High-throughput simultaneous analysis of RNA, protein, and lipid biomarkers in heterogeneous tissue samples

Preserving plant samples from remote locations for detection of RNA and DNA viruses

Viral diseases in plants have a significant impact on agricultural productivity. Effective detection is needed to facilitate accurate diagnosis and characterization of virus infections essential for crop protection and disease management. For sensitive polymerase chain reaction (PCR)-based methods, it is important to preserve the integrity of nucleic acids in plant tissue samples. This is especially critical when samples are collected from isolated areas, regions distant from a laboratory, or in developing countries that lack appropriate facilities or equipment for diagnostic analyses. RNAlater^® provides effective, reliable sample storage by stabilizing both RNA and DNA in plant tissue samples. Our work indicated that total RNA or DNA extracted from virus-infected leaf samples preserved in RNAlater^® was suitable for reverse transcription polymerase chain reaction (RT-PCR), PCR, Sanger sequencing, high-throughput sequencing (HTS), and enzyme-linked immunosorbent assay (ELISA)-based diagnostic analyses. We demonstrated the effectiveness of this technology using leaf tissue samples from plants with virus symptoms grown in farmers’ fields in Bangladesh. The results revealed that RNAlater^® technology was effective for detection and characterization of viruses from samples collected from remote areas and stored for extended periods. Adoption of this technology by developing countries with limited laboratory facilities could greatly increase their capacity to detect and diagnose viral infections in crop plants using modern analytical techniques.

Simultaneous lipidomic and transcriptomic profiling in mouse brain punches of acute epileptic seizure model compared to controls

In this study, we report the development of a dual extraction protocol for RNA and lipids, including phospholipids, endocannabinoids, and arachidonic acid, at high spatial resolution, e.g., brain punches obtained from whole frozen brains corresponding to four brain subregions: dorsal hippocampus, ventral hippocampus, basolateral amygdala, and hypothalamus. This extraction method combined with LC/multiple reaction monitoring for lipid quantifi-cation and quantitative PCR for RNA investigation allows lipidomic and transcriptomic profiling from submilligram amounts of tissue, thus benefiting the time and animal costs for analysis and the data reliability due to prevention of biological variability between animal batches and/or tissue heterogeneity, as compared with profiling in distinct animal batches. Moreover, the method allows a higher extraction efficiency and integrity preservation for RNA, while allowing concurrently quantitative analysis of low and high abundant lipids. The method was applied for brain punches obtained 1 h after kainic acid-induced epileptic seizures in mice (n = 10) compared with controls (n = 10), and enabled the provision of valuable new insights into the subregional lipid and RNA changes with epilepsy, highlighting its potential as a new viable tool in quantitative neurobiology.

Automated serial extraction of DNA and RNA from biobanked tissue specimens

BACKGROUND

With increasing biobanking of biological samples, methods for large scale extraction of nucleic acids are in demand. The lack of such techniques designed for extraction from tissues results in a bottleneck in downstream genetic analyses, particularly in the field of cancer research. We have developed an automated procedure for tissue homogenization and extraction of DNA and RNA into separate fractions from the same frozen tissue specimen. A purpose developed magnetic bead based technology to serially extract both DNA and RNA from tissues was automated on a Tecan Freedom Evo robotic workstation.

RESULTS

864 fresh-frozen human normal and tumor tissue samples from breast and colon were serially extracted in batches of 96 samples. Yields and quality of DNA and RNA were determined. The DNA was evaluated in several downstream analyses, and the stability of RNA was determined after 9 months of storage. The extracted DNA performed consistently well in processes including PCR-based STR analysis, HaloPlex selection and deep sequencing on an Illumina platform, and gene copy number analysis using microarrays. The RNA has performed well in RT-PCR analyses and maintains integrity upon storage.

CONCLUSIONS

The technology described here enables the processing of many tissue samples simultaneously with a high quality product and a time and cost reduction for the user. This reduces the sample preparation bottleneck in cancer research. The open automation format also enables integration with upstream and downstream devices for automated sample quantitation or storage.