Patent Application
20140086954
The present invention relates to the use of the bacterial flora for vaccine development, identification of therapeutic targets and prediction and/or diagnosis of metabolic diseases, such as diabetes, overweight and obesity, and their cardiovascular complications. In particular, the present invention provides immunogenic or vaccinal composition for preventing metabolic diseases and cardiovascular complications using attenuated or inactivated bacterial flora, or antigens derived thereof. The present invention also provides methods for identifying prognostic markers for metabolic diseases onset and cardiovascular complications and methods for in vitro prognosis of metabolic diseases and cardiovascular complications using bacterial flora.
Metabolic diseases, such as diabetes, overweight and obesity, both in developed and emerging countries have reached epidemic proportions. The set-up of a low tonus but chronic metabolic-type inflammatory reaction is one of the cellular mechanisms that appear early during the development of these diseases. The active molecules which are released by the inflammatory process lower the insulin action and secretion of insulin or any metabolically active hormone, impair the nervous system and favour the development of fat tissue and atheroma plaques leading to cardiovascular complications.
A body of evidence demonstrates that the intestinal microbiota, which corresponds to the overall bacterial community present in the intestine, and their corresponding expressed genes, which define the microbiome, play a role in the onset of metabolic diseases such as diabetes and obesity (Turnbaugh et al., Nature, 2006, 444:1027-31; Turnbaugh et al., Nature, 2009, 457:480-4; Cani et al., Diabetes, 2007, 56:1761-72). The causal role of the intestinal microbiota on weight gain was demonstrated in experiments in which germ-free mice colonized with intestinal microbiota from genetically obese ob/ob mice gained more weight than their counterparts colonized with microbiota from lean animals (Turnbaugh et al., Nature, 2006, 444:1027-31). In humans, Turnbaugh et al. showed that obesity is associated with phylum-level changes in the gut microbiota and reduced bacterial diversity (Turnbaugh et al., Nature, 2009, 457:480-4). Furthermore, it has been demonstrated that gut microbiota affects energy balance by influencing the efficiency of calorie harvest from the diet and the way this harvested energy is used and stored (Turnbaugh et al., Nature, 2006, 444:1027-31). In addition, the role of bacterial components within blood in relation to weight and glucose metabolism has also been demonstrated: mice fed normally and chronically infused with a low dose of lipopolysaccharides (LPS) developed inflammation, diabetes and obesity whereas mice carrying a deletion in the gene for CD14, a component of the principal receptor for bacterial LPS, did not (Cani et al., Diabetes, 2007, 56:1761-72). Interestingly, in humans, plasma LPS concentrations are increased in apparently healthy subjects eating a high-fat diet (Amar et al., Am J Clin Nutr., 2008, 87:1219-23). Moreover, the concentration of bacterial DNA such as 16S rDNA and LpxB DNA in the blood of a subject has been proved to be a reliable risk marker and a predictor of metabolic and/or cardiovascular diseases (WO/2010/092164).
It is predicted that the number of diabetic patients will increase from 285 million adults in 1997 to about 439 million in 2025 (Shaw et al., Diabetes Res Clin Pract., 2010, 87:4-14). Therefore, it is of utmost importance to detect those at risk of metabolic diseases at an early stage, when lifestyle modifications may be efficient and easier to install. In this respect, the current recognized risk factors for diabetes, such as central adiposity or high fasting blood glucose, are markers of an advanced stage of metabolic disease. Furthermore, there is a need for markers of diabetes, overweight and obesity risk that are independent of metabolic features in order to generate new concepts for therapeutic strategies. Due to the deleterious impact of these metabolic diseases and their cardiovascular complications in human health, there is a need to develop vaccination strategies for these diseases and complications and to find parameters which allow their prognosis.
In this study, the inventors surprisingly identified that the bacterial DNA present in blood or in subcutaneous adipose tissue and more broadly in any tissue can be the basis for the development of prognostic or diagnostic biomarkers of metabolic diseases onset. The inventors observed that the presence of 16S rDNA gene concentration of a specific phylum, family or genus of bacteria could be a prognostic or diagnostic marker of diabetes, overweight, obesity and morbide obesity. On the basis of these results, they demonstrated that specifically identified phyla, families and/or genera of bacteria can be the support to vaccination strategies against metabolic diseases.
In the context of the invention, a “metabolic disease” denotes a disease that disrupts normal metabolism. Preferably, the metabolic disease according to the invention is a carbohydrate metabolism disorder.
As used herein a “carbohydrate metabolism disorder” denotes a disease wherein the metabolism of carbohydrate, for example of glucose, is disrupted. Carbohydrate metabolism disorders include diabetes, high fasting glycemia, overweight, obesity and morbide obesity.
As used herein, “diabetes” denotes a syndrome of disordered metabolism, usually due to a combination of hereditary and environmental causes, resulting in a concentration of glucose in plasma superior to 7 mmol/L.
“Overweight”, “obesity” and “morbide obesity” are defined as abnormal or excessive fat accumulation that may impair health. Body mass index (BMI) is a simple index of weight-for-height that is commonly used in classifying overweight and obesity in adult populations and individuals. It is defined as the weight in kilograms divided by the square of the height in meters (kg/m2). “Overweight” is defined by a BMI equal to or more than 25, “obesity” as a BMI equal to or more than 30 and “morbide obesity” as a BMI equal to or more than 40.
