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Issues in Plant Cell Culture Engineering for Enhancement of Productivity.

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Dev. Chem. Eng. Mineral Process. 13(S/6), pp. S73-587, 2005.
Issues in Plant Cell Culture Engineering for
Enhancement of Productivity
Mohd A. Abdullah''2*, Nordin H. Lajis2, Abdul M. Ali',
M. Marziah2,Anthony J. Sinskey3 and ChoKyun Rha4
Department of Biotechnology and 'Phytomedicine Laboratory,
Institute of Bioscience, Universiti Putra Malaysia, Serdang, 43400,
Selangor,
Department of Biologv and 4BiomaterialsScience and Engineering
Laboratory, Massachusetts Institute of Technology, Cambridge,
Massachusetts 02139, USA
Plant cell culture is seen as an alternative source to whole plants for the production
of useful compounds, such as dyes, pharmaceuticals, perjiumes and insecticides.
Despite intensive research for the last 30 years, only a fac, products have reached
commercial production in bioreactors, and the number is far less than those
commercialized for bacterial and animal cells. Several biological challenges
including slow cell growth, low productivity, compartmentation, metabolite
channelling and poor metabolite secretion have hampered the realization of
commercialization of plant cell products. Other engineering and technological
problems include cell aggregation, plant cell shear sensitivity, foaming and lack of
automation. Several strategies are being explored to improve productivity including
medium optimization and cultural conditions, and the understanding of biochemical
and signal transduction pathways. In plant cell culture process development, there is
a great need to explore a more rational approach through metabolic and genetic
engineering by making use of advanced technologies in genomic, transcriptomic,
proteomic and metabolomic analyses. These should be integrated with developments
in bioprocess and systems engineering.
Introduction
The plant kingdom possesses a very large diversity in relation to biochemistry, thus
leading to a large number and many types of molecular structures that can be
synthesized [ 11. This versatility provides a wide scope for plant engineering including
food for human, feed for animals, fibers, fuels, pharmaceuticals and feedstocks for the
* Author for correspondence;current address: Department of Chemical Engineering,
Universiti Teknologi Petronas, Bandar Seri Iskandar, 3 I 750, Tronoh, Perak,
Malaysia (azmuddin@petronas.com.my).
573
M.A. Abdullah, NH.Lajis, A.M. Ali, M.Maniah, A.J. Sinskey and C.K. Rha
chemical industry [2]. Plant-derived drugs and intermediates, for example, account for
approximately US$9-11 billion annually in the USA [3]. Most of these
pharmacologically active plant products are secondary metabolites which are not
necessarily essential for growth but are often beneficial to the symbiotic relationships
between producer plants and their environment, such as in defence systems against
insect, h g a l or herbivorous attack. It is the possibility of using this broad capacity
for synthesis of high-value natural products that has provided the impetus behind
developments in plant cell and tissue culture technology over the last two decades [4].
These metabolites are of low-to-medium molecular weight and are structurally
complex with multiple chiral centres that determine biological activities [5]. This
complexity and the need to attain high stereochemical purity makes chemical
synthesis sometimes uneconomical. However, the natural heterogeneity of whole
plant material, coupled with variations in product content and supply, complicate the
design of product recovery systems from field-derived plants. Therefore plant cell
culture is seen as an alternative due to its independence from environmental factors,
homogeneity of the material produced and absence of significant amounts of
pigments, leading to a more consistent product quality and yield, and a more defined
production system [6].
Despite the high hopes and considerable research activities over the past 30 years,
the commercial exploitation of plant cell culture still lags behind microbial,
mammalian and insect cell culture. A few products have reached commercial stage of
production, for example, shikonin by Lithaspermum etythrorhizon in a 750 L stirredtank and 1000 L rotating drum bioreactors (Mitsui Chemicals, Japan); saponins by
Panax ginseng in a 25,000 L stirred-tank bioreactor (Nitto Denko, Japan);
polysaccharides by Polianthes iuberosa in a 4000 L stirred-tank bioreactor (Kao
Corp., Japan); and taxol by Taxus species, in a 20,000 L stirred-tank bioreactor
(Samyang Genex, S. Korea). Technological feasibility of large-scale plant cell
cultures has been demonstrated in Germany where a 75,000 L stirred-tank bioreactor
is being used for the production of biomass by Rauwolfia serpentina. Panax ginseng,
Echinuceaepurpureu (Diversa) and taxol by Taxus chinensis (Phyton Inc.) [7].
Challenges and Economic Issues
Plants are metabolically more complex than heterotrophs, as exhibited by the plant
pathways and control architectures [2]. There is a lack of sophisticated technology to
deal with this complexity, coupled with difficulties in plant process scale-up, high
production costs in comparison to those derived from the wild or field-cultivation,
small demand for plant-based high-value products, the instability of productive celllines and low product yield [ti]. Table 1 shows that the productivity of a number of
plant ceIl cultures has reached levels approaching those for some microbial processes,
particularly antibiotics. However, many of these highly productive plant cell cultures
are not targeted for commercialization.
