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Cirinciani M, Da Pozzo E, Trincavelli ML, Milazzo P, Martini C. Drug Mechanism: A bioinformatic update. Biochem Pharmacol 2024; 228:116078. [PMID: 38402909 DOI: 10.1016/j.bcp.2024.116078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Revised: 02/01/2024] [Accepted: 02/22/2024] [Indexed: 02/27/2024]
Abstract
A drug Mechanism of Action (MoA) is a complex biological phenomenon that describes how a bioactive compound produces a pharmacological effect. The complete knowledge of MoA is fundamental to fully understanding the drug activity. Over the years, many experimental methods have been developed and a huge quantity of data has been produced. Nowadays, considering the increasing omics data availability and the improvement of the accessible computational resources, the study of a drug MoA is conducted by integrating experimental and bioinformatics approaches. The development of new in silico solutions for this type of analysis is continuously ongoing; herein, an updating review on such bioinformatic methods is presented. The methodologies cited are based on multi-omics data integration in biochemical networks and Machine Learning (ML). The multiple types of usable input data and the advantages and disadvantages of each method have been analyzed, with a focus on their applications. Three specific research areas (i.e. cancer drug development, antibiotics discovery, and drug repurposing) have been chosen for their importance in the drug discovery fields in which the study of drug MoA, through novel bioinformatics approaches, is particularly productive.
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Affiliation(s)
- Martina Cirinciani
- Department of Pharmacy, University of Pisa, via Bonanno 6, 56126 Pisa, Italy
| | - Eleonora Da Pozzo
- Department of Pharmacy, University of Pisa, via Bonanno 6, 56126 Pisa, Italy; Center for Instrument Sharing University of Pisa (CISUP), Lungarno Pacinotti, 43/44, 56126 Pisa, Italy
| | - Maria Letizia Trincavelli
- Department of Pharmacy, University of Pisa, via Bonanno 6, 56126 Pisa, Italy; Center for Instrument Sharing University of Pisa (CISUP), Lungarno Pacinotti, 43/44, 56126 Pisa, Italy
| | - Paolo Milazzo
- Center for Instrument Sharing University of Pisa (CISUP), Lungarno Pacinotti, 43/44, 56126 Pisa, Italy; Department of Computer Science, University of Pisa, Largo Pontecorvo, 3, 56127 Pisa, Italy
| | - Claudia Martini
- Department of Pharmacy, University of Pisa, via Bonanno 6, 56126 Pisa, Italy; Center for Instrument Sharing University of Pisa (CISUP), Lungarno Pacinotti, 43/44, 56126 Pisa, Italy.
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2
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Espinoza JL, Phillips A, Prentice MB, Tan GS, Kamath PL, Lloyd KG, Dupont CL. Unveiling the microbial realm with VEBA 2.0: a modular bioinformatics suite for end-to-end genome-resolved prokaryotic, (micro)eukaryotic and viral multi-omics from either short- or long-read sequencing. Nucleic Acids Res 2024; 52:e63. [PMID: 38909293 DOI: 10.1093/nar/gkae528] [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: 03/08/2024] [Revised: 05/21/2024] [Accepted: 06/10/2024] [Indexed: 06/24/2024] Open
Abstract
The microbiome is a complex community of microorganisms, encompassing prokaryotic (bacterial and archaeal), eukaryotic, and viral entities. This microbial ensemble plays a pivotal role in influencing the health and productivity of diverse ecosystems while shaping the web of life. However, many software suites developed to study microbiomes analyze only the prokaryotic community and provide limited to no support for viruses and microeukaryotes. Previously, we introduced the Viral Eukaryotic Bacterial Archaeal (VEBA) open-source software suite to address this critical gap in microbiome research by extending genome-resolved analysis beyond prokaryotes to encompass the understudied realms of eukaryotes and viruses. Here we present VEBA 2.0 with key updates including a comprehensive clustered microeukaryotic protein database, rapid genome/protein-level clustering, bioprospecting, non-coding/organelle gene modeling, genome-resolved taxonomic/pathway profiling, long-read support, and containerization. We demonstrate VEBA's versatile application through the analysis of diverse case studies including marine water, Siberian permafrost, and white-tailed deer lung tissues with the latter showcasing how to identify integrated viruses. VEBA represents a crucial advancement in microbiome research, offering a powerful and accessible software suite that bridges the gap between genomics and biotechnological solutions.
