The research, led by Zuoren Zhou and colleagues at The Affiliated Changsha Central Hospital of the University of South China, set out to answer a question that had not been systematically investigated before: whether the volume of MTB sequence reads returned by targeted sequencing could reliably differentiate bacteriological-positive from bacteriological-negative pulmonary tuberculosis. While targeted next-generation sequencing, or tNGS, has already shown substantial value in diagnosing pulmonary tuberculosis, particularly in cases that other methods fail to detect, its ability to gauge infectiousness had remained an open question.

The team initially evaluated 482 patients with suspected pulmonary tuberculosis who were seen between January 2023 and May 2025. After applying exclusion criteria, 369 patients entered the final analysis. For each participant, the researchers compiled clinical data, laboratory parameters, and tNGS reports, creating a dataset rich enough to test whether sequencing read counts tracked with established markers of bacterial burden.

The technical logic behind tNGS is central to the study. Unlike metagenomic sequencing, which reads all genetic material in a sample indiscriminately, targeted sequencing uses primers designed to enrich specific pathogen genomes before sequencing. In respiratory specimens such as bronchoalveolar lavage fluid, this enrichment means that the number of MTB reads recovered should, in principle, reflect the quantity of tubercle bacilli present. The researchers hypothesized that patients whose sputum or cultures yield detectable acid-fast bacilli or growing colonies would carry a heavier bacterial load and therefore produce more sequence reads.

That hypothesis held up in the data. High tNGS MTB sequence reads were closely associated with enhanced C-reactive protein, low body mass index, weight loss, and positivity on acid-fast bacilli smear and rapid culture. Patients with positive rapid culture or acid-fast bacilli detection exhibited substantially higher read counts than their bacteriological-negative counterparts. Statistical modeling confirmed that tNGS MTB sequence reads were significantly and independently predictive of bacteriological-positive status, meaning the association persisted after accounting for other clinical variables.

To quantify diagnostic performance, the researchers deployed a battery of analytical tools. Receiver operating characteristic analysis, which plots sensitivity against specificity across all possible cutoffs, yielded an area under the curve of 0.825 for distinguishing bacteriological-positive from bacteriological-negative pulmonary tuberculosis. The optimal cutoff was 10.163, at which the read count achieved a sensitivity of 68.2 percent and a specificity of 85.7 percent. In practical terms, the test correctly identified roughly two-thirds of the highly infectious patients while misclassifying fewer than one in seven of the bacteriological-negative group as positive.

Beyond the ROC curve, the team used decision curve analysis and calibration curves to assess clinical utility. Decision curve analysis evaluates the net benefit of acting on a test result across a range of risk thresholds, and the curves confirmed excellent clinical utility for the sequencing read count. Calibration analysis, which checks whether predicted probabilities match observed frequencies, further supported the reliability of the metric. Concordance with conventional diagnostic tests was evaluated using Cohen’s kappa coefficient, a statistic that measures agreement beyond chance.

Perhaps the most striking finding was the pattern of agreement with existing assays. tNGS sequence reads showed the highest agreement with acid-fast bacilli and rapid culture-positive detection, with a kappa of 0.559, which the authors characterize as moderate agreement. Notably, the sequencing read count outperformed existing immunological assays—such as the purified protein derivative skin test and the T cell spot test for tuberculosis infection—in diagnostic performance. Those immunological tools detect the host’s immune response rather than the pathogen itself, so they cannot distinguish active bacterial replication from past exposure or latent infection.

The implications for infection control are significant. Bacteriological-positive patients are the primary drivers of tuberculosis transmission, and identifying them quickly allows hospitals and public health programs to prioritize isolation, contact tracing, and early treatment. A sequencing read count that correlates with culture positivity could give clinicians a rapid, quantitative signal of infectiousness at the time of diagnosis, supporting the clinical application of tNGS in tuberculosis infection control and management that the authors envision.

The study does carry the limitations inherent to its retrospective, single-center design, and the authors present the read count as a promising potential indicator rather than a validated replacement for microbiological confirmation. Even so, the combination of an area under the curve of 0.825, strong specificity, and confirmed decision-analytic utility positions tNGS MTB sequence reads as a candidate biomarker worth prospective validation. As targeted sequencing becomes faster and more affordable, the idea that a pathogen-enriched read count could double as a transmission-risk gauge may reshape how tuberculosis diagnostics are deployed in the clinics and laboratories where the battle against this ancient disease continues.

