Method for identifying microbial core species in river ecosystem

Abstract

The invention relates to a method for identifying microbial core species in a river ecosystem, and belongs to the field of microbial ecology. Through OTU relative abundance data, a presence-absence matrix is constructed, and an OTU occurrence rate and an average relative abundance are calculated. And evaluating the OTU ecological importance, and identifying a potential core OTU. And analyzing the consistency of the OTU occurrence frequency and the time scale in combination with the time point location, and generating a ranking index Index for ranking. And performing Bray-Curis similarity analysis to quantify the structural diversity of the OTU community, and identifying the OTU which has the greatest influence on the community similarity. And determining a core OTU threshold value based on an inflection point method and a growth rate method, verifying a core classification group combination mechanism by using a Sloan neutral model, and finally determining the representativeness of the core OTU by comparing the actual occurrence frequency with model prediction. According to the method, rich information is provided for explaining the diversity pattern of the microflora level.

Description

Technical Field

[0001] The invention belongs to the field of microbial ecology and relates to a method for identifying core species of microorganisms in a river ecosystem. Background Art

[0002] In the field of microbial ecology, the core microbiome is defined as the dominant and widely distributed important species in an ecosystem. Therefore, many studies have focused on the genes, functional pathways, and metabolic characteristics shared by microbial communities in some environments. Therefore, microbial taxa shared between two or more microbial communities represent the most ecologically and functionally important microorganisms in the environment under those conditions. Determining the components of the core microbiome is of great significance in formulating ecological management plans and responding to environmental changes.

[0003] While core taxonomic microbiome analyses have provided many insights into the microbial ecology of numerous rings, they often differ in the criteria used to quantify the core. Core microbiome studies are still largely in the discovery phase, relying heavily on Venn diagrams to identify taxa shared between samples. They further outline additional approaches for future studies, such as including the relative abundance of taxa when identifying cores, and measuring “persistent” or “dynamic” core microbiomes over time. These advances have led to discoveries such as the stability of specific microbial strains in the gut of individual humans and the persistence of certain microbial taxa across major environmental transitions, such as the migration of Atlantic salmon from saltwater to freshwater. On the other hand, some studies of phylogenetically diverse hosts have found that putative core microbiomes are composed of transient taxa that are repeatedly acquired from the environment rather than being obligate companions to the host. Later, some researchers have suggested abandoning the taxonomic approach in favor of a fully functional definition of the core microbiome, in which the core is defined as a complete set of microbial vectors, including replicators that encode essential functions for the fitness of the overall organism. One solution proposed to this problem is to specify the type of core microbiome of interest, such as a temporal core, an ecological core, or a functional core.

[0004] The core microbiome is usually quantified using one of the following three methods: 1) microbial taxa that co-occur in multiple samples from the same environment; 2) relative abundance ranking of microbial taxa in these samples; 3) a combination of occurrence rate and relative abundance. The advantage of using only occurrence rate or relative abundance to quantify core microorganisms is that the calculation is simple, but the disadvantage is that the threshold is selected arbitrarily and is seriously affected by the sampling range and sequencing depth. Using only relative abundance will ignore the influence of rare taxa. The method of combining occurrence rate and relative abundance is based on macroecological theory and can distinguish between randomly and deterministically selected cores. Summary of the invention

[0005] In view of this, the purpose of the present invention is to provide a method for identifying core species of microorganisms in river ecosystems. Based on the changes in the number and distribution of core species in environmental microbial communities, the health status of the ecosystem and the balance and stability of the ecosystem are evaluated to provide technical support for better microbial identification.

[0006] In order to achieve the above object, the present invention provides the following technical solutions:

[0007] A method for identifying core species of microorganisms in a river ecosystem, the method comprising the following steps:

[0008] Collecting biological data;

[0009] Occupancy-abundance analysis was performed on OTU to assess the ecological importance of OTU;

[0010] persistent species ordering over time scales;

[0011] Bray-Curtis similarity analysis quantified the beta diversity of OTU community structure;

[0012] Use SHAP values ​​to interpret the model and understand the impact of environmental factors on model predictions;

[0013] Definition and validation of core microorganisms.

[0014] Among them, the biological data are the relative abundance data of OTU in river microorganisms.

[0015] Potential core OTUs were identified by plotting the logarithmic mean relative abundance of OTUs versus occupancy.

[0016] First, occupancy-abundance analysis was performed to evaluate the ecological importance of OTUs. Then, the frequency of occurrence of each OTU at different time points was calculated and the OTUs were ranked. Bray-Curtis similarity analysis was used to quantify the β diversity of OTU community structure. Finally, the cumulative contribution of each OTU was calculated to identify the OTU with the greatest impact on community similarity.

