Construction of a 3D Quantum Dot Nanoassembly with Two-Step FRET for One-Step Sensing of Human Telomerase RNA in Breast Cancer Cells and Tissues.

Telomerase is an important biomarker for early diagnosis of cancers, but current telomerase assays usually rely on measuring the extension products of telomerase substrates, which increases the assay complexity. More evidence indicates that human telomerase RNA (hTR), as a core component of telomerase, is positively correlated with the telomerase activity. Herein, we demonstrate the development of a duplex-specific nuclease (DSN)-propelled 3D quantum dot (QD) nanoassembly with two-step Föster resonance energy transfer (FRET) for the one-step sensing of hTR in breast cancer cells and tissues. This assay involves only one hairpin probe modified with a Cy5 at the sixth base from the 5'-biotin end and a BHQ2 at the 3'-terminus, which integrates three functions of target recognition, target recycling amplification, and signal readout. The anchoring of the hairpin probe on the 605QD surface results in the formation of a 3D 605QD-Cy5-probe-BHQ2 nanoassembly in which two-step FRET occurs among the 605QD, Cy5, and BHQ2 quencher. Notably, the formation of 605QD-Cy5-probe-BHQ2 nanoassembly facilitates the reduction of background signal and the increase of signal-to-background ratio due to its dense, highly oriented nucleic acid shell-induced steric hindrance effect. This assay can achieve one-step and rapid detection of hTR with a detection limit of 2.10 fM, which is the simplest and most rapid hTR assay reported so far. Moreover, this assay can efficiently distinguish single-base mismatched sequences, and it can discriminate the hTR level between breast cancer patients and healthy donors with a high accuracy of 100%, with great prospects for early diagnosis of cancers.

Discrimination of Genetic Biomarkers of Disease through Machine-Learning-Based Hypothesis Testing of Direct SERS Spectra of DNA and RNA.

Cancer is globally a leading cause of death that would benefit from diagnostic approaches detecting it in its early stages. However, despite much research and investment, cancer early diagnosis is still underdeveloped. Owing to its high sensitivity, surface-enhanced Raman spectroscopy (SERS)-based detection of biomarkers has attracted growing interest in this area. Oligonucleotides are an important type of genetic biomarkers as their alterations can be linked to the disease prior to symptom onset. We propose a machine-learning (ML)-enabled framework to analyze complex direct SERS spectra of short, single-stranded DNA and RNA targets to identify relevant mutations occurring in genetic biomarkers, which are key disease indicators. First, by employing ad hoc-synthesized colloidal silver nanoparticles as SERS substrates, we analyze single-base mutations in ssDNA and RNA sequences using a direct SERS-sensing approach. Then, an ML-based hypothesis test is proposed to identify these changes and differentiate the mutated sequences from the corresponding native ones. Rooted in "functional data analysis," this ML approach fully leverages the rich information and dependencies within SERS spectral data for improved modeling and detection capability. Tested on a large set of DNA and RNA SERS data, including from miR-21 (a known cancer miRNA biomarker), our approach is shown to accurately differentiate SERS spectra obtained from different oligonucleotides, outperforming various data-driven methods across several performance metrics, including accuracy, sensitivity, specificity, and F1-scores. Hence, this work represents a step forward in the development of the combined use of SERS and ML as effective methods for disease diagnosis with real applicability in the clinic.

Codetection of Proteins and RNAs on Extracellular Vesicles for Pancreatic Cancer Early Diagnosis.

Tumor-derived extracellular vesicles (EVs) carry tumor-specific proteins and RNAs, thus becoming prevalent targets for early cancer diagnosis. However, low expression of EV cargos and insufficient diagnostic power of individual biomarkers hindered EVs application in clinical practice. Herein, we propose a multiplex Codetection platform of proteins and RNAs (Co-PAR) for EVs. Co-PAR adopted a pair of antibody-DNA probes to recognize the same target protein, which in turn formed a double-stranded DNA. Thus, the target protein could be quantified by detecting the double-stranded DNA via qPCR. Meanwhile, qRT-PCR simultaneously quantified the target RNAs. Thus, with a regular qPCR instrument, Co-PAR enabled the codetection of multiplex proteins and RNAs, with the sensitivity of 102 EVs/µL (targeting CD63) and 1 EV/µL (targeting snRNA U6). We analyzed the coexpressions of three protein markers (CD63, GPC-1, HER2) and three RNA markers (snRNA U6, GPC-1 mRNA, miR-10b) on EVs from three pancreatic cell lines and 30 human plasma samples using Co-PAR. The diagnostic accuracy of the 6-biomarker combination reached 92.9%, which was at least 6.2% higher than that of 3-biomarker combinations and at least 13.5% higher than that of 6 single biomarkers. Co-PAR, as a multiparameter detection platform for EVs, has great potential in early disease diagnosis.

