PhenoWell®-A novel screening system for soil-grown plants.

As agricultural production is reaching its limits regarding outputs and land use, the need to further improve crop yield is greater than ever. The limited translatability from in vitro lab results into more natural growth conditions in soil remains problematic. Although considerable progress has been made in developing soil-growth assays to tackle this bottleneck, the majority of these assays use pots or whole trays, making them not only space- and resource-intensive, but also hampering the individual treatment of plants. Therefore, we developed a flexible and compact screening system named PhenoWell® in which individual seedlings are grown in wells filled with soil allowing single-plant treatments. The system makes use of an automated image-analysis pipeline that extracts multiple growth parameters from individual seedlings over time, including projected rosette area, relative growth rate, compactness, and stockiness. Macronutrient, hormone, salt, osmotic, and drought stress treatments were tested in the PhenoWell® system. The system is also optimized for maize with results that are consistent with Arabidopsis while different in amplitude. We conclude that the PhenoWell® system enables a high-throughput, precise, and uniform application of a small amount of solution to individually soil-grown plants, which increases the replicability and reduces variability and compound usage.

Tissue-Engineered 3D In Vitro Disease Models for High-Throughput Drug Screening.

During high-throughput drug screening, in vitro models are fabricated and the effects of therapeutics on the models evaluated in high throughput-for example, with automated liquid handling systems and microplate reader-based high-throughput screening (HTS) assays. The most frequently-used model systems for HTS, 2D models, do not adequately model the in vivo 3D microenvironment-an important aspect of which is the extracellular matrix-and therefore, 2D models may not be appropriate for drug screening. Instead, tissue-engineered 3D models with extracellular matrix-mimicking components are destined to become the preferred in vitro systems for HTS. However, for 3D models, such as 3D cell-laden hydrogels and scaffolds, cell sheets, and spheroids as well as 3D microfluidic and organ-on-a-chip systems, to replace 2D models in HTS, they must be compatible with high-throughput fabrication schemes and evaluation methods. In this review, we summarize HTS in 2D models and discuss recent studies that have successfully demonstrated HTS-compatible 3D models of high-impact diseases, such as cancers or cardiovascular diseases.

An induced thymic epithelial cell-based high throughput screen for thymus extracellular matrix mimetics.

Thymic epithelial cells (TECs) are key effectors of the thymic stroma and are critically required for T-cell development. TECs comprise a diverse set of related but functionally distinct cell types that are scarce and difficult to isolate and handle. This has precluded TEC-based screening assays. We previously described induced thymic epithelial cells (iTECs), an artificial cell type produced in vitro by direct reprogramming, raising the possibility that iTECs might provide the basis for functional screens related to TEC biology. Here, we present an iTEC-based three-stage medium/high-throughput in vitro assay for synthetic polymer mimics of thymic extracellular matrix (ECM). Using this assay, we identified, from a complex library, four polymers that bind iTEC as well as or better than gelatin but do not bind mesenchymal cells. We show that these four polymers also bind and maintain native mouse fetal TECs and native human fetal TECs. Finally, we show that the selected polymers do not interfere with iTEC function or T-cell development. Collectively, our data establish that iTECs can be used to screen for TEC-relevant compounds in at least some medium/high-throughput assays and identify synthetic polymer ECM mimics that can replace gelatin or ECM components in TEC culture protocols.

Recent progress in assays for GPCR drug discovery.

G-protein-coupled receptors (GPCRs), also known as seven transmembrane receptors, are the largest family of cell surface receptors in eukaryotes. There are ∼800 GPCRs in human, regulating diverse physiological processes. The GPCRs are the most intensively studied drug targets. Drugs that target GPCRs account for about a quarter of the global market share of therapeutic drugs. Therefore, to develop physiologically relevant and robust assays to search new GPCR ligands or modulators remain the major focus of drug discovery research worldwide. Early functional GPCR assays mainly depend on the measurement of G-protein-mediated second messenger generation. Recent developments in GPCR biology indicate that the signaling of these receptors is much more complex than the oversimplified classical view. The GPCRs have been found to activate multiple G proteins simultaneously and induce ß-arrestin-mediated signaling. They have also been found to interact with other cytosolic scaffolding proteins and form dimer or heteromer with GPCRs or other transmembrane proteins. Here, we mainly discuss technologies focused on detecting protein-protein interactions, such as fluorescence resonance energy transfer/bioluminescence resonance energy transfer (FRET/BRET), NanoLuc binary technology (NanoBiT), Tango, etc., and their applications in measuring GPCRs interacting with various signaling partners. In the final part, we also discuss the species differences in GPCRs when using animal models to study the in vivo functions of GPCR ligands, and possible ways to solve this problem with modern genetic tools.

