Current technology permits an unbiased massive analysis of somatic genetic alterations from tumor DNA as well as the generation of individualized mouse xenografts (Avatar models). This work aimed to evaluate our experience integrating these two strategies to personalize the treatment of patients with cancer.
We performed whole-exome sequencing analysis of 25 patients with advanced solid tumors to identify putatively actionable tumor-specific genomic alterations. Avatar models were used as an in vivo platform to test proposed treatment strategies.
Successful exome sequencing analyses have been obtained for 23 patients. Tumor-specific mutations and copy-number variations were identified. All samples profiled contained relevant genomic alterations. Tumor was implanted to create an Avatar model from 14 patients and 10 succeeded. Occasionally, actionable alterations such as mutations in NF1, PI3KA, and DDR2 failed to provide any benefit when a targeted drug was tested in the Avatar and, accordingly, treatment of the patients with these drugs was not effective. To date, 13 patients have received a personalized treatment and 6 achieved durable partial remissions. Prior testing of candidate treatments in Avatar models correlated with clinical response and helped to select empirical treatments in some patients with no actionable mutations.
The use of full genomic analysis for cancer care is encouraging but presents important challenges that will need to be solved for broad clinical application. Avatar models are a promising investigational platform for therapeutic decision making. While limitations still exist, this strategy should be further tested.
The methodologies used to generate genome and metagenome annotations are diverse and vary between groups and laboratories. Descriptions of the annotation process are helpful in interpreting genome annotation data. Some groups have produced Standard Operating Procedures (SOPs) that describe the annotation process, but standards are lacking for structure and content of these descriptions. In addition, there is no central repository to store and disseminate procedures and protocols for genome annotation. We highlight the importance of SOPs for genome annotation and endorse an online repository of SOPs.
Besides the development of comprehensive tools for high-throughput 16S ribosomal RNA amplicon sequence analysis, there exists a growing need for protocols emphasizing alternative phylogenetic markers such as those representing eukaryotic organisms.
Here we introduce CloVR-ITS, an automated pipeline for comparative analysis of internal transcribed spacer (ITS) pyrosequences amplified from metagenomic DNA isolates and representing fungal species. This pipeline performs a variety of steps similar to those commonly used for 16S rRNA amplicon sequence analysis, including preprocessing for quality, chimera detection, clustering of sequences into operational taxonomic units (OTUs), taxonomic assignment (at class, order, family, genus, and species levels) and statistical analysis of sample groups of interest based on user-provided information. Using ITS amplicon pyrosequencing data from a previous human gastric fluid study, we demonstrate the utility of CloVR-ITS for fungal microbiota analysis and provide runtime and cost examples, including analysis of extremely large datasets on the cloud. We show that the largest fractions of reads from the stomach fluid samples were assigned to Dothideomycetes, Saccharomycetes, Agaricomycetes and Sordariomycetes but that all samples were dominated by sequences that could not be taxonomically classified. Representatives of the Candida genus were identified in all samples, most notably C. quercitrusa, while sequence reads assigned to the Aspergillus genus were only identified in a subset of samples. CloVR-ITS is made available as a pre-installed, automated, and portable software pipeline for cloud-friendly execution as part of the CloVR virtual machine package (http://clovr.org).
The CloVR-ITS pipeline provides fungal microbiota analysis that can be complementary to bacterial 16S rRNA and total metagenome sequence analysis allowing for more comprehensive studies of environmental and host-associated microbial communities.
Internal transcribed spacer (ITS); Fungal microbiota; Automated sequence analysis pipeline; Cloud computing
Xanthomonas is a large genus of bacteria that collectively cause disease on more than 300 plant species. The broad host range of the genus contrasts with stringent host and tissue specificity for individual species and pathovars. Whole-genome sequences of Xanthomonas campestris pv. raphani strain 756C and X. oryzae pv. oryzicola strain BLS256, pathogens that infect the mesophyll tissue of the leading models for plant biology, Arabidopsis thaliana and rice, respectively, were determined and provided insight into the genetic determinants of host and tissue specificity. Comparisons were made with genomes of closely related strains that infect the vascular tissue of the same hosts and across a larger collection of complete Xanthomonas genomes. The results suggest a model in which complex sets of adaptations at the level of gene content account for host specificity and subtler adaptations at the level of amino acid or noncoding regulatory nucleotide sequence determine tissue specificity.
Motivation: Analysis of multiple genomes requires sophisticated tools that provide search, visualization, interactivity and data export. Comparative genomics datasets tend to be large and complex, making development of these tools difficult. In addition to scalability, comparative genomics tools must also provide user-friendly interfaces such that the research scientist can explore complex data with minimal technical expertise.
