Full-length tRNAs lacking a functional CCA tail are selectively sorted into the lumen of extracellular vesicles.

Small extracellular vesicles (sEVs) are heterogenous lipid membrane particles typically less than 200 nm in size and secreted by most cell types either constitutively or upon activation signals. sEVs isolated from biofluids contain RNAs, including small non-coding RNAs (ncRNAs), that can be either encapsulated within the EV lumen or bound to the EV surface. EV-associated microRNAs (miRNAs) are, despite a relatively low abundance, extensively investigated for their selective incorporation and their role in cell-cell communication. In contrast, the sorting of highly-structured ncRNA species is understudied, mainly due to technical limitations of traditional small RNA sequencing protocols. Here, we adapted ALL-tRNAseq to profile the relative abundance of highly structured and potentially methylated small ncRNA species, including transfer RNAs (tRNAs), small nucleolar RNAs (snoRNAs), and Y RNAs in bulk EV preparations. We determined that full-length tRNAs, typically 75 to 90 nucleotides in length, were the dominant small ncRNA species (>60% of all reads in the 18-120 nucleotides size-range) in all cell culture-derived EVs, as well as in human plasma-derived EV samples, vastly outnumbering 21 nucleotides-long miRNAs. Nearly all EV-associated tRNAs were protected from external RNAse treatment, indicating a location within the EV lumen. Strikingly, the vast majority of luminal-sorted, full-length, nucleobase modification-containing EV-tRNA sequences, harbored a dysfunctional 3' CCA tail, 1 to 3 nucleotides truncated, rendering them incompetent for amino acid loading. In contrast, in non-EV associated extracellular particle fractions (NVEPs), tRNAs appeared almost exclusively fragmented or 'nicked' into tRNA-derived small RNAs (tsRNAs) with lengths between 18 to 35 nucleotides. We propose that in mammalian cells, tRNAs that lack a functional 3' CCA tail are selectively sorted into EVs and shuttled out of the producing cell, offering a new perspective into the physiological role of secreted EVs and luminal cargo-selection.

IsoSeek for unbiased and UMI-informed sequencing of miRNAs from low input samples at single-nucleotide resolution.

Besides canonical microRNAs (miRNAs), sequence-based variations called isomiRs have biological relevance and diagnostic potential; however, accurate calling of these post-transcriptional modifications is challenging, especially for low input samples. Here, we present IsoSeek, a sequencing protocol that reduces ligation and PCR amplification bias and improves the accuracy of miRNA detection in low input samples. We describe steps for using randomized adapters combined with unique molecular identifiers (UMI), library quantification, and sequencing, followed by detailed procedures for data processing and analysis. For complete details on the use and execution of this protocol, please refer to C. Gómez-Martín et al. (2023)1 and Van Eijndhoven et al. (2021).2.

NORMSEQ: a tool for evaluation, selection and visualization of RNA-Seq normalization methods.

RNA-sequencing has become one of the most used high-throughput approaches to gain knowledge about the expression of all different RNA subpopulations. However, technical artifacts, either introduced during library preparation and/or data analysis, can influence the detected RNA expression levels. A critical step, especially in large and low input datasets or studies, is data normalization, which aims at eliminating the variability in data that is not related to biology. Many normalization methods have been developed, each of them relying on different assumptions, making the selection of the appropriate normalization strategy key to preserve biological information. To address this, we developed NormSeq, a free web-server tool to systematically assess the performance of normalization methods in a given dataset. A key feature of NormSeq is the implementation of information gain to guide the selection of the best normalization method, which is crucial to eliminate or at least reduce non-biological variability. Altogether, NormSeq provides an easy-to-use platform to explore different aspects of gene expression data with a special focus on data normalization to help researchers, even without bioinformatics expertise, to obtain reliable biological inference from their data. NormSeq is freely available at: https://arn.ugr.es/normSeq.

ALL-tRNAseq enables robust tRNA profiling in tissue samples.

Transfer RNAs (tRNAs) are small adaptor RNAs essential for mRNA translation. Alterations in the cellular tRNA population can directly affect mRNA decoding rates and translational efficiency during cancer development and progression. To evaluate changes in the composition of the tRNA pool, multiple sequencing approaches have been developed to overcome reverse transcription blocks caused by the stable structures of these molecules and their numerous base modifications. However, it remains unclear whether current sequencing protocols faithfully capture tRNAs existing in cells or tissues. This is specifically challenging for clinical tissue samples that often present variable RNA qualities. For this reason, we developed ALL-tRNAseq, which combines the highly processive MarathonRT and RNA demethylation for the robust assessment of tRNA expression, together with a randomized adapter ligation strategy prior to reverse transcription to assess tRNA fragmentation levels in both cell lines and tissues. Incorporation of tRNA fragments not only informed on sample integrity but also significantly improved tRNA profiling of tissue samples. Our data showed that our profiling strategy effectively improves classification of oncogenic signatures in glioblastoma and diffuse large B-cell lymphoma tissues, particularly for samples presenting higher levels of RNA fragmentation, further highlighting the utility of ALL-tRNAseq for translational research.

sRNAbench and sRNAtoolbox 2022 update: accurate miRNA and sncRNA profiling for model and non-model organisms.

