Network


Latest external collaboration on country level. Dive into details by clicking on the dots.

Hotspot


Dive into the research topics where Rebecca E. Colman is active.

Publication


Featured researches published by Rebecca E. Colman.


Journal of Bacteriology | 2006

Effect of Repeat Copy Number on Variable-Number Tandem Repeat Mutations in Escherichia coli O157:H7

Amy J. Vogler; Christine Keys; Yoshimi Nemoto; Rebecca E. Colman; Zack J Jay; Paul Keim

Variable-number tandem repeat (VNTR) loci have shown a remarkable ability to discriminate among isolates of the recently emerged clonal pathogen Escherichia coli O157:H7, making them a very useful molecular epidemiological tool. However, little is known about the rates at which these sequences mutate, the factors that affect mutation rates, or the mechanisms by which mutations occur at these loci. Here, we measure mutation rates for 28 VNTR loci and investigate the effects of repeat copy number and mismatch repair on mutation rate using in vitro-generated populations for 10 E. coli O157:H7 strains. We find single-locus rates as high as 7.0 x 10(-4) mutations/generation and a combined 28-locus rate of 6.4 x 10(-4) mutations/generation. We observed single- and multirepeat mutations that were consistent with a slipped-strand mispairing mutation model, as well as a smaller number of large repeat copy number mutations that were consistent with recombination-mediated events. Repeat copy number within an array was strongly correlated with mutation rate both at the most mutable locus, O157-10 (r2= 0.565, P = 0.0196), and across all mutating loci. The combined locus model was significant whether locus O157-10 was included (r2= 0.833, P < 0.0001) or excluded (r2= 0.452, P < 0.0001) from the analysis. Deficient mismatch repair did not affect mutation rate at any of the 28 VNTRs with repeat unit sizes of >5 bp, although a poly(G) homomeric tract was destabilized in the mutS strain. Finally, we describe a general model for VNTR mutations that encompasses insertions and deletions, single- and multiple-repeat mutations, and their relative frequencies based upon our empirical mutation rate data.


PLOS Pathogens | 2010

Within-host evolution of Burkholderia pseudomallei in four cases of acute melioidosis.

Erin P. Price; Heidie Hornstra; Direk Limmathurotsakul; Tamara Max; Derek S. Sarovich; Amy J. Vogler; Julia L. Dale; Jennifer L. Ginther; Benjamin Leadem; Rebecca E. Colman; Jeffrey T. Foster; Apichai Tuanyok; David M. Wagner; Sharon J. Peacock; Talima Pearson; Paul Keim

Little is currently known about bacterial pathogen evolution and adaptation within the host during acute infection. Previous studies of Burkholderia pseudomallei, the etiologic agent of melioidosis, have shown that this opportunistic pathogen mutates rapidly both in vitro and in vivo at tandemly repeated loci, making this organism a relevant model for studying short-term evolution. In the current study, B. pseudomallei isolates cultured from multiple body sites from four Thai patients with disseminated melioidosis were subjected to fine-scale genotyping using multilocus variable-number tandem repeat analysis (MLVA). In order to understand and model the in vivo variable-number tandem repeat (VNTR) mutational process, we characterized the patterns and rates of mutations in vitro through parallel serial passage experiments of B. pseudomallei. Despite the short period of infection, substantial divergence from the putative founder genotype was observed in all four melioidosis cases. This study presents a paradigm for examining bacterial evolution over the short timescale of an acute infection. Further studies are required to determine whether the mutational process leads to phenotypic alterations that impact upon bacterial fitness in vivo. Our findings have important implications for future sampling strategies, since colonies in a single clinical sample may be genetically heterogeneous, and organisms in a culture taken late in the infective process may have undergone considerable genetic change compared with the founder inoculum.


