Capturing the 'ome': the expanding molecular toolbox for RNA and DNA library construction

RNA-based detection of genetically modified plants via current-voltage characteristic measurement

The widespread adoption of genetically modified (GM) crops has escalated concerns about their safety and ethical implications, underscoring the need for efficient GM crop detection methods. Conventional detection methods, such as polymerase chain reaction, can be costly, lab-bound, and time-consuming. To overcome these challenges, we have developed RapiSense, a cost-effective, portable, and sensitive biosensor platform. This sensor generates a measurable voltage shift (0.1-1 V) in the system's current-voltage characteristics, triggered by an increase in membrane's negative charge upon hybridization of DNA/RNA targets with a specific DNA probe. Probes designed to identify the herbicide resistance gene hygromycin phosphotransferase show a detection range from ∼1 nM to ∼10 μM and can discriminate between complementary, non-specific, and mismatched nucleotide targets. The incorporation of a small membrane sensor to detect fragmented RNA samples substantially improve the platform's sensitivity. In this study, RapiSense has been effectively used to detect specific DNA and fragmented RNA in transgenic variants of Arabidopsis, sweet potato, and rice, showcasing its potential for rapid, on-site GM crop screening.

Cytochrome gene expression shifts in Geobacter sulfurreducens to maximize energy conservation in response to changes in redox conditions

Previous studies have identified that Geobacter sulfurreducens has three different electron transfer pathways for respiration, and it switches between these pathways to adapt to the redox potential of its electron acceptor. However, only a small fraction of the electron carriers from each pathway have been identified. In this study, we combined electrochemical and gene expression data to identify electron carriers in the inner membrane, periplasm, outer membrane, and exterior of the cell that may be induced by the use of the three different electron transfer pathways. Cyclic voltammetry was performed on thin biofilms grown on anodes poised at different redox potentials, providing a quantitative assessment of the relative use of three electron-transfer pathways in each condition (catalytic midpoint potentials (EKAs) of -0.227 V [Low], -0.15 V [Medium], -0.1 V [High] vs. SHE). Transcriptomic analyses as a function of electrochemical signals or fumarate utilization showed differential induction in inner membrane (Medium: cbcL), periplasmic (Low: ppcB/ppcE, Medium: ppcA), outer membrane (Low: extA/extC, Medium: extJ/extK, Fumarate: extF/extG), and extracellular (Medium: omcZ, High/Fumarate: omcS/omcT) cytochromes, suggesting the pathway signals are associated with complex transcriptomic responses in genes across the electron transfer pathway. Our method combining electrochemical modeling and transcriptomics could be adapted to better understand electron transport in other electroactive organisms with complex metabolisms.

The peptide woods are lovely, dark and deep: Hunting for novel cancer antigens

Harnessing the patient's immune system to control a tumor is a proven avenue for cancer therapy. T cell therapies as well as therapeutic vaccines, which target specific antigens of interest, are being explored as treatments in conjunction with immune checkpoint blockade. For these therapies, selecting the best suited antigens is crucial. Most of the focus has thus far been on neoantigens that arise from tumor-specific somatic mutations. Although there is clear evidence that T-cell responses against mutated neoantigens are protective, the large majority of these mutations are not immunogenic. In addition, most somatic mutations are unique to each individual patient and their targeting requires the development of individualized approaches. Therefore, novel antigen types are needed to broaden the scope of such treatments. We review high throughput approaches for discovering novel tumor antigens and some of the key challenges associated with their detection, and discuss considerations when selecting tumor antigens to target in the clinic.

