Application of bacteroides faecalis as target spot in detection and promotion of hot habit taking

Abstract

The invention provides application of bacteroides faecalis as a target spot in detection and promotion of hot habit. Through systematic metagenomics analysis on excrement samples of hot-area crowds and warm-area control crowds and through difference comparison and verification research, the characteristic microbial marker bacteroides faecalis significantly related to the hot habit state is identified for the first time. The method can accurately reflect the adaptive state of an individual to the thermal environment, and can be used for non-invasive evaluation or auxiliary detection of the thermal habit degree. Based on the marker, the probability that an individual is in a hot habit state or a non-habit state can be quantitatively evaluated, and a new biomarker detection method is provided for objective diagnosis of hot habit.

Description

TECHNICAL FIELD

[0001] The present application belongs to the field of biological detection and medicine, and relates to the application of Bacteroides cacae as a heat acclimatization detection marker and a heat acclimatization promoter. BACKGROUND

[0002] Heat acclimatization refers to a series of adaptive responses of the body to repeated heat exposure. It is characterized by the gradual improvement of the body's reflex regulation function to heat and the achievement of a new level of various physiological functions. Heat acclimatization is crucial for people working in high-temperature environments, such as soldiers, construction workers, and firefighters, and can effectively reduce the risk of heat-related diseases such as heat stroke and heat stroke.

[0003] Currently, the main method for determining heat acclimatization is to monitor physiological indicators such as heart rate and rectal temperature. For example, under the condition of fixed environmental standards and training intensity, if the heart rate exceeds 150 beats per minute and the rectal temperature exceeds 38.5°C for 60 minutes, it indicates poor heat tolerance and the need for heat acclimatization training. Heat tolerance testing can also be used to determine whether the heat acclimatization standard is met, i.e., in a closed space with a temperature of 40°C and a relative humidity of 40%, the subject pedals at a speed of 5 kilometers per hour for 2 hours. If the core temperature exceeds 38.5°C and the heart rate exceeds 150 beats per minute during this process, it indicates that the subject has not achieved good heat acclimatization or has poor heat tolerance. However, these traditional detection methods have certain limitations. On the one hand, the detection process is relatively cumbersome and requires specific equipment and environment. On the other hand, these physiological indicators are easily influenced by various factors such as individual exercise state and psychological factors, resulting in the need for improvement in the accuracy and reliability of the detection results. Therefore, it is of great practical significance to find a more accurate, convenient, and specific heat acclimatization detection marker.

[0004] Bacteroides spp. belongs to the domain Bacteria, phylum Bacteroidetes, class Bacteroidia, order Bacteroidales, family Bacteroidaceae, and genus Bacteroides. This genus includes several important species closely related to human health, including Bacteroides fragilis, Bacteroides vulgatus, and Bacteroides thetaiotaomicron.

[0005] Morphologically, B. caccae is a gram-negative, non-spore-forming, obligate anaerobic bacillus. The size of the bacterial cell is usually 0.5-0.8 x 1.5-4.5 microns, and the cell appears rod-shaped or coccobacillary. The bacteria can exist singly or in pairs or short chains. The bacteria do not form spores, lack flagella, and are non-motile. When cultured on anaerobic blood agar plates, the bacteria form characteristic colonies that are grayish white, smooth, centrally raised, and have a neat edge. The growth temperature range of the bacteria is 25-45°C, and the optimal growth temperature is 37°C. The optimal pH value is 6.8-7.2. Notably, the bacteria have a highly developed polysaccharide-degrading enzyme system, which enables them to efficiently use various complex carbohydrates as energy sources.

[0006] In terms of ecological distribution, B. caccae mainly colonizes the gastrointestinal system of humans and mammals, especially the colon and rectum, and constitutes one of the most abundant obligate anaerobic bacterial groups in the intestinal microbial community. The density of B. caccae in the adult intestinal tract can be as high as 10¹¹ CFU / g of feces. In addition, the bacteria are also distributed in small amounts in the oral cavity, vagina, and other mucosal surfaces. In the unique anaerobic microenvironment of the intestinal tract, B. caccae establishes and maintains a stable and precise symbiotic relationship with the host.

