In our single center retrospective study, patients in mNGS group had a higher proportion of ARDS, lower absolute number of peripheral blood lymphoid bacteria, higher LDH level, and higher APACHE II score (although there was no statistical difference between the two groups). This indicating that in clinical work, we prefer to mNGS detection for patients with more severe disease severity and lower immune level [21]. In contrast, the 28-day mortality rate of the patients in the mNGS group was lower after the baseline difference correction, indicating that mNGS could improve the prognosis of patients in ICU [22, 23]. Moreover, subgroup analysis showed that mNGS could improve the 28-day mortality of nonimmunosuppressive patients. While for immunosuppressive patients, the expected conclusion has not been reached. That’s probably because the cases of nonimmunosuppressive patients are not enough in this retrospective study, and more cases of immunosuppressive patients are needed for further clarifying [24].
Logistic regression showed that, not performing mNGS, high APACHE II score and hypertension were independent risk factors for 28-day mortality, which strongly suggested that mNGS was one of the key factors affecting prognosis [23]. The improvement of prognosis may be related to the sensitivity of mNGS to pathogen detection. Despite prolonged hospital stay and increased costs, this is more likely to be associated with the severity of the illness.
mNGS can improve the sensitivity of pathogens detection, including bacteria, fungi, viruses and parasite are more sensitive than the conventional culture and PCR methods at the same time. Although it is still unable to distinguish whether the pathogens detected by mNGS are pathogenic microorganisms, combined with prognostic indicators, it can provide more enlightenment for clinical work [4–7]. Theoretically, it can detect all pathogens in a clinical sample unbiased at one time, and shows proven advantages for rare, novel, difficult cases of infectious diseases. However, there is still a lot of improvements for this technique, for example, to formulate negative and positive criteria, improve the turnaround time and optimize the method for drug resistance prediction for clinical.
For different sample type like blood, sputum, cerebrospinal fluid, tissue, swab and other miscellaneous specimen, how to establish a unified nucleic acid extraction standard makes the detection efficiency of pathogens maximization difficult. Host nucleic acid contamination is also a major factor that interferes with pathogen detection. In the process of nucleic acid extraction, how to remove host effectively, thereby enrich pathogen nucleic acid and improve the sensitivity of mNGS, this still needs relevant research to be solved. In terms of bioinformatics, recent studies have evaluated the merits and demerits of different tools. The existing methods not only have different algorithms, but also use different databases, which leads to differences in pathogen identification ability and relative abundance calculation [25]. In the absence of a unified standard in the process of mNGS, the user's choice of the software based on personal experience, accessibility and convenience will affect the repeatability and reliability of the results, which will become an obstacle to the clinical standardization of mNGS.
This technique takes a long time comparatively, usually 24 to 48 hours of turnaround time at present. This needs to be further improved to meet the needs of ICU. In addition, the application of mNGS for patient in ICU is suitable for carrying out in the hospital, while expensive instruments and difficulty of operation present to be a problem.
Presently, mNGS is mainly based on short read length sequencing, for the characteristics of sequencing platforms (Illumina, Thermo Fisher, MGISEQ). In 2014, Hasman et al clarified that mNGS can be used for the detection of pathogens and drug-resistant genes in urine samples [26]. However, samples with low abundance of microbial sequences, it is difficult to determine the attribution of the drug-resistant genes accurately. Improvement of this technique is expected in the future so as to provide proven precise medical service for infectious pathogens identification for clinical practice.