Reference values for gut microbiota parameters in rhesus macaques established by real-time polymerase chain reaction

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Introduction

The gut microbiota (GM), which constitutes a complex ecosystem of microorganisms, is a key factor in maintaining homeostasis and overall health [1, 2]. For biomedical research, particularly translational research, animal models that are as close as possible to humans in terms of physiology and pathogenesis are of key importance. Rhesus macaques (Macaca mulatta)¹ are among the most sought-after and relevant models for studying infectious, immunological, neurodegenerative, and metabolic diseases. Accordingly, understanding the characteristics and normal microbiome of their gut microbiota is of critical importance for the correct interpretation of experimental data and ensuring the reproducibility of results.

However, despite the active use of these animals in scientific research, a critical gap persists in the literature and laboratory practice — the lack of species-specific reference values for the quantitative assessment of the gut microbiome. Traditionally, studies extrapolate data obtained for humans to primates or use relative qualitative profiles obtained by sequencing methods [2, 3]. An additional factor that must be taken into account when developing standards is the dynamic nature of the gut microbiota throughout an animal’s life. Studies on rhesus macaques in captivity reveal pronounced age-related characteristics of their gut microbiota composition [2–5] and also indicate the presence of critical periods in gut microbiota formation, analogous to those in humans [6].

Comparative studies convincingly demonstrate that the composition of the gut microbiota, the ratio of key phyla such as Firmicutes and Bacteroidetes (now known as Bacillota and Bacteroidota) [3], and the spectrum of microbial metabolites (e.g., short-chain fatty acids) differ significantly not only between humans and laboratory rodents but also between humans and non-human primates [7–9]. Moreover, the primate gut microbiota exhibits high plasticity and species specificity, responding sensitively to dietary changes [10, 11].

Modern approaches to studying the gut microbiota are based on metagenomic sequencing of the microbiome — shotgun sequencing and amplicon sequencing of 16S rRNA, 18S rRNA, and ITS genes — as well as on the use of quantitative PCR. Unlike culture-based methods, these techniques allow for the assessment of taxonomic composition, including uncultivable taxa [12].

In selecting a research strategy, we were guided by criteria of cost-effectiveness and suitability for routine monitoring. Unlike sequencing, which is widely used abroad but is financially costly [13, 14], the real-time quantitative polymerase chain reaction method represents a cost-effective and high-throughput alternative. This method allows for the rapid generation of quantitative data on the presence of marker taxa, including microorganisms that cannot be cultured in vitro. This approach facilitates the transition to a quantitative assessment of microbial community structure, which is critical for scalable monitoring of large animal populations.

The aim of the study is to establish age-specific reference ranges for key taxa of the gut microbiota of rhesus macaques based on a comprehensive analysis of samples obtained under controlled housing conditions at the Kurchatov Medical Primatology Complex.

Materials and methods

The study utilized 120 fecal samples from clinically healthy rhesus macaques that had not previously participated in experiments, ensuring the absence of any factors that could influence the composition of the fecal microbiota (Table 1).

 

Table 1. Age groups of the study subjects (monkeys)

Group	Age, years	Amount
I — infants	Under 1	12
II — prepubescent	1–3	36
III — young adults	4–7	12
IV — adults	8–14	12
V — middle aged	15–20	24
VI — elderly	21–25	12
VII — old	26–34	12
Total		120

 

The monkeys were housed in individual cages equipped with feeders and automatic water dispensers. Each cage was labeled with the animal’s identification number. The diet consisted of a complete, in-house-produced pelleted feed (in accordance with GOST 34566-2019²), bread, eggs, and fruit. Feed rations were determined based on each animal’s body weight. The study protocol was approved by the Local Ethics Committee of the Kurchatov Institute Research Center (No. 2PR dated 02/20/2024).

Fecal samples were collected in the morning after the monkey housing areas had been wet-cleaned and the trays thoroughly sanitized with disinfectants.

Observation of the animals continued until the collection of fecal samples, which were collected from the trays into sterile containers. The collected material was transported to the laboratory within 30 minutes, labeled, and placed in long-term storage under frozen conditions at –70°C.

