红花单细胞克隆的建立

KT,2,4-D 及 NAA 能提高红花(Cathamus tinctorius)细胞克隆平板培养的植板率。这三种激素对细胞生长的最佳搭配是2,4-D2.0mg/l,KT0.3mg/l,NAA 0.5mg/1。红花细胞悬浮继代培养代数不同,其植板率相差甚远,用悬浮培养第三代的细胞做材料最好,其植板率是第一代悬浮培养细胞做材料的8.5倍。红花细胞克隆的条件培养的植板率是普通平板培养的3.6倍。固-液双层培养的植板率是普通平板培养的4.7倍。对已建立的红花细胞克隆进行生长速率的比较表明,生长最漫的克隆的生长速率为3.08g/g/35天,生长最决的克隆的生长速率高达23.33g/g/35天。     

Single-cell cloning and expansion of human induced pluripotent stem cells by a microfluidic culture device

The microenvironment of cells, which includes basement proteins, shear stress, and extracellular stimuli, should be taken into consideration when examining physiological cell behavior. Although microfluidic devices allow cellular responses to be analyzed with ease at the single-cell level, few have been designed to recover cells. We herein demonstrated that a newly developed microfluidic device helped to improve culture conditions and establish a clonality-validated human pluripotent stem cell line after tracing its growth at the single-cell level. The device will be a helpful tool for capturing various cell types in the human body that have not yet been established in vitro.     

Deep Multilayer Brain Proteomics Identifies Molecular Networks in Alzheimer’s Disease Progression

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Single-cell RNA sequencing identifies novel cell types in Drosophila blood

Drosophila has been extensively used to model the human blood-immune system,as both systems share many developmental and immune response mechanisms.However,while many human blood cell types have been identified,only three were found in flies:plasmatocytes,crystal cells and lamellocytes.To better understand the complexity of fly blood system,we used single-cell RNA sequencing technology to generate co mprehensive gene expression profiles for Drosophila circulating blood cells.In addition to the known cell types,we identified two new Drosophila blood cell types:thanacytes and primocytes.Thanacytes,which express many stimulus response genes,are involved in distinct responses to different types of bacteria.Primocytes,which express cell fate commitment and signaling genes,appear to be involved in keeping stem cells in the circulating blood.Furthermore,our data revealed four novel plasmatocyte subtypes(Ppn+,CAH7~+,Lsp~+ and reservoir plasmatocytes),each with unique molecular identities and distinct predicted functions.We also identified cross-species markers from Drosophila hemocytes to human blood cells.Our analysis unveiled a more complex Drosophila blood system and broadened the scope of using Drosophila to model human blood system in development and disease.     

Antioxidative effects of fluvastatin and its metabolites against oxidative DNA damage in mammalian cultured cells

We investigated the effects of fluvastatin, a 3-hydroxy-3-methylglutaryl coenzyme A reductase inhibitor, on reactive oxygen species (ROS) and on oxidative DNA damage in vitro, as well as the effects of the main fluvastatin metabolites (M2, M3, and M4) and other inhibitors of the same enzyme, pravastatin and simvastatin. The hydroxyl radical and the superoxide anion scavenging activities of fluvastatin and its metabolites were evaluated using an electron spin resonance spectrometer. Fluvastatin and its metabolites showed superoxide anion scavenging activity in the hypoxanthine-xanthine oxidase system and a strong scavenging effect on the hydroxyl radical produced from Fenton's reaction. Protective effects of fluvastatin on ROS-induced DNA damage of CHL/IU cells were assessed using the single-cell gel electrophoresis assay. CHL/IU cells were exposed to either hydrogen peroxide or t-butylhydroperoxide. Fluvastatin and its metabolites showed protective effects on DNA damage as potent as the reference antioxidants, ascorbic acid, trolox, and probucol, though pravastatin and simvastatin did not exert clear protective effects. These observations suggest that fluvastatin and its metabolites may have radical scavenging activity and the potential to protect cells against oxidative DNA damage. Furthermore, ROS are thought to play a major role in the etiology of a wide variety of diseases such as cellular aging, inflammation, diabetes, and cancer development, so fluvastatin might reduce these risks.     