[0007] B. caccae plays multiple key roles in maintaining human physiological balance: first, in terms of nutritional metabolism, the bacteria effectively participate in the degradation of complex carbohydrates by secreting a variety of polysaccharide-degrading enzymes, producing a variety of short-chain fatty acids including acetic acid, propionic acid, and butyric acid. These metabolic products not only provide an important energy source for intestinal epithelial cells but also have the function of regulating intestinal pH; second, in terms of immune regulation, the unique polysaccharide A (PSA) component of the cell wall can precisely regulate the host immune system by promoting the differentiation and maturation of regulatory T cells, effectively maintaining intestinal immune homeostasis; third, in terms of intestinal barrier maintenance, the bacteria inhibit the colonization of pathogenic microorganisms through competitive occupation and secrete a variety of antibacterial active substances, thereby synergistically maintaining the balance of the intestinal microecology; and finally, in terms of metabolic regulation, B. caccae actively participates in the biological transformation of bile acids, deeply affecting the lipid metabolism and energy balance of the host, and its abundance is closely related to the occurrence and development of metabolic diseases such as obesity and type 2 diabetes. In summary, as a core member of the intestinal microbiome, B. caccae has irreplaceable importance in maintaining human health and preventing diseases.

[0008] The intestinal microbiota is a large and complex collection of microorganisms that contributes to the health of the body by regulating various physiological functions, playing an important role in energy metabolism, inflammation regulation, immune response, etc. In addition, the dynamic changes of the intestinal flora endow animals with the ability to adjust the heat production under heat stress, which suggests that there may be a potential correlation between the intestinal flora and the heat tolerance. Metabolomics, as a discipline that studies the change rules of metabolic products after the body is disturbed by environmental or self factors, has been widely used in the field of molecular biology due to its high throughput and high sensitivity. The pathological and physiological processes of the body are studied through the change rules of metabolites, and the complex changes of metabolic pathways are described.

[0009] The differences in the microbial distribution of the intestine of the heat acclimatization population and the population in other areas have not been reported so far, and exploring the bacterial markers closely related to the heat acclimatization state of the human body has a positive significance for the detection and state promotion of heat acclimatization. SUMMARY

[0010] The present application is directed to the above problems, and through a large amount of research and experiments, it is found that Bacteroides stercoris is closely related to the heat acclimatization state of the human body, and is expected to be developed as a new heat acclimatization detection marker.

[0011] The present application aims to provide a heat acclimatization marker based on the intestinal microbiome, and also provides a new application of Bacteroides stercoris; the second object of the present application is to provide the application of Bacteroides stercoris as a target in the detection of heat acclimatization, and specifically provides a corresponding detection kit; the third object of the present application is to provide a method for detecting Bacteroides stercoris by using a heat acclimatization detection kit, and the heat acclimatization state is evaluated by detecting the abundance of Bacteroides stercoris; the fourth object of the present application is to provide the application of Bacteroides stercoris in promoting heat acclimatization, and to provide a heat acclimatization promoter taking Bacteroides stercoris as an active ingredient.

[0012] The research idea of the present application is as follows: through systematic microbiome 16S rRNA sequencing of the fecal samples of the heat zone population and the control population in the warm zone, through differential comparison and verification research, the characteristic microbial marker Bacteroides stercoris significantly related to the heat acclimatization state is first identified. These markers can accurately reflect the adaptation state of individuals to the heat environment, and can be used for non-invasively evaluating or assisting in detecting the degree of heat acclimatization. Based on the marker, the probability of an individual being in a heat acclimatization state or a non-acclimatization state can be quantitatively evaluated, and a new biomarker detection method for the objective diagnosis of heat acclimatization is provided.

[0013] Based on the above research, the technical scheme of the present application is as follows:

[0014] In a first aspect, the application provides use of B. caccae as a marker for detecting heat acclimatization. Specifically, the application provides use of a reagent for detecting B. caccae in preparation of a kit for detecting heat acclimatization.

[0015] Preferably, the reagent for detecting B. caccae is a reagent for detecting abundance of B. caccae in a fecal sample, and the kit comprises the reagent for detecting abundance of B. caccae.

