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+ | ====== Presentation - It is time to bury Koch - Infectious disease transitions to an understanding of the Metagenome ====== | ||
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+ | {{ vimeo> | ||
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+ | **Type:** Conference presentation\\ | ||
+ | **Presenter: | ||
+ | **Conference: | ||
+ | **Location: | ||
+ | **Date: | ||
+ | **See also:** [[https:// | ||
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+ | ===== Transcript ===== | ||
+ | |||
+ | Well thank you very much for inviting me. It’s great to be here in Prague. | ||
+ | It’s my first visit to Prague. And I must say I’m enjoying the city. | ||
+ | |||
+ | ==== Slide # 1: Topic introduction ==== | ||
+ | |||
+ | What I’m going to talk about is a new concept called the “metagenome.” | ||
+ | |||
+ | As we understand more about the human genome and the pathogenic genomes we are starting to understand more about how the various pathogens -- be they // | ||
+ | |||
+ | And so my title is based on “Infectious Disease transitions to an understanding of the Metagenome.” | ||
+ | |||
+ | ==== Slide # 2: In-vivo, in-vitro, in-silico ==== | ||
+ | |||
+ | There are three types of biology that are pretty common these days. | ||
+ | The first type, //in vivo//, of course in animal or human models. | ||
+ | //In vitro// is where a lot of the work on antibiotics is being done -- in cell culture, in the lab. | ||
+ | |||
+ | //In silico// is very new. The first time I came across //in silico// was at this gathering here in Toronto back in 1981. Human insulin had just been synthesized using mathematical formulae -- using the IBM supercomputer that could simulate the insulin molecule at the level of the mathematics. | ||
+ | And that’s really what I’ve been doing over the last decade. | ||
+ | |||
+ | ==== Slide # 3: The NIH Human Microbiome Project ==== | ||
+ | |||
+ | There’s a new push going on at the moment. The NIH in the USA has started the Microbiome Project. | ||
+ | The goal of the Microbiome Project is to characterize all of the places in the human body where genomes—other than the human genome—are also present. The NIH has estimated that about 10% of the cells in the body are human cells, and about 90% of the cells—in a normal healthy individual’s body—are bacterial cells. Now remember that bacteria cells are very, very small—and in most cases bacterial cells—many, | ||
+ | |||
+ | We are starting to get to an understanding now that the human body does not work—the human genome does not work—in isolation. It works in concert with a symbiosis of other genomes that have gathered throughout a person’s lifetime, and indeed throughout the ages. | ||
+ | |||
+ | ==== Slide # 4: The Metagenome of Human Saliva ==== | ||
+ | |||
+ | This study has just been published. It’s a metagenome of human saliva. | ||
+ | |||
+ | It was a study done by Max Planck Institute in Germany. They took samples of saliva from 10 different places in the world—all over the world geographically—and individuals in those 10 places—and then they sequenced the genes. Because now, with //in silico// technology, we don’t rely on being able to culture the organism any more, we can actually sequence the sample and then find these little fragments of DNA we can match up with our known database of 800 or more identified pathogens. | ||
+ | |||
+ | What they found was that there was more variation individual-to-individual, | ||
+ | |||
+ | // | ||
+ | |||
+ | ==== Slide # 5: Microbiota on Prosthetic Hip Joints ==== | ||
+ | |||
+ | A similar study on prosthetic hip joints. This is hip joints that were being replaced during surgery. They used a special procedure with ultrasound to shake the biofilm off the hip joints, and see what species were present. Of course, you’ve got all the normal ones. You’ve got staph. You’ve got the gliding bacteria you’d expect to find in a biofilm, // | ||
+ | |||
+ | ==== Slide # 6: The Human Disease Network ==== | ||
+ | |||
+ | Now there’s two ways of looking at disease. One way of looking at disease is saying, “Well, this person is sick. She can’t put her weight on her leg. She has to lie down all the time.” In other words, focus on the symptoms. And categorize diseases based on symptoms. And that’s the way that medicine has done it for the last century. | ||
+ | |||
