JP2019176754A - Inspection method for ovulation disorders - Google Patents

Abstract

To provide inspection methods for ovulation disorders that have high determination accuracy and less invasive to the subject even with simple sample collection.SOLUTION: Provided is an inspection method for ovulation disorders characterized by detecting bacteria in the gut microbiota in a specimen; more preferably, the bacteria are one or more selected from the group consisting of the following [B1] to [B4], [F1] to [F13], [A1], [FS1], and [P1]; more preferably, the bacteria are one or more selected from the group consisting of the following [B1] to [B4], [F1] to [F13], [A1], [FS1], and [P1].SELECTED DRAWING: None

Description

  The present technology relates to a method for testing ovulation disorders, a method for assisting diagnosis of ovulation disorders, a method for producing a composition containing an edible material for improving ovulation disorders, and the like.

In a woman having normal menstruation, one mature egg from the ovaries is usually excreted around 14 days from the start of menstruation, and ovulation is performed. In order for ovulation to occur normally, it is necessary for the three sites of the hypothalamus, pituitary gland, and ovary to secrete hormones.
However, a state in which this ovulation is not performed normally occurs due to an external factor or an internal factor, and this state is referred to as ovulation disorder (for example, mild to severe ovulation disorder, hyperprolactin ovulation disorder). Among these ovulation disorders, it is said that there are many relatively mild ovulation disorders of mild to moderate. Factors of this relatively mild ovulation disorder include, for example, excessive dieting and physical and mental stress such as work and family mental work. And it is said that such a factor triggers so-called hormone balance and causes ovulation disorders.

This ovulation disorder is one of the causes of infertility. In recent years, infertility in women caused by this ovulation disorder has been increasing.
For example, Patent Document 1 discloses improvement / treatment of ovulation disorders characterized by using soybean fine powder as an active ingredient, and various symptoms based on ovulation disorders including irregular menstruation, infertility, hormonal abnormalities, infertility anxiety, and stress. Agents have been proposed.

  Here, when determining whether it is an ovulation disorder, measuring basal body temperature has been performed for a long time. This is based on the fact that body temperature changes occur in two phases, the "low temperature period (about 2 weeks)" from the start of menstruation to ovulation and the "high temperature period (about 2 weeks)" from ovulation to the next menstruation. . If there is no ovulation, the woman will continue the low-temperature period for a long time, so this state is judged as an ovulation disorder.

  In addition, when a doctor determines whether or not a subject has an ovulation disorder, a plurality of times (specifically, four times of a low temperature period, an ovulation period, a high temperature period, and a menstrual period) in a physiological cycle (about 1 month), The subject performs an outpatient examination, and a doctor determines ovulation disorder based on the examination result. And as an inspection method for determining with an ovulation disorder, an internal examination, a transvaginal ultrasonic test | inspection, a uterine fallopian imaging test, a blood test etc. are mentioned, for example.

JP 2003-306439 A

As described above, the basal body temperature needs to be measured daily, and it is necessary to go to the hospital multiple times a month for testing for ovulation disorders. There are many financial, physical and mental burdens on the subject. For this reason, there is a request from the subject to know whether or not the ovulation disorder is as accurate as possible with the simplest possible method.
In addition, ultrasonic tomography is one of the non-invasive methods for testing ovulation disorders. In this ultrasonic tomography test, ovulation can be confirmed but there is no ovulation. Can not. For this reason, the fact that confirming that there is no ovulation is mainly basal body temperature measurement and blood hormone blood test. This blood collection is invasive with bleeding and pain and needs to be performed by a healthcare professional.
In addition, since it is determined by a doctor's empirical personal skill whether or not the subject has an ovulation disorder, the diagnosis result of the ovulation disorder is likely to vary.
Even if a drug for ovulation disorders is used, it is important to first determine whether or not the subject has an ovulation disorder.

  As described above, there are few or limited methods for examining ovulation disorders. Needless to say, judgment criteria for ovulation disorders that have good judgment accuracy even with simple sample collection and are less invasive to the subject (so-called minimally invasive or non-invasive) and testing methods using this are still sufficiently proposed. Not.

  Therefore, the main object of the present technology is to provide a method for examining an ovulation disorder that has good determination accuracy even with simple sample collection and is less invasive to a subject.

  As a result of various investigations on the criteria for determining ovulation disorders, the present inventors have found that intestines contained in fecal samples of women who are “ovulation disorders (no ovulation)” and “not ovulation disorders (with ovulation)” women. As a result of confirming the internal bacterial flora, the occupancy rate of specific intestinal bacteria has changed between women who are "ovulation disorders (no ovulation)" and "no ovulation disorders (with ovulation)" I noticed. As a result, the present inventors have found that the use of specific intestinal bacteria in the intestinal flora and their occupancy ratio as criteria for determining ovulation disorders can be used for the examination of ovulation disorders, and completed the present invention. It was. The present invention is as follows.

[1]
A test method for ovulation disorders, which comprises detecting bacteria in an intestinal flora in a specimen.
[2]
The bacterium is one or more bacteria selected from the group consisting of the following [B1] to [B4], [F1] to [F13], [A1], [FS1], and [P1]. The method according to [1] above.
[B1]: Bacteroidetes genus Bacteroidia class Bacteroidales> Prevotlaceae family Prevotella genus,
[B2]: Bacteroidetes gate Bacteroidia class Bacteroidales eyes S24-7,
[B3]: Bacteroidetes Gate Bacteroidia class Bacteroidales eyes Rikenellaceae,
[B4]: Bacteroidetes gate Bacteroidia class Bacteroidales eyes [Paraprevotellaceae],
[F1]: Firmicutes Gate Clostridia Class Closridiales eyes,
[F2]: Firmicutes gate Clostridia class Closridiales eyes Lachnospiraceae,
[F3]: Firmicutes Clostridia Class Closridiales [Tissierellaceae] Family WAL_1855D,
[F4]: Firmicutes Clostridia class Closridiales> Ruminococcaceae family Oscillospira,
[F5]: Firmicutes gate Clostridia class Closridiales eyes Lachnospiraceae family Anaerostipes genus,
[F6]: Firmicutes gate Clostridia class Closridiales eyes Veillonellaceae family Dialister genus,
[F7]: Firmicutes Clostridia class Closridiales> Ruminococcaceae family Ruminococcus,
[F8]: Firmicutes Clostridia class Closridiales> Peptococcaceae family rc4-4,
[F9]: Firmicutes Gate Clostridia Class Closridiales> Lachnospiraceae Family Roseburia,
[F10]: Firmicutes gate Erysipelotrichi class Erysipelotrichales> Erysipelotrichaceae family AllobacuLum,
[F11]: Firmicutes Clostridia class Closridiales> Clostridiaceae family Candidatus Arthromitus,
[F12]: Firmicutes Gate Clostridia Class Closridiales> Ruminococcaceae Family Other,
[F13]: Firmicutes Clostridia class Closridiales> Peptococcaceae family Peptococcus genus,
[A1]: Actinobacteria genus Coriobacteriia class Coriobacteriales order Coriobacteriaceae family Atopobium genus,
[FS1]: Fusobacteria genus Fusobacteriia class Fusobacteriales order Leptotrichiaceae Leptorichia genus,
[P1]: Proteobacteria genus Betaproteobacteria class Burkholderiales, Burkholderiaceae family Burkholderia genus [3]
The bacteria are two types of combinations [B1] and [B2], two types of combinations [F1] and [F3], or at least one of the above [B1] to [B4] and the above [F1] to [F1] The method according to [1] or [2] above, which is a combination of at least one of [F13].
[4]
A method for assisting diagnosis of an ovulation disorder, comprising a step of determining an ovulation disorder based on an occupation ratio of bacteria in an intestinal flora in a specimen.
[5]
A method of measuring bacterial occupancy in the intestinal flora to determine ovulation disorders.
[6]
A method for detecting a substance that regulates ovulation disorders based on the occupancy rate of bacteria in the intestinal flora in a specimen.
[7]
The detection method according to [6] is a detection method including the following (1) and (2).
(1) a first detection step of detecting an occupancy rate of bacteria in an intestinal bacterial flora in the sample from a sample collected from a subject who has ingested the test substance;
(2) A second detection step of determining whether or not the test substance is a substance that regulates ovulation disorders based on a change in the occupancy rate of the bacteria in the intestinal flora, and detecting a substance that regulates ovulation disorders.
[8]
The method according to [7] above, wherein the test substance is an edible material.
[9]
The manufacturing method of the composition which detects the edible material for ovulation disorder improvement by the method of said [8] description, and contains the said edible material for ovulation disorder improvement.

According to the present technology, it is possible to provide a method for testing an ovulation disorder that has good determination accuracy even with simple sample collection and is less invasive to a subject.
In addition, the effect described here is not necessarily limited, and may be any effect described in the present technology.