Analytical validation of HER2DX genomic test for early-stage HER2-positive breast cancer.

BACKGROUND: HER2DX, a multianalyte genomic test, has been clinically validated to predict breast cancer recurrence risk (relapse risk score), the probability of achieving pathological complete response post-neoadjuvant therapy (pCR likelihood score), and individual ERBB2 messenger RNA (mRNA) expression levels in patients with early-stage human epidermal growth factor receptor 2 (HER2)-positive breast cancer. This study delves into the comprehensive analysis of HER2DX's analytical performance. MATERIALS AND METHODS: Precision and reproducibility of HER2DX risk, pCR, and ERBB2 mRNA scores were assessed within and between laboratories using formalin-fixed paraffin-embedded (FFPE) tumor tissues and purified RNA. Robustness was appraised by analyzing the impact of tumor cell content and protocol variations including different instruments, reagent lots, and different RNA extraction kits. Variability was evaluated across intratumor biopsies and genomic platforms [RNA sequencing (RNAseq) versus nCounter], and according to protocol variations. RESULTS: Precision analysis of 10 FFPE tumor samples yielded a maximal standard error of 0.94 across HER2DX scores (1-99 scale). High reproducibility of HER2DX scores across 29 FFPE tumors and 20 RNAs between laboratories was evident (correlation coefficients >0.98). The probability of identifying score differences >5 units was ≤5.2%. No significant variability emerged based on platform instruments, reagent lots, RNA extraction kits, or TagSet thaw/freeze cycles. Moreover, HER2DX displayed robustness at low tumor cell content (10%). Intratumor variability across 212 biopsies (106 tumors) was <4.0%. Concordance between HER2DX scores from 30 RNAs on RNAseq and nCounter platforms exceeded 90.0% (Cohen's κ coefficients >0.80). CONCLUSIONS: The HER2DX assay is highly reproducible and robust for the quantification of recurrence risk, pCR likelihood, and ERBB2 mRNA expression in early-stage HER2-positive breast cancer.

Enhancing Specific Fluorescence In Situ Hybridization with Quantum Dots for Single-Molecule RNA Imaging in Formalin-Fixed Paraffin-Embedded Tumor Tissues.

Single-molecule fluorescence in situ hybridization (smFISH) represents a promising approach for the quantitative analysis of nucleic acid biomarkers in clinical tissue samples. However, low signal intensity and high background noise are complications that arise from diagnostic pathology when performed with smFISH-based RNA imaging in formalin-fixed paraffin-embedded (FFPE) tissue specimens. Moreover, the associated complex procedures can produce uncertain results and poor image quality. Herein, by combining the high specificity of split DNA probes with the high signal readout of ZnCdSe/ZnS quantum dot (QD) labeling, we introduce QD split-FISH, a high-brightness smFISH technology, to quantify the expression of mRNA in both cell lines and clinical FFPE tissue samples of breast cancer and lung squamous carcinoma. Owing to its high signal-to-noise ratio, QD split-FISH is a fast, inexpensive, and sensitive method for quantifying mRNA expression in FFPE tumor tissues, making it suitable for biomarker imaging and diagnostic pathology.

Lanthanide Complex for Single-Molecule Fluorescent in Situ Hybridization and Background-Free Imaging.

Traditional single-molecule fluorescence in situ hybridization (smFISH) methods for RNA detection often face sensitivity challenges due to the low fluorescence intensity of the probe. Also, short-lived autofluorescence complicates obtaining clear signals from tissue sections. In response, we have developed an smFISH probe using highly grafted lanthanide complexes to address both concentration quenching and autofluorescence background. Our approach involves an oligo PCR incorporating azide-dUTP, enabling conjugation with lanthanide complexes. This method has proven to be stable, convenient, and cost-effective. Notably, for the mRNA detection in SKBR3 cells, the lanthanide probe group exhibited 2.5 times higher luminescence intensity and detected 3 times more signal points in cells compared with the Cy3 group. Furthermore, we successfully applied the probe to image HER2 mRNA molecules in breast cancer FFPE tissue sections, achieving a 2.7-fold improvement in sensitivity compared to Cy3-based probes. These results emphasize the potential of time-resolved smFISH as a highly sensitive method for nucleic acid detection, free of background fluorescence interference.

