Chapter 3 - Omics approaches in aging research

BackgroundThe genus Allium (Family: Amaryllidaceae) is an economically important group of crops cultivated worldwide for their use as a vegetable and spices. Alliums are also well known for their nutraceutical properties. Among alliums, onion, garlic, leek, and chives cultivated worldwide. Despite their substantial economic and medicinal importance, the genome sequence of any of the Allium is not available, probably due to their large genome sizes. Recently evolved omics technologies are highly efficient and robust in elucidating molecular mechanisms of several complex life processes in plants. Omics technologies, such as genomics, transcriptomics, proteomics, metabolomics, metagenomics, etc. have the potential to open new avenues in research and improvement of allium crops where genome sequence information is limited. A significant amount of data has been generated using these technologies for various Allium species; it will help in understanding the key traits in Allium crops such as flowering, bulb development, flavonoid biosynthesis, male sterility and stress tolerance at molecular and metabolite level. This information will ultimately assist us in speeding up the breeding in Allium crops.MethodIn the present review, major omics approaches, and their progress, as well as potential applications in Allium crops, could be discussed in detail.ResultsHere, we have discussed the recent progress made in Allium research using omics technologies such as genomics, transcriptomics, micro RNAs, proteomics, metabolomics, and metagenomics. These omics interventions have been used in alliums for marker discovery, the study of the biotic and abiotic stress response, male sterility, organ development, flavonoid and bulb color, micro RNA discovery, and microbiome associated with Allium crops. Further, we also emphasized the integrated use of these omics platforms for a better understanding of the complex molecular mechanisms to speed up the breeding programs for better cultivars.ConclusionAll the information and literature provided in the present review throws light on the progress and potential of omics platforms in the research of Allium crops. We also mentioned a few research areas in Allium crops that need to be explored using omics technologies to get more insight. Overall, alliums are an under-studied group of plants, and thus, there is tremendous scope and need for research in Allium species.

The medical biotechnology community has undertaken significant endeavors to gain a comprehensive understanding of SARS-CoV-2’s biology and pathogenesis mechanisms. Omics approaches and technologies have been widely employed in the fight against SARS-CoV-2. Since the onset of the virus outbreak, researchers have demonstrated how recent omics and bioinformatics technological advancements have contributed to the diagnosis, vaccine development, treatment, and control of disease transmission. Studies conducted since the outbreak have been collected and summarized, with a focus on bioinformatics approaches and their contribution to controlling this pandemic. Developments and advanced omics technology in connection to the COVID-19 pandemic have been analyzed. The multi-omics technology, which offers various strategies in identifying potential diagnostics, therapeutics, studies of variants of concern, and drug repurposing approaches, has been assessed. Pandemic response has seen the application of multi-omics and pan-genomics approaches, including genomics, metabolomics, transcriptomics, proteomics, epigenomics, clustered regularly interspaced short palindromic repeats (CRISPR) technology, host-pathogen interactions, artificial intelligence, and machine learning in various research areas. Additionally, bioinformatics and mathematical modeling have played a significant role in disease control. The use of smart technologies to control virus transmission and predict patients’ health conditions and treatment outcomes has also been crucial. Transcriptome analysis has emerged as a major application, contributing to the generation of new knowledge on viral sequences and intracellular signaling pathways that regulate viral infection and pathogenesis mechanisms. The sequencing of the virus has paved the way for the use of omics technologies and an integrative technique in combating the pandemic. In general, the advancement of omics technology during this pandemic has been fascinating and has contributed a significant role to the science of health biotechnology in general and omics and bioinformatics in particular.Keywords: bioinformatics, coronavirus, COVID-19, omics, SARS COV-2

What Is Aging?

