SNP markers, combinations and oligonucleotide sequences for a dynamic diagnostic panel for pathogen identification in bacterial infections

Abstract

In the study carried out with 17 microorganism agents at the species and genus level, a comparison was made to provide distinction between species, and as a result of the comparison, it relates to the identification of candidate points that can be used in differential diagnosis. Each detected nucleotide position was screened for polymorphisms in the equivalent positions of the genes / genomes of other members of the same species / genus in the database and 8 SNP biomarkers were detected and a difference matrix was created by calculating the identification power for each candidate point, enabling the detection of probe and SNP combinations for the diagnosis of bacterial species in multiple samples with a single panel.

Description

[0001] DESCRIPTION

[0002] SNP MARKERS, COMBINATIONS AND OLIGONUCLEOTIDE SEQUENCES FOR A DYNAMIC DIAGNOSTIC PANEL FOR PATHOGEN IDENTIFICATION IN BACTERIAL INFECTIONS

[0003] Field of the Invention

[0004] In the study carried out with 17 microorganism agents at the species and genus level, a comparison was made to provide distinction between species, and as a result of the comparison, it relates to the identification of candidate points that can be used in differential diagnosis.

[0005] Each detected nucleotide position was screened for polymorphisms in the equivalent positions of the genes / genomes of other members of the same species / genus in the database and 8 SNP biomarkers were detected and a difference matrix was created by calculating the identification power for each candidate point, enabling the detection of probe and SNP combinations for the diagnosis of bacterial species in multiple samples with a single panel.

[0006] Prior Art

[0007] Infection is the invasion of the host by microorganisms, and these microorganisms can cause a number of different infections of varying severity. Bacteria can be divided into three groups according to their pathogenicity; some are primary pathogens, others are opportunistic pathogens and some are nonpathogens. The virulence of a bacterium is related to its ability to cause disease despite host resistance mechanisms, and susceptibility to bacterial infections depends on the physiological and immunological state of the host and the virulence of the bacterium (Peterson, 1996).

[0008] Traditional surveillance methods rely on the culture and typing of known individual cultivable organisms, but it is becoming clear that microbes interact within larger bacterial communities. Genomic sequencing of microbial communities can complement traditional methods and help investigate changes in species-level prevalence and bacterial population structure, particularly in the context of monitoring antibiotic-resistant bacteria (Conlan et al., 2012). According to current models and estimates, eleven infectious syndromes caused by thirty-three bacterial pathogens accounted for 57% of the 13.7 million deaths due to infections in 2019. To overcome this burden, health systems need to be strengthened with better diagnostic equipment, infection control and antimicrobial stewardship, as well as preventive initiatives such as safe food and water and immunisation. These bacteria cause deaths, poorer quality of life and shorter life spans (Ikuta et al., 2022).

[0009] Based on current trends and estimates of lower respiratory tract infections and thorax-related infections, meningitis and other bacterial central nervous system infections, bloodstream infections, skin and subcutaneous bacterial infections, urinary tract infections and pyelonephritis, peritoneal and intra-abdominal infections, bone, joint and related organ infections, cardiac infections and diarrhoeal diseases, eleven infectious syndromes are estimated to be responsible for approximately 57% of the 13.7 million deaths due to infections in 2019 (Ikuta et al., 2022).

