Single-Molecule Approach to 16S rRNA for Vaginal Microbiome Signatures in Response to Metronidazole Treatment

Qin, Hanyu; Jiao, Jiao; Disi, A; Hua, Mingxi; Han, Kai; Du, Haonan; Wang, Zhen; Li, Jiarui; Zhang, Dai; Xiao, Bingbing; Chen, Chen

doi:10.1128/spectrum.01706-22

Cited by 3 publications

(2 citation statements)

References 59 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…With decreasing error rates and costs associated with long-read sequencing technologies, full-length 16S rRNA gene sequencing can reliably resolve species and even strains (70). Full-length 16S rRNA gene sequencing surveys have been instrumental in identifying new 16S rRNA gene variants, e.g., those in the vaginal microbiome (71), bacterial transmission, e.g., motherto-infant transmission of oral bacteria (72), and temporal dynamics, e.g., gut microbiota post-antibiotic treatment (73). Conducting such full-length 16S rRNA gene sequence surveys of the urobiome have only recently been explored (74).…”

Section: Peribacillus Frigoritolerans Bacillus Simplexmentioning

confidence: 99%

Cataloging variation in 16S rRNA gene sequences of female urobiome bacteria

Baddoo,

Ene,

Merchant

et al. 2024

Front. Urol.

View full text Add to dashboard Cite

Continued efforts to isolate and sequence bacteria of the urinary tract has increased representation of these species in publicly available databases. This in turn has improved taxonomic classifications of the urinary microbiome (urobiome). Short-read sequencing targeting a variable region(s) of the 16S rRNA gene sequence has been fundamental in characterizing the urobiomes of males and females with and without lower urinary tract symptoms, as well as cancers of the urinary tract. Here, we have compiled a data set of full-length or near-full-length 16S rRNA gene sequences for the urobiome. To generate this data set, we first plated 203 isolates from the bladder on differential media and sequenced their full-length 16S rRNA gene sequence. We combined this data set with publicly available genomes from primarily the female urinary tract. The final data set includes 399 sequences representative of 160 different species from 73 genera. We assessed the ability of publicly available databases to correctly predict these sequences based on the V1-V3, V4, and V4-V6 variable regions. As expected, species designations based upon these variable regions is often not possible or incorrect. We also detected incorrect genus-level classifications. This data set can be used to supplement existing databases, by increasing urobiome species variation, and thus improve future studies characterizing urobiomes.

show abstract

Section: Peribacillus Frigoritolerans Bacillus Simplexmentioning

confidence: 99%

Cataloging variation in 16S rRNA gene sequences of female urobiome bacteria

Baddoo,

Ene,

Merchant

et al. 2024

Front. Urol.

View full text Add to dashboard Cite

show abstract

“…This establishes an acidic vaginal environment and forms a physiological barrier on the vaginal surface [ 10 , 11 ] that can restrict, coordinate, and balance with the host and environment to form a vaginal microecological environment and maintain normal vaginal microecological homeostasis [ 12 – 14 ]. The disruption of this balance may lead to bacterial vaginosis [ 15 ]. Several studies have highlighted that continuous disturbances in vaginal microecology are significant contributing factors to gynecological cancer [ 16 , 17 ].…”

Section: Introductionmentioning

confidence: 99%

Vaginal microbial profile of cervical cancer patients receiving chemoradiotherapy: the potential involvement of Lactobacillus iners in recurrence

Wang,

Yan

et al. 2024

J Transl Med

View full text Add to dashboard Cite

The vaginal microbiome is an immune defense against reproductive diseases and can serve as an important biomarker for cervical cancer. However, the intrinsic relationship between the recurrence and the vaginal microbiome in patients with cervical cancer before and after concurrent chemoradiotherapy is poorly understood. Here, we analyzed 125 vaginal microbial profiles from a patient cohort of stage IB–IVB cervical cancer using 16S metagenomic sequencing and deciphered the microbial composition and functional characteristics of the recurrent and non-recurrent both before and after chemoradiotherapy. We demonstrated that the abundance of beneficial bacteria and stability of the microbial community in the vagina decreased in the recurrence group, implying the unique characteristics of the vaginal microbiome for recurrent cervical cancer. Moreover, using machine learning, we identified Lactobacillus iners as the most important biomarker, combined with age and other biomarkers (such as Ndongobacter massiliensis, Corynebacterium pyruviciproducens ATCC BAA-1742, and Prevotella buccalis), and could predict cancer recurrence phenotype before chemoradiotherapy. This study prospectively employed rigorous bioinformatics analysis and highlights the critical role of vaginal microbiota in post-treatment cervical cancer recurrence, identifying promising biomarkers with prognostic significance in the context of concurrent chemoradiotherapy for cervical cancer. The role of L. iners in determining chemoradiation resistance in cervical cancer warrants further detailed investigation. Our results expand our understanding of cervical cancer recurrence and help develop better strategies for prognosis prediction and personalized therapy.

show abstract

A quantitative approach to measure and predict microbiome response to antibiotics

Tu,

Ren,

Tanes

et al. 2024

mSphere

View full text Add to dashboard Cite

Although antibiotics induce sizable perturbations in the human microbiome, we lack a systematic and quantitative method to measure and predict the microbiome's response to specific antibiotics. Here, we introduce such a method, which takes the form of a microbiome response index (MiRIx) for each antibiotic. Antibiotic-specific MiRIx values quantify the overall susceptibility of the microbiota to an antibiotic, based on databases of bacterial phenotypes and published data on intrinsic antibiotic susceptibility. We applied our approach to five published microbiome studies that carried out antibiotic interventions with vancomycin, metronidazole, ciprofloxacin, amoxicillin, and doxycycline. We show how MiRIx can be used in conjunction with existing microbiome analytical approaches to gain a deeper understanding of the microbiome response to antibiotics. Finally, we generate antibiotic response predictions for the oral, skin, and gut microbiome in healthy humans. Our approach is implemented as open-source software and is readily applied to microbiome data sets generated by 16S rRNA marker gene sequencing or shotgun metagenomics. IMPORTANCE Antibiotics are potent influencers of the human microbiome and can be a source for enduring dysbiosis and antibiotic resistance in healthcare. Existing microbiome data analysis methods can quantify perturbations of bacterial communities but cannot evaluate whether the differences are aligned with the expected activity of a specific antibiotic. Here, we present a novel method to quantify and predict antibiotic-specific microbiome changes, implemented in a ready-to-use software package. This has the potential to be a critical tool to broaden our understanding of the relationship between the microbiome and antibiotics.

show abstract

Single-Molecule Approach to 16S rRNA for Vaginal Microbiome Signatures in Response to Metronidazole Treatment

Abstract: Bacterial vaginosis (BV) is a common infectious disease of the reproductive tract. Metronidazole treatment, as the first line of treatment, frequently fails at recovery of the microbiome.

Cited by 3 publications

References 59 publications

Cataloging variation in 16S rRNA gene sequences of female urobiome bacteria

Cataloging variation in 16S rRNA gene sequences of female urobiome bacteria

Vaginal microbial profile of cervical cancer patients receiving chemoradiotherapy: the potential involvement of Lactobacillus iners in recurrence

A quantitative approach to measure and predict microbiome response to antibiotics

Contact Info

Product

Resources

About