BioTechniques

Museum collections of Coleoptera contain genetic material of potential interest to biotechnology, and non-destructive DNA extraction enables the preservation of important specimens with concomitant release of mitochondrial and genomic DNA. Mini-barcoding of regions of the mitochondrial cytochrome oxidase subunit I (MT-COI) gene helps identify and eliminate known species from further investigation. Here we identify a novel luciferase gene, using Consensus Degenerate Hybrid Oligonucleotide (CODEHOP) primers targeting the region of the luciferase gene spanning the fourth exon, intron, and fifth exon to detect luciferase gene content and eliminate samples containing known luciferase sequences. Biotinylated luciferase gene probes from the firefly Photinus pyralis enabled the enrichment of potential luciferase gene fragments for next-generation sequencing. A bioinformatic analysis suite was then used to identify a luciferase gene sequence from a previously unidentified firefly originally collected in Costa Rica in 2012. We demonstrate that this newly discovered luciferase, termed CRLuc, catalyses a bioluminescent reaction and we determined its emission spectra, Km for the substrates ATP and D-luciferin, and pH stability.

BackgroundDNA polymerase activity assays are required for enzyme quality control in biotechnology and diagnostics, but standard methods rely on specialist reagents, radioactivity and other hazardous materials, or real-time PCR instruments that are not widely accessible in resource-limited settings. This constrains local production of high quality, validated reagents and increases dependence on imported enzymes. MethodsBased on experiences derived from partnerships with scientists in several low and middle-income countries (LMICs) and stakeholder consultations, we adapted a commercial EvaGreen-based fluorometric DNA polymerase activity assay for isothermal operation using minimal equipment. Assay conditions were optimized using Design of Experiments (DOE) methodology, varying temperature, reaction volume, and MgCl2 concentration. To address reagent cost and supply-chain constraints, we developed detailed protocols for in-house synthesis of the off-patent AOAO-12 DNA dye (sold commercially as EvaGreen) and generation of single-stranded DNA templates via asymmetric PCR. ResultsOptimized isothermal assay conditions (40{degrees}C, 7.75 mM MgCl2) reliably quantified activity across multiple DNA polymerase families. In-house synthesized AOAO-12 dye exhibited comparable DNA-binding performance to commercial alternatives (R{superscript 2} = 0.95), reducing costs by more than an order of magnitude when normalized to working concentrations, enabling assay costs of approximately {pound}0.001 per reaction. The assay is effective across multiple polymerases (Bst-LF, OpenVent, Taq, Q5) and is compatible with both plate readers and qByte, a low-cost, open-source fluorometric device. ConclusionsThis stakeholder-informed assay provides an accessible, cost-effective solution for DNA polymerase quality control in resource-limited settings. The combination of optimized commercial protocols and in-house reagent synthesis offers flexibility for different resource contexts, potentially improving access to molecular biology tools globally.

Advances in transcriptomic technologies have transformed the study of complex biological processes, including tissue regeneration, by enabling high-resolution characterization of gene expression programs. In regenerative vertebrate models such as the Iberian ribbed newt (Pleurodeles waltl), these approaches can provide critical insight into the molecular mechanisms underlying retina and lens regeneration. However, single-cell and single-nucleus RNA sequencing studies lack spatial resolution, therefore the ability to validate gene expression patterns within ocular tissues is essential and requires optimization. In this study, we optimized hybridization chain reaction fluorescent in situ hybridization (HCR-FISH) for use in P. waltl eyes. HCR-FISH enables sensitive and specific detection of mRNA transcripts through split-initiator probes and hairpin-based signal amplification with automatic background suppression. In addition, because incomplete genome annotation in emerging model organisms complicates transcript selection and probe design, we optimized an optional in silico workflow to support transcript screening, orthology confirmation, and split-initiator probe generation. We systematically optimized fixation duration, proteinase K concentration, and tissue processing parameters to preserve tissue integrity while enhancing signal quality. To overcome imaging constraints imposed by highly pigmented ocular tissues, we implemented a whole-mount protocol with optional bleaching followed by cryosectioning, enabling improved visualization without compromising spatial localization. Using this workflow, we successfully detected key retinal markers including SLC1A3 (Muller glia cells) and RPE65 (retinal pigment epithelium) within the newt eye. Notably, the RPE65 probe was designed in house and showed comparable detection to a standard Molecular Instruments probe across two sample-preparation protocols. This study presents a reproducible framework for spatial transcript detection in an emerging eye regenerative model and facilitates integration of transcriptomic and anatomical data. Together, the integrated design-to-detection pipeline will strengthen spatial validation of RNA sequencing profiles in P. waltl.

