Copyright Taylor & Francis Group. Do Not Distribute ...anthracis, Yersinia pestis, Mycobacterium tuberculosis) ... microbiota can alter the permeability of the BBB thereby affecting

In previous chapters we have given many examples of the role played by the human microbiota in maintaining human health and well-being. These include influencing tissue development, controlling the induction and maturation of an effective immune system, excluding exogenous pathogens, contributing to our nutritional needs, contributing to our energy requirements and detoxifying potentially dangerous constituents of our diet. We have also indicated the downside of having a microbiota—the ability of some of our symbionts to turn on us and cause disease. Since the formulation of the germ theory of disease, determining the involvement of microbes in human disease has been one of the main driving forces of the science of microbiology. It is not surprising, therefore, that modern-day microbiologists should also show a keen interest in the disease potential of our microbial symbionts. However, we have moved on from the notion that an infectious disease is a simple equation involving the presence of a particular organism and the onset of disease. While there are certainly many examples (Bacillus anthracis, Yersinia pestis, Mycobacterium tuberculosis) of the ability of highly pathogenic microbes from the external environment (including other animals) to cause disease in otherwise healthy individuals, our relationship with our indigenous microbiota from the point of view of disease is more complex. Some members of our microbiota, known as pathobionts (for example N. meningitidis, Strep. pyogenes, Strep. pneumoniae, H. influenzae, and Staph. aureus), are recognized as having considerable disease-causing potential, but other species are less threatening and only cause disease when our defense systems are compromised in some way. We now find that the idea of labeling particular species as being commensal, opportunistic, or pathogenic is less helpful as it is too microbe-centered and fails to give sufficient weight to the status of the host in determining the outcome of any host–microbe interaction. Nevertheless, it is useful to have some assessment of the relative risks of disease posed by individual symbionts and for this

MICROBIAL COMMUNITY DISRUPTION—A ROLE IN OTHER HUMAN DISEASES?

10

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In this chapter:

• The microbiota–gut–brain axis in health and disease

• Microbiota and behavior

• Microbiota and neurodegenerative diseases

• Microbiota and autism spectrum disorders

• Microbiota and cancer

• Microbiota and diabetes

• Microbiota and rheumatoid arthritis

Copyright Taylor & Francis Group. Do Not Distribute.

Chapter 10: Microbial Community Disruption—A Role in Other Human Diseases?428

purpose, a reasonable approach is to use the classification system of the American Biological Safety Association which groups organisms on the basis of their infection risk. Of the bacteria isolated from humans: 94% belong to Risk Group 1 (defined as having no or low individual and community risk), which includes microbes that are unlikely to cause disease in humans; 5% belong to risk Group 2 (defined as having a moderate risk to individuals and a low community risk)—this includes microbes that could cause disease in individuals but are unlikely to spread into the community; and 1% belong to risk Group 3 (defined as having a high individual risk but low community risk)—this includes bacteria that could cause severe or lethal human infections and could be a serious hazard to health-care workers. None of the human isolates are assigned to risk group 4—defined as having a high individual risk and community risk, for which no effective treatment or prophylaxis exists.

However, we are moving away from the idea that a disease is always caused by individual species and are now aware of diseases due to microbial consortia (polymicrobial infections). Disease may also be a consequence of some change in the composition of the community at a particular body site so that it is no longer in a state of harmony with its host—the community is said to be dysbiotic. However, it has to be pointed out that in many cases it has not yet been established whether the dysbiosis observed at a body site during the course of a particular disease is a cause or a consequence of that disease. In many cases all we can really say is that there is an association between the disease and the observed dysbiosis. However, correlation does not necessarily equate to causation. A causative relationship can only be established by unraveling the mechanisms by which a microbial community shift results in the pathology characteristic of that disease.

At this moment in time, research into the human microbiota and its contribution to health and disease is a very exciting field that is attracting considerable attention from researchers, the media, and the general public. The availability of relatively cheap and rapid methods for determining the composition of the various communities that reside on our bodies has facilitated a large number of research projects that focus on the possible roles of our symbionts in a variety of human conditions. In this chapter, we will examine some of the recent suggestions of such associations. It must be remembered, however, that many of these claims are based on only a limited number of investigations involving very small numbers of individuals. They imply some very exciting possibilities, but many may turn out to be unsupported by more extensive investigation.

