Omics Approaches Research Articles

Beyond Asexual: Genomics-Driven Progress in Unveiling Sexual Reproduction in Cereal Rust Fungi.

Recent advances in genomics technologies have revolutionized our understanding of cereal rust fungi, providing unprecedented insights into the complexities of their sexual life cycle. Genomic approaches, including long-read sequencing, genome assembly, and haplotype phasing technologies, have revealed critical insights into mating systems, genetic diversity, virulence evolution, and host adaptation. Population genomics studies have uncovered diverse reproductive strategies across different cereal rust species and geographic regions, highlighting the interplay between sexual recombination and asexual reproduction. Transcriptomics have begun to unravel the gene expression networks driving sexual reproduction, while complementary omics approaches such as proteomics, and metabolomics offer potential insights into the underlying molecular processes. Despite this progress, many aspects of rust sexual reproduction remain elusive. Integrating multiple omics approaches with advanced cell biology techniques can help address these knowledge gaps, particularly in understanding sexual reproduction and its role in pathogen evolution. This comprehensive approach will be crucial for developing more targeted and resilient crop protection strategies, ultimately contributing to global food security.

Proteomics and transcriptomic analyses provide new insights into the pectin polysaccharide biosynthesis in Premna puberula Pamp

Premna puberula Pamp. is a plant with similarities to both food and medicine, which has attracted the attention of researchers because of the rich pectin in its leaves. However, the mechanism of efficient pectin accumulation remains unclear. Through transcriptomic and proteomic analyses, this study investigated the differentially expressed genes and proteins associated with pectin during various developmental stages of P. puberula. The combined omics approach revealed that the majority of differential genes are mainly involved in the anabolic metabolism of primary and secondary metabolites. Notable differential pathways include starch and sucrose metabolism, amino acid sugar metabolism, and nucleotide sugar metabolism. The SWEET gene family was identified and analyzed, leading to the cloning of PpSWEET15 and subcellular localization. Overexpression of PpSWEET15 resulted in a significant decrease in sucrose content in leaves from 134.44 μg·g−1 to <10 μg·g−1. Glucose content decreased from 407.75 μg·g−1 to 318.38 μg·g−1, while fructose levels showed no significant difference between the two groups of leaves. This comprehensive transcriptomic and proteomic analysis provides valuable insights into the molecular mechanisms underlying the efficient accumulation of pectin in P. puberula.

Rhizochemistry and soil bacterial community are tailored to natural stress gradients

Plants modulate their rhizochemistry, which affects soil bacterial communities and, ultimately, plant performance. Although our understanding of rhizochemistry is growing, knowledge of its responses to abiotic constraints is limited, especially in realistic ecological contexts. Here, we combined predictive metabolomics with soil metagenomics to investigate how rhizochemistry responded to environmental constraints and how it in turn shaped soil bacterial communities across stress gradients in the Atacama Desert. We found that rhizochemical adjustments predicted the environment (i.e. elevation, R2 between 96% and 74%) of two plant species, identifying rhizochemical markers for plant resilience to harsh edaphic conditions. These metabolites (e.g. glutamic and succinic acid, catechins) were consistent across years and could predict the elevation of two independent plant species, suggesting biochemical convergence. Next, convergent patterns in the dynamics of bacterial communities were also observed across the elevation gradient. Finally, rhizosphere predictors were associated with variation in composition and abundance of bacterial species. Biochemical markers and convergences as well as potential roles of associated predictive bacterial families reflected the requirements for plant life under extreme conditions. This included biological processes such as nitrogen and water starvation (e.g. glutamic and organic acids, Bradyrhizobiaceae), metal pollution (e.g. Caulobacteraceae) and plant development and defence (e.g. flavonoids, lipids, Chitinophagaceae). Overall, findings highlighted convergent patterns belowground, which represent exciting insights in the context of evolutionary biology, and may indicate unique metabolic sets also relevant for crop engineering and soil quality diagnostics. Besides, the results emphasise the need to integrate ecology with omics approaches to explore plant-soil interactions and better predict their responses to climate change.

