A formalized design process for bacterial consortia that perform logic computing

Harnessing Microbial Signal Transduction Systems in Natural and Synthetic Consortia for Biotechnological Applications

Signal transduction is crucial for communication and cellular response in microbial communities. Consortia rely on it for effective communication, responding to changing environmental conditions, establishing community structures, and performing collective behaviors. Microbial signal transduction can be through quorum sensing (QS), two-component signal transduction systems, biofilm formation, nutrient sensing, chemotaxis, horizontal gene transfer stress response, and so forth. The consortium uses small signaling molecules in QS to regulate gene expression and coordinate intercellular communication and behaviors. Biofilm formation allows cells to adhere and aggregate, promoting species interactions and environmental stress resistance. Chemotaxis enables directional movement toward or away from chemical gradients, promoting efficient resource utilization and community organization within the consortium. In recent years, synthetic microbial consortia have gained attention for their potential applications in biotechnology and bioremediation. Understanding signal transduction in natural and synthetic microbial consortia is important for gaining insights into community dynamics, evolution, and ecological function. It can provide strategies for biotechnological innovation for enhancing biosensors, biodegradation, bioenergy efficiency, and waste reduction. This review provides compelling insight that will advance our understanding of microbial signal transduction dynamics and its role in orchestrating microbial interactions, which facilitate coordination, cooperation, gene expression, resource allocation, and trigger specific responses that determine community success.

Implementing re-configurable biological computation with distributed multicellular consortia

The use of synthetic biological circuits to deal with numerous biological challenges has been proposed in several studies, but its implementation is still remote. A major problem encountered is the complexity of the cellular engineering needed to achieve complex biological circuits and the lack of general-purpose biological systems. The generation of re-programmable circuits can increase circuit flexibility and the scalability of complex cell-based computing devices. Here we present a new architecture to produce reprogrammable biological circuits that allow the development of a variety of different functions with minimal cell engineering. We demonstrate the feasibility of creating several circuits using only a small set of engineered cells, which can be externally reprogrammed to implement simple logics in response to specific inputs. In this regard, depending on the computation needs, a device composed of a number of defined cells can generate a variety of circuits without the need of further cell engineering or rearrangements. In addition, the inclusion of a memory module in the circuits strongly improved the digital response of the devices. The reprogrammability of biological circuits is an intrinsic capacity that is not provided in electronics and it may be used as a tool to solve complex biological problems.

Interleukin-17A: The Key Cytokine in Neurodegenerative Diseases

Neurodegenerative diseases are characterized by the loss of neurons and/or myelin sheath, which deteriorate over time and cause dysfunction. Interleukin 17A is the signature cytokine of a subset of CD4⁺ helper T cells known as Th17 cells, and the IL-17 cytokine family contains six cytokines and five receptors. Recently, several studies have suggested a pivotal role for the interleukin-17A (IL-17A) cytokine family in human inflammatory or autoimmune diseases and neurodegenerative diseases, including psoriasis, rheumatoid arthritis (RA), Alzheimer’s disease (AD), Parkinson’s disease (PD), multiple sclerosis (MS), amyotrophic lateral sclerosis (ALS), and glaucoma. Studies in recent years have shown that the mechanism of action of IL-17A is more subtle than simply causing inflammation. Although the specific mechanism of IL-17A in neurodegenerative diseases is still controversial, it is generally accepted now that IL-17A causes diseases by activating glial cells. In this review article, we will focus on the function of IL-17A, in particular the proposed roles of IL-17A, in the pathogenesis of neurodegenerative diseases.