There are major differences between plant cells and microbial cells that affect
bioreactor design and the process economics, including cell size and aggregation, cell
growth rates and batch-cycle times, culture age, inoculum age and density, foaming
and wall-growth, shear sensitivity, rheological properties, metabolic activity and
oxygen demands, product yield and titers, nature of product accumulation, and mode
of bioreactor operation. A shift towards commercialization depends partly on the
5 74
Issues in Plant Cell Culture Engineering for Enhancement of Productivity
development of a high-degree of automation for routine, large-scale processing of
plant cell production systems [8].However, technological feasibility alone is not
enough as it is the overall market size or price of the compound and its demand that
will eventually govern the success (or otherwise) of attempts to develop commercial
processes. There are three market considerations that would dictate the selection of
potential targets for commercialization via plant cell and tissue cultures [9].These are
(1) the issue of natural versus synthetic product; (2) the positioning of the
biotechnology-based product versus the existing products; and (3) the relationship
between the product value and the expected annual usage.
Table 1. Comparison of productivities among different plant cell suspension and
microbial cultures.
Natural product
Cell-line
Rosmarinic acid
Berberine
Rosmarinic acid
Anthraquinones
Shikonin
Podoverine
Anthraquinones
Anthocyanin
Anthocyanin
Sanguinarine
Berberine
Diosgenin
Penicillin'
Citric acid'
Monosodium glutamate'
Coleus blumei
Coptisjaponica
Salvia officinalis
Morinda elliptica
Lithospermum erythrorhizon
Podophyllum versipelle
Morinda elliptica
Perilla fnrtescens
Vitis species
Papaver somngerum
Thalictmm minus
Dioscorea species
Penicillium species
Aspergillus niger
Colynebacterium glutamicum
Source: Adaptedfiom [ll] and [lZ];
Productivi&
(g L-' day-')
0.91
0.60
0.22
0.21
0.15
0.15
0.14
0.12
0.06
0.034
0.03
0.028
1.4- 2.1
30 - 38
53 - 67
' is a microbialproduct.
Figure 1 presents a generalized plot that may be used to select candidates for
production via plant cell culture. The area above the curve indicates the region of
economic feasibility, whilst anything closer to the curve may require a more detailed
economic analysis in terms of manufacturing costs, risks and time-frame estimations,
including the costs of research and development leading to commercialization [9].The
best product candidates are those of high value (US%500-1000kg-') and yielding a
revenue of about 12 cents L-'day-' [3].
5 75
M.A. Abdullah, N.H. Lajis, A.M. Ali, M. Maniah, A.J. Sinskey and C.K. Rha
1000 i
100 :
10
'
I 'uL*''
' ' 'n''''' '
'""'U
' ' -"'
'
' """'
' '
lLLI
Figure 1. A generalized plot on the relationship between product value and volume
(Adaptedfiom [lo]).
Strategies to Enhance Productivity
Several parameters are suggested that may cause low productivity (< 0.02 g L-' day-')
of plant cell cultures, e.g. slow growth rate (< 0.1 day-'), low cell concentration
(< 10 g L-I), and low product yield (< 0.5 g L-') [13]. If overall economic viability is
to be achieved, improvements should be made by focusing on key areas of overall
processes [6], namely:
1. High cell growth rate. Long average generation times (normally 3-4 days,
about 15 hours in the minimum case) and low maximum concentration of
intracellular metabolites (less than 10% dry weight normally, 36% dry weight
in the maximum case) render metabolites from plant cell cultivation expensive.
2. High biomass level (> 40 g L-')and lugh volumetric yield (> 1 g L').
Several strategies to achieve these can be applied through biological and technological
approaches.
(0
Nutritional, Physiological and Environmental Factors
To accelerate plant cell process optimization, screening of culture conditions and
suitable culture methods for high-yielding cell-lines and high-quality inoculum, must
be employed. This would reduce development times and ensure that only the best
possible candidates are chosen for optimization before further process evaluation.
Using intermediary (G) and production (P) medium strategies where cells are grown
in the former before being inoculated into the latter, can elevate anthraquinones
production in Morinda elliptica from 2-6 mg g-' DW to 80-100 mg g-' DW [12]. We
envisage an intermediary medium rather than growth medium (where cells are grown
5 76
Issues in Plant Cell Culture Engineeringfor Enhancement of Productivity
to a maximum [ 6 ] ) or conditioned medium (where cells are pre-conditioned or
acclimatized with the spent medium [ 141) to introduce the concept of transition period
between maintenance (M) and production (P) medium. Cells are grown for a short
period of time before a fraction of the culture being inoculated into P medium. With
this comes the flexibility that intermediary medium can be different from M and P
medium, and G medium on its own together with the duration of transition period or
its combination with regards to M and P medium, can be subjected to optimization.
As shown in Figure 2 and Table 2, with this strategy it is possible to achieve high dry
cell weight and high production capacity together, but at the expense of cell growth
rate. The same strategy applied to Centella asiatica cell cultures for triterpenoids
production, however results in induction of other compounds, potentially stressrelated, and not triterpenoids [15]. Hence, no single approach is a panacea, as it
depends on species, cell-line and compounds of interest.
60
--
50
;-1
,M 40
2
.-M 30
2.
