Robustness to Sub-optimal Temperatures of the Processes of Tsr

Cluster Formation and Positioning in Escherichia Coli

Teppo Annila, Ramakanth Neeli-Venkata and Andre S. Ribeiro

Department of Signal Processing, Tampere University of Technology, Korkeakoulunkatu 10, Tampere, Finland

Keywords: Protein Cluster, Tsr Proteins, Cluster Localization, Microscopy.

Abstract: Clustering and positioning of chemotaxis-associated proteins are believed to be essential steps for their

proper functioning. We investigate the robustness of these processes to sub-optimal temperatures by

studying the size and location of clusters of Tsr-Venus proteins in live cells. We find that the degree of

clustering of Tsr proteins is maximal under optimal temperature. The data further suggests that the

weakening of the clustering process in lower-than and higher-than optimal temperatures is not due to the

same cause. Meanwhile, the location of the clusters is found to be weakly temperature independent, within

the range tested. We conclude that while the clustering of Tsr is heavily temperature dependent, the

localization is only weakly dependent, suggesting that the functionality of the proteins responsible for

retaining Tsr-clusters at the cell poles, such as the Tol-Pal complex, is robust to suboptimal temperatures.

1 INTRODUCTION

Escherichia coli have evolved mechanisms to

respond to external stimuli, such as chemotaxis. This

process is based on clusters of chemoreceptors

(Sourjik and Berg, 2004; Wadhams and Armitage,

2004; Parkinson et al., 2005) that can perform

multiple tasks, including thermosensing (Lee et al.

1988) and aerotaxis (Rebbapragada et al. 1997).

One identified transmembrane chemotaxis

receptor protein is Tsr, a cytoplasmic double

membrane-spanning serine receptor (Lee et al.,

1988) that preferentially accumulates at the cell

poles, where it forms clusters (Thiem et al., 2007).

Clustering and positioning at the poles of the

chemotaxis-associated protein clusters are believed

to be essential for their proper functioning, namely,

they are expected to affect the signal processing

capabilities of the receptor system (Kentner and

Sourjik, 2006; Vaknin and Berg, 2006; Skidmore et

al., 2000; Lybarger and Maddock, 1999), even

though changes in receptor activity do not

necessarily require changes in the assembly process

of the clusters (Liberman et al., 2004).

Recent evidence suggests that the retention of the

clusters at the poles is made possible by proteins

such as the trans-envelope Tol-Pal complex, a

widely conserved component of the cell envelope of

Gram-negative bacteria (Santos et al., 2014). Little

is known about how robust this process to sub-

optimal conditions is.

Here, we use the Tsr-Venus construct (Yu et al.,

2006) to study, in live E. coli cells, the robustness of

the clustering process and spatial distributing of Tsr

clusters to sub-optimal temperatures. We chose this

construct since the tagging of Tsr with Venus does

not affect its spatial distribution, due to a linker

sequence that allows the cytoplasmic domain of Tsr

to freely interact with other signalling proteins,

similar to the natural system (Yu et al., 2006).

Meanwhile, the Venus protein is a YFP variant,

derived from GFP, that has a fast maturation time

(Nagai et al., 2002), allowing real time imaging by

fluorescence microscopy.

2 MATERIALS AND METHODS

2.1 Chemicals

For routine cultures, the M9 glucose media

components, isopropyl β-D-1-thiogalactopyranoside

(IPTG), agarose for microscopic slide gel

preparation and antibiotics were purchased from

Sigma-Aldrich. The amino acids and vitamins were

purchased from ThermoFisher.

Annila, T., Neeli-Venkata, R. and Ribeiro, A.

Robustness to Sub-optimal Temperatures of the Processes of Tsr Cluster Formation and Positioning in Escherichia Coli.

DOI: 10.5220/0005647001370141

In Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2016) - Volume 3: BIOINFORMATICS, pages 137-141

ISBN: 978-989-758-170-0

137

2.2 Bacterial Strain and Growth

Conditions

We used E. coli K-12 strain SX4, harbouring the

Tsr-Venus gene construct under the control of the

lac promoter (P

lac

) (Yu et al., 2006), a kind gift from

Sunny Xie, Harvard University, U.S.A. Overnight

liquid cultures were grown in M9 glucose (0.4%)

media, supplemented with amino acids along with

the appropriate antibiotics for 14 h, at 37°C with

shaking (250 rpm).