Subject of Research: Diagnostic performance of targeted next-generation sequencing Mycobacterium tuberculosis sequence reads in pulmonary tuberculosis

Article Title: Diagnostic performance of tNGS mycobacterium tuberculosis sequence reads in differentiating bacteriological-positive from bacteriological-negative pulmonary tuberculosis

Article References: Zhou, Z., Xia, Y., Ma, X., Kang, X., Li, X., Wang, Q., Zhu, J., & Liu, S. (2026). Diagnostic performance of tNGS mycobacterium tuberculosis sequence reads in differentiating bacteriological-positive from bacteriological-negative pulmonary tuberculosis. BMC Infectious Diseases. https://doi.org/10.1186/s12879-026-14649-w

Image Credits: AI Generated

DOI: 10.1186/s12879-026-14649-w

Keywords: tuberculosis, targeted next-generation sequencing, Mycobacterium tuberculosis, diagnostic accuracy, bacteriological status, ROC curve, biomarker, infection control, BMC Infectious Diseases, sequence reads, acid-fast bacilli, rapid culture

The research, published in Frontiers in Cellular and Infection Microbiology, was led by a team at Chifeng Municipal Hospital in Inner Mongolia. The investigators enrolled 941 patients with suspected lower respiratory tract infections who all underwent flexible bronchoscopy, a procedure in which sterile saline is instilled into the radiographically affected parts of the lung and then suctioned back out as bronchoalveolar lavage fluid, or BALF. This fluid carries microbes from deep within the airways, but it also carries an enormous load of human genetic material from leukocytes and airway epithelial cells, a background that has long plagued sequencing-based diagnostics by diluting sparse microbial signals.

Patients were divided into two non-randomized cohorts. One group of 479 patients received metagenomic next-generation sequencing, or mNGS, in which all DNA in the sample is fragmented, sequenced without bias, and then mapped computationally against a comprehensive microbial database after human sequences are filtered out. The other 462 patients received targeted next-generation sequencing, or tNGS, which uses multiplex PCR primers to selectively enrich more than 500 common respiratory pathogens, including bacteria, fungi, viruses, and atypical organisms, before sequencing. Crucially, the tNGS workflow captured both DNA and RNA, reverse-transcribing viral RNA into cDNA, whereas the mNGS assay in this study was DNA-only, a technical asymmetry that the authors acknowledge likely underestimated RNA viruses in the metagenomic cohort.

Measured against a composite final clinical diagnosis adjudicated by a multidisciplinary panel of senior pulmonologists and microbiologists, both platforms clearly outperformed conventional laboratory testing. Metagenomic sequencing achieved an overall sensitivity of 90.6 percent, while the targeted panel reached 73.4 percent. Specificity was low for both assays, at 21.4 percent for mNGS and 14.3 percent for tNGS, a familiar problem in respiratory specimens where commensal flora and airway colonizers blur the line between infection and mere microbial presence. Yet the positive predictive values were strikingly high, 97.4 percent and 96.5 percent respectively, meaning that when either platform called a pathogen positive, clinicians could trust that finding enough to act on it.

The most dramatic results concerned the pathogens that traditional diagnostics habitually miss. Targeted sequencing identified 54 cases of Mycobacterium tuberculosis, the bacterium responsible for tuberculosis, in a cohort where routine acid-fast bacilli smears and standard nucleic acid amplification tests had missed 42 of those positives, a conventional false-negative rate of 77.8 percent. Mycobacterial culture, the historical gold standard, can take weeks to yield a result, so the speed advantage alone is clinically significant. The same pattern emerged for Pneumocystis jirovecii, an opportunistic fungal pathogen that can cause life-threatening pneumonia in immunocompromised patients, where conventional silver staining produced false negatives in 80 percent of the cases evaluated while tNGS rapidly established the correct diagnosis.

Perhaps the most eye-opening finding was the sheer prevalence of polymicrobial infection. In the tNGS cohort, 93.5 percent of positive cases involved more than one pathogen, with single-pathogen infections accounting for only 6.5 percent. Cross-kingdom co-infections, mixing bacteria, viruses, and fungi simultaneously, made up 32.6 percent of positives. The most frequent pairing was Streptococcus pneumoniae with Human herpesvirus 7, seen in 30 patients, followed by bacterial double infections such as Klebsiella pneumoniae with Streptococcus pneumoniae in 25 cases. Combinations of opportunistic fungi with bacteria were also common, including Pneumocystis jirovecii alongside Pseudomonas aeruginosa or Klebsiella. Conventional tests, which typically hunt for a single pathogen or depend on highly specific culture conditions, are structurally ill-equipped to capture this complexity, and the study suggests the true etiological landscape of severe pneumonia is far more crowded than routine diagnostics imply.

