BG67567B1 - Quantitative assessment method for rapid prediction and control of dysbiosis in breast-fed newborns aged one month to one year - Google Patents

Abstract

The present invention relates to a method for in-vitro assessment and prediction of the balance of intestinal microbiomes in newborns aged from one month to one year. Said method is based on an integrated approach which includes calculation of correlation factors between key indicators divided into three main groups: 1. Correlation between the composition and quantity of microorganisms found in the breast milk and in the feces of the infant; 2. Correlation between the enzyme profile and the activity of enzymes responsible for the absorption and metabolism of breast milk components (lactose, lipids, oligosaccharides, proteins) found in the breast milk and in the feces of the infant; 3. Correlation between the quantity of metabolites resulting from the metabolism of breast milk components by microbiomes and found in the breast milk and in the feces of the infant. The method according to the present invention enables the rapid prediction of dysbiosis in breast-fed infants aged from one month to one year. Thus, it would be applied in the protocol for accurate diagnosis of the intestinal microbiomes in newborns aged from one month to one year. Furthermore, the method also facilitates the making of a rapid subsequent identification of the type and gravity of dysbiosis.

Description

The present invention relates to the field of medical diagnostics, pharmacy, biotechnology.

Prior art

There is mixed evidence that breastfeeding provides significant protection against infectious and inflammatory diseases, various disabilities, and improves cognition (Bartick and Reinhold, 2010; Dieterich et al., 2013; Kramer et al., 2009). This is largely due to the properties of breast milk and its oligosaccharides to influence microbial colonization in newborns. Palmer et al. (2007) showed that infants are colonized with approximately 107 different types of microorganisms during the first week of life. These close relationships of the organism with the gastrointestinal microflora may underlie and be critical in relation to the health of the newborn, as well as the risk of developing various other non-infectious diseases. In fact, optimal breastfeeding remains a highly effective public health strategy for infant survival, especially for reducing mortality due to gastroenteritis and pneumonia in developing countries (Bhutta et al., 2013). Research on breastfeeding has shown the protective role of breast milk against many chronic and immune conditions, in particular, type 1 diabetes, necrotizing enterocolitis, asthma and leukemia (Bartick and Reinhold, 2010).

The development of the microbiota in the digestive system of the newborn is a gradual and dynamic process that is determined by several factors, such as mode of birth, prematurity, type of feeding, associated diseases and antibiotic therapy, as well as environmental influences, which necessitates a personalized approach (Wall et al. 2009). In addition, the colonization process is strongly influenced by the diet (milk and/or formula). During the first month after birth, bifidobacteria and coliforms (especially E. coli) are predominant, followed by Lactobacillus spp. and Bacteroides and varies widely between individuals (Wall et al., 2009). Changes in the ratio of the dominant representatives of the intestinal microflora of newborns appear after about one year of life, mainly as a result of introducing new food into the baby's diet. The number of representatives of Lactobacillus spp., Bacteroides spp. and Clostridia increased while bifibroids and E. coli decreased. Finally, at around 2 years of age, gut microbial communities reach a composition similar to that found in the adult gut (Koenig et al. 2011). The species Bifidobacterium longum is the most common initial colonizer of the gastrointestinal tract of neonates (Palmer et al., 2007).

Human milk possesses multiple mechanisms to protect newborns: immune response cells, immunoglobulins, innate defense proteins, peptides, free fatty acids, cytokines and chemokines, glycans and oligosaccharides (Ballard and Morrow, 2013). Among the various bioactive components of human milk, oligosaccharides are the most abundant and include significantly more than 100 different bioactive carbohydrates built from 3 to 32 monosaccharides (Newburg et al., 2005). As a class, oligosaccharides are 6 - 12 g/L of breast milk and are largely synthesized from lactose (Bode, 2012). Human colostrum contains approximately 22 - 24 g/L milk oligosaccharides (Newburg et al., 1995; Urashima et al., 2012). In human milk, oligosaccharides are the third most concentrated component after lactose and lipids, and their amount is much higher than that of proteins (Newburg et al., 1995). The structure of more than 100 human oligosaccharides has been characterized to date (Urashima et al., 2011a,b; Kobata, 2010). Characterization of the physiology of bifidobacteria has focused largely on their ability to metabolize various dietary oligosaccharides. This genus of bacteria possesses a set of transmembrane permeases that ensure the metabolism of various carbohydrate polymers, such as dietary fiber, including human milk oligosaccharides, which pass undigested to the distal parts of the digestive tract (Moro et al., 2006; Macfarlane and Cummings, 1999).

There are only a few species of bifidobacteria capable of metabolizing and using human milk oligosaccharides as a carbon source. Such species are typically isolated primarily from the microflora of the gastrointestinal tract of newborns. Neonatal-associated bifidobacteria have been found to be capable of predominantly digesting lacto-N-tetraoses (LNT) or lacto-N-neotetraoses (LNnT) (LoCascio et al., 2007).

B bifidum secretes an extracellular 1,2-n-1-fucosidase (EC 3.2.1.63) that cleaves terminal 1,2-vfucosyl bonds that protect galactose residues in lacto-N-biose, thus allowing catabolite processes to continue until their complete absorption (Katayama et al., 2004; Nagae et al., 2007). In addition, lacto-N-biosidase (EC 3.2.1.140) releases lacto-N-biose from lacto-N-tetraose and from other milk oligosaccharides lacking fucosylation or sialylation (Wada et at., 2008). Once produced, lacto-N-biose is transported across the cell membrane by a special ABC transporter that integrates a lacto-N-bioso binding subunit (Suzuki et al., 2008; Wada et al., 2007). B. longum is also known to use endo-β-N-acetylgalactosaminidase (EC 3.2.1.97) to extract galacto-N-biose from O-linked mucin glycans (Fujita et al., 2005). Indeed, the presence of both endo-N-acetylgalactosaminidase and fucosidase activity enables B. bifidum to degrade mucin (Ruas-Madiedo et al., 2008). Data on the absorption of oligosaccharides from breast milk by lactobacilli and the remaining accompanying microflora are scarce, as there are no specific correlations in the direction of type of enzyme-enzyme activity-type of microorganism-quantity of microorganisms.

Metabolites are a consequence of the physiological state of the human organism on the one hand, and on the other hand of the physiological activity of the accompanying microflora in the intestinal tract. This makes them an ideal way to track changes caused by a disease state or treatment. Assessing the amount and diversity of metabolites is particularly important for understanding the multiple interactions between genetics, environment, and microbiota. At key points in the metabolic processes where they intersect, low molecular weight metabolites mediate these relationships.

Researchers are looking at the microbiome as a potential source of biomarkers for various diseases. Although this may be a fertile area for biomarkers, there are many examples of different metabolites being associated with the same disease, which reduces their reliability as biomarkers.

Another indicator whose potential is being investigated as a biomarker is the pH values of faecal samples. There is evidence that they directly correlate with the bacterial species colonizing the baby's gut. For example, a direct correlation was found between lower pH values of faecal samples and significantly reduced amounts of potentially pathogenic bacterial populations (ie Clostridiaceae, Enterobacteriaceae, Peptosteptoccocaceae and Veillonellaceae). Another example is the correlation found between the abundance of specific Enterobacteriaceae species that cause intestinal inflammation and the presence of colic in infants. These unfavorable effects may be due to the fact that lipopolysaccharides derived from enterobacteria induce stronger inflammatory activity compared to other lipopolysaccharide-producing bacteria.