Results: We describe a new version of the Sybil software package and its application to the important human pathogen Streptococcus pneumoniae. This new software provides a feature-rich set of comparative genomics tools for inspection of multiple genome structures, mining of orthologous gene families and identification of potential vaccine candidates.
Availability: The S.pneumoniae resource is online at http://strepneumo-sybil.igs.umaryland.edu. The software, database and website are available for download as a portable virtual machine and from http://sourceforge.net/projects/sybil.
Supplementary information: Supplementary data are available at Bioinformatics online.
The widespread popularity of genomic applications is threatened by the “bioinformatics bottleneck” resulting from uncertainty about the cost and infrastructure needed to meet increasing demands for next-generation sequence analysis. Cloud computing services have been discussed as potential new bioinformatics support systems but have not been evaluated thoroughly.
We present benchmark costs and runtimes for common microbial genomics applications, including 16S rRNA analysis, microbial whole-genome shotgun (WGS) sequence assembly and annotation, WGS metagenomics and large-scale BLAST. Sequence dataset types and sizes were selected to correspond to outputs typically generated by small- to midsize facilities equipped with 454 and Illumina platforms, except for WGS metagenomics where sampling of Illumina data was used. Automated analysis pipelines, as implemented in the CloVR virtual machine, were used in order to guarantee transparency, reproducibility and portability across different operating systems, including the commercial Amazon Elastic Compute Cloud (EC2), which was used to attach real dollar costs to each analysis type. We found considerable differences in computational requirements, runtimes and costs associated with different microbial genomics applications. While all 16S analyses completed on a single-CPU desktop in under three hours, microbial genome and metagenome analyses utilized multi-CPU support of up to 120 CPUs on Amazon EC2, where each analysis completed in under 24 hours for less than $60. Representative datasets were used to estimate maximum data throughput on different cluster sizes and to compare costs between EC2 and comparable local grid servers.
Although bioinformatics requirements for microbial genomics depend on dataset characteristics and the analysis protocols applied, our results suggests that smaller sequencing facilities (up to three Roche/454 or one Illumina GAIIx sequencer) invested in 16S rRNA amplicon sequencing, microbial single-genome and metagenomics WGS projects can achieve cost-efficient bioinformatics support using CloVR in combination with Amazon EC2 as an alternative to local computing centers.
Next-generation sequencing technologies have decentralized sequence acquisition, increasing the demand for new bioinformatics tools that are easy to use, portable across multiple platforms, and scalable for high-throughput applications. Cloud computing platforms provide on-demand access to computing infrastructure over the Internet and can be used in combination with custom built virtual machines to distribute pre-packaged with pre-configured software.
We describe the Cloud Virtual Resource, CloVR, a new desktop application for push-button automated sequence analysis that can utilize cloud computing resources. CloVR is implemented as a single portable virtual machine (VM) that provides several automated analysis pipelines for microbial genomics, including 16S, whole genome and metagenome sequence analysis. The CloVR VM runs on a personal computer, utilizes local computer resources and requires minimal installation, addressing key challenges in deploying bioinformatics workflows. In addition CloVR supports use of remote cloud computing resources to improve performance for large-scale sequence processing. In a case study, we demonstrate the use of CloVR to automatically process next-generation sequencing data on multiple cloud computing platforms.
The CloVR VM and associated architecture lowers the barrier of entry for utilizing complex analysis protocols on both local single- and multi-core computers and cloud systems for high throughput data processing.
Enterotoxigenic Escherichia coli (ETEC) is a major cause of diarrheal illness in children less than 5 years of age in low- and middle-income nations, whereas it is an emerging enteric pathogen in industrialized nations. Despite being an important cause of diarrhea, little is known about the genomic composition of ETEC. To address this, we sequenced the genomes of five ETEC isolates obtained from children in Guinea-Bissau with diarrhea. These five isolates represent distinct and globally dominant ETEC clonal groups. Comparative genomic analyses utilizing a gene-independent whole-genome alignment method demonstrated that sequenced ETEC strains share approximately 2.7 million bases of genomic sequence. Phylogenetic analysis of this “core genome” confirmed the diverse history of the ETEC pathovar and provides a finer resolution of the E. coli relationships than multilocus sequence typing. No identified genomic regions were conserved exclusively in all ETEC genomes; however, we identified more genomic content conserved among ETEC genomes than among non-ETEC E. coli genomes, suggesting that ETEC isolates share a genomic core. Comparisons of known virulence and of surface-exposed and colonization factor genes across all sequenced ETEC genomes not only identified variability but also indicated that some antigens are restricted to the ETEC pathovar. Overall, the generation of these five genome sequences, in addition to the two previously generated ETEC genomes, highlights the genomic diversity of ETEC. These studies increase our understanding of ETEC evolution, as well as provide insight into virulence factors and conserved proteins, which may be targets for vaccine development.
