@article {206, title = {Rapid Reduction of Species in the Gut Microbiome of Preschool Children after Oral Azithromycin: A Randomized Controlled Trial.}, journal = {Am J Trop Med Hyg}, volume = {103}, year = {2020}, month = {2020 09}, pages = {1266-1269}, abstract = {

has emerged as a potential important cause of childhood morbidity in sub-Saharan Africa. Biannual mass azithromycin distribution has previously been shown to reduce all-cause child mortality in sub-Saharan Africa. We conducted a randomized controlled trial in Burkina Faso in which children were randomized in a 1:1 fashion to a 5-day course of azithromycin or placebo to investigate the effect of oral antibiotics on the gut microbiome. We evaluated the changes in the gut microbiome of preschool children treated with azithromycin using metagenomic DNA sequencing. We found that three species were reduced with azithromycin treatment compared with placebo. These results were consistent with other studies that have shown decreases in species after azithromycin treatment, generating the hypothesis that a decrease in may contribute to observations of reduction in mortality following azithromycin distribution.

}, keywords = {Anti-Bacterial Agents, Azithromycin, Burkina Faso, Campylobacter, Campylobacter Infections, Child Mortality, Child, Preschool, Gastrointestinal Microbiome, Humans, Infant, Metagenomics, Sequence Analysis, DNA}, issn = {1476-1645}, doi = {10.4269/ajtmh.19-0940}, author = {Hinterwirth, Armin and Sie, Ali and Coulibaly, Boubacar and Ouermi, Lucienne and Dah, Clarisse and Tapsoba, Charlemagne and Zhong, Lina and Chen, Cindi and Lietman, Thomas M and Keenan, Jeremy D and Doan, Thuy and Oldenburg, Catherine E} } @article {151, title = {High-throughput sequencing of pooled samples to determine community-level microbiome diversity.}, journal = {Ann Epidemiol}, volume = {39}, year = {2019}, month = {2019 11}, pages = {63-68}, abstract = {

PURPOSE: Community-level interventions in cluster randomized controlled trials may alter the gut microbiome of individuals. The current method of estimating community diversities uses microbiome data obtained from multiple individual{\textquoteright}s specimens. Here we propose randomly pooling a number of microbiome samples from the same community into one sample before sequencing to estimate community-level microbiome diversity.

METHODS: We design and analyze an experiment to compare community microbiome diversity (gamma-diversity) estimates derived from 16S rRNA gene sequencing of 1) individually sequenced specimens vs. 2) pooled specimens collected from a community. Pool sizes of 10, 20, and 40 are considered. We then compare the gamma-estimates using Pearson{\textquoteright}s correlation as well as using Bland and Altman agreement analysis for three established diversity indices including richness, Simpson{\textquoteright}s and Shannon{\textquoteright}s.

RESULTS: The gamma-diversity estimates are highly correlated, with most being statistically significant. All correlations between all three diversity estimates are significant in the 10-pooled data. Pools comprising 40 specimens are closest to the line of agreement, but all pooled samples and individual samples fall within the 95\% limits of agreement.

CONCLUSIONS: Pooling microbiome samples before DNA amplification and metagenomics sequencing to estimate community-level diversity is a viable measure to consider in population-level association research studies.

}, keywords = {Administration, Oral, Anti-Bacterial Agents, Azithromycin, Bacteria, Biodiversity, Child, Preschool, Female, Gastrointestinal Microbiome, Gastrointestinal Tract, High-Throughput Nucleotide Sequencing, Humans, Infant, Infant, Newborn, Male, Metagenomics, Microbiota, Niger, Placebos, RNA, Ribosomal, 16S, Sequence Analysis, DNA}, issn = {1873-2585}, doi = {10.1016/j.annepidem.2019.09.002}, author = {Ray, Kathryn J and Cotter, Sun Y and Arzika, Ahmed M and Kim, Jessica and Boubacar, Nameywa and Zhou, Zhaoxia and Zhong, Lina and Porco, Travis C and Keenan, Jeremy D and Lietman, Thomas M and Doan, Thuy} } @article {126, title = {Unbiased Pathogen Detection and Host Gene Profiling for Conjunctivitis.}, journal = {Ophthalmology}, volume = {126}, year = {2019}, month = {2019 08}, pages = {1090-1094}, abstract = {

PURPOSE: The etiology of conjunctivitis is often misdiagnosed. An ideal diagnostic test would identify all possible infectious causes. In this study, we apply unbiased metagenomic RNA deep sequencing (MDS) to identify pathogens causing conjunctivitis.