2.3 Induction of Tsr-Venus Expression

From overnight cultures, cells were inoculated into a

fresh media with the same antibiotics as above, at an

initial OD of 0.05 at 600nm, and grown until the

OD600 reached ~ 0.3, at 37°C with shaking (250

rpm). The induction of Tsr-Venus expression was

performed by adding 200µM IPTG to the culture,

which was left in the incubator at appropriate

temperature (10°C, 15°C, 24°C, 37°C and 43°C) for

1 hour before imaging.

2.4 Microscopy

To study the formation and localization of Tsr-

Venus clusters, 8 µL of cells left at appropriate

temperature were then placed on 1% agarose gel pad

prepared in M9 glucose media for image acquisition.

Cells were visualized in a Nikon Eclipse (Ti-E,

Nikon, Japan) inverted microscope with a C2

confocal laser scanning system using a 100x Apo

TIRF (1.49 NA, oil) objective. Images of cells were

taken with Nikon NIS-elements. The Tsr-Venus

proteins can be detected as fluorescent spots under

the fluorescent confocal microscope using a 488 nm

argon ion laser (Melles-Griot) and a 515/30 nm

detection filter. Images were acquired using a large

pinhole, gain 165 and 3.36 µs pixel dwell.

2.5 Image Analysis

Cell segmentation was performed by a custom-made

software that integrates MAMLE (Chowdhury et al.,

2013) and CellAging (Häkkinen et al., 2013), for

cell segmentation. Phase contrast images were

automatically segmented and the results were

manually corrected as needed. Finally, fluorescence

images were automatically aligned to phase-contrast

images. The fluorescence in each cell was then

extracted and analysed by a custom-made Matlab

script.

To assess the location of Tsr-Venus clusters

along the major axis of a cell, we first formally

defined a ‘cluster’ or ‘spot’ as a connected

component with each pixel having a light intensity

above a threshold. For this, we performed a

Laplacian of Gaussian based spot detection

combined with an adaptive local thresholding step

(Annila, 2015). It assumes that the background pixel

intensities follow a Gaussian distribution. The

threshold is then selected for each cell separately

based on the fitted distribution such that the

probability of mislabeling a pixel from this

distribution is smaller than 0.005. From the

segmented image, the number of clusters was

counted and the area of each cluster was calculated

by counting the number of pixels within.

To distinguish between midcell and poles, we

defined a boundary between them at 0.5 (with 0

being midcell and 1 being the cell extreme) (Santos

et al., 2014).

Finally, the intensity of the clusters was directly

acquired from background corrected cells, which

were obtained by subtracting the median cell

intensity from each pixel of the cell. Next, for each

cell, the total protein fluorescence was obtained by

summing the fluorescent intensity of the clusters.

3 RESULTS

First, after segmenting cells and clusters of Tsr-

Venus (see example Figure 1), for each temperature

condition, we extracted from each cell the total

fluorescence of the clusters, the number of clusters

and the area occupied by the clusters (Table 1).

Figure 1: Fluorescence microscopy image of Escherichia

coli cells expressing Tsr-Venus.

From Table 1, the production of Tsr-Venus proteins

under the control of P

lac

is heavily temperature

dependent, as expected (Kandhavelu et al., 2012),

BIOINFORMATICS 2016 - 7th International Conference on Bioinformatics Models, Methods and Algorithms

138

Table 1: Tsr-Venus clustering at different temperatures. Standard error of the mean (SEM) is shown in parenthesis.

10°C 15°C 24°C 37°C 43°C

No. cells 176 301 259 265 299

Mean total cluster

fluorescence (a.u.)

0.3x10

(0.02x10

)

0.8x10

(0.04x10

)

1.5x10

(0.06x10

)

1.5x10

(0.08x10

)

0.8x10

(0.08x10

)

Avg. no. clusters per cell 0.53 (0.05) 0.74 (0.03) 1.02 (0.03) 1.23 (0.03) 0.49 (0.04)

Avg. cluster area (µm

) 0.5 (0.03) 0.74 (0.02) 1.1 (0.03) 1.1 (0.04) 0.8 (0.04)

Clustering coefficient (%) 13.9 (1.4) 30.6 (1.5) 56.2 (1.6) 61.5 (1.2) 18.0 (1.4)

with the total fluorescence per cell from these

proteins being maximized at 37°C. Meanwhile, we

expect the decrease in mean fluorescence per cell

from 37°C to 43°C to likely be due to the increased

cell division rate with temperature not being

compensated sufficiently by an increase in protein

production.

