Project description:Recent efforts towards the comprehensive identification of RNA-bound proteomes have revealed a large, surprisingly diverse family of candidate RNA-binding proteins (RBPs). Quantitative metrics for characterization and validation of protein-RNA interactions and their dynamic interactions have, however, proven to be analytically challenging and prone to error. Here we report a novel method termed LEAP-RBP for the selective, quantitative recovery of UV-crosslinked RNA-protein complexes. By virtue of its high specificity and yield, LEAP-RBP distinguishes RNA-bound and RNA-free protein levels and reveals common sources of experimental noise in RNA-centric RBP enrichment methods. We introduce new strategies for accurate RBP identification and signal-based metrics for quantifying protein-RNA complex enrichment, relative RNA occupancy, and method specificity. The utility of our approach is validated by comprehensive identification of RBPs whose association with mRNA is modulated in response to global mRNA translation state changes and through in-depth benchmark comparisons with current methodologies.
Project description:Recent efforts towards the comprehensive identification of RNA-bound proteomes have revealed a large, surprisingly diverse family of candidate RNA-binding proteins (RBPs). Quantitative metrics for characterization and validation of protein-RNA interactions and their dynamic interactions have, however, proven analytically challenging and prone to error. Here we report a method termed LEAP-RBP (Liquid-Emulsion-Assisted-Purification of RNA-Bound Protein) for the selective, quantitative recovery of UV-crosslinked RNA-protein complexes. By virtue of its high specificity and yield, LEAP-RBP distinguishes RNA-bound and RNA-free protein levels and reveals common sources of experimental noise in RNA-centric RBP enrichment methods. We introduce strategies for accurate RBP identification and signal-based metrics for quantifying protein-RNA complex enrichment, relative RNA occupancy, and method specificity. In this work, the utility of our approach is validated by comprehensive identification of RBPs whose association with mRNA is modulated in response to global mRNA translation state changes and through in-depth benchmark comparisons with current methodologies.
Project description:To minimize the distortion of genetic signal by system noise, we have explored the latter in an archive of hybridizations in which no genetic signal is expected. This archive is obtained by comparative genomic hybridization (CGH) of a reference sample in one channel to the same sample in the other channel, which we have termed ‘self-self’ data. We show that these self-self hybridizations trap a variety of system noise inherent in sample-reference (test) data. Through singular value decomposition (SVD) of self-self data, we are able to determine the principal components of system noise. Assuming simple linear models of noise generation, we present evidence that the linear correction of test data with self-self data—which we call system normalization—reduces local and long-range correlations as well as improves signal-to-noise metrics, yet does not introduce detectable spurious signal.
Project description:Spatial transcriptomics is a rapidly advancing field, yet it lacks standardized metrics for evaluating imaging-based in situ hybridization technologies. In this study, we emphasize the importance of rigorous experimental design and standardized operating procedures (SOPs) in defining performance metrics across multiple modalities—from single-cell to spatial transcriptomics to spatial proteomics. Our Spatial Touchstone (ST) dataset, generated from six tissue types across three global sites (n=76 assays), provides a comprehensive evaluation of reproducibility, sensitivity, dynamic ranges, signal-to-noise ratio, false discovery rates, cell type annotation, and congruence with single-cell profiling. Using single-nucleus RNA sequencing (snRNA-seq) on the same formalin-fixed paraffin-embedded tissues, we created a reference for transcriptional profiles to assess cellular organization and biomarker localization. In the absence of an independent 'gold standard’ in the field, this study provides an objective assessment of technical performance through standardized protocols, Spatial Touchstone Protocols (STSOP). Our open-source software, SpatialQC, allows users to evaluate samples across all technical metrics and directly impute cell annotations from single-cell datasets. This study features the largest imaging-based spatial transcriptomics data repository available, with a total of 203 spatial profiles. It incorporates both public (n=127) and ST datasets (n=76) through the Spatial Touchstone Portal (STP), available at www.spatialtouchstone.org. This resource offers users easy access to analyze and compare their own data against an extensive collection of imaging-based datasets. We show that the ST datasets demonstrate high reproducibility (r=0.93 to 1.0) and set a new benchmark for the field. Finally, we establish metrics to evaluate and integrate imaging based multi omics data from single cell into spatial transcriptomics to spatial proteomics. The ST project provides a comprehensive, reproducible assessment across platforms and sites, establishing essential standards for imaging-based spatial multi omics (transcriptomics and proteomics) and paving the way for future research and technological advancements.
Project description:The molecular mechanisms underlying the great differences in susceptibility to noise-induced hearing loss (NIHL) exhibited by both humans and laboratory animals are unknown. Using microarray technology, the present study demonstrates that the effects of noise overexposure on the expression of molecules likely to be important to the development of NIHL differ among inbred mice that have distinctive susceptibilities to NIHL including B6.CAST, 129X1/SvJ, and 129S1/SvImJ. The noise-exposure protocol produced, on average, a permanent loss of about 40 dB in sensitivity for auditory brainstem responses in susceptible B6.CAST mice, but no threshold elevations for the two resistant 129S1/SvImJ and 129X1/SvJ substrains. Measurements of noise-induced gene expression changes 6 h after the noise exposure revealed significant alterations in the expression levels of 48 genes in the resistant mice, while by these same criteria, there were seven differentially expressed genes in the susceptible B6.CAST mice. Differentially expressed genes in both groups of mice included subsets of transcription factors. However, only in the resistant mice was there a significant induction of proteins involved in cell-survival pathways such as HSP70, HSP40, p21, GADD45ï¢, Ier3, and Nfï«ï¢iïº. Moreover, increased expression of three of these factors after noise was confirmed at the protein level. Drastically enhanced HSP70, GADD45ï¢, and p21 immunostaining were detected 6 h after the noise exposure in subsets of cells of the lateral wall, spiral limbus, and organ of Corti as well as in cochlear nerve fibers. Upregulation of these proteins after noise exposure likely contributes to the prevalence of survival cellular pathways and thus to the resistance to NIHL that is characteristic of the 129X1/SvJ mice. Experiment Overall Design: Female 10-wk-old mice of the B6.CAST and 129X1/SvJ strains were divided randomly into non-noise control and noise-exposure groups. The non-noise mice served as controls in the gene-profiling experiments to control for the stress induced by experimenter handling and/or confinement of the mice in the noise-exposure chamber that was not directly related to the noise. This mice were in the noise chamber for a sham exposure. In contrast, the ânoiseâ groups were exposed to a 105-dB SPL, 10-kHz octave band of noise for 1 h and sacrificed 6 h after the exposure. Of each of these major groups, eight mice were used for each of three 129X1/SvJ control and three noise-exposed 129X1/SvJ arrays and two B6.CAST control and two noise-exposed B6.CAST arrays. Consequently within each subgroup the arrays are biological replicates.
