Low-cost, high-throughput, automated counting of bacterial colonies

Improved automated spot counting and modeling with bias correction

A complete workflow was presented for estimating the concentration of microorganisms in biological samples by automatically counting spots that represent viral plaque forming units (PFU) bacterial colony forming units (CFU), or spot forming units (SFU) in images, and modeling the counts. The workflow was designed for processing images from dilution series but can also be applied to stand-alone images. The accuracy of the methods was greatly improved by adding a newly developed bias correction method. When the spots in images are densely populated, the probability of spot overlapping increases, leading to systematic undercounting. In this paper, this undercount issue was addressed in an empirical way. The proposed empirical bias correction method utilized synthetic images with known spot sizes and counts as a training set, enabling the development of an effective bias correction function using a thin-plate spline model. Its application focused on the bias correction for the automated spot counting algorithm LoST proposed by Lin et al. Simulation results demonstrated that the empirical bias correction significantly improved spot counts, reducing bias for both fixed and random spot sizes and counts.

U2-Net and ResNet50-Based Automatic Pipeline for Bacterial Colony Counting

In this paper, an automatic colony counting system based on an improved image preprocessing algorithm and convolutional neural network (CNN)-assisted automatic counting method was developed. Firstly, we assembled an LED backlighting illumination platform as an image capturing system to obtain photographs of laboratory cultures. Consequently, a dataset was introduced consisting of 390 photos of agar plate cultures, which included 8 microorganisms. Secondly, we implemented a new algorithm for image preprocessing based on light intensity correction, which facilitated clearer differentiation between colony and media areas. Thirdly, a U2-Net was used to predict the probability distribution of the edge of the Petri dish in images to locate region of interest (ROI), and then threshold segmentation was applied to separate it. This U2-Net achieved an F1 score of 99.5% and a mean absolute error (MAE) of 0.0033 on the validation set. Then, another U2-Net was used to separate the colony region within the ROI. This U2-Net achieved an F1 score of 96.5% and an MAE of 0.005 on the validation set. After that, the colony area was segmented into multiple components containing single or adhesive colonies. Finally, the colony components (CC) were innovatively rotated and the image crops were resized as the input (with 14,921 image crops in the training set and 4281 image crops in the validation set) for the ResNet50 network to automatically count the number of colonies. Our method achieved an overall recovery of 97.82% for colony counting and exhibited excellent performance in adhesion classification. To the best of our knowledge, the proposed "light intensity correction-based image preprocessing→U2-Net segmentation for Petri dish edge→U2-Net segmentation for colony region→ResNet50-based counting" scheme represents a new attempt and demonstrates a high degree of automation and accuracy in recognizing and counting single-colony and multi-colony targets.

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.

GMP manufacture of Shigella flexneri 2a Artificial Invaplex (InvaplexAR) and evaluation in a Phase 1 Open-label, dose escalating study administered intranasally to healthy, adult volunteers

Shigella species cause severe disease among travelers to, and children living in, endemic countries. Although significant efforts have been made to improve sanitation, increased antibiotic resistance and other factors suggest an effective vaccine is a critical need. Artificial Invaplex (InvaplexAR) is a subunit vaccine approach complexing Shigella LPS with invasion plasmid antigens. In pre-clinical studies, the InvaplexAR vaccine demonstrated increased immunogenicity as compared to the first generation product and was subsequently manufactured under cGMP for clinical testing in a first-in-human Phase 1 study. The primary objective of this study was the safety of S. flexneri 2a InvaplexAR given by intranasal (IN) immunization (without adjuvant) in a single-center, open-label, dose-escalating Phase 1 trial and secondarily to assess immunogenicity to identify a dose of InvaplexAR for subsequent clinical evaluations. Subjects received three IN immunizations of InvaplexAR, two weeks apart, in increasing dose cohorts (10 µg, 50 µg, 250 µg, and 500 μg). Adverse events were monitored using symptom surveillance, memory aids, and targeted physical exams. Samples were collected throughout the study to investigate vaccine-induced systemic and mucosal immune responses. There were no adverse events that met vaccination-stopping criteria. The majority (96%) of vaccine-related adverse events were mild in severity (most commonly nasal congestion, rhinorrhea, and post-nasal drip). Vaccination with InvaplexAR induced anti-LPS serum IgG responses and anti-Invaplex IgA and IgG antibody secreting cell (ASC) responses at vaccine doses ≥250 µg. Additionally, mucosal immune responses and functional antibody responses were seen from the serum bactericidal assay measurements. Notably, the responder rates and the kinetics of ASCs and antibody lymphocyte secretion (ALS) were similar, suggesting that either assay may be employed to identify IgG and IgA secreting cells. Further studies with InvaplexAR will evaluate alternative immunization routes, vaccination schedules and formulations to further optimize immunogenicity. (Clinical Trial Registry Number NCT02445963).

High-Content and High-Throughput Clonogenic Survival Assay Using Fluorescence Barcoding

The Clonogenic Survival Assay (CSA) is a fundamental tool employed to assess cell survival and proliferative potential in cancer research. Despite its importance, CSA faces limitations, primarily its time- and labor-intensive nature and its binary output. To overcome these limitations and enhance CSA's utility, several approaches have been developed, focusing on increasing the throughput. However, achieving both high-content and high-throughput analyses simultaneously has remained a challenge. In this paper, we introduce LeGO-CSA, an extension of the classical CSA that employs the imaging of cell nuclei barcoded with fluorescent lentiviral gene ontology markers, enabling both high-content and high-throughput analysis. To validate our approach, we contrasted it with results from a classical assay and conducted a proof-of-concept screen of small-molecule inhibitors targeting various pathways relevant to cancer treatment. Notably, our results indicate that the classical CSA may underestimate clonogenicity and unveil intriguing aspects of clonal cell growth. We demonstrate the potential of LeGO-CSA to offer a robust approach for assessing cell survival and proliferation with enhanced precision and throughput, with promising implications for accelerating drug discovery and contributing to a more comprehensive understanding of cellular behavior in cancer.

Evaluation of an Automated System for the Counting of Microbial Colonies

Counting of microbial colonies is a common technique employed in research and diagnostics. To simplify this tedious and time-consuming process, automated systems have been proposed. This study aimed to elucidate the reliability of automated colony counting. We evaluated a commercially available instrument (UVP ColonyDoc-It Imaging Station) in regard to its accuracy and potential time savings. Suspensions of Staphylococcus aureus, Escherichia coli, Pseudomonas aeruginosa, Klebsiella pneumoniae, Enterococcus faecium, and Candida albicans (n = 20 each) were adjusted to achieve growth of approximately 1,000, 100, 10, and 1 colony per plate, respectively, after overnight incubation on different solid media. Compared with manual counting, each plate was automatically counted by the UVP ColonyDoc-It with and without visual adjustment on a computer display. For all bacterial species and concentrations automatically counted without visual correction, an overall mean difference from manual counts of 59.7%, a proportion of isolates with overestimation/underestimation of colony numbers of 29%/45%, respectively, and only a moderate relationship (R2 = 0.77) with the manual counting were shown. Applying visual correction, the overall mean difference from manual counts was 1.8%, the proportion of isolates with overestimation/underestimation of colony numbers amounted to 2%/42%, respectively, and a strong relationship (R2 = 0.99) with the manual counting was observed. The mean time needed for manual counting compared with automated counting without and with visual correction was 70 s, 30 s, and 104 s, respectively, for bacterial colonies through all concentrations tested. Generally, similar performance regarding accuracy and counting time was observed with C. albicans. In conclusion, fully automatic counting showed low accuracy, especially for plates with very high or very low colony numbers. After visual correction of the automatically generated results, the concordance with manual counts was high; however, there was no advantage in reading time. IMPORTANCE Colony counting is a widely utilized technique in the field of microbiology. The accuracy and convenience of automated colony counters are essential for research and diagnostics. However, there is only sparse evidence on performance and usefulness of such instruments. This study examined the current state of reliability and practicality of the automated colony counting with an advanced modern system. For this, we thoroughly evaluated a commercially available instrument in terms of its accuracy and counting time required. Our findings indicate that fully automatic counting resulted in low accuracy, particularly for plates with very high or very low colony numbers. Visual correction of the automated results on a computer screen improved concordance with manual counts, but there was no benefit in counting time.

