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Jensen IT, Janss L, Radutoiu S, Waagepetersen R. Compositionally aware estimation of cross-correlations for microbiome data. PLoS One 2024; 19:e0305032. [PMID: 38941272 PMCID: PMC11213360 DOI: 10.1371/journal.pone.0305032] [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: 10/18/2023] [Accepted: 05/22/2024] [Indexed: 06/30/2024] Open
Abstract
In the field of microbiome studies, it is of interest to infer correlations between abundances of different microbes (here referred to as operational taxonomic units, OTUs). Several methods taking the compositional nature of the sequencing data into account exist. However, these methods cannot infer correlations between OTU abundances and other variables. In this paper we introduce the novel methods SparCEV (Sparse Correlations with External Variables) and SparXCC (Sparse Cross-Correlations between Compositional data) for quantifying correlations between OTU abundances and either continuous phenotypic variables or components of other compositional datasets, such as transcriptomic data. SparCEV and SparXCC both assume that the average correlation in the dataset is zero. Iterative versions of SparCEV and SparXCC are proposed to alleviate bias resulting from deviations from this assumption. We compare these new methods to empirical Pearson cross-correlations after applying naive transformations of the data (log and log-TSS). Additionally, we test the centered log ratio transformation (CLR) and the variance stabilising transformation (VST). We find that CLR and VST outperform naive transformations, except when the correlation matrix is dense. SparCEV and SparXCC outperform CLR and VST when the number of OTUs is small and perform similarly to CLR and VST for large numbers of OTUs. Adding the iterative procedure increases accuracy for SparCEV and SparXCC for all cases, except when the average correlation in the dataset is close to zero or the correlation matrix is dense. These results are consistent with our theoretical considerations.
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Affiliation(s)
- Ib Thorsgaard Jensen
- Department of Molecular Biology and Genetics, Aarhus University, Aarhus, Denmark
- Department of Mathematical Sciences, Aalborg University, Aalborg, Denmark
| | - Luc Janss
- Center for Quantitative Genetics and Genomics, Aarhus University, Aarhus, Denmark
| | - Simona Radutoiu
- Department of Molecular Biology and Genetics, Aarhus University, Aarhus, Denmark
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Csorba C, Rodić N, Antonielli L, Sessitsch A, Vlachou A, Ahmad M, Compant S, Puschenreiter M, Molin EM, Assimopoulou AN, Brader G. Soil pH, developmental stages and geographical origin differently influence the root metabolomic diversity and root-related microbial diversity of Echium vulgare from native habitats. FRONTIERS IN PLANT SCIENCE 2024; 15:1369754. [PMID: 38984162 PMCID: PMC11232435 DOI: 10.3389/fpls.2024.1369754] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/12/2024] [Accepted: 06/03/2024] [Indexed: 07/11/2024]
Abstract
Improved understanding of the complex interaction between plant metabolism, environmental conditions and the plant-associated microbiome requires an interdisciplinary approach: Our hypothesis in our multiomics study posited that several environmental and biotic factors have modulating effects on the microbiome and metabolome of the roots of wild Echium vulgare plants. Furthermore, we postulated reciprocal interactions between the root metabolome and microbiome. We investigated the metabolic content, the genetic variability, and the prokaryotic microbiome in the root systems of wild E. vulgare plants at rosette and flowering stages across six distinct locations. We incorporated the assessment of soil microbiomes and the measurement of selected soil chemical composition factors. Two distinct genetic clusters were determined based on microsatellite analysis without a consistent alignment with the geographical proximity between the locations. The microbial diversity of both the roots of E. vulgare and the surrounding bulk soil exhibited significant divergence across locations, varying soil pH characteristics, and within the identified plant genetic clusters. Notably, acidophilic bacteria were characteristic inhabitants of both soil and roots under acidic soil conditions, emphasizing the close interconnectedness between these compartments. The metabolome of E. vulgare significantly differed between root samples from different developmental stages, geographical locations, and soil pH levels. The developmental stage was the dominant driver of metabolome changes, with significantly higher concentrations of sugars, pyrrolizidine alkaloids, and some of their precursors in rosette stage plant roots. Our study featured the complex dynamics between soil pH, plant development, geographical locations, plant genetics, plant metabolome and microbiome, shedding light on existing knowledge gaps.
