Endotoxin as a Marker for Water Quality.

BACKGROUND: Water quality testing is vital to protect human health. Current testing relies mainly on culture-based detection of faecal indicator organisms such as Escherichia coli (E.coli). However, bacterial cultures are a slow process, taking 24-48 h and requiring specialised laboratories and trained personnel. Access to such laboratories is often sparse in developing countries and there are many fatalities deriving from poor water quality. Endotoxin is a molecular component of Gram-negative bacterial cell walls and can be used to detect their presence in drinking water. METHOD: The current study used a novel assay (BacterisK) to rapidly detect endotoxin in various water samples and correlate the results with E. coli content measured by culture methods. The data generated by the BacterisK assay are presented as an 'endotoxin risk' (ER). RESULTS: The ER values correlate with E. coli and thus endotoxin can be used as a marker of faecal contamination in water. Moreover, the BacterisK assay provides data in near real-time and can be used in situ allowing water quality testing at different spatial and temporal locations. CONCLUSION: We suggest that BacterisK can be used as a convenient risk assessment tool to assess water quality where results are required quickly or access to laboratories is lacking.

A Label-Free DNA-Immunosensor Based on Aminated rGO Electrode for the Quantification of DNA Methylation.

In this work, we developed a sandwich DNA-immunosensor for quantification of the methylated tumour suppressor gene O-6-methylguanine-DNA methyltransferase (MGMT), which is a potential biomarker for brain tumours and breast cancer. The biosensor is based on aminated reduced graphene oxide electrode, which is achieved by ammonium hydroxide chemisorption and anti-5-methylcytosine (anti-5mC) as a methylation bioreceptor. The target single-strand (ss) MGMT oligonucleotide is first recognised by its hybridisation with complementary DNA to form double-stranded (ds) MGMT, which is then captured by anti-5mC on the electrode surface due to the presence of methylation. Raman spectroscopy, X-ray photoelectron spectroscopy (XPS) and Scanning electron microscopy (SEM) techniques were used to characterise the electrode surface. Cyclic voltammetry (CV) and differential pulse voltammetry (DPV) techniques were used for electrochemical measurements. Under optimised conditions, the proposed biosensor is able to quantify a linear range of concentrations of the MGMT gene from 50 fM to 100 pM with a limit of detection (LOD) of 12 fM. The sandwich design facilitates the simultaneous recognition and quantification of DNA methylation, and the amination significantly improves the sensitivity of the biosensor. This biosensor is label-, bisulfite- and PCR-free and has a simple design for cost-efficient production. It can also be tailor-made to detect other methylated genes, which makes it a promising detection platform for DNA methylation-related disease diagnosis and prognosis.

Fat mass prediction equations and reference ranges for Saudi Arabian Children aged 8-12 years using machine technique method.

BACKGROUND: The number of children with obesity has increased in Saudi Arabia, which is a significant public health concern. Early diagnosis of childhood obesity and screening of the prevalence is needed using a simple in situ method. This study aims to generate statistical equations to predict body fat percentage (BF%) for Saudi children by employing machine learning technology and to establish gender and age-specific body fat reference range. METHODS: Data was combined from two cross-sectional studies conducted in Saudi Arabia for 1,292 boys and girls aged 8-12 years. Body fat was measured in both studies using bio-electrical impedance analysis devices. Height and weight were measured and body mass index was calculated and classified according to CDC 2,000 charts. A total of 603 girls and 374 boys were randomly selected for the learning phase, and 153 girls and 93 boys were employed in the validation set. Analyses of different machine learning methods showed that an accurate, sensitive model could be created. Two regression models were trained and fitted with the construction samples and validated. Gradient boosting algorithm was employed to achieve a better estimation and produce the equations, then the root means squared error (RMSE) equation was performed to decrease the error. Body fat reference ranges were derived for children aged 8-12 years. RESULTS: For the gradient boosting models, the predicted fat percentage values were more aligned with the true value than those in regression models. Gradient boosting achieved better performance than the regression equation as it combined multiple simple models into a single composite model to take advantage of that weak classifier. The developed predictive model archived RMSE of 3.12 for girls and 2.48 boys. BF% and Fat mass index charts were presented in which cut-offs for 5th, 75th and 95th centiles are used to define 'under-fat', 'normal', 'overfat' and 'subject with obesity'. CONCLUSION: Machine learning models could represent a significant advancement for investigators studying adiposity-related issues in children. These models and newly developed centile charts could be useful tools for the estimation and classification of BF%.

