Transcriptomic responses to antibiotic exposure in Mycobacterium tuberculosis.

Transcriptional responses in bacteria following antibiotic exposure offer insights into antibiotic mechanism of action, bacterial responses, and characterization of antimicrobial resistance. We aimed to define the transcriptional antibiotic response (TAR) in Mycobacterium tuberculosis (Mtb) isolates for clinically relevant drugs by pooling and analyzing Mtb microarray and RNA-seq data sets. We generated 99 antibiotic transcription profiles across 17 antibiotics, with 76% of profiles generated using 3-24 hours of antibiotic exposure and 49% within one doubling of the WHO antibiotic critical concentration. TAR genes were time-dependent, and largely specific to the antibiotic mechanism of action. TAR signatures performed well at predicting antibiotic exposure, with the area under the receiver operating curve (AUC) ranging from 0.84-1.00 (TAR <6 hours of antibiotic exposure) and 0.76-1.00 (>6 hours of antibiotic exposure) for upregulated genes and 0.57-0.90 and 0.87-1.00, respectfully, for downregulated genes. This work desmonstrates that transcriptomics allows for the assessment of antibiotic activity in Mtb within 6 hours of exposure.

Analysis of Genome-Wide Mutational Dependence in Naturally Evolving Mycobacterium tuberculosis Populations.

Pathogenic microorganisms are in a perpetual struggle for survival in changing host environments, where host pressures necessitate changes in pathogen virulence, antibiotic resistance, or transmissibility. The genetic basis of phenotypic adaptation by pathogens is difficult to study in vivo. In this work, we develop a phylogenetic method to detect genetic dependencies that promote pathogen adaptation using 31,428 in vivo sampled Mycobacterium tuberculosis genomes, a globally prevalent bacterial pathogen with increasing levels of antibiotic resistance. We find that dependencies between mutations are enriched in antigenic and antibiotic resistance functions and discover 23 mutations that potentiate the development of antibiotic resistance. Between 11% and 92% of resistant strains harbor a dependent mutation acquired after a resistance-conferring variant. We demonstrate the pervasiveness of genetic dependency in adaptation of naturally evolving populations and the utility of the proposed computational approach.

A convolutional neural network highlights mutations relevant to antimicrobial resistance in Mycobacterium tuberculosis.

Long diagnostic wait times hinder international efforts to address antibiotic resistance in M. tuberculosis. Pathogen whole genome sequencing, coupled with statistical and machine learning models, offers a promising solution. However, generalizability and clinical adoption have been limited by a lack of interpretability, especially in deep learning methods. Here, we present two deep convolutional neural networks that predict antibiotic resistance phenotypes of M. tuberculosis isolates: a multi-drug CNN (MD-CNN), that predicts resistance to 13 antibiotics based on 18 genomic loci, with AUCs 82.6-99.5% and higher sensitivity than state-of-the-art methods; and a set of 13 single-drug CNNs (SD-CNN) with AUCs 80.1-97.1% and higher specificity than the previous state-of-the-art. Using saliency methods to evaluate the contribution of input sequence features to the SD-CNN predictions, we identify 18 sites in the genome not previously associated with resistance. The CNN models permit functional variant discovery, biologically meaningful interpretation, and clinical applicability.

Co-evolution of interacting proteins through non-contacting and non-specific mutations.

Proteins often accumulate neutral mutations that do not affect current functions but can profoundly influence future mutational possibilities and functions. Understanding such hidden potential has major implications for protein design and evolutionary forecasting but has been limited by a lack of systematic efforts to identify potentiating mutations. Here, through the comprehensive analysis of a bacterial toxin-antitoxin system, we identified all possible single substitutions in the toxin that enable it to tolerate otherwise interface-disrupting mutations in its antitoxin. Strikingly, the majority of enabling mutations in the toxin do not contact and promote tolerance non-specifically to many different antitoxin mutations, despite covariation in homologues occurring primarily between specific pairs of contacting residues across the interface. In addition, the enabling mutations we identified expand future mutational paths that both maintain old toxin-antitoxin interactions and form new ones. These non-specific mutations are missed by widely used covariation and machine learning methods. Identifying such enabling mutations will be critical for ensuring continued binding of therapeutically relevant proteins, such as antibodies, aimed at evolving targets.

Dormant spores sense amino acids through the B subunits of their germination receptors.

