Monitoring Forest Damage with Mass Spectrometry-Based Metabolomics Methods E-Book
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- Herausgeber: John Wiley & Sons
- Kategorie: Wissenschaft und neue Technologien
- Serie: Wiley-Interscience Series on Mass Spectrometry
- Sprache: Englisch
Understand forest responses to climate change with this timely introduction Forests are among the most critical parts of our global ecosystem, responsible for the air we breathe, home to most of the earth's species, and crucial sources of food and raw materials. Forest development is therefore one of the most important areas of ecological study, and damage to forests is potentially existential. Metabolomics, a toolkit which accrues data on interactions between genetic and environmental conditions, promises to advance our understanding of how these vital ecosystems respond to dramatic changes in climate and environment. Monitoring Forest Damage with Mass Spectrometry-Based Metabolomics Methods offers a thorough, accessible discussion of metabolomic techniques and their applications in forest tree research. It promises to enrich the reader's understanding of how forests are being transformed by globe-spanning changes, and to arm researchers with tools for reacting to these potentially epochal developments. Monitoring Forest Damage with Mass Spectrometry-Based Metabolomics Methods readers will also find: * Analysis of specialized secondary metabolites such as phytohormones * Detailed discussion of ecologically important tree genera such as Pinus, Populus, Quercus, and many more * Supplementary materials related to study design, sample preparation, and instrumental analysis protocols Monitoring Forest Damage with Mass Spectrometry-Based Metabolomics Methods is ideal for researchers in analytical chemistry, mass spectrometry, metabolomics, forest research, the life sciences, and all other related fields.
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Table of Contents
Cover
Table of Contents
Title Page
Copyright
List of Contributors
Preface
1 Forest Tree Metabolomics Under a Changing Climate
1.1 Introduction
1.2 Forest Damage
1.3 Forest Tree Metabolomics
1.4 Conclusion and Future Perspectives
References
2 Experimental Methodology for Clonal Forest Research
2.1 Introduction
2.2 Defining the Objectives of an Experiment
2.3 Sampling Strategies to Represent the Species
2.4 Planning and Establishing the Experimental Design
2.5 Examples of the Implementation of Field Trials to Quantify Genetic Variability within a Species
2.6 Statistical Analysis and Quantification of Genetic Variability within a Species
2.7 Conclusions
Acknowledgments
References
3 Sample Preparation for Forest Tree Metabolomics
3.1 Experimental Design for Metabolomics
3.2 Sampling and Quenching of Tree Tissue Material
3.3 Labeling of Tree Tissues
3.4 Metabolite Extraction and Mass Spectrometry‐Based Metabolite Analysis
3.5 Conclusions
References
4 Systems Biology as a Tool to Uncover Interdisciplinary Links within the Complex Forest Tree System
4.1 Systems Biology
4.2 Strategies for Data Integration and Network Analysis
4.3 Integration of Genomics and Metabolomics Data
4.4 Systems Biology to Provide Clues for Metabolite Annotation in Different Tree Species in Recent Years
4.5 Challenges in Integrating Metabolomics and Other Omics
4.6 Conclusion and Future Perspectives
References
5 A Workflow for Metabolomics of Forest Tree Biotic Stress Response and Applications for Management
5.1 Introduction
5.2 Methods
5.3 Application
5.4 Case Studies
5.5 Conclusions and Future Perspectives
Acknowledgments
References
6 Analysis of Volatile Organic Compounds
6.1 Plant Volatile Organic Compounds
6.2 Methodologies for Detecting Plant VOCs
6.3 Analytical Systems for Measuring Plant VOCs
6.4 Concluding Remarks and Future Perspectives
References
7 Assessing Specialized Metabolites in Tree Bark Using Wide‐Targeted LC–MS Analysis
7.1 Introduction
7.2 Materials and Methods
7.3 Data Analysis
7.4 Data Interpretation
7.5 Conclusions and Future Perspectives
References
8 Plant Hormone Analysis in Forest Tree Species
8.1 Importance of Forest Tree Species
8.2 Plant Hormones and Their Roles in Plant Physiology, Biochemistry, and Development
8.3 Forest Tree Sampling
8.4 Analytical Methods for Plant Hormone Analysis and Profiling
8.5 Applications of Plant Hormone Profiling to Understand Forest Tree Physiology
8.6 Future Prospects in Plant Hormone Analysis
Acknowledgments
References
9 Metabolomics of Nutrient‐Deprived Forest Trees
9.1 Introduction
9.2 Macronutrient Deficiency and Wood Production
