Throat microbiota drives alterations in pulmonary alveolar microbiota in patients with septic ARDS

ABSTRACT

Objectives

The translocation of intestinal flora has been linked to the colonization of diverse and heavy lower respiratory flora in patients with septic ARDS, and is considered a critical prognostic factor for patients.

Methods

On the first and third days of ICU admission, BALF, throat swab, and anal swab were collected, resulting in a total of 288 samples. These samples were analyzed using 16S rRNA analysis and the traceability analysis of new generation technology.

Results

On the first day, among the top five microbiota species in abundance, four species were found to be identical in BALF and throat samples. Similarly, on the third day, three microbiota species were found to be identical in abundance in both BALF and throat samples. On the first day, 85.16% of microorganisms originated from the throat, 5.79% from the intestines, and 9.05% were unknown. On the third day, 83.52% of microorganisms came from the throat, 4.67% from the intestines, and 11.81% were unknown. Additionally, when regrouping the 46 patients, the results revealed a significant predominance of throat microorganisms in BALF on both the first and third day. Furthermore, as the disease progressed, the proportion of intestinal flora in BALF increased in patients with enterogenic ARDS.

Conclusions

In patients with septic ARDS, the main source of lung microbiota is primarily from the throat. Furthermore, the dynamic trend of the microbiota on the first and third day is essentially consistent.It is important to note that the origin of the intestinal flora does not exclude the possibility of its origin from the throat.

KEYWORDS:

• Sepsis
• ARDS
• bronchoalveolar lavage fluid
• throat swab
• anal swab
• 16S rRNA

Objectives

Sepsis is a medical emergency that poses a significant threat to patients’ health [1]. It is characterized by a complex mechanism involving severe immune dysregulation induced by systemic inflammation and infection [2]. The global impact of sepsis is substantial, causing approximately 11 million deaths worldwide each year [3,4]. It not only results in loss of life but also imposes a heavy burden on patients, their families, and society as a whole.Acute respiratory distress syndrome (ARDS) is a fatal disease that occurs as a result of endothelial cell injury and local inflammation in the lungs. Sepsis is the leading cause of ARDS, accounting for 32% of all cases [5]. Furthermore, ARDS is considered a devastating complication of severe sepsis. Patients who experience both sepsis and ARDS have worse clinical outcomes compared to those with either condition alone [6,7].

The structure and composition of lung microbiota play a crucial role in the progression of various chronic respiratory diseases [8]. Lung microbiota contribute to lung inflammation and the advancement of pulmonary fibrosis [9]. Subjects with decreased lung function exhibit lower diversity in lung microbiota compared to healthy individuals [10]. Recent studies have indicated that the enrichment of intestinal flora in lung microbiota is associated with the presence of ARDS [11,12]. Similarly, another study found that intestinal flora were enriched in the lower respiratory tract of patients with septic ARDS, suggesting an interaction between intestinal flora and the progression of septic ARDS [11]. Analyzing the microbial composition of bronchoalveolar lavage fluid (BALF) has not only revealed specific patterns of lung microbiota related to the mortality of ARDS patients [13] but also has the potential to predict disease outcomes [14]. However, previous research has lacked matched throat microbial specimens and has not conducted traceability analysis of the microbes in the lower respiratory tract of septic ARDS patients.

In this study, we analyzed the microbial load and community diversity in the BALF, throat swab, and anal swab on the first and third days of ICU admission for patients with septic ARDS using 16S rRNA sequencing. Subsequently, based on disease and intestinal markers, 46 of these patients were regrouped into enteric ARDS and non-enteric ARDS. The dynamic changes in the microflora of the BALF, throat swab, and anal swab of patients with septic ARDS on the first and third days of their ICU admission.

