Protein Engineering for Enzyme Catalysis with Microgels - Prof. Dr. Ulrich Schwaneberg
←
→
Page content transcription
If your browser does not render page correctly, please read the page content below
Protein Engineering
for Enzyme Catalysis with Microgels
Prof. Dr. Ulrich Schwaneberg
Lehrstuhl für Biotechnologie, RWTH Aachen University und
DWI-Leibniz Institut für Interaktive Materialien
Monschau SFB Mikrogele Summer School 2018, 11.7.2018
Microgels as Versatile Containers for
Immobilisation of Enzymes
Motivation: Enhance performance of enzymes
- Avoid deactivations e.g. in organic solvents
- Avoid degradation e.g. proteolytic digest
- Recovery in processes for reuse
- Efficient diffusion
- General applicable
- High compound loads possible
Immobilisation of Enzymes
3
Chem. Soc. Rev., 2013, 42, 6223-6235
Polymer-Biomacromolecule
Conjugates
-fast reactions in water
-no toxic by-products
-formation of stable covalent bonds
-orthogonal reactions
4
Sortase-Mediated Surface
Functionalization of Stimuli-Responsive Microgels
Conclusions:
• SrtA-mediated ligation enabled the efficient and
controllable decoration of the PVCL microgel surface
with the model protein GGG-eGFP
• Sortase-mediated ligation is a very promising and
powerful tool for the surface functionalization of
Sortase-mediated conjugation of eGFP on the surface microgels with biomolecules which opens up
of PVCL/GMA numerous possibilities to develop microgels with
tailored properties for biomedical and other
applications
Elisabeth Gau Diana M. Mate
Acknowledgements:
EG, AT and AP thank Volkswagen Foundation and DFG Collaborative Research
AFM images and confocal images of (a) PVCL/GMA-LPETG- Center 985 “Functional Microgels and Microgel Systems” for financial support. ZZ
microgels (no sortase) and (b) PVCL/GMA-LPETG-eGFP hybrid (with gratefully acknowledges the Chinese Scholarship Council (CSC) for his PhD
sortase ligation) fellowship.
Internal manuscript No. 188 Gau‡, Mate‡, Zou, Oppermann, Töpel, Jakob, Schwaneberg* and Pich* . Biomacromolecules. 2017;18,2789–2798. 5
Tunable Enzymatic Activity and Enhanced Stability of
Cellulase Immobilized in Biohybrid Nanogels
Facile approach for encapsulation of enzymes in nanogels
How is the biocatalytic activity
and stability of trapped protein
influenced by the chemical
structure of nanogel network?
Synthetic Procedure To Obtain Biohybrid Nanogels via
Cross-Linking in w/o emulsion
poly(N-vinylpyrrolidone-co-N-methacryloxysuccinimide)
167 Peng, H., Rübsam, K., Jakob, F., Schwaneberg, U., Pich, A. BioMacromolecules, 2016 6
Tunable Enzymatic Activity and Enhanced Stability
of Cellulase Immobilized in Biohybrid Nanogels
Biohybrid nanogels with varied degree of crosslinking density
(CNG4, CNG6, CNG8, and CNG10) were generated
Cryo-FESEM of biohybrid nanogels CNG4
Cellulase nanogels show decreased
activity compared to free cellulase
Specific activities of biohybrid nanogels CNGn (n = 4, 6, 8, and 10)
Secondary structures of the immobilized
cellulase is altered with increase of crosslink
density
Cellulase nanogels demonstrate
compared to free cellulase
significantly improved stability
organic solvents
chaotropic agents
storage stability
CD spectra of cellulase biohybrid Residual activities of free cellulase, CNG4,
nanogels CNG4, CNG6, CNG8, and CNG10 CNG6, CNG8, and CNG10, incubated with
organic solvents
167 Peng, H., Rübsam, K., Jakob, F., Schwaneberg, U., Pich, A. BioMacromolecules, 2016 7
Reversible Deactivation of Enzymes (Cellulase) by
Redox-Responsive Nanogel Carriers
self- add cross-
add DTT
assembly linker
Aggregate formation Protein encapsulated Protein encapsulated
(trapping of enzyme) nanogels (inactive) nanogels (active)
Highly efficient enzyme encapsulation and reversible modulation of enzyme activity by novel redox-
responsive polymeric nanogels cross-linker
co-polymer proteins
Figure 1. Enzyme encapsulation/deactivation in polymeric nanogels followed by release/activation under reducing conditions.
