1

• God could cause us considerable
• embarrassment by revealing
• all the secrets of nature to us
• we should not know what to do for
• sheer apathy and boredom.
• -- Johann Wolfgang
• von Goethe

2
Systems Biology of Osmotic Shock in Antibody
Producing Cell Lines

• Candidacy Proposal
• Thomas R. Kiehl
• NSF Graduate Research Fellow,
• Multidisciplinary Science Ph.D. Program

3
What is an Antibody?

• Antibodies are an important component of the
  bodys natural defenses.
• These glycoproteins recognize foreign substances
  and tag them for remediation by other parts of
  the immune system.
• mAbs are an effective part of a growing number
  of medical treatments, lab techniques,
  diagnostics and imaging.

Image source Wikipedia
4
Roche buys antibody technology company for 56.6
mln, Apr 2,2007

• ZURICH (MarketWatch) -- Swiss drugmaker Roche
  Holding AG (RHHBY) Monday said it has acquired
  privately-held Therapeutic Human Polyclonals Inc,
  an emerging biotechnology company focused on
  research in human antibody technologies, for
  56.6 million in cash.
• Roche, based in Basel, said it plans to fully
  integrate THP, which is based in Germany and the
  U.S., into its protein research center in
  Penzberg, Germany.
• "We are delighted about this acquisition as it
  builds on our strength in therapeutic
  antibodies," said Jonathan Knowles, head of
  global research at Roche.
• The development of therapeutic proteins and
  antibodies is an important area of research for
  the company, Roche said.
• At 0826 GMT, Roche shares were CHF1.80, or 0.8
  higher, at CHF216.80, in a slightly lower broader
  market.
• THP focuses on research in the field of human
  antibody technologies, where drugs made out of
  antibodies fight infectious agents, including
  bacteria and viruses, by seeking them out and
  helping the body to destroy them.
• THP says it has developed a unique transgenic
  mammalian platform to create human antibodies.
  The technology will enable the generation of both
  monoclonal and polyclonal antibody drugs with
  enhanced efficacy, Roche said.
• Monoclonal antibodies are identical because they
  were produced by one type of immune cell and are
  all clones of a single parent cell.
• "Improved monoclonal antibody companies are hot
  commodities," said Denise Anderson,
  pharmaceutical analyst in Zurich with broker
  Kepler Equities, who has a buy rating on the
  stock, pointing to a string of deals over the
  past twelve months.
• Roche itself paid 181 million last year to
  acquire GlycArt Biotechnology AG of Zurich, which
  also had a crop of early-stage antibodies.
• In May, Merck Co. (MRK) agreed to pay a
  combined 480 million to acquire Abmaxis and
  GlycoFi, two biotechnology firms that brought the
  drug maker new methods to discover and produce
  drugs. Merck, based in Whitehouse Station, N.J.,
  isn't affiliated with its German namesake.
• Also in the second quarter of 2006, Pfizer inc.
  (PFE) acquired Bioren, a small specialist in the
  discovery of monoclonal antibodies.
• "We think the deal makes good strategic sense for
  Roche, where top drugs Rituxan, Herceptin and
  Avastin are all antibodies, Anderson said.
• At a time when many traditional drugs made from
  small molecules are facing the loss of patent
  protection, medicines made out of large proteins
  are still protected from this threat not only
  because they've only entered the market over the
  past decade but also because they are more
  complex to imitate.

Monday (Roche) said it has acquired
privately-held Therapeutic Human Polyclonals Inc,
an emerging biotechnology company focused on
research in human antibody technologies, for
56.6 million in cash.
Roche itself paid 181 million last year to
acquire GlycArt Biotechnology AG of Zurich, which
also had a crop of early-stage antibodies.
In May, Merck Co. (MRK) agreed to pay a
combined 480 million to acquire Abmaxis and
GlycoFi, two biotechnology firms that brought the
drug maker new methods to discover and produce
drugs.
Also in the second quarter of 2006, Pfizer inc.
(PFE) acquired Bioren, a small specialist in the
discovery of monoclonal antibodies.
5
2005 Market, 13 Billion

• ½ of that from just two drugs
• Rituxan (3.3Bn) non-Hodgkins Lymphoma (CD20)
• Remicade (3.4Bn) - rheumatoid arthritis (TNF-a)
• 17 therapeutic monoclonal antibodies have
  received FDA approval and are on the market in
  the U.S.
• Several antibodies have been approved for use in
  diagnostic imaging applications.
• Report does not mention BMS Abatacept which is a
  fusion protein composed of an immunoglobulin
  fused to the extracellular domain of CTLA-4
  (Sales for the second quarter of 2006 were 18
  million, sales could reach US 1 billion by
  2009/2010, )

