Wadhwa, N. & Berg, H. C. Bacterial motility: machinery and mechanisms. Nat. Rev. Microbiol. 20, 161–173 (2022). This recent review provides an excellent overview of the diversity in bacterial propulsion mechanisms.
Google Scholar
Burrows, L. L. Pseudomonas aeruginosa twitching motility: type IV pili in action. Annu. Rev. Microbiol. 66, 493–520 (2012).
Google Scholar
Dufrêne, Y. F. & Persat, A. Mechanomicrobiology: how bacteria sense and respond to forces. Nat. Rev. Microbiol. 18, 227–240 (2020).
Google Scholar
Jarrell, K. F. & McBride, M. J. The surprisingly diverse ways that prokaryotes move. Nat. Rev. Microbiol. 6, 466–476 (2008).
Google Scholar
Berg, H. C. E. coli in Motion (Springer, 2004).
Bi, S. & Sourjik, V. Stimulus sensing and signal processing in bacterial chemotaxis. Curr. Opin. Microbiol. 45, 22–29 (2018).
Google Scholar
Parkinson, J. S., Hazelbauer, G. L. & Falke, J. J. Signaling and sensory adaptation in Escherichia coli chemoreceptors: 2015 update. Trends Microbiol. 23, 257–266 (2015).
Google Scholar
Porter, S. L., Wadhams, G. H. & Armitage, J. P. Signal processing in complex chemotaxis pathways. Nat. Rev. Microbiol. 9, 153–165 (2011).
Google Scholar
Colin, R. & Sourjik, V. Emergent properties of bacterial chemotaxis pathway. Curr. Opin. Microbiol. 39, 24–33 (2017).
Google Scholar
Brumley, D. R. et al. Cutting through the noise: bacterial chemotaxis in marine microenvironments. Front. Mar. Sci. 7, 527 (2020).
Hein, A. M., Carrara, F., Brumley, D. R., Stocker, R. & Levin, S. A. Natural search algorithms as a bridge between organisms, evolution, and ecology. Proc. Natl Acad. Sci. USA 113, 9413–9420 (2016).
Google Scholar
Wong-Ng, J., Celani, A. & Vergassola, M. Exploring the function of bacterial chemotaxis. Curr. Opin. Microbiol. 45, 16–21 (2018).
Google Scholar
Colin, R., Ni, B., Laganenka, L. & Sourjik, V. Multiple functions of flagellar motility and chemotaxis in bacterial physiology. FEMS Microbiol. Rev. 45, fuab038 (2021).
Google Scholar
Schweinitzer, T. & Josenhans, C. Bacterial energy taxis: a global strategy? Arch. Microbiol. 192, 507–520 (2010).
Google Scholar
Somavanshi, R., Ghosh, B. & Sourjik, V. Sugar influx sensing by the phosphotransferase system of Escherichia coli. PLoS Biol. 14, e2000074 (2016).
Google Scholar
Cremer, J. et al. Chemotaxis as a navigation strategy to boost range expansion. Nature 575, 658–663 (2019). This work uses a quantitative approach to describe the classic assay of bacterial growth and migration in soft agar, and elucidates the distinct roles of attractant and nutrient in colony expansion.
Google Scholar
Raina, J.-B., Fernandez, V., Lambert, B., Stocker, R. & Seymour, J. R. The role of microbial motility and chemotaxis in symbiosis. Nat. Rev. Microbiol. 17, 284–294 (2019). This study presents a comprehensive overview of the role of bacterial motility and chemotaxis in establishing and maintaining symbiotic relationships.
Google Scholar
Matilla, M. A. & Krell, T. The effect of bacterial chemotaxis on host infection and pathogenicity. FEMS Microbiol. Rev. 42, fux052 (2018). This work presents an extensive review of the role of bacterial motility and chemotaxis in host pathogenicity from plants to animals.
Perkins, A., Tudorica, D. A., Amieva, M. R., Remington, S. J. & Guillemin, K. Helicobacter pylori senses bleach (HOCl) as a chemoattractant using a cytosolic chemoreceptor. PLoS Biol. 17, e3000395 (2019).
Google Scholar
Tohidifar, P. et al. The unconventional cytoplasmic sensing mechanism for ethanol chemotaxis in Bacillus subtilis. mBio 11, e02177-20 (2020).