DDT: dithiothreitol, PMT: pentaerythritol tetrakis (3-mercaptopropionate), EED: 2,2′-(ethylenedioxy)diethanethiol
165 Peng, H., Rübsam, K., Jakob, F., Pazdzior, P., Schwaneberg, U., Pich, A. Macromol. Rapid Commun., 2016 8
Reversible Deactivation of Enzymes by Redox-Responsive Nanogel Carriers
Cellulase activity is determined
Degradation of generated Reduced activity of cellulase, by substrate diffusion process
protein nanogels by addition of when it is encapsulated in the in nonreductive conditions
DTT nanogels Increased acitivity of PNG
Particle size remains the same Cellulase activity is rapidly incubated with DTT can be
when no DTT was recovered in DTT solution attributed to release of
supplemented cellulase from nanogel
Specific nanogel activity [U/mg]
Light scattering intensity
Normalized emmission
intensity
RH/nm Incubation time Wavelength [nm]
DLS meassurement of PNG1 degradability Determination of protein nanogel cellulase FRET: Chromophore release from 2
in presence of 10 mM DTT activity (4-MUC assay) w/o 10 mM DDT differently loaded nanogels; upon addtion
of DTT emmision intensity shifts
immediately
PNG – protein nanogel; NG - nanogel
165 Peng, H., Rübsam, K., Jakob, F., Pazdzior, P., Schwaneberg, U., Pich, A. Macromol. Rapid Commun., 2016 9
Protein Engineering Worlds
10Mutagenesis methods for diversity generation
in directed evolution
Protein Engineering: Focused vs Random mutagenesis
Localized & rationally Non-understood
addressable properties properties
• Activity / Selectivity • Organic solvent
• Substrate profile • Ionic liquid
• Thermal resistance • pH stability
• Molar substrate/product
• ?pH profile? concentrations….
Shivange, A., Marienhagen, J., Schenk, A and Schwaneberg, U. (2009). Advances in Generating Functional Diversity, Curr.
Opin. Biotechnol., 13, 19-25.
11Why is focused mutagenesis necessary? ● Methods for ideal diversity generation: 100 aa: 20100= 1.267*10124 variants ● 1.000.000 variants screening: represents in [%] of sequence space
Random mutagenesis
13Directed protein evolution
● Key technologies are diversity generation and high throughput screening
● Traditional directed evolution:
● Low mutagenesis frequency: 1 to 5 mutations per 1000 bp usually 1 to 3 amino acid exchanges
● Small library size sampled: 1000-3000 clones
● Three to six iterative cycles often >6 amino acid substitutions in most beneficial variants
● Usually no molecular understanding of improved property
● Time requirements usually 1 to 2 years including screening development
14Classification of random mutagenesis methods
Wong, T. S., Zhurina, D. and Schwaneberg, U. (2006). The diversity challenge in directed protein evolution,
Combinatorial Chemistry and High Throughput Screening, 9, 271-289.
15Limitations of epPCR
Polymerase bias Only one nt of a codon Organisation of the
is mutated genetic code
63 of 100 mutations are 150 of 380 possible 1.67 codons per
A to G or T to C mutations amino acid exchanges “aromatic” amino acid
11Why is throughput important?
MAP benchmarking on the protein level!
12Consequences of bias on the protein level
Example: Subtilisin from Bacillus lentus (1GCI), epPCR (balanced dNTPs + Mn2+)
From: ● Schenk, A., Wong, T. S., Roccatano, D., Hauer, B. and Schwaneberg, U. (2006). SeSaM (Sequence Saturation
Mutagenesis): Eine Methode zur Sättigungsmutagenese eines Genes, BIOspektrum, 3 , 277-279.
● Wong, T. S., Roccatano, D., Zacharias, M. and Schwaneberg, U. (2006). A statistical analysis of current random
mutagenesis methods for directed protein evolution, J. Mol. Biol. 355, 858-871 (cover page).
● Low diversity and preference
● Mutagenic hot spots and barely for aa-substitutions to chemically
mutated regions similar ones
13MAP 3D Verma,R., Schwaneberg, U., and Roccatano, D. (2012). MAP2.03D: A sequence/structure based server for protein engineering. Synth. Biol., 1, 139-150.
State of the art
What do we find in a traditional directed evolution experiment?