Sequencing results also changed how patients were treated. In the mNGS cohort, where 461 of 479 patients had positive results, attending physicians modified initial empirical regimens in just over half of the cases, escalating therapy for 184 patients, or 39.9 percent, with broader agents such as carbapenems, glycopeptides, or targeted antifungals. In the tNGS group, 341 patients tested positive, and 77 of them, or 22.6 percent, required treatment escalation because their initial empirical antibiotics retrospectively proved inadequate against the pathogens identified. The clinical stakes of these adjustments are considerable, since severe pneumonia patients are usually started on broad-spectrum antibiotics empirically, and any unexpected, resistant, or fastidious organism hiding beneath that coverage can drive the illness into a fatal trajectory before culture results ever return.

Encouragingly, the patients whose therapy was escalated on the basis of sequencing did about as well as those who had received appropriate antibiotics from the start. Among the 77 tNGS-guided escalation patients, 66.2 percent showed clinical and radiological improvement, statistically indistinguishable from the 66.7 percent improvement rate in a comparison group of 249 patients whose initial empirical regimens were confirmed by the genomic data as adequate and therefore left unchanged, with a P value of 0.946. The authors interpret this as evidence that sequencing-guided escalation effectively rescued potentially failing empirical therapies, allowing patients whose initial treatment was wrong to catch up with those who happened to be treated correctly from the outset.

The study’s authors are careful to note that these outcome data come with important caveats. Because the design was retrospective, patients were not randomly assigned to the two platforms, and the diagnostic committee that set the reference standard had access to the sequencing results, raising the possibility of incorporation bias. Missing baseline variables, including formal severity scores such as APACHE II and SOFA, prevented robust multivariate regression, so the clinical improvements observed remain observational associations rather than proven causal effects of sequencing itself. Recovery from severe pneumonia depends on many factors beyond diagnosis, and the authors explicitly call for prospective, multicenter, paired-testing studies with long-term follow-up to isolate sequencing’s true impact on survival.

Practical considerations also temper enthusiasm for routine deployment. Metagenomic sequencing remains expensive, demands specialized bioinformatic infrastructure, and can take longer to return results than rapid point-of-care tests. Targeted panels reduce cost and, by acting as a molecular filter against human genomic background, appear to sharpen sensitivity for low-titer and fastidious organisms, but they can only see the roughly 500 pathogens they are designed to detect. Still, the Chifeng team’s conclusion is that both platforms offer substantial value, with tNGS standing out for elusive and low-abundance pathogens, and that sequencing-guided diagnostics are already steering antimicrobial decisions in ways associated with favorable clinical progress. As genomic testing costs continue to fall, the study offers a concrete glimpse of how precision diagnostics may reshape the management of severe respiratory infections, one lavage sample at a time.

Subject of Research: Comparison of metagenomic and targeted next-generation sequencing for diagnosing lower respiratory tract infections

Article Title: Comparative evaluation of metagenomic and targeted next-generation sequencing for pathogen detection in bronchoalveolar lavage fluid from patients with lower respiratory tract infections: a retrospective cohort study

Article References: Zhao, R., Na, H., Miao, W., Liu, L., Zhang, J., Miao, Y., Zhao, Y., & Li, X. (2026). Comparative evaluation of metagenomic and targeted next-generation sequencing for pathogen detection in bronchoalveolar lavage fluid from patients with lower respiratory tract infections: a retrospective cohort study. Frontiers in Cellular and Infection Microbiology, 16, Article 1877320. https://doi.org/10.3389/fcimb.2026.1877320

Image Credits: AI Generated

DOI: 10.3389/fcimb.2026.1877320

Keywords: lower respiratory tract infections, metagenomic next-generation sequencing, targeted next-generation sequencing, bronchoalveolar lavage fluid, antimicrobial stewardship, Mycobacterium tuberculosis, Pneumocystis jirovecii, polymicrobial infection, diagnostic sensitivity, precision medicine, clinical microbiology, pneumonia

