Functional compositions and methods of use thereof in the treatment and recurrence prophylaxis of clostridioides difficile infection and restoration of healthy microbiota

Abstract

The present disclosure relates to bacterial compositions with specific genotypes useful in treating Clostridioides Difficile Infection (CDI) and / or recurrent CDI (rCDI), in their recurrence prophylaxis and (but not exclusively) simultaneously restoration of a healthy microbiome. For conciseness, CDI and rCDI will be collectively referred to as CDI. More specifically, the bacterial compositions provided herein have been designed to exhibit certain properties (functions) to prevent the risk of CDI recurrence and restore a healthy microbiome.

Description

[0001] FUNCTIONAL COMPOSITIONS AND METHODS OF USE THEREOF IN THE TREATMENT AND RECURRENCE PROPHYLAXIS OF CLOSTRIDIOIDES DIFFICILE INFECTION AND

[0002] RESTORATION OF HEALTHY MICROBIOTA

[0003] REFERENCE TO A SEQUENCE LISTING

[0004] This application includes a Sequence Listing with 3070 sequences submitted electronically as a text file named “231040-1 sequence listing. xml”, created on November 4, 2024, with a size of 6141 kilobytes. The sequence listing is incorporated by reference.

[0005] FIELD OF INVENTION

[0006] The present disclosure relates to bacterial compositions with specific genotypes useful in treating Clostridioides Difficile Infection (CDI) and / or recurrent CDI (rCDI), in their recurrence prophylaxis and (but not exclusively) simultaneously restoration of a healthy microbiome. For conciseness, CDI and rCDI will be collectively referred to as CDI. More specifically, the bacterial compositions provided herein have been designed to exhibit certain properties (functions) to prevent the risk of CDI recurrence and restore a healthy microbiome. The disclosure also relates to corresponding methods and uses.

[0007] BACKGROUND OF THE INVENTION

[0008] Scientists in many studies demonstrated that faecal microbiota transplants (FMT) could be used to treat patients with CDI, prevent its recurrence and restore a healthy microbiome. However, the use of FMT has its limitations. Donors could have an insufficient number of strains with the desired therapeutic properties. In addition, donors may have potentially pathogenic bacteria, viruses, prions that may be dangerous to patients with weakened immunity. FMT is composed, as a faecal filtrate, of mostly unidentified matter, and could not be designed to exert specific functions - all matters from the donor stool composition.

[0009] Live Biotherapeutic Products (LBPs), a relatively new medicinal product category, consisting of live bacteria, are strictly designed in terms of composition (in most cases, but not always, for example the equivalent of FMT is "standardized FMT", which, despite maintaining certain standards, is not fully characterized) being equivalent of FMT. To this day, the known LBPs are products with a maximum of a dozen or several dozen strains, which - if have a biological effect (all of them are in clinical trials and the results and effectiveness of their treatment are not known yet) - do not rebuild the full spectrum of the intestinal microbiome, and often also the protective mechanisms, such as “colonization resistance", which is necessary to restore full health. These products have a chance to cure the disease, but without curing the patient and restoring the patient’s full well-being. In view of the limited treatment options currently available, improved methods of treating CDI and restoring a healthy microbiome are needed. There is a need to replace FMT with scalable and safe therapies.

[0010] There are studies showing that antibiotic therapy used prophylactically as part of CDI pretreatment usually leads to severe gut dysbiosis. In most cases the microbiome can rebuild itself, but it takes at least 40 days and is much less effective (Palleja A, Mikkelsen KH, Forslund SK, Kashani A, Allin KH, Nielsen T, Hansen TH, Liang S, Feng Q, Zhang C, Pyl PT, Coelho LP, Yang H, Wang J, Typas A, Nielsen MF, Nielsen HB, Bork P, Wang J, Vilsboll T, Hansen T, Knop FK, Arumugam M, Pedersen O. “Recovery of gut microbiota of healthy adults following antibiotic exposure.” (Nat Microbiol. 2018 Nov;3(l 1): 1255-1265. doi: 10.1038 / s41564-018-0257-9. Epub 2018 Oct 22. PMID: 30349083)). Therefore, FMT could be considered as a method that accelerates the reconstruction of the microbiota and has higher effectiveness. With regards to the statement above, novel therapies overcoming FMT imperfections are needed, especially biosynthetic, donor-independent, scalable biotherapeutics.

[0011] Confirmation of the FMTs efficacy, where each had a different composition, created the need to develop methods that would allow explaining the effectiveness of these compositions. The current state of the art indicates that there are many bacterial combinations (FMT compositions) that bring a therapeutic effect, some of which are disclosed in patent applications.

[0012] Solutions that relate to many combinations of compositions at once do not prove the effectiveness of these compositions. Selected combinations are tested to obtain the desired therapeutic effect in mouse models. However, the effectiveness of selected consortia does not guarantee the effectiveness of other untested compositions, which are also considered within the scope of these solutions.

[0013] Due to the diversity and variability of donor microbiomes, determining the efficacy of a specific microbiome in treating CDI is not obvious to medical professionals. It is also impossible to assess whether a certain bacterial composition will be effective without appropriate in silico or in vivo analyses.

[0014] Additionally, for a microbiome-based solution to be fully valuable, it should rebuild the full spectrum of functions and taxonomical diversity of a healthy microbiome. The currently available solutions do not provide microbiome reconstitution, making it susceptible to other pathologies.