Q
20
10
0
A
0
2
LG
4
- - + - -DP
5
7
-
9 I I 13 15 16 18 21 24
Time (days)
W-DG
-36LM
+LP
Figure 2. Profile of dry cell weight and anthraquinones titre of 18 month-old
M. elliptica cell cultures in maintenance (M),intermediary (G) and production (P)
medium strategies under 1200 lux illumination (L) or in the dark (0).
577
M.A. Abdullah, N.H. Lajis, A.M. Ali, M.Maniah, A.J. Sinskey and C.K. Rha
Table 2. Kinetics data of biomass and anthraquinoneproduction of 18-month old
M. elliptica cell cultures in M, G and P medium under illumination of 1200 lux (L)
and in the dark (0).
I
I I . Biomass
Xmcu
(g L-')
r, (g day“)
A I M (day-')
td (days)
Yds, (g g suc'')
2. Anthraquinones
p m a (mg g"DW)
pmcu (g L -9
Overall r, ( g L %iv-'l
(g g-'daY-')
YP/*,.,(g g suc-l)
l?P
LM
LG
DG
LP
DP
18.2
2.27
0.309
2.2
0.56
54.8
5.54
0.322
2.2
0.68
49.0
4.47
0.261
2.7
0.60
58.8
3.52
0.218
3.2
0.73
59.7
3.53
0.145
4.8
0.74
2.26
0.021
0.002
7.23
0.38
0.021
0.0004
0.005
13.6
0.65
0.031
0.0006
0.008
52.9
2.92
0.139
0.0024
0.037
80.4
4.48
0.213
0.0036
0.056
0.0001
0.001
1
Secondary metabolites could either be constitutive metabolites or phytoalexins. In
the case of phytoalexins, regulation of defence mechanisms and stress signals could
be used as a means to increase secondary metabolism in plant cell culture. We have
shown that different stages of cell growth cycle and medium strategies not only
results in different level of anthraquinones, but also hydrogen peroxide level, lipid
peroxidation and antioxidant vitamins [ 161. The addition of autoclaved Aspergillus
awamori and A. flaws h g a l homogenates, yeast extract, jasmonic acid and silver
nitrate as sources of biotic and abiotic elicitors, enhanced both anthraquinone
production and excretion in M. elliptica cell culture, though cell growth may be
retarded depending on elicitor concentration and day of elicitor treatment.
(ii) Integrated Bioprocess and Systems Engineering
(a) General requirements
For large-scale high density plant cell culture, there are challenges associated with
rheological behavior, shear sensitivity, nutrient limitation, decreases in specific
productivity, gas composition and "crowding effect" [17]. The large cell size, rigid
cell wall, and large vacuoles make plant cells shear sensitive. Efficient mixing is
essential, using appropriate impeller design, correct agitation speed and the right
bioreactor configuration. This must be attained without compromising the need for
even distribution of nutrients, a homogeneous cell suspension, and heat and gas
transfer. To overcome foaming and wall-growth, different strategies that have been
applied include bubble-free aeration, anti-foaming agents and bioreactor wall
coatings, medium strategies or mechanical-foam breaking system [6].
5 78
Issues in Plant Cell Culture Engineeringfor Enhancement of Productivity
(b) Types of culture system
High-density plant cell cultures over extended periods can be attained through fedbatch or perfusion culture and/or immobilization techniques. A two-stage fed-batch
process can be utilized whereby in the first stage rapid cell growth takes place but
minimal production, and in the second stage minimal cell growth but high product
formation [ 181. Pefision culture has been used for plant cells with potentially higher
density than fed-batch [19]. Cells are retained in a retention device, and the specific
growth rate is manipulated by adjusting the flow rate of the bleed stream. With
constant supply of fresh nutrient and broth removal, nutrient-limiting condition or byproducts inhibition can be removed efficiently at high perfusion rates without cell
washout. With an immobilization technique, aggregate geometry of the cells is
controlled. There is evidence that intentionally aggregated plant-cells may enhance
production of secondary metabolites, possibly due to cell-to-cell contact and
differentiation [3,20]. The three main types of immobilization that can be applied are:
adsorption of cells onto various support materials; covalent attachment of cells to
substrates using coupling agents such as glutaraldehyde; and cell entrapment using
alginate, polyurethane foam or confiiement behind semi-permeable membranes.
(c) Product recovery
The strategy for continuous use of whole cell biocatalysts depends upon the nature of
product accumulation. Many plant cell secondary products are either stored
intracellularly in the vacuole or other organelles, or are released extracellularly but
bound to the cell wall. Cells can be permeabilized by chemical, enzymatic or physical
treatments to induce outward diffusion of relevant products while cells remain viable.
Enzymes such as lipases and Pluronic F-68 surfactant interact with some of the
phospholipids in the membrane double layer, resulting in a brief or “reversible
perforation” of the tonoplast, without releasing the toxic wastes that could cause
damage [21]. Another approach is to carry out continuous or discontinuous recovery
while the culture is actively growing. In siiu removal of an extracellular product can
promote product release presumably by preventing feedback mhibition, or in the case
of adsorbents by providing an extra storage compartment. Two-phase cultures can be
applied where one phase is aqueous medium and the second phase is either a waterimmiscible organic solvent, such as n-hexadecane, or solid adsorbents such as ion
exchange resins (Amberlite) and the neutral polymeric resins XAD-4 and XAD-7.
