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The search for specific productivity (qP) determinants in Chinese hamster ovary (CHO) cells has been the focus of the biopharmaceutical cell line engineering efforts aimed at creating "super-producer" cell lines. In this study, we evaluated the impact of small-molecule inducers and temperature shift on recombinant protein production, and used transcriptomic analysis to define gene-phenotype correlations for qP in our biological system. Next-generation RNA Sequencing (RNA-Seq) analysis revealed that each individual inducer (caffeine, hexamethylene bisacetamide (HMBA) and sodium butyrate (NaBu)) or a combination treatment had a distinct impact on the gene expression program of the RANK-Fc cell line. Temperature shift to 31 °C impacted inducer action with respect to transcriptional changes and phenotypic cell line parameters. We showed that inducer treatment was able to increase expression level of the Fc- fusion mRNA and the selectable marker mRNA from 16% up to 45% of total mRNA in the cell. We further demonstrated that qP exhibited a strong positive linear correlation to transcript levels of both the RANK-Fc fusion protein and the dihydrofolate reductase (DHFR) selectable marker. In fact, these were 2 out of 7 transcripts with significant positive correlation to qP at both temperatures. Many more transcripts were anti- correlated to qP, and gene set enrichment analysis (GSEA) revealed that those were involved in cell cycle progression, transcription, mRNA processing, translation and protein folding. Therefore, we postulate that the transcript level of the recombinant protein is a major qP determinant in our biological system, while downregulation of routine activity within the cell is necessary to divert cellular resources towards recombinant protein production.

Peroxisome proliferation occurs by at least two routes, division of existing peroxisomes and de novo biogenesis from the endoplasmic reticulum (ER). The proteins and molecular mechanisms governing peroxisome emergence from the ER are poorly characterized. In this study, we report that two integral membrane peroxins (proteins required for peroxisome biogenesis) in Saccharomyces cerevisiae, Pex29 and Pex30, reside in distinct regions of the ER and associate with Rtn1 and Yop1, reticulon family members that contribute to ER morphology, to govern peroxisome emergence from the ER. In vivo and in vitro analyses reveal that peroxisome proliferation is therefore not restricted to the peroxisome but begins at the level of the ER.

Reversible phosphorylation is the most common posttranslational modification used in the regulation of cellular processes. This study of phosphatases and kinases required for peroxisome biogenesis is the first genome-wide analysis of phosphorylation events controlling organelle biogenesis. We evaluate signaling molecule deletion strains of the yeast Saccharomyces cerevisiae for presence of a green fluorescent protein chimera of peroxisomal thiolase, formation of peroxisomes, and peroxisome functionality. We find that distinct signaling networks involving glucose-mediated gene repression, derepression, oleate-mediated induction, and peroxisome formation promote stages of the biogenesis pathway. Additionally, separate classes of signaling proteins are responsible for the regulation of peroxisome number and size. These signaling networks specify the requirements of early and late events of peroxisome biogenesis. Among the numerous signaling proteins involved, Pho85p is exceptional, with functional involvements in both gene expression and peroxisome formation. Our study represents the first global study of signaling networks regulating the biogenesis of an organelle.

Non-enzymatic glycation is a challenging post-translational modification to characterize due to the structural heterogeneity it generates in proteins. Glycation has become increasingly recognized as an important product quality attribute to monitor, particularly for the biotechnology sector, which produces recombinant proteins under conditions that are amenable to protein glycation. The elucidation of sites of glycation can be problematic using conventional collision-induced dissociation (CID)-based mass spectrometry because of the predominance of neutral loss ions. A method to characterize glycation using an IgG1 monoclonal antibody (mAb) as a model is reported here. The sugars present on this mAb were derivatized using sodium borohydride chemistry to stabilize the linkage and identified using CID-based MS(2) mass spectrometry and spectral search engines. Quantification of specific glycation sites was then done using a targeted MS(1) based approach, which allowed the identification of a glycation hot spot in the heavy chain complementarity-determining region 3 of the mAb. This targeted approach provided a path forward to developing a structural understanding of the propensity of sites to become glycated on mAbs. Through structural analysis we propose a model in which the number and 3-dimensional distances of carboxylic acid amino acyl residues create a favorable environment for glycation to occur.

