微生物学报

Energy source	Energy conversion stage	Representative limiting steps or processes	Representative systems	Metric type	Typical efficiency range	Primary constraints
Light	Photon capture & charge separation	PSII and antenna complexes	Cyanobacteria, algae	Quantum efficiency (RE)	0.6-0.8 (maximum)	Photo inhibition, reactive oxygen species, formation, limited spectral utilization
Electron transport	Cytochrome b6f complex, PSI	Oxygenic phototrophs	Electron transfer efficiency (RE)	~60%-80%	Proton gradient buildup, diffusion limitation
ATP generation	F-type ATP synthase	Chloroplasts, cyanobacteria	PMF-to-ATP conversion efficiency	~70%-90%	Proton leakage, coupling efficiency
CO₂ fixation	RuBisCO	Plants, cyanobacteria	Turnover rate (k_cat)	~1-10 s^-1	Low catalytic efficiency, oxygenation side reaction
Chemical (H₂)	Primary electron supply	Hydrogenase-mediated electron transfer	Hydrogen-oxidizing bacteria	Electron utilization efficiency (RE)	~50%-80%	Oxygen sensitivity, enzyme kinetics
Chemical (reduced sulfur)	Electron extraction	Sox multienzyme system	Sulfur-oxidizing bacteria	Energy recovery efficiency (EE)	~40%-70%	Multi-step electron loss
Chemical	Respiratory electron transport	Complex I (NADH dehydrogenase)	Chemolithotrophs	PMF generation efficiency	~60%-80%	Electron leakage, membrane coupling efficiency
Electricity	Extracellular electron uptake	EET pathways (cytochromes, nanowires)	Geobacter, Shewanella	Coulombic efficiency (RE)	~40%-80%	Electrode-cell interface resistance, transfer distance
Intracellular redox conversion	NAD(P)H/ferredoxin generation pathways	Electrosynthesis systems	Redox conversion efficiency (RE)	~50%-70%	Inefficient electron integration into metabolism
Chemical/electric	C1 reduction	Formate dehydrogenase	Formatotrophs	Electron utilization efficiency (RE)	~60%-85%	Thermodynamic and kinetic limitations
Acetyl-CoA synthesis	CODH/ACS complex	Acetogens	Carbon fixation efficiency (ECE)	~40%-70%	Oxygen sensitivity, complex metalloclusters

Energy source	Energy conversion stage	Representative limiting steps or processes	Representative systems	Metric type	Typical efficiency range	Primary constraints
Light	Photon capture & charge separation	PSII and antenna complexes	Cyanobacteria, algae	Quantum efficiency (RE)	0.6-0.8 (maximum)	Photo inhibition, reactive oxygen species, formation, limited spectral utilization
Electron transport	Cytochrome b6f complex, PSI	Oxygenic phototrophs	Electron transfer efficiency (RE)	~60%-80%	Proton gradient buildup, diffusion limitation
ATP generation	F-type ATP synthase	Chloroplasts, cyanobacteria	PMF-to-ATP conversion efficiency	~70%-90%	Proton leakage, coupling efficiency
CO₂ fixation	RuBisCO	Plants, cyanobacteria	Turnover rate (k_cat)	~1-10 s^-1	Low catalytic efficiency, oxygenation side reaction
Chemical (H₂)	Primary electron supply	Hydrogenase-mediated electron transfer	Hydrogen-oxidizing bacteria	Electron utilization efficiency (RE)	~50%-80%	Oxygen sensitivity, enzyme kinetics
Chemical (reduced sulfur)	Electron extraction	Sox multienzyme system	Sulfur-oxidizing bacteria	Energy recovery efficiency (EE)	~40%-70%	Multi-step electron loss
Chemical	Respiratory electron transport	Complex I (NADH dehydrogenase)	Chemolithotrophs	PMF generation efficiency	~60%-80%	Electron leakage, membrane coupling efficiency
Electricity	Extracellular electron uptake	EET pathways (cytochromes, nanowires)	Geobacter, Shewanella	Coulombic efficiency (RE)	~40%-80%	Electrode-cell interface resistance, transfer distance
Intracellular redox conversion	NAD(P)H/ferredoxin generation pathways	Electrosynthesis systems	Redox conversion efficiency (RE)	~50%-70%	Inefficient electron integration into metabolism
Chemical/electric	C1 reduction	Formate dehydrogenase	Formatotrophs	Electron utilization efficiency (RE)	~60%-85%	Thermodynamic and kinetic limitations
Acetyl-CoA synthesis	CODH/ACS complex	Acetogens	Carbon fixation efficiency (ECE)	~40%-70%	Oxygen sensitivity, complex metalloclusters

Energy source	Carbon fixation pathway	Engineering strategy	Energy carriers	Representative outcome	References
Light-driven	rGly pathway	Semiconductor-microbe hybrid (MR-1@CdS) enabling photoelectron transfer	ATP, NADH	Sustained acetate production from CO₂ and autotrophic growth	[72]
CBB cycle	InP nanomaterials enhance PSI activity and photosynthetic electron flux	ATP, NADPH	Increased ethylene production	[78]
HWLS pathway	CdS-driven NADH regeneration coupled with proteorhodopsin-mediated ATP synthesis	ATP, NADPH	Product yields exceed theoretical limits (malate, butyrate)	[79]
Artificial CO₂ fixation (ADRP)	Synthetic photosystem generating ATP and NADH	NADH, ATP	Production of pyruvate-derived chemicals with negative carbon footprint	[80]
Electro-driven	rGly pathway	Microbial electrosynthesis with direct cathodic electron supply	ATP, NADH	Efficient acetate synthesis from CO₂	[73]
WL pathway	Direct electron uptake via EET (cytochromes and conductive pili)	ATP, NADH, Fd _red	Acetate production up to 11.05 mmol/L	[81]
WL pathway	Tandem electrocatalysis (CO₂→acetate) coupled with microbial PHB synthesis	ATP, NADH, NADPH	Increased PHB production	[82]
Artificial marine system	CO₂ electroreduction to formate followed by microbial upgrading	H₂, formate, NAD(P)H, ATP	Efficient growth and succinate production in seawater system	[83]
Chemical-driven	CBB cycle	Water splitting to generate H₂ driving hydrogen-oxidizing autotrophy	H₂, NADH, ATP	Isopropanol production up to 216 mg/L	[84]
Ribulose 5-phosphate (RuMP) pathway	Enhanced methanol oxidation and cofactor redistribution	Methanol, NAD(P)H, ATP	Improved growth and product yields	[63]
CBB cycle	Decoupling carbon fixation from energy metabolism using pyruvate	Pyruvate, NADH, ATP	Semi-autotrophic growth and sugar production	[18]
CBB cycle	Reducing energy dissipation and enhancing FDH activity	Formate, NADPH, ATP	Improved CO₂-to-sugar conversion	[19]
rGly pathway	Combined methanol and formate oxidation for redox supply	Methanol, formate, NAD(P)H, ATP	Improved growth and carbon utilization	[85]
Serine pathway	NADPH-generating methanol dehydrogenase and PPP enhancement	Methanol, NADPH, ATP	Increased product yield with maintained growth	[86]

Energy source	Carbon fixation pathway	Engineering strategy	Energy carriers	Representative outcome	References
Light-driven	rGly pathway	Semiconductor-microbe hybrid (MR-1@CdS) enabling photoelectron transfer	ATP, NADH	Sustained acetate production from CO₂ and autotrophic growth	[72]
CBB cycle	InP nanomaterials enhance PSI activity and photosynthetic electron flux	ATP, NADPH	Increased ethylene production	[78]
HWLS pathway	CdS-driven NADH regeneration coupled with proteorhodopsin-mediated ATP synthesis	ATP, NADPH	Product yields exceed theoretical limits (malate, butyrate)	[79]
Artificial CO₂ fixation (ADRP)	Synthetic photosystem generating ATP and NADH	NADH, ATP	Production of pyruvate-derived chemicals with negative carbon footprint	[80]
Electro-driven	rGly pathway	Microbial electrosynthesis with direct cathodic electron supply	ATP, NADH	Efficient acetate synthesis from CO₂	[73]
WL pathway	Direct electron uptake via EET (cytochromes and conductive pili)	ATP, NADH, Fd _red	Acetate production up to 11.05 mmol/L	[81]
WL pathway	Tandem electrocatalysis (CO₂→acetate) coupled with microbial PHB synthesis	ATP, NADH, NADPH	Increased PHB production	[82]
Artificial marine system	CO₂ electroreduction to formate followed by microbial upgrading	H₂, formate, NAD(P)H, ATP	Efficient growth and succinate production in seawater system	[83]
Chemical-driven	CBB cycle	Water splitting to generate H₂ driving hydrogen-oxidizing autotrophy	H₂, NADH, ATP	Isopropanol production up to 216 mg/L	[84]
Ribulose 5-phosphate (RuMP) pathway	Enhanced methanol oxidation and cofactor redistribution	Methanol, NAD(P)H, ATP	Improved growth and product yields	[63]
CBB cycle	Decoupling carbon fixation from energy metabolism using pyruvate	Pyruvate, NADH, ATP	Semi-autotrophic growth and sugar production	[18]
CBB cycle	Reducing energy dissipation and enhancing FDH activity	Formate, NADPH, ATP	Improved CO₂-to-sugar conversion	[19]
rGly pathway	Combined methanol and formate oxidation for redox supply	Methanol, formate, NAD(P)H, ATP	Improved growth and carbon utilization	[85]
Serine pathway	NADPH-generating methanol dehydrogenase and PPP enhancement	Methanol, NADPH, ATP	Increased product yield with maintained growth	[86]

