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Gaëtan J, Halary S, Millet M, Bernard C, Duval C, Hamlaoui S, Hecquet A, Gugger M, Marie B, Mehta N, Moreira D, Skouri-Panet F, Travert C, Duprat E, Leloup J, Benzerara K. Widespread formation of intracellular calcium carbonates by the bloom-forming cyanobacterium Microcystis. Environ Microbiol 2023; 25:751-765. [PMID: 36550062 DOI: 10.1111/1462-2920.16322] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Accepted: 12/15/2022] [Indexed: 12/24/2022]
Abstract
The formation of intracellular amorphous calcium carbonates (iACC) has been recently observed in a few cultured strains of Microcystis, a potentially toxic bloom-forming cyanobacterium found worldwide in freshwater ecosystems. If iACC-forming Microcystis are abundant within blooms, they may represent a significant amount of particulate Ca. Here, we investigate the significance of iACC biomineralization by Microcystis. First, the presence of iACC-forming Microcystis cells has been detected in several eutrophic lakes, indicating that this phenomenon occurs under environmental conditions. Second, some genotypic (presence/absence of ccyA, a marker gene of iACC biomineralization) and phenotypic (presence/absence of iACC) diversity have been detected within a collection of strains isolated from one single lake. This illustrates that this trait is frequent but also variable within Microcystis even at a single locality. Finally, one-third of publicly available genomes of Microcystis were shown to contain the ccyA gene, revealing a wide geographic and phylogenetic distribution within the genus. Overall, the present work shows that the formation of iACC by Microcystis is common under environmental conditions. While its biological function remains undetermined, this process should be further considered regarding the biology of Microcystis and implications on the Ca geochemical cycle in freshwater environments.
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Affiliation(s)
- Juliette Gaëtan
- Sorbonne Université, Muséum National d'Histoire Naturelle, UMR CNRS-SU-MNHN 7590, Institut de Minéralogie, de Physique des Matériaux et de Cosmochimie (IMPMC), Paris, France
- Sorbonne Université, UMR 7618 CNRS-INRA-IRD-Paris 7-UPEC, Institut d'Ecologie et des Sciences de l'Environnement de Paris (iEES-Paris), Paris, France
| | - Sébastien Halary
- Muséum National d'Histoire Naturelle, UMR 7245 CNRS-MNHN, Molécules de Communication et Adaptation des Microorganismes, Paris, France
| | - Maxime Millet
- Sorbonne Université, Muséum National d'Histoire Naturelle, UMR CNRS-SU-MNHN 7590, Institut de Minéralogie, de Physique des Matériaux et de Cosmochimie (IMPMC), Paris, France
| | - Cécile Bernard
- Muséum National d'Histoire Naturelle, UMR 7245 CNRS-MNHN, Molécules de Communication et Adaptation des Microorganismes, Paris, France
| | - Charlotte Duval
- Muséum National d'Histoire Naturelle, UMR 7245 CNRS-MNHN, Molécules de Communication et Adaptation des Microorganismes, Paris, France
| | - Sahima Hamlaoui
- Muséum National d'Histoire Naturelle, UMR 7245 CNRS-MNHN, Molécules de Communication et Adaptation des Microorganismes, Paris, France
| | - Amandine Hecquet
- Sorbonne Université, UMR 7618 CNRS-INRA-IRD-Paris 7-UPEC, Institut d'Ecologie et des Sciences de l'Environnement de Paris (iEES-Paris), Paris, France
| | - Muriel Gugger
- Institut Pasteur, Université Paris Cité, Collection of Cyanobacteria, Paris, France
| | - Benjamin Marie
- Muséum National d'Histoire Naturelle, UMR 7245 CNRS-MNHN, Molécules de Communication et Adaptation des Microorganismes, Paris, France
| | - Neha Mehta
- Sorbonne Université, Muséum National d'Histoire Naturelle, UMR CNRS-SU-MNHN 7590, Institut de Minéralogie, de Physique des Matériaux et de Cosmochimie (IMPMC), Paris, France
| | - David Moreira
- Unité d'Ecologie Systématique et Evolution, CNRS, Université Paris-Saclay, AgroParisTech, Gif-sur-Yvette, France
| | - Fériel Skouri-Panet
- Sorbonne Université, Muséum National d'Histoire Naturelle, UMR CNRS-SU-MNHN 7590, Institut de Minéralogie, de Physique des Matériaux et de Cosmochimie (IMPMC), Paris, France
| | - Cynthia Travert
- Sorbonne Université, Muséum National d'Histoire Naturelle, UMR CNRS-SU-MNHN 7590, Institut de Minéralogie, de Physique des Matériaux et de Cosmochimie (IMPMC), Paris, France
| | - Elodie Duprat
- Sorbonne Université, Muséum National d'Histoire Naturelle, UMR CNRS-SU-MNHN 7590, Institut de Minéralogie, de Physique des Matériaux et de Cosmochimie (IMPMC), Paris, France
| | - Julie Leloup
