Considerations for mass spectrometry-based multi-omic analysis of clinical samples

Relative quantification of progressive changes in healthy and dysferlin-deficient mouse skeletal muscle proteomes

INTRODUCTION/AIMS

Individuals with dysferlinopathies, a group of genetic muscle diseases, experience delay in the onset of muscle weakness. The cause of this delay and subsequent muscle wasting are unknown, and there are currently no clinical interventions to limit or prevent muscle weakness. To better understand molecular drivers of dysferlinopathies, age-dependent changes in the proteomic profile of skeletal muscle (SM) in wild-type (WT) and dysferlin-deficient mice were identified.

METHODS

Quadriceps were isolated from 6-, 18-, 42-, and 77-wk-old C57BL/6 (WT, Dysf+/+ ) and BLAJ (Dysf-/- ) mice (n = 3, 2 male/1 female or 1 male/2 female, 24 total). Whole-muscle proteomes were characterized using liquid chromatography-mass spectrometry with relative quantification using TMT10plex isobaric labeling. Principle component analysis was utilized to detect age-dependent proteomic differences over the lifespan of, and between, WT and dysferlin-deficient SM. The biological relevance of proteins with significant variation was established using Ingenuity Pathway Analysis.

RESULTS

Over 3200 proteins were identified between 6-, 18-, 42-, and 77-wk-old mice. In total, 46 proteins varied in aging WT SM (p < .01), while 365 varied in dysferlin-deficient SM. However, 569 proteins varied between aged-matched WT and dysferlin-deficient SM. Proteins with significant variation in expression across all comparisons followed distinct temporal trends.

DISCUSSION

Proteins involved in sarcolemma repair and regeneration underwent significant changes in SM over the lifespan of WT mice, while those associated with immune infiltration and inflammation were overly represented over the lifespan of dysferlin-deficient mice. The proteins identified herein are likely to contribute to our overall understanding of SM aging and dysferlinopathy disease progression.

Congenital cataracts affect the retinal visual cycle and mitochondrial function: A multi-omics study of GJA8 knockout rabbits

Congenital cataracts are a threat to visual development in children, and the visual impairment persists after surgical treatment; however, the mechanisms involved remain unclear. Previous clinical studies have identified the effect of congenital cataracts on retinal morphology and function. To further understand the molecular mechanisms by which congenital cataracts affect retinal development, we analyzed retina samples from 7-week-old GJA8-knockout rabbits with congenital cataracts and controls by four-dimensional label-free quantification proteomics and untargeted metabolomics. Bioinformatics analysis of proteomic data showed that retinol metabolism, oxidative phosphorylation, and fatty acid degradation pathways were downregulated in the retinas of rabbits with congenital cataracts, indicating that their visual cycle and mitochondrial function were affected. Additional validation of differentially abundant proteins related to the visual cycle and mitochondrial function was performed using Parallel reaction monitoring and western blot experiments. Untargeted metabolome analysis showed significant upregulation of the antioxidant glutathione and ascorbic acid in the retinas of rabbits with congenital cataracts, indicating that their oxidative stress balance was not dysregulated. SIGNIFICANCE: Congenital cataracts in children can alter retinal structure and function, yet the mechanisms are uncertain. Here is the first study to use proteomics and metabolomics approaches to investigate the effects of congenital cataracts on retinal development in the early postnatal period. Our findings suggest that congenital cataracts have an impact on the retinal visual cycle and mitochondrial function. These findings give insight on the molecular pathways behind congenital cataract-induced visual function impairment in the early postnatal period.

Proteomes Are of Proteoforms: Embracing the Complexity

Proteomes are complex-much more so than genomes or transcriptomes. Thus, simplifying their analysis does not simplify the issue. Proteomes are of proteoforms, not canonical proteins. While having a catalogue of amino acid sequences provides invaluable information, this is the Proteome-lite. To dissect biological mechanisms and identify critical biomarkers/drug targets, we must assess the myriad of proteoforms that arise at any point before, after, and between translation and transcription (e.g., isoforms, splice variants, and post-translational modifications [PTM]), as well as newly defined species. There are numerous analytical methods currently used to address proteome depth and here we critically evaluate these in terms of the current 'state-of-the-field'. We thus discuss both pros and cons of available approaches and where improvements or refinements are needed to quantitatively characterize proteomes. To enable a next-generation approach, we suggest that advances lie in transdisciplinarity via integration of current proteomic methods to yield a unified discipline that capitalizes on the strongest qualities of each. Such a necessary (if not revolutionary) shift cannot be accomplished by a continued primary focus on proteo-genomics/-transcriptomics. We must embrace the complexity. Yes, these are the hard questions, and this will not be easy…but where is the fun in easy?