WO2023209747A1

WO2023209747A1 - Method for determining a metabolic functionality of a bacterial population and apparatus for performing the said method

Info

Publication number: WO2023209747A1
Application number: PCT/IT2023/050112
Authority: WO
Inventors: Andrea CASTAGNETTI; Matteo SOVERINI
Original assignee: Wellmicro S.R.L.
Priority date: 2022-04-29
Filing date: 2023-04-28
Publication date: 2023-11-02
Also published as: IT202200008705A1

Abstract

Computer-implemented method for calculating a metabolic functionality of a bacterial population comprising the step of acquiring information on an analyzed bacterial population, wherein said information comprises an identification of a first plurality of enzymes which are associated with said bacterial population. The method comprises the following steps: selecting an element, compound or microbial function of interest; selecting a plurality of enzymes of interest, wherein said one or more enzymes of interest are directly involved in the production or in the degradation of said element or compound, or they are involved in said microbial function of interest; calculating an abundance of the enzymes of said plurality of enzymes of interest; comparing a value associated with said plurality of enzymes of interest with statistical data obtained from scientific studies.

Description

METHOD FOR DETERMINING A METABOLIC FUNCTIONALITY OF A BACTERIAL POPULATION AND APPARATUS FOR PERFORMING THE SAID METHOD

FIELD OF THE INVENTION

The embodiments described here concern a computer-implemented method for determining microbiota functionality and an apparatus for executing said method.

The method for determining specific metabolic functionalities of a bacterial population described here is used to verify specific metabolisms of interest in a human microbiota.

The apparatus, such as an electronic device for example, or a data processing apparatus in general, comprises means and is configured to execute said method.

In a preferential but non-limiting manner, the method and corresponding apparatus described here can be applied in the nutraceutical sector or in the sector of non-invasive diagnostics to verify a pathological or physiological state of an individual, to predict the efficacy of drugs that directly or indirectly interact with the microbiota or with the metabolites and cytokines released by the microorganisms making up the microbiota, or that their efficacy is in any case influenced by the quali- quantitative composition of the microbiota. BACKGROUND OF THE INVENTION

It is known that a large variety and quantity of microorganisms (fungi, bacteria and viruses) populate districts and/or organs, such as the skin, the oral cavity, the gastro-intestinal tract or suchlike, forming the so-called human microbiota.

In the last twenty years, the number of scientific studies on the microbiota has rapidly increased and has brought to light the importance of these microorganisms in regulating a large number of physiological functions that are crucial in maintaining a good state of health.

Various studies have also highlighted the correlation between the composition of the microbiota of a subject and its physiological or pathological, inflammatory, autoimmune, tumoral, etc. conditions.

In particular, we have seen how the analysis of the microbiota can be used to predict particular altered physiological or pathological states that are not necessarily symptomatic, or to detect partly symptomatic pathological states. For this purpose, various tests are known which provide information on the composition of the microbiota starting from organic samples, such as urine, feces, saliva, etc. samples for example.

Some of these tests can also calculate a metabolic potential, for example when the sample being studied is a fecal sample, based on the presence or absence of certain bacterial taxa.

Moreover, tests aimed at verifying the composition of the microbiota are used to predict the risk of developing a pathological condition, or as a marker for the use of drugs and/or medicines. Current tests that allow to obtain information on the state of health of an individual through the analysis of his/her microbiota use classical methods of cell culture or molecular methods (such as quantitative PCR). These methods allow to determine the presence of a very limited and specific number of bacteria in the microbiota and do not allow to verify the bacterial population of the analyzed biological sample as completely as possible.

One disadvantage of the state of the art is that the systems for determining metabolic potential or, equivalently, metabolic functional information are often inaccurate, since they are based exclusively on information regarding the mere presence/absence of specific bacterial taxa. Another disadvantage is due to the fact that the results of tests carried out on the microbiota are compared with generic and/or outdated scientific literature data, which may not take into account boundary conditions, such as the subject’s ethnicity, age, gender, lifestyle, etc.

Another disadvantage of the state of the art is that without a complete characterization of the microbiota, it is difficult to administer therapies, treatments, diets or suchlike to improve the state of health of the individual by means of actions aimed at re-establishing the correct population of bacterial taxa that have a low presence, or which are excessively present.

Another disadvantage is due to the fact that the state of the art only allows to determine general metabolic functional information and not particular metabolic functional information aimed at verifying a particular physiological or pathological state.

Another disadvantage is due to the fact that the state of the art does not allow to determine a metabolic potential for the production and/or degradation of a certain element or compound.

Another disadvantage is that the state of the art does not allow to concentrate the analysis on a particular microbial functionality and therefore does not allow to obtain detailed information, as in other more expensive and/or invasive tests.

The scientific article Soverini, M. et al. doi:l 0.3389/fmicb.2017.02079 describes the pattern variation of carbohydrate-active enzymes in the intestinal microbiota of healthy subjects and patients with type 2 diabetes. This article describes how a pan-microbiome representative of the “Italian pan-microbiota” is generated, whose genomes are subsequently downloaded from the NCBI repository. Within these genomes, the ORFs (Open Reading Frames) are subsequently identified and, by means of the HMMScan tool, only the carbohydrate-active enzymes (CAZymes) are isolated and characterized.

Document WO 2021/058523 Al discloses a method for highlighting functional heterogeneity in the fermentation capabilities of the healthy human intestinal microbiota. More specifically, this method is used to predict a response to different dietary fibers on the basis of analysis and measurement of the metabolic fermentation capabilities of a subject’s intestinal microbiota.

Document WO 2019/178610 Al discloses a method for metabolism-correlated prediction which includes: generating an enzyme dataset; generating a substrate dataset; generating a metabolism model to predict an enzyme characteristic associated with the metabolism of a query molecule, on the basis of the enzyme dataset and/or the substrate dataset; determining a microorganism taxon associated with the metabolism of the query molecule on the basis of one or more predicted enzyme characteristics of the metabolism model and/or determining a query molecule score for one or more users on the basis of the microorganism taxon.

Document US 2018/357375 Al discloses a method for determining metabolic maps, and identifying the presence and estimating the abundance of the metabolic pathways of the microbiome in an individual for the purpose of a personalized microbial therapy, in particular this known method provides to determine the abundance of a metabolic pathway from a sample comprising a population of a plurality of different organisms.

Document WO 2021/237312 Al discloses a method for in vitro assessment and prognosis for balancing the intestinal microbiota in infants aged between one month and one year, the method being based on an integrated approach, by calculating coefficients of correlation between key indicators, which are divided into three main groups: 1. Correlation between composition and quantity of microorganisms in breast milk and in infant feces; 2. Correlation between enzyme profile and activity of the enzymes responsible for the assimilation and metabolism of milk components (lactose, lipids, oligosaccharides, proteins) in samples of breast milk and infant feces; 3. Correlation between the amount of metabolites obtained from the metabolism of the main components of breast milk from the microbiota in breast milk and in infant feces.