Fluorescent in situ hybridization (FISH) enables highly sensitive, high-resolution detection of gene transcripts. Moreover, by employing multiple probes, this technique allows for multiplexed, simultaneous detection of distinct gene expression patterns spatiotemporally, making it a valuable spatial transcriptomics approach. Owing to these advantages, FISH techniques are rapidly being adopted across diverse areas of basic biology. However, conventional protocols often rely on volatile, toxic reagents such as formalin or methanol, posing potential health risks to researchers. Here, we present a safer protocol that replaces these chemicals with low-toxicity alternatives, without compromising the high detection sensitivity of FISH. We validated this protocol using both in situ hybridization chain reaction (HCR) and signal amplification by exchange reaction (SABER)-FISH in frozen sections of various model organisms, including mouse (Mus musculus), amphibians (Xenopus laevis and Pleurodeles waltl), and medaka (Oryzias latipes). Our results demonstrate successful multiplexed detection of morphogenetic and cell-type marker genes in these model animals using this safer protocol. The protocol has the additional advantage of requiring no proteolytic enzyme treatment, thus preserving tissue integrity. Furthermore, we show that this protocol is fully compatible with EGFP immunostaining, allowing for the simultaneous detection of mRNAs and reporter proteins in transgenic animals. This protocol retains the benefits of highly sensitive, multiplexed, and multimodal detection afforded by integrating in situ HCR and SABER-FISH with immunohistochemistry, while providing a safer option for researchers, thereby offering a valuable tool for basic biology.

Multiplexing samples in long-read sequencing with Oxford Nanopore Next Generation Sequencing Technology (ONT) by ligating specific native barcodes to individual DNA samples enables significant increases of high throughput sequencing combined with a significant reduction of sequencing costs. However, this advantage carries the risk of barcode misassignment / crosstalk. Employing ONT multiplex sequencing with samples, we observed misassigned barcodes so called barcode crosstalk, after ONT library preparation according to the standard protocol, particularly in samples with low input DNA concentrations. We assumed that these barcode misassignments are largely due to misligation of remaining native barcodes during subsequent the subsequent sequencing adapter ligation. To systematically investigate and quantify barcode crosstalk, genomic DNA (gDNA) from four bacterial type strains with different DNA input concentrations was prepared using three protocols for library preparation: the Nanopore standard protocol (protocol A: version valid until July 2, 2025) the new Nanopore protocol (protocol B: version from July 2, 2025), and an in house protocol with pooling of the barcoded samples only after the sequencing adapter ligation step (protocol C: in house). All samples were sequenced on a Nanopore PromethIon device. The results clearly showed that the use of protocol A resulted in a pronounced barcode crosstalk especially detectable in samples with low DNA input concentrations (up to 2.4% misassigned reads). The ONT adjustment in protocol B (altered washing buffer vs. protocol A) significantly alleviated the barcode crosstalk to below 0.01%, whereas protocol C eliminated barcode crosstalk virtually completely. These observations emphasize that sequencing results obtained with older ONT native barcoding protocol variants should be critically reviewed. The newer ONT barcoding protocol is preferable for sequencing, but it does not completely eliminate the barcode crosstalk effect. In conclusion, for low DNA input and high accuracy sequencing, protocol C is recommended.

