Physics and physiology determine strategies of bacterial investment in flagellar motility

Physics and physiology determine strategies of bacterial investment in flagellar motility | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Physics and physiology determine strategies of bacterial investment in flagellar motility Victor Sourjik, Irina Lisevich, Remy Colin, Hao Yuan Yang, Bin Ni This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4044856/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 18 Feb, 2025 Read the published version in Nature Communications → Version 1 posted You are reading this latest preprint version Abstract Regulatory strategies that allow microorganisms to balance their investment of limited resources in different physiological functions remain poorly understood, particularly for numerous cellular functions that are not directly required for growth. Here, we investigate the allocation of resources to flagellar swimming, the most prominent and costly behavior in bacteria that is not directly required for growth. We show that the dependence of motile behavior on gene expression is determined by the hydrodynamics of propulsion, which limits the ability of bacteria to increase their swimming by synthesizing more than a critical number of flagellar filaments. Together with the fitness cost of flagellar biosynthesis, this defines the physiologically relevant range of investment in motility. Gene expression in all E. coli isolates tested falls within this range, with many strains maximizing motility under nutrient-rich conditions, particularly when grown on a porous medium. The hydrodynamics of swimming may further explain the bet-hedging behavior observed at low levels of motility gene expression. Biological sciences/Microbiology/Bacteria/Bacterial systems biology Biological sciences/Microbiology/Bacteria/Bacterial physiology Biological sciences/Biophysics/Motility/Cellular motility Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Microorganisms, like all living systems, must achieve multiple physiological objectives that may change when encountering new environments. To perform successfully, microorganisms have therefore evolved numerous regulatory mechanisms responsible for allocating limited resources to specific physiological functions 1 , 2 . Bacteria, including Escherichia coli have become convenient models to address this fundamental resource allocation problem 3 , with a primary focus on proteome partitioning 4 – 7 . To allocate their proteomic resources into protein biosynthesis as a function of growth rate, bacteria appear to obey linear rules known as growth laws 4 , 5 : the fraction of the proteome responsible for biomass production expands with growth rate, whereas the fraction responsible for nutrient uptake and catabolism decreases with growth rate. This leads to the negative linear relation between the expression of carbon catabolic genes and growth rate, known as the C-line 5 , which has been proposed to maximize growth. However, although growth maximization is an important research allocation strategy 4 – 6 , 8 , it is not always the case 9 , 10 and cells may instead prioritize other targets such as energy yield or stress response 11 , 12 . Furthermore, while previous studies have mostly focused on the optimized expression of catabolic 4 , 5 , 8 , 10 , anabolic 5 , 6 or ribosomal 2 , 5 , 6 genes, microbial strategies for resource allocation to multiple functions not directly required for growth remain unclear 13 . The most prominent example of such a costly physiological function is swimming motility. Motile bacteria are propelled by the rotation of long helical flagellar filaments powered by a motor that is typically proton-driven 14 . Motility enables bacteria to follow spatial gradients of nutrients or harmful chemicals sensed by the chemotaxis signaling pathway 15 , 16 . Motility consumes several percent of total cellular resources in E. coli and other bacteria 17 – 19 , primarily due to the protein budget required for the biosynthesis of flagella 20 , 21 . Consistent with this high cost, several studies have observed a trade-off between growth and motility in E. coli 21 – 24 . However, the exact dependence of this trade-off on the absolute level of resource allocation to swimming motility remains uninvestigated. Interestingly, the flagellar regulon in E. coli is controlled by catabolite repression 25 , such that flagellar gene expression increases in minimal medium during growth on poor carbon sources in accordance with the C-line 7 , 21 . The physiological relevance of such an investment strategy remains debated. One proposed explanation is that it ensures an anticipatory allocation of resources towards motility, in proportion to the potential benefit of finding additional nutrient sources via chemotaxis, which is higher in nutrient-poor environments 21 . Alternatively, it has been suggested that the number of flagella is tuned to match growth rate-dependent changes in cell size 23 . In this study, we quantified the relation between the expression of motility genes and motile behavior, as well as the impact of motility on the growth fitness of E. coli . We demonstrate that major limitations on resource investment in motility, at both high and low levels of gene expression, arise from hydrodynamic constraints on bacterial swimming. Together with the fitness cost of flagellar synthesis and operation, this creates the physiologically relevant range within which the expression level of motility genes can vary depending on the conditions. We observe that within this range, E. coli follows different strategies of resource allocation towards motility depending on the medium, growth rate and isolate. Results Native regulation of motility genes in nutrient-rich medium maximizes swimming while limiting the cost of expression To investigate how motility and growth depend on the expression of flagellar genes, we engineered a derivative of E. coli K-12 strain MG1655 with titratable expression of the flhDC operon that encodes the master activator of the entire flagellar regulon (Fig. 1 a, Supplementary Table 1 and Methods). Expression of the flagellar regulon at different levels of Ptac - flhDC induction was quantified using a fluorescent reporter for flagellin ( fliC gene) promoter activity (P fliC ), which was previously shown to efficiently report the production of flagella in E. coli 20 , 21 , 26 . Reporter activity was measured using either a plate reader to follow changes in in the mean expression over time (Extended Data Fig. 1 a, b), or flow cytometry to determine the distribution of single-cell expression levels within the cell population at a defined time point in mid-exponential phase (Fig. 1 b). We confirmed that both readouts yielded similar results for E. coli cultures grown in nutrient-rich tryptone broth (TB) medium, with native MG1655 (wild-type; MG1655 WT ) expression falling at an intermediate level within the range covered by the inducible Ptac strain (Fig. 1 c and Extended Data Fig. 1 b). To understand how motility changes as a function of gene expression, we characterized swimming behavior in populations of MG1655 WT and Ptac cells using differential dynamic microscopy 27 (see Supplementary Note 1 and Extended Data Fig. 2 ). We observed that population-averaged cell swimming velocity initially increased with expression at low levels of induction, but saturated at high levels of expression (Fig. 1 d). Notably, this saturation occurred around the level of motility gene expression seen in the wild-type strain. A similar pattern was observed when the fraction of well-swimming cells within the population, as determined by our motility assay, and the swimming velocity of only these cells were plotted individually (Extended Data Fig. 1 c, d). The cell swimming velocity at the highest expression level was even slightly reduced (Fig. 1 d and Extended Data Fig. 1 c). Two other derivatives of E. coli K-12, W3110 28 and RP437 (the latter is commonly studied as a wild type for E. coli chemotaxis 29 ), both showed a similar relation between flagellar gene expression and motility, but were slightly less motile than MG1655 WT (Fig. 1 d). The poorer swimming performance of RP437 may be a consequence of its extensive mutagenization 29 , and a previous study showed that the motility of this strain can be improved by experimental evolution 20 . We further investigated the effect of motility on fitness by co-culturing CFP-labeled MG1655 WT or Ptac strains with a non-flagellated YFP-labeled ΔflhC strain. The fitness cost of flagellar regulon activity over a culture passage was determined as the reduction in relative cell number of the tested strain in the co-culture from the initial 50% at inoculation 20 , 21 . This cumulative fitness cost gradually increased with the level of motility genes expression over the entire range of induction tested (Fig. 1 e). Thus, expression of motility genes beyond the native level in E. coli K-12 strains does not appear to provide any additional benefit, but nevertheless imposes an increasing fitness cost. Hydrodynamic constraints limit cell velocity at high levels of flagellar production The saturation of E. coli motility at high levels of flagellar gene expression could be due either to some bottleneck in the biogenesis of functional flagella or to limits in the physical propulsion by multiple flagella. To distinguish between these two possibilities, we first determined how the activity of the flagellar regulon corresponds to changes in flagellation. Staining flagella with an amino-specific fluorescent dye 30 revealed a clear dependence of the number and length of flagella on the expression of the flagellar regulon (Fig. 2 a). The average number of flagellar filaments per cell showed an approximately linear increase with the activity of the P fliC reporter (Fig. 2 b, Extended Data Fig. 3 a). The length of flagellar filaments also showed a moderate increase followed by an apparent saturation (Fig. 2 c, Extended Data Fig. 3 b). These results were consistent with increased amounts of intra- and extracellular flagellin, determined by immunoblotting (Extended Data Fig. 4 ). Thus, E. coli cells can synthesize more flagella at levels of motility gene expression that exceed those of wild-type cells, but this increase does not translate into higher swimming velocity. Alternatively, this saturation of swimming with flagella number could be explained by the physics of E. coli motility. The hydrodynamics of flagella-propelled bacterial swimming is well understood and can be captured by relatively simple mathematical models such as resistive force theory (RFT) 31 , 32 . We therefore used RFT to describe the swimming of a multi-flagellated bacterium, where multiple flagella form a tight bundle that rotates to propel the cell (Supplementary Note 2 and Extended Data Fig. 5a). Based on our experimental measurements (Extended Data Fig. 5b,c), we assume that the flagellar motors operate at a constant speed that does not depend on the number of flagella, which may be the maximum speed of the motor torque-speed relationship. Indeed, the load per motor is low and decreases as the number of flagella increases (Extended Data Fig. 5g), because now multiple motors share the torque generation necessary for bundle rotation and cell propulsion. Our model predicts that swimming velocity should initially increase with motility gene expression and then saturate, in agreement with the experimental data (Fig. 2 d and Extended Data Fig. 5d-f). The initial increase stems from the increase of flagellar length and the increased thickness of the bundle formed by more flagella. Saturation then occurs in the RFT model at high number of filaments because the viscous drag of the cell body becomes negligible compared to the drag of the flagella themselves. As a consequence, any increase in thrust resulting from adding more flagella is offset by an equal increase in viscous drag, since the two have identical dependencies on flagellar length and bundle thickness. Although our model is clearly simplified, in particular, does not capture all the complexity of flagella bundle hydrodynamics 33 , it strongly indicates that the ability of E. coli to increase its swimming velocity by increasing the number and length of flagella is indeed limited by the hydrodynamics and mechanics of flagellar propulsion in viscous media. Motility gene expression follows the potential benefit of chemotaxis under carbon-limited conditions Since expression of the flagellar regulon is under catabolite repression during carbon-limited growth in minimal media, we asked whether this regulation serves to maximize swimming, as observed in nutrient-rich medium, or whether it optimizes an alternative target. Consistent with its C-line-dependent regulation 7 , 21 , 25 , the expression of motility genes in the MG1655 WT strain grown in the minimal medium was much lower in the presence of a good (glucose) than a poor (succinate) carbon source (Fig. 3 a). Expression in the Ptac strain at a given induction was also lower during growth on glucose, but this dependence was weaker, as expected for promoters that are not catabolite repressed 34 . Despite these differences, both swimming velocity (Fig. 3 b) and growth fitness cost (Extended Data Fig. 6) in the Ptac strain showed the same dependence on motility gene expression for both carbon sources. MG1655 WT levels also fit to this curve, but unlike growth in nutrient-rich medium, the native activity of the flagellar regulon clearly does not maximize swimming velocity in this case. Instead, we hypothesized that native gene expression under carbon-limited growth might correlate with the potential benefit that could be achieved in a given carbon source by performing chemotaxis towards sources of additional nutrients, as proposed before 21 . Following this previous study, we measured the benefit of chemotaxis by providing localized sources of amino acids in co-culture between the Ptac strain (labeled with CFP) and its motile but non-chemotactic ΔcheY derivative (labeled with YFP) for different levels of motility gene induction (Extended Data Fig. 7). While the benefit of chemotaxis saturated at high levels of motility gene expression in both carbon sources, saturation occurred at much lower expression in the presence of glucose, with the point of saturation close to the native level of expression in the respective carbon source. Another notable finding was the appearance of two distinct subpopulations, with almost negative and strongly positive expression, at low average levels of reporter activity in the Ptac strain (Fig. 3 a and Extended Data Fig. 8). Interestingly, this separation appeared to be a function of the average reporter activity and did not depend on the carbon source (Fig. 3 a and Fig. 3 c). In this low expression range, the proportion of positive cells in the population increased up to a critical level of expression, after which the distribution became unimodal and it was rather the mean of the positive peak that increased with induction. Motility gene expression in MG1655 WT cells was above the critical level where bimodal behavior becomes apparent, even in culture grown on glucose. To investigate whether native regulation could also exhibit bimodality, we further reduced motility gene expression in wild-type cells by prolonged growth under catabolite repression in glucose, either by using a higher dilution of the TB-grown overnight culture or by pre-growing the overnight culture in glucose (Fig. 3 c, Extended Data Fig. 9a). Indeed, both conditions reduced P fliC activity in the MG1655 WT cell population and revealed a bimodal pattern similar to that observed in the Ptac strain. Bimodality was also observed for a non-induced Ptac strain grown in TB (Fig. 1 c and Fig. 3 c). Thus, bimodality appears to depend solely on the expression level and not on the details of transcriptional regulation of the flhDC operon or on the growth medium. Motility gene expression in E. coli has previously been shown to be pulsatile 26 , 35 and this may be the cause of the observed bimodality. In the closely related species Salmonella enterica , motility genes are also known to exhibit bistable expression 36 . Both bistability (in S. enterica ) and pulsatility (in E. coli ) of expression were attributed to negative regulation of FlhDC activity by YdiV (RflP) 37 , with organism-specific differences in the topology of the YdiV regulatory circuit 35 , 37 . We therefore tested whether regulation by YdiV could be responsible for the emergence of bimodality in our experiments. As expected, the expression level of motility genes in a ΔydiV strain was elevated, and it was above the bimodality threshold in glucose even when the culture was inoculated from TB at a 1:1000 dilution (Fig. 3 c and Extended Data Fig. 9b). However, when the expression level was sufficiently lowered by pre-growth in glucose, two distinct subpopulations could be clearly observed in the ΔydiV strain, suggesting that negative regulation by YdiV is not sufficient to explain the bimodal activation of the P fliC reporter. Activity of the flagellar regulon in natural isolates of E. coli Finally, to investigate how investment in motility varies among E. coli strains that may have adapted to different ecological niches, we used the ECOR collection, which contains 72 isolates from different hosts and geographical regions 38 . From this collection, we first selected 61 strains that were sensitive to kanamycin and thus transformable with the P fliC reporter plasmid, and then discarded 23 non-swimming isolates that did not spread in porous (0.27%) TB agar. From the remaining 38 spreading isolates, a subset of 24 strains with moderate and good spreading abilities was chosen for further investigation (Supplementary Table 2). Although the activity of the P fliC reporter varied widely among the TB-grown ECOR strains, it was consistently below or similar to that of the MG1655 WT strain (Fig. 4 a and Extended Data Fig. 10a), indicating that the investment in motility by natural E. coli isolates is under similar limitation as in the K-12 strains. However, the swimming velocity of the majority of ECOR strains grown in liquid TB medium was lower than that of MG1655 WT and Ptac strains at similar levels of P fliC reporter activity (Fig. 4 a and Extended Data Fig. 10a). Since previous studies showed that the motility of several pathogenic E. coli strains 39 and other bacteria 40 can be activated when cells are grown on a surface or in a porous medium, we measured the ability of ECOR strains to spread in porous 0.27% TB agar. Indeed, the spreading of most ECOR strains, including those that were poorly motile when grown in liquid, was comparable to that of MG1655 WT and Ptac (Fig. 4 b). A possible explanation for this difference could be increased expression of motility genes in cells grown in porous media or on a semi-solid agar surface, where flagella rotate under high load 39 , 41 – 43 . We therefore measured the activity of the P fliC reporter in cultures grown on 0.5% TB agar plates. In this case, expression in individual strains correlated well with their spreading (Extended Data Fig. 10b). While we indeed observed an upregulation of reporter activity in such surface-grown compared to liquid-grown cultures for a few isolates (e.g. ECOR-72), this was not the case for the majority of ECOR strains (Fig. 4 c, Extended Data Fig. 10c and Supplementary Table 2). However, when the motility of cells grown on an agar surface was subsequently analyzed in motility buffer (see Methods for details), the average cell swimming velocity was indeed higher for many ECOR strains compared to liquid-grown cultures, now showing a dependence of swimming velocity on expression similar to the MG1655 WT and Ptac strains (Fig. 4 d, Extended Data Fig. 10d and Supplementary Table 2). Thus, the observed poor motility of many ECOR isolates grown in liquid medium cannot be generally explained by low activity of the flagellar regulon but rather indicates some deficiency in flagellar assembly or function in liquid-grown cell. Notably, however, both motility gene expression and swimming of all ECOR strains were always below or comparable to that of MG1655 WT , further supporting the fundamental nature of limitation imposed on E. coli motility by hydrodynamics. Discussion How microorganisms regulate the allocation of their limited cellular resources under varying environmental conditions remains an open question. Although optimality theory 50 predicts that gene expression levels should have been evolutionarily tuned to maximize an organism’s fitness, such optimization is a multifactorial problem with mostly uncharacterized constraints and trade-offs between conflicting optimization goals. Particularly challenging to understand are microbial strategies for allocating resources to costly functions that do not directly benefit growth or are not used under certain conditions, which can account for up to half of cellular protein resources 13 , 44 , 45 . Here, we investigated resource allocation to flagellar motility, the most prominent of such non-growth related cellular functions in bacteria, by titrating the expression of the flagellar gene regulon and quantifying its impact on E. coli motility. We observed that the biogenesis of the motility apparatus, i.e., the number of flagella and their length, shows a dependence on gene expression over a wide range, demonstrating that E. coli can increase its flagellation beyond the level observed in wild-type strains with the native regulation of gene expression. The effect on growth fitness increases proportionally with resource investment, too, consistent with flagella biosynthesis being the major component of motility costs 20 , 21 . In contrast, cell swimming velocity increases as a function of motility gene expression until the number of flagella reaches ~ 5, but saturates above this level. This dependence of swimming velocity on the number and length of filaments was well captured by a mathematical model describing the swimming of a multi-flagellated bacterium using the resistive force theory, suggesting that the observed saturation of cell velocity is the consequence of hydrodynamic constraints on E. coli motility. Further supporting the general nature of this relation, not only the K-12 strains, but also the majority of motile natural isolates of E. coli mapped to the same unique expression-swimming relation under conditions that favored their motility. Strikingly, although the activity of the flagellar regulon differed among the wild-type E. coli strains tested and between conditions, it was invariably confined to the sub-saturating part of the expression-swimming relation. In a fraction of the strains, including K-12 derivatives and several natural isolates, motility gene expression in the nutrient-rich medium was most likely selected to maximize swimming velocity. This could indicate a high importance of swimming, e.g., for colonization of the environment 19 , 46 . However, even in these strains, expression levels remain bounded by the critical level at which swimming velocity saturates, indicating that cells avoid unnecessary resource expenditures that provide no additional benefit. Expression levels in other E. coli isolates map to different points on the expression-swimming curve, covering the range below saturation of motility. Such heterogeneity could be due to different selection pressures on motility in the ecological niches occupied by these isolates, which is consistent with findings that differences in motility allow coexistence and niche segregation between E. coli strains, both in vitro 25 and in an animal host 47 . While many E. coli strains, including the K-12 derivatives and some natural isolates, swim similarly well when grown in either liquid or porous media, we observed that most natural isolates showed good motility only when grown in porous or semi-solid media, possibly reflecting conditions in the animal gut. The mechanism underlying this effect needs to be further characterized, but it does not seem to be explained by a previously reported mechanosensing-based upregulation of the entire flagellar gene regulon in porous media 39 . Many E. coli isolates swim poorly when grown in liquid despite having comparatively high activity of the flagellar regulon, and only achieve the motility expected based on their gene expression when grown on semi-solid medium. For these isolates, growth in liquid may result in the assembly of poorly functional motors or flagella. A potential mechanism for such flagellar motor remodeling in E. coli could be the previously described recruitment of additional force-generating units under load 41 , 43 , but it remains to be seen whether this recruitment is sufficiently long-lasting to account for these isolates retaining high motility even after transfer to a liquid environment. When grown under carbon limitation, E. coli cells exhibited similar expression-swimming and expression-cost relations in both good and poor carbon sources, despite expected growth-dependent changes in cell size 23 . However, under these conditions, native expression of E. coli motility genes clearly does not maximize swimming. Instead, it correlates well with saturation of the benefit that E. coli could derive from chemotaxis-dependent accumulation to sources of additional nutrients, consistent with the strategy of anticipatory investment in motility 21 . The reduced activity of the flagellar regulon under carbon-limited growth revealed another prominent feature of its regulation in E. coli , namely the appearance of two distinct subpopulations of cells below a certain threshold of average P fliC reporter activity. This bimodality may be related to the recently described pulsatile activation of flagellar genes in E. coli at intermediate expression levels of the master regulator FlhDC 26 , 35 . However, whereas this previous work concluded that pulsatility of expression is caused by the negative regulation of FlhDC by YdiV 26 , this regulation was not sufficient to explain the bimodality in our experiments. Furthermore, based on the established quantitative relation between gene expression and swimming motility, we could speculate on possible physiological reasons for such differentiation into distinct subpopulations. The bimodality of gene expression in microorganisms is commonly interpreted as stochastic bet-hedging behavior, which may be a better strategy in an unpredictable environment than a single adaptive phenotype 48 – 50 . While similar arguments were used to rationalize the differentiation of a bacterial population into motile and non-motile phenotypes 26 , 35 , 36 , here we propose a different, though not mutually exclusive, explanation. We noticed that the bimodality in our experiments occurs at the average expression that is below the level that would correspond to approximately two flagella per cell. Given that swimming with fewer than two flagella becomes inefficient, we argue that the observed bifurcation serves to avoid this “average”, poorly motile phenotype, which is unable to benefit from motility but still pays the fitness cost. Such “enforced” bet hedging may provide an alternative explanation for evolutionarily selected bimodality of gene expression, which is likely to apply not only to bacterial motility, but also to other cases where an intermediate phenotype is less fit than either of the extreme phenotypes. Thus, the hydrodynamics of flagella-mediated motility may not only determine the upper limit of swimming velocity at high levels of motility gene expression, but may also explain its bimodality at low levels of expression. Methods Strains and growth conditions All E. coli strains, including natural isolates from the E. coli Reference Collection (ECOR) 38 and plasmids used in this study are described in Supplementary Tables 1 and 2. The strain with inducer-dependent expression of flhDC operon ( Ptac ) was constructed previously 21 by replacing the native regulatory region of the flhDC operon, including the upstream IS1H insertion element, in the MG1655 Δflu background with the tac promoter inducible by isopropyl β-d-1-thiogalactopyranoside (IPTG). To reduce the basal expression of the flhDC