TIdeS: a comprehensive framework for accurate open reading frame identification and classification in eukaryotic transcriptomes.

Studying fundamental aspects of eukaryotic biology through genetic information can face numerous challenges, including contamination and intricate biotic interactions, which are particularly pronounced when working with uncultured eukaryotes. However, existing tools for predicting open reading frames (ORFs) from transcriptomes are limited in these scenarios. Here we introduce Transcript Identification and Selection (TIdeS), a framework designed to address these non-trivial challenges associated with current 'omics approaches. Using transcriptomes from 32 taxa, representing the breadth of eukaryotic diversity, TIdeS outperforms most conventional ORF-prediction methods (i.e., TransDecoder), identifying a greater proportion of complete and in-frame ORFs. Additionally, TIdeS accurately classifies ORFs using minimal input data, even in the presence of 'heavy contamination'. This built-in flexibility extends to previously unexplored biological interactions, offering a robust single-stop solution for precise ORF predictions and subsequent decontamination. Beyond applications in phylogenomic-based studies, TIdeS provides a robust means to explore biotic interactions in eukaryotes (e.g., host-symbiont, prey-predator) and for reproducible dataset curation from transcriptomes and genomes.

Multiomics analysis reveals microbial diversity and activity through spontaneous fermentation of Theobroma cacao

To gain insight into the active microbiota during spontaneous fermentation of Theobroma cacao L., this study assessed protein diversity during 120 h using a combined metabarconding and metaproteomics approach. During the first days of fermentation, most of the peptides were associated with T. cacao and yeast (0–72 h). Peptides associated with bacteria became more abundant after 72 h of fermentation, coinciding with a decrease in peptides associated with cocoa (96–120 h). In addition to the known microorganisms involved in fermentation, such as Saccharomyces, Lactobacillus and Acetobacter, novel genera were also metabolically active, including Microvirga, Inquilinus, Candolleomyces and Lasiodiplodia.. The results showed a consistency in the main genera detected by both techniques, but the identification of unexplored genera such as Inquilinus, Microvirga, Cyphellophora and Ashbya gossypii, among others, suggests that this omics approach needs to be used together for more comprehensive results on spontaneous fermentation. In conclusion, studies combining techniques such as metabarcoding and metaproteomics should be considered in fermentation studies, as a single technique would result in omissions regarding the activity of certain microorganisms that may be important for the course of spontaneous fermentation.

Metabolomics and dual proteomics identify contrasting patterns of major pathways affected in asparagus shoot upon Fusarium infection

Abstract Aims Infections with soil-borne pathogens have considerable detrimental effects on asparagus (Asparagus officinalis) growth and production, notably caused by the Fusarium species F. oxysporum f.sp. asparagi, F. proliferatum, and F. redolens. To get insight into the systemic effects of fungal infection on plant physiology to identify candidate resistance traits, we investigated this interaction using a multi omics approach. Methods Asparagus plants were inoculated with one of the three Fusarium species. After 8 weeks, basal stem parts were harvested and subjected to metabolome and proteome analysis as well as detection of fungal DNA. Results Upon infection, the pathogen spreads systemically from the root to the shoot and, consequently, fungal DNA and mycotoxins were detected in the basal part of the plant stem. Metabolite data revealed that the main pathway affected by Fusarium infections was “Fatty acids”, specifically the superclasses “Glycerophospholipids”, “Glycerolipids” and “Sphingolipids” being lower abundant upon infection. Another main pathway identified in the analysis was “Shikimates and Phenylpropanoids” with compounds assigned to these classes being mainly enriched upon infection. Proteome data revealed an induction of pathogen-defense proteins upon infection in asparagus, while proteins involved in vesicle trafficking and lipid metabolism were lower abundant. Conclusions This indicates that not only lipid-based signaling processes are distorted by Fusarium, but also fundamental processes such as vesicle formation, membrane integrity and cell wall organization. In planta proteome analysis of F. oxysporum led to the identification of 1,488 fungal proteins, including proteins involved in metabolic and cellular processes as well as putative virulence factors.

