key: cord-0870625-iqrfi06u
authors: Silverstein, Affiliations Ana R.; Flores, Melanie; Miller, Brendan; Kim, Su-Jeong; Yen, Kelvin; Mehta, Hemal H.; Cohen, Pinchas
title: Mito-Omics and immune function: Applying novel mitochondrial omic techniques to the context of the aging immune system
date: 2020-08-21
journal: Transl Med Aging
DOI: 10.1016/j.tma.2020.08.001
sha: 16208527e08a23b2f9f615065f6767b5d6ff058e
doc_id: 870625
cord_uid: iqrfi06u

Recent advancements in genomic, transcriptomic, proteomic, and metabolomic techniques have prompted fresh inquiry in the field of aging. Here, we outline the application of these techniques in the context of the mitochondrial genome and suggest their potential for use in exploring the biological mechanisms of the aging immune system.

the future application of Mito-Omics in studying the aging immune system. 26

Next generation sequencing was a paradigm shifter for not only the aging field 29 but life sciences in general. With the ability to sequence individual human genomes, 30 population geneticists have been able to identify novel genomic variants that associate 31 with certain diseases and conditions. One such analytical method is Genome-Wide 32

Association Study (GWAS), an experimental protocol designed to identify associations 33 between genetic variants and traits of interest in a given population. Since its 34 development, GWAS has been used to identify novel single nucleotide polymorphisms 35 (SNPs) that map back to genes involved in the pathology of many diseases of interest 36

(1-3). Most GWAS pipelines have used SNP-based-arrays to generate millions of 37 genotypes, but high-throughput next generation whole genome sequencing can now be 38 used to identify extremely rare SNPs in regions of the genome that have historically 39 been missed (e.g., introns, small open reading frame microproteins, etc.) (4). GWAS 40 has indeed identified genome variants that associate with disease, but GWAS is mostly 41 focused on nuclear genes, overlooking an opportunity for biological analysis that lies 42 within the mitochondrial genome. 43

The maternally inherited mitochondrial genome (mtDNA) consists of a subset of 44 genes that, although small in number, are mighty in their contributions to proper cell 45 function. Collectively, the compact mtDNA encodes 13 proteins, 22 tRNAs, 2 rRNAs, 46 and a growing list of microproteins (5). Together, these genes actively regulate cellular 47 damage and its absence of effective DNA repair mechanisms, mtDNA is prone to much 49 higher rates of somatic mutation than the nuclear genome (6). These mutations often 50 lead to mitochondrial dysfunction, making them an important genetic contributor to 51 many diseases of aging (8, 9) . However, the extent to which inherited mtDNA SNPs 52 (mtSNPs) contribute to disease risk remains unclear. 53

By adapting the GWAS experimental design to target mtDNA it is possible to 54 identify novel mtSNPs that associate with diseases, especially diseases with a 55 metabolic pathology (e.g., Alzheimer's disease, diabetes, etc.); we have named this 56 experimental approach Mitochondrial-wide Association Study (MiWAS) (9,10). Since 57 most SNP-based-arrays only capture roughly a hundred mtSNPs, implementing whole 58 mtDNA sequencing may reveal a set of mtSNPs that have previously remained 59 unidentified, expanding our considerations for biological contributors to disease (10). 60

Nevertheless, challenges specific to mitochondrial genetics leave uncertainty in the 61 findings of MiWAS. 62

One MiWAS challenge is mitochondrial heteroplasmy. Hundreds of copies of 63 mtDNA are present in each cell, with variances in the number and types of mtDNA 64 mutations present within each copy of the mitochondrial genome (i.e., heteroplasmy). 65

Due to heteroplasmy, it can be difficult to assess the overall impact of a mtSNP on cell 66 function, as the identified mutation may only be present in some but not all 67 mitochondrial genomes, and thus may only be affecting some but not all mitochondria 68 within a cell. (11, 12 pathology. However, when utilizing mito-transcriptomics techniques, the structure and 108 replication behavior of mtDNA must be taken into account. One important evaluation 109 method for mtDNA that addresses its unique structure involves identifying the strand-110 specific transcription patterns of genes of interest (28). Within its structural 111 arrangement, the mtDNA has genes encoded on both the heavy and light-strand of its 112 genome. Collectively, mtDNA contains 28 genes on the heavy-strand, and 9 on the 113 light-strand. Therefore, when evaluating mtDNA transcription patterns, distinguishing 114 between strands may play an important role in identifying its unknown genetic 115 contributors to disease (29). To evaluate this pattern, sequence markers or adapters 116

can be used distinguish one strand from another when compiling transcriptomic 117 information (28, 30). Applying these methods to the mitochondrial genome helps 118 confirm the location of genes of interest, further enhancing our understanding of mtSNP 119 expression patterns. Such methods might be used to identify the transcriptome of small 120 open reading frames (smORFs) that encode for mitochondrial-derived peptides, which 121 are bioactive peptides involved in cellular metabolism. The use of high-throughput 122 sequencing methods has also improved our understanding of mitochondrial interactions between mtDNA and disease pathology. 127

Additionally, while the field of mitochondrial epigenetics is still emerging, there is 128 evidence that mtDNA undergoes methylation (31), and that this can affect the 129 expression of mitochondrial-derived peptides (32).Through transcriptomic analysis, the loop may play a pivotal role in early-onset AD pathogenesis. This study is one of few 141 that explore this potential correlation, further expanding on an important potential 142 contributor to AD development. 143

Utilizing emerging techniques in transcriptomic analysis to understand the role of 144 mtDNA transcript levels in disease pathogenesis is of increasing importance for many 145 age-related diseases. However, to holistically assess changes in gene expression, both 146 transcript levels and protein levels must be measured; to do so, proteomic analysis is 147 required.

