Software for quantification of labeled bacteria from digital microscope images by automated image analysis

Automated counting and classifying Daphnia magna using machine vision

Daphnia magna (D. magna) is a model organism widely used in aquatic ecotoxicology research due to its sensitivity to environmental changes. The survival and reproduction rates of D. magna are easily affected by toxic environments. However, their small size, fragility, and transparency, especially in neonate stages, make them challenging to count accurately. Traditionally, counting adult and neonate D. magna relies on manual separation and visual observation, which is not only tedious but also prone to inaccuracies. Previous attempts to aid counting with optical sensors have faced issues such as inducing stress damage due to vertical movement and an inability to distinguish between adults and neonates. With the advancement of deep learning technologies, our study employs a simple light source culture device and utilizes the Mask2Former model to analyze D. magna against the background. Additionally, the U-Net model is used for comparative analysis. We also applied OpenCV technology for automatic counting of adult and neonate D. magna. The model's results were compared against manual counting performed by experienced technicians. Our approach achieves an average relative accuracy of 99.72 % for adult D. magna and 98.30 % for neonate. This method not only enhances counting accuracy but also provides a fast and reliable technique for studying the survival and reproduction rates of D. magna as a model organism.

Rapid screening of bacteriostatic and bactericidal antimicrobial agents against Escherichia coli by combining machine learning (artificial intelligence) and UV-VIS spectroscopy

Antibiotics are compounds that have a particular mode of action upon the microorganism they are targeting. However, discovering and developing new antibiotics is a challenging and timely process. Antibiotic development process can take up to 10-15 years and over $1billion to develop a single new therapeutic product. Rapid screening tools to understand the mode of action of the new antimicrobial agent are considered one of the main bottle necks in the antimicrobial agent development process. Classical approaches require multifarious microbiological methods and they do not capture important biochemical and organism therapeutic-interaction mechanisms. This work aims to provide a rapid antibiotic-antimicrobial biochemical diagnostic tool to reduce the timeframes of therapeutic development, while also generating new biochemical insight into an antimicrobial-therapeutic screening assay in a complex matrix. The work evaluates the effect of antimicrobial action through "traditional" microbiological analysis techniques with a high-throughput rapid analysis method using UV-VIS spectroscopy and chemometrics. Bacteriostatic activity from tetracycline and bactericidal activity from amoxicillin were evaluated on a system using non-resistant Escherichia coli O157:H7 by confocal laser scanning microscopy (CLSM), scanning electron microscopy (SEM), and UV-VIS spectroscopy (high-throughput analysis). The data were analysed using principal component analysis (PCA) and support vector machine (SVM) classification. The rapid diagnostic technique could easily identify differences between bacteriostatic and bactericidal mechanisms and was considerably quicker than the "traditional" methods tested.

Cell Adhesion, Elasticity, and Rupture Forces Guide Microbial Cell Death on Nanostructured Antimicrobial Titanium Surfaces

Naturally occurring and synthetic nanostructured surfaces have been widely reported to resist microbial colonization. The majority of these studies have shown that both bacterial and fungal cells are killed upon contact and subsequent surface adhesion to such surfaces. This occurs because the presence of high-aspect-ratio structures can initiate a self-driven mechanical rupture of microbial cells during the surface adsorption process. While this technology has received a large amount of scientific and medical interest, one important question still remains: what factors drive microbial death on the surface? In this work, the interplay between microbial-surface adhesion, cell elasticity, cell membrane rupture forces, and cell lysis at the microbial-nanostructure biointerface during adsorptive processes was assessed using a combination of live confocal laser scanning microscopy, scanning electron microscopy, in situ amplitude atomic force microscopy, and single-cell force spectroscopy. Specifically, the adsorptive behavior and nanomechanical properties of live Gram-negative (Pseudomonas aeruginosa) and Gram-positive (methicillin-resistant Staphylococcus aureus) bacterial cells, as well as the fungal species Candida albicans and Cryptococcus neoformans, were assessed on unmodified and nanostructured titanium surfaces. Unmodified titanium and titanium surfaces with nanostructures were used as model substrates for investigation. For all microbial species, cell elasticity, rupture force, maximum cell-surface adhesion force, the work of adhesion, and the cell-surface tether behavior were compared to the relative cell death observed for each surface examined. For cells with a lower elastic modulus, lower force to rupture through the cell, and higher work of adhesion, the surfaces had a higher antimicrobial activity, supporting the proposed biocidal mode of action for nanostructured surfaces. This study provides direct quantification of the differences observed in the efficacy of nanostructured antimicrobial surface as a function of microbial species indicating that a universal, antimicrobial surface architecture may be hard to achieve.

Rice Plant Counting, Locating, and Sizing Method Based on High-Throughput UAV RGB Images

Rice plant counting is crucial for many applications in rice production, such as yield estimation, growth diagnosis, disaster loss assessment, etc. Currently, rice counting still heavily relies on tedious and time-consuming manual operation. To alleviate the workload of rice counting, we employed an UAV (unmanned aerial vehicle) to collect the RGB images of the paddy field. Then, we proposed a new rice plant counting, locating, and sizing method (RiceNet), which consists of one feature extractor frontend and 3 feature decoder modules, namely, density map estimator, plant location detector, and plant size estimator. In RiceNet, rice plant attention mechanism and positive-negative loss are designed to improve the ability to distinguish plants from background and the quality of the estimated density maps. To verify the validity of our method, we propose a new UAV-based rice counting dataset, which contains 355 images and 257,793 manual labeled points. Experiment results show that the mean absolute error and root mean square error of the proposed RiceNet are 8.6 and 11.2, respectively. Moreover, we validated the performance of our method with two other popular crop datasets. On these three datasets, our method significantly outperforms state-of-the-art methods. Results suggest that RiceNet can accurately and efficiently estimate the number of rice plants and replace the traditional manual method.

Isolation and transfection of myenteric neurons from mice for patch-clamp applications

The enteric nervous system (ENS) is a complex neuronal network organized in ganglionated plexuses that extend along the entire length of the gastrointestinal tract. Largely independent of the central nervous system, the ENS coordinates motility and peristalsis of the digestive tract, regulates secretion and absorption, and is involved in immunological processes. Electrophysiological methods such as the patch-clamp technique are particularly suitable to study the function of neurons as well as the biophysical parameters of the underlying ion channels under both physiological and pathophysiological conditions. However, application of the patch-clamp method to ENS neurons remained difficult because they are embedded in substantial tissue layers that limit access to and targeted manipulation of these cells. Here, we present a robust step-by-step protocol that involves isolation of ENS neurons from adult mice, culturing of the cells, their transfection with plasmid DNA, and subsequent electrophysiological characterization of individual neurons in current-clamp and voltage-clamp recordings. With this protocol, ENS neurons can be prepared, transfected, and electrophysiologically characterized within 72 h. Using isolated ENS neurons, we demonstrate the feasibility of the approach by functional overexpression of recombinant voltage-gated Na_V1.9 mutant channels associated with hereditary sensory and autonomic neuropathy type 7 (HSAN-7), a disorder characterized by congenital analgesia and severe constipation that can require parenteral nutrition. Although our focus is on the electrophysiological evaluation of isolated ENS neurons, the presented methodology is also useful to analyze molecules other than sodium channels or to apply alternative downstream assays including calcium imaging, proteomic and nucleic acid approaches, or immunochemistry.

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.