  Next, a preferred embodiment of the present invention will be described. However, the present invention is not limited to the following preferred embodiments, and can be freely changed within the scope of the present invention. In the present specification, percentages are expressed by mass unless otherwise specified.

The present technology provides a test method for an ovulation disorder characterized by detecting bacteria in an intestinal flora in a specimen.
By using specific intestinal bacteria in the intestinal flora (more preferably, the occupancy rate of the bacteria) as criteria for determining ovulation disorders, the accuracy of determination is good even with simple sample collection and invasiveness to the subject. Can provide a method for examining ovulation disorders, a diagnosis assistance method, a diagnosis method and a determination method, and a method for detecting an ovulation disorder regulating substance.

In the present technology, the bacterium is one or two selected from the group consisting of the following [B1] to [B4], [F1] to [F13], [A1], [FS1], and [P1]. The above bacteria are preferred.
Furthermore, in the present technology, the bacterium is the two types of combinations [B1] and [B2], the two types of combinations [F1] and [F3], or at least one of the above [B1] to [B4]. In addition, a combination of at least one of [F1] to [F13] is preferable.
Hereinafter, the present technology will be described in detail.

[Inspection marker]
This technique uses a specific intestinal bacterium in the intestinal flora and its occupancy rate as a test standard or a judgment standard for ovulation disorders. Bacteria and their occupancy used in this technology can be used for the purpose of detection or determination of ovulation disorders, can be used as indicators of ovulation disorders, and can also be used as test markers or determination markers. is there.
More specifically, the specific intestinal bacteria in the intestinal flora used for the test standards for ovulation disorders in this technology are (1) [Bacteroidetes], (2) [Firmicutes], (3) [Actinobacteria] , (4) [Fusobacteria], and (5) [Proteobacteria], or one or more bacteria selected from the group consisting of [Proteobacteria].
The (1) [Bacteroidetes], (2) [Firmicutes], (3) [Actinobacteria], (4) [Fusobacteria], and (5) [Proteobacteria] refer to bacteria classified at the portal level. .
Bacteria (hereinafter also referred to as “the respective bacteria of the present technology” or “the respective bacteria”) used in the test standards for ovulation disorders of the present technology are more preferably the following [B1] to [B4], [F1 ] To [F13], [A1], [FS1], and [P1], or one or more kinds of bacteria selected from the group consisting of [P1].
The [B1] to [B4], [F1] to [F13], [A1], [FS1] and [P1] refer to bacteria classified into any one of the eye, family and genus levels.

(1) As [Bacteroidetes]
[B1]: Bacteroidetes genus Bacteroidia class Bacteroidales> Prevotlaceae family Prevotella genus,
[B2]: Bacteroidetes gate Bacteroidia class Bacteroidales eyes S24-7,
[B3]: Bacteroidetes Gate Bacteroidia class Bacteroidales eyes Rikenellaceae,
[B4]: The Bacteroidetes Bacteroidia class Bacteroidales (Paraprevotellaceae) family.

(2) As [Firmicutes]
[F1]: Firmicutes Gate Clostridia Class Closridiales eyes,
[F2]: Firmicutes gate Clostridia class Closridiales eyes Lachnospiraceae,
[F3]: Firmicutes Clostridia Class Closridiales [Tissierellaceae] Family WAL_1855D,
[F4]: Firmicutes Clostridia class Closridiales> Ruminococcaceae family Oscillospira,
[F5]: Firmicutes gate Clostridia class Closridiales eyes Lachnospiraceae family Anaerostipes genus,
[F6]: Firmicutes gate Clostridia class Closridiales eyes Veillonellaceae family Dialister genus,
[F7]: Firmicutes Clostridia class Closridiales> Ruminococcaceae family Ruminococcus,
[F8]: Firmicutes Clostridia class Closridiales> Peptococcaceae family rc4-4,
[F9]: Firmicutes Gate Clostridia Class Closridiales> Lachnospiraceae Family Roseburia,
[F10]: Firmicutes gate Erysipelotrichi class Erysipelotrichales> Erysipelotrichaceae family AllobacuLum,
[F11]: Firmicutes Clostridia class Closridiales> Clostridiaceae family Candidatus Arthromitus,
[F12]: Firmicutes Gate Clostridia Class Closridiales> Ruminococcaceae Family Other,
[F13]: Firmicutes Clostridia class Closridiales> Peptococcaceae family Peptococcus.

(3) As [Actinobacteria]
[A1]: Actinobacteria genus Coriobacteriia class Coriobacteriales order Coriobacteriaceae family Atopobium genus.
(4) As [Fusobacteria]
[FS1]: Fusobacteria genus Fusobacteriia class Fusobacteriales, Leptotrichiaceae family Leptorichia genus.
(5) As [Proteobacteria]
[P1]: Proteobacteria genus Betaproteobacteria class Burkholderiales> Burkholderiaceae family Burkholderia genus.

In this technology, by detecting bacteria in the gut microbiota from the subject's specimen, the subject determines whether the subject is “applicable” or “not applicable” for the ovulation disorder; Can be determined as “present” and “none”. That is, bacteria present in the intestinal flora can be used as a test marker.
In the test method of the present technology, it is more preferable to use each bacterium of the present technology, and each bacterium used for the test marker is “corresponds to an ovulation disorder” from a sample that is easy to collect and less invasive. Since the determination can be performed with high accuracy, it is excellent.

[Sample]
The specimen used in the present technology is not particularly limited as long as it is a sample derived from a subject and contains intestinal bacteria, and examples thereof include feces, digestive tract fluid, digestive tract washing fluid, and biological sample. Of these, feces are preferable because they have less burden on the subject and less invasiveness.
The collection of feces is not particularly limited, but examples include rectal stool collection methods (using rectal swabs, etc.), excrement stool collection methods (using fecal swabs, etc.), and rectal stool collection methods using rectal swabs are accurate. From the viewpoint of

〔subject〕
The subject in this technology is a woman. The subject is preferably adolescent to sexual maturity from the viewpoint of accuracy, and less than 40 years old is preferable from the viewpoint of accuracy. Since this technique is derived from the relationship between a woman diagnosed with and without ovulation disorder and its intestinal microflora, as shown in the examples described later, it is highly accurate.

When testing ovulation disorders using bacteria in the gut microbiota in the sample, use known analysis methods to determine the presence and occupancy of each bacterium in the gut microbiota. To measure. Based on this measurement result and <cut-off value> described later, the presence or absence of ovulation disorder can be determined from the specimen, and this determination can be used as the test result. More specific methods for measuring the intestinal microflora will be described later in <Measurement of the total number of enteric bacteria contained in the specimen> and <Measurement of presence / absence of each bacterium in the intestinal microflora and each occupancy>. .
Since the present inventors have a strong relationship between the occupancy rate of a specific intestinal bacterium in the intestinal flora and a subject with or without ovulation disorder as shown in Examples below, the bacterium (more preferably Is used as a criterion for determining ovulation disorders, and the occupancy of this specific intestinal bacterium is a cut-off value.
For this reason, this technique can determine the presence or absence of an ovulation disorder by measuring and detecting each bacterium of this technique, and can also test | inspect an ovulation disorder by this.
Furthermore, the present technology can test the ovulation disorder more accurately based on the occupancy of each bacterium and the following [cutoff value], and thereby can accurately determine whether or not the subject has the ovulation disorder. .
In addition, the determination of “whether or not ovulation disorder” may be a two-stage determination of “with ovulation disorder” or “without ovulation disorder”, or “is ovulation disorder” “high possibility of ovulation disorder” It may be a multi-step determination in which a plurality of determination categories are provided such as “the probability of ovulation failure is low” and “not ovulation failure”.

[Cutoff value]
In the test marker of the present technology, it is preferable to detect the ovulation disorder using the cut-off value shown below as a criterion for determining the ovulation disorder with higher accuracy. .
In addition, it is possible to make more accurate judgment by changing the cutoff value up and down or setting multiple cutoff values, and multi-stage judgment with boundary area and category classification etc. It is also possible to make it.

In the present technology, in the case of a bacterium whose cut-off value is set to “above (including bacteria detection)”, the subject whose occupancy rate of the set bacteria is “above (including bacteria detection)” is “ A subject who is determined to have ovulation disorder (no ovulation) and does not fall under “above (including bacteria detection)” is determined to be “not ovulation disorder (with ovulation)”.
In the present technology, in the case of bacteria whose cutoff value is set to “below (including bacteria non-detection)”, subjects whose occupancy of the set bacteria is “below (including bacteria non-detection)” Is determined to be “ovulation disorder (no ovulation)”, and a subject who does not fall under “below (including non-detection of bacteria)” is determined to be “not ovulation disorder (with ovulation)”.
Thus, in the present technology, it is preferable that a subject corresponding to the cutoff value is determined as “a subject having an ovulation disorder”, and a subject not corresponding to the cutoff value is determined as a “subject not having an ovulation disorder”. It is.

