TACOS: a novel approach for accurate prediction of cell-specific long noncoding RNAs subcellular localization.

Long noncoding RNAs (lncRNAs) are primarily regulated by their cellular localization, which is responsible for their molecular functions, including cell cycle regulation and genome rearrangements. Accurately identifying the subcellular location of lncRNAs from sequence information is crucial for a better understanding of their biological functions and mechanisms. In contrast to traditional experimental methods, bioinformatics or computational methods can be applied for the annotation of lncRNA subcellular locations in humans more effectively. In the past, several machine learning-based methods have been developed to identify lncRNA subcellular localization, but relevant work for identifying cell-specific localization of human lncRNA remains limited. In this study, we present the first application of the tree-based stacking approach, TACOS, which allows users to identify the subcellular localization of human lncRNA in 10 different cell types. Specifically, we conducted comprehensive evaluations of six tree-based classifiers with 10 different feature descriptors, using a newly constructed balanced training dataset for each cell type. Subsequently, the strengths of the AdaBoost baseline models were integrated via a stacking approach, with an appropriate tree-based classifier for the final prediction. TACOS displayed consistent performance in both the cross-validation and independent assessments compared with the other two approaches employed in this study. The user-friendly online TACOS web server can be accessed at https://balalab-skku.org/TACOS.

Performance evaluation of commercial library construction kits for PCR-based targeted sequencing using a unique molecular identifier.

BACKGROUND: Target enrichment is a critical component of targeted deep next-generation sequencing for the cost-effective and sensitive detection of mutations, which is predominantly performed by either hybrid selection or PCR. Despite the advantages of efficient enrichment, PCR-based methods preclude the identification of PCR duplicates and their subsequent removal. Recently, this limitation was overcome by assigning a unique molecular identifier(UMI) to each template molecule. Currently, several commercial library construction kits based on PCR enrichment are available for UMIs, but there have been no systematic studies to compare their performances. In this study, we evaluated and compared the performances of five commercial library kits from four vendors: the Archer® Reveal ctDNA™ 28 Kit, NEBNext Direct® Cancer HotSpot Panel, Nugen Ovation® Custom Target Enrichment System, Qiagen Human Comprehensive Cancer Panel(HCCP), and Qiagen Human Actionable Solid Tumor Panel(HASTP). RESULTS: We evaluated and compared the performances of the five kits using 50 ng of genomic DNA for the library construction in terms of the library complexity, coverage uniformity, and errors in the UMIs. While the duplicate rates for all kits were dramatically decreased by identifying unique molecules with UMIs, the Qiagen HASTP achieved the highest library complexity based on the depth of unique coverage indicating superb library construction efficiency. Regarding the coverage uniformity, the kits from Nugen and NEB performed the best followed by the kits from Qiagen. We also analyzed the UMIs, including errors, which allowed us to adjust the depth of unique coverage and the length required for sufficient complexity. Based on these comparisons, we selected the Qiagen HASTP for further performance evaluations. The targeted deep sequencing method based on PCR target enrichment combined with UMI tagging sensitively detected mutations present at a frequency as low as 1% using 6.25 ng of human genomic DNA as the starting material. CONCLUSION: This study is the first systematic evaluation of commercial library construction kits for PCR-based targeted deep sequencing utilizing UMIs. Because the kits displayed significant variability in different quality metrics, our study offers a practical guideline for researchers to choose appropriate options for PCR-based targeted sequencing and useful benchmark data for evaluating new kits.

Bridging genomics and phenomics of gastric carcinoma.

