METHODS: This study enumerated the abundance of E. coli in the water and sediment at five urban lakes in the Kuala Lumpur-Petaling Jaya area, state of Selangor, Malaysia. We developed a novel method for measuring habitat transition rate of sediment E. coli to the water column, and evaluated the effects of habitat transition on E. coli abundance in the water column after accounting for its decay in the water column.
RESULTS: The abundance of E. coli in the sediment ranged from below detection to 12,000 cfu g-1, and was about one order higher than in the water column (1 to 2,300 cfu mL-1). The habitat transition rates ranged from 0.03 to 0.41 h-1. In contrast, the E. coli decay rates ranged from 0.02 to 0.16 h-1. In most cases (>80%), the habitat transition rates were higher than the decay rates in our study.
DISCUSSION: Our study provided a possible explanation for the persistence of E. coli in tropical lakes. To the best of our knowledge, this is the first quantitative study on habitat transition of E. coli from sediments to water column.
METHODS: RNA was isolated from peripheral whole blood samples (2 x 10 ml) collected from NPC patients/controls (EDTA vacutainer). Gene expression patterns from 99 samples (66 NPC; 33 controls) were assessed using the Affymetrix array. We also collected expression data from 447 patients with other cancers (201 patients) and non-cancer conditions (246 patients). Multivariate logistic regression analysis was used to obtain biomarker signatures differentiating NPC samples from controls and other diseases. Differences were also analysed within a subset (n=28) of a pre-intervention case cohort of patients whom we followed post-treatment.
RESULTS: A blood-based gene expression signature composed of three genes - LDLRAP1, PHF20, and LUC7L3 - is able to differentiate NPC from various other diseases and from unaffected controls with significant accuracy (area under the receiver operating characteristic curve of over 0.90). By subdividing our NPC cohort according to the degree of patient response to treatment we have been able to identify a blood gene signature that may be able to guide the selection of treatment.
CONCLUSION: We have identified a blood-based gene signature that accurately distinguished NPC patients from controls and from patients with other diseases. The genes in the signature, LDLRAP1, PHF20, and LUC7L3, are known to be involved in carcinoma of the head and neck, tumour-associated antigens, and/or cellular signalling. We have also identified blood-based biomarkers that are (potentially) able to predict those patients who are more likely to respond to treatment for NPC. These findings have significant clinical implications for optimizing NPC therapy.