9.3 General Use of Mass Spectrometry‐Based Metabolomics to Study Wood
9.4 Tree Nutrition and Metabolome
9.5 Final Remarks
Acknowledgments
References
10 The Impact of Drought on Plant Metabolism in
Quercus
Species – From Initial Response to Recovery
10.1 Introduction
10.2 Primary Metabolic Pathways and Metabolite Levels
10.3 Secondary Metabolic Pathways and Metabolite Levels
10.4 The Transport of Metabolites within the Plant – Transport Rates and Sap Composition
10.5 The Release of Metabolites Outside the Plant
10.6 Conclusions
References
Further Reading/Resources
11 Metabolomics of Forest Tree Responses to Fluctuations of Temperature and Elevated Atmospheric CO
2
11.1 Introduction
11.2 Metabolic Response of Trees to Temperature Changes
11.3 Temperature Effect on Primary Metabolism
11.4 Temperature Effect on Secondary Metabolism
11.5 Effects of Elevated CO
2
on Tree Metabolism
11.6 CO
2
Effects on Isoprene Emissions
11.7 CO
2
and Plant Productivity
11.8 Acclimation After a Long Period of CO
2
Exposure
11.9 The Interactive Effect of Elevated CO
2
and High Temperature in Trees
11.10 Conclusions and Future Perspectives
Acknowledgments
References
12 Integration of Primary Metabolism with Physiological and Anatomical Data to Assess Dutch Elm Disease Susceptibility in Three Elm Species – A Case Study
12.1 Impacts of Dutch Elm Disease on Plant Metabolism and Its Modulation by Climate
12.2 Material and Methods
12.3 Results
12.4 Discussion
12.5 Conclusions
Acknowledgments
References
Further Reading/Resources
13 Metabolomics of
Pinus
spp. in Response to Pinewood Nematode Infection
13.1 Introduction
13.2 Mass Spectrometry‐Based Metabolite Responses to Pinewood Nematode Infection
13.3 Disease Management
13.4 Conclusions and Future Perspectives
References
Index
End User License Agreement
List of Tables
Chapter 3
Table 3.1 Methods used to sample phloem exudate.
Table 3.2 Methods for collecting xylem sap.
Table 3.3 Most commonly used techniques in spatial metabolomics or mass spectr...
Chapter 4
Table 4.1 Summary of transcript‐metabolite integration studies in tree species...
Table 4.2 Summary of transcript‐metabolite integration studies in tree species...
Table 4.3 Summary of multi‐omics integration studies in tree species.
Table 4.4 Linkage studies for metabolic traits in trees.
Table 4.5 Summary of genome‐wide association studies (GWAS) of metabolic trait...
Table 4.6 Genomic selection studies performed for metabolic traits of trees.
Chapter 5
Table 5.1 Commonly used chemometric methods in forest tree biotic stress studi...
Chapter 7
Table 7.1 Liquid chromatography gradient for specialized secondary metabolite ...
Chapter 8
Table 8.1 Important forest trees and shrubs.
Table 8.2 List of the most important plant hormones in plant physiology.
Chapter 10
Table 10.1 Studies of metabolite contents in oak species in response to natura...
Chapter 12
Table 12.1 Mean (± SE) stomatal conductance averaged over 2015 in elm trees sa...
Table 12.2 Metabolomics Standards Initiative (MSI) Compliant Metadata: metadat...
Table 12.3 Mean (± SE) annual radial growth and wood anatomical traits in elm ...
Table 12.4 Fold changes in relative levels of primary metabolites in stem and ...
Table 12.5 Fold changes in relative levels of primary metabolites in branch an...
List of Illustrations
Chapter 1
Figure 1.1 Forest tree metabolite responses to abiotic (e.g. light, heat, drou...
Chapter 2
Figure 2.1 Layout of the replicates for the Mediterranean stone pine clonal fi...
Figure 2.2 Layout of a row–column design, generated in CycDesigN 7.0 software,...
Figure 2.3 Field layout for the eight contiguous replicates for testing 420 ma...
Figure 2.4 Layout of four from the eight contiguous replicates of the Latinize...
Chapter 3
Figure 3.1 Cross section of a hybrid aspen stem, stained with Safranin O and A...
Figure 3.2 General scheme for metabolite extraction highlighting the main chem...
Chapter 5
Figure 5.1 A workflow for metabolomics studies of forest tree biotic stress in...
Chapter 6
Figure 6.1 Major classes of plant volatile organic compounds (VOCs). Terpene a...
Figure 6.2 Main origins of plant VOCs, their biochemical pathways, and link to...
Figure 6.3 Plant VOCs are emitted mainly from foliage, fruits, and flowers. Co...
Figure 6.4 Examples of VOCs as biomarkers elicited following specific (a)bioti...
Figure 6.5 Example of a schematic analytical system to analyze plant VOCs. A w...
Figure 6.6 Examples of different enclosure systems used to measure plant VOCs....
Figure 6.7 (a) Schematic workflow of VOC analysis with TD–GC–MS. (b) A constan...