Asthma is the most common chronic disease of childhood. A correlation has been established by Canadian scientists between changes in the gut microbiome in babies up to one year (dysbiosis) that affect the development of asthma. The effects of gut microbial dysbiosis on atopic wheezing in a population living in developing countries with a low economic standard were investigated. Microbial dysbiosis at 3 months of age is associated with later development of atopic wheezing. For example, dysbiosis was observed in Ecuadorian infants involving various bacterial taxa, including several taxa of microscopic fungi. Faecal short-chain fatty acid levels in three-month-old infants with atopic wheezing showed clear trends of increased acetate concentration and decreased caproic acid concentration.

Some of the protective mechanisms of human milk are due to oligosaccharides. Given the increasing rate of disease associated with dysregulated host microbiota and immunity, there is global interest in testing novel nutritional approaches and functional foods matching those found in breast milk to optimize host health and restore the bacterial flora. The data from the literature described so far prove that the research models used both for diagnostic purposes and for microbiota control in children up to one year of age cannot provide an algorithm for a quick and reliable assessment of the state of the intestinal microbiota and its association with various diseases , because they are linear, referred to only one indicator.

The creation of a quantitative assessment method for the rapid prediction of dysbiosis in infants from 1 month to 1 year and for the study of deviations in the human microbiota requires an interdisciplinary approach and in the final assessment may include the data from different research methods that are processed as databases with specific computational techniques.

Technical essence of the invention

The task of the invention is to create a method based on in vitro quantitative assessment, which will provide an opportunity for rapid prediction of dysbiosis in infants aged 1 month to 1 year, and which will find application in creating a model (algorithm) for precise diagnosis of the intestinal microbiota in newborns aged one month to one year, and the method also helps to quickly establish the type of dysbiosis and the degree of disorder. The method is based on an interdisciplinary approach in the analysis of the quantitative and qualitative composition of the microbiota, the type and quantity of key enzymes and metabolites and data analysis by means of an information system.

Over the past few years, studies have revealed that both colostrum and breast milk from healthy women contain bacteria, including staphylococci, streptococci, corynebacteria, lactic acid bacteria, propionobacteria, and bifidobacteria (Fernandez et al., 2013). Recently, the application of various techniques, including metagenomic approaches, confirmed the presence of DNA from these and other bacterial genera in breast milk and colostrum (Hunt et al., 2011; Cabrera-Rubio et al., 2012; Fernandez et al., 2013; Jost et al. al., 2013, 2014; Ward et al., 2013; Jimenez et al., 2015). Therefore, these biological fluids are continuous sources of live bacteria to the gastrointestinal tract (McGuire and McGuire, 2015) Other studies have shown that there is a transfer of bacterial strains from mother to infant in the breastfeeding process (Albesharat et al., 2011; Martin et al., 2012; Jost et al., 2014). Despite some established correlations of the amount and composition of the intestinal microbiota with the detection of certain diseases, the molecular biological methods used are lengthy and expensive for daily practice, which makes them inaccessible for mass use. There are no established correlations with data on key enzymes and metabolites responsible for the absorption of specific components from colostrum and breast milk and their concentration dynamics when changing the diet and overcoming intestinal dysbiosis.

Some bacteria from the infant's oral cavity can contaminate milk during suckling due to backflow of milk into the milk ducts (Ramsey et al., 2004). Within 24 hours after birth, colostrum has been found to contain typical oral bacteria such as Veillonella, Leptotrichia and Prevotella (CabreraRubio et al., 2012). Although the origin of the human salivary microbiome is still rather poorly understood (Zaura et al., 2014), Streptococcus spp. appears to be one of the dominant species in both adults (Nasidze et al., 2009; Yang et al., 2012) and infants (Bearfield et al., 2002; Cephas et al., 2011). Streptococci are also among the dominant species in human colostrum and breast milk (Jimenez et al., 2008a, b; Hunt et al., 2011; Martin et al., 2015). It has been shown that the oral health of the mother correlates closely with the likelihood of developing dental caries in the child (Zaura et al., 2014). Certain compounds in human milk (eg, human milk oligosaccharides, proteins) may affect the colonization of individual species indirectly. For example, milk proteins such as caseins and lactoferrin have been found to have the ability to inhibit the attachment of cariogenic streptococci to hydroxyapatite and promote the attachment of commensal bacteria in vitro (Johansson and Lif Holgerson, 2011). There have been no sufficiently large-scale and long-term studies characterizing the development of the oral microflora during the neonatal period and childhood. In initial studies, it was thought that oral colonization by dental caries-causing bacteria could occur after the first baby teeth erupted in the newborn, but it was later shown that the cariogenic Streptococcus mutans could be present in the infant's oral cavity before the appearance of hard tissues there (Law et al., 2007).

Epidemiological studies reveal a number of environmental exposures associated with asthma. This could explain the escalation of asthma over the past 30 years. Infants at risk of asthma exhibit transient states of gut dysbiosis and metabolic changes (eg, urobilinogen) during the first 3 months of life. These metabolites or differences in the microbiome are used in the design of advance for the use of probiotics or to serve as prognostic biomarkers. A model was developed by combining estimates of ecosystem productivity and the generation of ecosystem services for the definition of dysbiosis in infants. According to him, the gut microbiome is characterized by: 1) no disturbance in the composition and amounts of taxa when changing the diet or taking antibiotics; 2) high susceptibility to invasion by external taxa; and 3) poor use of available resources (including breast milk oligosaccharides). The healthy/balanced state of the microbiota is characterized as a highly functioning ecosystem when the gut microbiome is: 1) stable over time in terms of composition and amount of taxa, 2) resistant to invasion by allochthonous bacteria; and 3) to demonstrate high conversion of breast milk oligosaccharides into end products and biomass beneficial to infants. This model is agnostic by method and selection index and provides a quantitative indicator and an objective approach to assess the microbiome, but it is mainly limited in data on the composition and quantity of microorganisms and is not based on correlations between composition and quantity of microorganisms, activity of enzymes , responsible for the absorption of oligosaccharides from breast milk and the amount of metabolites secreted by the microbiota.

The present patent application relates to the development of a specific in vitro quantitative assessment method for the rapid prediction of dysbiosis in infants aged 1 month to 1 year, in which the possibility of controlling the human microbiome is achieved, as the method described take into account, on the one hand, general indicators such as age and gender, and on the other hand, the specific indicators of a person's state of health. The proposed method is based on the processing of data from analyzes of the diversity and ratio of microorganisms in the intestinal tract of the child and other body fluids (saliva, breast milk, feces), the amount of metabolites used as biomarkers and reporting the level of enzyme activity of enzymes, used as biomarkers, allowing consideration of the individual characteristics of people.

The method, the subject of the present patent application, is based on an integrated approach for in vitro analysis of the balance of the intestinal microbiota in children from one to twelve months and prediction of its recovery in case of established dysbiosis, by means of the calculation of correlation coefficients between key indicators divided into three main groups:

1. Correlation between composition and amount of microorganisms in mother's breast milk and in the child's feces.

2. Correlation between enzyme profile and activity of enzymes responsible for absorption and metabolization of breast milk components (lactose, lipids, oligosaccharides, proteins) in a sample of breast milk and a sample of the child's feces.

