The research team, led by Guangqi Li and colleagues at the General Hospital of Ningxia Medical University, conducted a three-part investigation. First, they performed a one-year retrospective epidemiological analysis of 16,970 blood culture specimens processed between January and December 2024. Second, they assembled a retrospective clinical cohort of 295 patients with culture-confirmed BSI, extending the study period from January 2022 to December 2024 to capture enough polymicrobial cases, which are relatively rare. Third, they carried out a prospective molecular comparison in 20 patients with suspected BSI, running three detection methods in parallel: conventional blood culture, 16S rDNA PCR library construction, and direct 16S rDNA amplicon high-throughput sequencing.

The epidemiological survey revealed that 1,321 of the 16,970 blood culture specimens—7.8 percent—were positive for microbial growth. The overwhelming majority, 96.6 percent, were classified as monomicrobial infections, while polymicrobial BSIs accounted for just 3.4 percent. Escherichia coli emerged as the most frequently identified pathogen, followed by coagulase-negative staphylococci and Brucella species. The prominence of Brucella is notable: the Ningxia Hui Autonomous Region, where the study was conducted, is an area where human brucellosis remains a significant public health concern linked to extensive livestock farming and pastoral communities, with Brucella melitensis the predominant circulating species. The authors caution that this regional epidemiological background shapes the pathogen spectrum and may not generalize to other healthcare settings.

To understand what distinguishes polymicrobial infections clinically, the researchers compared inflammatory markers between the monomicrobial and polymicrobial groups in the 295-patient cohort. The differences were striking. Polymicrobial BSI was associated with significantly higher white blood cell (WBC) counts, neutrophil percentage, absolute neutrophil count, neutrophil-to-lymphocyte ratio, neutrophil-to-platelet ratio, systemic immune-inflammation index, systemic inflammatory response index, and procalcitonin (PCT) levels—all with P values below 0.05. Median WBC counts reached 15.18 × 10⁹/L in the polymicrobial group versus 10.13 × 10⁹/L in the monomicrobial group, while median PCT levels were 14.00 ng/mL compared with 1.40 ng/mL. Moreover, within polymicrobial infections, those involving mixed Gram types—both Gram-positive and Gram-negative organisms—showed even higher inflammatory burdens than single Gram-type infections, with median PCT soaring to 31.00 ng/mL in mixed cases.

Multivariable logistic regression confirmed that WBC count and PCT were independent predictors of polymicrobial BSI. Elevated WBC carried an odds ratio of 1.723 (95 percent confidence interval 1.472–2.017, P < 0.001), while PCT carried an odds ratio of 1.028 (95 percent confidence interval 1.003–1.054, P = 0.031). For mixed Gram-type infections specifically, WBC (OR = 1.486) and PCT (OR = 1.042) were again independently associated. Receiver operating characteristic (ROC) analysis quantified the discriminatory power of these markers. WBC alone achieved an area under the curve (AUC) of 0.890, with 77.1 percent sensitivity and 90.0 percent specificity at a cutoff of 12.54 × 10⁹/L. PCT alone achieved an AUC of 0.910, with 88.0 percent sensitivity and 80.0 percent specificity at 3.20 ng/mL. Combining the two markers improved performance further, yielding an AUC of 0.927 with balanced sensitivity of 84.0 percent and specificity of 91.8 percent. For identifying mixed Gram-type infections, the combined markers performed even better, reaching an AUC of 0.950 with 94.3 percent sensitivity and 89.8 percent specificity.

These biomarker findings carry practical significance. Because polymicrobial BSIs are associated with higher mortality, increased treatment failure, and greater clinical complexity than monomicrobial infections, identifying patients at elevated risk early in their clinical course could guide decisions about escalating empiric antimicrobial coverage and pursuing additional molecular testing. The authors suggest that when WBC and PCT monitoring suggests a possible polymicrobial infection, 16S rDNA molecular diagnosis can be deployed as a supplementary method to achieve more rapid identification of the full pathogen spectrum.

The molecular comparison cohort of 20 patients provided the study’s most technically revealing results. For the clone-based workflow, cell-free DNA (cfDNA) extracted from plasma was subjected to broad-range PCR amplification of bacterial 16S rDNA using universal primers 16F and 1492R, producing amplicons of approximately 1,500 base pairs—consistent with the near-full-length 16S rRNA gene. The purified amplicons were ligated into T5 cloning vectors and transformed into Escherichia coli DH5α competent cells. Positive clones were screened by colony PCR with M13 primers and then subjected to amplified ribosomal DNA restriction analysis (ARDRA) using the restriction enzymes HhaI and RsaI. Clones displaying identical restriction fragment patterns were clustered into operational taxonomic units (OTUs), and representative clones from each OTU were sequenced by Sanger sequencing, with taxonomic classification determined by BLAST alignment against the NCBI GenBank database. This cloning step physically separates individual rDNA sequences before sequencing, which is the method’s defining feature.

