Omics Strategies Research Articles

Current Insights on Neurodegeneration by the Italian Proteomics Community.

The growing number of patients affected by neurodegenerative disorders represents a huge problem for healthcare systems, human society, and economics. In this context, omics strategies are crucial for the identification of molecular factors involved in disease pathobiology, and for the discovery of biomarkers that allow early diagnosis, patients’ stratification, and treatment response prediction. The integration of different omics data is a required step towards the goal of personalized medicine. The Italian proteomics community is actively developing and applying proteomics approaches to the study of neurodegenerative disorders; moreover, it is leading the mitochondria-focused initiative of the Human Proteome Project, which is particularly important given the central role of mitochondrial impairment in neurodegeneration. Here, we describe how Italian research groups in proteomics have contributed to the knowledge of many neurodegenerative diseases, through the elucidation of the pathobiology of these disorders, and through the discovery of disease biomarkers. In particular, we focus on the central role of post-translational modifications analysis, the implementation of network-based approaches in functional proteomics, the integration of different omics in a systems biology view, and the development of novel platforms for biomarker discovery for the high-throughput quantification of thousands of proteins at a time.

Biomarkers and kidney diseases: a brief narrative review

Background and Objective: Current biomolecular identification techniques expose new aspects in the biological universe of the human body. Omics strategies through genomics, metabolomics, lipidomics and proteomics generate thousands of information that demand math resources to integrate the meanings of multiple molecular patterns in the construction of modern biochemical knowledge of the interior environment. Biomarkers are endogenous molecules, detected qualitatively and/or quantitatively, which provide peculiar data for the identification of physiological or pathophysiological processes, as well as for the control of pharmacological responses. This narrative literature review aims to provide an update on biomarkers of kidney diseases.

Omics technologies in allergy and asthma research: An EAACI position paper.

Allergic diseases and asthma are heterogenous chronic inflammatory conditions with several distinct complex endotypes. Both environmental and genetic factors can influence the development and progression of allergy. Complex pathogenetic pathways observed in allergic disorders present a challenge in patient management and successful targeted treatment strategies. The increasing availability of high-throughput omics technologies, such as genomics, epigenomics, transcriptomics, proteomics, and metabolomics allows studying biochemical systems and pathophysiological processes underlying allergic responses. Additionally, omics techniques present clinical applicability by functional identification and validation of biomarkers. Therefore, finding molecules or patterns characteristic for distinct immune-inflammatory endotypes, can subsequently influence its development, progression, and treatment. There is a great potential to further increase the effectiveness of single omics approaches by integrating them with other omics, and nonomics data. Systems biology aims to simultaneously and longitudinally understand multiple layers of a complex and multifactorial disease, such as allergy, or asthma by integrating several, separated data sets and generating a complete molecular profile of the condition. With the use of sophisticated biostatistics and machine learning techniques, these approaches provide in-depth insight into individual biological systems and will allow efficient and customized healthcare approaches, called precision medicine. In this EAACI Position Paper, the Task Force "Omics technologies in allergic research" broadly reviewed current advances and applicability of omics techniques in allergic diseases and asthma research, with a focus on methodology and data analysis, aiming to provide researchers (basic and clinical) with a desk reference in the field. The potential of omics strategies in understanding disease pathophysiology and key tools to reach unmet needs in allergy precision medicine, such as successful patients' stratification, accurate disease prognosis, and prediction of treatment efficacy and successful prevention measures are highlighted.

Mast Cell Desensitization in Allergen Immunotherapy.

Allergen immunotherapy (AIT) is the only treatment with disease-transforming potential for allergic disorders. The immunological mechanisms associated with AIT can be divided along time in two phases: short-term, involving mast cell (MC) desensitization; and long-term, with a regulatory T cell (Treg) response with significant reduction of eosinophilia. This regulatory response is induced in about 70% of patients and lasts up to 3 years after AIT cessation. MC desensitization is characteristic of the initial phase of AIT and it is often related to its success. Yet, the molecular mechanisms involved in allergen-specific MC desensitization, or the connection between MC desensitization and the development of a Treg arm, are poorly understood. The major AIT challenges are its long duration, the development of allergic reactions during AIT, and the lack of efficacy in a considerable proportion of patients. Therefore, reaching a better understanding of the immunology of AIT will help to tackle these short-comings and, particularly, to predict responder-patients. In this regard, omics strategies are empowering the identification of predictive and follow-up biomarkers in AIT. Here, we review the immunological mechanisms underlying AIT with a focus on MC desensitization and AIT-induced adverse reactions. Also, we discuss the identification of novel biomarkers with predictive potential that could improve the rational use of AIT.