There is therefore the need to perfect a method for determining the functionality of the microbiota and a corresponding apparatus for executing said method, which can overcome at least one of the disadvantages of the state of the art.

In particular, one purpose of the invention is to provide a dynamic method for determining metabolic functional information, that is, a method which is suitable to interpret data of a subject belonging to a community, a subset of the population selected according to criteria of ethnicity, sex, lifestyle or suchlike, for which the average composition of the microbiota may differ substantially from the average data in scientific literature. Another purpose of the invention is to provide a method for determining personalized metabolic functional information on the basis of the patient’s subjective needs.

Another purpose of the invention is to provide a method for determining the metabolic function which considers the metabolic processes involved in detail. The Applicant has devised, tested and embodied the present invention to overcome the shortcomings of the state of the art and to obtain these and other purposes and advantages.

SUMMARY OF THE INVENTION

The present invention is essentially set forth and characterized in the independent claims, while the dependent claims describe other characteristics of the present invention or variants to the main inventive idea.

In accordance with the above purposes, some embodiments described here concern a computer-implemented method for calculating a metabolic functionality of a bacterial population comprising the step of acquiring information on an analyzed bacterial population, wherein the information comprises an identification of a first plurality of enzymes which are associated with the bacterial population.

The method also comprises the following steps: selecting an element, a compound or a microbial function of interest; selecting a plurality of enzymes of interest, wherein the one or more enzymes of interest are directly involved in the production or in the degradation of the element or compound, or they are involved in the microbial function of interest; calculating an abundance of the enzymes of the plurality of enzymes of interest; comparing a value associated with the plurality of enzymes of interest with statistical data obtained from scientific studies.

In accordance with one example of the invention, the information is information on a bacterial population of the microbiota obtained by means of specific analysis, for example analysis of bacterial DNA, of one or each single biological or organic sample originating from an individual.

In accordance with one example of the invention, the method comprises calculating a metabolic potential as the ratio between the abundance of the enzymes of the plurality of enzymes of interest and an abundance of the enzymes belonging to the first plurality of enzymes or to a second plurality of enzymes which are associated with the element, compound or microbial function selected.

In accordance with one example of the invention, said value is the abundance of the plurality of enzymes and/or said value is the metabolic potential.

In accordance with one example of the invention, the calculation of the enzyme abundance and/or of the metabolic potential is used to determine a pathological or physiological condition of the individual as regards the metabolism of the element or compound of interest, or to evaluate a physiological or pathological condition of the microbial function of interest.

In accordance with one example of the invention, the information on a bacterial population comprises information on metabolic pathways which are associated with the bacterial population, wherein the information on the metabolic pathways associated with the bacterial population comprises a list of one or more metabolic pathways which are associated with the bacterial population and the identification of the first plurality of enzymes which are associated with the bacterial population and, therefore, associated with the one or more metabolic pathways.

In accordance with one example of the invention, the metabolic potential is used to evaluate the importance of the metabolism of the element, compound or microbial function within all the metabolisms performed by the bacteria identified in the biological or organic sample, that is, within the plurality of metabolic pathways relating to the microbiota which is associated with the biological or organic sample, wherein the importance of a particular metabolism is used to estimate the quantity of an element or compound produced by the bacterial activity of the microbiota and/or estimate the quantity of an element or compound degraded by the bacterial activity of the microbiota because used by the enzymes during the metabolism itself.

In accordance with one example of the invention, the method comprises a specific analysis of the one or each individual biological or organic sample originating from an individual, wherein the specific analysis comprises: i) extraction of the bacterial DNA found in the organic biological sample; ii) determination of the taxonomic profile to identify the bacterial populations present in the sample; iii) obtaining functional metabolic information of the bacterial community whose taxonomic profile has been determined; wherein the acquisition of the information on a bacterial population of the microbiota is obtained by means of the analysis of the biological or organic sample.

In accordance with one example of the invention, acquiring information on an analyzed bacterial population comprises acquiring information on a taxonomy of bacteria belonging to the bacterial population, wherein the identification of the first plurality of enzymes is based on the taxonomy.

In another example, the bacterial population is analyzed starting from an organic sample originating from an individual.

In another example, the element or compound or the microbial function of interest are selected from at least one of: acetate, propionate, lactate, butyrate, ethanol, TMA, EPS, CH4, H2S H2, NH3, pLactams, kanamycin, streptomycin, cephalosporin, penicillin, chloramphenicol, vitamin Bl, vitamin B2, vitamin B3, vitamin B5, vitamin B6, vitamin B7, indole, quinilonate, GABA, proteolysis, mucolysis. In another example, selecting a plurality of enzymes of interest comprises selecting enzymes that directly produce the element or compound of interest.

In another example, selecting a plurality of enzymes of interest comprises selecting enzymes that directly degrade the element or compound of interest.

In another example, the method comprises calculating a metabolic potential as the ratio between the abundance of the enzymes of the plurality of enzymes of interest and an abundance of the enzymes belonging to the first plurality of enzymes.

In one further example, selecting an element, compound or microbial function of interest comprises identifying a second plurality of enzymes which are associated with the element, compound or microbial function.

In one further example, the method comprises calculating a metabolic potential as the ratio between the abundance of the enzymes of the plurality of enzymes of interest and an abundance of the enzymes belonging to the second plurality of enzymes.

In another example, said value is associated with the abundance of the plurality of enzymes.

In another example, said value associated with the abundance of the plurality of enzymes is the abundance of the plurality of enzymes.

In one further example, said value associated with the abundance of the plurality of enzymes is the metabolic potential.

In another example, comparing the value associated with the abundance of the plurality of enzymes of interest comprises determining a physiological state if the value lies between the tenth and ninetieth percentile of a distribution of the scientific data, optionally, if the value lies between the twentieth and the eightieth percentile.

In one further example, comparing the value associated with the abundance of the plurality of enzymes of interest comprises determining a pathological state if the value lies below the tenth and above the ninetieth percentile of a distribution of the scientific data, optionally, if the value lies below the twentieth and above the eightieth percentile.

According to another aspect of the invention, there is provided an electronic device, or a data processing device in general, comprising a processor, a memory unit configured to store data, and a communication unit, wherein the electronic device is configured to execute a method for calculating a metabolic functionality.

Another aspect described here is a computer program comprising instructions which, when the program is executed by a computer, determine the execution of the method in accordance with the present description.

One further aspect described here is a computer-readable mean comprising instructions which, once executed by a computer, determine the execution of the method in accordance with the present description.

One advantage of the invention is that it provides a dynamic method for determining metabolic functional information, that is, a method which is suitable for interpreting data of a subject belonging to a community, subset of the population, etc. for which the average composition of the microbiota differs substantially from the average data of the scientific literature.

