Main Points of the Talk

• Solving anatomical homeostasis is key to transformative regenerative medicine, including addressing aging.
• Current approaches (stem cell biology, genomic editing) are limited; understanding the “software of life” is crucial.
• Non-neural bioelectricity is a key medium for cellular computation and decision-making in vivo.
• We can now read and write goal states into the collective intelligence of tissues.
• Cracking the bioelectric code (evolutionary precursor to brain’s electrical code) will enable electroceuticals for birth defects, regenerative medicine, cancer, aging, and synthetic bioengineering.
• Simplified: All body cells, not just brain, make decisions regarding body and stucture, with which we can interface.

Fundamental Knowledge Gaps

• We lack an “anatomical compiler” to translate desired anatomical forms into stimuli that guide cell behavior. This compiler would allow total control over morphology (livers, hearts, new organisms, etc.).
• Genomics alone can’t predict anatomical outcomes (e.g., will a frog-axolotl hybrid have legs?). We need to understand how cell groups “know” what to make and when to stop.
• Cell groups exhibit collective intelligence, resulting in the self-assembly. We also wonder: How do cells build? What could else they build?

The Limitations of the Current Paradigm

• Current Paradigm is difficult: We need to “invert” the complicated sequence to control for regeneration, when there exist a feedback system.
• The mainstream paradigm (gene regulatory networks leading to emergent complexity) is difficult to “invert” for regenerative purposes. Figuring out which genes to edit for complex anatomical changes is intractable.
• We’re good at understanding pathways, but not at predicting or rationally altering different shapes.

Regeneration Examples

• Axolotls regenerate limbs, eyes, ovaries, portions of heart/brain, spinal cords. Regeneration stops when the *correct* structure is formed, showing adaptive problem-solving.
• Human liver regeneration, deer antler regeneration (up to 1.5 cm of bone per day in mammals!), and fingertip regeneration in young children show regenerative potential.
• Planaria: Champions of regeneration. Can regrow from tiny fragments, have true brains, learn, and are biologically immortal.
• Planeria still mostly reform to normal form: when a piccaso-ized tadpole regrows, they adjust from random position, such as misplaced eyes.

Problem-Solving by Cellular Collective Intelligence

• Example: “Picasso tadpoles” with misplaced facial features still develop into largely normal frogs. Components move in novel paths, showing error minimization and an internal representation of a correct frog face.
• This demonstrates collective intelligence: cells solve problems from different starting configurations.

Computer Science Analogy

• Early programming (1940s-50s) required physical rewiring. Modern computing uses software to interact with reprogrammable hardware.
• Modern biology is mostly focused on the “hardware” (single molecules, gene editing). We need to understand the “software” and use stimuli, not rewiring, to control morphology.
• Theorizes feedback homeostasis: We may alter body “thermostat” for repair, not having to control step by step but the output.

Homeostatic Model

• Proposes a feedback loop model where challenges (injury, aging, pathogens) trigger responses to return to the correct “target morphology.”
• The “set point” is not a simple number, but a complex, coarse-grained representation of the anatomy.
• The system has a “goal” (in the cybernetic sense) and expends energy to minimize the error between the current and target shapes.
• Goal prediction is that target may be altereted, rewriting the output, much like a thermostat changes temperature but works the same way.

Developmental Bioelectricity

• Cells exist in a morphogenetic field of information (chemical gradients, mechanical forces, and bioelectricity). Bioelectricity is a uniquely powerful layer.
• Cells make bioelectricity through the use of ION channels, which pass ions in/out of cells and the cell state.
• All cells (not just neurons) have ion channels and gap junctions, creating electrical networks. This is ancient, dating back to bacterial biofilms.
• Bioelectricity and brains is useful for behaviour and cognition to solve problems, while bioelectricity controls and develop and move in space, solving anatomical growth problems.
• Tools: Voltage-sensitive fluorescent dyes reveal real-time electrical communication. Computational modeling and functional techniques (optogenetics, drugs, mutations) allow us to change electrical information processing without electrodes or electromagnetics.
• In tadpoles, there exist electrical gradient pattern, like faces, and they exist before actual changes in genes/cells. These patterns exist as the scaffolding to be referenced by cellls.

Examples of Bioelectric Control

• “Electric face” in tadpoles: A bioelectric pattern that *looks like a face* precedes gene expression and anatomical changes. Altering this pattern changes anatomy.
• Tumorigenesis: Cells with aberrant electrical potentials dissociate from the network, reverting to a unicellular state (metastasis). Preventing this dissociation (with ion channels) can prevent tumor formation despite oncogene expression.
• Ectopic organ induction: Inducing a specific voltage state can cause cells to build an eye (with all correct layers) in the wrong location (gut, tail, etc.). These cells recruit neighbors.
• It appears there is something like built-in routines for body part construction and they exist a the bioelectric level, with which scientists can leverage, like software functions in programming.