In the context of the invention, a “cardiovascular complication” refers to a disease that results from the onset of a metabolic disorder and affects the heart or blood vessels (arteries and veins). More particularly, a cardiovascular complication according to the invention denotes a disease, lesion or symptom associated with an atherogenesis process that affects the cardiovascular system. It includes especially the conditions in which an atheroma plaque develops as well as the complications due to the formation of an atheroma plaque (stenosis, ischemia) and/or due to its evolution toward an acute ischemic stroke (thrombosis, embolism, infarction, arterial rupture).
Cardiovascular complications include coronary artery disease, coronary heart disease, hypertension, atherosclerosis, in particular iliac or femoral atherosclerosis, angina pectoris, thrombosis, heart failure, stroke, vascular aneurysm, vascular calcification, acute coronary syndromes such as myocardial infarction, vascular stenosis and infarction, and vascular dementia. Preferably, the cardiovascular disease according to the invention is selected from the group consisting of coronary artery disease, hypertension, atherosclerosis, vascular aneurysm, vascular calcification, vascular dementia and heart failure. More preferably, the cardiovascular disease according to the invention is atherosclerosis. Most preferably, the cardiovascular disease according to the invention is atherosclerotic carotid plaques.
In the context of the invention, “bacterial DNA” refers to a DNA belonging to any bacteria. In particular, a bacterial DNA according to the invention denotes a DNA sequence from the genome of a bacterium.
Preferably, the bacterial DNA is 16S rDNA. More preferably, the bacterial DNA is the V2 region of 16S rDNA.
As used herein, “16S rDNA” refers to the gene encoding the 16S ribosomal RNA (16S rRNA DNA) constituted of about 1500 nucleotides, which is the main component of the small prokaryotic ribosomal subunit (30S). 16S rDNA is highly conserved among bacteria.
As used herein, V2 region of 16S rDNA refers to an hypervariable region of the 16S rDNA that can provide species-specific signature sequences useful for bacterial identification.
As used herein, a “biological sample” denotes a biological tissue, such as an intestine tissue, or its content, an adipose tissue, liver, muscles, etc, or a body fluid such as saliva, urines, blood, plasma, serum. In a preferred embodiment, the biological sample is a sample of intestine or subcutaneous adipose tissue or vascular stroma of subcutaneous tissue or blood or plasma.
As used herein, the term “subject” denotes a non-human mammal or a human. Preferred non-human mammals include primates, rodents, such as mouse or rat, feline, canine, bovine and ovine. More particularly, the subject is a human, in particular a child, an adult, a woman or a man.
The invention provides a method for identifying a phylum, family and/or genus of bacteria, which is a prognostic marker of metabolic diseases, and optionally of cardiovascular complications, which method comprises the steps consisting of:
Preferably, the metabolic disease is selected from the group consisting of diabetes, overweight, obesity and/or morbide obesity.
The bacteria quantity may be determined by quantifying the amount of bacterial DNA and more preferably the bacterial 16S rDNA gene by methods known to the one skilled in the art such as for example by quantitative polymerase chain reaction (PCR), most preferably by real-time quantitative PCR. More preferably, the V2 variable region of 16s rDNA gene is quantified by quantitative PCR.
Preferably, when the amplification is performed by PCR, a reporter that produces fluorescence, such as SYBR Green and “universal primers” referring to primers comprising a sequence which is able to hybridize to 16S rDNA from essentially any origin, are used. In a preferred embodiment, the “universal primers” according to the invention are the forward eubac-F primer of sequence 5′-TCCTACGGGAGGCAGCAGT-3′ (SEQ ID NO: 1) and the reverse eubac-R primer of sequence 5′-GGACTACCAGGGTATCTAATCCTGTT-3′ (SEQ ID NO: 2). In another preferred embodiment, the “universal primers” according to the invention are the forward F-Bact1369 primer of sequence 5′-CGGTGAATACGTTCCCGG-3′ (SEQ ID NO: 3) and the reverse R-Prok1492 primer of sequence 5′-TACGGCTACCTTGTTACGACTT-3′ (SEQ ID NO: 4).
According to the method of the invention, in step a) the quantification of bacteria is performed in a biological sample of a subject healthy at the time of sampling and who developed a metabolic disease and optionally cardiovascular complications within a ten year period after sampling, preferably within a 9, 8, 7, 6, 5, 4, 3, 2 or 1 year period after sampling.
The method according to the invention also involves comparing the quantified bacteria with the bacteria of a control. The “control” denotes a subject who was healthy at the time of sampling and who did not developed a metabolic disease within at least a 3, 6 or 9 year period after sampling and preferably at least within a ten year period of sampling.