Distributed Implementation of Boolean Functions by Transcriptional Synthetic Circuits

Starting in the early 2000s, sophisticated technologies have been developed for the rational construction of synthetic genetic networks that implement specified logical functionalities. Despite impressive progress, however, the scaling necessary in order to achieve greater computational power has been hampered by many constraints, including repressor toxicity and the lack of large sets of mutually orthogonal repressors. As a consequence, a typical circuit contains no more than roughly seven repressor-based gates per cell. A possible way around this scalability problem is to distribute the computation among multiple cell types, each of which implements a small subcircuit, which communicate among themselves using diffusible small molecules (DSMs). Examples of DSMs are those employed by quorum sensing systems in bacteria. This paper focuses on systematic ways to implement this distributed approach, in the context of the evaluation of arbitrary Boolean functions. The unique characteristics of genetic circuits and the properties of DSMs require the development of new Boolean synthesis methods, distinct from those classically used in electronic circuit design. In this work, we propose a fast algorithm to synthesize distributed realizations for any Boolean function, under constraints on the number of gates per cell and the number of orthogonal DSMs. The method is based on an exact synthesis algorithm to find the minimal circuit per cell, which in turn allows us to build an extensive database of Boolean functions up to a given number of inputs. For concreteness, we will specifically focus on circuits of up to 4 inputs, which might represent, for example, two chemical inducers and two light inputs at different frequencies. Our method shows that, with a constraint of no more than seven gates per cell, the use of a single DSM increases the total number of realizable circuits by at least 7.58-fold compared to centralized computation. Moreover, when allowing two DSM's, one can realize 99.995% of all possible 4-input Boolean functions, still with at most 7 gates per cell. The methodology introduced here can be readily adapted to complement recent genetic circuit design automation software. A toolbox that uses the proposed algorithm was created and made available at https://github.com/sontaglab/DBC/.

Pathways to cellular supremacy in biocomputing

Synthetic biology uses living cells as the substrate for performing human-defined computations. Many current implementations of cellular computing are based on the “genetic circuit” metaphor, an approximation of the operation of silicon-based computers. Although this conceptual mapping has been relatively successful, we argue that it fundamentally limits the types of computation that may be engineered inside the cell, and fails to exploit the rich and diverse functionality available in natural living systems. We propose the notion of “cellular supremacy” to focus attention on domains in which biocomputing might offer superior performance over traditional computers. We consider potential pathways toward cellular supremacy, and suggest application areas in which it may be found.

Synthetic biology uses cells as its computing substrate, often based on the genetic circuit concept. In this Perspective, the authors argue that existing synthetic biology approaches based on classical models of computation limit the potential of biocomputing, and propose that living organisms have under-exploited capabilities.

Characterization of diverse homoserine lactone synthases in Escherichia coli

Quorum sensing networks have been identified in over one hundred bacterial species to date. A subset of these networks regulate group behaviors, such as bioluminescence, virulence, and biofilm formation, by sending and receiving small molecules called homoserine lactones (HSLs). Bioengineers have incorporated quorum sensing pathways into genetic circuits to connect logical operations. However, the development of higher-order genetic circuitry is inhibited by crosstalk, in which one quorum sensing network responds to HSLs produced by a different network. Here, we report the construction and characterization of a library of ten synthases including some that are expected to produce HSLs that are incompatible with the Lux pathway, and therefore show no crosstalk. We demonstrated their function in a common lab chassis, Escherichia coli BL21, and in two contexts, liquid and solid agar cultures, using decoupled Sender and Receiver pathways. We observed weak or strong stimulation of a Lux receiver by longer-chain or shorter-chain HSL-generating Senders, respectively. We also considered the under-investigated risk of unintentional release of incompletely deactivated HSLs in biological waste. We found that HSL-enriched media treated with bleach were still bioactive, while autoclaving deactivates LuxR induction. This work represents the most extensive comparison of quorum signaling synthases to date and greatly expands the bacterial signaling toolkit while recommending practices for disposal based on empirical, quantitative evidence.

