High-Throughput Method for Automated Colony and Cell Counting by Digital Image Analysis Based on Edge Detection

Systematic optimization of culture media for maintenance of human induced pluripotent stem cells using the response surface methodology

The application of human induced pluripotent stem cells (hiPSCs) provides tremendous opportunities in cell therapy. However, culturing these cells faces many practical challenges, including costs associated with cell culture media and the optimization of cell culture conditions. Providing an optimized culture platform for hiPSCs to maintain pluripotency and self-renewal and generate cost-effective and robust therapeutics is an immediate requirement. This study used the design of experiments and the response surface methodology, a powerful statistical tool, to generate empirical models for predicting the optimal culture conditions of the hiPSCs. Pluripotency and cell proliferation were applied as read-outs to determine the optimal concentration of basic fibroblast growth factor (bFGF) and cell density. One model was defined to predict pluripotency and cell proliferation in terms of the predictor variables of the bFGF concentration and cell seeding density. Predicted culture conditions to maximize maintaining cell pluripotency were successfully validated. The present study's findings provide a novel approach that can potentially allow controllable hiPSC culture routine in translational research.

HERC5 downregulation in non-small cell lung cancer is associated with altered energy metabolism and metastasis

BACKGROUND

Metastasis is the leading cause of cancer-related death in non-small cell lung cancer (NSCLC) patients. We previously showed that low HERC5 expression predicts early tumor dissemination and a dismal prognosis in NSCLC patients. Here, we performed functional studies to unravel the mechanism underlying the "metastasis-suppressor" effect of HERC5, with a focus on mitochondrial metabolism pathways.

METHODS

We assessed cell proliferation, colony formation potential, anchorage-independent growth, migration, and wound healing in NSCLC cell line models with HERC5 overexpression (OE) or knockout (KO). To study early tumor cell dissemination, we used these cell line models in zebrafish experiments and performed intracardial injections in nude mice. Mass spectrometry (MS) was used to analyze protein changes in whole-cell extracts. Furthermore, electron microscopy (EM) imaging, cellular respiration, glycolytic activity, and lactate production were used to investigate the relationships with mitochondrial energy metabolism pathways.

RESULTS

Using different in vitro NSCLC cell line models, we showed that NSCLC cells with low HERC5 expression had increased malignant and invasive properties. Furthermore, two different in vivo models in zebrafish and a xenograft mouse model showed increased dissemination and metastasis formation (in particular in the brain). Functional enrichment clustering of MS data revealed an increase in mitochondrial proteins in vitro when HERC5 levels were high. Loss of HERC5 leads to an increased Warburg effect, leading to improved adaptation and survival under prolonged inhibition of oxidative phosphorylation.

CONCLUSIONS

Taken together, these results indicate that low HERC5 expression increases the metastatic potential of NSCLC in vitro and in vivo. Furthermore, HERC5-induced proteomic changes influence mitochondrial pathways, ultimately leading to alterations in energy metabolism and demonstrating its role as a new potential metastasis suppressor gene.

Nondestructive, quantitative viability analysis of 3D tissue cultures using machine learning image segmentation

Ascertaining the collective viability of cells in different cell culture conditions has typically relied on averaging colorimetric indicators and is often reported out in simple binary readouts. Recent research has combined viability assessment techniques with image-based deep-learning models to automate the characterization of cellular properties. However, further development of viability measurements to assess the continuity of possible cellular states and responses to perturbation across cell culture conditions is needed. In this work, we demonstrate an image processing algorithm for quantifying features associated with cellular viability in 3D cultures without the need for assay-based indicators. We show that our algorithm performs similarly to a pair of human experts in whole-well images over a range of days and culture matrix compositions. To demonstrate potential utility, we perform a longitudinal study investigating the impact of a known therapeutic on pancreatic cancer spheroids. Using images taken with a high content imaging system, the algorithm successfully tracks viability at the individual spheroid and whole-well level. The method we propose reduces analysis time by 97% in comparison with the experts. Because the method is independent of the microscope or imaging system used, this approach lays the foundation for accelerating progress in and for improving the robustness and reproducibility of 3D culture analysis across biological and clinical research.

Differential effects of sleep deprivation on behavior and microglia in a brain-region-specific manner in young and aged male mice

Microglia, resident immune cells in the central nervous system, constantly monitor the state of the surrounding brain activity. The animal model induced by sleep deprivation (SD) is widely used to study the pathophysiological mechanisms of insomnia and bipolar disorder. However, it remains unclear whether SD affects behaviors in young and aged male mice and microglia in various brain regions. In this study, we confirmed brain region-specific changes in microglial density and morphology in the accumbens nucleus (Acb), amygdala (AMY), cerebellum (Cb), corpus callosum (cc), caudate putamen, hippocampus (HIP), hypothalamus (HYP), medial prefrontal cortex (mPFC), and thalamus (TH) of young mice. In addition, the density of microglia in old mice was higher than that in young mice. Compared with young mice, old mice showed a markedly increased microglial size, decreased total length of microglial processes, and decreased maximum length. Importantly, we found that 48-h SD decreased microglial density and morphology in old mice, whereas SD increased microglial density and morphology in most observed brain regions in young mice. SD-induced hyperactivity was observed only in young mice but not in old mice. Moreover, microglial density (HIP, AMY, mPFC, CPu) was significantly positively correlated with behaviors in SD- and vehicle-treated young mice. Contrarily, negative correlations were shown between the microglial density (cc, Cb, TH, HYP, Acb, AMY) and behaviors in vehicle-treated young and old mice. These results suggest that SD dysregulates the homeostatic state of microglia in a region- and age-dependent manner. Microglia may be involved in regulating age-related behavioral responses to SD.

Engrailed-1 Promotes Pancreatic Cancer Metastasis

Engrailed-1 (EN1) is a critical homeodomain transcription factor (TF) required for neuronal survival, and EN1 expression has been shown to promote aggressive forms of triple negative breast cancer. Here, it is reported that EN1 is aberrantly expressed in a subset of pancreatic ductal adenocarcinoma (PDA) patients with poor outcomes. EN1 predominantly repressed its target genes through direct binding to gene enhancers and promoters, implicating roles in the activation of MAPK pathways and the acquisition of mesenchymal cell properties. Gain- and loss-of-function experiments demonstrated that EN1 promoted PDA transformation and metastasis in vitro and in vivo. The findings nominate the targeting of EN1 and downstream pathways in aggressive PDA.

Agricultural intensification reduces selection of putative plant growth-promoting rhizobacteria in wheat

The complex evolutionary history of wheat has shaped its associated root microbial community. However, consideration of impacts from agricultural intensification has been limited. This study investigated how endogenous (genome polyploidization) and exogenous (introduction of chemical fertilizers) factors have shaped beneficial rhizobacterial selection. We combined culture-independent and -dependent methods to analyze rhizobacterial community composition and its associated functions at the root-soil interface from a range of ancestral and modern wheat genotypes, grown with and without the addition of chemical fertilizer. In controlled pot experiments, fertilization and soil compartment (rhizosphere, rhizoplane) were the dominant factors shaping rhizobacterial community composition, whereas the expansion of the wheat genome from diploid to allopolyploid caused the next greatest variation. Rhizoplane-derived culturable bacterial collections tested for plant growth-promoting (PGP) traits revealed that fertilization reduced the abundance of putative plant growth-promoting rhizobacteria in allopolyploid wheats but not in wild wheat progenitors. Taxonomic classification of these isolates showed that these differences were largely driven by reduced selection of beneficial root bacteria representative of the Bacteroidota phylum in allopolyploid wheats. Furthermore, the complexity of supported beneficial bacterial populations in hexaploid wheats was greatly reduced in comparison to diploid wild wheats. We therefore propose that the selection of root-associated bacterial genera with PGP functions may be impaired by crop domestication in a fertilizer-dependent manner, a potentially crucial finding to direct future plant breeding programs to improve crop production systems in a changing environment.