Methods

Patient

This experiment was conducted in the Department of Critical Care Medicine at the First Affiliated Hospital of Harbin Medical University in Heilongjiang Province, China. The study included patients from July 2021 to July 2022. Patient identification was based on the third international consensus definition of sepsis, and diagnostic criteria aligned with ARDS. The trial was conducted after obtaining informed consent from the patients’ families.Patients with sepsis due to lung infection were excluded.

Collection and preservation of specimens

Bronchoalveolar lavage fluid

For patients meeting the inclusion criteria and diagnosed with septic ARDS, BALF samples were collected on the first and third days of ICU admission. Prior to bronchoalveolar lavage, the patients were sedated, mechanically ventilated, and underwent ECG monitoring. The collection of BALF samples involved selecting diseased or new progressive invasive leaf segments, and in cases of bilateral diffuse infection, the left lung tongue segment was chosen. The bronchoscope tip was then positioned in the appropriate bronchial branch and 100 ml of sterile isotonic saline (in 5 aliquots of 20 ml) was instilled, followed by suction to perform BAL. Approximately 30% to 50% of the aliquot was retrieved. Subsequently, the collected irrigation solution was promptly centrifuged at 4°C for 30 minutes at 22,500 g, and the supernatant was removed to obtain the sediment. The enriched samples were rapidly frozen in liquid nitrogen and stored at −80°C until RNA extraction.

Throat swabs and anal swabs

During throat swab sampling, the patient was positioned in a posterior head tilt position, and the tongue was immobilized using a tongue depressor. RNase- and DNase-free cotton swabs were then utilized to access the posterior pharyngeal wall and tonsillar crypts located above the base of the tongue. These areas were swabbed repeatedly 3–5 times before the swabs were carefully removed. To prevent contact with the oral and tongue mucosa, it is essential to ensure that the swabs do not make any such contact. Prior to pharyngeal sampling, all patients received comprehensive oral care from a nurse. After successful collection, the swabs were promptly placed in protective tubes made of polystyrene. To preserve the integrity of the samples, they were immediately snap frozen in liquid nitrogen and stored in a refrigerator at −80°C until the RNA extraction process.

During anal swab sampling, the patient was positioned in the left lateral position. RNase- and DNase-free cotton swabs were inserted 2–3 cm into the rectal sphincter, rotated 360°, and left in place for approximately 20 seconds. Subsequently, the swabs were carefully removed and checked for successful sampling. Once collected, the swabs were promptly placed in protective tubes made of polystyrene. To preserve the integrity of the samples, they were immediately snap frozen in liquid nitrogen and stored in a refrigerator at −80°C until the RNA extraction process.

Enzyme-linked immunosorbent assays

Peripheral blood samples were obtained from each group and centrifuged at 4,000 rpm for 10 minutes at 4°C to collect serum. The serum was subsequently stored at −80°C until further use. The levels of FABP2 were measured using People ELISA kits (JL44346, Jonln, China).

16S rRNA analysis of the microbial community

The corresponding DNA extraction kit (QIAamp Fast DNA Stool Mini Kit, No. 51604) was used to extract genomic DNA from each sample according to the instructions. Then, 1% agarose gel electrophoresis was used to detect the integrity and purity of DNA. DNA concentration and purity were checked using NanoDrop One (Thermo Fisher Scientific, MA, USA). PCR amplification and product electrophoresis detection used genomic DNA as the template and according to the selection of the sequencing region. PCR amplification was performed using primers (Cord: 338F 5′-ACTCCTACGGGAGGCAGCA-3′ and 806 R (5′-GGACTACHVGGGTWTCTAAT-3′, Invitrogen, Carlsbad, CA, USA) with barcodes and PremisTaq (TaKaRa Biotechnology, Dalian Co., Ltd., China). One microliter of each primer (10 μM) and 3 μl of DNA (20 ng/μl) template in a volume of 50 μl were amplified by thermocycling as follows: 5 min at 94°C for initialization; 30 cycles of 30 s denaturation at 94°C, 30 s annealing at 52°C, and 30 s extension at 72°C; followed by a 10-min final elongation at 72°C. The PCR instrument was a Bio-Rad S1000 (Bio-Rad Laboratory, CA, USA). After comparing the concentrations of PCR products using Gene Tool Analysis software (Version 4.03.05.0, SynGene, England), the required volume of each sample was calculated according to the principle of equal mass, and the PCR products were mixed. The PCR mixture was recovered using the E.Z.N.A. Gel Extraction Kit (Omega, USA), and the target DNA fragments were recovered by elution with TE buffer. Subsequent library construction was performed according to the standard process of NEBNext Ultra™ DNA Library Prep Kit for Illumina (New England Biolabs, MA, USA). Upon completion, library quality was assessed on a Qubit 2.0 fluorometer (Thermo Fisher Scientific, MA, USA). Once complete, in-flight sequencing was performed using the high-throughput sequencing platform HiSeq or MiSeq. Base calling is an algorithm that identifies DNA sequences from row images through computer vision and finally generates sequencing reports.®®®

