Hideo Nakano

Translation-enhancing peptides (TEPs) that reduce ribosomal stallling in Escherichia coli were identified through comprehensive screening, and their activity was predicted using a machine learning model.

Polyproline residues are well known to induce ribosomal stalling during translation. Our previous work demonstrated that inserting a short translation-enhancing peptide, Ser-Lys-Ile-Lys (SKIK), immediately upstream of such difficult-to-translate sequences can significantly alleviate ribosomal stalling in Escherichia coli. In this study, we provide a quantitative evaluation of its translational effect by kinetically analyzing the influence of the SKIK peptide on polyproline motifs using a reconstituted E. coli in vitro translation system. Translation rates estimated under reasonable assumptions fitted well to a Hill equation within a Michaelis–Menten-like kinetic framework. We further revealed that repetition of the SKIK tag did not provide any positive effect on translation. Moreover, introduction of the SKIK tag increased the production of polyproline-containing proteins, including human interleukin 11, human G protein signaling modulator 3, and DUF58 domain–containing protein from Streptomyces sp. in E. coli cell-free protein synthesis. These findings not only provide new insight into the fundamental regulation of translation by nascent peptides but also demonstrate the potential of the SKIK peptide as a practical tool for synthetic biology, offering a strategy to improve the production of difficult-to-express proteins.

We previously reported that the nascent SKIK peptide enhances translation and alleviates ribosomal stalling caused by arrest peptides (APs) such as SecM and polyproline when positioned immediately upstream of the APs in both Escherichia coli in vivo and in vitro translation systems. In this study, we performed a comprehensive screening of translation-enhancing peptides (TEPs) using a randomized artificial tetrapeptide library. The screening was based on the ability of the peptides to suppress SecM AP-induced translational stalling in E. coli cells. Various TEPs exhibiting a range of translation-enhancing activities were identified. In vitro translation analysis suggested that the fourth amino acid in the tetrapeptide plays a key role in reducing SecM AP-mediated stalling. Furthermore, we developed a machine learning model using a random forest algorithm to predict TEP activity. The predicted values showed a strong correlation with experimentally measured activities. These findings offer a compact peptide toolkit and a data-driven approach for mitigating AP-induced ribosome stalling, with potential applications in synthetic biology.

This study introduces SMART ( S ingle M olecule A ssay on R ibonucleic Acid by T ranslated Product), an innovative in vitro platform integrating mRNA display, next-generation sequencing, and bioinformatics to address several key challenges in enzyme engineering. The characteristic feature of SMART is its auxiliary unit, attached to the mRNA-displayed enzyme library to mediate the biotinylation of reactive enzyme variants and enable their enrichment by streptavidin beads pull-down. The unit comprises a hairpin single-stranded DNA that hybridizes with the mRNA and anchors a DNA-binding protein, single-chain Cro, which carries functional auxiliary molecules specific to the enzyme of interest. Here, we report on the establishment of SMART for the engineering of oxidases, specifically D-amino acid oxidase (DAAO) from Schizosaccharomyces pombe , with engineered ascorbate peroxidase 2 as its auxiliary enzyme. In a single selection round of a DAAO library with randomized catalytic residue Y232 and D-Alanine as the substrate, we identified several catalytically active enzyme variants with altered substrate specificity in a matter of days. This surpasses traditional enzyme engineering methods in speed, cost, library capacity, and precision. This research underscores the potential of SMART for the engineering of various oxidases, and other enzymes after the corresponding adjustment of the auxiliary unit.

A method has been developed for efficiently enriching and analyzing high-affinity antibody variants by combining the PURE ribosome display (ribosome display using purified cell-free protein synthesis components) with next-generation sequencing (NGS) and the Brevibacillus choshinensis secretion system, using the NZ-1 antibody, which targets the PA tag peptide (GVAMPGAEDDVV), as a model antibody. An artificial DNA encoding the single-chain fragment of binding (scFab) of the NZ-1 antibody was synthesized and actively expressed by cell-free protein synthesis system (CFPS). Region-specific saturation mutations were introduced into the scFab gene based on its structural information. The resulting scFab library was selected against the PA tag through two rounds of PURE ribosome display, followed by Illumina sequencing to identify potential scFab variants with higher affinity. The candidates were expressed as Fab fragments using the B. choshinensis secretion system. These Fab fragments were then purified from the culture supernatant using two-step column chromatography. The binding affinity of the purified Fab was evaluated using a biolayer interferometry assay, revealing a variant Fab with higher affinity than the wild-type Fab. These results demonstrate that integrating PURE ribosome display with NGS analysis and the B. choshinensis secretion expression system enables the rapid identification and analysis of high-affinity antibody variants.

Immunoglobulins in the intestine have been reported to play a pivotal role in regulating the composition and function of intestinal microbiota. However, the relationship between monoclonal antibodies (mAbs) and intestinal bacteria remains elusive due to the lack of analytical methods. Here we report the utilization of Ecobody technology, a single B cell technique developed by our group, for obtaining and investigating intestinal bacteria-binding mAbs derived from single B cells of a non-immunized rabbit. Bacteroides cellulosilyticus isolated from the rabbit stool was used as the antigen for selecting B cells, followed by antibody gene amplification, mAb expression in cell-free protein synthesis (CFPS), and activity evaluation. For large-scale and cost-effective production of the selected mAb, we employed the secretion expression system for antigen-binding fragment (Fab) using Brevibacillus choshinensis , and successfully yielded ∼2.0 mg/L-culture of purified antibody with high affinity to the target bacterium. Purified Fab showed binding activity towards various intestinal bacteria, suggesting the broad specificity toward intestinal bacteria-associated antigens.

DNA-binding transcription factors (TFs) play a central role in transcriptional regulation mechanisms, mainly through their specific binding to target sites on the genome and regulation of the expression of downstream genes. Therefore, a comprehensive analysis of the function of these TFs will lead to the understanding of various biological mechanisms. However, the functions of TFs in vivo are diverse and complicated, and the identified binding sites on the genome are not necessarily involved in the regulation of downstream gene expression. In this study, we investigated whether DNA structural information around the binding site of TFs can be used to predict the involvement of the binding site in the regulation of the expression of genes located downstream of the binding site. Specifically, we calculated the structural parameters based on the DNA shape around the DNA binding motif located upstream of the gene whose expression is directly regulated by one TF AoXlnR from Aspergillus oryzae, and showed that the presence or absence of expression regulation can be predicted from the sequence information with high accuracy ([ ]–1.0) by machine learning incorporating these parameters.