Planaria and Bioelectric Memory

• Cutting a planarian creates a voltage gradient that specifies where to build a head and tail. Manipulating this gradient can create two-headed or no-headed animals.
• These altered body plans are *stable*. Cut pieces from a two-headed worm continue to regenerate as two-headed, even with a wild-type genome. This demonstrates bioelectric memory of the target morphology.
• Perturbing the electrical network can induce head shapes and brain shapes appropriate to *other planarian species*, accessing different attractors in the state space of possibilities.
• Same geneome with a bioelectrical difference yields drastically different forms and structures.

Frog Leg Regeneration

• Frogs don’t normally regenerate legs.
• A designed by looking at bioelectrical output, we designed a drug cocktail that is “worn” on the stump as bioreactors for only a 24 hr intervention: The results yields 13+ months, yielding touch-sensitive, moving legs.
• A cocktail of ion channel drugs applied for just 24 hours can kick-start leg regeneration, activating pro-regenerative genes and leading to a functional leg.
• This approach also works in human mesenchymal stem cells and cardiomyocytes. Human channelopathies (ion channel mutations) confirm the importance of bioelectricity in human morphology.
• The drugs induce a biological states.

Computational Models and Machine Learning

• We’re developing multi-scale models to link genes, ion channels, physiological tissues, organ structures, and algorithmic control of electrical activity.
• Machine learning helps discover electrical circuits and design therapeutic modulations.
• Example: Modeling the bioelectric circuit of the brain can identify which channels to target to rescue brain development after mutations or teratogen exposure (nicotine, alcohol).

Towards Electroceuticals

• Goal: A pipeline from ion channel information to desired bioelectrical state to drug selection (channel openers/blockers). ~20% of all drugs target ion channels.
• Electroceuticals (ion channel drugs) can be repurposed for regenerative medicine, guided by computational simulations.
• They provide a free software online.

Summary

• There’s a powerful physiological “software” layer between genotype and anatomy, a tractable target for regenerative biomedicine.
• Electrical signaling is a convenient medium for computation and global decision-making (exploited by brains, computers, and morphogenesis).
• Cracking this code allows us to rewrite pattern memories and control large-scale shape.
• AI tools enable rational design for addressing birth defects, cancer, regeneration, and creating synthetic living organisms.

Q&A Highlights

• We want to learn how cells make decisions using bioloectrity.
• Reviews: Many reviews are available on bioelectricity. (Email Levin for recommendations)
• Transduction to gene expression: Multiple pathways are known (voltage-gated calcium, neurotransmitter control, voltage-sensitive phosphatases, etc.), but global dynamics are key.
• The function bioelectricity do are largely to keep morphostasis and against senscence and tumor, keeping the tissue/organs healthy.
• Adult bioelectric networks: Likely involved in morphostasis (maintaining tissue integrity) and cancer suppression. Aging-bioelectricity interface is poorly understood.
• Electrical zones appearance and dispersal: ION Channels control electricy while emergence create structures.
• Planarian learned behaviors: *Yes*, learned behaviors *are* retained in regenerated fragments, indicating information storage outside the brain.
• We don’t know what is a human “regeneration button”: Intervention tools: Ion channel drugs, guided by computational models, are the most promising tools.
• Relation: relationship is unsure with peptide based ION Channels.
• Cocktail for limb regeneration: Will be published soon; contains five ingredients. He does not have any dpca at this point but maybe soon.
• We don’t know: We don’t have info yet on the biological age of regerated tissue yet but soon as his partner has the info and testing method ready.
• *Yes*, bioelectric signaling could potentially trigger rapid bone regrowth (like deer antlers).
• Using electroical signals for cell control: not easy because they may just migrate with such external devices. Optogenetics are preferrable to set more complesx outputs.
• Leveraging new technology to improve toolkit? More improved dies to better study tissues, their state, behaviour, condition. Also NGS sequencing will allow more easy access of which tissue control which cells/tissues.
• Lack of labs: it’s very niche, most biologists “fall into” through genetic study and channel diseases. Funding for study is near impossible. Michael Levin published various studies and welcomes collaborations.
• Future: next company focus on limited area such as limbs with the use of bioreactors. They can do this in mice and hoping someday they can do this to human limbs. Future is broad approach for picking bioelectriceuticals. Michael welcome investors.
• Michael challenge for longevity channel is image of Bioelectric status to do all the work, of many more model to really speed up this industry/scientific field.

