DOI: 10.5061/dryad.h70rxwdq5
title: Data from: A synthetic biology and green bioprocess approach to recreate agarwood sesquiterpenoid mixtures

description: Certain endangered Thymelaeaceous trees are major sources of the fragrant
 and highly valued resinous agarwood, comprised of hundreds of oxygenated
 sesquiterpenoids (STPs). Despite growing pressure on natural agarwood
 sources, the chemical complexity of STPs severely limits synthetic
 production. Here, we catalogued the chemical diversity in 58 agarwood
 samples by two-dimensional gas chromatography–mass spectrometry and
 partially recreated complex STP mixtures through synthetic biology. We
 improved STP yields in the unicellular alga Chlamydomonas reinhardtii by
 combinatorial engineering to biosynthesise nine macrocyclic STP backbones
 found in agarwood. A bioprocess following green-chemistry principles was
 developed that exploits ‘milking’ of STPs without cell lysis,
 solvent–solvent STP extraction, solvent–STP nanofiltration, and bulk STP
 oxy-functionalisation to obtain terpene mixtures like those of agarwood.
 This process occurs with total solvent recycling and enables continuous
 production. Our synthetic-biology approach offers a sustainable
 alternative to harvesting agarwood trees to obtain mixtures of complex,
 fragrant, oxygenated STPs.
description: <strong>Agarwood sample collection and
 processing</strong> Agarwood samples were
 procured from the old-town market "Al Balad" in Jeddah, Saudi
 Arabia (21.481° N, 39.187° E) in Winter 2023. The collection includes 36
 different samples of agarwood chips, dried <em>Aquilaria</em>
 spp. wood (also known as "bahkour"), and 22 agarwood
 steam-distillate oils, known as "oudh". The ages of the plants
 at harvest and origins of these samples cannot be accurately traced;
 however, many were labelled with their country of origin. The samples
 varied in price at the time of purchase, reflecting their purported
 rarity, the density of fragrant compounds, and complexity of aromatic
 notes (Supplementary Table 1). It was determined that the appropriate
 organic solvent for extraction was acetone based on preliminary analysis
 with different solvents, and each agarwood sample was then diluted to
 obtain chromatograms with clear peaks for product detection and
 identification. All samples were processed within 16 weeks of being
 procured. The wood samples were weighed (1 g) and ground into a fine
 powder using a combination of freeze–thaw cycles with liquid nitrogen and
 mechanical grinding. The homogenised samples were immersed in 5 mL of 1:1
 hexane:acetone and subjected to ultrasonic agitation at 40°C for 8 h to
 facilitate terpenoid extraction. The samples were then passed through a
 0.2 µm filter to obtain clear solvent extracts that were evaporated under
 a nitrogen stream for 20 min to concentrate the terpenoids in the samples.
 Concentrated samples were resuspended in 500 µL acetone and stored at
 –20°C until gas chromatography–flame-ionisation detector and mass
 spectrometry (GC–MS/FID) and two-dimensional gas chromatography with
 time-of-flight mass spectrometry (GCxGC–TOF/MS) analyses. All photographs
 were captured with a Canon EOS RP camera using a Canon RF 24–105 mm
 f/4-7.1 IS STM lens (Canon, Tokyo, Japan) and ColorChecker Passport
 (CCPP2, Calibrite LLC, DE, USA) used for colour calibration.
 <strong>Algal strain cultivation</strong>
 <em>Chlamydomonas reinhardtii </em>strain UPN22 was
 used for all experiments. <em>C. reinhardtii </em>UPN22 is a
 derivative of the UVM4 strain. It has been genetically enhanced to use
 phosphite and nitrate as a sole source of phosphorous and nitrogen,
 respectively, to minimise contamination and maximise cell densities in
 cultivation. Strains were cultured in Tris-acetate phosphite nitrate
 (TAPhi-NO<sub>3</sub>) liquid medium with shaking at 120 rpm
 or on solid agar and 150 µmol m<sup>–2</sup>
 s<sup>–1</sup> light intensity from a combination of cool- and
 warm white LED tubes (light spectra as reported in). 500 mL algal cultures
 were agitated with stirring in Erlenmeyer flasks under the same growth
 conditions. <strong>Plasmid construction, algal
 transformation, and screening for sesquiterpenoid synthase
 expression</strong> Heterologous expression of
 sesquiterpenoid synthases (STPSs) in <em>C. reinhardtii
 </em>was achieved through synthetic transgene redesign based on the
 amino-acid sequences of each STPS, following previously established
 protocols. We selected 21 STPSs from various species encoding isoforms
 that yield nine different STP skeletons (Table 1). Targeted STPSs for
 aristolochene, δ-guaiene, santalene, valencene, valerianol, zizaene,
 τ-cadinol, bisabolol, and patchoulol were designed; all accession numbers
 are listed in Table 1. Their amino-acid sequences were used to generate
 algal-adapted nucleotide coding sequences using the Intronserter
 programme. This programme back-translates amino-acid sequences to
 frequently used codons, removes unwanted restriction sites, and
 systematically integrates the first intron of
 <em>Cr</em>RBCS2i1 at a set distance to enable expression from
 the <em>C. reinhardtii</em> nuclear genome, as previously
 reported. Algal-adapted coding sequences were synthesised and sub-cloned
 into pOptimized_3 expression plasmids by Genscript (Piscataway, NJ, USA).