Immunophenotypic and Gene Expression Analyses of the Inflammatory Microenvironment in High-Grade Oral Epithelial Dysplasia and Oral Lichen Planus.

BACKGROUND: Oral lichen planus (OLP) and oral epithelial dysplasia (OED) present diagnostic challenges due to clinical and histologic overlap. This study explores the immune microenvironment in OED, hypothesizing that immune signatures could aid in diagnostic differentiation and predict malignant transformation. METHODS: Tissue samples from OED and OLP cases were analyzed using immunofluorescence/immunohistochemistry (IF/IHC) for CD4, CD8, CD163/STAT1, and PD-1/PDL-1 expression. RNA-sequencing was performed on the samples, and data was subjected to CIBERSORTx analysis for immune cell composition. Gene Ontology analysis on the immune differentially expressed genes was also conducted. RESULTS: In OED, CD8 + T-cells infiltrated dysplastic epithelium, correlating with dysplasia severity. CD4 + lymphocytes increased in the basal layer. STAT1/CD163 + macrophages correlated with CD4 + intraepithelial distribution. PD-1/PDL-1 expression varied. IF/IHC analysis revealed differential immune cell composition between OED and OLP. RNA-sequencing identified upregulated genes associated with cytotoxic response and immunosurveillance in OED. Downregulated genes were linked to signaling, immune cell recruitment, and tumor suppression. CONCLUSIONS: The immune microenvironment distinguishes OED and OLP, suggesting diagnostic potential. Upregulated genes indicate cytotoxic immune response in OED. Downregulation of TRADD, CX3CL1, and ILI24 implies dysregulation in TNFR1 signaling, immune recruitment, and tumor suppression. This study contributes to the foundation for understanding immune interactions in OED and OLP, offering insights into future objective diagnostic avenues.

Nucleic acid hybridization-based detection of pathogenic RNA using microscale thermophoresis.

Infectious diseases are one of the world's leading causes of morbidity. Their rapid spread emphasizes the need for accurate and fast diagnostic methods for large-scale screening. Here, we describe a robust method for the detection of pathogens based on microscale thermophoresis (MST). The method involves the hybridization of a fluorescently labeled DNA probe to a target RNA and the assessment of thermophoretic migration of the resulting complex in solution within a 2 to 30-time window. We found that the thermophoretic migration of the nucleic acid-based probes is primarily determined by the fluorescent molecule used, rather than the nucleic acid sequence of the probe. Furthermore, a panel of uniformly labeled probes that bind to the same target RNA yields a more responsive detection pattern than a single probe, and moreover, can be used for the detection of specific pathogen variants. In addition, intercalating agents (ICA) can be used to alter migration directionality to improve detection sensitivity and resolving power by several orders of magnitude. We show that this approach can rapidly diagnose viral SARS-CoV2, influenza H1N1, artificial pathogen targets, and bacterial infections. Furthermore, it can be used for anti-microbial resistance testing within 2 h, demonstrating its diagnostic potential for early pathogen detection.

Self-Assembling Polypeptides in Complex Coacervation.