+ | But now we’re starting to view diseases based on the genes. On the common genes that affect the various diseases. This [referring to slide] is a gene map that was produced a year or two ago now, 2007, and it has all of the diseases: neurological diseases, deafness; the autoimmune diseases; cancers. It has them all linked together based on common genes. | ||
+ | |||
+ | ==== Slide # 7: Human Disease Network, close-up of area around the autoimmune diseases ==== | ||
+ | |||
+ | If we look at a close-up of the area around the autoimmune diseases, you can see that this one gene here, called ACE—which is involved in the progression of SARS, the infectious disease SARS—it’s involved in myocardial infarction, it’s involved in Alzheimer’s, | ||
+ | |||
+ | What’s interesting about this common gene, ACE, it’s not only involved in so many of what we would think of as different diseases—kidney disease, cardiac disease, Alzheimer’s--but also that this particular gene we know is affected by some of the bacteria which are present in every person’s body. In particular, // | ||
+ | |||
+ | Down here we have another gene, PTPN22, and that one’s associated with Lupus-SLE, Rheumatoid arthritis and Diabetes. That one is one of the body’s primary responses to // | ||
+ | |||
+ | So by looking at the genes in disease we can get a totally different picture from trying to work basically on symptoms, on differentiating symptoms as we have done for the last century. | ||
+ | |||
+ | ==== Slide # 8: HIV – a well-studied genome ==== | ||
+ | |||
+ | Well, Chlamydia is not a very well-studied genome. I’ll give you some data on Chlamydia in a little while, but the one that I want to focus on—because it illustrates the problem that we have; we, being, //Homo sapiens//, as a species have—and that is the HIV genome. | ||
+ | |||
+ | The HIV genome is very small. It’s a small strand of RNA. From that genome 17 proteins (19 including cleavage), but 17 proteins that are generated from this one strand of RNA, which is the HIV genome. So, HIV does all it’s damage by generating only 17 proteins. You compare that typically with a bacterium which certainly generates hundreds of proteins, usually close to a thousand proteins. | ||
+ | |||
+ | The HIV genome transcribes for 17 proteins. And with the billions of dollars we’ve spent analyzing HIV, finding out what it does, we have identified—we being science—has identified that there are over 3,000 interactions between those 17 proteins and the human metabolome, the human genome. | ||
+ | |||
+ | So if we take the saliva genome, which we saw on slide [4]—which has got more than a hundred species, and they transcribe for approximately 50,000 protein products—we compare 50,000 here to 17 here [referring to slide]. And then we look at 3,000 [interactions with HIV proteins]… how large is that 3,000 going to rise if you’ve got that many more proteins being generated by the salivary metagenome? | ||
+ | |||
+ | The answer is, it’s imponderable. You get to a point where you are just looking at noise. You’re looking at stochastics. The body is trying desperately to deal with the species that it’s got there—the DNA at the level of the transcription—trying to ignore all of the proteins and the enzymes that are coming from the pathogenic genomes and still produce good quality proteins from the human DNA and it’s just an imponderably complex problem. | ||
+ | |||
+ | ==== Slide # 9: Why the Complexity of Interactions? | ||
+ | |||
+ | Why is it so complex? This is a slide courtesy of Professor Peter Wright at the Scripps Institute. This is a human transcription factor called CBP/P300. This transcribes some very important enzymes and proteins—I’ll be dealing with one of them later in the presentation. | ||
+ | |||
+ | What happens is, you’ve got a strand of DNA here [referring to slide] and the transcription factors look for areas of that DNA where they’re attracted—where their active areas are attracted—and then the DNA is transcribed, | ||
+ | |||
+ | This loop here (referring to loop in CBP/P300 on slide) will bind to other substances, it binds to other proteins. Depending on whether that loop is squashed up, or stretched out, you’ll be decoding a totally different region of the DNA. This one transcription factor actually transcribes thousands of human genes. | ||
+ | |||
