From Natural Microbe Screening to Sustained Chitinase Activity in Exogenous Hosts.

Genetic parts and hosts can be sourced from nature to realize new functions for synthetic biology or to improve performance in a particular application environment. Here, we proceed from the discovery and characterization of new parts to stable expression in new hosts with a particular focus on achieving sustained chitinase activity. Chitinase is a key enzyme for various industrial applications that require the breakdown of chitin, the second most abundant biopolymer on the earth. Diverse microbes exhibit chitinase activity, but for applications, the environmental conditions for optimal enzyme activity and microbe fitness must align with the application context. Achieving sustained chitinase activity under broad conditions in heterologous hosts has also proven difficult due to toxic side effects. Toward addressing these challenges, we first screen ocean water samples to identify microbes with chitinase activity. Next, we perform whole genome sequencing and analysis and select a chitinase gene for heterologous expression. Then, we optimize transformation methods for target hosts and introduce chitinase. Finally, to achieve robust function, we optimize ribosome binding sites and discover a beneficial promoter that upregulates chitinase expression in the presence of colloidal chitin in a sense-and-respond fashion. We demonstrate chitinase activity for >21 days in standard (Escherichia coli) and nonstandard (Roseobacter denitrificans) hosts. Besides enhancing chitinase applications, our pipeline is extendable to other functions, identifies natural microbes that can be used directly in non-GMO contexts, generates new parts for synthetic biology, and achieves weeks of stable activity in heterologous hosts.

Examining the effect of wound cleansing on the microbiome of venous stasis ulcers.

Common treatment for venous leg wounds includes topical wound dressings with compression. At each dressing change, wounds are debrided and washed; however, the effect of the washing procedure on the wound microbiome has not been studied. We hypothesized that wound washing may alter the wound microbiome. To characterize microbiome changes with respect to wound washing, swabs from 11 patients with chronic wounds were sampled before and after washing, and patient microbiomes were characterized using 16S rRNA sequencing and culturing. Microbiomes across patient samples prior to washing were typically polymicrobial but varied in the number and type of bacterial genera present. Proteus and Pseudomonas were the dominant genera in the study. We found that washing does not consistently change microbiome diversity but does cause consistent changes in microbiome composition. Specifically, washing caused a decrease in the relative abundance of the most highly represented genera in each patient cluster. The finding that venous leg ulcer wound washing, a standard of care therapy, can induce changes in the wound microbiome is novel and could be potentially informative for future guided therapy strategies.

A mixed community of skin microbiome representatives influences cutaneous processes more than individual members.

BACKGROUND: Skin, the largest organ of the human body by weight, hosts a diversity of microorganisms that can influence health. The microbial residents of the skin are now appreciated for their roles in host immune interactions, wound healing, colonization resistance, and various skin disorders. Still, much remains to be discovered in terms of the host pathways influenced by skin microorganisms, as well as the higher-level skin properties impacted through these microbe-host interactions. Towards this direction, recent efforts using mouse models point to pronounced changes in the transcriptional profiles of the skin in response to the presence of a microbial community. However, there is a need to quantify the roles of microorganisms at both the individual and community-level in healthy human skin. In this study, we utilize human skin equivalents to study the effects of individual taxa and a microbial community in a precisely controlled context. Through transcriptomics analysis, we identify key genes and pathways influenced by skin microbes, and we also characterize higher-level impacts on skin processes and properties through histological analyses. RESULTS: The presence of a microbiome on a 3D skin tissue model led to significantly altered patterns of gene expression, influencing genes involved in the regulation of apoptosis, proliferation, and the extracellular matrix (among others). Moreover, microbiome treatment influenced the thickness of the epidermal layer, reduced the number of actively proliferating cells, and increased filaggrin expression. Many of these findings were evident upon treatment with the mixed community, but either not detected or less pronounced in treatments by single microorganisms, underscoring the impact that a diverse skin microbiome has on the host. CONCLUSIONS: This work contributes to the understanding of how microbiome constituents individually and collectively influence human skin processes and properties. The results show that, while it is important to understand the effect of individual microbes on the host, a full community of microbes has unique and pronounced effects on the skin. Thus, in its impacts on the host, the skin microbiome is more than the sum of its parts. Video abstract.

Isolation and characterization of diverse microbial representatives from the human skin microbiome.

