Counting of bacterial colonies on agar plates is a routine practice to get a rough estimate of the number of viable cells in a sample. The number of colonies in a culture is predominantly manually counted to calculate the concentration of bacteria in the original broth; however, manual counting can be tedious, time-consuming and imprecise. Automation of colony counting has been of increasing interest for many decades, and these methods have been shown to be more consistent than manual counting. Significant limitations of many algorithms used in automated systems are their inability to recognize overlapping colonies as distinct and to count colonies on the plate boundary. This study proposes an interactive counting system and a fully automated system using image processing which overcomes these problems. The proposed system is capable to reduce the manpower and time required for counting while taking account colonies both around the central area and boundary areas of the dish. These systems are part of an application to count colonies based in a mobile phone camera.
TopIntroduction
Bacterial colony is a group of bacteria growing on a plate that is derived from one original starting cell. An agar plate is a sterile Petri dish that contains a growth medium (typically agar plus nutrients) used to culture microorganisms. The growth and maintenance of bacteria on agar plates (Petri dishes) has been a common practice in microbiology.
Individual microorganisms placed on the plate will grow into individual colonies, each a clone genetically identical to the individual ancestor organism. Thus, the plate can be used either to estimate the concentration of organisms in a liquid culture or a suitable dilution of that culture, using a colony counter, or to generate genetically pure cultures from a mixed culture of genetically different organisms.
The Colony Forming Unit (CFU) assay is universally recognized as the gold standard method for measuring the effect of radiation on cell viability, environmental control, food and beverage safety assessment and clinical laboratory exams. A significant example is the monitoring or quality control of drinking water, where bacteria such as Escherichia coli, Enterococcus, Cryptosporidium and faecal coliforms are the main indicator of microbiological water quality for human consumption (EPA, 2006). The culturing process starts by inoculating the strain to be examined on the agar, thus a suspension of the strain is spread over the agar surface. After inoculation, bacterial cultures are incubated to reproduce good conditions for pathogens bacteria growth. Figure 1 shows a Petri dish with several Escherichia coli colonies.
Figure 1.
Escherichia coli bacterial colonies in a Petri dish
The number of colonies in a culture is usually counted manually to calculate the concentration of bacteria based on the assumption that each colony has raised from one single bacterium (colony forming unit, CFU). Bacterial colony counting process is usually performed by well-trained technicians manually. However, there might exist hundreds of colonies in a traditional 100mm Petri dish as shown in Figure 1. Thus, this process is time-consuming (sometimes, the human who counts the colonies need to realize the procedure during many hours or even days), tedious (it is a monotonous procedure) and error prone (with the fatigue, the human being has more tendency to fail the evaluation). The obtained counting results depend on the human conducting the count. This variability is one of the sources of error in the colony counting process that, along with methodological differences between different laboratories or even within a laboratory, can result in considerable fluctuations in results (Bewes, Suchowerska, & Mckenzie, 2008). Due to this, for cultures with high density of colonies, manual counting mostly uses estimation methods, making an extrapolation from a small section of the Petri dish. Automating the detection, counting and analysis of CFU offers significant benefits to eliminate the risk of subjectivity, bias and human error, increasing speed and accuracy, and delivering unprecedented data archiving and retrieval capabilities.
Commercial products exist to facilitate accurate colony counting, ranging from manual counting aids (e.g., counting pens) to all-in-one platforms including image acquisition, processing, and analysis. However, fully automated counting systems also capable of batch processing multiple images at once can be prohibitively expensive for small labs and large facilities may necessitate multiple counting instruments posing a significant budgetary challenge to many laboratories (Putman & Burton, 2005). Yet, with the development of document scanners, mobile phones and digital cameras alternatives to commercial products has been proposed showing that it is not necessary to use costly hardware and imaging system to easily collect the images of bacterial colonies.