TW201247875A - Microbial signatures as indicators of radiation exposure - Google Patents

Abstract

The present disclosure defines a method for identifying and characterizing radiation exposure after, for example, a nuclear event such as detonation of a nuclear weapon or a nuclear meltdown of a nuclear power plant, using changes in microbiomes. The present disclosure demonstrates that microbiomes are reproducibly and detectably altered by exposure to radiation. As described herein, microbial signatures can be used to characterize components of microbiomes that are altered by exposure to radiation.

Description

201247875 VI. INSTRUCTIONS: GOVERNMENT SUPPORT The U.S. government has provided funding for the development of the present invention. In particular, the National Institutes of Health, Grant No. AI080363, has funded the development of the present invention. The U.S. Government may have certain rights in the invention. _ Related Applications This application claims US Provisional Patent Application No. 61/446,696 (filed February 25, 2011); No. 61/451,930 (US application for March 2011); No. 61/479,786 (Applied on April 27, 2011); and priority to No. 61/491,452 (filed May 31, 2011), each of which is hereby incorporated by reference in its entirety. [Prior Art] As of 2011, it is estimated that there are more than 2, 5 nuclear warheads in the world, of which about 4,800 remain on standby for possible use. Even small nuclear weapons can destroy the entire city. In addition, there are 439 operating nuclear reactors around the world; failures in nuclear power plants can cause major damage to surrounding areas. SUMMARY OF THE INVENTION The present invention encompasses recognizing reproducible and detectable changes in microbial composition and/or activity in response to radiation exposure. The present invention allows for the identification and/or characterization of microbial markers that reflect such changes, and also provides a system for such microbial markers to assess or detect the extent and/or type of radiation that an individual or region may have been exposed to. In some embodiments, the 'microbial marker" comprises the content of one or more microorganisms or their 162630.doc 201247875 component or product, and is not so exposed (eg, not fully exposed or has varying degrees and/or types of exposure) Or a group of microorganisms that have been exposed to radiation of known reference doses and/or types, sufficient to distinguish or characterize a group of microorganisms that are exposed to radiation (and/or to a particular degree or type of radiation). For example, in some embodiments, the microbial marker obtained from the gastrointestinal microbiome of an individual suspected or exposed to radiation exposure is sufficient to diagnose the individual compared to the microbial marker of the gastrointestinal microbiome of the unexposed individual and/or the reference exposed individual. . According to the present invention, the microbial marker of a particular microbial phase sample is defined relative to a suitable reference microbial phase sample. In some embodiments, the particular microbial phase sample has a common radiation exposure characteristic that is not common to the reference microbial phase sample. In some embodiments, a particular microbial phase sample differs from a reference microbial phase sample in that it is a sample from a different source. In some embodiments, the particular microbial phase sample differs from the reference microbial phase sample in that the reference microbial phase sample is a historical microbial phase sample of the same or different source. In certain embodiments 'the invention provides a method of identifying and/or characterizing radiation exposure' comprising providing a reference microbial marker associated with the extent and/or type of radiation exposure and determining a microbial phase sample of the radiation exposed individual to be identified or characterized Microbial markers present in the body. In some embodiments, the microbial phase sample comprises a sample of one or more types of microorganisms found in the gastrointestinal tract of an individual. In some embodiments the 'microbial marker" comprises a content or amount of one or more of the 16S rRNA gene sequences of one or more types of microorganisms. In certain embodiments, the present invention provides a method of defining a microbial marker associated with a radiation exposure profile 162630.doc 201247875. In the examples, the present invention provides a method comprising the steps of: measuring the first group of microbial phase samples - or the first of a plurality of types of microorganisms or components or products thereof Each of the first set of microbial phase samples in the set of pots has a common radiation exposure characteristic; the second set of microbial phase 讳 σ is determined by the second set of one or more types of microorganism standing components or products Content, the second group of microbial phase samples do not have: the same radiation exposure characteristics, as other aspects can be similar to the first group of microbial phase samples; and identification of microbial markers, including the first or second group content and common radiation exposure The presence or absence of a characteristic is associated with the content. In some embodiments, the radiation exposure characteristic comprises an exposure intensity of the range of 〇 to 1 ()Gy). In some embodiments... or a plurality of types of microorganisms or components thereof or product t-group content comprising a collection of 16S rRNA gene sequence content of one or more types of microorganisms found in the gastrointestinal tract of the sample of the collection phase [embodiment] Definition犮 Capital: As used herein, the term "antibiotic" means a group of chemicals derived from natural sources or derived from antibiotics isolated from natural sources, which inhibit the growth of bacteria and other microorganisms or destroy bacteria and The ability of other microorganisms is mainly used for the treatment of infectious diseases. Examples of antibiotics include, but are not limited to, penicillin G (Penici Ilin G); Methicillin; Nafcillin; Oxacillin; Chlorine cioxacillin; Dicloxacillin; Ampicillin; Amoxicillin 162630.doc 201247875 (Amoxicillin); Ticarcillin; Carbenicillin; Mezlocillin; Azlocillin 0 Piperacillin; Imipenem; Aztreonam; Cephalothin; Cefaclor; Cefoxitin; Cefuroxime; Cefonicid; CeHnetazole; Cefotetan; Cefprozil; Loracarbef; Cefetamet); Cefoperazone; Cefotaxime; Ceftizoxime; Ceftriaxone; Ceftazidime; Cephalosporin Cefepime); Cefixime; Cefide loss (Cef) Podoxime); Cefsulodin; Fleroxacin; Nalidixic acid; Norfloxacin; Ciprofloxacin; Ofloxacin; Enoxacin; Lomefloxacin; Cinoxacin; Doxycycline; Minocycline; Tetracycline; Amikacin ); Gentamicin; Kanamycin; Netilmicin; Tobramycin; Streptomycin; Azithromycin; Clarithromycin; Erythromycin; Erythromycin estolate; Red 162630.doc 201247875 Erythromycin ethyl succinate; Erythromycin glucoheptonate; Erythromycin lactobionate; Erythromycin stearate; Vancomycin; Teicoplanin; Chloramphenicol; Clindamycin; Trimethoprim; Sulfamethoxazole; stone xiaohua. Nitrofurantoin; Rifampin; Mupirocin; Metronidazole; Cephalexin; Roxithromycin; Co-amoxiclavuanate; a combination of Piperacillin and Tazobactam; and its various salts, acids, tests and other derivatives. Antibacterial antibiotics include, but are not limited to, penicillins, cephalosporins, carbacephems, cephamycins, carbapenems, monocyclic beta -mon〇bactams, aglycosides, glycopeptides, quinolones, tetracyclines, macrolides, sulfonamides, fluoroquinolones and lincosamides ° Antibacterial agents also include antibacterial peptides. Examples include, but are not limited to, maxima H5, dermcidin, cecropins, andropin, moricin, ceratotoxin , melittin, magainin, dermaseptin, bombinin, brevinin-l, esculentins, Buffulin II (buforin 162630.doc 201247875 II), CAP18, LL37, abacin, apidaecins, prophenin, indicicin, Brevinins, protegrin, tachyplesins, defensins and/or drosomycin 〇T: similarity is sufficient to allow comparison, but in There is a difference in at least one feature. To give: As used herein, the term "related" has the general meaning of "display correlation." It will be understood by those skilled in the art that if two features, items or values tend to appear and/or change together, they exhibit a correlation with each other. In some embodiments, if the correlation P value is less than 〇〇5, then It is statistically significant; in some embodiments, if the correlation P value is less than 〇.〇1, it is statistically significant. In some embodiments, the correlation is assessed by regression analysis. In some embodiments, the correlation is a correlation number.昼分. As used herein, the term "distinguish" means defining or distinguishing from other entities (e.g., comparable entities). In some embodiments, differentiation means distinguishing from other types that are present together in a source and/or sample. Spoiler: The term "microorganism" in this technology generally refers to small organisms under the microscope, such as bacteria, fungi, protozoa or viruses. In some embodiments, the microorganism is a bacterium, an archaeon, a monocytogene (e.g., yeast), an algae, or a protozoan (e.g., a variant of a malaria pathogen). In some embodiments, the microorganism is characterized according to its boundaries. In some embodiments, the microorganism is characterized according to its gate. In some embodiments, 162630.doc 201247875 microorganisms are characterized according to their outline. In some embodiments, the microorganism is characterized according to its family. In some embodiments, the microorganism is characterized according to its genus. In some embodiments, the microorganism is characterized according to its species. In some embodiments, the microorganism is characterized according to its subspecies. In some embodiments, the microorganism is characterized according to its strain. Microorganisms (such as bacteria) included in subspecies are sometimes used in other taxonomic categories (eg, serovar or serotype). Serum variants differ from serotypes in their different types of attachment behavior in the cell membrane. In some embodiments, genus and species are utilized and/or characterized by microorganisms (e.g., one of the samples). In the second embodiment, subspecies, serotypes and/or strains are used to identify and/or identify microbes (e.g., in a sample). Alternatively or additionally, in some embodiments: using - or a plurality of distinguishing features such as pathogenicity (i.e., ability to cause a particular disease), or resistance to a plurality of antibiotics, metabolic profiles, morphology, etc., identification and/or Or characterize a microorganism (eg in a sample). Splash to. As understood from the context, the term "microbial type" is used herein to refer to a microorganism having a common feature. In some implementations, microbes are identified as groups of microorganisms with common detectable characteristics. In some embodiments, the common detectable feature is or contains an amount of a particular job sequence or a particular sequence. In some embodiments, it can be said that there is a specific RNA transcript or a specific r transcript in the assay. In some embodiments, the 'common detectable feature is or comprises the amount of a polypeptide (e.g., a polypeptide produced by a microorganism) or a polypeptide. In some embodiments, the co-detectable feature is or comprises the presence of enzymatic activity (eg, microbial enzyme: tongue) or enzymatic activity. In some embodiments, the microorganisms of the common type according to the standard member's knowledge are specific classes of microorganisms. Those skilled in the art can understand that the term "microbial type" as used herein is not limited to a particular resolution; techniques for achieving different levels of resolution can be used to detect different features. In some embodiments, the common type of microorganism is a microorganism of the same microbial community. In some embodiments, the common type of microorganism is a microorganism of the same microorganism. In some embodiments, the common type of microorganism is a microorganism of the same microbial class. In some embodiments, the common type of microorganism is a microorganism of the same microbiology family. In some embodiments, the common type of microorganism is a microorganism of the same microorganism. In some cases, the microorganisms of the common type are microorganisms of the same microorganism species. In some embodiments, the common type of microorganism is a microbial of the same microbial subspecies. In some embodiments, the common type of microorganism is a microorganism of the same microorganism. In some embodiments, the common type of microsteps are microorganisms of the same neoplastic serotype. In some embodiments, the common prize microorganisms are microorganisms of the same strain. : As understood from the context, the term "radiation" can refer to any type of energy emission, such as electromagnetic waves or particles such as moving subatoms. In some embodiments of the invention the radiation comprises ionizing radiation. Ionization is a radiation that is high enough to ionize atoms. Types of ionizing radiation include, but are not limited to, alpha radiation, radon radiation, cosmic radiation, neutron radiation, x-ray radiation, and gamma radiation. In the column embodiment, the radiation comprises non-ionizing radiation. Non-ionizing radiation type packages: (but not limited to) visible light, infrared light, microwave radiation, radio waves, very low frequency radiation, very low frequency radiation, thermal radiation, and black body radiation. _ Finance: As understood from the context, the reference sample or individual is a sample that is sufficiently similar to the particular sample or individual of interest to allow for a relevant comparison or for a sample. In some embodiments, information about a particular sample is obtained at the same time. In the case of a real greed and a two-way yoke, the relevant reference σ is historically poor. In some implementations, the specific sample of the reference sample stored in, for example, a computer readable medium, is identical, similar, or different than the particular sample of interest to the reference sample shirt. > for or containing bone marrow, blood; blood cells; ascites; body fluids containing cells; self-floating nucleic acids; medullary fluid; peritoneal fluid; pleural fluid; feces; lymphoids; vaginal swabs; buccal swabs; nasal swabs such as Catheter lavage fluid or fiberoptic sulcus alveolar lavage fluid sample; tissue biopsy sample; surgical sample; feces, other body fluids; secretions and / or excretions: and / or cells therein. In some embodiments, the biological sample is or comprises cells obtained from an individual. In some embodiments the cells obtained are or include cells from the individual from which the sample was obtained. In some embodiments, the resulting cells are or comprise microbial cells of the individual microbiome. In some embodiments, the 'sample is obtained directly from the source of interest by any suitable means. For example, in some examples, in some cases: as used herein, the term "sample" refers to a source obtained from a source of interest. Biological or environmental samples. In some embodiments, the source of the subject, including the organism, such as an insect, animal, human, or plant, in some embodiments, the source of interest includes soil, sediment, groundwater, surface water, and/or Or air. In some embodiments the biological sample comprises biological tissue or liquid. In some embodiments, the biological sample can be tissue or fine needle biopsy saliva; urine; cerebrospinal gynecological fluid; skin wipes or lavage, aspirate; debris; bone 162630.doc • 11· 201247875 by live Tissue examination (eg, body fluids (eg, blood, lymphocytes, in some embodiments, 'primary biological samples are selected from a fine needle aspiration or tissue biopsy), surgery, collection of bark, feces, etc.) In the method of obtaining, the primary environmental sample is obtained by excavation, core sampling and/or extraction or a combination thereof. ## Clearly understanding the term "sample" from the context means processing the primary sample (for example by A preparation obtained by removing one or more components of the primary sample and/or by adding - or a plurality of agents to the primary sample. For example, a semi-permeable membrane is used for filtration. The "processed sample" may comprise, for example, a nucleic acid or protein obtained by sample extraction or by techniques such as mRNA amplification or reverse transcription, isolation and/or purification of certain parameters of the primary sample. As used herein, the term "substantially" means a qualitative condition that exhibits the characteristics or properties of all or nearly all of the scope or extent of interest. It is generally understood by those skilled in the art that biological and chemical phenomena are rarely, if any, completed and/or performed to completion or to achieve or avoid absolute results. The term “substantially” is used herein to reflect the potential lack of completeness, which is inherent in many biological and chemical phenomena. #录勿: As used herein, the term "transcript" refers to a molecule that is transcribed or processed in one or more splicing steps. DETAILED DESCRIPTION OF CERTAIN EMBODIMENTS Exposure Exposure In recent history, multiple nuclear events have destroyed local populations. For example, the Chernobyl nuclear power plant disaster in 1986, the atomic bomb that fell to Sakamoto Hiroshima and Nagasaki during the Second World War 162630.doc 12 201247875 and the recent disaster damage and group chaos in the Fukushima nuclear power plant And the treatment of a large number of exposure survivors causes a large number of casualties and requires rapid medical screening in areas where infrastructure care is impeded. The method of the present invention provides a means of identifying and/or characterizing radiation exposure. During a nuclear event, there is a need for a fast and reliable way to illuminate an individual and characterize their exposure. Human 龆a' # ^ Humans are very sensitive to radiation exposure, but proper medical care can have a significant impact on survival and/or disease or ailment. In some cases, 'not only identification but also quantitative _ amount can be critical, as appropriate medical sputum is highly dose dependent. The rapid and reliable means of identifying radiation-exposed individuals after the nuclear event may provide a means of excluding the individual from the treatment and the degree or type of treatment of the individual. Because of the exposure of the individual; = symptoms and due to human money, the large number of potentially exposed individuals who are required to be exposed to the test are usually significantly greater in number than the individual in need of treatment, especially if a nuclear event occurs in a residential area. It provides vital information about the ability to exclude unexposed individuals from treatment, not only for controlling available medical resources, but also for preventing panic from spreading within the community. Examples of sources of radiation exposure include, but are not limited to, nuclear power plants, nuclear weapons, cosmic rays, radiation therapy, nuclear matter, radiopharmaceuticals, xenon ray tubes, particle accelerators, exposure to cesium-222, exposure to cesium 232, exposure to uranium 235 and uranium-238, exposure to potassium-40, exposure to radium 226, smoke detectors, airport baggage screening machines, radiological diagnostics (CT scans), radioactive dirty bombs and space flight or any combination thereof. In the absence of appropriate medical care, humans have a 5 5 Gyi semi-lethal 162630.doc •13·201247875 radiation dose (LD50/60 is the dose that kills 50% of the exposed population within 60 days of exposure) (Mole, RH “The LD50 for uniform low LET irradiation of man" Br J Radiol. 57: 355-69, 1984). However, this dose can be doubled under appropriate medical conditions. Proper medical care is highly dose dependent. Doses of less than 1 Gy usually do not require treatment. Dosages of i to 7 Gy are usually treated with antibiotics, platelets, or cytokine therapy or any combination thereof. Cytokines suitable for treatment include, but are not limited to, granule globule stimulating factor filgrastim, PEGylated granule globulum stimulating factor PEGylated pegfilgrastim, granule macrophage Cell community stimulating factor and / or sargrasostim. 7 to 1 〇 Gy dose is treated with bone marrow transplantation. A dose of more than 1 〇 Gy is usually believed to cause fatal gastrointestinal damage. In some embodiments of the invention, the radiation exposure or exposure to radiation comprises any amount of radiation that the individual or article has exposed. In some embodiments, the light exposure comprises exposure to non-ionizing radiation. In some embodiments, the radiation exposure comprises exposure to ionizing radiation. In some embodiments, the radiation exposure comprises exposure to ionizing radiation between 0 and 1 Gy. In some embodiments, the radiation exposure comprises ionizing radiation that is exposed to 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, or more than 1 〇 Gore. "Gore is a measure of radiation exposure, defined as One joule of ionizing radiation is absorbed by a kilogram of object. Clinical manifestations of radiation exposure include, but are not limited to, bone marrow cell loss and/or injury, lymphopenia, altered granulocyte content, gastrointestinal symptoms (including intestinal crypt loss and gastrointestinal barrier collapse), epidermal and/or dermal cell loss, and / or damage, and combinations thereof. 162630.doc 201247875 The 'T'/ ringing individual can immediately show signs of radiation exposure. Affected individuals may be initially asymptomatic and will begin to show exposure symptoms over time. Affected individuals can start to show symptoms after h, 2, 3'4, 5, 6, 7, 8, 9, __ 1 leap seconds. Affected individuals may begin to show symptoms after 1, 2, 3, 4, 5 6 7 8 , 9 , 1 , or more than 1 minute. The affected individual can begin to show symptoms after 1, 2, 3, 4, 5, 6, 7, 8'9, 1 or more than 1 hour. Affected individuals may begin to show that the symptomatic individual may be asymptomatic after 1, 2, 3, 4, 〇, ,, 8, 9 '1 〇 or more than 10 days. In the second embodiment, radiation exposure symptoms include (but are not limited to) nosebleeds, mouth bleeding, bleeding gums, rectal bleeding, bloody stools, subcutaneous hemorrhage, mental confusion, dehydration, diarrhea, syncope, fatigue, fever, hair loss, exposure Area inflammation (redness, tenderness, swelling, bleeding), oral ulceration... nausea and vomiting, skin sores, skin burns (redness, blisters), peeling, esophageal ulcers, gastric ulcers, intestinal ulcers , vomiting blood, weakness and their combination. Methods for assessing radiation exposure include, but are not limited to, assessing the presence of symptoms, obtaining biological samples for radioactivity monitoring, determining absolute lymphocyte counts, lymphocyte failure motility#, chromosomal domain cytogenetic assays, and testing blood. The eukaryotic gene and protein expression in the urine, in the urine: eukaryotic gene and protein expression, and enamel and the electronic spin resonance of the nail. Monitoring the kinetics of lymphocytopenia is often considered a practical method for assessing radiation doses within hours or days after exposure to light radiation. Lymphocyte failure kinetics can detect the dose of M〇 Gy at a resolution of 2 Gy. however < , 162630.doc -15- 201247875 Characterization of lymphocyte failure kinetics requires hematology laboratory capabilities and a minimum of 3 complete blood counts for four days immediately after radiation exposure. In order to obtain a more refined result, 'theoretically requires 6 complete blood counts within 2 to 3 days of exposure, and the first blood count is obtained within 4 hours of exposure. β. It may be difficult to monitor the dynamics of lymphocyte failure after a severe nuclear event. 'The cytogenetic assay for chromosomal aberrations remains the highest standard for quantitative radiation exposure after a severe nuclear event. However, the main disadvantage of this assay is that it is not possible to obtain results. Blood samples were collected 24 hours after exposure and subsequently processed for 48 to 72 hours. It is clear that there is a need for a way to easily and quickly quantify radiation exposure after a nuclear event. Microbiome The human body* contains ten times as many microbial (and especially bacterial) cells as the human cells it has. Many or most of these microorganisms are not harmful or even beneficial to their human host. Studies have increasingly shown that these microorganisms play a significant role in maintaining and/or increasing health. Gastrointestinal bacteria are examples of well-studied studies. These bacteria provide a variety of important reductions, including (but not limited to) contributing to carbohydrate digestion. Intestinal cell growth inhibits the growth of pathogenic microorganisms, promotes the development of intestinal adhesion immunity, metabolizes carcinogens, and prevents allergies. Symptoms and inflammatory bowel disease. Most other multicellular organisms are similarly present in a symbiotic relationship with a large number of microorganisms. Examples of symbiotic relationships between microorganisms and mites are in the movements (9), plants, and I are short-lived in the I-gas, and there are luminescent bacteria in the genus Euprymna scolopes. Vibrio fischeri "The organ of the heart, so that the squid can eat at night. Legumes have the roots of nitrogen-fixing bacteria on their roots. 162630.doc •16·201247875 Tumor. The termite gut contains all types in a specific environment. The abundance of microorganisms constitutes a microbiome. Since microorganisms are almost ubiquitous, the microbiome is present in most locations. In some embodiments, the microbiome comprises microorganisms that are inconsistent with any defined location. In some embodiments, The microbiome comprises microorganisms associated with non-living components of the natural environment. Examples include, but are not limited to, rock soil and any form of water, including natural water, ponds, ponds or water in (d). In some embodiments The microbiome contains microorganisms associated with non-living components of the manufacturing environment. Examples include, but are not limited to, computer keyboards or Mouse surface, manufacturing equipment surface or door handle. In some embodiments, the microbiome comprises microorganisms associated with a living organism or a particular portion, organ, tissue or component thereof. In some embodiments, the organism is A human non-human multicellular organism in a shared environment. In some embodiments, the organism is a plant. In some embodiments, the organism is an insect. In some embodiments, the organism is an animal. In the examples, the animals are mice, Oshima, dogs, wolves, coyotes, deer, foxes, stinks, rabbits, leopards, rats, horses, cows, goats, sheep, possums, possums, and scorpions. In some embodiments, 'animals are non-human « long classes. In some embodiments, the organism is a human. The substance · and its internal compound (such as the type and/or abundance of the microorganisms present) And/or behavior (eg, producing - or multiple markers, respiratory rate and/or rate of growth - migration, etc.) may be shaped by the local environment - in some implementations 'single organisms, eg, in vivo or within their body parts Different locations contain multiple different micros Group. Human Microbiome Program 162630.doc 201247875 (httP://commonfund.nih.gov/hmp/) Characterizes microbial groups found in several different parts of the human body, including the nostrils, mouth, skin, gastrointestinal tract and genitourinary In some embodiments, the microbiome used in the present invention is a microbiome associated with a particular site or location (e.g., tissue or organ) of the organism. In some embodiments, the microbiome comprises microbes associated with the skin. In an embodiment, the microbiome comprises microbes associated with the teeth. In some embodiments, the microbiome comprises microorganisms associated with the oral mucosa. In some embodiments, the microbiome comprises microorganisms associated with the nostrils. In some embodiments, The microbiome contains microorganisms associated with the genitourinary system. In some embodiments, the microbiome comprises microorganisms associated with the gastrointestinal tract. In some embodiments, the microbiome comprises a single microorganism. In some embodiments, the microbiome comprises from one to one trillion or more than one trillion individual microorganisms. In some embodiments, the microbiome comprises a single type of microorganism. In some embodiments, the microbiome comprises from 1 to 1 million or more than one million types of microorganisms. In some embodiments, the microbiome comprises from 500 to 5,000 types of microorganisms. In some embodiments, the microbiome comprises 1, from 2,000 species to 2,000 species of microorganisms. The type of microorganisms present in the intestine is usually described in terms of the gate, the outline, the eye and the grade. In some embodiments, there are between 1 000 and 1 5 bacterial species in the gastrointestinal microbiome. Microbiome Variations The present invention teaches microbiome composition and/or activity, and more specifically changes in microbial composition and/or activity to provide information about particular environmental conditions. The invention presented herein encompasses the discovery that the microbiome composition 162630.doc *18· 201247875 and/or the activity can be altered in a detectable and reproducible manner associated with radiation exposure. In some embodiments, the change in microbiome composition and/or activity comprises any one or more of the microbial types in the microbiome and/or any changes in the abundance and/or type of one or the other components produced therefrom. In some embodiments, the change in microbiome composition and/or activity comprises an increase in the abundance of one or more of the microbial types or one or more components from which the microbial population is produced. Alternatively or additionally, in some embodiments, the change in microbiome composition and/or activity comprises one or more microbial types in the microbiome and/or abundance reduction of one or more components from which it is produced. In some embodiments, the change in microbiome composition and/or activity comprises an increase in the abundance of one or more microbial types and/or components produced therefrom, and one or more microbial types in the microbiome and/or from The abundance of the components produced is reduced. In accordance with the present invention, microbiome changes associated with the extent and/or type of light exposure are identified, characterized, and/or detected. In some embodiments, analyzing the changes comprises controlling and/or excluding the effects of one or more other changes in the composition and/or activity of the microbiome. Events external or internal to the host organism can cause detectable changes in the composition and/or activity of the microbiome. For example, oral ingestion of an antibiotic by an individual can significantly alter the composition and/or activity of its gastrointestinal microbiome. In some embodiments, the microbiome composition and/or activity changes in response to a disease in the host organism. In some embodiments, the microbiome composition and/or activity is altered in response to infection by the host organism with the pathogenic bacteria. In some embodiments, the composition and/or activity of the microbiome changes in response to a change in the main organism's stalks in the I62630.doc •19·201247875. In some embodiments, the composition and/or activity of the microorganism changes in response to changes in the water source of the host organism. In some embodiments, the microbiome composition and/or activity changes in response to environmental changes in the host organism (e.g., the individual can move to a new city or country). In some embodiments, the microbiome composition and/or activity changes in response to changes in the host organism's personal hygiene habits. In some embodiments, the microbiome composition and/or activity changes in response to changes in the weight of the host organism. In some embodiments, the microbiome composition and/or activity changes in response to changes in the age of the host organism. In some embodiments, the microbiome composition and/or activity changes in response to changes in the host organism's chemical exposure. In some embodiments, the microbiome composition and/or activity may change upon exposure to the microbiota altering agent. In some embodiments, the microbiome modifier comprises a chemical agent. In some embodiments, the microbiome altering agent comprises an antimicrobial agent. In some embodiments, the microbiome altering agent comprises an antibiotic. In some embodiments, the microbiome altering agent comprises a bacterium. In some embodiments, the microbiome altering agent comprises a probiotic. In some embodiments, the microbial modifying agent comprises an antimicrobial peptide. In some embodiments, the microbial modifying agent comprises an antifungal agent. In some embodiments, the microbial modifying agent comprises a bacteriophage. Microbial Labeling The present invention encompasses the recognition that microbial markers can be relied upon to represent microbial composition and/or activity. The microbial marker contains data points as a microbiome composition and/or activity indicator. Thus, in accordance with the present invention, microbiome changes can be detected and/or analyzed by detecting a 162630.doc • 20-201247875 or multiple microbial marker signatures. In some embodiments, the microbial marker comprises information regarding the absolute amount of one or more microbial types and/or their products. In some embodiments, the microbial marker includes information regarding the relative amount of one or more microbial types and/or their products. In some embodiments, the microbial marker comprises information regarding the presence, amount, and/or activity of at least one type of microorganism. In some embodiments, the microbial marker comprises information regarding the presence, amount, and/or activity of one to one species of microorganism. In some embodiments, the microbial marker comprises information regarding the presence, amount, and/or activity of one to 100 types of microorganisms. In some embodiments, the microbial marker includes information regarding the presence, amount, and/or activity of one to more than one or more than one type of microorganism. In some embodiments, the microbial marker includes information regarding the presence, amount, and/or activity of all types of microorganisms on the shell in the microbiome. In some embodiments, the microbial marker comprises a content or amount of one or more microbial types or components or products thereof. In some embodiments, the microbial marker comprises a content or amount of one or more DN A sequences. In some embodiments, the microbial marker comprises a content or amount of one or more 16S rRNA gene sequences. In some embodiments, the microbial marker comprises a content or amount of the 丨8S rRNA gene sequence. In some embodiments, the microbial marker comprises a content or amount of one or more RNA transcripts. In some embodiments, the microbial marker comprises a content or amount of one or more proteins. In some instances, the microbial marker comprises a concentration or amount of one or more metabolites. 162630.doc •21· 201247875 The 16S and 18S rRNA gene sequences encode the subunit components of prokaryotic ribosomes and eukaryotic ribosomes, respectively. The rRNA gene is particularly useful for discriminating microbial types' because although these gene sequences differ among microbial species, these genes have highly conserved regions for primer binding. This specificity between conserved primer binding regions allows the rRNA genes of many different types of microorganisms to be amplified using a single set of primers and subsequently distinguished by amplification sequences. In the method of the invention, microbial markers are obtained and/or determined using microbial phase samples. The microbial phase sample contains a sample of the microorganism of the microorganism group and/or a component or product thereof. In some embodiments, the microbial phase sample is collected by any means of recovering the microorganisms of the microorganism group or a component or product thereof and suitable for the source of the relevant microbiome. For example, a microbial phase sample of the gastrointestinal tract is obtained from a stool sample. Quantifying Microbial Content In the method of the present invention, microbial markers are determined and/or obtained by quantifying microbial content. Methods for quantifying various types of microbial content are described herein. In some embodiments, determining the amount or amount of one or more types of microorganisms or components or products thereof comprises determining the amount or amount of one or more DNA sequences. In some embodiments, the one or more DNA sequences comprise any DNA sequence that can be used to distinguish between different microbial types. In certain embodiments, the one or more DNA sequences comprise a 16S rRNA gene sequence. In certain embodiments, the one or more DNA sequences comprise an 18S rRNA gene sequence. In some embodiments, 'amplification 1, 2, 3, 4, 5, 10, 15, 20, 25, 50, 162630.doc • 22 · 201247875 100, 1,000, 5,000 or more than 5,000 sequences. In some embodiments, the amount or amount of one or more DNA sequences of the microbial phase sample is directly assayed. In some embodiments, the DNA is isolated from the microbial phase sample and the amount or amount of one or more DNA sequences of the isolated DNA is assayed. Methods for isolating microbial DNA are well known in the art. Examples include, but are not limited to, phenol-chloroform extraction and a variety of commercially available kits, including the QIAamp Fecal DNA Mini Kit (Qiagen, Valencia, CA). In some embodiments, the content or amount of one or more DNA sequences is determined by amplifying the DNA sequence using PCR (e.g., standard PCR, semi-quantitative PCR, or quantitative PCR). In some embodiments, the amount or amount of one or more DNA sequences is determined by amplifying the DNA sequence using quantitative PCR. Such DNA amplification procedures and other basic DNA amplification procedures are well known to those skilled in the art and are described in Ausebel et al. (Ausubel FM, Brent R, Kingston RE, Moore DD, Seidman JG, Smith JA, Struhl K (eds. ). \99. Current Protocols in Molecular Biology. WAey, New York. In some embodiments, DNA sequences are amplified using primers that are specific for distinguishing between individual microbial types and one or more sequences of other different microbial types. In some embodiments, the 16S rRNA gene sequence or a fragment thereof is amplified using primers specific for the 16S rRNA gene sequence. In some embodiments, the 18S DNA sequence is amplified using primers specific for the 18S DNA sequence. In some embodiments, the 16S rRNA gene sequence is amplified using the primer sequences set forth in Tables 1 or 2.

