Part V — Chapter 13

Terpenoid Biosynthesis

The isoprenoid pathway: IPP and DMAPP as universal C5 building blocks, the MEP and MVA biosynthetic routes, prenyl transferases assembling C10–C40 products, and the spectacular diversity of plant terpenes.

MEP (Plastidial) vs MVA (Cytosolic) Pathways

MEP Pathway — 7 Plastidial Steps

The 2-C-methyl-D-erythritol 4-phosphate (MEP) pathway is the major route for terpenoid biosynthesis in plant plastids. It begins with the condensation of pyruvate and glyceraldehyde-3-phosphate (G3P) by 1-deoxy-D-xylulose 5-phosphate synthase (DXS), the committed step and major regulatory point.

Step 1: DXS (DXP synthase)

Pyruvate + G3P + TPP → DXP + CO₂. Thiamine diphosphate-dependent. Rate-limiting; transcript regulated by light and developmental cues.

\( \text{Pyruvate} + \text{G3P} \xrightarrow{\text{DXS, TPP}} \text{DXP} + \text{CO}_2 \)

Step 2: DXR (DXP reductoisomerase)

DXP + NADPH → MEP. Intramolecular rearrangement then reduction. Target for fosmidomycin, an antiparasitic drug that blocks the MEP pathway in Plasmodium.

\( \text{DXP} + \text{NADPH} \xrightarrow{\text{DXR}} \text{MEP} + \text{NADP}^+ \)

Steps 3–5: CDP-ME activation

CMS (CTP-dependent), CMK (ATP-dependent kinase), and MCS (cyclase) convert MEP → CDP-ME → CDP-MEP → ME-cPP (methylerythritol cyclic diphosphate).

Steps 6–7: Ferredoxin-dependent reductions

HDS (HMBPP synthase) and HDR (HMBPP reductase) use reduced ferredoxin (from photosynthesis) to produce HMBPP, then IPP + DMAPP simultaneously in a 5:1 ratio.

\( \text{HMBPP} + 2\,\text{Fd}_{\text{red}} \xrightarrow{\text{HDR}} \text{IPP} + \text{DMAPP} \)

MEP Net Reaction

\( \text{Pyruvate} + \text{G3P} + \text{CTP} + 2\,\text{ATP} + 3\,\text{Fd}_{\text{red}} \rightarrow \text{IPP} + \text{DMAPP} + \text{CO}_2 \)

Plastidial location links MEP pathway activity directly to photosynthetic electron flow via ferredoxin.

MVA Pathway — 6 Cytosolic/ER Steps

The mevalonate (MVA) pathway operates in the cytosol and ER and supplies IPP for sesquiterpenoids, sterols, and triterpenes. The HMG-CoA reductase (HMGR) reaction is the rate-limiting step and the target of statin drugs in animals.

Steps 1–2: HMG-CoA formation

Two acetyl-CoA condense to acetoacetyl-CoA (thiolase), then HMGS adds a third acetyl-CoA to yield HMG-CoA. Compartment: cytosolic.

Step 3: HMGR (rate-limiting)

HMG-CoA + 2 NADPH → mevalonate. Committed, irreversible step. Plants have multiple HMGR isoforms (cytosolic + ER-anchored) regulated by developmental and stress signals.

\( \text{HMG-CoA} + 2\,\text{NADPH} \xrightarrow{\text{HMGR}} \text{MVA} + \text{CoA} \)

Steps 4–6: MVA → IPP

MVK phosphorylates MVA (ATP), PMK phosphorylates again, then MVD decarboxylates to yield IPP. IPP isomerase (IDI) equilibrates IPP ↔ DMAPP.

\( 3\,\text{Acetyl-CoA} + 3\,\text{ATP} + 2\,\text{NADPH} \xrightarrow{\text{MVA pathway}} \text{IPP} + 3\,\text{CoA} + 3\,\text{ADP} + 3\,\text{P}_i + \text{CO}_2 \)

Prenyl Transferases and Terpene Diversity

Once formed, IPP and DMAPP are condensed by prenyl diphosphate synthases in sequential head-to-tail additions. The chain length is determined by the enzyme’s active site geometry:

Enzyme	Product	C length	Downstream terpenes
GPP synthase (GPPS)	Geranyl diphosphate (GPP)	C10	Monoterpenes (e.g., limonene, linalool, menthol)
FPP synthase (FPPS)	Farnesyl diphosphate (FPP)	C15	Sesquiterpenes (e.g., farnesene, artemisinin) + squalene → sterols
GGPP synthase (GGPPS)	Geranylgeranyl diphosphate (GGPP)	C20	Diterpenes (e.g., gibberellin, taxol precursors) + phytol for chlorophyll
Squalene synthase	Squalene (C30)	C30	Triterpenes, sterols, brassinosteroids
Phytoene synthase (PSY)	Phytoene (C40)	C40	Carotenoids (lycopene, beta-carotene, xanthophylls)