+ | The important thing to note is where is this human protein has got areas that are very well structured—and these are the colored areas that are defined—very well structured, and the disordered loops are relatively small in size and number. | ||
+ | |||
+ | In a virus, the viral proteins are almost all totally disordered. So they have no shape until they wrap themselves around a protein or an enzyme from their host—from the human body. Then, depending on which atoms attract each other, they take on the shape of the host protein. They can change very quickly. They can mutate very quickly. As you all know that is one of the biggest problems with HIV. | ||
+ | |||
+ | ==== Slide # 10: A common underlying mechanism ==== | ||
+ | |||
+ | Even though the plethora of interactions is imponderable, | ||
+ | |||
+ | **The catastrophic failure of the human metabolism we see in chronic disease, which at first glance appears so diverse—and so different between the various disease diagnosis--is actually due to the same underlying mechanism—a ubiquitous microbiota which has evolved to persist in the cytoplasm of nucleated cells.** | ||
+ | |||
+ | It’s very important that these bacteria persist by overcoming the innate immune response. The very cells that are supposed to kill the bacterial pathogens, they actually overcome, and they live within those phagocytes--and live within those phagocytes for quite a long time. | ||
+ | |||
+ | The same cause is behind Hashimoto’s hypothyroiditis and Multiple Sclerosis. The same cause is behind Chronic fatigue and Rheumatoid Arthritis. Diseases that we wouldn’t normally associate if we are looking at them as symptoms. But when we look at them as genes, we can see how they’re associated. | ||
+ | |||
+ | ==== Slide # 11: Gene Expression in Sarcoidosis ==== | ||
+ | |||
+ | In fact, when you do a genome-wide study—this is one of apoptosis in Sarcoidosis, | ||
+ | |||
+ | ==== Slide # 12: Mycobacteria ==== | ||
+ | |||
+ | If we take // | ||
+ | |||
+ | They are not talking about one toxin. There’s not one toxin. There were 463 genes whose expression were changed. 366 of them were known genes. The other genes were unknown —mutations. And the genes function in various cellular processes including intracellular signaling, cytoskeletal rearrangement, | ||
+ | |||
+ | In fact everything, effectively, | ||
+ | |||
+ | ==== Slide # 13: Chlamydia ==== | ||
+ | |||
+ | // | ||
+ | |||
+ | ==== Slide # 14: Gene Expression During CPN Infective Cycle ==== | ||
+ | |||
+ | Gene Expression During CPN Infective Cycle was published in //PLoS Pathology// in 2007. | ||
+ | |||
+ | ==== Slide # 15: Why is the Cytoplasm of Nucleated Cells Important? ==== | ||
+ | |||
+ | Why is the cytoplasm of nucleated cells—that means cells with a nucleus, the phagocytes in particular—why is that so important? Once again, we’ll go back to our old friend HIV, because it’s pretty well studied. | ||
+ | |||
+ | HIV infects through the cell membrane—through the CD4 receptors typically—and then the RNA of the HIV is reverse transcripted into DNA, double stranded DNA. Which then goes into the nucleus where it becomes integrated with the human genome, and then transcription occurs in the normal way. The viral RNA leaves the nucleus, is assembled once again, reconstructed and then leaves the cell. The important thing to notice is a lot of the work is done in the cytoplasm—in the region around the nucleus. In the nucleus you have the integration, | ||
+ | |||
+ | ==== Slide # 16: Wirostko TEM study ==== | ||
+ | |||
+ | Here we have a picture from a transmission electron microscopy study at Columbia University back in the 1980's by Emil Wirostko. Emil’s group studied lymphocytes, | ||
+ | |||
+ | ==== Slide # 17: Video from optical microscope ==== | ||
+ | |||
+ | If we look at it with an optical microscope, we can see we have a nucleus here [referring to video on the screen] and a cytoplasm which is just swelled and exploded as a result of these small colonies of biofilm-like pathogens. These huge long tubules are being thrown out from the degrading cell. These are very, very thin tubules, caused by bacterial protein. This one’s about 20 cell diameters long, extremely long. | ||
+ | |||
+ | That’s what happens with the cytoplasm of the cell becomes so infected that the pathogens start to break out—the biofilm starts to break out to try and find more suitable hosts—other than that particular cell. Here we can see [referring to image on the screen], zoomed out, the length of this huge long biofilm tubule that is put out. | ||
