Microorganism analysis system and microorganism analysis method

Abstract

A microorganism analysis system (1) is for estimating the presence, absence or abundance of a target microorganism (212) in a space (SP) of interest, the microorganism analysis system (1) including a first information acquisition unit (20) and a control unit (40). The first information acquisition unit (20) acquires first information (21) that relates to the space (SP) of interest but is different from information relating to the presence, absence or abundance of the target microorganism (212) itself. The control unit (40) estimates, on the basis of the first information (21), the presence, absence or abundance of the target microorganism (212) in the space (SP) of interest.

Description

Microbial analysis system and microbial analysis method

[0001] The present invention relates to a microbial analysis system and a microbial analysis method.

[0002] Conventionally, microorganisms have been detected by obtaining genomic material or DNA from microorganisms, amplifying it, and identifying specific regions of the genomic material or DNA (Patent Document 1 (JP 2020-529869 A)).

[0003] However, conventional methods for detecting microorganisms have the drawback of requiring expert operation and dedicated equipment, which can be time-consuming and labor-intensive.

[0004] A first aspect of the present invention is a microorganism analysis system for estimating the presence or absence or abundance of a target microorganism in a target space, and includes a first information acquisition unit and a control unit. The first information acquisition unit acquires first information about the target space, which is information different from the presence or absence and abundance of the target microorganism itself. The control unit estimates the presence or absence or abundance of the target microorganism in the target space based on the first information.

[0005] This microorganism analysis system eliminates the need for 100% testing, reducing the labor and costs required for testing.

[0006] A microorganism analysis system according to a second aspect is the system according to the first aspect, wherein the first information is environmental information of the target space. The environmental information is information about the amount of material collected from the target space, which is highly correlated with the amount of the target microorganism present.

[0007] In this microbial analysis system, the amount of sampled material, which has a high correlation with the amount of target microorganisms present, is used as environmental information, making it possible to estimate the presence of target microorganisms based on the environment surrounding the target microorganisms.

[0008] A microorganism analysis system according to a third aspect is the system according to the first aspect, wherein the first information includes either information about a representative microorganism that is present in the target space simultaneously with the target microorganism, or information about a representative microorganism that suppresses the presence of the target microorganism. The information about the representative microorganism includes the presence or absence or abundance of the representative microorganism in the target space. The control unit estimates the presence or absence or abundance of the target microorganism based on the information about the representative microorganism as the first information.

[0009] In this microorganism analysis system, even if a target microorganism is difficult to measure, it is possible to measure a representative microorganism that is easy to measure and infer the presence of the target microorganism from the relationship between the two.

[0010] A microorganism analysis system according to a fourth aspect is the system according to the third aspect, wherein the target microorganisms include microorganisms that adhere to a filter that collects suspended matter in the target space.

[0011] This microorganism analysis system can estimate the presence of target microorganisms attached to the filter.

[0012] A microorganism analysis system according to a fifth aspect is the system according to the third or fourth aspect, further comprising an image analysis unit. The image analysis unit identifies the microorganisms based on their shapes. The representative microorganisms are of a size that can be identified by image analysis by the image analysis unit.

[0013] In this microbial analysis system, the image analysis unit distinguishes representative microorganisms that are relatively large in size, making it easy to estimate the presence of target microorganisms, even if they can only be analyzed by culture methods.

[0014] A microbial analysis system according to the sixth aspect is a system according to the third or fourth aspect, in which the representative microorganism is a microorganism that can be cultured or subjected to a PCR reaction more safely than the target microorganism in terms of a safety index indicated by a biosafety level (BSL), or a microorganism that can be cultured or subjected to a PCR reaction more quickly than the target microorganism.

[0015] In this microbial analysis system, the presence of target microorganisms can be easily estimated by culturing or PCR-reacting representative microorganisms more safely and quickly than target microorganisms.

[0016] A seventh aspect of the present invention is a microorganism analysis system according to any one of the third to sixth aspects, further comprising a correspondence information storage unit. The correspondence information storage unit stores correspondence information indicating the correspondence between the target microorganism and the representative microorganism. The control unit further estimates the presence or absence or abundance of the target microorganism based on the correspondence information.

[0017] In this microorganism analysis system, the presence of target microorganisms can be easily predicted using information on representative microorganisms and information on the correspondence between target microorganisms and representative microorganisms.

[0018] A microorganism analysis system according to an eighth aspect is the system according to the seventh aspect, in which the correspondence information storage unit acquires correspondence information, which is a result of learning by a machine learning device that learns correspondence relationships between target microorganisms and representative microorganisms, from the machine learning device and stores the information. The control unit estimates the presence or absence or abundance of the target microorganism from the presence or absence or abundance of the representative microorganism based on the results of the correspondence information.

[0019] This microbial analysis system can accurately estimate the presence of representative microorganisms based on the results of learning by the machine learning device.

[0020] A ninth aspect of the present invention relates to a microorganism analysis system, which is the system according to any one of the third to eighth aspects, wherein the representative microorganism is one or more species selected from the group consisting of fungi, bacteria, pollen, and viruses.

[0021] In this microbial analysis system, the presence of target microorganisms can be easily estimated by using predetermined representative microorganisms.

[0022] A microbial analysis system according to a tenth aspect is a system according to the seventh or eighth aspect, in which the correspondence information includes at least one correspondence between the target microorganism and the representative microorganism, in which the target microorganism and the representative microorganism are either a first fungus and a second fungus, a first bacterium and a second bacterium, a first pollen and a second pollen, or a first virus and a second virus.

[0023] This microbial analysis system can estimate the presence of a target microorganism even when the target microorganism and a representative microorganism are included in the same group of microorganisms.

[0024] The microorganism analysis system of an eleventh aspect is the system of the seventh or eighth aspect, and the correspondence information includes at least one correspondence in which, when the target microorganism is a fungus, the representative microorganism is either a bacterium, pollen, or virus; when the target microorganism is a bacterium, the representative microorganism is either a fungus, pollen, or virus; when the target microorganism is pollen, the representative microorganism is either a fungus, bacterium, or virus; and when the target microorganism is a virus, the representative microorganism is either a fungus, bacterium, or pollen.

[0025] This microbial analysis system can estimate the presence of a target microorganism even if the target microorganism and the representative microorganism belong to different groups of microorganisms.

[0026] A twelfth aspect of the microorganism analysis system is the system of any one of the ninth aspect to the eleventh aspect, wherein the fungus is a fungus of the genus Aspergillus, a fungus of the genus Nigrospora, a fungus of the genus Cladosporium, a fungus of the genus Fusarium, a fungus of the genus Alternaria, a fungus of the genus Schizophyllum, a fungus of the genus Penicillium, a fungus of the genus Epicoccum, a fungus of the genus Hortaea, a fungus of the genus Eupenidiella, a fungus of the genus Chaetomium, a fungus of the genus Trametes, or a fungus of the genus Pseudopithomyces. Fungi of the genus Toxicocladosporium, fungi of the genus Peniophora, fungi of the genus Talaromyces, fungi of the genus Didymella, fungi of the genus Pleurotus, fungi of the genus Wallemia, fungi of the genus Curvularia, fungi of the genus Loweporus, fungi of the genus Periconia, fungi of the genus Candida ida fungi, Gibberella fungi, Auricularia fungi, Malassezia fungi, Naganishia fungi, Neurospora fungi, Ganoderma fungi, Engyodontium fungi, Ustilaginoidea fungi, Peroneutypa fungi, Fungi of the genus Flammulina, fungi of the genus Filobasidium, fungi of the genus Cercospora, fungi of the genus Hannaella, fungi of the genus Coprinopsis, fungi of the genus Irpex, fungi of the genus Phlebia, fungi of the genus Pyronema, fungi of the genus Microascus, fungi of the genus Sterigmatomyces,Fungi of the genus Trichosporon, Spissiomyces, Botrytis, Rhodotorula, Stachybotrys, Fibroporia, Bjerkandera, Phanerochete, Emmia, and Coprinellus , fungi of the genus Trechispora, fungi of the genus Acremonium, fungi of the genus Aureobasidium, fungi of the genus Lopharia, fungi of the genus Heterochaete, fungi of the genus Cutaneotrichosporon, fungi of the genus Aplosporella, and fungi of the genus Eutypella.

