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Abdill RJ, Graham SP, Rubinetti V, Ahmadian M, Hicks P, Chetty A, McDonald D, Ferretti P, Gibbons E, Rossi M, Krishnan A, Albert FW, Greene CS, Davis S, Blekhman R. Integration of 168,000 samples reveals global patterns of the human gut microbiome. Cell 2025; 188:1100-1118.e17. [PMID: 39848248 PMCID: PMC11848717 DOI: 10.1016/j.cell.2024.12.017] [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: 10/02/2023] [Revised: 09/09/2024] [Accepted: 12/13/2024] [Indexed: 01/25/2025]
Abstract
The factors shaping human microbiome variation are a major focus of biomedical research. While other fields have used large sequencing compendia to extract insights requiring otherwise impractical sample sizes, the microbiome field has lacked a comparably sized resource for the 16S rRNA gene amplicon sequencing commonly used to quantify microbiome composition. To address this gap, we processed 168,464 publicly available human gut microbiome samples with a uniform pipeline. We use this compendium to evaluate geographic and technical effects on microbiome variation. We find that regions such as Central and Southern Asia differ significantly from the more thoroughly characterized microbiomes of Europe and Northern America and that composition alone can be used to predict a sample's region of origin. We also find strong associations between microbiome variation and technical factors such as primers and DNA extraction. We anticipate this growing work, the Human Microbiome Compendium, will enable advanced applied and methodological research.
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Affiliation(s)
- Richard J Abdill
- Section of Genetic Medicine, Department of Medicine, University of Chicago, Chicago, IL, USA
| | - Samantha P Graham
- Department of Genetics, Cell Biology, and Development, University of Minnesota, Minneapolis, MN, USA
| | - Vincent Rubinetti
- Department of Biomedical Informatics, University of Colorado School of Medicine, Aurora, CO, USA; Center for Health Artificial Intelligence (CHAI), University of Colorado School of Medicine, Aurora, CO, USA
| | - Mansooreh Ahmadian
- Department of Biostatistics and Informatics, University of Colorado Anschutz Medical Campus, School of Public Health, Aurora, CO, USA
| | - Parker Hicks
- Department of Biomedical Informatics, University of Colorado School of Medicine, Aurora, CO, USA
| | - Ashwin Chetty
- Section of Genetic Medicine, Department of Medicine, University of Chicago, Chicago, IL, USA
| | - Daniel McDonald
- Department of Pediatrics, School of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Pamela Ferretti
- Section of Genetic Medicine, Department of Medicine, University of Chicago, Chicago, IL, USA
| | - Elizabeth Gibbons
- Section of Genetic Medicine, Department of Medicine, University of Chicago, Chicago, IL, USA
| | - Marco Rossi
- Section of Genetic Medicine, Department of Medicine, University of Chicago, Chicago, IL, USA
| | - Arjun Krishnan
- Department of Biomedical Informatics, University of Colorado School of Medicine, Aurora, CO, USA; Department of Biostatistics and Informatics, University of Colorado Anschutz Medical Campus, School of Public Health, Aurora, CO, USA
| | - Frank W Albert
- Department of Genetics, Cell Biology, and Development, University of Minnesota, Minneapolis, MN, USA
| | - Casey S Greene
- Department of Biomedical Informatics, University of Colorado School of Medicine, Aurora, CO, USA; Center for Health Artificial Intelligence (CHAI), University of Colorado School of Medicine, Aurora, CO, USA
| | - Sean Davis
- Department of Biomedical Informatics, University of Colorado School of Medicine, Aurora, CO, USA; Center for Health Artificial Intelligence (CHAI), University of Colorado School of Medicine, Aurora, CO, USA
| | - Ran Blekhman
- Section of Genetic Medicine, Department of Medicine, University of Chicago, Chicago, IL, USA.
