Airway microbiome signature accurately discriminates Mycobacterium tuberculosis infection status

Description

We screened for M.tb infection during the follow-up phase of a longitudinal HIV-Lung Microbiome cohort of 200 individuals recruited from two large independent cohorts in rural Uganda.

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To investigate the relationship between airway microbiome composition and M.tb-specific IFNgamma immune responses in a rural Ugandan cohort, we performed 16SrRNA amplicon sequencing on induced sputum samples to determine the airway microbiome profile as our primary endpoint. Briefly, we extracted genomic DNA and PCR-amplified V3-V4 hypervariable region of the 16S rRNA gene using the 341F-785R primer set. Amplicon sequencing was performed using the MiSeq platform following standard protocol. Raw sequence reads were processed using LotuS (1.62)31. To remove potential human contamination, we mapped raw reads to the human genome and discarded reads upon 95% identity. Poisson binomial model-based read filtering was applied 32 and Operational taxonomic unit (OTU) clustering using UPARSE33 was based on sequence similarity of 97%, while SILVA version 138 34 was incrementally used as a database for a taxonomic assignment using a Lambda taxonomic similarity search. The taxonomic classification (genus thresholded at 95% identity) was parsed using a custom Perl script, such that unassigned taxonomic levels were assigned to the last known taxonomic level and sequentially numbered. All samples were processed together and standardized using the R package rarefaction tool kit (rtk 0.93.1) with default settings 35, ensuring a consistent approach to analysis.

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