Construction of an experimental study and addition of adapter sequences using HiDi DNA polymerase for improving DNA normalization methods relevant to novel gene discovery

Microorganisms in the environment can be distinguished into dominant and rare microbial species based on their genes. It is difficult to obtain genetic information derived from rare microbial species (rare genes) because of the differences in relative abundance. DNA normalization is an approach that is used to obtain genetic information derived from rare microbial species from an environmental sample. This method involves the addition of adapter sequences for the amplification, denaturation, and reassociation of the DNA fragments and single-stranded DNA (ssDNA)/double-stranded DNA (dsDNA) separation. In this method, the amount of a high-copy-number of DNA fragments and a low-copy-number of DNA fragments can be equalized. Improvements in this technique are expected to provide novel genetic information or genes in rare microbial species. However, few model experimental systems have been reported to validate the DNA normalization techniques. This study is aimed to improve the DNA normalization technique used to obtain genetic information of rare genes from rare microbial species. An experimental study was constructed with two antibiotic resistance genes, whose copy numbers differed up to a million-fold. Both genes were mixed and the mixture of DNA fragments, of high- and low-copy-number, containing these genes was normalized by separating ssDNA/dsDNA fragments using hydroxyapatite. Normalized DNA fragments were introduced into Escherichia coli and DNA normalization was evaluated by counting colonies. Moreover, we improved the method to amplify a low-copy-number of DNA fragments by the addition of adapter sequences to DNA fragments using HiDi DNA polymerase to increase the efficiency of DNA normalization. This normalization method was achieved with a 100,000-fold difference. These methods allowed for quantitative evaluation of the DNA normalization efficiency. The experimental data and methods obtained in this study are expected to improve the DNA normalization efficiency to obtain novel genetic information or genes.

Translation complex stabilization on messenger RNA and footprint profiling to study the RNA responses and dynamics of protein biosynthesis in the cells

During protein biosynthesis, ribosomes bind to messenger (m)RNA, locate its protein-coding information, and translate the nucleotide triplets sequentially as codons into the corresponding sequence of amino acids, forming proteins. Non-coding mRNA features, such as 5' and 3' untranslated regions (UTRs), start sites or stop codons of different efficiency, stretches of slower or faster code and nascent polypeptide interactions can alter the translation rates transcript-wise. Most of the homeostatic and signal response pathways of the cells converge on individual mRNA control, as well as alter the global translation output. Among the multitude of approaches to study translational control, one of the most powerful is to infer the locations of translational complexes on mRNA based on the mRNA fragments protected by these complexes from endonucleolytic hydrolysis, or footprints. Translation complex profiling by high-throughput sequencing of the footprints allows to quantify the transcript-wise, as well as global, alterations of translation, and uncover the underlying control mechanisms by attributing footprint locations and sizes to different configurations of the translational complexes. The accuracy of all footprint profiling approaches critically depends on the fidelity of footprint generation and many methods have emerged to preserve certain or multiple configurations of the translational complexes, often in challenging biological material. In this review, a systematic summary of approaches to stabilize translational complexes on mRNA for footprinting is presented and major findings are discussed. Future directions of translation footprint profiling are outlined, focusing on the fidelity and accuracy of inference of the native in vivo translation complex distribution on mRNA.

A Primer on the Analysis of High-Throughput Sequencing Data for Detection of Plant Viruses

High-throughput sequencing (HTS) technologies have become indispensable tools assisting plant virus diagnostics and research thanks to their ability to detect any plant virus in a sample without prior knowledge. As HTS technologies are heavily relying on bioinformatics analysis of the huge amount of generated sequences, it is of utmost importance that researchers can rely on efficient and reliable bioinformatic tools and can understand the principles, advantages, and disadvantages of the tools used. Here, we present a critical overview of the steps involved in HTS as employed for plant virus detection and virome characterization. We start from sample preparation and nucleic acid extraction as appropriate to the chosen HTS strategy, which is followed by basic data analysis requirements, an extensive overview of the in-depth data processing options, and taxonomic classification of viral sequences detected. By presenting the bioinformatic tools and a detailed overview of the consecutive steps that can be used to implement a well-structured HTS data analysis in an easy and accessible way, this paper is targeted at both beginners and expert scientists engaging in HTS plant virome projects.