In the Policy Forum “To help aging populations, classify organismal senescence” (1 November 2019, p. [576][1]), S. R. G. Calimport et al. call for classification of senescence as a disease and propose a classification methodology. Unfortunately, their call to action comes a year after the publication of the 11th International Classification of Diseases (ICD) ([ 1 ][2]). The next revision of the ICD is expected in 2028 or later, and much progress needs to be made in basic research and clinical trials before including senescence would be possible. Calimport et al. 's assertion that aging-related diseases can be classified using current information overestimates our understanding of senescence. Multiple studies suggest that aging starts in utero ([ 2 ][3]) and staging of most senescence processes will require massive longitudinal studies in humans and animals. Furthermore, the first clinical trials targeting aging, such as Targeting Aging with Metformin (TAME), are under discussion, and no aging biomarker consensus or hierarchical structuring has yet emerged ([ 3 ][4], [ 4 ][5]). Staging senescence at the tissue-specific level for the purposes of preventative intervention may be a model for private or national health care plans and systems; however, these plans do not require these processes to be classified in the ICD with the individual codes. In addition to providing a general disease framework, ICD codes are used internationally to standardize burden of disease reports and assess cause of death. The concept of staging senescence does not fit the current ICD framework. The addition would likely require a new international initiative to develop a comprehensive set of biomarkers and interventions for senescence and longevity, as well as a set of recommendations for reducing the burden of senescence and aging-associated diseases. Pharmaceutical companies are already working on the interventions targeting the common biological pathways implicated in aging to deliver therapeutics against age-related diseases within the traditional health care paradigm. To accelerate drug development efforts focused on aging as a disease in the pharmaceutical industry, we need to demonstrate that basic research into whether aging is a biological process disease can yield valuable targets or interventions that demonstrate efficacy in treating or preventing age-related diseases. 1. [↵][6]1. A. Zhavoronkov, 2. B. Bhullar , Front. Genet. 6, 326 (2015). [OpenUrl][7] 2. [↵][8]1. B. J. Allison et al ., FASEB 30, 5 (2016). [OpenUrl][9] 3. [↵][10]1. J. N. Justice et al ., Cardiovasc. Endocrinol. Metab. 7, 80 (2018). [OpenUrl][11] 4. [↵][12]American Federation for Aging Research, “TAME trial” (2020); [www.afar.org/research/TAME/][13]. A.Z. is the founder and CEO of Insilico Medicine, a Hong Kong-based artificial intelligence company focused on drug discovery and aging research. He is also an adviser to Haut. AI Ltd., an Estonia-based artificial intelligence company focused on artificial intelligence for skin care and aging research. He is a director and co-founder of Deep Longevity, Inc., an artificial intelligence company focused on aging biomarkers. He is an adviser to the All Party Parliamentary Group (APPG) for Longevity in the UK. He is the seed investor in Retrotope, Inc., a California-based drug discovery company focused on age-related diseases. He may be associated with other startup companies in aging research as an adviser or through investments in Longenesis. [1]: http://www.sciencemag.org/content/366/6465/576 [2]: #ref-1 [3]: #ref-2 [4]: #ref-3 [5]: #ref-4 [6]: #xref-ref-1-1 View reference 1 in text [7]: {openurl}?query=rft.jtitle%253DFront.%2BGenet.%26rft.volume%253D6%26rft.spage%253D326%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [8]: #xref-ref-2-1 View reference 2 in text [9]: {openurl}?query=rft.jtitle%253DFASEB%26rft.volume%253D30%26rft.spage%253D5%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [10]: #xref-ref-3-1 View reference 3 in text [11]: {openurl}?query=rft.jtitle%253DCardiovasc.%2BEndocrinol.%2BMetab.%26rft.volume%253D7%26rft.spage%253D80%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [12]: #xref-ref-4-1 View reference 4 in text [13]: http://www.afar.org/research/TAME/

Acute-on-chronic liver failure (ACLF) is a complex syndrome that develops in patients with acutely decompensated cirrhosis. In this condition, dysbalanced immune function and excessive systemic inflammation are closely associated with organ failure and high short-term mortality. In this review, we describe how omic technologies have contributed to the characterization of the hyperinflammatory state in patients with acutely decompensated cirrhosis developing ACLF, with special emphasis on the role of metabolomics, lipidomics and transcriptomics in profiling the triggers (pathogen- and damage-associated molecular patterns [PAMPs and DAMPs]) and effector molecules (cytokines, chemokines, growth factors and bioactive lipid mediators) that lead to activation of the innate immune system. This review also describes how omic approaches can be invaluable tools to accelerate the identification of novel biomarkers that could guide the implementation of novel therapies/interventions aimed at protecting these patients from excessive systemic inflammation and organ failure.