ConspectusIntracellular compartmentalization plays a pivotal role in cellular function, with membrane-bound organelles and membrane-less biomolecular "condensates" playing key roles. These condensates, formed through liquid-liquid phase separation (LLPS), enable selective compartmentalization without the barrier of a lipid bilayer, thereby facilitating rapid formation and dissolution in response to stimuli. Intrinsically disordered proteins (IDPs) or proteins with intrinsically disordered regions (IDRs), which are often rich in charged and polar amino acid sequences, scaffold many condensates, often in conjunction with RNA.Comprehending the impact of IDP/IDR sequences on phase separation poses a challenge due to the extensive chemical diversity resulting from the myriad amino acids and post-translational modifications. To tackle this hurdle, one approach has been to investigate LLPS in simplified polypeptide systems, which offer a narrower scope within the chemical space for exploration. This strategy is supported by studies that have demonstrated how IDP function can largely be understood based on general chemical features, such as clusters or patterns of charged amino acids, rather than residue-level effects, and the ways in which these kinds of motifs give rise to an ensemble of conformations.Our laboratory has utilized complex coacervates assembled from oppositely charged polypeptides as a simplified material analogue to the complexity of liquid-liquid phase separated biological condensates. Complex coacervation is an associative LLPS that occurs due to the electrostatic complexation of oppositely charged macro-ions. This process is believed to be driven by the entropic gains resulting from the release of bound counterions and the reorganization of water upon complex formation. Apart from their direct applicability to IDPs, polypeptides also serve as excellent model polymers for investigating molecular interactions due to the wide range of available side-chain functionalities and the capacity to finely regulate their sequence, thus enabling precise control over interactions with guest molecules.Here, we discuss fundamental studies examining how charge patterning, hydrophobicity, chirality, and architecture affect the phase separation of polypeptide-based complex coacervates. These efforts have leveraged a combination of experimental and computational approaches that provide insight into molecular level interactions. We also examine how these parameters affect the ability of complex coacervates to incorporate globular proteins and viruses. These efforts couple directly with our fundamental studies into coacervate formation, as such "guest" molecules should not be considered as experiencing simple encapsulation and are instead active participants in the electrostatic assembly of coacervate materials. Interestingly, we observed trends in the incorporation of proteins and viruses into coacervates formed using different chain length polypeptides that are not well explained by simple electrostatic arguments and may be the result of more complex interactions between globular and polymeric species. Additionally, we describe experimental evidence supporting the potential for complex coacervates to improve the thermal stability of embedded biomolecules, such as viral vaccines.Ultimately, peptide-based coacervates have the potential to help unravel the physics behind biological condensates, while paving the way for innovative methods in compartmentalization, purification, and biomolecule stabilization. These advancements could have implications spanning medicine to biocatalysis.

Influence of the isolation method on characteristics and functional activity of mesenchymal stromal cell-derived extracellular vesicles.

BACKGROUND AIMS: Extracellular vesicle (EV) isolation methods are based on different physicochemical properties and may result in the purification of distinct EV populations. We compared two different isolation methods suitable for producing clinical-grade mesenchymal stromal cell-derived EVs (MSC-EVs)-ion exchange chromatography (IEX) and ultrafiltration (UF)-and evaluated their impact on the composition and functional properties of EVs. METHODS: EVs were purified from conditioned culture medium using an anion exchange resin (IEX) or Amicon filters with a 100-kDa cutoff (UF) (MilliporeSigma, Burlington, MA, USA). We assessed nanoparticle size and distribution by nanoparticle tracking analysis (NTA) and tunable resistive pulse sensing (TRPS) and morphology by transmission electron microscopy. We also measured protein, lipid and total RNA concentration and immunophenotyped both EV populations by flow cytometry (MACSPlex assay; Miltenyi Biotec, Bergisch Gladbach, Germany). Moreover, immunomodulatory activity was tested using a standardized macrophage polarization assay and T-cell stimulation assay. Finally, proteomic analysis and cytokine quantification were carried out to better characterize both EV populations. RESULTS: We found by both TRPS and NTA that IEX and UF yielded a comparable amount of total particles with similar size and distribution. In addition, a similar quantity of lipids was obtained with the two procedures. However, IEX yielded 10-fold higher RNA quantity and a larger amount of proteins than UF. MSC-EVs isolated from IEX and UF were positive for the exosome markers CD9, CD63 and CD81 and showed a comparable surface marker expression pattern. Both populations demonstrated immunomodulatory activity in vitro, as they prevented acquisition of the M1 phenotype in lipopolysaccharide-stimulated macrophages and inhibited acquisition of the activation markers CD69 and CD25 on T cells, but the IEX-EVs exerted a significantly greater immunomodulatory effect on both macrophages and T cells compared with UF-EVs. Proteomic analysis and gene ontology enrichment analysis revealed no major differences between the preparations. Finally, cytokine quantification revealed that IEX-EVs were more enriched in some crucial anti-inflammatory and immunomodulatory cytokines (e.g., IL-2, IL-10, transforming growth factor beta and vascular endothelial growth factor) compared with UF-EVs. CONCLUSIONS: MSC-EVs isolated by IEX and UF displayed similar physicochemical, phenotypic and functional characteristics. In our conditions, both EV populations demonstrated important anti-inflammatory activity in macrophages and T cells. However, IEX-EVs were more potent than UF-EVs, which may indicate the superiority of this method for the production of clinical-grade EVs.

Rigorous Comparison of Extracellular Vesicle Processing to Enhance Downstream Analysis for Glioblastoma Characterization.

