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Extracellular vesicles (EVs) are cell-derived membranous vesicles secreted by cells into the extracellular space, which play a role in cell to cell communication. EVs are categorized into 3 groups depending on their size, surface marker, and method of release from the host cell. Recently, EVs have become of interest in the study of multiple disease etiologies and are believed to be potential biomarkers for many diseases. Multiple different methods have been developed to isolate EVs from different samples such as cell culture medium, serum, blood, and urine. Once isolated, EVs can be characterized by technology such as nanotracking analysis, dynamic light scattering, and nanoscale flow cytometry. In this review, we summarize the current methods of EV isolation, provide details into the three methods of EV characterization, and provide insight into which isolation approaches are most suitable for EV isolation from bronchoalveolar lavage fluid (BALF).

The purpose of this study was to assess the value of metagenomic next-generation sequencing (mNGS) of bronchoalveolar lavage fluid (BALF) for the diagnosis of severe respiratory diseases based on interpretation of sequencing results. BALF samples were harvested and used for mNGS as well as microbiological detection. Infectious bacteria or fungi were defined according to relative abundance and number of unique reads. We performed mNGS on 35 BALF samples from 32 patients. The positive rate reached 100% in the mNGS analysis of nine immunocompromised patients. Compared with the culture method, mNGS had a diagnostic sensitivity of 88.89% and a specificity of 74.07% with an agreement rate of 77.78% between these two methods. Compared with the smear method and PCR, mNGS had a diagnostic sensitivity of 77.78% and a specificity of 70.00%. In 13 cases, detection results were positive by mNGS but negative by culture/smear and PCR. The mNGS findings in 11/32 (34.4%) cases led to changes in treatment strategies. Linear regression analysis showed that diversity was significantly correlated with interval between disease onset and sampling. Dynamic changes in reads could indirectly reflect therapeutic effectiveness. BALF mNGS improves sensitivity of pathogen detection and provides guidance in clinical practice. Potential pathogens can be identified based on relative abundance and number of unique reads.

Metagenomic next-generation sequencing (mNGS) is a powerful method for pathogen detection. In this study, we assessed the value of mNGS for bronchoalveolar lavage (BAL) samples in the diagnosis of pulmonary infections. From February 2018 to April 2019, BAL samples were collected from 235 patients with suspected pulmonary infections. mNGS and microbial culture were performed to evaluate the effectiveness of mNGS in pulmonary infection diagnosis. We employed mNGS to evaluate the alpha diversity, results suggesting that patients with confirmed pathogens had a lower microbial diversity index compared to that of patients with uncertain pathogens. For the patients admitted to the respiratory intensive care unit (RICU) or on a ventilator, they experienced a lower diversity index than that of the patients in the general ward or not on a ventilator. In addition, mNGS of BAL had a diagnostic sensitivity of 88.89% and a specificity of 14.86% in pulmonary infection, with 21.16% positive predictive value (PPV) and 83.87% negative predictive value (NPV). When rare pathogens were excluded, the sensitivity of mNGS decreased to 73.33%, and the specificity increased to 41.71%. For patients in the simple pulmonary infection group and the immunocompromised group, the main infection types were bacterial infection (58.33%) and mixed-infection (43.18%). Furthermore, mNGS had an advantage over culture in describing polymicrobial ecosystem, demonstrating the microbial distribution and the dominant strains of the respiratory tract in patients with different underlying diseases. The study indicated that mNGS of BAL samples could provide more accurate diagnostic information in pulmonary infections and demonstrate the changes of respiratory microbiome in different underlying diseases. This method might play an important role in the clinical use of antimicrobial agents in the future.

Although the emerging NGS-based assays, metagenomic next-generation sequencing (mNGS) and targeted next-generation sequencing (tNGS), have been extensively utilized for the identification of pathogens in pulmonary infections, there have been limited studies systematically evaluating differences in the efficacy of mNGS and multiplex PCR-based tNGS in bronchoalveolar lavage fluid (BALF) specimens. In this study, 85 suspected infectious BALF specimens were collected. Parallel mNGS and tNGS workflows to each sample were performed; then, we comparatively compared their consistency in detecting pathogens. The differential results for clinically key pathogens were confirmed using PCR. The microbial detection rates of BALF specimens by the mNGS and tNGS workflows were 95.18% (79/83) and 92.77% (77/83), respectively, with no significant difference. mNGS identified 55 different microorganisms, whereas tNGS detected 49 pathogens. The comparative analysis of mNGS and tNGS revealed that 86.75% (72/83) of the specimens were complete or partial concordance. Particularly, mNGS and tNGS differed significantly in detection rates for some of the human herpesviruses only, including (P<0.001), (P<0.001), (P<0.05) and (P<0.01), in which tNGS always had higher detection rates. Orthogonal testing of clinically critical pathogens showed a total coincidence rate of 50% for mNGS and PCR, as well as for tNGS and PCR. Overall, the performance of mNGS and multiplex PCR-based tNGS assays was similar for bacteria and fungi, and tNGS may be superior to mNGS for the detection of DNA viruses. No significant differences were seen between the two NGS assays compared to PCR.