Google Scholar
Kundu, P., Blacher, E., Elinav, E. & Pettersson, S. Our gut microbiome: the evolving inner self. Cell 171, 1481–1493 (2017).
Google Scholar
Azam, F. & Malfatti, F. Microbial structuring of marine ecosystems. Nat. Rev. Microbiol. 5, 782–791 (2007).
Google Scholar
Buchan, A., LeCleir, G. R., Gulvik, C. A. & González, J. M. Master recyclers: features and functions of bacteria associated with phytoplankton blooms. Nat. Rev. Microbiol. 12, 686–698 (2014).
Google Scholar
Savageau, M. A. Escherichia coli habitats, cell types and molecular mechanisms of gene control. Am. Nat. 122, 732–744 (1983).
Google Scholar
Vorholt, J. A. Microbial life in the phyllosphere. Nat. Rev. Microbiol. 10, 828–840 (2012).
Google Scholar
Scharf, B. E., Hynes, M. F. & Alexandre, G. M. Chemotaxis signaling systems in model beneficial plant–bacteria associations. Plant. Mol. Biol. 90, 549–559 (2016).
Google Scholar
Stocker, R. & Seymour, J. R. Ecology and physics of bacterial chemotaxis in the ocean. Microbiol. Mol. Biol. Rev. 76, 792–812 (2012).
Google Scholar
Datta, M. S., Sliwerska, E., Gore, J., Polz, M. F. & Cordero, O. X. Microbial interactions lead to rapid micro-scale successions on model marine particles. Nat. Commun. 7, 11965 (2016).
Google Scholar
Barbara, G. M. & Mitchell, J. G. Bacterial tracking of motile algae. FEMS Microbiol. Ecol. 44, 79–87 (2003).
Google Scholar
Garren, M. et al. A bacterial pathogen uses dimethylsulfoniopropionate as a cue to target heat-stressed corals. ISME J. 8, 999–1007 (2014).
Google Scholar
Szurmant, H. & Ordal, G. W. Diversity in chemotaxis mechanisms among the bacteria and archaea. Microbiol. Mol. Biol. Rev. 68, 301–319 (2004).
Google Scholar
Wuichet, K. & Zhulin, I. B. Origins and diversification of a complex signal transduction system in prokaryotes. Sci. Signal. 3, ra50 (2010).
Google Scholar
Zehr, J. P., Weitz, J. S. & Joint, I. How microbes survive in the open ocean. Science 357, 646–647 (2017).
Google Scholar
McDougald, D., Rice, S. A., Barraud, N., Steinberg, P. D. & Kjelleberg, S. Should we stay or should we go: mechanisms and ecological consequences for biofilm dispersal. Nat. Rev. Microbiol. 10, 39–50 (2012).
Google Scholar
Yawata, Y., Carrara, F., Menolascina, F. & Stocker, R. Constrained optimal foraging by marine bacterioplankton on particulate organic matter. Proc. Natl Acad. Sci. USA 117, 25571–25579 (2020). This study reveals that a marine bacterium foraging on particulate nutrient hotspots optimizes nutrient uptake using rapid switches between chemotactic and non-motile lifestyles.
Google Scholar
Paul, K., Nieto, V., Carlquist, W. C., Blair, D. F. & Harshey, R. M. The c-di-GMP binding protein YcgR controls flagellar motor direction and speed to affect chemotaxis by a “backstop brake” mechanism. Mol. Cell 38, 128–139 (2010).
Google Scholar
Fenchel, T. Microbial behavior in a heterogeneous world. Science 296, 1068–1071 (2002).
Google Scholar
Stocker, R. Marine microbes see a sea of gradients. Science 338, 628–633 (2012).
Google Scholar
McDonald, D. E., Pethick, D. W., Mullan, B. P. & Hampson, D. J. Increasing viscosity of the intestinal contents alters small intestinal structure and intestinal growth, and stimulates proliferation of enterotoxigenic Escherichia coli in newly-weaned pigs. Br. J. Nutr. 86, 487–498 (2001).
Google Scholar
Berg, H. C. & Turner Movement of microorganisms in viscous environments. Nature 278, 349–351 (1979).
