# Substrate stiffness modulates bacterial adhesion and diversity of adherent
phenotypes across growth stages

René Riedel1, Garima Rani1, Anupam Sengupta ${}^{1,2^{\ast}}$

1Physics of Living Matter Group, Department of Physics and Materials Science,
University of Luxembourg, 162 A, Avenue de la Faïencerie, L-1511, Luxembourg
2Institute for Advanced Studies, University of Luxembourg,
2, Avenue de l’Université, L-4365, Esch-sur-Alzette, Luxembourg
∗E-mail<EMAIL_ADDRESS>
> Surface-adhesion and stiffness of underlying substrates mediate geometry,
> mechanics and self-organization of expanding bacterial colonies. Recent
> studies have qualitatively indicted that stiffness may impact bacterial
> attachment and accumulation, yet the variation of cell-to-surface adhesion
> with substrate stiffness remains to be quantified. Here, by developing a
> cell-level Force Distance Spectroscopy (FDS) technique based on Atomic Force
> Microscopy (AFM), we simultaneously quantify the cell-surface adhesion
> alongside stiffness of the underlying substrates to reveal stiffness-
> dependent adhesion in phototrophic bacterium Chromatium okenii. As stiffness
> of the soft substrate, modelled via low-melting-point (LMP) agarose pad, was
> varied between 20 kPa and 120 kPa by changing agarose concentrations, we
> observe a progressive increase of the mean adhesion force by over an order
> of magnitude, from $0.21\pm 0.10$ nN to $2.42\pm 1.16$ nN. In contrast,
> passive polystyrene (PS) microparticles of comparable dimensions showed no
> perceptible change in their surface adhesion, confirming that the stiffness-
> dependent adhesive interaction of C. okenii is of biological origin.
> Furthermore, for Escherichia coli, the cell-surface adhesion varied between
> $0.29\pm 0.17$ nN to $0.39\pm 0.20$ nN, showing a weak dependence on the
> substrate stiffness, thus suggesting that the stiffness-modulated adhesion
> is a species-specific trait. Finally, by quantifying the adhesion of C.
> okenii population across different timescales, we report an emergent co-
> existence of weak and strongly adherent sub-populations, demonstrating a
> diversification of adherent phenotypes over the growth stages. Taken
> together, these findings suggest that bacteria, depending on the species and
> their physiological stage, may actively modulate cell-to-surface adhesion in
> response to the stiffness of soft surfaces. Our results suggest how bacteria
> could leverage stiffness-dependent adhesion, and the diversity therein, as
> functional traits to modulate initial attachment, colonization and
> proliferation on soft substrates during the early stages of biofilm
> development.

## Introduction

From living tissues to biomedical scaffolds, bacteria attach and colonize a
wide range of surfaces, spanning orders of magnitude of stiffness (?, ?). Once
attached, subsequent growth and accumulation the surface-associated bacterial
populations are underpinned by mechanotransduction, ultimately leading to
well-developed biofilm structures (?, ?, ?, ?). Surface sensing and mechano-
response during initial stages of biofilm development (?, ?, ?, ?) are crucial
for the long term fate of biofilms. At the scale of individual cells, the
surface energy of underlying substrates, i.e., their hydrophobicity and
hydrophilicity, influence bacterial adhesion (?, ?, ?, ?, ?). In addition, van
der Waals and electrostatic forces could regulate the cell-surface
interactions (?, ?), thereby influencing biofilm growth. Recent results have
also accounted for local osmotic pressure and poroelastic attributes of
substrates in controlling biofilm growth and morphology (?).

Over the recent years, multiple studies have indicated at the possible role of
the substrate stiffness on the bacteria-surface adhesion. Majority of these
studies have been conducted on agarose and poly-ethylene glycol (PEG)
hydrogels (?, ?, ?), and on polymeric substrates including poly-
dimethylsiloxane (PDMS) (?, ?, ?) and composite thin films (?, ?). While
different bacterial species have been covered in these studies, a generalized
framework – capturing the impact of stiffness on bacterial adhesion – is yet
to emerge, in part due to observable inconsistencies across the reported
trends (?, ?, ?). Traditionally, agarose, a linear polymer composed of
alternating D-galactose and 3,6-anhydro-L-galactopyranose monomers (?) has
been frequently used in studying bacterial growth and biofilm assays. Agarose
possesses high gel strength, transparency, (?) and non-toxicity, making them
suitable for investigating bacterial adhesion, growth and self-organization on
such surfaces (?, ?, ?, ?). More recently, low-melting-point (LMP) agarose has
gained attention as a special form of agarose (?, ?, ?) wherein the gelling
temperature is decreased due to chemical modifications, for example via
hydroxyethylation (?). The ability to form thermoreversible gels at low
temperatures makes LMP agarose a preferred choice where gentle gelation
conditions are desired, for instance, for bacterial assays (?, ?, ?),
encapsulation of heat-sensitive biomolecules (?), tissue engineering scaffolds
(?), drug delivery systems (?, ?), and 3D cell culture models (?).

Despite the growing relevance of LMP agarose for bacterial studies, a thorough
quantification of their mechanical properties are largely lacking. Bulk and
local elasticity, stiffness and adhesion of substrates are of particular
interest in microbial ecology, as they not only influence the physiology and
behavior of cells, but also impact the biophysical underpinnings of bacterial
growth, feedback and emergent traits (?, ?, ?). Elasticity is a fundamental
mechanical property that characterizes the ability of a material to deform
under an applied force and return to its original shape upon force removal.
Various techniques, including bulk rheology and local atomic force microscopy
(AFM) have been employed to investigate the elastic properties of such soft
gels to understand their behavior under different loading conditions (?, ?,
?). Adhesion, the ability of a material to stick to another material, may
originate either due to mechanical interlocking or various physico-chemical
interactions between surface molecules (?). In the context of bacterial
adhesion, diverse species- and trait-specific attachment mechanisms have been
proposed, which ultimately underpin the growth and dynamic self-organization
into bacterial colonies (?, ?, ?, ?, ?). While recent studies have indicated
that bacterial attachment and accumulation could be impacted by the stiffness
of the underlying substrates, currently we lack methodologies which could
allow simultaneous measurement of both parameters. Furthermore, how stiffness-
dependent adhesion evolves with the age of a bacterial population remains
unexplored. As described in the aforementioned studies, the impact of
stiffness on cell-surface adhesion has received qualitative treatment so far,
either by estimation of the surface density of the adhering cells, or via
retention-assays which estimate the relative fraction of leftover cells
following a washing protocol. Quantification of the cell-surface adhesion
forces, alongside concomitant measurement of the underlying substrate
stiffness is currently lacking.

Motivated by the gaps in our current understanding, here we investigate the
mechanical properties of LMP agarose gels prepared with different LMP agarose
concentrations in Lysogeny broth (LB) medium, a nutrient-rich liquid used for
growing bacteria. We measure their elasticity by Young’s modulus, and the
adhesion property, both native and with respect to different bacterial
species, by means of cellular Force Distance Spectroscopy (FDS) technique
based on an Atomic Force Microscopy (AFM), under the LB medium as well as
deionized (DI) water. Focusing on the Gram negative bacterial species,
Chromatium okenii, we measure their cell-surface adhesion to the LMP agarose
and analyze how their adhesion develops over the physiological growth stages.
We compare our results with another Gram negative species, Escherichia coli,
as well as assess the possibility of active modulation of cell adhesion by
contrasting the bacterial experiments against adhesion of passive polystyrene
beads of 5$~{}\mu$m and 20$~{}\mu$m diameters to LMP agarose substrates.
Overall, our findings reveal that that bacteria, depending on the species and
their physiological state, can actively modulate cell-to-surface adhesion, as
a response to changes in the stiffness of underlying soft surfaces. In doing
so, bacteria may harness adherent phenotypes within a population to initiate
attachment and optimize proliferation strategies on soft substrates across a
range of stiffness.

