Search

Pregnancy complications are poorly represented in the archeological record, despite their importance in contemporary and ancient societies. While excavating a Byzantine cemetery in Troy, we discovered calcified abscesses among a woman's remains. Scanning electron microscopy of the tissue revealed 'ghost cells', resulting from dystrophic calcification, which preserved ancient maternal, fetal and bacterial DNA of a severe infection, likely chorioamnionitis. Gardnerella vaginalis and Staphylococcus saprophyticus dominated the abscesses. Phylogenomic analyses of ancient, historical, and contemporary data showed that G. vaginalis Troy fell within contemporary genetic diversity, whereas S. saprophyticus Troy belongs to a lineage that does not appear to be commonly associated with human disease today. We speculate that the ecology of S. saprophyticus infection may have differed in the ancient world as a result of close contacts between humans and domesticated animals. These results highlight the complex and dynamic interactions with our microbial milieu that underlie severe maternal infections., Competing Interests: The authors declare that no competing interests exist.

Francisella tularensis is classified as a Class A bioterrorism agent by the U.S. government due to its high virulence and the ease with which it can be spread as an aerosol. It is a facultative intracellular pathogen and the causative agent of tularemia. Ciprofloxacin (Cipro) is a broad spectrum antibiotic effective against Gram-positive and Gram-negative bacteria. Increased Cipro resistance in pathogenic microbes is of serious concern when considering options for medical treatment of bacterial infections. Identification of genes and loci that are associated with Ciprofloxacin resistance will help advance the understanding of resistance mechanisms and may, in the future, provide better treatment options for patients. It may also provide information for development of assays that can rapidly identify Cipro-resistant isolates of this pathogen. In this study, we selected a large number of F. tularensis live vaccine strain (LVS) isolates that survived in progressively higher Ciprofloxacin concentrations, screened the isolates using a whole genome F. tularensis LVS tiling microarray and Illumina sequencing, and identified both known and novel mutations associated with resistance. Genes containing mutations encode DNA gyrase subunit A, a hypothetical protein, an asparagine synthase, a sugar transamine/perosamine synthetase and others. Structural modeling performed on these proteins provides insights into the potential function of these proteins and how they might contribute to Cipro resistance mechanisms., Competing Interests: Eureka Genomics provided fee-for-service work for Lawrence Livermore National Lab on DNA sequencing and data analysis. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

Venezuelan equine encephalitis virus (VEEV) is a mosquito-borne alphavirus that has caused large outbreaks of severe illness in both horses and humans. New approaches are needed to rapidly infer the origin of a newly discovered VEEV strain, estimate its equine amplification and resultant epidemic potential, and predict human virulence phenotype. We performed whole genome single nucleotide polymorphism (SNP) analysis of all available VEE antigenic complex genomes, verified that a SNP-based phylogeny accurately captured the features of a phylogenetic tree based on multiple sequence alignment, and developed a high resolution genome-wide SNP microarray. We used the microarray to analyze a broad panel of VEEV isolates, found excellent concordance between array- and sequence-based SNP calls, genotyped unsequenced isolates, and placed them on a phylogeny with sequenced genomes. The microarray successfully genotyped VEEV directly from tissue samples of an infected mouse, bypassing the need for viral isolation, culture and genomic sequencing. Finally, we identified genomic variants associated with serotypes and host species, revealing a complex relationship between genotype and phenotype.

Background: Historically, identification of causal agents of disease has relied heavily on the ability to culture the organism in the laboratory and/or the use of pathogen-specific antibodies or sequence-based probes. However, these methods can be limiting: Even highly sensitive PCR-based assays must be continually updated due to signature degradation as new target strains and near neighbors are sequenced. Thus, there has been a need for assays that do not suffer as greatly from these limitations and/or biases. Recent advances in library preparation technologies for Next-Generation Sequencing (NGS) are focusing on the use of targeted amplification and targeted enrichment/capture to ensure that the most highly discriminating regions of the genomes of known targets (organism-unique regions and/or regions containing functionally important genes or phylogenetically-discriminating SNPs) will be sequenced, regardless of the complex sample background., Results: In the present study, we have assessed the feasibility of targeted sequence enhancement via amplification to facilitate detection of a bacterial pathogen present in low copy numbers in a background of human genomic material. Our results indicate that the targeted amplification of signature regions can effectively identify pathogen genomic material present in as little as 10 copies per ml in a complex sample. Importantly, the correct species and strain calls could be made in amplified samples, while this was not possible in unamplified samples., Conclusions: The results presented here demonstrate the efficacy of a targeted amplification approach to biothreat detection, using multiple highly-discriminative amplicons per biothreat organism that provide redundancy in case of variation in some primer regions. Importantly, strain level discrimination was possible at levels of 10 genome equivalents. Similar results could be obtained through use of panels focused on the identification of amplicons targeted for specific genes or SNPs instead of, or in addition to, those targeted for specific organisms (ongoing gene-targeting work to be reported later). Note that without some form of targeted enhancement, the enormous background present in complex clinical and environmental samples makes it highly unlikely that sufficient coverage of key pathogen(s) present in the sample will be achieved with current NGS technology to guarantee that the most highly discriminating regions will be sequenced.

Unlabelled: We announce the release of kSNP3.0, a program for SNP identification and phylogenetic analysis without genome alignment or the requirement for reference genomes. kSNP3.0 is a significantly improved version of kSNP v2., Availability and Implementation: kSNP3.0 is implemented as a package of stand-alone executables for Linux and Mac OS X under the open-source BSD license. The executable packages, source code and a full User Guide are freely available at https://sourceforge.net/projects/ksnp/files/, Contact: barryghall@gmail.com., (© The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

Identifying causative disease agents in human patients from shotgun metagenomic sequencing (SMS) presents a powerful tool to apply when other targeted diagnostics fail. Numerous technical challenges remain, however, before SMS can move beyond the role of research tool. Accurately separating the known and unknown organism content remains difficult, particularly when SMS is applied as a last resort. The true amount of human DNA that remains in a sample after screening against the human reference genome and filtering nonbiological components left from library preparation has previously been underreported. In this study, we create the most comprehensive collection of microbial and reference-free human genetic variation available in a database optimized for efficient metagenomic search by extracting sequences from GenBank and the 1000 Genomes Project. The results reveal new human sequences found in individual Human Microbiome Project (HMP) samples. Individual samples contain up to 95% human sequence, and 4% of the individual HMP samples contain 10% or more human reads. Left unidentified, human reads can complicate and slow down further analysis and lead to inaccurately labeled microbial taxa and ultimately lead to privacy concerns as more human genome data is collected., (© 2015 Ames et al.; Published by Cold Spring Harbor Laboratory Press.)

