Expression systems, recombinant cells and uses thereof

Abstract

Transcriptome analysis of constitutively upregulated genes in high-producing clones was performed to assess their ability to increase the production of proteins of interest. The products of these genes (metabolic effect products (MIPs)), such as actin, Erp27, Erp57, Foxa1, PPAR, Ca3, and Tagap, can be subdivided into different functional categories, such as signal transduction, protein folding, cytoskeleton organization, and cell survival.

Description

[Background technology]

[0001] Substantial improvements in recombinant transgene expression have steadily enhanced the production capacity of cells expressing recombinant proteins, especially recombinant therapeutic proteins (Farrell, McLoughlin, Milne, Marison, & Bones, 2014 ; Kim, Kim, & Lee, 2012 ; Wurm, 2004 ).

[0002] Chinese hamster ovary (CHO) cells are widely used host cell factories for recombinant therapeutic protein production. They offer several advantages, including their ability to generate human-like post-translational modifications and their ability to grow to high densities in suspension in chemically defined media. Furthermore, CHO cells are considered to be a safe host for the production of recombinant therapeutic proteins (Hansen, Pristovsek, Kildegaard, & Lee, 2017).

[0003] Cell engineering has so far focused mainly on improving the time integral of viable cell concentration by increasing the maximum viable cell density and extending the culture duration, as well as improving the specific productivity of CHO cells, since both parameters are determinants for the volumetric productivity of recombinant therapeutic proteins (Farrell et al., 2014; Kim et al., 2012). This has been achieved by modulating the expression of genes involved in various cellular functions, such as apoptosis, metabolism, cell cycle, and secretion, among others (Fischer, Handrick, & Otte, 2015).

[0004] However, several cellular processes have not been the subject of such intensive research, as they remain suboptimal or limiting for therapeutic protein production in CHO cells and therefore could be improved by overexpression, downregulation or knockout of specific genes (Baek, Kim, Park, & Lee, 2015; Hansen et al., 2017).

[0005] Protein folding in the endoplasmic reticulum (ER) in particular is a crucial step for therapeutic protein production, which has therefore been extensively studied (Hansen et al., 2017). Protein disulfide isomerase (PDI) is an enzyme that catalyzes native disulfide bond formation, thus facilitating protein folding. PDI is also involved in the reorganization of incorrectly formed disulfide bonds (Wang, Wang, & Wang, 2015). While some studies reported an increase in the specific productivity of some therapeutic proteins upon PDI overexpression, others observed no effect or even a decrease in the specific productivity or protein titer (Borth, Mattanovich, Kunert, & Katinger, 2005; Davis, Schooley, Rasmussen, Thomas, & Reddy, 2000; Hayes, Smales, & Klappa, 2010; Johari, Estes, Alves, Sinacore, & James, 2015; Mohan, Park, Chung, & Lee, 2007; Pybus et al., 2014). Another member of the PDI family, Erp57, was also investigated for its potential in improving therapeutic protein production. Erp57 induces disulfide bond formation in glycosylated proteins through interaction with two ER lectin chaperones calreticulin (CRT) and calnexin (CNX). (Tannous, Pisoni, Hebert, & Molinari, 2015). Upregulation of CHO cell-derived Erp57 or both CNX and CRT was found to increase the specific productivity of thrombopoietin in CHO cells (Chung, Lim, Hong, Hwang, & Lee, 2004; Hwang, Chung, & Lee, 2003). However, expression of a mouse version of Erp57 reduced the specific productivity of α1-antitrypsin and C1 esterase inhibitor (Hansen et al., 2015). These contradictory effects may be due to the individual enzyme expression levels, origin as well as the therapeutic protein expressed (Hansen et al., 2017).

[0006] Given the large amount of genes whose expression can be tuned to potentially improve therapeutic protein production, more comprehensive engineering strategies have focused on the expression of transcription factors that can act as master regulators of gene expression ( Gutierrez-Gonzalez et al., 2019 ). In particular, overexpression of ER stress-related transcription factors, sXBP1, sATF6, ATF4 and CHOP, successfully improved the specific productivity and / or titer of various therapeutic proteins (Becker, Florin, Pfizenmaier, & Kaufmann, 2008; Cain et al., 2013; Gulis, Simi, de Toledo, Maranhao, & Brigido, 2014; Haredy et al., 2013; Ku, Ng, Yap, & Chao, 2008; Nishimiya, Mano, Miyadai, Yoshida, & Takahashi, 2013; Ohya et al., 2008; Pybus et al., 2014; Tigges & Fussenegger, 2006), whereas conflicting results were obtained with sXBP1 overexpression (Ku et al., 2008; Rahimpour et al., 2013). Moreover, overexpression of YY1, a zinc finger transcription factor with pleiotropic effects on many cellular processes, led to increased antibody titers in CHO cells ( Tastanova et al., 2016 ).

[0007] Despite these advances, it has so far been difficult to identify CHO cell activities whose up- or down-regulation can have a consistent positive effect, regardless of the therapeutic protein. Moreover, only a few Chinese hamster genes have been investigated for their potential to improve therapeutic protein production. At the same time, there are an increasing number of chimeric or modified therapeutic proteins that remain difficult to express at sufficient titers for clinical and therapeutic use (Hansen et al., 2017).

[0008] It has previously been described how vitamin B5 depletion in CHO (Chinese Hamster Ovary) cell culture media, combined with gene transfer of an expression vector for the vitamin B5 transport protein, allows the identification of cell mutants capable of expressing recombinant proteins at very high levels, including the "easy to express" (ETE) trastuzumab antibody, as well as "difficult to express" (DTE) proteins such as infliximab that cannot be expressed at sufficient levels for therapeutic protein production in other contexts (WO 2016 / 156574; U.S. Patent Application Publication No. 20180066268).

[0009] However, these highly productive and efficient cells still represent a very small percentage of all stably transfected and selected cells and therefore remain difficult to identify and isolate. Publications, including patents and published patent applications, referred to in this document and / or the accompanying bibliography are hereby incorporated by reference in their entirety.

[0010] There is a need in the art to identify specific modifications of these high producing cells that confer such desired production characteristics in order to construct cell lines, particularly CHO cell lines, that are permanently more effective in producing molecules of interest. There is also a need in the art to use knowledge of the specific modifications found in high producing cells to generate expression systems and cells with such characteristics. The invention described herein addresses this and other needs. Summary of the Invention

[0011] Disclosed herein is the use of expression vectors / systems expressing MIPs (i.e. products that affect metabolism), in particular their use to express MIPs or combinations of MIPs, preferably to improve the metabolism of mammalian cells such as CHO cells, more particularly to improve the metabolism of mammalian cells, e.g. causing increased production of a protein of interest, preferably a therapeutic protein. Also disclosed herein are cells engineered to express MIPs. The MIP candidates are listed in Table 1 and are preferably related to the cellular functions listed in Figure ID.

[0012] MIPs preferably comprise mPPARα and / or Foxa1 transcription factors, m(mouse)PPARα and / or Foxa1 activated CHO cell genes or homologs such as human homologs, structural proteins such as actin, proteins involved in basic cellular metabolism such as mRNA translation, signaling and transport activities such as Tagap, Rassf9, Erp27, Erp57, Clstn3, cell survival proteins CDK15 and Ca3, proteins involved in apoptosis such as CFLAR or SOD1, proteins involved in glutathione catabolism such as GCLM or GGCT, or specific combinations thereof. Cells of the invention overexpress said MIPs or MIP human homologs and / or are treated with chemicals that increase said MIP activity, such as bezafibrate PPAR agonists and other chemical or biological agonists.

[0013] In one embodiment, the present invention is directed to a eukaryotic expression system comprising at least one metabolic impact product (MIP) expression vector comprising at least one nucleic acid encoding at least one MIP under the control of at least one regulatory sequence, wherein the MIP is preferably one of Table 1, in particular: at least one transcription factor, more preferably a pioneer transcription factor, such as Foxa1 (Forkhead box protein A1) or at least one transcription factor involved in fatty acid metabolism, such as at least one PPAR (peroxisome proliferator-activated receptor), at least one factor that regulates RNA translation, such as Casc3, and / or at least one structural protein, such as actin, and / or a protein folding protein, such as Erp27 (endoplasmic reticulum protein 27), or a protein interacting with an individual protein folding protein, such as Erp57 (endoplasmic reticulum protein 57), at least one protein involved in signal transduction, vesicle trafficking and / or cell adhesion activity, such as Tagap (T-cell GTPase-activating protein), Rassf9 (Ras-binding domain family member 9), and / or Clstn3 (calsyntenin 3), at least one protein involved in cell survival and / or proliferation, such as CDK15 (cyclin-dependent kinase 15) or Ca3 (carbonic anhydrase 3), at least one protein involved in apoptosis, such as CFLAR (CASP8 and FADD-like regulator of apoptosis) or SOD1 (superoxide dismutase 1) and / or at least one protein involved in glutathione catabolism, such as GCLM (glutamate-cysteine ​​ligase regulator subunit) or GGCT (gamma-glutamyl cyclotransferase); It is.

[0014] The at least one MIP may comprise at least one PPAR, in particular PPARα, PPARβ / δ or PPARγ and / or Foxa1, actin, Erp27 optionally in combination with Erp57. The at least one regulatory sequence may be a promoter selected from the group of CMV, EF1 alpha, CMV / EF1 alpha, SV40, RSV, PGK, promoters with expression levels of CMV, EF1 alpha, CMV / EF1 alpha, SV40, RSV, PGK and combinations thereof.

[0015] The at least one MIP may comprise at least one (including, for example, two or three) primary MIP and at least one or two or three additional MIPs that are neither primary nor secondary MIPs. In one eukaryotic expression system, there may be at least two, three, four, five or more MIPs. The MIP expression vector may further comprise a first ITR (inverted terminal repeat) upstream and a second ITR downstream of the nucleic acid encoding the MIP. The at least one regulatory sequence may comprise a MAR element or MAR construct, such as MAR1-68 and / or MARX-29, optionally comprising a unique MAR element or MAR construct between the first and second ITRs. The MIP expression vector may be a transposon donor vector. The expression system may further comprise a transposase expression helper vector or mRNA. The transposase expression helper vector may contain a PB (piggybac) transposase coding sequence, optionally flanked upstream and downstream by untranslated terminal regions (UTRs).

[0016] The eukaryotic expression system may further comprise a carrier vector comprising at least one restriction enzyme cleavage site adapted for the insertion of a nucleic acid encoding a protein of interest. The carrier vector may further comprise an antibiotic resistance gene and / or a vitamin transport protein, such as the sodium-multivitamin transporter SLC5A6. Elements of the carrier vector may also be part of another vector of the expression system.

[0017] In another embodiment, the present invention provides (a) transfecting a cell with any one of the expression vectors of the expression systems disclosed herein, and / or adding to the eukaryotic cell at least one activator of the protein product of a gene expressing a MIP; and (b) optionally transfecting the cells with a carrier vector containing the protein of interest; The present invention relates to a method comprising:

[0018] The at least one activator added to the eukaryotic cell may be an activator of at least one, two or all of the PPARs, in particular PPARα, PPARβ / δ or PPARγ, such as bezafibrate. The MA / EL of the protein of interest may be greater than 1.5x, greater than 2xML, or even greater than 2.5x or 3xML.

[0019] In one embodiment, the present invention is directed to a kit comprising in one container the eukaryotic expression system according to any one of the preceding claims and in a second container instructions on how to use said system. The kit may further comprise at least one activator of at least one MIP, where the MIP is preferably at least one PPAR, in particular PPARα, PPARβ / δ or PPARγ, and the activator may be an activator of at least one, two or all PPARs, e.g. bezafibrate.

[0020] The present invention also relates, in one embodiment, to recombinant eukaryotic cells, such as Chinese Hamster Ovary (CHO) cells, comprising any of the eukaryotic expression systems disclosed herein. The cells may be stably transfected with a MIP expression vector or a portion thereof comprising at least one, at least two, three or four MIPs.

[0021] The present invention is also directed to a eukaryotic cell comprising at least one endogenous or exogenous MIP under the control of at least one exogenous promoter, which may be part of a promoter ladder and is selected from the group of exogenous or recombinant endogenous promoters having expression levels of CMV, EF1 alpha, CMV / EF1 alpha, SV40, RSV, PGK and combinations thereof. [Brief description of the drawings]