Combined treatments of chitosan, calcium alginate immobilization and in situ
adsorption via Amberlite XAD-7 in Plumbago rosea cell cultures has been reported to
increase the yield 21 times of plumbagin production at 92.1 mg g-’ DW [22].
(d) Process monitoring and control
Bioprocesses are non-linear, time-dependent, and challenging for control and
instrumentation because of the genetic and enzymatic control mechanisms involved
[23]. Traditional plant cell batch culture involves predetermined set points for culture
variables, prescribed formula of medium, off-line gas analysis of events and changes
in cell status, and preset and predicted timing for the cell cycle beginning and
termination. These are based on empirical observations of cell culture performance
5 79
M.A. Abdullah, N.H.Lajis, A.M. Ali, M. Maniah, A.J. Sinskey and C.K.Rha
disregarding the direct cause and effect relationships between disturbances in
variables and changes in metabolite yield [8]. Furthermore, the evaluation of culture
performance is often far-removed in time from the actual event due to lack of sensors
that could detect cellular-events and process-state on-line. An ideal situation would
allow the operator to alter bioreactor parameters in prompt response to shifting
environmental and cellular signals [8]. There are issues in gathering information on
the quality of this environment through reliable physical, chemical and biochemical
sensors; in dealing with highly non-linearity of cultivation through estimation
techniques, set-point optimization, optimal trajectories, adaptive control and design of
special control algorithms; and methodology of automation through modeling,
simulation, identification and data acquisition [24]. In the biotechnology industry,
there are trends towards knowledge-based models, expert systems and application of
neural networks in product design, formulation and manufacturing, process
monitoring, diagnosis, modeling, control and optimization [23]. A knowledge-based
process control regime is based upon developing a database that chronicles data and
experience on biological characteristics of the process, and the integration of more
sophisticated sensors. The actual state of the bioprocess is provided by sensor
information which is then compared with the control “blueprint”. The knowledgebased controller then changes the time course of the process to meet a process target.
(e) Image processing
Image processing or machine vision has been developed and applied to provide a
more accurate, sensitive and non-destructive method for measuring growth in cell and
tissue culture, and for quantitative assessment and pattern recognition analysis of cell
characteristics [25, 261. Machine vision (video-image analysis) is used in the study of
secondary metabolites of plant cells (especially pigmented or pigment-associated
compounds) as an image analysis system to extract process knowledge from the
image and measurements, in order to monitor and control the bioprocess [8].
Computer imaging captures visible cellular information in digital form, and provides
more subtle and in-depth detail for possible measurement and for the decision-making
process. Successful commercialization of processes from plant cells eventually
necessitates the ability to control and optimize the overall process scheme. This
requires that all stages of the process described earlier be examined together [27], and
the systems can then be engineered to optimum capacity.
(iii) Metabolic and Genetic Engineering
(a) Rational approach
Whilst many strategies are devised on an ad hoc and an empirical basis, metabolic
engineering is an emerging discipline attempting to look at productivity enhancement
from a rational point of view. It is defined as targeted improvement of cellular
activities to generate new types of producing cells by making use of modem methods
of molecular biology, physiology, bioinformatics, computer modeling and control
engineering. Metabolic engineering comprises a synthesis step that introduces new
pathways and genetic controls; an analysis step aiming at elucidating the properties of
metabolic reaction networks in their entirety; and the rigorous evaluation of the
580
Issues in Plant Cell Culture Engineeringfor Enhancement of Productivity
physiological state of resulting recombinant cells via metabolic flux determination
[28]. It emphasizes integration and systems-based analysis of biosynthetic pathways
and metabolism by addressing the questions of pathway synthesis, reaction and/or
transport bottlenecks, thermodynamic feasibility, pathway flux distribution and flux
control, identification of targets for modification and evaluation of the resulting
cellular phenotype.
(b) Plant metabolic engineering
The advantages of plant metabolic engineering are the potential for the rational design
of quantity and distribution of secondary metabolites in plant cell and tissue cultures,
the ability to transfer enzymes (hence metabolites) to species that previously lacked
them, relatively rapid transformation compared to plant, and expression of an enzyme
in a specified amount, tissue and subcellular location. Among successhl metabolic
engineering applications to plant secondary metabolites are change of flower colors
and coloration of tobacco chromoplasts and nectarines, modification of carotenoid
pathway in “golden rice” project, down-regulation of lignin synthesis, conversion of
hyoscyamine into scopolamine in Atropa belladonna, and the production of
polyhydroxybutyrate (PHB) in Arabidopsis thaliana [5,29].