[0027] In this microbial analysis system, the presence of target microorganisms can be easily estimated by using a specific fungus as a representative microorganism.

[0028] A thirteenth aspect of the microbial analysis system is the system of any one of the ninth to eleventh aspects, wherein the bacteria include one or more species selected from the group consisting of Streptococcus bacteria, Acinetobacter bacteria, Alcaligenaceae bacteria, Pseudomonas bacteria, Paracoccus bacteria, Sphingomonas bacteria, Corynebacterium bacteria, Staphylococcus bacteria, Haemophilus bacteria, Parvum, Clostridium botulinum, and Chlamydia psittaci.

[0029] In this microbial analysis system, the presence of target microorganisms can be easily estimated by using a specific bacterium as a representative microorganism.

[0030] A microbial analysis system according to a fourteenth aspect is the system according to any one of the ninth aspect to the eleventh aspect, wherein the pollen is selected from the group consisting of Humulus pollen, Boehmeria pollen, Acalypha pollen, Magnolia pollen, Artemisia pollen, Cucumis pollen, Astragalus pollen, and Pou pollen. The pollen comprises one or more species selected from the group consisting of pollen of the genus Triticum, genus Citrullus, genus Podocarpus, genus Digitaria, genus Funaria, genus Solanum, genus Allium, and genus Glycine.

[0031] In this microbial analysis system, the presence of target microorganisms can be easily estimated by using a specific pollen as a representative microorganism.

[0032] A microbial analysis system according to a fifteenth aspect is the system according to any one of the ninth to eleventh aspects, wherein the virus comprises one or more viruses selected from the group consisting of influenza virus, monkeypox virus, rabies virus, dengue virus, and Japanese encephalitis virus.

[0033] In this microorganism analysis system, the presence of target microorganisms can be easily estimated by using a predetermined virus as a representative microorganism.

[0034] A microbial analysis system of a sixteenth aspect is a system of any one of the third to fifteenth aspects, wherein the relationship between the target microorganism and the representative microorganism is such that there is a negative correlation between the target microorganism that is any of the fungi of the genus Gibberella, Nigrospora, Fusarium, Cladosporium, Epicoccum, Periconia, Alternaria, Penicillium, Filobasidium, or Pleurotus, and the representative microorganism that is a fungus of the genus Aspergillus. There is a positive correlation between target microorganisms that are Penicillium fungi or Nigrospora fungi and representative microorganisms that are Boehmeria pollen. There is a positive correlation between target microorganisms that are Corynebacterium fungi or Alternaria fungi and representative microorganisms that are Humulus pollen. There is a positive correlation between target microorganisms that are Enhydrobacter bacteria and representative microorganisms that are Tramaetes fungi, Chaetomiun fungi, or Boehmeria pollen. Among the target microorganisms or representative microorganisms, Staphylococcus bacteria, Gibberella fungi, Cladosporium fungi, Cercospora fungi, and Curvularia fungi have a mutually positive correlation. Streptococcus bacteria, Haemophilus bacteria, Solanum pollen, and Cucumis pollen also have a mutually positive correlation.

[0035] This microbial analysis system can estimate the presence of a target microorganism in a plurality of combinations of the target microorganism and a representative microorganism.

[0036] A microbiological analysis system according to a seventeenth aspect is the system according to the seventh aspect, wherein the control unit creates the correspondence relationship information by machine learning.

[0037] In this microorganism analysis system, the correspondence information can be easily created by creating the correspondence information through machine learning.

[0038] In an eighteenth aspect, the microorganism analysis system is the system of the first aspect, wherein the first information is operational status information relating to the operational status of an air conditioning device installed in the target space, and the control unit estimates the presence or absence or amount of the target microorganism based on the operational status information as the first information.

[0039] In this microbial analysis system, the presence of target microorganisms can be easily estimated using information on the operational status of the air conditioning device.

[0040] A microbial analysis system according to a nineteenth aspect is the system according to the eighteenth aspect, wherein the first information is information relating to the correspondence between the operational status of the air conditioning device and the type and abundance of the representative microorganism. The control unit estimates the presence or absence or the abundance of the target microorganism based on the first information, which is information relating to the correspondence between the operational status of the air conditioning device and the type and abundance of the representative microorganism.

[0041] In this microbial analysis system, the presence of target microorganisms can be easily estimated by using information regarding the correspondence between the operational status of the air conditioning apparatus and the type and abundance of representative microorganisms.

[0042] A microbial analysis system of a twentieth aspect is a system of the eighteenth or nineteenth aspect, in which the operating status of the air conditioning device includes at least one of the operating time, operating mode, air volume, set temperature, set humidity, intake air temperature, and intake air humidity of the air conditioning device, and a non-cleaning period of the air conditioning device.

[0043] This microorganism analysis system can easily estimate the presence of target microorganisms even when the presence of target microorganisms changes depending on the operating state of the air conditioning device.

[0044] A microbial analysis system according to a twenty-first aspect is the system according to any one of the third to eighteenth aspects, wherein the first information is target space-related information of the target space. The target space-related information includes at least one of the following information: the climate, weather, geographical features, latitude, longitude, and altitude of the location where the target space is located; characteristics of the building that contains the target space; and the family composition of the residents of the target space. The control unit further uses the target space-related information as the first information to estimate the presence or absence or amount of the target microorganism.

[0045] In this microorganism analysis system, by further using information related to the target space, the presence of the target microorganism in the target space can be easily estimated.

[0046] A microbial analysis method according to a twenty-second aspect is a microbial analysis method for estimating the presence or absence or abundance of a target microorganism in a target space, wherein the presence or absence or abundance of the target microorganism in the target space is estimated based on first information about the target space, which is information different from the presence or absence and abundance of the target microorganism itself.

[0047] This microbial analysis method does not require 100% testing, which reduces the labor and costs required for testing.

[0048] 1 is a configuration diagram of a microbial analysis system. FIG. 2 is a diagram showing an example of the correlation between fungi, bacteria, and pollen. FIG. 3 is a diagram showing an example of fungi having a negative correlation with Aspergillus fungi. FIG. 4 is a flowchart for explaining an example of processing in a microbial analysis system. FIG. 5 is a diagram showing an example of the relative ratio of fungal abundance by city. FIG. 6 is a diagram showing an example of the relative ratio of fungal abundance. FIG. 7 is a diagram showing an example of a heat map showing the ratio of fungal abundance by season. FIG. 8 is a diagram showing an example of a heat map showing the ratio of fungal abundance by city. FIG. 9 is a diagram showing an example of a heat map showing the ratio of fungal abundance by region. FIG. 10 is a diagram showing an example of the relationship between bacterial diversity and non-cleaning periods. FIG. 11 is a configuration diagram of another microbial analysis system. FIG. 12 is a configuration diagram of another microbial analysis system.

[0049] (1) Overall Configuration of Microbial Analysis System A microbiota analysis system 1 of this embodiment is shown in Fig. 1. The microbiota analysis system 1 collects, as a sample, microorganisms 210 attached to a filter 101 of an air conditioning apparatus 100 installed in a target space (indoor space) SP contained in a structure such as a house, building, factory, or public facility using a sampling device 200, and analyzes the microorganisms 210 using captured images 301 of the microorganisms 210 captured by a photographing device 300.

[0050] The microorganism analysis system 1 is realized by a computer, and includes an image analysis unit 10 , a first information acquisition unit 20 , a correspondence relationship information accumulation unit 30 , and a control unit 40 .

[0051] (2) Detailed Configuration of Microorganism Analysis System (2-1) Image Analysis Unit The image analysis unit 10 acquires a photographed image 301 of the microorganism 210 photographed by the photographing device 300 and identifies the microorganism 210 based on the shape of the microorganism 210 .

[0052] The microorganisms 210 include representative microorganisms 211 and target microorganisms 212. The representative microorganisms 211 are one or more types selected from the group consisting of fungi, bacteria, pollen, and viruses. The target microorganisms 211 are microorganisms whose presence or absence or amount in the target space SP is to be determined.

