Food for Thought: Cheese as a Model Microbial Ecosystem

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00:00:07.00 My name is Rachel Dutton and
00:00:09.01 I am a Bauer fellow at the Harvard University
00:00:12.06 Center for Systems Biology and
00:00:14.23 I am going to be talking today about
00:00:16.17 work in my lab using cheese as a model
00:00:19.28 system for studying microbial communities.
00:00:26.09 I'd like to start with a question: why should we
00:00:29.15 even study microbial communities?
00:00:31.29 Fact is that most microbes in nature
00:00:35.02 exist as part of communities. However we
00:00:38.19 know incredibly little about what is actually
00:00:40.22 happening within these communities of microbes.
00:00:44.07 So often as a microbiologist, what we'll
00:00:46.07 study is an organism in isolation in the lab.
00:00:50.13 For example E.coli, growing as a
00:00:53.01 population of cells, individually.
00:00:57.00 However in the real world what we have are
00:01:01.03 these communities of different species living together.
00:01:04.12 And so that is not to say that one of
00:01:06.16 these is necessarily a better
00:01:07.28 way to study microbes;
00:01:09.02 just that we can get at different
00:01:10.21 types of question about biology
00:01:12.25 under these two different
00:01:14.11 types of systems.
00:01:17.16 In the lab, by studying E.coli
00:01:19.18 over many decades we have a
00:01:22.08 really fundamental understanding
00:01:23.28 of how cells work, how they
00:01:25.26 respond to the environment,
00:01:26.24 how they use nutrients, how they grow.
00:01:29.01 However if we are able to
00:01:30.21 study microbes within
00:01:31.22 the context of community,
00:01:33.14 we might be able to get some
00:01:34.22 questions that will confer very
00:01:37.16 interesting biology such as how often
00:01:40.17 do species interact with each other,
00:01:42.24 what are the mechanisms they
00:01:43.28 use to do so and are there any
00:01:45.13 general principles or mechanisms
00:01:47.27 of community formation.
00:01:50.04 These microbial communities
00:01:54.03 are pretty much everywhere on the planet.
00:01:56.13 Whether we are thinking about the soil,
00:01:58.15 in which you have billions of
00:02:00.22 organisms in every gram or
00:02:03.03 the human body, so
00:02:03.29 for example in the gut we have
00:02:06.12 again billions of organisms
00:02:09.18 in every single one of us.
00:02:13.15 Now the challenge with
00:02:14.22 understanding how these
00:02:16.09 communities work is that these
00:02:18.17 communities are often incredibly complex.
00:02:20.20 So in the two systems for example
00:02:23.02 we have hundreds or thousands
00:02:25.07 of different species all living together.
00:02:27.25 If we want to be able to understand
00:02:30.24 how these communities work,
00:02:32.08 we might be able to take an approach
00:02:34.02 similar to be using E.coli as a model
00:02:36.03 organism where use model
00:02:38.14 communities or model ecosystems.
00:02:40.14 So, can we actually come up with
00:02:41.29 model ecosystems that will help us
00:02:43.17 understand how these complex
00:02:46.09 multi-species communities work?
00:02:49.15 What we ideally like to have is an
00:02:53.10 experimentally tractable ecosystem
00:02:55.07 that we can use to really link the
00:02:57.08 ecology of the system, what is
00:02:58.25 happening out in the natural
00:03:00.11 environment, to mechanisms of how things work.
00:03:03.20 So what we would like to be able to do
00:03:05.18 is have a microbial ecosystem where we can
00:03:08.14 study the microbial ecology in the
00:03:11.23 native setting and this will allow us to
00:03:13.19 generate hypotheses about how this
00:03:15.23 community functions and what it does.
00:03:18.09 Then what we would like to be able
00:03:20.08 to do is bring the system into a lab and
00:03:22.14 be able to deconstruct it through isolation
00:03:26.06 of the organisms that are present in
00:03:27.19 the community and then ideally reconstruct
00:03:30.09 it under conditions that resemble those
00:03:32.19 found in the environment so that we can start
00:03:34.02 to test hypotheses of how these
00:03:36.26 microbes form communities and
00:03:38.03 eventually get to a mechanistic
00:03:39.21 understanding of how the system works.
00:03:44.05 What kind of communities might we
00:03:46.20 look towards for finding these sort of
00:03:48.29 experimentally tractable systems?
00:03:53.00 We'd like in an ecosystem that is
00:03:55.23 relatively simple, so instead of
00:03:57.22 hundreds or thousands of species,
00:03:59.19 maybe on the order of tens of
00:04:00.24 species that we would work with.
00:04:04.03 We would like for this community
00:04:05.17 to be very reproducible.
00:04:08.00 It would be great if it were easy
00:04:09.11 to get a hold of samples, easy to access the
00:04:11.11 community it self and ideally
00:04:13.03 something we can manipulate the
00:04:14.19 community at many different levels
00:04:16.06 whether we’re thinking of the
00:04:17.16 environment in which the community is growing,
00:04:19.26 the substrates on which it’s growing,
00:04:21.25 or the individual organisms.