Secondary hypertension (SH) is a form of high blood pressure caused by an identifiable underlying condition. Although, it accounts for a small fraction of the overall hypertensive population, detection and management of SH is of utmost importance, because SH phenotypes carry a high cardiovascular risk and can possibly be cured by timely treatment. This review focuses on the endocrine causes of SH, such as primary aldosteronism, Cushing syndrome, thyroid disease, pheochromocytoma and paraganglioma, acromegaly, and rare monogenic forms. It discusses current biomarkers, analytical methods, and diagnostic strategies, highlighting advantages and limitations of each approach. It also explores the emerging -omics technologies that can provide a comprehensive and multidimensional assessment of SH and its underlying mechanisms. Endocrine SH is a heterogeneous and complex condition that requires proper screening and confirmatory tests to avoid diagnostic delays and improve patient outcomes. Careful biomarker interpretation is essential due to potential interferences, variability, and method-dependent differences. Liquid chromatography-tandem mass spectrometry is a superior method for measuring low-concentration hormones and metabolites involved in SH, but it requires expertise. Omics approaches have great potential to identify novel biomarkers, pathways, and targets for SH diagnosis and treatment, especially considering its multifactorial nature.

experienced a paradigm shift towards synthetic biology, precision microbiome engineering, personalized medicine, and sustainable bioprocessing techniques with the advent of rapid and extensive development of state-of-the-art microbial and OMICs approaches. OMICs technologies are becoming more prevalent in all facets of microbiotechnology, contributing meaningful datasets in accelerating our understanding and excel in the subject. These technologies are used either DNA or RNA based technologies like metagenomics or metatranscriptomics, respectively. However, with the introduction of high-throughput techniques in other disciplines, OMICs technologies now encompass metabolomics, metaproteomics, phenomics, epigenetics, and other emerging 'omics studies (Altermann and Hickey, 2020). Using these novel technologies, abundance of microorganisms have been thoroughly studied and used in a wide variety of applications, such as agricultural productivity, plant protection, pollution remediation, and the improvement of plant and human health (Anand et al., 2022;Hadibarata et al., 2022;Afridi et al., 2022;Poppeliers et al., 2023;Rafeeq et al., 2023).By issuing this call for papers on "Insights in Microbiotechnology-2022" in the esteemed journal, Frontiers in Microbiology, we sought contributions in the form of research, reviews, mini-reviews, perspectives, and opinions to provide a comprehensive overview of the current state and prospects of the field. This subject explicitly encompasses the most noteworthy scientific discoveries, breakthroughs, challenges, advancements, and potential avenues within the realm of microbiotechnology throughout the year 2022.The carbohydrate-active enzymes known as glycoside hydrolases (GHs) are crucial for a variety of biotechnological and environmental activities, including the production of biofuels and the carbon cycle. Bacteria need numerous enzymes working in a coordinated manner to complete carbohydrate processing. Berlemont (2023) conducted a study to investigate the distribution pattern of 406,337 GH genes and their association with transporter genes in 15,640 fully sequenced bacterial genomes. Although the levels of clustered and scattered GH-genes were conserved throughout different bacterial lineages, the overall occurrence of GH-gene clustering was generally higher than that in randomized genomes. The genomic adaptations for carbohydrate processing in bacteria with the most identified GH-genes also demonstrated the diverse environmental origin of the sequenced strains, including soil and mammal gut. Most scattered genomes are linked to soil ecosystems, whereas most clustered genomes come from aquatic environments and animal GIT. Therefore, the microorganisms with the most significant potential for carbohydrates adapted to their environments in various ways.In order to create synthetic microbial communities (SynCom), la Vega-Camarillo et al.

