OmniLog/PM Assay TechnologyLeveraging Metabolism For Optimal Bioprocess

Development

Importance of Metabolism and Operational Constraints

•

Energy generation is an important driver of cell growth and bioproduction

•

Making improvements in growth and production requires having a good understanding of cellular metabolism

•

Optimizing growth and productivity means matching relevant substrates to these bioprocessing

phases

•

Gene engineering can alter metabolic programming

•

Culture conditions can alter metabolic programming

2 Primary Components of the OmniLog/PM Cell Assay Platform

Colorimetric cell assays in 96-well microplates

Incubation and recording of data in the OmniLog

Phenotype MicroArrays™

OmniLog™

Incubator/Reader

The Metabolic Dimension of Cells

PM Assays Phenotype Cells for their Unique Bioenergetics Characteristics

carbon/ energy

substrate

Biolog’s Redox DyeNADH

mitochondria

cell

pyruvate glucose

hexanoate

lactate

acetoacetate

galactose

alanine

glutamine

The Heart of PMs

-

Colorimetric Redox

Assays

Add cells and Redox

Dye

Each well contains a different substrate or metabolic effector. Redox

Dye reduction in each well reflects the number of cells and specific pathway bioenergetics activity. No reporter gene required.

Results in 1 -

4 hours

Biolog Redox

Dye Comparison: Sensitivity

MA dye

XTT dye

MTT dye

MTS dye

3.2e6160k

8.0e540k

2.0e510k

5.0e42.5k

1.25e4625

3.12e3156

cells per mlcells per well

A549 human lung cells incubated for 4 hours with 500 μM dye

The PM Assay Portfolio for BioProcessing

•

4X96-Well Plates: 367 Different Carbon- Energy and Nitrogen Substrates (at single

concentration)

•

1X96-well Plate: 22 Trace Elements as Co- factors (at 4 different concentrations)

•

3X96-Well Plates: 45 Hormones and Cytokines (at 6 different concentrations)

PM-M1: Carbon-Energy Supplements for Cells

Showing Plate 1 of 4 plates: Each well has a different KEGG-indexed metabolic substrate

Alcohols and Organic Acids

Nucleosides

Monosaccharides, Oligosaccharides, and Polysaccharides

Ketone

Bodies and Short Chain Fatty Acids

No Substrate

PM Assays are Easy to Run

OmniLog PM System

Holds 50 microplates

at aset temperature

and measures color formation at 5-minute intervals

Kinetic assay readoutfor up to 5,000 wells

CVs typically < 10%

Assays Initiated by adding cells to wells

typically in 50 μlglucose/glutamine-

free media

2 Phases of Typical BioProcesses

Cell

Dens

ity (O

D)

Prod

uct (

g/L)

0 1 2 3 40

Time (Days)

0.1

1

10

100

5

4

3

2

1

Growth Product formation

Analyzing Cell Growth and Media Supplements

Growth/Death Assays Using PM-M1

HepG2/C3A cellsseeded into 6 PM-M1microplates at 2500 cellsper well.

Cells incubated in IF-M1+4 mM

glutamine +1x pen/strep in a 37°

CO2incubator. Each day, oneplate was removed andBiolog Redox Dye MA plus 5mM glucose was added. Plate was thenincubated in an OmniLogfor 18 hours with datacollection.

Day 0 to Day 5 in order -red, yellow, green, blue,purple, black

Growth/Death Assays Using PM-M1

Growth B-4 D-Glucose

Fast Death

D-4 L-Fucose

Stasis A-9 D-Maltose

Slow Death

B-11 D-Sorbitol

Advantages of feeding Mannose vs

Glucose

Chemical Engineering Science (2011) 66: 2431-9

Effect of Copper on Lactate Metabolism in CHO cells

Biotechnol Bioeng. 2011 Sep 30. doi: 10.1002/bit.23291. [Epub ahead of print]

Comparative metabolite analysis to understand lactate metabolism shift in Chinese hamster ovary cell culture process. Luo J, Vijayasankaran N, Autsen J, Santuray R, Hudson T, Amanullah A, Li F.

Oceanside Pharma Technical Development, Genentech, Inc., 1 Antibody Way, Oceanside, California 92056; telephone: 760 231

2127; fax: 760 231 2465.

