Morphogenesis of bacterial colonies in polymeric environments

Many bacteria live in polymeric fluids, such as mucus, environmental polysaccharides, and extracellular polymers in biofilms. However, lab studies typically focus on cells in polymer-free fluids. Here, we show that interactions with polymers shape a fundamental feature of bacterial life-how they proliferate in space in multicellular colonies. Using experiments, we find that when polymer is sufficiently concentrated, cells generically and reversibly form large serpentine "cables" as they proliferate. By combining experiments with biophysical theory and simulations, we demonstrate that this distinctive form of colony morphogenesis arises from an interplay between polymer-induced entropic attraction between neighboring cells and their hindered ability to diffusely separate from each other in a viscous polymer solution. Our work thus reveals a pivotal role of polymers in sculpting proliferating bacterial colonies, with implications for how they interact with hosts and with the natural environment, and uncovers quantitative principles governing colony morphogenesis in such complex environments.

Interfacial exchange dynamics of biomolecular condensates are highly sensitive to client interactions

Phase separation of biomolecules can facilitate their spatiotemporally regulated self-assembly within living cells. Due to the selective yet dynamic exchange of biomolecules across condensate interfaces, condensates can function as reactive hubs by concentrating enzymatic components for faster kinetics. The principles governing this dynamic exchange between condensate phases, however, are poorly understood. In this work, we systematically investigate the influence of client-sticker interactions on the exchange dynamics of protein molecules across condensate interfaces. We show that increasing affinity between a model protein scaffold and its client molecules causes the exchange of protein chains between the dilute and dense phases to slow down and that beyond a threshold interaction strength, this slowdown in exchange becomes substantial. Investigating the impact of interaction symmetry, we found that chain exchange dynamics are also considerably slower when client molecules interact equally with different sticky residues in the protein. The slowdown of exchange is due to a sequestration effect, by which there are fewer unbound stickers available at the interface to which dilute phase chains may attach. These findings highlight the fundamental connection between client-scaffold interaction networks and condensate exchange dynamics.

The value of information gathering in phage-bacteria warfare

Phages-viruses that infect bacteria-have evolved over billions of years to overcome bacterial defenses. Temperate phage, upon infection, can "choose" between two pathways: lysis-in which the phage create multiple new phage particles, which are then liberated by cell lysis, and lysogeny-where the phage's genetic material is added to the bacterial DNA and transmitted to the bacterial progeny. It was recently discovered that some phages can read information from the environment related to the density of bacteria or the number of nearby infection attempts. Such information may help phage make the right choice between the two pathways. Here, we develop a theoretical model that allows an infecting phage to change its strategy (i.e. the ratio of lysis to lysogeny) depending on an outside signal, and we find the optimal strategy that maximizes phage proliferation. While phages that exploit extra information naturally win in competition against phages with a fixed strategy, there may be costs to information, e.g. as the necessary extra genes may affect the growth rate of a lysogen or the burst size of new phage for the lysis pathway. Surprisingly, even when phages pay a large price for information, they can still maintain an advantage over phages that lack this information, indicating the high benefit of intelligence gathering in phage-bacteria warfare.

Interfacial morphodynamics of proliferating microbial communities

In microbial communities, various cell types often coexist by occupying distinct spatial domains. What determines the shape of the interface between such domains-which in turn influences the interactions between cells and overall community function? Here, we address this question by developing a continuum model of a 2D spatially-structured microbial community with two distinct cell types. We find that, depending on the balance of the different cell proliferation rates and substrate friction coefficients, the interface between domains is either stable and smooth, or unstable and develops finger-like protrusions. We establish quantitative principles describing when these different interfacial behaviors arise, and find good agreement both with the results of previous experimental reports as well as new experiments performed here. Our work thus helps to provide a biophysical basis for understanding the interfacial morphodynamics of proliferating microbial communities, as well as a broader range of proliferating active systems.

Erratum: Mechanical Frustration of Phase Separation in the Cell Nucleus by Chromatin [Phys. Rev. Lett. 126, 258102 (2021)]

This corrects the article DOI: 10.1103/PhysRevLett.126.258102.

Single-cell massively-parallel multiplexed microbial sequencing (M3-seq) identifies rare bacterial populations and profiles phage infection

Bacterial populations are highly adaptive. They can respond to stress and survive in shifting environments. How the behaviours of individual bacteria vary during stress, however, is poorly understood. To identify and characterize rare bacterial subpopulations, technologies for single-cell transcriptional profiling have been developed. Existing approaches show some degree of limitation, for example, in terms of number of cells or transcripts that can be profiled. Due in part to these limitations, few conditions have been studied with these tools. Here we develop massively-parallel, multiplexed, microbial sequencing (M3-seq)-a single-cell RNA-sequencing platform for bacteria that pairs combinatorial cell indexing with post hoc rRNA depletion. We show that M3-seq can profile bacterial cells from different species under a range of conditions in single experiments. We then apply M3-seq to hundreds of thousands of cells, revealing rare populations and insights into bet-hedging associated with stress responses and characterizing phage infection.

Pattern formation by bacteria-phage interactions

The interactions between bacteria and phages-viruses that infect bacteria-play critical roles in agriculture, ecology, and medicine; however, how these interactions influence the spatial organization of both bacteria and phages remain largely unexplored. Here, we address this gap in knowledge by developing a theoretical model of motile, proliferating bacteria that aggregate via motility-induced phase separation (MIPS) and encounter phage that infect and lyse the cells. We find that the non-reciprocal predator-prey interactions between phage and bacteria strongly alter spatial organization, in some cases giving rise to a rich array of finite-scale stationary and dynamic patterns in which bacteria and phage coexist. We establish principles describing the onset and characteristics of these diverse behaviors, thereby helping to provide a biophysical basis for understanding pattern formation in bacteria-phage systems, as well as in a broader range of active and living systems with similar predator-prey or other non-reciprocal interactions.

