Comparison between Fluorimetry (Qubit) and Spectrophotometry (NanoDrop) in the Quantification of DNA and RNA Extracted from Frozen and FFPE Tissues from Lung Cancer Patients: A Real-World Use of Genomic Tests

Comparison of DeNovix, NanoDrop and Qubit for DNA quantification and impurity detection of bacterial DNA extracts

Accurate DNA quantification is key for downstream application including library preparations for whole genome sequencing (WGS) and the quantification of standards for quantitative PCR. Two commonly used technologies for nucleic acid quantification are based on spectrometry, such as NanoDrop, and fluorometry, such as Qubit. The DS-11+ Series spectrophotometer/fluorometer (DeNovix) is a UV spectrophotometry-based instrument and is a relatively new spectrophotometric method but has not yet been compared to established platforms. Here, we compared three DNA quantification platforms, including two UV spectrophotometry-based techniques (DeNovix and NanoDrop) and one fluorometry-based approach (Qubit). We used genomic prokaryotic DNA extracted from Streptococcus pneumoniae using a Roche DNA extraction kit. We also evaluated purity assessment and effect of a single freeze-thaw cycle. Spectrophotometry-based methods reported 3 to 4-fold higher mean DNA concentrations compared to Qubit, both before and after freezing. The ratio of DNA concentrations assessed by spectrophotometry on the one hand, and Qubit on the other hand, was function of the A260/280. In case DNA was pure (A260/280 between 1.7 and 2.0), the ratio DeNovix or Nanodrop vs. Qubit was close or equal to 2, while this ratio showed an incline for DNA with increasing A260/280 values > 2.0. The A260/280 and A260/230 purity ratios exhibited negligible variation across spectrophotometric methods and freezing conditions. The comparison of DNA concentrations from before and after freezing revealed no statistically significant disparities for each technique. DeNovix exhibited the highest Spearman correlation coefficient (0.999), followed by NanoDrop (0.81), and Qubit (0.77). In summary, there is no difference between DeNovix and NanoDrop in estimated gDNA concentrations of S. pneumoniae, and the spectrophotometry methods estimated close or equal to 2 times higher concentrations compared to Qubit for pure DNA.

Evaluation of DNA yield from various tissue and sampling sources for use in single nucleotide polymorphism panels

Genetics studies are used by wildlife managers and researchers to gain inference into a population of a species of interest. To gain these insights, microsatellites have been the primary method; however, there currently is a shift from microsatellites to single nucleotide polymorphisms (SNPs). With the different DNA requirements between microsatellites and SNPs, an investigation into which samples can provide adequate DNA yield is warranted. Using samples that were collected from previous genetic projects from regions in the USA from 2014 to 2021, we investigated the DNA yield of eight sample categories to gain insights into which provided adequate DNA to be used in ddRADseq or already developed high- or medium-density SNP panels. We found seven sample categories that met the DNA requirements for use in all three panels, and one sample category that did not meet any of the three panels requirements; however, DNA integrity was highly variable and not all sample categories that met panel DNA requirements could be considered high quality DNA. Additionally, we used linear random-effects models to determine which covariates would have the greatest influence on DNA yield. We determined that all covariates (tissue type, storage method, preservative, DNA quality, time until DNA extraction and time after DNA extraction) could influence DNA yield.

Quantitative Analysis of Genomic DNA Degradation of E. coli Using Automated Gel Electrophoresis under Various Levels of Microwave Exposure

