5' tRNA halves are highly expressed in the primate hippocampus and might sequence-specifically regulate gene expression.

Fragments of mature tRNAs have long been considered as mere degradation products without physiological function. However, recent reports show that tRNA-derived small RNAs (tsRNAs) play prominent roles in diverse cellular processes across a wide spectrum of species. Contrasting the situation in other small RNA pathways the mechanisms behind these effects appear more diverse, more complex, and are generally less well understood. In addition, surprisingly little is known about the expression profiles of tsRNAs across different tissues and species. Here, we provide an initial overview of tsRNA expression in different species and tissues, revealing very high levels of 5' tRNA halves (5' tRHs) particularly in the primate hippocampus. We further modulated the regulation capacity of selected 5' tRHs in human cells by transfecting synthetic tsRNA mimics ("overexpression") or antisense-RNAs ("inhibition") and identified differentially expressed transcripts based on RNA-seq. We then used a novel k-mer mapping approach to dissect the underlying targeting rules, suggesting that 5' tRHs silence genes in a sequence-specific manner, while the most efficient target sites align to the mid-region of the 5' tRH and are located within the CDS or 3' UTR of the target. This amends previous observations that tsRNAs guide Argonaute proteins to silence their targets via a miRNA-like 5' seed match and suggests a yet unknown mechanism of regulation. Finally, our data suggest that some 5' tRHs that are also able to sequence-specifically stabilize mRNAs as up-regulated mRNAs are also significantly enriched for 5' tRH target sites.

miR-Blood - a small RNA atlas of human blood components.

miR-Blood is a high-quality, small RNA expression atlas for the major components of human peripheral blood (plasma, erythrocytes, thrombocytes, monocytes, neutrophils, eosinophils, basophils, natural killer cells, CD4+ T cells, CD8+ T cells, and B cells). Based on the purified blood components from 52 individuals, the dataset provides a comprehensive repository for the expression of 4971 small RNAs from eight non-coding RNA classes.

Early Detection of Lung Cancer Using Small RNAs.

INTRODUCTION: Lung cancer remains the deadliest cancer in the world, and lung cancer survival is heavily dependent on tumor stage at the time of detection. Low-dose computed tomography screening can reduce mortality; however, annual screening is limited by low adherence in the United States of America and still not broadly implemented in Europe. As a result, less than 10% of lung cancers are detected through existing programs. Thus, there is a great need for additional screening tests, such as a blood test, that could be deployed in the primary care setting. METHODS: We prospectively recruited 1384 individuals meeting the National Lung Screening Trial demographic eligibility criteria for lung cancer and collected stabilized whole blood to enable the pipetting-free collection of material, thus minimizing preanalytical noise. Ultra-deep small RNA sequencing (20 million reads per sample) was performed with the addition of a method to remove highly abundant erythroid RNAs, and thus open bandwidth for the detection of less abundant species originating from the plasma or the immune cellular compartment. We used 100 random data splits to train and evaluate an ensemble of logistic regression classifiers using small RNA expression of 943 individuals, discovered an 18-small RNA feature consensus signature (miLung), and validated this signature in an independent cohort (441 individuals). Blood cell sorting and tumor tissue sequencing were performed to deconvolve small RNAs into their source of origin. RESULTS: We generated diagnostic models and report a median receiver-operating characteristic area under the curve of 0.86 (95% confidence interval [CI]: 0.84-0.86) in the discovery cohort and generalized performance of 0.83 in the validation cohort. Diagnostic performance increased in a stage-dependent manner ranging from 0.73 (95% CI: 0.71-0.76) for stage I to 0.90 (95% CI: 0.89-0.90) for stage IV in the discovery cohort and from 0.76 to 0.86 in the validation cohort. We identified a tumor-shed, plasma-bound ribosomal RNA fragment of the L1 stalk as a dominant predictor of lung cancer. The fragment is decreased after surgery with curative intent. In additional experiments, results of dried blood spot collection and sequencing revealed that small RNA analysis could potentially be conducted through home sampling. CONCLUSIONS: These data suggest the potential of a small RNA-based blood test as a viable alternative to low-dose computed tomography screening for early detection of smoking-associated lung cancer.

A blood-based miRNA signature with prognostic value for overall survival in advanced stage non-small cell lung cancer treated with immunotherapy.