A review of open-source image analysis tools for mammalian cell culture: algorithms, features and implementations

Cell culture is undeniably important for multiple scientific applications, including pharmaceuticals, transplants, and cosmetics. However, cell culture involves multiple manual steps, such as regularly analyzing cell images for their health and morphology. Computer scientists have developed algorithms to automate cell imaging analysis, but they are not widely adopted by biologists, especially those lacking an interactive platform. To address the issue, we compile and review existing open-source cell image processing tools that provide interactive interfaces for management and prediction tasks. We highlight the prediction tools that can detect, segment, and track different mammalian cell morphologies across various image modalities and present a comparison of algorithms and unique features of these tools, whether they work locally or in the cloud. This would guide non-experts to determine which is best suited for their purposes and, developers to acknowledge what is worth further expansion. In addition, we provide a general discussion on potential implementations of the tools for a more extensive scope, which guides the reader to not restrict them to prediction tasks only. Finally, we conclude the article by stating new considerations for the development of interactive cell imaging tools and suggesting new directions for future research.

Machine learning for enumeration of cell colony forming units

As one of the most widely used assays in biological research, an enumeration of the bacterial cell colonies is an important but time-consuming and labor-intensive process. To speed up the colony counting, a machine learning method is presented for counting the colony forming units (CFUs), which is referred to as CFUCounter. This cell-counting program processes digital images and segments bacterial colonies. The algorithm combines unsupervised machine learning, iterative adaptive thresholding, and local-minima-based watershed segmentation to enable an accurate and robust cell counting. Compared to a manual counting method, CFUCounter supports color-based CFU classification, allows plates containing heterologous colonies to be counted individually, and demonstrates overall performance (slope 0.996, SD 0.013, 95%CI: 0.97–1.02, p value < 1e-11, r = 0.999) indistinguishable from the gold standard of point-and-click counting. This CFUCounter application is open-source and easy to use as a unique addition to the arsenal of colony-counting tools.

Quantifying biofilm propagation on chemically modified surfaces

Conditions affecting biofilm formation differ among bacterial species and this presents a challenge to studying biofilms in the lab. This work leverages functionalized silanes to control surface chemistry in the study of early biofilm propagation, quantified with a semi-automated image processing algorithm. These methods support the study of Pantoea sp. YR343, a gram-negative bacterium isolated from the poplar rhizosphere. We found that Pantoea sp. YR343 does not readily attach to hydrophilic surfaces but will form biofilms with a “honeycomb” morphology on hydrophobic surfaces. Our image processing algorithm described here quantified the evolution of the honeycomb morphology over time, and found the propagation to display a logarithmic behavior. This methodology was repeated with a flagella-deficient fliR mutant of Pantoea sp. YR343 which resulted in reduced surface attachment. Quantifiable differences between Pantoea WT and ΔfliR biofilm morphologies were captured by the image processing algorithm, further demonstrating the insight gained from these methods.

An Application of Pixel Interval Down-Sampling (PID) for Dense Tiny Microorganism Counting on Environmental Microorganism Images

This paper proposes a novel pixel interval down-sampling network (PID-Net) for dense tiny object (yeast cells) counting tasks with higher accuracy. The PID-Net is an end-to-end convolutional neural network (CNN) model with an encoder–decoder architecture. The pixel interval down-sampling operations are concatenated with max-pooling operations to combine the sparse and dense features. This addresses the limitation of contour conglutination of dense objects while counting. The evaluation was conducted using classical segmentation metrics (the Dice, Jaccard and Hausdorff distance) as well as counting metrics. The experimental results show that the proposed PID-Net had the best performance and potential for dense tiny object counting tasks, which achieved 96.97% counting accuracy on the dataset with 2448 yeast cell images. By comparing with the state-of-the-art approaches, such as Attention U-Net, Swin U-Net and Trans U-Net, the proposed PID-Net can segment dense tiny objects with clearer boundaries and fewer incorrect debris, which shows the great potential of PID-Net in the task of accurate counting.

Methods to monitor bacterial growth and replicative rates at the single-cell level

The heterogeneity of bacterial growth and replicative rates within a population was proposed a century ago notably to explain the presence of bacterial persisters. The term "growth rate" at the single-cell level corresponds to the increase in size or mass of an individual bacterium while the "replicative rate" refers to its division capacity within a defined temporality. After a decades long hiatus, recent technical innovative approaches allow population growth and replicative rates heterogeneity monitoring at the single-cell level resuming in earnest. Among these techniques, the oldest and widely used is time-lapse microscopy, most recently combined with microfluidics. We also discuss recent fluorescence dilution methods informing only on replicative rates and best suited. Some new elegant single cell methods so far only sporadically used such as buoyant mass measurement and stable isotope probing have emerged. Overall, such tools are widely used to investigate and compare the growth and replicative rates of bacteria displaying drug-persistent behaviors to that of bacteria growing in specific ecological niches or collected from patients. In this review, we describe the current methods available, discussing both the type of queries these have been used to answer and the specific strengths and limitations of each method.

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.

Dihydroconiferyl Ferulate Isolated from Dendropanax morbiferus H.Lév. Suppresses Stemness of Breast Cancer Cells via Nuclear EGFR/c-Myc Signaling

Breast cancer is the leading cause of global cancer incidence and breast cancer stem cells (BCSCs) have been identified as the target to overcome breast cancer in patients. In this study, we purified a BCSC inhibitor from Dendropanax morbiferus H.Lév. leaves through several open column and high-performance liquid chromatography via activity-based purification. The purified cancer stem cell (CSC) inhibitor was identified as dihydroconiferyl ferulate using nuclear magnetic resonance and mass spectrometry. Dihydroconiferyl ferulate inhibited the proliferation and mammosphere formation of breast cancer cells and reduced the population of CD44^high/CD24^low cells. Dihydroconiferyl ferulate also induced apoptosis, inhibited the growth of mammospheres and reduced the level of total and nuclear EGFR protein. It suppressed the EGFR levels, the interaction of Stat3 with EGFR, and c-Myc protein levels. Our findings show that dihydroconiferyl ferulate reduced the level of nuclear epidermal growth factor receptor (EGFR) and induced apoptosis of BCSCs through nEGFR/Stat3-dependent c-Myc deregulation. Dihydroconiferyl ferulate exhibits potential as an anti-CSC agent through nEGFR/Stat3/c-Myc signaling.

Immunization of Rabbits with a Quadrivalent Shigella Bioconjugate Vaccine Induces Functional Antibodies Reactive with Shigella Isolates from Kenya

Diarrheal diseases are a leading cause of global morbidity and mortality, disproportionately affecting children in resource-limited settings. Although improvements in hygiene and access to clean water are helpful, vaccines are considered essential due to the low infectious dose of Shigella species and increasing antibiotic resistance. Building on achievements with conjugate vaccines, a safe and immunogenic novel bioconjugate vaccine linking Shigella O-antigen to Pseudomonas aeruginosa exoprotein A has been developed to induce immunity against Shigella flexneri 2a, 3a, and 6 and S. sonnei. This study evaluated the breadth of reactivity and functionality of pooled serum from rabbits immunized with monovalent and quadrivalent Shigella bioconjugates formulated with or without an adjuvant against Shigella serotypes isolated in Kenya. Rabbit sera were assayed by colony blot for reactivity with 67 isolates of Shigella serotypes targeted by the vaccine, S. flexneri (2a, 3a, and 6) and S. sonnei, and 42 isolates of Shigella serotypes not targeted by the vaccine, S. flexneri (1b, 2b, 4a, and 4b), S. boydii, and S. dysenteriae. Shigella isolates testing positive in the colony blot assay were then used to assess functional activity using a bactericidal assay. Of the 41 Shigella isolates targeted by the vaccine, 22 were reactive with the adjuvanted quadrivalent and the respective monovalent rabbit sera. The S. flexneri 2a and 3a monovalent rabbit serum cross-reacted with S. flexneri 3a, 2b, and 2a, respectively. Immunization with the adjuvanted quadrivalent vaccine also induced cross-reactivity with isolates of S. flexneri 2b, 4a, and 4b. Collectively, these results suggest that the Shigella quadrivalent vaccine may be more broadly protective than designed, offering a promising solution to Shigella infections.