Biosensors as a future diagnostic approach for COVID-19.

Biosensors are important devices in clinical diagnostics, food processing, and environmental monitoring for detecting various analytes, especially viruses. These biosensors provide rapid and effective instruments for qualitative and quantitative detection of infectious diseases in real-time. Here, we report the development of biosensors based on various techniques. Additionally, we will explain the mechanisms, advantages, and disadvantages of the most common biosensors that are currently used for viral detection, which could be optical (e.g., surface-enhanced Raman scattering (SERS), Surface plasmon resonance (SPR)) and electrochemical biosensors. Based on that, this review recommends methods for efficient, simple, low-cost, and rapid detection of SARS-CoV-2 (the causative agent of COVID-19) that employ the two types of biosensors depending on attaching hemoglobin ß-chain and binding of specific antibodies with SARS-CoV-2 antigens, respectively.

Evaluation of the proinflammatory effects of contaminated bathing water.

Contaminated marine bathing water has been reported to adversely affect human health. Our data demonstrated a correlation between total endotoxin (lipopolysaccharide; LPS) levels and degree of contamination of marine bathing waters. To assess the potential health implications of LPS present in marine bathing waters, the inflammation-inducing potency of water samples collected at different time points at multiple sampling sites were assessed using a cell culture-based assay. The numbers of fecal indicator bacteria (FIB) were also examined in the same samples. Water samples were used to stimulate two cell culture models: (1) a novel non-transformed continuously growing murine cell line Max Plank Institute (MPI) characteristic of alveolar macrophages and (2) human MonoMac 6 monocyte cell line. The inflammatory potential of the samples was assessed by measuring the release of inflammatory cytokines. The presence of high levels of LPS in contaminated bathing water led to induction of inflammatory response from our in vitro cell-based bioassays suggesting its potential health impact. This finding introduces an in vitro culture assay that reflects the level of LPS in water samples. These observations further promote previous finding that LPS is a reliable surrogate biomarker for fecal contamination of bathing water.

Evaluation of recombinant factor C assay for the detection of divergent lipopolysaccharide structural species and comparison with Limulus amebocyte lysate-based assays and a human monocyte activity assay.

PURPOSE: The Limulus amebocytelysate (LAL) assay is widely used for the screening of lipopolysaccharide (LPS) in parenteral pharmaceuticals. However, correlation of LPS in Gram-negative bacterial infections by LAL assay has been problematic, partly due to the variable reactivity of different LPS structures. Recombinant factor C (rFC) has allowed the development of a new simple, specific and sensitive LPS detection system (PyroGene). In this work, the potential of the new assay for detecting various LPS structures has been investigated and compared with two LAL-based assays and a human monocyte activity assay. METHODOLOGY: The activity of the various LPS structures has been investigated by PyroGene and two LAL-based assays and a human monocyte activity assay. RESULTS: The rFC assay detected most LPS structures in picogram quantities and the potency of E. coli, B. cepacia, Salmonella smooth and Salmonella R345 LPS was no different when measured with PyroGene or LAL assays. However, the reactivity of K. pneumoniae, S. marcescens, B. pertussis and P. aeruginosa LPS differed significantly between these assays. Importantly, pairwise correlation analysis revealed that only the PyroGene assay produced a significant positive correlation with the release of IL-6 from a monocytic cell line. CONCLUSION: We conclude that the rFC-based assay is a good replacement for conventional LAL assays and as it correlates significantly with IL-6 produced by a human monocyte cell line it could potentially be more useful for detecting LPS in a clinical setting.

The potential of lipopolysaccharide as a real-time biomarker of bacterial contamination in marine bathing water.

The use of total lipopolysaccharide (LPS) as a rapid biomarker for bacterial pollution was investigated at a bathing and surfing beach during the UK bathing season. The levels of faecal indicator bacteria Escherichia coli (E. coli), the Gram-positive enterococci, and organisms commonly associated with faecal material, such as total coliforms and Bacteroides, were culturally monitored over four months to include a period of heavy rainfall and concomitant pollution. Endotoxin measurement was performed using a kinetic Limulus Amebocyte Lysate (LAL) assay and found to correlate well with all indicators. Levels of LPS in excess of 50 Endotoxin Units (EU) mL(-1) were found to correlate with water that was unsuitable for bathing under the current European regulations. Increases in total LPS, mainly from Gram-negative indicator bacteria, are thus a potential real-time, qualitative method for testing bacterial quality of bathing waters.