Immunotherapies have recently gained traction as highly effective therapies in a subset of late-stage cancers. Unfortunately, only a minority of patients experience the remarkable benefits of immunotherapies, whilst others fail to respond or even come to harm through immune-related adverse events. For immunotherapies within the PD-1/PD-L1 inhibitor class, patient stratification is currently performed using tumor (tissue-based) PD-L1 expression. However, PD-L1 is an accurate predictor of response in only ~30% of cases. There is pressing need for more accurate biomarkers for immunotherapy response prediction. We sought to identify peripheral blood biomarkers, predictive of response to immunotherapies against lung cancer, based on whole blood microRNA profiling. Using three well-characterized cohorts consisting of a total of 334 stage IV NSCLC patients, we have defined a 5 microRNA risk score (miRisk) that is predictive of overall survival following immunotherapy in training and independent validation (HR 2.40, 95% CI 1.37-4.19; P < 0.01) cohorts. We have traced the signature to a myeloid origin and performed miRNA target prediction to make a direct mechanistic link to the PD-L1 signaling pathway and PD-L1 itself. The miRisk score offers a potential blood-based companion diagnostic for immunotherapy that outperforms tissue-based PD-L1 staining.

Effects of Distal Mutations on Prolyl-Adenylate Formation of Escherichia coli Prolyl-tRNA Synthetase.

Enzymes play important roles in many biological processes. Amino acid residues in the active site pocket of an enzyme, which are in direct contact with the substrate(s), are generally believed to be critical for substrate recognition and catalysis. Identifying and understanding how these "catalytic" residues help enzymes achieve enormous rate enhancement has been the focus of many structural and biochemical studies over the past several decades. Recent studies have shown that enzymes are intrinsically dynamic and dynamic coupling between distant structural elements is essential for effective catalysis in modular enzymes. Therefore, distal residues are expected to have impact on enzyme function. However, few studies have investigated the role of distal residues on enzymatic catalysis. In the present study, the effects of distal residue mutations on the catalytic function of an aminoacyl-tRNA synthetase, namely, prolyl-tRNA synthase, were investigated. The present study demonstrates that distal residues significantly contribute to catalysis of the modular Escherichia coli prolyl-tRNA synthetase by maintaining intrinsic protein flexibility.

Widespread selection for extremely high and low levels of secondary structure in coding sequences across all domains of life.

Codon composition, GC content and local RNA secondary structures can have a profound effect on gene expression, and mutations affecting these parameters, even though they do not alter the protein sequence, are not neutral in terms of selection. Although evidence exists that, in some cases, selection favours more stable RNA secondary structures, we currently lack a concrete idea of how many genes are affected within a species, and whether this is a universal phenomenon in nature. We searched for signs of structural selection in a global manner, analysing a set of 1 million coding sequences from 73 species representing all domains of life, as well as viruses, by means of our newly developed software PACKEIS. We show that codon composition and amino acid identity are main determinants of RNA secondary structure. In addition, we show that the arrangement of synonymous codons within coding sequences is non-random, yielding extremely high, but also extremely low, RNA structuredness significantly more often than expected by chance. Taken together, we demonstrate that selection for high and low levels of secondary structure is a widespread phenomenon. Our results provide another line of evidence that synonymous mutations are less neutral than commonly thought, which is of importance for many evolutionary models.

PIWI genes and piRNAs are ubiquitously expressed in mollusks and show patterns of lineage-specific adaptation.

PIWI proteins and PIWI-interacting RNAs (piRNAs) suppress transposon activity in animals, thus protecting their genomes from detrimental insertion mutagenesis. Here, we reveal that PIWI genes and piRNAs are ubiquitously expressed in mollusks, similar to the situation in arthropods. We describe lineage-specific adaptations of transposon composition in piRNA clusters in the great pond snail and the pacific oyster, likely reflecting differential transposon activity in gastropods and bivalves. We further show that different piRNA clusters with unique transposon composition are dynamically expressed during oyster development. Finally, bioinformatics analyses suggest that different populations of piRNAs presumably bound to different PIWI paralogs participate in homotypic and heterotypic ping-pong amplification loops in a tissue- and sex-specific manner. Together with recent findings from other animal species, our results support the idea that somatic piRNA expression represents the ancestral state in metazoans.