 Ketocarotenoid biosynthesis in alga was achieved by transformation with
 the pOpt2_<em>Cr</em>BKT_aadA plasmid, and knockdown of
 <em>C. reinhardtii </em>squalene synthase (Uniprot: A8IE29)
 was achieved using the previously reported luciferase–artificial microRNA
 expression plasmid pOpt2_
 <em>c</em>CA_<em>g</em>Luc-TAA_i3_ami_Spec. Both
 plasmids confer resistance to spectinomycin as a selectable marker.
 Combining both cassettes into a single plasmid was unsuccessful.
 Co-transformation of both plasmids and selection on spectinomycin was
 combined with robotics assisted colony picking and plate-level screening
 of 768 transformants to find those with luciferase activity (indicative of
 SQS knockdown) and a brown-colony phenotype from
 <em>Cr</em>BKT-mediated ketocarotenoid biosynthesis. All
 plasmid constructs used are listed in Supplementary Table 6 and the
 complete annotated plasmid sequences are available in Supplementary File
 5. The glass-bead protocol was used to transform the
 nuclear genome of <em>C. reinhardtii </em>with a plasmid DNA.
 Each plasmid was linearised using restriction enzymes
 (<em>Xba</em>I + <em>Kpn</em>I, Thermo Scientific
 FastDigest), and 10 µg of DNA was used for each transformation. Following
 an ~8 h recovery period in liquid TAPhi-NO<sub>3</sub> medium
 under low light, algal cells were plated on a selective medium with
 paromomycin (10 µg mL<sup>–1</sup>), spectinomycin (200
 µg mL<sup>–1</sup>) or zeocin (15
 µg mL<sup>—1</sup>) antibiotics either individual or
 combinations of selection agents relative to each target plasmid. Plates
 were illuminated continuously for ~7 d before colony picking. A PIXL robot
 (Singer Instruments, Watchet, UK) transferred up to 384 colonies per
 transformation event to TAPhi-NO<sub>3</sub> agar plates.
 After an additional 3 d, a ROTOR robot (Singer Instruments) was used to
 replicate colonies onto new medium and plates containing amido black (150
 µg mL<sup>–1</sup>) for fluorescence screening as previously
 described. All algal-optimised STPSs were expressed as
 fusions with mVenus (yellow fluorescent protein) or the monomeric teal
 (cyan) fluorescent protein 1 (mTFP1). Transgene expression of each STPS
 was determined by fluorescence imaging at the agar-plate level, as
 previously described. Chlorophyll fluorescence was observed with 2 sec of
 475/20 nm excitation and 640/160 nm emission to show colony
 presence/absence on amido black-containing plates. Cyan-green fluorescence
 was captured with 420/20 nm excitation and 480/20 nm emission filters
 using 2.5 min exposure. Yellow fluorescent signals were captured with
 504/10 nm excitation and 530/10 nm emission filters with 30-sec exposures.
 Transformants displaying strong fluorescent-protein signals were selected
 and inoculated into 12-well plates containing 2 mL of liquid
 TAPhi-NO<sub>3</sub> medium and grown with shaking at 160 rpm.
 Predicted molecular masses of the expressed heterologous STPS–FP fusions
 were verified using sodium dodecyl sulphate-polyacrylamide gel
 electrophoresis (SDS–PAGE) in-gel fluorescence against the fusion-protein
 fluorescent reporter. <strong>Heterologous
 sesquiterpenoid biosynthesis analyses</strong>
 For each transformant, biosynthesis of heterologous STPs was
 assessed by gas chromatography–mass spectrometry (GC–MS/FID). Four
 individual transformants containing each plasmid with the highest
 fluorescence signals were selected, and solvent–culture two-phase living
 extractions were performed using a 10% v/v dodecane–culture overlay in
 6-well plates, as previously reported<sup>17,53</sup>.
 Cultivations were performed in biological triplicate for 6 d in 4.5 mL
 TAPhi-NO<sub>3</sub> media with 500 µL dodecane overlay.
 Phases were separated, and culture samples were taken for cell-density
 analysis by flow cytometry as previously described, and dodecane was spun
 at 20,000 x <em>g</em> for 3 min,  then 150 µL clarified
 solvent was transferred into amber GC vials in triplicate prior to
 analysis. Samples were analysed as previously described
 using an Agilent 7890A gas chromatograph equipped with a mass spectrometer
 and a flame-ionisation detector (GC–MS/FID). The gas chromatograph
 comprises a 5975C inert MSD with a triple-axis detector and a DB-5MS
 column (30 m × 0.25 mm i.d., 0.25 μm film thickness). The injector,
 interface, and ion-source temperature profiles were set to 250°C, 250°C,
 and 220°C, respectively. In splitless mode, 1 μL of the sample was
 injected using an autosampler (G4513A, Agilent). The column flow was
 constant at 1 mL min<sup>−1</sup>, with helium as carrier gas.