微生物固碳能量-碳流耦合定量评价及多尺度协同设计

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吴龙昊 ¹ , 王源 ¹ , 刘子鹤 ²^,^*

微生物学报 | 综述 2026,66(9): 4320-4340

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微生物学报 |综述 2026 , 66 (9) : 4320 -4340

微生物固碳能量-碳流耦合定量评价及多尺度协同设计

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吴龙昊¹, 王源¹, 刘子鹤²^,^*

作者信息

^1.北京化工大学，北京软物质科学与工程高精尖创新中心，北京

^2.北京化工大学生命科学与技术学院，北京

通讯作者:

刘子鹤

作者简介:

作者贡献声明

吴龙昊：论文构思、文献调研及论文撰写；王源：参与文献调研、图表绘制及论文撰写；刘子鹤：参与论文构思，负责论文指导与修改，并提供经费支持。

Quantitative evaluation of energy-carbon flux coupling and multi-scale synergistic design for microbial carbon fixation

Longhao WU¹, Yuan WANG¹, Zihe LIU²^,^*

Affiliations

^1.Beijing Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, Beijing, China

^2.College of Life Science and Technology, Beijing University of Chemical Technology, Beijing, China

Corresponding Author:

^*E-mail: zihe@mail.buct.edu.cn

出版时间: 2026-09-04 doi: 10.13343/j.cnki.wsxb.20260365

文章导航

摘要

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将CO₂高效转化为燃料与化学品是实现可持续生物制造的重要路径，微生物细胞工厂在其中具有广阔应用前景。然而，尽管固碳途径设计与碳流重构不断进展，体系性能仍主要受限于能量供给与利用效率，其根本在于能量代谢与碳固定之间在能量载体形式[ATP、NAD(P)H及低电势电子]、供给比例及氧化还原电势上的系统性失配，从而限制碳通量与能量利用效率。本文从能量-碳流耦合视角出发，提出能量转化链条框架，将固碳过程统一为能量输入、电子传递与碳同化过程的级联网络，并建立涵盖能量输入效率(energy input efficiency, EE)、电子利用效率(redox/electron utilization efficiency, RE)及能量-碳转化效率(energy-to-carbon conversion efficiency, ECE)的定量评价体系。结合实验测量与代谢建模，系统解析能量载体分布与电子流动特征，识别出关键瓶颈，包括能量输入通量、电子传递损耗、辅因子失配及反应网络效率等。在工程层面，进一步总结底盘宿主选择、外源供能模块构建及内源能量网络重构等策略，并提出多尺度能量-碳流协同设计框架，实现能量供给与固碳需求的精准匹配。总体而言，本综述从系统层面重塑能量在固碳工程中的核心地位，为构建高效、稳定的CO₂生物转化体系提供了理论基础与工程路径。

关键词

微生物固碳 / 能量代谢 / 辅因子工程 / 适配性调控 / 合成生物学

Abstract

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The efficient conversion of CO₂ into fuels and chemicals represents a key route toward sustainable biomanufacturing, and microbial cell factories offer significant potential for this purpose. Despite substantial advances in carbon fixation pathway design and carbon flux rewiring, the performance of microbial CO₂-fixing systems remains largely constrained by the efficiency of energy supply and utilization. At the core of this limitation is a systemic mismatch between energy metabolism and carbon fixation, involving discrepancies in energy carrier types [ATP, NAD(P)H, and low-potential electrons], supply ratios, and redox potential, which ultimately restrict carbon flux and energy utilization efficiency. From the perspective of energy-carbon flux coupling, this review proposes an energy conversion chain framework that conceptualizes carbon fixation as a cascade network comprising energy input, electron transfer, and carbon assimilation. On the basis of this framework, a quantitative evaluation system is established, encompassing energy input efficiency (EE), redox/electron utilization efficiency (RE), and energy-to-carbon conversion efficiency (ECE). By integrating experimental measurements with metabolic modeling, we systematically analyze the distribution of energy carriers and electron fluxes and identify key bottlenecks, including limitations in energy input flux, electron transfer losses, cofactor mismatches, and reaction network efficiency. At the engineering level, we further summarize strategies for improving energy-carbon compatibility, including chassis selection under energy constraints, construction of exogenous energy-supplying modules, and rewiring of endogenous energy networks. Building upon these advances, a multi-scale energy-carbon co-design framework is proposed to achieve precise matching between energy supply and carbon fixation demand. Overall, this review redefines energy metabolism as a central design dimension in carbon fixation engineering and provides both a theoretical foundation and engineering strategies for the development of efficient and robust CO₂ bioconversion systems.

Key words

microbial carbon fixation / energy metabolism / cofactor engineering / adaptive regulation / synthetic biology

引用本文

吴龙昊, 王源, 刘子鹤. 微生物固碳能量-碳流耦合定量评价及多尺度协同设计. 微生物学报, 2026 , 66 (9) : 4320 -4340 . DOI: 10.13343/j.cnki.wsxb.20260365

Longhao WU, Yuan WANG, Zihe LIU. Quantitative evaluation of energy-carbon flux coupling and multi-scale synergistic design for microbial carbon fixation[J]. Acta Microbiologica Sinica, 2026 , 66 (9) : 4320 -4340 . DOI: 10.13343/j.cnki.wsxb.20260365

正文

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将CO₂高效转化为燃料与高附加值化学品，是实现碳中和与构建可持续化学工业的核心挑战之一^[1]。微生物细胞工厂凭借其可编程代谢网络与多样化合成能力，在CO₂资源化利用中展现出独特优势。近年来，多种天然与人工固碳途径已被成功重构或移植至模式微生物中，为一碳(C1)生物制造提供了重要技术基础^[2-4]。然而，尽管碳流重构与路径优化不断进展，体系的产率、速率与能量效率仍远未达到热力学与化学计量所允许的理论上限。

这一性能瓶颈的根源在于能量代谢的系统性约束。CO₂处于高度氧化态，其还原与同化过程对ATP与还原力具有高强度依赖^[5-6]，不同固碳途径在能量需求的形式[ATP、NAD(P)H或低电势电子]、比例及电势层面存在显著差异^[7-8]。然而，天然宿主的能量代谢网络围绕其原生生理功能演化，难以满足非原生固碳路径在化学计量与热力学上的特定需求，导致能量供给与碳固定之间普遍失配^[9]。这种失配不仅体现为总量不足，更表现为能量形式、供给比例及动态响应的不协调，进而在多层级限制碳通量与能量利用效率^[9]。

光驱动半人工光合体系、电驱动平台及化学供能策略等外源能量模块的发展，为突破内源性能量限制提供了新路径，但这些策略仍面临效率损失、界面耦合不足及辅因子匹配不佳等问题^[10-12]。与此同时，针对内源能量代谢网络的工程化改造(如辅因子重分配、呼吸链调控及低电势电子生成)虽在局部取得进展，但缺乏统一的分析框架以指导系统级优化。因此，如何在统一尺度上定量刻画能量流动，并据此实现能量供给与碳固定需求的精准匹配成为当前微生物固碳研究中的关键科学问题。

为应对这一挑战，本文从能量-碳流耦合的视角出发，构建了贯穿机制解析与工程设计的系统性分析框架。首先，引入能量转化链条概念，将固碳过程抽象为由能量输入、电子传递及碳同化过程构成的多级转化网络，并提出能量输入效率(energy input efficiency, EE)、电子利用效率(redox/electron utilization efficiency, RE)及能量-碳转化效率(energy-to-carbon conversion efficiency, ECE) 3类指标进行定量刻画。在此基础上，结合实验测量与多尺度建模方法对能量载体分布、电子流动及关键动力学过程进行系统解析，从而识别限制固碳效率的关键瓶颈。进一步地，基于上述机制认知，本文总结并归纳了当前实现能量-碳流适配的主要工程策略，包括底盘宿主的能量约束筛选、外源供能模块的引入以及内源能量网络的重构与优化，并提出多尺度的能量-碳流协同设计框架。该框架从能量输入、形式匹配、通量拓展及系统调控等多个层级出发，为构建高效、稳定且可扩展的微生物固碳系统提供理论指导与工程路径。

通过将能量代谢从辅助因素提升为设计核心，本文旨在为下一代高效固碳细胞工厂的构建提供统一的分析范式与理性设计原则，从而推动CO₂生物转化向更高效率与更广应用场景迈进。

