Progress in the diagnosis of infectious pathogens depends on the development of effective methods and the discovery of suitable biomarkers. There are several kinds of methods that have been used in diagnosis of various pathogens, such as microscopic examination, culture, serologic diagnosis or molecular approaches, etc. However, these methods have similar limitations, that is, the single detection of reagents. More importantly, physicians seldom consider infections with rare pathogens. Recently developed metagenomic next-generation sequencing (mNGS) has the capability to overcome limitations of traditional diagnostic tests. This new technology could identify all pathogens directly from sample with a single run in a hypothesis-free and culture-independent manner. Studies have shown that mNGS is more sensitive than traditional culture method in clinical conditions such as blood stream, respiratory and general infections. More importantly, due to unbiased sampling, mNGS is theoretically able to identify not only known but also unexpected pathogens or even discovery novel organisms. It should be noted that mNGS also has some limitations such as human genome contamination and possibly environmental microbial contamination. The vast majority of reads in mNGS are derived from human host. This would impede the overall analytical sensitivity of mNGS for pathogen detection. Host depletion methods or targeted sequencing may help to partially mitigate this disadvantage. As mNGS could not, by itself, define whether the detected microbe is the causative pathogen or environmental microorganism, a multidisciplinary discussion by clinicians, microbiologists as well as the lab technicians is required to interpret the result.

Inclusion Criteria:

• All the patients have received mNGS testing in clinical practice.

Exclusion Criteria:

• Interruption of patient treatment process and incomplete information

All the enrolled patients have received mNGS testing in clinical practice. Clinical data were rigorously evaluated and summarized, patients' data were compiled until death or hospital discharge.