Preliminary processing of fecal samples was performed using validated methods in accordance with Chapter IV of SanPiN 3.3686-21 “Sanitary and Epidemiological Requirements for the Prevention of Infectious Diseases.”³.

Polymerase chain reaction

DNA extraction from fecal samples was performed using the Express-DNA-Bio thermal lysis-based reagent kit (Alcor Bio).

Molecular genetic analysis of 24 microbiological parameters was performed using the KOLONOFLOR-16 (biocenosis) reagent kit (AlfaLab). Results were detected on a CFX-96 amplifier (Bio-Rad Laboratories, Inc.).

Statistical analysis of data

Raw data were processed using Microsoft Office Excel 2016. Microorganism abundance was expressed as detection frequencies, presented as percentages (%). Quantitative indicators were expressed as the decimal logarithm of DNA copies per milliliter. The χ² test was used to assess the significance of differences in the distribution of microorganism detection frequencies across all age groups.

Data were visualized and analyzed using OriginPro v. 8.6 software. To compare indicators within each age group, the median (Me) and interquartile range [Q₁–Q₃] were used.

To test the statistical significance of differences in the distribution of indicators between age groups, the nonparametric Kruskal–Wallis test was applied. This test is used to compare three or more groups when the data do not follow a normal distribution. The normality of the distribution was tested using the Shapiro–Wilk test. To test for statistical significance between groups, a post-hoc analysis (Dunn’s test with Bonferroni correction) was applied for pairwise comparisons.

Scatter plots were used to analyze the continuous relationship between the relative abundance of phylotypes and age. To visualize and quantitatively assess the linear trend, a regression line was superimposed on the plots, constructed using the least squares method, which approximates the linear relationship. The nature and strength of the linear relationship were assessed using the slope (k) of this line. The coefficient k, equal to the tangent of the slope of the regression line, quantitatively expresses the rate of change in relative abundance per unit change in age. A negative value of k indicates a downward trend, while a positive value indicates an upward trend in abundance with age.

To assess the pairwise linear relationships between all studied parameters (age and phylotypes), a correlation matrix was constructed and presented as a lower triangular matrix, with duplicate data omitted to improve readability. The strength and direction of the linear relationships were determined using Pearson’s correlation coefficient (r). The statistical significance of each correlation coefficient was assessed by calculating the corresponding p-value. To estimate the proportion of explained variance, the coefficient of determination (r²) was calculated.

The a priori level of statistical significance was set at α = 0.05. All differences were considered statistically significant at p < α.

Results

Table 2 presents the reference ranges for key GM taxa, established based on a study of seven age groups of rhesus macaques. For comparison, reference values for humans, as provided in the Kolonoflor-16 (Biocenosis) reagent kit, are also included.

 

Table 2. Age-related reference ranges for the gut microbiota of rhesus macaques (log₁₀, copies/mL), Q₁–Q₃