Google Scholar
Borer, B., Tecon, R. & Or, D. Spatial organization of bacterial populations in response to oxygen and carbon counter-gradients in pore networks. Nat. Commun. 9, 769 (2018).
Google Scholar
Whitman, W. B., Coleman, D. C. & Wiebe, W. J. Prokaryotes: the unseen majority. Proc. Natl Acad. Sci. USA 95, 6578–6583 (1998).
Google Scholar
Raynaud, X. & Nunan, N. Spatial ecology of bacteria at the microscale in soil. PLoS ONE 9, e87217 (2014).
Google Scholar
Lindow, S. E. & Brandl, M. T. Microbiology of the phyllosphere. Appl. Env. Microbiol. 69, 9 (2003).
Fernandez, V. I., Yawata, Y. & Stocker, R. A foraging mandala for aquatic microorganisms. ISME J. 13, 563–575 (2019).
Google Scholar
Purcell, E. M. Life at low Reynolds number. Am. J. Phys. 45, 10 (1977).
Dusenbery, D. B. Living at Micro Scale: The Unexpected Physics of Being Small (Harvard Univ. Press, 2011).
Phillips, R. & Milo, R. Cell Biology by the Numbers (Garland Science, 2015).
Darnton, N. C., Turner, L., Rojevsky, S. & Berg, H. C. On torque and tumbling in swimming Escherichia coli. J. Bacteriol. 189, 1756–1764 (2007).
Google Scholar
Ryu, W. S., Berry, R. M. & Berg, H. C. Torque-generating units of the flagellar motor of Escherichia coli have a high duty ratio. Nature 403, 444–446 (2000).
Google Scholar
Chattopadhyay, S., Moldovan, R., Yeung, C. & Wu, X. L. Swimming efficiency of bacterium Escherichia coli. Proc. Natl Acad. Sci. USA 103, 13712–13717 (2006).
Google Scholar
Sowa, Y., Hotta, H., Homma, M. & Ishijima, A. Torque–speed relationship of the Na+-driven flagellar motor of Vibrio alginolyticus. J. Mol. Biol. 327, 1043–1051 (2003).
Google Scholar
Taylor, J. R. & Stocker, R. Trade-offs of chemotactic foraging in turbulent water. Science 338, 675–679 (2012).
Google Scholar
Govern, C. C. & ten Wolde, P. R. Optimal resource allocation in cellular sensing systems. Proc. Natl Acad. Sci. USA 111, 17486–17491 (2014).
Google Scholar
Sourjik, V. & Berg, H. C. Binding of the Escherichia coli response regulator CheY to its target measured in vivo by fluorescence resonance energy transfer. Proc. Natl Acad. Sci. USA 99, 12669–12674 (2002).
Google Scholar
Lan, G., Sartori, P., Neumann, S., Sourjik, V. & Tu, Y. The energy–speed–accuracy trade-off in sensory adaptation. Nat. Phys. 8, 422–428 (2012).
Google Scholar
Stouthamer, A. H. & Bettenhaussen, C. W. A continuous culture study of an ATPase-negative mutant of Escherichia coli. Arch. Microbiol. 113, 185–189 (1977).
Google Scholar
Macnab, R. M. in Escherichia coli and Salmonella Typhimurium: Cellular and Molecular Biology Vol. 1 (eds Nerdhardt, F. et al.) 732–759 (American Society for Microbiology, 1987).
Kempes, C. P. et al. Drivers of bacterial maintenance and minimal energy requirements. Front. Microbiol. 8, 31 (2017).
Google Scholar
Lynch, M. & Marinov, G. K. The bioenergetic costs of a gene. Proc. Natl Acad. Sci. USA 112, 15690–15695 (2015).
Google Scholar
Hoehler, T. M. & Jørgensen, B. B. Microbial life under extreme energy limitation. Nat. Rev. Microbiol. 11, 83–94 (2013).
Google Scholar
Boehm, A. et al. Second messenger-mediated adjustment of bacterial swimming velocity. Cell 141, 107–116 (2010).
Google Scholar
Fang, X. & Gomelsky, M. A post-translational, c-di-GMP-dependent mechanism regulating flagellar motility: c-di-GMP-dependent flagellum rotation bias. Mol. Microbiol. 76, 1295–1305 (2010).
