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Investigating effects of morphology and flagella dynamics on swimming kinematics of different helicobacter species using single-cell imagingConstantino, Maira Alves 14 February 2018 (has links)
This work explores the effects of body shape and configuration of flagella on motility of Helicobacter pylori, a helical-shaped bacterium that inhabits the viscoelastic gastric mucosa and causes gastritis, ulcers and gastric cancer. Although it is well known that different shapes produce different hydrodynamic drag thus altering the speed and that helical shapes generate additional thrust this has not been quantitatively established for flagellated bacteria. Using fast time-resolution and high-magnification two-dimensional phase-contrast microscopy to simultaneously image and track individual H. pylori and its rod-shaped isogenic mutant in broth and mucin solutions, the shape as well as rotational and translational speed was determined. In collaboration with Professor Henry Fu and Mehdi Jabbarzadeh the experimental data was used to validate the method of regularized Stokeslets by directly comparing the observed speeds to numerical calculations. The results show that due to relatively slow body rotation rates, the helical shape makes at most a 15% contribution to speeds. In order to explore the effects of arrangement of flagella on motility three different Helicobacter spp. were examined: H. suis (bipolar, multiple flagella), H. cetorum (bipolar, single flagellum) and H. pylori (unipolar, multiple flagella) swimming in broth and mucin. Results show that regardless of media, the flagella bundles of bipolar bacteria can assume one of two configurations interchangeably: extended away from the body or wrapped around it. H. suis predominantly swims with the lagging flagella extended behind the body and the leading flagella wrapped around it, but cases where both bundles are extended or both are wrapped have also been observed. In addition the effects of varying pH on motility of H. suis in broth and mucin were investigated. In broth the rotational speed is not significantly affected by varying pH and the peak of the speed distribution shifts to lower values as the pH decreases. However in mucin the rotational speed decreases by a factor of 20 from pH5 to 4 and the motion is completely hindered below pH4. This indicates that H. suis is unable to move below pH4, in agreement with previous findings on H. pylori, due to gelation of mucin below pH4.
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An Experimentally-validated Agent-based Model to Study the Emergent Behavior of Bacterial CommunitiesLeaman, Eric Joshua 03 February 2017 (has links)
Swimming bacteria are ubiquitous in aqueous environments ranging from oceans to fluidic environments within a living host. Furthermore, engineered bacteria are being increasingly utilized for a host of applications including environmental bioremediation, biosensing, and for the treatment of diseases. Often driven by chemotaxis (i.e. biased migration in response to gradients of chemical effectors) and quorum sensing (i.e. number density dependent regulation of gene expression), bacterial population dynamics and emergent behavior play a key role in regulating their own life and their impact on their immediate environment. Computational models that accurately and robustly describe bacterial population behavior and response to environmental stimuli are crucial to both understanding the dynamics of microbial communities and efficiently utilizing engineered microbes in practice. Many existing computational frameworks are finely-detailed at the cellular level, leading to extended computational time requirements, or are strictly population scale models, which do not permit population heterogeneities or spatiotemporal variability in the environment. To bridge this gap, we have created and experimentally validated a scalable, computationally-efficient, agent-based model of bacterial chemotaxis and quorum sensing (QS) which robustly simulates the stochastic behavior of each cell across a wide range of bacterial populations, ranging from a few to several hundred cells. We quantitatively and accurately capture emergent behavior in both isogenic QS populations and the altered QS response in a mixed QS and quorum quenching (QQ) microbial community. Finally, we show that the model can be used to predictively design synthetic genetic components towards programmed microbial behavior. / Master of Science / Bacteria are an integral part of life and possess a host of characteristics that make them a powerful tool with which to confront many modern day problems. Using genetic engineering and the burgeoning field of synthetic biology, these single-celled organisms can be manipulated to perform many useful tasks such as detecting oil spills or other environmental pollutants, producing pharmaceuticals such as insulin, and even invading and killing cancer cells. Accurate computational simulations of microbial behavior will aid in the efficient design of such synthetic bacteria-based systems and reduce dependency on the current time-intensive “guess and check” paradigm. Towards this goal, we have built a comprehensive computer simulation of bacterial swimming behavior, response to chemo-effector concentration gradients called chemotaxis, a form of microbial communication called quorum sensing (QS), and a form of communication disruption called quorum quenching (QQ). Not only do we demonstrate an unprecedented level of accuracy in predicting experimental results, but we also couple the simulation with synthetic biology to precisely tune bacteria QS behavior, neither of which have previously been reported in literature. The overarching outcome of this thesis is a tool that could be used to improve the design process of useful bacteria-based systems in diverse areas of biotechnology.
