Identification of β-lactam antibiotics using bioluminescent Escherichia coli and a support vector machine classifier algorithm

We propose the use of bioluminescent whole cell biosensor combined with a pattern classification algorithm to automatically detect and identify β-lactam antibiotic substances. Escherichia coli cells with a plasmid harboring luxCDABE genes under the β-lactam sensitive promoter element are used as sensors. We present experimental measurements of light production of bioluminescent bacteria subject to 11 antibiotic substances. The patterns of measured light production are classified using a support vector machine classifier. The accuracy and reliability of the classification suggests that this method can be used in the future to probe for new antibiotic substances.     

Detection of Escherichia coli using CMOS array photo sensor-based enzyme biochip detection system

This work presents optical enzyme detection system based on the CMOS array photo sensor and 1 × 3 polymeric enzyme biochip for detecting Escherichia coli in a one-step procedure. This assay, using 4-methylumbelliferyl-β-d-glucuronide (MUG) as a fluorogenic substrate, had a detection limit of 0.1 U/ml for β-glucuronidase (GUD), which was approximately equal to a cell concentration of 10⁶ CFU/ml of E. coli. MUG was incorporated into lauryl tryptose broth at a final concentration of 100 μg/ml for immediate verification of the presence of E. coli in 1 × 3 polymeric enzyme biochip. The 40 strains of E. coli studied all produced GUD. Of another 36 strains of bacteria tested, one strain (Salmonella choleraesuis subsp. choleraesuis) yielded very small amounts of GUD after 24 h incubation. The optical enzyme detection system was sensitive and rapid.     

A wireless, remote-query sensor for real-time detection of Escherichia coli O157:H7 concentrations

This paper describes the real-time detection of Escherichia coli O157:H7 concentrations using a remote-query (wireless, passive) magnetoelastic sensor. The resonance frequency of a liquid immersed magnetoelastic sensor, measured through magnetic field telemetry, changes mainly in response to bacteria adhesion to the sensor and the liquid properties (viscosity, density, elasticity, etc.) of the culture medium. In the described application, during its growth and reproduction we find E. coli consumes nutrients from a liquid culture medium that decreases the solution viscosity, and in turn changes the resonance frequency of the medium-immersed magnetoelastic sensor. Using the described technique we are able to directly quantify E. coli O157:H7 concentrations of 2 × 10² to 3 × 10⁶ cells ml⁻¹, and quantify the effect of gentamycin sulfate injection (GSI) on proliferation of the bacteria. The lack of any physical connections between the sensor and the monitoring electronics facilitates aseptic operation, and makes the sensor platform ideally suited for monitoring bacteria from within, for example, sealed food containers.     

A photoluminescence-based quantum semiconductor biosensor for rapid in situ detection of Escherichia coli

This work describes a novel method of detecting Escherichia coli using photoluminescence (PL) emission from III–V quantum semiconductor (QS) devices functionalized with two different antibody-based architectures. The first approach employed self-assembled monolayers of biotinylated polyethylene glycol thiols to immobilize biotinylated antibody via neutravidin. In the second approach, we used QS microstructures coated with a thin layer of Si₃N₄ allowing direct functionalization with E. coli antibodies through hydrofluoric acid etching and glutaraldehyde-based reticulation. Atomic force, optical and fluorescence microscopy measurements were used to assess the immobilization process. Depending on the biosensing architecture, density of the immobilized bacteria was observed in the range of 0.5–0.7 bacteria/100 μm². The detection of E. coli at 10⁴ CFU/ml was achieved within less than 120 min of the bacteria exposure. It is expected that an even better sensitivity threshold could be achieved following further optimization of the method.     