3. Correlation between the amount of metabolites obtained from the metabolization of the main components of breast milk by the microbiota in breast milk and in the child's feces.

The in vitro quantitative assessment method for rapid prediction of dysbiosis in infants up to one year requires the following course of analysis:

1. Protocol for quantitative analysis of human microbiota by real-time qPCR. The presented protocol can be applied to establish deviations for analysis of dysbiosis in newborns from one to twelve months and be included in an algorithm for identifying condition, deviations and rules for restoring the microbiota balance. Through it, it will be possible to quantify different groups of microorganisms from the beneficial and pathogenic microflora, which can be used to calculate the ratios between individual species (table 1). Of essential importance for determining the degree of dysbiosis are the bifidobacteria/bacteroid ratios; lactobacilli/bacteroides; (bifidobacteria+lactobacilli)/bacteroids;(bifidobacteria+lactobacilli)/yeasts;

(bifidobacteria+lactobacilli)/E. coli. Another important indicator is the ratio between bifidobacteria and the main enzymes responsible for digesting the main components of breast milk (lactose, lipids, proteins, oligosaccharides).

The values of the individual ratios vary depending on age, health and diet. The range of ratios in healthy subjects is presented in Table 6.

Bi LAB Vas Dr Bi E a- C- a- Lip Pro Μ fi ter aw fa cob yes! gat fuc ase tea em df old du du/ act att mi se ab es asi an das on 5 des das e am is e μ we Sacreraitfes Yeast £_ eoM a- — ______ 1 in-gatactasfdasn a-fucosidosc Lipase Protease — --- | Metabolites L 1

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Table 1. Model of comparison of the data from the 12 investigated indicators.

2. Analysis of enzymes in samples of breast milk and feces from children from one to twelve months, which are responsible for metabolizing the main components of breast milk (lactose, oligosaccharides, lipids, proteins - β-galactosidase, α-galactosidase, α-glucosidase , β-glucosidase, α-fucosidase, lipase, protease). For the purposes of the method, the ratios between the individual enzymes are calculated, which gives information about the type of metabolic processes that take place, and on the other hand, they give information about the capacity of the beneficial microflora to maintain the balance of the intestinal microflora. The enzyme α-fucosidase gives direct information about the adhesion potential of the beneficial microflora (bifidobacteria and lactobacilli) on the epithelial cells of the intestinal mucosa, while the other enzymes give information about the rate of reproduction of the beneficial microorganisms and their place with this specific ecological niche. Enzyme amount data correlates with metabolite amount data found in the respective samples. The ratio range of enzyme activity values is described in Table 6.

3. Analysis of the amount of short-chain fatty acids in samples of breast milk and feces of infants from one to twelve months. The quantitative analysis of lactate, acetate propionate and butyrate in samples of breast milk and feces of babies up to one year of age provide objective information about the metabolic processes carried out with the participation of the accompanying microbiota. The presence of short-chain fatty acids is a direct confirmation of the functional activity of bifidobacteria and lactobacilli. The ratio between the individual groups of microorganisms described in the first point of the proposed method and the amount of short-chain fatty acids provides essential information about the balance of the microbiota and its functional state. Furthermore, for the purposes of the proposed method, the ratios between the enzyme activities of the enzymes from the second point (the second stage of the analysis) and the amount of short-chain fatty acids can be calculated. The ratio range of enzyme activity values is described in Table 6.

4. Calculation of the correlation dependences between the ratios of the individual components to define the status of the microbiome in children from one to twelve months. Our proposed in vitro model for the determination of intestinal dysbiosis in children from one to twelve months, as a state of the specific ecological niche in the intestinal tract, correlating with a reduction in the risk of acute and chronic diseases. In addition, the model may provide a framework for evaluating the effectiveness of strategies for the prevention and treatment of intestinal dysbiosis.

Examples of implementation of the invention

Example 1

In vitro study of 12 indicators of microbiota balance assessment in infants from one month to twelve months:

1. Protocol for quantitative analysis of the human microbiota by real-time qPCR.

The presented protocol can be applied to establish deviations for analysis of dysbiosis in newborns from one to twelve months and be included in an algorithm for identifying condition, deviations and rules for restoring the microbiota balance.

A. Primers and fluorescently labeled probes for real-time qPCR detection of bacterial groups and species in samples from target groups.

Primer pairs and fluorescently labeled probes for performing real-time qPCR detection of bacterial species and communities and in samples from the target groups are presented in Table 2

Table 2. Primers and fluorescently labeled probes for real-time qPCR detection of bacterial groups and species in the presented study.

Ttprentt Oiitrishpa group· IM sang PrgVchgrki indie HaTirfttWK i Bifidobacterium ip. Bif-F Bif-R TCGCGTC KGGTGTGAAAG CCAC ATCCAGCRTSSAC Rinffita e! cl!, 2004 ____________________[, iumr/ildel, G r t v is 1 t i i a FcWsfiiyrmtioriiH BPP-F BPP-R GGTGTCGCrCTTA AGTGCCAT CGGAYGTAAGGGCCGTGC tiirwia fl al. 20&t Loctobucilius Lacb-F 1 .act*· Fl AGCAGTAGGGAATC ГГССА CAСГПСТАСАCACATGGAG Wafer ci ui.. iWf Heitigfio! _t Bijidchaetemirrt F Bifid 04c RBiHd 06 CGGGTGAGTA ATGUGTG ACC TGATAGGACGCGACCCCA Phew! Bacteraidei, PrcvotcHe F Barter II R Bartct 08 CCTWCOATGGATAGGGGTT C ACGCTACTTCXXTTGGTTCA G Fuki et uL 2i?(W Luctiihailllti» Ltueotoitnc, ReLostSgit FJ.actt DS R L-Mto tM agc act aggg a atcttcc a cgccactggtgttcvtccatata Fum ft tit-. 1009 Total 4pciha bacterial microflora F Ban 1369 R~Prokl4« cggtgaatacgttcccgg tacggctaccttgttacgactt cl pl,. lOM F CkptOD RCiept DU CCTTCCGTGCCQSAGTTA GAATTAAACCACATACTCCACTOCTT Fwct ct at 1009 CiaiSritiivm ctxcaitlei FCcoc 07 R_Ccoc 14 GACGCCOCGTGAAGGA AGCCCC AGCCTTTC ACATC Fiwt etat. 1009 Bifiitfibaeieriiirt probe P_Bifid tFAM-CTCCTGGAAAC6<4i TG-HHQ-I Furet at at.. 2009 Butltrfildfi, Pwalella OWJW PBkJOj HEX-AAGGTCCCCCACATTG-bmq-i Atanzcfat, 1996 To Til of CrbKna bacterial ni iroflpra Probe P TMISIOF ό F A M*CTTG T A C A C ACCGCCC □ TC BHQ-I Sublet et al., 2000 Ootfridutm itptum Probe FclepOl 6FAM- CACAATAAGTAATCCACCBHQ- Fort tint.. 2009 ' Clwiridwm eocenides Ssnklia F_Lr«4H2 HEX- CGGTACCTGACTAAGAAGUHQ*I Frenis eta), i9Wi

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2. Control bacterial strains

Bacterial strains used to control the specificity of the primers and labeled probes used, as well as for the quantitative assessment of individual bacterial species and communities are presented in Table 3. The strains used were purchased from the National Bank for Industrial Microorganisms and Cell Cultures (NBPMK) and the German collection of Microorganisms and cell cultures (DSMZ). The strains are cultivated aerobically or anaerobically in selective nutrient media, according to the recommendations of NBPMK and DSMZ. Dilution series were made from the grown cultures for each strain and plated on the appropriate agar medium in a petri dish to determine the total number of bacterial colony-forming units (CFU). Additionally, samples of 1.0 ml are taken from the dilutions, which are centrifuged under the following conditions: 12000 rpm/3min. The obtained sediments of bacterial cells were stored at - 80°C until their use for analysis.