Developmentally regulated generation of a systemic signal for long-lasting defence priming in tomato.

Tomato is a major global crop. However, its production is limited by Botrytis cinerea. Due to the toxicity of postharvest pesticide application, alternative control methods such as priming are being investigated. Plants were treated with β-aminobutyric acid (BABA) at two developmental stages and resistance against B. cinerea was tested in fruit tissue and in progenies. DNA methylation and RNA sequencing were conducted to characterise the (epi)genetic changes associated with long-lasting resistance. Grafting experiments were done to assess the systemic nature of this signal, which was further characterised by small RNA (sRNA) sequencing of scions. Only BABA-treated seedlings displayed induced resistance (IR). DNA methylation analysis revealed seedling-specific changes, which occurred in the context of lower basal methylation. BABA-IR was found to be transmissible from primed rootstock to grafted unprimed scions. In these scions, we identified a subset of mobile 24 nt sRNAs associated with genes showing primed expression during infection in fruit. Our results demonstrate the functional association of a systemic signal with long-lasting IR and priming. Through integrated omics approaches, we have identified markers of long-lasting priming in tomato fruit which could also serve as targets for durable resistance in other crops.

"OMICS" in Human Milk: Focus on Biological Effects on Bone Homeostasis.

Human milk (HM) is a complex biofluid rich in nutrients and bioactive compounds essential for infant health. Recent advances in omics technologies-such as proteomics, metabolomics, and transcriptomics-have shed light on the influence of HM on bone development and health. This review discusses the impact of various HM components, including proteins, lipids, carbohydrates, and hormones, on bone metabolism and skeletal growth. Proteins like casein and whey promote calcium absorption and osteoblast differentiation, supporting bone mineralization. Long-chain polyunsaturated fatty acids like docosahexaenoic acid (DHA) contribute to bone health by modulating inflammatory pathways and regulating osteoclast activity. Additionally, human milk oligosaccharides (HMOs) act as prebiotics, improving gut health and calcium bioavailability while influencing bone mineralization. Hormones present in HM, such as insulin-like growth factor 1 (IGF-1), leptin, and adiponectin, have been linked to infant growth, body composition, and bone density. Research has shown that higher IGF-1 levels in breast milk are associated with increased weight gain, while leptin and adiponectin influence fat mass and bone metabolism. Emerging studies have also highlighted the role of microRNAs (miRNAs) in regulating key processes like adipogenesis and bone homeostasis. Furthermore, microbiome-focused techniques reveal HM's role in establishing a balanced infant gut microbiota, indirectly influencing bone development by enhancing nutrient absorption. Although current findings are promising, comprehensive longitudinal studies integrating omics approaches are needed to fully understand the intricate relationships among maternal diet, HM composition, and infant bone health. Bridging these gaps could offer novel dietary strategies to optimize skeletal health during infancy, advancing early-life nutrition science.

Mass Spectrometry-Based Metabolomics Reveals a Salivary Signature for Low-Severity COVID-19.

Omics approaches were extensively applied during the coronavirus disease 2019 (COVID-19) pandemic to understand the disease, identify biomarkers with diagnostic and prognostic value, and discover new molecular targets for medications. COVID-19 continues to challenge the healthcare system as the virus mutates, becoming more transmissible or adept at evading the immune system, causing resurgent epidemic waves over the last few years. In this study, we used saliva from volunteers who were negative and positive for COVID-19 when Omicron and its variants became dominant. We applied a direct solid-phase extraction approach followed by non-target metabolomics analysis to identify potential salivary signatures of hospital-recruited volunteers to establish a model for COVID-19 screening. Our model, which aimed to differentiate COVID-19-positive individuals from controls in a hospital setting, was based on 39 compounds and achieved high sensitivity (85%/100%), specificity (82%/84%), and accuracy (84%/92%) in training and validation sets, respectively. The salivary diagnostic signatures were mainly composed of amino acids and lipids and were related to a heightened innate immune antiviral response and an attenuated inflammatory profile. The higher abundance of thyrotropin-releasing hormone in the COVID-19 positive group highlighted the endocrine imbalance in low-severity disease, as first reported here, underscoring the need for further studies in this area.