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Multi-flagellated bacteria : stochastic model for run-and-tumble chemotaxisRaharinirina, Nomenjanahary Alexia 03 1900 (has links)
Thesis (MSc)--Stellenbosch University, 2012. / ENGLISH ABSTRACT: Bacterial chemotaxis, as observed for Escherichia coli, in a field of chemoattractant
molecules is characterised by a run-and-tumble motion. The motion
is effected by the clockwise (CW) or counter-clockwise (CCW) rotation
of flagella; filamentous appendages attached to molecular motors on the
cell body. Runs appear when all flagella turn in the CCW-direction and are
used to maintain a favourable direction. Tumbles emerge as soon as one
flagellum starts to turn CW and are used for reorientation. Because of the
variation observed between individual bacteria displaying run-and-tumble
motion, we choose to model this behaviour within a probabilistic framework.
An important feature of the chemotactic ability of E.coli is that the cell increases
run while moving in the right direction and shortens it in the opposite
case. This underlines that tumbles are used for reorientation. It has been
found from experiments that there can be significant variation in the tumble
fashion depending on the fraction of CW-rotating motors (Turner et al.,
2000). The change in angle produced when fewer flagella are rotating CW
was found to be smaller when compared to the case for many CW-rotating
flagella. In addition, the change of direction contributed by a small portion
of CW-rotating flagella is rarely significant for bacteria with many flagella.
Based on these observations, we have distinguished between models for the
one-flagellated and the multi-flagellated cases.
Furthermore, since the tumbling angle change increases with the fraction
of CW-rotating motors, it would not be impossible to have some cases where
the amount of turn produced by the CW-rotating motors induces the bacterium
to have a change of direction greater than 2π. But, this feature could not have been observed because when the bacterium tumbles it can effectuate
several revolutions before resuming to a new direction. Therefore, we
do not restrict our change of direction to (0,2π) to allow the bacteria to have
the possibility to effectuate change of directions of magnitude greater than
2π. To this end, we differentiate between the probability of having directional
change of magnitude α and α +2π . Thus we do not use angle change
distributions that are defined modulo 2π such as the von Mises distribution
or the wrapped normal distribution.
The chemotactic ability of the bacterium is modelled by representing the
CCW-bias of a single flagellum as a function of the chemoattractant concentration.
The model includes the temporal memory of chemoattractant
concentration that the bacterium has, which usually spans about 4s. The
information about the quality of the current direction of the bacterium is
transmitted to the flagellar motor by assuming that this one varies with the
chemoattractant concentration level. In addition, the saturation of the bias
is incorporated by assuming that the bacterium performs a temporal comparison
of the receptor occupancy. The present CCW-bias-Model accounts
for the chemotactic ability of the bacterium as well as its adaptation to uniform
chemoattractant environment.
The models of one-flagellated and multi-flagellated bacterial motion, are
used to investigate two main problems. The first one consists of determining
the optimal tumbling angle strategy of the bacteria. The second one
consists of looking at the effects of the tumble variation on the chemotactic
efficiency of the bacteria. In order to address these questions, the chemotactic
efficiency measure is defined in such a way that it reflects the ability of
the bacteria to converge and to stay in a near neighbourhood of the source
so that they gain more nutrients.
Since its movement is entirely governed by its single flagellum, the one
flagellated bacterium is more able to effectuate a run motion. Tumbling
events are modelled to be all equivalent because there is not any fraction of
flagella to consider.
