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1.
Nat Commun ; 13(1): 3901, 2022 07 06.
Article in English | MEDLINE | ID: mdl-35794179

ABSTRACT

Bacteroides species are prominent members of the human gut microbiota. The prevalence and stability of Bacteroides in humans make them ideal candidates to engineer as programmable living therapeutics. Here we report a biotic decision-making technology in a community of Bacteroides (consortium transcriptional programming) with genetic circuit compression. Circuit compression requires systematic pairing of engineered transcription factors with cognate regulatable promoters. In turn, we demonstrate the compression workflow by designing, building, and testing all fundamental two-input logic gates dependent on the inputs isopropyl-ß-D-1-thiogalactopyranoside and D-ribose. We then deploy complete sets of logical operations in five human donor Bacteroides, with which we demonstrate sequential gain-of-function control in co-culture. Finally, we couple transcriptional programs with CRISPR interference to achieve loss-of-function regulation of endogenous genes-demonstrating complex control over community composition in co-culture. This work provides a powerful toolkit to program gene expression in Bacteroides for the development of bespoke therapeutic bacteria.


Subject(s)
Bacteroides , Gastrointestinal Microbiome , Bacteroides/genetics , Clustered Regularly Interspaced Short Palindromic Repeats , Humans , Promoter Regions, Genetic/genetics , Transcription Factors/genetics
2.
Proc Natl Acad Sci U S A ; 118(46)2021 11 16.
Article in English | MEDLINE | ID: mdl-34772815

ABSTRACT

Signal processing is critical to a myriad of biological phenomena (natural and engineered) that involve gene regulation. Biological signal processing can be achieved by way of allosteric transcription factors. In canonical regulatory systems (e.g., the lactose repressor), an INPUT signal results in the induction of a given transcription factor and objectively switches gene expression from an OFF state to an ON state. In such biological systems, to revert the gene expression back to the OFF state requires the aggressive dilution of the input signal, which can take 1 or more d to achieve in a typical biotic system. In this study, we present a class of engineered allosteric transcription factors capable of processing two-signal INPUTS, such that a sequence of INPUTS can rapidly transition gene expression between alternating OFF and ON states. Here, we present two fundamental biological signal processing filters, BANDPASS and BANDSTOP, that are regulated by D-fucose and isopropyl-ß-D-1-thiogalactopyranoside. BANDPASS signal processing filters facilitate OFF-ON-OFF gene regulation. Whereas, BANDSTOP filters facilitate the antithetical gene regulation, ON-OFF-ON. Engineered signal processing filters can be directed to seven orthogonal promoters via adaptive modular DNA binding design. This collection of signal processing filters can be used in collaboration with our established transcriptional programming structure. Kinetic studies show that our collection of signal processing filters can switch between states of gene expression within a few minutes with minimal metabolic burden-representing a paradigm shift in general gene regulation.


Subject(s)
Allosteric Regulation/genetics , Signal Processing, Computer-Assisted/instrumentation , Transcription Factors/genetics , Escherichia coli/genetics , Gene Expression/genetics , Gene Expression Regulation/genetics , Gene Regulatory Networks/genetics , Kinetics , Promoter Regions, Genetic/genetics , Protein Binding/genetics , Protein Engineering/instrumentation , Protein Engineering/methods , Synthetic Biology/methods
3.
Annu Rev Biophys ; 50: 303-321, 2021 05 06.
Article in English | MEDLINE | ID: mdl-33606944

ABSTRACT

Allosteric function is a critical component of many of the parts used to construct gene networks throughout synthetic biology. In this review, we discuss an emerging field of research and education, biomolecular systems engineering, that expands on the synthetic biology edifice-integrating workflows and strategies from protein engineering, chemical engineering, electrical engineering, and computer science principles. We focus on the role of engineered allosteric communication as it relates to transcriptional gene regulators-i.e., transcription factors and corresponding unit operations. In this review, we (a) explore allosteric communication in the lactose repressor LacI topology, (b) demonstrate how to leverage this understanding of allostery in the LacI system to engineer non-natural BUFFER and NOT logical operations, (c) illustrate how engineering workflows can be used to confer alternate allosteric functions in disparate systems that share the LacI topology, and (d) demonstrate how fundamental unit operations can be directed to form combinational logical operations.


Subject(s)
Lactose/metabolism , Allosteric Regulation , Gene Regulatory Networks , Humans , Lactose/genetics , Protein Engineering , Synthetic Biology , Transcription Factors/genetics , Transcription Factors/metabolism
4.
Nat Commun ; 11(1): 4440, 2020 09 07.
Article in English | MEDLINE | ID: mdl-32895374

ABSTRACT

Traditionally engineered genetic circuits have almost exclusively used naturally occurring transcriptional repressors. Recently, non-natural transcription factors (repressors) have been engineered and employed in synthetic biology with great success. However, transcriptional anti-repressors have largely been absent with regard to the regulation of genes in engineered genetic circuits. Here, we present a workflow for engineering systems of non-natural anti-repressors. In this study, we create 41 inducible anti-repressors. This collection of transcription factors respond to two distinct ligands, fructose (anti-FruR) or D-ribose (anti-RbsR); and were complemented by 14 additional engineered anti-repressors that respond to the ligand isopropyl ß-d-1-thiogalactopyranoside (anti-LacI). In turn, we use this collection of anti-repressors and complementary genetic architectures to confer logical control over gene expression. Here, we achieved all NOT oriented logical controls (i.e., NOT, NOR, NAND, and XNOR). The engineered transcription factors and corresponding series, parallel, and series-parallel genetic architectures represent a nascent anti-repressor based transcriptional programming structure.


Subject(s)
Bioengineering/methods , Lac Repressors/antagonists & inhibitors , Escherichia coli Proteins/metabolism , Gene Expression/physiology , Gene Regulatory Networks , Lac Repressors/chemical synthesis , Ligands , Repressor Proteins/antagonists & inhibitors , Repressor Proteins/chemical synthesis , Synthetic Biology/methods , Transcription Factors/chemical synthesis , Transcription Factors/metabolism
5.
Nat Commun ; 10(1): 4784, 2019 10 21.
Article in English | MEDLINE | ID: mdl-31636266

ABSTRACT

The control of gene expression is an important tool for metabolic engineering, the design of synthetic gene networks, and protein manufacturing. The most successful approaches to date are based on modulating mRNA synthesis via an inducible coupling to transcriptional effectors. Here we present a biological programming structure that leverages a system of engineered transcription factors and complementary genetic architectures. We use a modular design strategy to create 27 non-natural and non-synonymous transcription factors using the lactose repressor topology as a guide. To direct systems of engineered transcription factors we employ parallel and series genetic (DNA) architectures and confer fundamental and combinatorial logical control over gene expression. Here we achieve AND, OR, NOT, and NOR logical controls in addition to two non-canonical half-AND operations. The basic logical operations and corresponding parallel and series genetic architectures represent the building blocks for subsequent combinatorial programs, which display both digital and analog performance.


Subject(s)
Gene Expression Regulation/genetics , Metabolic Engineering/methods , Transcription Factors/genetics , Transcriptional Activation/genetics , DNA , Gene Regulatory Networks , Genetic Engineering/methods , Genetic Vectors , Synthetic Biology , Transcription, Genetic
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