演讲要点

• 解决解剖稳态是变革性再生医学的关键，包括解决衰老问题。
• 当前的方法（干细胞生物学、基因组编辑）是有限的；理解“生命软件”至关重要。
• 非神经生物电是在体细胞计算和决策的关键媒介。
• 我们现在可以将目标状态读取和写入组织的集体智能中。
• 破解生物电密码（大脑电密码的进化前体）将使电疗法能够用于出生缺陷、再生医学、癌症、衰老和合成生物工程。
• 简化版：所有身体细胞，不仅仅是大脑，都会对身体和结构做出决定，我们可以与之交互。

基本知识差距

• 我们缺乏一个“解剖编译器”来将所需的解剖形式转换为指导细胞行为的刺激。这个编译器将允许完全控制形态（肝脏、心脏、新生物等）。
• 仅基因组学无法预测解剖结果（例如，青蛙-蝾螈杂交体会长腿吗？）。我们需要了解细胞群如何“知道”要制造什么以及何时停止。
• 细胞群表现出集体智能，导致自组装。我们也想知道：细胞如何构建？它们还能构建什么？

当前范式的局限性

• 当前范式很困难：我们需要“反转”复杂的序列来控制再生，因为存在反馈系统。
• 主流范式（导致涌现复杂性的基因调控网络）很难“反转”以用于再生目的。弄清楚要编辑哪些基因以进行复杂的解剖变化是棘手的。
• 我们擅长理解通路，但不擅长预测或合理地改变不同的形状。

再生实例

• 蝾螈再生四肢、眼睛、卵巢、心脏/大脑部分、脊髓。当形成*正确的*结构时，再生停止，显示出自适应解决问题。
• 人类肝脏再生、鹿角再生（哺乳动物每天最多 1.5 厘米的骨骼！）以及幼儿的指尖再生显示了再生潜力。
• 涡虫：再生的冠军。可以从微小的碎片中再生，拥有真正的大脑，学习，并且在生物学上是不朽的。
• 即使被“毕加索化”：当毕加索化的蝌蚪重新生长时，它们会从随机位置进行调整，例如错位的眼睛, 涡虫仍然主要恢复到正常形态。

通过细胞集体智能解决问题

• 例子：面部特征错位的“毕加索蝌蚪”仍然发育成基本正常的青蛙。组件沿着新的路径移动，显示出误差最小化和正确青蛙脸的内部表示。
• 这证明了集体智能：细胞从不同的起始配置解决问题。

计算机科学类比

• 早期编程（1940-50 年代）需要物理重新布线。现代计算使用软件与可重新编程的硬件进行交互。
• 现代生物学主要关注“硬件”（单分子、基因编辑）。我们需要了解“软件”并使用刺激，而不是重新布线，来控制形态。
• 理论化反馈稳态：我们可以改变身体“恒温器”进行修复，不必逐步控制而是控制输出。

稳态模型

• 提出了一种反馈回路模型，其中挑战（损伤、衰老、病原体）触发响应以返回到正确的“目标形态”。
• “设定点”不是一个简单的数字，而是解剖结构的复杂、粗粒度表示。
• 系统有一个“目标”（在控制论意义上）并消耗能量以最小化当前形状和目标形状之间的误差。
• 目标预测是目标可能会改变，重写输出，就像恒温器改变温度但工作方式相同一样。

发育生物电

• 细胞存在于信息的形态发生场（化学梯度、机械力和生物电）中。生物电是一个独特强大的层。
• 细胞通过使用离子通道产生生物电，离子通道将离子传入/传出细胞和细胞状态。
• 所有细胞（不仅仅是神经元）都有离子通道和间隙连接，形成电网络。这很古老，可以追溯到细菌生物膜。
• 生物电和大脑对解决问题的行为和认知很有用，而生物电控制和发展并在空间中移动，解决解剖生长问题。
• 工具：电压敏感荧光染料揭示实时电通信。计算建模和功能技术（光遗传学、药物、突变）使我们能够在没有电极或电磁学的情况下改变电信息处理。
• 在蝌蚪中，存在电梯度模式，如面部，它们存在于基因/细胞实际变化之前。这些模式作为细胞参考的支架而存在。

生物电控制的例子

• 蝌蚪中的“电脸”：一个*看起来像脸*的生物电模式先于基因表达和解剖变化。改变这种模式会改变解剖结构。
• 肿瘤发生：具有异常电位的细胞与网络分离，恢复到单细胞状态（转移）。防止这种分离（使用离子通道）可以防止肿瘤形成，尽管有癌基因表达。
• 异位器官诱导：诱导特定的电压状态可以导致细胞在错误的位置（肠道、尾巴等）构建眼睛（具有所有正确的层）。这些细胞会招募邻近的细胞。
• 似乎存在类似于内置的身体部位构建程序，它们存在于生物电水平，科学家可以利用它们，就像编程中的软件功能一样。