In some embodiments, the use of the phylochip technique to determine the content or content of one or more 16S I62630.doc -23-201247875 rRNA gene sequences is well known in the art and described in Hazen et al. Deep-sea oil plume enriches indigenous oil-degrading bacteria. "Science, 330, 204-208, 2010), which is incorporated herein by reference in its entirety. Briefly, 'Amplification using DNA extracted from a microbial phase sample and labeling the 16S rRNA gene sequence>> then hybridizing the amplified DNA to an array containing the probe of the microorganism 16S rRNA gene. Next, the degree of binding to each probe is quantitatively determined to obtain the content of the microorganism type corresponding to the 16S rRNA gene sequence probe in the sample. In some embodiments, phylo chip analysis is performed by a vendor. Examples include, but are not limited to, Second Genome Inc. (San Francisco, CA). In some embodiments, determining the amount or amount of one or more types of microorganisms or components or products thereof comprises determining one or more microbial RNA molecules. Content or content group (eg, transcript) "Methods for quantifying RNA transcript levels are well known in the art and include, but are not limited to, Northern analysis, semi-quantitative reverse transcriptase PCR, quantitative reverse transcriptase PCR, and microarrays analysis. Such RNA transcript detection programs and other basic rnA transcript detection procedures are described in Ausebel et al. (Ausubel FM, Brent R, Kingston RE, Moore DD, Seidman JG, Smith JA, Struhl K (ed.). 1998. 7'"0^0^0'·5 Mo/ecw/or Wiley: New York). In some embodiments, determining the amount or amount of one or more types of microorganisms or components or products thereof comprises determining the amount or amount of one or more microbial proteins. Methods for quantifying protein content are well known in the art and include, but are not limited to, Western analysis and mass spectrometry. These protein detection procedures and 162630.doc • 24 - 201247875 All other basic protein detection procedures are described in Ausebel et al. (Ausubel FM, Brent R, Kingston RE, Moore DD, Seidman JG, Smith JA, Struhl K (ed.) 1998. Cwrrewi Proiocoh Mo/ecwZar 5io/og>\ Wiley: New York). In some embodiments, determining the amount or amount of one or more types of microorganisms or components or products thereof comprises determining the amount or amount of one or more microbial metabolites. In some embodiments, the metabolite content is determined by mass spectrometry. In some embodiments, the metabolite content is determined by nuclear magnetic resonance spectroscopy. In some embodiments, the metabolite content is determined by enzyme-linked immunosorbent assay (ELISA). In some embodiments, the metabolite content is determined by colorimetry. In some embodiments, the determination of metabolite content by spectrophotometry. Microbial markers associated with light exposure. The present invention encompasses the following recognition. Changes in microbial markers can be relied upon to indicate changes in microbiome composition and/or activity. Thus, specific changes in the microbiome being detected and/or analyzed will contribute to the characteristics of the microbial markers. In certain embodiments, the present invention is directed to a method of defining a microbial marker indicative of light exposure by identifying components of a microbiome affected by radiation exposure. In some embodiments, the microbes associated with the exposure characteristics include the types of microorganisms or their components or products that allow for differences between exposure and non-exposure (4) and/or for exposed microorganisms. Any method by which a group is defined or classified. In some implementations, the definition of the microbial marker associated with the radiation exposure profile comprises determining the first group of microorganisms or components or products of the first group of microbial phase samples - or more I62630.doc • 25 - 201247875 Each of the microbial phase samples in the set of microbial phase samples has a common Korean: violent: characteristic, determining the second set of microorganisms of one or more types of microorganisms or a group of knives or products of the second set of microbial phase samples The phase sample does not have the same radiation exposure characteristics, but may otherwise resemble the first group of microbial phase samples; and the clocked microbial marker, including the presence or absence of the first or second group of content and common radiation exposure characteristics There is a relevant content. 3 In some real towels, a group of microorganisms are similar. Contains at least one microbial phase. . . In some embodiments, the microbial phase sample comprises 1, 2, 3, 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 1 or 10,000 or more than 1,000 samples. In some implementations, the second-group microbial phase samples are any two sets of microbial phase samples that differ in the characteristics of the Korean radiant but are otherwise similar. In some embodiments, the first and second sets of microbial phase samples are obtained from different sputum organisms. In some embodiments, the 'and the second set of microbial phase samples were obtained from the same set of hosts at different times. In some embodiments, the characteristic of the radiation exposure comprises obtaining a radiation exposure dose of the primary of the microbial phase. In some embodiments, the radiation exposure agent comprises between 0 Gy and 1 Gy. In some embodiments, the radiation exposure dose is 13 1 , 2'3, 4, 5, 6, 7, 8, 9, or 1 or more than 1 〇〇丫. y. In some embodiments, the characteristic of the radiation exposure comprises obtaining a microscopic phase-like estimate of the duration of the rolling exposure. In some embodiments, the duration 1 is 0 to 1 second. In some embodiments, the duration is 1, 2, 3, 4, 6, 7, 8, 9, 10, or more than 10 seconds. In some embodiments, 16263 〇. <j〇c • 26· 201247875 The continuation time is 1, 2, 3, 4, s, c — 6, 7, 8, 9, 10 minutes or more than i〇 minutes. In some embodiments, the duration is i, 2, 3, 4, 5, 6, 7, 8 1 1G hours or more than 1 G hours. In some embodiments, the duration is 1 2 3, 4, 5, 6 , 7, 8, 9, 10 days or more than 1 day. In some embodiments, the feature of the footwear exposure includes the duration of exposure of the host obtaining the microbial phase sample. + In some embodiments, the duration is 1, 2, 3'4, 5, 6, 7, s η 8, 9, 10 minutes or more than 10 minutes. In some embodiments, the duration is 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 hours or more than 10 hours. In the second embodiment, the duration is 1, 2, 3, 4, 5, 0, 7, 8, q _ 8 9 , 丨〇 day or more than 10 days. In one such embodiment, the duration is 丨 2 3 2, 3, 4, 5, 6, 7, 8, 9, in weeks or more than 10 weeks. In some implementations, 〇^^.H^ 傲 包含 contains the microbes that are exposed to the mouth of the mouth. The frequency of exposure to the frequency of the frequency phase of the sample contains the host's exposure to the 匕3匕The mother second is exposed to one instance of the radiation and is exposed to _鼾> 4S t Θ in the frequency of the implementation of the Ji Tian shot. In this case, the f-clip blast is exposed to radiation one or more times in the case of one or four radiation exposures. The _ primordial mother contains a small sequence of host Iα s. The exposure to the radiation of the 3 佰 main mother day is exposed to radiation — or the eve of the 耵疋 I exposure to the light shot contains the host every two: Example times. In some embodiments. "In the radiation one or more + recognizing the r storm in the frequency of radiation, the sentence is eight:: face-shot - or multiple times. In some embodiments, the violent lord of the second violent two-year value of the main exposure to radiation one or The frequency of multiple road shots is 4 fortunately, although the frequency of the shots is ~ some rewards of Hungarian, 1 sheep contains the letter of the main - life exposed to light shots more than 1 h storm 162630.doc • 27· 201247875 In some embodiments, The characteristics of the radiation exposure include the type of radiation exposure. The types of radiation exposure of the present invention include, but are not limited to, ionizing radiation, alpha radiation, beta radiation, cosmic radiation, neutron radiation, radiant radiation, and gamma radiation, or combinations thereof. In some embodiments, identifying the microbial marker comprises any means that allows for the identification of a marker associated with the radiation exposure characteristic. In some embodiments, identifying the microbial marker comprises identifying one or more of the first set of levels of the first set of microbial phase samples The amount is increased and/or decreased compared to the second group of the second set of microbial phase samples. In some embodiments, identifying the microbial marker comprises identifying the content of one or more DNA sequences in the first set of microbial phase samples The second set of microbial phase samples is increased and/or decreased. In some embodiments, the DNA sequences are identified by comparing semi-quantitative or quantitative real-time PCR data of the first and second sets of microbial phase samples. The case towel is compared with the DNA sequence by cluster analysis of the phyl〇chip data generated from the first and second groups of microbial phase samples. In some implementations, the identification of the microorganisms includes the identification of the first group of microbial phase samples. The content of one or more RN A transcripts is increased and/or decreased compared to the second group of microbial phase samples. In a two-dimensional example, by comparing the first and second groups of microbial phase samples Quantitative or quantitative real-time reverse transcriptase PCR data to identify RNA transcripts. In some embodiments, RNA sequences are identified by cluster analysis of microarray data generated from samples of the first and second microbial phase samples. In an embodiment, identifying the microbial marker comprises identifying an increase and/or a decrease in one or more of the one or more proteins in the first set of microbial phase samples compared to the first set of microbial phase samples. Use 162630.doc -28 - 201247875 The present invention is believed to rely on changes in microbial markers as a diagnostic tool for determining and characterizing n-ray exposure. As described herein, current tests for radiation exposure require extensive retesting or exposure after exposure. More than three days. In the case of a nuclear event, more sensitive testing is required using less of the required resources so that the exposed individual gets treated as early as possible and leaves the unexposed individual out of the medical environment. In some embodiments, The invention provides a method of determining and/or characterizing radiation exposure comprising determining a microbial marker in a microbial phase sample of an individual to be identified or characterized by radiation exposure and comparing it to a reference microbial marker associated with one or more characteristics of the radiation exposure. In some embodiments, the individual comprises any individual that is exposed to, suspected of being exposed to, and/or at risk of being exposed to radiation. In some embodiments, the reference microbial marker comprises any value associated with known radiation exposure characteristics. In some implementations, the ginseng microbial marker contains microbial markers obtained from individuals who have not been exposed to radiation. In some embodiments, the reference microbial marker comprises a microbial marker of an individual that has been exposed to radiation of known characteristics. In some embodiments, the reference microbial marker comprises a microbial marker of an individual that is similar to the individual from which the radiation is to be identified or characterized. In some embodiments, the reference microbial marker comprises a microbial marker obtained at different times from the radiation exposure of the individual to be identified or characterized. In some embodiments, 'different times occur before radiation exposure. In some embodiments, the reference microbial marker is from a microbial phase sample from which the individual to be identified is exposed to radiation. In some embodiments, the reference microbial marker comprises the content and/or activity of one or more microorganisms. In some embodiments 162,630.doc -29 to 201247875, the reference microbial marker comprises the content and/or activity of one or more microorganisms wherein the or the content and/or activity of the microorganisms remains substantially unchanged in response to radiation exposure . In some embodiments, comparing the microbial marker to the reference microbial marker in the microbial phase sample of the individual exposed to the radiation to be identified or characterized comprises comparing the microbial marker obtained from the two individual individuals. In some embodiments, comparing the microbial markers comprises comparing the microbial markers obtained from the same individual at respective time points. In some embodiments, comparing microbial markers comprises comparing microbial markers of the same microbial sample. In some embodiments, comparing microbial markers comprises comparing the relative amounts and/or activities of two or more microorganisms. In some embodiments, comparing the microbial markers comprises comparing the relative amounts and/or activities of the two or more microorganisms, wherein at least one of the first microorganisms (ie, the content and/or activity of the at least one first microorganism) remains substantially Constant. In some such embodiments, comparing the microbial markers comprises comparing the relative amounts and/or activities of the two or more microorganisms, wherein at least one of the second microorganisms is altered. EXAMPLES Example 1: Obtaining a microbial sample of irradiated rat In the following example, a method of obtaining a microbial sample from a irradiated rat was used using a 5-week-old male WAG/RijCmcr (Wistar) rat. Rats born in the same place (n=5/group) were randomly assigned to receive single or multiple fractions of 10 0 Gy and 1,8 Gy of whole body X-ray radiation. At a dose rate of 1.95 Gy/min, the whole body was irradiated (Baker et al, Total body irradiation increased risk of coronary sclerosis, degeneration of heart 162630.doc 201247875 structure and function in a rat model. Int J Radiat Biol, 85(12): 1089-1100, 2009). After irradiation, each group of rats was maintained at a maximum of three per cage for subsequent monitoring. Fresh fecal pellets were obtained from each rat before irradiation (days) and on days 4, 11, and 21 after irradiation. The fecal pellets were homogenized in 1 ml PBS and the microbial DNA was isolated using a Q μamp fecal DNA mini-set (Qiagen, Valencia, CA) using 200 μM homogenate. Example 2 · Phylochip analysis of rat microbial group In the following examples, a method of quantifying microbial DNA using the phylochip 16S rRNA gene microarray was described. Microbial diversity and comparative community architecture of rat fecal DNA samples were characterized by Second Genome Inc. (San Francisco, CA) using a high-density G3 PhyloChipTM 16S rRNA microarray assay (PN49-0002A) and bioinformatics methods. The microbial phase analysis focused on calculating the distance between samples and assessing the significance of differences in microbial groups (Hazen et al, Deep-sea oil plume enriches indigenous oil-degrading bacteria. Science, 330 (6001): 204-8, 2010). Data analysis combines several individual stages; preprocessing and data simplification, summarization, time-of-time correction, inter-sample distance measurement, sorting/clustering, sample classification, and significance testing. Pre-processing and data simplification: To calculate the total intensity of each feature on each array, the 9 center pixels of the individual features are graded by intensity and used at 75% percentile. The probe intensity was subtracted from the background and adjusted to the PhyloChipTM control MixTM (Second Genome, Inc., San Francisco). The hybridization fraction (HybScore) of the operational classification unit (OTU) was calculated by removing the average intensity of the maximum and minimum perfectly matched probes. Simplified data, taxonomic group 162630.doc •31· 201247875 is considered to exist, as described in Hazen et al., and filtered into at least one type of sample t or a majority of the profiles and other zero categories A taxonomic group that exists. Distance function between samples: All profiles are compared to each other in a pairwise manner to determine the disparity scores and store them in a distance matrix order. Select a distance function that produces similar biological samples with only a small difference score. The Bray-Curtis index uses the difference in the taxonomic abundance of the samples, but uses a pairwise correction by dividing the sum of the differences by the sum of all the abundances. Sorting, clustering, and categorizing methods: Create a two-dimensional sorting of the sample in a tree view and a hierarchical clustering graph to graphically summarize the relationships between the samples. To create a tree, the distance matrix samples are hierarchically clustered using the farthest proximity method (ie, fully interlocked). Non-metric multidimensional scaling (NMDS) is a two-dimensional sorting and mapping method for visualizing complex relationships between samples. NMDS uses only the distinct value rank order to position the points relative to each other. Use Tibshirani et al. in Pre-validation and inference in microarrays· (Stat Appl