Genomes provide us with a blue print for the potential of a cell. However, the activity of a cell is expressed in its proteome. Full understanding of the complexity of cells demands a comprehensive view of the proteome; its interactions, activity states and organization. Comprehensive proteomic approaches applied to peroxisomes have yielded new insights into the organelle and its dynamic interplay with other cellular structures. As technologies and methodologies improve, proteomics hold the promise for new discoveries of peroxisome function and a full description of this dynamic organelle.

We have combined classical subcellular fractionation with large-scale quantitative mass spectrometry to identify proteins that enrich specifically with peroxisomes of Saccharomyces cerevisiae. In two complementary experiments, isotope-coded affinity tags and tandem mass spectrometry were used to quantify the relative enrichment of proteins during the purification of peroxisomes. Mathematical modeling of the data from 306 quantified proteins led to a prioritized list of 70 candidates whose enrichment scores indicated a high likelihood of them being peroxisomal. Among these proteins, eight novel peroxisome-associated proteins were identified. The top novel peroxisomal candidate was the small GTPase Rho1p. Although Rho1p has been shown to be tethered to membranes of the secretory pathway, we show that it is specifically recruited to peroxisomes upon their induction in a process dependent on its interaction with the peroxisome membrane protein Pex25p. Rho1p regulates the assembly state of actin on the peroxisome membrane, thereby controlling peroxisome membrane dynamics and biogenesis.

Five missense mutations (P79L, P79T, I91S, I91T and R127H) within the forkhead DNA-binding domain of the FOXC1 transcription factor, identified in patients with Axenfeld-Rieger (AR) malformations, were studied to identify the effects of these mutations on FOXC1 structure and function. Molecular modeling and threading analyses predict that the I91S and T mutations may generate local disruptions to the structure of the forkhead domain while the R127H mutation alters the electrostatic charge of the DNA binding surface of the forkhead domain. The P79L and T mutations are not predicted to grossly perturb the structure of the forkhead domain. Biological analyses indicate that all of these missense mutations cause a range of FOXC1 perturbations, including nuclear localization defects, reduced or abolished DNA binding capacity, and a reduction in the transactivation capacity of FOXC1. These experiments extend our previous hypothesis that reduced transactivation of appropriate target genes by FOXC1, underlie AR malformations mapping to human chromosome 6p25. Importantly, these results can also be applied to predict the consequences of the molecular effects of mutations of other FOX genes that have analogous missense mutations, including FOXP2, FOXE3 and FOXC2.

Mutations in the FOXC1 gene result in Axenfeld-Rieger malformations of the anterior segment of the eye and lead to an increased susceptibility of glaucoma. To understand how the FOXC1 protein may function in contributing to these malformations, we identified functional regions in FOXC1 required for nuclear localization and transcriptional regulation. Two regions in the FOXC1 forkhead domain, one rich in basic amino acid residues, and a second, highly conserved among all FOX proteins, were necessary for nuclear localization of the FOXC1 protein. However, only the basic region was sufficient for nuclear localization. Two transcriptional activation domains were identified in the extreme N- and C-terminal regions of FOXC1. A transcription inhibitory domain was located at the central region of the protein. This region was able to reduce the trans-activation potential of the C-terminal activation domain, as well as the GAL4 activation domain. Lastly, we demonstrate that FOXC1 is a phosphoprotein, and a number of residues predicted to be phosphorylated were localized to the FOXC1 inhibitory domain. Removal of residues 215-366 resulted in a transcriptionally hyperactive FOXC1 protein, which displayed a reduced level of phosphorylation. These results indicate that FOXC1 is under complex regulatory control with multiple functional domains modulating FOXC1 transcriptional regulation.

The continued need to improve therapeutic recombinant protein productivity has led to ongoing assessment of appropriate strategies in the biopharmaceutical industry to establish robust processes with optimized critical variables, that is, viable cell density (VCD) and specific productivity (product per cell, qP). Even though high VCD is a positive factor for titer, uncontrolled proliferation beyond a certain cell mass is also undesirable. To enable efficient process development to achieve consistent and predictable growth arrest while maintaining VCD, as well as improving qP, without negative impacts on product quality from clone to clone, we identified an approach that directly targets the cell cycle G1-checkpoint by selectively inhibiting the function of cyclin dependent kinases (CDK) 4/6 with a small molecule compound. Results from studies on multiple recombinant Chinese hamster ovary (CHO) cell lines demonstrate that the selective inhibitor can mediate a complete and sustained G0/G1 arrest without impacting G2/M phase. Cell proliferation is consistently and rapidly controlled in all recombinant cell lines at one concentration of this inhibitor throughout the production processes with specific productivities increased up to 110 pg/cell/day. Additionally, the product quality attributes of the mAb, with regard to high molecular weight (HMW) and glycan profile, are not negatively impacted. In fact, high mannose is decreased after treatment, which is in contrast to other established growth control methods such as reducing culture temperature. Microarray analysis showed major differences in expression of regulatory genes of the glycosylation and cell cycle signaling pathways between these different growth control methods. Overall, our observations showed that cell cycle arrest by directly targeting CDK4/6 using selective inhibitor compound can be utilized consistently and rapidly to optimize process parameters, such as cell growth, qP, and glycosylation profile in recombinant antibody production cultures.