Bacteria from the orders Bacillales and Clostridiales differentiate into stress-resistant spores that can remain dormant for years, yet rapidly germinate upon nutrient sensing. How spores monitor nutrients is poorly understood but in most cases requires putative membrane receptors. The prototypical receptor from Bacillus subtilis consists of three proteins (GerAA, GerAB, GerAC) required for germination in response to L-alanine. GerAB belongs to the Amino Acid-Polyamine-Organocation superfamily of transporters. Using evolutionary co-variation analysis, we provide evidence that GerAB adopts a structure similar to an L-alanine transporter from this superfamily. We show that mutations in gerAB predicted to disrupt the ligand-binding pocket impair germination, while mutations predicted to function in L-alanine recognition enable spores to respond to L-leucine or L-serine. Finally, substitutions of bulkier residues at these positions cause constitutive germination. These data suggest that GerAB is the L-alanine sensor and that B subunits in this broadly conserved family function in nutrient detection.

Large-scale discovery of protein interactions at residue resolution using co-evolution calculated from genomic sequences.

Increasing numbers of protein interactions have been identified in high-throughput experiments, but only a small proportion have solved structures. Recently, sequence coevolution-based approaches have led to a breakthrough in predicting monomer protein structures and protein interaction interfaces. Here, we address the challenges of large-scale interaction prediction at residue resolution with a fast alignment concatenation method and a probabilistic score for the interaction of residues. Importantly, this method (EVcomplex2) is able to assess the likelihood of a protein interaction, as we show here applied to large-scale experimental datasets where the pairwise interactions are unknown. We predict 504 interactions de novo in the E. coli membrane proteome, including 243 that are newly discovered. While EVcomplex2 does not require available structures, coevolving residue pairs can be used to produce structural models of protein interactions, as done here for membrane complexes including the Flagellar Hook-Filament Junction and the Tol/Pal complex.

Structural coordination of polymerization and crosslinking by a SEDS-bPBP peptidoglycan synthase complex.

The shape, elongation, division and sporulation (SEDS) proteins are a highly conserved family of transmembrane glycosyltransferases that work in concert with class B penicillin-binding proteins (bPBPs) to build the bacterial peptidoglycan cell wall1-6. How these proteins coordinate polymerization of new glycan strands with their crosslinking to the existing peptidoglycan meshwork is unclear. Here, we report the crystal structure of the prototypical SEDS protein RodA from Thermus thermophilus in complex with its cognate bPBP at 3.3 Å resolution. The structure reveals a 1:1 stoichiometric complex with two extensive interaction interfaces between the proteins: one in the membrane plane and the other at the extracytoplasmic surface. When in complex with a bPBP, RodA shows an approximately 10 Å shift of transmembrane helix 7 that exposes a large membrane-accessible cavity. Negative-stain electron microscopy reveals that the complex can adopt a variety of different conformations. These data define the bPBP pedestal domain as the key allosteric activator of RodA both in vitro and in vivo, explaining how a SEDS-bPBP complex can coordinate its dual enzymatic activities of peptidoglycan polymerization and crosslinking to build the cell wall.

Interaction specificity of clustered protocadherins inferred from sequence covariation and structural analysis.

Clustered protocadherins, a large family of paralogous proteins that play important roles in neuronal development, provide an important case study of interaction specificity in a large eukaryotic protein family. A mammalian genome has more than 50 clustered protocadherin isoforms, which have remarkable homophilic specificity for interactions between cellular surfaces. A large antiparallel dimer interface formed by the first 4 extracellular cadherin (EC) domains controls this interaction. To understand how specificity is achieved between the numerous paralogs, we used a combination of structural and computational approaches. Molecular dynamics simulations revealed that individual EC interactions are weak and undergo binding and unbinding events, but together they form a stable complex through polyvalency. Strongly evolutionarily coupled residue pairs interacted more frequently in our simulations, suggesting that sequence coevolution can inform the frequency of interaction and biochemical nature of a residue interaction. With these simulations and sequence coevolution, we generated a statistical model of interaction energy for the clustered protocadherin family that measures the contributions of all amino acid pairs at the interface. Our interaction energy model assesses specificity for all possible pairs of isoforms, recapitulating known pairings and predicting the effects of experimental changes in isoform specificity that are consistent with literature results. Our results show that sequence coevolution can be used to understand specificity determinants in a protein family and prioritize interface amino acid substitutions to reprogram specific protein-protein interactions.

The EVcouplings Python framework for coevolutionary sequence analysis.

SUMMARY: Coevolutionary sequence analysis has become a commonly used technique for de novo prediction of the structure and function of proteins, RNA, and protein complexes. We present the EVcouplings framework, a fully integrated open-source application and Python package for coevolutionary analysis. The framework enables generation of sequence alignments, calculation and evaluation of evolutionary couplings (ECs), and de novo prediction of structure and mutation effects. The combination of an easy to use, flexible command line interface and an underlying modular Python package makes the full power of coevolutionary analyses available to entry-level and advanced users. AVAILABILITY AND IMPLEMENTATION: https://github.com/debbiemarkslab/evcouplings.