The problem that this study addresses is to understand how microwave radiation is able to degrade genomic DNA of E. coli. In addition, a comparative study was made to evaluate the suitability of a high-throughput automated electrophoresis platform for quantifying the DNA degradation under microwave radiation. Overall, this study investigated the genomic DNA degradation of E. coli under microwave radiation using automated gel electrophoresis. To examine the viable organisms and degradation of genomic DNA under microwave exposure, we used three methods: (1) post-microwave exposure, where E. coli was enumerated using modified mTEC agar method using membrane filtration technique; (2) extracted genomic DNA of microwaved sample was quantified using the Qubit method; and (3) automated gel electrophoresis, the TapeStation 4200, was used to examine the bands of extracted DNA of microwaved samples. In addition, to examine the impacts of microwaves, E. coli colonies were isolated from a fecal sample (dairy cow manure), these colonies were grown overnight to prepare fresh E. coli culture, and this culture was exposed to microwave radiation for three durations: (1) 2 min; (2) 5 min; and (3) 8 min. In general, Qubit values (ng/µL) were proportional to the results of automated gel electrophoresis, TapeStation 4200, DNA integrity numbers (DINs). Samples from exposure studies (2 min, 5 min, and 8 min) showed no viable E. coli. Initial E. coli levels (at 0 min microwave exposure) were 5 × 108 CFU/mL, and the E. coli level was reduced to a non-detectable level within 2 min of microwave exposure. The relationships between Qubit and TapeStation measurements was linear, except for when the DNA level was lower than 2 ng/µL. In 8 min of microwave exposure, E. coli DNA integrity was reduced by 61.7%, and DNA concentration was reduced by 81.6%. The overall conclusion of this study is that microwave radiation had a significant impact on the genomic DNA of E. coli, and prolonged exposure of E. coli to microwaves can thus lead to a loss of genomic DNA integrity and DNA concentrations.

Review: Wildlife forensic genetics-Biological evidence, DNA markers, analytical approaches, and challenges

Wildlife-related crimes are the second most prevalent lawbreaking offense globally. This illicit trade encompasses hunting, breeding and trafficking. Besides diminishing many species and their habitats and ecosystems, hindering the economic development of local communities that depend on them, undermining the rule of law and financing terrorism, various cross-species transmissions (zoonoses) of pathogens, including COVID-19, can be attributed to wildlife crimes. Wildlife forensics applies interdisciplinary scientific analyses to support law enforcement in investigating wildlife crimes. Its main objectives are to identify the taxonomic species in question, determine if a crime has been committed, link a suspect to the crime and support the conviction and prosecution of the perpetrator. This article reviews wildlife crime and its implications, wildlife forensic science investigation, common forms of wildlife biological evidence, including DNA, wildlife DNA techniques and challenges in wildlife forensic genetics. The article also reviews the contributions of genetic markers such as short tandem repeat (STR) and mitochondrial DNA (mtDNA) markers, which provide the probative genetic data representing the bulk of DNA evidence for solving wildlife crime. This review provides an overview of wildlife DNA databases, which are critical for searching and matching forensic DNA profiles and sequences and establishing how frequent forensic DNA profiles and sequences are in a particular population or geographic region. As such, this review will contain an in-depth analysis of the current status of wildlife forensic genetics, and it will be of general interest to wildlife and conservation biologists, law enforcement officers, and academics interested in combating crimes against wildlife using animal forensic DNA methods.

Fluorescent Techniques for RNA Detection in Nanoparticles

The utilization of drug delivery systems, such as lipid nanoparticles and polyplexes/micelleplexes, has shown promise in intracellularly delivering nucleic acids for addressing various diseases. Accurate quantification of the nucleic acid cargo within nanoparticles is essential for the development of safe and effective nanomedicines. Currently, the RiboGreen and SYBR Gold methods are regarded as standard techniques for the precise quantification of RNA in lipid nanoparticles and polyplexes/micelleplexes, respectively. In this chapter, we present a comprehensive protocol for the precise evaluation of the encapsulation efficiency in such formulations using these methods. Additionally, we offer detailed instructions for nanoparticle preparation, characterization, and a comparative analysis of the sensitivity of both methods in quantifying unencapsulated siRNA.

