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Xu W, Liu Z, Wang J, Jin K, Yue L, Yu L, Niu L, Dou Q, Liu J, Zhang Y, Zhu X, Wu Y. Extending visual range of bacteria with upconversion nanoparticles and constructing NIR-responsive bio-microrobots. J Colloid Interface Sci 2025; 682:608-618. [PMID: 39642547 DOI: 10.1016/j.jcis.2024.11.225] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2024] [Revised: 11/16/2024] [Accepted: 11/27/2024] [Indexed: 12/09/2024]
Abstract
The motility of bacteria is crucial for navigating competitive environments and is closely linked to physiological activities essential for their survival, such as biofilm development. Precise regulation of bacterial motility enhances our understanding of these complex processes. While optogenetic tools have been used to control and investigate bacterial motility, the excitation light in most existing systems are limited to the visible light spectrum. Here, we introduce a new type of bio-microrobot comprising genetically engineered E. coli cells and orthogonally emissive upconversion nanoparticles that can respond to both 980 nm and 808 nm NIR light. This system allows toggling of bacterial states between tumbling and swimming via simply alternating the NIR light between different wavelengths. It is believed that the use of NIR light with deeper tissue penetration suggests potential applications for these bio-microrobots in areas like targeted drug delivery.
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Affiliation(s)
- Wei Xu
- Department of Environmental and Chemical Engineering, Shanghai University, Shanghai, China
| | - Zhen Liu
- Department of Environmental and Chemical Engineering, Shanghai University, Shanghai, China
| | - Jing Wang
- Department of Environmental and Chemical Engineering, Shanghai University, Shanghai, China
| | - Kai Jin
- Department of Environmental and Chemical Engineering, Shanghai University, Shanghai, China
| | - Lulu Yue
- Department of Environmental and Chemical Engineering, Shanghai University, Shanghai, China
| | - Lin Yu
- Department of Environmental and Chemical Engineering, Shanghai University, Shanghai, China; School of Medicine, Shanghai University, Shanghai, China
| | - Luqi Niu
- Department of Environmental and Chemical Engineering, Shanghai University, Shanghai, China
| | - Qingqing Dou
- Department of Environmental and Chemical Engineering, Shanghai University, Shanghai, China
| | - Jinliang Liu
- Department of Environmental and Chemical Engineering, Shanghai University, Shanghai, China
| | - Yuzhe Zhang
- School of Environmental Science and Engineering, Changzhou University, Changzhou, China
| | - Xiaohui Zhu
- Department of Environmental and Chemical Engineering, Shanghai University, Shanghai, China.
| | - Yihan Wu
- Department of Environmental and Chemical Engineering, Shanghai University, Shanghai, China.
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Spasokukotskiy K. Synthetic consciousness architecture. Front Robot AI 2024; 11:1437496. [PMID: 39669909 PMCID: PMC11634756 DOI: 10.3389/frobt.2024.1437496] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2024] [Accepted: 10/22/2024] [Indexed: 12/14/2024] Open
Abstract
This paper presents a theoretical inquiry into the domain of secure artificial superintelligence (ASI). The paper introduces an architectural pattern tailored to fulfill friendly alignment criteria. Friendly alignment refers to a failsafe artificial intelligence alignment that lacks supervision while still having a benign effect on humans. The proposed solution is based on a biomimetic approach to emulate the functional aspects of biological consciousness. It establishes "morality" that secures alignment in large systems. The emulated function set is drawn from a cross section of evolutionary and psychiatric frameworks. Furthermore, the paper assesses the architectural potential, practical utility, and limitations of this approach. Notably, the architectural pattern supports straightforward implementation by activating existing foundation models. The models can be underpinned by simple algorithms. Simplicity does not hinder the production of high derivatives, which contribute to alignment strength. The architectural pattern enables the adjustment of alignment strength, enhancing the adaptability and usability of the solution in practical applications.