Plant metabolic engineering has developed more slowly than microbial metabolic
engineering. Hanson and Shanks [2] outline four reasons for plant metabolism to be
inherently harder to engineer: (1) plants are built to run on supplies of water, C02and
light rather than as heterotrophic culture; (2) different types of plant cells and organs
not only compete but are also dependent on each other, so that changes of flux in one
will affect the other; (3) intracellular compartmentation which include chloroplasts,
mitochondria and cytosol may cause metabolic pathways to occur in one or more
compartments, or metabolic reaction starting in one compartment and ending in
another, leading to issues of redundancy and intracellular transport processes; and (4)
plant biochemistry is less well explored than microorganisms, and many plant
enzymes needed for engineering have yet to be cloned and characterized. There are
various other issues related to plant metabolic engineering such as reversible and
irreversible reactions, feedback regulation, product degradation, multiple routes to
end-product, low amount of enzymes, transformation procedures, selectable markers,
components of the transgene and gene silencing [5, 301. Most of the strategies
developed for new product formation, reduction or overproduction of a metabolite in
plant cells involve either introduction of heterologous genes isolated from more
efficient organisms; or blocking a product or pathway via anti-sense or co-suppression
techniques; or overexpressing an endogenous enzyme by promoters that enhance the
expression of a target gene [29].
(c) Metabolic control and flux analysis
To identify elements controlling the regulation of the entire pathway, kinetics of
individual reactions and network properties must be analysed by expressing all
aspects of flux control through experimentally measurable quantities; and assessing
productivity improvements and flux redistribution as a result of perturbations.
Metabolic flux control can be determined by dividing the entire metabolic network
58I
M.A. Abdullah, N.H.Lajis, A.M. Ali, M.Maniah, A.J. Sinskey and C.K.Rha
into small number of reaction blocks producing and consuming a common metabolite,
and using group control coefficients to describe the degree of control exercised by
each group of reactions [31]. Flux quantification can be divided into measured
quantities of enzymes and model-based metabolite measurements. The most widely
adopted approach for estimating flux-limiting steps is the measure of timing, kinetics
and localization of enzyme activities [5]. It is done using mass-balance techniques by
measuring the rate of change of substrate disap earance and product accumulation,
and by determining the flow of a label (either C or I3C), In situ determination of
metabolic fluxes is the most important step in an establishing experimental basis for
rational analysis and evaluation of the dynamics of metabolic networks. However,
quantification of metabolic fluxes in plants has met with some problems due to slow
measurement of the rate of change of compound, and the requirement for
experimental systems capable of quantifying compounds reliably over long-term
culture conditions [32]. NMR methods, both spectroscopy and imaging, can be used
to detect, identify, quantify and localize novel metabolites in vivo and in extracts; to
reveal the composition and physical state of cell wall and other polymers; to identify
active pathways and monitor non-invasively temporal concentrations of several
intermediates in primary metabolic pathway at the same time; to provide quantitative
measures of metabolic flux; determine independently certain fluxes; confirm massbalance estimates and elucidate split ratios; and test the hypotheses about the effects
of engineered traits on plant physiological function [32,33].
Another approach to metabolic flux analysis is to use mathematical modeling and
computation. The availability of substrates and energy molecules is determined by an
analysis of overall mass and energy balances for the whole reaction network, and the
stoichiometric model based on plant metabolism is developed. Assuming pseudo
steady-state conditions, if a suficient number of metabolites is measured then the flux
for all reactions can be calculated [ 5 ] . However, because of a large number of
metabolically active compartments and non-steady-state conditions, transient isotopic
flux analysis and kinetic modeling approaches are widely applied in
compartmentalized, dynamic metabolic systems in order to address metabolic flux
responses to environmental and genetic perturbations in plant metabolism [34]. Whilst
metabolic control analysis will continue to assist in understanding the quantitative
distribution of flux control, synergy between experiments and mathematical
methodologies could discover creative methods for controlling the distribution of flux
by genetic or environmental means, and therefore assists in analyzing complex
systems, or calculating expected responses of metabolism to genetic modifications,
and identifjmg the most promising targets for metabolic engineering [5,34].
E
(d) Functional genomics and proteomics
For the study of plant functional genomics, effectiveness relies on high-throughput
techniques for measuring the mRNA (the transcriptome), protein (the proteome) and
metabolite (the metabolome) components of plants as well as their organs and tissues
[35]. DNA microarrays for studying gene expression on a large scale and protein
microarrays for profiling of proteins encoded by differentially expressed cDNA
clones, provide novel approaches to enzyme identification and pathway elucidation
through systematic analysis of proteins expressed by the genome [36]. However,
582
Issues in Plant Cell Culture Engineeringfor Enhancement of Productivity
generation of transgenic and mutant plants and multiparallel analyses of mRNA and
proteins alone, do not provide direct information about how a change in mRNA or
protein is coupled to a change in biological function. Thus metabolite profiling, in
combination with genomic methodologies, provide some answers by defining
precisely the biochemical function of plant metabolism, and elucidating a direct link
between gene sequence and the function and regulation of the metabolic network in
plants [37].
