Identification of Manipulated Variables for aGlycosylation Control Strategy

Melissa M. St. Amand,1 Devesh Radhakrishnan,1 Anne S. Robinson,1,2

Babatunde A. Ogunnaike1

1Department of Chemical and Biomolecular Engineering, University of Delaware, 150

Academy Street, Newark, Delaware 19716; telephone: 302-831-4504; fax: 302-831-1048;

e-mail: ogunnaike@udel.edu2Department of Chemical and Biomolecular Engineering, Tulane University,

New Orleans, Louisiana

ABSTRACT: N-linked glycan distribution affects importantend-use characteristics such as the bioactivity and efficacy ofmany therapeutic proteins, (including monoclonal anti-bodies), in vivo. Yet, obtaining desired glycan distributionsconsistently during batch-to-batch production can bechallenging for biopharmaceutical manufacturers. Whilean appropriately implemented on-line glycosylation controlstrategy during production can help to ensure a consistentglycan distribution, to date no such strategies have beenreported. Our goal is to develop and validate a comprehen-sive strategy for effective on-line control of glycosylation, thesuccessful achievement of which requires first identifyingappropriate manipulated variables that can be used to directthe glycan distribution to a desired state. While variousculture conditions such as bioreactor process variables,media type, and media supplements have been shown toaffect the glycan distribution, in this study we focus on thelatter. Specifically, we implemented a statistically designedseries of experiments to determine the significant maineffects (as well as interaction effects) of media supplemen-tation with manganese, galactose, ammonia and found thateach had significant effects on certain glycans. We alsoinclude data indicating the glycosylation enzyme genetranscript levels as well as the intracellular nucleotide sugarconcentrations in the presence of the media supplements toprovide insight into the intracellular conditions that may becontributing to the changes in glycan distribution. Theacquired experimental data sets were then used to identifywhich glycans can be controlled by the media supplementsand to what degree. We determined that MnCl2 can be usedas a manipulated variable to increase the relative abundanceof M51 and decrease FA2 simultaneously, and galactose can

be used as a manipulated variable to increase the relativeabundance of FA2G1 and decrease FA2 and A2 simulta-neously.

Biotechnol. Bioeng. 2014;111: 1957–1970.

� 2014 Wiley Periodicals, Inc.

KEYWORDS: glycosylation; monoclonal antibody; design ofexperiments (DoE); media supplements; controllability;enzyme expression; nucleotide sugar

Introduction

N-linked glycan distribution affects the bioactivity andefficacy of many therapeutic proteins in vivo (Arnold et al.,2007; Raju, 2008; Schiestl et al., 2011). Specifically formonoclonal antibody therapeutics, terminal galactosylationcan affect complement-dependent cytotoxicity (CDC)(Hodoniczky et al., 2005); core fucosylation can affectantibody-dependent cell-mediated cytotoxicity (ADCC)(Shields et al., 2002); and terminal sialylation can affectinflammatory properties as well as ADCC (Anthony et al.,2008; Kaneko et al., 2006; Scallon et al., 2007). In addition,terminal mannose and terminal n-acetylglucosamine(GlcNAc) can reduce serum half-life (Jones et al., 2007;Wright et al., 2000). Despite its importance for therapeuticbioactivity and efficacy in vivo, obtaining a desired glycandistribution consistently during batch-to-batch productioncontinues to present a challenge for many biopharma-ceutical manufacturers (Federici et al., 2013; McCamishand Woollett, 2013; Schiestl et al., 2011). Implementingan on-line glycosylation control strategy during produc-tion would help to address the problem of glycandistribution variability. However, to date successfulimplementation of on-line glycosylation control duringbiopharmaceutical manufacturing has yet to be reported inthe open literature.The successful achievement of glycosylation control

requires first identifying appropriate manipulated variables

Correspondence to: B.A. Ogunnaike

Contract grant sponsor: NSF-CBET

Contract grant number: 1034213

Contract grant sponsor: NSF Graduate Research Fellowship

Contract grant number: 2008067497

Received 22 January 2014; Revision received 12 March 2014; Accepted 28 March 2014

Accepted manuscript online 12 April 2014;

Article first published online 22 May 2014 in Wiley Online Library

(http://onlinelibrary.wiley.com/doi/10.1002/bit.25251/abstract).

DOI 10.1002/bit.25251

ARTICLE

� 2014 Wiley Periodicals, Inc. Biotechnology and Bioengineering, Vol. 111, No. 10, October, 2014 1957

that can be used to direct the glycan distribution to a desiredstate. It is known that a manufactured protein’s glycandistribution can be affected by the choice of cell culturemedia, feeds, and supplements. Various nutrients, nucleo-tide sugar precursors, amino acids, trace metals, andhormones in the culture media or feed have all been shownto affect protein glycan distribution (Chen and Harcum,2005; Gawlitzek et al., 2000, 2009; Hills et al., 2000; Wonget al., 2005). Specifically when IgG was produced with CHOcells, Hong et al. (2010) found that the relative percentage ofproteins with galactosylated glycans (i.e., FA2G11 andFA2G2) was increased by supplementing the culture mediawith glutamate rather than glutamine. Hong et al. (2010)also found that supplementing culture media with NH4Cldecreased the production of galactosylated glycans. Grameret al. (2011) found that supplementing feed medium withvarious concentrations of uridine, MnCl2, and galactoseincreased the relative percentage of FA2G1 and decreasedthe relative percentage of FA2 in IgG. Grainger and James(2013) also studied the effects of uridine, MnCl2, andgalactose, finding that manganese alone was not sufficientby itself to improve the percentage of galactosylated glycans;maximizing galactosylation required the additional syner-gistic effects of galactose and uridine. In addition, mediaosmolality has been shown to influence glycan distribution.Pacis et al. (2011) found that high osmolality (400mOsm)produced greater amounts of M5 in IgG produced withCHO cells. Konno et al. (2012) also found that osmolalitycan be used as a means to control fucosylation duringperfusion culture. Knowing the magnitude by which amedia supplement affects a protein’s glycan distribution aswell as the direction in which the relative percentage of aglycan is affected provides important information that canbe used to design a strategy for active control of the glycandistribution.