Rapid annotation and comparisons of genomes from multiple isolates (pan-genomes) is becoming commonplace due to advances in sequencing technology. Genome annotations can contain inconsistencies and errors that hinder comparative analysis even within a single species. Tools are needed to compare and improve annotation quality across sets of closely related genomes.
We introduce a new tool, Mugsy-Annotator, that identifies orthologs and evaluates annotation quality in prokaryotic genomes using whole genome multiple alignment. Mugsy-Annotator identifies anomalies in annotated gene structures, including inconsistently located translation initiation sites and disrupted genes due to draft genome sequencing or pseudogenes. An evaluation of species pan-genomes using the tool indicates that such anomalies are common, especially at translation initiation sites. Mugsy-Annotator reports alternate annotations that improve consistency and are candidates for further review.
Whole genome multiple alignment can be used to efficiently identify orthologs and annotation problem areas in a bacterial pan-genome. Comparisons of annotated gene structures within a species may show more variation than is actually present in the genome, indicating errors in genome annotation. Our new tool Mugsy-Annotator assists re-annotation efforts by highlighting edits that improve annotation consistency.
Motivation: The relative ease and low cost of current generation sequencing technologies has led to a dramatic increase in the number of sequenced genomes for species across the tree of life. This increasing volume of data requires tools that can quickly compare multiple whole-genome sequences, millions of base pairs in length, to aid in the study of populations, pan-genomes, and genome evolution.
Results: We present a new multiple alignment tool for whole genomes named Mugsy. Mugsy is computationally efficient and can align 31 Streptococcus pneumoniae genomes in less than 2 hours producing alignments that compare favorably to other tools. Mugsy is also the fastest program evaluated for the multiple alignment of assembled human chromosome sequences from four individuals. Mugsy does not require a reference sequence, can align mixtures of assembled draft and completed genome data, and is robust in identifying a rich complement of genetic variation including duplications, rearrangements, and large-scale gain and loss of sequence.
Availability: Mugsy is free, open-source software available from http://mugsy.sf.net.
Supplementary information: Supplementary data are available at Bioinformatics online.
Streptococcus pneumoniae is one of the most important causes of microbial diseases in humans. The genomes of 44 diverse strains of S. pneumoniae were analyzed and compared with strains of non-pathogenic streptococci of the Mitis group.
Despite evidence of extensive recombination, the S. pneumoniae phylogenetic tree revealed six major lineages. With the exception of serotype 1, the tree correlated poorly with capsular serotype, geographical site of isolation and disease outcome. The distribution of dispensable genes - genes present in more than one strain but not in all strains - was consistent with phylogeny, although horizontal gene transfer events attenuated this correlation in the case of ancient lineages. Homologous recombination, involving short stretches of DNA, was the dominant evolutionary process of the core genome of S. pneumoniae. Genetic exchange occurred both within and across the borders of the species, and S. mitis was the main reservoir of genetic diversity of S. pneumoniae. The pan-genome size of S. pneumoniae increased logarithmically with the number of strains and linearly with the number of polymorphic sites of the sampled genomes, suggesting that acquired genes accumulate proportionately to the age of clones. Most genes associated with pathogenicity were shared by all S. pneumoniae strains, but were also present in S. mitis, S. oralis and S. infantis, indicating that these genes are not sufficient to determine virulence.
Genetic exchange with related species sharing the same ecological niche is the main mechanism of evolution of S. pneumoniae. The open pan-genome guarantees the species a quick and economical response to diverse environments.
Motivation: The growth of sequence data has been accompanied by an increasing need to analyze data on distributed computer clusters. The use of these systems for routine analysis requires scalable and robust software for data management of large datasets. Software is also needed to simplify data management and make large-scale bioinformatics analysis accessible and reproducible to a wide class of target users.
Results: We have developed a workflow management system named Ergatis that enables users to build, execute and monitor pipelines for computational analysis of genomics data. Ergatis contains preconfigured components and template pipelines for a number of common bioinformatics tasks such as prokaryotic genome annotation and genome comparisons. Outputs from many of these components can be loaded into a Chado relational database. Ergatis was designed to be accessible to a broad class of users and provides a user friendly, web-based interface. Ergatis supports high-throughput batch processing on distributed compute clusters and has been used for data management in a number of genome annotation and comparative genomics projects.