Parameter	Reference values for humans: KOLONOFLOR-16	Group I (younger than 1 year)	Group II (1–3 years)	Group III (4–7 years)	Group IV (8–14 years)	Group V (15–20 years)	Group VI (21–25 years)	Group VII (older than 26 years)
Total bacteria mass	11.00–13.00	10.08–11.48	8.30–11.18	9.30–11.65	9.30–10.30	8.65–9.90	9.48–10.18	9.65–11.7
Lactobacillus spp.	7.00–8.00	7.74–9.81	7.65–8.65	6.30–8.65	7.74–9.90	5.85–8.48	5.18–8.74	5.88–6.98
Bifidobacterium spp.	9.00–10.00	9.93–11.18	8.74–9.74	8.48–10.11	9.60–11.08	8.85–10.00	9.54–10.81	9.18–10.90
E. coli	6.00–8.00	7.30–9.04	6.30–7.30	6.78–7.98	6.30–7.74	5.88–6.74	5.18–5.81	5.85–7.48
Bacteroides spp.	9.00–12.00	7.60–8.85	7.60–8.95	8.90–11.08	8.85–10.30	7.60–9.48	9.48–10.30	9.30–10.18
F. prausnitzii	8.00–11.00	8.60–11.16	9.00–10.30	8.95–10.78	9.93–10.60	9.18–10.40	9.60–10.54	9.88–10.48
Bacteroides fragilis group/ Faecalibacterium prausnitzii	0.01–100	0.002–0.171	0.005–0.5	0.241–4.215	0.046–1.415	0.005–0.422	0.085–1.625	0.092–1.50
B. thetaiotaomicron	Any	–	13.30–13.30	–	8.30–8.30	–	–	–
A. muciniphila	Less than 11.00	–	12.30–12.30	–	9.30–9.84	6.47–10.69	9.00–10.69	6.00–7.69
Enterococcus spp.	Less than 8.00	5.30–6.00	5.84–7.00	7.30–10.15	8.30–8.30	10.84–11.38	8.77–8.77	5.00–11.60
E. coli enteropathogenic	Less than 4.00	5.69–7.30	5.30–7.30	6.77–6.77	–	–	–	4.60–4.60
K. pneumoniae	Less than 4.00	6.47–6.47	–	–	–	10.47–10.47	–	5.00–5.60
K. oxytoca	Less than 4.00	5.00–5.00	–	9.77–9.77	–	7.69–8.22	9.84–9.84	9.00–9.69
Candida spp.	Less than 4.00	6.00–6.00	–	–	8.00–8.00	–	–	5.00–5.00
Staphylococcus aureus	Less than 4.00	5.30–7.83	5.69–7.38	6.30–6.30	6.84–7.76	6.30–8.30	5.77–6.69	7.30–7.30
Clostridioides difficile	Unidentified	8.84–8.84	–	–	–	–	–	–
Clostridioides perfringens	Unidentified	7.60–9.24	7.71–9.26	6.69–6.69	–	5.84–7.69	7.30–8.47	–
Proteus vulgaris/mirabilis	Less than 4.00	6.00–8.69	6.30–7.60	–	7.00–7.90	5.47–7.00	5.00–8.30	7.69–7.69
Citrobacter spp.	Less than 4.00	5.47–6.30	5.60–10.00	–	–	–	–	–
Enterobacter spp.	Less than 4.00	7.30–9.30	7.30–7.78	5.47–5.47	6.69–7.00	6.69–8.30	5.69–7.30	7.47–8.30
Fusobacterium nucleatum	Unidentified	5.30–5.69	6.00–6.00	–	–	5.30–5.30	–	5.00–6.47
Parvimonas micra	Unidentified	5.77–7.30	7.26–10.24	–	10.60–10.60	5.62–9.15	6.30–10.30	5.70–7.78
Salmonella spp.	Unidentified	–	–	–	–	–	–	–
Shigella spp.	Unidentified	–	–	–	–	–	–	–

 

Symbionts and key commensals (Lactobacillus spp. (p = 1,000), Bifidobacterium spp. (p = 1,000), Escherichia coli (p = 1,000), Bacteroides spp. (p = 1,000), Faecalibacterium prausnitzii (p = 1,000) were detected in 100% of individuals across all age groups, indicating a similarity in the baseline composition of the gut microbiota.

Total bacterial mass (TBM) is an integral indicator reflecting the total number of all microorganisms inhabiting the gut. It is characterized by relatively stable values and the absence of a marked age-related decline (p = 1.000). In all age groups, TBM is slightly below the range typical for humans, indicating species-specific features of the total microbial load in rhesus macaques. Group I (infants under 1 year of age) is characterized by the highest levels of Lactobacillus spp. and Bifidobacterium spp., which is similar to the human infant gut microbiota. A decrease in the levels of Lactobacillus spp. and Escherichia coli to minimal values is observed in groups V–VI. In older individuals (Group VII), Escherichia coli levels remained lower than the human norm. Levels of Faecalibacterium prausnitzii — one of the main producers of butyric acid — remain consistently high across all age groups, corresponding to the human norm.

The Bacteroides fragilis group/Faecalibacterium prausnitzii ratio (p = 1.000) is another comprehensive indicator that demonstrates variability within the population; in rhesus macaques at an early age (groups I, II, IV), it is an order of magnitude lower than in humans, indicating a different balance between these important groups of microorganisms.