[0022] [Figure 1]Identification of MIPs through transcriptome analysis. (A) Overview of transcriptome analysis by RNASeq comparing unselected, B5 selected and antibiotic selected cells producing easy to express (ETE) or difficult to express (DTE) proteins of interest. (B) Graph representing two major expression patterns of selected B5 target genes, here in ETE cells. Gene expression corresponds to gene read counts from RNASeq analysis. (C) Identification of transcripts upregulated in Trastuzumab high producers compared to CHO-M wild type (WT) cells and compared to cell polyclonal for Trastuzumab production. 51 mRNAs encoded by 32 genes were identified. (D) Functional classes of candidate genes identified through transcriptome analysis and literature screening (see Table 1). [Diagram 2]Effect of candidate MIPs on an expression-ready (ETE) protein of interest: Trastuzumab production. (A) Clones were isolated from the trastuzumab polyclonal population used for transcriptome analysis (see FIG. 1C). Moderate producer clones Tras6 and Tras14, which maintained a fast cell division rate in fed-batch culture, were used in the next experiment. (B) Production of expression-ready (ETE) trastuzumab antibody at days 6 (white bars), 9 (grey bars) and 11 (black bars) of fed-batch culture after stable overexpression of candidate MIPs in Tras14 clones. SRP14 overexpression was used as a positive control (LeFourn et al., 2013), and cells expressing GFP or transfected with empty vector were used as negative controls. (C) Production of trastuzumab antibody at day 11 of fed-batch culture. Stable cells expressing increasing amounts of a particular MIP were obtained by transfecting increasing amounts of MIP plasmid in the trastuzumab clone. (D) Production of trastuzumab antibody at day 13 of fed-batch culture after stable overexpression of Foxa1 in the trastuzumab clone. (E) Relative expression of Foxa1, Ca3 and Rassf9 in cells stably transfected with Foxa1 (white bars), GFP (grey bars) and in non-transfected cells (black bars) to illustrate the increased expression of Ca3 and Rassf9 secondary MIPs upon overexpression of the Foxa1 primary MIP. RNA was extracted at day 8 of fed-batch culture. [Diagram 3] Effect of candidate MIPs on a difficult to express (DTE) protein of interest: infliximab expression. MIPs were stably overexpressed in recombinant clones expressing the difficult to express (DTE) infliximab antibody. (A) Production of infliximab antibody at days 9 (grey bars) and 11 (black bars) of fed-batch culture after candidate gene overexpression. Cells transfected with empty vector were used as negative control. (B) Viable cell density of cells at days 0 (white bars), 6 (light grey bars), 9 (black bars) and 11 (dark grey bars) of fed-batch culture. [Figure 4] 1 provides a schematic diagram highlighting B5 target genes found to be regulated by PPARs. [Diagram 5]PPAR activation test in expression-ready (ETE) cells: endogenous PPAR agonist in B5 secreting cells. PPAR transient activation assay using a PPAR-reporter DsRed gene whose promoter contains a PPAR response element (PPRE). (A) Antibiotic (AB)-selected ETE cells and B5-selected ETE (trastuzumab) cells were transiently transfected with a peroxisome proliferator response element (PPRE)-DsRed reporter or cotransfected with a PPRE reporter and mouse PPARα. DsRed activity was normalized to the BFP2 marker (see Materials and Methods). (B) Negative control for PPAR transient assay corresponds to DsRed activity without a PPRE reporter. Data from panels A and B represent the mean fluorescence ± SE of corrected DsRed activity from four independent experiments. Statistics: *P≦0.05 and **P≦0.02 (one-tailed t-test; paired samples). (C) Schematic illustrating the transient PPARα activation data. [Figure 6] PPAR activation studies in expression-ready (ETE) clones: effect of exogenous pan-PPAR agonists. (A) ETE clones untreated (control) or treated with 10 mM bezafibrate PPARα ligand (trastuzumab) after 3 days of fed-batch culture (+bezafibrate). Candidate gene expression was quantified by RT-qPCR on day 6. (B) ETE cells were treated with 10 mM bezafibrate after 1 day of fed-batch culture and IgG titers were measured 10 days later. Data are means ± SE from 4 independent experiments. *P ≤ 0.05 and **P ≤ 0.02 (t-test; two-tailed; independent samples, unequal variance). [Figure 7]PPARα overexpression in difficult to express (DTE) cells Antibiotic-selected DTE (infliximab) cells were stably transfected with mouse PPARα or with empty vector. Gene expression, IgG titers and cell viability analyses were performed comparing DTE clones with empty vector and PPARα overexpressing cells (PPARα_OE). (A) Gene expression of PPARα targets, PPARα and IgG (qRT-PCR) in untreated or bezafibrate (BEZA)-treated cells. Bezafibrate was added at 10 mM on day 1 of fed-batch culture. RNA was extracted on day 6 of fed-batch culture. Infliximab IgG specific productivity (B) and cell viability (C) in non-selective or B5 starvation medium are illustrated. Cells were cultured in 12-well plates at a starting volume of 2*105 cells / mL in non-selective or B5 starvation medium for 5 days and then transferred to non-selective medium. IgG specific productivity (PCD) was then measured over 3 days of culture in non-selective medium. Each measurement is the result of three independent cultures. Statistics: *P≦0.05 and **P≦0.02 (t-test; one-tailed; independent samples, unequal variances). [Figure 8] Metabolic analysis of antibiotic- or B5-selected CHO cells overexpressing or not PPARα MIP. Vitamin B5 (Figure 8A), lactate (Figure 8B), acetyl-CoA (Figure 8C) and ketone (3-hydroxybutyrate) (Figure 8D) were quantified by LC-HRMS (liquid chromatography coupled with high-resolution mass spectrometry) in puromycin- or B5-selected polyclonal cell pools as indicated. Data are presented ± SE from four independent biological experiments. Statistics: *P ≤ 0.05 and **P ≤ 0.02 (two-tailed t-test; paired samples). Levels of these metabolites were also quantified in antibiotic-selected DTE (infliximab) cells and in DTE cell pools stably transfected with mouse PPARα expression vector (PPARa_OE) or empty vector (Figures 8E-8H). Data are presented ± SE from three technically independent experiments. Statistics: *P ≤ 0.05 and **P ≤ 0.02 (two-tailed t-test; equal variances). [Figure 9]ACTC1 overexpression in ETE and DTE CHO cells. ETE (trastuzumab, "TRAS") and DTE (Fc-fusion protein) cells were stably transfected with Chinese hamster ACTC1 cDNA encoding actin or empty vector. Gene expression and IgG titer analysis was performed comparing ETE clones (control) with empty vector cells and ACTC1 overexpressing cells (ACTC1_OE). (A) ACTC1, IgG light chain (Lc) and heavy chain (He) gene expression (qRT-PCR). Each measurement is the result of two independent cultures. (B) IgG specific productivity (PCD), i.e. picograms of secreted IgG / cell and / day, is measured over a 3-day culture in non-selective medium. (C) Production in DTE Fc-fusion protein (Ctrl=control, empty vector). [Figure 10] Effect of individual or combined expression of CFLAR, GCLM and ACTC1 on secretion of IgG1-bevacizumag-, Fc-fusion- and Fab-enzyme-fusion expressing CHO-M clones. Bevacizumag-expressing clones (Figure 10A), fc-fusion-expressing clones (Figure 10B) and fab-enzyme-fusion expressing clones (DTE) (Figure 10C) were retransfected with various individual transposable CFLAR (CASP8 and FADD-like apoptosis regulator), GCLM (glutamate-cysteine ​​ligase regulatory subunit), ACTC1 expression vectors or combinations thereof. The specific productivity of the resulting cell pools was then evaluated through their subculture in adjusted batches every 3 or 4 days. Results were presented as % of their individual bevacizumab- or Fc-fusion-control cell PCD values ​​(pg / cell / day). [Figure 11]Effect of Erp27 and / or Erp57 overexpression on therapeutic protein production. Clones producing easy-to-express or difficult-to-express therapeutic proteins were stably transfected with Erp27 or Erp57 expression vectors or co-transfected with both Erp27 and Erp57 expression vectors. Gene expression, cell proliferation, cell viability and protein production were assessed in stable polyclonal populations (panels a-e) or clones (panels f-h) in fed-batch cultures. (a) Quantification of Erp27 and Erp57 mRNA levels in Tras-producing clones expressed as fold change relative to their levels in non-transfected parental CHO cells at days 0 and 8 of fed-batch culture, assessed by qRT-PCR. Error bars are shown as SD, n=3, p-values ​​were determined using an independent one-tailed t-test. (b) Tras producing clones (parental Tras clones) were stably transfected with Erp27 and / or Erp57 expression vectors and titers of secreted trastuzumab antibodies were determined from cell culture supernatants at the end of the fed-batch culture. Cells transfected with GFP expression vector were used as control. Error bars shown as SD, n=3, independent one-tailed t-test. (c) Parental Tras clones were stably transfected with decreasing amounts of Erp27 expression vector along with an empty vector to keep the total amount of plasmid constant. Cells transfected with empty vector plasmid were used as control. Trastuzumab titers were determined at the end of the fed-batch culture. Error bars shown as SD, n=3, independent one-tailed t-test. (d) Infliximab-producing clones were characterized for secreted monoclonal antibody titers obtained during fed-batch culture using either the parental clone or the derived cell populations obtained after transfection of Erp27 and / or Erp57, or of GFP expression vectors, as indicated. Titers are shown as Tukey box plots with median (middle bar) and 25-50% and 50-75% quartiles (boxes). Whiskers extend to the minimum and maximum values ​​and remain within a 1.5-fold interquartile range. (e) Viable cell density of the fed-batch culture analyzed in panel d. Error bars are shown as SD, independent one-tailed t-test (panels d and e, n>4).(f) Etanercept-producing clones were stably transfected with Erp27 and Erp57 expression vectors or with an empty vector as a control. Cell colonies were isolated using the ClonePix® instrument and clones with the highest etanercept secretion halos were isolated and characterized for etanercept titer at the end of fed-batch culture. Titer fold change compared to control cells is illustrated as Tukey box plot for panel d. (g,h) Viable cell density and cell viability of fed-batch culture analyzed in panel f. Error bars indicate SEM, panels f-h (n≧8). [Figure 12] Effect of Foxa1 overexpression on Tras production. Tras-producing clones were stably transfected with Foxa1 or GFP expression vectors. Trastuzumab titers (a), viable cell density (b) and cell viability (c) were assessed during 10 days of fed-batch culture. n=5, independent one-tailed t-test. Titers are illustrated as Tukey box plots as described for FIG. 2, while error bars are shown as SD (panels b, c). (d) RT-qPCR analysis of mRNA levels of Foxa1 target genes and other related genes identified in FIG. 1c was performed in Foxa1-overexpressing cells, GFP-expressing cells or parental Tras clones on day 8 of the fed-batch culture. Error bars are shown as SD, n=3, paired one-tailed t-test. (e) RT-qPCR quantification of Foxa1, Ca3, Rassf9 and Tagap mRNA levels in Foxa1-overexpressing cells, GFP-expressing cells or parental Tras clones on day 0 of fed-batch culture. Error bars are shown as SD, n = 3, unpaired t test. (f) Assessment of intracellular ROS levels using carboxy-H2DCFDA in Foxa1-overexpressing cells and the parental Tras clone at days 0, 3, 6, 8 and 9 of fed-batch culture. Error bars are shown as SD, n = 3, unpaired t test. [Figure 13]Effect of Ca3, Rassf9 and Tagap overexpression on Tras production. Tras-producing Tras6 clones were stably transfected with Ca3, Rassf9, Tagap or GFP expression vectors. Trastuzumab titers (a), viable cell density (b) and cell viability (c) were determined during 10 days of fed-batch culture. Error bars are shown as SD, n=3, independent two-tailed t-test. (d) Quantification of candidate gene mRNA levels by RT-qPCR analysis in Ca3-, Rassf9- or Tagap-expressing stable populations. Data are shown relative to mRNA levels in control GFP-expressing cells. Error bars are shown as SD, n=3, paired two-tailed t-test. (e) Tras clones were stably transfected with various amounts of Ca3 expression vector together with an empty vector to keep the total amount of plasmid constant. Trastuzumab titers obtained from these cells were assessed at the end of fed-batch culture. Error bars are shown as SD, n=3, independent one-tailed t-test. [Figure 14] Effect of Foxa1 overexpression on infliximab production. Infliximab-producing clones were stably transfected with Foxa1 or GFP expression vectors and infliximab titer (a), viable cell density (b) and cell viability (c) were assessed during 9 days of fed-batch culture. n=5, independent one-tailed t-test. Titers are shown as described for FIG. 2 (panel a), while error bars are shown as SD (panels b, c). (d) Assessment of intracellular ROS levels using carboxy-H2DCFDA for Foxa1-overexpressing cells and for the parental infliximab-producing clone at days 3, 6, 7 and 8 of fed-batch culture. Error bars are shown as SD, n=3, independent one-tailed t-test. (e) RT-qPCR quantification of Foxa1, Ca3, Rassf9 and Tagap mRNA levels in Foxa1-overexpressing cells, GFP-expressing cells or in the parental infliximab clone at day 6 of fed-batch culture. Error bars are shown as SD, n = 3, one-tailed paired t test. [Figure 15]Effect of Tagap overexpression on infliximab production. Infliximab-producing clones were stably transfected with Tagap or GFP expression vectors and infliximab titer (a), viable cell density (b) and cell viability (c) were assessed during 9 days of fed-batch culture. n=4, independent one-tailed t-test. Titers are shown as described for FIG. 2. Error bars are shown as SD for panels b, c. (d) RT-qPCR quantification of Foxa1, Ca3, Rassf9 and Tagap mRNA levels in Tagap-overexpressing cells, GFP-expressing cells or in the parental clone at day 6 of fed-batch culture by RT-qPCR. Error bars are shown as SD, n=3, two-tailed paired t-test. [Figure 16] mRNA levels of candidate genes obtained from RNASeq analysis or using qPCR analysis. mRNA levels of Erp27 (a), Foxa1 (b), Ca3 (c) and Tagap (d) in parental CHO cells, Tras polyclonal cells and Tras high producing (HP) clones were analyzed by RNASeq and shown as transcripts / kilobase million (TBM) or analyzed using RT-qPCR. Data are given relative to parental CHO cells. Error bars are shown as SD. Three biological replicates were used for Tras high producing clones, while three technical replicates were used for parental CHO cells and for Tras producing polyclonal cell populations. [Figure 17]Fed-batch analysis and mRNA levels of cells producing easy-to-express or difficult-to-express therapeutic proteins and overexpressing Erp27, Erp57 or both. Viable cell density (a) and cell viability (b) of Trastuzumab-producing clones stably transfected with expression vectors for Erp27 and / or Erp57 in fed-batch culture. Error bars shown as SD, n=3, independent one-tailed t-test. Quantification of Erp27 (c) and Erp57 (d) mRNA levels in different cell populations by qRT-PCR. Data are given relative to the mRNA levels of control GFP-expressing cells. Error bars shown as SD, n=3. (e) Quantification of Erp27 mRNA levels by qRT-PCR in Tras clones stably transfected with decreasing amounts of Erp27 expression vector together with an empty vector to keep the total amount of plasmid constant. Data are given relative to Erp27 mRNA levels in control cells. Error bars shown as SD, n=2. (f and g) qRT-PCR quantification of Erp27 and Erp57 mRNA levels in infliximab-producing clones stably transfected with expression vectors for Erp27 and Erp57. Data are given relative to mRNA levels in control cells. Error bars are shown as SD, n=2. (h) Cell viability of the different cell populations analyzed during fed-batch culture. Error bars are shown as SD, independent one-tailed t-test, n>4. [Figure 18] mRNA levels of candidate genes and trastuzumab HC and LC transgenes during fed-batch culture. (a) RT-qPCR quantification of Foxa1, Rassf9, Ca3 and Tagap mRNA levels in trastuzumab (Tras) producing clones at days 0 and 8 of fed-batch culture. Data are given relative to mRNA levels in CHO cells. Error bars are shown as SD, n=3. (b) RT-qPCR quantification of Tras heavy chain (HC) and light chain (LC) mRNA levels in Foxa1 overexpressing cells, GFP expressing cells or in the parental Tras clone at day 8 of fed-batch culture. Data are given relative to mRNA levels in control GFP-expressing cells. Error bars are shown as SD, n=3, one-tailed paired t-test. [Figure 19]Analysis of Trastuzumab and Ca3 mRNA levels. (a) RT-qPCR quantification of Tras immunoglobulin heavy and light chain mRNA levels in Cas3, Rassf9 and Tagap overexpressing cells. Data are presented relative to Tras heavy and light chain mRNA levels in control GFP-expressing cells. Error bars shown as SD, n=3, one-tailed paired t-test. (b) RT-qPCR quantification of Ca3 mRNA levels in Tras clones stably transfected with various amounts of Ca3 expression vector and empty vector to keep the total amount of plasmid constant. Data are presented relative to Ca3 mRNA levels in control GFP-expressing cells. [Figure 20]Expression of ACTC1 and TAGAP genes after vitamin B5 selection. In (a) and (b), the figures show transcriptome RNA sequencing (RNA-Seq) analysis of ACTC1 and TAGAP mRNA levels in non-transfected, unselected parental control cells (C) compared to transfected cells subjected to antibiotic or B5 selection and expressing trastuzumab (ETE, panel a) and interferon-beta (DTE, panel b). After selection of transfected cells, cultures were grown in non-selective complete medium, total mRNA was isolated and subjected to high-throughput sequencing to identify genes upregulated in cell populations subjected to the B5 selection process. Relative mRNA levels correspond to normalized read counts from RNA-Seq analysis. (c) Effect of SLC5A6 overexpression and B5 depletion selection on ACTC1 and TAGAP gene expression. Cells were co-transfected with ACTC1 or TAGAP expression vectors and a puromycin resistance gene with or without an SLC5A6 expression vector, and cultures were then selected either in B5-deficient medium (B5-deficient) or in the presence of puromycin (antibiotic selection), respectively. Selected cells were transferred to non-selective medium, followed by quantification of ACTC1 and TAGAP mRNA by RT-qPCR. mRNA levels in cells selected by B5-deficiency were normalized to levels in antibiotic-selected cells. (d) Vitamin B5 content of transfected and selected cells as described for panel C was measured by LC-MS after 6 days in batch culture. (e) Comparison of ACTC1 and TAGAP mRNA levels in cells transfected with an antibiotic resistance gene with or without an SLC5A6 expression vector and subjected to antibiotic selection. Relative mRNA levels were determined by RT-qPCR and normalized to levels in antibiotic-resistant cells. Data are the mean ± SEM of three to five biological replicates. For antibiotic selection, *P ≤ 0.05; **P ≤ 0.02 (t test; one-tailed). [Figure 21]ACTC1 levels in ETE-producing cells overexpressing TAGAP. Puromycin-selected clones expressing trastuzumab antibody were stably retransfected with CHO TAGAP expression vector or empty vector and blasticidin resistance gene and selected for blasticidin resistance. The resulting stable polyclonal cell pools were used to assess TAGAP relative mRNA levels by RT-qPCR (a); and ACTC1 protein levels (b). Immunoblots of total protein extracts were probed with ACTC1 or GAPDH mouse antibodies. Ratios of ACTC1 signals were quantified by ImageJ and normalized to GAPDH. Data represent mean fluorescence ± SEM of triplicates. **P ≤ 0.02 vs. empty vector-transfected cells (t-test; two-tailed). [Figure 22] Overexpression of ACTC1 in recombinant protein producing cells. (a) Puromycin-selected clones expressing infliximab antibody were stably retransfected with CHO ACTC1 expression vector or empty vector and blasticidin resistance gene and selected for blasticidin resistance. The resulting stable cell pools were used to quantify relative mRNA levels of ACTC1 by RT-qPCR. (b) Immunoblots of total protein extracts from cell pools in panel B were probed with ACTC1 or GAPDH mouse antibodies. The ratio of signal for ACTC1 compared to GAPDH was quantified using ImageJ. (c) Red Ponceau staining of total protein of immunoblot membranes in panel C. Data show the mean ± SEM of three replicates. [Diagram 23]DTE recombinant protein production in cells overexpressing ACTC1. In (a), (b) and (c), the figures show antibiotic-selected immunoglobulin gamma (IgG)-expressing clones stably retransfected with ACTC1 or an empty expression vector, and the IgG specific productivity of the resulting stable cell pools was measured after selection for resistance to different antibiotics. The specific productivities of etanercept Fc-fusion (Enbrel®) (panel A), bevacizumab lgG1 (panel B) and infliximab lgG1 (panel C) are given as picograms of secreted IgG / cell and / day as mean ± SEM of three replicates. (d) The level of infliximab IgG of the cells analyzed in panel C was assessed under fed-batch conditions over three days in non-selective medium, where the titer of IgG released in the medium of the cell culture represents the mean ± SEM of three biological replicates. (e) Lactate content of pools of infliximab-expressing cells transfected with ACTC1-expressing or empty vector was measured after 3 days of batch culture from two independent cell pools using an LC-MS assay. Lactate concentrations represent the mean ± SEM from three technical replicates. *P≦0.05 and **P≦0.02 vs. empty vector (t-test; two-tailed). [Figure 24] Characterization of ACTC1 overexpressing cells Trastuzumab expressing CHO cell clones were stably retransfected with antibiotic resistance plasmid together with CHO ACTC1 expression vector or empty expression vector. Stably transfected antibiotic resistant cells were then selected from which clones were isolated for further analysis. (a) Quantification of ACTC1 relative mRNA levels determined by RT-qPCR. (b) Red Ponceau staining of total protein immunoblot membrane in Fig. 25a. (c) Viable cell density of clones over 10 days of fed-batch culture as performed in Fig. 25b. [Diagram 25]Productivity characterization of ACTC1 overexpressing cells Trastuzumab expressing clones were stably retransfected with CHO ACTC1 or empty expression vector and cell clones were isolated for further analysis. (a) Immunoblots of total protein extracts labeled with ACTC1 or GAPDH mouse antibodies. Histograms show the ratio of ACTC1 signal to GAPDH, assessed using Image J. Ponceau red stained membrane is shown in Figure 24a. (b) Secreted IgG titers in culture supernatants were assessed by double sandwich ELISA over 13 days of fed-batch culture. [Figure 26] Actin polymerization levels in ETE clones. (a) Representative Sir-actin fluorescent staining of F-actin in cells from a representative trastuzumab clone overexpressing ACTC1 (ACTC1_Clone2) or from a control clone transfected with an empty expression vector (Empty_Clone2). Unstained cells were used as negative control. (b) Mean fluorescent signal of Sir-actin staining from flow cytometry analysis. A total of 2x104 cells were analyzed per condition. Data illustrated in the graph represent the mean ± SEM from assays of 4 independent clones. *P<0.05 (t-test; two-tailed; unequal variance). [Figure 27] Actin polymerization levels in ETE clones. Sir-actin fluorescence histograms of F-actin in cells from all tested trastuzumab clones, clones overexpressing ACTC1 (ACTC1_clone) or control clones transfected with an empty expression vector (empty_clone) obtained from flow cytometry. Unstained cells were used as negative control. [Figure 28]Sorting of therapeutic protein-producing cell pools according to their F-actin polymerization level. (a) Representative histograms of flow cytometry analysis of trastuzumab-expressing polyclonal populations treated with SiR-actin staining. Unstained control and other analyses are shown in Figure S4. A total of 5*10 cells were analyzed per acquisition, among which 0.4-1.4*10 cells were sorted by cytofluorometry according to their low, medium or high actin polymerization (pol.) level, as indicated. (b) Selected cells were transferred to antibiotic-containing medium, followed by analysis of IgG cell surface presentation by immunofluorescence staining cytofluorometry. (c) IgG secretion assay of sorted cells in panel B. Histograms represent the mean ± SEM from 6 cell pools. **P ≤ 0.02 compared to low actin polymerization category (t-test; two-tailed; paired). [Figure 29] Sorting of Trastuzumab-expressing cell pools according to their actin polymerization levels Representative histograms of flow cytometric analysis of processed trastuzumab polyclonal populations by Sir-actin staining as described in the legend of Figure 5. The top histogram corresponds to unstained control cells, the bottom one represents the cytometric analysis of an independent Sir-actin stained cell pool. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0023] Specific alterations were identified in high producing cells, and thus in cells that produce a protein of interest, e.g. vitamin deficient cells, at higher levels than the corresponding cells growing in standard medium. In particular, metabolic factors that support the desired level of protein of interest production. It was investigated which changes in metabolism result from or are associated with the overexpression of specific CHO cell genes in rare subpopulations of CHO cells. In this way, changes in CHO cell gene expression were identified that are linked to increased CHO protein synthesis associated with high productivity of the protein of interest: products, particularly proteins whose synthesis is high and associated with recombinant protein production, were called metabolic impact products (MIPs), in particular RNA-encoded proteins, but also non-coding RNAs. Thus, the mRNA levels of high producing CHO cells selected either using vitamin B5 selection or conventional means were compared to identify mRNA level changes that are specific hallmarks of high producing cells.

[0024] FIG. 1 illustrates the cell selection approach and the comparison performed between various types of selected high producing cells and control cells.