A high-throughput and low-waste viability assay for microbes

Counting viable cells is a universal practice in microbiology. The colony-forming unit (CFU) assay has remained the gold standard to measure viability across disciplines, but it is time-intensive and resource-consuming. Here we describe the geometric viability assay (GVA) that replicates CFU measurements over 6 orders of magnitude while reducing over 10-fold the time and consumables required. GVA computes a sample's viable cell count on the basis of the distribution of embedded colonies growing inside a pipette tip. GVA is compatible with Gram-positive and Gram-negative planktonic bacteria (Escherichia coli, Pseudomonas aeruginosa and Bacillus subtilis), biofilms and fungi (Saccharomyces cerevisiae). Laborious CFU experiments such as checkerboard assays, treatment time-courses and drug screens against slow-growing cells are simplified by GVA. The ease and low cost of GVA evinces that it can replace existing viability assays and enable viability measurements at previously impractical scales.

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.

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.

Depletion of microglia with PLX3397 attenuates MK-801-induced hyperactivity associated with regulating inflammation-related genes in the brain

Acute administration of MK-801 (dizocilpine), an N-methyl-D-aspartate receptor (NMDAR) antagonist, can establish animal models of psychiatric disorders. However, the roles of microglia and inflammation-related genes in these animal models of psychiatric disorders remain unknown. Here, we found rapid elimination of microglia in the prefrontal cortex (PFC) and hippocampus (HPC) of mice following administration of the dual colony-stimulating factor 1 receptor (CSF1R)/c-Kit kinase inhibitor PLX3397 (pexidartinib) in drinking water. Single administration of MK-801 induced hyperactivity in the open-field test (OFT). Importantly, PLX3397-induced depletion of microglia prevented the hyperactivity and schizophrenia-like behaviors induced by MK-801. However, neither repopulation of microglia nor inhibition of microglial activation by minocycline affected MK-801-induced hyperactivity. Importantly, microglial density in the PFC and HPC was significantly correlated with behavioral changes. In addition, common and distinct glutamate-, GABA-, and inflammation-related gene (116 genes) expression patterns were observed in the brains of PLX3397- and/or MK-801-treated mice. Moreover, 10 common inflammation-related genes ( CD68, CD163, CD206, TMEM119, CSF3R, CX3CR1, TREM2, CD11b, CSF1R, and F4/80) with very strong correlations were identified in the brain using hierarchical clustering analysis. Further correlation analysis demonstrated that the behavioral changes in the OFT were most significantly associated with the expression of inflammation-related genes ( NLRP3, CD163, CD206, F4/80, TMEM119, and TMEM176a), but not glutamate- or GABA-related genes in PLX3397- and MK-801-treated mice. Thus, our results suggest that microglial depletion via a CSF1R/c-Kit kinase inhibitor can ameliorate the hyperactivity induced by an NMDAR antagonist, which is associated with modulation of immune-related genes in the brain.

High Throughput Viability Assay for Microbiology

Counting viable cells is a universal practice in microbiology. The colony forming unit (CFU) assay has remained the gold standard to measure viability across disciplines; however, it is time-intensive and resource-consuming. Herein, we describe the Geometric Viability Assay (GVA) that replicates CFU measurements over 6-orders of magnitude while reducing over 10-fold the time and consumables. GVA computes a sample's viable cell count based on the distribution of embedded colonies growing inside a pipette tip. GVA is compatible with gram-positive and -negative planktonic bacteria, biofilms, and yeast. Laborious CFU experiments such as checkerboard assays, treatment time-courses, and drug screens against slow-growing cells are simplified by GVA. We therefore screened a drug library against exponential and stationary phase E. coli leading to the discovery of the ROS-mediated, bactericidal mechanism of diphenyliodonium. The ease and low cost of GVA evinces it can accelerate existing viability assays and enable measurements at previously impractical scales.

Using Bland-Altman Analysis to Identify Appropriate Clonogenic Assay Colony Counting Techniques

OBJECTIVE

Determine the interchangeability of various methods utilized for counting colonies in clonogenic assays.

METHODS

Clonogenic assays of 2 head and neck cancer cell lines were counted through 4 different counting modalities: Manual counting pen, via microscope, 1 publicly available automated algorithm, and a semiautomated algorithm presented by the authors. Each method counted individual wells (N = 24). Pen and microscopic counts were performed by 2 observers. Parameters included both low-growth (<150 colonies/well) and high-growth (>150 colonies/well) cell lines. Correlational and Bland-Altman analyses were performed using SPSS software.

RESULTS

Interobserver manual pen count correlation R2 value in both growth conditions was 0.902; controlling for only low-growth conditions decreased R2 to 0.660. Correlation of microscopic versus pen counts R2 values for observers 1 and 2 were 0.955 and 0.775, respectively. Comparing techniques, Bland-Altman revealed potential bias with respect to the magnitude of measurement (P < .001) for both observers. Correlation of microscopic counts for both interobserver (R2 = 0.902) and intraobserver (R2 = 0.916) were analyzed. Bland-Altman revealed no bias (P = .489). Automated versus microscopic counts revealed no bias between methodologies (P = .787) and a lower correlation coefficient (R2 = 0.384). Semiautomated versus microscopic counts revealed no bias with respect to magnitude of measurement for either observer (P = .327, .229); Pearson correlation was 0.985 (R2 = 0.970) and 0.965 (R2 = 0.931) for observer 1 and 2. Semiautomated versus manual pen colony counts revealed a significant bias with respect to magnitude of measurement (P < .001).

CONCLUSION

Counting with a manual pen demonstrated significant bias when compared to microscopic and semiautomated colony counts; 2 methods were deemed to be interchangeable. Thus, training algorithms based on manual counts may introduce this bias as well. Algorithms trained to select colonies based on size (pixels2) and shape (circularity) should be prioritized. Solely relying on Bland-Altman or correlational analyses when determining method interchangeability should be avoided; they rather should be used in conjunction.

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.

Novel prokaryotic system employing previously unknown nucleic acids-based receptors

The present study describes a previously unknown universal system that orchestrates the interaction of bacteria with the environment, named the Teazeled receptor system (TR-system). The identical system was recently discovered within eukaryotes. The system includes DNA- and RNA-based molecules named "TezRs", that form receptor's network located outside the membrane, as well as reverse transcriptases and integrases. TR-system takes part in the control of all major aspects of bacterial behavior, such as intra cellular communication, growth, biofilm formation and dispersal, utilization of nutrients including xenobiotics, virulence, chemo- and magnetoreception, response to external factors (e.g., temperature, UV, light and gas content), mutation events, phage-host interaction, and DNA recombination activity. Additionally, it supervises the function of other receptor-mediated signaling pathways. Importantly, the TR-system is responsible for the formation and maintenance of cell memory to preceding cellular events, as well the ability to "forget" preceding events. Transcriptome and biochemical analysis revealed that the loss of different TezRs instigates significant alterations in gene expression and proteins synthesis.

