Targeting the Bet-Hedging Strategy with an Inhibitor of Bacterial Efflux Capacity Enhances Antibiotic Efficiency and Ameliorates Bacterial Persistence In Vitro.

Persistence is a bet-hedging strategy in bacterial populations that increases antibiotic tolerance and leads to the establishment of latent infections. In this study, we demonstrated that a synthetic non-toxic taxane-based reversal agent (tRA), developed as an inhibitor of ABC transporter systems in mammalian cancer cells, enhanced antibiotic killing of persister populations from different pathogens, including Burkholderia, Pseudomonas, Francisella, and Yersinia. Acting as an inhibitor of bacterial efflux at 100 nM, tRA99020 enhanced antibiotic efficiency and suppressed the production of natural products of Burkholderia species polyketide synthase (PKS) function. We demonstrate that the metabolites produced by PKS in response to stress by different antibiotics act as inhibitors of mammalian histone deacetylase activity and stimulate cell death. Applying a single-molecule fluorescence in situ hybridization (smFISH) assay, we analyzed on a single-cell level the activation profiles of the persistence regulating pks gene in Burkholderia thailandensis treated with tRA99020 and antibiotics. We posit that a multi-pronged approach encompassing antibiotic therapies and inhibition of efflux systems and fatty acid catabolism will be required for efficient eradication of persistent bacterial populations.

Defending Our Public Biological Databases as a Global Critical Infrastructure.

Progress in modern biology is being driven, in part, by the large amounts of freely available data in public resources such as the International Nucleotide Sequence Database Collaboration (INSDC), the world's primary database of biological sequence (and related) information. INSDC and similar databases have dramatically increased the pace of fundamental biological discovery and enabled a host of innovative therapeutic, diagnostic, and forensic applications. However, as high-value, openly shared resources with a high degree of assumed trust, these repositories share compelling similarities to the early days of the Internet. Consequently, as public biological databases continue to increase in size and importance, we expect that they will face the same threats as undefended cyberspace. There is a unique opportunity, before a significant breach and loss of trust occurs, to ensure they evolve with quality and security as a design philosophy rather than costly "retrofitted" mitigations. This Perspective surveys some potential quality assurance and security weaknesses in existing open genomic and proteomic repositories, describes methods to mitigate the likelihood of both intentional and unintentional errors, and offers recommendations for risk mitigation based on lessons learned from cybersecurity.

Development of forensic assay signatures for ebolaviruses.

Ebolaviruses are a diverse group of RNA viruses comprising five different species, four of which cause fatal hemorrhagic fever in humans. Because of their high infectivity and lethality, ebolaviruses are considered major biothreat agents. Although detection assays exist, no forensic assays are currently available. Here, we report the development of forensic assays that differentiate ebolaviruses. We performed phylogenetic analyses and identified canonical SNPs for all species, major clades and isolates. TaqMan-MGB allelic discrimination assays based on these SNPs were designed, screened against synthetic RNA templates, and validated against ebolavirus genomic RNAs. A total of 45 assays were validated to provide 100% coverage of the species and variants with additional resolution at the isolate level. These assays enabled accurate forensic analysis on 4 "unknown" ebolaviruses. Unknowns were correctly classified to species and variant. A goal of providing resolution below the isolate level was not successful. These high-resolution forensic assays allow rapid and accurate genotyping of ebolaviruses for forensic investigations.

Forensic signatures for Marburgviruses.

Marburgvirus is one of the most important hemorrhagic fever viruses with extremely high infectivity and fatality rate (~90%). It is transmitted easily in human populations through a respiratory route and therefore considered as a major biothreat agent. Although detection assays have been developed, no assay is available for forensic analysis. Here we report development of forensic assays for Marburgvirus. We performed detailed phylogenetic analysis of strains and isolates from all known Marburg virus outbreaks as well as from several laboratory strains and identified canonical SNPs for all major clades (outbreaks) and strains. TaqMan-MGB allelic discrimination assays targeting these SNPs were designed and experimentally screened against synthetic RNA templates and genomic RNAs. A total of 45 assays were validated to provide 100% coverage of the clades (outbreaks) and 91% at the strain level (21 out of the 23 targeted Marburgvirus strains) with built-in redundancy for increased robustness. Using these validated assays, we were able to provide accurate forensic analysis on 3 "unknown" Marburgviruses. These high-resolution forensic assays allow rapid and accurate genotyping of Marburgviruses for forensic investigations.