IMPORTANCE Diarrheal diseases are the third leading cause of death globally, disproportionally affecting low- to middle-income countries like Kenya, with Shigella species being the leading cause of bacterial diarrhea, especially in children. The low infectious dose and high antibiotic resistance levels complicate treatment, leading to long-term sequelae that necessitate control measures such as vaccines to reduce morbidity and mortality rates, especially among children under 5 years of age. A quadrivalent bioconjugate Shigella vaccine was recently developed to safely and effectively induce immunity against four important Shigella spp. This study demonstrates the breadth of reactivity and functionality of the parenterally administered bioconjugate vaccine by evaluating the ability of rabbit sera to bind and kill Shigella isolates recently collected in Kenya. These results suggest that the Shigella quadrivalent vaccine may be more broadly protective than designed and may offer a promising solution to the morbidity and mortality associated with Shigella infections.

Evaluation of a method to measure fluorescent cell burden in complex culture systems

Purpose. This work introduces and evaluates a method for accurate in-vitro measurement of fluorescent cell burden in complex 3D-culture conditions.Methods.The Fluorescent Cell Burden (FCB) method was developed to analyze the burden of 4T1 mCherry-expressing cells grown in an organotypic co-culture model of brain metastasis using 400μm rat brain slices. As a first step, representative simulated image-data accurately reflecting the 4T1 experimental data, but with known ground truth burden, were created. The FCB method was then developed in the CellProfiler software to measure the integrated intensity and area of the colonies in the simulated image data. Parameters in the pipeline were varied to span the experimentally observed range (e.g. of cell colony size) and the result compared with simulation ground truth to evaluate and optimize FCB performance. The optimized CellProfiler pipeline was then applied to the original 4T1 tumor cell images to determine colony growth with time, and re-applied with upper and lower bound parameters to determine uncertainty estimates.Results.The FCB method measured integrated intensity across 10 simulated images with an accuracy of 99.23% ± 0.75%. When colony density was increased by increasing colony number to 450, 600, and 750, the FCB measurement was 98.68%, 100.9%, 97.6% and 113.5% of the true value respectively. For the increasing number of cells plated on the rat brain slices, the integrated intensity increased nearly linearly with cell count except for at high cell counts, where it is hypothesized that shadowing from clumped cells causes a sub-linear relationship.Conclusion. The FCB method accurately measured an integrated fluorescent light intensity to within 5% of ground truth for a wide range of simulated image data spanning the range of observed variability in experimental data. The method is readily customizable to in-vitro studies requiring estimation of fluorescent tumor cell burden.

A New Few-Shot Learning Method of Bacterial Colony Counting Based on the Edge Computing Device

Bacterial colony counting is a time consuming but important task for many fields, such as food quality testing and pathogen detection, which own the high demand for accurate on-site testing. However, bacterial colonies are often overlapped, adherent with each other, and difficult to precisely process by traditional algorithms. The development of deep learning has brought new possibilities for bacterial colony counting, but deep learning networks usually require a large amount of training data and highly configured test equipment. The culture and annotation time of bacteria are costly, and professional deep learning workstations are too expensive and large to meet portable requirements. To solve these problems, we propose a lightweight improved YOLOv3 network based on the few-shot learning strategy, which is able to accomplish high detection accuracy with only five raw images and be deployed on a low-cost edge device. Compared with the traditional methods, our method improved the average accuracy from 64.3% to 97.4% and decreased the False Negative Rate from 32.1% to 1.5%. Our method could greatly improve the detection accuracy, realize the portability for on-site testing, and significantly save the cost of data collection and annotation over 80%, which brings more potential for bacterial colony counting.

Scan4CFU: Low-cost, open-source bacterial colony tracking over large areas and extended incubation times

A hallmark of bacterial populations cultured in vitro is their homogeneity of growth, where the majority of cells display identical growth rate, cell size and content. Recent insights, however, have revealed that even cells growing in exponential growth phase can be heterogeneous with respect to variables typically used to measure cell growth. Bacterial heterogeneity has important implications for how bacteria respond to environmental stresses, such as antibiotics. The phenomenon of antimicrobial persistence, for example, has been linked to a small subpopulation of cells that have entered into a state of dormancy where antibiotics are no longer effective. While methods have been developed for identifying individual non-growing cells in bacterial cultures, there has been less attention paid to how these cells may influence growth in colonies on a solid surface. In response, we have developed a low-cost, open-source platform to perform automated image capture and image analysis of bacterial colony growth on multiple nutrient agar plates simultaneously. The descriptions of the hardware and software are included, along with details about the temperature-controlled growth chamber, high-resolution scanner, and graphical interface to extract and plot the colony lag time and growth kinetics. Experiments were conducted using a wild type strain of Escherichia coli K12 to demonstrate the feasibility and operation of our setup. By automated tracking of bacterial growth kinetics in colonies, the system holds the potential to reveal new insights into understanding the impact of microbial heterogeneity on antibiotic resistance and persistence.

A comprehensive review of image analysis methods for microorganism counting: from classical image processing to deep learning approaches

Microorganisms such as bacteria and fungi play essential roles in many application fields, like biotechnique, medical technique and industrial domain. Microorganism counting techniques are crucial in microorganism analysis, helping biologists and related researchers quantitatively analyze the microorganisms and calculate their characteristics, such as biomass concentration and biological activity. However, traditional microorganism manual counting methods, such as plate counting method, hemocytometry and turbidimetry, are time-consuming, subjective and need complex operations, which are difficult to be applied in large-scale applications. In order to improve this situation, image analysis is applied for microorganism counting since the 1980s, which consists of digital image processing, image segmentation, image classification and suchlike. Image analysis-based microorganism counting methods are efficient comparing with traditional plate counting methods. In this article, we have studied the development of microorganism counting methods using digital image analysis. Firstly, the microorganisms are grouped as bacteria and other microorganisms. Then, the related articles are summarized based on image segmentation methods. Each part of the article is reviewed by methodologies. Moreover, commonly used image processing methods for microorganism counting are summarized and analyzed to find common technological points. More than 144 papers are outlined in this article. In conclusion, this paper provides new ideas for the future development trend of microorganism counting, and provides systematic suggestions for implementing integrated microorganism counting systems in the future. Researchers in other fields can refer to the techniques analyzed in this paper.

Inexpensive Apparatus for High-Quality Imaging of Microbial Growth on Agar Plates

The ability to capture images of results or processes is an important tool in the biologist’s tool kit. In microbiology, capturing high-quality images of microbial growth on agar plates is difficult due to the reflective surface of the plates and limitations in common photography techniques. Equipment is available to overcome these challenges, but acquisition costs are high. We have developed and tested an inexpensive and efficient apparatus for high-quality imaging of microbial colonies. The imaging box, as we have named the apparatus, is designed to eliminate glare and reduce reflections on the surface of the plate while providing uniform, diffuse light from all sides. The imaging box was used to capture hundreds of images in research and teaching lab settings.

5-Desmethylsinensetin isolated from Artemisia princeps suppresses the stemness of breast cancer cells via Stat3/IL-6 and Stat3/YAP1 signaling

AIMS

To study 5-desmethylsinensetin exhibiting potential anticancer activity against breast cancer stem cells and the related molecular mechanism.

MAIN METHODS

In this study, isolation of a cancer stem cell (CSC) inhibitor of Artemisia princeps was performed using a silica gel column, a Sephadex gel column, and high-performance liquid chromatography. A single compound was purified via activity-based isolation using mammosphere formation assays. An MTS was used to examine the proliferation of breast cancer cells, and flow cytometry was used to analyze apoptosis and cancer stem cell markers. Western blotting was used to detect the signaling pathway.