SourceTracke analysis

SourceTracker is one of the most effective methods for microbial traceability. It can evaluate all assignments of the sequence to all source samples, including unknown sources,SourceTracker first needs to determine the classification of sample sources, such as different environmental samples, different tissue samples, etc. Sufficient samples are required for each classification to establish a representative microbial composition.It performs 16S rRNA sequencing analysis on each sample source to obtain the microbial composition data for each source.Perform 16S rRNA sequencing analysis on the microbial composition of the target sample to obtain the microbial composition data.Input the microbial composition data of the target sample into the SourceTracker algorithm, combined with the microbial composition data of sample sources, to calculate and determine the source proportions of the microbial community in the target sample.Through Bayesian methods, the proportions of microbial composition sources in the target sample can be determined, thereby identifying the contributions of different sample sources in the target sample and assisting researchers in understanding the microbial origins and their associations in the target sample.

Statistical analysis

The Kruskal−Wallis rank-sum test was used to compare the significant differences among multiple groups, Dunn’s test was used afterwards, and the FDR method was used to correct the p-value. One-way ANOVA was used to test whether the means of multiple groups of samples were the same, and all two groups were tested post hoc using methods such as Scheffe’s test. When the variance between the two groups was equal, Student’s t-test was used, but since the samples in this experiment were independent samples, the independent samples t-test or the Wilcoxon rank-sum test was selected, and the p-value was corrected by various methods. The differences were considered to be significant if p < 0.05.

Result

A total of 93 participants were enrolled between July 2021 and June 2022. However, 45 patients were excluded from the experimental group due to either inadequate data on the third day or low RNA concentration after amplification (see Table 1 in the supplementary document for the patient enrollment flow chart). The basic characteristics of the remaining 48 patients included in the study are presented in Table 1.

Table 1. Demographic and clinical characteristics of the cohort at study.

Characteristic	Study cohort (n=48)
Age,years	61.5(44.25,71.75)
Male, men	21/48(43.75%)
Smoking(Current smoker, %)	14/48(29.17%)
Mean SOFA(SD)	11.21±3.61
Mean APACHE II(SD)	21.1±5.22
PaO2/FIO2(SD)	205.34±60.46
LYMPH,median (IQR)	0.87(0.54,1.088)
PCT,median (IQR)	9.7(1.32,45.00)
CRP(SD)	208.74±130.56
7-day mortality(%)	5/48(10.42%)
28-day mortality(%)	16/48(33.33%)
Ventilator-free days, median (IQR)	1(0,4)
Length of days in the ICU(IQR)	16.5(7,35.25)

Abbreviations: SOFA:Sequential Organ Failure Assessment;APACHEII:Acute Physiology and Chronic Health Evaluation II;LYMPH:lymphocyte count;PCT:procalcitonin;CRP:C-reactive protein;IQR:interquartile range;ICU:intensive care unit. Data are reported as median with interquartile range (IQR) for continuous variable and with number and percentage (%) for non-continuous variables.