The three methods produced distinctly different detection profiles. Blood culture detected 0 to 1 microbial taxon per patient, identifying one pathogen in 17 patients and returning negative results in 3 patients. The clone-based 16S rDNA PCR library method detected a broader spectrum, identifying 0 to 5 taxa per patient, and uncovered 16 bacterial species overall—including Escherichia coli, Klebsiella pneumoniae, and Chryseobacterium chrysogenum as the most frequently detected taxa—compared with only 10 species detected by culture. Direct 16S rDNA amplicon high-throughput sequencing showed the broadest detection range of all, with more than five taxa detected in 9 of the 20 patients. At the genus level, the most abundant taxa in the sequencing data included Escherichia (23.3 percent), Streptococcus (18.6 percent), and Staphylococcus (14.0 percent). Mixed bacterial signals—defined as detection of two bacterial species in a single sample by the 16S method—were observed in all 20 samples analyzed by the library approach.

When blood culture was used as the reference standard, the clone-based method demonstrated an overall percent agreement of 80.0 percent with a sensitivity of 88.2 percent, whereas high-throughput sequencing showed a concordance rate of 70.0 percent and a sensitivity of 82.4 percent. Concordance analysis between blood culture and the library method classified results as completely consistent in 6 cases (30 percent), partially consistent in 10 cases (50 percent), and inconsistent in 4 cases (20 percent). The researchers interpret the higher agreement of the clone-based approach cautiously, noting that it may partly reflect the narrower taxonomic yield compared with high-throughput sequencing. However, because the library method detected more taxa than culture, its higher concordance cannot be explained simply by an inability to detect additional organisms. Instead, the cloning step appears to provide an additional layer of signal separation, reducing redundant sequencing signals from highly abundant organisms and allowing individual sequence reads to be traced back to representative clones—physical material that is retained for downstream confirmatory testing, an advantage high-throughput sequencing lacks.

The study’s authors position the 16S rDNA PCR library approach not as a replacement for modern next-generation sequencing platforms but as a practical, comparatively lower-cost adjunctive strategy for settings where broad molecular detection is needed but standardized NGS interpretation remains challenging. High-throughput sequencing, despite its superior depth, suffers from the absence of clinically validated diagnostic thresholds, making it difficult to distinguish true pathogens from commensal microbiota, environmental contaminants, and low-abundance background signals. A multilaboratory assessment involving 90 metagenomic NGS laboratories previously documented substantial interlaboratory variability in microbial identification, particularly for low-abundance organisms. The study also illustrates the library method’s real-world value through case examples: in an immunocompromised patient with lung adenocarcinoma whose blood cultures were negative, the 16S library successfully detected Streptococcus constellatus, cross-validated by a parallel wound secretion culture; in a case of hollow viscus perforation where empirical antibiotics rendered routine cultures sterile, the library identified Klebsiella pneumoniae and Escherichia coli, matching the anatomical source of gastrointestinal leakage and validating the clinician’s escalated antibiotic strategy.

Limitations remain. The single-center design and modest sample size constrain generalizability, the exclusion of viral and fungal co-infections leaves the true polymicrobial burden incompletely assessed, and the 30-to-36-hour turnaround time for library construction—although optimized with automated instruments and simultaneous multi-sample processing—remains impractical for acute clinical decisions. Universal primers also introduce amplification bias against highly divergent 16S sequences such as Mycoplasma, and fungal pathogens, which are critical in polymicrobial BSI among neutropenic patients, are not captured by the current bacterial workflow. Cost is another barrier, with per-sample molecular testing expenses often an order of magnitude higher than traditional culture. Nevertheless, the study demonstrates that WBC and PCT can serve as accessible biomarkers to triage patients for molecular testing, and that the cloning-based 16S rDNA PCR library offers a balanced middle ground—broader than culture, more focused than direct amplicon sequencing, and traceable at the sequence level—for unraveling the microbial complexity of polymicrobial bloodstream infections.

Subject of Research: Molecular detection of polymicrobial bloodstream infections using 16S rDNA PCR library amplicons compared with blood culture and high-throughput sequencing

Article Title: Enhanced detection of polymicrobial bloodstream infections with 16S rDNA PCR library amplicons and clinical relevance

Article References: Li, G., Wu, G., Yin, H., McGraw, K. A., Hou, J., & Zhao, Z. (2026). Enhanced detection of polymicrobial bloodstream infections with 16S rDNA PCR library amplicons and clinical relevance. Frontiers in Microbiology, 17, Article 1916658. https://doi.org/10.3389/fmicb.2026.1916658

Image Credits: AI Generated

DOI: 10.3389/fmicb.2026.1916658

Keywords: bloodstream infection, polymicrobial infection, 16S rDNA, PCR library, blood culture, procalcitonin, white blood cell count, high-throughput sequencing, sepsis, molecular diagnostics, Brucella, cell-free DNA