Sequence-function-stability relationships in proteins from datasets of functionally annotated variants: the case of TEM β-lactamases

Context-aware geometric deep learning for protein sequence design

Protein design and engineering are evolving at an unprecedented pace leveraging the advances in deep learning. Current models nonetheless cannot natively consider non-protein entities within the design process. Here, we introduce a deep learning approach based solely on a geometric transformer of atomic coordinates and element names that predicts protein sequences from backbone scaffolds aware of the restraints imposed by diverse molecular environments. To validate the method, we show that it can produce highly thermostable, catalytically active enzymes with high success rates. This concept is anticipated to improve the versatility of protein design pipelines for crafting desired functions.

Exploiting the aggregation propensity of beta-lactamases to design inhibitors that induce enzyme misfolding

There is an arms race between beta-lactam antibiotics development and co-evolving beta-lactamases, which provide resistance by breaking down beta-lactam rings. We have observed that certain beta-lactamases tend to aggregate, which persists throughout their evolution under the selective pressure of antibiotics on their active sites. Interestingly, we find that existing beta-lactamase active site inhibitors can act as molecular chaperones, promoting the proper folding of these resistance factors. Therefore, we have created Pept-Ins, synthetic peptides designed to exploit the structural weaknesses of beta-lactamases by causing them to misfold into intracellular inclusion bodies. This approach restores sensitivity to a wide range of beta-lactam antibiotics in resistant clinical isolates, including those with Extended Spectrum variants that pose significant challenges in medical practice. Our findings suggest that targeted aggregation of resistance factors could offer a strategy for identifying molecules that aid in addressing the global antibiotic resistance crisis.

Metallo-Beta-Lactamase-like Encoding Genes in Candidate Phyla Radiation: Widespread and Highly Divergent Proteins with Potential Multifunctionality

The Candidate Phyla Radiation (CPR) was found to harbor a vast repertoire of genes encoding for enzymes with potential antibiotic resistance activity. Among these, as many as 3349 genes were predicted in silico to contain a metallo-beta-lactamase-like (MBL-like) fold. These proteins were subject to an in silico functional characterization by comparing their protein profiles (presence/absence of conserved protein domains) to other MBLs, including 24 already expressed in vitro, along with those of the beta-lactamase database (BLDB) (n = 761). The sequence similarity network (SSN) was then used to predict the functional clusters of CPR MBL-like sequences. Our findings showed that CPR MBL-like sequences were longer and more diverse than bacterial MBL sequences, with a high content of functional domains. Most CPR MBL-like sequences did not show any SSN connectivity with expressed MBLs, indicating the presence of many potential, yet unidentified, functions in CPR. In conclusion, CPR was shown to have many protein functions and a large sequence variability of MBL-like folds, exceeding all known MBLs. Further experimental and evolutionary studies of this superfamily of hydrolyzing enzymes are necessary to illustrate their functional annotation, origin, and expansion for adaptation or specialization within a given niche or compared to a specific substrate.

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.

Inhibitors of β-Lactamases. New Life of β-Lactam Antibiotics

β-Lactam antibiotics account for about 60% of all produced antibiotics. Due to a high activity and minimal side effects, they are the most commonly used class of antibacterial drugs for the treatment of various infectious diseases of humans and animals, including severe hospital infections. However, the emergence of bacteria resistant to β-lactams has led to the clinical inefficiency of these antibiotics, and as a result, their use in medicine has been limited. The search for new effective ways for overcoming the resistance to β-lactam antibiotics is an essential task. The major mechanism of bacterial resistance is the synthesis of β-lactamases (BLs) that break the antibiotic β-lactam ring. Here, we review specific inhibitors of serine β-lactamases and metallo-β-lactamases and discuss approaches for creating new inhibitors that would prolong the "life" of β-lactams.

