Phospho‐RNA‐seq: a modified small RNA‐seq method that reveals circulating mRNA and lncRNA fragments as potential biomarkers in human plasma

Extracellular RNAs (exRNAs) in biofluids have attracted great interest as potential biomarkers. Although extracellular microRNAs in blood plasma are extensively characterized, extracellular messenger RNA (mRNA) and long non‐coding RNA (lncRNA) studies are limited. We report that plasma contains fragmented mRNAs and lncRNAs that are missed by standard small RNA‐seq protocols due to lack of 5′ phosphate or presence of 3′ phosphate. These fragments were revealed using a modified protocol (“phospho‐RNA‐seq”) incorporating RNA treatment with T4‐polynucleotide kinase, which we compared with standard small RNA‐seq for sequencing synthetic RNAs with varied 5′ and 3′ ends, as well as human plasma exRNA. Analyzing phospho‐RNA‐seq data using a custom, high‐stringency bioinformatic pipeline, we identified mRNA/lncRNA transcriptome fingerprints in plasma, including tissue‐specific gene sets. In a longitudinal study of hematopoietic stem cell transplant patients, bone marrow‐ and liver‐enriched exRNA genes were tracked with bone marrow recovery and liver injury, respectively, providing proof‐of‐concept validation as a biomarker approach. By enabling access to an unexplored realm of mRNA and lncRNA fragments, phospho‐RNA‐seq opens up new possibilities for plasma transcriptomic biomarker development.SynopsisA modified RNA‐seq method (Phospho‐RNA‐seq) revealed a new population of mRNA/lncRNA fragments in plasma, including ones that track with disease. This opens up new possibilities for disease detection via RNA profiling of plasma and other biofluids.Phospho‐RNA‐seq reveals a large population of mRNA and long non‐coding RNA fragments in human plasma, which are missed by standard small RNA‐seq protocols that depend on target RNAs having a 5′ P and 3′ OH.Accurate detection of plasma mRNA and lncRNA fragments requires a stringent bioinformatic analysis pipeline to avoid false positive alignments to mRNA and lncRNA genes.Phospho‐RNA‐seq identified ensembles of tissue‐specific transcripts in plasma of hematopoietic stem cell transplant patients, which show co‐expression patterns that vary dynamically and track with pathophysiological processes.By enabling access to an unexplored space of extracellular mRNA and lncRNA fragments, phospho‐RNA‐seq opens up new possibilities for monitoring health and disease via transcriptome fragment profiling of plasma and potentially other biofluids.A modified RNA‐seq method reveals a large population of mRNA/lncRNA fragments in plasma that are missed by standard small RNA‐seq protocols including ones that are associated with disease.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/149518/1/embj2019101695_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/149518/2/embj2019101695-sup-0002-EVFigs.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/149518/3/embj2019101695.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/149518/4/embj2019101695-sup-0001-Appendix.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/149518/5/embj2019101695.reviewer_comments.pd

Maximal Extraction of Biological Information from Genetic Interaction Data

Targeted genetic perturbation is a powerful tool for inferring gene function in model organisms. Functional relationships between genes can be inferred by observing the effects of multiple genetic perturbations in a single strain. The study of these relationships, generally referred to as genetic interactions, is a classic technique for ordering genes in pathways, thereby revealing genetic organization and gene-to-gene information flow. Genetic interaction screens are now being carried out in high-throughput experiments involving tens or hundreds of genes. These data sets have the potential to reveal genetic organization on a large scale, and require computational techniques that best reveal this organization. In this paper, we use a complexity metric based in information theory to determine the maximally informative network given a set of genetic interaction data. We find that networks with high complexity scores yield the most biological information in terms of (i) specific associations between genes and biological functions, and (ii) mapping modules of co-functional genes. This information-based approach is an automated, unsupervised classification of the biological rules underlying observed genetic interactions. It might have particular potential in genetic studies in which interactions are complex and prior gene annotation data are sparse

Urinary MicroRNA Profiling in the Nephropathy of Type 1 Diabetes

Background: Patients with Type 1 Diabetes (T1D) are particularly vulnerable to development of Diabetic nephropathy (DN) leading to End Stage Renal Disease. Hence a better understanding of the factors affecting kidney disease progression in T1D is urgently needed. In recent years microRNAs have emerged as important post-transcriptional regulators of gene expression in many different health conditions. We hypothesized that urinary microRNA profile of patients will differ in the different stages of diabetic renal disease. Methods and Findings: We studied urine microRNA profiles with qPCR in 40 T1D with >20 year follow up 10 who never developed renal disease (N) matched against 10 patients who went on to develop overt nephropathy (DN), 10 patients with intermittent microalbuminuria (IMA) matched against 10 patients with persistent (PMA) microalbuminuria. A Bayesian procedure was used to normalize and convert raw signals to expression ratios. We applied formal statistical techniques to translate fold changes to profiles of microRNA targets which were then used to make inferences about biological pathways in the Gene Ontology and REACTOME structured vocabularies. A total of 27 microRNAs were found to be present at significantly different levels in different stages of untreated nephropathy. These microRNAs mapped to overlapping pathways pertaining to growth factor signaling and renal fibrosis known to be targeted in diabetic kidney disease. Conclusions: Urinary microRNA profiles differ across the different stages of diabetic nephropathy. Previous work using experimental, clinical chemistry or biopsy samples has demonstrated differential expression of many of these microRNAs in a variety of chronic renal conditions and diabetes. Combining expression ratios of microRNAs with formal inferences about their predicted mRNA targets and associated biological pathways may yield useful markers for early diagnosis and risk stratification of DN in T1D by inferring the alteration of renal molecular processes. © 2013 Argyropoulos et al

