Preclinical safety and biodistribution of CRISPR targeting SIV in non-human primates.

In this study, we demonstrate the safety and utility of CRISPR-Cas9 gene editing technology for in vivo editing of proviral DNA in ART-treated, virally controlled simian immunodeficiency virus (SIV) infected rhesus macaques, an established model for HIV infection. EBT-001 is an AAV9-based vector delivering SaCas9 and dual guide RNAs designed to target multiple regions of the SIV genome: the viral LTRs, and the Gag gene. The results presented here demonstrate that a single IV inoculation of EBT-001 at each of 3 dose levels (1.4 × 1012, 1.4 × 1013 and 1.4 × 1014 genome copies/kg) resulted in broad and functional biodistribution of AAV9-EBT-001 to known tissue reservoirs of SIV. No off-target effects or abnormal pathology were observed, and animals returned to their normal body weight after receiving EBT-001. Importantly, the macaques that received the 2 highest doses of EBT-001 showed improved absolute lymphocyte counts as compared to antiretroviral-treated controls. Taken together, these results demonstrate safety, biodistribution, and in vivo proviral DNA editing following IV administration of EBT-001, supporting the further development of CRISPR-based gene editing as a potential therapeutic approach for HIV in humans.

Molecular Features and Stages of Pulmonary Fibrosis Driven by Type 2 Inflammation.

Systemic sclerosis (SSc) is a progressive, multiorgan disease with limited treatment options. Although a recent proof-of-concept study using romilkimab or SAR156597, a bispecific IL-4/IL-13 antibody, suggests a direct role of these cytokines in the pathophysiology of SSc, their contributions to the balance between inflammation and fibrosis are unclear. Here, we determine the roles of type 2 inflammation in fibrogenesis using FRA2-Tg (Fos-related antigen 2-overexpressing transgenic) mice, which develop spontaneous, age-dependent progressive lung fibrosis. We defined the molecular signatures of inflammation and fibrosis at three key stages in disease progression, corresponding to preonset, inflammatory dominant, and fibrosis dominant biology, and revealed an early increase in cytokine-cytokine receptor interactions and antigen-processing and presentation pathways followed by enhanced Th2- and M2 macrophage-driven type 2 responses. This type 2 inflammation progressed to extensive fibrotic pathology by 14-18 weeks of age, with these gene signatures overlapping significantly with those seen in the lungs of patients with SSc with interstitial lung disease (ILD). These changes were also evident in the histopathology, which showed perivascular and peribronchiolar inflammation with prominent eosinophilia and accumulation of profibrotic M2-like macrophages followed by rapid progression to fibrosis with thickened alveolar walls with multifocal fibrotic bands and signs of interstitial pneumonia. Critically, treatment with a bispecific antibody targeting IL-4 and IL-13 during the inflammatory phase abrogated the Th2 and M2 responses and led to near-complete abrogation of lung fibrosis. These data recapitulate important features of fibrotic progression in the lungs of patients with SSc-ILD and enhance our understanding of the progressive pathobiology of SSc. This study also further establishes FRA2-Tg mice as a valuable tool for testing future therapeutic agents in SSc-ILD.

Sample Preparation for Rapid Lipid Analysis in Drosophila Brain using Matrix-assisted Laser Desorption/Ionization Mass Spectrometry Imaging.

Lipid profiling, or lipidomics, is a well-established technique used to study the entire lipid content of a cell or tissue. Information acquired from lipidomics is valuable in studying the pathways involved in development, disease, and cellular metabolism. Many tools and instrumentations have aided lipidomics projects, most notably various combinations of mass spectrometry and liquid chromatography techniques. Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI) has recently emerged as a powerful imaging technique that complements conventional approaches. This novel technique provides unique information on the spatial distribution of lipids within tissue compartments, which was previously unattainable without the use of excessive modifications. The sample preparation of the MALDI MSI approach is critical and, therefore, is the focus of this paper. This paper presents a rapid lipid analysis of a large number of Drosophila brains embedded in optimal cutting temperature compound (OCT) to provide a detailed protocol for the preparation of small tissues for lipid analysis or metabolite and small molecule analysis through MALDI MSI.

Anti-microRNA-21 Therapy on Top of ACE Inhibition Delays Renal Failure in Alport Syndrome Mouse Models.

