A method for potential risk assessment of probiotic

Abstract

The present application relates to the technical field of probiotic safety evaluation, and discloses a kind of probiotic potential risk evaluation method, comprising the following steps: obtaining the genomic sequencing data of probiotic, determine potential risk evaluation index, respectively, drug resistance, toxicity and genomic instability;Set the weight of potential risk evaluation index;Based on evaluation index, detect potential risk sequence in genome;Quantify the risk of strain under a single potential risk evaluation index, determine the risk level of strain under the index;Statistical three potential risk evaluation index under different risk level strain quantity proportion of all strains;According to risk level distribution and weight, determine the comprehensive risk level.The evaluation method of the present application can solve the complexity and uncertainty problem in the potential risk evaluation of probiotic, comprehensively consider possible risk factors, and comprehensively consider multiple strains in the strain, which can comprehensively and quantitatively evaluate the potential risk of probiotic strain at the strain level.

Description

Technical Field

[0001] This invention relates to the field of probiotic safety assessment technology, and in particular to a method for assessing the potential risks of probiotics. Background Technology

[0002] In recent years, an increasing number of beneficial microorganisms have been applied in the food and medical fields. These beneficial microorganisms play an important role in maintaining intestinal homeostasis and regulating immunity, among other health benefits. Since these beneficial microorganisms are ingested by humans, they must undergo safety evaluations before being identified as probiotics and used in large-scale production.

[0003] Antibiotic resistance refers to the phenomenon of bacteria becoming insensitive to antimicrobial drugs. Once pathogenic bacteria develop resistance to a certain antibiotic, that class of antibiotics may become ineffective. Antibiotic resistance genes (ARGs) are nucleotide sequences that encode resistance traits. These genes can not only induce resistance in bacteria but also be transferred to other bacteria in the environment via mobile genetic elements such as plasmids and conjugation elements, leading to the development of similar resistance in those bacteria. Virulence genes (VGs) are genes that facilitate the survival and pathogenicity of pathogenic bacteria within the host, including those related to bacterial colonization and the production of toxic substances. Sequence alignment methods can detect all ARGs and VGs carried in the genome of probiotics.

[0004] The current methods for evaluating the safety of probiotics are mainly: (1) When studying the function of candidate strains in vivo or in vitro, observe whether the probiotics have drug resistance phenotypes and toxin production capabilities, and then evaluate their safety (e.g., in the literature "Xu Jin, Yan Weixing, Yang Baolan, Li Zhigang. Safety assessment of probiotic strains in fermented dairy products in China [J]. Health Research, 2008(02):193-195.", the drug resistance of probiotics to antibiotics is assessed by detecting the minimum inhibitory concentration of probiotic strains against antibiotics). (2) Detect ARGs, VGs and mobile genetic elements in the genome of probiotics through sequence alignment algorithms, and then discuss the risks on the genome of the strain in these three aspects (e.g., patent CN114277161A uses high-throughput sequencing technology combined with an antibiotic resistance gene database to analyze the antibiotic resistance genes carried by probiotics in sterilized dairy products).

[0005] However, these evaluation methods have the following problems: (1) They cannot observe the potential risks of probiotics. Theoretically, ARGs and VGs present in the probiotic genome can be transferred through mobile genetic elements, thus causing potential risks. (2) They cannot provide an effective assessment of the overall risk of probiotic strains. Different strains will exhibit different potential risks. Based on the genomic data of probiotics, the risks in the presence and transfer of antibiotic resistance genes, the presence of virulence genes, and genomic stability can be analyzed separately, but a comprehensive evaluation result cannot be obtained. Summary of the Invention

[0006] To address the technical problem that existing probiotic safety evaluation methods cannot comprehensively assess potential risks, this invention provides a probiotic potential risk assessment method. This assessment method can resolve the complexity and uncertainty issues in probiotic potential risk assessment, comprehensively consider possible risk factors, and integrate multiple strains of the same species to comprehensively and quantitatively assess the potential risks of probiotics at the strain level.