Assessing the validity and sensitivity of microbial processes within a hydrodynamic model

Eutrophication due to excess anthropogenic nutrients in waterways is a significant issue worldwide. The pressure-stressor-response of a waterway to excessive nutrient loading is reliant on numerous physical and biological factors, including hydrodynamics and microbial processing. While substantial progress has been made towards simulating these mechanisms there are limited multi-disciplinary studies that relate the physical hydrodynamics of a site with the ecological response from linked laboratory and field studies. This paper presents the development of a coupled hydrodynamic and aquatic ecosystem response model, expanded to include an integrated microbial loop, that allows the explicit representation of heterotrophic bacteria growth and dissolved organic nutrient mineralisation. A unique long-term water quality dataset at an estuary in south-eastern Australia was used to validate and assess the model's sensitivity to complex biophysical processes driving the observed water quality variability. Results indicate that explicit time-varying bacterial mineralisation rates provide a substantially improved understanding of the broader aquatic ecosystem response than assigned fixed bulk rate parameter values, which are typically derived from non-local literature. Implementation of a microbial loop at the study site indicated that the model is sensitive to the boundary conditions, in particular catchment loads, with both net transport rates and the net growth rates of heterotrophic bacteria demonstrating different responses. Under average flow conditions, a smaller net transport and reduced nutrient availability has a pronounced effect of lowering net growth rates through the applied limitation factors. During high flow conditions, freshwater inflows increased net transport and nutrient loads, which resulted in higher net growth rates. Further, temporal variability in water temperature had a compounding effect on the model's response sensitivity. This approach has broader application in other riverine systems subject to eutrophication, and in interrogating linkages in hydrodynamic and microbial mediated processes (e.g., productivity). Future studies are recommended to better understand the sensitivity of aquatic ecosystem response models to microbial net growth rate kinetics at different temperatures and from top-down predation (e.g., zooplankton grazing).

Self-normalized density map (SNDM) for counting microbiological objects

The statistical properties of the density map (DM) approach to counting microbiological objects on images are studied in detail. The DM is given by U\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$^2$$\end{document}2-Net. Two statistical methods for deep neural networks are utilized: the bootstrap and the Monte Carlo (MC) dropout. The detailed analysis of the uncertainties for the DM predictions leads to a deeper understanding of the DM model’s deficiencies. Based on our investigation, we propose a self-normalization module in the network. The improved network model, called Self-Normalized Density Map (SNDM), can correct its output density map by itself to accurately predict the total number of objects in the image. The SNDM architecture outperforms the original model. Moreover, both statistical frameworks—bootstrap and MC dropout—have consistent statistical results for SNDM, which were not observed in the original model. The SNDM efficiency is comparable with the detector-base models, such as Faster and Cascade R-CNN detectors.

Generation of microbial colonies dataset with deep learning style transfer

We introduce an effective strategy to generate an annotated synthetic dataset of microbiological images of Petri dishes that can be used to train deep learning models in a fully supervised fashion. The developed generator employs traditional computer vision algorithms together with a neural style transfer method for data augmentation. We show that the method is able to synthesize a dataset of realistic looking images that can be used to train a neural network model capable of localising, segmenting, and classifying five different microbial species. Our method requires significantly fewer resources to obtain a useful dataset than collecting and labeling a whole large set of real images with annotations. We show that starting with only 100 real images, we can generate data to train a detector that achieves comparable results (detection mAP \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$=0.416$$\end{document}=0.416, and counting MAE \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$=4.49$$\end{document}=4.49) to the same detector but trained on a real, several dozen times bigger dataset (mAP \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$=0.520$$\end{document}=0.520, MAE \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$=4.31$$\end{document}=4.31), containing over 7 k images. We prove the usefulness of the method in microbe detection and segmentation, but we expect that it is general and flexible and can also be applicable in other domains of science and industry to detect various objects.

Limiting nitrate triggered increased EPS film but decreased biocorrosion of copper induced by Pseudomonas aeruginosa

Biocorrosion of Cu remains a significant challenge in marine engineering but the mechanism is still not clear. The nutrients in marine environment affect the microbe's growth and the formation of biofilm, and then affect biocorrosion of metal to a large extent. In this study, the effect of NO3- concentration in Pseudomonas aeruginosa (P. aeruginosa) medium on the formation of extracellular polymer substance (EPS) film and biocorrosion of Cu were studied. The experiments results showed that limiting NO3- in culture medium triggered increased EPS film but decreased biocorrosion of Cu induced by P. aeruginosa. With increase of NO3- content in the culture medium, the Cu surface attached less polysaccharides and proteins, but the Cu corrosion rate was accelerated. The weight loss of Cu and the maximum pit depth were both increased with increase of NO3- content. The XPS and XRD analyses indicated that the major corrosion product is Cu2O. The increased corrosion rate with increase of the NO3- level were attributed to the EET-MIC route, the formation of Cu(NH3)2+, and the more loose EPS film.

Perfusion System for Modification of Luminal Contents of Human Intestinal Organoids and Realtime Imaging Analysis of Microbial Populations

Intestinal organoids are 3D cell structures that replicate some aspects of organ function and are organized with a polarized epithelium facing a central lumen. To enable more applications, new technologies are needed to access the luminal cavity and apical cell surface of organoids. We developed a perfusion system utilizing a double-barrel glass capillary with a pressure-based pump to access and modify the luminal contents of a human intestinal organoid for extended periods of time while applying cyclic cellular strain. Cyclic injection and withdrawal of fluorescent FITC-Dextran coupled with real-time measurement of fluorescence intensity showed discrete changes of intensity correlating with perfusion cycles. The perfusion system was also used to modify the lumen of organoids injected with GFP-expressing E. coli. Due to the low concentration and fluorescence of the E. coli, a novel imaging analysis method utilizing bacteria enumeration and image flattening was developed to monitor E. coli within the organoid. Collectively, this work shows that a double-barrel perfusion system provides constant luminal access and allows regulation of luminal contents and luminal mixing.

Liquid metal polymer composite: Flexible, conductive, biocompatible, and antimicrobial scaffold

Gallium and its alloys, such as eutectic gallium indium alloy (EGaIn), a form of liquid metal, have recently attracted the attention of researchers due to their low toxicity and electrical and thermal conductivity for biomedical application. However, further research is required to harness EGaIn-composites advantages and address their application as a biomedical scaffold. In this research, EGaIn-polylactic acid/polycaprolactone composites with and without a second conductive filler, MXene, were prepared and characterized. The addition of MXene, into the EGaIn-composite, can improve the composite's electrochemical properties by connecting the liquid metal droplets resulting in electrically conductive continuous pathways within the polymeric matrix. The results showed that the composite with 50% EGaIn and 4% MXene, displayed optimal electrochemical properties and enhanced mechanical and radiopacity properties. Furthermore, the composite showed good biocompatibility, examined through interactions with fibroblast cells, and antibacterial properties against methicillin-resistant Staphylococcus aureus. Therefore, the liquid metal (EGaIn) polymer composite with MXene provides a first proof-of-concept engineering scaffold strategy with low toxicity, functional electrochemical properties, and promising antimicrobial properties.

Counterpropagating Gradients of Antibacterial and Antifouling Polymer Brushes

We report on the formation of counterpropagating density gradients in poly([2-dimethylaminoethyl] methacrylate) (PDMAEMA) brushes featuring spatially varying quaternized and betainized units. Starting with PDMAEMA brushes with constant grafting density and degree of polymerization, we first generate a density gradient of quaternized units by directional vapor reaction involving methyl iodide. The unreacted DMAEMA units are then betainized through gaseous-phase betainization with 1,3-propanesultone. The gas reaction of PDMAEMA with 1,3-propanesultone eliminates the formation of byproducts present during the liquid-phase modification. We use the counterpropagating density gradients of quaternized and betainized PDMAEMA brushes in antibacterial and antifouling studies. Completely quaternized and betainized brushes exhibit antibacterial and antifouling behaviors. Samples containing 12% of quaternized and 85% of betainized units act simultaneously as antibacterial and antifouling surfaces.