Cell division depends critically on the temporally controlled assembly of mitotic spindles, which are responsible for the distribution of duplicated chromosomes to each of the two daughter cells. To gain insight into the process, Vizeacoumar et al., in this issue (Vizeacoumar et al. 2010. J. Cell Biol. doi:10.1083/jcb.200909013), have combined systems genetics with high-throughput and high-content imaging to comprehensively identify and classify novel components that contribute to the morphology and function of the mitotic spindle.

Cellular control of protein activities by modulation of their abundance or compartmentalization is not easily measured on a large scale. We developed and applied a method to globally interrogate these processes that is widely useful for systems-level analyses of dynamic cellular responses in many cell types. The approach involves subcellular fractionation followed by comprehensive proteomic analysis of the fractions, which is enabled by a data-independent acquisition mass spectrometry approach that samples every available mass to charge channel systematically to maximize sensitivity. Next, various fraction-enrichment ratios are measured for all detected proteins across different environmental conditions and used to group proteins into clusters reflecting changes in compartmentalization and relative conditional abundance. Application of the approach to characterize the response of yeast proteins to fatty acid exposure revealed dynamics of peroxisomes and novel dynamics of MCC/eisosomes, specialized plasma membrane domains comprised of membrane compartment occupied by Can1 (MCC) and eisosome subdomains. It also led to the identification of Fat3, a fatty acid transport protein of the plasma membrane, previously annotated as Ykl187.

A common regulatory motif, where a heterodimeric transcriptional regulator positively autoregulates only one of its components, is found to have particular properties that enable precise and robust control of cellular responses to environmental stimuli, providing an explanation for the prevalence of this motif in evolved regulatory networks., Many important biological systems rely on regulation by dimers of proteins which upregulate the transcription of numerous targets, including one, and only one, of the dimer pair. This is termed asymmetric self-upregulation. ASymmetric Self-UpREgulated (ASSURE) networks confer rapid induction of their targets and their network behaviors are robust to parameter variation—both features appear to have contributed to the prevalence of the network across widely different biological systems. Likely evolutionary precursors to ASSURE networks are symmetrically self-upregulated network mediated by homodimers. In silico and experimental studies demonstrate that the ASSURE network confers a competitive advantage over its symmetrical counterpart., Positive feedback is a common mechanism enabling biological systems to respond to stimuli in a switch-like manner. Such systems are often characterized by the requisite formation of a heterodimer where only one of the pair is subject to feedback. This ASymmetric Self-UpREgulation (ASSURE) motif is central to many biological systems, including cholesterol homeostasis (LXRα/RXRα), adipocyte differentiation (PPARγ/RXRα), development and differentiation (RAR/RXR), myogenesis (MyoD/E12) and cellular antiviral defense (IRF3/IRF7). To understand why this motif is so prevalent, we examined its properties in an evolutionarily conserved transcriptional regulatory network in yeast (Oaf1p/Pip2p). We demonstrate that the asymmetry in positive feedback confers a competitive advantage and allows the system to robustly increase its responsiveness while precisely tuning the response to a consistent level in the presence of varying stimuli. This study reveals evolutionary advantages for the ASSURE motif, and mechanisms for control, that are relevant to pharmacologic intervention and synthetic biology applications.

Here, we present a detailed method for generating a dynamic transcriptional regulatory network from large-scale chromatin immunoprecipitation data, and functional analysis of participating factors through the identification and characterization of significantly overrepresented multi-input motifs in the network. This is done by visualizing interactive data using a network analysis tool, such as Cytoscape, clustering DNA targets of the transcription factors based on their network topologies, and statistically analyzing each cluster based on its size and properties of its members. These analyses yield testable predictions about the conditional and cooperative functions of the factors. This is a versatile approach that allows the visualization of network architecture on a genome-wide level and is applicable to understanding combinatorial control mechanisms of DNA-binding regulators that conditionally cooperate in a wide variety of biological models.

