makes SARS-CoV-2 spike glycoprotein more fit towards its human host remains unexplored. Therefore, in present bioinformatics study we identify coevolving amino acids in spike glycoprotein. Additionally, the effects of coevolution on the stability of the spike glycoprotein as well as its binding with receptor ACE2 were predicted. The results clearly indicate that coevolutionary forces play a pivotal role in increasing the fitness of spike glycoprotein against ACE2.

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Coevolutionary amino acids increasing the fitness of spike glycoprotein against ACE2 were analysed

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Role of coevolution on the stability of the spike glycoprotein and its binding with receptor ACE2 were predicted

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Findings of present analysis suggest that coevolutionary forces help to increase the infectivity of SARS-CoV-2

Analysis of Protein-Protein Interaction Networks through Computational Approaches

The interactions among proteins and genes are extremely important for cellular functions. Molecular interactions at protein or gene levels can be used to construct interaction networks in which the interacting species are categorized based on direct interactions or functional similarities. Compared with the limited experimental techniques, various computational tools make it possible to analyze, filter, and combine the interaction data to get comprehensive information about the biological pathways. By the efficient way of integrating experimental findings in discovering PPIs and computational techniques for prediction, the researchers have been able to gain many valuable data on PPIs, including some advanced databases. Moreover, many useful tools and visualization programs enable the researchers to establish, annotate, and analyze biological networks. We here review and list the computational methods, databases, and tools for protein-protein interaction prediction.

Engineering lytic polysaccharide monooxygenases (LPMOs)

Lytic polysaccharide monooxygenases (LPMOs) are mono-copper enzymes that catalyze the hydroxylation of glycosidic bonds found in the most abundant and recalcitrant polysaccharides on Earth. Since their discovery in 2010, these enzymes have received extensive attention in both fundamental and applied research due to their remarkable oxidative power and synergistic interplay with hydrolytic enzymes. The harsh and unnatural conditions used in industrial enzymatic saccharification processes and the sensitivity of LPMOs for damage induced by reactive oxygen species call for enzyme engineering to develop LPMOs to become robust industrial biocatalysts. Other engineering targets include improved catalytic activity, adjusted substrate specificity and the introduction of completely new activities. Reaching these targets not only requires appropriate methods for measuring enzyme activity, but also requires in-depth knowledge of the active site and the reaction mechanism, which is yet to be achieved in the LPMO field. Here we describe what has been done in the LPMO engineering field so far. Furthermore, we address the difficulties involved in properly assessing LPMO functionality, which are due to common side reactions taking place in LPMO reactions and which complicate screening methods.

Evolutionary Study of the Crassphage Virus at Gene Level

crAss-like viruses are a putative family of bacteriophages recently discovered. The eponym of the clade, crAssphage, is an enteric bacteriophage estimated to be present in at least half of the human population and it constitutes up to 90% of the sequences in some human fecal viral metagenomic datasets. We focused on the evolutionary dynamics of the genes encoded on the crAssphage genome. By investigating the conservation of the genes, a consistent variation in the evolutionary rates across the different functional groups was found. Gene duplications in crAss-like genomes were detected. By exploring the differences among the functional categories of the genes, we confirmed that the genes encoding capsid proteins were the most ubiquitous, despite their overall low sequence conservation. It was possible to identify a core of proteins whose evolutionary trees strongly correlate with each other, suggesting their genetic interaction. This group includes the capsid proteins, which are thus established as extremely suitable for rebuilding the phylogenetic tree of this viral clade. A negative correlation between the ubiquity and the conservation of viral protein sequences was shown. Together, this study provides an in-depth picture of the evolution of different genes in crAss-like viruses.

A versatile genetic control system in mammalian cells and mice responsive to clinically licensed sodium ferulate

Dynamically adjustable gene- and cell-based therapies are recognized as next-generation medicine. However, the translation of precision therapies into clinics is limited by lack of specific switches controlled by inducers that are safe and ready for clinical use. Ferulic acid (FA) is a phytochemical with a wide range of therapeutic effects, and its salt sodium ferulate (SF) is used as an antithrombotic drug in clinics. Here, we describe an FA/SF-adjustable transcriptional switch controlled by the clinically licensed drug SF. We demonstrated that SF-responsive switches can be engineered to control CRISPR-Cas9 systems for on-command genome/epigenome engineering. In addition, we integrated FA-controlled switches into programmable biocomputers to process logic operations. We further demonstrated the dose-dependent SF-inducible transgene expression in mice by oral administration of SF tablets. Engineered switches responsive to small-molecule clinically licensed drugs to achieve adjustable transgene expression profiles provide new opportunities for dynamic interventions in gene- and cell-based precision medicine.