[0017] Preprocessing of persistent species ranking data on time scale: Generate time points based on the year and month of the sample, calculate the frequency of each OTU at different time points, and quantify the consistency of OTU on time scale by frequency on time scale, and combine these two indicators to generate a ranking index Index to rank OTU. The higher the Index, the wider the distribution of the OTU on time scale and the more persistent microorganisms at more sites.

[0018] Bray-Curtis similarity analysis: Bray-Curtis similarity analysis was used to quantify the beta diversity of OTU community structure. It was calculated using the following formula:

[0019]

[0020] Among them, S is the number of common OTUs, min(A i ,B i ) is the minimum abundance value of the i-th OTU in the two samples. is the sum of the abundances of the two samples.

[0021] Definition and verification of core microorganisms: The Bray-Curtis similarity of the top 500 OTUs was calculated. The OTUs with the greatest impact on community similarity were identified by calculating the cumulative contribution of each OTU. The threshold and range of core OTUs were determined based on the elbow method and the growth rate method.

[0022] The beneficial effects of the present invention are:

[0023] (1) Based on the frequency of occurrence and relative abundance of OTUs in the community, this paper plots the relationship between the logarithmic mean relative abundance and occupancy of OTUs and analyzes the occupancy-abundance relationship to assess the ecological importance of OTUs and identify potential core OTUs. Abundance and occupancy together provide rich information for explaining the diversity pattern at the microbial community level.

[0024] (2) The present invention uses the occupancy-abundance relationship to divide core species. Different from traditional abundant species or dominant species, they can exist in the ecosystem for a long time and have a high abundance. A method for determining the core members of the community based on the frequency of occurrence of each community member in different sub-communities is proposed, and the statistical strength of the core microbial community and the corresponding core members are tested by a bootstrap strategy of random sampling.

[0025] (3) The present invention determines the threshold and range of the core OTU based on both the inflection point method and the growth rate method, providing a division standard and scientific basis for the final determination of the core microbial community.

[0026] (4) The present invention helps to formulate more accurate and timely ecological management plans, and provides a scientific basis for microbial regulation and management in ecosystems by accurately obtaining information on core species in microbial ecosystems.

[0027] (5) The present invention is mainly applied in the field of microbial ecology research and is an important tool for understanding the composition and functional structure of microbial communities in complex environmental ecosystems.

[0028] Other advantages, objectives and features of the present invention will be described in the following description to some extent, and to some extent, will be obvious to those skilled in the art based on the following examination and study, or can be taught from the practice of the present invention. The objectives and other advantages of the present invention can be realized and obtained through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to make the purpose, technical solutions and advantages of the present invention more clear, the present invention will be described in detail below in conjunction with the accompanying drawings, wherein:

[0030] Figure 1 It is a flow chart of the present invention;

[0031] Figure 2 A graph showing the relationship between microbial occupancy and average relative abundance in a specific embodiment of the present invention;

[0032] Figure 3 The relative abundance distribution results of the top 500 OTUs at different classification levels in a specific embodiment of the present invention;

[0033] Figure 4 This is the core species classification threshold result in a specific embodiment of the present invention;

[0034] Figure 5 The distribution of core species in the neutral model obtained in the specific embodiment of the present invention. DETAILED DESCRIPTION

[0035] The following describes the embodiments of the present invention by specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the illustrations provided in the following embodiments only illustrate the basic concept of the present invention in a schematic manner, and the following embodiments and features in the embodiments can be combined with each other without conflict.

[0036] Among them, the drawings are only used for illustrative explanations, and they only represent schematic diagrams rather than actual pictures, and should not be understood as limitations on the present invention. In order to better illustrate the embodiments of the present invention, some parts of the drawings may be omitted, enlarged or reduced, and do not represent the size of actual products. For those skilled in the art, it is understandable that some well-known structures and their descriptions in the drawings may be omitted.

[0037] The same or similar numbers in the drawings of the embodiments of the present invention correspond to the same or similar parts; in the description of the present invention, it should be understood that if the terms "upper", "lower", "left", "right", "front", "rear", etc. indicate the orientation or position relationship, they are based on the orientation or position relationship shown in the drawings, which is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operate in a specific orientation. Therefore, the terms describing the position relationship in the drawings are only used for illustrative purposes and cannot be understood as limiting the present invention. For ordinary technicians in this field, the specific meanings of the above terms can be understood according to specific circumstances.

[0038] Figure 1 This is a flow chart of the present invention. This embodiment uses a method for identifying core microbial species based on the species occupancy-relative abundance relationship to identify core species of environmental microorganisms, which specifically includes the following steps:

[0039] 1. Compile and organize river bacterial plankton OTU data.

[0040] 2. OTU occupancy and abundance analysis.

