Quantitative and sensitive RNA based detection of Bacillus spores

Accurate identification of living Bacillus spores using laser tweezers Raman spectroscopy and deep learning

Accurately, rapidly, and noninvasively identifying Bacillus spores can greatly contribute to controlling a plenty of infectious diseases. Laser tweezers Raman spectroscopy (LTRS) has confirmed to be a powerful tool for studying Bacillus spores at a single cell level. In this study, we constructed a single-cell Raman spectra dataset of living Bacillus spores and utilized deep learning approach to accurately, nondestructively identify Bacillus spores. The trained convolutional neural network (CNN) could efficiently extract tiny Raman spectra features of five spore species, and provide a prediction accuracy of specie identification as high as 100 %. Moreover, the spectral feature differences in three Raman bands at 660, 826, and 1017 cm^-1 were confirmed to mostly contribute to producing such high prediction accuracy. In addition, optimal CNN model was employed to monitor and identify sporulation process at different metabolic phases in one growth cycle. The obtained average prediction accuracy of metabolic phase identification was approximately 88 %. It can be foreseen that, LTRS combined with CNN approach have great potential for accurately identifying spore species and metabolic phases at a single cell level, and can be gradually extended to perform identification for many unculturable bacteria growing in soil, water, and food.

Capturing colloidal nano- and microplastics with plant-based nanocellulose networks

Microplastics accumulate in various aquatic organisms causing serious health issues, and have raised concerns about human health by entering our food chain. The recovery techniques for the most challenging colloidal fraction are limited, even for analytical purposes. Here we show how a hygroscopic nanocellulose network acts as an ideal capturing material even for the tiniest nanoplastic particles. We reveal that the entrapment of particles from aqueous environment is primarily a result of the network’s hygroscopic nature - a feature which is further intensified with the high surface area of nanocellulose. We broaden the understanding of the mechanism for particle capture by investigating the influence of pH and ionic strength on the adsorption behaviour. We determine the nanoplastic binding mechanisms using surface sensitive methods, and interpret the results with the random sequential adsorption (RSA) model. These findings hold potential for the explicit quantification of the colloidal nano- and microplastics from different aqueous environments, and eventually, provide solutions to collect them directly on-site where they are produced.

Nanoplastic particles in aqueous environments are challenging to quantify and characterize due to a lack of methods to capture and analyze them. Here the authors demonstrate that nanocellulose networks can be used to capture colloidal plastics and quantify them through their fluorescence and adsorption, providing kinetic information on their uptake.

Rapid Detection of Bacillus anthracis Spores Using Immunomagnetic Separation and Amperometry

Portable detection and quantitation methods for Bacillus anthracis (anthrax) spores in pure culture or in environmental samples are lacking. Here, an amperometric immunoassay has been developed utilizing immunomagnetic separation to capture the spores and remove potential interferents from test samples followed by amperometric measurement on a field-portable instrument. Antibody-conjugated magnetic beads and antibody-conjugated glucose oxidase were used in a sandwich format for the capture and detection of target spores. Glucose oxidase activity of spore pellets was measured indirectly via amperometry by applying a bias voltage after incubation with glucose, horseradish peroxidase, and the electron mediator 2,2′-azino-bis (3-ethylbenzthiazoline-6-sulphonic acid). Target capture was mediated by polyclonal antisera, whereas monoclonal antibodies were used for signal generation. This strategy maximized sensitivity (500 target spores, 5000 cfu/mL), while also providing a good specificity for Bacillus anthracis spores. Minimal signal deviation occurs in the presence of environmental interferents including soil and modified pH conditions, demonstrating the strengths of immunomagnetic separation. The simultaneous incubation of capture and detection antibodies and rapid substrate development (5 min) result in short sample-to-signal times (less than an hour). With attributes comparable or exceeding that of ELISA and LFDs, amperometry is a low-cost, low-weight, and practical method for detecting anthrax spores in the field.