operon, the lacI gene encoding the Lac repressor was additionally inserted upstream of the tac promoter. Deletion of the ydiV gene in MG1655 Δflu and its Ptac derivative was performed by P1 transduction from the KEIO collection 51 followed by curation of the resistance cassette by FLP recombination 52 . Deletion of the flu gene encoding the major E. coli adhesin, antigen 43, in the MG1655 group strains was used to prevent autoaggregation of motile planktonic cells 53 and thus facilitate subsequent characterization of motility 21 . To evaluate the activity of the flagellar regulon, strains were transformed with the plasmid carrying the GFP reporter for fliC promoter (P fliC ) as described previously 21 . For pairwise growth competition experiments, performed as before 21 , the strains were labeled by expression of either cyan or yellow fluorescent proteins (CFP or YFP) from the pTrc99a vector under the control of the IPTG-inducible synthetic P trc promoter 54 . Since pTrc99a carries an extra copy of lacI , which reduces the leaky expression from the genomic P tac promoter and thus the inducibility of expression in the Ptac strain, an empty pTrc99a vector was transformed into Ptac and other E. coli K-12 strains for comparability. E. coli strains were grown in either lysogeny broth (LB; 10 g l − 1 of tryptone, 5 g l − 1 of yeast extract, 5 g l − 1 of NaCl), tryptone broth (TB; 10 g l − 1 of tryptone, 5 g l − 1 of NaCl), and either M9 (5× stock made with 64 g l − 1 of Na 2 HPO 4 -7H 2 O, 15 g l − 1 of KH 2 PO 4 , 2.5 g l − 1 of NaCl, 5.0 g l − 1 of NH 4 Cl, 2 mM MgSO 4 , 0.1 mM CaCl 2 , 1µM FeSO 4 , and 1µM ZnCl 2 ) or Tanaka (34 mM Na 2 HPO 4 , 0.3 mM MgSO 4 , 64 mM KH 2 PO 4 , 10 µM CaCl 2 , 1µM FeSO 4 , and 1µM ZnCl 2 ) 55 minimal media supplemented with 0.4% glucose or 15 mM succinate as the sole carbon source. Ampicillin (100 µg ml − 1 ) and/or kanamycin (100 µg ml − 1 ), and isopropyl β-d-1 thiogalactopyranoside (IPTG) were added to the media when necessary. Reporter activity measurements P fliC reporter activity was measured by either flow cytometry or plate reader assay. Unless otherwise stated, for flow cytometry, overnight cultures grown in TB (37°C, 200 rpm) were diluted 1:100 in 10 ml of the respective target medium. When minimal medium was used, cells were washed three times in medium without carbon source before inoculation. Cultures were incubated at 34°C with shaking (270 rpm) and harvested at mid-exponential phase (OD 600 = 0.4–0.6 for TB or 0.3–0.5 for M9). Cultures were diluted ~ 50-fold in tethering buffer (6.15 mM K 2 HPO 4 , 3.85 mM KH 2 PO 4 , 0.1 mM EDTA, 1 µM methionine, 10 mM sodium lactate, pH 7.0) and fluorescence was detected using a 488 nm laser (100 mW) and a 510/20 nm bandpass filter for GFP on a BD LSRFortessa SORP cell analyzer (BD Biosciences, Germany). 30,000 individual events were analyzed in each experimental run. Gating was first performed on an FSC-A/SSC-A plot and on an SSC-W over SSC-H plot to exclude doublets. Events in the samples with fluorescence intensities higher than the background signal from the MG1655 WT or Ptac strain without the reporter plasmid were considered ‘positive’. The proportion of ‘positive’ events per sample and summary statistics (mean, median fluorescence values) of both the ‘positive’ and the ‘whole’ population were assessed during the measurements using BD FACSDiva™ Software v8.0.1 during measurements. Data were collected in FCS 3.0 file format and analyzed using the flowCore package in R v. 4.2.2. For growth and expression measurements in the BioTek Synergy H1 plate reader, cultures were inoculated into the 96-well plates (Greiner Bio-One) at a dilution of 1:1000 and grown at 34°C with double orbital shaking at a frequency of 548 cycles per minute (CPM) and a shaking amplitude of 2mm for 24 h (TB) or for 48–64 h (M9). GFP fluorescence was quantified using a monochromator-based filter set (excitation 485 nm, emission 530 nm, with a bandpass ≤ 18 nm for detection). Fluorescence and optical density (OD 600 ) were measured every 10 min. For experiments shown in Extended Data Fig. 7, the TECAN Infinite M1000 PRO plate reader was used instead for consistency with the previous study 21 . Reporter activity in ECOR isolates was measured after growth in liquid TB medium or on the surface of semi-solid TB agar (0.5%). For the liquid medium setup, day cultures were prepared in the same manner as for flow cytometry. For the semi-solid condition, 20 µL of the same overnight culture was spread on the surface of TB agar using glass beads. After drying for 15–20 min, the plates were incubated at 34°C for the same time as the strain grew in liquid medium until OD 600 = 0.4–0.6 (i.e., 2.5-4h). Cells were gently washed from the plates with 2 ml of motility buffer (6.15 mM K 2 HPO 4 , 3.85 mM KH 2 PO 4 , 0.1 mM EDTA, 67 mM NaCl, pH 7.0) and adjusted if necessary to final OD 600 = 0.5, and 1 ml of a liquid-grown culture was also washed once in motility buffer. After another washing step, the cells were resuspended in 1 ml motility buffer supplemented with 1% glucose and 0.001% Tween-80. GFP fluorescence was measured in a TECAN Infinite 200 PRO plate reader at 480 nm wavelength, 9 nm bandwidth for excitation and 510 nm wavelength, 20 nm bandwidth for emission. Analysis of swimming velocity and flagella rotation Bacterial cell motility was analyzed as previously described 21 , 56 . Briefly, 1 ml of the same cell culture as prepared for flow cytometry was gently centrifuged (4000 rpm, 5 min), washed twice in motility buffer, and resuspended in 1 ml motility buffer supplemented with 1% glucose and 0.001% Tween-80. 3–5 µL of this cell suspension was introduced into a custom-made chamber between two coverslips, and motility was imaged by phase-contrast video-microscopy (Nikon TI Eclipse, 10x objective with NA = 0.3, Phase 1 ring, CMOS camera EoSens 4CXP), with 10,000 frames being recorded at a rate of 100 frames per second (fps). Motility parameters, in particular the fraction of swimming cells and the swimming velocity of the swimmers, are extracted from the movies using differential dynamic microscopy (DDM) 55 (see Supplementary Note 1). To determine the frequency of flagella rotation, samples were prepared in the same manner as described for swimming velocity analysis. A 10,000-frame movie with a field of view of 512 x 512 px 2 (1 px = 0.7 µm) was acquired far from the sample surfaces under dark field illumination (Nikon TI Eclipse, 10x objective with NA = 0.3, CMOS camera EoSens 4CXP) at a rate of 800 fps. Dark field illumination is obtained by combining an aligned Ph3 condenser ring with the 10x objective on the Nikon TI Eclipse microscope. All data were analyzed using the dark field flicker microscopy (DFFM) method 57 (see Supplementary Note 1) implemented in ImageJ ( https://imagej.nih.gov/ij/ ) with custom-written plugins. Briefly, DFFM uses the flickering that results from changes in the direction in which light is scattered by anisotropic objects as they rotate to measure the rotation speeds of the cell body and flagella. Motility assay in soft agar Motility driven spreading of E. coli in 0.27% TB soft agar was analyzed as previously described 39 . Briefly, 2 µl of overnight cultures grown in TB (37°C, 200 rpm) were transferred to the soft agar plates, and the diameters of the spreading zones were measured after 4–5 h of incubation at 34°C by capturing images with an iPad camera and quantifying the diameter of the spreading zone using ImageJ. Pairwise growth competition Growth competition assays were performed as previously described 21 . Briefly, the overnight cultures of the MG1655 WT or Ptac strain expressing CFP and the ΔflhC strain expressing YFP, grown individually in TB (37°C, 200 rpm), were mixed in a 1:1 ratio to final OD 600 = 0.0025 in 2.5 mL of fresh media and cultured for 24 h (TB) or 48–72 h (M9 minimal medium) at 34°C and 200 rpm. The expression of YFP and CFP was induced with 10 µM IPTG for the co-culture containing the MG1655 WT strain or by the corresponding IPTG concentrations used for induction of the chromosomal Ptac promoter. For the chemotactic benefit assay, differentially labeled non-chemotactic ΔcheY strain and MG1655 WT or Ptac strains were grown in Tanaka minimal medium for 72 h without shaking in the presence of nutrient gradients generated by 40 µLlarge agarose beads (2% agarose) containing 12% casein hydrolysate as described previously 21 . The initial and final proportions of CFP- and YFP-labeled cells were measured by flow cytometry on the BD LSRFortessa SORP cell analyzer (BD Biosciences). The sample was excited with lasers at 447 nm (75 mW), 514 nm (100 mW), and 488 nm (20 mW), with the latter used to identify all cells. CFP and YFP emission signals were detected at 470/15 nm and 542/27 nm, respectively. The fraction of CFP/YFP-‘positive’ events per sample was assessed during the measurements using BD FACSDiva™ Software v8.0.1. Summary statistics were collected in csv file format and analyzed in R v. 4.2.2. Measurements of flagellar length and number For flagella staining, 1 ml of the mid-exponential cell culture grown in TB as described above was centrifuged (3000g, 3 min) and gently washed three times in Buffer A (10 mM KPO 4 buffer, 0.1 mM EDTA dipotassium salt, 67 mM NaCl, 0.001% Tween-80, pH 7.0). The cell pellet was resuspended in 400 µL of Buffer B (same as Buffer A but adjusted to pH 7.8 with NaHCO 3 ), and 8 µl of 10 µg ml − 1 Alexa Fluor 594 succinimidyl ester dye dissolved in DMSO was added to the mixture. Samples were incubated at 30°C in the dark with gentle shaking (100 rpm) for 90 min, washed three times in Buffer A and diluted fivefold in Buffer A. 3–5 µl of cell suspension was applied to a 1% agarose pad (in tethering buffer) and transferred to a 2-well µ-Slide (ibidi, Germany). Fluorescence widefield images were acquired using a Zeiss Elyra 7 inverted microscope with a 63x oil/1.46 oil objective and a further 1.6X magnification. The sample was excited with a 561 nm 500 mW laser (1% power) using a quadruple band dichroic and emission filter. The fluorescence emission of the succinimidyl ester was detected at 595/50 nm interval with a PCO 4.2 Edge sCMOS camera, the exposure time was 100 ms. The number of flagella was quantified for randomly selected 100 cells in multiple fields of view, including both flagellated and non-flagellated cells. The length of flagellar filaments (35–50 filaments per condition) was measured using segmented line tool of ImageJ. Immunoblot analysis of intra- and extracellular flagellin To shear flagellar filaments, a 1 ml aliquot of the mid-exponential cell culture was passed through a 1 ml syringe with the 26G needle 20 times, and centrifuged at 2500 g for 10 min. The supernatant and cell pellet, resuspended in 333 µL of TB medium, were further analyzed by immunoblot. To transfer the samples to the membrane after SDS-PAGE, a PerfectBlue Semi-Dry Electroblotter (Peqlab, VWR, Germany) was used at constant amperage for 1 h (150 mA for 8*6 cm membrane and 1.5 mm thick gel). After transfer, the membrane was stained with Revert™ 700 Total Protein Stain for Western Blot Normalization (LI-COR Biosciences, Germany) and, after blocking,incubated overnight (4°C, orbital shaking) with the primary anti-flagellin antibody (Antikoerper, Germany) diluted 1:10000 followed by the secondary IRDye 800CW anti-rabbit IgG antibody (LI-COR Biosciences, Germany) antibody at a dilution of 1:10000. Fluorescence was measured using an Odyssey Clx Infrared Imaging System (LI-COR Biosciences, Germany) in two channels (700 and 800 nm). Images were analyzed and processed using ImageJ. The model of flagellum-mediated bacterial swimming The model for multiflagellated propulsion extends the classical force balance analysis for uniflagellated propulsion 31 , 58 and accounts for our measurements of swimming speed, cell body rotation speed, and flagellar rotation speed, as well as flagellar length, flagellar number, and cell size. The model is described in detail in Supplementary Note 2. Briefly, we assume that the N flagella form a single tight bundle, described in the framework of resistive force theory 31 , 59 – 61 as a helix of larger thickness for a higher number of flagella, which is justified considering several macroscopic experiments at low Reynolds number with multiple helices 62 , 63 . We account for the increase in both flagellar length and flagellar number with increasing flhDC induction. The cell body is described as a counter-rotating rod 64 , 65 of fixed size, consistently with our observation. The flagellar motor speed is assumed to be constant, in agreement with our measurements of the flagella and cell body rotation speeds. The balance of forces and torques acting on the cell body and the flagellar bundle provides predictions of the swimming speed and the rotation frequencies. Declarations Data and materials availability All data are available in the main text or in Extended Data. All materials are available from the corresponding author upon request. Acknowledgments We thank Julian Pietsch for careful reading of the manuscript. We thank Julian Pietsch and Santiago Kuhl for fruitful discussions. We thank Silvia Gonzalez Sierra and Gabriele Malengo for the technical assistance with flow cytometry and microscopy experiments, and Irina Kalita for the help with flagella labeling. This research was funded by the Max-Planck-Gesellschaft and by the Max Planck School Matter to Life supported by the German Federal Ministry of Education and Research (BMBF). Author contributions I.L., B.N. and V.S. designed the study. I.L., R.C., B.N. and V.S. designed the experiments. I.L., R.C., H.Y., and B.N. performed the experiments. I.L., R.C, and H.Y. analysed the data. I.L., R.C., and V.S. wrote the manuscript. Competing interests Authors declare that they have no competing interests. 