##  1 Experimental

###  1.1 Force Distance Spectroscopy of bacterial cells on soft surfaces

By means of a Nanoscope® V controller (Veeco) AFM with Multimode 8 scanner,
force distance curves on pure agarose gels were measured using probes with a
spherical $\ch{SiO2}$ tip (3.5 µm diameter, 0.2 N/m force constant, CP-CONT-
SiO, nanoandmore GmbH, Germany). For cell adhesion measurement, tipless
cantilever (0.2 N/m force constant, TL-CONT, nanoandmore GmbH, Germany) were
used. Sample measurement was fulfilled in fluid (deionised (DI) water or LB
medium) using a fluid chamber with inlets and rubber sealing. Deflection
sensitivity was determined beforehand from the slope of the retract curve of a
force distance spectroscopy measurement performed in measurement fluid on a
silicon surface. To translate deflection to forces, the force constant
measured by nanoandmore GmbH was used. After removing the cover slip, the
prepared sample holder was put in the AFM and a droplet of the measurement
fluid was transferred onto the agarose gel surface. The prepared fluid chamber
was installed and filled with measurement fluid through the inlets using
syringes. Subsequently, the cantilever was manually approached to the surface
but not brought to contact. During this procedure, the horizontal position of
the cantilever was moved to the center position of the region of interest.
After visually close tip and surface approximation, the probe was false
engaged (i.e. tip-surface contact was simulated) and the sample was
subsequently manually approached by means of the step motor control and
continuously measured force distance curves until an increase in slope was
detectable. For cell and microparticle adhesion measurement, the cantilever
tip region was first approached towards cell accumulation regions. A
cell/microparticle was picked up by the tipless cantilever and used as
cantilever tip. The subsequent measurements were executed at a
cell/microparticle-free region on the sample surface. Force spectroscopy
curves were recorded on 16 × 16 equidistant spots around the initial tip-
surface contact point. The distance between adjacent spots was 500 nm. The
measurements were repeated at least 4 times on the same sample. Maximum
applied force did not exceed 10 nN.

###  1.2 Optical Microscopy

To ensure that cells and microparticles were present on the tipless
cantilever, the sample holder as well as the tip holder were both investigated
under an optical microscope (Eclipse LV100N POL, Nikon Corporation) in
reflected light mode right after measurement and careful removal of excess
liquid with a soft absorbant tissue.

###  1.3 Evalution of the Force Distance Spectroscopy data

AtomicJ (v 2.3.1, Pawel Hermanowicz) was used to extract the measured values
from the recorded data files and process them by applying different
theoretical contact mechanic models. A typical force distance curve is shown
schematically in Figure 1A. It consists of a region of no contact between tip
and substrate and a region of indentation. These two regions are connected by
the Contact Point $z_{c}$. For proper calculation, precise determination of
the position of the contact point is indispensable. Contact mechanic models
are applied to the contact area of the force distance curves. They are based
on the Hertz model (?), which describes the interaction between two spheres or
a sphere and an endless, plane surface (see Figure 1B). According to Hertz,
the generalised force-indentation relation can be described by:

$F=\lambda\delta^{\beta}$ (1)

where $F$ is the applied force, $\delta$ is the indentation depth, $\lambda$
and $\beta$ are values that depend on the underlying model. For the basic
Hertz model indentation of a spherical body into a plane surface, $\beta$ is
3/2 and $\lambda$ is given by the following equation:

$F=\frac{4ER^{1/2}}{3(1-\upsilon^{2})}\delta^{3/2}$ (2)

Here, $E$ is the elasticity modulus, $R$ is the tip radius and $\upsilon$ is
the Poisson Ratio. The latter is assumed to be $\approx$ 0.5 for very soft
samples.

The Hertz model is a very basic model that does not consider adhesion forces
and their subsequent contact area enhancement. Derjaguin, Muller and Toporov
(DMT) (?) as well as Johnson, Kendall and Roberts, JKR (?), have parallely
created extended models based on the Hertz model to incorporate adhesion
forces. These two models represent the limit values for the true value of
elasticity. While DMT is more accurate for harder samples with low adhesion,
soft samples with higher adhesion are better described by JKR.

In this paper we therefore focus on the evaluation using the JKR model via the
following three equations:

$\delta=\frac{\alpha_{\text{JKR}}^{2}}{R}-\frac{4}{3}\sqrt{\frac{\alpha_{\text{JKR}}F_{\text{ad}}}{RK}}$
(3)
$\alpha_{\text{JKR}}=\left[\frac{R}{K}\left(\sqrt{F_{\text{ad}}}+\sqrt{F+F_{\text{ad}}}\right)^{2}\right]^{\frac{1}{3}}$
(4) $F_{\text{ad}}=\frac{3}{2}\pi\gamma R$ (5)
$K=\frac{4E}{3(1-\upsilon^{2})}$ (6)

where $\alpha_{\text{JKR}}$ is the JKR-extended contact area between tip and
sample, $F_{\text{ad}}$ is the tip-sample adhesion force, $K$ is the elastic
constant of the sample, and $\gamma$ is the interfacial energy. The adhesion
force, $F_{ad}$, was evaluated from the minimum point of the force distance
curve relative to its baseline.

$E$ can hence be calculated by plotting $\delta$ versus $F$ and adjust $K$ to
minimize the least square error between the resultant plot and the measured
data, starting from the tip-sample contact point. This latter is ascertained
numerically for best fit. More comprehensive details on force spectroscopy
data evolution is well described by the works of Lin, Dimitriadis, and Horkay
(?, ?). The evaluated data are represented as boxplots without whiskers. The
inner 50 $\%$ of the measured values sorted in ascending order are represented
by a coloured area containing the median as a horizontal line. Outliers were
identified as data points that lie below $Q_{1}-1.5*IQR$ or above
$Q_{3}+1.5*IQR$, where $Q_{1}$ and $Q_{3}$ are the first and third quartiles,
respectively, and $IQR$ is the interquartile range ($Q_{3}-Q_{1}$). Outliers
are not shown here. In addition, the average value is shown as a point and the
standard deviation as an error bar.

###  1.4 Low-melting-point agarose gel preparation

Agarose gels with different concentrations (see Table 1) were prepared by
slowly dissolving the respective quantity of low-melting agarose gel (Agarose,
LMP, Preparative Grade for Large Fragments ($>$ 1,000 bp), Promega, USA) in 5
ml LB medium in an autoclaved glass tube under occasional stirring on a heat
plate (50 °C). When the powder was completely dissolved, the solution was left
to cool down to room temperature and then stored in a fridge (4 °C).

