Methylome-wide Analysis of Chronic HIV Infection Reveals Five-Year Increase in Biological Age and Epigenetic Targeting of HLA.

HIV-infected individuals are living longer on antiretroviral therapy, but many patients display signs that in some ways resemble premature aging. To investigate and quantify the impact of chronic HIV infection on aging, we report a global analysis of the whole-blood DNA methylomes of 137 HIV+ individuals under sustained therapy along with 44 matched HIV- individuals. First, we develop and validate epigenetic models of aging that are independent of blood cell composition. Using these models, we find that both chronic and recent HIV infection lead to an average aging advancement of 4.9 years, increasing expected mortality risk by 19%. In addition, sustained infection results in global deregulation of the methylome across >80,000 CpGs and specific hypomethylation of the region encoding the human leukocyte antigen locus (HLA). We find that decreased HLA methylation is predictive of lower CD4 / CD8 T cell ratio, linking molecular aging, epigenetic regulation, and disease progression.

Immunodeficiency and autoimmune enterocolopathy linked to NFAT5 haploinsufficiency.

The link between autoimmune diseases and primary immunodeficiency syndromes has been increasingly appreciated. Immunologic evaluation of a young man with autoimmune enterocolopathy and unexplained infections revealed evidence of immunodeficiency, including IgG subclass deficiency, impaired Ag-induced lymphocyte proliferation, reduced cytokine production by CD8(+) T lymphocytes, and decreased numbers of NK cells. Genetic evaluation identified haploinsufficiency of NFAT5, a transcription factor regulating immune cell function and cellular adaptation to hyperosmotic stress, as a possible cause of this syndrome. Inhibition or deletion of NFAT5 in normal human and murine cells recapitulated several of the immune deficits identified in the patient. These results provide evidence of a primary immunodeficiency disorder associated with organ-specific autoimmunity linked to NFAT5 deficiency.

Comparison of protein, microRNA, and mRNA yields using different methods of urinary exosome isolation for the discovery of kidney disease biomarkers.

Urinary exosomes are 40-100 nm vesicles containing protein, mRNA, and microRNA that may serve as biomarkers of renal dysfunction and structural injury. Currently, there is a need for more sensitive and specific biomarkers of renal injury and disease progression. Here we sought to identify the best exosome isolation methods for both proteomic analysis and RNA profiling as a first step for biomarker discovery. We used six different protocols; three were based on ultracentrifugation, one used a nanomembrane concentrator-based approach, and two utilized a commercial exosome precipitation reagent. The highest yield of exosomes was obtained using a modified exosome precipitation protocol, which also yielded the highest quantities of microRNA and mRNA and, therefore, is ideal for subsequent RNA profiling. This method is likewise suitable for downstream proteomic analyses if an ultracentrifuge is not available and/or a large number of samples are to be processed. Two of the ultracentrifugation methods, however, are better options for exosome isolation if an ultracentrifuge is available and few samples will be processed for proteomic analysis. Thus, our modified exosome precipitation method is a simple, fast, highly scalable, and effective alternative for the isolation of exosomes, and may facilitate the identification of exosomal biomarkers from urine.

Optimizing sequencing protocols for leaderboard metagenomics by combining long and short reads.

As metagenomic studies move to increasing numbers of samples, communities like the human gut may benefit more from the assembly of abundant microbes in many samples, rather than the exhaustive assembly of fewer samples. We term this approach leaderboard metagenome sequencing. To explore protocol optimization for leaderboard metagenomics in real samples, we introduce a benchmark of library prep and sequencing using internal references generated by synthetic long-read technology, allowing us to evaluate high-throughput library preparation methods against gold-standard reference genomes derived from the samples themselves. We introduce a low-cost protocol for high-throughput library preparation and sequencing.

MiSeq: A Next Generation Sequencing Platform for Genomic Analysis.