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.

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.

Trigeminal Nerve Stimulation Improves Cerebral Macrocirculation and Microcirculation After Subarachnoid Hemorrhage: An Exploratory Study

BACKGROUND

Delayed cerebral ischemia (DCI) is the most consequential secondary insult after aneurysmal subarachnoid hemorrhage (SAH). It is a multifactorial process caused by a combination of large artery vasospasm and microcirculatory dysregulation. Despite numerous efforts, no effective therapeutic strategies are available to prevent DCI. The trigeminal nerve richly innervates cerebral blood vessels and releases a host of vasoactive agents upon stimulation. As such, electrical trigeminal nerve stimulation (TNS) has the capability of enhancing cerebral circulation.

OBJECTIVE

To determine whether TNS can restore impaired cerebral macrocirculation and microcirculation in an experimental rat model of SAH.

METHODS

The animals were randomly assigned to sham-operated, SAH-control, and SAH-TNS groups. SAH was induced by endovascular perforation on Day 0, followed by KCl-induced cortical spreading depolarization on day 1, and sample collection on day 2. TNS was delivered on day 1. Multiple end points were assessed including cerebral vasospasm, microvascular spasm, microthrombosis, calcitonin gene-related peptide and intercellular adhesion molecule-1 concentrations, degree of cerebral ischemia and apoptosis, and neurobehavioral outcomes.

RESULTS

SAH resulted in significant vasoconstriction in both major cerebral vessels and cortical pial arterioles. Compared with the SAH-control group, TNS increased lumen diameters of the internal carotid artery, middle cerebral artery, and anterior cerebral artery, and decreased pial arteriolar wall thickness. Additionally, TNS increased cerebrospinal fluid calcitonin gene-related peptide levels, and decreased cortical intercellular adhesion molecule-1 expression, parenchymal microthrombi formation, ischemia-induced hypoxic injury, cellular apoptosis, and neurobehavioral deficits.

CONCLUSION

Our results suggest that TNS can enhance cerebral circulation at multiple levels, lessen the impact of cerebral ischemia, and ameliorate the consequences of DCI after SAH.

Sexual dimorphism in the bed nucleus of the stria terminalis, medial preoptic area and suprachiasmatic nucleus in male and female tree shrews

Sex differences in behaviour partly arise from the sexual dimorphism of brain anatomy between males and females. However, the sexual dimorphism of the tree shrew brain is unclear. In the present study, we examined the detailed distribution of vasoactive intestinal polypeptide-immunoreactive (VIP-ir) neurons and fibres in the suprachiasmatic nucleus (SCN) and VIP-ir fibres in the bed nucleus of the stria terminalis (BST) of male and female tree shrews. The overall volume of the SCN in male tree shrews was comparable with that in females. However, males showed a significantly higher density of VIP-ir cells and fibres in the SCN than females. The shape of the VIP-stained area in coronal sections was arched, elongated or oval in the lateral division (STL) and the anterior part of the medial division (STMA) of the BST and oval or round in the posterior part of the medial division of the BST (STMP). The volume of the VIP-stained BST in male tree shrews was similar to that in females. The overall distribution of VIP-ir fibres was similar between the sexes throughout the BST except within the STMA, where darkly stained fibres were observed in males, whereas lightly stained fibres were observed in females. Furthermore, male tree shrews showed a significantly higher intensity of Nissl staining in the medial preoptic area (MPA) and the ventral part of the medial division of the BST than females. These findings are the first to reveal sexual dimorphism in the SCN, BST and MPA of the tree shrew brain, providing neuroanatomical evidence of sexual dimorphism in these regions related to their roles in sex differences in physiology and behaviour.

Histone Acetylation Defects in Brain Precursor Cells: A Potential Pathogenic Mechanism Causing Proliferation and Differentiation Dysfunctions in Mitochondrial Aspartate-Glutamate Carrier Isoform 1 Deficiency

Mitochondrial aspartate-glutamate carrier isoform 1 (AGC1) deficiency is an ultra-rare genetic disease characterized by global hypomyelination and brain atrophy, caused by mutations in the SLC25A12 gene leading to a reduction in AGC1 activity. In both neuronal precursor cells and oligodendrocytes precursor cells (NPCs and OPCs), the AGC1 determines reduced proliferation with an accelerated differentiation of OPCs, both associated with gene expression dysregulation. Epigenetic regulation of gene expression through histone acetylation plays a crucial role in the proliferation/differentiation of both NPCs and OPCs and is modulated by mitochondrial metabolism. In AGC1 deficiency models, both OPCs and NPCs show an altered expression of transcription factors involved in the proliferation/differentiation of brain precursor cells (BPCs) as well as a reduction in histone acetylation with a parallel alteration in the expression and activity of histone acetyltransferases (HATs) and histone deacetylases (HDACs). In this study, histone acetylation dysfunctions have been dissected in in vitro models of AGC1 deficiency OPCs (Oli-Neu cells) and NPCs (neurospheres), in physiological conditions and following pharmacological treatments. The inhibition of HATs by curcumin arrests the proliferation of OPCs leading to their differentiation, while the inhibition of HDACs by suberanilohydroxamic acid (SAHA) has only a limited effect on proliferation, but it significantly stimulates the differentiation of OPCs. In NPCs, both treatments determine an alteration in the commitment toward glial cells. These data contribute to clarifying the molecular and epigenetic mechanisms regulating the proliferation/differentiation of OPCs and NPCs. This will help to identify potential targets for new therapeutic approaches that are able to increase the OPCs pool and to sustain their differentiation toward oligodendrocytes and to myelination/remyelination processes in AGC1 deficiency, as well as in other white matter neuropathologies.

Influence of Glucose Concentration on Colony-Forming Efficiency and Biological Performance of Primary Human Tissue-Derived Progenitor Cells

OBJECTIVE

Glucose concentrations used in current cell culture methods are a significant departure from physiological glucose levels. The study focuses on comparing the effects of glucose concentrations on primary human progenitors (connective tissue progenitors [CTPs]) used for cartilage repair.

DESIGN

Cartilage- (Outerbridge grade 1, 2, 3; superficial and deep zone cartilage), infrapatellar fatpad-, synovium-, and periosteum-derived cells were obtained from 63 patients undergoing total knee arthroplasty and cultured simultaneously in fresh chondrogenic media containing 25 mM glucose (HGL) or 5 mM glucose (NGL) for pairwise comparison. Automated ASTM-based quantitative image analysis was used to determine colony-forming efficiency (CFE), effective proliferation rates (EPR), and sulfated-proteoglycan (GAG-ECM) staining of the CTPs across tissue sources.

RESULTS

HGL resulted in increased cell cultures with CFE = 0 compared with NGL in all tissue sources (P = 0.049). The CFE in NGL was higher than HGL for superficial cartilage (P < 0.001), and contrary for synovium-derived CTPs (P = 0.046) when CFE > 0. EPR of the CTPs did not differ between the media in the 6-day assay time period (P = 0.082). The GAG-ECM area of the CTPs and their progeny was increased in presence of HGL (P = 0.027).

