A Genome-Wide Analysis of Promoter-Mediated Phenotypic Noise in Escherichia coli

Gene expression is subject to random perturbations that lead to fluctuations in the rate of protein production. As a consequence, for any given protein, genetically identical organisms living in a constant environment will contain different amounts of that particular protein, resulting in different phenotypes. This phenomenon is known as “phenotypic noise.” In bacterial systems, previous studies have shown that, for specific genes, both transcriptional and translational processes affect phenotypic noise. Here, we focus on how the promoter regions of genes affect noise and ask whether levels of promoter-mediated noise are correlated with genes' functional attributes, using data for over 60% of all promoters in Escherichia coli. We find that essential genes and genes with a high degree of evolutionary conservation have promoters that confer low levels of noise. We also find that the level of noise cannot be attributed to the evolutionary time that different genes have spent in the genome of E. coli. In contrast to previous results in eukaryotes, we find no association between promoter-mediated noise and gene expression plasticity. These results are consistent with the hypothesis that, in bacteria, natural selection can act to reduce gene expression noise and that some of this noise is controlled through the sequence of the promoter region alon

Ribozyme-based insulator parts buffer synthetic circuits from genetic context

Synthetic genetic programs are built from circuits that integrate sensors and implement temporal control of gene expression. Transcriptional circuits are layered by using promoters to carry the signal between circuits. In other words, the output promoter of one circuit serves as the input promoter to the next. Thus, connecting circuits requires physically connecting a promoter to the next circuit. We show that the sequence at the junction between the input promoter and circuit can affect the input-output response (transfer function) of the circuit. A library of putative sequences that might reduce (or buffer) such context effects, which we refer to as 'insulator parts', is screened in Escherichia coli. We find that ribozymes that cleave the 5′ untranslated region (5′-UTR) of the mRNA are effective insulators. They generate quantitatively identical transfer functions, irrespective of the identity of the input promoter. When these insulators are used to join synthetic gene circuits, the behavior of layered circuits can be predicted using a mathematical model. The inclusion of insulators will be critical in reliably permuting circuits to build different programs.Life Technologies, Inc.United States. Defense Advanced Research Projects Agency (DARPA CLIO N66001-12-C-4018)United States. Office of Naval Research (N00014-10-1-0245)National Science Foundation (U.S.) (CCF-0943385)National Institutes of Health (U.S.) (AI067699)National Science Foundation (U.S.). Synthetic Biology Engineering Research Center (SynBERC, SA5284-11210

Engineering modular and orthogonal genetic logic gates for robust digital-like synthetic biology

Modular and orthogonal genetic logic gates are essential for building robust biologically based digital devices to customize cell signalling in synthetic biology. Here we constructed an orthogonal AND gate in Escherichia coli using a novel hetero-regulation module from Pseudomonas syringae. The device comprises two co-activating genes hrpR and hrpS controlled by separate promoter inputs, and a σ54-dependent hrpL promoter driving the output. The hrpL promoter is activated only when both genes are expressed, generating digital-like AND integration behaviour. The AND gate is demonstrated to be modular by applying new regulated promoters to the inputs, and connecting the output to a NOT gate module to produce a combinatorial NAND gate. The circuits were assembled using a parts-based engineering approach of quantitative characterization, modelling, followed by construction and testing. The results show that new genetic logic devices can be engineered predictably from novel native orthogonal biological control elements using quantitatively in-context characterized parts

Genomic mining of prokaryotic repressors for orthogonal logic gates

Genetic circuits perform computational operations based on interactions between freely diffusing molecules within a cell. When transcription factors are combined to build a circuit, unintended interactions can disrupt its function. Here, we apply 'part mining' to build a library of 73 TetR-family repressors gleaned from prokaryotic genomes. The operators of a subset were determined using an in vitro method, and this information was used to build synthetic promoters. The promoters and repressors were screened for cross-reactions. Of these, 16 were identified that both strongly repress their cognate promoter (5- to 207-fold) and exhibit minimal interactions with other promoters. Each repressor-promoter pair was converted to a NOT gate and characterized. Used as a set of 16 NOT/NOR gates, there are >10[superscript 54] circuits that could be built by changing the pattern of input and output promoters. This represents a large set of compatible gates that can be used to construct user-defined circuits.United States. Air Force Office of Scientific Research (Award FA9550-11-C-0028)American Society for Engineering Education. National Defense Science and Engineering Graduate Fellowship (32 CFR 168a)United States. Defense Advanced Research Projects Agency. Chronical of Lineage Indicative of Origins (N66001-12-C-4016)United States. Office of Naval Research (N00014-13-1-0074)National Institutes of Health (U.S.) (GM095765)National Science Foundation (U.S.). Synthetic Biology Engineering Research Center (SA5284-11210