Table 3 Control bacterial strains used in the study

Save Hrwmrc Prvlakpik n rtsoMM DNA ιψ· ipeuaw PCR _ Lactobacillus deibruectit subip. ButgarKus 1113-2 T ΗΕΠΜΚΚ detection nv Lactnhaciilus, without yugalavance nnd fluorescent probes Laciobacillus acidophilus IBW T NBPMKK leteici* of Laetabaciifus, 6ci ncgshshmne of fluorescent sieves tjiiiiituKittui rhuittnasur 1010 T HbilMKK detection of Loctolmciil^ without the use of fluorescent probes BtfiitebacteruM longvm iubsp. inngum DSM*20219 DSMZ detection of Bifidobaciermni, without the use of fluorescent «ndI Bacieraidet /rugllil DSM-2151 DSMZ detection nv without nzpsshshe of fluorescent isdn ndulescintis 3 DSMZ detection of Bifidirhticteriitm, with fluorescently labeled probes BifidobtKiifrmm Icmgwn sutsp. infunhs D$M-2M88 D5MZ detection of Bijidiibacterium, is fluorescently labeled probes Bifidobacterium breve DSM-202 i J DSMZ detection of Bifidobacterium, with fluorescently labeled probes Ch>slridiun> tepirtm ΟΐΜ-753 DSMZ detection cd with fluorescent labeled probes Clostridium eoeeoidtt (Siautla iueeoidts) D5M-935 DSMZ detection nv Closindium is a fluorescent beta nv probes

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3. Isolation of DNA from bacterial cultures and samples from the target groups

Bacterial genomic DNA from control strains and isolates from target group samples was extracted using the Blood and Tissue kit DNeasy (Qiagen, Hilden, Germany).

Microbial DNA from faecal samples and from breast milk was isolated QIAamp DNA Stool mini kit (Qiagen, Hilden, Germany). Initially, 200 mg of faecal sample/milk was diluted with 1.8 ml of sterile Pbs buffer. To 200 μΐ diluted faecal sample, 20 μΐ lysozyme (150 mg/ml) and 130 μΐ lysis buffer (2.0 Mm Na2EDTA; 20 Mm Tris-HCL; 1.2 1.2% Triton X-100) were added. The mixture was incubated at 37°C for 30 min, after which DNA was isolated.

4. Quantification of DNA

The amount and frequency of bacterial genomic DNA isolated from the standard strains and from the tested samples was determined spectrophotometrically. For this purpose, the absorbance of the suitably diluted DNA samples was determined at wavelengths of 260 nm and 280 nm. Measurements were performed on a Shimadzu UV-2600 spectrophotometer at an 8.5 mm light beam, after zeroing the apparatus against a cuvette with elution buffer. Homogeneity of genomic DNA was determined by visualizing the isolated DNA in a 1% (w/v) agarose gel by electrophoresis and staining with ethidium bromide. Samples with isolated DNA were stored at -20°C.

5. Conduct Real-time qPCR

Real-time qPCR reactions for detection and quantification without using fluorescent probes used SYBR Green PCR Master Mix (Applied Biosystems). Reactions were plated in 96-well plates with a final volume of 25 μΐ each. Reactions were performed on a real-time PCR CFX96 Touch (BIO-RAD) with software version 3.0.1224 under conditions for each of the target groups indicated in Table 4.

Table 4 Primers and reaction conditions for performing real-time qPCR for the quantification of bacteria in faecal samples.

DryaTsyamrn· dmMkya The whole collapsed Reanshtta umvshts it Bi UF and Bif-R 1 Bifiiiubaclcrimii Take measures - 0.5 μ M each; Presnsturaiia-3 m in^5 *C; Dsshturztzsh - |5 “C; Connect the meters 20, Uyam*avdns “ 30 sci/72 X; Detection )0 «cXOH; Number of weeks - 35- BPP-F in BPP-R Ulgrkugptopt PrYYiertz -0.5 dM kskch; Prszhniturapig - 5 ntih/95 X; Dsiiuraci* |5«t/95X; Connecting the primes - 20 "C; He lied - 30 sec/72 X; Detection - 30 ZSS&O X; Number of cycles -35. Latb-F and LaclabaciHia Primers 0.5 μΜ incl.; Before μggurail - 5 Ηΐίη/95 X; Dsn^turalaya - 15 sw-45 X: Binding of the primers - 20 «s/58 X; Flash - 30 ms/72 X; Detection - 30 kCSO X; Number incl.-35.

F Jjirto 05 and R_Latie> 04

Example^ - 0.2 μ M lsec; Prsde(|shgu1I11nv - 10 min'95 Deiaturation - 30 soc^S X; € binding of primesrlts - 30 («Μ X;

Udio*ayang I min.T2 °C;

Detection - 30 tes/NAU *With Number of tsnclcs Yu.

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Real-time qPCR reactions for detection and quantification of bacteria using fluorescently labeled probes used TaqMan Universal PCR Master Mix (Applied Biosystems). Reactions were seeded in 96-well plates with a final volume of each reaction of 25 μΐ. Conditions for conducting each of the assays to determine the target groups of bacteria are listed in Table 5.

Table 5. Primers, fluorescent probes and reaction conditions for conducting Real-time qPCR for the quantification of bacteria in faecal samples.

Prajmkrpdm&k* Whole group yr And detection ¹ F Bifid 09c, R Bifid 06. probe Bifidobacterium Prdymsri - 0.2 μ M each; Probe - 0.2 μΜ: Prelenaturacil - 10 min^S C; Denaturation - 30 sec/95 ΎΖ; Extension of nraimerte n children = 1 τηϊπ/60 C: Spoil cycles = 40. F Bactcr 11, R Banter OS, PBasZOZ probe Bacteniides*. Prevaietla F Bart 1369. R 1492, probe Determination of total bacterial count F Ckpt 09, R Clepi 08, PilepOl probe Clostridium leprum F CcocOT, R Ccoc 14, probe P”Erec482 Ciostndt urn caecaides

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All Real-time qPCR assays for bacterial quantification in faecal samples and breast milk were performed with a minimum of two replicates from different assays.

6. Electrophoretic analysis of DNA fragments obtained after performing real-time qPCR.

Agarose gel electrophoresis of the reaction products was performed to verify the size and integrity of the amplimers obtained after performing real-time qPCR. The separation of the DNA fragments was performed in a 2% agarose gel at a voltage of 35 V and a current of 25 mA. The separated fragments are visualized fluorescently - by treating the gel with ethidium bromide and illuminating with UB light. The approximate sizes of the DNA fragments are determined by comparison with a standard containing small DNA fragments of known sizes - SmartLadder SF (Eurogentec, Belgium).