Is there a microbiota–gut–brain axis?The most recent of these new ideas suggests an involvement of the gut microbiota in various conditions related to the functioning of the central nervous system (CNS). The gut has an extensive neuronal network, known as the enteric nervous system (ENS), which is so large that it has been referred to as our second brain. It has long been known that the CNS and gut influence one another by a variety of neural, endocrine, nutrient, and immunological signals and this has been termed the gut–brain axis. What is now being proposed is that this should be extended to include the gut microbiota so that we have a microbiota–gut–brain axis (Figure 10.1). The core feature of this concept is that there is a bi-directional interaction involving diverse mechanisms.

There are a number of pathways in the microbiota–gut–brain axis that enable bi-directional communication between the microbiota and the CNS. Firstly, the microbiota is known to stimulate the release of various cytokines and chemokines. These not only affect the composition of the microbiota but can also alter the integrity of the gut epithelium, interact with the CNS via neuronal receptors and can enter the systemic circulation where they can induce a variety of immune responses. Secondly, some members of the


429Does the Gut Microbiota Influence Human Behavior?

microbiota are able to produce neuroactive substances such as catecholamines, histamine, γ-aminobutyric acid, serotonin, and SCFAs. These compounds can influence the CNS by interacting with neuronal receptors in the GIT or in the brain following their absorption into the bloodstream and crossing the blood–brain barrier (BBB). Thirdly, the gut microbiota can alter the permeability of the BBB thereby affecting the uptake of various immune mediators and microbial metabolites facilitating their interaction with the brain. Finally, the nerves of the ENS have been shown to express a number of Toll-like receptors (TLRs), including TLR2, 3, 4, and 7, which enable direct stimulation of the CNS by microbes and their components. The CNS can, of course, affect the GIT in a number of ways. By means of the vagus nerve it controls the mechanical mixing of food in the stomach, coordinates muscle contractions to propel food along the rest of the GIT, maintains the correct environment within different sections of the gut to enable digestive enzymes to function optimally, and controls glandular secretion. All of these actions will, of course, affect the composition of the gut microbiota. In addition, some of the compounds produced by the CNS such as catecholamines have been shown to influence bacterial growth and the production of virulence factors.

Does the gut microbiota influence human behavior?A number of studies have investigated the possible involvement of the gut microbiota in the regulation of animal behavior. The behavior of germ-free animals has been found to differ in several respects from that of conventionally raised animals and it has also been shown that restoration of their microbiota, or the administration of probiotics, can reverse these differences. Furthermore, administration of probiotics can also affect the behavior of conventionally raised animals. The results of some of these studies are summarized in Table 10.1.

Healthystatus

• Normal gutmicrobiota

• Healthy levels ofinflammatory cellsand/or mediators

• Normal brainfunction

Healthy CNSfunction

Healthy gutfunction

Abnormal CNSfunction

Abnormal gutfunction

Increased gutpermability

• Intestinal dysbiosis

• Altered levels of LPS,inflammatory cellsand/or mediators

• Alterations in brainfunction

Figure 10.1. The microbiota–gut–brain axis in health and disease. (From van Hemert S et al. (2014). Front Neurol 5:241. doi: 10.3389/fneur.2014.00241. Published under CC BY 4.0.)

Table 10.1. Studies of the effects of the indigenous microbiota on animal behavior.

TREATMENT BEHAVIORAL EFFECTSAdministration of Bif. breve, Bif. longum, Lactobacillus helveticus or L. rhamnosus to normal, conventionally reared mice

Reduced anxiety-like behavior

Colonization of germ-free mice with gut microbiota of normal mice

Increased exploratory behavior

Administration of Bif. infantis to germ-free rats

Reversed the reduced familiar social recognition observed in the germ-free animals

Administration of Bif. infantis to germ-free mice

Reversed the increased stress response seen in the germ-free animals

Re-colonization of germ-free mice with gut microbiota

Reversed the increased social avoidance seen in the germ-free animals



A limited number of studies in humans have also reported probiotic-induced behavioral changes and the results of such studies are summarized in Table 10.2.