00:04:25.23 Now in my lab we are using fermented
00:04:28.05 foods as our model ecosystems
00:04:31.09 and fermented foods are actually one of
00:04:33.01 the most ancient forms of
00:04:34.27 biotechnology where humans have
00:04:36.02 intentionally manipulated an environment so
00:04:37.29 that we can control the growth of
00:04:39.13 certain types of microbes.
00:04:41.06 Many of these fermented foods actually
00:04:43.08 have these wonderful reproducible microbial
00:04:46.02 communities forming during
00:04:47.02 the process of fermentation.
00:04:49.01 So we will spend the rest of the time today
00:04:50.27 talking about cheese but there's
00:04:52.07 many other examples. We have
00:04:54.11 fermented beers, dry salamis and
00:04:58.19 sausages, fermented vegetables such
00:05:02.03 as kimchi, which is fermented
00:05:04.09 cabbage. Chocolate and coffee are
00:05:07.14 both great examples of fermented foods.
00:05:11.03 Things like pickles, natto, which is a
00:05:14.16 really interesting Japanese fermentation,
00:05:16.16 and things like soy sauce.
00:05:18.01 Pretty much every culture on the
00:05:20.24 planet has come up with many
00:05:22.29 different examples of fermented
00:05:24.01 foods and all these fermentations
00:05:25.26 involve the metabolism of different
00:05:29.02 foods by microbial communities.
00:05:33.03 In the case of cheese, there are two
00:05:36.05 really important steps in cheese
00:05:37.17 making in which the microbial
00:05:39.13 communities are important. We have
00:05:43.29 microbes actually responsible
00:05:45.09 for the complete transformation
00:05:47.12 of milk into cheese
00:05:49.06 through a couple different steps.
00:05:50.17 We start with milk
00:05:52.29 which will come from some dairy
00:05:55.26 animal, whether it is a cow or goat or
00:05:58.11 sheep, and this milk, from the
00:06:00.19 perspective of the microbe,
00:06:01.25 really is just a great of food.
00:06:05.06 We drink milk because it is
00:06:06.19 nutritious but microbes also think
00:06:08.28 it is very nutritious so
00:06:09.29 milk is a great source of
00:06:11.21 protein in form of caseins,
00:06:13.08 sugar in the form of lactose and
00:06:17.29 fat in the form of different kinds triglycerides.
00:06:21.16 The way that this simple,
00:06:25.11 very common food source is
00:06:29.17 transformed into cheese is first
00:06:30.29 through the action of lactic acid
00:06:32.26 bacteria and the enzyme rennet.
00:06:34.12 Lactic acid bacteria are can
00:06:37.24 be commonly found in
00:06:39.07 many different environments
00:06:40.27 and they're also found in milk,
00:06:45.00 or they can be added to
00:06:45.23 the milk to make cheese.
00:06:49.23 These lactic acid bacteria,
00:06:51.27 they are also known as
00:06:52.20 starter cultures, are really
00:06:54.05 what help turn the milk into
00:06:55.22 the curds, which is the first
00:06:57.01 stage of cheese making.
00:06:59.04 They do this through the
00:06:59.17 fermentation of the
00:07:00.21 milk sugar, lactose.
00:07:03.16 If we have lactose,
00:07:05.04 these bacteria have the
00:07:06.12 enzyme which is able to
00:07:08.24 break down lactose, which
00:07:10.14 is a disaccharide, into the simple sugars
00:07:12.22 and then take these simple
00:07:15.05 sugars and ferment
00:07:16.01 them for energy and this
00:07:18.00 results in the production of lactic acid.
00:07:20.14 Lactic acid serves many
00:07:22.29 different purposes. In
00:07:24.29 cheese making as well in
00:07:25.19 many different fermented foods,
00:07:27.28 some of these purposes
00:07:29.14 are the flavor, so it
00:07:31.03 gives the sort of
00:07:31.18 tartness to the food.
00:07:35.15 It helps in preservation - so the
00:07:36.29 acidity inhibits the growth
00:07:38.13 of many pathogens
00:07:39.04 that might otherwise be
00:07:40.15 a problem in food spoilage.
00:07:42.22 And it helps the protein,
00:07:45.00 or the caseins, in the milk
00:07:46.08 start to come together
00:07:47.24 into aggregates which
00:07:48.19 are called curds.
00:07:49.02 Now if you were to just use
00:07:52.14 lactic acid bacteria
00:07:53.29 during the production
00:07:55.17 or for the fermentation of milk, what
00:07:57.10 you would end up with is yogurt.
00:07:58.08 Yogurt is a very simple
00:08:00.11 fermented product which
00:08:02.19 just uses the action of
00:08:03.19 these lactic acid bacteria
00:08:05.12 to coagulate the milk into this gel
00:08:08.04 of yogurt.