Genetic alterations are the starting point leading to numerous changes in clinical and pathologic features (phenotypes) of individual cancers; however, their inter-relationships in gastric cancers (GC) are unclear. We performed massive parallel sequencing of 381 cancer-related genes and compared the results with clinical and pathologic findings in 330 GC. High tumor mutation burden (TMB) accounted for 11% of GC (n = 37) and all 19 MSI-H GCs were high TMB. High TMB was significantly more frequent in intestinal-type by Lauren, tumor with higher host cellular immune response, earlier AJCC stage and favorable prognosis. The most significantly mutated genes were TP53 (54%), ARID1A (23%), CDH1 (22%), PIK3CA (12%), RNF43 (10%) and KRAS (9%). For receptor tyrosine kinases, amplifications detected by immunohistochemistry were higher than sequencing (HER2, 9.1% vs. 5.8%; EGFR, 11.2% vs. 6.1%; FGFR2, 4.6% vs. 3.9%, c-MET, 3.4% vs. 0.9%). PTEN protein loss (22%) correlated well with underlying PTEN alterations while ATM loss (27%) was not significantly correlated with genetic alterations of ATM. p53 protein expression predicted alterations of TP53 with high sensitivity (97.8%) and low (15.9%) specificity. The poorly cohesive histology/CDH1-mutant GC subgroup showed the worst survival (p < 0.001). PD-L1 expression was significantly associated with MSI-H, MLH1 loss, ATM loss, MET positivity, higher host immune response, and genetic alterations of ARID1A, BRD3, PIK3CA, KRAS, MAP3K13, CDH2, PTEN and ESR1. The merged clinical, pathology and genomics of GC provide a better understanding of GC and new insights into the treatment of GC.

Effect of Dietary Vitamin C Supplementation on Growth Performance and Biochemical Parameters in Grower Walleye Pollock, Gadus chalcogrammus.

The optimal dietary vitamin C (VC) levels for walleye pollock (Gadus chalcogrammus) remain undefined. This study aimed to assess the effect of dietary VC levels on the growth performance and biochemical parameters of grower walleye pollock and determine the optimal VC level for their diet. Six experimental diets (VC0, VC1, VC3, VC5, VC7, and VC10) with VC levels of 3.24, 21.92, 63.31, 101.42, 145.46, and 202.51 mg kg-1 diet, respectively, were fed to fish (initial mean weight: 173.5 ± 0.31 g) for 8 weeks. At the end of the feeding trial, fish fed the VC7 and VC10 diets exhibited significantly higher growth (final body weight, weight gain, and specific growth rate) and improved feed utilization (feed efficiency and protein efficiency ratio) compared with fish fed the VC0 diet (p < 0.05). The VC3-VC10 diets significantly reduced plasma superoxide dismutase (SOD) activity (p < 0.05). Compared with the VC0 group, fish fed the VC7 and VC10 diets showed significantly elevated growth hormone and insulin-like growth factor-1 levels in plasma (p < 0.05). In conclusion, dietary VC supplementation in walleye pollock improved growth performance and SOD activity. Moreover, broken-line analysis on weight gain indicated that the optimal dietary VC level for grower walleye pollock was approximately 156.42 mg kg-1 diet.

3-Fucosyllactose-mediated modulation of immune response against virus infection.

Viral pathogens, particularly influenza and SARS-CoV-2, pose a significant global health challenge. Given the immunomodulatory properties of human milk oligosaccharides, in particular 2'-fucosyllactose and 3-fucosyllactose (3-FL), we investigated their dietary supplementation effects on antiviral responses in mouse models. This study revealed distinct immune modulations induced by 3-FL. RNA-sequencing data showed that 3-FL increased the expression of interferon receptors, such as Interferon Alpha and Beta Receptor (IFNAR) and Interferon Gamma Receptor (IFNGR), while simultaneously downregulating interferons and interferon-stimulated genes, an effect not observed with 2'-fucosyllactose supplementation. Such modulation enhanced antiviral responses in both cell culture and animal models while attenuating pre-emptive inflammatory responses. Nitric oxide concentrations in 3-FL-supplemented A549 cells and mouse lung tissues were elevated exclusively upon infection, reaching 5.8- and 1.9-fold increases over control groups, respectively. In addition, 3-FL promoted leukocyte infiltration into the site of infection upon viral challenge. 3-FL supplementation provided protective efficacy against lethal influenza challenge in mice. The demonstrated antiviral efficacy spanned multiple influenza strains and extended to SARS-CoV-2. In conclusion, 3-FL is a unique immunomodulator that helps protect the host from viral infection while suppressing inflammation prior to infection.