Expanding on the findings from the transcriptome, proteomic analysis uses both 150 computational and experimental techniques to identify proteins of interest, distinguishing 151 between coding and non-coding regions of the genome (35). Just as transcriptomics 152 confirms differential transcript expression associated with disease, proteomics can be 153 used to confirm differential protein expression associated with disease. Thus, proteomic NMR spectroscopy is a high-throughput, nondestructive, nonbiased, and easily 234 biomarkers and have proven to be valuable tools for incorporating metabolomic data 241 into the promising field of precision medicine. In one such application, researchers 242 utilized the results from metabolomic analysis to identify changes in metabolic enzymes 243 associated with alterations in various oncogenes (50). Applying similar techniques to the 244 context of the mitochondrial metabolome may also prove to be beneficial in designing 245 novel therapeutics to address many diseases of aging. 246

Mitochondria play a vital role in many metabolic processes. Analyzing the 247 mitochondrial metabolome is an important part of developing a holistic understanding of 248 the role of mitochondrial function in age-related diseases. More specifically, 249 mitochondrial metabolomics may further refine our understanding of the underlying 250 biology involving mitochondrial peptides (51). We recently applied a mito-metabolomics 251 approach to assess the effect of two mitochondrially-derived peptides (MDPs), humanin 252 (HNG) and small-humanin-like peptide 2 (SHLP2), on metabolic pathways in mice 253 models. Results showed that treatment with HNG or SHLP2 led to a reduction in the 254 production of many metabolic intermediates involved in the glutathione cycle and 255 sphingolipid pathways, which have been identified as important metabolic pathways 256 associated with cancer and tumor development, and aging, diabetes, and obesity, 257 respectively (7). Identifying the effects of these MDPs on key metabolic pathways not 258 only improves our understanding of the mitochondrial role in disease pathology, but also 259 highlights the potential therapeutic function of MDPs that may be utilized in the future. 260

However, as with mitochondrial proteomics, effectively utilizing common metabolomic 261 analytical tools for mitochondrial metabolome analysis will primarily require their When combined with genomics, transcriptomics, and proteomics, mitochondrial 264 metabolomics will further contribute to the future design of novel therapeutics involved 265 in treating many diseases of aging. 266

A recently proposed contributor to many diseases of aging is 269 immunosenescence; a term coined for the observed dysregulation in immune system oligomers that were present in the AD brain were also shown to contribute to synapse 293 deterioration and memory impairment (60) Impaired immune function also contributes to 294 cancer development. Immunosenescence causes defects in naive memory T-cell 295 populations that impair the immune system's ability to mount responses against tumor 296 cells (61). Additionally, terminally differentiated CD8 + T cells with diminished 297 functionality exhibit increased cytokine production which contributes to a 298 proinflammatory state that may stimulate tumor development (62). 299

The immune system network is intricate and complex, and thus many 300 contributors to immunosenescence remain undiscovered. However, novel cellular 301 mechanisms associated with immune function are frequently being exposed. Many of 302 these mechanisms link back to the powerhouses of the cell, the mitochondria. 303

Mitochondria play a key role in regulating the immune system, and thus 305 potentially play an important role in immune dysfunction and associated age-related 306 diseases. Many innate immune system pathways are stimulated through mtDNA. After 307 cell damage, mtDNA is released and directly activates Toll-like receptor 9 (TLR9), 308 1β, and MMP-8 (63). Cytosolic mtDNA also plays a key role in activating Nod-like 310 receptor 3 (NLRP3), stimulating caspase-1 and facilitating IL-1β and IL-18 maturation 311 and proinflammatory cell death of sentinel cells in the innate immune system (64) . (66). Another mitochondrial peptide, humanin, also has anti-inflammatory effects (67, 68). 318

In adaptive immunity, mitochondria are also necessary for maintaining Regulatory T cell 319 (T reg cells) function. T reg cells are essential for maintaining self-tolerance in the adaptive 320 immune system (69, 70). T reg cells require mitochondrial complex III to preserve proper 321

Mitochondrial components thus act to both stimulate and preserve proper immune 323 function (Fig 2) . Age-associated damage to these mitochondrial components of interest 324 may be a critical contributor to observed immunosenescence. 325

Proper immune system function is a vital contributor to healthy aging. The critical 328 role that immune dysfunction may play in disease pathology is important to consider. 

of biological mechanisms contributing to many diseases of aging. Expanding these 429 techniques to consider mtDNA for Mito-Omics will enable a more extensive analysis of 430 the biological contributors to age-related diseases. Advancements in specialized 431 genomic, transcriptomic, proteomic, and metabolomic techniques for mtDNA analysis 432 that account for its unique structure and function will be vital for accurately identifying its 433 contributions to age-related diseases, including the aging immune system. 

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The mitochondrial-derived peptide MOTS-c is a regulator of plasma 621 metabolites and enhances insulin sensitivity

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Humanin preserves endothelial 668 function and prevents atherosclerotic plaque progression in hypercholesterolemic 669

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