Another advantage of the invention is that it provides a method for determining personalized metabolic functional information on the basis of a patient’s subjective needs.

Another advantage of the invention is that it provides a method for determining the metabolic function which considers the metabolic processes involved in detail.

Moreover, in the method described here, each single biological or organic sample is analyzed and, contrary to the state of the art, for example Soverini et al, no pan-microbiome is generated, and no representative genome is downloaded. Furthermore, the assignment of the functional metabolic potential is related to all possible bacterial metabolic classes, and not just some, such as carbohydrate-active enzymes (CAZymes), for example. Once the functional imputation has been carried out, specific enzymes are selected (based on their E.C. number) which correspond to key points of metabolisms of interest. In this way, the functional potential is defined for each individual sample.

DESCRIPTION OF THE DRAWINGS

These and other aspects, characteristics and advantages of the present invention will become apparent from the following description of some embodiments, given as a non-restrictive example with reference to the attached drawings wherein:

- fig. 1 shows a diagram of a method for determining metabolic functionality according to the state of the art; - fig. 2 shows an example diagram of metabolic pathways starting from a precursor;

- fig. 3 shows a diagram of a method for determining metabolic functionality according to one example of the present invention;

- fig. 4 shows an example diagram of an electronic device. To facilitate comprehension, the same reference numbers have been used, where possible, to identify identical common elements in the drawings. It is understood that elements and characteristics of one embodiment can be conveniently combined or incorporated into other embodiments without further clarifications.

DESCRIPTION OF SOME EMBODIMENTS Fig. 1 shows a generic method, in accordance with the state of the art, used to obtain information relating to a metabolic function, hereafter metabolic functional information. The method provides a step of obtaining SI 00 a sample of biological material from an individual. This biological sample can be, for example, a fecal sample, a sample resulting from a biopsy of an intestinal or gastric tract, a urine sample, a saliva sample, a mucus sample obtained from the oro-rhino-pharyngeal cavity, a skin biopsy sample and suchlike.

The person of skill in the art will understand that the method described below can also be performed on any substance produced, secreted or excreted from the body of an individual and/or on any biological sample originating from any district, apparatus, organ or tissue of an individual’s body.

The method in accordance with the embodiments described here is described in relation to a human being; however, it can be performed in the same way using a biological sample originating from an animal.

Once the biological sample has been obtained, the method proceeds with the step of extracting S I 10 the bacterial DNA found in the sample. For a correct isolation of the bacterial DNA, it is preferable to homogenize, optionally using a homogenizer, the sample, a part of which will later be used for the extraction of the bacterial DNA.

The sample amount used for the extraction step should be at least equal to the detection or sensitivity limit of the methodology and/or of the apparatuses used to amplify the DNA. Optionally, the sample amount used for the extraction step ranges from 100 to 500 mg, more preferably from 200 to 400 mg, even more preferably a sample amount of about 250 mg is used. The DNA is extracted, using known techniques, from cells duly obtained from the homogenized sample. The basic procedure comprises disrupting the cell membrane resulting in the exposure of cell contents, including DNA, by using chemical substances or by agitation of a solution containing salts and denatured proteins. Following the rupture of the cell membrane, the solution is centrifuged in order to separate the DNA from compounds with a lower weight, such as proteins, lipids, or RNA. The RNA can also be eliminated by using enzymes suitable for this purpose.

The DNA is then extracted by precipitation with alcohols, preferably issopranol, and further centrifugation. The person of skill in the art will understand that DNA extraction can also be obtained by using other methodologies or variations of the methodology described above.

Once the DNA has been extracted, the method provides the step of determining S 120 the taxonomic profile in order to identify the bacterial populations present in the sample. By taxonomic profile we mean the classification of bacteria according to phylum, class, order, family, genus and/or species.

The step of determining S 120 the taxonomic profile comprises the amplification of at least one portion of the 16S rRNA gene by polymerase chain reaction (PCR) and DNA sequencing. The techniques used in the determination step S 120 will not be described here, since they are known to the person of skill in the art.

The taxonomic profile is determined SI 20 on the basis of the amplicon-related sequences of the 16S rRNA gene. These sequences are used as input for computer- implemented models which allow to reconstruct the metabolic profile, in other words obtain functional metabolic information S130, of the bacterial community whose taxonomic profile has been obtained.

One of these models is represented by the PICRUSt2 code which receives at input the sequences relating to the amplicons of the 16S rRNA gene of the bacterial population of the sample, and returns as output functional information, that is, information on the metabolisms in which the bacteria of the bacterial population identified are involved.

By metabolisms we mean the metabolic pathways, that is, the set of chemical reactions, enzymes involved, elements or compounds produced or degraded by a bacterium. In biochemistry, a sequence of enzyme-mediated chemical reactions that occur within a cell is called a metabolic pathway. In each metabolic pathway, starting from a precursor element or compound, at least one end product is produced through the action of one or more enzymes. In the transition between the precursor and the end product(s), a plurality of intermediate products, which can serve as a substrate for another chemical reaction of a metabolic pathway, are created. In other words, the metabolic pathway is a set of interrelated chemical reactions which, starting from one or more initial elements or compounds, produce one or more end elements or compounds. If a metabolic pathway needs an input of external energy in order to reach the end products, starting from the initial elements or compounds, this is referred to as an anabolic pathway. If a metabolic pathway produces energy, this is instead referred to as a catabolic pathway.

A metabolic pathway consists of a plurality of chemical reactions that can be promoted, facilitated or made possible by the presence of one or more enzymes.

The enzymes act as accelerators of the chemical reactions of the metabolic pathways, transforming a substrate (initial element or compound) into an end product (element or compound). A substrate can be used by one or more enzymes to produce one or more end products. In other words, starting from a single precursor element or compound, a plurality of end products can be formed, through the action of enzymes, by means of an interconnected network of chemical reactions mediated by enzymes.

Fig. 2 shows a simplified example of the transformation of a precursor product P, hereafter simply precursor P, by a plurality of enzymes identified by arrows. In the drawing, the precursor P is the substrate for a plurality of enzymes 100- 1, 100-2, 100-3, and 100-N by means of which the intermediate products Ii,i, h , h,3, and h,N, respectively, are metabolized.

The intermediate products Ii.i, h.i, I23, and h,N can in turn serve as substrates for other enzymes, leading to the production of further intermediate products, such as I1 , h,2, b,2, Ii, MI, Ii, M2, 13,M3, and IN, 2.

An intermediate product can be produced by two enzymes that use two different substrates, as shown in the drawing for the intermediate product 11,3 produced by the enzymes 100-4 and 100-5 that use the substrate Ii,i and 12,1, respectively, or the intermediate product h,2 produced by the enzymes 100-7 and 100-8 that use the substrate 13,1 and IN,I, respectively.