Boolean-chemotaxis of logibots deciphering the motions of self-propelling microorganisms

We demonstrate the feasibility of a self-propelling mushroom motor, namely a 'logibot', as a functional unit for the construction of a host of optimized binary logic gates. Emulating the chemokinesis of unicellular prokaryotes or eukaryotes, the logibots made stimuli responsive conditional movements at varied speeds towards a pair of acid-alkali triggers. A series of integrative logic operations and cascaded logic circuits, namely, AND, NAND, NOT, OR, NOR, and NIMPLY, have been constructed employing the decisive chemotactic migrations of the logibot in the presence of the pH gradient established by the sole or coupled effects of acid (HCl-catalase) and alkali (NaOH) drips inside a peroxide bath. The imposed acid and/or alkali triggers across the logibots were realized as inputs while the logic gates were functionally reconfigured to several operational modes by varying the pH of the acid-alkali inputs. The self-propelling logibot could rapidly sense the external stimuli, decide, and act on the basis of intensities of the pH triggers. The impulsive responses of the logibots towards and away from the external acid-alkali stimuli were interpreted as the potential outputs of the logic gates. The external stimuli responsive self-propulsion of the logibots following different logic gates and circuits can not only be an eco-friendly alternative to the silicon-based computing operations but also be a promising strategy for the development of intelligent pH-responsive drug delivery devices.

Artificial Symmetry-Breaking for Morphogenetic Engineering Bacterial Colonies

Morphogenetic engineering is an emerging field that explores the design and implementation of self-organized patterns, morphologies, and architectures in systems composed of multiple agents such as cells and swarm robots. Synthetic biology, on the other hand, aims to develop tools and formalisms that increase reproducibility, tractability, and efficiency in the engineering of biological systems. We seek to apply synthetic biology approaches to the engineering of morphologies in multicellular systems. Here, we describe the engineering of two mechanisms, symmetry-breaking and domain-specific cell regulation, as elementary functions for the prototyping of morphogenetic instructions in bacterial colonies. The former represents an artificial patterning mechanism based on plasmid segregation while the latter plays the role of artificial cell differentiation by spatial colocalization of ubiquitous and segregated components. This separation of patterning from actuation facilitates the design-build-test-improve engineering cycle. We created computational modules for CellModeller representing these basic functions and used it to guide the design process and explore the design space in silico. We applied these tools to encode spatially structured functions such as metabolic complementation, RNAPT7 gene expression, and CRISPRi/Cas9 regulation. Finally, as a proof of concept, we used CRISPRi/Cas technology to regulate cell growth by controlling methionine synthesis. These mechanisms start from single cells enabling the study of morphogenetic principles and the engineering of novel population scale structures from the bottom up.

Artificial cell-cell communication as an emerging tool in synthetic biology applications

Cell-cell communication is a widespread phenomenon in nature, ranging from bacterial quorum sensing and fungal pheromone communication to cellular crosstalk in multicellular eukaryotes. These communication modes offer the possibility to control the behavior of an entire community by modifying the performance of individual cells in specific ways. Synthetic biology, i.e., the implementation of artificial functions within biological systems, is a promising approach towards the engineering of sophisticated, autonomous devices based on specifically functionalized cells. With the growing complexity of the functions performed by such systems, both the risk of circuit crosstalk and the metabolic burden resulting from the expression of numerous foreign genes are increasing. Therefore, systems based on a single type of cells are no longer feasible. Synthetic biology approaches with multiple subpopulations of specifically functionalized cells, wired by artificial cell-cell communication systems, provide an attractive and powerful alternative. Here we review recent applications of synthetic cell-cell communication systems with a specific focus on recent advances with fungal hosts.

Can the natural diversity of quorum-sensing advance synthetic biology?

Quorum-sensing networks enable bacteria to sense and respond to chemical signals produced by neighboring bacteria. They are widespread: over 100 morphologically and genetically distinct species of eubacteria are known to use quorum sensing to control gene expression. This diversity suggests the potential to use natural protein variants to engineer parallel, input-specific, cell-cell communication pathways. However, only three distinct signaling pathways, Lux, Las, and Rhl, have been adapted for and broadly used in engineered systems. The paucity of unique quorum-sensing systems and their propensity for crosstalk limits the usefulness of our current quorum-sensing toolkit. This review discusses the need for more signaling pathways, roadblocks to using multiple pathways in parallel, and strategies for expanding the quorum-sensing toolbox for synthetic biology.