The advent of genome databases, protein databanks and other databases
containing unprecedented detailed information about biological systems changes the
landscape of biological research. The combination of computational biology and
expression-based analysis of large amounts of sequence information emerge as
powerful tools for gene discovery and characterization. A shift from mechanisticbased models to data driven models is a direct consequence of the rapidly increasing
database size. Whilst the former is the outcome of reductionist research prescribing
focused experiments and generating specialized data, the latter attempt to identify
homogeneous subsets of data with similar characteristics, capture discriminating
features, and pattern recogmtion that can be used for sequence identification, function
assignment or process diagnosis [38]. Efforts toward large-scale quantitative
measurement of mRNA transcript levels using DNA micromays, small metabolite
intermediates and protein level and activity, could generate data of unprecedented
completeness about all levels of cellular function and aid dramatically the analytical
approach of metabolic engineering [28]. With continued developments in isotopic and
kinetic modeling, quantification of metabolite exchange between compartments, and
transcriptional and post-transcriptional regulatory mechanisms governing enzyme
level and activity could enable simulation of large sections of plant metabolism under
non-steady-state conditions [34].
Future Directions
Bioprocess and cell culture engineering have moved slowly but steadily from an
empirical art, from mainly knowing-how, to a science of knowing-why of culture
behaviour [39]. Figure 3 shows the issues that need to considered by bioprocess and
cell culture engineers when attempting a rational approach to productivity
enhancement. The need to consider cells and organisms as hugely complex systems
requires an understanding of metabolic pathway analysis, metabolic engineering and
systems biology. Very powerful monitoring tools which include semi-online analyses
of culture broth such as high performance liquid chromatography (HPLC), gas
chromatography (GC) or flow injection analysis (FLA); as well as non-invasive
methods such as midrange infrared (IR), Raman and capacitance spectroscopy and
on-line reaction calorimetry, enable engineers to understand and explain
quantitatively the cellular activities on a metabolic basis. Studies on functional
genomics and proteomics now permit genome-wide exploration of transcriptional and
expression profiles based on advances in microarray technology, capillary
electrophoresis, 2D-gel electrophoresis, mass spectrometry and bioinformatics, which
could assist prediction of relevant features of metabolome and Buxome [28, 33, 34,
35, 37, 381. As well as the tools for analyses of metabolites and gene expressions,
there is also strong development in miniaturized analytical devices which could
583
M.A. Abdullah, N.H. Lajis, A.M. Ali, M.Maniah, A.J. Sinskey and C.K.Rha
reduce reagents, but more importantly for rapid sampling and to reduce sample
consumption by improving analytical speed through shortening of analysis time or by
running several analyses in parallel [40]. In combination with the development of
optical sensor technology, the low-cost microbioreactor has become increasingly
relevant for the investigation of biological kinetics and for high-throughput evaluation
of the effects of operational or nutritional parameters on cell growth and product
formation in a systematic and statistically significant manner [41,42].
For the plant system in particular, much work remains to investigate the large
number of pathways leading to valuable plant secondary metabolites. Knowledge of
product biosynthesis needs to be enhanced in the area of site of biosynthesis,
compartmentation, and the temporal and spatial regulation of enzymes, genes and
metabolites. There is a need for continued improvement of transformation
technologies and development of molecular biology tools that allow controlled gene
expression in multiple systems, use of selective markers to allow greater numbers of
genes to be inserted to plants, and bioinformatics tools to identify targets for cloning.
Microbioreactor for High-throughput
Bioprocessing
Environmental I Genetic
Perturbation
Miniaturized Analytical Assay
Functional Cenomics
(Genome, Transcriptom,
Proteome, Metabolome,
Fluxome)
>-b
Stoichiometric Modelling
(Metabolic Flux Analysis)
Kinetlcs analysis
Validation
(Metabolic Control Analysis)
Product separation
and recovery
Online and Semi-Online
Control and Monitoring
Figure 3. Issues in bioprocess and cell culture engineering.
584
Issues in Plant Cell Culture Engineeringfor Enhancement of Productivity
Better techniques need to be developed for flux quantification using various
metabolite labeling techques, and genetic alterations, to provide greater insight into
metabolic regulation [5, 30, 321. There is a strong need to make plant cell
cryopreservationa routine protocol by establishing a master and working cell-bank, as
currently practiced in bacterial and animal cell culture. New approaches which have
been explored include low-cost bioreactors with a reduction of on-line controls and
probes; growing entire plants with sterile roots for recovering recombinant proteins;
growing photosynthetically-active plants supplemented with mineral-based medium
in aeroponic or hydroponic conditions; and shoot and hajr-root cultures for more
genetically-stable material [29].
Conclusions
The breakthrough required in order to reach an industrial accomplishment for
products from plant cell, tissue and organ cultures lies in multidisciplinary and multidimensional approaches. It is necessary to integrate engineering know-how with cell
physiological, biochemical, molecular biological and genetic approaches. Engineers
and scientists of many disciplines must share their expertise to tackle the problems
associated with the complexities of plant metabolism, so that commercialization
becomes a reality.
Acknowledgments
The authors would like to thank the Ministry of Science, Technology and
Environment of Malaysia for funding the research work camed out in Universiti Putra
Malaysia under IRPA programme (Grant No. 03-02-04-0046), and in the
Massachusetts Institute of Technology (MIT), USA under Malaysia-MIT
Biotechnology Partnership Programme (MMBPP).