Google Scholar
Sathyamoorthy, R. et al. To hunt or to rest: prey depletion induces a novel starvation survival strategy in bacterial predators. ISME J. 15, 109–123 (2020).
Google Scholar
Adler, J. & Templeton, B. The effect of environmental conditions on the motility of Escherichia coli. J. Gen. Microbiol. 46, 175–184 (1967).
Google Scholar
Berg, H. C. & Tedesco, P. M. Transient response to chemotactic stimuli in Escherichia coli. Proc. Natl Acad. Sci. USA 72, 3235–3239 (1975).
Google Scholar
Mitchell, J. G. The influence of cell size on marine bacterial motility and energetics. Microb. Ecol. 22, 227–238 (1991).
Google Scholar
Castro-Sowinski, S., Burdman, S., Matan, O. & Okon, Y. in Plastics from Bacteria Vol. 14 (ed. Chen, G. G.-Q.) 39–61 (Springer, 2010).
Walter, J. M., Greenfield, D., Bustamante, C. & Liphardt, J. Light-powering Escherichia coli with proteorhodopsin. Proc. Natl Acad. Sci. USA 104, 2408–2412 (2007).
Google Scholar
Gude, S. et al. Bacterial coexistence driven by motility and spatial competition. Nature 578, 588–592 (2020). This work presents evidence for a trade-off between motility and growth, which supports bacterial diversity through spatial segregation.
Google Scholar
Ni, B., Colin, R., Link, H., Endres, R. G. & Sourjik, V. Growth-rate dependent resource investment in bacterial motile behavior quantitatively follows potential benefit of chemotaxis. Proc. Natl Acad. Sci. USA 117, 595–601 (2020). This work systematically compares the cost and benefit of chemotaxis in spatially extended and well-mixed environments.
Google Scholar
Li, M. & Hazelbauer, G. L. Cellular stoichiometry of the components of the chemotaxis signaling complex. J. Bacteriol. 186, 3687–3694 (2004).
Google Scholar
Neumann, S., Hansen, C. H., Wingreen, N. S. & Sourjik, V. Differences in signalling by directly and indirectly binding ligands in bacterial chemotaxis. EMBO J. 29, 3484–3495 (2010).
Google Scholar
Akashi, H. & Gojobori, T. Metabolic efficiency and amino acid composition in the proteomes of Escherichia coli and Bacillus subtilis. Proc. Natl Acad. Sci. USA 99, 3695–3700 (2002).
Google Scholar
Basan, M. et al. Overflow metabolism in Escherichia coli results from efficient proteome allocation. Nature 528, 99–104 (2015).
Google Scholar
Ni, B. et al. Evolutionary remodeling of bacterial motility checkpoint control. Cell Rep. 18, 866–877 (2017).
Google Scholar
Fraebel, D. T. et al. Environment determines evolutionary trajectory in a constrained phenotypic space. eLife 6, e24669 (2017).
Google Scholar
Honda, T. et al. Coordination of gene expression with cell size enables Escherichia coli to efficiently maintain motility across conditions. Preprint at bioRxiv https://doi.org/10.1101/2021.05.12.443892 (2021).
Google Scholar
Zampieri, M., Hörl, M., Hotz, F., Müller, N. F. & Sauer, U. Regulatory mechanisms underlying coordination of amino acid and glucose catabolism in Escherichia coli. Nat. Commun. 10, 3354 (2019).
Google Scholar
Zhao, Z. et al. Frequent pauses in Escherichia coli flagella elongation revealed by single cell real-time fluorescence imaging. Nat. Commun. 9, 1885 (2018).
Google Scholar
Zhuang, X. et al. Live‐cell fluorescence imaging reveals dynamic production and loss of bacterial flagella. Mol. Microbiol. 114, 279–291 (2020).
Google Scholar
Chevance, F. F. V. & Hughes, K. T. Coordinating assembly of a bacterial macromolecular machine. Nat. Rev. Microbiol. 6, 455–465 (2008). This work presents a classic overview of the gene regulatory pathway that controls flagella assembly in Gram-negative bacteria.
