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Zhang S, Han Y, Schofield W, Nicosia M, Karell PE, Newhall KP, Zhou JY, Musich RJ, Pan S, Valujskikh A, Sangwan N, Dwidar M, Lu Q, Stappenbeck TS. Select symbionts drive high IgA levels in the mouse intestine. Cell Host Microbe 2023; 31:1620-1638.e7. [PMID: 37776865 DOI: 10.1016/j.chom.2023.09.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 07/14/2023] [Accepted: 09/01/2023] [Indexed: 10/02/2023]
Abstract
Immunoglobulin A (IgA) is an important factor in maintaining homeostasis at mucosal surfaces, yet luminal IgA levels vary widely. Total IgA levels are thought to be driven by individual immune responses to specific microbes. Here, we found that the prebiotic, pectin oligosaccharide (pec-oligo), induced high IgA levels in the small intestine in a T cell-dependent manner. Surprisingly, this IgA-high phenotype was retained after cessation of pec-oligo treatment, and microbiome transmission either horizontally or vertically was sufficient to retain high IgA levels in the absence of pec-oligo. Interestingly, the bacterial taxa enriched in the overall pec-oligo bacterial community differed from IgA-coated microbes in this same community. Rather, a group of ethanol-resistant microbes, highly enriched for Lachnospiraceae bacterium A2, drove the IgA-high phenotype. These findings support a model of intestinal adaptive immunity in which a limited number of microbes can promote durable changes in IgA directed to many symbionts.
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Affiliation(s)
- Shanshan Zhang
- Department of Inflammation and Immunity, Learner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA; Department of Gastroenterology, Qilu Hospital, Shandong University, Jinan 250000, P.R. China; College of Food Science and Technology, Huazhong Agricultural University, Wuhan 430070, P.R. China
| | - Yi Han
- Department of Inflammation and Immunity, Learner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA
| | | | - Michael Nicosia
- Department of Inflammation and Immunity, Learner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA
| | - Paul E Karell
- Department of Inflammation and Immunity, Learner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA
| | - Kevin P Newhall
- Department of Inflammation and Immunity, Learner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA
| | - Julie Y Zhou
- Department of Inflammation and Immunity, Learner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA
| | - Ryan J Musich
- Department of Inflammation and Immunity, Learner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA
| | - Siyi Pan
- College of Food Science and Technology, Huazhong Agricultural University, Wuhan 430070, P.R. China
| | - Anna Valujskikh
- Department of Inflammation and Immunity, Learner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA
| | - Naseer Sangwan
- Department of Cardiovascular and Metabolic Sciences, Learner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA; Center for Microbiome & Human Health, Cleveland Clinic, Cleveland, OH 44195, USA
| | - Mohammed Dwidar
- Department of Cardiovascular and Metabolic Sciences, Learner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA; Center for Microbiome & Human Health, Cleveland Clinic, Cleveland, OH 44195, USA
| | - Qiuhe Lu
- Department of Inflammation and Immunity, Learner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA.
| | - Thaddeus S Stappenbeck
- Department of Inflammation and Immunity, Learner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA.
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Almas S, Carpenter RE, Rowan C, Tamrakar VK, Bishop J, Sharma R. Advantage of precision metagenomics for urinary tract infection diagnostics. Front Cell Infect Microbiol 2023; 13:1221289. [PMID: 37469596 PMCID: PMC10352793 DOI: 10.3389/fcimb.2023.1221289] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Accepted: 06/15/2023] [Indexed: 07/21/2023] Open
Abstract
Background Urinary tract infections (UTIs) remain a diagnostic challenge and often promote antibiotic overuse. Despite urine culture being the gold standard for UTI diagnosis, some uropathogens may lead to false-negative or inconclusive results. Although PCR testing is fast and highly sensitive, its diagnostic yield is limited to targeted microorganisms. Metagenomic next-generation sequencing (mNGS) is a hypothesis-free approach with potential of deciphering the urobiome. However, clinically relevant information is often buried in the enormous amount of sequencing data. Methods Precision metagenomics (PM) is a hybridization capture-based method with potential of enhanced discovery power and better diagnostic yield without diluting clinically relevant information. We collected 47 urine samples of clinically suspected UTI and in parallel tested each sample by microbial culture, PCR, and PM; then, we comparatively analyzed the results. Next, we phenotypically classified the cumulative microbial population using the Explify® data analysis platform for potential pathogenicity. Results Results revealed 100% positive predictive agreement (PPA) with culture results, which identified only 13 different microorganisms, compared to 19 and 62 organisms identified by PCR and PM, respectively. All identified organisms were classified into phenotypic groups (0-3) with increasing pathogenic potential and clinical relevance. This PM can simultaneously quantify and phenotypically classify the organisms readily through bioinformatic platforms like Explify®, essentially providing dissected and quantitative results for timely and accurate empiric UTI treatment. Conclusion PM offers potential for building effective diagnostic models beyond usual care testing in complex UTI diseases. Future studies should assess the impact of PM-guided UTI management on clinical outcomes.