A microarray predictive analysis using the nearest shrunken centroid method described in Genet Mol Biol, 1: Article 1, 2002) obtains a list of significant taxonomic groups for abundance characterization of each category. Hybrid Fraction and Saturation: To calculate the total intensity of each feature on each array, the nine center pixels of the individual features were ranked by intensity and the 75% percentile was used as the probe intensity. The probe strength is subtracted from the background and adjusted to the standard scale to

PhyloChipTM Control Mixture (second Genome Inc., San

Francisco), such that the average probe intensity of all probes complementary to any of the targets in the control mixture is equal to 10,000 units. As added to each 162630.doc -32· 201247875

The concentration of the blended mixture in the PhyloChip assay is the same, so the scaled probe intensities can be compared directly across the array. When the scaled probe intensity varies between arrays, it indicates a change in target DNA concentration. Operational Classification The total score for the unit (0 TU) is calculated as the average intensity of the perfectly matched probes that remove the maximum and minimum values. These trimming averages can theoretically range from 〇 to 65,536, but in real microbiome samples, a range of about 100 to about 17,000 is generally observed. A common practice using microarray data is to logarithmically convert fractions so that the variance is constant over a wide range of concentrations. The score uses a base 2 logarithm, such as converting 100 to 6_644 and converting 17 to 14. to 14.053. In some applications, floating point numbers are difficult to process, so the last step is multiplied by 1000 to obtain an integer HybScore such as 6,644 or 14,053. in

Among the supplements of Hazen et al., a series of concentrations of 26 different taxon groups from iDNAw to 480 pM were applied to the PhyloChip assay. HybScore is highly correlated with the concentration of the entire range (r=〇941), but there is a slight slope reduction observed in 8 taxa in 26 taxa with HybScore exceeding 15,000. In the inventor's experimental data, no observation was observed. HybSc〇re exceeds 15,000 threshold.

Example 3: Quantitative PCR of Microbial 16S rRNA Genes In the following examples, a method of quantifying the content of 16S rRNA gene sequences in microorganisms by quantitative PCR is described. The isolated DNA samples were subjected to quantitative PCR using iCycler (Bi〇Rad, Hercules, CA) or any other quantitative pcR machine for microbial population counting. The PCR reaction mixture consisted of 50% iQ SYBR Green Supermix (Bio-Rad), 0.4 μΜ forward and reverse primers and 3.8% template in RNase/DNase-free water 162630.doc •33- 201247875. The combination of primers shown can detect the specified bacterial taxonomic group (Table 1) or the specified biomarker (Table 2). Use the paired students t-test to find significant differences in qPCR data variables. Changes in PCR data are shown in the representative scatter plot (Figure 1). Table 1: 16S primer pairs for bacterial taxa

Identification of the taxonomic group Gene orientation Sequence Bacteroides BactF285 Forward GGTTCTGAGAGGAGGTCCC UniR338 Reverse GCTGCCTCCCGTAGGAGT Clostridium UniF338 Forward ACTCCTACGGGAGGCAGC CcocR491 Reverse GCTTCTTAGTCAGGTACCGTCAT Proteobacteria Uni515F Forward GTGCCAGCMGCCGCGGTAA Ent826R Reverse GCCTCAAGGGCACAACCTCCAAG Table 2: Biomarker primer pairs

Biomarker Orientation Sequence Stabilization after Radiation (StableF) Forward TTCGCTTCTCTTCGTATGCGGC Ratio Stabilization (StableR) Reverse TCTTCACACACGCGGCATGGC Decrease After Radiation (DownF) Positive CGCGTGGGTACACCTGCCCTG Ratio Decrease (DownR) Reverse CCGGGGTCCATCCTATACCGCA Post-radiation Acute (AcuteF) Positive TCGGGCCTCTTGCCATCGGA Acute Ratio ( AcuteR) Reverse CCGGTTAACGCTTGCACCCCT Chronic after radiation (ChronicF) Forward CTGGGATGGACCTGCGGTGT Chronic ratio (ChronicR) Reverse TTACGAGCCGAAACCCTTCTTCAC Example 4: Identification of candidate biomarkers prior to radiation exposure In the following examples, 'candidate biomarkers prior to radiation exposure were identified. The 16S ribosomal RNA (rRNA) gene sequence is unique to each eubacterial taxonomic group, and the change in the number of 16S rRNA genes in all DNA extraction products indicates the change in species abundance. At all time points after irradiation (daysday, day 4, day 11, and day 21), microorganisms were obtained from the feces of five independent rats for analysis using the technique described in Example i. The microbial diversity and comparative community structure of rat fecal D N A samples were characterized using the G3 PMoChip 16S microarray assay and bioinformatics method described in Example 2, 162630.doc -34 - 201247875. The members of the Fimicutes and Proteobacteria were found to be the most abundant microbial phase present in the flank (Fig.... Microbiological phase analysis focused on calculating the distance between samples and evaluating the microbiome without using pre-exposure controls) Distinctive significance. This analysis is extremely important for the final conversion to the classification of patients with radiation injuries. 'The towel cannot obtain the pre-exposure control for each individual. In the case; a total of 7,484 bacterial operation taxa were detected in one sample (〇 Τυ). Adonis test proves that the bacterial community is different in different days than it is in the same day (p<0.001). When using the Bray_Curtis dissimilarity method, all the taxa in at least one sample are used. Separating the samples by day is clearer than separating the samples by the rats (Fig. 3). The hierarchical clustering using a fully linked tree diagram shows a close relationship on Days, 4, 11 and 2 (days) ( Figure 3). To identify candidate biomarkers before radiation exposure, identify 〇τυ that exhibits abundance of abundance from day 4 to day 21 after irradiation. ^ As estimated by q value, wrong When the number of findings was limited to 5 (all), it was found that the abundance of 276 OTUs varied from day 4 to day 21 (all days, Figure 4) (Turnbaugh, PJ et al. "The effect of diet on the human gut microbiome: a metagenomic analysis in humanized gnotobiotic mice, j

