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Although the normal flora provides many health benefits, some of the microbes of the normal flora can cause serious infection and disease in the right circumstances. Most potential pathogens found in the normal flora are opportunistic pathogens.
Infections arising from a person’s own flora are considered endogenous. One way an endogenous infection can occur is for a bacterium which normally resides in one part of the body is introduced to another. An example is E. coli and other Enterobacteriaceae. Most Enterobacteriaceae can cause wound infections if they are introduced to broken skin, although this usually happens when someone is in a weakened state. Most urinary tract infections are caused by E. coli. E. coli can easily be introduced into the urethra when using the toilet or during intercourse (particularly for women). Once in the urethra, many strains of E. coli are able to adhere to the urinary tract with fimbriae and establish an infection. In rare cases, E. coli can even cause systemic infections such as meningitis or septicemia.
The viridans Streptococci normally found in the mouth can cause serious cardiovascular damage. If these bacteria are introduced into the bloodstream (usually by a dental procedure) they can settle and grow on damaged heart valves. These growths are called vegetations. The resulting infection is subacute bacterial endocarditis. In addition to flu-like symptoms (such as low-grade fever, fatigue, shortness of breath), characteristic symptoms of this disease are small, tender nodules on the fingers or toes, and tiny broken blood vessels on the whites of the eyes, the palate, inside the cheeks, on the chest, or on the fingers and toes. Once diagnosed, subacute bacterial endocarditis is usually easily treated.
Another way a microbe can cause endogenous infection is if the immune system is impaired or the normal flora is disrupted. Disruption of the normal flora, as mentioned above, can lead to infections with Candida or C. difficile.
Other examples of opportunistic pathogens of the normal flora which can cause endogenous infections include:
- Streptococcus pneumoniae
- Staphylococcus aureus
- Haemophilus influenzae
Pathogens from the normal flora can also infect other people. These are exogenous infections. Most opportunistic pathogens of the normal flora can also infect others. Many nosocomial (healthcare associated) infections can be acquired this way.
Occasionally, a person might carry a primary pathogen in their flora asymptomatically. Some pathogens such as Streptococcus pyogenes and Neisseria meningitidis can only grow in a human host. On occasion, people can be carriers of these and other pathogens without any sign of disease.
Normal Respiratory Flora as a Cause of Community-Acquired Pneumonia
Background: Intensive studies have failed to identify an etiologic agent in >50% cases of community-acquired pneumonia (CAP). Bacterial pneumonia follows aspiration of recognized bacterial pathogens (RBPs) such as Streptococcus pneumoniae, Haemophilus influenzae, and Staphylococcus aureus after they have colonize the nasopharynx. We hypothesized that aspiration of normal respiratory flora (NRF) might also cause CAP.
Methods: We studied 120 patients hospitalized for CAP who provided a high-quality sputum specimen at, or soon after admission, using Gram stain, quantitative sputum culture, bacterial speciation by matrix-assisted laser desorption ionization time-of-flight, and viral polymerase chain reaction. Thresholds for diagnosis of bacterial infection were ≥10 5 colony-forming units (cfu)/mL sputum for RBPs and ≥10 6 cfu for NRF.
Results: Recognized bacterial pathogens were found in 68 of 120 (56.7%) patients 14 (20.1%) of these had a coinfecting respiratory virus. Normal respiratory flora were found in 31 (25.8%) patients 10 (32.2%) had a coinfecting respiratory virus. Infection by ≥2 RBPs occurred in 10 cases and by NRF together with RBPs in 13 cases. Among NRF, organisms identified as Streptococcus mitis, which share many genetic features of S pneumoniae, predominated. A respiratory virus alone was found in 16 of 120 (13.3%) patients. Overall, an etiologic diagnosis was established in 95.8% of cases.
Conclusions: Normal respiratory flora, with or without viral coinfection, appear to have caused one quarter of cases of CAP and may have played a contributory role in an additional 10.8% of cases caused by RBPs. An etiology for CAP was identified in >95% of patients who provided a high-quality sputum at, or soon after, the time of admission.
Keywords: community-acquired pneumonia etiology lower respiratory infection normal respiratory flora.
© The Author(s) 2020. Published by Oxford University Press on behalf of Infectious Diseases Society of America.
The skin surface microbiome and its role in skin diseases have received increasing attention over the past years. Beyond, there is evidence for a continuous exchange with the cutaneous immune system in healthy skin, where hair follicles (HFs) provide unique anatomical niches. Especially, scalp HFs form large tubular invaginations, which extend deeply into the skin and harbour a variety of microorganisms. The distinct immunology of HFs with enhanced immune cell trafficking in superficial compartments in juxtaposition to immune-privileged sites crucial for hair follicle cycling and regeneration makes this organ a highly susceptible structure. Depending on composition and penetration depth, microbiota may cause typical infections, but may also contribute to pro-inflammatory environment in chronic inflammatory scalp diseases. Involvement in hair cycle regulation and immune cell maturation has been postulated. Herein, we review recent insights in hair follicle microbiome, immunology and penetration research and discuss clinical implications for scalp health and disease.
13.3: Pathogens in the Normal Flora - Biology
Tag words: bacteriology, bacteria, microbiology, microbe, normal flora, indigenous bacteria, E. coli, Staphylococcus, Streptococcus, Enterococcus, Lactobacillus, Bifidobacterium, corynebacteria, clostridium, neisseria, bacteroides, Haemophilus, biofilm, dental plaque, dental caries, periodontal disease.
Beneficial Effects of the Normal Flora
The effects of the normal flora are inferred by microbiologists from experimental comparisons between "germ-free" animals (which are not colonized by any microbes) and conventional animals (which are colonized with a typical normal flora). Briefly, some of the characteristics of a germ-free animals that are thought to be due to lack of exposure to a normal flora are:
1. vitamin deficiencies, especially vitamin K and vitamin B12
2. increased susceptibility to infectious disease
3. poorly developed immune system, especially in the gastrointestinal tract
4. lack of "natural antibody" or natural immunity to bacterial infection
Because these conditions in germ-free mice and hamsters do not occur in conventional animals, or are alleviated by introduction of a bacterial flora (at the appropriate time of development), it is tempting to conclude that the human normal flora make similar contributions to human nutrition, health and development. The overall beneficial effects of microbes are summarized below.
1. The normal flora synthesize and excrete vitamins in excess of their own needs, which can be absorbed as nutrients by their host. For example, in humans, enteric bacteria secrete Vitamin K and Vitamin B12, and lactic acid bacteria produce certain B-vitamins. Germ-free animals may be deficient in Vitamin K to the extent that it is necessary to supplement their diets.
2. The normal flora prevent colonization by pathogens by competing for attachment sites or for essential nutrients. This is thought to be their most important beneficial effect, which has been demonstrated in the oral cavity, the intestine, the skin, and the vaginal epithelium. In some experiments, germ-free animals can be infected by 10 Salmonella bacteria, while the infectious dose for conventional animals is near 10 6 cells.
3. The normal flora may antagonize other bacteria through the production of substances which inhibit or kill nonindigenous species. The intestinal bacteria produce a variety of substances ranging from relatively nonspecific fatty acids and peroxides to highly specific bacteriocins, which inhibit or kill other bacteria.
4. The normal flora stimulate the development of certain tissues , i.e., the caecum and certain lymphatic tissues (Peyer's patches) in the GI tract. The caecum of germ-free animals is enlarged, thin-walled, and fluid-filled, compared to that organ in conventional animals. Also, based on the ability to undergo immunological stimulation, the intestinal lymphatic tissues of germ-free animals are poorly-developed compared to conventional animals.
5. The normal flora stimulate the production of natural antibodies . Since the normal flora behave as antigens in an animal, they induce an immunological response, in particular, an antibody-mediated immune (AMI) response. Low levels of antibodies produced against components of the normal flora are known to cross react with certain related pathogens, and thereby prevent infection or invasion. Antibodies produced against antigenic components of the normal flora are sometimes referred to as "natural" antibodies, and such antibodies are lacking in germ-free animals.