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Affiliation(s)
- Josh L Espinoza
- Department of Environment and Sustainability, J. Craig Venter Institute, La Jolla, CA 92037, USA
- Department of Genomic Medicine and Infectious Diseases, J. Craig Venter Institute, La Jolla, CA 92037, USA
| | - Allan Phillips
- Department of Environment and Sustainability, J. Craig Venter Institute, La Jolla, CA 92037, USA
- Department of Genomic Medicine and Infectious Diseases, J. Craig Venter Institute, La Jolla, CA 92037, USA
| | - Melanie B Prentice
- School of Food and Agriculture, University of Maine, Orono, ME 04469, USA
| | - Gene S Tan
- Department of Genomic Medicine and Infectious Diseases, J. Craig Venter Institute, La Jolla, CA 92037, USA
| | - Pauline L Kamath
- School of Food and Agriculture, University of Maine, Orono, ME 04469, USA
- Maine Center for Genetics in the Environment, University of Maine, Orono, ME 04469, USA
| | - Karen G Lloyd
- Microbiology Department, University of Tennessee, Knoxville, TN 37917, USA
| | - Chris L Dupont
- Department of Environment and Sustainability, J. Craig Venter Institute, La Jolla, CA 92037, USA
- Department of Genomic Medicine and Infectious Diseases, J. Craig Venter Institute, La Jolla, CA 92037, USA
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3
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Romano KP, Bagnall J, Warrier T, Sullivan J, Ferrara K, Orzechowski M, Nguyen P, Raines K, Livny J, Shoresh N, Hung D. Perturbation-Specific Transcriptional Mapping for unbiased target elucidation of antibiotics. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.25.590978. [PMID: 38712067 PMCID: PMC11071498 DOI: 10.1101/2024.04.25.590978] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2024]
Abstract
The rising prevalence of antibiotic resistance threatens human health. While more sophisticated strategies for antibiotic discovery are being developed, target elucidation of new chemical entities remains challenging. In the post-genomic era, expression profiling can play an important role in mechanism-of-action (MOA) prediction by reporting on the cellular response to perturbation. However, the broad application of transcriptomics has yet to fulfill its promise of transforming target elucidation due to challenges in identifying the most relevant, direct responses to target inhibition. We developed an unbiased strategy for MOA prediction, called Perturbation-Specific Transcriptional Mapping (PerSpecTM), in which large-throughput expression profiling of wildtype or hypomorphic mutants, depleted for essential targets, enables a computational strategy to address this challenge. We applied PerSpecTM to perform reference-based MOA prediction based on the principle that similar perturbations, whether chemical or genetic, will elicit similar transcriptional responses. Using this approach, we elucidated the MOAs of three new molecules with activity against Pseudomonas aeruginosa by comparing their expression profiles to those of a reference set of antimicrobial compounds with known MOAs. We also show that transcriptional responses to small molecule inhibition resemble those resulting from genetic depletion of essential targets by CRISPRi by PerSpecTM, demonstrating proof-of-concept that correlations between expression profiles of small molecule and genetic perturbations can facilitate MOA prediction when no chemical entities exist to serve as a reference. Empowered by PerSpecTM, this work lays the foundation for an unbiased, readily scalable, systematic reference-based strategy for MOA elucidation that could transform antibiotic discovery efforts.
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4
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French S, Guo ABY, Ellis MJ, Deisinger JP, Johnson JW, Rachwalski K, Piquette ZA, Lluka T, Zary M, Gamage S, Magolan J, Brown ED. A platform for predicting mechanism of action based on bacterial transcriptional responses identifies an unusual DNA gyrase inhibitor. Cell Rep 2024; 43:114053. [PMID: 38578824 DOI: 10.1016/j.celrep.2024.114053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Revised: 02/02/2024] [Accepted: 03/19/2024] [Indexed: 04/07/2024] Open
Abstract
In the search for much-needed new antibacterial chemical matter, a myriad of compounds have been reported in academic and pharmaceutical screening endeavors. Only a small fraction of these, however, are characterized with respect to mechanism of action (MOA). Here, we describe a pipeline that categorizes transcriptional responses to antibiotics and provides hypotheses for MOA. 3D-printed imaging hardware PFIboxes) profiles responses of Escherichia coli promoter-GFP fusions to more than 100 antibiotics. Notably, metergoline, a semi-synthetic ergot alkaloid, mimics a DNA replication inhibitor. In vitro supercoiling assays confirm this prediction, and a potent analog thereof (MLEB-1934) inhibits growth at 0.25 μg/mL and is highly active against quinolone-resistant strains of methicillin-resistant Staphylococcus aureus. Spontaneous suppressor mutants map to a seldom explored allosteric binding pocket, suggesting a mechanism distinct from DNA gyrase inhibitors used in the clinic. In all, the work highlights the potential of this platform to rapidly assess MOA of new antibacterial compounds.
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Affiliation(s)
- Shawn French
- McMaster University, Department of Biochemistry and Biomedical Sciences and Michael G. DeGroote Institute for Infectious Disease Research, Hamilton, ON L8S 4L8, Canada
| | - Amelia Bing Ya Guo
- McMaster University, Department of Biochemistry and Biomedical Sciences and Michael G. DeGroote Institute for Infectious Disease Research, Hamilton, ON L8S 4L8, Canada
| | - Michael J Ellis
- McMaster University, Department of Biochemistry and Biomedical Sciences and Michael G. DeGroote Institute for Infectious Disease Research, Hamilton, ON L8S 4L8, Canada
| | - Julia P Deisinger
- McMaster University, Department of Biochemistry and Biomedical Sciences and Michael G. DeGroote Institute for Infectious Disease Research, Hamilton, ON L8S 4L8, Canada
| | - Jarrod W Johnson
- McMaster University, Department of Biochemistry and Biomedical Sciences and Michael G. DeGroote Institute for Infectious Disease Research, Hamilton, ON L8S 4L8, Canada
| | - Kenneth Rachwalski
- McMaster University, Department of Biochemistry and Biomedical Sciences and Michael G. DeGroote Institute for Infectious Disease Research, Hamilton, ON L8S 4L8, Canada
| | - Zoë A Piquette
- McMaster University, Department of Biochemistry and Biomedical Sciences and Michael G. DeGroote Institute for Infectious Disease Research, Hamilton, ON L8S 4L8, Canada
| | - Telmah Lluka
- McMaster University, Department of Biochemistry and Biomedical Sciences and Michael G. DeGroote Institute for Infectious Disease Research, Hamilton, ON L8S 4L8, Canada
| | - Miranda Zary
- McMaster University, Department of Biochemistry and Biomedical Sciences and Michael G. DeGroote Institute for Infectious Disease Research, Hamilton, ON L8S 4L8, Canada
| | - Sineli Gamage
- McMaster University, Department of Biochemistry and Biomedical Sciences and Michael G. DeGroote Institute for Infectious Disease Research, Hamilton, ON L8S 4L8, Canada
| | - Jakob Magolan
- McMaster University, Department of Biochemistry and Biomedical Sciences and Michael G. DeGroote Institute for Infectious Disease Research, Hamilton, ON L8S 4L8, Canada
| | - Eric D Brown
- McMaster University, Department of Biochemistry and Biomedical Sciences and Michael G. DeGroote Institute for Infectious Disease Research, Hamilton, ON L8S 4L8, Canada.