Sci Transl Med, l(6): 6ral4, 2009). These 276 OTUs were then compared to 3855 OTUs and 237 OTUs significantly changed on the 11th and 21st days (Day 11 and Day 21, Figure 4). A common set of 147 OTUs were found between these three comparisons and used as candidate biomarkers. 162630.doc -35- 201247875 Initial 'Month# Use non-metric multidimensional scaling method, using these 10 sorts will be Koda These data points are separated by the number of days after shooting (ρ < 〇〇〇 [). The representative οτυ of this list is shown in Figure 5. Among the 276 OTUs showing a significant change between the background day and the 4th day to the 21st day, the step-by-step selection showed a constant decrease in the abundance of 〇τυ (circle 5) after the light shot. Although the abundance of these 〇τυ is not as large as the 147 other candidates mentioned above, it is found that 165 pseudobacteria, Lactobacillus and Staphylococcus aureus were observed after radiation exposure. Enhancement; found that 142 shuttle g families and digestive streptococci OTU abundance unchanged 'which can serve as an internal control; and identify 47 individual Clostridium OTU performance weakened" appendix provides increase and decrease after light shot Or a complete list of unchanged OTUs. The results of the microarray studies described herein are also specific to individual bacteria. For example, in the period of days 4-21 after radiation exposure, the abundance of Kenting 1; 31902 (Blue fungus) is increased, and the abundance of 〇11; 39153 (Cymenoptera) is reduced, and οτυ 42924 The abundance of (Compyella) is unchanged (Figure 6). 3 The ratio of "increase/decrease" of 1902/391 53 increases from _4 to +2, indicating 4th, "and 64 times change in days (Figure 6) after radiation, and can also be used as radiation Possible biomarkers prior to exposure. It may be advantageous to use the ratio of the formation of the gut microbiota as a biomarker for radiation biodosimetry, as pre-exposure samples will not be available during or after the explosion of the radiation device. The specific bacterial group identified by microarray analysis was detected, and the expression of 16S rRNA in the selected intestinal microbial phase group of feces was also analyzed using the trait (3). The abundance of the proteobacteria was 1 〇 (Jy whole body radiation * days The increase was almost 1〇〇〇 and then returned to the control value (Fig. 7A). The abundance of Clostridium and Bacteroides is less affected during this period. The results of this paper indicate abundance 162630.doc •36· 201247875 The target can be used as a specific microbial taxonomic group (see Figure 5, Figure 7A) for the detection of 1 〇〇 in each bacterial group (see Figure 5, Figure 7A). In these studies, more than one individual member of the 6S rRNA primer. The OTU content of the rat feces Analysis of significant $ 212 kinds having a different MIN

The bacteria's "increase/decrease ratio" is a steady and steady recording signal, and these records are 21 days less. Compared with the third day, the two ratios increased by 64 times on the 21st day. The results of the present invention demonstrate the utility of such bacteria as a biomarker prior to exposure to ionizing radiation, as evidenced by the PCR results described herein. Such biomarkers may also indicate early gastrointestinal system damage after fractional therapeutic radiation. The evidence that the copy of the i6s rRNA gene is abundant in response to ionizing radiation is conclusive. The present invention thus demonstrates that gene abundance markers may be converted from a discovery platform to the development of a "fieldabu" assay platform that is more suitable for actual biological dosimetry. Example 5: Dose-Response Study In the following examples, a dose response study to determine the effect of different radiation doses was described. To determine the effect of radiation dose, six exposures of 18 Gy total were used during the three days to simulate clinically used therapeutic chemistries. A method of collecting a microbial sample using the self-irradiated rat described in Example 1. The microbial 16S rRNA gene was subjected to quantitative PCR using the method described in Example 3 to quantify the amount of bacteria in each taxonomic group. The results described in this paper show i 8 162630.doc •37· 201247875

The Gy radiation-induced proteobacteria increased for 5 days (Fig. 7B) longer than the 3 days observed after 10 Gy (Fig. 7A). In addition, 18 Gy radiation-induced Clostridium was reduced 10-fold on days 1-3, and this phenomenon was not observed with 10 Gy radiation. Since the 18 Gy regimen was administered in six doses over three days (rather than one day), the increase in proteobacteria at 18 Gy after two light shots met the equivalent response observed four days after 10 Gy radiation. Example 6: Designing a biomarker assay prior to radiation exposure In the following examples, a test to develop a detectable microbial marker is described. Based on the biomarker 0TU found using the PhyloChip assay described in Example 4, PCR primers were designed to quantitatively PCR the microbial 16S rRNA gene using the method described in Example 3 to confirm treatment according to the protocol described in Example 1. Radiation-induced changes in the abundance of biomarkers in irradiated rats. Biomarkers were identified that stabilized, decreased, acutely increased (in the first week), and chronically enlarged (more than 21 days) after irradiation (Figure 8). The biomarker ratio "acute increase/decrease" increased from day 2 to day 8 after 10 Gy and 18 Gy radiation, while the ratio "chronic increase/decrease" was from day 8 to day 21 after irradiation. The sky is increasing (Figures 9A and 9B). The invention thus recognizes the presence of a microbial individual or group of microorganisms that can act as a biomarker prior to radiation exposure. EXAMPLES • Effects of factors other than radiation on microbial populations In the following examples, the effects of factors other than radiation on the microbial population were evaluated to determine the effect of age on the abundance of gut microbiota. Wings were collected from 5 week old non-irradiated rats according to the protocol described in Example 1 for 21 days. The abundance of Bacteroides, Proteobacteria and Clostridium was determined by quantitative PCR of the microorganism 16S rRNA gene described in Example 3. The contents of Bacteroides, Proteobacteria and Clostridium were not changed in the 21-day study. 162630.doc -38 · 201247875. Therefore, the abundance of the three major groups of bacteria affected by radiation (>90 〇/〇 of the microbial phase) did not change with time in the rats not exposed to radiation (Fig. 10A). The present invention thus demonstrates that the genetic background and age do not appear to alter the abundance of multiple bacterial taxa (including Bacteroides, Bacteroides, and Clostridia) in control rats that are not exposed to radiation. In control rats, the abundance of multiple intestinal bacterial taxa was also unaffected by diet. To determine the genetic background and the effect of diet on the abundance of the microbial population present in the rat's self-feeding silver Teklad 8604 food inbreeding WAG/RijCmcr rats, feeding the LabDiet 5010 food distantly mating history pogodoli rats (Sprague Dawley rat) and inbred Dahl S rats fed LabDiet 5010 food collected feces. All three rat strains studied remained unchanged. The abundance of Bacteroides, Proteobacteria, and Clostridium was determined by quantitative PCR using the microbial 16S rRNA gene described in Example 3. The contents of Bacteroides, Proteobacteria, and Clostridium were similar in these three rat strains and were stable during the 6-day study period. The present invention thus shows that strains and diets have no effect on these three bacterial populations present in rat feces (Fig. 10B). Example 8: Human and rat are similar, in the following examples, the human gastrointestinal microbiome was studied to identify similarities with the data found in rats. Six human stool samples were analyzed using G3 phyl〇Chips. The present invention shows that when comparing this data with the data of the rat of Example 4, all of the 47 〇τυ found in the rat were present in humans, and 142 071 [; In humans, and the addition of 165 TU TUfl in rats, 2 were found in human orders. The present invention I62630.doc •39·201247875 thus indicates that these 157 OTUs form microbial markers that are associated with pre-radiation exposure and appear to be characteristic prior to radiation exposure. Further expansion of the bacterial taxonomic group detected in the 373 stool samples collected during the comparison between the rat OTU of Example 4 and the Human Microbiome Project (http://www.hmpdacc.org/data-browser.php) Rats are analyzed relative to humans. Rat fecal OTUs were pooled by genus to match pyrosequencing data from human samples (Figure 9). The 47 〇 TUs reduced in rats were matched to two genera: Clostridium and Sarcina (both in humans). Of the 142 stable OTUs, 89 were matched to 14 genera of the thick-walled phylum (Fig. 11), 13 of which were found in humans. An increase of 165 〇1 in rats; 141 matches three genus: Barnesie Ua, Lactobacillus and Streptococcus and all three are present in humans. The present invention thus indicates that more than 96% of the classified rat biomarkers match the bacterial gene present in humans. Example 9: Determination of the Minimum Dose Detectable by Microbial Markers The following example describes an experiment using microbial markers to determine the minimum detectable amount of sputum. The following experimental methods can be used to determine the minimum detectable dose by the biomarkers of the present invention. Male rats were irradiated with a single exposure of 350 kVp X-rays (n=5/k) in the range of 1-10 Gy (n=50) and subsequently irradiated with mixed or beagle dogs (n = l) 〇) to determine the earliest reaction time and duration of action (1-15 days). The dose was first increased using a 1 Gy dose followed by a 1 Gy increment. Confirm the lowest dose and the earliest reaction between the rat and the dog. Feces were collected each time and analyzed using microarray analysis markers specific for the radiation exposure described herein. The results were confirmed using qPCR. This method allows the dose-response characteristics and time-response characteristics of the intestinal microbial phase to be determined prior to exposure to light exposure at 162630.doc -40·201247875. Intestinal microbial phase changes after radiation are expected to be detected as early as 24 hours after exposure, and the radiation signature persists for at least 15 days. It is expected that light exposure levels that were previously exposed to doses as low as 2 Gy (which are considered important for the identification of the wounded and sick) will be detected. Respiratory exposure to energy levels greater than 2 Gy is important for determining medical treatment. It is expected that the dog will begin to vent after 4-8 hours after exposure to 4 exposures. Animals will receive medical help as needed. Monitoring the gastrointestinal symptoms of a dog can determine whether it is related to the microbial phase profile. The response of oral microbes to ionizing light shots is another alternative. Example 10. Determine the effect of health status on the intestinal microbial phase after irradiation. The following example describes an experiment to determine the effect of health status on microbial markers. Antibiotics are commonly used in the US population (GrijaWa et al, Antibiotic prescription rates for acute respiratory tract infections in US ambulatory settings. JAMA, 302: 758-66, 2009). Azithromycin is currently the most common prescribed macrolide for acute respiratory infections and otitis media. Supportive care including antibiotics immediately after a nuclear explosion can improve the prognosis of some radiation casualties (DiCarlo et al. Radiation injury after a nuclear detonation: medical consequences and the need for scarce resources allocation. Disaster Med Public Health Preparedness, 5: S32-S44 , 2011). Oral administration of vancomycin (currently used antibiotics) and a mixture of streptomycin, bacitracin polymyxin B and neomycin (Croswell et al. Prolonged impact of antibiotics on intestinal microbial ecology and susceptibility to enteric I62630. Doc -41 - 201247875

Salmonella infecti〇n. Infect Immun, 77:274ΐ53, 2〇〇9) Altered the abundance of the intestinal microbial phase present in the feces of inbred Wistar rats (Fig. 12). The response experienced in distantly mating Sturgeon rats and inbred DaM s rats is essentially equivalent to β. The following experimental methods can be used to examine the effect of pre-existing azithromycin on the abundance of intestinal microbial phase after radiation exposure. To determine whether the microorganisms affected by the antibiotic are the same as the microorganisms affected by the radiation. Three groups of X-rays were exposed to radiation and examined for changes in intestinal microbial phase markers in their feces. Rats in the first group (n=15) and dogs (n=5) were treated with azithromycin (156 mg/kg per day) for 7 days prior to irradiation. After irradiation, the second group (rat, n=i5 and dog, η=5) 2·ΐ5 days was treated with ciprofloxacin (female day 15 30 mg/kg), and the third group (rat, η= 15) Accept skin wounds after irradiation. Confirm the results using qPCR. For individuals who received skin trauma 24 hours prior to the study, the hair on the dorsal side of the rat was removed using a light shearing knife under light anesthesia (inhalation of isoflurane). On the day of the experiment (Day 0), two rats were placed each time in a custom acrylic dislocation for radiation or sham treatment. The rats were anesthetized (inhaled isoflurane) and sterilized according to standard surgical procedures within a few hours after irradiation. Under sterile conditions, 8 mm diameter biopsy bores were used, and two full-thickness round wounds were made in the center of the radiation field above the spinal cord of the rat's back. Hemostasis is achieved by blotting the wound with sterile gauze. A 5 mg/kg analgesic, Rimadyle (carprofen, pfizer, uSA), was administered subcutaneously every 12 hours for two days. The wound remained exposed during the study. The skin wound model has been described in J〇urdan#A(r Deposition is Diminished in Irradiated Skin I62630.doc -42· 201247875 in an Animal Model of Combined Radiation and Wound Skin

Injury." Radiat Res. 176:636-48, 2011). Both antibiotics are expected to affect the specific microbial phase present in the feces. This method will be able to determine the extent to which the antibiotic distort the radiation marker. It is expected that skin wounds may also affect the intestinal microbial phase after radiation exposure. It may include granulosa cell stimulating factor stimulating factors that stimulate blood cell production as an alternative to antibiotics. The method can determine whether such basic health conditions interfere with the response of intestinal microbes to relative radiation. EQUIVALENTS It will be appreciated by those skilled in the art that many equivalents of the specific embodiments of the invention described herein can be determined. The scope of the invention is not intended to be limited to the above description, but is described in the following claims. [Simplified Schematic] A scatter plot of 6 rat data is displayed to show the difference in data in irradiated rats. The information presented herein is used to generate the materials shown in Figures 7A and 7B. Since the rats failed to produce feces at the time of sampling, about 5% of the 432 values were lost. Each data point consisted of at least 4 biological replicate experiments. The bar shape presented by the mushroom 2 shows the proportion of the operational classification unit (OTU) of the Yi class classification present in the rat feces. For each sample, the six most abundant members of the department were shown. Each color block represents the comparison between the percentage of 〇τυ detected in the section and the total number of οτυ detected in the six most abundant sections. Grinding Μ Μ Describes the intestinal microflora in the feces before and after irradiation. In Figure 3, the Bray_Curtis distance between the different rat fecal samples was made using the 16S rRNA sequence measured by phyloChip. Analysis 162630.doc •43· 201247875 The presence of all hybridization signals in all 7484 〇τυ - no score. The Wdonis test determined and lined for clarity, the non-metric multidimensional scaling of the samples showed that the microbial community was significantly different in days (P < 0.001), whereas in rats it was not (p &lt; 〇〇 9 ). The hierarchical clustering described in 03b shows the pedigree relationship of the microbial phase in rat f. The sample lines were clustered using the farthest nearest neighbor distance (completely linked) algorithm to show a strong correlation between the microscopic phase and the number of days after irradiation. Iron describes candidate biomarkers for radiation exposure. Figure 4 shows a Venus diagram illustrating the OTU abundance, showing the background between Days and Days; between the background and Day 21; and between the background and the combined Day 4-21 (all days) The statistics have changed significantly. The black numbers indicate the number of OTUs shared between the analyses. The non-metric multidimensional scaling of the samples based on the 147 common OTUs found in Figure 4A shown in Figure 48 shows that the distances are far apart (P&lt;0.001)' This is not the case with rats (p&lt;〇〇9). For the sake of clarity, the data points are drawn with lines. Yan 5 presents a heat map that highlights the tendency of 〇τυ to increase (blue) and decrease (, 'work color) after radiation. The Log2 change multiple of Days compared to the average of Day 4, Day π, and Day 21 is shown along with the t-test ρ value. Genera 6 presents a linear circle' which shows a continuous change in the abundance of 〇 TU after radiation exposure. The abundances of the three representative 〇TUs: 31902 '42924 and 39153 shown show enhanced, stable, and attenuated 16S rRNA performance. The error bars of the five rats at each time point indicate intra-group variation. The ratio of 39102 abundance to 39153 (ie log2 39102-log2 39153) acts as a potential composite biomarker for radiation. The value of this biomarker is on Days, 4, Days and 21 162630.doc 201247875 The days are -3.95, 0.98, 16 and respectively! 42. The value of each day was calculated independently and was statistically significant compared to day 0 (*=p&lt;〇 〇〇1). (d)... Explain that exposure to 10 Gy (accurate to 18 Gy (the axis of the sacred stools of the sputum of the various human bacteria in the transient changes. After the _ post' deformation of the abundance increased almost (10) times, while Clostridium. The abundance and the abundance _ abundance is relatively stable. Only (4) (4) The wing of the rat is observed to reduce the number of Clostridia by 10 times. The data are mean ± standard deviation. n = 5 / group (* = ρ &lt; 0.05 ' compared (Day )天). (4) The current-group line graph, which shows the exposure to the heart after the exposure of the first day, the second day, the fourth day, the 苐8 day, the first day, the 15th day, and the illusion day. And the abundance of biomarkers in the feces of rats irradiated with 18 Gy. (10)-峨exposed to 1 () Gy (Figure) and 18 Gy (pCR of biomarker dynamics in feces of rats in Figure 9) Confirmation. The dotted line shows the ratio of biomarkers of "acute increase/acute reduction", and the solid line shows the ratio of biomarkers of "chronic increase/chronic decrease". The data is the standard deviation of the flat soil. n=5 / group (* = ρ &lt; 〇, () 5, compared to "Tianbu" "heart (4) (10) shows the age and age of the rats not exposed to radiation (Figure 1 品) lines and diet (Figure just A bar graph of the stability of the population. 羼&quot; presents a map matching the rat biomarker 0TU with the human microbiome plan pyrosequencing data. _ shows the abundance of different microbial types in rats treated with different antibiotics A mixture of vancomycin and chloramphenicol, bacitracin polymyxin B and neomycin to alter the abundance of the intestinal microbial phase present in rat feces. 162630.doc -45- 201247875 Appendix Table 1: Increased οτυ after radiation