[0016] Further, the reagent for detecting abundance of B. caccae is selected from a PCR detection reagent, a genomic sequencing reagent, or a combination of the two, preferably the combination of the two.

[0017] The PCR detection reagent comprises primers for amplifying B. caccae based on 16S rRNA, and the primer sequences are shown below; and the genomic sequencing reagent is selected from a chip for high-throughput sequencing using a sequencing platform.

[0018]

[0019] In a second aspect, the application provides a kit for detecting heat acclimatization, comprising a PCR detection reagent and a genomic sequencing chip. The PCR detection reagent comprises a primer system and an amplification system, and the primer sequences of the primer system are shown in SEQ ID NO. 1-2; and the genomic sequencing chip is a chip for 16S rRNA high-throughput sequencing.

[0020] In a third aspect, the application provides a method for detecting B. caccae using the kit for detecting heat acclimatization, characterized by comprising the following steps:

[0021] (1) After extracting DNA from a fecal sample to be detected and detecting the integrity of the DNA, amplifying based on bacterial 16S rRNA and purifying;

[0022] (2) Sequencing the amplification product, trimming and filtering the adapter and primers, optimizing the sequence by aligning with the paired-end sequence, and clustering the optimized sequence into amplicon sequence variants (ASV) at a sequence similarity of 97%;

[0023] (3) Classifying and annotating each ASV according to the 16S rRNA gene Sliva database (confidence threshold of 0.7); then determining the similarity of microbial communities in different samples by calculating the sparse curve, alpha diversity index, and beta diversity index, and principal coordinate analysis; using multivariate permutation variance analysis test to evaluate statistical significance, and using linear discriminant analysis effect size to identify significantly different bacterial taxa between groups and construct a biological co-occurrence network to determine the internal community relationship between samples, and further determine the abundance of B. caccae.

[0024] The application adopts the above method, and the high-abundance marker bacteria genus in the heat acclimatization population is screened in advance, and the feasibility is verified, and the results show that the abundance of Bacteroides caccae in the intestinal tract can be detected to screen whether the human body belongs to the heat acclimatization state.

[0025] In the fourth aspect of the application, the application of Bacteroides caccae in preparing a heat acclimatization promoter is provided. Since the abundance of Bacteroides caccae in the heat acclimatization population is high, during the heat acclimatization training process, the human body can be promoted to reach the heat acclimatization standard or improve the adaptability in the high-temperature environment by taking the Bacteroides caccae live bacterial body preparation.

[0026] In the fifth aspect of the application, a heat acclimatization promoter is provided, which comprises an active component and a pharmaceutically acceptable adjuvant, the active component is Bacteroides caccae live bacterial body, and the adjuvant is selected from a protective agent, a carrier or an activator that maintains the activity of the bacterial body.

[0027] For example, the adjuvant can be selected from a sugar (trehalose), gelatin, glycerol, mannitol or plant starch (corn starch, potato starch). The sugar helps to stabilize the cell membrane and resist freeze-drying damage; the gelatin embeds the bacterial body and delays the release of gastric acid; the glycerol and mannitol act as cryoprotective agents to protect the bacterial body during freeze-drying and improve the flowability of the preparation; the plant starch

[0028] Low cost and easy degradation are common pharmaceutical adjuvants.

[0029] The beneficial guarantees and effects of the application are as follows:

[0030] (1) reasonable design

[0031] This part investigates the composition and structural characteristics of the intestinal flora of the heat zone and the warm zone population, analyzes the differences between the intestinal flora of different heat zone populations and the warm zone population, and explores the common difference flora, and the results show that the intestinal flora of the heat zone population and the warm zone population has different composition and development expression characteristics, which indicates that the intestinal flora of the heat zone population and the warm zone population has different composition and development expression characteristics, and the different flora between different heat zone populations has a variety of same beneficial bacteria classification groups, which indicates that the microorganisms have changed in the heat environment tolerance, and even the same change characteristics exist in different heat environments.