[0015] US11730775B2 discloses therapeutic compositions containing non-pathogenic, germination- competent bacterial spores, for the prevention, control, and treatment of gastrointestinal diseases, disorders and conditions and for general nutritional health. The invention and drug composition is not “computed” to select appropriate drug components, but rather is a “purified FMT” of only sporeforming bacteria, which has no properties to rebuild the full microbiota ecosystem. EP3388069B1 discloses compositions comprising specific consortia of living bacteria strains and to manufacturing such compositions, particularly by co-cultivation; and to the use of such compositions in pharmaceutical applications, such as the treatment of diseases associated with intestinal microbiota dysbiosis, particularly intestinal infections such as CDI and IBD (Inflammatory Bowel Diseases). Low number of bacteria within the drug without functions carried disclosure have no properties to rebuild the full microbiota ecosystem. The origin of the strains is also “random” - not from previously tested in proof-of-concept studies - FMT donors.

[0016] EP3468573B1 discloses compositions and methods for the treatment or prevention of pathogenic infections.

[0017] SUMMARY OF THE INVENTION

[0018] In view of the previous findings, it is necessary to determine some minimum requirements that must be met in order to achieve the desired therapeutic effect and to rebuild the full microbiome ecosystem.

[0019] The present invention is aimed at addressing the needs mentioned with respect to the prior art. It differs by indicating a specific functional potential set (delivered by means of a bacterial consortium) to bring a therapeutic effect and, in a preferred embodiment, restore the microbiome ecosystem.

[0020] The present invention relates to production of next-generation biotherapeutics (NGBs), which are based on creating artificial bacterial ecosystems composed of cultured bacteria, isolated (at least in vast majority of cases) from donors whose FMT products were previously tested in proof-of- concept studies and are proven to be effective - this means the “strain specificity” phenomenon preservation and are designed in silico to exert the desired biological effect, such as "colonization resistance" to C. difficile (as in this case) and rebuild the full spectrum of the functional microbiome, ensuring patient well-being and minimizing the risk of any negative microbiome-related events in the future. The present invention provides a new vision of LBP, realistically introducing a biosynthetic, donor-independent microbiome as a "smart drug," i.e. a drug that restores well-being but at the same time is designed to exert a specific function against the disease it treats.

[0021] The present invention is based on the finding that changes in specific functions provided by bacteria in the CDI patient microbiome following FMT correlate with clinical remission, and further with rebuilding the full microbiota ecosystem. Thus, the inventors have found that the count of identified engrafted bacterial strains encoding specific functions, from donor stool into the patients correlates with treatment response (see Figure 1). Consequently, the clinical effect depends solely on the engrafted bacteria. The invention is based on the inventors’ finding that recipient post-FMT microbiota consist of bacteria remaining in recipient gut during therapy, coming from donor samples (FMT) and other environmental sources (i.e diet).

[0022] The invention is based on the inventors’ finding that the failure to detect strains at a given time point is not evidence that those strains are not present in the sample. They remain below the detection threshold. Bacteria being below the detection threshold is equivalent to very low abundance, which limits the impact of such bacteria on the final clinical outcome in the patient.

[0023] The invention is based on the inventors’ finding that the entire set of FMT bacteria is not required to obtain therapeutic effect. In other words, only a subset of the donor strains are confirmed to contribute to the therapeutic effect. According to the literature and inventors’ findings, there has never been a recorded case where all the strains from a donor were engrafted. The engrafted strains constitute on average about 20% of all detected recipient strains (see Figure 2).

[0024] The invention is based on the finding that there is a set of functions (in the context of KEGG (Kyoto Encyclopedia of Genes and Genomes) Orthology functions, hereinafter referred to simply as functions or KOs) that are missing in sick patients. References to the KOs provided in this description are compliant with the KEGG database release 110.0 of 1 April 2024, published at https: / / www.genome.jp / kegg / . There are functions present in healthy and dysbiotic microbiomes that do not have an impact on the development of the invention. More than half of the functions present in healthy individuals are functions occurring in every single healthy person. These functions have a high prevalence, which means that they occur on many bacteria, including pathogenic ones. Therefore, only functions being statistically significantly different between healthy and disrupted microbiomes were selected (see Figure 3). These functions were considered as potential components of functional consortia.

[0025] The inventors determined a set of functions, herein referred to as the first set, detected on strains engrafted in recipient microbiome from donors, and those functions are shared between cured CDI patients (see Table 1). Providing an LBP (NGB) consortium covering the first set of functions ensured remission of CDI symptoms and prevented its recurrence.

[0026] The inventors also determined a second set of functions detected on strains engrafted from donors shared between patients with restored healthy microbiome (see Table 2). Providing an LBP (NGB) consortium covering functions provided as second set ensures restoration of a healthy microbiome (based on metrics and normatives provided below).

[0027] In this patent application, the term "bacteria" is used expansively to include both typical bacterial organisms and archaea. This interpretation considers that while archaea and bacteria are distinct domains of life with unique biochemical and genetic characteristics, both share certain cellular structures and functional roles that are relevant to the intended molecular functions in this composition. Therefore, for the purposes of this application, "bacteria" is understood to encompass archaea as well, thereby including any prokaryotic organisms capable of performing the specified molecular functions within the described composition.

[0028] Selecting a minimal functional set providing clinical goals and full microbiome restoration should be considered as an optimization method, aimed at determining the minimal composition (as functional or taxonomical) with a given therapeutic effect, however, any consortium larger than the minimal one (with redundant genes coding above mentioned functions), having proposed first set of functions or both sets of functions, should still be considered as within the scope of the present invention (as even having better stability and resilience).

[0029] The results were confirmed in silico, which is a generally accepted premise for drawing reliable conclusions by experts, as described by Duncker, K.E., Holmes, Z.A. & You, L. in “Engineered microbial consortia: strategies and applications” (Microb Cell Fact 20, 211 (2021). https: / / doi.org / 10.1186 / sl2934-021-01699-9).