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Vo L, Avgidis F, Mattingly HH, Edmonds K, Burger I, Balasubramanian R, Shimizu TS, Kazmierczak BI, Emonet T. Non-genetic adaptation by collective migration. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.02.573956. [PMID: 38260286 PMCID: PMC10802332 DOI: 10.1101/2024.01.02.573956] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
Cell populations must adjust their phenotypic composition to adapt to changing environments. One adaptation strategy is to maintain distinct phenotypic subsets within the population and to modulate their relative abundances via gene regulation. Another strategy involves genetic mutations, which can be augmented by stress-response pathways. Here, we studied how a migrating bacterial population regulates its phenotypic distribution to traverse diverse environments. We generated isogenic Escherichia coli populations with varying distributions of swimming behaviors and observed their phenotype distributions during migration in liquid and porous environments. We found that the migrating populations became enriched with high-performing swimming phenotypes in each environment, allowing the populations to adapt without requiring mutations or gene regulation. This adaptation is dynamic and rapid, reversing in a few doubling times when migration ceases. By measuring the chemoreceptor abundance distributions during migration towards different attractants, we demonstrated that adaptation acts on multiple chemotaxis-related traits simultaneously. These measurements are consistent with a general mechanism in which adaptation results from a balance between cell growth generating diversity and collective migration eliminating under-performing phenotypes. Thus, collective migration enables cell populations with continuous, multi-dimensional phenotypes to flexibly and rapidly adapt their phenotypic composition to diverse environmental conditions. Significance statement Conventional cell adaptation mechanisms, like gene regulation and stochastic phenotypic switching, act swiftly but are limited to a few traits, while mutation-driven adaptations unfold slowly. By quantifying phenotypic diversity during bacterial collective migration, we discovered an adaptation mechanism that rapidly and reversibly adjusts multiple traits simultaneously. By balancing the generation of diversity through growth with the loss of phenotypes unable to keep up, this process tunes the phenotypic composition of migrating populations to the environments they traverse, without gene regulation or mutations. Given the prevalence of collective migration in microbes, cancers, and embryonic development, non-genetic adaptation through collective migration may be a universal mechanism for populations to navigate diverse environments, offering insights into broader applications across various fields.
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Phan TV, Mattingly HH, Vo L, Marvin JS, Looger LL, Emonet T. Direct measurement of dynamic attractant gradients reveals breakdown of the Patlak-Keller-Segel chemotaxis model. Proc Natl Acad Sci U S A 2024; 121:e2309251121. [PMID: 38194458 PMCID: PMC10801886 DOI: 10.1073/pnas.2309251121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Accepted: 12/07/2023] [Indexed: 01/11/2024] Open
Abstract
Chemotactic bacteria not only navigate chemical gradients, but also shape their environments by consuming and secreting attractants. Investigating how these processes influence the dynamics of bacterial populations has been challenging because of a lack of experimental methods for measuring spatial profiles of chemoattractants in real time. Here, we use a fluorescent sensor for aspartate to directly measure bacterially generated chemoattractant gradients during collective migration. Our measurements show that the standard Patlak-Keller-Segel model for collective chemotactic bacterial migration breaks down at high cell densities. To address this, we propose modifications to the model that consider the impact of cell density on bacterial chemotaxis and attractant consumption. With these changes, the model explains our experimental data across all cell densities, offering insight into chemotactic dynamics. Our findings highlight the significance of considering cell density effects on bacterial behavior, and the potential for fluorescent metabolite sensors to shed light on the complex emergent dynamics of bacterial communities.
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Affiliation(s)
- Trung V. Phan
- Department of Molecular, Cellular, and Developmental Biology, Yale University, New Haven, CT06511
- Quantitative Biology Institute, Yale University, New Haven, CT06511
| | | | - Lam Vo
- Department of Molecular, Cellular, and Developmental Biology, Yale University, New Haven, CT06511
- Quantitative Biology Institute, Yale University, New Haven, CT06511
| | - Jonathan S. Marvin
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA20147
| | - Loren L. Looger
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA20147
- HHMI, University of California, San Diego, CA92093
- Department of Neurosciences, University of California, San Diego, CA92093
| | - Thierry Emonet
- Department of Molecular, Cellular, and Developmental Biology, Yale University, New Haven, CT06511
- Quantitative Biology Institute, Yale University, New Haven, CT06511
- Department of Physics, Yale University, New Haven, CT06511
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Zhao H, Košmrlj A, Datta SS. Chemotactic Motility-Induced Phase Separation. PHYSICAL REVIEW LETTERS 2023; 131:118301. [PMID: 37774273 DOI: 10.1103/physrevlett.131.118301] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/29/2023] [Revised: 06/08/2023] [Accepted: 08/16/2023] [Indexed: 10/01/2023]
Abstract
Collectives of actively moving particles can spontaneously separate into dilute and dense phases-a fascinating phenomenon known as motility-induced phase separation (MIPS). MIPS is well-studied for randomly moving particles with no directional bias. However, many forms of active matter exhibit collective chemotaxis, directed motion along a chemical gradient that the constituent particles can generate themselves. Here, using theory and simulations, we demonstrate that collective chemotaxis strongly competes with MIPS-in some cases, arresting or completely suppressing phase separation, or in other cases, generating fundamentally new dynamic instabilities. We establish principles describing this competition, thereby helping to reveal and clarify the rich physics underlying active matter systems that perform chemotaxis, ranging from cells to robots.