In the present technology, “increasing the accuracy of the cut-off value” makes it possible to determine with higher accuracy.
Note that “increasing the accuracy of the cut-off value” means that the value obtained by subtracting the false negative degree (the ratio at which positive is determined to be negative) from the sensitivity (the ratio at which positive is correctly determined as positive) is more In this technique, in the ROC curve used for obtaining the cutoff value, the area (AUC) under the curve of each cutoff value is set to a larger value. is there.

Further, as shown in <each cut-off value> described later, it is also possible to set the determination along the order of the accuracy of the cut-off value. More specifically, the “more preferable cutoff value” can be set to High, the “more preferable cutoff value” can be set to Middle, and the “preferable cutoff value” can be set to Low. For example, in the case of [B1], “preferably 8.41% or more” is set to Low, “more preferably 9.15% or more” is set to Middle, and “more preferably 10.03% or more” is set to High. It is also possible to keep it.
By setting in this way, when the cut-off value is High, “very strong suspicion of ovulation disorder”, when cut-off value Middle is “highly suspected ovulation disorder”, and when the cut-off value is Low, “ovulation disorder” It is also possible to make a multistage determination that there is a suspicion.

  In addition, in the present technology, when “applicable” and “not applicable” are mixed in the cutoff value, “applicable” is preferentially adopted, and it is determined that “the subject has an ovulation disorder”. desirable.

<Each cut-off value>
The cut-off values of the present technology are shown in the following (1) to (6).
(1) [Bacteroidetes]
[B1]: In the case of Bacteroidetes genus Bacteroidales, Prevotella genus Prevotella, the cut-off value is preferably 8.41% or more, more preferably 9.15% or more, and still more preferably 10.03% or more. It is.
[B2] In the case of Bacteroidetes genus Bacteroidales> S24-7 family bacteria, the cut-off value is preferably 12.30% or less, more preferably 11.46% or less, and even more preferably 7.75% or less. is there.
[B3] In the case of Bacteroidetes Bacteroidia class Bacteroidales> Rikenellaceae bacteria, the cut-off value is preferably 0.59% or less, more preferably 0.48% or less, and still more preferably 0.41% or less.
[B4] In the case of Bacteroidetes genus Bacteroidales family [Paraprevotellaceae] bacteria, the cut-off value is preferably 0.93% or less, more preferably 0.74% or less, and even more preferably 0.47% or less. is there.

(2) [Firmicutes]
In the case of bacteria of the order [F1] Firmicutes Clostridia Closridiales, the cut-off value is preferably 10.12% or less, more preferably 8.66% or less, and still more preferably 7.62% or less.
In the case of bacteria of the family [F2] Firmicutes Clostridia Class Losridiales> Lachnospiraceae, the cutoff value is preferably 4.58% or less, more preferably 4.20% or less, and even more preferably 3.25% or less.
[F3] Firmicutes Clostridia Class Closridiales [Tissierellaceae] Family WAL_1855D, the cut-off value is preferably 0.52% or more, more preferably 1.46% or more, and even more preferably 2.25%. That's it.
[F4] Firmicutes Clostridia class Closridiales> Ruminococcaceae family Oscillospira, the cut-off value is preferably 0.87% or less, more preferably 0.78% or less, and even more preferably 0.58% or less. is there.
[F5] In the case of bacteria of the genus Anaerostipes belonging to the order of [F5] Firmicutes Clostridia Class Closridiales Lachnospiraceae, the cutoff value is preferably 0.06% or less, more preferably 0.05% or less, and further preferably 0.03% or less. is there.

In the case of a bacterium belonging to the family [F6] Firmicutes Clostridia class Closridiales> Veilillonellaceae family Dialister, the cut-off value is preferably 1.44% or more, more preferably 1.53% or more, and further preferably 3.15% or more. is there.
[F7] In the case of bacteria belonging to the genus Ruminococcus belonging to the order of [F7] Firmicutes Clostridia Class Closridiales, the cut-off value is preferably 1.08% or less, more preferably 0.75% or less, and even more preferably 0.61% or less. is there.
[F8] Firmicutes Clostridia class Closridiales> Peptococcaceae family rc4-4 genus bacteria, the cutoff value is preferably 0.14% or less, more preferably 0.11% or less, more preferably 0.10% It is as follows.
In the case of a bacterium belonging to the genus Roseburia belonging to the order [F9] Firmicutes Clostridia class Clostridiaes, the cut-off value is preferably 0.02% or less, more preferably 0.01% or less, and still more preferably "not detected". .

In the case of the bacterium of [F10] Firmicutes genus Erysipelotrichi class Erysipelotrichales> Erysipelotrichaceae family AllobacuLum: It is.
[F11] In the case of bacteria belonging to the genus Candidatus Arthromitus belonging to the order of [F11] Firmicutes Clostridia Class Closridiales Clostridiaceae, the cutoff value is preferably 0.02% or less, more preferably 0.015% or less, and still more preferably 0.01% or less. It is.
[F12] In the case of the bacteria of the [F12] Firmicutes Clostridia class Closridiales> Ruminococcaceae family, the cutoff value is preferably 0.05% or less, more preferably 0.03% or less, and even more preferably 0.01% or less. .
[F13] In the case of bacteria of the genus Peptococcus belonging to the order of [F13] Firmicutes Clostridia class Clostridiaes, the cutoff value is preferably 0.07% or more, more preferably 0.08% or more, and further preferably 0.14% or more. is there.

(3) [Actinobacteria]
[A1] In the case of the bacterium belonging to the genus Atopobium belonging to the class Coriobacteriales Coriobacteriales Coriobacteriales, the cut-off value is preferably 0.10% or more, more preferably 0.11% or more, further preferably 0.14%. That's it.

(4) [Fusobacteria]
[FS1] In the case of bacteria belonging to the genus Fusobacteria genus Fusobacteriales, Leptotrichiaceae, Leptotrichia, the cut-off value is preferably 0.08% or less, more preferably 0.05% or less, and still more preferably "not detected". .

(5) [Proteobacteria]
[P1] In the case of bacteria belonging to the Proteobacteria genus Betaproteobacteria class Burkholderiales> Burkholderiaceae family Burkholderia, the cutoff value is preferably 0.09% or less, more preferably 0.08% or less, and even more preferably 0.07% or less. is there.

(6) [Combination of specific bacteria in intestinal flora]
The test marker of the present technology is preferably composed of two or more kinds of bacteria selected from the following [B1], [B2], [F1] and [F3]. More preferably, it is composed of three or more kinds of bacteria selected from [B1], [B2], [F1] and [F3], and more preferably these four kinds of bacteria.
[B1] Bacteroidetes Gate Bacteroidia class Bacteroidales> Prevotlaceae family Prevotella genus,
[B2] Bacteroidetes gate Bacteroidia class Bacteroidales eyes S24-7,
[F1] Firmicutes Gate Clostridia Class Closridiales, and
[F3] Firmicutes Clostridia class Closridiales order [Tissierellaceae] family WAL_1855D genus.

  In addition, the test marker of the present technology includes two types of combinations [B1] and [B2], two types of combinations [F1] and [F3], and at least one type of [B1] to [B4]. A combination with at least one of [F1] to [F13] is preferred.

  The cut-off values of these bacteria are as described in (1) to (5) above. Even if these cut-off values are set to Low, as shown in the examples described later, the determination accuracy can be further improved by combining a plurality of cut-off values. Moreover, it is excellent also from a viewpoint that these specific multiple combinations are easy from the same specimen.

The following combinations [1] to [3] are preferable as a suitable combination of bacteria in the intestinal flora for increasing the accuracy of determining ovulation disorders, which is preferable from the viewpoint of improving accuracy such as detection of ovulation disorders. Although there is, it is not limited to this.
[1] The test marker of the present technology is preferably a combination of the bacterium of [B1] and the bacterium of [B2], and more preferably a combination of the above-described cut-off values.
More preferably, the cut-off value of bacteria [B1] (10.03% or more) and the cut-off value of bacteria [B2] (7.75% or less) are combined. Thereby, the coincidence rate can be 90% or more.
[2] The test marker of the present technology is preferably a combination of the bacterium of [F1] and the bacterium of [F3], and more preferably a combination of the above-described cut-off values.
Even more preferably, the [F1] bacterial cut-off value (7.62% or less) and the [F3] bacterial cut-off value (2.25% or more) are combined. Thereby, a coincidence rate can be 90% or more.
[3] The test marker of the present technology is preferably a combination of the bacterium [B1], the bacterium [B2], the bacterium [F1] and the bacterium [F3], and more preferably the above-described cut-off values. Is a combination.
More preferably, the cut-off value of the bacteria [B1] (10.03% or more), the cut-off value of the bacteria [B2] (7.75% or less), the cut-off value of the bacteria [F1] (7.62% or less) and [F3] bacterial cut-off value (2.25% or more). Thereby, a coincidence rate can be 95% or more.