Log2 change factor 曰 average Log2 signal value before radiation compared to post-irradiation OTU All categories 0 4 11 21 Log2 P value 31902 Bacteria: cyanobacteria: YS2_SP: Rs-H34_CL: Uncategorized: unclassified: sfA 10.94 15.29 15.04 14.28 - 3.93 2.10E-04 46156 Bacteria: Bacteroides: P-184-o5_SP: C9_ B12_CL: Bacteroides: undivided &amp;:sfA 9.53 10.27 11.54 15.92 -3.04 2.90E-03 31674 Bacteria: cyanobacteria: YS2_SP: Rs-H34_CL: Not categorized: Not categorized: sfA &quot; 13.28 16.12 16.06 15.44 -2.60 7.29E-04 46174 Bacteria: Bacteroides: P-184-o5_SP: Bacteroides a_CL: Bacteroides: Unclassified: sfA 10.87 11.73 12.58 15.82 -2.50 3.23E-03 45878 Fine 3: Bacteroides: P-丨84-o5_SP: Bacteroides S_CL: Bacteroides: Unclassified: sfA 11.49 11.91 13.21 16.08 -2.25 4.11E-03 46045 Fine S: Bacillus: P-184-o5_SP: Bacteroides _CL: Bacteroides: Unclassified: sfK 11.88 12.80 13.48 16.11 -2.25 4.54E-03 46464 Bacteria: Bacteroides: P-184-o5_SP: Bacteroides g_CL: Bacteroides: unclassified: sfA 12.29 12.89 14.10 16.40 -2.17 1.30E-03 46118 Fine S: Bacteroides: p-184-o5_SP: Bacteroides g_CL: Bacteroides: undivided Class: sfA 12.18 12.71 13.79 16.44 -2.13 3.96E-03 46123 Fine: Bacteroides: P-184-o5_SP: Bacteroides g_CL: Bacteroides: Unclassified: sfA 12.13 12.62 13.76 16.40 -2.13 2.49E-03 10509 Fine ^: Thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 13.65 13.87 16.56 16.89 -2.12 2.91E-04 10461 Bacteria: thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 12.88 12.96 15.75 16.16 -2.07 3.70E-03 46422 Bacteria: Bacteroides: p-184-o5_SP: Bacteroides g_CL: Bacteroides: unclassified: sfA 12.65 13.11 14.43 16.27 -1.95 3.93E-03 10021 Fine^: Thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 13.60 14.10 16.34 16.17 -1.94 2.64E-03 46592 Bacteria: Bacteroides: p-184-o5_SP: Bacteroides g_CL: Bacteroides: unclassified: sfA 12.49 12.64 14.17 16.47 -1.93 5.86E-03 45539 Fine &quot;Ϊ: Bacteroides: p-184-o5_SP: rc5-47_CL: Bacteroides: unclassified: sfA 11.71 12.30 13.13 15.45 -1.92 5.88E-03 46370 Pseudomonas: p-184-o5_SP: SWPTl 5_aaa02b04_CL: Bacteroides: unclassified: sfA 12.58 13. 13 14.21 16.15 -1.92 1.39E-03 9685 Bacteria: thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus ihsfA 14.04 14.20 16.69 16.92 -1.90 5.63E-04 46656 Bacteria: Bacteroides Gate: P-184-o5_SP: Bacteroides a_CL: Bacteroides: Unclassified: sfA 13.10 13.68 14.67 16.57 -1.87 2.77E-03 10405 Fine S: thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus g:sfA 13.39 13.33 16.06 16.37 -1.87 1.50E-03 162630.doc -46 - 201247875 10597 Bacteria: thick-walled bacillus: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Milk Bacillaceae: sfA 13.63 13.84 16.15 16.39 -1.83 4.48E-04 10577 Bacteria: Thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 14.05 14.30 16.60 16.70 -1.82 6.08E -04 10309 Bacteria: thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus g: sfA 14.27 14.59 16.81 16.85 -1.81 4.71E-04 10155 Bacteria: thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus g: sfA 14.32 14.67 16.80 16.87 -1.79 2.54E-04 10849 Bacteria: thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus : Breast Section: sfA 14.51 14.92 17.02 16.89 -1.77 6.51E-04 45635 Bacteria: Bacteroides: p-184_o5_SP: rc2· 15_CL: Bacteroides: unclassified: sfA 13.29 13.86 14.78 16.54 -1.77 4.21E-03 10632 Thin thick wall Bacterium: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 14.43 14.98 16.86 16.74 -1.76 2.94E-04 32070 Bacteria: cyanobacteria: YS2_SP: Rs-H34_CL: Uncategorized: Not Classification: sfA 13.31 15.33 15.28 14.57 -1.75 5.64E-03 46404 Bacteria: Bacteroides: P-184-o5_SP: Bacteroides _CL: Bacteroides: Unclassified: sfA 13.15 13.97 14.50 16.22 -1.75 2.23E-03 46326 Fine &quot;Ϊ: Bacteroides: P-184-o5_SP: Bacteroides _CL: Bacteroides: Unclassified: sfA 13.27 13.71 14.86 16.47 -1.75 1.72E-03 46044 Bacteria: Bacteroides: p-184 -o5_SP: Bacteroides _CL·Bacteroides: Unclassified: sfA 12.74 13.21 14.33 15.87 -1.73 2.21E-03 10168 Bacteria: Thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus family: sfA 13.94 13.71 16.47 16.77 -1.72 2.38E-03 46556 Bacteria: Bacteroides: ρ·184-o5_SP: rc5-47_CL: Bacteroides: unclassified: sfA 13.29 13.65 14.74 16.62 -1.72 3.99E-03 10516 Bacteria: thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 14.15 14.31 16.62 16.66 • 1.71 5.78E-04 9808 Bacteria: thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 14.44 14.83 16.82 16.81 -1.71 2.61E-04 10830 Bacteria: phylum: bacillus _SP: Lactobacillus _CL: milk Bacillus: Lactobacillus Jf: sfA 14.02 13.88 16.50 16.67 -1.66 2.00E-03 10768 Bacteria: Thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Streptococcus: sfA 14.03 15.36 15.97 15.72 -1.66 1.87E-04 10001 Bacteria: Thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus g: sfA 14.31 14.60 16.74 16.49 -1.64 3.93E-03 45933 Bacteria: Bacteroides :p-184-o5_SP:rc5-47_CL: Bacteroides: unclassified: sfA 12.98 13.10 14.39 16.31 -1.62 5.65E-03 10232 Bacteria: thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus Eye: Streptococcus: sfA 13.17 14.04 15.20 15.14 -1.62 1.12E-03 10250 Bacteria: Thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Streptococcus: sfA 13.17 14.04 15.20 15.14 - 1.62 1.12E -03 10596 Bacteria: thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Streptococcus: sfA 13.17 14.04 15.20 15.14 -1.62 1.12E-03 35067 Bacteria: thick-walled bacteria: Clostridium _SP: C18_h03_2_CL: Clostridium: unclassified: sfA 14.82 15.60 17.20 16.53 -1.62 4.28E-03 9680 Bacteria: thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus g :sfA 14.52 14.56 16.86 16.98 -1.61 3.48E-03 162630.doc • 47· 201247875 10858 Bacteria: thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 14.93 15.45 17.20 16.96 -1.61 2.55E-03 10122 Bacteria: thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 14.50 14.61 16.86 16.81 -1.59 9.20E-04 10078 Bacteria: thick wall Bacterium: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus if: sfA 14.90 15.30 17.13 17.02 -1.58 2.77E-04 9710 Bacteria: thick-walled bacteria: Bacillus _SP: Lactobacillus _ CL: Lactobacillus: Lactobacillus: sfA 14.57 14.79 16.85 16.82 -1.58 6.19E-04 31568 Bacteria: cyanobacteria: YS2_SP: Rs-H34_CL: Uncategorized: unclassified: sfA 14.91 16.62 16.73 16.05 -1.56 2.06E-03 45735 Bacteria: Bacteroides: p-184-o5_SP: Bacteroides g_CL: Bacteroides: Unclassified: sfA 12.79 13.32 14.26 15.46 -1.55 3.68E-03 10520 Fine ^: Thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 14.51 14.84 16.77 16.55 -1.54 2.36E-03 10148 Bacteria: thick-walled bacteria: bacillus _SP: Lactobacillus _CL: Lactobacillus : Lactobacillus if: sfA 14.70 14.64 16.99 17.07 -1.54 1.58E-03 9839 Bacteria: thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Streptococcus: sfA 13.55 14.49 15.45 15.31 -1.53 1.76E-04 31504 Bacteria: cyanobacteria: YS2_SP: Rs-H34_CL: unclassified: unclassified: sfA 14.27 15.84 16.14 15.40 -1.52 5.27E-03 45848 Bacteria: Bacteroides: p-184-o5__SP: Bacteroides g_CL : Bacteroides: Unclassified: sfG 13.75 14.45 15.08 16.27 -1.52 3.88E-03 45505 Bacteria: Bacteroides: P-184-o5_SP: Bacteroides@_CL: Bacteroides: Unclassified: sfG 13.75 14.45 15.08 16.27 - 1.52 3.88E-03 46054 Bacteria: Bacteroides: p-184-o5_SP: Bacteroides S_CL: Bacteroides: Unclassified: sfG 13.75 14.45 15.08 16.27 -1.52 3.88E-03 10701 Fine &quot;Ϊ: Thick Mycelium: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 14.58 14.46 16.86 16.97 -1.52 2.20E-03 10474 Bacteria: thick-walled bacteria: Bacillus _SP: Lactobacillus _ CL: Lactobacillus: Lactobacillus: sfA 14.56 14.45 16.81 16.91 -1.50 3.00E-03 10135 Bacteria: Thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 14.78 14.78 17.02 17.05 • 1.50 1.32E-03 10356 Bacteria: Thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 14.76 15.13 16.93 16.71 -1.49 1.43E-03 9747 Bacteria: Thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus if: sfA 14.77 15.03 16.94 16.79 -1.49 7.73E-04 9883 Bacteria: thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 14.43 14.76 16.62 16.35 -1.48 5.48E-04 10017 Bacteria: thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 14.54 14.67 16.71 16.66 -1.48 1.79E-03 10140 Bacteria: thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 14.61 14.63 16.83 16.80 -1.48 1.39E-03 9727Bacteria: thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 14.63 14.55 16.85 16.92 -1.47 3.10E-03 10801 Bacteria: thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 14.70 14.69 16.90 16.92 -1.47 2.21E-03 10654 Bacteria: thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus Section: sfA 14.63 14.62 16.88 16.81 -1.47 1.96E-03 • 48 · 162630.doc 201247875 10456 Bacteria: thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 14.80 14.76 17.01 17.02 -1.47 1.81E-03 10711 Bacteria: Thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 15.03 15.19 17.17 17.12 -1.46 1.55E-03 9635 Bacteria: Thick Mycobacterium: bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 14.91 14.99 17.07 17.06 -1.46 1.48E-03 10722 Bacteria: thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus i_.sfA 14.76 14.72 16.97 16.99 -1.46 2.45E-03 10277 Bacteria: Thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 14.55 14.55 16.77 16.73 -1.46 2.17E-03 10823 Bacteria: Thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 15.06 15.48 17.12 16.96 -1.46 3.47E-04 10484 Bacteria: Thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 14.90 15.23 16.99 16.83 -1.45 1.79E-03 10636 Bacteria: thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 14.82 14.85 17.00 16.96 -1.45 2.05E-03 10281 Bacteria: thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 14.98 15.01 17.11 17.17 -1.45 2.64E-03 45631 Bacteria: Bacteroides: p-184-o5_SP: rc5-47_CL: Bacteroides: unclassified: sfA 14.01 14.62 15.33 16.41 -1.44 3.04E-03 9843 Fine&quot; Ϊ: thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 14.84 15.02 16.95 16.89 -1.44 1.15E-03 9694 Bacteria: thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 14.98 14.98 17.11 17.13 -1.42 2.25E-03 9954 Bacteria: thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus Section: sfA 14.14 13.96 16.31 16.41 -1.42 5.34E-03 10347 Bacteria: thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus A: sfA 14.59 14.65 16.68 16.67 -1.41 5.55E-03 10661 Bacteria: Thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 15.08 15.22 17.23 17.01 -1.41 4.18E-03 46647 Bacteria: Bacteroides: p-184-o5_SP: Bacteroides _CL: Bacteroides: unclassified: sfG 14.02 14,70 15.31 16.25 -1.40 5.67E-03 10243 Bacteria: thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus A :sfA 15.16 15.25 17.23 17.19 -1.40 2.27E-03 10313 Bacteria: thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 14.90 14.82 17.04 17.02 -1.39 3.12E-03 10134 Bacteria: thick-walled bacteria: bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 14.88 14.84 17.01 16.95 -1.39 3.03E-03 9884 Bacteria: thick-walled bacteria: Bacillus _SP : Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 14.88 14.84 17.01 16.95 -1.39 3.03E-03 10230 Bacteria: Thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Milk Bacillaceae: sfA 14.73 14.80 16.79 16.76 -1.39 2.47E-03 46449 Bacteria: Bacteroides: p-184-o5_SP: Bacteroides g_CL: Bacteroides: unclassified: sfA 14.24 14.73 15.63 16.50 -1.38 4.48E-03 9763 Fine ^: thick wall Bacterium: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 14.76 14.98 16.73 16.70 -1.38 1.61E-03 9794 Bacteria: thick-walled bacteria: Bacillus _SP: Lactobacillus _ CL: Lactobacillus: Lactobacillus: sfA 14.50 14.85 16.54 16.24 -1.38 2.62E-03 • 49· 162630.doc 3 201247875 10397 Bacteria: thick-walled bacteria: Bacillus genus _SP: Lactobacillus _CL: Lactobacillus Head: Lactobacillus family: sfA 13.99 14.13 16.18 15.79 -1.37 1.53E-03 10750 Bacteria: thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 15.25 15.35 17.30 17.22 - 1.37 2.58E-03 10803 Bacteria: Thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 15.29 15.37 17.36 17.24 -1.37 2.29E-03 10044 Bacteria: thick-walled bacteria : Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus if: sfA 15.21 15.41 17.23 17.07 -1.36 3.61E-03 10561 Bacteria: thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 15.21 15.41 17.23 17.07 -1.36 3.61E-03 10441 Bacteria: thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 15.34 15.53 17.36 17.19 -1.35 2.28E-03 9992 Bacteria: Thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 15.34 15.53 17.36 17.19 -1.35 2.28E-03 10675 Bacteria: thick wall Mycelium: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus if: sfA 15.34 15.53 17.36 17.19 • 1.35 2.28E-03 9670 Bacteria: thick-walled bacteria: bacillus _SP: Lactobacillus _ CL: Lactobacillus: Lactobacillus g: sfA 15.34 15.53 17.36 17.19 -1.35 2.28E-03 9899 Bacteria: Thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 15.34 15.53 17.36 17.19 -1.35 2.28E-03 10116 Bacteria: Thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Streptococcus: sfA 14.08 15.17 15.79 15.30 -1.35 4.57E-03 10713 Bacteria: Thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 15.36 15.50 17.38 17.23 -1.34 2.54E-03 10201 Bacteria: thick-walled bacteria: Bacillus _SP: milk Bacillus _CL: Lactobacillus: Lactobacillus: sfA 15.36 15.50 17.38 17.23 -1.34 2.54E-03 10074 Bacteria: Thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus :sfA 15.36 15.50 17.38 17.23 -1.34 2.54E-03 10619 Bacteria: thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus g: sfA 15.36 15.50 17.38 17.23 -1.34 2.54E-03 9770 Bacteria: thick-walled bacteria: bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 15.36 15.50 17.38 17.23 -1.34 2.54E-03 10660 Bacteria: thick-walled bacteria: Bacillus _SP : Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 15.36 15.50 17.38 17.23 -1.34 2.54E-03 9717 Bacteria: Thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Milk Bacillaceae: sfA 15.36 15.50 17.38 17.23 -1.34 2.54E-03 9779 Bacteria: Thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 15.36 15.50 17.38 17.23 -1.34 2.54E -03 10680 Bacteria: thick-walled