Table 1: Agarose concentrations [g/ml] | [%]
---|---
0.0150 | 1.5
0.0183 | 1.8
0.0221 | 2.2
0.0262 | 2.6
0.0306 | 3.1

Sample preparation is shown in Figure 1C. A ring-shaped sample holder with an
inner diameter of 10 mm and a height of 2 mm was glued onto a glass coverslip
with a diameter of 12 mm so that no glue was inside the ring. A magnetic plate
was glued to the other side of the coverslip. The whole setup was dried for 24
hours and used as AFM sample holder. Prior to sample preparation, the agarose
gel was taken out of the fridge and slowly heated on a heater plate. In order
to increase hydrophilicity of the sample holder glass, the sample holder glass
surface was plasma-treated for 45 seconds using a plasma torch (Mode BD-20,
Electro-Technic Products, Inc., USA). 200 µl of the warm and viscous agarose
gel was transferred to the sample holder. A coverslip was placed onto the
sample holder so as to enclose the agarose gel while avoiding to trap air
inside. The agarose gel was left to cool down for 30 minutes, then the
coverslip was slowly and horizontally removed just prior to measurement. The
topographies of two samples with 2.2 % agarose concentration were measured (in
LB medium environment and in water environment) by means of a Nanoscope® V
controller (Veeco) AFM with Multimode 8 scanner in Tapping mode using probes
with a spherical $\ch{SiO2}$ tip (3.5 µm diameter, 0.2 N/m force constant, CP-
CONT-SiO, nanoandmore GmbH, Germany).

Figure 1: Experimental evaluation and setup. A) Example Force Distance Curve.
The inlet shows an enlargement of the dashed area. Adhesion force is extracted
from the lowest force relative to the baseline. Young’s modulus is calculated
from the slope of the curve. Maximum indentation force was 100 nN. B) Hertz
Model when a solid sphere with radius $R$ indents a sample with Young’s
modulus $E$ and Poisson Ratio $v$. C) Sample preparation: The sample holder
consists of a magnetic bar to immobilize the holder on the AFM scanner, a
glass plate as bottom and the sample holder confinement (i). The glass is
plasma-treated (ii) for 45 s. Agarose gel is heated up to liquefaction and
then transferred to the sample holder (iii) until complete filling (iv). While
still liquid, a glass coverslip is placed onto the sample holder while
avoiding air entrapment (v). The sample is allowed to gelify and cool down for
30 min. Before measurement, the coverslip is removed horizontally (v, vi). The
sample is placed onto the AFM and the measurement liquid is injected (vii).
After 15 min of relaxation time, the measurement begins (ix).

###  1.5 Adhesion of polystyrene beads to LMP agarose gel

Polystyrene microparticles with 5 µm and 20 µm were purchased from
microparticles GmbH, Germany (product numbers PS/Q-R-KM650 and PS/Q-R-KM636
respectively). The stock solutions were diluted by factor $1\times 10^{-3}$
until single particles were visible on the substrate after sedimentation. The
agarose gel sample was prepared as described above. After removement of the
coverslip from the agarose gel sample, a drop of the microparticles solution
was put onto the agarose gel sample. The microparticles were allowed to settle
down for 30 minutes before the drop was carefully removed. Subsequently, force
distance curves were recorded as described above. This procedure was repeated
three times. In order to measure the adhesion of the passive particles, the
same measurements were repeated with agarose gel based on DI water as well.
For each agarose concentration and particle size, the procedure was repeated
three times.

###  1.6 Preparation of bacterial assays

Adhesion forces of two different cell species Escherichia coli (strain NCM
3722 $\Delta$motA, referred to as E. coli) and Chromatium okenii (referred to
as C. okenii) to LMP agarose gel with different concentrations (1.5 %, 2.2 %
and 3.1 %) were determined.

E. coli were stored in a freezer at -80 °C. Agar plates were prepared by
dissolving 16 g of LB-agar (LB-Agar (Luria/Miller), CARL ROTH, Germany) in 400
ml deionized water with subsequent autoclaving and stored at 4 °C. The cells
were taken out of the freezer and streaked on an agar plate in sterile
environment at room temperature. The agar plate was placed in an incubator for
48 h at 30 °C. Subsequently, a single cell island was transferred from the
agar plate into 8 ml LB medium using a bacterial loop in sterile environment.
The cell solution was placed into the incubator at 30 °C and shaken at 180 RPM
during 24 hours. Thereafter, 200 µl of this cell solution was transferred to 2
ml LB medium and kept in the incubator at 30 °C under continuous shaking at
180 RPM. After 160 min, the cell suspension was centrifuged at 2000 rpm for 5
min. Except for 100 µl, the centrifugate was slowly removed. The cells were
resuspended and transferred onto a freshly prepared agarose gel surface sample
(described above). The cells were allowed to settle down on the agarose gel
surface for 30 minutes. The drop was then carefully removed and FDS was
executed as described below, under the LB medium environment.

Phototrophic sulfur bacteria C. okenii was obtained from Lake Cadagno in the
Piora Valley (46°33’N, 8°43’E) in the southern Swiss Alps, following the
protocol described in Ref. (?). They play a key role in sulfide removal from
shallow sediments and stratified waters (?). Upon transferring the cells to
laboratory, they were grown and propagated in Pfennig’s Medium I protocol with
periodic spiking of hydrogen sulphide (?). Cultivation was run under
light/dark photoperiod (16/8 h) with a light intensity of 38.9 µmol $m^{-2}$
$s^{-1}$. After soft shaking, 100 µl of the cell solution was transferred onto
the freshly prepared LMP agarose surface (described above). The cells were
allowed to settle down for 30 minutes. Subsequently, the drop was carefully
removed, and measurement was executed as described below under acqueous
environment.

###  1.7 Quantification of C. okenii adhesion properties over growth stages

In order to track the evolution of cell-surface adhesion over time, FDS was
carried after 2 weeks, 10 weeks and 14 weeks of inoculation of C. okenii in
Pfennig’s Medium I. Although motile in their natural lake ecosystem, under
laboratory conditions, C. okenii gradually shifts to a sessile lifeform (?).
The physiology-dependent measurements were conducted on agarose concentration
of 2.2 %, following the gel preparation protocol described previously. The
cell solution was kept in a glass container enclosed with a septum so as to
protect it from air contact. For each measurement, 0.8 ml of cell solution was
taken using a 1 ml syringe and needle. The cells were collected either from
the surface of the cell solution (top cells) or from the bottom of the glass
container (bottom cells) and transferred to a 2 ml Eppendorf tube. After
removal, the cells were centrifuged at 6000 RPM for 180 s. The pellet was
carefully aspirated using a 10 µl pipette and finally transferred to the
prepared LMP agarose gel substrate. The sample was then left to stand for 30
minutes so that the cells could settle on the substrate. The cantilever was
wetted with a drop of DI water before the cantilever holder was installed.
This gentle method minimised fluid flow which could interfere measurements
within the sample solution. Each measurement series consisted of six
measurements. Firstly, three measurements were carried out with top cells.
Then three measurements were taken with bottom cells. Each series of
measurements was completed within 3 days.

##  2 Results

###  2.1 Topography of LMP agarose gel surfaces

Figure 2 shows the topography of 2.2 % agarose gel in LB medium (A) and DI
water (B) environments. The sample surfaces showed overall low surface
roughness, furthermore, no significant difference in roughness was observed
between the two cases.

Figure 2: Sample topographies on a 15 x 15 µm² area of 2.2 % LMP agarose gel
concentration samples in LB medium (A) and water (B) environment. The
roughness is 16.01 ($\pm$ 3.96) nm, and 16.80 ($\pm$ 4.37) nm, respectively
(C). The scale bars indicate 3 $\mu$m.

###  2.2 Mechanical properties of the LMP agarose gels

A representative example for a measured force distance curve is given in
Figure 1A. The computed outcomes of Young’s modulus and adhesion values of
agarose gel samples without cells are presented in Table 2. Figure 3 shows the
corresponding measurements conducted in DI water and LB medium. The provided
data includes both median and mean values ($n>500$).