CONCLUSION

Glucose concentration is critical to progenitor's physiology and should be taken into account in the setting of protocols for clinical or in vitro cell expansion strategies.

Analysis of clonogenic growth in vitro

The clonogenic assay measures the capacity of single cells to form colonies in vitro. It is widely used to identify and quantify self-renewing mammalian cells derived from in vitro cultures as well as from ex vivo tissue preparations of different origins. Varying research questions and the heterogeneous growth requirements of individual cell model systems led to the development of several assay principles and formats that differ with regard to their conceptual setup, 2D or 3D culture conditions, optional cytotoxic treatments and subsequent mathematical analysis. The protocol presented here is based on the initial clonogenic assay protocol as developed by Puck and Marcus more than 60 years ago. It updates and extends the 2006 Nature Protocols article by Franken et al. It discusses different strategies and principles to analyze clonogenic growth in vitro and presents the clonogenic assay in a modular protocol framework enabling a diversity of formats and measures to optimize determination of clonogenic growth parameters. We put particular focus on the phenomenon of cellular cooperation and consideration of how this can affect the mathematical analysis of survival data. This protocol is applicable to any mammalian cell model system from which single-cell suspensions can be prepared and which contains at least a small fraction of cells with self-renewing capacity in vitro. Depending on the cell system used, the entire procedure takes ~2-10 weeks, with a total hands-on time of <20 h per biological replicate.

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.

Hollow Dodecahedra Graphene Oxide- Cuprous Oxide Nanocomposites With Effective Photocatalytic and Bactericidal Activity

In this study, a kind of graphene oxide-cuprous oxide (GO-Cu₂O) nanocomposites was fabricated with different morphologies to serve as a photocatalytic material for the degradation of organic/inorganic dyes under visible light and the bactericidal effect against pathogenic bacteria. The GO-Cu₂O was prepared with solid cube and hollow dodecahedra morphologies through in-situ synthesis, and characterized by scanning electron microscopy (SEM), transmission electron microscope (TEM), X-ray diffraction (XRD), Raman, Ultraviolet and visible spectrophotometry (UV/vis), and Fourier transform infrared spectroscopy. In comparison with cubic GO-Cu₂O, the absorption and degradation efficiency of the GO-Cu₂O dodecahedra (GCD) composite in Methyl orange (MO), Rhodamine B (RhB), and phenol was higher owning to the more active sites for the simultaneous dye and light absorption of hollow structure. The antibacterial effect of the GO-Cu2O dodecahedra was examined by the flat colony counting method with an excellent bactericidal effect against pathogenic bacteria. The possible mechanism for the preparation of GCD possessing the enhancement of the visible-light photocatalytic and antibacterial efficiencies were also investigated.

Development of convolutional neural networks for recognition of tenogenic differentiation based on cellular morphology

BACKGROUND AND OBJECTIVE

The use of automated systems for image recognition is highly preferred for regenerative medicine applications to evaluate stem cell differentiation early in the culturing state with non-invasive methodologies instead of invasive counterparts. Bone marrow-derived mesenchymal stem cells (BMSCs) are able to differentiate into desired cell phenotypes, and thereby promise a proper cell source for tendon regeneration. The therapeutic success of stem cell therapy requires cellular characterization prior to the implantation of cells. The foremost problem is that traditional characterization techniques require cellular material which would be more useful for cell therapy, complex laboratory procedures, and human expertise. Convolutional neural networks (CNNs), a class of deep neural networks, have recently made great improvements in image-based classifications, recognition, and detection tasks. We, therefore, aim to develop a potential CNN model in order to recognize differentiated stem cells by learning features directly from image data of unlabelled cells.

METHODS

The differentiation of bone marrow mesenchymal stem cells (BMSCs) into tenocytes was induced with the treatment of bone morphogenetic protein-12 (BMP-12). Following the treatment and incubation step, the phase-contrast images of cells were obtained and immunofluorescence staining has been applied to characterize the differentiated state of BMSCs. CNN models were developed and trained with the phase-contrast cell images. The comparison of CNN models was performed with respect to prediction performance and training time. Moreover, we have evaluated the effect of image enhancement method, data augmentation, and fine-tuning training strategy to increase classification accuracy of CNN models. The best model was integrated into a mobile application.

RESULTS

All the CNN models can fit the biological data extracted from immunofluorescence characterization. CNN models enable the cell classification with satisfactory accuracies. The best result in terms of accuracy and training time is achieved by the model proposed based on Inception-ResNet V2 trained from scratch using image enhancement and data augmentation strategies (96.80%, 434.55 sec).

CONCLUSION

Our study reveals that the CNN models show good performance by identifying stem cell differentiation. Importantly this technique provides a faster and real-time tool in comparison to traditional methods enabling the adjustment of culture conditions during cultivation to improve the yield of therapeutic stem cells.

Automatic cell counting for phase-contrast microscopic images based on a combination of Otsu and watershed segmentation method

Cell counting plays a vital role in biomedical researches. However, manual cell counting is time-consuming, laborious, and low efficiency and has a high counting error rate problem. An automatic counting approach for Hela cells of phase-contrast microscopic images is proposed based on the combination of Otsu and watershed segmentation methods to solve the mentioned issues. Firstly, image preprocessing is performed. Secondly, the Otsu method was used to obtain an automatic global optimal threshold for segmentation to achieve batch counting of images. Thirdly, the marker watershed was performed to separate adherent cells and to avoid over-segmentation simultaneously. Finally, cells in phase-contrast microscopic images were counted by detecting the numbers of connected domains in the binary image. Taking the manual counting result as the counting standard and MIS, INC, and ACC are used as evaluation indicators. The experimental results showed that the average values of MIS, INC, and ACC of the proposed method are only 3.31%, 3.49%, and 96.69%, respectively. Additionally, each cell image was counted only takes 0.65 s on averagely. To further test the performance of the proposed method, a comparative experiment was carried out by Image J, and the result shows that the proposed method has a better counting performance with a higher average accuracy of 96.55% to Image J with 93.39%.The proposed method for cell counting is simple, feasible, fast and high accurate, and it can be used as an effective method for cell counting of the phase-contrast microscopic images.

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.

Preparation of graphene oxide (GO)/lanthanum coordination polymers for enhancement of bactericidal activity

In this study, graphene oxide/lanthanum coordination polymer (GLCP) nanocomposites are prepared and their bactericidal activities against seven typical Pathogenic bacteria are evaluated. The GLCPs are fabricated through the electrostatic self-assembly of La ions on negatively charged graphene oxide (GO), followed by the stabilization of π-π stacking to ensure the formation of lanthanum coordination polymers on the GO surface. The morphologies and structures of the synthesized GLCPs are characterized using scanning electron microscopy (SEM), transmission electron microscopy (TEM), ultraviolet-visible (UV-vis) spectroscopy, Fourier transform infrared (FT-IR) spectroscopy, X-ray photoelectron spectroscopy (XPS) and thermogravimetric analysis (TGA). Moreover, the bactericidal effects of the well-coordinated GLCPs are investigated using the zone of inhibition and flat colony counting methods, as well as by determining the minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC). The five GLCPs synthesized in this study exhibit broad-spectrum antibacterial activities against seven typical Pathogenic bacteria. We believe that our study could serve as a starting point to prepare bactericidal materials for further applications.