Statistically significant age-related differences allowed us to identify taxa with pronounced age specificity. The most striking pattern is observed for Akkermansia muciniphila (p = 0.006), whose frequency progressively increased from complete absence in individuals of groups I and III to maximum values in group VI (50%), which may reflect the maturation process of the intestinal mucosal barrier. Its levels demonstrate significant individual variation, especially in groups V and VI. In group II, a maximum level exceeding typical human values was recorded. However, in adulthood, concentrations stabilize within the reference ranges established for rhesus macaques, which persist into old age (groups IV–VII; Table 2).

Enterococcus spp. was detected in all 7 age groups. Statistically significant differences in prevalence between groups were observed (p = 0.035), with the highest prevalence in groups II–III (33.33%). Quantitative data showed moderate variability. In groups IV–VII, levels exceeded the human norm (> 8.00 lg, copies/mL), which may be a variant of the norm for rhesus macaques. This profile indicates a constant presence with marked individual fluctuations.

Fusobacterium nucleatum was detected sporadically (p = 0.044) in 4 (I, II, V, VII) of the 7 groups at low or moderate titers. This irregular distribution pattern is characteristic of transient carriage or episodic colonization. At the same time, a U-shaped colonization profile was observed with peak values in groups I (46.67%) and VII (41.67%), which may indicate reactivation in older age.

Microorganisms with clinically significant but statistically non-significant prevalence rates included several key taxa. Detected in all age groups in quantities exceeding the human norm: Enterobacter spp. (p = 0.334) exhibited an extremely high colonization frequency in group I (75%) followed by stabilization at 40–50% in adults. A similar pattern of dominance at an early age followed by a decline was observed for Staphylococcus aureus (p = 0.861) (66.67% in Group I).

Parvimonas micra is consistently detected in most age groups (groups I, II, IV, V, VI, VII; p = 0.460) and exhibits a biphasic distribution with high prevalence rates in groups I (50%) and VII (66.67%). The data confirm that the use of human references (not detected) to assess the gut microbiota of rhesus macaques is incorrect. Parvimonas micra is a normal, constantly present component of the gut microbiota, unlike in humans.

Analysis of species-specific colonization patterns allowed for the identification of three categories of microorganisms. Clostridioides difficile (p = 0.603) and Citrobacter spp. (p = 0.460), detected predominantly in the early period (Group I), were classified as early colonizers. Late colonizers, such as Klebsiella pneumoniae (p = 0.515) and K. oxytoca (p = 0.341), appeared in older age groups. The group of persistent microorganisms consisted of Proteus vulgaris/mirabilis (p = 0.705), which were consistently present in most of the study groups, as well as Clostridioides perfringens, detected in 5 (I, II, III, V, VI) of the 7 groups studied (p = 0.292). As previous studies have shown, anaerobic spore-forming rods of the Clostridioides genus are representatives of the gut microbiota of the large intestine in monkeys [2, 15]. Enteropathogenic Escherichia coli was detected in 4 of the 7 studied groups (p = 0.126).

In contrast to resident and persistent species, the detection of taxa such as Candida spp. (p = 0.493) and Bacteroides thetaiotaomicron (p = 0.074) — for which isolated values without a range were recorded — most likely reflects random occurrence and is not associated with persistent carriage.

The analysis revealed complex and multidirectional dynamics of age-dependent colonization of the rhesus macaque intestine by opportunistic pathogens and commensals.

An important finding is the absence of absolute pathogens: Salmonella spp. and Shigella spp. were not detected in any age group, indicating the favorable epizootic status of the studied population and controlled animal housing conditions.

The rhesus macaque gut microbiota constitutes a unique ecosystem that exists in dynamic equilibrium with the host organism. Its main characteristic is the constant presence of a significant number of opportunistic microorganisms, which are not an anomaly but a variant of the species norm.

Nevertheless, the reference ranges for rhesus macaques differ significantly from those of humans for most microbiological parameters, confirming the need to use species-specific norms.

Clear evidence of this is a comprehensive analysis of the age-related dynamics of dominant taxa in the gut microbiota of rhesus macaques, with an assessment of the statistical significance of the identified differences between age groups, presented in Fig. 1.