[0032] (2) higher detection accuracy

[0033] Existing heat acclimatization detection techniques often rely on indirect physiological indicators such as body temperature, heart rate, blood pressure, etc. These indicators are easily disturbed by various factors, such as individual's basic health status, exercise state, emotional fluctuations, etc., resulting in large errors and uncertainties in the detection results. There is a direct and stable correlation between B. caccae and heat acclimatization status. Heat acclimatization process will cause specific changes in the intestinal microecological environment of the human body, and the abundance and activity of B. caccae will change predictably, which can accurately reflect the degree of heat acclimatization. By detecting B. caccae-related indicators, the heat acclimatization status can be more accurately evaluated, greatly improving the accuracy and reliability of the detection results.

[0034] (3) Stronger specificity

[0035] Some of the heat acclimatization detection markers currently used are not specific to heat acclimatization status. They may also change in other physiological or pathological processes. For example, certain inflammatory factors may also rise in cases of infection, trauma, etc., making it difficult to accurately distinguish between changes caused by heat acclimatization or other factors. B. caccae as a heat acclimatization detection marker has high specificity. It mainly responds to intestinal microecological adjustments during heat stress and heat acclimatization, and its changes are relatively small under other non-heat-related physiological or pathological conditions. Therefore, using B. caccae as a marker for detection can more accurately determine whether the body is in a heat acclimatization state, reducing interference from other factors.

[0036] (4) More convenient detection method

[0037] Some existing heat acclimatization detection techniques require complex equipment and professional operators, such as using large physiological monitoring instruments for long-term continuous monitoring, or performing invasive blood and tissue sample collection. These methods not only have complicated operations, but also bring great inconvenience and pain to the subjects. The present invention uses B. caccae as a marker, and the detection sample can be non-invasive samples such as feces, with a simple and painless collection process, without the need for special equipment and professional skills, and the subjects can complete the sample collection themselves. In addition, detection techniques for B. caccae, such as molecular biology-based detection methods, are relatively simple to operate and can obtain detection results in a short time, greatly improving the convenience and efficiency of detection.

[0038] (5) Better cost-effectiveness

[0039] The existing heat habit detection technology usually involves expensive equipment purchase, maintenance cost and professional training cost, resulting in high detection cost. This limits the wide application of heat habit detection to some extent, especially in resource-limited areas or large-scale population screening. The detection method of the present application takes B. caccae as a marker, and the required reagents and equipment are relatively inexpensive, the detection process is simple, and no complex instruments and professional technicians are required. This greatly reduces the detection cost, improves the cost performance of detection, is more suitable for large-scale popularization and application, and can provide heat habit detection services for more people.

[0040] (6) wider application range

[0041] The existing heat habit detection technology mainly focuses on specific professional groups, such as high-temperature workers, athletes, etc., and the application scene is relatively limited. The present application uses B. caccae as a marker, and due to the convenience and low cost of the detection method, it can not only be applied to the heat habit detection of the above-mentioned professional groups, but also be expanded to a wider field. For example, in military training, the heat habit state of soldiers can be quickly and accurately evaluated to provide a scientific basis for adjusting the training plan; in the general population, it can also be used to evaluate the adaptability of individuals in hot environments and guide people to take reasonable protective measures to prevent the occurrence of heat-related diseases. Therefore, the present application has a wider application prospect and social value. BRIEF DESCRIPTION OF DRAWINGS

[0042] The present disclosure will be further described below in conjunction with the drawings, wherein these displays are only for illustrating the embodiments of the present disclosure, but not for limiting the scope of the present disclosure.

[0043] Figure 1 A flow chart of bacterial marker screening is shown.

[0044] Figure 2 Dilution curves of sequencing data of the detection groups in Guangdong Chaozhou (CZ group), Guangdong Yangjiang (YJ group), Shanghai (SH group: high-temperature workers) and warm area group (TA group) in Example 1 of Example 1 are shown. A: CZ group; B: YJ group; C: SH group; D: TA group.

[0045] Figure 3 The results of the alpha diversity analysis of the bacterial flora in Example 1 are shown. A: evaluation of alpha diversity at ASV level based on Chao1 index; B: evaluation of alpha diversity at ASV level based on Shannon index.

