**2. Results**

### *2.1. Data Annotation and Sample Overview*

A total of 120 nasopharyngeal microbiomes from 120 healthy individuals were analyzed. A total of 4,538,196 high-quality 16S rRNA sequences ranging from 10,627 to 256,449 sequences per sample (mean = 37,818.3; median = 33,169) were obtained after quality control analyses and OTU filtering. The 16S rRNA sequences were binned into 128 families, 250 genera and 561 species. The most abundant families were Staphylococcaceae (12.14%), Burkholderiaceae (11.52%), Carnobacteriaceae (11.48%) and Corynebacteriaceae (9.47%). The most abundant genera were *Staphylococcus* (13.06%), *Dolosigranulum* (11.99%), *Corynebacterium* (10.18%) and *Ralstonia* (10.08%). The most abundant species were *Dolosigranulum pigrum* (24.55%), *Ralstonia pickettii* (19.02%), *Corynebacterium pseudodiphtheriticum* (4.87%) and *Propionibacterium acnes* (4.85%). We excluded one sample with an abnormally high proportion of *Chlamydophila*, which is an indication of an abnormal sampling or pathological disorder of this individual 'C\_A1\_M8'. To reveal age-related progression of nasopharyngeal microbiota, we divided the samples into six age groups, each divided into females and males to be able to also study possible sex-associated differences (Table S1). There were 20 samples in each age group and 10 samples in each sex group within them, except for the first age group (A1: 1–20 years) where one male had to be excluded as indicated above (Table S1).

We sought to determine the ways in which different samples were grouped according to their OTU composition. To that end, we applied nonmetric multidimensional scaling (NMDS), which is a powerful statistical tool that enables complex multivariate data sets to be visualized in a reduced number of dimensions, to determine the clustering patterns of samples according to their Bray–Curtis distances (which were calculated based on the relative abundance matrix of the 250 genera across the 119 samples) (Figure 1). The analysis of similarities (ANOSIM), which is a non-parametric statistical test, was used to analyze whether there were statistically significant differences among the different age groups included in this study. Thus, even though the samples apparently did not form distinct clusters when viewed using this approach as they appeared mostly intermixed and the different confidence ellipses overlapped each other, the differences between the age groups A1–A4 (ANOSIM statistic, 0.1075; significance, 0.016) and A1–A5 (ANOSIM statistic, 0.1075; significance, 0.016) were significant according to ANOSIM (Figure 1). Similar result was obtained when focusing on possible differences between the two sexes, as samples from females and males also appeared completely intermixed and did not form any groups, and significant differences were not detected according to ANOSIM (Figure 1).

**Figure 1.** Microbial community composition. Nonmetric multidimensional scaling (NMDS) plot of the Bray–Curtis distances which were calculated using the relative abundance of the 250 genera across the 119 samples as input. Each sample is represented by one dot, colored according to age, and shaped according to sex. The 90% confidence data ellipses are shown for each age group.

#### *2.2. Bacterial Diversity in the Nasopharynx of Healthy Individuals Is Stable throughout Lifespan*

The fact that significant changes in bacterial diversity throughout life had previously been described in the well-studied gut microbiota of healthy individuals [24] prompted us to test whether similar changes occur in the nasopharynx by analyzing the alpha diversity, referred to as within-community diversity [25], for the different age and sex groups established for this study (Table S1). However, the Shannon's diversity index, which measures evenness and richness of communities within a sample, did not show any statistically significant changes in bacterial diversity among the different age groups (Figure 2a). Moreover, alpha diversity also did not vary as a function of sex when the Shannon index was calculated considering all individuals of all ages included in this study (Figure 2b), nor when the same analysis was performed comparing females and males within each age group (Figure 2c). The use of other indexes commonly used to measure alpha diversity, such as the inverse Simpson's diversity index, which is an indication of the richness in a community with uniform evenness that would have the same level of diversity (Figure S1), or the Chao1 index, which measures the total richness of communities within a sample (Figure S2), confirmed the absence of any statistically significant differences in bacterial diversity between the different age groups (Figures S1a and S2a) or between females and males (Figures S1b,c and S2b,c). Therefore, all these results together suggest that contrary to what occurs in other anatomical areas, such as the gut where bacterial diversity decreases with aging [24], it remains stable in the nasopharynx of healthy people over time, without notable changes at any stage of life, not even in very young people or in the elderly over 70 years of age (Figure 2a and Figures S1a and S2a). Curiously, another interesting finding provided by this work, for the first time, is that there are no significant differences when comparing bacterial diversity in the nasopharynx of healthy females and males (Figure 2b,c and Figures S1b,c and S2b,c), regardless of the stage of life studied and the important hormonal differences that exist between both sexes at certain ages.

**Figure 2.** Comparison of alpha diversity parameters across the age and sex groups studied. Boxwhisker plots of the alpha diversity Shannon index and its comparison using the Kruskal–Wallis test among the different age groups established for this study (**a**), and the Wilcoxon signed-rank test between females and males (**b**,**c**). Each sample is represented by one dot. The age group A1 includes subjects between 1 and 20 years old, A2 between 21 and 40, A3 between 41 and 50, A4 between 51 and 60, A5 between 61 and 70, and A6 includes individuals over 70 years of age (Table S1).