Extracellular vesicles (EVs) have been identified as key messengers of intracellular communication in health and disease, including the lung. EVs that can be found in bronchoalveolar lavage fluid (BALF) are released by multiple cells of the airways including bronchial epithelial cells, endothelial cells, alveolar macrophages, and other immune cells, and they have been shown to mediate proinflammatory signals in many inflammatory lung diseases. They transfer complex molecular cargo, including proteins, cytokines, lipids, and nucleic acids such as microRNA, between structural cells such as pulmonary epithelial cells and innate immune cells such as alveolar macrophages, shaping mutually their functions and affecting the alveolar microenvironment homeostasis. Here, we discuss this distinct molecular cargo of BALF-EVs in the context of inducing and propagating inflammatory responses in particular acute and chronic lung disorders. We present different identified cellular interactions in the inflammatory lung via EVs and their role in lung pathogenesis. We also summarize the latest studies on the potential use of BALF-EVs as diagnostic and prognostic biomarkers of lung diseases, especially of lung cancer.

There is a correlation between the dysbiosis of the respiratory microbiota and the occurrence, severity, frequency, and mortality of Chronic Obstructive Pulmonary Disease (COPD). However, it is not unclear if there are differences in the bronchoalveolar lavage fluid (BALF) microbiota among patients at differente lung function. In this study, BALF samples were collected from 70 COPD patients experiencing acute exacerbations (AECOPD). The patients were divided into a mild group (FEV1/pre ≥ 50; PFT I, n = 50) and a severe group (FEV1/pre < 50; PFT II, n = 20) according to the lung function: or a frequent exacerbation (FE, n = 41) group and a non-frequent exacerbation (NFE, n = 29) group according to their exacerbation history. Microbiota analysis of BALF samples was conducted using mNGS and bioinfromatic analysis. Compared to PFT I group, PFT II group exhibited a significant decrease in species diversity (Shannon index), as well as a significant reduction in total species count and richness (Chao1, ACE indices). NFE group demonstrated diversity similar to that of FE group. Conversely, the microbial diversity of NFE group was comparable to that of FE group. The most abundant bacterial genera were Streptococcus , Prevotella , Veillonella , Rod-shaped Bacillus , and Rothia . Aspergillus was the most dominant fungal genus in AECOPD. Lymphocryptovirus was the most prevalent virus in AECOPD.Compared to the PFT I group, Corynebacterium’s abundance significantly increased in PFT II group. Furthermore, FE group showed a notable increase in Streptococcus mitis abundance relative to NFE group. Bubble plot analysis revealed a significant increase in Moraxella , Fusobacterium , Haemophilus , Pseudomonas , Streptomyces , and Klebsiella in PFT II group, including a notable increase in typical Veillonella , Actinomyces , and Gordonia . The NFE group exhibited a significant increase in Bacteroides and Prevotella’s relative abundance. Spearman correlation analysis revealed strong positive correlations among certain microbial communities. There exists a significant variation in microbial composition across groups of AECOPD patients at different lung function. Specifically, patients with severe airflow limitations exhibit a significant reduction in microbial diversity. Additionally, distinct bacterial taxa are enriched in patients characterized by varying levels of airflow limitation and exacerbation frequency. These observations offer vital insights into the pathogenesis of AECOPD, suggesting a potentially crucial role for the microbiota in its development. Such findings pave the way for identifying potential therapeutic targets and intervention strategies, ultimately aiming to improve treatment outcomes for AECOPD patients.

Chronic obstructive pulmonary disease (COPD) is a heterogeneous condition, with varying clinical phenotypes and prognoses. Regulatory T cells (Tregs), particularly CD4 + FOXP3 + T cell subpopulations, are crucial in modulating immune responses. This study investigates the distribution of two CD4 + FOXP3 + T cell subpopulations in bronchoalveolar lavage fluid (BALF) from COPD patients and their association with disease phenotypes and prognosis. Patients were classified into Type A (lower frequencies of inflammatory FOXP3 lo T cells) and Type B (higher frequencies of inflammatory FOXP3 lo T cells). Type B COPD patients, who demonstrated more severe emphysema, heightened inflammatory responses, faster lung function decline, and more pronounced osteoporosis, showed a significant increase in FOXP3 lo non-suppressive T cells. In contrast, Type A patients exhibited a higher proportion of FOXP3 hi Treg cells, which correlated with milder disease phenotypes. The distinct distribution of CD4 + FOXP3 + T cell subpopulations provides insights into the progression of COPD and suggests that these cells could serve as potential biomarkers for disease severity and prognosis. Further research may offer new therapeutic avenues by targeting these Treg subpopulations in COPD management.