Table 2: Young’s modulus of agarose gel samples with different agarose concentrations | Concentration | Young’s modulus | Adhesion Force | Number of
---|---|---|---|---
|  | Average | Median | Average | Median | measurements
| [%] | [kPa] | [kPa] | [nN] | [nN] | (n)
LB Medium | 1.5 | 25.1 ($\pm$ 2.1) | 24.8 | 0.15 ($\pm$ 0.06) | 0.14 | 881
1.8 | 31.1 ($\pm$ 4.0) | 31.1 | 0.16 ($\pm$ 0.08) | 0.13 | 1083
2.2 | 51.9 ($\pm$ 5.7) | 51.4 | 0.10 ($\pm$ 0.02) | 0.10 | 1069
2.6 | 75.1 ($\pm$ 7.5) | 75.2 | 0.08 ($\pm$ 0.02) | 0.08 | 589
3.1 | 95.5 ($\pm$ 6.7) | 95.6 | 0.08 ($\pm$ 0.01) | 0.07 | 529
Water | 1.5 | 20.9 ($\pm$ 2.6) | 21.2 | 0.12 ($\pm$ 0.03) | 0.11 | 557
1.8 | 31.0 ($\pm$ 3.1) | 31.0 | 0.13 ($\pm$ 0.04) | 0.12 | 589
2.2 | 54.7 ($\pm$ 5.1) | 55.2 | 0.08 ($\pm$ 0.02) | 0.07 | 931
2.6 | 72.4 ($\pm$ 5.3) | 72.0 | 0.05 ($\pm$ 0.01) | 0.05 | 522
3.1 | 92.4 ($\pm$ 5.1) | 92.3 | 0.05 ($\pm$ 0.01) | 0.05 | 503

The Young’s modulus, also known as the modulus of elasticity, is a measure of
the stiffness of a material, defined as the ratio of stress to strain within
the elastic limit of the material. Upon increasing the LMP agarose
concentration, the Young’s modulus increases, for both DI water and LB medium
environments. With Young’s moduli smaller than 100 kPa, the agarose substrate
falls within the range of soft biomaterials (e.g., cells, organs) and soft
synthetic polymers (?, ?). The observed trend can be elucidated by examining
the underlying structure of agarose gels (?, ?, ?). LMP agarose monomers
consist $\beta$-D-galactose and 3,6-anhydro-$\alpha$-L-galactose units. Upon
cooling the agarose gel solution below the gelation temperature (24 - 28 °C),
the equatorial hydrogen atoms of the 3,6-anhydro-$\alpha$-L-galactose residues
form hydrogen bonds with each other, inducing the formation of
$\alpha$-helices, forming a single chain or double chains. The cooling rate
determines the ratio of one-chain and two-chains $\alpha$-helices. This
process results in the formation of a 3D secondary agarose gel structure. The
gelation temperature and pore size of the gel primarily depend on the
availability of hydrogen and oxygen in the agarose solution. A lower agarose
concentration leads to fewer $\alpha$-helices, resulting in reduced structural
stability and larger pore sizes. Alongside $\alpha$-helices, other types of
physical cross-linking between the chains increase the stability of the gel
matrix. The structural stability directly correlates with the gel’s Young’s
modulus, explaining the increase in Young’s modulus with higher agarose
concentration. Low-melting agarose is produced by hydroxyethylation such that
a portion of the available alcoholic side groups is substituted by ethyl
groups and hence unable to form hydrogen bonds. This substitution reduces the
density and strength of $\alpha$-helices, leading to a lower Young’s modulus
(?). Overall, the Young’s moduli we measure are lower than those of normal
melting agarose gels, as reported in literature (?). Roberts et al.
investigated the elastic storage modulus of 1 $\%$ normal agarose gel to be
around 80 kPa (?), with other reports corroborating their results (?, ?, ?, ?,
?).

The mechanical properties of LMP agarose gels in LB medium have received
limited investigation so far. Existing studies report varying results on
mechanical properties across different agarose concentrations, though the
overall range matches well with our measurements. Kontomaris et al. used a
similar LMP agarose gel and measured an elastic modulus of 154 kPa (2.5 $\%$)
(?), while Topuz et al. observed values in the same range as this study for
LMP agarose gel (?). Finally, Zamora-Mora et al. measured an Young’s modulus
of 400 Pa for 0.5 $\%$ agarose gel and 1.45 kPa for 2 $\%$ agarose
concentration. (?), similar to Kumachev et al.. who reported the range to be
between 50 Pa (0.75 $\%$) to 2.5 kPa (3.00 $\%$) (?). It is to noted that last
two studies measured the shear modulus, though the Young’s modulus is expected
to be in the same range as well.

Figure 3: Measured mechanical properties of agarose gel with different
concentrations. The inner 50 $\%$ of the measured values sorted in ascending
order are represented by a coloured area containing the median as a horizontal
line. In addition, the average is shown as a point and the standard deviation
as an error bar. The difference between water and LB medium as measurement
environment is imperceptible. The Young’s modulus of agarose gel increases
with rising LMP agarose concentration and lies between 20 and 100 kPa in both
LB medium (A) and water (B) environment. Only small adhesion forces in sub-nN
scale could be observed for both LB medium (C) and water (D) environment in
contact to a spherical SiO2 tip (3.5 µm). Adhesion forces decrease slightly
with increasing LMP agarose concentration.

###  2.3 Cell-surface adhesion force on LMP agarose gels

The evaluated values for adhesion of E. coli and C. okenii cells to LMP
agarose gel with different agarose concentrations are listed in Table 3 and
plotted in Figure 4. Optical microscopy images (Figure 4A and B) reveal that
cells were attached to the cantilever surface, confirming that the adhesion
force between cell and agarose gel surface was measured. The force distance
curves show a smooth adhesion characteristic, as has been observed for cell
initial adhesion on hydrophilic surfaces (?). For E. coli, the adhesion values
are in weak sub-nN range. As can be seen, adhesion forces slightly increase as
agarose concentration increases, which is in agreement with the adhesion to
normal agarose gels (?).

Table 3: Adhesion force of bacteria to agarose gel of different concentrations Strain | Concentration [%] | Average [nN] | Median [nN] | Measurements
---|---|---|---|---
E. coli | 1.5 | 0.29 ($\pm$ 0.17) | 0.27 | 482
E. coli | 2.2 | 0.35 ($\pm$ 0.23) | 0.29 | 722
E. coli | 3.1 | 0.39 ($\pm$ 0.20) | 0.36 | 917
C. okenii | 1.5 | 0.21 ($\pm$ 0.10) | 0.20 | 862
C. okenii | 2.2 | 0.73 ($\pm$ 0.60) | 0.54 | 1476
C. okenii | 3.1 | 2.42 ($\pm$ 1.16) | 3.04 | 443

For C. okenii, however, the adhesion force increased by up to an order of
magnitude compared to E. coli adhesion forces. Furthermore, the C. okenii are
found to be more sensitive to changes in the LMP agarose concentration. While
doubling the agarose concentration from 1.5 % to 3.1 % increases the median of
adhesion force surface by factor 1.3 for E. coli cells, it is enhances by a
factor of 15 for C. okenii. Furthermore, a detailed examination of the
adhesion force data distribution for C. okenii reveals emergence of a bimodal
distribution of adhesion force at LMP agarose concentrations of 2.2 %, which
then becomes more pronounced when the agarose concentration is raised to 3.1 %
(see Figure 5). In order to understand the co-existence of the adherent
phenotypes, we separated the two peaks in the bimodal adhesion force
distribution for 2.2 $\%$ and 3.1 $\%$ agarose concentrations, with dynamic
threshold adhesion values, as indicated by the yellow and green regions in
Figure 5. The bimodal distributions indicate the co-existence of two different
adherent sub-populations: weakly adherent cells (yellow regions of the plot),
and the strongly adherent cells (green regions of the plot), which emerge as
the stiffness of the underlying substrate is modulated. At an LMP
concentration of 1.5 $\%$, such a bimodality could not be detected.