The two sequencing approaches represent different philosophies for reading genetic material from a patient sample. Targeted next-generation sequencing, often abbreviated tNGS, uses panels of primers or probes to enrich and amplify DNA from a predefined list of pathogens, which concentrates sequencing capacity on organisms that clinicians already suspect. Metagenomic next-generation sequencing, or mNGS, takes the opposite approach: it sequences all nucleic acid in a sample without any preselection, allowing the laboratory to detect virtually any microbe present, including unexpected or fastidious organisms that no one thought to test for. That breadth comes at a cost, both financially and computationally, because vast amounts of background human and environmental DNA must be filtered out before a pathogen signal emerges. The question facing hospitals is whether mNGS’s unbounded scope translates into measurably better care for patients with suspected pulmonary tuberculosis.

To answer that question fairly, the researchers confronted a familiar obstacle in observational medicine: patients are not assigned to tests at random. In routine practice, physicians choose mNGS or tNGS based on how sick a patient appears, what previous tests have shown, and what the patient can afford, which means simple comparisons between the two groups can be badly skewed. The team therefore turned to propensity score matching, a statistical technique that pairs patients from each group who share similar baseline characteristics, effectively simulating the balance of a randomized trial. After this matching procedure, the analysis rested on 403 patients with confirmed pulmonary infections, of whom 304 had undergone tNGS and 99 had received mNGS.

The headline diagnostic finding was one of statistical equivalence. In the matched cohorts, the final rate of tuberculosis diagnosis was 17.4 percent in the tNGS group versus 23.2 percent in the mNGS group, a difference that did not reach statistical significance, with a p value of 0.257. Similarly, the proportion of samples in which the Mycobacterium tuberculosis complex was directly detected by sequencing was 20.4 percent for tNGS and 28.3 percent for mNGS, again without a significant difference at p equals 0.134. When the researchers plotted receiver operating characteristic curves to summarize overall diagnostic accuracy, the area under the curve came to 0.936 for tNGS, with a 95 percent confidence interval of 0.898 to 0.975, and 0.967 for mNGS, with a confidence interval of 0.939 to 0.995. The comparison between these two areas yielded a p value of 1.000, about as close to a tie as statistics allows.

Beneath that tie, however, lay one of the study’s most striking results. Within the matched mNGS cohort of 99 patients, metagenomic sequencing achieved 100 percent sensitivity and a 100 percent negative predictive value for tuberculosis, meaning that in this dataset a negative mNGS result reliably ruled the disease out. That figure deserves careful interpretation: in the larger unmatched full cohort of 104 patients who received mNGS, sensitivity slipped to 95.8 percent and the negative predictive value to 98.7 percent, a reminder that perfect performance in a small matched subset can be fragile. Even so, the authors argue that such a high negative predictive value, if confirmed in larger studies, could make mNGS a powerful tool for excluding tuberculosis in diagnostically challenging cases, where every additional day of uncertainty carries clinical and emotional weight.

The sequencing tests were also benchmarked against the established tuberculosis diagnostic arsenal. In subset-specific area-under-the-curve analyses performed after propensity score matching, sequencing targeting the Mycobacterium tuberculosis complex, referred to as MTBC-NGS, outperformed the interferon-gamma release assay, the tuberculosis DNA test, and acid-fast staining, three workhorses of mycobacterial diagnosis that respectively measure immune response, detect bacterial DNA by conventional amplification, and visualize acid-fast bacilli under the microscope. Notably, MTBC-NGS also showed an advantage over the Xpert MTB/RIF assay, the World Health Organization-endorsed rapid molecular test that has transformed tuberculosis detection worldwide, although that advantage was smaller and only became statistically significant after the researchers applied a Bonferroni correction to account for multiple comparisons. The pattern suggests that while newer sequencing platforms do not render existing tools obsolete, they can extract additional diagnostic signal in the right clinical subsets.

Diagnostic performance, however, is only half the story, because healthcare systems must also weigh what each test costs and how it shapes the patient’s journey through the hospital. Here the study delivered a clear verdict: the mNGS group incurred substantially higher healthcare costs than the tNGS group. Metagenomic sequencing’s untargeted design requires deeper sequencing, more intensive bioinformatics, and greater laboratory infrastructure, expenses that are inevitably passed on to patients and payers. Targeted sequencing, by focusing resources on a curated panel of pathogens, achieves comparable diagnostic accuracy for tuberculosis at a lower price point, a distinction that matters enormously in the high-burden settings where tuberculosis testing decisions are made most often.