Many of the disease syndromes challenging the commercial swine industry involve the analysis of complex problems caused by polymicrobial, emerging or reemerging, and transboundary pathogens. This study investigated the utility of the Lawrence Livermore Microbial Detection Array (Lawrence Livermore National Laboratory, Livermore, California), designed to detect 8,101 species of microbes, in the evaluation of known and unknown microbes in serum, oral fluid, and tonsil from pigs experimentally coinfected with Porcine reproductive and respiratory syndrome virus (PRRSV) and Porcine circovirus-2 (PCV-2). The array easily identified PRRSV and PCV-2, but at decreased sensitivities compared to standard polymerase chain reaction detection methods. The oral fluid sample was the most informative, possessing additional signatures for several swine-associated bacteria, including Streptococcus sp., Clostridium sp., and Staphylococcus sp., (© 2015 The Author(s).)

Vaccinations against the encephalitic alphaviruses (western, eastern, and Venezuelan equine encephalitis virus) are of significant interest to biological defense, public health, and agricultural communities alike. Although vaccines licensed for veterinary applications are used in the Western Hemisphere and attenuated or inactivated viruses have been used under Investigational New Drug status to protect at-risk personnel, there are currently no licensed vaccines for use in humans. Here, we will discuss the need for a trivalent vaccine that can protect humans against all three viruses, recent progress to such a vaccine, and a strategy to continue development to Food and Drug Administration licensure., (© The American Society of Tropical Medicine and Hygiene.)

Background: Pairing up primers to amplify desired targets and avoid undesired cross reactions can be a combinatorial challenge. Effective prediction of specificity and inclusivity from multiplexed primers and TaqMan®/Luminex® probes is a critical step in PCR design., Results: Code is described to identify all primer and probe combinations from a list of unpaired, unordered candidates that should produce a product. It predicts and extracts all amplicon sequences in a large sequence database from a list of primers and probes, allowing degenerate bases and user-specified levels of primer-target mismatch tolerance. Amplicons hit by TaqMan®/Luminex® probes are indicated, and products may be annotated with gene information from NCBI. Fragment length distributions are calculated to predict electrophoretic gel banding patterns., Conclusions: Simulate_PCR is the only freely available software that can be run from the command line for high throughput applications which can calculate all products from large lists of primers and probes compared to a large sequence database such as nt. It requires no prior knowledge of how primers should be paired. Degenerate bases are allowed and entire amplicon sequences are extracted and annotated with gene information. Examples are provided for sets of TaqMan®/Luminex® PCR signatures predicted to amplify all HIV-1 genomes, all Coronaviridae genomes, and a group of antibiotic resistance genes. The software is a command line perl script freely available as open source.

Combat wound healing and resolution are highly affected by the resident microbial flora. We therefore sought to achieve comprehensive detection of microbial populations in wounds using novel genomic technologies and bioinformatics analyses. We employed a microarray capable of detecting all sequenced pathogens for interrogation of 124 wound samples from extremity injuries in combat-injured U.S. service members. A subset of samples was also processed via next-generation sequencing and metagenomic analysis. Array analysis detected microbial targets in 51% of all wound samples, with Acinetobacter baumannii being the most frequently detected species. Multiple Pseudomonas species were also detected in tissue biopsy specimens. Detection of the Acinetobacter plasmid pRAY correlated significantly with wound failure, while detection of enteric-associated bacteria was associated significantly with successful healing. Whole-genome sequencing revealed broad microbial biodiversity between samples. The total wound bioburden did not associate significantly with wound outcome, although temporal shifts were observed over the course of treatment. Given that standard microbiological methods do not detect the full range of microbes in each wound, these data emphasize the importance of supplementation with molecular techniques for thorough characterization of wound-associated microbes. Future application of genomic protocols for assessing microbial content could allow application of specialized care through early and rapid identification and management of critical patterns in wound bioburden., (Copyright © 2014, American Society for Microbiology. All Rights Reserved.)

Emerging viruses are usually endemic to tropical and sub-tropical regions of the world, but increased global travel, climate change and changes in lifestyle are believed to contribute to the spread of these viruses into new regions. Many of these viruses cause similar disease symptoms as other emerging viruses or common infections, making these unexpected pathogens difficult to diagnose. Broad-spectrum pathogen detection microarrays containing probes for all sequenced viruses and bacteria can provide rapid identification of viruses, guiding decisions about treatment and appropriate case management. We report a modified Whole Transcriptome Amplification (WTA) method that increases unbiased amplification, particular of RNA viruses. Using this modified WTA method, we tested the specificity and sensitivity of the Lawrence Livermore Microbial Detection Array (LLMDA) against a wide range of emerging viruses present in both non-clinical and clinical samples using two different microarray data analysis methods.

In 2010, researchers reported that the two US-licensed rotavirus vaccines contained DNA or DNA fragments from porcine circovirus (PCV). Although PCV, a common virus among pigs, is not thought to cause illness in humans, these findings raised several safety concerns. In this study, we sought to determine whether viruses, including PCV, could be detected in ileal tissue samples of children vaccinated with one of the two rotavirus vaccines. A broad spectrum, novel DNA detection technology, the Lawrence Livermore Microbial Detection Array (LLMDA), was utilized, and confirmation of viral pathogens using the polymerase chain reaction (PCR) was conducted. The LLMDA technology was recently used to identify PCV from one rotavirus vaccine. Ileal tissue samples were analyzed from 21 subjects, aged 15-62 months. PCV was not detected in any ileal tissue samples by the LLMDA or PCR. LLMDA identified a human rotavirus A from one of the vaccinated subjects, which is likely due to a recent infection from a wild type rotavirus. LLMDA also identified human parechovirus, a common gastroenteritis viral infection, from two subjects. Additionally, LLMDA detected common gastrointestinal bacterial organisms from the Enterobacteriaceae, Bacteroidaceae, and Streptococcaceae families from several subjects. This study provides a survey of viral and bacterial pathogens from pediatric ileal samples, and may shed light on future studies to identify pathogen associations with pediatric vaccinations.

