Omics Tools Research Articles

Can Transcriptomics Elucidate the Role of Regulation in Invasion Success?

When a species invades a novel environment, it must bridge the environment-phenotype mismatch in its new range to persist. Contemporary invasion biology research has focused on the role that trait variation and adaptation, and their underlying genomic factors, play in a species' adaptive potential, and thus facilitating invasion. Empirical studies have provided valuable insights into phenotypes that persist and arise in novel environments, coupled with 'omics tools that further the understanding of the contributions of genomic architecture in species establishment. Particularly, the use of transcriptomics to explore the role of plasticity in the initial stages of an invasion is growing. Here, we assess the role of various mechanisms relating to regulation and functional adaptation (often measured via the transcriptome) that support trait-specific plasticity in invasive species, allowing phenotypic variability without directly altering genomic diversity. First, we present a comprehensive review of the studies utilising transcriptomics in invasion biology. Second, we collate the evidence for and against the role of a range of regulatory processes in contributing to invasive species plasticity. Finally, we pose open questions in invasion biology where the use of transcriptome data may be valuable, as well as discuss the methodological limitations.

Probing the functional significance of wild animal microbiomes using omics data

Abstract Host‐associated microbiomes are thought to play a key role in host physiology and fitness, but this conclusion mainly derives from systems biased towards animal models and humans. While many studies on non‐model and wild animals have characterised the taxonomic diversity of their microbiomes, few have investigated the functional potential of these microbial communities. Functional ‘omics’ approaches, such as metagenomics, metatranscriptomics and metabolomics, represent promising techniques to probe the significance of host‐associated microbiomes in the wild. In this review, we propose to (1) briefly define the main available functional omics tools along with their strengths and limitations, (2) summarise the key advances enabled by omics tools to understand microbiome function in human and animal models, (3) showcase examples of how these methods have already brought invaluable insights into wild host microbiomes and (4) provide guidelines on how to implement these tools to address outstanding questions in the field of wild animal microbiomes. To conclude, we suggest that, building on knowledge derived from cheaper, more traditional approaches (e.g. 16S metabarcoding and qPCR), functional omics tools represent a promising approach to test hypotheses regarding the ecological and evolutionary significance of the resident microbiota in wild animals. Read the free Plain Language Summary for this article on the Journal blog.

Alginate oligosaccharide supplementation improves boar semen quality under heat stress

Heat stress is a serious problem that affects animal husbandry by reducing growth and reproductive performance of animals. Adding plant extracts to the diet is an effective way to help overcome this problem. Alginate oligosaccharide (AOS) is a natural non-toxic antioxidant with multiple biological activities. This study analyzed the potential mechanism of AOS in alleviating heat stress and improving semen quality in boars through a combination of multiple omics tools. The results indicated that AOS could significantly increase sperm motility (P < 0.001) and sperm concentration (P < 0.05). At the same time, AOS improved the antioxidant capacity of blood and semen, and increased blood testosterone (P < 0.05) level. AOS could improve the metabolites in sperm, change the composition of gut microbiota, increase the relative abundance of beneficial bacteria such as Pseudomonas (P < 0.01), Escherichia-Shigella (P < 0.05), Bifidobacterium (P < 0.01), reduce the relative abundance of harmful bacteria such as Prevotella_9 (P < 0.05), Prevotellaceae_UCG-001 (P < 0.01), and increase the content of short chain fatty acids. Proteomic results showed that AOS increased proteins related to spermatogenesis, while decreasing heat shock protein 70 (P < 0.05) and heat shock protein 90 (P < 0.01). These results were verified using immunofluorescence staining technology. There was a good correlation among sperm quality, sperm metabolome, sperm proteome, and gut microbiota. In conclusion, AOS can be used as a feed additive to increase the semen quality of boars to enhance reproductive performance under heat stress.

Biotechnological approaches for enhancement of heavy metal phytoremediation capacity of plants.

