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Associations between bacterial and fungal communities in the human gut microbiota and their implications for nutritional status and body weight – Scientific Reports

In this study, we assessed the IBac (Intestinal Bacteriota) and IMy (Intestinal Mycobiota) profiles of 10 healthy-weight, 10 overweight, and 10 obese subjects, categorized according to the World Health Organization body mass index (BMI) classification. Anthropometric, dietary, and biochemical analyses were also conducted on each participant. The study cohort predominantly consisted of women, with an average age of 29.53 ± 7.85 years. Notably, significant differences in anthropometric parameters were observed among the healthy-weight, overweight, and obese groups. The percentage of fat mass increased progressively with BMI in all three groups (26.64 ± 9.79%, 29.01 ± 4.80%, and 37.40 ± 4.69%, respectively), whereas the percentage of lean mass exhibited a corresponding decrease (30.30 ± 0.09%, 24.9 ± 3.92%, and 23.52 ± 3.39%, respectively) (p < 0.0041). Waist average circumferences also escalated with BMI, with values of 77.23 ± 8.88 cm, 81.96 ± 4.36 cm, and 101.58 ± 13.12 cm in the healthy-weight, overweight, and obese groups, respectively (p < 0.0001) (Table 1). Biochemical analyses showed statistically significant distinctions among the groups. In particular, the obese group exhibited elevated levels of ALT, GGT enzymes, triglycerides, and glucose (p < 0.05), while HDL levels were higher in the healthy-weight group (54.04 ± 12.05) compared to the overweight (41.17 ± 6.33) and obese (38.08 ± 2.67) groups (p < 0.003). Regarding dietary parameters, kilocalories, carbohydrates, proteins, simple and complex carbohydrates, meat, and vegetable intake were notably higher in the obese group in comparison to the healthy-weight and overweight groups. However, only protein and meat consumption had significant statistical differences (p < 0.05). Significant differences remained after FDR correction (p < 0.05) (Table S1).

Table 1 Sociodemographic, anthropometric, biochemical, and dietary characteristics of the participants.

To elucidate the gut microbial composition, we sequenced samples using the 16S and ITS rRNA gene genetic markers to determine bacterial and fungal microorganisms, respectively. Sequencing data analysis revealed a total of 4,379,541 raw reads obtained for the V3–V4 hypervariable region of the 16S rRNA gene, while the ITS1 region yielded 3,775,592 reads. SILVA reference database analysis classified 74.70% of these reads as bacteria, while UNITE database analysis identified 32.36% as fungi (Table S2). The rarefaction curve illustrates the attainment of an asymptotic phase in the sampled data (Fig. S1). Interestingly, at the genus level, no significant differences were detected in the analysis of alpha diversity (including the Shannon index, Chao 1, and Simpson) for either IBac or IMy among the three study groups (Figs. S2, S3, respectively). Notably, bacteria displayed higher alpha diversity values compared to fungal communities across all three study groups. Healthy individuals exhibited lower alpha diversity in their bacterial communities compared to overweight and obese subjects. The Bray–Curtis dissimilarity metric was employed to perform beta diversity analysis (Fig. 1). The outcomes were graphically represented using Principal Coordinates Analysis (PCoA) at the genus level for both IBac and IMy. The PCoA plot for IBac indicated that the overweight group did not overlap with either the obesity or healthy-weight groups. This suggests statistically significant differences between the groups (p < 0.028) (Fig. 1a). In contrast, the PCoA plot for IMy showed overlapping clusters, revealing no statistically significant differences among the groups (p < 0.677) (Fig. 1b).

Figure 1
figure 1

Beta diversity analysis of the dataset focusing on the bacterial (a) and fungal (b) genera present in the gut microbiota of the participants.

The taxonomic distribution of bacterial and fungal communities at the phylum and genus levels is presented in Fig. 2. Bacillota and Bacteroidota were the predominant phyla across all three study groups (Fig. 2a). Bacillota exhibited an increasing trend with rising BMI in the healthy-weight, overweight, and obese groups (48.32%, 50.43%, and 60.84%, respectively), while Bacteroidota displayed the opposite pattern, decreasing with elevated BMI in these groups (45.17%, 38.79%, and 29.95%, respectively). Pseudomonadota (previously Proteobacteria11) accounted for 3.28%, 4.81%, and 4.36% of the microbial composition in healthy-weight, overweight, and obese subjects, respectively. At the genus level, Prevotella exhibited a higher prevalence in the healthy-weight group (26.05%), gradually declining in the overweight and obese groups (9.87% and 4.51%, respectively). Bacteroides showed substantial abundance in all three groups, comprising 15.52%, 18.88%, and 20.51% in healthy-weight, overweight, and obese groups, respectively (Fig. 2b and Table S3). Overweight and obese individuals had elevated abundance of Akkermansia, Dialister, Phascolarctobacterium, Subdoligranulum, and Ruminococcus, compared to the healthy-weight group.