Guiding the Design of Synthetic DNA-Binding Molecules with Massively Parallel Sequencing

Genomic applications of DNA-binding molecules require an unbiased knowledge of their high affinity sites. We report the high-throughput analysis of pyrrole-imidazole polyamide DNA-binding specificity in a 10^(12)-member DNA sequence library using affinity purification coupled with massively parallel sequencing. We find that even within this broad context, the canonical pairing rules are remarkably predictive of polyamide DNA-binding specificity. However, this approach also allows identification of unanticipated high affinity DNA-binding sites in the reverse orientation for polyamides containing β/Im pairs. These insights allow the redesign of hairpin polyamides with different turn units capable of distinguishing 5′-WCGCGW-3′ from 5′-WGCGCW-3′. Overall, this study displays the power of high-throughput methods to aid the optimal targeting of sequence-specific minor groove binding molecules, an essential underpinning for biological and nanotechnological applications

Origin of Secretin Receptor Precedes the Advent of Tetrapoda: Evidence on the Separated Origins of Secretin and Orexin

At present, secretin and its receptor have only been identified in mammals, and the origin of this ligand-receptor pair in early vertebrates is unclear. In addition, the elusive similarities of secretin and orexin in terms of both structures and functions suggest a common ancestral origin early in the vertebrate lineage. In this article, with the cloning and functional characterization of secretin receptors from lungfish and X. laevis as well as frog (X. laevis and Rana rugulosa) secretins, we provide evidence that the secretin ligand-receptor pair has already diverged and become highly specific by the emergence of tetrapods. The secretin receptor-like sequence cloned from lungfish indicates that the secretin receptor was descended from a VPAC-like receptor prior the advent of sarcopterygians. To clarify the controversial relationship of secretin and orexin, orexin type-2 receptor was cloned from X. laevis. We demonstrated that, in frog, secretin and orexin could activate their mutual receptors, indicating their coordinated complementary role in mediating physiological processes in non-mammalian vertebrates. However, among the peptides in the secretin/glucagon superfamily, secretin was found to be the only peptide that could activate the orexin receptor. We therefore hypothesize that secretin and orexin are of different ancestral origins early in the vertebrate lineage

Compensatory Evolution of Gene Regulation in Response to Stress by Escherichia coli Lacking RpoS

The RpoS sigma factor protein of Escherichia coli RNA polymerase is the master transcriptional regulator of physiological responses to a variety of stresses. This stress response comes at the expense of scavenging for scarce resources, causing a trade-off between stress tolerance and nutrient acquisition. This trade-off favors non-functional rpoS alleles in nutrient-poor environments. We used experimental evolution to explore how natural selection modifies the regulatory network of strains lacking RpoS when they evolve in an osmotically stressful environment. We found that strains lacking RpoS adapt less variably, in terms of both fitness increase and changes in patterns of transcription, than strains with functional RpoS. This phenotypic uniformity was caused by the same adaptive mutation in every independent population: the insertion of IS10 into the promoter of the otsBA operon. OtsA and OtsB are required to synthesize the osmoprotectant trehalose, and transcription of otsBA requires RpoS in the wild-type genetic background. The evolved IS10 insertion rewires expression of otsBA from RpoS-dependent to RpoS-independent, allowing for partial restoration of wild-type response to osmotic stress. Our results show that the regulatory networks of bacteria can evolve new structures in ways that are both rapid and repeatable

Meeting report: discussions and preliminary findings on extracellular RNA measurement methods from laboratories in the NIH Extracellular RNA Communication Consortium

Extracellular RNAs (exRNAs) have been identified in all tested biofluids and have been associated with a variety of extracellular vesicles, ribonucleoprotein complexes and lipoprotein complexes. Much of the interest in exRNAs lies in the fact that they may serve as signalling molecules between cells, their potential to serve as biomarkers for prediction and diagnosis of disease and the possibility that exRNAs or the extracellular particles that carry them might be used for therapeutic purposes. Among the most significant bottlenecks to progress in this field is the lack of robust and standardized methods for collection and processing of biofluids, separation of different types of exRNA-containing particles and isolation and analysis of exRNAs. The Sample and Assay Standards Working Group of the Extracellular RNA Communication Consortium is a group of laboratories funded by the U.S. National Institutes of Health to develop such methods. In our first joint endeavour, we held a series of conference calls and in-person meetings to survey the methods used among our members, placed them in the context of the current literature and used our findings to identify areas in which the identification of robust methodologies would promote rapid advancements in the exRNA field

Comparing the MicroRNA Spectrum between Serum and Plasma

MicroRNAs (miRNAs) are small, non-coding RNAs that regulate various biological processes, primarily through interaction with messenger RNAs. The levels of specific, circulating miRNAs in blood have been shown to associate with various pathological conditions including cancers. These miRNAs have great potential as biomarkers for various pathophysiological conditions. In this study we focused on different sample types’ effects on the spectrum of circulating miRNA in blood. Using serum and corresponding plasma samples from the same individuals, we observed higher miRNA concentrations in serum samples compared to the corresponding plasma samples. The difference between serum and plasma miRNA concentration showed some associations with miRNA from platelets, which may indicate that the coagulation process may affect the spectrum of extracellular miRNA in blood. Several miRNAs also showed platform dependent variations in measurements. Our results suggest that there are a number of factors that might affect the measurement of circulating miRNA concentration. Caution must be taken when comparing miRNA data generated from different sample types or measurement platform