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Affiliation(s)
- Sadia Almas
- Department of Research, Advanta Genetics, Tyler, TX, United States
| | - Rob E. Carpenter
- Department of Research, Advanta Genetics, Tyler, TX, United States
- Soules College of Business, University of Texas at Tyler, Tyler, TX, United States
| | - Chase Rowan
- Department of Research, Advanta Genetics, Tyler, TX, United States
| | - Vaibhav K. Tamrakar
- Divison of Communicable Diseases, ICMR-National Institute of Research in Tribal Health, Jabalpur, India
- Department of Research, RetroBioTech LLC, Coppell, TX, United States
| | - Joseph Bishop
- Department of Research, Advanta Genetics, Tyler, TX, United States
| | - Rahul Sharma
- Department of Research, Advanta Genetics, Tyler, TX, United States
- Department of Research, RetroBioTech LLC, Coppell, TX, United States
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Beaudry MS, Wang J, Kieran TJ, Thomas J, Bayona-Vásquez NJ, Gao B, Devault A, Brunelle B, Lu K, Wang JS, Rhodes OE, Glenn TC. Improved Microbial Community Characterization of 16S rRNA via Metagenome Hybridization Capture Enrichment. Front Microbiol 2021; 12:644662. [PMID: 33986735 PMCID: PMC8110821 DOI: 10.3389/fmicb.2021.644662] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Accepted: 03/22/2021] [Indexed: 01/04/2023] Open
Abstract
Environmental microbial diversity is often investigated from a molecular perspective using 16S ribosomal RNA (rRNA) gene amplicons and shotgun metagenomics. While amplicon methods are fast, low-cost, and have curated reference databases, they can suffer from amplification bias and are limited in genomic scope. In contrast, shotgun metagenomic methods sample more genomic regions with fewer sequence acquisition biases, but are much more expensive (even with moderate sequencing depth) and computationally challenging. Here, we develop a set of 16S rRNA sequence capture baits that offer a potential middle ground with the advantages from both approaches for investigating microbial communities. These baits cover the diversity of all 16S rRNA sequences available in the Greengenes (v. 13.5) database, with no sequence having <78% sequence identity to at least one bait for all segments of 16S. The use of our baits provide comparable results to 16S amplicon libraries and shotgun metagenomic libraries when assigning taxonomic units from 16S sequences within the metagenomic reads. We demonstrate that 16S rRNA capture baits can be used on a range of microbial samples (i.e., mock communities and rodent fecal samples) to increase the proportion of 16S rRNA sequences (average > 400-fold) and decrease analysis time to obtain consistent community assessments. Furthermore, our study reveals that bioinformatic methods used to analyze sequencing data may have a greater influence on estimates of community composition than library preparation method used, likely due in part to the extent and curation of the reference databases considered. Thus, enriching existing aliquots of shotgun metagenomic libraries and obtaining modest numbers of reads from them offers an efficient orthogonal method for assessment of bacterial community composition.
