The read-through transcription-mediated autoactivation circuit for virulence regulator expression drives robust type III secretion system 2 expression in Vibrio parahaemolyticus.

Vibrio parahaemolyticus is the leading cause of seafood-borne gastroenteritis in humans worldwide. The major virulence factor responsible for the enteropathogenicity of this pathogen is type III secretion system 2 (T3SS2), which is encoded on the 80-kb V. parahaemolyticus pathogenicity island (Vp-PAI), the gene expression of which is governed by the OmpR-family transcriptional regulator VtrB. Here, we found a positive autoregulatory feature of vtrB transcription, which is often observed with transcriptional regulators of bacteria, but the regulation was not canonically dependent on its own promoter. Instead, this autoactivation was induced by heterogeneous transcripts derived from the VtrB-regulated operon upstream of vtrB. VtrB-activated transcription overcame the intrinsic terminator downstream of the operon, resulting in transcription read-through with read-in transcription of the vtrB gene and thus completing the autoregulatory loop for vtrB gene expression. The dampening of read-through transcription with an exogenous strong terminator reduced vtrB gene expression. Furthermore, a V. parahaemolyticus mutant with defects in the vtrB autoregulatory loop also showed compromises in T3SS2 expression and T3SS2-dependent cytotoxicity in vitro and enterotoxicity in vivo, indicating that this autoregulatory loop is essential for sustained vtrB activation and the consequent robust expression of T3SS2 genes for pathogenicity. Taken together, these findings demonstrate that the regulatory loop for vtrB gene expression based on read-through transcription from the upstream operon is a crucial pathway in T3SS2 gene regulatory network to ensure T3SS2-mediated virulence of V. parahaemolyticus.

Unfolding the Bacterial Transcriptome Landscape Using Oxford Nanopore Technology Direct RNA Sequencing.

Current genome annotation ignores important features of the transcriptome, such as untranslated regions and operon maps. RNA sequencing (RNA-seq) helps in identifying such features; however, the fragmentation step of classical RNA-seq makes this task challenging. Long-read sequencing methods, such as that of Oxford Nanopore Technologies (ONT), enable the sequencing of intact RNA molecules. Here, we present a method to annotate the full features of bacterial transcriptomes by combining a modified ONT direct RNA-seq method with our computational pipeline, UNAGI bacteria. The method reveals the full complexity of the bacterial transcriptome landscape, including transcription start sites, transcription termination sites, operon maps, and novel genes.

UNAGI: Yeast Transcriptome Reconstruction and Gene Discovery Using Nanopore Sequencing.

Computational approaches are the main approaches used in genome annotation. However, accuracy is low. Untranslated regions are not identified, complex isoforms are not predicted correctly and discovery rate of noncoding RNA is low. RNA-seq has revolutionized transcriptome reconstruction over the last decade. However, fragmentation included in cDNA sequencing leads to information loss, requiring transcripts to be assembled and reconstructed, thus affecting the accuracy of reconstructed transcriptome. Recently, long-read sequencing has been introduced with technologies such as Oxford Nanopore sequencing. cDNA is sequenced directly without fragmentation producing long reads that don't need to be assembled keeping the transcript structure intact and increasing the accuracy of transcriptome reconstruction.Here we present a protocol and a pipeline to reconstruct the transcriptome of compact genomes including yeasts. It involves generating full-length cDNA and using Oxford Nanopore ligation-based sequencing kit to sequence multiple samples in the same run. The pipeline (1) strands the generated long reads, (2) corrects the reads by mapping them to the reference genome, (3) identifies transcripts including 5'UTR and 3'UTR, (4) profiles the isoforms, filtering out artifacts resulting from low accuracy in sequencing, and (5) improves accuracy of provided annotations. Using long reads improves the accuracy of transcriptome reconstruction and helps in discovering a significant number of novel RNAs.

Different pancreatic cancer microenvironments convert iPSCs into cancer stem cells exhibiting distinct plasticity with altered gene expression of metabolic pathways.

BACKGROUND: Cancer stem cells (CSCs) are generated under irregular microenvironment in vivo, of which mimic is quite difficult due to the lack of enough information of the factors responsible for cancer initiation. Here, we demonstrated that mouse induced pluripotent cells (miPSCs) reprogrammed from normal embryonic fibroblasts were susceptible to the microenvironment affected by cancer cells to convert into CSCs in vivo. METHODS: Three different pancreatic cancer line cells, BxPC3, PANC1, and PK8 cells were mixed with miPSCs and subcutaneously injected into immunodeficient mice. Tumors were evaluated by histological analysis and cells derived from iPSCs were isolated and selected from tumors. The isolated cells were characterized for cancer stem cell characters in vitro and in vivo as well as their responses to anticancer drugs. The impact of co-injection of iPSCs with cancer cells on transcriptome and signaling pathways of iPSCs was investigated. RESULTS: The injection of miPSCs mixed with human pancreatic cancer cells into immunodeficient mice maintained the stemness of miPSCs and changed their phenotype. The miPSCs acquired CSC characteristics of tumorigenicity and self-renewal. The drug responses and the metastatic ability of CSCs converted from miPSCs varied depending on the microenvironment of cancer cells. Interestingly, transcriptome profiles of these cells indicated that the pathways related with aggressiveness and energy production were upregulated from the levels of miPSCs. CONCLUSIONS: Our result suggests that cancer-inducing microenvironment in vivo could rewire the cell signaling and metabolic pathways to convert normal stem cells into CSCs.