Local polar order controls mechanical stress and triggers layer formation in developing Myxococcus xanthus colonies

Colonies of the social bacterium Myxococcus xanthus go through a morphological transition from a thin colony of cells to three-dimensional droplet-like fruiting bodies as a strategy to survive starvation. The biological pathways that control the decision to form a fruiting body have been studied extensively. However, the mechanical events that trigger the creation of multiple cell layers and give rise to droplet formation remain poorly understood. By measuring cell orientation, velocity, polarity, and force with cell-scale resolution, we reveal a stochastic local polar order in addition to the more obvious nematic order. Average cell velocity and active force at topological defects agree with predictions from active nematic theory, but their fluctuations are anomalously large due to polar active forces generated by the self-propelled rod-shaped cells. We find that M. xanthus cells adjust their reversal frequency to tune the magnitude of this local polar order, which in turn controls the mechanical stresses and triggers layer formation in the colonies.

Effects of linker length on phase separation: lessons from the Rubisco-EPYC1 system of the algal pyrenoid

Biomolecular condensates are membraneless organelles formed via phase separation of macromolecules, typically consisting of bond-forming "stickers" connected by flexible "linkers". Linkers have diverse roles, such as occupying space and facilitating interactions. To understand how linker length relative to other lengths affects condensation, we focus on the pyrenoid, which enhances photosynthesis in green algae. Specifically, we apply coarse-grained simulations and analytical theory to the pyrenoid proteins of Chlamydomonas reinhardtii: the rigid holoenzyme Rubisco and its flexible partner EPYC1. Remarkably, halving EPYC1 linker lengths decreases critical concentrations by ten-fold. We attribute this difference to the molecular "fit" between EPYC1 and Rubisco. Varying Rubisco sticker locations reveals that the native sites yield the poorest fit, thus optimizing phase separation. Surprisingly, shorter linkers mediate a transition to a gas of rods as Rubisco stickers approach the poles. These findings illustrate how intrinsically disordered proteins affect phase separation through the interplay of molecular length scales.

Proximity to criticality predicts surface properties of biomolecular condensates

It has recently become appreciated that cells self-organize their interiors through the formation of biomolecular condensates. These condensates, typically formed through liquid-liquid phase separation of proteins, nucleic acids, and other biopolymers, exhibit reversible assembly/disassembly in response to changing conditions. Condensates play many functional roles, aiding in biochemical reactions, signal transduction, and sequestration of certain components. Ultimately, these functions depend on the physical properties of condensates, which are encoded in the microscopic features of the constituent biomolecules. In general, the mapping from microscopic features to macroscopic properties is complex, but it is known that near a critical point, macroscopic properties follow power laws with only a small number of parameters, making it easier to identify underlying principles. How far does this critical region extend for biomolecular condensates and what principles govern condensate properties in the critical regime? Using coarse-grained molecular-dynamics simulations of a representative class of biomolecular condensates, we found that the critical regime can be wide enough to cover the full physiological range of temperatures. Within this critical regime, we identified that polymer sequence influences surface tension predominately via shifting the critical temperature. Finally, we show that condensate surface tension over a wide range of temperatures can be calculated from the critical temperature and a single measurement of the interface width.

Proliferating active matter

The fascinating patterns of collective motion created by autonomously driven particles have fuelled active-matter research for over two decades. So far, theoretical active-matter research has often focused on systems with a fixed number of particles. This constraint imposes strict limitations on what behaviours can and cannot emerge. However, a hallmark of life is the breaking of local cell number conservation by replication and death. Birth and death processes must be taken into account, for example, to predict the growth and evolution of a microbial biofilm, the expansion of a tumour, or the development from a fertilized egg into an embryo and beyond. In this Perspective, we argue that unique features emerge in these systems because proliferation represents a distinct form of activity: not only do the proliferating entities consume and dissipate energy, they also inject biomass and degrees of freedom capable of further self-proliferation, leading to myriad dynamic scenarios. Despite this complexity, a growing number of studies document common collective phenomena in various proliferating soft-matter systems. This generality leads us to propose proliferation as another direction of active-matter physics, worthy of a dedicated search for new dynamical universality classes. Conceptual challenges abound, from identifying control parameters and understanding large fluctuations and nonlinear feedback mechanisms to exploring the dynamics and limits of information flow in self-replicating systems. We believe that, by extending the rich conceptual framework developed for conventional active matter to proliferating active matter, researchers can have a profound impact on quantitative biology and reveal fascinating emergent physics along the way.

Phase-separating pyrenoid proteins form complexes in the dilute phase

While most studies of biomolecular phase separation have focused on the condensed phase, relatively little is known about the dilute phase. Theory suggests that stable complexes form in the dilute phase of two-component phase-separating systems, impacting phase separation; however, these complexes have not been interrogated experimentally. We show that such complexes indeed exist, using an in vitro reconstitution system of a phase-separated organelle, the algal pyrenoid, consisting of purified proteins Rubisco and EPYC1. Applying fluorescence correlation spectroscopy (FCS) to measure diffusion coefficients, we found that complexes form in the dilute phase with or without condensates present. The majority of these complexes contain exactly one Rubisco molecule. Additionally, we developed a simple analytical model which recapitulates experimental findings and provides molecular insights into the dilute phase organization. Thus, our results demonstrate the existence of protein complexes in the dilute phase, which could play important roles in the stability, dynamics, and regulation of condensates.

Size distributions of intracellular condensates reflect competition between coalescence and nucleation

Phase separation of biomolecules into condensates has emerged as a mechanism for intracellular organization and affects many intracellular processes, including reaction pathways through the clustering of enzymes and pathway intermediates. Precise and rapid spatiotemporal control of reactions by condensates requires tuning of their sizes. However, the physical processes that govern the distribution of condensate sizes remain unclear. Here we show that both native and synthetic condensates display an exponential size distribution, which is captured by Monte Carlo simulations of fast nucleation followed by coalescence. In contrast, pathological aggregates exhibit a power-law size distribution. These distinct behaviours reflect the relative importance of nucleation and coalescence kinetics. We demonstrate this by utilizing a combination of synthetic and native condensates to probe the underlying physical mechanisms determining condensate size. The appearance of exponential distributions for abrupt nucleation versus power-law distributions under continuous nucleation may reflect a general principle that determines condensate size distributions.

