The Escherichia coli Fur pan-regulon has few conserved but many unique regulatory targets.

While global transcription factors (TFs) have been studied extensively in Escherichia coli model strains, conservation and diversity in TF regulation between strains is still unknown. Here we use a combination of ChIP-exo-to define ferric uptake regulator (Fur) binding sites-and differential gene expression-to define the Fur regulon in nine E. coli strains. We then define a pan-regulon consisting of 469 target genes that includes all Fur target genes in all nine strains. The pan-regulon is then divided into the core regulon (target genes found in all the strains, n = 36), the accessory regulon (target found in two to eight strains, n = 158) and the unique regulon (target genes found in one strain, n = 275). Thus, there is a small set of Fur regulated genes common to all nine strains, but a large number of regulatory targets unique to a particular strain. Many of the unique regulatory targets are genes unique to that strain. This first-established pan-regulon reveals a common core of conserved regulatory targets and significant diversity in transcriptional regulation amongst E. coli strains, reflecting diverse niche specification and strain history.

Deep-learning optimized DEOCSU suite provides an iterable pipeline for accurate ChIP-exo peak calling.

Recognizing binding sites of DNA-binding proteins is a key factor for elucidating transcriptional regulation in organisms. ChIP-exo enables researchers to delineate genome-wide binding landscapes of DNA-binding proteins with near single base-pair resolution. However, the peak calling step hinders ChIP-exo application since the published algorithms tend to generate false-positive and false-negative predictions. Here, we report the development of DEOCSU (DEep-learning Optimized ChIP-exo peak calling SUite), a novel machine learning-based ChIP-exo peak calling suite. DEOCSU entails the deep convolutional neural network model which was trained with curated ChIP-exo peak data to distinguish the visualized data of bona fide peaks from false ones. Performance validation of the trained deep-learning model indicated its high accuracy, high precision and high recall of over 95%. Applying the new suite to both in-house and publicly available ChIP-exo datasets obtained from bacteria, eukaryotes and archaea revealed an accurate prediction of peaks containing canonical motifs, highlighting the versatility and efficiency of DEOCSU. Furthermore, DEOCSU can be executed on a cloud computing platform or the local environment. With visualization software included in the suite, adjustable options such as the threshold of peak probability, and iterable updating of the pre-trained model, DEOCSU can be optimized for users' specific needs.

ChEAP: ChIP-exo analysis pipeline and the investigation of Escherichia coli RpoN protein-DNA interactions.

Genome-scale studies of the bacterial regulatory network have been leveraged by declining sequencing cost and advances in ChIP (chromatin immunoprecipitation) methods. Of which, ChIP-exo has proven competent with its near-single base-pair resolution. While several algorithms and programs have been developed for different analytical steps in ChIP-exo data processing, there is a lack of effort in incorporating them into a convenient bioinformatics pipeline that is intuitive and publicly available. In this paper, we developed ChIP-exo Analysis Pipeline (ChEAP) that executes the one-step process, starting from trimming and aligning raw sequencing reads to visualization of ChIP-exo results. The pipeline was implemented on the interactive web-based Python development environment - Jupyter Notebook, which is compatible with the Google Colab cloud platform to facilitate the sharing of codes and collaboration among researchers. Additionally, users could exploit the free GPU and CPU resources allocated by Colab to carry out computing tasks regardless of the performance of their local machines. The utility of ChEAP was demonstrated with the ChIP-exo datasets of RpoN sigma factor in E. coli K-12 MG1655. To analyze two raw data files, ChEAP runtime was 2 min and 25 s. Subsequent analyses identified 113 RpoN binding sites showing a conserved RpoN binding pattern in the motif search. ChEAP application in ChIP-exo data analysis is extensive and flexible for the parallel processing of data from various organisms.

Characterization of an Entner-Doudoroff pathway-activated Escherichia coli.