[0025] Table 1 provides a list of candidate MIP-encoding genes identified by various approaches. It should be noted that metabolism-related MIPs may be regulatory proteins, such as transcription factors like PPARs or Foxa1, whose elevated mRNA and protein levels may then activate the expression of their target genes, such as lipid and sugar catabolic genes or anabolic genes encoding, for example, components of the mRNA translation machinery, cellular structural proteins like actin, or cellular survival factors like Ca3 or CDK15, as well as the metabolic genes themselves.

[0026] To identify genes and proteins that actually cause improved cellular metabolic properties, candidate MIPs were expressed, for example, in CHO cells expressing a therapeutic protein to determine whether their increased expression causes improved production of the protein of interest (Figures 2-3). The effect of overexpressing regulated MIPs (e.g., primary MIPs) such as Foxa1 or PPAR on the expression of other MIPs (e.g., secondary MIPs) and whether they could collectively improve cellular metabolism, e.g., metabolism of lipids, lipid precursors such as acetyl-CoA, and by-products such as lactate, thereby possibly improving the metabolic fitness of the cell, which in turn could further increase production of a protein of interest, such as therapeutic IgG. Alternatively, it was also tested whether overexpressing structural MIPs such as actin could result in increased synthesis and therefore production of the protein of interest. These figures illustrate that some, but not all, MIP candidates can increase production of the easy to express (ETE) trastuzumab antibody and / or the difficult to express (DTE) infliximab antibody. Certain MIPs may be shown to improve production of one, for example, therapeutic protein, but not another.

[0027] Eukaryotic cells, including mammalian cells, such as recombinant mammalian cells, according to the present invention can be maintained under cell culture conditions. Non-limiting examples of this type of cell are HEK293 (human embryonic kidney), Chinese hamster ovary (CHO) cells and mouse myeloma cells, including NS0 and Sp2 / 0 cells. Modified forms of CHO cells include CHO-K1 and CHO pro-3. In a preferred embodiment, the SURE CHO-M cell line (SELEXIS SA, Switzerland) is used. The cellular proteins of these eukaryotic cells support the expression of transgenes encoding proteins of interest that have been transfected into the eukaryotic cells. These cellular proteins are involved, among others, in lipid metabolism, signal transduction, protein trafficking, transcription and translation, cell trafficking, protein repair, protein folding and cell adhesion, all of which are required for the expression of these transgenes encoding proteins of interest and which are considered to be their counterparts in other species, such as humans, as metabolic impact products (MIPs), particularly proteins, and also non-coding RNAs, such as those shown in Table 1. One or more transgenes expressing these MIPs (MIP transgenes) may be added to a cell via a MIP eukaryotic expression vector described herein. Alternatively, or in addition, endogenous MIP expression (i.e., expression of a nucleic acid in the genome of a cell encoding one or more MIPs) may be stimulated via the addition of one or more substances that directly or indirectly affect expression of MIPs, including endogenous genes expressing MIPs, such as the PPAR agonist bezafibrate, or via promoter exchange, where such endogenous MIPs are placed under the control of different exogenous or endogenous promoters, each of which is associated with a specific expression level of such MIP and can therefore be used to alter expression of such endogenous MIPs.Preferably, the selected MIPs according to the invention are MIPs whose expression results in cells that also carry a transgene encoding a protein of interest (generally, but not necessarily, on a separate vector, referred to herein as the carrier vector) that is expressed at a level that exceeds the level of expression of the transgene when the cell is not transfected with a vector containing one or more of the selected MIPs. The nucleic acid encoding the MIP generally comprises or consists of the coding sequence (CDS) of the cellular or human counterpart. Table 1 shows some MIPs.

[0028] Primary MIPs increase the expression of their target genes and of secondary MIPs, regulatory proteins such as: Foxa1 (forkhead box protein A1) is a transcription factor involved in embryonic development, in establishing tissue-specific gene expression in differentiated tissues and in regulating gene expression, and is thought to act as a "pioneer" factor, thus opening condensed chromatin to other proteins, in the case of Foxa1, through interactions with nucleosomal core histones, thereby displacing linker histones at target enhancer and / or promoter sites.

[0029] PPARs (peroxisome proliferator-activated receptors) are ligand-activated transcription factors. PPARs exist primarily in three subtypes; α, β / δ, and γ, each of which mediates the physiological actions of various fatty acids (FAs) and FA-derived molecules and is involved in FA metabolism. Activation of PPAR-β / δ promotes fatty acid metabolism. Thus, the PPAR family plays a major regulatory role in energy homeostasis and metabolic function in cells. All PPARs heterodimerize with retinoid X receptors (RXRs) and bind to specific regions on the DNA of target genes. These DNA sequences are called PPREs (peroxisome proliferator hormone response elements). The consensus sequence of PPREs consists of two AG-GTCA-like sequences unidirectionally aligned with a single nucleotide spacer. Generally, this sequence occurs in the promoter region of a gene, and when PPAR binds its ligand, transcription of the target gene is increased or decreased depending on the gene. The promoter region with PPREs, TATA boxes, and transcription start sites can be located in repressive chromatin structures. Binding of ligand to the PPAR / RXR / corepressor complex causes the release of the corepressor from the ligand-activated PPAR / RXR complex. The activated PPAR / RXR complex binds to the PPRE and induces a structural change in chromatin, resulting in the release of histone H1. The PPRE-bound PPAR / RXR targets a coactivator-acetyltransferase complex to the promoter. The coactivator-acetyltransferase complex acetylates the histone tail (Ac), thereby generating a transcriptionally active structure. Additional transcription factors (TFs) and RNA Pol II initiation complexes are recruited to accessible promoters and transcription is initiated. Figure 4 highlights B5 target genes found to be regulated by PPAR, most of which ultimately feed into lipid metabolism.

[0030] Endogenous ligands (endogenous agonists) that activate PPARs include free fatty acids and eicosanoids. PPARs are also the molecular targets of many drugs (exogenous agonists). For example, fibrates, such as clofibrate, gemfibrozil, ciprofibrate, bezafibrate, and fenofibrate, activate PPARα. They are indicated for cholesterol disorders characterized by high triglycerides. Bezafibrate also activates other types of PPARs, namely PPARβ / δ and PPARγ, and is therefore considered a pan-PPAR activator. Antidiabetic thiazolidinediones (TZDs) activate PPARγ and are used against diseases characterized by insulin resistance, such as diabetes. GW501516 (also known as GW-501, 516, GW1516, GSK-516) is a PPARδ receptor agonist. The synthetic chemical perfluorooctanoic acid activates PPARα, whereas the synthetic perfluorononanoic acid activates both PPARα and PPARγ.

[0031] Secondary MIPs are MIPs expressed as a result of overexpression of primary MIPs, such as PPARs and / or Foxa1. As described elsewhere herein, cells expressing a protein of interest above a threshold level not only expressed PPARs and unrelated MIPs at levels not observed in cells that did not express the protein of interest above the threshold level, but also expressed MIPs whose expression is known or thought to be influenced by PPARs, such as Hmgcs2, Acot1, and Cyp4a14. Ca3 and Rassf9 are Foxa1 transcriptional targets and therefore may be secondary MIPs. The MIPs discussed below may or may not be secondary MIPs.

[0032] Structural MIP The cytoskeleton comprises a network of actin microfilaments, microtubules and intermediate filaments that are required for multiple cellular processes such as cell shape and resistance to mechanical deformation (Mays, Beck, & Nelson, 1994), protein synthesis (Hudder, Nathanson, & Deutscher, 2003), protein transport and secretion (Paavilainen, Bertling, Falck, & Lappalainen, 2004; Stamnes, 2002), linking of cellular components (Knull & Walsh, 1992) and metabolic channeling (Aon & Cortassa, 2002). Furthermore, increases in monoclonal antibody production correlated with significant increases in cytoskeletal proteins such as actin, tubulin or actinin-binding cofilin (Dinnis et al., 2006). Recent studies have shown that suspension CHO cells develop from adherent cells due to the disruption of the extracellular attachment matrix accompanied by major changes in the cytoskeleton, such as increased expression of actin filaments, which are required for proper interaction with integrins, resistance to shear stress, and cell growth in suspension (Walther, Whitfield, & James, 2016). Thus, cytoskeletal organization and regulation of actin filament levels may affect the fitness of suspension cells and recombinant protein expression, from mRNA translation to protein secretion.

[0033] Structural MIPs directly contribute to cell structure and include actin. Actin monomers polymerize to form filaments that organize into dynamic networks with fundamental roles in multiple diverse cellular processes. Actin network turnover drives multiple cellular processes, including cell migration, cell adhesion, changes in cell morphology, vesicle trafficking, and cytokinesis. ACTC1 is a major protein of cardiac sarcomere thin filaments, which contributes to cardiac muscle contractile function. Consistently, ACTC1 deficiency has been primarily associated with cardiac disease (Debold et al., 2010; Wang et al., 2016).

[0034] MIPs involved in signal transduction, vesicle transport activity and cell adhesion include, for example, Tagap (T cell GTPase-activating protein), Rassf9 (Ras binding domain family member 9).

[0035] The protein encoded by the Rassf9 gene is localized to perinuclear endosomes. This protein associates with peptidylglycine alpha-amidating monooxygenase and may be involved in the transport of this enzyme through the secretory or endosomal pathway. Clstn3 (calsyntenin 3) may regulate calcium-mediated postsynaptic signals.

[0036] TAGAP is not only a signaling protein, but also participates in cytoskeletal organization (see ACTC1 above). Thus, TAGAP is involved in thymocyte loss of adhesion and cytoskeletal reorganization of thymocytes and T cells (Connelly et al., 2014; Duke-Cohan et al., 2018). Alterations in the TAGAP gene have been associated with various autoimmune diseases (Eyre et al., 2010).

[0037] MIPs involved in fundamental cellular metabolism, such as mRNA translation, include, for example, asparaginyl-t-RNA synthetase (see Table 1 for further examples).

[0038] Proteins involved in protein folding (also protein folding proteins) include Erp27 (endoplasmic reticulum protein 27.7 kDa), which is thought to have chaperone activity, ERp57, which is a luminal protein of the endoplasmic reticulum (ER) and a member of the protein disulfide isomerase (PDI) family, and ERP44, which is also a protein disulfide isomerase and is involved in protein quality control at the endoplasmic reticulum-Golgi interface.

[0039] Cell survival and / or proliferation proteins include CDK15 (cyclin-dependent kinase 15), which belongs to a large family of serine / threonine protein kinases that regulate cell proliferation, apoptosis, cell differentiation and embryonic development. Ca3 (carbonic anhydrase 3) is involved in the reversible hydration of carbon dioxide.

[0040] Proteins involved in apoptosis include CFLAR (CASP8 and FADD-like regulator of apoptosis) or SOD1 (superoxide dismutase 1).

[0041] Proteins involved in glutathione catabolism include GCLM (glutamate-cysteine ​​ligase modifier subunit) or GGCT (gamma glutamyl cyclotransferase).

[0042] Eukaryotic cells such as Chinese Hamster Ovary (CHO) cells (also referred to herein as eukaryotic host cells or simply host cells) are widely used in industrial processes for the production of recombinant therapeutic proteins. The viability of e.g. CHO cells, NSO, BHK and human embryonic kidney-293 (HEK-293) depends on vitamin uptake. Mammalian cells cannot synthesize them and therefore mammals must obtain them from their diet. The main function of vitamins is to act as cofactors or coenzymes in various enzymatic reactions such as acetyl-CoA biosynthesis. It has been shown that vitamin depletion during fed-batch bioreactor production conditions can be used to improve the viability of cell clones and their productivity in terms of titers of secreted recombinant therapeutic proteins. These effects were obtained, for example, by reducing the levels of B5 or H vitamins. Vitamin metabolism proteins can improve vitamin availability in cells and in particular vitamin transport proteins can act as selectable markers. Thus, in its simplest form, recombinant eukaryotic cells expressing the respective vitamin transport protein as a selectable marker in media lacking a certain vitamin can grow better than cells that do not express the respective vitamin transport protein. The sodium-multivitamin transporter SLC5A6 has been characterized as a transport protein for both B5 and H vitamins. Other examples of vitamin metabolism proteins include pantothenate kinase 1, 2, or 3. Pantothenate kinase is a key regulatory enzyme in the biosynthesis of coenzyme A (CoA).

[0043] A transgene, as used in the context of the present invention, is an isolated deoxyribonucleotide (DNA) sequence that codes for a certain protein. In the case of MIPs, the transgene DNA sequence may also code for non-coding RNA. The term transgene is used in the context of the present invention to refer to a DNA sequence that is introduced into a cell, such as a eukaryotic host cell, via gene transfer. Thus, a transgene is always exogenous, but may be heterologous or homologous.

[0044] Exogenous nucleic acid, as used herein, means that the referenced nucleic acid is introduced into a host cell. The source of the exogenous nucleic acid may be the expressed homologous or heterologous nucleic acid. Correspondingly, the term endogenous refers to a nucleic acid molecule present in the host cell prior to gene transfer. The term heterologous nucleic acid refers to a nucleic acid molecule originating from a source other than the species of the host cell, while the term homologous nucleic acid refers to a nucleic acid molecule originating from the same species as the host cell. Thus, an exogenous nucleic acid according to the present invention may utilize either or both heterologous or homologous nucleic acids. For example, a cDNA of a human interferon gene is a heterologous exogenous nucleic acid in CHO cells, but a homologous exogenous nucleic acid in HeLa cells. Similarly, the genes encoding the MIPs shown in Table 1 are exogenous nucleic acids when introduced into CHO cells via a vector, such exogenous nucleic acids being heterologous (e.g., human, mouse, E. coli) or homologous (e.g., Cricetulus griseus).

[0045] Apart from the MIP transgene, some transgenes according to the invention are transgenes encoding proteins of interest, such as therapeutic proteins, thus therapeutically active proteins including immunoglobulins (Ig) and Fc fusion proteins. Certain immunoglobulins, such as infliximab (Remicade) or coagulation factor VIII, are extremely difficult to express due to poorly characterized bottlenecks within the cells. With the aid of the MIP expression vectors, recombinant eukaryotic cells and methods of the invention, these bottlenecks can be identified and / or removed.

[0046] Specific productivity, such as IgG productivity, of a clone expressing a transgene, such as a protein of interest, is typically determined as the slope of IgG concentration versus integrated viable cell count (IVCD) calculated during the production phase from day 3 to day 7, and expressed as pg / cell and / day (pcd).

[0047] Easily expressed (ETE) transgenes, particularly those encoding proteins of interest such as therapeutic proteins, are expressed in CHO at levels greater than 10 pcd in standard media. An example of an ETE transgene is the trastuzumab antibody.

[0048] Difficult to express (DTE) transgenes, particularly transgenes encoding proteins, particularly proteins of interest such as therapeutic proteins, are generally expressed in standard media in CHO at levels below 10pcd. Examples of DTE transgenes are transgenes encoding infliximab IgG1 (Remicade), etanercept Fc-fusion (Enbrel®) or bevacizumab or other secreted proteins such as coagulation factor VIII, as well as interferon beta proteins. As used herein, the term transgene does not include non-transcribed adjacent regions such as RNA transcription initiation signals, polyadenylation addition sites, promoters or enhancers.

[0049] A vector according to the invention is a nucleic acid molecule capable of transporting another nucleic acid, such as a nucleic acid encoding a MIP, into a cell. For example, a plasmid is one type of vector, and a retrovirus or lentivirus is another type of vector. In one embodiment, the vector is linearized prior to gene transfer.

[0050] MIP expression vectors contain regulatory sequences, such as promoters, enhancers, locus control regions (LCRs), matrix attachment regions (MARs), scaffold attachment regions (SARs), insulator elements and / or nuclear matrix attached DNA, that provide for efficient transcription of the MIP incorporated into the expression vector. These regulatory sequences are always exogenous and often heterologous (see below).

[0051] A promoter refers to a DNA sequence that can control the expression of a coding sequence. In some embodiments, a promoter sequence includes proximal and more distant upstream elements, the latter elements often being called enhancers. Thus, an "enhancer" is a DNA sequence that can stimulate promoter activity, and can be homologous or heterologous.

[0052] A MIP expression vector, as well as any other vector or recombinant cell disclosed herein, may comprise one or more promoters selected from the group consisting of CMV, EF1 alpha, CMV / EF1 alpha fusion promoter, SV40, RSV, PGK and combinations thereof, which may be used, for example, to express any one or combination of MIPs at expression levels specific for each promoter. For example, the promoter CMV / EF1 alpha (commonly referred to as very strong promoter) can be used to express the respective genes at a first expression level (= CMV / EF1 alpha promoter expression level + / - 5% or 10%) specific for the CMV / EF1 alpha promoter), while the promoter CMV (commonly referred to as strong promoter when it is full length (hereinafter "CMV promoter") can be used to express the respective genes at a second expression level (= CMV promoter expression level + / - 5% or 10%) when it is provided as a modified full length CMV promoter for reduced expression (sometimes referred to as "minimal CMV promoter"), where the first expression level exceeds the second expression level specific for the CMV promoter. Depending on the type of protein of interest to be expressed, one or the other promoters can be used. These promoters are inducible in certain embodiments. The different promoters can be part of a promoter ladder comprising at least two promoters.

[0053] Promoter replacement, including the introduction of one or more promoters and / or the generation of variants of one or more promoters (referred to herein as "recombinant promoters") within a host cell, may also be used to alter the expression levels of a MIP that exhibits multiple expression levels (e.g. promoter ladders) or different regulatory properties (e.g. tighter control regulation of selected genes) and that is endogenous to a eukaryotic cell (host cell), such as a CHO cell.

[0054] A promoter ladder comprises multiple promoters with different levels of promoter activity. A promoter ladder can comprise two, three, four, five or more promoters, each associated with an activity that provides an expression level of a gene under the control of the promoter, for example, a second expression level that exceeds a first expression level. A promoter ladder can be associated with a gene of an endogenous MIP, but also with an exogenous counterpart. The ladder allows promoter switching depending on the MIP level required for the expression of a transgene that expresses a product of interest at a certain level. Such ladders can also be used to optimize the expression level used in the context of different types of such transgenes.

[0055] The carrier vector according to the present invention is an expression vector adapted to transport a transgene expressing a protein of interest into a cell. It also contains a regulatory sequence and generally has at least one restriction enzyme cleavage site adapted to insert a nucleic acid encoding the protein of interest and optionally an antibiotic resistance gene and / or a vitamin transport protein such as sodium-multivitamin transporter SLC5A6. The expression vector may also contain an origin of replication. As those skilled in the art will readily understand, a transgene expressing a protein of interest may also be incorporated into a MIP vector.

