Model-Based Analysis of Lactuca sativa Root Growth under the Action of Herbicides in Milli-Channel Arrays with In Situ Imaging.

Extracting practical information from the large amounts of data gathered during the live imaging analysis of plant organs is a challenging issue. The present work investigates the use of the logistic growth model to analyze experimental data from root elongation assays performed in milli-fluidic devices with in situ imaging. Lactuca sativa was used as a bioindicator and was subjected to wide concentration ranges of four different herbicides: 2,4-D, atrazine, glyphosate, and paraquat. The model parameters were directly connected to standard indicators of toxicity and plant development, such as the LD50 and the absolute growth rate, respectively. In addition, it was found that realistic predictions of the maximum root length can be achieved about 60 h before the bioassay end point, which could significantly shorten the turnaround time. The combination of milli-fluidic devices, real-time imaging, and model-based data analysis becomes a powerful tool for environmental studies and ecotoxicity testing.

Field-deployable aptasensor with automated analysis of stain patterns for the detection of chlorpyrifos in water.

Organophosphorus compounds such as chlorpyrifos (CPS) are causing serious environmental problems worldwide. Efficient monitoring of the CPS levels in water resources demands portable devices for on-field testing. Here we report the development of a CPS sensor coupled with smartphones for automated reading and data analysis. The sensing mechanism makes use of gold nanoparticles stabilized by a CPS-specific aptamer, where colloidal destabilization occurs in presence of competing CPS molecules. In particular, an innovative readout is proposed: quantitative analysis of the stain patterns left by evaporating drops of the test solutions. We have found that the CPS-induced destabilization suppresses the typical coffee-ring stain of the colloidal gold, and then exploited the phenomenon to quantitatively determine the CPS concentration in water samples. A strong correlation between CPS level in samples and the alteration of the stain patterns was established for a wide range of CPS concentrations (0.048 µM-482 µM). The limit of detection of the sensor was 0.2 µM. The assay was implemented on Whatman filter paper cards that were specially patterned by wax-printing. A smartphone-based Python program was written for fully automated image capture and processing. Notably, as we analyze the spatial configuration of the stains, the reading system is independent of external illumination. The system also enables data management and traceability, which are highly desirable attributes for environmental monitoring.

A free customizable tool for easy integration of microfluidics and smartphones.

The integration of smartphones and microfluidics is nowadays the best possible route to achieve effective point-of-need testing (PONT), a concept increasingly demanded in the fields of human health, agriculture, food safety, and environmental monitoring. Nevertheless, efforts are still required to integrally seize all the advantages of smartphones, as well as to share the developments in easily adoptable formats. For this purpose, here we present the free platform appuente that was designed for the easy integration of microfluidic chips, smartphones, and the cloud. It includes a mobile app for end users, which provides chip identification and tracking, guidance and control, processing, smart-imaging, result reporting and cloud and Internet of Things (IoT) integration. The platform also includes a web app for PONT developers, to easily customize their mobile apps and manage the data of administered tests. Three application examples were used to validate appuente: a dummy grayscale detector that mimics quantitative colorimetric tests, a root elongation assay for pesticide toxicity assessment, and a lateral flow immunoassay for leptospirosis detection. The platform openly offers fast prototyping of smartphone apps to the wide community of lab-on-a-chip developers, and also serves as a friendly framework for new techniques, IoT integration and further capabilities. Exploiting these advantages will certainly help to enlarge the use of PONT with real-time connectivity in the near future.

Milli-channel array for direct and quick reading of root elongation bioassays.

A novel platform to perform systematic analysis and direct reading of root elongation bioassays is presented. The device was designed to include multiplexed microenvironments for the germination and growth of individual seeds, which allows observation by the naked eye or by optical systems, notably cellphone cameras. Prototypes were fabricated by laser micromachining on a highly transparent material that is fully compatible with biological systems. The effectiveness of the milli-channel array was verified against the conventional system (Petri dish). Lactuca sativa was chosen as a model species and glyphosate as a typical toxic agent. All tests were run according to standardized procedures and data analysis was carried out through different statistical indicators such as the root elongation and germination indexes. Results attained in the milli-channel array were identical to those in Petri dish, with the remarkable benefit that several steps required in the conventional system were avoided, which enormously decreases the operation time and the possibility of experimental errors. Further advantages of the milli-channel array are also reported, such as the capability to achieve live imaging of plant organs growth through a simple experiment. The developed device has been proven to be effective, versatile, easy-to-use, and integrable to cellphones, which naturally provide facilities for data recording, analysis, and networking. These improvements open the route to novel applications of bioassays in the wide field of ecotoxicology and environmental studies.