Molecular epidemiology of non-tuberculous mycobacteria in clinical samples from Jiangxi Province, 2021–2023

Abstract

Background

Non-tuberculous mycobacteria (NTM) pose diagnostic and therapeutic challenges in tuberculosis (TB)-endemic regions like Jiangxi Province, China, due to clinical and radiological similarities to TB. This study elucidates the molecular epidemiology of NTM in Jiangxi (2021–2023).

Methods

A retrospective analysis of 20,724 clinical specimens from Jiangxi Chest Hospital was conducted using PCR-reverse blot hybridization assay (PCR-REBA) for NTM species identification. Inclusion required clinical/radiological suspicion of mycobacterial disease and specimens with sufficient volume (≥ 2 mL for liquid samples or ≥ 0.5 g for tissue). Statistical analyses determined prevalence, species distribution, and predictors.

Results

Among 5,331 Mycobacterium-positive specimens, 333 (1.60%; 95% CI: 1.43–1.77) were NTM. Males had significantly lower odds of infection than females (aOR 0.499, P < 0.001), with the highest prevalence observed in individuals aged ≥ 65 years (2.64%) compared to the ≤ 24 years reference group (aOR 12.922, 95% CI: 5.288–31.578, P < 0.001). Dominant species were Mycobacterium intracellulare (MIN, 51.7%), Mycobacterium abscessus (MAB, 30.9%), and Mycobacterium avium (MAV, 9.3%). MIN and MAB predominated in pulmonary samples (97.9% of cases), while MAV showed significant extrapulmonary tropism (42.9% vs. 8.6% pulmonary, P = 0.02). Detection rates fluctuated temporally (peak: 1.93% in 2021; trough: 1.20% in 2022; P = 0.004), potentially influenced by the COVID-19 pandemic.

Conclusion

Jiangxi exhibits a distinct NTM profile with elevated MAB prevalence, emphasizing the need for species-level diagnosis to prevent misclassification as multidrug-resistant TB. Age, sex, and temporal trends emphasizing the critical need for species-level identification to facilitate early, targeted antimicrobial therapy and prevent the misclassification of NTM as multidrug-resistant TB.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12866-026-04732-2.

Introduction

The Mycobacterium genus comprises over 190 named species, each exhibiting distinct phenotypic and genotypic characteristics, as well as unique virulence traits [1]. Among these, Mycobacterium tuberculosis (M. tb), Mycobacterium leprae, and non-tuberculous mycobacteria (NTM) species are the primary human pathogens [2]. M. tb is the causative agent of tuberculosis (TB), a progressive granulomatous infectious disease transmitted via airborne particles from infected individuals through coughing, sneezing, or spitting. TB predominantly affects the lungs and has re-emerged as the second leading infectious killer globally in the post-COVID-19 era, surpassing AIDS [3]. In 2022, TB claimed approximately 1.3 million lives worldwide, including 167,000 individuals with HIV, with the highest burden observed in developing countries [4].

NTM species represent a group of opportunistic pathogens distinct from M. tb and M. leprae. Ubiquitous in natural and human-influenced environments such as soil, water, milk, and food products, NTM infections manifest across a broad clinical spectrum [5]. These include pulmonary diseases, disseminated infections in immunocompromised individuals, skin and soft tissue infections, and superficial lymphadenitis, particularly cervical lymphadenitis in pediatric patients [6]. Globally, the incidence and prevalence of NTM pulmonary disease (NTM-PD) are rising, often associated with poor clinical outcomes [7]. The nonspecific symptoms of NTM-PD, such as cough, dyspnea, hoarseness, and bronchospasm, overlap with those of other pulmonary infections, complicating diagnosis [8]. Furthermore, the fibrocavitary radiological patterns of NTM-PD closely resemble those of pulmonary tuberculosis (PTB), making differentiation based solely on imaging or clinical features nearly impossible [9].

The diagnostic challenge is exacerbated by the inherent resistance of NTM to standard first-line antituberculosis medications [10]. This complicates the management of patients co-infected with M. tb and NTM, who are frequently misclassified as having multidrug-resistant tuberculosis (MDR-TB) [11]. In high-TB-burden regions, NTM lung infections are often misdiagnosed as PTB, leading to ineffective treatments, repeated therapeutic failures, and increased morbidity [12]. Accurate identification of Mycobacterium species is critical, as treatment protocols are highly specific to NTM strains. Traditional diagnostic methods, such as biochemical and immunological assays, are limited by cross-reactivity, prolonged turnaround times, and insufficient sensitivity.

