Evolutionary action of mutations reveals antimicrobial resistance genes in Escherichia coli.

Since antibiotic development lags, we search for potential drug targets through directed evolution experiments. A challenge is that many resistance genes hide in a noisy mutational background as mutator clones emerge in the adaptive population. Here, to overcome this noise, we quantify the impact of mutations through evolutionary action (EA). After sequencing ciprofloxacin or colistin resistance strains grown under different mutational regimes, we find that an elevated sum of the evolutionary action of mutations in a gene identifies known resistance drivers. This EA integration approach also suggests new antibiotic resistance genes which are then shown to provide a fitness advantage in competition experiments. Moreover, EA integration analysis of clinical and environmental isolates of antibiotic resistant of E. coli identifies gene drivers of resistance where a standard approach fails. Together these results inform the genetic basis of de novo colistin resistance and support the robust discovery of phenotype-driving genes via the evolutionary action of genetic perturbations in fitness landscapes.

Identification of evolutionarily stable functional and immunogenic sites across the SARS-CoV-2 proteome and greater coronavirus family.

MOTIVATION: Since the first recognized case of COVID-19, more than 100 million people have been infected worldwide. Global efforts in drug and vaccine development to fight the disease have yielded vaccines and drug candidates to cure COVID-19. However, the spread of SARS-CoV-2 variants threatens the continued efficacy of these treatments. In order to address this, we interrogate the evolutionary history of the entire SARS-CoV-2 proteome to identify evolutionarily conserved functional sites that can inform the search for treatments with broader coverage across the coronavirus family. RESULTS: Combining coronavirus family sequence information with the mutations observed in the current COVID-19 outbreak, we systematically and comprehensively define evolutionarily stable sites that may provide useful drug and vaccine targets and which are less likely to be compromised by the emergence of new virus strains. Several experimentally validated effective drugs interact with these proposed target sites. In addition, the same evolutionary information can prioritize cross reactive antigens that are useful in directing multi-epitope vaccine strategies to illicit broadly neutralizing immune responses to the betacoronavirus family. Although the results are focused on SARS-CoV-2, these approaches stem from evolutionary principles that are agnostic to the organism or infective agent. AVAILABILITY AND IMPLEMENTATION: The results of this work are made interactively available at http://cov.lichtargelab.org. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Identification of evolutionarily stable functional and immunogenic sites across the SARS-CoV-2 proteome and the greater coronavirus family.

Since the first recognized case of COVID-19, more than 100 million people have been infected worldwide. Global efforts in drug and vaccine development to fight the disease have yielded vaccines and drug candidates to cure COVID-19. However, the spread of SARS-CoV-2 variants threatens the continued efficacy of these treatments. In order to address this, we interrogate the evolutionary history of the entire SARS-CoV-2 proteome to identify evolutionarily conserved functional sites that can inform the search for treatments with broader coverage across the coronavirus family. Combining this information with the mutations observed in the current COVID-19 outbreak, we systematically and comprehensively define evolutionarily stable sites that may provide useful drug and vaccine targets and which are less likely to be compromised by the emergence of new virus strains. Several experimentally-validated effective drugs interact with these proposed target sites. In addition, the same evolutionary information can prioritize cross reactive antigens that are useful in directing multi-epitope vaccine strategies to illicit broadly neutralizing immune responses to the betacoronavirus family. Although the results are focused on SARS-CoV-2, these approaches stem from evolutionary principles that are agnostic to the organism or infective agent.

CRISPR-FRT targets shared sites in a knock-out collection for off-the-shelf genome editing.

CRISPR advances genome engineering by directing endonuclease sequence specificity with a guide RNA molecule (gRNA). For precisely targeting a gene for modification, each genetic construct requires a unique gRNA. By generating a gRNA against the flippase recognition target (FRT) site, a common genetic element shared by multiple genetic collections, CRISPR-FRT circumvents this design constraint to provide a broad platform for fast, scarless, off-the-shelf genome engineering.