Direct RNA Sequencing Unfolds the Complex Transcriptome of Vibrio parahaemolyticus.

Conventional bacterial genome annotation provides information about coding sequences but ignores untranslated regions and operons. However, untranslated regions contain important regulatory elements as well as targets for many regulatory factors, such as small RNAs. Operon maps are also essential for functional gene analysis. In the last decade, considerable progress has been made in the study of bacterial transcriptomes through transcriptome sequencing (RNA-seq). Given the compact nature of bacterial genomes, many challenges still cannot be resolved through short reads generated using classical RNA-seq because of fragmentation and loss of the full-length information. Direct RNA sequencing is a technology that sequences the native RNA directly without information loss or bias. Here, we employed direct RNA sequencing to annotate the Vibrio parahaemolyticus transcriptome with its full features, including transcription start sites (TSSs), transcription termination sites, and operon maps. A total of 4,103 TSSs were identified. In comparison to short-read sequencing, full-length information provided a deeper view of TSS classification, showing that most internal and antisense TSSs were actually a result of gene overlap. Sequencing the transcriptome of V. parahaemolyticus grown with bile allowed us to study the landscape of pathogenicity island Vp-PAI. Some genes in this region were reannotated, providing more accurate annotation to increase precision in their characterization. Quantitative detection of operons in V. parahaemolyticus showed high complexity in some operons, shedding light on a greater extent of regulation within the same operon. Our study using direct RNA sequencing provides a quantitative and high-resolution landscape of the V. parahaemolyticus transcriptome. IMPORTANCE Vibrio parahaemolyticus is a halophilic bacterium found in the marine environment. Outbreaks of gastroenteritis resulting from seafood poisoning by these pathogens have risen over the past 2 decades. Upon ingestion by humans-often through the consumption of raw or undercooked seafood-V. parahaemolyticus senses the host environment and expresses numerous genes, the products of which synergize to synthesize and secrete toxins that can cause acute gastroenteritis. To understand the regulation of such adaptive response, mRNA transcripts must be mapped accurately. However, due to the limitations of common sequencing methods, not all features of bacterial transcriptomes are always reported. We applied direct RNA sequencing to analyze the V. parahaemolyticus transcriptome. Mapping the full features of the transcriptome is anticipated to enhance our understanding of gene regulation in this bacterium and provides a data set for future work. Additionally, this study reveals a deeper view of a complicated transcriptome landscape, demonstrating the importance of applying such methods to other bacterial models.

UNAGI: an automated pipeline for nanopore full-length cDNA sequencing uncovers novel transcripts and isoforms in yeast.

Sequencing the entire RNA molecule leads to a better understanding of the transcriptome architecture. SMARTer (Switching Mechanism at 5'-End of RNA Template) is a technology aimed at generating full-length cDNA from low amounts of mRNA for sequencing by short-read sequencers such as those from Illumina. However, short read sequencing such as Illumina technology includes fragmentation that results in bias and information loss. Here, we built a pipeline, UNAGI or UNAnnotated Gene Identifier, to process long reads obtained with nanopore sequencing and compared this pipeline with the standard Illumina pipeline by studying the Saccharomyces cerevisiae transcriptome in full-length cDNA samples generated from two different biological samples: haploid and diploid cells. Additionally, we processed the long reads with another long read tool, FLAIR. Our strand-aware method revealed significant differential gene expression that was masked in Illumina data by antisense transcripts. Our pipeline, UNAGI, outperformed the Illumina pipeline and FLAIR in transcript reconstruction (sensitivity and specificity of 80% and 40% vs. 18% and 34% and 79% and 32%, respectively). Moreover, UNAGI discovered 3877 unannotated transcripts including 1282 intergenic transcripts while the Illumina pipeline discovered only 238 unannotated transcripts. For isoforms profiling, UNAGI also outperformed the Illumina pipeline and FLAIR in terms of sensitivity (91% vs. 82% and 63%, respectively). But the low accuracy of nanopore sequencing led to a closer gap in terms of specificity with Illumina pipeline (70% vs. 63%) and to a huge gap with FLAIR (70% vs 0.02%).

Polymorphism of IFN-γ (+874 T/A) in Syrian patients with chronic hepatitis B.

AIM: This study aimed to investigate the association of IFN- γ +874 (T/A) polymorphism with susceptibility to chronic HBV infection in the Syrian population. BACKGROUND: Accumulating evidence indicate that the inadequate immune responses are responsible for HBV persistency. Therefore, polymorphisms in genes encoding the cytokines, which are responsible for regulation of the immune response, can affect the course and outcome of the infection. The IFN-γ +874 T/A polymorphism affects the expression of IFN-γ, which has been shown to be crucial to HBV clearance. METHODS: In this case-control study, 140 samples were collected (70 healthy individuals, 70 chronic HBV patients), and genomic DNA was isolated. Sequencing and ARMS-PCR were performed to genotype the IFN-γ +874 T/A polymorphism. RESULTS: Results of this study showed an association between IFN- γ +874 T/A polymorphism and the susceptibility to chronic HBV infection (P < 0.05). In addition, results showed that the AA genotype increased the risk of chronicity (OR = 3.05, 95% CI = 1.35 - 6.89), whereas the AT and TT genotypes reduced the risk of chronicity (OR = 0.33, 95% CI = 0.150 - 0.753). CONCLUSION: Results of this study conclude that the IFN- γ +874 T/A polymorphism may be associated with the chronic HBV infection, according to the genetic model AA vs. AT&TT.