Metastatic Colorectal Cancer Treatment Response Evaluation by Ultra-Deep Sequencing of Cell-Free DNA and Matched White Blood Cells.

PURPOSE: Circulating tumor DNA (ctDNA) has the potential to guide therapy selection and monitor treatment response in patients with metastatic cancer. However, germline and clonal hematopoiesis-associated alterations can confound identification of tumor-specific mutations in cell-free DNA (cfDNA), often requiring additional sequencing of tumor tissue. The current study assessed whether ctDNA-based treatment response monitoring could be performed in a tumor tissue-independent manner by combining ultra-deep targeted sequencing analyses of cfDNA with patient-matched white blood cell (WBC)-derived DNA. EXPERIMENTAL DESIGN: In total, 183 cfDNA and 49 WBC samples, along with 28 tissue samples, from 52 patients with metastatic colorectal cancer participating in the prospective phase III CAIRO5 clinical trial were analyzed using an ultra-deep targeted sequencing liquid biopsy assay. RESULTS: The combined cfDNA and WBC analysis prevented false-positives due to germline or hematopoietic variants in 40% of patients. Patient-matched tumor tissue sequencing did not provide additional information. Longitudinal analyses of ctDNA were more predictive of overall survival than standard-of-care radiological response evaluation. ctDNA mutations related to primary or acquired resistance to panitumumab were identified in 42% of patients. CONCLUSIONS: Accurate calling of ctDNA mutations for treatment response monitoring is feasible in a tumor tissue-independent manner by combined cfDNA and patient-matched WBC genomic DNA analysis. This tissue biopsy-independent approach simplifies sample logistics and facilitates the application of liquid biopsy ctDNA testing for evaluation of emerging therapy resistance, opening new avenues for early adaptation of treatment regimens.

Automated next-generation profiling of genomic alterations in human cancers.

The lack of validated, distributed comprehensive genomic profiling assays for patients with cancer inhibits access to precision oncology treatment. To address this, we describe elio tissue complete, which has been FDA-cleared for examination of 505 cancer-related genes. Independent analyses of clinically and biologically relevant sequence changes across 170 clinical tumor samples using MSK-IMPACT, FoundationOne, and PCR-based methods reveals a positive percent agreement of >97%. We observe high concordance with whole-exome sequencing for evaluation of tumor mutational burden for 307 solid tumors (Pearson r = 0.95) and comparison of the elio tissue complete microsatellite instability detection approach with an independent PCR assay for 223 samples displays a positive percent agreement of 99%. Finally, evaluation of amplifications and translocations against DNA- and RNA-based approaches exhibits >98% negative percent agreement and positive percent agreement of 86% and 82%, respectively. These methods provide an approach for pan-solid tumor comprehensive genomic profiling with high analytical performance.

Tumor-immune microenvironment revealed by Imaging Mass Cytometry in a metastatic sarcomatoid urothelial carcinoma with a prolonged response to pembrolizumab.

Sarcomatoid urothelial carcinoma (SUC) is a rare subtype of urothelial carcinoma (UC) that typically presents at an advanced stage compared to more common variants of UC. Locally advanced and metastatic UC have a poor long-term survival following progression on first-line platinum-based chemotherapy. Antibodies directed against the programmed cell death 1 protein (PD-1) or its ligand (PD-L1) are now approved to be used in these scenarios. The need for reliable biomarkers for treatment stratification is still under research. Here, we present a novel case report of the first Imaging Mass Cytometry (IMC) analysis done in SUC to investigate the immune cell repertoire and PD-L1 expression in a patient who presented with metastatic SUC and experienced a prolonged response to the anti-PD1 immune checkpoint inhibitor pembrolizumab after progression on first-line chemotherapy. This case report provides an important platform for translating these findings to a larger cohort of UC and UC variants.

Validation of a Circulating Tumor DNA-Based Next-Generation Sequencing Assay in a Cohort of Patients with Solid tumors: A Proposed Solution for Decentralized Plasma Testing.