Similarly, it may happen that an intermediate product, for example h.i, is used by two different enzymes, for example 100-5 and 100-6, for the production of two different intermediate products 11,3 and 12,2.

Ultimately, the sequence of chemical reactions which lead from a certain precursor P to a certain end product such as Fi, F2, F3, FL can involve a plurality of enzymes which metabolize a plurality of intermediate products until the end product is reached. Each unique sequence of precursor, enzymes, intermediate products, and end product is defined as a metabolic pathway. In the case of fig. 2, a plurality of metabolic pathways is shown, each of which consists of a particular pathway that links the precursor and the end product through a plurality of enzymes and intermediate products. In the method of the state of the art described, one or more metabolic pathways are determined in which the bacteria identified in the organic sample are involved.

In this way, the method of the state of the art determines the metabolic functional information, that is, which elements or compounds are produced or degraded by the bacteria identified in the organic sample taken or the microbial functions performed by the bacteria.

The method of the state of the art allows to obtain a general description of the total metabolism of all the bacteria present in the microbiota of an individual, but it does not allow to know the metabolic functionality (production or degradation) connected with the production or degradation of single chemical elements or compounds, or with a specific microbial function of interest.

In order to obtain information on how a particular metabolism or a certain microbial function operate, the method described in relation to fig. 3 was developed.

We will now refer in detail to the possible embodiments of the invention, one or more examples of which are shown in the attached drawings by way of a nonlimiting example. The phraseology and terminology used here is also for the purpose of providing non-limiting examples.

Fig. 3 is used to describe some embodiments of a computer-implemented method for predicting a metabolic functionality of the microbiota according to one example of the invention.

A first step of the method comprises acquiring S 135 functional information on an analyzed bacterial population. Such information on a bacterial population can be information on a bacterial population of the microbiota obtained by analyzing an organic sample originating from an individual, as described in the method of the state of the art with reference to fig. 1.

For example, the information on a bacterial population comprises information on the metabolic pathways which are associated with the bacterial population and can be the result of a method used in the state of the art, such as the one described in relation to fig. 1.

The information on the metabolic pathways which are associated with the bacterial population comprises a list of the one or more metabolic pathways associated with the bacterial population and an identification of a first plurality of enzymes associated with the bacterial population or, likewise, associated with the one or more metabolic pathways.

Databases are known which contain information on the main metabolic pathways, in other words on the enzymes, precursors, products of the chemical reactions, both final and intermediate, involved in such metabolic pathways.

An example of these databases is the KEGG pathway database, which allows to obtain information on the different metabolic pathways used by living organisms. This information contains, for example, a list of the metabolic pathways and a list of the enzymes involved in each of the metabolic pathways. In one example, this database can also be generated by the method of the state of the art described in fig. 1. In other words, the output of the step of determining the metabolic functional information S130 can provide functional information on one or more metabolic pathways which are associated with an analyzed bacterial population, where this information is a list of the metabolic pathways and contains an identification of all the enzymes involved in said one or more metabolic pathways, defined above as first plurality of enzymes.

In more detail, in the example disclosed above, the output of the step of determining the metabolic functional information S 130 of the method of the state of the art described in relation to fig. 1 provides a list of N metabolic pathways Mi which are connected with the bacteria identified in the biological sample. In other words, the output of the step of determining the metabolic functional information SI 30 of the method described in relation to fig. 1 returns a set of {Mi} metabolic pathways with i = 1, ..., N which can be used as input in the step of acquiring functional information SI 35.

The output of the step of determining the metabolic functional information SI 30 also comprises information, that is, an identification, on precursors, enzymes, intermediate products and end products of each metabolic pathway which is contained in the set of metabolic pathways {Mi}.

A subsequent step of the method comprises selecting an element, compound or microbial function of interest S 140.

By element or compound of interest we mean an element or compound produced or degraded by bacteria of the microbiota and of interest for the study of a particular metabolism of an individual’s microbiota. The element or product of interest can be a precursor, an intermediate product, or an end product of a metabolic pathway.

By microbial function we mean a function of the bacteria of the microbiota in creating or transforming a particular element or compound, for example carbohydrate metabolism, protein metabolism, lipid metabolism, production of short-chain fatty acids, mucolysis, etc.

In the step of selecting an element, compound or microbial function of interest S 140, that is, one for which the metabolism is to be studied, the element, compound or microbial function can be selected from: acetate, propionate, lactate, butyrate, ethanol, TMA, LPS, CH4, H2S H2, NH3, ^Lactams, kanamycin, streptomycin, cephalosporin, penicillin, chloramphenicol, vitamin Bl, vitamin B2, vitamin B3, vitamin B5, vitamin B6, vitamin B7, indole, quinilonate, GABA, proteolysis, mucolysis.

It is possible to study the production of these elements, compounds or microbial functions, for example the production of at least one of: acetate, propionate, lactate, butyrate, TMA, LPS, CH4, H2S H2, NH3, vitamin Bl, vitamin B2, vitamin B3, vitamin B5, vitamin B6, vitamin B7, indole, quinilonate, GABA.

It is also possible to study the consumption of these elements, compounds or microbial functions, for example the consumption of at least one of: acetate, propionate, lactate, butyrate, ethanol, vitamin Bl, vitamin B2, vitamin B3, vitamin B5, vitamin B6, vitamin B7, proteolysis, mucolysis.

It is also possible to study the antibiotic resistance of these elements, compounds or microbial functions, for example the resistance to at least one of: [BLactams, kanamycin, streptomycin, cephalosporin, penicillin, chloramphenicol.

Once the element, compound, or microbial functionality of interest has been selected SI 40, the method can continue with the step of identifying a second plurality of enzymes SI 50 which involve the production or degradation of the element or compound, or which involve said microbial function, for example bacterial resistance. It will be clear to the person of skill in the art that the second plurality of enzymes is comprised in the first plurality of enzymes.

The information on the first and second plurality of enzymes is closely linked to the metabolic pathways associated with an analyzed bacterial population.

In one example of the invention, the step of selecting an element, compound or metabolic function SI 40 therefore allows to carry out the step of identifying a second plurality of enzymes SI 50 which are involved in one or more metabolic pathways {Mi}, subset of {Mi}, which are associated with the element, compound or microbial function selected. In other words, one or more metabolic pathways {Mi} in which the element or compound appears as a precursor, intermediate product or end product.

An element, compound or microbial function can be associated with more than one metabolic pathway, for example an element or compound can be present in a plurality of metabolic pathways either as a precursor, intermediate product or end product. For simplicity, the first plurality of enzymes or the second plurality of enzymes will be referred to hereafter as the enzyme set {Ej}.

In other words, the second plurality of enzymes consists of all the enzymes involved in the set of metabolic pathways {Mi}, that is, in the set of metabolic pathways in which the compound or element appears, or which are used for the microbial function of interest.