Connecting signals and benefits through partner choice in plant-microbe interactions

Stabilizing mechanisms in plant-microbe symbioses are critical to maintaining beneficial functions, with two main classes: host sanctions and partner choice. Sanctions are currently presumed to be more effective and widespread, based on the idea that microbes rapidly evolve cheating while retaining signals matching cooperative strains. However, hosts that effectively discriminate among a pool of compatible symbionts would gain a significant fitness advantage. Using the well-characterized legume-rhizobium symbiosis as a model, we evaluate the evidence for partner choice in the context of the growing field of genomics. Empirical studies that rely upon bacteria varying only in nitrogen-fixation ability ignore host-symbiont signaling and frequently conclude that partner choice is not a robust stabilizing mechanism. Here, we argue that partner choice is an overlooked mechanism of mutualism stability and emphasize that plants need not use the microbial services provided a priori to discriminate among suitable partners. Additionally, we present a model that shows that partner choice signaling increases symbiont and host fitness in the absence of sanctions. Finally, we call for a renewed focus on elucidating the signaling mechanisms that are critical to partner choice while further aiming to understand their evolutionary dynamics in nature.

Domain-mediated interactions for protein subfamily identification

Within a protein family, proteins with the same domain often exhibit different cellular functions, despite the shared evolutionary history and molecular function of the domain. We hypothesized that domain-mediated interactions (DMIs) may categorize a protein family into subfamilies because the diversified functions of a single domain often depend on interacting partners of domains. Here we systematically identified DMI subfamilies, in which proteins share domains with DMI partners, as well as with various functional and physical interaction networks in individual species. In humans, DMI subfamily members are associated with similar diseases, including cancers, and are frequently co-associated with the same diseases. DMI information relates to the functional and evolutionary subdivisions of human kinases. In yeast, DMI subfamilies contain proteins with similar phenotypic outcomes from specific chemical treatments. Therefore, the systematic investigation here provides insights into the diverse functions of subfamilies derived from a protein family with a link-centric approach and suggests a useful resource for annotating the functions and phenotypic outcomes of proteins.

Insights into archaeal chaperone machinery: a network-based approach

Molecular chaperones are a diverse group of proteins that ensure proteome integrity by helping the proteins fold correctly and maintain their native state, thus preventing their misfolding and subsequent aggregation. The chaperone machinery of archaeal organisms has been thought to closely resemble that found in humans, at least in terms of constituent players. Very few studies have been ventured into system-level analysis of chaperones and their functioning in archaeal cells. In this study, we attempted such an analysis of chaperone-assisted protein folding in archaeal organisms through network approach using Picrophilus torridus as model system. The study revealed that DnaK protein of Hsp70 system acts as hub in protein-protein interaction network. However, DnaK protein was present only in a subset of archaeal organisms and absent from many archaea, especially members of Crenarchaeota phylum. Therefore, a similar network was created for another archaeal organism, Sulfolobus solfataricus, a member of Crenarchaeota. The chaperone network of S. solfataricus suggested that thermosomes played an integral part of hub proteins in archaeal organisms, where DnaK was absent. We further compared the chaperone network of archaea with that found in eukaryotic systems, by creating a similar network for Homo sapiens. In the human chaperone network, the UBC protein, a part of ubiquitination system, was the most important module, and interestingly, this system is known to be absent in archaeal organisms. Comprehensive comparison of these networks leads to several interesting conclusions regarding similarities and differences within archaeal chaperone machinery in comparison to humans.

Characterization of C-ring component assembly in flagellar motors from amino acid coevolution

Bacterial flagellar motility, an important virulence factor, is energized by a rotary motor localized within the flagellar basal body. The rotor module consists of a large framework (the C-ring), composed of the FliG, FliM and FliN proteins. FliN and FliM contacts the FliG torque ring to control the direction of flagellar rotation. We report that structure-based models constrained only by residue coevolution can recover the binding interface of atomic X-ray dimer complexes with remarkable accuracy (approx. 1 Å RMSD). We propose a model for FliM-FliN heterodimerization, which agrees accurately with homologous interfaces as well as in situ cross-linking experiments, and hence supports a proposed architecture for the lower portion of the C-ring. Furthermore, this approach allowed the identification of two discrete and interchangeable homodimerization interfaces between FliM middle domains that agree with experimental measurements and might be associated with C-ring directional switching dynamics triggered upon binding of CheY signal protein. Our findings provide structural details of complex formation at the C-ring that have been difficult to obtain with previous methodologies and clarify the architectural principle that underpins the ultra-sensitive allostery exhibited by this ring assembly that controls the clockwise or counterclockwise rotation of flagella.

Selection on the Major Color Gene Melanocortin-1-Receptor Shaped the Evolution of the Melanocortin System Genes

Modular genetic systems and networks have complex evolutionary histories shaped by selection acting on single genes as well as on their integrated function within the network. However, uncovering molecular coevolution requires the detection of coevolving sites in sequences. Detailed knowledge of the functions of each gene in the system is also necessary to identify the selective agents driving coevolution. Using recently developed computational tools, we investigated the effect of positive selection on the coevolution of ten major genes in the melanocortin system, responsible for multiple physiological functions and human diseases. Substitutions driven by positive selection at the melanocortin-1-receptor (MC1R) induced more coevolutionary changes on the system than positive selection on other genes in the system. Contrarily, selection on the highly pleiotropic POMC gene, which orchestrates the activation of the different melanocortin receptors, had the lowest coevolutionary influence. MC1R and possibly its main function, melanin pigmentation, seems to have influenced the evolution of the melanocortin system more than functions regulated by MC2-5Rs such as energy homeostasis, glucocorticoid-dependent stress and anti-inflammatory responses. Although replication in other regulatory systems is needed, this suggests that single functional aspects of a genetic network or system can be of higher importance than others in shaping coevolution among the genes that integrate it.