Background. Targeted enrichment improves coverage of highly mutable viruses at low concentration in complex samples. Degenerate primers that anneal to conserved regions can facilitate amplification of divergent, low concentration variants, even when the strain present is unknown. Results. A tool for designing multiplex sets of degenerate sequencing primers to tile overlapping amplicons across multiple whole genomes is described. The new script, run_tiled_primers, is part of the PriMux software. Primers were designed for each segment of South American hemorrhagic fever viruses, tick-borne encephalitis, Henipaviruses, Arenaviruses, Filoviruses, Crimean-Congo hemorrhagic fever virus, Rift Valley fever virus, and Japanese encephalitis virus. Each group is highly diverse with as little as 5% genome consensus. Primer sets were computationally checked for nontarget cross reactions against the NCBI nucleotide sequence database. Primers for murine hepatitis virus were demonstrated in the lab to specifically amplify selected genes from a laboratory cultured strain that had undergone extensive passage in vitro and in vivo. Conclusions. This software should help researchers design multiplex sets of primers for targeted whole genome enrichment prior to sequencing to obtain better coverage of low titer, divergent viruses. Applications include viral discovery from a complex background and improved sensitivity and coverage of rapidly evolving strains or variants in a gene family.

Effective use of rapid and inexpensive whole genome sequencing for microbes requires fast, memory efficient bioinformatics tools for sequence comparison. The kSNP v2 software finds single nucleotide polymorphisms (SNPs) in whole genome data. kSNP v2 has numerous improvements over kSNP v1 including SNP gene annotation; better scaling for draft genomes available as assembled contigs or raw, unassembled reads; a tool to identify the optimal value of k; distribution of packages of executables for Linux and Mac OS X for ease of installation and user-friendly use; and a detailed User Guide. SNP discovery is based on k-mer analysis, and requires no multiple sequence alignment or the selection of a single reference genome. Most target sets with hundreds of genomes complete in minutes to hours. SNP phylogenies are built by maximum likelihood, parsimony, and distance, based on all SNPs, only core SNPs, or SNPs present in some intermediate user-specified fraction of targets. The SNP-based trees that result are consistent with known taxonomy. kSNP v2 can handle many gigabases of sequence in a single run, and if one or more annotated genomes are included in the target set, SNPs are annotated with protein coding and other information (UTRs, etc.) from Genbank file(s). We demonstrate application of kSNP v2 on sets of viral and bacterial genomes, and discuss in detail analysis of a set of 68 finished E. coli and Shigella genomes and a set of the same genomes to which have been added 47 assemblies and four "raw read" genomes of H104:H4 strains from the recent European E. coli outbreak that resulted in both bloody diarrhea and hemolytic uremic syndrome (HUS), and caused at least 50 deaths.

Microbial genotyping is essential for forensic discrimination of pathogen strains, tracing epidemics, and understanding evolutionary processes. Phylogenetic analyses were performed and genotyping assays designed for five viral species complexes or genera: Western, Eastern, and Venezuelan equine encephalitis viruses, hantavirus segments L, M, and S, and orthopoxviruses. For each group, sequence alignments and phylogenetic trees were built. PCR signatures composed of primer pairs or TaqMan™ triplets were designed and mapped to nodes of the trees for sub-type or strain specific PCR-based identification. In addition, single nucleotide polymorphisms (SNPs) were identified and mapped to trees, and SNP microarray probes were designed to enable highly multiplexed genotyping of an unsequenced sample by hybridization. SNP-based trees corresponded well with MSA trees. Near-perfect isolate resolution was possible for all viruses analyzed computationally using either SNPs or PCR signatures. More tree nodes were represented by SNP loci than by PCR signatures, as PCR signatures often represented subsets of strains not corresponding to a branch. However, while PCR genotyping is possible, the number of PCR signatures needed to characterize an unknown can be very large. SNP microarrays are a suitable alternative, as arrays enable highly multiplexed, high resolution genotyping of an unknown in a single hybridization assay., (Copyright © 2013 The Authors. Published by Elsevier B.V. All rights reserved.)

Motivation: Deep metagenomic sequencing of biological samples has the potential to recover otherwise difficult-to-detect microorganisms and accurately characterize biological samples with limited prior knowledge of sample contents. Existing metagenomic taxonomic classification algorithms, however, do not scale well to analyze large metagenomic datasets, and balancing classification accuracy with computational efficiency presents a fundamental challenge., Results: A method is presented to shift computational costs to an off-line computation by creating a taxonomy/genome index that supports scalable metagenomic classification. Scalable performance is demonstrated on real and simulated data to show accurate classification in the presence of novel organisms on samples that include viruses, prokaryotes, fungi and protists. Taxonomic classification of the previously published 150 giga-base Tyrolean Iceman dataset was found to take <20 h on a single node 40 core large memory machine and provide new insights on the metagenomic contents of the sample., Availability: Software was implemented in C++ and is freely available at http://sourceforge.net/projects/lmat, Contact: allen99@llnl.gov, Supplementary Information: Supplementary data are available at Bioinformatics online.

Bacillus anthracis is the potentially lethal etiologic agent of anthrax disease, and is a significant concern in the realm of biodefense. One of the cornerstones of an effective biodefense strategy is the ability to detect infectious agents with a high degree of sensitivity and specificity in the context of a complex sample background. The nature of the B. anthracis genome, however, renders specific detection difficult, due to close homology with B. cereus and B. thuringiensis. We therefore elected to determine the efficacy of next-generation sequencing analysis and microarrays for detection of B. anthracis in an environmental background. We applied next-generation sequencing to titrated genome copy numbers of B. anthracis in the presence of background nucleic acid extracted from aerosol and soil samples. We found next-generation sequencing to be capable of detecting as few as 10 genomic equivalents of B. anthracis DNA per nanogram of background nucleic acid. Detection was accomplished by mapping reads to either a defined subset of reference genomes or to the full GenBank database. Moreover, sequence data obtained from B. anthracis could be reliably distinguished from sequence data mapping to either B. cereus or B. thuringiensis. We also demonstrated the efficacy of a microbial census microarray in detecting B. anthracis in the same samples, representing a cost-effective and high-throughput approach, complementary to next-generation sequencing. Our results, in combination with the capacity of sequencing for providing insights into the genomic characteristics of complex and novel organisms, suggest that these platforms should be considered important components of a biosurveillance strategy.

