Microbial biofilms are shaped by the constant dialogue between biological and physical forces in the extracellular matrix

Abstract

The biofilm matrix, with its diversity of extracellular polymeric substances (EPS), remains a poorly understood entity. It consists of a heterogeneous, multifunctional microenvironment that imparts a range of emergent properties to the biofilm, including social cooperation and resource sharing, adaptation to environmental changes, and resistance to harmful chemicals and antibiotics. Generally, studies of the biofilm matrix focus on the regulation of EPS gene expression and associated biofilm phenotypes (Flemming et al., 2022; Flemming & Wingender, 2010). For example, the differential regulation of exopolymers, which impart different mechanical properties, is an often-studied genetic marker for characterizing transitions between different stages of biofilm development (Chew, Kundukad, et al., 2014; Irie et al., 2012). New insights, however, suggest that the emergent properties of the matrix, which arise because of physical interactions between EPS molecules as well as those between EPS and bacterial cells, also play important roles in biofilm formation and organization (Liu et al., 2022; Rubinstein et al., 2012). For example, the secretion and accumulation of EPS components generate new physical forces, such as osmotic stresses, bridging interactions, and depletion effects within the crowded matrix (Liu et al., 2022). These forces alter the physical environment of the biofilm, affecting conformational and aggregational landscapes and dynamics, and thus functions, of matrix biopolymers. Together with the biological program, they stabilize extended structural, compositional, and morphological gradients in space and time, drive phase transitions, immobilize cells, and induce phase separation, creating spatial functional niches within the matrix (Worlitzer et al., 2022). Considering these insights, we highlight here the emerging perspective that understanding the competition and the collaboration between physical and biological factors is crucial for a more complete appreciation of biofilm formation, dynamics, organization, and function. Although single-celled, most bacteria acquire a multicellular lifestyle by their organization into collective, complex populations or communities, consisting of single or multiple species of microorganisms (Berlanga & Guerrero, 2016). This multicellular mode of life enables bacteria to develop social synergies such as communication, labor division, spatial arrangements, and metabolic cooperation (Elias & Banin, 2012). It also affords the assemblage and shared abilities to sense, respond, as well as adapt to cues, stresses, and perturbations from their microenvironment (Flemming et al., 2016). Taken together, these attributes enable bacterial communities to develop an organization that reflects an optimal survival strategy (Fux et al., 2005) and promotes their collective fitness (Elias & Banin, 2012) In this regard, the biofilm lifestyle, in which heterogeneous aggregates of microorganisms become embedded within a three-dimensional matrix of self-secreted, extracellular polymeric substances (EPS), represents one of the most versatile forms of multicellularity (Costerton et al., 1995). The adoption of the biofilm lifestyle is mediated by the regulation of biofilm-specific genes in response to many different signals (Flemming et al., 2016). Common signals that trigger the lifestyle switch in bacteria include changes in temperature, pH, osmolality, nutrient availability, selected chemicals (e.g., antibiotics), and the presence of a surface (Morales & Kolter, 2014). These signals activate many core gene regulatory derived processes including (i) secretion of cell-density dependent quorum sensing molecules (e.g., cyclic-di-GMP) and (ii) modulation of genes responsible for cellular motility and the production of EPS (Fu et al., 2021; Mukherjee & Bassler, 2019). Together, these changes characterize the biological program for initiating biofilm formation. However, the biological program alone does not fully determine the physical organization of the biofilm. This is because the very implementation of the biological program also leads to many emergent and significant physical mechanisms which also shape the biofilm (Flemming et al., 2016; Karimi et al., 2015). For example, EPS secretion crowds the extracellular surroundings with multicomponent mixtures of biopolymers containing different types of polysaccharides, proteins, lipids, and extracellular DNA (Ghosh et al., 2015). In this crowded macromolecular environment, bacterial cells become subject to new physical forces and interactions. Some prominent examples involve excluded volume (see Box 1) and steric interactions, entropic depletion forces, matrix-mediated attractive bridging interactions, and colloidal osmotic stresses (Ghosh et al., 2015; Worlitzer et al., 2022). Together, these emergent interactions (i) facilitate the creation of physical–chemical gradients, such as those of nutrients, oxygen, and pH; (ii) generate structural, morphological, and topographical patterns, often extending over multiple length and timescales; and (iii) induce phase transitions, which produce the viscoelastic matrix, arrest cellular motility, and immobilize the biofilm. Thus, these physical factors, which arise due to the implementation of the biological program contribute non-trivially to shaping the biofilm organization, and endowing it with novel emergent properties and collective behaviours (Flemming et al., 2016). The synergistic partnership between physical mechanisms and