Now, a team of researchers led by Yunchao Zhou, Yiwei Liu, Bin Cong, Jianhua Chen, and Jianqiang Deng has published an experimental study in the journal iScience demonstrating that a combination of multiplex polymerase chain reaction (PCR) and high-resolution melting (HRM) analysis can rapidly and accurately identify both single and mixed diatom species. The work, which screened 83 primer pairs and validated 15 for diatom detection, offers a compelling alternative to both traditional microscopy and expensive high-throughput sequencing, particularly for laboratories that lack access to costly sequencing infrastructure.

The study focused on eight species of pure marine diatoms: Navicula sp., Odontella sp., Nitzschia sp., Chaetoceros sp., Ditylum sp., Skeletonema sp., Cylindrotheca sp., and Asterionellopsis sp. Scanning electron microscopy confirmed that all eight cultured strains exhibited morphological characteristics consistent with their purchased taxa, ensuring that the molecular results could be confidently attributed to the correct organisms. The researchers then extracted DNA from each species and set about designing and screening primers targeting a range of genetic markers, including the 18S and 28S ribosomal RNA genes, the chloroplast genes rbcL and PsaA, and the universal plastid amplicon UPA.

Through repeated experiments, the team identified 15 primer pairs capable of diatom detection—eight drawn from the published literature and seven designed in-house. When each primer pair was used to amplify DNA from a single diatom species followed by HRM analysis, the results were striking. Each amplification product formed a distinct characteristic peak in the derivative melting curve, with the horizontal coordinate of the highest point corresponding to the melting temperature. Different species yielded peaks of varying shapes at distinct positions, enabling identification based on these features alone. Nine primers—UPA99, 18S-V7, PsaA-2, rbcL197, DiatrbcL708, Primer1, ND, 28S-191C, and 18S-333N—could specifically amplify all eight species, each producing eight distinct melting curves. Others were more selective: 18S-356H and 18S-341J amplified seven species, rbcL-256Z amplified four, 18S-196O and rbcL-N amplified only two, and DNGT amplified only Skeletonema sp. No detection peaks were observed in any negative control group, underscoring the specificity of the approach.

However, the real challenge lay in mixed samples. In natural water environments, diatoms almost never appear as pure cultures; they exist as complex communities of many species. When the researchers used a single primer pair to amplify pairwise mixtures of diatoms, they observed a troubling phenomenon: mutual inhibition during amplification or fusion of characteristic peaks among species with similar melting temperatures. For example, when Navicula sp. was mixed with six other species using the DiatrbcL708 primer, only the characteristic peaks of the other diatoms appeared, without forming double peaks with Navicula sp. Asterionellopsis sp. proved particularly susceptible to suppression in mixed systems, its signal vanishing entirely when combined with most other species. When the researchers attempted to amplify a mixture of all eight species with a single primer, the resulting curves formed only double peaks that could not be attributed to any specific pair of species, demonstrating that single-primer HRM analysis lacks the discriminatory power needed for complex mixed samples.

The solution emerged from combining multiple primer pairs within a single reaction tube. The researchers first demonstrated that a mixture of two primers with similar annealing temperatures—28S-191C and PsaA-2—could form characteristic double peaks when amplifying a single diatom, with each peak corresponding to the signal produced by the respective primer alone. No amplification inhibition or peak fusion occurred, confirming that multiple primers can coexist in one reaction without interfering with each other. Building on this principle, the team then combined the primers 18S-196O, rbcL-N, and DNGT into a multiplex PCR-HRM system. This three-primer combination successfully distinguished four diatom species—Odontella sp., Navicula sp., Cylindrotheca sp., and Skeletonema sp.—in mixed samples. Remarkably, the melting curves produced by the mixed samples of four species and the mixed samples of all eight species were almost identical in shape and position, indicating that the system could simultaneously demonstrate the presence of these four species within a complex mixture.

The success of the multiplex PCR-HRM approach hinges on careful primer design. The annealing temperatures of primers must not differ by more than 4°C, or they cannot react efficiently in the same PCR system. At the same time, the melting temperatures of the amplified products must not be too close, or fusion peaks will form and species cannot be distinguished. The researchers noted that when the length of an amplified product exceeds 400 base pairs, the sensitivity and specificity of HRM analysis decline slightly. The most common problem encountered during the experiments was complementarity between primers, which produced excessive primer dimers. Fortunately, during HRM analysis, the presence of primer dimers can be observed directly in the melting curves, eliminating the need for agarose gel electrophoresis. Other factors influencing the system include the ratio of primers, the concentration of deoxynucleotide triphosphates (dNTPs), and the concentration of magnesium ions. Excessively high primer concentrations lead to competition among primers for PCR materials, causing amplification imbalance. Insufficient dNTP concentrations reduce the yield of amplification products, while inadequate magnesium ion concentrations impair polymerase activity, reducing amplification efficiency. Conversely, excessively high magnesium ion concentrations increase nonspecific amplification.