Subcellular localization of type IV pili regulates bacterial multicellular development

In mammals, subcellular protein localization of factors like planar cell polarity proteins is a key driver of the multicellular organization of tissues. Bacteria also form organized multicellular communities, but these patterns are largely thought to emerge from regulation of whole-cell processes like growth, motility, cell shape, and differentiation. Here we show that a unique intracellular patterning of appendages known as type IV pili (T4P) can drive multicellular development of complex bacterial communities. Specifically, dynamic T4P appendages localize in a line along the long axis of the cell in the bacterium Acinetobacter baylyi. This long-axis localization is regulated by a functionally divergent chemosensory Pil-Chp system, and an atypical T4P protein homologue (FimV) bridges Pil-Chp signaling and T4P positioning. We further demonstrate through modeling and empirical approaches that subcellular T4P localization controls how individual cells interact with one another, independently of T4P dynamics, with different patterns of localization giving rise to distinct multicellular architectures. Our results reveal how subcellular patterning of single cells regulates the development of multicellular bacterial communities.

Global and gene-specific translational regulation in Escherichia coli across different conditions

How well mRNA transcript levels represent protein abundances has been a controversial issue. Particularly across different environments, correlations between mRNA and protein exhibit remarkable variability from gene to gene. Translational regulation is likely to be one of the key factors contributing to mismatches between mRNA level and protein abundance in bacteria. Here, we quantified genome-wide transcriptome and relative translation efficiency (RTE) under 12 different conditions in Escherichia coli. By quantifying the mRNA-RTE correlation both across genes and across conditions, we uncovered a diversity of gene-specific translational regulations, cooperating with transcriptional regulations, in response to carbon (C), nitrogen (N), and phosphate (P) limitations. Intriguingly, we found that many genes regulating translation are themselves subject to translational regulation, suggesting possible feedbacks. Furthermore, a random forest model suggests that codon usage partially predicts a gene's cross-condition variability in translation efficiency; such cross-condition variability tends to be an inherent quality of a gene, independent of the specific nutrient limitations. These findings broaden the understanding of translational regulation under different environments and provide novel strategies for the control of translation in synthetic biology. In addition, our data offers a resource for future multi-omics studies.

Membrane fission during bacterial spore development requires cellular inflation driven by DNA translocation

Bacteria require membrane fission for both cell division and endospore formation. In Bacillus subtilis, sporulation initiates with an asymmetric division that generates a large mother cell and a smaller forespore that contains only a quarter of its genome. As the mother cell membranes engulf the forespore, a DNA translocase pumps the rest of the chromosome into the small forespore compartment, inflating it due to increased turgor. When the engulfing membrane undergoes fission, the forespore is released into the mother cell cytoplasm. The B. subtilis protein FisB catalyzes membrane fission during sporulation, but the molecular basis is unclear. Here, we show that forespore inflation and FisB accumulation are both required for an efficient membrane fission. Forespore inflation leads to higher membrane tension in the engulfment membrane than in the mother cell membrane, causing the membrane to flow through the neck connecting the two membrane compartments. Thus, the mother cell supplies some of the membrane required for the growth of the membranes surrounding the forespore. The oligomerization of FisB at the membrane neck slows the equilibration of membrane tension by impeding the membrane flow. This leads to a further increase in the tension of the engulfment membrane, promoting its fission through lysis. Collectively, our data indicate that DNA translocation has a previously unappreciated second function in energizing the FisB-mediated membrane fission under energy-limited conditions.

Signal Transduction Network Principles Underlying Bacterial Collective Behaviors

Bacteria orchestrate collective behaviors and accomplish feats that would be unsuccessful if carried out by a lone bacterium. Processes undertaken by groups of bacteria include bioluminescence, biofilm formation, virulence factor production, and release of public goods that are shared by the community. Collective behaviors are controlled by signal transduction networks that integrate sensory information and transduce the information internally. Here, we discuss network features and mechanisms that, even in the face of dramatically changing environments, drive precise execution of bacterial group behaviors. We focus on representative quorum-sensing and second-messenger cyclic dimeric GMP (c-di-GMP) signal relays. We highlight ligand specificity versus sensitivity, how small-molecule ligands drive discrimination of kin versus nonkin, signal integration mechanisms, single-input sensory systems versus coincidence detectors, and tuning of input-output dynamics via feedback regulation. We summarize how different features of signal transduction systems allow groups of bacteria to successfully interpret and collectively react to dynamically changing environments.

Modelling the pyrenoid-based CO2-concentrating mechanism provides insights into its operating principles and a roadmap for its engineering into crops

Many eukaryotic photosynthetic organisms enhance their carbon uptake by supplying concentrated CO₂ to the CO₂-fixing enzyme Rubisco in an organelle called the pyrenoid. Ongoing efforts seek to engineer this pyrenoid-based CO₂-concentrating mechanism (PCCM) into crops to increase yields. Here we develop a computational model for a PCCM on the basis of the postulated mechanism in the green alga Chlamydomonas reinhardtii. Our model recapitulates all Chlamydomonas PCCM-deficient mutant phenotypes and yields general biophysical principles underlying the PCCM. We show that an effective and energetically efficient PCCM requires a physical barrier to reduce pyrenoid CO₂ leakage, as well as proper enzyme localization to reduce futile cycling between CO₂ and HCO₃^-. Importantly, our model demonstrates the feasibility of a purely passive CO₂ uptake strategy at air-level CO₂, while active HCO₃^- uptake proves advantageous at lower CO₂ levels. We propose a four-step engineering path to increase the rate of CO₂ fixation in the plant chloroplast up to threefold at a theoretical cost of only 1.3 ATP per CO₂ fixed, thereby offering a framework to guide the engineering of a PCCM into land plants.