Frontiers in Genetics | 2015

Best Practices for Evaluating Single Nucleotide Variant Calling Methods for Microbial Genomics

Nathanael D. Olson; Steven P. Lund; Rebecca E. Colman; Jeffery T. Foster; Jason W. Sahl; James M. Schupp; Paul Keim; Jayne B. Morrow; Marc L. Salit; Justin M. Zook

Innovations in sequencing technologies have allowed biologists to make incredible advances in understanding biological systems. As experience grows, researchers increasingly recognize that analyzing the wealth of data provided by these new sequencing platforms requires careful attention to detail for robust results. Thus far, much of the scientific Communit’s focus for use in bacterial genomics has been on evaluating genome assembly algorithms and rigorously validating assembly program performance. Missing, however, is a focus on critical evaluation of variant callers for these genomes. Variant calling is essential for comparative genomics as it yields insights into nucleotide-level organismal differences. Variant calling is a multistep process with a host of potential error sources that may lead to incorrect variant calls. Identifying and resolving these incorrect calls is critical for bacterial genomics to advance. The goal of this review is to provide guidance on validating algorithms and pipelines used in variant calling for bacterial genomics. First, we will provide an overview of the variant calling procedures and the potential sources of error associated with the methods. We will then identify appropriate datasets for use in evaluating algorithms and describe statistical methods for evaluating algorithm performance. As variant calling moves from basic research to the applied setting, standardized methods for performance evaluation and reporting are required; it is our hope that this review provides the groundwork for the development of these standards.


PLOS ONE | 2012

Whole genome sequence typing to investigate the Apophysomyces outbreak following a tornado in Joplin, Missouri, 2011.

Kizee A. Etienne; John D. Gillece; Remy Hilsabeck; Jim M. Schupp; Rebecca E. Colman; Shawn R. Lockhart; Lalitha Gade; Elizabeth H. Thompson; Deanna A. Sutton; Robyn Neblett-Fanfair; Benjamin J. Park; George Turabelidze; Paul Keim; Mary E. Brandt; Eszter Deak; David M. Engelthaler

Case reports of Apophysomyces spp. in immunocompetent hosts have been a result of traumatic deep implantation of Apophysomyces spp. spore-contaminated soil or debris. On May 22, 2011 a tornado occurred in Joplin, MO, leaving 13 tornado victims with Apophysomyces trapeziformis infections as a result of lacerations from airborne material. We used whole genome sequence typing (WGST) for high-resolution phylogenetic SNP analysis of 17 outbreak Apophysomyces isolates and five additional temporally and spatially diverse Apophysomyces control isolates (three A. trapeziformis and two A. variabilis isolates). Whole genome SNP phylogenetic analysis revealed three clusters of genotypically related or identical A. trapeziformis isolates and multiple distinct isolates among the Joplin group; this indicated multiple genotypes from a single or multiple sources. Though no linkage between genotype and location of exposure was observed, WGST analysis determined that the Joplin isolates were more closely related to each other than to the control isolates, suggesting local population structure. Additionally, species delineation based on WGST demonstrated the need to reassess currently accepted taxonomic classifications of phylogenetic species within the genus Apophysomyces.


PLOS ONE | 2015

Detection of Low-Level Mixed-Population Drug Resistance in Mycobacterium tuberculosis Using High Fidelity Amplicon Sequencing.

Rebecca E. Colman; James M. Schupp; Nathan D. Hicks; David Smith; Jordan L. Buchhagen; Faramarz Valafar; Valeriu Crudu; Elena Romancenco; Ecaterina Noroc; Lynn Jackson; Donald G. Catanzaro; Timothy C. Rodwell; Antonino Catanzaro; Paul Keim; David M. Engelthaler