When the researchers performed HRM analysis on the eight diatom species using a single primer, they found that the melting temperatures of amplification products from different species were sometimes identical or differed by less than 0.1°C. For instance, the melting temperature of both Chaetoceros sp. and Cylindrotheca sp. amplified by the UPA99 primer was 79.28°C. This could be due to the similarity of the amplified sequences or to fluctuations in temperature differences between wells on the real-time PCR instrument. The researchers addressed this ambiguity by mixing two primers in the same reaction tube to amplify the diatoms, and if two primers still could not identify a species, a combination of three primers could be employed. However, the more primers used, the more difficult the experiment becomes to optimize and interpret.

Compared to high-throughput sequencing, which remains the most effective molecular approach for identifying species in complex mixed samples, multiplex PCR-HRM offers distinct practical advantages. Sequencing can simultaneously obtain DNA sequence data from a large number of species and has the potential to reveal unknown species within complex samples, but it is limited by high costs, long experimental cycles, and vast and complex data analysis requirements. It also depends heavily on the completeness and reliability of reference databases. Multiplex PCR-HRM, by contrast, completes PCR amplification and HRM detection in the same closed tube without any intermediate operations, reducing the risk of cross-contamination while simplifying the process and saving time. The technology requires only a high-resolution real-time fluorescence PCR instrument and corresponding reagents, resulting in relatively low costs that place it within reach of basic laboratories.

The researchers acknowledge that their current system can detect only four types of diatoms from a mixture of eight samples, a limitation they attribute to an insufficient number of specific primers and differences in amplification efficiency among them. They plan to continue designing primers for additional diatom species and to optimize the multiplex PCR-HRM system by adjusting the PCR reaction conditions, verifying the sensitivity of each primer, and refining the concentration ratios between primers. Importantly, the study did not validate the system using environmental water samples, so its performance on unknown samples remains to be determined. Nevertheless, this preliminary demonstration establishes the feasibility of the multiplex PCR-HRM approach for analyzing mixed diatom samples, offering a rapid, specific, low-cost, and operationally simple method with promising prospects for both environmental monitoring and forensic practice. As climate change and pollution continue to pressure aquatic ecosystems worldwide, and as forensic laboratories seek faster and more reliable tools for drowning diagnosis, this elegant fusion of molecular biology and thermal analysis may soon find itself at the forefront of diatom identification technology.

Subject of Research: Molecular Diagnostics

Article Title: An experimental study on HRM combined with multiplex PCR for the identification of single and mixed diatom species

Article References: Zhou, Y., Liu, Y., Cong, B., Chen, J., & Deng, J. (2026). An experimental study on HRM combined with multiplex PCR for the identification of single and mixed diatom species. iScience, 29(11), Article 117909. https://doi.org/10.1016/j.isci.2026.117909

Image Credits: AI Generated

DOI: 10.1016/j.isci.2026.117909

Keywords: experimental, combined, multiplex, identification, single, mixed, diatom, species, scientific research

The platform, described in BMC Cancer, is called StarTrace, and its central idea is deceptively simple. Patient-derived organoids, miniature tumors grown in the laboratory from a patient’s own cancer cells, are already recognized as accurate avatars of the tumors they came from. What StarTrace adds is a way to pool organoids from many different patients into a single dish, expose the entire pool to a drug, and then determine how each patient’s organoid fared. The trick that makes this possible is clonal DNA barcoding: each organoid line is tagged with a unique DNA barcode, one of 72 distinct sequences assembled for the study, that travels with the cells as they grow, divide, and respond to treatment.

Reading out the results relies on a Darwinian logic. When a pool of barcoded organoids is treated with a drug, sensitive organoids die or stop proliferating, so the abundance of their barcodes in the population falls. Resistant organoids keep growing, and their barcodes rise in relative frequency. By comparing barcode abundance before and after treatment, the researchers obtain a quantitative measure of the relative fitness of every organoid in the pool under every drug condition tested. A barcode that drops sharply in frequency after 28 days of exposure to a tyrosine kinase inhibitor flags that patient’s tumor as sensitive; a barcode that holds steady or climbs flags resistance.