Diverse Microbial Distribution across throat swab, bronchoalveolar lavage, and anal Swab in different anatomical Sites

The throat swabs had 632 microbiota species unique on the first day,1510 microbiota species unique on the third day,and 1318 microbiota species in common (Figure 1a).The BALF had 3159 microbiota species unique on the first day,3959 microbiota species unique on the third day,and 7302 microbiota species in common (Figure 1b).The anal swabs had 505 microbiota species unique on the first day,447 microbiota species unique on the third day,and 1702 microbiota species in common (Figure 1c).And shared microbial communities among throat swabs, BALF, and anal swabs in septic ARDS Patients: a total of 582 species (Figure 1d).

Figure 1. Distribution of microbiota in the BALF, throat swab, and anal swab on day 1 and day 3 in patients with septic ARDS (a) The number of unique microbiota species in the throat swab on the first day and on the third day in patients with septic ARDS; (b) The number of unique microbiota species in the BALF on the first day and on the third day in patients with septic ARDS;C:The number of unique microbiota species in anal swab on the first day and on the third day in patients with septic ARDS;D:The number of unique microbiota for each group.

We defined “S.ALI.Day1.TS” as the throat swab in patients with septic ARDS on the first day;“S.ALI.Day3.TS” as the throat swab in patients with septic ARDS on the third daya;“S.ALI.Day1.BALF” as the BALF in patients with septic ARDS on the first day;“S.ALI.Day3.BALF” as the BALF in patients with septic ARDS on the third day;“S.ALI.Day1.AT” as the anal swab in patients with septic ARDS on the first day;“S.ALI.Day3.AT” as the anal swab in patients with septic ARDS on the third day.

The microbial diversity of the lung, throat, and intestinal microbiota in patients with septic ARDS gradually declines over time

The microbial alpha diversity was analyzed to determine the microbial diversity and composition of BALF, throat swab, and anal swab samples on the first and third days.The Chao1 index was utilized to quantify the abundance of microorganisms in various sample sites and time points.Based on the Chao1 index analysis, it was observed that the bacterial flora abundance in the BALF, throat swab, and anal swab samples of patients exhibited a decline on the third day when compared to the first day(Figure 2a,b,c).By beta diversity analysis, we found that the composition of the microbiota in throat swabs, alveolar lavage fluid, and anal samples of sepsis patients on day 1 was different from that on day 3(Figure 2d,e,f).

Figure 2. Changes in the composition of the microbiota in the BALF, throat swab, and anal swab in patients with septic ARDS on the first and third days (a) Comparison of microbial richness in the BALF on the first and third day; (b) Comparison of microbial richness in the throat swabs on the first and third day; (c) Comparison of microbial richness in the anal swab on the first and third day; (d,e,f) PCoA analysis. The dots with different colours represent different sample groups. The closer the spatial distance of the sample is, the more similar the species composition structure of the sample is.

Throat and intestinal microbes inhabit distinct ecological niches and play a role in shaping the lung microbiota in patients with septic ARDS

At the phylum level (Figure 3), the findings indicated that in BALF, the genera showing a significant increase in abundance on the third day compared to the first day were Acinetobacter OTU1, Enterococcus OTU3, and Pseudomonas OTU9. As for throat swabs, the genera displaying a significant increase in abundance on the third day compared to the first day were Acinetobacter OTU1, Enterococcus OTU3, and Staphylococcus OTU7. The microbial genera that exhibited a significant reduction in flora in both BALF and throat swab samples were Enterobacteriaceae OTU4, Eschi-Shigella OTU2, and Coryneaceae OTU5. In anal swabs, the three genera that exhibited the greatest increase in abundance on the third day compared to the first day were Acinetobacter OTU1, Eschi-Shigella OTU2, and Bacteroides OTU18, while the three genera that displayed the greatest decrease in abundance were Enterobacter OTU4, Enterococcus OTU3, and Coryneaceae OTU5.