[0053] The representative microorganisms 211 are of a size that can be distinguished by image analysis using the image analysis unit 10. The size of the representative microorganisms 211 is preferably 0.2 μm or more, and more preferably 2 μm or more. 0.2 μm is the same as the limit value that can be seen with an optical microscope. 2 μm is the same as the size that can be seen with a practical magnification of an optical microscope (approximately 1000x). Most fungi are about 2 μm or more in size. Most bacteria are 1 μm or less in size. In particular, fungi and pollen have large particle diameters and can be distinguished by image analysis, so they are preferably used as the representative microorganisms 211.

[0054] The target microorganisms 212 include microorganisms that adhere to the filter 101 of the air conditioning apparatus 100 that has captured suspended matter in the target space SP.

[0055] (2-1-1) Fungi Fungi include fungi of the genus Aspergillus, fungi of the genus Nigrospora, fungi of the genus Cladosporium, fungi of the genus Fusarium, fungi of the genus Alternaria, fungi of the genus Schizophyllum, fungi of the genus Penicillium, fungi of the genus Epicoccum, fungi of the genus Hortaea, fungi of the genus Eupenidiella, fungi of the genus Chaetomium, fungi of the genus Trametes, fungi of the genus Pseudopithomyces, fungi of the genus Toki, fungi of the genus Toxicocladosporium fungi, Peniophora fungi, Talaromyces fungi, Didymella fungi, Pleurotus fungi, Wallemia fungi, Curvularia fungi, Loweporus fungi, Periconia fungi, Candida fungi, Gibberella fungi, The fungi of the genus Gibberella, the fungi of the genus Auricularia, the fungi of the genus Malassezia, the fungi of the genus Naganishia, the fungi of the genus Neurospora, the fungi of the genus Ganoderma, the fungi of the genus Engyodontium, the fungi of the genus Ustilaginoidea, the fungi of the genus Peroneutypa, and the fungi of the genus Flammulina Fungi, Filobasidium fungi, Cercospora fungi, Hannaella fungi, Coprinopsis fungi, Irpex fungi, Fungi of the genus Phlebia, fungi of the genus Pyronema, fungi of the genus Microascus, fungi of the genus Sterigmatomyces, fungi of the genus Trichosporon,Spissiomyces, Botrytis, Rhodotorula, Stachybotrys, Fibroporia, Bjerkandera, Phanerochete, Emmia, Coprinellus, Trexpora The fungi include one or more species selected from the group consisting of fungi of the genus Acremonium, fungi of the genus Aureobasidium, fungi of the genus Lopharia, fungi of the genus Heterochaete, fungi of the genus Cutaneotrichosporon, fungi of the genus Aplosporella, and fungi of the genus Eutypella.

[0056] The fungi may include one or more species selected from the group consisting of fungi of the genus Clanostachys, fungi of the class Sordariomycetes, fungi of the genus Amphobotrys, fungi of the genus Dokmaya, and fungi of the genus Bipolaris.

[0057] (2-1-2) Pollen The pollen includes at least one species selected from the group consisting of Humulus pollen, Boehmeria pollen, Acalypha pollen, Magnolia pollen, Artemisia pollen, Cucumis pollen, Astragalus pollen, Pouzolzia pollen, Osmanthus pollen, Triticum pollen, Citrullus pollen, Podocarpus pollen, Digitaria pollen, Funaria pollen, Solanum pollen, Allium pollen, and Glycine pollen.

[0058] The pollen may include one or more species selected from the group consisting of Astragalus pollen, Ulmus pollen, Brassica pollen, Dinebra pollen, and Streptophyta pollen.

[0059] (2-1-3) Bacteria The bacteria include one or more species selected from the group consisting of Streptococcus, Acinetobacter, Alcaligenaceae, Pseudomonas, Paracoccus, Sphingomonas, Corynebacterium, Staphylococcus, Haemophilus, parvum, Clostridium botulinum, and Chlamydia psittaci.

[0060] The bacteria may include one or more species selected from the group consisting of mitochondria, chloroplasts, bacteria of the genus Brevundimonas, bacteria of the genus Prebotella, bacteria of the genus Micrococcus, bacteria of the genus Roseomonas, bacteria of the genus Craurococcus Caldobatus, bacteria of the genus Allorhizobium, bacteria of the genus Neisseria, bacteria of the genus Skermanella, bacteria of the genus Enhydrobactor, bacteria of the genus Cutibacterium, and bacteria of the genus Lactobacillus. The bacteria may also include one or more species selected from the group consisting of bacteria of the genus Acinetobacter, bacteria of the genus Craurococcus-Caldovatus (pathogens), and Lactocacillus (good bacteria).

[0061] (2-1-4) Viruses The viruses include one or more selected from the group consisting of influenza virus, monkeypox virus, rabies virus, dengue virus, and Japanese encephalitis virus.

[0062] (2-2) First Information Acquisition Unit The first information acquisition unit 20 acquires first information 21 regarding the target space SP, which is information different from the presence or absence and abundance of the target microorganisms 212 themselves.

[0063] In this embodiment, the first information acquisition unit 20 acquires first information 21 from the analysis result of the captured image 301 by the image analysis unit 10. The first information 21 includes either information about the representative microorganism 211 that is present in the target space SP simultaneously with the target microorganism 212, or information about the representative microorganism 211 that suppresses the presence of the target microorganism 212. The information about the representative microorganism 211 includes the presence or absence or the amount of the representative microorganism 211 in the target space SP.

[0064] (2-3) Correspondence Information Storage Unit The correspondence information storage unit 30 stores correspondence information 31 indicating the correspondence between the target microorganisms 212 and the representative microorganisms 211 .

[0065] The correspondence information 31 includes information on whether the target microorganism 212 and the representative microorganism 211 have a positive correlation or a negative correlation. When the target microorganism 212 and the representative microorganism 211 have a positive correlation, the target microorganism 212 is considered to be present when the representative microorganism 211 is present. When the target microorganism 212 and the representative microorganism 211 have a negative correlation, the presence of the representative microorganism 211 is considered to suppress the presence of the target microorganism 212.

[0066] In this embodiment, correspondence relationship information 31 relating to the correspondence between the representative microorganisms 211 and the target microorganisms 212 is acquired in advance and stored in the correspondence relationship information storage unit 30 .

[0067] FIG. 2 is a diagram showing an example of the correlation between fungi, bacteria, and pollen.

[0068] The fungi listed in Figure 2 include fungi of the genus Aspergillus, fungi of the genus Nigrospora, fungi of the genus Cladosporium, fungi of the genus Alternaria, fungi of the genus Schizophyllum, fungi of the genus Penicillium, fungi of the genus Chaetomium, fungi of the genus Trametes, fungi of the genus Pseudopithomyces, fungi of the genus Toxicocladosporium ... The 20 species are: fungi of the genus xicocladosporium, fungi of the genus Curvularia, fungi of the genus Candida, fungi of the genus Gibberella, fungi of the genus Ganoderma, fungi of the genus Cercospora, fungi of the genus Clanostachys, fungi of the class Sordariomycetes, fungi of the genus Amphobotrys, fungi of the genus Dokmaya, and fungi of the genus Bipolaris.

[0069] Among these, fungi of the genus Aspergillus, Nigrospora, Cladosporium, Alternaria, Penicillium, Curvularia, Cercospora, and Bipolaris are potentially harmful fungi.

[0070] The bacteria listed in Figure 2 include Paracoccus bacteria, Sphingomonas bacteria, Corynebacterium bacteria, Staphylococcus bacteria, Haemophilus bacteria, Streptococcus bacteria, Mitochondria, Chlopoplast, Brevundimonas bacteria, Prebotella The 19 species are: bacteria of the genus Bacillus, Micrococcus, Roseomonas, Craurococcus Caldobatus, Allorhizobium, Neisseria, Skermanella, Enhydrobactor, Cutibacterium, and Lactobacillus.

[0071] Among these, bacteria of the genus Sphingomonas, Corynebacterium, Staphylococcus, Haemophilus, Streptococcus, Brevundimonas, Prebotella, Roseomonas, Craurococcus Caldobatus, Allorhizobium, Neisseria, Skermanella, and Enhydrobactor are potentially harmful bacteria.

[0072] The pollens listed in Figure 2 include pollen from the genus Humulus, Boehmeria, Acalypha, Magnolia, Artemisia, Cucumis, Astragalus, Pouzolzia, Osmanthus, and wheat. The 20 species are: Citrus riticum pollen, Citrullus pollen, Podocarpus pollen, Digitaria pollen, Funaria pollen, Solanum pollen, Allium pollen, Ulmus pollen, Brassica pollen, Dinebra pollen, and Streptophyta pollen.