Unraveling heterogeneity and treatment of asthma through integrating multi-omics data.

Asthma has become one of the most serious chronic respiratory diseases threatening people's lives worldwide. The pathogenesis of asthma is complex and driven by numerous cells and their interactions, which contribute to its genetic and phenotypic heterogeneity. The clinical characteristic is insufficient for the precision of patient classification and therapies; thus, a combination of the functional or pathophysiological mechanism and clinical phenotype proposes a new concept called "asthma endophenotype" representing various patient subtypes defined by distinct pathophysiological mechanisms. High-throughput omics approaches including genomics, epigenomics, transcriptomics, proteomics, metabolomics and microbiome enable us to investigate the pathogenetic heterogeneity of diverse endophenotypes and the underlying mechanisms from different angles. In this review, we provide a comprehensive overview of the roles of diverse cell types in the pathophysiology and heterogeneity of asthma and present a current perspective on their contribution into the bidirectional interaction between airway inflammation and airway remodeling. We next discussed how integrated analysis of multi-omics data via machine learning can systematically characterize the molecular and biological profiles of genetic heterogeneity of asthma phenotype. The current application of multi-omics approaches on patient stratification and therapies will be described. Integrating multi-omics and clinical data will provide more insights into the key pathogenic mechanism in asthma heterogeneity and reshape the strategies for asthma management and treatment.

Looking back at the TEDDY study: lessons and future directions.

The goal of theTEDDY (The Environmental Determinants of Diabetes in the Young) study is to elucidate factors leading to the initiation of islet autoimmunity (first primary outcome) and those related to progression to type 1 diabetes mellitus (T1DM; second primary outcome). This Review outlines the key findings so far, particularly related to the first primary outcome. The background, history and organization of the study are discussed. Recruitment and follow-up (from age 4 months to 15 years) of 8,667 children showed high retention and compliance. End points of the presence of autoantibodies against insulin, GAD65, IA-2 and ZnT8 revealed the HLA-associated early appearance of insulin autoantibodies (1-3 years of age) and the later appearance of GAD65 autoantibodies. Competing autoantibodies against tissue transglutaminase (marking coeliac disease autoimmunity) also appeared early (2-4 years). Genetic and environmental factors, including enterovirus infection and gastroenteritis, support mechanistic differences underlying one phenotype of autoimmunity against insulin and another against GAD65. Infant growth and both probiotics and high protein intake affect the two phenotypes differently, as do serious life events during pregnancy. As the end of the TEDDY sampling phase is approaching, major omics approaches are in progress to further dissect the mechanisms that might explain the two possible endotypes of T1DM.

Multi-site Ultrasound-guided Fine Needle Aspiration to Study Cells and Soluble Factors From Human Lymph Nodes.

Lymph nodes (LNs) are specialized secondary lymphoid tissues essential to the priming and maintenance of adaptive immune responses, including the B cell germinal center response; thus, they are central to immunity. However, the anatomically restricted and time-resolved nature of immune priming means that sampling disease-relevant human LNs requires specialized techniques. This article describes the application of ultrasound-guided fine-needle aspiration (FNA) to sample LNs, using cervical LNs of the head and neck as an exemplar. This minimally invasive technique allows collection of both immune cells and cell-free material that are relevant to both neuroimmune diseases and basic lymphatic functions. Downstream use of cellular material can include multiplexed flow cytometry, single-cell transcriptome sequencing (RNA-seq), and B cell cultures. The cell-free supernatant can be used for proteomics or other similar 'omics approaches. This unit describes collection of samples by FNA as well as processing and storage of samples for downstream assays. © 2024 The Author(s). Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Sampling of human cervical lymph nodes by ultrasound-guided fine-needle aspiration Alternate Protocol: Sampling of human lymph nodes by ultrasound-guided fine-needle aspiration with negative pressure Basic Protocol 2: Processing and storage of human lymph node samples.