bacteria: bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus g: sfA 15.36 15.50 17.38 17.23 -1.34 2.54E-03 10299 Bacteria: thick-walled bacteria: rod _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 15.36 15.50 17.38 17.23 -1.34 2.54E-03 10278 Bacteria: thick-walled bacteria: bacillus _SP: Lactobacillus _CL: Lactobacillus目: Lactobacillus family: sfA 15.36 15.50 17.38 17.23 -1.34 2.54E-03 10640 Bacteria: thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 15.36 15.50 17.38 17.23 • 1.34 2.54E-03 10634 Bacteria: thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 15.36 15.50 17.38 17.23 -1.34 2.54E-03 -50- 162630.doc 201247875 9714 Bacteria: Thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus if: sfA 15.36 15.50 17.38 17.23 • 1.34 2.54E-03 10418 Bacteria: thick-walled bacteria: Bacillus _SP : Lactobacillus _CL: Lactobacillus: Lactobacillus if: sfA 15.36 15.50 17.38 17.23 -1.34 2.54E-03 10354 Bacteria: thick-walled bacterium: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Milk Bacilli ih:sfA 15.36 15.50 17.38 17.23 -1.34 2.54E-03 10216 Bacteria: thick-walled bacteria: bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 15.36 15.50 17.38 17.23 • 1.34 2.54E-03 10519 Bacteria: Thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 15.36 15.50 17.38 17.23 • 1.34 2.54E-03 9806 Bacteria: thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus g: sfA 15.36 15.50 17.38 17.23 -1.34 2.54E-03 9977 Bacteria: Thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Milk Bacillus: Lactobacillus: sfA 15.36 15.50 17.38 17.23 -1.34 2.54E-03 10420 Bacteria: Thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 15.36 15.50 17.38 17.23 -1.34 2.54E-03 10403 Bacteria: Thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus g: sfA 15.36 15.50 17.38 17.23 -1.34 2.54E-03 10287 Bacteria: thick-walled bacteria Gate: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 15.05 15.10 17.06 17.01 -1.34 3.58E-03 10246 Bacteria: thick-walled bacteria: bacillus _SP: Lactobacillus _CL : Lactobacillus: Lactobacillus g: sfA 14.96 14.81 17.03 17.03 -1.33 4.27E-03 9981 Bacteria: Thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus g: sfA 15.19 15.23 17.23 17.11 -1.3 3 2.55E-03 10301 Bacteria: thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 15.46 15.63 17.46 17.29 -1.33 2.54E-03 10386 Bacteria: thick-walled bacteria : Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus g: sfA 14.91 14.98 16.92 16.81 - 1.33 3.00E-03 9741 Bacteria: Thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus g:sfA 15.29 15.43 17.26 17.14 -1.32 2.25E-03 10436 Bacteria: Thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Streptococcus: sfA 13.65 14.21 15.42 15.26 -1.31 5.82E-03 10317 Bacteria: thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus if: sfA 15.34 15.51 17.31 17.12 -1.31 2.50E-03 10372 Bacteria: thick wall Bacterium: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus fhsfA 15.24 15.35 17.21 17.07 -1.30 3.69E-03 10407 Bacteria: thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 15.01 15.21 16.99 16.73 -1.30 1.63E-03 9814 Bacteria: Thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus g: sfA 14.75 14.89 16.70 16.53 -1.29 5 .05E-03 10829 Bacteria: Thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 14.93 14.87 16.95 16.85 -1.29 4.03E-03 9919 Bacteria: thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 14.98 15.39 16.88 16.53 -1.29 1.25E-03 10736 Bacteria: thick-walled bacteria: bacillus _SP: Lactobacillus _CL: milk Bacillus: Lactobacillus: sfA 15.43 15.59 17.37 17.18 -1.29 2.44E-03 10624 Bacteria: Thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 15.42 15.62 17.36 17.14 -1.28 2.23E-03 -51 - 162630.doc 201247875 10504 Bacteria: Thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 14.92 14.83 16.94 16.85 -1.28 4.69E- 03 9660 Bacteria: thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 15.42 15.55 17.34 17.17 -1.27 2.66E-03 10559 Bacteria: thick-walled bacteria: Bacillus _ SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 15.34 15.50 17.26 17.05 -1.27 2.63E-03 9667 Bacteria: Thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus :sfA 15.42 15.52 17.36 17.15 -1.26 3.01E-03 10026 Bacteria: thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 15.00 15.21 16.95 16.62 -1.26 3.21E-03 10344 Bacteria: Thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 14.71 14.85 16.69 16.37 -1.26 4.04E-03 9993 Bacteria: thick-walled bacteria: Bacillus _SP : Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 15.49 15.70 17.39 17.12 -1.25 1.20E-03 10235 Bacteria: Thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Milk Bacillaceae: sfA 15.35 15.38 17.31 17.11 -1.25 5.34E-03 10324 Bacteria: Thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus ^: sfA 14.90 15.01 16.81 16.63 -1.25 4.21E -03 10767 Bacteria: thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 15.07 15.39 16.94 16.60 -1.24 3.90E-03 9812 Bacteria: thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 15.46 15.69 17.32 17.09 -1.24 3.14E-03 10718 Bacteria: thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus : Lactobacillus family: sfA 14.74 14.64 16.66 16.62 -1.24 5.96E-03 45563 Bacteria: Bacteroides: P-184-o5_SP: Bacteroides _CL: Bacteroides: unclassified: sfA 14.46 15.03 15.84 16.23 -1.24 5.23 E-03 10495 Bacteria: thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 15.63 15.83 17.50 17.23 -1.23 3.88E-03 10743 Bacteria: thick-walled bacteria: bacillus __SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 14.86 14.99 16.76 16.49 -1.22 3.62E-03 9905 Bacteria: thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus Eye: Streptococcus: sfA 14.04 14.67 15.61 15.48 -1.22 6.65E-04 10703 Bacteria: Thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Streptococcus: sfA 13.72 14.28 15.37 15.16 - 1.21 5.I3E-03 9927 Bacteria: thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 15.66 15.79 17.55 17.26 -1.21 4.30E-03 9790 Bacteria: thick-walled bacteria Gate: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 15.70 15.86 17.57 17.27 -1.20 5.02E-03 9706 Bacteria: thick-walled bacteria: bacillus _SP: Lactobacillus _CL :milk Bacillus: Lactobacillus: sfA 15.70 15.86 17.57 17.27 • 1.20 5.02E-03 10721 Bacteria: Thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 15.23 15.45 17.02 16.70 -1.17 3.77E-03 10258 Bacteria: Thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 15.58 15.85 17.35 17.02 -1.16 4.27E-03 10385 Bacteria: thick-walled bacteria Gate: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 15.62 16.05 17.35 16.89 -1.14 4.11E-03 9847 Bacteria: thick-walled bacteria: Bacillus _SP: Lactobacillus _CL : Lactobacillus: Lactobacillus: sfA 15.29 15.56 17.03 16.65 -1.12 5.11E-03 162630.doc -52- 201247875 10781 Bacteria: thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus : Lactobacillus isfA 15.67 15.89 17.40 17.08 -1.12 4.95E-03 10202 Bacteria · Thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Streptococcus g: sfA 14,17 14.71 15.70 15.38 - 1.09 3.47E-03 Table 2: οτυ after radiation reduction L〇g2 change multiple 曰 average Log2 signal value before radiation compared to after οτυ all categories 0 4 11 21 L〇g2 P value 39143 Bacteria: thick-walled bacteria: Clostridium net _SP: Clostridium _CL: Clostridium: Clostridium: s£i 15.33 14.40 13.04 12.71 1.94 1.88E-03 39672 Bacteria: thick-walled bacteria: Clostridium _SP: Clostridium _CL: Clostridium: Clostridium: sfyi 15.28 14.33 13.30 12.72 1.83 2.35E-03 39286 Bacteria: thick-walled bacteria: Clostridium _SP: Clostridium _CL: Clostridium : Clostridium: sf 15.43 14.56 13.15 12.80 1.92 2.37E-03 39546 Bacteria: thick-walled bacteria: Clostridium _SP: Clostridium _CL: Clostridium: Clostridium: sf 15.20 14.39 12.94 12.59 1.90 2.49E-03 39988 Bacteria: thick-walled bacteria: Clostridium sp. SP: Clostridium _CL: Clostridium: Clostridium: sf乂15.34 14.55 13.31 12.93 1.74 3.49E-03 39172 Bacteria: thick-walled bacteria : Clostridium SP: Clostridium _CL: Clostridium: Clostridium: sf^ 15.33 14.47 13.51 12.97 1.68 3.51E-03 39360 Bacteria: thick-walled bacteria: Clostridium _SP: Clostridium _CL: Clostridium: Clostridium: sf 15.55 14.74 13.66 13.13 1.71 3.66E-03 39375 bacteria · thick-walled bacteria: Clostridium _SP: Clostridium _CL: Clostridium: Clostridium: sfi 15.41 14.59 13.60 13.09 1.65 3.66E-03 39292 Bacteria: thick-walled bacteria: Clostridium sp. SP: Clostridium _CL: Clostridium: Clostridium :sfi 15.25 14.35 13.42 12.87 1.71 3.89E-03 40032 Bacteria: thick-walled bacteria: Clostridium sp. SP: Clostridium _CL: Clostridium: Clostridium: sf 15.25 14.35 13.42 12.87 1.71 3.89E-03 38998 Bacteria: thick-walled bacteria: Clostridium sp. SP: Clostridium _CL: Clostridium: shuttle g: Sf and 15.35 14.53 13.61 13.04 1.62 4.54E-03 39482 Bacteria: thick-walled bacteria: fusi _5卩: Clostridium _CL: Shuttle g: Clostridium: sfA 15.41 14.51 13.86 13.17 1.57 4.75E-03 40092 Bacteria: thick-walled bacteria: Clostridium net SP: Clostridium _CL: Clostridium: shuttle Department of bacteria: sf^ 15.24 14.46 13.41 12.96 1.63 4.98E-03 39490 Bacteria: thick-walled bacteria: mold fungi SP: Clostridium _CL: shuttle g: Clostridium: Sf 15.42 14.64 13.83 13.24 1.52 5.42E -03 39320 Bacteria: thick-walled bacteria: Clostridium sp. SP: Clostridium _CL: Clostridium: Clostridium: sf and 15.45 14.66 13.86 13.28 1.51 5.67E-03 39540 Bacteria: thick-walled bacteria: Clostridium SP: Clostridium _CL·· Clostridium: Clostridium: sf and 15.29 14.42 13.71 13.08 1.55 5.72E-03 39162 Bacteria: thick-walled bacteria: Clostridium sp.: Clostridium _CL: Clostridium Objective: Clostridium: sf; [ 15.30 14.42 13.72 13.08 1.56 5.72E-03 39354 Bacteria: thick wall Gate: Clostridium sp: Clostridium i _CL: Clostridium: Clostridium: sf;; 15.23 14.39 13.56 12.97 1.58 5.88E-03 162630.doc •53- 201247875 39536 Bacteria: thick-walled bacteria: Clostridium _SP: Clostridium _CL: Clostridium: Clostridium: sfA 15.18 14.32 13.52 12.99 1.57 5.95E-03 39645 Bacteria: thick-walled bacteria: Clostridium _SP: Clostridium _CL: Clostridium : Clostridium: sfA 15.24 14.38 13.80 13.16 1.46 6.01E-03 40015 Bacteria: thick-walled bacteria: Clostridium _SP: Clostridium _CL: Clostridium: Clostridium: sfA 15.35 14.59 13.73 13.14 1.53 6.16 E-03 39762 Bacteria: thick-walled bacteria: Clostridium _SP: Clostridium _CL: Clostridium: Clostridium: sfi 15.27 14.57 13.57 13.17 1.50 6.58E-03 38995 Bacteria: thick-walled bacteria: shuttle Fungi _SP: Clostridium _CL: Clostridium: Clostridium: sfA 15.35 14.61 13.79 13.23 1.47 7.30E-03 40033 Bacteria: thick-walled bacteria: Clostridium _SP: Clostridium _CL: Shuttle Fungi: Clostridium: sfi 15.39 14.66 13.92 13.33 1.42 7.69E-03 39297 Bacteria: thick-walled bacteria: Clostridium _SP: Clostridium _CL: Clostridium: Clostridium: sfA 15.39 14.70 13.77 13.28 1.48 7.92E-03 39153 Bacteria: thick-walled bacteria: Clostridium _SP: Clostridium _CL: Clostridium : Clostridium: sfA 14.89 13.95 13.45 12.86 1.47 8.04E-03 39310 Bacteria: thick-walled bacteria: Clostridium _SP: Clostridium _CL: Clostridium: Clostridium: sfA 15.61 14.82 14.36 13.64 1.33 8.31 E-03 39947 Bacteria: thick-walled bacteria: Clostridium _SP: Clostridium _CL: Clostridium: Clostridium: sfA 15.28 14.56 13.83 13.26 1.40 8.34E-03 39741 Bacteria: thick-walled bacteria: shuttle Fungi _SP: Clostridium _^CL: Clostridium: Clostridium: sfA 15.43 14.58 14.09 13.52 1.37 8.39E-03 39381 Bacteria: thick-walled bacteria: Clostridium _SP: Clostridium _CL: Clostridium: Clostridium: sfA 15.44 14.62 14.14 13.55 1.34 8.97E-03 39164 Bacteria: thick-walled bacteria: Clostridium _SP: Clostridium _CL: Clostridium: Clostridium: sfA 15.44 14.76 14.03 13.35 1.39 8.98E-03 39283 Bacteria: thick-walled bacteria: Clostridium _SP: Clostridium _CL: Clostridium: Clostridium: sfA 15.34 14.65 13.96 13.33 1.36 9.27E-03 39682 Bacteria: thick-walled bacteria Door: Clostridium net _SP: Clostridium _CL: Clostridium: Clostridium: sf^ 15.10 14.33 13.74 13.04 1.39 1.04E-02 39895 Bacteria: thick-walled bacteria: Clostridium _SP: Clostridium _CL: Clostridium: Clostridium: sfA 15.45 14.69 14.18 13.54 1.32 1.09E-02 39747 Bacteria: Mycobacterium: Clostridium _SP: Clostridium _CL: Clostridium: Clostridium: sfA 15.31 14.56 13.96 13.21 1.40 1.12E-02 39368 Bacteria: thick-walled bacteria: Clostridium _SP: Clostridium _CL: Clostridium: Clostridium: sfA 15.20 14.52 13.83 13.21 1.35 1.20E-02 39237 Bacteria: thick-walled bacteria: Clostridium _SP ·. Clostridium _CL: Clostridium: Clostridium :sfA 15.21 14.45 13.97 13.33 1.29 1.25E-02 39814 Bacteria: thick-walled bacteria: Clostridium _SP: Clostridium _CL: Clostridium: scorpion: sfA 15.12 14.39 14.07 13.30 1.20 1.30E-02 39828 Bacteria: thick-walled bacteria: Clostridium _SP: Clostridium _CL: Clostridium: Clostridium: sfA 15.49 14.72 14.36 13.74 1.22 1.32E-02 39823 Bacteria: thick-walled bacteria: Clostridium _SP : Clostridium _CL: Clostridium: Clostridium: sfA 15.34 14.59 14.10 13.60 1.24 1.37E-02 40020 Bacteria: thick-walled bacteria: Clostridium _SP: Clostridium _CL: Clostridium: excellent Bacillus 14.96 14.13 13.80 13.11 1.27 1.39E-02 40029 Bacteria: thick-walled bacteria: Clostridium _SP: Clostridium _CL: Clostridium: Clostridium: sfA 15.53 14.77 14.48 13.84 1.17 1.61E-02 -54 - 162630.doc 201247875 39783 Bacteria: thick-walled bacteria: Clostridium nets SP: Clostridium _CL: Clostridium : Clostridium: sf again 15.57 14.84 14.47 13.98 1.13 1.70E-02 39870 Bacteria: thick-walled bacteria: Clostridium _SP: Clostridium _CL: Clostridium: Clostridium: sf 15.28 14.49 14.20 13.62 1.18 1.95E-02 39035 Bacteria: thick-walled bacteria: Clostridium sp. SP: Clostridium _CL: Clostridium: Clostridium: sf and 15.06 14.21 13.97 13.58 1.14 2.06E-02 39763 Bacteria: thick-walled bacteria : Clostridium _SP: Clostridium _CL: Clostridium · Clostridium: 15.22 14.57 14.21 13.41 1.16 2.06E-02 39475 Bacteria: thick-walled bacteria: Clostridium _SP: Clostridium _CL : Clostridium: Clostridium: sf and 15.43 14.79 14.51 13.83 1.05 2.ΠΕ-02