 The initial GC oven temperature was set to 80°C for 1 min, increased to
 120°C at 10°C min<sup>−1</sup>, raised to 160°C at 3°C
 min<sup>−1</sup>, and to 240°C at 10°C
 min<sup>−1</sup>, holding for 3 min. After a 12-min solvent
 delay, mass spectra were recorded using a scanning range of 50–750
 <em>m/z</em> at 20 scans per second. Chromatograms were
 analysed with MassHunter Workstation software version B.08.00 (Agilent),
 and STPs were identified using the National Institute of Standards and
 Technology (NIST) library (Gaithersburg, MD, USA). Further identification
 was conducted with purified standard calibration curves ranging from
 concentrations of 1–1,200 μM in dodecane of δ-guaiene (CAT#B942760),
 patchoulol (CAT#P206200), santalene (CAT#S15065), valerianol (CAT#V914000,
 Toronto Research Chemicals, ON, Canada), bisabolol (CAT#95426), valencene
 (CAT#06808), cedrene (CAT#22133, Sigma-Aldrich, MO, USA) (Supplementary
 Fig. 6). For compound identification, retention-time acquisition, internal
 digital-library calibration, and method development, we used a set of 12
 microampules containing a standard terpene mixture, which covered 98
 terpenes at 1 mM in methanol (CAT# MSITPN101, MetaSci, ON, Canada,
 Supplementary Table 4). <strong>Two-dimensional
 Gas chromatography time-of-flight mass spectrometry (GCxGC–TOF/MS)
 analysis</strong> Comprehensive two-dimensional
 gas chromatography time-of-flight mass spectrometry (GCxGC–TOF/MS)
 analysis of agarwood and distillate extracts in acetone was performed
 using an Agilent 7890B gas-chromatography system equipped with a Zoex ZX1
 cryogenic thermal modulator and a JEOL TOF MS (AccuTOF GCx-plus, JEOL,
 Japan). The GCxGC system featured a normal (non-polar x mid-polar)
 two-dimensional column configuration, comprising a first-dimension column
 with a 30 m non-polar HP-5MS UI capillary column
 (5%-phenyl-methylpolysiloxane) and a second-dimension column with a 2 m
 mid-polar BPX-50 capillary column (50% phenyl polysilphenylene-siloxane).
 We used helium (99.999%) as the carrier gas at a constant flow rate of 0.8
 mL min<sup>−1</sup>. The GCxGC–TOF/MS injector temperature was
 maintained at 300°C with a 10:1 split ratio. The oven temperature was
 initially held at 80°C for 1 min, then increased to 325°C at 2°C
 min<sup>−1</sup>. The modulation period was set at 6 s with a
 pulse time of 0.35 ms. The mass spectrometer operated in electron
 ionisation (EI+) mode at 70 eV. Both the transfer-line and ion-source
 temperatures were maintained at 250°C. The detector voltage of TOF was set
 to 2,500 Volts, and data were acquired at a rate of 50 Hz. Mass spectra
 were obtained within a mass-to-charge ratio (<em>m/z)
 </em>from 50 to 600. <strong>Gas
 chromatography data analysis</strong> The
 analysis of terpenoid extracts followed a procedure similar to previously
 reported methods, and qualitative analyses primarily relied on the
 retention index and match factor. The GC–MS/FID data were processed using
 the MassHunter Workstation software version B.08.00 (Agilent Technologies,
 USA). The identification of compounds was assisted by the NIST Mass
 Spectral Library Version 2.3 (National Institute of Standards and
 Technology, Gaithersburg, MD, USA). The mass-spectral data, derived from
 the GCxGC–TOF/MS analysis, were evaluated with GC Image<sup>TM
 </sup>Version 2.9 software (Lincoln, NE, USA) and referenced against
 the NIST2020/EPA/NIH EI Mass Spectral Library. The spectral data were
 cross-referenced with library spectra to identify potential chemical
 structures, facilitated by calculating the match factor and probability,
 thereby generating a list of probable compound matches. The match factor
 directly compares the unknown mass spectrum peaks with those in the
 library spectra, indicating their similarity. In contrast, the probability
 determines the relative likelihood of the list of hits being accurate,
 assuming that the unknown spectrum is present in the library. Using these
 metrics provides the relative assuredness of matching chemical structures
 within the library spectra.
 <strong>Sesquiterpenoid production and
 concentration</strong> Transformants of
 best-performing STPS isoforms that accumulated the most of each
 heterologous sesquiterpenoid in screening conditions, were subjected to
 solvent–culture two-phase cultivations at 300 mL scale in TAPhi-NO3 medium
 using FC-3283 as a solvent underlay phase, as previously described.
 FC-3283 is a perfluorinated amine that is inert and denser than water,
 forming an underlay to the culture and accumulating heterologous terpene
 products from the algae. After 6 days of cultivation, gravity and gentle
 centrifugation separated the fluorocarbon and cultures. After
 centrifugation to clarify, fluorocarbons were subjected to liquid–liquid
 extraction to partition accumulated STPs into an equal volume of 96%
 ethanol. The mixture was shaken for 16 h at room temperature at 200 rpm.
