Synthetic biology in biofilms: Tools, challenges, and opportunities

Abstract

The field of synthetic biology seeks to program living cells to perform novel functions with applications ranging from environmental biosensing to smart cell‐based therapeutics. Bacteria are an especially attractive chassis organism due to their rapid growth, ease of genetic manipulation, and ability to persist across many environmental niches. Despite significant progress in bacterial synthetic biology, programming bacteria to perform novel functions outside the well‐controlled laboratory context remains challenging. In contrast to planktonic laboratory growth, bacteria in nature predominately reside in the context of densely packed communities known as biofilms. While biofilms have historically been considered environmental and biomedical hazards, their physiology and emergent behaviors could be leveraged for synthetic biology to engineer more capable and robust bacteria. Specifically, bacteria within biofilms participate in complex emergent behaviors such as collective organization, cell‐to‐cell signaling, and division of labor. Understanding and utilizing these properties can enable the effective deployment of engineered bacteria into natural target environments. Toward this goal, this review summarizes the current state of synthetic biology in biofilms by highlighting new molecular tools and remaining biological challenges. Looking to future opportunities, advancing synthetic biology in biofilms will enable the next generation of smart cell‐based technologies for use in medicine, biomanufacturing, and environmental remediation.

Ecological firewalls for synthetic biology

“…Such a strategy can be one of the most optimal ways of cooperation in environments such as rivers or the surface of the ocean (on plastic debris). Because of their prevalence in both natural and anthropogenic environments and their robust structural properties (that favor for example division of labor and enhanced persistence), they are becoming a major target for synthetic biology [ Tran and Prindle, 2021 ; Kassinger and van Hoek, 2020 ].…”

“…As we can see, a low- S coexistence attractor dominates the parameter space, where higher ECM production, along with the nonlinear interactions associated with biofilm formation, provides the desired firewall for the synthetic population. As mentioned earlier, one relevant application of this EFW is environmental bioremediation, where our synthetic strain would help with the removal hazardous components (from drugs in waste waters to heavy metals) that would end up safely stored in the extracellular matrix of the biofilm (see [ Tran and Prindle, 2021 ] and references cited).…”

Ecological Firewalls for Synthetic Biology

“…By contrast, the bacteria surrounded by the biofilm should be more stressed due to nutrient deprivation. Because of their prevalence in natural environments and their robust structural properties (that favour for example division of labour and enhanced persistence) they are becoming a major target for synthetic biology [46,89].…”

“…As we can see, a low-S coexistence attractor dominates the parameter spece, where higher synthetsis of extra cellular matrix ECM), along with the nonlinear interactions associated with biofilm formation, provides the desired firewall for the synthetic population. As mentioned above, one relevant application of this EFW is environmental bioremediation, where our synthetic strain would help with the removal hazardous components (from drugs in waste waters to heavy metals) that would end up safely stored in the extracellular matrix of the biofilm (see [89] and references cited).…”

Oral Osteomicrobiology: The Role of Oral Microbiota in Alveolar Bone Homeostasis

“…Therefore, the following requirements should be considered when selecting the microbial communities: there must be variation between competing communities in terms of community traits, communities must be able to replicate, and the community trait must be heritable ( Buss, 1983 ). Furthermore, it has recently become possible to automate synthetic microbiome design ( Tran and Prindle, 2021 ). For example, computer-guided design has been used to select optimal microbial consortia that promote the activation of regulatory T cells in a gut microbiota-immune system model ( Stein et al., 2018 ).…”