+ | |||
+ | ==== Slide # 18: Summary ==== | ||
+ | |||
+ | In the three decades that have gone past since my early research in Perth, Western Australia, and Toronto, Canada, the number of symptomatic similarities which existed between the various chronic diseases become more and more obvious to me. | ||
+ | |||
+ | It became pretty clear to me that all the chronic inflammatory diseases were arising from a common pathogenesis. Which I figured had to be a failure of the innate immune system. And we found that it had to be a Th1-dominant cytoplasmic, | ||
+ | |||
+ | There’s no other way that the biochemistry all fits together. If you look at the number of changes to the molecular chemistry which occurs in these chronic disease states it is imponderable, | ||
+ | |||
+ | But the thing that’s really important is, for decades, chronic disease patients have been given antibiotics and have responded to the antibiotics differently from the way healthy people responded to the antibiotics. One of the reasons for that is because the postulates of Koch, from 1897, said basically, “Look, you’ve got to be able to examine the bacterium out of the body, in the lab.” | ||
+ | |||
+ | The moment you take it out of the body, you get rid of a whole lot of things that happen inside the cells of the human body. For example, if you take the antibiotics clindamycin, | ||
+ | |||
+ | ==== Slide # 19: Overcoming Antibiotic Resistance ==== | ||
+ | |||
+ | In //Homo sapiens// — and this is different from animals, animals have different function in their DNA transcription—but in //Homo sapiens// the VDR Nuclear Receptor transcribes genes for TLR2, as well as the Cathelicidin and beta-defensin antimicrobial peptides, all of which are essential to intraphagocytic innate immune defenses. | ||
+ | |||
+ | A microbiota has evolved, which we’ve called a Th1 microbiota because one of the common factors is interferon-gamma which is produced when the innate immune system is attacked by these persistent pathogens. | ||
+ | |||
+ | The Th1 microbiota evades the human immune system by blocking DNA transcription by the VDR, which consequently blocks expression of these endogenous antimicrobials. | ||
+ | |||
+ | So it comes as no surprise then that we now know that **HIV totally disables VDR.** HIV takes VDR and actually uses it to help transcribe it’s own RNA genome, its LTR transcription-repeat. The tat protein from HIV actually takes away one of the human body’s main innate defenses and uses it as part of the viral replication. We saw earlier that // | ||
+ | |||
+ | Unfortunately during the 20th century, //Homo sapiens// changed their lifestyle in several ways that has resulted in further downregulation of gene expression by the VDR and which made their bodies more susceptible when infections came along, like HIV or TB; that required weak VDRs in order to become persistent. | ||
+ | |||
+ | ==== Slide # 20: VDR Activation ==== | ||
+ | |||
+ | The VDR is called the VDR because it’s short for vitamin D receptor. Now, vitamin D is not a nutrient. Despite what we’ve thought for 100 years, certainly back to the 1930’s. Which is what? 80 years. For the last 80 years we’ve thought vitamin D was a nutrient, but it’s not a nutrient. The body manufactures vitamin D. There’s been no human study on whether any vitamin D is necessary. There has certainly been studies in other other animals. A very elegant study in fish showed that the body manufactures all the vitamin D it needs. | ||
+ | |||
+ | Vitamin D is not a nutrient. It’s a transcriptional activator. It’s a secosteriod hormone. There’s a very complex control system here which involves the P300/CBP that I was talking about earlier, as well as the VDR to synthesize from 7-dehydrocholesterol--the cathelicidin, | ||
+ | |||
+ | ==== Slide # 21: Only 1, | ||
+ | |||
+ | Now, what we found was that only the active metabolite [1, | ||
+ | |||
+ | We’ve got the various forms of vitamin D docked here [referring to slide] as they exist within the molecules (this is some //in silico// work) and only one of them has got the 1-alpha hydroxylation needed to activate the VDR. All the others will take up space in the VDR, but they won’t activate genes. They just get in the way. | ||
+ | |||
+ | |||
+ | |||
+ | ==== Slide # 22: Homo sapiens VDR Olmesartan in LBP (Ligand Binding Pocket) ==== | ||
+ | |||