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Affiliation(s)
- Hongbo Zhao
- Department of Chemical and Biological Engineering, Princeton University, Princeton, New Jersey 08544, USA
| | - Andrej Košmrlj
- Department of Mechanical and Aerospace Engineering, Princeton University, Princeton, New Jersey 08544, USA
- Princeton Materials Institute, Princeton University, Princeton, New Jersey 08544, USA
| | - Sujit S Datta
- Department of Chemical and Biological Engineering, Princeton University, Princeton, New Jersey 08544, USA
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Collective behavior and nongenetic inheritance allow bacterial populations to adapt to changing environments. Proc Natl Acad Sci U S A 2022; 119:e2117377119. [PMID: 35727978 DOI: 10.1073/pnas.2117377119] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Collective behaviors require coordination among a group of individuals. As a result, individuals that are too phenotypically different from the rest of the group can be left out, reducing heterogeneity, but increasing coordination. If individuals also reproduce, the offspring can have different phenotypes from their parent(s). This raises the question of how these two opposing processes-loss of diversity by collective behaviors and generation of it through growth and inheritance-dynamically shape the phenotypic composition of an isogenic population. We examine this question theoretically using collective migration of chemotactic bacteria as a model system, where cells of different swimming phenotypes are better suited to navigate in different environments. We find that the differential loss of phenotypes caused by collective migration is environment-dependent. With cell growth, this differential loss enables migrating populations to dynamically adapt their phenotype compositions to the environment, enhancing migration through multiple environments. Which phenotypes are produced upon cell division depends on the level of nongenetic inheritance, and higher inheritance leads to larger composition adaptation and faster migration at steady state. However, this comes at the cost of slower responses to new environments. Due to this trade-off, there is an optimal level of inheritance that maximizes migration speed through changing environments, which enables a diverse population to outperform a nondiverse one. Growing populations might generally leverage the selection-like effects provided by collective behaviors to dynamically shape their own phenotype compositions, without mutations.
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Muskhelishvili G, Sobetzko P, Travers A. Spatiotemporal Coupling of DNA Supercoiling and Genomic Sequence Organization-A Timing Chain for the Bacterial Growth Cycle? Biomolecules 2022; 12:biom12060831. [PMID: 35740956 PMCID: PMC9221221 DOI: 10.3390/biom12060831] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Revised: 06/08/2022] [Accepted: 06/08/2022] [Indexed: 01/25/2023] Open
Abstract
In this article we describe the bacterial growth cycle as a closed, self-reproducing, or autopoietic circuit, reestablishing the physiological state of stationary cells initially inoculated in the growth medium. In batch culture, this process of self-reproduction is associated with the gradual decline in available metabolic energy and corresponding change in the physiological state of the population as a function of "travelled distance" along the autopoietic path. We argue that this directional alteration of cell physiology is both reflected in and supported by sequential gene expression along the chromosomal OriC-Ter axis. We propose that during the E. coli growth cycle, the spatiotemporal order of gene expression is established by coupling the temporal gradient of supercoiling energy to the spatial gradient of DNA thermodynamic stability along the chromosomal OriC-Ter axis.