BACKGROUND: Escherichia coli have both the Embden-Meyerhof-Parnas pathway (EMPP) and Entner-Doudoroff pathway (EDP) for glucose breakdown, while the EDP primarily remains inactive for glucose metabolism. However, EDP is a more favorable route than EMPP for the production of certain products. RESULTS: EDP was activated by deleting the pfkAB genes in conjunction with subsequent adaptive laboratory evolution (ALE). The evolved strains acquired mutations in transcriptional regulatory genes for glycolytic process (crp, galR, and gntR) and in glycolysis-related genes (gnd, ptsG, and talB). The genotypic, transcriptomic and phenotypic analyses of those mutations deepen our understanding of their beneficial effects on cellulosic biomass bio-conversion. On top of these scientific understandings, we further engineered the strain to produce higher level of lycopene and 3-hydroxypropionic acid. CONCLUSIONS: These results indicate that the E. coli strain has innate capability to use EDP in lieu of EMPP for glucose metabolism, and this versatility can be harnessed to further engineer E. coli for specific biotechnological applications.

Enhanced production of nonanedioic acid from nonanoic acid by engineered Escherichia coli.

In this study, whole-cell biotransformation was conducted to produce nonanedioic acid from nonanoic acid by expressing the alkane hydroxylating system (AlkBGT) from Pseudomonas putida GPo1 in Escherichia coli. Following adaptive laboratory evolution, an efficient E. coli mutant strain, designated as MRE, was successfully obtained, demonstrating the fastest growth (27-fold higher) on nonanoic acid as the sole carbon source compared to the wild-type strain. Additionally, the MRE strain was engineered to block nonanoic acid degradation by deleting fadE. The resulting strain exhibited a 12.8-fold increase in nonanedioic acid production compared to the wild-type strain. Six mutations in acrR, Pcrp , dppA, PfadD , e14, and yeaR were identified in the mutant MRE strain, which was characterized using genomic modifications and RNA-sequencing. The acquired mutations were found to be beneficial for rapid growth and nonanedioic acid production.

Genome sequence of the potential probiotic eukaryote Saccharomyces cerevisiae KCCM 51299.

Saccharomyces cerevisiae KCCM 51299, a potential probiotic yeast overproducing glutathione, has been isolated from among 272 yeast strains from the relatively safe Nuruk. The genome sequence of S. cerevisiae KCCM 51299 was analyzed and a near-complete genome (12 Mb) with 19 contigs was assembled after PacBio single-molecule real-time (SMRT) sequencing. The genome of S. cerevisiae KCCM 51299 was compared to the S. cerevisiae s288c reference genome. Additionally, genes involved in glutathione biosynthesis were identified, and the glutathione biosynthesis pathway was constructed in silico based on these genes. Furthermore, S. cerevisiae KCCM 51299 genes were compared with those in other yeast genomes. Finally, genome-scale in silico flux analysis was carried out, and a metabolic engineering strategy for glutathione biosynthesis was generated. These results provide useful information to further develop eukaryotic probiotics to overproduce glutathione.

Fermentation product with new equol-producing Lactobacillus paracasei as a probiotic-like product candidate for prevention of skin and intestinal disorder.

BACKGROUND: Equol is a major isoflavone metabolite, and equol-producing bacteria have been isolated and characterized; however, fermentation has been performed with soybean-based products as substrates. Pueraria lobata has been reported as a plant with higher content of isoflavones. RESULTS: The genome of new equol-producing bacteria, Lactobacillus paracasei JS1, was analyzed. Also, the effect of P. lobata extract fermented with L. paracasei JS1 (FPE) on the skin and intestinal immune response was examined. With gene expression analysis, it was proven that seven skin-related proteins, hyaluronan synthase-1, -2, -3, collagen, elastin, epidermal growth factor, and epidermal growth factor receptor were differentially expressed upon FPE treatment. The messenger RNA expression increased with treatment with the FPE, and a skin moisturizing effect was confirmed by a hematoxylin-eosin staining experiment. In addition, such an experiment showed that proinflammatory cytokines, tumor necrosis factor-α, cyclooxygenase-2, inducible nitric oxide synthase, interleukin-1ß, -4, and -6, were reduced in large intestine when treated with FPE. CONCLUSION: L. paracasei JS1 has the ability to produce equol having beneficial effects on the skin. Moreover, FPE also has an inhibitory effect on inflammation cytokines in the large intestine. Thus, the novel and edible equol-producing L. paracasei JS1 and FPE have thepotential to be developed as nutricosmetic resources. © 2019 Society of Chemical Industry.