00:08:08.23 With cheese making, the enzyme
00:08:10.13 rennet helps stimulate the
00:08:12.05 further coagulation of milk
00:08:14.02 proteins into curds so
00:08:16.02 that you can separate the
00:08:17.13 whey from the curd and that
00:08:19.03 curd is what becomes the
00:08:20.10 starting point for many
00:08:21.19 different kinds of cheese.
00:08:23.16 The second stage,
00:08:25.19 which I think is the most
00:08:27.01 interesting part of
00:08:27.26 cheese making, is the
00:08:29.19 secondary stage, which is
00:08:32.01 aging of the cheese.
00:08:33.21 Initially you have lactic
00:08:34.23 acid bacteria growing,
00:08:35.23 you have the fresh
00:08:36.11 cheese formed which
00:08:37.28 basically just tastes a little bit like sour
00:08:40.20 milk; something very fresh and tart.
00:08:42.19 You can take this cheese now and age it
00:08:46.11 and depending on how you age it
00:08:48.28 you get many different kinds
00:08:50.27 of aged cheeses which
00:08:52.29 have different aromas, flavors,
00:08:54.28 textures, appearances and the key
00:08:58.27 factor on determining
00:09:00.12 what kind of aged cheese
00:09:01.26 you end up with are
00:09:03.02 the microbes that
00:09:04.03 are colonizing surface of the cheese.
00:09:06.07 We have different bacteria
00:09:08.02 and fungi, many of
00:09:09.06 which are coming in
00:09:09.26 from the environment.
00:09:10.26 They are not inoculated,
00:09:12.19 yet they form these
00:09:14.00 reproducible communities
00:09:15.16 on the surface of the cheese.
00:09:18.11 So this rind forms
00:09:22.14 during the aging process
00:09:23.25 and this rind is actually a
00:09:25.26 surface associated microbial community.
00:09:28.10 So if you look at this picture
00:09:30.24 here: this is a close up of a
00:09:33.04 cross section of a slice of cheese
00:09:35.00 and this top layer is the
00:09:37.10 rind, or this biofilm,
00:09:39.29 that is formed during the aging
00:09:41.06 process. And the first time I
00:09:44.01 saw a cheese up close like this
00:09:46.19 it reminded me of when I
00:09:49.02 was a student in the microbial diversity
00:09:51.16 course at Woods Hole, at the MBL and we
00:09:55.00 had spent a lot of time out
00:09:56.29 in the salt marshes looking
00:09:57.29 at microbial mats and it reminded me
00:10:02.03 exactly of a microbial mat.
00:10:03.24 You have this beautiful
00:10:06.12 community that is
00:10:08.28 forming on a surface.
00:10:11.00 And so I say this to make the point that
00:10:13.28 the communities we are studying
00:10:15.17 on the rind of cheese are not really
00:10:18.01 unique to cheese. They are
00:10:20.02 an example of a type of community
00:10:22.07 that you find in many different
00:10:24.04 environments. In the case of microbial mats,
00:10:26.03 we have fossil evidence suggesting that
00:10:28.04 this type of microbial community
00:10:29.20 can date back at least
00:10:30.29 3.2 billion years.
00:10:36.14 These rind communities
00:10:37.24 can take many different
00:10:38.21 forms. Here we have pictures of
00:10:41.09 many different kinds of aged cheeses.
00:10:44.02 There are hundreds if not
00:10:45.17 thousands of varieties of cheese
00:10:47.18 and we wanted to get an idea of
00:10:52.09 what type of diversity there
00:10:53.28 is within these communities.
00:10:55.24 When I started this project, we would
00:10:59.17 just do simple things like,
00:11:01.00 culture from the surface
00:11:03.24 of the cheese just to get an
00:11:05.01 idea of what types of microbes
00:11:06.20 we might find in this environment.
00:11:08.26 These are just some pictures that I took from
00:11:12.00 cultures that we grew in the
00:11:13.28 lab just on standard media
00:11:15.18 on petri dishes and these
00:11:17.10 are just close up shots
00:11:18.22 of some of the gorgeous
00:11:20.21 organisms that we have growing
00:11:22.06 together in these communities.
00:11:23.18 In this particular one,
00:11:24.27 we have filamentous fungi, or molds,
00:11:27.15 growing with what appeared to
00:11:30.05 be bacterial cells, bacterial colonies.
00:11:32.25 Here's another where
00:11:34.21 we have a mixture of
00:11:36.16 different types of microbes
00:11:37.28 growing together. These are
00:11:39.29 all isolated from different types
00:11:41.12 of cheeses.
00:11:43.21 Another here where we have another mold
00:11:46.07 growing with other bacteria.
00:11:49.02 And again, just a really
00:11:52.24 wonderful microbial communities that
00:11:55.01 we have isolated from these cheeses.
00:11:58.15 Now this is looking
00:11:59.29 at colonies we have isolate from the
00:12:01.29 surface of a cheese but
00:12:03.04 what happens if we look
00:12:04.07 directly at these communities.
00:12:06.10 What does that look like?
00:12:07.21 We have done some
00:12:08.25 scanning electron microscopy
00:12:10.10 to visualize the communities
00:12:13.05 directly in situ and
00:12:15.25 this is looking top down
00:12:17.19 at the surface of a cheese.