Figure 6.8 Schematic representation of thermal desorption gas chromatography m...
Figure 6.9 Example of the mass selective detector (MSD) response to the same a...
Figure 6.10 Examples of a chromatogram, mass spectra, and deconvolution proces...
Figure 6.11 Schemes describing the working parts of PTR–QMS and PTR–TOF–MS ins...
Figure 6.12 (a) Real‐time monitoring of
13
C‐incorporation into isoprene by PTR...
Figure 6.13 (a) Real‐time evolution of the VOC emission blend induced by wound...
Figure 6.14 (a) Blends of VOC emissions from different
Trichoderma
species det...
Chapter 7
Figure 7.1 Fragmentation pattern of a metabolite peak (Rt 12.17 minutes) from
Figure 7.2 Relative retention times of common flavonoid aglycones and attached...
Figure 7.3 Comparison of standard and sample chromatograms using base peak and...
Figure 7.4 Metabolite profiling of
P. thunbergii
bark tissue by LC–MS. (a) Ext...
Figure 7.5 Metabolite profiling of forest and commercial crop tree bark tissue...
Chapter 8
Figure 8.1 Important considerations when planning a field sampling of forest t...
Figure 8.2 Typical analytical methods for plant hormone extraction and analysi...
Chapter 10
Figure 10.1 Qualitative changes in leaf primary metabolites belonging to sugar...
Figure 10.2 (a) The use of chromatographic techniques allows the determination...
Figure 10.3 General changes in secondary metabolites in oaks under water stres...
Chapter 11
Figure 11.1 Pipeline for metabolomics studies in trees.
Figure 11.2 Effects of high temperature on tree primary and secondary metaboli...
Figure 11.3 Schematic view of elevated CO
2
effects in plant metabolism. The bl...
Figure 11.4 Combined impact of temperature stress and high CO
2
levels on tree ...
Chapter 12
Figure 12.1 Mean (± SE) leaf stomatal conductance (
g
s
) in elm trees watered (W...
Figure 12.2 Partial least squares discriminant analysis (PLS‐DA) score plots (...
Figure 12.3 Partial least squares discriminant analysis (PLS‐DA) score plots (...
Figure 12.4 Heatmap representing the changes in relative levels of primary met...
Figure 12.5 Box‐plots of percentage foliar wilting at 14, 30, 60, and 120 dpi....
Figure 12.6 Partial least squares discriminant analysis (PLS‐DA) score plots (...
Figure 12.7 Partial least squares discriminant analysis (PLS‐DA) score plots (...
Figure 12.8 Heatmap representing the changes in relative levels of primary met...
Chapter 13
Figure 13.1 Brief description of the relationship between the life cycle of th...
Figure 13.2 Schematic illustration of the main metabolic responses in suscepti...
Figure 13.3 Conventional (in black) and emergent (in orange) disease mitigatio...
Guide
Cover
Table of Contents
Title Page
Copyright
List of Contributors
Preface
Begin Reading
Index
End User License Agreement
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Carla António (Editor) Monitoring Forest Damage with Mass Spectrometry‐Based Metabolomics Methods
Monitoring Forest Damage with Mass Spectrometry‐Based Metabolomics Methods
Edited by
Carla António
Plant Metabolomics Lab Portugal
Forest Research Centre (CEF)
School of Agriculture (ISA)
University of Lisbon (ULisboa)
Lisbon
Portugal
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Library of Congress Cataloging‐in‐Publication Data
Name: António, Carla, editor.Title: Monitoring forest damage with mass spectrometry‐based metabolomics methods / edited by Carla António.Description: Hoboken, New Jersey : Wiley, 2024. | Series: Wiley series on mass spectrometry | Includes index.Identifiers: LCCN 2023032892 (print) | LCCN 2023032893 (ebook) | ISBN 9781119868729 (hardback) | ISBN 9781119868736 (adobe pdf) | ISBN 9781119868743 (epub)Subjects: LCSH: Forests and forestry–Research. | Metabolites. | Mass spectrometry.Classification: LCC SD356.4 .M66 2024 (print) | LCC SD356.4 (ebook) | DDC 634.9072–dc23/eng/20231006LC record available at https://lccn.loc.gov/2023032892LC ebook record available at https://lccn.loc.gov/2023032893
Cover Design: WileyCover Image: Courtesy of Ana Margarida Rodrigues
List of Contributors
Ilka Nacif Abreu
Department of Plant Biochemistry
Albrecht‐von‐Haller‐Institute for Plant Sciences
University of Goettingen
Goettingen
Germany
Juan Manuel Acién
Departament de Biologia
Bioquímica i Ciències Naturals
Universitat Jaume I
Castelló de la Plana
Spain
Sara Adrián Lopez de Andrade
Department of Plant Biology
Institute of Biology
University of Campinas
Campinas
Brazil
Carla António
Plant Metabolomics Lab Portugal
Centro de Estudos Florestais (CEF)
Instituto Superior de Agronomia (ISA)