Harmful Effects of the Normal Flora
Harmful effects of the normal flora, some of which are observed in studies with germ-free animals, can be put in the following categories. All but the last two are fairly insignificant.
1. Bacterial synergism between a member of the normal flora and a potential pathogen. This means that one organism is helping another to grow or survive. There are examples of a member of the normal flora supplying a vitamin or some other growth factor that a pathogen needs in order to grow. This is called cross-feeding between microbes. Another example of synergism occurs during treatment of "staph-protected infections" when a penicillin-resistant staphylococcus that is a component of the normal flora shares its drug resistance with pathogens that are otherwise susceptible to the drug.
2. Competition for nutrients Bacteria in the gastrointestinal tract must absorb some of the host's nutrients for their own needs. However, in general, they transform them into other metabolisable compounds, but some nutrient(s) may be lost to the host. Germ-free animals are known to grow more rapidly and efficiently than conventional animals. One explanation for incorporating antibiotics into the food of swine, cows and poultry is that the animal grows faster and can therefore be marketed earlier. Unfortunately, this practice contributes to the development and spread of bacterial antibiotic resistance within the farm animals, as well as humans.
3. Induction of a low grade toxemia Minute amounts of bacterial toxins (e.g. endotoxin) may be found in the circulation. Of course, it is these small amounts of bacterial antigen that stimulate the formation of natural antibodies.
4. The normal flora may be agents of disease. Members of the normal flora may cause endogenous disease if they reach a site or tissue where they cannot be restricted or tolerated by the host defenses. Many of the normal flora are potential pathogens, and if they gain access to a compromised tissue from which they can invade, disease may result.
5. Transfer to susceptible hosts Some pathogens of humans that are members of the normal flora may also rely on their host for transfer to other individuals where they can produce disease. This includes the pathogens that colonize the upper respiratory tract such as Neisseria meningitidis, Streptococcus pneumoniae, Haemophilus influenzae and Staphylococcus aureus, and potential pathogens such as E. coli, Salmonella or Clostridium in the gastrointestinal tract.
Part 2: Community Behavior of an Extracellular Pathogen
00:00:08.20 My name is Ralph Isberg.
00:00:09.29 I'm a professor of Molecular Biology and Microbiology
00:00:12.12 at Tufts University School of Medicine in Boston,
00:00:15.20 and I'm an investigator of the
00:00:17.16 Howard Hughes Medical Institute.
00:00:19.18 And in this talk,
00:00:20.23 which is the second talk of two in this series,
00:00:23.05 I would like to discuss community behavior
00:00:24.28 of an extracellular pathogen in tissues.
00:00:27.02 In my first talk,
00:00:28.15 I gave a very simple model
00:00:29.14 for what differentiates a pathogen from a non-pathogen.
00:00:32.14 In this talk, what you'll see is that
00:00:35.12 the differences between a pathogen and a non-pathogen
00:00:37.21 are not so clear-cut,
00:00:39.16 and what you'll see is that a pathogen
00:00:41.02 can behave both like a non-pathogen,
00:00:43.01 as well as like a pathogen,
00:00:45.00 within host tissues.
00:00:46.25 And so, before I go into the details of this talk,
00:00:49.07 I just want to give you the take-home messages,
00:00:51.20 which I'll try to actually make you understand today.
00:00:57.17 And the first thing that I'd like to discuss is that
00:01:01.22 pathogen-specific proteins are expressed
00:01:03.15 by only a fraction of bacteria,
00:01:06.12 and the way you normally think of bacteria growing in culture is that
00:01:10.03 a microorganism gives rise
00:01:12.23 to two genetically identical microorganisms,
00:01:15.20 and furthermore, these microorganisms
00:01:17.29 then give rise to other organisms
00:01:20.04 which have the same gene expression profiles
00:01:22.26 as the initial parents.
00:01:25.05 This is called a homogenous population
00:01:27.06 of bacteria growing in culture.
00:01:29.22 And what I'd like to try to convince you of today
00:01:32.13 is that when bacteria grow within tissue sites
00:01:36.04 that this probably is not the case.
00:01:38.09 Instead, what happens
00:01:40.02 is that bacteria may initially grow within a tissue
00:01:45.09 and be homogenous.
00:01:47.13 They then give rise to, occasionally,
00:01:51.00 bacterial cells which have a different transcriptional
00:01:54.14 and translational profile than the parent.
00:01:57.10 And then. these then.
00:01:59.16 these organisms then go on to generate more of their kind,
00:02:02.01 as well as generate other organisms
00:02:04.17 which may have other different transcriptional profiles.
00:02:08.28 And therefore what I'll to convince you of is that
00:02:12.17 bacteria growing within tissues are transcriptionally heterogeneous.
00:02:18.22 The second thing that I'd like to convince you of is that
00:02:21.08 one of the reasons for this heterogeneity in gene expression
00:02:24.16 is that the microenvironment in which these organisms grow
00:02:27.08 controls the bacterial gene expression profile,
00:02:29.19 and that can be seen in this slide.
00:02:31.07 What I'm trying to describe here for you
00:02:34.01 are different microenvironments which the microorganism will encounter.
00:02:38.03 When the organism grows
00:02:40.25 and moves out of one microenvironment
00:02:44.24 it then encounters another microenvironment,
00:02:47.22 and then that causes switching of the transcriptional profile
00:02:50.18 so that it now assumes a transcriptional profile
00:02:53.26 which is appropriate for that particular microenvironment.
00:02:58.06 The bugs will continue to grow and expand
00:03:00.12 and then they'll encounter other microenvironments,
00:03:02.29 where they'll also, similarly,
00:03:05.16 respond to that particular microenvironment.
00:03:08.15 And then, there's one more thing that I'd like to point out.
00:03:11.22 and that is that there is community behavior.
00:03:14.29 So, what is community behavior?
00:03:16.26 And community behavior of bacteria
00:03:18.26 is such that the bacteria would change the microenvironment
00:03:21.16 in which other bacteria are able to grow,
00:03:24.14 and this change can be due to a number of different things.
00:03:28.18 One way in which this change can occur
00:03:30.23 is that the organisms could secrete molecules
00:03:33.19 which change the microenvironment,
00:03:36.13 and other bacteria are able to respond to those molecules.
00:03:39.16 But there's other ways in which this can occur,
00:03:41.20 in which the microorganism is actually able to change the environment
00:03:46.15 and deplete certain molecules which are within the microenvironment,
00:03:51.02 and then generate a whole new environment
00:03:53.05 in which the molecular aspects of the environment
00:03:55.10 are different than the original.
00:03:57.12 As a result, then, the new bacteria which grow in this new environment
00:04:00.12 have different transcriptional profiles,
00:04:02.19 which allow them to respond to this new microenvironment.
00:04:10.26 so, the story I'd like to tell you is about an organism,
00:04:12.22 Yersinia pseudotuberculosis.
00:04:15.03 It's called an enteric organism
00:04:16.17 because it causes disease
00:04:18.16 through ingestion of contaminated foodstuffs.
00:04:20.24 The organism is a Gram negative rod.
00:04:23.14 That is, it's an organism
00:04:25.00 which doesn't stain with Gram stain.
00:04:27.16 I've displayed this as red,
00:04:29.05 which is typically how microbiologists
00:04:31.22 display Gram negative rods.
00:04:34.10 And then. disease that's caused in humans
00:04:36.28 often results in growth in regional lymph nodes
00:04:40.22 in the intestine.
00:04:42.20 This is known as mesenteric adenitis.
00:04:46.03 In the lab, we model this disease in mice.
