Development of Solid-Phase RPA on a Lateral Flow Device for the Detection of Pathogens Related to Sepsis

Heeroma, Alice; Gwenin, Christopher

doi:10.3390/s20154182

Cited by 5 publications

(3 citation statements)

References 57 publications

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“…The double-stranded DNA template is dissociated by a recombinase and single-stranded binding protein, and then, Sau DNA polymerase generates new complementary products within 5-20 min [18]. The results of alternative post-RPA detection methods using SYBR Green or a lateral flow strip assay (LFA) are easily observed by the naked eye, and can be applied for point-of-care testing and field studies [19][20][21]. Hence, this study attempted to develop multiplex RPA combined with LFA to detect the three most common ESBL genes (bla CTX-M , bla OXA , and bla SHV ).…”

Section: Introductionmentioning

confidence: 99%

Rapid detection of extended spectrum β-lactamase producing Escherichia coli isolated from fresh pork meat and pig cecum samples using multiplex recombinase polymerase amplification and lateral flow strip analysis

et al. 2021

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The emergence and dissemination of extended-spectrum β-lactamase (ESBL)-producing Escherichia coli is a global health issue. Food-producing animals, including pigs, are significant reservoirs of antimicrobial resistance (AMR), which can be transmitted to humans. Thus, the rapid detection of ESBLs is required for efficient epidemiological control and treatment. In this study, multiplex recombinase polymerase amplification (RPA) combined with a single-stranded tag hybridization chromatographic printed-array strip (STH-PAS), as a lateral flow strip assay (LFA), was established for the rapid and simultaneous detection of multiple bla genes in a single reaction. Visible blue lines, indicating the presence of the blaCTX-M, blaSHV, and blaOXA genes, were observed within 10 min by the naked eye. The limit of detection of all three genes was 2.5 ng/25 μL, and no cross-reactivity with seven commensal aerobic bacteria was observed. A total of 93.9% (92/98) and 96% (48/50) of the E. coli isolates from pork meat and fecal samples, respectively, expressed an ESBL-producing phenotype. Nucleotide sequencing of the PCR amplicons showed that blaCTX-M was the most prevalent type (91.3–95.83%), of which the main form was blaCTX-M-55. The sensitivity and specificity of the RPA-LFA were 99.2% and 100%, respectively, and were in almost perfect agreement (κ = 0.949–1.000) with the results from PCR sequencing. Thus, the RPA-LFA is a promising tool for rapid and equipment-free ESBL detection and may facilitate clinical diagnosis in human and veterinary medicine, as well as AMR monitoring and surveillance.

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Section: Introductionmentioning

confidence: 99%

Rapid detection of extended spectrum β-lactamase producing Escherichia coli isolated from fresh pork meat and pig cecum samples using multiplex recombinase polymerase amplification and lateral flow strip analysis

et al. 2021

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“…Other studies have investigated the use of biomarkers in combination with clinical and laboratory parameters to improve the accuracy of septic shock diagnosis. To aid in the diagnosis of sepsis, researchers have developed a Lateral Flow Solid-Phase RPA for Sepsis-Related Pathogen Detection [15]. Quantitative identifcation of lactate using optical spectroscopy to help in continuous monitoring of serum lactate levels as a precondition for sepsis-prone patients requiring intensive care [16].…”

Section: Biomarkers Of Septic Shockmentioning

confidence: 99%

Conditional Tabular Generative Adversarial Net for Enhancing Ensemble Classifiers in Sepsis Diagnosis

Alfakeeh,

Sharif,

Zorto

et al. 2023

Applied Computational Intelligence and Soft Computing

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Antibiotic-resistant bacteria have proliferated at an alarming rate as a result of the extensive use of antibiotics and the paucity of new medication research. The possibility that an antibiotic-resistant bacterial infection would progress to sepsis is one of the major collateral problems affecting people with this condition. 31,000 lives were lost due to sepsis in England with costs about two billion pounds annually. This research aims to develop and evaluate several classification approaches to improve predicting sepsis and reduce the tendency of underdiagnosis in computer-aided predictive tools. This research employs medical datasets for patients diagnosed with sepsis, and it analyses the efficacy of ensemble machine learning techniques compared to nonensemble machine learning techniques and the significance of data balancing and conditional tabular generative adversarial nets for data augmentation in producing reliable diagnosis. The average F Score obtained by the nonensemble models trained in this paper is 0.83 compared to the ensemble techniques average of 0.94. Nonensemble techniques, such as Decision Tree, achieved an F score of 0.90, an AUC of 0.90, and an accuracy of 90%. Histogram-basedgradient boosting classification tree achieved an F score of 0.96, an AUC of 0.96, and an accuracy of 95%, surpassing the other models tested. Additionally, when compared to the current state-of-the-art sepsis prediction models, the models developed in this study demonstrated higher average performance in all metrics, indicating reduced bias and improved robustness through data balancing and conditional tabular generative adversarial nets for data augmentation. The study revealed that data balancing and augmentation on the ensemble machine learning algorithms boost the efficacy of clinical predictive models and can help clinics decide which data types are most important when examining patients and diagnosing sepsis early through intelligent human-machine interface.