Here, in the present technology, as shown in the examples described later, the number of enteric bacteria in the stool of a subject who does not regularly observe ovulation (more specifically, the bacterial occupancy in the intestinal flora) and There was a significant correlation with subjects who did not regularly ovulate (ie, subjects with ovulation disorders).
Further, in the present technology, the number of bacteria of the intestinal bacteria in the stool (more specifically, the occupancy rate of bacteria in the intestinal flora) of the subject in whom ovulation is regularly observed, and the subject in which ovulation is regularly observed (that is, There was also a significant correlation with (non-ovulatory subjects).
There are no reports that enterobacteria are used for the examination of ovulation disorders, and there is no report that supports the judgment of ovulation disorders, and there are no specific enteric bacteria and their occupancy rates in determining the accuracy of ovulation disorders. None of the reports have been shown to be strongly involved.

Furthermore, one or more bacteria selected from the group consisting of [B1] to [B4], [F1] to [F13], [A1], [FS1], and [P1] (hereinafter, Based on the "accuracy rate of subjects without ovulation" and "accuracy rate of subjects with ovulation" in "the above-mentioned bacteria" or "bacteria of this technology") ), The present inventors were able to find each bacterium that can be used as a test marker with higher accuracy in determining ovulation disorders.
The coincidence rate (100%) is calculated by “the total number of persons / applicable subjects / non-ovulatory subjects” × 100 in a certain bacterium. The corresponding number of people is “a total number of subjects who are ovulatory disorders: the number of people corresponding to the cut-off value and subjects who are not the ovulation disorder: the number of people not corresponding to the cut-off value” in a certain bacterium.

For example, in Tables 4 and 5, the intestinal microflora is examined in a total of 32 people, including 8 subjects with ovulation disorders and 24 subjects with no ovulation disorders.
A cut-off value for determining that the bacterium is “ovulatory disorder” from a bacterium occupancy rate in the intestinal flora of a bacterium and all subjects is set.

  As an example, with reference to Tables 4 and 5, the cut-off value and ovulation disorder determination will be described in more detail using the [B1] bacteria as a test marker.

When the cut-off value of the bacteria of [B1] is set to be 8.41% or more, 8 subjects out of ovulation disorders fall under this cut-off value, and the accuracy rate (also referred to as sensitivity, 100%) is obtained. .
Specifically, the accuracy rate for determining whether there is an ovulation disorder is 100% from “8 subjects who have the ovulation disorder who fall within the bacterial cutoff value of [B1] / 8 subjects who have the ovulation disorder”. . That is, if the cut-off value of [B1] bacteria is set to be 8.41% or more, the determination accuracy without ovulation in the subject is 100%.

On the other hand, in the case of this [B1] cut-off value of bacteria (8.41% or more), 9 persons who are not ovulation disorders in the subject correspond to this cut-off value. Since it is determined that there is an ovulation disorder if it corresponds to this cut-off value, “9 people who are not ovulatory disorder” corresponding to this cut-off value is fraudulent, and fraud probability (also called non-specificity, 37.5% )become.
Specifically, the fraud probability is 37.5% from “9 subjects who are not ovulatory disorders and corresponding to the bacterial cutoff value of [B1] / 24 subjects who are not ovulatory disorders”.
In other words, when the cut-off value (8.41% or more) of the bacterium of [B1] is used, 15 subjects who are not ovulation disorders do not fall under this cut-off value, and the accuracy rate (62 .5%).

And, when the cut-off value of the bacteria of [B1] is set to be 8.41% or more, “the total number of 8 applicable persons among subjects having ovulation disorder and 15 non-applicable persons among subjects having no ovulation disorder” A total determination rate (also referred to as a coincidence rate) of 71.9% is obtained from “23 persons / 32 subjects”. The higher the matching rate, the higher the accuracy (accuracy rate) of the determination when determining that the subject is “ovulation disorder” or “not ovulation disorder”. Furthermore, by setting the cut-off value to 10.03% or higher of High, an overall determination rate (also referred to as a coincidence rate) of 81.3% can be obtained, and in this way "to increase the accuracy of the cut-off value" With this, it is possible to perform determination with higher accuracy.
Incidentally, a biomarker having a determination rate of 70% or more is regarded as a highly accurate determination marker.

Then, the present inventors repeatedly performed the above-mentioned precise trial and error many times while a large number of intestinal bacteria exist in the stool specimen and, naturally, many bacteria that are inappropriate for determination are included.
As a result, one or more bacteria selected from the group consisting of [B1] to [B4], [F1] to [F13], [A1], [FS1] and [P1] are ovulation disorders. The present inventors have found that it can be used as a marker for detection of.
Furthermore, as shown in the Examples below, as a result of further examination of various combinations of bacteria among the bacteria, the present inventors have found that ovulation disorders can be detected with higher accuracy. In addition, when each bacterium of the present technology is used as a test marker for ovulation disorder, each bacterium and its occupancy can be easily measured from a specimen containing an intestinal flora. That is, the present technology can be said to be a simple collection method and a less invasive collection method.

Therefore, this technique is characterized by detecting bacteria in the intestinal flora in the specimen.
Furthermore, the present technology provides one or more bacteria selected from the group consisting of [B1] to [B4], [F1] to [F13], [A1], [FS1] and [P1]. It is preferred to use to test for ovulation disorders.
In addition, the method of the present technology may be a method for assisting diagnosis of ovulation disorder, including a step of determining ovulation disorder based on the occupancy rate of bacteria in the intestinal flora in the specimen. Furthermore, the present technology provides one or more test markers selected from the group consisting of [B1] to [B4], [F1] to [F13], [A1], [FS1] and [P1]. What contains the process of determining an ovulation disorder using the bacterium for an operation is suitable.
In addition, the method of the present technology may be a bacteria measurement method that measures each of the above-mentioned bacteria that are bacteria in the intestinal flora for the purpose of examining or determining ovulation disorders.

It is preferable that the method of the present technology further includes a bacteria measurement step, in which case, at least one kind of each of the bacteria in the intestinal flora under test and a occupancy rate thereof are measured, and It is preferable to perform a step of detecting an ovulation disorder based on the determination information of each bacterium and a determination step of determining the ovulation disorder from the detection result.
The method of the present technology may include a method for assisting diagnosis of an ovulation disorder and a method for diagnosing an ovulation disorder.
The method of the present technology may further include a display step of notifying or displaying the determination information (or inspection result). Examples of the display include screen display, paper printing, data display, and voice display.
The determination information includes, for example, a determination result (with or without ovulation disorder), a cut-off value for one or a plurality of bacteria, a measurement result of the occupation ratio, and the like, and can be selected as appropriate.
Moreover, each bacterium of this technique can be used for the test marker of an ovulation disorder, and can be used for the use.
In addition, each bacterium of the present technology can be used as a test marker in a test kit for ovulation disorders, and can be used to obtain an antigen antibody, a 16S rRNA sequence and the like for producing the test kit.

In addition, each of the bacteria used in the present technology and the occupancy ratio thereof (hereinafter also referred to as “measurement of bacteria of the present technology”) can be performed using a known bacterial measurement method or a known bacterial detection method. It is possible and the method is not limited. Thus, the presence or absence of one or more bacteria selected from the above-mentioned [B1] to [B4], [F1] to [F13], [A1], [FS1] and [P1] and the intestines The occupancy in the internal flora can be measured.
In addition, the method of the present technology may include determination of whether or not each bacterium is present (qualitative) and measurement (quantification) of each bacterium.
This technique preferably uses one or more methods selected from sequence analysis, MALDI-TOF-MS, microarray method, PCR method, FISH method and the like. Furthermore, a sequencer analysis method using a sequence analysis and a quantitative PCR method is preferable from the viewpoint of accuracy.

Examples of the bacteria measuring means or method of the present technology include a method of culturing intestinal bacteria in a pre-selected selective medium and measuring turbidity and absorbance, FISH method, real-time PCR method, and the like. It is suitable for measuring (occupancy).
Examples of the bacteria measurement means or method of the present technology include a sequencer (first generation to third generation, etc.), a MALDI-TOF-MS measurement device, and the like. Examples of the sequencer include a single read method, a pair end method, and a multiplex method. These can accurately measure the total number of bacteria in the intestinal flora and the occupancy rate of the bacteria of each of the determination markers, and are suitable for making a more accurate determination.
In addition, when measuring bacteria of the present technology, an indicator substance for bacterial measurement is prepared using one or more kinds selected from bacterial base sequences or fragments thereof, bacterial cells or fragments thereof. Also good. Thereby, the indicator substance (for example, a primer, a marker, etc.) used for bacteria measurement can be obtained. Further, as a label, a radioisotope, a phosphor, a colorant, or the like may be used. The bacteria of the present technology can be measured using one or two or more selected from those derived from the bacteria.