14BSLA lipase (181 aas):
State of the art random mutagenesis by epPCR
• epPCR library with low mutations frequency (3.1 per kb)
epPCR-low
sequencing of 1000 mutations
• epPCR library with high mutations frequency (11.7 per kb)
sequencing of 1000 mutations
epPCR-high
What do you find?
0-4 amino acid substitutions of 19 possible substitutions
How many of the 181 amino acid positions are found to 15 positions epPCR-low
improve ionic liquid resistance BMIM-Cl? 18 positions epPCR-high
Zhao J, Kardashliev T, Joëlle Ruff A, Bocola M, Schwaneberg U. (2014). Lessons from diversity of directed evolution experiments by an analysis
of 3,000 mutations. Biotechnol Bioeng, 111(12), 2380-2389.
15What potential of improvement is obtainable?
22What potential for improvement is obtainable?
Library of BSLA variants is generated in which
• every variants habors one amino acid exchange
• the FULL natural diversity is covered (20*181= 3620 variants)
19Case study BSLA lipase (181 aas):
focused mutagenesis (with KE Jaeger)
• Saturation mutagenesis library of each position
• Extensive sequencing
• All 341 missing substitutions were manually
prepared via site directed mutagenesis
• Screening of eight properties
Bacillus subtilis BSLA
• Sequencing of the best 20 clones per position to 181 amino acids = 181 tripletts
gain a molecular understanding of interactions 64 x 181 = 11,584 mutant genes
19 x 181 = 3,440 variant proteins
For eight properties we can have the information on how many positions contribute to
property improvement and what improvement is obtainable with ONE amino acid exchange
How many of the 181 amino acid positions contribute to 104 positions
improve ionic liquid resistance BMIM-Cl? >50 %
VJ Frauenkron-Machedjou, A Fulton, L Zhu, C Anker, M Bocola, KE Jaeger and U Schwaneberg, ChemBioChem, 2015,
16(6):937-945
20Similar trends for other properties: Organic solvent resistance: out 181 positions
No. of beneficial positions
DMSO Dioxane TFE 104 positions
SSM 107 75 74 40 to 59 % of positions
epPCR-low 24 11 14 contribute again!
epPCR-high 29 13 19
Location of beneficial positions for dioxane
exposed buried
WT all positions 71% 29% Exposed positions
SSM 81% 19% preferred
epPCR-low 82% 18%
epPCR- high 92% 8%
a) SSM TFE
Strong preference for
charged and aromatic
substitutions
21Number of substitutions
Markel*, U., Zhu*, L., Frauenkron-Machedjou, V. J., Zhao, J., Bocola, M., Davari, M. D., Jaeger, K.-E., Schwaneberg, U.
(2017). Are Directed Evolution Approaches Efficient in Exploring Nature’s Potential to Stabilize a Lipase in Organic
Cosolvents? Catalysts, 7, 142
26Coverage of amino acid substitutions patterns for P450 BM3 heme domain
error-prone PCR SeSaM-TV SeSaM-TV-III
See: www.sesam-biotech.com
27Main conclusions
I. State of the art directed evolution experiments identify only a
small fraction of beneficial positions (Time efficient protein engineering
Key: Balance throughput and time requirement (5 to 6 aas)