Figure 2
figure 2

Taxonomic assignments of the intestinal bacteriota (IBac) and intestinal mycobiota (IMy) of participants, presented at the phylum (a, c) and genus (b, d) levels, respectively, using the QIIME 2.0 software.

In the analysis of IMy, Ascomycota and Basidiomycota were the dominant phyla across all three groups. Ascomycota constituted 97.19%, 94.72%, and 93.26% in the healthy-weight, overweight, and obese groups, respectively, while Basidiomycota accounted for 2.81%, 5.27%, and 6.74% in the healthy-weight, overweight, and obese groups, respectively (Fig. 2d). Among the fungal genera, Nakaseomyces exhibited the highest prevalence in all three groups, representing 41.39%, 17.48%, and 28.33% in the healthy-weight, obese, and overweight groups, respectively. Saccharomyces accounted for 9.15%, 36.00%, and 44.52% in the healthy-weight, overweight, and obese groups, respectively. Candida exhibited elevated abundance in overweight individuals (21.86%), followed by the healthy-weight group (4.15%) and the obese group (3.35%). Debaryomyces displayed higher prevalence in overweight and obese subjects (8.64% and 4.96%, respectively) compared to healthy-weight subjects (1.15%). Kazachstania, Kluyveromyces, and Hanseniaspora were notably more prevalent in the healthy-weight group (26.29%, 3.09%, and 7.52%, respectively) compared to the overweight (1.10%, 2.71%, and 0.5%, respectively), and obese groups (0.01%, 0.60%, and 0.01%, respectively) (Table S4). Additionally, Pichia was abundant in obese subjects (1.84%).

Volcano plots revealed distinct statistical differences in genus abundance in bacterial and fungal genera across weight groups (Fig. 3). Among bacterial genera, Faecalibacterium, Lachnospira, Histophilus, Rikenella, Holdemanella, Hydrogenoanaerobacterium, and Haemophillus were found to be significantly different between the healthy-weight and overweight groups (Fig. 3a). In comparison to obese subjects, healthy-weight subjects showed differential taxa including Prevotella, Blautia, Lachnospira, Rikenella, Anaerostipes, Odoribacter, Marvinbryantia and Histophilus, while obese subjects had three differential taxa, namely Allisonella, Subdoligranulum and Dielma (Fig. 3b). Additionally, Lachnospira, Romboutsia and Clostridium were found to be differential genera in obese subjects in comparison to the overweight group, which had Flavonifractor, Eggerthella and Alloprevotella as differential genera (Fig. 3c). In terms of fungal genera, Malassezia and Aspergillus were differential genera in obese subjects (Fig. 3d).

Figure 3
figure 3

Volcano plots show statistically significant differences between weight groups in bacterial and fungal genus abundance. The x-axis shows the log2 of the fold change and the y-axis shows the -log of the p-value. (a) bacterial genera between the overweight and healthy-weight groups, (b) bacterial genera between the obese and healthy-weight groups, (c) bacterial genera between the obese and overweight groups, and (d) fungal genera between the obese and healthy-weight groups.

