One origin for metallo-β-lactamase activity, or two? An investigation assessing a diverse set of reconstructed ancestral sequences based on a sample of phylogenetic trees

Worldwide trend discovery of structural and functional relationship of metallo-β-lactamase for structure-based drug design: A bibliometric evaluation and patent analysis

Metallo-β-lactamase (MBL) is an enzyme produced by clinically important bacteria that can inactivate many commonly used antibiotics, making them a significant concern in treating bacterial infections and the risk of having high antibiotic resistance issues among the community. This review presents a bibliometric and patent analysis of MBL worldwide research trend based on the Scopus and World Intellectual Property Organization databases in 2013-2022. Based on the keywords related to MBL in the article title, abstract, and keywords, 592 research articles were retrieved for further analysis using various tools such as Microsoft Excel to determine the frequency analysis, VOSviewer for bibliometric networks visualization, and Harzing's Publish or Perish for citation metrics analysis. Standard bibliometric parameters were analysed to evaluate the field's research trend, such as the growth of publications, topographical distribution, top subject area, most relevant journal, top cited documents, most relevant authors, and keyword trend analysis. Within 10 years, MBL discovery has shown a steady and continuous growth of interest among the community of researchers. United States of America, China, and the United Kingdom are the top 3 countries contribute high productivity to the field. The patent analysis also shows several impactful filed patents, indicating the significance of development research on the structural and functional relationship of MBL for an effective structure-based drug design (SBDD). Developing new MBL inhibitors using SBDD could help address the research gap and provide new successful therapeutic options for treating MBL-producing bacterial infections.

Phylogenomics, phenotypic, and functional traits of five novel (Earth-derived) bacterial species isolated from the International Space Station and their prevalence in metagenomes

With the advent of long-term human habitation in space and on the moon, understanding how the built environment microbiome of space habitats differs from Earth habitats, and how microbes survive, proliferate and spread in space conditions, is becoming more important. The microbial tracking mission series has been monitoring the microbiome of the International Space Station (ISS) for almost a decade. During this mission series, six unique strains of Gram-stain-positive bacteria, including two spore-forming and three non-spore-forming species, were isolated from the environmental surfaces of the ISS. The analysis of their 16S rRNA gene sequences revealed > 99% similarities with previously described bacterial species. To further explore their phylogenetic affiliation, whole genome sequencing was undertaken. For all strains, the gyrB gene exhibited < 93% similarity with closely related species, which proved effective in categorizing these ISS strains as novel species. Average nucleotide identity and digital DNA-DNA hybridization values, when compared to any known bacterial species, were < 94% and <50% respectively for all species described here. Traditional biochemical tests, fatty acid profiling, polar lipid, and cell wall composition analyses were performed to generate phenotypic characterization of these ISS strains. A study of the shotgun metagenomic reads from the ISS samples, from which the novel species were isolated, showed that only 0.1% of the total reads mapped to the novel species, supporting the idea that these novel species are rare in the ISS environments. In-depth annotation of the genomes unveiled a variety of genes linked to amino acid and derivative synthesis, carbohydrate metabolism, cofactors, vitamins, prosthetic groups, pigments, and protein metabolism. Further analysis of these ISS-isolated organisms revealed that, on average, they contain 46 genes associated with virulence, disease, and defense. The main predicted functions of these genes are: conferring resistance to antibiotics and toxic compounds, and enabling invasion and intracellular resistance. After conducting antiSMASH analysis, it was found that there are roughly 16 cluster types across the six strains, including β-lactone and type III polyketide synthase (T3PKS) clusters. Based on these multi-faceted taxonomic methods, it was concluded that these six ISS strains represent five novel species, which we propose to name as follows: Arthrobacter burdickii IIF3SC-B10T (= NRRL B-65660T = DSM 115933T), Leifsonia virtsii F6_8S_P_1AT (= NRRL B-65661T = DSM 115931T), Leifsonia williamsii F6_8S_P_1BT (= NRRL B-65662T = DSM 115932T), Paenibacillus vandeheii F6_3S_P_1CT (= NRRL B-65663T = DSM 115940T), and Sporosarcina highlanderae F6_3S_P_2T (= NRRL B-65664T = DSM 115943T). Identifying and characterizing the genomes and phenotypes of novel microbes found in space habitats, like those explored in this study, is integral for expanding our genomic databases of space-relevant microbes. This approach offers the only reliable method to determine species composition, track microbial dispersion, and anticipate potential threats to human health from monitoring microbes on the surfaces and equipment within space habitats. By unraveling these microbial mysteries, we take a crucial step towards ensuring the safety and success of future space missions.