Automated evaluation of tumor spheroid behavior in 3D culture using deep learning-based recognition

Three-dimensional in vitro tumor models provide more physiologically relevant responses to drugs than 2D models, but the lack of proper evaluation indices and the laborious quantitation of tumor behavior in 3D have limited the use of 3D tumor models in large-scale preclinical drug screening. Here we propose two indices of 3D tumor invasiveness-the excess perimeter index (EPI) and the multiscale entropy index (MSEI)-and combine these indices with a new convolutional neural network-based algorithm for tumor spheroid boundary detection. This new algorithm for 3D tumor boundary detection and invasiveness analysis is more accurate than any other existing algorithms. We apply this spheroid monitoring and AI-based recognition technique ("SMART") to evaluating the invasiveness of tumor spheroids grown from tumor cell lines and from primary tumor cells in 3D culture.

Effects of Simulated Microgravity on the Proteome and Secretome of the Polyextremotolerant Black Fungus Knufia chersonesos

Black fungi are a group of melanotic microfungi characterized by remarkable polyextremotolerance. Due to a broad ecological plasticity and adaptations at the cellular level, it is predicted that they may survive in a variety of extreme environments, including harsh niches on Earth and Mars, and in outer space. However, the molecular mechanisms aiding survival, especially in space, are yet to be fully elucidated. Based on these premises, the rock-inhabiting black fungus Knufia chersonesos (Wt) and its non-melanized mutant (Mut) were exposed to simulated microgravity-one of the prevalent features characterizing space conditions-by growing the cultures in high-aspect-ratio vessels (HARVs). Qualitative and quantitative proteomic analyses were performed on the mycelia and supernatant of culture medium (secretome) to assess alterations in cell physiology in response to low-shear simulated microgravity (LSSMG) and to ultimately evaluate the role of cell-wall melanization in stress survival. Differential expression was observed for proteins involved in carbohydrate and lipid metabolic processes, transport, and ribosome biogenesis and translation via ribosomal translational machinery. However, no evidence of significant activation of stress components or starvation response was detected, except for the scytalone dehydratase, enzyme involved in the synthesis of dihydroxynaphthalene (DNH) melanin, which was found to be upregulated in the secretome of the wild type and downregulated in the mutant. Differences in protein modulation were observed between K. chersonesos Wt and Mut, with several proteins being downregulated under LSSMG in the Mut when compared to the Wt. Lastly, no major morphological alterations were observed following exposure to LSSMG. Similarly, the strains' survivability was not negatively affected. This study is the first to characterize the response to simulated microgravity in black fungi, which might have implications on future astrobiological missions.

Image recognition technology based on cloud computing platform

The rapid development of computers makes people’s production and life rich and colorful, and people communicate with each other in the world of the Internet. The daily downloads and uploads of network pictures are countless. The existing image recognition technology alone cannot meet the currently required functions, so technology is needed to meet the retrieval requirements. The purpose of this paper is to study the image recognition technology based on the computer platform. This paper takes vehicle image recognition as an example. By performing a deblurring operation on the vehicle image, the edge detection method is used to separate the target vehicle image from the background, and the image is binary. Processing. Based on different eigenvalue categories, intelligent recognition of vehicle models is achieved through Bayesian classifiers. Collect experimental data through simulation experiments. Experimental data shows that after a certain number of nodes, the recognition efficiency is higher than the image recognition technology running on a stand-alone platform. The experimental data show that the image recognition technology based on a cloud computing platform is conducive to the development of image recognition technology. It can quickly solve the problems of traditional image detection systems in terms of computing efficiency and data processing ability, and has guiding significance for the development of image recognition technology.

Mitochondrial apurinic/apyrimidinic endonuclease 1 enhances mtDNA repair contributing to cell proliferation and mitochondrial integrity in early stages of hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is the leading cause of primary liver cancers. Surveillance of individuals at specific risk of developing HCC, early diagnostic markers, and new therapeutic approaches are essential to obtain a reduction in disease-related mortality. Apurinic/apyrimidinic endonuclease 1 (APE1) expression levels and its cytoplasmic localization have been reported to correlate with a lower degree of differentiation and shorter survival rate. The aim of this study is to fully investigate, for the first time, the role of the mitochondrial form of APE1 in HCC.

METHODS

As a study model, we analyzed samples from a cohort of patients diagnosed with HCC who underwent surgical resection. Mitochondrial APE1 content, expression levels of the mitochondrial import protein Mia40, and mtDNA damage of tumor tissue and distal non-tumor liver of each patient were analyzed. In parallel, we generated a stable HeLa clone for inducible silencing of endogenous APE1 and re-expression of the recombinant shRNA resistant mitochondrially targeted APE1 form (MTS-APE1). We evaluated mtDNA damage, cell growth, and mitochondrial respiration.

RESULTS

APE1's cytoplasmic positivity in Grades 1 and 2 HCC patients showed a significantly higher expression of mitochondrial APE1, which accounted for lower levels of mtDNA damage observed in the tumor tissue with respect to the distal area. In the contrast, the cytoplasmic positivity in Grade 3 was not associated with APE1's mitochondrial accumulation even when accounting for the higher number of mtDNA lesions measured. Loss of APE1 expression negatively affected mitochondrial respiration, cell viability, and proliferation as well as levels of mtDNA damage. Remarkably, the phenotype was efficiently rescued in MTS-APE1 clone, where APE1 is present only within the mitochondrial matrix.

CONCLUSIONS

Our study confirms the prominent role of the mitochondrial form of APE1 in the early stages of HCC development and the relevance of the non-nuclear fraction of APE1 in the disease progression. We have also confirmed overexpression of Mia40 and the role of the MIA pathway in the APE1 import process. Based on our data, inhibition of the APE1 transport by blocking the MIA pathway could represent a new therapeutic approach for reducing mitochondrial metabolism by preventing the efficient repair of mtDNA.

A Deep Learning-Based System (Microscan) for the Identification of Pollen Development Stages and Its Application to Obtaining Doubled Haploid Lines in Eggplant

The development of double haploids (DHs) is a straightforward path for obtaining pure lines but has multiple bottlenecks. Among them is the determination of the optimal stage of pollen induction for androgenesis. In this work, we developed Microscan, a deep learning-based system for the detection and recognition of the stages of pollen development. In a first experiment, the algorithm was developed adapting the RetinaNet predictive model using microspores of different eggplant accessions as samples. A mean average precision of 86.30% was obtained. In a second experiment, the anther range to be cultivated in vitro was determined in three eggplant genotypes by applying the Microscan system. Subsequently, they were cultivated following two different androgenesis protocols (Cb and E6). The response was only observed in the anther size range predicted by Microscan, obtaining the best results with the E6 protocol. The plants obtained were characterized by flow cytometry and with the Single Primer Enrichment Technology high-throughput genotyping platform, obtaining a high rate of confirmed haploid and double haploid plants. Microscan has been revealed as a tool for the high-throughput efficient analysis of microspore samples, as it has been exemplified in eggplant by providing an increase in the yield of DHs production.