Whether or not the probiotics themselves, or changes (if any) induced in the gut microbiota by probiotic consumption, were responsible for the observed behavioral changes remains to be established. It is important to bear in mind that the number of studies carried out so far is small and that these have not involved large numbers of participants.

Does the microbiota play in role in neurodegenerative diseases?Parkinson’s disease (PD) is the second most common neurodegenerative disorder of aging, and is projected to affect nearly 10 million people by 2030. A diagnostic feature of PD is the presence of neuronal inclusions termed Lewy bodies (Figure 10.2) which contain aggregates of α-synuclein and these are responsible for the neurological symptoms of the disease. α-synuclein filaments may also be deposited in some of the neurites (axons or dendrons) of the neurons of affected individuals—these are known as Lewy neurites (see Figure 10.2).

It is thought that the aggregates result from oxidative injury but the source of this is not known. It has been suggested that the GIT is a major site and source of oxidative stress in neuronal tissue because it is the largest interface between neural tissue and the environment, it has an extensive neuronal network, and this network is in close proximity to the gut microbiota which contains products, such as lipopolysaccharide (LPS), capable of inducing oxidative stress. PD subjects have been shown to have significantly greater intestinal permeability than controls, have increased levels of mucosa-associated E. coli (Figure 10.3), and increased concentrations of LPS-binding protein, which is indicative of exposure to high levels of LPS. It has been suggested that LPS, a well-known inducer of pro-inflammatory modulators, stimulates the enteric immune system to promote local oxidative stress which results in α-synuclein misfolding, aggregation and subsequent neuronal damage in the ENS.

Recently, it has also been shown that PD is accompanied by a dysbiosis of the gut microbiota in which there are elevated proportions of a number of

Table 10.2. Effects of probiotic administration on human behavior.

TREATMENTNUMBER AND TYPE OF SUBJECTS BEHAVIORAL EFFECTS

Daily consumption for 30 days of L. helveticus and Bif. longum

Healthy volunteers; 26 test and 29 controls

Displayed reduced levels of depression and anger–hostility compared to controls

Daily consumption for 3 weeks of L. helveticus fermented milk

29 elderly subjects Significant improvement in sleep efficiency and decreased number of wakening episodes

Daily consumption for 3 weeks of a milk containing L. casei

Healthy volunteers; 62 test, 62 controls

Improved the mood of those whose mood was initially poor

Daily consumption for 2 months of L. casei

19 test subjects with chronic fatigue syndrome, 16 controls

Significant decrease in anxiety symptoms compared to controls; significant increase in proportions of Lactobacillus and Bifidobacterium in feces of test subjects

Daily consumption for 4 weeks of a probiotic containing Bif. bifidum, Bif. lactis, L. acidophilus, L. brevis, L. casei, L. salivarius, and L. lactis

Healthy volunteers; 20 test, 20 controls

Reduced aggressive and ruminative thoughts associated with sad mood


431Does the Microbiota Play in Role in Neurodegenerative Diseases?

taxa including Ruminococcaceae and Clostridiales incertae sedis IV but decreased proportions of Prevotellaceae (Figure 10.4). At least two other studies have also confirmed a decreased proportion of Prevotellaceae in the gut microbiota.

Alzheimer’s Disease (AD) is an irreversible, progressive brain disorder that involves the loss of cognitive functions and usually first appears in those who are over the age of 65 years. It is the most common cause of dementia among older adults and affects more than 46 million people worldwide—this is estimated to increase to 131.5 million by 2050. A number of studies have implied a link between the oral microbiota and AD. Oral bacteria and species closely related to those found in the oral cavity have been found at a higher frequency postmortem in the brains of patients with AD than in those of patients who did not have AD. The most frequently detected species are various spirochetes belonging to the genus Treponema—T. denticola, T. pectinovorum (Figure 10.5), T. vincenti, T. amylovorum, T. maltophilum, T. medium, and T. socranskii—which are found in elevated proportions in the dysbiotic subgingival microbiota associated with periodontitis.