 Next, samples were again centrifuged gently to further separate the
 phases. FC-3283, after ethanol extraction, can be reused on algal cultures
 and is effectively recycled in this process. 500 μL aliquots from each
 phase were sampled and stored in separate GC vials at –20°C for subsequent
 analysis and separation performance quantification. For
 each of the nine STPs biosynthesised by the algae, 20 mL 96%
 ethanol-containing STOs were generated. The ethanol fractions were pooled
 and subjected to organic solvent nanofiltration (OSN) in a dead-end cell
 to concentrate the terpenes in ethanol without evaporative losses. A
 Duramem solvent-resistant membrane (Evonik, Germany) with a nominal
 molecular weight cut-off value of 300 g mol<sup>–1</sup>
 suitable for STP retention and chemical compatibility with ethanol was
 selected. The 200 mL ethanol–sesquiterpenoid mixture was loaded into the
 OSN chamber containing a 16 mm membrane disc and subjected to 20 bar
 pressure delivered by CO<sub>2</sub> as an inert gas, to drive
 the ethanol phase through the nanofiltration membrane at 2.84 L
 m<sup>–2</sup> h<sup>–1</sup> flux. While ethanol
 permeated the membrane, STPs were kept in the retentate due to their
 molecular weight and consequently concentrated in the ethanol. The
 permeate ethanol is suitable for recycling and can be reused in subsequent
 liquid–liquid extraction processes. <strong>Bulk
 hydroxylation of sesquiterpenoid backbones</strong>
 To selectively introduce hydroxyl groups at the double bonds
 present in the terpenes, hydroboration-oxidation reactions were performed
 using two distinct organoboron reagents: borane–tetrahydrofuran complex
 (BH<sub>3</sub>·THF) (CAT#176192, Sigma-Aldrich) and
 9-borabicyclo[3.3.1]nonane (151076, Sigma-Aldrich). Three different
 stoichiometric ratios (0.5, 1.0, and 2.0) were explored for each reagent
 to investigate different degrees of hydroxylation within the STP mixture.
 The sterically hindered 9-BBN was anticipated to selectively react with
 the least sterically demanding sites of the terpenes, while the
 borane–tetrahydrofuran complex was expected to facilitate hydroxylation
 even at the more challenging endocyclic positions. To remove residual
 ethanol and water content from the concentrated terpene mixture, a rotary
 evaporator was used under reduced pressure at 40°C, ensuring effective
 removal without compromising the integrity of the terpenes. To ensure the
 complete removal of water, molecular sieves (CAT#105734, Sigma-Aldrich)
 were added to the terpene–THF solvent mixture. The reactions were carried
 out in anhydrous tetrahydrofuran (THF, Sigma-Aldrich) to enable removal by
 evaporation after completion. Hydrogen peroxide
 (H<sub>2</sub>O<sub>2</sub>, 30%, VWR Chemicals)
 and sodium hydroxide aqueous solution (NaOH, Sigma-Aldrich) were used to
 convert the organoboron intermediates into non-toxic, water-soluble boric
 acid after the reaction. All subsequent terpene derivatives were extracted
 from the aqueous mixture with ethyl acetate.
 <strong>Data analysis</strong>
 To evaluate the impact of engineered modifications on STP
 biosynthesis and growth characteristics in <em>C. reinhardtii
 </em>strains, one-way analysis of variance (ANOVA) was performed to
 compare mean STP (patchoulol) titres and growth rates among different
 transformants and the parental control strain. This statistical approach
 allowed for the simultaneous analysis of differences between multiple
 groups, to provide a robust assessment of the experimental manipulations.
 ANOVAs were performed separately for STP titres and growth rates under
 mixotrophic and phototrophic conditions. Post-hoc pairwise comparisons
 using Tukey's HSD were conducted to identify which groups were
 statistically significantly different. A one-way ANOVA was used to assess
 the effects of differences in STP biosynthesis among tested strategies
 (single or double transformation), followed by a post hoc Tukey's HSD
 test for specific pairwise data-set comparisons. Mean production values
 (in fg cell<sup>–1</sup> and mg L<sup>–1</sup>)
 for each STP were compared, considering standard deviations to evaluate
 data variability. Mean values were considered statistically significantly
 different at a level of <em>p </em>&lt; 0.05. For data
 analyses, JMP v.16 (SAS Institute Inc, NC, USA) and Rstudio 3.6.2 (Posit
 Software, Boston, USA) were used. Data visualisation was done using JMP
 v.16 and GraphPad Prism v.10 (GraphPad Software, MA, USA). Image
 adjustments involved ColourChecker calibration (Calibrite LLC, DE, USA)
 paired with Adobe Lightroom (Adobe Inc., CA, USA) for colour accuracy. The
 Gardner Colour Scale was used for agarwood sample assessment. Images were
 cropped and organised in Affinity Photo v.1.10.6 (Serif Ltd., WB, UK).
 Analysis of images and assignment of colour values according to the
 Gardner scale was conducted using ImageJ software (NIH, USA). Diagrams and
 illustrations were made using Affinity Designer v.1.10.6 (Serif Ltd., WB,
 UK), chemical structures with ChemDraw v.20.1 (PerkinElmer, MA, USA) and
 all visual elements were harmonised in Affinity Publisher v.1.10.6 (Serif
 Ltd., WB, UK).
description: This README file was generated on 2024-01-12 by Sergio Gutiérrez # General
 information ## Dataset Title A Synthetic Biology and Green Bioprocess
 Approach to Recreate Agarwood Sesquiterpenoid Mixtures ## Date of Data
 Collection 2022-2023 ## Contributors * Sergio Gutiérrez, Sebastian
 Overmans, Gordon B. Wellman: Bioengineering Program, BESE Division, KAUST,
 Thuwal, Saudi Arabia. * Vasilios G. Samaras: Analytical Chemistry Core Lab
 (ACL), KAUST, Thuwal, Saudi Arabia. * Claudia Oviedo: Advanced Membranes
 and Porous Materials Center (AMPM), PSE Division & Environmental
 Science and Engineering Program, BESE Division, KAUST, Thuwal, Saudi
 Arabia. * Martin Gede: AMPM, PSE Division & Chemical Engineering
 Program, KAUST, Thuwal, Saudi Arabia. * Gyorgy Szekely: AMPM, PSE
 Division, Environmental Science and Engineering Program, BESE Division
 & Chemical Engineering Program, KAUST, Thuwal, Saudi Arabia. * Kyle J.