Ready to go 3D? A semi-automated protocol for microwell spheroid arrays to increase scalability and throughput of 3D cell culture testing

3-dimensional (3D) cell cultures are being increasingly recognized as physiologically more relevant in vitro models than traditional monolayer cultures, because they better mimic in vivo-like microenvironment, cell-cell and cell-extracellular matrix interactions. Nevertheless, the broader use of 3D models might be limited by requirements for special consumables, equipment, or skills for 3D cell cultures, and by their limited throughput and scalability. In this study, we optimized and adapted a commercially available agarose-micromolding technique to produce scaffold-free spheroid cultures. Brightfield microscopy was used for routine nondestructive and noninvasive evaluation of spheroid formation and growth. The workflow is compatible with manual, as well as high speed automated microscopic image acquisition, and it is supplemented with an in-house developed macro 'Spheroid_Finder' for open source software Fiji to facilitate rapid automated image analysis. This protocol was used to characterize and quantify spheroid formation and growth of two different hepatic cell lines, hTERT immortalized, but non-cancerous, adult human liver stem cell line HL1-hT1, and human hepatocellular carcinoma cell line HepG2, as well as their responses to a model antiproliferative and cytotoxic agent, 5-fluorouracil. The complete protocol provides a simple and ready-to-use solution to initiate scaffold-free spheroid cultures in any laboratory with standard equipment for mammalian in vitro cell culture work. Thus, it allows to increase throughput and scale of spheroid culture experiments, which can be greatly utilized in different areas of biomedical, pharmaceutical and toxicological research.

Transcriptome sequencing supports a conservation of macrophage polarization in fish

Mammalian macrophages can adopt polarization states that, depending on the exact stimuli present in their extracellular environment, can lead to very different functions. Although these different polarization states have been shown primarily for macrophages of humans and mice, it is likely that polarized macrophages with corresponding phenotypes exist across mammals. Evidence of functional conservation in macrophages from teleost fish suggests that the same, or at least comparable polarization states should also be present in teleosts. However, corresponding transcriptional profiles of marker genes have not been reported thus far. In this study we confirm that macrophages from common carp can polarize into M1- and M2 phenotypes with conserved functions and corresponding transcriptional profiles compared to mammalian macrophages. Carp M1 macrophages show increased production of nitric oxide and a transcriptional profile with increased pro-inflammatory cytokines and mediators, including il6, il12 and saa. Carp M2 macrophages show increased arginase activity and a transcriptional profile with increased anti-inflammatory mediators, including cyr61, timp2b and tgm2b. Our RNA sequencing approach allowed us to list, in an unbiased manner, markers discriminating between M1 and M2 macrophages of teleost fish. We discuss the importance of our findings for the evaluation of immunostimulants for aquaculture and for the identification of gene targets to generate transgenic zebrafish for detailed studies on M1 and M2 macrophages. Above all, we discuss the striking degree of evolutionary conservation of macrophage polarization in a lower vertebrate.

SimpylCellCounter: an automated solution for quantifying cells in brain tissue

Manual quantification of activated cells can provide valuable information about stimuli-induced changes within brain regions; however, this analysis remains time intensive. Therefore, we created SimpylCellCounter (SCC), an automated method to quantify cells that express cFos protein, an index of neuronal activity, in brain tissue and benchmarked it against two widely-used methods: OpenColonyFormingUnit (OCFU) and ImageJ Edge Detection Macro (IMJM). In Experiment 1, manually-obtained cell counts were compared to those detected via OCFU, IMJM and SCC. The absolute error in counts (manual versus automated method) was calculated and error types were categorized as false positives or negatives. In Experiment 2, performance analytics of OCFU, IMJM and SCC were compared. In Experiment 3, SCC analysis was conducted on images it was not trained on, to assess its general utility. We found SCC to be highly accurate and efficient in quantifying cells with circular morphologies that expressed cFos. Additionally, SCC utilized a new approach to count overlapping cells with a pretrained convolutional neural network classifier. The current study demonstrates that SCC is a novel, automated tool to quantify cells in brain tissue and complements current, open-sourced methods designed to detect cells in vitro.

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.

Influence of Fluid Properties on Intensity of Hydrodynamic Cavitation and Deactivation of Salmonella typhimurium

In this study, three microfluidic devices with different geometries are fabricated on silicon and are bonded to glass to withstand high-pressure fluid flows in order to observe bacteria deactivation effects of micro cavitating flows. The general geometry of the devices was a micro orifice with macroscopic wall roughness elements. The width of the microchannel and geometry of the roughness elements were varied in the devices. First, the thermophysical property effect (with deionized water and phosphate-buffered saline (PBS)) on flow behavior was revealed. The results showed a better performance of the device in terms of cavitation generation and intensity with PBS due to its higher density, higher saturation vapor pressure, and lower surface tension in comparison with water. Moreover, the second and third microfluidic devices were tested with water and Salmonella typhimurium bacteria suspension in PBS. Accordingly, the presence of the bacteria intensified cavitating flows. As a result, both devices performed better in terms of the intensity of cavitating flow with the presence of bacteria. Finally, the deactivation performance was assessed. A decrease in the bacteria colonies on the agar plate was detected upon the tenth cycle of cavitating flows, while a complete deactivation was achieved after the fifteenth cycle. Thus, the proposed devices can be considered as reliable hydrodynamic cavitation reactors for “water treatment on chip” applications.

Morphological quantification of proliferation-to-invasion transition in tumor spheroids

BACKGROUND

Metastasis determines the lethality of cancer. In most clinical cases, patients are able to live with tumor proliferation before metastasis. Thus, the transition from tumor proliferation to metastasis/invasion is essential. However, the mechanism is still unclear and especially, the proliferation-to-metastasis/invasion transition point has not been well defined. Therefore, quantitative characterization of this transition is urgently needed.

METHODS

We have successfully developed a home-built living-cell incubation system combined with an inverted optical microscope, and a systematic, quantitative approach to describing the major characteristic morphological parameters for the identification of the critical transition points for tumor-cell spheroids in a collagen fiber scaffold.

RESULTS

The system focuses on in vitro tumor modeling, e.g. the development of tumor-cell spheroids in a collagen fiber scaffold and the monitoring of cell transition from proliferation to invasion. By applying this approach to multiple tumor spheroid models, such as U87 (glioma tumor), H1299 (lung cancer), and MDA-MB-231 (breast cancer) cells, we have obtained quantitative morphological references to evaluate the proliferation-to-invasion transition time, as well as differentiating the invasion potential of tumor cells upon environmental changes, i.e. drug application.

CONCLUSIONS

Our quantitative approach provides a feasible clarification for the proliferation-to-invasion transition of in vitro tumor models (spheroids). Moreover, the transition time is a useful reference for the invasive potential of tumor cells.

GENERAL SIGNIFICANCE

This quantitative approach is potentially applicable to primary tumor cells, and thus has potential applications in the fields of cancer metastasis investigations and clinical diagnostics.

Novel Poly(Methyl Methacrylate) Containing Nanodiamond to Improve the Mechanical Properties and Fungal Resistance

Herein we evaluate the effect of nanodiamond (ND) incorporation on the mechanical properties of poly(methyl methacrylate) (PMMA) nanocomposite. Three quantities of ND (0.1, 0.3, and 0.5 wt.%) were tested against the control and zirconium oxide nanoparticles (ZrO). Flexural strength and elastic modulus were measured using a three-point bending test, surface hardness was evaluated using the Vickers hardness test, and surface roughness was evaluated using atomic force microscopy (AFM), while fungal adhesion and viability were studied using Candida albicans. Samples were also analyzed for biofilm thickness and biomass in a saliva-derived biofilm model. All groups of ND-PMMA nanocomposites had significantly greater mean flexural strengths and statistically improved elastic modulus, compared to the control and ZrO groups (P < 0.001). The Vickers hardness values significantly increased compared to the control group (P < 0.001) with 0.3% and 0.5% ND. ND addition also gave significant reduction in fungal adhesion and viability (P < 0.001) compared to the control group. Finally, salivary biofilm formation was markedly reduced compared to the ZrO group. Hence, the incorporation of 0.1–0.5 wt.% ND with auto- polymerized PMMA resin significantly improved the flexural strength, elastic modulus, and surface hardness, and provided considerable fungal resistance.