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Rotational dynamics of rigid, symmetric top macromolecules. Application to circular cylinders. J. Chem. Phys. 73 , 1986-1993 (2008). Tirado, M.M., Martínez, C.L. & de la Torre, J.G. Comparison of theories for the translational and rotational diffusion coefficients of rod‐like macromolecules. Application to short DNA fragments. J. Chem. Phys. 81 , 2047-2052 (1984). Additional Declarations There is NO Competing Interest. Supplementary Files SupplementarytablesLisevich.xlsx Supplementary Tables 1 and 2 SupplementaryNotesLisevich.docx Supplementary Notes 1 and 2 ExtendedDataFigures.docx Cite Share Download PDF Status: Published Journal Publication published 18 Feb, 2025 Read the published version in Nature Communications → Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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The native regulatory region of the \u003cem\u003eflhDC\u003c/em\u003e operon, including the upstream \u003cem\u003eIS1H\u003c/em\u003e insertion element, was replaced in the \u003cem\u003ePtac\u003c/em\u003e strain with the \u003cem\u003etac \u003c/em\u003epromoter inducible by isopropyl β-d-1-thiogalactopyranoside (IPTG); an additional copy of the \u003cem\u003elacI \u003c/em\u003egene (Lac repressor) was inserted upstream of the \u003cem\u003etac \u003c/em\u003epromoter to reduce the basal expression. \u003cstrong\u003eb,\u003c/strong\u003e Flow cytometry measurement of P\u003csub\u003e\u003cem\u003efliC\u003c/em\u003e\u003c/sub\u003e-GFP reporter activity in mid-exponential cultures of MG1655\u003cem\u003e WT\u003c/em\u003e or its \u003cem\u003ePtac\u003c/em\u003e derivative grown in tryptone broth (TB) medium. Flagellar gene expression in the \u003cem\u003ePtac\u003c/em\u003e strain was induced with the indicated concentrations of IPTG (in µM). Flow cytometry histograms of three biological replicates (\u003cem\u003en =\u003c/em\u003e 3) are shown as violin plots in different hues (AU – arbitrary units). \u003cstrong\u003ec,\u003c/strong\u003e P\u003csub\u003e\u003cem\u003efliC\u003c/em\u003e\u003c/sub\u003e reporter activity determined either as the median GFP intensity at mid-exponential growth phase in flow cytometry (FC) measurements (black symbols) or as the peak of GFP expression normalized by OD\u003csub\u003e600 \u003c/sub\u003ein plate reader (PR) cultures (red symbols). Both data sets were aligned by MG1655 \u003cem\u003eWT\u003c/em\u003e expression (horizontal dashed line). Points are the mean values (\u003cem\u003en \u003c/em\u003e= 3) and error bars are the standard deviations (mean ± s.d.). \u003cstrong\u003ed\u003c/strong\u003e, Dependence of the average cell swimming velocity in cultures of the indicated \u003cem\u003eE. coli\u003c/em\u003e strains on the activity of the P\u003csub\u003e\u003cem\u003efliC\u003c/em\u003e\u003c/sub\u003e reporter as determined by flow cytometry. The average swimming velocity was calculated as the product of the swimming fraction and the swimming velocity of motile cells (see Extended Data Fig. 1c,d for individual values). Motility and reporter expression were determined separately for each replicate culture (indicated by individual symbols). \u003cstrong\u003ee\u003c/strong\u003e, The growth fitness cost of flagellar gene expression. Fitness cost was determined as the percentage of cells (in %) of either the MG1655 \u003cem\u003eWT \u003c/em\u003eor \u003cem\u003ePtac\u003c/em\u003e strain induced by different concentrations of IPTG in co-cultures with the non-flagellated \u003cem\u003eΔflhC\u003c/em\u003e strain after 24 h of growth with shaking (200 rpm) in TB medium. The strains were initially co-inoculated in a 1:1 ratio. P\u003csub\u003e\u003cem\u003efliC \u003c/em\u003e\u003c/sub\u003eactivity measured in the plate reader was used to plot the data; mean ± s.d. (\u003cem\u003en =\u003c/em\u003e 3) is shown for both parameters.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4044856/v1/ffe83f9f68a29afc82d13fdf.png"},{"id":54883456,"identity":"dfdab7d4-9375-4b2b-bc5d-d86d54da465c","added_by":"auto","created_at":"2024-04-18 05:32:12","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":270230,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLimitation of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eE. coli\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e motility at high expression of flagellar genes. a-c\u003c/strong\u003e, Changes in \u003cem\u003eE. coli\u003c/em\u003e flagellation with varying expression of flagellar genes. Fluorescence microscopy images of MG1655 \u003cem\u003eWT\u003c/em\u003e or \u003cem\u003ePtac \u003c/em\u003ecells grown either without (\u003cem\u003ePtac0\u003c/em\u003e) or with 50 μM IPTG (\u003cem\u003ePtac50\u003c/em\u003e), stained with amino-specific fluorescent dye to visualize flagella (\u003cstrong\u003ea\u003c/strong\u003e). Corresponding quantification of the number (\u003cstrong\u003eb\u003c/strong\u003e, \u003cem\u003eN\u003c/em\u003e flagella) and length (\u003cstrong\u003ec\u003c/strong\u003e, in µm) of flagella as a function of P\u003csub\u003e\u003cem\u003efliC\u003c/em\u003e\u003c/sub\u003e activity measured by flow cytometry (FC, \u003cem\u003en\u003c/em\u003e = 3 biological replicates, mean ± s.d.). Data from the same experiments were used to quantify both the number and length of flagella; \u003cem\u003en\u003c/em\u003e = 100 cells from different fields of view (\u003cstrong\u003eb\u003c/strong\u003e) and \u003cem\u003en\u003c/em\u003e = 35-50 flagellar filaments in 10-20 cells (\u003cstrong\u003ec\u003c/strong\u003e). See Extended Data Fig. 3 for value distributions and significance analysis. \u003cstrong\u003ed\u003c/strong\u003e, Dependence of swimming velocity on the number of flagellar filaments, predicted by the RFT physical model of the multi-flagellated microswimmer (see Supplementary Note 2 for details). Our RFT model takes into account that cells with a higher number of flagella also have longer filaments, as observed experimentally.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4044856/v1/18014d32ed38f7d20bd7a921.png"},{"id":54883457,"identity":"d2160102-824b-4178-bbf7-23294fcca3c5","added_by":"auto","created_at":"2024-04-18 05:32:12","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":305435,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMotility of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eE. coli\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e as a function of gene expression in minimal medium.\u003c/strong\u003e \u003cstrong\u003ea\u003c/strong\u003e, Flow cytometry measurements of the P\u003csub\u003e\u003cem\u003efliC\u003c/em\u003e\u003c/sub\u003e-GFP reporter of MG1655 \u003cem\u003eWT\u003c/em\u003e or \u003cem\u003ePtac \u003c/em\u003estrains grown to mid-exponential phase in M9 minimal medium, with either glucose (left) or succinate (right) as the sole carbon source. Labels are as in Fig. 1b. Flow cytometry histograms of three biological replicates are shown as violin plots in different hues (AU – arbitrary units). \u003cstrong\u003eb\u003c/strong\u003e, Dependence of average swimming velocity on the median P\u003csub\u003e\u003cem\u003efliC\u003c/em\u003e\u003c/sub\u003e reporter activity (flow cytometry, FC) for the indicated carbon sources and strains. Each dot represents an independent culture (biological replicate) for which both expression (P\u003csub\u003e\u003cem\u003efliC\u003c/em\u003e\u003c/sub\u003e reporter activity) and swimming were determined. \u003cstrong\u003ec\u003c/strong\u003e, Percentage of GFP-positive cells within the population of the MG1655 \u003cem\u003eWT\u003c/em\u003e, \u003cem\u003ePtac\u003c/em\u003e and \u003cem\u003eΔydiV \u003c/em\u003e(lacks YdiV, the negative regulator of FlhDC; open symbols) strains as a function of median P\u003csub\u003e\u003cem\u003efliC\u003c/em\u003e\u003c/sub\u003e reporter activity, both measured by flow cytometry as in (\u003cstrong\u003ea\u003c/strong\u003e). Each symbol represents an independent culture. The inset describes different conditions used for the starting culture: the overnight culture pre-grown in TB (TB) or M9 glucose (M9+glu) was diluted to the fresh TB or M9 media (1:100 and 1:1000 indicate the dilution).\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-4044856/v1/9eb2c29ed8d5de5434299dee.png"},{"id":54883609,"identity":"e1a90a6a-0bab-4783-9a2b-e36999facf67","added_by":"auto","created_at":"2024-04-18 05:40:12","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":70923,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMotility of natural \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eE. coli\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e isolates. a\u003c/strong\u003e, Relation between flagellar regulon activity and motility for representative ECOR strains (indicated here and throughout by their number in the collection) compared to MG1655 \u003cem\u003eWT\u003c/em\u003e and \u003cem\u003ePtac\u003c/em\u003e strains; corresponding inducer concentrations (IPTG, µM) used for the \u003cem\u003ePtac\u003c/em\u003e strain are indicated by numbers in red. All \u003cem\u003eE. coli\u003c/em\u003e cultures were grown in a liquid TB medium (indicated by L). The same mid-exponential cell culture was used to measure the P\u003csub\u003e\u003cem\u003efliC\u003c/em\u003e\u003c/sub\u003e reporter activity in the plate reader (GFP fluorescence normalized to OD\u003csub\u003e600\u003c/sub\u003e) and average swimming velocity (see Methods for details). Each point represents the mean value for both parameters (\u003cem\u003en\u003c/em\u003e = 3), with error bars indicating the standard deviations. \u003cstrong\u003eb\u003c/strong\u003e, Diameters of spreading zones formed by MG1655 \u003cem\u003eWT\u003c/em\u003e, \u003cem\u003ePtac\u003c/em\u003e and ECOR strains in porous 0.27% TB agar, measured after 4-5 h incubation at 34°C (\u003cem\u003en\u003c/em\u003e = 3; mean ± s.d.). \u003cstrong\u003ec\u003c/strong\u003e, Correlation between P\u003csub\u003e\u003cem\u003efliC\u003c/em\u003e\u003c/sub\u003e reporter activity of in \u003cem\u003eE. coli\u003c/em\u003e strains grown in liquid (L) or semi-solid (indicated by S) medium (0.5% TB agar) (\u003cem\u003en\u003c/em\u003e = 3; mean ± s.d.). \u003cstrong\u003ed\u003c/strong\u003e, Dependence of swimming velocity on\u0026nbsp; P\u003csub\u003e\u003cem\u003efliC\u003c/em\u003e\u003c/sub\u003e activity for ECOR, MG1655 \u003cem\u003eWT\u003c/em\u003e and \u003cem\u003ePtac \u003c/em\u003estrains grown on semi-solid (S) medium (\u003cem\u003en\u003c/em\u003e = 3, mean ± s.d.).\u003cstrong\u003e \u003c/strong\u003eData for other ECOR strains are shown in Extended Data Fig. 10.\u003cstrong\u003e \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-4044856/v1/29b646f9bf5c04eb4b811066.png"},{"id":76640384,"identity":"e12e00e7-4d5e-4a99-a57e-c43da76e4d71","added_by":"auto","created_at":"2025-02-19 08:09:24","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2034850,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4044856/v1/fa041fdc-ac4d-47aa-be83-b9c736de06b6.pdf"},{"id":54883454,"identity":"519db512-3710-428b-a72f-23c653f1e8ed","added_by":"auto","created_at":"2024-04-18 05:32:12","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":18253,"visible":true,"origin":"","legend":"Supplementary Tables 1 and 2","description":"","filename":"SupplementarytablesLisevich.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-4044856/v1/e32df38d9e5d9a3855049da3.xlsx"},{"id":54883607,"identity":"74b168d3-4e36-4272-a7f8-efafd698fe61","added_by":"auto","created_at":"2024-04-18 05:40:12","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":56899,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary Notes 1 and 2\u003c/p\u003e","description":"","filename":"SupplementaryNotesLisevich.docx","url":"https://assets-eu.researchsquare.com/files/rs-4044856/v1/851b67dc5e815f30619846db.docx"},{"id":54883608,"identity":"5a34a0be-adf2-49db-8224-b6884ae8f802","added_by":"auto","created_at":"2024-04-18 05:40:12","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":2254279,"visible":true,"origin":"","legend":"","description":"","filename":"ExtendedDataFigures.docx","url":"https://assets-eu.researchsquare.com/files/rs-4044856/v1/0c495b5d934c3f87d2059909.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Physics and physiology determine strategies of bacterial investment in flagellar motility","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMicroorganisms, like all living systems, must achieve multiple physiological objectives that may change when encountering new environments. To perform successfully, microorganisms have therefore evolved numerous regulatory mechanisms responsible for allocating limited resources to specific physiological functions\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Bacteria, including \u003cem\u003eEscherichia coli\u003c/em\u003e have become convenient models to address this fundamental resource allocation problem\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e, with a primary focus on proteome partitioning\u003csup\u003e\u003cspan additionalcitationids=\"CR5 CR6\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. To allocate their proteomic resources into protein biosynthesis as a function of growth rate, bacteria appear to obey linear rules known as growth laws\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e: the fraction of the proteome responsible for biomass production expands with growth rate, whereas the fraction responsible for nutrient uptake and catabolism decreases with growth rate. This leads to the negative linear relation between the expression of carbon catabolic genes and growth rate, known as the C-line\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e, which has been proposed to maximize growth. However, although growth maximization is an important research allocation strategy\u003csup\u003e\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e, it is not always the case\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e and cells may instead prioritize other targets such as energy yield or stress response\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. Furthermore, while previous studies have mostly focused on the optimized expression of catabolic\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e, anabolic\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e or ribosomal\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e genes, microbial strategies for resource allocation to multiple functions not directly required for growth remain unclear\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe most prominent example of such a costly physiological function is swimming motility. Motile bacteria are propelled by the rotation of long helical flagellar filaments powered by a motor that is typically proton-driven\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. Motility enables bacteria to follow spatial gradients of nutrients or harmful chemicals sensed by the chemotaxis signaling pathway\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. Motility consumes several percent of total cellular resources in \u003cem\u003eE. coli\u003c/em\u003e and other bacteria\u003csup\u003e\u003cspan additionalcitationids=\"CR18\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e, primarily due to the protein budget required for the biosynthesis of flagella\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. Consistent with this high cost, several studies have observed a trade-off between growth and motility in \u003cem\u003eE. coli\u003c/em\u003e\u003csup\u003e\u003cspan additionalcitationids=\"CR22 CR23\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. However, the exact dependence of this trade-off on the absolute level of resource allocation to swimming motility remains uninvestigated.