RESULTS

The isolated compound was identified as 5-desmethylsinensetin using nuclear magnetic resonance and mass spectrometry. 5-Desmethylsinensetin suppresses the proliferation and mammosphere formation of breast cancer cells, reduces the subpopulations of CD44⁺/CD24^- and ALDH1⁺ cancer cells, and reduces the transcription of the stemness markers Oct4, c-Myc, Nanog and CD44 in Breast CSCs. 5-Desmethylsinensetin inhibits the total and nuclear expression of Stat3 and p-Stat3, as well as the translocation of YAP1. Additionally, 5-desmethylsinensetin reduces the mRNA and protein levels of IL-6.

CONCLUSION

Our results show that 5-desmethylsinensetin exhibits potential anticancer activity against breast cancer stem cells via Stat3-IL-6 and Stat3-YAP1 signaling.

Immune response characterization in a human challenge study with a Shigella flexneri 2a bioconjugate vaccine

BACKGROUND

Diarrheal diseases are a leading cause of global morbidity and mortality affecting all ages, but especially children under the age of five in resource-limited settings. Shigella is a leading contributor to diarrheal diseases caused by bacterial pathogens and is considered a significant antimicrobial resistance threat. While improvements in hygiene, and access to clean water help as control measures, vaccination remains one of the most viable options for significantly reducing morbidity and mortality.

METHODS

Flexyn2a is a bioconjugate vaccine manufactured using novel conjugation methodologies enzymatically linking the O-polysaccharide of S. flexneri 2a to exotoxin A of Pseudomonas aeruginosa. The protective capacity of Flexyn2a was assessed in a controlled human infection model after two intramuscular immunizations. Immune responses pre- and post-immunization and/or infection were investigated and are described here.

FINDINGS

Flexyn2a induced lipopolysaccharide (LPS)-specific serum IgG responses post-immunization which were associated with protection against shigellosis. Additionally, several other immune parameters, including memory B cell responses, bactericidal antibodies and serum IgA, were also elevated in vaccinees protected against shigellosis. Immunization with Flexyn2a also induced gut-homing, LPS-specific IgG and IgA secreting B cells, indicating the vaccine induced immune effectors functioning at the site of intestinal infection.

INTERPRETATION

Collectively, the results of these immunological investigations provide insights into protective immune mechanisms post-immunization with Flexyn2a which can be used to further guide vaccine development and may have applicability to the larger Shigella vaccine field.

FUNDING

Funding for this study was provided through a Wellcome Trust grant.

TASBE Image Analytics: A Processing Pipeline for Quantifying Cell Organization from Fluorescent Microscopy

Laboratory automation now commonly allows high-throughput sample preparation, culturing, and acquisition of microscopy images, but quantitative image analysis is often still a painstaking and subjective process. This is a problem especially significant for work on programmed morphogenesis, where the spatial organization of cells and cell types is of paramount importance. To address the challenges of quantitative analysis for such experiments, we have developed TASBE Image Analytics, a software pipeline for automatically segmenting collections of cells using the fluorescence channels of microscopy images. With TASBE Image Analytics, collections of cells can be grouped into spatially disjoint segments, the movement or development of these segments tracked over time, and rich statistical data output in a standardized format for analysis. Processing is readily configurable, rapid, and produces results that closely match hand annotation by humans for all but the smallest and dimmest segments. TASBE Image Analytics can thus provide the analysis necessary to complete the design-build-test-learn cycle for high-throughput experiments in programmed morphogenesis, as validated by our application of this pipeline to process experiments on shape formation with engineered CHO and HEK293 cells.

The Antiasthma Medication Ciclesonide Suppresses Breast Cancer Stem Cells through Inhibition of the Glucocorticoid Receptor Signaling-Dependent YAP Pathway

Ciclesonide is an FDA-approved glucocorticoid used to treat asthma and allergic rhinitis. However, whether it has anticancer and anti-cancer stem cell (CSC) effects is unknown. This study focused on investigating the effect of ciclesonide on breast cancer and CSCs and determining its underlying mechanism. Here, we showed that ciclesonide inhibits breast cancer and CSC formation. Similar glucocorticoids-dexamethasone and prednisone-did not inhibit CSC formation. Ciclesonide-induced glucocorticoid receptor (GR) degradation was dependent on ubiquitination. We showed via GR small interfering RNA (siRNA) that GR plays an important role in CSC formation. We showed via western blot and immunofluorescence assays that ciclesonide reduces the nuclear level of GR. The GR antagonist RU-486 also inhibited CSC formation. Ciclesonide reduced the protein level of the Hippo transducer Yes-associated protein (YAP). GR siRNA induced a decrease in YAP protein expression and inhibited mammosphere formation. The YAP inhibitor verteporfin inhibited CSC formation and transcription of the connective tissue growth factor and cysteine-rich protein 61 genes. The GR/YAP1 pathway regulated breast CSC formation. We showed that the GR/YAP signaling pathway regulates breast CSC formation and revealed a new approach for targeting GR and YAP to inhibit CSC formation.

Plant Volatile, Phenylacetaldehyde Targets Breast Cancer Stem Cell by Induction of ROS and Regulation of Stat3 Signal

Cancer stem cells (CSCs) are undifferentiated cells that give rise to tumor and resistance to chemotherapy. This study reports that phenylacetaldehyde (PAA), a flower flavor, inhibits formation on breast CSCs. PAA showed anti-proliferation and increased apoptosis of breast cancer. PAA also reduced tumor growth in an in vivo mice model. PAA reduced the CD44⁺/CD24⁻ and ALDH1-expressing cells, mammosphere formation, and CSC marker genes. PAA preferentially induced reactive oxygen species (ROS) production and combined treatment with PAA and N-acetyl cysteine (NAC) decreased inhibition of mammosphere formation. PAA reduced phosphorylation of nuclear Stat3. PAA inhibited Stat3 signaling through de-phosphorylation of Stat3 and reduced secretory IL-6. Our results suggest that the PAA-induced ROS deregulated Stat3/IL-6 pathway and PAA may be a potential agent targeting breast cancer and CSCs.

Efficient microbial colony growth dynamics quantification with ColTapp, an automated image analysis application

Populations of genetically identical bacteria are phenotypically heterogeneous, giving rise to population functionalities that would not be possible in homogeneous populations. For instance, a proportion of non-dividing bacteria could persist through antibiotic challenges and secure population survival. This heterogeneity can be studied in complex environmental or clinical samples by spreading the bacteria on agar plates and monitoring time to growth resumption in order to infer their metabolic state distribution. We present ColTapp, the Colony Time-lapse application for bacterial colony growth quantification. Its intuitive graphical user interface allows users to analyze time-lapse images of agar plates to monitor size, color and morphology of colonies. Additionally, images at isolated timepoints can be used to estimate lag time. Using ColTapp, we analyze a dataset of Staphylococcus aureus time-lapse images including populations with heterogeneous lag time. Colonies on dense plates reach saturation early, leading to overestimation of lag time from isolated images. We show that this bias can be corrected by taking into account the area available to each colony on the plate. We envision that in clinical settings, improved analysis of colony growth dynamics may help treatment decisions oriented towards personalized antibiotic therapies.