Prediction of various freshness indicators in fish fillets by one multispectral imaging system

In current study, a simple multispectral imaging (430–1010 nm) system along with linear and non-linear regressions were used to assess the various fish spoilage indicators during 12 days storage at 4 ± 2 °C. The indicators included Total-Volatile Basic Nitrogen (TVB-N) and Psychrotrophic Plate Count (PPC) and sensory score in fish fillets. immediately, after hyperspectral imaging, the reference values (TVB-N, PPC and sensory score) of samples were obtained by traditional method. To simplify the calibration models, nine optimal wavelengths were selected by genetic algorithm. The prediction performance of various chemometric models including partial least-squares regression (PLSR), multiple-linear regression (MLR), least-squares support vector machine (LS-SVM) and back-propagation artificial neural network (BP-ANN) were compared. All models showed acceptable performance for simultaneous predicting of PPC, TVB-N and sensory score (R²_P ≥ 0.853 and RPD ≥ 2.603). Non-linear models were considered better quantitative model to predict all of three freshness indicators in fish fillets. Among the three spoilage indices, the best predictive power was obtained for PPC value and the weakest one was acquired for TVB-N content prediction. The best model for prediction TVB-N (R²_p = 0.862; RMSEP = 3.542 and RPD = 2.678) and sensory score (R²_p = 0.912; RMSEP = 1.802 and RPD = 3.33) belonged to GA-LS-SVM and for prediction of PPC value was BP-ANN (R²_p = 0.921; RMSEP = 0.504 and RPD = 3.64). Therefore, developing multispectral imaging system based on LS-SVM model seems to be suitable for simultaneous prediction of all three indicators (R²_P > 0.862 and RPD > 2.678). Further studies needed to improve the accuracy and applicability of HSI system for predicting freshness of rainbow-trout fish.

ViralPlaque: a Fiji macro for automated assessment of viral plaque statistics

Plaque assay has been used for a long time to determine infectious titers and characterize prokaryotic and eukaryotic viruses forming plaques. Indeed, plaque morphology and dimensions can provide information regarding the replication kinetics and the virulence of a particular virus. In this work, we present ViralPlaque, a fast, open-source and versatile ImageJ macro for the automated determination of viral plaque dimensions from digital images. Also, a machine learning plugin is integrated in the analysis algorithm for adaptation of ViralPlaque to the user's needs and experimental conditions. A high correlation between manual and automated measurements of plaque dimensions was demonstrated. This macro will facilitate reliable and reproducible characterization of cytolytic viruses with an increased processing speed.

Deficiency of Mitochondrial Aspartate-Glutamate Carrier 1 Leads to Oligodendrocyte Precursor Cell Proliferation Defects Both In Vitro and In Vivo

Aspartate-Glutamate Carrier 1 (AGC1) deficiency is a rare neurological disease caused by mutations in the solute carrier family 25, member 12 (SLC25A12) gene, encoding for the mitochondrial aspartate-glutamate carrier isoform 1 (AGC1), a component of the malate-aspartate NADH shuttle (MAS), expressed in excitable tissues only. AGC1 deficiency patients are children showing severe hypotonia, arrested psychomotor development, seizures and global hypomyelination. While the effect of AGC1 deficiency in neurons and neuronal function has been deeply studied, little is known about oligodendrocytes and their precursors, the brain cells involved in myelination. Here we studied the effect of AGC1 down-regulation on oligodendrocyte precursor cells (OPCs), using both in vitro and in vivo mouse disease models. In the cell model, we showed that a reduced expression of AGC1 induces a deficit of OPC proliferation leading to their spontaneous and precocious differentiation into oligodendrocytes. Interestingly, this effect seems to be related to a dysregulation in the expression of trophic factors and receptors involved in OPC proliferation/differentiation, such as Platelet-Derived Growth Factor α (PDGFα) and Transforming Growth Factor βs (TGFβs). We also confirmed the OPC reduction in vivo in AGC1-deficent mice, as well as a proliferation deficit in neurospheres from the Subventricular Zone (SVZ) of these animals, thus indicating that AGC1 reduction could affect the proliferation of different brain precursor cells. These data clearly show that AGC1 impairment alters myelination not only by acting on N-acetyl-aspartate production in neurons but also on OPC proliferation and suggest new potential therapeutic targets for the treatment of AGC1 deficiency.

Nucleoporin insufficiency disrupts a pluripotent regulatory circuit in a pro-arrhythmogenic stem cell line

Nucleoporins have been reported to regulate pluripotent biology, but how they do so remains partially characterized. This study examined the effects of nup155 gene disruption on mouse embryonic stem cells to gain insights into possible mechanisms by which nucleoporins regulate pluripotency in a pro-arrhythmogenic stem cell line. Embryonic stem cells with gene-trapped nup155 exhibited aberrant colony morphology underscored by abnormal transcriptome remodeling. Bioinformatic analysis of whole transcriptome data from nup155^+/- embryonic stem cells revealed changes in a variety of non-coding RNA elements, with significant under expression of miR291a, miR291b, miR293, and miR294. These miRNAs are members of the larger regulatory miR290-295 cluster that regulates pluripotency and are controlled by the canonical stem cell-related factors SOX2, OCT4, and NANOG. Expression analysis of these factors revealed downregulation in all three, supported by biochemical profiling and image analysis. These data implicate disruption of the miR-SOX2/OCT4/NANOG regulatory circuit occurs downstream of nup155 gene lesion.

DeepPhagy: a deep learning framework for quantitatively measuring autophagy activity in Saccharomyces cerevisiae