Sequence-structure-function relationships in class I MHC: A local frustration perspective

Class I Major Histocompatibility Complex (MHC) binds short antigenic peptides with the help of Peptide Loading Complex (PLC), and presents them to T-cell Receptors (TCRs) of cytotoxic T-cells and Killer-cell Immunglobulin-like Receptors (KIRs) of Natural Killer (NK) cells. With more than 10000 alleles, human MHC (Human Leukocyte Antigen, HLA) is the most polymorphic protein in humans. This allelic diversity provides a wide coverage of peptide sequence space, yet does not affect the three-dimensional structure of the complex. Moreover, TCRs mostly interact with HLA in a common diagonal binding mode, and KIR-HLA interaction is allele-dependent. With the aim of establishing a framework for understanding the relationships between polymorphism (sequence), structure (conserved fold) and function (protein interactions) of the human MHC, we performed here a local frustration analysis on pMHC homology models covering 1436 HLA I alleles. An analysis of local frustration profiles indicated that (1) variations in MHC fold are unlikely due to minimally-frustrated and relatively conserved residues within the HLA peptide-binding groove, (2) high frustration patches on HLA helices are either involved in or near interaction sites of MHC with the TCR, KIR, or tapasin of the PLC, and (3) peptide ligands mainly stabilize the F-pocket of HLA binding groove.

Highly Contingent Phenotypes of Lon Protease Deficiency in Escherichia coli upon Antibiotic Challenge

Evolutionary trajectories and mutational landscapes of drug-resistant bacteria are influenced by cell-intrinsic and extrinsic factors. In this study, I demonstrated that loss of the Lon protease altered susceptibility of Escherichia coli to trimethoprim and that these effects were strongly contingent on the drug concentration and genetic background. Lon, an AAA⁺ ATPase, is a bacterial master regulator protease involved in cytokinesis, suppression of transposition events, and clearance of misfolded proteins. I show that Lon deficiency enhances intrinsic drug tolerance at sub-MIC levels of trimethoprim. As a result, loss of Lon, though disadvantageous under drug-free conditions, has a selective advantage at low concentrations of trimethoprim. At high drug concentrations, however, Lon deficiency is detrimental for E. coli I show that the former is explained by suppression of drug efflux by Lon, while the latter can be attributed to SulA-dependent hyperfilamentation. On the other hand, deletion of lon in a trimethoprim-resistant mutant E. coli strain (harboring the Trp30Gly dihydrofolate reductase [DHFR] allele) directly potentiates resistance by enhancing the in vivo stability of mutant DHFR. Using extensive mutational analysis at 3 hot spots of resistance, I show that many resistance-conferring mutations render DHFR prone to proteolysis. This trade-off between gaining resistance and losing in vivo stability limits the number of mutations in DHFR that can confer trimethoprim resistance. Loss of Lon expands the mutational capacity for acquisition of trimethoprim resistance. This paper identifies the multipronged action of Lon in trimethoprim resistance in E. coli and provides mechanistic insight into how genetic backgrounds and drug concentrations may alter the potential for antimicrobial resistance evolution.IMPORTANCE Understanding the evolutionary dynamics of antimicrobial resistance is vital to curb its emergence and spread. Being fundamentally similar to natural selection, the fitness of resistant mutants is a key parameter to consider in the evolutionary dynamics of antimicrobial resistance (AMR). Various intrinsic and extrinsic factors modulate the fitness of resistant bacteria. This study demonstrated that Lon, a bacterial master regulator protease, influences drug tolerance and resistance. Lon is a key regulator of several fundamental processes in bacteria, including cytokinesis. I demonstrated that Lon deficiency produces highly contingent phenotypes in E. coli challenged with trimethoprim and can expand the mutational repertoire available to E. coli to evolve resistance. This multipronged influence of Lon on drug resistance provides an illustrative instance of how master regulators shape the response of bacteria to antibiotics.