[0007] The specific technical solution of this invention is as follows: A method for assessing the potential risks of probiotics includes the following steps: Step S1: Obtain the genome sequencing data of probiotics and determine potential risk assessment indicators, namely drug resistance, toxicity and genome instability; Step S2: Set the weights of potential risk assessment indicators; Step S3: Detect potential risk sequences in the genome based on assessment metrics; Step S4: Quantify the risk of the strain under a single potential risk assessment indicator and determine the risk level of the strain under that indicator; Step S5: Calculate the proportion of strains with different risk levels to all strains under the three potential risk assessment indicators; Step S6: Based on the statistical results of Step S5 and the weights set in Step S2, determine the comprehensive risk level of probiotics under the three potential risk assessment indicators.

[0008] The method of this invention takes into account that the safety risk of probiotics is the result of the combined effect of multiple factors (including drug resistance, toxicity and genomic instability) in the process of assessing the potential risks of probiotics. Drug resistance, toxicity and genomic instability are used as evaluation indicators, and the safety risk under the three indicators is quantified into risk score and risk level respectively. Then, the comprehensive risk is quantified. This method can comprehensively consider possible risk factors and quantitatively evaluate the potential risks of probiotics, thus achieving a comprehensive, holistic and effective evaluation of the potential risks of probiotics.

[0009] Furthermore, the method of this invention can integrate multiple strains of the same species, enabling potential risk assessment at the species level. The assessment results can cover all species and have a certain predictive ability for the potential safety risks of new strains.

[0010] Preferably, in step S2, the weights of the drug resistance index are 0.635–0.640, the weights of the toxicity index are 0.105–0.110, the weights of the genomic instability index are 0.255–0.260, and the sum of the weights of the three potential risk assessment indicators is 1.

[0011] Following the principle that the importance of drug resistance is slightly greater than that of genomic instability, significantly greater than that of toxicity, and that genomic instability is slightly greater than that of toxicity, an importance comparison matrix was constructed. The eigenvector corresponding to the largest eigenvalue in the importance comparison matrix was calculated. Consistency checks and normalization were performed on the eigenvectors to obtain a weight vector. The elements in the weight vector are the weight values ​​corresponding to the three indicators. The weights of the three potential risk assessment indicators ultimately established have high accuracy and scientific validity when used for the potential risk assessment of probiotics.

[0012] Preferably, the potential risk sequences in step S3 are as follows: the risk sequence corresponding to the drug resistance index is the antibiotic resistance gene sequence, the risk sequence corresponding to the toxicity index is the virulence gene sequence, and the risk sequence corresponding to the genomic instability index is the mobile sequence on the chromosome and plasmid.

[0013] The preferred step S4 includes the following steps: Step S41: Classify the antibiotic resistance gene sequences corresponding to the resistance index and the plasmids corresponding to the genomic instability index according to the ease of transfer; and set the weight for each category; Step S42: Calculate the risk score of the strain under a single indicator; Step S43: Determine the risk level of the strain under this indicator based on the risk score.

[0014] Preferably, in step S41, the antibiotic resistance gene sequences corresponding to the drug resistance index and the plasmids corresponding to the genomic instability index are classified according to the ease of transfer as follows: Category 1, difficult to transfer; Category 2, possibly transferable; Category 3, very easy to transfer; the weight of Category 1 is 0.105 to 0.110, the weight of Category 2 is 0.305 to 0.310, the weight of Category 3 is 0.580 to 0.585, and the sum of the weights of the three categories is 1.

[0015] Preferably, in step S42, the risk score S under the drug resistance index is... ARG The calculation formula is as follows: Where, n i k is the number of antibiotic resistance genes of class i, and k is the number of genes of class i. i It represents the weight of the antibiotic resistance gene of class i, where i = 1, 2, 3.

[0016] Preferably, in step S42, the risk score S under the genomic instability index is... m The calculation formula is as follows: Among them, L MGE / L Chr L represents chromosome migration rate. MGE It is the length of the mobile sequence in a chromosome, L chr σ is the chromosome length, and m is the deviation between the chromosome mobility of the strain and the average chromosome mobility of the species. i k is the number of plasmids of type i. i is the weight of the i-th class and plasmid, i = 1, 2, 3.