In this study, we identify media supplements that can beused as manipulated variables in a glycosylation controlstrategy for an IgG1 produced with CHO-K1 cells. Weimplemented a statistically designed series of experiments todetermine the significant main effects (as well as interactioneffects) of MnCl2, galactose, and NH4Cl. To understand theintracellular conditions contributing to the media supple-ment effects on glycan distribution, we include dataindicating the glycosylation enzyme transcript levels as wellas intracellular nucleotide sugar concentrations. The ac-quired experimental data sets were then used to identifywhich glycans can be controlled by MnCl2, galactose, and/orNH4Cl.

Materials and Methods

Experimental Design

A CHO-K1 cell line producing an IgG1 (gift of Genentech,South San Francisco, CA) was used during this work. After asurvey of more than 70 peer reviewed journal articles, MnCl2,galactose, and NH4Cl media concentrations were chosen asfactors for this study as these media supplements were mostlikely to cause significant differences in the glycan distributionof an IgG1 produced with CHO-K1 cells. Experimental datawas generated on the basis of a 23 factorial design withMnCl2,galactose, and NH4Cl media concentrations as factors. Table Ilists the high and low media supplement concentration valuesused during the experiments.MnCl2 and galactose were addedto the culture media at the time of inoculation; NH4Cl, whichcan cause cell death, was added 48 h after inoculation to allowthe cells to grow to sufficient biomass before introducing thestress. All experiments were performed in shake flasks with a60mL working volume of a custom CD OPTICHO formula-tion (provided by Life Technologies, Grand Island,NY), whichwas supplemented with 4mM glutamine, 5 g/L glucose, and25 nMMTX. Variable amounts of 300 g/L NaCl were added toeach flask to adjust the initial osmolality of all cultures to315mOsm/Kg as determined by a freezing point osmometer(Advanced Instruments, Norwood, MA). Flasks were inocu-lated with a cell density of 7.5� 105 cells/mL and grown on anorbital shaker in a 5% CO2 overlay, 37

�C incubator. Every 2days cell count, viability, titer and media metabolite, andnutrient concentrations were measured using a hemocytome-ter, BioProfile 100þ (Nova Biomedical, Waltham, MA) and astandard Protein A HPLC method with the BiomonolithProtein A HPLC column (Agilent Technologies, Santa Clara,CA), respectively. Media samples for glycan analysis and cellpellets forenzyme transcript andsugarnucleotideanalysisweretaken at the endof the run (Day7) and stored at�80�Cprior toanalysis. Factor coefficients and associated P-values weredetermined from the resulting glycan distribution data usinganalysis of variance (ANOVA), from which we quantifiedexplicitly the magnitude (and statistical significance) of mediasupplement effects.

Glycan Distribution Assay

Permethylated glycans were analyzed via a 4800MALDI TOF/TOF (ABSciex, Framingham, MA). Briefly, the glycanpreparation procedure consisted of the following steps:200mg IgG1 was purified from the media sample using the

Table I. High and low factor values (media supplement concentrations,

mM) of 23 factorial design of experiments.

Factor Low High

MnCl2 0 100Galactose 0.001 0.04NH4Cla 0 10

aNote Ammonia was added 48 h after inoculation.

1Oxford nomenclature for glycans. See Table SI in supplementalmaterial for symbolic representation of glycan structures. Harvey DJ,Merry AH, Royle L, Campbell MP, Dwek RA, Rudd PM. 2009. Proposalfor a standard system for drawing structural diagrams of N- and O-linked carbohydrates and related compounds. Proteomics 9(15):3796–3801.

1958 Biotechnology and Bioengineering, Vol. 111, No. 10, October, 2014

ME1000 system with Protein A Phytip Cartridges accordingto the manufacturer’s protocol (Phynexus, San Jose, CA).Once purified, the IgG1 was digested with trypsin (Promega,Madison, WI) and glycans were cleaved using N-glycanase(Prozyme, Hayward, CA). Cleaved glycans were purified withHypersep Hyper Carb SPE cartridges (Thermo Scientific,Waltham, MA) using 5% v/v acetonitrile with 0.1% v/v TFAas a wash and 50% acetonitrile with 0.1% v/v TFA to elute theglycans. Purified glycans were concentrated to dried stateunder airflow, then permethylated using methyl iodide in thepresence of NaOH and DMSO. Permethylated glycans werepurified first using 2:5 liquid–liquid extraction with chloro-form then againwith a second purification step using Sep-PakC18 SPE cartridges (Waters, Milford, MA) with isocraticelution fractions in 15%, 35%, 50%, and 75% acetonitrile.Eluted fractions were evaporated with a speedvac, and thenresuspended in 30mL of 80%methanol. Resuspended glycanswere analyzed via mass spectrometry with a 4800 MALDITOF/TOF Analyzer (ABSciex) in positive ion, reflector modewith DHB as the matrix. The relative glycan percentage of 20glycans typically found on monoclonal antibodies (see TableSI in Supplemental Material) was determined by manuallycalculating the ratio of the individual glycan peak height tothe sum of all glycan peak heights. Biological replicates ofshake flask experiments (n¼ 2) were pooled and used todetermine an appropriate 95% confidence interval for eachglycan measurement.