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Cervoni M, Sposato D, Ferri G, Bähre H, Leoni L, Rampioni G, Visca P, Recchiuti A, Imperi F. The diadenosine tetraphosphate hydrolase ApaH contributes to Pseudomonas aeruginosa pathogenicity. PLoS Pathog 2024; 20:e1012486. [PMID: 39159286 PMCID: PMC11361744 DOI: 10.1371/journal.ppat.1012486] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2024] [Revised: 08/29/2024] [Accepted: 08/07/2024] [Indexed: 08/21/2024] Open
Abstract
The opportunistic bacterial pathogen Pseudomonas aeruginosa causes a wide range of infections that are difficult to treat, largely because of the spread of antibiotic-resistant isolates. Antivirulence therapy, í.e. the use of drugs that inhibit the expression or activity of virulence factors, is currently considered an attractive strategy to reduce P. aeruginosa pathogenicity and complement antibiotic treatments. Because of the multifactorial nature of P. aeruginosa virulence and the broad arsenal of virulence factors this bacterium can produce, the regulatory networks that control the expression of multiple virulence traits have been extensively explored as potential targets for antivirulence drug development. The intracellular signaling molecule diadenosine tetraphosphate (Ap4A) has been reported to control stress resistance and virulence-related traits in some bacteria, but its role has not been investigated in P. aeruginosa so far. To fill this gap, we generated a mutant of the reference strain P. aeruginosa PAO1 that lacks the Ap4A-hydrolysing enzyme ApaH and, consequently, accumulates high intracellular levels of Ap4A. Phenotypic and transcriptomic analyses revealed that the lack of ApaH causes a drastic reduction in the expression of several virulence factors, including extracellular proteases, elastases, siderophores, and quorum sensing signal molecules. Accordingly, infection assays in plant and animal models demonstrated that ApaH-deficient cells are significantly impaired in infectivity and persistence in different hosts, including mice. Finally, deletion of apaH in P. aeruginosa clinical isolates demonstrated that the positive effect of ApaH on the production of virulence-related traits and on infectivity is conserved in P. aeruginosa. This study provides the first evidence that the Ap4A-hydrolysing enzyme ApaH is important for P. aeruginosa virulence, highlighting this protein as a novel potential target for antivirulence therapies against P. aeruginosa.
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Affiliation(s)
| | | | - Giulia Ferri
- Department of Medical, Oral and Biotechnology Sciences, University of Chieti-Pescara, Chieti, Italy
| | - Heike Bähre
- Research Core Unit Metabolomics, Hannover Medical School, Hannover, Germany
| | - Livia Leoni
- Department of Science, University Roma Tre, Rome, Italy
| | - Giordano Rampioni
- Department of Science, University Roma Tre, Rome, Italy
- IRCCS Fondazione Santa Lucia, Rome, Italy
| | - Paolo Visca
- Department of Science, University Roma Tre, Rome, Italy
- IRCCS Fondazione Santa Lucia, Rome, Italy
- NBFC, National Biodiversity Future Center, Palermo, Italy
| | - Antonio Recchiuti
- Department of Medical, Oral and Biotechnology Sciences, University of Chieti-Pescara, Chieti, Italy
| | - Francesco Imperi
- Department of Science, University Roma Tre, Rome, Italy
- IRCCS Fondazione Santa Lucia, Rome, Italy
- NBFC, National Biodiversity Future Center, Palermo, Italy
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Hsieh YYP, Sun W, Young JM, Cheung R, Hogan DA, Dandekar AA, Malik HS. Widespread fungal-bacterial competition for magnesium lowers bacterial susceptibility to polymyxin antibiotics. PLoS Biol 2024; 22:e3002694. [PMID: 38900845 PMCID: PMC11218974 DOI: 10.1371/journal.pbio.3002694] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2024] [Revised: 07/02/2024] [Accepted: 05/29/2024] [Indexed: 06/22/2024] Open
Abstract
Fungi and bacteria coexist in many polymicrobial communities, yet the molecular basis of their interactions remains poorly understood. Here, we show that the fungus Candida albicans sequesters essential magnesium ions from the bacterium Pseudomonas aeruginosa. To counteract fungal Mg2+ sequestration, P. aeruginosa expresses the Mg2+ transporter MgtA when Mg2+ levels are low. Thus, loss of MgtA specifically impairs P. aeruginosa in co-culture with C. albicans, but fitness can be restored by supplementing Mg2+. Using a panel of fungi and bacteria, we show that Mg2+ sequestration is a general mechanism of fungal antagonism against gram-negative bacteria. Mg2+ limitation enhances bacterial resistance to polymyxin antibiotics like colistin, which target gram-negative bacterial membranes. Indeed, experimental evolution reveals that P. aeruginosa evolves C. albicans-dependent colistin resistance via non-canonical means; antifungal treatment renders resistant bacteria colistin-sensitive. Our work suggests that fungal-bacterial competition could profoundly impact polymicrobial infection treatment with antibiotics of last resort.