[0046] Figure 4The results of the beta diversity analysis of the flora in Example 1 are shown, A: PCoA analysis based on Bray-Curtis distance (2D+3D); B: non-metric multidimensional scaling analysis based on Bray-Curtis distance (2D+3D).

[0047] Figure 5 The door classification level composition analysis is shown.

[0048] Figure 6 The verification results of the 6 hot zone individuals in Example 2 are shown.

[0049] Figure 7 The verification results of the 2 warm zone individuals in Example 2 are shown. DETAILED DESCRIPTION

[0050] The following examples and experimental examples further illustrate the present application and are not to be construed as limiting it. The examples do not include detailed descriptions of conventional methods, such as PCR methods. Such methods are well known to those of ordinary skill in the art and are described in many publications.

[0051] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. In addition, any method and material similar or equivalent to those described herein can be used in the practice of the present application, and the preferred methods and materials are presented by way of example only.

[0052] I. Screening and detection methods of heat acclimatization marker bacteria

[0053] The screening process of heat acclimatization marker bacteria and the detection process after screening are basically the same, and the flow chart is shown in Figure 1 .

[0054] 1. Materials and methods:

[0055] 1.1 Test materials

[0056] 1.1.1 Sample collection

[0057] After heat acclimatization, fresh fecal samples were collected by rectal swab. Before sampling, the subject was required to fast for 12 hours. The feces were collected in sterile disposable tubes and stored in a -80°C freezer.

[0058] 1.2 Experimental methods

[0059] 1.2.1 DNA extraction from samples

[0060] DNA was extracted according to the E.Z.N.A.® soil DNA Kit kit instruction. The DNA concentration and purity of each sample were detected by micro-spectrophotometer, and the sample DNA integrity was evaluated by 1% agarose gel electrophoresis. The samples meeting the quality requirements (OD260 / 280 = 1.8-2.0, no obvious degradation of DNA) were used for subsequent use.

[0061] 1.2.2 PCR amplification

[0062] 16S rRNA is widely present in bacteria, and has the advantages of good evolutionary conservation, suitable analysis length and easy PCR amplification, and becomes a standard identification sequence for bacterial molecular identification. The V3-V4 region was amplified by PCR using an ABI GeneAmp 9700 PCR instrument, and the sequencing primer sequences are shown in Table 1. The PCR amplification conditions are as follows: 95°C pre-denaturation for 3 min; 30 cycles, each cycle including 95°C denaturation for 30 s, 55°C annealing for 30 s, 72°C extension for 45 s; 72°C extension for 10 min, 10°C holding to the end, and the reaction system is shown in Table 2. The PCR product was extracted using a gel kit, the target band was recovered and purified, and the recovered product was quantified using a Quantus fluorometer.

[0063] Table 1 Primer sequence

[0064]

[0065] Table 2 PCR amplification 20 μL reaction system

[0066]

[0067] 1.2.3 Sequencing analysis

[0068] Paired-end sequencing was performed on Illumina MiSeq PE300 platform following the standard protocol of Majorbio Bio-Pharm Technology Co. Ltd with equimolar purified amplicons. The raw FASTQ files were trimmed and filtered for adapters and primers using Cutadapt (Version 1.9.1). Further, the paired-end sequences were aligned using the DADA2 package (Version 1.22.0) and subsequent quality filtering and removal of chimeras were performed. The optimized sequences were clustered into amplicon sequence variants (ASVs) at 97% sequence similarity. Each ASV was taxonomically analyzed and annotated to species according to the 16S rRNA gene Sliva database (Version SSU 138.1) with a confidence threshold of 0.7. Sparse curves, a-diversity indices and b-diversity indices were calculated using the MicrobiomeAnalyst cloud platform. Principal coordinate analysis (PCoA) was performed using the Vegan package (Version 2.5.7) to determine the similarity of microbial communities in different samples. Permutational Multivariate Analysis of Variance (PERMANOVA) test was used to assess statistical significance. Linear discriminant analysis effect size (LEfSe)

[24] was used to identify significantly different bacterial taxa between groups. The microbial co-occurrence network was constructed using the ggClusterNet package (Version 0.1.0) and Gephi (Version 0.9.2) to explore the internal community relationships between samples.