Here, we present a detailed method for generating a dynamic transcriptional regulatory network from large-scale chromatin immunoprecipitation data, and functional analysis of participating factors through the identification and characterization of significantly overrepresented multi-input motifs in the network. This is done by visualizing interactive data using a network analysis tool, such as Cytoscape, clustering DNA targets of the transcription factors based on their network topologies, and statistically analyzing each cluster based on its size and properties of its members. These analyses yield testable predictions about the conditional and cooperative functions of the factors. This is a versatile approach that allows the visualization of network architecture on a genome-wide level and is applicable to understanding combinatorial control mechanisms of DNA-binding regulators that conditionally cooperate in a wide variety of biological models.

Phosphorylation of proteins is a key posttranslational modification in cellular signaling, regulating many aspects of cellular responses. We used a quantitative, integrated, phosphoproteomics approach to characterize the cellular responses of the yeast Saccharomyces cerevisiae to the fatty acid oleic acid, a molecule with broad human health implications and a potent inducer of peroxisomes. A combination of cryolysis and urea solubilization was used to minimize the opportunity for reorientation of the phosphoproteome, and hydrophilic interaction liquid chromatography and IMAC chemistries were used to fractionate and enrich for phosphopeptides. Using these approaches, numerous phosphorylated peptides specific to oleate-induced and glucose-repressed conditions were identified and mapped to known signaling pathways. These include several transcription factors, two of which, Pip2p and Cst6p, must be phosphorylated for the normal transcriptional response of fatty acid-responsive loci encoding peroxisomal proteins. The phosphoproteome data were integrated with results from genome-wide assays studying the effects of signaling molecule deletions and known protein-protein interactions to generate a putative fatty acid-responsive signaling network. In this network, the most highly connected nodes are those with the largest effects on cellular responses to oleic acid. These properties are consistent with a scale-free topology, demonstrating that scale-free properties are conserved in condition-specific networks.

Chz1p is a histone chaperone that interacts physically and functionally with the histone variant Htz1p, which has been implicated in establishing and maintaining boundaries between transcriptionally inactive heterochromatin and active euchromatin. To investigate the role of Chz1p in chromatin organization, we performed genome-wide expression arrays and chromatin immunoprecipitations of SIR complex components and modified histones in a CHZ1 deletion strain. Deletion of CHZ1 led to reduced ubiquitination of subtelomere-associated H2B, reduced subtelomeric H3K79 di-methylation, and increased binding of Sir3p, and Sir4p at telomere-distal euchromatin regions, correlating with decreased gene expression in subtelomeric regions. This anti-silencing defect appears to be mediated by enhanced association of de-ubiquitinase Ubp10p with subtelomeric DNA, as detected by chromatin immunoprecipitation analysis. In support of this, we show that deletion of UBP10 can antagonize the subtelomeric silencing phenotype of Deltachz1. Taken together, the results demonstrate a novel role for Chz1p in epigenetic regulation, through H2B de-ubiquitination by Ubp10p.

This protocol describes the growth and stimulation, with the fatty acid oleate, of isotopically heavy and light S. cerevisiae cells. Cells are ground using a cryolysis procedure in a ball mill grinder and the resulting grindate brought into solution by urea solubilization. This procedure allows for the lysis of the cells in a metabolically inactive state, preserving phosphorylation and preventing reorientation of the phosphoproteome during cell lysis. Following reduction, alkylation, trypsin digestion of the proteins, the samples are desalted on C18 columns and the sample complexity reduced by fractionation using hydrophilic interaction chromatography (HILIC). HILIC columns preferentially retain hydrophilic molecules which is well suited for phosphoproteomics. Phosphorylated peptides tend to elute later in the chromatographic profile than the non phosphorylated counterparts. After fractionation, phosphopeptides are enriched using immobilized metal chromatography, which relies on charge-based affinities for phosphopeptide enrichment. At the end of this procedure the samples are ready to be quantitatively analyzed by mass spectrometry.