BACKGROUND: The skin micro-environment varies across the body, but all sites are host to microorganisms that can impact skin health. Some of these organisms are true commensals which colonize a unique niche on the skin, while open exposure of the skin to the environment also results in the transient presence of diverse microbes with unknown influences on skin health. Culture-based studies of skin microbiota suggest that skin microbes can affect skin properties, immune responses, pathogen growth, and wound healing. RESULTS: In this work, we greatly expanded the diversity of available commensal organisms by collecting > 800 organisms from 3 body sites of 17 individuals. Our collection includes > 30 bacterial genera and 14 fungal genera, with Staphylococcus and Micrococcus as the most prevalent isolates. We characterized a subset of skin isolates for the utilization of carbon compounds found on the skin surface. We observed that members of the skin microbiota have the capacity to metabolize amino acids, steroids, lipids, and sugars, as well as compounds originating from personal care products. CONCLUSIONS: This collection is a resource that will support skin microbiome research with the potential for discovery of novel small molecules, development of novel therapeutics, and insight into the metabolic activities of the skin microbiota. We believe this unique resource will inform skin microbiome management to benefit skin health. Video abstract.

A Stoichioproteomic Analysis of Samples from the Human Microbiome Project.

Ecological stoichiometry (ES) uses organism-specific elemental content to explain differences in species life histories, species interactions, community organization, environmental constraints and even ecosystem function. Although ES has been successfully applied to a range of different organisms, most emphasis on microbial ecological stoichiometry focuses on lake, ocean, and soil communities. With the recent advances in human microbiome research, however, large amounts of data are being generated that describe differences in community composition across body sites and individuals. We suggest that ES may provide a framework for beginning to understand the structure, organization, and function of human microbial communities, including why certain organisms exist at certain locations, and how they interact with both the other microbes in their environment and their human host. As a first step, we undertake a stoichioproteomic analysis of microbial communities from different body sites. Specifically, we compare and contrast the elemental composition of microbial protein samples using annotated sequencing data from 690 gut, vaginal, oral, nares, and skin samples currently available through the Human Microbiome Project. Our results suggest significant differences in both the median and variance of the carbon, oxygen, nitrogen, and sulfur contents of microbial protein samples from different locations. For example, whereas proteins from vaginal sites are high in carbon, proteins from skin and nasal sites are high in nitrogen and oxygen. Meanwhile, proteins from stool (the gut) are particularly high in sulfur content. We interpret these differences in terms of the local environments at different human body sites, including atmospheric exposure and food intake rates.

Preservation of protein expression systems at elevated temperatures for portable therapeutic production.

Many biotechnology capabilities are limited by stringent storage needs of reagents, largely prohibiting use outside of specialized laboratories. Focusing on a large class of protein-based biotechnology applications, we address this issue by developing a method for preserving cell-free protein expression systems for months above room temperature. Our approach realizes unprecedented long-term stability at elevated temperatures by leveraging the sugar alcohol trehalose, a simple, low-cost, open-air drying step, and strategic separation of reaction components during drying. The resulting preservation capacity enables efficient production of a wide range of on-demand proteins under adverse conditions, for instance during emergency outbreaks or in remote locations. To demonstrate application potential, we use cell-free reagents subjected to months of exposure at 37°C and atmospheric conditions to produce sufficient concentrations of a pyocin protein to kill Pseudomonas aeruginosa, a troublesome pathogen for traumatic and burn wound injuries. Our work makes possible new biotechnology applications that demand ruggedness and scalability.

Cell-free synthetic biology for environmental sensing and remediation.

The fields of biosensing and bioremediation leverage the phenomenal array of sensing and metabolic capabilities offered by natural microbes. Synthetic biology provides tools for transforming these fields through complex integration of natural and novel biological components to achieve sophisticated sensing, regulation, and metabolic function. However, the majority of synthetic biology efforts are conducted in living cells, and concerns over releasing genetically modified organisms constitute a key barrier to environmental applications. Cell-free protein expression systems offer a path towards leveraging synthetic biology, while preventing the spread of engineered organisms in nature. Recent efforts in the areas of cell-free approaches for sensing, regulation, and metabolic pathway implementation, as well as for preserving and deploying cell-free expression components, embody key steps towards realizing the potential of cell-free systems for environmental sensing and remediation.

Invasion speeds in microbial systems with toxin production and quorum sensing.

The theory of invasions and invasion speeds has traditionally been studied in macroscopic systems. Surprisingly, microbial invasions have received less attention. Although microbes share many of the features associated with competition between larger-bodied organisms, they also exhibit distinctive behaviors that require new mathematical treatments to fully understand invasions in microbial systems. Most notable is the possibility for long-distance interactions, including competition between populations mediated by diffusible toxins and cooperation among individuals of a single population using quorum sensing. In this paper, we model bacterial invasion using a system of coupled partial differential equations based on Fisher's equation. Our model considers a competitive system with diffusible toxins that, in some cases, are expressed in response to quorum sensing. First, we derive analytical approximations for invasion speeds in the limits of fast and slow toxin diffusion. We then test the validity of our analytical approximations and explore intermediate rates of toxin diffusion using numerical simulations. Interestingly, we find that toxins should diffuse quickly when used offensively, but that there are two optimal strategies when toxins are used as a defense mechanism. Specifically, toxins should diffuse quickly when their killing efficacy is high, but should diffuse slowly when their killing efficacy is low. Our approach permits an explicit investigation of the properties and characteristics of diffusible compounds used in non-local competition, and is relevant for microbial systems and select macroscopic taxa, such as plants and corals, that can interact through biochemicals.