Canine idiopathic pulmonary fibrosis (CIPF) affects old dogs from the West Highland white terrier (WHWT) breed and mimics idiopathic pulmonary fibrosis (IPF) in human. The disease results from deposition of fibrotic tissue in the lung parenchyma causing respiratory failure. Recent studies in IPF using single-cell RNA sequencing (scRNA-seq) revealed the presence of profibrotic macrophage populations in the lung, which could be targeted for therapeutic purpose. In dogs, scRNA-seq was recently validated for the detection of cell populations in bronchoalveolar lavage fluid (BALF) from healthy dogs. Here we used the scRNA-seq to characterize disease-related heterogeneity within cell populations of macrophages/monocytes (Ma/Mo) in the BALF from five WHWTs affected with CIPF in comparison with three healthy WHWTs. Gene set enrichment analysis was also used to assess pro-fibrotic capacities of Ma/Mo populations. Five clusters of Ma/Mo were identified. Gene set enrichment analyses revealed the presence of pro-fibrotic monocytes in higher proportion in CIPF WHWTs than in healthy WHWTs. In addition, monocyte-derived macrophages enriched in pro-fibrotic genes in CIPF compared with healthy WHWTs were also identified. These results suggest the implication of Ma/Mo clusters in CIPF processes, although, further research is needed to understand their role in disease pathogenesis. Overexpressed molecules associated with pulmonary fibrosis processes were also identified that could be used as biomarkers and/or therapeutic targets in the future.

Immune checkpoint inhibitor related pneumonitis is a serious adverse reaction with diverse clinical and radiologic patterns, which make both diagnosis and treatment challenging. Therefore, understanding its underlying biology is crucial for improving clinical management. Bronchoalveolar lavage fluid provides a minimally invasive way to explore the lung immune environment, and it supports cytologic, molecular, and multi-omics analyses. In particular, BALF lymphocytosis serves as a key diagnostic sign. Furthermore, single-cell sequencing has revealed that abnormal T-cell activation and myeloid cell reprogramming play central roles in the development of CIP. These findings have, in turn, led to the identification of potential biomarkers such as CCL18, IL-6, and IP-10 for early detection and disease monitoring. However, the absence of standardized sampling and interpretation methods still limits the reproducibility of results and the broader application of BALF analysis in clinical practice. In the future, integrating BALF-derived data into artificial intelligence frameworks may enhance diagnostic precision and guide personalized therapy. Overall, BALF represents a valuable platform for refining CIP classification, clarifying disease mechanisms, and supporting the development of targeted treatments.

The secondary immunomodulatory effects of conventional therapeutics, such as antibiotics and cytostatics, are frequently overlooked despite their significant clinical implications. Building on our previous findings that drugs like paclitaxel and doxorubicin heavily influence macrophage polarization—potentially driving metastasis or inflammation—this study systematically evaluates the secondary immune-modulating actions of standard drugs and natural adjuvants. Using patient-derived bronchoalveolar lavage (BAL) fluid (ex vivo alveolar macrophages), we developed an analytical platform using synthetic carbohydrate-functionalized fluorescent ligands targeting key receptors (CD206, CD209, CD280, CD301). Integrating ligand-binding profiles with Linear Discriminant Analysis (LDA) yielded quantitative immune-state vectors capable of differentiating favorable and unfavorable prognostic signatures and imbalanced immune states. Pro-filing samples across heterogeneous respiratory conditions revealed highly con-text-dependent responses. While some treatments synergistically corrected unfavorable imbalanced profiles, others provoked dysregulation. Notably, in pneumonia or bronchitis with an asthma-prone M2-dominant profile, specific antibiotic regimens are critical; doxycycline, for instance, may exacerbate patient deterioration by further driving M2a polarization. Crucially, we identified that natural adjuvants (e.g., curcumin, coumarins, polyphenols) exhibit potent properties capable of correcting these adverse secondary drug effects. Ultimately, this profiling platform highlights the necessity of evaluating patient-specific secondary drug effects, offering a functional blueprint for precision immunotherapy and the rational design of adjuvant-enhanced treatments.