FTIR nanobiosensors for Escherichia coli detection

Surface chemical modification of poly(dimethylsiloxane) for stabilizing antibody immobilization and T cell cultures

Advances in cell immunotherapy underscore the need for effective methods to produce large populations of effector T cells, driving growing interest in T-cell bioprocessing and immunoengineering. Research suggests that T cells demonstrate enhanced expansion and differentiation on soft matrices in contrast to rigid ones. Nevertheless, the influence of antibody conjugation chemistry on these processes remains largely unexplored. In this study, we examined the effect of antibody conjugation chemistry on T cell activation, expansion and differentiation using a soft and biocompatible polydimethylsiloxane (PDMS) platform. We rigorously evaluated three distinct immobilization methods, beginning with the use of amino-silane (PDMS-NH2-Ab), followed by glutaraldehyde (PDMS-CHO-Ab) or succinic acid anhydride (PDMS-COOH-Ab) activation, in addition to the conventional physical adsorption (PDMS-Ab). By employing both stable amide bonds and reducible Schiff bases, antibody conjugation significantly enhanced antibody loading and density compared to physical adsorption. Furthermore, we discovered that the PDMS-COOH-Ab surface significantly promoted IL-2 secretion, CD69 expression, and T cell expansion compared to the other groups. Moreover, we observed that both PDMS-COOH-Ab and PDMS-NH2-Ab surfaces exhibited a tendency to induce the differentiation of naïve CD4+ T cells into Th1 cells, whereas the PDMS-Ab surface elicited a Th2-biased immunological response. These findings highlight the importance of antibody conjugation chemistry in the design and development of T cell culture biomaterials. They also indicate that PDMS holds promise as a material for constructing culture platforms to modulate T cell activation, proliferation, and differentiation.

Efficient classification of Escherichia coli and Shigella using FT-IR spectroscopy and multivariate analysis

Accurate and effective discrimination of E. coli and Shigella is an important clinical issue, and there are many limitations in traditional methods of analysis. FT-IR shows great potential in the classification of bacteria with high specificity and low cost. In this study, we evaluated the efficiency of this technique when combined with multivariate analysis for rapid classification of E. coli and Shigella, which is difficult using traditional analytical methods. Machine learning and statistical tools were employed in combination with FT-IR to classify 14 E. coli and 9 Shigella strains. The classification accuracies for select E. coli and Shigella strains from blood agar were 0.7826, 0.8696, and 0.9565 at the genus, species, and strain levels, respectively. In addition, we used the FT-IR data of select strains from three different culture media for cross-validation, yielding an accuracy of 0.3681 at the strain level. These results indicate that the bacterial culture conditions have a significant impact on the FT-IR patterns. Based on this, an improved strategy for training an ensemble classifier model considering bacterial culture factors was constructed, resulting in almost perfect separation with an accuracy of 0.9394 for strain-level classification. These results show the potential of FT-IR combined with multivariate analysis for more reliable bacterial classification.

Characterisation and Classification of Foodborne Bacteria Using Reflectance FTIR Microscopic Imaging

This work investigates the application of reflectance Fourier transform infrared (FTIR) microscopic imaging for rapid, and non-invasive detection and classification between Bacillus subtilis and Escherichia coli cell suspensions dried onto metallic substrates (stainless steel (STS) and aluminium (Al) slides) in the optical density (OD) concentration range of 0.001 to 10. Results showed that reflectance FTIR of samples with OD lower than 0.1 did not present an acceptable spectral signal to enable classification. Two modelling strategies were devised to evaluate model performance, transferability and consistency among concentration levels. Modelling strategy 1 involves training the model with half of the sample set, consisting of all concentrations, and applying it to the remaining half. Using this approach, for the STS substrate, the best model was achieved using support vector machine (SVM) classification, providing an accuracy of 96% and Matthews correlation coefficient (MCC) of 0.93 for the independent test set. For the Al substrate, the best SVM model produced an accuracy and MCC of 91% and 0.82, respectively. Furthermore, the aforementioned best model built from one substrate was transferred to predict the bacterial samples deposited on the other substrate. Results revealed an acceptable predictive ability when transferring the STS model to samples on Al (accuracy = 82%). However, the Al model could not be adapted to bacterial samples deposited on STS (accuracy = 57%). For modelling strategy 2, models were developed using one concentration level and tested on the other concentrations for each substrate. Results proved that models built from samples with moderate (1 OD) concentration can be adapted to other concentrations with good model generalization. Prediction maps revealed the heterogeneous distribution of biomolecules due to the coffee ring effect. This work demonstrated the feasibility of applying FTIR to characterise spectroscopic fingerprints of dry bacterial cells on substrates of relevance for food processing.