Complementary omics strategies to dissect p53 signaling networks under nutrient stress

Signaling trough p53is a major cellular stress response mechanism and increases upon nutrient stresses such as starvation. Here, we show in a human hepatoma cell line that starvation leads to robust nuclear p53 stabilization. Using BioID, we determine the cytoplasmic p53 interaction network within the immediate-early starvation response and show that p53 is dissociated from several metabolic enzymes and the kinase PAK2 for which direct binding with the p53 DNA-binding domain was confirmed with NMR studies. Furthermore, proteomics after p53 immunoprecipitation (RIME) uncovered the nuclear interactome under prolonged starvation, where we confirmed the novel p53 interactors SORBS1 (insulin receptor signaling) and UGP2 (glycogen synthesis). Finally, transcriptomics after p53 re-expression revealed a distinct starvation-specific transcriptome response and suggested previously unknown nutrient-dependent p53 target genes. Together, our complementary approaches delineate several nodes of the p53 signaling cascade upon starvation, shedding new light on the mechanisms of p53 as nutrient stress sensor. Given the central role of p53 in cancer biology and the beneficial effects of fasting in cancer treatment, the identified interaction partners and networks could pinpoint novel pharmacologic targets to fine-tune p53 activity.

Increase Crop Resilience to Heat Stress Using Omic Strategies.

Varieties of various crops with high resilience are urgently needed to feed the increased population in climate change conditions. Human activities and climate change have led to frequent and strong weather fluctuation, which cause various abiotic stresses to crops. The understanding of crops’ responses to abiotic stresses in different aspects including genes, RNAs, proteins, metabolites, and phenotypes can facilitate crop breeding. Using multi-omics methods, mainly genomics, transcriptomics, proteomics, metabolomics, and phenomics, to study crops’ responses to abiotic stresses will generate a better, deeper, and more comprehensive understanding. More importantly, multi-omics can provide multiple layers of information on biological data to understand plant biology, which will open windows for new opportunities to improve crop resilience and tolerance. However, the opportunities and challenges coexist. Interpretation of the multidimensional data from multi-omics and translation of the data into biological meaningful context remained a challenge. More reasonable experimental designs starting from sowing seed, cultivating the plant, and collecting and extracting samples were necessary for a multi-omics study as the first step. The normalization, transformation, and scaling of single-omics data should consider the integration of multi-omics. This review reports the current study of crops at abiotic stresses in particular heat stress using omics, which will help to accelerate crop improvement to better tolerate and adapt to climate change.

Methods applied in studies about fermented foods

Fermented foods have been produced for thousands of years. In recent decades, its production and consumption have increased due to potential beneficial health effects attributed to its intake. This has stimulated the development of scientific studies on food fermentation. In this context, the development of complex methods capable of characterizing the fermenting microbiota and relating it to the desired characteristics and quality has enabled a greater understanding of the role of different microbial groups in the fermentation process. In this article, the main methods used in research on fermented foods are briefly presented, highlighting the most widely used omics strategies, such as metagenomic, metaproteomic and metabolomic analysis.

Feedomics provides bidirectional omics strategies between genetics and nutrition for improved production in cattle.

Increasing the efficiency and sustainability of cattle production is an effective way to produce valuable animal proteins for a growing human population. Genetics and nutrition are the 2 major research topics in selecting cattle with beneficial phenotypes and developing genetic potentials for improved performance. There is an inextricable link between genetics and nutrition, which urgently requires researchers to uncover the underlying molecular mechanisms to optimize cattle production. Feedomics integrates a range of omic techniques to reveal the mechanisms at different molecular levels related to animal production and health, which can provide novel insights into the relationships of genes and nutrition/nutrients. In this review, we summarized the applications of feedomics techniques to reveal the effect of genetic elements on the response to nutrition and investigate how nutrients affect the functional genome of cattle from the perspective of both nutrigenetics and nutrigenomics. We highlighted the roles of rumen microbiome in the interactions between host genes and nutrition. Herein, we discuss the importance of feedomics in cattle nutrition research, with a view to ensure that cattle exhibit the best production traits for human consumption from both genetic and nutritional aspects.