Two complementary readout methods track the barcodes. The first is quantitative real-time PCR, a fast and inexpensive assay that can measure the abundance of specific barcode sequences directly. The second is next-generation sequencing, which in this study took the form of single-molecule sequencing assays capable of counting all 72 barcodes simultaneously and deconvoluting the pool over time. The team used the sequencing approach to follow the log-fold change in frequency of each barcoded organoid across a 28-day treatment course, comparing each barcode against a vehicle-treated control. Supplementary data released with the paper include the barcode sequences and their raw counts after each drug treatment, allowing the fitness calculations to be examined in detail.

The organoids themselves came from a biobank of colorectal cancer samples collected under an approved institutional protocol, the Palmetto Health–University of South Carolina Biorepository. Each organoid line was genetically characterized by whole exome sequencing, and somatic mutations in known driver genes were cataloged, with patient-matched normal organoids serving as controls to distinguish inherited variants from tumor-specific ones. The lines included both TP53-mutant and TP53-wildtype organoids, giving the pool a spread of genetic backgrounds against which drug responses could be compared. This genetic annotation matters because one long-term aim of the work is to connect observed drug sensitivity or resistance back to the mutations that cause it, building a map of drug-genetic interactions from real phenotypic data.

The multiplexing is what transforms the economics of the assay. In a conventional organoid drug screen, each patient’s organoids must be plated, treated, and analyzed separately, so testing ten patients against ten drugs requires a hundred independent cultures. In a StarTrace pool, those same hundred data points emerge from a handful of pooled cultures, because every dish contains all ten patients’ organoids at once and each drug condition is tested against the full pool simultaneously. The researchers describe the approach as streamlined and scalable, and the barcode counts from sequencing provide the quantitative depth needed to detect relative fitness changes even when individual organoids grow at different baseline rates within the pool.

The study focused on small molecule inhibitors, including tyrosine kinase inhibitors of the kind widely used in cancer therapy. By tracking relative changes in barcode abundance, the platform compared different patients’ organoid avatars’ responses to the various drugs, generating sensitivity and resistance profiles for each line. The authors note that these comparative response patterns may inform treatment selection in future applications, effectively offering a phase-zero-style phenotypic trial conducted entirely in vitro before any drug reaches the patient. Rather than asking whether a mutation predicts response, the assay asks the tumor itself how it responds, which is the question clinicians actually need answered.

The implications run in two directions. For personalized medicine, a platform that can test a patient’s organoid avatar against a panel of drugs quickly and quantitatively could help oncologists rank treatment options when genetic data alone is ambiguous, a common situation in colorectal cancer where resistance mechanisms are poorly mapped. For preclinical drug development, the same multiplexing logic allows a candidate compound to be screened against dozens of genetically diverse tumor avatars at once, revealing early whether activity is broad or confined to a specific molecular subset. High-throughput screening, phenotypic drug screening, and lab-on-a-chip technologies are all listed among the related subject areas, reflecting where the authors see the platform fitting into the broader research landscape.

The work is early-stage, and the authors are careful about what the current results demonstrate. The published study establishes the quantitative platform and shows that pooled barcode readouts can compare organoid drug responses across patients; clinical validation, prospective trials, and regulatory pathways remain ahead. The team has also moved to protect the invention, filing a U.S. patent application in November 2024 covering the multiplex drug testing platform. Organoid biobanking was supported by an NCI Small Business Innovation Research award, signaling that the group intends to develop the technology toward practical use rather than leave it as a laboratory curiosity.

StarTrace arrives at a moment when organoid technology is maturing from a research tool into a potential clinical decision-support system. Its contribution is architectural rather than biological: by borrowing the barcode-counting logic of modern genomics and applying it to pooled living tumor avatars, it converts drug sensitivity testing from a series of separate experiments into a single scalable measurement. If subsequent studies confirm that pooled barcode fitness readouts predict patient outcomes, the days of choosing cancer therapy by mutation guesswork may be numbered, replaced by a quantitative answer delivered by the tumor itself.

Subject of Research: Multiplex DNA-barcoded organoid avatars for pooled drug sensitivity testing in colorectal cancer

Article Title: StarTrace: a multiplex organoid avatar drug testing platform for personalized medicine

Article References: Khalili, S., Patel, S., Patel, N., Moy, V., Lyons, S., Gray, E., Brents, R., Banister, C. E., Morrison, S. E., & Buckhaults, P. J. (2026). StarTrace: a multiplex organoid avatar drug testing platform for personalized medicine. BMC Cancer. https://doi.org/10.1186/s12885-026-16921-3

Image Credits: AI Generated

DOI: 10.1186/s12885-026-16921-3

Keywords: patient-derived organoids, colorectal cancer, drug screening, precision medicine, DNA barcoding, high-throughput screening, quantitative PCR, next-generation sequencing, StarTrace, multiplex, organoid, avatar