Navigating the Pandemic Response Life Cycle: Molecular Diagnostics and Immunoassays in the Context of COVID-19 Management

Coronavirus disease 2019 (COVID-19) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). To counter COVID-19 spreading, an infrastructure to provide rapid and thorough molecular diagnostics and serology testing is the cornerstone of outbreak and pandemic management. We hereby review the clinical insights with regard to using molecular tests and immunoassays in the context of COVID-19 management life cycle: the preventive phase, the preparedness phase, the response phase and the recovery phase. The spatial and temporal distribution of viral RNA, antigens and antibodies during human infection is summarized to provide a biological foundation for accurate detection of the disease. We shared the lessons learned and the obstacles encountered during real world high-volume screening programs. Clinical needs are discussed to identify existing technology gaps in these tests. Leverage technologies, such as engineered polymerases, isothermal amplification, and direct amplification from complex matrices may improve the productivity of current infrastructure, while emerging technologies like CRISPR diagnostics, visual end point detection, and PCR free methods for nucleic acid sensing may lead to at-home tests. The lessons learned, and innovations spurred from the COVID-19 pandemic could upgrade our global public health infrastructure to better combat potential outbreaks in the future.

Parallel analysis of miRNAs and mRNAs suggests distinct regulatory networks in Crassostrea gigas infected by Ostreid herpesvirus 1

Background

Since 2008, the aquaculture production of Crassostrea gigas was heavily affected by mass mortalities associated to Ostreid herpesvirus 1 (OsHV-1) microvariants worldwide. Transcriptomic studies revealed the major antiviral pathways of the oyster immune response while other findings suggested that also small non-coding RNAs (sncRNA) such as microRNAs might act as key regulators of the oyster response against OsHV-1. To explore the explicit connection between small non-coding and protein-coding transcripts, we performed paired whole transcriptome analysis of sncRNA and messenger RNA (mRNA) in six oysters selected for different intensities of OsHV-1 infection.

Results

The mRNA profiles of the naturally infected oysters were mostly governed by the transcriptional activity of OsHV-1, with several differentially expressed genes mapping to the interferon, toll, apoptosis, and pro-PO pathways. In contrast, miRNA profiles suggested more complex regulatory mechanisms, with 15 differentially expressed miRNAs (DE-miRNA) pointing to a possible modulation of the host response during OsHV-1 infection. We predicted 68 interactions between DE-miRNAs and oyster 3′-UTRs, but only few of them involved antiviral genes. The sncRNA reads assigned to OsHV-1 rather resembled mRNA degradation products, suggesting the absence of genuine viral miRNAs.

Conclusions

We provided data describing the miRNAome during OsHV-1 infection in C. gigas. This information can be used to understand the role of miRNAs in healthy and diseased oysters, to identify new targets for functional studies and, eventually to disentangle cause and effect relationships during viral infections in marine mollusks.

A smart polymer for sequence-selective binding, pulldown, and release of DNA targets

Selective isolation of DNA is crucial for applications in biology, bionanotechnology, clinical diagnostics and forensics. We herein report a smart methanol-responsive polymer (MeRPy) that can be programmed to bind and separate single- as well as double-stranded DNA targets. Captured targets are quickly isolated and released back into solution by denaturation (sequence-agnostic) or toehold-mediated strand displacement (sequence-selective). The latter mode allows 99.8% efficient removal of unwanted sequences and 79% recovery of highly pure target sequences. We applied MeRPy for the depletion of insulin, glucagon, and transthyretin cDNA from clinical next-generation sequencing (NGS) libraries. This step improved the data quality for low-abundance transcripts in expression profiles of pancreatic tissues. Its low cost, scalability, high stability and ease of use make MeRPy suitable for diverse applications in research and clinical laboratories, including enhancement of NGS libraries, extraction of DNA from biological samples, preparative-scale DNA isolations, and sorting of DNA-labeled non-nucleic acid targets.

Krieg et al. describe a methanol responsive polymer that can capture complementary DNA using grafted oligonucleotides. They successfully demonstrate its efficacy with simultaneous and sequence-specific isolation of three target genes (cDNA) from clinical NGS libraries with high efficiency. This method is fast, effective, scalable, modular, and versatile.