<Measurement of total number of intestinal flora contained in specimen>
The measurement of the total number of bacteria in the intestinal flora contained in the specimen can be obtained using a known method, and the method is not particularly limited.
For example, in the sequencer analysis method, the sequence of the 16S rRNA gene is decoded using a primer that binds to a common base sequence portion among the bacteria contained in the sample in the sequence of the 16S rRNA gene. By this decoding, the copy numbers of 16S rRNA genes other than bacteria of [B1] to [B4], [F1] to [F13], [A1], [FS1] and [P1] can also be calculated. For this reason, the total number of bacteria contained in the specimen may be, for example, the sum of the copy numbers of 16S rRNA genes of all the bacteria measured in the specimen. Alternatively, the number of all bacteria contained in the sample may be obtained by counting the bacteria contained in the sample using a microscope or the like.
When performing the method of the present technology, it is preferable to have a step of decoding the base sequence of the 16S rRNA gene in the bacterial measurement step or as the pretreatment step.
In addition, the specimen used in the present technology is preferably a specimen that has not been subjected to a culture operation after collection. This is in order to avoid a change in each recent ratio in the specimen at the time of collection due to a difference in the growth rate of each bacterium due to the culture operation.

<Measurement of presence and absence of each bacterium in [B1] to [B4], [F1] to [F13], [A1], [FS1] and [P1] in the intestinal flora>
The above-mentioned bacterial ratio (also referred to as “occupation ratio”) of each bacterium to the total number of bacteria in the intestinal flora contained in the sample is a relative value when the total number of bacteria contained in the sample is “100%”. It is.
Moreover, the ovulation disorder can be detected or determined by comparing the occupancy rate of each bacterium with each of the cut-off values described above. When the occupation ratio corresponds to the cut-off value, it is detected or determined as an ovulation disorder, and when it does not correspond to the cut-off value, it is detected or determined as not an ovulation disorder.
Also, the copy number of 16S rRNA gene of each bacterium of [B1] to [B4], [F1] to [F13], [A1], [FS1] and [P1] and 16S rRNA of all the bacteria contained in the specimen The bacterial ratio (occupancy) can also be obtained from the gene copy number.
In addition, among the bacteria of [B1] to [B4], [F1] to [F13], [A1], [FS1] and [P1], the bacteria ratio (or occupancy) is not detected. 0% or not detected.

Although a more specific example is given about the measurement of each group of bacteria in this technique, this technique is not limited to this.
<Measurement process of each bacterium and its occupancy>
Among the bacteria contained in the specimen, the number of bacteria classified into each of the above bacteria and the total number of bacteria in the intestinal flora can be determined using a known method, and the method is not particularly limited.
For example, regarding the classification of bacteria, each bacterium is classified into each of the above-mentioned bacteria or other based on the base sequence of a gene (16S rRNA gene) encoding RNA present in the small subunit (16S) constituting the ribosome. Can be divided into bacteria.
The number of bacteria of each bacterium contained in the sample can also be calculated by, for example, quantifying the amount of DNA and the copy number of the 16S rRNA gene derived from each bacterium contained in the sample.
An example is given below for calculating the number of bacteria, but is not limited thereto. The calculation of the total number of intestinal bacterial flora contained in the sample can be performed in the same manner, and is not limited to this.

  In order to calculate the number of bacteria based on the base sequence, first, bacterial DNA contained in the sample is extracted from the sample. Extraction of DNA from a specimen can be performed using a known technique, and the technique is not particularly limited. For example, an extraction method using phenol / chloroform, a spin column method including a filter, and the like can be given.

  For DNA obtained from a specimen, it is preferable to perform a nucleic acid amplification reaction in order to obtain the amount of DNA or the number of copies necessary for the measurement of the number of bacteria. Amplification of DNA can be performed using a known technique such as PCR (Polymerase Chain Reaction), and primers used in the nucleic acid amplification reaction can also be designed using a known design technique. Furthermore, the primer may be designed so that a sequence necessary for DNA analysis is incorporated into the amplified nucleic acid chain during the nucleic acid amplification reaction.

The number of bacteria classified into each of the above bacteria can be measured by, for example, a quantitative PCR method using a DNA contained in the DNA solution as a template, a T-RFLP (Terminal-Restriction Fragment Length Polymorphism) method, or the like.
In the quantitative PCR method, the DNA amount or copy number of a desired bacterial 16S rRNA gene is measured by performing a nucleic acid amplification reaction using a primer that binds to a specific sequence portion of each bacterial 16S rRNA gene. Can do.
In the T-RFLP method, an amplified nucleic acid chain containing a sequence portion specific to each bacterium of 16S rRNA gene is generated using a primer labeled at the end, and the obtained amplified nucleic acid chain is treated with a restriction enzyme. And fragmented into DNA fragments of different sizes. The DNA fragments can be separated by electrophoresis, and the DNA amount or copy number of the desired bacterial 16S rRNA gene can be determined from the identification and peak intensity of each peak in the electrophoresis pattern.

  Moreover, about the DNA contained in the said DNA solution, you may calculate the DNA amount or copy number of 16S rRNA gene of desired bacteria by FISH (Fluorescence in situ hybridization) method. In addition, the DNA amount or copy number of the 16S rRNA gene can be calculated using a DNA microarray.

  In addition to the method described above, the DNA amount or copy number of the 16S rRNA gene can be determined from the number of times that a specific sequence is decoded by determining the base sequence of DNA extracted from a specimen using a sequencer. In the case of the method using a sequencer, the DNA amount or the copy number of the 16S rRNA gene of a bacterium other than the above-mentioned bacteria contained in the specimen can also be determined by the same operation.

Examples of the method using a sequencer include a clone library method, a DGGE / TGGE (Denaturing / Temperature Gradient Gel Electrophoresis) method, and a metagenome analysis method.
In the clone library method, the 16S rRNA gene of DNA extracted from a specimen is amplified by a sequence portion specific to each bacterium, the resulting amplified nucleic acid strand is inserted into a plasmid, and a plasmid containing the amplified nucleic acid strand The base sequence of
In the DGGE / TGGE method, DNA is amplified in the same manner as the clone library method, and the obtained nucleic acid strands are separated according to the sequence of the nucleic acid strands by electrophoresis, the bands are cut out, and the DNA in the gel is recovered. The base sequence of the DNA is determined.
In the metagenome analysis, DNA obtained from a specimen is fragmented and subjected to a nucleic acid amplification reaction or the like as necessary, and then the base sequence of each DNA fragment or amplified nucleic acid chain is determined.

  The above-described determination of the base sequence can be performed by a sequencer using the principle of the Sanger method, or can be performed by a next-generation sequencer (also referred to as a second-generation sequencer). In particular, metagenomic analysis is preferably performed with a next-generation sequencer with higher decoding performance. For metagenome analysis, a multiplex method, a single read method, a paired end method, or the like is used. The single read method is a method of sequencing one side of a DNA fragment after cluster formation by bridge PCR. The paired-end method is a method of sequencing from both sides of a fragment after cluster formation by bridge PCR, and the paired-end method is preferable because more accurate data can be obtained. The multiplex method is a method for accurately identifying DNA sequences derived from a plurality of samples by adding a barcode sequence to a DNA fragment.

When identifying bacteria from a base sequence decoded using a sequencer, a known analysis method using analysis software, a database, or the like can be used. Examples of the database include Genbank, ENA, DDBJ, and the like. In addition, Greengenes database, which is a database specialized for 16S rRNA genes, can also be used.
Bacteria contained in the specimen can be identified by performing a homology search on the DNA analysis results obtained from the specimen against the base sequences of the bacteria accumulated in these databases. Of the sequences identified in any bacterium, the number of copies of the sequence identified as the 16S rRNA gene of each bacterium can be the number of each bacterium. Moreover, the homology at the time of identification is 95% or more, More preferably, it is 97% or more.

[Other Embodiments]
As another aspect of the present technology, bacteria in the human intestinal microflora (preferably [B1] to [B4], [F1] to [F13], [A1], [FS1] and [P1] The following test kit using each bacterium), a method for detecting or screening an ovulation disorder regulating substance, a method for producing a food material-containing composition for improving ovulation disorder, a control unit for determining ovulation disorder, or for determining ovulation disorder A device etc. can be provided.

