The immune system of prokaryotes: potential applications and implications for gene editing

Exploration of the biodiversity and mining novel target genes of Listeria monocytogenes strains isolated from beef through comparative genomics analysis

L. monocytogenes is a significant foodborne pathogen. This study aims to explore the biodiversity and evolutionary characteristics of L. monocytogenes isolated from beef through pan-genome analysis, and to provide important reference value for its specific molecular detection. This study conducted an in-depth analysis of the virulence genes, antimicrobial resistance genes, and environmental resistance genes of 344 L. monocytogenes strains isolated from beef. Pan-genomic analysis revealed that L. monocytogenes from beef have open genomes, providing a solid genetic basis for adaptation to different environments. MLST analysis revealed that the most prevalent types of L. monocytogenes isolated from beef were ST9 and CC9. A total of 50 virulence genes were detected in these strains, with 26 virulence genes such as inlA, inlB, plcA, plcB, and prfA, present in all L. monocytogenes strains. The four most prevalent antibiotic resistance genes in L. monocytogenes were norB, lin, mprF, and FosX, indicating high resistance to fluoroquinolones, lincosamides, peptides, and phosphonic acid antibiotics. A total of 416 potential target genes were identified through pan-genomic screening, which were then further filtered using a hub gene selection method to mining novel target genes. Ultimately, 10 highly connected hub genes were selected: bglF_2, tilS, group_2105, group_2431, oleD, ndk, flgG, purB, pbpB, and fni. These genes play a crucial role in the pathogenesis of L. monocytogenes. The PCR results demonstrated the excellent specificity of the bglF_2 gene for L. monocytogenes. Moreover, in the artificial contamination experiment, the bglF_2 gene was able to effectively detect L. monocytogenes in beef samples. Therefore, the bglF_2 gene holds potential as a specific molecular target for the detection of L. monocytogenes strains in beef samples.

Resolving the Trade-Off Between Toxicity and Efficiency of CRISPR-Cas9 System for Genome Editing Within Escherichia coli

Efficient gene editing of Escherichia coli BL21 (DE3) holds significant practical value as a host for heterologous protein expression. Recently reported CRISPR-Cas9 editing systems for this strain exhibit a trade-off between efficiency and toxicity. In this study, we addressed this trade-off by employing the strategy to transiently induce Cas9 expression in the high-copy plasmid during the editing stage. Furthermore, we demonstrated that eliminating the sgRNA-expressing plasmid using a temperature-sensitive replicon, combined with SacB for removing the Cas9-expressing plasmid, exhibited higher efficiency compared to previously reported strategies for editing system removal. We assigned this optimized CRISPR-Cas9 genome editing system as the pEBcas9/pEBsgRNA system, which has successfully achieved efficient five rounds of genome editing and simultaneous editing of multiple loci in E. coli BL21 (DE3). Using this system, we identified several loci suitable for multi-copy integrated expression of exogenous genes. Overall, the pEBcas9/pEBsgRNA system may facilitate the application of E. coli in both industrial and academic fields.

TIR predictor and optimizer: Web-tools for accurate prediction of translation initiation rate and precision gene design in Saccharomyces cerevisiae

Translation initiation is the primary determinant of the rate of protein production. The variation in the rate with which this step occurs can cause up to three orders of magnitude differences in cellular protein levels. Several mRNA features, including mRNA stability in proximity to the start codon, coding sequence length, and presence of specific motifs in the mRNA molecule, have been shown to influence the translation initiation rate. These molecular factors acting at different strengths allow precise control of in vivo translation initiation rate and thus the rate of protein synthesis. However, despite the paramount importance of translation initiation rate in protein synthesis, accurate prediction of the absolute values of initiation rate remains a challenge. In fact, as of now, there is no available model for predicting the initiation rate in Saccharomyces cerevisiae. To address this, we train a machine learning model for predicting the in vivo initiation rate in S. cerevisiae transcripts. The model is trained using a diverse set of mRNA transcripts, enabling the comparison of initiation rates across different transcripts. Our model exhibited excellent accuracy in predicting the translation initiation rate and demonstrated its effectiveness with both endogenous and exogenous transcripts. Then, by combining the machine learning model with the Monte-Carlo search algorithm, we have also devised a method to optimize the nucleotide sequence of any gene to achieve a specific target initiation rate. The machine learning model we've developed for predicting translation initiation rates, along with the gene optimization method, are deployed as a web server. Both web servers are accessible for free at the following link: ajeetsharmalab.com/TIRPredictor. Thus, this research advances our fundamental understanding of translation initiation processes, with direct applications in biotechnology.

Comprehensive analysis of the CRISPR-Cas systems in Streptococcus thermophilus strains isolated from traditional yogurts

Phage resistance is crucial for lactic acid bacteria in the dairy industry. However, identifying all phages affecting these bacteria is challenging. CRISPR-Cas systems offer a resistance mechanism developed by bacteria and archaea against phages and plasmids. In this study, 11 S. thermophilus strains from traditional yogurts underwent analysis using next-generation sequencing (NGS) and bioinformatics tools. Initial characterization involved molecular ribotyping. Bioinformatics analysis of the NGS raw data revealed that all 11 strains possessed at least one CRISPR type. A total of 21 CRISPR loci were identified, belonging to CRISPR types II-A, II-C, and III-A, including 13 Type II-A, 1 Type III-C, and 7 Type III-A CRISPR types. By analyzing spacer sequences in S. thermophilus bacterial genomes and matching them with phage/plasmid genomes, notable strains emerged. SY9 showed prominence with 132 phage matches and 30 plasmid matches, followed by SY12 with 35 phage matches and 25 plasmid matches, and SY18 with 49 phage matches and 13 plasmid matches. These findings indicate the potential of S. thermophilus strains in phage/plasmid resistance for selecting starter cultures, ultimately improving the quality and quantity of dairy products. Nevertheless, further research is required to validate these results and explore the practical applications of this approach.