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Systematic Identification of the Optimal Housekeeping Genes for Accurate Transcriptomic and Proteomic Profiling of Tissues following Complex Traumatic Injury.

ABSTRACT: Trauma triggers critical molecular and cellular signaling cascades that drive biological outcomes and recovery. Variations in the gene expression of common endogenous reference housekeeping genes (HKGs) used in data normalization differ between tissue types and pathological states. Systematically, we investigated the gene stability of nine HKGs (Actb, B2m, Gapdh, Hprt1, Pgk1, Rplp0, Rplp2, Tbp, and Tfrc) from tissues prone to remote organ dysfunction (lung, liver, kidney, and muscle) following extremity trauma. Computational algorithms (geNorm, Normfinder, ΔCt, BestKeeper, RefFinder) were applied to estimate the expression stability of each HKG or combinations of them, within and between tissues, under both steady-state and systemic inflammatory conditions. Rplp2 was ranked as the most suitable in the healthy and injured lung, kidney, and skeletal muscle, whereas Rplp2 and either Hprt1 or Pgk1 were the most suitable in the healthy and injured liver, respectively. However, the geometric mean of the three most stable genes was deemed the most stable internal reference control. Actb and Tbp were the least stable in normal tissues, whereas Gapdh and Tbp were the least stable across all tissues post-trauma. Ct values correlated poorly with the translation from mRNA to protein. Our results provide a valuable resource for the accurate normalization of gene expression in trauma-related experiments.

SUBMITTER: Dragon AH

PROVIDER: S-EPMC10037587 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature

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Systematic Identification of the Optimal Housekeeping Genes for Accurate Transcriptomic and Proteomic Profiling of Tissues following Complex Traumatic Injury.

Dragon Andrea H AH Rowe Cassie J CJ Rhodes Alisha M AM Pak Olivia L OL Davis Thomas A TA Ronzier Elsa E

Methods and protocols 20230223 2

Trauma triggers critical molecular and cellular signaling cascades that drive biological outcomes and recovery. Variations in the gene expression of common endogenous reference housekeeping genes (HKGs) used in data normalization differ between tissue types and pathological states. Systematically, we investigated the gene stability of nine HKGs (Actb, B2m, Gapdh, Hprt1, Pgk1, Rplp0, Rplp2, Tbp, and Tfrc) from tissues prone to remote ...[more]

PMID: 36961042

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Project description:BackgroundThe recent development within high-throughput technologies for expression profiling has allowed for parallel analysis of transcriptomes and proteomes in biological systems such as comparative analysis of transcript and protein levels of tissue regulated genes. Until now, such studies of have only included microarray or short length sequence tags for transcript profiling. Furthermore, most comparisons of transcript and protein levels have been based on absolute expression values from within the same tissue and not relative expression values based on tissue ratios.ResultsPresented here is a novel study of two porcine tissues based on integrative analysis of data from expression profiling of identical samples using cDNA microarray, 454-sequencing and iTRAQ-based proteomics. Sequence homology identified 2.541 unique transcripts that are detectable by both microarray hybridizations and 454-sequencing of 1.2 million cDNA tags. Both transcript-based technologies showed high reproducibility between sample replicates of the same tissue, but the correlation across these two technologies was modest. Thousands of genes being differentially expressed were identified with microarray. Out of the 306 differentially expressed genes, identified by 454-sequencing, 198 (65%) were also found by microarray. The relationship between the regulation of transcript and protein levels was analyzed by integrating iTRAQ-based proteomics data. Protein expression ratios were determined for 354 genes, of which 148 could be mapped to both microarray and 454-sequencing data. A comparison of the expression ratios from the three technologies revealed that differences in transcript and protein levels across heart and muscle tissues are positively correlated.ConclusionWe show that the reproducibility within cDNA microarray and 454-sequencing is high, but that the agreement across these two technologies is modest. We demonstrate that the regulation of transcript and protein levels across identical tissue samples is positively correlated when the tissue expression ratios are used for comparison. The results presented are of interest in systems biology research in terms of integration and analysis of high-throughput expression data from mammalian tissues.

Project description:Traumatic brain injury (TBI) is a primary cause of disability and death across the world. Previously, RNA analysis was widely used to study the pathophysiological mechanisms underlying TBI; however, the relatively low correlation between the transcriptome and proteome revealed that RNA transcription abundance does not reliably predict protein abundance, which led to the emergence of proteomic research. In this study, an iTRAQ proteomics approach was applied to detect protein alterations after TBI on a large scale. A total of 3937 proteins were identified, and 146 proteins were significantly changed after TBI. Moreover, 23 upregulated proteins were verified by parallel reaction monitoring (PRM), and fold changes in 16 proteins were consistent with iTRAQ outcomes. Transthyretin (Ttr) upregulation has been demonstrated at the transcriptional level, and this study further confirmed this at the protein level. After treatment with thyroxine (T4), which is transported by Ttr, the effects of T4 on neuronal histopathology and behavioral performance were determined in vivo (TBI + T4 group). Brain edema was alleviated, and the integrity of the blood brain barrier (BBB) improved. Escape latency in the Morris water maze (MWM) declined significantly compared with the group without T4 treatment. Modified neurological severity scores (mNSS) of the TBI + T4 group decreased from day 1 to day 7 post-TBI compared with the TBI + saline group. These results indicate that T4 treatment has potential to alleviate pathologic and behavioral abnormalities post-TBI. Protein alterations after T4 treatment were also detected by iTRAQ proteomics. Upregulation of proteins like Lgals3, Gfap and Apoe after TBI were reversed by T4 treatment. GO enrichment showed T4 mainly affected intermediate filament organization, cholesterol transportation and axonal regeneration. In summary, iTRAQ proteomics provides information about the impact of TBI on protein alterations and yields insight into underlying mechanisms and pathways involved in TBI and T4 treatment. Finally, Ttr and other proteins identified by iTRAQ may become potential novel treatment targets post-TBI.

Dataset Information

Systematic Identification of the Optimal Housekeeping Genes for Accurate Transcriptomic and Proteomic Profiling of Tissues following Complex Traumatic Injury.

Publications

Systematic Identification of the Optimal Housekeeping Genes for Accurate Transcriptomic and Proteomic Profiling of Tissues following Complex Traumatic Injury.

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