Gene expression profiling reveals the genomic changes caused by MLN4924 and the sensitizing effects of NAPEPLD knockdown in pancreatic cancer.

MLN4924 inhibits the proteolytic degradation of Cullin-Ring E3 ligase (CRL) substrates and exhibits antitumor activity toward various malignancies, including pancreatic cancer. MLN4924 suppresses tumor growth by altering various key regulator proteins; however, its impact on gene expression in tumors remains unknown. In this study, the genomic changes caused by MLN4924 in pancreatic cancer were examined by gene chip analysis and ingenuity pathway analysis. Eleven pathways were significantly altered (5 activated and 6 inhibited), 45 functions were significantly changed (21 activated and 24 inhibited), and the most activated upstream factor was predicted to be TNF. Of 691 differentially expressed genes, NAPEPLD knockdown showed synergism with MLN4924, as determined by real-time quantitative PCR and high content screening. NAPEPLD knockdown enhanced the effect of MLN4924 on inhibiting proliferation and inducing apoptosis in vitro. In a pancreatic cancer nude mouse model, MLN4924 inhibited tumor growth more significantly in the NAPEPLD knockdown group than in the control group. NAPEPLD expression was higher in pancreatic cancer tissues than in the normal pancreas but was not associated with prognosis. These findings indicate that MLN4924 causes extensive genomic changes in pancreatic cancer cells, and targeting NAPEPLD may increase the efficacy of MLN4924.

Two-Dimensional and Three-Dimensional Cartilage Model Platforms for Drug Evaluation and High-Throughput Screening Assays.

Osteoarthritis (OA) is a severely painful and debilitating disease of the joint, which brings about degradation of the articular cartilage and currently has few therapeutic solutions. Two-dimensional (2D) high-throughput screening (HTS) assays have been widely used to identify candidate drugs with therapeutic potential for the treatment of OA. A number of small molecules which improve the chondrogenic differentiation of progenitor cells for tissue engineering applications have also been discovered in this way. However, due to the failure of these models to accurately represent the native joint environment, the efficacy of these drugs has been limited in vivo. Screening systems utilizing three-dimensional (3D) models, which more closely reflect the tissue and its complex cell and molecular interactions, have also been described. However, the vast majority of these systems fail to recapitulate the complex, zonal structure of articular cartilage and its unique cell population. This review summarizes current 2D HTS techniques and addresses the question of how to use existing 3D models of tissue-engineered cartilage to create 3D drug screening platforms with improved outcomes. Impact statement Currently, the use of two-dimensional (2D) screening platforms in drug discovery is common practice. However, these systems often fail to predict efficacy in vivo, as they do not accurately represent the complexity of the native three-dimensional (3D) environment. This article describes existing 2D and 3D high-throughput systems used to identify small molecules for osteoarthritis treatment or in vitro chondrogenic differentiation, and suggests ways to improve the efficacy of these systems based on the most recent research.

High-yield synthesis and purification of recombinant human GABA transaminase for high-throughput screening assays.

