The field of antibiotic drug discovery and the monitoring of new antibiotic resistance elements have yet to fully exploit the power of the genome revolution. Despite the fact that the first genomes sequenced of free living organisms were those of bacteria, there have been few specialized bioinformatic tools developed to mine the growing amount of genomic data associated with pathogens. In particular, there are few tools to study the genetics and genomics of antibiotic resistance and how it impacts bacterial populations, ecology, and the clinic. We have initiated development of such tools in the form of the Comprehensive Antibiotic Research Database (CARD; http://arpcard.mcmaster.ca). The CARD integrates disparate molecular and sequence data, provides a unique organizing principle in the form of the Antibiotic Resistance Ontology (ARO), and can quickly identify putative antibiotic resistance genes in new unannotated genome sequences. This unique platform provides an informatic tool that bridges antibiotic resistance concerns in health care, agriculture, and the environment.A ntibiotic resistance is an increasing crisis as both the range of microbial antibiotic resistance in clinical settings expands and the pipeline for development of new antibiotics contracts (1). This problem is compounded by the global genomic scope of the antibiotic resistome, such that antibiotic resistance spans a continuum from genes in pathogens found in the clinic to those of benign environmental microbes along with their proto-resistance gene progenitors (2, 3). The recent emergence of New Delhi metallo-ß-lactamase (NDM-1) in Gram-negative organisms (4), which can hydrolyze all ␤-lactams with the exception of monobactams, illustrates the capacity of new antibiotic resistance genes to emerge rapidly from as-yet-undetermined reservoirs. Surveys of genes originating from both clinical and environmental sources (microbes and metagenomes) will provide increasing insight into these reservoirs and offer predictive capacity for the emergence and epidemiology of antibiotic resistance.The increasing opportunity to prepare a broader and comprehensive antibiotic resistance gene census is facilitated by the power and falling costs of next-generation DNA sequencing. For example, whole-genome sequencing (WGS) is being increasingly used to examine new antibiotic-resistant isolates discovered in clinical settings (5). Additionally, culture-independent metagenomic surveys are adding tremendously to the pool of known genes and their distribution outside clinical settings (6, 7). These approaches have the advantage of providing a rapid survey of the antibiotic resistome of new strains, the discovery of newly emergent antibiotic resistance genes, the epidemiology of antibiotic resistance genes, and the horizontal gene transfer (HGT) of known antibiotic resistance genes through plasmids and transposable elements. However, despite the existence of tools for general annotation of prokaryotic genomes (see, e.g., reference 8), prediction of an antibiotic resista...

The discovery of antibiotics more than 70 years ago initiated a period of drug innovation and implementation in human and animal health and agriculture. These discoveries were tempered in all cases by the emergence of resistant microbes. This history has been interpreted to mean that antibiotic resistance in pathogenic bacteria is a modern phenomenon; this view is reinforced by the fact that collections of microbes that predate the antibiotic era are highly susceptible to antibiotics. Here we report targeted metagenomic analyses of rigorously authenticated ancient DNA from 30,000-year-old Beringian permafrost sediments and the identification of a highly diverse collection of genes encoding resistance to β-lactam, tetracycline and glycopeptide antibiotics. Structure and function studies on the complete vancomycin resistance element VanA confirmed its similarity to modern variants. These results show conclusively that antibiotic resistance is a natural phenomenon that predates the modern selective pressure of clinical antibiotic use.

Purine biosynthesis requires ten enzymatic transformations to generate inosine monophosphate. PurF, PurD, PurL, PurM, PurC, and PurB are common to all pathways, while PurN or PurT, PurK/PurE-I or PurE-II, PurH or PurP, and PurJ or PurO catalyze the same steps in different organisms. X-ray crystal structures are available for all 15 purine biosynthetic enzymes, including seven ATP-dependent enzymes, two amidotransferases and two tetrahydrofolate-dependent enzymes. Here we summarize the structures of the purine biosynthetic enzymes, discuss similarities and differences, and present arguments for pathway evolution. Four of the ATP-dependent enzymes belong to the ATP-grasp superfamily and two to the PurM superfamily. The amidotransferases are unrelated with one utilizing an NTN-glutaminase and the other utilizing a triad glutaminase. Likewise the tetrahydrofolate-dependent enzymes are unrelated. Ancestral proteins may have included a broad specificity enzyme instead of PurD, PurT, PurK, PurC, and PurP, and a separate enzyme instead of PurM and PurL.

Pathogens deliver complex arsenals of translocated effector proteins to host cells during infection, but the extent to which these proteins are regulated once inside the eukaryotic cell remains poorly defined. Among all bacterial pathogens, Legionella pneumophila maintains the largest known set of translocated substrates, delivering over 300 proteins to the host cell via its Type IVB, Icm/Dot translocation system. Backed by a few notable examples of effector-effector regulation in L. pneumophila, we sought to define the extent of this phenomenon through a systematic analysis of effector-effector functional interaction. We used Saccharomyces cerevisiae, an established proxy for the eukaryotic host, to query > 108,000 pairwise genetic interactions between two compatible expression libraries of~330 L. pneumophila-translocated substrates. While capturing all known examples of effectoreffector suppression, we identify fourteen novel translocated substrates that suppress the activity of other bacterial effectors and one pair with synergistic activities. In at least nine instances, this regulation is direct-a hallmark of an emerging class of proteins called metaeffectors, or "effectors of effectors". Through detailed structural and functional analysis, we show that metaeffector activity derives from a diverse range of mechanisms, shapes evolution, and can be used to reveal important aspects of each cognate effector's function. Metaeffectors, along with other, indirect, forms of effector-effector modulation, may be a common feature of many intracellular pathogens-with unrealized potential to inform our understanding of how pathogens regulate their interactions with the host cell.

The need for new antibiotic therapies is acute and growing in large part because of the emergence of drug-resistant pathogens. A vast number of resistance determinants are, however, found in nonpathogenic micro-organisms. The resistance totality in the global microbiota is the antibiotic resistome and includes not only established resistance genes but also genes that have the potential to evolve into resistance elements. We term these proto-resistance genes and hypothesize that they share common ancestry with other functional units known as housekeeping genes. Genomic enzymology is the study of protein structure-function in light of genetic context and evolution of protein superfamilies. This concept is highly applicable to study of antibiotic resistance evolution from proto-resistance elements. In this review, we summarize some of the genomic enzymology evidence for resistance enzymes pointing to common ancestry with genes of other metabolic functions. Genomic enzymology plays a key role in understanding the origins of antibiotic resistance and aids in designing strategies for diagnosis and prevention thereof.