Availability: Ergatis is an open-source project and is freely available at http://ergatis.sourceforge.net
The human malaria parasite Plasmodium vivax is responsible for 25-40% of the ~515 million annual cases of malaria worldwide. Although seldom fatal, the parasite elicits severe and incapacitating clinical symptoms and often relapses months after a primary infection has cleared. Despite its importance as a major human pathogen, P. vivax is little studied because it cannot be propagated in the laboratory except in non-human primates. We determined the genome sequence of P. vivax in order to shed light on its distinctive biologic features, and as a means to drive development of new drugs and vaccines. Here we describe the synteny and isochore structure of P. vivax chromosomes, and show that the parasite resembles other malaria parasites in gene content and metabolic potential, but possesses novel gene families and potential alternate invasion pathways not recognized previously. Completion of the P. vivax genome provides the scientific community with a valuable resource that can be used to advance scientific investigation into this neglected species.
Parasitic nematodes that cause elephantiasis and river blindness threaten hundreds of millions of people in the developing world. We have sequenced the ~90 megabase (Mb) genome of the human filarial parasite Brugia malayi and predict ~11,500 protein coding genes in 71 Mb of robustly assembled sequence. Comparative analysis with the free-living, model nematode Caenorhabditis elegans revealed that, despite these genes having maintained little conservation of local synteny during ~350 million years of evolution, they largely remain in linkage on chromosomal units. More than 100 conserved operons were identified. Analysis of the predicted proteome provides evidence for adaptations of B. malayi to niches in its human and vector hosts and insights into the molecular basis of a mutualistic relationship with its Wolbachia endosymbiont. These findings offer a foundation for rational drug design.
With the quantity of genomic data increasing at an exponential rate, it is imperative that these data be captured electronically, in a standard format. Standardization activities must proceed within the auspices of open-access and international working bodies. To tackle the issues surrounding the development of better descriptions of genomic investigations, we have formed the Genomic Standards Consortium (GSC). Here, we introduce the minimum information about a genome sequence (MIGS) specification with the intent of promoting participation in its development and discussing the resources that will be required to develop improved mechanisms of metadata capture and exchange. As part of its wider goals, the GSC also supports improving the ‘transparency’ of the information contained in existing genomic databases.
Many biological databases that provide comparative genomics information and tools are now available on the internet. While certainly quite useful, to our knowledge none of the existing databases combine results from multiple comparative genomics methods with manually curated information from the literature. Here we describe the Princeton Protein Orthology Database (P-POD, http://ortholog.princeton.edu), a user-friendly database system that allows users to find and visualize the phylogenetic relationships among predicted orthologs (based on the OrthoMCL method) to a query gene from any of eight eukaryotic organisms, and to see the orthologs in a wider evolutionary context (based on the Jaccard clustering method). In addition to the phylogenetic information, the database contains experimental results manually collected from the literature that can be compared to the computational analyses, as well as links to relevant human disease and gene information via the OMIM, model organism, and sequence databases. Our aim is for the P-POD resource to be extremely useful to typical experimental biologists wanting to learn more about the evolutionary context of their favorite genes. P-POD is based on the commonly used Generic Model Organism Database (GMOD) schema and can be downloaded in its entirety for installation on one's own system. Thus, bioinformaticians and software developers may also find P-POD useful because they can use the P-POD database infrastructure when developing their own comparative genomics resources and database tools.
Anaplasma (formerly Ehrlichia) phagocytophilum, Ehrlichia chaffeensis, and Neorickettsia (formerly Ehrlichia) sennetsu are intracellular vector-borne pathogens that cause human ehrlichiosis, an emerging infectious disease. We present the complete genome sequences of these organisms along with comparisons to other organisms in the Rickettsiales order. Ehrlichia spp. and Anaplasma spp. display a unique large expansion of immunodominant outer membrane proteins facilitating antigenic variation. All Rickettsiales have a diminished ability to synthesize amino acids compared to their closest free-living relatives. Unlike members of the Rickettsiaceae family, these pathogenic Anaplasmataceae are capable of making all major vitamins, cofactors, and nucleotides, which could confer a beneficial role in the invertebrate vector or the vertebrate host. Further analysis identified proteins potentially involved in vacuole confinement of the Anaplasmataceae, a life cycle involving a hematophagous vector, vertebrate pathogenesis, human pathogenesis, and lack of transovarial transmission. These discoveries provide significant insights into the biology of these obligate intracellular pathogens.