BACKGROUND: Characterization of circulating tumor DNA (ctDNA) has been integrated into clinical practice. Although labs have standardized validation procedures to develop single locus tests, the efficacy of on-site plasma-based next-generation sequencing (NGS) assays still needs to be proved. MATERIALS AND METHODS: In this retrospective study, we profiled DNA from matched tissue and plasma samples from 75 patients with cancer. We applied an NGS test that detects clinically relevant alterations in 33 genes and microsatellite instability (MSI) to analyze plasma cell-free DNA (cfDNA). RESULTS: The concordance between alterations detected in both tissue and plasma samples was higher in patients with metastatic disease. The NGS test detected 77% of sequence alterations, amplifications, and fusions that were found in metastatic samples compared with 45% of those alterations found in the primary tumor samples (p = .00005). There was 87% agreement on MSI status between the NGS test and tumor tissue results. In three patients, MSI-high ctDNA correlated with response to immunotherapy. In addition, the NGS test revealed an FGFR2 amplification that was not detected in tumor tissue from a patient with metastatic gastric cancer, emphasizing the importance of profiling plasma samples in patients with advanced cancer. CONCLUSION: Our validation experience of a plasma-based NGS assay advances current knowledge about translating cfDNA testing into clinical practice and supports the application of plasma assays in the management of oncology patients with metastatic disease. With an in-house method that minimizes the need for invasive procedures, on-site cfDNA testing supplements tissue biopsy to guide precision therapy and is entitled to become a routine practice. IMPLICATIONS FOR PRACTICE: This study proposes a solution for decentralized liquid biopsy testing based on validation of a next-generation sequencing (NGS) test that detects four classes of genomic alterations in blood: sequence mutations (single nucleotide substitutions or insertions and deletions), fusions, amplifications, and microsatellite instability (MSI). Although there are reference labs that perform single-site comprehensive liquid biopsy testing, the targeted assay this study validated can be established locally in any lab with capacity to offer clinical molecular pathology assays. To the authors' knowledge, this is the first report that validates evaluating an on-site plasma-based NGS test that detects the MSI status along with common sequence alterations encountered in solid tumors.

Next-Generation Sequencing Concordance Analysis of Comprehensive Solid Tumor Profiling between a Centralized Specialty Laboratory and the Decentralized Personal Genome Diagnostics elio Tissue Complete Kitted Solution.

Genomic tumor profiling by next-generation sequencing (NGS) allows for large-scale tumor testing to inform targeted cancer therapies and immunotherapies, and to identify patients for clinical trials. These tests are often underutilized in patients with late-stage solid tumors and are typically performed in centralized specialty laboratories, thereby limiting access to these complex tests. Personal Genome Diagnostics Inc., elio tissue complete NGS solution is a comprehensive DNA-to-report kitted assay and bioinformatics solution. Comparison of 147 unique specimens from >20 tumor types was performed using the elio tissue complete solution and Foundation Medicine's FoundationOne test, which is of similar size and gene content. The analytical performance of all genomic variant types was evaluated. In general, the overall mutational profile is highly concordant between the two assays, with agreement in sequence variants reported between panels demonstrating >95% positive percentage agreement for single-nucleotide variants and insertions/deletions in clinically actionable genes. Both copy number alterations and gene translocations showed 80% to 83% positive percentage agreement, whereas tumor mutation burden and microsatellite status showed a high level of concordance across a range of mutation loads and tumor types. The Personal Genome Diagnostics Inc., elio tissue complete assay is comparable to the FoundationOne test and will allow more laboratories to offer a diagnostic NGS assay in house, which will ultimately reduce time to result and increase the number of patients receiving molecular genomic profiling and personalized treatment.

A machine learning approach for somatic mutation discovery.

Variability in the accuracy of somatic mutation detection may affect the discovery of alterations and the therapeutic management of cancer patients. To address this issue, we developed a somatic mutation discovery approach based on machine learning that outperformed existing methods in identifying experimentally validated tumor alterations (sensitivity of 97% versus 90 to 99%; positive predictive value of 98% versus 34 to 92%). Analysis of paired tumor-normal exome data from 1368 TCGA (The Cancer Genome Atlas) samples using this method revealed concordance for 74% of mutation calls but also identified likely false-positive and false-negative changes in TCGA data, including in clinically actionable genes. Determination of high-quality somatic mutation calls improved tumor mutation load-based predictions of clinical outcome for melanoma and lung cancer patients previously treated with immune checkpoint inhibitors. Integration of high-quality machine learning mutation detection in clinical next-generation sequencing (NGS) analyses increased the accuracy of test results compared to other clinical sequencing analyses. These analyses provide an approach for improved identification of tumor-specific mutations and have important implications for research and clinical management of cancer patients.