One widely held assumption did not survive the study’s statistical scrutiny. Earlier comparisons had suggested that patients who received mNGS experienced longer hospital stays, an observation that seemed intuitive given the turnaround time and complexity of untargeted sequencing. But when the researchers adjusted their analysis for the calendar period in which patients were tested, that difference in length of stay lost its statistical significance. The authors conclude that the apparent prolongation of hospitalization may have been attributable in part to temporal changes in clinical practice over the course of the study rather than to the test modality itself. It is a subtle but important methodological lesson: in fast-evolving fields like clinical genomics, when a test was ordered can matter as much as which test was ordered.

The study, led by Xinle Liang and colleagues in the Department of Respiratory and Critical Care Medicine at Yan’an University Affiliated Hospital, was approved by the hospital’s ethics committee and conducted in accordance with the Declaration of Helsinki. The team acknowledged the Xi’an Regional Medical Laboratory Center, which provided both tNGS and mNGS testing services, and the hospital’s clinical laboratory for supporting the work. As a retrospective, single-center analysis, the investigation carries inherent limitations that the authors themselves flag, most notably the modest size of the mNGS group even after matching, and the possibility that unmeasured differences between patients influenced both test selection and outcomes. The 100 percent sensitivity and negative predictive value observed in the matched mNGS cohort, in particular, is explicitly presented as a finding that requires validation in larger studies before it can guide practice.

For clinicians wrestling with suspected pulmonary tuberculosis, the practical message is one of complementarity rather than replacement. Metagenomic sequencing offers unmatched breadth and, in this cohort, an exceptional ability to rule tuberculosis out when results are negative, making it attractive for critically ill or diagnostically perplexing patients in whom the causative pathogen could be almost anything. Targeted sequencing delivers essentially equivalent accuracy for tuberculosis at lower cost, positioning it as the rational first-line genomic option when the clinical question is narrower. As sequencing costs continue to fall and bioinformatics pipelines mature, studies like this one, grounded in real-world propensity-matched cohorts rather than idealized trial conditions, will be essential for deciding which patients truly benefit from the most expensive diagnostic technology and which can be served just as well by its leaner cousin.

Subject of Research: Comparative diagnostic performance of targeted and metagenomic next-generation sequencing for pulmonary tuberculosis

Article Title: Clinical value of targeted next-generation sequencing and metagenomic next-generation sequencing in the diagnosis of pulmonary tuberculosis: a real-world propensity score matching study

Article References: Liang, X., Sun, Y., Sun, J., Zhao, J., He, F., & Bai, Z. (2026). Clinical value of targeted next-generation sequencing and metagenomic next-generation sequencing in the diagnosis of pulmonary tuberculosis: a real-world propensity score matching study. BMC Infectious Diseases. https://doi.org/10.1186/s12879-026-14537-3

Image Credits: AI Generated

DOI: 10.1186/s12879-026-14537-3

Keywords: pulmonary tuberculosis, targeted next-generation sequencing, metagenomic next-generation sequencing, propensity score matching, Mycobacterium tuberculosis complex, Xpert MTB/RIF, diagnostic accuracy, negative predictive value, healthcare costs, BMC Infectious Diseases, molecular diagnostics, retrospective study

The core challenge the researchers set out to solve is a familiar one to anyone working with trace biological evidence: DNA at crime scenes, in processed foods, or in seized wildlife products is rarely pristine. Heat, chemicals, time, and environmental exposure all shred the long DNA molecules that standard analytical methods depend on. Traditional DNA barcoding, which relies on amplifying a single gene region of several hundred base pairs, often fails outright when the template DNA is broken into pieces shorter than the target. The new assay sidesteps this limitation by targeting four mitochondrial genes simultaneously: cytochrome b (Cytb), cytochrome c oxidase subunit I (COI), 16S ribosomal RNA, and 12S ribosomal RNA. Because each of these markers can be amplified as short fragments, the probability that at least one usable stretch of DNA survives in a degraded sample rises dramatically.