- Sorbonne Université, UMR 7618 CNRS-INRA-IRD-Paris 7-UPEC, Institut d'Ecologie et des Sciences de l'Environnement de Paris (iEES-Paris), Paris, France
| | - Karim Benzerara
- Sorbonne Université, Muséum National d'Histoire Naturelle, UMR CNRS-SU-MNHN 7590, Institut de Minéralogie, de Physique des Matériaux et de Cosmochimie (IMPMC), Paris, France
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Murugaiyah V, Mattson MP. Neurohormetic phytochemicals: An evolutionary-bioenergetic perspective. Neurochem Int 2015; 89:271-80. [PMID: 25861940 DOI: 10.1016/j.neuint.2015.03.009] [Citation(s) in RCA: 40] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2015] [Revised: 03/20/2015] [Accepted: 03/26/2015] [Indexed: 12/25/2022]
Abstract
The impact of dietary factors on brain health and vulnerability to disease is increasingly appreciated. The results of epidemiological studies, and intervention trials in animal models suggest that diets rich in phytochemicals can enhance neuroplasticity and resistance to neurodegeneration. Here we describe how interactions of plants and animals during their co-evolution, and resulting reciprocal adaptations, have shaped the remarkable characteristics of phytochemicals and their effects on the physiology of animal cells in general, and neurons in particular. Survival advantages were conferred upon plants capable of producing noxious bitter-tasting chemicals, and on animals able to tolerate the phytochemicals and consume the plants as an energy source. The remarkably diverse array of phytochemicals present in modern fruits, vegetables spices, tea and coffee may have arisen, in part, from the acquisition of adaptive cellular stress responses and detoxification enzymes in animals that enabled them to consume plants containing potentially toxic chemicals. Interestingly, some of the same adaptive stress response mechanisms that protect neurons against noxious phytochemicals are also activated by dietary energy restriction and vigorous physical exertion, two environmental challenges that shaped brain evolution. In this perspective article, we describe some of the signaling pathways relevant to cellular energy metabolism that are modulated by 'neurohormetic phytochemicals' (potentially toxic chemicals produced by plants that have beneficial effects on animals when consumed in moderate amounts). We highlight the cellular bioenergetics-related sirtuin, adenosine monophosphate activated protein kinase (AMPK), mammalian target of rapamycin (mTOR) and insulin-like growth factor 1 (IGF-1) pathways. The inclusion of dietary neurohormetic phytochemicals in an overall program for brain health that also includes exercise and energy restriction may find applications in the prevention and treatment of a range of neurological disorders.
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Affiliation(s)
- Vikneswaran Murugaiyah
- School of Pharmaceutical Sciences, Universiti Sains Malaysia, 11800, Pulau Pinang, Malaysia
| | - Mark P Mattson
- Laboratory of Neurosciences, National Institute on Aging Intramural Research Program, Baltimore, MD 21224, USA.
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Ochoa D, Pazos F. Practical aspects of protein co-evolution. Front Cell Dev Biol 2014; 2:14. [PMID: 25364721 PMCID: PMC4207036 DOI: 10.3389/fcell.2014.00014] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2014] [Accepted: 04/02/2014] [Indexed: 11/15/2022] Open
Abstract
Co-evolution is a fundamental aspect of Evolutionary Theory. At the molecular level, co-evolutionary linkages between protein families have been used as indicators of protein interactions and functional relationships from long ago. Due to the complexity of the problem and the amount of genomic data required for these approaches to achieve good performances, it took a relatively long time from the appearance of the first ideas and concepts to the quotidian application of these approaches and their incorporation to the standard toolboxes of bioinformaticians and molecular biologists. Today, these methodologies are mature (both in terms of performance and usability/implementation), and the genomic information that feeds them large enough to allow their general application. This review tries to summarize the current landscape of co-evolution-based methodologies, with a strong emphasis on describing interesting cases where their application to important biological systems, alone or in combination with other computational and experimental approaches, allowed getting new insight into these.