CloVR-Comparative: automated, cloud-enabled comparative microbial genome sequence analysis pipeline.

BACKGROUND: The benefit of increasing genomic sequence data to the scientific community depends on easy-to-use, scalable bioinformatics support. CloVR-Comparative combines commonly used bioinformatics tools into an intuitive, automated, and cloud-enabled analysis pipeline for comparative microbial genomics. RESULTS: CloVR-Comparative runs on annotated complete or draft genome sequences that are uploaded by the user or selected via a taxonomic tree-based user interface and downloaded from NCBI. CloVR-Comparative runs reference-free multiple whole-genome alignments to determine unique, shared and core coding sequences (CDSs) and single nucleotide polymorphisms (SNPs). Output includes short summary reports and detailed text-based results files, graphical visualizations (phylogenetic trees, circular figures), and a database file linked to the Sybil comparative genome browser. Data up- and download, pipeline configuration and monitoring, and access to Sybil are managed through CloVR-Comparative web interface. CloVR-Comparative and Sybil are distributed as part of the CloVR virtual appliance, which runs on local computers or the Amazon EC2 cloud. Representative datasets (e.g. 40 draft and complete Escherichia coli genomes) are processed in <36 h on a local desktop or at a cost of <$20 on EC2. CONCLUSIONS: CloVR-Comparative allows anybody with Internet access to run comparative genomics projects, while eliminating the need for on-site computational resources and expertise.

Personalized genomic analyses for cancer mutation discovery and interpretation.

Massively parallel sequencing approaches are beginning to be used clinically to characterize individual patient tumors and to select therapies based on the identified mutations. A major question in these analyses is the extent to which these methods identify clinically actionable alterations and whether the examination of the tumor tissue alone is sufficient or whether matched normal DNA should also be analyzed to accurately identify tumor-specific (somatic) alterations. To address these issues, we comprehensively evaluated 815 tumor-normal paired samples from patients of 15 tumor types. We identified genomic alterations using next-generation sequencing of whole exomes or 111 targeted genes that were validated with sensitivities >95% and >99%, respectively, and specificities >99.99%. These analyses revealed an average of 140 and 4.3 somatic mutations per exome and targeted analysis, respectively. More than 75% of cases had somatic alterations in genes associated with known therapies or current clinical trials. Analyses of matched normal DNA identified germline alterations in cancer-predisposing genes in 3% of patients with apparently sporadic cancers. In contrast, a tumor-only sequencing approach could not definitively identify germline changes in cancer-predisposing genes and led to additional false-positive findings comprising 31% and 65% of alterations identified in targeted and exome analyses, respectively, including in potentially actionable genes. These data suggest that matched tumor-normal sequencing analyses are essential for precise identification and interpretation of somatic and germline alterations and have important implications for the diagnostic and therapeutic management of cancer patients.

Notch1 mutations are drivers of oral tumorigenesis.

Disruption of NOTCH1 signaling was recently discovered in head and neck cancer. This study aims to evaluate NOTCH1 alterations in the progression of oral squamous cell carcinoma (OSCC) and compare the occurrence of these mutations in Chinese and Caucasian populations. We used a high-throughput PCR-based enrichment technology and next-generation sequencing (NGS) to sequence NOTCH1 in 144 samples collected in China. Forty-nine samples were normal oral mucosa from patients undergoing oral surgery, 45 were oral leukoplakia biopsies, and 50 were chemoradiation-naïve OSCC samples with 22 paired-normal tissues from the adjacent unaffected areas. NOTCH1 mutations were found in 54% of primary OSCC and 60% of premalignant lesions. Importantly, almost 60% of patients with leukoplakia with mutated NOTCH1 carried mutations that were also identified in OSCC, indicating an important role of these clonal events in the progression of early neoplasms. We then compared all known NOTCH1 mutations identified in Chinese patients with OSCC with those reported in Caucasians to date. Although we found obvious overlaps in critical regulatory NOTCH1 domains alterations and identified specific mutations shared by both groups, possible gain-of-function mutations were predominantly seen in Chinese population. Our findings demonstrate that premalignant lesions display NOTCH1 mutations at an early stage and are thus bona fide drivers of OSCC progression. Moreover, our results reveal that NOTCH1 promotes distinct tumorigenic mechanisms in patients from different ethnical populations.

