Study participantsAmong the 69 PLWH participants in this study, the median age was 54 (IQR, 45–62) years, the median duration on ART was 7 (IQR, 4–15) years, and the median BMI was 25 (IQR, 23–27) kg/m2. For the HC (n = 80), the median age was 53 (IQR, 34–66) years and the median BMI was 25.1 (IQR, 23–29) kg/m2. More than 90% of PLWH had less than 50 HIV RNA copies/mL at the microbiome collection. There were no significant differences between age, sex, and BMI between PLWH and HC (Table 1). The ART regimens included a backbone of NRTIs with either an INSTI (n = 56) or an NNRTI (n = 13), and PI (n = 2) as third drug. INSTI treated participants were either on dolutegravir (DTG, 75%) or bictegravir (BIC, 23%). The major modes of transmission (MSM vs. Heterosexual) were similarly distributed among those treated with INSTIs and NNRTIs.Table 1 Baseline demographic and clinical characteristics of the study participants.Lower bacterial diversity and enrichment of pathobionts in PLWH compared to HCPLWH showed significantly lower alpha diversity, particularly richness, compared to HC in both fecal (Observed p = 0.048, Shannon, p = 0.001, Simpson p = 0.001) and oral samples (Observed p < 0.0001, Shannon, p = 0.051) (Fig. 1A). Additionally, there were also significant differences in the beta diversity between these two groups (Fig. 1B, p = 0.001), with distinct clustering patterns in both gut and oral environments (Fig. 1B). A total of 258 bacterial taxa were detected in the entire cohort including both fecal and oral samples with several significant differences in microbial composition between PLWH and HC. For the fecal samples, Klebsiella (p = 0.046), Succinivibrio (p = 0.014), Escherichia-Shigella (p < 0.0001), Cloacibacillus (p = 0.03) and Ruminococcus gnavus group (p = 0.02) were significantly enriched in PLWH, whereas Faecalibacterium (p < 0.0001), Ruminococcus (p = 0.001), Lachnospira (p = 0.02) and Bifidobacterium (p = 0.004) were significantly more abundant in the HC (Fig. 1C). In the oral samples, Pseudorhodobacter (p = 0.01) and Bulleidia (p = 0.018) were significantly more abundant in PLWH and Leptotrichia (p = 0.01) in HC (Fig. 1D).Figure 1Alpha diversity and compositional changes in the gut and oral microbiome between Healthy Controls (HC, n = 80) and People living with HIV (PLWH, n = 69). (A) Boxplots showing the differences in the alpha diversity indices within the HC and PLWH in the gut and oral environment (B) NMDS plot illustrating the changes of beta diversity within the HC and PLWH in the gut and oral environment. Linear discriminant analysis effect size (LEfSe) analysis at the genus level showing the differentially abundant microbiota between HC and PLWH in the (C) gut and (D) oral samples, respectively.Alterations in the microbial compositions in PLWH based on immune status and time on antiretroviral therapyPLWH were further stratified for three parameters into two groups based on CD4+ T-cell count (< / ≥ 350 cells/µL), CD4+ Nadir (< / ≥ 200 cells/µL), CD4/CD8 ratio (< / ≥ 0.79), and time on ART (< / ≥ 5 years). There were no differences observed in the alpha diversity indices between the individuals belonging to the different groups defined by above-mentioned variables (data not shown). However, individuals with high CD4/CD8 ratio showed higher abundance of Dialister (p = 0.03), Agathobacter (p = 0.03), Succinivibrio (p = 0.03), and Butyrivibrio (p = 0.01) in the gut environment and Dialister (p = 0.01), Alloprevotella (p = 0.03) and Megasphaera (p = 0.02) in the oral environment. Conversely, individuals with low CD4/CD8 ratio were significantly enriched with Ruminococcus gnavus group (p = 0.03) in the gut environment and Streptococcus (p = 0.04) and Rothia (p = 0.03) in the oral environment (Fig. 2A).Figure 2Differences in abundance of bacterial taxa evaluated using Linear discriminant effect size (LEfSe) analysis in both gut and oral environment in (A) Individuals with high (n = 39) and low CD4/CD8 ratio (n = 30), (B) individuals who received long-term ART (n = 49) or short-term ART (n = 20), (C) PLWH on NNRTI (n = 13) and INSTI (n = 53) and (D) subjects under different INSTI drug regimens (DTG, n = 41) (BIC, n = 12) and NNRTI treatment (n = 13). NNRTI: non-nucleoside reverse transcriptase inhibitors, INSTI: integrase strand transfer