Urinary exposure marker discovery for toxicants using ultra-high pressure liquid chromatography coupled with Orbitrap high resolution mass spectrometry and three untargeted metabolomics approaches.

Human biomonitoring is the assessment of actual internal contamination of chemicals by measuring exposure markers, chemicals or their metabolites, in human urine, blood, serum, and other body fluids. However, the metabolism of chemicals within an organism is extremely complex. Therefore, the identification of metabolites is often difficult and laborious. Several untargeted metabolomics methods have been developed to perform objective searching/filtering of accurate-mass-based LC-MS data to facilitate metabolite identification. In this study, three metabolomics data processing approaches were used for chemical exposure marker discovery in urine with an LTQ-Orbitrap high-resolution mass spectrometry (HRMS) dataset; di-isononyl phthalate (DINP) was used as an example. The data processing techniques included the SMAIT, mass defect filtering (MDF), and XCMS Online. Sixteen, 83, and 139 probable DINP metabolite signals were obtained using the SMAIT, MDF, and XCMS procedures, respectively. Fourteen probable metabolite signals mined simultaneously by the three metabolomics approaches were confirmed as DINP metabolites by structural information provided by LC-MS/MS. Among them, 13 probable metabolite signals were validated as exposure-related markers in a rat model. Six (m/z 319.155, 361.127, 373.126, 389.157, 437.112 and 443.130) of the 13 exposure-related DINP metabolite signals have not previously been reported in the literature. Our data indicate that SMAIT provided an efficient method to discover effectively and systematically urinary exposure markers of toxicant. The DINP metabolism information can provide valuable information for further investigations of DINP toxicity, toxicokinetics, exposure assessment, and human health effects.

Label-free proteomic analysis of environmental acidification-influenced Streptococcus pyogenes secretome reveals a novel acid-induced protein histidine triad protein A (HtpA) involved in necrotizing fasciitis.

Streptococcus pyogenes is responsible for various diseases. During infection, bacteria must adapt to adverse environments, such as the acidic environment. Acidic stimuli may stimulate S. pyogenes to invade into deeper tissue. However, how this acidic stimulus causes S. pyogenes to manipulate its secretome for facilitating invasion remains unclear. The dynamic label-free LC-MS/MS profiling identified 97 proteins, which are influenced by environmental acidification. Among these, 33 (34%) of the identified proteins were predicted to be extracellular proteins. Interestingly, classical secretory proteins comprise approximately 90% of protein abundance of the secretome in acidic condition at the stationary phase. One acid-induced secreted protein, HtpA, was selected to investigate its role in invasive infection. The mouse infected by the htpA deficient mutant showed lower virulence and smaller lesion area than the wild-type strain. The mutant strain was more efficiently cleared at infected skin than the wild-type strain. Besides, the relative phagocytosis resistance is lower in the mutant strain than in the wild-type strain. These data indicate that a novel acid-induced virulence factor, HtpA, which improves anti-phagocytosis ability for causing necrotizing fasciitis. Our investigation provides vital information for documenting the broad influences and mechanisms underlying the invasive behavior of S. pyogenes in an acidified environment. BIOLOGICAL SIGNIFICANCE: The acidified infected environment may facilitate S. pyogenes invasion from the mucosa to the deeper subepithelial tissue. The acid stimuli have been considered to affect the complex regulatory network of S. pyogenes for causing severe infections. Many of secreted virulence factors influenced by acidified environment may also play a crucial role in pathogenesis of invasive disease. To investigate temporal secretome changes under acidic environment, a comparative secretomics approach using label-free LC-MS/MS was undertaken to analyze the secretome in acidic and neutral conditions. The dynamic label-free LC-MS/MS profiling and secretome prediction were used in this study for mining acid-influenced secreted proteins. We identified 33 acid-influenced secreted proteins in this study. Among these proteins, a novel acid-induced virulence factor, HtpA, was demonstrated to improve anti-phagocytosis ability for causing necrotizing fasciitis. In addition, our study demonstrates the first evidence that acidic stimuli and growth-phase cues are crucial for classical protein secretion in S. pyogenes.