Structure of the peptidoglycan polymerase RodA resolved by evolutionary coupling analysis.

The shape, elongation, division and sporulation (SEDS) proteins are a large family of ubiquitous and essential transmembrane enzymes with critical roles in bacterial cell wall biology. The exact function of SEDS proteins was for a long time poorly understood, but recent work has revealed that the prototypical SEDS family member RodA is a peptidoglycan polymerase-a role previously attributed exclusively to members of the penicillin-binding protein family. This discovery has made RodA and other SEDS proteins promising targets for the development of next-generation antibiotics. However, little is known regarding the molecular basis of SEDS activity, and no structural data are available for RodA or any homologue thereof. Here we report the crystal structure of Thermus thermophilus RodA at a resolution of 2.9 Å, determined using evolutionary covariance-based fold prediction to enable molecular replacement. The structure reveals a ten-pass transmembrane fold with large extracellular loops, one of which is partially disordered. The protein contains a highly conserved cavity in the transmembrane domain, reminiscent of ligand-binding sites in transmembrane receptors. Mutagenesis experiments in Bacillus subtilis and Escherichia coli show that perturbation of this cavity abolishes RodA function both in vitro and in vivo, indicating that this cavity is catalytically essential. These results provide a framework for understanding bacterial cell wall synthesis and SEDS protein function.

Core Genes Evolve Rapidly in the Long-Term Evolution Experiment with Escherichia coli.

Bacteria can evolve rapidly under positive selection owing to their vast numbers, allowing their genes to diversify by adapting to different environments. We asked whether the same genes that evolve rapidly in the long-term evolution experiment (LTEE) with Escherichia coli have also diversified extensively in nature. To make this comparison, we identified ∼2000 core genes shared among 60 E. coli strains. During the LTEE, core genes accumulated significantly more nonsynonymous mutations than flexible (i.e., noncore) genes. Furthermore, core genes under positive selection in the LTEE are more conserved in nature than the average core gene. In some cases, adaptive mutations appear to modify protein functions, rather than merely knocking them out. The LTEE conditions are novel for E. coli, at least in relation to its evolutionary history in nature. The constancy and simplicity of the environment likely favor the complete loss of some unused functions and the fine-tuning of others.

Genomic Epidemiology of Gonococcal Resistance to Extended-Spectrum Cephalosporins, Macrolides, and Fluoroquinolones in the United States, 2000-2013.

BACKGROUND: Treatment of Neisseria gonorrhoeae infection is empirical and based on population-wide susceptibilities. Increasing antimicrobial resistance underscores the potential importance of rapid diagnostic tests, including sequence-based tests, to guide therapy. However, the usefulness of sequence-based diagnostic tests depends on the prevalence and dynamics of the resistance mechanisms. METHODS: We define the prevalence and dynamics of resistance markers to extended-spectrum cephalosporins, macrolides, and fluoroquinolones in 1102 resistant and susceptible clinical N. gonorrhoeae isolates collected from 2000 to 2013 via the Centers for Disease Control and Prevention's Gonococcal Isolate Surveillance Project. RESULTS: Reduced extended-spectrum cephalosporin susceptibility is predominantly clonal and associated with the mosaic penA XXXIV allele and derivatives (sensitivity 98% for cefixime and 91% for ceftriaxone), but alternative resistance mechanisms have sporadically emerged. Reduced azithromycin susceptibility has arisen through multiple mechanisms and shows limited clonal spread; the basis for resistance in 36% of isolates with reduced azithromycin susceptibility is unclear. Quinolone-resistant N. gonorrhoeae has arisen multiple times, with extensive clonal spread. CONCLUSIONS: Quinolone-resistant N. gonorrhoeae and reduced cefixime susceptibility appear amenable to development of sequence-based diagnostic tests, whereas the undefined mechanisms of resistance to ceftriaxone and azithromycin underscore the importance of phenotypic surveillance. The identification of multidrug-resistant isolates highlights the need for additional measures to respond to the threat of untreatable gonorrhea.

Impact of a homing intein on recombination frequency and organismal fitness.