Identification of phyla, families and/or genera which are present in different proportions within the sample assayed in step a) and the control may be performed by sequencing the V2 variable region of 16s rDNA gene after its amplification by quantitative PCR. In a preferred embodiment, the said identification of phyla, families and/or genera is performed by pyrosequencing the V2 variable region of 16s rDNA gene. In a preferred embodiment, the primers are the forward primer of sequence 5′-AGAGTTTGATCMTGGCTCAG-3′ (SEQ ID NO: 5) and the reverse eubac-R primer of sequence 5′-GTCGCCTCCCGTAGGAGT-3′ (SEQ ID NO: 6).
Identification of phyla, families and/or genera of bacteria which are present in different proportions within the sample assayed in step a) and the control means that the quantity of phyla, families and/or genera of bacteria assayed in step a) is significantly inferior or superior to the quantity of phyla, families and/or genera of bacteria in the control. By “significantly” is intented to denote a measurable and statistically significant difference. Alternatively, a significant difference may denote an at least 1%, 2%, 3%, 4%, 5%, 10%, 15%, 20% difference in the proportions of bacteria of a phylum, a family or a genus between control and sample assayed.
Preferably the control sample is the same type of sample than the analyzed biological sample of step a). For example, if the biological sample of step a) is blood, the control sample is blood.
Preferably, if said metabolic disease is diabetes, then the biological sample of step a) and the control sample are blood samples or biopsy of subcutaneous adipose tissue.
Preferably, if said metabolic disease is overweight, obesity or morbide obesity, the biological sample of step a) and the control sample are biopsy of subcutaneous adipose tissue, and more preferably are samples of vascular stroma of subcutaneous adipose tissue.
The inventors identified that apparently healthy patients, who will develop a metabolic disease, and optionally cardiovascular complications, differ from controls healthy individuals, who will not develop a metabolic disease, by the presence of a higher 16s rDNA gene concentration of specific phyla, families and/or genera of bacteria.
Thus, the invention further provides an in vitro method for prognosing a metabolic disease and optionally cardiovascular complications, which method comprises the steps consisting of:
Preferably, the metabolic disease is selected from the group consisting of diabetes, overweight, obesity and/or morbide obesity.
The bacteria quantity may be determined by quantifying the amount of bacterial DNA and more preferably the bacterial 16S rDNA gene by methods known to the one skilled in the art such as for example by quantitative PCR, most preferably by real-time quantitative PCR. More preferably, the V2 variable region of 16s rDNA gene is quantified.
According to the method of the invention, in step a) the quantification of bacteria is performed in a biological sample of a subject healthy at the time of sampling.
The method according to the invention also involves comparing the quantified bacteria with the bacteria of a control. The “control” denotes a subject who was healthy at the time of sampling and who did not developed a metabolic disease within at least a 3, 6 or 9 year period after sampling and preferably at least within a ten year period of sampling.
Identification of phyla, families and/or genera which are prognostic markers and which are present in different proportions within the sample assayed in step a) and the control may be performed by sequencing the V2 variable region of 16s rDNA gene after its amplification by PCR.
Preferably said phyla of bacteria which are prognostic markers of metabolic disease onset and optionally of cardiovascular complications are prognostic markers of diabetes, overweight, obesity and/or morbide obesity. Preferably said phyla of bacteria which are prognostic markers of diabetes, overweight, obesity and/or morbide obesity are selected from the group consisting of Proteobacteria and Firmicutes. More preferably, the Proteobacteria phylum is a prognostic marker of diabetes onset, overweight onset, obesity onset and/or morbide obesity onset and the Firmicutes phylum is a prognostic marker of overweight onset, obesity onset and/or morbide obesity onset. Preferably said families of bacteria which are prognostic markers of metabolic disease and optionally of cardiovascular complications are prognostic markers of diabetes, overweight, obesity and/or morbide obesity. Preferably said families of bacteria which are prognostic markers of diabetes are any of families of the Proteobacteria phylum, and said families of bacteria which are prognostic markers of overweight, obesity and/or morbide obesity are any of the families of the Proteobacteria phylum and/or the Firmicutes phylum. More preferably, said families which are prognostic markers of diabetes, overweight, obesity and/or morbide obesity are selected from the group consisting of Burkhloderiaceae, Pseudomonaceae, Oxalobacteriaceae, Neisseriaceae, Enterobacteriaceae, Moraxellaceae, Streptococcaceae, Lactobacillaceae, Staphylococcaceae, Leuconostocaceae, Clostridiaceae and Veillonellaceae. More preferably, Burkhloderiaceae and/or Pseudomonaceae families of the Proteobacteria phylum are prognostic markers of diabetes, and Oxalobacteriaceae, Burkhloderiaceae, Neisseriaceae, Enterobacteriaceae and/or Moraxellaceae families of the Proteobacteria phylum and/or Lactobacillaceae, Leuconostocaceae, Clostridiaceae and/or Veillonellaceae families of the Firmicutes phylum are prognostic markers of overweight, and Oxalobacteriaceae, Burkhloderiaceae, Neisseriaceae, Enterobacteriaceae and/or Moraxellaceae families of the Proteobacteria phylum and/or Streptococcaceae, Lactobacillaceae, Clostridiaceae, Veillonellaceae and/or Staphylococcaceae families of the Firmicutes phylum are prognostic markers of obesity and/or morbide obesity.