Rapid phylogenetic and functional classification of short genomic fragments with signature peptides.

BACKGROUND: Classification is difficult for shotgun metagenomics data from environments such as soils, where the diversity of sequences is high and where reference sequences from close relatives may not exist. Approaches based on sequence-similarity scores must deal with the confounding effects that inheritance and functional pressures exert on the relation between scores and phylogenetic distance, while approaches based on sequence alignment and tree-building are typically limited to a small fraction of gene families. We describe an approach based on finding one or more exact matches between a read and a precomputed set of peptide 10-mers. RESULTS: At even the largest phylogenetic distances, thousands of 10-mer peptide exact matches can be found between pairs of bacterial genomes. Genes that share one or more peptide 10-mers typically have high reciprocal BLAST scores. Among a set of 403 representative bacterial genomes, some 20 million 10-mer peptides were found to be shared. We assign each of these peptides as a signature of a particular node in a phylogenetic reference tree based on the RNA polymerase genes. We classify the phylogeny of a genomic fragment (e.g., read) at the most specific node on the reference tree that is consistent with the phylogeny of observed signature peptides it contains. Using both synthetic data from four newly-sequenced soil-bacterium genomes and ten real soil metagenomics data sets, we demonstrate a sensitivity and specificity comparable to that of the MEGAN metagenomics analysis package using BLASTX against the NR database. Phylogenetic and functional similarity metrics applied to real metagenomics data indicates a signal-to-noise ratio of approximately 400 for distinguishing among environments. Our method assigns ~6.6 Gbp/hr on a single CPU, compared with 25 kbp/hr for methods based on BLASTX against the NR database. CONCLUSIONS: Classification by exact matching against a precomputed list of signature peptides provides comparable results to existing techniques for reads longer than about 300 bp and does not degrade severely with shorter reads. Orders of magnitude faster than existing methods, the approach is suitable now for inclusion in analysis pipelines and appears to be extensible in several different directions.

A robust PCR primer design platform applied to the detection of Acidobacteria Group 1 in soil.

Environmental biosurveillance and microbial ecology studies use PCR-based assays to detect and quantify microbial taxa and gene sequences within a complex background of microorganisms. However, the fragmentary nature and growing quantity of DNA-sequence data make group-specific assay design challenging. We solved this problem by developing a software platform that enables PCR-assay design at an unprecedented scale. As a demonstration, we developed quantitative PCR assays for a globally widespread, ecologically important bacterial group in soil, Acidobacteria Group 1. A total of 33,684 Acidobacteria 16S rRNA gene sequences were used for assay design. Following 1 week of computation on a 376-core cluster, 83 assays were obtained. We validated the specificity of the top three assays, collectively predicted to detect 42% of the Acidobacteria Group 1 sequences, by PCR amplification and sequencing of DNA from soil. Based on previous analyses of 16S rRNA gene sequencing, Acidobacteria Group 1 species were expected to decrease in response to elevated atmospheric CO(2). Quantitative PCR results, using the Acidobacteria Group 1-specific PCR assays, confirmed the expected decrease and provided higher statistical confidence than the 16S rRNA gene-sequencing data. These results demonstrate a powerful capacity to address previously intractable assay design challenges.

Simultaneous pathogen detection and antibiotic resistance characterization using SNP-based multiplexed oligonucleotide ligation-PCR (MOL-PCR).

Extensive use of antibiotics in both public health and animal husbandry has resulted in rapid emergence of antibiotic resistance in almost all human pathogens, including biothreat pathogens. Antibiotic resistance has thus become a major concern for both public health and national security. We developed multiplexed assays for rapid, simultaneous pathogen detection and characterization of ciprofloxacin and doxycycline resistance in Bacillus anthracis, Yersinia pestis, and Francisella tularensis. These assays are SNP-based and use Multiplexed Oligonucleotide Ligation-PCR (MOL-PCR). The MOL-PCR assay chemistry and MOLigo probe design process are presented. A web-based tool - MOLigoDesigner (http://MOLigoDesigner.lanl.gov) was developed to facilitate the probe design. All probes were experimentally validated individually and in multiplexed assays, and minimal sets of multiplexed MOLigo probes were identified for simultaneous pathogen detection and antibiotic resistance characterization.

Steps toward broad-spectrum therapeutics: discovering virulence-associated genes present in diverse human pathogens.