00:12:20.05 This is the rind of the cheese
00:12:21.10 and conveniently a little chunk
00:12:23.29 has sort of been removed from the
00:12:26.13 top of this cheese so
00:12:27.20 we can start to see the
00:12:29.02 inside of this community
00:12:32.05 and if we go down deeper into the rind,
00:12:35.06 if you sort of imagine that you shrink
00:12:38.10 yourself down to the size of the bacterium,
00:12:41.17 and you are standing inside the rind of a cheese
00:12:43.27 and you look around,
00:12:45.12 this is what you would see.
00:12:46.28 So we see this incredible
00:12:49.29 collection of different microbial cells.
00:12:53.08 We have small cells of
00:12:55.10 different shapes which
00:12:56.23 look like they are bacterial
00:12:58.10 cells, different types of bacteria.
00:13:00.20 We have fungal cells.
00:13:02.01 So these look like they
00:13:03.23 could be spores from fungi and this
00:13:06.28 is an incredibly densely packed
00:13:08.18 environment so we estimate that
00:13:12.09 we have about 10 billion
00:13:13.21 cells for every gram of cheese
00:13:16.03 rind that you would eat.
00:13:18.19 What we would like to do is
00:13:21.02 use this wonderful fermented food
00:13:24.11 to try and dissect the
00:13:25.10 formation of microbial communities.
00:13:26.20 Could we actually use cheese
00:13:29.05 as a model ecosystem;
00:13:31.12 something where we can study the diversity
00:13:35.09 ecology of the system in its natural state.
00:13:37.11 We could potentially dissect it in the lab
00:13:40.16 and then recreate conditions
00:13:41.24 so we can start forming the
00:13:43.26 communities and understanding how they work.
00:13:48.14 And so the first step we had to
00:13:50.08 do is actually characterize
00:13:51.27 what types of microbes are present.
00:13:53.10 Despite the fact that cheese
00:13:55.16 has been made for thousands
00:13:57.14 of years, we don't really
00:13:59.03 have a very complete understanding of
00:14:02.02 what types of microbes are present on cheese,
00:14:04.12 as well as on many of these
00:14:05.06 other fermented foods. So
00:14:08.00 we took a approach to
00:14:09.26 look at the organisms
00:14:11.17 using DNA sequencing technologies.
00:14:16.02 And I though I would go through,
00:14:17.20 very quickly, how we actually
00:14:20.19 approach this question when we
00:14:22.23 have an environmental sample.
00:14:24.13 How do we actually know which
00:14:26.01 species are present in this environment
00:14:27.27 when we can't necessary
00:14:29.10 distinguish all the organisms by eye?
00:14:33.10 So the first thing we do is go out
00:14:34.29 to the environment and collect samples.
00:14:36.26 So in our case, we are collecting samples
00:14:38.18 from cheese. We collect
00:14:40.05 the surface of cheese,
00:14:41.17 or the rind, and then we
00:14:43.19 bring it back to the lab.
00:14:45.13 Once we get the sample back to the lab
00:14:48.14 we remove the DNA from
00:14:51.24 the rest of the sample,
00:14:52.12 and that is what we're
00:14:53.09 going after, is the DNA, so the
00:14:54.25 genetic information, from each of these cells.
00:14:57.06 Every single microbial cell has its genome.
00:15:00.06 We extract the those genomes from the sample.
00:15:04.17 Now with this mixture of genomes
00:15:06.14 what we can do is use a method called PCR
00:15:10.26 to just target regions that
00:15:14.02 are somewhat like a fingerprint
00:15:15.24 for a microbe. Every different microbe
00:15:17.25 has a different sequence.
00:15:19.25 Based on what species it is
00:15:22.12 and by looking at this region, we can
00:15:24.15 identify what type of species are present.
00:15:27.28 Once we have amplified these samples using PCR
00:15:30.26 what we can do is sequence
00:15:34.00 each of these regions from
00:15:35.26 the different species.
00:15:37.13 We can use this next generation sequencing
00:15:41.22 to actually read out all
00:15:44.00 the sequences that present
00:15:45.11 in any sample that we have.
00:15:48.11 And then to be able to determine
00:15:49.17 what species are actually present,
00:15:51.21 we then compare the sequences,
00:15:53.26 or these fingerprints, to databases.
00:15:56.19 We can use several different
00:15:59.05 types of databases which
00:16:00.13 have collections of microbial
00:16:02.18 sequences that we use as references.
00:16:05.15 This gives us a good idea
00:16:07.11 of the amount of diversity and
00:16:10.23 the particular organisms that
00:16:12.13 we have in each of our samples.
00:16:14.11 Using this method, we
00:16:16.16 wanted to look as broadly as possible
00:16:18.26 to see what type of diversity is present in
00:16:21.16 cheeses around the world.