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Affiliation(s)
- Cintia Csorba
- AIT Austrian Institute of Technology GmbH, Center for Health & Bioresources, Bioresources Unit, Tulln, Austria
| | - Nebojša Rodić
- Aristotle University of Thessaloniki, School of Chemical Engineering, Laboratory of Organic Chemistry and Center for Interdisciplinary Research and Innovation, Natural Products Research Centre of Excellence (NatPro-AUTh), Thessaloniki, Greece
| | - Livio Antonielli
- AIT Austrian Institute of Technology GmbH, Center for Health & Bioresources, Bioresources Unit, Tulln, Austria
| | - Angela Sessitsch
- AIT Austrian Institute of Technology GmbH, Center for Health & Bioresources, Bioresources Unit, Tulln, Austria
| | - Angeliki Vlachou
- Aristotle University of Thessaloniki, School of Chemical Engineering, Laboratory of Organic Chemistry and Center for Interdisciplinary Research and Innovation, Natural Products Research Centre of Excellence (NatPro-AUTh), Thessaloniki, Greece
| | - Muhammad Ahmad
- AIT Austrian Institute of Technology GmbH, Center for Health & Bioresources, Bioresources Unit, Tulln, Austria
- Department of Forest Growth, Silviculture and Genetics, Austrian Research Centre for Forests (BFW), Vienna, Austria
| | - Stéphane Compant
- AIT Austrian Institute of Technology GmbH, Center for Health & Bioresources, Bioresources Unit, Tulln, Austria
| | - Markus Puschenreiter
- Institute of Soil Research, University of Natural Resources and Life Sciences Vienna, Vienna, Austria
| | - Eva M. Molin
- AIT Austrian Institute of Technology GmbH, Center for Health & Bioresources, Bioresources Unit, Tulln, Austria
| | - Andreana N. Assimopoulou
- Aristotle University of Thessaloniki, School of Chemical Engineering, Laboratory of Organic Chemistry and Center for Interdisciplinary Research and Innovation, Natural Products Research Centre of Excellence (NatPro-AUTh), Thessaloniki, Greece
| | - Günter Brader
- AIT Austrian Institute of Technology GmbH, Center for Health & Bioresources, Bioresources Unit, Tulln, Austria
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Kimotho RN, Maina S. Unraveling plant-microbe interactions: can integrated omics approaches offer concrete answers? JOURNAL OF EXPERIMENTAL BOTANY 2024; 75:1289-1313. [PMID: 37950741 PMCID: PMC10901211 DOI: 10.1093/jxb/erad448] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/26/2023] [Accepted: 11/08/2023] [Indexed: 11/13/2023]
Abstract
Advances in high throughput omics techniques provide avenues to decipher plant microbiomes. However, there is limited information on how integrated informatics can help provide deeper insights into plant-microbe interactions in a concerted way. Integrating multi-omics datasets can transform our understanding of the plant microbiome from unspecified genetic influences on interacting species to specific gene-by-gene interactions. Here, we highlight recent progress and emerging strategies in crop microbiome omics research and review key aspects of how the integration of host and microbial omics-based datasets can be used to provide a comprehensive outline of complex crop-microbe interactions. We describe how these technological advances have helped unravel crucial plant and microbial genes and pathways that control beneficial, pathogenic, and commensal plant-microbe interactions. We identify crucial knowledge gaps and synthesize current limitations in our understanding of crop microbiome omics approaches. We highlight recent studies in which multi-omics-based approaches have led to improved models of crop microbial community structure and function. Finally, we recommend holistic approaches in integrating host and microbial omics datasets to achieve precision and efficiency in data analysis, which is crucial for biotic and abiotic stress control and in understanding the contribution of the microbiota in shaping plant fitness.