[0056] Transposons are mobile genetic elements that efficiently transpose between vectors and chromosomes via a "cut and paste" or "copy and paste" mechanism. During transposition, the transposase of a transposon system (e.g., the PB transposase of the PiggyBac transposon system) recognizes the transposon-specific terminal inverted repeats (ITRs) located at both ends of the transposon (for any transposon system, there are 5'- and 3' ITRs), displaces its contents from the original site, and integrates them into a chromosomal site, such as the TTAA chromosomal site. For example, the strong activity of the PiggyBac transposon system allows a gene of interest located between two ITRs to easily move into a target genome. The PiggyBac transposon system is described, for example, in U.S. Patent Application Publication No. 2010 / 0154070, which is incorporated herein by reference in its entirety (see also U.S. Patent Application Publication No. 2015 / 0361451). Among non-viral vectors, transposons are attractive due to their ability to integrate single copies of DNA sequences at high frequencies at multiple loci within the host genome. Unlike viral vectors, some transposons have been reported not to preferentially integrate near cellular genes, and therefore they are less likely to introduce deleterious mutations. Furthermore, transposons are easily generated and manipulated, and are generally composed of a transposon donor vector / plasmid (or simply "transposon vector") containing cargo DNA flanked by inverted repeat sequences and a transposase-expressing helper vector / plasmid (also referred to herein as "transposase-expressing vector") or mRNA. Several transposon systems have been developed to mobilize DNA in various cell lines without interfering with endogenous transposon copies. For example, the PiggyBac (PB) transposon, originally isolated from the cabbage looper moth, efficiently transposes cargo DNA into various mammalian cells.In transposon donor plasmids, epigenetic regulatory elements can be used to protect cargo DNA from unwanted epigenetic effects when placed near transgenes on plasmid vectors. For example, MARs can enhance cargo DNA genomic integration and transcription while preventing heterochromatin repression, as exemplified by the strong human MAR1-68 and MAR X-29 elements. They can also act as insulators, thereby preventing the activation of nearby cellular genes. MAR elements have therefore been used to mediate high and sustained expression in the context of plasmid or viral vectors (see US Patent Publication No. 2015 / 0361451, specifically incorporated herein by reference in its entirety).

[0057] MAR elements (also called MAR sequences or MARs) belong to a broader group of epigenetic regulator elements, which also include boundary or insulator elements, such as cHS4, locus control regions (LCRs), stabilizing anti-repressor (STAR) elements, ubiquitously acting chromatin opening (UCOE) elements, or histone modifiers, such as histone deacetylases (HDACs).

[0058] MAR elements can be defined based on the identified MAR on which they are primarily based: thus, the MAR construct is a MAR element with the majority of its nucleotides (50%+, preferably 60%, 70% or 80%) based on MAR S4. Some simple sequence motifs, such as high A and T content, have been found to be abundant in MARS. Other commonly found motifs are the A-box, T-box, DNA unwinding motif, SATB1 binding site (H-box, A / T / C25) and consensus topoisomerase II site for vertebrates or Drosophila.

[0059] MARs are generally characterized as sequences in the DNA of eukaryotic chromosomes to which nuclear matrix is ​​attached. The properties of MARs are only partially determined by their primary structure. It is known that the typical primary structure found in MAR elements, such as AT-rich regions, results in tertiary structures, i.e., certain curvatures that define the function of MARs. Thus, MARs are often not only determined by their primary structure, but also by their secondary and tertiary structures, such as their degree of curvature and / or physical properties such as melting temperature.

[0060] A curved DNA region rich in AT / TA-dinucleotides (hereinafter referred to as "AT-rich region"), as is commonly found in MAR elements, is a curved DNA region that contains a large number of A and T, particularly in the form of the dinucleotides AT and TA. In a preferred embodiment, it contains at least 10% of the dinucleotides TA and / or at least 12% of the dinucleotides AT over a stretch of 100 consecutive base pairs, preferably at least 33% of the dinucleotides TA and / or at least 33% of the dinucleotides AT over a stretch of 100 consecutive base pairs (or over the respective shorter stretches, if the AT-rich region is of shorter length), while having a curved secondary structure. However, an "AT-rich region" may be as short as about 30 nucleotides or less, but is preferably about 50 nucleotides, about 75 nucleotides, about 100 nucleotides, about 150, about 200, about 250, about 300, about 350 or about 400 nucleotides long or longer.

[0061] Some binding sites also often have a relatively high A and T content, such as the SATB1 binding site (H-box, A / T / C25) and the consensus topoisomerase II site for vertebrates (RNYNNCNNGYNGKTNYNY) (SEQ ID NO: 154) or for Drosophila (GTNWAYATTNATNNR) (SEQ ID NO: 155). However, binding site regions (modules), especially TFBS regions, containing clusters of binding sites, can be easily distinguished from AT and TA dinucleotide rich regions ("AT rich regions") from MAR elements with high A and T content by comparison of the bending patterns of the regions. For example, in the case of human MAR1_68, the latter may have an average degree of bending of about 3.8 or more than about 4.0, while the TFBS regions may have an average degree of bending of about 3.5 or less than about 3.3. The identified regions of MARs may also be confirmed by alternative means, such as, but not limited to, relative melting temperatures as described elsewhere herein. However, such values ​​are species-specific and therefore may vary between species, e.g., may be lower. Thus, each AT and TA dinucleotide rich region may have a lower degree of curvature, such as about 3.2 to about 3.4, or about 3.4 to about 3.6, or about 3.6 to about 3.8, and the TFBS region may have a relatively lower degree of curvature, such as less than about 2.7, less than about 2.9, less than about 3.1, less than about 3.3, etc. In SMAR ScanII, each lower region size may be selected by one skilled in the art.

[0062] Some preferred identified MAR elements include, but are not limited to, MAR1_68, MAR X_29, MAR1_6, MAR S4, MAR S46, including all their immature forms as disclosed in WO2005040377 and US20070178469, which are specifically incorporated by reference herein for their disclosure of sequences of these and other MAR elements. Chicken lysozyme MAR is also a preferred embodiment (see U.S. Pat. No. 7,129,062, which is also specifically incorporated herein for its disclosure of MAR elements).

[0063] When a vector is said to contain a unique MAR, this means that there is one MAR in this vector and no other MARs of either the same or different type or structure in this vector. Such a unique MAR is, in one embodiment, located downstream of the integration site of a transgene encoding a protein of interest, for example, between the transgene integration site and the 3'ITR. In one embodiment, such a transgene is a CDS encoding a MIP, located between the 5'ITR and the 3'ITR. The MAR follows the polyadenylation signal at the 3' end of the CDS encoding the MIP, and is located between the polyadenylation site and the 3'ITR. A promoter, such as a CMV promoter and / or a CMV / EF1 alpha fusion promoter, is located in the 5'ITR and the CDS encoding the MIP.

[0064] Gene transfer, as used herein, refers to the introduction of a nucleic acid, including naked or purified nucleic acid or a vector' that carries a specific nucleic acid into a cell, particularly a eukaryotic cell, including a mammalian cell. Any known gene transfer method can be used in the context of the present invention. Some of these methods involve promoting the permeability of biological membranes to bring the nucleic acid into the cell. Prominent examples are electroporation or microporation. The method can be used by itself or can be supported by sound waves, electromagnetic and thermal energy, chemical permeabilization enhancers, pressure, etc., to selectively promote the rate of entry of the nucleic acid into the host cell. Other gene transfer methods, such as lipofection or carrier-based gene transfer, including viruses (also called transduction) and chemical-based gene transfer, are also within the scope of the present invention. However, any method that brings a nucleic acid inside a cell can be used. Transiently transfected cells carry / express the transfected RNA / DNA for a short period of time and do not transmit it. Stable transfected cells continually express and propagate the transfected DNA: the exogenous nucleic acid is integrated into the genome of the cell. Stable transfected cells according to the invention include, for example, cells in which the MIP transgene becomes part of the genome of the cell following transfection with a transposon vector.

[0065] Cells growing in complete medium have all vitamins available at standard concentrations. Standard concentrations are referred to herein as 1X. Standard concentrations for B1, B5 and H(1X) were set at 7.5 μM, 2.5 μM and 0.5 μM, respectively. B5 was added at 10 μM for CHO cells. -4 X~10 -3 It was determined that the proliferation-limiting concentration range was around X (0.25 to 2.5 nM), while 10 -2 Concentrations above X allowed normal culture growth. The limiting concentration of B1 was 10 for CHO cells. -5 X(15pM)~10 -4 X (150 pM), whereas it is 10 -5 It was lower than X (5 pM).

[0066] In media with limiting concentrations of the vitamins (defined or deficient media), the concentration is less than 1X, e.g., 10X, relative to the standard concentration of each vitamin present in complete media (1X). -1 X, 10 -2 X, 10 -3 X, 10 -4 X, 10 -5 X. A vitamin concentration is considered to be saturated (also referred to herein as a "saturating medium") if the concentration exceeds the concentration in a standard reference medium (e.g., 2X, 3X, 4X, 5X, or 10X the amount found in complete medium).

[0067] The present invention takes advantage, inter alia, of the fact that in a restrictive medium, cell growth and / or division can be arrested and the cells generate MIPs that cause the production of a protein of interest at a maximum arrested / expression level ("MA / EL" in [g / 1]). When the protein of interest is co-transfected into the cells with one or more genes encoding the MIPs that are produced during cell arrest, the protein of interest can be produced at an MA / EL that can exceed the maximum level ("ML" in [g / 1]) of the protein expressed by the same type of cell in the absence of one or more MIPs / when cell growth and / or division is not arrested. The MA / EL can be greater than 1.5xML, greater than 2xML, or even greater than 2.5x or 3xML. For example, the ML of a protein of interest, such as an antibody, expressed by a recombinant cell, such as a recombinant CHO cell, that is not co-transfected with a MIP may be about 1 g / L of antibody, while the MA / EL of a protein of interest, such as an antibody, expressed by a recombinant cell that also expresses one or more MIPs may be about 1.5 g / L or 2 g / L of antibody or more.

[0068] Expression systems / vectors generally contain a selectable marker gene that facilitates the selection of eukaryotic cells (host cells, also referred to herein as recombinant eukaryotic cells) that are transformed with a vector containing a polynucleotide encoding a protein of interest. The selectable marker (or "selectable protein") expressed by the gene is often based on antibiotic resistance. For example, a puromycin resistance selection expression cassette can be used to identify cells that have been successfully transformed with the cassette through the addition of puromycin. However, selection without resistance to antibiotics is also possible. In the context of the present invention, vitamin metabolism proteins, especially vitamin transport proteins, can act as selectable markers either alone or in combination with other selectable markers. Thus, in its simplest form, recombinant eukaryotic cells expressing individual vitamin transport proteins as selectable markers can grow better than cells that do not express the individual vitamin transport proteins in media lacking one vitamin, such as B5 (pantothenic acid), vitamin B1 (thiamine) and / or H (B8 or biotin). However, as discussed herein, even in standard media, vitamin transport proteins provide a growth advantage and can therefore be used as selectable markers. The expression system of the present invention can contain, in addition to selectable marker genes based on, for example, antibiotic resistance, as selectable markers, vitamin metabolism proteins, in particular vitamin transport proteins, such as the sodium-multivitamin transporter SLC5A6.

[0069] Nucleic acids and proteins having greater than 50%, 60%, 70%, 75%, 80%, 85%, 90%, 95%, 96%, 97%, 98% or 99% sequence identity with the polynucleotide and protein sequences disclosed herein are also part of the invention, either alone or as part of any of the systems (e.g. vectors and cells), cells, methods and kits disclosed herein. The nucleic acids of the invention may differ from any wild-type sequence by at least 1, 2, 3, 4, 5, 6, 7, 8, 9 or more nucleotides. In many instances, nucleic acids composed of the CDS of individual genes / cDNAs are preferred.

[0070] The term sequence identity refers to a measure of the identity of nucleotide or amino acid sequences. Generally, sequences are aligned to obtain the greatest correspondence. "Identity" per se has an art-recognized meaning and can be calculated using published techniques (see, for example: Computational Molecular Biology, Lesk, AM, ed., Oxford University Press, New York, 1988; Biocomputing: Informatics and Genome Projects, Smith, DW, ed., Academic Press, New York, 1993; Computer Analysis of Sequence Data, Part I, Griffin, AM, and Griffin, HG, eds., Humana Press, New Jersey, 1994; Sequence Analysis in Molecular Biology, von Heinje, G., Academic Press, 1987; and Sequence Analysis Primer, Gribskov, M. and Devereux, J., eds., M Stockton Press, New York, 1991). While there are many methods for measuring identity between two polynucleotide or polypeptide sequences, the term "identity" is well known to those of skill in the art (Carillo, H. & Lipton, D., SIAM J Applied Math 48:1073 (1988)).

[0071] Whether any particular nucleic acid molecule is at least 50%, 60%, 70%, 75%, 80%, 85%, 90%, 95%, 96%, 97%, 98% or 99% identical to a particular nucleic acid sequence, or portion thereof, encoding, for example, a MIP, may be determined conventionally using known computer programs such as DNAsis software (Hitachi Software, San Bruno, Calif.) for initial sequence alignment, followed by ESEE version 3.0 DNA / protein sequence software for multiple sequence alignments.

[0072] Whether an amino acid sequence is at least 50%, 60%, 70%, 75%, 80%, 85%, 90%, 95%, 96%, 97%, 98% or 99% identical to a MIP or a portion thereof, for example in the form of a protein, can be determined conventionally using known computer programs such as the BESTFIT program (Wisconsin Sequence Analysis Package, Version 8 for Unix, Genetics Computer Group, University Research Park, 575 Science Drive, Madison, Wis. 53711). BESTFIT uses the local homology algorithm of Smith and Waterman, Advances in Applied Mathematics 2:482-489 (1981), to find the best segment of homology between two sequences. Many MIPs have been well studied and have one, but many have multiple conserved regions. As the skilled artisan will appreciate, changes in the nucleic acid / protein sequence are preferably, but not exclusively, outside such conserved regions of the individual MIP.

[0073] When using DNAsis, ESEE, BESTFIT or any other sequence alignment program to determine whether a particular sequence is, for example, 95% identical to a reference sequence according to the invention, parameters are set such that the percentage of identity is calculated over the entire length of the reference nucleic acid or amino acid sequence and allow gaps in homology of up to 5% of the total number of nucleotides in the reference sequence.

[0074] Influence of selected MIPs on transgene expression As discussed above, Foxa1 generally increases cell viability, viable cell density, and the production of both easy-to-express and difficult-to-express therapeutic proteins when overexpressed. This effect can be assigned to Foxa1-mediated Tagap upregulation. Indeed, when overexpressed, Tagap can transiently increase viable cell density, and increased titers of both easy-to-express and difficult-to-express therapeutic proteins have been observed.

[0075] Tagap is a signaling protein member of the Rho GTPase-activating protein (GAP) family. In thymocytes, it has been shown to regulate the abundance of active RhoA, thus promoting cytoskeletal rearrangements and the release of β1-integrin-mediated adhesions to allow thymocyte migration from the cortex to the medulla (Duke-Cohan et al., 2018). Furthermore, Tagap and cardiac actin alpha (ACTC1) were found to be upregulated in vitamin B5-selected cells that produce therapeutic proteins at very high levels, and Tagap overexpression was shown to increase the expression of ACTC1, which in turn increases the production of various therapeutic proteins. Thus, in CHO suspension cells, TAGAP may function as an intermediary for intracellular cytoskeletal signals to cell surface integrins, thus improving cell proliferation, viability, and adaptation to suspension.

[0076] Interestingly, spherical integrin clustering as well as increased actin content and the formation of spherical actin sheaths were observed in suspension-adapted CHO cells (Walther, Whitfield, & James, 2016). Elevated expression of Tagap may therefore contribute to improving actin-mediated cell adaptation in a suspension environment. Tagap upregulation may also contribute to improving therapeutic protein secretion, as the actin cytoskeleton is involved in the control of the secretory pathway (Stamnes, 2002). Notably, another candidate gene upregulated in Tras high-producing clones, Arhgap42 (Rho GTPase-activating protein 42), is a Rho GTPase-activating protein that has been shown to localize to actin stress fibers and focal adhesions and promote cell motility (Hu et al., 2018; Luo et al., 2017). Furthermore, Arhgap42 is also a Foxa1 target gene. Thus, Arhgap42 expression is also within the scope of the present invention, preferably for increasing titer and viable cell density.

[0077] As mentioned above, the ACTC1 (actin alpha cardiac muscle 1) gene is known to be involved in cardiac muscle alpha actin synthesis. This also acts to improve the expression and secretion of ETE and DTE therapeutic proteins by recombinant eukaryotic cells such as CHO cells. It was observed that increased ACTC1 levels were accompanied by a decrease in overall actin polymerization, suggesting that cytoskeleton organization controls or influences the expression or secretion of therapeutic proteins. To support this observation, it was shown that a CHO cell pool with naturally reduced actin polymerization levels secreted significantly higher levels of recombinant protein. As the increased release of therapeutic proteins by actin-overexpressing cells was not accompanied by an increase in IgG light and heavy chain mRNA (data not shown), it was concluded that this actin effect was post-transcriptional.

[0078] The data confirm that ACTC1 overexpression accumulates excess actin monomers, which may disturb the intracellular balance with G / F-actin, thereby causing the observed decrease in F-actin polymerized morphology. A correlation between actin dynamics and gene expression has already been proposed in mammalian cells. For example, it was found that treatment of primary mouse cells with chemical agents that induce F-actin disruption induced a widespread inhibition of translation and protein synthesis and that this activated the cellular stress response (Silva, Sattlegger, & Castilho, 2016). Here, it could be shown that the decrease in actin polymerization, either spontaneous or induced by ACTC1 overexpression, was rather mediated by an increase in recombinant protein expression by CHO cells and did not impair cell division or viability. It could be speculated that F-actin depolymerization may induce a turnover of actin assemblies that may facilitate vesicle and protein transport. For example, colifin is an actin-depolymerizing protein that induces actin reorganization, thereby promoting exocytosis of small molecules and vesicle transport (Birkenfeld, Kartmann, Betz, & Roth, 2001). Similarly, CHO suspension cells selected for lower levels of polymerized actin may exhibit higher cytoskeletal reorganization, which in turn may improve recombinant protein secretion. However, another favorable effect of ACTC1 overexpression is to reduce the accumulation of the cytotoxic lactate by-product of early glycolysis. An interrelationship between lactate accumulation and the cytoskeleton is suggested by a report showing that perturbation of the cytoskeleton can inhibit lactate transporters and import by oocytes (Tosco, Faelli, Gastaldi, Paulmichl, & Orsenigo, 2008), suggesting that CHO cell actin depolymerization may prevent the accumulation of toxic intracellular lactate concentrations.