Universidade de Lisboa (ULisboa)
Lisboa
Portugal
Ismael Aranda
Instituto de Ciencias Forestales (ICIFOR‐INIA)
CSIC
Madrid
Spain
Vicent Arbona
Departament de Biologia
Bioquímica i Ciències Naturals
Universitat Jaume I
Castelló de la Plana
Spain
Pierluigi Bonello
Department of Plant Pathology
The Ohio State University
Columbus
USA
Federico Brilli
Institute for Sustainable Plant Protection (IPSP)
National Research Council of Italy (CNR)
Sesto Fiorentino (Florence)
Italy
Ilara Gabriela Frasson Budzinski
Department of Genetics
Max Feffer Laboratory of Plant Genetics
‘Luiz de Queiroz’ College of Agriculture
University of São Paulo
Piracicaba
SP
Brazil
Eva Cañizares
Departament de Biologia
Bioquímica i Ciències Naturals
Universitat Jaume I
Castelló de la Plana
Spain
Francisco Javier Cano
Instituto de Ciencias Forestales (ICIFOR‐INIA)
CSIC
Madrid
Spain
and
ARC Centre of Excellence for Translational Photosynthesis
Hawkesbury Institute for the Environment
Western Sydney University
Penrith
NSW
Australia
Isabel Carrasquinho
Instituto Nacional de Investigação
Agrária e Veterinária I. P. Avenida da República
Oeiras
Portugal
and
LEAF—Linking Landscape
Environment, Agriculture and Food Research Centre
Associated Laboratory TERRA
Instituto Superior de Agronomia
Universidade de Lisboa
Lisboa
Portugal
Fernanda Rezende Castro‐Moretti
Department of Plant Pathology
School of Agriculture Luiz de Queiroz
University of São Paulo
Piracicaba
SP
Brazil
Thaís Regiani Cataldi
Department of Genetics
Max Feffer Laboratory of Plant
Genetics
‘Luiz de Queiroz’ College of
Agriculture
University of São Paulo
Piracicaba
SP
Brazil
Anna O. Conrad
Northern Research Station
USDA Forest Service
West Lafayette
USA
Jorge Domínguez
Department of Natural Systems and Resources
Research Group
Functioning of Forest Systems in a Changing Environment
Universidad Politécnica de Madrid
Madrid
Spain
Pia Guadalupe Dominguez
Instituto de Agrobiotecnología y Biología Molecular (IABIMO)
Instituto Nacional de Tecnología Agropecuaria (INTA)
Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET)
Hurlingham
Buenos Aires
Argentina
Daniela Feltrim
Department of Plant Biology
Institute of Biology
University of Campinas
Campinas
SP
Brazil
Andrea Ghirardo
Research Unit Environmental Simulation (EUS)
Helmholtz Zentrum München
Neuherberg
Germany
Luis Gil
Department of Natural Systems and Resources
Research Group Functioning of Forest Systems in a Changing Environment
Universidad Politécnica de Madrid
Madrid
Spain
Elsa Gonçalves
LEAF—Linking Landscape Environment, Agriculture and Food Research Centre
Associated Laboratory TERRA
Instituto Superior de Agronomia
Universidade de Lisboa
Lisboa
Portugal
Miguel González‐Guzmán
Departament de Biologia
Bioquímica i Ciències Naturals
Universitat Jaume I
Castelló de la Plana
Spain
Maria Kenosis Emmanuelle Galingay Lachica
Division of Biological Sciences
Nara Institute of Science and
Technology (NAIST) – Graduate
School of Science and Technology
Ikoma
Nara
Japan
Rosana López
Department of Natural Systems and
Resources
Research Group Functioning of Forest Systems in a
Changing Environment
Universidad Politécnica de Madrid
Madrid
Spain
Juan Antonio Martín
Department of Natural Systems and
Resources
Research Group
Functioning of Forest Systems in a Changing Environment
Universidad Politécnica de Madrid
Madrid
Spain
Paulo Mazzafera
Department of Plant Biology
Institute of Biology
University of Campinas
Campinas
Brazil
Thomas Moritz
Department of Forest Genetics and Plant Physiology
Umeå Plant Science Centre
Swedish University of Agricultural Sciences
Umeå
Sweden
Vinícius Henrique de Oliveira
Department of Plant Biology
Institute of Biology
University of Campinas
Campinas
Brazil
Ana Margarida Rodrigues
Plant Metabolomics Lab Portugal
Centro de Estudos Florestais (CEF)
Instituto Superior de Agronomia (ISA)
Universidade de Lisboa (ULisboa)
Lisboa
Portugal
Jesús Rodríguez‐Calcerrada
Research Group Functioning of Forest Systems in a Changing Environment
Department of Natural Systems and Resources
Universidad Politécnica de Madrid
Madrid
Spain
Marta Nunes da Silva
CBQF – Centro de Biotecnologia e Química Fina – LaboratórioAssociado
Escola Superior de Biotecnologia
Universidade Católica Portuguesa
Porto
Portugal
María Brígida Fernández de Simón
Instituto de Ciencias Forestales (ICIFOR‐INIA)
CSIC
Madrid
Spain
Juan Sobrino‐Plata
Research Group Functioning of Forest Systems in a Changing Environment
Department of Natural Systems and Resources
Universidad Politécnica de Madrid
Madrid
Spain
and
Department of Genetics
