Systematic dissection, preservation, and multiomics in whole human and bovine hearts

Abstract

Objectives: We sought to develop a rigorous, systematic protocol for the dissection and preservation of human hearts for biobanking that expands previous success in postmortem transcriptomics to multiomics from paired tissue.

Background: Existing cardiac biobanks consist largely of biopsy tissue or explanted hearts in select diseases and are insufficient for correlating whole organ phenotype with clinical data.

Methods: We demonstrate optimal conditions for multiomics interrogation (ribonucleic acid (RNA) sequencing, untargeted metabolomics) in hearts by evaluating the effect of technical variables (storage solution, temperature) and simulated postmortem interval (PMI) on RNA and metabolite stability. We used bovine (n=3) and human (n=2) hearts fixed in PAXgene or snap-frozen with liquid nitrogen.

Results: Using a paired Wald test, only two of the genes assessed were differentially expressed between left ventricular samples from bovine hearts stored in PAXgene at 0 and 12 hours PMI (FDR q<0.05). We obtained similar findings in human left ventricular samples, suggesting stability of RNA transcripts at PMIs up to 12 hours. Different library preparation methods (mRNA poly-A capture vs. rRNA depletion) resulted in similar quality metrics with both library preparations achieving >95% of reads properly aligning to the reference genomes across all PMIs for bovine and human hearts. PMI had no effect on RNA Integrity Number or quantity of RNA recovered at the time points evaluated. Of the metabolites identified (855 total) using untargeted metabolomics of human left ventricular tissue, 503 metabolites remained stable across PMIs (0, 4, 8, 12 hours). Most metabolic pathways retained several stable metabolites.

Conclusions: Our data demonstrate a technically rigorous, reproducible protocol that will enhance cardiac biobanking practices and facilitate novel insights into human CVD.

Condensed abstract: Cardiovascular disease (CVD) is the leading cause of mortality worldwide. Current biobanking practices insufficiently capture both the diverse array of phenotypes present in CVDs and the spatial heterogeneity across cardiac tissue sites. We have developed a rigorous and systematic protocol for the dissection and preservation of human cardiac biospecimens to enhance the availability of whole organ tissue for multiple applications. When combined with longitudinal clinical phenotyping, our protocol will enable multiomics in hearts to deepen our understanding of CVDs.

Keywords: Biobank; Cardiovascular; Metabolomics; Multiomics; Postmortem interval; RNA-Seq.

Fig. 1.

Schematic illustration of the cardiac dissection workflow. Repeated sampling was performed from 2 human and 3 bovine hearts stored in either phosphate buffered saline or cardioplegic solution during a simulated postmortem interval (PMI). Following the PMI, samples were either flash frozen or fixed in the PAXgene preservation system and then stored at −80 °C. RNA sequencing was performed on an Illumina NextSeq 500 machine using RNA isolated from both flash frozen and PAXgene fixed human and bovine cardiac tissue. Unbiased metabolomics was also performed on flash frozen human and bovine cardiac tissue for evaluation of metabolite stability.

Fig. 2.

Illustrative dissection of a bovine heart for multiomics. A bovine heart was dissected, creating 7 transverse slices from the apex to 2 cm below the atrioventricular valves (A). Slices are numerically ordered from apex to base. Transverse slice 1 consists of the apex; slice 2 contains the apical most portion of the interventricular septum and left ventricle; slice 3 consists of the superior portion of the apex and ventricular tissue of both left and right ventricles; slice 4 consists of the apical-most mid-ventricular tissue; slice 5 consists of the basal-most mid-ventricular tissue; slice 6 contains the apical-most portion of the base below the atrioventricular valves; and slice 7 contains the basal-most portion of the base just below the atrioventricular valves. The base of the heart consisting of the atria and proximal major vessels was further dissected along the lines of flow (not pictured). The preservation methods and the scientific applications afforded for each transverse slice are detailed.(B).

Fig. 3.

RNA quality control metrics in human and bovine cardiac samples. Total ribonucleic acid (RNA) recovered from human left ventricle (LV) and right ventricle (RV), and bovine LV tissue normalized to tissue wet weight was evaluated across several postmortem intervals (PMI) (A). A260:280nm ratios were measured in RNA recovered from human LV and RV and bovine LV samples across several PMIs (B). RNA integrity number (RIN) for human and bovine LV samples across several PMIs was assessed (C). n=2–3/group, ^∗P<.05 using repeated measures one-way analysis of variance (ANOVA) with post-hoc Tukey’s test compared to lowest PMI baseline within each group.

Fig. 4.

Principal component analysis (PCA) of human and bovine RNA-Seq samples across multiple cardiac sites and over varying postmortem intervals (PMI). PCA of two human heart samples (H1, H2) before (A) and after adjusting for subject as a covariate (B) shows most of the variance is explained by subject. PCA of two human heart samples (H1, H2) excluding right ventricle 8 hour PMI before (C) and after adjusting for subject as a covariate (D) shows most of the variance is still explained by subject. PCA of three bovine heart samples (B1, B2, B3) before (E) and after adjusting for subject as a covariate (F) shows that most of the variance is explained by inter-individual difference followed by PMI and cardiac site. N=2–3 samples/group/timepoint

Fig. 5.

Metabolomics data revealing differentially expressed pathways in a heatmap and principal component analysis (PCA) of metabolites in human cardiac samples over multiple postmortem intervals (PMI). Heatmap displaying relative metabolite abundance in multiple metabolic pathways in human cardiac tissue across PMIs of 4, 6, and 12 hours shows that 58% (503 of 855 metabolites identified), do not significantly change across PMIs (compared to 0 hours) (A). PCA of human cardiac samples revealed that inter-individual differences and PMI were the greatest contributors to sample variation across PMIs (B).