Current technical advancements in plant epitranscriptomic studies

The growth and development of plants are the result of the interplay between the internal developmental programming and plant-environment interactions. Gene expression regulations in plants are made up of multi-level networks. In the past few years, many studies were carried out on co- and post-transcriptional RNA modifications, which, together with the RNA community, are collectively known as the "epitranscriptome." The epitranscriptomic machineries were identified and their functional impacts characterized in a broad range of physiological processes in diverse plant species. There is mounting evidence to suggest that the epitranscriptome provides an additional layer in the gene regulatory network for plant development and stress responses. In the present review, we summarized the epitranscriptomic modifications found so far in plants, including chemical modifications, RNA editing, and transcript isoforms. The various approaches to RNA modification detection were described, with special emphasis on the recent development and application potential of third-generation sequencing. The roles of epitranscriptomic changes in gene regulation during plant-environment interactions were discussed in case studies. This review aims to highlight the importance of epitranscriptomics in the study of gene regulatory networks in plants and to encourage multi-omics investigations using the recent technical advancements.

An Optimized Active Sampling Procedure for Aerobiological DNA Studies

The Earth's atmosphere plays a critical role in transporting and dispersing biological aerosols. Nevertheless, the amount of microbial biomass in suspension in the air is so low that it is extremely difficult to monitor the changes over time in these communities. Real-time genomic studies can provide a sensitive and rapid method for monitoring changes in the composition of bioaerosols. However, the low abundance of deoxyribose nucleic acid (DNA) and proteins in the atmosphere, which is of the order of the contamination produced by operators and instruments, poses a challenge for the sampling process and the analyte extraction. In this study, we designed an optimized, portable, closed bioaerosol sampler based on membrane filters using commercial off-the-shelf components, demonstrating its end-to-end operation. This sampler can operate autonomously outdoors for a prolonged time, capturing ambient bioaerosols and avoiding user contamination. We first performed a comparative analysis in a controlled environment to select the optimal active membrane filter based on its ability to capture and extract DNA. We have designed a bioaerosol chamber for this purpose and tested three commercial DNA extraction kits. The bioaerosol sampler was tested outdoors in a representative environment and run for 24 h at 150 L/min. Our methodology suggests that a 0.22-µm polyether sulfone (PES) membrane filter can recover up to 4 ng of DNA in this period, sufficient for genomic applications. This system, along with the robust extraction protocol, can be automated for continuous environmental monitoring to gain insights into the time evolution of microbial communities within the air.

Optimized Detection of Unknown MET Exon 14 Skipping Mutations in Routine Testing for Patients With Non-Small-Cell Lung Cancer

PURPOSE

MET exon 14 (METex14) skipping is an actionable biomarker in non-small-cell lung cancer. However, MET variants are highly complex and diverse, and not all variants lead to exon 14 skipping. Assessing the skipping effect of unknown variants is still a key issue in molecular diagnosis.

MATERIALS AND METHODS

We retrospectively collected MET variants around exon 14 from 4,233 patients with non-small-cell lung cancer who underwent next-generation sequencing testing using DNA, as well as two published data sets.

RESULTS

Among the 4,233 patients, 44 unique variants including 29 novel variants (65.9%) were discovered from 53 patients. Notably, 31 samples (58.5%) failed RNA verification. Using RNA verification, nine novel skipping variants and five nonskipping variants were confirmed. We further used SpliceAI with the delta score cutoff of 0.315 to aid the classification of novel variants (sensitivity = 98.88% and specificity = 100%). When applied to the reported variants, we also found three wrongly classified nonskipping variants. Finally, an optimized knowledge-based interpretation procedure for clinical routine was built according to the mutation type and location, and five more skipping mutations from the 13 unknown variants were determined, which improved the population determination rate to 0.92%.

CONCLUSION

This study discovered more METex14 skipping variants and optimized an innovative approach that could be adapted for the interpretation of infrequent or novel METex14 variants timely without experimental validation.