Antibiotics as a selective driver for conjugation dynamics.

It is generally assumed that antibiotics can promote horizontal gene transfer. However, because of a variety of confounding factors that complicate the interpretation of previous studies, the mechanisms by which antibiotics modulate horizontal gene transfer remain poorly understood. In particular, it is unclear whether antibiotics directly regulate the efficiency of horizontal gene transfer, serve as a selection force to modulate population dynamics after such gene transfer has occurred, or both. Here, we address this question by quantifying conjugation dynamics in the presence and absence of antibiotic-mediated selection. Surprisingly, we find that sublethal concentrations of antibiotics from the most widely used classes do not significantly increase the conjugation efficiency. Instead, our modelling and experimental results demonstrate that conjugation dynamics are dictated by antibiotic-mediated selection, which can both promote and suppress conjugation dynamics. Our findings suggest that the contribution of antibiotics to the promotion of horizontal gene transfer may have been overestimated. These findings have implications for designing effective antibiotic treatment protocols and for assessing the risks of antibiotic use.

Multi-input regulation and logic with T7 promoters in cells and cell-free systems.

Engineered gene circuits offer an opportunity to harness biological systems for biotechnological and biomedical applications. However, reliance on native host promoters for the construction of circuit elements, such as logic gates, can make the implementation of predictable, independently functioning circuits difficult. In contrast, T7 promoters offer a simple orthogonal expression system for use in a variety of cellular backgrounds and even in cell-free systems. Here we develop a T7 promoter system that can be regulated by two different transcriptional repressors for the construction of a logic gate that functions in cells and in cell-free systems. We first present LacI repressible T7lacO promoters that are regulated from a distal lac operator site for repression. We next explore the positioning of a tet operator site within the T7lacO framework to create T7 promoters that respond to tet and lac repressors and realize an IMPLIES gate. Finally, we demonstrate that these dual input sensitive promoters function in an E. coli cell-free protein expression system. Our results expand the utility of T7 promoters in cell based as well as cell-free synthetic biology applications.

Probing cell-free gene expression noise in femtoliter volumes.

Cell-free systems offer a simplified and flexible context that enables important biological reactions while removing complicating factors such as fitness, division, and mutation that are associated with living cells. However, cell-free expression in unconfined spaces is missing important elements of expression in living cells. In particular, the small volume of living cells can give rise to significant stochastic effects, which are negligible in bulk cell-free reactions. Here, we confine cell-free gene expression reactions to cell-relevant 20 fL volumes (between the volumes of Escherichia coli and Saccharomyces cerevisiae ), in polydimethylsiloxane (PDMS) containers. We demonstrate that expression efficiency varies widely among different containers, likely due to non-Poisson distribution of expression machinery at the observed scale. Previously, this phenomenon has been observed only in liposomes. In addition, we analyze gene expression noise. This analysis is facilitated by our use of cell-free systems, which allow the mapping of the measured noise properties to intrinsic noise models. In contrast, previous live cell noise analysis efforts have been complicated by multiple noise sources. Noise analysis reveals signatures of translational bursting, while noise dynamics suggest that overall cell-free expression is limited by a diminishing translation rate. In addition to offering a unique approach to understanding noise in gene circuits, our work contributes to a deeper understanding of the biophysical properties of cell-free expression systems, thus aiding efforts to harness cell-free systems for synthetic biology applications.

Expression optimization and synthetic gene networks in cell-free systems.

Synthetic biology offers great promise to a variety of applications through the forward engineering of biological function. Most efforts in this field have focused on employing living cells, yet cell-free approaches offer simpler and more flexible contexts. Here, we evaluate cell-free regulatory systems based on T7 promoter-driven expression by characterizing variants of TetR and LacI repressible T7 promoters in a cell-free context and examining sequence elements that determine expression efficiency. Using the resulting constructs, we then explore different approaches for composing regulatory systems, leading to the implementation of inducible negative feedback in Escherichia coli extracts and in the minimal PURE system, which consists of purified proteins necessary for transcription and translation. Despite the fact that negative feedback motifs are common and essential to many natural and engineered systems, this simple building block has not previously been implemented in a cell-free context. As a final step, we then demonstrate that the feedback systems developed using our cell-free approach can be implemented in live E. coli as well, illustrating the potential for using cell-free expression to fast track the development of live cell systems in synthetic biology. Our quantitative cell-free component characterizations and demonstration of negative feedback embody important steps on the path to harnessing biological function in a bottom-up fashion.