1 能量模块与碳固定模块的适配与调控：评价框架与系统解析

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在微生物固碳体系中，能量供给不仅决定反应是否能够发生，更从根本上约束其通量上限与效率边界^[9]。以往的综述性论文通常遵循以碳流为中心的分析范式，例如Liu等^[13]梳理了天然及人工CO₂固定途径、工程策略，并在此基础上进一步讨论工业化面临的主要瓶颈和C1化合物利用的最新进展^[14]。越来越多的研究表明，固碳过程本质上受限于能量的获取、转化与分配过程，其效率取决于能量流与碳流之间的耦合程度^[15-16]。然而，由于外源能量输入形式多样(光能、电能与化学能)，且细胞内能量载体[ATP、NAD(P)H及低电势电子]在功能与热力学属性上存在显著差异，现有研究通常难以在统一尺度上对不同体系进行定量比较与机制解析^[17]。

为系统解析这一问题，本文引入能量转化链条作为分析框架，将固碳过程抽象为由能量输入、能量传递与碳同化过程构成的连续转化网络。在此基础上，构建涵盖能量输入效率、电子利用效率与能量-碳转化效率的多层级评价体系，用于从热力学能量利用、电子分配以及碳转化能力3个维度定量表征体系性能。进一步地，通过整合实验测量与多尺度建模方法，对关键能量载体、电子流及其空间分布进行系统解析，从而实现对能量状态的精确刻画。基于上述分析框架，本章进一步从能量转化链条的不同层级出发，系统识别限制固碳效率的关键瓶颈，包括能量输入通量上限、电子传递损耗、辅因子供给结构失配以及反应网络实现效率等问题。通过对这些限制因素的分层解析，为后续能量-碳流耦合的工程设计提供定量依据与理论基础。

1.1 碳固定系统中能量效率的定量评价指标

在能量转化链条框架下，微生物固碳体系的整体性能可被分解为多个连续的能量转化过程。因此，对体系效率的评估不应局限于单一能量载体或局部反应，如图1A所示，需要从能量输入-能量转化-碳固定产物生成的整体视角进行定量刻画^[18-19]。基于这一思路可从3个层级刻画体系性能：(1)能量输入效率，反映外部能量向产物化学能的转化效率；(2)电子利用效率，描述电子在目标产物中的分配比例；(3)能量-碳转化效率，衡量单位能量输入对应的CO固定能力。该指标体系为不同供能策略的比较提供了统一框架。

1.1.1 能量输入效率

能量输入效率用于描述外部能量被转化并储存在目标产物中的总体效率，其定义为产物中累积的化学自由能与体系总能量输入之间的比值^[20]，如公式(1)所示。

E E = n p r o d u c t × ∆ G f o r m a t i o n ○ E i n p u t

(1)

式中：

∆ G f o r m a t i o n ○

为目标产物生成所储存的标准吉布斯自由能，

E i n p u t

为体系的总能量输入。该指标从热力学角度刻画了能量转化链条上游(能量输入与初级转化过程)的整体效率。例如，在2种具有相同CO₂固定速率的体系中，若一种体系需要更高能量输入才能实现相同产物输出，则其EE较低。这表明该体系在能量捕获或初级能量转换过程中存在更大的热力学损耗。在光驱动固碳体系中，不同光能捕获模块对太阳能的利用能力存在显著差异^[9,21]。天然光合作用通常仅能利用部分可见光波段，而引入半导体光敏材料后可扩展光谱吸收范围并提高光能向生物可利用能量的转化比例，从而提高体系的EE^[21]。相较于传统以ATP或NAD(P)H消耗量衡量碳固定代价的方法，基于吉布斯自由能的表征能够将不同类型的能量载体统一映射到相同尺度，从而实现跨途径、跨能量形式(光能、电能与化学能)的直接比较^[22]。基于此类分析，不同固碳途径可根据单位CO₂固定所需的自由能消耗划分为高能耗路径与节能路径，反映其在热力学驱动力与能量代价之间的权衡关系^[23]。

1.1.2 辅因子生成与电子利用效率

辅因子生成与电子利用效率用于衡量输入电子在目标产物合成中的有效利用比例，如公式(2)所示。

R E = n p r o d u c t × v e, p r o d u c t n e, i n p u t

(2)

式中：

n p r o d u c t

为生成产物的物质的量，

v e, p r o d u c t

表示生成单位产物所需的电子数，

n e, i n p u t

为体系输入的电子总量。该指标主要反映能量转化链条中段(电子传递与辅因子生成过程)的效率，即输入电子在固碳反应与副反应之间的分配情况。在光驱或电驱体系中，电子泄漏、呼吸消耗及旁路反应通常导致大量电子未能进入目标代谢路径，从而显著降低RE。例如，在电驱动固碳体系中若仅有部分阴极电子最终用于目标产物合成，而其余电子被呼吸链消耗或用于副产物生成，则体系可能表现出较高的能量输入效率，但电子利用效率仍然较低，而通过工程化操作可定向控制能量流动进而提升RE^[24]。因此，该指标对于评估电子传递网络的耦合效率及识别能量损耗来源具有重要意义。不同固碳途径在还原当量需求上的差异也会直接影响RE，例如还原型乙酰辅酶A途径通常具有较低的电子需求，而卡尔文(Calvin-Benson-Bassham, CBB)循环则对还原力消耗更高^[20]。

1.1.3 能量-碳转化效率

能量-碳转化效率用于描述单位能量输入所驱动的碳固定能力，在实验体系中，该指标通常通过量子效率、法拉第效率、库仑效率、ATP生成效率或碳收率等参数进行量化，是连接能量输入与碳输出的综合性能指标^[25]，如公式(3)所示。

E C E = n p r o d u c t × C p r o d u c t E i n p u t

(3)

式中：

C p r o d u c t

表示单位产物所含的碳原子数。该指标从系统层面刻画了能量转化链条末端(碳固定与产物生成过程)的效率。例如，CBB循环与Wood-Ljungdahl (WL)途径均可利用输入电子将CO₂还原为细胞碳源，因此可能表现出相近的RE。然而，CBB循环固定1 mol CO₂通常需要消耗更多ATP，而WL途径则是目前已知ATP需求最低的天然固碳途径之一^[13]。因此，在相同电子输入条件下，WL途径通常能够实现更高的碳固定量和生物量得率，从而表现出更高的ECE。这一差异反映了固碳途径能量需求及代谢网络特征对最终碳转化能力的重要影响。在具体应用中，ECE可根据研究目标进一步扩展为单位能量输入对应的CO₂固定速率、生物量生成量或目标产物产率。不同能量驱动体系中，

E i n p u t

的计算方式存在差异，例如光驱体系可表示为吸收光子数与单光子能量的乘积，而电驱体系则由电压与电流积分确定，化能驱动体系则可通过底物氧化反应释放的自由能进行表征。

需要指出的是，在比较不同体系的能量-碳转化效率时必须明确系统边界并统一能量计量尺度。不同形式的能量输入应转换为统一的热力学单位，同时需考虑维持代谢、电子泄漏及副反应等不可避免的能量损耗过程，否则可能对体系效率产生系统性高估^[26]。总体而言，EE、RE与ECE分别对应能量转化链条中的输入、传递与输出3个关键阶段，从热力学能量利用、电子分配及碳转化能力3个层面对固碳体系性能进行定量刻画，为不同能量驱动策略的比较及能量模块与碳固定模块的协同设计提供了统一而可推广的分析框架。

1.2 固碳途径能量需求与细胞能量状态的分析方法

在上述能量效率评价框架下，对微生物固碳体系的定量分析依赖于对能量载体、电子流及能量转化过程的准确测量与系统解析。如图1B所示，由于能量转化链条涉及多个层级(能量输入、电子传递、辅因子生成及碳固定驱动)，单一测量手段难以全面反映体系状态。因此，需要结合多尺度实验方法与计算建模对关键参数进行分层表征，从而实现对EE、RE与ECE等指标的可靠量化与机制解析。

1.2.1 能量载体与辅因子水平的定量测量

细胞内ATP及还原型辅因子(NADH、NADPH等)的浓度与比例是连接电子传递与碳固定反应的核心参数，直接影响能量-碳转化效率^[7-8]。传统方法主要通过酶联反应体系对ATP、ADP与AMP进行定量，例如利用己糖激酶、葡萄糖-6-磷酸脱氢酶及萤火虫荧光素酶构建的级联检测体系，其灵敏度可达皮摩尔水平^[27-28]。还原型辅因子则可通过其在340 nm处的特征吸收或内源荧光进行检测，但该方法在低浓度范围内灵敏度有限。为提高检测精度，电化学方法与生物发光检测体系被广泛应用。前者具有较高灵敏度，但易受电极污染及体系复杂性的影响^[29]；后者对NAD(P)H的检测具有较高灵敏度，但成本较高，限制了其在高通量分析中的应用^[30]。此外，四唑盐类试剂(如WST-8)可在NAD(P)H存在下被还原生成有色产物，从而实现比色定量^[31]。这些方法为RE与ECE的定量计算提供了基础数据支持。

1.2.2 区室化能量分布的原位监测

在真核微生物中，能量载体通常呈显著的区室化分布，不同细胞器之间的NAD(P)H与ATP难以自由扩散。因此，仅测定总体浓度通常无法准确反映其在固碳反应位点的真实可利用性，从而对RE和ECE的评估产生偏差。针对这一问题，近年来发展了多种基于代谢反应或荧光探针的原位监测方法。例如，基于辅因子依赖酶反应构建的生物传感器可用于实时报告胞质NADPH/NADP⁺比值^[32]，而融合荧光探针的蛋白体系(如CoA-Snifit^[33])则可实现对不同细胞区室中游离辅酶A水平的动态监测。这类方法能够在空间分辨尺度上刻画能量载体的分布与可达性，从而提高对电子利用效率RE的解释能力。