[0030] BRIEF DESCRIPTION OF THE DRAWINGS

[0031] The figures are illustrative only and are not required for enablement of the disclosure. For clarity, not every component may be labeled in every drawing. In the drawings:

[0032] Figure 1 shows that engraftment of bacterial strains from donor stool to recipient is associated with treatment response. The results of this comparison show that the count of engrafted strains is significantly important for patient recovery.

[0033] Figure 2 shows the percentage distribution of engrafted and non-engrafted strains for selected ten samples with the highest engrafted strains ratio. The results show that only part of strains in post FMT recipients come from donors.

[0034] Figure 3 shows differences in functional potential (KOs) in healthy donor samples and pre- FMT patients, identified using a pangenome (all functions, even detected on unbinned contigs), binary approach. The Kruskal -Wallis test was applied to determine differences in occurrence of KOs between groups, with p-values corrected using the Benjamini -Hochberg (BH) method.

[0035] Figure 4 shows scatter plots showing correlation between the number of species classified using MAG (Metagenome-Assembled Genomes) approach and Kraken approach in all samples. The value of R represents the Pearson correlation. This figure shows that there is a moderate correlation between the number of species identified by Kraken and the number of MAGs in donor samples. The strongest correlation has been observed at the family level (RA2 = 0.77).

[0036] Figure 5 shows a comparison of unique functions counts identified in donors, patients pre-FMT and cured patients post-FMT. Figure 6 shows a comparison of in-house and public data in terms of quality for metagenomic analyses. The X axis represents sequencing depth in base pairs (bp), while the Y axis represents the unique function (KO) count. The results show a significant difference in sequencing depth, quality measures and the number of unique features detected, favoring the in-house data.

[0037] Figure 7 shows principal component analysis (PCA) of the functional potential (KOs) of selected MAGs and ATCC-derived strains (American Type Culture Collection). The X-axis represents the first principal component, and the Y-axis represents the second principal component. The results show strong clustering of MAGs and ATCC strains based on taxonomy, but there is high variance between strains within clusters. This allows for a transition from general analyses to detailed analyses at the level of individual strain differences.

[0038] Figure 8 shows taxonomic diversity among in-house donor samples. These results show that most taxa at the species level differ between samples.

[0039] Figure 9 shows a Venn diagram representing microbiome compositions in patients achieving remission of CDI symptoms with no recurrence and restoration of a healthy microbiome. Both conditions can occur independently.

[0040] Figure 10 shows the overlap between the first set and second set. There is a minimal overlap between the functional first set and second set.

[0041] Figure 11 shows a comparison of engrafted functions from the first set between recurrent and cured triads. These results demonstrate the identification of a limited set of functional potential necessary to achieve disease symptom resolution and recurrence prophylaxis.

[0042] Figure 12 shows a comparison of engrafted functions from the second set between restored and non-restored healthy microbiome triads. These results demonstrate the determination of a limited set of functional potential necessary to achieve restoration of a healthy microbiome.

[0043] Figure 13 shows a Principal Component Analysis (PCA) of an engrafted bacterial composition (derived from FMT), computed NGB consortia and other artificial consortia. The results show two clusters of engrafted consortia from cured patients and one cluster of engrafted consortia of recurrent recipients. Computed NGB consortia strongly cluster with both engrafted consortia clusters. Single bacteria and artificial consortia (with pathogens) cluster with consortia from recurrent recipients.

[0044] DETAILED DESCRIPTION

[0045] In the following passages, different aspects of the invention are defined in more detail. Each aspect described herein may be combined with any other aspect or aspects unless clearly indicated to the contrary. In particular, any feature indicated as being preferred or advantageous may be combined with any other feature or features indicated as being preferred or advantageous. The invention relates to therapeutic bacterial compositions, each comprising one or more bacteria, e.g. a consortium of defined bacterial isolates. The compositions are useful in the treatment and recurrence prophylaxis of CDI and (but not exclusively) in restoration of a healthy microbiome.

[0046] The bacterial composition is selected based on the ability of the live bacterial product to induce or stimulate a desired response when administered to a subject (e.g., a CDI patient).

[0047] The invention relates to compositions comprising a plurality of bacteria, e.g. a consortium of defined bacterial isolates (LBP; NGB) or a consortium of bacteria in the form of gut microbiota obtained from a donor (e.g. as a stool sample) for faecal microbiota transplantation (FMT) procedure. Plurality of bacteria present in the composition comprises plurality of genes encoding plurality of molecular functions. The compositions are useful in the treatment of CDI, its recurrence prophylaxis and healthy microbiome restoration.

[0048] Isolated bacteria can be (and to achieve “strain specificity phenomenon” preservation must be) obtained from gut microbiota obtained from a donor whose faecal microbiota transplantation (FMT) preparations were used in proof-of-concept studies showing its therapeutic efficacy. Bacterial strains with beneficial therapeutic properties that are capable of engrafting into the recipient microbiota can be identified based on metagenomic analyses, which allow (by high quality, deep sequencing) for the indication of MAGs belonging to the same strains that occurred in the donor material and later engrafted into the recipient microbiota. These strains can then be identified among the isolated strains from the donor material based on genomic analyses (e.g. average nucleotide identity (ANI) analysis or DNA-DNA digital hybridization (dDDH)). Then, the strains identified in this way with beneficial properties can become a component of a bacterial composition consisting of isolated bacteria. In such a composition, isolated bacteria from one donor can be combined, but it is also possible to combine isolated bacteria from multiple donors if a particular strain in different donors exhibits better functions or more abundant functions than in other donors. Combining isolated bacterial strains from different donors allows for an increase in the diversity of the composition and can help increase the effectiveness of therapy using such a bacterial composition.

