Meta-analysis of –omics level data for efficient production of N-linked glycoproteins

in a bacterial host

Stephen Jaffé – PDRA - University of Sheffield, UKPI – Prof Phil Wright

Co-I – Dr Jagroop Pandhal7th ICBE – San Diego

10/01/2017 1

2

Signal peptide modifications and chromosomal basing of key gene

Meta-analysis of –omics level data

Mass spec based glyco-quant

Key points of the talk

Aim – Increase the glycosylation efficiency, glycoprotein yield and develop a more accurate analytic technique

Glycotherapeutic market

• $140 billion market in 2013 [1]

• Chinese Hamster Ovary (CHO) cells are the predominant host cell for glycotherapeutic production [1]

• CHO cells generate fully functional

complex proteins (most notably mAbs)

• Humanised glycan structure [3]

3

[4][1] Walsh. B. (2014) Biopharmaceutical benchmarks 2014. Nature Biotechnology. 32. 10. 992-1000 [3] Hossler. P., Khattak. S. F., Li. Z. J. (2009) Optimal and consistent protein glycosylation in mammalian cell culture. Glycobiology. 19. 9. 936-949. [4] Baker. J. L., Celik. E., DeLisa. M. P. (2013) Expanding the glycoengineering toolbox: the rise of bacterial N-linked protein glycosylation. Trends in biotechnology. 31. 5. 313-323.

Glycosylation is in all domains of life

4[4]

[4] Baker. J. L., Celik. E., DeLisa. M. P. (2013) Expanding the glycoengineering toolbox: the rise of bacterial N-linked protein glycosylation. Trends in biotechnology. 31. 5. 313-323.

Bacterial glycosylation

5[5] Wacker. M., Linton. W., Hitchen. P. G., Nita-Lazar. M., Haslam. S. M. North. S. J., Panico. M., Morris. H. R., Dell. A., Wren. B. W., Aebi. M. (2002). N-linked glycosylation in Campylobacter and its functional transfer into E. coli. Science. 298.1790-1793.

[5]

6

• Paper generated idea of making therapeutic glycoproteins in the primary organism for recombinant protein production – E. coli [7]

• Highly adaptable “plug and play”

system for glycans of choice

• Recombinant prokaryotic glycosylation

system allows for defined glycoforms [8]

E. coli N-linked glycosylation

[7] Huang et al (2012) Industrial production of recombinant therapeutics in Escherichia coli and its recent advancements. J Ind Microbiol Biotechnol. 39. 383-399 [8] Jaffé et al. (2014)Escherichia coli as a glycoprotein production host: recent developments and challenges. Current Opinion in Biotechnology. 30. 205-210.

[8]

N-linked glycosylation in E. coli

• Block transfer

• Glycans generated in cytoplasm

• Built onto cytoplasmic face of IM

• Transferred to periplasm

7[6] Nothaft. H., Szymanski. C. 2010. Protein glycosylation in bacteria: sweeter than ever. Nature Reviews Microbiology. 8. 768-778

N-linked glycosylation in E. coli

• Block transfer

• Glycans generated in cytoplasm

• Built onto cytoplasmic face of IM

• Transferred to periplasm

• Attached to defined protein sequon

8

[6]

[6] Nothaft. H., Szymanski. C. 2010. Protein glycosylation in bacteria: sweeter than ever. Nature Reviews Microbiology. 8. 768-778

9

Advantages and uses of the technology

• Expression in bacteria is much cheaper than mammalian cells

• Homogenous glycoprofile

• Currently most successfully applied towards glyco vaccines

• Possible to expand to vast number of glycans and glycan structures

Shake flask strain testing

pACYCpgl2 14,949 bp

Glycosylation

pECAcrA6,552 bp

Target protein

5.5 mg/L19% glyco efficiency

10

Shake flask strain testing

• How can we move beyond our current glycosylation efficiency limits?