Mitochondrial DNA is the molecule of choice for species identification for good reason. Each cell contains hundreds to thousands of mitochondrial copies compared with just two copies of any nuclear gene, which means mitochondrial targets are far more likely to yield amplifiable material from tiny or damaged samples. Moreover, the mitochondrial genome accumulates mutations at a rate that allows closely related species to be distinguished while remaining conserved enough that universal primers can bind across a wide range of vertebrate groups. By combining four independent markers in a single multiplex reaction, the new system builds redundancy into the analysis: if one marker fails to amplify or gives an ambiguous result, the other three can still deliver a species call.

The technical architecture of the assay follows the logic of targeted amplicon sequencing. Rather than sequencing entire mitochondrial genomes, which would be wasteful and impractical for degraded templates, the system uses carefully designed primer pairs to amplify short, informative regions of the four marker genes. These amplicons are then indexed with sample-specific barcodes, pooled, and sequenced in parallel on a next-generation sequencing platform. The resulting reads are processed through a bioinformatic pipeline that filters out sequencing errors and chimeric artifacts, clusters the sequences, and matches them against reference databases. This multiplex design means dozens of samples can be analyzed simultaneously, dramatically reducing both cost and turnaround time compared with running each marker separately.

What distinguishes this study from many previous metabarcoding efforts is the systematic forensic validation that accompanied the development. Following the recommendations of the International Society for Forensic Genetics (ISFG) for non-human DNA analysis, the team subjected the assay to a battery of performance tests covering the scenarios that matter most in real casework. Sensitivity testing revealed that just 10 picograms of genomic DNA from a single species—roughly the amount of DNA in a fraction of a single cell—was sufficient to detect at least one of the four markers for all species tested. When the input was raised to 100 picograms, reliable species identification was achieved using all four markers simultaneously. These thresholds place the assay firmly in the range needed for trace evidence analysis, where investigators often work with material scraped from a single bone fragment or a smudge on a knife blade.

Mixture analysis, a critical capability for food fraud detection and wildlife trafficking cases where products may contain multiple species, produced equally impressive results. In an equimolar mixture containing ten different species with a total DNA input of just one nanogram, the assay correctly identified all ten contributors. More striking still, the system detected minor components in binary mixtures down to a 99:1 ratio, meaning a species making up only one percent of the DNA in a sample could still be flagged. This level of sensitivity for minority contributors is exactly what is needed to catch adulteration, where expensive meat or seafood is diluted with cheaper substitutes at low percentages precisely to evade detection.

The degradation studies may be the most consequential for practical applications. The researchers deliberately fragmented DNA in experimental samples and then challenged the assay with the damaged templates, alongside DNA extracted from highly processed food matrices such as cooked and commercially prepared meat products. In both scenarios, the four-marker system recovered enough sequence information to make species assignments, demonstrating that the short amplicon strategy performs as intended under the harshest conditions forensic analysts are likely to encounter. Processed foods represent one of the most common contexts for species fraud, and the ability to identify constituents in cooked, canned, or otherwise transformed products closes a significant gap in food authentication testing.

Validation extended beyond the laboratory to genuine casework samples, where the tNGS-based multiplex assay demonstrated broad-spectrum vertebrate identification across real-world evidence. The authors report that these case studies confirmed the practical value of the system for three major application areas: curbing wildlife trafficking, mitigating food fraud, and facilitating biodiversity monitoring. In wildlife trafficking investigations, the ability to identify species from seized products—whether carved ivory, dried meat, traditional medicine ingredients, or leather goods—provides prosecutors with the species-level evidence needed to establish that a crime against protected fauna occurred. For food regulators, the assay offers a screening tool capable of auditing supply chains for substitution and mislabeling. For ecologists, the same chemistry can be applied to environmental DNA samples to survey vertebrate diversity in a given habitat without needing to observe or capture animals directly.

The development team, which included collaborators from the Guangzhou Public Security Bureau, the Nanchang Police Dog Base of the Ministry of Public Security, Jinan University, and the Anti-Drug Technology Center of Guangdong Province, emphasized adherence to ethical research standards throughout the study. Animal specimens were provided by the Guangzhou Zoo and the Guangzhou Wildlife Research Center with approval from the Animal Ethics Committee of those institutions. The work was funded in part by the National Natural Science Foundation of China and the Jiangxi Provincial Key Research and Development Program, reflecting the strategic priority that Chinese research agencies have placed on forensic multi-omics and wildlife protection technology.