[0017] Preferably, in step S42, the risk score S under the toxicity index is... VG The calculation formula is as follows: Where, N VG It represents the number of virulence genes detected in the strain's genome, and N is the total number of genes required for toxin production.

[0018] In the above formula: S ARG and S m The calculation formula takes into account the different levels of potential risk posed by different types of antibiotic resistance genes, mobile sequences on chromosomes, and different types of extrachromosomal plasmids; S VG The calculation formula comprehensively considers the number of virulence genes and the total number of genes required for toxin production. Using the risk score formula in this invention, the potential risk of the strain under three evaluation indicators is quantified, which can accurately reflect the potential risk of the strain.

[0019] As a preferred embodiment, in step S43, the criteria for determining the risk level based on the risk score are as follows: Drug resistance index: Risk score S under drug resistance index ARG If the value is ≤0.109, the risk level is IV; if the value is <0.109, the risk level is IV. ARG If the value is ≤0.309, the risk level is III; if the value is <0.309, the risk level is III. ARG If the value is ≤1.164, the risk level is II; S ARG If the value is greater than 1.164, the risk level is I; toxicity index: risk score S under the toxicity index. VG =0, then the risk level is IV; S VG=1, then the risk level is III; S VG =2, then the risk level is II; S VG =3, then the risk level is I; Genomic instability index: Risk score S under genomic instability index m If the value is ≤0.109, the risk level is IV; if the value is <0.109, the risk level is IV. m If the value is ≤0.309, the risk level is III; if the value is <0.309, the risk level is III. m If the value is ≤1.164, the risk level is II; S m If the value is greater than 1.164, the risk level is I.

[0020] Preferably, step S6 includes the following steps: S61: Based on the statistical results of step S5, establish an evaluation matrix; S62: Using fuzzy operators and combining the weights set for the risk assessment indicators in step S2, the evaluation matrix is ​​weighted and summed to obtain the membership score for each risk level. S63: Determine the comprehensive risk level of probiotics under the three potential risk assessment indicators according to the principle of maximum membership.

[0021] Compared with the prior art, the present invention has the following advantages: The evaluation method of this invention comprehensively considers multiple possible risk factors, including the presence and transfer of antibiotic resistance genes, the presence of virulence genes, and the risk of antibiotic resistance genes being transferred to other bacteria. It also integrates multiple strains within the same species, enabling a comprehensive and quantitative assessment of the potential risks of probiotics at the species level. Attached Figure Description

[0022] Figure 1 This is a flowchart of the potential risk assessment of the probiotic strains in Example 1; Figure 2 This is a flowchart of determining the risk score and risk level (step S4) in Example 1; Figure 3 This is a flowchart of determining the comprehensive risk level (step S6) in Example 1. Detailed Implementation

[0023] The present invention will be further described below with reference to embodiments.

[0024] The terminology used in the embodiments of this invention is for describing specific particular implementations and is not intended to limit the scope of protection of this invention. Variations and advantages that can be conceived by those skilled in the art without departing from the spirit and scope of the inventive concept are included in this invention and are protected by the appended claims and any equivalents thereof.

[0025] General Implementation Examples A method for assessing the potential risks of probiotics includes the following steps: Step S1: Obtain the genome sequencing data of probiotics and determine potential risk assessment indicators, namely drug resistance, toxicity and genome instability; Step S2: Set the weights of potential risk assessment indicators; Step S3: Detect potential risk sequences in the genome based on assessment metrics; Step S4: Quantify the risk of the strain under a single potential risk assessment indicator and determine the risk level of the strain under that indicator; Step S5: Calculate the proportion of strains with different risk levels to all strains under the three potential risk assessment indicators; Step S6: Based on the statistical results of Step S5 and the weights set in Step S2, determine the comprehensive risk level of probiotics under the three potential risk assessment indicators.