7. Statistical data processing

Statistical processing of the data and their graphical presentation were performed with SYSTAT version 13.2 and SigmaPlot version 12.0 software (Systat Software Inc., USA).

Analysis of enzymes in breast milk and newborn fecal samples

1. Determination of β-galactosidase enzyme activity (EU 3.2.1.23)

The enzyme reaction was carried out under the following conditions: 100 mM sodium acetate buffer, pH 6.0, containing a 2 mM solution of o-nitrophenyl-3-O-galactopyranoside (ONP-Gal) and appropriately diluted cells or supernatant after cell disintegration at 37°C The reaction was quenched with 1 M sodium carbonate. One unit of enzyme activity catalyzes the production of 1.0 pmol o-nitrophenol in one minute at pH 4.0 and 37°C. The o-nitrophenol content was determined spectrophotometrically at 410 nm wavelength on a Beckman Coulter DU 800 spectrophotometer.

All experiments for the determination of enzyme activity were performed in triplicate.

2. Determination of α-galactosidase activity (EU 3.2.1.22)

The enzyme reaction was carried out under conditions: 400 mM citrate buffer, pH 4.0, containing a 9.9 mM p-nitrophenyl α-D-galactopyranoside (PNP-Gal) solution (prepared in distilled water by dissolving p-nitrophenol α-D-galactopyranoside, Sigma cat. N. « N-0877) and appropriately diluted cells or supernatant after disintegration of the cells at 37°C. The reaction was stopped with 200 mM borate buffer, pH 9.8. One unit of activity converts 1.0 qmole of p-nitrophenyl α-D-galactopyranoside to o-nitrophenol and D-galactose in one minute at pH 4.0 and 37°C.

The p-nitrophenol content was determined spectrophotometrically at 405 nm wavelength on a Beckman Coulter DU 800 spectrophotometer.

All experiments for the determination of enzyme activity were performed in triplicate.

3. Determination of the activity of α-L - fucosidase (EU 3.2.1.51)

The enzyme reaction was carried out under conditions: 100 mM citrate buffer, pH 6.5, containing 10 mM solution of p-nitrophenyl α-L-fucopyranoside (PNP-FUC) (prepared by diluting p-nitrophenyl α-Lfucopyranoside (Sigma cat. no. N3628) with distilled water and appropriately diluted cells at 37° C. The reaction is stopped with 200 mM borate buffer, pH 9.8. One unit of activity converts 1.0 pmole of p-nitrophenyl α-L-fucopyranoside to p-nitrophenol and L-fucopyranoside in one minute at pH 4.0 and 37° C. Nitrophenol content was determined spectrophotometrically at 405 nm wavelength on a Beckman Coulter DU 800 spectrophotometer.

All experiments for the determination of enzyme activity were performed in triplicate.

4. Determination of α-glucosidase activity (EC 3.2.1.20)

The enzyme reaction was carried out under conditions: 100 mM acetate buffer, pH 6.0, containing 1.25 mM solution of p-nitrophenyl α-D-glucopyranoside (prepared by diluting p-nitrophenyl α-Dglucopyranoside (Sigma cat. no. N3628) with distilled water , and suitably diluted cells at 37° C. The reaction was stopped with 0.5 M sodium carbonate. One unit of activity converted 1.0 pmol of p-nitrophenol α-D-glucopyranoside to p-nitrophenol and D-glucopyranoside in one minute at pH 6.0 and 37° C The p-nitrophenol content was determined spectrophotometrically at 405 nm wavelength on a Beckman Coulter DU800 spectrophotometer.

All experiments for the determination of enzyme activity were performed in triplicate.

5. Determination of β-glucosidase activity (EU 3.2.1.28)

The enzyme reaction was carried out under conditions: 0.1 M acetate buffer, pH 5.0, containing a 20 mM solution of p-nitrophenyl-b-D-glucopyranoside (ONP-Glu) and appropriately diluted cells at 37°C. The reaction was stopped with 0.2 M sodium carbonate. One unit of activity converts 1.0 pmole of p-nitrophenyl α-D-glucopyranoside to p-nitrophenol and D-glucopyranoside in one minute at pH 5.0 and 37°C. The p-nitrophenol content was determined spectrophotometrically at 405 nm wavelength on a Beckman Coulter DU 800 spectrophotometer.

All experiments for the determination of enzyme activity were performed in triplicate.

6. Determination of protease activity

Protease activity of cells and hydatid fluid (HYT) was assayed in the presence of casein (Fluka) as a substrate. One unit (U) of protease activity is defined as the amount of enzyme that hydrolyzes casein to 1 pmol of tyrosine in 1 minute, at pH 7.5 and 37°C.

The enzyme reaction was carried out under the following conditions: 0.65% (w/v) casein and 1.0 ml of appropriately diluted sample (cells or HYT) were dissolved in 50 mM phosphate buffer, pH 7.5. The reaction takes place for 10 min at 37°C in a water bath. The reaction was stopped by the addition of 110 mM trichloroacetic acid (THO) (Merck) at 37°C. Samples were incubated with THO for 30 min at the same temperature. To separate the undegraded casein, the samples were centrifuged at 9000 rpm/15 min, 4°C. The supernatant was analyzed for the amount of tyrosine released, from the degradation of casein, in the presence of 500 mM NazCOs and 0.5 M Folin's reagent solution (Merck) at 37°C for 30 minutes. Absorbance at Z = 660 nm (A660) was measured on a Beckman Coulter DU 800 spectrophotometer against a control containing distilled water instead of sample. The tyrosine concentration (pmol) was determined from the measured A660 according to a standard curve. L-tyrosine (Sigma-Aldrich) was used as a standard for the construction of a standard curve.

All experiments for the determination of protease activity were performed in triplicate at least.

7. Determination of lipase activity (EU 3.1.1.3)

The enzyme reaction was carried out under conditions: 0.1 M acetate buffer, pH 7.6, containing 0.8 mM solution of p-nitrophenyl-palmitate and appropriately diluted cells at 37°C. The reaction was stopped with 0.2 M lead acetate lead (II). One unit of activity converts 1.0 pmole of p-nitrophenyl palmitate to p-nitrophenol and palmitate in one minute at pH 7.6 and 37°C. The p-nitrophenol content was determined spectrophotometrically at 405 nm wavelength on a Beckman Coulter DU 800 spectrophotometer.

All experiments for the determination of enzyme activity were performed in triplicate.

Analysis of short-chain fatty acids in breast milk and faecal samples of one- to twelve-month-old infants.

The following protocol has been developed for the display of short-chain fatty acids in excrement samples:

1. Isolation of short-chain fatty acids from excreta.

2% H3PO4 or 0.05% H2SO4 in a ratio of 1:10 is added to 100 mg of fresh fecal sample or breast milk. The samples are homogenized very well on a vortex 2 times for 2 min each. The resulting homogenate was centrifuged for 10 min, 13,000 rpm, after which the supernatant was separated. 200 pL were taken from the supernatant and extracted with 200 μL organic solvent (CH 2 Cl 2 , AcCN, EtOH, EtOAc). Samples were homogenized, then centrifuged for 5 min, 13,000 rpm. The resulting organic layer was separated and subjected to HPLC analysis.