Many studies have focussed on modulating the activity of γ-aminobutyric acid transaminase (GABA-T), a GABA-catabolizing enzyme, for treating neurological diseases, such as epilepsy and drug addiction. Nevertheless, human GABA-T synthesis and purification have not been established. Thus, biochemical and drug design studies on GABA-T have been performed by using porcine GABA-T mostly and even bacterial GABA-T. Here we report an optimised protocol for overexpression of 6xHis-tagged human GABA-T in human cells followed by a two-step protein purification. Then, we established an optimised human GABA-T (0.5 U/mg) activity assay. Finally, we compared the difference between human and bacterial GABA-T in sensitivity to two irreversible GABA-T inhibitors, gabaculine and vigabatrin. Human GABA-T in homodimeric form showed 70-fold higher sensitivity to vigabatrin than bacterial GABA-T in multimeric form, indicating the importance of using human GABA-T. In summary, our newly developed protocol can be an important first step in developing more effective human GABA-T modulators.

Pluripotent stem cell-based screening identifies CUDC-907 as an effective compound for restoring the in vitro phenotype of Nakajo-Nishimura syndrome.

Nakajo-Nishimura syndrome (NNS) is an autoinflammatory disorder caused by a homozygous mutations in the PSMB8 gene. The administration of systemic corticosteroids is partially effective, but continuous treatment causes severe side effects. We previously established a pluripotent stem cell (PSC)-derived NNS disease model that reproduces several inflammatory phenotypes, including the overproduction of monocyte chemoattractant protein-1 (MCP-1) and interferon gamma-induced protein-10 (IP-10). Here we performed high-throughput compound screening (HTS) using this PSC-derived NNS model to find potential therapeutic candidates and identified CUDC-907 as an effective inhibitor of the release of MCP-1 and IP-10. Short-term treatment of CUDC-907 did not induce cell death within therapeutic concentrations and was also effective on primary patient cells. Further analysis indicated that the inhibitory effect was post-transcriptional. These findings suggest that HTS with PSC-derived disease models is useful for finding drug candidates for autoinflammatory diseases.

Discovery of retinoic acid receptor agonists as proliferators of cardiac progenitor cells through a phenotypic screening approach.

Identification of small molecules with the potential to selectively proliferate cardiac progenitor cells (CPCs) will aid our understanding of the signaling pathways and mechanisms involved and could ultimately provide tools for regenerative therapies for the treatment of post-MI cardiac dysfunction. We have used an in vitro human induced pluripotent stem cell-derived CPC model to screen a 10,000-compound library containing molecules representing different target classes and compounds reported to modulate the phenotype of stem or primary cells. The primary readout of this phenotypic screen was proliferation as measured by nuclear count. We identified retinoic acid receptor (RAR) agonists as potent proliferators of CPCs. The CPCs retained their progenitor phenotype following proliferation and the identified RAR agonists did not proliferate human cardiac fibroblasts, the major cell type in the heart. In addition, the RAR agonists were able to proliferate an independent source of CPCs, HuES6. The RAR agonists had a time-of-differentiation-dependent effect on the HuES6-derived CPCs. At 4 days of differentiation, treatment with retinoic acid induced differentiation of the CPCs to atrial cells. However, after 5 days of differentiation treatment with RAR agonists led to an inhibition of terminal differentiation to cardiomyocytes and enhanced the proliferation of the cells. RAR agonists, at least transiently, enhance the proliferation of human CPCs, at the expense of terminal cardiac differentiation. How this mechanism translates in vivo to activate endogenous CPCs and whether enhancing proliferation of these rare progenitor cells is sufficient to enhance cardiac repair remains to be investigated.

TIMP1 Is A Potential Key Gene Associated With The Pathogenesis And Prognosis Of Ulcerative Colitis-Associated Colorectal Cancer.