Structure-Based Analysis of Cryptic-Site Opening

Many proteins in their unbound structures have cryptic sites that are not appropriately sized for drug binding. We consider here 32 proteins from the recently published CryptoSite set with validated cryptic sites, and study whether the sites remain cryptic in all available X-ray structures of the proteins solved without any ligand bound near the sites. It was shown that only few of these proteins have binding pockets that never form without ligand binding. Sites that are cryptic in some structures but spontaneously form in others are also rare. In most proteins the forming of pockets is affected by mutations or ligand binding at locations far from the cryptic site. To further explore these mechanisms, we applied adiabatic biased molecular dynamics simulations to guide the proteins from their ligand-free structures to ligand-bound conformations, and studied the distribution of druggability scores of the pockets located at the cryptic sites.

The impact of long-distance mutations on the Ω-loop conformation in TEM type β-lactamases

β-lactamases are hydrolytic enzymes primarily responsible for occurrence and abundance of bacteria resistant to β-lactam antibiotics. TEM type β-lactamases are formed by the parent enzyme TEM-1 and more than two hundred of its mutants. Positions for the known amino acid substitutions cover ∼30% of TEM type enzyme's sequence. These substitutions are divided into the key mutations that lead to changes in catalytic properties of β-lactamases, and the secondary ones, which role is poorly understood. In this study, Residue Interaction Networks were constructed from molecular dynamic trajectories of β-lactamase TEM-1 and its variants with two key substitutions, G238S and E240K, and their combinations with secondary ones (M182T and Q39K). Particular attention was paid to a detailed analysis of the interactions that affect conformation and mobility of the Ω-loop, representing a part of the β-lactamase active site. It was shown that key mutations weakened the stability of contact inside the Ω-loop thus increasing its mobility. Combination of three amino acid substitutions, including the 182 residue, leads to the release of R65 promoting its new contacts with N175 and D176. As a result, Ω-loop is fixed on the protein globule. The second distal mutation Q39K prevents changes in spatial position of R65, which lead to the weakening of the effect of M182T substitution and the recovery of the Ω-loop mobility. Thus, the distal secondary mutations are directed for recovering the mobility of enzyme disturbed by the key mutations responsible for expansion of substrate specificity. AbbreviationsESBLextended spectrum beta-lactamasesIRinhibitor resistant beta-lactamasesMDmolecular dynamicsRINresidue interaction networksRMSDroot mean square deviationRMSFroot mean square fluctuations.Communicated by Ramaswamy H. Sarma.

Trade-offs with stability modulate innate and mutationally acquired drug resistance in bacterial dihydrofolate reductase enzymes

Structural stability is a major constraint on the evolution of protein sequences. However, under strong directional selection, mutations that confer novel phenotypes but compromise structural stability of proteins may be permissible. During the evolution of antibiotic resistance, mutations that confer drug resistance often have pleiotropic effects on the structure and function of antibiotic-target proteins, usually essential metabolic enzymes. In the present study, we show that trimethoprim (TMP)-resistant alleles of dihydrofolate reductase from Escherichia coli (EcDHFR) harboring the Trp30Gly, Trp30Arg or Trp30Cys mutations are significantly less stable than the wild-type, making them prone to aggregation and proteolysis. This destabilization is associated with a lower expression level, resulting in a fitness cost and negative epistasis with other TMP-resistant mutations in EcDHFR. Using structure-based mutational analysis, we show that perturbation of critical stabilizing hydrophobic interactions in wild-type EcDHFR enzyme explains the phenotypes of Trp30 mutants. Surprisingly, though crucial for the stability of EcDHFR, significant sequence variation is found at this site among bacterial dihydrofolate reductases (DHFRs). Mutational and computational analyses in EcDHFR and in DHFR enzymes from Staphylococcus aureus and Mycobacterium tuberculosis demonstrate that natural variation at this site and its interacting hydrophobic residues modulates TMP resistance in other bacterial DHFRs as well, and may explain the different susceptibilities of bacterial pathogens to TMP. Our study demonstrates that trade-offs between structural stability and function can influence innate drug resistance as well as the potential for mutationally acquired drug resistance of an enzyme.