To overcome these limitations, molecular techniques such as the PCR-based reverse blot hybridization assay (PCR-REBA) have emerged as superior tools for concurrent detection and precise identification of NTM species [13]. PCR-REBA leverages 16 S rRNA sequencing and species-specific probes, offering practical advantages in clinical settings, including rapid processing and compatibility with standard laboratory equipment. Commercial kits like PCR-REBA Myco-ID enable the identification of 22 clinically significant mycobacterial species, streamlining diagnostics and facilitating targeted treatment. This study employs PCR-REBA to elucidate the molecular epidemiology of NTM in Jiangxi Province, a high-TB-burden region in China, aiming to enhance understanding of regional NTM trends and inform global surveillance strategies.

Materials and methods

Study design, site, and population

This retrospective analytical study was conducted at Jiangxi Province Chest Hospital (the only provincial TB-designated tertiary medical institution) in Jiangxi province, which covers approximately 45.0 million inhabitants—a high TB incidence region in South China. Patients with clinical or histological findings compatible with TB or NTM between January 2021 and December 2023 were eligible. In this study, NTM confirmation was defined as a positive species-level identification via the PCR-REBA Myco-ID assay. To distinguish true infection from potential environmental contamination, inclusion was strictly limited to patients presenting with both (1) clinical symptoms suggestive of mycobacterial disease and (2) corresponding radiologic or histologic evidence. While these criteria align with the clinical suspicion of NTM disease, the study categorized these cases as ‘NTM-positive’ based on molecular detection within a clinical context. Inclusion criteria were: (1) Symptoms or signs suggestive of mycobacterial disease (e.g., persistent cough > 2 weeks, fever, weight loss, hemoptysis); (2) Radiologic findings (e.g., cavities, nodules, infiltrates) or histologic evidence (e.g., granulomas, acid-fast bacilli); (3) Availability of specimens for PCR-REBA testing. Exclusion criteria were: (1) Insufficient specimen volume (< 1 mL for liquid samples) or samples consisting primarily of saliva; (2) Missing demographic data. Disease categories were defined as: Pulmonary TB/NTM: Involvement of lung parenchyma/tracheobronchial tree (± mediastinal lymph nodes); Extrapulmonary TB/NTM: Disease at sites outside the lungs (e.g., pleura, peripheral lymph nodes, CNS, genitourinary tract, bones/joints). Data on prior TB treatment history was not consistently available in medical records and thus not collected. Patient data were evaluated from archived PCR-REBA results.

Specimen collection

Specimens were collected from patients with clinical or radiographic findings suggestive of tuberculosis (TB) or nontuberculous mycobacterial (NTM) infection. To ensure analytical validity, all samples met predefined laboratory quality standards and minimum volume requirements (≥ 2 mL for liquids; ≥0.5 g for tissues). The collected specimens were categorized as: (1) Purulent specimens (e.g., sputum, purulent bronchoalveolar lavage fluid, purulent pleural fluid); (2) non-purulent fluids specimen (e.g., CSF, urine, clear pleural fluid); (3) Solid specimens (e.g., tissue biopsies, lymph node aspirates).

Specimen processing

The purulent specimens (e.g., sputum, purulent bronchoalveolar lavage fluid, purulent pleural fluid) underwent digestion with an equal volume of 4% NaOH for 10 min at room temperature. The mixture was centrifuged at 12,000 g for 5 min, and the supernatant was discarded. Non-purulent fluid specimens (e.g., cerebrospinal fluid, urine, clear pleural fluid) were centrifuged directly at 12,000 g for 5 min at room temperature, followed by supernatant removal. Solid specimens (e.g., tissue biopsies, lymph node aspirates) were homogenized in an equal volume of sterile water using a sterile mortar and pestle. The homogenate was centrifuged at 12,000 g for 5 min at room temperature, and the supernatant was discarded. For all specimen types, the resulting pellet was washed with 1 mL of washing solution (Yaneng BioSciences, Shenzhen, China). The suspension was centrifuged at 12,000 g for 3 min, and the supernatant was discarded. The final pellet was used for DNA isolation.