[0073] Of these, Humulus pollen, Artemisia pollen, Solanum pollen, and Ulmus pollen are potentially harmful pollens.

[0074] For example, as shown in FIG. 2, the relationship between the target microorganism 212 and the representative microorganism 211 is such that the target microorganism 212, which is a fungus of the genus Penicillium or Nigrospora, and the representative microorganism 211, which is pollen of the genus Boehmeria, have a positive correlation.

[0075] Furthermore, there is a positive correlation between the target microorganism 212, which is a bacterium of the genus Corynebacterium or a fungus of the genus Alternaria, and the representative microorganism 211, which is Humulus pollen.

[0076] There is a positive correlation between the target microorganism 212, which is a bacterium of the genus Enhydrobacter, and the representative microorganism 211, which is any one of a fungus of the genus Tramaetes, a fungus of the genus Chaetomiun, or pollen of the genus Boehmeria.

[0077] Among the target microorganisms 212 or representative microorganisms 211, Staphylococcus bacteria, Gibberella fungi, Cladosporium fungi, Cercospora fungi, and Curvularia fungi are positively correlated with one another. Streptococcus bacteria, Haemophilus bacteria, Solanum pollen, and Cucumis pollen are also positively correlated with one another.

[0078] 3 is a diagram showing an example of fungi having a negative correlation with Aspergillus fungi. As shown in FIG. 3, for example, the relationship between the target microorganism 212 and the representative microorganism 211 is such that the target microorganism 212, which is any of the fungi of the genus Gibberella, Nigrospora, Fusarium, Cladosporium, Epicoccum, Periconia, Alternaria, Penicillium, Filobasidium, and Pleurotus, has a negative correlation with the representative microorganism 211, which is a fungus of the genus Aspergillus.

[0079] (2-4) Control Unit The control unit 40 is realized by a computer. The control unit 40 includes a control and arithmetic unit and a storage device (not shown). A processor such as a CPU or a GPU can be used for the control and arithmetic unit. The control and arithmetic unit reads a program stored in the storage device and performs predetermined image processing and arithmetic processing according to the program. Furthermore, the control and arithmetic unit can write the results of calculations to the storage device and read information stored in the storage device according to the program. The storage device can be used as a database.

[0080] The control unit 40 estimates the presence or absence or abundance of the target microorganisms 212 in the target space SP based on the first information 21. The control unit 40 estimates the presence or absence or abundance of the target microorganisms 212 based on information related to the representative microorganisms 211 as the first information 21. In this embodiment, the control unit 40 further estimates the presence or absence or abundance of the target microorganisms 212 based on the correspondence information 31.

[0081] (3) Overall Operation of Microbiological Analysis System An example of the processing of the microbiological analysis system 1 will be described with reference to the flowchart of FIG.

[0082] In step S101, the image analysis unit 10 acquires a captured image 301 captured by the imaging device 300. In this embodiment, the image analysis unit 10 acquires the captured image 301 of the microorganisms 210 collected as a sample by the sampling device 200 from the filter 101 of the air conditioning device 100 installed in the target space SP.

[0083] The sampling device 200 immerses the filter 101 cut to a predetermined size in an elution solution to elute the microorganisms 210 adhering to the filter 101 and collect them as a sample. The elution solution is, for example, phosphate buffered saline (PBS-T). The sampling device 200 is, for example, a 10 cm ２ The size and number of filters 101 used by the sampling device 200 are not limited to this.

[0084] The imaging device 300 captures an image of the microorganisms 210 collected as a sample from the filter 101. The imaging device 300 may be, for example, a JIS B7271 (portable microorganism observation device). However, the imaging device 300 is not limited to this.

[0085] In step S102, the image analysis unit 10 identifies the microorganism 210 using the photographed image 301 of the microorganism 210 acquired in step S1.

[0086] In this embodiment, the image analysis unit 10 identifies representative microorganisms 211 that are large enough to be identified by image analysis from among the microorganisms 210 sampled from the filter 101 of the air conditioning apparatus 100 installed in the target space SP. In this embodiment, the representative microorganisms 211 are fungi of the genus Aspergillus. The representative microorganisms 211 are not limited to fungi of the genus Aspergillus, and may be one or more types selected from the group consisting of fungi, bacteria, pollen, and viruses.

[0087] In step S103, the first information acquisition unit 20 acquires information about the representative microorganism 211 as the first information 21. In this embodiment, the first information acquisition unit 20 acquires the presence or absence of fungi of the genus Arpergillus as the information about the representative microorganism 211. If fungi of the genus Arpergillus are present in the photographed image 301 acquired in step S1, the first information acquisition unit 20 may acquire the abundance of fungi of the genus Arpergillus as the information about the representative microorganism 211.

[0088] In step S104, the control unit 40 estimates the presence or absence or amount of the target microorganism 212 based on the information regarding the representative microorganism, which is the first information 21 acquired in step S3, and the correspondence information 31 stored in the correspondence information storage unit 30.

[0089] In this embodiment, the representative microorganism is a fungus of the genus Aspergillus, and the target microorganism is a fungus of the genus Nigrospora. The correspondence between the fungus of the genus Aspergillus and the fungus of the genus Nigrospora is negatively correlated. The relationship between the target microorganism 212 and the representative microorganism 211 is not limited to the relationship between the fungus of the genus Nigrospora and the fungus of the genus Aspergillus. The presence or absence or abundance of a microorganism having a positive or negative correlation with the representative microorganism 211 is estimated as the target microorganism 212. In this embodiment, when the first information acquisition unit 20 acquires information detecting the presence of a fungus of the genus Aspergillus in step S3, the control unit 40 estimates in step S4 that the presence of a fungus of the genus Nigrospora is suppressed.

[0090] (4) Characteristics of microorganisms present in air conditioning unit filters The inventors of the present application collected filters 101 from air conditioning units 100 in 12 cities in China and examined the microorganisms 210 present in the filters 101, and discovered that malignant microorganisms (allergens, etc.) are present in the filters 101, that the microorganisms present in the filters 101 depend on how the air conditioning units 100 are used and on the region, and that certain combinations of microorganisms have a co-occurrence relationship in which they influence each other's existence.

[0091] (4-1) Overall Trends of Adherent Bacteria Figure 5 is a diagram showing an example of the relative proportion of the abundance of fungi adhering to the filter 101 of the air conditioning device 100 in winter for each of 12 cities. Figure 6 is a diagram showing an example of the relative proportion of the abundance of fungi adhering to the filter 101 of the air conditioning device 100 in winter, aggregated values ​​for all 12 cities. The 12 cities include northern cities 1 to 3 (N1 to N3) and southern cities 1 to 9 (S1 to S9).

[0092] As shown in Figure 5, in most of the 12 cities, except for Northern City 3 (N3), the relative proportion of fungal abundance was dominated by Aspergillus fungi. Furthermore, as shown in Figure 6, the relative proportion of fungi detected across the 12 cities in China was 49.44%, with a significant difference from the second most common species, Nigrospora fungi (8.82%). Meanwhile, the most common relative proportion of bacteria detected across the 12 cities in China was Paracoccus (6.12%), with a less pronounced difference than the second most common species, Acinetobacter (4.85%) (not shown).

[0093] 7 is a diagram showing an example of a heat map showing the proportion of the abundance of fungi detected on the filter 101 of the air conditioning apparatus 100 by season. The proportion of the abundance of fungi of the genus Aspergillus is particularly high in winter, summer, and autumn.

[0094] (4-2) Regional Characteristics There are combinations of cities in which the types of fungi and bacteria present on the filters 101 of the air conditioning apparatus 100 are similar.

[0095] FIG. 8 is a diagram showing an example of a heat map showing the ratio of the abundance of fungi detected on the filter 101 of the air conditioning apparatus 100 by city.

[0096] For example, the types of fungi present in the filter 101 of the air conditioning unit 100 are similar in each of the combinations of Southern City 7 (S7) (not shown) and Southern City 4 (S4), Southern City 8 (S8) and Northern City 2 (N2), Southern City 5 (S5) and Southern City 9 (S9), and Southern City 6 (S6), Southern City 3 (S3), Southern City (S1) and Southern City 2 (S2).