1.2.3 能量输入与电子传递过程的动力学解析

在能量转化链条的上游与中段，EE和RE高度依赖于初级能量捕获及电子传递过程的动力学特性。针对光驱与半人工光合体系，光合生理学与光谱学技术提供了重要分析手段。叶绿素荧光分析可用于评估光系统Ⅱ的光化学效率^[34]，而膜进样质谱(membrane inlet mass spectrometry, MIMS)能够实时测定O₂与CO₂通量，从而区分光合放氧与呼吸耗氧过程^[35]。电子顺磁共振(electron paramagnetic resonance, EPR)可直接检测光系统中的顺磁中间体，揭示电子传递路径^[36]；电致变色位移(electrochromic shift, ECS)测量则可量化质子动力势(proton motive force, PMF)及其组成，反映跨膜能量耦合效率^[37]。此外，差分吸收光谱(如DUAL-KLAS-NIR)可解析光系统I、质体蓝素及铁氧还蛋白之间的氧化还原动力学^[38]。

在半人工体系中，瞬时吸收光谱与时间分辨红外光谱可用于追踪光生电子在半导体材料与生物催化体系之间的转移过程^[39]，从而揭示界面电子传递效率及其对RE的影响。对于电驱动体系，电化学分析方法(如循环伏安与电流响应测量)也可用于评估电子注入速率及界面耦合效率。

1.2.4 培养条件与测量体系的影响因素

在实际实验体系中，培养条件及检测体系可能对能量测量结果产生显著干扰。例如，富营养培养基中的有机组分既可能作为碳源，也可能作为额外能量输入，从而影响对EE与ECE的准确评估。此外，一些具有氧化还原活性的分子(如抗坏血酸、尿酸及葡萄糖)可能干扰辅因子的检测结果^[40]。因此，在进行能量状态分析时需要严格控制培养条件并校正潜在干扰，以确保测量数据的可比性与可靠性。

1.2.5 多尺度建模与系统级整合分析

除实验测量外，将组学数据整合至代谢模型中是解析能量-碳流适配关系的重要手段。通量平衡分析(flux balance analysis, FBA)可在给定约束条件下预测稳态代谢通量分布，并评估体系的能量平衡与路径兼容性^[41]；酶成本最小化(enzyme cost minimization, ECM)通过估算支持目标通量所需的最优酶与代谢物浓度，揭示蛋白质资源与能量效率之间的权衡关系^[42-43]；最小-最大驱动力(max-min driving force, MDF)模型则从热力学角度筛选具有最大驱动力的代谢路径，以避免反应接近平衡所带来的通量限制^[44-45]。近年来，数据驱动与人工智能方法为固碳体系的建模与设计提供了新的范式。蛋白质语言模型[如进化尺度建模(evolutionary scale modeling, ESM)系列]可在序列空间中进行固碳关键酶[如核酮糖-1,5-二磷酸羧化酶/加氧酶(ribulose-1,5-bisphosphate carboxylase/oxygenase, RuBisCO)、甲酸脱氢酶、转氢酶等]的功能预测与虚拟筛选，加速酶的定向进化；图神经网络(graph neural network, GNN))已被用于代谢路径的热力学可行性评估与能量耦合效率预测，辅助设计新型合成固碳途径；深度强化学习方法在代谢通量的动态优化与多目标调控策略设计中展现出潜力，可同时考虑能量效率与碳固定通量的权衡。此外，自动化设计-构建-测试-学习(design-build-test-learn, DBTL)平台通过高通量实验与机器学习模型的闭环迭代能够加速“能量模块-碳固定模块”适配的多维参数空间探索，显著缩短工程周期。

上述实验测量与计算建模方法能够从系统层面连接能量输入、辅因子生成与碳同化过程，对EE、RE与ECE进行整体预测与优化分析。机理模型与数据驱动方法的融合有望进一步提升对复杂能量-碳流网络的刻画能力，为能量模块与碳固定模块的理性设计提供更全面的理论指导。

1.3 能量供给对固碳效率与反应速率的瓶颈

尽管近年来微生物固碳途径设计与代谢工程改造取得了显著进展，体系性能仍普遍受限于能量供给与利用效率。如表1所示，对于任何固碳体系而言，外部能量都需依次经历能量输入、电子传递、辅因子生成及碳固定等连续转化过程，任一环节的能量损失或供需失配均可能导致整体效率下降^[46]。因此，从能量转化链条的角度分析能量流动过程有助于揭示限制固碳效率与反应速率的共性规律。如图1C所示，微生物固碳体系的能量瓶颈主要表现为能量输入通量受限、能量传递与耦合损耗、能量形式与比例失配以及反应网络利用效率不足4个层级，并分别影响EE、RE和ECE。

(1) 能量输入通量上限决定系统的供能能力。能量转化链条的首要约束来源于外部能量向细胞可利用形式的初级转化过程。无论采用光能、电能还是化学能驱动固碳，体系都首先受到单位时间内可输入能量总量的限制^[47-48]。因此，能量输入通量决定了固碳反应能够获得的最大ATP和还原力供给能力，并构成EE的理论上限。从本质上看，能量输入通量受热力学可获得性与动力学转化速率的共同制约。一方面，外部能源的能量密度、传递方式及供给稳定性决定了体系能够利用的理论能量上限；另一方面，能量捕获与转换过程本身并非完全高效，能量在转化初期即会发生不可逆损失。例如，在光驱动体系中，仅部分入射光能够被有效吸收并转化为电子流，而光抑制、反应中心饱和及活性氧积累均会进一步降低有效能量输入^[47-48]；在电驱动体系中，电极-细胞界面的电子传递速率受到界面阻抗、电子传递距离及生物膜结构的限制^[49-50]；在化能驱动体系中，底物氧化速率以及关键供能酶的催化能力则决定电子与ATP的生成上限^[51]。总体而言，能量输入通量不仅影响体系能够获得的总能量，而且决定了后续电子传递和辅因子再生过程的运行空间。

(2) 能量传递与耦合效率决定电子利用水平。在从能量输入端到代谢网络的传递过程中，电子通常需要经过多个载体和能量转换步骤才能最终形成驱动固碳反应所需的ATP和还原力。在这一过程中，电子泄漏、旁路反应以及能量耦合不完全等现象普遍存在，从而导致大量输入能量无法进入目标代谢途径，并直接影响RE。当电子在传递过程中发生泄漏时不仅会降低还原力，还可能形成活性氧等副产物，引发额外的细胞应激和能量消耗^[52]。例如在奥奈达湖希瓦氏菌(Shewanella oneidensis)中，电子需通过外膜细胞色素复合体跨膜传递至胞内载体，过程中的多级传递显著增加能量损耗^[53]。当输入电子的电势与目标反应需求不匹配时，细胞需要通过电子分叉、反向电子传递或辅因子转换等过程重新分配电子^[54-55]。这些过程虽然提高了电子的可利用性，但通常需要额外消耗离子梯度或ATP，从而进一步降低整体能量效率。因此，能量传递过程不仅承担着电子输送的功能，更决定了输入能量中有多少能够以有效形式进入代谢网络。

(3) 能量形式与比例匹配决定辅因子供给效率。当电子被成功导入细胞后，其并不能直接驱动碳固定反应，而需要进一步转化为ATP和还原力等代谢可利用的能量形式。因此，决定固碳效率的关键不仅在于能量供给总量，更在于供给形式是否与固碳途径的需求相匹配。从能量转化角度看，ATP生成依赖于跨膜离子梯度的建立与ATP合酶的能量耦合过程，而还原力则来源于电子向NADH、NADPH或铁氧还蛋白(Fd _red )等载体的转移。无论是光驱、电驱还是化能驱动体系，这些过程均伴随着不可避免的能量损耗^[17,56-57]。例如不同辅因子之间的相互转换通常需要额外能量输入，从而进一步增加系统负担^[55,58]。更重要的是，不同固碳途径对能量载体的需求具有显著差异。CBB循环需要大量ATP与NADPH，而WL途径则更依赖低电势铁氧还蛋白供能；部分人工固碳途径虽然降低了ATP消耗，却提高了对特定还原力形式的依赖。因此，固碳体系面临的关键问题并非单纯提高能量供给，而是在ATP生成、辅因子形成及电子分配之间建立合理的匹配关系。总而言之，能量载体种类、供给速率及供给比例与固碳需求之间的匹配程度通常决定了单位输入能量最终能够转化为多少有效碳通量。