DNA isolation

The bacterial pellet was extracted with DNA lysis solution (Yaneng BioSciences, Shenzhen, China), and the suspended bacterial solution was boiled at 100 °C for 10 min, and centrifuged at 12,000 r/min for 3 min. The supernatant containing genomic DNA samples were either used immediately or stored at 80 C pending analysis.

Real-time polymerase chain reaction

5µL of each DNA sample was applied into the PCR tubes (Yaneng BioSciences, Shenzhen, China) which contained reaction mixture including primer, Taq man polymerase, and dN(U)TP. The experimental protocol and subsequent real-time PCR program conducted on the ABI instrument were meticulously configured as follows: An initial incubation at 50 °C for 2 min, followed by a single cycle. A gradual ramp-up from 50 °C to 95 °C at a rate of 1.4 °C per second. A hold at 95 °C for 10 min, constituting a single cycle. A denaturation step at 95 °C for 45 s, followed by a transition from 95 °C to 62 °C at a rate of 1.4 °C per second, and an annealing/extension step at 60 °C for 30 s, repeated for 30 cycles. Another ramp-up from 62 °C to 95 °C at 1.4 °C per second, a denaturation at 95 °C for 30 s, a transition from 95 °C to 54 °C at 1.4 °C per second, an annealing step at 54 °C for 30 s, and an extension at 68 °C for 45 s, repeated for 30 cycles. A final extension at 68 °C for 5 min to complete the program. The mixture was added to the reaction to detect the amplification of target bacterial DNA (7500 Real-Time PCR System, Thermo Fisher Scientific, Waltham, MA, USA). The analysis of the real-time PCR results was facilitated by the Real-Time PCR Software, version 1.2.3 and the amplification plots were reviewed for baseline and threshold value correction.

PCR-reverse blot hybridization assay (PCR-REBA Myco-ID)

The amplified PCR products were detected for Mycobacterium species identification using PCR-REBA Myco-ID kit (Yaneng BioSciences, Shenzhen, China), following the manufacturer’s protocol.

Hybridization

The nylon membrane strip labeled with probes was place into 15 ml conical centrifuge tubes, gently mixed well with 5 ml of hybridization buffer (containing 2x Saline-sodium citrate, SSC; and 0.1% Sodium dodecyl sulfate, SDS) and all the PCR product (25 µl). The tube was tightly sealed with cap and heated in the boiling water bath (100℃) for 10 min (ensuring that the hybridization liquid level is completely below the level of boiling water bath). The tube was placed in a hybridization box at 57 ℃ for 1.5 h.

Washing strips

40mL of wash buffer (containing 0.5x SSC; and 0.1% SDS) was transformed into a 50 mL conical centrifuge tube with screw-top cap and preheat to 57 ℃ in a water bath. The membrane strips were taken out from the 15 ml tube and transferred into the preheated wash buffer at 57 ℃ for 15 min, and gently shaken.

Colorimetric analysis

The membrane strips were incubated with a 1:2000 dilution of streptavidin-peroxidase conjugate (POD) in hybridization buffer at room temperature for 30 min with gentle shaking. The POD solution was then discarded. The strips were washed twice with hybridization buffer for 5 min each at room temperature with gentle shaking, followed by a 2-minute rinse with 0.1 mol/L sodium citrate at room temperature. Color development was performed by incubating the strips in a freshly prepared substrate solution containing 0.01% (w/v) tetramethylbenzidine dihydrochloride (TMB) and 0.006% (v/v) hydrogen peroxide in 0.1 M sodium citrate, under dark conditions for 10 min. The reaction was stopped by rinsing the membranes thoroughly with distilled water. The hybridization band patterns were interpreted visually by the naked eye.

Quality control

To ensure assay validity and control for false positives and negatives, internal controls were included in each run. For the PCR amplification, one positive control (DNA from inactivated Mycobacterium species) and one negative control (DNA from inactivated Escherichia coli) were processed alongside clinical samples. For the hybridization assay, each membrane strip contains a Colorimetric Control (CC) point. This point is coated with a biotin-labeled probe that binds the streptavidin-peroxidase conjugate during the colorimetric analysis step. A visible blue CC spot confirms the successful completion of the hybridization, POD incubation, and color development procedures. The absence of CC spot coloration invalidates the test run.