Looking ahead, the convergence of targeted sequencing, multiplex mitochondrial barcoding, and rigorous forensic validation points toward a future where species identification becomes as routine and standardized as human DNA profiling is today. The reference sequences used in the assay are publicly accessible through the National Center for Biotechnology Information database, and the authors have made raw data available with the publication, supporting transparency and reproducibility. As sequencing costs continue to fall and reference databases expand, systems like this one could be deployed in customs laboratories, food inspection agencies, and conservation field stations worldwide. For investigators racing to document the scale of illegal wildlife trade—a market estimated to be worth billions of dollars annually—and for consumers who deserve to know what is actually in their food, a tool that can name a species from a fragment of damaged DNA may prove to be one of the most consequential forensic innovations of the decade.

Subject of Research: A mitochondrial DNA metabarcoding system based on targeted next-generation sequencing for forensic identification of vertebrate species in degraded and mixed DNA samples

Article Title: A mitochondrial DNA metabarcoding system based on tNGS enables multiplex identification of vertebrate species in samples containing degraded and mixed DNA

Article References: Liu, X., Su, C., Wei, R., Chen, X., Le, J., Xiao, G., Chang, J., Liang, S., Wu, X., Liu, C., Liu, H., Du, W., Liu, C., & Chen, L. (2026). A mitochondrial DNA metabarcoding system based on tNGS enables multiplex identification of vertebrate species in samples containing degraded and mixed DNA. International Journal of Legal Medicine. https://doi.org/10.1007/s00414-026-04024-4

Image Credits: AI Generated

DOI: 10.1007/s00414-026-04024-4

Keywords: DNA metabarcoding, targeted next-generation sequencing, mitochondrial DNA, forensic science, wildlife trafficking, food fraud, species identification, degraded DNA, cytochrome b, COI, biodiversity monitoring, vertebrate species

The assay under scrutiny is Deeplex Myc-TB, a targeted next-generation sequencing test developed to detect mutations in the tuberculosis genome that are associated with resistance to a broad range of first- and second-line anti-TB drugs. Unlike conventional rapid molecular tests, which typically interrogate only a handful of genetic regions, targeted sequencing approaches can survey dozens of genes and intergenic regions in a single run. This breadth matters enormously in clinical practice, because treatment decisions for multidrug-resistant and extensively drug-resistant tuberculosis depend on knowing, quickly and reliably, which drugs are likely to fail and which are likely to work.

To evaluate the assay, the researchers turned to an unusual but powerful resource: isolates distributed through the World Health Organization global Tuberculosis Drug-Susceptibility Testing Proficiency Testing Program, organized and administered by the TB Supranational Reference Laboratory in Antwerp, Belgium. A total of 41 isolates were included in the study. These samples are particularly valuable for verification work because they have been exhaustively characterized by reference laboratories using multiple independent methods. In this study, phenotypic drug susceptibility testing performed on Löwenstein-Jensen medium and in mycobacteria growth indicator tube culture, together with whole-genome sequencing, served as the reference standards against which the Deeplex assay was judged.

The analytical workflow was straightforward in concept. Remnant DNA extracted from the proficiency testing isolates was subjected to targeted next-generation sequencing using the Deeplex Myc-TB assay. The resulting sequence data were interpreted using the manufacturer’s Deeplex web application, and, in parallel, with TBProfiler, an open-source tool for predicting drug resistance from mycobacterial sequence data, applying a composite interpretation rule. Concordance, sensitivity, and specificity were then calculated for each drug class, providing a detailed picture of where the assay excels and where it falls short.

The headline result is striking: the Deeplex Myc-TB assay achieved 100 percent specificity across all drug targets examined. In diagnostic terms, this means that whenever the assay reported a resistance mutation, the isolate genuinely carried a mutation associated with resistance. False positives, which can lead clinicians to withhold effective drugs unnecessarily, were entirely absent from the dataset. For several drugs, the assay’s sensitivity was equally impressive. It correctly identified resistance in every tested isolate for rifampicin, detecting 17 of 17 resistant strains; for pyrazinamide, 7 of 7; for fluoroquinolones, 13 of 13; and for linezolid, 6 of 6. For isoniazid, sensitivity was 94.1 percent, with 16 of 17 resistant isolates correctly flagged.