Phylogenetic affiliations and genomic characterization of novel bacterial species and their abundance in the International Space Station

Background

With the advent of long-term human habitation in space and on the moon, understanding how the built environment microbiome of space habitats differs from Earth habits, and how microbes survive, proliferate and spread in space conditions, is coming more and more important. The Microbial Tracking mission series has been monitoring the microbiome of the International Space Station (ISS) for almost a decade. During this mission series, six unique strains of Gram-positive bacteria, including two spore-forming and three non-spore-forming species, were isolated from the environmental surfaces of the International Space Station (ISS).

Results

The analysis of their 16S rRNA gene sequences revealed <99% similarities with previously described bacterial species. To further explore their phylogenetic affiliation, whole genome sequencing (WGS) was undertaken. For all strains, the gyrB gene exhibited <93% similarity with closely related species, which proved effective in categorizing these ISS strains as novel species. Average ucleotide identity (ANI) and digital DNA-DNA hybridization (dDDH) values, when compared to any known bacterial species, were less than <94% and 50% respectively for all species described here. Traditional biochemical tests, fatty acid profiling, polar lipid, and cell wall composition analyses were performed to generate phenotypic characterization of these ISS strains. A study of the shotgun metagenomic reads from the ISS samples, from which the novel species were isolated, showed that only 0.1% of the total reads mapped to the novel species, supporting the idea that these novel species are rare in the ISS environments. In-depth annotation of the genomes unveiled a variety of genes linked to amino acid and derivative synthesis, carbohydrate metabolism, cofactors, vitamins, prosthetic groups, pigments, and protein metabolism. Further analysis of these ISS-isolated organisms revealed that, on average, they contain 46 genes associated with virulence, disease, and defense. The main predicted functions of these genes are: conferring resistance to antibiotics and toxic compounds, and enabling invasion and intracellular resistance. After conducting antiSMASH analysis, it was found that there are roughly 16 cluster types across the six strains, including β-lactone and type III polyketide synthase (T3PKS) clusters.

Conclusions

Based on these multi-faceted taxonomic methods, it was concluded that these six ISS strains represent five novel species, which we propose to name as follows: Arthrobacter burdickii IIF3SC-B10T (=NRRL B-65660T), Leifsonia virtsii, F6_8S_P_1AT (=NRRL B-65661T), Leifsonia williamsii, F6_8S_P_1BT (=NRRL B- 65662T and DSMZ 115932T), Paenibacillus vandeheii, F6_3S_P_1CT(=NRRL B-65663T and DSMZ 115940T), and Sporosarcina highlanderae F6_3S_P_2 T(=NRRL B-65664T and DSMZ 115943T). Identifying and characterizing the genomes and phenotypes of novel microbes found in space habitats, like those explored in this study, is integral for expanding our genomic databases of space-relevant microbes. This approach offers the only reliable method to determine species composition, track microbial dispersion, and anticipate potential threats to human health from monitoring microbes on the surfaces and equipment within space habitats. By unraveling these microbial mysteries, we take a crucial step towards ensuring the safety and success of future space missions.