Extracellular vesicles (EVs) are highly sought after as a source of biomarkers for disease detection and monitoring. Tumor EV isolation, processing, and evaluation from biofluids is convoluted by EV heterogeneity and biological contaminants and is limited by technical processing efficacy. This study rigorously compares common bulk EV isolation workflows (size exclusion chromatography, SEC; membrane affinity, MA) alongside downstream RNA extraction protocols to investigate molecular analyte recovery. EV integrity and recovery is evaluated using a variety of technologies to quantify total intact EVs, total and surface proteins, and RNA purity and recovery. A comprehensive evaluation of each analyte is performed, with a specific emphasis on maintaining user (n = 2), biological (n = 3), and technical replicates (n≥3) under in vitro conditions. Subsequent study of tumor EV spike-in into healthy donor plasma samples is performed to further validate biofluid-derived EV purity and isolation for clinical application. Results show that EV surface integrity is considerably preserved in eluates from SEC-derived EVs, but RNA recovery and purity, as well as bulk protein isolation, is significantly improved in MA-isolated EVs. This study concludes that EV isolation and RNA extraction pipelines govern recovered analyte integrity, necessitating careful selection of processing modality to enhance recovery of the analyte of interest.

RNA-seq RNAaccess identified as the preferred method for gene expression analysis of low quality FFPE samples.

Clinical tumor tissues that are preserved as formalin-fixed paraffin-embedded (FFPE) samples result in extensive cross-linking, fragmentation, and chemical modification of RNA, posing significant challenges for RNA-seq-based gene expression profiling. This study sought to define an optimal RNA-seq protocol for FFPE samples. We employed a common RNA extraction method and then compared RNA-seq library preparation protocols including RNAaccess, RiboZero and PolyA in terms of sequencing quality and concordance of gene expression using FFPE and case-matched fresh-frozen (FF) triple-negative breast cancer (TNBC) tissues. We found that RNAaccess, a method based on exome capture, produced the most concordant results. Applying RNAaccess to FFPE gastric cancer tissues, we established a minimum RNA DV200 requirement of 10% and a RNA input amount of 10ng that generated highly reproducible gene expression data. Lastly, we demonstrated that RNAaccess and NanoString platforms produced highly concordant expression profiles from FFPE samples for shared genes; however, RNA-seq may be preferred for clinical biomarker discovery work because of the broader coverage of the transcriptome. Taken together, these results support the selection of RNA-seq RNAaccess method for gene expression profiling of FFPE samples. The minimum requirements for RNA quality and input established here may allow for inclusion of clinical FFPE samples of sub-optimal quality in gene expression analyses and ultimately increasing the statistical power of such analyses.

Multitarget Stool RNA Test for Colorectal Cancer Screening.

Importance: Noninvasive tests for colorectal cancer screening must include sensitive detection of colorectal cancer and precancerous lesions. These tests must be validated for the intended-use population, which includes average-risk individuals 45 years or older. Objective: To evaluate the sensitivity and specificity of a noninvasive, multitarget stool RNA (mt-sRNA) test (ColoSense) test compared with results from a colonoscopy. Design, Setting, and Participants: This phase 3 clinical trial (CRC-PREVENT) was a blinded, prospective, cross-sectional study to support a premarket approval application for a class III medical device. A total of 8920 participants were identified online using social media platforms and enrolled from June 2021 to June 2022 using a decentralized nurse call center. All participants completed the mt-sRNA test, which incorporated a commercially available fecal immunochemical test (FIT), concentration of 8 RNA transcripts, and participant-reported smoking status. Stool samples were collected prior to participants completing a colonoscopy at their local endoscopy center. The mt-sRNA test results (positive or negative) were compared with index lesions observed on colonoscopy. Over the course of 12 months, individuals 45 years and older were enrolled in the clinical trial using the decentralized recruitment strategy. Participants were enrolled from 49 US states and obtained colonoscopies at more than 3800 different endoscopy centers. Main Outcomes and Measures: The primary outcomes included the sensitivity of the mt-sRNA test for detecting colorectal cancer and advanced adenomas and the specificity for no lesions on colonoscopy. Results: The mean (range) age of participants was 55 (45-90) years, with 4% self-identified as Asian, 11% as Black, and 7% as Hispanic. Of the 8920 eligible participants, 36 (0.40%) had colorectal cancer and 606 (6.8%) had advanced adenomas. The mt-sRNA test sensitivity for detecting colorectal cancer was 94%, sensitivity for detecting advanced adenomas was 46%, and specificity for no lesions on colonoscopy was 88%. The mt-sRNA test showed significant improvement in sensitivity for colorectal cancer (94% vs 78%; McNemar P = .01) and advanced adenomas (46% vs 29%; McNemar P < .001) compared with results of the FIT. Conclusions and Relevance: In individuals 45 years and older, the mt-sRNA test showed high sensitivity for colorectal neoplasia (colorectal cancer and advanced adenoma) with significant improvement in sensitivity relative to the FIT. Specificity for no lesions on colonoscopy was comparable to existing molecular diagnostic tests. Trial Registration: ClinicalTrials.gov Identifier: NCT04739722.