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Alqedari H, Altabtbaei K, Espinoza JL, Bin-Hasan S, Alghounaim M, Alawady A, Altabtabae A, AlJamaan S, Devarajan S, AlShammari T, Ben Eid M, Matsuoka M, Jang H, Dupont CL, Freire M. Host-microbiome associations in saliva predict COVID-19 severity. PNAS NEXUS 2024; 3:pgae126. [PMID: 38617584 PMCID: PMC11010653 DOI: 10.1093/pnasnexus/pgae126] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Accepted: 03/07/2024] [Indexed: 04/16/2024]
Abstract
Established evidence indicates that oral microbiota plays a crucial role in modulating host immune responses to viral infection. Following severe acute respiratory syndrome coronavirus 2, there are coordinated microbiome and inflammatory responses within the mucosal and systemic compartments that are unknown. The specific roles the oral microbiota and inflammatory cytokines play in the pathogenesis of coronavirus disease 2019 (COVID-19) are yet to be explored. Here, we evaluated the relationships between the salivary microbiome and host parameters in different groups of COVID-19 severity based on their oxygen requirement. Saliva and blood samples (n = 80) were collected from COVID-19 and from noninfected individuals. We characterized the oral microbiomes using 16S ribosomal RNA gene sequencing and evaluated saliva and serum cytokines and chemokines using multiplex analysis. Alpha diversity of the salivary microbial community was negatively associated with COVID-19 severity, while diversity increased with health. Integrated cytokine evaluations of saliva and serum showed that the oral host response was distinct from the systemic response. The hierarchical classification of COVID-19 status and respiratory severity using multiple modalities separately (i.e. microbiome, salivary cytokines, and systemic cytokines) and simultaneously (i.e. multimodal perturbation analyses) revealed that the microbiome perturbation analysis was the most informative for predicting COVID-19 status and severity, followed by the multimodal. Our findings suggest that oral microbiome and salivary cytokines may be predictive of COVID-19 status and severity, whereas atypical local mucosal immune suppression and systemic hyperinflammation provide new cues to understand the pathogenesis in immunologically compromised populations.
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Affiliation(s)
- Hend Alqedari
- Department of Public Health and Community Service, Tufts University School of Dental Medicine, 1 Kneeland Street, Boston, MA 02111, USA
- Dasman Diabetes Institute, 1180 Dasman, 9XQV+V9 Kuwait City, Kuwait
| | - Khaled Altabtbaei
- Faculty of Medicine and Dentistry, School of Dentistry, University of Alberta, Edmonton, AB T6G 2L7, Canada
| | - Josh L Espinoza
- Department of Genomic Medicine and Infectious Diseases, J. Craig Venter Institute, La Jolla, CA 92037, USA
| | - Saadoun Bin-Hasan
- Department of Pediatrics, Farwaniyah Hospital, Ministry of Health, 7XF4+WPJ Al Farwaniyah, Kuwait
| | - Mohammad Alghounaim
- Department of Pediatrics, Amiri Hospital, Ministry of Health, 9XQQ+42 Kuwait City, Kuwait
| | - Abdullah Alawady
- Department of Pediatrics, Farwaniyah Hospital, Ministry of Health, 7XF4+WPJ Al Farwaniyah, Kuwait
| | - Abdullah Altabtabae
- Department of Pediatrics, Farwaniyah Hospital, Ministry of Health, 7XF4+WPJ Al Farwaniyah, Kuwait
| | - Sarah AlJamaan
- Department of Pediatrics, Farwaniyah Hospital, Ministry of Health, 7XF4+WPJ Al Farwaniyah, Kuwait
| | | | | | - Mohammed Ben Eid
- Department of Pediatrics, Farwaniyah Hospital, Ministry of Health, 7XF4+WPJ Al Farwaniyah, Kuwait
| | - Michele Matsuoka
- Department of Genomic Medicine and Infectious Diseases, J. Craig Venter Institute, La Jolla, CA 92037, USA
| | - Hyesun Jang
- Department of Genomic Medicine and Infectious Diseases, J. Craig Venter Institute, La Jolla, CA 92037, USA
| | - Christopher L Dupont
- Department of Genomic Medicine and Infectious Diseases, J. Craig Venter Institute, La Jolla, CA 92037, USA
| | - Marcelo Freire
- Department of Genomic Medicine and Infectious Diseases, J. Craig Venter Institute, La Jolla, CA 92037, USA
- Division of Infectious Diseases and Global Public Health Department of Medicine, University of California San Diego, La Jolla, CA 92093, USA
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6
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Espinoza JL, Phillips A, Prentice MB, Tan GS, Kamath PL, Lloyd KG, Dupont CL. Unveiling the Microbial Realm with VEBA 2.0: A modular bioinformatics suite for end-to-end genome-resolved prokaryotic, (micro)eukaryotic, and viral multi-omics from either short- or long-read sequencing. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.08.583560. [PMID: 38559265 PMCID: PMC10979853 DOI: 10.1101/2024.03.08.583560] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
The microbiome is a complex community of microorganisms, encompassing prokaryotic (bacterial and archaeal), eukaryotic, and viral entities. This microbial ensemble plays a pivotal role in influencing the health and productivity of diverse ecosystems while shaping the web of life. However, many software suites developed to study microbiomes analyze only the prokaryotic community and provide limited to no support for viruses and microeukaryotes. Previously, we introduced the Viral Eukaryotic Bacterial Archaeal (VEBA) open-source software suite to address this critical gap in microbiome research by extending genome-resolved analysis beyond prokaryotes to encompass the understudied realms of eukaryotes and viruses. Here we present VEBA 2.0 with key updates including a comprehensive clustered microeukaryotic protein database, rapid genome/protein-level clustering, bioprospecting, non-coding/organelle gene modeling, genome-resolved taxonomic/pathway profiling, long-read support, and containerization. We demonstrate VEBA's versatile application through the analysis of diverse case studies including marine water, Siberian permafrost, and white-tailed deer lung tissues with the latter showcasing how to identify integrated viruses. VEBA represents a crucial advancement in microbiome research, offering a powerful and accessible platform that bridges the gap between genomics and biotechnological solutions.
