Multiscale positive feedbacks contribute to unidirectional gastric disease progression induced by helicobacter pylori infection

Transcriptomic and Functional Approaches Unveil the Role of tmRNA in Zinc Acetate Mediated Levofloxacin Sensitivity in Helicobacter pylori

Rapid increase in resistance of Helicobacter pylori (H. pylori) has hindered antibiotics-based eradication efforts worldwide and raises the need for additional approaches. Here, we investigate the role of zinc-based compounds in inhibiting H. pylori growth and modulating antibiotic sensitivities, interrogate their downstream transcriptomic changes, and highlight the potential mechanism driving the observed effects. We showed that zinc acetate inhibited H. pylori growth and increased H. pylori sensitivity to levofloxacin. Transcriptomic profiling showed distinct gene expression patterns between zinc acetate treated groups versus controls. In particular, we independently replicated the association between zinc acetate treatment and increased ssrA expression. Knockdown of ssrA restored levofloxacin resistance to levels of the control group. In this study, we first demonstrated the role of zinc acetate in H. pylori growth and antibiotic sensitivities. Additionally, we explored the transcriptomic perturbations of zinc acetate followed by functional knockdown follow-up of differentially expressed ssrA, highlighting the role of tmRNA and trans-translation in H. pylori levofloxacin resistance. Our results provide alternative and complementary strategies for H. pylori treatment and shed light on the underlying mechanisms driving these effects. IMPORTANCE Helicobacter pylori (H. pylori) eradication plays an important role in gastric cancer prevention, but the antimicrobial resistance of H. pylori is fast becoming a growing concern. In this study, we investigated the role of zinc acetate in inhibiting H. pylori growth and modulating antibiotic sensitivities in vitro. Additionally, we explored the transcriptomic perturbations of zinc acetate followed by functional knockdown follow-up of differentially expressed ssrA, highlighting the role of tmRNA and trans-translation in H. pylori levofloxacin resistance. Our results open up a new horizon for the treatment of antibiotic-resistant H. pylori.

Understanding virtual patients efficiently and rigorously by combining machine learning with dynamical modelling

Individual biological organisms are characterized by daunting heterogeneity, which precludes describing or understanding populations of ‘patients’ with a single mathematical model. Recently, the field of quantitative systems pharmacology (QSP) has adopted the notion of virtual patients (VPs) to cope with this challenge. A typical population of VPs represents the behavior of a heterogeneous patient population with a distribution of parameter values over a mathematical model of fixed structure. Though this notion of VPs is a powerful tool to describe patients’ heterogeneity, the analysis and understanding of these VPs present new challenges to systems pharmacologists. Here, using a model of the hypothalamic–pituitary–adrenal axis, we show that an integrated pipeline that combines machine learning (ML) and bifurcation analysis can be used to effectively and efficiently analyse the behaviors observed in populations of VPs. Compared with local sensitivity analyses, ML allows us to capture and analyse the contributions of simultaneous changes of multiple model parameters. Following up with bifurcation analysis, we are able to provide rigorous mechanistic insight regarding the influences of ML-identified parameters on the dynamical system’s behaviors. In this work, we illustrate the utility of this pipeline and suggest that its wider adoption will facilitate the use of VPs in the practice of systems pharmacology.

Pharmacological Effects and Toxicogenetic Impacts of Omeprazole: Genomic Instability and Cancer

Omeprazole (OME) is commonly used to treat gastrointestinal disorders. However, long-term use of OME can increase the risk of gastric cancer. We aimed to characterize the pharmacological effects of OME and to correlate its adverse effects and toxicogenetic risks to the genomic instability mechanisms and cancer-based on database reports. Thus, a search (till Aug 2019) was made in the PubMed, Scopus, and ScienceDirect with relevant keywords. Based on the study objective, we included 80 clinical reports, forty-six in vitro, and 76 in vivo studies. While controversial, the findings suggest that long-term use of OME (5 to 40 mg/kg) can induce genomic instability. On the other hand, OME-mediated protective effects are well reported and related to proton pump blockade and anti-inflammatory activity through an increase in gastric flow, anti-inflammatory markers (COX-2 and interleukins) and antiapoptotic markers (caspases and BCL-2), glycoprotein expression, and neutrophil infiltration reduction. The reported adverse and toxic effects, especially in clinical studies, were atrophic gastritis, cobalamin deficiencies, homeostasis disorders, polyp development, hepatotoxicity, cytotoxicity, and genotoxicity. This study highlights that OME may induce genomic instability and increase the risk of certain types of cancer. Therefore, adequate precautions should be taken, especially in its long-term therapeutic strategies and self-medication practices.

Unraveling the Control of Cell Cycle Periods during Intestinal Stem Cell Differentiation

During differentiation, intestinal stem cells (ISCs), a prototypical adult stem cell pool, become either secretory transit-amplifying cells, which give rise to all secretory cell types, or absorptive transit-amplifying cells, which give rise to enterocytes. These cells exhibit distinct cell cycle dynamics: ISCs cycle with a period of 24 h and absorptive transit-amplifying cells cycle with a period of ∼12 h, whereas secretory transit-amplifying cells arrest their cycle. The cell cycle dynamics of ISCs and their progeny are a systems-level property that emerges from interactions between the cell cycle control machinery and multiple regulatory pathways. Although many mathematical models have been developed to study the details of the cell cycle and related regulatory pathways, few models have been constructed to unravel the dynamic consequences of their interactions. To fill this gap, we present a simplified model focusing on the interaction between four key regulatory pathways (STAT, Wnt, Notch, and MAPK) and cell cycle control. After experimentally validating a model prediction, which showed that the Notch pathway can fine-tune the cell cycle period, we perform further model analysis that reveals that the change of cell cycle period accompanying ISC differentiation may be controlled by a design principle that has been well studied in dynamical systems theory-a saddle node on invariant circle bifurcation. Given that the mechanisms that control the cell cycle are conserved in most eukaryotic cell types, this general principle potentially controls the interplay between proliferation and differentiation for a broad range of stem cells.