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Affiliation(s)
- Megan S. Beaudry
- Department of Environmental Health Science, University of Georgia, Athens, GA, United States
| | - Jincheng Wang
- Department of Environmental Health Science, University of Georgia, Athens, GA, United States
- Interdisciplinary Toxicology Program, University of Georgia, Athens, GA, United States
| | - Troy J. Kieran
- Department of Environmental Health Science, University of Georgia, Athens, GA, United States
| | - Jesse Thomas
- Department of Environmental Health Science, University of Georgia, Athens, GA, United States
- Savannah River Ecology Laboratory, University of Georgia, Aiken, SC, United States
| | - Natalia J. Bayona-Vásquez
- Department of Environmental Health Science, University of Georgia, Athens, GA, United States
- Institute of Bioinformatics, University of Georgia, Athens, GA, United States
| | - Bei Gao
- Department of Environmental Health Science, University of Georgia, Athens, GA, United States
| | | | | | - Kun Lu
- Department of Environmental Health Science, University of Georgia, Athens, GA, United States
| | - Jia-Sheng Wang
- Department of Environmental Health Science, University of Georgia, Athens, GA, United States
- Interdisciplinary Toxicology Program, University of Georgia, Athens, GA, United States
| | - Olin E. Rhodes
- Savannah River Ecology Laboratory, University of Georgia, Aiken, SC, United States
| | - Travis C. Glenn
- Department of Environmental Health Science, University of Georgia, Athens, GA, United States
- Interdisciplinary Toxicology Program, University of Georgia, Athens, GA, United States
- Institute of Bioinformatics, University of Georgia, Athens, GA, United States
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Andermann T, Torres Jiménez MF, Matos-Maraví P, Batista R, Blanco-Pastor JL, Gustafsson ALS, Kistler L, Liberal IM, Oxelman B, Bacon CD, Antonelli A. A Guide to Carrying Out a Phylogenomic Target Sequence Capture Project. Front Genet 2020; 10:1407. [PMID: 32153629 PMCID: PMC7047930 DOI: 10.3389/fgene.2019.01407] [Citation(s) in RCA: 44] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2019] [Accepted: 12/24/2019] [Indexed: 12/17/2022] Open
Abstract
High-throughput DNA sequencing techniques enable time- and cost-effective sequencing of large portions of the genome. Instead of sequencing and annotating whole genomes, many phylogenetic studies focus sequencing effort on large sets of pre-selected loci, which further reduces costs and bioinformatic challenges while increasing coverage. One common approach that enriches loci before sequencing is often referred to as target sequence capture. This technique has been shown to be applicable to phylogenetic studies of greatly varying evolutionary depth. Moreover, it has proven to produce powerful, large multi-locus DNA sequence datasets suitable for phylogenetic analyses. However, target capture requires careful considerations, which may greatly affect the success of experiments. Here we provide a simple flowchart for designing phylogenomic target capture experiments. We discuss necessary decisions from the identification of target loci to the final bioinformatic processing of sequence data. We outline challenges and solutions related to the taxonomic scope, sample quality, and available genomic resources of target capture projects. We hope this review will serve as a useful roadmap for designing and carrying out successful phylogenetic target capture studies.
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Affiliation(s)
- Tobias Andermann
- Department of Biological and Environmental Sciences, University of Gothenburg, Gothenburg, Sweden
- Gothenburg Global Biodiversity Centre, Gothenburg, Sweden
| | - Maria Fernanda Torres Jiménez
- Department of Biological and Environmental Sciences, University of Gothenburg, Gothenburg, Sweden
- Gothenburg Global Biodiversity Centre, Gothenburg, Sweden
| | - Pável Matos-Maraví
- Department of Biological and Environmental Sciences, University of Gothenburg, Gothenburg, Sweden
- Gothenburg Global Biodiversity Centre, Gothenburg, Sweden
- Institute of Entomology, Biology Centre of the Czech Academy of Sciences, České Budějovice, Czechia
| | - Romina Batista
- Gothenburg Global Biodiversity Centre, Gothenburg, Sweden
- Programa de Pós-Graduação em Genética, Conservação e Biologia Evolutiva, PPG GCBEv–Instituto Nacional de Pesquisas da Amazônia—INPA Campus II, Manaus, Brazil
- Coordenação de Zoologia, Museu Paraense Emílio Goeldi, Belém, Brazil
| | - José L. Blanco-Pastor
- Department of Biological and Environmental Sciences, University of Gothenburg, Gothenburg, Sweden
- INRAE, Centre Nouvelle-Aquitaine-Poitiers, Lusignan, France
| | | | - Logan Kistler
- Department of Anthropology, National Museum of Natural History, Smithsonian Institution, Washington, DC, United States
| | - Isabel M. Liberal
- Department of Biological and Environmental Sciences, University of Gothenburg, Gothenburg, Sweden
| | - Bengt Oxelman
- Department of Biological and Environmental Sciences, University of Gothenburg, Gothenburg, Sweden
- Gothenburg Global Biodiversity Centre, Gothenburg, Sweden
| | - Christine D. Bacon
- Department of Biological and Environmental Sciences, University of Gothenburg, Gothenburg, Sweden
- Gothenburg Global Biodiversity Centre, Gothenburg, Sweden
| | - Alexandre Antonelli
- Department of Biological and Environmental Sciences, University of Gothenburg, Gothenburg, Sweden
- Gothenburg Global Biodiversity Centre, Gothenburg, Sweden
- Royal Botanic Gardens, Kew, Richmond-Surrey, United Kingdom
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