In addition, the present technology can provide a test kit. As the test kit of the present technology, a test kit including a protocol for measuring the intestinal bacteria in a specimen is preferable. Thereby, the determination method and test | inspection method of an ovulation disorder of this technique can be implemented. The kit contains measuring reagents and protocols for detecting intestinal microflora (intestinal bacterial measurement method, ovulation disorder determination method, in particular, cut-off value of test marker bacteria, factors affecting measurement results and their effects) Etc.), etc. are included.
The determination criteria include the standard number of bacteria of each of the intestinal bacteria, a cut-off value that is determined to be highly likely to be an ovulation disorder, and the like. The cut-off value can be appropriately changed in accordance with diagnostic uses such as early detection purpose, detection purpose of an ovulation disorder regulating substance, screening purpose, improvement of diagnostic accuracy, selection of a patient to be administered a drug for ovulation disorder, and the like. What is necessary is just to determine a test subject's ovulation disorder | damage | failure state using the criteria used as the test | inspection marker bacteria, the occupation rate, and the cut-off value. This determination result can be used to assist a doctor's diagnosis as determination information.
Examples of the reagent for measuring the test marker of the present technology include the intestinal bacterial count measuring reagent, the mRNA detecting reagent, the DNA detecting reagent, and the antigen-antibody reaction reagent.

The present technology can also provide a method for detecting a substance that regulates ovulation disorders based on bacteria in the intestinal flora in a specimen. The ovulation disorder regulating substance is detected from one or more test substances.
Furthermore, the detection method containing the following (1) and (2) is suitable for the detection method of the ovulation disorder regulator of this technique.
(1) a first detection step of detecting an occupancy rate of bacteria in an intestinal microflora in the sample from a sample collected from a subject who has ingested the test substance;
(2) Second detection for detecting an ovulation disorder regulating substance by judging whether or not the test substance is a substance regulating ovulation disorder based on a change in the occupancy rate of the determination marker bacteria in the intestinal flora A process can be provided.
The “bacteria” in the occupancy rate of the bacteria is preferably each bacterium described in [Test Marker] described above.
The first detection step may include a measurement step of measuring the occupancy rate of bacteria in the intestinal flora in order to detect the occupancy rate.
In the method of the present technology, a substance that regulates ovulation disorders may be detected using the above-described [test marker] bacteria.

The test substance may be a new substance or a known substance.
The method for detecting an ovulation disorder regulating substance of the present technology may include a step of selecting one or more types of test substances from a test substance group consisting of a plurality of types of test substances before the first detection step. The test substance may be a mixture in which a plurality of different types of test substances are mixed.
Further, the test substance may be selected from, for example, an edible material group (for example, dairy products, cereals, vegetables, fish, fats and oils, lactic acid bacteria, bifidobacteria, etc.) with sufficient food experience or safety ensured. Good. Then, one or more types of edible materials can be selected from an edible material group consisting of a plurality of types of edible materials.
The specimen used when detecting the ovulation disorder regulating substance is not particularly limited as long as it can compare the presence or absence of the ingestion of the test substance. For example, it may be a sample before ingesting a test substance and a sample after ingestion, or may be a sample of a subject who has ingested a test substance or a sample of a subject who has not ingested the test substance.

In the present technology, substances that regulate ovulation disorders are substances that make ovulation disorders positive to negative, and more specifically, substances that improve ovulation disorders (disorders:-), substances that worsen ovulation disorders (disorders: +) And substances that do not affect ovulation disorders (disorders: none or unknown).
Further, in the present technology, it is possible to determine whether or not the test substance is a substance (positive to negative) that regulates ovulation disorders based on the change in the occupancy of each bacterium described above depending on whether or not the test substance is administered.
For example, when the test substance is ingested by the subject and does not correspond to the cut-off value of the present technology (that is, the ovulation disorder is eliminated), the test substance can be determined as a substance that can improve the ovulation disorder. In addition, when the test substance is ingested, the test substance can be determined as a substance that worsens the ovulation disorder when the cut-off value is reached (that is, ovulation disorder occurs). Further, when the cut-off value does not change even when the test substance is ingested, it can be determined that the substance does not affect ovulation disorders. The cutoff value can be selected from one or more selected from the above <each cutoff value>. Thereby, an ovulation disorder regulator can be detected.

To explain an example in more detail, if a test substance collected by ingesting a test substance for a subject with ovulation disorder does not correspond to the cut-off value of the present technology, the test The substance is determined as an ovulation disorder improving substance (disorder-) and can be detected as an ovulation disorder improving substance.
In addition, when the test substance obtained by ingesting the test substance with respect to a subject who is not ovulatory disorder is measured, the test substance becomes a substance that deteriorates ovulation disorder ( It can be detected as a substance that worsens ovulation disorders.
In addition, even if the test substance is ingested by the subject, if there is no change in the cut-off value of each bacterium of this technology, the test substance is determined to be a substance that does not affect ovulation disorders and affects ovulation disorders. It can be detected as a non-performing substance (no obstacle).
In addition, the detection method of this technique can also detect whether an ovulation disorder can be adjusted with the intake by adjusting the intake of a test substance further.

An example of a method for detecting a substance that regulates ovulation disorders according to the present technology will be described below, but is not limited thereto.
By considering the change in the occupancy rate and the cutoff value of <each cutoff value> described above, it is possible to determine and detect what kind of ovulation disorder regulating substance the test substance is.
For example, using a test marker that is a subject having an ovulation disorder and a bacterium is determined to have an ovulation disorder with a cut-off value of 10% or more, the test substance is examined on the condition that the test substance has been ingested for a certain period of time. The intake period can be set arbitrarily and may be one week or one month.
A sample is collected from the subject after ingestion, and the gut microbiota and the occupancy rate of each of the bacteria are measured from the collected sample.
From the measurement results of intestinal bacteria, when the test substance intake is reduced compared to the case without test substance intake, the occupancy rate of this bacterium (bacteria set with a cut-off value above) decreases. This test substance can be determined and detected as a substance that may improve ovulation disorders. Furthermore, in the case of a test substance that has been reduced to a cut-off value of less than 10% by ingestion, this test substance can be determined and detected as a stronger ovulation disorder improving substance. The present technology can determine and detect the strength of the effect according to the degree of change in the occupation ratio.
In this way, by looking at the variation of each of the above-mentioned [test markers] in the sample when the edible material is ingested, an edible material that is likely to cause ovulation disorders, an edible material that can improve ovulation disorders, and ovulation disorders It can be determined and detected as an edible material that has little effect on food.
The edible material may be a normal food or drink, or a raw material of the product (for example, lipid, protein, carbohydrate, dietary fiber, etc.). More specifically, for example, vegetables, seaweed, rice, wheat, fish, beef, soybeans and the like can be mentioned.

Furthermore, the present technology is a method for producing a composition containing an edible material for improving ovulation disorder by detecting an edible material for improving ovulation disorder based on the occupancy rate of bacteria in the intestinal flora of the sample. The manufacturing method includes the following steps.
In the present technology, an edible material for improving ovulation disorder may be detected using the bacteria described in [Test Marker].
Moreover, it is more preferable that the manufacturing method of the present technology includes a design method including the following steps.
(A) a measurement step of measuring an occupancy rate of the determination marker bacteria in an intestinal flora in the sample from a sample collected from a subject who has consumed an edible material as a test substance;
(B) A detection step of determining whether or not the edible material is a substance that improves ovulation disorders based on a change in the occupancy rate of the determination marker bacteria in the intestinal flora, and detecting a substance that improves ovulation disorders. c) It is also possible to provide a design process for designing blending of the detected edible material for improving ovulation disorder into the composition.

Furthermore, the design method of the present technology may include selecting one or more types of edible materials from an edible material group including a plurality of types of edible materials.
Furthermore, this technique can also provide the manufacturing method of the composition containing the edible raw material for ovulation disorder improvement using the said design method.

Further, the present technology is a method for producing a composition containing an edible material for improving ovulation disorder by detecting an edible material for improving ovulation disorder based on the occupancy rate of bacteria in the intestinal flora in the sample. A production method comprising the following steps;
(A) a measurement step of measuring an occupancy rate of the determination marker bacteria in an intestinal microflora in the sample from a sample collected from a subject who has consumed an edible material as a test substance;
(B) A detection step of determining whether or not the edible material is a substance that improves ovulation disorders based on a change in the occupancy rate of the determination marker bacteria in the intestinal flora, and detecting a substance that improves ovulation disorders. c) a design process for designing blending of the detected edible material for improving ovulation disorder into the composition;
(D) It is also possible to provide a blending step of blending the designed edible material for improving ovulation disorder into the composition.

  According to the present technology, an edible material for improving ovulation disorders can be blended into the composition, thereby providing a composition for improving ovulation disorders. Moreover, the composition for ovulation disorder improvement which adjusted the compounding quantity of the edible material for ovulation disorder improvement by this technique can also be provided.

