Biomedical subjects

Thidathip Wongsurawat

Publications and source records attributed to Thidathip Wongsurawat.

5 recordsLinked to original sources

PubMed2026

Cross-Platform Concordance in DNA Methylation Based Classification of CNS Tumors.

DNA methylation profiling enables precise classification of pediatric central nervous system (CNS) tumors. Oxford Nanopore Technologies (ONT) offers same-day, single-sample methylation readouts, but its concordance with Illumina EPIC arrays in routine diagnostic tasks remains incompletely defined. We profiled 23 pediatric tumors (18 CNS, 5 non-CNS) by EPIC arrays and ONT. Methylation profiles from both platforms were classified with crossNN (brain model or pan-cancer model); ONT data were additionally classified with Rapid-CNS2 and Sturgeon. We compared (i) classifier agreement with integrated histology (w/o NGS) at family/class levels, (ii) pass-rate above platform-specific score cutoffs, (iii) cross-platform concordance of copy-number variation (CNV), and MGMT promoter methylation status. In CNS cases, ONT and EPIC methylation profiles demonstrated strong correlation, except for a single outlier (P2), which was excluded from further analysis. Comparative assessment of the two platforms showed that: (a) Molecular classification of CNS tumors using the crossNN classifier was consistent with histology (w/o NGS) at the family level in all cases. (b) Copy-number profiles showed high concordance between platforms. (c) MGMT promoter methylation status matched in 94% of cases (16/17). When comparing ONT-specific analysis pipelines using the ONT data, the Rapid-CNS2 pipeline yielded the most reliable class level assignments with 94% (16/17) concordance with the histopathological diagnosis, which marginally exceeded the crossNN and sturgeon classifiers. In non-CNS tumors, the pan-cancer model produced low-confidence outputs with poor agreement with histology (w/o NGS) (only 1/5 concordant), indicating limited readiness for these entities. In conclusion, ONT enables same-day, clinically reliable family-level CNS tumor classification with high concordance to arrays, while EPIC retains a modest class-level edge. A key limitation of ONT is its reliance on fresh-frozen DNA and on classifiers originally built around array-derived CpG sites, rather than on models developed natively from ONT data.

DNA methylation↗

PubMed2026

Intra-amniotic infection: diagnosis, nomenclature, clinical significance, management, and microbiologic tools used for the diagnosis.

SUMMARYIntra-amniotic infection is the main cause of spontaneous preterm birth and adverse maternal-fetal outcomes; therefore, rapid, robust, and accurate diagnosis remains a clinical priority. Conventional microbiological techniques, especially culture-based methods, are limited by long turnaround times and the inability to detect fastidious or unculturable organisms. This review summarizes the diagnosis, nomenclature, clinical significance, management, and laboratory approaches for diagnosing intra-amniotic infection. Targeted nucleic acid amplification methods, including species-specific polymerase chain reaction and broad-range 16S rRNA gene sequencing, have improved the detection of bacterial DNA and enabled the identification of organisms that evade routine culture in intra-amniotic infection. More recently, whole-genome sequencing and metagenomic next-generation sequencing have provided culture-independent strategies for comprehensive pathogen profiling, allowing simultaneous detection of bacteria, viruses, and fungi, as well as characterization of antimicrobial resistance determinants and virulence-associated genes. However, challenges remain, particularly in low-biomass samples such as amniotic fluid, where contamination, host DNA background, and data interpretation can compromise specificity. This review critically evaluates the advantages and limitations of each molecular modality and discusses pre-analytical, analytical, and bioinformatic considerations essential for reliable implementation. Integration of molecular diagnostics into clinical workflows holds promise for improving etiological diagnosis and guiding targeted therapy in intra-amniotic infection, thereby improving maternal and fetal outcomes.

Humans↗

PubMed2026

Hybrid genome assembly and phenotypic assays reveal carbohydrate metabolism diversity in Lacticaseibacillus strains.

