Microorganisms do not work alone but instead function as collaborative microsocieties. The spatial distribution of different bacterial strains (micro-biogeography) in a shared volumetric space and their degree of intimacy greatly influences their societal behavior. Current microbiological techniques are commonly focused on the culture of well-mixed bacterial communities and fail to reproduce the micro-biogeography of polybacterial societies.
Here, theybioprinted fine-scale bacterial microcosms using chaotic flows induced by a printhead containing a static mixer. This straightforward approach (i.e., continuous chaotic bacterial bioprinting) enables the fabrication of hydrogel constructs with intercalated layers of bacterial strains. These multilayered constructs are used to analyze how the spatial distributions of bacteria affect their social behavior. For example, they show that bacteria within these biological microsystems engage in either cooperation or competition, depending on the degree of shared interface. The extent of inhibition in predator–prey scenarios (i.e., probiotic–pathogen bacteria) increases when bacteria are in greater intimacy. Furthermore, two Escherichia coli strains exhibit competitive behavior in well-mixed microenvironments, whereas stable coexistence prevails for longer times in spatially structured communities.
They anticipate that chaotic bioprinting will contribute to the development of greater complexity of polybacterial microsystems, tissue-microbiota models, and biomanufactured materials.
Microorganisms do not work alone but instead function in highly dynamic societies in which members collaborate and/or compete. A growing body of evidence demonstrates that the spatial distribution in microbial societies also matters. Micro-biogeography, the spatial patterns of microbial communities through time and space,greatly influences the dynamics of microbial ecosystems. In turn, the emergence of any particular microgeography depends on gradients in the local microenvironment (i.e., variations in temperature, oxygen concentration, pH, and nutrients) that often are induced by the concerted acting of microorganisms.
(A) A single KSM element seen from two view angles. (B) Illustration of a multilamellar pattern developed by the successive splitting and folding of bioinks at each mixing element. (C) Schematic diagram of the procedure for bioprinting and culture microcosms-containing fibers using a printhead equipped with 3-KSM elements. The outlet of the KSM printhead must be immersed in the calcium chloride (CaCl2) solution. A cross-section of a printed fiber is shown. Scale bar: 500 μm. (D) Printheads containing different numbers of KSM elements and representative micrographs of the micro-biogeographies produced. (E) Quantification of the DSI at each micro-biogeography. ***p-value < 0.001 (n = 3).
This interplay between micro-biogeography and societal function has diverse examples in nature. For instance, in the plant kingdom, trees host microcommunities with structured micro-biogeographies, such as lung lichens made of bacteria, algae, and fungi. Associations of algae and bacteria have been observed in lichen cross sections, forming 30-μm-wide interspersed lamellae. In biofilms, bacteria form aggregates made of mono- or polybacterial species that play distinct roles according to their phenotypes.When bacteria at the periphery cause a depletion of available substrates at the interior, the inner cells starve and interrupt the synthesis of metabolites that are vital for their counterparts on the outside. This dynamic leads to spatiotemporal variations in the bacterial community.
(A) Axial view of a fiber printed using three KSM elements. Scale bar: 1000 μm. (B) Cross-sectional cuts of the same fiber at different lengths exhibit a conserved multilamellar pattern. Scale bar: 500 μm. (C) Mirror-like projections of homologous lamellae marked by the same number (I and II), and CFD simulation of the cross-sectional microstructure after 3-KSM elements (III). (D) The individual and total (Σ) areas of red and black striations among seven cross-sectional cuts obtained experimentally. Nonsignificant difference (n.s.) at p-value < 0.05 (n = 7).
Similarly, the distribution and composition of human microbiota vary across different body habitats.In caries and periodontal pockets, mosaic architectures of biofilms emerge due to the presence of anaerobes in the interior and aero-tolerant taxa on the exterior, creating hedgehog, corncob, and cauliflower-like microstructures. An improved understanding of microbiota organization on teeth, for example, may help in developing more efficient dental therapies.
(A) Cross-section of the micro-biogeographies containing RFP-expressing E. coli (EcRFP; red) and LGG (black), chaotically printed using 1-, 3-, or 6-KSM elements (scale bar: 500 μm). (B) Coculture viability over a 12 h duration, normalized by the number of colony-forming units (CFUs) just after bioprinting. (C) SEM micrographs showing the invasion of EcRFP neighborhoods by LGG, in constructs printed using 1- (I) and 3- (II) KSM elements. *p-value < 0.05; **p-value < 0.001; ***p-value < 0.001 (n = 6).
In the gut, the micro-biogeography is also very complex and dynamic. A large variety of symbiotic microorganisms coexist in digestive tract of mammals. Their interactions and their interplay with host cells play a crucial role in health and disease. However, the microbiota is not “well-mixed” but stratified and segregated to accomplish complex societal functions.
(A) Cross-section of micro-biogeographies containing EcRFP (red) and EcGFP (green), chaotically bioprinted using 10-, 6-, 3-, or 1-KSM elements (scale bar: 500 μm). (B) Viability of EcRFP and EcGFP for 48 h, normalized by the number of CFUs just after bioprinting (X0). One plot per micro-biogeography. *p-value < 0.05; **p-value < 0.001; ***p-value < 0.001 (n = 6).
Among the many factors that govern the degree of interaction between different organisms in a bacterial society, the extent of segregation or mixing and the degree of shared interface has proven to be highly relevant.Nevertheless, conventional microbiological culture techniques fail to generate these complex microarchitectures of bacteria and substrates, thereby limiting the study of the effects of spatial variations on the societal dynamics of microbial communities. One strategy to address this issue is to use biofabrication techniques, such as bioprinting, micromolding, photolithography patterning, and microfluidics-based manufacturing in microbiology. Hynes et al. accommodated spatially distinct aggregates of Escherichia coli and Salmonella enterica using a casting-based method and suggested that interactions in this consortium may be influenced by spatial scales. Similarly, Chen et al. used photolithography to create patterns in adhesion polymers at a resolution of 10 μm. The patterns were subsequently used for specific anchoring of E. coli at those locations, and the authors then monitored bacterial crosstalk using a reporter gene activated by the high cell concentration in neighboring fronts. Qian et al. used an extrusion-based system to print diverse 3D geometries with a 200 μm resolution for biomanufacturing purposes. Lattice-shaped scaffolds containing Saccharomyces cerevisiae were capable of a continuous synthesis of ethanol not possible when these organisms were cultured in solid layers. This difference presumably arose because the porosity of the latticed scaffolds facilitated mass transfer. However, often these technologies demand sophisticated equipment, are labor intensive, require technical expertise to be built or operated, or exhibit a modest throughput.
In this contribution, they show that continuous chaotic bioprinting is a versatile, cost-effective, user-friendly, and high-throughput microbiology tool for creating bacterial microsystems with a printing resolution of a few tens of micrometers.
In addition, they show that their printed microcosms are alive, and dynamic eco-systems respond to the printed micro-biogeography; the degree of shared interface between two distinct microbial communities greatly matters to determine the dynamics of competition in the entire microsystem. They first demonstrate that bacterial viability inhibition is strongly influenced by the degree of intimacy between two distinct bacterial strains. They then show that even cells from the same species may exhibit competition, depending on their spatial distribution1.