Col4a3-/- Alport mice serve as an animal model for renal fibrosis. MicroRNA-21 (miR-21) expression has been shown to be increased in the kidneys of Alport syndrome patients. Here, we investigated the nephroprotective effects of Lademirsen anti-miR-21 therapy. We used a fast-progressing Col4a3-/- mouse model with a 129/SvJ background and an intermediate-progressing F1 hybrid mouse model with a mixed genetic background, with angiotensin-converting enzyme inhibitor (ACEi) monotherapy in combination with anti-miR-21 therapy. In the fast-progressing model, the anti miR-21 and ACEi therapies showed an additive effect in the reduction in fibrosis, the decline of proteinuria, the preservation of kidney function and increased survival. In the intermediate-progressing F1 model, the anti-miR-21 and ACEi therapies individually improved kidney pathology. Both also improved kidney function and survival; however, the combination showed a significant additive effect, particularly for survival. RNA sequencing (RNA-seq) gene expression profiling revealed that the anti-miR-21 and ACEi therapies modulate several common pathways. However, anti-miR-21 was particularly effective at normalizing the expression profiles of the genes involved in renal tubulointerstitial injury pathways. In conclusion, significant additive effects were detected for the combination of anti-miR-21 and ACEi therapies on kidney function, pathology and survival in Alport mouse models, as well as a strong differential effect of anti-miR-21 on the renal expression of fibrotic factors. These results support the addition of anti-miR-21 to the current standard of care (ACEi) in ongoing clinical trials in patients with Alport syndrome.

Blood phenylalanine reduction reverses gene expression changes observed in a mouse model of phenylketonuria.

Phenylketonuria (PKU) is a genetic deficiency of phenylalanine hydroxylase (PAH) in liver resulting in blood phenylalanine (Phe) elevation and neurotoxicity. A pegylated phenylalanine ammonia lyase (PEG-PAL) metabolizing Phe into cinnamic acid was recently approved as treatment for PKU patients. A potentially one-time rAAV-based delivery of PAH gene into liver to convert Phe into tyrosine (Tyr), a normal way of Phe metabolism, has now also entered the clinic. To understand differences between these two Phe lowering strategies, we evaluated PAH and PAL expression in livers of PAHenu2 mice on brain and liver functions. Both lowered brain Phe and increased neurotransmitter levels and corrected animal behavior. However, PAL delivery required dose optimization, did not elevate brain Tyr levels and resulted in an immune response. The effect of hyperphenylalanemia on liver functions in PKU mice was assessed by transcriptome and proteomic analyses. We observed an elevation in Cyp4a10/14 proteins involved in lipid metabolism and upregulation of genes involved in cholesterol biosynthesis. Majority of the gene expression changes were corrected by PAH and PAL delivery though the role of these changes in PKU pathology is currently unclear. Taken together, here we show that blood Phe lowering strategy using PAH or PAL corrects both brain pathology as well as previously unknown lipid metabolism associated pathway changes in liver.

Small RNA sequencing evaluation of renal microRNA biomarkers in dogs with X-linked hereditary nephropathy.

Dogs with X-linked hereditary nephropathy (XLHN) are an animal model for Alport syndrome in humans and progressive chronic kidney disease (CKD). Using mRNA sequencing (mRNA-seq), we have characterized the gene expression profile affecting the progression of XLHN; however, the microRNA (miRNA, miR) expression remains unknown. With small RNA-seq and quantitative RT-PCR (qRT-PCR), we used 3 small RNA-seq analysis tools (QIAGEN OmicSoft Studio, miRDeep2, and CPSS 2.0) to profile differentially expressed renal miRNAs, top-ranked miRNA target genes, and enriched biological processes and pathways in CKD progression. Twenty-three kidney biopsies were collected from 5 dogs with XLHN and 4 age-matched, unaffected littermates at 3 clinical time points (T1: onset of proteinuria, T2: onset of azotemia, and T3: advanced azotemia). We identified up to 23 differentially expressed miRNAs at each clinical time point. Five miRNAs (miR-21, miR-146b, miR-802, miR-142, miR-147) were consistently upregulated in affected dogs. We identified miR-186 and miR-26b as effective reference miRNAs for qRT-PCR. This study applied small RNA-seq to identify differentially expressed miRNAs that might regulate critical pathways contributing to CKD progression in dogs with XLHN.

Elevated protein synthesis in microglia causes autism-like synaptic and behavioral aberrations.