[0097] Furthermore, the types of bacteria present in the filter 101 of the air conditioning unit 100 are similar in each of the combinations, for example, Northern City 3 (N3), Southern City 9 (N9), and Southern City 7 (S7), Southern City 5 (S5), Southern City 2 (S2), and Southern City (S6), and Northern City 2 (N2), Southern City 1 (S1), and Northern City 1 (N1) (not shown).

[0098] Furthermore, the ratio of fungi and bacteria present in the filter 101 of the air conditioner 100 tends to differ between the north and south regions.

[0099] FIG. 9 is a diagram showing an example of a heat map showing the ratio of the abundance of fungi detected on the filter 101 of the air conditioning apparatus 100 by north and south region.

[0100] The northern region includes northern cities 1 to 3 (N1 to N3), and the southern region includes southern cities 1 to 9 (S1 to S9).

[0101] The further south you go, the more common the fungi are of the genus Aspergillus, and the more common the bacteria are of the genus Roseomonas (pathogens) and the genus Craurococcus-Caldovatus (pathogens) (not shown).

[0102] (4-3) Relationship with Environmental Factors The diversity and quantity of bacteria attached to the filter 101 of the air conditioning device 100 correlate with the non-cleaning period of the air conditioning device 100, the family composition (number of people) of the residents in the target space SP, and the characteristics (number of floors) of the building containing the target space SP.

[0103] Figure 10 is a diagram showing an example of the relationship between the diversity of bacteria adhering to the filter 101 of the air conditioning apparatus 100 and the non-cleaning period in 12 cities. The vertical axis represents the diversity of bacteria, and the horizontal axis represents the non-cleaning period. As shown in Figure 10, the diversity of bacteria decreases as the non-cleaning period of the air conditioning apparatus 100 becomes longer.

[0104] Furthermore, the diversity of bacteria adhering to the filter 101 of the air conditioner 100 tends to increase slightly with a larger family size (not shown). Furthermore, with regard to the amount of microorganisms adhering to the filter 101 of the air conditioner 100, the larger the family structure (number of people) of the occupants in the target space SP, the more Candida fungi (pathogens) and Roseomonas bacteria (pathogens) there are, and the higher the floor, the more Nigrospora fungi (pathogens) and Lactocacillus (good bacteria) there are (not shown).

[0105] (5) Features (5-1) The microbial analysis system 1 according to this embodiment is a microbial analysis system 1 that estimates the presence or absence or abundance of target microorganisms 212 in a target space SP, and includes a first information acquisition unit 20 and a control unit 40. The first information acquisition unit 20 acquires first information 21 regarding the target space SP, which is information different from the presence or absence and abundance of the target microorganisms 212 themselves. The control unit 40 estimates the presence or absence or abundance of the target microorganisms 212 in the target space SP based on the first information 21.

[0106] Traditionally, analyzing microorganisms has been laborious and time-consuming, requiring, for example, cultivation, specialized skills, and equipment.

[0107] With this microbial analysis system 1, even if it is not possible to directly measure the microorganisms (target microorganisms) 212 whose presence or absence is to be determined, it is possible to estimate the presence and amount of the target microorganisms 212 that may adhere to the filter 101 of the air conditioning device 100 by determining the presence and amount of co-occurring microorganisms (representative microorganisms) 211. With this microbial analysis system 1, 100% testing is not required, and therefore the effort and cost required for testing can be reduced.

[0108] (5-2) In the microorganism analysis system 1 according to this embodiment, the first information 21 includes either information about the representative microorganism 211 that is present in the target space SP simultaneously with the target microorganism 212, or information about the representative microorganism 211 that suppresses the presence of the target microorganism 212. The information about the representative microorganism 211 includes the presence or absence or the amount of the representative microorganism 211 in the target space SP.

[0109] In this microorganism analysis system 1, information on the representative microorganism 211 related to the presence or absence of the target microorganism 212 can be obtained.

[0110] (5-3) In the microorganism analysis system 1 according to this embodiment, the target microorganisms 212 include microorganisms that adhere to the filter 101 that has collected suspended matter in the target space SP.

[0111] In this microorganism analysis system 1, the presence of target microorganisms 212 attached to the filter 101 of the air conditioning device 100 can be estimated.

[0112] (5-4) The microorganism analysis system 1 according to this embodiment further includes an image analysis unit 10. The image analysis unit 10 distinguishes the microorganisms 210 based on the shapes of the microorganisms 210. The representative microorganisms 211 are of a size that can be distinguished by image analysis by the image analysis unit 10.

[0113] It is possible to reduce the effort, time, cost, and safety risks by selecting a microorganism that is large in size, can be image-analyzed, and is easy to detect as the representative microorganism 211. This microorganism analysis system 1 is particularly effective in situations such as when the target microorganism 212 is a dangerous microorganism, when it is difficult to cultivate the target microorganism 212, when the target microorganism 212 is small and image analysis is difficult, or when there is a microorganism similar in shape to the target microorganism 212 and image analysis is difficult.

[0114] In this microorganism analysis system 1, by using the image analysis unit 10 to identify representative microorganisms 211 that are relatively large in size, the presence of target microorganisms 212 can be easily estimated even if the target microorganisms 212 can only be analyzed by a culture method.

[0115] (5-5) The microorganism analysis system 1 according to this embodiment further includes a correspondence information storage unit 30. The correspondence information storage unit 30 stores correspondence information 31 indicating the correspondence between the target microorganism 212 and the representative microorganism 211. The control unit 40 estimates the presence or absence or the amount of the target microorganism 212 based on the correspondence information 31 and information on the representative microorganism 211, which is the first information 21. The correspondence information 31 stored in the correspondence information storage unit 30 may be known correspondence information.

[0116] In this microbial analysis system 1, the presence of the target microorganism 212 can be easily predicted using information regarding the representative microorganism 211 and information regarding the correspondence between the target microorganism 212 and the representative microorganism 211 that has been stored in advance in the correspondence information storage unit 30.

[0117] (5-6) In the microorganism analysis system 1 according to this embodiment, the representative microorganism 211 is one or more types selected from the group consisting of fungi, bacteria, pollen, and viruses, and is a fungus of the genus Aspergillus.

[0118] In this microorganism analysis system 1, by using a fungus of the genus Aspergillus as the representative microorganism 211, the presence or abundance of a target microorganism 212 associated with the presence of a fungus of the genus Aspergillus can be easily estimated.

[0119] (5-7) In the microorganism analysis system 1 according to this embodiment, the fungi include fungi of the genus Aspergillus, fungi of the genus Nigrospora, fungi of the genus Cladosporium, fungi of the genus Fusarium, fungi of the genus Alternaria, fungi of the genus Schizophyllum, fungi of the genus Penicillium, fungi of the genus Epicoccum, fungi of the genus Hortaea, fungi of the genus Eupenidiella, fungi of the genus Chaetomium, fungi of the genus Trametes, and fungi of the genus Pseudopithomyces. Fungi of the genus Toxicocladosporium, fungi of the genus Peniophora, fungi of the genus Talaromyces, fungi of the genus Didymella, fungi of the genus Pleurotus, fungi of the genus Wallemia, fungi of the genus Curvularia, fungi of the genus Loweporus, fungi of the genus Periconia, fungi of the genus Candida ida fungi, Gibberella fungi, Auricularia fungi, Malassezia fungi, Naganishia fungi, Neurospora fungi, Ganoderma fungi, Engyodontium fungi, Ustilaginoidea fungi, Peroneutypa fungi, Fungi of the genus Flammulina, fungi of the genus Filobasidium, fungi of the genus Cercospora, fungi of the genus Hannaella, fungi of the genus Coprinopsis, fungi of the genus Irpex, fungi of the genus Phlebia, fungi of the genus Pyronema, fungi of the genus Microascus, fungi of the genus Sterigmatomyces,Fungi of the genus Trichosporon, Spissiomyces, Botrytis, Rhodotorula, Stachybotrys, Fibroporia, Bjerkandera, Phanerochete, Emmia, and Coprinellus , fungi of the genus Trechispora, fungi of the genus Acremonium, fungi of the genus Aureobasidium, fungi of the genus Lopharia, fungi of the genus Heterochaete, fungi of the genus Cutaneotrichosporon, fungi of the genus Aplosporella, and fungi of the genus Eutypella.