MiR-29 and MiR-140 regulate TRAIL-induced drug tolerance in lung cancer.

Tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) has chemotherapeutic potential as a regulator of an extrinsic apoptotic ligand, but its effect as a drug is limited by innate and acquired resistance. Recent findings suggest that an intermediate drug tolerance could mediate acquired resistance, which has made the main obstacle for limited utility of TRAIL as an anti-cancer therapeutics. We propose miRNA-dependent epigenetic modification drives the drug tolerant state in TRAIL-induced drug tolerant (TDT). Transcriptomic analysis revealed miR-29 target gene activation in TDT cells, showing oncogenic signature in lung cancer. Also, the restored TRAIL-sensitivity was associated with miR-29ac and 140-5p expressions, which is known as tumor suppressor by suppressing oncogenic protein RSK2 (p90 ribosomal S6 kinase), further confirmed in patient samples. Moreover, we extended this finding into 119 lung cancer cell lines from public data set, suggesting a significant correlation between TRAIL-sensitivity and RSK2 mRNA expression. Finally, we found that increased RSK2 mRNA is responsible for NF-κB activation, which we previously showed as a key determinant in both innate and acquired TRAIL-resistance. Our findings support further investigation of miR-29ac and -140-5p inhibition to maintain TRAIL-sensitivity and improve the durability of response to TRAIL in lung cancer.

A DNA-derived phage nose using machine learning and artificial neural processing for diagnosing lung cancer.

There is a growing interest in electronic nose-based diagnostic systems that are fast and portable. However, existing technologies are suitable only for operation in the laboratory, making them difficult to apply in a rapid, non-face-to-face, and field-suitable manner. Here, we demonstrate a DNA-derived phage nose (D2pNose) as a portable respiratory disease diagnosis system requiring no pretreatment. D2pNose was produced based on phage colour films implanted with DNA sequences from mammalian olfactory receptor cells, and as a result, it possesses the comprehensive reactivity of these cells. The manipulated surface chemistry of the genetically engineered phages was verified through a correlation analysis between the calculated and the experimentally measured reactivity. Breaths from 31 healthy subjects and 31 lung cancer patients were collected and exposed to D2pNose without pretreatment. With the help of deep learning and neural pattern separation, D2pNose has achieved a diagnostic success rate of over 75% and a classification success rate of over 86% for lung cancer based on raw human breath. Based on these results, D2pNose can be expected to be directly applicable to other respiratory diseases.

Junction Location Identifier (JuLI): Accurate Detection of DNA Fusions in Clinical Sequencing for Precision Oncology.

Accurate detection of genomic fusions by high-throughput sequencing in clinical samples with inadequate tumor purity and formalin-fixed, paraffin-embedded tissue is an essential task in precise oncology. We developed the fusion detection algorithm Junction Location Identifier (JuLI) for optimization of high-depth clinical sequencing. Novel filtering steps were implemented to minimize false positives in the clinical setting. The algorithm was comprehensively validated using high-depth sequencing data from cancer cell lines and clinical samples and genome sequencing data from NA12878. JuLI showed improved performance mainly in positive predictive value over state-of-the-art fusion callers in cases with high-depth clinical sequencing and rescued a driver fusion from false negative in plasma cell-free DNA using joint calling.

Stretchable and Low-Haze Ag-Nanowire-Network 2-D Films Embedded into a Cross-linked Polydimethylsiloxane Elastomer.