To analyze the associations between bacterial and fungal genera and weight status, a linear discriminant analysis (LDA) utilizing multi-mode predictor variables was employed. The LDA classified samples into distinct groups corresponding to healthy-weight, overweight, and obese individuals (Fig. 4). The scatterplots in Fig. 4a and b show the coefficients of the linear discriminant functions, revealing a pattern for the data in the three groups with overlapping areas. This indicates that the discriminant functions can distinguish between the presence of bacterial and fungal genera in healthy-weight, overweight, and obese subjects. The correlation was observed among anthropometric (Fig. 5a), biochemical (Fig. 5b), and dietetic (Fig. 5c) parameters in relation to the bacterial genera identified in healthy-weight, overweight, and obese groups. The bacterial genera with high abundance in the healthy-weight group showed positive correlations with parameters related to good health and negative relationships with parameters related to weight gain. For example, Histophilus showed a positive correlation with high-density lipoproteins (HDL) and a negative correlation with weight gain, BMI, waist and hip circumferences, carbohydrate intake, LDL cholesterol, and triglycerides (p < 0.05). Faecalibacterium showed a positive correlation with HDL and kilocalories intake from protein, and a negative correlation with fat mass and low-density cholesterol (LDL) (p < 0.05). Lachnospira was positively correlated with triglycerides, glucose, and very low-density lipoprotein (VLDL) cholesterol (p < 0.05). It also showed a negative correlation with simple carbohydrates such as sucrose, but this correlation did not reach statistical significance. Odoribacter showed a positive correlation with HDL and a negative correlation with BMI, waist circumference, glucose, and triglycerides, as well as carbohydrates intake, simple carbohydrates intake, and kilocalories. Prevotella had a negative correlation with BMI and carbohydrates intake (p < 0.05). In contrast, the bacterial genera that exhibited high abundance in the overweight and obese groups showed a positive correlation with parameters associated with obesity. Eggerthella showed a positive correlation with LDL cholesterol, total cholesterol, and simple carbohydrates intake (p < 0.05). Allisonella showed a positive correlation with weight gain, BMI, biceps skinfold, subscapular skinfold, suprailiac skinfold, waist and hip circumferences, fat mass, VLDL cholesterol, triglycerides, serum glucose, carbohydrate intake, and kilocalories (p < 0.05). Dielma showed a positive correlation with weight, BMI, triceps skinfold, subscapular skinfold, suprailiac skinfold, fat mass, kilocalories, and carbohydrates intake. However, the correlation did not reach statistical significance. Clostridium was positively correlated with obesity-related parameters such as weight gain, waist and hip circumferences, BMI, fat mass, triglycerides, glucose, VLDL cholesterol, kilocalories, and carbohydrate intake (p < 0.05).

Figure 4
figure 4

Comparison of the linear discriminant analysis of bacterial genera (a) and fungal genera (b) found in the intestinal microbiota of healthy-weight, overweight, and obese groups.

Figure 5
figure 5

Spearman correlation analysis of intestinal bacterial genera among the healthy-weight, overweight, and obese groups with anthropometric (a), biochemical (b), and dietary (c) variables. Total iron-binding capacity (TIBC) high-density lipoprotein (HDL), low-density lipoprotein (LDL), very low-density lipoprotein (VLDL), alanine aminotransferase (ALT), aspartate aminotransferase (AST), glutamic gamma transferase (GGT), and lactate dehydrogenase (LDH). *p < 0.05.

The correlation was observed among anthropometric (Fig. 6a), biochemical (Fig. 6b), and dietetic (Fig. 6c) parameters and the intestinal mycobiota in healthy-weight, overweight, and obese groups. Aspergillus and Malassezia showed a positive correlation with anthropometric parameters related to obesity, such as weight, BMI, subscapular and suprailiac skinfolds, waist, hip, and arm circumferences, but this correlation was not statistically significant. Saccharomyces exhibited a positive correlation with weight, BMI, triceps skinfold, biceps skinfold, and suprailiac skinfold, as well as with high fat mass (p < 0.05). Pichia showed a positive correlation with BMI, triceps skinfold, suprailiac skinfold, arm circumference, and fat mass (p < 0.05). Yarrowia displayed a positive correlation with weight, BMI, tricipital skinfold, suprailiac skinfold, and subscapular skinfold, waist and hip circumferences, and fat mass; however, it did not reach statistical significance except for the subscapular fold (p < 0.05). The correlation matrix of mycobiota and biochemical parameters showed fewer statistically significant correlations. Aspergillus showed a positive correlation with total bilirubin and direct bilirubin, whereas Pichia showed a positive correlation with total cholesterol (p < 0.05). Saccharomyces demonstrated a positive correlation with VLDL cholesterol, triglycerides, and glucose, and a negative correlation with total cholesterol, HDL, and LDL cholesterol, although this difference was not statistically significant. Candida, Yarrowia, Aspergillus, Saturnispora and Dekkera showed a positive correlation with the consumption of simple carbohydrates (p < 0.05). Hanseniaspora presented a positive correlation with meat consumption (p < 0.05). Malassezia and Pichia showed a positive correlation with kilocalories and carbohydrate consumption; however, this difference was not statistically significant.

Figure 6
figure 6

Spearman correlation analysis of intestinal fungal genera among the healthy-weight, overweight, and obese groups with anthropometric (a), biochemical (b), and dietary (c) variables. Total iron-binding capacity (TIBC) high-density lipoprotein (HDL), low-density lipoprotein (LDL), very low-density lipoprotein (VLDL), alanine aminotransferase (ALT), aspartate aminotransferase (AST), glutamic gamma transferase (GGT), and lactate dehydrogenase (LDH). *p < 0.05.