the biological program in determining the organization of biofilms is perhaps best exemplified by a recent observation of iterative feedback between biological and physical processes (Rubinstein et al., 2012). Here, the initiation of the biological program, highlighted by the accumulation of exopolysaccharides in the Bacillus subtilis matrix, gave rise to new physical forces. In particular, rising concentrations of exopolysaccharides in the biofilm creates an osmotic pressure gradient between the cell and the matrix. This in turn alters the biological program by inhibiting the expression of EPS genes. Thus, physical forces (i.e., osmotic stresses) arise as a consequence of a gene-regulated activity (i.e., the production of EPS components), and in turn suppress the very same gene regulatory program in a negative feedback loop. This iterative, biological-physical-biological, collaborative partnership illustrates one of the many intricate relationships between the biological program and physical interactions/mechanisms that emerge during the formation of biofilms. Here, we highlight the perspective that a synergistic- and collaborative partnership, indeed a constant dialogue, between physical forces and the biological program determines the organization, dynamics, and ultimately the fate of the biofilm. We focus on the roles of the biofilm matrix, the biologically prompted secretion of which dynamically introduces new physical–chemical forces and interactions that enhance regulatory networks, enabling biofilm formation, growth, and organization. We consider three distinct classes of matrix-mediated physical processes, whose progression under non-equilibrium conditions play important roles in the formation, growth, and organization of the biofilm. These include: (1) motility-induced phase separation (see Box 1) and depletion interactions in facilitating the transition of bacterial swarms into biofilms; (2) jamming (see Box 1) and gelation in driving the formation of the glassy or viscoelastic EPS matrix; and (3) physical liquid–liquid and liquid–solid phase separation (see Box 1), in determining the spatial organization of the EPS components and generating compositional and thus functional niches within the otherwise unstructured EPS. Many different microbial lifestyles (e.g., planktonic, dense colonies, active swarms) in diverse environments (e.g., bulk fluid, surface-attached bacteria) can switch to the biofilm mode of life (Worlitzer et al., 2022). These lifestyle swaps occur in response to environmental cues and involve the implementation of specific biological programs with changes in gene regulatory processes that alter cellular motility and EPS secretion. As discussed above, these outcomes inevitably introduce new physical forces and mechanisms (Flemming et al., 2016). Nonetheless, how the biological programs and physical forces interact in determining the biofilm fate are only beginning to be understood (Worlitzer et al., 2022). Among the many different microbial lifestyle switches, that of the conversion of an active swarm into a biofilm is particularly interesting, as it involves a drastic transition between opposing and mutually exclusive phenotypes. During this lifestyle switch, an active swarm, which reflects a collective motility state characterized by dynamic patterns, is converted into a sessile, biofilm mode of life (Srinivasan et al., 2019; Verstraeten et al., 2008; Worlitzer et al., 2022). This transition also highlights two opposing scenarios that underscore the complex hierarchy and the sequence of interactions between the biological program and the emergent physical forces (Figure 1). In the crowding-first scenario, it has been suggested that the transition begins with a physical change. According to this view, a non-equilibrium physical process, unique to self-propelled active particles and termed motility-induced phase separation (MIPS), (Cates & Tailleur, 2015) seeds early events. Here, in the dynamic patterns of the active swarm, fluctuations in cell densities can occur spontaneously and randomly. These fluctuations transiently produce small high-density clusters in parts of the swarm in which cells movement slows due to enhanced molecular crowding. These cells accumulate, further increasing the crowding, which further decreases subsequent motion (Be'er & Ariel, 2019). Thus, a positive feedback loop–slowing, accumulating, slowing–thereby drives phase separation and generates two co-existing phases: a low-density phase of swarming cells and high-density clusters of jamming (see Box 1) and immobilizing cells. These high-density clusters of jammed cells are then proposed to initiate the biological program that produces EPS and restricts mobility, thus driving the transition from an active swarm to an immobile biofilm (Grobas et al., 2021; Srinivasan et al., 2019). Such transitions in the bacterial lifestyle and biofilm matrix phases have recently been observed during B. subtilis biofilm formation, and are suggested to be driven by physical interactions between swarming cells (Grobas et al., 2021). The alternative EPS-first scenario regards the biological programs as the primary event driving the lifestyle switch. In this scenario, secreted EPS components, a key part of the biological program, surround the bacterial cells. In this crowded extracellular space, the EPS components act as small depletants and introduce new physical forces (see Box 2). Specifically, as non-adhering molecules in the matrix, they engage in depletion interaction with the bacterial cells. Here, the depletants push bacterial cells to cluster together and undergo phase