Kidney transplantation is the preferred treatment for patients with end-stage kidney disease, because it prolongs survival and improves quality of life. Allograft biopsy is the gold standard for diagnosing allograft rejection. However, it is invasive and reactive, and continuous monitoring is unrealistic. Various biomarkers for diagnosing allograft rejection have been developed over the last two decades based on omics technologies to overcome these limitations. Omics technologies are based on a holistic view of the molecules that constitute an individual. They include genomics, transcriptomics, proteomics, and metabolomics. The omics approach has dramatically accelerated biomarker discovery and enhanced our understanding of multifactorial biological processes in the field of transplantation. However, clinical application of omics-based biomarkers is limited by several issues. First, no large-scale prospective randomized controlled trial has been conducted to compare omics-based biomarkers with traditional biomarkers for rejection. Second, given the variety and complexity of injuries that a kidney allograft may experience, it is likely that no single omics approach will suffice to predict rejection or outcome. Therefore, integrated methods using multiomics technologies are needed. Herein, we introduce omics technologies and review the latest literature on omics biomarkers predictive of allograft rejection in kidney transplant recipients.

Sense of mastery, a personal resource, is likely to have an inverse association with alcohol dependence. Previous evidence, however, is sparse. In addition, the extent to which an association is due to genetic or environmental factors is unknown. Data were from 3,983 male twins and 2,630 female twins who had ever used alcohol, interviewed in the Virginia Adult Twin Study of Psychiatric and Substance Use Disorders. Mastery was measured by a 6-item scale. Lifetime diagnosis of alcohol dependence was based on DSM-IV criteria assessed in a structured diagnostic interview. Univariate analyses modeled the relative contributions of genetic and environmental factors to mastery and alcohol dependence using Mx software. Bivariate Cholesky models were fit to the mastery and alcohol dependence raw data. In the best-fitting model of mastery, genetic factors accounted for about 33% of the observed variance. Nonshared environmental factors, including random measurement error, accounted for the remaining 67%. Fifty-six percent of the variance in liability to alcohol dependence was genetic, and the other 44% was explained by the nonshared environment. The phenotypic polychoric correlation between mastery and alcohol dependence of -0.18 was primarily (67% in the best-fitting model) explained by genes common to both low mastery and alcohol dependence; the rest was explained by nonshared environmental factors. The findings indicate that genetic risk for alcohol dependence overlaps with genetic factors that influence sense of mastery. Key challenges for future research are to identify the genes that influence mastery and alcohol dependence, as well as the environmental pathways by which they come to be linked.

The biology of aging is immensely complex. Aging occurs at the molecular, cellular, tissue, organ, and organismal level and drives the onset and progression of nearly every medically relevant disease in developed nations. Aging is influenced by multiple genetic and environmental factors, some of which are conserved across broad evolutionary distance. This special issue is aimed at presenting the complexity of aging in a manner accessible to a broad readership, with particular emphasis on genomic and systems biology approaches to understand the aging process. Such approaches are needed to better model the pathways and interactions that underlie the aging process. The issue begins with an overview of large-scale and genome-wide studies of aging by McCormick and Kennedy. A synthesis of studies from multiple model systems including Saccharomyces cerevisiae, Caenorhabditis elegans, Drosophila melanogaster, and Mus musculus is presented. Yanos et al. focus in detail on what has been gleaned from genomic RNAi longevity screens in C. elegans. Hundreds of genes that limit lifespan have been identified from such studies, which has provided a wealth of information but also the challenge of trying to understand how these genetic factors interact to influence aging. The importance of the specific longevity pathways involved, including insulin-like signaling, dietary restriction, mRNA translation, and mitochondrial function is discussed. Mitochondria have long been thought to contribute to aging through the production of damaging reactive oxygen species; however, as Hwang et al. describe, more recent findings have forced a reevaluation of this model. It is now clear that certain forms of mitochondrial stress are compatible with longer and healthier life in organisms from yeast to mice. Specific models accounting for these observations, including possible involvement of the hypoxic response transcription factor, HIF-1, are described in detail. Although chromatin modifying factors, such as histone deacetylases, were among the first enzymes to be shown to modulate lifespan in model organisms, the full importance of epigenetics in aging has only recently been appreciated. Liu and Zhou present an overview of the importance of chromatin remodeling in aging and the response to DNA damage. MicroRNAs represent yet another level of complexity in the aging process. These small RNAs are able to regulate the expression of numerous mRNAs, some of which directly influence aging and age-related diseases. Jung and Suh describe what we know about the importance of microRNAs in aging and how this exciting new field is just starting to become explored. The last review in this special issue by Hou et al. brings things together nicely with a systems biology perspective of aging. In order to model the immense complexity of aging, we require systems-level approaches. This review describes how several groups are trying to tackle this problem and some of the new insights that have already been gained. I would like to thank all of the authors and reviewers for their efforts in putting together such a timely and informative special issue.

