An experimental setup and segmentation method for CFU counting on agar plate for the assessment of drinking water

Quantification of bacterial colonies on an agar plate is a daily routine for a microbiologist to determine the number of viable microorganisms in the sample. In general, microbiologists perform a visual assessment of bacterial colonies which is time-consuming (takes 2 min per plate), tedious, and subjective. Some automatic counting algorithms are developed that save labour and time, but their results are affected by the non-illumination on an agar plate. To improve this, the present manuscript aims to develop an inexpensive and efficient device to acquire S.aureus images via an automatic counting method using image processing techniques under real laboratory conditions. The proposed method (P_ColonyCount) includes the region of interest extraction and color space transformation followed by filtering, thresholding, morphological operation, distance transform, and watershed technique for the quantification of isolated and overlapping colonies. The present work also shows a comparative study on grayscale, K, and green channels by applying different filter and thresholding techniques on 42 images. The results of all channels were compared with the score provided by the expert (manual count). Out of all the proposed method (P_ColonyCount), the K channel gives the best outcome in comparison with the other two channels (grayscale and green) in terms of precision, recall, and F-measure which are 0.99, 0.99, and 0.99 (2 h), 0.98, 0.99, and 0.98 (4 h), and 0.98, 0.98, 0.98 (6 h) respectively. The execution time of the manual and the proposed method (P_ColonyCount) for 42 images ranges from 19 to 113 s and 15 to 31 s respectively. Apart from this, a user-friendly graphical user interface is also developed for the convenient enumeration of colonies without any expert knowledge/training. The developed imaging device will be useful for researchers and teaching lab settings.

A state-of-the-art survey of object detection techniques in microorganism image analysis: from classical methods to deep learning approaches

Microorganisms play a vital role in human life. Therefore, microorganism detection is of great significance to human beings. However, the traditional manual microscopic detection methods have the disadvantages of long detection cycle, low detection accuracy in large orders, and great difficulty in detecting uncommon microorganisms. Therefore, it is meaningful to apply computer image analysis technology to the field of microorganism detection. Computer image analysis can realize high-precision and high-efficiency detection of microorganisms. In this review, first,we analyse the existing microorganism detection methods in chronological order, from traditional image processing and traditional machine learning to deep learning methods. Then, we analyze and summarize these existing methods and introduce some potential methods, including visual transformers. In the end, the future development direction and challenges of microorganism detection are discussed. In general, we have summarized 142 related technical papers from 1985 to the present. This review will help researchers have a more comprehensive understanding of the development process, research status, and future trends in the field of microorganism detection and provide a reference for researchers in other fields.

Image Analysis Semi-Automatic System for Colony-Forming-Unit Counting

Background: Accurate quantitative analysis of microorganisms is recognized as an essential tool for gauging safety and quality in microbiology settings in a wide range of fields. The enumeration process of viable microorganisms via traditional culturing techniques are methodically convenient and cost-effective, conferring high applicability worldwide. However, manual counting can be time-consuming, laborious and imprecise. Furthermore, particular cases require an urgent and accurate response for effective processing. Methods: To reduce time limitations and discrepancies, this work introduces an image processing method capable of semi-automatically quantifying the number of colony forming units (CFUs). This rapid enumeration technique enables the technician to provide an expeditious assessment of the microbial load of a given sample. To test and validate the system, three bacterial species were cultured, and a labeled database was created, with subsequent image acquisition. Results: The system demonstrated acceptable classification measures; the mean values of Accuracy, Recall and F-measure were: (1) 95%, 95% and 0.95 for E. coli; (2) 91%, 91% and 0.90 for P. aeruginosa; and (3) 84%, 86% and 0.85 for S. aureus. Conclusions: Evidence related to the time-saving potential of the system was achieved; the time spent on quantification tasks of plates with a high number of colonies might be reduced to a half and occasionally to a third.

