Flow-cytometry and cell sorting: An efficient approach to investigate productivity and cell physiology in mammalian cell factories Niraj Kumar 1 , Nicole Borth ⇑ Department of Biotechnology, BOKU University Vienna, Austria article info Article history: Available online 14 March 2012 Keywords: Flow-cytometry Cell sorting Cell surface capture technology Gel microdrop Cold-capture Cell enrichment Cell proliferation and apoptosis abstract The performance of cell lines used for the production of biotherapeutic proteins typically depends on the number of cells in culture, their specific growth rate, their viability and the cell specific productivity (qP). Therefore both cell line development and process development are trying to (a) improve cell proliferation to reduce lag-phase and achieve high number of cells; (b) delay cell death to prolong the production phase and improve culture longevity; (c) and finally, increase qP. All of these factors, when combined in an optimised process, concur to increase the final titre and yield of the recombinant protein. As cellular performance is at the centre of any improvement, analysis meth- ods that enable the characterisation of individual cells in their entirety can help in identifying cell types and culture conditions that perform exceptionally well. This observation of cells and their complexity is reflected by the term ‘‘cytomics’’ and flow cytometry is one of the methods used for this purpose. With its ability to analyse the distribution of physiological properties within a population and to isolate rare outliers with exceptional properties, flow cytometry ideally complements other methods used for opti- misation, including media design and cell engineering. In the present review we describe approaches that could be used, directly or indirectly, to analyse and sort cellular phenotypes characterised by improved growth behaviour, reduced cell death or high qP and outline their potential use for cell line and process optimisation. Ó 2012 Elsevier Inc. All rights reserved. 1. Introduction The industrially most important application of animal cell technology is the production of biotherapeutics [1,2]. Despite the higher cost incurred by use of mammalian cells, they are indis- pensable for the production of proteins that require complex post-translational modifications such as glycosylation, as these determine both the biologic activity and the immunogenicity of biotherapeutics [3]. Today, worldwide, antibody products account for an annual revenue approaching 100 billion US $, however, other mammalian cell derived products such as growth factors, cytokines or blood clothing factors gain in importance, even though they are still produced at smaller scale [4]. The most frequently used cell line for such recombinant biotherapeutics are Chinese Hamster Ovary (CHO) cells, mainly because of their ability to create hu- man-like glycosylation structures and because of their relative resistance to viral contaminations, an important safety issue with therapeutic products derived from mammalian cells. Despite the dominance of CHO cells as the single most fre- quently used cell factory, there is high diversity in the properties of individual subclones derived from this cell line [5,6]. The pre- dictability and reproducibility of cellular performance of clones as well as the stability of their phenotype with respect to produc- tivity and product quality is limited, which results in a high work- load and lengthy timelines required to select the rare clone with optimal and stable properties, followed by extensive monitoring and documentation during production processes [7]. Both cause substantial cost, delay product development and market introduc- tion and require sophisticated and expensive analyses [8]. As few and typically elaborate methods (such as differential protein or gene expression profiling) are currently available that allow a view into the black box cell and its regulatory network, the most com- mon approach is based on the empirical selection of appropriate cell lines with more stable phenotype by screening a large number of clones (typically several thousands, frequently using automated methods) for high product yield, followed by a more or less arbi- trary testing of culture conditions, build on experience. In view of the diversity observed in recombinant cell lines and even in the individual cells within a clone [6], it is extremely important to use high throughput, single cell analysis methods for the isola- tion of rare variants in phenotype during this clone selection and 1046-2023/$ - see front matter Ó 2012 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.ymeth.2012.03.004 ⇑ Corresponding author. Address: Department of Biotechnology, BOKU University Vienna, Muthgasse 18, 1190 Vienna, Austria. Fax: +43 1 369 7615. E-mail address: [email protected](N. Borth). 1 Current address: Centre for Biodesign and Diagnostic (CBD), THSTI, Gurgaon, India. Methods 56 (2012) 366–374 Contents lists available at SciVerse ScienceDirect Methods journal homepage: www.elsevier.com/locate/ymeth
Transcript
Methods 56 (2012) 366–374
Contents lists available at SciVerse ScienceDirect
Methods
journal homepage: www.elsevier .com/locate /ymeth
Flow-cytometry and cell sorting: An efficient approach to investigateproductivity and cell physiology in mammalian cell factories
Niraj Kumar 1, Nicole Borth ⇑Department of Biotechnology, BOKU University Vienna, Austria
a r t i c l e i n f o
Article history:Available online 14 March 2012
Keywords:Flow-cytometryCell sortingCell surface capture technologyGel microdropCold-captureCell enrichmentCell proliferation and apoptosis
1046-2023/$ - see front matter � 2012 Elsevier Inc. Ahttp://dx.doi.org/10.1016/j.ymeth.2012.03.004
⇑ Corresponding author. Address: Department of BioVienna, Muthgasse 18, 1190 Vienna, Austria. Fax: +43
E-mail address: [email protected] (N. Borth)1 Current address: Centre for Biodesign and Diagn
India.
a b s t r a c t
The performance of cell lines used for the production of biotherapeutic proteins typically depends on thenumber of cells in culture, their specific growth rate, their viability and the cell specific productivity (qP).Therefore both cell line development and process development are trying to (a) improve cell proliferationto reduce lag-phase and achieve high number of cells; (b) delay cell death to prolong the productionphase and improve culture longevity; (c) and finally, increase qP.
All of these factors, when combined in an optimised process, concur to increase the final titre and yieldof the recombinant protein. As cellular performance is at the centre of any improvement, analysis meth-ods that enable the characterisation of individual cells in their entirety can help in identifying cell typesand culture conditions that perform exceptionally well. This observation of cells and their complexity isreflected by the term ‘‘cytomics’’ and flow cytometry is one of the methods used for this purpose. With itsability to analyse the distribution of physiological properties within a population and to isolate rareoutliers with exceptional properties, flow cytometry ideally complements other methods used for opti-misation, including media design and cell engineering. In the present review we describe approaches thatcould be used, directly or indirectly, to analyse and sort cellular phenotypes characterised by improvedgrowth behaviour, reduced cell death or high qP and outline their potential use for cell line and processoptimisation.
