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A FRET-based method to study the activity of electron or oxygen transfer proteins and redox enzymes Zauner, G.

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oxygen transfer proteins and redox enzymes

Zauner, G.

Citation

Zauner, G. (2008, October 23). A FRET-based method to study the activity of electron or oxygen transfer proteins and redox enzymes. Retrieved from https://hdl.handle.net/1887/13201

Version: Corrected Publisher’s Version

License: Licence agreement concerning inclusion of doctoral thesis in the Institutional Repository of the University of Leiden

Downloaded from: https://hdl.handle.net/1887/13201

Note: To cite this publication please use the final published version (if applicable).

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Appendix to Chapter VI

The Enzyme Mechanism of Nitrite Reductase Studied at Single Molecule

Level

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Effect of bin size on autocorrelation graphs

Figure A.1. Autocorrelation graphs calculated with the use of bin sizes varying from 1 to 10 ms. The direct autocorrelation graph was calculated on the basis of the photon arrival times (1;2). The latter procedure turned out to be time consuming in our hands, which is why binning was preferred. The bin size eventually used for the calculation of the correlation graphs was 1 ms. The graphs were calculated from the fluorescence time trace of a single immobilized and labeled NiR molecule in the presence of 5

M nitrite. For other experimental conditions: see Methods section.

Enzyme mechanism

Regarding the enzyme mechanism two pathways have been distinguished: “reduction first” (3;4) and “binding first” (5). Recent investigations show that the enzyme operates according to a "random sequential mechanism" in which both pathways run in parallel (6). This is summarised in Scheme A1 where "A" denotes the "reduction first" pathway and "B" the "binding first" alternative. At saturating nitrite

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concentrations pathway "B" becomes the preferred pathway, while at high pH the Michaelis-Menten constant KM of this pathway becomes so large that "A" prevails.

The choice of pH and nitrite concentration in the present study favour the lower pathway ("A") (6). Scheme 6.1 is obtained from Scheme A1 by considering only pathway "A" and by taking into account that the last step in the substrate conversion (i.e. the step OxRed.S ----> OxOx + P) is not rate limiting (6-9).

RedOx

RedOx.S

OxOx

OxRed

OxRed.S S

OxOx + P

S

A B

R

Scheme A.1. Enzyme mechanism of NiR. "RedOx" denotes the state of the enzyme in which the type-1 site is reduced and the type-2 site oxidized and so on. R, S and P denote reductant, substrate and product, respectively. The states in red exhibit a high dye label fluorescence intensity, the others a low intensity.

"A" and "B" denote the "reduction first" and the "binding first" pathway, respectively.

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Absorption spectra of label and nitrite reductase

400 500 600 700 800 900

0 1 2 3 4 5 6

0.0 0.2 0.4 0.6 0.8 1.0

NiR absorption, mM-1 cm-1

Wavelength, nm

ATTO 655 emission

Figure A.2. Alcaligenes faecalis S-6 nitrite reductase absorption (solid line) and Atto655 emission (dashed line).

Calculation of Förster radius

R0 = 3.5 nm for the Atto655 to type-1 Cu of NiR energy transfer. R0 was calculated from the equation R0 = 0.211(JN2n-4)D)1/6 Å (10), with a refractive index n of 1.4, an orientation factor N of 2/3, corresponding to free rotation of both donor and acceptor (10) and a quantum yield of Atto655, )D, in the absence of the acceptor of 0.3 as given by the manufacturers. The spectral overlap integral J = ³FD(O)HA(O)O4dO /

³FD(O)dO was calculated from the fluorescence spectrum of the donor Atto655, FD(O), as supplied by the manufacturer, and the measured absorption spectrum of NiR, HA(O), as measured in the present study. The distance from Atto655 to type-1 Cu of NiR was estimated as R = (d + 1) nm ± 0.5 nm = 3.9 ± 0.5 nm, where d is the

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distance from the dye attachment point to type-1 Cu as derived from the protein crystal structure (11). As the structure of Atto655 is proprietary, a more precise estimation of the donor-acceptor distance is not possible. (For further details on the estimation of the distances between donor and acceptor as well the influence of N, please also see chapter 2.)

Fluorescence traces under aerobic and anaerobic conditions

Figure A.3. Fluorescence traces of a labeled, immobilized single molecule of the H145A/L93C variant of NiR. This (colourless, since the type 1 site is permanently reduced) variant is enzymatically inactive and exhibits no turn-over. The top trace was measured in buffer only (20 mM Hepes, pH 7), the lower trace after addition of ascorbate/PES (see Methods section for details). Addition of nitrite has no effect on the appearance of the traces.

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Autocorrelation graphs at two nitrite concentrations

Figure A.4. Autocorrelation graphs of fluorescence traces of six labeled and immobilized L93C NiR molecules at room temperature and 50 M nitrite. The trace of a seventh molecule is left out because of excessive noise. For other experimental conditions: see Methods section.

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Figure A.5. Autocorrelation graphs of fluorescence traces of seven labeled and immobilized L93C NiR molecules at room temperature and 500 M nitrite. For other experimental conditions: see Methods section.