Cooperativity of Negative Autoregulation Confers Increased Mutational Robustness.

Negative autoregulation is universally found across organisms. In the bacterium Escherichia coli, transcription factors often repress their own expression to form a negative feedback network motif that enables robustness to changes in biochemical parameters. Here we present a simple phenomenological model of a negative feedback transcription factor repressing both itself and another target gene. The strength of the negative feedback is characterized by three parameters: the cooperativity in self-repression, the maximal expression rate of the transcription factor, and the apparent dissociation constant of the transcription factor binding to its own promoter. Analysis of the model shows that the target gene levels are robust to mutations in the transcription factor, and that the robustness improves as the degree of cooperativity in self-repression increases. The prediction is tested in the LexA transcriptional network of E. coli by altering cooperativity in self-repression and promoter strength. Indeed, we find robustness is correlated with the former. Considering the proposed importance of gene regulation in speciation, parameters governing a transcription factor's robustness to mutation may have significant influence on a cell or organism's capacity to evolve.

Specific TP53 Mutants Overrepresented in Ovarian Cancer Impact CNV, TP53 Activity, Responses to Nutlin-3a, and Cell Survival.

Evolutionary Action analyses of The Cancer Gene Atlas data sets show that many specific p53 missense and gain-of-function mutations are selectively overrepresented and functional in high-grade serous ovarian cancer (HGSC). As homozygous alleles, p53 mutants are differentially associated with specific loss of heterozygosity (R273; chromosome 17); copy number variation (R175H; chromosome 9); and up-stream, cancer-related regulatory pathways. The expression of immune-related cytokines was selectively related to p53 status, showing for the first time that specific p53 mutants impact, and are related to, the immune subtype of ovarian cancer. Although the majority (31%) of HGSCs exhibit loss of heterozygosity, a significant number (24%) maintain a wild-type (WT) allele and represent another HGSC subtype that is not well defined. Using human and mouse cell lines, we show that specific p53 mutants differentially alter endogenous WT p53 activity; target gene expression; and responses to nutlin-3a, a small molecular that activates WT p53 leading to apoptosis, providing "proof of principle" that ovarian cancer cells expressing WT and mutant alleles represent a distinct ovarian cancer subtype. We also show that siRNA knock down of endogenous p53 in cells expressing homozygous mutant alleles causes apoptosis, whereas cells expressing WT p53 (or are heterozygous for WT and mutant p53 alleles) are highly resistant. Therefore, despite different gene regulatory pathways associated with specific p53 mutants, silencing mutant p53 might be a suitable, powerful, global strategy for blocking ovarian cancer growth in those tumors that rely on mutant p53 functions for survival. Knowing p53 mutational status in HGSC should permit new strategies tailored to control this disease.

Prediction and redesign of protein-protein interactions.

Understanding the molecular basis of protein function remains a central goal of biology, with the hope to elucidate the role of human genes in health and in disease, and to rationally design therapies through targeted molecular perturbations. We review here some of the computational techniques and resources available for characterizing a critical aspect of protein function - those mediated by protein-protein interactions (PPI). We describe several applications and recent successes of the Evolutionary Trace (ET) in identifying molecular events and shapes that underlie protein function and specificity in both eukaryotes and prokaryotes. ET is a part of analytical approaches based on the successes and failures of evolution that enable the rational control of PPI.

Negative feedback in genetic circuits confers evolutionary resilience and capacitance.

Natural selection for specific functions places limits upon the amino acid substitutions a protein can accept. Mechanisms that expand the range of tolerable amino acid substitutions include chaperones that can rescue destabilized proteins and additional stability-enhancing substitutions. Here, we present an alternative mechanism that is simple and uses a frequently encountered network motif. Computational and experimental evidence shows that the self-correcting, negative-feedback gene regulation motif increases repressor expression in response to deleterious mutations and thereby precisely restores repression of a target gene. Furthermore, this ability to rescue repressor function is observable across the Eubacteria kingdom through the greater accumulation of amino acid substitutions in negative-feedback transcription factors compared to genes they control. We propose that negative feedback represents a self-contained genetic canalization mechanism that preserves phenotype while permitting access to a wider range of functional genotypes.