pACYCpgl2 14,949 bp

Glycosylation

pECAcrA6,552 bp

Target protein

5.5 mg/L19% glyco efficiency

11

Signal peptide modification

0

1000

2000

3000

4000

5000

6000

Sec Tat

Are

a u

nd

er p

eak

Export mechanism/signal sequence

CLM24 pgl2 pEC based plasmids • Glycosylation occurs in periplasm

• Varying export pathway changes product yield

• 86% increase using Tat over Sec

12

Chromosomal basing of OST

• N-linked glycosylation reliant

upon a key oligosaccharide protein, PglB

• Site specific chromosomal integration

Plasmid based pglB

Chromosomally based PglB

pglB minus strain

13

Chromosomal basing of OST

• N-linked glycosylation reliant

upon a key oligosaccharide protein, PglB

• Site specific chromosomal integration

• Increases glycosylation efficiency by 85%

over plasmid based expression

Plasmid based pglB

Chromosomally based PglB

pglB minus strain

14

Glyco band

Noglyco band

Glycosylation of human therapeutics

15

• Fermenter study using IFNα2b with internal glycosylation site

• Glycosylation efficiency up to 19% identified

Aglycosylated band

Glycosylated band

Glycosylation of human therapeutics

16

• Fermenter study using IFNα2b with internal glycosylation site

• Glycosylation efficiency up to 19% identified

Aglycosylated band

Glycosylated band

17

Identifying metabolic bottlenecks

• Cells aren’t inherently optimised to generate glycoprotein

• Global approach to identify metabolic bottlenecks within cells

• Quantitative proteomics - iTRAQ

• Inverse metabolic engineering – with Ryan Gill’s group

[9]

[9] Pandhal. J., Woodruff. L. B. A., Jaffé. S., Desai. P., Ow. S. Y., Noirel. J., Gill. R. T., Wright. P. C. (2013) Inverse metabolic engineering to improve Escherichia coli as an N-glycosylation host. Biotechnology and Bioengineering. 110. 9. 2482-2493. [10] Pandhal. J. et al (2011) Improving N-glycosylation efficiency in Escherichia coli using shotgun proteomics, metabolic network analysis, and selective reaction monitoring. Biotechnology and Bioengineering. 108. 4. 902-912.

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Removing metabolic bottlenecks

• Overexpression of components ofcentral metabolism

• Isocitrate lyase (ICL) – 3.8 fold increase GP[10]

• Phosphotransferase system (ptsA) – 6.7 fold increase TP [9]

• 1-deoxyxylulose-5-phosphate synthase (dxs) – 1.6 fold increase GP [9]

• How do we push this further?[8] Jaffé et al. (2014) Escherichia coli as a glycoprotein production host: recent developments and challenges. Current Opinion in Biotechnology. 30. 205-210. [9] Pandhal. J et al. (2013) Inverse metabolic engineering to improve Escherichia coli as an N-glycosylation host. Biotechnology and Bioengineering. 110. 9. 2482-2493. [10] Pandhal. J. et al (2011) Improving N-glycosylation efficiency in Escherichia coli using shotgun proteomics, metabolic network analysis, and selective reaction monitoring. Biotechnology and Bioengineering. 108. 4. 902-912.

[8]

19

Combining -omics data sets

Identifying overlapping targets

Quantitative proteomics 1

Quantitative proteomics 2

Quantitative proteomics 3

Genetic level analysis

• Pooling of the global analysis data

• Identification of key targets

• Necessity to add directionality todata

20

Adding directionality and weighting

Quant proteomics 1

Quant proteomics 2

Quant proteomics 3 (1)

Quant proteomics 3 (2) IME

21

Metabolic engineering testing

• Plasmid consolidation and overexpression of central carbon metabolism enzymes

pACYCpgl2 14,949 bp

Glycosylation

pECAcrA-met eng 9,325 bp

Target and met eng

pECAcrA-met-eng

10,456 bpTarget and met eng

28% glycosylation efficiency

26% glycosylation efficiency

22

Glyco quant

• Currently a combination of western blot and mass spectrometry

• Mass spec is the gold standard of this technology

• Simplified methodology

• Developing a methodology to simultaneously:– Determine absolute protein concentration– Glycosylation efficiency

23

No released glycan analysis

24[11] Marino. K., Bones. J., Kattla. J. J., Rudd. P. M. (2010) A systematic approach to protein glycosylation analysis: a path through the maze. Nature chemical biology. 6. 713-723.

Glyco quant - Western

25

kDa Ladder G1 G2 AG1

Glyco quant – Westerns

26

Glyco quant – Mass spec

27

N14 – Target (light) protein

Glyco quant – Mass spec

28

N14 – Target (light) protein N15 – Heavy protein

Glyco quant – Mass spec

29

N15 – Heavy protein

Glyco quant – Mass spec

30

• Purify and quantify N15 protein using HPLC

Inte

nsi

ty

Retention time

Glyco quant – Mass spec

31

N15 – Heavy peptides

• Selectively digest protein using protease of choice i.e. Trypsin

Glyco quant – Mass spec

32

• Run on mass spec

• Identify peptides

• Identify m/z

Glyco quant – Mass spec

33

• Generate standard curve of proteins to run on MS

• Determine which peptides show linearity at varyingconcentrations

0.0

Pe

ak In

ten

sity

IDLDHTEIK

Glyco quant – Mass spec

34

0.4 µg of 15N AcrA spiked into the sample pre-tryptic digestion

IDLDHTEIK

Glyco quant – Mass spec

35

0.2 µg of 15N AcrA spiked into the sample pre-tryptic digestion

IDLDHTEIK

Glyco quant – Mass spec

36

0.1 µg of 15N AcrA spiked into the sample pre-tryptic digestion

IDLDHTEIK

Glyco quant – Mass spec

37N14 – Target (light) protein N15 – Heavy protein

• Mix undigested heavy (N15) protein with undigested light (N14) protein and co-digest