(4) 反应实现效率决定碳固定通量输出。输入的能量能否最终稳定、高效地转化为目标碳通量，不仅取决于能量供给水平，还取决于固碳反应网络对这些能量的利用能力。因此，该层级构成决定ECE的最终约束。与传统观点将瓶颈归因于单个关键酶不同，越来越多研究表明固碳效率通常由整个反应网络的系统特性共同决定。一方面，关键固碳反应的动力学特征会限制能量向碳流的转化速率。例如，CBB循环中RuBisCO较低的催化效率和竞争性加氧反应会降低ATP和还原力的利用效率^[59]；而一些低能耗固碳途径虽然能够减少能量消耗，却通常依赖低电势电子或热力学驱动力较弱的反应，从而降低系统对能量波动的耐受性^[60]。另一方面，代谢网络的整体适配性同样决定能量利用效率。固碳途径产生的中间体需要能够被宿主代谢网络有效接纳并进一步转化，否则即使固碳反应本身能够进行，也难以形成持续稳定的碳流。例如，部分人工固碳循环在理论上具有较高的能量效率，但其产物与宿主中心代谢连接较弱，需要额外的代谢重构才能实现高效利用^[61]。这表明固碳系统的性能不仅取决于途径本身的热力学和动力学性质，还取决于其与宿主代谢网络之间的协同程度。

综上所述，在能量转化链条框架下，微生物固碳体系的能量瓶颈呈现出由能量输入通量上限-传递损耗→耦合效率-能量形式→比例失配-反应实现效率逐级传递与放大的特征，并分别对应EE、RE及ECE等关键指标。由于各层级过程高度耦合，单一环节的优化通常难以显著提升整体性能。因此，实现高效固碳的关键在于在系统层面协调能量输入形式、传递效率及辅因子供给结构，使其与固碳反应网络的需求实现动态匹配，从而最大化能量利用效率与碳固定通量。

2 能量-碳流耦合系统的协同设计与适配策略

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在明确能量-碳流失配的机制基础上，如何将这些约束转化为可操作的工程策略是实现高效微生物固碳的关键。不同于天然系统中相对固定的能量供给与碳代谢耦合关系，工程化固碳体系需要在多尺度上重构能量流的输入、分配与利用方式，从而实现对碳同化过程的定向驱动与精确调控。因此，固碳系统的设计不再是单一代谢路径的优化问题，而是一个涉及能量模块与碳固定模块协同配置的系统工程问题。

围绕这一逻辑，近年来的工程实践逐步从单一策略优化转向多模块协同设计。一方面，通过理性选择或构建底盘宿主，使其内源能量网络(即宿主细胞天然编码的能量产生与分配体系，包括糖酵解、三羧酸循环(tricarboxylic acid cycle, TCA cycle)、呼吸链及辅因子再生通路等)在形式与比例上更接近目标路径需求；另一方面，引入光、电及化学驱动等外源供能模块以突破天然能量供给上限并实现碳源与能量输入的解耦；进一步地，通过辅因子重分配、ATP供给优化及低电势电子生成等策略，在局部尺度上实现能量载体的定向匹配与高效利用。这些策略在不同体系中已被证明能够显著提升碳固定效率与产物合成能力。

基于上述认识，本章将从宿主选择与能量适配、外源供能模块的构建以及固碳路径与内源能量网络的局部匹配3个层面，系统总结当前微生物固碳工程中的关键策略与代表性进展，并在此基础上提炼通用设计原则，为构建高效、可扩展的能量驱动型固碳体系提供理论依据与工程指导。

2.1 碳固定底盘宿主的选择与能量代谢适配原则

在工程化微生物固碳体系中，底盘宿主的选择决定了能量模块与碳固定路径能否实现有效耦合。从能量转化的角度看，不同固碳途径在ATP消耗、还原力类型及氧化还原电势需求上存在本质差异，而宿主内源能量代谢网络则具有相对固定的输出结构。当两者在能量形式、供给比例或电势层面发生偏离时通常导致碳通量受限及能量利用效率下降。因此，宿主选择应被视为一个能量约束下的匹配问题，而非单纯基于遗传操作便利性的经验决策。

在此框架下，不同类型宿主呈现出明显差异。典型呼吸型微生物如大肠埃希氏菌(Escherichia coli)和酿酒酵母(Saccharomyces cerevisiae)以NADH为主要还原力载体，并依赖氧化磷酸化生成ATP，其能量网络更适用于高ATP需求或NADH驱动的代谢过程。但在NADPH供给及低电势电子生成方面存在局限^[62-63]。然而，近年研究表明，呼吸型宿主的能量代谢网络具有超越传统认知的可塑性，其ATP及还原力输出结构并非不可改变。例如Qin等^[64]构建杂合糖酵解菌株并鉴定出OCA5编码一种此前功能未知的焦磷酸肌醇磷酸酶，催化5-InsP₇向InsP₆的转化；研究表明，5-InsP₇水平通过转录因子Gcr1和Hap4全局调控糖酵解基因和呼吸基因的表达，构成一条独立于单磷酸腺苷激活的蛋白激酶(adenosine 5′- monophosphate-activated protein kinase, AMPK)通路和雷帕霉素机制靶蛋白(mechanistic target of rapamycin, mTOR)通路的ATP感知机制；敲除OCA5的工程菌株解除了Crabtree效应，且游离脂肪酸产量达到2.68 g/L；这一工作从分子层面证明，通过干预焦磷酸肌醇信号通路即可从根本上重塑呼吸型宿主的能量代谢输出模式，使原本倾向于发酵的碳流重定向至呼吸与合成代谢；这意味着底盘宿主的选择不应仅基于其原生能量网络特征，而应充分考虑其能量代谢调控网络的可工程化潜力。相比之下，部分厌氧微生物通过电子分叉机制可利用低电势铁氧还蛋白，从而天然适配还原型TCA循环或WL途径等低电势电子依赖路径^[51]。光合微生物则通过光反应直接耦合ATP与NADPH生成，在驱动CBB循环等高ATP需求路径方面具有显著优势^[65]。此外，一些高还原力供给型宿主在NADPH生成及氧化还原稳态维持方面表现突出，适用于还原力密集型合成过程^[66]，尤其恶臭假单胞菌(Pseudomonas putida)可编码多种以甲醇为底物的醇脱氢酶，这些酶以吡咯喹啉醌(pyrroloquinoline quinone, PQQ)或NAD(P)⁺为辅因子^[67]。PQQ依赖型甲醇脱氢酶(methanol dehydrogenases, MDH)在合成甲基营养方面具有广阔的应用前景，虽然PQQ依赖型MDH依赖氧气，但与NAD(P)依赖型酶相比，它们具有更优异的热力学和动力学性质。

随着合成生物学的发展，新型底盘的引入进一步拓展了宿主选择空间。例如，需钠弧菌(Vibrio natriegens)凭借其极快的生长速率、高通量能量代谢及优异的蛋白表达能力，为构建高通量能量模块提供了理想平台^[68]；通过整合丝氨酸循环与TCA循环构建的非天然代谢网络，已实现高效甲酸利用及目标产物合成^[69]。类似地，恶臭假单胞菌通过构建依赖C1底物的生长耦合系统，进一步验证了通过宿主能量网络重构实现碳-能量耦合的可行性^[70]。这些案例表明，宿主选择不仅是初始设计步骤，也是实现系统级优化的重要杠杆。需要指出的是，宿主适配不仅取决于能量匹配，还需综合考虑遗传操作可行性、代谢调控灵活性以及对外源供能模块(如光能或电能)的兼容性。例如，S. oneidensis以其多样化的电子接受途径而闻名，这些途径使其能够将有机物的分解与各种末端电子受体的还原偶联起来^[71]。目前已有许多成功的案例利用微生物通过光电催化实现从CO₂向乙酸盐^[72-73]、苹果酸^[74]、琥珀酸^[75]等产品的成功转化。

综上所述，底盘宿主的选择应从经验驱动转向基于能量约束的理性设计，即在明确固碳途径能量需求的基础上，从能量形式、供给比例及电势匹配3个层面构建系统化筛选策略。在此基础上，后续工程可通过局部代谢重构与供能模块优化，进一步实现能量供给与碳固定需求之间的精准耦合。

2.2 固碳微生物的能量获取方式与工程化供能模块

天然固碳微生物主要依赖光能或化学能驱动碳同化：光自养通过光反应生成ATP与还原力，化能自养依赖无机电子供体经呼吸链供能，而兼养体系虽可利用有机底物补充能量，但碳源与能量高度耦合^[76]。对于一碳生物制造，这一内源性能量网络存在明显上限：ATP及还原性辅因子的生成能力受限于底物供给与呼吸链容量，从而限制最大合成通量，尤其在高ATP需求的固碳路径中成为关键瓶颈^[51]。为突破该限制，发展了光、电及化学驱动等外源供能策略(如材料-微生物杂化体系与生物电化学平台)^[13,77]，以实现能量输入与碳同化的解耦并支撑高能需求路径(表2)。