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Affiliation(s)
- Yu-Ying Phoebe Hsieh
- Division of Basic Sciences, Fred Hutchinson Cancer Center, Seattle, Washington, United States of America
| | - Wanting Sun
- Division of Basic Sciences, Fred Hutchinson Cancer Center, Seattle, Washington, United States of America
| | - Janet M. Young
- Division of Basic Sciences, Fred Hutchinson Cancer Center, Seattle, Washington, United States of America
| | - Robin Cheung
- Department of Microbiology, University of Washington, Seattle, Washington, United States of America
| | - Deborah A. Hogan
- Department of Microbiology and Immunology, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire, United States of America
| | - Ajai A. Dandekar
- Department of Microbiology, University of Washington, Seattle, Washington, United States of America
- Department of Medicine, University of Washington, Seattle, Washington, United States of America
| | - Harmit S. Malik
- Division of Basic Sciences, Fred Hutchinson Cancer Center, Seattle, Washington, United States of America
- Howard Hughes Medical Institute, Fred Hutchinson Cancer Center, Seattle, Washington, United States of America
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Neff SL, Doing G, Reiter T, Hampton TH, Greene CS, Hogan DA. Pseudomonas aeruginosa transcriptome analysis of metal restriction in ex vivo cystic fibrosis sputum. Microbiol Spectr 2024; 12:e0315723. [PMID: 38385740 PMCID: PMC10986534 DOI: 10.1128/spectrum.03157-23] [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: 08/24/2023] [Accepted: 01/22/2024] [Indexed: 02/23/2024] Open
Abstract
Chronic Pseudomonas aeruginosa lung infections are a feature of cystic fibrosis (CF) that many patients experience even with the advent of highly effective modulator therapies. Identifying factors that impact P. aeruginosa in the CF lung could yield novel strategies to eradicate infection or otherwise improve outcomes. To complement published P. aeruginosa studies using laboratory models or RNA isolated from sputum, we analyzed transcripts of strain PAO1 after incubation in sputum from different CF donors prior to RNA extraction. We compared PAO1 gene expression in this "spike-in" sputum model to that for P. aeruginosa grown in synthetic cystic fibrosis sputum medium to determine key genes, which are among the most differentially expressed or most highly expressed. Using the key genes, gene sets with correlated expression were determined using the gene expression analysis tool eADAGE. Gene sets were used to analyze the activity of specific pathways in P. aeruginosa grown in sputum from different individuals. Gene sets that we found to be more active in sputum showed similar activation in published data that included P. aeruginosa RNA isolated from sputum relative to corresponding in vitro reference cultures. In the ex vivo samples, P. aeruginosa had increased levels of genes related to zinc and iron acquisition which were suppressed by metal amendment of sputum. We also found a significant correlation between expression of the H1-type VI secretion system and CFTR corrector use by the sputum donor. An ex vivo sputum model or synthetic sputum medium formulation that imposes metal restriction may enhance future CF-related studies.IMPORTANCEIdentifying the gene expression programs used by Pseudomonas aeruginosa to colonize the lungs of people with cystic fibrosis (CF) will illuminate new therapeutic strategies. To capture these transcriptional programs, we cultured the common P. aeruginosa laboratory strain PAO1 in expectorated sputum from CF patient donors. Through bioinformatic analysis, we defined sets of genes that are more transcriptionally active in real CF sputum compared to a synthetic cystic fibrosis sputum medium. Many of the most differentially active gene sets contained genes related to metal acquisition, suggesting that these gene sets play an active role in scavenging for metals in the CF lung environment which may be inadequately represented in some models. Future studies of P. aeruginosa transcript abundance in CF may benefit from the use of an expectorated sputum model or media supplemented with factors that induce metal restriction.