Enzyme Gene Expression Assay

The expression of 30 glycosylation enzyme transcripts (seeTable SII, Supplemental Material) was determined with theBiomark high throughput QRTPCR system (Fluidigm, SouthSan Francisco, CA). Approximately 10� 106 CHO-K1 cellswere removed from each shake flask and centrifugedimmediately (4�C, 2,601g, 5min). The supernatant wasdiscarded and cell pellets were flash frozen on dry ice thenstored at�80�C until extraction. RNAwas extracted from theCHO-K1 cell pellet using the RNeasy kit (Qiagen, Valencia,CA). cDNA was generated from the RNA using the HighCapacity cDNA Reverse Transcription Kit (Applied Biosys-tems, Carlsbad, CA) and amplified using Multiplex PCR 5XMaster Mix (New England BioLabs, Ipswich, MA). TheBiomark 48.48 Dynamic array chip was loaded accordingto the manufacture’s SsoFast EvaGreen Supermix protocol.Ct values were generated using the Fluidigm Real-Time PCRanalysis software package and exported to Excel. Twohousekeeping genes were used as controls for the analysis:Cricetulus griseus b-actin (GenBank Accession No.U20114) andGAPDH (Gene Accession X52123.1). In this study, b-actinand GAPDH expression levels were confirmed to be relativelyunchanged across all samples with a 95% confidence interval�0.6 for both housekeeping genes. Relative changes in geneexpression with respect to the control were calculatedmanually in Excel using the delta-delta threshold cyclemethod(Livak and Schmittgen, 2001). The threshold for significantfold difference in enzyme expression was chosen as the 95%

confidence interval of the variation in housekeeping geneexpression (i.e., 2�DDCt > 0:6). Data shown is the average oftwo RNA extraction and qPCR replicates.

Sugar Nucleotide Assay

The sugar nucleotide extraction and analysis procedure wasadapted from Kochanowski et al. (2006). Briefly, approxi-mately 4� 106 CHO-K1 cells were removed from each flaskand immediately centrifuged (4�C, 2,601g, 5min). Thesupernatant was discarded and cell pellets were flash frozenon dry ice and stored at �70�C until extraction. To extractsugar nucleotides, 185mL of cold 0.5M perchloric acid(Fisher, Waltham, MA) was added to the samples andincubated on ice for 2min then centrifuged (16,000g, 5min).The solubilized material was neutralized using 42mL of cold2.5M KOH (Fisher) in 1.5M K2HPO4 (Fisher), incubated onice for 2min, and then centrifuged (16,000g, 5min).Supernatants were loaded into an Agilent 1100 HPLC withreverse phase C18 Eclipse Column (3.5mm, 100mm� 4.6mm) at 40�C. Nucleotide sugar separation was achievedusing a gradient method with Buffers A: 100mM potassiumphosphate buffer (Fisher Scientific) with 8mM tetrabuty-lammonium hydrogen sulphate (Sigma–Aldrich, St. Louis,MO), pH 6.5 and B: 80% Buffer Aþ 20% Acetonitrile, pH6.5. The gradient method consisted of 5% B (isocratic) for10min followed by þ4.5%B/min gradient for 20min and aregeneration with 70%ACN and 30% Buffer A for 7min at aflowrate of 1mL/min. Chromatograms were collected at254 nm and analyzed using Agilent ChemStation Software(Rev. B 04.02). Sugar nucleotide concentrations weredetermined by analyzing standard curves of various sugarnucleotide standards (Sigma–Aldrich).

Controllability Analysis

Controllability analysis was performed on the experimentallygenerated glycan distribution data using the methoddescribed in St. Amand et al. (2014). Briefly, estimates ofthe significant process gains were obtained as the significantcoefficients (significance level a¼ 0.1) identified followinganalysis (via ANOVA) of the glycan distribution datagenerated from the 23 factorial design described inExperimental Design section. Singular value decomposition(SVD) was performed on the resulting process gainmatrix, K,to produce the singular value matrix,S, and unitary matricesW and VT needed to construct the orthogonal output modeshi, and orthogonal input modes, mi. Modes associated withsi> s� ¼ 1 were considered controllable.

Results

Cell Culture Performance Was Minimally Affected byMedia Supplements

Culture performance data was similar for each of the cultureconditions specified in the experimental design (see Fig. 1).

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Biotechnology and Bioengineering

Figure 1. a: Viable cell count, (b) % viability, (c) total cell count, (d) IgG titer, (e) glutamine media concentration, (f) glutamate media concentration, (g) glucose media

concentration (h), lactate media concentration, (i) ammonia media concentration, (j) media osmolality data for CHO-K1 cells grown with various media supplements. The highest

total cell count and IgG1 titer was observed in the control flask, which reached a total cell count of 8� 106 cells/mL and a titer of 14.3mg/mL. The supplemented flasks reached

maximum total cell counts between 4.5� 106 and 6� 106 cells/mL. Despite the differences in cell count, all supplemented flasks produced a titer of 9� 1mg/mL, which is within the

error of the assay. Cell viability remained >90% for all flasks until Day 6 of culture.