We report the fabrication of stretchable transparent electrode films (STEF) using 15-nm-diameter Ag nanowires networks embedded into a cross-linked polydimethylsiloxane elastomer. 15-nm-diameter Ag NWs with a high aspect ratio (˃1000) were synthesized through pressure-induced polyol synthesis in the presence of AgCl particles with KBr. These Ag NW network-based STEF exhibited considerably low haze values (<1.5%) with a transparency of 90% despite the low sheet resistance of 20 Ω/sq. The STEF exhibited an outstanding mechanical elasticity of up to 20% and no visible change occurred in the sheet resistance after 100 cycles at a stretching-release test of 20%.

Ambient-Stable and Durable Conductive Ag-Nanowire-Network 2-D Films Decorated with a Ti Layer.

Highly stable and durable conductive silver nanowire (Ag NW) network electrode films were prepared through decoration with a 5-nm-thick Ti layer. The Ag NW network 2-D films showed sheet resistance values as low as 32 ohm/sq at 88% transparency when decorated with Ti. These 2-D films exhibited a 30% increase in electrical conductivity while maintaining good stability of the films through enhanced resistance to moisture and oxygen penetration as a result of the protective effect of the Ti layer.

Performance evaluation method for read mapping tool in clinical panel sequencing.

In addition to the rapid advancement in Next-Generation Sequencing (NGS) technology, clinical panel sequencing is being used increasingly in clinical studies and tests. However, tools that are used in NGS data analysis have not been comparatively evaluated in performance for panel sequencing. This study aimed to evaluate the tools used in the alignment process, the first procedure in bioinformatics analysis, by comparing tools that have been widely used with ones that have been introduced recently. With the accumulated panel sequencing data, detected variant lists were cataloged and inserted into simulated reads produced from the reference genome (h19). The amount of unmapped reads and misaligned reads, mapping quality distribution, and runtime were measured as standards for comparison. As the most widely used tools, Bowtie2 and BWA-MEM each showed explicit performance with AUC of 0.9984 and 0.9970 respectively. Kart, maintaining superior runtime and less number of misaligned read, also similarly possessed high level of AUC (0.9723). Such selection and optimization method of tools appropriate for panel sequencing can be utilized for fields requiring error minimization, such as clinical application and liquid biopsy studies.

Comparison of alternative image reformatting techniques in micro-computed tomography and tooth clearing for detailed canal morphology.

INTRODUCTION: Micro-computed tomography (MCT) shows detailed root canal morphology that is not seen with traditional tooth clearing. However, alternative image reformatting techniques in MCT involving 2-dimensional (2D) minimum intensity projection (MinIP) and 3-dimensional (3D) volume-rendering reconstruction have not been directly compared with clearing. The aim was to compare alternative image reformatting techniques in MCT with tooth clearing on the mesiobuccal (MB) root of maxillary first molars. METHODS: Eighteen maxillary first molar MB roots were scanned, and 2D MinIP and 3D volume-rendered images were reconstructed. Subsequently, the same MB roots were processed by traditional tooth clearing. Images from 2D, 3D, 2D + 3D, and clearing techniques were assessed by 4 endodontists to classify canal configuration and to identify fine anatomic structures such as accessory canals, intercanal communications, and loops. RESULTS: All image reformatting techniques in MCT showed detailed configurations and numerous fine structures, such that none were classified as simple type I or II canals; several were classified as types III and IV according to Weine classification or types IV, V, and VI according to Vertucci; and most were nonclassifiable because of their complexity. The clearing images showed less detail, few fine structures, and numerous type I canals. Classification of canal configuration was in 100% intraobserver agreement for all 18 roots visualized by any of the image reformatting techniques in MCT but for only 4 roots (22.2%) classified according to Weine and 6 (33.3%) classified according to Vertucci, when using the clearing technique. CONCLUSIONS: The combination of 2D MinIP and 3D volume-rendered images showed the most detailed canal morphology and fine anatomic structures.