00:04:50.25 So with mice,
00:04:52.16 what happens is we allow them to orally ingest the organism,
00:04:55.10 or we will inject the organism intravenously,
00:04:59.23 and then, through either route,
00:05:02.10 the organism will enter into deep tissue sites
00:05:04.27 and grow within the spleen.
00:05:07.11 This particular disease then mimics what we call
00:05:10.13 invasive diseases,
00:05:12.04 in which organisms move from one tissue site to another.
00:05:14.26 In this case, the tissue site which the organism is moving
00:05:17.11 is from the intestine
00:05:19.10 into deeper tissue sites such as the spleen.
00:05:22.20 We've been interested in this process for a number of years,
00:05:26.00 and the way we look at this
00:05:28.05 is that the organism is first ingested into the intestine,
00:05:30.26 and what I'm showing here is a diagram
00:05:33.09 of what the small intestine looks like.
00:05:35.23 The small intestine has crypts,
00:05:38.11 which have their own specific crypt cells.
00:05:40.29 It has microvilli
00:05:43.07 which are associated with the cells.
00:05:45.05 Then, it has the villus itself,
00:05:48.09 which is up here at the top.
00:05:50.02 In addition, there are regional lymph nodes,
00:05:51.21 and the regional lymph nodes which we're most familiar with.
00:05:54.25 which we work with,
00:05:56.21 are regional lymph nodes called by the Peyer's patches,
00:05:58.20 as well as mesenteric lymph nodes,
00:06:00.16 and the mesenteric lymph node
00:06:02.08 is a small node which drains into the Peyer's patches.
00:06:05.29 So, both the intestinal epithelium,
00:06:07.27 the intestinal lumen,
00:06:09.14 and these regional lymph nodes
00:06:11.04 are sites which can be exposed to the organism,
00:06:13.19 if the organism is able to move
00:06:16.02 from the lumen of the intestine
00:06:18.15 into these tissue sites.
00:06:20.16 And it's been known for a number of years,
00:06:23.23 really since the 1950s,
00:06:25.20 that when the organism is ingested by a host
00:06:28.08 the organism has the ability to move into both of these tissue sites
00:06:32.03 that are associated with the intestine,
00:06:34.06 as well as deeper tissue sites such as the spleen.
00:06:37.16 Now, we originally become interested in this
00:06:39.14 a number of years ago,
00:06:41.12 when an MD fellow working in my lab, Penelope Barnes,
00:06:44.16 who is currently an infectious disease specialist
00:06:47.04 at University of Oregon,
00:06:49.17 was wondering whether, when bacteria enter into these regional lymph nodes,
00:06:52.28 whether they'll drain from the regional lymph nodes into deep tissue sites.
00:06:57.08 And she got a very surprising result.
00:06:59.21 And what she found is that
00:07:01.19 the bacteria which grow within these regional lymph nodes
00:07:03.28 are actually a different population of bacteria
00:07:06.21 than the ones which are able to grow
00:07:09.00 within deep tissue sites.
00:07:11.17 So, the way we look at the organism,
00:07:13.06 the initial aspects of the disease, are the following,
00:07:16.16 because of her studies.
00:07:18.05 The bacteria enter into.
00:07:20.05 are ingested by the host, in this case the mouse.
00:07:23.09 Then, the organism will then translocate across the epithelium.
00:07:29.17 It translocates through a very special cell called the M cell,
00:07:32.13 which are on the surface of Peyer's patches,
00:07:34.28 and then will enter into the Peyer's patch.
00:07:36.28 And we believe that once the organism
00:07:39.22 is found in the Peyer's patch,
00:07:41.20 the immune response then will keep the replication in check,
00:07:45.01 and even though you'll see very large boluses of growth
00:07:47.28 of the organism in this site,
00:07:49.20 the organism doesn't drain
00:07:51.20 further from the site into deep tissue sites.
00:07:53.24 It may drain from the Peyer's patches
00:07:55.23 into the mesenteric lymph node,
00:07:57.19 but there it's restricted
00:07:59.11 and the immune response is very effective
00:08:01.03 in keeping the organism from going any further
00:08:04.00 into deep tissues.
00:08:05.23 Instead, there's some kind of mysterious process that occurs,
00:08:08.06 and we still don't know what it is,
00:08:10.05 in which the organism is able to
00:08:12.24 move across the intestinal epithelium.
00:08:14.29 this can be seen over here.
00:08:16.27 and then is able to find its way into the bloodstream,
00:08:20.09 and then once in the bloodstream,
00:08:21.23 the organism makes its way
00:08:23.25 into deep tissue sites such as the liver and spleen.
00:08:25.24 So, we look at this disease as a couple different things
00:08:28.03 occurring simultaneously:
00:08:30.01 an infection that occurs in regional lymph nodes,
00:08:32.06 and an infection that occurs in deep tissue sites.
00:08:34.24 And there is actually little communication occurring
00:08:36.27 between these two regions of the host.
00:08:43.09 Now, in the deep tissue site.
00:08:45.19 this is a micrograph from my
00:08:47.22 close colleague Joan Mecsas,
00:08:49.17 who works at Tufts Medical School.
00:08:51.19 this is a section through the spleen.
00:08:53.27 On the top is a section
00:08:56.00 in which an animal has been euthanized.
00:08:58.14 The spleen has been frozen, and frozen sections are taken.
00:09:01.17 And then there is a histological stain
00:09:04.12 which allows you to detect bacteria,
00:09:07.10 and if you look in higher magnifications,
00:09:09.08 you can see these foci of replication,
00:09:12.01 and the dark dots are staining of
00:09:15.03 replicating Yersinia pseudotuberculosis.
00:09:17.09 And so we became very curious
00:09:18.28 about the nature of these black spots.
00:09:21.00 How do they on to cause disease?
00:09:23.00 And how do they spread throughout the spleen?
00:09:27.02 So, what does it mean to colonize a tissue?
00:09:29.15 Now, the original view that we had
00:09:31.16 from Penelope Barnes' work a number of years ago in my lab,
00:09:34.26 was that a few bacteria cells
00:09:36.27 were seeding the spleen.
00:09:39.14 So, typically she'd see between 1 and 4 cells
00:09:42.03 initially seeding the spleen,
00:09:44.01 and of course then the bacteria would go on
00:09:45.26 to kill the host through unabated replication of the organism
00:09:49.07 in this tissue site.
00:09:51.08 So, one way of looking at this
00:09:53.01 is that these few organisms go on
00:09:54.29 as if the spleen is simply a broth culture
00:09:59.05 and they continue to grow
00:10:01.14 as if the spleen is a broth culture,
00:10:03.08 and then eventually overwhelm the spleen.
00:10:09.03 One way of looking at this
00:10:10.26 is it's very similar to inoculation of a broth culture
00:10:13.27 in the lab.
00:10:15.25 So, this here is my colleague.
00:10:17.20 Here's taking a colony from a plate
00:10:19.13 and then inoculating it in a broth culture.
00:10:22.03 This is similar to inoculation
00:10:23.29 of the spleen that occurs after bacteria penetrate from the intestine
00:10:27.18 and go into the deep tissue sites.
00:10:30.13 Then, once the bacteria hit the spleen,
00:10:32.07 in this case we've mimicked this
00:10:33.24 by growing in broth culture,
00:10:35.22 the bacteria will grow,
00:10:38.02 since the immune response isn't able to limit replication of the organism,
00:10:41.13 it's a pathogen after all.
00:10:43.12 The organism is able to grow in culture
00:10:45.17 and then we see a uniform broth culture within tissue sites.
00:10:49.14 So that's one model,
00:10:51.02 and I have to confess,
00:10:52.27 this is the way I was thinking for a number of years.
00:10:55.19 However, there's another model
00:10:57.13 which maybe seems more obvious to you,
00:10:59.13 but wasn't obvious to me,
00:11:01.18 and that is that the bacteria
00:11:03.13 were initially seeding the spleen,
00:11:05.28 as between 1 and 4 cells,
00:11:08.10 and then each of these cells
00:11:10.16 were then giving rise to individual colonies.