Furthermore, epidemiological studies have shown a link between poor cognitive performance and tooth loss, and tooth loss has been associated with an increased risk of both dementia and cognitive decline. However, a confounding factor is that dementia and cognitive impairment are likely to result in poor oral hygiene (resulting in eventual tooth loss) in patients suffering from these conditions, which means that oral dysbiosis could be a consequence, rather than a cause, of AD. In a longitudinal study of the serum levels of antibodies against a range of oral bacteria in elderly individuals, high levels of antibodies to A. naeslundii were found to be associated with a high risk of AD while high levels of antibodies to Eub. nodatum were associated with a low risk of AD. A lower level of Fusobacteriaceae and a

(A) (B)

(C) (D)

Figure 10.2. Photomicrograph of two regions of the midbrain in a patient with Parkin-son’s disease showing Lewy bodies and Lewy neurites. The left-hand and right- hand panels are from different regions of the midbrain. The presence of Lewy bodies and neurites (red/brown-stained structures) has been revealed by immunohistochemical staining using monoclonal antibodies to α-synuclein. Top panels (A and B) show a ×60 magnification of the Lewy bodies. The bottom panels (C and D) are ×20 magnification images that show rounded Lewy bodies of various sizes as well as Lewy neurites (filamentous structures). (Courtesy of Suraj Rajan published under CC BY-SA 3.0.)

(A)

(B)

(C)

Figure 10.3. Immunohistochemical staining of intestinal biopsies for E. coli (brown-staining regions). (A, B) Representative images from a patient with Parkinson’s disease at magnifica-tions of ×10 and ×40, respectively. (C) A healthy control subject at a magnification of ×40. Staining intensity is far greater in the case of the patient with Parkinson’s disease. (From Forsyth CB et al. (2011). PLOS ONE 6:e28032. doi:10.1371/journal.pone.0028032. Published under CC BY 4.0.)



higher level of Prevotellaceae have been reported in the subgingival plaque of a small group of patients with dementia compared with healthy controls.

Multiple sclerosis (MS) is a condition that can affect the brain and/or the spinal cord and results in a wide range of possible symptoms including fatigue and problems with vision, movement, sensation, or balance. It is a life-long condition and affects approximately 2.5 million people worldwide. Animal studies have suggested a role for the gut microbiota in MS but few studies have been carried out in humans. MS patients have been found to have lower levels of Faec. prausinitzii (Figure 10.6) in their feces compared with healthy controls. Faec. prausinitzii is a well-known producer of butyrate, which has anti-inflammatory properties, and the low levels of butyrate in Faecalibacterium-deficient MS patients may contribute to the condition. Interestingly, administration of vitamin D, which is frequently used in the treatment of MS, resulted in increased levels of Faec. prausinitzii. Another study found that MS patients have high levels of Meth. smithii in their feces, but low levels of the butyrate-producing organisms Butyricimonas and Lachnospiraceae. A number of other studies found a reduction in Bacteroidetes and Firmicutes in the feces of MS patients and these are important in the production of butyrate and other SCFAs.

Is the gut microbiota involved in autism spectrum disorders?Autism spectrum disorders (ASDs) are a group of conditions characterized by a range of behavioral, communication, and social disorders. Asperger’s

0 5 10 15 20 25 30 35 40

Prevotellaceae

Lactobacillaceae

Verrucomicrobiaceae

Bradyrhizobiaceae

Clostridiales incertae sedis IV

Ruminococcaceae

Proportion of sequences (%)

ControlPatients

Figure 10.4. Fecal microbiota of 72 patients with Parkinson’s disease and 72 healthy controls as determined by 16S rRNA gene sequencing. The figures show the proportions of sequences of those taxa that showed a significant difference between patients and controls.

10 µm

Figure 10.5. Section from an 84-year-old female subject with Alzheimer’s disease showing the presence of Treponema pectinov-orum (arrows) stained dark blue following immunostaining using antibodies against the organism. (From Riviere GR et al. (2002). Oral Microbiol Immunol 17:113–118. Copyright Wiley-VCH Verlag GmbH & Co. KGaA. Reproduced with permission.)