Moreover, this technique can provide the control part for determining an ovulation disorder. Thereby, it can be determined and detected whether a subject is an ovulation disorder.
It is preferable that the control part of this technique determines an ovulation disorder by each bacteria as described in the said [test marker] and / or its occupation rate, or using the said test marker. It is more preferable that the control unit has the above-described <each cut-off value> and the information data of the combination of the cut-off value and the bacteria in [Examples below], or the storage unit storing them. It is. In addition, you may input the measured bacteria result (total bacteria count, each bacteria count, an occupation rate, etc.) manually from an input part. The input unit transmits each input data to the storage unit or the control unit.
Further, it is more preferable that the control unit can access the above-described bacteria measuring unit that measures bacteria. The said control part can control measuring bacteria and analyzing the result (occupation rate etc. of each said bacteria).
In addition, the control unit preferably controls the determination information described above and can access a display unit that notifies or displays the determination information. The said control part can perform the measurement of the microbe to test | inspect and its occupation rate, and the setting of a cutoff value. Moreover, the said control part can display a determination result on a display part. Examples of the display unit include a display, a speaker, and a paper medium.

  It is also possible to store the method of the present technology as a program in a hardware resource including a control unit including a CPU of the apparatus and a storage medium (USB memory, HDD, CD, network server, etc.), and can be realized by the control unit. It is. Further, the present technology may be a program for causing a computer to function as a design method of the present technology.

Furthermore, the present technology may be an ovulation disorder detection control device including a control unit that determines an ovulation disorder. Thereby, it can be determined and detected whether a subject is an ovulation disorder.
The control device only needs to be provided with a part having an arithmetic processing capability (for example, a CPU) such as a personal computer, and other measurement devices (for example, a bacteria measurement device) or a storage device (for example, on a server or the Internet). The above database etc. may be accessible.
Moreover, this technique is an ovulation disorder determination measuring apparatus which has a bacteria measurement part and a control part, and, thereby, can determine and detect whether a test subject is an ovulation disorder.
In the present technology, the bacteria measuring unit measures the bacteria of the intestinal flora in the specimen; the control unit determines whether the subject has an ovulation disorder based on the result of the bacteria measuring unit and determines the ovulation disorder. It may be an ovulation disorder detecting and measuring device that performs the detecting.
Furthermore, the present technology provides a detection device in which the control unit detects a substance that regulates ovulation disorders; a design device for designing an edible material-containing composition for improving ovulation disorders; and an edible material-containing composition for improving ovulation disorders It may be a manufacturing control device that performs manufacturing control.

The present technology can also employ the following configurations.
[1]
A test method for ovulation disorders, characterized by detecting bacteria in an intestinal flora in a specimen.
Preferably, the bacterium is one or two selected from the group consisting of the following [B1] to [B4], [F1] to [F13], [A1], [FS1], and [P1]. These are more bacteria.
[2]
It is a test marker or determination marker for ovulation disorders using bacteria in the intestinal flora,
The marker is composed of one or more bacteria selected from the group consisting of [B1] to [B4], [F1] to [F13], [A1], [FS1], and [P1]. Markers that are things.
[3]
A method for assisting diagnosis of an ovulation disorder or a method for diagnosing an ovulation disorder, comprising detecting bacteria in an intestinal flora in a specimen.
Preferably, one or more bacteria selected from the group consisting of [B1] to [B4], [F1] to [F13], [A1], [FS1], and [P1] are used. That is.
[4]
A method for assisting diagnosis of an ovulation disorder or a method for diagnosing an ovulation disorder, comprising a step of detecting bacteria in an intestinal flora in a sample and a step of determining an ovulation disorder.
It is preferable to use the bacterium described in [1] as a test marker for ovulation disorders.
[5]
1 selected from the group consisting of [B1] to [B4], [F1] to [F13], [A1], [FS1], and [P1] for use as a test marker or determination marker for ovulation disorders Species or two or more bacteria or use thereof.
[6]
A test kit for confirming the presence or absence of an ovulation disorder, comprising the determination marker derived from the bacterium according to [1].

[7]
A method for measuring bacteria in the intestinal flora for the purpose of detecting or determining ovulation disorders,
A method for measuring bacteria, comprising measuring the bacteria described in [1] as a test marker.
[8]
A method for detecting a substance that regulates ovulation disorders based on the occupancy rate of bacteria in the intestinal flora in a specimen.
[9]
The detection method according to [8] is a detection method including the following (1) and (2).
(1) a first detection step of detecting an occupancy rate of bacteria in an intestinal bacterial flora in the sample from a sample collected from a subject who has ingested the test substance;
(2) A second detection step of determining whether or not the test substance is a substance that regulates ovulation disorders based on a change in the occupancy rate of the bacteria in the intestinal flora, and detecting a substance that regulates ovulation disorders.

[10]
A method for designing a composition containing an edible material for improving ovulation disorders by detecting an edible material for improving ovulation disorders based on the occupancy ratio of bacteria in the intestinal flora in the sample.
[11]
A method for producing a composition containing an edible material for improving ovulation disorder by detecting an edible material for improving ovulation disorder based on the occupancy ratio of bacteria in the intestinal flora in the sample.

[12]
By detecting the edible material for ovulation disorder improvement by the detection method of the above [8], and / or by designing the edible material for ovulation disorder improvement mixed by the design method of the above [9], A method for producing a composition containing an edible material for improving ovulation disorders.
More preferably, the manufacturing method of the composition of said [11] description including the following (a)-(d) process.
(A) a measurement step of measuring the occupancy of the bacteria in the intestinal microflora in the sample from a sample collected from a subject who has consumed an edible material as a test substance;
(B) a detection step of determining whether or not the edible material is a substance that improves ovulation disorders based on a change in the occupancy rate of the bacteria in the intestinal flora, and detecting a substance that improves ovulation disorders;
(C) A design process for designing blending of the detected edible material for improving ovulation disorder into the composition.

[13]
In any one of the above [1] to [12],
One or more bacteria selected from the group consisting of [B1] to [B4], [F1] to [F13], [A1], [FS1], and [P1] from the collected samples Measuring process to measure,
The measurement result and one or more bacteria selected from the group consisting of [B1] to [B4], [F1] to [F13], [A1], [FS1], and [P1]. It is preferable to include a determination step of determining whether or not there is an ovulation disorder based on the cutoff value.
Further, the measurement result in the determination step is one or more selected from the group consisting of [B1] to [B4], [F1] to [F13], [A1], [FS1], and [P1]. It is preferable that the occupancy rate of two or more kinds of bacteria.

[14]
In any one of [1] to [13], the two types of combinations [B1] and [B2], the two types of combinations [F1] and [F3], or the above [B1] to [B4] A combination of at least one or more of [F1] to [F13] is preferred.
[15]
In any one of the above [1] to [14], when measuring bacteria, sequencer analysis method, sequence analysis method, MALDI-TOF-MS method, microarray method, immunoassay method, hybridization method, PCR method, FISH It is preferable to use a method or a blotting method. A sequencer analysis method is more preferable.

  Hereinafter, the present invention will be described in more detail with reference to examples, but the present invention is not limited to these examples.

<Subject>
Female patients younger than 40 years who visited obstetrics and gynecology outpatients and reproductive endocrine outpatients. Patients with regular ovulation observed in a cycle of 25-30 days (with ovulation: not ovulation disorder) and those with no ovulation (no ovulation: For ovulation disorders, stool is collected from the rectum using a rectal swab (collection swab for rectal stool) (rectal stool collection method) (hereinafter referred to as rectal swab stool sample), and the flora is analyzed by the following method Went.
The presence or absence of ovulation disorder was confirmed by a basal body temperature table and a hormone test in blood.

<Measurement of intestinal flora>
<Sample collection>
DNA was extracted from rectal swab stool samples of 8 patients with ovulation disorders and 24 healthy subjects by the following method. The portion of the rectal swab from which the feces were collected was cut out and placed in a mixture of 500 μL of RTF solution * 1 and 1000 μL of extract (100 mM Tris / HCl, 4 mM EDTA, pH 9.0), and the cell disruption device MμLti Beads. Extraction processing was carried out at 1,400 rpm for 5 min with a Shocker (YASUUI KIKAI). 800 μL of the extract, 300 mg of 0.1 mm diameter glass beads, and 800 μL of TE saturated phenol (Wako Pure Chemical Industries, Ltd.) were mixed and subjected to crushing treatment at 2,700 rpm for 180 sec using a cell crusher MμLti Beads Shocker (YASUI KIKAI). After centrifugation at 10,000 g for 10 minutes, 400 μL of the supernatant was taken, 500 μL of phenol / chloroform solution (Wako Pure Chemical Industries) was added and mixed, and after centrifugation at 10,000 g for 10 minutes, 250 μL of supernatant was obtained. Further, 250 μL of 2-propanol was added, and isopropanol precipitated was dissolved in 20 μL of Tris-EDTA buffer (pH 8.0) to obtain a DNA solution.