00:11:13.12 So, the disease was caused by colonization
00:11:17.07 through a number of independent colonies forming in tissue sites.
00:11:21.23 This could be mimicked, also, in the laboratory.
00:11:26.13 So, here you see my colleague, then,
00:11:29.27 inoculating a petri dish.
00:11:32.07 Again, this is similar to what we might see
00:11:34.17 with seeding of the spleen.
00:11:36.16 Bacteria are initially ingested by the host.
00:11:40.13 Then the organism, then,
00:11:42.14 is diluted and then goes into the spleen,
00:11:44.04 and then individual cells seed the spleen.
00:11:46.20 In this case, it would be the petri dish.
00:11:48.28 Then, once the petri dish is allowed to incubate
00:11:51.05 for an appropriate amount of time,
00:11:54.19 you get individual colonies coming up on the petri dish.
00:11:57.18 So then, the question is,
00:11:59.18 are we getting a broth culture growing in the spleen,
00:12:02.13 or are the bacteria growing as an agar plate?
00:12:05.13 And so, this is a very simple experiment,
00:12:07.12 and the way we distinguish between these two models
00:12:09.12 is the following.
00:12:11.17 We take two bacterial strains
00:12:13.22 that are genetically identical
00:12:16.05 except they differ in a single gene.
00:12:18.03 One has a fluorescent protein called mCherry,
00:12:20.29 which glows red as you might imagine,
00:12:23.14 and the other one has a fluorescent protein
00:12:25.23 that glows green, called GFP.
00:12:28.26 We take these two bacterial cultures
00:12:31.23 and then we mix them all up
00:12:33.21 so we have a culture that's full of red and green bacteria.
00:12:37.14 Please excuse the use of red and green if you're colorblind
00:12:40.12 I'll try to talk this through for you.
00:12:43.02 And then we take this mixed culture
00:12:45.23 and then we inoculate it intravenously into an animal.
00:12:50.01 a few hundred or a few thousand bacteria into the animal.
00:12:53.15 And then we allow some bacteria to seed
00:12:55.18 the deep tissue site.
00:12:58.11 So in this, we've taken an i.v. inoculation,
00:13:00.16 and we use a mouse,
00:13:02.04 and then we euthanize the mouse,
00:13:03.03 and then we analyze the spleens
00:13:04.29 by taking frozen sections of the spleen
00:13:08.11 and then looking at these frozen sections
00:13:11.02 in the fluorescence microscope.
00:13:16.24 And you get, you know,
00:13:18.16 a very obvious result.
00:13:20.13 And that is, it's the victory for the agar plate model.
00:13:23.10 So, as you can see right here, if we have a green colony,
00:13:25.18 it's not mixed.
00:13:27.04 If we have a red colony, it's not mixed.
00:13:29.12 You might see some spread of the green cells
00:13:31.23 into other tissue sites,
00:13:33.19 but you don't see a mixture of red and green.
00:13:36.01 So therefore,
00:13:37.18 what happens when the bacteria are seeded
00:13:39.15 into the spleen,
00:13:40.28 it's as if they've been seeded onto an agar plate.
00:13:42.29 Individual bacteria
00:13:44.17 go on to form individual colonies,
00:13:47.10 and there doesn't appear to be any mixing
00:13:49.10 between the colonies.
00:13:50.23 Once a colony is established,
00:13:52.07 the bacteria do seem to be able to migrate
00:13:54.07 from that colony to other sites,
00:13:56.00 and establish other colonies within the tissue.
00:13:58.28 Alright, now.
00:14:03.04 when you look at this, you see there's a problem.
00:14:05.16 As I mentioned in the first talk,
00:14:07.16 we distinguish pathogens from non-pathogens
00:14:10.06 by the virulence proteins which pathogen make.
00:14:13.25 And what determines whether a pathogen
00:14:15.21 will make a virulence protein
00:14:17.02 is whether its actually interacting directly with host tissues.
00:14:20.24 But what you can see here is, when a colony forms,
00:14:23.08 not all the bacteria are interacting with host cells.
00:14:26.06 We have bacteria internal to these small colonies,
00:14:28.20 and all they're seeing is other bacteria in the colony,
00:14:31.26 whereas we have other bacteria
00:14:33.18 where they're at the peripheries of this colony,
00:14:35.14 and they're clearly interacting with host cells.
00:14:38.02 And the host cells that we see that surround these bacteria,
00:14:40.19 and this will be demonstrated later in this talk,
00:14:43.08 these host cells are neutrophils,
00:14:45.23 phagocytic cells which are trying to destroy the microorganism,
00:14:49.13 and the neutrophils are displayed here in blue.
00:14:53.08 They're displayed here in blue
00:14:56.05 because we've stained their nuclei with a DNA stain.
00:14:58.16 Alright, so now the question is,
00:15:00.08 what it is about these bacteria
00:15:02.03 in these different environments?
00:15:03.16 Do they behave differently?
00:15:07.09 So when we look at this,
00:15:08.28 there's clearly something going on.
00:15:10.20 The first thing that you notice in this particular tissue site
00:15:13.17 is that we've recruited neutrophils to this site,
00:15:16.03 and the bacteria are still alive.
00:15:18.11 And also, what you see is that
00:15:20.13 the bacteria are encountering the phagocytic cell,
00:15:23.06 and there are a subset of bacteria
00:15:25.07 which are interacting with the phagocytic cell,
00:15:27.05 but the bacteria are not being phagocytized
00:15:29.04 they're simply bound to the surface.
00:15:31.01 The second thing you notice is that
00:15:32.25 there are bacteria within this colony,
00:15:34.28 which are not interacting with the phagocytic cells at all.
00:15:37.11 So the question is, why are you.
00:15:39.10 why do you have one set of bacteria
00:15:41.06 directly interacting with host cells,
00:15:42.28 and the other one that seems to be naive to these cells.
00:15:47.12 So, clearly this pathogen
00:15:49.22 is doing something to the phagocyte.
00:15:51.11 It's preventing phagocytosis.
00:15:53.25 The way it does that
00:15:56.19 is it has a Type III secretion system.
00:15:59.03 A Type III secretion system
00:16:00.21 is one of the specialized secretion systems
00:16:02.21 which I described in the previous talk,
00:16:04.24 and the Type III secretion system
00:16:06.24 allows movement of a protein into the host cell,
00:16:10.17 which interferes with phagocytosis.
00:16:13.05 And the way that these proteins
00:16:14.22 are able to move from the bacterium
00:16:16.26 into the host cell
00:16:18.16 is through this needle-like structure
00:16:20.02 which is on the surface of the bacterium,
00:16:22.02 in which bacterial proteins
00:16:24.29 which interfere with phagocytosis of the host cell
00:16:27.10 move through this structure,
00:16:29.12 across the plasma membrane of the host cell,
00:16:31.06 and then are able to get a cytoplasmic target.
00:16:34.08 target a cytoplasmic protein
00:16:36.29 within the host phagocyte.
00:16:39.04 This is.
00:16:41.15 the structure of these particular secretion complexes
00:16:45.17 was initially described in Jorge Galán's lab,
00:16:50.09 and there's some beautiful structures
00:16:52.10 that have been now demonstrated
00:16:55.09 in the lab of Marlovits and coworkers,
00:16:57.13 and this is an EM structure of such a complex.
00:17:01.02 As you can see, there's a base
00:17:03.22 which is through the envelope of the bacterial cell
00:17:06.08 and then there's this needle
00:17:08.02 which sticks out from the surface of the bacterial cell
00:17:10.08 into the host cell.