 Lauersen (Corresponding Author): Bioengineering Program, BESE Division,
 KAUST, Thuwal, Saudi Arabia. ## Overview This supplementary dataset,
 integral to our research paper, contains data crucial for understanding
 the key findings of our study. It includes multidimensional
 chromatographic and mass spectrometric analysis data, making it a valuable
 resource for metabolomics, phytochemistry, and related fields. The dataset
 presents diverse metabolic profiles and is ideal for comparative studies,
 compound identification, and bioinformatics analysis. The raw data from
 GCxGC-TOF/MS is in its original format, promoting transparency and
 allowing for varied data processing and analysis methods, thus
 facilitating diverse scientific interpretations and collaborative
 research. ## Data Formats ### **Metadata and Binary Files:** * **.nc
 (NetCDF)**: * Contains detailed mass spectrometry data, including the
 mass-to-charge ratio (m/z) range from 50 to 600, crucial for understanding
 the metabolite profiles. * **Excel Files:** * **.xlsx/.xls**: Utilized for
 organizing and presenting data summaries and metadata, possibly including
 retention times, peak areas, and compound identifications. * **Text
 Files:** * **.txt**: May include methodological details, parameter
 settings for the GCxGC–TOF/MS system, or additional notes relevant to the
 experiments. * **GenBank Files:** * **.gbk/.gb**: Essential for detailing
 the genetic constructs used in the engineered algae strains, if relevant
 to the dataset. ### **Additional File Types:** * **.xlm**: Excel macro
 files, potentially containing scripts for automating data processing steps
 or analysis functions. * **.pei, .cpl, .dfa, .gci, .RBC, .RBS**:
 Proprietary or instrument-specific formats related to the GCxGC-TOF/MS
 system, likely containing instrumental settings, method details, or other
 operational data. These file types reflect the specific configurations and
 methodologies employed, as detailed in the materials and methods section.
 * **log**: Log files documenting the operational details of the
 GCxGC-TOF/MS analyses, including temperature settings, flow rates, and
 modulation periods. ## Recommended Software for Data Analysis: ###
 GCxGC-TOF/MS Data Analysis: * **Primary Software**: GC Image™ Version 2.9
 - Ideal for processing and visualizing .raw, .d, and .cdf files from
 agarwood samples. * **Alternative Software**: OpenChrom - An open-source
 alternative that can handle various chromatography data formats. ###
 GC-MS/FID Data Analysis: * **Primary Software**: ChromaTOF (LECO) -
 Suitable for LECO instrument data. * **Additional Options**: Agilent
 MassHunter - For Agilent instrument data; also supports a range of GC/MS
 file formats. ### Genomic Data Analysis: * **Software Options**:
 NCBI's BLAST, Artemis, and GBRAP (GenBank Retrieving, Analyzing, and
 Parsing software) for handling .gbk/.gb files. ### Additional File Types:
 * **.xlm Files**: Microsoft Excel - For handling Excel macro files. *
 **.pei, .cpl, .dfa, .gci, .RBC, .RBS**: Proprietary or instrument-specific
 formats related to the GCxGC-TOF/MS system, likely containing instrumental
 settings, method details, or other operational data. These file types
 reflect the specific configurations and methodologies employed, as
 detailed in the materials and methods section. * **.log**: Log files
 documenting the operational details of the GCxGC-TOF/MS analyses,
 including temperature settings, flow rates, and modulation periods. ##
 Usage, Compatibility, and Accessibility This dataset encompasses a wide
 range of file formats, catering to diverse research needs in the fields of
 metabolomics and genomics. By providing data in its original formats, from
 raw spectral files to GenBank genetic sequences, we ensure comprehensive
 access and maintain the integrity of the information. We acknowledge that
 the dataset includes certain proprietary file types, such as .pei files,
 which are specific to the instruments and software used in our study.