Statistical analysis

Data were statistically analyzed using the Statistical Package for Social Sciences (SPSS) version 27.0 (IBM Corp, USA). Categorical data were presented as frequencies, percentages, and 95% confidence intervals (95% CI). Univariate and multivariable logistic regression analyses were performed to evaluate predictors of NTM infection, with age and sex included as covariates based on their established epidemiological relevance to NTM susceptibility. Chi-square tests were used for large sample sizes, and Fisher’s exact tests were applied for small sample sizes to assess differences in variables (e.g., species distribution, detection trends). No adjustment for multiple comparisons was made, as the analysis was exploratory and focused on predefined demographic variables. A P-value < 0.05 was considered statistically significant.

Results

Socio-demographic and clinical characteristics of NTM infections

Among the 20,724 clinical specimens analyzed, representing 20,724 individual patients, Mycobacterium genus infections were identified in 5,331 (25.7%) cases. NTM were confirmed in 333 specimens, representing 1.60% (95% CI: 1.43–1.77) of the total specimens and 6.2% (95% CI: 5.6–6.9) of the Mycobacterium genus infections (Fig. 1). The prevalence of NTM by age group and sex, along with 95% confidence intervals, is detailed in Table 1. Univariate and multivariable logistic regression analysis revealed significant disparities in NTM prevalence based on age and sex. Using the ≤ 24 years age group as the reference (prevalence 0.23%), the risk of NTM infection demonstrated a striking age-dependent increase, peaking in the ≥ 65 years group (aOR 12.922, 95% CI 5.288–31.578, P < 0.001). No NTM cases were detected in pediatric populations (0–14 years). Females demonstrated a significantly higher infection rate than males; the adjusted odds ratio for males was 0.505 (95% CI 0.406–0.629, P < 0.001) compared to the female reference group. Additionally, cases of MTC and NTM coinfection were identified and are summarized in Supplementary Table 1.

Fig. 1.

Schematic overview of Mycobacterium genus infectionanalysis in the study. Schematic flowchart illustrating the specimen processing and analysisworkflow for the identification of Mycobacterium tuberculosis complex (MTC)and non-tuberculous mycobacteria (NTM) from clinical samples

Table 1.

Univariable and multiple logistic regression analysis of predictors for NTM infection*

Variable	Total(n)	NTM cases, n(%)	Prevalence,% (95%CI)	Univariable Analysis		Multivariable Analysis
				Odds Ratio (95%CI)	P Value	Odds Ratio (95%CI)	P Value
Overall	20,724	333	1.61(1.44,1.78)
Age
0 ~ 25	2211	5	0.23(0.03,0.42)	1(Reference)
25 ~ 45	4163	31	0.74(0.48,1.01)	3.31(1.285,8.525)	0.013	3.21(1.246,8.269)	0.016
45 ~ 65	8904	153	1.72(1.45,1.99)	7.714(3.162,18.821)	< 0.001	7.859(3.221,19.179)	< 0.001
≥ 65	5446	144	2.64(2.22,3.07)	11.983(4.906,29.267)	< 0.001	12.922(5.288,31.578)	< 0.001
Sex
Male	13,455	171	1.27(1.08,1.46)	0.565(0.455,0.701)	< 0.001	0.505(0.406,0.629)	< 0.001
Female	7269	162	2.23(1.89,2.57)	1(Reference)

* NTM non-tuberculous mycobacteria species

Dominant NTM species and their age-specific distribution

Species identification of 333 NTM isolates revealed 10 distinct species, with an overall detection rate of 1.6% (Supplementary Table 2). Chi-square analysis indicated significant age-specific variations in their distribution: MIN (χ² = 26.435, P < 0.001), MAV (χ² = 11.648, P = 0.006), and MAB (χ² = 8.821, P = 0.025) (Table 2). MIN infections were most prevalent in the ≥ 65 years age group (n = 91, 52.9% of MIN cases), followed by the 45–64 years group (n = 75, 43.6%). MAB infections also peaked in the 45–64 years group (n = 44, 42.7%) and the ≥ 65 years group (n = 40, 38.8%), while MAV showed a higher frequency in the 45–64 years group (n = 18, 58.1%). No significant sex-based differences were observed for MIN (P = 0.73), MAB (P = 0.488), or MAV (P = 0.359) (Supplementary Table 3).