[0049] In a preferred, but non-limiting embodiment, the bacterial compositions of the invention include isolated bacteria and are not therefore faecal microbiota transplants (FMT). They do not contain faecal material, but contain defined mixtures of bacterial isolates free of faecal material. Preparations that contain a defined bacterial mixture are generally accepted to be a safer treatment than FMT. An advantage of the present composition in such an embodiment is that it comprises only fully defined and characterized bacteria proven to exert particular biological role in a previously performed proof-of-concept FMT study (the same strains provided in FMT from the in-house donor biobank compose the final drug composition) and no undefined or unwanted components, which may be present in donor stools, thereby allowing the therapeutic composition to be standardized and increase safety of the composition, and additionally preserving the “strain specificity” phenomenon. Thus, in some aspects relating to bacterial compositions, the invention may exclude the administration of faecal transplants.

[0050] As used herein, the term “species” refers to a taxonomic entity as conventionally defined by genomic sequence and phenotypic characteristics. A “strain” is a particular instance of a species from a given sample, for which genome assembly (MAG) was prepared and taxonomy was assigned. Additionally unbinned contigs were also included in analysis as an undefined bacteria containing a specific set of functional properties.

[0051] There is a problem with defining the parameters of a healthy microbiome. Scientists obtain different results, e.g. the number of bacteria detected in the human gut. This has been discussed in a number of publications:

[0052] Yang J, Pu J, Lu S, Bai X, Wu Y, Jin D, Cheng Y, Zhang G, Zhu W, Luo X, Rossell6-M6ra R, Xu J. “Species-Level Analysis of Human Gut Microbiota With Metataxonomics” (Front Microbiol. 2020 Aug 26; 11 :2029. doi: 10.3389 / fmicb.2020.02029. PMID: 32983030; PMCID: PMC6479098),

[0053] Gupta VK, Kim M, Bakshi U, Cunningham KY, Davis JM 3rd, Lazaridis KN, Nelson H, Chia N, Sung J. “A predictive index for health status using species-level gut microbiome profiling” (Nat Commun. 2020 Sep 15; 11(1):4635. doi: 10.1038 / s41467-020-18476-8. PMID: 32934239; PMCID: PMC6492273),

[0054] Sheng Y, Wang J, Gao Y, Peng Y, Li X, Huang W, Zhou H, Liu R, Zhang W. “Combined analysis of cross-population healthy adult human microbiome reveals consistent differences in gut microbial characteristics between Western and non-Westem countries” (Comput Struct Biotechnol J. 2023 Nov 28;23:87-95. doi: 10.1016 / j .csbj .2023.11.047. PMID: 38116074; PMCID: PMC9730331),

[0055] Quigley EM “Gut bacteria in health and disease” (Gastroenterol Hepatol (N Y). 2013 Sep;9(9):560-9. PMID: 24729765; PMCID: PMC3983973).

[0056] This is due to differences resulting from sequencing depth, sequencing technology, used software and adopted thresholds. Therefore, several definitions and normatives of the healthy microbiome will be defined for the purposes of the present description, as elaborated in detail below. This allows for the diagnosis of each sample and identification of whether the patient has a healthy or abnormal microbiome (see. Table 3). It is particularly difficult to determine the exact number of bacteria in a healthy sample. Metagenome-assembled genomes (MAGs) and Kraken-detected (species detected using Kraken software) strains / species counts will not perfectly reflect the real number of bacteria in a healthy microbiome. MAGs underrepresent and Kraken-detected species overrepresent a real number of species in a sample. However, there is a correlation (see Figure 4) between these counts. Both metrics will be therefore included to describe a healthy microbiome.

[0057] The advantage of the approach presented herein lies in focusing on functions rather than on composition of bacteria in the context of taxonomic names, in contrast to descriptions commonly presented in other patent applications. Functions, rather than just the composition of the microbiome, are a key element in the functioning of the human gut ecosystem. It is widely known that the same functions can be encoded by completely unrelated bacteria and still possess the same benefits to gut microbiome. Bacterial compositions presented herein, that encode a set of functions present in a healthy microbiome, i.e., glycosylation of mucins, short-chain fatty acids production, biotransformation of bile acids, optimal carbon source metabolism, ascorbate metabolism, methane metabolism, degradation of benzoate and aromatic compounds, porphyrin metabolism and biosynthesis of amino acids encoded by protein, disclose a set of KOs that are crucial for remission of CDI symptoms, its recurrence prophylaxis and (but not exclusively) healthy microbiome restoration.

[0058] Donors with different taxonomic compositions produce the same positive clinical outcome. Therefore, taxonomic analyses do not allow defining patterns and principles responsible for patient cure. Functional analysis of the microbiome has enabled the determination of common features that are the basis for creating effective consortia for treating CDI, its recurrence prophylaxis and healthy microbiome restoration, which is the primary inventors’ finding revealed here. It is worth mentioning that the diversity or large number of functions itself may be related to the pathological status, not health (see Figure 5). In the FMT treatment procedure and the method proposed herein, it is important to deliver / engraft specific functions that cause a therapeutic effect.

[0059] As explained herein, the bacterial compositions of the invention have a therapeutic effect when administered to a subject and can be used in the treatment and / or prevention of CDI and healthy microbiota restoration. Thus, the compositions as described herein are therapeutic / prophylactic compositions. Thus, the invention also extends to pharmaceutical compositions comprising a composition of bacteria as described herein and methods of use thereof.

[0060] Identification of therapeutic components in total stool microbiota allows the identification of donors and stool samples with increased therapeutic / prophylactic efficacy.