Thursday, July 26, 29 in Concepts:
Knowledge gaining directed evolution: KnowVolution
Cheng, F, Zhu, L, Schwaneberg, U (2015) Directed evolution 2.0: improving and deciphering enzyme properties, ChemComm, 51(48):9760-72.Focused mutagenesis
31Focused Mutagenesis
3500000
3200000
3000000
Protein variants
2500000
2000000
1500000 State of the art
1000000
20 400 8000 160000
500000
0
1 AS 2 AS 3 AS 4 AS 5 AS
32OmniChange: Focused mutant library generation (EU patent granted)
Position G31 T77 K139 G187 V298
3 200 000 variants generated in one afternoon
START T77 Fw K139Fw G187 Fw V298 Fw D52 Fw STOP
V V 1 aag aag aaa aat aat
2 aag aat aag aag aat
Vector A1 B C D E A2 Vector 3 aat acg aag aag aat
4 aat acg aag aag aat
*D52 Rv
*T77 Rv
*K139 Rv
*
G187 Rv
*V298 Rv 5 acg act aat acg act
6 acg agt acg acg act
7 acg agt acg act agt
Step 1 Amplification by PCR, DpnI digestion and pufication 8 acg agt agg act atg
9 acg atg agg act att
10 acg att agg act cag
STOP START
V V 11 acg cag agg agg cag
12 act cag agt agt cat
A2 Vector A1 B C D E 13 atg cat agt agt cat
* * * * * 14 cat cat agt atg ccg
15 ccg ccg agt att cct
16 ccg ccg atg cag cct
Step 2 Cleavage (6 mM I2/EtOH; 5 min at 70 C)
17 ccg ccg att cag cct
18 ccg cgg att cag ctg
19 ccg cgg cag cat ctg
STOP START Fragment Amplification Primer Name Primer Sequence (5’-3’)
V V 20 cct ctg cag ccg ctt
21
A2-Vector-A1
cct E31Fw ctg ccg cct
ctagtgcttcagCGTAAGGGGCAAG ctt
A2 Vector A1 B C D E 22 cct E31Rv ctg ccg cgg gag
gataaccactcgMNNCAAAGTGTAACCCGTC
* * * * * 23
B
cct T77Fw ctt ccg cgt
cgagtggttatcTTGAGCCGCCATG gag
24 cct T77Rv gat cct ctg gag
catagaagccgccCATCAGMNNCACTAATTGCGC
25 cct K139 gcg ctg ctg
ggcggcttctatgGTGATTATTTCCG
gag
Step 3 Hybridization (5 min at 20 C) 26
C cct
Fw
gcg ctt ctg gat
K139Rv gaaacagtggatcAACCTTMNNCAAATCAGCCTG
27 cgg gcg gag ctt gcg
G187Fw gatccactgtttcACCCCGTCGAAG
* * * 28
D ctg gcg gag gag gct
* * * 29 ctg G187Rv gct gtg gag ggg
cagtgaaattgagAATCTCMNNCATCTGGGCAAATG
*
* 30 ctg V298Fw ggg gcg gat
ctcaatttcactgCTTCCCCCTATTGC ggg
E
* 31 gag V298Rv ggt gcg gat ggt
* ctgaagcactagCGCCGTMNNAATCTGTTGCAAC
Step 4 No gel extraction step
32
C/D/E/A2-Vector-A1
33
gag K139Fw ggt
gat D52 gtg
gcg gct
ggcggcttctatgGTGATTATTTCCG
gct gct
ggt
gtg
Transformation Rv ccacttatccggTGTGACMNNATTCATTAACTCTG
* * *
* No final PCR applification step
34
B’
35
gat D77Fw’ gtg
gcg gtt
gct ggc
ccggataagtggCCTCAATGGCCGGTAC
ggg ggt
gtg
gtt
36 gct T77Rv’ tag catagaagccgccCATCAGMNNCACTAATTGCGC
tat ggt tag
*
No additional sequences
37PCR gtt Forward primer
Colony
38
tag
tag Reverse primer
tat
TAATACGACTCACTATAGGG
tat
tcg
TCCAAAAGAAGTCGAGTGG
gtg
gtt
tat
tcg
1
No limitation by aa-positions
39
40
tat
tat
tat
tcg
tcg
tcg
tct
tgg
tct
tgg
41 tat tcg tcg tgg tgg
42 tat tcg tct ttg tgt
Dennig, A., Shivange, A.V., Marienhagen, J., and Schwaneberg, U. (2011). OmniChange: The Sequence
Independent Method for Simultaneous Site-Saturation of Five Codons, PLoS ONE 6(10): 26222.bt.
33Can those numbers be screened?