[0079] Overall, several mechanisms may explain the positive effect of actin overexpression on protein production by eukaryotic cells such as CHO cells, which may relate to both energy production by basal metabolism and glycolysis of these cells, and by potential activation of protein secretion. In summary, it may be shown that both ACTC1 overexpression and / or assays for spontaneous changes in F-actin polymerization using SiR-actin staining and cell sorting may be used to facilitate the isolation of high-expressing CHO cells from stable cell pools.

[0080] It may be shown that modulation of cytoskeletal proteins and cytoskeletal organization can be used to enhance protein production for biotechnological purposes.

[0081] As mentioned above, Erp27 is a protein that selectively binds unfolded proteins and interacts with the disulfide isomerase Erp57 in the ER (Alanen et al., 2006; Kober et al., 2013). Also as noted above, Foxa1 is a pioneer transcription factor involved in the development of various organs (Zaret & Carroll, 2011). Expression of specific combinations of these MIPs can be shown to cause increased cell density and viability in fed-batch cultures, higher production of easy-to-express and difficult-to-express therapeutic proteins, and reduced reactive oxygen species, providing a new avenue for highly efficient therapeutic protein production. Table 2 shows genes upregulated in Tras high-producing clones (HPCs) relative to parental CHO cells and relative to Tras polyclonal cells (PCs) (Figures 11-15).

[0082] The ER-localized protein Erp27 has been identified as involved in the high-level production of both easy-to-express and difficult-to-express therapeutic proteins. Despite the fact that Erp27 is a redox-inactive member of the PDI family, it likely contributes to protein folding, as it selectively binds unfolded proteins and interacts with the disulfide isomerase Erp57 (Alanen et al., 2006; Kober et al., 2013). Significantly difficult-to-express proteins are prone to misfolding, and the unfolded protein response (UPR) has been shown to be activated upon expression of difficult-to-express proteins (reviewed in Hansen et al., 2017). Thus, Erp27 and Erp57 overexpression probably directly contribute to reducing the accumulation of misfolded and difficult-to-express proteins, thereby preventing or delaying UPR-induced apoptosis. This well explains the increased cell viability and viable cell density upon co-overexpression of Erp27 and Erp57 in cells expressing difficult-to-express proteins. While Erp27 and Erp57 have been shown to be upregulated upon ER stress (Bargsted, Hetz, & Matus, 2016; Kober et al., 2013), this upregulation may not be sufficient to handle large amounts of misfolded recombinant proteins. In addition to improving the yield of therapeutic proteins, overexpression of Erp27 and Erp57 may also prevent product quality issues, as antibody quality was found to decrease along with cell viability (Kaneko, Sato, & Aoyagi, 2010). On the other hand, high production of trastuzumab antibody did not trigger a full UPR response (Le Fourn et al., 2014), which is consistent with the finding that Erp27 overexpression, with or without Erp57, did not improve cell viability and had little or no effect on viable cell density in these conditions. Nevertheless, the folding capacity of CHO cells may still represent a bottleneck in these conditions, as shown by the fact that modest overexpression of Erp27 increased trastuzumab titers.

[0083] While protein folding in the ER has been shown to be a limiting step for the production of several therapeutic proteins, conflicting results have been published regarding the impact of PDI and Erp57 overexpression on therapeutic protein production (reviewed in Hansen et al., 2017). Ca3 upregulation was observed in high-producing clones of both easy-to-express and difficult-to-express proteins, as well as in Foxa1-overexpressing cells and, to a lesser extent, in Tagap-overexpressing cells. Notably, Ca3 was shown to inhibit H2O2-induced apoptosis and reduce H2O2-induced ROS activity (Raisanen et al., 1999; Shi et al., 2018). It was also shown to protect cells against hypoxic stress (reviewed in Di Fiore et al., 2018). Importantly, accumulation of ROS was observed during fed-batch culture, indicating that oxidative stress affects antibody yield and galactosylation (Ha, Hansen, Kol, Kildegaard, & Lee, 2018). Furthermore, the addition of antioxidants baicalein or S-sulfocysteine ​​during fed-batch culture improved cell viability and antibody production in fed-batch culture (Ha et al., 2018; Hecklau et al., 2016). Consistently, we found a decrease in ROS accumulation and an increase in cell viability in Foxa1-overexpressing cells during the last days of fed-batch culture. In contrast, while Ca3 overexpression led to an increase in Tras titers, we did not observe any positive effect on cell viability. A possible explanation is that Ca3 was not overexpressed at the appropriate level. It is also possible that Foxa1-mediated increase in cell viability requires the activation of other genes. A possible candidate is CDK15, which was also upregulated in Tras high-producing clones and was shown to protect cells from apoptosis (Park, Kim, Kim, & Chung, 2014), but whether CDK15 is a Foxa1 target gene remains to be examined.

[0084] Finally, Rassf9 upregulation was also observed in easy-to-express and difficult-to-express high-producing clones as well as in Foxa1-overexpressing cells. Rassf9 has been shown to be involved in endosomal recycling and has been proposed to regulate vesicular trafficking through its interaction with complex membrane proteins (Chen, Johnson, & Milgram, 1998). Its overexpression resulted in an increase in therapeutic protein titers only for Tras14, but not for Tras6, raising the possibility that it may be involved in the secretion of therapeutic proteins.

[0085] Overall, it can be observed that upregulation of several CHO cell genes contributes to improving the production yield of various easy-to-express and difficult-to-express therapeutic proteins. Interestingly, some of these CHO genes appear to be upregulated by the Foxa1 transcriptional activator. Thus, the inventors conclude that elevated Foxa1 expression can induce a transcriptional program favorable for high-level therapeutic protein production, and this provides a convenient approach to improve the production of recombinant proteins of interest. The present invention is described below by way of non-limiting examples.

[0086] Working Example MIP candidate selection RNA Seq Overview We deciphered the genetic and metabolic changes that occur in cells during B5 selection. To do so, we performed transcriptome analysis by RNASeq (Figure 1A) comparing unselected cells with B5 and with antibiotics. Genes whose expression was significantly upregulated (at least 1.5-fold increase with P>0.5) between AB and B5 selection were identified and detected in both ETE and DTE recombinant cell lines. We found 31 genes candidate as B5 selection targets (Table 1).

[0087] The expression patterns of these genes can be classified into two categories (Figure 1B). The first category, which included most of the candidate genes, showed reduced gene expression after transfection with recombinant proteins during antibiotic (AB) selection (top graph). However, gene expression was improved in B5-selected recombinant cells. The hypothesis for this expression pattern was that gene transcription was difficult due to competition for the cellular machinery to produce recombinant proteins in high amounts. Instead, B5 selection may improve overall cell fitness and metabolism, which may lead to improved target gene expression.

[0088] For the second expression pattern (Figure 1B, bottom graph), the target gene was induced in both AB and B5 selected cells, with higher expression in B5 selected cells, when compared to non-transfected cells. In this case, the target gene may be induced in response to the recombinant protein and may be involved in either different steps of recombinant protein production and secretion from the cells, or may be part of the detoxification process triggered by the inflammatory response.

[0089] B5 selection induced changes mainly in metabolic genes, such as enzymes and transporters (9 / 31 target genes). Because B5 selection was based on changes in primary metabolism due to B5 deficiency, a significant number of target genes were expected to be part of diverse cellular metabolism.

[0090] Surprisingly, five of these genes were involved in lipid metabolism, and by looking deeper into the literature, the inventors found that three of them, Hmgcs2, Acot1 and Cyp4a14, were targets of a common transcription factor, PPAR (Rakhshandehroo et al., 2010).

[0091] Hydroxymethylglutaryl-CoA synthase 2 (Hmgcs2) encodes a mitochondrial protein that catalyzes the first reaction of ketogenesis by condensing acetyl-CoA with acetoacetyl-CoA to form HMG-CoA, which determines the metabolic fate of fatty acids in the liver of starved animals ( Vila-Brau et al., 2011 ).

[0092] Acot1 encodes an acyl-CoA thioesterase that catalyzes the hydrolysis of acyl-CoA to free fatty acids and coenzyme A (CoASH), which is involved in long-chain fatty acid metabolism.

[0093] Cyp4a14, a cytochrome P450, has been shown to be involved in liver injury, inflammation, and fibrosis in mice (Zhang, 2017).

[0094] Peroxisome proliferator-activated receptors (PPARs) are ligand-activated transcription factors that belong to the nuclear hormone receptor superfamily and play an important role in nutrient homeostasis (Kersten et al., 2000). Three distinct PPAR subtypes are known: PPARα, RRARβ / δ and PPARγ. All PPARs form heterodimers with the nuclear receptor RXR and subsequently bind to PPAR response element (PPRE) sequences located in the promoters of their target genes. Transcriptional activation by PPARs depends on many different steps, including ligand binding to PPARs, binding of PPARs to target genes, removal of corepressors and recruitment of coactivators, remodeling of chromatin structure and finally promotion of gene transcription (Michalik et al., 2006). PPARs regulate gene expression that functions in lipid and carbohydrate metabolism, vascular biology, tissue repair, cell proliferation and differentiation and sex differences (Wahli et al., 2012). Therefore, studies focused on PPARs and PPAR targets to examine whether there is a link between B5 selection and PPAR activation leading to PPAR target activation.

[0095] Another target gene that was noted was the ACTC1 gene, which is involved in actin synthesis. Cytoskeleton organization is important for many cellular components such as protein synthesis and secretion (Hudder et al., 2003) or metabolic network stability (Aon and Cortassa, 2002). Thus, increased recombinant protein production may correlate with improved cytoskeleton together with improved secretory pathways (ER chaperones) and metabolic machinery (Dinnis et al., 2006). Recent studies have shown that suspension CHO cells have evolved from adherent cells by reorganizing their cytoskeleton to strengthen their subcortical actin sheath (Walther, 2016). Thus, actin adjustment may have an impact on suspension cell fitness and recombinant protein production.

[0096] Identification of genes associated with high productivity for therapeutic proteins Genes showing expression changes associated with high-level therapeutic protein production by CHO cells were identified and tested as new cell engineering candidates to improve therapeutic protein production. For this purpose, transcriptome analysis was performed to compare three different types of cells: CHO cell clones producing the easily expressed trastuzumab (Tras) antibody at high levels while maintaining high cell density and showing an average specific productivity of 19.3 pg of Tras secreted per cell and per day (pg / cell / day) and an average maximum viable cell density (VCD) of 43.3 million cells / mL. These cell lines were compared with a Tras polyclonal cell population obtained after antibiotic selection of cells stably expressing the transgene (specific productivity of 7.4 pg / cell / day, maximum VCD of 36.3 million cells / mL) and with the non-transfected parental CHO cells (Figure 1c).

[0097] Candidate genes were selected according to two criteria: an initial 113 mRNAs were selected that were significantly upregulated in Tras high-producing clones when compared to parental CHO cells (Fig. 1c). 1774 mRNAs were also selected that were upregulated in high-producing clones when compared to the polyclonal Tras-expressing cell pool. 51 mRNAs were found to match both criteria and correspond to 32 genes whose upregulated expression may be associated with Tras high productivity (Fig. 1c, Table 2). The changes in the mRNA levels of the candidate genes were further confirmed in different samples using RT-qPCR (Fig. 16, data not shown). Surprisingly, ontology analysis showed that the candidate protein-coding genes were largely related to signal transduction and cell adhesion (Table 2, Fig. 1d). We also identified genes involved in protein folding (Erp27), cell survival (Ca3, Cdk15, Vegfd), cell proliferation (Clstn3), vesicular trafficking (Rassf9, Clstn3) and cytoskeleton organization (Mybpc2, Tagap, Arhgap42), cellular functions previously proposed to affect therapeutic protein production (Table 2, Fig. 1d, Baek et al., 2015; Fischer et al., 2015; Hansen et al., 2017). Interestingly, most of these candidate genes were also upregulated in CHO cell clones producing high levels of another easy-to-express antibody, bevacizumab, and a difficult-to-express interferon beta protein, when compared to their expression in parental CHO cells (data not shown). This indicated that candidate gene upregulation was not exclusively associated with cells exhibiting high trastuzumab antibody productivity, and therefore suggested that such candidate genes may be involved in the high-level production of a variety of easy-to-express and difficult-to-express therapeutic proteins.

[0098] An overview of the positive effects of PPAR, ACTC1 and other MIP candidates of various origins on the production of ETE and DTE CHO cell lines is illustrated in Figures 4-10.

[0099] Figure 1 and Table 2 show that: Genes associated with high trastuzumab productivity include genes involved in protein folding, cell survival, vesicle trafficking and cytoskeletal remodeling. · The pioneer transcription factor Foxa1 was upregulated in high trastuzumab producers and could activate transcriptional responses that favor therapeutic protein production. · B5 selection induced changes in lipid metabolism genes. · PPAR transcription factors appear to be regulators of several B5 target lipid genes. Cytoskeletal regulation and morphology through actin production can contribute to cell fitness and recombinant protein production.

[0100] Comments Figure 1 and Table 1: Transcriptome analysis was performed to identify genes associated with high trastuzumab productivity. In this analysis, genes upregulated in trastuzumab high-producing clones compared to CHO-M WT cells were selected and compared to cells polyclonal for trastuzumab production (Figure 1C). Thirty-two genes associated with high productivity were identified (candidate genes, Table 1). Importantly, the expression of these genes may be a cause or consequence of high trastuzumab productivity. Further focus was placed on candidate genes that could potentially improve therapeutic protein productivity based on their functions (Figure 1D).

[0101] An overview of the impact of these different MIPs (Erp27, Erp57, Ca3, CDK15, Rassf9, Clstn3, Tagap and Foxa1) on trastuzumab (ETE) and infliximab (DTE) production is provided in Figures 2 and 3.

[0102] MIP candidate identified in a clone that produces a high level of therapeutic protein Overexpression of the candidate genes increases trastuzumab production (Figure 2): Figures 2A-E show the effect of candidate MIPs on the production of the easy to express (ETE) antibody, trastuzumab. To this end, two trastuzumab medium producers that maintained fast cell division were isolated from the trastuzumab polyclonal population used for transcriptome analysis. These clones were stably transfected with plasmids for MIP expression (Tagap, Rassf9, Erp27, Erp57, Erp27+Erp57, Clstn3, CDK15, Ca3 and Foxa1). Trastuzumab production was evaluated in these stable populations at various times of fed-batch culture. Overexpression of SRP14 was used as a positive control and cells expressing GFP or transfected with an empty vector were used as negative controls. Overexpression of Rassf9, Foxa1 and Ca3 increased trastuzumab production, while overexpression of Erp57, Clstn3 and CDK15 and simultaneous overexpression of Erp27 and Erp57 did not affect trastuzumab production. Tagap overexpression had variable but sometimes positive effects on trastuzumab production. When strongly overexpressed, Erp27 reduced trastuzumab production, and when slightly overexpressed, it increased trastuzumab production. According to the database, Ca3 and Rassf9 are Foxa1 transcriptional targets. Overexpression of Ca3 and Rassf9 was indeed found in Foxa1 overexpressing cells. These results strongly suggest that Foxa1 overexpression induces the transcription of genes that improve trastuzumab production.

[0103] In summary, we found the following: · Rassf9, Ca3 and Foxa1 overexpression improves trastuzumab production. When strongly overexpressed, Erp27 decreases trastuzumab production, whereas when slightly overexpressed it increases trastuzumab production. Overexpression of Erp57, Clstn3 and CDK15 and simultaneous overexpression of Erp27 and Erp57 do not affect trastuzumab production. · The Foxa1 transcriptional response may generate a favorable environment for trastuzumab production.

[0104] Overexpression of specific candidate MIPs increases production of infliximab, a difficult to express (DTE) antibody (Figure 3): Figures 3A and 3B show the effect of candidate MIPs on the production of the difficult to express (DTE) antibody, infliximab. Infliximab producing clones were stably transfected with plasmids for MIP expression. Infliximab production was evaluated in these stable populations at different times of fed-batch culture. Cells transfected with empty vector were used as negative controls. Expression of Erp27 or Erp57 did not increase infliximab production, while co-expression of Erp27 and Erp57 or expression of Tagap increased infliximab production. Viable cell density was higher for cells overexpressing Tagap and Erp27+Erp57 at days 9 and 11 of fed-batch culture.

[0105] In summary, it was found that overexpression of Tagap and simultaneous overexpression of Erp27 and Erp57 increased the viable cell density on days 6 and 9 of fed-batch culture, improving infliximab production.

[0106] Erp27 is a protein present in the endoplasmic reticulum that binds to unfolded proteins (Kober et al., 2013). Although originally described as a protein disulfide isomerase (PDI), Erp27 lacks any redox activity. Notably, Erp27 contains the noncatalytic b and b' domains of PDI, which lack the CXXC active site required to catalyze dithiol-disulfide exchange (Alanen et al., 2006). It is, however, known to interact with the PDI Erp57, which initiates disulfide bond formation (Alanen et al., 2006). Increased expression of Erp57 was notably found to increase thrombopoietin productivity in CHO cells (Hwang et al., 2003).

[0107] Overexpression of Erp27 alone or together with Erp57 improves therapeutic protein production. As Erp27 has been shown to bind to the disulfide isomerase Erp57 in vitro and in vivo ( Alanen et al., 2006 ), it was hypothesized that the Erp27-Erp57 complex may be involved in therapeutic protein folding and provide a production advantage.

[0108] This hypothesis was evaluated by assessing the effect of Erp27 and Erp57 overexpression on Trastuzumab secretion levels. For this purpose, clones were isolated from the Trastuzumab polyclonal population previously used for transcriptome analysis, and a clone was selected that showed high productivity (1.8-fold higher than that of the polyclonal population) while maintaining a fast cell division rate in fed-batch culture. In particular, Erp27 mRNA levels in this clone were found to be upregulated 3-6-fold when compared to parental CHO cells on day 0 or day 8 of fed-batch culture (Figure 11a). Meanwhile, Erp57 mRNA levels were similar to the CHO parental cells and Tras-producing clones on day 0, while a slight 1.2-fold upregulation in the clone was observed on day 8. The clones were stably transfected with Erp27 and / or Erp57 expression vectors or a GFP expression vector as a control, and the levels of selected Tras were evaluated during the fed-batch culture of the polyclonal population.

[0109] Upon Erp57 overexpression with or without Erp27 coexpression, viable cell density increased on day 6 of fed-batch culture, while cell viability decreased on day 10 (Fig. 17a, b). Overall, Tras titer levels in Erp57-overexpressing cells were similar to control cells (Fig. 11b). Meanwhile, growth and cell viability during fed-batch culture were not affected by Erp27 overexpression (Fig. 17a, b). However, Erp27 overexpression led to a decrease in Tras levels, which was also observed upon Erp57 coexpression (Fig. 11b). It was found that Erp27 overexpression led to a very large increase in Erp27 mRNA levels when compared to Tras-producing clones (Fig. 17c-d), suggesting that such overexpression levels lead to a metabolic imbalance of these protein activities, thus rather reducing Tras expression. The amount of Erp27 expression vector in stably transfected cells was therefore gradually reduced. Indeed, a 14% increase in Tras levels was observed upon reduced overexpression of Erp27 (Figures llc and 17e). Overall, the results indicated that modulating overexpression of Erp27 increased Tras production.