Undetected and untreated, low-levels of drug resistant (DR) subpopulations in clinical Mycobacterium tuberculosis (Mtb) infections may lead to development of DR-tuberculosis, potentially resulting in treatment failure. Current phenotypic DR susceptibility testing has a theoretical potential for 1% sensitivity, is not quantitative, and requires several weeks to complete. The use of “single molecule-overlapping reads” (SMOR) analysis with next generation DNA sequencing for determination of ultra-rare target alleles in complex mixtures provides increased sensitivity over standard DNA sequencing. Ligation free amplicon sequencing with SMOR analysis enables the detection of resistant allele subpopulations at ≥0.1% of the total Mtb population in near real-time analysis. We describe the method using standardized mixtures of DNA from resistant and susceptible Mtb isolates and the assay’s performance for detecting ultra-rare DR subpopulations in DNA extracted directly from clinical sputum samples. SMOR analysis enables rapid near real-time detection and tracking of previously undetectable DR sub-populations in clinical samples allowing for the evaluation of the clinical relevance of low-level DR subpopulations. This will provide insights into interventions aimed at suppressing minor DR subpopulations before they become clinically significant.


Emerging Infectious Diseases | 2009

Fine-scale Identification of the Most Likely Source of a Human Plague Infection

Rebecca E. Colman; Amy J. Vogler; Jennifer L. Lowell; Kenneth L. Gage; Christina Morway; Pamela J. Reynolds; Paul Ettestad; Paul Keim; Michael Y. Kosoy; David M. Wagner

We describe an analytic approach to provide fine-scale discrimination among multiple infection source hypotheses. This approach uses mutation-rate data for rapidly evolving multiple locus variable-number tandem repeat loci in probabilistic models to identify the most likely source. We illustrate the utility of this approach using data from a North American human plague investigation.


Journal of Clinical Microbiology | 2012

Comparison of TaqMan PCR Assays for Detection of the Melioidosis Agent Burkholderia pseudomallei in Clinical Specimens

Mirjam Kaestli; Leisha J. Richardson; Rebecca E. Colman; Apichai Tuanyok; Erin P. Price; Jolene Bowers; Mark Mayo; Erin Kelley; Meagan L. Seymour; Derek S. Sarovich; Talima Pearson; David M. Engelthaler; David M. Wagner; Paul Keim; James M. Schupp; Bart J. Currie

ABSTRACT Melioidosis is an emerging infectious disease caused by the soil bacterium Burkholderia pseudomallei. In diagnostic and forensic settings, molecular detection assays need not only high sensitivity with low limits of detection but also high specificity. In a direct comparison of published and newly developed TaqMan PCR assays, we found the TTS1-orf2 assay to be superior in detecting B. pseudomallei directly from clinical specimens. The YLF/BTFC multiplex assay (targeting the Yersinia-like fimbrial/Burkholderia thailandensis-like flagellum and chemotaxis region) also showed high diagnostic sensitivity and provides additional information on possible geographic origin.


Genome Medicine | 2015

Phylogenetically typing bacterial strains from partial SNP genotypes observed from direct sequencing of clinical specimen metagenomic data

Jason W. Sahl; James M. Schupp; David A. Rasko; Rebecca E. Colman; Jeffrey T. Foster; Paul Keim

We describe an approach for genotyping bacterial strains from low coverage genome datasets, including metagenomic data from complex samples. Sequence reads from unknown samples are aligned to a reference genome where the allele states of known SNPs are determined. The Whole Genome Focused Array SNP Typing (WG-FAST) pipeline can identify unknown strains with much less read data than is needed for genome assembly. To test WG-FAST, we resampled SNPs from real samples to understand the relationship between low coverage metagenomic data and accurate phylogenetic placement. WG-FAST can be downloaded from https://github.com/jasonsahl/wgfast.


Journal of Clinical Microbiology | 2016

Rapid Drug Susceptibility Testing of Drug-Resistant Mycobacterium tuberculosis Isolates Directly from Clinical Samples by Use of Amplicon Sequencing: a Proof-of-Concept Study

Rebecca E. Colman; Julia Anderson; Darrin Lemmer; Erik Lehmkuhl; Sophia B. Georghiou; Hannah Heaton; Kristin Wiggins; John D. Gillece; James M. Schupp; Donald G. Catanzaro; Valeriu Crudu; Ted Cohen; Timothy C. Rodwell; David M. Engelthaler