Evidence for Induction of Integron-Based Antibiotic Resistance by the SOS Response in a Clinical Setting

Bacterial resistance to β-lactams may rely on acquired β-lactamases encoded by class 1 integron-borne genes. Rearrangement of integron cassette arrays is mediated by the integrase IntI1. It has been previously established that integrase expression can be activated by the SOS response in vitro, leading to speculation that this is an important clinical mechanism of acquiring resistance. Here we report the first in vivo evidence of the impact of SOS response activated by the antibiotic treatment given to a patient and its output in terms of resistance development. We identified a new mechanism of modulation of antibiotic resistance in integrons, based on the insertion of a genetic element, the gcuF1 cassette, upstream of the integron-borne cassette blaOXA-28 encoding an extended spectrum β-lactamase. This insertion creates the fused protein GCUF1-OXA-28 and modulates the transcription, the translation, and the secretion of the β-lactamase in a Pseudomonas aeruginosa isolate (S-Pae) susceptible to the third generation cephalosporin ceftazidime. We found that the metronidazole, not an anti-pseudomonal antibiotic given to the first patient infected with S-Pae, triggered the SOS response that subsequently activated the integrase IntI1 expression. This resulted in the rearrangement of the integron gene cassette array, through excision of the gcuF1 cassette, and the full expression the β-lactamase in an isolate (R-Pae) highly resistant to ceftazidime, which further spread to other patients within our hospital. Our results demonstrate that in human hosts, the antibiotic-induced SOS response in pathogens could play a pivotal role in adaptation process of the bacteria

ART: A machine learning Automated Recommendation Tool for synthetic biology

Biology has changed radically in the last two decades, transitioning from a descriptive science into a design science. Synthetic biology allows us to bioengineer cells to synthesize novel valuable molecules such as renewable biofuels or anticancer drugs. However, traditional synthetic biology approaches involve ad-hoc engineering practices, which lead to long development times. Here, we present the Automated Recommendation Tool (ART), a tool that leverages machine learning and probabilistic modeling techniques to guide synthetic biology in a systematic fashion, without the need for a full mechanistic understanding of the biological system. Using sampling-based optimization, ART provides a set of recommended strains to be built in the next engineering cycle, alongside probabilistic predictions of their production levels. We demonstrate the capabilities of ART on simulated data sets, as well as experimental data from real metabolic engineering projects producing renewable biofuels, hoppy flavored beer without hops, and fatty acids. Finally, we discuss the limitations of this approach, and the practical consequences of the underlying assumptions failing

RsmW, Pseudomonas aeruginosa small non-coding RsmA-binding RNA upregulated in biofilm versus planktonic growth conditions

BACKGROUND: Biofilm development, specifically the fundamentally adaptive switch from acute to chronic infection phenotypes, requires global regulators and small non-coding regulatory RNAs (sRNAs). This work utilized RNA-sequencing (RNA-seq) to detect sRNAs differentially expressed in Pseudomonas aeruginosa biofilm versus planktonic state. RESULTS: A computational algorithm was devised to detect and categorize sRNAs into 5 types: intergenic, intragenic, 5′-UTR, 3′-UTR, and antisense. Here we report a novel RsmY/RsmZ-type sRNA, termed RsmW, in P. aeruginosa up-transcribed in biofilm versus planktonic growth. RNA-Seq, 5’-RACE and Mfold predictions suggest RsmW has a secondary structure with 3 of 7 GGA motifs located on outer stem loops. Northern blot revealed two RsmW binding bands of 400 and 120 bases, suggesting RsmW is derived from the 3’-UTR of the upstream hypothetical gene, PA4570. RsmW expression is elevated in late stationary versus logarithmic growth phase in PB minimal media, at higher temperatures (37°C versus 28°C), and in both gacA and rhlR transposon mutants versus wild-type. RsmW specifically binds to RsmA protein in vitro and restores biofilm production and reduces swarming in an rsmY/rsmZ double mutant. PA4570 weakly resembles an RsmA/RsmN homolog having 49% and 51% similarity, and 16% and 17% identity to RsmA and RsmN amino acid sequences, respectively. PA4570 was unable to restore biofilm and swarming phenotypes in ΔrsmA deficient strains. CONCLUSION: Collectively, our study reveals an interesting theme regarding another sRNA regulator of the Rsm system and further unravels the complexities regulating adaptive responses for Pseudomonas species