Heavy metals are extremely hazardous for human health due to their toxic effects. They are non-biodegradable in nature, thus remain in the environment and enter and accumulate in the human body through biomagnification; hence, there is a serious need of their remediation. Phytoremediation has emerged as a green, sustainable, and effective solution for heavy metal removal and many plant species could be employed for this purpose. Plants are able to sequester substantial quantity of heavy metals, in some cases thousands of ppm, due to their robust physiology enabling high metal tolerance and anatomy supporting metal ion accumulation. Identification and modification of potential target genes involved in heavy metal accumulation have led to improved phytoremediation capacity of plants at the molecular level. The introduction of foreign genes through genetic engineering approaches has further enhanced phytoremediation capacity manifolds. This review gives an insight towards improving the phytoremediation efficiency through a better understanding of molecular mechanisms involved, expression of different proteins, genetic engineering approaches for transgenic production, and genetic modifications. It also comprehends novel omics tools such as genomics, metabolomics, proteomics, transcriptomics, and genome editing technologies for improvement of phytoremediation ability of plants.

Lessons from Extremophiles: Functional Adaptations and Genomic Innovations across the Eukaryotic Tree of Life.

From hydrothermal vents, to glaciers, to deserts, research in extreme environments has reshaped our understanding of how and where life can persist. Contained within the genomes of extremophilic organisms are the blueprints for a toolkit to tackle the multitude of challenges of survival in inhospitable environments. As new sequencing technologies have rapidly developed, so too has our understanding of the molecular and genomic mechanisms that have facilitated the success of extremophiles. Although eukaryotic extremophiles remain relatively understudied compared to bacteria and archaea, an increasing number of studies have begun to leverage 'omics tools to shed light on eukaryotic life in harsh conditions. In this perspective paper, we highlight a diverse breadth of research on extremophilic lineages across the eukaryotic tree of life, from microbes to macrobes, that are collectively reshaping our understanding of molecular innovations at life's extremes. These studies are not only advancing our understanding of evolution and biological processes but are also offering a valuable roadmap on how emerging technologies can be applied to identify cellular mechanisms of adaptation to cope with life in stressful conditions, including high and low temperatures, limited water availability, and heavy metal habitats. We shed light on patterns of molecular and organismal adaptation across the eukaryotic tree of life and discuss a few promising research directions, including investigations into the role of horizontal gene transfer in eukaryotic extremophiles and the importance of increasing phylogenetic diversity of model systems.

Traditional to technological advancements in Ganoderma detection methods in oil palm.

Ganoderma sp., the fungal agent causing basal stem rot (BSR), poses a severe threat to global oil palm production. Alarming increases in BSR occurrences within oil palm growing zones are attributed to varying effectiveness in its current management strategies. Asymptomatic progression of the disease and the continuous monoculture of oil palm pose challenges for prompt and effective management. Therefore, the development of precise, early, and timely detection techniques is crucial for successful BSR management. Conventional methods such as visual assessments, culture-based assays, and biochemical and physiological approaches prove time-consuming and lack specificity. Serological-based diagnostic methods, unsuitable for fungal diagnostics due to low sensitivity, assay affinity, cross-contamination which further underscores the need for improved techniques. Molecular PCR-based assays, utilizing universal, genus-specific, and species-specific primers, along with functional primers, can overcome the limitations of conventional and serological methods in fungal diagnostics. Recent advancements, including real-time PCR, biosensors, and isothermal amplification methods, facilitate accurate, specific, and sensitive Ganoderma detection. Comparative whole genomic analysis enables high-resolution discrimination of Ganoderma at the strain level. Additionally, omics tools such as transcriptomics, proteomics, and metabolomics can identify potential biomarkers for early detection of Ganoderma infection. Innovative on-field diagnostic techniques, including remote methods like volatile organic compounds profiling, tomography, hyperspectral and multispectral imaging, terrestrial laser scanning, and Red-Green-Blue cameras, contribute to a comprehensive diagnostic approach. Ultimately, the development of point-of-care, early, and cost-effective diagnostic techniques accessible to farmers is vital for the timely management of BSR in oil palm plantations.

CViewer: a Java-based statistical framework for integration of shotgun metagenomics with other omics datasets