[0041] The OTU abundance table was converted to presence-absence format, with "1" indicating presence and "0" indicating absence. The relative abundance was standardized using the vegan package (v2.6.4) in R4.3.3. The presence / absence matrix of OTU and the occurrence rate of each row (otu_occ) were calculated, and the relative abundance of OTU (otu_rel) was calculated. The occurrence rate and relative abundance were combined into a data frame (occ_abun) for occupancy-abundance relationship analysis to assess the ecological importance of OTU. The relationship between the logarithmic mean relative abundance and occupancy of OTU was plotted using the ggplot2 (v3.5.1) package to identify potential core OTUs. The results are shown in Figure 2. Figure 2 As shown in the figure, the relationship between the occupancy and relative abundance of OTUs is shown, and log10 transformation is performed. The color and size of the data points correspond to the standard deviation of OTU occupancy and relative abundance, respectively. The most abundant taxa of river plankton bacteria show the highest occupancy, while the rare taxa show the lowest occupancy. The closer the OTU is to the upper right corner, the more likely it is to belong to the "core".

[0042] 3. Persistent species ordering over time scales.

[0043] Generate time points based on the year and month of the sample, calculate the frequency of occurrence of each OTU at different time points, and quantify the consistency of OTU on the time scale through sumF and sumG, and combine these two indicators to generate a ranking index Index to rank OTU. sumF is the sum of the frequency of occurrence at the time point, and sumG represents the core time point. These two indicators are used to quantify the consistency and distribution characteristics of OTU on the time scale, and their mathematical expression is:

[0044]

[0045] in, Indicates the frequency of occurrence of the OTU at the i-th time point, where n is the number of all time points. Specifically, the frequency of occurrence of an OTU at each time point is calculated by whether it exists at that point, and then the frequencies of occurrence of all points are summed. The larger sumF is, the more commonly the OTU is distributed across the entire time scale. coreTime i is a binary variable. If OTU is a persistent microorganism at the i-th time point, that is, coreTime i =1; otherwise coreTime i =0. The larger the sumG, the more persistent microorganisms the OTU exists at more time sites. Index indicates the consistency and persistence of the OTU at all time sites. The higher the Index, the wider the distribution of the OTU on the time scale and the more persistent microorganisms it exists at. By quantifying the consistency and distribution characteristics of OTUs on the time scale, the OTUs are sorted and the distribution of the top 500 OTUs at different classification levels is analyzed. Figure 3 shown.

[0046] 4. Bray-Curtis similarity analysis.

[0047] Bray-Curtis similarity analysis was used to quantify the beta diversity of OTU community structure. It was calculated using the following formula:

[0048]

[0049] Among them, S is the number of common OTUs, min(A i ,B i ) is the minimum abundance value of the i-th OTU in the two samples. is the sum of the abundances of the two samples. The Bray-Curtis similarity analysis results calculated in the example are shown in Table 1.

[0050] Table 1

[0051] rank MeanBC Proportion BC Increase BC Fo_diffs 1 0.001611133 0.002464914 0 -0.00104 2 0.004016863 0.006145502 2.493191322 0.000165 3 0.015819327 0.024202397 3.938229442 0.003719 4 0.02063288 0.031566777 1.304293108 0.003746 5 0.036092085 0.055218214 1.749250938 0.005916 6 0.038679087 0.059176136 1.071677824 0.005201 7 0.0497841 0.076165981 1.28106364 0.005926 8 0.053865517 0.082410247 1.081982349 0.005582 9 0.065077667 0.099564006 1.208150796 0.006123 10 0.073605895 0.112611562 1.131046923 0.006286

[0052] 5. Use the inflection point method and growth rate method to calculate the core species classification threshold.

[0053] The thresholds for core species division were calculated based on the inflection point method and the growth rate method, and the distribution of core OTUs in all OTUs was studied, such as Figure 4 shown. Figure 4 The core OTU thresholds calculated by these two methods are shown. The red dashed line represents the core OTU threshold defined by the inflection point method, while the blue dashed line represents the core OTU threshold defined by the Bray-Curtis similarity last 2% increment point method. OTUs defined as "core" are shown in blue. The core OTU division of the inflection point method is more strict, with only 16 OTUs meeting the requirements; while the number of core OTUs divided based on the growth rate method is 157.

[0054] 6. Verify and sort core species based on the neutral model

[0055] The abundance-occupancy distribution generally shows an "S"-shaped trend, that is, the most abundant taxa show the highest occupancy, while rare taxa show lower occupancy. Figure 5 The validation results of the core species based on the neutral model are presented. Figure 5 The distribution of core OTUs inside and outside the confidence interval of the neutral model is shown. OTUs falling outside the confidence interval are considered to be taxa affected by deterministic selection, especially most core OTUs are distributed below the fitting curve, indicating that they are more sensitive to the influence of local environmental conditions.