Microarrays to characterize single nucleotide polymorphisms (SNPs) provide a cost-effective and rapid method (under 24h) to genotype microbes as an alternative to sequencing. We developed a pipeline for SNP discovery and microarray design that scales to 100's of microbial genomes. Here we tested various SNP probe design strategies against 8 sequenced isolates of Bacillus anthracis to compare sequence and microarray data. The best strategy allowed probe length to vary within 32-40 bp to equalize hybridization free energy. This strategy resulted in a call rate of 99.52% and concordance rate of 99.86% for finished genomes. Other probe design strategies averaged substantially lower call rates (94.65-96.41%) and slightly lower concordance rates (99.64-99.80%). These rates were lower for draft than finished genomes, consistent with higher incidence of sequencing errors and gaps. Highly accurate SNP calls were possible in complex soil and blood backgrounds down to 1000 copies, and moderately accurate SNP calls down to 100 spiked copies. The closest genome to the spiked strain was correctly identified at only 10 spiked copies. Discrepancies between sequence and array data did not alter the SNP-based phylogeny, regardless of the probe design strategy, indicating that SNP arrays can accurately place unsequenced isolates on a phylogeny., (© 2013. Published by Elsevier B.V. All rights reserved.)

Background: Decades after the eradication of smallpox, its etiological agent, variola virus (VARV), remains a threat as a potential bioweapon. Outbreaks of smallpox around the time of the global eradication effort exhibited variable case fatality rates (CFRs), likely attributable in part to complex viral genetic determinants of smallpox virulence. We aimed to identify genome-wide single nucleotide polymorphisms associated with CFR. We evaluated unadjusted and outbreak geographic location-adjusted models of single SNPs and two- and three-way interactions between SNPs., Findings: Using the data mining approach multifactor dimensionality reduction (MDR), we identified five VARV SNPs in models significantly associated with CFR. The top performing unadjusted model and adjusted models both revealed the same two-way gene-gene interaction. We discuss the biological plausibility of the influence of the SNPs identified these and other significant models on the strain-specific virulence of VARV., Conclusions: We have identified genetic loci in the VARV genome that are statistically associated with VARV virulence as measured by CFR. While our ability to infer a causal relationship between the specific SNPs identified in our analysis and VARV virulence is limited, our results suggest that smallpox severity is in part associated with VARV strain variation and that VARV virulence may be determined by multiple genetic loci. This study represents the first application of MDR to the identification of pathogen gene-gene interactions for predicting infectious disease outbreak severity.

PriMux is a new software package for selecting multiplex compatible, degenerate primers and probes to detect diverse targets such as viruses. It requires no multiple sequence alignment, instead applying k-mer algorithms, hence it scales well for large target sets and saves user effort from curating sequences into alignable groups. PriMux has the capability to predict degenerate primers as well as probes suitable for TaqMan or other primer/probe triplet assay formats, or simply probes for microarray or other single-oligo assay formats. PriMux employs suffix array methods for efficient calculations on oligos 10-~100 nt in length. TaqMan® primers and probes for each segment of Rift Valley fever virus were designed using PriMux, and lab testing comparing signatures designed using PriMux versus those designed using traditional methods demonstrated equivalent or better sensitivity for the PriMux-designed signatures compared to traditional signatures. In addition, we used PriMux to design TaqMan® primers and probes for unalignable or poorly alignable groups of targets: that is, all segments of Rift Valley fever virus analyzed as a single target set of 198 sequences, or all 2863 Dengue virus genomes for all four serotypes available at the time of our analysis. The PriMux software is available as open source from http://sourceforge.net/projects/PriMux.

Background: We developed an extendable open-source Loop-mediated isothermal AMPlification (LAMP) signature design program called LAVA (LAMP Assay Versatile Analysis). LAVA was created in response to limitations of existing LAMP signature programs., Results: LAVA identifies combinations of six primer regions for basic LAMP signatures, or combinations of eight primer regions for LAMP signatures with loop primers, which can be used as LAMP signatures. The identified primers are conserved among target organism sequences. Primer combinations are optimized based on lengths, melting temperatures, and spacing among primer sites. We compare LAMP signature candidates for Staphylococcus aureus created both by LAVA and by PrimerExplorer. We also include signatures from a sample run targeting all strains of Mycobacterium tuberculosis., Conclusions: We have designed and demonstrated new software for identifying signature candidates appropriate for LAMP assays. The software is available for download at http://lava-dna.googlecode.com/.

Background: Identifying the bacteria and viruses present in a complex sample is useful in disease diagnostics, product safety, environmental characterization, and research. Array-based methods have proven utility to detect in a single assay at a reasonable cost any microbe from the thousands that have been sequenced., Methods: We designed a pan-Microbial Detection Array (MDA) to detect all known viruses (including phages), bacteria and plasmids and developed a novel statistical analysis method to identify mixtures of organisms from complex samples hybridized to the array. The array has broader coverage of bacterial and viral targets and is based on more recent sequence data and more probes per target than other microbial detection/discovery arrays in the literature. Family-specific probes were selected for all sequenced viral and bacterial complete genomes, segments, and plasmids. Probes were designed to tolerate some sequence variation to enable detection of divergent species with homology to sequenced organisms, and to have no significant matches to the human genome sequence., Results: In blinded testing on spiked samples with single or multiple viruses, the MDA was able to correctly identify species or strains. In clinical fecal, serum, and respiratory samples, the MDA was able to detect and characterize multiple viruses, phage, and bacteria in a sample to the family and species level, as confirmed by PCR., Conclusions: The MDA can be used to identify the suite of viruses and bacteria present in complex samples.

We describe a Multiplex Primer Prediction (MPP) algorithm to build multiplex compatible primer sets to amplify all members of large, diverse and unalignable sets of target sequences. The MPP algorithm is scalable to larger target sets than other available software, and it does not require a multiple sequence alignment. We applied it to questions in viral detection, and demonstrated that there are no universally conserved priming sequences among viruses and that it could require an unfeasibly large number of primers ( approximately 3700 18-mers or approximately 2000 10-mers) to generate amplicons from all sequenced viruses. We then designed primer sets separately for each viral family, and for several diverse species such as foot-and-mouth disease virus (FMDV), hemagglutinin (HA) and neuraminidase (NA) segments of influenza A virus, Norwalk virus, and HIV-1. We empirically demonstrated the application of the software with a multiplex set of 16 short (10 nt) primers designed to amplify the Poxviridae family to produce a specific amplicon from vaccinia virus.