Inteins are parasitic genetic elements that excise themselves at the protein level by self-splicing, allowing the formation of functional, nondisrupted proteins. Many inteins contain a homing endonuclease (HEN) domain and rely on its activity for horizontal propagation. However, successful invasion of an entire population will make this activity redundant, and the HEN domain is expected to degenerate quickly under these conditions. Several theories have been proposed for the continued existence of the both active HEN and noninvaded alleles within a population. However, to date, these models were not directly tested experimentally. Using the natural cell fusion ability of the halophilic archaeon Haloferax volcanii we were able to examine this question in vivo, by mating polB intein-positive [insertion site c in the gene encoding DNA polymerase B (polB-c)] and intein-negative cells and examining the dispersal efficiency of this intein in a natural, polyploid population. Through competition between otherwise isogenic intein-positive and intein-negative strains we determined a surprisingly high fitness cost of over 7% for the polB-c intein. Our laboratory culture experiments and samples taken from Israel's Mediterranean coastline show that the polB-c inteins do not efficiently take over an inteinless population through mating, even under ideal conditions. The presence of the HEN/intein promoted recombination when intein-positive and intein-negative cells were mated. Increased recombination due to HEN activity contributes not only to intein dissemination but also to variation at the population level because recombination tracts during repair extend substantially from the homing site.

Antiparallel protocadherin homodimers use distinct affinity- and specificity-mediating regions in cadherin repeats 1-4.

Protocadherins (Pcdhs) are cell adhesion and signaling proteins used by neurons to develop and maintain neuronal networks, relying on trans homophilic interactions between their extracellular cadherin (EC) repeat domains. We present the structure of the antiparallel EC1-4 homodimer of human PcdhγB3, a member of the γ subfamily of clustered Pcdhs. Structure and sequence comparisons of α, ß, and γ clustered Pcdh isoforms illustrate that subfamilies encode specificity in distinct ways through diversification of loop region structure and composition in EC2 and EC3, which contains isoform-specific conservation of primarily polar residues. In contrast, the EC1/EC4 interface comprises hydrophobic interactions that provide non-selective dimerization affinity. Using sequence coevolution analysis, we found evidence for a similar antiparallel EC1-4 interaction in non-clustered Pcdh families. We thus deduce that the EC1-4 antiparallel homodimer is a general interaction strategy that evolved before the divergence of these distinct protocadherin families.

Sequence co-evolution gives 3D contacts and structures of protein complexes.

Protein-protein interactions are fundamental to many biological processes. Experimental screens have identified tens of thousands of interactions, and structural biology has provided detailed functional insight for select 3D protein complexes. An alternative rich source of information about protein interactions is the evolutionary sequence record. Building on earlier work, we show that analysis of correlated evolutionary sequence changes across proteins identifies residues that are close in space with sufficient accuracy to determine the three-dimensional structure of the protein complexes. We evaluate prediction performance in blinded tests on 76 complexes of known 3D structure, predict protein-protein contacts in 32 complexes of unknown structure, and demonstrate how evolutionary couplings can be used to distinguish between interacting and non-interacting protein pairs in a large complex. With the current growth of sequences, we expect that the method can be generalized to genome-wide elucidation of protein-protein interaction networks and used for interaction predictions at residue resolution.

Reconstruction of ancestral 16S rRNA reveals mutation bias in the evolution of optimal growth temperature in the Thermotogae phylum.

Optimal growth temperature is a complex trait involving many cellular components, and its physiology is not yet fully understood. Evolution of continuous characters, such as optimal growth temperature, is often modeled as a one-dimensional random walk, but such a model may be an oversimplification given the complex processes underlying the evolution of continuous characters. Recent articles have used ancestral sequence reconstruction to infer the optimal growth temperature of ancient organisms from the guanine and cytosine content of the stem regions of ribosomal RNA, allowing inferences about the evolution of optimal growth temperature. Here, we investigate the optimal growth temperature of the bacterial phylum Thermotogae. Ancestral sequence reconstruction using a nonhomogeneous model was used to reconstruct the stem guanine and cytosine content of 16S rRNA sequences. We compare this sequence reconstruction method with other ancestral character reconstruction methods, and show that sequence reconstruction generates smaller confidence intervals and different ancestral values than other reconstruction methods. Unbiased random walk simulation indicates that the lower temperature members of the Thermotogales have been under directional selection; however, when a simulation is performed that takes possible mutations into account, it is the high temperature lineages that are, in fact, under directional selection. We find that the evolution of Thermotogales optimal growth temperatures is best fit by a biased random walk model. These findings suggest that it may be easier to evolve from a high optimal growth temperature to a lower one than vice versa.

Reconstructed ancestral Myo-inositol-3-phosphate synthases indicate that ancestors of the Thermococcales and Thermotoga species were more thermophilic than their descendants.