Brain banks provide small tissue samples fixed in neutral-buffered-formalin (NBF), but human anatomy teaching laboratories could provide full brains fixed with solutions that are more appropriate for gross anatomy such as a saturated salt solution (SSS) or an alcohol-formaldehyde solution (AFS). Advanced aging and prolonged exposure to aldehydes are known to enhance brain tissue autofluorescence (AF), limiting the efficacy of immunofluorescence (IF) procedures. We have previously shown by IF staining the antigenicity preservation in mouse brains fixed with the three solutions. We now aimed to compare the quality of IF staining in human brains fixed with SSS, AFS and NBF. In addition, we compared the efficiency of AF quenching methods, namely the application of SudanBlackB (SBB) and the treatment of sections with sodium borohydride (NaBH4). Blocks of neocortex were extracted from 18 brains (NBF=6, SSS=6, AFS=6) and cut into 40{micro}m sections. Neurons (anti-NeuN, AlexaFluor-488) and astrocytes (anti-GFAP, AlexaFluor-555) were revealed with IF after an antigen retrieval protocol, while two treatments (SBB or NaBH4) were used to quench AF. We then assessed the degree of AF (criteria: background or cell AF) and the immunostaining quality with excitation wavelengths of 488nm, 555nm and 647nm. Brains fixed with all three solutions showed well-labeled astrocytes, whereas neurons werent always stained, but this was not associated to the fixative solution. The overall AF intensity was similar in sections from brains fixed with all three solutions. Finally, the SBB treatment was the most effective at reducing AF in all specimens. Given the similarity in AF and antigenicity assessment across the three solutions, we conclude that brains fixed with SSS and AFS could be good alternatives for NBF-fixed specimens in the context of IF experiments processed with a SBB protocol. Highlights- Immunofluorescence staining is feasible in brains fixed with anatomy labs solutions - GFAP is less affected by fixation than NeuN - Autofluorescence can be reduced by Sudan Black treatment

Assessing reproducibility across different molecular profiling studies is a persistent methodological challenge (Zhang et al., 2009; Sweeney et al., 2017; Ioannidis, 2005). Differences in platform technology, cohort composition, analytical pipelines, and feature definitions often make it difficult to interpret cross-study comparisons based solely on gene-identity overlap. In this study, we conducted a retrospective computational analysis of seven publicly available analytical datasets (including alternative analytical pipelines applied to the same cohort) derived from five biologically independent peripheral blood transcriptomic and DNA methylation cohorts, comprising 3,487 samples (1,824 Parkinsons disease cases and 1,663 controls). Reproducibility was evaluated using gene-identity overlap, enrichment-based comparisons, and a permutation-based framework to assess directional consistency of effect estimates across datasets. We also tested the robustness of results by varying false discovery rate thresholds and applying alternative probe-to-gene collapsing strategies. All analyses were performed using reproducible workflows implemented in R and Python with fixed random seeds. Across independent cohorts, gene-identity overlap was generally limited, with enrichment ratios close to one, especially when datasets were generated using different platforms. In several datasets, limited numbers of statistically significant features further constrained overlap-based comparisons. In contrast, directional consistency showed greater stability. High levels of directional consistency were observed across independent cohort comparisons when restricted to overlapping statistically significant features and remained stable across statistical thresholds (90.0% at FDR < 0.05 and 82.8% at FDR < 0.10). When evaluated across the full shared gene universe without conditioning on statistical significance, directional consistency was substantially lower ([~]30 to 32%) but remained significantly above permutation-based null expectations. Permutation testing confirmed that the observed directional consistency exceeded what would be expected by chance. A combined analysis including methodological replicates (n [&ge;] 3 datasets) showed 98.3% directional consistency; however, this estimate includes non-independent analytical pipelines applied to the same cohort and reflects analytical stability rather than independent biological replication. Rather than introducing a new statistical method, this study examines how commonly used reproducibility metrics behave under crossstudy heterogeneity and identifies their practical limitations and appropriate use boundaries.