Interdigitated Electrode Biosensor Based on Plasma-Deposited TiO2 Nanoparticles for Detecting DNA

Bioelectrodes mediated by metal oxide nanoparticles have facilitated the development of new sensors in medical diagnosis. High-purity TiO₂ nanoparticles (NPs) were synthesized through thermal plasma and deposited directly on an interdigitated electrode. The surface of the TiO₂-deposited electrode was activated with (3-aminopropyl) triethoxysilane (APTES) followed by fixing the single-stranded probe deoxyribonucleic acid (DNA) to fabricate the DNA biosensor. The structural properties of the deposited TiO₂ nanoparticles were analyzed using a transmission electron microscope (TEM), X-ray diffraction (XRD), and a dynamic light scattering (DLS) system. The chemical composition and structural properties of the TiO₂ nanoparticle layer and the fixed layer were analyzed by X-ray photoelectron spectroscopy (XPS) and scanning electron microscopy (SEM). E. coli O157:H7, a well-known pernicious pathogenic bacterial species, was detected as a target DNA of the prepared DNA biosensor, and the characteristics of DNA detection were determined by the current change using a picoammeter. The degree of binding between the probe DNA and the target DNA was converted into an electrical signal using the picoammeter method to quantitatively analyze the concentration of the target DNA. With the specificity experiment, it was confirmed that the biosensor was able to discriminate between nucleotides with mismatched, non-complementary, or complementary sequences.

Applications of nanotechnology on vegetable crops

Agriculture is the backbone of most developing countries, and most of their people depend on it for their livelihood. The world population is increased by approximately 83 million people each year, so there is a need to increase agricultural productivity. At present, productivity growth can be achieved either by expanding the area cultivated or increasing crop yields through improving the efficiency of fertilizers used. Therefore, there has been a trend to use modern technologies, such as nanotechnology (NT), to increase the productivity of plants. Where, it is involved in the food production process, from planting to packaging. NT improves plants' ability to absorb nutrients, and the agronomic properties of soil, which improves plant growth and productivity. Economically, NT increased the efficiency of nano-fertilizers, and so contributed to increasing productivity and the production of crops. However, the study of the effect of nanotechnology on the environment of soils and plants did not receive the required study. In this review, a comprehensive survey is exhibited on NT as an effective method in dealing with the problem of fertilizer loss during irrigation. This review discusses the technologies and applications of the latest research findings in this field. Furthermore, this review deals with the forms and types of nanoparticles and the methods of their transmission in plants, as well as their effect on plants (physiological and DNA) as well as on those who eat those plants.

Antibody Immobilization in Zinc Oxide Thin Films as an Easy-Handle Strategy for Escherichia coli Detection

The antibody immobilization compatible with low-cost materials and label-free strategies is a challenge for biosensor device fabrication. In this study, ZnO thin film deposition was carried out on corning glass substrates by ultrasonic spray pyrolysis at 200 °C. The thin films were analyzed as platforms for enteropathogenic Escherichia coli (E. coli EPEC) antibody immobilization. The modification of thin films from the functionalization and antibody immobilization steps was visualized using Fourier transform infrared spectroscopy (FTIR) spectroscopy, and surface changes were observed by atomic force microscopy. The obtained FTIR spectra after functionalization showed a contribution of the amino group (NH₂) derived from silane (3-aminopropyltrimethoxysilane). The antibody immobilization showed an amide I conserved signal corresponding to the C=O stretching vibrations and the amide II signal related to the N-H scissor vibration mode. In this way, the signals observed are correlated with the presence of antibody immobilized on the film. The ZnO film morphology changes after every stage of the process and allows observing the antibody distribution on the immobilized surface. In order to validate the antibody recognition capability as well as the E. coli EPEC detection in situ, polymerase chain reaction was used.

Effects of Ultrafine Bubbles on Gram-Negative Bacteria: Inhibition or Selection?