MiSeq, Illumina's integrated next generation sequencing instrument, uses reversible-terminator sequencing-by-synthesis technology to provide end-to-end sequencing solutions. The MiSeq instrument is one of the smallest benchtop sequencers that can perform onboard cluster generation, amplification, genomic DNA sequencing, and data analysis, including base calling, alignment and variant calling, in a single run. It performs both single- and paired-end runs with adjustable read lengths from 1 × 36 base pairs to 2 × 300 base pairs. A single run can produce output data of up to 15 Gb in as little as 4 h of runtime and can output up to 25 M single reads and 50 M paired-end reads. Thus, MiSeq provides an ideal platform for rapid turnaround time. MiSeq is also a cost-effective tool for various analyses focused on targeted gene sequencing (amplicon sequencing and target enrichment), metagenomics, and gene expression studies. For these reasons, MiSeq has become one of the most widely used next generation sequencing platforms. Here, we provide a protocol to prepare libraries for sequencing using the MiSeq instrument and basic guidelines for analysis of output data from the MiSeq sequencing run.

Correction: Role of MicroRNA 1207-5P and Its Host Gene, the Long Non-Coding RNA Pvt1, as Mediators of Extracellular Matrix Accumulation in the Kidney: Implications for Diabetic Nephropathy.

[This corrects the article DOI: 10.1371/journal.pone.0077468.].

From Sample to Multi-Omics Conclusions in under 48 Hours.

Multi-omics methods have greatly advanced our understanding of the biological organism and its microbial associates. However, they are not routinely used in clinical or industrial applications, due to the length of time required to generate and analyze omics data. Here, we applied a novel integrated omics pipeline for the analysis of human and environmental samples in under 48 h. Human subjects that ferment their own foods provided swab samples from skin, feces, oral cavity, fermented foods, and household surfaces to assess the impact of home food fermentation on their microbial and chemical ecology. These samples were analyzed with 16S rRNA gene sequencing, inferred gene function profiles, and liquid chromatography-tandem mass spectrometry (LC-MS/MS) metabolomics through the Qiita, PICRUSt, and GNPS pipelines, respectively. The human sample microbiomes clustered with the corresponding sample types in the American Gut Project (http://www.americangut.org), and the fermented food samples produced a separate cluster. The microbial communities of the household surfaces were primarily sourced from the fermented foods, and their consumption was associated with increased gut microbial diversity. Untargeted metabolomics revealed that human skin and fermented food samples had separate chemical ecologies and that stool was more similar to fermented foods than to other sample types. Metabolites from the fermented foods, including plant products such as procyanidin and pheophytin, were present in the skin and stool samples of the individuals consuming the foods. Some food metabolites were modified during digestion, and others were detected in stool intact. This study represents a first-of-its-kind analysis of multi-omics data that achieved time intervals matching those of classic microbiological culturing. IMPORTANCE Polymicrobial infections are difficult to diagnose due to the challenge in comprehensively cultivating the microbes present. Omics methods, such as 16S rRNA sequencing, metagenomics, and metabolomics, can provide a more complete picture of a microbial community and its metabolite production, without the biases and selectivity of microbial culture. However, these advanced methods have not been applied to clinical or industrial microbiology or other areas where complex microbial dysbioses require immediate intervention. The reason for this is the length of time required to generate and analyze omics data. Here, we describe the development and application of a pipeline for multi-omics data analysis in time frames matching those of the culture-based approaches often used for these applications. This study applied multi-omics methods effectively in clinically relevant time frames and sets a precedent toward their implementation in clinical medicine and industrial microbiology.

A modified precipitation method to isolate urinary exosomes.

Identification of biomarkers that allow early detection of kidney diseases in urine and plasma has been an area of active interest for several years. Urinary exosome vesicles, 40-100 nm in size, are released into the urine under normal conditions by cells from all nephron segments and may contain protein, mRNA and microRNA representative of their cell type of origin. Under conditions of renal dysfunction or injury, exosomes may contain altered proportions of these components, which may serve as biomarkers for disease. There are currently several methods available for isolation of urinary exosomes, and we have previously conducted an experimental comparison of each of these approaches, including three based on ultracentrifugation, one using a nanomembrane ultrafiltration concentrator, one using a commercial precipitation reagent and one using a modification of the precipitation technique using ExoQuick reagent that we developed in our laboratory. We found the modified precipitation method produced the highest yield of exosome particles, miRNA, and mRNA, making this approach suitable for the isolation of exosomes for subsequent RNA profiling. We conclude that the modified exosome precipitation method offers a quick, scalable, and effective alternative for the isolation of exosomes from urine. In this report, we describe our modified precipitation technique using ExoQuick reagent for isolating exosomes from human urine.