Market Report Monoclonal Antibodies From
Magic Bullets to Successful Drugs Abatacept
Nature Reviews Drug Discovery 5, 185-186 (March
2006)
6
Herceptin, A prototypical Antibody Therapeutic

• This mAb targets a receptor which is over
  expressed in certain breast cancers (Bange 2001,
  Sliwkowski 1999).
• Herceptin targets the epidermal growth factor
  receptor, HER2, which is part of the ErbB family
  of tyrosine kinases.
• This targeting results in cell cycle arrest and
  suppression of tumor growth.

7
Systems Biology of Osmotic Shock in Antibody
Producing Cell Lines

• Candidacy Proposal
• Thomas R. Kiehl
• NSF Graduate Research Fellow,
• Multidisciplinary Science Ph.D. Program

8
How do you make mAbs?

• In 1975 Köhler and Milstein first developed cell
  lines which could reliably produce monoclonal
  antibodies
• These cell lines, known as hybridomas, were a
  fusion of an antibody-secreting murine lymphocyte
  cell with an murine myleoma cell.
• From this process emerges an immortalized cell
  line which secretes identical antibodies that
  have been raised against a specific antigen.

9
Systems Biology of Osmotic Shock in Antibody
Producing Cell Lines

• Candidacy Proposal
• Thomas R. Kiehl
• NSF Graduate Research Fellow,
• Multidisciplinary Science Ph.D. Program

10
Why Osmotic Shock?

• Osmotic stress as well as a number of other
  stresses can increase the antibody production
  rates of a culture
• Just add NaCl.

Sun, Z., Zhou, R., Liang, S., McNeeley, K.M.,
Sharfstein, S.T. (2004) Biotechnology Progress.
20, 576-589 Ozturk, S.S., Palsson, B.O. (1991)
Biotechnology and Bioengineering, Vol. 37, Pp.
989-993
11
Is it really that easy?

• Higher osmolarities negatively impact viable cell
  concentration.

Sun, Z., Zhou, R., Liang, S., McNeeley, K.M.,
Sharfstein, S.T. (2004) Biotechnology Progress.
20, 576-589 Ozturk, S.S., Palsson, B.O. (1991)
Biotechnology and Bioengineering, Vol. 37, Pp.
989-993
12
So, just shock them a little. Right?

• In fed-batch cultures osmolarity becomes
  problematic both due to the addition of nutrients
  as well as the production of waste products,
  primarily lactic acid.
• Lactic acid acidifies the culture, necessitating
  the addition of base to control the pH.
• Over the course of a fed-batch culture the
  osmolarity can increase from 290mOsm/kg to
  500mOsm/kg (Zhu 2005).
• Viability can be reduced by as much as 50
  (Kurano 1990).

13
Systems Biology of Osmotic Shock in Antibody
Producing Cell Lines

• Candidacy Proposal
• Thomas R. Kiehl
• NSF Graduate Research Fellow,
• Multidisciplinary Science Ph.D. Program

14
Systems Biology

• I am a Biologist, and I work on systems.
• I guess that makes me a Systems Biologist.
• -Howard Berg, ICSB 2005

15
Systems Biology

• To understand biology at the system level, we
  must examine the structure and dynamics of
  cellular and organismal function, rather than the
  characteristics of isolated parts of a cell or
  organism. Properties of systems, such as
  robustness, emerge as central issues, and
  understanding these properties may have an impact
  on the future of medicine. Hiroaki Kitano

Kitano, H. (2002), Systems Biology a brief
overview, Science, 2951662-1664
16
3 Cs of Systems Biology

• Complexity
• Computation
• Cross-Disciplinary Cooperation

17
Systems Biology
Lab Experiment(s)
Refine model
In-Silico Experiment(s)
18
Systems Biology of Osmotic Shock in Antibody
Producing Cell Lines

• Candidacy Proposal
• Thomas R. Kiehl
• NSF Graduate Research Fellow,
• Multidisciplinary Science Ph.D. Program

19
Objective

• Engineer mammalian cells for optimal recombinant
  protein production.
• To build a model of the cellular response to
  osmotic shock.
• Characterize the response in terms of some
  specific components.