[0069] 1.2.4 Statistical methods

[0070] Statistical analyses of study population characteristics and questionnaire information were performed using IBM SPSS Statistics (Version 26.0), GraphPad Prism (Version 8.3), and R statistical package (Version 4.2.2). Data were presented as mean ± standard deviation (Mean ± SD). Sequencing data were analyzed in R (Version 4.2.2) and visualized at all species levels in the MicrobiomeAnalyst cloud platform. Independent sample t-test was used for normally distributed, homoscedastic data, and Mann-Whitney test was used for non-normally distributed, heteroscedastic data between two groups. Correlation analysis was analyzed using Spearman correlation. Statistical significant difference was considered when P < 0.05 in the test analysis.

[0071] 2. Abundance comparison to determine individual status

[0072] The present application quantifies the abundance of specific heat acclimatization marker microorganisms in an individual's fecal sample and compares it to a control group to accurately determine the individual's heat acclimatization status. The control group includes fecal samples from multiple individuals known to be in a heat acclimatized or unacclimatized state, providing a reliable reference for abundance comparison. These heat acclimatization marker microorganisms, which are indicative, are ultimately determined by the inventors based on in-depth difference analysis of the gut microbial community in fecal samples from heat acclimatized and unacclimatized groups, and through rigorous verification of large-scale known state samples. Specific embodiments

[0073] Example 1: Screening of heat acclimatization marker bacteria

[0074] A total of 134 subjects were included in this study, including 44 people from Chaozhou, Guangdong (CZ group), 21 people from Yangjiang, Guangdong (YJ group), 10 people from Shanghai (SH group: high-temperature operation population), and 59 people from the warm area group (TA group). The local temperature during sample collection is shown in Table 3. Three comparison groups were set up: heat zone 1 group (CZ group vs. TA group), heat zone 2 group (YJ group vs. TA group), and heat environment group (SH group vs. TA group). All study subjects were of Han nationality, with an average age of 22.6 ± 2.9 years, an average height of 179.7 ± 4.2 cm, an average weight of 72.9 ± 5.9 kg, and an average BMI of 22.6 ± 1.6 kg / m 2 The demographic characteristics of the study subjects in each group are shown in Table 4. The results showed that there were no significant differences in age, height, weight, and BMI statistics among the groups (P > 0.05). In general, the sequencing data of each sample in the above-mentioned control group was downloaded, and a heat acclimatization reference gene set was constructed.

[0075] Table 3: Meteorological data

[0076]

[0077] The average temperature of the working environment was 41℃ and the average temperature of the resting environment was 9℃ in the SH group.

[0078] Table 4 Demographic data and estimated nutrient intake of the study subjects

[0079]

[0080] Quantitative data were expressed as mean (SD) and categorical data were expressed as count (percentage). The t-test was used to compare age, weight, height, and BMI. P1: comparison between the hot zone group and the warm zone group; P2: comparison between the hot zone group and the rapid-advance hot zone group; P3: comparison between the warm zone group and the rapid-advance hot zone group.

[0081] 1.1 Quality control of sequencing data

[0082] To explore the differences in the characteristics of intestinal flora between the hot zone and the warm zone, 16S rRNA high-throughput sequencing of the fecal samples of 134 study subjects from the four groups was performed. A total of 3639413 reads were obtained from the sequencing results of all samples. The average reads of the CZ group was 30568 (±5645 SD), the average reads of the YJ group was 31056 (±6708 SD), the average reads of the SH group was 30771 (±2627 SD), and the average reads of the TA group was 30994 (±4989 SD). The dilution curve of the sequencing data of each group is shown in Figure 2 The results show that with the increase of sequencing depth, the end tends to be stable, and increasing the sequencing depth cannot bring more meaningful results. The data meet the requirements of analysis.