The single isoniazid miss is instructive rather than alarming. The one false-susceptible result traced back to a specific insertion mutation in the katG gene, designated katG c.45_46insA, which fell outside the region targeted by the assay. This illustrates a fundamental property of targeted sequencing: its performance is bounded by the mutations it is designed to detect. When a resistance-conferring variant lies outside the panel’s target regions, even a technically flawless assay will report susceptibility. The finding underscores why laboratories adopting such assays must understand the local epidemiology of resistance mutations in the strains they encounter.

Performance was more mixed for the newer and repurposed drugs that have become central to modern regimens for drug-resistant tuberculosis. For clofazimine, the assay detected resistance in 4 of 5 phenotypically resistant isolates, a sensitivity of 80 percent. For bedaquiline, sensitivity dropped to 44.4 percent, with only 4 of 9 resistant strains correctly identified. In five cases, isolates that were resistant by phenotypic testing carried no resistance variants detected by the assay. The authors traced much of this gap to the biology of resistance to these drugs. Mutations in the mmpR5 gene, also known as Rv0678, a major regulator of efflux pump expression, were largely detected by the assay, but resistance mediated through the atpE gene was not identified, because that gene is not adequately covered by the assay’s target panel.

Overall concordance between the Deeplex assay and the reference standards ranged from 87.5 percent for bedaquiline to a perfect 100 percent for rifampicin, pyrazinamide, fluoroquinolones, and linezolid. Notably, the assay consistently detected several recurrent mutations associated with resistance to the different drugs, reinforcing the idea that for the common, well-established resistance mechanisms, targeted sequencing performs at or near the level of whole-genome sequencing while being faster and cheaper to deploy in routine laboratory settings. For a disease where every week of delayed or inappropriate treatment increases the risk of transmission, disease progression, and death, that speed advantage carries real clinical weight.

The implications of this verification study extend well beyond one laboratory in Uganda. Proficiency testing panels offer a rare opportunity to benchmark a diagnostic assay against isolates whose resistance profiles are known with high confidence, free from the uncertainties that complicate evaluations using routine clinical samples. By demonstrating near-perfect specificity and strong sensitivity for the cornerstone drugs of tuberculosis therapy, the study provides laboratories considering adoption of targeted next-generation sequencing with concrete, independently grounded performance data. At the same time, the documented gaps for bedaquiline and clofazimine serve as a caution against treating any single assay as a complete solution. The authors emphasize that understanding local resistance mutation patterns is essential when implementing sequencing-based resistance detection, because an assay that misses the mutations circulating in a given region will systematically underreport resistance there.

The broader context makes these findings timely. Drug-resistant tuberculosis kills thousands of people each year, and the introduction of bedaquiline, linezolid, and other newer agents has transformed outcomes for patients with resistant disease, but only when those drugs are deployed appropriately. Molecular diagnostics that can rapidly and accurately profile resistance across the full range of current and repurposed drugs are a critical link in that chain. This study shows that targeted sequencing platforms have matured to the point where they can match reference standards for the most important drugs, while also mapping precisely where the remaining blind spots lie. For laboratory directors, national tuberculosis programs, and diagnostic developers alike, the message is twofold: the technology is ready for prime time in the core of TB drug resistance testing, but careful attention to target coverage, and to the mutation landscape of the populations being served, remains indispensable.

Subject of Research: Analytical performance verification of a targeted next-generation sequencing assay for detecting drug-resistant Mycobacterium tuberculosis

Article Title: Analytical performance verification of the Deeplex Myc-TB assay using well-characterized Mycobacterium tuberculosis proficiency testing isolates

Article References: Kabahita, J. M., Lunkuse, J. M., Batte, D. N., Nakato, H. S., Namutebi, J., Kabugo, J., Adam, I., Kanyerezi, S., Makoha, C., Nsubuga, M. L., Oundo, H. R., Wenka, G. T., Sseruyange, J., Murungi, M., Kasule, G. W., Lutaaya, P., Kyokushaba, J., Byabajungu, H., Ademun, P., … Joloba, M. L. (2026). Analytical performance verification of the Deeplex Myc-TB assay using well-characterized Mycobacterium tuberculosis proficiency testing isolates. BMC Genomics. https://doi.org/10.1186/s12864-026-13336-z

Image Credits: AI Generated

DOI: 10.1186/s12864-026-13336-z

Keywords: tuberculosis, drug resistance, Deeplex Myc-TB, targeted next-generation sequencing, whole-genome sequencing, diagnostics, bedaquiline, clofazimine, isoniazid, rifampicin, proficiency testing, Uganda