Noisy metabolism can promote microbial cross-feeding

Cross-feeding, the exchange of nutrients between organisms, is ubiquitous in microbial communities. Despite its importance in natural and engineered microbial systems, our understanding of how inter-species cross-feeding arises is incomplete, with existing theories limited to specific scenarios. Here, we introduce a novel theory for the emergence of such cross-feeding, which we term noise-averaging cooperation (NAC). NAC is based on the idea that, due to their small size, bacteria are prone to noisy regulation of metabolism which limits their growth rate. To compensate, related bacteria can share metabolites with each other to ‘average out’ noise and improve their collective growth. According to the Black Queen Hypothesis, this metabolite sharing among kin, a form of ‘leakage’, then allows for the evolution of metabolic interdependencies among species including de novo speciation via gene deletions. We first characterize NAC in a simple ecological model of cell metabolism, showing that metabolite leakage can in principle substantially increase growth rate in a community context. Next, we develop a generalized framework for estimating the potential benefits of NAC among real bacteria. Using single-cell protein abundance data, we predict that bacteria suffer from substantial noise-driven growth inefficiencies, and may therefore benefit from NAC. We then discuss potential evolutionary pathways for the emergence of NAC. Finally, we review existing evidence for NAC and outline potential experimental approaches to detect NAC in microbial communities.

Quantitative input-output dynamics of a c-di-GMP signal transduction cascade in Vibrio cholerae

Bacterial biofilms are multicellular communities that collectively overcome environmental threats and clinical treatments. To regulate the biofilm lifecycle, bacteria commonly transduce sensory information via the second messenger molecule cyclic diguanylate (c-di-GMP). Using experimental and modeling approaches, we quantitatively capture c-di-GMP signal transmission via the bifunctional polyamine receptor NspS-MbaA, from ligand binding to output, in the pathogen Vibrio cholerae. Upon binding of norspermidine or spermidine, NspS-MbaA synthesizes or degrades c-di-GMP, respectively, which, in turn, drives alterations specifically to biofilm gene expression. A long-standing question is how output specificity is achieved via c-di-GMP, a diffusible molecule that regulates dozens of effectors. We show that NspS-MbaA signals locally to specific effectors, sensitizing V. cholerae to polyamines. However, local signaling is not required for specificity, as changes to global cytoplasmic c-di-GMP levels can selectively regulate biofilm genes. This work establishes the input-output dynamics underlying c-di-GMP signaling, which could be useful for developing bacterial manipulation strategies.

piRNAs of Caenorhabditis elegans broadly silence nonself sequences through functionally random targeting

Small noncoding RNAs such as piRNAs are guides for Argonaute proteins, enabling sequence-specific, post-transcriptional regulation of gene expression. The piRNAs of Caenorhabditis elegans have been observed to bind targets with high mismatch tolerance and appear to lack specific transposon targets, unlike piRNAs in Drosophila melanogaster and other organisms. These observations support a model in which C. elegans piRNAs provide a broad, indiscriminate net of silencing, competing with siRNAs associated with the CSR-1 Argonaute that specifically protect self-genes from silencing. However, the breadth of piRNA targeting has not been subject to in-depth quantitative analysis, nor has it been explained how piRNAs are distributed across sequence space to achieve complete coverage. Through a bioinformatic analysis of piRNA sequences, incorporating an original data-based metric of piRNA-target distance, we demonstrate that C. elegans piRNAs are functionally random, in that their coverage of sequence space is comparable to that of random sequences. By possessing a sufficient number of distinct, essentially random piRNAs, C. elegans is able to target arbitrary nonself sequences with high probability. We extend this approach to a selection of other nematodes, finding results which elucidate the mechanism by which nonself mRNAs are silenced, and have implications for piRNA evolution and biogenesis.

Stoichiometry Controls the Dynamics of Liquid Condensates of Associative Proteins

Multivalent associative proteins with strong complementary interactions play a crucial role in phase separation of intracellular liquid condensates. We study the internal dynamics of such "bond-network" condensates comprising two complementary proteins via scaling analysis and molecular dynamics. We find that when stoichiometry is balanced, relaxation slows down dramatically due to a scarcity of alternative binding partners following bond breakage. This microscopic slow-down strongly affects the bulk diffusivity, viscosity, and mixing, which provides a means to experimentally test this prediction.

Enzyme regulation and mutation in a model serial-dilution ecosystem

Microbial communities are ubiquitous in nature and come in a multitude of forms, ranging from communities dominated by a handful of species to communities containing a wide variety of metabolically distinct organisms. This huge range in diversity is not a curiosity-microbial diversity has been linked to outcomes of substantial ecological and medical importance. However, the mechanisms underlying microbial diversity are still under debate, as simple mathematical models only permit as many species to coexist as there are resources. A plethora of mechanisms have been proposed to explain the origins of microbial diversity, but many of these analyses omit a key property of real microbial ecosystems: the propensity of the microbes themselves to change their growth properties within and across generations. In order to explore the impact of this key property on microbial diversity, we expand upon a recently developed model of microbial diversity in fluctuating environments. We implement changes in growth strategy in two distinct ways. First, we consider the regulation of a cell's enzyme levels within short, ecological times, and second we consider evolutionary changes driven by mutations across generations. Interestingly, we find that these two types of microbial responses to the environment can have drastically different outcomes. Enzyme regulation may collapse diversity over long enough times while, conversely, strategy-randomizing mutations can produce a "rich-get-poorer" effect that promotes diversity. This paper makes explicit, using a simple serial-dilutions framework, the conflicting ways that microbial adaptation and evolution can affect community diversity.