[0010] Escherichia coli (E. coli) is a gram-negative, rod-shaped bacterium belonging to the Enterobacteriaceae family (Pakbin et al.) Some strains, such as Shiga toxinproducing Escherichia coli (STEC), can cause foodborne illness. People are infected with this bacterium through consumption of foods such as raw or undercooked meat products, raw milk, and contaminated raw vegetables. Another way of transmission is through person-to-person contact or oral-fecal contact. Enterobacter sp. are anaerobic, gram-negative bacteria that are commonly found in soil, water and sewage (Laura and Fisher, 2009). It is included in the pathogen group called "ESKAPE" (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter species), which are the leading causes of hospital infections worldwide (Rice., 2008). 22 species were found in the Enterobacter genus. However, it is not known whether all species cause human disease. Enterobacter species cause many hospital infections, including endocarditis, respiratory tract infections, urinary tract infections (UTI) and soft tissue infections (Ramiroz and Giron., 2022). Serratia species are gram-negative, motile, facultative anaerobic members of the order Enterobacterales (loannou et al., 2022). Serratia marcescens is among the Serratia species and is naturally found in water and soil. It can cause sepsis, wound infections, respiratory tract and urinary system infections (Buckle., 2014). Klebsiella sp. are opportunistic pathogens that can be found in the intestinal flora, skin, nose and throat of healthy individuals. This pathogen can cause a range of infections such as sepsis, surgical wound infections, urinary tract infections, pneumonia and bloodstream infections (Dong et al., 2022). Klebsiella sp. can exist in the human intestines without causing human disease. Klebsiella infections are usually seen in patients who are hospitalized for treatment of different diseases. Haemophilus influenzae is a gram-negative, facultative coccobacillus pathogen. It can be transmitted to humans through secretion droplets and direct close contact (Zhou et al., 2023). H. influenzae can cause swelling in the throat, pneumonia, infectious arthritis, meningitis by invading the fluid around the spine and brain, or bacteremia by entering the bloodstream. Invasive disease usually requires hospitalization and can sometimes result in death (Haemophilus Influenzae’. Types of Infection | CDC, 2022). Pseudomonas aeruginosa is a multidrug-resistant (MDR) opportunistic pathogen that causes acute or chronic infection in immunocompromised individuals (Qin et al., 2022, WHO prioritization of pathogens., 2017), such as ventilator-associated pneumonia (VAP) caused by diseases such as chronic obstructive pulmonary disease (COPD), sepsis and COVID-19 (Yang et al., 2021). Pseudomonas can be found widely in the environment, such as in soil and water. It can spread to people, especially in hospitals, when they interact with these contaminated agents (Pseudomonas aeruginosa Infection | HAI | CDC, 2019). Carbapenem-resistant P. Aeruginosa is at a critical level on the WHO priority pathogen list for which drug development is required first (WHO Publishes List of Bacteria for Which New Antibiotics Are Urgently Needed., 2017). Acinetobacter spp. are catalase-positive, non-motile and aerobic gram-negative coccobacilli (Lin and Lan., 2014). Acinetobacter species have emerged as one of the opportunistic pathogens associated with healthcare (Rady and Amine., 2022). A. baumannii is the most important bacterium among Acinetobacter species that causes the most common hospital infections (Lin and Lan., 2014). Neisseria meningitidis is a gram-negative diplococcus that can cause life-threatening disease (Potts et al., 2022). N. meningitidis (meningococcus) causes significant morbidity and mortality in children and adults worldwide through epidemics or septicaemia. It can be transmitted to people through breathing or saliva. Staphylococcus aureus is a gram-positive cocci-shaped bacteria that can grow aerobically or anaerobically (Taylor and llnakal., 2022). S. aureus is very common in the human population and is an important opportunistic pathogen that causes very high morbidity and mortality globally (Howden., 2023). It causes diseases such as gastroenteritis, prosthetic device infections, urinary tract infections, septic arthritis, bacteremia, toxic shock syndrome and meningitis (Taylor., 2022). Listeria monocytogenes is a facultative rod-shaped gram-positive bacterium and catalase positive (Rogalla and Bomar., 2023). It is widespread in the environment and animals, especially cattle, can be carriers and excrete the bacteria in their faeces. The bacteria can survive for a long time in food processing plants with the ability to survive in acidic, salty, very cold and hot environments. The genus Brucella consists of an increasing number of species that infect a wide variety of mammals as primary hosts, including monkeys, cattle, sheep, goats, camels, pigs, deer, as well as marine mammals such as seals, dolphins and whales (Celli., 2019). Mycobacterium tuberculosis is an obligate pathogenic bacterium of the family Mycobacteriaceae and is one of the top 10 causes of death globally. (WHO prioritization of pathogens., 2017). WHO Global Tuberculosis Report., 2022). M. tuberculosis, a respiratory pathogen, is transmitted only through the air (Russel., 2001, WHO prioritisation of pathogens., 2017).