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Affiliation(s)
- Josh L. Espinoza
- Department of Environment and Sustainability, J. Craig Venter Institute, La Jolla, CA 92037, USA
- Department of Genomic Medicine and Infectious Diseases, J. Craig Venter Institute, La Jolla, CA 92037, USA
| | - Allan Phillips
- Department of Environment and Sustainability, J. Craig Venter Institute, La Jolla, CA 92037, USA
- Department of Genomic Medicine and Infectious Diseases, J. Craig Venter Institute, La Jolla, CA 92037, USA
| | | | - Gene S. Tan
- Department of Genomic Medicine and Infectious Diseases, J. Craig Venter Institute, La Jolla, CA 92037, USA
| | - Pauline L. Kamath
- School of Food and Agriculture, University of Maine, Orono, ME 04469, USA
| | - Karen G. Lloyd
- Microbiology Department, University of Tennessee, Knoxville, TN 37917, USA
| | - Chris L. Dupont
- Department of Environment and Sustainability, J. Craig Venter Institute, La Jolla, CA 92037, USA
- Department of Genomic Medicine and Infectious Diseases, J. Craig Venter Institute, La Jolla, CA 92037, USA
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7
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Garza EA, Bielinski VA, Espinoza JL, Orlandi K, Alfaro JR, Bolt TM, Beeri K, Weyman PD, Dupont CL. Validating a Promoter Library for Application in Plasmid-Based Diatom Genetic Engineering. ACS Synth Biol 2023; 12:3215-3228. [PMID: 37857380 PMCID: PMC10661051 DOI: 10.1021/acssynbio.3c00163] [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: 03/21/2023] [Indexed: 10/21/2023]
Abstract
While diatoms are promising synthetic biology platforms, there currently exists a limited number of validated genetic regulatory parts available for genetic engineering. The standard method for diatom transformation, nonspecific introduction of DNA into chromosomes via biolistic particle bombardment, is low throughput and suffers from clonal variability and epigenetic effects. Recent developments in diatom engineering have demonstrated that autonomously replicating episomal plasmids serve as stable expression platforms for diverse gene expression technologies. These plasmids are delivered via bacterial conjugation and, when combined with modular DNA assembly technologies, provide a flexibility and speed not possible with biolistic-mediated strain generation. In order to expand the current toolbox for plasmid-based engineering in the diatom Phaeodactylum tricornutum, a conjugation-based forward genetics screen for promoter discovery was developed, and application to a diatom genomic DNA library defined 252 P. tricornutum promoter elements. From this library, 40 promoter/terminator pairs were delivered via conjugation on episomal plasmids, characterized in vivo, and ranked across 4 orders of magnitude difference in reporter gene expression levels.
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Affiliation(s)
- Erin A. Garza
- J. Craig Venter Institute, La Jolla, California 92037, United States
| | | | - Josh L. Espinoza
- J. Craig Venter Institute, La Jolla, California 92037, United States
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8
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Walworth NG, Espinoza JL, Argyle PA, Hinners J, Levine NM, Doblin MA, Dupont CL, Collins S. Genus-Wide Transcriptional Landscapes Reveal Correlated Gene Networks Underlying Microevolutionary Divergence in Diatoms. Mol Biol Evol 2023; 40:msad218. [PMID: 37874344 PMCID: PMC10595192 DOI: 10.1093/molbev/msad218] [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: 04/28/2023] [Revised: 08/24/2023] [Accepted: 09/21/2023] [Indexed: 10/25/2023] Open
Abstract
Marine microbes like diatoms make up the base of marine food webs and drive global nutrient cycles. Despite their key roles in ecology, biogeochemistry, and biotechnology, we have limited empirical data on how forces other than adaptation may drive diatom diversification, especially in the absence of environmental change. One key feature of diatom populations is frequent extreme reductions in population size, which can occur both in situ and ex situ as part of bloom-and-bust growth dynamics. This can drive divergence between closely related lineages, even in the absence of environmental differences. Here, we combine experimental evolution and transcriptome landscapes (t-scapes) to reveal repeated evolutionary divergence within several species of diatoms in a constant environment. We show that most of the transcriptional divergence can be captured on a reduced set of axes, and that repeatable evolution can occur along a single major axis of variation defined by core ortholog expression comprising common metabolic pathways. Previous work has associated specific transcriptional changes in gene networks with environmental factors. Here, we find that these same gene networks diverge in the absence of environmental change, suggesting these pathways may be central in generating phenotypic diversity as a result of both selective and random evolutionary forces. If this is the case, these genes and the functions they encode may represent universal axes of variation. Such axes that capture suites of interacting transcriptional changes during diversification improve our understanding of both global patterns in local adaptation and microdiversity, as well as evolutionary forces shaping algal cultivation.