\u003c/p\u003e \u003cp\u003eInterestingly, the flagellar regulon in \u003cem\u003eE. coli\u003c/em\u003e is controlled by catabolite repression\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e, such that flagellar gene expression increases in minimal medium during growth on poor carbon sources in accordance with the C-line\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. The physiological relevance of such an investment strategy remains debated. One proposed explanation is that it ensures an anticipatory allocation of resources towards motility, in proportion to the potential benefit of finding additional nutrient sources via chemotaxis, which is higher in nutrient-poor environments\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. Alternatively, it has been suggested that the number of flagella is tuned to match growth rate-dependent changes in cell size\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn this study, we quantified the relation between the expression of motility genes and motile behavior, as well as the impact of motility on the growth fitness of \u003cem\u003eE. coli\u003c/em\u003e. We demonstrate that major limitations on resource investment in motility, at both high and low levels of gene expression, arise from hydrodynamic constraints on bacterial swimming. Together with the fitness cost of flagellar synthesis and operation, this creates the physiologically relevant range within which the expression level of motility genes can vary depending on the conditions. We observe that within this range, \u003cem\u003eE. coli\u003c/em\u003e follows different strategies of resource allocation towards motility depending on the medium, growth rate and isolate.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e \u003cb\u003eNative regulation of motility genes in nutrient-rich medium maximizes swimming while limiting the cost of expression\u003c/b\u003e \u003c/p\u003e \u003cp\u003eTo investigate how motility and growth depend on the expression of flagellar genes, we engineered a derivative of \u003cem\u003eE. coli\u003c/em\u003e K-12 strain MG1655 with titratable expression of the \u003cem\u003eflhDC\u003c/em\u003e operon that encodes the master activator of the entire flagellar regulon (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea, Supplementary Table\u0026nbsp;1 and Methods). Expression of the flagellar regulon at different levels of \u003cem\u003ePtac\u003c/em\u003e-\u003cem\u003eflhDC\u003c/em\u003e induction was quantified using a fluorescent reporter for flagellin (\u003cem\u003efliC\u003c/em\u003e gene) promoter activity (P\u003csub\u003e\u003cem\u003efliC\u003c/em\u003e\u003c/sub\u003e), which was previously shown to efficiently report the production of flagella in \u003cem\u003eE. coli\u003c/em\u003e\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. Reporter activity was measured using either a plate reader to follow changes in in the mean expression over time (Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea, b), or flow cytometry to determine the distribution of single-cell expression levels within the cell population at a defined time point in mid-exponential phase (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb). We confirmed that both readouts yielded similar results for \u003cem\u003eE. coli\u003c/em\u003e cultures grown in nutrient-rich tryptone broth (TB) medium, with native MG1655 (wild-type; MG1655 \u003cem\u003eWT\u003c/em\u003e) expression falling at an intermediate level within the range covered by the inducible \u003cem\u003ePtac\u003c/em\u003e strain (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec and Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb).\u003c/p\u003e \u003cp\u003eTo understand how motility changes as a function of gene expression, we characterized swimming behavior in populations of MG1655 \u003cem\u003eWT\u003c/em\u003e and \u003cem\u003ePtac\u003c/em\u003e cells using differential dynamic microscopy\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e (see Supplementary Note 1 and Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). We observed that population-averaged cell swimming velocity initially increased with expression at low levels of induction, but saturated at high levels of expression (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ed). Notably, this saturation occurred around the level of motility gene expression seen in the wild-type strain. A similar pattern was observed when the fraction of well-swimming cells within the population, as determined by our motility assay, and the swimming velocity of only these cells were plotted individually (Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec, d). The cell swimming velocity at the highest expression level was even slightly reduced (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ed and Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec). Two other derivatives of \u003cem\u003eE. coli\u003c/em\u003e K-12, W3110\u003csup\u003e28\u003c/sup\u003e and RP437 (the latter is commonly studied as a wild type for \u003cem\u003eE. coli\u003c/em\u003e chemotaxis\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e), both showed a similar relation between flagellar gene expression and motility, but were slightly less motile than MG1655 \u003cem\u003eWT\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ed). The poorer swimming performance of RP437 may be a consequence of its extensive mutagenization\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e, and a previous study showed that the motility of this strain can be improved by experimental evolution\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eWe further investigated the effect of motility on fitness by co-culturing CFP-labeled MG1655 \u003cem\u003eWT\u003c/em\u003e or \u003cem\u003ePtac\u003c/em\u003e strains with a non-flagellated YFP-labeled \u003cem\u003eΔflhC\u003c/em\u003e strain. The fitness cost of flagellar regulon activity over a culture passage was determined as the reduction in relative cell number of the tested strain in the co-culture from the initial 50% at inoculation\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. This cumulative fitness cost gradually increased with the level of motility genes expression over the entire range of induction tested (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ee). Thus, expression of motility genes beyond the native level in \u003cem\u003eE. coli\u003c/em\u003e K-12 strains does not appear to provide any additional benefit, but nevertheless imposes an increasing fitness cost.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eHydrodynamic constraints limit cell velocity at high levels of flagellar production\u003c/h2\u003e \u003cp\u003eThe saturation of \u003cem\u003eE. coli\u003c/em\u003e motility at high levels of flagellar gene expression could be due either to some bottleneck in the biogenesis of functional flagella or to limits in the physical propulsion by multiple flagella. To distinguish between these two possibilities, we first determined how the activity of the flagellar regulon corresponds to changes in flagellation. Staining flagella with an amino-specific fluorescent dye\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e revealed a clear dependence of the number and length of flagella on the expression of the flagellar regulon (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea). The average number of flagellar filaments per cell showed an approximately linear increase with the activity of the P\u003csub\u003e\u003cem\u003efliC\u003c/em\u003e\u003c/sub\u003e reporter (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb, Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea). The length of flagellar filaments also showed a moderate increase followed by an apparent saturation (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec, Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb). These results were consistent with increased amounts of intra- and extracellular flagellin, determined by immunoblotting (Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Thus, \u003cem\u003eE. coli\u003c/em\u003e cells can synthesize more flagella at levels of motility gene expression that exceed those of wild-type cells, but this increase does not translate into higher swimming velocity.\u003c/p\u003e\u003cp\u003eAlternatively, this saturation of swimming with flagella number could be explained by the physics of \u003cem\u003eE. coli\u003c/em\u003e motility. The hydrodynamics of flagella-propelled bacterial swimming is well understood and can be captured by relatively simple mathematical models such as resistive force theory (RFT)\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e,\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. We therefore used RFT to describe the swimming of a multi-flagellated bacterium, where multiple flagella form a tight bundle that rotates to propel the cell (Supplementary Note 2 and Extended Data Fig.\u0026nbsp;5a). Based on our experimental measurements (Extended Data Fig.\u0026nbsp;5b,c), we assume that the flagellar motors operate at a constant speed that does not depend on the number of flagella, which may be the maximum speed of the motor torque-speed relationship. Indeed, the load per motor is low and decreases as the number of flagella increases (Extended Data Fig.\u0026nbsp;5g), because now multiple motors share the torque generation necessary for bundle rotation and cell propulsion. Our model predicts that swimming velocity should initially increase with motility gene expression and then saturate, in agreement with the experimental data (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed and Extended Data Fig.\u0026nbsp;5d-f). The initial increase stems from the increase of flagellar length and the increased thickness of the bundle formed by more flagella. Saturation then occurs in the RFT model at high number of filaments because the viscous drag of the cell body becomes negligible compared to the drag of the flagella themselves. As a consequence, any increase in thrust resulting from adding more flagella is offset by an equal increase in viscous drag, since the two have identical dependencies on flagellar length and bundle thickness. Although our model is clearly simplified, in particular, does not capture all the complexity of flagella bundle hydrodynamics\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e, it strongly indicates that the ability of \u003cem\u003eE. coli\u003c/em\u003e to increase its swimming velocity by increasing the number and length of flagella is indeed limited by the hydrodynamics and mechanics of flagellar propulsion in viscous media.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eMotility gene expression follows the potential benefit of chemotaxis under carbon-limited conditions\u003c/h2\u003e \u003cp\u003eSince expression of the flagellar regulon is under catabolite repression during carbon-limited growth in minimal media, we asked whether this regulation serves to maximize swimming, as observed in nutrient-rich medium, or whether it optimizes an alternative target. Consistent with its C-line-dependent regulation\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e, the expression of motility genes in the MG1655 \u003cem\u003eWT\u003c/em\u003e strain grown in the minimal medium was much lower in the presence of a good (glucose) than a poor (succinate) carbon source (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea). Expression in the \u003cem\u003ePtac\u003c/em\u003e strain at a given induction was also lower during growth on glucose, but this dependence was weaker, as expected for promoters that are not catabolite repressed\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. Despite these differences, both swimming velocity (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb) and growth fitness cost (Extended Data Fig.\u0026nbsp;6) in the \u003cem\u003ePtac\u003c/em\u003e strain showed the same dependence on motility gene expression for both carbon sources. MG1655 \u003cem\u003eWT\u003c/em\u003e levels also fit to this curve, but unlike growth in nutrient-rich medium, the native activity of the flagellar regulon clearly does not maximize swimming velocity in this case.\u003c/p\u003e \u003cp\u003eInstead, we hypothesized that native gene expression under carbon-limited growth might correlate with the potential benefit that could be achieved in a given carbon source by performing chemotaxis towards sources of additional nutrients, as proposed before\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. Following this previous study, we measured the benefit of chemotaxis by providing localized sources of amino acids in co-culture between the \u003cem\u003ePtac\u003c/em\u003e strain (labeled with CFP) and its motile but non-chemotactic \u003cem\u003eΔcheY\u003c/em\u003e derivative (labeled with YFP) for different levels of motility gene induction (Extended Data Fig.