00:17:14.29 Alright, so now the secreted protein
00:17:16.24 goes through the Type III translocation apparatus,
00:17:20.02 and what's probably the most important protein
00:17:21.29 for this process
00:17:23.22 is the protein YopE,
00:17:25.17 which is one of these proteins
00:17:27.01 that targets small GTPases in the host cell
00:17:28.24 and inactivates Rho family members
00:17:30.17 to prevent phagocytosis.
00:17:32.11 So, what you see here
00:17:33.25 is YopE is being secreted by the bacterium.
00:17:36.19 It's now interfering with phagocytosis
00:17:38.17 by the neutrophils that are surrounding the [bacterial] cell,
00:17:42.02 and then you see this frustrated phagocytosis event.
00:17:45.06 On the other hand, the bacteria which are within the colony
00:17:48.13 do not have to deal directly with the phagocyte,
00:17:50.26 therefore they may not need
00:17:53.16 the transcriptional program
00:17:55.23 which makes these proteins
00:17:57.23 which have to inactivate the neutrophil.
00:18:02.04 So what we wanted to ask then is,
00:18:05.07 is there spatial regulation?
00:18:07.09 So, do the bacteria which interact directly with the neutrophil
00:18:10.02 have a different transcriptional profile
00:18:12.00 than the bacteria which are growing
00:18:14.05 within the center of these host cells.
00:18:16.25 And so.
00:18:18.18 we believe that that's probably the case,
00:18:20.15 and we had reason to believe this was the case
00:18:22.13 based on previous work from workers studying
00:18:25.29 organisms growing within the lumen of the intestine.
00:18:28.13 And, in this particular work,
00:18:30.02 which was done by Sansonetti and coworkers.
00:18:32.20 Christoph Tang.
00:18:34.21 what they did is they fed another pathogen, Shigella flexneri,
00:18:38.16 into animals,
00:18:41.00 and they noticed that bacteria
00:18:43.00 that were growing near the interface of intestinal epithelium,
00:18:45.19 and in the lumen,
00:18:47.19 seemed to be seeing a different environment
00:18:50.00 in regards to oxygen tension.
00:18:52.11 And the way this could be seen
00:18:54.20 is with one of these fluorescent proteins, GFP,
00:18:56.26 which only folds if you have sufficient oxygen in the environment.
00:18:59.15 And what they found is that,
00:19:01.19 in the case of these GFP-encoding Shigella,
00:19:04.28 bacteria which were growing within the lumen did not fluoresce,
00:19:08.23 but as you got closer and closer to the lumen of the intestine,
00:19:11.29 what happens is they begin to fluoresce,
00:19:14.09 and the reason why is because the oxygen tension here,
00:19:16.21 near the intestinal epithelial cells,
00:19:19.12 is much higher than in the lumen of the intestine,
00:19:21.24 which is basically anaerobic,
00:19:23.27 and the GFP will not fold.
00:19:28.19 And so this colored our way of looking at things.
00:19:32.20 And so we asked if a similar thing could be going on,
00:19:35.02 but it's a little different than the oxygen environment.
00:19:37.04 What we're seeing here is we're seeing a cell interactive environment
00:19:40.22 as well as an environment
00:19:43.01 in which the bacteria are growing within the center.
00:19:46.28 So now, the second thing that we were interested in, then,
00:19:49.19 is whether there is community behavior.
00:19:52.01 And, we defined community behavior by the following,
00:19:54.09 and that is that the activity of one population
00:19:56.28 causes a second population to be differentially regulated.
00:20:00.01 So, as you recall from the early slides,
00:20:02.08 bacteria which would be growing associated with tissues,
00:20:05.17 in this case neutrophils,
00:20:08.11 might change the environment,
00:20:10.09 so that the bacteria growing within the center of the colony
00:20:12.15 then are experiencing a different environment
00:20:16.20 and, as a result of this different environment then,
00:20:19.02 they undergo a different transcriptional profile
00:20:21.19 that looks very different from the bacteria
00:20:23.17 which are growing associated with host cells.
00:20:28.00 Okay, so let's go and talk about the first point.
00:20:31.25 And again, YopE will interact with the phagocyte.
00:20:35.00 interfere with phagocytosis.
00:20:37.00 And so, one of the interesting aspects of the regulation
00:20:40.12 of the gene that encodes this protein
00:20:43.10 is that it has been shown by Hans Wolf-Watz and coworkers,
00:20:46.03 almost twenty years ago,
00:20:49.25 that the gene for this protein is upregulated,
00:20:54.03 so the gene is transcribed at higher levels,
00:20:56.25 when bacteria are growing in contact with host cells
00:20:59.24 than when they're not.
00:21:01.08 In this simple experiment from Wolf-Watz's lab,
00:21:03.19 he takes bacteria in which a luciferase reporter
00:21:05.27 is fused to the gene for YopE
00:21:08.07 and then incubates it with cultured cells,
00:21:10.22 in this case it's HeLa cells,
00:21:12.24 and then the bacteria which are associated
00:21:16.01 simply with the extracellular matrix are not turning on this gene,
00:21:18.15 but those which are associated with the cells are.
00:21:21.22 So then what we asked is,
00:21:23.21 is this really what's going on in tissues?
00:21:27.27 And so, we made a similar type of reporter,
00:21:30.17 and this reporter actually has two different fluorescent proteins in it.
00:21:33.23 One fluorescent protein has GFP,
00:21:36.23 and GFP is just made constitutively,
00:21:38.29 so it's always on,
00:21:40.28 and the other has Cherry.
00:21:43.04 Cherry is a red fluorescent protein,
00:21:44.25 and it's under the transcriptional control
00:21:46.24 of the YopE gene.
00:21:48.20 Otherwise, this organism is totally wild type.
00:21:51.23 It has all the components necessary
00:21:53.28 for causing disease.
00:21:56.00 Then, we take this particular construct,
00:21:57.29 we then inject animals intravenously,
00:22:00.27 we allow infection to go on for three days,
00:22:03.19 we then harvest the spleens
00:22:05.16 and we perform histology on frozen sections,
00:22:07.26 using fluorescence microscopy.
00:22:11.03 Usually, we use confocal microscopy to do this.
00:22:16.12 And you see a very striking result.
00:22:18.19 Again, red is the YopE gene.
00:22:20.23 Green is just constitutive expression.
00:22:23.06 And what you can see is that on the edges of these colonies
00:22:26.05 the bacteria are glowing red.
00:22:28.19 If they're in contact with the host cells,
00:22:30.04 with the neutrophils,
00:22:31.18 they're turned on.
00:22:33.13 But the bacteria in the center have a different transcriptional profile
00:22:35.29 they're green.
00:22:37.15 They're not turning on this gene,
00:22:39.02 so they're in a protective environment
00:22:40.21 in which they're not directly interacting with phagocytic cells.
00:22:43.24 They're growing, in essence,
00:22:45.16 in some ways,
00:22:47.06 very similarly to bacteria which are not growing in tissue.
00:22:53.16 So, there's the contact with the host cells,
00:22:56.02 and those are the bacteria that are internal.
00:22:59.18 Now, this gives us
00:23:02.09 two transcriptionally distinct populations,
00:23:07.17 and it's clear that it looks like there's an altruistic effect,
00:23:10.27 so that the bacteria directly interacting
00:23:13.06 with the host cells
00:23:14.25 are changing the environment
00:23:16.17 so that the bacteria in the center
00:23:18.25 are able to actually avoid phagocytosis.
00:23:21.13 And not only does avoid phagocytosis mean that they don't have to worry
00:23:24.16 about being killed by the phagocyte,
00:23:26.20 it means they can undergo a transcriptional profile
00:23:29.02 which starts to look a little bit like what a non-pathogen
00:23:31.15 looks like, in that they may not be making some of the genes that are.
00:23:35.20 expressing some of the genes that are important for disease.
00:23:41.24 But the question is, there's other things going on in tissue,
00:23:44.14 and I mentioned in the previous talk,
00:23:47.11 when these foci start to get larger,
00:23:51.14 what happens is there are secondary responses
00:23:53.24 in which the host tries to clear out microorganisms.