(A) (B)

Figure 10.6. Faec. prausnitzii. (A) Scanning elec-tron micrograph showing long bacilli (approxi-mately 2 µm) with rounded ends and a number of characteristic budlike protrusions from the cell wall (arrowed). (B) Higher magnification image showing the budding more clearly. ([B] Reprinted from Miguel S et al. Curr Opin Microbiol 16:255–261, doi:10.1016/j.mib.2013.06.003, Copyright 2013, with permission from Elsevier.)


433Is the Microbiota Involved in Some Cancers?

syndrome is one well-known example of an ASD. They affect approximately 1% of the population—males are four times more likely to be affected than females. Studies of children with ASDs have found that between 24% and 70% have some disturbance of the GIT such as diarrhea, constipation, bloating, or abdominal pain. These findings have prompted researchers to investigate a possible link between the microbiota of the GIT and ASDs. A number of studies have shown that the gut microbiota of children with ASDs differs from that of healthy controls but there is little agreement between these studies with regard to the nature of the dysbiosis (Table 10.3). A possible confounding factor is that children with ASDs are often fussy eaters and may not have a balanced diet and this could also affect the composition of the gut microbiota.

A number of metabolomic studies of children with ASD have been carried out and these have usually involved determining the metabolites present in urine or blood. The main findings are:

• ASD children have increased urinary concentrations of tartaric acid (2, 3-dihydroxybutanedioic acid), d-mannitol, hippurate, phenyacetylglu-tamine, 3-hydroxybenzoic acid, and p-hydroxyphenylacetic acid.

• In ASD children there is a decrease in the conversion of tryptophan to melatonin.

• A number of metabolites associated with tricarboxylic acid cycle (citric acid, succinic acid, cis-acotinic acid, and β-hydroxybutyric acid) are altered in ASD patients, suggesting that mitochondrial dysfunction may be a crucial risk factor for autism.

Investigations of the possible role of the microbiota in ASDs are still at a very early stage and the absence of a consensus on the nature of the dysbiosis accompanying the condition has hindered progress and makes it difficult to postulate on the underlying mechanisms involved in the pathology of the condition.

Is the microbiota involved in some cancers?The role of Hel. pylori in gastric cancer and lymphomas is well established (see Chapter 9) but a number of studies have found a correlation between dysbiosis and cancer at other body sites and these are summarized in Table 10.4.

The cross-sectional nature of the studies summarized in Table 10.4 limits their value and, furthermore, most of them involved only small numbers of subjects. There is a need for much larger, longitudinal studies. The evidence for an involvement of the human microbiota in cancer is strongest in the case of colorectal cancer although the mechanisms involved have not been elucidated.

Table 10.3. Studies of the fecal microbiota of children with ASDs.

NATURE OF STUDYOBSERVED DYSBIOSIS IN THE FECAL MICROBIOTA

19 children with ASD and 20 healthy controls

Lower abundance of Prevotella, Coprococcus, and unclassified Veillonellaceae in ASD subjects


No difference between patients and controls


Increased proportions of Desulfovibrio, Parabacteroides, and Bacteroides; decreased proportions of Turicibacter, Clostridium, Weissella, Anaerofilum, Ruminococcus, Streptococcus, and Dialister in ASD subjects


Increased proportions of Clostridium and Ruminococcus in ASD subjects


Increased proportions of Clostridium, Alistipes, Akkermansia, Caloramator, and Sarcina; decrease in Prevotella, Eubacterium siraeum, and Bifidobacterium



Is the gut microbiota involved in Type I diabetes?Type 1 diabetes mellitus (DM) is a chronic immune-mediated disease characterized by the loss of insulin-producing β cells in the pancreas. Insulin is a hormone that controls the concentration of glucose in the blood and a deficiency results in high blood glucose levels—hyperglycemia. The disease affects between 20 and 40 million people worldwide. DM can develop at any age but usually appears before the age of 40, especially in childhood and is the most common type of diabetes found in children. Patients with DM must receive daily injections of insulin.

The few studies that have been carried out to date indicate that the intestinal microbiota of individuals with DM is different to that of healthy individuals, and most studies have reported increased proportions of Bacteroidetes (Table 10.5).