Terpene synthases (TPSs) then catalyse cyclisation and rearrangement of the prenyl diphosphate substrates via carbocation intermediates, generating the extraordinary structural diversity of plant terpenes (>50,000 structures). The reaction proceeds through ionisation of the diphosphate ester to form an allylic carbocation, followed by ring closure(s) and proton loss or water capture:

\( \text{GPP} \xrightarrow{\text{monoterpene synthase, Mg}^{2+}} [\text{geranyl}^+] \rightarrow \text{cyclisation} \rightarrow \text{monoterpene} + \text{PP}_i \)

Carotenoid Biosynthesis

Carotenoids are C40 tetraterpenes synthesised entirely in plastids. They function as accessory light-harvesting pigments and essential photoprotectors that quench singlet oxygen and excess triplet chlorophyll.

2 GGPP → Phytoene

PSY (phytoene synthase)

Rate-limiting; regulated by light

Phytoene → Lycopene

PDS + ZDS + CRTISO

4 desaturations + isomerisation; colourless → red

Lycopene → α-carotene

LCY-e + LCY-b

1 epsilon + 1 beta ring

Lycopene → β-carotene

LCY-b × 2

2 beta rings; orange pigment

β-carotene → Zeaxanthin

β-CHX (hydroxylase)

Xanthophyll; epoxidation/de-epoxidation (VDE/ZEP)

Zeaxanthin → Violaxanthin

ZEP (zeaxanthin epoxidase)

Via antheraxanthin; xanthophyll cycle

Violaxanthin → Neoxanthin

NSY

ABA precursor (via xanthoxin)

Isoprene Emission

Isoprene (2-methylbuta-1,3-diene, C5) is the most abundant volatile organic compound (VOC) emitted by vegetation globally (~500 Tg C/yr). It is produced from DMAPP in chloroplasts by isoprene synthase (IspS), a monoterpene synthase that does not cyclise its product.

\( \text{DMAPP} \xrightarrow{\text{IspS, Mg}^{2+}} \text{isoprene} + \text{PP}_i \)

Function: membrane stabilisation at high temperatures, quenching of reactive oxygen species, and possibly anti-herbivory. Emission is controlled by temperature and light (DMAPP pool size). At 40°C, isoprene emission can consume up to 2% of photosynthetically fixed carbon.

Commercially important terpenoids include taxol (diterpene, anti-cancer), artemisinin (sesquiterpene lactone, anti-malarial), menthol (monoterpene), and rubber (polyisoprene, >10,000 IPP units).

Python: MEP vs MVA Carbon & Energy Efficiency

Compare the theoretical carbon efficiency (C in product / C input) and ATP cost per terpenoid carbon produced by the MEP and MVA pathways across terpene classes.

Python

script.py107 lines

import numpy as np
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import matplotlib.patches as mpatches

# Carbon efficiency of MEP vs MVA pathways to IPP/DMAPP
# MEP (2-C-methyl-D-erythritol 4-phosphate) pathway: plastidial
#   Input:  1 pyruvate (3C) + 1 G3P (3C) = 6C
#   Output: 1 IPP (5C) + 1 DMAPP (5C) initially as 1 HMBPP -> both 5C
#   Net:    6C input -> 5C product, 1C lost as CO2 from decarboxylation
#   ATP cost: ~2 ATP + 3 NADPH equivalent (CTP, Fd, NADPH)

# MVA (mevalonate) pathway: cytosolic
#   Input:  3 acetyl-CoA (2C each) = 6C total
#   Output: 1 IPP (5C)
#   Net:    6C input -> 5C output, 1C lost as CO2
#   ATP cost: 3 ATP + 2 NADPH per IPP

# Terpene classes and carbon numbers
terpene_classes = {
    'Isoprene (C5)': 5,
    'Monoterpenes (C10)': 10,
    'Sesquiterpenes (C15)': 15,
    'Diterpenes (C20)': 20,
    'Triterpenes (C30)': 30,
    'Tetraterpenes (C40)': 40,
}

# Number of IPP units needed for each class
ipp_units = {k: v // 5 for k, v in terpene_classes.items()}

# Theoretical carbon efficiency: C in product / C in IPP feedstock
# MEP: 6C input -> 5C product per IPP/DMAPP unit
mep_c_per_ipp = 6.0   # carbons consumed per IPP equivalent
mva_c_per_ipp = 6.0   # carbons consumed per IPP equivalent (3 acetyl-CoA)