As shown in the boxplots, Figure 6, the lower range of C. okenii adhesion
force distribution peaks around the same range as for E. coli cells, i.e., low
adhesion force that depends weakly on the agarose concentration. In contrast,
the higher adhesion force peaks seen in C. okenii, reveal a stronger
dependence on LMP agarose concentration. The small adhesion noted in both E.
coli and C. okenii corresponds with the general observation that bacteria with
hydrophobic surfaces tend to adhere more readily to hydrophobic than
hydrophilic surfaces. Nevertheless, the weak adhesion forces observed here,
vary slightly as the agarose concentration is increased. To understand this, a
bacteria can be modeled as solid body, with biopolymers on their surface
represented by flexible chains (?). During the separation of a cell from the
surface, various forces including electrostatic forces, hydrogen bonds, dipole
interactions, and Lifshitz-Van der Waals forces act to oppose detachment.
Taken together, the interactions can be captured using the extended DLVO
theory (xDLVO) (?), however, in a more complex biological context (as the one
studied here), the xDLVO theory might require further modifications, which are
beyond the scope of this work. Another possible effect during the detachment
of a bacterial cell is steric hindrance, due to the partial entanglement of
the polymeric surface chains (?). The minimum force required for complete
separation corresponds to the adhesion force, which depends on the properties
of the flexible surface chains and the structure and properties of the
underlying network, which in turn, alter with agarose concentration, offering
a possible reason for the slight enhancement of the weak adhesion forces with
increase in the agarose concentration.

Figure 4:  Adhesion properties of E. coli and C. okenii on agarose gel with
varying concentration. By utilizing optical microscopy, the cells on the
cantilevers were clearly observed, as shown in (A) for E. coli and (B) for C.
okenii. The presence of cells on the cantilever (encircled) provided
compelling evidence that the adhesion between the gel surface and the cells
was successfully captured by the measurement. The insets display optical
microscopy images of E. coli (A) and C. okenii (B) on agarose gel, with a
scale bar of 10 µm. In C and D, the inner 50 $\%$ of the measured adhesion
force values towards LMP agarose gel sorted in ascending order are represented
by a coloured area containing the median as a horizontal line. In addition,
the average is shown as a point and the standard deviation as an error bar
Interestingly, as the LMP agarose concentration was increased, a slight rise
in adhesion force for E. coli bacterial cells (C) and a more substantial
increase for C. okenii bacterial cells (D) were observed.  Figure 5: Adhesion
force distribution of C. okenii on 1.5 % LMP agarose gel (A), 2.2 % LMP
agarose gel (B) and 3.1 % LMP agarose gel (C). While for 1.5 % LMP agarose gel
the adhesion force is unimodal, two peaks occur for 2.2 % (B) and 3.1 % (C)
agarose concentrations. A manually threshold was set to divide the occuring
peaks into lower adhesion force part (highlighted in yellow) and higher
adhesion part (highlighted in green).

While E. coli showed weak adhesion forces across different LMP agarose
concentrations tested, C. okenii showed different trend. The bimodal
distribution indicates that a few cells bind strongly to the surface
macromolecules, while others bind weakly. Similar behaviour had been observed
also for Staphylococcus aureus on hydrophobic surfaces (?). Increasing the LMP
agarose concentration could provide more anchor points for the C. okenii
cells, thus increasing the overall adhesion force. However, the exact binding
mechanism is currently under investigation, and will be discussed elsewhere.

Figure 6: Adhesion force of E. coli and C. okenii towards LMP agarose gel with
various concentrations. The inner 50 $\%$ of the measured values sorted in
ascending order are represented by a coloured area containing the median as a
horizontal line. In addition, the average is shown as a point and the standard
deviation as an error bar. While E. coli shows little adhesion (A), the
adhesion force of C. okenii strongly depends on LMP agarose concentration (B).
Adhesion force values for 2.2 % and 3.1 % LMP agarose concentrations are
bimodally distributed (see Figure 5). Seperating these peaks and replotting
shows weak adhesion force for the lower adhesion part (C), comparable to (A),
while the higher adhesion peaks show stronger adhesion forces that clearly
depend on LMP agarose concentration (D). The occurrence of two adhesion force
peaks signify two different adhesion mechanisms of C. okenii towards LMP
agarose gel. Figure 7: Adhesion forces of polystyrene microparticles towards
LMP agarose gel with various concentrations measured in DI water environment.
The inner 50 $\%$ of the measured values sorted in ascending order are
represented by a coloured area containing the median as a horizontal line. In
addition, the average is shown as a point and the standard deviation as an
error bar. A) 5 µm particles showing low to medium adhesion towards LB medium
based LMP agarose gel with a slight increase in adhesion force as the agarose
concentration is increased. B) 5 µm particles show a similar behavior towards
DI water based LMP agarose gel as in (A). C,D) 20 µm microparticles show
similar behavior towards LB medium based LMP agarose gel (C) as 5 µm
microparticles (A) with a similar adhesion force range, and similar behavior
towards DI water based LMP agarose gel (D) as 5 µm microparticles (B) with a
similar adhesion force range.

###  2.4 Adhesion of polystyrene microparticles on LMP agarose gels

To better understand the adhesion force results and to see if there is an
active biological modulation of adhesion, experiments were repeated with
passive PS microparticles. As with the bacterial cells, the PS microparticles
possessed hydrophobic surfaces. To maintain a comparable size range,
microparticles with diameters of 5 µm and 20 µm were used. The system also
consisted of an agarose gel based on LB medium as the substrate and DI water
as the surrounding medium. To minimize the influence of ions present in the LB
medium, these experiments were repeated in a system with agarose gel based on
DI water in a DI water environment. The results are shown in Figure 7, while
the corresponding values are provided in Table 4. The adhesion forces fall in
the nN range, with marginal increase increase with the agarose concentration.
A comparison with the results for E. coli and C. okenii shows that the
adhesion force for PS beads is somewhat higher. Though our results cannot
conclusively confirm if E. coli actively tune their adhesion with LMP agarose,
C. okenii exhibits a distinct adhesion trend, suggesting a specific
interaction between the substrate and the bacteria that manifests at a
specific agarose concentration. This phenomenon aligns with previous findings
on the adhesion of Staphylococcus aureus (?), suggesting the presence of
diverse active adhesion mechanisms in bacteria.