Ehrlichiosis is an acute disease that triggers flu-like symptoms in both humans and animals. It is caused by a range of bacteria transmitted by ticks or flukes. Because these bacteria are difficult to culture, however, the organisms are poorly understood. The genomes of three emerging human pathogens causing ehrlichiosis were sequenced. A database was designed to allow the comparison of these three genomes to sixteen other bacteria with similar lifestyles. Analysis from this database reveals new species-specific and disease-specific genes indicating niche adaptations, pathogenic traits, and other features. In particular, one of the organisms contains more than 100 copies of a single gene involved in interactions with the host(s). These comparisons also enabled a reconstruction of the metabolic potential of five representative genomes from these bacteria and their close relatives. With this work, scientists can study these emerging pathogens in earnest.
Staphylococcus aureus is an opportunistic pathogen and the major causative agent of numerous hospital- and community-acquired infections. Staphylococcus epidermidis has emerged as a causative agent of infections often associated with implanted medical devices. We have sequenced the ∼2.8-Mb genome of S. aureus COL, an early methicillin-resistant isolate, and the ∼2.6-Mb genome of S. epidermidis RP62a, a methicillin-resistant biofilm isolate. Comparative analysis of these and other staphylococcal genomes was used to explore the evolution of virulence and resistance between these two species. The S. aureus and S. epidermidis genomes are syntenic throughout their lengths and share a core set of 1,681 open reading frames. Genome islands in nonsyntenic regions are the primary source of variations in pathogenicity and resistance. Gene transfer between staphylococci and low-GC-content gram-positive bacteria appears to have shaped their virulence and resistance profiles. Integrated plasmids in S. epidermidis carry genes encoding resistance to cadmium and species-specific LPXTG surface proteins. A novel genome island encodes multiple phenol-soluble modulins, a potential S. epidermidis virulence factor. S. epidermidis contains the cap operon, encoding the polyglutamate capsule, a major virulence factor in Bacillus anthracis. Additional phenotypic differences are likely the result of single nucleotide polymorphisms, which are most numerous in cell envelope proteins. Overall differences in pathogenicity can be attributed to genome islands in S. aureus which encode enterotoxins, exotoxins, leukocidins, and leukotoxins not found in S. epidermidis.
The genomes of three strains of Listeria monocytogenes that have been associated with food-borne illness in the USA were subjected to whole genome comparative analysis. A total of 51, 97 and 69 strain-specific genes were identified in L.monocytogenes strains F2365 (serotype 4b, cheese isolate), F6854 (serotype 1/2a, frankfurter isolate) and H7858 (serotype 4b, meat isolate), respectively. Eighty-three genes were restricted to serotype 1/2a and 51 to serotype 4b strains. These strain- and serotype-specific genes probably contribute to observed differences in pathogenicity, and the ability of the organisms to survive and grow in their respective environmental niches. The serotype 1/2a-specific genes include an operon that encodes the rhamnose biosynthetic pathway that is associated with teichoic acid biosynthesis, as well as operons for five glycosyl transferases and an adenine-specific DNA methyltransferase. A total of 8603 and 105 050 high quality single nucleotide polymorphisms (SNPs) were found on the draft genome sequences of strain H7858 and strain F6854, respectively, when compared with strain F2365. Whole genome comparative analyses revealed that the L.monocytogenes genomes are essentially syntenic, with the majority of genomic differences consisting of phage insertions, transposable elements and SNPs.
We sequenced the complete genome of Bacillus cereus ATCC 10987, a non-lethal dairy isolate in the same genetic subgroup as Bacillus anthracis. Comparison of the chromosomes demonstrated that B.cereus ATCC 10987 was more similar to B.anthracis Ames than B.cereus ATCC 14579, while containing a number of unique metabolic capabilities such as urease and xylose utilization and lacking the ability to utilize nitrate and nitrite. Additionally, genetic mechanisms for variation of capsule carbohydrate and flagella surface structures were identified. Bacillus cereus ATCC 10987 contains a single large plasmid (pBc10987), of ∼208 kb, that is similar in gene content and organization to B.anthracis pXO1 but is lacking the pathogenicity-associated island containing the anthrax lethal and edema toxin complex genes. The chromosomal similarity of B.cereus ATCC 10987 to B.anthracis Ames, as well as the fact that it contains a large pXO1-like plasmid, may make it a possible model for studying B.anthracis plasmid biology and regulatory cross-talk.