34iVDT-Basistechnologie-Platform High throughput screening by flow cytometry
BDInflux
• Analyzing of 200.000 and sorting of 70.000 events per s-1
( running at a few thousands per s-1)
• Sorting of 10.000.0000 events per hour
• Analysis and sorting based on fluorescence
• Enrichment in the active enzyme population as a
benchmark
Enables novel directed evolution strategies with
high mutational loads for efficient identification of beneficial amino acid positions
Best use as PRESCREENING system: sorting of ~2000 beneficial variants in MTPs/agar plates
35BMBF Basistechnologie Project iVDT:
Highlights
Whole cell: Fluorescent hydrogel-based FACS platform for hydrolytic enzymes
E. coli cells E. coli cells
• Coupled enzymatic reaction (phytase – glucose oxidase) phytase (-) phytase (+)
Strategy
• E. coli cells expressing active phytase form a fluorescent hydrogel around
Scanning force
microscopy
Confocal
microscopy
Activity distribution
Phytase activity
before sorting
Phytase
activity after
sorting
36BMBF Basistechnologie Project iVDT
A fluorescent hydrogel-based FACS screening platform for hydrolytic enzymes
Proof of concept for phytases: Toolbox for hydrolases
Fur-Shell technology was advanced
for three additional hydrolases:
cellulase, esterase, and lipase
Simple handing
High throughput screening toolbox
for directed hydrolase evolution
Esterase variant with 7-fold increase
in kcat and 2-fold reduced KM
Traditional directed evolution
yield often 1.5-2.5-fold
Lülsdorf,improvement
N., Pitzler, C. Biggel,per roundR., Vojcic, L. and
M., Martinez,
Schwaneberg, U. A flow cytometer-based whole cell screening toolbox
Pitzler, C., Wirtz, G., Vojcic, L., Hiltl, S., Böker, A., Martinez, R., for directed hydrolase evolution through fluorescent hydrogels, Chem.
Schwaneberg, U., Chem Biol. (2014) 21 (12):1733-42 Commun., 2015, 51(41):8679-82.
37From whole cell to cell free
38Part I – Optimization of in vitro cellulase production in emulsions
0 mg/ml BSA 1 mg/ml BSA
0.328 µM DNA
pIX3.0RMT7
°C
vector
25°C lin. DNA
(30°C)
2 mg/ml BSA
1 mg/ml
Additives e.g.
0.656 µM DNA BSA
4h
Substrate
Substrate
concentration
0.46 mM FDC
Amount of
0.656 µM
DNA
39Validation of the uHTS-IVC platform for directed cellulase evolution
- Screening of >1,2 Mio. events
- MTP analysis of 528 variants with 4-MUC assay revealed 33 cellulase variants improved
activity compared to parent
- Most promising variants were selected for rescreening
- Best identified variant CelA2-H288F-M1 (N273D/N468S) was purified and kinetically
characterized
Specific
kcat KM kcat/KM Amino acid
activity
[min-1] [µM] [min-1 µM-1] substitutions
[U mg-1]
CelA2-WT 0.11 (± 0.02) 48.37 (± 24.30) 0.002 16.57 (± 3.13) -
CelA2-H288F 0.50 (± 0.02) 8.95 (± 1.62) 0.056 72.62 (± 3.21) H288F
CelA2-H288F-M1 1.52 (± 0.04) 9.66 (± 1.19) 0.157 220.6 (± 6.71) N273D/H288F/N468S
Characterization in MTP format revealed the 13-fold improved cellulase variant M1
Flow cytometer-based uHTS-IVC technology platform successfully validated
Körfer, G., Pitzler, C., Vojcic, L., Martinez, R., Schwaneberg, U. (2016) In vitro flow cytometry-based screening platform for cellulase engineering,
Scientific Reports, 6, 1-12. DOI: 10.1038/srep26128.
40iVDTv2:Cellulase evolution: OmniChange library using in vitro flow cytometer platform
-In vitro expression in (w/o/w) emulsion and screening of 36,757,972 events by flow cytometer
-Sorting of 395,229 events
Georgette
Körfer
Reanalysis of sorted sample revealed 30-fold enrichment of active fraction
Kinetic characterization:
kcat/KM
kcat KM Specific activity Amino acid
Variants [min-1
[min-1] [µM] [U mg-1] substitution
µM-1]
CelA2-WT 0.11 (± 0.01) 22.53 (± 4.78) 0.005 16.27 (± 1.04) -
CelA2-H288F 0.58 (± 0.02) 7.66 (± 1.12) 0.075 83.87 (± 2.89) H288F
CelA2-H288F-M3 4.65 (± 0.26) 51.19 (± 7.55) 0.091 674.50 (± 38.17) H288F/H524Q
M3 shows 41-fold higher specific activity compared to CelA2-WT
Combinatorial effect between F288 and Q524 (N524, M524) successfully identified
41Summary
KnowVolution a strategy to balance throughput and time
requirement (5 to 6 aas)
Barely exploit the potential of protein sequence space
Main technical limitation: throughput screening technologies
Microgels enable to the converge the worlds of biocatalysis and
chemical catalysisThank you!
Towards understanding structure-function relationships ~60 PhD, post-docs, staff
Questions?
43You can also read