00:16:23.26 To sample the microbial diversity of cheese,
00:16:26.17 what we did was collect
00:16:28.22 samples from 10 different countries,
00:16:30.24 137 different types of cheese,
00:16:34.09 and 362 wheels of cheese.
00:16:38.14 We took each of these samples through the
00:16:42.16 protocol that I just told you about
00:16:44.15 to look at the types of bacteria and fungi
00:16:48.18 that are present in each of these communities.
00:16:51.26 This is a representation of
00:16:54.17 the data that we have from this study.
00:16:58.00 We have on the top a
00:17:00.21 set of columns - the different
00:17:03.27 abundances of bacteria in each of the samples
00:17:06.15 and on the bottom set of columns,
00:17:07.18 the different abundances of fungi.
00:17:10.09 In this graph, each of the
00:17:12.25 columns is a different type of cheese.
00:17:16.13 We took this data, we clustered them
00:17:20.09 based on the similarity of species within
00:17:23.14 each of the communities, and you can start to see
00:17:25.08 some of these similar
00:17:26.29 clusters of cheeses that
00:17:28.15 have related communities
00:17:29.25 on this phylogenetic tree.
00:17:32.22 Now, when we started
00:17:33.29 looking at what organisms
00:17:36.08 were actually present
00:17:37.12 in these cheeses, we had a few surprises.
00:17:41.06 Now if we start to zoom
00:17:42.02 in on the bacteria that we
00:17:44.00 found in these samples,
00:17:45.10 what we see are 14
00:17:48.00 dominant genera of bacteria.
00:17:50.00 These are all of the genera that we find
00:17:52.09 greater than 1% abundance
00:17:54.09 across our dataset,
00:17:56.21 and while some of
00:17:58.03 these organisms had been studied
00:17:59.21 in various fermented foods before,
00:18:01.24 such as Staphylococcus
00:18:03.01 and Brevibacterium, we had
00:18:05.23 a couple organisms that
00:18:07.01 were new to fermented foods,
00:18:08.27 had never been described
00:18:09.24 in cheese or any other
00:18:10.26 fermented food before
00:18:11.28 such as Nocardiopsis and Yaniella.
00:18:14.16 We don't really know what they
00:18:16.22 are contributing to the cheese environment
00:18:19.11 but they can be very
00:18:21.17 abundant in certain samples.
00:18:23.07 And the other surprising
00:18:24.20 thing about the bacterial samples
00:18:26.14 is that we actually have a lot of bacteria
00:18:28.09 that you would normally associate with
00:18:29.28 the marine environment.
00:18:31.14 So we have many sequences that
00:18:35.08 belong to genera Halomonas, Psychobacter,
00:18:39.18 Pseudoalteromonas, and Vibrio
00:18:41.27 which are very often associated
00:18:43.29 with marine environments and so
00:18:45.28 we are very interested in
00:18:46.22 understanding where these microbes are
00:18:48.08 coming from and what they might be
00:18:49.13 doing in this particular community.
00:18:52.06 If we look at the fungal
00:18:54.27 portion of the diversity,
00:18:57.10 we see a slightly smaller set of organisms:
00:19:03.10 ten dominant genera that we find
00:19:05.06 over and over again in different cheeses.
00:19:08.18 Again, some of these have been studied before:
00:19:11.19 Debaryomyces and Galactomyces for example but then
00:19:14.19 we have this wonderful collection of
00:19:16.07 other fungi which we know very little about.
00:19:18.22 For example, Scopulariopsis,
00:19:20.25 which you can see in brown,
00:19:22.19 is very abundant in many of
00:19:26.12 the samples and we know
00:19:28.14 virtually nothing about this organism,
00:19:30.20 yet we think it has some really
00:19:33.04 interesting roles in terms interactions
00:19:34.27 which I'll show you in a moment.
00:19:39.08 This is looking at the
00:19:41.08 cheese at its sort of final stage,
00:19:43.06 right before it would be ready to eat.
00:19:44.28 These are the communities, after
00:19:46.13 they have already been established.
00:19:48.17 But one of the nice things about
00:19:49.29 working with fermented foods
00:19:51.18 is that you can sample the formation
00:19:54.07 of community as it's actually happening.
00:19:57.02 This is something that can be
00:19:58.03 really challenging in many
00:19:59.22 environments where it's not
00:20:01.12 clear where the beginning and end of
00:20:03.14 the community formation is.
00:20:06.11 So these communities we know are very dynamic.
00:20:09.21 This is a picture from aging
00:20:12.16 cheese in a cave in Vermont
00:20:14.08 and over a 2 months aging period,
00:20:17.00 you can see this very dramatic change of
00:20:21.13 the microbial community over time
00:20:23.15 just by eye. And so we wanted
00:20:25.11 to go in and use these sequencing
00:20:26.25 methods to actually tell us what was
00:20:29.08 happening within the formation of these communities
00:20:31.26 How did the communities get to the
00:20:33.18 point that we saw in the previous study.
00:20:38.04 So we ended up sampling 3 different batches of cheese.