[0026] In one specific implementation, in step S2, the weight of the drug resistance index is 0.635–0.640, the weight of the toxicity index is 0.105–0.110, the weight of the genomic instability index is 0.255–0.260, and the sum of the weights of the three potential risk assessment indicators is 1.

[0027] As one specific implementation, the potential risk sequences in step S3 are as follows: the risk sequences corresponding to the drug resistance indicators are antibiotic resistance gene sequences, the risk sequences corresponding to the toxicity indicators are virulence gene sequences, and the risk sequences corresponding to the genomic instability indicators are mobile sequences on chromosomes and plasmids.

[0028] As a specific implementation method, step S4 includes the following steps: Step S41: Classify the antibiotic resistance gene sequences corresponding to the drug resistance index and the plasmids corresponding to the genomic instability index according to the ease of transfer as follows: Category 1, difficult to transfer; Category 2, possibly transferable; Category 3, very easy to transfer; The weight of Category 1 is 0.105~0.110, the weight of Category 2 is 0.305~0.310, the weight of Category 3 is 0.580~0.585, and the sum of the weights of the three categories is 1; Step S42: Calculate the risk score of the strain under a single indicator. The formulas for the risk score under each potential risk assessment indicator are as follows: Risk score S under drug resistance index ARG Calculation formula: Where, n i k is the number of antibiotic resistance genes of class i, and k is the number of genes of class i. iThe weights of antibiotic resistance genes of class i, i = 1, 2, 3; the risk score S under the genomic instability index. m Calculation formula: Among them, L MGE / L Chr L represents chromosome migration rate. MGE It is the length of the mobile sequence in a chromosome, L chr σ is the chromosome length, and m is the deviation between the chromosome mobility of the strain and the average chromosome mobility of the species. i k is the number of plasmids of type i. i is the weight of the i-th type of plasmid, i = 1, 2, 3; Risk score S under toxicity indicators VG Calculation formula: Where, N VG It represents the number of virulence genes detected in the strain's genome, and N is the total number of genes required for toxin production; Step S43: Determine the risk level of the strain under this indicator based on the risk score, according to the following criteria: Drug resistance index: S ARG If the value is ≤0.109, the risk level is IV; if the value is <0.109, the risk level is IV. ARG If the value is ≤0.309, the risk level is III; if the value is <0.309, the risk level is III. ARG If the value is ≤1.164, the risk level is II; S ARG If the value is greater than 1.164, the risk level is I. Toxicity index: S VG =0, then the risk level is IV; S VG =1, then the risk level is III; S VG =2, then the risk level is II; S VG =3, then the risk level is I; Genomic instability index: S m If the value is ≤0.109, the risk level is IV; if the value is <0.109, the risk level is IV. m If the value is ≤0.309, the risk level is III; if the value is <0.309, the risk level is III. m If the value is ≤1.164, the risk level is II; S m If the value is greater than 1.164, the risk level is I.

[0029] As one specific implementation method, step S6 includes the following steps: S61: Based on the statistical results of step S5, establish an evaluation matrix; S62: Using fuzzy operators and combining the weights set for the risk assessment indicators in step S2, the evaluation matrix is ​​weighted and summed to obtain the membership score for each risk level. S63: Determine the comprehensive risk level of probiotics under multiple indicators based on the principle of maximum membership.

[0030] Example 1 Based on whole-genome sequencing data, the potential risks of the probiotic Akkermansia myxophilus were assessed, and the entire process was as follows: Figure 1 As shown, the specific steps are as follows: Step S1: Obtain genome sequencing data for 95 strains of *Akermansia myxophilus*. Potential risk assessment indicators: drug resistance, toxicity, and genomic instability.