PURPOSE: Colorectal cancer (CRC) is the third most frequently diagnosed cancer worldwide. As a high-risk factor for CRC, ulcerative colitis (UC) has been demonstrated to lead to epithelial dysplasia, DNA damage, and eventually cancer. There are approximately 18% of patients with UC may develop CRC. PATIENTS AND METHODS: The gene expression profiles were retrieved from the Gene Expression Omnibus. The Database for Annotation, Visualization and Integrated Discovery was employed to conduct gene annotations. Protein-protein interaction network was constructed by the Search Tool for the Retrieval of Interacting Genes, and further analysed by the Molecular Complex Detection. The correlation between TIMP1 and prognosis was evaluated by the Gene Expression Profiling Interactive Analysis. To predict the potential functions of TIMP1, the GeneMANIA, Coremine, and FunRich were employed. After transfection with small interfering RNA targeting TIMP1, cell proliferation, migration, and apoptosis were determined by CCK-8, scratch wound, and Annexin V-FITC/PI assays, respectively. RESULTS: TIMP1, consistently overexpressed in the initiation and progression of UC-associated CRC (ucaCRC), was identified to be a potential biomarker for the prognosis of patients with CRC. Experimental results showed knockdown of TIMP1 could increase the migration, while did not affect the proliferation and apoptosis of RKO cells. The role of TIMP1 in the malignant transformation of ucaCRC was confirmed by using the protein/gene interactions and biological process annotation and validated by analysing the transcription factors targeting TIMP1. CONCLUSION: TIMP1 is consistently upregulated in the pathological process of ucaCRC and can be a potential biomarker for the worse prognosis of CRC.

Development of an automated capillary nano-immunoassay-Simple Western assay-to quantify total TDP43 protein in human platelet samples.

Frontotemporal lobar degeneration syndrome is the second cause of young-onset dementia. Unfortunately, reliable biomarkers are currently lacking for the diagnosis of this disease. As TDP43 protein is one of the proteins pathologically involved in frontotemporal lobar degeneration, many studies have been performed to assess TDP43 protein diagnostic performances. Mixed results were obtained using cerebrospinal fluid and plasma samples so far. The aim of the study was to develop an automated capillary nano-immunoassay-Simple Western assay-to detect and quantify TDP43 protein simultaneously in human blood-based samples. Simple Western assay was developed with two different cell lysates used as positive controls and was compared to Western blot. TDP43 protein profiles in plasma samples were disappointing, as they were discordant to our positive controls. On the contrary, similar TDP43 patterns were obtained between platelet samples and cell lysates using both assays. Simple Western assay provided good quantitative performances in platelet samples: a linearity of signals could be observed (r2 = 0.994), associated to a within-run variability at 5.7%. Preliminary results based on a cohort of patients suffering from frontotemporal lobar degeneration showed large inter-individual variations superior to Simple Western's analytical variability. Simple Western assay seems to be suitable for detecting and quantifying TDP43 protein in platelet samples, providing a potential candidate biomarker in this disease. Further confirmation studies should now be performed on larger cohorts of patients to assess diagnostic performances of TDP43 protein in platelet samples.

High-throughput RNA sequencing for screening the circular RNA expression profiling associated with chemo-resistance inosteosarcoma / 中华骨科杂志

Objective To screen the expression profile of circular RNA associated with chemo-resistance in osteosarcoma,and to analyze and identify its possible molecular functions.Methods Three pairs of matched drug-resistant and sensitive human osteosarcoma cell lines (MG63/DXR vs MG63,U2OS/DXR vs U2OS,KHOS/DXR vs KHOS) were first tested by CCK-8 assay for three commonly used osteosarcoma chemotherapy drugs (doxorubicin,cisplatin,and methotrexate);then,using next-generation high-throughput RNA sequencing technology,comparative analysis of circRNA expression was performed in three pairs of matched multidrug-resistant and sensitive human osteosarcoma cell lines;followed by real-time quantitative PCR (qRT-PCR) to confirm the reliability and accuracy of sequencing data in chemotherapy-resistant osteosarcoma cell lines and tissues.In addition,a variety of bioinformatics analyses,including GO,KEGG pathway analysis and the construction of circRNA-miRNA networks,were performed to predict potential molecular functions of differentially expressed circRNAs and to construct relevant regulatory pathways or networks.Results Three osteosarcoma-resistant cells (MG63/DXR,U2OS/DXR,KHOS/DXR) were significantly resistant to the three common osteosarcoma chemotherapy drugs compared with control cells (MG63,U2OS,KHOS),which laid a solid foundation for the further experiments.RNA sequencing revealed a total of 80 circRNAs differentially expressed between the two groups.Compared with drug-sensitive osteosarcoma cells,57 circRNAs were upregulated and 23 circRNAs weredownregulated in the drug-resistant osteosarcoma cell lines (fold change≥ 2 or ≤0.5,P ＜ 0.05).Tenrandomly selected circRNAs were verified by qRT-PCR and the results showed that 9 of the 10 circRNAswere consistent with the sequencing results.In addition,KEGG pathway analysis showed that 56 pathways were significantly enriched in differentially expressed circRNAs,including Glycolysis/gluconeogenesis,ABC transporter,VEGF signaling pathway,and so on.Moreover,thedifferently expressedcircRNA-hsa_circ_0004674 with the highestfold change was highly expressedin the chemotherapy-resistant osteosarcoma cells and tissues,associated with poor prognosis in osteosarcoma patients.Some potential endogenous competitive RNA (ceRNA) regulatory pathways associated with hsa_circ_0004674,such as hsa_circ_0004674-miR-490-3p-ABCC2 and hsa_circ_0004674-miR-1254-EGFR,were constructed by use of the authoritative databases (target scan and miRanda) and literature searching and the miRNA response element sequences (MREs) between miRNAs that have a potential ceRNA regulatory relationship with hsa_circ_0004674 were alsopredicted.Conclusion CircRNA is closely related to tumor progression and may play a role in ostoosarcoma chemo-resistance.Besides,hsa_circ_0004674 may be a potential candidate for reversing drug resistance of osteosarcoma.