On the other hand, the tumble variation of the multi-flagellated bacteria
is modelled by assuming that the directional change during a tumble is a
function of the fraction of CW-rotating motors. By assuming that the number
of CW-rotating flagella follows a binomial distribution, we suppose that
the multi-flagellated bacteria are less able to effectuate a run motion. This
also implies that the change of direction produced by fewer CW-rotating
flagella are more likely to happen, and this compensates the lack of run.
The models show that the optimal tumbling angle change for the bacteria
is less than 2π and that higher flagellated bacteria have higher chemotacitc
efficiency. As the number of flagella of the bacteria increases, there can be
more tumble variation, in this case the bacteria are more capable of adjusting
their direction. There could be some situation were the bacteria are not
moving to the right direction, but do not require a large change of direction. This ability to adjust their direction accordingly allows them to converge
nearer to the source and to gain more nutrients.
In addition, the dependence of the tumbling angle on the fraction of
CW-rotating flagella of the mutli-flagellated bacteria, implies that there is
a correlation between the tumbling angle deviation and the external environment,
because the rotational states CCW-CW of the flagella depends on
the external cue. Consequently, it would not be impossible that the average
magnitude of tumbling angle change depends on the external environment.
To investigate this possibility we analyse the distribution of the tumbling
tendency of a single bacterium over time, which is the distribution over
time of the average positive tumbling change of the bacterium, within zerogradient
environment and within non-zero-gradient environment. We defined
the average of these tumbling tendency over time as the directional
persistence.
We observe that the directional persistence within these different nonzero-
gradient environment remains the same. However, the difference between
the directional persistence within zero-gradient and non-zeros gradient
environment gets larger as the number of flagella of the cell increases.
There is more correlation between the external environment and the tumbling
tendency of the bacterium. Which is the reason why the higher flagellated
bacteria responds the best to the external environment by having the
higher chemotactic performance.
Finally, the total directional persistence generated by the optimal tumbling
angle change of the bacteria is the average directional persistence of
the bacteria regardless of their number of flagella. Its value, predicted by
the model is 1.54 rad within a non-zero-gradient environment and 1.63 rad
within a zero-gradient environment. / AFRIKAANSE OPSOMMING: Bakteriese chemotakse, soos waargeneem word vir Escherichia coli, in ’n
veld van chemiese lokmiddel molekules word gekenmerk deur ’n hardloopen-
tuimel beweging. Die beweging word bewerkstellig deur die regsom of
linksom rotasie van flagella; filamentagtige aanhangsels geheg aan molekulêre
motors op die selliggaam. ’n Hardloop aksie kom voor as al die
flagella linksom roteer en word gebruik om ’m voordelige koers te handhaaf.
Tuimels kom voor sodra een van die flagella regsom draai en word
gebruik vir heroriënteering. Van wee die variasie wat waargeneem word
tussen individuele bakterieë wat hardloop-en-tuimel bewegiging vertoon,
verkies ons ’n probabilistiese raamwerk om in te werk.
’n Belangrike eienskap van die chemotakse vermoë van E. coli is dat die
sel meer gereeld hardloop terwyl dit in die regte rigting beweeg en minder
gereeld in die teenoorgestelde geval. Dit beklemtoon dat tuimels gebruik
word vir heroriënteering. Dit is al eksperimenteel vasgestel dat daar
betekenisvolle variasie kan wees in die tuimel wyse, wat afhang van die
breukdeel regsom roterende motors (Turner et al., 2000). Die hoekverskil
afkomstig van minder regsom roterende flagella was vasgestel om kleiner
te wees in vergelyking met die menig regsom roterende geval. Verder word
die bydrae tot die hoekverskil van ’n klein breukdeel regsom roterende flagella
selde beduidend vir bakterieë met baie flagella. As gevolg van hierdie
waarnemings, tref ons onderskeid tussen modelle vir een-flagella en multiflagella
gevalle. Aangesien die tuimel hoeksverskil vergroot saam met die breukdeel regsom
roterende motore, is dit nie onmoontlik om gevalle te hê waar die hoeveelheid
draaiaksie gegenereer deur die regsom roterende motore ’n rigtingsverskil
groter as 2π kan bewerkstellig nie. Dit was nie moontlik om
hierdie eienskap waar te neem nie aangesien die bakterieë ’n paar keer kan
tuimel voordat ’n nuwe rigting vasgestel word. Vir hierdie rede beperk ons
nie die hoeksverskil tot (0,2π) nie om die bakterieë toe te laat om rigtings
veranderinge groter as 2π te ondergaan. Vir hierdie doel, onderskei ons tussen
die waarskynlikheid van ’n rigtinsverskil met grootte α en α + 2π. Dus,
gebruik ons nie hoekverskil verspreidings wat modulo 2 gedefinieer is nie,
soos die von Mises verspreiding of omwinde normaalverdeling.
