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The importance of fluid mechanics in the microbial world: From the transport of bacteria to the formation

of biofilms

Prof. Roberto Rusconi

ERC Advanced Grant (N. 339032) “NewTURB” (P.I. Prof. Luca Biferale)

Università degli Studi di Roma Tor Vergata C.F. n. 80213750583 – Partita IVA n. 02133971008 - Via della Ricerca Scientifica, 1 – 00133 ROMA

The importance of fluid mechanics in the microbial world:

From the transport of bacteria to the formation of biofilms

Roberto Rusconi

Bacteria within biofilms are up to 1000 times more resistant to antibiotics

Hall-Stoodley et al. Nat. Rev. Microbiol. 2004

Catheters

Implants

Gums

Endocarditis

Lung infections

Urinary infections

The “biofilm” threat

University of Rome Tor Vergata - 29th November 2018

Monds & O’Toole. Trends Microbiol. 2009

Industrial applications

Medical devices

Environment

Biofilms form everywhere and often in the presence of flow


Rusconi & Stocker. Curr. Op. Microbiol. 2015

Guasto, Rusconi & Stocker. Annu. Rev. Fluid Mech. 2012

How does fluid flow affect bacterial swimming dynamics?

Relative flow speed (mm/s)

Shear (s-1)0-10 10

0 0.5-0.5

Bacillus subtilis

1 cm

x

y

H=

750

µm

x

y

z


Flow, t = 15 sFlow, t = 5 s Flow, t = 30 s

Bacterial concentration0.5 1 1.50

No flow

0

-0.3

0.3

y/W

How does fluid flow affect bacterial swimming dynamics?

Dead cells

Flow, t = 30 s

0.5 1 1.50

1 cm

x

y

H=

750

µm

x

y

z


Mean shear S = 1.25 s-1 S = 2.5 s-1 S = 5 s-1 S = 10 s-1 S = 25 s-1 S = 50 s-1

Bac

teria

l con

cent

ratio

n

0.5

1.5

Maximal depletion occurs at intermediate shear

100

B. subtilis – wild typeB. subtilis – smooth swimmerP. aeruginosa

0

0.2

0.4

1 10D

eple

tion

inde

xMean shear rate, S (s-1)

• Rod shape (1µm x 3µm)

• Multiple flagella

• Rod shape (0.5µm x 1.5µm)

• Single flagellum

Bacillus subtilis

Pseudomonas aeruginosa

1



Bac

teria

l con

cent

ratio

n

0.5

1.5


1


x

y

ϕ

V

q Swimming speed, V = 50 µm/s

Rotational diffusion, DR = 1 rad2/s

Aspect ratio, q = 10


Bac

teria

l con

cent

ratio

n

0.5

1.5


1


x

y

ϕ

V




Experiments Simulations


Bac

teria

l con

cent

ratio

n

0.5

1.5


1


x

y

ϕ

V




Experiments Simulations Simulations, spheres (q = 1)


Bac

teria

l con

cent

ratio

n

0.5

1.5


1


Swimming speed, V = 50 µm/s



Experiments

Elongated particle in shear flow

Simulations Simulations, spheres (q = 1)

Elongation and rotational diffusion control bacterial depletion in flow


Rusconi et al. Nat. Phys. 2014

B. subtilis – smooth swimmer

DR = 0

0

-0.3

0.3

y/W

ϕ

0 π/2 π-π/2-π

Zöttl & Stark. EPJE 2013

Tumbling

Swinging

Separatrix



DR = 1 rad2/s

ϕ

0 π/2 π-π/2-π

DR = 1 rad2/s, Experiments

ϕ

0 π/2 π-π/2-π

DR = 0

0

-0.3

0.3

y/W

ϕ

0 π/2 π-π/2-π

WS ~ S-0.5




DR = 1 rad2/s, Experiments

ϕ

0 π/2 π-π/2-π


Experiments, no flow

Experiments

Fokker-Planck



Dep

letio

n In

dex

Rotational Péclet number, Pe = S/DR

10-3

10-2

10-1

100

10-2 10-1 100 101 102 103

Pe2 S-0.5

Pe<<1Competition between shear-induced alignment and rotational diffusion

Pe>>1Depletion effect is limited by the distance between the separatrices


Ezhilan & Saintillan. J. Fluid Mech. 2015

Spatial heterogeneity in suspensions of phytoplankton cells




10 µm



10 µm

Barry, Rusconi et al. J. Roc. Soc. Interface 2015

Shear suppresses bacterial chemotaxis

1 cm

400 µm

N2 O2 (mM)

Glass

PDMS

1.2

0.1

Mean shear rate, S (s-1)

Che

mot

actic

inde

x

0

1

1 10 100Bac

teria

l con

cent

ratio

n

y/W

0

1

2

0-0.3 0.3

S = 2.5 s-1

S = 10 s-1

S = 25 s-1

S = 50 s-1

No flow

O2


Shear promotes surface attachment

1 cmB

acte

rial s

urfa

ce c

over

age

(%)

