SummaryLittle is known about the functions of miRNAs in human longevity. Here, we present the first genome-wide miRNA study in longlived individuals (LLI) who are considered a model for healthy aging. Using a microarray with 863 miRNAs, we compared the expression profiles obtained from blood samples of 15 centenarians and nonagenarians (mean age 96.4 years) with those of 55 younger individuals (mean age 45.9 years). Eighty miRNAs showed aging-associated expression changes, with 16 miRNAs being up-regulated and 64 down-regulated in the LLI relative to the younger probands. Seven of the eight selected aging-related biomarkers were technically validated using quantitative RT-PCR, confirming the microarray data. Three of the eight miRNAs were further investigated in independent samples of 15 LLI and 17 younger participants (mean age 101.5 and 36.9 years, respectively). Our screening confirmed previously published miRNAs of human aging, thus reflecting the utility of the applied approach. The hierarchical clustering analysis of the miRNA microarray expression data revealed a distinct separation between the LLI and the younger controls (P-value < 10 )5). The down-regulated miRNAs appeared as a cluster and were more often reported in the context of diseases than the up-regulated miRNAs. Moreover, many of the differentially regulated miRNAs are known to exhibit contrasting expression patterns in major age-related diseases. Further in silico analyses showed enrichment of potential targets of the down-regulated miRNAs in p53 and other cancer pathways. Altogether, synchronized miRNA-p53 activities could be involved in the prevention of tumorigenesis and the maintenance of genomic integrity during aging.

The setup of synthetic biological systems involving millions of bases is still limited by the required high quality of synthetic DNA. Important drivers to further open up the field are the accuracy and scale of chemical DNA synthesis and the downstream processing of longer DNA assembled from short fragments. We developed a new, highly parallel and miniaturized method for the preparation of high quality DNA termed “Megacloning” by using Next Generation Sequencing (NGS) technology in a preparative way. We demonstrate our method by processing both conventional and microarray-derived DNA oligonucleotides in combination with a bead-based high throughput pyrosequencing platform, gaining a 500-fold error reduction for microarray oligonucleotides in a first embodiment. We also show the assembly of synthetic genes as part of the Megacloning process. In principle, up to millions of DNA fragments can be sequenced, characterized and sorted in a single Megacloner run, enabling many new applications.

MicroRNAs (miRNAs) are increasingly envisaged as biomarkers for various tumor and non-tumor diseases. MiRNA biomarker identification is, as of now, mostly performed in a candidate approach, limiting discovery to annotated miRNAs and ignoring unknown ones with potential diagnostic value. Here, we applied high-throughput SOLiD transcriptome sequencing of miRNAs expressed in human peripheral blood of patients with lung cancer. We developed a bioinformatics pipeline to generate profiles of miRNA markers and to detect novel miRNAs with diagnostic information. Applying our approach, we detected 76 previously unknown miRNAs and 41 novel mature forms of known precursors. In addition, we identified 32 annotated and seven unknown miRNAs that were significantly altered in cancer patients. These results demonstrate that deep sequencing of small RNAs bears high potential to quantify miRNAs in peripheral blood and to identify previously unknown miRNAs serving as biomarker for lung cancer.

Listeria monocytogenes, a gram-positive pathogen, and causative agent of listeriosis, has become a widely used model organism for intracellular infections. Recent studies have identified small non-coding RNAs (sRNAs) as important factors for regulating gene expression and pathogenicity of L. monocytogenes. Increased speed and reduced costs of high throughput sequencing (HTS) techniques have made RNA sequencing (RNA-Seq) the state-of-the-art method to study bacterial transcriptomes. We created a large transcriptome dataset of L. monocytogenes containing a total of 21 million reads, using the SOLiD sequencing technology. The dataset contained cDNA sequences generated from L. monocytogenes RNA collected under intracellular and extracellular condition and additionally was size fractioned into three different size ranges from <40 nt, 40–150 nt and >150 nt. We report here, the identification of nine new sRNAs candidates of L. monocytogenes and a reevaluation of known sRNAs of L. monocytogenes EGD-e. Automatic comparison to known sRNAs revealed a high recovery rate of 55%, which was increased to 90% by manual revision of the data. Moreover, thorough classification of known sRNAs shed further light on their possible biological functions. Interestingly among the newly identified sRNA candidates are antisense RNAs (asRNAs) associated to the housekeeping genes purA, fumC and pgi and potentially their regulation, emphasizing the significance of sRNAs for metabolic adaptation in L. monocytogenes.