For this reason, defining the set of metabolic pathways {Mi} and therefore the second plurality of enzymes is an advantageous characteristic, since it limits the number of enzymes to be considered with respect to the totality of enzymes which are associated with the bacterial population, the first plurality of enzymes, and which are not directly or indirectly involved with the element, compound or microbial function.

We must clarify that the step of identifying the second plurality of enzymes S 150 is an optional and not necessary step of the method described here.

To explain the difference between the first plurality of enzymes and the second plurality of enzymes we refer to fig. 2, which shows a plurality of metabolic pathways which degrade a precursor P to create a plurality of end products Fi, F2, F3, ..., FL. This plurality of metabolic pathways can be considered as the functional information described in detail above.

In connection with fig. 2, the first plurality of enzymes associated with the plurality of metabolic pathways comprises a list of all the enzymes involved in all the metabolic pathways that lead from the precursor P to each end products F.

For simplicity, a partial example of the first plurality of enzymes associated with the metabolic pathways that produce Fi starting from P will be given. This partial example of the first plurality of enzymes comprises the list of the following enzymes: 100-1, 100-4, 101-1, 100-2, 100-5, 101-1, 100-2 100-6, 101-2, 100-3, 100-7, 100-10, 101-3, 100-N 100-8, 100-10, 101-3, 100-N, 100-9, 101-3.

The person of skill in the art will understand that this list has to be compiled for each metabolic pathway shown in fig. 2 in order to obtain the first plurality of enzymes, that is, the plurality of enzymes also contains the enzymes marked with two dashed arrows in the drawing.

We must clarify that the above list contains a list of the enzymes involved, in which some enzymes are repeated more than once. This repetition gives information on the presence of this enzyme in all metabolic pathways which are associated with the bacterial population of the sample analyzed.

Again, with reference to fig. 2, an example of a second plurality of metabolic pathways will be given.

If in the step of selecting an element, compound, or microbial function of interest SI 40 the end product Fi is selected as the element or product of interest, identifying a second plurality of enzymes SI 50 means identifying only a plurality of metabolic pathways that start from the precursor P and arrive at the end product Fi. This corresponds to the partial list disclosed above in exemplifying a part of the first plurality of enzymes.

In other words, the second plurality of enzymes is a subset of the first plurality of enzymes and contains only the enzymes involved in those metabolic pathways in which the element or compound of interest selected in the selection step SI 40 appears as a precursor, intermediate product or end product.

The second plurality of enzymes also comprises information regarding the number of repetitions in which the enzyme appears in the metabolic pathways associated with the second plurality of enzymes.

Such information regarding the number of repetitions can consist of an integer that reflects the number of repetitions, or such information can be conveyed by means of a repetition of the identifier of the enzyme that is repeated within the second plurality of enzymes, as seen in the example concerning the first plurality of enzymes.

The method also provides a step of selecting a plurality of enzymes of interest SI 60 in which a set of enzymes {E*_m} comprised in the first plurality of enzymes or in the second plurality of enzymes is selected.

This set of enzymes {E*_m} , the plurality of enzymes of interest, exclusively comprises those enzymes that directly produce the element or compound of interest, or those enzymes that directly degrade the element or compound of interest, that is, enzymes for which the element or compound of interest is the substrate. Additionally, the plurality of enzymes of interest can comprise enzymes that are present in a crucial branch of a metabolic pathway in which the element or compound is the end product or precursor.

In other words, by enzymes of interest we mean those enzymes which are directly involved in the production or degradation of the element or compound of interest, that is, those enzymes which directly produce the element or compound of interest or those enzymes which use the element or compound of interest as a substrate.

In addition, by enzymes of interest we also mean those enzymes which are involved in a branch of the metabolic pathway that is crucial for the production of the element or compound of interest, when the latter is an end product of the metabolic pathway.

It will be clear that the enzyme set {E*_m}, the plurality of enzymes of interest, is a subset of the enzyme set {Ej}, that is, the first or second plurality of enzymes, depending on whether the step of identifying a second plurality of enzymes SI 50 is performed or not.

With reference to fig. 2, if the element or compound of interest is the intermediate product h,i, the enzymes of interest are the enzyme 100-2 which produces h.i and the enzymes 100-5 and 100-6 which degrade h,i in Ii,3 and h,2, respectively. In other words, in this case, the plurality of enzymes of interest comprises the enzymes 100-2, 100-5 and 100-6.

Again, with reference to fig. 2, a crucial branch of the metabolic pathway to create the final product FL comprises, in order, the precursor P, the enzyme 100- N, the intermediate product I_n,i, the enzyme 100-9, the intermediate product IN, 2 and the enzyme 100- 11.

In other words, in this case, the plurality of enzymes of interest comprises the enzymes 100-N, 100-9, and 100-11. A list of the enzymes of the plurality of enzymes of interest is generated and contains an identifier of the enzymes of interest conforming to one or more enzyme classification methods. Advantageously, the enzymes are classified and identified on the basis of the EC (Enzyme Commission) numbers. The plurality of enzymes of interest, the set {E*_m}, maintains the information regarding the frequency of appearance of each enzyme, that is, the number of times in which the enzyme identifier appears in the first plurality of enzymes or the second plurality of enzymes, the enzyme set {Ej}.

In another example, the step of selecting the plurality of enzymes of interest SI 60 comprises determining a list of such enzymes which contains only the enzymes involved in the production of the element or compound, when the element or compound is an end product.

In another example of the invention, the element or compound of interest corresponds to an intermediate product of one or more metabolic pathways.

In this case, the element or compound of interest can be viewed as a substrate of an enzyme or a product of another enzyme. For example, in fig. 3, the intermediate product h,i is substrate for enzymes 100-5 and 100-6, and it is a product of enzyme 100-2. In this case, the step of selecting the plurality of enzymes of interest SI 60 comprises identifying the enzymes which contribute to the degradation of the metabolite of interest, such as enzymes 100-5 and 100-6, or those which contribute to its formation, such as enzyme 100-2.

In one example, the step of selecting the plurality of enzymes of interest SI 60 comprises determining a list of only the enzymes that are involved in the production of the element or compound, when the element or compound is an intermediate product.

In another example, the step of selecting the plurality of enzymes of interest S 160 comprises determining a list only of the enzymes which are involved in the degradation of the element or compound, when the element or compound is an intermediate product.

In a further example, the step of selecting the plurality of enzymes of interest SI 60 comprises determining a list of the enzymes which are involved in the degradation or production of the element or compound, when the element or compound is an intermediate product. In a further example of the invention, the step of selecting the plurality of enzymes of interest SI 60 comprises determining a list of the enzymes which are involved in performing a certain microbial function.

The list of enzymes obtained in the step of selecting the plurality of enzymes of interest S 160 is used for the step of calculating S 180 the metabolic potential of one or more enzymes.

The step of calculating the metabolic potential SI 80 is preceded by the step of calculating the enzyme abundance SI 70 of the enzymes of interest.