Preferably said genera of bacteria which are prognostic markers of metabolic disease and optionally of cardiovascular complications are prognostic markers of diabetes, overweight, obesity and/or morbide obesity. Preferably said genera of bacteria which are prognostic markers of diabetes are any of the genera of the Proteobacteria phylum and said genera of bacteria which are prognostic markers of overweight, obesity and/or morbide obesity are any of genera of the Proteobacteria phylum and/or the Firmicutes phylum. More preferably, said genera of bacteria which are prognostic markers of diabetes, overweight, obesity and/or morbide obesity are selected from the group consisting of Ralstonia, Undibacterium, Neisseriales, Enteric—Bacteria—Cluster, Enhydrobacter and/or Acinetobacter genera of the Proteobacteria phylum.
Identification of said phyla and/or genera which are present in different proportions within the sample assayed in step a) and the control means that the quantity of phyla and/or genera of bacteria assayed in step a) is significantly inferior or superior than the quantity of phyla and/or genera of bacteria in the control. By “significantly” is intented to denote a measurable and statistically significant difference. Alternatively, a significant difference may denote an at least 1%, 2%, 3%, 4%, 5%, 10%, 15%, 20% difference in the proportions of bacteria of a phylum, a family or a genus between control and sample assayed.
Preferably the control sample is the same type of sample than the analyzed biological sample of step a). For example, if the biological sample of step a) is blood, the control sample is blood.
Preferably, if said metabolic disease is diabetes, then the biological sample of step a) and the control sample are blood samples.
Preferably, if said metabolic disease is overweight or obesity, the biological sample of step a) and the control sample are biopsy of adipose tissue, and more preferably are samples of vascular stroma of adipose tissue.
The inventors demonstrated that administration of a composition comprising an antigen preparation of attenuated and/or inactivated bacteria of at least one phylum, family and/or genus of bacteria which is a prognostic marker of metabolic disease and optionally of cardiovascular complications as defined above is capable of eliciting an immune response protecting an individual against metabolic disease and cardiovascular complications.
Thus the invention relates to an immunogenic or vaccinal composition comprising or consisting of:
The invention also provides attenuated or inactivated bacteria of at least one phylum, family and/or genus of bacteria which is a prognostic marker of metabolic disease and optionally of cardiovascular complications, or at least one immunogenic peptide from a bacterium of a phylum, family and/or genus of bacteria which is a prognostic marker of metabolic disease and optionally of cardiovascular complications, for use for preventing and/or treating metabolic disease and optionally of cardiovascular complications.
According to one embodiment, attenuated or inactivated bacteria originate from a biological tissue such as an adipose tissue, liver, muscles, or from a body fluid such as saliva, urines, blood, plasma, serum. Preferably, attenuated or inactivated bacteria do not originate from the intestine tissue content.
By “originate” it is meant that, e.g. attenuated or inactivated bacteria originating from blood were obtained by attenuating or inactivating bacteria isolated from a blood sample.
In the context of the invention, the term “treating” or “treatment”, as used herein, means reversing, alleviating, inhibiting the progress of, or preventing the disorder or condition to which such term applies, or one or more symptoms of such disorder or condition.
Preferably, the metabolic disease is selected from the group consisting of diabetes, overweight, obesity and/or morbide obesity.
According to particular embodiments of the present invention, said at least one phylum, family and/or genus of bacteria which is a prognostic marker of metabolic disease onset and optionally of cardiovascular complications onset is selected from the group consisting of Proteobacteria and Firmicutes phyla.
Preferably, said family of bacteria which is a prognostic marker of metabolic disease onset and optionally cardiovascular complications onset is selected from the group consisting of Burkhloderiaceae, Pseudomonaceae, Oxalobacteriaceae, Neisseriaceae, Enterobacteriaceae, Moraxellaceae, Streptococcaceae, Lactobacillaceae, Staphylococcaceae, Leuconostocaceae, Clostridiaceae and Veillonellaceae.
Preferably, said genus of bacteria which is a prognostic marker of metabolic disease onset and optionally cardiovascular complications onset is selected from the group consisting of Ralstonia, Undibacterium, Neisseriales, Enteric Bacteria Cluster, Enhydrobacter and/or Acinetobacter.
In particular preferred embodiments, said phylum which is a prognostic marker of diabetes, overweight, obesity and/or morbide obesity consists of the Proteobacteria phylum, and said phylum which is a prognostic marker of overweight, obesity and/or morbide obesity consists of the Firmicutes phylum.
In still particular embodiments, said family which is a prognostic marker of diabetes is selected from the group consisting of Burkhloderiaceae, Pseudomonaceae families of Proteobacteria phylum, family which is a prognostic marker of overweight is selected from the group consisting of Burkhloderiaceae, Oxalobacteriaceae, Neisseriaceae, Enterobacteriaceae and Moraxellaceae families of the Proteobacteria phylum and Lactobacillaceae, Leuconostocaceae, Clostridiaceae and Veillonellaceae families of the Firmicutes phylum, and family which is a prognostic marker of obesity and/or morbide obesity is selected from the group consisting of Burkhloderiaceae, Oxalobacteriaceae, Neisseriaceae, Enterobacteriaceae and Moraxellaceae families of the Proteobacteria phylum and Streptococcaceae, Lactobacillaceae, Staphylococcaceae, Clostridiaceae and Veillonellaceae of the Firmicutes phylum.