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Affiliation(s)
- Roy Njoroge Kimotho
- Hebei Key Laboratory of Soil Ecology, Key Laboratory of Agricultural Water Resources, Centre for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang 050021, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Solomon Maina
- Elizabeth Macarthur Agricultural Institute, NSW Department of Primary Industries, Menangle, New South Wales 2568, Australia
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Liu Q, Cheng L, Nian H, Jin J, Lian T. Linking plant functional genes to rhizosphere microbes: a review. PLANT BIOTECHNOLOGY JOURNAL 2023; 21:902-917. [PMID: 36271765 PMCID: PMC10106864 DOI: 10.1111/pbi.13950] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Revised: 10/09/2022] [Accepted: 10/16/2022] [Indexed: 05/04/2023]
Abstract
The importance of rhizomicrobiome in plant development, nutrition acquisition and stress tolerance is unquestionable. Relevant plant genes corresponding to the above functions also regulate rhizomicrobiome construction. Deciphering the molecular regulatory network of plant-microbe interactions could substantially contribute to improving crop yield and quality. Here, the plant gene-related nutrient uptake, biotic and abiotic stress resistance, which may influence the composition and function of microbial communities, are discussed in this review. In turn, the influence of microbes on the expression of functional plant genes, and thereby plant growth and immunity, is also reviewed. Moreover, we have specifically paid attention to techniques and methods used to link plant functional genes and rhizomicrobiome. Finally, we propose to further explore the molecular mechanisms and signalling pathways of microbe-host gene interactions, which could potentially be used for managing plant health in agricultural systems.
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Affiliation(s)
- Qi Liu
- The State Key Laboratory for Conservation and Utilization of Subtropical Agro‐BioresourcesSouth China Agricultural UniversityGuangzhouChina
- The Key Laboratory of Plant Molecular Breeding of Guangdong Province, College of AgricultureSouth China Agricultural UniversityGuangzhouChina
| | - Lang Cheng
- The State Key Laboratory for Conservation and Utilization of Subtropical Agro‐BioresourcesSouth China Agricultural UniversityGuangzhouChina
- The Key Laboratory of Plant Molecular Breeding of Guangdong Province, College of AgricultureSouth China Agricultural UniversityGuangzhouChina
| | - Hai Nian
- The State Key Laboratory for Conservation and Utilization of Subtropical Agro‐BioresourcesSouth China Agricultural UniversityGuangzhouChina
- The Key Laboratory of Plant Molecular Breeding of Guangdong Province, College of AgricultureSouth China Agricultural UniversityGuangzhouChina
| | - Jian Jin
- Northeast Institute of Geography and AgroecologyChinese Academy of SciencesHarbinChina
- Department of Animal, Plant and Soil Sciences, Centre for AgriBioscienceLa Trobe UniversityBundooraVictoriaAustralia
| | - Tengxiang Lian
- The State Key Laboratory for Conservation and Utilization of Subtropical Agro‐BioresourcesSouth China Agricultural UniversityGuangzhouChina
- The Key Laboratory of Plant Molecular Breeding of Guangdong Province, College of AgricultureSouth China Agricultural UniversityGuangzhouChina
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Ali S, Tyagi A, Mushtaq M, Al-Mahmoudi H, Bae H. Harnessing plant microbiome for mitigating arsenic toxicity in sustainable agriculture. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2022; 300:118940. [PMID: 35122918 DOI: 10.1016/j.envpol.2022.118940] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Revised: 01/08/2022] [Accepted: 01/30/2022] [Indexed: 06/14/2023]
Abstract
Heavy metal toxicity has become an impediment to agricultural productivity, which presents major human health concerns in terms of food safety. Among them, arsenic (As) a non-essential heavy metal has gained worldwide attention because of its noxious effects on agriculture and public health. The increasing rate of global warming and anthropogenic activities have promptly exacerbated As levels in the agricultural soil, thereby causing adverse effects to crop genetic and phenotypic traits and rendering them vulnerable to other stresses. Conventional breeding and transgenic approaches have been widely adapted for producing heavy metal resilient crops; however, they are time-consuming and labor-intensive. Hence, finding new mitigation strategies for As toxicity would be a game-changer for sustainable agriculture. One such promising approach is harnessing plant microbiome in the era of 'omics' which is gaining prominence in recent years. The use of plant microbiome and their cocktails to combat As metal toxicity has gained widespread attention, because of their ability to metabolize toxic elements and offer an array of perquisites to host plants such as increased nutrient availability, stress resilience, soil fertility, and yield. A comprehensive understanding of below-ground plant-microbiome interactions and their underlying molecular mechanisms in exhibiting resilience towards As toxicity will help in identifying elite microbial communities for As mitigation. In this review, we have discussed the effect of As, their accumulation, transportation, signaling, and detoxification in plants. We have also discussed the role of the plant microbiome in mitigating As toxicity which has become an intriguing research frontier in phytoremediation. This review also provides insights on the advancements in constructing the beneficial synthetic microbial communities (SynComs) using microbiome engineering that will facilitate the development of the most advanced As remedial tool kit in sustainable agriculture.