Metabolic channeling: predictions, deductions, and evidence

With the elucidation of myriad anabolic and catabolic enzyme-catalyzed cellular pathways crisscrossing each other, an obvious question arose: how could these networks operate with maximal catalytic efficiency and minimal interference? A logical answer was the postulate of metabolic channeling, which in its simplest embodiment assumes that the product generated by one enzyme passes directly to a second without diffusion into the surrounding medium. This tight coupling of activities might increase a pathway's metabolic flux and/or serve to sequester unstable/toxic/reactive intermediates as well as prevent their access to other networks. Here, we present evidence for this concept, commencing with enzymes that feature a physical molecular tunnel, to multi-enzyme complexes that retain pathway substrates through electrostatics or enclosures, and finally to metabolons that feature collections of enzymes assembled into clusters with variable stoichiometric composition. Lastly, we discuss the advantages of reversibly assembled metabolons in the context of the purinosome, the purine biosynthesis metabolon.

Mechanical Frustration of Phase Separation in the Cell Nucleus by Chromatin

Liquid-liquid phase separation is a fundamental mechanism underlying subcellular organization. Motivated by the striking observation that optogenetically generated droplets in the nucleus display suppressed coarsening dynamics, we study the impact of chromatin mechanics on droplet phase separation. We combine theory and simulation to show that cross-linked chromatin can mechanically suppress droplets' coalescence and ripening, as well as quantitatively control their number, size, and placement. Our results highlight the role of the subcellular mechanical environment on condensate regulation.

Roadmap on emerging concepts in the physical biology of bacterial biofilms: from surface sensing to community formation

Bacterial biofilms are communities of bacteria that exist as aggregates that can adhere to surfaces or be free-standing. This complex, social mode of cellular organization is fundamental to the physiology of microbes and often exhibits surprising behavior. Bacterial biofilms are more than the sum of their parts: single-cell behavior has a complex relation to collective community behavior, in a manner perhaps cognate to the complex relation between atomic physics and condensed matter physics. Biofilm microbiology is a relatively young field by biology standards, but it has already attracted intense attention from physicists. Sometimes, this attention takes the form of seeing biofilms as inspiration for new physics. In this roadmap, we highlight the work of those who have taken the opposite strategy: we highlight the work of physicists and physical scientists who use physics to engage fundamental concepts in bacterial biofilm microbiology, including adhesion, sensing, motility, signaling, memory, energy flow, community formation and cooperativity. These contributions are juxtaposed with microbiologists who have made recent important discoveries on bacterial biofilms using state-of-the-art physical methods. The contributions to this roadmap exemplify how well physics and biology can be combined to achieve a new synthesis, rather than just a division of labor.

FisB relies on homo-oligomerization and lipid binding to catalyze membrane fission in bacteria

Little is known about mechanisms of membrane fission in bacteria despite their requirement for cytokinesis. The only known dedicated membrane fission machinery in bacteria, fission protein B (FisB), is expressed during sporulation in Bacillus subtilis and is required to release the developing spore into the mother cell cytoplasm. Here, we characterized the requirements for FisB-mediated membrane fission. FisB forms mobile clusters of approximately 12 molecules that give way to an immobile cluster at the engulfment pole containing approximately 40 proteins at the time of membrane fission. Analysis of FisB mutants revealed that binding to acidic lipids and homo-oligomerization are both critical for targeting FisB to the engulfment pole and membrane fission. Experiments using artificial membranes and filamentous cells suggest that FisB does not have an intrinsic ability to sense or induce membrane curvature but can bridge membranes. Finally, modeling suggests that homo-oligomerization and trans-interactions with membranes are sufficient to explain FisB accumulation at the membrane neck that connects the engulfment membrane to the rest of the mother cell membrane during late stages of engulfment. Together, our results show that FisB is a robust and unusual membrane fission protein that relies on homo-oligomerization, lipid binding, and the unique membrane topology generated during engulfment for localization and membrane scission, but surprisingly, not on lipid microdomains, negative-curvature lipids, or curvature sensing.

Evolution of an asymptomatic first stage of infection in a heterogeneous population

Pathogens evolve different life-history strategies, which depend in part on differences in their host populations. A central feature of hosts is their population structure (e.g. spatial). Additionally, hosts themselves can exhibit different degrees of symptoms when newly infected; this latency is a key life-history property of pathogens. With an evolutionary-epidemiological model, we examine the role of population structure on the evolutionary dynamics of latency. We focus on specific power-law-like formulations for transmission and progression from the first infectious stage as a function of latency, assuming that the across-group to within-group transmission ratio increases if hosts are less symptomatic. We find that simple population heterogeneity can lead to local evolutionarily stable strategies (ESSs) at zero and infinite latency in situations where a unique ESS exists in the corresponding homogeneous case. Furthermore, there can exist more than one interior evolutionarily singular strategy. We find that this diversity of outcomes is due to the (possibly slight) advantage of across-group transmission for pathogens that produce fewer symptoms in a first infectious stage. Thus, our work reveals that allowing individuals without symptoms to travel can have important unintended evolutionary effects and is thus fundamentally problematic in view of the evolutionary dynamics of latency.

Decoding the physical principles of two-component biomolecular phase separation

Cells possess a multiplicity of non-membrane-bound compartments, which form via liquid-liquid phase separation. These condensates assemble and dissolve as needed to enable central cellular functions. One important class of condensates is those composed of two associating polymer species that form one-to-one specific bonds. What are the physical principles that underlie phase separation in such systems? To address this question, we employed coarse-grained molecular dynamics simulations to examine how the phase boundaries depend on polymer valence, stoichiometry, and binding strength. We discovered a striking phenomenon – for sufficiently strong binding, phase separation is suppressed at rational polymer stoichiometries, which we termed the magic-ratio effect. We further developed an analytical dimer-gel theory that confirmed the magic-ratio effect and disentangled the individual roles of polymer properties in shaping the phase diagram. Our work provides new insights into the factors controlling the phase diagrams of biomolecular condensates, with implications for natural and synthetic systems.