Application of weighted gene co-expression network analysis technology in human tumor research / 肿瘤

Weighted gene co-expression network analysis (WGCNA) technology is a high-throughput gene expression data mining algorithm, which uses the idea of system biology to find the correlation of gene expression and to construct gene modules, so as to further discovery a high-throughput data mining algorithm with biological significance modules. In recent years, with the deep understanding of human diseases to gene level, WGCNA has been used increasingly in the researches of various diseases, especially in mining the highthroughput data about tumor-related genes. Moreover, with the continuous improvement of this technology, the research of this technology in disease pathogenesis, development and treatment etc has been developed from a single co-expression network analysis to the multiple technologies [such as genome-wide association study (GWAS) and support vector machine (SVM)] combined WGCNA or the innovative applicated WGCNA. As a high-throughput research method based on gene level, WGCNA is playing an important role.

Caenorhabditis elegans Show Preference for Stimulants and Potential as a Model Organism for Medications Screening.

The nematode Caenorhabditis elegans (C. elegans) is a popular invertebrate model organism to study neurobiological disease states. This is due in part to the intricate mapping of all neurons and synapses of the entire animal, the wide availability of mutant strains, and the genetic and molecular tools that can be used to manipulate the genome and gene expression. We have shown that, C. elegans develops a conditioned preference for cues that had previously been paired with either cocaine or methamphetamine exposure that is dependent on dopamine neurotransmission, similar to findings using place conditioning with rats and mice. In the current study, we show C. elegans also display a preference for, and self-exposure to, cocaine and nicotine. This substance of abuse (SOA) preference response can be selectively blocked by pretreatment with naltrexone and is consistent with the recent discovery of an opioid receptor system in C. elegans. In addition, pre-exposure to the smoking cessation treatment varenicline also inhibits self-exposure to nicotine. Exposure to concentrations of treatments that inhibit SOA preference/self-exposure did not induce any significant inhibition of locomotor activity or affect food or benzaldehyde chemotaxis. These data provide predictive validity for the development of high-throughput C. elegans behavioral medication screens. These screens could enable fast and accurate generation of data to identify compounds that may be effective in treating human addiction. The successful development and validation of such models would introduce powerful and novel tools in the search for new pharmacological treatments for substance use disorders, and provide a platform to study the mechanisms that underlie addictions.

High-Throughput Identification of Candidate Strains for Biopreservation by Using Bioluminescent Listeria monocytogenes.