Synthetic microbial consortia: from systematic analysis to construction and applications

Synthetic biology is an emerging research field that focuses on using rational engineering strategies to program biological systems, conferring on them new functions and behaviours. By developing genetic parts and devices based on transcriptional, translational, post-translational modules, many genetic circuits and metabolic pathways had been programmed in single cells. Extending engineering capabilities from single-cell behaviours to multicellular microbial consortia represents a new frontier of synthetic biology. Herein, we first reviewed binary interaction modes of microorganisms in microbial consortia and their underlying molecular mechanisms, which lay the foundation of programming cell-cell interactions in synthetic microbial consortia. Systems biology studies on cellular systems enable systematic understanding of diverse physiological processes of cells and their interactions, which in turn offer insights into the optimal design of synthetic consortia. Based on such fundamental understanding, a comprehensive array of synthetic microbial consortia constructed in the last decade were reviewed, including isogenic microbial communities programmed by quorum sensing-based cell-cell communications, sender-receiver microbial communities with one-way communications, and microbial ecosystems wired by two-way (bi-directional) communications. Furthermore, many applications including using synthetic microbial consortia for distributed bio-computations, chemicals and bioenergy production, medicine and human health, and environments were reviewed. Synergistic development of systems and synthetic biology will provide both a thorough understanding of naturally occurring microbial consortia and rational engineering of these complicated consortia for novel applications.

Basis for a neuronal version of Grover's quantum algorithm

Grover's quantum (search) algorithm exploits principles of quantum information theory and computation to surpass the strong Church–Turing limit governing classical computers. The algorithm initializes a search field into superposed N (eigen)states to later execute nonclassical “subroutines” involving unitary phase shifts of measured states and to produce root-rate or quadratic gain in the algorithmic time (O(N^1/2)) needed to find some “target” solution m. Akin to this fast technological search algorithm, single eukaryotic cells, such as differentiated neurons, perform natural quadratic speed-up in the search for appropriate store-operated Ca²⁺ response regulation of, among other processes, protein and lipid biosynthesis, cell energetics, stress responses, cell fate and death, synaptic plasticity, and immunoprotection. Such speed-up in cellular decision making results from spatiotemporal dynamics of networked intracellular Ca²⁺-induced Ca²⁺ release and the search (or signaling) velocity of Ca²⁺ wave propagation. As chemical processes, such as the duration of Ca²⁺ mobilization, become rate-limiting over interstore distances, Ca²⁺ waves quadratically decrease interstore-travel time from slow saltatory to fast continuous gradients proportional to the square-root of the classical Ca²⁺ diffusion coefficient, D^1/2, matching the computing efficiency of Grover's quantum algorithm. In this Hypothesis and Theory article, I elaborate on these traits using a fire-diffuse-fire model of store-operated cytosolic Ca²⁺ signaling valid for glutamatergic neurons. Salient model features corresponding to Grover's quantum algorithm are parameterized to meet requirements for the Oracle Hadamard transform and Grover's iteration. A neuronal version of Grover's quantum algorithm figures to benefit signal coincidence detection and integration, bidirectional synaptic plasticity, and other vital cell functions by rapidly selecting, ordering, and/or counting optional response regulation choices.

The biological microprocessor, or how to build a computer with biological parts

Systemics, a revolutionary paradigm shift in scientific thinking, with applications in systems biology, and synthetic biology, have led to the idea of using silicon computers and their engineering principles as a blueprint for the engineering of a similar machine made from biological parts. Here we describe these building blocks and how they can be assembled to a general purpose computer system, a biological microprocessor. Such a system consists of biological parts building an input / output device, an arithmetic logic unit, a control unit, memory, and wires (busses) to interconnect these components. A biocomputer can be used to monitor and control a biological system.