Investigation of carbohydrate metabolism in lactic acid bacteria is essential for the rational selection of strains for fermentation processes, particularly in emerging applications involving non-conventional substrates or building of synthetic microbial consortia. However, establishing robust genotype-phenotype relationships remains challenging, as gene presence alone often fails to explain observed metabolic traits without considering the genomic context and regulatory architecture. In the present study, we combined hybrid genome assembly (Illumina and Oxford Nanopore) with high-throughput phenotype profiling (Biolog GENIII and PM2A) to investigate carbohydrate utilization in five Lacticaseibacillus strains. Phenotypic assays revealed clear intra- and inter-specific variability in substrate utilization. We therefore investigated whether such differences could be attributed to the organization and regulatory context of carbohydrate-associated loci, rather than to gene presence alone. Functional annotation based on COG and CAZyme databases revealed candidate genomic regions potentially involved in carbohydrate metabolism. Comparative analysis between predicted and experimentally observed substrate usage highlighted specific loci associated with carbohydrate utilization profile. The trehalose (tre) operon was conserved across all strains, while at least two distinct cellobiose-associated loci were detected in each genome. Despite the presence of these loci, L. paracasei strains were unable to metabolize cellobiose, a phenotype likely linked to the presence of a downstream TetR-type transcriptional repressor within the cellobiose (cel) operon. Additionally, a genomic region uniquely found in L. rhamnosus strains was associated with gentiobiose utilization, consistent with phenotypic observations. Overall, these findings highlight the importance of integrating phenotypic validation with complete genome context to support the identification of candidate structural and regulatory determinants of carbohydrate utilization in lactic acid bacteria. KEY POINTS: • Phenotype microarrays reveal metabolic traits of interest in isolated strains. • Regulatory context is key to understanding carbohydrate metabolism differences. • Basis of subspecies-dependent cellobiose metabolism in L. paracasei is provided.

Carbohydrate Metabolism↗

PubMed2026

Whole-genome sequencing reveals hidden antimicrobial resistance genes in phenotypically susceptible probiotic candidate lactic acid bacteria.

Phenotypic assays commonly used to evaluate probiotic safety may fail to detect clinically relevant antimicrobial resistance (AMR), potentially allowing genetically concerning strains to appear acceptable based on MIC testing alone. To explore this issue, we applied whole-genome sequencing (WGS) to three lactic acid bacteria (LAB) isolates previously identified as probiotic candidates based on acid and bile tolerance, antagonism against enteric pathogens, and biofilm formation in vitro: Lactiplantibacillus plantarum L25F and L22F (from pigs) and Ligilactobacillus salivarius AF2319 (from a chicken). Genome annotation identified extensive repertoires of probiotic-associated genes (46-47 per strain) linked to stress tolerance, adhesion, immunomodulation, and quorum sensing, supporting functional potential. The two L. plantarum strains exhibited broader predicted metabolic capacities than L. salivarius AF2319. However, genomic analysis revealed acquired AMR genes with complex genotype-phenotype relationships not fully apparent from phenotypic testing. The L. plantarum strains harbored lnu(A) (99.79% identity) on extrachromosomal DNA, conferring the L-phenotype (lincomycin resistance, clindamycin susceptibility); clindamycin MICs (1 mg/L) were concordant with this genotype, though lincomycin MICs were not determined. L. salivarius AF2319 carried tet(M), tet(L), and erm(C) (99.48%, 99.49%, and 99.45% identity by ResFinder, respectively) on extrachromosomal DNA; notably, the erythromycin MIC (1 mg/L) was precisely at the EFSA breakpoint (≤ 1 mg/L), representing borderline genotype-phenotype discordance potentially due to silent gene expression. Under current EFSA QPS criteria, these acquired ARGs would preclude all three strains from approval as probiotic feed additives despite favorable functional profiles, underscoring the indispensable role of WGS-based AMR gene detection in modern probiotic safety evaluation.

Probiotics↗

PubMed2026

Oxford Nanopore Sequencing of Clinical DNA for Identification and Comparative Genomic Analysis of Erysipelothrix piscisicarius.

The genus Erysipelothrix comprises facultative anaerobic, nonspore-forming, gram-positive bacteria that can cause skin infections and severe diseases such as septicemia and endocarditis in humans. Although E. rhusiopathiae is the primary pathogen, other species may also be involved, necessitating accurate identification. However, 16S rDNA sequencing lacks sufficient resolution to differentiate among Erysipelothrix species. In this study, we used Oxford Nanopore Technology (ONT) to directly sequence low-quality DNA extracted from heart valve tissue of a 66-year-old female patient with a fatal case of septicemia and aortic endocarditis. In contrast to 16S rDNA Illumina sequencing and matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS), which incorrectly identified the pathogen as E. rhusiopathiae, direct sequencing via ONT precisely identified E. piscisicarius as the cause of infection. About 1.47 Mb genome was retrieved from nanopore direct sequencing. Within the E. piscisicarius genome, we detected genes associated with virulence. Phylogenetic analysis showed that our strain clustered with a human-derived E. piscisicarius strain from China and swine-derived strains from Brazil. In conclusion, this study demonstrated that ONT can be used to sequence low-quality DNA extracted directly from patient specimens, obtain a draft bacterial genome, and reliably distinguish between pathogenic species.

Aged↗