+ | So we can luckily restore innate immunity by using a VDR agonist. I identified one called olmesartan. And here we have a protein [referring to animation on screen] this is a human VDR—it’s moving all the time—all proteins are in motion all the time. In the binding pocket, there is the olmesartan drug | ||
+ | |||
+ | ==== Slide # 23: Rattus norvegicus VDR Olmesartan in LBP ==== | ||
+ | |||
+ | This is the olmesartan drug here in yellow [referring to animation on screen]. This is actually the rat VDR shown on this particular slide. | ||
+ | |||
+ | ==== Slide # 24: VDR human and rat ==== | ||
+ | |||
+ | I’ll show you the human and the rat side by side, and show you that the two are not the same. The drug behaves differently in the rat and in the human. If you look at this tetrazole ring [referring to slide], you can see it’s in different orientations in the rat, and in the human. In fact there’s two less hydrogen bonds and that’s stabilizing, | ||
+ | |||
+ | So this drug does not perform in the same way in the rat as it does in the human. Big problem of course, because most our studies are still being performed in animals, even though we have the capability of examining //in silico//, at the molecular level, there are very few people doing that at this point. | ||
+ | |||
+ | ==== Slide # 25: Data from Observational Cohort sample of response in Autoimmune Disease ==== | ||
+ | |||
+ | So what happens when you address the problem of the VDR and remove exogenous—that means from outside the body— remove exogenous vitamin D and just allow the body to make the vitamin D it needs, and then at that point the body becomes susceptible to very small amounts of antibiotics—the antibiotics which really did very little when the VDR was overcome by the pathogens, once the VDR has been reactivated again, then the patient starts to respond to antibiotics in the same way that a normal, healthy individual would do. And I’ll be talking more about that this afternoon, when I talk about the protocol that we have put in place to reverse the mechanisms that the bugs have used to overcome our immune systems. | ||
+ | |||
+ | This is the data that was reported at the Autoimmunity Congress in Portugal last September. It shows a small portion of our clinical cohort, observational cohort. Diseases from Rheumatoid Arthritis, Hashimoto’s Thyroiditis, | ||
+ | |||
+ | ==== Slide # 26: Notable outcomes ==== | ||
+ | |||
+ | What was surprising was it wasn’t just the autoimmune conditions that responded to the antibacterial therapy, but also Chronic Fatigue Syndrome—Myalgic Encephalomyelitis, | ||
+ | |||
+ | So as these people got better, all of these things that we never really associated with pathogens—osteoporosis, | ||
+ | |||
+ | The homeostasis of other Type 1 Nuclear Receptors is also indirectly upset by the pathogens. And in particular the thyroid receptors. You’ll notice that we had a lot of people with Hashimoto’s Thyroiditis diagnosis, partly that’s because a lot of people with chronic disease have thyroid problems. Because one of the first things that happens when the VDR stops working, the level of 1, | ||
+ | |||
+ | The reason you can’t get rid of chronic disease by giving people vitamin D is because that vitamin D collects in the body and it starts to hit the other receptors at the same time as it’s overcoming the bacterial effect on the VDR. | ||
+ | |||
+ | **So when people get sick to a certain level, they’ll no longer respond to conventional therapy.** At that point the bacteria are in control. And usually that occurs late in life—except with people that come down with chronic disease—and tragically these days we are seeing even kids coming down with the chronic diseases that they use not to get. | ||
+ | |||
+ | But typically they just cause the ‘diseases of aging’—dementia, | ||
+ | |||
+ | I’ve already mentioned that the loss of Glucocorticoid and Thyroid homeostasis leads to diagnosable disease states. | ||
+ | |||
+ | ==== Slide # 27: Gradual loss of genome integrity ==== | ||
+ | |||
+ | The genomes accumulate gradually during life. Very important—you were born with this microbiota. Depending on what you come in contact with during life, from food, from saliva, from aerosols through the air, and from infections of course. Actual acute infections. Your metagenome will gradually be built up. And so at any point in life it will be different than it was a decade earlier. | ||
+ | |||