� 2012 Elsevier Inc. All rights reserved.
1. Introduction
The industrially most important application of animal celltechnology is the production of biotherapeutics [1,2]. Despite thehigher cost incurred by use of mammalian cells, they are indis-pensable for the production of proteins that require complexpost-translational modifications such as glycosylation, as thesedetermine both the biologic activity and the immunogenicity ofbiotherapeutics [3]. Today, worldwide, antibody products accountfor an annual revenue approaching 100 billion US $, however, othermammalian cell derived products such as growth factors, cytokinesor blood clothing factors gain in importance, even though they arestill produced at smaller scale [4]. The most frequently used cellline for such recombinant biotherapeutics are Chinese HamsterOvary (CHO) cells, mainly because of their ability to create hu-man-like glycosylation structures and because of their relativeresistance to viral contaminations, an important safety issue withtherapeutic products derived from mammalian cells.
ll rights reserved.
technology, BOKU University1 369 7615.
.ostic (CBD), THSTI, Gurgaon,
Despite the dominance of CHO cells as the single most fre-quently used cell factory, there is high diversity in the propertiesof individual subclones derived from this cell line [5,6]. The pre-dictability and reproducibility of cellular performance of clonesas well as the stability of their phenotype with respect to produc-tivity and product quality is limited, which results in a high work-load and lengthy timelines required to select the rare clone withoptimal and stable properties, followed by extensive monitoringand documentation during production processes [7]. Both causesubstantial cost, delay product development and market introduc-tion and require sophisticated and expensive analyses [8]. As fewand typically elaborate methods (such as differential protein orgene expression profiling) are currently available that allow a viewinto the black box cell and its regulatory network, the most com-mon approach is based on the empirical selection of appropriatecell lines with more stable phenotype by screening a large numberof clones (typically several thousands, frequently using automatedmethods) for high product yield, followed by a more or less arbi-trary testing of culture conditions, build on experience. In viewof the diversity observed in recombinant cell lines and even inthe individual cells within a clone [6], it is extremely importantto use high throughput, single cell analysis methods for the isola-tion of rare variants in phenotype during this clone selection and
N. Kumar, N. Borth / Methods 56 (2012) 366–374 367
for characterisation of cellular states during bioprocesses. One ofthe most efficient methods for this purpose is flow-cytometry,which not only allows the rapid and semi-quantitative analysisof several thousands of cells with respect to multiple parameters,but also enables isolation of individual cells with defined charac-teristics by cell sorting [9–12]. This, by focusing only on the mostpromising candidates, will speed up the selection process and re-duce the workload of screening and clone testing. Despite the obvi-ous potential of sorting, one should not forget the benefit of usingflow-cytometry as a tool to analyse and characterise cells and theirbehaviour: the understanding of how the fluorescent signal fromdifferent staining protocols correlates to cellular physiology orchanging culture conditions is the foundation for developing newsorting applications and also provides the user with a powerfultool to integrate the cellular phenotype into process optimisation.This paper therefore first reviews available methods for sorting ofhigh producers and their application in cell line development. Sub-sequently, methods that characterise growth, viability and cellularphysiology are described and their potential application for cellularmonitoring and sorting in the context of bioprocesses discussed.For those protocols that are well established in our lab, detailedprocedures are included, while for others, found in the literatureand with potential applications in this context, we provide the ref-erences and a discussion of their possible use.
2. Individual cell specific productivity
The overall yield of biotherapeutics from mammalian cell cul-tures are directly dependent on the number of cells in culture, theirviability and longevity and on the specific productivity of the cellline used. Cell line development for biotherapeutics is, however,a very tedious and time consuming task, as large numbers ofclones, typically several thousands, need to be tested, due to thehigh variability that is observed. Due to this high work load andthe need to achieve clone selection quickly, most screening pro-grams are based primarily on the identification of cells with highproductivity. The ability of flow-cytometers to analyse a largenumber of cells (up to several million within a few minutes) hasmade it an attractive technique for isolation of rare high producers.An important aspect to consider in all screening and sorting ap-proaches is the fact that typically high producers have lowergrowth rates compared to non-producing cells, so that, eventhough pool enrichment (repetitive sorting of cells representingsimilar phenotype, without subcloning) has its place, ultimatelyfor all sorting methods, it is very important to perform single cellcloning to ensure maintenance of the rare property that one is try-ing to isolate [6,13,14]. Most viable-cell staining methods for pro-ductivity are based on capturing the secreted product in thevicinity of the individual cell that has secreted the product. Theycan be summarised in the following groups: microdrop methods,affinity capture methods and cold capture (Fig. 1) and are comple-mented by methods based on co-transfection with a sort-able re-porter molecule.