Once again, as in many examples of dysbioses, it remains to be established whether the observed changes in the composition of the gut microbiota are a cause or consequence of DM.

Is the gut microbiota involved in Type 2 diabetes?Type 2 diabetes (T2D) is a metabolic disorder in which the pancreas does not produce sufficient insulin and/or the body’s cells fail to react to the

Table 10.4. Studies reporting an association between cancer and dysbiosis.

CONDITION NUMBER OF SUBJECTS INVOLVED MAIN FINDINGSEsophageal cancer 142 subjects with esophageal squamous dysplasia

and 191 withoutDecreased microbial richness (in terms of the number of bacterial genera) in the esophageal microbiota of patients with esophageal squamous dysplasia, which is a precursor to esophageal squamous cell carcinoma

Pancreatic cancer 10 subjects with pancreatic cancer and 10 healthy controls

Proportions of Neisseria elongata and Strep. mitis were significantly decreased in the saliva of patients with pancreatic cancer relative to healthy controls

Lung cancer 8 subjects with lung cancer and 8 healthy controls Proportions of Granulicatella, Abiotrophia, and Streptococcus in sputum were increased in patients compared with controls

Colorectal cancer 7 different studies involving 291 patients with colorectal cancer and 386 healthy controls

High prevalence and levels of Fusobacterium and Porphyromonas, and lower levels of Ruminococcus in the feces of patients compared with controls

Breast cancer 48 postmenopausal women with breast cancer and 48 controls

Lower community diversity in the gut microbiota of patients compared with controls

Table 10.5. Examples of studies comparing the fecal microbiota of patients with Type I diabetes with that of healthy controls.

STUDY PARTICIPANTS MAIN FINDINGS18 patients and 18 controls • Reduced abundance of lactate-producing bacteria

and butyrate-producing bacteria in the patients• Decreased abundance of two dominant

Bifidobacterium species and an increased abundance of Bacteroides in the patients

21 patients and eight controls • Patients had an increased abundance of Bacteroides, whereas controls had a higher abundance of Prevotella

28 patients and 27 controls • Patients had increased microbial diversity and a reduced fraction of butyrate-producing species within Clostridium clusters IX and XIVa

16 patients and 16 controls • In patients the Firmicutes to Bacteroidetes ratio was decreased

• Patients had increased proportions of Clostridium, Bacteroides, and Veillonella and a decrease in Lactobacillus, Bifidobacterium, the Blautia coccoides–Eub. rectale group, and Prevotella


435Are the Oral and Gut Microbiotas Involved in Rheumatoid Arthritis?

insulin produced. Although there is a genetic predisposition to T2D, it is caused mainly by obesity and lack of exercise. The incidence of T2D has more than doubled since 1980, with over 382 million affected individuals worldwide, in conjunction with an increase in obesity rates and the spread of a Western lifestyle.

A number of studies have reported an association between T2D and dysbiosis of the fecal microbiota (Table 10.6).

The results of these and other studies generally agree that in the fecal microbiota of patients with T2D there is a reduction in the proportions of members of the Firmicutes (mainly Clostridium, Eub. rectale, Faec. prausnitzii, Roseburia, and Akkermansia muciniphila) and an enrichment in the Betaproteobacteria, Desulfovibrio, and some lactobacilli. Furthermore, the proportions of Betaproteobacteria positively correlates with blood glucose levels in patients with T2D. Butyrate, an important metabolite of many Firmicutes, is known to play a role in regulating human mitochondrial function, energy generation, glucose metabolism, and lipid metabolism. Changes in butyrate concentrations in the GIT as a result of dysbiosis may, therefore, be a contributing factor in T2D and obesity.

Are the oral and gut microbiotas involved in rheumatoid arthritis?Rheumatoid arthritis (RA) is a chronic, inflammatory autoimmune disease that results in painful and swollen joints—usually in the hands, wrists, and feet. It affects approximately 1% of the population but over 30% of individuals are over the age of 65 years. It is characterized by the presence of specific autoantibodies—rheumatoid factor and anti-citrullinated protein antibodies (ACPAs). Studies have investigated the possible involvement of both the gut and oral microbiotas in RA.