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Affiliation(s)
- Samuel L. Neff
- Department of Microbiology and Immunology, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire, USA
| | - Georgia Doing
- Department of Microbiology and Immunology, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire, USA
| | - Taylor Reiter
- Department of Biomedical Informatics, University of Colorado School of Medicine, Aurora, Colorado, USA
| | - Thomas H. Hampton
- Department of Microbiology and Immunology, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire, USA
| | - Casey S. Greene
- Department of Biomedical Informatics, University of Colorado School of Medicine, Aurora, Colorado, USA
| | - Deborah A. Hogan
- Department of Microbiology and Immunology, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire, USA
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Zhao Y, Xie L, Wang C, Zhou Q, Jelsbak L. Comparative whole-genome analysis of China and global epidemic Pseudomonas aeruginosa high-risk clones. J Glob Antimicrob Resist 2023; 35:149-158. [PMID: 37709140 DOI: 10.1016/j.jgar.2023.08.020] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Revised: 08/15/2023] [Accepted: 08/31/2023] [Indexed: 09/16/2023] Open
Abstract
OBJECTIVES The various sequence types (STs) of Pseudomonas aeruginosa (P. aeruginosa) high-risk clones (HiRiCs) have been sporadically reported in China, but the systematic analysis of genomes for these STs remains limited. This study aimed to address the evolutionary pathways underlying the emergence of HiRiCs and their routes of dissemination from Chinese and global perspectives. METHODS The phylogenetic analysis was performed based on 416 newly sequenced clinical P. aeruginosa strains from Guangdong (GD), published genome sequences of 282 Chinese isolates, and 868 HiRiCs isolates from other countries. The genomic comparison study of global HiRiC ST244 was conducted to detect the model of global dissemination and local separation driven by association regional-specific antibiotic resistance genes. Furthermore, the evolutionary route of the emerging, China-specific HiRiC ST1971 was explored using Most Recent Common Ancestor (MRCA) analysis. RESULTS Based on comparative genomics analysis, we found a clear geographical separation of ST244 isolates, yet with an association between ST244 isolates from GD and America. We identified a set of 38 AMR genes that contribute to the geographical separation in ST244, and we identified genetic determinants either positively (MexB) and negatively (opmD) associated with GD ST244. For the China-unique HiRiC ST1971, its evolutionary history across different continents before emerging as ST1971 in China was also deduced. CONCLUSION This study provides insight into the specific genetics underlying regional differences among globally disseminated P. aeruginosa HiRiCs (ST244) as well as new understanding of the dissemination and evolution of a regional HiRiC (ST1971). Understanding the genetics of these and other HiRiCs may assist in controlling their emergence and further spread.
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Affiliation(s)
- Yonggang Zhao
- Department of Biotechnology and Biomedicine, Technical University of Denmark, Lyngby, Denmark
| | - Lu Xie
- Research Center for Micro-Ecological Agent Engineering and Technology of Guangdong Province, Guangzhou, Guangdong Province, China
| | - Chongzhi Wang
- Department of Biotechnology and Biomedicine, Technical University of Denmark, Lyngby, Denmark
| | - Qian Zhou
- Department of Computer Science, City University of Hong Kong, Hong Kong, China.
| | - Lars Jelsbak
- Department of Biotechnology and Biomedicine, Technical University of Denmark, Lyngby, Denmark.
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Abdill RJ, Graham SP, Rubinetti V, Albert FW, Greene CS, Davis S, Blekhman R. Integration of 168,000 samples reveals global patterns of the human gut microbiome. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.11.560955. [PMID: 37873416 PMCID: PMC10592789 DOI: 10.1101/2023.10.11.560955] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
Understanding the factors that shape variation in the human microbiome is a major goal of research in biology. While other genomics fields have used large, pre-compiled compendia to extract systematic insights requiring otherwise impractical sample sizes, there has been no comparable resource for the 16S rRNA sequencing data commonly used to quantify microbiome composition. To help close this gap, we have assembled a set of 168,484 publicly available human gut microbiome samples, processed with a single pipeline and combined into the largest unified microbiome dataset to date. We use this resource, which is freely available at microbiomap.org, to shed light on global variation in the human gut microbiome. We find that Firmicutes, particularly Bacilli and Clostridia, are almost universally present in the human gut. At the same time, the relative abundance of the 65 most common microbial genera differ between at least two world regions. We also show that gut microbiomes in undersampled world regions, such as Central and Southern Asia, differ significantly from the more thoroughly characterized microbiomes of Europe and Northern America. Moreover, humans in these overlooked regions likely harbor hundreds of taxa that have not yet been discovered due to this undersampling, highlighting the need for diversity in microbiome studies. We anticipate that this new compendium can serve the community and enable advanced applied and methodological research.