Physiology and Microbiology
Universidad Complutense de Madrid
Madrid
Spain
Takayuki Tohge
Division of Biological Sciences
Nara Institute of Science and
Technology (NAIST) – Graduate
School of Science and Technology
Ikoma
Nara
Japan
Marta Vasconcelos
CBQF – Centro de Biotecnologia e Química Fina – Laboratório Associado
Escola Superior de Biotecnologia
Universidade Católica Portuguesa
Porto
Portugal
Caterina Villari
Warnell School of Forestry
University of Georgia
Athens
USA
Mutsumi Watanabe
Division of Biological Sciences
Nara Institute of Science and Technology (NAIST) – Graduate School of Science and Technology
Ikoma
Nara
Japan
Preface
Many of the world's forest ecosystems are severely damaged by climate change. Not only are warmer and drier climates expected to increase the risks of droughts (abiotic forest damage) and forest insect pest outbreaks (biotic forest damage), but warmer and rainier climates are also expected to increase unhealthy pathogen interactions. This book covers the latest challenges and resources provided by highly sensitive mass spectrometry (MS)‐based metabolomics methods to support forest tree research and explore the mechanisms and metabolic landscapes of forest tree species (i.e. primary and secondary metabolites, including phytohormones) in response to damage associated with the adverse effects of global climate change. Although much work is still needed to better understand the molecular basis underlying growth, development, and tree tolerance to environmental fluctuations, unraveling the pathways that fuel tree‐specific resistance mechanisms is essential for the protection of our forests and, ultimately, ourselves.
Chapters 1–5 introduce the existing challenges facing forest tree metabolomics research, including challenges in the experimental design and sample preparation workflows prior to the extraction of metabolites from forest tree tissues and MS‐based metabolomics analysis. The planning of the experimental design is the first crucial step of the entire metabolomics workflow and should include (in great detail) all the technical parameters that ensure data consistency and reproducibility of the generated data and metadata among metabolomics datasets for reliable biological interpretation. Moreover, metabolites are organized in a wide metabolic network, itself composed of multi‐biochemical pathways that are dependent on many genetic and signaling networks for their regulation. A glimpse on systems biology frameworks that integrate MS‐based metabolomics data with other Omics technologies (e.g. genomics, transcriptomics, proteomics) is explored to help uncover interdisciplinary links within the complex forest tree systems.
Chapters 6–8 cover recent advances in leading MS‐based methodologies in forest tree metabolomics, including the analysis of volatile organic compounds (VOCs), specific secondary (specialized) metabolites, and phytohormones. Chapters provide an overview of the methodology, general aspects of instrumentation, analytical approaches, sample preparation, and the latest trends relevant to forest tree research.
Chapters 9–13 examine how comprehensive MS‐based metabolomics has helped advance our understanding of forest tree adaptations in response to a changing climate through studies related to (i) forest tree metabolite responses to abiotic and/or combined abiotic stresses and (ii) forest tree diseases caused by biotic disturbances (insect pest and pathogen outbreaks). Particular focus is given to the mechanisms and metabolite adjustments involved in central metabolism and infection‐related metabolic pathways in metabolomics studies of economically and ecologically important forest tree species, such as Populus, Pinus, Picea, Eucalyptus, Quercus, and Ulmus spp.
I hope that both new and well‐established academics and students in the forest tree research field find in this book helpful guidelines and valuable insights for running forest tree metabolomics experiments.
I would like to express my heartfelt thanks to all contributors who made this book possible and Professors Dominic M. Desiderio and Joseph A. Loo (Wiley Series on Mass Spectrometry Editors) for the opportunity to take on the role of editor for what I hope will be an important source of informed MS‐based metabolomics methods to monitor forest damage.
Last but not least, next time you walk in the forest, I hope you feel the fertile pulse beneath your feet. And as you wander in contemplation of this vital source, may each breath you take be a reminder of the beauty that surrounds you.