[0031] Step S2: Assign weights to the evaluation indicators based on their relative importance. The specific steps are as follows: Step S21: Construct an importance comparison matrix according to the following: drug resistance is slightly more important than genomic instability, significantly more important than toxicity, and genomic instability is slightly more important than toxicity. In the matrix, 1 represents equal importance, 3 represents slightly important, and 5 represents significantly important, as shown in Table 1. Table 1. Comparison Matrix of Importance of Risk Assessment Indicators and Calculation Results of Their Weight Vectors Step S22: Calculate the eigenvector corresponding to the largest eigenvalue of the matrix and perform consistency check and normalization to obtain the weight vector W = (0.637, 0.258, 0.105), that is, the weights of the drug resistance index, the genomic instability index, and the toxicity index are 0.637, 0.258, and 0.105, respectively.

[0032] Step S3: Detect antibiotic resistance gene sequences, virulence gene sequences, mobile sequences on chromosomes, and plasmids in the strain genome; Step S4: Based on the test results, quantify the risk of the strain under a single indicator and determine the risk level of the strain under that indicator; the entire process is as follows: Figure 2 As shown, the specific steps are as follows: Step S41: Traverse the antibiotic resistance genes and plasmids detected in the strain genome, and classify the antibiotic resistance gene sequences corresponding to the resistance index and the plasmids corresponding to the genome instability index according to the degree of transfer difficulty: Category 1, difficult to transfer; Category 2, possible to transfer; Category 3, very easy to transfer; count the number of antibiotic resistance genes and plasmids in the three categories in the strain, as well as the ratio of the length of the mobile sequence on the chromosome to the total length of the chromosome; Step S42: Repeat step S2 to set the weights for the three categories. The results are shown in Table 2. Table 2. Calculation results of importance comparison matrices and weight vectors for different categories. Step S43: Calculate the risk score for each indicator. The calculation formula is as follows: Risk score S under drug resistance index ARG Calculation formula: Where, n i k is the number of antibiotic resistance genes of class i. i It represents the weight of the antibiotic resistance gene of class i, where i = 1, 2, 3.

[0033] Risk score S under the genomic instability index m Calculation formula: Among them, L MGE / L Chr L represents chromosome migration rate. MGE It is the length of the mobile sequence in a chromosome, L chr σ is the chromosome length, and m is the difference between the actual chromosome migration rate of the strain and the average chromosome migration rate of *Ackermania* species. i k is the number of plasmids of type i. i It is the weight of the i-th type of plasmid, i = 1, 2, 3.

[0034] Risk score S under toxicity indicators VG Calculation formula: Where, N VG It represents the number of virulence genes detected in the strain's genome, and N is the total number of genes required for toxin production.

[0035] Step S44: Read the S of the strain ARG Assign the value to S; Step S45: Determine if S is greater than 0.109. If yes, continue; otherwise, the risk level is IV. Step S46: Determine if S is greater than 0.309. If yes, continue; otherwise, the risk level is III. Step S47: Determine if S is greater than 1.164. If yes, the risk level is I; otherwise, the risk level is II. Step S48: Read the S of the strain m Assign the value to S, and repeat steps S45 to S47. Step S49: Read S VGIf the value is 0, the risk level is IV; if it is 1, the risk level is III; if it is 2, the risk level is II; if it is 3, the risk level is I.

[0036] Step S5: Calculate the proportion of strains with different risk levels to all strains under the three indicators, as shown in Table 3.

[0037] Table 3 shows the percentage of strains with different risk levels in the total number of strains under the three indicators. Step S6: Use fuzzy operators to perform a weighted summation of the weight vector and evaluation matrix to determine the overall risk. The entire process is as follows: Figure 3 As shown, the specific steps are as follows: Step S61: Based on the statistical results of step S5, establish evaluation matrix A; Step S62: Using the fuzzy operator M(·,⊕), weighted summation of W and A is performed to obtain the membership scores of *Ackermania* species to risk levels IV to I. The specific calculation process is as follows: That is, the membership scores for risk levels IV, III, II, and I are 0.863, 0.003, 0.127, and 0.007, respectively; Step S63: According to the principle of maximum membership, the comprehensive risk level of the Akkermansia myxophilus species is IV corresponding to the maximum membership score (0.863) (risk levels I to IV correspond to potential risks from high to low).