In still particular embodiments, said genus which is a prognostic marker of diabetes, overweight, obesity and/or morbide obesity is selected from the group consisting of Ralstonia, Undibacterium, Neisseriales, Enteric Bacteria Cluster, Enhydrobacter and/or Acinetobacter genera of the Proteobacteria phylum.
As used herein, an “attenuated bacteria” is a live bacterium whose aggressiveness against the body is weak or null.
An “inactivated bacteria” refers to whole-killed bacteria.
Methods of obtaining attenuated or inactivated bacteria are well known in the art.
As used herein, an “immunogenic peptide” is a protein or a fragment thereof obtained from a bacterium. Preferably, the immunogenic peptide is a flagellae protein, a pili protein, a secreted protein, an internal protein or a fragment thereof.
Methods of obtaining immunogenic peptide are well known in the art.
“Immunogenic composition” as used in the context of the present invention relates to a composition comprising at least one protein or fragment thereof (hereafter referred to as “antigen”) which provokes or immunomodulates (i.e. immunosuppress or immunostimulate) an immune response when administered to an individual. Preferably, the protein which provokes or immunomodulates an immune response is a flagellae protein, a pili protein, a secreted protein, an internal protein or a fragment thereof.
A “vaccinal composition” as used herein refers to a composition, such as the immunogenic composition described herein which is administered to immunomodulate an immune response, that will protect or treat an individual from illness, in particular due to that agent. The vaccine of the present invention is intended for use both as a therapeutic (treatment) vaccine, i.e. for administration to the individual after development of the disease with the intention to reduce or arrest disease progression and as a preventive (prophylactic) vaccine, for administration to the individual prior to the development of the disease, with the intent to prevent initial (and/or recurrent) infection.
For use as a vaccine in the context of the present invention the immunogenic composition may comprise whole-killed (inactive) bacteria, live-attenuated bacteria or processed and/or artificial bacterial preparations or combinations thereof. Processed bacterial preparations included preparations of bacterial proteins which are partially or completely purified and/or pretreated.
Methods of obtaining immunogenic composition are well known in the art. Generally such methods involve extracting proteins from bacterial preparations using techniques such as sonication, proteolytic digestion, heat treatment, freeze-thaw treatment, osmotic shock treatment etc. . . . Examples of artificial bacterial preparations include protein preparations either in part or entirely obtained by synthetic or recombinant methods. Oligonucleotides and probes can be devised based on the sequences of the bacterial genome and can be used to probe genomic or cDNA libraries for genes encoding antigens useful in the context of the invention. Genes can be isolated using standard techniques.
The object of the immunogenic or vaccinal composition according to the present invention includes obtaining at least partial and preferably complete protection against diabetes, overweight, obesity and/or morbide obesity by preventing the apparition or development of at least one phylum, family and/or genus of bacteria which is a prognostic marker of diabetes, overweight, obesity and/or morbide obesity onset, and/or by reducing the bacterial burden of at least one phylum, family and/or genus of bacteria which is a prognostic marker of diabetes, overweight, obesity and/or morbide obesity onset. Most particularly, the present invention relates to immunogenic or vaccinal composition which ensures a protective effect or reduced bacterial burden for a prolonged period of time, such as during at least 6 months, 1 years, 5 years, 10 years.
The immunogenic or vaccinal composition can comprise a suitable adjuvant. The type of adjuvant will vary, depending on the type of antigen preparation and route of administration used. Any adjuvant known in the art may be used in the immunogenic or vaccinal composition, including oil-based adjuvants such as Freund's Complete Adjuvant and Freund's Incomplete Adjuvant, mycolate-based adjuvants (e.g., trehalose dimycolate), bacterial lipopolysaccharides (LPS), peptidoglycans (i.e., mureins, mucopeptides, or glycoproteins such as N-Opaca, muramyl dipeptide [MDP], or MDP analogs), proteoglycans (e.g., extracted from Klebsiella pneumoniae), streptococcal preparations (e.g., OK432), Biostim™ (e.g., 01K2), the “Iscoms” of EP 109 942, EP 180 564 and EP 231 039, aluminum hydroxide, saponin, DEAE-dextran, neutral oils (such as miglyol), vegetable oils (such as arachis oil), liposomes, Pluronic® polyols. Adjuvants include, but are not limited to, the RIBI adjuvant system (Ribi Inc.), alum, aluminum hydroxide gel, cholesterol, oil-in water emulsions, water-in-oil emulsions such as, e.g., Freund's complete and incomplete adjuvants, Block co-polymer (CytRx, Atlanta Ga.), SAF-M (Chiron, Emeryville Calif.), AMPHIGEN® adjuvant, saponin, Quil A, QS-21 (Cambridge Biotech Inc., Cambridge Mass.), GPI-0100 (Galenica Pharmaceuticals, Inc., Birmingham, Ala.) or other saponin fractions, monophosphoryl lipid A, Avridine lipid-amine adjuvant, heat-labile enterotoxin from E. coli (recombinant or otherwise), cholera toxin, or muramyl dipeptide, among many others.