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Affiliation(s)
- Nathan G Walworth
- Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089-0371, USA
- J.Craig Venter Institute, La Jolla, CA 92037, USA
| | | | - Phoebe A Argyle
- Climate Change Cluster, University of Technology Sydney, Sydney, New South Wales 2007, Australia
| | - Jana Hinners
- School of Biological Sciences, University of Edinburgh, Edinburgh EH9 3FL, UK
- Helmholtz-Zentrum Hereon, 21502 Geesthacht, Germany
| | - Naomi M Levine
- Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089-0371, USA
| | - Martina A Doblin
- Climate Change Cluster, University of Technology Sydney, Sydney, New South Wales 2007, Australia
| | | | - Sinéad Collins
- School of Biological Sciences, University of Edinburgh, Edinburgh EH9 3FL, UK
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Wong F, de la Fuente-Nunez C, Collins JJ. Leveraging artificial intelligence in the fight against infectious diseases. Science 2023; 381:164-170. [PMID: 37440620 PMCID: PMC10663167 DOI: 10.1126/science.adh1114] [Citation(s) in RCA: 60] [Impact Index Per Article: 60.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2023] [Accepted: 06/05/2023] [Indexed: 07/15/2023]
Abstract
Despite advances in molecular biology, genetics, computation, and medicinal chemistry, infectious disease remains an ominous threat to public health. Addressing the challenges posed by pathogen outbreaks, pandemics, and antimicrobial resistance will require concerted interdisciplinary efforts. In conjunction with systems and synthetic biology, artificial intelligence (AI) is now leading to rapid progress, expanding anti-infective drug discovery, enhancing our understanding of infection biology, and accelerating the development of diagnostics. In this Review, we discuss approaches for detecting, treating, and understanding infectious diseases, underscoring the progress supported by AI in each case. We suggest future applications of AI and how it might be harnessed to help control infectious disease outbreaks and pandemics.
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Affiliation(s)
- Felix Wong
- Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Institute for Medical Engineering & Science and Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Cesar de la Fuente-Nunez
- Machine Biology Group, Departments of Psychiatry and Microbiology, Institute for Biomedical Informatics, Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Departments of Bioengineering and Chemical and Biomolecular Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA
- Penn Institute for Computational Science, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - James J. Collins
- Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Institute for Medical Engineering & Science and Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA 02115, USA
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10
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Alqedari H, Altabtbaei K, Espinoza JL, Bin-Hasan S, Alghounaim M, Alawady A, Altabtabae A, AlJamaan S, Devarajan S, AlShammari T, Eid MB, Matsuoka M, Jang H, Dupont CL, Freire M. Host-Microbiome Associations in Saliva Predict COVID-19 Severity. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.02.539155. [PMID: 37205528 PMCID: PMC10187185 DOI: 10.1101/2023.05.02.539155] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
Established evidence indicates that oral microbiota plays a crucial role in modulating host immune responses to viral infection. Following Severe Acute Respiratory Syndrome Coronavirus 2 - SARS-CoV-2 - there are coordinated microbiome and inflammatory responses within the mucosal and systemic compartments that are unknown. The specific roles that the oral microbiota and inflammatory cytokines play in the pathogenesis of COVID-19 are yet to be explored. We evaluated the relationships between the salivary microbiome and host parameters in different groups of COVID-19 severity based on their Oxygen requirement. Saliva and blood samples (n = 80) were collected from COVID-19 and from non-infected individuals. We characterized the oral microbiomes using 16S ribosomal RNA gene sequencing and evaluated saliva and serum cytokines using Luminex multiplex analysis. Alpha diversity of the salivary microbial community was negatively associated with COVID-19 severity. Integrated cytokine evaluations of saliva and serum showed that the oral host response was distinct from the systemic response. The hierarchical classification of COVID-19 status and respiratory severity using multiple modalities separately (i.e., microbiome, salivary cytokines, and systemic cytokines) and simultaneously (i.e., multi-modal perturbation analyses) revealed that the microbiome perturbation analysis was the most informative for predicting COVID-19 status and severity, followed by the multi-modal. Our findings suggest that oral microbiome and salivary cytokines may be predictive of COVID-19 status and severity, whereas atypical local mucosal immune suppression and systemic hyperinflammation provide new cues to understand the pathogenesis in immunologically naïve populations.
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Affiliation(s)
- Hend Alqedari
- Department of Oral Health Policy and Epidemiology, Harvard School of Dental Medicine, Boston, MA, 02115, USA; Dasman Diabetes Institute, Kuwait
- Dasman Diabetes Institute, 1180, Dasman, Kuwait
| | - Khaled Altabtbaei
- School of Dentistry, Faculty of Medicine and Dentistry. University of Alberta. Edmonton AB, T6G 2L7, Canada
| | - Josh L. Espinoza
- Department of Genomic Medicine and Infectious Diseases, J. Craig Venter Institute, La Jolla, CA 92037, USA
| | - Saadoun Bin-Hasan
- Department of Pediatrics, Farwaniyah Hospital, Ministry of Health, Kuwait
| | | | - Abdullah Alawady
- Department of Pediatrics, Farwaniyah Hospital, Ministry of Health, Kuwait
| | | | - Sarah AlJamaan
- Department of Pediatrics, Farwaniyah Hospital, Ministry of Health, Kuwait
| | | | | | - Mohammed Ben Eid
- Department of Pediatrics, Farwaniyah Hospital, Ministry of Health, Kuwait
| | - Michele Matsuoka
- Department of Genomic Medicine and Infectious Diseases, J. Craig Venter Institute, La Jolla, CA 92037, USA
| | - Hyesun Jang
- Department of Genomic Medicine and Infectious Diseases, J. Craig Venter Institute, La Jolla, CA 92037, USA
| | - Christopher L. Dupont
- Department of Genomic Medicine and Infectious Diseases, J. Craig Venter Institute, La Jolla, CA 92037, USA
| | - Marcelo Freire
- Department of Genomic Medicine and Infectious Diseases, J. Craig Venter Institute, La Jolla, CA 92037, USA
- Division of Infectious Diseases and Global Public Health Department of Medicine, University of California San Diego, La Jolla, CA, USA
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Espinoza JL, Torralba M, Leong P, Saffery R, Bockmann M, Kuelbs C, Singh S, Hughes T, Craig JM, Nelson KE, Dupont CL. Differential network analysis of oral microbiome metatranscriptomes identifies community scale metabolic restructuring in dental caries. PNAS NEXUS 2022; 1:pgac239. [PMID: 36712365 PMCID: PMC9802336 DOI: 10.1093/pnasnexus/pgac239] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Accepted: 10/14/2022] [Indexed: 11/05/2022]
Abstract
Dental caries is a microbial disease and the most common chronic health condition, affecting nearly 3.5 billion people worldwide. In this study, we used a multiomics approach to characterize the supragingival plaque microbiome of 91 Australian children, generating 658 bacterial and 189 viral metagenome-assembled genomes with transcriptional profiling and gene-expression network analysis. We developed a reproducible pipeline for clustering sample-specific genomes to integrate metagenomics and metatranscriptomics analyses regardless of biosample overlap. We introduce novel feature engineering and compositionally-aware ensemble network frameworks while demonstrating their utility for investigating regime shifts associated with caries dysbiosis. These methods can be applied when differential abundance modeling does not capture statistical enrichments or the results from such analysis are not adequate for providing deeper insight into disease. We identified which organisms and metabolic pathways were central in a coexpression network as well as how these networks were rewired between caries and caries-free phenotypes. Our findings provide evidence of a core bacterial microbiome that was transcriptionally active in the supragingival plaque of all participants regardless of phenotype, but also show highly diagnostic changes in the ways that organisms interact. Specifically, many organisms exhibit high connectedness with central carbon metabolism to Cardiobacterium and this shift serves a bridge between phenotypes. Our evidence supports the hypothesis that caries is a multifactorial ecological disease.
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Affiliation(s)
- Josh L Espinoza
- Department of Environment and Sustainability, J. Craig Venter Institute, La Jolla, CA 92037, USA,Department of Human Biology and Genomic Medicine, J. Craig Venter Institute, La Jolla, CA 92037, USA,Department of Human Biology and Genomic Medicine, J. Craig Venter Institute, Rockville, MD 20850, USA
| | - Manolito Torralba
- Department of Human Biology and Genomic Medicine, J. Craig Venter Institute, Rockville, MD 20850, USA
| | - Pamela Leong
- Epigenetics, Murdoch Children's Research Institute and Department of Paediatrics, The University of Melbourne, Parkville, VIC 3052, Australia
| | - Richard Saffery
- Epigenetics, Murdoch Children's Research Institute and Department of Paediatrics, The University of Melbourne, Parkville, VIC 3052, Australia
| | - Michelle Bockmann
- Adelaide Dental School, The University of Adelaide, Adelaide, SA 5005, Australia
| | - Claire Kuelbs
- Department of Human Biology and Genomic Medicine, J. Craig Venter Institute, La Jolla, CA 92037, USA
| | - Suren Singh
- Department of Human Biology and Genomic Medicine, J. Craig Venter Institute, Rockville, MD 20850, USA
| | - Toby Hughes
- Adelaide Dental School, The University of Adelaide, Adelaide, SA 5005, Australia
| | - Jeffrey M Craig
- Epigenetics, Murdoch Children's Research Institute and Department of Paediatrics, The University of Melbourne, Parkville, VIC 3052, Australia,IMPACT Strategic Research Centre, Deakin University School of Medicine, Geelong, VIC 3220, Australia
| | - Karen E Nelson
- Department of Human Biology and Genomic Medicine, J. Craig Venter Institute, La Jolla, CA 92037, USA,Department of Human Biology and Genomic Medicine, J. Craig Venter Institute, Rockville, MD 20850, USA
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12
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Espinoza JL, Dupont CL. VEBA: a modular end-to-end suite for in silico recovery, clustering, and analysis of prokaryotic, microeukaryotic, and viral genomes from metagenomes. BMC Bioinformatics 2022; 23:419. [PMID: 36224545 PMCID: PMC9554839 DOI: 10.1186/s12859-022-04973-8] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Accepted: 09/27/2022] [Indexed: 11/23/2022] Open
Abstract
BACKGROUND With the advent of metagenomics, the importance of microorganisms and how their interactions are relevant to ecosystem resilience, sustainability, and human health has become evident. Cataloging and preserving biodiversity is paramount not only for the Earth's natural systems but also for discovering solutions to challenges that we face as a growing civilization. Metagenomics pertains to the in silico study of all microorganisms within an ecological community in situ, however, many software suites recover only prokaryotes and have limited to no support for viruses and eukaryotes. RESULTS In this study, we introduce the Viral Eukaryotic Bacterial Archaeal (VEBA) open-source software suite developed to recover genomes from all domains. To our knowledge, VEBA is the first end-to-end metagenomics suite that can directly recover, quality assess, and classify prokaryotic, eukaryotic, and viral genomes from metagenomes. VEBA implements a novel iterative binning procedure and hybrid sample-specific/multi-sample framework that yields more genomes than any existing methodology alone. VEBA includes a consensus microeukaryotic database containing proteins from existing databases to optimize microeukaryotic gene modeling and taxonomic classification. VEBA also provides a unique clustering-based dereplication strategy allowing for sample-specific genomes and genes to be directly compared across non-overlapping biological samples. Finally, VEBA is the only pipeline that automates the detection of candidate phyla radiation bacteria and implements the appropriate genome quality assessments. VEBA's capabilities are demonstrated by reanalyzing 3 existing public datasets which recovered a total of 948 MAGs (458 prokaryotic, 8 eukaryotic, and 482 viral) including several uncharacterized organisms and organisms with no public genome representatives. CONCLUSIONS The VEBA software suite allows for the in silico recovery of microorganisms from all domains of life by integrating cutting edge algorithms in novel ways. VEBA fully integrates both end-to-end and task-specific metagenomic analysis in a modular architecture that minimizes dependencies and maximizes productivity. The contributions of VEBA to the metagenomics community includes seamless end-to-end metagenomics analysis but also provides users with the flexibility to perform specific analytical tasks. VEBA allows for the automation of several metagenomics steps and shows that new information can be recovered from existing datasets.