Google Scholar
Amsler, C. D., Cho, M. & Matsumura, P. Multiple factors underlying the maximum motility of Escherichia coli as cultures enter post-exponential growth. J. Bacteriol. 175, 6238–6244 (1993).
Google Scholar
Lopes, J. G. & Sourjik, V. Chemotaxis of Escherichia coli to major hormones and polyamines present in human gut. ISME J. 12, 2736–2747 (2018).
Google Scholar
Yang, J. et al. Biphasic chemotaxis of Escherichia coli to the microbiota metabolite indole. Proc. Natl Acad. Sci. USA 117, 6114–6120 (2020).
Google Scholar
Matz, C. & Jürgens, K. High motility reduces grazing mortality of planktonic bacteria. Appl. Environ. Microbiol. 71, 921–929 (2005).
Google Scholar
Cummings, L. A., Wilkerson, W. D., Bergsbaken, T. & Cookson, B. T. In vivo, fliC expression by Salmonella enterica serovar Typhimurium is heterogeneous, regulated by ClpX, and anatomically restricted. Mol. Microbiol. 61, 795–809 (2006).
Google Scholar
Yuan, J. & Berg, H. C. Ultrasensitivity of an adaptive bacterial motor. J. Mol. Biol. 425, 1760–1764 (2013).
Google Scholar
Lestas, I., Vinnicombe, G. & Paulsson, J. Fundamental limits on the suppression of molecular fluctuations. Nature 467, 174–178 (2010).
Google Scholar
Frankel, N. W. et al. Adaptability of non-genetic diversity in bacterial chemotaxis. eLife 3, e03526 (2014).
Google Scholar
Goldbeter, A. & Koshland, D. E. An amplified sensitivity arising from covalent modification in biological systems. Proc. Natl Acad. Sci. USA 78, 6840–6844 (1981).
Google Scholar
Waite, A. J. et al. Non‐genetic diversity modulates population performance. Mol. Syst. Biol. 12, 895 (2016).
Google Scholar
Fu, X. et al. Spatial self-organization resolves conflicts between individuality and collective migration. Nat. Commun. 9, 2177 (2018). This sophisticated microfluidic study reveals that a chemotactic population may travel as a cohesive unit despite strong phenotypic heterogeneity within the population.
Google Scholar
Long, Z., Quaife, B., Salman, H. & Oltvai, Z. N. Cell–cell communication enhances bacterial chemotaxis toward external attractants. Sci. Rep. 7, 12855 (2017).
Google Scholar
Laganenka, L., Colin, R. & Sourjik, V. Chemotaxis towards autoinducer 2 mediates autoaggregation in Escherichia coli. Nat. Commun. 7, 12984 (2016). This study demonstrates that bacteria may chase self-generated gradients by producing quorum-sensing molecules.
Google Scholar
Park, S. et al. Influence of topology on bacterial social interaction. Proc. Natl Acad. Sci. USA 100, 13910–13915 (2003).
Google Scholar
Phan, T. V. et al. Bacterial route finding and collective escape in mazes and fractals. Phys. Rev. X 10, 031017 (2020).
Google Scholar
Waite, A. J., Frankel, N. W. & Emonet, T. Behavioral variability and phenotypic diversity in bacterial chemotaxis. Annu. Rev. Biophys. 47, 595–616 (2018). This work presents a review of the mechanisms underlying behavioural variation in bacterial chemotaxis and the consequences for chemotactic performance.
Google Scholar
Ackermann, M. A functional perspective on phenotypic heterogeneity in microorganisms. Nat. Rev. Microbiol. 13, 497–508 (2015).
Google Scholar
Bódi, Z. et al. Phenotypic heterogeneity promotes adaptive evolution. PLoS Biol. 15, e2000644 (2017).
Google Scholar
Seymour, J. R., Amin, S. A., Raina, J.-B. & Stocker, R. Zooming in on the phycosphere: the ecological interface for phytoplankton–bacteria relationships. Nat. Microbiol. 2, 17065 (2017).
Google Scholar
Weber, L., Gonzalez‐Díaz, P., Armenteros, M. & Apprill, A. The coral ecosphere: a unique coral reef habitat that fosters coral–microbial interactions. Limnol. Oceanogr. 64, 2373–2388 (2019).