Mutations that inactivate negative translation regulators cause autism spectrum disorders (ASD), which predominantly affect males and exhibit social interaction and communication deficits and repetitive behaviors. However, the cells that cause ASD through elevated protein synthesis resulting from these mutations remain unknown. Here we employ conditional overexpression of translation initiation factor eIF4E to increase protein synthesis in specific brain cells. We show that exaggerated translation in microglia, but not neurons or astrocytes, leads to autism-like behaviors in male mice. Although microglial eIF4E overexpression elevates translation in both sexes, it only increases microglial density and size in males, accompanied by microglial shift from homeostatic to a functional state with enhanced phagocytic capacity but reduced motility and synapse engulfment. Consequently, cortical neurons in the mice have higher synapse density, neuroligins, and excitation-to-inhibition ratio compared to control mice. We propose that functional perturbation of male microglia is an important cause for sex-biased ASD.

ZIAQ: a quantile regression method for differential expression analysis of single-cell RNA-seq data.

MOTIVATION: Single-cell RNA sequencing (scRNA-seq) has enabled the simultaneous transcriptomic profiling of individual cells under different biological conditions. scRNA-seq data have two unique challenges that can affect the sensitivity and specificity of single-cell differential expression analysis: a large proportion of expressed genes with zero or low read counts ('dropout' events) and multimodal data distributions. RESULTS: We have developed a zero-inflation-adjusted quantile (ZIAQ) algorithm, which is the first method to account for both dropout rates and complex scRNA-seq data distributions in the same model. ZIAQ demonstrates superior performance over several existing methods on simulated scRNA-seq datasets by finding more differentially expressed genes. When ZIAQ was applied to the comparison of neoplastic and non-neoplastic cells from a human glioblastoma dataset, the ranking of biologically relevant genes and pathways showed clear improvement over existing methods. AVAILABILITY AND IMPLEMENTATION: ZIAQ is implemented in the R language and available at https://github.com/gefeizhang/ZIAQ. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Dysregulated Expression of microRNA-21 and Disease-Related Genes in Human Patients and in a Mouse Model of Alport Syndrome.

Alport syndrome is a genetic disease caused by mutations in type IV collagen and is characterized by progressive kidney disease. The Col4α3-/- mouse model recapitulates the main features of human Alport syndrome. Previously, it was reported that kidney microRNA-21 (miR-21) expression is significantly increased in Col4α3-/- mice, and administration of anti-miR-21 oligonucleotides (anti-miR-21) attenuates kidney disease progression in Col4α3-/- mice, indicating that miR-21 is a viable therapeutic target for Alport syndrome. However, the expression pattern of miR-21 in the kidneys of patients with human Alport syndrome has not been evaluated. Paraffin-embedded kidney specimens were obtained from 27 patients with Alport syndrome and from 10 normal controls. They were evaluated for miR-21 expression and for in situ hybridization and mRNA expression by quantitative polymerase chain reaction. In addition, anti-miR-21 was administrated to Col4α3-/- mice at different stages of disease, and changes in proteinuria, kidney function, and survival were monitored. Transcriptomic analysis of mouse kidney was conducted using RNA sequencing. miR-21 expression was significantly elevated in kidney specimens from patients with Alport syndrome compared to normal controls. Elevated renal miR-21 expression positively correlated with 24 h urine protein, serum blood urea nitrogen, serum creatinine, and severity of kidney pathology. On histological evaluation, high levels of miR-21 were localized to damaged tubular epithelial cells and glomeruli. Kidney specimens from both humans and mice with Alport syndrome exhibited abnormal expression of genes involved in kidney injury, fibrosis, inflammation, mitochondrial function, and lipid metabolism. Administration of anti-miR-21 to Alport mice resulted in slowing of kidney function decline, partial reversal of abnormal gene expression associated with disease pathology, and improved survival. Increased levels of miR-21 in human Alport kidney samples showed a correlation with kidney disease severity measured by proteinuria, biomarkers of kidney function, and kidney histopathology scores. These human data, combined with the finding that a reduction of miR-21 in Col4α3-/- mice improves kidney phenotype and survival, support miR-21 as a viable therapeutic target for the treatment of Alport syndrome.

An integrated hierarchical Bayesian approach to normalizing left-censored microRNA microarray data.