Die chemotakse vermoë van die bakterium word gemodelleer deur die
linksom sydigheid van ’n enkele flagellum as ’n funksie van die chemotakse
lokmiddel konsentrasie voor te stel. Die model sluit in die tydelike
geheue wat die bakterium besit oor chemotakse lokmiddel konsentrasie,
wat gewoonlik oor 4s strek. Die informasie oor die kwaliteit van die huidige
rigting van die bakterium word deur gegee na die flagella motor toe
deur die aanname te maak dat dit wissel met die chemotakse lokmiddel
konsentrasie vlak. Die versadiging van die sydigheid word geinkorporeer
deur aan te neem dat die bakterium ’n temporale vergelyking maak tussen
reseptor okkupasie. Die huidige linksom sydige model neem die bakterium
chemotakse vermoë in ag, as ook aanpassing tot ’n uniforme chemotakse
lokmiddel omgewing.
Die modelle van een-flagella en multi-flagella bakteriële beweging word
gebruik om twee hoof probleme te bestudeer. Die eerste, bestaan daaruit om
vas te stel wat die optimale tuimel hoek strategie van die bakterieë is. Die
tweede kyk na die uitwerking van tuimel variasie op chemotakse effektiwiteit.
In orde om hierdie vra te adreseer word die chemotakse effektiwiteit
op so mannier gedefinieer dat dit die bakteriese vermoë om die buurt om
die oorsprong te nader en daar te bly.
Aangesien die beweging heeltemal vasgestel word deur een flagella, in
die een-flagella geval, is ’n bakterium meer in staat daartoe om ’n hardloop
aksie te bewerkstellig. Tuimel voorvalle word as ekwivalent gemodeleer
omdat daar geen breukdeel roterende flagella is om in ag te neem nie.
In teenstelling, word die tuimel variasie van multi-flagella bakterieë gemodeleer
deur die aanname te maak dat rigtingsverandering gedurende ’n
tuimel ’n funksie is van die breukdeel regsom roterende motore. Deur die
aanname te maak dat die getal regsom roterende flagella ’n binomiese verspreiding
volg, veronderstel ons dat multi-flagella bakterieë minder in staat
daartoe is om ’n hardloop aksie te onderneem. Hierdie impliseer ook dat
rigtingverandering wat geproduseer word deur minder regsom roterende
flagella meer geneig is om voor te kom en dan kompenseer vir ’n tekortkoming
aan hardloop gebeure.
Die modelle wys dat die optimale tuimelhoek verandering minder as 2 is en dat bakterieë met meer flagella meer chemotaksies effektief is. Soos
die getal flagella vermeder, kan daar meer tuimel variasie wees, en in die
geval is die bakterieë meer in staat om hul rigting te verander. Daar kan
omstandighede wees waar die bakterieë nie in die regtige rigting beweeg
nie, maar nie ’n groot rigtingsverskil nodig het nie. Hierdie vermoë om hul
rigting byvolglik te verander stel hul in staat om nader aan die oorsprong
te konvergeer en dus meer voedingstowwe op te neem.