Figure 3. Histogram of BALF throat swabs and anal swabs microbiota distribution in the survival group and the non-survival group on the first and third days. The abscissa represents the groupings, and the ordinate represents the gut microbiota abundance values. The taxa with an abundance above 1% were selected, and all abundances were in the top 15 for classification.

Trends in microbial dynamics in lung of patients with septic ARDS were more similar to those in throat, meanwhile both sites were enriched with intestinal flora

To investigate the interconnection between changes in microbial populations in BALF, throat swab, and anal swab over time on the first and third day, we compared microorganisms with higher abundance at these sampling sites during the same time period. The statistical analysis included horizontal sequence information of phylum, class, order, family, genus, and species in OTU. Additionally, the relative abundance of each taxa was calculated. Taxa with a relative abundance above 1% (default value) were selected. The analysis results were then plotted, presenting the top 15 (default value) classifications of abundance (Figure 4).

Figure 4. Microbial relative abundance in BALF, throat swab and anal swab of patients with septic ARDS on the first and third day. Comparison of microbiota in different position of the two groups. The abscissa represents the abundance values, and the ordinate represents the bacterial groups. The Wilcoxon signed-rank sum test was used. (a) Comparison of microbiota between the first day and the third day in the BALF; (b) Comparison of microbiota between the first day and the third day in the anal swab; (c) Comparison of microbiota between the first day and the third day in the throat swab.

We observed that on the first day, the top five flora identified in BALF were consistent with those found in the throat, namely Acinetobacter, Enterobacteriaceae, Corynebacterium, and Streptococcus. Similarly, on the third day, the top five flora in BALF remained consistent with those in the throat, including Acinetobacter, Enterobacteriaceae, and Enterococcus. Regarding the anal swab, on the first day, the top five abundant flora comprised Enterococcus OTU3, Escherichia-Shigella OTU2, Enterobacteriaceae OTU4, Bacteroides OTU18, and Bacteroides OTU23. On the third day, the top five abundant flora consisted of Escherichia-Shigella OTU2, Enterococcus OTU3, Acinetobacter OTU1, Bacteroides OTU18, and EnterobacterOTU4.The results demonstrated a general similarity between the changes in lung microflora in septic ARDS patients and that in the throat, both of which displayed enrichment of intestinal microflora. Recent research has indicated that the transfer of microflora from the stomach and/or throat to the lower respiratory tract is one of the major pathogenic mechanisms in patients with severe pneumonia. Moreover, relevant literature has reported the occurrence of silent aspiration in recovered AECOPD patients, with a significantly higher incidence rate compared to age-matched healthy volunteers [15]. Additionally, literature supports the notion that microaspiration under the glottis can impact lung microflora [16]. Therefore, our study further verifies the similarity in the dynamic patterns of lung microbes in septic ARDS patients and the throat, both of which demonstrate enrichment with intestinal flora. However, it cannot be completely ruled out that the intestinal flora may originate from the throat.

The traceability analysis of BALF microorganisms in patients with septic ARDS revealed a significant presence of throat flora and an increase in intestinal-associated flora

To further investigate the similarity between BALF and the microbial communities in the throat and intestinal region, we leveraged a novel generation of traceability technology. We conducted traceability analyses comparing the first and third-day BALF samples with their corresponding throat and anal swab samples, as shown in (Figure 5). The analysis revealed that on the first day of the BALF sampling, microorganisms originating from the throat constituted 85.16% of the total, while the intestine accounted for 5.79%, and 9.05% remained unidentified. Similarly, on the third day of the BALF sampling, the throat contributed 83.52% of the microorganisms, the intestine accounted for 4.67%, and 11.81% remained unknown. These findings suggest a higher presence of throat-associated microbial communities in the BALF of patients with septic ARDS, potentially indicating a close relationship between the throat microbiota and the occurrence and development of ARDS.