Table 4: Adhesion force of polystyrene microparticles on LPM agarose gels. Agarose gel | Particle | Agarose | Adhesion force | Number of
---|---|---|---|---
medium | diameter | concentration | Average | Median | measurements
| [µm] | [$\%$] | [kPa] | [kPa] | (n)
LB medium | 5 | 1.5 | 0.54 ($\pm$ 0.27) | 0.52 | 902
LB medium | 5 | 2.2 | 0.73 ($\pm$ 0.37) | 0.72 | 475
LB medium | 5 | 3.1 | 0.83 ($\pm$ 0.41) | 0.80 | 466
LB medium | 20 | 1.5 | 0.45 ($\pm$ 0.25) | 0.53 | 474
LB medium | 20 | 2.2 | 0.68 ($\pm$ 0.36) | 0.63 | 429
LB medium | 20 | 3.1 | 0.74 ($\pm$ 0.34) | 0.72 | 256
DI water | 5 | 1.5 | 0.59 ($\pm$ 0.19) | 0.56 | 389
DI water | 5 | 2.2 | 0.72 ($\pm$ 0.52) | 0.56 | 390
DI water | 5 | 3.1 | 0.59 ($\pm$ 0.23) | 0.59 | 300
DI water | 20 | 1.5 | 0.47 ($\pm$ 0.23) | 0.45 | 432
DI water | 20 | 2.2 | 0.58 ($\pm$ 0.39) | 0.50 | 319
DI water | 20 | 3.1 | 0.63 ($\pm$ 0.12) | 0.64 | 387

###  2.5 Evolution of C. okenii adhesion over growth stages

As a final step of our experiments, we measured the evolution of the C. okenii
adhesion forces during the course of laboratory inoculation. Recent report by
the authors have demonstrated that, under laboratory conditions, C. okenii
undergoes a lifeform shift from a free-living motile to biofilm forming
sessile phenotypes (?). Since bacterial adhesion to surfaces is central to
biofilm formation, the final measurements are motivated by the question: Does
the lifeform shift of C. okenii correspond to changes in their cell-substrate
adhesion properties? Regardless of the exact mechanism of adhesion between C.
okenii and the LMP agarose substrate, it is intriguing that C. okenii
populations elicit wek and strong adherent phenotypes at higher substrate
stiffness. Relative to the planktonic states with suppressed cell-surface
adhesion properties, transition to sessile lifeforms could be triggered by
amplified adhesion mechanisms (for instance, via secretion of exopolymeric
substances under environmental stressors), driving cellular flocculation and
surface attachment, ultimately leading to sessile lifeforms (?). Thus,
starting with a fresh sample of planktonic C. okenii isolated from their
natural lake habitat, we analysed their cell-substrate adhesion forces, and
compared them with lab-grown cultures over a period of 14 weeks (late
stationary phase, (?)). Macroscopically, we observed two distinct C. okenii
layers in the inoculation bottle: a bottom layer attached to the floor of the
glass bottom, and a top suspended layer at the air-water interface, as
visualized and labeled in Figure 8.

Figure 8B-D illustrates the adhesion values of both top and bottom cells to a
2.2 % agarose gel substrate over time since their removal from their natural
habitat and maintenance under laboratory conditions. The combination of top
and bottom cells from each time period is shown in Figure 9, including data
for populations grown into late stationary phase (Figure 9B). Table 5 lists
corresponding values.

After two weeks of laboratory inoculation, i.e., when the C. okenii population
is in its mid-exponential phase, the cell adhesion forces fell within a narrow
range, with top cells exhibiting higher adhesion ($0.36\pm 0.18$ nN), relative
to their bottom counterparts ($0.12\pm 0.07$ nN). The scenario changes after
ten weeks, when the C. okenii population enters stationary phase: the bottom
sub-populations have an enhanced adhesion, with an overall increase in the
diversity of the adherent phenotypes (as indicated by the high standard
deviations in our measurements, see Table 5). The difference between median
values of upper and lower cells decreased. Finally, once the population
reached late stationary phase (at 14 weeks), the bottom population is now
considerably more adherent, with a larger diversity of the adherent
phenotypes. The top population however maintains its adhesion. A closer
examination of the separate measurements for bottom and top cells revealed a
progressive evolution of adherent characteristics of the bottom cells, whereas
the adhesion properties of the top cells appear to stabilize over the same
period of time. Thus, not only do the mean and median adhesion forces
increase, the entire range of adhesion forces, including the maximum adhesion
force, enhance over time, accompanied by an overall decrease in the number of
top cells.

Figure 8: C. okenii adhesion force measurements towards 2.2 % LMP agarose gel. (A) The freshly harvested C. okenii cells were stored in a glass jar under anaerobic conditions exposed to room temperature and daylight. A bottom and a top layer of C. okenii formed within the vessel. For each chosen time point, three samples of the top layer and three samples of the bottom layer were measured. For B, C and D, the inner 50 $\%$ of the measured values sorted in ascending order are represented by a coloured area containing the median as a horizontal line. In addition, the average is shown as a point and the standard deviation as an error bar. (B) Adhesion force results of bottom and top layer cells 2 weeks after removal from natural habitat, showing small adhesion only. (C) Adhesion force results of bottom and top layer cells 10 weeks after removal from natural habitat, Showing increased adhesion force range for all samples. (D) Adhesion force results of bottom and top layer cells 14 weeks after removal from natural habitat, showing large adhesion force range especially for bottom cells. Table 5: Adhesion force of C. okenii to LMP agarose gel across growth stages Time since | Extraction | Adhesion force | Number of
---|---|---|---
inoculation | point | Average | Median | measurements
[weeks] |  | [nN] | [nN] | (n)
2 | Bottom | 0.12 ($\pm$ 0.07) | 0.09 | 1479
2 | Top | 0.36 ($\pm$ 0.18) | 0.32 | 1310
10 | Bottom | 0.33 ($\pm$ 0.23) | 0.29 | 1940
10 | Top | 0.23 ($\pm$ 0.24) | 0.22 | 2042
14 | Bottom | 0.45 ($\pm$ 0.37) | 0.35 | 2338
14 | Top | 0.23 ($\pm$ 0.16) | 0.19 | 1922
Figure 9:  Evolution of C. okenii cell adhesion towards 2.2 % LMP agarose gel
over time in laboratory conditions. The inner 50 $\%$ of the measured values
sorted in ascending order are represented by a coloured area containing the
median as a horizontal line. In addition, the average is shown as a point and
the standard deviation as an error bar. The plots show the evaluated adhesion
force data 2, 10 and 14 weeks after transfer from lake to laboratory. A) shows
separated data of bottom and top cells. As can be seen, the top cells
initially show slightly higher adhesion than the bottom cells. B) shows the
combined bottom/top cells data in function of time. For comparison, control
cells of 8th generation in laboratory are shown on the right. The increase of
adhesion with domestication time indicates the growing ability of cells to
form biofilms. Furthermore, the growing adhesion range is an indication for
different development stage either towards biofilm formation or within biofilm
circle.

##  3 Discussions and Conclusion

In this work, we present a Force Distance Spectroscopic approach to
simultaneously measure the stiffness and adhesion of low-melting-point agarose
gel, both in its native state as well as in the context of cell-surface
adhesion of bacterial species. Our results show that with increasing agarose
concentration, the substrate stiffness goes up, however, remains below the
typical value of normal melting agarose gels. The Young’s moduli of LMP
agarose gels increase from approximately 20 kPa to around 100 kPa as the LMP
agarose concentration is doubled from 1.5 % to 3 %. The reported range of
Young’s moduli falls between ultralow-melting-point agarose and the normal-
melting-point agarose, and thus offers a well-suited alternative to existing
hydrogels used in biomedical research and engineering. No significant
difference was observed depending on the choice of the liquid environments (LB
versus DI water) within which the measurements were conducted. The stiffness
of LMP agarose gel lies in the range of soft tissues such as muscle,
epithelial and neural tissues (?), making it potential material for organ-on-
a-chip tissue engineering applications.