Google Scholar
Salek, M. M., Carrara, F., Fernandez, V., Guasto, J. S. & Stocker, R. Bacterial chemotaxis in a microfluidic T-maze reveals strong phenotypic heterogeneity in chemotactic sensitivity. Nat. Commun. 10, 1877 (2019).
Google Scholar
Ford, R. M. & Lauffenburger, D. A. Measurement of bacterial random motility and chemotaxis coefficients: II. Application of single-cell-based mathematical model. Biotechnol. Bioeng. 37, 661–672 (1991).
Google Scholar
Lambert, B. S., Fernandez, V. I. & Stocker, R. Motility drives bacterial encounter with particles responsible for carbon export throughout the ocean. Limnol. Oceanogr. Lett. 4, 113–118 (2019).
Słomka, J., Alcolombri, U., Secchi, E., Stocker, R. & Fernandez, V. I. Encounter rates between bacteria and small sinking particles. N. J. Phys. 22, 043016 (2020).
Hein, A. M. & Martin, B. T. Information limitation and the dynamics of coupled ecological systems. Nat. Ecol. Evol. 4, 82–90 (2020).
Google Scholar
Kiorboe, T., Grossart, H.-P., Ploug, H. & Tang, K. Mechanisms and rates of bacterial colonization of sinking aggregates. Appl. Environ. Microbiol. 68, 3996–4006 (2002).
Google Scholar
Viswanathan, G. M. et al. Optimizing the success of random searches. Nature 401, 911–914 (1999).
Google Scholar
Korobkova, E., Emonet, T., Vilar, J. M. G., Shimizu, T. S. & Cluzel, P. From molecular noise to behavioural variability in a single bacterium. Nature 428, 574–578 (2004).
Google Scholar
Tu, Y. & Grinstein, G. How white noise generates power-law switching in bacterial flagellar motors. Phys. Rev. Lett. 4, 208101 (2005).
Huo, H., He, R., Zhang, R. & Yuan, J. Swimming Escherichia coli explore the environment by Lévy walk. Appl. Environ. Microbiol. 87, e02429–20 (2021).
Google Scholar
Keegstra, J. M. et al. Phenotypic diversity and temporal variability in a bacterial signaling network revealed by single-cell FRET. eLife 6, e27455 (2017).
Google Scholar
Colin, R. & Sourjik, V. Multiple sources of slow activity fluctuations in a bacterial chemosensory network. eLife 6, e26796 (2017).
Google Scholar
Karin, O. & Alon, U. Temporal fluctuations in chemotaxis gain implements a simulated tempering strategy for efficient navigation in complex environments. SSRN Electron. J. 24, 102796 (2021).
Google Scholar
Carey, J. N. et al. Regulated stochasticity in a bacterial signaling network permits tolerance to a rapid environmental change. Cell 173, 196–207.e14 (2018).
Google Scholar
Kamino, K., Keegstra, J. M., Long, J., Emonet, T. & Shimizu, T. S. Adaptive tuning of cell sensory diversity without changes in gene expression. Sci. Adv. 6, eabc1087 (2020). This study shows that a bacterial population increases chemotactic bed-hedging when environmental signals are unavailable, but suppresses the sensory diversity when a traceable signal is presented.
Google Scholar
Bassler, B. L. & Losick, R. Bacterially speaking. Cell 125, 237–246 (2006).
Google Scholar
Mukherjee, S. & Bassler, B. L. Bacterial quorum sensing in complex and dynamically changing environments. Nat. Rev. Microbiol. 17, 371–382 (2019).
Google Scholar
Budrene, E. O. & Berg, H. C. Dynamics of formation of symmetrical patterns by chemotactic bacteria. Nature 376, 49–53 (1995).
Google Scholar
Ben-Jacob, E., Cohen, I. & Levine, H. Cooperative self-organization of microorganisms. Adv. Phys. 49, 395–554 (2000).
Google Scholar
Adler, J. Chemotaxis in bacteria. Science 153, 708–716 (1966).
Google Scholar
Keller, E. F. & Segel, L. A. Model for chemotaxis. J. Theor. Biol. 30, 225–234 (1971).