Abstract A metabolic shift from lactate production (LP) to net lactate consumption (LC) phenotype was observed in certain Chinese hamster ovary (CHO) cell lines during the implementation of a new chemically defined medium (CDM) formulation for antibody production. In addition, this metabolic shift typically leads to process performance improvements in cell growth, productivity, process robustness, and scalability. In our previous studies, a correlation between a key media component, copper, and this lactate metabolism shift was observed. To further investigate this phenomenon, two complementary studies were conducted. In the first study, a single cell line was cultivated in two media that only differed in their copper concentrations, yet were known to generate an LP or LC phenotype with that cell line. In the second study, two different cell lines, which were known to possess inherently different lactate metabolic characteristics, were cultivated in the same medium with a high level of copper; one cell line produced lactate throughout the duration of the culture, and the other consumed lactate after an initial period of LP. Cell pellet and supernatant samples from both studies were collected at regular time intervals, and their metabolite profiles were investigated. The primary finding from the metabolic analysis was that the cells in LP conditions exhibited a less efficient energy metabolism, with glucose primarily being converted into pyruvate, sorbitol, lactate, and other glycolytic intermediates. This decrease in energy efficiency may be due to an inability of pyruvate and acetyl-CoA to progress into the TCA cycle. The lack of progression into the TCA cycle or overflow metabolism in the LP phenotype resulted in the inadequate supply of ATP for the cells. As a consequence, the glycolysis pathway remained the major source of ATP, which in turn, resulted in continuous LP throughout the culture. In addition, the accumulation of free fatty acids was observed; this was thought to be a result of phospholipid catabolism that was being used to supplement the energy produced through glycolysis in order to meet the needs of LP cells. A thorough review of the metabolic profiles indicated that the lactate metabolic shift could be related to the oxidative metabolic capacity of cells. Biotechnol. Bioeng. © 2011 Wiley Periodicals, Inc.

Copyright © 2011 Wiley Periodicals, Inc.

CHO-k1 Cells Carbon Metabolism in PM-M1

Cultured in serum-free Irvine Scientific CHO-Chemically Defined Media (without glucose/glutamine)

6 hr in OmniLog/PM

glycogen maltose

G6P glucose

mannose turanose

F6P fructose

galactose

b-me-galactoside

adenosine inosine

adonitol

xylitol

acetoacetate

a-keto-butyrate

Carbon Substrates Stimulating CHO Cell Growth

Can we identify compounds to add to glucose containing medium that will improve growth rate?

10 Substrates Augment CHO Growth on Glucose

0

5

10

15

20

25

30

RPMI-1

640 A B C D E F G H I J

Dou

blin

g Ti

me

(Hrs

) ***** **********************

*** P < 0.001** P < 0.01* P < 0.05

RPMI Additions

Doubling time decreased from 23 to 18 hr

Optimizing Hybridoma

Media for MAb

Titer

Indirect ELISA assay of PM-M1 culture supernatants from a monoclonal antibody-producing Sp2/0 hybridoma

413-15D12

Can we identify compounds to add to glucose containing medium that will improve antibody yield?

6 PMM Supplements Increase MAb

Titer

0

10

20

30

40

50

60

A B C D E F

RPMI Additions

% Incr

easse in M

Ab T

iter

Antibody titer increased nearly 50%

Study on Industrial CHO Cells

Examined 4 CHO cell lines commonly used in the bioprocess industry:

• Cell line 1

• Cell line 2

• Cell line 3

• Cell line 4 (same as 3 but producing IgG)

Differences in Metabolic Rates Between CHO Cell Lines

Distinguishing Glycolytic/Oxidative Metabolism Preferences

1

10

100

1000

a-D-G

lucos

eD-M

anno

seD-Tag

atose

Palatin

ose

L-Sorb

ose

D-Fructos

e

D-Fructos

e-6-P

hosp

hate

D-Gluc

uronic

acid

D-Gluc

ose-6

-Pho

spha

teD-G

alacto

sePyru

vic ac

idD,L-

Lacti

c acid

L-Glut

amine

Ala-Gln

His-Trp

nega

tive c

ontro

l

Bio

log

Sig

nal

Cell Line 1Cell Line 2Cell Line 3Cell Line 4

Figure 5: Biolog initial rate of dye reduction for selected components that show a large signal and apparent differences between cell lines. Results shown are the average ± SD for the triplicate cultures that were analyzed

Glucose

3>4>2>1

Fructose 1>2,4>3

Cell line 1: G/F = 5.9 Cell line 2: G/F = 8.6 Cell line 3: G/F = 20.4 Cell line 4: G/F = 10.4

Changes in Metabolic Rates of IgG-Producing CHO Cells Over a 13 Day Culture in a Fed-Batch Bioreactor Process

1

10

100

1000

a-D-G

lucos

eD-M

anno

seD-Tag

atose

Palatin

ose

L-Sorb

ose

D-Fructos

e

D-Fruc

tose-6

-Pho

spha

teD-G

lucuro

nic ac

id

D-Gluc

ose-6

-Pho

spha

teD-G

alacto

sePyru

vic ac

idD,L-

Lacti

c acid

L-Glut

amine

Ala-Gln

Gln-Gln

Negati

ve co

ntrol

(avg)

Bio

log

Sig

nal

0 3 6 10 13

Figure 8. Biolog initial rate of dye reduction for selected components that show a large signal and apparent differences between cell lines. Results shown are the average ± SD for the triplicate bioreactor cultures that were analyzed.