Fsr quorum sensing system modulates the temporal development of Enterococcus faecalis biofilm matrix

Quorum sensing (QS) is a cell-to-cell communication process that regulates major pathogenic attributes in bacteria including biofilm formation, secretion of virulence factors, and antimicrobial resistance. The two-component Fsr-QS system of the nosocomial pathogen Enterococcus faecalis controls the production of extracellular gelatinase that contributes to biofilm development by enhancing the release of nucleic acids into the biofilm matrix. However, the contribution of this system to the deposition of other biofilm matrix components such as polysaccharides and proteins remains unknown. Using wild type and mutant strains, we discovered that biofilm formation was attenuated by inactivation of the Fsr system or its downstream gelatinase production. Inactivation of the Fsr system caused a modest, yet significant reduction in biofilm metabolic activity without affecting cell counts. Inactivation of the QS-signal sensor FsrC and response regulator FsrA resulted in decreased extracellular polysaccharides and proteins in biofilms in a temporal manner. Irrespective of biofilm age, eDNA levels were reduced in the gelatinase mutant strain. Our results collectively suggest that the Fsr system contributes to the temporal deposition of polysaccharides and proteins into the extracellular polymeric matrix (EPS) of E. faecalis biofilm, without affecting bacterial viability. This understanding of the role of the Fsr-QS system in biofilm development may reveal a novel target to develop effective antibiofilm agents to tackle E. faecalis-mediated infections such as in dental root canals, heart valves, and surgical sites.

A Liquid Metal Mediated Metallic Coating for Antimicrobial and Antiviral Fabrics

Fabrics are widely used in hospitals and many other settings for bedding, clothing, and face masks; however, microbial pathogens can survive on surfaces for a long time, leading to microbial transmission. Coatings of metallic particles on fabrics have been widely used to eradicate pathogens. However, current metal particle coating technologies encounter numerous issues such as nonuniformity, processing complexity, and poor adhesion. To overcome these issues, an easy-to-control and straightforward method is reported to coat a wide range of fabrics by using gallium liquid metal (LM) particles to facilitate the deposition of liquid metal copper alloy (LMCu) particles. Gallium particles coated on the fabric provide nucleation sites for forming LMCu particles at room temperature via galvanic replacement of Cu²⁺ ions. The LM helps promote strong adhesion of the particles to the fabric. The presence of the LMCu particles can eradicate over 99% of pathogens (including bacteria, fungi, and viruses) within 5 min, which is significantly more effective than control samples coated with only Cu. The coating remains effective over multiple usages and against contaminated droplets and aerosols, such as those encountered in facemasks. This facile coating method is promising for generating robust antibacterial, antifungal, and antiviral fabrics and surfaces.

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.

Rumen Ciliated Protozoa of the Free-Living European Bison (Bison bonasus, Linnaeus)

This study aims to perform population analysis of the rumen ciliated protozoa of the free-living European bison (wisent, Bison bonasus, Linnaeus). The samples of the rumen fluid from the 18 bison subjected to the controlled culls within the free-ranging population in the Bialowieza primeval forest in Poland were collected and examined. The examined ciliates population consisted of the species of the families Isotrichidae and Ophryoscolecidae. There were 12 genera (Isotricha, Dasytricha, Diplodinium, Elytroplastron, Entodinium, Eodinium, Epidinium, Eremoplastron, Eudiplodinium, Metadinium, Ophryoscolex, and Ostracodinium) and 32 morphospecies of the ciliates. We observed the prevalence of a type B protozoan population (56% animals) with the typical Epidinium and Eudiplodinium genera members. Other examined animals possessed the mixed A-B population with Ophryoscolex genus, distinct for type A ciliate population. The average total ciliates count was 2.77 ± 1.03 × 105/ml (mean ± SD). The most abundant genera were Entodinium, 83%, and Dasytricha, 14%. The abundance of other genera was <1% of the total count. Within the 16 Entodinium species determined, the most abundant species was Entodinium nanellum (16.3% of total ciliates count). The average Shannon-Wiener diversity index was 2.1 ± 0.39, evenness was 0.7 ± 0.11, and species richness was 24 ± 3.0 (mean ± SD). Our study is the first report on the population composition and diversity of rumen ciliates of European bison. The composition and counts of ciliate genera and species were similar to the composition and counts of the rumen ciliated protozoa of American bison and many other kinds of free-living and domestic ruminants. Our European bison ciliate population analysis has shown medium ciliate density and high diversity typical for large free-living ruminants with mixed feeding behavior.

Fluorescent Magnesium Hydroxide Nanosheet Bandages with Tailored Properties for Biocompatible Antimicrobial Wound Dressings and pH Monitoring

Magnesium hydroxide (Mg(OH)₂) is hailed as a cheap and biocompatible material with antimicrobial potential; however, research aimed at instilling additional properties and functionality to this material is scarce. In this work, we synthesized novel, fluorescent magnesium hydroxide nanosheets (Mg(OH)₂-NS) with a morphology that closely resembles that of graphene oxide. These multifunctional nanosheets were employed as a potent antimicrobial agent against several medically relevant bacterial and fungal species, particularly on solid surfaces. Their strong fluorescence signature correlates to their hydroxide makeup and can therefore be used to assess their degradation and functional antimicrobial capacity. Furthermore, their pH-responsive change in fluorescence can potentially act as a pH probe for wound acidification, which is characteristic of healthy wound healing. These fluorescent antimicrobial nanosheets were stably integrated into biocompatible electrospun fibers and agarose gels to add functionality to the material. This reinforces the suitability of the material to be used as antimicrobial bandages and gels. The biocompatibility of the Mg(OH)₂-NS for topical medical applications was supported by its noncytotoxic action on human keratinocyte (HaCaT) cells.

Trans-Cinnamaldehyde Attenuates Enterococcus faecalis Virulence and Inhibits Biofilm Formation

Enterococcus faecalis as an important nosocomial pathogen is critically implicated in the pathogenesis of endocarditis, urinary tract, and persistent root canal infections. Its major virulence attributes (biofilm formation, production of proteases, and hemolytic toxins) enable it to cause extensive host tissue damage. With the alarming increase in enterococcal resistance to antibiotics, novel therapeutics are required to inhibit E. faecalis biofilm formation and virulence. Trans-cinnamaldehyde (TC), the main phytochemical in cinnamon essential oils, has demonstrated promising activity against a wide range of pathogens. Here, we comprehensively investigated the effect of TC on planktonic growth, biofilm formation, proteolytic and hemolytic activities, as well as gene regulation in E. faecalis. Our findings revealed that sub-inhibitory concentrations of TC reduced biofilm formation, biofilm exopolysaccharides, as well as its proteolytic and hemolytic activities. Mechanistic studies revealed significant downregulation of the quorum sensing fsr locus and downstream gelE, which are major virulence regulators in E. faecalis. Taken together, our study highlights the potential of TC to inhibit E. faecalis biofilm formation and its virulence.

Microbial diversity and activity in Southern California salterns and bitterns: analogues for remnant ocean worlds

Concurrent osmotic and chaotropic stress make MgCl₂ -rich brines extremely inhospitable environments. Understanding the limits of life in these brines is essential to the search for extraterrestrial life on contemporary and relict ocean worlds, like Mars, which could host similar environments. We sequenced environmental 16S rRNA genes and quantified microbial activity across a broad range of salinity and chaotropicity at a Mars-analogue salt harvesting facility in Southern California, where seawater is evaporated in a series of ponds ranging from kosmotropic NaCl brines to highly chaotropic MgCl₂ brines. Within NaCl brines, we observed a proliferation of specialized halophilic Euryarchaeota, which corresponded closely with the dominant taxa found in salterns around the world. These communities were characterized by very slow growth rates and high biomass accumulation. As salinity and chaotropicity increased, we found that the MgCl₂ -rich brines eventually exceeded the limits of microbial activity. We found evidence that exogenous genetic material is preserved in these chaotropic brines, producing an unexpected increase in diversity in the presumably sterile MgCl₂ -saturated brines. Because of their high potential for biomarker preservation, chaotropic brines could therefore serve as repositories of genetic biomarkers from nearby environments (both on Earth and beyond) making them prime targets for future life-detection missions.