Arctic's hidden hydrocarbon degradation microbes: investigating the effects of hydrocarbon contamination, biostimulation, and a surface washing agent on microbial communities and hydrocarbon biodegradation pathways in high-Arctic beaches

BackgroundCanadian Arctic summer sea ice has dramatically declined due to global warming, resulting in the rapid opening of the Northwest Passage (NWP), slated to be a major shipping route connecting the Atlantic and Pacific Oceans by 2040. This development elevates the risk of oil spills in Arctic regions, prompting growing concerns over the remediation and minimizing the impact on affected shorelines.ResultsThis research aims to assess the viability of nutrient and a surface washing agent addition as potential bioremediation methods for Arctic beaches. To achieve this goal, we conducted two semi-automated mesocosm experiments simulating hydrocarbon contamination in high-Arctic beach tidal sediments: a 32-day experiment at 8 °C and a 92-day experiment at 4 °C. We analyzed the effects of hydrocarbon contamination, biostimulation, and a surface washing agent on the microbial community and its functional capacity using 16S rRNA gene sequencing and metagenomics. Hydrocarbon removal rates were determined through total petroleum hydrocarbon analysis. Biostimulation is commonly considered the most effective strategy for enhancing the bioremediation process in response to oil contamination. However, our findings suggest that nutrient addition has limited effectiveness in facilitating the biodegradation process in Arctic beaches, despite its initial promotion of aliphatic hydrocarbons within a constrained timeframe. Alternatively, our study highlights the promise of a surface washing agent as a potential bioremediation approach. By implementing advanced -omics approaches, we unveiled highly proficient, unconventional hydrocarbon-degrading microorganisms such as Halioglobus and Acidimicrobiales genera.ConclusionsGiven the receding Arctic sea ice and the rising traffic in the NWP, heightened awareness and preparedness for potential oil spills are imperative. While continuously exploring optimal remediation strategies through the integration of microbial and chemical studies, a paramount consideration involves limiting traffic in the NWP and Arctic regions to prevent beach oil contamination, as cleanup in these remote areas proves exceedingly challenging and costly.

Omics in IgG4-related disease.

Research on IgG4-related disease (IgG4-RD), an autoimmune condition recognized to be a unique disease entity only two decades ago, has processed from describing patients' symptoms and signs to summarizing its critical pathological features, and further to investigating key pathogenic mechanisms. Challenges in gaining a better understanding of the disease, however, stem from its relative rarity-potentially attributed to underrecognition - and the absence of ideal experimental animal models. Recently, with the development of various high-throughput techniques, "omics" studies at different levels (particularly the single-cell omics) have shown promise in providing detailed molecular features of IgG4-RD. While, the application of omics approaches in IgG4-RD is still at an early stage. In this paper, we review the current progress of omics research in IgG4-RD and discuss the value of machine learning methods in analyzing the data with high dimensionality.

Integrated systems biology identifies disruptions in mitochondrial function and metabolism as key contributors to heart failure with preserved ejection fraction (HFpEF).