\u0026nbsp;7). While the benefit of chemotaxis saturated at high levels of motility gene expression in both carbon sources, saturation occurred at much lower expression in the presence of glucose, with the point of saturation close to the native level of expression in the respective carbon source.\u003c/p\u003e \u003cp\u003eAnother notable finding was the appearance of two distinct subpopulations, with almost negative and strongly positive expression, at low average levels of reporter activity in the \u003cem\u003ePtac\u003c/em\u003e strain (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea and Extended Data Fig.\u0026nbsp;8). Interestingly, this separation appeared to be a function of the average reporter activity and did not depend on the carbon source (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea and Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec). In this low expression range, the proportion of positive cells in the population increased up to a critical level of expression, after which the distribution became unimodal and it was rather the mean of the positive peak that increased with induction. Motility gene expression in MG1655 \u003cem\u003eWT\u003c/em\u003e cells was above the critical level where bimodal behavior becomes apparent, even in culture grown on glucose. To investigate whether native regulation could also exhibit bimodality, we further reduced motility gene expression in wild-type cells by prolonged growth under catabolite repression in glucose, either by using a higher dilution of the TB-grown overnight culture or by pre-growing the overnight culture in glucose (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec, Extended Data Fig.\u0026nbsp;9a). Indeed, both conditions reduced P\u003csub\u003e\u003cem\u003efliC\u003c/em\u003e\u003c/sub\u003e activity in the MG1655 \u003cem\u003eWT\u003c/em\u003e cell population and revealed a bimodal pattern similar to that observed in the \u003cem\u003ePtac\u003c/em\u003e strain. Bimodality was also observed for a non-induced \u003cem\u003ePtac\u003c/em\u003e strain grown in TB (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec and Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec). Thus, bimodality appears to depend solely on the expression level and not on the details of transcriptional regulation of the \u003cem\u003eflhDC\u003c/em\u003e operon or on the growth medium.\u003c/p\u003e \u003cp\u003eMotility gene expression in \u003cem\u003eE. coli\u003c/em\u003e has previously been shown to be pulsatile\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e,\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e and this may be the cause of the observed bimodality. In the closely related species \u003cem\u003eSalmonella enterica\u003c/em\u003e, motility genes are also known to exhibit bistable expression\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. Both bistability (in \u003cem\u003eS. enterica\u003c/em\u003e) and pulsatility (in \u003cem\u003eE. coli\u003c/em\u003e) of expression were attributed to negative regulation of FlhDC activity by YdiV (RflP)\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e, with organism-specific differences in the topology of the YdiV regulatory circuit\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e,\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. We therefore tested whether regulation by YdiV could be responsible for the emergence of bimodality in our experiments. As expected, the expression level of motility genes in a \u003cem\u003eΔydiV\u003c/em\u003e strain was elevated, and it was above the bimodality threshold in glucose even when the culture was inoculated from TB at a 1:1000 dilution (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec and Extended Data Fig.\u0026nbsp;9b). However, when the expression level was sufficiently lowered by pre-growth in glucose, two distinct subpopulations could be clearly observed in the \u003cem\u003eΔydiV\u003c/em\u003e strain, suggesting that negative regulation by YdiV is not sufficient to explain the bimodal activation of the P\u003csub\u003e\u003cem\u003efliC\u003c/em\u003e\u003c/sub\u003e reporter.\u003c/p\u003e \u003cp\u003e \u003cb\u003eActivity of the flagellar regulon in natural isolates of\u003c/b\u003e \u003cb\u003eE. coli\u003c/b\u003e\u003c/p\u003e \u003cp\u003eFinally, to investigate how investment in motility varies among \u003cem\u003eE. coli\u003c/em\u003e strains that may have adapted to different ecological niches, we used the ECOR collection, which contains 72 isolates from different hosts and geographical regions\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e. From this collection, we first selected 61 strains that were sensitive to kanamycin and thus transformable with the P\u003csub\u003e\u003cem\u003efliC\u003c/em\u003e\u003c/sub\u003e reporter plasmid, and then discarded 23 non-swimming isolates that did not spread in porous (0.27%) TB agar. From the remaining 38 spreading isolates, a subset of 24 strains with moderate and good spreading abilities was chosen for further investigation (Supplementary Table\u0026nbsp;2).\u003c/p\u003e \u003cp\u003eAlthough the activity of the P\u003csub\u003e\u003cem\u003efliC\u003c/em\u003e\u003c/sub\u003e reporter varied widely among the TB-grown ECOR strains, it was consistently below or similar to that of the MG1655 \u003cem\u003eWT\u003c/em\u003e strain (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea and Extended Data Fig.\u0026nbsp;10a), indicating that the investment in motility by natural \u003cem\u003eE. coli\u003c/em\u003e isolates is under similar limitation as in the K-12 strains. However, the swimming velocity of the majority of ECOR strains grown in liquid TB medium was lower than that of MG1655 \u003cem\u003eWT\u003c/em\u003e and \u003cem\u003ePtac\u003c/em\u003e strains at similar levels of P\u003csub\u003e\u003cem\u003efliC\u003c/em\u003e\u003c/sub\u003e reporter activity (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea and Extended Data Fig.\u0026nbsp;10a). Since previous studies showed that the motility of several pathogenic \u003cem\u003eE. coli\u003c/em\u003e strains\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e and other bacteria\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e can be activated when cells are grown on a surface or in a porous medium, we measured the ability of ECOR strains to spread in porous 0.27% TB agar. Indeed, the spreading of most ECOR strains, including those that were poorly motile when grown in liquid, was comparable to that of MG1655 \u003cem\u003eWT\u003c/em\u003e and \u003cem\u003ePtac\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb).\u003c/p\u003e \u003cp\u003eA possible explanation for this difference could be increased expression of motility genes in cells grown in porous media or on a semi-solid agar surface, where flagella rotate under high load\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e,\u003cspan additionalcitationids=\"CR42\" citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e. We therefore measured the activity of the P\u003csub\u003e\u003cem\u003efliC\u003c/em\u003e\u003c/sub\u003e reporter in cultures grown on 0.5% TB agar plates. In this case, expression in individual strains correlated well with their spreading (Extended Data Fig.\u0026nbsp;10b). While we indeed observed an upregulation of reporter activity in such surface-grown compared to liquid-grown cultures for a few isolates (e.g. ECOR-72), this was not the case for the majority of ECOR strains (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ec, Extended Data Fig.\u0026nbsp;10c and Supplementary Table\u0026nbsp;2). However, when the motility of cells grown on an agar surface was subsequently analyzed in motility buffer (see Methods for details), the average cell swimming velocity was indeed higher for many ECOR strains compared to liquid-grown cultures, now showing a dependence of swimming velocity on expression similar to the MG1655 \u003cem\u003eWT\u003c/em\u003e and \u003cem\u003ePtac\u003c/em\u003e strains (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ed, Extended Data Fig.\u0026nbsp;10d and Supplementary Table\u0026nbsp;2). Thus, the observed poor motility of many ECOR isolates grown in liquid medium cannot be generally explained by low activity of the flagellar regulon but rather indicates some deficiency in flagellar assembly or function in liquid-grown cell. Notably, however, both motility gene expression and swimming of all ECOR strains were always below or comparable to that of MG1655 \u003cem\u003eWT\u003c/em\u003e, further supporting the fundamental nature of limitation imposed on \u003cem\u003eE. coli\u003c/em\u003e motility by hydrodynamics.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eHow microorganisms regulate the allocation of their limited cellular resources under varying environmental conditions remains an open question. Although optimality theory\u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e predicts that gene expression levels should have been evolutionarily tuned to maximize an organism\u0026rsquo;s fitness, such optimization is a multifactorial problem with mostly uncharacterized constraints and trade-offs between conflicting optimization goals. Particularly challenging to understand are microbial strategies for allocating resources to costly functions that do not directly benefit growth or are not used under certain conditions, which can account for up to half of cellular protein resources\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e,\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eHere, we investigated resource allocation to flagellar motility, the most prominent of such non-growth related cellular functions in bacteria, by titrating the expression of the flagellar gene regulon and quantifying its impact on \u003cem\u003eE. coli\u003c/em\u003e motility. We observed that the biogenesis of the motility apparatus, i.e., the number of flagella and their length, shows a dependence on gene expression over a wide range, demonstrating that \u003cem\u003eE. coli\u003c/em\u003e can increase its flagellation beyond the level observed in wild-type strains with the native regulation of gene expression. The effect on growth fitness increases proportionally with resource investment, too, consistent with flagella biosynthesis being the major component of motility costs\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. In contrast, cell swimming velocity increases as a function of motility gene expression until the number of flagella reaches\u0026thinsp;~\u0026thinsp;5, but saturates above this level. This dependence of swimming velocity on the number and length of filaments was well captured by a mathematical model describing the swimming of a multi-flagellated bacterium using the resistive force theory, suggesting that the observed saturation of cell velocity is the consequence of hydrodynamic constraints on \u003cem\u003eE. coli\u003c/em\u003e motility. Further supporting the general nature of this relation, not only the K-12 strains, but also the majority of motile natural isolates of \u003cem\u003eE. coli\u003c/em\u003e mapped to the same unique expression-swimming relation under conditions that favored their motility.\u003c/p\u003e \u003cp\u003eStrikingly, although the activity of the flagellar regulon differed among the wild-type \u003cem\u003eE. coli\u003c/em\u003e strains tested and between conditions, it was invariably confined to the sub-saturating part of the expression-swimming relation. In a fraction of the strains, including K-12 derivatives and several natural isolates, motility gene expression in the nutrient-rich medium was most likely selected to maximize swimming velocity. This could indicate a high importance of swimming, e.g., for colonization of the environment\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e. However, even in these strains, expression levels remain bounded by the critical level at which swimming velocity saturates, indicating that cells avoid unnecessary resource expenditures that provide no additional benefit. Expression levels in other \u003cem\u003eE. coli\u003c/em\u003e isolates map to different points on the expression-swimming curve, covering the range below saturation of motility. Such heterogeneity could be due to different selection pressures on motility in the ecological niches occupied by these isolates, which is consistent with findings that differences in motility allow coexistence and niche segregation between \u003cem\u003eE. coli\u003c/em\u003e strains, both \u003cem\u003ein vitro\u003c/em\u003e\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e and in an animal host\u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eWhile many \u003cem\u003eE. coli\u003c/em\u003e strains, including the K-12 derivatives and some natural isolates, swim similarly well when grown in either liquid or porous media, we observed that most natural isolates showed good motility only when grown in porous or semi-solid media, possibly reflecting conditions in the animal gut. The mechanism underlying this effect needs to be further characterized, but it does not seem to be explained by a previously reported mechanosensing-based upregulation of the entire flagellar gene regulon in porous media\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. Many \u003cem\u003eE. coli\u003c/em\u003e isolates swim poorly when grown in liquid despite having comparatively high activity of the flagellar regulon, and only achieve the motility expected based on their gene expression when grown on semi-solid medium. For these isolates, growth in liquid may result in the assembly of poorly functional motors or flagella. A potential mechanism for such flagellar motor remodeling in \u003cem\u003eE. coli\u003c/em\u003e could be the previously described recruitment of additional force-generating units under load\u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e,\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e, but it remains to be seen whether this recruitment is sufficiently long-lasting to account for these isolates retaining high motility even after transfer to a liquid environment.