The step of calculating the enzyme abundance SI 70 comprises calculating an abundance of one or more enzymes of the plurality of enzymes of interest {E*_m} with respect to the total amount of enzymes present in the metabolic pathways which are associated with the bacterial population obtained from the study of the organic sample, for example by means of the method described in fig. 1 or by means of other equivalent methods.

A quantity that defines the enzyme abundance of the enzymes of interest {E*_m} is obtained by summing’ the frequencies with which each enzyme E*_m appears in the enzyme set {E*_m}, the plurality of enzymes of interest.

If the frequency of an enzyme E*_m is defined as g(E*_m), the sum S* of the frequencies of the enzymes of the enzyme set {E*_m} is defined as S* = The quantity S* defines the enzyme quantity or abundance of the enzymes of interest {E*_m}.

In order to calculate the metabolic potential SI 80, the quantity S* is compared with an enzyme abundance relating to the totality of enzymes present in the metabolic pathways which are associated with the bacterial population.

By totality of enzymes we mean the enzymes comprised in the first or second plurality of enzymes, hereafter simply indicated with the enzyme set {Ej}.

In particular, a quantity is obtained that defines the enzyme abundance of the totality of enzymes belonging to the enzyme set {Ej}, by summing the frequencies with which each enzyme identifier appears in the enzyme set {Ej}.

If the frequency of an enzyme Ej is defined as f(Ej), the sum T of the frequencies of all the enzymes is defined as

The quantity T defines the enzyme abundance of the totality of enzymes that belong to the enzyme set {Ej}, that is, to the first plurality of enzymes or to the second plurality of enzymes, depending on which plurality of enzymes was considered to carry out the calculation.

The ratio between the enzyme abundance S* of the enzymes of interest and the enzyme abundance T of the total enzymes returns a value, called metabolic potential MP, which allows to evaluate the importance of the metabolism of the element, compound or microbial function within all the metabolisms performed by the bacteria identified in the organic sample.

If the metabolic potential of interest is defined as MP, MP is defined as the ratio between the quantity of enzymes of interest and the quantity of total enzymes, that is, MP = -.

This metabolic potential is a percentage number and schematically corresponds to the importance of a particular metabolism within the plurality of metabolic pathways related to the microbiota.

Knowing the importance of a particular metabolism allows to estimate the quantity of an element or compound produced by the bacterial activity of the microbiota. Equally, knowing the importance of a particular metabolism allows to estimate the quantity of an element or compound degraded by the bacterial activity of the microbiota, since it is used by enzymes during the metabolism itself.

Optionally, the metabolic potential MP ratio can be obtained for two metabolisms, that is, two sets of enzymes of interest {E*_m} and {E*_p}. With the same procedure described above, MP_m and MP_p can be obtained, considering as numerators of the ratio of MP_m and MP_p respectively the sum

and the

In this way, the metabolic potentials of two metabolic pathways are obtained, and a comparison between the two potentials MP_m and MP_p can be obtained.

The method also provides the step of comparing SI 90 a value associated with the plurality of enzymes of interest, for example the enzyme quantity or abundance of the enzymes of interest, with statistical data obtained from scientific studies.

Alternatively, the step of comparing SI 90 comprises comparing a value associated with the plurality of enzymes of interest which is a metabolic potential MP with metabolic potential data obtained from scientific studies.

For the purposes of this method, a value associated with the plurality of enzymes of interest, be it an enzyme abundance S* or a metabolic potential MP, is considered to be average, and therefore associated with a physiological and non- pathological condition, if it falls between the tenth and ninetieth percentile of the data present in the literature. Optionally, the value is associated with a physiological and non-pathological condition if it is comprised between the twentieth and eightieth percentile of the data present in the literature.

On the contrary, if it is associated with values that are lower than the tenth percentile or higher than the ninetieth percentile of the data present in the literature, the value is linked to a pathological condition. Optionally, the connection of the value to a pathological condition occurs if the value is associated with a value lower than the twentieth percentile and higher than the eightieth percentile of a set of data present in the literature. Optionally, the comparison step SI 90 is performed using scientific literature data relating to a set of individuals belonging to a particular ethnic group, gender, age group, or group of individuals who share a particular lifestyle, etc.

The calculation of the enzyme abundance and/or of the metabolic potential allows to determine a pathological or physiological condition of the individual as regards the metabolism of the element or compound of interest, or to evaluate a physiological or pathological condition of the microbial function of interest.

Advantageously, in the method described here each single biological or organic sample originating from an individual is analyzed in order to then acquire, from this analysis, information on a bacterial population of the microbiota. Therefore, in the method described here and contrary to the state of the art, for example Soverini et al, no pan-microbiome is generated, and no representative genome is downloaded. Moreover, the assignment of functional metabolic potential is related to all possible bacterial metabolic classes and not just to some, such as carbohydrateactive enzymes (CAZymes) for example, as described in Soverini et al.

Once the functional imputation has been performed, specific enzymes are selected (based on their EC number) that correspond to key points of metabolisms of interest. In this way, the functional potential is defined for each individual sample.

Please note that the Enzyme Commission (EC) number is a numerical classification scheme for enzymes, which is based on the chemical reactions they catalyze. As an enzyme nomenclature system, each EC number is associated with a recommended name for the corresponding reaction catalyzed by the enzyme. EC numbers do not specify enzymes but enzyme-catalyzed reactions and, consequently, their functions.

It is clear to the person of skill in the art that the method described, relating to fig. 3, can be used to obtain a large amount of information from multiple individuals in order to form a dataset to be used, after statistical analysis, as a reference for a test that adopts the same method.

The method described above is performed by a computer, a data processing apparatus or any electronic calculation device 200 whatsoever, shown schematically in fig. 4. The electronic device 200 comprises at least one of either a computer, a smartphone, a tablet, a portable computing system, a medical, chemical or biological analysis device, a console, or any other electronic device whatsoever having computing capabilities.

The electronic computing device 200, hereafter electronic device 200, comprises at least one processor, or CPU, 210, and various units including a memory unit 220 for recording data and operating commands for executing a code, optionally one or more electronic databases, a communication unit 230 configured to allow communication between the processor 210 and an external device or between the processor 210 and an internal unit of the electronic device 200, for example between the processor 210 and the memory unit 220 or between the processor 210 and the communication unit 220 and auxiliary (or I/O) circuits (not shown). Optionally, the electronic device 200 comprises an interface unit, not shown in the drawings. The interface unit can be any element or device whatsoever able to provide information to an operator, such as visual, tactile, sound information, etc. The interface unit can be able to receive input from a user and to transmit that input to the processor 210 by means of the communication unit 230. The interface unit can consist of a screen, a touchscreen or suchlike.

The processor 210 is configured to control each individual unit of the electronic device 200 and to execute commands saved permanently or temporarily in the memory 210, and/or to process data and/or information saved in the memory 210.