PCPPI: a comprehensive database for the prediction of Penicillium-crop protein-protein interactions

Penicillium expansum , the causal agent of blue mold, is one of the most prevalent post-harvest pathogens, infecting a wide range of crops after harvest. In response, crops have evolved various defense systems to protect themselves against this and other pathogens. Penicillium -crop interaction is a multifaceted process and mediated by pathogen- and host-derived proteins. Identification and characterization of the inter-species protein-protein interactions (PPIs) are fundamental to elucidating the molecular mechanisms underlying infection processes between P. expansum and plant crops. Here, we have developed PCPPI, the Penicillium -Crop Protein-Protein Interactions database, which is constructed based on the experimentally determined orthologous interactions in pathogen-plant systems and available domain-domain interactions (DDIs) in each PPI. Thus far, it stores information on 9911 proteins, 439 904 interactions and seven host species, including apple, kiwifruit, maize, pear, rice, strawberry and tomato. Further analysis through the gene ontology (GO) annotation indicated that proteins with more interacting partners tend to execute the essential function. Significantly, semantic statistics of the GO terms also provided strong support for the accuracy of our predicted interactions in PCPPI. We believe that all the PCPPI datasets are helpful to facilitate the study of pathogen-crop interactions and freely available to the research community.

Database URL

: http://bdg.hfut.edu.cn/pcppi/index.html.

Gα and regulator of G-protein signaling (RGS) protein pairs maintain functional compatibility and conserved interaction interfaces throughout evolution despite frequent loss of RGS proteins in plants

Signaling pathways regulated by heterotrimeric G-proteins exist in all eukaryotes. The regulator of G-protein signaling (RGS) proteins are key interactors and critical modulators of the Gα protein of the heterotrimer. However, while G-proteins are widespread in plants, RGS proteins have been reported to be missing from the entire monocot lineage, with two exceptions. A single amino acid substitution-based adaptive coevolution of the Gα:RGS proteins was proposed to enable the loss of RGS in monocots. We used a combination of evolutionary and biochemical analyses and homology modeling of the Gα and RGS proteins to address their expansion and its potential effects on the G-protein cycle in plants. Our results show that RGS proteins are widely distributed in the monocot lineage, despite their frequent loss. There is no support for the adaptive coevolution of the Gα:RGS protein pair based on single amino acid substitutions. RGS proteins interact with, and affect the activity of, Gα proteins from species with or without endogenous RGS. This cross-functional compatibility expands between the metazoan and plant kingdoms, illustrating striking conservation of their interaction interface. We propose that additional proteins or alternative mechanisms may exist which compensate for the loss of RGS in certain plant species.

Evolutionary diversification of protein-protein interactions by interface add-ons

Cells contain a multitude of protein complexes whose subunits interact with high specificity. However, the number of different protein folds and interface geometries found in nature is limited. This raises the question of how protein-protein interaction specificity is achieved on the structural level and how the formation of nonphysiological complexes is avoided. Here, we describe structural elements called interface add-ons that fulfill this function and elucidate their role for the diversification of protein-protein interactions during evolution. We identified interface add-ons in 10% of a representative set of bacterial, heteromeric protein complexes. The importance of interface add-ons for protein-protein interaction specificity is demonstrated by an exemplary experimental characterization of over 30 cognate and hybrid glutamine amidotransferase complexes in combination with comprehensive genetic profiling and protein design. Moreover, growth experiments showed that the lack of interface add-ons can lead to physiologically harmful cross-talk between essential biosynthetic pathways. In sum, our complementary in silico, in vitro, and in vivo analysis argues that interface add-ons are a practical and widespread evolutionary strategy to prevent the formation of nonphysiological complexes by specializing protein-protein interactions.

Network analysis and cross species comparison of protein-protein interaction networks of human, mouse and rat cytochrome P450 proteins that degrade xenobiotics

Cytochrome P450 (CYP) enzymes that degrade xenobiotics play a critical role in the metabolism and biotransformation of drugs and xenobiotics in humans as well as experimental animal models such as mouse and rat. These proteins function as a network collectively as well as independently. Though there are several reports on the organization, regulation and functionality of various CYP enzymes at the molecular level, the understanding of organization and functionality of these proteins at the holistic level remain unclear. The objective of this study is to understand the organization and functionality of xenobiotic degrading CYP enzymes of human, mouse and rat using network theory approaches and to study species differences that exist among them at the holistic level. For our analysis, a protein-protein interaction (PPI) network for CYP enzymes of human, mouse and rat was constructed using the STRING database. Topology, centrality, modularity and robustness analyses were performed for our predicted CYP PPI networks that were then validated by comparison with randomly generated network models. Network centrality analyses of CYP PPI networks reveal the central/hub proteins in the network. Modular analysis of the CYP PPI networks of human, mouse and rat resulted in functional clusters. These clusters were subjected to ontology and pathway enrichment analysis. The analyses show that the cluster of the human CYP PPI network is enriched with pathways principally related to xenobiotic/drug metabolism. Endo-xenobiotic crosstalk dominated in mouse and rat CYP PPI networks, and they were highly enriched with endogenous metabolic and signaling pathways. Thus, cross-species comparisons and analyses of human, mouse and rat CYP PPI networks gave insights about species differences that existed at the holistic level. More investigations from both reductionist and holistic perspectives can help understand CYP metabolism and species extrapolation in a much better way.