All-in-one sequencing: an improved library preparation method for cost-effective and high-throughput next-generation sequencing

BACKGROUND

Next generation sequencing (NGS) has been widely used in biological research, due to its rapid decrease in cost and increasing ability to generate data. However, while the sequence generation step has seen many improvements over time, the library preparation step has not, resulting in low-efficiency library preparation methods, especially for the most time-consuming and labor-intensive steps: size-selection and quantification. Consequently, there can be bottlenecks in projects with large sample cohorts.

RESULTS

We have described the all-in-one sequencing (AIO-seq) method, where instead of performing size-selection and quantification for samples individually, one sample one tube, up to 116 samples are pooled and analyzed in a single tube, 'All-In-One'. The AIO-seq method pools libraries based on the samples' expected data yields and the calculated concentrations of the size selected regions (target region), which can easily be obtained with the Agilent 2100 Bioanalyzer and Qubit Fluorometer. AIO-seq was applied to whole genome sequencing and RNA-seq libraries successfully, and it is envisaged that it could be applied to any type of NGS library, such as chromatin immunoprecipitation coupled with massively parallel sequencing, assays for transposase-accessible chromatin with high-throughput sequencing, and high-throughput chromosome conformation capture. We also demonstrated that for genetic population samples with low coverage sequences, like recombinant inbred lines (RIL), AIO-seq could be further simplified, by mixing the libraries immediately after PCR, without calculating the target region concentrations.

CONCLUSIONS

The AIO-seq method is thus labor saving and cost effective, and suitable for projects with large sample cohorts, like those used in plant breeding or population genetics research.

Molecular sampling at logarithmic rates for next-generation sequencing

Next-generation sequencing is a cutting edge technology, but to quantify a dynamic range of abundances for different RNA or DNA species requires increasing sampling depth to levels that can be prohibitively expensive due to physical limits on molecular throughput of sequencers. To overcome this problem, we introduce a new general sampling theory which uses biophysical principles to functionally encode the abundance of a species before sampling, SeQUential depletIon and enriCHment (SQUICH). In theory and simulation, SQUICH enables sampling at a logarithmic rate to achieve the same precision as attained with conventional sequencing. A simple proof of principle experimental implementation of SQUICH in a controlled complex system of ~262,000 oligonucleotides already reduces sequencing depth by a factor of 10. SQUICH lays the groundwork for a general solution to a fundamental problem in molecular sampling and enables a new generation of efficient, precise molecular measurement at logarithmic or better sampling depth.

Next-generation sequencing enables measurement of chemical and biological signals at high throughput and falling cost. Conventional sequencing uses a process called simple random sampling which requires increasing the number of samples to be able to detect a signal precisely. We have developed a new way to sample, by first performing computations with DNA and then only sampling the output of the computations, requiring a much smaller number of samples to estimate at the same precision as without this method. In common applications such as RNA sequencing or biomarker detection, the method requires 100–1000 fold less sampling, and so reduces cost by 100–1000 fold. This means that the scale and precision of molecular measurement can be dramatically increased, enabling new efficiency in detecting biological molecules.

Phytovirome Analysis of Wild Plant Populations: Comparison of Double-Stranded RNA and Virion-Associated Nucleic Acid Metagenomic Approaches

