Biocontrol of plant parasitic nematodes by bacteria and fungi: a multi-omics approach for the exploration of novel nematicides in sustainable agriculture.

Plant parasitic nematodes (PPNs) pose a significant threat to global crop productivity, causing an estimated annual loss of US $157 billion in the agriculture industry. While synthetic chemical nematicides can effectively control PPNs, their overuse has detrimental effects on human health and the environment. Biocontrol agents (BCAs), such as bacteria and fungi in the rhizosphere, are safe and promising alternatives for PPNs control. These BCAs interact with plant roots and produce extracellular enzymes, secondary metabolites, toxins, and volatile organic compounds (VOCs) to suppress nematodes. Plant root exudates also play a crucial role in attracting beneficial microbes toward infested roots. The complex interaction between plants and microbes in the rhizosphere against PPNs is mostly untapped which opens new avenues for discovering novel nematicides through multi-omics techniques. Advanced omics approaches, including metagenomics, transcriptomics, proteomics, and metabolomics, have led to the discovery of nematicidal compounds. This review summarizes the status of bacterial and fungal biocontrol strategies and their mechanisms for PPNs control. The importance of omics-based approaches for the exploration of novel nematicides and future directions in the biocontrol of PPNs are also addressed. The review highlighted the potential significance of multi-omics techniques in biocontrol of PPNs to ensure sustainable agriculture.

Comparison of methane yield of a novel strain of Methanothermobacter marburgensis in pure and mixed adapted culture derived from a methanation bubble column bioreactor.

The ongoing discussion regarding the use of mixed or pure cultures of hydrogenotrophic methanogenic archaea in Power-to-Methane (P2M) bioprocess applications persists, with each option presenting its own advantages and disadvantages. To address this issue, a comparison of methane (CH4) yield between a novel methanogenic archaeon belonging to the species Methanothermobacter marburgensis (strain Clermont) isolated from a biological methanation column, and the community from which it originated, was conducted. This comparison included the type strain M. marburgensis str. Marburg. The evaluation also examined how exposure to oxygen (O2) for up to 240 min impacted the CH4 yield across these cultures. While both Methanothermobacter strains exhibit comparable CH4 yield, slightly higher than that of the mixed adapted culture under non-O2-exposed conditions, strain Clermont does not display the lag time observed for strain Marburg.

[Novel integrative multi-omics strategies of human's biological age computation.]

Multi-omics methods for analysing postgenomic data have become firmly established in the tools of molecular gerontology only in recent years, since previously there were no comprehensive integrative approaches adequate to the task of calculating biological age. This paper provides an overview of existing papers on multi-omics integrative approaches in calculating the biological age of a human. An analysis of the most common options for integrating methylomic, transcriptomic, proteomic, microbiomic and metabolomic datasets was carried out. We defined (1) concatenation (machine learning), in which models are developed using a concatenated data matrix, formed by combining multiple omics data sets; (2) fusion model approaches that create multiple intermediate submodels for different omics data to then build a final integrated model from the various intermediate submodels; and (3) transformation methods (via artificial intelligence) that first transform each of the single omics data sets into core plots or matrices, and then combine them all into one graph before building an integral complex model. It is unlikely that multi-omics approaches will find application in anti-aging personalized medicine, but they will undoubtedly deepen and expand the understanding of the fundamental processes standing behind the phenomenon of the biological aging clocks.

Multi-omics approaches for the understanding of therapeutic mechanism for Huang-Qi-Long-Dan Granule against ischemic stroke.

After long-term clinical application, traditional Chinese medicine (TCM) has accumulated rich experience in the stroke treatment. Huang-Qi-Long-Dan Granule (HQLDG) is a TCM formula that has been used in clinical for the treatment of acute ischemic stroke. However, its mechanism against ischemic stroke is still unknown. This study aimed to identify HQLDG's effect against ischemic stroke and explore its underlying mechanism. 16s rRNA sequencing, metabolomics/tryptophan (Trp)-targeted metabolomics analysis and transcriptomic analysis were used to investigate HQLDG underlying therapeutic mechanism. Our results revealed that HQLDG significantly decreased the infarct volume, improved mouse behavior and brain slices pathological staining. In addition, it could ameliorate intestinal barrier damage and regulate tight junction gene expression. 16s rRNA, metabolomics and transcriptomics analysis revealed that HQLDG treatment significantly improved the composition of gut microbiota and Trp metabolism pathway, and further downregulated Th17/IL-17 signaling pathway. HQLDG treatment could significantly decrease serum inflammatory cytokines, IL-17A and IL-22; down-regulate Trp metabolism receptor gene (Ahr), inflammatory cytokines genes (IL-17a, IL-22), and an important coding gene for maintaining the mature Th17 (rorc) in both brain and intestinal tissues. In the contrary, after gut microbiota removal, this effect of HQLDG was impaired. HQLDG treated mouse fecal microbiota transplantation also had positive effect against tMCAO injury. Moreover, AhR inhibitor could decrease IL-17A immunofluorescence. These results suggested that the gut microbiota regulation might be an important intermediate in HQLDG against tMCAO injury. HQLDG might exert anti-ischemic stroke effects through the gut microbiota-Trp metabolism-Th17/IL-17 signaling, which provides new insights into HQLDG-mediated prevention in ischemic stroke.