Analysis of the genes encoding the MBL-fold metallohydrolase superfamily proteins of the Pseudomonas putida BS3701 petroleum component-degrading strain

Objective. To determine whether the genes whose products are annotated as «MBL-fold metallohydrolase superfamily» are related to the proteins of the metallo-β-lactamase group. Materials and Methods. Sequences of the 7 genes annotated as «MBL-fold metallohydrolase superfamily» were analyzed using the following resources: ClustalW, IQ-TREE, iTOL. Selection of the oligonucleotides for real-time PCR was performed using the Primer-BLAST resource. The level of gene expression was assessed using real-time PCR. MIC and MBC measuring was performed using cefepime and meropenem. The double-disc method with EDTA was used to determine the presence of MBL in the strain. Results. Analysis of the nucleotide sequences of the studied genes revealed that all of them were not included in the clade containing sequences of metallo-β-lactamase. In the exponential growth phase, mRNAs corresponding to the studied proteins were found. Determination of MIC and MBC revealed a low level of resistance to antibiotics of the β-lactamase group. The phenotypic test was negative for MBL in P. putida strain BS3701. Conclusions. The investigated genes and corresponding proteins are not related to metallo-β-lactamases. They are not involved in the resistance of P. putida BS3701 to antibiotics of the metallo-β-lactamase group.

Metallo-β-lactamases in the Age of Multidrug Resistance: From Structure and Mechanism to Evolution, Dissemination, and Inhibitor Design

Antimicrobial resistance is one of the major problems in current practical medicine. The spread of genes coding for resistance determinants among bacteria challenges the use of approved antibiotics, narrowing the options for treatment. Resistance to carbapenems, last resort antibiotics, is a major concern. Metallo-β-lactamases (MBLs) hydrolyze carbapenems, penicillins, and cephalosporins, becoming central to this problem. These enzymes diverge with respect to serine-β-lactamases by exhibiting a different fold, active site, and catalytic features. Elucidating their catalytic mechanism has been a big challenge in the field that has limited the development of useful inhibitors. This review covers exhaustively the details of the active-site chemistries, the diversity of MBL alleles, the catalytic mechanism against different substrates, and how this information has helped developing inhibitors. We also discuss here different aspects critical to understand the success of MBLs in conferring resistance: the molecular determinants of their dissemination, their cell physiology, from the biogenesis to the processing involved in the transit to the periplasm, and the uptake of the Zn(II) ions upon metal starvation conditions, such as those encountered during an infection. In this regard, the chemical, biochemical and microbiological aspects provide an integrative view of the current knowledge of MBLs.

Ancient Antibiotics, Ancient Resistance

As the spread of antibiotic resistance threatens our ability to treat infections, avoiding the return of a preantibiotic era requires the discovery of new drugs. While therapeutic use of antibiotics followed by the inevitable selection of resistance is a modern phenomenon, these molecules and the genetic determinants of resistance were in use by environmental microbes long before humans discovered them. In this review, we discuss evidence that antibiotics and resistance were present in the environment before anthropogenic use, describing techniques including direct sampling of ancient DNA and phylogenetic analyses that are used to reconstruct the past. We also pay special attention to the ecological and evolutionary forces that have shaped the natural history of antibiotic biosynthesis, including a discussion of competitive versus signaling roles for antibiotics, proto-resistance, and substrate promiscuity of biosynthetic and resistance enzymes. Finally, by applying an evolutionary lens, we describe concepts governing the origins and evolution of biosynthetic gene clusters and cluster-associated resistance determinants. These insights into microbes' use of antibiotics in nature, a game they have been playing for millennia, can provide inspiration for discovery technologies and management strategies to combat the growing resistance crisis.

A promiscuous ancestral enzyme´s structure unveils protein variable regions of the highly diverse metallo-β-lactamase family

The metallo-β-lactamase fold is an ancient protein structure present in numerous enzyme families responsible for diverse biological processes. The crystal structure of the hyperthermostable crenarchaeal enzyme Igni18 from Ignicoccus hospitalis was solved at 2.3 Å and could resemble a possible first archetype of a multifunctional metallo-β-lactamase. Ancestral enzymes at the evolutionary origin are believed to be promiscuous all-rounders. Consistently, Igni18´s activity can be cofactor-dependently directed from β-lactamase to lactonase, lipase, phosphodiesterase, phosphotriesterase or phospholipase. Its core-domain is highly conserved within metallo-β-lactamases from Bacteria, Archaea and Eukarya and gives insights into evolution and function of enzymes from this superfamily. Structural alignments with diverse metallo-β-lactamase-fold-containing enzymes allowed the identification of Protein Variable Regions accounting for modulation of activity, specificity and oligomerization patterns. Docking of different substrates within the active sites revealed the basis for the crucial cofactor dependency of this enzyme superfamily.