1960 Biotechnology and Bioengineering, Vol. 111, No. 10, October, 2014

The highest total cell count and IgG1 titer was observed in thecontrol flask, which reached a total cell count of 8� 106 cells/mL, and a titer of 14.3mg/mL. The cultures with supple-mented media reached maximum total cell counts between4.5� 106 and 6� 106 cells/mL. Despite the differences in cellcount, each culture with supplemented media reached an IgGtiter of 9� 1mg/mL, which is within the error of the assay.Cell viability remained >90% until culture Day 6 for allculture conditions investigated in the experimental design.Final osmolalities of cultures with supplemented media

ranged from 280 to 400mOsm/kg despite adjusting the initialmedia osmolality to 315 kg/mOsm prior to inoculation.However, for the CHO-K1 cell line used in this study,osmolality did not significantly affect the glycan distribution(see Fig. S1, Supplemental Material). Therefore, mediaosmolality is not a suitable manipulated variable for aglycosylation control strategy. The robustness of this cell line’sglycan distribution to changes in osmolality suggests that anydifferences observed in glycan distribution in the presence ofthe media supplements are not caused by the variations infinal media osmolality.

Glycan Distribution Variations Occurred with theAddition of Media Supplements

Main Effects

As shown in Figure 2, glycan distribution varied greatly in thepresence of media supplements despite the similarity in titer

for each condition. The glycan distribution under the controlconditions was typical of an IgG1 protein: the FA2 andFA2G11 glycans dominated the distribution with relativepercentages 48.8� 2.2% and 18.9� 0.4%, respectively. Thenext most abundant glycans included A2, A1, and A2G1 at8.6� 2.42%, 5.1� 1.5%, and 4.3� 1.5%, respectively. Therelative percentages of all other glycans were less than 2.8%and thus were considered minor glycans.The main effects of the media supplements on the glycan

distribution are as follows: In the presence of 0.04mMMnCl2, compared to the control, the relative abundance ofthe FA2 and FA2G1 glycans decreased by 19� 2.2% and7� 0.8%, respectively. In addition, the relative abundance ofA1,M5, and A2 glycans all increased compared to the control.Like MnCl2, supplementing the culture media with 100mMgalactose decreased the relative abundance of the FA2 glycanby 14� 2.2% compared to the control. However, the additionof galactose increased the relative percentage of galatosylatedglycans; compared to the control, the relative abundance ofthe FA2G1 and FA2G2 glycans increased by 6� 0.4% and2� 0.1%, respectively.The addition of 10mM NH4Cl to the culture media 48 h

after inoculation decreased the relative percentage of FA2G1by 5� 0.4% compared to the control. To assess the effects ofNH4

þ, which accumulates as a natural byproduct of cellularmetabolism, glutamine, the typical nitrogen source in culturemedia, was substituted with glutamate, a nitrogen sourceknown to reduce ammonia accumulation in cultures. Thefinal NH4

þ accumulation in glutamate supplemented

Figure 2. Average relative percentage of glycans from IgG1 produced with CHO-K1 cells grown in the presence of various media supplements. Error bars indicate range of

biological replicates (n¼ 2).

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Biotechnology and Bioengineering

cultures was 3.3mM, whereas glutamine cultures accumu-lated 5.9mM NH4

þ. Despite the reduction in NH4þ

accumulation in glutamate supplemented cultures, nosignificant differences were found between the glycandistributions of glutamate and glutamine supplementedcultures (see Fig. S2 in Supplemental Material). However,using glutamate improved IgG titer slightly to 15.6mg/mLdespite only having a maximum total cell count of 4.5� 106

cells/mL (see Fig. 1). Therefore, using glutamate as a nitrogensource instead of glutaminemay be desirable if the objective isto increase titer while maintaining a consistent glycandistribution.

Interaction Effects

The objective of our study is to identify potentialmanipulated variables for a control strategy. Therefore, inaddition to identifying the main effects, it is also critical todetermine if the effect of two or more process variables issimply additive or if interaction effects are present.Interaction effects that are present but not accounted forduring controller design will result in decreased controllereffectiveness.

Supplementing cultures with both 0.04mM MnCl2 and100mM galactose decreased the relative percentage of FA2 by27� 2.2% and increased the relative percentage of M5 by20� 0.7% compared to the control. The interaction of Mn2þ

and galactose affected both glycans more than the main effectof either Mn2þ or galactose alone, but the effect ofsupplementation with both Mn2þ and galactose was notsimply additive of the main effects of each supplement.Therefore, Mn2þ and galactose interaction effects are presentduring this process. Also, the relative percentage of A2 wasincreased by 4� 2.4% compared to the control when theculture was supplemented with both MnCl2 and galactose.Therefore, the interaction effect ofMn2þ and galactose on therelative percentage of A2 is smaller than the main effect ofMn2þ, but larger than the main effect of galactose.

The addition of 0.04mMMnCl2 at inoculation and 10mMNH4Cl 48 h after inoculation decreased the relative abun-dances of FA2 and FA2G1 by 25� 2.2% and 12� 0.4%,respectively, compared to the control. The relative abundan-ces of M5 and A2 were increased by 20� 0.7% and13.5� 2.4%, respectively, compared to control. The interac-tion effect on the FA2, M5, and A2 glycans is greater than themain effects of either Mn2þ or NH4

þ. One the other hand,the relative percentage of FA2G1 was simply additive of themain effects of Mn2þ and NH4

þ; therefore there is nointeraction effect between Mn2þ and NH4

þ on the FA2G1glycan.

