Dataset Information

Impact of compounding error on strategies for subtyping pathogenic bacteria.

ABSTRACT: Comparative-omics will identify a multitude of markers that can be used for intraspecific discrimination between strains of bacteria. It seems intuitive that with this plethora of markers we can construct higher resolution subtyping assays using discrete markers to define strain "barcodes." Unfortunately, with each new marker added to an assay, overall assay robustness declines because errors are compounded exponentially. For example, the difference in accuracy of strain classification for an assay with 60 markers will change from 99.9% to 54.7% when average probe accuracy declines from 99.999% to 99.0%. To illustrate this effect empirically, we constructed a 19 probe bead-array for subtyping Listeria monocytogenes and showed that despite seemingly reliable individual probe accuracy (>97%), our best classification results at the strain level were <75%. A more robust strategy would use as few markers as possible to achieve strain discrimination. Consequently, we developed two variable number of tandem repeat (VNTR) assays (Vibrio parahaemolyticus and L. monocytogenes) and demonstrate that these assays along with a published assay (Salmonella enterica) produce robust results when products were machine scored. The discriminatory ability with four to seven VNTR loci was comparable to pulsed-field gel electrophoresis. Passage experiments showed some instability with ca. 5% of passaged lines showing evidence for new alleles within 30 days (V. parahaemolyticus and S. enterica). Changes were limited to a single locus and allele so conservative rules can be used to determine strain matching. Most importantly, VNTRs appear robust and portable and can clearly discriminate between strains with relatively few loci thereby limiting effects of compounding error.

SUBMITTER: Call DR

PROVIDER: S-EPMC3186708 | biostudies-literature | 2008 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Impact of compounding error on strategies for subtyping pathogenic bacteria.

Call Douglas R DR Orfe Lisa L Davis Margaret A MA Lafrentz Stacey S Kang Min-Su MS

Foodborne pathogens and disease 20080801 4

Comparative-omics will identify a multitude of markers that can be used for intraspecific discrimination between strains of bacteria. It seems intuitive that with this plethora of markers we can construct higher resolution subtyping assays using discrete markers to define strain "barcodes." Unfortunately, with each new marker added to an assay, overall assay robustness declines because errors are compounded exponentially. For example, the difference in accuracy of strain classification for an as ...[more]

PMID: 18713065

Similar Datasets

Project description:The ability to differentiate bacteria beyond the species level is essential for identifying and tracking infectious disease outbreaks and to improve our knowledge of the population genetics, epidemiology, and ecology of bacterial pathogens. Commonly used subtyping methods, such as serotyping, phage typing, ribotyping, and pulsed-field gel electrophoresis, can yield ambiguous results that are difficult to standardize and share among laboratories. DNA sequence-based subtyping strategies can reduce interpretation ambiguity. We report the development of a rational approach for designing sequence-based subtyping methods. Listeria monocytogenes was selected as the model organism for testing the efficacy of this approach. Two housekeeping genes (recA and prs), one stress response gene (sigB), two virulence genes (actA and inlA), and two intergenic regions (hly-mpl and plcA-hly) were sequenced for 15 L. monocytogenes isolates. Isolates were chosen from a representative collection of more than 1,000 L. monocytogenes isolates to reflect the genetic diversity of this species. DNA sequences were aligned, and sliding window analyses were performed for each gene to define 600-bp-long regions that were (i) most polymorphic (using ProSeq) or (ii) most discriminatory (using a new algorithm implemented in WINDOWMIN). Complete gene sequences for actA (1,929 bp) and inlA (2,235 bp) provided the highest discrimination (identifying 15 and 14 allelic types, respectively). WINDOWMIN allowed identification of 600-bp regions within these genes that provided similar discriminatory power (yielding 15 and 13 allelic types, respectively). The most discriminatory 600-bp fragments identified in the housekeeping and stress response genes differentiated the isolates into 8 to 10 subtypes; intergenic region sequences yielded 8 and 12 allelic types based on 335- and 242-bp sequences for hly-mpl and plcA-hly, respectively. Regions identified as most polymorphic were not necessarily most discriminatory; therefore, application of the WINDOWMIN algorithm provided a powerful tool for determining the best target regions for DNA sequence-based subtyping. Our specific results also show that inclusion of virulence gene target sequences in a DNA sequence-based subtyping scheme for L. monocytogenes is necessary to achieve maximum subtype differentiation.

Project description:Pancreatic ductal adenocarcinoma is a highly lethal malignancy, which has now become the seventh most common cause of cancer death in the world, with the highest mortality rates in Europe and North America. In the past 30 years, there has been some progress in 5-year survival (rates increasing from 2.5 to 10%), but this is still extremely poor compared to all other common cancer types. Targeted therapies for advanced pancreatic cancer based on actionable mutations have been disappointing, with only 3-5% showing even a short clinical benefit. There is, however, a molecular diversity beyond mutations in genes responsible for producing classical canonical signaling pathways. Pancreatic cancer is almost unique in promoting an excess production of other components of the stroma, resulting in a complex tumor microenvironment that contributes to tumor development, progression, and response to treatment. Various transcriptional subtypes have also been described. Most notably, there is a strong alignment between the Classical/Pancreatic progenitor and Quasi-mesenchymal/Basal-like/Squamous subtype signatures of Moffit, Collinson, Bailey, Puleo, and Chan-Seng-Yue, which have potential clinical impact. Sequencing of epithelial cell populations enriched by laser capture microscopy combined with single-cell RNA sequencing has revealed the potential genomic evolution of pancreatic cancer as being a consequence of a gene expression continuum from mixed Basal-like and Classical cell populations within the same tumor, linked to allelic imbalances in mutant KRAS, with metastatic tumors being more copy number-unstable compared to primary tumors. The Basal-like subtype appears more chemoresistant with reduced survival compared to the Classical subtype. Chemotherapy and/or chemoradiation will also enrich the Basal-like subtype. Squamous/Basal-like programs facilitate immune infiltration compared with the Classical-like programs. The immune infiltrates associated with Basal and Classical type cells are distinct, potentially opening the door to differential strategies. Single-cell and spatial transcriptomics will now allow single cell profiling of tumor and resident immune cell populations that may further advance subtyping. Multiple clinical trials have been launched based on transcriptomic response signatures and molecular subtyping including COMPASS, Precision Promise, ESPAC6/7, PREDICT-PACA, and PASS1. We review several approaches to explore the clinical relevance of molecular profiling to provide optimal bench-to-beside translation with clinical impact.

Dataset Information

Impact of compounding error on strategies for subtyping pathogenic bacteria.

Publications

Impact of compounding error on strategies for subtyping pathogenic bacteria.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets