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Hameed T, Motsi N, Bignell E, Tanaka RJ. Inferring fungal growth rates from optical density data. PLoS Comput Biol 2024; 20:e1012105. [PMID: 38753887 PMCID: PMC11098479 DOI: 10.1371/journal.pcbi.1012105] [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: 11/22/2023] [Accepted: 04/24/2024] [Indexed: 05/18/2024] Open
Abstract
Quantifying fungal growth underpins our ability to effectively treat severe fungal infections. Current methods quantify fungal growth rates from time-course morphology-specific data, such as hyphal length data. However, automated large-scale collection of such data lies beyond the scope of most clinical microbiology laboratories. In this paper, we propose a mathematical model of fungal growth to estimate morphology-specific growth rates from easy-to-collect, but indirect, optical density (OD600) data of Aspergillus fumigatus growth (filamentous fungus). Our method accounts for OD600 being an indirect measure by explicitly including the relationship between the indirect OD600 measurements and the calibrating true fungal growth in the model. Therefore, the method does not require de novo generation of calibration data. Our model outperformed reference models at fitting to and predicting OD600 growth curves and overcame observed discrepancies between morphology-specific rates inferred from OD600 versus directly measured data in reference models that did not include calibration.
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Affiliation(s)
- Tara Hameed
- Department of Bioengineering, Imperial College London, London, United Kingdom
| | - Natasha Motsi
- Department of Bioengineering, Imperial College London, London, United Kingdom
| | - Elaine Bignell
- Medical Research Council Centre for Medical Mycology, University of Exeter, Exeter, United Kingdom
| | - Reiko J. Tanaka
- Department of Bioengineering, Imperial College London, London, United Kingdom
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Miyazawa K, Umeyama T, Takatsuka S, Muraosa Y, Hoshino Y, Yano S, Abe K, Miyazaki Y. Real-time monitoring of mycelial growth in liquid culture using hyphal dispersion mutant of Aspergillus fumigatus. Med Mycol 2024; 62:myae011. [PMID: 38429972 DOI: 10.1093/mmy/myae011] [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: 11/02/2023] [Revised: 01/29/2024] [Accepted: 02/29/2024] [Indexed: 03/03/2024] Open
Abstract
Hyphal pellet formation by Aspergillus species in liquid cultures is one of the main obstacles to high-throughput anti-Aspergillus reagent screening. We previously constructed a hyphal dispersion mutant of Aspergillus fumigatus by disrupting the genes encoding the primary cell wall α-1,3-glucan synthase Ags1 and putative galactosaminogalactan synthase Gtb3 (Δags1Δgtb3). Mycelial growth of the mutant in liquid cultures monitored by optical density was reproducible, and the dose-response of hyphal growth to antifungal agents has been quantified by optical density. However, Δags1Δgtb3 still forms hyphal pellets in some rich growth media. Here, we constructed a disruptant lacking all three α-1,3-glucan synthases and galactosaminogalactan synthase (Δags1Δags2Δags3Δgtb3), and confirmed that its hyphae were dispersed in all the media tested. We established an automatic method to monitor hyphal growth of the mutant in a 24-well plate shaken with a real-time plate reader. Dose-dependent growth suppression and unique growth responses to antifungal agents (voriconazole, amphotericin B, and micafungin) were clearly observed. A 96-well plate was also found to be useful for the evaluation of mycelial growth by optical density. Our method is potentially applicable to high-throughput screening for anti-Aspergillus agents.