Biodegradation of acetaminophen: Microcosm centric genomic-proteomic-metabolomics evidences.

Acetaminophen (APAP) is a frequently used, over-the-counter analgesic and antipyretic medication. Considering increase in global consumption, its ubiquity in environment with potential toxic impacts has become a cause of great concern. Hence, bioremediation of this emerging contaminant is of paramount significance. The present study incorporates a microcosm centric omics approach to gain in-depth insights into APAP degradation by Paracoccus sp. APAP_BH8. It can metabolize APAP (300 mg kg-1) within 16 days in soil microcosms. Genome analysis revealed potential genes capable of mediating degradation includes M20 aminoacylase family protein, guanidine deaminase, 4-hydroxybenzoate 3-monooxygenase, and 4-hydroxyphenylpyruvate dioxygenase. Whole proteome analysis showed differential expression of enzymes and bioinformatics provided evidence for stable binding of intermediates at the active site of considered enzymes. Metabolites identified were 4-aminophenol, hydroquinone, and 3-hydroxy-cis, cis-muconate. Therefore, Paracoccus sp. APAP_BH8 with versatile enzymatic and genetic attributes can be a promising candidate for formulating improved in situ APAP bioremediation strategies.

Integrating Genome Sequencing and Untargeted Metabolomics in Monozygotic Twins with a Rare Complex Neurological Disorder.

Multi-omics approaches, which integrate genomics, transcriptomics, proteomics, and metabolomics, have emerged as powerful tools in the diagnosis of rare diseases. We used untargeted metabolomics and whole-genome sequencing (WGS) to gain a more comprehensive understanding of a rare disease with a complex presentation affecting female twins from a consanguineous family. The sisters presented with polymicrogyria, a Dandy-Walker malformation, respiratory distress, and multiorgan dysfunctions. Through WGS, we identified two rare homozygous variants in both subjects, a pathogenic variant in ADGRG1(p.Arg565Trp) and a novel variant in CNTNAP1(p.Glu910Val). These genes have been previously associated with autosomal recessive polymicrogyria and hypomyelinating neuropathy with/without contractures, respectively. The twins exhibited symptoms that overlapped with both of these conditions. The results of the untargeted metabolomics analysis revealed significant metabolic perturbations relating to neurodevelopmental abnormalities, kidney dysfunction, and microbiome. The significant metabolites belong to essential pathways such as lipids and amino acid metabolism. The identification of variants in two genes, combined with the support of metabolic perturbation, demonstrates the rarity and complexity of this phenotype and provides valuable insights into its underlying mechanisms.

QingXiaoWuWei decoction alleviates methicillin-resistant Staphylococcus aureus-induced pneumonia in mice by regulating metabolic remodeling and macrophage gene expression network via the microbiota-short-chain fatty acids axis.

IMPORTANCE: Methicillin-resistant Staphylococcus aureus (MRSA) colonizes the upper respiratory airways and is resistant to antibiotics. MRSA is a frequently acquired infection in hospital and community settings, including cases of MRSA-induced pneumonia. Multidrug-resistant Staphylococcus aureus and the limited efficacy of antibiotics necessitate alternative strategies for preventing or treating the infection. QingXiaoWuWei decoction (QXWWD) protects against both gut microbiota dysbiosis and MRSA-induced pneumonia. Furthermore, the QXWWD-regulated metabolic remodeling and macrophage gene expression network contribute to its protective effects through the microbiota-short-chain fatty acid axis. The results of this study suggest that QXWWD and its pharmacodynamic compounds might have the potential to prevent and treat pulmonary infections, especially those caused by multidrug-resistant organisms. Our study provides a theoretical basis for the future treatment of pulmonary infectious diseases by manipulating gut microbiota and their metabolites via traditional Chinese medicine.

Multi-omics approaches for in-depth understanding of therapeutic mechanism for Traditional Chinese Medicine.