[0061] All donor samples used in proof-of-concept studies were free of any Clostridioides difficile strains confirmed with methods such as: genomic (PCR (Polymerase Chain Reaction) and deep ONT NGS (Oxford Nanopore Technologies Next Generation Sequencing)) and culture. Therefore it is plausible that their microbiome composition on both functional and taxonomic levels grants colonization resistance against C. difficile and hence was used to determine functional and (afterwards) taxonomic sets of compositions granting colonization resistance against C. difficile. Samples used for analysis were very deeply (>20 Gbp per sample) sequenced using ONT Methods generally accepted by experts skilled in the art and in-house tools, were used to process these data. ONT allows obtaining results with high accuracy, thanks to the very long reads guaranteed by that technology (see Figure 6). Nanopore technology, which enables long-read sequencing, is particularly advantageous for reconstructing complete bacterial genomes from metagenomic samples. Unlike short-read sequencing technologies, which often struggle with resolving repetitive regions and complex genome structures, long reads generated by nanopore sequencing can span these difficult areas, allowing for more accurate assembly of full genomes. This is especially important in metagenomics, where DNA from multiple organisms is mixed, and achieving high-resolution assemblies is critical for identifying and characterizing microbial species and their functions. As a result, nanopore sequencing enhances the ability to reconstruct complete bacterial genomes with greater continuity and fewer gaps. The inventors found that the metagenome-assembled genomes (MAGs) reconstructed from the samples used, in most cases, contain fully recovered genomes when compared to reference genomes from the same bacterial species. By aligning and comparing the assembled MAGs with these reference genomes, a high degree of completeness and structural accuracy was observed, confirming that the long-read sequencing approach successfully captures the full genomic content of the bacteria present in the samples used. This validation highlights the robustness of the reconstruction process in accurately representing bacterial genomes (see Figure 7). This also allows for drawing reliable conclusions.

[0062] All analyzed samples were divided into “triads” (cases), which means sets of at least 3 samples from a single treatment. A triad consists of at least one sample from a patient before FMT (regardless of how many timepoints were set pre-FMT; usually 1 or 2), at least one sample from the donor stool used as FMT and at least one sample from the recipient after FMT (regardless of how many timepoints were set post-FMT; usually 3 to 8 within a year post FMT). Only a complete triad allows for drawing conclusions about causality and allows for correlation of treatment outcomes with changes occurring as a result of this treatment.

[0063] The new finding presented herein is a functional mechanism responsible for the therapeutic effect, which includes the prevention of CDI recurrence and, but not exclusively, the restoration of a fully functional healthy microbiome. It has been proven that the FMT procedure significantly accelerates the restoration of the microbiome and reduces the risk of CDI recurrence. Each therapy is significantly different because two completely different metagenomes are combined. Defining the engrafted strains in triads and identifying common features between them has allowed for defining the previously unknown functional potential of the microbiome needed for a therapeutic effect against CDI recurrences and, but not exclusively, the restoration of a healthy microbiome. It was also tested whether there were some common features of FMT between patients with remission and no recurrence of CDI symptoms. As previously discussed, FMT donor samples differed taxonomically (see Figure 8). The question remained whether functional similarity could be determined. To determine this, strain sets identified as independently engrafted for each triad were functionally coded. Subsequently determining the common part of all engrafted strain (functional) sets was possible. Additionally, a narrowing was applied only to features that were statistically significant in differentiating donor and pre-FMT samples (see Figure 3). The first set containing KEGG orthologous functions associated with remission and no recurrence of CDI symptoms was selected and is presented in Table 1.

[0064] It is to be stated that the aforementioned first set of functions introduced through a number of strains, where each strain encodes many more functions than those composing the first set, provides overall many more functions within the therapeutic NGB consortium than necessary to treat / prevent recurrence of CDI, thereby providing a “natural” therapeutic effect.

[0065] A healthy microbiome was defined as one whose metrics (normatives), measured using molecular diagnostics (especially with the NGS method), fall within acceptable norms established through population-based analyses (conducted especially for the invention described herein). The population-based analyses were conducted on a sample of 328 donors from different geographical regions. These metrics that have been developed relate to species richness, the level of taxonomic diversity, the presence of dominant bacteria and the ratio of Bacillota to Bacteroidota. Using these metrics, it is possible to determine the health status of the microbiome of any sample that has metagenomic sequencing results. All used metrics are presented in Table 3.

[0066] It was tested whether there were some common features of FMTs performed in proof-of- concept studies, between patients who restored a healthy microbiome. Patients with a healthy microbiome restoration were selected based on the health metrics previously described. To determine whether functional similarities existed, strain sets identified as independently engrafted for each triad were functionally coded. Subsequently, it was possible to determine the common part of all engrafted strain (functional) sets. The second set containing KEGG orthologous functions significant in the restoration of the healthy microbiome was selected and is presented in Table 2.

[0067] It was shown that the reduction in CDI symptoms with its recurrence prophylaxis and the restoration of a healthy microbiome could occur independently (see Figure 9). Additionally, it was shown that there is only a slight overlap between the first set and the second set (Figure 10). However there are engrafted consortia, and therefore NGB consortia, that have the ability to simultaneously rebuild the healthy microbiome and reduce the symptoms of CDI with its recurrence prevention (see Table 4). It was shown that the consortium encoding aforementioned first set needs to be supplemented by additional bacterial species encoding functions from the second set to provide full restoration of a healthy microbiome.

[0068] It was shown that the consortium encoding the aforementioned second set needs to be supplemented by additional bacterial species encoding functions from the first set to provide remission of CDI symptoms and anti-C. difficile colonization resistance mechanism (recurrence prophylaxis).