+ | The microbiota have access to the DNA transcription machinery. And that’s what I’ve been talking about—taking a strand of DNA and turning it into proteins that can actually do something. | ||
+ | |||
+ | But what’s more important, the DNA repair mechanisms become susceptible to all of this plethora of imponderable effects from the bacterial DNA. So you get modification of the human DNA repair mechanisms by ‘junk’ from the metagenome. HIV integrates itself into the human genome. HHV6 integrates itself into the human genome. There’s a lot of work being done to show that bacteria do the same thing. But you saw in the // | ||
+ | |||
+ | ==== Slide # 28: "Germy mouths linked to heart attacks" | ||
+ | |||
+ | This came out just last week on Reuters, Wednesday, April the 1st, and no, it’s not an April 1st joke. It was reporting a study on heart attacks. I love this word, “germy, | ||
+ | |||
+ | We are talking about a metagenomic--very many genomes--microbiota. | ||
+ | |||
+ | ==== Slide #29: Why have Murine Models failed? ==== | ||
+ | |||
+ | So, the last question. Really, second to last is, “Why have murine models failed?” Now what’s a murine model? That means, mice and rats. When we test these diseases out in mice and rats. Which we nearly always do, before we give it to mankind. | ||
+ | |||
+ | Unfortunately, | ||
+ | |||
+ | In particular, if you look at the VDR homology--and that means the […] in the VDR, the shape in the VDR that’s produced--the VDR of //Homo sapiens// transcribes different genes from the VDR of other mammals. Even the VDR of higher primates. | ||
+ | |||
+ | And in particular, the VDR from the murine and canine (or dog) genomes doesn’t transcribe Cathelicidin, | ||
+ | |||
+ | So the human metagenomic microbiota will not survive when transfected into a mouse. If you take the human microbiota, put it into a mouse, the mouse will be able to deal with it because, it’s VDR isn’t really as important as man’s is. | ||
+ | |||
+ | Different species and different mutations are necessary if the microbiota was to knock out the different gene pathways needed for survival in a mouse. That is one of the fundamental reasons why chronic disease has remained ‘of unknown cause’ for the last 50 years, in my opinion, is the reliance on mouse and rat models, and to a lesser extent on other mammal models. Without really questioning whether a mouse has the same immune system as a human being. | ||
+ | |||
+ | ==== Slide #31: Missing the primary disease mechanism ==== | ||
+ | |||
+ | Until the genome was cracked--until we could crack genomes, until we could sequence the DNA, and figure out exactly what we were dealing with, what made this organism tick, and whether the organism is //Homo sapiens//, or bacteria, or a virus like HIV, something makes that organism tick--and now, we have just started to figure it out. We have decades, maybe a century of figuring out this imponderable problem that I talked about earlier. | ||
+ | |||
+ | But we’ve just started. And until the genome was cracked, we only had the postulates of Koch as a guide. The postulates of Koch have formed the basis for infectious disease--clinical infectious disease at least--for a century. They caused us to look for a single species that was causing the disease process. Koch basically said, you have polio virus, and it causes, polio. Koch basically said, you have single pathogen, and it causes a singular disease. And that’s not what we’re finding. We’re finding is that the human body is a whole pelethora of pathogens, a whole pelethora of genomes, a metagenome. | ||
+ | |||
+ | So science became fixated on the co-infections--Chlamydia, | ||
+ | |||
+ | Well yes, the Chlamydia might very well be making them sick, because Chlamydia has got some very nasty toxins itself. But in order for the immune system to allow that Chlamydia to flourish, they first had to have a suppressed immune system from the metagenomic microbiota. | ||
+ | |||
+ | So for the last century, science became fixated on what are predominantly co-infections and have missed the primary disease mechanism. The primary disease mechanism being the intraphagocytic, | ||
+ | |||
+ | ==== Question: What are the methods for measuring the antimicrobial peptides in humans? ==== | ||
+ | |||
+ | The antimicrobial peptide work that I am relying upon was done by Brahmachary’s group in Singapore. I cite it in all of our papers, actually, I think you’ll find it cited.(({{pmid> | ||