2.1. Gel microdrops (GMDs)
This technology is based on creating small and isolated volumesof gel around individual cells that will retain the product secretedby an individual cell. Typically, low-temperature melting biotinyl-ated agarose containing cells in suspension is emulsified in oil toform small droplets aiming for one cell per droplet (gel microdrop).The pores of this gel are of a size that allows proteins (such as theproduct or the capture and staining antibodies) to freely diffuse inand out of the gel unless bound to the matrix. The gel droplets areincubated with avidin, which diffuses into the drops and binds to
the biotinylated agarose. This step is followed by incubation witha specific capture antibody labelled with biotin, which will bindto the avidin residues now in the gel matrix (Fig. 1A). The productsecreted by individual cells will then be bound by these captureantibodies upon release, so that it can be detected and quantifiedby staining of GMDs with another fluorescently-labelled productspecific antibody or antigen (in the case of screening for antigen-specific hybridoma clones). High producers are sorted based onhigher fluorescence intensity. The viable high-producing cells arerecovered from sorted GMDs by allowing them to grow out ofthe matrix or by digestion of the agarose by enzymes. The technol-ogy is universally applicable to any cell line that can survive thistreatment, and for any product for which a compatible pair of anti-bodies exist. It has been successfully used in mammalian systemsto separate secreting from non-secreting hybridomas and low-pro-ducing subpopulations [15,16] and also to enrich for antigen-spe-cific hybridoma cells. The advantage of this method is therestriction on the product diffusion within the gel [11] which pre-vents cross-contamination of non- or low-producing cells with sur-plus antibody secreted by another cell. In addition, the capsuleallows for the creation of many binding sites for product, so thatthere are little limitations for sorting of very highly productivecells.
Gel microdrop protocol [16]:
1. Harvest 2 � 106 cells and centrifuge at 1000 rpm for 5 minat room temperature, discard supernatant and suspendcells in 100 ll of used media (conditioned media).
2. Add 100 ll of pluronic acid solution, 350 ll of biotin conju-gated agarose (commercially available, CelBioGel, from OneCell Systems) and incubate at 37 �C for 5–10 min.
3. Load onto any standard microdrop maker instrument suchas CellSys 101�. Such instruments typically form an emul-sion from oil and aqueous solution of buffer (CelMix™ 200Emulsion Matrix from One Cell Systems) and melted aga-rose added to the glass container. As the emulsion is cooledin an ice water bath, the agarose solidifies to form micro-drops ideally 50 lm s in diameter.
4. Centrifuge sample for 10 min at 2200 rpm to isolate GMDsfrom the emulsion solution.
5. Wash twice with cold PBS, and incubate with streptavidinat 50–100 lg/ml for 10-30 min.
6. Wash off unbound streptavidin with cold PBS and incubatewith biotin-conjugated anti-target antibody (1–50 lg/ml)at 4 �C for 10–30 min.
7. Wash again to remove unbound antibody, transfer intogrowth medium and incubate (37 �C) for a period of timepreviously determined to be sufficient for accumulation ofsecreted antibody within the drop (typically 30–120 min,depending on the specific productivity of the cells).
8. Incubate GMDs with fluorophore-conjugated antibody (1–50 lg/ml) at 4 �C for 10–30 min.
9. Wash GMDs with PBS and analyse using in a flow-cytome-ter according to the size of the microdrop and fluorophore.
Note:
� The concentration of cells and antibodies and incubationtimes may vary between cell lines and therefore mayrequire optimisation.
� There are size restrictions for sorting due to the possibilityof laminar flow disturbances based on the gel microdropsize. A rule of thumb is that the diameter of the sorting noz-zle should be four times the diameter of the GMDs. Thismeans that for 50 lm GMDs a 200 lm nozzle is required.
Cell
Gel Microdrop
Biotin
BAP
Agarose
Avidin
Secreted Product
Capture Antibody
Detection Antibody
Fluorophore
D
C
40C
B
A
Fig. 1. Sorting for cell specific productivity. (A) Gel microdrops (GMDs): molten biotinylated agarose containing a low density cell suspension is emulsified to form smalldroplets aiming for one cell per droplet. A specific ‘capture’ antibody binds to the biotinylated matrix via an avidin linker. Once single encapsulated cells in GMD secreteproduct, it is bound by the capture antibody and is detected by using a second fluorescently-labelled antibody. (B) Affinity capture surface display (ACSD): cells are labelledwith biotin and then with a biotinylated capture antibody via an avidin bridge. These cells are then transferred into high viscosity medium where the secreted product fromthe cells gets attached via capture antibody on the cell surface. The product is then detected by another flourophore-labelled antibody. (C) Secretion and capture technology(SECANT™): cell surfaces are biotinylated and avidinylated. The protein of interest is intracellularly biotinylated by biotin-affinity peptides (BAP), biotin and biotin-ligationenzyme BirA. Once biotinylated product is secreted from the cell, it is captured by the biotin–avidin complex on the surface and is detected using a flourophore-labelledsecond antibody. (D) Cold capture surface display: transfer of cells to low temperature delays the release of protein product from secretion vesicles and facilitates the stainingof proteins on the cell surface using a fluorescently-labelled antibody.
368 N. Kumar, N. Borth / Methods 56 (2012) 366–374
Not all cell sorters are equipped with such large nozzlesand their use requires different instrument settings interms of pressure and vibration frequency and amplitude.Larger drops should be filtered out before sorting to pre-vent clogs in the nozzle. Please consult with your flow-cytometry expert.
2.2. Matrix-aided surface capture
If no specialised equipment for generation of droplets is avail-able and in some cases, where cells have problems growing outof the agarose matrix after sorting, a similar method that createsa capture matrix for the product directly on the surface of the cellscan be used (Fig. 1B and C). It was initially reported by Manz et al.[17] to enable sorting of different types of lymphocytes based ontheir secreted cytokines, and was soon adapted for production celllines [12,17–22]. The advantage of the method is that no specialequipment is required for drop formation and that the cells remaintheir normal size, which means that any standard flow-cytometercan be used for sorting. The disadvantage is the lengthy protocol,which sometimes significantly reduces cellular viability and thelimitation in achievable binding sites for the secreted product.Thus the productivity of very high producing cells may be underes-timated, as product that does not find a binding site on the secret-ing cell will diffuse away and potentially cross-stain other, non-producing cells.