MicroRNA-27a decreases the level and efficiency of the LDL receptor and contributes to the dysregulation of cholesterol homeostasis.

RATIONALE: A strong risk factor for atherosclerosis- the leading cause of heart attacks and strokes- is the elevation of low-density lipoprotein cholesterol (LDL-C) in blood. The LDL receptor (LDLR) is the primary pathway for LDL-C removal from circulation, and their levels are increased by statins -the main treatment for high blood LDL-C. However, statins have low efficiency because they also increase PCSK9 which targets LDLR for degradation. Since microRNAs have recently emerged as key regulators of cholesterol homeostasis, our aim was to identify potential microRNA-based therapeutics to decrease blood LDL-C and prevent atherosclerosis. METHODS AND RESULTS: We over expressed and knocked down miR-27a in HepG2 cells to assess its effect on the expression of key players in the LDLR pathway using PCR Arrays, Elisas, and Western blots. We found that miR-27a decreases LDLR levels by 40% not only through a direct binding to its 3' untranslated region but also indirectly by inducing a 3-fold increase in PCSK9, which enhances LDLR degradation. Interestingly, miR-27a also directly decreases LRP6 and LDLRAP1, two other key players in the LDLR pathway that are required for efficient endocytosis of the LDLR-LDL-C complex in the liver. The inhibition of miR-27a using lock nucleic acids induced a 70% increase in LDLR levels and, therefore, it would be a more efficient treatment for hypercholesterolemia because of its desirable effects not only on LDLR but also on PCSK9. CONCLUSION: The results presented here provide evidence supporting the potential of miR-27a as a novel therapeutic target for the prevention of atherosclerosis.

Biased estimates of clonal evolution and subclonal heterogeneity can arise from PCR duplicates in deep sequencing experiments.

Accurate allele frequencies are important for measuring subclonal heterogeneity and clonal evolution. Deep-targeted sequencing data can contain PCR duplicates, inflating perceived read depth. Here we adapted the Illumina TruSeq Custom Amplicon kit to include single molecule tagging (SMT) and show that SMT-identified duplicates arise from PCR. We demonstrate that retention of PCR duplicate reads can imply clonal evolution when none exists, while their removal effectively controls the false positive rate. Additionally, PCR duplicates alter estimates of subclonal heterogeneity in tumor samples. Our method simplifies PCR duplicate identification and emphasizes their removal in studies of tumor heterogeneity and clonal evolution.

Role of microRNA 1207-5P and its host gene, the long non-coding RNA Pvt1, as mediators of extracellular matrix accumulation in the kidney: implications for diabetic nephropathy.

Diabetic nephropathy is the most common cause of chronic kidney failure and end-stage renal disease in the Western World. One of the major characteristics of this disease is the excessive accumulation of extracellular matrix (ECM) in the kidney glomeruli. While both environmental and genetic determinants are recognized for their role in the development of diabetic nephropathy, epigenetic factors, such as DNA methylation, long non-coding RNAs, and microRNAs, have also recently been found to underlie some of the biological mechanisms, including ECM accumulation, leading to the disease. We previously found that a long non-coding RNA, the plasmacytoma variant translocation 1 (PVT1), increases plasminogen activator inhibitor 1 (PAI-1) and transforming growth factor beta 1 (TGF-ß1) in mesangial cells, the two main contributors to ECM accumulation in the glomeruli under hyperglycemic conditions, as well as fibronectin 1 (FN1), a major ECM component. Here, we report that miR-1207-5p, a PVT1-derived microRNA, is abundantly expressed in kidney cells, and is upregulated by glucose and TGF-ß1. We also found that like PVT1, miR-1207-5p increases expression of TGF-ß1, PAI-1, and FN1 but in a manner that is independent of its host gene. In addition, regulation of miR-1207-5p expression by glucose and TGFß1 is independent of PVT1. These results provide evidence supporting important roles for miR-1207-5p and its host gene in the complex pathogenesis of diabetic nephropathy.