inhibitors.Furthermore, Phascolarctobacterium (p = 0.03) was significantly more abundant in individuals with low CD4+ T-cell count whereas Dialister (p = 0.047), and certain members of Ruminicoccacea family, such as Ruminococcacea UCG-002 (p = 0.04) and Ruminococcacea UCG-013 (p = 0.02) were increased in individuals with high CD4+ T-cell count in the fecal samples (Fig S1 A). Moreover, the oral microbiome also showed enrichment of Dialister (p = 0.016) and Megasphaera (p = 0.003) in individuals with high CD4+ T-cell count (Fig S1 B). Similarly, when stratified based on their nadir CD4+ T-cell count, in the gut environment we observed a significant abundance of Succinivibrio (p = 0.03) and Dialister (p = 0.04) in PLWH with high nadir CD4 + T-cell count and Bacteriodes in PLWH with low nadir CD4 + T-cell. In the oral environment, we found a significant increase in Megasphaera (p = 0.003) and Dialister (p = 0.02) in PLWH with high nadir CD4+ T-cell count and Neisseria (p = 0.02) in PLWH with low nadir CD4 + T-cell count (data not shown).PLWH on ART for more than 5 years had increased numbers of Succinivibrio (p = 0.024), Christensenellaceae R-7 group (p = 0.015), and Dialister (p = 0.04) in the fecal samples, while Roseburia (p = 0.03) was significantly more abundant in PLWH on short-term ART (Fig. 2B). Moreover, in oral samples, individuals on longer duration of ART showed an abundance of Selenomonas (p = 0.016), Camphylobacter (p = 0.04) and Dialister (p = 001), which were also observed in individuals with high CD4/CD8 ratio. Likewise, individuals on short-term ART and with low CD4/CD8 ratio showed an abundance of Streptococcus (p = 0.04).Differences in the gut microbiome associated with different treatment regimensTo explore the influence of the INSTIs and NNRTIs on microbiome, we stratified PLWH based on their drug regimen. In the fecal samples, Faecalibacterium (p = 0.02) and Bifidobacterium (p = 0.04) were significantly more abundant in PLWH on INSTIs, while Escherichia-Shigella (p = 0.04), Gordonibacter (p = 0.04), Megasphaera (p = 0.01), and (p = 0.04) were enriched in PLWH on NNRTIs (Fig. 2C). In the oral samples, we found higher abundance of Veillonella (p = 0.006) in INSTI-treated individuals and significant enrichment of Fusobacterium (p = 0.02), Alloprevotella (p = 0.03), Staphylococcus (p = 0.04), and Dialister (p = 0.03) in PLWH on NNRTI-treatment.We further analyzed PLWH on dolutegravir (DTG) or bictegravir (BIC) and compared them to NNRTI. In the gut environment, a higher abundance of Bifidobacterium (p = 0.02), Anerostipes (p = 0.03), Butyricimonas (p = 0.04) and Butyricicoccus (p = 0.045) was observed in BIC-treated individuals, Faecalibacterium (p = 0.04) and Ruminococcus gauvreauii group (p = 0.03) in DTG-treated individuals and Megasphaera (p = 0.02) in NNRTI-treatment recipents (Fig. 2D). Conversely, in the oral environment we observed higher abundance of Alysiella (p = 0.003), Veillonella (p = 0.02), and Mycoplasma (p = 0.03) in BIC-, DTG-, and NNRTI-treated PLWH, respectively.Since mode of transmission (MOT) has been identified as one of the factors influencing microbiome in PLWH3,13, we stratified the individuals with different MOT (MSM vs Heterosexuals) into separate treatment groups. The same microbiome markers were not associated with MOT groups but varied within treatment groups (data not shown). This implies that MOT was not the major driver of microbiome changes in our cohort.Relationship between gut microbiota composition and BMIBased on the potential clinical association between INSTI treatment and weight gain reported in few studies19,20, we further explored the link between microbiome, ART, and BMI in our cohort. In the gut microbiome of PLWH, Succinivibrio (p = 0.045), Dorea (p = 0.004), and Bifidobacterium (p = 0.03) were significantly higher in individuals with high BMI (> 25) and Escherichia-Shigella (p = 0.01), Bacteroides (p = 0.04) and Klebsiella (p = 0.03) were enriched in group with low BMI (< 25). In oral samples, we observed higher abundance of Prevotella (p = 0.02), Dialister (p = 0.004), and Veillonella (p = 0.01) in PLWH with overweight and Neisseria (p = 0.03) in PLWH with low BMI (Fig. 3A, B). Similar microbial signatures were also observed in individuals with high and low BMI belonging to the whole cohort (PLWH and