This course will give you an introduction to bacteria and chronic infections. Leading experts in the field will make you familiar with the fundamental concepts of microbiology and bacteriology such as single cell bacteria, biofilm formation, and acute and chronic infections.
6.3 Evolution in biofilms - Part 2, by Associate professor Steve Diggle
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Del curso dictado por University of Copenhagen
Bacteria and Chronic Infections
590 calificaciones
De la lección
The evolutionary perspectives of biofilms
Dear all, welcome to this last module of the course. In this module you will learn about the evolutionary aspects of biofilms. You will hear about how bacteria adapt to chronic infections and how bacteria can cooperate or fight each other.
I hope you will have fun
CheersThomas
Conoce a los instructores
Thomas BjarnsholtProfessor
Costerton Biofim Centre
Hello everyone, my name is Steve Diggle and I am an Associate Professor in Sociomicrobiology
in the School of Life Science at the University of Nottingham in the UK. I started my research
career looking at the molecular mechanisms that control cell-to-cell signalling, usually
known as quorum sensing, in the opportunistic pathogen Pseudomonas aeruginosa. In 2006 I
was awarded a fellowship from the Royal Society to study quorum sensing from a more evolutionary
perspective. So, rather than working on ‘how’ quorum sensing works, I started to ask ‘why’
questions such as ‘is quorum sensing really a social behaviour’ and ‘why is it maintained
in natural populations’. Such questions are asked in the field of social evolution
and so in this lecture, I will tell you about social evolution in microbes, and at the end,
discuss why this is important in biofilms. In a microbial biofilm, innumerable cells
form complex structures in which each individual cell plays only a small role. Much of the
literature traditionally describes a biofilm as a coordinated and cooperative unit where
the activity of each individual cell benefits the overall group. Upon closer inspection
however, this is not always the case. First, the architectural features such as mushroom
like structures, water channels and stratifications may be the result of chemical gradients, simple
growth parameters and physiological adaptation to a particular micro-niche. These can arise
with no coordination, cooperation or communication between participant cells. Second, when a
behaviour is performed that confers a cost to the individual performing the behaviour,
and a benefit to the surrounding population, that behaviour is vulnerable to cheating strategies
which do not contribute a benefit to the population but benefit individuals. In this lecture I
will describe social evolution and social behaviours in microbes and discuss why this
might be important in biofilms. Before we talk specifically about biofilms,
let us first discuss why we might be interested in studying social evolution in microbes.
Social evolution has become an active area of research in microbiology for a number of
reasons. For example, microbes display many apparently social or cooperative behaviors,
and many of these behaviors seem to be crucial for those microbes to survive in their ecological
niches or to become successful pathogens. Biofılm formation could be a prime example
of a cooperative social behaviour. In addition, social evolution research also complements
mechanistic studies by presenting evolutionary problems for which there must be mechanistic
solutions. Next we must talk about what defines a social
behavior. There is a huge body of work examining microbial behaviours from a molecular perspective,
but comparatively little from an evolutionary standpoint. Social behaviours in microbes
have, until relatively recently, been ignored by evolutionary biologists, yet there has
been much work done in this area both theoretically and empirically in higher organisms such as
insects, birds and mammals. Social behaviours are those which have fitness consequences
for both the actor performing the behaviour and the recipient of the behaviour, and can
be broadly categorized into four types depending on the fitness consequences for both the actor
and the recipient. A behaviour that increases the fitness of the actor is mutually beneficial
if the recipient also benefits, and selfish if the recipient suffers a loss. A behaviour
that reduces the fitness of the actor is altruistic if the recipient benefits, and spiteful if
the recipient suffers a loss. It is important to understand the nature of the interaction
between actor and recipient as then we can make very different predictions as to how
such a behaviour evolves and is maintained in populations. One of the big challenges
for us as microbiologists, is to understand the multitude of behaviours that have been
described in a wide range of bacterial species from an evolutionary perspective, which will
increase our understanding of the nature of these behaviours, and complement previous
and future molecular work. Furthermore, understanding whether a behavior is social can help us understand
how bacterial populations interact within infected hosts, which will help explain how
virulence and antimicrobial resistance evolves. We could even use some of the ideas of social
evolution to help us reduce virulence during infection, and favourably improve the outcome
for patients. What are microbial social behaviours?
Microbial behaviours might seem simpler than those that have been described in higher organisms,
but they share a fundamental similar property: a shared investment in producing a group resource.
Many microbial social behaviours come in the form of public goods which are released into
the surrounding environment and are costly for individuals to make but provide a benefit
for all other individuals in the population. Microbes make a wide variety of public goods
including siderophores for iron scavenging, β-lactamases to inactivate antibiotics, exopolysaccarhides,
toxins, extracellular proteases, and quorum sensing signal molecules. I am sure that you
will be able to think of lots of other examples. However, despite the multitude of cooperative
behaviours seen in the natural world, explaining cooperative behaviours such as altruism has
been a significant challenge for evolutionary biologists. The problem arises because altruistic
behaviours, reduce the fitness of the actor. The question then becomes why help others
at a cost to yourself? This appears to conflict with Charles Darwin’s idea of the survival
of the fittest, because natural selection favours those individuals with the greatest
reproductive success relative to the rest of the population. It is therefore difficult
to see why altruistic behaviours, which reduce the fitness of the actor, can be evolutionarily
favoured. Because an actor accrues a fitness cost by performing a behaviour, there is the
potential of exploitation by cheats or freeloaders who do not cooperate, and who therefore gain
a fitness advantage in the population because they do not pay the costs of cooperation.