Adding 100mM galactose at inoculation and 10mMNH4Cl 48 h after inoculation decreased FA2 by 12� 2.2%compared to control. The presence of both galactose andNH4

þ increased the relative percentage of FA2G1 by only1.7� 0.4% compared to control. Whereas the main effect ofgalactose increased the relative percentage of FA2G1 by6� 0.4%. Therefore, the interaction effect between galactose

and NH4þ substantially affected the relative abundance of

FA2G1.The FA2 glycan, with the largest relative abundance,

remained dominant despite the main and interaction effectsof the media supplements discussed previously. However, thethree-way interaction of Mn2þ, galactose, and NH4

þ resultedin a 32% reduction in the relative percentage of FA2 and a1,400% increase in the relative percentage of M5. As such,M5, with a relative percentage of 38.7� 2.2%, replaced FA2as the dominant glycan in cultures supplemented withMnCl2, galactose, and NH4Cl. No other culture conditioninvestigated in the study produced such a striking change tothe glycan distribution.

Media Supplement Effects to the Glycan DistributionWere Statistically Significant

To determine statistical significance of media supplementeffects, ANOVA was applied to the glycan distribution data.Except for M4, M7, M8, and FA1G1S1, each glycan specifiedin Table SI, has amain effect with associated P-value<0.1 (seeFig. 3). This indicates that, at the significance level a¼ 0.1,most glycans were significantly affected by MnCl2, galactose,and/or NH4Cl supplementation.

The significant coefficients obtained from the glycandistribution data analyses, which indicate the direction andmagnitude of each media supplement effect, are representedin the heat map shown in Figure 4. Inspection of Figure 4showsM5, FA2, A2, and FA2G1 are the glycans most affectedby the media supplements tested in this study. Supplement-ing culture media with MnCl2, galactose, and/or NH4Clincreased the relative percentage of the M5 glycan. Thelargest significant coefficient for M5 is associated with themain effect of MnCl2, suggesting that MnCl2 had the largesteffect on M5. The heat map also indicates that the maineffects of bothMnCl2 and galactose significantly decrease therelative percentage of the FA2 glycan. The main effects ofMnCl2 and galactose also significantly affect the A2 glycan.However, the signs associated with the significant coef-ficients indicate that while MnCl2 increases the relativepercentage of the A2 glycan, galactose has the opposite effect.Inspection of the significant coefficients also shows thatgalactose supplementation increases the relative abundancesof both FA2G1and FA2G2. NH4Cl supplementation has anapproximately equal effect on the relative abundances of theFA2G1 and FA2G2 glycans as galactose; however, thepresence of NH4Cl decreased the relative abundance ofthese glycans.

Glycan Distribution Variations Result from Changes inGlycosylation Enzyme Transcript Level and IntracellularSugar Nucleotide Concentration

In supplemented cultures, a significant fold difference intranscript level was observed for many glycosylation enzymes(see Fig. 5). As shown in Figure 6, supplementing the culturemedia also altered intracellular sugar nucleotide content.

1962 Biotechnology and Bioengineering, Vol. 111, No. 10, October, 2014

Figure 4. Heat map of the significant factor coefficients (a¼ 0.1) obtained from ANOVA of glycan distribution data of the 23 factorial DoE with media supplements as factors.

Red indicates an increase in the relative percentage of glycan, whereas blue indicates a decrease. The color intensity corresponds to the magnitude of the significant coefficient (a

more intense color indicates a larger coefficient magnitude and thus a comparatively larger effect; conversely, a fainter color indicates with a comparatively smaller effect). The

magnitudes of the significant factor coefficients indicate that M5, FA2, A2, and FA2G1 are the glycans most affected by manganese, galactose, or ammonia. Supplementation with

manganese, galactose, and/or ammonia increased the relative percentage of the M5 glycan. Both manganese and galactose significantly decreased the relative percentage of the

FA2. Manganese increased the relative percentage of A2, whereas galactose decreased A2. Galactose and ammonia also have approximately equal and opposite effects to both the

FA2G1 and FA2G2 glycans.

Figure 3. Heat map of P-values from ANOVA of glycan distribution data obtained from the 23 factorial DoE with media supplements as factors. P-values indicate that all the

glycans studied can be significantly affected by MnCl2, galactose, and/or NH4 Cl.

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Biotechnology and Bioengineering

Using the known enzymatic network for N-glycan synthesisshown in Figure 7, one can hypothesize why the changes toglycosylation enzyme transcript level or intracellular sugarnucleotide content, which are indirectly altered by mediasupplementation, resulted in an increase or decrease in therelative percentage of certain glycans.

Manganese

Supplementing the culture media with 0.04mM MnCl2caused a significant decrease in the relative percentage of theFA2 glycan. Other studies have reported a similar decrease inthe FA2 glycan with MnCl2 media supplementation.However, in these studies, the FA2 decrease was coupledwith increased galactosylation (Grainger and James, 2013;Gramer et al., 2011; Witsell et al., 1990). For the CHO-K1 cellline used in this study, however, the relative percentage ofFA2G1 and FA2G2 decreased by 7� 0.8% and 0.5� 0.05%,respectively, compared to the control (Fig. 2). This decreasein galactosylation was observed despite the upregulation ofgalactosyltransferase expression (see Fig. 5).

Figure 5. Fold difference ð2�DDCt Þ for glycosylation enzyme expression of CHO cells from cultures supplemented with manganese, galactose, and NH4þ compared to control.

Blue indicates gene downregulation, and red indicates gene upregulation. Data shown is the average of two technical replicates. A fold difference threshold of 0.6 was determined

significant via the 95% confidence interval of the house keeping genes. Manganese supplementation decreased expression of GnTI and GnTII, but increased GnTIII expression.

Galactose supplementation increased expression of b-Gal II, III, IV, and UDP-GalT. NH4þ supplementation increased expression of all b-Gal enzymes as well as G6PI.