“Every walk in the forest is like taking a shower in oxygen.”
—Peter Wohlleben, The Hidden Life of Trees
Editor
Carla António
Lisbon, Portugal
21 June 2023
1Forest Tree Metabolomics Under a Changing Climate
Ana Margarida Rodrigues and Carla António
Plant Metabolomics Lab Portugal, Forest Research Centre, School of Agriculture, University of Lisbon, Lisboa, Portugal
1.1 Introduction
Forests are complex ecosystems and the vital source of the air we breathe. Forests cover about 31% of the total land area (1) and provide habitat for more than 75% of the terrestrial biodiversity, shelter, outdoor recreation spaces, food, medicines, and essential raw materials of great economic importance to humankind. Forests also provide important environmental services, such as soil erosion and flood control, air quality improvement, and play a direct role in climate change mitigation through carbon sequestration and storage (2). Maintaining and enhancing our forests' health, integrity, and resilience to the threats of climate change is therefore crucial for them to continue providing these ecological, environmental, and socio‐cultural benefits.
A forest is usually defined by the presence of trees; however, its designation is slightly more complex and also depends on biophysical and land‐use criteria (3). The FAO Global Forest Resources Assessment 2020 (FAO‐FRA 2020) defines forest as the “land spanning more than 0.5 hectares with trees higher than 5 meters and a canopy cover of more than 10 percent, or trees able to reach these thresholds in situ” (4). According to this definition, a forest area includes regeneration sites after harvesting, understocked sites due to clear‐cut and (natural) disasters, nurseries, forest roads and firebreaks, rubber‐wood, cork oak and Christmas tree plantations, areas with bamboo and palms (if height and canopy cover criteria are met), but excludes any agricultural or other specific non‐forest land use (i.e. fruit tree and oil palm plantations, olive orchards, or agroforestry systems). This definition has been openly criticized for failing to distinguish between land covered by natural forests and forest plantations; forest plantations cause a huge impact on the protection of natural forests because when these areas are cleared and replaced with plantations, no net loss of forest cover is reported (3, 5).
Research in forest trees has been primarily focused on ecologically and economically important tree species, such as Populus, Pinus, Picea, Eucalyptus, Quercus, and Ulmus spp. However, progress in this area has been slow mainly due to the long life cycles of trees, the extremely large genome sizes, and lack of genomic tools (6–8). Efforts by the forest scientific community motivated the development of a model tree system for functional genomics. The rapid growth and relatively small genome size of Populus trichocarpa (black cottonwood) compared to other trees (9–11) led to the sequencing of the first tree genome (12). The sequencing of the Populus genome allowed the first insight into the functional biology of a tree and enabled the development of valuable genetic and genomic resources that greatly facilitated research in forest trees (13). Since then, the application of omics technologies to forest tree species (i.e. genomics, transcriptomics, proteomics, and metabolomics) in studies of responses to abiotic and biotic stresses, tree growth and development, and elucidation of wood formation has been key to advance our understanding of complex traits of economic and ecological relevance that allow forest trees survive during long periods of time under threat associated with global climate change (6–8, 14, 15). Moreover, the growing availability of multi‐omics data and emergent integrative systems biology approaches provide new opportunities for studying forest tree resilience across multiple levels of omics information (i.e. from genome, transcriptome, and proteome to metabolome). By comprehensively identifying novel genes and pathways associated with target traits underlying enhanced resistance or susceptibility to abiotic and biotic stresses, important biological insights into the complex defense mechanisms involved in forest tree resilience can be achieved. This systems‐level integration provides powerful information to developing strategies (e.g. through conventional breeding, genetic engineering, and genome editing) that can help forest ecosystems mitigate the damaging effects of climate change and, ultimately, restore forest health (16–20).
1.2 Forest Damage
During the lifetime of forests, trees are exposed to many different environmental factors that can threaten their survival. This is particularly true for tree species that, given their long life cycle, must withstand regular unfavorable weather conditions over many changing seasons. To respond to recurring fluctuations in environmental conditions, trees rely on evolved adaptive mechanisms that allow them to survive long periods of time and maintain their cellular homeostasis. However, this homeostasis can be greatly disrupted by the occurrence of a wide range of abiotic (e.g. drought, heat, salinity, and cold) and biotic (e.g. herbivory, pathogen infection) stresses, which often occur in combination under natural field conditions (Figure 1.1) (21–24).
Figure 1.1 Forest tree metabolite responses to abiotic (e.g. light, heat, drought, cold, flooding, salinity, metals, and elevated CO2) and biotic stresses (e.g. pests, such as insects and herbivores, and pathogens) are often related to adjustments in the primary and secondary metabolism, respectively. However, these events can also be observed in combination, which further compromises tree survival. Metabolite regulation during stress response (single or combined) and the activation of resistance mechanisms are strongly dependent on the cross talk between primary and secondary metabolism (e.g. primary metabolite adjustments to provide energy for the activation of defense responses). In the context of global climate change, drought and heat stress, often in combination with elevated atmospheric CO2 concentration, are the most frequently abiotic‐stress factors being studied in forest metabolomics.