A protein of the metallo-hydrolase/oxidoreductase superfamily with both beta-lactamase and ribonuclease activity is linked with translation in giant viruses

Proteins with a metallo-beta-lactamase (MBL) fold have been largely studied in bacteria in the framework of resistance to beta-lactams, but their spectrum of activities is broader. We show here that the giant Tupanvirus also encodes a MBL fold-protein that has orthologs in other giant viruses, a deep phylogenetic root and is clustered with tRNases. This protein is significantly associated with translation components in giant viruses. After expression in Escherichia coli, it was found to hydrolyse nitrocefin, a beta-lactam, and penicillin G. This was inhibited by sulbactam, a beta-lactamase inhibitor. In addition, the tupanvirus MBL fold-protein was not active on single- or double-stranded DNA, but degraded RNAs from bacteria and Acanthamoeba castellanii, the tupanvirus amoebal host. This activity was not neutralized by sulbactam. Overall, our results still broaden the host range of MBL fold-proteins, showing dual beta-lactamase/nuclease activities in giant viruses.

Promiscuous Enzyme Activity as a Driver of Allo and Iso Convergent Evolution, Lessons from the β-Lactamases

The probability of the evolution of a character depends on two factors: the probability of moving from one character state to another character state and the probability of the new character state fixation. The more the evolution of a character is probable, the more the convergent evolution will be witnessed, and consequently, convergent evolution could mean that the convergent character evolution results as a combination of these two factors. We investigated this phenomenon by studying the convergent evolution of biochemical functions. For the investigation we used the case of β-lactamases. β-lactamases hydrolyze β-lactams, which are antimicrobials able to block the DD-peptidases involved in bacterial cell wall synthesis. β-lactamase activity is present in two different superfamilies: the metallo-β-lactamase and the serine β-lactamase. The mechanism used to hydrolyze the β-lactam is different for the two superfamilies. We named this kind of evolution an allo-convergent evolution. We further showed that the β-lactamase activity evolved several times within each superfamily, a convergent evolution type that we named iso-convergent evolution. Both types of convergent evolution can be explained by the two evolutionary mechanisms discussed above. The probability of moving from one state to another is explained by the promiscuous β-lactamase activity present in the ancestral sequences of each superfamily, while the probability of fixation is explained in part by positive selection, as the organisms having β-lactamase activity allows them to resist organisms that secrete β-lactams. Indeed, an organism that has a mutation that increases the β-lactamase activity will be selected, as the organisms having this activity will have an advantage over the others.

The functional convergence of antibiotic resistance in β-lactamases is not conferred by a simple convergent substitution of amino acid

Bacterial resistance to antibiotics is a serious medical and public health concern worldwide. Such resistance is conferred by a variety of mechanisms, but the extensive variability in levels of resistance across bacteria is a common finding. Understanding the underlying evolutionary processes governing this functional variation in antibiotic resistance is important as it may allow the development of appropriate strategies to improve treatment options for bacterial infections. The main objective of this study was to examine the functional evolution of β-lactamases, a common mechanism of enzymatic resistance that inactivates a widely used class of antibiotics. We first obtained β-lactamase protein sequences and minimal inhibitory concentration (MIC), a measure of antibiotic function, from previously published literature. We then used a molecular phylogenetic framework to examine the evolution of β-lactamase functional activity. We found that the functional activity of antibiotic resistance mediated by β-lactamase has evolved in a convergent manner within molecular classes, but is not associated with any single amino acid substitution. This suggests that the dynamics of convergent evolution in this system can vary between the functional and molecular (sequence) levels. Such disassociation may hamper bioinformatic approaches to antibiotic resistance determination and underscore the need for (less efficient but more effective) activity assays as an essential step in evaluating resistance in a given case.