BACKGROUND: New and improved antimicrobial countermeasures are urgently needed to counteract increased resistance to existing antimicrobial treatments and to combat currently untreatable or new emerging infectious diseases. We demonstrate that computational comparative genomics, together with experimental screening, can identify potential generic (i.e., conserved across multiple pathogen species) and novel virulence-associated genes that may serve as targets for broad-spectrum countermeasures. RESULTS: Using phylogenetic profiles of protein clusters from completed microbial genome sequences, we identified seventeen protein candidates that are common to diverse human pathogens and absent or uncommon in non-pathogens. Mutants of 13 of these candidates were successfully generated in Yersinia pseudotuberculosis and the potential role of the proteins in virulence was assayed in an animal model. Six candidate proteins are suggested to be involved in the virulence of Y. pseudotuberculosis, none of which have previously been implicated in the virulence of Y. pseudotuberculosis and three have no record of involvement in the virulence of any bacteria. CONCLUSION: This work demonstrates a strategy for the identification of potential virulence factors that are conserved across a number of human pathogenic bacterial species, confirming the usefulness of this tool.

Improved assay-dependent searching of nucleic acid sequence databases.

Nucleic acid-based biochemical assays are crucial to modern biology. Key applications, such as detection of bacterial, viral and fungal pathogens, require detailed knowledge of assay sensitivity and specificity to obtain reliable results. Improved methods to predict assay performance are needed for exploiting the exponentially growing amount of DNA sequence data and for reducing the experimental effort required to develop robust detection assays. Toward this goal, we present an algorithm for the calculation of sequence similarity based on DNA thermodynamics. In our approach, search queries consist of one to three oligonucleotide sequences representing either a hybridization probe, a pair of Padlock probes or a pair of PCR primers with an optional TaqMantrade mark probe (i.e. in silico or 'virtual' PCR). Matches are reported if the query and target satisfy both the thermodynamics of the assay (binding at a specified hybridization temperature and/or change in free energy) and the relevant biological constraints (assay sequences binding to the correct target duplex strands in the required orientations). The sensitivity and specificity of our method is evaluated by comparing predicted to known sequence tagged sites in the human genome. Free energy is shown to be a more sensitive and specific match criterion than hybridization temperature.

Genomorama: genome visualization and analysis.

BACKGROUND: The ability to visualize genomic features and design experimental assays that can target specific regions of a genome is essential for modern biology. To assist in these tasks, we present Genomorama, a software program for interactively displaying multiple genomes and identifying potential DNA hybridization sites for assay design. RESULTS: Useful features of Genomorama include genome search by DNA hybridization (probe binding and PCR amplification), efficient multi-scale display and manipulation of multiple genomes, support for many genome file types and the ability to search for and retrieve data from the National Center for Biotechnology Information (NCBI) Entrez server. CONCLUSION: Genomorama provides an efficient computational platform for visualizing and analyzing multiple genomes.

Computational improvements reveal great bacterial diversity and high metal toxicity in soil.

The complexity of soil bacterial communities has thus far confounded effective measurement. However, with improved analytical methods, we show that the abundance distribution and total diversity can be deciphered. Reanalysis of reassociation kinetics for bacterial community DNA from pristine and metal-polluted soils showed that a power law best described the abundance distributions. More than one million distinct genomes occurred in the pristine soil, exceeding previous estimates by two orders of magnitude. Metal pollution reduced diversity more than 99.9%, revealing the highly toxic effect of metal contamination, especially for rare taxa.

The TyrA family of aromatic-pathway dehydrogenases in phylogenetic context.

