MOESM3 of Prophage recombinases-mediated genome engineering in Lactobacillus plantarum

Additional file 3: Table S1 Strains and plasmids used in this study

MOESM2 of Prophage recombinases-mediated genome engineering in Lactobacillus plantarum

Additional file 2: Figure S2 Inspection of ΔldhD::gusA mutants for the GusA activity

Autoinduced AND Gate Controls Metabolic Pathway Dynamically in Response to Microbial Communities and Cell Physiological State

Quorum sensing (QS) systems have been widely applied in biotechnology and synthetic biology that require coordinated, community-level behaviors. Meanwhile, the cell physiological state is another key parameter that affects metabolic pathway regulation. Here, we designed an autoinduced AND gate that responds to both microbial communities and the cell physiological state. A series of tunable QS systems in response to different cell densities were obtained through random mutagenesis of LuxR and optimization of the <i>luxRI</i> promoter; the corresponding suitable stationary phase sensing system was selected after monitoring the fluorescence process during cell growth. The application of the final synthetic device was demonstrated using the polyhydroxybutyrate (PHB) production system. The AND gate system increased PHB production by 1–2-fold in <i>Escherichia coli</i>. This synthetic logic gate is a tool for developing a general dynamic regulation system in metabolic engineering in response to complex signals, without using a specific sensor

MOESM1 of Easy regulation of metabolic flux in Escherichia coli using an endogenous type I-E CRISPR-Cas system

Additional file 1. All strain’s name, plasmids, primers used in the study as well as figures mentioned in the main text are available in this file

Additional file 5 of Construction and yield optimization of a cinnamylamine biosynthesis route in Escherichia coli

Additional file 5: Figure S2. Intracellular NADH content of MER-oE strains under different medium conditions. Data represent mean ± S.D. (error bars) from three independent experiments

Additional file 4 of Construction and yield optimization of a cinnamylamine biosynthesis route in Escherichia coli

Additional file 4: Figure S1. Validation of ω-transaminase activity based on color reaction. 1: Control 2: Empty vector plasmid strain breaking solution 3: Breaking solution of strain expressing He-ωTA protein 4: Breaking solution of strain expressing Cv-ωTA protein 5: Purified He-ωTA protein solution 6: Purified Cv-ωTA protein solution

Additional file 6 of Construction and yield optimization of a cinnamylamine biosynthesis route in Escherichia coli

Additional file 6: Figure S3. The petP and petE plasmids expression in E. coil by SDS-PAGE analysis of whole cell (WC), supernatant (S), and protein marker (M)

Additional file 7 of Construction and yield optimization of a cinnamylamine biosynthesis route in Escherichia coli

Additional file 7: Figure S4. Yields of saturated mutants of three amino acid residues of Cv-ωTA converting cinnamaldehyde to cinnamylamine. (A) The production of cinnamylamine in saturated mutants of at the Phe22 site after adding cinnamaldehyde. (B) The production of cinnamylamine in saturated mutants of at the Tyr168 site after adding cinnamaldehyde. (C) The production of cinnamylamine in saturated mutants of at the Ala231 site after adding cinnamaldehyde. The mutant with the highest cinnamylamine production among the saturated mutants at each site is marked with a red inverted triangle. "X" represents any amino acid. Data represent mean ± S.D. (error bars) from three independent experiments

Additional file 3 of Construction and yield optimization of a cinnamylamine biosynthesis route in Escherichia coli

Additional file 3: Table S3. Oligonucleotides used in this study

Additional file 2 of Construction and yield optimization of a cinnamylamine biosynthesis route in Escherichia coli

Additional file 2: Table S2. Plasmids used in this study