(1) 光驱动系统通过引入半人工光合组件或异源光响应模块，将光能转化为细胞可利用的还原力或质子动力势。其中，半导体-微生物杂化体系可通过光生电子直接或间接注入代谢网络，驱动CO₂还原并合成多种产物(如乙酸^[72]、苹果酸^[79]及乙烯^[78]等)。该类体系的优势在于能够提供高能电子并实现碳源与能量输入的解耦，但其性能通常受限于生物-非生物界面的稳定性，如纳米材料的配体毒性及膜嵌入效应会影响细胞活性。针对这一问题，通过原位矿化构建半导体包覆生物膜已被证明可显著提升体系稳定性与转化效率^[87]。在产物拓展方面，生物杂化体系不仅能够生成小分子，还可用于合成多碳聚合物如聚羟基丁酸(polyhydroxybutyrate, PHB)，例如Li等构建了由石墨相氮化碳(g-C₃N₄)、硫纳米颗粒和沼泽红假单胞菌(Rhodopseudomonas palustris)组成的三元光合生物杂合体系在仅以CO₂为碳源的条件下实现3.19 g/L PHB积累，量子效率达11.8%^[85]。然而，有机半导体体系仍受限于光吸收范围窄及界面电子传递效率低^[88]，通过构建扩展共轭结构并增强膜相互作用可在一定程度上改善这一问题，实现稳定的连续生产^[88]。

除材料驱动外，生物源光响应模块为另一重要方向。微生物视紫红质可直接将光能转化为质子动力势，从而绕过传统电子传递链^[89-90]。例如，质子泵球状杆菌视紫红质(Gloeobacter rhodopsin)在E. coli中仍具光活性，并可在厌氧条件下驱动质子转运^[89]，其与曙红Y结合可同时实现ATP与NADH再生^[91]。此外，视紫红质产生的PMF还可逆驱动NADH脱氢酶，实现NAD⁺还原并通过转氢酶生成NADPH^[3]。进一步地，Hu等^[79]将变形杆菌视紫红质(proteorhodopsin)整合至E. coli-CdS体系中，可实现光生电子驱动NADH生成与PMF驱动ATP合成的协同作用，使L-苹果酸和丁酸产量分别达到1.48 mol/mol和0.79 mol/mol葡萄糖，突破理论得率。除了视紫红质外，在大肠埃希氏菌中异源引入光合反应中心核心蛋白PufL和细菌叶绿素a分子类似物MgP，将细胞内的ATP和NADH分别提升337.9%与383.7%，并实现CO₂向丙酮酸转化，其碳足迹为-0.84--0.23 kg CO₂ e/kg；此外该体系可支持以一碳底物进行光驱动生长(倍增时间19.86 h)^[80]。总体而言，光驱动策略的核心在于电子供给与跨膜能量耦合的协同设计。

(2) 在可再生电力驱动下，电驱动固碳体系兼具能量存储与低碳合成优势^[92]。尽管电催化CO₂还原可生成CO、甲酸及乙烯等小分子^[93-95]，其产物谱仍受催化选择性限制。因此，将电化学过程与生物代谢耦合，可利用细胞的合成能力拓展至多碳化学品与聚合物^[96-97]。

当前电驱动体系主要包括2类模式。其一为直接电子供给，即微生物附着于电极表面，通过胞外电子传递获取电子^[98]。例如，S. oneidensis等电活性微生物可通过细胞色素与导电结构实现电子摄取并驱动CO₂还原^[81]。该模式在理论上具有较高的能量转化效率，但在实际应用中常受到界面电子传递速率的限制，从而制约整体通量^[99]。此外，由于该体系多依赖WL途径，其代谢产物主要集中于短链化合物，功能拓展空间有限^[100]。其二为间接电子供给，即通过可溶性中介物(如CO、甲酸或H₂)在电极与微生物之间传递还原力。例如，通过电催化生成乙酸，再由杀虫贪铜菌(Cupriavidus necator)转化为PHB的两步体系，其碳转化效率可达62%^[82]。在最近的研究中，通过解耦的电-生物混合催化路径实现了从海水中直接捕集CO₂并转化为可再生生物塑料单体的全过程。该系统能在真实海水条件下高效运行(CO₂捕集效率>70%，能耗仅3 kWh/kg CO₂)，并在536 h的连续实验中保持稳定^[83]。总体来看，电驱动体系的核心瓶颈在于电子跨界面传递效率与体系集成复杂性之间的权衡。

(3) 化学驱动策略依赖外源还原性小分子(如甲酸、氢气、丙酮酸或亚磷酸盐等)，这类底物可通过专门的氧化还原酶，如氢酶、甲酸脱氢酶或磷酸亚铁脱氢酶，经分解代谢途径将电子传递给载体，从而产生还原力和ATP以驱动下游反应^[9]。相较于光电系统，该策略在工艺上更成熟，且底物具有良好的溶解与传输特性，但其还原力形式较为单一，通常需要辅因子转换以满足固碳路径需求^[9]。

其中，氢气因其低氧化还原电位(E°′≈-410 mV)可直接驱动多种还原反应。例如，在C. necator中，氢化酶可将H₂中的电子转移至NADH，从而为CO₂还原提供还原力，并实现异丙醇的生物合成，产量达216 mg/L^[84]。相比之下，液态一碳底物(如甲酸与甲醇)在工程应用中更具优势，其可同时提供碳源与还原力。例如，通过在大肠埃希氏菌中引入金属依赖型甲酸脱氢酶(Cupriavidus necator formate dehydrogenase, cnFDH)，可将甲酸氧化为CO₂并生成NADH，从而支持基于甲酸的营养生长，并实现甲戊二羟酸约3.8 g/L的积累^[49]。Wang等^[101]开发了一碳化合物转化策略，将甲酸与甲醇作为辅助碳源和还原力供给模块整合至酵母代谢网络，成功驱动了生物燃料前体的合成。在此基础上，Hou等^[102]进一步利用甲酸电解液同时作为电子供体和碳源，驱动工程化酿酒酵母合成脂肪酸。此外，部分中间代谢物(如丙酮酸)也可作为辅助能量输入节点，为CO₂同化途径提供额外的还原力与代谢驱动力，从而增强整体碳转化效率^[19]。类似地，表达甲醇脱氢酶(MDH)可将甲醇转化为甲酸并同步产生还原当量，进而支持多种还原产品的合成，包括乳酸、聚羟基丁酸酯、衣康酸及对氨基苯甲酸等^[12]。类似策略也可扩展至真核系统，用于增强酿酒酵母中还原性代谢产物的积累^[11]。

除传统能量形式外，机械能与热能等新型供能方式也开始被探索。例如，压电材料可将机械振动转化为电信号以驱动电子传递，而热电材料可利用温差产生电流^[103-104]。尽管目前仍处于概念验证阶段，这类策略为固碳系统在非常规环境中的应用提供了新的可能性。

2.3 固碳路径与内源能量网络的局部匹配与重构

在工程化宿主中，内源能量网络与外源固碳路径之间普遍存在系统性失配。当NADH、NADPH及Fd _red 的分配结构及ATP生成比例无法满足路径需求时，即使总体电子供给充足，仍会在特定能量载体层面形成局部瓶颈，从而限制RE与能量-碳转化效率。例如，巴豆酰辅酶A/乙基丙二酰辅酶A/羟基丁酰辅酶A [crotonyl-coenzyme A (CoA)/ethylmalonyl-CoA/hydroxybutyryl-CoA, CETCH]循环对ATP具有严格依赖，而丙二酰辅酶A-草酰乙酸-乙醛酸(malonyl-CoA-oxaloacetate-glyoxylate, MOG)途径虽降低能耗，但仍依赖宿主提供持续的辅因子再生流^[105-106]。因此，系统优化的关键不在于单一能量强化，而在于多类能量载体的定向重分配与化学计量匹配。围绕这一目标，局部匹配策略可在3个层级展开：还原力重构、ATP供给优化以及低电势电子生成。

(1) 当目标路径对NADPH或Fd _red 的需求超过宿主供给能力时，电子虽充足却无法以适配形式被利用，导致RE显著下降。针对还原力形式失配可通过3类策略实现定向调控：首先，通过增强内源还原力生成通路提高NADPH供给能力，例如强化磷酸戊糖途径或引入NADP⁺依赖性脱氢酶体系(如G6PDH、6PGDH、IDH、MaeB等)以扩大NADPH供给池。该策略本质上是通过重分配碳流来提升特定辅因子的生成能力，但通常伴随碳损失或代谢负担增加。其次，通过构建辅因子转换模块实现还原力形式的再分配，例如引入NAD激酶、NADH激酶或转氢酶，将NADH转换为NADPH，从而在不改变总电子输入的情况下优化还原力结构。已有研究表明，过表达NAD(P)转氢酶(PntAB)使蓝藻集胞藻(Synechocystis sp.) PCC 6803的固碳能力提高了3.2倍^[107]，验证了还原力重分配在路径匹配中的关键作用。再次，通过关键酶的辅因子偏好性工程使目标反应直接利用NADH，从而绕过能量依赖的辅因子转换过程^[108]。这一策略从需求侧降低系统对NADPH的依赖，是近年来提高系统能效的重要方向。对于依赖Fd _red 的固碳路径，还需进一步引入电子分叉或反向电子传递机制以生成低电势电子^[109]。然而，此类过程通常依赖PMF或额外能量输入，带来显著的热力学成本。总体而言，还原力工程的核心并非最大化某一辅因子，而是在满足路径电势与化学计量需求的前提下，最小化能量耦合代价。