The immunogenic or vaccinal composition of the present invention can be administered via any suitable route, such as by mucosal (intranasal), parenteral, or intramuscular administration, oral, intradermal, intraperitoneal, intravenous, or subcutaneous administration. Suitable vaccination routes also comprise combination administrations (e.g. oral/intramuscular administration).
The immunogenic or vaccinal composition of the present invention can be administered alone or with suitable pharmaceutical carriers, and can be in solid or liquid form such as, tablets, capsules, powders, solutions, suspensions, or emulsions.
The solid unit dosage forms can be of the conventional type. The solid form can be a capsule, such as an ordinary gelatin type containing the proteins or peptides of the present invention or the antibodies or binding portions thereof of the present invention and a carrier, for example, lubricants and inert fillers such as, lactose, sucrose, or cornstarch. In another embodiment, these compounds are tableted with conventional tablet bases such as lactose, sucrose, or corn starch in combination with binders like acacia, corn starch, or gelatin, disintegrating agents such as, corn starch, potato starch, or alginic acid, and a lubricant like stearic acid or magnesium stearate.
The immunogenic or vaccinal composition of the present invention may also be administered in injectable dosages by solution or suspension of these materials in a physiologically acceptable diluent with a pharmaceutical carrier. Such carriers include sterile liquids such as water and oils, with or without the addition of a surfactant and other pharmaceutically acceptable adjuvants. Illustrative oils are those of petroleum, animal, vegetable, or synthetic origin, for example, peanut oil, soybean oil, or mineral oil. In general, water, saline, aqueous dextrose and related sugar solution, and glycols such as, propylene glycol or polyethylene glycol, are preferred liquid carriers, particularly for injectable solutions.
For use as aerosols, the immunogenic or vaccinal composition of the present invention in solution or suspension may be packaged in a pressurized aerosol container together with suitable propellants, for example, hydrocarbon propellants like propane, butane, or isobutane with conventional adjuvants. The materials of the present invention also may be administered in a non-pressurized form such as in a nebulizer or atomizer.
Another embodiment of the invention is a method of immunizing and/or vaccinating a patient against metabolic disease and optionally of cardiovascular complications, wherein said method comprises the administration to the patient of an immunogenic or vaccinal composition comprising or consisting of:
Material and Methods
D.E.S.I.R. is a longitudinal cohort study of 5,212 adults aged 30-65 years at baseline; the primary aim of the study was to describe the natural history of the metabolic syndrome (Fumeron et al., Diabetes, 2004, 53:1150-7).
Participants were recruited in 1994-1996 from ten Social Security Health Examination centers in western-central France, from volunteers insured by the French national social security system (80% of the French population—any employed or retired person and their dependents are offered free periodic health examinations). Equal numbers of men and women were recruited in five-year age groups. All participants gave written informed consent, and the study protocol was approved by the CCPPRB (Comité Consultatif de Protection des Personnes pour la Recherche Biomédicale) of Hôpital Bicêtre (Paris, France). Participants were clinically and biologically evaluated at inclusion and at 3-, 6-, and 9-year follow-up visits. We included in the analyses, those individuals who had known diabetes status at the 9-year examination, and we excluded those with C reactive protein >30 mg/l.
Among this population, we conducted a nested control study. The study included 14 subjects at low risk of diabetes according to traditional risk factors (at baseline, these subjects were non smokers and had a waist perimeter below the median) who developed the disease after 6 years follow-up. They were matched on age, sex, central adiposity and fasting blood glucose with 25 controls free of diabetes over the entire follow-up period.
Incident cases of diabetes were identified by treatment for diabetes or a fasting plasma glucose ≧7.0 mmol/l at one of the four 3-yearly examinations.
16S rDNA Gene Quantification and Sequencing
Total DNA concentration was determined using the Quant-iT™ dsDNA Broad-Range Assay Kit (Invitrogen) and a procedure adapted by the genomic platform of the Genopole Toulouse Midi Pyrénées (http://genomique.genotoul.fr). The mean concentration was 121.1+/−2.9 ng/μl. Each sample was ten times diluted in Tris buffer EDTA. The DNA was amplified by realtime PCR (Stepone+; Applied Biosystems) in optical grade 96-well plates. The PCR reaction was performed in a total volume of 25 μL using the Power SYBR® Green PCR master mix (Applied Biosystems), containing 300 nM of each of the universal forward and reverse primers eubac-F 5′-TCCTACGGGAGGCAGCAGT-3′ (SEQ ID NO: 1) and eubac-R 5′-GGACTACCAGGGTATCTAATCCIGTT-3′ (SEQ ID NO: 2). The reaction conditions for amplification of DNA were 95° C. for 10 min and 35 cycles of 95° C. for 15 s and 60° C. for 1 min. The amplification step was followed by a melting curve step according to the manufacturer's instructions (from 60° C. to 90° C.) to determine the specificity of the amplification product obtained.
