Imagine two patients arrive at a clinic with identical symptoms: persistent cough, fever, and concerning shadows on their lung X-rays. Both appear to have a serious respiratory infection, but one has tuberculosis (TB)—a highly contagious disease that requires immediate isolation and specific antibiotics—while the other has a non-tuberculous mycobacterial lung disease (NTM-LD), which isn't typically contagious but poses serious health risks and requires completely different treatment. For doctors, rapidly telling these conditions apart remains a significant challenge, with implications for both individual patient care and public health protection.
Until recently, science offered limited solutions to this diagnostic puzzle. But groundbreaking research has now uncovered an unexpected ally in this distinction: the community of microbes living in our lungs. A remarkable study published in 2025 reveals that subtle variations in a common bacterium called Serratia may hold the key to distinguishing between these similar lung diseases 1 4 . This discovery opens new avenues for understanding how the microscopic inhabitants of our respiratory system influence health and disease.
TB and NTM-LD present with similar symptoms but require different treatments and isolation protocols.
Serratia bacteria in the lung microbiome show distinct patterns that can differentiate between these diseases.
For centuries, medical science largely considered healthy lungs to be sterile. This assumption has been completely overturned in recent years with the revolutionary discovery of the lung microbiome—the diverse community of bacteria, viruses, and fungi that inhabit our respiratory system 3 . Unlike the gut microbiome which contains trillions of microbes, the lung microbiome is far less dense, with approximately 10-100 bacterial cells per 1,000 human cells . This ecosystem is now understood to play crucial roles in training our immune system and protecting against pathogens.
The composition of this microbial community is shaped by a dynamic balance of three factors: microbial immigration (through breathing and microaspiration), microbial elimination (through coughing and immune mechanisms), and regional growth conditions created by the local environment of the airways 3 . In diseased lungs, this balance is disrupted, creating conditions where certain microbes can thrive while others diminish.
Among the many bacteria that can call our lungs home, Serratia stands out as a particularly interesting genus. These Gram-negative bacteria belong to the Yersiniaceae family and are commonly found in soil, water, and even our intestinal tracts. While some Serratia species can cause opportunistic infections in hospital settings, their presence in the lung microbiome appears to be part of a normal, healthy ecosystem 9 .
What makes Serratia particularly fascinating to scientists is its metabolic flexibility and ability to produce various enzymes and bioactive compounds. These traits allow different Serratia species to interact in distinct ways with our immune system and with other microbes in the lung environment 1 . Recent research suggests that specific Serratia traits might influence whether people develop active TB after exposure to the tuberculosis bacterium or progress to active NTM lung disease after encountering environmental mycobacteria.
To better understand the lung microbiome's role in mycobacterial diseases, researchers at the Research Center Borstel in Germany designed a comprehensive study comparing the microbial communities of patients with different lung conditions 1 2 4 . Their investigation included:
The researchers employed 16S rRNA amplicon sequencing—a technique that identifies bacteria by reading a specific genetic signature—to characterize the microbial composition in each sample. They supplemented this with exploratory whole-metagenome sequencing on selected specimens to gain finer taxonomic resolution 2 4 .
| Patient Group | Number of Patients | Average Age Range | Key Characteristics |
|---|---|---|---|
| Tuberculosis (TB) | 23 | 60-69 years (majority) | Some with HIV/hepatitis co-infections |
| NTM Lung Disease | 19 | 60-69 years (majority) | Some with COPD, bronchitis, or pneumonia |
| Non-infectious Inflammatory Disease | 4 | Spanning 10-89 years | Control group for comparison |
2003-2017: BALF samples collected from patients before antibiotic treatment
Human cell depletion and extracellular DNA removal to ensure accurate microbiome analysis
16S rRNA amplicon sequencing and exploratory whole-metagenome sequencing
Identification of microbial signatures and statistical analysis of differences between patient groups
When the sequencing data was analyzed, the researchers made a surprising discovery: the genera Serratia and unclassified Yersiniaceae dominated the lung microbiome across all patient groups, with mean relative abundances of >15% and >70%, respectively 1 2 . At first glance, the lung microbiomes of TB and NTM-LD patients appeared remarkably similar at this broad taxonomic level.
The real breakthrough came when researchers looked deeper at the sub-genus level, examining what are known as amplicon sequence variants (ASVs)—fine genetic differences that distinguish bacterial strains. Here, clear patterns emerged: TB patients exhibited increased community diversity and distinct signatures of specific ASVs, particularly ASV_7 (unclassified Yersiniaceae) and ASV_21 (Serratia) 2 6 .
Through further analysis, the team identified that these ASV signatures corresponded to specific Serratia species, including Serratia liquefaciens, Serratia grimesii, Serratia myotis, and Serratia quinivorans 1 . The presence or absence of certain Serratia traits was significantly associated with disease state, suggesting these subtle variations might play a role in the different pathways of TB versus NTM lung disease.