BackgroundShotgun metagenomics for microbial community survey recovers enormous amount of information for microbial genomes that include their abundances, taxonomic, and phylogenetic information, as well as their genomic makeup, the latter of which then helps retrieve their function based on annotated gene products, mRNA, protein, and metabolites. Within the context of a specific hypothesis, additional modalities are often included, to give host-microbiome interaction. For example, in human-associated microbiome projects, it has become increasingly common to include host immunology through flow cytometry. Whilst there are plenty of software approaches available, some that utilize marker-based and assembly-based approaches, for downstream statistical analyses, there is still a dearth of statistical tools that help consolidate all such information in a single platform. By virtue of stringent computational requirements, the statistical workflow is often passive with limited visual exploration.ResultsIn this study, we have developed a Java-based statistical framework (https://github.com/KociOrges/cviewer) to explore shotgun metagenomics data, which integrates seamlessly with conventional pipelines and offers exploratory as well as hypothesis-driven analyses. The end product is a highly interactive toolkit with a multiple document interface, which makes it easier for a person without specialized knowledge to perform analysis of multiomics datasets and unravel biologically relevant patterns. We have designed algorithms based on frequently used numerical ecology and machine learning principles, with value-driven from integrated omics tools which not only find correlations amongst different datasets but also provide discrimination based on case–control relationships.ConclusionsCViewer was used to analyse two distinct metagenomic datasets with varying complexities. These include a dietary intervention study to understand Crohn’s disease changes during a dietary treatment to include remission, as well as a gut microbiome profile for an obesity dataset comparing subjects who suffer from obesity of different aetiologies and against controls who were lean. Complete analyses of both studies in CViewer then provide very powerful mechanistic insights that corroborate with the published literature and demonstrate its full potential.EDLr-6-tH-9CdVCxoa6z_8Video

Insights into wheat science: A bibliometric review using unsupervised machine learning techniques

Wheat (Triticum spp.) has been one of the most important cereal crops, serving as a source of protein and energy in the human diet. It remains a vital component of global food security, with extensive scientific literature dedicated to its study, although the large volume of literature often hinders global analysis. In this study, different unsupervised machine learning techniques, such as K-Nearest Neighbors (KNN) and Uniform Manifold Approximation and Projection (UMAP), text mining analyses, including word embeddings and statistical word analysis, and graph analysis methodologies, were applied to gain a deeper understanding of the wheat literature. The proposed bibliometric analysis was conducted and integrated with the Journal Citation Reports (JCR) to identify major wheat research trends in the PubMed literature. This analysis examined the evolution of these trends over time, evaluated the geographical distribution, impact, and research domains, and assessed author collaboration networks and the evolving relevance of different countries. Research on disease resistance, genetic modification, and dietary impact demonstrates a consistent increase in output, while interest in topics related to overcoming salt stress and enhancing animal feed appears to be diminishing. Interestingly, research on wheat germ agglutinin saw a surge in interest during the late 2000s, stabilizing thereafter. These trends underscore the dynamic nature of wheat research, driven by evolving priorities and technological advancements, particularly in genetics and omics tools. Moreover, the increasing significance of China in wheat research, including its size, impact, and networking, alongside longstanding leaders such as the United States, signals a shifting landscape in global wheat research.

Progress in the Use of Combined Omics for Mungbean Breeding Improvement and Its Potential in Promoting Resistance against Cercospora Leaf Spot

Cercospora leaf spot (CLS) is the most destructive fungal disease, deteriorating the production and productivity of mungbean (Vigna radiata (L.) Wilczek). Mungbean is one of the most nutritionally and environmentally important legumes, with popularity currently increasing as a ‘future smart food crop’ due to its several health benefits. In recent years, there has been considerable research progress in improving disease resistance in legumes. However, only a limited number of studies have pinpointed potential genes and candidate genes associated with resistance traits to CLS in mungbeans. Identifying the potential resistant resources through combined omics approaches is an efficient strategy to screen the best Cercospora-resistant mungbean varieties for further molecular breeding and improvement. Potential omics approaches are important tools to predict disease management strategies, alleviate chemical overuse, and mitigate problems due to malnutrition. Sustainable breeding research efforts using potential combined omics, including automated phenotyping, to promote important resistant traits associated with CLS in mungbeans are still unexplored and a key issue that needs to be addressed. Omics-technology-based research findings on resistance genes, proteins, and metabolites against CLS in mungbean are recognised in this review. Due to a limitation of research findings specifically underscoring the use of omics tools for screening resistant mungbean against CLS, best related research outcomes on other crops are included in this review.