Accounting for epistatic interactions improves the functional analysis of protein structures.

MOTIVATION: The constraints under which sequence, structure and function coevolve are not fully understood. Bringing this mutual relationship to light can reveal the molecular basis of binding, catalysis and allostery, thereby identifying function and rationally guiding protein redesign. Underlying these relationships are the epistatic interactions that occur when the consequences of a mutation to a protein are determined by the genetic background in which it occurs. Based on prior data, we hypothesize that epistatic forces operate most strongly between residues nearby in the structure, resulting in smooth evolutionary importance across the structure. METHODS AND RESULTS: We find that when residue scores of evolutionary importance are distributed smoothly between nearby residues, functional site prediction accuracy improves. Accordingly, we designed a novel measure of evolutionary importance that focuses on the interaction between pairs of structurally neighboring residues. This measure that we term pair-interaction Evolutionary Trace yields greater functional site overlap and better structure-based proteome-wide functional predictions. CONCLUSIONS: Our data show that the structural smoothness of evolutionary importance is a fundamental feature of the coevolution of sequence, structure and function. Mutations operate on individual residues, but selective pressure depends in part on the extent to which a mutation perturbs interactions with neighboring residues. In practice, this principle led us to redefine the importance of a residue in terms of the importance of its epistatic interactions with neighbors, yielding better annotation of functional residues, motivating experimental validation of a novel functional site in LexA and refining protein function prediction. CONTACT: lichtarge@bcm.edu. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Separation of recombination and SOS response in Escherichia coli RecA suggests LexA interaction sites.

RecA plays a key role in homologous recombination, the induction of the DNA damage response through LexA cleavage and the activity of error-prone polymerase in Escherichia coli. RecA interacts with multiple partners to achieve this pleiotropic role, but the structural location and sequence determinants involved in these multiple interactions remain mostly unknown. Here, in a first application to prokaryotes, Evolutionary Trace (ET) analysis identifies clusters of evolutionarily important surface amino acids involved in RecA functions. Some of these clusters match the known ATP binding, DNA binding, and RecA-RecA homo-dimerization sites, but others are novel. Mutation analysis at these sites disrupted either recombination or LexA cleavage. This highlights distinct functional sites specific for recombination and DNA damage response induction. Finally, our analysis reveals a composite site for LexA binding and cleavage, which is formed only on the active RecA filament. These new sites can provide new drug targets to modulate one or more RecA functions, with the potential to address the problem of evolution of antibiotic resistance at its root.

Analysis of the plasticity of location of the Arg244 positive charge within the active site of the TEM-1 beta-lactamase.

A large number of beta-lactamases have emerged that are capable of conferring bacterial resistance to beta-lactam antibiotics. Comparison of the structural and functional features of this family has refined understanding of the catalytic properties of these enzymes. An arginine residue present at position 244 in TEM-1 beta-lactamase interacts with the carboxyl group common to penicillin and cephalosporin antibiotics and thereby stabilizes both the substrate and transition state complexes. A comparison of class A beta-lactamase sequences reveals that arginine at position 244 is not conserved, although a positive charge at this structural location is conserved and is provided by an arginine at positions 220 or 276 for those enzymes lacking arginine at position 244. The plasticity of the location of positive charge in the beta-lactamase active site was experimentally investigated by relocating the arginine at position 244 in TEM-1 beta-lactamase to positions 220, 272, and 276 by site-directed mutagenesis. Kinetic analysis of the engineered beta-lactamases revealed that removal of arginine 244 by alanine mutation reduced catalytic efficiency against all substrates tested and restoration of an arginine at positions 272 or 276 partially suppresses the catalytic defect of the Arg244Ala substitution. These results suggest an evolutionary mechanism for the observed divergence of the position of positive charge in the active site of class A beta-lactamases.