Coevolution of Domain Interactions in the Chloroplast TGD1, 2, 3 Lipid Transfer Complex Specific to Brassicaceae and Poaceae Plants

The import of lipids into the chloroplast is essential for photosynthetic membrane biogenesis. This process requires an ABC transporter in the inner envelope membrane with three subunits, TRIGALACTOSYLDIACYLGLYCEROL (TGD) 1, 2, and 3, named after the oligogalactolipids that accumulate in the respective Arabidopsis thaliana mutants. Unlike Arabidopsis, in the model grass Brachypodium distachyon, chloroplast lipid biosynthesis is largely dependent on imported precursors, resulting in a characteristic difference in chloroplast lipid acyl composition between the two plants. Accordingly, Arabidopsis is designated as a 16:3 (acyl carbons:double bounds) plant and Brachypodium as an 18:3 plant. Repression of TGD1 (BdTGD1) in Brachypodium affected growth without triggering oligogalactolipid biosynthesis. Moreover, expressing BdTGD1 in the Arabidopsis tgd1-1 mutant restored some phenotypes but did not reverse oligogalactolipid biosynthesis. A 27-amino acid loop (L45) is solely responsible for the incomplete functioning of BdTGD1 in Arabidopsis tgd1-1 Coevolutionary analysis and coimmunoprecipitation assays showed that the TGD1 L45 loop interacts with the mycobacterial cell entry domain of TGD2. To explain the observed differences in oligogalactolipid biosynthesis between the two species, we suggest that excess monogalactosyldiacylglycerol derived from chloroplast-derived precursors in Arabidopsis tgd1-1 is converted into oligogalactolipids, a process absent from Brachypodium with reduced TGD1 levels, which assembles monogalactosyldiacylglycerol exclusively from imported precursors.

Ablation of RNA interference and retrotransposons accompany acquisition and evolution of transposases to heterochromatin protein CENPB

Fission yeast have adapted to retrotransposon invasion by RNAi-mediated silencing, which has coevolved into a mechanism involving CENPB-mediated heterochromatinization together with ablation of RNAi components via accumulation of recombinogenic repeats in recently diverged species of Schizosaccharomyces. Similar trends are seen in the metazoans.

Inactivation of retrotransposons is accompanied by the emergence of centromere-binding protein-B (CENPB) in Schizosaccharomyces, as well as in metazoans. The RNA interference (RNAi)-induced transcriptional silencing (RITS) complex, comprising chromodomain protein-1 (Chp1), Tas3 (protein with unknown function), and Argonaute (Ago1), plays an important role in RNAi-mediated heterochromatinization. We find that whereas the Ago1 subunit of the RITS complex is highly conserved, Tas3 is lost and Chp1 is truncated in Schizosaccharomyces cryophilus and Schizosaccharomyces octosporus. We show that truncated Chp1 loses the property of heterochromatin localization and silencing when transformed in Schizosaccharomyces pombe. Furthermore, multiple copies of CENPB, related to Tc1/mariner and Tc5 transposons, occur in all Schizosaccharomyces species, as well as in humans, but with loss of transposase function (except Schizosaccharomyces japonicus). We propose that acquisition of Tc1/mariner and Tc5 elements by horizontal transfer in S. pombe (and humans) is accompanied by alteration of their function from a transposase/endonuclease to a heterochromatin protein, designed to suppress transposon expression and recombination. The resulting redundancy of RITS may have eased the selection pressure, resulting in progressive loss or truncation of tas3 and chp1 genes in S. octosporus and S. cryophilus and triggered similar evolutionary dynamics in the metazoan orthologues.

Recruitment of Tiam1 to Semaphorin 4D Activates Rac and Enhances Proliferation, Invasion, and Metastasis in Oral Squamous Cell Carcinoma

The semaphorins and the plexins are a family of large, cysteine-rich proteins originally identified as regulators of axon growth and lymphocyte activation that are now known to provide motility and positional information for a number of cell and tissue types. For example, our group and others have shown that some malignancies over express Semaphorin 4D (S4D), which acts through its receptor Plexin-B1 (PB1) on endothelial cells to attract blood vessels from the surrounding stroma for the purpose of supporting tumor growth. While plexins are the known functional receptors for the semaphorins, there is evidence that transmembrane semaphorins may transmit a signal themselves through their short cytoplasmic tail, a phenomenon known as ‘reverse signaling.’ We used computational methods based upon correlated evolution of sequences of interacting proteins, mutational analysis and in vitro and in vivo measurements of tumor aggressiveness to show that when bound to PB1, transmembrane S4D associates with the Rac GTPase exchange factor T lymphoma invasion and metastasis (Tiam) 1, which activates Rac and promotes proliferation, invasion and metastasis in oral squamous cell carcinoma (OSCC) cells. These results suggest that not only can S4D production by tumor cells affect the microenvironment, but engagement of this semaphorin at the cell surface activates a reverse signaling mechanism that influences tumor aggressiveness in OSCC.