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Affiliation(s)
- Josh L. Espinoza
- Department of Environment and Sustainability, J. Craig Venter Institute, 4120 Capricorn Ln, La Jolla, CA 92037 USA
- Department of Human Biology and Genomic Medicine, J. Craig Venter Institute, La Jolla, CA 92037 USA
| | - Chris L. Dupont
- Department of Environment and Sustainability, J. Craig Venter Institute, 4120 Capricorn Ln, La Jolla, CA 92037 USA
- Department of Human Biology and Genomic Medicine, J. Craig Venter Institute, La Jolla, CA 92037 USA
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13
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Warrier T, Romano KP, Clatworthy AE, Hung DT. Integrated genomics and chemical biology herald an era of sophisticated antibacterial discovery, from defining essential genes to target elucidation. Cell Chem Biol 2022; 29:716-729. [PMID: 35523184 PMCID: PMC9893512 DOI: 10.1016/j.chembiol.2022.04.006] [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: 12/14/2021] [Revised: 03/08/2022] [Accepted: 04/18/2022] [Indexed: 02/04/2023]
Abstract
The golden age of antibiotic discovery in the 1940s-1960s saw the development and deployment of many different classes of antibiotics, revolutionizing the field of medicine. Since that time, our ability to discover antibiotics of novel structural classes or mechanisms has not kept pace with the ever-growing threat of antibiotic resistance. Recently, advances at the intersection of genomics and chemical biology have enabled efforts to better define the vulnerabilities of essential gene targets, to develop sophisticated whole-cell chemical screening methods that reveal target biology early, and to elucidate small molecule targets and modes of action more effectively. These new technologies have the potential to expand the chemical diversity of antibiotic candidates, as well as the breadth of targets. We illustrate how the latest tools of genomics and chemical biology are being integrated to better understand pathogen vulnerabilities and antibiotic mechanisms in order to inform a new era of antibiotic discovery.
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Affiliation(s)
- Thulasi Warrier
- Department of Molecular Biology and Center for Computational and Integrative Biology, Massachusetts General Hospital, Boston, MA 02114, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Keith P Romano
- Department of Molecular Biology and Center for Computational and Integrative Biology, Massachusetts General Hospital, Boston, MA 02114, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA 02115, USA
| | - Anne E Clatworthy
- Department of Molecular Biology and Center for Computational and Integrative Biology, Massachusetts General Hospital, Boston, MA 02114, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Deborah T Hung
- Department of Molecular Biology and Center for Computational and Integrative Biology, Massachusetts General Hospital, Boston, MA 02114, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
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Abstract
With the overmining of actinomycetes for compounds acting against Gram-negative pathogens, recent efforts to discover novel antibiotics have been focused on other groups of bacteria. Teixobactin, the first antibiotic without detectable resistance that binds lipid II, comes from an uncultured Eleftheria terra, a betaproteobacterium; odilorhabdins, from Xenorhabdus, are broad-spectrum inhibitors of protein synthesis, and darobactins from Photorhabdus target BamA, the essential chaperone of the outer membrane of Gram-negative bacteria. Xenorhabdus and Photorhabdus are symbionts of the nematode gut microbiome and attractive producers of secondary metabolites. Only small portions of their biosynthetic gene clusters (BGC) are expressed in vitro. To access their silent operons, we first separated extracts from a small library of isolates into fractions, resulting in 200-fold concentrated material, and then screened them for antimicrobial activity. This resulted in a hit with selective activity against Escherichia coli, which we identified as a novel natural product antibiotic, 3′-amino 3′-deoxyguanosine (ADG). Mutants resistant to ADG mapped to gsk and gmk, kinases of guanosine. Biochemical analysis shows that ADG is a prodrug that is converted into an active ADG triphosphate (ADG-TP), a mimic of GTP. ADG incorporates into a growing RNA chain, interrupting transcription, and inhibits cell division, apparently by interfering with the GTPase activity of FtsZ. Gsk of the purine salvage pathway, which is the first kinase in the sequential phosphorylation of ADG, is restricted to E. coli and closely related species, explaining the selectivity of the compound. There are probably numerous targets of ADG-TP among GTP-dependent proteins. The discovery of ADG expands our knowledge of prodrugs, which are rare among natural compounds.
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Abstract
Despite the ever-growing antibiotic resistance crisis, the rate at which new antimicrobials are being discovered and approved for human use has rapidly declined over the past 75 years. A barrier for advancing newly identified antibiotics beyond discovery is elucidating their mechanism(s) of action.