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Affiliation(s)
- Richard J. Abdill
- Section of Genetic Medicine, Department of Medicine, University of Chicago, Chicago, Illinois, USA
| | - Samantha P. Graham
- Department of Genetics, Cell Biology, and Development, University of Minnesota, Minneapolis, Minnesota, USA
| | - Vincent Rubinetti
- Department of Biomedical Informatics, University of Colorado School of Medicine, Aurora, CO, USA
- Center for Health Artificial Intelligence (CHAI), University of Colorado School of Medicine, Aurora, CO, USA
| | - Frank W. Albert
- Department of Genetics, Cell Biology, and Development, University of Minnesota, Minneapolis, Minnesota, USA
| | - Casey S. Greene
- Department of Biomedical Informatics, University of Colorado School of Medicine, Aurora, CO, USA
- Center for Health Artificial Intelligence (CHAI), University of Colorado School of Medicine, Aurora, CO, USA
| | - Sean Davis
- Department of Biomedical Informatics, University of Colorado School of Medicine, Aurora, CO, USA
- Center for Health Artificial Intelligence (CHAI), University of Colorado School of Medicine, Aurora, CO, USA
| | - Ran Blekhman
- Section of Genetic Medicine, Department of Medicine, University of Chicago, Chicago, Illinois, USA
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Doing G, Lee AJ, Neff SL, Reiter T, Holt JD, Stanton BA, Greene CS, Hogan DA. Computationally Efficient Assembly of Pseudomonas aeruginosa Gene Expression Compendia. mSystems 2023; 8:e0034122. [PMID: 36541761 PMCID: PMC9948711 DOI: 10.1128/msystems.00341-22] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Accepted: 11/09/2022] [Indexed: 12/24/2022] Open
Abstract
Thousands of Pseudomonas aeruginosa RNA sequencing (RNA-seq) gene expression profiles are publicly available via the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA). In this work, the transcriptional profiles from hundreds of studies performed by over 75 research groups were reanalyzed in aggregate to create a powerful tool for hypothesis generation and testing. Raw sequence data were uniformly processed using the Salmon pseudoaligner, and this read mapping method was validated by comparison to a direct alignment method. We developed filtering criteria to exclude samples with aberrant levels of housekeeping gene expression or an unexpected number of genes with no reported values and normalized the filtered compendia using the ratio-of-medians method. The filtering and normalization steps greatly improved gene expression correlations for genes within the same operon or regulon across the 2,333 samples. Since the RNA-seq data were generated using diverse strains, we report the effects of mapping samples to noncognate reference genomes by separately analyzing all samples mapped to cDNA reference genomes for strains PAO1 and PA14, two divergent strains that were used to generate most of the samples. Finally, we developed an algorithm to incorporate new data as they are deposited into the SRA. Our processing and quality control methods provide a scalable framework for taking advantage of the troves of biological information hibernating in the depths of microbial gene expression data and yield useful tools for P. aeruginosa RNA-seq data to be leveraged for diverse research goals. IMPORTANCE Pseudomonas aeruginosa is a causative agent of a wide range of infections, including chronic infections associated with cystic fibrosis. These P. aeruginosa infections are difficult to treat and often have negative outcomes. To aid in the study of this problematic pathogen, we mapped, filtered for quality, and normalized thousands of P. aeruginosa RNA-seq gene expression profiles that were publicly available via the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA). The resulting compendia facilitate analyses across experiments, strains, and conditions. Ultimately, the workflow that we present could be applied to analyses of other microbial species.
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Affiliation(s)
- Georgia Doing
- Department of Microbiology and Immunology, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire, USA
| | - Alexandra J. Lee
- Genomics and Computational Biology Graduate Program, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Samuel L. Neff
- Department of Microbiology and Immunology, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire, USA
| | - Taylor Reiter
- Department of Biochemistry and Molecular Genetics, University of Colorado School of Medicine, Denver, Colorado, USA
| | - Jacob D. Holt
- Department of Microbiology and Immunology, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire, USA
| | - Bruce A. Stanton
- Department of Microbiology and Immunology, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire, USA
| | - Casey S. Greene
- Department of Biochemistry and Molecular Genetics, University of Colorado School of Medicine, Denver, Colorado, USA
- Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Deborah A. Hogan
- Department of Microbiology and Immunology, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire, USA
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