2.2.1. Affinity capture surface display (ACSD)Cells are labelled with biotin, either using a water soluble bio-
tinylation reagent (which may cause a significant loss of viability)or using a biotinylated protein that binds to the cell surface, suchas the lectin Concanavalin A. Cells are then either tagged directlywith an avidinated capture antibody or via an avidin bridge to a
biotinylated capture antibody (Fig. 1B) [18]. Use of avidin linkermaximises the binding capacity of the matrix (avidins have fourbinding sites for biotin). Cells are transferred into high viscositymedium, i.e. containing gelatine and incubated. The high viscosityrestricts the diffusion of product and hence facilitates substratecapture on the cell surface. The product bound to the cells is thendetected by a flourophore-labelled second antibody. It is importantto note that once all binding sites attached to the cell are occupiedby secreted product, no further increase in the fluorescence signalis possible, so that, if cells are incubated for too long, the signal ob-served does not reflect the specific productivity any more: as mostcells, even lower-producing ones will reach this state after longincubation periods, it becomes impossible to differentiate high-and low-producers. Thus the saturation time of each cell linesneeds to be determined to ensure that the maximum fluorescentsignal is not yet attained when sorting.
ACSD protocol [18]:
1. Wash 1 � 106 cells in PBS.2. Incubate for 15 min at room temperature in 200 ll PBS con-
taining 1% polyvinylpolypyrrolidone (for saturation) and50 lg/ml biotinylatedsuccinyl-Concanavalin A.
3. Wash in 10 ml medium.4. Incubate for 10 min on ice in 200 ll PBS containing 1 mg/ml
avidin or streptavidin.5. Wash in 10 ml PBS.6. Re-suspended in 200 ll of a 1:10 dilution of anti-product
antibody, biotin conjugate in medium.7. After 10 min on ice incubate for 10–30 min (depending on
expected productivity) at 37 �C.8. Wash with 10 ml cold PBS.9. Re-suspend in 200 ll of a 1:20 dilution of anti-product anti-
body, fluorescently labelled in PBS containing 3 lg/ml DAPI.
N. Kumar, N. Borth / Methods 56 (2012) 366–374 369
10. Incubate for 30 min at 4 �C.11. Analyse and sort.
Note:
� DAPI is added as a very sensitive indicator of cell viability.Three subpopulations are typically observed: cells that areclearly labelled and show cell cycle like distribution (deadcells, exclude from analysis); cells that have no fluores-cence (highly viable cells, use for gating and include in sortgate); cells with fluorescence intensities in between theabove (compromised cells, likely to not grown into colo-nies, exclude from sorting).
� For all sorting purposes: never use a gate that is based on asingle fluorescence histogram, as this will not represent theinfluence of cell size on the total fluorescent signal. Prefer-entially use a dot plot of a size related parameter such asforward scatter width vs. the fluorescence signal of interest.Design gates as shown in Fig. 2.
2.2.2. Secretion and capture technology (SECANT™)With GMD and ACSD, it is difficult to display proteins without
binding activity or to isolate medium- to low-affinity binding anti-bodies (Kd < 10 nM) due to their fast off-rates. Also these methodscannot be used to screen for production of proteins against whichno antibody for capture is available. A method described to over-come these limitations that can be used without any prior knowl-edge of the protein is called SECANT™ [12]. In this approach, thecell surface is biotinylated by incubating with NHS-PEG-biotinand then avidinylated. The protein of interest is expressed with avector that fuses a biotin-affinity peptides (BAP) and an acTEV pro-tease cleavage site to the N-terminus of the gene of interest. Theprotease cleavage site allows later removal of the fused part fromthe produced protein. After translation the biotin-affinity peptideon the protein is biotinylated by the intracellular enzyme BirA
Fig. 2. Design of sorting gates that account for cell size: smaller cells, for instancethose that are in G1-phase during staining, will have less binding sites on thesurface to catch the secreted product. Also on a per biomass basis, they will secreteless absolute amount of product. A gate that only uses the fluorescent signal as asingle parameter will enrich for cells that are either larger (potentially tetraploid) orin G2/M-phase. So as to identify those cells that have the highest relativeproductivity, a gate is drawn from a dot plot of a size related parameter (hereFSC-Width) and the fluorescent signal (here a Phycoerythrin conjugated antibody).
(Fig. 1C). Upon secretion, it is then captured by the avidin residuesattached to the surface of the cell so that it can be detected by aflourophore-labelled second antibody. Detailed protocols and dis-cussion of the potential use can be found in [12].
2.3. Cold-capture method
In 1990 it was observed that for some hybridoma cells, there is acorrelation between the fluorescent signal obtained by stainingproducer cells with an anti-product antibody and their specificproductivity [23]. For a long time it was assumed that this iscaused by presentation of the antibody on the cell membrane sim-ilar to the presentation of antibodies observed in B-cells. However,in 2003, Brezinsky and co-workers showed that this correlation isalso true for recombinant CHO cell lines [24]. Finally, Pichler andco-workers showed in 2009 that the fluorescent signal observedis based on a reaction similar to immunoprecipitation caused bythe locally high concentration of product and staining antibodiesat the sites of fusion of secretory vesicles on the cell surface [25].The fluorescent signal obtained was observed to correlate to thecell specific production rate of cells [25]. The method is simpleand quick, again is universally applicable for any product for whicha labelled antibody exists and gives a reasonably good, even if notperfect correlation to productivity. It has been used in several in-stances for the selection or enrichment of higher producing sub-clones, both for stable cells lines and after transient transfection[13,22,27].
Cold-capture protocol [25]:
1. Harvest 2 � 106 cells producing a recombinant or endogenousproduct and centrifuge at 1000 rpm for 5 min at room temper-ature, discard the supernatant and wash with PBS at 4 �C.
2. Resuspend cells in the corresponding volume of cold PBS+ 1%polyvinylpolypyrrolidone (for saturation) containing fluoro-phore-labelled anti-product antibody (1:10).
3. Incubate sample for 30 min in the dark.4. Analyse cells using standard flow-cytometer according to the
fluorophore used.