\u003c/p\u003e \u003cp\u003eWhen grown under carbon limitation, \u003cem\u003eE. coli\u003c/em\u003e cells exhibited similar expression-swimming and expression-cost relations in both good and poor carbon sources, despite expected growth-dependent changes in cell size\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. However, under these conditions, native expression of \u003cem\u003eE. coli\u003c/em\u003e motility genes clearly does not maximize swimming. Instead, it correlates well with saturation of the benefit that \u003cem\u003eE. coli\u003c/em\u003e could derive from chemotaxis-dependent accumulation to sources of additional nutrients, consistent with the strategy of anticipatory investment in motility\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe reduced activity of the flagellar regulon under carbon-limited growth revealed another prominent feature of its regulation in \u003cem\u003eE. coli\u003c/em\u003e, namely the appearance of two distinct subpopulations of cells below a certain threshold of average P\u003csub\u003e\u003cem\u003efliC\u003c/em\u003e\u003c/sub\u003e reporter activity. This bimodality may be related to the recently described pulsatile activation of flagellar genes in \u003cem\u003eE. coli\u003c/em\u003e at intermediate expression levels of the master regulator FlhDC\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e,\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. However, whereas this previous work concluded that pulsatility of expression is caused by the negative regulation of FlhDC by YdiV\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e, this regulation was not sufficient to explain the bimodality in our experiments. Furthermore, based on the established quantitative relation between gene expression and swimming motility, we could speculate on possible physiological reasons for such differentiation into distinct subpopulations. The bimodality of gene expression in microorganisms is commonly interpreted as stochastic bet-hedging behavior, which may be a better strategy in an unpredictable environment than a single adaptive phenotype\u003csup\u003e\u003cspan additionalcitationids=\"CR49\" citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e. While similar arguments were used to rationalize the differentiation of a bacterial population into motile and non-motile phenotypes\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e,\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e,\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e, here we propose a different, though not mutually exclusive, explanation. We noticed that the bimodality in our experiments occurs at the average expression that is below the level that would correspond to approximately two flagella per cell. Given that swimming with fewer than two flagella becomes inefficient, we argue that the observed bifurcation serves to avoid this \u0026ldquo;average\u0026rdquo;, poorly motile phenotype, which is unable to benefit from motility but still pays the fitness cost. Such \u0026ldquo;enforced\u0026rdquo; bet hedging may provide an alternative explanation for evolutionarily selected bimodality of gene expression, which is likely to apply not only to bacterial motility, but also to other cases where an intermediate phenotype is less fit than either of the extreme phenotypes. Thus, the hydrodynamics of flagella-mediated motility may not only determine the upper limit of swimming velocity at high levels of motility gene expression, but may also explain its bimodality at low levels of expression.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStrains and growth conditions\u003c/h2\u003e \u003cp\u003eAll \u003cem\u003eE. coli\u003c/em\u003e strains, including natural isolates from the \u003cem\u003eE. coli\u003c/em\u003e Reference Collection (ECOR)\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e and plasmids used in this study are described in Supplementary Tables\u0026nbsp;1 and 2. The strain with inducer-dependent expression of \u003cem\u003eflhDC\u003c/em\u003e operon (\u003cem\u003ePtac\u003c/em\u003e) was constructed previously\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e by replacing the native regulatory region of the \u003cem\u003eflhDC\u003c/em\u003e operon, including the upstream \u003cem\u003eIS1H\u003c/em\u003e insertion element, in the MG1655\u003cem\u003eΔflu\u003c/em\u003e background with the \u003cem\u003etac\u003c/em\u003e promoter inducible by isopropyl β-d-1-thiogalactopyranoside (IPTG). To reduce the basal expression of the \u003cem\u003eflhDC\u003c/em\u003e operon, the \u003cem\u003elacI\u003c/em\u003e gene encoding the Lac repressor was additionally inserted upstream of the \u003cem\u003etac\u003c/em\u003e promoter. Deletion of the \u003cem\u003eydiV\u003c/em\u003e gene in MG1655\u003cem\u003eΔflu\u003c/em\u003e and its \u003cem\u003ePtac\u003c/em\u003e derivative was performed by P1 transduction from the KEIO collection\u003csup\u003e\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e followed by curation of the resistance cassette by FLP recombination\u003csup\u003e\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e. Deletion of the \u003cem\u003eflu\u003c/em\u003e gene encoding the major \u003cem\u003eE. coli\u003c/em\u003e adhesin, antigen 43, in the MG1655 group strains was used to prevent autoaggregation of motile planktonic cells\u003csup\u003e\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e and thus facilitate subsequent characterization of motility\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eTo evaluate the activity of the flagellar regulon, strains were transformed with the plasmid carrying the GFP reporter for \u003cem\u003efliC\u003c/em\u003e promoter (P\u003csub\u003e\u003cem\u003efliC\u003c/em\u003e\u003c/sub\u003e) as described previously\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. For pairwise growth competition experiments, performed as before\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e, the strains were labeled by expression of either cyan or yellow fluorescent proteins (CFP or YFP) from the pTrc99a vector under the control of the IPTG-inducible synthetic P\u003csub\u003e\u003cem\u003etrc\u003c/em\u003e\u003c/sub\u003e promoter\u003csup\u003e\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e. Since pTrc99a carries an extra copy of \u003cem\u003elacI\u003c/em\u003e, which reduces the leaky expression from the genomic P\u003csub\u003e\u003cem\u003etac\u003c/em\u003e\u003c/sub\u003e promoter and thus the inducibility of expression in the \u003cem\u003ePtac\u003c/em\u003e strain, an empty pTrc99a vector was transformed into \u003cem\u003ePtac\u003c/em\u003e and other \u003cem\u003eE. coli\u003c/em\u003e K-12 strains for comparability.\u003c/p\u003e \u003cp\u003e \u003cem\u003eE. coli\u003c/em\u003e strains were grown in either lysogeny broth (LB; 10 g l\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e of tryptone, 5 g l\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e of yeast extract, 5 g l\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e of NaCl), tryptone broth (TB; 10 g l\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e of tryptone, 5 g l\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e of NaCl), and either M9 (5\u0026times; stock made with 64 g l\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e of Na\u003csub\u003e2\u003c/sub\u003eHPO\u003csub\u003e4\u003c/sub\u003e-7H\u003csub\u003e2\u003c/sub\u003eO, 15 g l\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e of KH\u003csub\u003e2\u003c/sub\u003ePO\u003csub\u003e4\u003c/sub\u003e, 2.5 g l\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e of NaCl, 5.0 g l\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e of NH\u003csub\u003e4\u003c/sub\u003eCl, 2 mM MgSO\u003csub\u003e4\u003c/sub\u003e, 0.1 mM CaCl\u003csub\u003e2\u003c/sub\u003e, 1\u0026micro;M FeSO\u003csub\u003e4\u003c/sub\u003e, and 1\u0026micro;M ZnCl\u003csub\u003e2\u003c/sub\u003e) or Tanaka (34 mM Na\u003csub\u003e2\u003c/sub\u003eHPO\u003csub\u003e4\u003c/sub\u003e, 0.3 mM MgSO\u003csub\u003e4\u003c/sub\u003e, 64 mM KH\u003csub\u003e2\u003c/sub\u003ePO\u003csub\u003e4\u003c/sub\u003e, 10 \u0026micro;M CaCl\u003csub\u003e2\u003c/sub\u003e, 1\u0026micro;M FeSO\u003csub\u003e4\u003c/sub\u003e, and 1\u0026micro;M ZnCl\u003csub\u003e2\u003c/sub\u003e)\u003csup\u003e\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u003c/sup\u003e minimal media supplemented with 0.4% glucose or 15 mM succinate as the sole carbon source. Ampicillin (100 \u0026micro;g ml\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) and/or kanamycin (100 \u0026micro;g ml\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), and isopropyl β-d-1 thiogalactopyranoside (IPTG) were added to the media when necessary.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eReporter activity measurements\u003c/h2\u003e \u003cp\u003eP\u003csub\u003e\u003cem\u003efliC\u003c/em\u003e\u003c/sub\u003e reporter activity was measured by either flow cytometry or plate reader assay. Unless otherwise stated, for flow cytometry, overnight cultures grown in TB (37\u0026deg;C, 200 rpm) were diluted 1:100 in 10 ml of the respective target medium. When minimal medium was used, cells were washed three times in medium without carbon source before inoculation. Cultures were incubated at 34\u0026deg;C with shaking (270 rpm) and harvested at mid-exponential phase (OD\u003csub\u003e600\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.4\u0026ndash;0.6 for TB or 0.3\u0026ndash;0.5 for M9). Cultures were diluted\u0026thinsp;~\u0026thinsp;50-fold in tethering buffer (6.15 mM K\u003csub\u003e2\u003c/sub\u003eHPO\u003csub\u003e4\u003c/sub\u003e, 3.85 mM KH\u003csub\u003e2\u003c/sub\u003ePO\u003csub\u003e4\u003c/sub\u003e, 0.1 mM EDTA, 1 \u0026micro;M methionine, 10 mM sodium lactate, pH 7.0) and fluorescence was detected using a 488 nm laser (100 mW) and a 510/20 nm bandpass filter for GFP on a BD LSRFortessa SORP cell analyzer (BD Biosciences, Germany). 30,000 individual events were analyzed in each experimental run. Gating was first performed on an FSC-A/SSC-A plot and on an SSC-W over SSC-H plot to exclude doublets. Events in the samples with fluorescence intensities higher than the background signal from the MG1655 \u003cem\u003eWT\u003c/em\u003e or \u003cem\u003ePtac\u003c/em\u003e strain without the reporter plasmid were considered \u0026lsquo;positive\u0026rsquo;. The proportion of \u0026lsquo;positive\u0026rsquo; events per sample and summary statistics (mean, median fluorescence values) of both the \u0026lsquo;positive\u0026rsquo; and the \u0026lsquo;whole\u0026rsquo; population were assessed during the measurements using BD FACSDiva\u0026trade; Software v8.0.1 during measurements. Data were collected in FCS 3.0 file format and analyzed using the flowCore package in R v. 4.2.2.\u003c/p\u003e \u003cp\u003eFor growth and expression measurements in the BioTek Synergy H1 plate reader, cultures were inoculated into the 96-well plates (Greiner Bio-One) at a dilution of 1:1000 and grown at 34\u0026deg;C with double orbital shaking at a frequency of 548 cycles per minute (CPM) and a shaking amplitude of 2mm for 24 h (TB) or for 48\u0026ndash;64 h (M9). GFP fluorescence was quantified using a monochromator-based filter set (excitation 485 nm, emission 530 nm, with a bandpass\u0026thinsp;\u0026le;\u0026thinsp;18 nm for detection). Fluorescence and optical density (OD\u003csub\u003e600\u003c/sub\u003e) were measured every 10 min. For experiments shown in Extended Data Fig.\u0026nbsp;7, the TECAN Infinite M1000 PRO plate reader was used instead for consistency with the previous study\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eReporter activity in ECOR isolates was measured after growth in liquid TB medium or on the surface of semi-solid TB agar (0.5%). For the liquid medium setup, day cultures were prepared in the same manner as for flow cytometry. For the semi-solid condition, 20 \u0026micro;L of the same overnight culture was spread on the surface of TB agar using glass beads. After drying for 15\u0026ndash;20 min, the plates were incubated at 34\u0026deg;C for the same time as the strain grew in liquid medium until OD\u003csub\u003e600\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.4\u0026ndash;0.6 (i.e., 2.5-4h). Cells were gently washed from the plates with 2 ml of motility buffer (6.15 mM K\u003csub\u003e2\u003c/sub\u003eHPO\u003csub\u003e4\u003c/sub\u003e, 3.85 mM KH\u003csub\u003e2\u003c/sub\u003ePO\u003csub\u003e4\u003c/sub\u003e, 0.1 mM EDTA, 67 mM NaCl, pH 7.0) and adjusted if necessary to final OD\u003csub\u003e600\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.5, and 1 ml of a liquid-grown culture was also washed once in motility buffer. After another washing step, the cells were resuspended in 1 ml motility buffer supplemented with 1% glucose and 0.001% Tween-80. GFP fluorescence was measured in a TECAN Infinite 200 PRO plate reader at 480 nm wavelength, 9 nm bandwidth for excitation and 510 nm wavelength, 20 nm bandwidth for emission.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eAnalysis of swimming velocity and flagella rotation\u003c/h2\u003e \u003cp\u003eBacterial cell motility was analyzed as previously described\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u003c/sup\u003e. Briefly, 1 ml of the same cell culture as prepared for flow cytometry was gently centrifuged (4000 rpm, 5 min), washed twice in motility buffer, and resuspended in 1 ml motility buffer supplemented with 1% glucose and 0.001% Tween-80. 