[0110] Since transcriptome analysis showed that Erp27 mRNA expression was also increased in clones expressing the difficult to express interferon beta at high levels (data not shown), we further evaluated what the impact of Erp27 and Erp57 overexpression was on the production of difficult to express therapeutic proteins. Infliximab chimeric immunoglobulin (Infli) and etanercept Fc-fusion were used as two further examples of difficult to express therapeutic proteins. In contrast to the results obtained for Tras, Infli titers were not affected upon Erp27 overexpression, but rather decreased upon Erp57 overexpression in infliximab expressing clones (Fig. 11d and 17f, g). However, simultaneous overexpression of Erp27 and Erp57 resulted in a 61% and 72% increase in infliximab titers compared to GFP-expressing control cells on days 9 and 11 of fed-batch culture, respectively (Fig. 2d). Furthermore, simultaneous overexpression of Erp27 and Erp57 resulted in increased viable cell density and cell viability on day 9 of fed-batch culture (FIGS. 11e and 17h).

[0111] The effect of simultaneous overexpression of Erp27 and Erp57 in etanercept-producing clones was also evaluated. Single subclones co-expressing Erp27 and Erp57 were isolated and their production was evaluated using the ClonePix® cell colony imaging device. Cell colonies exhibiting the broadest etanercept secretion halos were isolated from Erp27 and Erp57 overexpressing or control cell populations, and derived cell clones were evaluated for etanercept production in fed-batch cultures. Viable cell density and cell viability were promoted upon Erp27 and Erp57 overexpression, with a prolonged flattening phase of viable cells and a 37% increase in titer (Figure 11f-h). Taken together, these results support that moderate overexpression of Erp27 increases the production of easy-to-express therapeutic proteins, and that combined overexpression of Erp27 and Erp57 can promote viable cell density, cell viability, and titer of cells producing different difficult-to-express therapeutic proteins.

[0112] Foxa1 overexpression increases trastuzumab production and reduces oxidative stress. Surprisingly, among the 32 genes associated with high trastuzumab production, we found a pioneer transcription factor called Foxa1. Foxa1 can activate transcriptional responses favorable for therapeutic protein production. Foxa1 can bind to repressive heterochromatin structures, where it can drive gene expression independently of other transcription factors (for review, see Zaret & Carroll, 2011). It is involved in the development of different organs, such as the liver, pancreas, lungs and prostate (Friedman & Kaestner, 2006). Therefore, we hypothesized that Foxa1 can activate transcriptional programs favorable for the production of therapeutic proteins, such as Tras.

[0113] Consistently, Foxa1 mRNA expression was elevated in Tras clones compared to parental CFIO cells on days 0 and 8 of the fed-batch culture, with a 1.5- and 2.1-fold upregulation, respectively (Fig. 18a). A 3-fold upregulation was observed in Tras high-producing clones compared to parental CFIO cell controls in the transcriptome analysis, thus suggesting that Foxa1 expression could be further elevated (see Table 2). Tras-producing clones were therefore stably transfected with a Foxa1 expression vector. Stable expression of Foxa1 under the control of the strong CMV / EF1 alpha promoter resulted in elevated cell death during antibiotic-mediated selection (data not shown). However, replacement of this strong promoter with a minimal CMV promoter abrogated this unwanted effect, increasing the final Tras titer by 57% upon Foxa1 overexpression (Fig. 12a), while Foxa1 mRNA was upregulated 40- and 14-fold on days 0 and 8 of fed-batch culture, respectively (Fig. 12d, e). While cell growth in fed-batch cultures was similar when comparing Foxa1 overexpression to control cells up to day 6, Foxa1 overexpressing cells continued to divide up to day 9, reaching an average viable cell density of 31 million cells / mL, while control cells peaked at 19 million cells / mL on day 8 (Figure 12b). Furthermore, viability of Foxa1 overexpressing cells remained above 90% up to day 9, while control cell viability declined from day 7, falling below 75% on day 9 (Figure 12c).

[0114] Ca3, Rassf9 and Tagap are upregulated upon Foxa1 overexpression in Tras-producing clones. Several studies have revealed that productivity can be improved by extending cell survival in fed-batch cultures (for review, see Kim et al., 2012). Among the 32 genes identified, Ca3 and CDK15 (see Figure 2b) promote cell survival. Ca3 acts in protecting cells from oxidative stress (Di Fiore et al., 2018), while CDK15 protects cells from apoptosis (Park et al., 2014). Overexpression of these proteins can therefore extend cell lifespan in fed-batch cultures, thus improving productivity.

[0115] Further focus was placed on two proteins, Rassf9 and Clstn3, found in transport vesicles that may possibly be involved in therapeutic protein secretion (Chen et al., 1998; Rindler et al., 2007).

[0116] Tagap is a signaling protein involved in thymocyte loss of adhesion and cytoskeletal reorganization in thymocytes and T cells (Connelly et al., 2014; Duke-Cohan et al., 2018). Similarly, relative to actin, Tagap overexpression may improve cell adaptation to suspension and trigger cytoskeletal reorganization, thus improving secretion. Notably, Tagap was also overexpressed in B5-selected cells.

[0117] The fact that Foxa1 is a pioneer transcription factor suggested that it could directly increase the transcription of the trastuzumab heavy chain (HC) and light chain (LC) transgenes. However, no significant changes in trastuzumab HC and LC mRNA levels were observed upon Foxa1 overexpression (Figure 18b). To confirm that the Foxa1-mediated increase in trastuzumab titer was the result of transcriptional activation of CHO cell genes that were also upregulated in Tras high-producing clones (Table 2). The Harmonizome® web portal was used to identify potential Foxa1 target genes (Rouillard et al., 2016). Thus, 11 of the 25 protein-coding genes identified as upregulated in Tras high-producing clones were predicted to be Foxa1 target genes, including the Foxa1 gene itself (Table 2). We therefore tested whether these genes were upregulated upon Foxa1 overexpression in trastuzumab-producing clones and found that Ca3 and Rassf9 were highly upregulated upon Foxa1 overexpression on day 8 of fed-batch culture, while the expression of other potential Foxa1 target genes did not change significantly (Figure 12). Furthermore, Erp27 was not upregulated in Foxa1-overexpressing cells, whereas upregulation of the Tagap candidate gene was observed, which was also found to be upregulated in vitamin B5-selected cells producing therapeutic proteins at very high levels. Notably, there was also Rassf9, Ca3 and Tagap mRNA upregulation in Foxa1-overexpressing cells on day 0 of fed-batch culture, suggesting that their upregulation was not a consequence of the high cell proliferation observed on day 8 in Foxa1-overexpressing cells (Figure 12e). As Ca3 has been shown to protect cells against oxidative stress (reviewed in Di Fiore, Monti, Scaloni, De Simone, & Monti, 2018), the levels of intracellular reactive oxygen species (ROS) were assessed using the reactive fluorescent dye carboxy-H2DCFDA. Interestingly, while there was a slight increase in ROS levels in Foxa1-overexpressing cells on day 3, ROS levels were reduced in Foxa1-overexpressing cells on days 6, 8, and 9 (Figure S1f).

[0118] Ca3 and Tagap overexpression increases trastuzumab production. To test whether the increase in Tras titer due to Foxa1 overexpression was the result of Ca3, Rassf9 and / or Tagap upregulation, the three candidate genes were stably overexpressed in Tras-producing clones and the Tras titer obtained from fed-batch cultures was evaluated. Consistently, higher Tras titers were obtained upon Tagap overexpression in Tras-producing clones, while no effect was detected from Ca3 or Rassf9 overexpression (Fig. 13a). An increase in viable cell density was observed on days 6 and 8 of culture upon Tagap overexpression, with a maximum viable cell density of 31 million cells / mL on day 8 (Fig. 13b). However, cell viability was strongly reduced starting from day 9 (Fig. 13c). The increase in Tras production upon Tagap overexpression was similar to the levels obtained upon Foxa1 overexpression, with a titer of 1331 μg / mL, despite the decreased cell viability observed from Tagap overexpression during extended fed-batch culture (Figures 12a-c and 13a-c). A slight increase in Tras HC and LC expression (1.6 and 1.3, respectively) was also observed upon Tagap overexpression (Figure 19a).

[0119] Interestingly, a 10-fold increase in Ca3 expression was also observed upon Tagap overexpression (Fig. 13d). To assess whether the lack of effect of Ca3 overexpression alone could be due to unfavourable expression levels (Fig. 13a-c), the amount of expression vector used to establish stable cell lines was titrated. A slight increase in trastuzumab titer was obtained upon higher Ca3 overexpression levels, whereas viable cell density and viability were not affected (Fig. 13e and Fig. 19b and data not shown). In conclusion, Tagap overexpression recapitulated the Foxa1-mediated increase in trastuzumab titer, and while it could temporarily improve viable cell density, it rather reduced cell viability at the end of fed-batch culture. Thus, overall, it was concluded that the positive effect of Foxa1 on cell viability and cell growth during culture and on protein titers could be due to its influence on the expression of several target genes.

[0120] Foxa1 also improves production of difficult-to-express therapeutic proteins. The effect of Foxa1 overexpression on the secretion of the difficult-to-express infliximab was further evaluated. Impressively, infliximab production nearly doubled upon Foxa1 overexpression, with an average titer of 378 μg / mL observed when Foxa1 mRNA levels were elevated 8.2-fold (Fig. 14a, e). Notably, Foxa1 overexpressing cells showed a marked increase in viable cell density starting from day 6 to day 9, reaching a maximum viable cell density of 12.2 million cells / mL on day 7, while control cells only reached a viable cell density of 8.6 million cells / mL (Fig. 14b). Consistently, we observed that cell viability remained significantly higher in Foxa1 expressing cells, preventing the destruction of cell viability observed from day 7 in control cells (Fig. 14c). This was accompanied by a reduction in ROS accumulation on days 7 and 8 in Foxa1 overexpressing cells (Fig. 14d). Similar to what was observed upon Foxa1 overexpression in Tras-producing clones, Ca3, Rassf9 and Tagap mRNA levels were also upregulated upon Foxa1 overexpression (Fig. 14e). Consistently, we obtained a 45% increase in infliximab production upon Tagap overexpression, resulting in an average titer of 283 μg / mL (Fig. 15a). Thus, while Tagap overexpression could recapitulate the Foxa1-mediated Tras titer increase, it only partially mimicked the Foxa1-induced infliximab titer increase. As observed for Tras-producing clones, Tagap overexpression led to a sharp increase in viable cell density for infliximab clones, with a maximum viable cell density of 12 million cells / mL at day 6 (Fig. 15b). However, in contrast to Foxa1-overexpressing cells, cell viability remained almost unchanged upon Tagap overexpression (Fig. 15c). Notably, Tagap overexpression in infliximab-producing clones also resulted in upregulation of Ca3 mRNA levels (Fig. 15d). Collectively, these results demonstrated that Foxa1 overexpression can be used to increase the production levels of difficult-to-express as well as easy-to-express therapeutic proteins in CHO cells, and that this effect may be due in part to Foxa1-mediated increased Tagap expression levels.

[0121] MIP candidate (PPAR) found in B5 selection Figures 5A and 5B show the significant increase in DsRed (Discosoma sp. Red) activity observed between AB and B5 selected cells with or without the PPRE reporter sequence, indicating that DsRed expression is induced independently of PPAR activation, which may be explained by the overall improved fitness of B5 over AB selected cells.

[0122] However, when mPPARα was added exogenously, DsRed activity was significantly higher in B5-selected cells only when it was under the control of the PPRE reporter. This result indicates that B5 selection generated stable cells that constitutively produced an unknown PPAR agonist, possibly during B5 selection, which could be sensed by the cells as starvation stress. Thus, exogenous PPARα was activated to a greater extent in B5-selected cells compared to AB-selected cells.

[0123] summary: · An unidentified PPAR agonist accumulated during B5 starvation selection. Better fitness in B5-selected cells results in better overall gene expression compared to antibiotic-selected cells. · Activation of exogenous PPARα results in higher PPAR target gene expression in B5-selected cells compared to antibiotic-selected cells.

[0124] Figures 6A and 6B show the activity of bezafibrate (2-[4-[2-(4-chlorobenzamido)ethyl]phenoxy]-2-methylpropanoic acid), which has been reported to be a general PPAR pan-agonist (Wilson et al., 2000; Inoue et al., 2002).

[0125] It is already used in the clinic as an antihyperlipidemic drug. Bezafibrate addition to ETE after 3 days of fed-batch culture induces the PPAR target genes HmgCs2 and Acot1 found in the RNA-Seq screen, as well as the known PPAR targets DBI1, Ascl1 (Rakhshandehroo et al., 2010) and RXR nuclear receptor (Figure 6A). Cyp4a14 was not induced upon bezafibrate addition, which may mean that other agonists or other regulation through PPARs may control the expression of this gene. Interestingly, the B5 target Slc22a14 was activated in response to bezafibrate. The Slc22a14 gene has been shown to be involved in mouse male fertility (Maruyama, 2016), but no function associated with PPAR response has been described.

[0126] Addition of bezafibrate at day 3 of fed-batch culture significantly improved cell survival when subjected to starvation stress during the fed-batch process (data not shown), whereas no improvement in IgG production was observed under normal fed-batch nutritional conditions (see M&M for fed-batch culture). Day 3 of fed-batch culture corresponds to the exponential phase of cell division. Addition of bezafibrate earlier (day 1) during the fed-batch process was shown to be beneficial for recombinant protein at the end of the fed-batch culture (Figure 6B).

[0127] Bezafibrate was also tested in DTE cells. However, despite the induction of the same target genes, cell production and fitness were not improved. Therefore, it appears that PPAR activation and target gene induction through bezafibrate is not sufficient to overcome the bottleneck of cells synthesizing difficult-to-express proteins.

[0128] Because bezafibrate has a strong and broad effect on all PPAR activation and may alter cell division and metabolism at high concentrations, increasing the amount of bezafibrate in both ETE and DTE cells did not show any beneficial effect on both cell division, viability, and recombinant protein production (data not shown).

[0129] In summary, we found the following (see Figure 6): · PPAR targets identified by B5 selection can be chemically induced in CHO cells. · The Slc22a14 transporter, highlighted as a B5 target, is shown to be a novel PPAR target. This induction results in better IgG production in ETE cells. Recombinant cells expressing the DTE protein are not affected by bezafibrate induction.

[0130] When grown in complete non-stress medium, PPARα overexpression (e.g., PPARα_OE) did not show any difference in PPAR target gene expression and IgG production compared to wild-type and empty vector cells. However, when bezafibrate was added, exogenous PPARα present in PPARα_OE was activated and subsequently induced the transcription of PPAR-target genes as well as RXR nuclear factor and IgG light and heavy chains (Figure 7A). This increase resulted in higher IgG productivity of PPARα_OE cells (Figure 7B).

[0131] In summary, the following was found (Figures 7A and B): Activation of exogenous PPARs can generate DTE cells with improved cellular fitness, which leads to enhanced DTE therapeutic protein production.

[0132] In summary, the following was found (Figure 8A-D): · Lactate is reduced in B5-selected cells. · PPAR overexpression leads to reduced lactate content in CHO cells.

[0133] MIP candidate (actin) found by B5 selection Figure 9 already shows that overexpression of actin gene generated ETE cells with improved therapeutic protein production. Fc fusion expressing clones were retransfected with transposable ACTC1 expression vector. The specific productivity of the resulting cell pools was then evaluated through their subculture in batch conditions every 3 or 4 days. The results were expressed as fold change in PCD relative to the Fc-fusion-control cell PCD value. The results suggest that actin overexpression in suspension CHO cells may improve therapeutic protein production and secretion by modulating cytoskeleton organization and polymerization.

[0134] In further experiments, CHO cells were co-transfected with expression vectors encoding the "easy to express" (ETE) trastuzumab or "difficult to express" (DTE) infliximab or etanercept (Enbrel®) therapeutic proteins together with the vitamin B5 transporter SLC5A6 or together with an antibiotic resistance gene as a control. The cells were then selected for their suitability to survive in B5-deficient medium or for antibiotic resistance, respectively, and differentially expressed cellular genes were identified by RNA sequencing. After antibiotic selection, the expression of both ACTC1 and TAGAP was lower than in non-transfected cells, whereas they increased after B5 selection (Figures 20a and 20b). The increase in SLC5A6 expression and TAGAP expression after vitamin B5 starvation was verified using four independent trastuzumab-expressing CHO cell lines isolated using either antibiotic or B5 selection (Figure 20c).

[0135] Gene induction after B5 selection could be caused by overexpression of SLC5A6 itself, or by a combination of both effects, since SLC5A6 mediates higher vitamin B5 uptake into cells (Figure 20d) due to B5 starvation occurring during the selection process (Pourcel et al., 2019), as seen in previous studies. B5 is an essential cofactor for acetyl-CoA, a key factor in central and energy metabolism, which may be related to cytoskeleton regulation. To distinguish between these possibilities, cell lines overexpressing the SLC5A6 transporter were generated without B5 depletion, which showed that elevated SLC5A6 expression was sufficient to significantly upregulate the ACTC1 gene, while a non-significant increase in TAGAP expression was observed (Figure 20e). Thus, the B5 selection process could activate ACTC1 gene expression by increasing B5 intracellular import mediated by SLC5A6 overexpression, while a significant increase in TAGAP expression required a combination of both SLC5A6 overexpression and B5 starvation. It was also observed that TAGAP overexpression increased ACTC1 mRNA and protein accumulation (FIG. 21), suggesting that the increased ACTC1 expression resulting from the B5 selection process may be due in part to upregulation of TAGAP.

[0136] The effect of ACTC1 overexpression on recombinant protein expression was evaluated in antibiotic-selected cell clones expressing several DTE proteins, such as etanercept (Enbrel®) Fc-fusion or bevacizumab or infliximab IgG1, as well as in clones expressing ETE trastuzumab immunoglobulin. These cell clones were retransfected with the ACTC1 coding sequence together with another antibiotic selection gene, followed by selection of antibiotic-resistant cells overexpressing ACTC1 (Figure 22a-c). The specific productivity of the resulting cell pools was then evaluated after 3-4 days in batch culture conditions, suggesting a positive effect of ACTC1 high-level expression on the production of DTE proteins by CHO cells (Figure 23a-c). Further analysis in the infliximab-producing ACTC1-overexpressing cell pool showed a significant increase in IgG titers after 10 days of fed-batch culture (Figure 23d).