<Amplification of DNA>
Next, a nucleic acid amplification reaction was performed on the bacterial genome contained in the DNA solution. Tables 1 to 3 below show the primer sequences used in this experimental example. The primer set shown in Table 1 is a primer for amplifying the 3rd to 4th variable regions of the 16S rRNA gene. These primers are referred to as the first primer set for convenience.

  In Table 1, “R” means guanine or adenine. “W” means adenine or thymine or uracil. “H” means adenine or cytosine or thymine or uracil. “V” means adenine or guanine or cytosine.

  In addition, the primer sets shown in Table 2 and Table 3 below are sequences (adapter region and index region) necessary for analyzing the base sequence using a next-generation sequencer (Miseq (manufactured by Illumina)) as an amplified nucleic acid chain. It is a primer set for incorporation. The primers shown in Table 2 are forward primers, and the primers shown in Table 3 are reverse primers. These primers are referred to as the second primer set for convenience. In addition, the primer shown in Table 1-Table 3 was obtained by Life Technologies' oligo primer preparation service.

  A reaction solution having a total liquid volume of 25 μL containing the DNA solution and the first primer set described above was prepared using TaKaRa ExTaq HS kit (manufactured by Takara Bio Inc.). The nucleic acid amplification reaction is performed using a thermal cycler (Veriti 200 (manufactured by Life Technologies)), 94 ° C. for 3 minutes, 94 ° C. for 30 seconds, 50 ° C. for 30 seconds, and 72 ° C. for 30 seconds for one cycle. This was repeated 20 times, and then the PCR reaction was carried out at 72 ° C. for 10 minutes. The obtained PCR product was electrophoresed on a 1% agarose gel, and the amplified nucleic acid chain was confirmed by the band pattern.

  Subsequently, 1 μL of the obtained PCR product was used as a template, and a PCR reaction was performed in the same manner as described above using the second primer set. However, the number of cycles was 15 times. The obtained PCR product was electrophoresed on a 1% agarose gel, and after confirming the band pattern, the PCR product was purified using QIAquick 96 PCR Purification Kit (manufactured by Qiagen). About the PCR product after a refinement | purification, DNA concentration was measured by Quant-iT PicoGreen dsDNA Assay kit (made by Life Technologies).

<DNA sequence>
A mixture of PCR products derived from a plurality of stool specimens at the same concentration was supplied to Miseq v2 Reagent kit (manufactured by Illumina), and sequence analysis (Sequencing by synthesis: SBS method) was performed with Miseq.

<Bacterial identification and bacterial count calculation>
The paired end sequence obtained by the above sequence analysis is transferred to the QIIME software (version 1.1.2-301) (http://code.google.com/p/ea-utils/wiki/FastqJoin) 1.6.0) (http://qiime.org/), each sequence having 97% homology was defined as OUT (Operational Taxonomy Unit). The structure of the intestinal flora was analyzed by BLAST search of the representative sequences of each OUT against the following database.
Database: Greengenes database 12_10
(http://greengenes.secondgenome.com/downloads/database/12_10)

<Measurement results of intestinal flora>
Regarding the total number of bacteria in the intestinal microflora of each specimen described above, the total number of sequences as a result of the above-described structural analysis of the intestinal microflora was defined as the total number of bacteria contained in each fecal specimen. Furthermore, among the intestinal bacterial flora, each bacterium shown in Tables 4 and 5 was identified from the result of the homology search, and the occupation ratio of each bacterium was calculated.

<Discussion>
The ROC analysis was performed using statistical analysis software JMP13 (SAS Institute Inc.). The cutoff value of the present technology can be set by the ROC (Receiver Operating Characteristic) analysis. The ROC analysis method using this software is shown below, taking Bacteroidetes Bacteroidia class Bacteroidales> Prevotella as an example. First, the occupancy rate is set in multiple stages (0, 5, 10, 15, 20, 25, 30, 35, 40%, etc.), and when this is the cut-off value, it corresponds to no ovulation in each stage Obtain the number of subjects, the number of subjects corresponding to ovulation, and the total number. Next, the sensitivity for each cutoff value (number of subjects corresponding to no ovulation / total number of steps) and false negative (1-specificity (number of subjects applicable to ovulation / total number of steps)) are obtained. Logistic regression is performed based on the bivariate relationship to obtain an ROC curve (false negative on the X axis and sensitivity on the Y axis), and the area under the curve (AUC) at each cutoff value is maximized. The next point was determined as a more preferable cut-off value, the next point was set as a more preferable cut-off value, and the cut-off value at the third place was determined as a preferable cut-off value.
Furthermore, the occupancy rate of each bacterium in the intestinal flora and the relationship between subjects with ovulation disorder (without ovulation) and without ovulation disorder (with ovulation) were examined.
Then, from the relationship between the occupancy rate of each bacterium and the subject, a cut-off value serving as a criterion for determining whether or not there is an ovulation disorder is found. An example of the details of this examination is as described above. Thus, it is possible to provide a method for testing ovulation disorders with good determination accuracy and less invasiveness to the subject even with simple sample collection.

Claims (9)

  A test method for ovulation disorders, characterized by detecting bacteria in an intestinal flora in a specimen. The bacterium is one or more bacteria selected from the group consisting of the following [B1] to [B4], [F1] to [F13], [A1], [FS1], and [P1]. The method of claim 1, wherein:
[B1]: Bacteroidetes genus Bacteroidia class Bacteroidales> Prevotlaceae family Prevotella genus,
[B2]: Bacteroidetes gate Bacteroidia class Bacteroidales eyes S24-7,
[B3]: Bacteroidetes Gate Bacteroidia class Bacteroidales eyes Rikenellaceae,
[B4]: Bacteroidetes gate Bacteroidia class Bacteroidales eyes [Paraprevotellaceae],
[F1]: Firmicutes Gate Clostridia Class Closridiales eyes,
[F2]: Firmicutes gate Clostridia class Closridiales eyes Lachnospiraceae,
[F3]: Firmicutes Clostridia Class Closridiales [Tissierellaceae] Family WAL_1855D,
[F4]: Firmicutes Clostridia class Closridiales> Ruminococcaceae family Oscillospira,
[F5]: Firmicutes gate Clostridia class Closridiales eyes Lachnospiraceae family Anaerostipes genus,
[F6]: Firmicutes gate Clostridia class Closridiales eyes Veillonellaceae family Dialister genus,
[F7]: Firmicutes Clostridia class Closridiales> Ruminococcaceae family Ruminococcus,
[F8]: Firmicutes Clostridia class Closridiales> Peptococcaceae family rc4-4,
[F9]: Firmicutes Gate Clostridia Class Closridiales> Lachnospiraceae Family Roseburia,
[F10]: Firmicutes gate Erysipelotrichi class Erysipelotrichales> Erysipelotrichaceae family AllobacuLum,
[F11]: Firmicutes Clostridia class Closridiales> Clostridiaceae family Candidatus Arthromitus,
[F12]: Firmicutes Gate Clostridia Class Closridiales> Ruminococcaceae Family Other,
[F13]: Firmicutes Clostridia class Closridiales> Peptococcaceae family Peptococcus genus,
[A1]: Actinobacteria genus Coriobacteriia class Coriobacteriales order Coriobacteriaceae family Atopobium genus,
[FS1]: Fusobacteria genus Fusobacteriia class Fusobacteriales order Leptotrichiaceae Leptorichia genus,
[P1]: Proteobacteria genus Betaproteobacteria class Burkholderiales> Burkholderiaceae family Burkholderia genus   The bacteria are two types of combinations [B1] and [B2], two types of combinations [F1] and [F3], or at least one of the above [B1] to [B4] and the above [F1] to [F1] The method according to claim 1 or 2, which is a combination of at least one of [F13].   A method for assisting diagnosis of an ovulation disorder, comprising a step of determining an ovulation disorder based on an occupation ratio of bacteria in an intestinal flora in a specimen.   A method of measuring bacterial occupancy in the intestinal flora to determine ovulation disorders.   A method for detecting a substance that regulates ovulation disorders based on the occupancy rate of bacteria in the intestinal flora in a specimen. The detection method according to claim 6 includes the following (1) and (2).
(1) a first detection step of detecting an occupancy rate of bacteria in an intestinal bacterial flora in the sample from a sample collected from a subject who has ingested the test substance;
(2) A second detection step of determining whether or not the test substance is a substance that regulates ovulation disorders based on a change in the occupancy rate of the bacteria in the intestinal flora, and detecting a substance that regulates ovulation disorders.   The method according to claim 7, wherein the test substance is an edible material. The manufacturing method of the composition which detects the edible material for ovulation disorder improvement by the method of Claim 8, and contains the said edible material for ovulation disorder improvement.