Source: blueringmedia / Adobe Stock; KenStock / 94 images / Pixabay; David Pires / T. Michael Keesey / Public Domain.
1.2.1 Abiotic Forest Damage
Plant responses to abiotic stress are finely regulated by molecular networks, and significant advances using omics technologies have accelerated the discovery of stress‐responsive genes, proteins, and metabolites involved in these cascades (7, 25, 26). The damage caused by abiotic‐stress factors can deeply affect many aspects of plant physiology and metabolism, and further negatively impair plant growth and development.
In the presence of an abiotic‐stress event, the accumulation of phytohormones (e.g. abscisic acid [ABA]) and osmolytes (e.g. branched‐chained amino acids, soluble sugars, raffinose family of oligosaccharides, and polyamines) is well documented. Osmolyte accumulation has an important role in maintaining cell turgor by decreasing the osmotic potential of the cell and protection against oxidative damage by decreasing the levels of reactive oxygen species (ROS) to restore cellular redox balance. Stress‐tolerant plants can show higher levels of these metabolites even under normal growth conditions, thus preparing their metabolism for an adverse stress event. Abiotic‐stress factors also influence the accumulation of secondary metabolites due to their role as antioxidants against oxidative damage (25,27–33).
In the context of global climate change, the increased incidence of droughts and extreme heat events are the main abiotic‐stress factors driving forest damage by limiting the growth and productivity of tree species; hence, compromising their survival (34–38). Overall, drought and heat‐induced tree mortality are mainly related to impairments in hydraulic function (i.e. irreversible dysfunction in xylem water transport) and carbon and energy balance (39–46). Furthermore, the occurrence of such extreme weather conditions can result in a substantial loss of forest‐based ecosystem biodiversity. With the widespread forest damage and increased tree mortality, susceptible forest tree species tend to be replaced by species that display a set of morpho‐physiological traits that confer higher tolerance to these extreme weather events. Besides this loss in biodiversity, the increase in drought and heat‐induced tree mortality rates can also cause profound changes in global carbon and water cycles, thereby leading to a shift in global forest ecosystems from carbon sinks to carbon sources (47–49).
As a result of human activity and the rapid and intensifying global climate change, the negative consequences of abiotic stress events are undeniably expected to worsen (50, 51). The prevalence of more intense drought periods, in combination with the increased frequency of extreme heat events, has already been responsible for the amplified vulnerability of forest ecosystems all over the world, affecting several economically important fast‐growing forest tree species, mainly Pinus, Populus, and Eucalyptus (52–54).
1.2.2 Biotic Forest Damage
The combined effect of biotic and abiotic stresses has been associated with major forest damage and, consequently, extensive tree mortality (20, 52). Forest tree species are especially prone to insect pests and pathogen attacks because their long life cycle impairs trees to match the fast‐evolutionary rates of these organisms (55, 56). In addition, in the context of global climate change and the increased frequency and intensity of extreme weather events, tree vulnerability facilitates the spread, reproduction, and development of these biotic agents (57–59).
Forest pests and pathogens can also be subjected to the negative effects of climate change; however, further studies are urgently needed to better understand the dynamics between trees, pests and pathogens, and extreme weather conditions and their role in infection and disease outbreaks (20). For example, the effect of drought in combination with heat stress can have different effects depending on the type of disease, the affected tissue, and the severity of the abiotic stress (60, 61). Drought has been shown to significantly increase the damage caused by leaf pathogens and reduce that of root and stem pathogens (61). In addition, the interaction between drought, heat, and biotic agents often triggers physiological mechanisms of tree death, such as carbon starvation and hydraulic failure (62). However, studies in the literature are still scarce and often do not reflect accurate field conditions.
To deal with the constant threat of biotic agents, trees have evolved effective defense resistance mechanisms that allow them to survive during their long life cycle (63). These defense mechanisms associated with tree responses to biotic‐stress events include: (i) inducible chemical defenses (e.g. secondary metabolites such as terpenoids, phenolic compounds, and alkaloids); (ii) inducible protein‐based defenses (e.g. proteinase inhibitors); (iii) anatomical defenses acting as structural barriers (e.g. enhanced lignification); and (iv) indirect defenses (e.g. attraction of natural enemies) (64, 65). Phytohormones also have a crucial role in regulating plant defense responses against pests and pathogens, in particular jasmonic acid (JA), salicylic acid (SA), and ethylene (ET) (66). SA is generally involved in the activation of defense responses against biotrophic and hemi‐biotrophic pathogens, whereas JA and ET are responsible for defense responses against necrotrophic pathogens and herbivorous insects. Plant defense signaling pathways also involve the cross talk between primary and secondary metabolism. Primary metabolic pathways act as a source of energy to support defense responses and also as a source of signaling molecules to directly or indirectly trigger defense responses (67, 68).
