Zeng, A.-p. | bioRxiv Science

bioRxiv2022

Deep-learning-assisted Sort-Seq enables high-throughput profiling of gene expression characteristics with high precision

As an essential physiological process, gene expression determines the function of each cell. However, owing to the complex nondeterministic and nonlinear nature of gene expression, the steady-state intracellular protein abundance of a clonal population forms a distribution. The characteristics of this distribution, including expression strength and noise, are closely related to cellular behavior. Therefore, quantitative description of these characteristics is an important goal in biology. This task, however, has so far relied on arrayed methods, which are time-consuming and labor-intensive. To address this issue, we propose a deep-learning-assisted Sort-Seq approach (dSort-Seq) in this work, enabling high-throughput profiling of expression properties with high precision. We demonstrated the validity of dSort-Seq for large-scale assaying of the dose-response relationships of biosensors. In addition, we comprehensively investigated the contribution of transcription and translation to noise production in E. coli, from which we discovered that the expression noise is strongly coupled with the mean expression level instead of translation strength, even in the case of weak transcription. We also discovered that the transcriptional interference caused by overlapping RpoD-binding sites contributes to noise production, which suggested the existence of a simple and feasible noise control strategy in E. coli. Overall, dSort-Seq is able to efficiently determine the strength-noise landscape, which has promising applications in studies related to gene expression.

genetics↗

bioRxiv2021

Stand-alone lipoylated H-protein of the glycine cleavage system enables glycine cleavage and the synthesis of glycine from one-carbon compounds in vitro

H-protein, one of the four component proteins (H, T, P and L) of glycine cleavage system (GCS), is generally considered a shuttle protein interacting with the other three GCS-proteins via a lipoyl swinging arm. We report that without P-, T- and L-proteins, lipoylated H-protein (Hlip) enables GCS reactions in both glycine cleavage and synthesis directions in vitro. This apparent catalytic activity is closely related to the cavity on the H-protein surface where the lipoyl arm is attached. Heating or mutation of selected residues in the cavity destroys or reduces the stand-alone activity of Hlip, which can be restored by adding the other three GCS-proteins. Systematic study of the Hlip-catalyzed overall GCS reactions and the individual reaction steps provides a first step towards understanding the stand-alone function of Hlip. The results in this work provide some inspiration for further understanding the mechanism of the GCS and give some interesting implications on the evolution of the GCS. Significance statementGlycine cleavage system (GCS) plays central roles in C1 and amino acids metabolisms and the biosynthesis of purines and nucleotides. Manipulations of GCS are desired to promote plant growth or to treat serious pathophysiological processes such as aging, obesity and cancers. Reversed GCS reactions form the core of the reductive glycine pathway (rGP), one of the most promising pathway for the assimilation of formate and CO2 in the emerging C1-synthetic biology. H-protein, one of the four GCS component proteins (H, T, P and L) is generally considered a shuttle protein interacting with the other three proteins via a lipoyl swinging arm. Here, we discovered that without P-, T- and L-proteins, H-protein alone can catalyze GCS reactions in both glycine cleavage and synthesis directions in vitro. The surprising catalytic activities are related to a structural region of H-protein which can be manipulated. The results have impacts on engineering GCS to treat related diseases, to improve photorespiration, and to efficiently use C1-carbon for biosynthesis.

biochemistry↗