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Eisenhofer R, Nesme J, Santos-Bay L, Koziol A, Sørensen SJ, Alberdi A, Aizpurua O. A comparison of short-read, HiFi long-read, and hybrid strategies for genome-resolved metagenomics. Microbiol Spectr 2024; 12:e0359023. [PMID: 38451230 PMCID: PMC10986573 DOI: 10.1128/spectrum.03590-23] [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: 10/07/2023] [Accepted: 02/11/2024] [Indexed: 03/08/2024] Open
Abstract
Shotgun metagenomics enables the reconstruction of complex microbial communities at a high level of detail. Such an approach can be conducted using both short-read and long-read sequencing data, as well as a combination of both. To assess the pros and cons of these different approaches, we used 22 fecal DNA extracts collected weekly for 11 weeks from two respective lab mice to study seven performance metrics over four combinations of sequencing depth and technology: (i) 20 Gbp of Illumina short-read data, (ii) 40 Gbp of short-read data, (iii) 20 Gbp of PacBio HiFi long-read data, and (iv) 40 Gbp of hybrid (20 Gbp of short-read +20 Gbp of long-read) data. No strategy was best for all metrics; instead, each one excelled across different metrics. The long-read approach yielded the best assembly statistics, with the highest N50 and lowest number of contigs. The 40 Gbp short-read approach yielded the highest number of refined bins. Finally, the hybrid approach yielded the longest assemblies and the highest mapping rate to the bacterial genomes. Our results suggest that while long-read sequencing significantly improves the quality of reconstructed bacterial genomes, it is more expensive and requires deeper sequencing than short-read approaches to recover a comparable amount of reconstructed genomes. The most optimal strategy is study-specific and depends on how researchers assess the trade-off between the quantity and quality of recovered genomes.IMPORTANCEMice are an important model organism for understanding the gut microbiome. When studying these gut microbiomes using DNA techniques, researchers can choose from technologies that use short or long DNA reads. In this study, we perform an extensive benchmark between short- and long-read DNA sequencing for studying mice gut microbiomes. We find that no one approach was best for all metrics and provide information that can help guide researchers in planning their experiments.
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Affiliation(s)
- Raphael Eisenhofer
- Center for Evolutionary Hologenomics, Globe Institute, University of Copenhagen, Copenhagen, Denmark
| | - Joseph Nesme
- Section of Microbiology, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Luisa Santos-Bay
- Center for Evolutionary Hologenomics, Globe Institute, University of Copenhagen, Copenhagen, Denmark
| | - Adam Koziol
- Center for Evolutionary Hologenomics, Globe Institute, University of Copenhagen, Copenhagen, Denmark
| | - Søren Johannes Sørensen
- Section of Microbiology, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Antton Alberdi
- Center for Evolutionary Hologenomics, Globe Institute, University of Copenhagen, Copenhagen, Denmark
| | - Ostaizka Aizpurua
- Center for Evolutionary Hologenomics, Globe Institute, University of Copenhagen, Copenhagen, Denmark
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Sanders AE, Arnesen H, Shepherd FK, Putri DS, Fiege JK, Pierson MJ, Roach SN, Carlsen H, Masopust D, Boysen P, Langlois RA. Comparison of mouse models of microbial experience reveals differences in microbial diversity and response to vaccination. mSphere 2024; 9:e0065423. [PMID: 38286428 PMCID: PMC10900878 DOI: 10.1128/msphere.00654-23] [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: 11/13/2023] [Accepted: 12/14/2023] [Indexed: 01/31/2024] Open
Abstract
Specific pathogen-free (SPF) laboratory mice dominate preclinical studies for immunology and vaccinology. Unfortunately, SPF mice often fail to accurately model human responses to vaccination and other immunological perturbations. Several groups have taken different approaches to introduce additional microbial experience to SPF mice to better model human immune experience. How these different models compare is unknown. Here, we directly compare three models: housing SPF mice in a microbe-rich barn-like environment (feralizing), adding wild-caught mice to the barn-like environment (fer-cohoused), or cohousing SPF mice with pet store mice in a barrier facility (pet-cohoused); the two latter representing different murine sources of microbial transmission. Pet-cohousing mice resulted in the greatest microbial exposure. Feralizing alone did not result in the transmission of any pathogens tested, while fer-cohousing resulted in the transmission of several picornaviruses. Murine astrovirus 2, the most common pathogen from pet store mice, was absent from the other two model systems. Previously, we had shown that pet-cohousing reduced the antibody response to vaccination compared with SPF mice. This was not recapitulated in either the feralized or fer-cohoused mice. These data indicate that not all dirty mouse models are equivalent in either microbial experience or immune responses to vaccination. These disparities suggest that more cross model comparisons are needed but also represent opportunities to uncover microbe combination-specific phenotypes and develop more refined experimental models. Given the breadth of microbes encountered by humans across the globe, multiple model systems may be needed to accurately recapitulate heterogenous human immune responses.IMPORTANCEAnimal models are an essential tool for evaluating clinical interventions. Unfortunately, they can often fail to accurately predict outcomes when translated into humans. This failure is due in part to a lack of natural infections experienced by most laboratory animals. To improve the mouse model, we and others have exposed laboratory mice to microbes they would experience in the wild. Although these models have been growing in popularity, these different models have not been specifically compared. Here, we directly compare how three different models of microbial experience impact the immune response to influenza vaccination. We find that these models are not the same and that the degree of microbial exposure affects the magnitude of the response to vaccination. These results provide an opportunity for the field to continue comparing and contrasting these systems to determine which models best recapitulate different aspects of the human condition.