The results obtained from studies of the gut microbiota show little agreement. Some studies have reported an increased diversity in the fecal microbiota of patients with RA while others found a decrease in diversity. There are reports of decreased levels of Bifidobacterium and Bacteroides as well as increased proportions of Collinsella, Eggerthella, Prev. copri, and Faecalibacterium.

In contrast, there is considerable evidence in support of an association between RA and dysbiosis of the oral microbiota. The involvement of the oral microbiota, particularly the microbiota that is associated with periodontitis, in RA has been studied for many years. Both periodontitis and RA have several features in common: they are chronic inflammatory

Table 10.6. Examples of studies comparing the fecal microbiota of patients with Type 2 diabetes with that of healthy controls.

PARTICIPANTS MAIN FINDINGS173 patients with T2D and 173 controls Compared with controls, patients had:

• Moderate degree of dysbiosis• Decrease in the abundance of some butyrate-producing bacteria• Increase in various opportunistic pathogens

18 patients with T2D and 18 controls Compared with controls, patients had:• Lower abundance of Firmicutes• Higher proportion of Bacteroidetes• Higher proportion of Proteobacteria

53 women with T2D and 43 controls Compared with controls, patients had:• Increased proportions of L. gasseri, L. salivarius, L. antri, Lactobacillus oris, Cl. clostridioforme, and

Strep. mutans• Decreased proportions of Clostridium thermocellum, Clostridium botulinum, and Clostridium

beijerinkii

50 women with T2D and 50 controls Compared with controls, patients had:• Increased proportions of L. reuteri and other Lactobacillus spp.• Decreased proportions of Cl. coccoides group, Atopobium cluster, and Prevotella



conditions; they are characterized by high levels of cytokines, matrix-metalloproteinases, neutrophil-derived mediators, and oxidative stress; and they have a number of contributory factors in common such as smoking and low socio-economic status. Many studies have shown that there is a high incidence of periodontitis in patients with RA. Furthermore, in a recent review and meta-analysis of 17 studies involving 153,492 participants the authors concluded that there was a significant association between RA and periodontitis. There is also evidence that treatment of periodontitis is accompanied by a reduction in the symptoms of RA. However, a confounding factor is that patients with arthritis of the hands and/or wrists have a reduced ability to clean their teeth properly and this could eventually result in periodontitis, that is, periodontitis is a consequence, rather than a cause, of RA.

The etiology of RA involves an autoimmune response to citrullinated proteins and the presence of antibodies (anti-citrullinated protein antibodies—ACPAs) is diagnostic of the condition. Citrullinated proteins result from the action of peptidyl-arginine-deiminases (PADs) that convert peptidyl-arginine residues to peptidyl-citrulline on various proteins including α-enolase, keratin, fibrinogen, fibronectin, collagen, and vimentin. The loss of tolerance to these new epitopes results in the production of ACPAs and this auto-immune response results in the chronic inflammation characteristic of RA. One of the organisms whose proportions increase during the dysbiosis accompanying periodontitis is Por. gingivalis (Figure 10.7). This bacterium is the only species known to produce a PAD and has been shown to citrullinate fibrinogen, enolase, vimentin, and collagen. There is also evidence that some of the oral organisms in the dysbiotic community associated with periodontitis can directly cause damage to the joints in RA. DNA belonging to a number of bacterial species has been found in the synovial fluid of patients with RA including Por. gingivalis, Eub. saburreum, Parvimonas micra (formerly Peptostreptococcus micros), A. israelii, Selenomonas noxia, P. acnes, Camp. showae, Tan. forsythia, Cap. sputigena, Lep. buccalis, and Prev. intermedia.

KEY CONCEPTS• Dysbiosis is associated with a number of human diseases.

• In many cases it has not been established whether the dysbiosis associated with a disease is a cause of that disease or a consequence of it.

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2 µm

Figure 10.7. Scanning electron micrograph of Por. gingivalis. (From Zhu Y et al. (2013) PLOS ONE 8: e71727. doi:10.1371/journal.pone.0071. Published under CC BY 4.0.)


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