“Omic tools” for investigation creative plant systens

The result of the genotype/environment (G/E) interaction affects the success of the implementation of the genetic program of a plant biological system of any level, from a cell population to a multicellular organism. During this interaction, the plant system absorbs trophic and energy resources, processes and assimilates them. Under normal conditions, signal perception and transduction occurs against the background of homeostasis regulated by the genome. Genetic control is exercised at all stages of growth and development of plant systems via differential gene expression. The activity of metabolism is coordinated by the cooparated action of the ionome, proteome, metabolome, and transcriptome. Direct and cross connections between these aspects of life activity are established and developed constantly and manifest themselves in the form of dynamic phenotypic effects from structural formations and enzyme chains. Disturbanses within the individual stages of metabolism and the disconnection between them reveal differences between stable, sensitive and unstable forms. The obtained information is the basis for experiments to obtain forms with improved characteristics. A range of tasks has been outlined in this direction, and there have already been significant developments. Comparison of the dynamics of the functioning of creative variants of plant systems of any level showed their significant differences from the original forms. Changes in creative systems are determined by the interactions of transgenes with endogenous genes and can manifest themselves in the form of positive/negative/combined characteristics of the new system. Comparative studies of the dynamics of vital activity will provide information about the coordinated process of communication both within the cell and between the tissues of a multicellular organism. The use of various combinations of “omic tools” will facilitate the discovery of new promising candidates among structural and regulatory genes, as well as among promoters. On the other hand, the obtained biological information will be a stimulus for improving the methods and directions of research.

Multi-omic analysis tools for microbial metabolites prediction.

How to resolve the metabolic dark matter of microorganisms has long been a challenging problem in discovering active molecules. Diverse omics tools have been developed to guide the discovery and characterization of various microbial metabolites, which make it gradually possible to predict the overall metabolites for individual strains. The combinations of multi-omic analysis tools effectively compensates for the shortcomings of current studies that focus only on single omics or a broad class of metabolites. In this review, we systematically update, categorize and sort out different analysis tools for microbial metabolites prediction in the last five years to appeal for the multi-omic combination on the understanding of the metabolic nature of microbes. First, we provide the general survey on different updated prediction databases, webservers, or software that based on genomics, transcriptomics, proteomics, and metabolomics, respectively. Then, we discuss the essentiality on the integration of multi-omics data to predict metabolites of different microbial strains and communities, as well as stressing the combination of other techniques, such as systems biology methods and data-driven algorithms. Finally, we identify key challenges and trends in developing multi-omic analysis tools for more comprehensive prediction on diverse microbial metabolites that contribute to human health and disease treatment.

Insights into the differential proteome landscape of a newly isolated Paramecium multimicronucleatum in response to cadmium stress

Employing microbial systems for the bioremediation of contaminated waters represent a potential option, however, limited understanding of the underlying mechanisms hampers the implication of microbial-mediated bioremediation. The omics tools offer a promising approach to explore the molecular basis of the bioremediation process. Here, a mass spectrometry-based quantitative proteome profiling approach was conducted to explore the differential protein levels in cadmium-treated Paramecium multimicronucleatum. The Proteome Discoverer software was used to identify and quantify differentially abundant proteins. The proteome profiling generated 7,416 peptide spectral matches, yielding 2824 total peptides, corresponding to 989 proteins. The analysis revealed that 29 proteins exhibited significant (p ≤ 0.05) differential levels, including a higher abundance of 6 proteins and reduced levels of 23 proteins in Cd2+ treated samples. These differentially abundant proteins were associated with stress response, energy metabolism, protein degradation, cell growth, and hormone processing. Briefly, a comprehensive proteome profile in response to cadmium stress of a newly isolated Paramecium has been established that will be useful in future studies identifying critical proteins involved in the bioremediation of metals in ciliates. SignificanceCiliates are considered a good biological indicator of chemical pollution and relatively sensitive to heavy metal contamination. A prominent ciliate, Paramecium is a promising candidate for the bioremediation of polluted water. The proteins related to metal resistance in Paramecium species are still largely unknown and need further exploration. In order to identify and reveal the proteins related to metal resistance in Paramecia, we have reported differential protein abundance in Paramecium multimicronucleatum in response to cadmium stress. The proteins found in our study play essential roles during stress response, hormone processing, protein degradation, energy metabolism, and cell growth. It seems likely that Paramecia are not a simple sponge for metals but they could also transform them into less toxic derivatives or by detoxification by protein binding. This data will be helpful in future studies to identify critical proteins along with their detailed mechanisms involved in the bioremediation and detoxification of metal ions in Paramecium species.

Multiomics data integration, limitations, and prospects to reveal the metabolic activity of the coral holobiont.