This article describes a method for high-throughput competition assays using a bioluminescent strain of L. monocytogenes. This method is based on the use of the luminescent indicator strain L. monocytogenes EGDelux. The luminescence of this strain is correlated to growth, which make it suitable to monitor the growth of L. monocytogenes in mixed cultures. To this aim, luminescence kinetics were converted into a single numerical value, called the Luminescence Disturbance Indicator (LDI), which takes into account growth inhibition phenomena resulting in latency increase, decrease in the luminescence rate, or reduction of the maximum luminescence. The LDI allows to automatically and simultaneously handle multiple competition assays which are required for high-throughput screening (HTS) approaches. The method was applied to screen a collection of 1810 strains isolated from raw cow's milk in order to identify non-acidifying strains with anti-L. monocytogenes bioprotection properties. This method was also successfully used to identify anti-L. monocytogenes candidates within a collection of Lactococcus piscium, a species where antagonism was previously described as non-diffusible and requiring cell-to-cell contact. In conclusion, bioluminescent L. monocytogenes can be used in HTS to identify strains with anti-L. monocytogenes bioprotection properties, irrespectively of the inhibition mechanism.

The Deconstructed Granuloma: A Complex High-Throughput Drug Screening Platform for the Discovery of Host-Directed Therapeutics Against Tuberculosis.

Mycobacterium tuberculosis (Mtb) continues to be a threat to Global Public Health, and its control will require an array of therapeutic strategies. It has been appreciated that high-throughput screens using cell-based assays to identify compounds targeting Mtb within macrophages represent a valuable tool for drug discovery. However, the host immune environment, in the form of lymphocytes and cytokines, is completely absent in a chemical screening platform based on infected macrophages alone. The absence of these players unnecessarily limits the breadth of novel host target pathways to be interrogated. In this study, we detail a new drug screening platform based on dissociated murine TB granulomas, named the Deconstructed Granuloma (DGr), that utilizes fluorescent Mtb reporter strains screened in the host immune environment of the infection site. The platform has been used to screen a collection of known drug candidates. Data from a representative 384-well plate containing known anti-bacterial compounds are shown, illustrating the robustness of the screening platform. The novel deconstructed granuloma platform represents an accessible, sensitive and robust high-throughput screen suitable for the inclusive interrogation of immune targets for Host-Directed Therapeutics.

PASSPORT-seq: A Novel High-Throughput Bioassay to Functionally Test Polymorphisms in Micro-RNA Target Sites.

Next-generation sequencing (NGS) studies have identified large numbers of genetic variants that are predicted to alter miRNA-mRNA interactions. We developed a novel high-throughput bioassay, PASSPORT-seq, that can functionally test in parallel 100s of these variants in miRNA binding sites (mirSNPs). The results are highly reproducible across both technical and biological replicates. The utility of the bioassay was demonstrated by testing 100 mirSNPs in HEK293, HepG2, and HeLa cells. The results of several of the variants were validated in all three cell lines using traditional individual luciferase assays. Fifty-five mirSNPs were functional in at least one of three cell lines (FDR ≤ 0.05); 11, 36, and 27 of them were functional in HEK293, HepG2, and HeLa cells, respectively. Only four of the variants were functional in all three cell lines, which demonstrates the cell-type specific effects of mirSNPs and the importance of testing the mirSNPs in multiple cell lines. Using PASSPORT-seq, we functionally tested 111 variants in the 3' UTR of 17 pharmacogenes that are predicted to alter miRNA regulation. Thirty-three of the variants tested were functional in at least one cell line.

Human iPS-Derived Astroglia from a Stable Neural Precursor State Show Improved Functionality Compared with Conventional Astrocytic Models.

In vivo studies of human brain cellular function face challenging ethical and practical difficulties. Animal models are typically used but display distinct cellular differences. One specific example is astrocytes, recently recognized for contribution to neurological diseases and a link to the genetic risk factor apolipoprotein E (APOE). Current astrocytic in vitro models are questioned for lack of biological characterization. Here, we report human induced pluripotent stem cell (hiPSC)-derived astroglia (NES-Astro) developed under defined conditions through long-term neuroepithelial-like stem (ltNES) cells. We characterized NES-Astro and astrocytic models from primary sources, astrocytoma (CCF-STTG1), and hiPSCs through transcriptomics, proteomics, glutamate uptake, inflammatory competence, calcium signaling response, and APOE secretion. Finally, we assess modulation of astrocyte biology using APOE-annotated compounds, confirming hits of the cholesterol biosynthesis pathway in adult and hiPSC-derived astrocytes. Our data show large diversity among astrocytic models and emphasize a cellular context when studying astrocyte biology.