20
Overview

• Mammalian Pathway
• Yeast Model
• Model Scope
• Sample Model
• TonEBP/NFAT5/OREBP
• Experimental Plan Preliminary Results
• Related Efforts
• Batch Culture Model
• Microarrays
• CoEPrA
• Evolutionary Computing

21
Mammalian Pathway
Dmitrieva, N. I., M. B. Burg, et al. (2005). "DNA
damage and osmotic regulation in the kidney" Am J
Physiol Renal Physiol 289(1) F2-7.
22
Yeast Osmostress Signalling
23
Simulating Yeast Response to Osmotic Shock
Klipp, E., B. Nordlander, et al. (2005).
"Integrative model of the response of yeast to
osmotic shock." Nature Biotechnology 23(8)
975-982.
24
Yeast Model

• The ODEs in Klipps model generally take the form
  of equation 4. In this formulation m is the
  number of biochemical species, r is the number of
  reactions each with a rate v and stoichiometry n.
  This equation governs how the concentration of
  each species evolves over time.

25
Yeast Output
26
Yeast Model

• Klipp showed that the pathway can be activated
  again by an additional shock.
• They also showed that this reactivation would not
  be possible if the pathway were structured such
  that the phosphatases provided the primary
  feedback control.
• They demonstrated that the gene transcripts for
  phosphatases should not increase by more than
  two-fold.

27
Mammalian Pathway
Dmitrieva, N. I., M. B. Burg, et al. (2005). "DNA
damage and osmotic regulation in the kidney" Am J
Physiol Renal Physiol 289(1) F2-7.
28
Model Scope

• An initial model will capture three main
  concepts.
• The insult of osmolarity within the context of
  the cell culture life-cycle
• The dependence of TonEBP activation on osmolarity
• TonEBP-dependant osmolyte accumulation.

Osmolyte Accumulation
Osmolarity
TonEBP
29
Refined Objective

• Experimentally demonstrate the central role of
  NFAT5 in our cell lines the cellular osmotic
  response.
• Build a model to characterize that role
• What portion of the osmotic response can be
  accounted for solely by TonEBP?
• Are other factors or feedback loops required to
  explain observed dynamics?

30
Toward a simplified model
Osmolyte Accumulation
Osmolarity
TonEBP
Dmitrieva, N. I., M. B. Burg, et al. (2005). "DNA
damage and osmotic regulation in the kidney" Am J
Physiol Renal Physiol 289(1) F2-7.
31
Osmolarity

• This is the primary independent variable in the
  system
• Could be modeled in terms of a rapidly decreasing
  osmotic gradient
• Could be kept at a constant
• Could be modeled as a slowly increasing quantity.

Osmolyte Accumulation
Osmolarity
TonEBP
32
TonEBP

• First dependant variable, primarily dependant on
  the osmolarity
• Goal is to fit this quantity to experimental data

Osmolyte Accumulation
Osmolarity
TonEBP
33
Osmolyte Accumulation

• We presume that osmolyte accumulation is
  dependant on TonEBP activation
• Well use a proxy of cell volume initially.

Osmolyte Accumulation
Osmolarity
TonEBP
34
Basic Model
(a) (b) (c)

• O, the osmotic gradient. The kinetic constant,
  kO, governs the rapid equilibration of this
  gradient immediately after the osmotic shock.
• N, amount of activated transcription factor
• P, the amount of accumulated osmoprotectants.
• k1 relates the activation of TonEBP to the
  osmolarity (O).
• k2 is a decay rate for activated TonEBP
• k3 relates TonEBP activation to osmolyte
  accumulation

35
Model Output

• Osmotic gradient, blue.
• Level of activated NFAT5, red.
• Accumulation of osmolytes, green

36
Iterate on the model

• Generally fits with what we expect
• Missing some important features
• Must relate the model to actual data.

Osmolyte Accumulation
Osmolarity
TonEBP
37
Experimental Plans, Initial Data

• Osmotic stress protocol
• Quantify TonEBP
• Quantify Cell Volume
• Other experimental possibilities

38
Osmostress Experiment

• Stress cells with 100mOsm increase
• Sample Cells at
• Pre-stress Control
• Post-stress 5, 10, 15, 30, 60 120 min
• For western blot
• Lyse in SDS and shear DNA
• Use lysate in chemoluminescent or fluorescent
  western blot.

