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Measuring femto-Newton forces in enzyme turnover and its potential in highly specific pathogen detection Daniel Mitchell 1 , Simona Frustaci 2 , Frank Vollmer 2 , Neil Gow 3 , Jennifer Littlechild 1 . 1 Henry Wellcome Building for Biocatalysis, University of Exeter, Exeter, UK. 2 Life Sciences Institute, University of Exeter, Exeter, UK. 3 MRC Centre for Medical Mycology, University of Exeter, UK. [email protected] Cell wall remodelling enzymes of fungal pathogens present a promising new method of highly sensitive detection methods ΔΔ2 Δ1 Δ3 time Enzyme conformational states C 3 C 2 C 1 Whispering gallery mode sensors provide single-molecule level of detection From this we can generate an enzymes unique activity profile, allowing us to detect certain enzymes and substrates in a sample solution
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Page 1: Measuring femto-Newton forces in enzyme turnover and its ... · Measuring femto-Newton forces in enzyme turnover and its potential in highly specific pathogen detection Daniel Mitchell1,

Measuring femto-Newton forces in enzyme turnover and its potential in highly specific pathogen detection

Daniel Mitchell1, Simona Frustaci2, Frank Vollmer2, Neil Gow3, Jennifer Littlechild1.1Henry Wellcome Building for Biocatalysis, University of Exeter, Exeter, UK. 2Life Sciences Institute, University of Exeter,

Exeter, UK.3MRC Centre for Medical Mycology, University of Exeter, UK.

[email protected]

Cell wall remodelling enzymes of fungal pathogens present a promising

new method of highly sensitive detection methods

Δ⍵

Δ⍵ 2

Δ⍵ 1

Δ⍵ 3

time

Enzyme conformational states

C3

C2

C1

Whispering gallery mode sensors provide single-molecule level

of detection

From this we can generate an enzymes unique activity profile, allowing us to

detect certain enzymes and substrates in a sample solution

Page 2: Measuring femto-Newton forces in enzyme turnover and its ... · Measuring femto-Newton forces in enzyme turnover and its potential in highly specific pathogen detection Daniel Mitchell1,

Measuring femto-Newton forces in enzyme turnover and its potential in highly specific pathogen detection

Daniel Mitchell1, Simona Frustaci2, Frank Vollmer2, Neil Gow3, Jennifer Littlechild1.1Henry Wellcome Building for Biocatalysis, University of Exeter, Exeter, UK. 2Life Sciences Institute, University of Exeter, Exeter, UK.

3MRC Centre for Medical Mycology, University of Exeter, UK.

References:

Fungal pathogens, a world-wide health problem.Using whispering gallery mode sensors for enzyme

activity detection.

Attaching a model enzyme to the sensor. Key enzyme in pathogenic Candida albicans and

sensing

Creating a biosensor

How active is the enzyme on gold?

0 50 100 150

0.0

0.5

1.0

1.5

Concentration Serine (mM)

Acti

vit

y (

M.m

in-1

)

In Solution

On Gold

In S

olutio

n

On G

old

0.0

0.5

1.0

1.5

Vm

ax (

M.m

in-1

) In Solution

On Gold

Transaminase from

Chromobacterium violaceum

Use a transaminase enzyme from Chromobacterium

violaceum as a model test case.

R'

O

O

O

R

NH2

O

OR'

NH2

O

O

R

O

O

O

+ +

amine 1 oxo-acid 1 amine 2oxo-acid 2

• Thermophilic enzyme – stable at a

range of pH and temperatures.

• Large structural change - easier to pick

up on a sensor (solved crystal

structure).

• Relatively slow turnover – also easier to

see on sensor.

Which enzyme?

Attachment to AuNP:

AuNP Attach NTA-Ni to

AuNP Attach 6xHis Protein

We can successfully attach our enzyme to AuNPs via a 6xHis tag and it is active.

• Every year fungal infections kill approximately 1.5 million people

world-wide, yet remain understudied and underdiagnosed.1

• Multidrug resistant strains are also becoming more common.

1 G. D. Brown et. al. Science 2012; 336, pp. 647.2 https://www.gaffi.org/why/burden-of-disease-maps/cpa-prevalence.3 F. Bongomin et. al. J. Fungi, 2017; 3, pp. 57.4 M.R. Foreman et. al. Adv. Opt. Photonics, 2015; 7 pp. 168–240.

• Approximately 90% of deaths are

caused by 4 genera of fungi:

Candida, Aspergillus, Cryptococcus

and Pneumocystis.

• Detection and treatment is limited in

developing countries. Over 80 % of

deaths could be avoided with

appropriate diagnostics and

availability of antifungals.3

Estimated yearly fungal deaths in the USA2

Candida infection pathology2

Currently, the identification of fungal pathogens is largely limited to the detection of

β-1, 6-glucans on the fungal cell wall and this has serious issues with specificity

and resolution. we want to design a rapid and innovative new method for the

precise identification of fungal pathogens at low concentration.

World map showing chronic under-reporting of

fungal infections.3

Xog1 – An exoglucanase

A key enzyme of interest is the

exoglucanase, Xog1 which cleaves

the terminal glucose from glucans

within the fungi cell wall, hiding them

from our immune system.

Cleavage site

β- 1-3 glucan- Xog1 cuts the terminal glucose

Cuts any

exposed β-

1-3 glucan

Whispering galleries: optical and

acoustical

Candida albicans cell wall schematic5

The Xog1 is active and stable at a range of temperatures and attached to

gold nanoparticles making it a good choice for the biosensor!

Human antimicrobial peptide LL-37 which can bind Xog1 glucanase enzyme

1.Determine unique activity profile of Xog1 on whispering gallery sensor.

2.Human antimicrobial peptide LL-37 has been found to bind Xog16 – can use this to detect Xog1 from Candida, and bind it

to the whispering gallery sensor.

3.Use an electrochemical sensor to detect free glucose from Xog1 breakdown of β- glucans as per commonly used

diabetes sugar monitoring.7

Glucose

Glucose oxidase

FADH2

FAD

H2O2

O2

ElectrodeGluconolactone

Xog1 breaks

down β-glucans

Electrical current

5 N. A. R. Gow et. al. Nat. Rev. Microbiol. 2011; 10 pp.

112 – 122.6 P. W. Tsai et. al. PLoS One 2011; 6, e21394.7, E-H Yoo and S-Y Lee, Sensors, 2010; 10, 4558–4576.

Example detection of analyte using

antibody based whispering gallery sensor.

The femto – Newton conformational changes in enzymes during substrate

binding and turnover are impossible to measure using standard techniques.

We aim to use optoplasmonic sensors, consisting of a whispering gallery

resonator with attached plasmonic gold nanoparticle to detect the very

small changes in resonance caused by the conformational changes of an

enzyme.

From this we can build up a picture of each enzyme- substrate specific

interaction to build up a very specific single molecule detection system.

LL-37 binding site on Xog1

Δ⍵

Δ⍵ 2

Δ⍵ 1

Δ⍵ 3

time

Enzyme conformational states

C3

C2

C1

Example change in resonance frequency of the sensor when

the enzyme is in different conformations.

0 20 40 60

0.5

0.6

0.7

0.8

Concentration LL-37 (µM)

Activ

ity (µ

M.m

in-1

)

Activity of Xog1 with LL-37 Gold-labelled Xog1 on LL-37 superstructure.


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