Background: Finding the amino acid mutations that affect the severity of influenza infections remains an open and challenging problem. Of special interest is better understanding how current circulating influenza strains could evolve into a new pandemic strain. Influenza proteomes from distinct viral phenotype classes were searched for class specific amino acid mutations conserved in past pandemics, using reverse engineered linear classifiers., Results: Thirty-four amino acid markers associated with host specificity and high mortality rate were found. Some markers had little impact on distinguishing the functional classes by themselves, however in combination with other mutations they improved class prediction. Pairwise combinations of influenza genomes were checked for reassortment and mutation events needed to acquire the pandemic conserved markers. Evolutionary pathways involving H1N1 human and swine strains mixed with avian strains show the potential to acquire the pandemic markers with a double reassortment and one or two amino acid mutations., Conclusion: The small mutation combinations found at multiple protein positions associated with viral phenotype indicate that surveillance tools could monitor genetic variation beyond single point mutations to track influenza strains. Finding that certain strain combinations have the potential to acquire pandemic conserved markers through a limited number of reassortment and mutation events illustrates the potential for reassortment and mutation events to lead to new circulating influenza strains.

Background: In recent years real-time PCR has become a leading technique for nucleic acid detection and quantification. These assays have the potential to greatly enhance efficiency in the clinical laboratory. Choice of primer and probe sequences is critical for accurate diagnosis in the clinic, yet current primer/probe signature design strategies are limited, and signature evaluation methods are lacking., Methods: We assessed the quality of a signature by predicting the number of true positive, false positive and false negative hits against all available public sequence data. We found real-time PCR signatures described in recent literature and used a BLAST search based approach to collect all hits to the primer-probe combinations that should be amplified by real-time PCR chemistry. We then compared our hits with the sequences in the NCBI taxonomy tree that the signature was designed to detect., Results: We found that many published signatures have high specificity (almost no false positives) but low sensitivity (high false negative rate). Where high sensitivity is needed, we offer a revised methodology for signature design which may designate that multiple signatures are required to detect all sequenced strains. We use this methodology to produce new signatures that are predicted to have higher sensitivity and specificity., Conclusion: We show that current methods for real-time PCR assay design have unacceptably low sensitivities for most clinical applications. Additionally, as new sequence data becomes available, old assays must be reassessed and redesigned. A standard protocol for both generating and assessing the quality of these assays is therefore of great value. Real-time PCR has the capacity to greatly improve clinical diagnostics. The improved assay design and evaluation methods presented herein will expedite adoption of this technique in the clinical lab.

Using newly designed computational tools we show that, despite substantial shared sequences between natural plasmids and artificial vector sequences, a robust set of DNA oligomers can be identified that can differentiate artificial vector sequences from all available background viral and bacterial genomes and natural plasmids. We predict that these tools can achieve very high sensitivity and specificity rates for detecting new unsequenced vectors in microarray-based bioassays. Such DNA signatures could be important in detecting genetically engineered bacteria in environmental samples.

Human disease likely attributable to variola virus (VARV), the etiologic agent of smallpox, has been reported in human populations for >2,000 years. VARV is unique among orthopoxviruses in that it is an exclusively human pathogen. Because VARV has a large, slowly evolving DNA genome, we were able to construct a robust phylogeny of VARV by analyzing concatenated single nucleotide polymorphisms (SNPs) from genome sequences of 47 VARV isolates with broad geographic distributions. Our results show two primary VARV clades, which likely diverged from an ancestral African rodent-borne variola-like virus either approximately 16,000 or approximately 68,000 years before present (YBP), depending on which historical records (East Asian or African) are used to calibrate the molecular clock. One primary clade was represented by the Asian VARV major strains, the more clinically severe form of smallpox, which spread from Asia either 400 or 1,600 YBP. Another primary clade included both alastrim minor, a phenotypically mild smallpox described from the American continents, and isolates from West Africa. This clade diverged from an ancestral VARV either 1,400 or 6,300 YBP, and then further diverged into two subclades at least 800 YBP. All of these analyses indicate that the divergence of alastrim and variola major occurred earlier than previously believed.

Sequencing pathogen genomes is costly, demanding careful allocation of limited sequencing resources. We built a computational Sequencing Analysis Pipeline (SAP) to guide decisions regarding the amount of genomic sequencing necessary to develop high-quality diagnostic DNA and protein signatures. SAP uses simulations to estimate the number of target genomes and close phylogenetic relatives (near neighbors or NNs) to sequence. We use SAP to assess whether draft data are sufficient or finished sequencing is required using Marburg and variola virus sequences. Simulations indicate that intermediate to high-quality draft with error rates of 10(-3)-10(-5) (approximately 8x coverage) of target organisms is suitable for DNA signature prediction. Low-quality draft with error rates of approximately 1% (3x to 6x coverage) of target isolates is inadequate for DNA signature prediction, although low-quality draft of NNs is sufficient, as long as the target genomes are of high quality. For protein signature prediction, sequencing errors in target genomes substantially reduce the detection of amino acid sequence conservation, even if the draft is of high quality. In summary, high-quality draft of target and low-quality draft of NNs appears to be a cost-effective investment for DNA signature prediction, but may lead to underestimation of predicted protein signatures.