Conservation of miRNA-mediated silencing mechanisms across 600 million years of animal evolution

Our current knowledge about the mechanisms of miRNA silencing is restricted to few lineages such as vertebrates, arthropods, nematodes and land plants. miRNA-mediated silencing in bilaterian animals is dependent on the proteins of the GW182 family. Here, we dissect the function of GW182 protein in the cnidarian Nematostella, separated by 600 million years from other Metazoa. Using cultured human cells, we show that Nematostella GW182 recruits the CCR4-NOT deadenylation complexes via its tryptophan-containing motifs, thereby inhibiting translation and promoting mRNA decay. Further, similarly to bilaterians, GW182 in Nematostella is recruited to the miRNA repression complex via interaction with Argonaute proteins, and functions downstream to repress mRNA. Thus, our work suggests that this mechanism of miRNA-mediated silencing was already active in the last common ancestor of Cnidaria and Bilateria.

Allostery Wiring Map for Kinesin Energy Transduction and Its Evolution

How signals between the kinesin active and cytoskeletal binding sites are transmitted is an open question and an allosteric question. By extracting correlated evolutionary changes within 700+ sequences, we built a model of residues that are energetically coupled and that define molecular routes for signal transmission. Typically, these coupled residues are located at multiple distal sites and thus are predicted to form a complex, non-linear network that wires together different functional sites in the protein. Of note, our model connected the site for ATP hydrolysis with sites that ultimately utilize its free energy, such as the microtubule-binding site, drug-binding loop 5, and necklinker. To confirm the calculated energetic connectivity between non-adjacent residues, double-mutant cycle analysis was conducted with 22 kinesin mutants. There was a direct correlation between thermodynamic coupling in experiment and evolutionarily derived energetic coupling. We conclude that energy transduction is coordinated by multiple distal sites in the protein rather than only being relayed through adjacent residues. Moreover, this allosteric map forecasts how energetic orchestration gives rise to different nanomotor behaviors within the superfamily.

PTIR: Predicted Tomato Interactome Resource

Protein-protein interactions (PPIs) are involved in almost all biological processes and form the basis of the entire interactomics systems of living organisms. Identification and characterization of these interactions are fundamental to elucidating the molecular mechanisms of signal transduction and metabolic pathways at both the cellular and systemic levels. Although a number of experimental and computational studies have been performed on model organisms, the studies exploring and investigating PPIs in tomatoes remain lacking. Here, we developed a Predicted Tomato Interactome Resource (PTIR), based on experimentally determined orthologous interactions in six model organisms. The reliability of individual PPIs was also evaluated by shared gene ontology (GO) terms, co-evolution, co-expression, co-localization and available domain-domain interactions (DDIs). Currently, the PTIR covers 357,946 non-redundant PPIs among 10,626 proteins, including 12,291 high-confidence, 226,553 medium-confidence, and 119,102 low-confidence interactions. These interactions are expected to cover 30.6% of the entire tomato proteome and possess a reasonable distribution. In addition, ten randomly selected PPIs were verified using yeast two-hybrid (Y2H) screening or a bimolecular fluorescence complementation (BiFC) assay. The PTIR was constructed and implemented as a dedicated database and is available at http://bdg.hfut.edu.cn/ptir/index.html without registration.

p53 mRNA and p53 Protein Structures Have Evolved Independently to Interact with MDM2

The p53 tumor suppressor and its key regulator MDM2 play essential roles in development, ageing, cancer, and cellular stress responses in mammals. Following DNA damage, MDM2 interacts with p53 mRNA in an ATM kinase-dependent fashion and stimulates p53 synthesis, whereas under normal conditions, MDM2 targets the p53 protein for degradation. The peptide- and RNA motifs that interact with MDM2 are encoded by the same conserved BOX-I sequence, but how these interactions have evolved is unknown. Here, we show that a temperature-sensitive structure in the invertebrate Ciona intestinalis (Ci) p53 mRNA controls its interaction with MDM2. We also show that a nonconserved flanking region of Ci-BOX-I domain prevents the p53-MDM2 protein-protein interaction. These results indicate that the temperature-regulated p53 mRNA-MDM2 interaction evolved to become kinase regulated in the mammalian DNA damage response. The data also suggest that the negative regulation of p53 by MDM2 via protein-protein interaction evolved in vertebrates following changes in the BOX-I flanking sequence.

