Application of metagenomic next-generation sequencing in gastrointestinal infections in children after allogeneic hematopoietic stem cell transplantation.

BACKGROUND

Gastrointestinal infections are the leading cause of death for pediatric patients undergoing allogeneic hematopoietic stem cell transplantation (HSCT). Conventional microbiological testing (CMT) often fails to identify the pathogens, resulting in delayed diagnosis and poor treatment outcomes. Metagenomic next-generation sequencing (mNGS) offers a promising method that does not require cultivation, but its application in this specific situation has not been fully studied.

METHODS

185 fecal samples were collected from 96 children who underwent HSCT and suffered from diarrhea. All samples were simultaneously subjected to mNGS and CMT testing. The diagnostic performance, pathogen spectrum and prevalence of gastrointestinal infection pathogens were systematically analyzed and compared.

RESULTS

Compared with CMT, mNGS detected significantly more bacteria, viruses and atypical pathogens. Among the pathogens detected by mNGS in the 185 fecal samples, the predominant bacteria were Pseudomonas spp. (28 cases), Clostridioides spp. (28 cases), Campylobacter spp. (25 cases), Acinetobacter spp. (16 cases), and Staphylococcus aureus (13 cases). Clostridioides spp. exhibited a significantly higher detection rate in fecal samples from patients receiving CsA-based combination therapy (p=0.01099) and those with bone marrow from unrelated donors (p=0.03188). Pseudomonas aeruginosa (p = 0.03038) and Campylobacter spp.(p = 0.00549) were detected significantly more frequently in patients within the early phase (1-30 days). The detection rate of Adenovirus was markedly decreased during the intermediate phase (31-100 days) (p = 0.01458). Furthermore, Polyomavirus showed a significantly increased detection rate in patients with short-term diarrhea (1-3 days) (p=0.03451).

CONCLUSION

Our findings highlight the substantial superiority of mNGS over CMT in pathogen detection, with a broader coverage encompassing bacteria, viruses, and atypical organisms. It uncovers complex polymicrobial and viral-bacterial co-infections, delineates infection dynamics linked to immune reconstitution. Integrating mNGS into the diagnostic workflow holds great potential for enabling precision antimicrobial therapy and improving outcomes in this high-risk population.