Project description:Intrinsic biological fluctuation and/or measurement error can obscure the association of gene expression patterns between RNA and protein levels. Appropriate normalisation of reverse-transcription quantitative PCR (RT-qPCR) data can reduce technical noise in transcript measurement, thus uncovering such relationships. The accuracy of gene expression measurement is often challenged in the context of cancer due to its genetic instability and ‘splicing weakness’. Here we sequenced the poly(A) cancer transcriptome of canine osteosarcoma using mRNA-Seq. Expressed sequences were resolved at the level of two consecutive exons to enable the design of exon-border spanning RT-qPCR assays and ranked for stability based on the coefficient of variation (CV). Using the same template type for RT-qPCR validation, i.e. poly(A) RNA, avoided skewing of stability assessment by circular RNAs (circRNAs) and/or rRNA deregulation. The strength of the relationship between mRNA expression of the tumour marker S100A4 and its proportion score of quantitative immunochemistry (qIHC) was introduced as an experimental read-out to fine-tune the normalisation choice. Together with the essential logit transformation of qIHC scores, this approach reduced the noise of measurement as demonstrated by uncovering a highly significant, strong association between mRNA and protein expressions of S100A4 (Spearman's coefficient r = 0.72 (p = 0.006)).
Project description:Environmental stressors present in the modern world can have a fundamental effect on the physiology and health of humans. Exposure to stressors like air pollution, heat and traffic noise has been linked to a pronounced increase in non-communicable diseases. Specifically, aircraft noise has been identified as a risk factor for cardiovascular and metabolic diseases, such as arteriosclerosis, heart failure, stroke and diabetes. Noise stress leads to neuronal activation with subsequent stress hormone release that ultimately leads to activation of the renin-angiotensin-aldosterone system, increasing inflammation and oxidative stress, with dramatic effects on the cardiovascular system. However, despite the epidemiological evidence of a link between noise stress and metabolic dysfunction, the consequences of exposure at the molecular, metabolic level of the cardiovascular system are largely unknown. Here we use a murine model system of aircraft noise exposure to show that noise stress profoundly alters heart metabolism. Within days of exposing animals to aircraft noise the heart has a reduced potential for utilising fatty-acid beta-oxidation, the tricarboxylic acid cycle, and the electron transport chain for generating ATP. This is compensated by shifting energy production towards glycolysis. Intriguingly, the metabolic shift is reminiscent of what is observed in failing and ischaemic hearts. Our results demonstrate that within a relatively short exposure time, the cardiovascular system undergoes a fundamental metabolic shift that bears the hallmarks of cardiovascular disease. Overall, aircraft noise induces rapid, detrimental metabolic shifts in the heart, resembling patterns seen in cardiovascular diseases. These findings underscore the urgent need to comprehend molecular consequences of environmental stressors, paving the way for targeted interventions aiming mitigating health risks associated with chronic noise exposure in our modern, noisy environments.
Project description:The molecular mechanisms underlying the great differences in susceptibility to noise-induced hearing loss (NIHL) exhibited by both humans and laboratory animals are unknown. Using microarray technology, the present study demonstrates that the effects of noise overexposure on the expression of molecules likely to be important to the development of NIHL differ among inbred mice that have distinctive susceptibilities to NIHL including B6.CAST, 129X1/SvJ, and 129S1/SvImJ. The noise-exposure protocol produced, on average, a permanent loss of about 40 dB in sensitivity for auditory brainstem responses in susceptible B6.CAST mice, but no threshold elevations for the two resistant 129S1/SvImJ and 129X1/SvJ substrains. Measurements of noise-induced gene expression changes 6 h after the noise exposure revealed significant alterations in the expression levels of 48 genes in the resistant mice, while by these same criteria, there were seven differentially expressed genes in the susceptible B6.CAST mice. Differentially expressed genes in both groups of mice included subsets of transcription factors. However, only in the resistant mice was there a significant induction of proteins involved in cell-survival pathways such as HSP70, HSP40, p21, GADD45beta, Ier3, and Nf-kappaB. Moreover, increased expression of three of these factors after noise was confirmed at the protein level. Drastically enhanced HSP70, GADD45beta, and p21 immunostaining were detected 6 h after the noise exposure in subsets of cells of the lateral wall, spiral limbus, and organ of Corti as well as in cochlear nerve fibers. Upregulation of these proteins after noise exposure likely contributes to the prevalence of survival cellular pathways and thus to the resistance to NIHL that is characteristic of the 129X1/SvJ mice. Keywords: effects of noise exposure in distinct inbred mice