MOTIVATIONAdult cardiomyocytes are difficult to profile by whole-cell single-cell RNA sequencing because of their large size and fragility, which make them poorly compatible with standard workflows. Current approaches for adult cardiomyocyte transcriptomics often require a trade-off between data quality and throughput, thus, studies instead rely heavily on sequencing of nuclei alone. Therefore, we set out to develop a high-quality and scalable workflow for adult heart cells using in-cell ligation and split-pool barcoding strategies to address this methodological gap. This workflow may be further generalisable to other large cell types or samples containing cell populations with highly unequal RNA content. SUMMARYAdult cardiomyocytes are difficult to profile by whole-cell single-cell RNA sequencing (scRNA-seq). Here, we developed a high-quality and scalable workflow for adult heart cells using in-cell ligation and split-pool barcoding. We identified per-cell RNA content as a significant variable that must be accounted for. Separation of cardiomyocytes (large cells) and non-cardiomyocytes (small cells) before library construction, and allocation of deeper sequencing to cardiomyocytes, produced high-quality whole-cell datasets for both compartments. Compared with single-nucleus RNA sequencing, whole-cell cardiomyocyte profiling better recovered metabolic, mitochondrial, cytoplasmic translational, and contractile gene programs. This workflow provides a practical method for scalable, high-quality cardiomyocyte whole-cell scRNA-seq and offers general strategies for other large cell types or samples containing cell populations with highly unequal RNA content.

The design of the classical fluorescence microscope has undergone few changes since the 1970s-1980s, when Ploemopak modules with filter cubes became widespread. Most of these changes have been in the replacement of mercury and xenon lamps with LED illuminators in the 2010s. However, this does not mean that this stable design cannot be improved upon. New method: The implementation of a vibrating optical fiber, positioned using a micromanipulator and connected to any suitable type of laser, enables a full spectrum of fluorescence research. This work presents an advanced version of the Ellis concept, in which light is delivered directly onto the sample, rather than into the filter cube (technical novelty).To confirm the functionality of the microscope, vibrational slices of mouse brain stained with three fluorescent markers (B3-PPC, DiI and DiD) covering most of the visible spectrum were examined. The fiber-optic illumination system eliminates the need for bulky and obsolete high-voltage plasma arc lamp units without compromising image quality (confirmed by the USAF 1951 test and SDNR assessment on fluorescent beads). Furthermore, the optical fiber mounted on manipulators is convenient and easy to integrate, for example, into stereomicroscopes for scanning large brain tissue samples.

Coenzyme A is an essential cofactor synthesized from pantothenate, cysteine, and ATP, and is involved in numerous processes of cellular metabolism through its ability to carry activated acyl groups. Coenzyme A participates in catabolism of carbohydrate, fat and amino acids; biosynthesis of fatty acids, cholesterol and heme; and protein modification including acetylation and 4-phosphopantetheinylation. Despite CoAs critical functions, the regulation of CoA levels and the rate of CoA synthesis in different cell types and disease states are not well understood. One reason for this gap is that many acyl-CoA species are analytically challenging to measure due to factors including instability, poor ionization, and the wide range of biochemical properties conferred by different acyl chain lengths. In addition, most current methods do not support analysis of CoA isotopic labeling, which is required to quantify CoA synthesis rate or to measure absolute concentration using isotope-labeled internal standards. Here, we describe a method to quantify the concentration and isotopic labeling of total CoA, defined as the sum of CoASH plus all acyl-CoA species. Acyl-CoA species are hydrolyzed using sodium hydroxide to remove acyl chains, then CoA is derivatized on the thiol with N-ethylmaleimide (NEM). Following protein precipitation and solid phase extraction, samples are analyzed by liquid chromatography-mass spectrometry. This method is linear in a wide range that captures mouse tissue CoA levels, with accuracy within 15% error and precision below 15% relative standard deviation for both pure standards and tissue samples. We applied this method to measure total CoA concentration in five tissues from male and female mice, and total CoA synthesis rate in mouse liver via infusion of 13C-15N-pantothenate. Overall, this method offers a tractable approach to measure total CoA concentration and isotopic labeling to enable study of total CoA synthesis rates and concentrations in health and disease.