Ultrafine bubbles exist in all liquids and are naturally stable. As their properties are not entirely known, it is unclear how they impact the surrounding solution and comparable-sized particles within it. It is essential to further investigate the properties of ultrafine bubbles in order to expand their industrial application. In this regard, the effect of ultrafine bubbles on bacterial development is of particular interest. Our current study, using optical density measurements and fluorescence microscopic images has demonstrated that ultrafine gas bubbles impact the morphology and phenotype of Escherichia coli and Pseudomonas aeruginosa. Specifically, Fourier transform infrared spectroscopic measurements indicated a thickening of bacterial membranes in samples exposed to ultrafine bubbles. The study also confirmed that ultrafine bubbles can inhibit bacterial cell growth. This study signifies the role of surface phenomena in bacterial culture, which is crucial in the upstream processes of recombinant DNA technology applications.

Borosilicate Glass Fiber-Optic Biosensor for the Detection of Escherichia coli

Polyclonal antibodies against Escherichia coli and fluorescent, secondary, antibodies were immobilized on borosilicate glass fibers pre-treated with 3-glycidyloxypropyl trimethoxysilane (GPS). Light with an average wavelength of 627 nm, emitted by a diode placed at one end of the glass fiber, was detected by an ultrasensitive photodiode with peak sensitivity at 640 nm. Changes in fluorescence, caused by binding of E. coli to the antibodies, changed the net refractive index of the glass fiber and thus the internal reflection of light. These evanescent changes in photon energy were recorded by an ultrasensitive photodiode. Signals were amplified and changes in voltage recorded with a digital multimeter. A linear increase in voltage readings was recorded over 2 h when 3.0 × 10⁷ CFU/ml and 2.77 × 10⁹ CFU/ml E. coli were adhered to the antibodies. Voltage readings were recorded with E. coli cell numbers from 2 × 10³ CFU/ml to 2 × 10⁶ CFU/ml, but readings remained unchanged for 2 h, indicating that the limit of detection is 3.0 × 10⁷ CFU/ml. This simple technology may be used to develop a low-cost, portable, fiber-optic biosensor to detect E. coli in infections and may have applications in the medical field. Research is in progress to optimize the sensitivity of the fiber-optic biosensor and determine its specificity.

Applying graphene oxide nano-film over a polycarbonate nanoporous membrane to monitor E. coli by infrared spectroscopy

Nano-biosensors are excellent monitoring tools for rapid, specific, sensitive, inexpensive, in-field, on-line, and/or real-time detection of pathogens in foods, soil, air, and water samples. A variety of nano-materials (metallic, polymeric, and/or carbon-based) were employed to enhance the efficacy, efficiency, and sensitivity of these nano-biosensors, including graphene-based materials, especially graphene oxide (GO)-based materials. GO bears many oxygen-bearing groups, enabling ligand conjugation at the high density critical for sensitive detection. We have fabricated GO-modified nano-porous polycarbonate track-etched (PCTE) membranes that were conjugated to an Escherichia coli-specific antibody (Ab) and used to detect E. coli. The random distribution of nanopores on the PCTE membrane surface and the bright coating of the GO onto the membrane were confirmed by scanning electron microscope. Anti-E. coli β-gal Abs were conjugated to the GO surface via 1-ethyl-3,3-dimethylaminopropyl carbodiimide hydrochloride-N-hydroxysuccinimide chemistry; antibody coating was confirmed by the presence of a characteristic IR peak near 1600cm(-1). A non-corresponding Ab (anti-Pseudomonas) was used as a negative control under identical conditions. When E. coli interacted anti-E.coli β-gal with Ab-coated GO-nano-biosensor units, we observed a clear shift in the IR peak from 3373.14 to 3315cm(-1); in contrast, we did not observe any shift in IR peaks when the GO unit was coated with the non-corresponding Ab (anti-Pseudomonas). Therefore, the detection of E. coli using the described GO-nano-sensor unit is highly specific, is highly selective and can be applied for real-time monitoring of E. coli with a detection limit between 100μg/mL and 10μg/mL, similar to existing detection systems.

Nano/micro and spectroscopic approaches to food pathogen detection

Despite continuing research efforts, timely and simple pathogen detection with a high degree of sensitivity and specificity remains an elusive goal. Given the recent explosion of sensor technologies, significant strides have been made in addressing the various nuances of this important global challenge that affects not only the food industry but also human health. In this review, we provide a summary of the various ongoing efforts in pathogen detection and sample preparation in areas related to Fourier transform infrared and Raman spectroscopy, light scattering, phage display, micro/nanodevices, and nanoparticle biosensors. We also discuss the advantages and potential limitations of the detection methods and suggest next steps for further consideration.