Model for biological communication in a nanofabricated cell-mimic driven by stochastic resonance.

Cells offer natural examples of highly efficient networks of nanomachines. Accordingly, both intracellular and intercellular communication mechanisms in nature are looked to as a source of inspiration and instruction for engineered nanocommunication. Harnessing biological functionality in this manner requires an interdisciplinary approach that integrates systems biology, synthetic biology, and nanofabrication. Here, we present a model system that exemplifies the synergism between these realms of research. We propose a synthetic gene network for operation in a nanofabricated cell mimic array that propagates a biomolecular signal over long distances using the phenomenon of stochastic resonance. Our system consists of a bacterial quorum sensing signal molecule, a bistable genetic switch triggered by this signal, and an array of nanofabricated cell mimic wells that contain the genetic system. An optimal level of noise in the system helps to propagate a time-varying AHL signal over long distances through the array of mimics. This noise level is determined both by the system volume and by the parameters of the genetic network. Our proposed genetically driven stochastic resonance system serves as a testbed for exploring the potential harnessing of gene expression noise to aid in the transmission of a time-varying molecular signal.

Noise in biological circuits.

Noise biology focuses on the sources, processing, and biological consequences of the inherent stochastic fluctuations in molecular transitions or interactions that control cellular behavior. These fluctuations are especially pronounced in small systems where the magnitudes of the fluctuations approach or exceed the mean value of the molecular population. Noise biology is an essential component of nanomedicine where the communication of information is across a boundary that separates small synthetic and biological systems that are bound by their size to reside in environments of large fluctuations. Here we review the fundamentals of the computational, analytical, and experimental approaches to noise biology. We review results that show that the competition between the benefits of low noise and those of low population has resulted in the evolution of genetic system architectures that produce an uneven distribution of stochasticity across the molecular components of cells and, in some cases, use noise to drive biological function. We review the exact and approximate approaches to gene circuit noise analysis and simulation, and review many of the key experimental results obtained using flow cytometry and time-lapse fluorescent microscopy. In addition, we consider the probative value of noise with a discussion of using measured noise properties to elucidate the structure and function of the underlying gene circuit. We conclude with a discussion of the frontiers of and significant future challenges for noise biology.

Tying new knots in synthetic biology.

Recent years have seen the emergence of synthetic biology, which encompasses the engineering of living organisms as well as the implementation of biological behavior in non-living substrates. Many of these engineered systems have harnessed the diverse toolkit of proteins, genes, and cellular processes that nature offers. While these efforts have been fruitful, they have also illustrated the difficulty associated with programming highly complex functions by tapping into cellular processes. Another set of efforts has focused on building circuits, performing computation, and constructing nanoscale machines using nucleic acids. Zhang et al., 2007, Science 318, 1121-1125 and Yin et al., 2008, Nature 451, 318-322 recently demonstrated flexible approaches for the modular construction of such biochemical devices exclusively using DNA. These approaches have exciting implications both for engineering living cells and for mimicking life-like behavior at the nanoscale.

Engineered bidirectional communication mediates a consensus in a microbial biofilm consortium.

Microbial consortia form when multiple species colocalize and communally generate a function that none is capable of alone. Consortia abound in nature, and their cooperative metabolic activities influence everything from biodiversity in the global food chain to human weight gain. Here, we present an engineered consortium in which the microbial members communicate with each other and exhibit a "consensus" gene expression response. Two colocalized populations of Escherichia coli converse bidirectionally by exchanging acyl-homoserine lactone signals. The consortium generates the gene-expression response if and only if both populations are present at sufficient cell densities. Because neither population can respond without the other's signal, this consensus function can be considered a logical AND gate in which the inputs are cell populations. The microbial consensus consortium operates in diverse growth modes, including in a biofilm, where it sustains its response for several days.

Synthetic biology: new engineering rules for an emerging discipline.

Synthetic biologists engineer complex artificial biological systems to investigate natural biological phenomena and for a variety of applications. We outline the basic features of synthetic biology as a new engineering discipline, covering examples from the latest literature and reflecting on the features that make it unique among all other existing engineering fields. We discuss methods for designing and constructing engineered cells with novel functions in a framework of an abstract hierarchy of biological devices, modules, cells, and multicellular systems. The classical engineering strategies of standardization, decoupling, and abstraction will have to be extended to take into account the inherent characteristics of biological devices and modules. To achieve predictability and reliability, strategies for engineering biology must include the notion of cellular context in the functional definition of devices and modules, use rational redesign and directed evolution for system optimization, and focus on accomplishing tasks using cell populations rather than individual cells. The discussion brings to light issues at the heart of designing complex living systems and provides a trajectory for future development.