FDS experiments with E. coli and C. okenii bacteria on LMP agarose gel with
three different concentrations revealed a stiffness-dependent variation of the
cell-surface adhesion. While E. coli showed marginal increment of the adhesion
with increasing agarose content, the attachment of C. okenii showed two
different adherent phenotypes: one with adhesion force in the same range as
observed for E. coli (weak adhesion); and a second sub-population of strongly
adherent cells as well as increased adhesion with the LMP agarose
concentration. Previous works with diverse species and substrates have
indicated inconsistent adhesion forces, underscoring the possibility of
cofounding factors, beyond stiffness, to contribute to the dynamics of
bacteria-substrate adhesion. For example, Thio et al. determined the adhesion
forces of E. coli bacteria towards polystyrene and different polyamides to be
in the range of 2.9 nN to 9.7 nN (?), while Wang et al. reported that
Staphylococcus aureus adhesion on polyacrylamide hydrogels decrease by three
orders with increasing substrate stiffness (?). While E. coli and P.
aeruginosa show a similar adhesion trend on polydimethylsiloxane substrate
(0.1 MPa to 2.6 MPa) (?), E. coli and S. aureus show an increased adhesion to
stiffer poly(ethylene glycol) dimethacrylate hydrogels, relative to softer
ones (?, ?). This is also supported by Francius et al. (?) who observed a
linearly increasing adhesion dependence of different E. coli strains on
poly(allylamine hydrochloride)/hyaluronic acid hydrogels stiffness between 20
kPa and 700 kPa. Guégan et al. (?) measured the effect of the stiffness of
agarose gel of two different concentrations (0.75 % and 3.0 %) on the adhesion
capability of gram-negative Pseudoalteromonas sp. D41 and gram-positive
Bacillus sp. 4J6 using retention assays. While Pseudoalteromonas sp. D41
showed higher adhesion for softer agarose substrate, adhesion of Bacillus sp.
4J6 increased with increasing stiffness.

The mechanism of this adhesion process depends on the properties of the
bacteria, substrate and the local environment (?, ?, ?). For C. okenii, the
larger contact area of surface polymeric molecules on the substrate, as well
as its surface chemistry, may promote the observed adhesion and the adherent
diversity on the agarose gel substrates. Our experiments over the
physiological growth stages of C. okenii indicate a progressive increase in
adhesion (on 2.2 % agarose gel) over time, supporting the lifeform shift from
planktonic to biofilm state (?). The C. okenii biofilm formation could be
observed stably after 14 weeks of inoculation, as shown in Figure 10. As
reported previously by Di Nezio et al. (?), such shifts in lifeforms trigerred
by domestication of species, occur synergistically across multiple phenotypic
traits, including morphology, cell density, intracellular attributes, and
alteration of motility. The cell-substrate adhesion data supports the
previously reported shift in the C. okenii lifeform, occurring over a period
of weeks after laboratory inoculation. The phenotypic diversity of the
adherent cells increase over time, furthermore suggesting an adaptive
transformation which could allow the domesticated cells to optimise surface
attachment once they are inoculated over extended periods under laboratory
conditions. Alteration of cell adhesion following domestication has been
reported also for Saccharomyces cerevisiae (?), wherein such changes were
mediated by modified expression of genes related to cell-cell adhesion and the
production of EPS (?, ?). Similar pathways could be targeted in follow up
studies to delineate how planktonic C. okenii undergo lifeform shifts,
specifically in the context of stiffness- and physiology-dependent cell
adhesion.

Figure 10: C. okenii biofilm on 2.2 % LMP agarose gel for a 14 week old
culture. The cells form a monolayer on the underlying LMP agarose substrate.

## Acknowledgments

We thank F. Di Nezio and N. Storelli for sharing Chromatium okenii cells and
valuable discussions on their growth and physiology. We gratefully acknowledge
the support from the Institute for Advanced Studies, University of Luxembourg
(AUDACITY Grant: IAS-20/CAMEOS to A.S.) and a Human Frontier Science Program
Cross Disciplinary Fellowship (LT 00230/2021-C to G.R.). A.S. thanks
Luxembourg National Research Fund for the ATTRACT Investigator Grant (A17/MS/
11572821/MBRACE) and a CORE Grant (C19/MS/13719464/TOPOFLUME/Sengupta) for
supporting this work.

## Conflict of Interest

The authors declare no conflict of interest.

## Author contributions

Conceptualization, planning, administration, and supervision: A.S.
Methodology: R.R., G.R. and A.S. Investigation, data and statistical analysis:
R.R. with inputs from A.S. Writing: R.R. and A.S.

## Data Availability Statement

All data and supporting materials are included in the manuscript. Any
additional supporting material for this study can be obtained from the
corresponding author upon reasonable request.