Background: Microbial forensics is important in tracking the source of a pathogen, whether the disease is a naturally occurring outbreak or part of a criminal investigation., Results: A method and SPR Opt (SNP and PCR-RFLP Optimization) software to perform a comprehensive, whole-genome analysis to forensically discriminate multiple sequences is presented. Tools for the optimization of forensic typing using Single Nucleotide Polymorphism (SNP) and PCR-Restriction Fragment Length Polymorphism (PCR-RFLP) analyses across multiple isolate sequences of a species are described. The PCR-RFLP analysis includes prediction and selection of optimal primers and restriction enzymes to enable maximum isolate discrimination based on sequence information. SPR Opt calculates all SNP or PCR-RFLP variations present in the sequences, groups them into haplotypes according to their co-segregation across those sequences, and performs combinatoric analyses to determine which sets of haplotypes provide maximal discrimination among all the input sequences. Those set combinations requiring that membership in the fewest haplotypes be queried (i.e. the fewest assays be performed) are found. These analyses highlight variable regions based on existing sequence data. These markers may be heterogeneous among unsequenced isolates as well, and thus may be useful for characterizing the relationships among unsequenced as well as sequenced isolates. The predictions are multi-locus. Analyses of mumps and SARS viruses are summarized. Phylogenetic trees created based on SNPs, PCR-RFLPs, and full genomes are compared for SARS virus, illustrating that purported phylogenies based only on SNP or PCR-RFLP variations do not match those based on multiple sequence alignment of the full genomes., Conclusion: This is the first software to optimize the selection of forensic markers to maximize information gained from the fewest assays, accepting whole or partial genome sequence data as input. As more sequence data becomes available for multiple strains and isolates of a species, automated, computational approaches such as those described here will be essential to make sense of large amounts of information, and to guide and optimize efforts in the laboratory. The software and source code for SPR Opt is publicly available and free for non-profit use at http://www.llnl.gov/IPandC/technology/software/softwaretitles/spropt.php.

Computational analyses of genome sequences may elucidate protein signatures unique to a target pathogen. We constructed a Protein Signature Pipeline to guide the selection of short peptide sequences to serve as targets for detection and therapeutics. In silico identification of good target peptides that are conserved among strains and unique compared to other species generates a list of peptides. These peptides may be developed in the laboratory as targets of antibody, peptide, and ligand binding for detection assays and therapeutics or as targets for vaccine development. In this paper, we assess how the amount of sequence data affects our ability to identify conserved, unique protein signature candidates. To determine the amount of sequence data required to select good protein signature candidates, we have built a computationally intensive system called the Sequencing Analysis Pipeline (SAP). The SAP performs thousands of Monte Carlo simulations, each calling the Protein Signature Pipeline, to assess how the amount of sequence data for a target organism affects the ability to predict peptide signature candidates. Viral species differ substantially in the number of genomes required to predict protein signature targets. Patterns do not appear based on genome structure. There are more protein than DNA signatures due to greater intraspecific conservation at the protein than at the nucleotide level. We conclude that it is necessary to use the SAP as a dynamic system to assess the need for continued sequencing for each species individually and to update predictions with each additional genome that is sequenced.

We built a system to guide decisions regarding the amount of genomic sequencing required to develop diagnostic DNA signatures, which are short sequences that are sufficient to uniquely identify a viral species. We used our existing DNA diagnostic signature prediction pipeline, which selects regions of a target species genome that are conserved among strains of the target (for reliability, to prevent false negatives) and unique relative to other species (for specificity, to avoid false positives). We performed simulations, based on existing sequence data, to assess the number of genome sequences of a target species and of close phylogenetic relatives (near neighbors) that are required to predict diagnostic signature regions that are conserved among strains of the target species and unique relative to other bacterial and viral species. For DNA viruses such as variola (smallpox), three target genomes provide sufficient guidance for selecting species-wide signatures. Three near-neighbor genomes are critical for species specificity. In contrast, most RNA viruses require four target genomes and no near-neighbor genomes, since lack of conservation among strains is more limiting than uniqueness. Severe acute respiratory syndrome and Ebola Zaire are exceptional, as additional target genomes currently do not improve predictions, but near-neighbor sequences are urgently needed. Our results also indicate that double-stranded DNA viruses are more conserved among strains than are RNA viruses, since in most cases there was at least one conserved signature candidate for the DNA viruses and zero conserved signature candidates for the RNA viruses.

This review focuses on clinical trials and the approval process in order to understand the discrepancy between vibrant science and the continuing failure of mechanism-based anticancer drugs., Clinical Trials: Mechanistic trials in cancer require at least three elements: the assurance of tumor definition, knowledge of the natural history, and earlier intervention. Histologic identity is not a reliable surrogate of the functional nature or a predictor of the natural history. cDNA arrays and computational models have promise in improving diagnosis and prediction, and thereby making tailored therapy possible. The latter requires: the incorporation of initial and earlier rational combination therapy, dynamic models of disease progression, and methods to discourage the emergence of resistance. For cytostatics, and in early cancer, a delay in progression may represent a better index of survival than tumor shrinkage., Approval Process: Since mechanistic similarities may outweigh therapeutic predictions based on organ-and histology-defined cancer, there is a need for a revised process that would allow for tailored treatment and initial combination therapy to improve safety, efficacy, and circumvent resistance., Conclusion: In order to translate the major and immediate potential of cytostatic drugs, clinical trials and the approval process may need to shift to a mechanism-based framework.

Computational models of cancer chemotherapy have the potential to streamline clinical trial design, contribute to the design of rational, tailored treatments, and facilitate our understanding of experimental results. Mechanistic models based on functional data from tumor biopsies will enable physicians to predict response to treatment for a specific patient, in contrast to statistical models in which the probability of response for a given patient may differ substantially from the population average. While microarray analyses of gene expression also show promise for guiding individualized treatments, it may be difficult to link statistical mining of microarray data with mechanistic, tailored treatments. Furthermore, gene expression does not identify how drugs should be scheduled. This review summarizes mechanistic mathematical models developed to improve the design of chemotherapy regimens. Mechanistic models that incorporate both genetic resistance and cell cycle-mediated resistance during treatment with multiple drugs will be most useful in designing treatment regimens tailored for individuals. Because there are already a number of papers that address the applications of microarray technology, we will limit our discussion to the contrasts between mechanistic computational models and microarray technology, and how these two approaches may complement one another.

Recent events illustrate the imperative to rapidly and accurately detect and identify pathogens during disease outbreaks, whether they are natural or engineered. Particularly for our primary goal of detecting bioterrorist releases, detection techniques must be both species-wide (capable of detecting all known strains of a given species) and species specific. Due to classification restrictions on the publication of data for species that may pose a bioterror threat, we illustrate the challenges of finding such assays using five nonthreat organisms that are nevertheless of public health concern: human immunodeficiency virus (HIV) and four species of hepatitis viruses. Fluorogenic probe-based PCR assays (TaqMan; Perkin-Elmer Corp., Applied Biosystems, Foster City, Calif.) may be sensitive, fast methods for the identification of species in which the genome is conserved among strains, such as hepatitis A virus. For species such as HIV, however, the strains are highly divergent. We use computational methods to show that nine TaqMan primer and probe sequences, or signatures, are needed to ensure that all strains will be detected, but this is an unfeasible number, considering the cost of TaqMan probes. Strains of hepatitis B, C, and E viruses show intermediate divergence, so that two to three TaqMan signatures are required to detect all strains of each virus. We conclude that for species such as hepatitis A virus with high levels of sequence conservation among strains, signatures can be found computationally for detection by the TaqMan assay, which is a sensitive, rapid, and cost-effective method. However, for species such as HIV with substantial genetic divergence among strains, the TaqMan assay becomes unfeasible and alternative detection methods may be required. We compare the TaqMan assay with some of the alternative nucleic acid-based detection techniques of microarray, chip, and bead technologies in terms of sensitivity, speed, and cost.