[0011] Single nucleotide polymorphisms (SNPs) for the detection or discrimination of bacteria are polymorphisms caused by point mutations that lead to different alleles containing bases at a specific nucleotide position (Jin et al., 2016). Due to their high abundance in the genome, SNPs are used as biomarkers (Rahman et al., 2022).

[0012] In document numbered W02007097410A1 encountered in the art, the method of examination of pathogenic bacteria, enterohemorrhagic Escherichia coll and bacteria belonging to the genus Legionella is described. The method was developed to provide a method for the examination of pathogenic bacterial species, including bacteria belonging to the genera EHEC and Legionella, based on polymorphisms in their base sequences that can be stored as text data. Single nucleotide polymorphisms in a large number of base sequence regions that are highly homologous to each other in the genes of pathogenic bacteria are determined and genotypes are determined according to the single nucleotide polymorphism data obtained in this way. The pathogenic bacteria belong to enterohaemorrhagic Escherichia coli and highly homologous base sequence regions, as described above, occur in the prophage genomic sequences of Escherichia coli bacteria. Determination of single nucleotide polymorphisms in the genes of the pathogenic bacteria in question, which are located in a large number of nucleotide sequence regions with high homology with each other, and genotyping is determined according to the single nucleotide polymorphism information obtained. The homologous nucleotide sequence region is selected from the nucleotide sequence regions found in two or more genes in the pathogenic bacterial gene.

[0013] Document numbered CN115838786A encountered in the state of the art describes the detection technology for quantitative live bacterial RNA single nucleotide polymorphism. It describes a detection technology for quantitative live bacterial RNA single nucleotide polymorphism and belongs to the field of nucleic acid detection. The method integrates nucleic acid sequence-dependent amplification techniques (NASBAs) to produce rapid and specific target RNA amplification, as well as amplification inhibitory mutation systems (ARMSs) to increase the specificity of single nucleotide identification by introducing a mismatch to the base group at the 3'end of the forward primer. This enables the identification of high selection in RNA mutation, the sensitive identification of single nucleotide polymorphisms with abundances as low as 0.5% and the detection of Salmonella viable bacteria as low as 80 CFU.

[0014] The prior art document numbered KR101677951B1 discloses a genetic marker for the discrimination and detection of Streptococcus parauberis and a method for the discrimination and detection of Streptococcus parauberis using the same. A genetic marker for the identification and detection of a bacterial pathogen associated with streptococcal infection of fish and a method for the identification and detection of a bacterial pathogen using the same, and more specifically a method for the identification or detection of a bacterial species. Whether a fish is infected with the same type of bacteria depends on its melting temperature, with the following steps: Selection and amplification of a genetic marker containing a bacteria-specific single nucleotide polymorphism (SNP) among the DNA sequences encoding the 16S rDNA of Streptococcus parauberis.

[0015] In the document numbered KR101677952B1 seen in the state of the art, genetic marker for the discrimination and detection of Lactococcus garvieae and the method for the discrimination and detection of Lactococcus garvieae using the same are described. A genetic marker for the identification and detection of a bacterial pathogen causing streptococcal infection in fish and a method for the identification and detection of the bacterial pathogen using the same, and more specifically a method for the identification of a bacterium. Determination of whether a fish is infected with the same bacterial species based on its melting temperature by selecting a genetic marker containing a bacterium-specific single nucleotide polymorphism (SNP) of DNA sequences encoding the 16S rDNA of Lactococcus garvieae, the bacterial pathogen that causes and replicates streptococcal infection in fish; hybridising peptide nucleic acid (PNA) that specifically recognises the amplified product; obtaining a temperature-dependent melting profile of the hybridised product through temperature control; and analysing the melting profile obtained.