Mutual influence of secondary and key drug-resistance mutations on catalytic properties and thermal stability of TEM-type β-lactamases

Highly mutable β-lactamases are responsible for the ability of Gram-negative bacteria to resist β-lactam antibiotics. Using site-directed mutagenesis technique, we have produced in vitro a number of recombinant analogs of naturally occurring TEM-type β-lactamases, bearing the secondary substitution Q39K and key mutations related to the extended-spectrum (E104K, R164S) and inhibitor-resistant (M69V) β-lactamases. The mutation Q39K alone was found to be neutral and hardly affected the catalytic properties of β-lactamases. However, in combination with the key mutations, this substitution resulted in decreased KM values towards hydrolysis of a chromogenic substrate, CENTA. The ability of enzymes to restore catalytic activity after exposure to elevated temperature has been examined. All double and triple mutants of β-lactamase TEM-1 bearing the Q39K substitution showed lower thermal stability compared with the enzyme with Q39 intact. A sharp decrease in the stability was observed when Q39K was combined with E104K and M69V. The key R164S substitution demonstrated unusual ability to resist thermal inactivation. Computer analysis of the structure and molecular dynamics of β-lactamase TEM-1 revealed a network of hydrogen bonds from the residues Q39 and K32, related to the N-terminal α-helix, towards the residues R244 and G236, located in the vicinity of the enzyme's catalytic site. Replacement of Q39 by lysine in combination with the key drug resistance mutations may be responsible for loss of protein thermal stability and elevated mobility of its secondary structure elements. This effect on the activity of β-lactamases can be used as a new potential target for inhibiting the enzyme.

A Distal Disulfide Bridge in OXA-1 β-Lactamase Stabilizes the Catalytic Center and Alters the Dynamics of the Specificity Determining Ω Loop

Widespread antibiotic resistance, particularly when mediated by broad-spectrum β-lactamases, has major implications for public health. Substitutions in the active site often allow broad-spectrum enzymes to accommodate diverse types of β-lactams. Substitutions observed outside the active site are thought to compensate for the loss of thermal stability. The OXA-1 clade of class D β-lactamases contains a pair of conserved cysteines located outside the active site that forms a disulfide bond in the periplasm. Here, the effect of the distal disulfide bond on the structure and dynamics of OXA-1 was investigated via 4 μs molecular dynamics simulations. The results reveal that the disulfide promotes the preorganized orientation of the catalytic residues and affects the conformation of the functionally important Ω loop. Furthermore, principal component analysis reveals differences in the global dynamics between the oxidized and reduced forms, especially in the motions involving the Ω loop. A dynamical network analysis indicates that, in the oxidized form, in addition to its role in ligand binding, the KTG family motif is a central hub of the global dynamics. As activity of OXA-1 has been measured only in the reduced form, we suggest that accurate assessment of its functional profile would require oxidative conditions mimicking periplasm.

Detection and sequence/structure mapping of biophysical constraints to protein variation in saturated mutational libraries and protein sequence alignments with a dedicated server

Background

Protein variability can now be studied by measuring high-resolution tolerance-to-substitution maps and fitness landscapes in saturated mutational libraries. But these rich and expensive datasets are typically interpreted coarsely, restricting detailed analyses to positions of extremely high or low variability or dubbed important beforehand based on existing knowledge about active sites, interaction surfaces, (de)stabilizing mutations, etc.

Results

Our new webserver PsychoProt (freely available without registration at http://psychoprot.epfl.ch or at http://lucianoabriata.altervista.org/psychoprot/index.html) helps to detect, quantify, and sequence/structure map the biophysical and biochemical traits that shape amino acid preferences throughout a protein as determined by deep-sequencing of saturated mutational libraries or from large alignments of naturally occurring variants.