[0137] Next, individual clones overexpressing ACTC1 were analyzed. To do so, trastuzumab-producing clones were retransfected with ACTC1 or empty expression vector, and single colonies were picked using a Clonepix® instrument. Eight clones transfected with empty vector and 24 ACTC1-expressing clones were examined for ACTC1 transcript accumulation, among which four control clones and four ACTC1 high-expressing clones were randomly picked for further analysis (Figure 24a). ACTC1 protein overexpression was examined by Western blot (Figures 25a and 24b). Among these four ACTC1 overexpressing clones, three showed maximum IgG titers after 13 days of fed-batch culture when compared with the empty vector clone (Figures 25b and 24c).

[0138] To determine whether the elevated therapeutic protein secretion induced by ACTC1 overexpression could be due to changes in cellular metabolism, we measured primary metabolic markers by mass spectrometry of ACTC1-overexpressing cell pools. In particular, we evaluated the accumulation of lactate, a toxic by-product of the early steps of glycolysis that is well documented as a bottleneck for therapeutic protein production (Lao & Toth, 1997). This revealed a strong reduction in lactate accumulation by ACTC1-overexpressing cells after 3 days in batch culture when compared to control cells (Figure 2e). Overall, we therefore concluded that ACTC1 gene overexpression significantly improved the secretion of various therapeutic proteins, and that this effect could be related to a reduction in the accumulation of a toxic lactate metabolic by-product.

[0139] Significance of actin polymerization levels in recombinant protein secretion We next assessed whether actin polymerization status could be affected by ACTC1 overexpression. To do so, we utilized SiR-actin staining, which specifically binds to F-actin (Lukinavicius et al., 2014), resulting in a fluorescence level of stained cells proportional to actin polymerization. Comparison of SiR-actin-staining of ACTC1 and trastuzumab expressing clones to control clones revealed higher fluorescence in control clones than in ACTC1 overexpressing clones, indicating that actin polymerization levels were significantly reduced by ACTC1 overexpression (Figures 26a, b and 27).

[0140] To further evaluate whether actin polymerization can affect recombinant protein expression, two independent CHO cell polyclonal populations expressing trastuzumab protein but not subjected to ACTC1 vector gene transfection were stained with SiR-actin. The stained cells were then sorted in three independent cell batches according to their low, medium or high fluorescence levels, resulting in six cell pools for each fluorescence level (Fig. 28a and 29). The IgG secretion levels and IgG specific productivity of cells showing low, medium and high levels of polymerized actin were then evaluated (Fig. 28b, c). High SiR-actin stained cells showed significantly lower IgG expression levels than cells showing low SiR-actin, thus supporting the conclusion that cells with lower actin polymerization levels mediate higher recombinant protein secretion even without ACTC1 overexpression.

[0141] Effect of individual or combined expression of MIPs on the secretion of different therapeutic protein-expressing CHO clones Comment Figure 10: Bevacizumab-expressing (Figure 10A), fc-fusion-expressing (Figure 10B) and fab-enzyme-fusion-expressing (Figure 10C) clones were retransfected with various individual transposable CFLAR-, GCLM-, ACTC1-expressing vectors or combinations thereof. The specific productivity of the resulting cell pools was then assessed through their subculture in adjusted batches every 3-4 days. Results were expressed as % of their individual bevacizumab or Fc-fusion control cell PCD values ​​(pg-1.cell-1.day-1).

[0142] Summary Figure 10: ·Therapeutic protein secretion by CHO cells was increased after gene transfection with vectors expressing MIPs, including CFLAR, GCLM, and ACTC1 expression vectors. [Table 1] TIFF0007606463000002.tif222162TIFF0007606463000003.tif221162TIFF000 7606463000004.tif221162TIFF0007606463000005.tif219162TIFF00076064630 00006.tif222162TIFF0007606463000007.tif228162TIFF0007606463000008.t if214162TIFF0007606463000009.tif221162TIFF0007606463000010.tif189162 [Table 2] TIFF0007606463000012.tif221162TIFF0007606463000013.tif222162TIFF0007606463000014.tif42162 1 Genes upregulated in Tras high producing cell clones compared to parental CHO cells and compared to Tras polyclonal cells were selected according to the following criteria: log2 fold change >0.5 and p-value <0.05. 2Genes listed as Foxa1 target genes according to ChIP-seq datasets (ENCODE Transcription Factor Targets dataset) and low- or high-throughput transcription factor functional studies (TRANSFAC Curated Transcription Factor Targets Dataset), obtained using the Harmonizome web portal ( Rouillard et al., 2016 ). [Table 3] TIFF0007606463000016.tif223162TIFF0007606463000017.tif222162TIFF0007606463000018.tif218162TIFF0007606463000019.tif10162 [Table 4]

[0143] Materials and Methods MIP candidate selection and exploration Candidate gene sequences and DNA vector constructs Genomic and cDNA sequences of RNAseq MIP candidates were determined after alignment of homologous genes in mouse using NCBI BLAST software. Transcript sequences and corresponding gene accumulation were determined using the SELEXIS CHO-M gene expression database.

[0144] CHO-M (SURE CHO-M cell line™ (SELEXIS Inc., San Francisco, USA)), cDNA libraries were amplified using the GoScript Reverse Transcription System (Promega) for 10 min. 6 The fragments were amplified by reverse transcription (Nucleo-Spin™ RNA kit; Macherey-Nagel) from 1 μg total RNA isolated from CHO-M cells.

[0145] The MIP coding sequence (CDS) was cloned into the pBSK_ITR_BT+_EGFP_X29_ITR vector (SELEXIS Inc., San Francisco, USA) by excising the green fluorescent protein (GFP) gene and replacing it with the MIP CDS.

[0146] The vector was constructed as follows: the CDS was amplified from the CHO-M cDNA library by PCR (PHUSION High-Fidelity DNA Polymerase; Finnzymes, THERMO FISHER SCIENTIFIC) from the ATG to the termination using primers with restriction sites. Then, the cDNA product and the pBSK_ITR_BT+_EGFP_X29_ITR vector were double digested with the corresponding restriction enzymes. Finally, the cDNA was ligated into the pBSK_JTR_BT vector, in which the GFP sequence was excised after digestion with the same restriction enzymes.

[0147] The pBSK_ITR_BT+_EGFP_X29_ITR vector contains an expression cassette consisting of the CMV / EF1 alpha promoter and BGH polyadenylation signal followed by hMAR X-29. The expression cassette is flanked by inverted end sequences of the piggyBac transposon.

[0148] GFP protein was expressed using a eukaryotic expression cassette consisting of the human cytomegalovirus (CMV) enhancer upstream of the coding sequence and the human glyceraldehyde 3-phosphate dehydrogenase (GAPDH) promoter followed by the simian virus 40 (SV40) polyadenylation signal, the human gastrin terminator and the SV40 enhancer (Le Fourn et al., 2013). The pSG5_PPARα vector was obtained from Issemann and Green, 1990.

[0149] The blasticidin vector (pBlast) contains the blasticidin resistance gene under the control of the SV40 promoter derived from the pRc / RSV plasmid (INVITROGEN / LIFE TECHNOLOGIES).

[0150] RNASeq analysis The cells used for RNASeq analysis were as follows: -CHO-M WT cells - Polyclonal cell population expressing etanercept (ENBREL) Fc-fusion (difficult to express), selected with puromycin and B5 or with puromycin alone. - Polyclonal cell populations expressing trastuzumab IgG (easy to express), selected with puromycin and B5 or with puromycin alone. - Clones expressing trastuzumab IgG (easy to express), selected with puromycin. -Clones expressing bevacizumab IgG (easy to express), selected with puromycin. -Clones expressing interferon beta (difficult to express), selected with puromycin.

[0151] The cells were grown in spin tubes for 4 days without antibiotic selection. Total RNA was isolated from the cells using the NucleoSpin RNA kit (Macherey-Nagel). RNA quality was assessed using a Fragment Analyzer (Advanced Analytical). RNA-seq library preparation was achieved using 0.5 μg to 1 μg of total reversed cDNA using Illumina TruSeq® stranded mRNA-seq reagents (ILLUMINA). Sequencing of the RNA-seq library 100 nt paired ends was performed on an Illumina HiSeq 2500®. Read data were mapped to the CHO-K1 transcriptome (RefSeq, 2014).

[0152] Cell culture, stable transformation and stable polyclonal line analysis Suspension Chinese Hamster Ovary cells (CHO-M) were maintained in suspension culture in SFM4CHO Hyclone serum-free medium (SFM, THERMO SCIENTIFIC) supplemented with L-glutamine (PAA, Austria) and HT supplement (GIBCO, INVITROGEN LIFE SCIENCES) at 37°C and 5% CO2 in humidified air. The other cell culture medium used for these experiments is Deficient BalanCD CHO-M Growth A (B-CDmin; Irvine Scientific) supplemented with vitamin B1 (thiamine hydrochloride; SIGMA ALDRICH), vitamin B5 (calcium DL-pantothenate; TCI) and vitamin H (biotin, SIGMA ALDRICH).

[0153] CHO-M cells were transfected with pBSK-MIP, pBlast and pCS2-U5-PBU3 IgG1-Hc or IgG1-Lc expression vectors by electroporation (NEON DEVICES, INVITROGEN) according to the manufacturer's recommendations. Stable cell line production was achieved using SFM4CHO medium supplemented with 7.5 μg / mL blasticidin for 3 weeks.

[0154] GFP and IgG1 producing cell polyclonal lines expressing GFP or IgG were selected for further experiments as follows: for blasticidin selection, cells were seeded in SFM medium supplemented with 10 mg / mL blasticidin for 2 weeks, then transferred to wells containing SFM medium for 5 days, and then transferred to 50 mL spin tubes containing SFM medium.

[0155] For double selection of cells with puromycin and then B5, polyclonal stable cell lines were first selected with puromycin, then cells were seeded at 20,000 cells / mL in 24-well plates in B5 selection medium for 7 days (B-CD complete medium was used as a negative control), then transferred to SFM complete medium wells for 7 days, and then seeded into pin tubes containing SFM medium.

[0156] The percentage of fluorescent cells and fluorescence density of GFP-positive cells were determined by flow cytometry analysis using a CyAn ADP flow cytometer (BECKMAN COULTER). Immunoglobulin concentrations in cell culture supernatants were measured by sandwich ELISA. GFP, IgG1Lc, IgG1Hc and MIP transcript accumulation were confirmed by RT-quantitative PCR assays prior to analysis.

[0157] Surface IgG presentation was assessed by FACS analysis using flow cytometry (Beckman Coulter™). Stable clones expressing IgG were obtained by cell sorting on a FACS Aria III (BD), expanded and analyzed for IgG production levels (sandwich ELISA).

[0158] Transient assays for measuring peroxisome proliferator-activated receptor response elements (PPRE) and PPAR activation Transient transfection assays were performed as follows: CHO cells were transfected with PPRE-TK-DsRed (provided by Michalik lab., University of Lausanne) or TK-DsRed (PPRE sequence was excised from previous vector) without or with pSG5_PPARα vector. pE-BFP2-Nuc(2xNLS) was used as an internal transfection control. It contains eBFP2 (enhanced blue fluorescent protein 2) coding sequence under the control of a minimal CMV promoter and the nuclear localization sequence NLS. Cells were observed by flow cytometry 48 hours after transfection using a Beckman Coulter Gallios Cell counter® and signals were analyzed by Kaluza Acquisition® software. DsRed activity (detection: 638 nm) was normalized to BFP2 marker (detection 488 nm).

[0159] Fed-batch culture performance evaluation Growth and IgG secretion performance in fed-batch cultures was performed according to Le Fourn et al., 2013 with the following modifications: IgG-producing clones stably transfected for expression of MIPs were seeded at 0.3 million cells / mL in 5 mL medium in a 50 mL Falcon. Viable cell density and IgG titers (g / L) were assessed after 3, 6, 8, 9, 10 and 13 days.

[0160] Quantitative PCR analysis For quantitative PCR (qPCR) analysis, total RNA was diluted to 10 6 Cells were extracted and reverse transcribed into cDNA using the GoScript Reverse transcription System (Promega). Transcript accumulation was quantified by qPCR using a LightCycler® 480 SYBR Green I Master and LightCycler 480II instrument (Roche). Transcription levels were normalized to the SDHA housekeeping gene.

[0161] Metabolite analysis (metabolite extraction, sample amount normalization) Metabolite extraction For metabolite quantification, cell pellets were extracted with 1000 μL of pre-chilled MeOH:H2O (4:1, v / v) solvent mixture as the best intermediate to efficiently precipitate proteins, inactivate metabolism, and extract a wide range of polar metabolites. Samples were then probe sonicated (4 pulses x 5 sec) to completely lyse cells and improve metabolite extraction. To promote protein precipitation, samples were incubated at -20°C for 1 h, followed by centrifugation at 13,000 rpm at 4°C for 15 min. The resulting supernatant was collected and evaporated to dryness in a vacuum concentrator (LABCONCO, Missouri, US). Sample extracts were then reconstituted in 100 μL of MeOH:water (4:1) and injected into the LC-MS system.

[0162] Protein quantification Protein pellets were evaporated and dissolved in 20 mM Tris-HCl (pH 7.5), 4 M guanidine hydrochloride, 150 mM NaCl, 1 mM Na2EDTA, 1 mM EGTA, 1% Triton, 2.5 mM sodium pyrophosphate, 1 mM beta-glycerophosphate, 1 mM Na3CO4, 1 μg / mL leupeptin using brief probe sonication (5 pulses x 5 sec). Total protein concentration was measured (A562 nm) (HIDEX, Turku, Finland) using a BCA protein assay kit (THERMO SCIENTIFIC, Masschusetts, US).

[0163] Data acquisition-LC-HRMS Extracted samples were analyzed by hydrophilic interaction liquid chromatography coupled to high resolution mass spectrometry (HILIC-HRMS) using a Q-Exactive® instrument (Quadrupole Orbitrap® mass spectrometer) (THERMO FISHER SCIENTIFIC) operating at a mass resolution of 70,000 full width at half maximum (FWHM) in negative ionization mode. Metabolites were chromatographically separated using a ZIC pHILIC (100 mm, 2.1 mm ID and 5 μm particle size) column. The mobile phase consisted of A = 20 mM ammonium acetate and 20 mM NH4OH in water at pH 9.3 and B = 100% ACN. A linear gradient elution was applied from 90% B (0-1.5 min) decreasing to 50% B (1.5 min-8 min), followed by an isocratic step (8 min-11 min) and a linear gradient to 45% B (11 min-12 min). These conditions were held for 3 min. Finally, the initial chromatographic conditions were established as a run after a 9-minute run for column re-equilibration. The flow rate was 300 μL / min, column temperature 30° C. and sample injection volume 2.5 μL. The ESI source conditions were set as follows: probe heater temperature 200° C., sheath gas 60 a.u., auxiliary gas 15 a.u., capillary temperature 280° C. and ESI spray voltage −3600 V. Full scan mode was used as the collection mode to quantify lactate, pyruvate, 3-hydroxybutyrate and pantothenate, while acetyl-CoA was quantified using parallel reaction monitoring (PRM) collection mode with 30 eV as collision energy.

[0164] Data Processing Raw LC-HRMS data were processed using Thermo Fisher Scientific software (Xcalibur 4.0 QuanBrowser®, THERMO FISHER SCIENTIFIC). Metabolite quantification was performed using external calibration curves.

[0165] statistical analysis Results are expressed as mean ± standard error of the mean (SEM) or mean ± standard deviation (SD). Statistical analysis was performed using one-tailed or two-tailed Student's t-test. Asterisks in the figure panels indicate statistical probability. Statistical probability values ​​less than 0.05 were considered significant.

[0166] Materials and Methods for: Assessment of the effect of individual or combined expression of MIPs on the secretion of different therapeutic protein-expressing CHO clones CFLAR, GCLM, ACTC1: DNA vector constructs The PB transposase expression vector pCS2+U5V5PBU3 contains the PB transposase coding sequence surrounded by the 5' and 3' untranslated terminal regions (UTRs) of the Xenopus laevis beta globulin gene. This plasmid was constructed as follows: the 3'UTR 317 bp fragment from pBSSK / SB10 (kindly provided by Dr S. Ivies) was inserted into pCS2+U5 (INVITROGEN / LIFE Technologies, Paisley, UK) to obtain pCS2+U5U3. The PB transposase coding sequence (2067 bp, GenBank accession number: EF587698) was synthesized by ATG:Biosynthesis (Merzhausen, Germany) and cloned into the pCS2+U5U3 backbone between the two UTRs. The PB control vector corresponds to the unmodified pCS2+U5 plasmid (Figure 10, left panel). A different transposon vector was generated by introducing PB 235 bp 3' and 310 bp 5' inverted terminal repeats (ITRs) synthesized by ATG: Biosynthesis (Merzhausen, Germany) into the pBluescript SK-plasmid (pBSK ITR3'-ITR5', FIG. 1, right panel). The puromycin resistance gene (PuroR) under the control of the SV40 promoter (INVITROGEN / LIFE Technologies) from the pRc / RSV plasmid was then inserted between the two ITRs. The MAR 1-68 and MAR X-29 elements, the puromycin resistance and the GFP gene used in this study were as previously described.

[0167] Cell culture, stable transfection and subcloning of CHO cell lines Suspension Chinese Hamster Ovary cells (CHO-K1) were maintained in SFM4CHO Hyclone serum-free medium (THERMO SCIENTIFIC) supplemented with L-glutamine (PAA, Austria) and HT supplement (GIBCO, INVITROGEN life sciences) in humidified air at 37°C and 5% CO2. CHO-K1 cells were transfected with recombinant protein expression vectors of interest carrying a puromycin resistance gene by electroporation according to the manufacturer's recommendations (Neon devices, Invitrogen). After 2 days, cells were transferred to T75 plates in medium containing 10 μg / mL puromycin and the cells were further cultured under selection for 2 weeks. Stable individual cell clones expressing bevacizumab IgG, Fc fusion or circulating hormone were then generated by limiting dilution, expanded and analyzed for growth performance and production levels. The bevacizumab IgG-, Fc-fusion producer cell clone expressing the highest protein level was selected for further biochemical experiments.Circulating hormone-expressing CHOM clones were analyzed by SDS-PAGE and immunoblotting.

[0168] Some of these clones were then co-transfected with various metabolic improvement protein (MIP) expression vectors and a plasmid carrying the blasticidin resistance gene by electroporation as described below. The cells were then cultured in medium containing 10 μg / mL blasticidin for 2 weeks as described above. Stable clones were isolated by limiting dilution and clones were isolated using a clonepix instrument before being analyzed for growth and production.