Computational models of cancer chemotherapy enhance the understanding of in vitro, in vivo, and clinical trial data and have the potential to contribute to the design of rational treatment regimens. In particular, mechanistic, predictive models are superior to statistical, phenomenological descriptions of data. Mechanistic models based on functional data from tumor biopsies will enable the response to treatment to be predicted for a specific patient, in contrast to statistical models in which the probability of response for a given patient may differ substantially from the population average. This review summarizes mathematical models developed to improve the design of treatment regimens using cell-cycle phase-specific chemotherapy. It starts with simple models of dose response, then moves to more complex models of scheduling cell-cycle phase-specific drugs, and finally discusses mechanistic models that incorporate both genetic drug resistance and cell cycle-mediated drug resistance. This last class of models will be most useful in designing treatment regimens tailored for individual patients.

Recent evidence has shown that translocation frequencies decline over time. This phenomenon might be explained by the co-occurrence of translocations in cells that also contain dicentrics, in which case translocations would be eliminated as a by-product of selection against dicentrics. Alternatively, a fraction of translocations may themselves be lethal. Here we describe our initial approaches to develop mathematical models to test whether the decline in translocation frequencies results from the first, the second, or a combination of these two possibilities. The models assumed that all chromosome exchanges were simple, i.e., were comprised of dicentrics as well as one-way and two-way translocations. Complex aberrations (three or more breaks in two or more chromosomes) were not modeled, nor were fragments or intrachromosomal exchanges (rings, inversions). We tested the models using Monte Carlo simulations, and then we fitted the models to data describing chromosome aberration frequencies induced by a single acute in vitro exposure to (137)Cs gamma rays in human peripheral blood lymphocytes from two donors. Chromosome painting was used to enumerate translocations and dicentrics from 2 to 7 days after exposure. Our results indicate that in donor no. 2, the decline in translocation frequencies occurs as a by-product of selection against dicentrics. However, in donor no. 1, whose cells appeared more radiosensitive than cells from donor no. 2, up to 40% of the one-way translocations may themselves be lethal at high doses, although calculations indicate that two-way translocations do not cause lymphocyte mortality. Individual variation in the probability that translocations are lethal to cells appears to be important, and one-way translocations appear to be lethal more often than two-way translocations. Within the limits of these models, these findings indicate that both postulated mechanisms, i.e. inherent lethality and selection against dicentrics in the same cells, contribute to the loss of both one-way and two-way translocations.

Background: Predicting and tailoring optimal cancer treatments presents a major challenge., Methods: A computational model (kinetically tailored treatment, or KITT model) is developed to predict drug combinations, doses, and schedules likely to be effective in reducing tumor size and prolonging patient life. Treatment strategies may be tailored to individuals based on tumor cell kinetics. The model incorporates intra-tumor heterogeneity and evolution of drug resistance, apoptotic rates, and cell division rates. Tumor growth may follow an exponential or a Gompertzian trajectory. Drug pharmacodynamic and pharmacokinetic models are used. Toxicity is modeled in several ways., Results: A key prediction of KITT is that including cytostatic drugs like tamoxifen and herceptin during treatment with cytotoxic drugs substantially increases the probability of cure and prolongs patient life. Results also suggest that altering drug scheduling may be more effective but not more toxic than dose escalation. CAF chemotherapy (cyclophosphamide, adriamycin, and 5-fluorouracil) is predicted to be more effective than CMF (cyclophosphamide, methotrexate, and 5-fluorouracil). KITT also suggests that tumors with a high proliferative index (PI) may respond better to drug combinations incorporating two cell-cycle phase-specific drugs than do tumors with a low PI. Tumors with a low PI, in contrast, are predicted to respond better to regimens involving two cell-cycle phase-non-specific drugs than do tumors with a high PI. These predictions are borne out by clinical trial results published in the literature, which are discussed. Simulated predictions of the model match well with results from a clinical trial by Silvestrini et al. (2000. Int. J. Cancer 87, 405). The results of simulating the growth of 26896 tumors are used to construct a decision tree for prognosis to identify the key tumor and treatment variables., Conclusion: Additional tests of the model are needed in which physicians collect information on apoptotic and proliferative indices, cell-cycle times, and drug resistance from biopsies of each individual's tumor. Computational models may become important tools to help optimize and tailor cancer treatments., (Copyright 2002 Academic Press.)

Plants often suffer reductions in fecundity due to insect herbivory. Whether this loss of seeds has population-level consequences is much debated and often unknown. For many plants, particularly those with long-lived seedbanks, it is frequently asserted that herbivores have minimal impacts on plant abundance because safe-site availability rather than absolute seed number determines the magnitude of future plant recruitment and hence population abundance. However, empirical tests of this assertion are generally lacking and the interplay between herbivory, spatio-temporal variability in seed- or safe-site-limited recruitment, and seedbank dynamics is likely to be complex. Here we use a stochastic simulation model to explore how changes in the spatial and temporal frequency of seed-limited recruitment, the strength of density-dependent seedling survival, and longevity of seeds in the soil influence the population response to herbivory. Model output reveals several surprising results. First, given a seedbank, herbivores can have substantial effects on mean population abundance even if recruitment is primarily safe-site-limited in either time or space. Second, increasing seedbank longevity increases the population effects of herbivory, because annual reductions in seed input due to herbivory are accumulated in the seedbank. Third, population impacts of herbivory are robust even in the face of moderately strong density-dependent seedling mortality. These results imply that the conditions under which herbivores influence plant population dynamics may be more widespread than heretofore expected. Experiments are now needed to test these predictions.