Heart failure with preserved ejection fraction (HFpEF) accounts for ~50% of HF cases, with no effective treatments. The ZSF1-obese rat model recapitulates numerous clinical features of HFpEF including hypertension, obesity, metabolic syndrome, exercise intolerance, and LV diastolic dysfunction. Here, we utilized a systems-biology approach to define the early metabolic and transcriptional signatures to gain mechanistic insight into the pathways contributing to HFpEF development. Male ZSF1-obese, ZSF1-lean hypertensive controls, and WKY (wild-type) controls were compared at 14w of age for extensive physiological phenotyping and LV tissue harvesting for unbiased metabolomics, RNA-sequencing, and assessment of mitochondrial morphology and function. Utilizing ZSF1-lean and WKY controls enabled a distinction between hypertension-driven molecular changes contributing to HFpEF pathology, versus hypertension + metabolic syndrome. ZSF1-obese rats displayed numerous clinical features of HFpEF. Comparison of ZSF1-lean vs WKY (i.e., hypertension-exclusive effects) revealed metabolic remodeling suggestive of increased aerobic glycolysis, decreased β-oxidation, and dysregulated purine and pyrimidine metabolism with few transcriptional changes. ZSF1-obese rats displayed worsened metabolic remodeling and robust transcriptional remodeling highlighted by the upregulation of inflammatory genes and downregulation of the mitochondrial structure/function and cellular metabolic processes. Integrated network analysis of metabolomic and RNAseq datasets revealed downregulation of nearly all catabolic pathways contributing to energy production, manifesting in a marked decrease in the energetic state (i.e., reduced ATP/ADP, PCr/ATP). Cardiomyocyte ultrastructure analysis revealed decreased mitochondrial area, size, and cristae density, as well as increased lipid droplet content in HFpEF hearts. Mitochondrial function was also impaired as demonstrated by decreased substrate-mediated respiration and dysregulated calcium handling. Collectively, the integrated omics approach applied here provides a framework to uncover novel genes, metabolites, and pathways underlying HFpEF, with an emphasis on mitochondrial energy metabolism as a potential target for intervention.

Leveraging multi-omics tools to comprehend responses and tolerance mechanisms of heavy metals in crop plants.

Extreme anthropogenic activities and current farming techniques exacerbate the effects of water and soil impurity by hazardous heavy metals (HMs), severely reducing agricultural output and threatening food safety. In the upcoming years, plants that undergo exposure to HM might cause a considerable decline in the development as well as production. Hence, plants have developed sophisticated defensive systems to evade or withstand the harmful consequences of HM. These mechanisms comprise the uptake as well as storage of HMs in organelles, their immobilization via chemical formation by organic chelates, and their removal using many ion channels, transporters, signaling networks, and TFs, amid other approaches. Among various cutting-edge methodologies, omics, most notably genomics, transcriptomics, proteomics, metabolomics, miRNAomics, phenomics, and epigenomics have become game-changing approaches, revealing information about the genes, proteins, critical metabolites as well as microRNAs that govern HM responses and resistance systems. With the help of integrated omics approaches, we will be able to fully understand the molecular processes behind plant defense, enabling the development of more effective crop protection techniques in the face of climate change. Therefore, this review comprehensively presented omics advancements that will allow resilient and sustainable crop plants to flourish in areas contaminated with HMs.

Combining metabolomics and machine learning to discover biomarkers for early-stage breast cancer diagnosis.

There is an urgent need for better biomarkers for the detection of early-stage breast cancer. Utilizing untargeted metabolomics and lipidomics in conjunction with advanced data mining approaches for metabolism-centric biomarker discovery and validation may enhance the identification and validation of novel biomarkers for breast cancer screening. In this study, we employed a multimodal omics approach to identify and validate potential biomarkers capable of differentiating between patients with breast cancer and those with benign tumors. Our findings indicated that ether-linked phosphatidylcholine exhibited a significant difference between invasive ductal carcinoma and benign tumors, including cases with inconsistent mammography results. We observed alterations in numerous lipid species, including sphingomyelin, triacylglycerol, and free fatty acids, in the breast cancer group. Furthermore, we identified several dysregulated hydrophilic metabolites in breast cancer, such as glutamate, glycochenodeoxycholate, and dimethyluric acid. Through robust multivariate receiver operating characteristic analysis utilizing machine learning models, either linear support vector machines or random forest models, we successfully distinguished between cancerous and benign cases with promising outcomes. These results emphasize the potential of metabolic biomarkers to complement other criteria in breast cancer screening. Future studies are essential to further validate the metabolic biomarkers identified in our study and to develop assays for clinical applications.