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Affiliation(s)
- Ken Miyazawa
- Department of Fungal Infection, National Institute of Infectious Diseases, Tokyo, Japan
| | - Takashi Umeyama
- Department of Fungal Infection, National Institute of Infectious Diseases, Tokyo, Japan
| | - Shogo Takatsuka
- Department of Fungal Infection, National Institute of Infectious Diseases, Tokyo, Japan
| | - Yasunori Muraosa
- Department of Fungal Infection, National Institute of Infectious Diseases, Tokyo, Japan
| | - Yasutaka Hoshino
- Department of Fungal Infection, National Institute of Infectious Diseases, Tokyo, Japan
| | - Shigekazu Yano
- Graduate School of Sciences and Engineering, Yamagata University, Yonezawa, Japan
| | - Keietsu Abe
- Graduate School of Agricultural Science, Tohoku University, Sendai, Japan
| | - Yoshitsugu Miyazaki
- Department of Fungal Infection, National Institute of Infectious Diseases, Tokyo, Japan
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Huo Y, Li H, Wang X, Du X, Swain PS. Nunchaku: optimally partitioning data into piece-wise contiguous segments. Bioinformatics 2023; 39:btad688. [PMID: 37966918 PMCID: PMC10697733 DOI: 10.1093/bioinformatics/btad688] [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: 06/08/2023] [Revised: 11/06/2023] [Accepted: 11/14/2023] [Indexed: 11/17/2023] Open
Abstract
MOTIVATION When analyzing 1D time series, scientists are often interested in identifying regions where one variable depends linearly on the other. Typically, they use an ad hoc and therefore often subjective method to do so. RESULTS Here, we develop a statistically rigorous, Bayesian approach to infer the optimal partitioning of a dataset not only into contiguous piece-wise linear segments, but also into contiguous segments described by linear combinations of arbitrary basis functions. We therefore present a general solution to the problem of identifying discontinuous change points. Focusing on microbial growth, we use the algorithm to find the range of optical density where this density is linearly proportional to the number of cells and to automatically find the regions of exponential growth for both Escherichia coli and Saccharomyces cerevisiae. For budding yeast, we consequently are able to infer the Monod constant for growth on fructose. Our algorithm lends itself to automation and high throughput studies, increases reproducibility, and should facilitate data analyses for a broad range of scientists. AVAILABILITY AND IMPLEMENTATION The corresponding Python package, entitled Nunchaku, is available at PyPI: https://pypi.org/project/nunchaku.
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Affiliation(s)
- Yu Huo
- Centre for Engineering Biology, University of Edinburgh, Edinburgh EH9 3BF, United Kingdom
- School of Biological Sciences, University of Edinburgh, Edinburgh EH9 3BF, United Kingdom
| | - Hongpei Li
- School of Biological Sciences, University of Edinburgh, Edinburgh EH9 3BF, United Kingdom
| | - Xiao Wang
- School of Biological Sciences, University of Edinburgh, Edinburgh EH9 3BF, United Kingdom
| | - Xiaochen Du
- School of Biological Sciences, University of Edinburgh, Edinburgh EH9 3BF, United Kingdom
| | - Peter S Swain
- Centre for Engineering Biology, University of Edinburgh, Edinburgh EH9 3BF, United Kingdom
- School of Biological Sciences, University of Edinburgh, Edinburgh EH9 3BF, United Kingdom
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Woodrow C, Rosca AT, Fletcher R, Hone A, Ruta M, Hamer KC, Dunn JC. Haemoproteus parasites and passerines: the effect of local generalists on inferences of host-parasite co-phylogeny in the British Isles. Parasitology 2023; 150:1307-1315. [PMID: 37395052 PMCID: PMC10941225 DOI: 10.1017/s0031182023000628] [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: 07/09/2021] [Revised: 06/15/2023] [Accepted: 06/26/2023] [Indexed: 07/04/2023]
Abstract
Host–parasite associations provide a benchmark for investigating evolutionary arms races and antagonistic coevolution. However, potential ecological mechanisms underlying such associations are difficult to unravel. In particular, local adaptations of hosts and/or parasites may hamper reliable inferences of host–parasite relationships and the specialist–generalist definitions of parasite lineages, making it problematic to understand such relationships on a global scale. Phylogenetic methods were used to investigate co-phylogenetic patterns between vector-borne parasites of the genus Haemoproteus and their passeriform hosts, to infer the ecological interactions of parasites and hosts that may have driven the evolution of both groups in a local geographic domain. As several Haemoproteus lineages were only detected once, and given the occurrence of a single extreme generalist, the effect of removing individual lineages on the co-phylogeny pattern was tested. When all lineages were included, and when all singly detected lineages were removed, there was no convincing evidence for host–parasite co-phylogeny. However, when only the generalist lineage was removed, strong support for co-phylogeny was indicated, and ecological interactions could be successfully inferred. This study exemplifies the importance of identifying locally abundant lineages when sampling host–parasite systems, to provide reliable insights into the precise mechanisms underlying host–parasite interactions.