Module engineering coupled with omics strategies for enhancing D-pantothenate production in Escherichia coli

Biosynthesis of D-pantothenate has been widely studied as D-pantothenate is one kind of important vitamins used in food and pharmaceuticals. However, the engineered strain for D-pantothenate production was focused solely on the main biosynthetic pathway, while other important factors such as one carbon unit were ignored. Here the systematic modular engineering on different factors coupled with omics analysis were studied in Escherichia coli for efficient D-pantothenate production. Through reinforcing the precursor pool, refactoring the one carbon unit generation pathway, optimization of reducing power and energy supply, the D-pantothenate titer reached 34.12 g/L with the yield at 0.28 g/g glucose under fed-batch fermentation in 5-L bioreactor. With a further comparative transcriptome and metabolomics studies, the addition of citrate was implemented and 45.35 g/L D-pantothenate was accumulated with a yield of 0.31 g/g glucose. The systematic modular engineering coupled with omics studies provide useful strategies for the industrial production of D-pantothenate.

Diet and human reproductive system: Insight of omics approaches.

Nutrition and lifestyle have a great impact on reproduction and infertility in humans, as they are essential for certain processes such as implantation, placental growth, angiogenesis, and the transfer of nutrients from the mother to the fetus. The aim of this review is to provide the interconnection between nutrition and reproductive health through the insight of omics approaches (including metabolomics and nutrigenomics). The effect of various macronutrients, micronutrients, and some food‐associated components on male and female reproduction was discussed. Recent research work was collected through database search from 2010 to 2020 to identify eligible studies. Alterations of metabolic pathways in pregnant women were deliberated with an emphasis on different strategies of lifestyle and dietary interventions. Several nutritional methods, which are important for embryonic and child neurological development, nutritional supplements to lactation, and improved gestational length along with birth weight have been emphasized. Considerable advances in omics strategies show potential technological development for improving human reproductive health.

The way forward of Forest Plantation in Malaysia

Forest plantation strategies are the important components providing timber for downstream industrial manufacturing. This strategy has been quickly expanded in response to demands of the local market and government and has had noteworthy impacts on rural economy and livelihoods in Malaysia. Here, we first reviewed the history of forest plantation in Malaysia and consequently we have discussed the parameters influencing the sustainable production of forest plantation including genetic diversity, silviculture, and preserving site sustainability. Furthermore, we have deliberated different strategies which can be used during forest plantation and increase efficacy of this strategy. Different types of rotation plantations strategies such as very short rotation-, short rotation-, medium rotation-, long rotation-, mixed wild fruit-, and agroforestry-plantation systems have been discussed, accordingly. In the next step, the effects of different omics strategies on forest plantations have been reviewed. Finally, the impact of mathematical programming in the forest plantation have been explained, and the challenges and restrictions of forest plantation have been stated

VenomFlow: An Automated Bioinformatic Pipeline for Identification of Disulfide-Rich Peptides from Venom Arsenals.

Animal venoms are among the most complex natural secretions known, comprising a mixture of bioactive compounds often referred to as toxins. Venom arsenals are predominately made up of cysteine-rich peptide toxins that manipulate molecular targets, such as ion channels and receptors, making these venom peptides attractive candidates for the development of therapeutics to benefit human health. With the rise of omic strategies that utilize transcriptomic, proteomic, and bioinformatic methods, we are able to identify more venom proteins and peptides than ever before. However, identification and characterization of bioactive venom peptides remains a significant challenge due to the unique chemical structure and enormous number of peptides found in each venom arsenal (upward of 200 per organism). Here, we introduce a rapid and user-friendly in silico bioinformatic pipeline for the de novo identification and characterization of raw RNAseq reads from venom glands to elucidate cysteine-rich peptides from the arsenal of venomous organisms.Implementation: This project develops a user-friendly automated bioinformatics pipeline via a Galaxy workflow to identify novel venom peptides from raw RNAseq reads of terebrid snails. While designed for venomous terebrid snails, with minor adjustments, this pipeline can be made universal to identify secreted disulfide-rich peptide toxins from any venomous organism.