Note:
� The concentration of cells and antibodies and incubationtimes may vary with different cells and antibodies andtherefore may require optimisation.
2.4. Expression of marker proteins
An alternative method is based on the co-expression of eitherfluorescent or non-fluorescent reporter proteins with the productgene or gene of interest. For this the cells are transfected with aplasmid designed to bear the reporter gene in addition to the geneof interest. Generally, the expression of reporter genes shows goodcorrelation with the recombinant protein production [28]. Theexpression of these reporter genes is usually kept lower than theexpression of the gene of interest, to reduce the synthetic burdenon the cell [29] and to select only for the highest producers. Thiscan be achieved for instance by using a defective promoter, leakystart codon or a bi-cistronic vector with the marker gene posi-tioned behind the product gene. Reporter genes used may be GFPor a combination of GFP and YFP in the case of a product consistingof two genes such as antibodies [30], or proteins that localise to thecell surface and that can be stained with a fluorescently labelledantibody, such as CD4 or CD20 [28,31,32]. Cells are then sortedbased on the fluorescent signal of the marker protein, under the
370 N. Kumar, N. Borth / Methods 56 (2012) 366–374
assumption that the expression of the gene of interest will corre-late. These methods require that careful planning of the vector con-struct is done already before transfection, so that they cannot beused for sorting of already existing cell lines.
Recently, these methods have attracted renewed interest, how-ever, as the expression of reporter genes also enables the selectionof integration sites at transcription hot spots that can be used forsite directed homologous recombination with the gene of interestusing recombinase enzymes [33–35]. The site of integration ofthe product gene into the genome contributes significantly to theproductivity of the resulting cell lines [34]. It is hoped that devel-opment of cell lines tagged with recombination markers at suchhot spots will reduce the screening effort required for stable cellline development in the future [35], as many of the properties ofthe final cell line have to be screened for only once. With a highproducer with advantageous properties established, the markergene can then be replaced by new genes of interest to yield pro-ducer cell lines. This site directed integration will allow to generaterecombinant cells without severe genomic rearrangements.
3. Characterisation of growth and cellular metabolism
The yield of recombinant protein products at the end of a pro-cess is determined by two parameters: the cell specific productiv-ity and the integral of viable cells during the process. Thus theability of cells to grow fast and to high cell densities as well as theirability to remain viable as long as possible is of prime importancefor the economic success of a production process. The importanceof characterising the metabolic and growth properties of recombi-nant cell lines becomes more evident if one considers the fact thatover the last 20 years an increase in process yields from 0.5 g/l toreliably 5 g/l was achieved. This increase was mostly due to opti-misation of processes and media which resulted in higher cell con-centrations, while the specific productivities of the cell lines useddid not change much [36]. In addition, several reports show thatcell specific productivities can be directly related to growth. Forexample, it was shown that growth arrest by temperature shift in-creases the production of various recombinant proteins [26,37].Such arrested cells typically do not show any preference in tran-scription and/or translation of the protein of interest over othercellular proteins [38], but rather they have overall more activetranscription, translation and protein assembly which increasestheir total protein output including the protein of interest. In thiscontext flow cytometry can be used for two approaches: on theone hand, its ability to describe population characteristics suchas viability or metabolic activity can be used to analyse the stateof cells during process optimisation, so as to achieve conditionsthat allow cells to grow to high densities and to remain viableand actively producing for as long as possible. In addition, someof these methods can be used to isolate rare phenotypic variants,for instance with a more efficient metabolism or higher growthrates [58].
In the following we therefore present a selection of methodsthat describe the growth behaviour and metabolism of cells.
3.1. Measurement of cellular viability
Cellular viability is typically used to describe the state of cells inculture to optimise process conditions and nutrient feed. Ideallysuch analyses are able to detect not only the fact that cells aredead, but also whether they are already in a stressed and compro-mised state, so that countermeasures can still be taken. The mostfrequently used methods in this context are analysis of membranepermeability and apoptosis.
3.1.1. Membrane permeabilityMost methods for analysis of cellular viability are based on an
assessment of membrane permeability. Leaky membranes are con-sidered a determining factor of cell death, while already compro-mised membranes, unable to maintain membrane potential or toperform the transport processes required for homeostasis, are con-sidered to be a sign of severe cellular stress that will likely lead tocell death. DNA stains are used frequently for this purpose, as theytypically cannot enter through intact membranes, so that viable,intact cells remain unstained while dead cells with leaky mem-branes become fluorescent. The most commonly used dyes for thispurpose are propidium iodide (PI) and DAPI. The use of DAPI hasseveral advantages: DAPI is excited by UV light and also emits atlower wavelength, so that there is no interference between thefluorescent signal obtained from DAPI and the signal from othercommonly used fluorophores, which typically are excited by a488 nm laser. On the other hand, the requirement for a UV laseris the most significant block on the frequent use of DAPI. Uptakeof DAPI follows two stages: compromised cells with still intactmembranes take up low amounts of DAPI, while dead cells takeup large amounts. We have found, however, that already the com-promised cells with low uptake have significantly reduced cloningefficiency, so that for sorting purposes we usually exclude all, evenlow DAPI stained cells. Alternatively, propidium iodide can beused, which is excited by the 488 nm laser and has a broad emis-sion spectrum, which may interfere in multiparameter analyses.
Viability staining protocol
1. Harvest 2 � 105 cells and centrifuge at 1000 rpm for 5 min atroom temperature, discard supernatant and suspend cells in100 ll of used media (conditioned media).
2. Stain cells and measure fluorescence as given below.
DAPI:� Concentration range used: 1–5 lg/ml.� Excitation: UV, maximum at 360 nm.� Emission: 420–530 nm, maximum 460 nm.
Propidium iodide:� Concentration range used: 1–5 lg/ml.� Excitation: 488 nm.� Emission: 580–720 nm, maximum at 630 nm.