39
NFAT5 DNA Binding

• Consensus Sequence
• TGGAAANN(C/T)N(C/T) 1
• N any nucleotide
• C/T any pyrimidine
• NFAT Family, but similar to an NF-kB

1) Miyakawa H, Woo S K, Dahl S C, Handler J S,
Kwon H M. Proc Natl Acad Sci USA.
19999625382542. PubMed 2) ltimagegt James C.
Stroud et al Nature Structural Biology  9, 90 -
94 (2002)
40
About TonEBP

• Western blot of TonEBP after 18 hours of
  incubation in isotonic (I) and hypertonic (H)
  medium (Miyakawa 1999)

41
About TonEBP

• Localization of TonEBP under different mutations
  of the nuclear location signal (Tong 2006).

42
About TonEBP

• Ratio of TonEBP localization after 200, 300 or
  500 mosmol solution for 30 minutes (Zhang 2005)

43
TonEBP

• We intend to use a chemiluminescent EMSA to watch
  TonEBP activation over time
• Previous work (Stroud 2002, Kojima 2004)

44
Cell Size

• Intend to quantify with the FACS machine using
  forward light scattering techniques

Ozturk, S.S., Palsson, B.O. (1991) Biotechnology
and Bioengineering, Vol. 37, Pp. 989-993
45
(No Transcript)
46
Other measurements

• As time allows
• Upstream signaling components
• Specific osmolyte accumulation
• Lactic acid production

47
GPC Lactate

• Glycerophosphocholine and Lactate can both be
  quantitated by YSI

Lactic acid
48
Betaine

• Near IR spectroscopy

49
Sorbitol and Inositol

• Observe dehydrogenase activity by
  spectrophotometry
• Sorbitol Dehydrogenase and Inositol dehydrogenase
  respectively

50
Aldose Reductase Activity

• Spectrophotometry, absorbtion at 340 (Bagnasco et
  al., PNAS 841718) (JBC 1965 page 877)

51
PKA Fyn

• PKA by ELISA, from Stressgen Bioreagents (already
  attempted with a kit from Omnia, need to further
  optimize)
• Fyn immuniprecipitation following Ko et. al
  from JBC vol 273 pp 46083

52
P38 MAPK

• Chemiluminescent Western from Cell Signaling
  Technologies

53
MAPK
OKT3 30
Low 30
High
C
5
10
15
30
60
120
54
SAPK/JNK, HSP27

• Chemiluminescent Western from Cell Signaling
  Technologies

sapk/jnk
55
SAPK/JNK Initial Results

• Initial Experiment
• Currently replicating this work to see if we can
  get better resolution

56
Refined Objective

• Experimentally demonstrate the central role of
  TonEBP in our cell lines the cellular osmotic
  response.
• EMSA for TonEBP, FACS for size
• Westerns, ELISA Spectrophotometry as time and
  resources allow
• Build a model to characterize that role, informed
  by experimental data

Osmolyte Accumulation
Osmolarity
TonEBP
57
(No Transcript)
58
Other Efforts

• Microarray Analysis
• Batch Culture Model
• CoEPrA
• Evolving Bifurcating Networks

59
Microarray Analysis

• Looking at network component analysis (NCA)
• Conceptualized some other SVM related approaches
  with Prof. Embrects (DSES)

60
Batch Culture Model
(Gao 2007)
61
CoEPrAComparative Evaluation of Prediction
Algorithms

• Primitive Linear Algebra approach Placed 8th
  out of 16 participants on a classification task.
• Paper submission invited.
• Task was to classify short peptides (8-9 amino
  acids) so as to predict activity.

http//www.coepra.org
62
Method

• Our method utilized a simple mechanism of
  computing distances between LOGOs generated for
  each sequence and each class of sequences (Crooks
  2004).
• We used a random search algorithm to identify
  active nonapeptides in the prediction set.
• Random subsets of the joint calibration-prediction
  superset were compared with the active
  calibration subset. The retained loss function is
  the Frobenius matrix norm of the difference
  between the logos.
• One thousand runs were completed and results
  were pooled together to make the final prediction.

63
Logos

• Shown in figures 1-4 are visual representations
  of the Logos in question. The search algorithm
  seeks out a partitioning of the prediction data
  set (4). An optimal partitioning would yield a
  positive and negative subset of the prediction
  data set such that their logos would show a
  minimal distance to the respective calibration
  logo (2 or 3).