A curcumin-sophorolipid nanocomplex inhibits Candida albicans filamentation and biofilm development

Candida albicans is an opportunistic fungal pathogen that is highly resistant to contemporary antifungals, due to their biofilm lifestyle. The ability of C. albicans to invade human tissues is due to its filamentation. Therefore, inhibition of biofilms and filamentation of the yeast are high value targets to develop the next-generation antifungals. Curcumin (CU) is a natural polyphenol with excellent pharmacological attributes, but limitations such as poor solubility, acid, and enzyme tolerance have impeded its practical utility. Sophorolipids (SL) are biologically-derived surfactants that serve as efficient carriers of hydrophobic molecules such as curcumin into biofilms. Here, we synthesised a curcumin-sophorolipid nanocomplex (CUSL), and comprehensively evaluated its effects on C. albicans biofilms and filamentation. Our results demonstrated that sub-inhibitory concentration of CUSL (9.37 μg/mL) significantly inhibited fungal adhesion to substrates, and subsequent biofilm development, maturation, and filamentation. This effect was associated with significant downregulation of a select group of biofilm, adhesins, and hyphal regulatory genes. In conclusion, the curcumin-sophorolipid nanocomplex is a potent inhibitor of the two major virulence attributes of C. albicans, biofilm formation and filamentation, thus highlighting its promise as a putative anti-fungal agent with biofilm penetrative potential.

Effects of Rifaximin on Luminal and Wall-Adhered Gut Commensal Microbiota in Mice

Rifaximin is a broad-spectrum antibiotic that ameliorates symptomatology in inflammatory/functional gastrointestinal disorders. We assessed changes in gut commensal microbiota (GCM) and Toll-like receptors (TLRs) associated to rifaximin treatment in mice. Adult C57BL/6NCrl mice were treated (7/14 days) with rifaximin (50/150 mg/mouse/day, PO). Luminal and wall-adhered ceco-colonic GCM were characterized by fluorescent in situ hybridization (FISH) and microbial profiles determined by terminal restriction fragment length polymorphism (T-RFLP). Colonic expression of TLR2/3/4/5/7 and immune-related markers was assessed (RT-qPCR). Regardless the period of treatment or the dose, rifaximin did not alter total bacterial counts or bacterial biodiversity. Only a modest increase in Bacteroides spp. (150 mg/1-week treatment) was detected. In control conditions, only Clostridium spp. and Bifidobacterium spp. were found attached to the colonic epithelium. Rifaximin showed a tendency to favour their adherence after a 1-week, but not 2-week, treatment period. Minor up-regulation in TLRs expression was observed. Only the 50 mg dose for 1-week led to a significant increase (by 3-fold) in TLR-4 expression. No changes in the expression of immune-related markers were observed. Rifaximin, although its antibacterial properties, induces minor changes in luminal and wall-adhered GCM in healthy mice. Moreover, no modulation of TLRs or local immune systems was observed. These findings, in normal conditions, do not rule out a modulatory role of rifaximin in inflammatory and or dysbiotic states of the gut.

Responses to the Hydrostatic Pressure of Surface and Subsurface Strains of Pseudothermotoga elfii Revealing the Piezophilic Nature of the Strain Originating From an Oil-Producing Well

Microorganisms living in deep-oil reservoirs face extreme conditions of elevated temperature and hydrostatic pressure. Within these microbial communities, members of the order Thermotogales are predominant. Among them, the genus Pseudothermotoga is widespread in oilfield-produced waters. The growth and cell phenotypes under hydrostatic pressures ranging from 0.1 to 50 MPa of two strains from the same species originating from subsurface, Pseudothermotoga elfii DSM9442 isolated from a deep African oil-producing well, and surface, P. elfii subsp. lettingae isolated from a thermophilic sulfate-reducing bioreactor, environments are reported for the first time. The data support evidence for the piezophilic nature of P. elfii DSM9442, with an optimal hydrostatic pressure for growth of 20 MPa and an upper limit of 40 MPa, and the piezotolerance of P. elfii subsp. lettingae with growth occurring up to 20 MPa only. Under the experimental conditions, both strains produce mostly acetate and propionate as volatile fatty acids with slight variations with respect to the hydrostatic pressure for P. elfii DSM9442. The data show that the metabolism of P. elfii DSM9442 is optimized when grown at 20 MPa, in agreement with its piezophilic nature. Both Pseudothermotoga strains form chained cells when the hydrostatic pressure increases, especially P. elfii DSM9442 for which 44% of cells is chained when grown at 40 MPa. The viability of the chained cells increases with the increase in the hydrostatic pressure, indicating that chain formation is a protective mechanism for P. elfii DSM9442.

Broad-spectrum treatment of bacterial biofilms using magneto-responsive liquid metal particles

The formation and proliferation of bacterial biofilms on surfaces, particularly those on biomedical devices, is a significant issue that results in substantial economic losses, presenting severe health risks to patients. Furthermore, heterogeneous biofilms consisting of different bacterial species can induce the increase in pathogenicity, and the resistance to antimicrobial agents due to the synergistic interactions between the different species. Heterogeneous bacterial biofilms are notoriously difficult to treat due to the presence of extracellular polymeric substances (EPS) and, in conjunction with the rapid rise of multi-drug resistant pathogens, this means that new solutions for anti-biofilm treatment are required. In this study, we investigate the application of magneto-responsive gallium-based liquid metal (GLM-Fe) nanomaterials against a broad range of Gram-positive and Gram-negative bacterial mono-species and multi-species biofilms. The GLM-Fe particles exhibit a magneto-responsive characteristic, causing spherical particles to undergo a shape transformation to high-aspect-ratio nanoparticles with sharp asperities in the presence of a rotating magnetic field. These shape-transformed particles are capable of physically removing bacterial biofilms and rupturing individual cells. Following treatment, both mono-species and multi-species biofilms demonstrated significant reductions in their biomass and overall cell viability, demonstrating the broad-spectrum application of this antibacterial technology. Furthermore, the loss of integrity of the bacterial cell wall and membranes was visualized using a range of microscopy techniques, and the leakage of intracellular components (such as nucleic acids and protein) was observed. Insights gained from this study will impact the design of future liquid metal-based biofilm treatments, particularly those that rely on magneto-responsive properties.

Development of Digital Image Processing as an Innovative Method for Activated Sludge Biomass Quantification

Activated sludge process is the most common method for biological treatment of industrial and municipal wastewater. One of the most important parameters in performance of activated sludge systems is quantitative monitoring of biomass to keep the cell concentration in an optimum range. In this study, a novel method for activated sludge quantification based on image processing and RGB analysis is proposed. According to the results, the intensity of blue color in the macroscopic image of activated sludge culture can be a very accurate index for cell concentration measurement and R² coefficient, Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE) which are 0.990, 2.000, 0.323, and 13.848, respectively, prove this claim. Besides, in order to avoid the difficulties of working in the three-parameter space of RGB, converting to grayscale space has been applied which can estimate cell concentration with R ² = 0.99. Ultimately, an exponential correlation between RGB values and cell concentrations in lower amounts of biomass has been proposed based on Beer-Lambert law which can estimate activated sludge biomass concentration with R ² = 0.97 based on B index.