Competitive binding of independent extension and retraction motors explains the quantitative dynamics of type IV pili

Type IV pili (TFP) function through cycles of extension and retraction. The coordination of these cycles remains mysterious due to a lack of quantitative measurements of multiple features of TFP dynamics. Here, we fluorescently label TFP in the pathogen Pseudomonas aeruginosa and track full extension and retraction cycles of individual filaments. Polymerization and depolymerization dynamics are stochastic; TFP are made at random times and extend, pause, and retract for random lengths of time. TFP can also pause for extended periods between two extension or two retraction events in both wild-type cells and a slowly retracting PilT mutant. We developed a biophysical model based on the stochastic binding of two dedicated extension and retraction motors to the same pilus machine that predicts the observed features of the data with no free parameters. We show that only a model in which both motors stochastically bind and unbind to the pilus machine independent of the piliation state of the machine quantitatively explains the experimentally observed pilus production rate. In experimental support of this model, we show that the abundance of the retraction motor dictates the pilus production rate and that PilT is bound to pilus machines even in their unpiliated state. Together, the strong quantitative agreement of our model with a variety of experiments suggests that the entire repetitive cycle of pilus extension and retraction is coordinated by the competition of stochastic motor binding to the pilus machine, and that the retraction motor is the major throttle for pilus production.

Superinfection and the evolution of an initial asymptomatic stage

Pathogens have evolved a variety of life-history strategies. An important strategy consists of successful transmission by an infected host before the appearance of symptoms, that is, while the host is still partially or fully asymptomatic. During this initial stage of infection, it is possible for another pathogen to superinfect an already infected host and replace the previously infecting pathogen. Here, we study the effect of superinfection during the first stage of an infection on the evolutionary dynamics of the degree to which the host is asymptomatic (host latency) in that same stage. We find that superinfection can lead to major differences in evolutionary behaviour. Most strikingly, the duration of immunity following infection can significantly influence pathogen evolutionary dynamics, whereas without superinfection the outcomes are independent of host immunity. For example, changes in host immunity can drive evolutionary transitions from a fully symptomatic to a fully asymptomatic first infection stage. Additionally, if superinfection relative to susceptible infection is strong enough, evolution can lead to a unique strategy of latency that corresponds to a local fitness minimum, and is therefore invasible by nearby mutants. Thus, this strategy is a branching point, and can lead to coexistence of pathogens with different latencies. Furthermore, in this new framework with superinfection, we also find that there can exist two interior singular strategies. Overall, new evolutionary outcomes can cascade from superinfection.

Nutrient levels and trade-offs control diversity in a serial dilution ecosystem

Microbial communities feature an immense diversity of species and this diversity is linked to outcomes ranging from ecosystem stability to medical prognoses. Yet the mechanisms underlying microbial diversity are under debate. While simple resource-competition models don't allow for coexistence of a large number of species, it was recently shown that metabolic trade-offs can allow unlimited diversity. Does this diversity persist with more realistic, intermittent nutrient supply? Here, we demonstrate theoretically that in serial dilution culture, metabolic trade-offs allow for high diversity. When a small amount of nutrient is supplied to each batch, the serial dilution dynamics mimic a chemostat-like steady state. If more nutrient is supplied, community diversity shifts due to an 'early-bird' effect. The interplay of this effect with different environmental factors and diversity-supporting mechanisms leads to a variety of relationships between nutrient supply and diversity, suggesting that real ecosystems may not obey a universal nutrient-diversity relationship.

Modeling microbial metabolic trade-offs in a chemostat

Microbes face intense competition in the natural world, and so need to wisely allocate their resources to multiple functions, in particular to metabolism. Understanding competition among metabolic strategies that are subject to trade-offs is therefore crucial for deeper insight into the competition, cooperation, and community assembly of microorganisms. In this work, we evaluate competing metabolic strategies within an ecological context by considering not only how the environment influences cell growth, but also how microbes shape their chemical environment. Utilizing chemostat-based resource-competition models, we exhibit a set of intuitive and general procedures for assessing metabolic strategies. Using this framework, we are able to relate and unify multiple metabolic models, and to demonstrate how the fitness landscape of strategies becomes intrinsically dynamic due to species-environment feedback. Such dynamic fitness landscapes produce rich behaviors, and prove to be crucial for ecological and evolutionarily stable coexistence in all the models we examined.

Implications of localized charge for human influenza A H1N1 hemagglutinin evolution: Insights from deep mutational scans

Seasonal influenza A viruses of humans evolve rapidly due to strong selection pressures from host immune responses, principally on the hemagglutinin (HA) viral surface protein. Based on mouse transmission experiments, a proposed mechanism for immune evasion consists of increased avidity to host cellular receptors, mediated by electrostatic charge interactions with negatively charged cell surfaces. In support of this, the HA charge of the globally circulating H3N2 has increased over time since its pandemic. However, the same trend was not seen in H1N1 HA sequences. This is counter-intuitive, since immune escape due to increased avidity (due itself to an increase in charge) was determined experimentally. Here, we explore whether patterns of local charge of H1N1 HA can explain this discrepancy and thus further associate electrostatic charge with immune escape and viral evolutionary dynamics. Measures of site-wise functional selection and expected charge computed from deep mutational scan data on an early H1N1 HA yield a striking division of residues into three groups, separated by charge. We then explored evolutionary dynamics of these groups from 1918 to 2008. In particular, one group increases in net charge over time and consists of sites that are evolving the fastest, that are closest to the receptor binding site (RBS), and that are exposed to solvent (i.e., on the surface). By contrast, another group decreases in net charge and consists of sites that are further away from the RBS and evolving slower, but also exposed to solvent. The last group consists of those sites in the HA core, with no change in net charge and that evolve very slowly. Thus, there is a group of residues that follows the same trend as seen for the entire H3N2 HA. It is possible that the H1N1 HA is under other biophysical constraints that result in compensatory decreases in charge elsewhere on the protein. Our results implicate localized charge in HA interactions with host cells, and highlight how deep mutational scan data can inform evolutionary hypotheses.