Deep learning for predicting toxicity of chemicals: a mini review.

Humans and wildlife inhabit a world with panoply of natural and synthetic chemicals. Alarmingly, only a limited number of chemicals have undergone comprehensive toxicological evaluation due to limitations of traditional toxicity testing. High-throughput screening assays provide a higher-speed alternative for conventional toxicity testing. Advancement of high-throughput bioassay technology has greatly increased chemical toxicity data volumes in the past decade, pushing toxicology research into a "big data" era. However, traditional data analysis methods fail to effectively process large data volumes, presenting both a challenge and an opportunity for toxicologists. Deep learning, a machine learning method leveraging deep neural networks (DNNs), is a proven useful tool for building quantitative structure-activity relationship (QSAR) models for toxicity prediction utilizing these new large datasets. In this mini review, a brief technical background on DNNs is provided, and the current state of chemical toxicity prediction models built with DNNs is reviewed. In addition, relevant toxicity data sources are summarized, possible limitations are discussed, and perspectives on DNN utilization in chemical toxicity prediction are given.

Charaterizing cytotoxicity of nitrogen mustard HN-3 based on cellular high content analysis / 中国药理学与毒理学杂志

OBJECTIVE To study the cytotoxic characteristics of nitrogen mustard HN-3 in different cell. METHODS Human epidermal keratinocytes-fetal (HEKf), human dermal fibroblasts-adult (HDFa) and human lung fibroblasts (HLF) cell lines were treated with HN-3100, 300 and 450μmol·L-1 for 0.5, 2, 4, 6, 12, 24 and 48 h, respectively. Multi-parameter analysis technology based on cell imaging was used to examine the effects of HN-3 on cell survival, cell cycle arrest, apoptosis, autophagy and oxidative stress, along with parameters concerning nucleus, cytoskeleton (actin and tubulin), lysosome, nuclear membrane permeability (NMP), mitochondrial membrane potential (MMP) and phosphohistone H 2AX (pH2AX). RESULTS HN-3 caused irreversible cellular damage by significantly decreasing the number of HEKf, HDFa and HLF cells in a time-dependent manner (P<0.01). Before the cell number was reduced robustly, the content of reactive oxygen species and pH2AX significantly increased, but the glutathione content decreased after cells were exposed to HN-3 for 0.5 h (P<0.01). In addition, the content of lyso-some was reduced in HEKf cells at 0.5 h, but increased in HDFa and HLF cells at 0.5 and 2 h respec-tively, accompanied by the increase in microtubule-associated protein 1 light chain 3B (LC3B) puncta.With the significant reduction of the cell number in HEKf cell line, the nuclear intensity increased, nuclear area decreased, the intensity and area of F-actin and α-tubulin decreased, MMP decreased (P<0.01) and lysosomal intensity increased. But the effects of HN-3 on HDFa and HLF cell lines were quite different. The nuclear area increased, the intensity and area of F-actin and a-tubulin increased, MMP increased (P<0.01) and the intensity of lysosome increased. In HLF cells, there was an increase in LC3B puncta (P<0.01). In all the three cell lines, NMP and manganese superoxide dismutase content were increased, and cell cycle arrested at G2 phase. HN-3 Induced early apoptosis in HDFa cells but late apoptosis in HEKf cells. CONCLUSION HN-3 causes DNA damage, oxidative stress and lysosome damage at an early stage, whereas at the late stage, the imbalance of MMP, increase in NMP, and G2 phage arrest are the major cytotoxic effects. Moreover, HN-3 specifically induces nuclear condensation, cytoskeleton protein aggregation and apoptosis in HEKf cell. HN-3 Induces nuclear swelling, and loose cytoskeleton in HDFa cells and HLF cells, eventually inducing early apoptosis in HDFa cells and autophagic death in HLF cells.