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Scheme 6.1 and Michaelis-Menten kinetics

As stated in the main text, on the basis of the work by Qian and Elson (12) the general form of the autocorrelation function of the fluorescence intensity can be formulated as

) exp(

) exp(

)

(t A1 1t A2 2t

G ˜

O

 ˜

O

, Eq.A1

where

) 2(

1

3 3 2 1

2 ,

1  k ˜Sk k k r '

O

Eq.A2

3 3 2 2 3 3 2

1 ) 4( )

(k ˜Sk k k  k k k

' and S is the substrate concentration.

According to Scheme 6.1 the product formation rate, dt

dP, is given by

)

1 S P (OR

dt k dP

˜ SS

˜ . Eq.A3

The steady-state probability of the OR-state, PSS(OR), can be calculated from (12)

2 1

3

2

)

(

O O

k OR k

PSS Eq.A4

from which follows

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2 1

3 2 1

1 ( )

O O

S k k OR k P S dt k

dP

SS

˜ ˜

˜

With

O

1

O

2 k1S(k2 k3)k2(k3 k3) (see equation Eq. A2) it can be seen that

dt

dP follows Michaelis-Menten kinetics, i.e.

KM

S V S dt dP

˜ 

max ,

with

) (

) (

3 2 1

3 3 2

k k k

k k KM k



 

and

) ( 2 3

3 2

max k k

k V k



Alternative Schemes

The consequences of the use of an alternative for Scheme 6.1 have been investigated by considering

Scheme A2.

RR RO k

3

OR k

-3

k

1

NO

2-

Scheme A.2.

Here state "1" is the form of NiR in which the type-1 and the type-2 site are both reduced ("RR"). State "2" is the form in which the type-1 and the type-2 site are reduced and oxidized, respectively ("RO"). State "3" is the form in which the type-1 and the type-2 site are oxidized and reduced, respectively ("OR"). Conceivably this scheme might apply at very low nitrite concentrations or when the reduction of the type-1 site is very fast.

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Denoting the fluorescence signal from state i by f(i) (12) the mean fluorescence signal is

<f> = P1SS + P2SS

with PiSS denoting the steady state probability of occupation of state i. Following the formalism of ref. (12) the time correlation function becomes

C2() = P11() P1SS + P12() P1SS + P21() P2SS + P22() P2SS + - ( P1SS )2 - P1SS P2SS – P2SS P1SS - ( P2SS )2

The Pij() are bi-exponential functions with rate constants 1 and 2 so that

C2() = A1exp(1) + A2exp(2).

We further find after some algebra

-21,2 = (k1S + k2 + k3 + k-3) ±  Eq.A5

 = (k1S – k3 – k-3 – k2)2 – 4k2k3 Eq.A6

and

P1SS + P2SS = 1 – P3SS = 1 – k1S k3/( 1 2) Eq.A7

Retaining, as before, only 2 in the data analysis with

-22 = (k1S + k2 + k3 + k-3) -  Eq.A8

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and using equations Eqs.A8 and A7 (instead of equations Eqs.6.5 and 6.6 of the main text, respectively) to fit the data in Figures 6.4A and 6.4C no satisfactory global fit could be obtained.

When using equations Eqs. A7 and A8 to fit the low concentration data in Figures 6.4A and 6.4C (5 and 50 M nitrite) and equations Eqs. 6.5 and 6.6 of the main text to fit the high concentration data (500 and 5000 M nitrite) in a single global fit, the fit is almost as good as the one reported in the main text with values for the rate constants that are similar to the values reported in the main text within the experimental uncertainty.

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Reference List

1. Wahl, M., Gregor, I., Patting, M., and Enderlein, J. (2003) Optics Express 3583- 3591.

2. Laurence, T. A., Fore, S., and Huser, T. (2006) Optics Letters 829-831.

3. Zumft, W. G. (1997) Microbiol Mol Biol R 533-+.

4. Abraham, Z. H. L., Smith, B. E., Howes, B. D., Lowe, D. J., and Eady, R. R.

(1997) Biochemical Journal 511-516.

5. Adman, E. T. and Murphy, M. E. P. (2001) in Handbook of Metalloproteins (Messerschmidt, A., Huber, R., Poulos, T., and Wieghardt, K., Eds.), pp. 1381- 1390, John Wiley & Sons, Chichester.

6. Wijma, H. J., Jeuken, L. J. C., Verbeet, M. P., Armstrong, F. A., and Canters, G.

W. (2006) J Biol Chem 16340-16346.

7. Kobayashi, K., Tagawa, S., Deligeer, and Suzuki, S. (1999) Journal of Biochemistry 408-412.

8. Wijma, H. J., Jeuken, L. J. C., Verbeet, M. P., Armstrong, F. A., and Canters, G.

W. (2007) Journal of the American Chemical Society 8557-8565.

9. Zhao, Y. W., Lukoyanov, D. A., Toropov, Y. V., Wu, K., Shapleigh, J. P., and Scholes, C. P. (2002) Biochemistry 7464-7474.

10. Lakowicz J.R. (1999) Principles of fluorescence spectroscopy, Kluwer Academic/Plenum Publishers, New York, Boston, Dordrecht, Moscow.

11. Murphy, M. E. P., Turley, S., and Adman, E. T. (1997) J Biol Chem 28455- 28460.

12. Qian, H. and Elson, E. L. (2002) Biophys Chem 565-576.

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