3\u0026ndash;5 \u0026micro;L of this cell suspension was introduced into a custom-made chamber between two coverslips, and motility was imaged by phase-contrast video-microscopy (Nikon TI Eclipse, 10x objective with NA\u0026thinsp;=\u0026thinsp;0.3, Phase 1 ring, CMOS camera EoSens 4CXP), with 10,000 frames being recorded at a rate of 100 frames per second (fps). Motility parameters, in particular the fraction of swimming cells and the swimming velocity of the swimmers, are extracted from the movies using differential dynamic microscopy (DDM)\u003csup\u003e\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u003c/sup\u003e (see Supplementary Note 1).\u003c/p\u003e \u003cp\u003eTo determine the frequency of flagella rotation, samples were prepared in the same manner as described for swimming velocity analysis. A 10,000-frame movie with a field of view of 512 x 512 px\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e (1 px\u0026thinsp;=\u0026thinsp;0.7 \u0026micro;m) was acquired far from the sample surfaces under dark field illumination (Nikon TI Eclipse, 10x objective with NA\u0026thinsp;=\u0026thinsp;0.3, CMOS camera EoSens 4CXP) at a rate of 800 fps. Dark field illumination is obtained by combining an aligned Ph3 condenser ring with the 10x objective on the Nikon TI Eclipse microscope. All data were analyzed using the dark field flicker microscopy (DFFM) method\u003csup\u003e\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e (see Supplementary Note 1) implemented in ImageJ (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://imagej.nih.gov/ij/\u003c/span\u003e\u003cspan address=\"https://imagej.nih.gov/ij/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) with custom-written plugins. Briefly, DFFM uses the flickering that results from changes in the direction in which light is scattered by anisotropic objects as they rotate to measure the rotation speeds of the cell body and flagella.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eMotility assay in soft agar\u003c/h2\u003e \u003cp\u003eMotility driven spreading of \u003cem\u003eE. coli\u003c/em\u003e in 0.27% TB soft agar was analyzed as previously described\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. Briefly, 2 \u0026micro;l of overnight cultures grown in TB (37\u0026deg;C, 200 rpm) were transferred to the soft agar plates, and the diameters of the spreading zones were measured after 4\u0026ndash;5 h of incubation at 34\u0026deg;C by capturing images with an iPad camera and quantifying the diameter of the spreading zone using ImageJ.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003ePairwise growth competition\u003c/h2\u003e \u003cp\u003eGrowth competition assays were performed as previously described\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. Briefly, the overnight cultures of the MG1655 \u003cem\u003eWT\u003c/em\u003e or \u003cem\u003ePtac\u003c/em\u003e strain expressing CFP and the \u003cem\u003eΔflhC\u003c/em\u003e strain expressing YFP, grown individually in TB (37\u0026deg;C, 200 rpm), were mixed in a 1:1 ratio to final OD\u003csub\u003e600\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.0025 in 2.5 mL of fresh media and cultured for 24 h (TB) or 48\u0026ndash;72 h (M9 minimal medium) at 34\u0026deg;C and 200 rpm. The expression of YFP and CFP was induced with 10 \u0026micro;M IPTG for the co-culture containing the MG1655 \u003cem\u003eWT\u003c/em\u003e strain or by the corresponding IPTG concentrations used for induction of the chromosomal \u003cem\u003ePtac\u003c/em\u003e promoter. For the chemotactic benefit assay, differentially labeled non-chemotactic \u003cem\u003eΔcheY\u003c/em\u003e strain and MG1655 \u003cem\u003eWT\u003c/em\u003e or \u003cem\u003ePtac\u003c/em\u003e strains were grown in Tanaka minimal medium for 72 h without shaking in the presence of nutrient gradients generated by 40 \u0026micro;Llarge agarose beads (2% agarose) containing 12% casein hydrolysate as described previously\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. The initial and final proportions of CFP- and YFP-labeled cells were measured by flow cytometry on the BD LSRFortessa SORP cell analyzer (BD Biosciences). The sample was excited with lasers at 447 nm (75 mW), 514 nm (100 mW), and 488 nm (20 mW), with the latter used to identify all cells. CFP and YFP emission signals were detected at 470/15 nm and 542/27 nm, respectively. The fraction of CFP/YFP-\u0026lsquo;positive\u0026rsquo; events per sample was assessed during the measurements using BD FACSDiva\u0026trade; Software v8.0.1. Summary statistics were collected in csv file format and analyzed in R v. 4.2.2.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eMeasurements of flagellar length and number\u003c/h2\u003e \u003cp\u003eFor flagella staining, 1 ml of the mid-exponential cell culture grown in TB as described above was centrifuged (3000g, 3 min) and gently washed three times in Buffer A (10 mM KPO\u003csub\u003e4\u003c/sub\u003e buffer, 0.1 mM EDTA dipotassium salt, 67 mM NaCl, 0.001% Tween-80, pH 7.0). The cell pellet was resuspended in 400 \u0026micro;L of Buffer B (same as Buffer A but adjusted to pH 7.8 with NaHCO\u003csub\u003e3\u003c/sub\u003e), and 8 \u0026micro;l of 10 \u0026micro;g ml\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e Alexa Fluor 594 succinimidyl ester dye dissolved in DMSO was added to the mixture. Samples were incubated at 30\u0026deg;C in the dark with gentle shaking (100 rpm) for 90 min, washed three times in Buffer A and diluted fivefold in Buffer A. 3\u0026ndash;5 \u0026micro;l of cell suspension was applied to a 1% agarose pad (in tethering buffer) and transferred to a 2-well \u0026micro;-Slide (ibidi, Germany).\u003c/p\u003e \u003cp\u003eFluorescence widefield images were acquired using a Zeiss Elyra 7 inverted microscope with a 63x oil/1.46 oil objective and a further 1.6X magnification. The sample was excited with a 561 nm 500 mW laser (1% power) using a quadruple band dichroic and emission filter. The fluorescence emission of the succinimidyl ester was detected at 595/50 nm interval with a PCO 4.2 Edge sCMOS camera, the exposure time was 100 ms. The number of flagella was quantified for randomly selected 100 cells in multiple fields of view, including both flagellated and non-flagellated cells. The length of flagellar filaments (35\u0026ndash;50 filaments per condition) was measured using segmented line tool of ImageJ.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eImmunoblot analysis of intra- and extracellular flagellin\u003c/h2\u003e \u003cp\u003eTo shear flagellar filaments, a 1 ml aliquot of the mid-exponential cell culture was passed through a 1 ml syringe with the 26G needle 20 times, and centrifuged at 2500 g for 10 min. The supernatant and cell pellet, resuspended in 333 \u0026micro;L of TB medium, were further analyzed by immunoblot. To transfer the samples to the membrane after SDS-PAGE, a PerfectBlue Semi-Dry Electroblotter (Peqlab, VWR, Germany) was used at constant amperage for 1 h (150 mA for 8*6 cm membrane and 1.5 mm thick gel). After transfer, the membrane was stained with Revert\u0026trade; 700 Total Protein Stain for Western Blot Normalization (LI-COR Biosciences, Germany) and, after blocking,incubated overnight (4\u0026deg;C, orbital shaking) with the primary anti-flagellin antibody (Antikoerper, Germany) diluted 1:10000 followed by the secondary IRDye 800CW anti-rabbit IgG antibody (LI-COR Biosciences, Germany) antibody at a dilution of 1:10000. Fluorescence was measured using an Odyssey Clx Infrared Imaging System (LI-COR Biosciences, Germany) in two channels (700 and 800 nm). Images were analyzed and processed using ImageJ.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eThe model of flagellum-mediated bacterial swimming\u003c/h2\u003e \u003cp\u003eThe model for multiflagellated propulsion extends the classical force balance analysis for uniflagellated propulsion\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e,\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e and accounts for our measurements of swimming speed, cell body rotation speed, and flagellar rotation speed, as well as flagellar length, flagellar number, and cell size. The model is described in detail in Supplementary Note 2. Briefly, we assume that the \u003cem\u003eN\u003c/em\u003e flagella form a single tight bundle, described in the framework of resistive force theory\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e,\u003cspan additionalcitationids=\"CR60\" citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e\u003c/sup\u003e as a helix of larger thickness for a higher number of flagella, which is justified considering several macroscopic experiments at low Reynolds number with multiple helices\u003csup\u003e\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e,\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e\u003c/sup\u003e. We account for the increase in both flagellar length and flagellar number with increasing \u003cem\u003eflhDC\u003c/em\u003e induction. The cell body is described as a counter-rotating rod\u003csup\u003e\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e,\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e\u003c/sup\u003e of fixed size, consistently with our observation. The flagellar motor speed is assumed to be constant, in agreement with our measurements of the flagella and cell body rotation speeds. The balance of forces and torques acting on the cell body and the flagellar bundle provides predictions of the swimming speed and the rotation frequencies.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData and materials availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data are available in the main text or in Extended Data. All materials are available from the corresponding author upon request.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank Julian Pietsch for careful reading of the manuscript. We thank Julian Pietsch and Santiago Kuhl for fruitful discussions. We thank Silvia Gonzalez Sierra and Gabriele Malengo for the technical assistance with flow cytometry and microscopy experiments, and Irina Kalita for the help with flagella labeling. This research was funded by the Max-Planck-Gesellschaft and by the Max Planck School Matter to Life supported by the German Federal Ministry of Education and Research (BMBF). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eI.L., B.N. and V.S. designed the study. I.L., R.C., B.N. and V.S. designed the experiments. \u0026nbsp;I.L., R.C., H.Y., and B.N. performed the experiments. I.L., R.C, and H.Y. analysed the data. I.L., R.C., and V.S. wrote the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAuthors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMaterials \u0026amp; Correspondence\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCorrespondence and requests for materials should be addressed to\u0026nbsp;Victor Sourjik\u003cstrong\u003e\u0026nbsp;(\u003c/strong\[email protected]).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eMolenaar, D., van Berlo, R., de Ridder, D. \u0026amp; Teusink, B. Shifts in growth strategies reflect tradeoffs in cellular economics. \u003cem\u003eMol. Syst. Biol.\u003c/em\u003e \u003cstrong\u003e5\u003c/strong\u003e, 323 (2009).\u003c/li\u003e\n \u003cli\u003eBasan, M. 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Phys.\u003c/em\u003e \u003cstrong\u003e81\u003c/strong\u003e, 2047-2052 (1984).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-4044856/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4044856/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eRegulatory strategies that allow microorganisms to balance their investment of limited resources in different physiological functions remain poorly understood, particularly for numerous cellular functions that are not directly required for growth. Here, we investigate the allocation of resources to flagellar swimming, the most prominent and costly behavior in bacteria that is not directly required for growth. We show that the dependence of motile behavior on gene expression is determined by the hydrodynamics of propulsion, which limits the ability of bacteria to increase their swimming by synthesizing more than a critical number of flagellar filaments. Together with the fitness cost of flagellar biosynthesis, this defines the physiologically relevant range of investment in motility. Gene expression in all \u003cem\u003eE. coli\u003c/em\u003e isolates tested falls within this range, with many strains maximizing motility under nutrient-rich conditions, particularly when grown on a porous medium. The hydrodynamics of swimming may further explain the bet-hedging behavior observed at low levels of motility gene expression.\u003c/p\u003e","manuscriptTitle":"Physics and physiology determine strategies of bacterial investment in flagellar motility","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-18 05:32:07","doi":"10.21203/rs.3.rs-4044856/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"nature-communications","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"NCOMMS","sideBox":"Learn more about [Nature Communications](http://www.nature.com/ncomms/)","snPcode":"","submissionUrl":"https://mts-ncomms.nature.com/","title":"Nature Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature Communications","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"e6509cb5-d8e6-4d91-a15c-a9209d7b7b92","owner":[],"postedDate":"April 18th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":29688206,"name":"Biological sciences/Microbiology/Bacteria/Bacterial systems biology"},{"id":29688207,"name":"Biological sciences/Microbiology/Bacteria/Bacterial physiology"},{"id":29688208,"name":"Biological sciences/Biophysics/Motility/Cellular motility"}],"tags":[],"updatedAt":"2025-02-19T08:08:55+00:00","versionOfRecord":{"articleIdentity":"rs-4044856","link":"https://doi.org/10.1038/s41467-025-56980-x","journal":{"identity":"nature-communications","isVorOnly":false,"title":"Nature Communications"},"publishedOn":"2025-02-18 05:00:00","publishedOnDateReadable":"February 18th, 2025"},"versionCreatedAt":"2024-04-18 05:32:07","video":"","vorDoi":"10.1038/s41467-025-56980-x","vorDoiUrl":"https://doi.org/10.1038/s41467-025-56980-x","workflowStages":[]},"version":"v1","identity":"rs-4044856","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4044856","identity":"rs-4044856","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}