Shape-to-graph mapping method for efficient characterization and classification of complex geometries in biological images

With the ever-increasing quality and quantity of imaging data in biomedical research comes the demand for computational methodologies that enable efficient and reliable automated extraction of the quantitative information contained within these images. One of the challenges in providing such methodology is the need for tailoring algorithms to the specifics of the data, limiting their areas of application. Here we present a broadly applicable approach to quantification and classification of complex shapes and patterns in biological or other multi-component formations. This approach integrates the mapping of all shape boundaries within an image onto a global information-rich graph and machine learning on the multidimensional measures of the graph. We demonstrated the power of this method by (1) extracting subtle structural differences from visually indistinguishable images in our phenotype rescue experiments using the endothelial tube formations assay, (2) training the algorithm to identify biophysical parameters underlying the formation of different multicellular networks in our simulation model of collective cell behavior, and (3) analyzing the response of U2OS cell cultures to a broad array of small molecule perturbations.

In this paper, we present a methodology that is based on mapping an arbitrary set of outlines onto a complete, strictly defined structure, in which every point representing the shape becomes a terminal point of a global graph. Because this mapping preserves the whole complexity of the shape, it allows for extracting the full scope of geometric features of any scale. Importantly, an extensive set of graph-based metrics in each image makes integration with machine learning routines highly efficient even for a small data sets and provide an opportunity to backtrack the subtle morphological features responsible for the automated distinction into image classes. The resulting tool provides efficient, versatile, and robust quantification of complex shapes and patterns in experimental images.

Conformationally tuned antibacterial oligomers target the peptidoglycan of Gram-positive bacteria

The recent rise of antibiotic resistance amongst Staphylococcus aureus (S. aureus) populations has made treating Staph-based infections a global medical challenge. Therapies that specifically target the peptidoglycan layer of S. aureus have emerged as new treatment avenues, towards which bacteria are less likely to develop resistance. While the majority of antibacterial polymers/oligomers have the ability to disrupt bacterial membranes, the design parameters for the enhanced disruption of peptidoglycan outer layer of Gram-positive bacteria remain unclear. Here, the design of oligomeric structures with favorable conformational characteristics for improved disruption of the peptidoglycan outer layer of Gram-positive bacteria is reported. Molecular dynamics simulations were employed to inform the structure design and composition of cationic oligomers displaying collapsed and expanded conformations. The most promising diblock and triblock cationic oligomers were synthesized by photo-induced atom transfer radical polymerization (photo ATRP). Following synthesis, the diblock and triblock oligomers displayed average antibacterial activity of ~99% and ~98% for S. aureus and methicillin-resistant S. aureus (MRSA), respectively, at the highest concentrations tested. Importantly, triblock oligomers with extended conformations showed significantly higher disruption of the peptidoglycan outer layer of S. aureus compared to diblock oligomers with more collapsed conformation, as evidenced by a number of characterization techniques including scanning electron, confocal and atomic force microscopy. This work provides new insight into the structure/property relationship of antibacterial materials and advances the design of functional materials for combating the rise of drug-resistant bacteria.

Mild Stress Conditions during Laboratory Culture Promote the Proliferation of Mutations That Negatively Affect Sigma B Activity in Listeria monocytogenes

In Listeria monocytogenes, the full details of how stress signals are integrated into the σB regulatory pathway are not yet available. To help shed light on this question, we investigated a collection of transposon mutants that were predicted to have compromised activity of the alternative sigma factor B (σB). These mutants were tested for acid tolerance, a trait that is known to be under σB regulation, and they were found to display increased acid sensitivity, similar to a mutant lacking σB (ΔsigB). The transposon insertions were confirmed by whole-genome sequencing, but in each case, the strains were also found to carry a frameshift mutation in the sigB operon. The changes were predicted to result in premature stop codons, with negative consequences for σB activation, independently of the transposon location. Reduced σB activation in these mutants was confirmed. Growth measurements under conditions similar to those used during the construction of the transposon library revealed that the frameshifted sigB operon alleles conferred a growth advantage at higher temperatures, during late exponential phase. Mixed-culture experiments at 42°C demonstrated that the loss of σB activity allowed mutants to take over a population of parental bacteria. Together, our results suggest that mutations affecting σB activity can arise during laboratory culture because of the growth advantage conferred by these mutations under mild stress conditions. The data highlight the significant cost of stress protection in this foodborne pathogen and emphasize the need for whole-genome sequence analysis of newly constructed strains to confirm the expected genotype.IMPORTANCE In the present study, we investigated a collection of Listeria monocytogenes strains that all carried sigB operon mutations. The mutants all had reduced σB activity and were found to have a growth advantage under conditions of mild heat stress (42°C). In mixed cultures, these mutants outcompeted the wild type when mild heat stress was present but not at an optimal growth temperature. An analysis of 22,340 published L. monocytogenes genome sequences found a high rate of premature stop codons present in genes positively regulating σB activity. Together, these findings suggest that the occurrence of mutations that attenuate σB activity can be favored under conditions of mild stress, probably highlighting the burden on cellular resources that stems from deploying the general stress response.

Comparison of 2 fixatives in the porcine colon for in situ microbiota studies

Fixation is the first step towards preservation of tissues and can impact downstream histological applications. Historically, formalin has been the fixative of choice in both research and clinical settings due to cost, accessibility, and broad applicability. Here, we describe a method for collection of porcine colon, and compare the usage of Carnoy's solution (CS) to a 10% neutral buffered formalin (NBF) in tissue fixation. Consecutive colon samples were collected from 24 four-wk-old piglets and fixed in CS for 45 min or NBF for 24 h. We measured the thickness of the inner mucus layer using Alcian Blue stain and found thicker inner mucus layers in porcine colons fixed with CS as compared to NBF (P < 0.0001). Carnoy's solution-fixed colon exhibited greater bacterial cell counts than NBF-fixed colon (P < 0.0022) after labeling with an eubacterial probe in fluorescent in situ hybridization (FISH). No difference was observed between the mucosal height (P = 0.42) and number of goblet cells (P = 0.66) between the 2 fixatives. From this, we concluded CS is more suitable than NBF for the preservation of the mucus layer and the associated mucosal bacteria in the porcine colon without compromising on overall tissue morphology. This study provides a useful sampling and fixation methodology for histology studies in the porcine gastrointestinal tract, and may be beneficial to microbiota, pathology, and nutrition studies.

Rapid quantification of cellular proliferation and migration using ImageJ

Cellular proliferation and migration are crucial during development, regeneration and disease. Methods to quantify these processes are available; however, many are time consuming and require specialized equipment and costly reagents. Simple cell counts (proliferation analysis) and the scratch assay (migration analysis) are favorable methods due to their simplicity and cost-effectiveness; however, they rely on subjective and labor-intensive manual analysis, resulting in low throughput. We have developed optimized protocols to rapidly and accurately quantify adherent cell number and wound area using ImageJ, an open-source image processing program. Notably, these adaptable protocols facilitate quantification with significantly greater accuracy than manual identification.

Characterization of Human Induced Pluripotent Stem Cell-Derived Hepatocytes with Mature Features and Potential for Modeling Metabolic Diseases

There is a strong anticipated future for human induced pluripotent stem cell-derived hepatocytes (hiPS-HEP), but so far, their use has been limited due to insufficient functionality. We investigated the potential of hiPS-HEP as an in vitro model for metabolic diseases by combining transcriptomics with multiple functional assays. The transcriptomics analysis revealed that 86% of the genes were expressed at similar levels in hiPS-HEP as in human primary hepatocytes (hphep). Adult characteristics of the hiPS-HEP were confirmed by the presence of important hepatocyte features, e.g., Albumin secretion and expression of major drug metabolizing genes. Normal energy metabolism is crucial for modeling metabolic diseases, and both transcriptomics data and functional assays showed that hiPS-HEP were similar to hphep regarding uptake of glucose, low-density lipoproteins (LDL), and fatty acids. Importantly, the inflammatory state of the hiPS-HEP was low under standard conditions, but in response to lipid accumulation and ER stress the inflammation marker tumor necrosis factor α (TNFα) was upregulated. Furthermore, hiPS-HEP could be co-cultured with primary hepatic stellate cells both in 2D and in 3D spheroids, paving the way for using these co-cultures for modeling non-alcoholic steatohepatitis (NASH). Taken together, hiPS-HEP have the potential to serve as an in vitro model for metabolic diseases. Furthermore, differently expressed genes identified in this study can serve as targets for future improvements of the hiPS-HEP.