In vitro dose-response curves for anticancer agents are useful for predicting the clinical response to chemotherapy, and models to capture the time-dependency of dose-response curves are necessary for potential clinical extrapolation. Usually, the modified Hill model is used (see Levasseur et al., Cancer Res., 58: 5749-5761, 1998), although this model is neither mechanistic nor predictive for understanding how drug and tumor cell characteristics affect the shape of the dose-response curve. A new exponential kill (EK) model is proposed to predict the shape of dose-response curves based on the cell cycle phase specificity of a drug, the cell cycle time, the duration and concentration of drug exposure at the site of action, and a scaling factor for the level of drug resistance. Explicit analytical equations are presented for predicting the ICx (the concentration required to reduce cell growth by x%), the maximum cell kill achievable at high doses after a given duration of drug exposure, and the slope of the survival fraction versus log (concentration) plot at the ICx. Numerical solutions illustrate that there may be an optimal, finite duration of drug exposure that maximizes cell kill for a given area under the concentration versus time curve, and an analytical equation is given to calculate when such an optimal, finite duration exists. The EK model generates sigmoidal dose-response curves, like those seen empirically and previously described by the Hill model, which eventually plateau with increasing drug concentration at levels that depend on the cell cycle specificity of the drug, the cell cycle time, and the duration of exposure to the drug. This study includes no original data. Instead, empirical results in the literature are used to test the model. Because data by Levasseur et al. (1998) was fit to the Hill model assuming the plateau in the effect versus concentration curve to be independent of exposure duration, a full test of the model is not possible using their published data. Some tests of the EK model were possible, however, showing that EK model predictions yield good fits to in vitro data published in that and in another study. In addition, combining the EK model with a pharmacokinetic model resulted in predictions that were consistent with results of clinical studies comparing etoposide given in different schedules. Further tests of the model are necessary.

Some clonal organisms may live for thousands of years and show no signs of senescence, while others consistently die after finite life spans. Using two models, we examined how stage-specific life-history rates of a clone's modules determine whether a genetic individual escapes senescence by replacing old modules with new ones. When the rates of clonal or sexual reproduction and survival of individual modules decline with age, clones are more likely to experience senescence. In addition, the models predict that there is a greater tendency to find senescence in terms of a decline in the rate of sexual reproduction with clone age than in terms of an increase in the probability of clone mortality, unless rates of sexual reproduction increase dramatically with module stage. Using a matrix model modified to represent the clonal lifestyle, we show how a trade-off between sexual and clonal reproduction could result in selection for or against clonal senescence. We also show that, in contrast to unitary organisms, the strength of selection on life-history traits can increase with the age of a clone even in a growing population, countering the evolution of senescence.

A study was carried out in 1990 to guide the development of a protocol for assessing residential exposures of children to time-weighted-average (TWA) power-frequency magnetic fields. The principal goal of this dosimetry study was to determine whether area (i.e., spot and/or 24 h) measurements of power-frequency magnetic fields in the residences and in the schools and daycare centers of 29 children (4 months through 8 years of age) could be used to predict their measured personal 24-h exposures. TWA personal exposures, measured with AMEX-3D meters worn by subjects, were approximately log-normally distributed with both residential and nonresidential geometric means of 0.10 microT (1.0 mG). Between-subjects variability in residential personal exposure levels (geometric standard deviation of 2.4) was substantially greater than that observed for nonresidential personal exposure levels (1.4). The correlation between log-transformed residential and total personal exposure levels was 0.97. Time-weighted averages of the magnetic fields measured in children's bedrooms, family rooms, living rooms, and kitchens were highly correlated with residential personal exposure levels (r = 0.90). In general, magnetic field levels measured in schools and daycare centers attended by subjects were smaller and less variable than measured residential fields and were only weakly correlated with measured nonresidential personal exposures. The final measurement protocol, which will be used in a large US study examining the relationship between childhood leukemia and exposure to magnetic fields, contains the following elements: normal- and low-power spot magnetic field measurements in bedrooms occupied by subjects during the 5 years prior to the date of diagnosis for cases or the corresponding date for controls; spot measurements under normal and low power-usage conditions at the centers of the kitchen and the family room; 24-h magnetic-field recordings near subjects' beds; and wire coding using the Wertheimer-Leeper method.

The solutions of dobutamine hydrochloride (5 mg/ml), dopamine hydrochloride (4 mg/ml), nitroglycerin (1 mg/ml) and sodium nitroprusside (1 mg/ml) in dextrose 5% injection were stable for 24 h when stored at 25 degrees C in 60-ml plastic syringes. For sodium nitroprusside, the syringes must be wrapped with aluminium foil (provided by the manufacturer), otherwise the loss in potency is very high (22%). There was no change in the pH values of dobutamine and dopamine solutions as well as sodium nitroprusside solutions in the prewrapped syringes. However, the pH value of nitroglycerin solutions decreased to 4.3 from 4.6 and that of sodium nitroprusside solutions in unwrapped syringes from 4.2 to 3.5; these solutions had discoloured. The chromatogram also showed new peaks from the products of decomposition. The physical appearances of the other solutions did not change.

The chemical stabilities of isoetharine hydrochloride inhalation solution, metaproterenol sulphate inhalation solution and terbutaline sulphate injection, after diluting 1 in 10 with sodium chloride 0.9% injection were studied. On storing the solutions in amber-coloured syringes, they were stable for at least 120 days at 5 degrees C. At 25 degrees C they were also stable for 120 days except that isoetharine solution discoloured and lost 7.8% of its potency after 90 days of storage. There was a new peak in the chromatogram from the decomposition product. All other solutions remained clear for 120 days at both temperatures. The initial and final pH values were similar except that after 120 days at both temperatures. The initial and final pH values were similar except that after 120 days at 25 degrees C, the pH value of terbutaline solution had increased from 4.9 to 5.4.

The chemical stability of thiopental sodium injection (2.5%) when stored at 25 degrees and 5 degrees in disposable plastic syringes of two manufacturers (Monoject and Becton Dickenson and Co.) has been studied using the USP-NF method. The injection appeared to be stable for five days at 25 degrees and 45 days at 5 degrees with a loss in potency of less than 7%. The thiopental sodium did not adsorb on the syringes. The pH values and the physical appearance did not change. An additional peak was obtained in the chromatogram from both the freshly prepared and the assay solution probably due to an impurity in the powder.