Seeing is believing. The direct observation of GFP-Atg8 vacuolar delivery under confocal microscopy is one of the most useful end-point measurements for monitoring yeast macroautophagy/autophagy. However, manually labelling individual cells from large-scale sets of images is time-consuming and labor-intensive, which has greatly hampered its extensive use in functional screens. Herein, we conducted a time-course analysis of nitrogen starvation-induced autophagy in wild-type and knockout mutants of 35 AuTophaGy-related (ATG) genes in Saccharomyces cerevisiae and obtained 1,944 confocal images containing > 200,000 cells. We manually labelled 8,078 autophagic and 18,493 non-autophagic cells as a benchmark dataset and developed a new deep learning tool for autophagy (DeepPhagy), which exhibited superior accuracy in recognizing autophagic cells compared to other existing methods, with an area under the curve (AUC) value of 0.9710 from 10-fold cross-validations. We further used DeepPhagy to automatically analyze all the images and quantitatively classified the autophagic phenotypes of the 35 atg knockout mutants into 3 classes. The high consistency in our computational and biochemical results indicated the reliability of DeepPhagy for measuring autophagic activity. Moreover, we used DeepPhagy to analyze 3 additional types of autophagic phenotypes, including the targeting of Atg1-GFP to the vacuole, the vacuolar delivery of GFP-Atg19, and the disintegration of autophagic bodies indicated by GFP-Atg8, all with satisfying accuracies. Taken together, our study not only enables the GFP-Atg8 fluorescence assay to become a quantitative measurement for analyzing autophagic phenotypes in S. cerevisiae but also demonstrates that deep learning-based methods could potentially be applied to different types of autophagy.Abbreviations: Ac: accuracy; ALP: alkaline phosphatase; ALR: autophagic lysosomal reformation; ATG: AuTophaGy-related; AUC: area under the curve; CNN: convolutional neural network; Cvt: cytoplasm-to-vacuole targeting; DeepPhagy: deep learning for autophagy; fc_2: second fully connected; GFP: green fluorescent protein; MAP1LC3/LC3: microtubule-associated protein 1 light chain 3 beta; HAT: histone acetyltransferase; HemI: Heat map Illustrator; JRE: Java Runtime Environment; KO: knockout; LRN: local response normalization; MCC: Mathew Correlation Coefficient; OS: operating system; PAS: phagophore assembly site; PC: principal component; PCA: principal component analysis; PPI: protein-protein interaction; Pr: precision; QPSO: Quantum-behaved Particle Swarm Optimization; ReLU: rectified linear unit; RF: random forest; ROC: receiver operating characteristic; ROI: region of interest; SD: systematic derivation; SGD: stochastic gradient descent; Sn: sensitivity; Sp: specificity; SRG: seeded region growing; t-SNE: t-distributed stochastic neighbor embedding; 2D: 2-dimensional; WT: wild-type.

Modeling the Effect of the Metastatic Microenvironment on Phenotypes Conferred by Estrogen Receptor Mutations Using a Human Liver Microphysiological System

Reciprocal coevolution of tumors and their microenvironments underlies disease progression, yet intrinsic limitations of patient-derived xenografts and simpler cell-based models present challenges towards a deeper understanding of these intercellular communication networks. To help overcome these barriers and complement existing models, we have developed a human microphysiological system (MPS) model of the human liver acinus, a common metastatic site, and have applied this system to estrogen receptor (ER)+ breast cancer. In addition to their hallmark constitutive (but ER-dependent) growth phenotype, different ESR1 missense mutations, prominently observed during estrogen deprivation therapy, confer distinct estrogen-enhanced growth and drug resistant phenotypes not evident under cell autonomous conditions. Under low molecular oxygen within the physiological range (~5–20%) of the normal liver acinus, the estrogen-enhanced growth phenotypes are lost, a dependency not observed in monoculture. In contrast, the constitutive growth phenotypes are invariant within this range of molecular oxygen suggesting that ESR1 mutations confer a growth advantage not only during estrogen deprivation but also at lower oxygen levels. We discuss the prospects and limitations of implementing human MPS, especially in conjunction with in situ single cell hyperplexed computational pathology platforms, to identify biomarkers mechanistically linked to disease progression that inform optimal therapeutic strategies for patients.

Characterization of Biofilm Formed by Phenanthrene-Degrading Bacteria on Rice Root Surfaces for Reduction of PAH Contamination in Rice

One effective method in to reduce the uptake of organic contaminants by plants is the development of a root barrier. In this study, the characterization of biofilm structure and function by phenanthrene-degrading Pseudomonas sp. JM2-gfp on rice root surfaces were carried out. Our results showed that root surfaces from three rice species, namely Liaojing401, Koshihikari, and Zhenzhuhong all present hydrophobicity and a high initial adhesion of strain JM2-gfp. Matured robust biofilm formation occurred at 48 h on the root surfaces. The biofilm exhibited cell dense aggregates and biomass embedded in the extracellular polymeric substance (EPS) matrix. EPS composition results showed that the proteins, carbohydrates, lipids and nucleic acids are produced in the biofilm, while the content varied with rice species. Under the initial concentration of phenanthrene 50 mg·L-1, the residual phenanthrene in plant roots from 'Zhengzhuhong', 'Koshihikari' and 'Liaojing401' with biofilm mediated were significantly decreased by 71.9%, 69.3% and 58.7%, respectively, compared to those without biofilm groups after 10 days of exposure. Thus, the biofilm colonized on roots plays an important role of degradation in order to reduce the level of phenanthrene uptake of plants. Thereby, the present work provides significant new insights into lowering the environmental risks of polycyclic aromatic hydrocarbons (PAHs) in crop products from contaminated agriculture soils.

Rapid production of a chimeric antibody-antigen fusion protein based on 2A-peptide cleavage and green fluorescent protein expression in CHO cells

To enable large-scale antibody production, the creation of a stable, high producer cell line is essential. This process often takes longer than 6 months using standard limited dilution techniques and is very labor intensive. The use of a tri-cistronic vector expressing green fluorescent protein (GFP) and both antibody chains, separated by a GT2A peptide sequence, allows expression of all proteins under a single promotor in equimolar ratios. By combining the advantages of 2A peptide cleavage and single cell sorting, a chimeric antibody-antigen fusion protein that contained the variable domains of mouse IgG with a porcine IgA constant domain fused to the FedF antigen could be produced in CHO-K1 cells. After transfection, a strong correlation was found between antibody production and GFP expression (r = 0.69) using image analysis of formed monolayer patches. This enables the rapid selection of GFP-positive clones using automated image analysis for the selection of high producer clones. This vector design allowed the rapid selection of high producer clones within a time-frame of 4 weeks after transfection. The highest producing clone had a specific antibody productivity of 2.32 pg/cell/day. Concentrations of 34 mg/L were obtained using shake-flask batch culture. The produced recombinant antibody showed stable expression, binding and minimal degradation. In the future, this antibody will be assessed for its effectiveness as an oral vaccine antigen.

Dynamics of oligodendrocyte generation in multiple sclerosis

Oligodendrocytes wrap nerve fibres in the central nervous system with layers of specialized cell membrane to form myelin sheaths¹. Myelin is destroyed by the immune system in multiple sclerosis, but myelin is thought to regenerate and neurological function can be recovered. In animal models of demyelinating disease, myelin is regenerated by newly generated oligodendrocytes, and remaining mature oligodendrocytes do not seem to contribute to this process^2-4. Given the major differences in the dynamics of oligodendrocyte generation and adaptive myelination between rodents and humans^5-9, it is not clear how well experimental animal models reflect the situation in multiple sclerosis. Here, by measuring the integration of ¹⁴C derived from nuclear testing in genomic DNA¹⁰, we assess the dynamics of oligodendrocyte generation in patients with multiple sclerosis. The generation of new oligodendrocytes was increased several-fold in normal-appearing white matter in a subset of individuals with very aggressive multiple sclerosis, but not in most subjects with the disease, demonstrating an inherent potential to substantially increase oligodendrocyte generation that fails in most patients. Oligodendrocytes in shadow plaques-thinly myelinated lesions that are thought to represent remyelinated areas-were old in patients with multiple sclerosis. The absence of new oligodendrocytes in shadow plaques suggests that remyelination of lesions occurs transiently or not at all, or that myelin is regenerated by pre-existing, and not new, oligodendrocytes in multiple sclerosis. We report unexpected oligodendrocyte generation dynamics in multiple sclerosis, and this should guide the use of current, and the development of new, therapies.