P-217 Specific PCR Assays Using CRISPR Genes for Detection of AIEC in Fecal Samples
Bibliographic record
Abstract
Adherent-invasive Escherichia coli (AIEC) are implicated in the pathogenesis of Crohn's disease (CD). Many studies have defined pathogenic mechanisms using AIEC reference strain LF82. The phenotype for this group of bacteria includes their ability to adhere and invade intestinal epithelial cells and to survive within macrophages in vitro. Identification of individuals infected with AIEC requires phenotypic screening of cultured bacteria, a laborious and inefficient process. Loci common to and underlying the AIEC phenotype remain unknown in part because AIEC are clonally diverse and belong to distinct serotypes. The availability of specific molecular tools to detect and quantify AIEC would enable us to conduct large-scale epidemiologic studies to better understand the impact of this pathogen on CD disease severity. Our aim was to design AIEC specific genomic probes that can be applied to a non-invasive and high throughput assay. Here we present the design of gene expression assays to detect AIEC using 4 genes belonging to the clustered regularly interspaced short palindromic repeats region (CRISPR). Using BLAST, the genomes of 12 AIEC strains were compared to 10 non-pathogenic E. coli to identify genes present in the AIEC strains but not in commensals. Four genes were identified and primers were designed. Banked fecal samples stored in RNA stabilization solution were available through an IRB approved protocol at Stony Brook University. RNA was extracted from 53 fecal samples obtained from patients and from strains LF82 and MG1655. Twenty 2 subjects had inflammatory bowel diseases (IBD), including CD (n = 15), ulcerative colitis (UC) (n = 5), indeterminate colitis (n = 2), and 31 were healthy controls. Real time PCR assays were conducted using 16S rRNA as a reference, with positive results set at cycle thresholds (CT) <35. No single gene was unique to all 12 AIEC strains and absent from commensal E. coli, but genes were identified in 6 AIEC strains and absent from all non-pathogenic bacteria. The ΔCT (universal-E. coli) was lower (i.e., reflecting greater locus abundance) in IBD (−12.75) compared to control (−13.40) samples, although this difference was not statistically significant. Five CD samples, I UC sample and 2 control samples had positive CT values for 3 of the LF82 CRISPR genes. LF82 and MG1655, as expected, were positive and negative for all 4 genes. All other samples were negative for all 4 loci. Thirty three percent of CD samples were positive for LF82 CRISPR genes compared with 6.4% of controls (P = 0.029, using a Chi-square and Fisher's exact test). We identified 4 genes that are uniquely expressed in many AIEC strains. In some bacteria, CRISPR genes participate in the evasion of host recognition. PCR assays using these genomic regions can be optimized to create a non-invasive multiplex assay for detecting CD patients infected or colonized with AIEC.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".