(2) ATP是驱动固碳反应的直接能量来源，其生成主要依赖氧化磷酸化。因此，ATP供给能力由NADH通量、呼吸链效率及PMF维持能力共同决定。针对ATP不足问题，可通过重定向电子流与优化PMF利用实现调控。一方面，可通过增强NADH生成、调节氧供或重编程呼吸链组分，提高电子传递通量；另一方面，通过调控ATP合酶表达或膜特性以降低质子泄漏，从而提升ATP合成效率。研究表明，将ATP重新定向到大肠埃希氏菌中的RuBisCO羧化反应可使CO₂固定量提高870%并生产(387±43) mmol/L的苹果酸^[110]，说明ATP分配策略在路径匹配中的关键作用。此外，过表达ATP合酶也可增强整体代谢性能，进一步说明ATP供给是关键限制因素^[63]。除氧化磷酸化外，底物水平磷酸化可作为辅助供能路径，但受限于碳通量，在CO₂为唯一碳源的体系中难以承担主导作用。值得注意的是，ATP生成还受ADP供应调控：适度提高ADP/ATP比有利于增强驱动力，但过高则可能引发能量压力并抑制生长。因此，ATP工程需在供能强化与细胞稳态之间取得平衡。

(3) 部分厌氧固碳路径[如还原性三羧酸循环(reductive tricarboxylic acid cycle, rTCA cycle)]依赖Fd _red 作为电子供体。Fd含Fe-S簇，其还原电位通常低至-400 mV甚至更低，使其能够驱动高能障反应^[111]。然而，由于Fd电位极低，其由H₂或甲酸直接还原在热力学上通常不可行，因此需要额外的能量耦合机制。电子分叉被认为是解决该问题的核心策略，可利用NADH或H₂等较高电位电子供体驱动低电位Fd生成^[112]，相关分叉型氢化酶已在大肠埃希氏菌中实现表达。此外，通过引入丙酮酸:铁氧还蛋白氧化还原酶(pyruvate:ferredoxin oxidoreductase, PFOR)等代谢模块，可在丙酮酸转化为乙酰辅酶A的过程中直接生成还原型Fd (约-520 mV)，并进一步参与下游反应。该策略已在大肠埃希氏菌中验证，不仅提高了Fd依赖产物的合成效率，也为低电位驱动的固碳反应提供了可行路径^[113]。

上述多层级适配问题在酿酒酵母合成3-羟基丙酸(3-hydroxypropionate, 3-HP)的工程实践中得到了集中体现。3-HP的生物合成以乙酰辅酶A为前体，经丙二酸单酰辅酶A还原酶催化，该反应每生成1分子3-HP消耗1分子NADPH，同时固定1分子CO₂。从能量转化链条的角度分析，该路径的性能本质上由NADPH供给与碳固定反应之间的耦合效率决定。Qin等^[114]在研究初期发现，菌株胞内NADPH的绝对浓度和NADPH/NADP⁺比值均已处于较高水平，继续强化NADPH再生对产量提升效果有限；这表明在该体系中，限制RE和ECE的并非还原力供给总量，而是能量转化链条中“电子被有效传递至NADPH后”的后续环节，即NADPH的氧化速率受限于固碳底物(HCO₃⁻)的可利用性；作者通过增强碳酸氢根转运(Sul1)和优化丙二酸单酰辅酶A还原酶催化效率，使NADPH的消耗与CO₂固定重新匹配，同时通过促进产物外排(Esbp6)和阻断降解(Uga1)，减少已固定的碳和已消耗的还原力因产物积累或旁路代谢而浪费；综合改造后，菌株3-HP产量从0.14 g/L提高至11.25 g/L，在维持细胞生长的同时接近理论碳得率，这意味着单位NADPH氧化对应的3-HP生成量接近化学计量上限，即NADPH-产物转化的能量-碳耦合效率被推至最优。该工作的启示在于：能量模块与固碳模块的适配并非仅靠提升能量供给单侧发力，而需从能量载体消耗端识别瓶颈，使“供给”与“需求”在速率和比例上实现动态平衡。

综上所述，固碳路径与内源能量网络的适配本质上是一个多层级协同优化问题。有效策略并非单一模块强化，而是通过还原力重分配、ATP供给优化及低电势电子生成与碳流的协同设计，在满足路径化学计量需求的同时最小化能量损耗，从而实现高效稳定的能量-碳耦合。

3 总结与展望

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利用微生物细胞工厂实现CO₂固定与转化，代表着化工制造从资源消耗型向资源循环型模式的重要转变。然而，尽管近年来天然固碳途径挖掘、人工固碳循环设计以及底盘细胞工程取得了显著进展，体系性能仍普遍受限于能量供给与利用效率^[15]。本文提出的能量-碳流耦合框架表明，固碳效率的本质约束并非来源于单一酶或单一路径，而在于能量输入、电子传递、辅因子生成与碳固定之间的系统匹配程度。因此，未来高效固碳细胞工厂的设计目标应从“优化固碳途径”进一步拓展为“优化能量-碳流协同网络”，实现能量供给与碳同化需求在时空尺度上的精准匹配。

未来研究仍面临3方面关键挑战。首先，需要构建可编程且正交的能量供给模块，实现ATP、NAD(P)H及低电势电子等能量载体的按需生成与动态调控，从根本上提升能量供给与固碳需求之间的匹配性。其次，需要进一步提升固碳反应网络的能量利用效率，通过关键酶改造、人工途径设计、亚细胞区室化及代谢网络重构等策略提高能量向目标碳流的转化效率。第三，需要建立能够适应工业化运行条件的稳健能量-碳流调控体系以应对能量输入波动、底物变化及代谢负载扰动，实现长期稳定运行。

除效率提升外，固碳技术的产业化应用还需充分考虑经济性与环境可持续性。当前许多高性能供能策略仍依赖成本较高或存在环境风险的材料与能源。例如，半人工光合体系常采用CdS、InP等半导体材料，其制备成本、长期稳定性及潜在生态毒性均可能影响实际应用^[115]；电驱动体系虽然能够实现高效电子供给，但其整体碳减排效益高度依赖电力来源，当电能主要来自化石能源时体系的环境优势将显著削弱^[116]；而甲酸、氢气等化学供能策略的经济可行性则受到上游能源结构及制备成本的影响^[14]。因此，未来评价固碳技术时不仅需要关注能量输入效率(EE)、电子利用效率(RE)和能量-碳转化效率(ECE)等热力学指标，还应结合技术经济分析(techno-economic analysis, TEA)与生命周期评估(life cycle assessment, LCA)综合评估能量效率、生产成本和环境影响，从而为技术路线选择与工业化放大提供更全面的决策依据。

展望未来，人工智能与自动化生物工程的发展正在推动固碳系统设计从经验驱动向预测驱动转变。从蛋白质设计、人工辅因子开发到代谢网络优化与数字孪生建模，新一代数据驱动工具将显著提升能量模块与碳固定模块的协同设计能力。与此同时，绿色电力、先进光电材料以及新型储能技术的发展也将为微生物固碳体系提供更加稳定、高效和可持续的能量来源。随着合成生物学、人工智能与可再生能源技术的深度融合，未来的固碳细胞工厂有望实现能量流与碳流的精准调控，推动CO₂生物转化从实验室验证走向规模化应用，并成为支撑可持续生物制造与碳中和目标的重要技术平台。

基金

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国家重点研发计划(2025YFA0921800)
中央高校基本科研业务费专项资金(PT2026-09)

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2026年第66卷第9期

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接收时间：2026-05-02
首发时间：2026-09-09
出版时间：2026-09-04

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出版历史

收稿日期：2026-05-02
录用日期：2026-06-26

基金

the National Key Research and Development Program of China(2025YFA0921800)

国家重点研发计划(2025YFA0921800)

the Fundamental Research Funds for the Central Universities(PT2026-09)

中央高校基本科研业务费专项资金(PT2026-09)

作者信息

^1.北京化工大学，北京软物质科学与工程高精尖创新中心，北京

^2.北京化工大学生命科学与技术学院，北京

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https://castjournals.cast.org.cn/joweb/wswxb/CN/10.13343/j.cnki.wsxb.20260365

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2种不同金属材料的力学参数

科 Family	属数 Number of genus	种数 Number of species	占总种数比例 Percentage of total species (%)	属 Genus	种数 Number of species	占总种数比例 Percentage of total species (%)
鹅膏菌科Amanitaceae	2	11	5.26	鹅膏菌属 Amanita	10	4.78
小菇科 Mycenaceae	2	12	5.74	丝盖伞属 Inocybe	5	2.39
多孔菌科 Polyporaceae	8	14	6.70	蜡蘑属 Laccaria	5	2.39
红菇科 Russulaceae	3	23	11.00	小皮伞属 Marasmius	6	2.87
				小菇属 Mycena	11	5.26
				光柄菇属 Pluteus	5	2.39
				红菇属 Russula	17	8.13
				栓菌属 Trametes	5	2.39