## References

  * 1. C. F. Guimaraes, L. Gasperini, A. P. Marques, R. L. Reis, Nat. Rev. Mater. 5, 351 (2020).
  * 2. A. Serrano-Aroca, et al., Materials Today Bio 16, 100412 (2022).
  * 3. Y. F. Dufrêne, A. Persat, Nature Reviews Microbiology 18, 227 (2020).
  * 4. B. Maier, Annual Review of Biophysics 50, 401 (2021).
  * 5. L. Wang, et al., npj Biofilms Microbiomes 9, 78 (2023).
  * 6. R. Wittmann, G. H. Nguyen, H. Löwen, F. J. Schwarzendahl, A. Sengupta, Communications Physics 6 (2023).
  * 7. K. Otto, T. J. Silhavy, Proc. Natl Acad. Sci. USA 99, 2287–2292 (2002).
  * 8. C. K. Ellison, et al., Science 358, 535–538 (2017).
  * 9. I. Hug, S. Deshpande, K. S. Sprecher, T. Pfohl, U. Jenal, Science 358, 531–534 (2017).
  * 10. C. Berne, C. K. Ellison, A. Ducret, Y. V. Brun, Nature Reviews Microbiology 16, 616 (2018).
  * 11. V. Vadillo-Rodriguez, H. J. Busscher, H. C. van der Mei, J. de Vries, W. Norde, Colloids Surf. B: Biointerf. 41, 33–41 (2005).
  * 12. S. Bayoudh, et al., Mater. Sci. Eng. C 26, 300–305 (2006).
  * 13. Y. Yuan, M. P. Hays, P. R. Hardwidge, J. Kim, RSC Adv. 7, 14254–14261 (2017).
  * 14. N. Kandemir, W. Vollmer, N. S. Jakubovics, J. Chen, Scientific Reports 8, 10893 (2018).
  * 15. K. Yang, et al., J. Mater. Sci. Technol. 99, 82–100 (2022).
  * 16. V. Carniello, B. W. Peterson, H. C. van der Mei, H. J. Busscher, Adv. Colloid Interf. Sci. 261, 1 (2018).
  * 17. X. Zhang, et al., Colloids Surf. B: Biointerf. 177, 454–461 (2019).
  * 18. M. E. Asp, et al., PNAS nexus 1, pgac025 (2022).
  * 19. C. Guégan, et al., Colloids and Surfaces B: Biointerfaces 114, 193 (2014).
  * 20. F. Song, D. Ren, Langmuir 30, 10354 (2014). PMID: 25117376.
  * 21. H. Straub, et al., Advanced Healthcare Materials 8, 1801323 (2019).
  * 22. M. Bawazir, A. Dhall, J. Lee, B. Kim, G. Hwang, Colloids and Surfaces B: Biointerfaces 221, 112952 (2023).
  * 23. J. Lichter, et al., Biomacromolecules 9, 1571 (2008).
  * 24. D. Wilms, F. Schröer, T. Paul, S. Schmidt, Langmuir 36, 12555 (2020).
  * 25. K. W. Kolewe, S. R. Peyton, J. D. Schiffman, ACS Applied Materials & Interfaces 7, 19562 (2015).
  * 26. K. W. Kolewe, J. Zhu, N. R. Mako, S. S. Nonnenmann, J. D. Schiffman, ACS Applied Materials & Interfaces 10, 2275 (2018).
  * 27. M. Lahaye, C. Rochas, Hydrobiologia 221, 137 (1991).
  * 28. M. Bertasa, et al., European Polymer Journal 123, 109442 (2020).
  * 29. Z. You, D. J. G. Pearce, A. Sengupta, L. Giomi, Physical Review X 8, 031065 (2018).
  * 30. Z. You, D. J. Pearce, A. Sengupta, L. Giomi, Physical Review Letters 123, 178001 (2019).
  * 31. S. Nandhakumar, et al., Journal of Pharmacology & Pharmacotherapeutics 2, 107 (2011). Number: 2.
  * 32. N. Guarrotxena, G. Braun, Journal of Nanoparticle Research 14, 1199 (2012). Number: 10.
  * 33. J. Rodriguez Corral, H. Mitrani, M. Dade-Robertson, M. Zhang, P. Maiello, Canadian Geotechnical Journal 57, 2010 (2020).
  * 34. J. Sambrook, E. F. Fritsch, T. Maniatis, et al., Molecular cloning: A Laboratory Manual., no. Ed. 2 (Cold spring harbor laboratory press, 1989).
  * 35. J. S. Kim, N. Chowdhury, R. Yamasaki, T. K. Wood, Environmental Microbiology 20, 2038 (2018).
  * 36. D. D. Lewis, T. Gong, Y. Xu, C. Tan, Frontiers in Bioengineering and Biotechnology 10, 948483 (2022).
  * 37. J. Raghunath, J. Rollo, K. M. Sales, P. E. Butler, A. M. Seifalian, Biotechnology and Applied Biochemistry 46, 73 (2007).
  * 38. Y. Dong, S. Li, X. Li, X. Wang, International Journal of Biological Macromolecules 190, 693 (2021).
  * 39. M. K. Yazdi, et al., Journal of Controlled Release 326, 523 (2020).
  * 40. S. Torabi, et al., Langmuir 35, 10299 (2019). Number: 32 Publisher: American Chemical Society.
  * 41. A. Sengupta, Frontiers in Physics 8 (2020).
  * 42. C. Jin, A. Sengupta, Biophysical Reviews 16, 173–188 (2024).
  * 43. G. Rani, A. Sengupta, bioRxiv p. DOI:10.1101/2023.09.07.556749 (2024).
  * 44. J. J. Roberts, A. Earnshaw, V. L. Ferguson, S. J. Bryant, Journal of Biomedical Materials Research Part B: Applied Biomaterials 99B, 158 (2011).
  * 45. V. Normand, D. L. Lootens, E. Amici, K. P. Plucknett, P. Aymard, Biomacromolecules 1, 730 (2000).
  * 46. M. Watase, K. Nishinari, Rheologica Acta 22, 580 (1983).
  * 47. S. Kreve, A. C. D. Reis, Japanese Dental Science Review 57, 85 (2021).
  * 48. N. A. Araujo, et al., Soft Matter 9, 1695 (2023).
  * 49. L. A. Genova, et al., Proceedings of the National Academy of Sciences 116, 25462 (2019).
  * 50. J. Dhar, A. Thai, A. Ghoshal, L. Giomi, A. Sengupta, Nature Physics 18, 945 (2022).
  * 51. H. Hertz, J Reine und Angewandte Mathematik 1882, 156 (1882).
  * 52. B. V. Derjaguin, V. M. Muller, Y. P. Toporov, Journal of Colloid and interface science 53, 314 (1975).
  * 53. K. L. Johnson, K. Kendall, a. Roberts, Proc. Royal soc. London. A. Mathematical and Physical Sciences 324, 301 (1971).
  * 54. D. C. Lin, E. K. Dimitriadis, F. Horkay, Journal of Biomechanical Engineering 129, 904 (2007).
  * 55. D. C. Lin, E. K. Dimitriadis, F. Horkay, Journal of Biomechanical Engineering 129, 430 (2007).
  * 56. T. Sommer, et al., Geophysical Research Letters 44, 9424 (2017).
  * 57. J. Berg, et al., Environmental Microbiology 21, 1611 (2019).
  * 58. F. Di Nezio, et al., Frontiers in Microbiology 14, 1253009 (2023).
  * 59. F. Di Nezio, et al., bioRxiv p. DOI:10.1101/2023.10.20.563228 (2023).
  * 60. T. R. Cox, J. T. Erler, Disease Models & Mechanisms 4, 165 (2011).
  * 61. N. Sachot, E. Engel, O. Castaño, Current Organic Chemistry 18, 2299 (2014).
  * 62. S. Arnott, et al., Journal of Molecular Biology 90, 269 (1974).
  * 63. F. Jiang, et al., Marine Drugs 21 (2023).
  * 64. P. Serwer, Electrophoresis 4, 375 (1983).
  * 65. K. t. Nijenhuis, Adv Polym Sci 130, 169 (1997).
  * 66. J.-M. Guenet, C. Rochas, Macromolecular Symposia (Wiley Online Library, 2006), vol. 242 (1), pp. 65–70.
  * 67. E. Fernández, et al., Journal of Polymer Science Part B: Polymer Physics 46, 322 (2008). Number: 3.
  * 68. B. Mao, Adhesion, Drying and Formulation, Université de Bordeaux (2017).
  * 69. S. V. Kontomaris, A. Stylianou, A. Georgakopoulos, A. Malamou, Nanomaterials 13, 395 (2023).
  * 70. F. Topuz, A. Nadernezhad, O. S. Caliskan, Y. Z. Menceloglu, B. Koc, Carbohydrate Polymers 201, 105 (2018).
  * 71. V. Zamora-Mora, D. Velasco, R. Hernández, C. Mijangos, E. Kumacheva, Carbohydrate Polymers 111, 348 (2014).
  * 72. A. Kumachev, et al., Biomaterials 32, 1477 (2011). Number: 6.
  * 73. E. Maikranz, et al., Nanoscale 12, 19267 (2020).
  * 74. C. J. van Oss, Interfacial Forces in Aqueous Media (CRC Press, 1994).
  * 75. A. Sengupta, arXiv preprint arXiv:2301.09550 (2023).
  * 76. D. Ji, J. Kim, Advanced NanoBiomed Research 1, 2100026 (2021).
  * 77. B. J. R. Thio, J. C. Meredith, Colloids and Surfaces B: Biointerfaces 65, 308 (2008).
  * 78. Y. Wang, et al., Biomaterials 95, 74 (2016).
  * 79. G. Francius, et al., ACS Applied Bio Materials 4, 2614 (2021).
  * 80. V. D. Gordon, L. Wang, Journal of Cell Science 132, jcs227694 (2019).
  * 81. T. E. Kimkes, M. Heinemann, FEMS microbiology reviews 44, 106 (2020).
  * 82. M. Kuthan, et al., Molecular Microbiology 47, 745 (2003).
  * 83. S. Barua, L. Li, P. Lipke, A. Dranginis, mSphere 1 (2016).