Mineral deposition and vascular invasion of hydroxyapatite reinforced collagen scaffolds seeded with human adipose-derived stem cells

Background

Collagen-based scaffolds reinforced with hydroxyapatite (HA) are an attractive choice for bone tissue engineering because their composition mimics that of bone. We previously reported the development of compression-molded collagen-HA scaffolds that exhibited high porosity, interconnected pores, and mechanical properties that were well-suited for surgical handling and fixation. The objective of this study was to investigate these novel collagen-HA scaffolds in combination with human adipose-derived stem cells (hASCs) as a template for bone formation in a subcutaneous athymic mouse model.

Methods

Collagen-HA scaffolds and collagen-only scaffolds were fabricated as previously described, and a clinically approved bone void filler was used as a control for the material. Constructs were seeded with hASCs and were pre-treated with either control or osteogenic media. A cell-free group was also included. Scaffolds were implanted subcutaneously in the backs of athymic nude mice for 8 weeks. Mineral deposition was quantified via micro-computed tomography. Histological and immunofluorescence images of the explants were used to analyze their vascular invasion, remodeling and cellularity.

Results

Cell-free collagen-HA scaffolds and those that were pre-seeded with osteogenically differentiated hASCs supported mineral deposition and vascular invasion at comparable rates, while cell-seeded constructs treated with the control medium showed lower mineralization after implantation. HA-reinforcement allowed collagen constructs to maintain their shape, provided improved cell-tissue-scaffold integration, and resulted in a more organized tissue when pre-treated in an osteogenic medium. Scaffold type and pre-treatment also determined osteoclast activity and therefore potential remodeling of the constructs.

Conclusions

The results of this study cumulatively indicate that treatment medium and scaffold composition direct mineralization and angiogenic tissue formation in an ectopic model. The data suggest that it may be necessary to match the scaffold with a particular cell type and cell-specific pre-treatment to achieve optimal bone formation.

Automated image analysis with ImageJ of yeast colony forming units from cannabis flowers

Currently, in the state of Colorado and all other states within the United States of America with legalized marijuana programs, testing is required for bacteria, yeast, and mold on marijuana products. The Code of Colorado Regulations, 1 CCR 212-1, considers a passing result when a 1 g sample contains <10⁴ colony forming units (CFU) for the total yeast and mold count (TYMC). These measurements are usually obtained by manually counting colonies on petri-dishes or 3 M™ Petrifilms™, which is a time consuming and user subjective process. Therefore, an automated counting method utilizing ImageJ has been developed for CFU analysis of TYMC on Petrifilms. The performance of this colony counting method was demonstrated by comparing manual and automated counts from marijuana flower samples containing spikes of Candida albicans as well as samples that tested positive for the presence of yeast and mold. Fifteen images of Petrifilms showing various concentrations of colonies were studied by fifteen users at two institutions using both the automated and manual counting methods. All counts from the automated ImageJ procedure were within 12% of those obtained manually. In twelve out of fifteen Petrifilms, the average count of the automated method was statistically similar to the manual counts. The statistical differences of the other three samples were observed to be random and caused by user errors. The automated counting method could be used to quickly count numbers that are as high as 400 CFUs, reducing time of analysis with improved documentation because the images and the electronic colony counts can be saved on a computer or cloud for long term storage and data access.

Automated image processing as an analytical tool in cell cryopreservation for bioprocess development

The continuous availability of cells with defined cell characteristics represents a crucial issue in the biopharmaceutical and cell therapy industry. Here, development of cell banks with a long-term stability is essential and ensured by a cryopreservation strategy. The strategy needs to be optimized for each cell application individually and usually comprises controlled freezing, storage at ultra-low temperature, and fast thawing of cells. This approach is implemented by the development of master and working cell banks. Currently, empirical cryopreservation strategy development is standard, but a knowledge-based approach would be highly advantageous. In this article, we report the development of a video-based tool for the characterisation of freezing and thawing behaviour in cryopreservation process to enable a more knowledge-based cryopreservation process development. A successful tool validation was performed with a model cryopreservation process for the β-cell line INS-1E. Performance was evaluated for two working volumes (1.0 mL and 2.0 mL), based on freezing-thawing rates (20 °C to - 80 °C) and cell recovery and increase of biomass, to determine tool flexibility and practicality. Evaluation confirmed flexibility by correctly identifying a delay in freezing and thawing for the larger working volume. Further more, a decrease in cell recovery from 0.94 (± 0.14) % using 1.0 mL working volume to 0.61 (± 0.05) % using a 2.0 mL working volume displays tool practicality. The video-based tool proposed in this study presents a powerful tool for cell-specific optimisation of cryopreservation protocols. This can facilitate faster and more knowledge-based cryopreservation process development In this study, a video-based analytical tool was developed for the characterisation of freezing and thawing behaviour in cryopreservation process development. Evaluation of the practicality and flexibility of the developed tool was done based on a scale-up case study with the cell line INS-1E. Here, the influence of sample working volume on process performance was investigated. Increasing the volume from 1to 2 mL led to a delay in freezing and thawing behaviour which caused cell recovery loss. We believe that the developed tool will facilitate more directed and systematic cryopreservation process development.

Functionalization of PLLA with Polymer Brushes to Trigger the Assembly of Fibronectin into Nanonetworks

Poly-l-lactic acid (PLLA) has been used as a biodegradable polymer for many years; the key characteristics of this polymer make it a versatile and useful resource for regenerative medicine. However, it is not inherently bioactive. Thus, here, a novel process is presented to functionalize PLLA surfaces with poly(ethyl acrylate) (PEA) brushes to provide biological functionality through PEA's ability to induce spontaneous organization of the extracellular matrix component fibronectin (FN) into physiological-like nanofibrils. This process allows control of surface biofunctionality while maintaining PLLA bulk properties (i.e., degradation profile, mechanical strength). The new approach is based on surface-initiated atomic transfer radical polymerization, which achieves a molecularly thin coating of PEA on top of the underlying PLLA. Beside surface characterization via atomic force microscopy, X-ray photoelectron spectroscopy and water contact angle to measure PEA grafting, the biological activity of this surface modification is investigated. PEA brushes trigger FN organization into nanofibrils, which retain their ability to enhance adhesion and differentiation of C2C12 cells. The results demonstrate the potential of this technology to engineer controlled microenvironments to tune cell fate via biologically active surface modification of an otherwise bioinert biodegradable polymer, gaining wide use in tissue engineering applications.

Quantitative Imaging of Tumor-Associated Macrophages and Their Response to Therapy Using 64Cu-Labeled Macrin

Tumor-associated macrophages (TAMs) are widely implicated in cancer progression, and TAM levels can influence drug responses, particularly to immunotherapy and nanomedicines. However, it has been difficult to quantify total TAM numbers and their dynamic spatiotemporal distribution in a non-invasive and translationally relevant manner. Here, we address this need by developing a pharmacokinetically optimized, 64Cu-labeled polyglucose nanoparticle (Macrin) for quantitative positron emission tomography (PET) imaging of macrophages in tumors. By combining PET with high-resolution in vivo confocal microscopy and ex vivo imaging of optically cleared tissue, we found that Macrin was taken up by macrophages with >90% selectivity. Uptake correlated with the content of macrophages in both healthy tissue and tumors ( R2 > 0.9) and showed striking heterogeneity in the TAM content of an orthotopic and immunocompetent mouse model of lung carcinoma. In a proof-of-principle application, we imaged Macrin to monitor the macrophage response to neo-adjuvant therapy, using a panel of chemotherapeutic and γ-irradiation regimens. Multiple treatments elicited 180-650% increase in TAMs. Imaging identified especially TAM-rich tumors thought to exhibit enhanced permeability and retention of nanotherapeutics. Indeed, these TAM-rich tumors accumulated >700% higher amounts of a model poly(d,l-lactic- co-glycolic acid)- b-polyethylene glycol (PLGA-PEG) therapeutic nanoparticle compared to TAM-deficient tumors, suggesting that imaging may guide patient selection into nanomedicine trials. In an orthotopic breast cancer model, chemoradiation enhanced TAM and Macrin accumulation in tumors, which corresponded to the improved delivery and efficacy of two model nanotherapies, PEGylated liposomal doxorubicin and a TAM-targeted nanoformulation of the toll-like receptor 7/8 agonist resiquimod (R848). Thus, Macrin imaging offers a selective and translational means to quantify TAMs and inform therapeutic decisions.