00:20:43.13 We sampled the cheese every week
00:20:45.08 a they were aging and what
00:20:47.07 you can see is this absolutely
00:20:49.02 beautiful and reproducible succession
00:20:51.14 of species. So this is very consistent
00:20:57.04 change over time of species within these communities.
00:21:00.22 At early timepoints, you see
00:21:02.11 that the community is dominated in the
00:21:05.01 bacterial portion of the community
00:21:06.13 by the bacterium, Staphylococcus,
00:21:08.27 the green bacterium in this graph.
00:21:11.15 And then over time,
00:21:13.05 the community shifts to one,
00:21:14.21 in which is dominated by the bacterium, Brevibacterium.
00:21:18.02 In the fungal portion of the community,
00:21:20.14 we also see a secession where the community
00:21:23.01 early on is dominated by the yeast,
00:21:25.02 Candida, in light green and then that is
00:21:28.05 followed by the filamentous fungi, or
00:21:29.29 molds, Penicillium and then
00:21:31.29 eventually Scopulariopsis.
00:21:34.12 From this type of data, we think
00:21:36.05 that this is a nice way of generating hypotheses
00:21:39.15 about which organisms might be important
00:21:41.20 in the establishment of a community
00:21:44.08 and in directing what type of organisms
00:21:47.02 eventually end up in the specific communities.
00:21:49.23 So this generates a lot of questions for us
00:21:51.15 about, for example, whether
00:21:53.15 Staphylococcus growth is required
00:21:55.28 for the later growth of the species such as
00:21:58.05 Brevibacterium or for the fungi as well
00:22:01.03 and this is something we are
00:22:01.29 actively following up within the lab.
00:22:05.15 What we have done so
00:22:08.05 far is try to get a picture of the
00:22:10.28 microbial ecology of the system.
00:22:13.00 We've taken these molecular, microbial ecology
00:22:17.00 and sequencing based approaches
00:22:18.17 to get a good picture of the diversity
00:22:20.19 of the microbes in these communities.
00:22:24.05 So now we have an idea of what
00:22:25.20 these communities look like,
00:22:27.15 can we actually bring them into
00:22:28.20 the lab and start to dissect them.
00:22:30.07 So are we able to pull apart the
00:22:33.14 communities into their individual species components.
00:22:38.12 What I am showing you here
00:22:43.12 are from our sequencing, the most
00:22:46.07 abundant bacteria we find in the system-
00:22:49.06 the average relative abundance
00:22:52.04 of the different bacteria that
00:22:53.25 we see across the cheeses.
00:22:55.21 We went in and actively went
00:22:59.28 after each of these organisms and
00:23:01.16 tried to culture them in the lab
00:23:03.17 and it turns out that we are able to
00:23:05.09 culture representatives of every
00:23:07.25 single one of these bacterial groups.
00:23:10.27 So we have this wonderful culture
00:23:13.01 collection of different bacteria.
00:23:14.12 So we have different Actinobacteria,
00:23:17.04 different proteobacteria,
00:23:18.29 different Bacteroidetes and different Firmicutes.
00:23:23.05 For the fungi, we did the same thing
00:23:25.28 and again we are able to culture
00:23:28.24 representatives of every single
00:23:30.08 one of the major genera
00:23:31.14 that we found in our cheese.
00:23:33.19 We now have a mixture of phylogenetically
00:23:36.22 diverse molds and yeast
00:23:38.22 that makeup the fungal
00:23:41.16 portion of these communities.
00:23:43.14 What we have been able to
00:23:46.01 do up to this point is have
00:23:47.23 an understanding of the ecology
00:23:49.01 and we've been able to establish a culture
00:23:52.00 collection with all of the dominant organisms.
00:23:54.09 And this can be really challenging
00:23:56.01 part of studying microbial communities
00:23:58.09 because it is often very difficult
00:23:59.26 to be able to culture these organisms
00:24:02.03 in isolation from the rest of the community.
00:24:06.06 What do we do with this culture collection?
00:24:08.28 We wanted to know: can we actually start
00:24:10.18 to reconstruct communities in the lab
00:24:12.18 so that we can start ask questions
00:24:15.06 about what the roles of these different microbes are
00:24:18.26 in community formation.
00:24:23.11 What we've tried to do now is rebuild cheese.
00:24:27.03 And we do this by doing what
00:24:30.18 we refer to as in vitro cheese making.
00:24:33.03 In traditional cheese making,
00:24:37.00 a cheese maker will make a cheese
00:24:39.00 place it into a cave like environment,
00:24:40.27 this cheese can be churned
00:24:43.23 or washed or treated in different ways
00:24:47.20 to end up with a certain type of cheese
00:24:50.01 and so you end up with a diversity of
00:24:52.26 cheeses depending on how treat the cheese.
00:24:54.27 Now we can do this in the lab.
00:24:57.26 So we make cheese curd based medium,
00:25:01.11 we pour this into plates and we can actually
00:25:04.03 manipulate the species that
00:25:06.14 are going into our cheese
00:25:08.03 and the way we treat the
00:25:09.14 cheese in the laboratory.