 While these files are not essential for the primary data analysis, they
 are included to offer complete transparency regarding all the data
 generated during the research. This approach ensures that researchers have
 access to the fullest possible data set, providing an in-depth view of the
 study's methodologies and findings. Researchers are encouraged to use
 the original data formats for their analyses to ensure the accuracy and
 reliability of their results. However, we understand that some file
 formats may require specific software or tools for access. In such cases,
 or for any assistance with data conversion and analysis, researchers are
 welcome to contact the authors. We are committed to providing support and
 guidance to facilitate the effective use of this comprehensive dataset in
 further research and analysis. # Content: Supplementary files
 Supplementary Information File and Data within the Paper This file, along
 with the data presented in the main paper, provides comprehensive support
 for our research findings. It includes results from advanced analytical
 techniques: * **GCxGC-TOF/MS**: Detailed metabolomic analysis of agarwood
 samples. * **GC-MS/FID**: Analytical data from the study of
 genetically engineered algae strains. These datasets serve to substantiate
 the conclusions drawn in our study and are valuable for further scientific
 exploration and verification. ## 1. GCxGC-TOF/MS Raw Data Analysis of
 Agarwood Samples The dataset comprises extensive raw data files from
 GCxGC-TOF/MS analysis of agarwood samples. For optimal analysis and
 interpretation, we recommend using GC Image™ Version 2.9 software, a
 specialized tool for processing and visualizing GCxGC-MS data. Its
 tailored features ensure a precise and detailed examination of the complex
 metabolic profiles present in these samples. ## 2. GCxGC-TOF/MS Data
 Report for Agarwood Samples: This report presents a synthesized overview
 of the GCxGC-TOF/MS data, providing insights into the metabolic
 complexities of the agarwood samples. The report includes interpreted
 results, key findings, and relevant analytical parameters, offering a
 comprehensive understanding of the data. ## 3. GC-MS/FID Raw Data of
 Engineered Algae Strains: Raw data files from GC-MS/FID analysis are
 included, offering an in-depth look at the metabolic impacts of genetic
 engineering in algae strains. This data is crucial for understanding the
 metabolic pathways and the effects of genetic modifications. ## 4. Genetic
 Constructs Documentation: Detailed information on the genetic constructs
 used in the engineering of the algae strains is provided. These documents
 (.gbk/.gb files) include genetic sequences, annotations, and experimental
 design parameters, essential for replicating the experiments and
 comprehending the genetic modifications involved. # Supplementary File 1.
 ## File Format Excel File (.xlsx) ## Content Overview This file presents a
 detailed report for 58 agarwood samples, including both distillate
 ("Oudh") and wood pieces ("Bahkour"). ## Structure of
 the File **Tabs in Excel File** Each tab corresponds to one sample,
 ensuring organized data presentation. ### **Content in Each Tab** ####
 **Two-Dimensional Gas Chromatogram Image** * Displays the 2D gas
 chromatogram for each distillate sample, with an m/z range of 50-600. *
 Includes blob detection visualizations from GCxGC-TOF/MS, highlighting
 significant features in the chromatograms. #### **Compound Detection
 Table** Detailed listing of the top compounds detected in each sample
 through GCxGC-TOF/MS analysis using GC Image™ Version 2.9 software. ####
 **Table Columns** * **BlobID**: Unique identifier for each detected
 compound or feature in the chromatogram. * **Compound Name**: The probable
 identification of the detected compound. * **Hit Formula**: Molecular
 formula of the probable compound. * **Hit CAS#**: Chemical Abstracts
 Service number, a unique identifier for the chemical substance. * **Hit
 Base Peak**: The most intense peak (mass-to-charge ratio) in the mass
 spectrum of the compound. * **Retention I (min)**: The first dimension
 retention time in minutes. * **Retention II (sec)**: The second dimension
 retention time in seconds. * **Peak Value**: The intensity of the
 chromatographic peak. * **Volume**: The integrated total volume of the
 peak, reflecting the compound's abundance. ## Purpose and Utility *
 Provides an in-depth chemical profile for each agarwood sample, useful for
 comparative analysis, quality control, or further research into the
 metabolomic properties of agarwood. * The combination of visual
 chromatograms and detailed quantitative data offers a comprehensive tool
 for researchers in phytochemistry, fragrance industry, or related fields.
 # Supplementary File 2. ## File Format  Zip File (.zip) ## Content
 Overview This extensive collection contains all raw data files from
 GCxGC-TOF/MS analysis of 58 agarwood samples, encompassing both
 distillates ("Oudh") and wood pieces ("Bahkour"). ##
 Sample Folders Overview Each folder, labeled from 01 to 58, corresponds to
 a specific sample in the dataset. Within these sample folders, data is
 meticulously organized into several subfolders, each designated for a
 distinct type of data crucial for the comprehensive analysis of the
 samples: ### **AM Folder (Analytical Method)** #### Overview Housing files
 that comprehensively detail the analytical methods and instrument settings
 utilized in the study. This folder offers crucial insights into the
 experimental approach and the technical nuances of the instrumentation.
 #### **File Types** * **.pei**: Proprietary information related to the
 specific instrumentation used in the study. These files may include
 detailed instrument settings or configurations. * **.xml**: Methodological
 information. In this context, it could detail the parameters and settings
 used in the gas chromatography and mass spectrometry analyses. * **.pm**:
 Scripts or data processing information. These files are instrumental in
 understanding the computational approaches used in analyzing the data.