Metagenomic studies have indicated that the diversity of plant viruses was until recently far underestimated. As important components of ecosystems, there is a need to explore the diversity and richness of the viruses associated with plant populations and to understand the drivers shaping their diversity in space and time. Two viral sequence enrichment approaches, double-stranded RNA (dsRNA) and virion-associated nucleic acids (VANA), have been used and compared here for the description of the virome of complex plant pools representative of the most prevalent plant species in unmanaged and cultivated ecosystems. A novel bioinformatics strategy was used to assess viral richness not only at the family level but also by determining operational taxonomic units (OTU) following the clustering of conserved viral domains. A large viral diversity dominated by novel dsRNA viruses was detected in all sites, while a large between-site variability limited the ability to draw a clear conclusion on the impact of cultivation. A trend for a higher diversity of dsRNA viruses was nevertheless detected in unmanaged sites (118 versus 77 unique OTUs). The dsRNA-based approach consistently revealed a broader and more comprehensive diversity for RNA viruses than the VANA approach, whatever the assessment criterion. In addition, dissimilarity analyses indicated both approaches to be largely reproducible but not necessarily convergent. These findings illustrate features of phytoviromes in various ecosystems and a novel strategy for precise virus richness estimation. These results allow us to reason methodological choices in phytovirome studies and likely in other virome studies where RNA viruses are the focal taxa.IMPORTANCE There are today significant knowledge gaps on phytovirus populations and on the drivers impacting them but also on the comparative performance-methodological approaches for their study. We used and compared two viral sequence enrichment approaches, double-stranded RNAs (dsRNA) and virion-associated nucleic acids (VANA), for phytovirome description in complex pools representative of the most prevalent plant species in unmanaged and cultivated ecosystems. Viral richness was assessed by determining operational taxonomic units (OTU) following the clustering of conserved viral domains. There is some limited evidence of an impact of cultivation on viral populations. These results provide data allowing us to reason the methodological choices in virome studies. For researchers primarily interested in RNA viruses, the dsRNA approach is recommended because it consistently provided a more comprehensive description of the analyzed phytoviromes, but it understandably underrepresented DNA viruses and bacteriophages.

Deconvolution of nucleic-acid length distributions: a gel electrophoresis analysis tool and applications

Next-generation DNA-sequencing (NGS) technologies, which are designed to streamline the acquisition of massive amounts of sequencing data, are nonetheless dependent on various preparative steps to generate DNA fragments of required concentration, purity and average size (molecular weight). Current automated electrophoresis systems for DNA- and RNA-sample quality control, such as Agilent's Bioanalyzer® and TapeStation® products, are costly to acquire and use; they also provide limited information for samples having broad size distributions. Here, we describe a software tool that helps determine the size distribution of DNA fragments in an NGS library, or other DNA sample, based on gel-electrophoretic line profiles. The software, developed as an ImageJ plug-in, allows for straightforward processing of gel images, including lane selection and fitting of univariate functions to intensity distributions. The user selects the option of fitting either discrete profiles in cases where discrete gel bands are visible or continuous profiles, having multiple bands buried under a single broad peak. The method requires only modest imaging capabilities and is a cost-effective, rigorous alternative characterization method to augment existing techniques for library quality control.

The Impact of cDNA Normalization on Long-Read Sequencing of a Complex Transcriptome

Normalization of cDNA is widely used to improve the coverage of rare transcripts in analysis of transcriptomes employing next-generation sequencing. Recently, long-read technology has been emerging as a powerful tool for sequencing and construction of transcriptomes, especially for complex genomes containing highly similar transcripts and transcript-spliced isoforms. Here, we analyzed the transcriptome of sugarcane, a highly polyploidy plant genome, by PacBio isoform sequencing (Iso-Seq) of two different cDNA library preparations, with and without a normalization step. The results demonstrated that, while the two libraries included many of the same transcripts, many longer transcripts were removed, and many new generally shorter transcripts were detected by normalization. For the same input cDNA and data yield, the normalized library recovered more total transcript isoforms and number of predicted gene families and orthologous groups, resulting in a higher representation for the sugarcane transcriptome, compared to the non-normalized library. The non-normalized library, on the other hand, included a wider transcript length range with more longer transcripts above ∼1.25 kb and more transcript isoforms per gene family and gene ontology terms per transcript. A large proportion of the unique transcripts comprising ∼52% of the normalized library were expressed at a lower level than the unique transcripts from the non-normalized library, across three tissue types tested including leaf, stalk, and root. About 83% of the total 5,348 predicted long noncoding transcripts was derived from the normalized library, of which ∼80% was derived from the lowly expressed fraction. Functional annotation of the unique transcripts suggested that each library enriched different functional transcript fractions. This demonstrated the complementation of the two approaches in obtaining a complete transcriptome of a complex genome at the sequencing depth used in this study.