Sewage effluent from an Indian hospital harbors novel carbapenemases and integron-borne antibiotic resistance genes

BACKGROUND

Hospital wastewaters contain fecal material from a large number of individuals, of which many are undergoing antibiotic therapy. It is, thus, plausible that hospital wastewaters could provide opportunities to find novel carbapenemases and other resistance genes not yet described in clinical strains. Our aim was therefore to investigate the microbiota and antibiotic resistome of hospital effluent collected from the city of Mumbai, India, with a special focus on identifying novel carbapenemases.

RESULTS

Shotgun metagenomics revealed a total of 112 different mobile antibiotic resistance gene types, conferring resistance against almost all classes of antibiotics. Beta-lactamase genes, including encoding clinically important carbapenemases, such as NDM, VIM, IMP, KPC, and OXA-48, were abundant. NDM (0.9% relative abundance to 16S rRNA genes) was the most common carbapenemase gene, followed by OXA-58 (0.84% relative abundance to 16S rRNA genes). Among the investigated mobile genetic elements, class 1 integrons (11% relative abundance to 16S rRNA genes) were the most abundant. The genus Acinetobacter accounted for as many as 30% of the total 16S rRNA reads, with A. baumannii accounting for an estimated 2.5%. High throughput sequencing of amplified integron gene cassettes identified a novel functional variant of an IMP-type (proposed IMP-81) carbapenemase gene (eight aa substitutions) along with recently described novel resistance genes like sul4 and bla_RSA1. Using a computational hidden Markov model, we detected 27 unique metallo-beta-lactamase (MBL) genes in the shotgun data, of which nine were novel subclass B1 genes, one novel subclass B2, and 10 novel subclass B3 genes. Six of the seven novel MBL genes were functional when expressed in Escherichia coli.

CONCLUSION

By exploring hospital wastewater from India, our understanding of the diversity of carbapenemases has been extended. The study also demonstrates that the microbiota of hospital wastewater can serve as a reservoir of novel resistance genes, including previously uncharacterized carbapenemases with the potential to spread further.

Identification and reconstruction of novel antibiotic resistance genes from metagenomes

BACKGROUND

Environmental and commensal bacteria maintain a diverse and largely unknown collection of antibiotic resistance genes (ARGs) that, over time, may be mobilized and transferred to pathogens. Metagenomics enables cultivation-independent characterization of bacterial communities but the resulting data is noisy and highly fragmented, severely hampering the identification of previously undescribed ARGs. We have therefore developed fARGene, a method for identification and reconstruction of ARGs directly from shotgun metagenomic data.

RESULTS

fARGene uses optimized gene models and can therefore with high accuracy identify previously uncharacterized resistance genes, even if their sequence similarity to known ARGs is low. By performing the analysis directly on the metagenomic fragments, fARGene also circumvents the need for a high-quality assembly. To demonstrate the applicability of fARGene, we reconstructed β-lactamases from five billion metagenomic reads, resulting in 221 ARGs, of which 58 were previously not reported. Based on 38 ARGs reconstructed by fARGene, experimental verification showed that 81% provided a resistance phenotype in Escherichia coli. Compared to other methods for detecting ARGs in metagenomic data, fARGene has superior sensitivity and the ability to reconstruct previously unknown genes directly from the sequence reads.

CONCLUSIONS

We conclude that fARGene provides an efficient and reliable way to explore the unknown resistome in bacterial communities. The method is applicable to any type of ARGs and is freely available via GitHub under the MIT license.