00:23:56.21 And one of the secondary responses is nitric oxide.
00:23:59.20 So, there's cells that might come in
00:24:01.22 and make soluble mediators
00:24:03.22 to actually start to clear out the organism.
00:24:06.05 So what we wanted to ask is,
00:24:07.28 is this more heterogeneous than we even though initially?
00:24:10.20 Is there actually more than one population?
00:24:15.00 So, nitric oxide,
00:24:17.20 as I mentioned previously,
00:24:20.08 would be a very important antimicrobial molecule
00:24:22.29 that these cells might see.
00:24:25.06 It can diffuse into the center of these microcolonies,
00:24:28.00 and so the bacteria don't actually have to
00:24:30.06 directly interact with phagocytes
00:24:32.05 in order to see this antimicrobial molecule.
00:24:34.23 And nitric oxide, of course,
00:24:36.22 is made by inducible nitric oxide synthase.
00:24:40.27 So, now we believe that
00:24:45.24 Yersinia has to have strategies for dealing with nitric oxide,
00:24:48.27 and the reason for believing
00:24:51.00 is that the very closely related,
00:24:53.02 shockingly closely related organism, Yersinia pestis,
00:24:55.10 which causes bubonic plague.
00:24:57.08 but causes a disease that's very different
00:24:59.27 from Yersinia pseudotuberculosis.
00:25:02.25 appears to require strategies
00:25:04.20 for dealing with the nitric oxide response.
00:25:07.18 And in enteric organisms,
00:25:09.11 that is, Gram negative organisms
00:25:11.12 which are similar to E. coli,
00:25:13.22 the most important way in which these organisms
00:25:15.19 are able to inactive nitric oxide
00:25:18.15 is through the use of this protein called HMP,
00:25:20.23 which is a flavoprotein which inactivates nitric oxide.
00:25:24.13 And what Sebbane and coworkers showed
00:25:26.11 a number of years ago
00:25:28.16 is that if you don't have HMP,
00:25:30.23 then Yersinia pestis,
00:25:32.20 which causes a lethal disease in mice,
00:25:36.10 shows delayed or no death in other animals
00:25:40.10 if the bacteria are unable to make the HMP protein.
00:25:44.03 So, we decided to investigate this in detail,
00:25:46.27 and there were reasons for thinking that HMP
00:25:48.27 would be an important protein to look at,
00:25:51.02 because hmp is a gene
00:25:53.02 that's highly regulated by the presence of nitric oxide.
00:25:58.17 So, in bacteria,
00:26:00.22 nitric oxide is able to regulate a number of genes.
00:26:04.02 The HMP protein,
00:26:05.29 which takes nitric oxide and oxygen
00:26:08.11 and inactivates it by making NO3-,
00:26:11.03 is a flavoprotein as described right here,
00:26:13.29 and it's regulated by a transcriptional regulator
00:26:17.17 called NsrR, which recognizes
00:26:20.26 high levels of nitric oxide in tissues,
00:26:24.00 and then there's a conformational change in NsrR
00:26:27.08 which activates the gene for HMP,
00:26:29.12 and it then gets turned on.
00:26:31.08 That means we can use the gene for HMP
00:26:33.08 as a reporter for nitric oxide concentration
00:26:35.20 in host tissues.
00:26:39.09 So, the reporter we made was very similar
00:26:41.06 to the one we showed before,
00:26:43.00 and that is that we have a constitutively expressed GFP
00:26:45.14 and then we have Cherry under the control of the hmp gene.
00:26:50.10 So, what we see is something very similar
00:26:52.09 to what we saw with YopE,
00:26:54.21 and that's that there is an extreme gradient of expression
00:26:56.22 of the hmp gene.
00:26:58.15 On the edges, what we see.
00:27:00.08 and bacteria that are migrating into tissues.
00:27:03.10 the bacteria are all red, so they have high HMP expression.
00:27:08.07 However, in the center
00:27:10.21 you see the beginning of a gradient.
00:27:12.24 You see yellow,
00:27:14.19 which means that the red is expressed
00:27:16.23 at lower levels in these cells.
00:27:18.28 And in the center, frankly, you see green,
00:27:20.23 which means we see the green fluorescent protein
00:27:22.26 but we don't see the red fluorescent protein
00:27:26.09 in the center of these colonies.
00:27:28.12 Clearly, as the bugs migrate into tissues,
00:27:30.05 they're able to see nitric oxide.
00:27:32.11 This could also be displayed another way,
00:27:34.01 where we ratio the Cherry to the GFP
00:27:36.28 in this ratiometric display.
00:27:39.12 Red means that you have very high Cherry levels
00:27:41.28 blue means that the levels of GFP relative to Cherry
00:27:45.02 are very high.
00:27:46.16 This is over a 10-fold gradient
00:27:49.29 based on this ratiometric assay,
00:27:52.02 in which we can see that there's very low expressions of HMP
00:27:54.08 in the center of the colony
00:27:56.11 and very high on the edges.
00:27:58.02 This can also be displayed in another way,
00:28:00.28 in which we do 3-D imaging of this particular structure.
00:28:04.07 Okay, so.
00:28:05.26 now, the question is,
00:28:07.19 why is there this steep gradient?
00:28:10.02 And there's two explanations for why the gradient
00:28:12.09 could be steep.
00:28:13.29 One reason is that there's this gradient of expression,
00:28:16.21 where the bugs go from red to yellow to green
00:28:20.05 because the NO gradient in host tissues
00:28:22.26 is very steep.
00:28:24.10 As a result, the bacteria growing within the center of the colony
00:28:27.04 don't see NO.
00:28:29.02 But what we were more curious about
00:28:32.26 is whether we could find an example of community behavior.
00:28:35.04 That is, are the bacteria on the edges
00:28:37.09 facilitating growth of bacteria in the center
00:28:39.10 because they're removing nitric oxide from the center of the colony.
00:28:44.09 as displayed here.
00:28:46.27 Bacteria growing near a neutrophil
00:28:49.07 make the HMP protein.
00:28:51.18 They then remove or reduce the amount of NO
00:28:56.08 in the environment.
00:28:58.07 Blue is high NO
00:29:00.06 white or light blue is low NO.
00:29:02.10 Then as the NO gets lower,
00:29:04.11 then there's no NO in the system
00:29:05.29 where the bacteria are growing,
00:29:07.19 and then you no longer see hmp::Cherry on anymore,
00:29:11.01 and the bacteria are growing relatively free of NO
00:29:13.25 because of this community behavior.
00:29:16.00 So, how do we actually test this and
00:29:17.29 distinguish between these two models?
00:29:21.28 So, the way we distinguish between these two models
00:29:23.24 is we take advantage of the fact that
00:29:26.05 hmp actually inactivates NO,
00:29:28.03 so in a wild type organism,
00:29:30.27 the hmp will take NO
00:29:33.20 and reduce the amount of NO in the environment.
00:29:37.10 And in the wild type what will happen,
00:29:39.08 if there's a steep NO gradient.
00:29:41.07 we see a steep NO gradient with the wild type
00:29:43.09 because the gradient is simply steep,
00:29:46.03 and if you have an hmp- mutant
00:29:48.25 it doesn't matter whether it's inactivating the NO or not.
00:29:51.10 There's simply a steep gradient
00:29:53.04 from the presence of neutrophils making it high near them,
00:29:56.03 and then there's loss of NO
00:29:58.13 deeper into the colony.
00:30:00.15 On the other hand, if there's community behavior
00:30:03.23 you'll see a different result.
00:30:05.12 In the wild type, what happens is
00:30:07.29 the HMP protein would be removing the NO
00:30:10.18 from the environment
00:30:12.14 and then allowing bugs to grow
00:30:14.09 in the absence of hmp expression.