HC) in both oral and gut samples (Fig S2). These signatures were most likely shaped by PLWH status, since stratifying the HC group into high and low BMI have not revealed similar associations.Figure 3Differences in the gut and oral microbiome in PLWH, further divided into two groups based on BMI. Linear discriminant analysis effect size (LEfSe) analysis showing the significant microbial organisms between individuals with high and low BMI (< / ≥ 25 kg/m2) in the gut and oral environment: differences (A) in PLWH (high BMI n = 37, low BMI, n = 32), and (B) in PLWH treated with DTG (high BMI n = 24, low BMI n = 17). Spearman correlations showing the association between BMI and microbial composition at the genus level within the gut and oral environment in the (C) whole cohort and (D) PLWH.DTG has been primarily associated with visceral fat accumulation33. As nearly 70% of all PLWH were treated with DTG, we sub-categorized DTG-treated individuals based on low and high BMI. In the fecal samples Bifidobacterium (p = 0.01), Dorea (p = 0.03), and Streptococcus (p = 0.01) were significantly more abundant in people with high BMI, while Bacteroides (p = 0.047) and Escherichia-Shigella (p = 0.045) were more abundant in people with low BMI.We further investigated correlations between BMI and abundance of bacterial taxa in the whole cohort. We observed that Bifidobacterium (p = 0.04) was positively correlated with BMI and Klebsiella (p = 0.03), Escherichia-Shigella (p = 0.05), and Cloacibacillus (p = 0.046) were negatively correlated with BMI, in both oral and gut environment. In PLWH, positive correlation between Prevotella (p = 0.02), Dialister (p = 0.05), Megasphaera (p = 0.04), Bifidobacterium (p = 0.058) and BMI and negative correlation of Klebsiella (p = 0.02), Escherichia-Shigella and BMI were found (Fig. 3C, D).Effect of DTG on the gut and oral microbiotaWe conducted a more in-depth analysis of the associations between the microbiome and several clinical factors, such as age, duration of treatment, and CD4+ T-cell counts in PLWH on DTG. In the gut milieu, alpha diversity was lower in the younger individuals (18–39 years) compared to the elderly (> 60 years) (p < 0.01, Fig S3 A). We also found significant differences in beta-diversity among the age groups (p = 0.05) (Fig S3 B). At the genus level, younger individuals displayed a significantly greater abundance of Lachnospira (p = 0.04) and Eggerthella (p < 0.0001), while elderly individuals harbored a higher abundance of Coprococcus (p = 0.01) and Dorea (p = 0.01) (Fig S3 C). However, for oral samples, we found no significant differences in alpha and beta diversity between the age groups (Fig S3 D, E). We also found that Kingella was significantly abundant in younger individuals and Leptotrichia and Ruminococcaceae UCG-004 were abundant in the middle-aged group (40–59 years) (Fig S3 F).Moreover, in the DTG-treated group, PLWH with longer treatment duration exhibited significantly higher alpha diversity indices in fecal microbiome compared to those on short-term ART (Fig S4 A), with a higher abundance of Succinivibrio (p = 0.034) (Fig S4 B). On the other hand, the alpha diversity hasn’t changed significantly in between the individuals during longitudinal follow-up and short-term follow-up in the oral compartment (Fig S4 C), although the saliva samples of individuals under long-term ART had a higher prevalence of Dialister (p = 0.04) (Fig S4 D).Additionally, gut microbiome richness was increased in PLWH on DTG and higher CD4+ T-cell counts compared to those with lower immune status (Observed p = 0.014, Fig S5 A). We observed an enrichment of Fusobacterium (p = 0.05), Ruminococcus gnavus group (p = 0.02), and Lachnoclostridium (p = 0.01) in individuals with lower CD4+ T-cell counts, whereas Dialister (p = 0.01), Ruminococcus (p = 0.004), and Agathobacter (p = 0.02) were more abundant in those with higher CD4+ T-cell counts (Fig S5 B). Conversely, oral microbiome richness and diversity was higher in individuals with low CD4+ T-cell counts compared to that of individuals with higher counts (Simpson p = 0.046, Fig S5 C). As for oral samples, an enrichment of Peptococcus (p = 0.02), Kingella (p = 0.01), and Paludibacteraceae F0058 (p = 0.002) was noted in DTG-treated individuals with low CD4+ T-cell counts (Fig S5 D).