2. HPLC method for the analysis of short-chain fatty acids.

A Konik-Tech (Spain) HPLC system equipped with an Aminex НХ-87Н Ion Exclusion Column (7.8 mm i.d. x 30 cm, Biorad, Richmond, CA) and a Micro-Guard Cation-H pre-column (4.6 mm i.d. x 30 mm, Biorad). The determination of the samples was carried out with a UV detector at a wavelength of 210 nm, with a mobile phase of 0.005 M H2SO4, a flow rate of 0.6 ml/min and a column temperature T = 40°C.

Peaks were identified by retention times against standards of short chain fatty acids: lactic acid, acetic acid, propionic acid and butenoic acid. For the quantitative determination of short-chain fatty acids, standard lines were prepared in concentrations of 25 - 1.56 mmol/L. Correlation equations describing the area of the nick (y) and the concentration of short-chain fatty acids (x, mmol/L) were derived. The standard lines have linear sections between 25 - 1.65 mmol/L and a correlation coefficient of 2 > 0.9999.

| Parameters Breast milk Feces | Types of microorganisms 1 1. Bifndobaktsrni 10-10* 2 Lactobacillus 1040* 10M0* 3. Clostridine PV-10* 4. Bacte™ deles * J0M0? 5. Enteroyuki 1O ⁵ -1O ⁷ KH-IO 6 E. col and — typical - 7- Candida-like fungi of the genus Candida - 103-1 ¢5

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1. Alpha-galactosendase (U/mg protein 1 0.1 AZ 0JA1 2. Beta-gapactoside (P/mg protein) 0.4-2.0 0.2-1.0 3. Alpha-P yucosndase (U/mg protein) 0.2-1.2 0.1 A5 4, Bsta-glutpandase (U/mg protein) chamber chamber 5. Alpha-fucoside (U/mg protein) chamber 0.05 AZ 6. Linden (IJ/mg protein) 7. npoTtaia (U/mg protein) 0.5-3.0 0.2-1.5, Meta&olnts 1. Lactic acid n of {mmol/g) 0.5-1.2 0.2-0.8 2. Acetic acid (mmol/g) 0.2-0.6 0.3-0.7 3. Propionate kneslin (a 1mmoi/g) 0JA3 0.05-0.3 4. Butyric acid (mmol'g) 0.05-02 0.02-0.13

Table 6. Range of values of measured indicators in healthy children aged one to twelve months.

As a result of the analyzes of the tested mother's breast milk and feces from a newborn between the ages of one and twelve months, the following coefficient ratios are calculated:

- the amount of Bifidobacteria/Bacteroides >1.0;

- the amount of Bifidobacteria/Lactobacilli >1.0;

- the amount of Bifidobacteria+Lactobacilli/Bacteroides >1.0;

- the amount of Bifidobacteria+Lactobacilli/Yeast (for feces from the child) >1.0;

- the amount of Bacteroides/Yeast (for feces from the child) >1.0;

- the amount of Bifidobacteria+Lactobacilli/E. Cars >1.0;

- the amount of Bifidobacteria+Lactobacilli/beta-galactosidase activity at a ratio of 0.1 - 1.0;

- the amount of Bifidobacteria+Lactobacilli/alpha-fucosidase activity at a ratio of 0.1 > 1.0;

- the enzyme activities beta-galactosidase/alpha-galactosidase at a ratio of 0.1 > 1.0;

- the enzyme activities beta-galactosidase/alpha-fucosidase at a ratio of 0.1 > 1.0;

- beta-galactosidase/lipase enzyme activities at a ratio of 0.1 > 1.0;

- beta-galactosidase/protease enzyme activities at a ratio of 0.1 > 1.0;

- the enzyme activities beta-galactosidase+alpha-galactosidase/alpha-fucosidase at a ratio of 0.1 >1.0;

- the metabolites lactic acid/acetic acid/butyric acid at a ratio of 0.1 > 1.0.

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Where:

1. C - ratio between the number of bacteria (enzymes, metabolites) A and B;

2. A - number of bacteria (enzymes, metabolites) A;

3. A nom. min. - the lower limit of the norm for the number of bacteria (enzymes, metabolites) A;

A nom.max. - upper limit of the norm for the number of bacteria (enzymes, metabolites) A; B - number of bacteria (enzymes, metabolites) B;

In nom.min. - the lower limit of the norm for the number of bacteria (enzymes, metabolites) B;

In nom.max. - upper limit of the norm for the number of bacteria (enzymes, metabolites) B.

The trends in reporting ratios are expressed in Table 7, which are obtained at the corresponding ratio of the indicator from the column of the table to the indicator of the row of the table.

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Bifido

LAB

Bacteroides

Yeast

Bifido + ICD

E. coli «-galactosidase β-gatactoiidase α-fucasidase

Lipase

Protease

Metabolites

Would LAB You Dr Would Well. fi ter from fi cofl Yes aid di to+ MK

B

a- in σ- up Pro Me gal no O5C tea I7T0 EG€£ act perhaps se OS) das urn dos das is U is is

Table 7. Trends of the ratios between the individual indicators, an upward arrow indicates a positive effect on the microbiota, and a downward arrow indicates a negative effect on the microbiota.

Example 2.

In vitro study of 6 indicators for assessing the balance of the microbiota in babies from one month to twelve months:

1. Protocol for quantitative analysis of human microbiota by real-time qPCR.

The presented protocol can be applied to establish deviations for analysis of dysbiosis in newborns from one to twelve months and be included in an algorithm for identifying conditions, deviations and rules for restoring the balance of the microbiota.

A. Primers and fluorescently labeled probes for real-time qPCR detection of bacterial groups and species in target group samples

Primer pairs and fluorescently labeled probes for real-time qPCR detection of bacterial species and communities in samples from different target groups are presented in Table 8

Table 8. Primers and fluorescently labeled probes for real-time qPCR detection of bacterial groups and species used in the presented study

TftprrTUI baГПфШдв» group OR MNO First REPUBLIC OF 5*3 HiTwmur Bifidatsacterium sp. Qif-F HSK TCGCGTC YGGTGTGA A AG CC AC AGCC AGC RTCCAC Rinlftlu eiaL, 2004 You tetuides, P r is v d t with 11 a, Porpfyrun/ιηίΙ, dpp-f YRR-R GGTGTCGGCTTA AGTGCCAT CGG A YGTA AGGGCCG TGC Binifiln ei ai. Lactobacilli Lacb-F Lacb-R AGCAGTAGGGAATC GGSCA C ACCGCTAC AC AC ATOG AG Waiter el til.. 2001 2001 Btfidoftaclerium F_Ili|id09c I 06 CGGGTGA GTA Al GCG TG ACC TGATAGGACCCGACCCCA Furet et al., 2009 Bacteroidei, Prcvofila F_Bactcr 11 R_Bactcr OS CCTWCG ATGG A1AGGGGTT CACGCTACTTGGCTGGTTCAG Puret et al., 2009 LaciahaciilMt, Leμζvη os 1 pc, Pediacoccus F_Lazio 05 R^Laclo 04 AGC AGTAGCiG A ATCTTCC A CGCC ACTGGTGTTC YTCC ATATA - - Pitret er ai. _t 2009 1

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2. Control bacterial strains

Bacterial strains used to control the specificity of the primers and labeled probes used, as well as for the quantitative evaluation of individual bacterial species and communities are presented in Table 2. The strains used were purchased from the National Bank for Industrial Microorganisms and Cell Cultures (NBPMK) and German Collection of Microorganisms and Cell Cultures (DSMZ). The strains are cultivated aerobically or anaerobically in selective nutrient media, according to the recommendations of DSMZ and NBPMK. A series of dilutions is made from the developed cultures for each strain and plated on the corresponding agar medium in a petri dish to determine the total number of bacteria - colony-forming units (CFU). Additionally, samples of 1.0 ml are taken from the dilutions, which are centrifuged under the following conditions: 12000 rpm/3min. The resulting bacterial cell pellets were stored at -80°C until used for analysis.

