Molecular Approaches in the Diagnosis of Diarrhoeal Disease in Children from Rural Gambia
Bibliographic record
Abstract
Enteroaggregative Escherichia coli (EAEC) is a genetically diverse enteric pathogen that causes growth faltering among children, acute and chronic diarrhoea among children and adults living in both industrialised and low income countries. The German outbreak of EAEC-Shiga-toxin-E. coli in 2011 resulted in over 4000 confirmed cases of diarrhoea with over 54 fatalities in 14 European countries as well as United State of America and Canada. Several studies conducted in sub-Sahara Africa (SSA), Latin America and Asia countries have identified EAEC more frequently than any other bacterial pathogens. In SSA, case fatality due to EAEC is not well documented but the morbidity rate particularly among younger children is huge. Studies conducted in Senegal, Central-Africa-Republic and Tanzania showed that EAEC were endemic among HIV-positive patients with diarrhoea. Few studies from SSA have reported distribution of antimicrobial resistance pattern of EAEC. The Global Enteric Multisite Study (GEMS), a three-year case-control study conducted in seven African and Asia countries, showed that the prevalence of EAEC was higher among children with no diarrhoea (463/741, 62.5%) compared to children with diarrhoea (278/741, 37.5%). The aim of this retrospective analytical study nested to GEMS is to explore other molecular approaches that identify infectious EAEC and to show the genetic diversity and antimicrobial resistant pattern of EAEC. Study design of the first approach involves unmatched case-control 428 (157 cases and 271 controls) EAEC isolates that were examined by polymerase chain reaction (PCR) for the presence of 21 common EAEC virulence genes. This investigation implicated plasmid-encoded toxin (pet), AAF/1 fimbrial subunit (aggA) and hexosyltransferase homolog (capU) to be associated with diarrhoea in infants. In addition, two other virulence genes; Shigella exracellular protease A (sepA) and EAEC-heat-stable enterotoxin 1 (EAST1) were implicated in the EAEC that cause diarrhoea among children under 5 years old. The second approach utilised qualitative PCR (TaqMan-qPCR) method to assess the use of bacterial load diagnostic tool to diagnose infectious EAEC on selected matched case-control 160 (80 cases and 80 controls) EAEC isolates. Two biomarker genes, aatA and aaiC were the target in this study and both resulted in higher rate of higher bacterial load in controls (58/80 [72.5%]) compared to cases 48/80 [60%]), p – value 0.096. The third approach explored bacterial biofilm formation to diagnose infectious EAEC on 400 unmatched cases (150) and controls (250) EAEC isolates. Infectious EAEC produces biofilm to consolidate its colonisation in the host and damage to the tissue. The result of this study showed higher proportion of biofilm-producing EAEC in controls (61%) compared to cases (39%). However, biofilm-producing EAEC isolates that has aggR gene combined with one or all of the following virulence genes aatA, Aap, Orf3 and Orf61 revealed strong association with diarrhoea. Investigation into the antimicrobial resistant EAEC on the same 400 unmatched EAEC isolates revealed multi-drug resistant (MDR) EAEC infection as a significant problem among infants in the Gambia. MDR EAEC strains are almost equally distributed among cases and controls, and high (>71%) rate of resistant to Ampicillin, Sulphamethoxazole-trimethoprim and Tetracycline, and moderate (25%) rate of resistant to Chloramphenicol among study children. However, over ninety-four percent of the Gambia EAEC strains are susceptible to Cefotaxime, Ceftazidime, Ceftriaxone, Ciprofloxacin, Gentamicin and Amoxicillin-clavulanic acid. Additionally, result of whole genome sequencing (WGS) on 50 randomly selected EAEC isolates showed average 94% concordance of resistance genes with phenotypic disc diffusion method. This thesis provides detailed initial description and exploration of virulence genes associated with EAEC strains circulating in the rural Gambia and has revealed the likely biomarker genes to target in the diagnosis of infectious EAEC that cause diarrhoea in infant.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".