Google Scholar
Saragosti, J. et al. Directional persistence of chemotactic bacteria in a traveling concentration wave. Proc. Natl Acad. Sci. USA 108, 16235–16240 (2011).
Google Scholar
Mattingly & Emonet, T. The balancing act of growth and expansion. Nature 575, 602–603 (2019).
Google Scholar
Liu, W., Cremer, J., Li, D., Hwa, T. & Liu, C. An evolutionarily stable strategy to colonize spatially extended habitats. Nature 575, 664–668 (2019). This study reveals that chemotactic strains selected for different speeds of range expansion in semi-solid agar can stably coexist.
Google Scholar
Hui, S. et al. Quantitative proteomic analysis reveals a simple strategy of global resource allocation in bacteria. Mol. Syst. Biol. 11, 784 (2015).
Google Scholar
Maser, A., Peebo, K., Vilu, R. & Nahku, R. Amino acids are key substrates to Escherichia coli BW25113 for achieving high specific growth rate. Res. Microbiol. 171, 185–193 (2020).
Google Scholar
Yang, Y. et al. Relation between chemotaxis and consumption of amino acids in bacteria. Mol. Microbiol. 96, 1272–1282 (2015). This study is a pioneering work on the relation between chemotaxis and metabolism, where the relationship between amino acid uptake preference and chemotactic affinity in E. coli and B. subtilis is studied.
Google Scholar
Cadotte, M. W. et al. On testing the competition–colonization trade-off in a multispecies assemblage. Am. Nat. 168, 704–709 (2006).
Google Scholar
Amarasekare, P. Competitive coexistence in spatially structured environments: a synthesis. Ecol. Lett. 6, 1109–1122 (2003).
Levins, R. & Culver, D. Regional coexistence of species and competition between rare species. Proc. Natl Acad. Sci. USA 68, 1246–1248 (1971).
Google Scholar
Yawata, Y. et al. Competition–dispersal tradeoff ecologically differentiates recently speciated marine bacterioplankton populations. Proc. Natl Acad. Sci. USA 111, 5622–5627 (2014).
Google Scholar
Narla, A. V., Cremer, J. & Hwa, T. A traveling-wave solution for bacterial chemotaxis with growth. Proc. Natl Acad. Sci. USA 118, e2105138118 (2021). This work develops a comprehensive mathematical framework describing migrating bands of bacteria driven by growth and chemotaxis that is applicable to many environments.
Google Scholar
Bassler, B. L., Gibbons, P. J., Yu, C. & Roseman, S. Chemotaxis to chitin oligosaccharides by Vibrio furnissi. J. Biol. Chem. 266, 24268–24275 (1991).
Google Scholar
Konishi, H., Hio, M., Kobayashi, M., Takase, R. & Hashimoto, W. Bacterial chemotaxis towards polysaccharide pectin by pectin-binding protein. Sci. Rep. 10, 3977 (2020).
Google Scholar
Alcolombri, U. et al. Sinking enhances the degradation of organic particles by marine bacteria. Nat. Geosci. 14, 775–780 (2021).
Google Scholar
D’Souza, G. G., Povolo, V. R., Keegstra, J. M., Stocker, R. & Ackermann, M. Nutrient complexity triggers transitions between solitary and colonial growth in bacterial populations. ISME J. 1, 1 (2021).
Nesper, J. et al. Cyclic di-GMP differentially tunes a bacterial flagellar motor through a novel class of CheY-like regulators. eLife 6, e28842 (2017).
Google Scholar
Basan, M. et al. A universal trade-off between growth and lag in fluctuating environments. Nature 584, 470–474 (2020).
Google Scholar
Nguyen, J. et al. A distinct growth physiology enhances bacterial growth under rapid nutrient fluctuations. Nat. Commun. 12, 3662 (2021).
Google Scholar
Costello, E. K., Stagaman, K., Dethlefsen, L., Bohannan, B. J. M. & Relman, D. A. The application of ecological theory toward an understanding of the human microbiome. Science 336, 1255–1262 (2012).
Google Scholar
Cordero, O. X. & Datta, M. S. Microbial interactions and community assembly at microscales. Curr. Opin. Microbiol. 31, 227–234 (2016).