Figure 5. Pie chart of SourceTracke analysis of BALF on day one and day three in patients with septic ARDS A: a new generation of traceability technology, and performed traceability analysis of the first day of BALF with the first day of throat swabs and anal swabs respectively in septic ARDS;B:a new generation of traceability technology, and performed traceability analysis of the first day of BALF with the first day of throat swabs and anal swabs respectively in septic ARDS.

Traceability analysis of BALF in septic ARDS patients, with and without enterogenic infection, revealed that the highest number of associated flora originates from the throat, with a slight enrichment of intestinal-associated flora

Previous studies have revealed that the trends of microbial flora in both BALF and the throat are more similar in patients with septic ARDS. Additionally, BALF in septic ARDS has been predominantly found to originate from the throat. Interestingly, other investigations have demonstrated an association between enteric microbes and the development of septic ARDS [11,13]. Therefore, we classified a total of 46 patients with septic ARDS into two groups based on FABP2 levels, which serve as a marker of intestinal injury [17–19](see Supplementary Document Figure 1). Subsequently, we conducted traceability analysis of BALF, throat swabs, and anal swabs on the first and third days for both groups (Figure 6). The analysis revealed that on the first day of the BALF sampling, microorganisms originating from the throat constituted 86.2% of the total, while the intestine accounted for 1.2%, and 12.6% remained unidentified. Similarly, on the third day of the BALF sampling, the throat contributed 83.78% of the microorganisms, the intestine accounted for 3.65%, and 12.57% remained unknown.Based on our findings, it can be concluded that as the disease progresses, there is an increased presence of enteric-derived microflora in the lungs of patients with enteric-derived ARDS. However, it is worth noting that in the septic ARDS group with non-enterogenic infection, both on the first and third day, the microorganisms found in BALF originated predominantly from the throat. Simultaneously, a small number of microorganisms were traced back to the intestine, indicating a decreasing trend. Thus, it is undeniable that a significant proportion of BALF microorganisms in both enterogenic and non-enterogenic septic ARDS cases stem from the throat.

Figure 6. Pie chart of SourceTracke analysis of BALF on day one and day three in septic ARDS patients with enterogenic and non-enterogenic infection (a) A new generation of traceability technology, and performed traceability analysis of the first day of BALF with the first day of throat swabs and anal swabs respectively in septic ARDS patients with enterogenic infection; (b) A new generation of traceability technology, and performed traceability analysis of the third day of BALF with the third day of throat swabs and anal swabs respectively in septic ARDS patients with enterogenic infection; (c) A new generation of traceability technology, and performed traceability analysis of the first day of BALF with the first day of throat swabs and anal swabs respectively in septic ARDS patients without enterogenic infection; (d) A new generation of traceability technology, and performed traceability analysis of the third day of BALF with the third day of throat swabs and anal swabs respectively in septic ARDS patients without enterogenic infection.

Discussion

The relationship between the lung microbiome and intestinal colony has garnered considerable attention in recent years [20]. These studies have investigated the association between intestinal microorganisms and respiratory diseases, shedding light on the potential pathogenesis of such diseases in relation to factors like microbial flora abundance, species diversity, and specific bacteria. For instance, research has shown that low diversity of intestinal microbiota is linked to childhood asthma [21], while alpha diversity of gut flora is associated with 28-day mortality in critically ill patients [22]. Furthermore, the beta diversity of intestinal flora in lung cancer patients differs from that of healthy individuals [23], and asthma patients exhibit a rich presence of Neisseria, Moraxella, Haemophilus, and other bacteria in their pulmonary microflora [24]. Additionally, the airflow limitation in COPD is associated with the increased abundance of Pseudomonas in sputum and decreased levels of Treponema [25]. However, previous studies on ARDS have primarily focused on exploring intestinal microorganisms [13,14], and have thus neglected the examination of throat flora, thereby failing to establish correlation-based conclusions.