00:25:11.14 We go from our collection of species
00:25:13.05 we reconstruct communities and
00:25:15.03 follow their behavior over time.
00:25:17.29 We wanted to try and
00:25:19.06 reconstruct community formation
00:25:20.25 so what we did was a very
00:25:22.10 simple experiment where we took
00:25:24.27 the dominant microbes that we found
00:25:27.02 in the natural succession and
00:25:29.04 we mixed them together in equal numbers,
00:25:32.01 so all the bacteria and fungi, at the same time.
00:25:36.15 We basically took them together in
00:25:39.01 equal numbers, put them onto our in vitro media
00:25:42.08 and asked what happens when
00:25:44.26 you mix these organisms together.
00:25:47.29 And what we saw was, remarkably,
00:25:50.14 that succession in vitro follows a very
00:25:53.21 similar course to what we see in situ.
00:25:56.21 So this is showing the changes in
00:26:00.16 the population sizes of different species
00:26:03.00 over time. Again we started with
00:26:07.12 approximately equal numbers of
00:26:09.04 the different bacteria and fungi
00:26:10.12 and mixed them together and
00:26:11.27 what you see is that you get
00:26:14.01 similar patterns succession.
00:26:15.24 So the bacteria, initially Straphylococcus,
00:26:18.13 dominates the community that's followed by
00:26:20.08 Brevibacterium and in the fungi,
00:26:22.28 initially the yeast, Candida,
00:26:25.07 dominates the community
00:26:26.02 and that’s then followed by filamentous
00:26:28.19 fungi, Pencillium and then Scopulariopsis.
00:26:31.04 What this tells us is that the succession
00:26:35.06 that we are seeing in these communities
00:26:37.12 is not in any way random.
00:26:41.05 It's not dependent on the order
00:26:43.04 of arrival of the different organisms.
00:26:45.14 There is something intrinsic
00:26:46.17 about the growth of these organisms
00:26:48.12 in this particular environment
00:26:49.15 that leads to this particular
00:26:52.13 type of community formation.
00:26:53.29 And so what we are doing in the lab now
00:26:56.01 is trying to know remove species and look at
00:26:59.03 if we remove, say Straphylococcus,
00:27:01.29 what happens to the rest of the community.
00:27:03.21 And that is something we can do by having this very
00:27:06.02 experimentally tractable system.
00:27:09.24 Now one of the other things we're
00:27:11.10 starting to look at in a lot more detail
00:27:14.11 are interactions between species.
00:27:16.23 We now from working with the
00:27:21.06 system that we have observed many
00:27:23.12 different interactions between
00:27:24.29 microbes isolated from cheese.
00:27:26.28 So we have examples of pretty
00:27:28.10 much every type of
00:27:29.24 interaction: positive and negative.
00:27:32.28 We have examples of interactions
00:27:35.03 between bacteria, between fungi and
00:27:38.15 between bacteria and fungi.
00:27:41.09 And so these are pictures of
00:27:42.26 some of the very dramatic looking interactions
00:27:46.23 where we have a stimulation of bacteria by fungi
00:27:50.26 for example or these dramatic
00:27:53.11 zones of inhibition that we see
00:27:56.13 upon growing fungi in the
00:27:58.01 presence of certain bacteria.
00:28:00.00 So we wanted to develop a way
00:28:02.07 to look at this in a more systematic
00:28:04.23 way and so what we've done is use
00:28:07.29 96 well plate cheese curd agar to
00:28:11.02 look at series of pairwise interactions.
00:28:14.07 What we've done so far is look
00:28:16.18 at interactions between bacterium
00:28:19.14 and fungi, which we know are both
00:28:22.02 important players in this system
00:28:23.16 and so we can take from our
00:28:25.01 collection of cultured organisms
00:28:27.09 and grow them in any
00:28:28.20 combination we want and
00:28:30.05 look at how they grow,
00:28:31.18 either by themselves or
00:28:33.02 in combination with another organism.
00:28:36.20 And so I'll show you some
00:28:37.13 data from some of these
00:28:39.24 types of these interactions which has revealed to us
00:28:43.24 that interactions between species
00:28:46.00 in the system are incredibly widespread.
00:28:47.26 So what you are seeing here on the top
00:28:50.22 panel is the growth of different bacteria,
00:28:55.02 some of which are
00:28:57.11 the bacteria we find in the system
00:28:58.29 and how their growth responds
00:29:03.06 in the presences of different fungi.
00:29:05.13 So in black bars we have the
00:29:08.19 growth of bacterium alone and in the colored bars
00:29:11.11 are their growth in the presence of different fungi.
00:29:14.11 So what you can see is that the
00:29:16.22 bacteria are hugely influenced
00:29:19.03 by the presence of fungi.
00:29:20.22 So they can either influenced
00:29:22.17 in a positive way, so their growth stimulated,
00:29:24.29 or in a negative way, so their growth is inhibited.
00:29:28.23 In contrast, the fungi which you
00:29:30.19 see on the bottom panel,
00:29:32.07 don't really seem to be impacted
00:29:36.00 by the presence of bacteria
00:29:37.22 with a few exceptions.