BACKGROUND: The TyrA protein family includes members that catalyze two dehydrogenase reactions in distinct pathways leading to L-tyrosine and a third reaction that is not part of tyrosine biosynthesis. Family members share a catalytic core region of about 30 kDa, where inhibitors operate competitively by acting as substrate mimics. This protein family typifies many that are challenging for bioinformatic analysis because of relatively modest sequence conservation and small size. RESULTS: Phylogenetic relationships of TyrA domains were evaluated in the context of combinatorial patterns of specificity for the two substrates, as well as the presence or absence of a variety of fusions. An interactive tool is provided for prediction of substrate specificity. Interactive alignments for a suite of catalytic-core TyrA domains of differing specificity are also provided to facilitate phylogenetic analysis. tyrA membership in apparent operons (or supraoperons) was examined, and patterns of conserved synteny in relationship to organismal positions on the 16S rRNA tree were ascertained for members of the domain Bacteria. A number of aromatic-pathway genes (hisHb, aroF, aroQ) have fused with tyrA, and it must be more than coincidental that the free-standing counterparts of all of the latter fused genes exhibit a distinct trace of syntenic association. CONCLUSION: We propose that the ancestral TyrA dehydrogenase had broad specificity for both the cyclohexadienyl and pyridine nucleotide substrates. Indeed, TyrA proteins of this type persist today, but it is also common to find instances of narrowed substrate specificities, as well as of acquisition via gene fusion of additional catalytic domains or regulatory domains. In some clades a qualitative change associated with either narrowed substrate specificity or gene fusion has produced an evolutionary "jump" in the vertical genealogy of TyrA homologs. The evolutionary history of gene organizations that include tyrA can be deduced in genome assemblages of sufficiently close relatives, the most fruitful opportunities currently being in the Proteobacteria. The evolution of TyrA proteins within the broader context of how their regulation evolved and to what extent TyrA co-evolved with other genes as common members of aromatic-pathway regulons is now feasible as an emerging topic of ongoing inquiry.

SNPsFinder--a web-based application for genome-wide discovery of single nucleotide polymorphisms in microbial genomes.

UNLABELLED: Single nucleotide polymorphisms (SNPs) are the most abundant form of genetic variations in closely related microbial species, strains or isolates. Some SNPs confer selective advantages for microbial pathogens during infection and many others are powerful genetic markers for distinguishing closely related strains or isolates that could not be distinguished otherwise. To facilitate SNP discovery in microbial genomes, we have developed a web-based application, SNPsFinder, for genome-wide identification of SNPs. SNPsFinder takes multiple genome sequences as input to identify SNPs within homologous regions. It can also take contig sequences and sequence quality scores from ongoing sequencing projects for SNP prediction. SNPsFinder will use genome sequence annotation if available and map the predicted SNP regions to known genes or regions to assist further evaluation of the predicted SNPs for their functional significance. SNPsFinder can generate PCR primers for all predicted SNP regions according to user's input parameters to facilitate experimental validation. The results from SNPsFinder analysis are accessible through the World Wide Web. AVAILABILITY: The SNPsFinder program is available at http://snpsfinder.lanl.gov/. SUPPLEMENTARY INFORMATION: The user's manual is available at http://snpsfinder.lanl.gov/UsersManual/

Statistics of single-molecule measurements: applications in flow-cytometry sizing of DNA fragments.

BACKGROUND: The measurement of physical properties from single molecules has been demonstrated. However, the majority of single-molecule studies report values based on relatively large data sets (e.g., N > 50). While there are studies that report physical quantities based on small sample sets, there has not been a detailed statistical analysis relating sample size to the reliability of derived parameters. METHODS: Monte Carlo simulations and multinomial analysis, dependent on quantifiable experimental parameters, were used to determine the minimum number of single-molecule measurements required to produce an accurate estimate of a population mean. Simulation results were applied to the fluorescence-based sizing of DNA fragments by ultrasensitive flow cytometry (FCM). RESULTS: Our simulations show, for an analytical technique with a 10% CV, that the average of as few as five single-molecule measurements would provide a mean value within one SD of the population mean. Additional simulations determined the number of measurements required to obtain the desired number of replicates for each subpopulation within a mixture. Application of these results to flow cytometry data for lambda/HindIII and S. aureus Mu50/SmaI DNA digests produced accurate DNA fingerprints from as few as 98 single-molecule measurements. CONCLUSIONS: A surprisingly small number of single-molecule measurements are required to obtain a mean measurement descriptive of a normally-distributed parent population.

Development of rationally designed nucleic acid signatures for microbial pathogens.

The detection and identification of microbial pathogens are critical challenges in clinical medicine and public health surveillance. Advances in genome analysis technology are providing an unprecedented amount of information about bacterial and viral organisms, and hold great potential for pathogen detection and identification. In this paper, a rational approach to the development and application of nucleic acid signatures is described based on phylogenetically informative sequence features, especially single nucleotide polymorphisms. The computational tools that are available to enable the development of the next generation of microbial molecular signatures for clinical diagnostics and infectious disease surveillance are reviewed and the impact on public health and national security will be discussed.