The throat serves as a significant reservoir of both respiratory tract and intestinal flora [26]. Our study provides additional insights into the characteristics of throat flora in patients with septic ARDS. We observed a decrease in microbial communities in BALF, throat swabs, and anal swabs of septic ARDS patients on the third day compared to the first day. Moreover, we found an enrichment of enterococci in the BALF of septic ARDS patients, with an increased abundance of enterococci on the third day compared to the first day, suggesting a temporal longitudinal association. Our focus in this study was the dominant flora of microbial colonies sampled from these three sites. Additionally, we analyzed and compared the similarity of the flora in BALF, throat swabs, and anal swabs from septic ARDS patients. Building upon previous studies on intestinal lung displacement [12], our findings suggest that investigations on BALF in septic ARDS patients should include an assessment of the evolving upper respiratory flora as well. Another study exploring the link between oral and pulmonary microorganisms revealed that saliva can potentially serve as a predictor of lung microflora status [27]. This suggests that in the future, the changes in throat flora may serve as an indicator for the prognosis of patients with septic ARDS.

Concurrently, it is also feasible to intervene in the microbial flora of patients’ upper respiratory tract by improving oral care, thereby reducing lung injury.Additionally, the use of probiotics has demonstrated a correlation with certain respiratory diseases [28,29]. In the future, it is imperative to further study the connection between septic ARDS development and intervention in the microorganisms present in the upper respiratory tract and intestine.

Our study also has limitations. First, despite implementing strict patient inclusion criteria, the sample size consisted of only 48 patients, and the study was conducted in a single center. Secondly, our research lacks samples from the upper digestive tract, including the stomach. Obtaining samples from the upper digestive tract could provide evidence of the transfer of intestinal flora to the lung through the anatomical pathway of gut-stomach-throat-lower respiratory tract [30–32]. Additionally, our study was inevitably influenced by various factors, such as the patient’s physical condition and background interference, as microbial flora is closely associated with multiple elements.Despite the inability to eliminate the impact of antibiotics, previous studies have demonstrated the absence of a significant correlation between antibiotic administration and the composition of lung communities in patients with traumatic ARDS [12]. This suggests that our results still hold certain guiding significance.

Conclusions

In conclusion, our study demonstrated that lung microorganisms in patients with septic ARDS were primarily derived from the throat, and this trend was consistently observed.Both the lung and throat exhibited a high abundance of enteric flora, particularly Enterococcus and Enterobacter as the predominant enteric-derived microorganisms. However, it was unclear whether the enteric flora found in the BALF originated solely from the throat.Our findings suggest that changes in throat microorganisms may play a role in the development of septic ARDS, providing potential therapeutic targets for the prevention and treatment of these prevalent and life-threatening conditions.

Author contributions

All authors participated in the design, KY,MZ,CW,NL,KK,YZ andYL searched for the articles, screened titles and abstracts and extracted data. YP,LW,MM,FL and YL performed statistical analysis and interpretation of data.NL,KK,YL,JZ,YC,YW,JL,PC,QZ drafted the manuscript, and all authors revised it for important intellectual content. Final approval of the version submitted for publication was obtained for all authors.

Ethics approval and consent to participate

Ethical approval for the study was approved by the Ethics Committee of the first affiliated hospital of Harbin Medical University (IRB-AF/SC-04/02.0), Harbin, China And this study was conducted adhering to a protocol that was approved by the Medical Ethics Research Committee of our hospital. In this study, all research was conducted in accordance with the Declaration of Helsinki.

Acknowledgements

We shall thank all the doctors, nurses and clinical scientists who worked in the hospital during the period of patient recruitment as well as the patients who were involved in this study.

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/21505594.2024.2350775.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

All data generated or analyzed during this study are included in this published article.

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.

Additional information

Funding

This project was funded by the National Natural Science Foundation of China-Regional Innovation and Development Joint Fund (U20A20366) and the Postdoctoral Science Startup Foundation of the Heilongjiang Provincial Science (Grant 21042180268).