To investigate the effect of hfq variants on cellular gene expressions, RNA-seq analysis was conducted. When the hfq variant 4 was introduced into hfq-deleted DH5α, it achieved the highest cell density and comparably high growth rate. The mRNAs in the cells were prepared for the analysis. mRNAs extracted from hfq-deleted DH5α and wild-type DH5α were used as a control. Three samples from individual cultures at stationary phase were used for RNA-seq analysis.

The number of reads for each gene was determined using HTSeq [48]. To reduce gene length bias, Reads Per Kilobase Million (RPKM) of each gene were calculated by dividing the total number of read count aligned to a gene by 1,000,000 and by the length of the gene in kilobase [49].

To identify differentially expressed genes (DEGs), genes were filtered as the following criteria: |log2(fold change)| > 2; p-value < 0.05; and normalized read count ≥ 10. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment of DEGs were analyzed by the Database for Annotation, Visualization and Integrated Discovery (DAVID) [50]. Enriched GO terms and KEGG pathways were selected by a p-value < 0.05.

The protein-protein interaction (PPI) network of DEGs was constructed using the STRING database [51] and Cytoscape [52]. Highly interconnected clusters were identified using Molecular Complex Detection (MCODE) [53].

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