[0069] EXAMPLES

[0070] Example 1. In -silico identification of bacterial strains and engrafted strains consortia

[0071] Metagenomic sequencing and bioinformatic analysis were performed on patient and donor samples collectively composing 37 triads (236 samples in total, including 87 donor samples), across multiple time points, from a proof-of-concept study using faecal microbiota transplantation (FMT) in patients with CDI / rCDI (in-house data).

[0072] Using the microbiome profile of both FMT donor material and patient samples, several tools were used to determine which bacterial species from the donor material engrafted in the recipient and are associated with clinical remission and recurrence prophylaxis. To assess strain similarity between donors and post-FMT samples, fastANI software was used. For strains engraftment thresholds of ani value > 99 and mapped fragments > 0.90 were set.

[0073] Based on engrafted MAGs, engrafted consortia were selected for each triad. Donor MAGs shared with MAGs from at least one of post-FMT samples were selected as engrafted consortia.

[0074] Example 2, In-silico identification of CDS (coding sequences - proteins) and KO (KEGG Orthology)

[0075] Protein functions were determined using the KEGG database. This means that each protein could have an assigned specific KO identifier. Proteins without an assigned KO identifier have as yet unknown functions. Proteins with the same KO identifier encode similar functional properties. Table 5 contains the KO identifiers with their assigned sequence IDs.

[0076] The KO identifiers used herein are intended to serve as the functional names for the protein sequence clusters. However, it is recognized that the designated protein clusters may be known by other functional names that are not listed here. Therefore, any functional name that describes any subset of the protein sequences in a cluster shown in Table 5 should be considered the same as the cluster names used.

[0077] Proteins encoding each function identified with a KO identifier shown in Table 5 have been clustered within each function. Subclusters aligned by > 80% of total length and with E-value < 1.000E-03 have been saved, and the most representative sequence is shown for each subcluster. Such methodology is typically used for exhaustive reporting of protein clusters in the field (and it also results from the limitations of the patent application handling system).

[0078] Example 3, In-silico identification of engrafted functions

[0079] Engrafted functions are a unique set of KOs that consist of all KOs assigned to proteins encoded on the MAGs from the engrafted consortium. Table 6 shows engrafted strains for each triad. In all cases all functions listed in set 1 and set 2 were identified within engrafted strains.

[0080] Example 4 The engrafted consortia encoding the functional first set provide remission of CPI symptoms and its recurrence prophylaxis

[0081] Engrafted functions were selected for each triad, i.e. the functions that were present on the transplanted strains and were on the list of functions correlated with health (see Figure 3).

[0082] The overlap of functions engrafted between triads with a positive treatment response (cure of CDI and its recurrence prophylaxis) was computed and the first set of functions (KO) associated with recovery and recurrence prophylaxis was obtained. To exclude a false positive result the presence of these functions was checked on triads with no clinical response and / or CDI recurrence (see Figure 11). The analysis shows a lack of these functions in engrafted consortia of recurrent / not cured patients.

[0083] Example 5, The engrafted consortia encoding the functional second set restore a healthy microbiome Engrafted functions were selected for each triad, i.e. the functions that were present on the transplanted strains. All above mentioned functions were then analyzed for correlation with the metrics and normatives of a healthy microbiome described and calculated above.

[0084] The overlap of functions engrafted within triads with a healthy microbiome restoration was computed, and the second set of functions (KO) associated with restoration of a healthy microbiome was obtained. To exclude a false positive result the presence of these functions was checked on all triads (see Figure 12). The analysis shows a lack of these functions in engrafted consortia in patients without healthy microbiome restoration.

[0085] Example 6, In silico consortia prediction

[0086] Computed functions were permuted into different bacterial consortia and tested in silico for association with clinical response. The consortium of strains which maximized this effect was selected. As it is not known how many strains compose the healthy microbiome and whether providing functional completeness to exert the aimed biological role could be delivered within a smaller number of strains, this therapeutic consortia consisting of 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 200, 300 bacteria (as in-house internal normative showed 300 taxons as a median of the healthy population, and as few as 10 strains could encode all the functional potential necessary to exert the aimed role) were computed and included in Table 7.

[0087] Comparison of an in silico computed, real-life engrafted, random and other generated consortia were shown using PCA on Figure 13. Only specific consortia cluster together and separately from random, possibly non-therapeutic consortia.

[0088] TABLES

[0089] Table 1. List of Kegg Orthology functions (first set) engrafted within donor strains into recipients associated with CPI remission and its recurrence prevention (anti-C. diff colonization resistance).

[0090] Table 2. List of Kegg Orthology functions engrafted within donor strains into recipients associated with restoration of healthy microbiome (second set).

[0091] Table 3. Detailed information of metrics used to compose normatives, associated with healthy microbiome.

[0092] Analyses were performed on 328 donors from different geographical regions. Table 4. Engrafted real-life, FMT-derived consortia efficacy in treating GDI symptoms and its recurrence prevention and in healthy microbiome restoration (HMR). A plus sign was used to mark consortia that were effective in a given indication, a minus sign was used to mark consortia that were not effective in a given indication.

[0093] Table 5. KO with representative assigned seq IDs encoding them. Odd IDs correspond to nucleotide sequence encoding aminoacid sequence with the following even ID.

[0094] Table 6. A list of engrafted strains for each triad.

[0095] Table 7. Example NGB consortia composed of different numbers of strains. Names assigned to consortia according to the legend in Figure 13 were included.