QuickCount®: a novel automated software for rapid cell detection and quantification

We describe a novel automated cell detection and counting software, QuickCount® (QC), designed for rapid quantification of cells. The Bland–Altman plot and intraclass correlation coefficient (ICC) analyses demonstrated strong agreement between cell counts from QC to manual counts (mean and SD: -3.3 ± 4.5; ICC = 0.95). QC has higher recall in comparison to ImageJauto, CellProfiler and CellC and the precision of QC, ImageJauto, CellProfiler and CellC are high and comparable. QC can precisely delineate and count single cells from images of different cell densities with precision and recall above 0.9. QC is unique as it is equipped with real-time preview while optimizing the parameters for accurate cell count and needs minimum hands-on time where hundreds of images can be analyzed automatically in a matter of milliseconds. In conclusion, QC offers a rapid, accurate and versatile solution for large-scale cell quantification and addresses the challenges often faced in cell biology research.

Constant abundances of ubiquitous uncultured protists in the open sea assessed by automated microscopy

Protists have fundamental ecological roles in marine environments and their diversity is being increasingly explored, yet little is known about the quantitative importance of specific taxa in these ecosystems. Here we optimized a newly developed automated system of image acquisition and image analysis to enumerate minute uncultured cells of different sizes targeted by fluorescence in situ hybridization. The automated counting routine was highly reproducible, well correlated with manual counts, and was then applied on surface and deep chlorophyll maximum samples from the Malaspina 2010 circumnavigation. The three targeted uncultured taxa (MAST-4, MAST-7 and MAST-1C) were found in virtually all samples from several ocean basins (Atlantic, Indian and Pacific) in fairly constant cell abundances, following typical lognormal distributions. Their global abundances averaged 49, 23 and 7 cells ml^-1 , respectively, and altogether the three groups accounted for about 10%-20% of heterotrophic picoeukaryotes. Our innovative high-throughput cell counting routine allows for the first time a direct assessment of the biogeographic distribution of small protists (< 5 μm) and shows the ubiquity in sunlit oceans of three bacterivorous taxa, suggesting their key roles in marine ecosystems.

Automated Bright Field Segmentation of Cells and Vacuoles Using Image Processing Technique

Understanding the mechanisms and other variants of programmed cell death will help provide deeper insight into various disease processes. Although complex procedures are required to distinguish each type of cell death, the formation of vacuoles is one of the important features in some process of cell death under different conditions. Thus, monitoring and counting the number of vacuoles and the ratio of cells with vacuoles is a commonly used method to indicate and quantify the efficacy of the therapy. Several studies have shown that image processing can provide a quick, convenient and precise mean of performing cell detection. Hence, this study uses an image processing technique to detect and quantify vacuolated cells without the need for dyes. The system both counts the number of vacuolated cells and determines the ratio of cells with vacuoles. The performance of the proposed image processing system was evaluated using 38 images. It has been shown that a strong correlation exists between the automated counts and the manual counts. Furthermore, the absolute percentage errors between automated counts and manual counts for cell detection and vacuolated cell detection using data pooled from all images are 3.61 and 3.33%, respectively. A user-friendly graphical user interface (GUI) is also developed and freely available for download, providing researchers in biomedicine with a more convenient instrument for vacuolization analysis.

A Multi-well Format Polyacrylamide-based Assay for Studying the Effect of Extracellular Matrix Stiffness on the Bacterial Infection of Adherent Cells

Extracellular matrix stiffness comprises one of the multiple environmental mechanical stimuli that are well known to influence cellular behavior, function, and fate in general. Although increasingly more adherent cell types' responses to matrix stiffness have been characterized, how adherent cells' susceptibility to bacterial infection depends on matrix stiffness is largely unknown, as is the effect of bacterial infection on the biomechanics of host cells. We hypothesize that the susceptibility of host endothelial cells to a bacterial infection depends on the stiffness of the matrix on which these cells reside, and that the infection of the host cells with bacteria will change their biomechanics. To test these two hypotheses, endothelial cells were used as model hosts and Listeria monocytogenes as a model pathogen. By developing a novel multi-well format assay, we show that the effect of matrix stiffness on infection of endothelial cells by L. monocytogenes can be quantitatively assessed through flow cytometry and immunostaining followed by microscopy. In addition, using traction force microscopy, the effect of L. monocytogenes infection on host endothelial cell biomechanics can be studied. The proposed method allows for the analysis of the effect of tissue-relevant mechanics on bacterial infection of adherent cells, which is a critical step towards understanding the biomechanical interactions between cells, their extracellular matrix, and pathogenic bacteria. This method is also applicable to a wide variety of other types of studies on cell biomechanics and response to substrate stiffness where it is important to be able to perform many replicates in parallel in each experiment.

CAS: Cell Annotation Software - Research on Neuronal Tissue Has Never Been so Transparent

CAS (Cell Annotation Software) is a novel tool for analysis of microscopic images and selection of the cell soma or nucleus, depending on the research objectives in medicine, biology, bioinformatics, etc. It replaces time-consuming and tiresome manual analysis of single images not only with automatic methods for object segmentation based on the Statistical Dominance Algorithm, but also semi-automatic tools for object selection within a marked region of interest. For each image, a broad set of object parameters is computed, including shape features and optical and topographic characteristics, thus giving additional insight into data. Our solution for cell detection and analysis has been verified by microscopic data and its application in the annotation of the lateral geniculate nucleus has been examined in a case study.

Microplastic pollution increases gene exchange in aquatic ecosystems

Pollution by microplastics in aquatic ecosystems is accumulating at an unprecedented scale, emerging as a new surface for biofilm formation and gene exchange. In this study, we determined the permissiveness of aquatic bacteria towards a model antibiotic resistance plasmid, comparing communities that form biofilms on microplastics vs. those that are free-living. We used an exogenous and red-fluorescent E. coli donor strain to introduce the green-fluorescent broad-host-range plasmid pKJK5 which encodes for trimethoprim resistance. We demonstrate an increased frequency of plasmid transfer in bacteria associated with microplastics compared to bacteria that are free-living or in natural aggregates. Moreover, comparison of communities grown on polycarbonate filters showed that increased gene exchange occurs in a broad range of phylogenetically-diverse bacteria. Our results indicate horizontal gene transfer in this habitat could distinctly affect the ecology of aquatic microbial communities on a global scale. The spread of antibiotic resistance through microplastics could also have profound consequences for the evolution of aquatic bacteria and poses a neglected hazard for human health.