Since their radiation in the Middle Triassic period ∼240 million years ago, stony corals have survived past climate fluctuations and five mass extinctions. Their long-term survival underscores the inherent resilience of corals, particularly when considering the nutrient-poor marine environments in which they have thrived. However, coral bleaching has emerged as a global threat to coral survival, requiring rapid advancements in coral research to understand holobiont stress responses and allow for interventions before extensive bleaching occurs. This review encompasses the potential, as well as the limits, of multiomics data applications when applied to the coral holobiont. Synopses for how different omics tools have been applied to date and their current restrictions are discussed, in addition to ways these restrictions may be overcome, such as recruiting new technology to studies, utilizing novel bioinformatics approaches, and generally integrating omics data. Lastly, this review presents considerations for the design of holobiont multiomics studies to support lab-to-field advancements of coral stress marker monitoring systems. Although much of the bleaching mechanism has eluded investigation to date, multiomic studies have already produced key findings regarding the holobiont's stress response, and have the potential to advance the field further.

Advances in Genetic Enhancement of Nutritional Quality of Tropical Maize in West and Central Africa

Micronutrient deficiencies are pervasive in the diets of millions of people in developing countries, calling for effective mitigation measures. The development of biofortified cultivars through breeding holds promise for sustainable and affordable solutions to combat micronutrient deficiencies. Breeding efforts in the past decade have resulted in dozens of biofortified open-pollinated varieties and hybrids adapted to diverse agroecological zones. Advances in genomics and molecular tools enabled rapid identification of maize cultivars enriched with essential micronutrients such as pro vitamin A (PVA), iron (Fe), and zinc (Zn). Leveraging Multi-omics-driven discovery of the genetic factors underlying the vast array of nutritional traits is paramount to mainstreaming breeding for quality traits in the product profile. Molecular breeding schemes, and integrating emerging Omics tools at every stage of the breeding pipeline, are vital to enhancing genetic gain. The recent momentum in elucidating the metabolism of micronutrients should be expanded to novel breeding targets as well as to the simultaneous enhancement of nutritional qualities while curtailing anti-nutritional factors in staple food crops. Harnessing new technologies to establish comprehensive and integrated breeding approaches involving nutrigenomics, genome editing, and agronomic biofortification is crucial in tackling nutritional insecurity. This review highlights the prospect of integrating modern tools in hastening the genetic improvement of nutritionally enriched maize.

Packaging and containerization of computational methods.

Methods for analyzing the full complement of a biomolecule type, e.g., proteomics or metabolomics, generate large amounts of complex data. The software tools used to analyze omics data have reshaped the landscape of modern biology and become an essential component of biomedical research. These tools are themselves quite complex and often require the installation of other supporting software, libraries and/or databases. A researcher may also be using multiple different tools that require different versions of the same supporting materials. The increasing dependence of biomedical scientists on these powerful tools creates a need for easier installation and greater usability. Packaging and containerization are different approaches to satisfy this need by delivering omics tools already wrapped in additional software that makes the tools easier to install and use. In this systematic review, we describe and compare the features of prominent packaging and containerization platforms. We outline the challenges, advantages and limitations of each approach and some of the most widely used platforms from the perspectives of users, software developers and system administrators. We also propose principles to make the distribution of omics software more sustainable and robust to increase the reproducibility of biomedical and life science research.

Proteomic analysis reveals that the co-ordination of cytosolic and mitochondrial pathways is beneficial for sabinene biosynthesis in engineered Saccharomyces cerevisiae.

Reconstruction and optimization of biosynthetic pathways can help to overproduce target chemicals in microbial cell factories based on genetic engineering. However, the perturbation of biosynthetic pathways on cellular metabolism is not well investigated and profiling the engineered microbes remains challenging. The rapid development of omics tools has the potential to characterize the engineered microbial cell factory. Here, we performed label-free quantitative proteomic analysis and metabolomic analysis of engineered sabinene overproducing Saccharomyces cerevisiae strains. Combined metabolic analysis andproteomic analysis of targeted mevalonate (MVA) pathway showed that co-ordination of cytosolic and mitochondrial pathways had balanced metabolism, and genome integration of biosynthetic genes had higher sabinene production with less MVA enzymes. Furthermore, comparative proteomic analysis showed that compartmentalized mitochondria pathway had perturbation on central cellular metabolism. This study provided an omics analysis example for characterizing engineered cell factory, which can guide future regulation of the cellular metabolism and maintaining optimal protein expression levels for the synthesis of target products.