Figure 1. Logo for whole calibration data set.
Figure 2. Logo for negative examples in
calibration data set.
Figure 3. Logo for positive examples in
calibration data set.
Figure 4. Logo for prediction data set
64
Evolving Bifurcating Networks

• A good body of literature has started to form in
  the area of Evolving Biochemical Reaction
  Networks.
• Looking to build on previous work to create
  networks with specific distributions of outputs

65
Evolving Bifurcating Networks
1 2 3 4 5 34 35
1 2 3 4 5 34 35
1 2 3 4 5 34 35
66
"Evolving Synthetic Biochemical Reaction
Networks First Steps" , ICSB St. Louis, MO,
2003, Kiehl T.R., Bonissone P.P.
67
Bioinformatics. 2004 Feb 12 Kiehl et al.
20(3)316-22
68
Thanks.

• NSF GRF
• Susan Sharfstein
• Lealon Martin
• Sam Wait
• David Isaacson
• Joyce Diwan
• Mark Embrechts
• Numerous folks _at_ GE
• Charles Bergeron
• Duan Shen
• Family Friends

69
Ongoing work
the end
70
the end
71
Osmotic Shock
72
TonEBP Quantitation

• Chemiluminescent EMSA
• Cant use generic NFAT kits, since TonEBP (NFAT5)
  is very different from other NFATs. More like
  some NFKappas.

73
Antibody Production

• How does one stimulate production and maintain
  cell viability, thereby increasing specific
  productivity?
• Various types of stress are used to stimulate
  production, including Osmotic stress.
• What mechanisms are responsible for this response?

74
Batch Culture Timeline
minutes
hours
days
days
Stationary Phase Cell Death
Exponential Growth Phase
Osmotic Shock
Adaptation
Ozturk and Palsson Biotech. Bioeng. 37989-993
(1991)
75
Modelling Response to Osmotic Shock

• Incorporate the acquired data, along with data
  from literature to into a computational model
• Following Klipp et al in their yeast model

76
LP NCA
Ê Â Pbar
Pbar(,j) This column is our set of variables
Ê(i,j) Our target value and error tolerance
define constraints

Â(i) This row held constant
Minimize Â(i,)P(j) s.t. Â(i,)P(j) target
e1 Â(i,)P(j) target e1 For r ! i , 1 r
length(Â) Â(r,)P(j) initial value e2
Â(r,)P(j) initial value e2
Ê(r,j) Used to define secondary constraints
Ê(i) Each element in this row presents an LP
independent of the other elements in the row
77
PCA ? NCA

• With Prof. Martin
• Relative acid concentrations in grape varieties.
• Can NCA be applied to get more information out of
  the data?

78
Questions asked

• Where to publish?
• Sys bio journals, bioinformatics, ieee
• Probably multiple, some more bio focused, some
  more computationally focused.
• Have you thought about the model?
• Two main pieces, the structure and the numbers.

79
Afterthoughts continuing to work, towards next
step, all of this added post presentation.
osmolarity
waste
Extracellular
Aquaporin?
Intracellular
osmolytes
Endogenous production,Vs. transport.
80
Calculation of osmotic pressure

• Osmotic pressure in atmospheres
• p MRT
• M is the molar concentration of dissolved species
  (units of mol/L).
• R is the ideal gas constant (0.08206 L atm mol-1
  K-1, or other values depending on the pressure
  units).
• T is the temperature on the Kelvin scale.
  molarity R temp(kelvin)
• Quantitating amounts of osmolytes prior to stress
  should give us an idea of
• Baseline pressure
• Initial maximum pressure
• Quantitating during stress should give us a time
  course of osmotic pressure.

81
Random questions

• Osmolarity in our cultures vs. industry relevent
  cultures vs. in vivo renal medullary conditions
• Qi Cai et al 2004 cite different responses for
  linear increases in osmolarity vs. step incresases

82
Market reports

• are numerous.
• This is a very simplistic measure of the
  importance of this market
• Google monoclonal antibody market
• See how much money you could spend just buying
  reports on the market.

83
Biological Experiments and Computational Analysis
Toward the Elucidation of Signaling and Gene
Expression Responses to Osmotic Shock and
Resultant Osmolyte Accumulation in Antibody
Producing Cell Lines
(ROUGH) Candidacy Practice
Biological blablah blah blah blah blah blah blah
blah blah blah blah Signaling blah Gene
Expression blah blah blah Osmotic Shock blah
blah blah blah blah blah blah blah Antibody blah
blah blah blah

• Spring 2007
• Tom Kiehl

84
YSI Analyzer

• Can provide quick measurements of the following
  analytes
• D-Glucose (Dextrose)
• L-Lactate
• Sucrose
• Lactose
• Ethanol
• L-Glutamate
• Choline
• L-Glutamine
• Methanol
• Galactose
• Hydrogen Peroxide