Human disease biomarkers: challenges, advances, and trends in their validation

Biomarkers are important tools in the medical field, once they allow better prediction, characterization, and treatment of diseases. In this scenario, it is essential that biomarkers are highly accurate. Thus, biomarker validation is an essential part of ensuring the effectiveness of a biomarker. Validation of biomarkers is the process by which biomarkers are evaluated for accuracy and consistency, as well as their ability to inform the condition of health or disease. Although, there is no unique measure that can be used to determine the validity for all biomarkers, there are general criteria that all biomarkers must meet to be useful. In this work, we review the definition of biomarkers and discuss the validity components. We then critically discuss the main methods used to validate biomarkers and consider some examples of biomarkers of the diseases which most killer in the world (cardiovascular diseases, cancer, and viral infections), highlighting the potential biochemical pathways of these biomarkers in the biological system. In addition, we also comment on the omic strategies used in the biomarker discovery process and conclude with information about perspectives in biomarker validation through imaging techniques.

Omics Strategies in Current Advancements of Infectious Fish Disease Management.

Simple SummaryThe increasing demand for fish products has caused disease-related problems due to intense fish practices in fish farms. The fish diseases infection caused by bacteria, viruses, and parasites could lead to high fish mortality that affected the aquaculture industry. Recently, a systematic strategy to overcome fish disease problems using multi-omics platforms has been used to provide a better understanding of how to improve the resistance of fish to pathogen infection. In this review, we highlight the current multi-omics strategies such as transcriptomics, proteomics, and metabolomics to provide information regarding their molecular mechanisms of action, subsequently important in discovering potential biomarkers for various infectious fish diseases in the aquaculture system.Aquaculture is an important industry globally as it remains one of the significant alternatives of animal protein source supplies for humankind. Yet, the progression of this industry is being dampened by the increasing rate of fish mortality, mainly the outbreak of infectious diseases. Consequently, the regress in aquaculture ultimately results in the economy of multiple countries being affected due to the decline of product yields and marketability. By 2025, aquaculture is expected to contribute approximately 57% of fish consumption worldwide. Without a strategic approach to curb infectious diseases, the increasing demands of the aquaculture industry may not be sustainable and hence contributing to the over-fishing of wild fish. Recently, a new holistic approach that utilizes multi-omics platforms including transcriptomics, proteomics, and metabolomics is unraveling the intricate molecular mechanisms of host-pathogen interaction. This approach aims to provide a better understanding of how to improve the resistance of host species. However, no comprehensive review has been published on multi-omics strategies in deciphering fish disease etiology and molecular regulation. Most publications have only covered particular omics and no constructive reviews on various omics findings across fish species, particularly on their immune systems, have been described elsewhere. Our previous publication reviewed the integration of omics application for understanding the mechanism of fish immune response due to microbial infection. Hence, this review provides a thorough compilation of current advancements in omics strategies for fish disease management in the aquaculture industry. The discovery of biomarkers in various fish diseases and their potential advancement to complement the recent progress in combatting fish disease is also discussed in this review.

Context-aware synthetic biology by controller design: Engineering the mammalian cell.

The rise of systems biology has ushered a new paradigm: the view of the cell as a system that processes environmental inputs to drive phenotypic outputs. Synthetic biology provides a complementary approach, allowing us to program cell behavior through the addition of synthetic genetic devices into the cellular processor. These devices, and the complex genetic circuits they compose, are engineered using a design-prototype-test cycle, allowing for predictable device performance to be achieved in a context-dependent manner. Within mammalian cells, context effects impact device performance at multiple scales, including the genetic, cellular, and extracellular levels. In order for synthetic genetic devices to achieve predictable behaviors, approaches to overcome context dependence are necessary. Here, we describe control systems approaches for achieving context-aware devices that are robust to context effects. We then consider cell fate programing as a case study to explore the potential impact of context-aware devices for regenerative medicine applications.

Early diagnosis and therapeutic strategies for hepatocellular carcinoma: From bench to bedside.

Hepatocellular carcinoma (HCC) is the fourth leading cause of cancer-related deaths worldwide. The prognosis of patients with HCC remains poor largely due to the late diagnosis and lack of effective treatments. Despite being widely used, alpha-fetoprotein serology and ultrasonography have limited diagnostic performance for early-stage HCC. The emergence of omics strategies has contributed to significant advances in the development of non-invasive biomarkers for the early diagnosis of HCC including proteins, metabolites, circulating tumor deoxyribonucleic acid, and circulating non-coding ribonucleic acid. Early diagnosis is beneficial to patients as it increases the proportion who can be treated with curative treatment, thus prolonging survival outcomes. Currently, multiple clinical trials involving locoregional, systemic therapies, and combinations of these modalities are changing therapeutic strategies for different stage HCC. Success in several preclinical trials that involve immunotherapeutic innovations has created the potential to complement and enforce other treatment strategies in the future. This review summarizes the most recent advances in non-invasive early molecular detection, current therapy strategies, and potential immunotherapeutic innovations of HCC.