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Energy source	Energy conversion stage	Representative limiting steps or processes	Representative systems	Metric type	Typical efficiency range	Primary constraints
Light	Photon capture & charge separation	PSII and antenna complexes	Cyanobacteria, algae	Quantum efficiency (RE)	0.6-0.8 (maximum)	Photo inhibition, reactive oxygen species, formation, limited spectral utilization
Electron transport	Cytochrome b6f complex, PSI	Oxygenic phototrophs	Electron transfer efficiency (RE)	~60%-80%	Proton gradient buildup, diffusion limitation
ATP generation	F-type ATP synthase	Chloroplasts, cyanobacteria	PMF-to-ATP conversion efficiency	~70%-90%	Proton leakage, coupling efficiency
CO₂ fixation	RuBisCO	Plants, cyanobacteria	Turnover rate (k_cat)	~1-10 s^-1	Low catalytic efficiency, oxygenation side reaction
Chemical (H₂)	Primary electron supply	Hydrogenase-mediated electron transfer	Hydrogen-oxidizing bacteria	Electron utilization efficiency (RE)	~50%-80%	Oxygen sensitivity, enzyme kinetics
Chemical (reduced sulfur)	Electron extraction	Sox multienzyme system	Sulfur-oxidizing bacteria	Energy recovery efficiency (EE)	~40%-70%	Multi-step electron loss
Chemical	Respiratory electron transport	Complex I (NADH dehydrogenase)	Chemolithotrophs	PMF generation efficiency	~60%-80%	Electron leakage, membrane coupling efficiency
Electricity	Extracellular electron uptake	EET pathways (cytochromes, nanowires)	Geobacter, Shewanella	Coulombic efficiency (RE)	~40%-80%	Electrode-cell interface resistance, transfer distance
Intracellular redox conversion	NAD(P)H/ferredoxin generation pathways	Electrosynthesis systems	Redox conversion efficiency (RE)	~50%-70%	Inefficient electron integration into metabolism
Chemical/electric	C1 reduction	Formate dehydrogenase	Formatotrophs	Electron utilization efficiency (RE)	~60%-85%	Thermodynamic and kinetic limitations
Acetyl-CoA synthesis	CODH/ACS complex	Acetogens	Carbon fixation efficiency (ECE)	~40%-70%	Oxygen sensitivity, complex metalloclusters

Energy source

Energy conversion stage

Representative limiting steps or processes

Representative systems

Metric type

Typical efficiency range

Primary constraints

Light

Photon capture & charge separation

PSII and antenna complexes

Cyanobacteria, algae

Quantum efficiency (RE)

0.6-0.8 (maximum)

Photo inhibition, reactive oxygen species, formation, limited spectral utilization

Electron transport

Cytochrome b6f complex, PSI

Oxygenic phototrophs

Electron transfer efficiency (RE)

~60%-80%

Proton gradient buildup, diffusion limitation

ATP generation

F-type ATP synthase

Chloroplasts, cyanobacteria

PMF-to-ATP conversion efficiency

~70%-90%

Proton leakage, coupling efficiency

CO₂ fixation

RuBisCO

Plants, cyanobacteria

Turnover rate (k_cat)

~1-10 s^-1

Low catalytic efficiency, oxygenation side reaction

Chemical

(H₂)

Primary electron supply

Hydrogenase-mediated electron transfer

Hydrogen-oxidizing bacteria

Electron utilization efficiency (RE)

~50%-80%

Oxygen sensitivity, enzyme kinetics

Chemical (reduced sulfur)

Electron extraction

Sox multienzyme system

Sulfur-oxidizing bacteria

Energy recovery efficiency (EE)

~40%-70%

Multi-step electron loss

Chemical

Respiratory electron transport

Complex I (NADH dehydrogenase)

Chemolithotrophs

PMF generation efficiency

~60%-80%

Electron leakage, membrane coupling efficiency

Electricity

Extracellular electron uptake

EET pathways (cytochromes, nanowires)

Geobacter, Shewanella

Coulombic efficiency (RE)

~40%-80%

Electrode-cell interface resistance, transfer distance

Intracellular redox conversion

NAD(P)H/ferredoxin generation pathways

Electrosynthesis systems

Redox conversion efficiency (RE)

~50%-70%

Inefficient electron integration into metabolism

Chemical/electric

C1 reduction

Formate dehydrogenase

Formatotrophs

Electron utilization efficiency (RE)

~60%-85%

Thermodynamic and kinetic limitations

Acetyl-CoA synthesis

CODH/ACS complex

Acetogens

Carbon fixation efficiency (ECE)

~40%-70%

Oxygen sensitivity, complex metalloclusters

Energy source	Carbon fixation pathway	Engineering strategy	Energy carriers	Representative outcome	References
Light-driven	rGly pathway	Semiconductor-microbe hybrid (MR-1@CdS) enabling photoelectron transfer	ATP, NADH	Sustained acetate production from CO₂ and autotrophic growth	[72]
CBB cycle	InP nanomaterials enhance PSI activity and photosynthetic electron flux	ATP, NADPH	Increased ethylene production	[78]
HWLS pathway	CdS-driven NADH regeneration coupled with proteorhodopsin-mediated ATP synthesis	ATP, NADPH	Product yields exceed theoretical limits (malate, butyrate)	[79]
Artificial CO₂ fixation (ADRP)	Synthetic photosystem generating ATP and NADH	NADH, ATP	Production of pyruvate-derived chemicals with negative carbon footprint	[80]
Electro-driven	rGly pathway	Microbial electrosynthesis with direct cathodic electron supply	ATP, NADH	Efficient acetate synthesis from CO₂	[73]
WL pathway	Direct electron uptake via EET (cytochromes and conductive pili)	ATP, NADH, Fd _red	Acetate production up to 11.05 mmol/L	[81]
WL pathway	Tandem electrocatalysis (CO₂→acetate) coupled with microbial PHB synthesis	ATP, NADH, NADPH	Increased PHB production	[82]
Artificial marine system	CO₂ electroreduction to formate followed by microbial upgrading	H₂, formate, NAD(P)H, ATP	Efficient growth and succinate production in seawater system	[83]
Chemical-driven	CBB cycle	Water splitting to generate H₂ driving hydrogen-oxidizing autotrophy	H₂, NADH, ATP	Isopropanol production up to 216 mg/L	[84]
Ribulose 5-phosphate (RuMP) pathway	Enhanced methanol oxidation and cofactor redistribution	Methanol, NAD(P)H, ATP	Improved growth and product yields	[63]
CBB cycle	Decoupling carbon fixation from energy metabolism using pyruvate	Pyruvate, NADH, ATP	Semi-autotrophic growth and sugar production	[18]
CBB cycle	Reducing energy dissipation and enhancing FDH activity	Formate, NADPH, ATP	Improved CO₂-to-sugar conversion	[19]
rGly pathway	Combined methanol and formate oxidation for redox supply	Methanol, formate, NAD(P)H, ATP	Improved growth and carbon utilization	[85]
Serine pathway	NADPH-generating methanol dehydrogenase and PPP enhancement	Methanol, NADPH, ATP	Increased product yield with maintained growth	[86]

Energy source

Carbon fixation pathway

Engineering strategy

Energy carriers

Representative outcome

References

Light-driven

rGly pathway

Semiconductor-microbe hybrid (MR-1@CdS) enabling photoelectron transfer

ATP, NADH

Sustained acetate production from CO₂ and autotrophic growth

[72]

CBB cycle

InP nanomaterials enhance PSI activity and photosynthetic electron flux

ATP, NADPH

Increased ethylene production

[78]

HWLS pathway

CdS-driven NADH regeneration coupled with proteorhodopsin-mediated ATP synthesis

ATP, NADPH

Product yields exceed theoretical limits (malate, butyrate)

[79]

Artificial CO₂ fixation (ADRP)

Synthetic photosystem generating ATP and NADH

NADH, ATP

Production of pyruvate-derived chemicals with negative carbon footprint

[80]

Electro-driven

rGly pathway

Microbial electrosynthesis with direct cathodic electron supply

ATP, NADH

Efficient acetate synthesis from CO₂

[73]

WL pathway

Direct electron uptake via EET (cytochromes and conductive pili)

ATP, NADH, Fd _red

Acetate production up to

11.05 mmol/L

[81]

WL pathway

Tandem electrocatalysis (CO₂→acetate) coupled with microbial PHB synthesis

ATP, NADH, NADPH

Increased PHB production

[82]

Artificial marine system

CO₂ electroreduction to formate followed by microbial upgrading

H₂, formate, NAD(P)H, ATP

Efficient growth and succinate production in seawater system

[83]

Chemical-driven

CBB cycle

Water splitting to generate H₂ driving hydrogen-oxidizing autotrophy

H₂, NADH, ATP

Isopropanol production up to 216 mg/L

[84]

Ribulose 5-phosphate (RuMP) pathway

Enhanced methanol oxidation and cofactor redistribution

Methanol, NAD(P)H, ATP

Improved growth and product yields

[63]

CBB cycle

Decoupling carbon fixation from energy metabolism using pyruvate

Pyruvate, NADH, ATP

Semi-autotrophic growth and sugar production

[18]

CBB cycle

Reducing energy dissipation and enhancing FDH activity

Formate, NADPH, ATP

Improved CO₂-to-sugar conversion

[19]

rGly pathway

Combined methanol and formate oxidation for redox supply

Methanol, formate, NAD(P)H, ATP

Improved growth and carbon utilization

[85]

Serine pathway

NADPH-generating methanol dehydrogenase and PPP enhancement

Methanol, NADPH, ATP

Increased product yield with maintained growth

[86]