The hemagglutinin (HA) surface protein of influenza A viruses evolves rapidly to evade host immunity, leading to sizable yearly epidemics in human populations. Previous transmission experiments with H1N1 in mice have tied immune escape to an increase in HA avidity for cellular receptors, mediated by electrostatic charge. Furthermore, retrospective sequence analyses from a previous study confirmed that the HA of circulating global H3N2 has increased in net charge, yet surprisingly, that of H1N1 has not varied significantly. How is a stable net charge related to local patterns of H1N1 HA charge in response to selection? To elucidate the role of local electrostatic charge in host-virus interactions, we investigate characteristics of local charge on the H1N1 HA using functional data from deep mutational scan experiments. Combining measures of functional selection and expected charge at each site on DMS data from a 1933 H1N1 HA yields a striking visual pattern that identifies three groups of sites that have different biophysical properties and that prove to have distinct evolutionary patterns in natural human sequences. Essentially, we find evidence for an increase in charge near the receptor binding site and for compensatory changes elsewhere on the protein. Thus, our findings may reconcile disparate results from transmission experiments and natural sequence analyses, and highlight the importance of local properties of the HA protein. Overall, our findings further support the hypothesis of immune escape due to increased HA avidity to cellular receptors mediated by electrostatic charge. More generally, our work illustrates a novel method of leveraging deep mutational scans in conjunction with natural sequences to shed light on virus-host interactions.

Asymmetry between Activators and Deactivators in Functional Protein Networks

Are “turn-on” and “turn-off” functions in protein-protein interaction networks exact opposites of each other? To answer this question, we implement a minimal model for the evolution of functional protein-interaction networks using a sequence-based mutational algorithm, and apply the model to study neutral drift in networks that yield oscillatory dynamics. We study the roles of activators and deactivators, two core components of oscillatory protein interaction networks, and find a striking asymmetry in the roles of activating and deactivating proteins, where activating proteins tend to be synergistic and deactivating proteins tend to be competitive.

Cell position fates and collective fountain flow in bacterial biofilms revealed by light-sheet microscopy

Bacterial biofilms represent a basic form of multicellular organization that confers survival advantages to constituent cells. The sequential stages of cell ordering during biofilm development have been studied in the pathogen and model biofilm-former Vibrio cholerae It is unknown how spatial trajectories of individual cells and the collective motions of many cells drive biofilm expansion. We developed dual-view light-sheet microscopy to investigate the dynamics of biofilm development from a founder cell to a mature three-dimensional community. Tracking of individual cells revealed two distinct fates: one set of biofilm cells expanded ballistically outward, while the other became trapped at the substrate. A collective fountain-like flow transported cells to the biofilm front, bypassing members trapped at the substrate and facilitating lateral biofilm expansion. This collective flow pattern was quantitatively captured by a continuum model of biofilm growth against substrate friction. Coordinated cell movement required the matrix protein RbmA, without which cells expanded erratically. Thus, tracking cell lineages and trajectories in space and time revealed how multicellular structures form from a single founder cell.

Dynamics in a simple evolutionary-epidemiological model for the evolution of an initial asymptomatic infection stage

Pathogens exhibit a rich variety of life history strategies, shaped by natural selection. An important pathogen life history characteristic is the propensity to induce an asymptomatic yet productive (transmissive) stage at the beginning of an infection. This characteristic is subject to complex trade-offs, ranging from immunological considerations to population-level social processes. We aim to classify the evolutionary dynamics of such asymptomatic behavior of pathogens (hereafter "latency") in order to unify epidemiology and evolution for this life history strategy. We focus on a simple epidemiological model with two infectious stages, where hosts in the first stage can be partially or fully asymptomatic. Immunologically, there is a trade-off between transmission and progression in this first stage. For arbitrary trade-offs, we derive different conditions that guarantee either at least one evolutionarily stable strategy (ESS) at zero, some, or maximal latency of the first stage or, perhaps surprisingly, at least one unstable evolutionarily singular strategy. In this latter case, there is bistability between zero and nonzero (possibly maximal) latency. We then prove the uniqueness of interior evolutionarily singular strategies for power-law and exponential trade-offs: Thus, bistability is always between zero and maximal latency. Overall, previous multistage infection models can be summarized with a single model that includes evolutionary processes acting on latency. Since small changes in parameter values can lead to abrupt transitions in evolutionary dynamics, appropriate disease control strategies could have a substantial impact on the evolution of first-stage latency.

Concerted 2-5A-Mediated mRNA Decay and Transcription Reprogram Protein Synthesis in the dsRNA Response

Viral and endogenous double-stranded RNA (dsRNA) is a potent trigger for programmed RNA degradation by the 2-5A/RNase L complex in cells of all mammals. This 2-5A-mediated decay (2-5AMD) is a conserved stress response switching global protein synthesis from homeostasis to production of interferons (IFNs). To understand this mechanism, we examined 2-5AMD in human cells and found that it triggers polysome collapse characteristic of inhibited translation initiation. We determined that translation initiation complexes and ribosomes purified from translation-arrested cells remain functional. However, spike-in RNA sequencing (RNA-seq) revealed cell-wide decay of basal mRNAs accompanied by rapid accumulation of mRNAs encoding innate immune proteins. Our data attribute this 2-5AMD evasion to better stability of defense mRNAs and positive feedback in the IFN response amplified by RNase L-resistant molecules. We conclude that 2-5AMD and transcription act in concert to refill mammalian cells with defense mRNAs, thereby "prioritizing" the synthesis of innate immune proteins.