涡虫和生物电记忆

• 切割涡虫会产生一个电压梯度，指定在哪里构建头部和尾部。操纵这种梯度可以创造双头或无头动物。
• 这些改变的身体计划是*稳定的*。从双头蠕虫身上切下的碎片继续再生为双头，即使是野生型基因组。这证明了目标形态的生物电记忆。
• 扰动电网络可以诱导适合*其他涡虫物种*的头部形状和大脑形状，访问可能性状态空间中的不同吸引子。
• 具有生物电差异的相同基因组产生截然不同的形式和结构。

蛙腿再生

• 青蛙通常不再生腿。
• 通过观察生物电输出来设计的，我们设计了一种药物混合物，它作为生物反应器“佩戴”在残肢上仅 24 小时干预：结果产生 13 个月以上，产生触觉敏感、移动的腿。
• 仅应用 24 小时的离子通道药物混合物可以启动腿部再生，激活促再生基因并导致功能性腿部。
• 这种方法也适用于人类间充质干细胞和心肌细胞。人类通道病（离子通道突变）证实了生物电在人类形态学中的重要性。
• 这些药物诱导生物状态。

计算模型和机器学习

• 我们正在开发多尺度模型，以连接基因、离子通道、生理组织、器官结构和电活动的算法控制。
• 机器学习有助于发现电路并设计治疗性调节。
• 例子：对大脑的生物电回路进行建模可以确定突变或致畸剂暴露（尼古丁、酒精）后要拯救大脑发育的目标通道。

迈向电疗法

• 目标：从离子通道信息到所需生物电状态再到药物选择（通道开放剂/阻断剂）的流程。约 20% 的所有药物都靶向离子通道。
• 电疗法（离子通道药物）可以在计算模拟的指导下重新用于再生医学。
• 他们在网上提供免费软件。

总结

• 在基因型和解剖结构之间有一个强大的生理“软件”层，这是再生生物医学的一个易于处理的目标。
• 电信号是计算和全局决策的便捷媒介（由大脑、计算机和形态发生利用）。
• 破解这个密码使我们能够重写模式记忆并控制大规模形状。
• 人工智能工具能够进行合理的设计，以解决出生缺陷、癌症、再生和创造合成活生物体。

问答环节亮点

• 我们想了解细胞如何利用生物电做出决策。
• 评论：有许多关于生物电的评论。（给 Levin 发电子邮件以获取建议）
• 转导到基因表达：已知多种途径（电压门控钙、神经递质控制、电压敏感磷酸酶等），但全局动力学是关键。
• 生物电的功能主要是保持形态稳定和抵抗衰老和肿瘤，保持组织/器官健康。
• 成人生物电网络：可能参与形态稳定（维持组织完整性）和癌症抑制。衰老-生物电界面知之甚少。
• 电区出现和分散：离子通道控制电流，而涌现创造结构。
• 涡虫学习的行为：*是的*，学习的行为*被*保留在再生的碎片中，表明大脑之外的信息存储。
• 我们不知道什么是人类的“再生按钮”：干预工具：离子通道药物，在计算模型的指导下，是最有前途的工具。
• 关系：与基于肽的离子通道的关系不确定。
• 用于肢体再生的鸡尾酒疗法：即将发布；包含五种成分。 他目前没有任何 dpca，但可能很快就会有。
• 我们不知道：我们还没有关于再生组织的生物学年龄的信息，但很快他的合作伙伴就会准备好信息和测试方法。
• *是的*，生物电信号可能会触发骨骼快速再生（如鹿角）。
• 使用电信号进行细胞控制：并不容易，因为它们可能只会随着这种外部设备迁移。光遗传学更适合设置更复杂的输出。
• 利用新技术改进工具包？更改进的染料可以更好地研究组织、它们的状态、行为、状况。此外，NGS 测序将使人们更容易获得哪些组织控制哪些细胞/组织。
• 缺乏实验室：它非常小众，大多数生物学家都是通过基因研究和通道疾病“进入”的。研究经费几乎是不可能的。Michael Levin 发表了各种研究并欢迎合作。
• 未来：下一家公司专注于有限的领域，例如使用生物反应器的四肢。他们可以在老鼠身上做到这一点，并希望有一天他们可以对人类的四肢做到这一点。未来是选择生物电疗法的广泛方法。Michael 欢迎投资者。
• Michael 对长寿频道的挑战是生物电状态的形象，以完成所有工作，更多的模型才能真正加速这个行业/科学领域。