Claims

CLAIMS1. A composition comprising plurality of bacteria comprising genes encoding a plurality of molecular KEGG Orthology functions from a first set comprising: K09384, K00096, K10440, K02057, K05845, K03186, K01478, K23779, K07031, K09163, K05311, K00951, K09767, K02478, K01497, K05847, K05846, K22083, K09698, K01611, K02669, K09949, K15984, K07590, K21755, K01667, K06411, K10441, K03700, K13020, K21574, K03800, K01567, K00259, K14982, K06410, K18697, K05801, K09607, K02825, K18349, K03658, K07502, K21575, K03781, K06403, K03708, K19575, K16211, K13787, K24846, K00537, K01278, K19118, K06421, K07045, K08217, K25152, K20490, K12999, K15773, K02230, K06895, K00282, K25227, K06398, K07448, K20950, K19091, K02226, K25153, K19117, K17810, KOI 191, K06295, K00350, K01060, K13789, K09779, K25151, K20859, K00283, K13542, K17472, K20491, K14379, K02551, K07075, KI 1621, K17992, K09704, K19083, K00346, K06404, K01271, K03608, K07455, K18122, K19119 and K20492 functions.

2. The composition according to claim 1, wherein the plurality of molecular functions further comprise KEGG Orthology functions from a second set comprising: K19956, K06606, K02626, K22958, K06903, K02800, K08260, K07313, K06907, K15726, K17723, K03769, K21453, K07492, K07679, K01975, K03187, K09684, K09780, KI 1051, K23356, KI 1904, K02810, K10710, K00171, KI 1050, K01266, K18828, K07071, K21011, K15527, K00005, K09974, K19309, K13990, K00819, K03337, K22757, K12941, K06330, K00564, K21744, K23253, K16153, K03436, K10119, KOI 174, K18011, K01843, K00556, K21012, K15555, K19310, K10192, K01235, K00156, K19137, K01035, K03335, K07494, K05813, K25114, K16150, K05986, K10212, K18012, K01844, K02757, K00641, K07397, K09384, K15531, K03297, K00294, K25067, K03390, K17948, K13012, K22960, K01838, K00853, K10974, K13018, K13017, K09992, K06416, K02456, K18014, K10118, K16927, K06726, K00074, KOI 160, K02007, K13049, K24948, K06284, K09775, K15519 and K22699 functions.

3. The composition according to claim 1 or 2, wherein the plurality of bacteria comprises a consortium selected from the group consisting of: consortium Cl, C2, C3, C4, C5, C6, C7, C8, C9, CIO, Cl l, C12, C13, C14 and C15 of Table 7.

4. The composition according to claim 1 or 2, wherein the plurality of bacteria comprises a consortium selected from the group consisting of: consortium HBI2AA, HBI07, HBI08, HBI09, HBI11, HBI14, HBI16, HBI27, HBI30, HBI35, HBI38, HBI46, HBI69, HBI70, HBI74, HBI77, HBI81, HBI95, HBI116, HBI147A, HBI177, HBI178, HBI181 and HBI193 of Table 6.

5. A pharmaceutical composition comprising the composition of any one of the preceding claims, further comprising a pharmaceutically acceptable excipient.

6. The pharmaceutical composition according to claim 5, wherein the pharmaceutical composition is formulated for delivery to the intestine.

7. The composition according to any one of claims 1-6 for use as a medicament.

8. The composition according to claim 7, wherein the use comprises administering the composition in a form of faecal microbiota transplantation.

9. The composition according to claim 7, wherein the use comprises administering the composition in a form of an isolated bacteria consortium.

10. The composition according to any one of claims 1-6 for use in treatment of Clostridioides difficile infection.

11. The composition according to any one of claims 1-6 for use in preventing recurrence of Clostridioides difficile infection.

12. The composition according to any one of claims 2-6 for use in treatment of Clostridioides difficile infection, preventing recurrence of Clostridioides difficile infection and restoration of a healthy microbiome.

13. A method for treating Clostridioides difficile infection, in a subj ect in need for thereof, comprising administering a composition according to any one of claims 1-6 to the subject in an amount effective to treat Clostridioides difficile infection.

14. A method for preventing recurrence of Clostridioides difficile infection in a subject in need for thereof, comprising administering a composition according to any one of claims 1-6 to the subject in an amount effective to prevent recurrence of Clostridioides difficile infection.

15. A method for treatment of Clostridioides difficile infection, preventing recurrence of Clostridioides difficile infection and restoration of a healthy microbiome in a subject in need forthereof, comprising administering a composition according to any one of claims 2-6 to the subject in an amount effective to restorate a healthy microbiome.

16. A method for assessing a suitability of a composition comprising plurality of bacteria comprising genes encoding plurality of molecular functions for use in treatment of Clostridioides difficile infection or in preventing recurrence of Clostridioides difficile infection, comprising: isolating DNA from the composition to obtain a DNA isolate; sequencing the DNA isolate using nucleic acid sequencing methods to obtain a metagenome sequence; identifying in the metagenome sequence sequences of genes; assigning functions to the gene sequences based on their sequences; comparing whether the functions assigned to the gene sequences comprises KEGG Orthology functions from a first set comprising: K09384, K00096, K10440, K02057, K05845, K03186, K01478, K23779, K07031, K09163, K05311, K00951, K09767, K02478, K01497, K05847, K05846, K22083, K09698, K01611, K02669, K09949, K15984, K07590, K21755, K01667, K06411, K10441, K03700, K13020, K21574, K03800, K01567, K00259, K14982, K06410, K18697, K05801, K09607, K02825, K18349, K03658, K07502, K21575, K03781, K06403, K03708, K19575, K16211, K13787, K24846, K00537, K01278, K19118, K06421, K07045, K08217, K25152, K20490, K12999, K15773, K02230, K06895, K00282, K25227, K06398, K07448, K20950, K19091, K02226, K25153, K19117, K17810, KOI 191, K06295, K00350, K01060, K13789, K09779, K25151, K20859, K00283, K13542, K17472, K20491, K14379, K02551, K07075, KI 1621, K17992, K09704, K19083, K00346, K06404, K01271, K03608, K07455, K18122, K19119 and K20492 functions; and if the gene sequences comprises all the functions of the first set, the composition is considered suitable for use in treatment of recurrent Clostridioides difficile infection or in preventing recurrence of Clostridioides difficile infection; otherwise, the composition is not considered suitable for use in treatment of recurrent Clostridioides difficile infection or in preventing recurrence of Clostridioides difficile infection.