The bacterial genomes of Thermotoga species show evidence of significant interdomain horizontal gene transfer from the Archaea. Members of this genus acquired many genes from the Thermococcales, which grow at higher temperatures than Thermotoga species. In order to study the functional history of an interdomain horizontally acquired gene we used ancestral sequence reconstruction to examine the thermal characteristics of reconstructed ancestral proteins of the Thermotoga lineage and its archaeal donors. Several ancestral sequence reconstruction methods were used to determine the possible sequences of the ancestral Thermotoga and Archaea myo-inositol-3-phosphate synthase (MIPS). These sequences were predicted to be more thermostable than the extant proteins using an established sequence composition method. We verified these computational predictions by measuring the activities and thermostabilities of purified proteins from the Thermotoga and the Thermococcales species, and eight ancestral reconstructed proteins. We found that the ancestral proteins from both the archaeal donor and the Thermotoga most recent common ancestor recipient were more thermostable than their descendants. We show that there is a correlation between the thermostability of MIPS protein and the optimal growth temperature (OGT) of its host, which suggests that the OGT of the ancestors of these species of Archaea and the Thermotoga grew at higher OGTs than their descendants.

Genome sequence of the mesophilic Thermotogales bacterium Mesotoga prima MesG1.Ag.4.2 reveals the largest Thermotogales genome to date.

Here we describe the genome of Mesotoga prima MesG1.Ag4.2, the first genome of a mesophilic Thermotogales bacterium. Mesotoga prima was isolated from a polychlorinated biphenyl (PCB)-dechlorinating enrichment culture from Baltimore Harbor sediments. Its 2.97 Mb genome is considerably larger than any previously sequenced Thermotogales genomes, which range between 1.86 and 2.30 Mb. This larger size is due to both higher numbers of protein-coding genes and larger intergenic regions. In particular, the M. prima genome contains more genes for proteins involved in regulatory functions, for instance those involved in regulation of transcription. Together with its closest relative, Kosmotoga olearia, it also encodes different types of proteins involved in environmental and cell-cell interactions as compared with other Thermotogales bacteria. Amino acid composition analysis of M. prima proteins implies that this lineage has inhabited low-temperature environments for a long time. A large fraction of the M. prima genome has been acquired by lateral gene transfer (LGT): a DarkHorse analysis suggests that 766 (32%) of predicted protein-coding genes have been involved in LGT after Mesotoga diverged from the other Thermotogales lineages. A notable example of a lineage-specific LGT event is a reductive dehalogenase gene-a key enzyme in dehalorespiration, indicating M. prima may have a more active role in PCB dechlorination than was previously assumed.

A rooted net of life.

Phylogenetic reconstruction using DNA and protein sequences has allowed the reconstruction of evolutionary histories encompassing all life. We present and discuss a means to incorporate much of this rich narrative into a single model that acknowledges the discrete evolutionary units that constitute the organism. Briefly, this Rooted Net of Life genome phylogeny is constructed around an initial, well resolved and rooted tree scaffold inferred from a supermatrix of combined ribosomal genes. Extant sampled ribosomes form the leaves of the tree scaffold. These leaves, but not necessarily the deeper parts of the scaffold, can be considered to represent a genome or pan-genome, and to be associated with members of other gene families within that sequenced (pan)genome. Unrooted phylogenies of gene families containing four or more members are reconstructed and superimposed over the scaffold. Initially, reticulations are formed where incongruities between topologies exist. Given sufficient evidence, edges may then be differentiated as those representing vertical lines of inheritance within lineages and those representing horizontal genetic transfers or endosymbioses between lineages.

Reassessment of the lineage fusion hypothesis for the origin of double membrane bacteria.

In 2009, James Lake introduced a new hypothesis in which reticulate phylogeny reconstruction is used to elucidate the origin of gram-negative bacteria (Nature 460: 967-971). The presented data supported the gram-negative bacteria originating from an ancient endosymbiosis between the Actinobacteria and Clostridia. His conclusion was based on a presence-absence analysis of protein families that divided all prokaryotes into five groups: Actinobacteria, Double Membrane bacteria (DM), Clostridia, Archaea and Bacilli. Of these five groups, the DM are by far the largest and most diverse group compared to the other groupings. While the fusion hypothesis for the origin of double membrane bacteria is enticing, we show that the signal supporting an ancient symbiosis is lost when the DM group is broken down into smaller subgroups. We conclude that the signal detected in James Lake's analysis in part results from a systematic artifact due to group size and diversity combined with low levels of horizontal gene transfer.