1.3 Forest Tree Metabolomics
Metabolomics is the omics technology that best reflects the interaction between the genetic traits and environmental factors, thus being considered the molecular phenotype of a living organism (69, 70). Metabolomics studies greatly benefit from the development of next‐generation sequencing technologies and the availability of genome sequence data for the establishment of gene‐metabolite correlations that allow for a broader metabolome characterization and additional insights on the various functions of metabolites in biological processes, such as plant growth and development, and abiotic and biotic stress responses (71–77). After major genomics breakthroughs in forest tree research, that is the availability of the early reference genomes of Populus (the first tree genome) (12) and Eucalyptus(78) followed by the sequence of other important woody plant genomes (8, 79, 80), metabolomics studies in forest tree species have generated increased interest.
When compared to other plants, metabolomics studies using forest tree species are characterized by additional challenges. These include the need for an experimental design that takes into account the long life cycle and the genetic variability of forest tree species as well as the presence of interferents that can require additional processing steps during sample preparation. One strategy to overcome the effect of genetic variability of forest trees when evaluating quantitative traits (e.g. tree productivity and metabolite production) is the use of clonal stands. The introduction of clonal stands and clonal orchards can rapidly speed the breeding progress and plant selection of desired quantitative traits. However, in field conditions, the introduction of new clonal material among established natural forest ecosystems should not compromise the existent genetic or genotypic diversity, which could in turn lead to negative effects, such as increased competition and increased susceptibility to pests and pathogens (81). Other challenges concern the reporting standards because details of the experimental metadata (e.g. parental original, geographical location, field growth conditions, biological growth stages, and phenological parameters) that allow re‐use of the data are often not described (8, 82); see Chapters 2–5 for further discussions. Despite the struggles, continuous efforts from the metabolomics scientific community have been made to ensure forest metabolomics data and metadata reproducibility between laboratories and to promote the availability of curated databases and repositories containing high‐quality data (including dedicated woody species platforms).
Current plant metabolomics studies rely on the application of mass spectrometry (MS)‐ and nuclear magnetic resonance (NMR)‐based methods, and several detailed protocols are available (83). MS‐based methods, namely liquid chromatography mass spectrometry (LC–MS) and gas chromatography mass spectrometry (GC–MS), can deliver highly sensitive qualitative and quantitative data that provide a detailed description of the biochemical pathways that are influenced by environmental changes. In this context, although much work is still needed, the use of MS‐based metabolomics methods in forest tree research has been crucial to advance our understanding of the metabolic landscapes, that is primary and secondary (specialized) metabolites (including phytohormones), of forest trees in response to environmental cues, such as changing weather patterns (abiotic forest damage) and pathogen interactions (biotic forest damage) ((84–92); to name a few). For further examples and methods, see Chapters 6–13.
By contrast, despite requiring minimal sample preparation and being highly reproducible, NMR‐based methods are only able to detect highly abundant metabolites (93–95). Consequently, due to the lower high‐throughput relative to MS, NMR has been largely outperformed by MS‐based methods for a broader metabolite coverage (31,75–77, 96). Nevertheless, NMR has demonstrated to be a powerful complementary technique in plant metabolomics, being typically employed in natural products research (e.g. structure elucidation of unknown compounds) (94, 95). In forest tree research, NMR‐based methods have been used to explore the industrial processing of wood (e.g. pulp and paper industry or biofuel production), particularly in studies of the structure elucidation and composition of lignin in forest tree species, including Populus(97), Eucalyptus(98), and Quercus(99).
1.4 Conclusion and Future Perspectives
Many of the world's forest ecosystems are severely threatened by global climate change. Not only warmer and drier climates are expected to increase the risks of droughts and forest insect pest outbreaks, but also warmer and wetter climates are expected to increase unhealthy pathogen interactions. In addition, different forest tree species display a wide array of specific secondary (specialized) metabolites that might be produced for defense against abiotic and biotic‐stress factors only in specific environmental circumstances. More integrated research studies that combine multi‐level information from omics technologies and systems biology approaches are also needed to provide new insights into the complex molecular mechanisms involved in responses of forest trees to abiotic and biotic stresses. A better understanding of the specific mechanisms of resistance that fuel forest tree‐defense responses to abiotic and biotic threats is urgent to develop strategies for more resilient natural forest ecosystems around the world and to, ultimately, help them regenerate and fight climate change.
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