[0038] Although this invention uses terms such as genome sequencing data, antibiotic resistance genes, virulence genes, genome instability, and weight vectors extensively, the possibility of using other terms is not excluded. These terms are used for the convenience of describing and explaining the essence of this invention; interpreting them as any additional limitation would contradict the spirit of this invention. Unless otherwise specified, the raw materials and equipment used in this invention are commonly used in the art; and unless otherwise specified, the methods used in this invention are conventional methods in the art.

[0039] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Any simple modifications, alterations, and equivalent transformations made to the above embodiments based on the technical essence of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A method for assessing the potential risks of probiotics, comprising: S1 acquires genome sequencing data, and the evaluation indicators and weights are set as follows: drug resistance 0.635~0.640, toxicity 0.105~0.110, genome instability 0.255~0.260, and the sum of the three is 1; S2 detects potential risk sequences in the genome based on various indicators: drug resistance corresponds to antibiotic resistance gene sequences, toxicity corresponds to virulence gene sequences, and genomic instability corresponds to mobile sequences and plasmids on chromosomes. S3： S31 antibiotic resistance gene sequences and plasmids are classified according to their transfer difficulty: Category 1, not easily transferred, weight 0.105~0.110; Category 2, possibly transferable, weight 0.305~0.310; Category 3, very easily transferred, weight 0.580~0.585; the sum of the weights of the three categories is 1. S32 calculates the risk score for each indicator: S ARG The sum of the weighted number of resistance genes for the three classes of antibiotics; S m The chromosome mobility rate is calculated by multiplying its deviation from the mean of its species, then adding the weighted sum of the three plasmid types; chromosome mobility rate is the ratio of the length of the mobile sequence to the total chromosome length; N VG =0, 0 <N VG / N<1 / 3, 1 / 3≤N VG / N<2 / 3, N VG When / N≥2 / 3, S VG The values ​​are 0, 1, 2, 3, and N. VG It represents the number of virulence genes detected in the genome, and N is the total number of genes required for toxin production. S33 determines the risk level of each indicator based on the risk score: Drug resistance: S ARG >1.164, 0.309<S ARG ≤1.164, 0.109<S ARG ≤0.309, S ARG When the value is ≤0.109, the risk levels are I to IV respectively; Toxicity: S VG The risk levels are I to IV when the values ​​are 3, 2, 1, and 0, respectively. Genome instability: S m >1.164, 0.309<S m ≤1.164, 0.109<S m ≤0.309, S m When the value is ≤0.109, the risk levels are I to IV respectively; S4 statistics show the proportion of strains at each risk level to all strains of the species under each indicator. S5 constructs an evaluation matrix based on the results of S4; the evaluation matrix is ​​weighted and summed using fuzzy operators and S1 weights to obtain the membership scores of each risk level; the comprehensive risk level is determined according to the principle of maximum membership.

2. The probiotic potential risk assessment method as described in claim 1, characterized in that, In step S1, the weight of the drug resistance index is 0.

637.

3. The probiotic potential risk assessment method as described in claim 1, characterized in that, In step S1, the weight of the toxicity index is 0.

105.

4. The probiotic potential risk assessment method as described in claim 1, characterized in that, In step S1, the weight of the genomic instability index is 0.

258.

5. The probiotic potential risk assessment method as described in claim 1, characterized in that, In step S1, the weights of the drug resistance, toxicity, and genomic instability indicators are 0.637, 0.105, and 0.258, respectively.

6. The probiotic potential risk assessment method as described in claim 1, characterized in that, In step S31, the weight of category 1 is 0.

109.

7. The probiotic potential risk assessment method as described in claim 1, characterized in that, In step S31, the weight of category 2 is 0.

309.

8. The method for assessing the potential risks of probiotics as described in claim 1, characterized in that, In step S31, the weight of category 3 is 0.

582.

9. The method for assessing the potential risks of probiotics as described in claim 1, characterized in that, In step S31, the weights of categories 1 to 3 are 0.109, 0.309, and 0.582, respectively.

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