Cancer is a chronic, complex disease. With advanced high-throughput technologies i.e. various -omics approaches, molecular imaging and computer technologies, conventional medicine and its research of cancer is leading to the emergence of systems biology. Traditional Chinese medicine (TCM) focuses on the diseased person as a whole to formulate the therapeutic strategies to create a holistic systemic approach to treat the imbalanced systems of a person. TCM practices are usually descriptive, and empirical. To facilitate cross discipline dialog, and potentially research collaboration, it is important to move TCM research toward systems biological approaches. Analysis of FY2006 and 2007 NCI funded TCM research grants portfolio and research approaches will be discussed.

Medieval alchemists, craving the boon of youth and desiring renewed health and strength, were kept busy searching for the mythical elixir of life, a universal medicine supposedly containing a recipe for rejuvenescence.Now, in the 21 st century, their modern successors use the fruits of the genomics revolution to discover genetic factors that ward off aging and agingrelated diseases.In this issue of Aging, Gravina et al.[1] present evidence that the long life span of the more fortunate among us could be related to variants of the p21 cell cycle inhibitor.Longevity is simply defined as the property of being long-lived, i.e., approaching the life span of the oldest individual of a species or a population.The latter is also called 'maximum life span', which in contrast to life expectancy (mean age at death in a population) is not greatly influenced by environmental conditions.Longevity is attained by keeping aging at bay.Aging can be defined operationally as a time-dependent loss of fitness that begins to manifest after the organism attains its maximum reproductive competence.Unlike longevity, this loss of fitness cannot easily be caught in some simple measurement.There are no real biomarkers for aging and its phenotype is extremely complex.The large variation in maximum life span among species points toward genetic factors that specify the mechanisms that protect against aging and disease.The identification of these genetic factors is of interest since they would provide targets for modes of prevention and Preview www.impactaging.com

Many countries face an unprecedented challenge in aging demographics. This has led to an exponential growth in research on aging, which, coupled to a massive financial influx of funding in the private and public sectors, has resulted in seminal insights into the underpinnings of this biological process. However, critical validation in humans has been hampered by the limited translatability of results obtained in model organisms, additionally confined by the need for extremely time-consuming clinical studies in the ostensible absence of robust biomarkers that would allow monitoring in shorter time frames. In the future, molecular parameters might hold great promise in this regard. In contrast, biomarkers centered on function, resilience, and frailty are available at the present time, with proven predictive value for morbidity and mortality. In this review, the current knowledge of molecular and physiological aspects of human aging, potential antiaging strategies, and the basis, evidence, and potential application of physiological biomarkers in human aging are discussed.

Aging is characterized by a progressive deterioration of physiological integrity, leading to impaired functional ability and ultimately increased susceptibility to death. It is a major risk factor for chronic human diseases, including cardiovascular disease, diabetes, neurological degeneration, and cancer. Therefore, the growing emphasis on “healthy aging” raises a series of important questions in life and social sciences. In recent years, there has been unprecedented progress in aging research, particularly the discovery that the rate of aging is at least partly controlled by evolutionarily conserved genetic pathways and biological processes. In an attempt to bring full-fledged understanding to both the aging process and age-associated diseases, we review the descriptive, conceptual, and interventive aspects of the landscape of aging composed of a number of layers at the cellular, tissue, organ, organ system, and organismal levels.

Impact of cellular senescence signature on ageing research