 

Fig. 1. Age-related changes in the relative abundance of dominant taxa in the gut microbiota of rhesus macaques. a–e — relative abundance (copies/mL) of symbionts and key commensals (Lactobacillus spp., Bifidobacterium spp., Escherichia coli, Bacteroides spp., Faecalibacterium prausnitzii); g — ratio of Bacteroides fragilis group to Faecalibacterium prausnitzii. Data are presented as the median (Me) and interquartile range. The statistical significance of differences between age groups was assessed using the nonparametric Kruskal–Wallis test. Significance levels: *p < 0.05; **p < 0.01; ***p < 0.001; ns — statistically insignificant differences.

 

Statistically significant age-related trends were observed for most indicators (p < 0.01 according to the Kruskal–Wallis test): Lactobacillus spp. (p = 0.003616) — a marked decrease in abundance was observed from the maximum values in group I (7.74–9.81) to the minimum values in group VII (5.88–6.98), indicating a significant restructuring of the microbial community during ontogenesis. Despite the significance of the overall test, post-hoc analysis did not reveal significant pairwise differences between groups, indicating a distributed nature of the changes. Highly significant changes in Bifidobacterium spp. were detected (p = 0.000054), with peak values in groups I (9.93–11.18) and IV (9.60–11.08), indicating complex nonlinear dynamics of this key taxon. Significant differences were identified between groups I and II (p < 0.001), I and III (p = 0.023), and II and IV (p = 0.040). Escherichia coli reflects fundamental microbial changes in the microbial ecosystem (p = 0.000021), as this taxon exhibits the most significant age-related differences, with a progressive decrease in concentration from young to mature age. Significant differences: I and V (p < 0.001), I and VI (p < 0.001), II and VI (p = 0.0036), III and VI (p = 0.0021), IV and VI (p = 0.034). The processes characterizing the maturation of the Bacteroides spp. community (p = 0.000021) increase significantly with age, reaching a maximum in groups VI–VII (9.48–10.30). Statistically significant differences from group I were found for groups III–VII (p < 0.001); and with group II for groups III–VII (p < 0.001). Significant changes in the balance between the key bacterial groups Bacteroides fragilis group/Faecalibacterium prausnitzii (p = 0.004752) indicate age-related changes in the functional state of the gut microbiota. The overall test revealed significant differences; however, post-hoc analysis did not identify significant pairwise differences between specific age groups.

Key stable indicators (p ≥ 0.05): TBM (p = 0.075) remains relatively constant throughout life, indicating the preservation of a stable quantitative capacity of the gut microbiota despite age-related changes in its qualitative composition. F. prausnitzii (p = 0.617) demonstrates exceptional stability across all age groups, allowing it to be considered a stable core of the gut microbiota.

The reference ranges developed, which take into account the species and age of the animals, are an essential tool for reliably assessing the state of the gut microbiome in scientific research. Despite the similarities, our results not only demonstrate the inapplicability of human standards to primates but also reveal the complex dynamics of the age-related development of their microbial status, which necessitates the use of age-specific standards.

To analyze the continuous relationship between the relative abundance of taxa and age, scatter plots with trend lines were constructed (Fig. 2).

 

Fig. 2. The relationship between age-related dynamics and the composition of the gut microbiota in rhesus macaques. a–e — graphs showing the relationship between the relative abundance (copies/mL) of symbionts and key commensals (Lactobacillus spp., Bifidobacterium spp., Escherichia coli, Bacteroides spp., Faecalibacterium prausnitzii). The trend line with a slope coefficient (k). f — lower correlation triangle between age and the relative abundance of major GM taxa. Cell colors indicate the strength of the correlation: red indicates a positive correlation, blue a negative one. Pearson’s coefficients (r) are shown in the cells.

 

The plotting of trend lines and calculation of the slope revealed age-related changes in opposite directions: for Lactobacillus spp. (Fig. 2, a) and Escherichia coli (Fig. 2, c), the slope was negative, reflecting a tendency toward a decrease in their relative abundance with age, whereas for Bacteroides spp. (Fig. 2, d), the slope was positive, indicating a tendency toward an increase. At the same time, for Bifidobacterium spp. and Faecalibacterium prausnitzii, the visualized trend lines showed a weak positive slope.

Calculating the slope of the trend line not only quantitatively confirmed the previously identified age-related differences but also allowed us to determine the direction and strength of the continuous relationship between an individual’s age and the abundance of key taxa. This indicates the presence of stable ontogenetic trends: a progressive decrease in the proportion of Lactobacillus spp. and Escherichia coli, as well as an increase in the proportion of Bacteroides spp. in the gut microbiota of rhesus macaques throughout their lifetime.

