Evaluation of the Virulence of Low Pathogenic H9N2 Avian Influenza Virus Strains in Broiler Chickens.

Our study aimed to investigate the virulence of three recent H9N2 LPAIV strains belonging to the G1 lineage, isolated from field infections in North Africa and the Middle East. Three-week-old commercial broiler chickens (in total 62) were included and randomly allocated into three infected test groups and one control group. Each test group was inoculated intranasally/intratracheally with one of the three H9N2 isolates at a dose of 108 EID50 virus. The control group received phosphate-buffered saline (PBS) via the same route of application. The pathogenicity was evaluated based on clinical signs and gross pathological and histopathological lesions, the viral antigen load was assessed through immunohistochemistry staining (IHC), and a semi-quantitative detection of the genetic material was conducted via a real-time PCR. Our findings confirmed the obvious respiratory tract tropism of the virus strains with variable renal tropism. In contrast to the highly pathogenic AIVs, the tested H9N2 strains did not show replication in the central nervous system. The virus presence and lesions, mainly in the respiratory tract, were predominant on dpi 5 and significantly reduced or disappeared by dpi 11. A clear difference was demonstrated among the three isolates: the A/chicken/Morocco/2021/2016 strain proved to be significantly more virulent than the Egyptian and Saudi Arabian ones, which showed no remarkable difference.

Profiling Urinary Sulfate Metabolites With Mass Spectrometry.

The study of urinary phase II sulfate metabolites is central to understanding the role and fate of endogenous and exogenous compounds in biological systems. This study describes a new workflow for the untargeted metabolic profiling of sulfated metabolites in a urine matrix. Analysis was performed using ultra-high-performance liquid chromatography-high resolution tandem mass spectrometry (UHPLC-HRMS/MS) with data dependent acquisition (DDA) coupled to an automated script-based data processing pipeline and differential metabolite level analysis. Sulfates were identified through k-means clustering analysis of sulfate ester derived MS/MS fragmentation intensities. The utility of the method was highlighted in two applications. Firstly, the urinary metabolome of a thoroughbred horse was examined before and after administration of the anabolic androgenic steroid (AAS) testosterone propionate. The analysis detected elevated levels of ten sulfated steroid metabolites, three of which were identified and confirmed by comparison with synthesised reference materials. This included 5α-androstane-3ß,17α-diol 3-sulfate, a previously unreported equine metabolite of testosterone propionate. Secondly, the hydrolytic activity of four sulfatase enzymes on pooled human urine was examined. This revealed that Pseudomonas aeruginosa arylsulfatases (PaS) enzymes possessed higher selectivity for the hydrolysis of sulfated metabolites than the commercially available Helix pomatia arylsulfatase (HpS). This novel method provides a rapid tool for the systematic, untargeted metabolic profiling of sulfated metabolites in a urinary matrix.