Table 9. Control bacterial strains used in the study.

Strain HjTvHinik Tidal sht gtvknaya SCC npw ruJb din« HR Lactobacillus deibrueekii ziЬzr, BulgonciL! 1132 T NBG1MKK Detection of Lactobacillus, Get use of fluorescent probes Lactobacilli acidophilus Α89ά T NBPMKK petition pa Lactobacillus. without using fluorescent probes Laclobacitiia rhamtu/xiu 1-010 1 NBPMKK occurrences of LactfrbtiLiliux, without tpotshmne of flucsresseggtni sonan Bifidfd>actcrium tongam subsp, Amgum DSM-3Q2I9 DSMZ detection of Bifidobacterium without using fluorescent probes BacteroidcJJragdis DS M-2151 DSMZ detection of Bacte^ides. without the use of fluorescent probes Bifidobacterium adtdnscertii.t DSM*2OO8j DSMZ detection of Bifidobacterium, with fluorescently labeled probes Bifidobacterium Itmgum iubsp. Infinitis DSM-200S8 DSMZ detection of Bifidobacterium, is fluorescently labeled probes Bifidohctclerium breve DSM’20213 DSMZ detection of Bifidobacterium. is fluorescently labeled probes C/tumdium leptum DSM-75J DSMZ detection of Clostridium with fluorescently labeled probes Clostridium caccaidex ifHuuiia coceoidej} DSM-9JS DSMZ detection of Closfr/dtum with fluorescently labeled probes

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3. Isolation of DNA from bacterial cultures and samples from the target groups

Bacterial genomic DNA from control strains and isolates from target group samples was extracted using the Blood and Tissue kit DNeasy (Qiagen, Hilden, Germany). Microbial DNA from faecal samples and from breast milk was isolated using the QIAamp DNA Stool Mini Kit (Qiagen, Hilden, Germany). Initially, 200 mg of faecal sample/milk was diluted in 1.8 ml of sterile PBS buffer. To 200 μΐ of diluted fecal sample, 20 μΐ of lysozyme (150 mg/ml) and 130 μΐ of lysis buffer (2.0 mM Na2EDTA; 20 mM TrisHC1; 1.2% Triton X-100) were added. The mixture was incubated at 37°C for 30 min, after which DNA was isolated.

4. Quantification of DNA

The quantity and purity of the bacterial genomic DNA isolated from the standard strains and from the tested samples were determined spectrophotometrically. For this purpose, the absorbance of the suitably diluted DNA samples was determined at wavelengths of 260 nm and 280 nm. Measurements were performed on a Shimadzu UV-2600 spectrophotometer at a light path of 8.5 mm, after zeroing the apparatus against a cuvette with elution buffer. Homogeneity of genomic DNA was determined by visualizing the isolated DNA in a 1% (w/v) agarose gel by electrophoresis and ethidium bromide staining. Samples with isolated DNA were stored at -20°C.

5. Conduct Real-time qPCR

In real-time qPCR reactions for the detection and quantification of bacteria without the use of fluorescent probes, SYBR Green PCR Master Mix (Applied Biosystems) was used. Reactions were plated in 96-well plates with a final volume of each reaction of 25 pL. Reactions were run on a Real-Time PCR CFX96 Touch (BIO-RAD) with software version 3.0.1224 under conditions for each of the target groups of bacteria listed in Table 10.

Table 10. Primers and reaction conditions for conducting Real-time qPCR for quantification of bacteria in fecal samples.

1 Group uzdm· a YGPKSHTM L ЗГ-F n Bif R mfidetiacurium pdoiern - 0.5 _u m each; Prsdenaturaica S min/95 °C; - 15 ICs; Connecting the previews - 20 «a/ii Tl; Elongation -= 30 ksg73 °C; Temperature 30 °C; Number of uukjih - J5, ΕϊΡΡ-F n HPP-R 1 f'nrphyromamii Primers -0.5 μΜ each; P redeni t^ration — 5 ppOD f; Denaturant = 15 -C; Connection of primers - -0 5C:68 *C. I Elongation — J0 ЗсС/72 С; D«e*SHI- 30 ks/VD | Number of annals - 35.

Lacb-F and Lteb-I Primers - 0.5 μΜ each; Before niturdii! — 5 °C: Denatured - [5 ya&45 *C; Binding of primers — 20 °C; Temperature - South/72 °C; Detection - ЗОмслю °C; bpoil ιιηικλη-35. F Leclo 05 n R_Licto 04 /WinJet'uj YraRmsrn -0.1 µM each. Spun yarn - 10 °C. Ls#purvn1#1 - 30 iSUZ °C; Sprshne nd tsranmershe - ID κΰόΟ *С; Upmjlmne ~ 1 mln/73 °C; . Diacive 30 «e/VO *C; Cut cycles - 40.

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Real-time qPCR reactions for detection and quantification of bacteria using fluorescently labeled probes used TaqMan Universal PCR Master Mix (Applied Biosystems). Reactions were plated in 96-well plates with a final volume of each reaction of 25 pL. Conditions for conducting each of the analyzes to determine the target groups of bacteria are indicated in Table 11.

Table 11. Primers, fluorescent probes and reaction conditions for conducting Real-time qPCR for the quantification of bacteria in faecal samples.

¹ Pdoimfi· a : fyavorstTsipi bsljpia ozda Target group ————=----------. ----1 Ps1kpzhyapP1 ztlmka dgtooig» 09c, R Bifid 06, probe Ρ_ΒίίΜ BifltiotutcKrfvm Preachers -0.2 μΜ kekn: Probe -0.2 μΜ: Natural- IB min/95 "С; Dsnatu crabs* - 30 sec^S “S. Extension of gtray feathers and child kcnya - 1 ηίη'&ϋ Έ. F Bactcr 1L, R Bader 08, ctwm P^BlsUVB F Baa 1369, R >492, probes RLM13Я9Р Raeferotdtn, Γηνοίίϋϋ Determination of total amount of bacteria ——_____

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All Real-time qPCR assays for bacterial quantification in faecal samples and breast milk were performed with a minimum of two replicates from different assays.