Rapid differentiation between E. coli and Salmonella Typhimurium using metal oxide sensors integrated with pattern recognition

A rapid method to differentiate between E coli and Salmonella Typhimurium was developed. E. coli and S. Typhimurium were separately grown in super broth and incubated at 37 °C. Super broth without inoculation of E. coli or S. Typhimurium was used as control. Numbers of E. coli and S. Typhimurium were followed using a colony counting method. Identification of the volatile metabolites produced by E. coli and S. Typhimurium was determined using solid-phase microextraction coupled with gas chromatography/mass spectrometry. An electronic nose with 12 non-specific metal oxide sensors was used to monitor the volatile profiles produced by E. coli and S. Typhimurium. Principal component analysis (PCA) and back-propagation neural network (BPNN) were used as pattern recognition tools. PCA was used for data exploration and dimensional reduction. PCA could visualize class separation between sample subgroups. The BPNN was shown to be capable of predicting the number of E. coli and S. Typhimurium. Good prediction was possible as measured by a regression coefficient (R² = 0.96) between true and predicted data. Using metal oxide sensors and pattern recognition techniques, it was possible to discriminate between samples containing E. coli from those containing S. Typhimurium.     

Single step cell lysis/PCR detection of Escherichia coli in an independently controllable silicon microreactor

Our studies describe a novel microreactor capable of single step microbial assays involving cell lysis and DNA amplification. The device with an integrated platinum heater and temperature sensor, was fabricated using conventional silicon fabrication technologies and then anodically bonded to a Pyrex lid. Finite element analysis (FEA) and experiments have shown that the temperature uniformity in the microreactor reaction cavity is homogeneous and that the microreactor is capable of fast thermal cycling with heating and cooling rates of 11 and 2.7 °C/s, respectively. The microreactor has novel design features, such as a thermal isolation channel which eliminates thermal cross talk and an inlet/outlet port designed for ease of use. The fabricated microreactor was successfully characterised using a multifunction microbial assay involving cell lysis and PCR in a single step. An assay time of 32 min was achieved.     

Detection and discrimination of coliform bacteria with gas sensor arrays

Electronic noses, which are used for characterizing complex vapors and aromas, may be useful for detection of bacterial contamination or diagnosis of infections, if minimal standards of selectivity and sensitivity can be met. A culture of Enterobacter aerogenes is readily discriminated from an Escherichia coli strain using principal components analysis (PCA) of data generated by an array of eight quartz microbalance (QMB), eight metal oxide semiconductor (MOX), and four electrochemical gas sensors. Two strains of E. coli were not discriminated under identical conditions. Retaining headspace air in a sealed vial containing growing bacteria results in an enhancement of sensitivity, so that a concentration of bacteria of about 5×10⁸/ml may be both detected and distinguished from other species. Improvements in sensitivity to levels useful for practical applications will require enhancement of sensors, sampling system, and pattern classification.     

Application of radial basis function and feedforward artificial neural networks to the Escherichia coli fermentation process

Radial basis function and feedforward neural networks are considered for modelling of the recombinant Escherichia coli fermentation process. The models use industrial on-line data from the process as input variables in order to estimate the concentrations of biomass and recombinant protein, normally only available from off-line laboratory analysis. The models performances are compared by prediction error and graphical fit using results obtained from a common testing set of fermentation data.     

识别和计数微生物细胞的 伏安型生物传感器的研究

报道了一种半微分循环伏安型生物传感器，可同时完成对细胞的识别数。该传感器由一个平面热解石墨电极、铂电极及Ａｇ／ＡｇＣｌ电极的三电极系统组成。将阻留微生物细胞的滤膜紧附在工作电极表面，然后在工作电极与对极间施加一扫描电压，进行半微分循环伏安扫描，记录伏安图谱 。     

Tyr/MWNTs-Chit/GCE生物传感器的制备及其在快速检测大肠杆菌中的应用

该文基于多壁碳纳米管(muhiwalled carbon nanotubes,MWNTs)-壳聚糖(Chit)复合物修饰电极制备了灵敏、稳定的酪氨酸酶(tyrosinase.Tyr)生物传感器.由于MWNTs-Chit复合物具有好的生物兼容性以及电催化能力,Tyrr/MWNTs-Chit/GCE生物传感器在苯酚的检测中具有高灵敏度(412 mA/mo1),低检测限(5.0nmol/L),较宽的线性范围(1.0×10-8～2.8×10-5mol/L)以及良好的稳定性(10天后仍保持93%的活性).把Tyr/MWNTs-Chit/GCE生物传感器进一步应用于大肠杆菌的检测,大肠杆菌在104～107 cfu/mL范围内与电流响应成正比;经过5.0 h的培养,进一步降低大肠杆菌的检测限至10 cfu/mL.