The memory unit 220 consists of any physical medium which allows to store data such as a hard disk, a solid-state memory, an optical memory medium and suchlike, or any other form of digital storage, local or remote. The memory unit 220 can also be a unit that is external to the device and connected to the processor 210 through the communication unit 230. This memory unit 220 external to the electronic device 200 can also be comprised in an external server (not shown in the drawings) and connected to the processor 210 through the communication unit 230 via the Internet.

Software instructions and data can for example be coded and stored in the memory unit 220 in order to command the processor 210. Auxiliary circuits can also be connected to the processor 210 in order to assist the processor in a conventional manner. The auxiliary circuits can include, for example, at least one of either: cache circuits, power supply circuits, clock circuits, input/output circuitry, subsystems and suchlike. A program (or computer instructions) readable by the electronic device 200 can determine which tasks are feasible in accordance with the method according to the present disclosure. In some embodiments, the program is a software readable by the electronic device 200. The electronic device

200 includes a code for generating and storing information and data entered or generated in the course of the method in accordance with the present disclosure.

The communication unit 230 is configured to allow the processor 210 to communicate with the other units of the electronic device 200, or with external electronic devices or units. The communication can occur both through the transmission of electrical signals by means of a physical medium, such as a cable, a wire and suchlike, as well as in wireless mode, using short-range communication protocols, such as inductive coupling, capacitive coupling, NFC, RFID and suchlike, medium range communication protocols, such as Bluetooth and suchlike, long range communication protocols using radio frequencies. Communication can also occur by means of a LAN internet connection or in wireless mode.

Hereafter, we will refer to the processor 210 and the electronic device 200 interchangeably. The person of skill in the art will understand, when reference is made to the electronic device 200, which units of the electronic device are involved in the execution of each function.

The electronic device 200, in carrying out the method described with reference to fig. 3, to which we refer for further details, reads a first database registered in the memory unit 220 or, alternatively, registered in one or more external servers in communication with the electronic device 200 through the communication unit 230.

The first database comprises information relating to a plurality of metabolic pathways. For each metabolic pathway, the information comprises information on the enzymes involved in the metabolic pathway, elements or compounds used as a substrate by the enzymes or which have been produced by the enzymes, the energy created or used by each chemical reaction of the metabolic pathway and suchlike.

The information on the enzymes can be information related to their classification, such as EC numbers. An example of a database used in this method, and which comprises the information on a plurality of metabolic pathways, is the KEGG pathway database. The person of skill in the art will understand that any other database which allows to obtain the above mentioned information can be used, without compromising the protective purpose of the invention. The processor 210 is configured to acquire S135 functional information on an analyzed bacterial population, that is, information relating to a first plurality of enzymes, from the database.

Optionally, the database is the result of another method executed by the processor 210 or by an external electronic device connected to the electronic device 200, or it is entered manually by a user, for example by means of the interface unit.

The memory unit 220 can also contain data relating to elements or compounds of metabolic interest such as, for example, a list comprising the names of at least the elements or compounds or the microbial functions: acetate, propionate, lactate, butyrate, ethanol, TMA, LPS, CH4, H2S H2, NH3, [BLactams, kanamycin, streptomycin, cephalosporin, penicillin, chloramphenicol, vitamin Bl, vitamin B2, vitamin B3, vitamin B5, vitamin B6, vitamin B7, indole, quinilonate, GABA, proteolysis, mucolysis.

The processor 210 is configured to select SI 40 an element, compound or microbial function of interest from such list.

The processor 210 can select S 140 the element, compound or microbial function on the basis of an input entered by a user on the user interface.

Alternatively, processor 210 selects the element, compound or microbial function on the basis of selection information that is pre-recorded in the memory unit 210.

In another example of the invention, the processor 210 executes the selection on the basis of an input entered by an operator, optionally through the interface unit.

In another example of the invention, the processor 210 executes the selection on the basis of a result of a code executed by the processor 210.

Optionally, the processor 210 is configured to identify SI 50 a second plurality of enzymes SI 50 which involve the production or degradation of the element or compound of interest, or which involve the microbial function, for example bacterial resistance. It will be clear to the person of skill in the art that the second plurality of enzymes is comprised in the first plurality of enzymes.

For brevity, we refer to the discussion relating to the method shown in fig. 3 in relation to the characteristics of the first and second plurality of enzymes and their differences.

The processor 210 is configured to select a plurality of enzymes of interest S 160 exclusively comprising those enzymes that directly produce the element or compound of interest, or those enzymes that directly degrade the element or compound of interest, that is, enzymes for which the element or compound of interest is the substrate. Additionally, the plurality of enzymes of interest can comprise enzymes that are present in a crucial branch of a metabolic pathway in which the element or compound is the end product or precursor.

Once the plurality of enzymes of interest has been selected, the processor 210 records information relating to the plurality of enzymes of interest in the memory 220.

Such list relating to the plurality of enzymes of interest comprises at least one classifier of each enzyme, for example this list can comprise at least the EC number of each enzyme of the list.

The list of enzymes also contains information relating to the frequency with which each enzyme appears in the one or more metabolic pathways. For further details, we refer to the description of the general method shown in fig. 3.

The list can be recorded on a server or electronic device that is external to the electronic device 200.

Subsequently, the processor calculates SI 70 an enzyme abundance of the enzymes present in the list and the metabolic potential according to the method disclosed in connection with fig. 3 and to which we refer.

When the enzyme abundances for each enzyme present in the list of enzymes of interest have been obtained, the processor 210 calculates SI 80 the metabolic potential in order to obtain an indication of the importance of a metabolic pathway within the total metabolism of the microbiota. For the calculation of the metabolic potential, we refer to the detailed description disclosed in relation to fig. 3.

The processor 210 compares SI 90 the enzyme abundance value or the metabolic potential with scientific literature data and obtains a determination of a physiological or pathological condition, as set forth in the description of the method.

The method also allows to predict the efficacy of drugs that interact, directly or indirectly, with the microbiota or with the metabolites and cytokines released by the microorganisms that make up the microbiota.

In fact, if the composition of the microbiota is known, it is possible to infer, from data present in scientific literature, information on possible interactions between drugs or food supplements and the microbiota, or between drugs or food supplements and products of the microbiota’s metabolism.

The scientific literature data can be recorded in the memory unit 220 or on an external server connected to the electronic device 200 through the communication unit 230.

Some embodiments can provide the execution of various phases, steps and operations, as described above. These phases, steps and operations can be performed with instructions executed by a machine which cause the execution of certain steps by a general-purpose or special-purpose processor. Alternatively, such phases, steps and operations can be performed by specific hardware components that contain hardware logic for performing the steps, or by any combination of programmed computer components and customized hardware components.