Accurate quantification of fungi is important for a myriad of applications but remains challenging. Previously, we demonstrated that an approach called the adenine-HPLC method can quantify bacteria, including those with aggregating properties that are difficult to quantify using conventional methods, by measuring cellular adenine derived from DNA and converting the adenine amount to genome copy number, without being influenced by cell morphology. However, in this study, when this adenine-HPLC method was applied to the quantification of budding yeast as a model fungus, accurate measurement proved impossible. This limitation was attributed to adenine release from other adenine-containing biomolecules, such as RNA and ATP, and we therefore developed a method that suppresses adenine release from these molecules. This method involves reducing the temperature of the acid treatment and prewashing the cells before acid treatment. In addition, we incorporated a process that corrects for the naturally occurring free adenine level as background during total adenine measurement. The improved adenine-HPLC method based on these modifications enables accurate quantification of budding yeast using genomic DNA content in whole cells as the quantification unit.

The expansion of short tandem repeats is a feature of over 60 different human diseases. Ongoing somatic instability throughout a patients lifetime can influence disease progression and has emerged as a therapeutic target. Understanding its mechanism is essential for the identification of both drug targets and therapeutic interventions. A major obstacle towards this translational goal has been to measure changes in repeat size distribution in a timely manner. To address this, here we present Single Clone-based Instability Assay (SCIA), a streamlined experimental design that saves weeks in assessing the effect of a gene knockout on repeat instability. The approach avoids bulk cultures and does not require a reporter cell line. It uses targeted long-read sequencing as a readout for repeat instability. We have validated the approach using FAN1, PMS1, and MLH1 knockouts in HEK293-derived cells. We provide a visualization software that generates delta plots, extracts the instability frequency, the bias towards expansion or contraction, and the average size of the changes. Using SCIA, we find that although FAN1 knockout clones showed increased frequency of expansions, the size of the expansions were smaller. This highlights the wealth of information that can be extracted and the potential for novel insights into the mechanism of repeat instability.

BackgroundConventional clinical indicators of periodontitis progression detect disease after irreversible tissue destruction has occurred. Molecular biomarkers in gingival crevicular fluid (GCF) offer potential for earlier detection, but existing analytical approaches rely on cross-sectional snapshots that fail to capture the temporal dynamics of disease evolution. AimTo develop and validate a temporal deep learning framework leveraging longitudinal GCF protein profiles for (1) regression-based prediction of clinical attachment level (CAL) and probing depth (PD) changes, (2) current-visit classification of periodontitis progression, (3) next-visit prediction of progression with a 2-month clinical lead time, and (4) identification of the most informative biomarkers through systematic multi-method feature importance analysis. Materials and MethodsThis study utilized longitudinal GCF data from a prospective cohort of 413 participants (501 periodontal sites, 3,792 time-series observations) with 64 protein biomarkers measured at 2-month intervals over 12 months. A compact encoder-gated recurrent unit (GRU)-decoder architecture was developed through systematic experimentation across four phases, benchmarking temporal deep learning against cross-sectional machine learning baselines. Task-specific decoders addressed continuous regression (CAL and PD prediction) and binary classification (progression detection). Model development and reporting followed the TRIPOD+AI guidelines. ResultsThe temporal GRU achieved 47.7% CAL mean absolute error (MAE) reduction (1.139 to 0.596 mm) and 41.0% PD MAE reduction (0.902 to 0.532 mm) over linear regression baselines through the systematic model development progression. For binary classification, the model achieved AUC-ROC of 0.886 for current-visit classification and 0.867 for next-visit prediction with a 2-month lead time. Per-visit analysis revealed progressive improvement in both regression and classification accuracy as longitudinal data accumulated. Cross-method feature importance analysis identified Periostin, VEGF, MMP-2, IL-1RA, and MCP-4 as core predictive biomarkers, with divergent profiles between diagnostic and prognostic tasks suggesting distinct molecular signatures for concurrent versus incipient progression. ConclusionsTemporal deep learning applied to longitudinal GCF protein profiles enables both accurate regression prediction of clinical parameters and reliable classification of progression status, including 2-month-ahead forecasting suitable for clinical intervention planning. The compact architecture and non-invasive sampling approach make this framework suitable for integration into point-of-care periodontal monitoring workflows. Clinical RelevanceConventional clinical indicators of periodontitis progression, including probing depth changes, attachment loss, and radiographic bone loss, inherently detect disease after irreversible damage has occurred. This study shows that a compact deep learning model analyzing temporal GCF protein profiles can first accurately predict continuous changes in pocket depth and attachment loss, then classify progression status 2 months in advance, enabling proactive intervention before clinical manifestation of tissue destruction.