Fifty years of co-evolution and beyond: integrating co-evolution from molecules to species

Fifty years after Ehrlich and Raven's seminal paper, the idea of co-evolution continues to grow as a key concept in our understanding of organic evolution. This concept has not only provided a compelling synthesis between evolutionary biology and community ecology, but has also inspired research that extends beyond its original scope. In this article, we identify unresolved questions about the co-evolutionary process and advocate for the integration of co-evolutionary research from molecular to interspecific interactions. We address two basic questions: (i) What is co-evolution and how common is it? (ii) What is the unit of co-evolution? Both questions aim to explore the heart of the co-evolutionary process. Despite the claim that co-evolution is ubiquitous, we argue that there is in fact little evidence to support the view that reciprocal natural selection and coadaptation are common in nature. We also challenge the traditional view that co-evolution only occurs between traits of interacting species. Co-evolution has the potential to explain evolutionary processes and patterns that result from intra- and intermolecular biochemical interactions within cells, intergenomic interactions (e.g. nuclear-cytoplasmic) within species, as well as intergenomic interactions mediated by phenotypic traits between species. Research that bridges across these levels of organization will help to advance our understanding of the importance of the co-evolutionary processes in shaping the diversity of life on Earth.

Tex19 and Sectm1 concordant molecular phylogenies support co-evolution of both eutherian-specific genes

BACKGROUND

Transposable elements (TE) have attracted much attention since they shape the genome and contribute to species evolution. Organisms have evolved mechanisms to control TE activity. Testis expressed 19 (Tex19) represses TE expression in mouse testis and placenta. In the human and mouse genomes, Tex19 and Secreted and transmembrane 1 (Sectm1) are neighbors but are not homologs. Sectm1 is involved in immunity and its molecular phylogeny is unknown.

METHODS

Using multiple alignments of complete protein sequences (MACS), we inferred Tex19 and Sectm1 molecular phylogenies. Protein conserved regions were identified and folds were predicted. Finally, expression patterns were studied across tissues and species using RNA-seq public data and RT-PCR.

RESULTS

We present 2 high quality alignments of 58 Tex19 and 58 Sectm1 protein sequences from 48 organisms. First, both genes are eutherian-specific, i.e., exclusively present in mammals except monotremes (platypus) and marsupials. Second, Tex19 and Sectm1 have both duplicated in Sciurognathi and Bovidae while they have remained as single copy genes in all further placental mammals. Phylogenetic concordance between both genes was significant (p-value < 0.05) and supported co-evolution and functional relationship. At the protein level, Tex19 exhibits 3 conserved regions and 4 invariant cysteines. In particular, a CXXC motif is present in the N-terminal conserved region. Sectm1 exhibits 2 invariant cysteines and an Ig-like domain. Strikingly, Tex19 C-terminal conserved region was lost in Haplorrhini primates while a Sectm1 C-terminal extra domain was acquired. Finally, we have determined that Tex19 and Sectm1 expression levels anti-correlate across the testis of several primates (ρ = -0.72) which supports anti-regulation.

CONCLUSIONS

Tex19 and Sectm1 co-evolution and anti-regulated expressions support a strong functional relationship between both genes. Since Tex19 operates a control on TE and Sectm1 plays a role in immunity, Tex19 might suppress an immune response directed against cells that show TE activity in eutherian reproductive tissues.

Compensated pathogenic deviations

Deleterious or 'disease-associated' mutations are mutations that lead to disease with high phenotype penetrance: they are inherited in a simple Mendelian manner, or, in the case of cancer, accumulate in somatic cells leading directly to disease. However, in some cases, the amino acid that is substituted resulting in disease is the wild-type native residue in the functionally equivalent protein in another species. Such examples are known as 'compensated pathogenic deviations' (CPDs) because, somewhere in the second species, there must be compensatory mutations that allow the protein to function normally despite having a residue which would cause disease in the first species. Depending on the nature of the mutations, compensation can occur in the same protein, or in a different protein with which it interacts. In principle, compensation can be achieved by a single mutation (most probably structurally close to the CPD), or by the cumulative effect of several mutations. Although it is clear that these effects occur in proteins, compensatory mutations are also important in RNA potentially having an impact on disease. As a much simpler molecule, RNA provides an interesting model for understanding mechanisms of compensatory effects, both by looking at naturally occurring RNA molecules and as a means of computational simulation. This review surveys the rather limited literature that has explored these effects. Understanding the nature of CPDs is important in understanding traversal along fitness landscape valleys in evolution. It could also have applications in treating diseases that result from such mutations.

Mac-1 Regulates IL-13 Activity in Macrophages by Directly Interacting with IL-13Rα1

Mac-1 exhibits a unique inhibitory activity toward IL-13-induced JAK/STAT activation and thereby regulates macrophage to foam cell transformation. However, the underlying molecular mechanism is unknown. In this study, we report the identification of IL-13Rα1, a component of the IL-13 receptor (IL-13R), as a novel ligand of integrin Mac-1, using a co-evolution-based algorithm. Biochemical analyses demonstrated that recombinant IL-13Rα1 binds Mac-1 in a purified system and supports Mac-1-mediated cell adhesion. Co-immunoprecipitation experiments revealed that endogenous Mac-1 forms a complex with IL-13Rα1 in solution, and confocal fluorescence microscopy demonstrated that these two receptors co-localize with each other on the surface of macrophages. Moreover, we found that genetic inactivation of Mac-1 promotes IL-13-induced JAK/STAT activation in macrophages, resulting in enhanced polarization along the alternative activation pathway. Importantly, we observed that Mac-1(-/-) macrophages exhibit increased expression of foam cell differentiation markers including 15-lipoxygenase and lectin-type oxidized LDL receptor-1 both in vitro and in vivo. Indeed, we found that Mac-1(-/-)LDLR(-/-) mice develop significantly more foam cells than control LDLR(-/-) mice, using an in vivo model of foam cell formation. Together, our data establish for the first time a molecular mechanism by which Mac-1 regulates the signaling activity of IL-13 in macrophages. This newly identified IL-13Rα1/Mac-1-dependent pathway may offer novel targets for therapeutic intervention in the future.