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Affiliation(s)
- Autumn E Sanders
- Department of Microbiology and Immunology, University of Minnesota, Minneapolis, Minnesota, USA
| | - Henriette Arnesen
- Faculty of Veterinary Medicine, Norwegian University of Life Sciences, Ås, Norway
| | - Frances K Shepherd
- Department of Microbiology and Immunology, University of Minnesota, Minneapolis, Minnesota, USA
| | - Dira S Putri
- Department of Microbiology and Immunology, University of Minnesota, Minneapolis, Minnesota, USA
| | - Jessica K Fiege
- Department of Microbiology and Immunology, University of Minnesota, Minneapolis, Minnesota, USA
- Center for Immunology, University of Minnesota, Minneapolis, Minnesota, USA
| | - Mark J Pierson
- Center for Immunology, University of Minnesota, Minneapolis, Minnesota, USA
| | - Shanley N Roach
- Department of Microbiology and Immunology, University of Minnesota, Minneapolis, Minnesota, USA
| | - Harald Carlsen
- Faculty of Chemistry, Biotechnology and Food Science, Norwegian University of Life Sciences, Ås, Norway
| | - David Masopust
- Department of Microbiology and Immunology, University of Minnesota, Minneapolis, Minnesota, USA
- Center for Immunology, University of Minnesota, Minneapolis, Minnesota, USA
| | - Preben Boysen
- Faculty of Veterinary Medicine, Norwegian University of Life Sciences, Ås, Norway
| | - Ryan A Langlois
- Department of Microbiology and Immunology, University of Minnesota, Minneapolis, Minnesota, USA
- Center for Immunology, University of Minnesota, Minneapolis, Minnesota, USA
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Li Y, Molleston JM, Kim AH, Ingle H, Aggarwal S, Nolan LS, Hassan AO, Foster L, Diamond MS, Baldridge MT. Sequential early-life viral infections modulate the microbiota and adaptive immune responses to systemic and mucosal vaccination. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.31.555772. [PMID: 37693434 PMCID: PMC10491206 DOI: 10.1101/2023.08.31.555772] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/12/2023]
Abstract
Increasing evidence points to the microbial exposome as a critical factor in maturing and shaping the host immune system, thereby influencing responses to immune challenges such as infections or vaccines. To investigate the effect of early-life viral exposures on immune development and vaccine responses, we inoculated mice with six distinct viral pathogens in sequence beginning in the neonatal period, and then evaluated their immune signatures before and after intramuscular or intranasal vaccination against SARS-CoV-2. Sequential viral infection drove profound changes in all aspects of the immune system, including increasing circulating leukocytes, altering innate and adaptive immune cell lineages in tissues, and markedly influencing serum cytokine and total antibody levels. Beyond these immune responses changes, these exposures also modulated the composition of the endogenous intestinal microbiota. Although sequentially-infected mice exhibited increased systemic immune activation and T cell responses after intramuscular and intranasal SARS-CoV-2 immunization, we observed decreased vaccine-induced antibody responses in these animals. These results suggest that early-life viral exposures are sufficient to diminish antibody responses to vaccination in mice, and highlight their potential importance of considering prior microbial exposures when investigating vaccine responses.
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