[0120] By using the fungus of the genus Aspergillus as the representative microorganism 211, this microorganism analysis system 1 can easily estimate the presence of a target microorganism 212 that has a positive or negative correlation with the fungus of the genus Aspergillus.

[0121] (5-8) In the microorganism analysis system 1 according to this embodiment, the bacteria include one or more species selected from the group consisting of Streptococcus bacteria, Acinetobacter bacteria, Alcaligenaceae bacteria, Pseudomonas bacteria, Paracoccus bacteria, Sphingomonas bacteria, Corynebacterium bacteria, Staphylococcus bacteria, Haemophilus bacteria, Parvum, Clostridium botulinum, and Chlamydia psittaci.

[0122] In this microorganism analysis system 1, by using an Aspergillus fungus as a representative microorganism 211, when the target microorganism 212 is a bacterium, it is possible to easily estimate the presence of bacteria that have a positive or negative correlation with the Aspergillus fungus.

[0123] (5-9) In the microorganism analysis system 1 according to this embodiment, the pollen includes one or more species selected from the group consisting of Humulus genus pollen, Boehmeria genus pollen, Acalypha genus pollen, Magnolia genus pollen, Artemisia genus pollen, Cucumis genus pollen, Astragalus genus pollen, Pouzolzia genus pollen, Osmanthus genus pollen, Triticum genus pollen, Citrullus genus pollen, Podocarpus genus pollen, Digitaria genus pollen, Funaria genus pollen, Solanum genus pollen, Allium genus pollen, and Glycine genus pollen.

[0124] In this microorganism analysis system 1, by using an Aspergillus fungus as a representative microorganism 211, when the target microorganism 212 is pollen, it is possible to easily estimate the presence of pollen that has a positive or negative correlation with the Aspergillus fungus.

[0125] (5-10) In the microorganism analysis system 1 according to this embodiment, the viruses include one or more types selected from the group consisting of influenza virus, monkeypox virus, rabies virus, dengue virus, and Japanese encephalitis virus.

[0126] In this microorganism analysis system 1, by using an Aspergillus fungus as the representative microorganism 211, if the target microorganism 212 is a virus, it is possible to easily estimate the presence of a virus that has a positive or negative correlation with the Aspergillus fungus.

[0127] (5-11) In the microbial analysis system 1 according to this embodiment, the relationship between the target microorganism 212 and the representative microorganism 211 is such that there is a negative correlation between the target microorganism 212, which is any of the fungi of the genus Gibberella, Nigrospora, Fusarium, Cladosporium, Epicoccum, Periconia, Alternaria, Penicillium, Filobasidium, and Pleurotus, and the representative microorganism 211, which is a fungus of the genus Aspergillus. There is a positive correlation between the target microorganism 212, which is a fungus of the genus Penicillium or a fungus of the genus Nigrospora, and the representative microorganism 211, which is pollen of the genus Boehmeria. There is a positive correlation between the target microorganism 212, which is a bacterium of the genus Corynebacterium or a fungus of the genus Alternaria, and the representative microorganism 211, which is pollen of Humulus. There is a positive correlation between the target microorganism 212, which is a bacterium of the genus Enhydrobacter, and the representative microorganism 211, which is any of a fungus of the genus Tramaetes, a fungus of the genus Chaetomiun, or pollen of the genus Boehmeria. Among the target microorganisms 212 or representative microorganisms 211, bacteria of the genus Staphylococcus, fungi of the genus Gibberella, fungi of the genus Cladosporium, fungi of the genus Cercospora, and fungi of the genus Curvularia are positively correlated with one another. In addition, bacteria of the genus Streptococcus, bacteria of the genus Haemophilus, pollen of the genus Solanum, and pollen of the genus Cucumis are positively correlated with one another.

[0128] In this microorganism analysis system 1, the presence of the target microorganism 212 can be estimated for a plurality of combinations of the target microorganism 212 and the representative microorganism 211.

[0129] (5-12) The microbial analysis method according to this embodiment is a microbial analysis method that estimates the presence or absence or abundance of target microorganisms 212 in a target space SP. The presence or absence or abundance of target microorganisms 212 in the target space SP is estimated based on first information 21 about the target space SP, which is information different from the presence or absence and abundance of the target microorganisms 212 themselves.

[0130] This microbial analysis method does not require 100% testing, which reduces the labor and costs required for testing.

[0131] (6) Modifications (6-1) Modification 1A In the microorganism analysis system 1 shown in FIG. 1, the correspondence information storage unit 30 may acquire and store correspondence information 32, which is the result of learning by a machine learning machine (not shown), that learns the correspondence between the target microorganisms 212 and the representative microorganisms 211.

[0132] Furthermore, the correspondence relationship between the target microorganism 212 and the representative microorganism 211 in the correspondence relationship information 31, 32 is not limited to the correspondence relationship between fungi of the genus Nigrospora and fungi of the genus Aspergillus. The correspondence relationship information 31, 32 between the target microorganism 212 and the representative microorganism 211 may also include a correspondence relationship between a first fungus and a second fungus other than fungi of the genus Nigrospora and fungi of the genus Aspergillus. Furthermore, the correspondence relationship information 31, 32 may include at least one correspondence relationship between a first bacterium and a second bacterium, a first pollen and a second pollen, or a first virus and a second virus.

[0133] Furthermore, the correspondence information 31, 32 may include at least one correspondence in which, when the target microorganism 212 is a fungus, the representative microorganism 211 is either a bacterium, pollen or virus, when the target microorganism 212 is a bacterium, the representative microorganism 211 is either a fungus, pollen or virus, when the target microorganism 212 is pollen, the representative microorganism 211 is either a fungus, bacterium or virus, and when the target microorganism 212 is a virus, the representative microorganism 211 is either a fungus, bacterium or pollen.

[0134] In the microorganism analysis system of Modification 1A, the presence of the representative microorganism can be accurately estimated based on the correspondence information 32, which is the result of learning by the machine learning device. Furthermore, even if the target microorganism 212 and the representative microorganism 212 are included in the same group of the microorganisms 210, the presence of the target microorganism 212 can be estimated. Furthermore, even if the target microorganism 212 and the representative microorganism 211 are included in different groups of the microorganisms 210, the presence of the target microorganism 212 can be estimated.

[0135] (6-2) Modification 1B In the microorganism analysis system 1 shown in FIG. 1, the control unit 40 may create the correspondence information 31 stored in the correspondence information storage unit 30 by machine learning.

[0136] In the microorganism analysis system of modification 1B, the correspondence information 31 can be easily created by creating the correspondence information 31 through machine learning.

[0137] (6-3) Modification 1C In the microorganism analysis system 1a of Modification 1C, the first information 21a may be environmental information of the target space SP. The environmental information is information about the amount of material collected from the target space SP, which is highly correlated with the abundance of the target microorganisms 212.

[0138] A microorganism analysis system 1a of modification 1C is shown in Fig. 11. As shown in Fig. 11, the microorganism analysis system 1a includes a first information acquisition unit 20a and a control unit 40a.

[0139] The first information acquisition unit 20a acquires environmental information of the target space SP as the first information 21a. The environmental information includes, for example, the odor of fungi (mold), humidity in the target space SP, and the like.

[0140] When the first information 21a is the odor of fungus, the control unit 40a estimates, based on the odor of fungus, the presence of fungus, which is the target microorganism 212. When the first information 21a is the humidity in the target space SP, the control unit 40a estimates the presence of influenza virus, which is the target microorganism 212, in the target space SP.

[0141] In the microorganism analysis system 1a of variant 1C, the amount of collected material that is highly correlated with the amount of target microorganism 212 present is used as environmental information, so that the presence of target microorganism 212 can be estimated based on the environment surrounding the target microorganism 212.

[0142] (6-4) Modification 1D In a microorganism analysis system 1b of modification 1D, a control unit 40b estimates the presence or absence or the amount of target microorganisms based on information on representative microorganisms 211 as first information 21b.

[0143] A microorganism analysis system 1b of modification 1D is shown in Fig. 12. As shown in Fig. 12, the microorganism analysis system 1b includes a first information acquisition unit 20b and a control unit 40b.