Discussion

We exemplify how PsychoProt helps to (i) unveil protein structure-function relationships from experiments and from alignments that are consistent with structures according to coevolution analysis, (ii) recall global information about structural and functional features and identify hitherto unknown constraints to variation in alignments, and (iii) point at different sources of variation among related experimental datasets or between experimental and alignment-based data. Remarkably, metabolic costs of the amino acids pose strong constraints to variability at protein surfaces in nature but not in the laboratory. This and other differences call for caution when extrapolating results from in vitro experiments to natural scenarios in, for example, studies of protein evolution.

Conclusion

We show through examples how PsychoProt can be a useful tool for the broad communities of structural biology and molecular evolution, particularly for studies about protein modeling, evolution and design.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-016-1124-4) contains supplementary material, which is available to authorized users.

Protein Frustratometer 2: a tool to localize energetic frustration in protein molecules, now with electrostatics

The protein frustratometer is an energy landscape theory-inspired algorithm that aims at localizing and quantifying the energetic frustration present in protein molecules. Frustration is a useful concept for analyzing proteins’ biological behavior. It compares the energy distributions of the native state with respect to structural decoys. The network of minimally frustrated interactions encompasses the folding core of the molecule. Sites of high local frustration often correlate with functional regions such as binding sites and regions involved in allosteric transitions. We present here an upgraded version of a webserver that measures local frustration. The new implementation that allows the inclusion of electrostatic energy terms, important to the interactions with nucleic acids, is significantly faster than the previous version enabling the analysis of large macromolecular complexes within a user-friendly interface. The webserver is freely available at URL: http://frustratometer.qb.fcen.uba.ar.

Optimization of Conformational Dynamics in an Epistatic Evolutionary Trajectory

The understanding of protein evolution depends on the ability to relate the impact of mutations on molecular traits to organismal fitness. Biological activity and robustness have been regarded as important features in shaping protein evolutionary landscapes. Conformational dynamics, which is essential for protein function, has received little attention in the context of evolutionary analyses. Here we employ NMR spectroscopy, the chief experimental tool to describe protein dynamics at atomic level in solution at room temperature, to study the intrinsic dynamic features of a metallo- Β: -lactamase enzyme and three variants identified during a directed evolution experiment that led to an expanded substrate profile. We show that conformational dynamics in the catalytically relevant microsecond to millisecond timescale is optimized along the favored evolutionary trajectory. In addition, we observe that the effects of mutations on dynamics are epistatic. Mutation Gly262Ser introduces slow dynamics on several residues that surround the active site when introduced in the wild-type enzyme. Mutation Asn70Ser removes the slow dynamics observed for few residues of the wild-type enzyme, but increases the number of residues that undergo slow dynamics when introduced in the Gly262Ser mutant. These effects on dynamics correlate with the epistatic interaction between these two mutations on the bacterial phenotype. These findings indicate that conformational dynamics is an evolvable trait, and that proteins endowed with more dynamic active sites also display a larger potential for promoting evolution.

Mistranslation drives the evolution of robustness in TEM-1 β-lactamase

How biological systems such as proteins achieve robustness to ubiquitous perturbations is a fundamental biological question. Such perturbations include errors that introduce phenotypic mutations into nascent proteins during the translation of mRNA. These errors are remarkably frequent. They are also costly, because they reduce protein stability and help create toxic misfolded proteins. Adaptive evolution might reduce these costs of protein mistranslation by two principal mechanisms. The first increases the accuracy of translation via synonymous "high fidelity" codons at especially sensitive sites. The second increases the robustness of proteins to phenotypic errors via amino acids that increase protein stability. To study how these mechanisms are exploited by populations evolving in the laboratory, we evolved the antibiotic resistance gene TEM-1 in Escherichia coli hosts with either normal or high rates of mistranslation. We analyzed TEM-1 populations that evolved under relaxed and stringent selection for antibiotic resistance by single molecule real-time sequencing. Under relaxed selection, mistranslating populations reduce mistranslation costs by reducing TEM-1 expression. Under stringent selection, they efficiently purge destabilizing amino acid changes. More importantly, they accumulate stabilizing amino acid changes rather than synonymous changes that increase translational accuracy. In the large populations we study, and on short evolutionary timescales, the path of least resistance in TEM-1 evolution consists of reducing the consequences of translation errors rather than the errors themselves.