Two DNA samples, extracted from blood of cases and controls, were pyrosequenced using 16S rRNA genes amplicons in order to assess their microbial composition. Following V1-V2 region amplification of the rrs gene by PCR, 16S rRNA amplicons were sequenced from both forward and reverse sides on a multiplexed GS FLX-Ti pyrosequencing run according to the manufacturer's protocols (Roche Applied Science, Indianapolis, Ind.). Sequences were binned for pyrosequencing MIDs and PCR primers removal (forward: AGAGTTTGATCMTGGCTCAG (SEQ ID NO: 5), reverse: GTCGCCTCCCGTAGGAGT (SEQ ID NO: 6) a minimal sequence length of 250 bases and a maximal threshold percentage of “N” base per sequence of 5%. Meta RNA, a software designed for the identification of 16S rDNA gene sequences based on hidden Markov models (HMMs), was further applied to select prokaryotic rrs gene sequences (Huang et al., Bioinformatics, 2009, 25:1338-40). Resulting 16S rDNA sequences were assigned to phylum and genus level using RDP_classifier (Cole et al., Nucleic Acids Res., 2009, 37:D141-145).
Identification of Blood Bacteria Phyla and Genera Associated with Diabetes
The 16S rDNA gene was sequenced in the pooled DNA sample from cases of incident diabetes and from controls without diabetes over the entire follow-up period. We first analyzed the bacterial diversity which corresponds to groups of sequences by characterizing that two sequences are different if less than 3, 5, ou 10% of their sequence differs from each other. Each group of similar sequences defines an OTU. The number of OTUs at (i) 3% was 2010 and 2179 in cases and controls, respectively, (ii) 5% was 1343 and 1493 in cases and controls, respectively and (iii) 10% was 745 and 800 in cases and controls, respectively. A common core of 443 OTUs was identified. In addition, OTUs specific for cases and controls were also quantified. We then studied the diversity at the overall number of reads level: 75% of all reads were similar between controls and cases, whereas the specific reads were restricted to the remaining 25%. At the phylum level, Proteobacteria represented 80-90% of all phyla in the blood, both in controls and cases. Within the Proteobacteria phylum we analyzed the differences at the family and genus level; Burkholderiaceae and Pseudomonadaceae represented 40% of the total families and Pseudomonas and Ralstonia represented 40% of the total genera. No major qualitative differences were observed between the taxons from controls and cases, even at the genus level. We then represented the diversity of the taxons identified in a dendrogram analysis. The semiquantitative representation of the phylogenic tree for each group of patients is shown in red and blue when cases and controls, respectively, were the most represented for each subdivision of the phylogenic tree, black when no difference occurred. When both dendrograms were matched, data showed that Proteobacteria diversity was the most preponderant and superimposable between both groups of patients. However, the main difference resides in the Firmicutes which seem to show a higher diversity in cases compared to controls. The opposite observation is made for the Bacteroidetes phylum.
At the quantitative level, 357 sequences of bacterial bacterial 16S rDNA are identical in blood from healthy patients and diabetic patients (for the quota of 10% difference). 121 and 128 sequences of bacterial 16S rDNA are respectively specific for patients who will remain non-diabetic throughout the monitoring and for patients who will develop diabetes after 6 years of monitoring.
Proteobacteria phylum represents the vast majority of the microbiota in the two groups of patients. Proteobacteria phylum is represented in greater proportion in patients who will develop diabetes after 6 years of monitoring (Table 1).
Within the Proteobacteria phylum, families Burkhloderiaceae and Pseudomonaceae are represented in greater proportion in patients who will develop diabetes after 6 years of monitoring in comparison to healthy patients (Table 2).
To identify phyla and genera associated with obesity, 16S rDNA quantification and sequencing were performed on adipose tissue from thin patients, i.e. patients who not developed obesity throughout the period of monitoring and from patients who developed obesity throughout the period of monitoring. Adipose tissue from each group of patient was obtained by trans-epidermal liposuction and 16S rDNA quantification and sequencing were performed in the same manner as in example 1.
An average 600, 400 or 300 different sequences are found in the adipose tissue of thin patients while about the double is detected in obese patients demonstrating that bacterial diversity is more abundant in adipose tissue from patients who developed obesity than in adipose tissue from thin patients.
150 sequences of bacterial 16S rDNA are identical in adipose tissue from thin patients and obese patients (considering that two sequences are different if less than 10% of their sequences differ from each other) and, 43 and 174 sequences of bacterial 16S rDNA are specific for the thin patients and obese patients respectively.
Firmicute phylum is represented in greater proportion in patients who developed obesity during the period of monitoring.
Within the Firmicute Phylum, genera Streptococcaceae, Lactobacillaceae and Staphylococcaceae are represented in greater proportion in patients who developed obesity during the period of monitoring.
To identify phyla and genera associated with overweight, 16S rDNA quantification and sequencing were performed on the vascular stroma of white adipose tissue from thin patients, from overweight patients, from obese patients and from morbidly obese patients. Adipose tissue from each group of patient was obtained by trans-cutaneous liposuction and 16S rDNA quantification and sequencing were performed in the same manner as in example 1.
An average 500, 400, 200 different sequences are found in the vascular stroma from adipose tissue of thin patients while about 30% more is detected in overweight or obese patients demonstrating that bacterial diversity is more abundant in vascular stroma of adipose tissue from patients who developed obesity or overweight than in vascular stroma of adipose tissue from thin patients.