[0169] Cell culture and gene transfer analysis CHO-M cells were maintained in suspension culture in SFM4CHO Hyclone serum-free medium (THERMO SCIENTIFIC) supplemented with L-glutamine (PAA, Austria) and HT supplement (GIBCO, INVITROGEN life sciences) at 37°C and 5% CO2 in humidified air. The cells were transfected with transposon donor plasmids by electroporation according to the manufacturer's recommendations (Neon devices, INVITROGEN). Quantification of recombinant protein secretion levels was performed from batch cultures as previously described (see Le Fourn et al., 2013). Briefly, immunoglobulin-expressing cell populations were assessed in batch cultures in 50 mL mini-bioreactor tubes (TPP, Switzerland) at 37°C in a 5% CO2 humidified incubator over a period of 7 days. Immunoglobulin concentrations in cell culture supernatants were measured by sandwich ELISA.

[0170] Alternatively, two clones were isolated from the unsorted and unselected populations expressing each of the three IgGs using the ClonePix® instrument. Briefly, single cells were fixed using semi-solid medium and colonies secreting high amounts of IgG were picked 10 days after implantation. These cell lines were grown at 3x10 cells in peptone-containing growth medium (Hyclone SFM4CHO supplemented with 8 mM glutamine) in a humidified incubator maintained at 37°C and 5% CO2 with orbital shaking at 180 rpm. 5 The cells were passaged every 3 to 4 days in a spin tube bioreactor at a density of 1000 cells / mL.

[0171] When evaluating polyclonal cell populations, IgG titers were determined using 1x10 cells. 5The cell viability was determined from cells seeded at a cell density of 0.05 cells / mL and grown in 5 mL complete medium in a 50 mL spin tube bioreactor for 6 days. Alternatively, shake flask cultures of clonal populations were inoculated in SFM4CHO medium at a density of 3x05 cells / mL to start the fed-batch production process. Fed-batch production assays were performed in 125 mL shake flasks in a culture volume of 25 mL or in 50 mL TPP culture tubes in a culture volume of 5 mL in a humidified incubator maintained at 37°C and 5% CO2 with shaking at 0 rpm (25 mL shake flasks and spin tubes). Production was performed for 10 days by feeding 16% of the initial culture volume of a chemically defined concentrated feed (HYCLONE, Cell Boost 5, 52 g / L) on days 0, 3 and 6-8. No glutamine and glucose feeds were applied during the culture run. The viability and viable cell density (VCD) of the cultures were measured daily using a GUAVA® instrument (MILLIPORE). A double sandwich ELISA assay was used to determine the MAb concentrations secreted into the medium.

[0172] Batch and Fed-Batch Cultivation The growth and production performance of individual clones expressing bevacizumab IgG-, Fc-fusion and circulating hormone were evaluated in batch cultures in 50 mL mini-bioreactors (TPP, Switzerland) at 37°C in a 5% CO2 humidified incubator for 7 days. On cell culture days 3, 4 and 7, cell density and viability were determined using a Guava EasyCyte® flow cytometry system (MILLIPORE). IgG titers in cell culture supernatants were measured by sandwich ELISA. Cell density (Cv.mL 1) and IgG titer values ​​(pg.mL) were plotted at the designated treatment time sampling date.

[0173] The IgG specific productivity of recombinant protein-expressing clones was determined as the slope of MIP concentration versus integrated viable cell count (IVCD) calculated from days 3 to 7 (production phase) and expressed as pg / cell and per day (pcd). For fed-batch production cultures, cells were cultured at 0.3x10 in 125 mL shake flasks in 25 mL of SFM4CHO Hyclone serum-free medium. 6 Cells were seeded at 1000 cells / mL. Cultures were maintained at 37° C. and 5% CO2 with agitation. Cultures were fed daily with commercial Hyclone Feed (THERMO SCIENTIFIC). Cell density and IgG production were assessed daily.

[0174] Erp27 and Erp57: DNA vector constructs To obtain candidate gene coding sequences (CDS), total RNA was isolated from CHO-M cells (SURE CHO-M Cell Line™, Selexis SA, Switzerland) using the NucleoSpin™ RNA kit (MACHEREY-NAGEL). Reverse transcription was performed using the GoScript Reverse transcription System (Promega). Candidate gene CDS was inserted into pBSK_ITR_BT+_X29_ITR (pBSK_ITR) or pBSK_ITR_Blast vectors. The pBSK_ITR vector contains an expression cassette consisting of the CMV / EF1 alpha promoter and BGH polyadenylation signal followed by hMAR X-29 (Le Fourn, Girod, Buceta, Regamey, & Mermod, 2014). The expression cassette is flanked by terminal inverted sequences of the piggyBac transposon. In the pBSK_ITR_Blast vector, the blasticidin resistance gene under the control of the SV40 promoter was inserted after hMAR X-29. In experiments where Erp27 and Erp57 were overexpressed in difficult-to-express protein expressing cells or during titration of Erp27 or Ca3 overexpression, the pBSK_ITR plasmid was used and cells were co-transfected with a plasmid carrying blasticidin resistance under the control of the SV40 promoter. In other experiments, the pBSK_ITR_Blast vector was used. In experiments where Foxa1 was overexpressed, the CMV / EF1 alpha promoter was replaced by a minimal CMV promoter for the expression of both Foxa1 and GFP. The piggyBac transposase expression vector (pCS2+U5V5PBU3) was previously described (Ley et al., 2013).

[0175] Reactive oxygen species analysis Intracellular reactive oxygen species (ROS) levels were detected by using 6-carboxy-2',7'-dichlorodihydrofluorescein diacetate (carboxy-H2DCFDA, THERMOFFISHER SCIENTIFIC). On different days of fed-batch culture, 2 million cells were incubated in PBS containing 50 μM carboxy-H2DCFDA for 30 minutes. Cells were then centrifuged, resuspended in 1 mL PBS, and stained with DAPI to exclude dead cells. Carboxy-H2DCFDA fluorescence was analyzed by flow cytometry in DAPI-negative cell population (Gallios®, BECKMAN COULTER).

[0176] Cell culture, stable transformation and analysis of stable polyclonal lines Cells were maintained in suspension culture in SFM4CHO Hyclone serum-free medium (GE Healthcare) supplemented with 5% HyClone Cell Boost5 supplement (GE HEALTHCARE), 8 mM L-glutamine (PAA, Austria) and 1X HT supplement (GIBCO) at 37°C in a humidified incubator with 5% CO2. Polyclonal CHO-M cells producing trastuzumab or infliximab antibodies were generated and characterized as previously described (Le Fourn et al., 2014). IgG-expressing stable clones were obtained by cell sorting on a FACSAria II (BD), expanded and analyzed for IgG production levels by sandwich ELISA. Stable cell lines overexpressing the candidate genes were obtained by retransfecting pBSK_ITR CDS, pBlast and pCS2+U5V5PBU3, or pBSK_ITR_Blast_CDS and pCS2+U5V5PBU3 into trastuzumab- or infliximab-producing clones using electroporation according to the manufacturer's protocol (Neon® transfection system 100 μL Kit, INVITROGEN). Cells with stable insertions were selected using 3 or 7.5 μg / mL blasticidin (INVIVOGEN). For etanercept-producing clones, single subclones co-expressing Erp27 and Erp57 were isolated and their production was evaluated using a ClonePix cell colony imaging device. Cell colonies showing the widest etanercept-secreting halos were isolated from Erp27- and Erp57-overexpressing or control cell populations.

[0177] ACTC1 and TAGAP: DNA vector constructs Genomic and cDNA sequences of ACTC1 and TAGAP genes were determined after alignment to the homologous genes in mouse using NCBI BLAST software. Transcript sequence RNAseq analysis was performed on Selexis SA CHO K1 cells (CHO-M). The cDNA library was amplified using the GoScript® Reverse transcription System (PROMEGA) for 10 min. 6 The ACTC1 and TAGAP coding sequences (CDS) were cloned into the pBSK_ITR_BT+_EGFP_X29_ITR transposable expression vector (Le Fourn, Girod, Buceta, Regamey, & Mermod, 2014) to obtain the pBSK-ACTC1 and pBSK-TAGAP expression vectors. The pBSK_ITR_BT+_EGFP_X29_ITR vector contains an expression cassette consisting of a CMV / EF1 alpha fusion promoter and a BGH polyadenylation signal followed by hMAR X-29. The expression cassette is flanked by terminal inverted sequences of the piggyBac transposon. The blasticidin vector (pBlast) contains the blasticidin resistance gene under the control of the SV40 promoter originating from the pRc / RSV plasmid (Invitrogen / Life Technologies).

[0178] Cell culture and stable gene transfer CHO K1 cells were maintained in suspension culture in SFM4CHO Hyclone® serum-free medium (SFM, ThermoScientific™) supplemented with L-glutamine (PAA, Austria) and HT supplement (GIBCO, INVITROGEN LIFE SCIENCES) at 37° C. and 5% CO2 in humidified air. The other cell culture medium used for these experiments was Deficient BalanCD CHO Growth A (B-CDmin®; IRVINE SCIENTIFIC) supplemented with vitamin B1 (thiamine hydrochloride; SIGMA ALDRICH), vitamin B5 (calcium DL-pantothenate; TCI) and vitamin H (biotin, SIGMA ALDRICH). CHO cells were transfected with pBSK-ACTC1 or TAGAP, pBlast and pCS2-U5-PBU3 IgG1-Hc or IgG1-Lc expression vectors by electroporation according to the manufacturer's recommendations (NEONDEVICES, INVITROGEN). The generation of stable cell lines was achieved by culturing the transfected cells in SFM4CHO medium supplemented with 7.5 μg / mL blasticidin for 3 weeks. Polyclonal cell populations expressing IgG were selected for further experiments as follows: for blasticidin selection, cells were seeded in SFM4CHO medium supplemented with 10 μg / mL blasticidin for 2 weeks, then cultured in wells containing unsupplemented medium for 5 days, then transferred to 50 mL spin tubes.

[0179] Analysis of stable polyclonal and monoclonal lines Fed-batch culture performance evaluation, IgG cell surface staining, IgG cell secretion assay and vitamin B5 metabolite quantification were performed as previously described (Pourcel et al., 2019). Briefly, IgG secretion performance testing in fed-batch culture was performed as previously reported (Le Fourn et al., 2014). Assays for cell surface IgG were as previously reported (Brezinsky et al., 2003), and cell pools expressing recombinant IgG protein were subcloned using a ClonePix™ FL Imager from Molecular Devices®. For vitamin B5 metabolite quantification, cell pellets were extracted with 1 mL of cold MeOH:H2O (4:1, v / v) solvent mixture and then probe sonicated. The supernatant obtained after 1 hour incubation at -20°C followed by centrifugation at 13,000 rpm at 4°C for 15 minutes was collected, evaporated to dryness, then reconstituted in 100 μL MeOH:water (4:1) and injected into the LC-MS system. The protein pellet was evaporated and dissolved in 20 mM Tris-HCl (pH 7.5), 4 M guanidine hydrochloride, 150 mM NaCl, 1 mM Na2EDTA, 1 mM EGTA, 1% Triton, 2.5 mM sodium pyrophosphate, 1 mM beta-glycerophosphate, 1 mM Na3VO4, 1 μg / mL leupeptin using brief probe sonication. The extracted samples were analyzed by HILIC-HRMS in negative ionization mode using a Q-Exactive® instrument (Thermo Fisher Scientific®) operating at a mass resolution of 70,000 full width at half maximum. Raw LC-HRMS data was processed using Thermo Fisher Scientific® software (Xcalibur® 4.0 QuanBrowser®, THERMO FISFIER SCIENTIFIC). Metabolite quantification was performed using external calibration curves.

[0180] RNA RT-PCR and sequencing RNA-seq analysis For RNA reverse transcription and real-time quantitative PCR (RT-qPCR) analysis, total RNA was extracted from 10 cells. 6 Cells were extracted from 1000 cells and reverse transcribed into cDNA using a poly-T primer. Transcript accumulation was quantified by qPCR using the SYBR Green-Taq polymerase kit from EUROGENTEC Inc. and an ABI Prism 7700 PCR machine (APPLIED BIOSYSTEMS). Transcript levels were normalized to the GAPDH housekeeping gene. RNASeq analysis of B5-selected and puromycin-selected CHO cells was as previously described (Pourcel et al., 2019).

[0181] Briefly, total RNA was extracted from i) parental CHO cells, ii) CHO cell clones expressing interferon beta and B5 transporter SLC5A6 expression vectors subjected to B5 depletion / puromycin selection or puromycin selection alone, and iii) CHO cell pools expressing trastuzumab and SLC5A6 expression vectors selected as before by B5 depletion / puromycin selection or puromycin selection alone. cDNA was obtained from 0.5-1 μg of total RNA using Illumina TruSeq® stranded mRNA-seq reagent (ILLUMINA). RNA-seq libraries 100 nt paired ends were sequenced on an Illumina HiSeq 2500®. Reads were mapped to the CHO-K1 transcriptome (RefSeq, 2014).

[0182] Protein sample preparation and immunoblotting Total actin content was assessed as follows: Protein extraction was performed on 10 cells washed in PBS. 7Afterwards, the cell pellet was resuspended in RIPA lysis buffer (150 mM NaCl, 50 mM Tris-HCl pH 8.0, 1% NP-40, 0.1% sodium deoxycholate, 0.1% SDS) and stirred for 30 min. Cell debris was pelleted by centrifugation (5 min, 15.000 g) and the supernatant was collected. Equal volumes of protein samples were processed for denaturing gel electrophoresis and immunoblotting using 6-14% SDS / Page gels, Mini-Protean Tetra Gel (Bio-Rad) and Mini trans Blot Cell (Bio-Rad), and proteins were blotted onto nitrocellulose membranes. Membranes were blocked in TBST (Tris Base 20 mM, NaCl 135 mM, Tween-20 0.1%, pH 7.6) with 5% skim milk powder for 1 h at room temperature. The membrane was then incubated overnight with anti-alpha-cardiac actin polyclonal antibody (PA5-21396, Invitrogen, dilution 1:500) or anti-GAPDH (sc-32233, SANTA CRUZ BIOTECHNOLOGY, dilution 1:500), and then incubated for 1 hour with HRP-conjugated secondary antibody, anti-mouse (G21040, Invitrogen, dilution 1:1000). Protein bands were visualized by using SuperSignal West Pico PLUS® (34580, THERMO SCIENTIFIC) and ChemiDoc® Imaging System (BIO-RAD). The resulting protein band intensity was quantified by FIJI distribution in ImageJ® (NIH, Bethesda, MD).

[0183] Analysis of actin polymerization by fluorescence-activated cell sorting The level of polymerized actin (F-actin) was measured by culture of 2x10 cells in SFM. 5 The cells were evaluated in cell cultures initiated by seeding 10 cells / mL and incubating at 37°C with 5% CO for 3 days. 6Three aliquots were collected from each culture and the cells were resuspended in fresh medium supplemented with 200 nM Sir-actin (CY-SC001®, SPIROCHROME) and incubated for 4 hours at 37° C. and 5% CO2. The cells were then sorted by FACS (BD FACS Aria II, BD BIOSCIENCES, San Jose, CA) to sort the cells depending on their fluorescence level (Abs 652 nm, Em 674 nm; low, medium and high fluorescence). These cell populations were expanded and maintained at 37° C. and 5% CO2 until further analysis.

[0184] It will be appreciated that the systems (e.g., vectors / cells), methods, and kits of the present invention can be incorporated in the form of a variety of embodiments, only a few of which are disclosed herein. It will be appreciated by those skilled in the art that other embodiments exist and do not depart from the spirit of the present invention. Thus, the described embodiments are illustrative and should not be construed as limiting.

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Claims

1. 1. A eukaryotic expression system comprising at least one metabolic impact product (MIP) expression vector comprising at least one nucleic acid encoding at least one MIP under the control of at least one regulatory sequence, said at least one MIP comprising Foxa1 (Forkhead box protein A1) or at least one PPAR (Peroxisome Proliferator Activated Receptor) selected from PPARα, PPARβ / δ or PPARγ, said MIP expression vector further comprising a first ITR (Inverted Terminal Repeat) upstream and a second ITR downstream of the nucleic acid encoding said MIP.

2. 2. The eukaryotic expression system of claim 1, wherein the at least one regulatory sequence is a promoter selected from the group of promoters having expression levels of CMV, EF1 alpha, CMV / EF1 alpha, SV40, RSV, PGK, and CMV, EF1 alpha, CMV / EF1 alpha, SV40, RSV, PGK, and combinations thereof.

3. 3. A eukaryotic expression system according to claim 1 or 2, comprising at least two, three, four, five or more MIPs.

4. 4. The eukaryotic expression system according to claim 1, wherein said at least one regulatory sequence comprises a MAR element or construct comprising a specific MAR element or construct between said first and second ITRs, comprising MAR1-68 and / or MAR X-29.

5. 5. The eukaryotic expression system according to any one of claims 1 to 4, wherein the MIP expression vector is a transposon donor vector and the expression system further comprises a transposase expression helper vector or mRNA.

6. 6. The eukaryotic expression system according to any one of claims 1 to 5, comprising a carrier vector comprising at least one restriction enzyme cleavage site adapted for the insertion of a nucleic acid encoding a protein of interest and further comprising an antibiotic resistance gene and / or a vitamin transport protein, including the sodium-multivitamin transporter SLC5A6.

7. 7. The eukaryotic expression system of claim 5 or 6, wherein the transposase expression helper vector comprises a sequence encoding a PB transposase flanked upstream and downstream by untranslated terminal regions (UTRs).

8. (a) transfecting an expression vector of a eukaryotic expression system according to any one of claims 1 to 7 into a eukaryotic cell; and adding to said eukaryotic cell at least one activator of at least one, two or all of the PPARs selected from PPARα, PPARβ / δ or PPARγ, including bezafibrate; and (b) transfecting said cells with a carrier vector containing a protein of interest. The method includes:

9. 9. The method of claim 8, wherein the MA / EL (maximal inhibited / expression level) of the protein of interest is greater than 1.5x ML (maximal level), greater than 2x ML, or even greater than 2.5x or 3x ML.

10. A kit comprising in one container a eukaryotic expression system according to any one of claims 1 to 7, and in a second container instructions on how to use said system.

11. 11. The kit of claim 10, further comprising at least one activator of at least one MIP, wherein the MIP is at least one PPAR selected from PPARα, PPARβ / δ or PPARγ, and the activator is an activator of at least one, two or all PPARs, comprising bezafibrate.

12. A recombinant eukaryotic cell comprising the eukaryotic expression system according to any one of claims 1 to 7.

13. 13. A recombinant eukaryotic cell according to claim 12, wherein the cell is at least stably transfected with a MIP expression vector or a part thereof comprising at least one MIP and is a Chinese Hamster Ovary (CHO) cell.

14. Use of a eukaryotic expression system according to any one of claims 1 to 7 for the production of a recombinant eukaryotic cell expressing a transgene encoding a protein of interest.

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