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Affiliation(s)
- Sajad Ali
- Department of Biotechnology, Yeungnam University, Gyeongsan, Gyeongbuk, 38541, Republic of Korea
| | - Anshika Tyagi
- Department of Biotechnology, Yeungnam University, Gyeongsan, Gyeongbuk, 38541, Republic of Korea
| | | | - Henda Al-Mahmoudi
- Directorate of Programs, International Center for Biosaline Agriculture, Dubai, United Arab Emirates
| | - Hanhong Bae
- Department of Biotechnology, Yeungnam University, Gyeongsan, Gyeongbuk, 38541, Republic of Korea.
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Kang S, Kim KT, Choi J, Kim H, Cheong K, Bandara A, Lee YH. Genomics and Informatics, Conjoined Tools Vital for Understanding and Protecting Plant Health. PHYTOPATHOLOGY 2022; 112:981-995. [PMID: 34889667 DOI: 10.1094/phyto-10-21-0418-rvw] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Genomics' impact on crop production continuously expands. The number of sequenced plant and microbial species and strains representing diverse populations of individual species rapidly increases thanks to the advent of next-generation sequencing technologies. Their genomic blueprints revealed candidate genes involved in various functions and processes crucial for crop health and helped in understanding how the sequenced organisms have evolved at the genome level. Functional genomics quickly translates these blueprints into a detailed mechanistic understanding of how such functions and processes work and are regulated; this understanding guides and empowers efforts to protect crops from diverse biotic and abiotic threats. Metagenome analyses help identify candidate microbes crucial for crop health and uncover how microbial communities associated with crop production respond to environmental conditions and cultural practices, presenting opportunities to enhance crop health by judiciously configuring microbial communities. Efficient conversion of disparate types of massive genomics data into actionable knowledge requires a robust informatics infrastructure supporting data preservation, analysis, and sharing. This review starts with an overview of how genomics came about and has quickly transformed life science. We illuminate how genomics and informatics can be applied to investigate various crop health-related problems using selected studies. We end the review by noting why community empowerment via crowdsourcing is crucial to harnessing genomics to protect global food and nutrition security without continuously expanding the environmental footprint of crop production.
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Affiliation(s)
- Seogchan Kang
- Department of Plant Pathology and Environmental Microbiology, Pennsylvania State University, University Park, PA 16802, U.S.A
| | - Ki-Tae Kim
- Department of Agricultural Life Science, Sunchon National University, Suncheon 57922, Korea
| | - Jaeyoung Choi
- Korea Institute of Science and Technology Gangneung Institute of Natural Products, Gangneung 25451, Korea
| | - Hyun Kim
- Department of Agricultural Biotechnology, Seoul National University, Seoul 08826, Korea
| | - Kyeongchae Cheong
- Plant Immunity Research Center, Seoul National University, Seoul 08826, Korea
| | - Ananda Bandara
- Department of Plant Pathology and Environmental Microbiology, Pennsylvania State University, University Park, PA 16802, U.S.A
| | - Yong-Hwan Lee
- Department of Agricultural Biotechnology, Seoul National University, Seoul 08826, Korea
- Plant Immunity Research Center, Seoul National University, Seoul 08826, Korea
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Rane NR, Tapase S, Kanojia A, Watharkar A, Salama ES, Jang M, Kumar Yadav K, Amin MA, Cabral-Pinto MMS, Jadhav JP, Jeon BH. Molecular insights into plant-microbe interactions for sustainable remediation of contaminated environment. BIORESOURCE TECHNOLOGY 2022; 344:126246. [PMID: 34743992 DOI: 10.1016/j.biortech.2021.126246] [Citation(s) in RCA: 30] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Revised: 10/24/2021] [Accepted: 10/26/2021] [Indexed: 06/13/2023]
Abstract
The widespread distribution of organic and inorganic pollutants in water resources have increased due to rapid industrialization. Rhizospheric zone-associated bacteria along with endophytic bacteria show a significant role in remediation of various pollutants. Metaomics technologies are gaining an advantage over traditional methods because of their capability to obtain detailed information on exclusive microbial communities in rhizosphere of the plant including the unculturable microorganisms. Transcriptomics, proteomics, and metabolomics are functional methodologies that help to reveal the mechanisms of plant-microbe interactions and their synergistic roles in remediation of pollutants. Intensive analysis of metaomics data can be useful to understand the interrelationships of various metabolic activities between plants and microbes. This review comprehensively discusses recent advances in omics applications made hitherto to understand the mechanisms of plant-microbe interactions during phytoremediation. It extends the delivery of the insightful information on plant-microbiomes communications with an emphasis on their genetic, biochemical, physical, metabolic, and environmental interactions.