[0016] The prior art document numbered CN112930406A describes a method for single nucleotide polymorphism (SNP) detection using lamp and blocking primers. This application describes a new method to improve SNP detection under isothermal conditions. In a particular embodiment, the method is based on SNP-based loop- mediated isothermal amplification (sbLAMP) primers, which consist of six primers targeting eight different regions, two of which are responsible for AS-LAMP amplification. A novel unmodified self-stable (USS) primer consisting of a forward blocking primer (FB) and a reverse blocking primer (BB) complementary to the SNP at the 5'-end, which is responsible for preventing amplification and nonspecific amplification of sbLAMP. This application also explains general primer design guidelines. It also showed that the identification was based on the detection of SNP C580Y (a source of resistance to artemisinin-based antimalarial drug treatment) in AT-rich kelch 13 (K13) of Plasmodium falciparum (P. falciparum). Successful application of the method is based on universal primer design guidelines.

[0017] In the document numbered US2010279294A1 seen in the state of the art, Escherichia coli 0157:1-17 detection and genotyping methods are described. A method for detecting and genotyping Escherichia coli 0157: 1-17 strains, including detection of nucleotides at single nucleotide polymorphism (SNP) loci where the nucleotides define SNP genotypes. A method for genotyping Escherichia coli 0157: 1-17 strains, including detection of thirty-two nucleotides at thirty-two single nucleotide polymorphism (SNP) loci; the identity of the nucleotides defines thirty-six SNP genotypes. It is a kit containing multiplex primer triads and one or more primer triads that can detect nucleotides in Escherichia coli SNP loci. It contains methods for the detection of Escherichia coli 0157: H7 strains. It involves detecting Escherichia coli 0157: H7 strains in any of 36 SNP genotypes using multiplex primer sets capable of identifying 32 SNPs. It is used to detect Escherichia coli 0157: H7 strains with increased virulence, Escherichia coli 0157: H7 strains included or to be included in class 8 as defined herein.

[0018] In the state of the art, there is a patent application numbered TR 2016 / 08981 registered in the name of the inventors, and the invention relates to probes, SNP markers and SNP combinations used for the diagnosis of bacterial species. In the invention numbered 2016 / 08981, in particular, SNP Markers, SNP Marker combinations specific to bacterial species, which enable the identification of the inventive bacterial species at the species level, and probes that enable the determination of said SNP Markers are described, and in this technique, detection and diagnosis can be provided with the help of forward and reverse probes.

[0019] The invention differs from the cited existing techniques, and in particular from the application numbered 2016 / 08981, in that the invention enables the diagnosis of multiple pathogenic bacterial species (pathogen diagnosis in bacterial infections) without the need for reverse and forward probe, by detecting SNPs different from the previous one with a single kit.

[0020] Classical serological, biochemical and culture-based tests and classical PCR and qPCR-based molecular methods for disease control in the state of the art are described. However, since the current classical methods have to be applied separately for each bacterial species, they are not profitable in terms of labour and cost, especially for mass testing and reference laboratories where the sample diagnosis rate is high. It may cause different infections in the same sample to be missed. In addition, the sensitivity of these classical methods used in the art is low, some methods take a long time to apply and do not allow the detection of the causative agent, especially in the early stages of some infections. For this reason, an R&D study needs to be conducted in this field. Object of the Invention

[0021] The main object of the present invention is to provide a panel for the differentiation of 17 bacteria at the genus and species level selected from bacteria causing diseases such as lower respiratory tract infections and thorax- related infections, meningitis and other bacterial central nervous system infections, blood circulation infections, skin and subcutaneous bacterial infections, urinary tract infections and pyelonephritis, peritoneal and intraabdominal infections, bone, joint and related organ infections, heart infections and diarrhoea.

[0022] The object of the present invention is to be used for species discrimination and the discrimination matrices of the 17 species as Escherichia coli, Enterobacter spp, Serratia spp, Klebsiella spp, Haemophilus influenzae Pseudomonas aeruginosa, Acinetobacter baumannii, Neisseria meningitidis, Staphylococcus aureus, Streptococcus agalactiae, Streptococcus pneumoniae, Enterococcus faecalis, Listeria monocytogenes, Treponema pallidum, Brucella spp, Mycobacterium tuberculosis, Staphylococcus epiderm idis.