Traditional Chinese Medicine (TCM) is extensively utilized in clinical practice due to its therapeutic and preventative treatments for various diseases. With the development of high-throughput sequencing and systems biology, TCM research was transformed from traditional experiment-based approaches to a combination of experiment-based and omics-based approaches. Numerous academics have explored the therapeutic mechanism of TCM formula by omics approaches, shifting TCM research from the "one-target, one-drug" to "multi-targets, multi-components" paradigm, which has greatly boosted the digitalization and internationalization of TCM. In this review, we concentrated on multi-omics approaches in principles and applications to gain a better understanding of TCM formulas against various diseases from several aspects. We first summarized frequently used TCM quality assessment methods, and suggested that incorporating both chemical and biological ingredients analytical methods could lead to a more comprehensive assessment of TCM. Secondly, we emphasized the significance of multi-omics approaches in deciphering the therapeutic mechanism of TCM formulas. Thirdly, we focused on TCM network analysis, which plays a vital role in TCM-diseases interaction, and serves for new drug discovery. Finally, as an essential source for storing multi-omics data, we evaluated and compared several TCM databases in terms of completeness and reliability. In summary, multi-omics approaches have infiltrated many aspects of TCM research. With the accumulation of omics data and data-mining resources, deeper understandings of the therapeutic mechanism of TCM have been acquired or will be gained in the future.

Role of systems biology and multi-omics analyses in delineating spatial interconnectivity and temporal dynamicity of ER stress mediated cellular responses.

The endoplasmic reticulum (ER) is a membranous organelle involved in calcium storage, lipid biosynthesis, protein folding and processing. Many patho-physiological conditions and pharmacological agents are known to perturb normal ER function and can lead to ER stress, which severely compromise protein folding mechanism and hence poses high risk of proteotoxicity. Upon sensing ER stress, the different stress signaling pathways interconnect with each other and work together to preserve cellular homeostasis. ER stress response is a part of the integrative stress response (ISR) and might play an important role in the pathogenesis of chronic neurodegenerative diseases, where misfolded protein accumulation and cell death are common. The initiation, manifestation and progression of ER stress mediated unfolded protein response (UPR) is a complex procedure involving multiple proteins, pathways and cellular organelles. To understand the cause and consequences of such complex processes, implementation of an integrative holistic approach is required to identify novel players and regulators of ER stress. As multi-omics data-based systems analyses have shown potential to unravel the underneath molecular mechanism of complex biological systems, it is important to emphasize the utility of this approach in understanding the ER stress biology. In this review we first discuss the ER stress signaling pathways and regulatory players, along with their inter-connectivity. We next highlight the importance of systems and network biology approaches using multi-omics data in understanding ER stress mediated cellular responses. This report would help advance our current understanding of the multivariate spatial interconnectivity and temporal dynamicity of ER stress.

Investigating Molecular Mechanisms of Immunotoxicity and the Utility of ToxCast for Immunotoxicity Screening of Chemicals Added to Food.

The development of high-throughput screening methodologies may decrease the need for laboratory animals for toxicity testing. Here, we investigate the potential of assessing immunotoxicity with high-throughput screening data from the U.S. Environmental Protection Agency ToxCast program. As case studies, we analyzed the most common chemicals added to food as well as per- and polyfluoroalkyl substances (PFAS) shown to migrate to food from packaging materials or processing equipment. The antioxidant preservative tert-butylhydroquinone (TBHQ) showed activity both in ToxCast assays and in classical immunological assays, suggesting that it may affect the immune response in people. From the PFAS group, we identified eight substances that can migrate from food contact materials and have ToxCast data. In epidemiological and toxicological studies, PFAS suppress the immune system and decrease the response to vaccination. However, most PFAS show weak or no activity in immune-related ToxCast assays. This lack of concordance between toxicological and high-throughput data for common PFAS indicates the current limitations of in vitro screening for analyzing immunotoxicity. High-throughput in vitro assays show promise for providing mechanistic data relevant for immune risk assessment. In contrast, the lack of immune-specific activity in the existing high-throughput assays cannot validate the safety of a chemical for the immune system.

Reflections on the Use of an Invertebrate Chordate Model System for Studies of Gut Microbial Immune Interactions.

The functional ecology of the gastrointestinal tract impacts host physiology, and its dysregulation is at the center of various diseases. The immune system, and specifically innate immunity, plays a fundamental role in modulating the interface of host and microbes in the gut. While humans remain a primary focus of research in this field, the use of diverse model systems help inform us of the fundamental principles legislating homeostasis in the gut. Invertebrates, which lack vertebrate-style adaptive immunity, can help define conserved features of innate immunity that shape the gut ecosystem. In this context, we previously proposed the use of a marine invertebrate, the protochordate Ciona robusta, as a novel tractable model system for studies of host-microbiome interactions. Significant progress, reviewed herein, has been made to fulfill that vision. We examine and review discoveries from Ciona that include roles for a secreted immune effector interacting with elements of the microbiota, as well as chitin-rich mucus lining the gut epithelium, the gut-associated microbiome of adults, and the establishment of a large catalog of cultured isolates with which juveniles can be colonized. Also discussed is the establishment of methods to rear the animals germ-free, an essential technology for dissecting the symbiotic interactions at play. As the foundation is now set to extend these studies into the future, broadening our comprehension of how host effectors shape the ecology of these microbial communities in ways that establish and maintain homeostasis will require full utilization of "multi-omics" approaches to merge computational sciences, modeling, and experimental biology in hypothesis-driven investigations.