Synthetic biology for the directed evolution of protein biocatalysts: navigating sequence space intelligently

The amino acid sequence of a protein affects both its structure and its function. Thus, the ability to modify the sequence, and hence the structure and activity, of individual proteins in a systematic way, opens up many opportunities, both scientifically and (as we focus on here) for exploitation in biocatalysis. Modern methods of synthetic biology, whereby increasingly large sequences of DNA can be synthesised de novo, allow an unprecedented ability to engineer proteins with novel functions. However, the number of possible proteins is far too large to test individually, so we need means for navigating the 'search space' of possible protein sequences efficiently and reliably in order to find desirable activities and other properties. Enzymologists distinguish binding (Kd) and catalytic (kcat) steps. In a similar way, judicious strategies have blended design (for binding, specificity and active site modelling) with the more empirical methods of classical directed evolution (DE) for improving kcat (where natural evolution rarely seeks the highest values), especially with regard to residues distant from the active site and where the functional linkages underpinning enzyme dynamics are both unknown and hard to predict. Epistasis (where the 'best' amino acid at one site depends on that or those at others) is a notable feature of directed evolution. The aim of this review is to highlight some of the approaches that are being developed to allow us to use directed evolution to improve enzyme properties, often dramatically. We note that directed evolution differs in a number of ways from natural evolution, including in particular the available mechanisms and the likely selection pressures. Thus, we stress the opportunities afforded by techniques that enable one to map sequence to (structure and) activity in silico, as an effective means of modelling and exploring protein landscapes. Because known landscapes may be assessed and reasoned about as a whole, simultaneously, this offers opportunities for protein improvement not readily available to natural evolution on rapid timescales. Intelligent landscape navigation, informed by sequence-activity relationships and coupled to the emerging methods of synthetic biology, offers scope for the development of novel biocatalysts that are both highly active and robust.

How structural and physicochemical determinants shape sequence constraints in a functional enzyme

The need for interfacing structural biology and biophysics to molecular evolution is being increasingly recognized. One part of the big problem is to understand how physics and chemistry shape the sequence space available to functional proteins, while satisfying the needs of biology. Here we present a quantitative, structure-based analysis of a high-resolution map describing the tolerance to all substitutions in all positions of a functional enzyme, namely a TEM lactamase previously studied through deep sequencing of mutants growing in competition experiments with selection against ampicillin. Substitutions are rarely observed within 7 Å of the active site, a stringency that is relaxed slowly and extends up to 15–20 Å, with buried residues being especially sensitive. Substitution patterns in over one third of the residues can be quantitatively modeled by monotonic dependencies on amino acid descriptors and predictions of changes in folding stability. Amino acid volume and steric hindrance shape constraints on the protein core; hydrophobicity and solubility shape constraints on hydrophobic clusters underneath the surface, and on salt bridges and polar networks at the protein surface together with charge and hydrogen bonding capacity. Amino acid solubility, flexibility and conformational descriptors also provide additional constraints at many locations. These findings provide fundamental insights into the chemistry underlying protein evolution and design, by quantitating links between sequence and different protein traits, illuminating subtle and unexpected sequence-trait relationships and pinpointing what traits are sacrificed upon gain-of-function mutation.