[0083] 1.2 Analysis of intestinal diversity

[0084] To objectively evaluate the biological diversity of intestinal flora, α diversity and β diversity were used to assess the species richness and evenness within a specific range. In the α diversity analysis, the Chao1 index was used to evaluate the richness of the flora, and the Shannon index was used to evaluate the richness and evenness of the flora. As shown in Figure 3 The box plot based on the Chao1 index and the Shannon index, the α diversity of the CZ group (P=0.0001) and the SH group (P=0.003) was significantly higher than that of the TA group, indicating that the hot zone group had higher community richness. The Shannon index of the YJ group was slightly higher than that of the warm zone group, but there was no statistical difference (P>0.05).

[0085] The PCoA analysis results based on the Bray-Curtis distance are shown in Figure 4(A, B) showed that sample points in the hot zone 1 group (P = 0.001) and the hot zone 2 group (P = 0.001) were obviously clustered within each group, and there was a significant distinction between each group, although the YJ group and the TA group were not statistically different (P = 0.001) and the hot zone 2 group was statistically different (P = 0.001). The visualization plot based on Non-Metric Multi-Dimensional Scaling (NMDS) showed that sample points of each group were significantly clustered and evenly distributed, as shown in (C, D), and each group was statistically different. The beta diversity results suggested that sample points of each group were significantly clustered and there was a significant cluster discreteness between groups. Figure 4 Figure 5

[0086] 1.3 Analysis of intestinal flora composition

[0087] At the level of phylum classification, a total of 8 phylum classifications were found, among which the abundance of Firmicutes, Bacteroidota, Actinobacteriota and Proteobacteria occupied the main advantage. The composition analysis at the level of phylum classification is shown in (A, B). Figure 5 ​​As shown, the relative abundance of Firmicutes (74.0%) and Bacteroidota (5.3%) in the CZ group was significantly higher than that in the TA group, but the relative abundance of Actinobacteriota (13.1%) and Proteobacteria (7.5%) was lower than that in the TA group. The relative abundance of Actinobacteriota (18.1%), Bacteroidota (8.4%), and Proteobacteria (9.3%) in the YJ group was higher than that in the TA group, while the relative abundance of Firmicutes (64.1%) was lower than that in the TA group. The relative abundance of Bacteroidota (35.0%) in the SH group was higher than that in the TA group, while the relative abundance of Firmicutes (57.0%), Actinobacteriota (5.8%), and Proteobacteria (1.8%) was lower than that in the TA group. At the class level, the abundance of Clostridia, Bacteroidia, and Negativicutes was dominant, and the relative abundance of Bacteroidia and Negativicutes in the CZ, YJ, and SH groups was higher than that in the TA group. At the order level, the abundance of Lachnospirales (35.7%), Oscillospirales (21.2%), Bacteroidales (15.6%), and Bifidobacteriales (13.5%) was dominant, and the relative abundance of Oscillospirales, Veillonellales_Selenomonadales, and Bacteroidales in the CZ group was higher than that in the TA group; the relative abundance of Bifidobacteriales in the YJ group was higher than that in the TA group; and the relative abundance of Bacteroidales and Veillonellales_Selenomonadales in the SH group was also higher than that in the TA group. At the family level, the abundance of Lachnospiraceae (35.0%) and Ruminococcaceae (16.4%) was dominant. At the genus level, the relative abundance of Faecalibacterium, Bacteroides, Agathobacter, Lachnoclostridium, and Roseburia in the CZ, YJ, and SH groups was significantly higher than that in the TA group, and the relative abundance of the other four genera was more than twice that in the TA group, except for Lachnoclostridium.At the species level, the relative abundance of Faecalibacterium_prausnitzii, Bacteroides_plebeius and Bacteroides_vulgatus in CZ group, YJ group and SH group were significantly higher than that in TA group, while the relative abundance of Megamonas_funiformis, Prevotella_9_copri, Roseburia_inulinivorans and Bacteroides_coprocola in CZ group and SH group were higher than that in TA group.

[0088] 1.4 Comparison of different groups of bacteria

[0089] In order to find the characteristic difference markers of intestinal flora between groups, more detailed data analysis was carried out at the genus and species classification levels, as shown in Table 5:

[0090] Table 5 Common difference species of hot area group and warm area group at genus and species classification levels

[0091]

[0092] Note: Lachnospiraceae_ND3007*: Lachnospiraceae_ND3007_group; Lachnospiraceae_NK4A136*: Lachnospiraceae_NK4A136_group_bacterium.