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Nabwera HM, Espinoza JL, Worwui A, Betts M, Okoi C, Sesay AK, Bancroft R, Agbla SC, Jarju S, Bradbury RS, Colley M, Jallow AT, Liu J, Houpt ER, Prentice AM, Antonio M, Bernstein RM, Dupont CL, Kwambana-Adams BA. Interactions between fecal gut microbiome, enteric pathogens, and energy regulating hormones among acutely malnourished rural Gambian children. EBioMedicine 2021; 73:103644. [PMID: 34695658 PMCID: PMC8550991 DOI: 10.1016/j.ebiom.2021.103644] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Revised: 10/06/2021] [Accepted: 10/07/2021] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND The specific roles that gut microbiota, known pathogens, and host energy-regulating hormones play in the pathogenesis of non-edematous severe acute malnutrition (marasmus SAM) and moderate acute malnutrition (MAM) during outpatient nutritional rehabilitation are yet to be explored. METHODS We applied an ensemble of sample-specific (intra- and inter-modality) association networks to gain deeper insights into the pathogenesis of acute malnutrition and its severity among children under 5 years of age in rural Gambia, where marasmus SAM is most prevalent. FINDINGS Children with marasmus SAM have distinct microbiome characteristics and biologically-relevant multimodal biomarkers not observed among children with moderate acute malnutrition. Marasmus SAM was characterized by lower microbial richness and biomass, significant enrichments in Enterobacteriaceae, altered interactions between specific Enterobacteriaceae and key energy regulating hormones and their receptors. INTERPRETATION Our findings suggest that marasmus SAM is characterized by the collapse of a complex system with nested interactions and key associations between the gut microbiome, enteric pathogens, and energy regulating hormones. Further exploration of these systems will help inform innovative preventive and therapeutic interventions. FUNDING The work was supported by the UK Medical Research Council (MRC; MC-A760-5QX00) and the UK Department for International Development (DFID) under the MRC/DFID Concordat agreement; Bill and Melinda Gates Foundation (OPP 1066932) and the National Institute of Medical Research (NIMR), UK. This network analysis was supported by NIH U54GH009824 [CLD] and NSF OCE-1558453 [CLD].
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Affiliation(s)
- Helen M Nabwera
- Department of Clinical Sciences, Liverpool School of Tropical Medicine, Liverpool, L3 5QA, UK
| | - Josh L Espinoza
- J. Craig Venture Institute, 4120 Capricorn Ln, La Jolla, CA 92037, USA; Applied Sciences, Durban University of Technology, Durban, South Africa
| | - Archibald Worwui
- Medical Research Council Unit The Gambia at London School of Hygiene and Tropical Medicine, Fajara, Banjul, PO Box 273, The Gambia
| | - Modupeh Betts
- NIHR Global Health Research Unit on Mucosal Pathogens, Division of Infection and Immunity, University College London, London, United Kingdom
| | - Catherine Okoi
- Medical Research Council Unit The Gambia at London School of Hygiene and Tropical Medicine, Fajara, Banjul, PO Box 273, The Gambia
| | - Abdul K Sesay
- Medical Research Council Unit The Gambia at London School of Hygiene and Tropical Medicine, Fajara, Banjul, PO Box 273, The Gambia
| | - Rowan Bancroft
- Medical Research Council Unit The Gambia at London School of Hygiene and Tropical Medicine, Fajara, Banjul, PO Box 273, The Gambia
| | - Schadrac C Agbla
- Department of Health Data Science, University of Liverpool, Liverpool, UK
| | - Sheikh Jarju
- Medical Research Council Unit The Gambia at London School of Hygiene and Tropical Medicine, Fajara, Banjul, PO Box 273, The Gambia
| | | | - Mariama Colley
- Medical Research Council Unit The Gambia at London School of Hygiene and Tropical Medicine, Fajara, Banjul, PO Box 273, The Gambia
| | - Amadou T Jallow
- Medical Research Council Unit The Gambia at London School of Hygiene and Tropical Medicine, Fajara, Banjul, PO Box 273, The Gambia
| | - Jie Liu
- Division of Infectious Diseases and International Health, Department of Medicine, University of Virginia, Charlottesville, Virginia, United States of America
| | - Eric R Houpt
- Division of Infectious Diseases and International Health, Department of Medicine, University of Virginia, Charlottesville, Virginia, United States of America
| | - Andrew M Prentice
- Medical Research Council Unit The Gambia at London School of Hygiene and Tropical Medicine, Fajara, Banjul, PO Box 273, The Gambia
| | - Martin Antonio
- Medical Research Council Unit The Gambia at London School of Hygiene and Tropical Medicine, Fajara, Banjul, PO Box 273, The Gambia; Department of Infection Biology, Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, UK
| | - Robin M Bernstein
- Growth and Development Lab, Department of Anthropology, University of Colorado, Boulder, CO, United States of America
| | | | - Brenda A Kwambana-Adams
- NIHR Global Health Research Unit on Mucosal Pathogens, Division of Infection and Immunity, University College London, London, United Kingdom.
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Type III secretion system effector subnetworks elicit distinct host immune responses to infection. Curr Opin Microbiol 2021; 64:19-26. [PMID: 34537517 DOI: 10.1016/j.mib.2021.08.008] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2021] [Revised: 08/26/2021] [Accepted: 08/27/2021] [Indexed: 01/18/2023]
Abstract
Citrobacter rodentium, a natural mouse pathogen which colonises the colon of immuno-competent mice, provides a robust model for interrogating host-pathogen-microbiota interactions in vivo. This model has been key to providing new insights into local host responses to enteric infection, including changes in intestinal epithelial cell immunometabolism and mucosal immunity. C. rodentium injects 31 bacterial effectors into epithelial cells via a type III secretion system (T3SS). Recently, these effectors were shown to be able to form multiple intracellular subnetworks which can withstand significant contractions whilst maintaining virulence. Here we highlight recent advances in understanding gut mucosal responses to infection and effector biology, as well as potential uses for artificial intelligence (AI) in understanding infectious disease and speculate on the role of T3SS effector networks in host adaption.
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