Note:
� All DNA stains are highly cancerogenic, use extreme cau-tion in handling and disposal.
3.1.2. ApoptosisApoptosis is one of the most frequent mechanisms by which
cells dye in culture. Once this process is initiated, there is no turn-ing back for a cell, so that it is committed to dye, even if this is notyet observable from the outside. Thus cells that have started theprocess of apoptosis, but have not yet completed it, will appear via-ble by the membrane integrity methods described above, so thatanalysis of apoptosis in addition to viability allows an earlierassessment of stress in a culture, even though for those cells thathave started the process it may be too late.
Annexin-VIn healthy viable cells, phosphatidyl serine (PS) is located on the
cytoplasmic side of the cell membrane. However, in apoptotic cells,this orientation is lost, so that some of the PS is translocated fromthe inner to the outer leaflet of the plasma membrane [39]. The hu-man anticoagulant, annexin V, is a 35–36 kDa Ca2+-dependentphospholipid-binding protein that has a high affinity for PS [40].
N. Kumar, N. Borth / Methods 56 (2012) 366–374 371
Therefore, annexin V labelled with a fluorophore can identify apop-totic cells by binding to PS exposed on the outer leaflet [41]. Theviable cells remain unlabelled and non-fluorescent. To date, differ-ent fluorophores conjugated to annexin V are available commer-cially. This method can therefore be combined with otherstaining methods, including immunofluorescence of surface pro-teins and membrane integrity. The most frequent combination iswith propidium iodide to differentiate between live, apoptoticand dead cells (Fig. 3).
Annexin V – propidium iodide staining protocol:
1. Wash 2–5 � 105 cells in 1 ml binding buffer (25 mM HEPES,140 mM NaCl, 1 mM EDTA, pH 7.4), include three samplesfor control, best taken of the sample with the highestexpected number of apoptotic cells.
2. Resuspend unstained control cells in 200 ll binding buffer.3. Resuspend annexin V control cells in 200 ll binding buf-
fer + 4 ll annexin V-FITC conjugate.4. Resuspend propidium iodide control cells in 200 ll binding
fer + 1:1000 propidium stock solution + 1:50 annexin V-FITCconjugate) for all samples.
6. Resuspend samples in 200 ll staining buffer.7. Incubate for 15 min at room temperature.8. Set flow-cytometer instruments settings using the unstained
control, so that cells are in the lower left corner.9. Use annexin-V and propidium iodide controls to set com-
pensation, such that there is no signal overlap fromannexin-V to PI or vice versa.
10. Run samples and analyse as described in Fig. 3.
Note:
� If cells are cultivated in medium that contains serum, additionalwashing steps may be required.
Fig. 3. Analysis of apoptosis using annexin V and propidium iodide: unstained cellsin the lower left corner are viable (V). Apoptotic cells with intact membranes, butstained by annexin V, can be observed in the lower right quadrant (A), while deadcells with permeable membranes are in the upper right quadrant (N). Normally nocells should be in the upper left quadrant, as all dead cells, whether they died byapoptosis or necrosis, will bind annexin V.
Mitochondrial permeability transitionThe loss of mitochondrial membrane potential (DY) is a hall-
mark for apoptosis and has been used to identify apoptotic or deadcells. The dye JC-1 (5,50,6,60-tetrachloro-1,10,3,30-tetra-ethylbenz-imidazolyl-carbocyanine iodide) exists in the cytosol as a mono-mer (green emission light) and accumulates as aggregates (redemission) in mitochondria with active membrane potential in liveand intact cells. The two wavelengths are measured as a ratio,which corrects for difference in the number and size of mitochon-dria in individual cells. During cell death/apoptosis, the electro-chemical gradient across the mitochondrial membrane collapsesdue to the formation of pores in the mitochondria by dimerisedBax or activated Bid, Bak, or Bad proteins, followed by the releaseof cytochrome-c into the cytoplasm [42,43]. As a result, the mem-brane potential of the mitochondria breaks down, and the redemission of JC-1 is lost.
1. Prepare JC-1 stock solution in DMSO or DMF (typically at theconcentration of 0.5–5 mg/ml).
2. Harvest cells and centrifuge at 1000 rpm for 5 min at room tem-perature. Discard the supernatant and resuspend cells in usedmedia (conditioned media) to achieve 1–2 � 106 cells/ml.
3. Add 0.5–5 lg/ml dye to the sample and incubate at 37 �C for10–20 min.
4. Detect fluorescent signal at ex/em = 510/527 nm (green)and585/590 nm (red). Also measure the ratio of both fluores-cences (green/red) to distinguish between viable and apoptoticcells.
3.2. Measurement of cell growth and division
As already mentioned, the growth of cells during a productionprocess is a major factor determining the overall yield of product.Cells with higher growth rate may take less time to achieve maxi-mum biomass. The growth of cells is determined by their ability toinitiate and complete a cell cycle and to divide. This is typicallyanalysed by measuring the DNA content of individual cells in thepopulation and calculating a percent distribution of the cell cyclephases or by following the number of division that happen to indi-vidual cells over time. Applications of these methods for processoptimisation are further discussed in (4).