Figure 6. Relative percentage of intracellular sugar nucleotides extracted from

CHO cell cultures supplemented with manganese, galactose, and NH4þ. Data shown is

the average of sugar nucleotide of technical replicates (n¼ 3), error bars indicate

range. Galactose supplementation significantly increased UDP-Gal concentration

compared to the control.

1964 Biotechnology and Bioengineering, Vol. 111, No. 10, October, 2014

Supplementation with 0.04mM MnCl2 resulted in adecrease in the relative percentages of FA2, FA2G1, andFA2G2, but an increase in the relative percentages of M5, A1,and A2, all of which are glycans upstream of FA2 (see Fig. 2).Noting that N-glycan synthesis is sequential (see Fig. 7), itshould be expected that a decrease in downstream glycanswill be accompanied by an increase in upstream glycans.The increase in relative percentage of M5 and A1 may have

resulted from the downregulation of the associated glycosyl-ation enzymes. GnTI transfers GlcNAc fromUDP-GlcNAc tothe M5 glycan (see Fig. 7). As shown in Figure 5, the GnTItranscript level decreased 1.3-fold with 0.04mM MnCl2supplementation (see Fig. 5). As the first reaction followingM5 formation, lower concentrations of GnTI, which mayhave resulted from the decreased transcript level, may cause

early secretion of IgG with the M5 glycan before the enzymesdownstream in the N-glycan pathway can act upon theglycan. GnTI transcript expression may be rate-limiting sincethe UDP-GlcNAc concentration remained comparable to thecontrol after supplementation with 0.04mM MnCl2 (seeFig. 6). GnTII transcript expression also decreased by 1.1-foldcompared to the control in the presence of MnCl2. Again,GnTII is involved in the first reaction following A1 glycanformation. Therefore, with reduced availability of GnTII inthe Golgi apparatus, IgG with the A1 glycan may have beensecreted before the downstream enzymes could act upon theglycan.The relative percentage of the A2 glycan increased despite

an increase in the expression of FucT transcripts (see Fig. 2and Fig. 5). FucT transfers fucose from UDP-Fuc to A2 to

Figure 7. Schematic of N-glycan pathway. During N-linked glycosylation, a core pentasaccharide, or precursor glycan, composed of mannose and glucose monosaccharides

is synthesized and transferred from a dolicol linked pyrophosphate donor to the asparagine (N) residue of the consensus amino acid sequence, or sequon, of the recipient protein.

Occupation of the sequon (Asn-Xaa-Ser/Thr, where Xaa is any amino acid except proline) with the glycan occurs co-translationally in the endoplasmic reticulum via the action of the

enzyme oligosaccharyl transferase. Once attached, trimming of the glycan occurs by glucosidases and mannosidases located in the endoplasmic reticulum. Further processing of

the glycan occurs in the Golgi apparatus by the sequential addition of monosaccharides such as N-acetylglucosamine (GlcNAc), galactose, fucose, and sialic acid through a series

of transferase reactions which often do not go to completion. The nucleotide sugars used as substrates during N-glycan processing are synthesized in the cytosol and transported

into the Golgi apparatus via specific transporter enzymes. Glycan degradation can occur in the extracellular space post protein secretion. The mechanistic changes caused by

supplementing media with manganese or galactose are highlighted.

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Biotechnology and Bioengineering

form the FA2 glycan (see Fig. 7). The increase in A2 may bedue to the 1.0-fold increase in GnTIII glycan expression.GnTIII transfers a bisecting GlcNAc to various glycans,including the A1 glycan (see Fig. 7).While the A1 glycanwitha bisecting GlcNAc has the same molecular weight as the A2glycan (and thus cannot be distinguished from the A2 glycanvia MALDI-TOF analysis), the subsequent reactions inthe N-glycan pathway may not be able to occur with thepresence of a bisected GlcNAc. As such, an increase in therelative percentage of glycans with bisected GlcNAc couldhave caused the apparent increase in the A2 glycan as wellthe decrease in the relative percentage of FA2 andgalactosylation.

Galactose

The increased galactosylation in the presence of 100mMgalatose supplementation can be attributed to changes inboth enzyme expression and intracellular sugar nucleotidedonor concentration. As shown in Figure 5, supplementingculture medium with 100mM galactose increased thetranscript expression of b-Gal II, b-Gal III, b-Gal IV,and UDP-GalT transcripts. Each galactosyltransferasetransfers Gal from UDP-Gal to various glycans in aspecific manner (see Fig. 7). The increased availability ofthese galactosyltransferases likely resulted in more glycansbeing galactosylated. In addition, as shown in Figure 6,the intracellular UDP-Gal concentration increased by 9%in the galactose supplemented culture compared to thecontrol. Just as important as the increased galactosyl-transferase expression and UDP-Gal concentration, how-ever, may be the 1.8-fold increase in expression of GnTI.The increased expression of GnTI may help to ensure thatthe M5 glycan is acted upon by the enzymes downstreamin the N-glycan synthesis pathway such that theappropriate glycan substrates are available to be acted onby the galactosyltransferases.

Ammonia

The relative percentage of the FA2G1 glycan decreased by5� 0.4% when the culture media was supplemented with10mM NH4Cl 48 h after inoculation. Chen and Harcum(2006) found galactosylation inhibition in the presence ofammonia due to a decrease in the expression of galactosyl-transferases. However, for the CHO-K1 cell line used in ourstudy, the addition of ammonia to the culture increased theexpression of all galactosyltransferases analyzed, except forb-GalTVI (see Fig. 5). Alternatively, Figure 6 does show thatthe intracellular concentration of GDP-Fuc was 20% less inammonia supplemented culture than in the control culture.Also, the media supplemented cultures showed no detectableconcentration of UDP-Gal. Therefore, decreased nucleotidesugar availability may have caused the observed decrease ingalactosylation. As such these data suggest that, for this cellline, the nucleotide sugar concentration may be rate limitingfor galactosylation reactions.