Subcellular organelles are commonly analyzed using 2D fluorescent microscopy. However, 3D reconstruction and analysis of organelle topology in a high-throughput manner promises to result in a better understanding of cellular systems. We developed image analysis methods for automated quantitative analysis of peroxisome shapes. The methods employ 3D image stacks obtained by confocal microscopy. There are three fundamental phases: image preprocessing and segmentation, 3D reconstruction, and automated quantification of peroxisome topology in 3D using shape descriptors. The algorithms are shown to produce results that can be used to classify objects of different topologies, and to enable visual studies of peroxisomes in 3D.

An automated image analysis method for extract- ing the number of peroxisomes in yeast cells is presented. Two images of the cell population are required for the method: a bright field microscope image from which the yeast cells are detected and the respective fluorescent image from which the number of peroxisomes in each cell is found. The segmentation of the cells is based on clustering the local mean-variance space. The watershed transformation is thereafter employed to separate cells that are clustered together. The peroxisomes are detected by thresholding the fluorescent image. The method is tested with several images of a budding yeast Saccharomyces cerevisiae population, and the results are compared with man- ually obtained results. Index Terms— Yeast, peroxisome biogenesis, image analysis, quantification, segmentation, watershed transformation

PURPOSE. To determine the biochemical defects that underlie Axenfeld-Rieger malformations, to determine a functional role for wing 2 in FOXC1, and to understand how mutations in this region disrupt FOXC1 function. METHODS. Sequencing DNA from patients with Axenfeld-Rieger malformation resulted in the identification of two novel missense mutations (G165R and R169P) in wing 2 of FOXC1. Site-directed mutagenesis was used to introduce these mutations, as well as previously reported mutation (M161K), into the FOXC1 cDNA. These FOXC1 mutants were evaluated to determine their ability to localize to the nucleus, bind DNA and activate gene expression. RESULTS. Two novel missense mutations were identified in unrelated patients, in wing 2 of the FOXC1 forkhead domain. Because there had been no previous biochemical analysis, the mutation M161K was also investigated. All three mutant prey teins localized correctly to the nucleus. The G165R mutation maintained wild-type levels of DNA binding; however, both the M161K and R169P mutations displayed reduced DNA binding ability. Biochemical analysis showed that all three mutations disrupt FOXC1's transactivation ability. CONCLUSIONS. Biochemical analysis of mutations G165R and R169P and of a previously reported mutation, M161K, demonstrate the functional significance of wing 2. M161K and R169P disrupt DNA binding of FOXC1, consistent with the hypothesis that wing 2 is necessary for DNA binding. The results also suggest that wing 2 plays a role in gene activation. These results provide the first insights into how mutations in wing 2 disrupt FOXC1 function.

Peroxisomes are intracellular organelles that house a number of diverse metabolic processes, notably those required for beta-oxidation of fatty acids. Peroxisomes biogenesis can be induced by the presence of peroxisome proliferators, including fatty acids, which activate complex cellular programs that underlie the induction process. Here, we used multi-parameter quantitative phenotype analyses of an arrayed mutant collection of yeast cells induced to proliferate peroxisomes, to establish a comprehensive inventory of genes required for peroxisome induction and function. The assays employed include growth in the presence of fatty acids, and confocal imaging and flow cytometry through the induction process. In addition to the classical phenotypes associated with loss of peroxisomal functions, these studies identified 169 genes required for robust signaling, transcription, normal peroxisomal development and morphologies, and transmission of peroxisomes to daughter cells. These gene products are localized throughout the cell, and many have indirect connections to peroxisome function. By integration with extant data sets, we present a total of 211 genes linked to peroxisome biogenesis and highlight the complex networks through which information flows during peroxisome biogenesis and function.

DNA arrays are valuable tools in molecular biology laboratories. Their rapid acceptance was aided by the release of plans for a pin-spotting microarrayer by researchers at Stanford. Inkjet microarraying is a flexible, complementary technique that allows the synthesis of arrays of any oligonucleotide sequences de novo. We describe here an open-source inkjet arrayer capable of rapidly producing sets of unique 9,800-feature arrays.

A segmentation method for three-dimensional image stacks obtained by confocal microscopy is proposed. The method can be used to find two-dimensional object areas based on an image stack. The segmentation method is based on K- means clustering, global thresholding, and mathematical morphology. As a case study, the proposed method is applied to 244 image stacks of the yeast Saccharomyces cerevisiae. Quantitative comparisons with manually obtained results as well as with results obtained by a two-dimensional segmentation method are used to illustrate how the additional information provided by three-dimensional image stacks can improve segmentation results.