Hagnosa longicapillata, gen. nov., sp. nov., a New Sordariaceous ascomycete in the Indoor Environment, and the Proposal of Hagnosaceae fam. nov

Hagnosa longicapillata, gen. nov., sp. nov, is described and illustrated from wooden building materials collected in Hungary and from pure culture. This species has been collected exclusively from indoor environments, where it was quite common. The ascocarps develop in a thick layer of brown, woolly mats of mycelia. The ostiolar region of the perithecia is ornamented with a five-lobed, flower-shaped crown. Asci are four-spored; ascospores are dark brown, smooth, muriform, not constricted at the septa, and liberated mostly through crackings of the thin ascomatal wall. Apparently, ascospores are dispersed by the mechanical disturbance of the mycelial web. In the phylogenetic tree, Hagnosa samples were placed as a basal lineage, independently from the other family of Sordariomycetidae, with high support. To place Hagnosa in Sordariales, the new family, Hagnosaceae, is proposed.

Application of hyperspectral imaging technology in the rapid identification of microplastics in farmland soil

Microplastics (MPs) are emerging environmental pollutants and their accumulation in the soil can adversely affect the soil biota. This study aims to employ hyperspectral imaging technology for the rapid screening and classification of MPs in farmland soil. In this study, a total of 600 hyperspectral data are collected from 180 sets of farmland soil samples with a hyperspectral imager in the wavelength range of 369- 988 nm. To begin, the hyperspectral data are preprocessed by the Savitzky-Golay (S-G) smoothing filter and mean normalization. Second, principal component analysis (PCA) is used to minimize the dimensions of the hyperspectral data and hence the amount of data, making the subsequent model easier to construct. The cumulative contribution rate of the first three principal components is reached 98.37%, including the main information of the original spectral data. Finally, three models including decision tree (DT), support vector machine (SVM), and convolutional neural network (CNN) are established, all of which can achieve well classification effects on three MP polymers including polyethylene (PE), polypropylene (PP), and polyvinyl chloride (PVC) in farmland soil. By comparing the recognition accuracy of the three models, the classification accuracy of DT and SVM is 87.9% and 85.6%, respectively. The CNN model based on the S-G smoothing filter obtains the best prediction effect, the classification accuracy reaches 92.6%, exhibiting obvious advantages in classification effect. Altogether, these results show that the proposed hyperspectral imaging technique identifies the soil MPs rapidly and nondestructively, and provides an effective automated method for the detection of polymers, requiring only rapid and simple sample preparation.

Computerized fluorescence microscopy of microbial cells

The upgrading of fluorescence microscopy by the introduction of computer technologies has led to the creation of a new methodology, computerized fluorescence microscopy (CFM). CFM improves subjective visualization and combines it with objective quantitative analysis of the microscopic data. CFM has opened up two fundamentally new opportunities for studying microorganisms. The first is the quantitative measurement of the fluorescence parameters of the targeted fluorophores in association with certain structures of individual cells. The second is the expansion of the boundaries of visualization/resolution of intracellular components beyond the "diffraction limit" of light microscopy into the nanometer range. This enables to obtain unique information about the localization and dynamics of intracellular processes at the molecular level. The purpose of this review is to demonstrate the potential of CFM in the study of fundamental aspects of the structural and functional organization of microbial cells. The basics of computer processing and analysis of digital images are briefly described. The fluorescent molecules used in CFM with an emphasis on fluorescent proteins are characterized. The main methods of super-resolution microscopy (nanoscopy) are presented. The capabilities of various CFM methods for exploring microbial cells at the subcellular level are illustrated by the examples of various studies on yeast and bacteria.