[0023] Another object of the present invention is to identify candidate points that can be used in differential diagnosis in the study conducted with 17 causative species at the species and genus level, and to screen each nucleotide position detected for polymorphism in the equivalent positions of genes / genomes of other members of the same species / genus in the database and to identify 8 SNP biomarkers.

[0024] A further object of the present invention is to enable a difference matrix to be constructed by calculating the identification power for the candidate point of each species.

[0025] The object of the present invention is to determine the nucleotide sequences to be used to determine the genotypes in the bacterial infection panel and the discrimination points on the 23S rDNA gene sequence of 17 species.

[0026] Brief Description of the Invention

[0027] The present invention relates to SNP markers and combinations thereof for the diagnosis and genotyping of 17 species in different samples, which fulfil the above-mentioned requirements, eliminating all disadvantages and bringing some additional advantages.

[0028] In this study with 17 agents at species and genus level, comparisons were made to provide distinction. As a result of the comparison, candidate points that can be used in differential diagnosis were determined. Each detected nucleotide position was screened for polymorphisms in the equivalent positions of genes / genomes of other members of the same species / genus in the database and 8 SNP biomarkers were identified. A difference matrix was created by calculating the identification power for each candidate point.

[0029] Diagnosis of bacterial species is made separately using classical systems. Different methods with different sensitivities can be used to diagnose each bacterial species, and in some infections, early diagnosis cannot be made and multiple infections may be overlooked.

[0030] Escherichia coli (E. coli) is a gram-negative, rod-shaped bacterium belonging to the Enterobacteriaceae family (Pakbin et al.) Some strains, such as Shiga toxinproducing Escherichia coli (STEC), can cause foodborne illness. Listeria monocytogenes is a facultative rod-shaped gram-positive bacterium and catalase positive (Rogalla and Bomar., 2023). It is widespread in the environment and animals, especially cattle, can be carriers and excrete the bacteria in their faeces. The bacteria can survive for a long time in food processing plants with the ability to survive in acidic, salty, very cold and hot environments. These and similar bacteria cause deaths, poorer quality of life and shorter life spans. To overcome this burden, health systems need to be strengthened with better diagnostic equipment, infection control and antimicrobial stewardship, as well as preventive initiatives such as safe food and water and immunisation (Ikuta vd.., 2022).

[0031] Different bacteria cause different infections. The gene sequences of each bacterium are not the same as those of another; they show species-specific differences. With the help of the invention, these genus differences of different bacterial species are detected in multiple samples, enabling simultaneous diagnosis with high accuracy and sensitivity. The differences (SNPs) of bacterial species subject to this application were identified for the first time in this study. The probe sequences determined for each bacterium for diagnosis were determined for the first time in this study. It is possible to analyse the target bacteria of the panel independently from the sample or tissue source (blood, FFPE tissues, fresh tissue, food sample, etc.) from which they are isolated.

[0032] The comparison of the solutions in the state of the art and the solution developed 5 with the invention subject to this application is given in the table below.

[0033] Table a: Comparison of the state of the art with the invention in terms of features io Detailed Description of the Invention

[0034] In this study with 17 agents at species and genus level, comparisons were made to provide distinction. As a result of the comparison, candidate points that can be used in differential diagnosis were determined. Each detected nucleotide position was screened for polymorphisms in the equivalent positions of genes / genomes of 15 other members of the same species / genus in the database and 8 SNP biomarkers were identified. A difference matrix was created by calculating the identification power for each candidate point. Below is a list of bacteria that are distinguished by species in the invention.