Table 2.

Age-specific distribution of the top three Circulating NTM strains

NTM	0 ~ 25	25 ~ 45	45 ~ 65	≥ 65	Total	χ2	P Value
MIN	1(0.6)	5(2.9)	75(43.6)	91(52.9)	172(51.7)	26.435	< 0.001*
MAB	3(2.9)	16(15.5)	44(42.7)	40(38.8)	103(30.9)	8.821	0.025
MAV	0(0)	7(22.6)	18(58.1)	6(19.4)	31(9.3)	11.648	0.006

* using Fisher’s exact test

Pulmonary and extrapulmonary tropism of NTM species

Among the 333 NTM cases, 326 (97.9% [95% CI: 95.8–99.0]) were isolated from pulmonary specimens, while 7 (2.1% [95% CI: 0.96–4.20]) originated from extrapulmonary sites (Supplementary Table 4). MAV demonstrated a significant association with extrapulmonary infections, accounting for 42.9% [95% CI: 15.8–74.9] (n = 3) of extrapulmonary cases compared to 8.6% [95% CI: 5.9–12.1] (n = 28) of pulmonary isolates (χ² = 9.532, P = 0.02) (Table 3). In contrast, MIN and MAB showed no significant tropism differences between pulmonary and extrapulmonary specimens (MIN: P = 0.106; MAB: P = 0.582). MIN predominated in pulmonary samples (52.5% [95% CI: 46.8–58.1], n = 171), while MAB represented 31.3% (n = 102) of pulmonary isolates.

Table 3.

Comparison of infection frequency of top the top three Circulating NTM strains between extrapulmonary and pulmonary specimens

NTM, n (%)	Pulmonary	Extra pulmonary	Total	χ2	P Value
MIN	171(52.5)	1(14.3)	172(51.7)	2.615	0.106*
MAB	102(31.3)	1(14.3)	103(30.9)	0.302	0.582*
MAV	28(8.6)	3(42.9)	31(9.3)	9.532	0.020
Total	326(100)	7(100)	333(100)

Note: * using continuity correction in Chi-Square Test

Temporal trends in NTM detection rates

The NTM detection rate varied annually, with the highest rate recorded in 2021 at 1.93% and the lowest in 2022 at 1.20% (Table 4). The overall detection rate across the three years was 1.61%. The statistical analysis indicated a significant difference in detection rates (χ²=11.18, P = 0.004), suggesting a change in the prevalence of NTM over time. The sex distribution showed a near balance between males and females, with an overall ratio of 1:0.947. The χ² test did not reveal a significant difference in sex distribution across the years (χ²=2.23, P = 0.328). The age distribution showed a mean age of 61.45 years with a standard deviation of 12.83 years, indicating that the majority of NTM cases occurred in the elderly population. The F test did not show a significant difference in age distribution across the years (F = 0.592, P = 0.554), suggesting that the age profile of NTM cases remained consistent. Notably, the fluctuation in detection rates coincided with the COVID-19 pandemic, with the highest rate in 2021 during the critical phase of the pandemic.

Table 4.

Analysis of of NTM detection rate, sex, and, age distribution across the years 2020 to 2023

Variable	2021	2022	2023	Total	F/χ2	P value
Mycobacteria not detected	4982	4586	5825	15,393
NTM	130	74	129	333
MTC	1618	1525	1855	4998
NTM detection rate [95% CI]	1.93% [1.62–2.29%]	1.20% [0.95–1.50%]	1.65% [1.39–1.96%]	1.61% [1.45–1.79%]	11.18	0.004
Sex distribution
Male: Female	1:0.89	1:0.76	1:1.2	1:0.9	2.23	0.328
Counts (M: F)	69:61	42:32	60:69	171:16
Age (mean ± SD, years)	62.15 ± 12.34	60.12 ± 14.13	61.50 ± 12.56	61.45 ± 12.83	0.592	0.554

Annual distribution of NTM species

Throughout the study period from 2021 to 2023, MIN remained the consistently dominant species among the NTM isolates, followed by MAB and MAV (Supplementary Table 5). Although minor annual fluctuations were observed—such as a slight increase in the proportion of MAV in 2022—statistical analysis indicated that the species distribution remained stable over time. No significant annual differences were observed in the prevalence of MIN, MAB, or MAV (all P > 0.05; Table 5).