Matrix stiffness modulates infection of endothelial cells by Listeria monocytogenes via expression of cell surface vimentin

Extracellular matrix stiffness (ECM) is one of the many mechanical forces acting on mammalian adherent cells and an important determinant of cellular function. While the effect of ECM stiffness on many aspects of cellular behavior has been studied previously, how ECM stiffness might mediate susceptibility of host cells to infection by bacterial pathogens is hitherto unexplored. To address this open question, we manufactured hydrogels of varying physiologically relevant stiffness and seeded human microvascular endothelial cells (HMEC-1) on them. We then infected HMEC-1 with the bacterial pathogen Listeria monocytogenes (Lm) and found that adhesion of Lm to host cells increases monotonically with increasing matrix stiffness, an effect that requires the activity of focal adhesion kinase (FAK). We identified cell surface vimentin as a candidate surface receptor mediating stiffness-dependent adhesion of Lm to HMEC-1 and found that bacterial infection of these host cells is decreased when the amount of surface vimentin is reduced. Our results provide the first evidence that ECM stiffness can mediate the susceptibility of mammalian host cells to infection by a bacterial pathogen.

Fast and simple tool for the quantification of biofilm-embedded cells sub-populations from fluorescent microscopic images

Fluorescent staining is a common tool for both quantitative and qualitative assessment of pro- and eukaryotic cells sub-population fractions by using microscopy and flow cytometry. However, direct cell counting by flow cytometry is often limited, for example when working with cells rigidly adhered either to each other or to external surfaces like bacterial biofilms or adherent cell lines and tissue samples. An alternative approach is provided by using fluorescent microscopy and confocal laser scanning microscopy (CLSM), which enables the evaluation of fractions of cells subpopulations in a given sample. For the quantitative assessment of cell fractions in microphotographs, we suggest a simple two-step algorithm that combines single cells selection and the statistical analysis. To facilitate the first step, we suggest a simple procedure that supports finding the balance between the detection threshold and the typical size of single cells based on objective cell size distribution analysis. Based on a series of experimental measurements performed on bacterial and eukaryotic cells under various conditions, we show explicitly that the suggested approach effectively accounts for the fractions of different cell sub-populations (like the live/dead staining in our samples) in all studied cases that are in good agreement with manual cell counting on microphotographs and flow cytometry data. This algorithm is implemented as a simple software tool that includes an intuitive and user-friendly graphical interface for the initial adjustment of algorithm parameters to the microphotographs analysis as well as for the sequential analysis of homogeneous series of similar microscopic images without further user intervention. The software tool entitled BioFilmAnalyzer is freely available online at https://bitbucket.org/rogex/biofilmanalyzer/downloads/.

Quantitative Phenotypic Image Analysis of Three-Dimensional Organotypic Cultures

Glandular epithelial cells differentiate into three-dimensional (3D) multicellular or acinar structures, particularly when embedded in laminin-rich extracellular matrix (ECM). The spectrum of different multicellular morphologies formed in 3D is a reliable indicator for the differentiation potential of normal, non-transformed cells compared to different stages of malignant progression. Motile cancer cells may actively invade the matrix, utilizing epithelial, mesenchymal, or mixed modes of motility. Dynamic phenotypic changes involved in 3D tumor cell invasion are also very sensitive to small-molecule inhibitors that, e.g., target the actin cytoskeleton. Our strategy is to recapitulate the formation and the histology of complex solid cancer tissues in vitro, based on cell culture technologies that promote the intrinsic differentiation potential of normal and transformed epithelial cells, and also including stromal fibroblasts and other key components of the tumor microenvironment. We have developed a streamlined stand-alone software solution that supports the detailed quantitative phenotypic analysis of organotypic 3D cultures. This approach utilizes the power of automated image analysis as a phenotypic readout in cell-based assays. AMIDA (Automated Morphometric Image Data Analysis) allows quantitative measurements of a large number of multicellular structures, which can form a multitude of different organoid shapes, sizes, and textures according to their capacity to engage in epithelial differentiation programs or not. At the far end of this spectrum of tumor-relevant differentiation properties, there are highly invasive tumor cells or multicellular structures that may rapidly invade the surrounding ECM, but fail to form higher-order epithelial tissue structures. Furthermore, this system allows us to monitor dynamic changes that can result from the extraordinary plasticity of tumor cells, e.g., epithelial-to-mesenchymal transition in live cell settings. Furthermore, AMIDA supports an automated workflow, and can be combined with quality control and statistical tools for data interpretation and visualization. Our approach supports the growing needs for user-friendly, straightforward solutions that facilitate cell-based organotypic 3D assays in basic research, drug discovery, and target validation.

Single-molecule techniques in biophysics: a review of the progress in methods and applications

Single-molecule biophysics has transformed our understanding of biology, but also of the physics of life. More exotic than simple soft matter, biomatter lives far from thermal equilibrium, covering multiple lengths from the nanoscale of single molecules to up to several orders of magnitude higher in cells, tissues and organisms. Biomolecules are often characterized by underlying instability: multiple metastable free energy states exist, separated by levels of just a few multiples of the thermal energy scale k _B T, where k _B is the Boltzmann constant and T absolute temperature, implying complex inter-conversion kinetics in the relatively hot, wet environment of active biological matter. A key benefit of single-molecule biophysics techniques is their ability to probe heterogeneity of free energy states across a molecular population, too challenging in general for conventional ensemble average approaches. Parallel developments in experimental and computational techniques have catalysed the birth of multiplexed, correlative techniques to tackle previously intractable biological questions. Experimentally, progress has been driven by improvements in sensitivity and speed of detectors, and the stability and efficiency of light sources, probes and microfluidics. We discuss the motivation and requirements for these recent experiments, including the underpinning mathematics. These methods are broadly divided into tools which detect molecules and those which manipulate them. For the former we discuss the progress of super-resolution microscopy, transformative for addressing many longstanding questions in the life sciences, and for the latter we include progress in 'force spectroscopy' techniques that mechanically perturb molecules. We also consider in silico progress of single-molecule computational physics, and how simulation and experimentation may be drawn together to give a more complete understanding. Increasingly, combinatorial techniques are now used, including correlative atomic force microscopy and fluorescence imaging, to probe questions closer to native physiological behaviour. We identify the trade-offs, limitations and applications of these techniques, and discuss exciting new directions.

The effects of high dose of two manganese supplements (organic and inorganic) on the rumen microbial ecosystem

Little is known about the effects of the high dose and types of manganese supplements on rumen environment at manganese intake level close above the limit of 150 mg/kg of dry feed matter. The effects of high dose of two manganese supplements (organic and inorganic) on rumen microbial ecosystem after four months of treatment of 18 lambs divided into three treatment groups were studied. We examined the enzyme activities (α-amylase, xylanase, and carboxymethyl cellulase), total and differential microscopic counts of rumen ciliates, total microscopic counts of bacteria, and fingerprinting pattern of the eubacterial and ciliates population analyzed by PCR-DGGE. Lambs were fed a basal diet with a basal Mn content (34.3 mg/kg dry matter; control) and supplemented either with inorganic manganous sulfate or organic Mn-chelate hydrate (daily 182.7, 184 mg/kg dry matter of feed, respectively). Basal diet, offered twice daily, consisted of ground barley and hay (268 and 732 g/kg dry matter per animal and day). The rumens of the lambs harbored ciliates of the genera of Entodinium, Epidinium, Diplodinium, Eudiplodinium, Dasytricha, and Isotricha. No significant differences between treatment groups were observed in the total ciliate number, the number of ciliates at the genus level, as well as the total number of bacteria. Organic Mn did decrease the species richness and diversity of the eubacterial population examined by PCR-DGGE. No effects of type of Mn supplement on the enzyme activities were observed. In comparison to the control, α-amylase specific activities were decreased and carboxymethyl-cellulase specific activities were increased by the Mn supplements. Xylanase activities were not influenced. In conclusion, our results suggested that the intake of tested inorganic and organic manganese supplements in excess may affect the specific groups of eubacteria. More studies on intake of Mn supplements at a level close to the limit can reveal if the changes in microbial population impact remarkably the other rumen enzymatic activities.