ABSTRACT Increasingly complex drug-resistant tuberculosis (DR-TB) is a major global health concern and one of the primary reasons why TB is now the leading infectious cause of death worldwide. Rapid characterization of a DR-TB patients complete drug resistance profile would facilitate individualized treatment in place of empirical treatment, improve treatment outcomes, prevent amplification of resistance, and reduce the transmission of DR-TB. The use of targeted next-generation sequencing (NGS) to obtain drug resistance profiles directly from patient sputum samples has the potential to enable comprehensive evidence-based treatment plans to be implemented quickly, rather than in weeks to months, which is currently needed for phenotypic drug susceptibility testing (DST) results. In this pilot study, we evaluated the performance of amplicon sequencing of Mycobacterium tuberculosis DNA from patient sputum samples using a tabletop NGS technology and automated data analysis to provide a rapid DST solution (the Next Gen-RDST assay). One hundred sixty-six out of 176 (94.3%) sputum samples from the Republic of Moldova yielded complete Next Gen-RDST assay profiles for 7 drugs of interest. We found a high level of concordance of our Next Gen-RDST assay results with phenotypic DST (97.0%) and pyrosequencing (97.8%) results from the same clinical samples. Our Next Gen-RDST assay was also able to estimate the proportion of resistant-to-wild-type alleles down to mixtures of ≤1%, which demonstrates the ability to detect very low levels of resistant variants not detected by pyrosequencing and possibly below the threshold for phenotypic growth methods. The assay as described here could be used as a clinical or surveillance tool.


Scientific Reports | 2015

Phylogenetic and genomic diversity in isolates from the globally distributed Acinetobacter baumannii ST25 lineage

Jason W. Sahl; Mariateresa Del Franco; Spyros Pournaras; Rebecca E. Colman; Nabil Karah; Lenie Dijkshoorn; Raffaele Zarrilli

Acinetobacter baumannii is a globally distributed nosocomial pathogen that has gained interest due to its resistance to most currently used antimicrobials. Whole genome sequencing (WGS) and phylogenetics has begun to reveal the global genetic diversity of this pathogen. The evolution of A. baumannii has largely been defined by recombination, punctuated by the emergence and proliferation of defined clonal lineages. In this study we sequenced seven genomes from the sequence type (ST)25 lineage and compared them to 12 ST25 genomes deposited in public databases. A recombination analysis identified multiple genomic regions that are homoplasious in the ST25 phylogeny, indicating active or historical recombination. Genes associated with antimicrobial resistance were differentially distributed between ST25 genomes, which matched our laboratory-based antimicrobial susceptibility typing. Differences were also observed in biofilm formation between ST25 isolates, which were demonstrated to produce significantly more extensive biofilm than an isolate from the ST1 clonal lineage. These results demonstrate that within A. baumannii, even a fairly recently derived monophyletic lineage can still exhibit significant genotypic and phenotypic diversity. These results have implications for associating outbreaks with sequence typing as well as understanding mechanisms behind the global propagation of successful A. baumannii lineages.

Collaboration


Dive into the Rebecca E. Colman's collaboration.

Top Co-Authors

Avatar

James M. Schupp

Translational Genomics Research Institute

View shared research outputs
Top Co-Authors

Avatar

David M. Engelthaler

Translational Genomics Research Institute

View shared research outputs
Top Co-Authors

Avatar

Derek S. Sarovich

University of the Sunshine Coast

View shared research outputs
Top Co-Authors

Avatar

Bart J. Currie

Queensland University of Technology

View shared research outputs
Top Co-Authors

Avatar

Erin P. Price

University of the Sunshine Coast

View shared research outputs
Top Co-Authors

Avatar

Darrin Lemmer

Translational Genomics Research Institute

View shared research outputs
Top Co-Authors

Avatar
Top Co-Authors

Avatar

John D. Gillece

Translational Genomics Research Institute

View shared research outputs
Top Co-Authors

Avatar
Top Co-Authors

Avatar

Mark Mayo

Charles Darwin University

View shared research outputs
Researchain Logo
Decentralizing Knowledge