Accurate detection of RNA splice variants is often hindered when transcripts lack large distinguishable exonic regions, making conventional PCR strategies challenging. We developed a simple melting temperature (Tm)-guided exon-exon junction (EEJ) RT-PCR method to enable variant-specific detection under these conditions. Uni-directional primers spanning exon-exon junctions were designed so that approximately each half anneals to adjacent exons. The Tm of each half-site was set >7{degrees}C below the annealing temperature, preventing stable binding to individual exons and enforcing junction-dependent amplification. The method was evaluated using HTRA1-AS1 long noncoding RNA variants that share overlapping exon sequences but differ in splice connectivity. HTRA1-AS1 comprises five variants, only one with a large distinguishable exon. Tm-guided EEJ primers robustly discriminated the remaining four variants. After optimization, amplification yielded sharp, single bands with minimal cross-reactivity. Compared with conventional designs, this approach reduced heteroduplex and heteroquadruplex formation, improving band clarity. Sanger sequencing confirmed junction specificity, and the method performed well in multiplex settings. Overall, Tm-guided EEJ RT-PCR is a cost-effective, high-resolution approach for detecting RNA variants lacking easily distinguishable exonic regions, readily compatible with standard RT-PCR and qPCR workflows.

BackgroundGingival inflammation is associated with dysbiotic oral biofilms characterized by reduced nitrate-reducing capacity and diminished nitric oxide (NO) bioavailability. While dietary nitrate has been shown to influence oral microbial activity, the effects of sustained, localized nitrate delivery on oral biofilm ecology and gingival inflammation remain incompletely defined. Methods and findingsIn this randomized, double-blind, placebo-controlled trial, 30 adults with gingival bleeding were assigned to receive localized prebiotic nitrate ([~]0.989 mmol per dose) or placebo for 21 days. The primary outcome was mean bleeding on probing (mBOP). Secondary outcomes included modified Gingival Index (mGI), Quigley-Hein plaque index (QHPI), salivary nitrite (as a proxy for NO bioavailability), oral pH, and microbiome composition assessed by 16S rRNA gene sequencing. Nitrate supplementation significantly reduced mBOP (25.7% to 15.3%; p = 0.0002) compared to placebo. Salivary nitrite levels and oral pH increased, indicating enhanced nitrate metabolism. Microbiome analysis demonstrated enrichment of nitrate-reducing taxa, including Rothia mucilaginosa and Neisseria spp., and a relative reduction in inflammation-associated genera such as Prevotella and Porphyromonas. No significant differences were observed in plaque index, consistent with functional modulation of the biofilm rather than reduction in plaque accumulation. ConclusionsLocalized prebiotic nitrate supplementation was associated with reduced gingival inflammation and shifts in oral microbiome composition consistent with enhanced nitrate-reducing capacity critical in nitric oxide formation. These findings support a role for biofilm-directed nutritional modulation as a non-antimicrobial approach for managing gingival inflammation and improving nitric oxide bioavailability.

