Live imaging enables direct observation of dynamic biological processes,capturing their progression from molecular to organismal scales in space and time.Through high-resolution observation,it provides a powerful mean...Live imaging enables direct observation of dynamic biological processes,capturing their progression from molecular to organismal scales in space and time.Through high-resolution observation,it provides a powerful means to decode biological complexity by revealing dynamic behaviors,spatial patterns,and regulatory changes.This review illustrates the application of live imaging in investigating complex biological processes with spatiotemporal resolution and mechanistic insight.We first highlight the analytical power and integrative strategies of live imaging,and then summarize recent advances that further extend its capacities.We then focus on four complex processes―cell proliferation,lineage regulation,morphogenesis,and atlas construction―to elucidate how live imaging contributes to their decoding through representative studies.We also discuss the conceptual and practical limitations that currently constrain the full interpretive potential of live imaging,underscoring the need for deeper integration between observation,perturbation,and modeling.Looking ahead,live imaging will benefit from both technical refinement and advances in data standardization and visualization,functional quantification,multiscale integration,and the discovery of generalizable principles.Together,these directions advance a more integrative and mechanistic understanding of complex biological processes.展开更多
面对生命这一结构复杂、层级丰富、动态性强的系统,应当如何选择并采用更为有效的方法开展研究?这一问题的答案与重点在生命科学的不同发展阶段也不尽相同。20世纪90年代两则经典故事:《道格的救赎》(The Salvation of Doug)与《比尔的...面对生命这一结构复杂、层级丰富、动态性强的系统,应当如何选择并采用更为有效的方法开展研究?这一问题的答案与重点在生命科学的不同发展阶段也不尽相同。20世纪90年代两则经典故事:《道格的救赎》(The Salvation of Doug)与《比尔的消亡》(The Demise of Bill),曾以汽车为类比对象,用讽刺笔法生动呈现了遗传学家与生物化学家理解汽车运行机制所采用的不同研究策略:是通过拆解组分、解析互作来揭示潜在机制,还是借助功能扰动来识别系统的关键环节?哪种方法能更有效解析生命过程?作为启发式寓言,它们在当时引发了关于不同研究方法优劣与互补性的广泛讨论。时至今日,这两则故事仍是教学中的重要素材。当前,生命科学进入高通量、高精度、多维度融合的新阶段,传统的单一路径研究策略已难以支撑对复杂生命过程深入而系统地理解。生命活动具有模块化结构、调控网络、非线性响应以及适应性补偿等诸多特性,而单一策略往往仅能捕捉其局部、静态特征,难以还原整体的动态特征和调控规律,从而限制了对复杂生命过程的系统认知,也制约了理论深化与应用突破。基于此,本文尝试对上述两个经典故事进行了续写,将其延伸至更具时代特征的场景中,并赋予了主角具有象征意义的中文名字:“知微”(代表生化路径)和“思序”(象征遗传思路)。通过讲述他们在探索智能电动汽车系统的运行原理过程中,如何从各自为营的局面逐渐走向协作与共赢,运用高通量手段,开展系统性分析,并引入数字仿真建模,逐步揭示复杂系统行为背后的结构特性与运行逻辑。故事呼应当前生命科学对系统性与动态性研究的日益重视及其所面临的挑战,强调方法融合与创新的关键作用,鼓励读者思考遗传学方法在当代研究范式中的定位与价值,旨在为遗传学及相关学科的教学提供参考。展开更多
基金supported by the National Key Research and Development Program of China(2022YFA1303000 and 2021YFA0805800)the National Natural Science Foundation of China(32325032)the Chinese Academy of Sciences Project for Young Scientists in Basic Research(YSBR-073).
文摘Live imaging enables direct observation of dynamic biological processes,capturing their progression from molecular to organismal scales in space and time.Through high-resolution observation,it provides a powerful means to decode biological complexity by revealing dynamic behaviors,spatial patterns,and regulatory changes.This review illustrates the application of live imaging in investigating complex biological processes with spatiotemporal resolution and mechanistic insight.We first highlight the analytical power and integrative strategies of live imaging,and then summarize recent advances that further extend its capacities.We then focus on four complex processes―cell proliferation,lineage regulation,morphogenesis,and atlas construction―to elucidate how live imaging contributes to their decoding through representative studies.We also discuss the conceptual and practical limitations that currently constrain the full interpretive potential of live imaging,underscoring the need for deeper integration between observation,perturbation,and modeling.Looking ahead,live imaging will benefit from both technical refinement and advances in data standardization and visualization,functional quantification,multiscale integration,and the discovery of generalizable principles.Together,these directions advance a more integrative and mechanistic understanding of complex biological processes.
文摘面对生命这一结构复杂、层级丰富、动态性强的系统,应当如何选择并采用更为有效的方法开展研究?这一问题的答案与重点在生命科学的不同发展阶段也不尽相同。20世纪90年代两则经典故事:《道格的救赎》(The Salvation of Doug)与《比尔的消亡》(The Demise of Bill),曾以汽车为类比对象,用讽刺笔法生动呈现了遗传学家与生物化学家理解汽车运行机制所采用的不同研究策略:是通过拆解组分、解析互作来揭示潜在机制,还是借助功能扰动来识别系统的关键环节?哪种方法能更有效解析生命过程?作为启发式寓言,它们在当时引发了关于不同研究方法优劣与互补性的广泛讨论。时至今日,这两则故事仍是教学中的重要素材。当前,生命科学进入高通量、高精度、多维度融合的新阶段,传统的单一路径研究策略已难以支撑对复杂生命过程深入而系统地理解。生命活动具有模块化结构、调控网络、非线性响应以及适应性补偿等诸多特性,而单一策略往往仅能捕捉其局部、静态特征,难以还原整体的动态特征和调控规律,从而限制了对复杂生命过程的系统认知,也制约了理论深化与应用突破。基于此,本文尝试对上述两个经典故事进行了续写,将其延伸至更具时代特征的场景中,并赋予了主角具有象征意义的中文名字:“知微”(代表生化路径)和“思序”(象征遗传思路)。通过讲述他们在探索智能电动汽车系统的运行原理过程中,如何从各自为营的局面逐渐走向协作与共赢,运用高通量手段,开展系统性分析,并引入数字仿真建模,逐步揭示复杂系统行为背后的结构特性与运行逻辑。故事呼应当前生命科学对系统性与动态性研究的日益重视及其所面临的挑战,强调方法融合与创新的关键作用,鼓励读者思考遗传学方法在当代研究范式中的定位与价值,旨在为遗传学及相关学科的教学提供参考。