6. Electrophoretic analysis of DNA fragments obtained after performing real-time qPCR

Agarose gel electrophoresis of the reaction products was performed to verify the size and integrity of the amplimers obtained after performing real-time qPCR. The separation of the DNA fragments was performed in a 2% agarose gel, at a voltage of 35 V and a current of 25 mA. The separated fragments are visualized fluorescently - by treating the gel with ethidium bromide and illuminating with UB light. The approximate sizes of the DNA fragments are determined by comparison with a standard containing small DNA fragments of known sizes - SmartLadder SF (Eurogentec, Belgium).

7. Statistical data processing

Statistical processing of the data and their graphical presentation were performed with SYSTAT version 13.2 and SigmaPlot version 12.0 software (Systat Software Inc., USA).

Analysis of enzymes in breast milk and newborn fecal samples

1. Determination of enzymatic activity of O-galactosidase (EU 3.2.1.23)

The enzyme reaction was carried out under the following conditions: 100 mM sodium acetate buffer, pH 6.0, containing a 2 mM solution of o-nitrophenyl-B-O-galactopyranoside (ONP-Gal) and appropriately diluted cells or supernatant after cell disintegration at 37°C . The reaction was quenched with 1 M sodium carbonate. One unit of enzyme activity catalyzes the production of 1.0 pmol o-nitrophenol in one minute at pH 4.0 and 37°C. The o-nitrophenol content was determined spectrophotometrically at 410 nm wavelength on a Beckman Coulter DU 800 spectrophotometer.

All experiments for the determination of enzyme activity were performed in triplicate.

2. Determination of the activity of a-L-fucosidase (EU 3.2.1.51)

The enzyme reaction was carried out under conditions: 100 mM citrate buffer, pH 6.5, containing 10 mM solution of p-nitrophenyl α-L-fucopyranoside (PNP-FUC) (prepared by diluting p-nitrophenyl α-Lfucopyranoside (Sigma cat. no. N3628) with distilled water and appropriately diluted cells at 37° C. The reaction is stopped with 200 mM borate buffer, pH 9.8. One unit of activity converts 1.0 pmole of p-nitrophenyl a-L fucopyranoside to p-nitrophenol and L-fucopyranoside in one minute at pH 4.0 and 37° C. Nitrophenol content was determined spectrophotometrically at 405 nm wavelength on a Beckman Coulter DU 800 spectrophotometer.

All experiments for the determination of enzyme activity were performed in triplicate.

Analysis of short-chain fatty acids in breast milk and CSF samples of one- to twelve-month-old infants.

The following protocol has been developed for the detection of short-chain fatty acids in excrement samples:

3. Isolation of short-chain fatty acids from excrement.

2% HPO4 or 0.05% H2SO4 in a ratio of 1:10 is added to 100 mg of fresh fecal sample or breast milk. The samples are homogenized very well on a vortex 2 times for 2 min each. The resulting homogenate was centrifuged for 10 min, 13,000 rpm, after which the supernatant was separated. 200 pL were taken from the supernatant and extracted with 200 pL organic solvent (CH 2 Cl 2 , AcCN, EtOH, EtOAc). Samples were homogenized, then centrifuged for 5 min, 13,000 rpm. The resulting organic layer was separated and subjected to HPLC analysis.

4. HPLC method for the analysis of short-chain fatty acids.

A Konik-Tech (Spain) HPLC system equipped with an Aminex НХ-87Н Ion Exclusion Column (7.8 mm i.d. x 30 cm, Biorad, Richmond, CA) and a Micro-Guard Cation-H pre-column (4.6 mm i.d. x 30 mm, Biorad). The determination of the samples was carried out with a UV detector at a wavelength of 210 nm, with a mobile phase of 0.005 M H2SO4, a flow rate of 0.6 ml/min and a column temperature T = 40°C.

Peaks were identified by retention times against standards of short chain fatty acids: lactic acid, acetic acid, propionic acid and butenoic acid. For the quantitative determination of short-chain fatty acids, standard lines were prepared in concentrations of 25 - 1.56 mmol/L. Correlation equations describing the peak area (y) and the concentration of short-chain fatty acids (x, mmol/L) were derived. The standard lines are with linear sections between 25 - 1.65 mmol/L and with a correlation coefficient r2 > 0.9999.

Table 12. Range of parameters studied in children from one to twelve months.

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Parameters Feshs Rhjhw chnkroorganizkn 1. Bnfidobshsrpi 10=-10 ^pts IR-Jun 2. Lactichodli 10"-10" 3. BacteraidetEi - I0L | from Enzymes 4. Beta·galagnimdase (LP^mg protein) 0.4-2.0 0.2-1.0 5, A lfd~fukypNDill (U/mg ΠρίπτΗΉ } 0J4J.S 0.05-0.3 MegaVslitm 6. Milk protein (rnmol/g) 0.5-1D 0.2-O.8 7. Oic acid (mmol/g) DZ-0.7

a Acids i|mma|/g) 0.I-OJ 0.05-0.3 9. Oil kneelnnnn (minol/g} 0.05-03 0.02-O.N

As a result of the analyzes of the tested mother's breast milk and feces from a newborn between the ages of one and twelve months, the following coefficients are calculated:

1. Ratio of the amount of Bifidobacteria/Bacteroides;

2. The ratio of the amount of Bifidobacteria/Lactobacilli;

3. The ratio of the quantity (Bifidobacteria+Lactobacilli)/Bacteroides;

4. The ratio of the quantity (Bifidobacteria+Lactobacilli)/beta-galactosidase activity;

5. The ratio of the quantity (Bifidobacteria+Lactobacilli)/alpha-fucosidase activity;

6. The ratio of beta-galactosidase/alpha-fucosidase enzyme activities;

7. The ratio of beta-galactosidase/protease enzyme activities;

8. Lactic acid/acetic acid/butyric acid metabolite ratio.

Calculations are made according to the specified formula.

Table 13. Trends of the ratios between the individual indicators, an upward arrow indicates a positive effect on the microbiota, and a downward arrow indicates a negative effect on the microbiota.

Would LAB Bat Su β Y- Me fi ter fi gat ma to aid October es MX oil dm B dos e 0

L40 eactetaides

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Bifido + ICD

S-galactosidase α-fucasidose

MetaNolita

Claims (1)

Quantitative assessment method for rapid prediction and control of dysbiosis in infants from one month to one year by evaluating the quantitative and qualitative composition of the microbiome of a sample of maternal breast milk and a sample of infant feces, type and amount of enzymes and metabolites, characterizing provided that the method includes the following stages: a) conducting in vitro analyzes of the diversity and ratio of microorganisms in a sample of the infant's feces and a sample of the mother's breast milk; b) determination of the amount of metabolites used as biomarkers from a sample of the infant's feces and from a sample of the mother's breast milk; c) reporting the level of enzyme activity of enzymes used as biomarkers from a sample of the infant's feces and from a sample of the mother's breast milk; d) processing according to a mathematical model of the data from the previous stages, which as a result derive: - calculated correlation coefficients between the composition and quantity of microorganisms from a sample of the infant's feces and a sample of the mother's breast milk. - calculated correlation coefficients between enzyme profile and activity, the enzymes responsible for the absorption and metabolization of the components of a sample of the infant's feces and of a sample of the mother's breast milk; - calculated correlation coefficients between the amount of metabolites obtained from the metabolization of the main components of the microbiota from a sample of the infant's feces and the main components of the microbiota from a sample of the mother's breast milk.