Sequencing the respiratory tract transcriptome has the potential to provide insights into infectious pathogens and the hosts immune response. While DNA-based sequencing is more standard in clinical laboratories due to its stability, RNA assays offer unique advantages. RNA reflects dynamic physiological changes, and for RNA viruses, viral RNA particles directly represent copies of the viral genome, enabling greater diagnostic sensitivity. However, RNAs susceptibility to degradation remains a significant challenge, particularly in RNase-rich specimens like saliva. To address this, we conducted a systematic, combinatorial evaluation of 24 distinct mNGS workflows, crossing eight nucleic acid extraction methods with three RNA-Seq library preparation protocols. Remnant saliva samples (n = 6) were pooled and spiked with MS2 phage as a control. The SARS-CoV-2 virus was spiked into half of the samples, which were extracted using the eight different extraction methods (n = 3) and compared using RNA Integrity Number equivalent (RINe) scores and RNA concentration. The extracted RNA was then processed across the three library construction methods and subjected to short-read sequencing to assess all 24 combinations head-to-head. We compared methods based on viral read recovery and found that RINe and concentration did not correlate with viral detection. The Zymo Quick-RNA Magbead kit and the Tecan Revelo RNA-Seq High-Sensitivity RNA library kit were the extraction and library-preparation kits that yielded the most SARS-CoV-2 reads, respectively. Importantly, our combinatorial analysis revealed that any small variability attributable to different nucleic acid extraction methods was heavily overshadowed by differences in quality attributable to the RNA-Seq library preparation methods. These findings challenge the reliance on conventional RNA quality metrics for clinical metagenomics and underscore the need to redefine extraction quality standards for mNGS applications. IMPORTANCEmNGS is a powerful and unbiased approach towards pathogen detection that has mostly been applied to blood and cerebrospinal fluid samples. However mNGS has recently been applied to more areas including the respiratory pathogen detection space, with potential applications in both in-patient diagnostics and public health surveillance. Saliva samples are an ideal sample type for these use cases since they can be collected non-invasively. However, saliva is also a challenging sample type due to its high RNase activity and often yields low-quality nucleic acid. This study explores the feasibility of using saliva specimens in mNGS with contrived SARS-CoV-2 samples to optimize the combination of two factors: nucleic acid extraction and RNA-seq library preparation. Exploration in this area could enhance the sensitivity of saliva-based mNGS assays, with the goal of future expansion of this specimen type in clinical diagnostics and public health surveillance. Key PointsO_LIThe choice of RNA-Seq library preparation kit has a greater impact on pathogen detection than the nucleic acid extraction method. C_LIO_LIThe combination of Zymo Quick-RNA Magbead extraction kit and TECAN Revelo RNA-Seq High Sensitivity RNA library kit recovered the highest percentage of total SARS-CoV-2 reads. C_LIO_LIRNA quantity and RINe score do not correlate with viral read capture, indicating a need for an alternative metric to assess RNA quality for downstream mNGS clinical diagnostics. C_LI

Here we evaluated the performance of a previously published tiling PCR primer scheme by Ringlander et al. (2022) for whole-genome amplification of Hepatitis B virus (HBV) in combination with Oxford Nanopore sequencing. The primer set originally developed for Ion Torrent sequencing was adapted by removing platform-specific adapters and tested using clinical serum or plasma samples submitted for routine HBV genotyping and resistance testing. Two multiplexing strategies were compared: a single PCR pool containing all primers and a two-pool strategy with non-overlapping amplicons. Sequencing reads were processed using a Nanopore analysis pipeline, and genome coverage and amplicon performance were compared across samples spanning a wide Ct range and representing HBV genotypes A-E. Across all samples, the median genome coverage was approximately 50%, although recovery varied widely, ranging from complete failure to nearly full genomes. Combining all primers into a single PCR reaction, or separating overlapping amplicons into different reactions, had little overall impact on genome recovery, and no consistent differences between the two pooling strategies were observed. In contrast, amplification efficiency differed markedly between individual amplicons. Amplicons 1-5 generally produced higher sequencing depth, whereas amplicons 6-10 frequently showed low coverage and contributed to incomplete genome recovery. Genome coverage was strongly associated with Ct values, with higher coverage observed in samples with lower Ct values, while coverage was broadly similar across genotypes. These results demonstrate that the Ringlander et al. primer scheme can be adapted for multiplex PCR and Nanopore sequencing of HBV, but uneven amplicon performance limits consistent full-genome recovery and highlights the need for further optimization of HBV tiling PCR designs.