# Energy costs per IPP (ATP equivalents; NADPH ~ 2.5 ATP in mitochondria)
mep_atp_per_ipp = 2 + 3 * 2.5   # ~9.5 ATP equivalents
mva_atp_per_ipp = 3 + 2 * 2.5   # ~8.0 ATP equivalents

fig, axes = plt.subplots(1, 3, figsize=(14, 5))
fig.patch.set_facecolor('#0f172a')
for ax in axes:
    ax.set_facecolor('#1e293b')
    ax.tick_params(colors='#94a3b8')
    ax.spines['bottom'].set_color('#475569')
    ax.spines['left'].set_color('#475569')
    ax.spines['top'].set_visible(False)
    ax.spines['right'].set_visible(False)

# Plot 1: Carbon atoms per terpene class
labels = list(terpene_classes.keys())
c_values = list(terpene_classes.values())
short_labels = ['C5', 'C10 (Mono)', 'C15 (Ses)', 'C20 (Di)', 'C30 (Tri)', 'C40 (Tetra)']
colors = ['#a3e635', '#4ade80', '#34d399', '#22d3ee', '#60a5fa', '#a78bfa']
bars = axes[0].bar(short_labels, c_values, color=colors, alpha=0.85, edgecolor='#475569')
axes[0].set_xlabel('Terpene Class', color='#94a3b8', fontsize=9)
axes[0].set_ylabel('Carbon Atoms', color='#94a3b8', fontsize=9)
axes[0].set_title('Terpene Classes by Carbon Number', color='#e2e8f0', fontsize=10)
axes[0].tick_params(axis='x', rotation=45, labelsize=8)
for bar, val in zip(bars, c_values):
    axes[0].text(bar.get_x() + bar.get_width()/2, bar.get_height() + 0.5,
                 str(val), ha='center', va='bottom', color='#e2e8f0', fontsize=8)

# Plot 2: Carbon efficiency (C in product / C input)
n_ipps = list(range(1, 9))
mep_efficiency = [(n * 5) / (n * mep_c_per_ipp) * 100 for n in n_ipps]
mva_efficiency = [(n * 5) / (n * mva_c_per_ipp) * 100 for n in n_ipps]
terpene_carbons = [n * 5 for n in n_ipps]

axes[1].plot(terpene_carbons, mep_efficiency, 'o-', color='#a3e635', linewidth=2,
             markersize=6, label='MEP (plastid)')
axes[1].plot(terpene_carbons, mva_efficiency, 's--', color='#f59e0b', linewidth=2,
             markersize=6, label='MVA (cytosol)')
axes[1].axhline(y=83.33, color='#475569', linestyle=':', alpha=0.6, linewidth=1)
axes[1].text(42, 84, '83.3% theoretical max', color='#64748b', fontsize=7)
axes[1].set_xlabel('Carbon Atoms in Product', color='#94a3b8', fontsize=9)
axes[1].set_ylabel('Carbon Efficiency (%)', color='#94a3b8', fontsize=9)
axes[1].set_title('Carbon Efficiency: MEP vs MVA', color='#e2e8f0', fontsize=10)
axes[1].legend(fontsize=8, facecolor='#1e293b', edgecolor='#475569', labelcolor='#e2e8f0')
axes[1].set_ylim(0, 100)

# Plot 3: ATP cost per terpene carbon produced
mep_atp_per_c = [mep_atp_per_ipp * n / (n * 5) for n in n_ipps]
mva_atp_per_c = [mva_atp_per_ipp * n / (n * 5) for n in n_ipps]

axes[2].plot(terpene_carbons, mep_atp_per_c, 'o-', color='#a3e635', linewidth=2,
             markersize=6, label='MEP pathway')
axes[2].plot(terpene_carbons, mva_atp_per_c, 's--', color='#f59e0b', linewidth=2,
             markersize=6, label='MVA pathway')
axes[2].set_xlabel('Carbon Atoms in Product', color='#94a3b8', fontsize=9)
axes[2].set_ylabel('ATP equivalents / C', color='#94a3b8', fontsize=9)
axes[2].set_title('Energy Cost per Carbon (ATP equiv.)', color='#e2e8f0', fontsize=10)
axes[2].legend(fontsize=8, facecolor='#1e293b', edgecolor='#475569', labelcolor='#e2e8f0')

fig.suptitle('MEP vs MVA Pathway: Carbon & Energy Efficiency', color='#e2e8f0',
             fontsize=12, fontweight='bold', y=1.01)
plt.tight_layout()
plt.savefig('output.png', dpi=110, bbox_inches='tight',
            facecolor='#0f172a', edgecolor='none')
print("MEP pathway C efficiency:", round(5/6*100, 1), "%")
print("MVA pathway C efficiency:", round(5/6*100, 1), "%")
print("MEP ATP/C produced:", round(mep_atp_per_ipp/5, 2))
print("MVA ATP/C produced:", round(mva_atp_per_ipp/5, 2))
print("MVA is more energy-efficient by ~1.5 ATP per IPP; MEP is CO2-independent")

Click Run to execute the Python code

Code will be executed with Python 3 on the server

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