Table 5.

Prevalence trends of the top three Circulating NTM strains from 2021 to 2023

NTM	2021	2022	2023	Total	χ2	P Value
MIN	69(53.08)	33(44.59)	70(54.26)	172(51.65)	1.934	0.38
MAB	43(33.08)	26(35.14)	34(26.36)	103(30.93)	2.156	0.34
MAV	9(6.92)	10(13.51)	12(9.3)	31(9.31)	2.426	0.297

Discussion

Our comprehensive analysis of NTM epidemiology in Jiangxi Province, a high TB-burden region in China, reveals critical insights into population susceptibility, The risk of NTM infection showed a striking age-dependent increase, with individuals aged ≥ 65 years exhibiting a nearly 13-fold higher risk (aOR 12.922) compared to those aged ≤ 24 years. This aligns with global patterns of NTM pulmonary disease (NTM-PD), reinforcing the role of age-related imunosenescence and potential sex-specific factors in susceptibility [14, 15]. The absence of NTM cases in pediatric cohorts (0–14 years) further supports the established epidemiology where pediatric NTM disease primarily manifests as lymphadenitis, a presentation less likely to yield the pulmonary specimens dominating this study [16, 17]. The pronounced female predominance (aOR 0.505 for males) observed here resonates with findings from Japan [18, 19] and Korea [20], suggesting shared biological or environmental risk factors across East Asian populations, although contrasting reports from Western regions like Denmark [21] and Northern Israel [22] highlight significant geographical heterogeneity necessitating region-specific investigations.

Our findings in Jiangxi Province, China (2021–2023) identify MIN (51.7% [95% CI: 46.1–57.2]), MAB (30.9% [95% CI: 26.1–36.1]), and MAV (9.3% [95% CI: 6.4–12.9]) as the predominant NTM, consistent with China’s general MIN-MAB-MAV distribution pattern [23]. However, Jiangxi exhibits distinct regional characteristics: while aligning with southern provinces like Fujian (MIN 65.73%, MAB 18.78%) [24] and Hainan (MIN 39.49%, MAB 32.91%) [25], and Jiangsu (MIN 50.4%, MAV 17.3%, MAB 12.9%) [26], it diverges markedly from northern provinces (e.g., Shandong/Henan: MIN 69.8–74.4%, MAB 5.8–9.9%) [27, 28] with its significantly elevated MAB prevalence (30.9% vs. 5.8–9.9%). This high MAB burden parallels southern Guangdong (41.2%) [29] but contrasts with northern Shaanxi (26.6%) [30]. Globally, Jiangxi’s MIN predominance mirrors East Asia (South Korea: MIN 45.8% [31]) but differs from European (Poland: M. kansasii 34% ) [32] and Southeast Asian profiles (Singapore: MAB 49.9%) [33]. Its species profile intermediates between coastal Jiangsu (MAB 12.9%) [26] and Guangdong’s MAB dominance (41.2%) [29], establishing Jiangxi as an epidemiological transitional zone with a uniquely high MAB burden that distinguishes it from northern China and aligns it with southern hotspots. Crucially, the study identified significant age-dependent variations in species distribution: MIN and MAB exhibited a clear predilection for the elderly (≥ 65 years: MIN 57.6%, MAB 40.8%), while MAV peaked in middle age (45–54 years: 35.5%). This age stratification, confirmed by robust chi-square analyses (MIN: χ²=36.515, P < 0.001; MAB: χ²=11.403, P = 0.034; MAV: χ²=18.083, P = 0.002), strongly implicates complex interactions between cumulative environmental exposures, host immune status, and intrinsic pathogen factors over the lifespan. The lack of significant sex-based differences for these major species suggests that the overall female predominance in NTM infection may stem from factors affecting susceptibility broadly rather than tropism for specific species. This geographical heterogeneity in species prevalence is likely influenced by a combination of factors, including differences in climate, soil and water ecosystems (environmental reservoirs), host genetic predispositions in distinct populations, and variations in laboratory diagnostic capabilities and clinician awareness across regions.