Discussion

We have now identified the media supplements that had asignificant effect on the end-of-run glycan distribution andprovided data that describes the intracellular conditions thatmay be contributing to the observed changes in glycandistribution in the presence of media supplements. It shouldbe noted that only the effects on the end-of-run glycandistribution were considered because the characteristics ofthe final protein are ultimately what is most important forbiopharmaceutical production. To use this information todesign a glycosylation control strategy, the next step is toidentify the controllable modes from the experimentallygenerated glycan distribution data via controllability analysis.The controllable modes indicate which glycans can becontrolled, by how much, and by which media supplements.It is important to identify controllable modes because eachmedia supplement affects multiple glycans simultaneouslybut to different degrees. Identifying the controllable modesprovides a sense of which control objectives are achievableusing MnCl2, galactose, and NH4Cl to induce changes to theglycan distribution.

To perform controllability analysis and identify thecontrollable modes, singular value decomposition wasapplied to the process gain matrix, K (i.e., significantcoefficient matrix obtained via ANOVAof glycan distributiondata as shown in Figure 4) as described in ControllabilityAnalysis section. Singular value decomposition supplies mi

and hi, the orthogonal input and output modes, as well as si,the associated singular values. The magnitude of eachsingular value, si, provides a quantitative measure of therelative extent to which each output mode, hi, is controllableby the associated input mode,mi. As noted in St. Amand et al.(2014), relatively large values of si indicate that thecorresponding mode hi is relatively more controllable (i.e.,perturbations in mi will result in more noticeable changes tohi) than modes associated with smaller values of si. Forpractical applications, a threshold singular value, s�, shouldbe determined and considered the cut-off of practicalcontrollability. For the current application, output modeshi, associated with singular values, si� s� ¼ 1, were consid-ered controllable. The choice of the threshold value s� ¼ 1 issomewhat arbitrary, informed in this specific case by the

Table II. Singular values, si ,

obtained from singular value

decomposition of the matrix of

significant factor coefficients

for glycan distribution.

s1 33.2s2 12.1s3 8.3s4 2.2s5 0.8s6 0.4s7 0.3

Output modes associatedwith singular values si>s� ¼ 1are considered controllable.

1966 Biotechnology and Bioengineering, Vol. 111, No. 10, October, 2014

Figure 8. Graphical representation of the coefficients associated with each glycan in the controllable output modes, hi, and the media supplements comprising the associated

input mode,mi. Modes that were not controllable (i.e., associated with singular values, si< s� ¼ 1) are not shown. Controllability analysis suggests that manganese can be used as a

manipulated variable to increase M5 and decrease FA2 simultaneously, and galactose can be used a manipulated variable to increase FA2G1 and decrease FA2 and A2

simultaneously.While other glycans are affected in output modes h1 and h2, themagnitudes of their coefficients indicate that the changes to the relative percentage of these glycans

will be small compared to the changes observed in the relative percentage of the M5, FA2, FA2G1, and A2 glycans. The singular values associated with h3 and h4 suggest that in

practice these output modes may not be suitable for use in a glycosylation control strategy.

St. Amand et al.: Identifying Manipulated Variables for Glycosylation Control 1967

Biotechnology and Bioengineering

consideration that for those modes associated with si< 1,changes to mi will not produce changes in hi that are largeenough (by comparison) to be of practical consequence in aprocess control scheme. As shown in Table II, only four of theseven singular values are greater than s� ¼ 1, thus indicatingthat only four modes are controllable via supplementingculture media with MnCl2, galactose, and/or NH4Cl.

The composition of input and output modes providesinsight into which control objectives are achievable with thebiological process at hand by identifying which glycans canbe manipulated by which media supplement. Each outputmode hi and input mode mi arising from singular valuedecomposition of the significant coefficient matrix consists ofa weighted sum (or linear combination) of the originalvariables, with the elements of the ith row of the WT or VT

matrix as the weights. How much a glycoform contributes toan output mode, or media supplement contributes to aninput mode, is reflected in the coefficient associated with thatvariable in the linear combination. A dominant contributorto a mode (where one exists) is that variable with the largestcoefficient in the weighted sum. Figure 8 shows the co-efficients of glycoforms comprising each controllable outputmode, hi, and the coefficients of each enzyme and sugarnucleotide donor comprising each associated input mode,mi.

Output mode h1 is associated with the largest singularvalue s1¼ 33.2 and is thus the most controllable mode. Asshown in Figure 8, h1 is co-dominated by the M5 and FA2glycans since the associated coefficients are approximately ofequal magnitude. The associated input, m1, is dominated byMnCl2. Therefore MnCl2 can be used to manipulate therelative percentage of M5 and FA2. However, the co-dominance of M5 and FA2 in h1 indicates that these glycansare coupled in this mode; thus, changes to one glycanwill alsoresult in changes to the other. The opposite sign of thecoefficients indicates that manganese cannot be used todecrease FA2 without also increasing M5.