Immune Response Characterization after Controlled Infection with Lyophilized Shigella sonnei 53G

Shigella is a major cause of moderate to severe diarrhea largely affecting children (<5 years old) living in low- and middle-income countries. Several vaccine candidates are in development, and controlled human infection models (CHIMs) can be useful tools to provide an early assessment of vaccine efficacy and potentially support licensure. A lyophilized strain of S. sonnei 53G was manufactured and evaluated to establish a dose that safely and reproducibly induced a ≥60% attack rate. Samples were collected pre- and postchallenge to assess intestinal inflammatory responses, antigen-specific serum and mucosal antibody responses, functional antibody responses, and memory B cell responses. Infection with S. sonnei 53G induced a robust intestinal inflammatory response as well as antigen-specific antibodies in serum and mucosal secretions and antigen-specific IgA- and IgG-secreting B cells positive for the α4β7 gut-homing marker. There was no association between clinical disease outcomes and systemic or functional antibody responses postchallenge; however, higher lipopolysaccharide (LPS)-specific serum IgA- and IgA-secreting memory B cell responses were associated with a reduced risk of disease postchallenge. This study provides unique insights into the immune responses pre- and postinfection with S. sonnei 53G in a CHIM, which could help guide the rational design of future vaccines to induce protective immune responses more analogous to those triggered by infection.IMPORTANCE Correlate(s) of immunity have yet to be defined for shigellosis. As previous disease protects against subsequent infection in a serotype-specific manner, investigating immune response profiles pre- and postinfection provides an opportunity to identify immune markers potentially associated with the development of protective immunity and/or with a reduced risk of developing shigellosis postchallenge. This study is the first to report such an extensive characterization of the immune response after challenge with S. sonnei 53G. Results demonstrate an association of progression to shigellosis with robust intestinal inflammatory and mucosal gut-homing responses. An important finding in this study was the association of elevated Shigella LPS-specific serum IgA and memory B cell IgA responses at baseline with reduced risk of disease. The increased baseline IgA responses may contribute to the lack of dose response observed in the study and suggests that IgA responses should be further investigated as potential correlates of immunity.

6-Methoxymellein Isolated from Carrot (Daucus carota L.) Targets Breast Cancer Stem Cells by Regulating NF-κB Signaling

The presence of breast cancer stem cells (BCSCs) induces the aggressive progression and recurrence of breast cancer. These cells are drug resistant, have the capacity to self-renew and differentiate and are involved in recurrence and metastasis, suggesting that targeting BCSCs may improve treatment efficacy. In this report, methanol extracts of carrot root were purified by means of silica gel, Sephadex LH-20, and preparative high-performance liquid chromatography to isolate a compound targeting mammosphere formation. We isolated the compound 6-methoxymellein, which inhibits the proliferation and migration of breast cancer cells, reduces mammosphere growth, decreases the proportion of CD44⁺/CD24⁻ cells in breast cancer cells and decreases the expression of stemness-associated proteins c-Myc, Sox-2 and Oct4. 6-Methoxymellein reduces the nuclear localization of nuclear factor-κB (NF-κB) subunit p65 and p50. Subsequently, 6-methoxymellein decreases the mRNA transcription and secretion of IL-6 and IL-8. Our data suggest that 6-methoxymellein may be an anticancer agent that inhibits BCSCs via NF-κB/IL-6 and IL-8 regulation.

Liposomal dexamethasone-moxifloxacin nanoparticle combinations with collagen/gelatin/alginate hydrogel for corneal infection treatment and wound healing

Infectious keratitis is still one of the major causes of visual impairment and blindness, often affecting developing countries. Eye-drop therapy to reduce disease progression is the first line of treatment for infectious keratitis. The current limitations in controlling ophthalmic infections include rapid precorneal drug loss and the inability to provide long-term extraocular drug delivery. The aim of the present study was to develop a novel ophthalmic formulation to treat corneal infection. The formulation was prepared by constructing moxifloxacin (MFX) and dexamethasone (DEX)-loaded nanostructured lipid carriers (Lipo-MFX/DEX) mixed with a collagen/gelatin/alginate (CGA) biodegradable material (CGA-Lipo-MFX/DEX) for prolonged ocular application. The characteristics of the prepared Lipo-MFX/DEX nanoparticles were as follows: average size, 132.1 ± 73.58 nm; zeta potential, -6.27 ± 4.95 mV; entrapment efficiency, 91.5 ± 3.5%; drug content, 18.1 ± 1.7%. Our results indicated that CGA-Lipo-MFX/DEX could release an effective working concentration in 60 min and sustain the drug release for at least 12 h. CGA-Lipo-MFX/DEX did not produce significant toxicities, but it increased cell numbers when co-cultured with ocular epithelial cells. An animal study also confirmed that CGA-Lipo-MFX/DEX could inhibit pathogen microorganism growth and improve corneal wound healing. Our results suggest that CGA-Lipo-MFX/DEX could be a useful anti-inflammatory formulation for ophthalmological disease treatment.

Betavulgarin Isolated from Sugar Beet (Beta vulgaris) Suppresses Breast Cancer Stem Cells through Stat3 Signaling

Breast cancer is a major health problem that affects lives worldwide. Breast cancer stem cells (BCSCs) are small subpopulations of cells with capacities for drug resistance, self-renewal, recurrence, metastasis, and differentiation. Herein, powder extracts of beetroot were subjected to silica gel, gel filtration, thin layer chromatography (TLC), and preparatory high-pressure liquid chromatography (HPLC) for isolation of one compound, based on activity-guided purification using tumorsphere formation assays. The purified compound was identified as betavulgarin, using nuclear magnetic resonance spectroscopy and electrospray ionization (ESI) mass spectrometry. Betavulgarin suppressed the proliferation, migration, colony formation, and mammosphere formation of breast cancer cells and reduced the size of the CD44⁺/CD24⁻ subpopulation and the expression of the self-renewal-related genes, C-Myc, Nanog, and Oct4. This compound decreased the total level and phosphorylated nuclear level of signal transducer and activator of transcription 3 (Stat3) and reduced the mRNA and protein levels of sex determining region Y (SRY)-box 2 (SOX2), in mammospheres. These data suggest that betavulgarin inhibit the Stat3/Sox2 signaling pathway and induces BCSC death, indicating betavulgarin might be an anticancer agent against breast cancer cells and BCSCs.

Experimental setup and image processing method for automatic enumeration of bacterial colonies on agar plates

Automated colony counting methods have long been known in Microbiology. Numerous methods for automated image analysis have been described and a wide range of commercial products exists. Known advantages are saving cost by reducing enumeration time, automatic documentation, reproducibility, and operator independence. Still, even today the realization of all advantages of automated image analysis makes it necessary to either invest in an expensive, high performance commercial system, or to acquire expert knowledge in image processing. This is a considerable obstacle for many laboratories, and the reason why manual colony counting is still done frequently. This article describes an easy to apply automatic colony counting system–including suggestions for sample preparation–that can be put into operation with basic knowledge of image processing and low budget.

Caudatin Isolated from Cynanchum auriculatum Inhibits Breast Cancer Stem Cell Formation via a GR/YAP Signaling

In the complex tumor microenvironment, cancer stem cells (CSCs), a rare population of cells, are responsible for malignant tumor initiation, metastasis, drug resistance and recurrence. Controlling breast CSCs (BCSCs) using natural compounds is a novel potential therapeutic strategy for clinical cancer treatment. In this study, a mammosphere assay-guided isolation protocol including silica gel, a C18 column, gel filtration, and high-pressure liquid chromatography was used to isolate an inhibitory compound from Cynanchum auriculatum extracts. The isolated inhibitory compound was identified as caudatin. Caudatin inhibited breast cancer cell proliferation, mammosphere formation and tumor growth. Caudatin decreased the CD44⁺/CD24⁻ and aldehyde dehydrogenase⁺ cell proportions and the levels of c-Myc, Oct4, Sox2, and CD44. Caudatin induced ubiquitin (Ub)-dependent glucocorticoid receptor (GR) degradation and blocked subsequent Yes-associated protein (YAP) nuclear accumulation and target gene transcription signals in BCSCs. These results show that the GR/YAP signaling pathway regulates BCSC formation and that caudatin may be a potential chemopreventive agent that targets breast cancer cells and CSCs.