Die afhanklikheid van die tuimel hoek op die breukdeel regsom roterende
flagella van multi-flagella bakterieë dui daarop dat daar ’n korrelasie
is tussen die tuimel hoek afwyking en die eksterne omgewing, omdat
die roterings toestand, regs- of linksom, van die flagella afhanklik is van
die eksterne sein. As ’n gevolg, is dit nie onmoontlik dat die gemiddelde
grootte van die tuimel hoek verandering van die eksterne omgewing afhang
nie. Om hierdie moontlikheid te bestudeer, analiseer ons die verspreiding
van die tuimel neiging van ’n enkele bakterium oor tyd, wat die verspreiding
oor tyd van die gemiddelde positiewe tuimel verandering is, in ’n nulgradient
en nie-nul-gradient omgewing. Ons het hierdie gemiddelde tuimel
neigings oor tyd gedefinieer as die rigtings volharding.
Ons het waargeneem dat die rigtings volharding binne verskillende nienul-
gradient omgewings dieselfde bly. Nogtans is die verskil tussen die rigtings
volharding binne nul-gradient en nie-nul-gradient omgewings groter
soos die getal flagella vermeder. Daar is meer korrelasie tussen die eksterne
omgewing en tuimel neiging van die bakterium. Dit is die rede hoekom
bakterieë met meer flagella die beste reageer op die eksterne omgewing
deur beter chemotakse effektiwiteit.
Ten slotte, die totale rigtings volharding gegenereer deur die optimale
tuimel hoek verandering is die gemiddelde rigtings volharding ongeag van
die getal flagella. Die waarde wat deur die model voorspel word is 1.54
rad binne ’n nie-nul-gradient omgewing en 1.63 rad binne ’n nul-gradient
omgewing.
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Analyse expérimentale de la dynamique de nage des spermatozoïdes / Spermatozoa swimming experimental analysisCreppy, Adama Kpatagnon 21 September 2015 (has links)
Les microorganismes présentent des comportements collectifs qui émergent des interactions qui se produisent à l’échelle individuelle. Dans le cas des suspensions concentrées (fraction volumique > 50%) les effets stériques deviennent dominants. C’est le cas du sperme de bélier sur lequel cette étude a principalement porté. Nous avons étudié certains aspects hydrodynamiques liés à la rhéologie du sperme et à la rhéotaxie. Nous montrons un comportement rhéo-fluidifiant en loi de puissance du liquide séminal reproductible d’un in- dividu à l’autre. Nous avons aussi mis en évidence qu’un contrôle chimique peut fortement affecter le comportement rhéotactique des spermatozoı̈des chez l’ovin et chez l’homme. Nous avons par ailleurs étudié la dynamique collective de la semence confinée dans des chambres d’épaisseur contrôlée en apportant des éclaircissements sur l’origine et la caractérisation du comportement turbulent observé. Nos résultats montrent que certaines caractéristiques de la turbulence bidimensionnelle se manifestent (loi de puissance du spectre d’énergie des vitesses, loi de séparation des traceurs passifs) que nous interprétons comme résultant d’une stratification laminée de l’écoulement par les interactions stériques à forte concentration. Enfin, nous avons développé et breveté un système micro-fluidique dans lequel une mise en rotation spontanée de la semence apparaı̂t. Nous avons analysé ce phénomène et l’avons relié à une transition de phase d’orientation cohérente avec une modélisation de type Self-Organized-Hydrodynamics. De plus nos résultats montrent une bonne corrélation entre la vitesse de rotation et la note de mobilité massale, donnant des perspectives d’applications pour la prédiction de la fertilité à ce dispositif. / Microorganisms exhibit collective behaviors that emerge from interactions occurring at the individual scale. In the case of high concentrated suspensions (volume fraction > 50%) steric effects become dominant. This is the case of ram semen on which this study focused. We first studied some hydrodynamic aspects related to the semen rheology and rheotaxis. We show a reproducible seminal plasma power law shear-thinning behavior from one subject to another. We have also highlighted that a chemical control can strongly affect the rheotactic behavior of sperms in the ovine and humans. We also studied the collective dynamics of the semen in chambers of control depth by providing clarification on the origin and characterization of the observed turbulent behavior. Our results show that some characteristics of two-dimensional turbulence occur (power law of the velocity energy spectrum, the pair-particles separation law ) that we interpret as the result of a stratification laminated flow induced by steric interactions at high concentration. Finally, we have developed and patented a micro-fluidic system in which a spontaneous spin-up appears. We analyzed this phenomenon and we connect it to a coherent orientation phase transition with a Self-Organized-Hydrodynamics modeling. In addition, our results show a good correlation between the speed and scoring of mass mobility, giving opportunities for application of the prediction of fertility for this device.