Genomic analyses of gynaecologic carcinosarcomas reveal frequent mutations in chromatin remodelling genes.

Malignant mixed Müllerian tumours, also known as carcinosarcomas, are rare tumours of gynaecological origin. Here we perform whole-exome analyses of 22 tumours using massively parallel sequencing to determine the mutational landscape of this tumour type. On average, we identify 43 mutations per tumour, excluding four cases with a mutator phenotype that harboured inactivating mutations in mismatch repair genes. In addition to mutations in TP53 and KRAS, we identify genetic alterations in chromatin remodelling genes, ARID1A and ARID1B, in histone methyltransferase MLL3, in histone deacetylase modifier SPOP and in chromatin assembly factor BAZ1A, in nearly two thirds of cases. Alterations in genes with potential clinical utility are observed in more than three quarters of the cases and included members of the PI3-kinase and homologous DNA repair pathways. These findings highlight the importance of the dysregulation of chromatin remodelling in carcinosarcoma tumorigenesis and suggest new avenues for personalized therapy.

Integrated next-generation sequencing and avatar mouse models for personalized cancer treatment.

BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSION: 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.

CloVR-ITS: Automated internal transcribed spacer amplicon sequence analysis pipeline for the characterization of fungal microbiota.

BACKGROUND: 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. RESULTS: 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). CONCLUSION: 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.

Using Sybil for interactive comparative genomics of microbes on the web.

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.

Resources and costs for microbial sequence analysis evaluated using virtual machines and cloud computing.

BACKGROUND: 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. RESULTS: 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. CONCLUSIONS: 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.

CloVR: a virtual machine for automated and portable sequence analysis from the desktop using cloud computing.

BACKGROUND: 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. RESULTS: 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. CONCLUSION: 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.

Two new complete genome sequences offer insight into host and tissue specificity of plant pathogenic Xanthomonas spp.

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.

Improving pan-genome annotation using whole genome multiple alignment.

BACKGROUND: 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. RESULTS: 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. CONCLUSIONS: 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.

Neisseria meningitidis is structured in clades associated with restriction modification systems that modulate homologous recombination.

Molecular data on a limited number of chromosomal loci have shown that the population of Neisseria meningitidis (Nm), a deadly human pathogen, is structured in distinct lineages. Given that the Nm population undergoes substantial recombination, the mechanisms resulting in the evolution of these lineages, their persistence in time, and the implications for the pathogenicity of the bacterium are not yet completely understood. Based on whole-genome sequencing, we show that Nm is structured in phylogenetic clades. Through acquisition of specific genes and through insertions and rearrangements, each clade has acquired and remodeled specific genomic tracts, with the potential to impact on the commensal and virulence behavior of Nm. Despite this clear evidence of a structured population, we confirm high rates of detectable recombination throughout the whole Nm chromosome. However, gene conversion events were found to be longer within clades than between clades, suggesting a DNA cleavage mechanism associated with the phylogeny of the species. We identify 22 restriction modification systems, probably acquired by horizontal gene transfer from outside of the species/genus, whose distribution in the different strains coincides with the phylogenetic clade structure. We provide evidence that these clade-associated restriction modification systems generate a differential barrier to DNA exchange consistent with the observed population structure. These findings have general implications for the emergence of lineage structure and virulence in recombining bacterial populations, and they could provide an evolutionary framework for the population biology of a number of other bacterial species that show contradictory population structure and dynamics.

A comparative genomic analysis of diverse clonal types of enterotoxigenic Escherichia coli reveals pathovar-specific conservation.

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.