Inference of Evolutionary Forces Acting on Human Biological Pathways

Because natural selection is likely to act on multiple genes underlying a given phenotypic trait, we study here the potential effect of ongoing and past selection on the genetic diversity of human biological pathways. We first show that genes included in gene sets are generally under stronger selective constraints than other genes and that their evolutionary response is correlated. We then introduce a new procedure to detect selection at the pathway level based on a decomposition of the classical McDonald-Kreitman test extended to multiple genes. This new test, called 2DNS, detects outlier gene sets and takes into account past demographic effects and evolutionary constraints specific to gene sets. Selective forces acting on gene sets can be easily identified by a mere visual inspection of the position of the gene sets relative to their two-dimensional null distribution. We thus find several outlier gene sets that show signals of positive, balancing, or purifying selection but also others showing an ancient relaxation of selective constraints. The principle of the 2DNS test can also be applied to other genomic contrasts. For instance, the comparison of patterns of polymorphisms private to African and non-African populations reveals that most pathways show a higher proportion of nonsynonymous mutations in non-Africans than in Africans, potentially due to different demographic histories and selective pressures.

Cladograms with Path to Event (ClaPTE): a novel algorithm to detect associations between genotypes or phenotypes using phylogenies

BACKGROUND

Associations between genotype and phenotype provide insight into the evolution of pathogenesis, drug resistance, and the spread of pathogens between hosts. However, common ancestry can lead to apparent associations between biologically unrelated features. The novel method Cladograms with Path to Event (ClaPTE) detects associations between character-pairs (either a pair of mutations or a mutation paired with a phenotype) while adjusting for common ancestry, using phylogenetic trees.

METHODS

ClaPTE tests for character-pairs changing close together on the phylogenetic tree, consistent with an associated character-pair. ClaPTE is compared to three existing methods (independent contrasts, mixed model, and likelihood ratio) to detect character-pair associations adjusted for common ancestry. Comparisons utilize simulations on gene trees for: HIV Env, HIV promoter, and bacterial DnaJ and GuaB; and case studies for Oseltamavir resistance in Influenza, and for DnaJ and GuaB. Simulated data include both true-positive/associated character-pairs, and true-negative/not-associated character-pairs, used to assess type I (frequency of p-values in true-negatives) and type II (sensitivity to true-positives) error control.

RESULTS AND CONCLUSIONS

ClaPTE has competitive sensitivity and better type I error control than existing methods. In the Influenza/Oseltamavir case study, ClaPTE reports no new permissive mutations but detects associations between adjacent (in primary sequence) amino acid positions which other methods miss. In the DnaJ and GuaB case study, ClaPTE reports more frequent associations between positions both from the same protein family than between positions from different families, in contrast to other methods. In both case studies, the results from ClaPTE are biologically plausible.

Coordinated rates of evolution between interacting plastid and nuclear genes in Geraniaceae

Although gene coevolution has been widely observed within individuals and between different organisms, rarely has this phenomenon been investigated within a phylogenetic framework. The Geraniaceae is an attractive system in which to study plastid-nuclear genome coevolution due to the highly elevated evolutionary rates in plastid genomes. In plants, the plastid-encoded RNA polymerase (PEP) is a protein complex composed of subunits encoded by both plastid (rpoA, rpoB, rpoC1, and rpoC2) and nuclear genes (sig1-6). We used transcriptome and genomic data for 27 species of Geraniales in a systematic evaluation of coevolution between genes encoding subunits of the PEP holoenzyme. We detected strong correlations of dN (nonsynonymous substitutions) but not dS (synonymous substitutions) within rpoB/sig1 and rpoC2/sig2, but not for other plastid/nuclear gene pairs, and identified the correlation of dN/dS ratio between rpoB/C1/C2 and sig1/5/6, rpoC1/C2 and sig2, and rpoB/C2 and sig3 genes. Correlated rates between interacting plastid and nuclear sequences across the Geraniales could result from plastid-nuclear genome coevolution. Analyses of coevolved amino acid positions suggest that structurally mediated coevolution is not the major driver of plastid-nuclear coevolution. The detection of strong correlation of evolutionary rates between SIG and RNAP genes suggests a plausible explanation for plastome-genome incompatibility in Geraniaceae.