Transcriptomic and biochemical analyses of drought response mechanism in mung bean (Vignaradiata (L.) Wilczek) leaves

Drought is a major factor that limiting mung bean development. To clarify the molecular mechanism of mung bean in response to drought stress, 2 mung bean groups were established, the experimental group (drought-treated) and the control group (normal water management). With prominent difference of 2 groups in stomatal conductance, relative water content and phenotype, leaf samples were collected at 4 stages, and the physiological index of MDA, POD, chlorophyll, and soluble proteins were estimated. RNA-seq was used to obtain high quality data of samples, and differentially expressed genes were identified by DESeq2. With GO and KEGG analysis, DEGs were enriched into different classifications and pathways. WGCNA was used to detect the relationship between physiological traits and genes, and qPCR was performed to confirm the accuracy of the data. We obtained 169.49 Gb of clean data from 24 samples, and the Q30 of each date all exceeded 94%. In total, 8963 DEGs were identified at 4 stages between the control and treated samples, and the DEGs were involved in most biological processes. 1270 TFs screened from DEGs were clustered into 158 TF families, such as AP2, RLK-Pelle-DLSVA, and NAC TF families. Genes related to physiological traits were closely related to plant hormone signaling, carotenoid biosynthesis, chlorophyll metabolism, and protein processing. This paper provides a large amount of data for drought research in mung bean.

Procedures and potential pitfalls for constructing a bee-infecting RNA virus clone

Viruses are factors that can fluctuate insect populations, including honey bees. Most honey bee infecting viruses are single positive-stranded RNA viruses that may not specifically infect honey bees and can be hazardous to other pollinator insects. In addition, these viruses could synergize with other stressors to worsen the honey bee population decline. To identify the underlying detailed mechanisms, reversed genetic studies with infectious cDNA clones of the viruses are necessary. Moreover, an infectious cDNA clone can be applied to studies as an ideal virus isolate that consists of a single virus species with a uniform genotype. However, only a few infectious cDNA clones have been reported in honey bee studies since the first infectious cDNA clone was published four decades ago. This article discusses steps, rationales, and potential issues in bee-infecting RNA virus cloning. In addition, failed experiences of cloning a Deformed wing virus isolate that was phylogenetically identical to Kakugo virus were addressed. We hope the information provided in this article can facilitate further developments of reverse-genetic studies of bee-infecting viruses to clarify the roles of virus diseases in the current pollinator declines.

Performance of Spectrophotometric and Fluorometric DNA Quantification Methods

Accurate DNA quantification is a highly important method within molecular biology. Methods widely used to quantify DNA are UV spectrometry and fluorometry. In this research, seven different DNA samples and one blank (MilliQ ultrapure water) were quantified by three analysts using one spectrophotometric (i.e., a NanoDrop instrument) and three fluorometric (i.e., the AccuGreen High Sensitivity kit, the AccuClear Ultra High Sensitivity kit, and the Qubit dsDNA HS Assay kit) methods. An analysis of variance (ANOVA) scheme was used to determine the influence of the analyst, the method, and the combination of analyst and method, on DNA quantification. For most samples, the measured DNA concentration was close to or slightly above the concentration of 10 ng/μL as specified by the supplier. Results obtained by the three analysts were equal. However, it was found that, compared to the fluorometric kits, the used spectrophotometric instrument in the case of fish DNA samples tends to overestimate the DNA concentration. Therefore, if sufficient sample volume is available, a combination of a spectrophotometric and a fluorometric method is recommended for obtaining data on the purity and the dsDNA concentration of a sample.

A Comparison of Tissue Dissection Techniques for Diagnostic, Prognostic, and Theragnostic Analysis of Human Disease

Histopathology has historically been the critical technique for the diagnosis and treatment of human disease. Today, genomics, transcriptomics, and proteomics from specific cells, rather than bulk tissue, have become key to understanding underlying disease mechanisms and rendering useful diagnostic information. Extraction of desired analytes, i.e., nucleic acids or proteins, from easily accessible formalin-fixed paraffin-embedded tissues allows for clinically relevant activities, such as sequencing biomarker mutations or typing amyloidogenic proteins. Genetic profiling has become routine for cancers as varied as non-small cell lung cancer and prostatic carcinoma. The five main tissue dissection techniques that have been developed thus far include: bulk scraping, manual macrodissection, manual microdissection, laser-capture microdissection, and expression microdissection. In this review, we discuss the importance of tissue dissection in clinical practice and research, the basic methods, applications, as well as some advantages and disadvantages for each modality.