separation to maximize their own translational entropy (see Box 1). A recent computer simulation confirms this scenario in the context of the swarm-to-biofilm transition. It suggests that the presence of nonadsorbing EPS can lead to the spontaneous aggregation of active bacterial cells through the depletion force, thereby generating nonequilibrium emergent patterns of phase-separation in the bacterial colony (Ghosh et al., 2015). The EPS-first phenomenon was recognized by Asakura and Oosawa (Asakura & Oosawa, 1954; Asakura & Oosawa, 1958). They reasoned that, because the center-of-mass of the depletants cannot approach the larger cells beyond its own radius, a corona of excluded-volume surrounds each of the larger bacterial particles. When large particles approach one another, at distances smaller than their individual excluded-volumes, their coronas begin to overlap, effectively increasing the total space accessible to the center-of-mass of the smaller depletant particle. As a consequence, the depletant entropy increases and the overall free energy of the system decreases. The net result is an osmotic pressure imbalance arising from the difference in the concentration of small depletants, which acts to push the larger particles together (Yodh et al., 2001), giving rise to the depletion force. In summary, the two scenarios above illustrate two processes by which physical interactions and the biological program can interact to guide biofilm creation and organization. A key step in the adoption of the biofilm mode of life is a bacterial microenvironment transformation into a gel-like state, immobilizing bacteria and producing a consolidated community. This transformation is enabled by a component of the biological program (Wolska et al., 2016), which triggers EPS secretion and macromolecular crowding of the bacterial environments (Figure 2). As discussed above, these events introduce new physical forces that drive significant material changes to the system. In addition to the depletion interactions, which aggregate and phase-separate bacterial cells (see above), the crowding of EPS components also densifies the matrix due to their high molecular weights and elevated local concentrations, thereby creating conditions for macromolecular jamming. Here, beyond a threshold concentration of macromolecules, the dynamics are abruptly arrested, kinetically trapping (see Box 1) the system into a fixed state. This non-equilibrium phase transition then converts the bacterial environment into a dense, gel-like matrix, thus completing the biofilm formation. At the molecular level, matrix gelation can occur through a variety of different pathways. A number of disparate mechanisms for this process have been identified including physical entanglements, hydrogen or ionic bond interactions, and intermediate supra-structure formation (Dumitriu, 2004; Ganesan et al., 2013; Ganesan et al., 2016; Kundukad et al., 2017). Below, we highlight two prominent pathways that facilitate EPS gelation, one dominated by physical interactions, and the other involving molecule-specific information transfer. The physical interaction pathway relies on concentration-dependent entanglements and chemical cross-linking (Kim et al., 2013; Zhu et al., 2008). As the concentration of the matrix biopolymers crosses a threshold entanglement concentration, matrix polymers begin to intermingle with one another, forming physical entanglements (Dumitriu, 2004; Ganesan et al., 2013; Ganesan et al., 2016). In addition, specific functional groups of matrix polymers may also form chemical cross-links (with other matrix biopolymers, bacteria, or ions) through localized hydrogen bonding (e.g., OH mediated), ionic (e.g., Ca2+ mediated), or hydrophobic interactions (e.g., CH2 mediated) (Edens, 2005; Limoli et al., 2015). For example, the cationic exopolysaccharides, Pel and Psl, crosslink with eDNA in P. aeruginosa biofilms to form entanglements, (Jennings et al., 2015; Wang et al., 2015) whereas polysaccharide intercellular adhesin (PIA) in Staphylococcus epidermis biofilms self-assembles by associative interactions rather than entanglements, as PIA concentration in S. epidermis biofilms is far less than the entanglement concentration (Ganesan et al., 2016). From a mechanical point of view, it is important to note that the entanglements and crosslinks impart the EPS matrix with different properties. Physical entanglements allow the matrix to transmit, distribute, and share any mechanical forces (e.g., tension) it experiences. Whereas crosslinks serve to prevent disentangling under mechanical stresses. Thus, differential expression of the polysaccharides, Pel and Psl renders P. aeruginosa biofilms either softer or stiffer respectively, enabling for different functional outcomes (Chew et al., 2014; Kundukad et al., 2016). For the molecule-specific information transfer matrix gelation pathway, some molecules (e.g., eDNA and certain polysaccharides) of the biofilm matrix can adopt higher order structures that are important in their abilities to form gels (Stokke, 2019; Tako, 2015; Wilking et al., 2011). Here, the essential information needed to execute matrix gelation is coded in the design of the molecular structure itself. In other words, gelation through this pathway is pre-programmed, and regulated internally by molecule-specific information that is highly prescriptive. In this regard, the pathway resembles the biological program. This pathway is perhaps most prominently expressed by the higher-order organization of eDNA in the EPS matrix. Biofilm matrix eDNA forms highly specific supra-structures. Two major examples include