+ | |||
+ | ==== Slide #32: " | ||
+ | |||
+ | This is a slide that just came out last week from a group studying HIV. And what we’ve got here [referring to the animation on the screen] is we’ve got two cells--well a number of cells--but there’s a cell which has been infected with HIV. We have a cell which is brushing up against it. And at the junction of the two cells, the HIV is trying to get through the cell membranes into that [uninfected] cell. And in fact, that’s exactly what’s going to happen. This HIV infection is able to cross the membrane. You can see it frozen there as it’s starting to cross. In a little while you’ll find there will be fluorescent staining inside that cell, or fluorescent artifacts inside that cell to indicate that the tat protein has--there it is, it’s broken off, it’s now inside the other cell. One of the reasons that we don’t find these pathogens in the blood is because they don’t need to be in the blood. They can pass from cell to cell. That’s now been shown in HIV with this very elegant study from March 2009, " | ||
+ | |||
+ | All of this without the bacteria having to have to deal with what’s in the bloodstream. It hasn't had to deal with any antibiotics the patient’s been taking. Because it’s existing totally inside the cytoplasm of the cells. | ||
+ | |||
+ | ==== Question: When you follow the people for saliva samples in the world, do you see local similar profiles, like people from Prague would have certain profiles, but either people from New York would have different samples, or do they look the same? ==== | ||
+ | |||
+ | Firstly, **//I//** don’t follow them. But there have been studies done. The two that come to mind, are the study out of Imperial College in London, where they looked at the urine, they looked at the various proteins that were found in the urine that could not be produced by the human body itself, but were being produced by bacteria which were present in the urine--present in the kidneys, one assumes. And what they found was that there were very distinct grouping—the Japanese population, the Chinese population, and the US population—were all different. And when Japanese moved to the US, their microbiota changed to the US population. Because the food changed, their environment changed, everything changes. So we very much are a product of the bacteria that make us. Now, that was not specifically looking at saliva. | ||
+ | |||
+ | The study from Max Plank that looked at saliva did in fact look at 10 locations throughout the world to make sure that they had good geographic diversity. And if you look up the paper that I cited there you’ll find the detailed data.(({{pmid> | ||
+ | |||
+ | ==== Question: Because there is now a new field of human genomics, then you can track the ‘mother of mother’s’ in Africa, you can see how people moved in Europe, several passages, you can also follow certain tendencies to diseases, such as high blood pressure? ==== | ||
+ | |||
+ | Right. Well, for example, // | ||
+ | |||
+ | // | ||
+ | |||
+ | So we have an incredible opening up of discovery over the next decade or two as we start to get our minds around this concept of a microbiota, a community of pathogens | ||
+ | |||
+ | ==== Comment: Yes, I think that It’s always about the interaction between humans, and that we are exposed to selection criteria, so if we are in an environment where bacteria are and we cannot cope with them we die, only the people that can deal with them, survive. ==== | ||
+ | |||
+ | Yes. Many people are exposed to // | ||
+ | |||
+ | The status of the immune system when that person gets challenged by the acute pathogen that is so important in determining what’s ultimately going to happen during their lives. | ||
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+ | And therefore it’s very important to study the family, to study the maternal line--because these bugs are primarily passed down the maternal line--to study the maternal line, and you will find that a kid who’s got Lupus, had a mother who had arthritis, and grandmother that had thyroiditis. You can see the diseases. Once you realize that all these diseases, the chronic diseases, are inter-related from the same cause, you can track them from within a family, and also horizontally within families as well. | ||
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+ | ===== References ===== |