Serratia and unclassified Yersiniaceae dominated across all patient groups
Distinct ASV patterns differentiated TB from NTM patients
S. liquefaciens, S. grimesii, S. myotis, S. quinivorans associated with disease state
| Analysis Level | TB Patients | NTM-LD Patients | Statistical Significance |
|---|---|---|---|
| Genus Level | Dominated by Serratia and unclassified Yersiniaceae | Similar dominance pattern | Not significant |
| Sub-genus (ASV) Level | Distinct ASV_7 and ASV_21 signatures; increased diversity | Different ASV patterns | Significant association with disease state |
| Identified Species | Serratia liquefaciens, S. grimesii, S. myotis, S. quinivorans | Similar species but different abundances | Suggestive of ecological differences |
Cutting-edge lung microbiome research relies on specialized reagents and methodologies to overcome the unique challenges of working with low-biomass samples from the respiratory tract 2 4 .
Sterile saline solution is instilled into the airways and recollected, providing a sampling of the distal lung environment. This method offers a more direct representation of the lung microbiome than sputum samples, which can be contaminated by oral bacteria 2 .
Enzymatic treatments that degrade DNA outside bacterial cells, ensuring that sequencing results reflect viable, intact microorganisms rather than genetic debris from dead microbes 2 .
Computational tools and pipelines for processing sequencing data, identifying microbial taxa, and performing statistical analyses to identify significant differences between patient groups.
The German study's findings gain even more significance when viewed alongside complementary research from South Korea published in the same year. The Korean study analyzed BALF samples from 108 patients (38 TB, 29 NTM, 41 other respiratory diseases) and identified distinct microbial signatures for each condition 5 .
In TB patients, prominent species included Enterococcus faecalis, Streptococcus mutans, and Snodgrassella alvi, while NTM patients showed enrichment of Cariobacterium hominis and Prevotella nigrescens 5 . Notably, the Korean team developed a machine learning approach that could differentiate the conditions based solely on microbiome patterns, with the absence of Mobiluncus curtisii and presence of Cariobacterium hominis indicating a higher probability of NTM 5 .
These parallel findings from different continents and patient populations suggest that lung microbiome signatures could eventually be developed into reliable diagnostic tools, potentially supplementing existing methods that sometimes struggle to distinguish these conditions quickly enough.
Beyond diagnosis, these findings raise fascinating questions about the ecological relationships between Serratia species and pathogenic mycobacteria in the lung environment. The distinct Serratia traits observed in TB patients might create conditions that either encourage or discourage Mycobacterium tuberculosis growth and invasion 1 . Alternatively, these microbial patterns might reflect or even influence the host immune response to different mycobacterial pathogens.
This ecological perspective aligns with another 2025 study in BMC Microbiology that identified two distinct lung microbiome community types (pneumotypes) in NTM patients, with one type associated with significantly worse treatment outcomes 7 . Patients with "pneumotype 1"—characterized by co-dominance of Mycobacterium, opportunistic pathogens, and anaerobes—had a lower probability of sustained culture conversion (hazard ratio = 0.29) than those with "pneumotype 2," indicating a worse prognosis 7 .
| Application Area | Current Challenge | Microbiome-Based Solution |
|---|---|---|
| Diagnosis | Distinguishing TB from NTM-LD is difficult and time-consuming | Microbial signatures as diagnostic biomarkers |
| Prognosis | Limited ability to predict disease progression or treatment response | Pneumotype classification to identify high-risk patients |
| Treatment | Standardized regimens despite varied patient responses | Personalized approaches based on individual microbiome profiles |
| Prevention | Limited understanding of why some exposed individuals develop active disease | Microbiome modulation to reduce susceptibility |
The discovery that Serratia traits distinguish TB from NTM lung diseases represents more than just a potential diagnostic tool—it signifies a fundamental shift in how we understand respiratory health and disease. Rather than viewing lungs as merely passive victims of pathogenic invasion, we're beginning to appreciate them as complex ecosystems where the balance of microbial inhabitants significantly influences disease outcomes.
This new perspective opens exciting possibilities for future therapies. Could we eventually modulate the lung microbiome to create environments less favorable to pathogenic mycobacteria? Might specific Serratia species or their metabolic products yield new anti-mycobacterial compounds? While these questions remain to be answered, the path forward is clear: understanding the intricate relationships between our bodies and our microbial inhabitants will be crucial for developing better diagnostics and treatments for respiratory diseases that continue to affect millions worldwide.
As research in this field progresses, we move closer to a future where a simple analysis of a patient's lung microbiome could guide personalized treatment decisions, potentially transforming the management of not just TB and NTM-LD, but potentially many other respiratory conditions as well.