Vitamin D Supplementation in Laboratory-Bred Mice: An In Vivo Assay on Gut Microbiome and Body Weight

Saudi Arabia is in a tropical geographical region with a population that has access to adequate diet. There is, however, a high level of vitamin D deficiency in the Kingdom, comorbid with other disease. There is the postulation of a correlation between a healthy gut microbiota and balanced levels of serum vitamin D. This investigation looks into the effect of vitamin D supplementation on the gut flora of laboratory-bred mice as well as any possible association on body weight. BALB/C mice weighing between 34 and 35.8 g were divided into 4 groups and placed on daily doses of vitamin D of 3.75 µg (low dose), 7.5 µg (normal dose), and 15 µg (high dose). The fourth group was the control group that did not receive any supplementation with vitamin D. Body weights were monitored on weekly basis, while faecal samples from the rectum were obtained for microbial culturing and the monitoring of bacterial colony count using the Vitek 2 Compact automated system (BioMerieux, Marcy-l’Etoile, France) according to manufacturer’s guidelines. The data presented as mean ± SD, while significant differences were determined with 2-way analysis of variance in comparing differences within and between treatment groups. The different doses of vitamin D showed varying effects on the body weight and gut microbial colonies of the mice. There was a highly significant difference between the control, 15 µg (high), and 7.5 µg (normal) dose groups. This is suggestive that supplementation with vitamin D could a role in the gut microbial flora in the gut which could reflect in changes in body weight.

Assessment of Microbiological Content of Private and Public Recreational Water Facilities and Their Antimicrobial Susceptibility Pattern in Al-Ahsa

BACKGROUND

Water recreational facilities like swimming pools attract people of all ages. However, these facilities are very suitable for the transmission of various microbial diseases and have been shown to pose public health concerns.

AIMS

This study assesses the presence of different Gram-negative bacteria pathogens and their antimicrobial susceptibility pattern in both private and public pools in Al-Ahsa.

METHODS

11 private and 3 public recreational water facilities were sampled for the study. Collected water samples were inoculated into nutrient broth and incubated aerobically for 24 hours. The overnight growth was plated out on blood and MacConkey agars. Pure cultures of the bacteria samples were used for identification and antimicrobial susceptibility test using the Vitek 2 compactautomated system (BioMerieux, Marcy L'Etoile, France). Minimum inhibitory concentration was also provided by the Vitek 2 compact automated system.

RESULTS

13 different Gram-negative bacteria species isolates were encountered in both pool types sampled. More of potential pathogens were isolated from the private than the public pools, of which Klebsiella pneumoniae and Pseudomonas aeruginosa constituted 50% and 43%, respectively, of all the isolates. Findings also revealed a varied minimum inhibitory concentrations (MICs) indicating that the isolates were of different strains. Antibiotic susceptibility pattern also showed variability among the isolates.

CONCLUSIONS

This study has revealed a potential health risk associated with the use of water recreational facilities. The presence of K pneumoniae and P aeruginosa suggests a public health concern and should be looked into.

Application of Hyperspectral Imaging as a Nondestructive Technique for Foodborne Pathogen Detection and Characterization

Microbial food safety is a persistent and exacting global issue due to the multiplicity and complexity of foods and food production systems. Foodborne illnesses caused by foodborne bacterial pathogens frequently occur, thus endangering the safety and health of human beings. Factors such as pretreatments, that is, culturing, enrichment, amplification make the traditional routine identification and enumeration of large numbers of bacteria in a complex microbial consortium complex, expensive, and time-consuming. Therefore, the need for rapid point-of-use detection systems for foodborne bacterial pathogens with high sensitivity and specificity is crucial in food safety control. Hyperspectral imaging (HSI) as a powerful testing technology provides a rapid, nondestructive approach for pathogen detection. This article reviews some fundamental information about HSI, including instrumentation, data acquisition, image processing, and data analysis-the current application of HSI for the detection, classification, and discrimination of various foodborne pathogens. The merits and demerits of HSI for pathogen detection as well as current and future trends are discussed. Therefore, the purpose of this review is to provide a brief overview of HSI, and further lay emphasis on the emerging trend and importance of this technique for foodborne pathogen detection.

Description of Streptococcus mutans, Streptococcus sanguinis, and Candida albicans biofilms after exposure to propolis dentifrice by using OpenCFU method

Context

Dental caries is a major and chronic dental public health problem, which can usually be prevented by regular oral hygiene. The most common oral hygiene practice is brushing teeth with a dentifrice. Propolis has emerged as a promising anti-cariogenic agent, which is considered to be a good oral antiseptic for prevention of caries. Several studies have shown that the use of C has an influence in the growth of oral biofilms. There are several standard methods used to count bacterial colonies, such as crystal violet and CFU Count assays. OpenCFU method is a technique that can be used to calculate biofilm colonies more faster, precisely, and accurately.