The results of the correlation analysis, presented as a correlation matrix (Fig. 2 e), revealed statistically significant linear relationships with age. A moderate negative correlation between relative abundance and age was found for Lactobacillus spp. (r = –0.34; r² = 11.56%; p < 0.001) and Escherichia coli (r = –0.33; r² = 10.89%; p < 0.001). For Bacteroides spp., a weak but significant positive correlation was identified (r = 0.25; r² = 6.25%; p < 0.01). For Bifidobacterium spp. (r = 0.17; r² = 2.89%; p = 0.0668) and Faecalibacterium prausnitzii (r = 0.062; r² = 0.38%; p = 0.5027), no significant linear relationship with age was found, which may indicate the presence of a nonlinear relationship or a significant influence of other, unaccounted-for factors.

Thus, despite the moderate correlation coefficients, the proportion of explained variation (r² = 10–12%) is statistically significant (p < 0.001) and, given the high complexity of the microbial ecosystem, indicates a substantial contribution of age to the formation of quantitative characteristics of key GM taxa. The obtained data confirm that age is a significant factor determining the structure of the microbial community, and the identified indicator taxa can be considered as markers of the organism’s developmental stages. The established patterns reflect the complex nature of GM restructuring during the ontogenesis of rhesus macaques, where, alongside pronounced linear trends for some taxa (Lactobacillus spp., Escherichia coli, Bacteroides spp.), more complex dynamic patterns are observed for other taxa (Bifidobacterium spp., Faecalibacterium prausnitzii).

Discussion

This study reveals the complex dynamics of rhesus macaque gut microbiota formation during ontogenesis. The data demonstrate that, despite the preservation of a common structural core of the microbial community represented by universal symbionts, the quantitative indicators and age-related trajectories of most taxa exhibit distinct species-specific characteristics. This is consistent with the concept of the phylotype, where general features of the microbiome are conserved within the primate order [14, 16, 17], yet specific quantitative variations in taxa result from adaptation to the species’ diet and ecological niche, which is a key factor in species specificity [18, 19].

The observed progressive reduction in the abundance of Lactobacillus spp. and Escherichia coli against a background of an increase in the proportion of Bacteroides spp. and the progressively increasing prevalence of Akkermansia muciniphila in groups IV–VII reflect fundamental processes of microbial-host co-adaptation. Such succession — a decrease in the proportion of facultative anaerobes (Lactobacillus spp., Escherichia coli) against a background of accumulation of obligate anaerobes (Bacteroides spp.) — represents a conserved pattern of GM maturation in mammals, including humans, and is determined by key ontogenetic events: the transition to a solid diet and the functional maturation of the gut immune system [20]. Our data confirm the universality of this phenomenon in primates, while simultaneously revealing species-specific features of its dynamics. Statistical analysis confirms the significance of age as a factor determining these changes. Despite moderate correlation coefficients, the proportion of explained variance (r² = 10–12%) is statistically significant (p < 0.001), indicating that age is instrumental in shaping the quantitative characteristics of key taxa in the gut microbiota.

In the studied sample, the presence of Fusobacterium nucleatum is not associated with pathological conditions. Of particular interest is the U-shaped trend with reactivation in the older age group, which may be associated with involutive changes in the immune system and the intestinal mucosal barrier. Similar age-dependent changes in the prevalence of Fusobacterium nucleatum have been described in the gut microbiota of elderly individuals, indicating common, conserved mechanisms of age-related immunometabolic remodeling in primates [4, 21] and supporting our hypothesis.

The stability of the TBM and the levels of Faecalibacterium prausnitzii — a key producer of butyrate — indicates that the microbial community maintains metabolic homeostasis despite significant restructuring of its taxonomic composition, which is consistent with the principle of functional redundancy in microbial communities [22]. Low Bacteroides fragilis group/F. prausnitzii ratios at an early age highlight the specificity of microbial community formation in primates. This ratio is sometimes considered a marker of GM maturity, and its low initial values are consistent with the general model of gradual community maturation [8].