Table 3: OTU unchanged after irradiation

Log2 change multiples before exposure compared to after OTU all classification 0 4 11 21 L〇g2 40058 bacteria: thick-walled bacteria: Clostridium sp.: Clostridium CL: Clostridium: Clostridium: sfA &quot 14.35 13.16 15.08 14.41 0.13 39755 Bacteria: thick-walled bacteria: Clostridium SP: Clostridium CL: Clostridium: Clostridium: sfA — 15.25 14.76 15.76 14.83 0.13 42581 Bacteria · Thick-walled bacteria: Clostridium _SP: RF30 CL: Clostridium: RF6_FM: sfA ~ 15.30 14.31 15.86 15.36 0.13 3341 Bacteria: thick-walled bacteria: Clostridium _SP: C23 cl9 CL: Clostridium: unclassified: sfA &quot;&quot; 14.56 14.02 15.29 14.03 0.12 5410 Bacteria: thick-walled bacteria: Clostridium _SP: Clostridium CL: Clostridium: rumen genus _FM: sfA - 14.79 14.46 15.26 14.29 0.12 39597 bacteria: thick-walled bacteria: shuttle Fungi _SP: Clostridium CL: Clostridium: Clostridium: sfA — 14.77 14.58 15.07 14.33 0.11 11139 Bacteria: thick-walled bacteria: Bacillus _SP: Lactobacillus CL: Lactobacillus: Balloonaceae :sfA — 15.82 15.74 16.08 15.34 0.10 39194 Bacteria: thick-walled bacteria: Clostridium _SP: Clostridium CL: Clostridium: Clostridium: sfA &quot; 14.97 14.79 15.27 14.57 0.09 1207 Bacteria · Thick-walled bacteria: Clostridium _SP: Clostridium CL: Clostridium: Clostridium _FM: sfA ' 14.38 13.17 14.81 14.91 0.09 39723 Bacteria: thick-walled bacteria: Clostridium _SP: Clostridium CL: Clostridium: Clostridium: sfA ~ 15.37 15.06 15.80 15.00 0.09 43035 Bacteria: thick-walled bacteria: Clostridium _SP · Clostridium CL: Clostridium: Clostridium: sfA &quot 14.79 14.50 15.26 14.37 0.08 39885 Bacteria: thick-walled bacteria: Inoculation network _SP: Clostridium CL: Clostridium: Clostridium: sfA &quot; 14.92 14.08 15.52 14.91 0.08 40040 Bacteria: thick-walled bacteria: cast闺纲 I_SP: Clostridium CL: Clostridium: Clostridium: sfA ~ 14.78 14.48 15.26 14.36 0.08 39271 Bacteria: thick-walled bacteria: Clostridium net-SP: Clostridium CL: Clostridium: Clostridium :sfA ~ 15.15 14.90 15.56 14.76 0.08 39852 Bacteria: thick-walled bacteria: Clostridium _SP: Clostridium CL: Clostridium: Clostridium: sfA &quot; 14.97 14.80 15.35 14.53 0.08 I62630.doc -55- 201247875 39679 Bacteria: thick-walled bacteria: Clostridium _SP__ Clostridium _CL: Clostridium: Clostridium: sfA 15.15 14.97 15.56 14,72 0.07 42218 Bacteria: thick-walled bacteria: Clostridium _SP: RF30_CL: Clostridium S: RF6_FM: sfA 15.05 14 .23 15.86 14.86 0.06 39764 Bacteria: Thick-walled bacteria: Clostridium _SP: Clostridium _CL: Clostridium: Clostridium: sfA 14.92 14.66 15.34 14.58 0.06 43443 Bacteria: thick-walled g: Clostridium _SP: RL197_aah88clO_CL: Clostridium: unclassified: sfA 14.63 13.86 15.49 14.36 0.06 42850 Bacteria: thick-walled S-gate: Clostridium _SP: RF30_CL: Clostridium: RF6-FM: sfA 15.70 14.65 16.41 15.86 0.06 39099 Bacteria : Thick-walled bacteria: Clostridium _SP: Clostridium _CL: Clostridium: Clostridium: sfA 14.95 14.81 15.24 14.64 0.05 42710 Bacteria: thick-walled bacteria: Clostridium _SP: RF30_CL: Clostridium Head: RF6_FM: sfA 15.31 14.43 15.86 15.48 0.05 32681 Bacteria: thick-walled bacteria: Clostridium _SP: Cataquat _CL: Cata _OR: Cata _FM: sfL 15.90 14.58 16.71 16.26 0.05 40081 Bacteria : Thick-walled bacteria: Clostridium _SP: Clostridium _CL: Clostridium: Clostridium: sfA 14.81 14.60 15.23 14.45 0.05 39624 Bacteria: thick-walled bacteria: Clostridium _SP: Clostridium _ CL: Clostridium: Clostridium: sfA 14.86 14.67 15.30 14.47 0.05 7315 Bacteria: thick-walled bacteria: Clostridium _SP: Clostridium _CL: Clostridium: unclassified: sfA 15.14 14.42 16.17 14.69 0.05 39269Bacteria: thick-walled bacteria: Clostridium _SP: Clostridium _CL: Clostridium: Clostridium: sfA 15.59 15.39 15.95 15.30 0.04 3945 Bacteria: thick-walled bacillus: Clostridium _SP: C23_cl9_CL: shuttle Species: unclassified: sfA 14.85 14.45 15.59 14.40 0.04 39611 Bacteria: thick-walled bacteria: Clostridium _SP: Clostridium _CL: Clostridium: Clostridium: sfA 15.62 15.37 16.03 15.39 0.03 39996 Bacteria: thick Mycobacterium: Clostridium _SP: Clostridium _CL: Clostridium: Clostridium: sfA 15.85 15.67 16.24 15.57 0.02 39013 Bacteria: thick-walled bacteria: Clostridium _SP: Clostridium _CL: Clostridium: Clostridium: sfA 15.15 14.85 15.72 14.82 0.02 39208 Bacteria: thick-walled bacteria: Clostridium _SP: Clostridium _CL: scorpio: Clostridium: sfA 15.52 15.27 16.00 15.23 0.02 43541 bacteria : Thick-walled bacteria: Clostridium _SP: Clostridium _CL: Clostridium: Clostridium: sfA 15.89 15.80 16.17 15.67 0.01 39094 Bacteria: thick-walled bacteria: Clostridium _SP: Clostridium _ CL: Clostridium: Clostridium: sfA 15.63 15.44 16.08 15.33 0.01 42884 Bacteria: thick-walled bacteria: Clostridium net _SP: RF30_CL: Clostridium: RF6_FM: sfA 15, 57 14.72 16.38 15.60 0.01 1821 Bacteria: thick Mycobacterium: Clostridium _SP: BB6 8_CL: Clostridium: unclassified: sfA 15.19 14.80 15.97 14.80 0.01 39693 Bacteria: thick-walled bacteria: Clostridium _SP: Clostridium _CL: Clostridium: Clostridium: sfA 15.18 15.09 15.61 14.84 0.00 4457 Bacteria: thick-walled bacteria: Clostridium _SP: Clostridium _CL: Clostridium: Clostridium _FM: sfA 15.18 14.72 16.06 14.76 0.00 39139 Bacteria: thick-walled bacteria: Clostridium net _SP: shuttle Fungus _CL: Clostridium: Clostridium: sfA 15.55 15.43 16.01 15.25 -0.01 ·56· 162630.doc 201247875 241 Bacteria: thick-walled bacteria: Clostridium _SP: Clostridium _CL: Clostridium : Not classified as: sfA 14.90 14.19 15.64 14.90 -0.01 43252 Bacteria: Thick-walled bacteria: Clostridium _SP: Digestive Streptococcus _CL: Digestive Streptococcus 〇R: Digestive Streptococcus: sfA 15.47 15.34 15.75 15.34 -0.01 39815 Bacteria: Thick-walled bacteria: Clostridium _SP: Clostridium _CL: Clostridium: Clostridium: sfA 15.16 14.77 15.80 14.94 -0.01 39937 Bacteria: thick-walled bacteria: Clostridium _SP : Clostridium _CL: Clostridium: Clostridium: sfA 15.53 15.41 16.02 15.21 -0.02 8943 Bacteria: Thick-walled bacteria: Bacillus JP: Lactobacillus: L. Lactobacillus: Candida albicans _ FM: sfA 14.59 14.17 15. 22 14.46 -0.03 5627 Bacteria: thick-walled bacteria: Clostridium _SP: Clostridium _CL: Clostridium: Uncategorized: sfA 15.00 14.39 15.69 15,03 -0.04 37531 Bacteria: thick-walled bacteria: Clostridium _SP:SR5_CL: Clostridium: unclassified: sfG 15.31 14.40 16.21 15.44 -0.04 39274 Bacteria: thick-walled bacteria: Clostridium _SP: Clostridium _CL: Clostridium: Clostridium: sfA 14.81 14.75 15.31 14.47 -0.04 41940 Bacteria: thick-walled bacterium: Clostridium _SP: RF30_CL: Clostridium: RF6_FM: sfA 15.83 15.25 16.43 15.93 -0.04 39648 Bacteria: thick-walled bacteria: Clostridium net _SP: Clostridium _CL: Clostridium: Clostridium: sfA 15.44 15.31 15.96 15.17 -0.04 3517 Bacteria: thick-walled bacteria: Clostridium _SP: C23_cl9_CL: Clostridium: unclassified: sfA 14.46 14.16 15.37 13.97 -0.04 42941 Bacteria: thick-walled bacteria: Clostridium net _SP: RF30_CL: Clostridium S: RF6_FM: sfA 14.97 13.94 15.86 15.22 -0.04 43911 Bacteria: thick-walled bacteria: Clostridium _SP: Digestive Streptococcus _CL: Digestion Streptococcus _OR: Digestive Streptococcus: sfA 14.76 14.51 15.23 14.67 -0.04 42483 Bacteria: thick-walled bacteria: Clostridium _SP: RF30_CL: Clostridium: RF6_FM: sfA 14.87 13.71 15.95 15.08 -0.05 39544 Bacteria: thick-walled bacteria: Clostridium _SP: Clostridium _CL: Clostridium: Clostridium: sfA 15.00 14.62 15.71 14.82 -0.05 39667 Bacteria: thick-walled bacteria: Clostridium _SP: Clostridium _CL: Clostridium: Clostridium: sfA 14.93 14.77 15.56 14.62 -0.05 42965 Bacteria: thick-walled bacteria: Clostridium _SP: RF30_CL: Clostridium: RF6-FM: sfA 15.51 14.67 16.39 15.63 -0.06 43741 Bacteria: Thick-walled bacteria: Clostridium _SP: RL197_aah88clO_CL: Clostridium: unclassified: sfA 15.24 14.63 16.04 15.24 -0.06 5438 Bacteria: thick-walled bacteria: Clostridium _SP: Clostridium _CL: Clostridium: unclassified: sfA 14.71 14.13 15.46 14.73 -0.06 39911 Bacteria: thick-walled bacteria: Clostridium _SP: Clostridium _CL: Clostridium: Clostridium: sfA 14.87 14.75 15.46 14.58 -0.06 10036 Bacteria: thick-walled bacteria: bacillus _SP: Lactobacillus _CL: Lactobacillus: Streptococcus: sfA 15.20 14.70 15.88 15.21 -0.06 39951 Bacteria: thick-walled bacteria: Clostridium _SP: Clostridium _CL: Clostridium: Clostridium: sfA 15.16 15.05 15.67 14.94 -0.06 6638 Bacteria: thick-walled bacteria: Clostridium _SP: Clostridium _CL: Clostridium: unclassified: sfA 14.22 13.54 14.93 14.38 -0.06 39501 Bacteria: Thick Mycobacterium: Clostridium _SP: Clostridium _CL: Clostridium: Clostridium: sfA 14.98 14.85 15.56 14.71 -0.06 -57- 162630.doc 201247875 42924 Bacteria: thick-walled bacteria: Clostridium _ SP: RF30_CL: Clostridium: RF6_FM: sfA 15.56 15.14 16.23 15.49 -0.06 42293 Bacteria: thick-walled bacteria: Clostridium _SP: Digestive Streptococcus _CL: Digestive Streptococcus _OR: Digestive Streptococcus: sfA 15.56 15.53 15.91 15.43 -0.06 43372 Bacteria: thick-walled bacteria: Clostridium _SP: Digestive Streptococcus _CL: Digestive Streptococcus _OR: Digestive Streptococcus: sfA 16.01 15.93 16.30 15.99 -0.06 41704 Bacteria: Thick-walled bacteria: membranous bacteria _SP: RF39_CL: unclassified: unclassified: sfA 15.49 14.63 16.30 15.73 -0.07 42604 bacteria: thick-walled bacteria: Clostridium _SP: RF30_CL: Clostridium: RF6-FM :sfA 15.72 15.09 16.36 15.92 -0.07 39069 Bacteria: thick-walled bacteria: Clostridium _SP: Clostridium _CL: Clostridium: Clostridium: sfA 15.54 15.40 16.16 15.26 -0.07 8998 Bacteria: thick-walled bacteria : Bacillus _SP: Lactobacillus _CL: Lactobacillus: Candida albicans ^zsfA 14.34 13.97 14.88 14.37 -0.07 43775 Bacteria: thick-walled bacteria: Clostridium _SP: Streptococcus pneumoniae _CL: Digestive Streptococcus _OR: Digestive Streptococcus: sfA 15.16 15.04 15.50 15.15 -0.07 39875 Bacteria: Thick-walled bacteria: Clostridium _SP: Clostridium _CL: Clostridium: Clostridium :sfA 14.81 14.47 35.55 14.62 -0.07 6108 Bacteria: thick-walled bacteria: Clostridium _SP: Clostridium g_CL: Clostridium: Clostridium: sfA 13.73 12.97 14.61 13.83 -0.07 43133 Bacteria: thick-walled bacteria Door: Clostridium _SP: Digestive Streptococcus _CL: Digestive Streptococcus _R: Digestive Streptococcus: sfA 15.02 14.88 15.51 14.90 -0.08 1892 Bacteria: Thick-walled bacteria: Clostridium _SP: Shuttle Fungus _CL: Clostridium: Unsorted: sfA 15.22 14.82 16.24 14.82 -0.08 7499 Bacteria: thick-walled bacteria: Clostridium _SP: Digestive Streptococcus _CL: Digestive Streptococcus _OR: Streptococcus pneumoniae Section: sfA 15.78 15.73 16.05 15.80 •0.08 17452 Bacteria: thick-walled bacteria: Grignard _SP: gramia _CL: gramia _OR: gramia _FM: sfA 15.34 15.32 15.82 15.12 -0.08 43335 bacteria : Thick-walled bacteria: Clostridium net _SP: Digestive Streptococcus _CL: Digestive Streptococcus _OR: Digestive Streptococcus: sfA 15.59 15.49 15.96 15.58 -0.08 952 Bacteria: thick-walled bacteria: Clostridium _ SP: Clostridium _CL: Clostridium: genus genus _? 1^: 5 『14.74 13.95 15.81 14.72 -0.08 3122 Bacteria: thick-walled bacteria: Clostridium _SP: C23_k02_CL: Clostridium: C22_o06_FM: sfA 14.22 13.76 15.28 13.88 -0.08 2202 Bacteria: thick-walled bacteria: Clostridium net _SP: Clostridium _CL: Clostridium: Clostridium _ Bacteridae: sfA 15.64 15.03 16.50 15.66 -0.09 4715 Bacteria: thick-walled bacteria: Clostridium _SP: Clostridium _CL: Clostridium: rumen genus _FM: sfA 15.21 14.93 15.70 15.25 -0.09 11161 Bacteria: thick-walled bacteria: Bacillus JP: Lactobacillus: J: L: Lactobacillus: Balloonaceae: sfA 14.88 14.62 15.34 14.93 -0.09 42250 Bacteria: thick-walled bacteria: Clostridium net _SP: unclassified: unclassified: unclassified: sfA 14.74 14.32 15.76 14.39 -0.09 43391 bacteria: thick-walled bacteria: shuttle Fungi _SP: Digestive Streptococcus _CL: Digestive Streptococcus _011: Digestive Streptococcus: sfA 15.59 15.53 15.92 15.57 -0.09 43929 Bacteria: Thick-walled bacteria: Clostridium _SP: Digestive Streptococcus _ CL: Digestive Streptococcus _OR: Digestive Streptococcus: sfA 15.29 15.14 15.80 15.19 -0.09 39534 Bacteria: Thick-walled bacteria: Clostridium _SP: Clostridium _CL: Clostridium: Clostridium: sfA 15.1 9 14.97 15.85 15.01 -0.09 162630.doc -58- 201247875 39916 Bacteria: thick-walled bacteria: Clostridium _SP: Clostridium _CL: Clostridium: Clostridium: sfA 15.04 14.87 15.63 14.89 -0.09 39707 bacteria : Thick-walled bacteria: Clostridium _SP: Clostridium _CL: Clostridium: Clostridium: sfA 15.75 15.72 16.29 15.53 -0.09 39156 Bacteria: thick-walled bacteria: Clostridium _SP: Clostridium _CL: Clostridium: Clostridium: sfA 14.67 14.11 15.58 14.59 -0.09 42759 Bacteria: thick-walled bacteria: flexible membrane bacteria S_SP: Katerni _0 / Katney 8_OR: Katney S_FM: sfA 14.60 14.05 15.38 14.64 -0.09 1918 Bacteria: thick-walled bacteria: Clostridium _SP: Clostridium _CL: Clostridium: eubacteria 15.32 14.60 16.44 15.20 -0.09 39414 bacteria: thick-walled bacteria: Clostridium _SP: Clostridium _CL: Clostridium: Clostridium: sfA 14.88 14.74 15.49 14.70 -0.10 28133 Bacteria: thick-walled bacteria: Clostridium _SP: Digestive Streptococcus _CL: Digestive Streptococcus _OR: Streptococcus pneumoniae Section: sfA 14.80 14.62 15.24 14.82 -0.10 43501 Bacteria: thick-walled bacteria: Clostridium _SP: Digestive Streptococcus _CL: Digestive Streptococcus _OR: Digestive Streptococcus: sfA 15.83 15.79 16.17 15.82 -0.10 360 38 Bacteria: thick-walled bacteria: Clostridium _SP: Butyric acid-producing bacteria _Α2· 207_CL: Clostridium: unclassified: sfA 14.18 14.29 14.83 13.71 -0.10 43610 Fine-walled bacteria: Clostridium _SP: Digestive Streptococcus _CL: Digestive Streptococcus _OR: Digestive Streptococcus: sfA 15.85 15.77 16.21 15.85 -0.10 3801 Bacteria: Thick-walled bacteria: Clostridium _SP: C23_c 19_CL: Clostridium: Uncategorized: sfA 14.80 14.45 15.73 14.51 -0.10 1784 Bacteria: thick-walled bacteria: Clostridium _SP: Clostridium _CL: Clostridium: Clostridium _FM: sfA 15.11 14.32 15.82 15.49 •0.10 2210 Bacteria: thick-walled bacteria Door: Clostridium _SP: C23_k02_CL: Clostridium: C22-o06_FM: sfA 14.96 14.57 15.97 14.63 -0.10 2307 Bacteria: thick-walled bacteria: Clostridium _SP: Clostridium _CL: Clostridium: No Classification: sfA 15.46 14.70 16.84 15.15 -0.10 43826 Bacteria: thick-walled bacteria: Clostridium _SP: Digestive Streptococcus _CL: Digestive Streptococcus _OR: Digestive Streptococcus: sfA 15.91 15.87 16.26 15.92 -0.10 2486 Bacteria: thick-walled bacteria: Clostridium _SP: Clostridium _CL: Clostridium: Clostridium _FM: sfA 14.53 14.29 15.33 14.29 -0.10 39559 Bacteria: thick-walled bacteria: Clostridium _SP: Clostridium _CL: Shuttle Head: Clostridium: sfA 15.10 14.93 15.79 14.88 -0.10 9590 Bacteria: thick-walled bacteria: Bacillus _SP: Lactobacillus _CL: Lactobacillus: Candida albicans _FM: sfA 14.64 14.23 15.33 14.66 -0.10 278 Bacteria: thick-walled bacteria: Clostridium _SP: Clostridium _CL: Clostridium: eubacteria 14.10 13.33 15.08 14.21 -0.11 41631 bacteria: thick-walled bacteria: Clostridium _SP: Clostridium _ CL: Clostridium: Agrobacterium _?^1:5^0 14.88 14.66 15.56 14.73 -0.11 39376 Bacteria: thick-walled bacteria: Clostridium _SP: Clostridium _CL: Clostridium: Clostridium :sfA 15.45 15.35 16.07 15.26 •0.11 40458 Bacteria: thick-walled bacteria: flexible membrane bacteria S_SP: RF39_CL: p-3870-23G5_OR: unclassified: sffi 14.73 14.03 15.31 15.16 -0.11 11384 bacteria: thick-walled bacteria: bacillus _ SP: Lactobacillus _CL: Lactobacillus: Lactobacillus: sfA 14.04 13.31 14.87 14.26 -0.11 43268 Bacteria: thick-walled bacteria: Clostridium _SP: Digestive Streptococcus _CL: Digestive Streptococcus _OR : Digestive Streptococcus: sfA 15.28 15.23 15.71 15.24 -0.11 162630.doc -59- 201247875 43678 Bacteria: thick-walled bacteria: Clostridium _SP: Digestive Streptococcus _CL: Digestive Streptococcus _OR: Digestive Chain Department of bacteria: sfA 15.80 15.75 16.22 15.76 -0.11 3422 Bacteria: thick-walled bacteria: Clostridium _SP: BB68_CL: Clostridium: unclassified: sfA 15.30 15.35 15.95 14.92 -0.11 42934 Bacteria: thick-walled bacteria: Clostridium _SP: Uncategorized: Uncategorized: Uncategorized: sfA 15.30 14.86 16.29 15.09 -0.11 38464 Bacteria: Thick-walled bacteria: Clostridium _SP: p-4154-6 Wa5_CL: Clostridium: C10_I02_FM: sfA 14.74 13.78 15.26 15.50 -0.11 39516 Bacteria: thick-walled bacteria: Clostridium _SP: Clostridium _CL: Clostridium: Clostridium: sfA 15.30 14.96 16.01 15.25 -0.11 43544 Bacteria: thick-walled bacteria: Clostridium _SP: Digestive Streptococcus _CL: Digestive Streptococcus _OR: Digestive Streptococcus: sfA 15.30 15.15 15.56 15.54 -0.11 4764 Bacteria: Thick-walled bacteria: Clostridium _SP: Clostridium _CL: Shuttle Species: rumen genus _FM:sfA 14.40 13.94 15.38 14.21 -0.11 43658 Bacteria: thick-walled bacteria: Clostridium _SP: Digestive Streptococcus _CL: Digestive Streptococcus _OR: Digestive Streptococcus: sfA 16.04 16.02 16.42 16.03 -0.12 5475 Bacteria: thick-walled bacteria: Clostridium _SP: Clostridium _CL: Clostridium: rumen genus _FM: sfA 14.60 14.03 15.46 14.66 -0.12 39223 Fine : Thick-walled bacteria: Clostridium _SP: Clostridium _CL: Clostridium: Clostridium: sfA 15.33 15.14 15.97 15.24 -0.12 11663 Bacteria: thick-walled bacteria: Bacillus _SP: Lactobacillus _ CL: Lactobacillus: Balloonaceae: sfA 15.28 15.18 15.95 15.06 -0.12 42595 Bacteria: thick-walled bacteria: blister bacteria _SP: ketnibacterium J: L: hunger bacterium 〇 : :: hunter ®_FM:sfA 15.20 14.53 16.03 15.39 -0.12 110 Bacteria: thick-walled bacteria: Clostridium _SP: Clostridium _CL: Clostridium: rumen genus _FM:sfA 14.59 14.34 15.35 14.44 -0.12 3560 Bacteria: Thick-walled bacteria: Clostridium _SP: Clostridium _CL: Clostridium: Unclassified: sfA 14.78 14.64 15.52 14.54 -0.12 43819 Bacteria: thick-walled bacteria: Clostridium _SP: Digestive streptococci _ CL: Digestive Streptococcus _OR: Digestive Streptococcus: sfA 15.30 15.21 15.77 15.29 -0.12 42328 Bacteria: Thick-walled bacteria: Clostridium _SP: RF30_CL · Clostridium: RF6-FM: sfA 14.54 13.65 15.49 14.86 -0.12 4217 Bacteria: thick-walled bacteria: Clostridium _SP: Clostridium _CL: Clostridium: rumen genus _FM: sfA 15.35 15.22 16.11 15.09 -0.12 4595 bacteria: thick-walled bacteria: Clostridium _SP: Clostridium _CL· Clostridium Strong Senla g_FM: sfA 15.12 14.90 15.81 15.02 -0.12 42569 Bacteria: thick-walled bacteria: Clostridium _SP: RF30J: L: Clostridium: RF6-FM: sfA 15.01 14.01 16.01 15.39 -0.12 40518 Bacteria: thick wall Fungus: Clostridium _SP: Digestive Streptococcus _CL: Digestive Streptococcus _OR: Digestive Streptococcus: sfA 14.90 14.08 15.84 15.16 -0.12 43280 Bacteria: Thick-walled bacteria: Clostridium _SP: Digestion Streptococcus _CL: Digestive Streptococcus _OR: Digestive Streptococcus: sfA 15.79 15.72 16.21 15,81 -0.12 650 Bacteria: thick-walled bacteria: Clostridium _SP: Clostridium _CL: Clostridium : eubacteria l_FM: sfA 14.68 14.30 15.54 14.59 -0.13 43539 Bacteria: thick-walled bacteria: Clostridium _SP: Digestive Streptococcus _CL: Digestive Streptococcus _OR: Digestive Streptococcus: sfA 15.18 15.15 15.53 15.23 -0.13 43349 Bacteria: Thick-walled bacteria: Clostridium _SP: Digestive Streptococcus _CL: Digestive Streptococcus _OR: Digestive Streptococcus: sfA 15.64 15.53 16.16 15.62 -0.13 162630.doc -60- 201247875 43488 Bacteria: thick-walled bacteria: Clostridium _SP: Digestive Streptococcus _CL: Digestive Streptococcus _OR: Digestive Streptococcus: sfA 16.07 16.06 16.44 16.10 -0.13 43270 Bacteria: Thick Mycobacterium: Clostridium _SP: Clostridium _CL: Clostridium: rumen genus _FM: sfA 15.10 14.81 15.73 15.16 • 0.13 43334 Bacteria: thick-walled bacteria: Clostridium _SP: Streptococcus pneumoniae _CL: Digestive Streptococcus _011: Digestive Streptococcus: sfA 15.00 14.87 15.62 14.93 • 0.13 39515 Bacteria: Thick-walled bacteria: Clostridium _SP: Clostridium _CL: Clostridium: Clostridium :sfA 15.86 15.82 16.44 15.72 -0.13 36985 Bacteria: thick-walled bacteria: Clostridium _SP: p-3024-SwA5_CL: Clostridium: unclassified: sfA 15.47 15.24 16.33 15.24 -0.14 4229 Bacteria: thick-walled bacteria: Clostridium _SP: adhufec25_CL: Clostridium: unclassified: sfA 14.60 14.28 15.58 14.34 -0.14 43795 Bacteria: thick-walled bacteria: Clostridium _SP: Digestive Streptococcus _CL: Digestive Streptococcus _R : Digestive Streptococcus: sfA 15.66 15.61 16.16 15.63 -0.14 -61 - 162630.doc 201247875 Sequence &lt;1丨0&gt; American Cui Kedel Diagnostics Limited Company &lt;120&gt; Microbial Marker as Radiation Exposure Index&lt;140&gt; 101106420 &lt;141&gt; 2012-02-24 &lt;150&gt;61/446,696;61/451,930;61/479,786; 61/491,452 &lt;151&gt;2011/02/25;2011/03/11;2011/04/27; 2011/05/31 &lt;160&gt; 14 &lt;170&gt; Pateniin version 3.5 &lt;210&gt;] &lt;211&gt; 19 &lt;212&gt; DNA &lt;213&gt;