The Role of Diagnostic Biomarkers, Omics Strategies, and Single-Cell Sequencing for Nonalcoholic Fatty Liver Disease in Severely Obese Patients.

Liver disease due to metabolic dysfunction constitute a worldwide growing health issue. Severe obesity is a particularly strong risk factor for non-alcoholic fatty liver disease, which affects up to 93% of these patients. Current diagnostic markers focus on the detection of advanced fibrosis as the major predictor of liver-related morbidity and mortality. The most accurate diagnostic tools use elastography to measure liver stiffness, with diagnostic accuracies similar in normal-weight and severely obese patients. The effectiveness of elastography tools are however hampered by limitations to equipment and measurement quality in patients with very large abdominal circumference and subcutaneous fat. Blood-based biomarkers are therefore attractive, but those available to date have only moderate diagnostic accuracy. Ongoing technological advances in omics technologies such as genomics, transcriptomics, and proteomics hold great promise for discovery of biomarkers and increased pathophysiological understanding of non-alcoholic liver disease and steatohepatitis. Very recent developments have allowed for single-cell sequencing and cell-type resolution of gene expression and function. In the near future, we will therefore likely see a multitude of breakthrough biomarkers, developed from a deepened understanding of the biological function of individual cell types in the healthy and injured liver.

Spectral quality overrides software score―A brief tutorial on the analysis of peptide fragmentation data for mass spectrometry laymen

The Special Feature this month comes from Simone König, Interdisciplinary Center for Clinical Research, Medical Faculty, University of Münster, Germany. Her contribution serves both as a valuable guide to mass spectral interpretation - specifically peptide fragmentation, the basis of bottom-up proteomics - and as a cautionary note to all omics practitioners. Dr. König uses examples to highlight both the power and the potential pitfalls of automated omics strategies. She discusses what she describes as the potential for over-interpretation of mass spectral data when the user places undue confidence in the power of automated spectral software interpretation tools. Dr. König's tutorial reiterates an important take-away message multiple times, in various ways, and illustrates this message by numerous examples. Her message is simple: User beware! Omics methods combine powerful inline separation technologies, high throughput MS/MS spectral generation strategies, and automated data analysis/interpretation software to deliver what can only be described as an avalanche of data. But, without thoughtful consideration of each of the components and intelligent oversight of the whole process, regrettably, errors can abound.

Cancer Omics in Africa: Present and Prospects.

During the last century, cancer biology has been arguably one of the most investigated research fields. To gain deeper insight into cancer mechanisms, scientists have been attempting to integrate multi omics data in cancer research. Cancer genomics, transcriptomics, metabolomics, proteomics, and metagenomics are the main multi omics strategies used currently in the diagnosis, prognosis, treatment, and biomarker discovery in cancer. In this review, we describe the use of different multi omics strategies in cancer research in the African continent and discuss the main challenges facing the implementation of these approaches in African countries such as the lack of training programs in bioinformatics in general and omics strategies in particular and suggest paths to address deficiencies. As a way forward, we advocate for the establishment of an “African Cancer Genomics Consortium” to promote intracontinental collaborative projects and enhance engagement in research activities that address indigenous aspects for cancer precision medicine.

Identification of Novel Biomarkers for Predicting Kidney Injury Due to Drugs Using "Omic" Strategies.

Drug-induced kidney injury accounts for 20% of community- and hospital-acquired cases of acute kidney injury (AKI). The incidence is higher among older individuals, who often have co-existing morbidities and are exposed to more diagnostic procedures and therapies. While demographic and clinical components have been identified as risk factors, the proposed cellular mechanisms of drug-induced kidney injury are numerous and complicated. There are also limitations recognized in the use of traditional biomarkers, such as serum creatinine and blood urea nitrogen, to provide high sensitivity, specificity, and timeliness to identification of drug-induced kidney injury. Therefore, novel biomarkers are currently being investigated, identified, developed, and validated for their performance over the traditional biomarkers. This review will provide an overview of drug-induced kidney injury and will discuss what is known regarding “omic” (proteomic, genomic, transcriptomic, and metabolomic) biomarker strategies for drugs known to induce nephrotoxicity.