Inhibitory Effects of Tangeretin, A Citrus Peel-Derived Flavonoid, on Breast Cancer Stem Cell Formation through Suppression of Stat3 Signaling

Breast cancer stem cells (BCSCs) are responsible for tumor chemoresistance and recurrence. Targeting CSCs using natural compounds is a novel approach for cancer therapy. A CSC-inhibiting compound was purified from citrus extracts using silica gel, gel filtration and high-pressure liquid chromatography. The purified compound was identified as tangeretin by using nuclear magnetic resonance (NMR). Tangeretin inhibited cell proliferation, CSC formation and tumor growth, and modestly induced apoptosis in CSCs. The frequency of a subpopulation with a CSC phenotype (CD44⁺/CD24^-) was reduced by tangeretin. Tangeretin reduced the total level and phosphorylated nuclear level of signal transducer and activator of transcription 3 (Stat3). Our results in this study show that tangeretin inhibits the Stat3 signaling pathway and induces CSC death, indicating that tangeretin may be a potential natural compound that targets breast cancer cells and CSCs.

MF2C3: Multi-Feature Fuzzy Clustering to Enhance Cell Colony Detection in Automated Clonogenic Assay Evaluation

A clonogenic assay is a biological technique for calculating the Surviving Fraction (SF) that quantifies the anti-proliferative effect of treatments on cell cultures: this evaluation is often performed via manual counting of cell colony-forming units. Unfortunately, this procedure is error-prone and strongly affected by operator dependence. Besides, conventional assessment does not deal with the colony size, which is generally correlated with the delivered radiation dose or administered cytotoxic agent. Relying upon the direct proportional relationship between the Area Covered by Colony (ACC) and the colony count and size, along with the growth rate, we propose MF2C3, a novel computational method leveraging spatial Fuzzy C-Means clustering on multiple local features (i.e., entropy and standard deviation extracted from the input color images acquired by a general-purpose flat-bed scanner) for ACC-based SF quantification, by considering only the covering percentage. To evaluate the accuracy of the proposed fully automatic approach, we compared the SFs obtained by MF2C3 against the conventional counting procedure on four different cell lines. The achieved results revealed a high correlation with the ground-truth measurements based on colony counting, by outperforming our previously validated method using local thresholding on L*u*v* color well images. In conclusion, the proposed multi-feature approach, which inherently leverages the concept of symmetry in the pixel local distributions, might be reliably used in biological studies.

Machilin D, a Lignin Derived from Saururus chinensis, Suppresses Breast Cancer Stem Cells and Inhibits NF-κB Signaling

Cancer stem cells are responsible for breast cancer initiation, metastasis, and relapse. Targeting breast cancer stem cells (BCSCs) using phytochemicals is a good strategy for the treatment of cancer. A silica gel, a reversed-phase C18 column (ODS), a Sephadex LH-20 gel, thin layer chromatography, and high-performance liquid chromatography (HPLC) were used for compound isolation from Saururus chinensis extracts. The isolated compound was identified as machilin D by mass spectrometry and nuclear magnetic resonance (NMR). Machilin D inhibited the growth and mammosphere formation of breast cancer cells and inhibited tumor growth in a xenograft mouse model. Machilin D reduced the proportions of CD44⁺/CD24^- and aldehyde dehydrogenase 1 (ALDH1)-positive cells. Furthermore, this compound reduced the nuclear localization of the NF-κB protein and decreased the IL-6 and IL-8 secretion in mammospheres. These results suggest that machilin D blocks IL-6 and IL-8 signaling and induces CSC death and thus may be a potential agent targeting BCSCs.

The FDA-Approved Anti-Asthma Medicine Ciclesonide Inhibits Lung Cancer Stem Cells through Hedgehog Signaling-Mediated SOX2 Regulation

Ciclesonide is an FDA-approved glucocorticoid (GC) used to treat asthma and allergic rhinitis. However, its effects on cancer and cancer stem cells (CSCs) are unknown. Our study focuses on investigating the inhibitory effect of ciclesonide on lung cancer and CSCs and its underlying mechanism. In this study, we showed that ciclesonide inhibits the proliferation of lung cancer cells and the growth of CSCs. Similar glucocorticoids, such as dexamethasone and prednisone, do not inhibit CSC formation. We show that ciclesonide is important for CSC formation through the Hedgehog signaling pathway. Ciclesonide reduces the protein levels of GL1, GL2, and Smoothened (SMO), and a small interfering RNA (siRNA) targeting SMO inhibits tumorsphere formation. Additionally, ciclesonide reduces the transcript and protein levels of SOX2, and an siRNA targeting SOX2 inhibits tumorsphere formation. To regulate breast CSC formation, ciclesonide regulates GL1, GL2, SMO, and SOX2. Our results unveil a novel mechanism involving Hedgehog signaling and SOX2 regulated by ciclesonide in lung CSCs, and also open up the possibility of targeting Hedgehog signaling and SOX2 to prevent lung CSC formation.

The PAK1-Stat3 Signaling Pathway Activates IL-6 Gene Transcription and Human Breast Cancer Stem Cell Formation

Cancer stem cells (CSCs) have unique properties, including self-renewal, differentiation, and chemoresistance. In this study, we found that p21-activated kinase (PAK1) inhibitor (Group I, PAK inhibitor, IPA-3) and inactivator (ivermectin) treatments inhibit cell proliferation and that tumor growth of PAK1-knockout cells in a mouse model is significantly reduced. IPA-3 and ivermectin inhibit CSC formation. PAK1 physically interacts with Janus Kinase 2 (JAK2), and JAK2 inhibitor (TG101209) treatment inhibits mammosphere formation and reduces the nuclear PAK1 protein level. PAK1 interacts with signal transducer and activator of transcription 3 (Stat3), and PAK1 and Stat3 colocalize in the nucleus. We show through electrophoretic mobility shift assay (EMSA), chromatin immunoprecipitation (ChIP), and reporter assays that the PAK1/Stat3 complex binds to the IL-6 promoter and regulates the transcription of the IL-6 gene. Inhibition of PAK1 and JAK2 in mammospheres reduces the nuclear pStat3 and extracellular IL-6 levels. PAK1 inactivation inhibits CSC formation by decreasing pStat3 and extracellular IL-6 levels. Our results reveal that JAK2/PAK1 dysregulation inhibits the Stat3 signaling pathway and CSC formation, the PAK1/Stat3 complex regulates IL-6 gene expression, PAK1/Stat3 signaling regulates CSC formation, and PAK1 may be an important target for treating breast cancer.

Disruption of the NF-κB/IL-8 Signaling Axis by Sulconazole Inhibits Human Breast Cancer Stem Cell Formation

Breast cancer stem cells (BCSCs) are tumor-initiating cells that possess the capacity for self-renewal. Cancer stem cells (CSCs) are responsible for poor outcomes caused by therapeutic resistance. In our study, we found that sulconazole—an antifungal medicine in the imidazole class—inhibited cell proliferation, tumor growth, and CSC formation. This compound also reduced the frequency of cells expressing CSC markers (CD44^high/CD24^low) as well as the expression of another CSC marker, aldehyde dehydrogenase (ALDH), and other self-renewal-related genes. Sulconazole inhibited mammosphere formation, reduced the protein level of nuclear NF-κB, and reduced extracellular IL-8 levels in mammospheres. Knocking down NF-κB expression using a p65-specific siRNA reduced CSC formation and secreted IL-8 levels in mammospheres. Sulconazole reduced nuclear NF-κB protein levels and secreted IL-8 levels in mammospheres. These new findings show that sulconazole blocks the NF-κB/IL-8 signaling pathway and CSC formation. NF-κB/IL-8 signaling is important for CSC formation and may be an important therapeutic target for BCSC treatment.

Measuring quantity and function of pneumococcal antibodies in immunoglobulin products

BACKGROUND

Immunoglobulin replacement therapy is a cornerstone of the treatment of primary immunodeficiencies. Preparations used for replacement therapy are processed by purifying immunoglobulins from large pools of plasma, which were obtained from healthy donors. The constituent antibodies in these products depend on the immune history of the donor pool as well as manufacturing processes that differ among manufacturers. For these reasons various methods have been proposed to examine the levels and function of antibodies to organisms such as Streptococcus pneumoniae, which frequently causes infections in patients with immunodeficiencies. Pneumococcal antibody levels or antibody function can be measured with enzyme-linked immunosorbent assay (ELISA) or multiplexed opsonophagocytosis assay (MOPA). Although these assays were developed initially to assess the immunogenicity of pneumococcal vaccines, the techniques have been adapted to evaluate immunoglobulin products as well.

