Mechanobiology as a tool for addressing the genotype-to-phenotype problem in microbiology

Abstract

The central hypothesis of the genotype-phenotype relationship is that the phenotype of a developing organism (i.e., its set of observable attributes) depends on its genome and the environment. However, as we learn more about the genetics and biochemistry of living systems, our understanding does not fully extend to the complex multiscale nature of how cells move, interact, and organize; this gap in understanding is referred to as the genotype-to-phenotype problem. The physics of soft matter sets the background on which living organisms evolved, and the cell environment is a strong determinant of cell phenotype. This inevitably leads to challenges as the full function of many genes, and the diversity of cellular behaviors cannot be assessed without wide screens of environmental conditions. Cellular mechanobiology is an emerging field that provides methodologies to understand how cells integrate chemical and physical environmental stress and signals, and how they are transduced to control cell function. Biofilm forming bacteria represent an attractive model because they are fast growing, genetically malleable and can display sophisticated self-organizing developmental behaviors similar to those found in higher organisms. Here, we propose mechanobiology as a new area of study in prokaryotic systems and describe its potential for unveiling new links between an organism's genome and phenome.

FIG. 1.

Causal web of the genotype-to-phenotype problem: genetic instructions stored as DNA are expressed as phenotypes of collective living systems, but this occurs through a cyclical network of cause and effect. Specific genes are expressed either to run necessary cellular functions or in response to signals from outside the cell. These changes in gene expression alter the behavior of individual cells and may also produce signaling molecules that influence the gene expression of neighboring cells. These collective changes in behavior can, in turn, influence the quantity and characteristics of the cell-to-cell signals—for instance by changing cell motility—or even alter the local environment—for instance by excreting extracellular matrix compounds. These feedback signals allow the collective behavior to evolve over time into the resultant, emerging phenotype.

FIG. 2.

Mechanistic insights into the formation of bacterial biofilm and tools of characterization. The blue arrow denotes tools for morphological and mechanical properties assessment and the green arrow depicts tools for molecular mechanism detection. Numbers 1–5 depict sequence of events in the multicellular formation of bacteria colonies. The first step is bacteria making contact with a surface. Mechanosensing involves the transduction of mechanical input (surface contact) to a bacterial response and activation of distinct cellular machineries. Upon surface contact, biofilm formation commences by active import and release of ions, target gene activation and repression, production of EPS matrix, and intracellular signaling, migration, proliferation, and cell–cell communication. Environmental features that impact multicellular bacteria pattern formation include surface stiffness, roughness, adhesion, and surface tension, as well as ambient fluid flow that may be turbulent or laminar.

FIG. 3.

Effects of agar concentration on single cell and multicellular colony morphology. (a) The bacterium Proteus mirabilis forms swarming colonies on nutrient-rich low-concentration agar (1.5% agar) surfaces. Increasing agar changes the population morphology with the emergence of structured colony terraces and restricted growth above 2.5% agar. (b) Phase contrast images of cells as a function of increasing agar concentration. (c) Cell length increases with increasing agar concentration. Figure adopted from Ref. . Reproduced with permission from Little et al., J. Bacteriol. 201, e00726-00718 (2019). Copyright 2019 Authors, licensed under a Creative Commons Attribution (CC BY) license.

FIG. 4.

Bacterial motility. (a) Swimming motility powered by the rotation of bacterial flagella. (b) Twitching motility powered by the retraction of pili adhered to a solid surface. (c) Gliding motility, which in Myxococcus xanthus is powered by the rotation of a helical cytoskeletal track, moving the cell along a slime-coated surface, like a corkscrew tank. (d) Top-down image of B. subtilis colony. The biofilm is a more slowly growing colony than a bacterial swarm. In the biofilm, the bacteria produce extracellular polymeric substances, creating a semisolid matrix around the cells. Image adopted from Ref. . Reproduced with permission from Hou et al., npj Biofilms Microbiomes 7, 2 (2021). Copyright 2021 Authors, licensed under a Creative Commons Attribution (CC BY) license. (e) Swarming Serratia marcescens colony. Image shows the characteristic vortex patterns exhibited during swarming motility.

FIG. 5.

Bulk rheology of biofilms. (a) Bulk rheology of biofilms can be performed by growing up many bacteria colonies and gathering them as one sample on the rheometer plate, as shown for V. cholerae biofilms (b) Biofilms exhibit viscoelastic behavior, characterized by a shear storage modulus G′ and a viscous loss modulus G″. For low shear strains, the biofilm has a nearly constant shear modulus (∼1000 Pa), which begins to decrease above a critical shear strain value. This is referred to as a yielding point, above which more strain makes the sample softer and more viscous-like. Figure adopted from Ref. . Reproduced with permission from Yan et al., Adv. Mater. 30, 1804153 (2018). Copyright 2018 Authors, licensed under a Creative Commons Attribution (CC BY) license.

FIG. 6.

AFM characterization of bacteria appendages. (a) Electron micrograph image of type I pili in uropathogenic E. coli. (b) Schematic of experimental setup with AFM cantilever tip gripping a type 1 pili filament. (c) Force-extension curve showing a force plateau that corresponds to unwinding of the pilus sub-units at a constant force. Figure adopted from Ref. . Reproduced with permission from Miller et al., Biophys. J. 91, 3848 (2006). Copyright 2006 Authors, licensed under a Creative Commons Attribution (CC BY) license.

FIG. 7.

Effect of substrate stiffness on bacteria colony expansion. (a) Characterization of Serratia marcescens colony expansion on soft and stiff agar substrates vs soft and stiff synthetic polyacrylamide (PAA) substrates. While colony growth is slower on denser, stiffer agar, colony expansion increases with increasing stiffness on linearly elastic PAA gels. (b) Displacement of the substrates are monitored via fiducial markers, allowing computation of a corresponding (c) stress map. (d) The stress generated by the bacteria colony is greater on stiff PAA substrates (G′ = 5 kPa) compared to soft ones (G′ = 0.5 kPa). Figure adopted from Ref. . Reproduced with permission from Asp et al., PNAS Nexus, 1, pgac025 (2022). Copyright 2022 Authors, licensed under a Creative Commons Attribution (CC BY) license.

FIG. 8.

Effects of substrate stiffness on host cell invasion. Multiple studies have shown that increased matrix stiffness increases the number of host cells infected by bacteria pathogens. Host cells change their morphology and behavior on stiff substrates, in many aspects making them more susceptible to bacteria invasion. For instance, when cultured on stiff substrates compared to soft ones, endothelial cells express more extracellular attachment factors, such as extracellular vimentin, that bind bacteria and facilitate host cell uptake. Further, the host cell actin cytoskeleton—which is more prominent on stiff substrates—colocalizes at sites of bacteria invasion. While more host cells are infected on stiff substrates, the number of bacteria in infected cells can actually be higher on soft substrates. This may be due in part to endosomal escape, which is significantly more prevalent for host cells cultured on physiologically soft substrates compared to rigid glass or tissue culture plastic.