Google Scholar
Rusconi, R., Garren, M. & Stocker, R. Microfluidics expanding the frontiers of microbial ecology. Annu. Rev. Biophys. 43, 65–91 (2014).
Google Scholar
Lambert, B. S. et al. A microfluidics-based in situ chemotaxis assay to study the behaviour of aquatic microbial communities. Nat. Microbiol. 2, 1344–1349 (2017).
Google Scholar
Clerc, E. E., Raina, J.-B., Lambert, B. S., Seymour, J. & Stocker, R. In situ chemotaxis assay to examine microbial behavior in aquatic ecosystems. J. Vis. Exp. 159, e61062 (2020).
Pleška, M., Jordan, D., Frentz, Z., Xue, B. & Leibler, S. Nongenetic individuality, changeability, and inheritance in bacterial behavior. Proc. Natl Acad. Sci. USA 118, e2023322118 (2021).
Google Scholar
Figueroa-Morales, N. et al. 3D spatial exploration by E. coli echoes motor temporal variability. Phys. Rev. X 10, 021004 (2020).
Google Scholar
Hazelbauer, G. L. Bacterial chemotaxis: the early years of molecular studies. Annu. Rev. Microbiol. 66, 285–303 (2012).
Google Scholar
Adler, J., Hazelbauer, G. L. & Dahl, M. M. Chemotaxis toward sugars in Escherichia coli. J. Bacteriol. 115, 824–847 (1973).
Google Scholar
Mesibov, R. & Adler, J. Chemotaxis toward amino acids in Escherichia coli. J. Bacteriol. 112, 12 (1972).
Dekel, E. & Alon, U. Optimality and evolutionary tuning of the expression level of a protein. Nature 436, 588–592 (2005).
Google Scholar
Erickson, D. W. et al. A global resource allocation strategy governs growth transition kinetics of Escherichia coli. Nature 551, 119–123 (2017).
Google Scholar
Berg, H. C. & Purcell, E. M. Physics of chemoreception. Biophys. J. 20, 193–219 (1977).
Google Scholar
Mora, T. & Wingreen, N. S. Limits of sensing temporal concentration changes by single cells. Phys. Rev. Lett. 104, 248101 (2010).
Google Scholar
Brumley, D. R. et al. Bacteria push the limits of chemotactic precision to navigate dynamic chemical gradients. Proc. Natl Acad. Sci. USA 116, 10792–10797 (2019).
Google Scholar
Mattingly, H. H., Kamino, K., Machta, B. B. & Emonet, T. Escherichia coli chemotaxis is information limited. Nat. Phys. 17, 1426–1431 (2021).
Google Scholar
Clausznitzer, D., Micali, G., Neumann, S., Sourjik, V. & Endres, R. G. Predicting chemical environments of bacteria from receptor signaling. PLoS Comput. Biol. 10, e1003870 (2014).
Google Scholar
Flores, M., Shimizu, T. S., ten Wolde, P. R. & Tostevin, F. Signaling noise enhances chemotactic drift of E. coli. Phys. Rev. Lett. 109, 148101 (2012).
Google Scholar
Okubo, A. & Levin, S. A. Diffusion and Ecological Problems: Modern Perspectives Vol. 14 (Springer, 2001).
Fisher, R. A. The wave of advance of advantageous genes. Ann. Eugen. 7, 355–369 (1937).
Kolmogorov, A., Petrovskii, I. & Piskunov, N. Study of a diffusion equation that is related to the growth of a quality of matter and its application to a biological problem. Mosc. Univ. Math. Bull. 1, 1–26 (1937).
Giometto, A., Rinaldo, A., Carrara, F. & Altermatt, F. Emerging predictable features of replicated biological invasion fronts. Proc. Natl Acad. Sci. USA 111, 297–301 (2014).
Google Scholar
Gandhi, S. R., Yurtsev, E. A., Korolev, K. S. & Gore, J. Range expansions transition from pulled to pushed waves as growth becomes more cooperative in an experimental microbial population. Proc. Natl Acad. Sci. USA 113, 6922–6927 (2016).
Google Scholar
Painter, K. J. Mathematical models for chemotaxis and their applications in self-organisation phenomena. J. Theor. Biol. 481, 162–182 (2019).
Google Scholar
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