CBMAR: a comprehensive β-lactamase molecular annotation resource

β-Lactam antibiotics are among the most widely used antibiotics against microbial pathogens. However, enzymatic hydrolysis of these antibiotics by bacterial β-lactamases is increasingly compromising their efficiency. Although new generation β-lactam antibiotics have been developed to combat antibiotic resistance, β-lactamases have also evolved along with the new variants of the substrate. A strong selection pressure from the newer generation of β-lactam antibiotics has resulted in evolution of different families within each class of β-lactamase. To facilitate detailed characterization of different families of β-lactamases, we have created a database, CBMAR, which facilitates comprehensive molecular annotation and discovery of novel β-lactamases. As against the limited scope of other existing similar databases, CBMAR provides information useful for molecular and biochemical characterization of each family of β-lactamase. The basic architecture of CBMAR is based on Ambler classification, which divides β-lactamases as serine (Classes A, C and D) and metallo-β-lactamases (Class B). Each class is further divided into several families on the basis of their hydrolytic character. In CBMAR, each family is annotated with (i) sequence variability, (ii) antibiotic resistance profile, (iii) inhibitor susceptibility, (iv) active site, (v) family fingerprints, (vi) mutational profile, (vii) variants, (viii) gene location, (ix) phylogenetic tree and several other features. Each entry also has external links to the relevant protein/nucleotide sequence and structure databases. The database also supports sequence similarity searches using BLAST and assigns a new β-lactamase protein to its respective family on the basis of family-specific fingerprint. Database URL: http://14.139.227.92/mkumar/lactamasedb

A dimerization interface mediated by functionally critical residues creates interfacial disulfide bonds and copper sites in CueP

CueP confers bacterial copper resistance in the periplasm, particularly under anaerobic conditions, through an unknown mechanism. The only available structure and limited solution data suggest that CueP forms noncovalent dimers in solution, whereas sequence conservation suggests important roles for three cysteines and two histidines as copper ligands. Here we report evidence of a dimerization equilibrium mediated by a newly identified interface of functional relevance, which occludes internal copper sites and disulfide bonds but allows for intra- and interchain disulfide bonding, an extensive disulfide relay, and interfacial copper sites. Our results suggest a role for CueP linking redox-state sensing and copper detoxification.

Deletion mutations conferring substrate spectrum extension in the class A β-lactamase

We describe four new deletion mutations in a class A β-lactamase PenA in Burkholderia thailandensis, each conferring an extended substrate spectrum. Single-amino-acid deletions T171del, I173del, and P174del and a two-amino-acid deletion, R165_T167delinsP, occurred in the omega loop, increasing the flexibility of the binding cavity. This rare collection of mutations has significance, allowing exploration of the diverse evolutionary trajectories of β-lactamases and as potential future mutations conferring high-level ceftazidime resistance on isolates from clinical settings, compared with amino acid substitution mutations.

Antibiotics as selectors and accelerators of diversity in the mechanisms of resistance: from the resistome to genetic plasticity in the β-lactamases world

Antibiotics and antibiotic resistance determinants, natural molecules closely related to bacterial physiology and consistent with an ancient origin, are not only present in antibiotic-producing bacteria. Throughput sequencing technologies have revealed an unexpected reservoir of antibiotic resistance in the environment. These data suggest that co-evolution between antibiotic and antibiotic resistance genes has occurred since the beginning of time. This evolutionary race has probably been slow because of highly regulated processes and low antibiotic concentrations. Therefore to understand this global problem, a new variable must be introduced, that the antibiotic resistance is a natural event, inherent to life. However, the industrial production of natural and synthetic antibiotics has dramatically accelerated this race, selecting some of the many resistance genes present in nature and contributing to their diversification. One of the best models available to understand the biological impact of selection and diversification are β-lactamases. They constitute the most widespread mechanism of resistance, at least among pathogenic bacteria, with more than 1000 enzymes identified in the literature. In the last years, there has been growing concern about the description, spread, and diversification of β-lactamases with carbapenemase activity and AmpC-type in plasmids. Phylogenies of these enzymes help the understanding of the evolutionary forces driving their selection. Moreover, understanding the adaptive potential of β-lactamases contribute to exploration the evolutionary antagonists trajectories through the design of more efficient synthetic molecules. In this review, we attempt to analyze the antibiotic resistance problem from intrinsic and environmental resistomes to the adaptive potential of resistance genes and the driving forces involved in their diversification, in order to provide a global perspective of the resistance problem.