Image1_A complete workflow for single cell mtDNAseq in CHO cells, from cell culture to bioinformatic analysis.png

Chinese hamster ovary (CHO) cells have a long history in the biopharmaceutical industry and currently produce the vast majority of recombinant therapeutic proteins. A key step in controlling the process and product consistency is the development of a producer cell line derived from a single cell clone. However, it is recognized that genetic and phenotypic heterogeneity between individual cells in a clonal CHO population tends to arise over time. Previous bulk analysis of CHO cell populations revealed considerable variation within the mtDNA sequence (heteroplasmy), which could have implications for the performance of the cell line. By analyzing the heteroplasmy of single cells within the same population, this heterogeneity can be characterized with greater resolution. Such analysis may identify heterogeneity in the mitochondrial genome, which impacts the overall phenotypic performance of a producer cell population, and potentially reveal routes for genetic engineering. A critical first step is the development of robust experimental and computational methods to enable single cell mtDNA sequencing (termed scmtDNAseq). Here, we present a protocol from cell culture to bioinformatic analysis and provide preliminary evidence of significant mtDNA heteroplasmy across a small panel of single CHO cells.</p

[Cu(<i>o</i>‑phthalate)(phenanthroline)] Exhibits Unique Superoxide-Mediated NCI-60 Chemotherapeutic Action through Genomic DNA Damage and Mitochondrial Dysfunction

The <i>in cellulo</i> catalytic production of reactive oxygen species (ROS) by copper­(II) and iron­(II) complexes is now recognized as a major mechanistic model in the design of effective cytotoxins of human cancer. The developmental complex, [Cu­(<i>o</i>-phthalate)­(1,10-phenanthroline)] (<b>Cu-Ph</b>), was recently reported as an intracellular ROS-active cytotoxic agent that induces double strand breaks in the genome of human cancer cells. In this work, we report the broad-spectrum action of <b>Cu-Ph</b> within the National Cancer Institute’s (NCI) Developmental Therapeutics Program (DTP), 60 human cancer cell line screen. The activity profile is compared to established clinical agentsvia the COMPARE algorithmand reveals a novel mode of action to existing metal-based therapeutics. In this study, we identify the mechanistic activity of <b>Cu-Ph</b> through a series of molecular biological studies that are compared directly to the clinical DNA intercalator and topoisomerase II poison doxorubicin. The presence of ROS-specific scavengers was employed for <i>in vitro</i> and intracellular evaluation of prevailing radical species responsible for DNA oxidation with superoxide identified as playing a critical role in this mechanism. The ROS targeting properties of <b>Cu-Ph</b> on mitochondrial membrane potential were investigated, which showed that it had comparable activity to the uncoupling ionophore, carbonyl cyanide <i>m</i>-chlorophenyl hydrazine. The induction and origins of apoptotic activation were probed through detection of Annexin V and the activation of initiator (8,9) and executioner caspases (3/7) and were structurally visualized using confocal microscopy. Results here confirm a unique radical-induced mechanistic profile with intracellular hallmarks of damage to both genomic DNA and mitochondria

Regulating Bioactivity of Cu²⁺ Bis-1,10-phenanthroline Artificial Metallonucleases with Sterically Functionalized Pendant Carboxylates

The synthetic chemical nuclease, [Cu­(1,10-phenanthroline)₂]²⁺, has stimulated research within metallonuclease development and in the area of cytotoxic metallodrug design. Our analysis reveals, however, that this agent is “promiscuous” as it binds both dsDNA and protein biomolecules, without specificity, and induces general toxicity to a diversity of cell lineages. Here, we describe the synthesis and characterization of small-molecule metallonucleases containing the redox-active cation, [Cu­(RCOO)­(1,10-phen)₂]⁺, where 1,10-phen = 1,10-phenanthroline and R = −H, −CH₃, −C₂H₅, −CH­(CH₃)₂, and −C­(CH₃)₃. The presence of coordinated carboxylate groups in the complex cation functions to enhance dsDNA recognition, reduce serum albumin binding, and offer control of toxicity toward human cancer cells, Gram positive and negative bacteria, and fungal pathogens. The induction of genomic dsDNA breaks (DSBs) were identified in ovarian adenocarcinoma cells using immunodetection of γ-H2AX. Formate, acetate, and pivalate functionalized complexes induced DSBs in a higher percentage of cells compared with [Cu­(1,10-phen)₂]²⁺, which supports the importance of inner-sphere modification toward enhancing targeted biological application