Recent Advances in Exploration and Biotechnological Production of Bioactive Compounds in Three Cyanobacterial Genera: Nostoc, Lyngbya, and Microcystis.

Cyanobacteria, are only Gram-negative bacteria with the capacity of oxygenic photosynthesis, so termed as "Cyanophyta" or "blue-green algae." Their habitat is ubiquitous, which includes the diverse environments, such as soil, water, rock and other organisms (symbiosis, commensalism, or parasitism, etc.,). They are characterized as prominent producers of numerous types of important compounds with anti-microbial, anti-viral, anti-inflammatory and anti-tumor properties. Among the various cyanobacterial genera, members belonging to genera Nostoc, Lyngbya, and Microcystis possess greater attention. The major reason for that is the strains belonging to these genera produce the compounds with diverse activities/structures, including compounds in preclinical and/or clinical trials (cryptophycin and curacin), or the compounds retaining unique activities such as protease inhibitor (micropeptins and aeruginosins). Most of these compounds were tested for their efficacy and mechanism of action(MOA) through in vitro and/or in vivo studies. Recently, the advances in culture techniques of these cyanobacteria, and isolation, purification, and chromatographic analysis of their compounds have revealed insurmountable novel bioactive compounds from these cyanobacteria. This review provides comprehensive update on the origin, isolation and purification methods, chemical structures and biological activities of the major compounds from Nostoc, Lyngbya, and Microcystis. In addition, multi-omics approaches and biotechnological production of compounds from selected cyanobacterial genera have been discussed.

Integrative omics - from data to biology.

INTRODUCTION: Multi-omic approaches are promising a broader view on cellular processes and a deeper understanding of biological systems. with strongly improved high-throughput methods the amounts of data generated have become huge, and their handling challenging. Area Covered: New bioinformatic tools and pipelines for the integration of data from different omics disciplines continue to emerge, and will support scientists to reliably interpret data in the context of biological processes. comprehensive data integration strategies will fundamentally improve systems biology and systems medicine. to present recent developments of integrative omics, the göttingen proteomics forum (gpf) organized its 6th symposium on the 23rd of november 2017, as part of a series of regular gpf symposia. more than 140 scientists attended the event that highlighted the challenges and opportunities but also the caveats of integrating data from different omics disciplines. Expert commentary: The continuous exponential growth in omics data require similar development in software solutions for handling this challenge. Integrative omics tools offer the chance to handle this challenge but profound investigations and coordinated efforts are required to boost this field.

The future of metabolomics in ELIXIR.

Metabolomics, the youngest of the major omics technologies, is supported by an active community of researchers and infrastructure developers across Europe. To coordinate and focus efforts around infrastructure building for metabolomics within Europe, a workshop on the "Future of metabolomics in ELIXIR" was organised at Frankfurt Airport in Germany. This one-day strategic workshop involved representatives of ELIXIR Nodes, members of the PhenoMeNal consortium developing an e-infrastructure that supports workflow-based metabolomics analysis pipelines, and experts from the international metabolomics community. The workshop established metabolite identification as the critical area, where a maximal impact of computational metabolomics and data management on other fields could be achieved. In particular, the existing four ELIXIR Use Cases, where the metabolomics community - both industry and academia - would benefit most, and which could be exhaustively mapped onto the current five ELIXIR Platforms were discussed. This opinion article is a call for support for a new ELIXIR metabolomics Use Case, which aligns with and complements the existing and planned ELIXIR Platforms and Use Cases.

A community proposal to integrate proteomics activities in ELIXIR.

Computational approaches have been major drivers behind the progress of proteomics in recent years. The aim of this white paper is to provide a framework for integrating computational proteomics into ELIXIR in the near future, and thus to broaden the portfolio of omics technologies supported by this European distributed infrastructure. This white paper is the direct result of a strategy meeting on 'The Future of Proteomics in ELIXIR' that took place in March 2017 in Tübingen (Germany), and involved representatives of eleven ELIXIR nodes. These discussions led to a list of priority areas in computational proteomics that would complement existing activities and close gaps in the portfolio of tools and services offered by ELIXIR so far. We provide some suggestions on how these activities could be integrated into ELIXIR's existing platforms, and how it could lead to a new ELIXIR use case in proteomics. We also highlight connections to the related field of metabolomics, where similar activities are ongoing. This white paper could thus serve as a starting point for the integration of computational proteomics into ELIXIR. Over the next few months we will be working closely with all stakeholders involved, and in particular with other representatives of the proteomics community, to further refine this paper.