Genetic and structural characterization of an L201P global suppressor substitution in TEM-1 beta-lactamase.

TEM-1 beta-lactamase confers bacterial resistance to penicillin antibiotics and has acquired mutations that permit the enzyme to hydrolyze extended-spectrum cephalosporins or to avoid inactivation by beta-lactamase inhibitors. However, many of these substitutions have been shown to reduce activity against penicillin antibiotics and/or result in loss of stability for the enzyme. In order to gain more information concerning the tradeoffs associated with active site substitutions, a genetic selection was used to find second site mutations that partially restore ampicillin resistance levels conferred by an R244A active site TEM-1 beta-lactamase mutant. An L201P substitution distant from the active site that enhanced ampicillin resistance levels and increased protein expression levels of the R244A TEM-1 mutant was identified. The L201P substitution also increases the ampicillin resistance levels and restores expression levels of a poorly expressed TEM-1 mutant with a core-disrupting substitution. In vitro thermal denaturation of purified protein indicated that the L201P mutation increases the T(m) value of the TEM-1 enzyme. The X-ray structure of the L201P TEM-1 mutant was determined to gain insight into the increase in enzyme stability. The proline substitution occurs at the N-terminus of an alpha-helix and may stabilize the enzyme by reducing the helix dipole, as well as by lowering the conformational entropy cost of folding due to the reduced number of conformations available in the unfolded state. Collectively, the data suggest that L201P promotes tolerance of some deleterious TEM-1 mutations by enhancing the protein stability of these mutants.

A fitness cost associated with the antibiotic resistance enzyme SME-1 beta-lactamase.

The bla(TEM-1) beta-lactamase gene has become widespread due to the selective pressure of beta-lactam use and its stable maintenance on transferable DNA elements. In contrast, bla(SME-1) is rarely isolated and is confined to the chromosome of carbapenem-resistant Serratia marcescens strains. Dissemination of bla(SME-1) via transfer to a mobile DNA element could hinder the use of carbapenems. In this study, bla(SME-1) was determined to impart a fitness cost upon Escherichia coli in multiple genetic contexts and assays. Genetic screens and designed SME-1 mutants were utilized to identify the source of this fitness cost. These experiments established that the SME-1 protein was required for the fitness cost but also that the enzyme activity of SME-1 was not associated with the fitness cost. The genetic screens suggested that the SME-1 signal sequence was involved in the fitness cost. Consistent with these findings, exchange of the SME-1 signal sequence for the TEM-1 signal sequence alleviated the fitness cost while replacing the TEM-1 signal sequence with the SME-1 signal sequence imparted a fitness cost to TEM-1 beta-lactamase. Taken together, these results suggest that fitness costs associated with some beta-lactamases may limit their dissemination.

Characterization of the major antigenic protein 2 of Ehrlichia canis and Ehrlichia chaffeensis and its application for serodiagnosis of ehrlichiosis.

Canine monocytic ehrlichiosis, caused by Ehrlichia canis or Ehrlichia chaffeensis, can result in clinical disease in naturally infected animals. Coinfections with these agents may be common in certain areas of endemicity. Currently, a species-specific method for serological diagnosis of monocytic ehrlichiosis is not available. Previously, we developed two indirect enzyme-linked immunosorbent assays (ELISAs) using the major antigenic protein 2 (MAP2) of E. chaffeensis and E. canis. In this study, we further characterized the conservation of MAP2 among various geographic isolates of each organism and determined if the recombinant MAP2 (rMAP2) of E. chaffeensis would cross-react with E. canis-infected dog sera. Genomic Southern blot analysis using digoxigenin-labeled species-specific probes suggested that map2 is a single-copy gene in both Ehrlichia species. Sequences of the single map2 genes of seven geographically different isolates of E. chaffeensis and five isolates of E. canis are highly conserved among the various isolates of each respective ehrlichial species. ELISA and Western blot analysis confirmed that the E. chaffeensis rMAP2 failed to serologically differentiate between E. canis and E. chaffeensis infections.