DESIGN: Molecular study of prospectively collected conjunctival swabs from patients with presumed infectious conjunctivitis.

PARTICIPANTS: Patients with presumed acute infectious conjunctivitis.

METHODS: Conjunctival swabs were collected from patients presenting with acute conjunctivitis. Swabs were processed for MDS. Pathogens were identified using a rapid computational pipeline to analyze the nonhost sequences obtained from MDS. Differential gene expression analysis was performed to evaluate for host transcriptome signatures for infectious types. Clinical samples were deidentified, and laboratory personnel handling the samples and interpreting the data were masked.

MAIN OUTCOME MEASURES: Pathogens and differential transcripts identified by MDS.

RESULTS: Metagenomic RNA deep sequencing detected pathogens in 86\% (12/14) of the patients tested. Swabs from 10 of 14 patients were positive for human adenovirus (HAdV) while swabs from 2 of 14 patients were positive for Vittaforma corneae (a parasitic fungal species of the microsporidia group). Samples positive for HAdV by RNA-seq were independently verified in a CLIA-certified laboratory. Pathogen-directed polymerase chain reaction confirmed the presence of V.\ corneae genome in the samples positive by RNA-seq. Local host transcriptome analysis identified 12 differentially expressed genes that provided distinct expression signatures for patients infected with HAdV compared with V.\ corneae.

CONCLUSIONS: Metagenomic RNA deep sequencing can reliably detect and quantify common and rare pathogens causing conjunctivitis, and identify strains. The unbiased nature of metagenomic RNA deep sequencing allowed an expanded scope of pathogen detection, including fungal species not commonly associated with acute conjunctivitis. In addition, the identification of infection type-specific local host transcriptome signatures may allow for pathogen detection even when the pathogen load is too low for direct identification.

}, keywords = {Adult, Aged, Conjunctivitis, DNA, Bacterial, DNA, Fungal, DNA, Viral, Female, High-Throughput Nucleotide Sequencing, Humans, Male, Metagenomics, Middle Aged, Young Adult}, issn = {1549-4713}, doi = {10.1016/j.ophtha.2019.03.039}, author = {Lalitha, Prajna and Seitzman, Gerami D and Kotecha, Ritesh and Hinterwirth, Armin and Chen, Cindi and Zhong, Lina and Cummings, Susie and Lebas, Elodie and Sahoo, Malaya K and Pinsky, Benjamin A and Lietman, Thomas M and Doan, Thuy} } @article {241, title = {Metagenomic DNA Sequencing for the Diagnosis of Intraocular Infections.}, journal = {Ophthalmology}, volume = {124}, year = {2017}, month = {2017 08}, pages = {1247-1248}, keywords = {Cytomegalovirus, Cytomegalovirus Infections, DNA, Protozoan, DNA, Viral, Eye Infections, Parasitic, Eye Infections, Viral, Herpes Simplex, Herpes Zoster Ophthalmicus, Herpesvirus 3, Human, Humans, Metagenomics, Polymerase Chain Reaction, Sensitivity and Specificity, Sequence Analysis, DNA, Simplexvirus, Toxoplasma, Toxoplasmosis, Ocular, Uveitis, Vitreous Body}, issn = {1549-4713}, doi = {10.1016/j.ophtha.2017.03.045}, author = {Doan, Thuy and Acharya, Nisha R and Pinsky, Benjamin A and Sahoo, Malaya K and Chow, Eric D and Banaei, Niaz and Budvytiene, Indre and Cevallos, Vicky and Zhong, Lina and Zhou, Zhaoxia and Lietman, Thomas M and DeRisi, Joseph L} }