[0056] Example:

[0057] 1. Data Collection and Processing

[0058] Collect river bacterial planktonic OTU relative abundance data, for example, using high-throughput sequencing technology.

[0059] The OTU abundance table was converted to presence-absence format, with "1" representing presence and "0" representing absence.

[0060] The vegan package in R software was used for standardization and the occurrence rate and relative abundance of OTU were calculated.

[0061] 2. Occupancy and Abundance Analysis

[0062] Combine occurrence and relative abundance into a data frame for occupancy-abundance relationship analysis.

[0063] The ggplot2 package was used to plot the relationship between the logarithmic mean relative abundance and occupancy of OTUs and identify potential core OTUs.

[0064] 3. Persistent species ordering over time

[0065] Generates time points based on the year and month of the sample.

[0066] The frequency of each OTU at different time points was calculated, and the consistency of OTU on the time scale was quantified using sumF and sumG.

[0067] The ranking index Index is generated by combining sumF and sumG to rank OTUs.

[0068] 4. Bray-Curtis similarity analysis

[0069] The Bray-Curtis similarity of the top 500 OTUs was calculated.

[0070] The cumulative contribution of each OTU was calculated to identify the OTU with the greatest impact on community similarity.

[0071] 5. Determination of core OTUs

[0072] The threshold and range of core OTU were determined based on the inflection point method and the growth rate method.

[0073] The OTUs that meet the threshold are defined as “core” OTUs.

[0074] 6. Core species verification

[0075] The Sloan neutral model was used to explore and verify the combination mechanism of core taxonomic groups.

[0076] The representativeness of the core OTUs was further determined by calculating the actual occurrence frequency of OTUs and comparing it with the upper and lower limits predicted by the model.

[0077] 7. Results Analysis and Application

[0078] The community structure and functional characteristics of core OTUs were analyzed to assess the health status and stability of the river ecosystem.

[0079] Develop more accurate and timely ecological management plans to provide a scientific basis for microbial regulation and management impacts in ecosystems.

[0080] In this example, 16 core OTUs were identified by analyzing river bacterial planktonic OTU data, and it was found that these core OTUs were more sensitive to local environmental conditions, indicating that they play an important role in maintaining the stability of river ecosystems.

[0081] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the purpose and scope of the technical solution, which should be included in the scope of the claims of the present invention.

Claims

1. A method for identifying core species of microorganisms in a river ecosystem, characterized by: The following steps are involved: Collect the relative abundance data of operational taxonomic units (OTU) of river bacterial plankton; Construct the presence-absence matrix of OTU and calculate the occurrence rate and average relative abundance of each OTU; The ecological importance of OTUs was assessed based on the occupancy-relative abundance relationship; Generate time points based on the year and month of the sample, and calculate the frequency of each OTU at different time points; The number of core OTUs was determined based on the inflection point method and the Bray-Curtis similarity growth rate method.

2. The method for identifying core species of microorganisms in a river ecosystem according to claim 1, characterized in that: The steps of evaluating the ecological importance of OTU based on the occupancy-relative abundance relationship include: Plot the relationship between the logarithmic mean relative abundance and occupancy of OTU; By analyzing the relationship graph, potential core OTUs were identified.

3. The method for identifying core species of microorganisms in a river ecosystem according to claim 1, characterized in that: The step of generating time points based on the year and month of the sample and calculating the frequency of occurrence of each OTU at different time points includes: Generate time points based on the year and month of the sample; Calculate the frequency of occurrence of each OTU at different time points; The consistency of OTUs on a temporal scale is quantified by their frequency on a temporal scale; The consistency and distribution characteristics on the time scale are integrated to generate a sorting index to rank the OTUs.

4. The method for identifying core species of microorganisms in a river ecosystem according to claim 1, characterized in that: The step of determining the number of core OTUs based on the inflection point method and the Bray-Curtis similarity growth rate method includes: Calculate the Bray-Curtis similarity of the top 500 OTUs; The cumulative contribution of each OTU was calculated to identify the OTU with the greatest impact on community similarity; The threshold and range of core OTU were determined based on the inflection point method and the growth rate method.

5. The method for identifying core species of microorganisms in a river ecosystem according to claim 1, characterized in that: The identification method also includes the step of exploring and verifying the combination mechanism of the core taxonomic group using the Sloan neutral model.

6. The method for identifying core species of microorganisms in a river ecosystem according to claim 1, characterized in that: The identification method also includes a step of further determining the representativeness of the core OTU by calculating the actual occurrence frequency of the OTU and comparing it with the upper and lower limits predicted by the model.

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