Exploring bacterial organelle interactomes: a model of the protein-protein interaction network in the Pdu microcompartment

Bacterial microcompartments (MCPs) are protein-bound organelles that carry out diverse metabolic pathways in a wide range of bacteria. These supramolecular assemblies consist of a thin outer protein shell, reminiscent of a viral capsid, which encapsulates sequentially acting enzymes. The most complex MCP elucidated so far is the propanediol utilizing (Pdu) microcompartment. It contains the reactions for degrading 1,2-propanediol. While several experimental studies on the Pdu system have provided hints about its organization, a clear picture of how all the individual components interact has not emerged yet. Here we use co-evolution-based methods, involving pairwise comparisons of protein phylogenetic trees, to predict the protein-protein interaction (PPI) network governing the assembly of the Pdu MCP. We propose a model of the Pdu interactome, from which selected PPIs are further inspected via computational docking simulations. We find that shell protein PduA is able to serve as a “universal hub” for targeting an array of enzymes presenting special N-terminal extensions, namely PduC, D, E, L and P. The varied N-terminal peptides are predicted to bind in the same cleft on the presumptive luminal face of the PduA hexamer. We also propose that PduV, a protein of unknown function with remote homology to the Ras-like GTPase superfamily, is likely to localize outside the MCP, interacting with the protruding β-barrel of the hexameric PduU shell protein. Preliminary experiments involving a bacterial two-hybrid assay are presented that corroborate the existence of a PduU-PduV interaction. This first systematic computational study aimed at characterizing the interactome of a bacterial microcompartment provides fresh insight into the organization of the Pdu MCP.

Many bacteria produce giant proteinaceous structures within their cells, which they use to carry out special metabolic reactions in their interior. Much has been learned recently about the individual components—shell proteins and encapsulated enzymes—that assemble together, thousands of subunits in all, to make these bacterial microcompartments or MCPs. However, in order to carry out their biological functions, these systems must be highly organized through specific protein-protein interactions, and such a higher level understanding of organization in MCP systems is lacking. In this study, we use genomic data and phylogenetic analysis to predict the network of interactions between the approximately 20 different kinds of proteins and enzymes present in the Pdu MCP. Then, we use computational docking to examine a subset of those that are predicted to involve enzymes bound to the interior surface of the shell proteins, and show that the results are consistent with recent experimental data. We further provide new experimental evidence for one of the predicted protein-protein interactions. This study expands our understanding of a complex system of proteins serving as a metabolic organelle in bacterial cells, and provides a foundation for further experimental investigations.

Recent coselection in human populations revealed by protein-protein interaction network

Genome-wide scans for signals of natural selection in human populations have identified a large number of candidate loci that underlie local adaptations. This is surprising given the relatively short evolutionary time since the divergence of the human population. One hypothesis that has not been formally examined is whether and how the recent human evolution may have been shaped by coselection in the context of complex molecular interactome. In this study, genome-wide signals of selection were scanned in East Asians, Europeans, and Africans using 1000 Genome data, and subsequently mapped onto the protein-protein interaction (PPI) network. We found that the candidate genes of recent positive selection localized significantly closer to each other on the PPI network than expected, revealing substantial clustering of selected genes. Furthermore, gene pairs of shorter PPI network distances showed higher similarities of their recent evolutionary paths than those further apart. Last, subnetworks enriched with recent coselection signals were identified, which are substantially overrepresented in biological pathways related to signal transduction, neurogenesis, and immune function. These results provide the first genome-wide evidence for association of recent selection signals with the PPI network, shedding light on the potential mechanisms of recent coselection in the human genome.

Chemical reactivity drives spatiotemporal organisation of bacterial metabolism

In this review, we examine how bacterial metabolism is shaped by chemical constraints acting on the material and dynamic layout of enzymatic networks and beyond. These are moulded not only for optimisation of given metabolic objectives (e.g. synthesis of a particular amino acid or nucleotide) but also for curbing the detrimental reactivity of chemical intermediates. Besides substrate channelling, toxicity is avoided by barriers to free diffusion (i.e. compartments) that separate otherwise incompatible reactions, along with ways for distinguishing damaging vs. harmless molecules. On the other hand, enzymes age and their operating lifetime must be tuned to upstream and downstream reactions. This time dependence of metabolic pathways creates time-linked information, learning and memory. These features suggest that the physical structure of existing biosystems, from operon assemblies to multicellular development may ultimately stem from the need to restrain chemical damage and limit the waste inherent to basic metabolic functions. This provides a new twist of our comprehension of fundamental biological processes in live systems as well as practical take-home lessons for the forward DNA-based engineering of novel biological objects.

Conserved patterns in bacterial genomes: a conundrum physically tailored by evolutionary tinkering

The proper functioning of bacteria is encoded in their genome at multiple levels or scales, each of which is constrained by specific physical forces. At the smallest spatial scales, interatomic forces dictate the folding and function of proteins and nucleic acids. On longer length scales, stochastic forces emerging from the thermal jiggling of proteins and RNAs impose strong constraints on the organization of genes along chromosomes, more particularly in the context of the building of nucleoprotein complexes and the operational mode of regulatory agents. At the cellular level, transcription, replication and cell division activities generate forces that act on both the internal structure and cellular location of chromosomes. The overall result is a complex multi-scale organization of genomes that reflects the evolutionary tinkering of bacteria. The goal of this review is to highlight avenues for deciphering this complexity by focusing on patterns that are conserved among evolutionarily distant bacteria. To this end, I discuss three different organizational scales: the protein structures, the chromosomal organization of genes and the global structure of chromosomes.