Impact of saline irrigation and topical corticosteroids on the postsurgical sinonasal microbiota

BACKGROUND

Topical treatments with nasal saline irrigation, topical steroid sprays, or corticosteroid rinses can improve sinonasal symptoms in chronic rhinosinusitis (CRS). However, the impact of these therapies on commensals (Corynebacterium) and on biofilm pathogens associated with CRS (Staphylococcus aureus and Pseudomonas) is not well characterized.

METHODS

Paired nasal and sinus swabs were collected endoscopically from 28 controls and 14 CRS patients with nasal polyposis (CRSwNP) who had not received systemic antibiotics or corticosteroids in the previous 8 weeks. Total DNA from swab eluents were extracted and analyzed by 16S rRNA gene-based pyrosequencing. A total of 359,077 reads were obtained and classified taxonomically. The association of use of topical therapies with sinonasal microbiota composition was assessed by factor/vector-fitting. The proportional abundances of sinonasal bacteria between topical therapy users and nonusers were further compared by 2-tailed Kolmogorov-Smirnov test among controls and among CRSwNP participants.

RESULTS

Nasal saline irrigation, with or without added budesonide, was not associated with significantly distinct sinonasal microbiota composition or significantly decreased Pseudomonas or S. aureus abundances among either controls or CRSwNP participants. Corynebacterium was slightly lower in controls that reported using saline irrigation than those who did not. No significant association was found between nasal saline irrigation and the proportional abundances of Pseudomonas, S. aureus, and Corynebacterium in CRSwNP participants. However, male CRSwNP patients were noted to have significantly higher Corynebacterium proportional abundances than their female counterparts. The use of topical steroid sprays was associated with a distinct microbiota in control subjects, characterized by higher proportional abundances of Dolosigranulum and Simonsiella and a lower proportional abundance of Campylobacter.

CONCLUSION

Nasal saline irrigation is not associated with a distinct alteration in the proportional abundance of commensal bacteria or biofilm-forming pathogens in CRSwNP patients. However, use of topical intranasal corticosteroid sprays in control subjects is associated with a distinct sinonasal microbiota.

The semen microbiome and its relationship with local immunology and viral load in HIV infection

Semen is a major vector for HIV transmission, but the semen HIV RNA viral load (VL) only correlates moderately with the blood VL. Viral shedding can be enhanced by genital infections and associated inflammation, but it can also occur in the absence of classical pathogens. Thus, we hypothesized that a dysregulated semen microbiome correlates with local HIV shedding. We analyzed semen samples from 49 men who have sex with men (MSM), including 22 HIV-uninfected and 27 HIV-infected men, at baseline and after starting antiretroviral therapy (ART) using 16S rRNA gene-based pyrosequencing and quantitative PCR. We studied the relationship of semen bacteria with HIV infection, semen cytokine levels, and semen VL by linear regression, non-metric multidimensional scaling, and goodness-of-fit test. Streptococcus, Corynebacterium, and Staphylococcus were common semen bacteria, irrespective of HIV status. While Ureaplasma was the more abundant Mollicutes in HIV-uninfected men, Mycoplasma dominated after HIV infection. HIV infection was associated with decreased semen microbiome diversity and richness, which were restored after six months of ART. In HIV-infected men, semen bacterial load correlated with seven pro-inflammatory semen cytokines, including IL-6 (p = 0.024), TNF-α (p = 0.009), and IL-1b (p = 0.002). IL-1b in particular was associated with semen VL (r² = 0.18, p = 0.02). Semen bacterial load was also directly linked to the semen HIV VL (r² = 0.15, p = 0.02). HIV infection reshapes the relationship between semen bacteria and pro-inflammatory cytokines, and both are linked to semen VL, which supports a role of the semen microbiome in HIV sexual transmission.

The classical paradigm of HIV infectivity centers on the blood HIV RNA viral load. However, while other fluid compartments such as semen and cerebrospinal fluid can have distinct viral loads from blood, the causes of localized HIV shedding are not fully understood. Since the semen viral load is an independent predictor of HIV transmission risk, it is critical to understand the local factors that trigger increased semen viral shedding in order to develop novel preventative strategies. Here, we evaluated the semen microbiome, bacterial load, and cytokine levels in 22 HIV-uninfected men who have sex with men (MSM) and in 27 HIV-infected MSM before and after initiation of antiretroviral therapy (ART). We found that HIV infection reduces semen microbiome biodiversity, which is restored with ART and immune reconstitution. We also found that semen bacterial load in untreated, HIV-infected men is associated with the levels of seven semen cytokines, relationships not seen in the uninfected controls. In particular, the cytokine IL-1b was uniquely correlated with both semen bacterial and viral load. Our findings support the interaction between semen microbiome and local immunology, and suggest that IL-1b could be a mechanism for semen microbiome to trigger semen viral shedding.

Medical therapy reduces microbiota diversity and evenness in surgically recalcitrant chronic rhinosinusitis

BACKGROUND

Chronic rhinosinusitis (CRS) is a highly prevalent and heterogeneous condition frequently treated with antibiotics and corticosteroid therapy. However, the effect of medical therapy on sinus microbiota remains unknown.

METHODS

We enrolled CRS patients (n = 6) with patent maxillary antrostomies and active mucosal inflammation, who had not received antibiotics or corticosteroids in the previous 8 weeks. A pretreatment and posttreatment maxillary sinus swab was collected, from which DNA was extracted, pyrosequenced, and analyzed using a naïve Bayesian classifier and ecological analyses.

RESULTS

Four patients showed significant improvement in endoscopic appearance. The shifts in microbiota in response to therapy were highly individualized. There was no single common microbiota profile among patients with similar clinical outcomes, but overall there was significant decrease in microbiota diversity (t(5) = 2.05, p = 0.10) and evenness (t(5) = 2.28, p = 0.07) after treatment.

CONCLUSION

Our findings strongly correlate with earlier studies that examined the impact of antibiotics on human microbiota. We observed that posttreatment, patients frequently became colonized by taxa that are less susceptible to the prescribed antibiotics. Our findings highlight the challenge in seeking generalizable diagnostic and therapeutic options in CRS, particularly regarding microbiological response and outcomes.

FungiQuant: a broad-coverage fungal quantitative real-time PCR assay

BACKGROUND

Fungal load quantification is a critical component of fungal community analyses. Limitation of current approaches for quantifying the fungal component in the human microbiome suggests the need for new broad-coverage techniques.

METHODS

We analyzed 2,085 18S rRNA gene sequences from the SILVA database for assay design. We generated and quantified plasmid standards using a qPCR-based approach. We evaluated assay coverage against 4,968 sequences and performed assay validation following the Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) guidelines.

RESULTS

We designed FungiQuant, a TaqMan® qPCR assay targeting a 351 bp region in the fungal 18S rRNA gene. Our in silico analysis showed that FungiQuant is a perfect sequence match to 90.0% of the 2,617 fungal species analyzed. We showed that FungiQuant's is 100% sensitive and its amplification efficiencies ranged from 76.3% to 114.5%, with r(2)-values of >0.99 against the 69 fungal species tested. Additionally, FungiQuant inter- and intra-run coefficients of variance ranged from <10% and <20%, respectively. We further showed that FungiQuant has a limit of quantification 25 copies and a limit of detection at 5 copies. Lastly, by comparing results from human-only background DNA with low-level fungal DNA, we showed that amplification in two or three of a FungiQuant performed in triplicate is statistically significant for true positive fungal detection.

CONCLUSIONS

FungiQuant has comprehensive coverage against diverse fungi and is a robust quantification and detection tool for delineating between true fungal detection and non-target human DNA.