Jing Zhong

In China, there is a high prevalence of antibiotic-resistant Helicobacter pylori infections in the population. The aim of the study was to assess a new ARMS-PCR test for detection of H. pylori clarithromycin resistance (CR) and quinolone resistance (QR) mutations and evaluate the spectrum of antibiotic resistance in patients from three Chinese provinces. Sanger sequencing and multiplex ARMS-PCR were used to detect H. pylori CR and QR bacteria in gastric biopsy samples. Among the 1,182 patients enrolled with gastritis, 643 (54.4%) were positive for H. pylori. Of these, 371 (57.7%) had antibiotic-resistant strains, comprising 236 (63.6%) with a single drug antibiotic-resistant strain and 135 (36.4%) with multiple drug-resistant strains. Following Sanger sequencing analysis of 23S rRNA and gyrA gene for mutations (antibiotic resistance markers), rates of CR, QR, and multidrug resistance (CR and QR) were 19.9, 12.0, and 25.8%, respectively. The 23S rRNA CR mutation A2143G (286, 96.9%) and the gyrA QR mutations C261A (85, 31.5%) and G271A (71, 26.3%) were common. Benchmarking against Sanger sequencing results, multiplex ARMS-PCR test had a high diagnostic sensitivity and specificity for detection of CR (96 and 93%), QR (95 and 92%) and multidrug resistance (95 and 95%). Based on our findings, the high incidence of single and multiple antibiotic resistance requires the routine checking of antibiotic resistance in all patients with suspected H. pylori infections. Multiplex ARMS-PCR is a simple and rapid test that can be now used for more efficient treatment of H. pylori infections and reduces the misuse of antibiotics.

Gut dysbiosis contributes to the development of various human diseases. There are thousands of publications per year for investigating the role of gut microbiota in development of various diseases. However, emerging evidence has indicated data inconsistency between different studies frequently, but gained very little attention by scientists. There are many factors that can cause data variation and inconsistency during the process of microbiota study, in particular, sample storage conditions and subsequent sequencing process. Here, we systemically evaluated the impacts of six fecal sample storage conditions (including -80 ^oC, -80 ^oC with 70% ethanol (ET_-80 ^oC), 4 ^oC with 70% ethanol (ET_4^oC), and three commercial storage reagents including OMNIgene·GUT OMR-200 (GT), MGIEasy (MGIE), and Longsee (LS)), storage periods (1, 2 weeks or 6 months), and sequencing platform on gut microbiome profile using 16S rRNA gene sequencing. Our results suggested that -80^oC is acceptable for fecal sample storage, and the addition of 70% ethanol offers some benefits. Meanwhile, we found that samples in ET_4^oC and GT reagents are comparable, both introduced multi-dimensional variations. The use of MGIE resulted in the least alteration, while the greatest changes were observed in samples stored in LS reagents during the whole experiment. Finally, we also confirmed that variations caused by storage condition were larger than that of storage time and sequencing platform.

Chemotherapy induced diarrhea (CID) is a common side effect in patients receiving chemotherapy for cancer. The aim of our study was to explore the association between gut microorganisms and CID from the CapeOX regimen in resected stage III colorectal cancer (CRC) patients. After screening and identification, 17 stool samples were collected from resected stage III CRC patients undergoing the CapeOX regimen. Bacterial 16S ribosomal RNA genes was sequenced, and a bioinformatics analysis was executed to screen for the distinctive gut microbiome and the functional metabolism associated with CID due to the CapeOX regimen. The gut microbial community richness and community diversity were lower in CID (p < 0.05 vs control group). Klebsiella pneumoniae was the most predominant species (31.22%) among the gut microbiome in CRC patients with CID. There were 75 microorganisms with statistically significant differences at the species level between the CRC patients with and without CID (LDA, linear discriminant analysis score > 2), and there were 23 pathways that the differential microorganisms might be involved in. The gut microbial community structure and diversity have changed in CRC patients with CID. It may provide novel insights into the prevention and treatment of CID.

With accumulating public omics data, great efforts have been made to characterize the genetic heterogeneity of breast cancer. However, identifying novel targets and selecting the best from the sizeable lists of candidate targets is still a key challenge for targeted therapy, largely owing to the lack of economical, efficient and systematic discovery and assessment to prioritize potential therapeutic targets. Here, we describe an approach that combines the computational evaluation and objective, multifaceted assessment to systematically identify and prioritize targets for biological validation and therapeutic exploration. We first establish the reference gene expression profiles from breast cancer cell line MCF7 upon genome-wide RNA interference (RNAi) of a total of 3689 genes, and the breast cancer query signatures using RNA-seq data generated from tissue samples of clinical breast cancer patients in the Cancer Genome Atlas (TCGA). Based on gene set enrichment analysis, we identified a set of 510 genes that when knocked down could significantly reverse the transcriptome of breast cancer state. We then perform multifaceted assessment to analyze the gene set to prioritize potential targets for gene therapy. We also propose drug repurposing opportunities and identify potentially druggable proteins that have been poorly explored with regard to the discovery of small-molecule modulators. Finally, we obtained a small list of candidate therapeutic targets for four major breast cancer subtypes, i.e., luminal A, luminal B, HER2+ and triple negative breast cancer. This RNAi transcriptome-based approach can be a helpful paradigm for relevant researches to identify and prioritize candidate targets for experimental validation.