Some embodiments of the method in accordance with the present disclosure may be included in a computer program storable in a computer-readable mean that contains instructions which, once executed by the electronic device 200, determine the execution of the method disclosed here. In particular, some elements according to the present invention can be provided as machine-readable means for storing the machine-executable instructions. The machine-readable means can include, but are not limited to, floppy disks, optical disks, CD-ROMs, magneto-optical disks, ROMs, RAMs, EPROMs, EEPROMs, optical or magnetic cards, propagation means, or other types of machine-readable means which are suitable to store electronic information. For example, the present invention can be downloaded as a computer program that can be transferred from a remote computer (for example a server) to a requesting computer (for example a client) by means of data signals created with wave carriers or other propagation means, via a communication link (for example a modem or a network connection). It is clear that modifications and/or additions of parts and/or steps may be made to the method and apparatus as described heretofore, without departing from the field and scope of the present invention, as defined by the claims.

It is also clear that, although the present invention has been described with reference to some specific examples, a person of skill in the art will be able to achieve other equivalent forms of method and apparatus, having the characteristics as set forth in the claims and hence all coming within the field of protection defined thereby.

In the following claims, the sole purpose of the references in brackets is to facilitate reading and they must not be considered as restrictive factors with regard to the field of protection claimed in the specific claims.

Claims

1. Computer-implemented method for calculating a metabolic functionality of a bacterial population comprising the step of:

- acquiring (SI 35) information on an analyzed bacterial population, wherein said information comprises an identification of a first plurality of enzymes which are associated with said bacterial population, wherein said information is information on a bacterial population of the microbiota obtained by means of specific analysis of bacterial DNA of one or each individual biological or organic sample originating from an individual; characterized in that it comprises the following steps:

- selecting an element, a compound or a microbial function of interest (SI 40);

- selecting a plurality of enzymes of interest (SI 60), wherein said enzymes of interest are directly involved in the production or in the degradation of said element or compound, or they are involved in said microbial function of interest; - calculating an abundance (SI 70) of the enzymes of said plurality of enzymes of interest;

- calculating a metabolic potential (S 180) as the ratio between said abundance of the enzymes of said plurality of enzymes of interest and an abundance of the enzymes belonging to said first plurality of enzymes or to a second plurality of enzymes which are associated with said element, compound or microbial function selected;

- comparing (SI 90) a value associated with said plurality of enzymes of interest with statistical data obtained from scientific studies, wherein said value is said abundance of said plurality of enzymes and/or said value is said metabolic potential.

2. Method as in claim 1, characterized in that said calculation of the enzyme abundance (SI 70) and/or of the metabolic potential (SI 80) is used to determine a pathological or physiological condition of the individual as regards the metabolism of said element or compound of interest, or to evaluate a physiological or pathological condition of said microbial function of interest.

3. Method as in claim 1 or 2, characterized in that said information on a bacterial population comprises information on metabolic pathways which are associated with said bacterial population, wherein said information on metabolic pathways associated with said bacterial population comprises a list of one or more metabolic pathways which are associated with said bacterial population and said identification of said first plurality of enzymes which are associated with said bacterial population and, therefore, associated with said one or more metabolic pathways.

4. Method as in claim 1, 2 or 3, characterized in that said metabolic potential is used to evaluate the importance of the metabolism of said element, compound or microbial function within all the metabolisms performed by the bacteria identified in said biological or organic sample, that is, within the plurality of metabolic pathways relating to the microbiota which is associated with said biological or organic sample, wherein said importance of a particular metabolism is used to estimate the quantity of an element or compound produced by the bacterial activity of the microbiota and/or estimate the quantity of an element or compound degraded by the bacterial activity of the microbiota because used by the enzymes during the metabolism itself.

5. Method as in any claim hereinbefore, characterized in that acquiring (SI 35) information on an analyzed bacterial population comprises acquiring information on a taxonomy of bacteria belonging to said bacterial population, wherein said identification of said first plurality of enzymes is based on said taxonomy.

6. Method as in any claim hereinbefore, characterized in that said bacterial population is analyzed starting from an organic sample originating from an individual.

7. Method as in any claim hereinbefore, characterized in that said element or compound or said microbial function of interest are selected (SI 40) from at least one of: acetate, propionate, lactate, butyrate, ethanol, TMA, LPS, CP , H2S H2, NH3, pLactams, kanamycin, streptomycin, cephalosporin, penicillin, chloramphenicol, vitamin Bl, vitamin B2, vitamin B3, vitamin B5, vitamin B6, vitamin B7, indole, quinilonate, GABA, proteolysis, mucolysis.

8. Method as in any claim hereinbefore, characterized in that selecting a plurality of enzymes of interest (S 160) comprises selecting enzymes that directly produce said element or compound of interest.

9. Method as in any claim hereinbefore, characterized in that selecting a plurality of enzymes of interest (S 160) comprises selecting enzymes that directly degrade said element or compound of interest.

10. Method as in any claim hereinbefore, characterized in that selecting an element, compound or microbial function of interest (SI 40) comprises identifying said second plurality of enzymes (SI 50).

11. Method as in any claim hereinbefore, characterized in that said value is associated with said abundance of said plurality of enzymes.

12. Method as in any claim hereinbefore, characterized in that comparing (SI 90) said value associated with said abundance of said plurality of enzymes of interest comprises determining a physiological state if said value lies between the tenth and ninetieth percentile of a distribution of said scientific data, optionally, if said value lies between the twentieth and the eightieth percentile.

13. Method as in any claim hereinbefore, characterized in that comparing (S 190) said value associated with said abundance of said plurality of enzymes of interest comprises determining a pathological state if said value lies below the tenth and above the ninetieth percentile of a distribution of said scientific data, optionally, if said value lies below the twentieth and above the eightieth percentile.

14. Method as in any claim hereinbefore, characterized in that it comprises determining the effectiveness of a drug or a food supplement on the basis of said value associated with said abundance of said plurality of enzymes of interest.

15. Method as in any claim hereinbefore, characterized in that said method comprises a specific analysis of said one or each individual biological or organic sample originating from an individual, wherein said specific analysis comprises: i) extraction (S 110) of the bacterial DNA found in said organic biological sample; ii) determination (SI 20) of the taxonomic profile to identify the bacterial populations present in the sample; iii) obtaining functional metabolic information (SI 30) of the bacterial community whose taxonomic profile has been determined (SI 20); wherein said acquisition (SI 35) of said information on a bacterial population of the microbiota is obtained by means of said analysis of said biological or organic sample.

16. Electronic device (200) comprising a processor (210), a memory unit (220) configured to store data, and a communication unit (230), characterized in that it is configured to execute the method as in any claim hereinbefore.

17. Computer program comprising instructions which, when the program is executed by a computer, determine the execution of the method as in any claim from 1 to 15.

18. Computer-readable mean comprising instructions which, once executed by a computer, determine the execution of the method as in any claim from 1 to 15.