Spatial ecology of territorial populations

Many ecosystems, from vegetation to biofilms, are composed of territorial populations that compete for both nutrients and physical space. What are the implications of such spatial organization for biodiversity? To address this question, we developed and analyzed a model of territorial resource competition. In the model, all species obey trade-offs inspired by biophysical constraints on metabolism; the species occupy nonoverlapping territories, while nutrients diffuse in space. We find that the nutrient diffusion time is an important control parameter for both biodiversity and the timescale of population dynamics. Interestingly, fast nutrient diffusion allows the populations of some species to fluctuate to zero, leading to extinctions. Moreover, territorial competition spontaneously gives rise to both multistability and the Allee effect (in which a minimum population is required for survival), so that small perturbations can have major ecological effects. While the assumption of trade-offs allows for the coexistence of more species than the number of nutrients-thus violating the principle of competitive exclusion-overall biodiversity is curbed by the domination of "oligotroph" species. Importantly, in contrast to well-mixed models, spatial structure renders diversity robust to inequalities in metabolic trade-offs. Our results suggest that territorial ecosystems can display high biodiversity and rich dynamics simply due to competition for resources in a spatial community.

Revealing evolutionary constraints on proteins through sequence analysis

Statistical analysis of alignments of large numbers of protein sequences has revealed "sectors" of collectively coevolving amino acids in several protein families. Here, we show that selection acting on any functional property of a protein, represented by an additive trait, can give rise to such a sector. As an illustration of a selected trait, we consider the elastic energy of an important conformational change within an elastic network model, and we show that selection acting on this energy leads to correlations among residues. For this concrete example and more generally, we demonstrate that the main signature of functional sectors lies in the small-eigenvalue modes of the covariance matrix of the selected sequences. However, secondary signatures of these functional sectors also exist in the extensively-studied large-eigenvalue modes. Our simple, general model leads us to propose a principled method to identify functional sectors, along with the magnitudes of mutational effects, from sequence data. We further demonstrate the robustness of these functional sectors to various forms of selection, and the robustness of our approach to the identification of multiple selected traits.

Mechanical instability and interfacial energy drive biofilm morphogenesis

Surface-attached bacterial communities called biofilms display a diversity of morphologies. Although structural and regulatory components required for biofilm formation are known, it is not understood how these essential constituents promote biofilm surface morphology. Here, using Vibrio cholerae as our model system, we combine mechanical measurements, theory and simulation, quantitative image analyses, surface energy characterizations, and mutagenesis to show that mechanical instabilities, including wrinkling and delamination, underlie the morphogenesis program of growing biofilms. We also identify interfacial energy as a key driving force for mechanomorphogenesis because it dictates the generation of new and the annihilation of existing interfaces. Finally, we discover feedback between mechanomorphogenesis and biofilm expansion, which shapes the overall biofilm contour. The morphogenesis principles that we discover in bacterial biofilms, which rely on mechanical instabilities and interfacial energies, should be generally applicable to morphogenesis processes in tissues in higher organisms.

Engineers have long studied how mechanical instabilities cause patterns to form in inanimate materials, and recently more attention has been given to how such forces affect biological systems. For example, stresses can build up within a tissue if one layer grows faster than an adjacent layer. The tissue can release this stress by wrinkling, folding or creasing.

Though ancient and single-celled, bacteria can also develop spectacular patterns when they exist in the lifestyle known as a biofilm: a community of cells adhered to a surface. But do mechanical instabilities drive the patterns seen in biofilms?

To investigate, Yan, Fei, Mao et al. grew biofilms of the bacterium called Vibrio cholerae – which causes the disease cholera – on solid, non-growing ‘substrates’. This work revealed that as the biofilms grow, their expansion is constrained by the substrate, and this situation generates mechanical stresses. To release the stresses, the biofilm initially folds to form wrinkles. Later, as the biofilm expands further, small parts of it detach from the substrate to form blisters. The same forces that keep water droplets spherical (known as interfacial forces) dictate how the blisters evolve, interact, and eventually shape the expanding biofilm. Using these principles, Yan et al. could engineer the biofilm into desired shapes.

Collectively, the results presented by Yan et al. connect the shape of the biofilm surface with its material properties, in particular its stiffness. Understanding this relationship could help researchers to develop new ways to remove harmful biofilms, such as those that cause disease or that damage underwater structures. The stiffness of biofilms is already known to affect how well bacteria can resist antibiotics. Future studies could look for new genes or compounds that change the material properties of a biofilm, thereby altering the biofilm surface.

Cell geometry and leaflet bilayer asymmetry regulate domain formation in plasma membranes

We model how pattern formation in a multicomponent lipid bilayer pinned to an elastic substrate is governed by the interplay between lipid phase separation and the tendency of domains of high intrinsic curvature lipids to deform the membrane away from a stiff substrate such as the cell wall. The emergent patterns, which include compact and striped lipid microdomains, are anticorrelated across the two leaflets and depend on leaflet asymmetry, the ability of lipids to flip between leaflets, and the global geometry. We characterize analytically the dependence of stripe width on lipid parameters, and consider the implications of interleaflet patterning for curvature-dependent lipid localization.

Quorum sensing controls Vibrio cholerae multicellular aggregate formation

Bacteria communicate and collectively regulate gene expression using a process called quorum sensing (QS). QS relies on group-wide responses to signal molecules called autoinducers. Here, we show that QS activates a new program of multicellularity in Vibrio cholerae. This program, which we term aggregation, is distinct from the canonical surface-biofilm formation program, which QS represses. Aggregation is induced by autoinducers, occurs rapidly in cell suspensions, and does not require cell division, features strikingly dissimilar from those characteristic of V. cholerae biofilm formation. Extracellular DNA limits aggregate size, but is not sufficient to drive aggregation. A mutagenesis screen identifies genes required for aggregate formation, revealing proteins involved in V. cholerae intestinal colonization, stress response, and a protein that distinguishes the current V. cholerae pandemic strain from earlier pandemic strains. We suggest that QS-controlled aggregate formation is important for V. cholerae to successfully transit between the marine niche and the human host.