STUDY DESIGN AND METHODS

This article provides a concise review of the analytic techniques for measuring pneumococcal antibodies and prior studies of immunoglobulin products utilizing these methods.

RESULTS

Studies utilizing these assays have demonstrated that antibody levels of immunoglobulin products can vary with time, location, and manufacturer.

CONCLUSIONS

We highlight current issues and future considerations concerning measurement of pneumococcal antibodies in immunoglobulin products, and the assays used for this purpose.

Opsonophagocytic Killing Assay to Assess Immunological Responses Against Bacterial Pathogens

A key aspect of the immune response to bacterial colonization of the host is phagocytosis. An opsonophagocytic killing assay (OPKA) is an experimental procedure in which phagocytic cells are co-cultured with bacterial units. The immune cells will phagocytose and kill the bacterial cultures in a complement-dependent manner. The efficiency of the immune-mediated cell killing is dependent on a number of factors and can be used to determine how different bacterial cultures compare with regard to resistance to cell death. In this way, the efficacy of potential immune-based therapeutics can be assessed against specific bacterial strains and/or serotypes. In this protocol, we describe a simplified OPKA that utilizes basic culture conditions and cell counting to determine bacterial cell viability after co-culture with treatment conditions and HL-60 immune cells. This method has been successfully utilized with a number of different pneumococcal serotypes, capsular and acapsular strains, and other bacterial species. The advantages of this OPKA protocol are its simplicity, versatility (as this assay is not limited to antibody treatments as opsonins), and minimization of time and reagents to assess basic experimental groups.

Dihydrotanshinone-Induced NOX5 Activation Inhibits Breast Cancer Stem Cell through the ROS/Stat3 Signaling Pathway

Cancer stem cells (CSCs) are known to mediate metastasis and recurrence and are therefore a promising therapeutic target. In this study, we found that dihydrotanshinone (DHTS) inhibits CSC formation. DHTS inhibited mammosphere formation in a dose-dependent manner and showed significant tumor growth inhibition in a xenograft model. This compound reduced the CD44^high/CD24^low- and aldehyde dehydrogenase- (ALDH-) expressing cell population and the self-renewal-related genes Nanog, SOX2, OCT4, C-Myc, and CD44. DHTS induced NOX5 activation by increasing calcium, and NOX5 activation induced reactive oxygen species (ROS) production. ROS production reduced the nuclear phosphorylation levels of Stat3 and secreted IL-6 levels in the mammospheres. DHTS deregulated the dynamic equilibrium from non-stem cancer cells to CSCs by dephosphorylating Stat3 and decreasing IL-6 secretion and inhibiting CSC formation. These novel findings showed that DHTS-induced ROS deregulated the Stat3/IL-6 pathway and induced CSC death. NOX5 activation by DHTS inhibits CSC formation through ROS/Stat3/IL-6 signaling, and DHTS may be a promising potential therapeutic agent against breast CSCs.

Automated counting of bacterial colonies on agar plates based on images captured at near-infrared light

Counting colonies is usually used in microbiological analysis to assess if samples meet microbiological criteria. Although manual counting remains gold standard, the process is subjective, tedious, and time-consuming. Some developed automatic counting methods could save labors and time, but their results are easily affected by uneven illumination and reflection of visible light. To offer a method which counts colonies automatically and is robust to light, we constructed a convenient and cost-effective system to obtain images of colonies at near-infrared light, and proposed an automatic method to detect and count colonies by processing images. The colonies cultured by using raw cows' milk were used as identification objects. The developed system mainly consisted of a visible/near-infrared camera and a circular near-infrared illuminator. The automatic method proposed to count colonies includes four steps, i.e., eliminating noises outside agar plate, removing plate rim and wall, identifying and separating clustered or overlapped colonies, and counting colonies by using connected region labelling, distance transform, and watershed algorithms, etc. A user-friendly graphic user interface was also developed for the proposed method. The relative error and counting time of the automatic counting method were compared with those of manual counting. The results showed that the relative error of the automatic counting method was -7.4%~ + 8.3%, with average relative error of 0.2%, and the time used for counting colonies on each agar plate was 11-21 s, which was 15-75% of the time used in manual counting, depending on the numbers of colonies on agar plates. The proposed system and automatic counting method demonstrate promising performance in terms of precision, and they are robust and efficient in terms of labor- and time-savings.

Development, Interlaboratory Evaluations, and Application of a Simple, High-Throughput Shigella Serum Bactericidal Assay

Shigella is an important cause of diarrhea worldwide, and efforts are ongoing to produce a safe and effective Shigella vaccine. Although a clear immune correlate of protection has not been established, antibodies with bactericidal capacity may provide one means of protecting against shigellosis. Thus, it is important to measure the functional capacity of antibodies, as opposed to only binding activity. This article describes a simple, robust, and high-throughput serum bactericidal assay capable of measuring Shigella-specific functional antibodies in vitro. We show for the first time that this assay was successfully performed by multiple laboratories and generated highly comparable results, particularly when SBA titers were normalized using a reference standard. The serum bactericidal assay, along with a reference serum, should greatly facilitate Shigella vaccine development.

Shigella is an important cause of diarrhea worldwide, with serotypes Shigella flexneri 2a, S. flexneri 3a, and Shigella sonnei demonstrating epidemiological prevalence. Many development efforts are focused on Shigella lipopolysaccharide (LPS)-based vaccines, as O antigen-specific conjugate vaccines are immunogenic and efficacious. Immunization with Shigella vaccines containing LPS can elicit antibodies capable of killing Shigella in a serotype-specific manner. Thus, to facilitate Shigella vaccine development, we have developed a serum bactericidal assay (SBA) specific for three Shigella serotypes that measures killing of target bacteria at multiple serum dilutions and in the presence of exogenous complement. The SBA has a high analytical throughput and uses simple technologies and readily available reagents. The SBA was characterized with human sera with bactericidal antibodies against S. flexneri 2a, S. flexneri 3a, and S. sonnei. Purified LPS of a homologous serotype, but not a heterologous serotype, inhibited bacterial killing. Assessment of precision found median intra-assay precision to be 13.3% and median interassay precision to be 19 to 30% for the three serotypes. The SBA is linear, with slight deviations for samples with low (~40) killing indices. The SBA was sensitive enough to allow about 100-fold predilution of serum samples. Repeat assays yielded results with less than 2-fold deviations, indicating the robustness of the assay. Assay results from four different laboratories were highly comparable when normalized with a reference serum. The Shigella SBA, combined with a reference serum, should facilitate the development of Shigella vaccines across the field.

IMPORTANCEShigella is an important cause of diarrhea worldwide, and efforts are ongoing to produce a safe and effective Shigella vaccine. Although a clear immune correlate of protection has not been established, antibodies with bactericidal capacity may provide one means of protecting against shigellosis. Thus, it is important to measure the functional capacity of antibodies, as opposed to only binding activity. This article describes a simple, robust, and high-throughput serum bactericidal assay capable of measuring Shigella-specific functional antibodies in vitro. We show for the first time that this assay was successfully performed by multiple laboratories and generated highly comparable results, particularly when SBA titers were normalized using a reference standard. The serum bactericidal assay, along with a reference serum, should greatly facilitate Shigella vaccine development.

AutoCellSeg: robust automatic colony forming unit (CFU)/cell analysis using adaptive image segmentation and easy-to-use post-editing techniques

In biological assays, automated cell/colony segmentation and counting is imperative owing to huge image sets. Problems occurring due to drifting image acquisition conditions, background noise and high variation in colony features in experiments demand a user-friendly, adaptive and robust image processing/analysis method. We present AutoCellSeg (based on MATLAB) that implements a supervised automatic and robust image segmentation method. AutoCellSeg utilizes multi-thresholding aided by a feedback-based watershed algorithm taking segmentation plausibility criteria into account. It is usable in different operation modes and intuitively enables the user to select object features interactively for supervised image segmentation method. It allows the user to correct results with a graphical interface. This publicly available tool outperforms tools like OpenCFU and CellProfiler in terms of accuracy and provides many additional useful features for end-users.