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Affiliation(s)
- Niraj R Rane
- Department of Earth Resources and Environmental Engineering, Hanyang University, Seoul 04763, South Korea
| | - Savita Tapase
- Department of Biotechnology, Shivaji University, Kolhapur 416004, India
| | - Aakansha Kanojia
- Center of Plant Systems Biology and Biotechnology, 4000 Plovdiv, Bulgaria
| | - Anuprita Watharkar
- Amity Institute of Biotechnology, Amity University, Bhatan, Panvel, Mumbai, India
| | - El-Sayed Salama
- Occupational and Environmental Health Department, School of Public Health, Lanzhou University, Lanzhou 730000, Gansu Province, People's Republic of China
| | - Min Jang
- Department of Environmental Engineering, Kwangwoon University, Seoul 01897, Republic of Korea
| | - Krishna Kumar Yadav
- Faculty of Science and Technology, Madhyanchal Professional University, Ratibad, Bhopal, 462044, India
| | - Mohammed A Amin
- Department of Chemistry, College of Science, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia
| | - Marina M S Cabral-Pinto
- Geobiotec Research Centre, Department of Geoscience, University of Aveiro, 3810-193, Aveiro, Portugal
| | - Jyoti P Jadhav
- Department of Biochemistry, Shivaji University, Kolhapur 416004, India
| | - Byong-Hun Jeon
- Department of Earth Resources and Environmental Engineering, Hanyang University, Seoul 04763, South Korea.
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Krantz M, Zimmer D, Adler SO, Kitashova A, Klipp E, Mühlhaus T, Nägele T. Data Management and Modeling in Plant Biology. FRONTIERS IN PLANT SCIENCE 2021; 12:717958. [PMID: 34539712 PMCID: PMC8446634 DOI: 10.3389/fpls.2021.717958] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Accepted: 07/29/2021] [Indexed: 05/25/2023]
Abstract
The study of plant-environment interactions is a multidisciplinary research field. With the emergence of quantitative large-scale and high-throughput techniques, amount and dimensionality of experimental data have strongly increased. Appropriate strategies for data storage, management, and evaluation are needed to make efficient use of experimental findings. Computational approaches of data mining are essential for deriving statistical trends and signatures contained in data matrices. Although, current biology is challenged by high data dimensionality in general, this is particularly true for plant biology. Plants as sessile organisms have to cope with environmental fluctuations. This typically results in strong dynamics of metabolite and protein concentrations which are often challenging to quantify. Summarizing experimental output results in complex data arrays, which need computational statistics and numerical methods for building quantitative models. Experimental findings need to be combined by computational models to gain a mechanistic understanding of plant metabolism. For this, bioinformatics and mathematics need to be combined with experimental setups in physiology, biochemistry, and molecular biology. This review presents and discusses concepts at the interface of experiment and computation, which are likely to shape current and future plant biology. Finally, this interface is discussed with regard to its capabilities and limitations to develop a quantitative model of plant-environment interactions.
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Affiliation(s)
- Maria Krantz
- Theoretical Biophysics, Institute of Biology, Humboldt-Universität zu Berlin, Berlin, Germany
| | - David Zimmer
- Computational Systems Biology, Technische Universität Kaiserslautern, Kaiserslautern, Germany
| | - Stephan O. Adler
- Theoretical Biophysics, Institute of Biology, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Anastasia Kitashova
- Plant Evolutionary Cell Biology, Faculty of Biology, Ludwig-Maximilians-Universität München, Planegg-Martinsried, Germany
| | - Edda Klipp
- Theoretical Biophysics, Institute of Biology, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Timo Mühlhaus
- Computational Systems Biology, Technische Universität Kaiserslautern, Kaiserslautern, Germany
| | - Thomas Nägele
- Plant Evolutionary Cell Biology, Faculty of Biology, Ludwig-Maximilians-Universität München, Planegg-Martinsried, Germany
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