[0035] 20 Table 1. List of 17 species distinguished by the panel

[0036] In the study conducted with the NCBI BLAST tool, the NCBI nucleotide database was searched and biomarkers that can diagnose Escherichia coli, Enterobacter spp, Serratia spp, Klebsiella spp, Haemophilus influenzae Pseudomonas aeruginosa, Acinetobacter baumannii, Neisseria meningitidis, Staphylococcus aureus, Streptococcus agalactiae, Streptococcus pneumoniae, Enterococcus faecalis, Listeria monocytogenes, Treponema pallidum, Brucella spp, Mycobacterium tuberculosis and Staphylococcus epidermidisi were searched and identified.

[0037] Diagnosis panel in the system of the present invention comprises the following steps;

[0038] • Preparation of queries and downloading from open access database,

[0039] • Recording the information that will cluster the data into the desired categories in the local database,

[0040] • Aligning gene sequences and rearranging them in the database,

[0041] • Identifying conserved and variational regions within aligned gene sequences,

[0042] • Detection of SNPs within conserved regions,

[0043] • Defining a combinatorial panel of identified SNPs that can be used in the diagnosis of 17 species.

[0044] Table 2. NCBI Entry Accession Numbers of 23S Gene Sequences Used

[0045] In the invention, the highest priority was determined as the alignment of a large number of gene sequences belonging to 17 different species with precision and high performance. The targeted vehicle was divided into small and divided parts, the results of each stage were examined and the tasks to be performed for the iteration were redefined according to the success of the results. In this context, the Strategy- Based Local Alignment Tool was developed as a software that can perform the above-mentioned process steps and ODOTool, which was first mentioned in the article published in 2020 (Ugurel et al., 2020a). Local databases created within the scope of the software were prepared on the Python v3.8.10 platform using the Microsoft MySQL v8.0.32 platform. Biopython vl.75 library (Cock et al., 2009) was used as the alignment tool and Needleman- Wunsch algorithm (Needleman and Wunsch, 1970) was chosen as the alignment algorithm. C# v9.0 platform was also used in SNP detection and combination calculation steps. The nucleotide sequences used to determine discriminatory genotypes are given below. Establishment of a diagnostic panel that enables the identification of BEscherichia coii, Enterobacter sp, Serratia sp, Klebsiella sp, Haemophilus influenzae Pseudomonas aeruginosa, Acinetobacter baumannii, Neisseria meningitidis, Staphylococcus aureus, Streptococcus agalactiae, Streptococcus pneumoniae, Enterococcus faecalis, Listeria monocytogenes, Treponema pallidum, Brucella sp, Mycobacterium tuberculosis and Staphylococcus epidermidis species / genera at the species level and the identification of multiple bacterial pathogens or species / genera in a single sample to ensure species identification by creating genotype difference between species, characterized in that; it comprises the following process steps; preparation of queries and downloading from open access database, recording the information that will cluster the data into the desired categories in the local database, aligning gene sequences and rearranging them in the database, identifying conserved and variational regions within aligned gene sequences, detection of SNPs within conserved regions, defining a combinatorial panel of detected SNPs that can be used in the diagnosis of bacteria species.

[0046] Table 3. Nucleotide sequences used in determining genotypes

[0047] SNP1 SNP2

[0048]

[0049] The separation points on the nucleotide sequences determining the genotypes are given below.

[0050] Table 4. Discrimination Points and Genotype Combination Table on 23s rDNA Gene Sequence of 17 Species

[0051] Sensitivity and specificity of the identified SNP biomarkers were investigated using the BLAST tool. The BLAST tool (Basic Local Alignment Search Tool) is an alignment search engine for analysing nucleic acid and protein sequences of the GenBank database used in bioinformatics studies. This verification analysis was conducted in two stages. In the first stage, the oligo sequence to be used in genotyping was scanned for genomes that belonged only to that organism and could not be used in SNP detection, and the intra-species polymorphism risk of the detected SNP was examined. In the second stage, the risk of cross- reactivity between other species in the same panel and the risk of similarity to a region found in all genomes was investigated. SNP points determined in this study create genotype differences between species. In the following inter-species discrimination profiles, for each species the SNP number that distinguishes it from the opposite species is expressed. Interspecies Discrimination Matrix is given in the following table Table 5. Interspecies Discrimination Matrix

[0052] As a result of BLAST validations, it was determined that these 8 points were usable in the panel. The BLASTN control of SNP number 5 belonging to Escherichia coli is shown as an example in Figure 1.