 #### Subfolder Structure Does not contain subfolders, indicating a direct
 and consolidated approach to storing methodological data. This streamlined
 structure facilitates quick access to important methodological information
 and instrumental configurations used in the study. ### **CA Folder
 (Chromatographic Analysis)** #### Overview Dedicated to storing
 chromatographic data, which is fundamental for the analysis of compound
 separation and identification in the samples. This data is integral to
 understanding the distinct chromatographic profiles, aiding in the
 accurate identification and characterization of various compounds. The
 provided data and scripts enable a detailed analysis of the
 chromatographic separation, offering insights into the chemical
 composition and behavior of the samples under study. The inclusion of
 calibration and assignment data further enhances the reliability and
 interpretability of the chromatographic analysis. #### **File Types** *
 **.xml**: These files typically contain metadata or detailed information
 about the chromatographic analysis procedures, such as gradient profiles,
 temperature settings, and detector settings. * **.pl (Perl Scripts)**:
 Likely used for processing chromatographic data or automating certain
 aspects of data analysis, these scripts can be essential for custom
 analysis tasks or data manipulation. #### Subfolder Structure The CA
 Folder includes a single subfolder labeled as '0' (indicating
 the number zero), which corresponds to a specific set of chromatographic
 reads or analyses. * **Assign.xml**: Contains assignment data for
 chromatographic peaks, linking them to specific compounds or compound
 classes. * **Calib.xml**: Holds calibration data crucial for ensuring
 accurate and consistent chromatographic analyses across samples. *
 **Peak.pl**: A Perl script file, which may be used for processing peak
 data, such as identifying, quantifying, or categorizing chromatographic
 peaks. ### MC Folder (Mass Chromatography) #### Overview Containing mass
 spectrometry data files that are essential for the characterization and
 analysis of compounds. This folder provides a comprehensive view of the
 molecular components present in the samples. #### **File Types** *
 **.xml**: Contains metadata or methodological information related to mass
 spectrometry. * **.cpl**: Likely includes information related to
 chromatographic peaks, which could be instrumental in identifying and
 quantifying compounds. * **.pm**: May contain scripts or data processing
 information pertinent to mass spectrometry analysis. * **.dfa**: Typically
 stores detailed mass spectrometric data, which could include
 mass-to-charge ratios, peak intensities, and spectral information vital
 for molecular analysis. #### Subfolders Organization The MC Folder is
 organized into five numerical subfolders (0 to 5), each corresponding to a
 specific read or type of data collected during the analysis. The contents
 of each subfolder are tailored to provide a focused view of the data
 relevant to that particular read: * **Meta.xml (in each subfolder)**:
 Stores metadata specific to each read, providing contextual information
 that aids in the interpretation of the data. * **Peak.cpl (in each
 subfolder)**: Contains data related to chromatographic peaks observed in
 each read, crucial for understanding the compound profiles. * **Proces.pm
 (in each subfolder)**: Likely includes scripts or processing parameters
 used in the analysis of the mass spectrometry data for that particular
 read. * **Profile.dfa (in each subfolder)**: Stores the mass spectrometry
 profile data for each read, including detailed information such as
 mass-to-charge ratios and peak intensities. ### RD Folder (Raw Data)
 Contains the unprocessed, raw data directly from the GCxGC-TOF/MS
 instrument. #### **File Types** * **.cdf** (Common Data Format) * **.gci**
 (GC Image Data) * **.RBC** (Raw Binary Chromatogram) * .**RBS** (Raw
 Binary Spectrometry) * **.log** (Log Files) ## Note We acknowledge the
 presence of certain proprietary file types within this folder, such as
 .pei, .cpl, .dfa, .gci, .RBC, and .RBS. While these files may not be
 essential for standard data analysis, they have been included to uphold
 transparency and provide a holistic view of all data generated during our
 study. These proprietary files offer a comprehensive insight into the
 intricacies of our instrumentation and methodological configurations. They
 serve as a testament to the rigor and thoroughness of our research
 process. Researchers who do not require detailed knowledge of instrument
 settings or specific methodological configurations may prioritize their
 attention on the standard data files for their analyses. ## Recommended
 Software for Data Analysis ### **Primary Recommendation** **GC Image™
 Version 2.9**: This software is highly recommended for its exceptional
 capabilities in handling GCxGC-TOF/MS data. It excels in visualizing and
 interpreting complex chromatographic datasets, making it a crucial tool
 for thorough analysis of the data in this study. ### **Additional Software
 Options** * **ChromaTOF (LECO)**: Particularly suited for processing data
 from LECO instruments. It is compatible with various GCxGC data formats,
 making it a versatile choice for data analysis. * **OpenChrom**: A robust
 open-source alternative that supports a wide range of chromatography and
 mass spectrometry data formats. It is particularly useful for handling
 .cdf and .mzML files, offering a flexible solution for data analysis. *
 **Agilent MassHunter**: An excellent option for analyzing data from
 Agilent instruments. It also supports a broad spectrum of GC/MS file
 formats, providing a comprehensive tool for data analysis. * **NIST
 AMDIS**: A powerful software for deconvolution and compound identification
 in mass spectrometry. It is compatible with standard formats like .ms,
 making it invaluable for detailed molecular analysis. * **Thermo
 Xcalibur**: Designed primarily for data from Thermo Fisher instruments.