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Affiliation(s)
- Charlie Woodrow
- Joseph Banks Laboratories, School of Life Sciences, University of Lincoln, Green Lane, Lincoln LN6 7DL, UK
| | - Adina Teodora Rosca
- Joseph Banks Laboratories, School of Life Sciences, University of Lincoln, Green Lane, Lincoln LN6 7DL, UK
| | - Rachel Fletcher
- Joseph Banks Laboratories, School of Life Sciences, University of Lincoln, Green Lane, Lincoln LN6 7DL, UK
| | - Abigail Hone
- Joseph Banks Laboratories, School of Life Sciences, University of Lincoln, Green Lane, Lincoln LN6 7DL, UK
| | - Marcello Ruta
- Joseph Banks Laboratories, School of Life Sciences, University of Lincoln, Green Lane, Lincoln LN6 7DL, UK
| | - Keith C Hamer
- School of Biology, University of Leeds, Clarendon Way, Leeds LS2 9JT, UK
| | - Jenny Claire Dunn
- Joseph Banks Laboratories, School of Life Sciences, University of Lincoln, Green Lane, Lincoln LN6 7DL, UK
- School of Biology, University of Leeds, Clarendon Way, Leeds LS2 9JT, UK
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Scott J, Valero C, Mato-López Á, Donaldson IJ, Roldán A, Chown H, Van Rhijn N, Lobo-Vega R, Gago S, Furukawa T, Morogovsky A, Ben Ami R, Bowyer P, Osherov N, Fontaine T, Goldman GH, Mellado E, Bromley M, Amich J. Aspergillus fumigatus Can Display Persistence to the Fungicidal Drug Voriconazole. Microbiol Spectr 2023; 11:e0477022. [PMID: 36912663 PMCID: PMC10100717 DOI: 10.1128/spectrum.04770-22] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Accepted: 02/12/2023] [Indexed: 03/14/2023] Open
Abstract
Aspergillus fumigatus is a filamentous fungus that can infect the lungs of patients with immunosuppression and/or underlying lung diseases. The mortality associated with chronic and invasive aspergillosis infections remain very high, despite availability of antifungal treatments. In the last decade, there has been a worrisome emergence and spread of resistance to the first-line antifungals, the azoles. The mortality caused by resistant isolates is even higher, and patient management is complicated as the therapeutic options are reduced. Nevertheless, treatment failure is also common in patients infected with azole-susceptible isolates, which can be due to several non-mutually exclusive reasons, such as poor drug absorption. In addition, the phenomena of tolerance or persistence, where susceptible pathogens can survive the action of an antimicrobial for extended periods, have been associated with treatment failure in bacterial infections, and their occurrence in fungal infections already proposed. Here, we demonstrate that some isolates of A. fumigatus display persistence to voriconazole. A subpopulation of the persister isolates can survive for extended periods and even grow at low rates in the presence of supra-MIC of voriconazole and seemingly other azoles. Persistence cannot be eradicated with adjuvant drugs or antifungal combinations and seemed to reduce the efficacy of treatment for certain individuals in a Galleria mellonella model of infection. Furthermore, persistence implies a distinct transcriptional profile, demonstrating that it is an active response. We propose that azole persistence might be a relevant and underestimated factor that could influence the outcome of infection in human aspergillosis. IMPORTANCE The phenomena of antibacterial tolerance and persistence, where pathogenic microbes can survive for extended periods in the presence of cidal drug concentrations, have received significant attention in the last decade. Several mechanisms of action have been elucidated, and their relevance for treatment failure in bacterial infections demonstrated. In contrast, our knowledge of antifungal tolerance and, in particular, persistence is still very limited. In this study, we have characterized the response of the prominent fungal pathogen Aspergillus fumigatus to the first-line therapy antifungal voriconazole. We comprehensively show that some isolates display persistence to this fungicidal antifungal and propose various potential mechanisms of action. In addition, using an alternative model of infection, we provide initial evidence to suggest that persistence may cause treatment failure in some individuals. Therefore, we propose that azole persistence is an important factor to consider and further investigate in A. fumigatus.