00:29:39.17 One very noticeable exception is
00:29:42.20 the growth of Scopulariopsis which
00:29:45.04 is inhibited very strongly by the presence
00:29:47.25 of one of the bacteria Arthrobacter.
00:29:50.02 This is one of the ways we are
00:29:52.23 starting to generate information
00:29:54.20 about the types of interactions that
00:29:57.05 we have in our system,
00:29:58.20 and that eventually what we would like to
00:30:00.03 know is what is the genetic basis
00:30:02.24 of these interactions and what's the
00:30:05.09 chemical basis of these interactions.
00:30:09.05 What I've told you so far is that we've
00:30:13.01 been able to go in, look at the microbial
00:30:15.15 ecology, dissect the system
00:30:17.16 and now have in vitro system
00:30:20.07 for reconstructing the community
00:30:22.05 in which we see communities that form
00:30:24.04 that resemble the natural system
00:30:26.13 and that we can now start to dissect
00:30:28.11 and understand the interactions
00:30:30.26 that are at the base of this community formation.
00:30:34.21 Beyond understanding these
00:30:37.20 particular microbial communities
00:30:39.22 we think that this work will have
00:30:41.22 broad impact in the field of microbiology.
00:30:45.17 For example, we think that having
00:30:47.22 this very experimentally
00:30:49.09 tractable microbial ecosystem
00:30:50.29 we can start to get at some
00:30:52.06 of the general principles
00:30:54.02 of microbial community formation
00:30:55.17 and we think in doing so, we'll have an impact
00:30:58.20 on advancing the conceptual, practical
00:31:01.12 and mechanistic understanding of communities
00:31:04.00 either in these simple systems
00:31:05.16 or hopefully more complex systems.
00:31:07.25 We think that these more
00:31:10.17 complex systems, which are often very
00:31:12.01 difficult to manipulate, we might
00:31:13.17 be able to gain some
00:31:14.09 insight, specifically into
00:31:15.29 the types of interactions or
00:31:17.29 mechanisms that are important
00:31:20.06 for community formation.
00:31:21.15 One of the potentially
00:31:24.03 interesting connections would be to
00:31:26.03 the human skin. We
00:31:27.03 see actually a lot of phylogenetic
00:31:28.18 overlap between the
00:31:30.00 species found on our skin
00:31:31.21 and the species on cheese.
00:31:34.12 We also think that because
00:31:36.20 they are widespread interactions,
00:31:39.10 especially between bacteria
00:31:40.20 and fungi in the system
00:31:42.08 we might be able to
00:31:43.08 do things like discover molecules
00:31:45.22 to manipulate the
00:31:46.18 growth of individual species
00:31:48.23 or manipulate the formation
00:31:50.00 of communities which could
00:31:51.06 be important for human health
00:31:53.00 or the environment or
00:31:54.13 even more applied systems.
00:31:56.20 So I would like to thank
00:31:58.05 a number of people for
00:31:59.14 helping with the data that I presented in this
00:32:03.29 seminar. I have a great lab
00:32:08.03 at Harvard. 2 wonderful postdocs,
00:32:11.02 Benjamin Wolfe and Julie Button
00:32:12.25 who've been involved in every aspect of this work.
00:32:15.16 I want to thank the Bauer Fellows
00:32:18.24 Program in the FAS Center
00:32:20.27 for System Biology at Harvard,
00:32:22.08 for supporting my lab
00:32:23.19 and funding from the NIGMS
00:32:26.06 Centers for Systems Biology.
00:32:28.15 I'd like to thank Marcela Santarelli
00:32:30.16 who is was visiting
00:32:31.18 graduate student who helped with
00:32:33.00 some of this work as well as
00:32:34.18 Jasper Hill Farms and Cellars
00:32:36.02 for collaboration and providing
00:32:38.18 us with many samples and
00:32:39.29 access to different cheeses.
00:32:41.03 Thank you.

This Talk

Speaker: Rachel Dutton

Audience:

General Public
Educators of H. School / Intro Undergrad
Student
Educators of Adv. Undergrad / Grad
Researcher
Educators

Recorded: July 2014

Talk Overview

Most microbes in nature exist within a microbial community. However, little is known about how different microbial species interact with each other and their environment to form these communities. Rachel Dutton uses cheese as a model system for studying microbial ecosystems. By studying microbial communities in different types of cheese, and observing how they change during the cheese aging process, Dutton has uncovered many of the complexities of how these different microbes interact with one another over time. By recapitulating these interactions in vitro, Dutton is starting to answer fundamental questions about microbial community formation and dynamics.

Speaker Bio

Rachel Dutton

Rachel Dutton is a Bauer Fellow at the Harvard University Center for Systems Biology, where she studies microbial communities using cheese as a model system. She has collaborated with numerous chefs, as well as the food science author Harold McGee, and her work has been featured in the New York Times, Boston Globe, NPR, and… Continue Reading