 This software may also support additional formats like .raw, offering
 flexibility for data analysis across different instrument platforms. *
 **AnalyzerPro XD** (SpectralWorks): A productivity software with support
 for two-dimensional chromatography and Direct MS, suitable for complex
 data sets​​. * **AnalyzerPro** (SpectralWorks): Offers workflows for
 sample-to-sample comparison, target component analysis, quantitation, and
 library searching across LC-MS and GC-MS platforms​​. * **RemoteAnalyzer**
 (SpectralWorks): An open access software solution optimized for managing
 multiple types of analyses and instrument types from various vendors,
 suitable for diverse laboratory settings​​. ## Note on Proprietary File
 Types and Equipment Used * The dataset includes proprietary file types
 such as .pei, .cpl, .dfa, .gci, .RBC, and .RBS. These formats are specific
 to the chromatography and mass spectrometry instruments used in this
 study. The primary equipment includes an Agilent 7890B gas-chromatography
 system, a Zoex ZX1 cryogenic thermal modulator, and a JEOL TOF MS (AccuTOF
 GCx-plus, JEOL, Japan). These files offer comprehensive details on the
 instrumental and methodological setup used for the GCxGC-TOF/MS analysis.
 * While these proprietary files provide full transparency regarding data
 generation, they may require specific software for access, closely
 associated with the aforementioned equipment. For complete information on
 the analytical methods, instrument settings, and experimental procedures,
 please refer to the 'Materials and Methods' section of the
 dataset documentation. This section will provide additional context and
 guidance for understanding and utilizing these specialized file types
 effectively. ## Purpose and Utility * This file is a comprehensive
 resource for researchers aiming to conduct detailed analyses of agarwood
 samples. * The structured and clearly labeled folders make navigating the
 dataset efficient, allowing for targeted analyses of specific samples or
 comparative studies across the collection. * Offering raw data in this
 format empowers researchers to apply their analytical techniques,
 fostering diverse investigations in metabolomics, phytochemistry, and
 other relevant fields. # Supplementary File 3. ## File Format Zip File
 (.zip) ## Content Overview Supplementary File 3 encompasses a
 comprehensive collection of GC-TOF/MS raw data, meticulously obtained from
 GCxGC-TOF/MS analysis of 58 distinct agarwood samples. This includes both
 agarwood distillate, known as “Oudh,” and agarwood wood pieces, referred
 to as “Bahkour.” ## Structure and Data Organization * **Data Files**: The
 folder contains 58 individual text files (.txt), each distinctly labeled
 to correspond with the sample number (e.g., 01, 02, 03, etc.). * **File
 Contents**: * Each file houses data organized into two primary columns: *
 **Time of Elution Column**: Indicates the elution time in the Gas
 Chromatography (GC) process, measured in minutes. * **TOF-MS Response
 Column**: Shows the response recorded by the Time-Of-Flight Mass
 Spectrometry (TOF-MS) detector at the specific elution times. * This
 structured data format allows users to effectively reconstruct
 one-dimensional chromatograms for each sample. ## Purpose and Utility * By
 providing the elution time and corresponding TOF-MS responses, researchers
 can visualize the 'Y' axis as the detector response and the
 'X' axis as the time of elution, facilitating a clear
 understanding of the chromatographic behavior of each sample. * This data
 set is particularly useful for studies focusing on the identification of
 specific compounds, time-resolved analysis, and quantitative assessments
 in the context of agarwood research. # Supplementary File 4. ## File
 Format  Excel File (.xlsx) ## Content Overview Supplementary File 4
 comprises raw data obtained from GC-MS/FID analysis of engineered algae
 strains, presented in a structured and accessible Excel format. This data
 is vital for understanding the metabolic alterations in these strains. ##
 Structure and Data Organization * **Columns in Excel File**: * The first
 column of the Excel file details the time of elution in the Gas
 Chromatography (GC) process, measured in minutes. * Subsequent columns are
 dedicated to the Mass Spectrometry Detector (MSD) response at each elution
 time for a series of samples, including: * Blank (Dodecane) * Santalene
 (A) * Zizaene (B) * Aristolochene (C) * Valencene (D) * Delta-guaiene (E)
 * Cadinol (F) * Valerianol (G) * Patchoulol (H) * Bisabolol (I) ## Purpose
 and Utility * This data is instrumental for researchers in reconstructing
 one-dimensional chromatograms for each of the specified samples. * The
 chromatograms can be visualized with the 'Y' axis representing
 the MSD response and the 'X' axis representing the time of
 elution. * Chromatographic representations are crucial for analyzing the
 presence and concentration of various compounds in the engineered algae
 strains. # Supplementary File 5. ## File Format GenBank File (.gb or .gbk)
 ## Content Overview This file contains all the plasmid sequences used in
 genetically engineering algae strains in our study. It's essential
 for researchers interested in the genetic aspects of the algae
 modifications. ## Structure and Annotation * **Plasmid Constructs**: The
 file includes sequences of all plasmids used in the experiments. *
 **Annotations**: Each sequence is annotated with details like gene names,
 promoter regions, coding sequences, and resistance genes. These provide
 clear information about each plasmid's function. ## Purpose and
 Utility * The file is useful for examining the specific genetic changes in
 the algae. * Annotations help understand how each plasmid contributes to
 the algae’s genetic modification. ## Software Compatibility and
 Accessibility * **Compatible with Genetic Software**: The file can be
 opened using any genetic manipulation software that reads GenBank formats.
 * **Ease of Use**: The standard GenBank format and clear annotations make
 the file accessible for those with a background in genetics. ##
 Application in Research * Researchers can use this file for replicating
 the study, conducting genetic analysis, or for further research in genetic
 engineering and synthetic biology. * It serves as a reference for the
 plasmids used, allowing for further experimentation or design
 modifications in related fields.