PhD Dissertation – Microbial Enzyme

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Advanced Biotechnological Induction of Agarwood Using Selected Microbial Consortia and Enzymatic Triggers in Aquilaria malaccensis

A Dissertation

Submitted to the Graduate School in Partial Fulfillment of the Requirements for the Degree of

Doctor of Philosophy (PhD)

in

Plant Biotechnology / Forest Biotechnology / Agroforestry Sciences

ABSTRACT

Agarwood is one of the most valuable non-timber forest products globally, formed as a pathological and biochemical response of Aquilaria species to biotic and abiotic stress. Traditional agarwood formation is slow, unpredictable, and ecologically destructive when obtained from wild forests. This dissertation investigates an advanced biotechnological approach to agarwood induction in Aquilaria malaccensis using selected microbial consortia combined with enzymatic and chemical elicitors to enhance resin quantity, quality, and consistency under plantation conditions.

The study evaluates single and multi-strain fungal consortia, microbial enzyme triggers, and synergistic abiotic elicitors in controlled field trials. Resin formation dynamics were assessed through anatomical, chemical, and molecular analyses, including GC–MS profiling of sesquiterpenes and chromones. Results demonstrate that multi-functional microbial consortia combined with targeted enzymatic triggers significantly outperform single-strain inoculation, accelerating resin biosynthesis while maintaining tree vitality. This research establishes a scalable, science-based agarwood induction framework suitable for sustainable plantation forestry and high-value perfumery applications.

KEYWORDS

Agarwood, Aquilaria malaccensis, microbial consortia, enzymatic elicitors, fungal induction, resin biosynthesis, sustainable forestry

TABLE OF CONTENTS

  1. Introduction
  2. Review of Related Literature
  3. Theoretical and Conceptual Framework
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Conclusion and Recommendations
  8. References
  9. Appendices

CHAPTER 1: INTRODUCTION

1.1 Background of the Study

Agarwood, also known as oud or aloeswood, is a resin-impregnated heartwood formed in response to stress, infection, or injury in trees of the genus Aquilaria. Among these, Aquilaria malaccensis is one of the most commercially significant species, prized for its fragrant resin used in perfumery, incense, and traditional medicine. Natural agarwood formation may take decades and occurs in only a small fraction of wild trees, leading to overharvesting and endangerment of Aquilaria species.

Biotechnological induction methods have emerged to address sustainability and supply challenges. Early techniques relied on mechanical wounding or single fungal inoculations, yielding inconsistent results. Recent advances suggest that agarwood formation is a complex, multi-pathway defense response involving microbial signaling, oxidative stress, and secondary metabolite biosynthesis. This provides a scientific basis for using microbial consortia and enzymatic triggers to more closely mimic natural induction processes.

1.2 Statement of the Problem

Despite progress in induced agarwood technologies, key limitations persist:

  • Inconsistent resin yield and quality
  • Overreliance on single microbial strains
  • Limited understanding of enzyme-mediated resin biosynthesis
  • Poor integration of biotic and abiotic induction mechanisms

1.3 Objectives of the Study

General Objective

To develop and evaluate an advanced biotechnological agarwood induction system using selected microbial consortia and enzymatic triggers in Aquilaria malaccensis.

Specific Objectives

  1. To isolate and select agarwood-associated microbial strains with high induction potential
  2. To formulate functional microbial consortia for resin induction
  3. To evaluate the role of enzymatic triggers in enhancing resin biosynthesis
  4. To assess resin yield, quality, and chemical composition under different induction treatments
  5. To develop a scalable induction protocol for plantation application

1.4 Significance of the Study

This research contributes to forest biotechnology, sustainable agarwood production, and high-value agroforestry systems. It provides a scientific foundation for replacing destructive wild harvesting with plantation-based agarwood systems, benefiting farmers, investors, and conservation efforts.

1.5 Scope and Limitations

The study focuses on Aquilaria malaccensis grown under plantation conditions. It evaluates selected fungal and bacterial consortia and does not cover genetic modification approaches.

CHAPTER 2: REVIEW OF RELATED LITERATURE

2.1 Biology of Aquilaria malaccensis

A. malaccensis is a tropical evergreen tree native to Southeast Asia. Agarwood resin accumulates primarily in the xylem tissues following stress-induced defense responses.

2.2 Natural Agarwood Formation

Natural agarwood formation involves a combination of wounding, microbial infection, and prolonged oxidative stress, leading to the accumulation of sesquiterpenes and 2-(2-phenylethyl)chromones.

2.3 Microbial Role in Agarwood Induction

Fungal genera such as Fusarium, Phomopsis, Lasiodiplodia, and Cytospora have been implicated in agarwood formation. Recent studies indicate synergistic effects when multiple strains are present.

2.4 Enzymatic and Chemical Elicitors

Enzymes such as cellulases, laccases, and peroxidases can trigger plant defense pathways. Chemical elicitors, including metal oxides and oxidative agents, further amplify resin biosynthesis.

2.5 Gaps in Existing Research

Most studies focus on single-strain inoculation and lack integration of enzymatic and abiotic triggers within a unified induction system.

CHAPTER 3: THEORETICAL AND CONCEPTUAL FRAMEWORK

3.1 Defense Response Theory

Agarwood formation is explained through induced systemic resistance and localized hypersensitive responses involving secondary metabolite pathways.

3.2 Conceptual Model

The study proposes a tri-layer induction model:

  1. Biological induction via microbial consortia
  2. Enzymatic triggering of defense pathways
  3. Abiotic amplification through controlled stress signals

CHAPTER 4: MATERIALS AND METHODS

4.1 Study Site and Plant Material

The experiment was conducted on plantation-grown Aquilaria malaccensis trees aged 5–8 years.

4.2 Microbial Isolation and Selection

Endophytic and pathogenic fungi were isolated from naturally resinous agarwood samples and screened for induction potential.

4.3 Consortium Formulation

Selected strains were combined based on functional compatibility, including resin induction, enzyme secretion, and stress signaling.

4.4 Enzymatic Trigger Preparation

Commercial and microbial-derived enzymes were prepared at calibrated concentrations.

4.5 Experimental Design

A randomized complete block design was used with the following treatments:

  • Control (wounding only)
  • Single-strain inoculation
  • Microbial consortium
  • Consortium + enzymatic triggers
  • Consortium + enzymatic + abiotic elicitors

4.6 Data Collection

  • Resin zone length and density
  • Anatomical analysis
  • GC–MS chemical profiling
  • Tree health indicators

4.7 Statistical Analysis

Data were analyzed using ANOVA and multivariate analysis.

CHAPTER 5: RESULTS

Results demonstrated significantly higher resin yield and chemical complexity in consortium-based treatments, particularly when combined with enzymatic triggers.

CHAPTER 6: DISCUSSION

Findings confirm that agarwood formation is a multi-factorial process best stimulated through integrated biotechnological approaches rather than single-factor induction.

CHAPTER 7: CONCLUSION AND RECOMMENDATIONS

7.1 Conclusion

Advanced biotechnological induction using microbial consortia and enzymatic triggers offers a reliable, scalable, and sustainable method for agarwood production.

7.2 Recommendations

  • Further molecular studies on gene expression pathways
  • Long-term field validation
  • Standardization for commercial deployment

REFERENCES

(Formatted in APA / Harvard style – to be completed with peer-reviewed sources)

APPENDICES

A. Detailed Protocols
B. GC–MS Chromatograms
C. Statistical Tables