Next, in order to assess whether the clustering

process is temperature dependent, we calculated the

‘clustering coefficient’ of Tsr-Venus. We define this

quantity as the ratio between the fluorescence from

clusters and the total cell fluorescence. Averages

from all cells of these three quantities for each

condition are shown in Table 1. Visibly, the

clustering coefficient maximizes at 37°C and, thus,

we conclude that, under optimal temperature, the Tsr

proteins are more efficiently clustered.

We also plotted the mean cluster fluorescence

against the mean number of clusters per cell, for

each condition (Figure 2). Visibly, there is a lack of

linear relationship between temperatures lower than

and higher than the optimal. This suggests, as

mentioned above, that the underlying causes for

weaker clustering at low temperatures differ from

the causes at high temperatures. Further studies are

needed to identify these causes. We expect division

rates and diffusion rates of the clusters to play a role

in these differences.

To test whether Tsr-Venus fluorescence is

affected by temperature in the range studied, we

plotted the mean cluster fluorescence against the

mean area of the clusters per cell, for each condition

(Figure 3).

From Figure 3, we conclude that bigger clusters

tend to be brighter and that this relationship between

size and brightness is fairly independent of

temperature.

Finally, we studied whether the intracellular

localization of the clusters is affected by

temperature. For that, we measured the fractions of

Figure 2: Mean total fluorescence from Tsr clusters as a

function of the average number of these clusters per cell.

Figure 3: Mean total fluorescence from Tsr-clusters as a

function of the average area of the clusters per cell.

‘polar’ and ‘lateral’ clusters (Table 2). The former

are defined as those inside the poles of the cell,

while the latter are at midcell, the region in between

the poles.

In all cases, the percentage of polar clusters was

over 94%. We performed a binomial test for the

proportions of lateral clusters with the null

Robustness to Sub-optimal Temperatures of the Processes of Tsr Cluster Formation and Positioning in Escherichia Coli

139

hypothesis that they are coming from the same

distribution. It is usually accepted that, for p-values

smaller than 0.01, the null hypothesis is rejected.

Table 2: Localization of Tsr-Venus clusters. Shown are

the percentages of clusters at the poles (‘polar clusters’),

and the percentages of clusters at midcell (‘lateral

clusters’) for cells at 10°C, 15°C, 24°C, 37°C, and 43°C.

10°C 15°C 24°C 37°C 43°C

Polar

clusters (%)

98.9 99.1 99.6 96.0 94.5

Lateral

clusters (%)

1.1 0.9 0.4 4.0 5.5

From the comparisons between all pairs of

conditions, we find a tangible difference only

between 24°C and 43°C (all other p-values were

above 0.05). From this, we conclude that the

localization process is only weakly dependent of

temperature, in the range tested.

4 CONCLUSIONS

Tsr proteins play a central role in the chemotaxis

mechanisms of Escherichia coli. For this, they

participate in large clusters of various proteins.

From microscopy measurements of cells

expressing Tsr proteins tagged with Venus proteins,

we compared the clustering process and the

behaviour of the clusters at different temperatures.

We found that, in all conditions, these proteins

are able to form clusters and that these preferentially

locate at the cell poles. Nevertheless, the clustering

process is temperature dependent in that, at 37 °C,

the clusters clearly harness Tsr-Venus proteins more

efficiently than in the other conditions.

At the moment, the cause(s) for the dependence

of the clustering process on temperature is unknown.

However, recent studies showed that both the

cytoplasm viscosity (Parry et al., 2014) as well as

the relative nucleoid size of these cells are heavily

temperature dependent, which could explain why

temperature affects the long-term spatial distribution

of the clusters. Another possibility is that the

clustering process is not energy-free, and thus

depends on how much energy the cell has available

(similarly to the clustering of unwanted protein

aggregates (Govers et al., 2014)).

On the other hand, we observed that the

localization of the clusters (at the pole or at midcell),

appears to be only weakly temperature dependent,

within the range of temperatures studied. From this,

we conclude that the functionality of the proteins

responsible for retention of Tsr-clusters at the poles,

such as the Tol-Pal complex, is robust to suboptimal

temperatures, or that other, non-energy dependent

mechanisms, contribute to this preference for polar

localization.

In the future, it would be of interest to investigate

the causes for the temperature dependence of the

clustering process and for the temperature

independence of the localization process of these

proteins.

ACKNOWLEDGEMENTS

Work supported by Academy of Finland (257603,

ASR) and Portuguese Foundation for Science and

Technology (PTDC/BBB-MET/1084/2012, ASR).

The funders had no role in study design, data

collection and analysis, decision to publish, or

preparation of the manuscript.

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