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Affiliation(s)
- Jennifer Scott
- Manchester Fungal Infection Group, Division of Evolution, Infection, and Genomics, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom
| | - Clara Valero
- Manchester Fungal Infection Group, Division of Evolution, Infection, and Genomics, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom
- Faculdade de Ciências Farmacêuticas de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, Brazil
| | - Álvaro Mato-López
- Mycology Reference Laboratory (Laboratorio de Referencia e Investigación en Micología [LRIM]), National Centre for Microbiology, Instituto de Salud Carlos III (ISCIII), Majadahonda, Madrid, Spain
| | - Ian J. Donaldson
- Bioinformatics Core Facility, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom
| | - Alejandra Roldán
- Mycology Reference Laboratory (Laboratorio de Referencia e Investigación en Micología [LRIM]), National Centre for Microbiology, Instituto de Salud Carlos III (ISCIII), Majadahonda, Madrid, Spain
| | - Harry Chown
- Manchester Fungal Infection Group, Division of Evolution, Infection, and Genomics, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom
| | - Norman Van Rhijn
- Manchester Fungal Infection Group, Division of Evolution, Infection, and Genomics, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom
| | - Rebeca Lobo-Vega
- Mycology Reference Laboratory (Laboratorio de Referencia e Investigación en Micología [LRIM]), National Centre for Microbiology, Instituto de Salud Carlos III (ISCIII), Majadahonda, Madrid, Spain
| | - Sara Gago
- Manchester Fungal Infection Group, Division of Evolution, Infection, and Genomics, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom
| | - Takanori Furukawa
- Manchester Fungal Infection Group, Division of Evolution, Infection, and Genomics, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom
| | - Alma Morogovsky
- Department of Clinical Microbiology and Immunology, Sackler School of Medicine Ramat-Aviv, Tel-Aviv, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Ronen Ben Ami
- Department of Clinical Microbiology and Immunology, Sackler School of Medicine Ramat-Aviv, Tel-Aviv, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Paul Bowyer
- Manchester Fungal Infection Group, Division of Evolution, Infection, and Genomics, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom
| | - Nir Osherov
- Department of Clinical Microbiology and Immunology, Sackler School of Medicine Ramat-Aviv, Tel-Aviv, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Thierry Fontaine
- Institut Pasteur, Université de Paris, INRAE, USC2019, Unité Biologie et Pathogénicité Fongiques, Paris, France
| | - Gustavo H. Goldman
- Faculdade de Ciências Farmacêuticas de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, Brazil
| | - Emilia Mellado
- Mycology Reference Laboratory (Laboratorio de Referencia e Investigación en Micología [LRIM]), National Centre for Microbiology, Instituto de Salud Carlos III (ISCIII), Majadahonda, Madrid, Spain
- CiberInfec ISCIII, CIBER en Enfermedades Infecciosas, Instituto de Salud Carlos III, Majadahonda, Madrid, Spain
| | - Michael Bromley
- Manchester Fungal Infection Group, Division of Evolution, Infection, and Genomics, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom
| | - Jorge Amich
- Manchester Fungal Infection Group, Division of Evolution, Infection, and Genomics, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom
- Mycology Reference Laboratory (Laboratorio de Referencia e Investigación en Micología [LRIM]), National Centre for Microbiology, Instituto de Salud Carlos III (ISCIII), Majadahonda, Madrid, Spain
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