Nomenclature
Maximum dry cell weight (g L-')
Maximum anthraquinone content (mg g-' DW) or titre (g L-I)
Maximum specific growth rate (day-')
Maximum specific production rate (g g-' day")
Doubling time (day)
Overall cell growth rate (g L-' day-')
Overall production rate (g L-' day-')
Biomass yield to sucrose consumed (g g suc-I)
Anthraquinone yield to sucrose consumed (g g suc-')
Litre
Dry cell weight
585
M A . Abdullah, N.H.Lajis, A.M. Ali, M.Marziah, A.J. Sinskey and C.K. Rha
References
I.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
IS.
16.
17.
18.
19.
20.
21.
22.
586
Fowler, M.W., and Stafford, A. 1991. Plant cell culture, process systems and product synthesis. In:
Fowler, M.W., Warren, G., and Moo-Young, M. (Eds), Plant Biotechnology: Comprehensive
Biotechnology. Pergamon Press, LJK, pp.79-98.
Hanson, A.D., and Shanks, J.V. 2002. Plant Metabolic Engineering - Entering the S Curve. Metabolic
Engineering, 4: 1-2.
Sajc, L., Grubisic, D., and Novakovic, G.V. 2000. Bioreactors for plant engineering: an outlook for
further research. Biochemical Engineering Journal, 4: 89-99 (and literatures cited therein).
Taticek, R.A., Moo-Young, M., and Legge, R.L. 1991. The scale-up of plant cell culture: Engineering
considerations. Plant Cell Tissue and Organ Culture, 24: 139-158.
Morgan, J.A., Rijhwani, S.K., and Shanks, J.V. 1999. Metabolic Engineering for the production of
secondary metabolites. In: Lee, S.Y., and Papoutsakis, E.T. (Eds) Mefabolic Engineering, Marcel
Dekker, Inc.,New York, 325-351.
Abdullah, M.A. 1999. Establishment and Bioreactor cultivation of Morinda elliptica cell cultures for
the production of anthraquinones. PhD Thesis, Universiti Pum Malaysia (and literatures cited
therein).
Shuler, M.L. 2000. Overview of plant cell bioreactors, Paper presented at the Bioreactor Workshop,
23-24 May, Massachusetts Institute of Technology, USA.
Smith, M.A.L., and Reid, J.F. 1996. Machine Vision and Automation in Secondary Metabolite
Bioprocess Control, In: DiCosmo, F., and Misawa, M. Planf Cell Culture Secondary Metabolism,
CRC Press, Florida, USA, pp.53-77.
Sahai, 0. 1994. Plant Tissue Culture. In: Gabelman, A. (Ed.) Bioprocess Production of Flavor,
Fragrance and Colour Ingredients. John Wiley, New York, pp.239-275.
Goldstein, W.E. 1986. Economic factors in relationship to specialty chemical products by biocatalysis.
Biotechnol. Bioeng. a m p . , 17: 763-776.
Scragg, A.H. 1995. The problems associated with high biomass levels in plant cell suspensions. Planf
Cell, Tissue Organ Culture,43: 163-170.
Abdullah, M.A., Ali. A.M., Maniah, M.. Lajis, N.H., and Ariff, A.B. 1998. Establishment of cell
suspension cultures of Morinda elliptica for the production of anthraquinones. Plant Cell, Tissue
Organ Culture, 54: 113-182.
Atkinson, B., and Mavituna, F. 1991. Biochemical Engineering and Biotechnology Handbook. Second
edn (pp.365-446). New York.
Woragidbumnmg, K.. Sae-Tang, P., Yao, H., Han, J., Chauvatcharin, S., and Zhong, J.J. 2001. Impact
of conditioned medium on cell cultures of Panar notoginseng in a n airlift bioreactor. Process
Biochemistry, 37: 209-213.
Abdullah, M.A., Gorret, N., and Oppenheim, S. 2001. Cell growth, triterpenoids production and
induction of potentially stress-related compounds in Cenfella asiatica cell suspension culture. A
research report submitted to the National Biotechnology Directorate for Natural Product Discovery
Subprogramme under Malaysia-MIT Biotechnology Partnership Programme, Kuala Lumpur,
Malaysia.
Chong, T.M., Abdullah, M.A., Nor'Aini, M.F., Lai, O.M., and Lajis, N.H. 2003. Anthraquinone
production, Hydrogen peroxide level and antioxidant vitamins in Morinda elliptica cell suspension
cultures from intermediaryand production medium strategies. Plant Cell Report. 22: 951-958.
Taticek, R.A., Lee, W.T.C., and Shuler, M.L. 1994. Large scale insect and plant cell culture. Current
Opinion in Biology, 5: 165-174.
Matsubara, K., Yamada, Y., Kitani, S., Yoshioka, T., Morimoto, T., and Fujita, Y. 1989. High density
culture of Copfisjaponica cells increases berberine production. J. Chem. Tech. Biotechnol., 46: 61-69.
Su, W.W. 1995. Bioprocessing technology for plant cell suspension cultures. Applied Biochemistry
and Biofechnology, 50: 189-230.
