Sequence saturation mutagenesis (SeSaM) is a conceptually novel and practically simple method that truly randomizes a target sequence at every single nucleotide position. A SeSaM experiment can be accomplished within 2–3 days and comprises four steps: generating a pool of DNA fragments with random length, ‘tailing’ the DNA fragments with universal base using terminal transferase at 3′‐termini, elongating DNA fragments in a PCR to the full‐length genes using a single‐stranded template and replacing the universal bases by standard nucleotides. Random mutations are created at universal sites due to the promiscuous base‐pairing property of universal bases. Using enhanced green fluorescence protein as the model system and deoxyinosine as the universal base, we proved by sequencing 100 genes the concept of the SeSaM method and achieved a random distribution of mutations with the mutational bias expected for deoxyinosine.

Human mitochondrial transcription factor A (TFAM) is a multi-functional protein, involved in different aspects of maintaining mitochondrial genome integrity. In this report, we characterized TFAM and its interaction with tumor suppressor p53 using various biophysical methods. DNA-free TFAM is a thermally unstable protein that is in equilibrium between monomers and dimers. Self-association of TFAM is modulated by its basic C-terminal tail. The DNA-binding ability of TFAM is mainly contributed by its first HMG-box, while the second HMG-box has low-DNA-binding capability. We also obtained backbone resonance assignments from the NMR spectra of both HMG-boxes of TFAM. TFAM binds primarily to the N-terminal transactivation domain of p53, with a K_d of 1.95 ± 0.19 μM. The C-terminal regulatory domain of p53 provides a secondary binding site for TFAM. The TFAM–p53-binding interface involves both TAD1 and TAD2 sub-domains of p53. Helices α1 and α2 of the HMG-box constitute the main p53-binding region. Since both TFAM and p53 binds preferentially to distorted DNA, the TFAM–p53 interaction is implicated in DNA damage and repair. In addition, the DNA-binding mechanism of TFAM and biological relevance of the TFAM–p53 interaction are discussed.

Malonyl-CoA is the basic building block for synthesizing a range of important compounds including fatty acids, phenylpropanoids, flavonoids and non-ribosomal polyketides. Centering around malonyl-CoA, we summarized here the various metabolic engineering strategies employed recently to regulate and control malonyl-CoA metabolism and improve cellular productivity. Effective metabolic engineering of microorganisms requires the introduction of heterologous pathways and dynamically rerouting metabolic flux towards products of interest. Transcriptional factor-based biosensors translate an internal cellular signal to a transcriptional output and drive the expression of the designed genetic/biomolecular circuits to compensate the activity loss of the engineered biosystem. Recent development of genetically-encoded malonyl-CoA sensor has stood out as a classical example to dynamically reprogram cell metabolism for various biotechnological applications. Here, we reviewed the design principles of constructing a transcriptional factor-based malonyl-CoA sensor with superior detection limit, high sensitivity and broad dynamic range. We discussed various synthetic biology strategies to remove pathway bottleneck and how genetically-encoded metabolite sensor could be deployed to improve pathway efficiency. Particularly, we emphasized that integration of malonyl-CoA sensing capability with biocatalytic function would be critical to engineer efficient microbial cell factory. Biosensors have also advanced beyond its classical function of a sensor actuator for in situ monitoring of intracellular metabolite concentration. Applications of malonyl-CoA biosensors as a sensor-invertor for negative feedback regulation of metabolic flux, a metabolic switch for oscillatory balancing of malonyl-CoA sink pathway and source pathway and a screening tool for engineering more efficient biocatalyst are also presented in this review. We envision the genetically-encoded malonyl-CoA sensor will be an indispensable tool to optimize cell metabolism and cost-competitively manufacture malonyl-CoA-derived compounds.