BACKGROUND: MicroRNAs (miRNAs) are small endogenous ssRNAs that regulate target gene expression post-transcriptionally through the RNAi pathway. A critical pre-processing procedure for detecting differentially expressed miRNAs is normalization, aiming at removing the between-array systematic bias. Most normalization methods adopted for miRNA data are the same methods used to normalize mRNA data; but miRNA data are very different from mRNA data mainly because of possibly larger proportion of differentially expressed miRNA probes, and much larger percentage of left-censored miRNA probes below detection limit (DL). Taking the unique characteristics of miRNA data into account, we present a hierarchical Bayesian approach that integrates normalization, missing data imputation, and feature selection in the same model. RESULTS: Results from both simulation and real data seem to suggest the superiority of performance of Bayesian method over other widely used normalization methods in detecting truly differentially expressed miRNAs. In addition, our findings clearly demonstrate the necessity of miRNA data normalization, and the robustness of our Bayesian approach against the violation of standard assumptions adopted in mRNA normalization methods. CONCLUSION: Our study indicates that normalization procedures can have a profound impact on the detection of truly differentially expressed miRNAs. Although the proposed Bayesian method was formulated to handle normalization issues in miRNA data, we expect that biomarker discovery with other high-dimensional profiling techniques where there are a significant proportion of left-censored data points (e.g., proteomics) might also benefit from this approach.

Stitching together multiple data dimensions reveals interacting metabolomic and transcriptomic networks that modulate cell regulation.

Cells employ multiple levels of regulation, including transcriptional and translational regulation, that drive core biological processes and enable cells to respond to genetic and environmental changes. Small-molecule metabolites are one category of critical cellular intermediates that can influence as well as be a target of cellular regulations. Because metabolites represent the direct output of protein-mediated cellular processes, endogenous metabolite concentrations can closely reflect cellular physiological states, especially when integrated with other molecular-profiling data. Here we develop and apply a network reconstruction approach that simultaneously integrates six different types of data: endogenous metabolite concentration, RNA expression, DNA variation, DNA-protein binding, protein-metabolite interaction, and protein-protein interaction data, to construct probabilistic causal networks that elucidate the complexity of cell regulation in a segregating yeast population. Because many of the metabolites are found to be under strong genetic control, we were able to employ a causal regulator detection algorithm to identify causal regulators of the resulting network that elucidated the mechanisms by which variations in their sequence affect gene expression and metabolite concentrations. We examined all four expression quantitative trait loci (eQTL) hot spots with colocalized metabolite QTLs, two of which recapitulated known biological processes, while the other two elucidated novel putative biological mechanisms for the eQTL hot spots.

Metabolomics in pharmaceutical research and development: metabolites, mechanisms and pathways.

In recent years, quantitative metabolomics has played increasingly important roles in pharmaceutical research and development. Metabolic profiling of biofluids and tissues can provide a panoramic view of abundance changes in endogenous metabolites to complement transcriptomics and proteomics in monitoring cellular responses to perturbations such as diseases and drug treatments. Precise identification and accurate quantification of metabolites facilitate downstream pathway and network analysis using software tools for the discovery of clinically accessible and minimally invasive biomarkers of drug efficacy and toxicity. Metabolite abundance profiles are also indicative of biochemical phenotypes, which can be used to identify novel quantitative trait loci in genome-wide association studies. This review summarizes recent experimental and computational efforts to improve the metabolomics technology as well as progress towards in-depth integration of metabolomics with other disparate 'omics datasets to build mechanistic models in the form of detailed and testable hypotheses.

Integrated pathway analysis of rat urine metabolic profiles and kidney transcriptomic profiles to elucidate the systems toxicology of model nephrotoxicants.

In this study, approximately 40 endogenous metabolites were identified and quantified by (1)H NMR in urine samples from male rats dosed with two proximal tubule toxicants, cisplatin and gentamicin. The excreted amount of a majority of those metabolites in urine was found to be dose-dependent and exhibited a strong correlation with histopathology scores of overall proximal tubule damage. MetaCore pathway analysis software (GeneGo Inc.) was employed to identify nephrotoxicant-associated biochemical changes via an integrated quantitative analysis of both urine metabolomic and kidney transcriptomic profiles. Correlation analysis was applied to establish quantitative linkages between pairs of individual metabolite and gene transcript profiles in both cisplatin and gentamicin studies. This analysis revealed that cisplatin and gentamicin treatments were strongly linked to declines in mRNA transcripts for several luminal membrane transporters that handle each of the respective elevated urinary metabolites, such as glucose, amino acids, and monocarboxylic acids. The integrated pathway analysis performed on these studies indicates that cisplatin- or gentamicin-induced renal Fanconi-like syndromes manifested by glucosuria, hyperaminoaciduria, lactic aciduria, and ketonuria might be better explained by the reduction of functional proximal tubule transporters rather than by the perturbation of metabolic pathways inside kidney cells. Furthermore, this analysis suggests that renal transcription factors HNF1alpha, HNF1beta, and HIF-1 might be the central mediators of drug-induced kidney injury and adaptive response pathways.