The NCBI Sequence Read Archive currently hosts microRNA sequencing data for over 800 different species, evidencing the existence of a broad taxonomic distribution in the field of small RNA research. Simultaneously, the number of samples per miRNA-seq study continues to increase resulting in a vast amount of data that requires accurate, fast and user-friendly analysis methods. Since the previous release of sRNAtoolbox in 2019, 55 000 sRNAbench jobs have been submitted which has motivated many improvements in its usability and the scope of the underlying annotation database. With this update, users can upload an unlimited number of samples or import them from Google Drive, Dropbox or URLs. Micro- and small RNA profiling can now be carried out using high-confidence Metazoan and plant specific databases, MirGeneDB and PmiREN respectively, together with genome assemblies and libraries from 441 Ensembl species. The new results page includes straightforward sample annotation to allow downstream differential expression analysis with sRNAde. Unassigned reads can also be explored by means of a new tool that performs mapping to microbial references, which can reveal contamination events or biologically meaningful findings as we describe in the example. sRNAtoolbox is available at: https://arn.ugr.es/srnatoolbox/.

DPHL: A DIA Pan-human Protein Mass Spectrometry Library for Robust Biomarker Discovery.

To address the increasing need for detecting and validating protein biomarkers in clinical specimens, mass spectrometry (MS)-based targeted proteomic techniques, including the selected reaction monitoring (SRM), parallel reaction monitoring (PRM), and massively parallel data-independent acquisition (DIA), have been developed. For optimal performance, they require the fragment ion spectra of targeted peptides as prior knowledge. In this report, we describe a MS pipeline and spectral resource to support targeted proteomics studies for human tissue samples. To build the spectral resource, we integrated common open-source MS computational tools to assemble a freely accessible computational workflow based on Docker. We then applied the workflow to generate DPHL, a comprehensive DIA pan-human library, from 1096 data-dependent acquisition (DDA) MS raw files for 16 types of cancer samples. This extensive spectral resource was then applied to a proteomic study of 17 prostate cancer (PCa) patients. Thereafter, PRM validation was applied to a larger study of 57 PCa patients and the differential expression of three proteins in prostate tumor was validated. As a second application, the DPHL spectral resource was applied to a study consisting of plasma samples from 19 diffuse large B cell lymphoma (DLBCL) patients and 18 healthy control subjects. Differentially expressed proteins between DLBCL patients and healthy control subjects were detected by DIA-MS and confirmed by PRM. These data demonstrate that the DPHL supports DIA and PRM MS pipelines for robust protein biomarker discovery. DPHL is freely accessible at https://www.iprox.org/page/project.html?id=IPX0001400000.

Vesicle-bound EBV-BART13-3p miRNA in circulation distinguishes nasopharyngeal from other head and neck cancer and asymptomatic EBV-infections.

Cell-free microRNA (miRNA) in biofluids released by tumors in either protein or vesicle-bound form, represent promising minimally-invasive cancer biomarkers. However, a highly abundant non-tumor background in human plasma and serum complicates the discovery and detection of tumor-selective circulating miRNAs. We performed small RNA sequencing on serum and plasma RNA from Nasopharyngeal Carcinoma (NPC) patients. Collectively, Epstein Barr virus-encoded miRNAs, more so than endogenous miRNAs, signify presence of NPC. However, RNAseq-based EBV miRNA profiles differ between NPC patients, suggesting inter-tumor heterogeneity or divergent secretory characteristics. We determined with sensitive qRT-PCR assays that EBV miRNAs BART7-3p, BART9-3p and BART13-3p are actively secreted by C666.1 NPC cells bound to extracellular vesicles (EVs) and soluble ribonucleoprotein complexes. Importantly, these miRNAs are expressed in all primary NPC tumor biopsies and readily detected in nasopharyngeal brushings from both early and late-stage NPC patients. Increased levels of BART7-3p, BART9-3p and particularly BART13-3p, distinguish NPC patient sera from healthy controls. Receiver operating characteristic curve analysis using sera from endemic NPC patients, other head and neck cancers and individuals with asymptomatic EBV-infections reveals a superior diagnostic performance of EBV miRNAs over anti-EBNA1 IgA serology and EBV-DNA load (AUC 0.87-0.96 vs 0.86 and 0.66 respectively). The high specificity of circulating EBV-BART13-3p (97%) for NPC detection is in agreement with active secretion from NPC tumor cells. We conclude EV-bound BART13-3p in circulation is a promising, NPC-selective, biomarker that should be considered as part of a screening strategy to identify NPC in endemic regions.

A Multimodal Imaging Approach for Longitudinal Evaluation of Bladder Tumor Development in an Orthotopic Murine Model.

Bladder cancer is the fourth most common malignancy amongst men in Western industrialized countries with an initial response rate of 70% for the non-muscle invasive type, and improving therapy efficacy is highly needed. For this, an appropriate, reliable animal model is essential to gain insight into mechanisms of tumor growth for use in response monitoring of (new) agents. Several animal models have been described in previous studies, but so far success has been hampered due to the absence of imaging methods to follow tumor growth non-invasively over time. Recent developments of multimodal imaging methods for use in animal research have substantially strengthened these options of in vivo visualization of tumor growth. In the present study, a multimodal imaging approach was addressed to investigate bladder tumor proliferation longitudinally. The complementary abilities of Bioluminescence, High Resolution Ultrasound and Photo-acoustic Imaging permit a better understanding of bladder tumor development. Hybrid imaging modalities allow the integration of individual strengths to enable sensitive and improved quantification and understanding of tumor biology, and ultimately, can aid in the discovery and development of new therapeutics.