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Affiliation(s)
- Georgi Muskhelishvili
- School of Natural Sciences, Biology Program, Agricultural University of Georgia, 0159 Tbilisi, Georgia
- Correspondence:
| | - Patrick Sobetzko
- Synmikro, Loewe Center for Synthetic Microbiology, Philipps-Universität Marburg, 35043 Marburg, Germany;
| | - Andrew Travers
- MRC Laboratory of Molecular Biology, Cambridge Biomedical Campus, Cambridge CB2 0QH, UK;
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Alert R, Martínez-Calvo A, Datta SS. Cellular Sensing Governs the Stability of Chemotactic Fronts. PHYSICAL REVIEW LETTERS 2022; 128:148101. [PMID: 35476484 DOI: 10.1103/physrevlett.128.148101] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/24/2021] [Accepted: 02/28/2022] [Indexed: 06/14/2023]
Abstract
In contexts ranging from embryonic development to bacterial ecology, cell populations migrate chemotactically along self-generated chemical gradients, often forming a propagating front. Here, we theoretically show that the stability of such chemotactic fronts to morphological perturbations is determined by limitations in the ability of individual cells to sense and thereby respond to the chemical gradient. Specifically, cells at bulging parts of a front are exposed to a smaller gradient, which slows them down and promotes stability, but they also respond more strongly to the gradient, which speeds them up and promotes instability. We predict that this competition leads to chemotactic fingering when sensing is limited at too low chemical concentrations. Guided by this finding and by experimental data on E. coli chemotaxis, we suggest that the cells' sensory machinery might have evolved to avoid these limitations and ensure stable front propagation. Finally, as sensing of any stimuli is necessarily limited in living and active matter in general, the principle of sensing-induced stability may operate in other types of directed migration such as durotaxis, electrotaxis, and phototaxis.
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Affiliation(s)
- Ricard Alert
- Princeton Center for Theoretical Science, Princeton University, Princeton, New Jersey 08544, USA
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey 08544, USA
- Max Planck Institute for the Physics of Complex Systems, Nöthnitzerstraße 38, 01187 Dresden, Germany
- Center for Systems Biology Dresden, Pfotenhauerstraße 108, 01307 Dresden, Germany
| | - Alejandro Martínez-Calvo
- Princeton Center for Theoretical Science, Princeton University, Princeton, New Jersey 08544, USA
- Department of Chemical and Biological Engineering, Princeton University, Princeton, New Jersey 08544, USA
| | - Sujit S Datta
- Department of Chemical and Biological Engineering, Princeton University, Princeton, New Jersey 08544, USA
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Bhattacharjee T, Amchin DB, Alert R, Ott JA, Datta SS. Chemotactic smoothing of collective migration. eLife 2022; 11:e71226. [PMID: 35257660 PMCID: PMC8903832 DOI: 10.7554/elife.71226] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2021] [Accepted: 01/24/2022] [Indexed: 12/24/2022] Open
Abstract
Collective migration-the directed, coordinated motion of many self-propelled agents-is a fascinating emergent behavior exhibited by active matter with functional implications for biological systems. However, how migration can persist when a population is confronted with perturbations is poorly understood. Here, we address this gap in knowledge through studies of bacteria that migrate via directed motion, or chemotaxis, in response to a self-generated nutrient gradient. We find that bacterial populations autonomously smooth out large-scale perturbations in their overall morphology, enabling the cells to continue to migrate together. This smoothing process arises from spatial variations in the ability of cells to sense and respond to the local nutrient gradient-revealing a population-scale consequence of the manner in which individual cells transduce external signals. Altogether, our work provides insights to predict, and potentially control, the collective migration and morphology of cellular populations and diverse other forms of active matter.
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Affiliation(s)
- Tapomoy Bhattacharjee
- The Andlinger Center for Energy and the Environment, Princeton UniversityPrincetonUnited States
| | - Daniel B Amchin
- Department of Chemical and Biological Engineering, Princeton UniversityPrincetonUnited States
| | - Ricard Alert
- Lewis-Sigler Institute for Integrative Genomics, Princeton UniversityPrincetonUnited States
- Princeton Center for Theoretical Science, Princeton UniversityPrincetonUnited States
| | - Jenna Anne Ott
- Department of Chemical and Biological Engineering, Princeton UniversityPrincetonUnited States
| | - Sujit Sankar Datta
- Department of Chemical and Biological Engineering, Princeton UniversityPrincetonUnited States
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