6. CONCLUSION 5. APPLICATION: MINIBODY

1. INTRODUCTION

REFERENCES

3. CELLULAR PATHWAY ENGINEERING

2. TOOLS FOR LIBRARY CONSTRUCTION

4. CHO-Mplus LIBRARY GENERATION

In an effort to improve product yield of mammalian cell lines, we have previously demonstrated that our proprietary DNA elements, Selexis Genetic Elements (SGEs), increase the transcription of a given transgene1, thus boosting the overall expression of a therapeutic protein drug in mammalian cells.

However, there are additional cellular bottlenecks, notably in the molecular machineries of the secretory pathways. Most importantly, mammalian cells have some limitations in their intrinsic capacity to manage high level of protein synthesis as well as folding recombinant proteins. These bottlenecks often lead to increased cellular stress and, therefore, low production rates.

Our specific approach involves CHO cell line engineering. We constructed a CHO-M library based upon the CHO-M genome and transcriptome and using unique proprietary transposon vectors harboring SGE DNA elements to compensate for rate-limiting factors. This CHO-Mplus library displays a diversity of greater than 1x107 auxiliary proteins involved in secretory pathway machineries and cellular metabolism.

We show that our CHO-Mplus library enabled the selection of a clonal cell line expressing 10 fold more product by comparison to standard approaches.

The elucidation of protein expression bottlenecks is time-consuming, labor intensive and is dependent on the gene to be expressed. By mapping both the genome and the transcriptome of its CHO-M cell line, we have developed the combinatorial CHO-Mplus library which addresses a broad range of expression issues simultaneously.

The combinatorial library metrics are:

1. Specifically tailored to improve production and secretion properties of recombinant proteins in the CHO-M production cell line

2. Combines SGE DNA elements and transposon technology to ensure maximum expression of both secretory components as well as recombinant proteins of interest

3. Addresses > 100 different secretory components of the CHO cell line 4. The combinatorial library complexity is greater than 1x107 5. Easily integrated with selection criteria for most recombinant proteins

We have applied this strategy to select for clonal cell lines expressing secreted proteins such as monoclonal antibodies, enzymes, hormones, blood factors as well as membrane-bound proteins such as GPCRs and ion-channels.

1 Ley D, Harraghy N, Le Fourn V, Bire S, Girod PA, Regamey A, Rouleux-Bonnin F, Bigot Y, Mermod N. MAR Elements and Transposons for Improved Transgene Integration and Expression. PLoS One 2013 Apr 30;8(4). 2 Le Fourn V, Girod PA, Buceta M, Regamey A, Mermod N. CHO cell engineering to prevent polypeptide aggregation and improve therapeutic protein secretion. Metab. Eng. (2013) Feb 1. 3 Girod PA, Nguyen DQ, Calabrese D, Puttini S, Grandjean M, Martinet D, Regamey A, Saugy D, Beckmann JS, Bucher P, Mermod N. Genome-wide prediction of matrix attachment regions that increase gene expression in mammalian cells. Nat Methods. 2007 Sep;4(9):747-53. Epub 2007 Aug 5. www.selexis.com

PB

Amp Ori

PB transposase

ITR ITR

Amp Ori

Puro-GFP-transposon

Puro GFP SGE 1-68

Stable Expression by Combining SGEs and Transposon Vectors

Transposon Expression System Work Flow

Transposase expression

Transposon integration into Host genome

ITR

Transposon excision Transposase binding to ITR GOI-transposon vector

+ Host genome

The addition of SGEs to GFP-transposon vectors enhances the expression of GFP per

transgene copy number.

The combination of SGEs containing transposon vectors with double transfection results in

50% of the CHO-M cells expressing the transgene without any antibiotic selection.

Transposon expression vectors:

Single transfection

% G

FP p

osi

tive

cel

ls

Double transfection

0

10

20

30

40

No selection

Tran

sgen

e co

py

nu

mb

er

0

2

4

6

(-) SGE

No selection

GFP

flu

ore

scen

ce

per

tra

nsg

ene

cop

y

120

0

40

80

(-) SGE

No selection

No transposase With transposase

InflixiMab Clone Overexpressing Secretion Pathway Proteins

golgi

SRP Receptor

Translocon

Delayed Light Chain elongation results in correct processing and folding of IgG Light Chain and higher antibody titer in supernatant.

Spe

cifi

c p

rod

uct

ivit

y (p

cd)

Tras Infli

-- S -- S

10

20

30

40

50

0 G = GFP S = SRP14

40%

400%

The iterative application of the CHO-Mplus library enabled the selection of a clonal cell line expressing 10 fold more product by comparison to standard approaches.

CHO CELL LIBRARY FOR THE SELECTION OF IMPROVED RECOMBINANT THERAPEUTIC PROTEIN PRODUCTION CLONES

Engineered Translation and ER

Translocation Pathways

SRP receptor; translocon subunits; SRP9, 14, 54 proteins overexpressed

in various combinations

Control A B C D E F G 0.0

0.5

1.0

1.5

2.0

2.5

3.0

Qp

fo

ld in

cre

ase

(/P

G c

on

tro

l)

Tras Infli

TX-100 soluble fraction

TX-100 insoluble fraction

Chaperones : -- G S -- G S

Free-LC

Free-HC

HC-LC

IgG (HC)2

Aggregated Misprocessed-LC

Misprocessed-LC

G = GFP S = SRP14

Low Expressor: InflixiMab IgG Clone

ER stress induction

IgG Light Chain misprocessed, IB aggregation induce UPR Stress responses, cell cycle delays, …

LC IB

Efficient folding and secretion of IgG after a multistep pathway engineering yields a secretion increase of 40% to

400% of Trastuzumab (Tras) and Infliximab (Infli).

Novel Scaffold Minibody, single chain variable region (VH-VL) fused to Fc

region (H-CH2-CH3)

CH2

scFv

CH3

Tite

r (m

g/L)

300

250

200

Productivity

0

0.01

0.02

0.03

0.04

0.05

0.06

Original CHOMPlus 1 CHOMPlus 2

Level of Minibody mRNA

CHO-Mplus 1 CHO-Mplus 2

Original CHO-Mplus 1 CHO-Mplus 2

150

100

50

0 0

2

4

6

8

10

12

14

16

18

Original CHOMPlus 1 CHOMPlus 2

Gene copy number

CHO-Mplus 1 CHO-Mplus 2

The CHO-Mplus library expressing combinations of auxiliary proteins to rescue and support secretory pathway machineries and cellular metabolism.

Valérie Le Fourn1, David Calabrese1, Alexandre Regamey1, Deborah Ley2, Nicolas Mermod2, Igor Fisch1 and Pierre-Alain Girod1 1Selexis SA, Plan-Les-Ouates, Switzerland; 2University of Lausanne, Switzerland