00:30:16.03 And then in the case of the mutant,
00:30:19.04 the hmp is no longer removing
00:30:22.01 NO from the tissues,
00:30:23.27 and now what happens is what we see.
00:30:26.10 is that the bacteria now are able to
00:30:29.17 induce the hmp expression because NO is not removed.
00:30:32.23 Alright, so this is a very simple experiment,
00:30:34.15 and we get a relatively simple answer.
00:30:38.21 The answer is the following.
00:30:40.29 that the gradient that we see is now gone.
00:30:43.12 So now, in this experiment what we do is
00:30:45.16 we've inverted the GFP.
00:30:47.09 what we've done here is we've taken the hmp- and the hmp+,
00:30:51.14 and what you see is the hmp+.
00:30:53.29 you see Cherry expression on the edges,
00:30:57.05 and then in the center
00:30:59.14 there's little expression at all.
00:31:01.06 So we've seen this before.
00:31:02.24 Now what happens, in the case of.
00:31:04.24 if we have an hmp- mutant,
00:31:06.13 this gradient is gone and we start, now,
00:31:08.00 to see Cherry now expressed at high levels
00:31:10.15 in the center of these colonies.
00:31:12.17 This can be seen in this 3-D reconstruction.
00:31:15.01 So right here,
00:31:17.18 the way we've displayed this data is,
00:31:19.19 if you have high fluorescence,
00:31:21.13 in the X axis you see high peaks,
00:31:23.16 and if you have low levels of expression
00:31:25.17 you see absence of peaks.
00:31:27.16 What you can see is, in the wild type situation,
00:31:29.26 there's a loss of expression in the center,
00:31:32.01 but in the deletion, where we're allowing
00:31:34.01 NO to get into the center of the colony,
00:31:35.25 we're seeing expression throughout the colony.
00:31:37.25 So we view this as community behavior.
00:31:41.17 Alright, now the question is this.
00:31:44.06 so, one of the most interesting aspects of this
00:31:46.27 is the fact that the bacteria on the edges of the colony
00:31:51.00 are facilitating the bacteria in the center to grow,
00:31:54.14 so that you actually need that expression on the outside
00:31:56.20 in order to cause disease,
00:31:58.19 and that can be seen here.
00:32:00.02 I showed you pictures of animals
00:32:02.03 in which we've sectioned through the spleen
00:32:04.12 3 days after infection,
00:32:06.14 and the size of the colonies
00:32:08.01 in either the wild type or the Δhmp mutant
00:32:10.08 look almost identical.
00:32:12.04 However, if you wait 5 days after infection,
00:32:14.02 what happens is the colonies continue to grow
00:32:16.23 in the wild type situation,
00:32:18.17 but in the mutant the colonies start to break apart.
00:32:21.20 What we find interesting about this
00:32:23.20 is that the ability to establish this colony
00:32:25.24 and maintain the colony is dependent on only a subset of bacteria
00:32:29.22 expressing this gene,
00:32:31.12 because these bacteria in the center aren't expressing it.
00:32:33.19 So, if the bugs on the outside
00:32:35.11 are unable to express this particular protein,
00:32:37.19 then what happens is the whole colony breaks apart.
00:32:43.12 Alright, now. so, the question is,
00:32:46.20 are we actually seeing two signals?
00:32:48.26 Is there a signal that's coming direct from the cell?
00:32:51.29 Or is there actually a soluble signal
00:32:53.26 and a signal that's coming from the host cell?
00:32:56.06 So, we look at that as either cell contact and NO
00:32:59.14 as a single signal that might be coming in
00:33:02.05 and the bugs on the edges are responding to,
00:33:04.16 whereas the bugs in the center
00:33:06.15 are responding to no signal at all,
00:33:08.27 and they're growing.
00:33:11.14 something in between a pathogen and non-pathogen.
00:33:14.15 Now, the alternative is that
00:33:16.08 there's actually three signals going on,
00:33:18.10 and that there's a cell contact and an NO signal
00:33:20.04 going on at the edges because these cells
00:33:22.08 are seeing NO as well as cell contact,
00:33:24.26 but then there's other bugs
00:33:26.29 which are within this particular tissue site
00:33:29.19 which are seeing NO but they're not seeing the host cell,
00:33:33.22 and then perhaps there's a third population
00:33:35.11 which is seeing neither the host cell nor NO.
00:33:37.24 So the, we draw this, therefore,
00:33:39.19 as three populations
00:33:41.24 in which there's bacteria on the edges
00:33:43.24 directly contacting the host,
00:33:45.27 and then there's other bacteria
00:33:47.19 which are not directly contacting a host cell,
00:33:49.19 but they might be seeing NO,
00:33:51.18 and then the ones in the center,
00:33:54.06 they're seeing neither NO nor the host cells.
00:33:57.20 So now, to distinguish between these two models
00:34:00.19 we set up another reporter situation.
00:34:03.00 So, in this reporter situation
00:34:04.18 we have the cell contact signal reporter,
00:34:09.02 yopE, now in red,
00:34:12.05 and GFP now fused to hmp.
00:34:14.13 We put them both into
00:34:16.18 either a wild type or a Δhmp strain,
00:34:18.26 and then we ask whether
00:34:21.02 we see a gradient of expression like we'd seen before.
00:34:23.29 If these two proteins. these two genes
00:34:27.01 are now responding to the identical signals,
00:34:29.20 the gradient that we see,
00:34:31.23 that gets removed when we're studying the hmp gene,
00:34:33.28 should also be removed
00:34:36.03 when we look at expression of yopE.
00:34:38.16 However, that's not what we see.
00:34:43.05 What you see is that.
00:34:44.25 now, the green GFP is HMP,
00:34:47.13 and what you see is there's HMP expression
00:34:49.10 throughout the colony,
00:34:51.13 but YopE is still expressed
00:34:53.15 at very high levels around the edges,
00:34:55.14 where it's in contact with host cells.
00:34:57.14 So, these two proteins are responding, therefore,
00:34:59.11 to different signals.
00:35:01.03 On the wild type, again, you see something similar
00:35:03.02 to what we've seen before.
00:35:04.20 You see this extreme gradient of expression of hmp.
00:35:12.11 Alright, so now we believe
00:35:14.00 that we've got three different signals.
00:35:15.23 There's ones that are missing both the cell contact signal
00:35:18.11 and the NO signal.
00:35:19.26 It doesn't mean they're not seeing some other signals
00:35:21.14 we haven't identified and, in fact,
00:35:24.03 my lab is trying to identify some other signals
00:35:25.24 that these ones in the center might be seeing
00:35:27.11 that might distinguish these cells
00:35:29.06 from organisms that are growing simply in culture.
00:35:31.24 There's ones that are responding to an NO signal.
00:35:34.03 They're not in contact with a host cell,
00:35:36.01 but they're turning on their high GFP levels.
00:35:38.21 And then the ones that are high GFP levels
00:35:40.19 that are on the edges
00:35:42.09 are responding to both the cell contact signal
00:35:44.00 and to an NO signal.
00:35:46.29 So now, the question is,
00:35:48.07 where is the nitric oxide coming from?
00:35:50.27 So, it could be coming directly from the host cells
00:35:53.17 which the organism is interacting with,
00:35:56.17 or it could be coming from somewhere else,
00:35:58.26 and the most straightforward way
00:36:00.22 to find out where the NO is coming from
00:36:02.24 is to study inducible nitric oxide synthase,
00:36:05.14 the protein which makes nitric oxide.
00:36:08.18 And so, we can determine
00:36:10.13 where the nitric oxide is coming from
00:36:13.01 by simply probing with antibody directly against
00:36:14.25 inducible nitric oxide synthase
00:36:16.26 and identifying cells
00:36:18.29 which are expressing this protein in tissues.
