ArticleScientific reports2016
Real-time bacterial microcolony counting using on-chip microscopy.
Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed, 52 citations in OpenAlex.
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- Microfluidics on lensless, semiconductor optical image sensors: challenges and opportunities for democratization of biosensing at the micro-and nano-scale.Nanophotonics (Berlin, Germany) · 2023Review
- Accelerating the Detection of Bacteria in Food Using Artificial Intelligence and Optical Imaging.Applied and environmental microbiology · 2023Article
- Diagnosing ventilator-associated pneumonia (VAP) in UK NHS ICUs: the perceived value and role of a novel optical technology.Diagnostic and prognostic research · 2022Article
- A comprehensive review of image analysis methods for microorganism counting: from classical image processing to deep learning approaches.Artificial intelligence review · 2022Article
- Viable but nonculturable bacteria and their resuscitation: implications for cultivating uncultured marine microorganisms.Marine life science & technology · 2021Review
- Photodegradable Hydrogels for Rapid Screening, Isolation, and Genetic Characterization of Bacteria with Rare Phenotypes.Biomacromolecules · 2020Article
- Food Microstructure and Fat Content Affect Growth Morphology, Growth Kinetics, and Preferred Phase for Cell Growth ofApplied and environmental microbiology · 2019Article
- Development of an automated wet-cyclone system for rapid, continuous and enriched bioaerosol sampling and its application to real-time detection.Sensors and actuators. B, Chemical · 2019Article
- Digital, Rapid, Accurate, and Label-Free Enumeration of Viable Microorganisms Enabled by Custom-Built On-Glass-Slide Culturing Device and Microscopic Scanning.Sensors (Basel, Switzerland) · 2018Article
- G3 PhyloChip Analysis Confirms the Promise of Plant-Based Culture Media for Unlocking the Composition and Diversity of the Maize Root Microbiome and for Recovering Unculturable Candidate Divisions/Phyla.Microbes and environments · 2018Article
- Colony Fingerprint-Based Discrimination ofSensors (Basel, Switzerland) · 2018Article
- Reducing Uncertainty for Acute Febrile Illness in Resource-Limited Settings: The Current Diagnostic Landscape.The American journal of tropical medicine and hygiene · 2017Review
- Impact of saccharides on the drying kinetics of agarose gels measured by in-situ interferometry.Scientific reports · 2017Article
- Colony fingerprint for discrimination of microbial species based on lensless imaging of microcolonies.PloS one · 2017Article
- General calibration of microbial growth in microplate readers.Scientific reports · 2016Article
Corrections and comments
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Authors and funding
2 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Observing microbial colonies is the standard method for determining the microbe titer and investigating the behaviors of microbes. Here, we report an automated, real-time bacterial microcolony-counting system implemented on a wide field-of-view (FOV), on-chip microscopy platform, termed ePetri. Using sub-pixel sweeping microscopy (SPSM) with a super-resolution algorithm, this system offers the ability to dynamically track individual bacterial microcolonies over a wide FOV of 5.7 mm × 4.3 mm without requiring a moving stage or lens. As a demonstration, we obtained high-resolution time-series images of S. epidermidis at 20-min intervals. We implemented an image-processing algorithm to analyze the spatiotemporal distribution of microcolonies, the development of which could be observed from a single bacterial cell. Test bacterial colonies with a minimum diameter of 20 μm could be enumerated within 6 h. We showed that our approach not only provides results that are comparable to conventional colony-counting assays but also can be used to monitor the dynamics of colony formation and growth. This microcolony-counting system using on-chip microscopy represents a new platform that substantially reduces the detection time for bacterial colony counting. It uses chip-scale image acquisition and is a simple and compact solution for the automation of colony-counting assays and microbe behavior analysis with applications in antibacterial drug discovery.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.