Output mode h2 is the next controllable mode with asingular value s2¼ 12.1. As with the first output mode, h2 isalso dominated by two glycans; the A2 and FA2G1 glycanshave approximately equal, but again opposite, magnitudes(see Fig. 8). The associated input mode, m2, is dominated bygalactose. Therefore media can be supplemented withgalactose to manipulate the relative percentage of A2 andFA2G1 glycans, but their co-dominance in h2 dictates thatgalactose cannot be used to increase FA2G1 without alsodecreasing A2 and vice versa. This coupling of the glycansmakes sense since A2 is the precursor glycan of FA2G1 (seeFig. 1).

While output modes h3 and h4 are theoretically controlla-ble, in practice these output modes may not be suitable foruse in a glycosylation control strategy. Figure 8 shows thatoutput mode h3 is dominated by the M5, A2, and FA2glycans. However, as was mentioned previously, the relativeabundance of the M5 and FA2 glycans can be controlled bythe h1 output mode and the A2 glycan by the h2 output mode.Output mode h3, which is associated with a singular values3¼ 8.3, is not as controllable as either output mode h1 or h2.

Therefore control strategies using h3 to achieve controlobjectives that aim to manipulate the relative percentage ofeither M5, A2, or FA2 will not be as efficient or effective asstrategies that use h1 or h2. Even if one wanted to achievecontrol of all three glycans simultaneously, a parallel strategywhich employed both input modes m1 and m2 to manipulateh1 and h2, respectively, would likely be more efficient thanusing input mode m3 to control h3.

Also, while output mode h4 is theoretically consideredcontrollable with a singular value s4¼ 2.2, control of h4 viathe associated input mode m4 will be difficult. Output modeh4 is dominated by A1 and A2G1 (see Fig. 8). Thus h4provides control over additional glycans that cannot bemanipulated by using output modes h1, h2, or h3. However,the small singular value indicates that large perturbations inthe input modem4, which may be outside the allowable rangeof values for the process, are required to observe even smallchanges to the output mode h4. Therefore, while analysis ofthe singular values suggests that supplementing the culturewith MnCl2, galactose, and/or NH4Cl can provide fourcontrollable modes with which to manipulate the glycandistribution, further analysis suggests that only two of thefour controllable modes are of practical use when designing aglycosylation control strategy.

To summarize, the controllablity analysis suggests that theachievable control objectives that are practical for this processare as follows: (1) MnCl2 can be used as a manipulatedvariable to increase the relative abundance of M5 anddecrease FA2 simultaneously, and (2) galactose can be used amanipulated variable to increase the relative abundance ofFA2G1 and decrease FA2 and A2 simultaneously. While otherglycans are affected in output modes h1 and h2, themagnitudes of their coefficients indicate that the changesto the relative percentage of these glycans will be smallcompared to the changes observed in the relative percentageof the M5, FA2, FA2G1, and A2 glycans.

Conclusions

This study shows that the glycan distribution of an IgG1produced with CHO-K1 cells can be altered significantlyand reproducibly by supplementing culture media withMnCl2, galactose, and NH4Cl. Thus the results presentedsuggest that control of protein glycosylation is in factpossible in practice. The enzyme transcript expression andintracellular sugar nucleotide data also provide somemechanistic explanations as to why the glycan distributionwas altered as a result of media supplementation. Throughcontrollability analysis the following controllable modeswere identified for this process: (1) MnCl2 can be used tomanipulate the relative abundance of M5 and FA2simultaneously, and (2) galactose can be used to manipu-late the relative abundance of FA2G1, FA2, and A2simultaneously. A long-term implication of this work is thedevelopment of an online control strategy for glycosyla-tion. The next steps to achieving online glycosylationcontrol involve acquiring a method to obtain real-time

1968 Biotechnology and Bioengineering, Vol. 111, No. 10, October, 2014

glycosylation measurements and developing a method tomanipulate the media supplements actively during theprotein production.While design and implementation of a glycosylation

control strategy may not be practical in the short term dueto the remaining technical requirements described above, theresults of this study have immediate implications for mediaand process design. The results presented suggest thatsubstituting glutamate as a nitrogen source instead ofglutamine can increase titer while maintaining a consistentglycan distribution. However, if the process does not yieldprotein with the desired glycan distribution, this workprovides viable manipulated variables to use in changing theglycan distribution. If, for instance, a distribution withgalactosylated glycans is desired, then this study suggests thatculture media should be supplemented with galactose toincrease the relative percentage of galactosylated glycans. Onthe other hand, if one wishes to decrease the relativepercentage of the FA2 glycan while maintaining thepercentage of galactosylated glycans, the culture mediashould be supplemented with both manganese and galactose.Future studies might involve adding media supplements invarious concentrations and at different time points duringculture to determine the trajectory of supplement effects onthe glycan distribution (i.e., to determine whether a mediasupplement effect is linear or non-linear and in what range).Data from such experiments can be used to develop modelswhich in turn can then be used to specify, à priori, mediacomponent concentrations required to produce a mediaformulation that is tailor-made to yield a certain desiredglycan distribution.In addition, the approach of applying controllability

analysis to DoE data can be generalized to determine,quantitatively, the effects of culture conditions on qualityattributes. As such, this work provides a practical method forassessing the effectiveness of various media supplements (orother culture conditions) in producing desired changes to aproduct quality attribute. This work has therefore provided atool that can be used to guide rational media and processdevelopment.

The authors wish to thank Genentech for gifting the cell line used inthis work and Life Technologies for supplying custom media. Theauthors are also grateful for financial contributions from thefollowing grants: NSF-CBET 1034213 and NSF Graduate ResearchFellowship-2008067497.

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Supporting Information

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1970 Biotechnology and Bioengineering, Vol. 111, No. 10, October, 2014