G-quadruplex (Seviour et al., 2021) and Holliday junctions (Devaraj et al., 2019), both of which facilitate matrix gelation (Seviour et al., 2021). The biofilm matrix is a crowded environment with high concentrations of large macromolecules, including exopolysaccharides, eDNA, and proteins. Under these conditions, the matrix constituents experience (i) excluded-volume interactions (arising from the inaccessible space pre-occupied by neighbouring molecules), which reduce the translational mobilities (or diffusion); (ii) steric repulsions, and (iii) short-range depletion attractions, all of which have important consequences as discussed above. Here, we consider another significant influence of the crowded molecular environment of the biofilm matrix, namely its effect on the phase behaviour of the EPS matrix itself. Molecules of the matrix inevitably engage in a variety of intermolecular interactions, both associative and segregative, which act to separate the matrix into complex emulsion consisting of co-existing phases through the thermodynamic tendencies of liquid–liquid or liquid–solid phase separation (LLPS or LSPS). Indeed, these behaviours are reverberating across much of the discipline of eukaryotic cell biology. A recent pioneering study (Li et al., 2012) used a cell-free, in vitro assay to demonstrate interactions between many different polymers (including proteins and RNA) through multivalent associations that give rise to liquid–liquid phase separation, as characterized by micrometre-scale liquid-like droplets in aqueous solution. Another study (Patel et al., 2015) demonstrated that in vitro, the prion-like FUS protein, mutations of which are associated with amyotrophic lateral sclerosis (ALS) disease, also produces micrometre-scale liquid-like droplets. Since these early observations, a large number of disparate cases confirm crowding-induced cytosolic phase separation. Some examples include protein-RNA droplets, such as (i) Cajal bodies (Handwerger et al., 2005) in the nucleus, which play a role in RNA metabolism; (ii) cytoplasmic P-granules in Caenorhabditis elegans, (Brangwynne et al., which are in and (iii) cytoplasmic (Brangwynne et al., which serve as a for In these and other the number of molecules in droplets is only a are to be needed to induce (Brangwynne et al., 2015; et al., 2014; et al., 2012). A shared by these molecules to be the presence of producing & 2005; et al., 2012). Indeed, a recent of studies suggest that the presence of may be a and an for in the cellular context et al., et al., 2021). In this regard, it is that many biofilm proteins that have or that form Some major examples include in Staphylococcus et al., et al., surface in & et al., and in et al., et al., et al., 2015). These proteins are to have roles in facilitating of to proteins, and EPS gelation during the stages of the biofilm. The proteins this by the conformational (i.e., needed to transition into conformational (i.e., structure & that drive their into on the above, we suggest that the functional bacterial also in the context of the EPS matrix & & Such an enable proteins to biofilm matrix formation. this is only beginning to be in the biofilm is a for this with in other formation, which leads to in the and disease, is also by into droplets & et al., proteins and undergo to form droplets under crowded et al., droplets to et al., 2019; et al., 2022). aggregation of in vitro produces et al., 2019). It is thus that in biofilms may also transition through intermediate and contribute to distinct localized that biofilm formation or biofilm protein, otherwise to form structures cell was recently to be a major EPS in an biofilm et al., This also and to produce droplets under crowded These droplets and cells, the for in and formation (Seviour et al., (Figure In addition, the also a We that due to and translational mechanisms (e.g., single extracellular proteins transition through multiple on to effectively multiple For the protein, this include secretion through the cell formation of structures on the cell and through the extracellular matrix, and the of biofilm matrix. it is how the transitions through these the illustrate the to focus on dynamics and phase transitions, rather than a single of the transition in order to the role of extracellular proteins in biofilm and formation. In this we two well physical forces, motility-induced phase separation in shaping bacterial swarms into and the collective transition in shaping the EPS matrix. In the we highlight the collaborative between the biological program and the emerging physical forces, in which one the and The which is by biological different physical which ultimately lead to a jammed gel-like matrix. Here, we highlight the that the information for the transition is not only in the primary sequence of the biopolymers also in the higher-order for G-quadruplex eDNA and kinetically for proteins. between physical–chemical properties of recently bacterial extracellular proteins and and more examples and of eukaryotic we a physical force, namely liquid–liquid or liquid–solid phase separation as a for EPS matrix formation. Here, the crowded biofilm matrix as a environment for large eDNA and to phase separate into heterogeneous to the physical forces and biological cues allow to further the transition into complex biofilm and to the emergent behaviours of EPS matrix biopolymers. they enable a understanding of the biofilm matrix in of phase transition arising from and physical interactions, which in a constant with the program the microbial in a essential and and and and and and and and and The from and of for the that they have of