In search of a counter you can count on: relative efficacy of human visual and automated colony counting

To evaluate comparative efficiency of traditional vs automated colony counting methods, cultures of Escherichia coli (ATCC 25945), Staphylococcus epidermidis (ATCC 12225), Streptococcus pyogenes (ATCC19615) and Streptococcus pneumoniae (ATCC49619) were prepared as pure cultures and mixed cultures at 0·5 McFarland standard and serial dilutions were performed. Plates were inoculated in triplicate with 50, 125, 250 and 500 colony forming units and counted by four researchers, visually and using each of the automated counters. Colony count and counting time were recorded. The pattern of efficiency for all bacterial species was similar: plates with low counts were accurate and quick to count for all methods, with an increase in time and a decrease in accuracy and precision as counts rose. Higher counts of single round colonies required less time and had greater precision with automated counters than human visual counting counts with no loss of accuracy; however, counts were reduced in accuracy and increased in time for species with less regular morphology or when plates had mixed species. Surprisingly, a free phone application was only slightly less precise and more time consuming than the high-end professional counter indicating that automation may be achievable at lower cost than expected.

SIGNIFICANCE AND IMPACT OF THE STUDY

Colony quantification is essential in clinical and research settings as well as pedagogy at the college level. Human visual (HV) counting, the most common method, is time consuming and fraught with errors. The time, accuracy and precision of HV counting were compared to a high-end professional automated counter, an inexpensive phone application and a free phone application. Low cost benefits of increased speed and accuracy with automated counting are maximized when counting single round colonies; but much reduced if colonies have irregular morphology or demonstrate haemolysis.

A new method for non-invasive biomass determination based on stereo photogrammetry

A novel, non-destructive method for the biomass estimation of biological samples on culture dishes was developed. To achieve this, a photogrammetric system, which consists of a digital single-lens reflex camera (DSLR), an illuminated platform where the culture dishes are positioned and an Arduino board which controls the capturing process, was constructed. The camera was mounted on a holder which set the camera at different title angles and the platform rotated, to capture images from different directions. A software, based on stereo photogrammetry, was developed for the three-dimensional (3D) reconstruction of the samples. The proof-of-concept was demonstrated in a series of experiments with plant tissue cultures and specifically with calli cultures of Salvia fruticosa and Ocimum basilicum. For a period of 14 days images of these cultures were acquired and 3D-reconstructions and volumetric data were obtained. The volumetric data correlated well with the experimental measurements and made the calculation of the specific growth rate, µ _max, possible. The µ _max value for S. fruticosa samples was 0.14 day^-1 and for O. basilicum 0.16 day^-1. The developed method demonstrated the high potential of this photogrammetric approach in the biological sciences.

Area-based cell colony surviving fraction evaluation: A novel fully automatic approach using general-purpose acquisition hardware

BACKGROUND

The current methodology for the Surviving Fraction (SF) measurement in clonogenic assay, which is a technique to study the anti-proliferative effect of treatments on cell cultures, involves manual counting of cell colony forming units. This procedure is operator-dependent and error-prone. Moreover, the identification of the exact colony number is often not feasible due to the high growth rate leading to the adjacent colony merging. As a matter of fact, conventional assessment does not deal with the colony size, which is generally correlated with the delivered radiation dose or the administered cytotoxic agent.

METHOD

Considering that the Area Covered by Colony (ACC) is proportional to the colony number and size as well as to the growth rate, we propose a novel fully automatic approach exploiting Circle Hough Transform, to automatically detect the wells in the plate, and local adaptive thresholding, which calculates the percentage of ACC for the SF quantification. This measurement relies just on this covering percentage and does not consider the colony number, preventing inconsistencies due to intra- and inter-operator variability.

RESULTS

To evaluate the accuracy of the proposed approach, we compared the SFs obtained by our automatic ACC-based method against the conventional counting procedure. The achieved results (r = 0.9791 and r = 0.9682 on MCF7 and MCF10A cells, respectively) showed values highly correlated with the measurements using the traditional approach based on colony number alone.

CONCLUSIONS

The proposed computer-assisted methodology could be integrated in laboratory practice as an expert system for the SF evaluation in clonogenic assays.

The Pneumococcal Serotype 15C Capsule Is Partially O-Acetylated and Allows for Limited Evasion of 23-Valent Pneumococcal Polysaccharide Vaccine-Elicited Anti-Serotype 15B Antibodies

As a species, Streptococcus pneumoniae (the pneumococcus) utilizes a diverse array of capsular polysaccharides to evade the host. In contrast to large variations in sugar composition and linkage formation, O-acetylation is a subtle capsular modification that nonetheless has a large impact on capsular shielding and recognition of the capsule by vaccine-elicited antibodies. Serotype 15B, which is included in the 23-valent pneumococcal polysaccharide vaccine (PPV23), carries the putative O-acetyltransferase gene wciZ The coding sequence of wciZ contains eight consecutive TA repeats [(TA)₈]. Replication slippage is thought to result in the addition or loss of TA repeats, subsequently causing frameshift and truncation of WciZ to yield a nonacetylated serotype, 15C. Using sensitive serological tools, we show that serotype 15C isolates whose wciZ contains seven or nine TA repeats retain partial O-acetylation, while serotype 15C isolates whose wciZ contains six TA repeats have barely detectable O-acetylation. We confirmed by inhibition enzyme-linked immunosorbent assay that (TA)₇ serotype 15C is ∼0.1% as acetylated as serotype 15B, while serotype 15X is nonacetylated. To eliminate the impact of genetic background, we created isogenic serotype 15B, (TA)₇ serotype 15C, and 15BΔwciZ (15X) strains and found that reduction or absence of WciZ-mediated O-acetylation did not affect capsular shielding from phagocytes, biofilm formation, adhesion to nasopharyngeal cells, desiccation tolerance, or murine colonization. Sera from PPV23-immunized persons opsonized serotype 15B significantly but only slightly better than serotypes 15C and 15X; thus, PPV23 may not result in expansion of serotype 15C.

Opsonophagocytic Antibodies to Serotype Ia, Ib, and III Group B Streptococcus among Korean Infants and in Intravenous Immunoglobulin Products

Group B streptococcus (GBS) infection is a leading cause of sepsis and meningitis among infants, and is associated with high rates of morbidity and mortality in many countries. Protection against GBS typically involves antibody-mediated opsonization by phagocytes and complement components. The present study evaluated serotype-specific functional antibodies to GBS among Korean infants and in intravenous immunoglobulin (IVIG) products. An opsonophagocytic killing assay (OPA) was used to calculate the opsonization indices (OIs) of functional antibodies to serotypes Ia, Ib, and III in 19 IVIG products from 5 international manufacturers and among 98 Korean infants (age: 0-11 months). The GBS Ia, Ib, and III serotypes were selected because they are included in a trivalent GBS vaccine formulation that is being developed. The OI values for the IVIG products were 635-5,706 (serotype Ia), 488-1,421 (serotype Ib), and 962-3,315 (serotype III), and none of the IVIG lots exhibited undetectable OI values (< 4). The geometric mean OI values were similar for all 3 serotypes when we compared the Korean manufacturers. The seropositive rate among infants was significantly lower for serotype Ia (18.4%), compared to serotype Ib and serotype III (both, 38.8%). Infant age of ≥ 3 months was positively correlated with the seropositive rates for each serotype. Therefore, only a limited proportion of infants exhibited protective immunity against serotype Ia, Ib, and III GBS infections. IVIG products that exhibit high antibody titers may be a useful therapeutic or preventive measure for infants. Further studies are needed to evaluate additional serotypes and age groups.