Lactic acid consumption

rate rises

PM Assays

Distinguishing the Metabolism Dynamics and Substrate Preferences of Different Clones and

Cell Lines

Advantages of Using the OmniLog

PM System

Time

Dye

For

mat

ion

Lag

Slop

e MaxMax Slope Time

First Derivative

Average Height

Min

Area Under the Curve

•Each PMM well will exhibit a different rate of dye formation, so single endpoint reads for an entire plate are not ideal

•OmniLog

PMM software computes multiple parameters for

phenotypic characterization and comparison

Metabolic Comparisons of 16 Cell Sub-lines

Clustering ‘Kinetic Curve Profiles’

for 367 Metabolic Substrates

Provides a Means to Compare Closely-RelatedEngineered Clones or Sub-lines for Selection,

Media Composition, and Scale-up

PM Assays

Gene Engineering

and Metabolic Reprogramming

PM Platform -

Comparing Metabolic Phenotypes of Parent Lines

and their Clones

Parent A

Clone B

PM Kinetic ResultPM Pattern OmniLog PM SystemYellow indicates computer-

generated red-green overlays indicating extent of similar response to a given substrate

Cell-Line Engineering and Clone Characterization

OmniLog/PM:

A Highly

Sensitive Platform for Detecting and

Characterizing Metabolic Changes Arising from the Genetic Engineering of a Clone

Case Study: A Single-Point Mutation

Metabolic Differences between Parent

HME Line and it’s PI3K Single-Point Mutation Clone

Dextrin

G-1-PG-6-P Glucose

Mannose

F-6-P Fructose

Maltose

Galactose InosineAdenosine

GlycerolPhosphate

Uridine

Propionate

Maltotriose

Turanose

beta-HydroxyButyrate

Point Mutation shut down metabolism of sugar phosphates

Same approach can be taken to study metabolism changes in any engineered clones

Computer generatedoverlay of parent phenotype plate and clone phenotype plate. Yellow indicates the extent of same substrate metabolism

Carbon-Energy Substrate Changes in Parent MCF10a

vs

PI3K Clone CL1

Biolog Plate PM-M1

Lactic acid Pyruvic

acid

Comparison of Isogenic

PI3K Clones CL1

vs

CL2 Using Biolog Plate PM-M1 and PM-M2

PM Assays

Highly Reproducible

PM Assays are Highly Reproducible OmniLog

Record for Mitochondria Inhibition Done in Triplicate

12/18/09

inosine

galactose

glucose-1-phosphate

xylitol

a-ketoglutarate

b-hydroxybutyrate

pyruvate

glucose

0 3.1 6.25 12.5 25 100

[FCCP] / uM

500.1 0.2 0.4 1.60.8Substrates:Decoupler

Conclusions and Summary

PM Advantages

•

Uniquely characterizes the metabolic dimension of cells in real time•

Works on any type of cell, no cell engineering required•

Can be integrated with gene expression, proteomics and mass-spec analysis

•

Robust and simple technology available to all labs•

Provided in standard 96-well microplate

format•

Provides an entirely novel view of cells•

Provides more high content info than any other technology•

Flexible number of assays –

hundreds or thousands•

Flexible levels of automation and throughput•

Very wide range of uses

Steps in BioProcess

Development Aided by PM

•

Characterize cell lines and clonal

variants to understand their culture properties to select the best one to use

•

Understand how genetic changes affect the cell line

•

Simulate hundreds/thousands of culture conditions to find the key culture variables that affect the process

•

Optimize culture conditions for both rapid growth and maximum product yield

•

Use it as a QC tool to test cell-bank stocks for metabolic phenotype consistency and metabolic stability

The Goal: To Find the Optimal BioProcess

Metabolism drives cell performance and influences product quality.

PM Metabolic Phenotypes deliver unique

insights and guidance.

Comments on using OmniLog-PMM Technology

•

We have been using PMM since January 2011 in our bioprocess development group and have found it to be a very powerful tool to study cell

phenotypes and also cell metabolism under different conditions. During development of CHO cell lines for production of recombinant proteins, we have used PMM to distinguish between cell clones and find those with desirable and stable phenotypes. We are also investigating whether clonal cell phenotypes change over long term cultivation as a potential indicator of genetic instability.

•

According to our experience so far, PMM could successfully be used to reveal differences in nutrient utilization between different cell clones, so we could use this information to optimize cell culture medium towards more energy efficient nutrient utilization,

as well as optimize recombinant protein production and protein glycosylation.

•

PMM is currently used to test alternative substrates during bioreactor process development to improve cell performance,

and also to investigate changes in cell phenotypes under different process conditions (for example, temperature changes).

•

PMM chemistry is a simple and powerful tool to study cell potential, however it is not a "plug and play" technology. This is mainly due to complexity of biological systems tested, which require disciplined and skilled handling. Also, comprehensive understanding of cell metabolism is required to cope with interpretation of PMM massive data and to come up with useful scientific conclusions.

•

Dr. Vatroslav

Spudic, Biotechnical Faculty, Ljubljana, Slovenia

Questions?

For Technical Inquiries:

Dr. Elina Golder-Novoselsky, Ph.D.Product Sales Manager / PMM Assays and OmniLog-PMT: 510 461-2669Email: EGolder@biolog.com

For Customer Service or Order Placement:

Call 800-284-4949 or Email csorder@biolog.com