A key finding with direct clinical implications is the distinct extrapulmonary tropism demonstrated by MAV. MAV was significantly associated with extrapulmonary infections (42.9% [95% CI: 15.8–74.9] of extrapulmonary cases vs. 8.6% [95% CI: 5.9–12.1] of pulmonary isolates; χ²=9.532, P = 0.02), consistent with its established role in disseminated disease in immunocompromised hosts and pediatric lymphadenitis [17, 34, 35]. This contrasts sharply with MIN and MAB, which showed no significant preference for extrapulmonary sites. Consequently, the detection of MAV, particularly in non-pulmonary specimens, warrants heightened clinical suspicion for disseminated infection or lymph node involvement, especially in vulnerable populations. The overwhelming predominance of pulmonary specimens (97.9%) in our cohort underscores the primary challenge of NTM-PD in this region and its potential for misdiagnosis as pulmonary TB.

The significant temporal fluctuation in NTM detection rates (χ²=11.18, P = 0.004), peaking in 2021 (1.93% [95% CI: 1.62–2.29]) and dipping in 2022 (1.20% [95% CI: 0.95–1.50]), reveals a dynamic epidemiological landscape. While consistent environmental factors like climate or water distribution systems likely contribute to baseline endemicity [36], the 2021 peak coincides with the COVID-19 pandemic’s critical phase. This temporal association raises plausible hypotheses regarding pandemic impacts. The peak in 2021 might be attributed to several factors: (1) increased hospital admissions and diagnostic testing for respiratory symptoms during the pandemic, leading to higher detection of NTM; (2) the potential for SARS-CoV-2 co-infection or post-COVID-19 lung damage creating an opportunistic environment for NTM colonization and infection [37]; and (3) the widespread use of immunosuppressive therapies (such as corticosteroids) for severe COVID-19 [38], which might have predisposed patients to NTM infections. Conversely, the dip in 2022 could reflect a temporary reduction in healthcare access due to pandemic-related restrictions or a shift in clinical focus towards COVID-19, resulting in underdiagnosis of NTM [39]. It is also possible that the natural dynamics of respiratory pathogens were altered by non-pharmaceutical interventions (e.g., mask-wearing, social distancing) during the pandemic, which might have reduced exposure to NTM in 2022. However, the subsequent rebound in 2023 (1.65%) suggests a return towards pre-pandemic patterns. These hypotheses are supported by studies from other regions, such as Iran, which documented increased NTM incidence during the pandemic [40], and research highlighting the vulnerability of geriatric patients to NTM in this context [41]. Although our study lacks direct coinfection data, these parallels underscore the need for future investigations into pandemic-driven NTM dynamics. However, the stability in the mean age of cases (~ 61.45 years, F = 0.592, P = 0.554) and sex distribution (χ²=2.23, P = 0.328) across the study years reinforces the persistent vulnerability of the elderly population, likely driven by comorbidities like chronic obstructive pulmonary disease, prior TB, bronchiectasis, or silicosis prevalent in this demographic [42].

Clinically, the dominance of MIN (51.7%) and MAB (30.9%) in Jiangxi poses therapeutic challenges. MIN infections typically require macrolide-based multidrug regimens (e.g., azithromycin/ethambutol/rifampin), but emerging macrolide resistance necessitates susceptibility testing prior to treatment [43, 44]. MAB, intrinsically resistant to most antimycobacterial, demands aggressive initial therapy with parenteral agents (e.g., amikacin/imipenem) followed by oral macrolide/clofazimine combinations, emphasizing the need for early species identification to avoid futile standard TB therapy [45–47]. MAV’s extrapulmonary tropism (42.9% of extrapulmonary cases) warrants vigilance for disseminated disease in immunocompromised hosts, managed with clarithromycin/ethambutol/rifabutin regimens [48, 49]. Crucially, misdiagnosis of these NTM as MDR-TB perpetuates ineffective treatment; thus, Jiangxi’s TB programs must prioritize species-directed therapy.