Double blocking gap-filling-ligation coupled with cascade isothermal amplification for ultrasensitive quantification of N6-methyladenosine.

We developed a method for quantifying N6-methyladenosine at one-nucleotide resolution based on double blocking gap-filling-ligation and cascade isothermal amplification. This proposed method can detect as low as 1 fM target RNA, achieving selectivity up to approximately 100-fold between m6A and A, and has been successfully applied to the analysis of m6A at specific sites in cell samples.

Utility of Gene Expression Profiling in Skin Cancer: A Comprehensive Review.

Understanding the metastatic potential of a skin cancer is essential to effective management. Gene expression profiling (GEP) is an innovative technology that has allowed for a better understanding of tumor biology in various skin cancers. Current methods focus on identifying and quantifying ribonucleic acid (RNA) transcripts in tissue samples. Using reverse transcriptase-polymerase chain reaction, specific RNA transcripts are reverted into deoxyribonucleic acid (DNA) for quantification. The addition of RNA-seq has further enhanced our knowledge of genomes not only by measuring known sequences, but also by identifying novel genes in various skin cancers. GEP requires only a small amount of RNA and has a high level of reproducibility. Using this technology, several GEPs for skin cancers have been developed to augment diagnosis and prognosis of skin cancer. This article reviews the process of gene expression profiling and the current GEPs that are available or under investigation for skin cancer. J Drugs Dermatol. 2023;22(5): doi:10.36849/JDD.7017.

The Application of Guanidinium to Improve Biomolecule Quality in Fixed, Paraffin-embedded Tissue.

Neutral buffered formalin (NBF) is the most common fixative in clinical applications. However, NBF damages proteins and nucleic acids, limiting the quality of proteomic and nucleic acid-based assays. Prior studies have demonstrated that BE70, a fixative of buffered 70% ethanol, has many benefits over NBF but the degradation of proteins and nucleic acids in archival paraffin blocks remain a challenge. Thus, we evaluated the addition of guanidinium salts to BE70 with the hypothesis that this may protect RNA and protein. Guanidinium salt supplemented BE70 (BE70G)-fixed tissue is comparable with that of BE70 via histology and immunohistochemistry. Western blot analysis also revealed that HSP70, AKT, and glyceraldehyde 3-phosphate dehydrogenase (GAPDH) expression signals in BE70G-fixed tissue were higher than those in BE70-fixed tissue. The quality of nucleic acids extracted from BE70G-fixed, paraffin-embedded tissue was also superior, and BE70G provides improved protein and RNA quality at shorter fixation times than its predecessors. The degradation of proteins, AKT and GAPDH, in archival tissue blocks is also decreased with the addition of guanidinium salt to BE70. In conclusion, BE70G fixative improves the quality of molecular analysis with more rapid fixation of tissue and enhanced long-term storage of paraffin blocks at room temperature for evaluation of protein epitopes.

The proteome and transcriptome of stress granules and P bodies during human T lymphocyte activation.

Stress granules (SGs) and processing bodies (PBs) are membraneless cytoplasmic assemblies regulating mRNAs under environmental stress such as viral infections, neurological disorders, or cancer. Upon antigen stimulation, T lymphocytes mediate their immune functions under regulatory mechanisms involving SGs and PBs. However, the impact of T cell activation on such complexes in terms of formation, constitution, and relationship remains unknown. Here, by combining proteomic, transcriptomic, and immunofluorescence approaches, we simultaneously characterized the SGs and PBs from primary human T lymphocytes pre and post stimulation. The identification of the proteomes and transcriptomes of SGs and PBs indicate an unanticipated molecular and functional complementarity. Notwithstanding, these granules keep distinct spatial organizations and abilities to interact with mRNAs. This comprehensive characterization of the RNP granule proteomic and transcriptomic landscapes provides a unique resource for future investigations on SGs and PBs in T lymphocytes.