Acidification of the oral environment has been implicated in the initiation and progression of oral pathologies including oral cancer, but how acidic environments modulate normal oral epithelial cell (OEC) responses to microbial ligands is not understood. This study examined the impact of acidic stress on OEC morphological, molecular, and functional responses to toll-like-receptor ligand engagement in vitro. OEC cultures were exposed to either normal (pH:=:8.0) or acidified growth media (pH:=:3.0) for 24 hours prior to machine-learning-guided morphological analysis and exposure to either toll-like receptor (TLR)5 (flagellin) or TLR2/TLR1 (Pam3CSK4) agonists. Multiplex gene expression technology was used to quantify the transcriptional responses of metabolic-and immune-related genes at 6 hours post-TLR agonist exposure. OEC-mediated production of transforming growth factor-beta (TGF-{beta}) was assessed by enzyme-linked immunosorbent assay at 2-, 6-, and 24-hours post-agonist exposure. Results showed that acid exposure induced significant changes to OEC morphology resembling epithelial-mesenchymal transition, the differential expression of n=197 metabolic-and n=43 immune-related genes and significantly increased OEC TGF-{beta}1 production. The results demonstrate that acid stress skews normal OECs towards pro-inflammatory and pro-oncogenic phenotypes when faced with concomitant microbial ligand challenge and provide key molecular clues to OEC survival strategies with potential implications for elucidating the early molecular events in the development of epithelial dysplasia. Article HighlightsO_LIAcute acid exposure reduces survival of OECs C_LIO_LIA subpopulation of OECs is resistant to acid-mediated cell loss and undergo morphometric changes consistent with epithelial-mesenchymal transition C_LIO_LIConcurrent acid stress and TLR stimulation modulates transcription of immune and metabolic genes in OECs C_LIO_LIAcid stress increases TGF-{beta}1 protein production of OECs following TLR agonist stimulation C_LI

Nicking Loop is a PCR-free targeted library preparation method that combines conversion of linear target DNA into circular single-stranded DNA (CssDNA) library with early sample indexing in a single step. The resulting CssDNA libraries can be either directly sequenced or optionally amplified, offering maximum flexibility across sequencing applications. This study demonstrates the compatibility of Nicking Loop circular libraries with a MGIs DNBSEQ platform. Compatibility was evaluated against established linear Nicking Loop libraries sequenced on Illumina MiSeq platform. Using synthetic reference samples with defined variant allele frequencies, Nicking Loop method demonstrated matching performance across both library formats and sequencing platforms. Key quality metrics, including unique molecular identifier (UMI) distributions, error profiles and VAF detection, were all highly consistent. Both library types generated over 97% singleton UMIs, indicating uniform template sampling, and VAF measurements were strongly concordant across platforms (Spearmans {rho} = 0.939). Collectively, these findings demonstrate that Nicking Loop method is directly applicable to circular NGS platforms, such as DNBSEQ, strongly supporting its use as a platform-agnostic library preparation strategy for targeted sequencing applications.

Terrestrial environmental DNA (eDNA) approaches are rapidly expanding, yet robust, field-ready substrates for detecting insect DNA remain limited in forest ecosystems. Tree sap is a localized microhabitat that attracts diverse insects and may provide a useful substrate for surface eDNA sampling, but its potential for insect monitoring has rarely been evaluated. Here, we present a pilot proof-of-concept study testing naturally exuding tree sap and sap-mimicking traps as terrestrial eDNA substrates. We collected swab samples from sap and trap surfaces at two forest sites in Japan (Fujisawa and Minamisanriku) and performed metabarcoding using COI and an arthropod-focused 16S marker (gInsect). Reads were processed into amplicon sequence variants and assigned by BLAST top hits against NCBI nt, with high-confidence detections defined at identity [&ge;]98%. Across sites, sap and trap swabs yielded multiple high-confidence insect detections spanning several orders, including sap-associated stag beetles (Dorcus spp.). Overlap with contemporaneous conventional monitoring was limited, suggesting that sap-surface eDNA and conventional surveys capture partly different components of sap-associated insect assemblages. In a targeted 2024 spot survey, actively fermenting sap yielded multiple insect eDNA detections, whereas inactive, non-fermented sap yielded no high-confidence insect detections. Although limited by small sample size and the absence of dedicated process controls, these findings support the feasibility of tree sap as a localized terrestrial eDNA substrate and provide a basis for future replicated studies of sap-associated insect monitoring.