Several limitations warrant consideration. The retrospective design using data from a single tertiary referral center may introduce selection bias, potentially overrepresenting severe or complex cases and limiting generalizability to community settings or asymptomatic colonization. The reliance on PCR-REBA, while highly specific and advantageous for rapid identification of the 22 targeted species, may miss rare or newly emerging NTM species not included in the assay panel. The exclusion of specimens with insufficient volume may have introduced selection bias, potentially affecting the overall prevalence estimates. The lack of detailed clinical data (e.g., immune status, specific comorbidities, treatment history, environmental exposures) and outcomes precludes analysis of risk factors beyond basic demographics and prevents assessment of the clinical significance of all NTM isolates (disease vs. colonization). Furthermore, as a retrospective molecular epidemiological study, the primarily report the prevalence of NTM isolation among symptomatic patients. While the inclusion criteria required clinical and radiological suspicion, it could not strictly apply the full ATS/IDSA diagnostic criteria for NTM Pulmonary Disease (NTM-PD)—which requires multiple positive cultures over time—for every patient in this cohort. Consequently, some cases may represent persistent colonization rather than active disease. Future prospective studies incorporating longitudinal clinical follow-up are needed to further delineate the progression from NTM isolation to clinical disease in this region.

Conclusions

This study provides the first comprehensive molecular epidemiological profile of NTM in Jiangxi Province, China. The study identified a distinct NTM species distribution dominated by MIN (51.7%), MAB (30.9%), and MAV (9.3%). Notably, the prevalence of MAB significantly exceeds rates reported in northern China, establishing Jiangxi as a high-burden region for this difficult-to-treat species. Infections exhibited a powerful age-dependent trend, with the highest risk in individuals aged ≥ 65 years (aOR 12.922) and a significant female predominance (aOR 0.505 for males). MAV demonstrated a unique predilection for extrapulmonary sites. Temporal fluctuations in detection rates (peaking in 2021) suggest potential impacts from the COVID-19 pandemic. These findings underscore the critical need for integrating species-level molecular identification into routine diagnostics to prevent TB misclassification and ensure tailored therapy.

Abbreviations

CSF

Cerebrospinal fluid

M. tb

Mycobacterium tuberculosis

MAB

Mycobacterium abscessus

MAV

Mycobacterium avium

MCH

Mycobac-terium chelonae

MDR-TB

Multidrug-resistant tuberculosis

MFO

Mycobacterium fortuitum

MGI

Mycobacterium gilvum

MIN

Mycobacterium intracellulare

MKA

Mycobacterium kansasii

MMA

Mycobacterium marinum

NTM

Non-tuberculous mycobacteria

NTM-PD

Non-tuberculous mycobacteria pulmonary disease

PCR-REBA

PCR-based reverse blot hybridization assay

PTB

Pulmonary tuberculosis

SDS

Sodium Dodecyl Sulfate

SM

Streptomycin

SPSS

Statistical Package for Social Sciences

SR

Specimen reagent

SSC

Saline Sodium Citrate

TB

Tuberculosis

TMB

Tetramethylbenzidine dihydrochloride

Authors’ contributions

Conceptualization: Zhan Qiu Mao, Qi Long Zhang. Methodology: Zhan Qiu Mao. Formal Analysis: Zhan Qiu Mao, Huilie Zheng. Investigation: Zhan Qiu Mao, Hui Qiong Yang, Qian Zhong Liu, Yu Hong Xiong1, Zhen Qiong Liu. Resources: Zhan Qiu Mao. Data Curation: Zhan Qiu Mao. Writing – Original Draft: Zhan Qiu Mao. Visualization: Zhan Qiu Mao. Supervision: Qi Long Zhang. Validation: Zhan Qiu Mao. Project Administration: Zhan Qiu Mao. Funding Acquisition: Qi Long Zhang. All authors reviewed, edited, and approved the final manuscript.

Funding

This research was sponsored by Jiangxi Provincial Health Technology Project.

Data availability

The data sets generated and/or analyzed during the current study are available from the corresponding authors on reasonable request.

Declarations

Ethics approval and consent to participate

This study was performed in accordance with the Declaration of Helsinki and was approved by the Ethics Committee of Jiangxi Chest Hospital (Reference number: 202510588). The need for informed consent was waived by the Ethics Committee of Jiangxi Chest Hospital due to the retrospective nature of the study.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.