[0144] In the microbial analysis system 1b, the representative microorganism 211 is a microorganism that can be cultured or subjected to PCR reaction more safely than the target microorganism 212 in terms of the safety index indicated by the biosafety level (BSL), or a microorganism that can be cultured or subjected to PCR reaction more quickly than the target microorganism 212.

[0145] For example, when bacteria or viruses are used as the representative microorganisms 211, the representative microorganisms 211 are those that are relatively safe, with a BSL of 1 or 2 and a disease classification of Class 5 or 4.

[0146] Examples of bacterial BSLs and disease classifications are shown in Table 1.

[0147]

[0148] Examples of viral BSLs and disease classifications are shown in Table 2.

[0149]

[0150] In Modification 1D, the sampling device 201 collects, as a sample, microorganisms 210 attached to the filter 101 of the air conditioning device 100 installed in the target space SP.

[0151] The sampling device 201 immerses the filter 101 cut to a predetermined size in an elution solution to elute the microorganisms 210 adhering to the filter 101 and collect them as a sample. The elution solution is, for example, phosphate buffered saline (PBS-T). The sampling device 201 is, for example, a 10 cm ２ The size and number of filters 101 used by the sampling device 201 are not limited to this.

[0152] The eluted microorganisms 210 are cultured to increase their numbers. Alternatively, the sampling device 201 extracts DNA from the cultured microorganisms and performs a PCR reaction. The sampling device 201 then decodes the base sequence of the genes of the microorganisms 210 that underwent the PCR reaction.

[0153] The first information acquisition unit 20b acquires genetic sequence data of the microorganisms 210 from the sampling device 201, and acquires, as first information 21b, information related to the representative microorganisms 211. For example, if the representative microorganisms 211 are bacteria of the genus Streptococcus, the first information acquisition unit 20b acquires, as first information 21b, information related to the presence or abundance of bacteria of the genus Streptococcus from the genetic sequence data acquired from the sampling device 201.

[0154] The control unit 40b estimates the presence or absence or amount of target microorganisms 212 related to the presence of Streptococcus bacteria based on information 21b regarding Streptococcus bacteria, which is the representative microorganism 211 acquired by the first information acquisition unit 20b.

[0155] By selecting microorganisms that are easy to detect, such as those that are easy to cultivate and safe, as the representative microorganisms 211, it is possible to reduce the effort, time, cost, and safety risks. This microorganism analysis system 1b is particularly effective in situations where, for example, the target microorganisms 212 are dangerous microorganisms or where it is difficult to cultivate the target microorganisms 212. Although the case where the representative microorganisms 211 are Streptococcus bacteria has been described, the present invention is not limited to this.

[0156] In the microorganism analysis system 1b of variation 1D, even if the target microorganism 212 is difficult to measure, it is possible to measure the representative microorganism 211, which is easy to measure, and estimate the presence of the target microorganism 212 from the relationship between the two. Furthermore, in the microorganism analysis system 1b, the presence of the target microorganism 212 can be easily estimated by culturing or performing a PCR reaction on the representative microorganism 211 more safely and quickly than on the target microorganism 212.

[0157] (6-5) Modification 1E In the microorganism analysis system 1 shown in Fig. 1, the first information 21 may be operational status information regarding the operational status of the air conditioning apparatus 100 installed in the target space SP. The control unit 40 estimates the presence or absence or the amount of target microorganisms 212 based on the operational status information as the first information 21.

[0158] 1 , the first information 21 may be information relating to the correspondence between the operational status of the air conditioning apparatus 100 and the type and abundance of the representative microorganisms 211. The control unit 40 estimates the presence or absence or abundance of the target microorganisms 212 based on the information relating to the correspondence between the operational status of the air conditioning apparatus 100 and the type and abundance of the representative microorganisms 211 as the first information 21.

[0159] The operational status of the air conditioning apparatus 100 includes at least one of the operating time, operating mode, airflow rate, set temperature, set humidity, intake air temperature, and intake air humidity of the air conditioning apparatus 100, and the non-cleaning period of the air conditioning apparatus 100. For example, the air conditioning apparatus 100 may transmit operational status information relating to the operational status, and the first information acquisition unit 20 may acquire the operational status information from the air conditioning apparatus 100.

[0160] The balance of microorganisms present in the target space SP is affected by the operating status of the air conditioning apparatus 100, such as the non-cleaning period of the air conditioning apparatus 100, the temperature of the intake air, and the humidity of the intake air, and therefore can be corrected using operating status information to improve the accuracy of estimating the presence or absence or amount of target microorganisms 212. For example, if the non-cleaning period of the air conditioning apparatus 100 is short, the diversity of microorganisms (bacteria) is high, and if the non-cleaning period of the air conditioning apparatus 100 is long, the diversity of bacteria decreases.

[0161] In the microbial analysis system of Modification 1E, the presence of the target microorganism 212 can be easily estimated using information on the operational status of the air conditioning apparatus 100. Furthermore, the presence of the target microorganism 212 can be easily estimated by using information on the correspondence between the operational status of the air conditioning apparatus 100 and the type and abundance of the representative microorganism 211. Furthermore, even if the presence of the target microorganism 212 changes depending on the operational status of the air conditioning apparatus 100, the presence of the target microorganism 212 can be easily estimated.

[0162] (6-6) Modification 1F In the microorganism analysis system 1 shown in FIG. 1, the first information acquisition unit 20 may further acquire, as the first information 21, target space-related information of the target space SP.

[0163] The target space-related information includes at least one of the following information: the climate, weather, geographical features, latitude, longitude, and altitude of the location where the target space SP exists; the characteristics of the building that includes the target space SP; and the family composition of the residents of the target space SP. For example, the first information acquisition unit 20 may acquire the target space-related information via a network from a user terminal (not shown) owned by a resident of the target space SP in which the air conditioning device 100 is installed. The user terminal is, for example, a smartphone owned by the resident of the target space SP.

[0164] The control unit 40 estimates the presence or absence or the amount of the target microorganisms 212 using the information on the representative microorganisms 211 and the target space related information as the first information 21 .

[0165] In the microorganism analysis system of variant 1F, the presence of the target microorganism 212 in the target space SP can be easily estimated by further using the target space related information in addition to the information on the representative microorganism 211.

[0166] (6-7) Modification 1G In this embodiment, a case has been described in which the microorganisms 210 adhering to the filter 101 of the air conditioning device 100 installed in the target space SP are collected as a sample and analyzed, but the present invention is not limited to this. The microorganisms 210 may be collected from the air within the target space SP. Furthermore, the microorganisms 210 may be collected from the walls, ceiling, floor, etc. of the target space SP.

[0167] (6-8) Modification 1H The microbiological analysis system 1 shown in Fig. 1 may further include an air conditioning device 100, a sampling device 200, and an imaging device 300. The microbiological analysis system 1a shown in Fig. 11 may further include an air conditioning device 100. The microbiological analysis system 1b shown in Fig. 12 may further include an air conditioning device 100 and a sampling device 201.

[0168] (6-9) Although the embodiments of the present disclosure have been described above, it will be understood that various changes in form and details can be made without departing from the spirit and scope of the present disclosure as defined in the claims.

[0169] REFERENCE SIGNS LIST 1, 1a, 1b Microbial analysis system 10 Image analysis unit 20, 20a, 20b First information acquisition unit 21, 21a, 21b First information 30 Correspondence relationship information storage unit 31, 32 Correspondence relationship information 40, 40a, 40b Control unit 100 Air conditioning device 101 Filter 200, 201 Sampling device 210 Microorganism 211 Representative microorganism 212 Target microorganism 300 Imaging device 301 Photographed image

[0170] Special table 2020-529869 publication

Claims

1. A microbial analysis system (1, 1a, 1b) that estimates the presence / absence or abundance of a target microorganism (212) in a target space (SP), comprising: a first information acquisition unit (20, 20a, 20b) that acquires first information (21, 21a, 21b) regarding the target space, which is information different from the presence / absence and abundance of the target microorganism itself; and a control unit (40, 40a, 40b), wherein the control unit estimates the presence / absence or abundance of the target microorganism in the target space based on the first information.

2. The microbial analysis system of claim 1, wherein the first information is environmental information of the target space, and the environmental information is information regarding the amount of material collected from the target space, which is highly correlated with the amount of the target microorganism present.