Multiomics approach discloses lipids and metabolites profiles associated to Parkinson's disease stages and applied therapies

Profiling circulating lipids and metabolites in Parkinson's disease (PD) patients could be useful not only to highlight new pathways affected in PD condition but also to identify sensitive and effective biomarkers for early disease detection and potentially effective therapeutic interventions. In this study we adopted an untargeted omics approach in three groups of patients (No L-Dopa, L-Dopa and DBS) to disclose whether long-term levodopa treatment with or without deep brain stimulation (DBS) could reflect a characteristic lipidomic and metabolomic signature at circulating level. Our findings disclosed a wide up regulation of the majority of differentially regulated lipid species that increase with disease progression and severity. We found a relevant modulation of triacylglycerols and acyl-carnitines, together with an altered profile in adiponectin and leptin, that can differentiate the DBS treated group from the others PD patients. We found a highly significant increase of exosyl ceramides (Hex2Cer) and sphingoid bases (SPB) in PD patients mainly in DBS group (p < 0.0001), which also resulted in a highly accurate diagnostic performance. At metabolomic level, we found a wide dysregulation of pathways involved in the biosynthesis and metabolism of several amino acids. The most interesting finding was the identification of a specific modulation of L-glutamic acid in the three groups of patients. L-glutamate levels increased slightly in No L-Dopa and highly in L-Dopa patients while decreased in DBS, suggesting that DBS therapy might have a beneficial effect on the glutamatergic cascade. All together, these data provide novel insights into the molecular and metabolic alterations underlying PD therapy and might be relevant for PD prediction, diagnosis and treatment.

The toxic effects of exposure to fibrous and fragmented microplastic in juvenile rockfish based on two omics approach

Although the hazards of environmental microplastics (MPs) are well known, it is unclear which of their characteristics have the greatest effects on organism. We investigated the toxic effects of oral administration according to physical properties, including the shape of fragmented polyethylene terephthalate (PET) (FrPET) and fibrous PET (FiPET) MPs. After 72 h of exposure, apoptosis and phagocytic activity varied significantly among juvenile rockfish (Sebastes schlegeli) exposed to both FrPET and FiPET. The levels of immune-related genes and hepatic metabolic activity also increased after exposure to both shapes of MPs, but the variation in responses was greater in fish exposed to FiPET compared with those exposed to FrPET. The transcriptomic and metabolomics analysis results indicated that the maintenance and homeostasis of immune system was affected by oral exposure to FrPET and FiPET. The amino acid metabolic processes were identified in rockfish exposed to FrPET, but the notch signaling pathway were evident in the FiPET exposure group. Metabolomics analysis revealed that oral ingestion of MP fibers led to a stronger inflammatory response and greater oxidative stress in juvenile rockfish. These results can be used to understand environmentally dominant MP toxic effects such as type, size, shapes, as well as to prioritize ecotoxicological management.

LITERATURE REVIEW: THE OMICS STUDY FOR DETERMINING BIOMARKERS IN HUMAN SERUM AND PLASMA WITH DIFFERENT COVID-19 SEVERITY

The severity of COVID-19 provides information on various stages of changes in the body's normal state in various parameters called biological markers (biomarkers) as the initial identification that facilitates management, selection, and total outcomes in therapy. These biomarkers were selected from the selection of samples that are often used in the advanced diagnosis of COVID-19, serum and plasma. This study aims to determine what biomarkers are measured in serum and plasma samples of COVID-19 patients. This literature review is classified as non-experimental, qualitative, and descriptive research. The inclusion criteria are the full-text journals published within the last two years regarding biomarkers in the serum and plasma of COVID-19 patients. Based on these criteria, 49 relevant articles were obtained. The results show that changes occur in the protein, lipid, and metabolite in serum and plasma by the omics approach. These alterations can be in the form of increasing or decreasing levels of each parameter determined through various analytical methods. The biomarkers profile correlates with the severity of COVID-19 as well as with host cells.