Glyco quant – Mass spec

38

N14 and N15 – Light and Heavy peptides

All 1:1 ratio

Glyco quant – Mass spec

39

N14 and N15 – Light and Heavy peptides

Glyco quant – Mass spec

40

N14 and N15 – Light and Heavy peptides

1 0.55

Glyco quant – Mass spec

41

N14 and N15 – Light and Heavy peptides

1 0.55 0.45

Glycopeptide analysis

• Detection of glycan diagnostic ions within IFN

= HexNAc= HexHexNAc

42

Summary

• Metabolic engineering strategies can be utilised to increase glycoprotein yield

• Chromosomally basing OST, pglB, increases glycosylation efficiency

• Mass spectrometry can provide accurate, simultaneous yield and glycosylation efficiency data

43

Thank youDr. Benjamin Strutton –Recently passed PhD student – University of Sheffield, UK

Dr. Gregory Fowler – Post Doc – University of Sheffield, UK

Dr. Jagroop Pandhal –Lecturer – University of Sheffield, UK

Prof. Phillip C. Wright. –Pro Vice chancellor of Science, Agriculture and Engineering – Newcastle University, UK

Prof. Colin Robinson –University of Kent, UK

44

Dr. Zdeno Levarski – Post Doc – Comenius University Science Park, Slovakia

Dr. Caroline Evans – Post Doc – University of Sheffield, UK

Email: s.jaffe@sheffield.ac.uk

Dr. Josselin Noirel –Lecturer - Conservatoire national des arts et métiers, France

mailto:s.jaffe@sheffield.ac.uk

References

1. Walsh. B. (2014) Biopharmaceutical benchmarks 2014. Nature Biotechnology. 32. 10. 992-1000

2. Munkley. J., Mills. I. G., Elliott. D. J. (2016) The role of glycans in the development and progression of prostrate cancer. Nature reviews urology. 13. 324-333.

3. Hossler. P., Khattak. S. F., Li. Z. J. (2009) Optimal and consistent protein glycosylation in mammalian cell culture. Glycobiology. 19. 9. 936-949.

4. Baker. J. L., Celik. E., DeLisa. M. P. (2013) Expanding the glycoengineering toolbox: the rise of bacterial N-linked protein glycosylation. Trends in biotechnology. 31. 5. 313-323.

5. Wacker. M., Linton. W., Hitchen. P. G., Nita-Lazar. M., Haslam. S. M. North. S. J., Panico. M., Morris. H. R., Dell. A., Wren. B. W., Aebi. M. (2002). N-linked glycosylation in Campylobacter and its functional transfer into E. coli. Science. 298.1790-1793.

6. Nothaft. H., Szymanski. C. 2010. Protein glycosylation in bacteria: sweeter than ever. Nature Reviews Microbiology. 8. 768-778

7. Huang. C. J., Lin. H., Yang. X. (2012) Industrial production of recombinant therapeutics in Escherichia coli and its recent advancements. J Ind Microbiol Biotechnol. 39. 383-399

8. Jaffé. S. R. P., Strutton. B., Levarski. Z., Pandhal. J., Wright. P. C. (2014) Escherichia coli as a glycoprotein production host: recent developments and challenges. Current Opinion in Biotechnology. 30. 205-210.

9. Pandhal. J., Woodruf. L. B. Jaffe. S., Desai. P., Ow. S. Y., Noirel. J., Gill. R. T., Wright. P. C. (2013) Inverse metabolic engineering to improve Escherichia coli as an N-glycosylation host. Biotechnol. Bioeng. 110. 9. 2482-2493.

10. Pandhal. J. Ow. S. Y., Noirel. J. Wright. P. C. (2011) Improving N-Glycosylation Efficiency in Escherichia coli Using Shotgun Proteomics, Metabolic Network Analysis, and Selective Reaction Monitoring. Biotechnol. Bioeng. 108. 4. 902-912.

11. Marino. K., Bones. J., Kattla. J. J., Rudd. P. M. (2010) A systematic approach to protein glycosylation analysis: a path through the maze. Nature chemical biology. 6. 713-723. 45