3. The microbial analysis system of claim 1, wherein the first information includes either information about a representative microorganism (211) that is present in the target space simultaneously with the target microorganism, or information about a representative microorganism that suppresses the presence of the target microorganism, the information about the representative microorganism includes the presence or absence or the amount of the representative microorganism in the target space, and the control unit estimates the presence or absence or the amount of the target microorganism based on the information about the representative microorganism as the first information.

4. The microbial analysis system according to claim 3, wherein the target microorganisms include microorganisms (210) that adhere to a filter (101) that collects suspended solids in the target space.

5. The microbial analysis system according to claim 3 or 4, further comprising an image analysis unit (10) that identifies the microorganisms based on their shapes, and the representative microorganisms are of a size that can be identified by image analysis by the image analysis unit.

6. The microbial analysis system according to claim 3 or 4, wherein the representative microorganism is a microorganism that can be cultured or subjected to a PCR reaction more safely than the target microorganism in terms of a safety index indicated by a biosafety level (BSL), or a microorganism that can be cultured or subjected to a PCR reaction more quickly than the target microorganism.

7. A microbial analysis system as described in any one of claims 3 to 6, further comprising a correspondence information storage unit (30) that stores correspondence information (31) indicating the correspondence between the target microorganism and the representative microorganism, wherein the control unit further estimates the presence or absence or the amount of the target microorganism based on the correspondence information.

8. The microbial analysis system of claim 7, wherein the correspondence information storage unit acquires and stores the correspondence information (32), which is the result of learning by a machine learning machine that learns the correspondence between the target microorganism and the representative microorganism, and the control unit estimates the presence or absence or abundance of the target microorganism from the presence or absence or abundance of the representative microorganism based on the results of the correspondence information.

9. The microorganism analysis system according to any one of claims 3 to 8, wherein the representative microorganism is one or more selected from the group consisting of fungi, bacteria, pollen and viruses.

10. The microorganism analysis system of claim 7 or 8, wherein the correspondence information includes at least one correspondence between the target microorganism and the representative microorganism, in which the target microorganism and the representative microorganism are either a first fungus and a second fungus, a first bacterium and a second bacterium, a first pollen and a second pollen, or a first virus and a second virus.

11. The microorganism analysis system of claim 7 or 8, wherein the correspondence information includes at least one correspondence in which, when the target microorganism is a fungus, the representative microorganism is any one of bacteria, pollen, and viruses; when the target microorganism is a bacterium, the representative microorganism is any one of fungi, pollen, and viruses; when the target microorganism is pollen, the representative microorganism is any one of fungi, bacteria, and viruses; and when the target microorganism is a virus, the representative microorganism is any one of fungi, bacteria, and pollen.

12. The fungus may be any of the following fungi: Aspergillus, Nigrospora, Cladosporium, Fusarium, Alternaria, Schizophyllum, Penicillium, Epicoccum, Hortaea, Eupenidiella, Chaetomium, Trametes, Pseudopithomyces, Toki Toxicocladosporium fungi, Peniophora fungi, Talaromyces fungi, Didymella fungi, Pleurotus fungi, Wallemia fungi, Curvularia fungi, Loweporus fungi, Periconia fungi, Candida fungi, Gibberella fungi, The genus Gibberella, the genus Auricularia, the genus Malassezia, the genus Naganishia, the genus Neurospora, the genus Ganoderma, the genus Engyodontium, the genus Ustilaginoidea, the genus Peroneutypa, and the genus Flammulina. Fungi, Filobasidium fungi, Cercospora fungi, Hannaella fungi, Coprinopsis fungi, Irpex fungi, Fungi of the genus Phlebia, fungi of the genus Pyronema, fungi of the genus Microascus, fungi of the genus Sterigmatomyces, fungi of the genus Trichosporon,Spissiomyces, Botrytis, Rhodotorula, Stachybotrys, Fibroporia, Bjerkandera, Phanerochete, Emmia, Coprinellus, Trexpora The microbial analysis system according to any one of claims 9 to 11, comprising one or more fungi selected from the group consisting of fungi of the genus A. hispora, fungi of the genus Acremonium, fungi of the genus Aureobasidium, fungi of the genus Lopharia, fungi of the genus Heterochaete, fungi of the genus Cutaneotrichosporon, fungi of the genus Aplosporella, and fungi of the genus Eutypella.

13. The microbial analysis system according to any one of claims 9 to 11, wherein the bacteria include one or more species selected from the group consisting of Streptococcus, Acinetobacter, Alcaligenaceae, Pseudomonas, Paracoccus, Sphingomonas, Corynebacterium, Staphylococcus, Haemophilus, parvum, Clostridium botulinum, and Chlamydia psittacosis.

14. The microbial analysis system according to any one of claims 9 to 11, wherein the pollen comprises one or more species selected from the group consisting of Humulus pollen, Boehmeria pollen, Acalypha pollen, Magnolia pollen, Artemisia pollen, Cucumis pollen, Astragalus pollen, Pouzolzia pollen, Osmanthus pollen, Triticum pollen, Citrullus pollen, Podocarpus pollen, Digitaria pollen, Funaria pollen, Solanum pollen, Allium pollen, and Glycine pollen.

15. The microbiological analysis system according to any one of claims 9 to 11, wherein the virus includes one or more types selected from the group consisting of influenza virus, monkeypox virus, rabies virus, dengue virus, and Japanese encephalitis virus.

16. The relationship between the target microorganism and the representative microorganism is such that the target microorganism, which is any one of the fungi of the genus Gibberella, Nigrospora, Fusarium, Cladosporium, Epicoccum, Periconia, Alternaria, Penicillium, Filobasidium, and Pleurotus, and the representative microorganism, which is a fungus of the genus Aspergillus, have a negative correlation; There is a positive correlation between the target microorganism which is a fungus of the genus Penicillium or a fungus of the genus Nigrospora and the representative microorganism which is pollen of the genus Boehmeria; There is a positive correlation between the target microorganism which is a bacterium of the genus Corynebacterium or a fungus of the genus Alternaria and the representative microorganism which is pollen of Humulus; There is a positive correlation between the target microorganism which is a bacterium of the genus Enhydrobacter and the representative microorganism which is any of a fungus of the genus Tramaetes, a fungus of the genus Chaetomiun or pollen of the genus Boehmeria; Among the target microorganisms or the representative microorganisms, 16. The microbial analysis system according to claim 3, wherein Staphylococcus bacteria, Gibberella fungi, Cladosporium fungi, Cercospora fungi, and Curvularia fungi are positively correlated with each other, and Streptococcus bacteria, Haemophilus bacteria, Solanum pollen, and Cucumis pollen are positively correlated with each other.

17. The microbial analysis system according to claim 7, wherein the control unit creates the correspondence information through machine learning.

18. The microbial analysis system of claim 1, wherein the first information is operational status information regarding the operational status of an air conditioning unit (100) installed in the target space, and the control unit estimates the presence or absence or the amount of the target microorganism based on the operational status information as the first information.

19. The microbial analysis system of claim 18, wherein the first information is information relating to the correspondence between the operational status of the air conditioning device and the type and abundance of the representative microorganism, and the control unit estimates the presence or absence or the abundance of the target microorganism based on the first information, which is information relating to the correspondence between the operational status of the air conditioning device and the type and abundance of the representative microorganism.

20. A microbial analysis system as described in claim 18 or 19, wherein the operational status of the air conditioning device includes at least one of the operating time, operating mode, air volume, set temperature, set humidity, intake air temperature, and intake air humidity of the air conditioning device, and a non-cleaning period of the air conditioning device.

21. A microbial analysis system as described in claims 3 to 18, wherein the first information is target space-related information of the target space, the target space-related information including at least one of information on the climate, weather, geographical features, latitude, longitude, and altitude of the location where the target space is located, characteristics of the building containing the target space, and family composition of the residents in the target space, and the control unit further uses the target space-related information as the first information to estimate the presence or absence or amount of the target microorganism.

22. A microbial analysis method for estimating the presence / absence or abundance of a target microorganism in a target space, comprising: estimating the presence / absence or abundance of a target microorganism in the target space based on first information regarding the target space, which is information different from the presence / absence and abundance of the target microorganism itself.

Images