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Affiliation(s)
- David Ochoa
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI) Hinxton, UK
| | - Florencio Pazos
- Computational Systems Biology Group, National Centre for Biotechnology (CNB-CSIC) Madrid, Spain
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Tiwary BK. The coordinated expression, interaction and evolution of the neuroendocrine genes. Integr Biol (Camb) 2012; 4:1377-85. [PMID: 22990097 DOI: 10.1039/c2ib20081c] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
The neuroendocrine system is a complex biological system controlled by various neuropeptides and hormones. The evolution and network properties of neuroendocrine genes are analyzed along with their expression profiles. The neuroendocrine genes show very similar expression profiles and local network properties across a wide range of tissues consistent with the physiological roles of their proteins. Moreover, the coordinated evolution of 10 neuroendocrine genes involved in mammalian reproduction and homeostasis is demonstrated using several methods, such as correlated evolution, relative-rate test, relative-ratio test and codon usage bias. The neuroendocrine genes seem to evolve predominantly under similar selective strengths and regimes of purifying selection, which is well reflected in their evolutionary fingerprints. This result demonstrates for the first time a key role of natural selection in creating and maintaining a well-designed neuroendocrine system at the genomic level. It also indicates that component properties of a complex system at a higher physiological scale may determine component properties at a lower genomic scale and/or vice versa.
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Affiliation(s)
- Basant K Tiwary
- Centre for Bioinformatics, School of Life Sciences, Pondicherry University, Pondicherry-605 014, India.
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Rorick M. Quantifying protein modularity and evolvability: a comparison of different techniques. Biosystems 2012; 110:22-33. [PMID: 22796584 DOI: 10.1016/j.biosystems.2012.06.006] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2011] [Revised: 06/20/2012] [Accepted: 06/27/2012] [Indexed: 10/28/2022]
Abstract
Modularity increases evolvability by reducing constraints on adaptation and by allowing preexisting parts to function in new contexts for novel uses. Protein evolution provides an excellent context to study the causes and consequences of biological modularity. In order to address such questions, however, an index for protein modularity is necessary. This paper proposes a simple index for protein modularity-"module density"-which is the number of evolutionarily independent modules that compose a protein divided by the number of amino acids in the protein. The decomposition of proteins into constituent modules can be accomplished by either of two classes of methods. The first class of methods relies on "suppositional" criteria to assign amino acids to modules, whereas the second class of methods relies on "coevolutionary" criteria for this task. One simple and practical method from the first class consists of approximating the number of modules in a protein as the number of regular secondary structure elements (i.e., helices and sheets). Methods based on coevolutionary criteria require more elaborate data, but they have the advantage of being able to specify modules without prior assumptions about why they exist. Given the increasing availability of datasets sampling protein mutational spectra (e.g., from comparative genomics, experimental evolution, and computational prediction), methods based on coevolutionary criteria will likely become more promising in the near future. The ability to meaningfully quantify protein modularity via simple indices has the potential to aid future efforts to understand protein evolutionary rate determinants, improve molecular evolution models and engineer novel proteins.
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Affiliation(s)
- Mary Rorick
- University of Michigan, Department of Ecology and Evolutionary Biology, Ann Arbor, MI 48109-1048, United States.
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Tuller T, Mossel E. Co-evolution is incompatible with the Markov assumption in phylogenetics. IEEE/ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2011; 8:1667-1670. [PMID: 21116038 DOI: 10.1109/tcbb.2010.124] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/30/2023]
Abstract
Markov models are extensively used in the analysis of molecular evolution. A recent line of research suggests that pairs of proteins with functional and physical interactions co-evolve with each other. Here, by analyzing hundreds of orthologous sets of three fungi and their co-evolutionary relations, we demonstrate that co-evolutionary assumption may violate the Markov assumption. Our results encourage developing alternative probabilistic models for the cases of extreme co-evolution.
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Affiliation(s)
- Tamir Tuller
- Faculty of Mathematics and Computer Science, Weizmann Institute of Science, PO Box 26, Rehovot 76100, Israel.
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