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“…paratuberculosis infection in cattle [33]. Furthermore, recently Gwenin et al fabricated (a) a label free colorimetric assay for active botulinum neurotoxin using soluble N-ethylmaleimide-sensitive attachment protein receptor (SNARE) proteins (SNAP-25) conjugated gold nanoparticles [34], (b) a biosensor over gold working electrode for the detection of active botulinum neurotoxin in a real pharmaceutical sample using EIS [16], (c) SNAP-25 and vesicle associated membrane protein (VAMP) based EIS biosensors over a gold working electrode for detecting the activity of five botulinum neurotoxin serotypes (A-E) [17], and (d) a lateral flow device for the detection of sepsis pathogens using recombinase polymerase amplification [35]. In addition, Liu et al used a nanocomposite of Au nanoparticles/toluidine-graphene oxide modified glassy carbon electrode for the fabrication of a label free electrochemical DNA biosensor to detect a multidrug resistance gene [36].…”

Section: Introductionmentioning

confidence: 99%

Development of Electrochemical DNA Biosensor for Equine Hindgut Acidosis Detection

Davies

Thomas

Rizwan

et al. 2021

Sensors

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The pH drop in the hindgut of the horse is caused by lactic acid-producing bacteria which are abundant when a horse’s feeding regime is excessively carbohydrate rich. This drop in pH below six causes hindgut acidosis and may lead to laminitis. Lactic acid-producing bacteria Streptococcus equinus and Mitsuokella jalaludinii have been found to produce high amounts of L-lactate and D-lactate, respectively. Early detection of increased levels of these bacteria could allow the horse owner to tailor the horse’s diet to avoid hindgut acidosis and subsequent laminitis. Therefore, 16s ribosomal ribonucleic acid (rRNA) sequences were identified and modified to obtain target single stranded deoxyribonucleic acid (DNA) from these bacteria. Complementary single stranded DNAs were designed from the modified target sequences to form capture probes. Binding between capture probe and target single stranded deoxyribonucleic acid (ssDNA) in solution has been studied by gel electrophoresis. Among pairs of different capture probes and target single stranded DNA, hybridization of Streptococcus equinus capture probe 1 (SECP1) and Streptococcus equinus target 1 (SET1) was portrayed as gel electrophoresis. Adsorptive stripping voltammetry was utilized to study the binding of thiol modified SECP1 over gold on glass substrates and these studies showed a consistent binding signal of thiol modified SECP1 and their hybridization with SET1 over the gold working electrode. Cyclic voltammetry and electrochemical impedance spectroscopy were employed to examine the binding of thiol modified SECP1 on the gold working electrode and hybridization of thiol modified SECP1 with the target single stranded DNA. Both demonstrated the gold working electrode surface was modified with a capture probe layer and hybridization of the thiol bound ssDNA probe with target DNA was indicated. Therefore, the proposed electrochemical biosensor has the potential to be used for the detection of the non-synthetic bacterial DNA target responsible for equine hindgut acidosis.

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Development of Solid-Phase RPA on a Lateral Flow Device for the Detection of Pathogens Related to Sepsis

Cited by 5 publications

References 57 publications

Rapid detection of extended spectrum β-lactamase producing Escherichia coli isolated from fresh pork meat and pig cecum samples using multiplex recombinase polymerase amplification and lateral flow strip analysis

Rapid detection of extended spectrum β-lactamase producing Escherichia coli isolated from fresh pork meat and pig cecum samples using multiplex recombinase polymerase amplification and lateral flow strip analysis

Conditional Tabular Generative Adversarial Net for Enhancing Ensemble Classifiers in Sepsis Diagnosis

Development of Electrochemical DNA Biosensor for Equine Hindgut Acidosis Detection

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