17. The method of claim 16, further comprising comparing whether the functions assigned to the gene sequences further comprises KEGG Orthology functions from a second set comprising: K19956, K06606, K02626, K22958, K06903, K02800, K08260, K07313, K06907, K15726, K17723, K03769, K21453, K07492, K07679, K01975, K03187, K09684, K09780, KI 1051, K23356, KI 1904, K02810, K10710, K00171, KI 1050, K01266, K18828, K07071, K21011, K15527, K00005, K09974, K19309, K13990, K00819, K03337, K22757, K12941, K06330, K00564, K21744, K23253, K16153, K03436, K10119, KOI 174, K18011, K01843, K00556, K21012, K15555, K19310, K10192, K01235,K00156, K19137, K01035, K03335, K07494, K05813, K25114, K16150, K05986, K10212, K18012, K01844, K02757, K00641, K07397, K09384, K15531, K03297, K00294, K25067, K03390, K17948, K13012, K22960, K01838, K00853, K10974, K13018, K13017, K09992, K06416, K02456, K18014, K10118, K16927, K06726, K00074, KOI 160, K02007, K13049, K24948, K06284, K09775, K15519 and K22699 functions; and if the gene sequences comprises all the functions of the first set and the second set, the composition is considered further suitable for use in restoration of a healthy microbiome; otherwise, the composition is not considered further suitable for restoration of a healthy microbiome.

18. A method for assessing a suitability of a stool sample comprising plurality of bacteria comprising genes encoding plurality of molecular functions for use in faecal microbiota transplant (FMT) in treatment of recurrent Clostridioides difficile infection or in preventing recurrence of Clostridioides difficile infection, comprising: isolating DNA from the stool sample to obtain a DNA isolate; depleting human DNA in the DNA isolate; sequencing the DNA isolate using nucleic acid sequencing methods to obtain a metagenome sequence; removing from the metagenome sequence sequences belonging to human genome; identifying in the metagenome sequence gene sequences; assigning functions to the gene sequences based on their sequences; comparing whether the functions assigned to the gene sequences comprises KEGG Orthology functions from a first set comprising: K09384, K00096, K10440, K02057, K05845, K03186, K01478, K23779, K07031, K09163, K05311, K00951, K09767, K02478, K01497, K05847, K05846, K22083, K09698, K01611, K02669, K09949, K15984, K07590, K21755, K01667, K06411, K10441, K03700, K13020, K21574, K03800, K01567, K00259, K14982, K06410, K18697, K05801, K09607, K02825, K18349, K03658, K07502, K21575, K03781, K06403, K03708, K19575, K16211, K13787, K24846, K00537, K01278, K19118, K06421, K07045, K08217, K25152, K20490, K12999, K15773, K02230, K06895, K00282, K25227, K06398, K07448, K20950, K19091, K02226, K25153, K19117, K17810, KOI 191, K06295, K00350, K01060, K13789, K09779, K25151, K20859, K00283, K13542, K17472, K20491, K14379, K02551, K07075, KI 1621, K17992, K09704, K19083, K00346, K06404, K01271, K03608, K07455, K18122, K19119 and K20492 functions; and if the gene sequences comprises all the functions from the first set, the stool sample is considered suitable for use in faecal microbiota transplant (FMT) in treatment of recurrent Clostridioides difficile infection or in preventing recurrence of Clostridioides difficile infection;otherwise, the stool sample is not considered suitable for use in treatment of recurrent Clostridioides difficile infection or in preventing recurrence of Clostridioides difficile infection.

19. The method of claim 18, further comprising comparing whether the functions assigned to the gene sequences further comprises KEGG Orthology functions from a second set comprising: K19956, K06606, K02626, K22958, K06903, K02800, K08260, K07313, K06907, K15726, K17723, K03769, K21453, K07492, K07679, K01975, K03187, K09684, K09780, KI 1051, K23356, KI 1904, K02810, K10710, K00171, KI 1050, K01266, K18828, K07071, K21011, K15527, K00005, K09974, K19309, K13990, K00819, K03337, K22757, K12941, K06330, K00564, K21744, K23253, K16153, K03436, K10119, KOI 174, K18011, K01843, K00556, K21012, K15555, K19310, K10192, K01235, K00156, K19137, K01035, K03335, K07494, K05813, K25114, K16150, K05986, K10212, K18012, K01844, K02757, K00641, K07397, K09384, K15531, K03297, K00294, K25067, K03390, K17948, K13012, K22960, K01838, K00853, K10974, K13018, K13017, K09992, K06416, K02456, K18014, K10118, K16927, K06726, K00074, KOI 160, K02007, K13049, K24948, K06284, K09775, K15519 and K22699 functions; and if the gene sequences comprises all the functions of the first set and the second set, the stool sample is considered suitable for use in faecal microbiota transplant (FMT) in restoration of a healthy microbiome; otherwise, the stool sample is not considered suitable in restoration of a healthy microbiome.

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