91 sequences of bacterial 16S rDNA are identical in thin patients and overweight patients (considering that two sequences are different if less than 10% of their sequences differ from each other) and, 26, 76, 51 and 56 sequences of bacterial 16S rDNA are respectively specific for the thin patients, overweight patients, obese patients and morbidly obese patients.
Firmicute and Proteobacteria phyla are represented in greater proportion in overweight, obese and morbidly obese patients (Table 3).
Within the Firmicute phylum:
Within the Proteobacteria phylum Burkhloderiaceae and Oxalobacteriaceae families are represented in greater proportion in overweight, obese and morbidly obese patients, and Neisseriaceae, Enterobacteriaceae and Moraxellaceae families are represented in lesser proportion in overweight, obese and morbidly obese patients (Table 5).
Within the Proteobacteria phylum Ralstonia and Undibacterium genera are represented in greater proportion in overweight, obese and morbidly obese patients, and Neisseriales, Enteric—Bacteria—Cluster, Enhydrobacter and Acinetobacter genera are represented in lesser proportion in overweight, obese and morbidly obese patients (Table 6),
Asticcacaulis
Brevundimonas
Caulobacter
Bradyrhizobium
Rhodopseudomonas
Ochrobactrum
Devosia
Hyphomicrobium
Pedomicrobium
Methylobacterium
Pleomorphomonas
Defluvibacter
Mesorhizobium
Phyllobacterium
Rhizobium
Amaricoccus
Paracoccus
Rhodobacter
Rubellimicrobium
Roseomonas
Azospirillum
Telmatospirillum
Porphyrobacter
Novosphingobium
Sphingomonas
Sphingopyxis
Achromobacter
Alcaligenes
Castellaniella
Parasutterella
Burkholderia
Cupriavidus
Polynucleobacter
Ralstonia
Acidovorax
Aquabacterium
Aquamonas
Comamonas
Curvibacter
Delftia
Diaphorobacter
Hydrogenophaga
Methylibium
Pelomonas
Polaromonas
Rhodoferax
Schlegelella
Variovorax
Duganella
Herbaspirillum
Herminiimonas
Janthinobacterium
Massilia
Oxalobacter
Undibacterium
Methylobacillus
Methylophilus
Aquitalea
Deefgea
Neisseria
Neisseriales
Azoarcus
Azospira
Dechloromonas
Methyloversatilis
Thauera
Uliginosibacterium
Zoogloea
Bacteriovorax
Bdellovibrio
Desulfovibrio
Myxococcaceae
Polyangiaceae
Arcobacter
Sulfurospirillum
Aeromonas
Tolumonas
Alishewanella
Rheinheimera
Morganella
Proteus
Rickettsiella
Legionella
Marinomonas
Pseudospirillum
Haemophilus
Acinetobacter
Enhydrobacter
Psychrobacter
Azomonas
Cellvibrio
Pseudomonas
Nevskia
Arenimonas
Rhodanobacter
Stenotrophomonas
Thermomonas
In order to induce an immunization process which could involve a resistance to the effect of fat diet on the development of metabolic diseases, the intestinal bacterial flora has been inactivated and then administered by intraperitoneal route to mice in a repetitive manner.
We identified that during a fat diet, bacteria of the intestine are translocated in the adipose tissue and then induce an inflammatory response which is responsible for the development of the adipose tissue leading to obesity and for the resistance to the insulin leading to diabetes.
We demonstrated that repeated injections of intestinal bacteria which translocated in the adipose tissue allowed healthy mice to resist to development of impaired glucose tolerance (IGT) and then to diabetes (
It has been demonstrated that a fat-enriched diet induces diabetes and modifies the bacterial phylotypes from the intestinal microbiota (metagenome). Therefore it is suggested that this change corresponded to a change in the corresponding antigenic repertoire. Hence a single subcutaneous administration to mice of bacterial extracts from the ileum of diabetic mice has been shown to be able to reduce the impact of a diabetogenic diet (high fat diet) on the vaccinated mouse. The protection was shown using intraperitoneal glucose tolerance test. It was analyzed 19, 30, 38 and 66 days following the beginning of the diabetogenic diet. The effects of the subcutaneous administration of bacterial extracts prepared in the same condition but issued from normal chow fed non diabetic mice were compared. The bacterial extract from normal mice could not protect against high fat diet induced diabetes (
The treatment of donor mice with antibiotics also prevented the efficacy of the bacterial extracts to reduce the impact of a fat-enriched diet on a vaccinated mouse. This suggests that the ileum extract should contain bacteria to efficiently vaccinate the mice. Eventually it has been demonstrated that the vaccinated process did indeed involve a lymphocyte mediated immune response since the transfer of the lymphocytes from the spleen of the vaccinated mouse does protect the recipient mouse from high fat diet induced diabetes (
| Number | Date | Country | Kind |
|---|---|---|---|
| 11305366.4 | Mar 2011 | EP | regional |
| Filing Document | Filing Date | Country | Kind | 371c Date |
|---|---|---|---|---|
| PCT/EP2012/055983 | 4/2/2012 | WO | 00 | 12/6/2013 |