Aim

To compare several methods for evaluating the number of biofilm colonies formed with exposure to a standard dentifrice and propolis.

Methods and materials

Biofilm assays were carried out on 96-well microplates. Reference strains of oral Streptococcus species (S. mutans ATCC 25175^T and S. sanguinis ATCC 10566^T) and yeast (Candida albicans ATCC 10231^T) were inoculated into wells, and 200 µL of standard and propolis dentifrice solution were added to each well and incubated for 18 h at 37 °C. Bacteria and yeast were then sub-cultured on respective media and the colony-forming units (CFU) were counted manually. The other wells were stained by crystal violet and incubated for 15 min, followed by observation using an inverted microscope and evaluated using crystal violet analysis and the OpenCFU automated method.

Results

The numbers of CFUs determined for all strains were similar in the standard-dentifrice group and propolis-dentifrice group, and were similar among the three methods: crystal violet staining, manual CFU count, and OpenCFU analysis.

Conclusion

OpenCFU analysis can be reliably used as a rapid and a more practical method to analyse the growth of oral microorganism biofilms. However, high digital image quality is required to provide an accurate analysis for colony counting.

Estimating Bacterial Concentrations in Fibrous Substrates Through a Combination of Scanning Electron Microscopy and ImageJ

Conventional signal-based microanalytical techniques for estimating bacterial concentrations are often susceptible to false signals. A visual quantification, therefore, may compliment such techniques by providing additional information and support better management decisions in the event of outbreaks. Herein, we explore a method that combines electron microscopy (EM) and image-analysis techniques and allows both visualization and quantification of pathogenic bacteria adherent even to complex nonuniform substrates. Both the estimation and imaging parameters were optimized to reduce the estimation error ( E, %) to close to ±5%. The method was validated against conventional microbiological techniques such as the use of optical density, flow cytometry, and quantitative real-time PCR (qPCR). It could easily be tailored to estimate different species of pathogens, such as Escherichia coli O157, Listeria innocua, Staphylococcus aureus, Enterococcus faecalis, and Bacillus anthracis, on samples similar to those in real-time contamination scenarios. The present method is sensitive enough to detect ∼100 bacterial CFU/mL but has the potential to estimate even lower concentrations with increased imaging and computation times. Overall, this imaging-based method may greatly complement any signal-based pathogen-detection technique, especially in negating false signals, and therefore may significantly contribute to the field of analytical microbiology and biochemistry.

A Changeable Lab-on-a-Chip Detector for Marine Nonindigenous Microorganisms in Ship's Ballast Water

The spread and invasion of many nonindigenous species in the ship's ballast water around the world has been a hazard and threat to ecology, economy, and human health. The rapid and accurate detection of marine invasive species in ship's ballast water is essential. This article is aimed at analysing ballast water quality by means of a changeable microfluidic chip detector thus comply with the D-2 standard of ship's ballast water management and sediment convention. The detection system was designed through the integration of microfluidic chip technology, the impedance pulse sensing and LED light induced chlorophyll fluorescence (LED-LICF) detection. This system can measure the number, size, shape, and volume of targeted microorganisms, and it can also determine the chlorophyll fluorescence intensity, which is an important factor in analysing the activity of phytoplankton. The targeted samples were Chlorella volutis, Dunaliella salina, Platymonas subcordiformis, Chrysophytes, Escherichia coli, and Enterococci. The whole detection or operation can be accomplished through online detection in a few minutes with using micron volume of the sample solution. The valid data outputs are simultaneously displayed in terms of both impedance pulse amplitudes and fluorescent intensity signals. The detection system is designed for multi-sizes real time detection through changing the microchannel sizes on the microfluidic chip. Because it can successfully detect the label-free microorganisms, the system can be applicable to in-situ detections with some modifications to the system.