MiR-7 Triggers Cell Cycle Arrest at the G1/S Transition by Targeting Multiple Genes Including Skp2 and Psme3

<div><p>MiR-7 acts as a tumour suppressor in many cancers and abrogates proliferation of CHO cells in culture. In this study we demonstrate that miR-7 targets key regulators of the G1 to S phase transition, including Skp2 and Psme3, to promote increased levels of p27^KIP and temporary growth arrest of CHO cells in the G1 phase. Simultaneously, the down-regulation of DNA repair-specific proteins via miR-7 including Rad54L, and pro-apoptotic regulators such as p53, combined with the up-regulation of anti-apoptotic factors like p-Akt, promoted cell survival while arrested in G1. Thus miR-7 can co-ordinate the levels of multiple genes and proteins to influence G1 to S phase transition and the apoptotic response in order to maintain cellular homeostasis. This work provides further mechanistic insight into the role of miR-7 as a regulator of cell growth in times of cellular stress.</p></div

Expression of IGF1-R, p27, c-MYC, p53 and p-AKT in cells transfected with either a non-specific mimic (pm-neg) or miR-7 mimic (pm-7).

<p>GAPDH was used as a loading control.</p

Transcriptomic analysis of miR-7 transfected cells.

<p>Following pm-7 or pm-neg transfection, gene expression profiling was performed on biological triplicates using oligonucleotide arrays. Genes were considered to be differentially expressed and statistically significant if a 1.2 fold change in either direction was observed along with a Bonferroni adjusted p-value<0.05. Using the LIMMA method and Bonferroni algorithm, gene expression between the three groups was evaluated and compared (A). Unique and commonly differentially expressed probesets across the three comparisons were identified (B). <i>Red</i>: Down-regulated; <i>Blue</i>: Up-regulated. The biological processes most significantly represented by these DE genes were identified <i>in silico</i> using PANTHER and Pathway Studio (C).</p

Impact of Psme3 and Skp2 on cell proliferation.

<p>Two siRNAs (a&b) for Psme3 and Skp2 were transfected separately (A) or simultaneously (B) at a final concentration of 50 nM. Cell growth was assessed at day 3 after transfection. Knockdown of PSME3 and SKP2 was confirmed by western blotting (A). GAPDH was used as a loading control. Error bars represent standard deviations across biological triplicates. Significance was evaluated with a Sztudent's t-test. **: p-value<0.01; ***: p-value<0.001.</p

MiR-7 does not induce senescence.

<p>β-galactosidase activity was assayed after 96 hrs in cells treated with BrdU or transfected with pm-neg or pm-7. A: HCC1419 cells treated with 50 µM BrdU as positive control for senescence; B: pm-neg-treated CHO cells; C: pm-7-treated cells; D: CHO cells treated with 500 µM BrdU.</p

Binding sites of miR-7 predicted in Psme3, Rad54L and Skp2.

<p>The mature sequence of cgr-miR-7 was aligned with the sequences of its CHO mRNA targets, Psme3 (A), Skp2 (B) and Rad54L (C) using RNAhybrid <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0065671#pone.0065671-Zhao1" target="_blank">[23]</a>.</p

Impact of miR-7 on cell cycle and apoptosis.

<p>For cell cycle analysis, cells were stained with Guava Cell Cycle reagent at 3 days after treatment with pm-neg (A) or pm-7 (B). Apoptosis was evaluated with the Nexin assay reagent at day 3 (C) and day 5 (D) after transfection. The data were captured using a Guava Flow cytometer. FCS files from cell cycle assay were extracted and analysed using FCS Express Plus. Standard deviations represent four biological replicates. Significance was evaluated with a Student's t-test. ***: p-value<0.001.</p