Systematic Identification and Classification of β-Lactamases Based on Sequence Similarity Criteria: β-Lactamase Annotation

β-lactamases, the enzymes responsible for resistance to β-lactam antibiotics, are widespread among prokaryotic genera. However, current β-lactamase classification schemes do not represent their present diversity. Here, we propose a workflow to identify and classify β-lactamases. Initially, a set of curated sequences was used as a model for the construction of profiles Hidden Markov Models (HMM), specific for each β-lactamase class. An extensive, nonredundant set of β-lactamase sequences was constructed from 7 different resistance proteins databases to test the methodology. The profiles HMM were improved for their specificity and sensitivity and then applied to fully assembled genomes. Five hierarchical classification levels are described, and a new class of β-lactamases with fused domains is proposed. Our profiles HMM provide a better annotation of β-lactamases, with classes and subclasses defined by objective criteria such as sequence similarity. This classification offers a solid base to the elaboration of studies on the diversity, dispersion, prevalence, and evolution of the different classes and subclasses of this critical enzymatic activity.

Phylogenomic Analysis of β-Lactamase in Archaea and Bacteria Enables the Identification of Putative New Members

β-lactamases are enzymes which are commonly produced by bacteria and which degrade the β-lactam ring of β-lactam antibiotics, namely penicillins, cephalosporins, carbapenems, and monobactams, and inactivate these antibiotics. We performed a rational and comprehensive investigation of β-lactamases in different biological databases. In this study, we constructed hidden Markov model profiles as well as the ancestral sequence of four classes of β-lactamases (A, B, C, and D), which were used to identify potential β-lactamases from environmental metagenomic (1206), human microbiome metagenomic (6417), human microbiome reference genome (1310), and NCBI's nonredundant databases (44101). Our analysis revealed the existence of putative β-lactamases in the metagenomic databases, which appeared to be similar to the four different molecular classes (A-D). This is the first report on the large-scale phylogenetic diversity of new members of β-lactamases, and our results revealed that metagenomic database dark-matter contains β-lactamase-like antibiotic resistance genes.

Enzyme function and its evolution

With rapid increases over recent years in the determination of protein sequence and structure, alongside knowledge of thousands of enzyme functions and hundreds of chemical mechanisms, it is now possible to combine breadth and depth in our understanding of enzyme evolution. Phylogenetics continues to move forward, though determining correct evolutionary family trees is not trivial. Protein function prediction has spawned a variety of promising methods that offer the prospect of identifying enzymes across the whole range of chemical functions and over numerous species. This knowledge is essential to understand antibiotic resistance, as well as in protein re-engineering and de novo enzyme design.

Identification of 76 novel B1 metallo-β-lactamases through large-scale screening of genomic and metagenomic data

BACKGROUND

Metallo-β-lactamases are bacterial enzymes that provide resistance to carbapenems, the most potent class of antibiotics. These enzymes are commonly encoded on mobile genetic elements, which, together with their broad substrate spectrum and lack of clinically useful inhibitors, make them a particularly problematic class of antibiotic resistance determinants. We hypothesized that there is a large and unexplored reservoir of unknown metallo-β-lactamases, some of which may spread to pathogens, thereby threatening public health. The aim of this study was to identify novel metallo-β-lactamases of class B1, the most clinically important subclass of these enzymes.

RESULTS

Based on a new computational method using an optimized hidden Markov model, we analyzed over 10,000 bacterial genomes and plasmids together with more than 5 terabases of metagenomic data to identify novel metallo-β-lactamase genes. In total, 76 novel genes were predicted, forming 59 previously undescribed metallo-β-lactamase gene families. The ability to hydrolyze imipenem in an Escherichia coli host was experimentally confirmed for 18 of the 21 tested genes. Two of the novel B1 metallo-β-lactamase genes contained atypical zinc-binding motifs in their active sites, which were previously undescribed for metallo-β-lactamases. Phylogenetic analysis showed that B1 metallo-β-lactamases could be divided into five major groups based on their evolutionary origin. Our results also show that, except for one, all of the previously characterized mobile B1 β-lactamases are likely to have originated from chromosomal genes present in Shewanella spp. and other Proteobacterial species.

CONCLUSIONS

This study more than doubles the number of known B1 metallo-β-lactamases. The findings have further elucidated the diversity and evolutionary history of this important class of antibiotic resistance genes and prepare us for some of the challenges that may be faced in clinics in the future.