The presence of a significant number of opportunistic pathogens within the physiological norm of rhesus macaques indicates tolerance mechanisms developed through evolution that are absent in humans. Virtually all of the listed opportunistic pathogens, such as Enterobacter spp., Klebsiella spp., Staphylococcus aureus, and others, are consistently detected in macaques in quantities exceeding human reference values (often by 1–3 orders of magnitude), while some (Clostridioides difficile, Clostridioides perfringens) are present even when the human norm is not detected. This demonstrates a species-specific microbiome profile, where these microorganisms are not markers of pathology but rather part of a stable normal microbiota. This supports the argument that extrapolating human reference values to primates is inappropriate. Studies on other non-human primates also show higher baseline levels of potential pathogens compared to humans, a finding attributed to differences in immune regulation and environmental stressors [18].

An important discovery is the absence of the pathogenic microorganisms Salmonella spp. and Shigella spp. — the most significant pathogens of bacterial diseases in monkeys⁴. This indicates the epizootic well-being of the studied population under controlled monkey husbandry conditions.

Conclusion

This study determined the species- and age-specific ranges of the quantitative content of key gut microbiota taxa in rhesus macaques, as detected by real-time PCR using the KOLONOFLOR-16 test system. The data obtained serve as a basis for assessing microbial status when using monkeys to study pathologies associated with dysbiosis (inflammatory bowel diseases, metabolic syndrome, etc.).

The study was conducted on rhesus macaques kept under strictly controlled conditions: a standardized diet, identical microclimate parameters, and no history of experimental interventions. This allowed us to minimize the influence of external factors and identify age-related changes in the gut microbiota under the most homogeneous conditions possible.

The data presented in this study will be used to establish reference ranges based on larger samples, as well as to interpret microbial status in translational studies involving primates.

The patterns identified underscore the complex nature of microbe-host coevolution and the need to account for age-specific norms when assessing the microbiome of laboratory primates. The data obtained provide a basis for developing more accurate diagnostic criteria for various pathological conditions in order to study the functional consequences of the identified age-related changes in the microbiome.

 

¹ NCBI Taxonomy to include phylum rank in taxonomic names. URL: https://ncbiinsights.ncbi.nlm.nih.gov/2021/12/10/ncbi-taxonomy-prokaryote-phyla-added

² GOST 34566-2019 "Complete Feed for Laboratory Animals."

³ SanPiN 3.3686-21 "Sanitary and Epidemiological Requirements for the Prevention of Infectious Diseases."

⁴ Guideline 1.3.0012/1-13. Monkey diseases dangerous to humans. Rules for the maintenance and handling of monkeys in quarantine upon receipt of animals from external sources, as well as during experimental infection.

About the authors

Veronika I. Polyakova

Kurchatov Complex of Medical Primatology of NRC "Kurchatov Institute"

Author for correspondence.
Email: veronika-9509@mail.ru
ORCID iD: 0009-0001-5799-4697

Researcher, Laboratory of microbiology and virology

Russian Federation, Sochi

Anton P. Pushkarev

Kurchatov Complex of Medical Primatology of NRC "Kurchatov Institute"

Email: pushkarev@neuro.nnov.ru
ORCID iD: 0000-0002-8690-8444

junior researcher, Laboratory of gerontology

Russian Federation, Sochi

Alvard V. Demerchyan

Kurchatov Complex of Medical Primatology of NRC "Kurchatov Institute"

Email: demerchyan71@mail.ru
ORCID iD: 0009-0007-6473-3237

researcher, Laboratory of microbiology and virology

Russian Federation, Sochi

Ilona M. Arshba

Kurchatov Complex of Medical Primatology of NRC "Kurchatov Institute"

Email: aim26@mail.ru
ORCID iD: 0000-0003-3098-8104

Cand. Sci. (Biol.), Head, Laboratory of microbiology and virology

Russian Federation, Sochi

Alexander V. Popov

Kurchatov Complex of Medical Primatology of NRC "Kurchatov Institute"

Email: popov@neuro.nnov.ru
ORCID iD: 0000-0003-1827-6841

Cand. Sci. (Tech.), Head, Laboratory of gerontology, Deputy Head

Russian Federation, Sochi

References

Supplementary files