3.2.1. Cell cycleThe analysis of cellular DNA content is one of the most direct
measurements of the current growth state of cells. This is espe-cially true for adherent cells where the arrest in G1 phase uponreaching density inhibition is almost complete. In cells grown insuspension, especially in immortalised and disregulated cell linessuch as hybridoma cells or suspension adapted CHO cells, this isunfortunately not the case, as these cells in our experience willcontinue to grow until they die, so that, even under severe nutrientlimitation and already decreasing viability, there will still be a sig-nificant number of cells found in S-phase and G2/M phase. Never-theless, even for these cells, the percentage of cells in G1-phasewill increase upon growth arrest, for instance after temperatureshift. The more commonly used methods for cell cycle analysisuse propidium iodide, a dye specific for double stranded nucleicacids, including DNA and RNA (most of the RNA in cells typicallyforms hairpin loops and therefore is double stranded). Thus, tobe used for cell cycle analysis, cells need to be treated by RNAse,which makes the method more cumbersome and time consuming.The fastest and simplest method for cell cycle analysis, and onethat also gives the best results in terms of quality of the cell cycle
372 N. Kumar, N. Borth / Methods 56 (2012) 366–374
histogram, is the use of DAPI in a mild detergent solution. DAPIspecifically binds to AT rich regions, which are not present inRNA, so that no RNAse treatment is required. Using this method,a cell cycle histogram can be generated within 10 min from sam-pling. This makes the method suitable as an online measurementtool for process monitoring.
Cell cycle analysis protocol:
1. Harvest cells and centrifuge at 1000 rpm for 5 min at roomtemperature. Discard the supernatant and suspend cells indetergent buffer (0.1% Triton X-100, 0.1 M Tris HCL, 2 mMMgCl2, pH 7.4) containing 3 lg/ml DAPI to achieve 1–2 � 106 cells/ml. Alternatively add same volume of 2� buf-fer directly to sample.
2. Detect fluorescent signal at ex/em = UV/424 nm.
3.2.2. Analysis of division ratesThe division rate of cells can be analysed using a number of dif-
ferent techniques. Most of these are based on either labelling intra-cellular proteins (for instance carboxyfluorescein diacetatesuccinimidyl ester CSFE) or membranes (PHK or long-chain dialkyl-carbocyanines such as DiL) with a stable fluorophore that is not de-graded or shed by the cells and is passed on equally at half the leveleach to daughter cells after division. The concomitant dilution en-ables the history of cells to be followed over several divisions. Fordetails on the methods and their evaluation, we refer the readerto the excellent review by Wallace et al. [45]. These methods couldbe used to evaluate the growth potential of individual cells and tosort for faster growing cells under defined culture conditions, orto analyse growth behaviour in a bioprocess retrospectively (seeSection 4).
3.3. Cellular physiology and metabolism
In addition to cellular growth and division, the physiologicactivity of cells and the level of stress they experience are impor-tant parameters to evaluate for process optimisation. The mostimportant cellular stress observed in cells in culture is oxidativestress, caused by radicals generated during energy generation inthe mitochondria. Methods for its analysis are described below.Another type of stress observed in production cell lines is unfoldedprotein response (UPR), however, unfortunately, there are cur-rently no specific flow cytometric methods available for this typeof stress, except for general measurements of the size of ER orimmunofluorescent staining of ER-resident, stress indicating pro-teins such as BiP or other chaperones. In addition to these stressindicators, the general uptake rate of nutrients has been relatedto cellular efficiency and the ability of cells to achieve higher finalcell densities and better viability [57,58,68]. An example for mea-surement of nutrient uptake rates by flow cytometry is thereforediscussed in Section 3.3.2.
3.3.1. Reactive oxygen species (ROS) and oxidative stressROS are chemically-reactive molecules containing oxygen such
as oxygen ions [singlet oxygen & superoxides (SOx)], free radicals,and peroxide. They are highly reactive due to the presence of un-paired valence and electrons and are natural by-products of oxida-tive phosphorylation or energy production in the mitochondria.ROS has been identified as a major contributor to aging related cel-lular damage, especially to DNA by inducing the oxidation of bases[46–48]. ROS could also lead to oxidative modifications of proteinsand lipids resulting in the loss of their biological function and ulti-mately directing them to degradation [48]. Protection against suchoxidative stress is achieved via the glutathione (GSH) system [46].
GSH, a tripeptide (glutamate-cysteine-glycine), is an integral oxi-dant scavenger which reacts as either a one-electron donor to rad-icals or a two-electron donor to electrophiles to neutralise them. Itis present in all mammalian cell types. ROS and GSH have been re-ported to be involved in regulation of cell proliferation in cultureand therefore have also been associated with various growth re-lated disorders, such as cancer [49]. As ROS and SOx are directlyassociated with the energy metabolism of cells and with oxidativestress, they can be considered important indicators of cellular stateand growth potential.
Protocol for ROS according to [50]:
1. Harvest cells and centrifuge at 1000 rpm for 5 min at roomtemperature. Discard the supernatant and suspend cells inused media (conditioned media) to achieve 1–2 � 106 cells/ml.
2. Add 20 lM 20,70-dichlorodihydrofluorescein diacetate(H2DC FDA) dye to the sample and incubate for 30 min atroom temperature.
3. Detect fluorescent signal at ex/em = 495/529 nm.
Note:
� The concentration of dye, time and temperature of incubationcould be cell line specific and therefore may requireoptimisation.
Protocol for SOx according to [50]:
1. Harvest cells and centrifuge at 1000 rpm for 5 min at roomtemperature. Discard the supernatant and suspend cells inused media (conditioned media) to achieve 1–2 � 106 cells/ml.
2. Add 20 lM dihydroethidium (DHE) dye to the sample andincubate for 30 min.
3. Detect fluorescent signal at ex/em = 518/605 nm.
Note:
� The concentration of dye, time and temperature of incubationcould be cell line specific and therefore may requireoptimisation.
Protocol for GSH according to [51]:
1. Harvest cells and centrifuge at 1000 rpm for 5 min at roomtemperature. Discard the supernatant and suspend cells inused media (conditioned media) to achieve 1–2 � 106 cells/ml.
2. Add 10 lM monochlorobimane (MCB) dye to the sampleand incubate at room temperature for 10–30 min.
3. Detect fluorescent signal at ex/em = 350/424 nm.
Note:
� The concentration of dye, time and temperature of incubationcould be cell line specific and therefore may require optimisation.