00:36:23.04 So what I'm going to show you
00:36:24.25 is a series of panels
00:36:26.24 in which I show you a typical colony
00:36:28.10 of Yersinia pseudotuberculosis growing in tissues.
00:36:30.23 In blue are the bacteria,
00:36:32.09 which we stain with antibody directed against the bacteria,
00:36:35.15 and you see this nice colony.
00:36:37.20 And then the second thing I'm going to show you
00:36:39.26 is a stain, now, for inducible nitric oxide synthase.
00:36:43.26 And surprisingly, what you see
00:36:46.05 is that although bacteria are growing within this colony here,
00:36:48.22 there's a gap,
00:36:50.09 and as I'll show you on the next side,
00:36:52.01 this gap actually has cells.
00:36:53.29 This gap where the cells
00:36:55.28 are not making inducible nitric oxide synthase.
00:36:58.09 Instead, the inducible nitric oxide synthase
00:37:00.15 is coming from cells in the periphery.
00:37:03.02 These cells out here
00:37:05.06 that are making inducible nitric oxide synthase,
00:37:07.03 we believe are macrophages and lymphocytes.
00:37:09.29 Now, if we stain with neutrophils,
00:37:11.22 which I've incessantly told you
00:37:14.16 the bugs are interacting with,
00:37:16.06 without actually giving you any evidence for,
00:37:18.13 what we find is that the neutrophils
00:37:20.14 are directly interacting with the bacteria,
00:37:23.03 but the neutrophils that are interacting with the bacteria
00:37:25.27 are, indeed, not making nitric oxide synthase.
00:37:28.16 So, the nitric oxide synthase is coming from afar,
00:37:31.19 and then managing to migrate through the neutrophils
00:37:35.11 and actually attacking the bacteria on the edges.
00:37:39.29 Okay, so this sort of summarizes
00:37:42.11 what I'd like to communicate with you today,
00:37:45.21 and that is that the nitric oxide-producing cells
00:37:48.19 are very far away,
00:37:50.25 and the nitric oxide producing cells
00:37:52.17 are not directly in contact with the [bacterial] cells,
00:37:54.26 but the bacteria are still responding to the nitric oxide.
00:37:58.17 When they respond to nitric oxide
00:38:00.20 , the nitric oxide gradient, which is displayed here
00:38:03.25 as blue:high to yellow:low,
00:38:06.14 when the bacteria encounter it,
00:38:08.14 the HMP protein inactivates it,
00:38:10.16 allowing bacteria in the center of the colony
00:38:12.11 to be naive for nitric oxide,
00:38:14.08 and not see it.
00:38:15.21 Furthermore, the bacteria in the center
00:38:17.12 are also protected from phagocytes,
00:38:19.18 because the ones on the edges
00:38:21.20 are acting to interfere with phagocytosis
00:38:23.20 and prevent their access
00:38:26.10 to the bacteria in the center of the colony.
00:38:29.07 Alright, so now,
00:38:31.07 why do we think this is important?
00:38:33.02 Do you think that this is a general model
00:38:34.24 for how all pathogens work?
00:38:36.20 And so, our way of thinking about this
00:38:38.21 is colored by work
00:38:41.03 that was published last year in Nature
00:38:44.00 by Hardt and Ackermann and coworkers,
00:38:46.26 who demonstrated, that in the case of Salmonella,
00:38:50.05 that if bacteria are.
00:38:52.18 in bacteria which are inoculated into an animal,
00:38:55.05 in this case a mouse,
00:38:56.26 and in this case it's Salmonella,
00:38:58.18 bacteria will make a virulence-dependent cascade,
00:39:03.17 which will allow them to invade into host tissues
00:39:07.02 and bypass the immune response.
00:39:10.16 What they demonstrated is that
00:39:12.29 all the bacteria in the population
00:39:14.28 actually express genes associated with virulence.
00:39:17.10 What they saw is that,
00:39:19.01 if you model this,
00:39:20.18 that the number of bacteria that are fully virulent
00:39:23.18 will decrease over time,
00:39:25.10 and instead they'll be replaced
00:39:27.04 by avirulent derivatives of the organism.
00:39:29.23 So, by having a virulence cascade
00:39:33.09 which is on in all the organisms in a tissue,
00:39:35.28 you actually select, now,
00:39:38.05 for faster growing, non-pathogenic variants,
00:39:40.20 which will overgrow the population.
00:39:42.29 On the other hand, if you build a pathogen
00:39:44.15 a little more wisely,
00:39:46.10 so that a proportion of the organisms
00:39:49.22 are not producing virulence-associated proteins,
00:39:53.08 then you see higher persistence
00:39:55.01 of the fully virulent organism.
00:39:57.05 So, what we believe is that
00:39:59.25 the reason why pathogens have this heterogeneous population
00:40:02.21 is that it's able to now allow
00:40:05.23 expression of proteins on the edges
00:40:08.06 which result in the organisms actually growing slower,
00:40:11.09 but dealing directly with the host immune function,
00:40:14.23 and then there's another population protected.
00:40:17.03 And this faster growing population,
00:40:18.23 which doesn't have to directly interact with host cells,
00:40:23.01 can outcompete avirulent derivatives,
00:40:25.11 because they're able to grow
00:40:27.14 just as fast as some avirulent derivative.
00:40:29.23 So, the fitness cost that an organism might have
00:40:32.20 from making virulence-associated proteins
00:40:35.06 is partially overcome
00:40:37.09 from the ability of these organisms to grow heterogeneously
00:40:39.18 in tissues.
00:40:42.08 So, let me summarize now,
00:40:44.20 with the three points that I want to make.
00:40:46.27 is that pathogen-specific proteins are only expressed
00:40:49.00 by a fraction of bacteria,
00:40:50.23 and we believe the reason for that
00:40:52.24 is because this allows them to
00:40:56.16 have a fitness cost which is less than they would have
00:40:58.24 if all the bacteria in the population
00:41:01.01 actually expressed virulence-associated proteins.
00:41:06.16 The environment in which the bacteria encounter
00:41:10.01 is different in different sites within the tissue,
00:41:13.09 and that includes in the narrow environment
00:41:15.17 in which the organism is growing.
00:41:17.18 And then finally,
00:41:20.03 as the bugs move into other sites,
00:41:22.05 there are different environments
00:41:24.07 which the microorganism encounters,
00:41:26.18 and when it encounters these different sites,
00:41:28.11 it encounters.
00:41:30.04 it will now respond with a different transcriptional profile.
00:41:34.26 So finally, I'd like to thank the people
00:41:37.15 who worked on this.
00:41:39.12 Sina Mohammadi was a graduate student
00:41:41.09 and a postdoc in my lab,
00:41:42.21 who did the initial reporters
00:41:44.06 to allow following of gene expression in tissues.
00:41:47.13 And of course, I'd like to thank Penelope Barnes,
00:41:49.14 who was an MD fellow in my lab,
00:41:51.09 who got us thinking about colonies within tissues.
00:41:54.15 And Molly Bergman and Greg Crimmins
00:41:57.04 did the initial studies which led to
00:41:59.18 most of this work which I've described,
00:42:01.09 which was performed by Kim Davis in my lab.
00:42:03.04 I've acknowledged her work throughout, on the slides,
00:42:05.04 with her name there.
00:42:07.12 And in addition, I'd like to thank Kerri Sheahan,
00:42:10.07 who's developed analysis of Type III translocation in my lab,
00:42:13.07 as well as special thanks to Joan Mecsas,
00:42:15.19 who is a far more expert
00:42:18.05 at animal infection models than I am,
00:42:20.04 and much of what I've learned has been learned from her.
00:42:22.24 And then my funding is from NIAID,
00:42:25.11 which has funded my lab on Yersinia
00:42:27.21 for over 20 years,
00:42:30.09 as well as Howard Hughes Medical Institute.
00:42:32.16 Thank you.
- />Part 1: What Distinguishes a Pathogen from a Non-Pathogen?