This is sometimes referred to as a ‘tragedy of the commons’, which was originally used
to describe human economics and morality, but can also be applied to microbes. The tragedy
is that if everyone cooperated this would benefit the population, but cheating, even
though these individuals benefit in the short term, puts the entire population at a risk
of collapse or extinction. To illustrate social evolution in microbes
we will look at the well studied social trait of quorum sensing. This is a process where
cells communicate with each other via diffusible signal molecules. These signals coordinate
a wide range of behaviors at the population or group level. In a range of gram-negative
and gram-positive bacterial species, QS signals regulate the production of extracellular “public
goods,” including nutrient-scavenging molecules, exoproteases, toxins, and surfactants that
aid cellular motility. In the opportunistic pathogens Pseudomonas aeruginosa and Staphylococcus
aureus, quorum sensing has been shown to be both costly and exploitable by cheats. Using
a synthetic growth medium where quorum sensing-dependent exoprotease production is important for growth,
wild-type Pseudomonas aeruginosa populations grow well, but populations of quorum sensing
mutants grow poorly. Crucially, in mixed cultures, quorum sensing mutants act as social cheats
because they have a fitness advantage due to exploitation of the exoprotease production
of wild-type cells. Similarly, when mice with burned skin or with chronic wounds are infected
with Pseudomonas aeruginosa, quorum sensing mutants act as cheats and invade the bacterial
population within days. In waxmoth larvae infections, a similar pattern of sociality
for Staphylococcus aureus can be observed. Quorum sensing mutants are less fit than their
wild-type counterparts in monoculture infections but demonstrate social cheating when in mixed
infection. Such results help us to explain why quorum sensing mutants often arise in
clinical infections even though such loss-of-function mutations might appear to be detrimental to
fitness. Furthermore, mixed infections of wild type cells with cheats, show a reduced
virulence, because cheats do not make tissue damaging toxins. This could be used to our
advantage because cheats could be introduced into infections to both reduce virulence and
buy time for the immune system to deal with the infection. This has resulted in the term
‘cheatobiotics’, but a lot more research is need in this area.
How can cooperation be maintained in the light of cheating?
A key question in the social evolution field is how are social behaviours maintained given
that cheats enjoy large fitness advantages in mixed populations? One of the most studied
ideas is ‘inclusive fitness’. This is the idea that an individual maximises its
inclusive fitness, not just by maximising its own reproduction, but the reproduction
of its genes even if they happen to be in other individuals. So by helping a relative
reproduce, this still increases inclusive fitness. This theory was developed by the
evolutionary biologist William Hamilton in the 1960s, and has since been termed ‘kin
selection’. A classic example of this can be found in insects. Many social insects such
as bees and ants, have sterile worker castes that completely forgo their own reproduction
in favour of that of the queen. How is this altruism inherited if the altruists never
reproduce? The behaviour can be inherited if the benefits accrue to individuals which
share the genes for altruism. This is the case in insects, but how does this manifest
in bacterial populations? Selection for cooperative traits in microbes can be maximized when relatedness
is kept high but how can this be achieved? One way that kin selection can work is via
limited dispersal. Here relatives are kept close together, increasing the probability
of interactions occurring amongst relatives, which favours indiscriminate altruism towards
neighbours. This does not require complex recognition systems, and therefore is likely
to be important in microbes. Biofilms and cooperation
Many of the experimental social evolution studies so far, have been performed in well
mixed planktonic cultures, where there is ample opportunity for cheats to freely disperse
and indiscriminantly exploit public goods production by cooperators. One key way for
microbes to limited dispersal, is to grow in a biofilm which is surrounded by an exopolysaccarhide
matrix. Such a spatially structured environment has the potential to keep cooperating genotypes
together and limit the invasion and spread of cheating genotypes. A possible outcome
of this is the general maintenance of social traits within the biofilm. Though it might
seem obvious that the formation of a biofilm involves cooperation between cells, the processes
involved need not always be cooperative. Inspired by spectacular modern microscopic observations
of biofilms, such as the mushroom-like structures of Pseudomonas aeruginosa, researchers have
modeled in silico, the growth and spatial patterns of cells growing on a surface with
interesting results. Using these computer simulations, it is possible to observe the
types of vertical structures typical of in vitro biofilms using only basic growth limitation
criteria in the environment and simple growth parameters of the organism. Secondly, in competitive
growth simulations between a wild type bacterium and a mutant that does not produce a ‘scaffolding’
polymer, a polymer mutant can be outgrown and covered by the cooperative wild type.
Where oxygen gradients are present, an overproducer of the scaffold polymer pushes its cell lineage
vertically into favourable oxygen conditions. In this in silico model of growth on a surface,
mixing genotypes does not select for cheating due to the local benefit of polymer secretion.
However if you introduce a new parameter to the model, the possibility that one genotype
can mutate into the other, the result is different. The cheating mutant now gains an advantage
if it occurs in an oxygen rich region where it can quickly produce lots of cells. The
key point here is that both the biological environment, and the social environment, determine
where and how we expect to observe biofilm formation, and why biofilms are maintained.
We are only just beginning to study social behaviours in biofilms, and it is now crucial
that we perform experimental tests to confirm the predictions that are observed during computer
simulations. This will help to inform us why biofilms form, and which traits are social
and non-social in biofilms. This is important because it will allow us to test whether targeting
specific traits, will result in us being able to better control biofilms, which are becoming
increasingly problematic in clinical and industrial settings.
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