An isothermal absorptiometric assay for viable microbes using the redox color indicator 2,6-dichlorophenolindophenol

A simple and rapid isothermal absorptiometric assay for detection of viable microbes using the redox color indicator 2,6-dichlorophenolindophenol (DCPIP) was studied. The absorbance of DCPIP decreased at 600 nm because of a redox reaction occurring between DCPIP and the surface membrane of viable microbes and was inversely proportional to the viable cell density. The redox reaction was found not only with bacteria, but also with yeast and a mixture of bacteria and yeast. In this assay, the influence of light scattering and absorption caused by microbial cells and coexisting substances in the sample was excluded by a time difference method. The assay required only 10 min for one incubation mixture, and highly repeatable results from three consecutive measurements were obtained by isothermal incubation for specific times at 30 °C using a thermostable three-cuvette-stir system. Thus, the cell density of microbial cell suspensions or growth medium was successfully determined, and a practical lower detection limit for food inspection was obtained at 10⁴–10⁶ cfu/ml. Single-cell effects on DCPIP reduction were evaluated and compared between species. Consequently, this assay is expected to be a useful tool for the rapid measurement of viable microbes as a preliminary assay for the Hazard Analysis Critical Control Point program.     

The role of single-cell analyses in understanding cell lineage commitment

The study of cell lineage commitment is critical for improving our understanding of tissue development and regeneration, and for realizing stem cell-based therapies and engineered tissue replacements. Recently, the discovery of an unanticipated degree of variability in fundamental biological processes, including divergent responses of genetically identical cells to various stimuli, has provided mechanistic insight into cellular decision making and the collective behavior of cell populations. Therefore, the study of lineage commitment with single-cell resolution could provide greater knowledge of cellular differentiation mechanisms and the influence of noise on cellular processes. This will require the adoption of new technologies for single-cell analysis as traditional methods typically measure average values of bulk population behavior. This review discusses the recent developments in methods for analyzing the behavior of individual cells, and how these approaches are leading to a deeper understanding and better control of cellular decision making.     

Survival prediction in patients with colon adenocarcinoma via multiomics data integration using a deep learning algorithm

The present study proposed a deep learning (DL) algorithm to predict survival in patients with colon adenocarcinoma (COAD) based on multiomics integration. The survival-sensitive model was constructed using an autoencoder for DL implementation based on The Cancer Genome Atlas (TCGA) data of patients with COAD. The autoencoder framework was compared with PCA, NMF, t-SNE, and univariable Cox-PH model for identifying survival-related features. The prognostic robustness of the inferred survival risk groups was validated using three independent confirmation cohorts. Differential expression analysis, Pearson’s correlation analysis, construction of miRNA–target gene network, and function enrichment analysis were performed. Two risk groups with significant survival differences were identified in TCGA set using the autoencoder-based model (log-rank P-value = 5.51e⁻⁰⁷). The autoencoder framework showed superior performance compared with PCA, NMF, t-SNE, and the univariable Cox-PH model based on the C-index, log-rank P-value, and Brier score. The robustness of the classification model was successfully verified in three independent validation sets. There were 1271 differentially expressed genes, 10 differentially expressed miRNAs, and 12 hypermethylated genes between the survival risk groups. Among these, miR-133b and its target genes (GNB4, PTPRZ1, RUNX1T1, EPHA7, GPM6A, BICC1, and ADAMTS5) were used to construct a network. These genes were significantly enriched in ECM–receptor interaction, focal adhesion, PI3K–Akt signaling pathway, and glucose metabolism-related pathways. The risk subgroups obtained through a multiomics data integration pipeline using the DL algorithm had good robustness. miR-133b and its target genes could be potential diagnostic markers. The results would assist in elucidating the possible pathogenesis of COAD.