Exploring the past and the future of protein evolution with ancestral sequence reconstruction: the 'retro' approach to protein engineering

A central goal in molecular evolution is to understand the ways in which genes and proteins evolve in response to changing environments. In the absence of intact DNA from fossils, ancestral sequence reconstruction (ASR) can be used to infer the evolutionary precursors of extant proteins. To date, ancestral proteins belonging to eubacteria, archaea, yeast and vertebrates have been inferred that have been hypothesized to date from between several million to over 3 billion years ago. ASR has yielded insights into the early history of life on Earth and the evolution of proteins and macromolecular complexes. Recently, however, ASR has developed from a tool for testing hypotheses about protein evolution to a useful means for designing novel proteins. The strength of this approach lies in the ability to infer ancestral sequences encoding proteins that have desirable properties compared with contemporary forms, particularly thermostability and broad substrate range, making them good starting points for laboratory evolution. Developments in technologies for DNA sequencing and synthesis and computational phylogenetic analysis have led to an escalation in the number of ancient proteins resurrected in the last decade and greatly facilitated the use of ASR in the burgeoning field of synthetic biology. However, the primary challenge of ASR remains in accurately inferring ancestral states, despite the uncertainty arising from evolutionary models, incomplete sequences and limited phylogenetic trees. This review will focus, firstly, on the use of ASR to uncover links between sequence and phenotype and, secondly, on the practical application of ASR in protein engineering.

Resurrecting ancestral structural dynamics of an antiviral immune receptor: adaptive binding pocket reorganization repeatedly shifts RNA preference

Background

Although resurrecting ancestral proteins is a powerful tool for understanding the molecular-functional evolution of gene families, nearly all studies have examined proteins functioning in relatively stable biological processes. The extent to which more dynamic systems obey the same ‘rules’ governing stable processes is unclear. Here we present the first detailed investigation of the functional evolution of the RIG-like receptors (RLRs), a family of innate immune receptors that detect viral RNA in the cytoplasm.

Results

Using kinetic binding assays and molecular dynamics simulations of ancestral proteins, we demonstrate how a small number of adaptive protein-coding changes repeatedly shifted the RNA preference of RLRs throughout animal evolution by reorganizing the shape and electrostatic distribution across the RNA binding pocket, altering the hydrogen bond network between the RLR and its RNA target. In contrast to observations of proteins involved in metabolism and development, we find that RLR-RNA preference ‘flip flopped’ between two functional states, and shifts in RNA preference were not always coupled to gene duplications or speciation events. We demonstrate at least one reversion of RLR-RNA preference from a derived to an ancestral function through a novel structural mechanism, indicating multiple structural implementations of similar functions.

Conclusions

Our results suggest a model in which frequent shifts in selection pressures imposed by an evolutionary arms race preclude the long-term functional optimization observed in stable biological systems. As a result, the evolutionary dynamics of immune receptors may be less constrained by structural epistasis and historical contingency.

Electronic supplementary material

The online version of this article (doi:10.1186/s12862-016-0818-6) contains supplementary material, which is available to authorized users.

Why do Sequence Signatures Predict Enzyme Mechanism? Homology versus Chemistry

First, we identify InterPro sequence signatures representing evolutionary relatedness and, second, signatures identifying specific chemical machinery. Thus, we predict the chemical mechanisms of enzyme-catalyzed reactions from catalytic and non-catalytic subsets of InterPro signatures. We first scanned our 249 sequences using InterProScan and then used the MACiE database to identify those amino acid residues that are important for catalysis. The sequences were mutated in silico to replace these catalytic residues with glycine and then again scanned using InterProScan. Those signature matches from the original scan that disappeared on mutation were called catalytic. Mechanism was predicted using all signatures, only the 78 “catalytic” signatures, or only the 519 “non-catalytic” signatures. The non-catalytic signatures gave indistinguishable results from those for the whole feature set, with precision of 0.991 and sensitivity of 0.970. The catalytic signatures alone gave less impressive predictivity, with precision and sensitivity of 0.791 and 0.735, respectively. These results show that our successful prediction of enzyme mechanism is mostly by homology rather than by identifying catalytic machinery.