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Effect of Spatial Organization and Population Ratios on the Dynamics of Quorum Sensing and Quorum Quenching in Bacteria CommunitiesThielman, Maria-Fe Sayon 05 February 2024 (has links)
Quorum sensing (QS) is a type of microbial communication used by bacteria to coordinate their behavior based on population density, regulating complex processes like biofilm formation and virulence, among other behaviors. Quorum quenching (QQ), on the other hand, disrupts this communication, usually by degradation of the QS signaling molecule. QQ offers a potential strategy for controlling bacterial behaviors linked to pathogenicity and biofouling. Despite significant advances in understanding and modeling the spatial-temporal behavior of QS, predictive modeling of QQ remains nascent, with a notable gap in the quantitative assessment of QQ's impact on QS. Here we show quantitative evaluation and characterization of the effect of QQ on QS in agar-based experiments, combined with an experimentally validated computational model. This research utilizes green fluorescence in E. coli MG 1655 as an indicator of QS activation, focusing on the degradation of Acyl-Homoserine Lactone (AHL), a key QS molecule in Gram-negative bacteria linked to pathogenicity, by the AiiA enzyme in engineered AiiA-producing Salmonella Typhimurium 14028. Our findings suggest that QQ more effectively influences QS in spatial configurations of the populations with larger interaction surfaces and shorter diffusion distances. Contrary to our initially held hypothesis, the primary effect of QQ is not a delay in QS onset but rather an attenuation of QS activity, with the area-under-the-curve of fluorescence serving as a quantitative metric. This study also introduces, to the best of our knowledge, one of the first instances of experimentally validated predictive modeling for QQ, applied to agar-based experimental setups. We posit that the quantitative experimental characterization and modeling framework presented in this research will enhance the understanding of bacterial community interactions. Enhanced comprehension of QQ and QS behaviors holds significant promise for advancing practical applications, particularly in mitigating or diminishing undesirable QS-associated activities. This is especially relevant in areas like biofouling, waste treatment, and the reduction of infections and progression of diseases in plants and animals, areas increasingly important as concerns about drug resistance in microbes and food security escalates. / Master of Science / One of the ways bacteria communicate with each other is called quorum sensing (QS), where they use chemical signals to organize and time group behavior, including forming communities encapsulated in protective layers, called biofilms, and engaging in virulent attacks against hosts. Quorum quenching (QQ) in bacteria, however, disrupts this communication system, usually by breaking down the chemical signals that bacteria use to send messages to each other.
Even though QS has been studied extensively, determining how to predict and control QQ is still a nascent area of research. Here, we studied and characterized how QQ affects QS by doing experiments with bacteria populations in agar (a jelly-like substance) and applied a computational model to explain and ultimately predict the experimental observations. Engineered QS population (E. coli MG 1655) produced Acyl-Homoserine Lactone (AHL) signaling molecules, and engineered QQ bacteria (S. Tm 14028) used the Autoinducer Inactivation A (AiiA) enzyme to break down the AHL.
According to our results, QQ doesn't delay the QS bacteria's group behaviors (in our case, green fluorescent signal production); it weakens the signal instead.
Understanding QQ and QS better, especially through measurements and modeling, could lead to expanded methods of deterring harmful bacterial behavior, managing waste better, and stopping diseases in plants, animals, and humans, especially with the concerning rise of drug-resistant microbes and food security. One exciting possibility is using QQ to protect plants from bacterial infections. This could be a way to shield our crops without always relying on antibiotics.
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