Lindsey, K., and Yeoman, M.M. 1985. Immobilized plant cell culture systems. In: Neumann, K.H.,
Barz. W., and Reinhard, E. (Eds) Primary and Secondary Mefabolism of Plant Cell Cultures,
Springer-Verlag, Berlin, pp.304-3 15.
Bassetti, L., and Tramper, J. 1995. Increased anthraquinone production by Morinda citrijblia in a twophase system with Pluronic F-68, Enzyme Microbial Technol., 17: 353-358.
Komaraiah, P., Ramakrhisna, S.V.,Reddanna, P., and Kavi Kishor, P.B. 2003. Enhanced production
of plumbagin in immobilized cells of Plumbago rosea by elicitation and in sifu adsorption. J.
Biotechnol., 101: 181-187.
Issues in Plant Cell Culture Engineeringfor Enhancement of Productivity
23. Baughman, D.R., and Liu, Y.A. 1995. Neural Networks in Bioprocessing and Chemical Engineering.
Academic Press, New York.
24. Pons, M. 1992. Bioprocess Monitoring and Control, Hanser Publishers, New York.
25. Olofsdotter, M. 1993. Image processing: a nondestructive method for measuring growth in cell and
tissue culture. Plant CellRepori, 12: 216-219.
26. Miyanaga, K., Seki, M., and Furusaki, S. 2000. Quantitative determination of cultured strawbeny-cell
heterogeneity by image analysis: effects of medium modification on anthocyanin accumulation.
Biochemical Engineering Journal, 5: 201 -207.
27. Vieth, W.R. 1994. Gene expression with plant cells. Bioprocess Engineering, 265-324.
28. Stephanopoulos, G., and Stafford, D.E. 2002. Metabolic Engineering: A new frontier of chemical
reaction engineering, Chemical Engineering Science, 57(14): 2595-2602.
29. Bourgaud, F., Gravot, A., Milesi, S., and Gontier, E. 2001. Production of plant secondary metabolites:
a historical perspective, Plant Science, 161: 839-851.
30. Lessard, P.A., Kulaveerasingam, H., York, G.M., Strong, A., and Sinskey, A.J. 2002. Manipulating
gene expression for the metabolic engineering of plants. Metabolic Engineering, 4: 67-79.
31. Stephanopoulos, G., and Sinskey, A.J. 1993. Metabolic Engineering Methodologies and future
prospects, TIBTECH, 11: 392-396.
32. Shanks, J.V.. Rijhwani, S.K.,Morgan, J.A.. Vani, S., Bhadra, R., and Ho, C.H. 1999. Quantification
of metabolic fluxes for metabolic engineering of plant products, In: Fun, T.J., Singh, G., Curtis, W.R
(Eds) Plant Cell and Tissue Culture for the Production of Food Ingredients, Kluwer Academic,
Plenum Publishers, New York, pp.45-60.
33. Shachar-Hill, Y. 2002. Nuclear Magnetic Resonance and Plant Metabolic Engineering. Metubolic
Engineering, 4: 90-97.
34. Morgan, J.A., and Modes, D. 2002. Mathematical modeling of plant metabolic pathways. Metabolic
Engineering, 4: 80-89.
35. Oliver, D.J., Nikolau, B., and Wurtele. E.S. 2002. Functional genomics: High-throughput mRNA,
protein and metabolite analyses. Metabolic Engineering, 4: 98-106.
36. Han, Y.S., der Heijden, R.V., and Verpoorte, R. 2001. Biosynthesis of anthraquinones in cell cultures
of Rubiaceae, Plant Cell, Tissue and Organ Culture,67(3): 201-220.
31. Fiehn, O., Kopka, J., Dormann, P., Alhnann, T., Trethewey, R.N., and Willmitzer, L. 2000.
Metabolite profiling for plant functional genomics, Nature Biotechnology, 18: 1157-1161.
38. Stephanopoulos, G. 1999. Emerging directions in computer applications to biotechnology: Upgrading
the information content of biological data. Annual Reviews in Control, 23: 61 -69.
39. von Stockar, U., Valentinotti, S., Marison, I., Cannizzaro, C., and Herwig, C. 2003. Know-how and
know-why in biochemical engineering, Biotechnology Advances, 21 : 41 7-430.
40. Guijt-van Duijn, R.A., Moerman, R, Kroon, A., van Dedem, G.W.K., van den Doel, R., van Vliet, L.,
Young, I.T., hugere, F., Bossche, A,, and Sarro, P. 2003. Miniaturized analytical assays in
Biotechnology. Biotechnology Advances. 21: 431 -444.
41. Kostov, Y.,Harms, P., Randers-Eichhom, L., and Rao, G. 2001. Low-cost microbioreactor for highthroughput bioprocessing. Biotechnology Bioengineering, 72: 346-352.
42. Heinzle, E., Meyer, B., Oezemre, A.,and Dunn, I.J. 1998. A microreactor with on-line massspectrometry for the investigation of biological kinetics. In: Ehrfeld, W. (Ed.) Microreaction
Technology. Proceedings of the First International Conference on Microreaction Technology,
Springer-Verlag, Berlin, pp.267-274.
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