Decoupling between the genetic potential and the metabolic regulation and expression in microbial organic matter cleavage across microbiomes.

Omics tools are used to explore adaptive mechanism of microbes in diverse systems, but the advantages and limitations of different omics tools remain skeptical. Here, we reported distinct profiles in microbial secretory enzyme composition revealed by different omics methods. In general, the predicted function from metagenomic analysis decoupled from the expression of corresponding transcripts/proteins. Linking omics results to taxonomic origin, functional capability, substrate specificity, secretion preference, and enzymatic activity measurement suggested the substrate's source, concentration and stoichiometry impose strong filtering on the expression of extracellular enzymes, which may overwrite the genetic potentials. Our results present an integrated perspective on the need for multi-dimensional characterization of microbial adaptation in a changing environment.

Comparative analysis of 10X Chromium vs. BD Rhapsody whole transcriptome single-cell sequencing technologies in complex human tissues

The development of single-cell omics tools has enabled scientists to study the tumor microenvironment (TME) in unprecedented detail. However, each of the different techniques may have its unique strengths and limitations. Here we directly compared two commercially available high-throughput single-cell RNA sequencing (scRNA-seq) technologies - droplet-based 10X Chromium vs. microwell-based BD Rhapsody - using paired samples from patients with localized prostate cancer (PCa) undergoing a radical prostatectomy.Although high technical consistency was observed in unraveling the whole transcriptome, the relative abundance of cell populations differed. Cells with low mRNA content such as T cells were underrepresented in the droplet-based system, at least partly due to lower RNA capture rates. In contrast, microwell-based scRNA-seq recovered less cells of epithelial origin. Moreover, we discovered platform-dependent variabilities in mRNA quantification and cell-type marker annotation. Overall, our study provides important information for selection of the appropriate scRNA-seq platform and for the interpretation of published results.

Transcriptomics-based identification of transcription factors in the halophyte Apocynum venetum L.

ABSTRACT The medicinal halophyte plant Apocynum venetum L. can tolerate high salt levels in the soil, which significantly affects its growth and development. To study the molecular mechanisms underlying its environmental adaptations, omics tools were employed. Apocynum venetum L. plants were subjected to varying levels of salt stress. The corresponding RNA of Apocyni Veneti Folium (AVF), the leaf of Apocynum venetum L., was sequenced using a de novo approach. Functional annotation and expression analysis were utilised to identify differentially expressed transcription factors (TFs). The classification of these TFs was further divided into different families, including AP2/ERF, bHLH, WRKY, and HSF. Under conditions of modest saline stress, the majority of TF genes exhibited a predilection for up-regulation, particularly bHLHs, which were discovered to be consistent with the build-up of flavonoid glycosides. In conjunction with previous proteomics and metabolomics findings, we have discovered that the gene bHLH35 is a potential candidate. This gene has shown changes at both the transcript and protein levels, indicating that it may play a crucial role in the biosynthesis of flavonoids under salt-induced environments. These findings provide invaluable information on the identification of key genes involved in elucidating flavonoid biosynthesis mechanisms and serve as a basis for the improvement of the halophyte AVF’s quality.

Recent advances in applying omic technologies for studying acetic acid bacteria in industrial vinegar production: A comprehensive review.

Vinegar and related bioproducts containing acetic acid as the main component are among the most appreciated fermented foodstuffs in numerous European and Asian countries because of their exceptional organoleptic and bio-healthy properties. Regarding the acetification process and obtaining of final products, there is still a lack of knowledge on fundamental aspects, especially those related to the study of biodiversity and metabolism of the present microbiota. In this context, omic technologies currently allow for the massive analysis of macromolecules and metabolites for the identification and characterization of these microorganisms working in their natural media without the need for isolation. This review approaches comprehensive research on the application of omic tools for the identification of vinegar microbiota, mainly acetic acid bacteria, with subsequent emphasis on the study of the microbial diversity, behavior, and key molecular strategies used by the predominant groups throughout acetification. The current omics tools are enabling both the finding of new vinegar microbiota members and exploring underlying strategies during the elaboration process. The species Komagataeibacter europaeus may be a model organism for present and future research in this industry; moreover, the development of integrated meta-omic analysis may facilitate the achievement of numerous of the proposed milestones. This work might provide useful guidance for the vinegar industry establishing the first steps towards the improvement of the acetification conditions and the development of new products with sensory and bio-healthy profiles adapted to the agri-food market.