[0053] As a result, with the SNPs obtained, a panel that will provide discrimination for the diagnosis of 17 bacterial species created within the scope of the thesis and the SNPs determined for the discrimination of 17 species, SNP combinations and nucleotide sequences to be used to determine these SNPs were created. The ability to detect multiple bacterial pathogens in a single sample will help identify outbreaks and track the spread of infections. Additionally, the panel can be used to monitor the effectiveness of antibiotic treatment and identify emerging patterns of antibiotic resistance. Future research may focus on expanding the panel to include additional bacterial pathogens and optimizing the assay for use in point-of-care settings.

Claims

CLAIMS1. A diagnostic panel that allows the identification of genetic markers and the differentiation of more than one bacterial pathogen or species in a single sample, and allows the identification of Escherichia coli, Enterobacter sp, Serratia sp, Klebsiella sp, Haemophilus influenzae Pseudomonas aeruginosa, Acinetobacter baumannii, Neisseria meningitidis, Staphylococcus aureus, Streptococcus agalactiae, Streptococcus pneumoniae, Enterococcus faecalis, Listeria monocytogenes, Treponema pallidum, Brucella sp, Mycobacterium tuberculosis and Staphylococcus epidermidis species / strains at the species level, which cause diseases such as lower respiratory tract infections and thorax-related infections, meningitis and other bacterial central nervous system infections, bloodstream infections, skin and subcutaneous bacterial infections, urinary tract infections and pyelonephritis, peritoneal and intra-abdominal infections, bone, joint and related organ infections, heart infections and diarrhea, and enables species detection by creating genotype differences between species, characterized in that; the following SNP or SNP combinations provide species identification by creating genotype differences between species of 17 active microorganisms,2. The SNP or combination of SNPs according to claim 1, characterized in that; the discrimination matrix of the 17 species is said SNP points on the 23S rDNA gene sequence.

3. The SNP or combination of SNPs according to any one of the preceding claims, characterized in that; said SNPs have the following nucleotide sequences enabling their identification;SNP5 SNP6SNP7 SNP84. The SNP or combination of SNPs according to any one of the preceding claims, characterized in that; the SNP numbers mentioned in the interspecific discrimination profiles providing for each species the interspecific discrimination matrix given below, where each species is separated from the other species5. The SNP or SNP combinations according to any one of the preceding claims, characterized in that; BLAST, which provides an alignment for the analysis of nucleic acid and protein sequences belonging to the GenBank database used in bioinformatics studies, and enables the determination of the sensitivity and specificity of the determined SNP biomarkers.

6. The SNPs or combinations of SNPs according to any one of the preceding claims, characterized in that; NCBI is the nucleotide database that provides biomarkers for the diagnosis of 17 species.

7. Establishment of a diagnostic panel that enables the identification of BEscherichia coll, Enterobacter sp, Serratia sp, Klebsiella sp, Haemophilus influenzae Pseudomonas aeruginosa, Acinetobacter baumannii, Neisseria meningitidis, Staphylococcus aureus, Streptococcus agalactiae, Streptococcus pneumoniae, Enterococcus faecalis, Listeria monocytogenes, Treponema pallidum, Brucella sp, Mycobacterium tuberculosis and Staphylococcus epidermidis species / genera at the species level and the identification of multiple bacterial pathogens or species / genera in a single sample to ensure species identification by creating genotype difference between species, characterized by comprising the process steps of; preparation of queries and downloading from open access database, recording the information that will cluster the data into the desired categories in the local database, aligning gene sequences and rearranging them in the database, identifying conserved and variational regions within aligned gene sequences, detection of SNPs within conserved regions, defining a combinatorial panel of detected SNPs that can be used in the diagnosis of bacteria species.

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