Early detection and classification of live bacteria using time-lapse coherent imaging and deep learning.

Early identification of pathogenic bacteria in food, water, and bodily fluids is very important and yet challenging, owing to sample complexities and large sample volumes that need to be rapidly screened. Existing screening methods based on plate counting or molecular analysis present various tradeoffs with regard to the detection time, accuracy/sensitivity, cost, and sample preparation complexity. Here, we present a computational live bacteria detection system that periodically captures coherent microscopy images of bacterial growth inside a 60-mm-diameter agar plate and analyses these time-lapsed holograms using deep neural networks for the rapid detection of bacterial growth and the classification of the corresponding species. The performance of our system was demonstrated by the rapid detection of Escherichia coli and total coliform bacteria (i.e., Klebsiella aerogenes and Klebsiella pneumoniae subsp. pneumoniae) in water samples, shortening the detection time by >12 h compared to the Environmental Protection Agency (EPA)-approved methods. Using the preincubation of samples in growth media, our system achieved a limit of detection (LOD) of ~1 colony forming unit (CFU)/L in ≤9 h of total test time. This platform is highly cost-effective (~$0.6/test) and has high-throughput with a scanning speed of 24 cm2/min over the entire plate surface, making it highly suitable for integration with the existing methods currently used for bacteria detection on agar plates. Powered by deep learning, this automated and cost-effective live bacteria detection platform can be transformative for a wide range of applications in microbiology by significantly reducing the detection time and automating the identification of colonies without labelling or the need for an expert.

Early detection of E. coli and total coliform using an automated, colorimetric and fluorometric fiber optics-based device.

Lack of access to clean water is a major global issue that affects millions of people worldwide. Drinking contaminated water can be extremely hazardous, so it is imperative that it is tested sufficiently. One method commonly used to determine the quality of water is testing for both E. coli and total coliform. Here, we present a cost-effective and automated device which can concurrently test drinking water samples for both E. coli and total coliform using an EPA-approved reagent. Equipped with a Raspberry Pi microcontroller and camera, we perform automated periodic measurements of both the absorption and fluorescence of the water under test over 24 hours. In each test, 100 mL of the water sample is split into a custom designed 40-well plate, where the transmitted blue light and the fluorescent light (under UV excitation) are collected by 520 individual optical fibers. Images of these fiber outputs are then acquired periodically, and digitally processed to determine the presence of the bacteria in each well of the 40-well plate. We demonstrate that this cost-effective device, weighing 1.66 kg, can automatically detect the presence of both E. coli and total coliform in drinking water within ∼16 hours, down to a level of one colony-forming unit (CFU) per 100 mL. Furthermore, due to its automated analysis, this approach is also more sensitive than a manual count performed by an expert, reducing the time needed to determine whether the water under test is safe to drink or not.

ß-carotene treatment alters the cellular death process in oxidative stress-induced K562 cells.

Oxidizing agents (e.g., H2 O2 ) cause structural and functional disruptions of molecules by affecting lipids, proteins, and nucleic acids. As a result, cellular mechanisms related to disrupted macro molecules are affected and cell death is induced. Oxidative damage can be prevented at a certain point by antioxidants or the damage can be reversed. In this work, we studied the cellular response against oxidative stress induced by H2 O2 and antioxidant-oxidant (ß-carotene-H2 O2 ) interactions in terms of time, concentration, and treatment method (pre-, co-, and post) in K562 cells. We showed that co- or post-treatment with ß-carotene did not protect cells from the damage of oxidative stress furthermore co- and post-ß-carotene-treated oxidative stress induced cells showed similar results with only H2 O2 treated cells. However, ß-carotene pre-treatment prevented oxidative damage induced by H2 O2 at concentrations lower than 1,000 µM compared with only H2 O2 -treated and co- and post-ß-carotene-treated oxidative stress-induced cells in terms of studied cellular parameters (mitochondrial membrane potential [Δψm ], cell cycle and apoptosis). Prevention effect of ß-carotene pre-treatment was lost at concentrations higher than 1,000 µM H2 O2 (2-10 mM). These findings suggest that ß-carotene pre-treatment alters the effects of oxidative damage induced by H2 O2 and cell death processes in K562 cells.

K562 cells display different vulnerability to H2O2 induced oxidative stress in differing cell cycle phases.

Oxidative stress can be defined as the increase of oxidizing agents like reactive oxygen and nitrogen species, or the imbalance between the antioxidative defense mechanism and oxidants. Cell cycle checkpoint response can be defined as the arrest of the cell cycle functioning after damaging chemical exposure. This temporary arrest may be a period of time given to the cells to repair the DNA damage before entering the cycle again and completing mitosis. In order to determine the effects of oxidative stress on several cell cycle phases, human erytroleukemia cell line (K562) was synchronized with mimosine and genistein, and cell cycle analysis carried out. Synchronized cells were exposed to oxidative stress with hydrogen peroxide (H2O2) at several concentrations and different times. Changes on mitochondria membrane potential (ΔΨm) of K562 cells were analyzed in G1, S, and G2 /M using Rhodamine 123 (Rho 123). To determine apoptosis and necrosis, stressed cells were stained with Annexin V (AnnV) and propidium iodide (PI) for flow cytometry. Changes were observed in the ΔΨm of synchronized and asynchronized cells that were exposed to oxidative stress. Synchronized cells in S phase proved resistant to the effects of oxidative stress and synchronized cells at G2 /M phase were sensitive to the effects of H2O2 -induced oxidative stress at 500 µM and above.