The microbiome is a diverse ecosystem that includes all host-associated microorganisms and their genomes. These microorganisms belong to various kingdoms including some potential pathogens such as bacteria, viruses and fungi. To obtain a comprehensive view of the lung microbiome, including not only bacterial but also viral and fungal data, is of great value to improve our understanding of critical lung illnesses such as VAP or ARDS. The evolution of the lung microbiome over time and the description of its dysbiosis will be key elements to improve diagnosis and preventive measures in ventilated patients.
Study | Enrolled Patients | Methods (Sampling and Sequencing) | Main Results |
---|---|---|---|
Panzer et al., 2018 [13] | 30 ventilated patients (severe blunt traumatism) - 13 ARDS 1 patients - 17 non-ARDS patients |
ETA 2 on admission and 24 h after V4 16s-rRNA MiSeq Illumina sequencer |
- Association between ARDS development and lung community composition at 48 h (r2 = 0.08, p = 0.04) - ARDS patients: microbiota enriched with Enterobacteriaceae, Prevotella and Fusobacterium |
Kyo et al., 2019 [14] | 47 ventilated patients: - 40 ARDS - 7 non-ARDS |
BAL 3 within 24 h after intubation V5-6 16s-rRNA Ion One Touch sequencer |
- Decreased alpha diversity in ARDS patient compared to controls (p = 0.031) - Copy number of 16S rRNA gene of Betaproteobacteria decreased in non-surviving (n = 16) vs. surviving patient (n = 24). (106 vs. 104; p < 0.05) |
Dickson et al., 2020 [11] | 91 ventilated patients - 17 ARDS - 84 non-ARDS |
BAL within 24 h of ICU admission V4 16s-rRNA MiSeq Illumina sequencer |
- Increased relative abundance of Enterobacteriaceae in ARDS patient (12.5% vs. 0.8%) (p = 0.002). - Association between presence of gut associated bacteria in the lung microbiota and the ventilator-free days at day 28 (p = 0.003) |
Schmitt et al., 2020 [15] | 30 ventilated patients (surgical) - 15 patients with sepsis-induced ARDS - 15 controls |
BAL at ARDS onset (D0 4, D5 5, D10) V4 16s-rRNA MiSeq Illumina sequencer |
- Lower alpha diversity in BAL of ARDS patients vs. controls (Shannon index 3 (2;3.6) vs. 1 (0.5;1.5); p = 0.007) - Decrease in anaerobic bacteria Prevotella spp (p = 0.0033) and Veillonella spp (p = 0.0002) in ARDS patient - Decreased alpha diversity associated with increased length of mechanical ventilation (ρ = −0.48, p = 0.009) |
Study | Enrolled Patients | Methods (Sampling and Sequencing) | Main Results |
---|---|---|---|
Kelly et al., 2016 [8] | - 15 MV 1 patients from medical intensive care unit - 12 healthy unventilated patients |
ETA 2 and OS 3 within 24 h of orotracheal intubation and every 72 h after V1–V2 16s-rRNA MiSeq Illumina sequencer |
- Lower alpha diversity in intubated patients than healthy controls (p = 2.3 × 10−13) - Decreasing alpha diversity overtime in URT 4 of VAP 5 patient (p = 0.0015) - Higher beta diversity in MV patients than in healthy controls |
Zakharkina et al., 2017 [9] | - 11 ventilated patients with VAP 5 - 18 ventilated patients without VAP - 6 HAP 6/CAP 7 - non ventilated control patients |
- BAL 8 for VAP suspicion - ETA at ICU 9 admission and twice a week thereafter 16s-rRNA 454 platform |
- Decreased alpha diversity associated with increased length of mechanical ventilation (fixed effect regression coefficient (β): −0.03 CI95% [−0.05; −0.005]) - Increase in β diversity for VAP patients (p = 0.03) |
Emonet et al. 2019 [16] | - 16 late onset confirmed VAP patient - 38 matched ventilated controls |
- ETA and OS at five time points during MV including the diagnosis of VAP (DVAP) and three days later (DVAP +3) V3-V4 16s-rRNA MiSeq Illumina sequencer |
- Progressive increase in Proteobacteria and decrease in Firmicutes (40% vs. 30%) in OS and ETA of VAP patients - Greater initial abundance of the Bacilli class in ETA from control patients - Association between presence of gut associated bacteria in the lung microbiota and the ventilator-free days at day 28 (p = 0.003) |
Further longitudinal metagenomic studies are now needed to fully characterize pulmonary dysbiosis in ventilated patients who have developed a VAP or an ARDS to understand whether pulmonary dysbiosis is a cause, a consequence or both. These studies will have to use standardized methods that will allow their comparability.
One of the daily issues intensivists face is the accurate diagnosis of VAP in ventilated patient. Regardless of the type of respiratory specimen, pathogen identification by conventional culture-based microbiology techniques is time-consuming and requires a minimum delay of 24–48 h. Promising results were performed with next-generation specific platform BIGISEQ→ platform [66], or Oxford Nanopore→ MinION device (Oxford Nanopore Technologies, UK) [64], techniques that are not currently available in every country or not available enough to respond to the clinical demands of ICUs. Moreover, these studies have been performed with different experimental protocols, sequencing platforms and bioinformatic tools. Further larger studies are therefore required with a similar protocol to confirm the usefulness of such techniques for a large panel of microorganisms, including virus.
In parallel to the challenges of VAP diagnosis, VAP prevention is of high importance for the management of ICU patients. Obviously, a better understanding of pathophysiological infectious steps can help to define targeted interventions on the bacterial microbiota, the mycobiota and the virome. Targeting very specific bacterial strains with bacteriophages may also be an interesting field to treat lung dysbiosis and restore normal flora. The same reasoning may be held with antiviral treatment of viral colonization or co-infection.
This entry is adapted from the peer-reviewed paper 10.3390/life12010007