Time (s)0 1000 2000 3000

0

0.5

1

1.5

2S = 5 s-1

S = 10 s-1

S = 25 s-1

S = 50 s-1

No flow

S = 100 s-1

P. aeruginosa

Mean shear rate, S (s-1)10010

Sur

face

cov

erag

e ra

tio

1

2

P. aeruginosa


H. Auradou et al., in preparation

Wall shear rate (s-1)

E. coli

Nor

mal

ized

den

sity

Flow velocity Shear rate

Shear induces preferential attachment to corrugated surfaces



ExperimentsE. coli



Experiments

Simulations

E. coli




h= 100 µm

y x

z


Intensity distribution0.51 0

Escherichia coli GFP

q = 8, V = 22 µm/s, DR = 0.5 rad2/s



h= 100 µm

y x

z

Escherichia coli GFP

q = 8, V = 22 µm/s, DR = 0.5 rad2/s


Intensity distribution0.51 0



h= 100 µm

y x

zy(

µm)

15

0

0x (µm)

-15

20 40 60 80 100

V= 22 µm/s

V= 0 µm/s

Simulations

FlowFlow

Radial shear rate, S

r(1/s)

15

30

0

x (µm)0 25 50

FlowFlow



Experiments

Simulations

Motility and flow control bacterial transport and attachment around pillars


50 µm

U (m

m/s)

Sr (1/s)

0.5

1

0

20

40

0

FlowFlow velocity, U

Radial shear rate, Sr

200 µm

100 µm

50 µm

100 µmx

y

z



50 µmFlow

Flow

Pseudomonas aeruginosa PA14

50µmU=150 µm/s



y (µ

m)

P. aeruginosa PA14 GFP

45

0

0

-45

45-45x (µm)

Flow 25 µm

Intensity, I (a.u.)25 500

Fluorescent image of cells attached after 6 h of

continuous flow

PA14 wt GFPIntensity,I (a.u.)

5

10

0

PA14 ΔflgE GFP PA14 ΔmotB GFP



Id0.5

1

0

U= 150 µm/s U= 300 µm/s U= 600 µm/s U= 1000 µm/s

Normalized intensity distribution

Polar distribution

Simulations, ExperimentsFlow



Flow velocity, U (µm/s)500 1000

Τ𝜎 𝜃

𝜎 𝑢 0.8

1.2

0.4

B

U=

1000

µm

/sU

= 30

0 µm

/s

I/Imax0.51 0

B

C

C

1500

Τ𝜎 𝜃

𝜎 𝑢 0.8

1.2

0.4

Flow velocity, U (µm/s)500 1000 1500

(Τ

𝜎 𝜃𝜎 𝑢) e

xp

( Τ𝜎𝜃 𝜎𝑢) sim

1

0.510.5


1

0.6

1

0.6



Capture efficiency

η = Particles captured by the collector

Particles in the volume of liquid passing through the projected

area of the collector

Flow, Uη

0.00

1

250

0.00

01

500 750 1000

Flow velocity, U (μm/s)



Cap

ture

effi

cien

cy, η

1

0.1

10Péclet number, Pe

0.01

Simulations

1 103 105

Non-motile particles

Dcoll = 50 μmDcoll = 100 μmDcoll = 200 μm



Experiments – P. aeruginosa Simulations

η/D

pill(μ

m-1

)

10-2

I/Dpi

ll(a

.u.)

0.1

1

10 1000100

~Pe-1.1 10-4

10-3

~Pe-1.3

10 1000100Péclet number, Pe Péclet number, Pe

Flow around corners triggers the formation of streamers

100 µm

Pseudomonas aeruginosa suspension

Confocal z-scan after 8 hours of flow



100 µm

100 µm100 µm

100 µm 100 µm



100 µm

30 min 60 min 90 min

Bottom surface Mid-plane

100 µm


Streamer formation is independent of bacterial motility

100 µm 100 µm

100 µm 100 µm


Secondary flow drives streamer formation

100 µm

100 µmRusconi et al. J. R. Soc. Interface 2010


Secondary flow drives streamer formation

Rusconi et al. Biophys. J. 2011

100 µmNumerical simulations

Sharper turns

More streamers


Streamers are frequent in natural and artificial systems

Valiei et al. Lab Chip 2012

Drescher et al. PNAS 2013

Porous media

Filtration systems

Marty et al. Biofouling 2012

Medical stents


Summary and acknowledgments

Flow controls the spatial distribution of motile microorganisms

Flow affects the formation and the structure of biofilms

Flow induces preferential attachment of bacteria to surfaces


[email protected]

Eleonora Secchi (ETH)Roman Stocker (ETH)

Howard Stone (Princeton)

Jeff Guasto (Tufts)

Sigolene Lecuyer (Lyon)

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