&lt;400&gt; I ggttctgaga ggaggtccc &lt;210&gt; 2 &lt;211&gt; 18 &lt;212&gt; DNA &lt;213&gt; primer sequence &lt;400&gt; 2 gctgcctccc gtaggagt &lt;210&gt; 3 &lt;2Π&gt; 18 &lt;212&gt; DNA &lt;213&gt;Introduction sequence &lt;400&gt; 3 actcctacgg gaggcagc &lt;210&gt; 4 &lt;211&gt; 23 &lt;2)2&gt; DNA &lt;213&gt;Introduction sequence &lt;400&gt; 4 gcttcttagt caggtaccgt cat &lt;210&gt; 5 &lt ; 211 &gt; 19 &lt;212&gt; DNA &lt;2Π&gt; primer sequence &lt;400&gt; 5 gtgccagcmg ccgcggtaa &lt;210&gt; 6 &lt;211&gt; 23 &lt;212&gt; DNA &lt;213&gt; primer sequence &lt;400&gt; 6 162630· Sequence Listing.doc 201247875 23 scctcaaggg cacaacctcc aag —HJ t 歹β sequence tc ct 722DN5 7 ct Λ ΛΛΑ &gt; c 012 3 ο 0&amp; 1 Tl. 1 11 Λν c 2 ow22 4 t &lt; V &lt;&lt;&lt; t

Gc s 8C 2 2 &lt;210&gt; 8 &lt;211&gt; 21 &lt;212&gt; DNA &lt;2丨3&gt; primer sequence &lt;400&gt; 8 icitcacaca cgcggcatgg c 2! &lt;210&gt; 9 &lt;211&gt; 20 &lt;2Ώ&gt; DNA &lt;2&gt;3&gt;Introduction sequence &lt;400&gt; 9 cgcgtgggta acctgccctg &lt;210&gt; 10 &lt;211&gt; 22 &lt;212&gt; DNA &lt;2]3&gt;Introduction sequence &lt;400&gt; 10 cgcgggtcca icctataccg ca 22 &lt;210&gt; 11 &lt;2Π&gt; 20 &lt;212&gt; DNA &lt;213&gt; primer sequence &lt;Α0ΰ&gt; 11 tcgggccict igccatcgga &lt;210&gt; 12 &lt;211&gt; 21 &lt;212>leg&lt;2]3&gt; Sequence &lt;400&gt; 12 ccggttaacg cttgcacccc t 21 &lt;210&gt; 13 &lt;23.]&gt; 20 &lt;212&gt; DNA &lt;213&gt; primer sequence &lt;400&gt; 13 ctgggatgga cctgcggtgt , 7r\ 77 0 12 3 &lt;21&lt;21&lt;21&lt;21 14 24 DNA primer sequence &lt;400> 14 ttacga£ccg aaaccctict tcac 24 162630-SEQ ID NO.

Claims (1)

201247875 VII. Patent Application Range: 1. A method for identifying and/or characterizing radiation exposure, comprising: providing a reference microbial marker associated with one or more characteristics of the radiation exposure; and 7 identifying or characterizing the radiation exposure thereof The microbial markers present in the microbial phase sample are determined in the individual. 2. A method according to π, wherein the microbial phase sample comprises a sample of a plurality of types of microorganisms found in a particular organ or tissue of the individual. 3. The method of claim 1, wherein the microbial phase sample comprises a sample of substantially all types of microorganisms found in a particular organ or tissue of the individual. 4. The method of claim 2 or 3, wherein the particular organ or tissue of the individual is the gastrointestinal tract of the individual. 5. 6. The method of Kiss 4, wherein the microbial phase sample is a stool sample. The method of claim 1, wherein the microbial marker comprises a content or a content of one or more types of microorganisms or components or products thereof present in the microbial sample. The method of claim 1, wherein the microbial marker comprises a content group of substantially all types of microorganisms or components or products thereof present in the microbial sample. 8. One or more of the methods of claim 1. And wherein the microbial marker comprises the activity of the microbial sample species of the microorganism or a component or product thereof. 9. The method of claim 6 or 7 wherein the content or content of the DNA sequence, wherein the microbial marker comprises one or more quantitative groups. 10. The method of claim 6 or 7, wherein the microbial marker comprises a content or a content of one or more 16S rRNA gene sequences. The method of claim 10, wherein the 16S rRNA gene sequence is selected from the group consisting of Clostridium, Sarcina, Barnesiena, and milk. The method of claim 1 or claim 2, wherein the at least one of the 16S rRNA gene sequences is selected from the group consisting of firmicutes. e 13. The method of claiming, wherein the individual is a human. 14. The method of claim 1, wherein the individual is an animal. 15. The method of claim 1, wherein the individual is a plant. 16. The method of claim 1 wherein the radiation exposure characteristic comprises a light exposure agent. 17. The method of claim 1, wherein the radiation exposure characteristic of the gamma + soil θ Λ 包含 comprises a radiation exposure type of a microbial marker defining a pattern associated with the radiation exposure. The method comprises the steps of: determining the first group of microbial phases The first group of one or more types of microorganisms or 'and a knife or product in the sample, wherein the first group of microorganisms (4) has the common feature of radiation exposure; the second group of microorganisms is determined to be phase 0. The second combination of one or more types of microorganisms or components or products in the sputum, the second group of microbial phase samples of 5 hai has no common feature of radiation exposure, and the burren may be similar to the sample of the first group of microorganisms in other aspects; 162630 .doc 201247875 Identification of microbial markers 'contains the presence of common features of the first exposure 卞m The amount of summer associated with the presence or absence of radiation. The method of item 18, wherein the sample of the microorganism phase is contained in a sample of the microorganism of the same type, or the plurality of types 2, such as the method of claim 1, the sample of the microorganism of the specific type of the microorganism phase sample. The phase sample comprises substantially all of the 21. 22. intestines found in the collection of the isomorphic official or tissue. The method comprising the method of claim 19 or 2G, wherein the organ or tissue is the method of claim 18, The method of claim 18, wherein the common feature of the radiation exposure comprises a duration after exposure. [24] The method of claim 18, wherein the light exposure is common Features include exposure dose. 25. The method of claim 24, wherein the radiation is exposed to a dose of GGy to 10 Gy. 26. The method of claim 18, wherein the common feature of the light exposure comprises an exposure type β" 27. The method of claim 18, wherein the one or more types of microorganisms or components or products thereof comprise a group Or a group of DNA sequences of various types of microorganisms. 28. The method of claim 27, wherein the one or more types of microorganisms or components or products thereof comprise a group of 16S rRNA gene sequences of one or more types of microorganisms. I62630.doc