3.3.2. Single cell glucose uptake ratesMammalian cells in culture, and especially transformed and
immortalised cell lines, are characterised by an inefficient energymetabolism and typically convert �80% of the available glucoseto lactate [52]. To compensate for the inefficient energy gain fromglucose, mammalian cells are fed high concentrations of glucose
N. Kumar, N. Borth / Methods 56 (2012) 366–374 373
and glutamine, resulting in the accumulation of lactate and ammo-nia, which in turn can cause a lower final cell concentration andproduct titre [53]. Cultivation of cells at lower nutrient concentra-tions results in a metabolic shift to a more efficient utilisation ofsubstrates and thus decreased waste product levels [54–56]. Cellspecific glucose uptake rates are correlated to the glucose concen-tration in the media, but may vary between cell lines [57,58]. Theiranalysis could therefore also be used to assess the energy efficiencyor state of cells during bioprocesses and clone development.
The most frequently used dye for this purpose is a fluorescentlylabelled glucose analog, 2-(N-(7-nitrobenz-2-oxa-1,3-diazol-4-yl)amino)-2-deoxyglucose (2-NBDG). For details on protocolsplease refer to Yamada et al. [59] or Zou et al. [60].
4. Process monitoring and optimisation using flow-cytometry
Recently, several examples were published that use automatedflow-cytometric analyses online as a tool for process monitoring toevaluate the cell physiology in production cultures. Such onlinemonitoring of the culture enables to record cell behaviour in theculture in real-time and thus offers the potential to establish feed-back loops in process control that are based on cellular behaviourand respond to changes in culture condition, thus resulting in opti-mised process control and higher product yields [61–63]. Alongwith automation, this also minimises the required analytical workto be performed at-line, so that personnel and the risk of manualerrors are reduced. Sitton and Srienc connected a flow-cytometeronline (automated and real-time) with a bioreactor to sampleand analyse the DNA distribution (cell cycle analysis), viable cellconcentration, apoptotic cell concentration, and light scatteringproperties every 25 min over 4.5 days in response to nutrientdeprivation and nutrient upshift [62]. Feeding cells at nutrientdepletion was reported to restart cell proliferation by release ofcells from nutrient mediated G1-phase arrest. This suggests thatthe investigation of cell-cycle distribution and/or perturbationsfollowing addition or deletion of specific nutrient(s) could be usedto identify those media components that play a role in the regula-tion of cell-growth and thus to improve culture media and feedstrategies.
Brogner et al. [61] described the establishment of a Flow Injec-tion Flow Cytometer directly coupled to a bioreactor to assess thepopulation average intensity as well as the distribution of a GFP-tagged product protein, to assess the heterogeneity of productexpression in cell lines and the response of cells to process changeswith respect to productivity. The system was tested with yeast andbacteria, however its transfer and use with mammalian cells shouldbe simple.
With the above described online testing tools, flow cytometrymethods that look at cellular growth characteristics together withproductivity and the use of this information for process controlshould become an important contribution to process analyticaltechnologies PAT as required by the regulatory authorities [63].Especially the use of methods described in Section 3 should enablea more in depth look on the physiologic and metabolic state ofcells, which will be complemented with more mechanistic analy-ses of cellular processes using transcriptome and metabolome. To-gether these methods will in the near future increase ourunderstanding of the needs of cell factories and thus lead to furtherimprovements in product titre. The importance of flow-cyto-metryin this context is its ability to analyse the distribution ofparameters within a population, which will enhance the awarenessof process engineers of the fact that cells in culture, even if clonal,will not behave in a homogeneous way, as each individual cell hasslightly different gene expression patterns and therefore also dif-ferent responses to the environmental conditions encountered[61,65,66]. While the above mentioned transcriptomic and meta-
bolomic analyses yield results as population averages, single-cellfluorescence intensities of most parameters measured by flow-cytometry are typically distributed over a broad range within thepopulation, which explains some of the unpredictability and vari-ance observed between processes even of the same cell line.Flow-cytometric on-line measurements of the state and physiolog-ical response of cells that are integrated into the regulatory systemof a process will reduce this variance and ultimately lead to morereproducible processes that enable maximal productivity, whilereducing the number of processes that have to be discarded be-cause they did not fall within the required design space [67].
5. Conclusion
Due to the ease of measuring cellular productivity even fromsmall scale cultures such as microtiter plates, most screening pro-grams still use qP as the only selection parameter in their earlystages, despite the already mentioned fact that historicallyimprovements in process yields were mostly due to changes inprocess and media design. All other process and product relevantparameters are typically tested later, at larger scale, which meansthat those cell lines that perform best in the early test stages,which usually occur in static culture without optimisation, aera-tion or control, may not be the ones that perform best in the finalbioprocess [64]. Using combinations of the methods described inthis review, both for productivity and growth related parameters,will help to obtain a more complete picture on how individual cellswill perform under bioprocess conditions. Such predictions on pro-cess relevant performance will reduce the number of clones thathave to be carried along and tested, by making possible a more tar-geted, knowledge based rejection of unsuitable cell lines and theretention of the truly best performers. In addition, the amount ofwork and handling required will be further reduced if these meth-ods are also used for sorting. We have for this reason, with fewexceptions, focused on methods that keep cells viable throughoutthe staining process. Even though so far few publications describethe use of multi-parameter analyses with respect to combining forinstance cell specific productivity with metabolic rates or physio-logical status of cells, we claim that this will change in the near fu-ture, as more studies become available which demonstrate theirbenefit.
As a perfect combination of different process relevant properties(such as energy efficiency, qP and growth) is necessary for an opti-mal production clone, the development of such multiparameterprocedures is of obvious importance for the biopharmaceuticalindustry, both in terms of development timelines and economicsuccess. Flow-cytometry and cell sorting offer enormous potentialand will in the future contribute to isolate just the right cell type fas-ter and more reliably.
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