[0093] The results showed that Bacteroides spp. had expression difference between the three hot area groups and the warm area group.

[0094] Case 2

[0095] In order to verify that the species markers determined in case 1 can be used as a marker for colorectal cancer, the species and functional composition of the fecal samples of 4 hot area individuals and 2 warm area individuals were analyzed. Among them, the DNA sequencing and gene abundance analysis in feces were carried out according to the sequencing instructions of the selected sequencing platform and the above steps.

[0096] The results showed that, compared with the intestinal flora polymorphism results of 2 warm area individuals (TA1 and TA2), Figure 7 , the abundance of Bacteroides spp. in the intestinal flora polymorphism results of 4 hot area individuals was greatly improved. Figure 6

[0097] ​The present application accurately determines the heat acclimatization state of an individual by quantifying the abundance of specific heat acclimatization marker microorganisms in the individual's fecal sample and comparing it to a control group. The control group contains fecal samples from multiple individuals known to be in a heat acclimatized or unacclimatized state, providing a reliable reference for abundance comparison. These heat acclimatization marker microorganisms, which are indicative, are ultimately determined by the inventors based on in-depth differential analysis of the gut microbial communities in the fecal samples of the heat acclimatized and unacclimatized groups, and through rigorous validation of large-scale known state samples.

[0098] The unexplained part involved in the present application is the same as or realized by using the prior art. The applicant declares that the present application is illustrated by the above detailed method, but the present application is not limited to the above detailed method, that is, it does not mean that the present application must rely on the above detailed method to be implemented. It should be understood by those skilled in the art that any improvement of the present application, equivalent replacement of each raw material of the product of the present application, addition of auxiliary ingredients, selection of specific methods, etc. fall within the protection scope and disclosure scope of the present application.

Claims

1. Application of Bacteroides cacae as a marker in detection of heat acclimatization.

2. Application of a reagent for detecting Bacteroides cacae in preparation of a heat acclimatization detection kit.

3. Use according to claim 2, characterized in that, The reagent for detecting Bacteroides cacae is a reagent for detecting the abundance of Bacteroides cacae in a fecal sample, and the kit comprises the reagent for detecting the abundance of Bacteroides cacae.

4. Use according to claim 1, characterized in that, The reagent for detecting the abundance of Bacteroides cacae is selected from a PCR detection reagent, a genomic sequencing reagent, or a combination of the two.

5. Use according to claim 4, characterized in that, The PCR detection reagent comprises primers for amplifying the 16S rRNA of Bacteroides cacae, and the primer sequences are shown in SEQ ID NO. 1 and 2; and the genomic sequencing reagent is selected from a chip for high-throughput sequencing of 16S rRNA using a sequencing platform.

6. A heat acclimation test kit, characterized in that, The kit comprises a PCR detection reagent comprising a primer system and an amplification system, and the primer sequences of the primer system are shown in SEQ ID NO. 1-2.

7. The heat stress detection kit of claim 6, wherein, The genomic sequencing chip is a chip for high-throughput sequencing of 16S rRNA.

8. A method for detecting B. caccae using the heat acclimation detection kit according to claim 6 or 7, characterized in that, The kit comprises the following steps: (1) After extracting DNA from the fecal sample to be detected and detecting the integrity thereof, amplifying based on bacterial 16S rRNA and purifying; (2) Sequencing the amplification product, trimming and filtering the adapter and primers, optimizing the sequence by aligning with the paired-end sequence, and clustering the optimized sequence into amplicon sequence variants at a sequence similarity of 97%; (3) Classifying and annotating each amplicon sequence variant, determining the similarity of microbial communities in different samples, identifying significantly different bacterial taxa between groups, and determining the abundance of Bacteroides cacae.

9. Application of Bacteroides cacae in preparation of a heat acclimatization promoter.

10. A heat acclimation facilitator, characterized in that, The kit comprises an active ingredient and a pharmaceutically acceptable excipient, the active ingredient is Bacteroides cacae live bacteria, and the excipient is selected from a protective agent, a carrier, or an activator that maintains the activity of the bacteria.

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