Assessment of internal exposure risk from metals pollution of occupational and non-occupational populations around a non-ferrous metal smelting plant.

Non-ferrous metal smelting poses significant risks to public health. Specifically, the copper smelting process releases arsenic, a semi-volatile metalloid, which poses an emerging exposure risk to both workers and nearby residents. To comprehensively understand the internal exposure risks of metal(loid)s from copper smelting, we explored eighteen metal(loid)s and arsenic metabolites in the urine of both occupational and non-occupational populations using inductively coupled plasma mass spectrometry with high-performance liquid chromatography and compared their health risks. Results showed that zinc and copper (485.38 and 14.00 µg/L), and arsenic, lead, cadmium, vanadium, tin and antimony (46.80, 6.82, 2.17, 0.40, 0.44 and 0.23 µg/L, respectively) in workers (n=179) were significantly higher compared to controls (n=168), while Zinc, tin and antimony (412.10, 0.51 and 0.15 µg/L, respectively) of residents were significantly higher than controls. Additionally, workers had a higher monomethyl arsenic percentage (MMA%), showing lower arsenic methylation capacity. Source appointment analysis identified arsenic, lead, cadmium, antimony, tin and thallium as co-exposure metal(loid)s from copper smelting, positively relating to the age of workers. The hazard index (HI) of workers exceeded 1.0, while residents and control were approximately at 1.0. Besides, all three populations had accumulated cancer risks exceeding 1.0 × 10-4, and arsenite (AsIII) was the main contributor to the variation of workers and residents. Furthermore, residents living closer to the smelting plant had higher health risks. This study reveals arsenic exposure metabolites and multiple metals as emerging contaminants for copper smelting exposure populations, providing valuable insights for pollution control in non-ferrous metal smelting.

Facial synthesis of fluorine-engineered magnetic covalent organic framework for selective and ultrasensitive determination of fipronil, its metabolites and analogs in food samples.

To improve the adsorption affinity and selectivity of fipronils (FPNs), including fipronil, its metabolites and analogs, a magnetic covalent organic framework (Fe3O4@COF-F) with copious fluorine affinity sites was innovatively designed as an adsorbent of magnetic solid-phase extraction (MSPE). The enhanced surface area, pore size, crystallinity of Fe3O4@COF-F and its exponential adsorption capacities (187.3-231.5 mg g-1) towards fipronils were investigated. Combining MSPE with high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS), an analytical method was established for the selective determination of fipronils in milk and milk powder samples. This method achieved high sensitivity (LODs: 0.004-0.075 ng g-1), satisfactory repeatability and accuracy with spiked recoveries ranging from 89.9% to 100.3% (RSDs≤5.1%). Overall, the constructed Fe3O4@COF-F displayed great potential for the selective enrichment of fipronils, which could be ascribed to fluorine­fluorine interaction. This method proposed a feasible and promising strategy for the development of functionalized COF and broadened its application in fluorine containing hazards detection.

Influencia de la edad en el contenido de fenoles y ligninas en Gmelina arborea (Lamiaceae) / The influence of age on the phenolic contents and lignins of Gmelina arborea (Lamiaceae)

Resumen Introducción: La melina (Gmelina arborea), es una especie de gran interés por su madera y propiedades medicinales. En Costa Rica, existen clones genéticamente superiores que se propagan sin el conocimiento de la edad ontogénica y fisiológica de los materiales. Objetivo: Evaluar la relación del contenido de fenoles y ligninas en hojas, peciolos, tallos y raíces de plantas con diferentes edades. Métodos: Los contenidos de fenoles y ligninas totales se determinaron mediante el método colorimétrico de Folin-Ciocalteu y el método de extracción alcalina, respectivamente. Para la investigación se eligieron plantas in vitro "año cero" y árboles de año y medio, cuatro, siete y 20 años. El muestreo se realizó en marzo y abril del 2021. Resultados: Se demostró que todas las partes de la planta analizadas contienen compuestos fenólicos y ligninas, independientemente de su edad. No hubo una correlación positiva entre la edad con el contenido de fenoles y ligninas para ninguna condición de desarrollo, pues los valores más altos no se obtuvieron en los árboles más longevos. Los extractos de hojas de las plantas in vitro y los árboles de siete años mostraron, respectivamente, los contenidos más altos de fenoles y ligninas para todas las condiciones (P < 0.05). Los valores promedio más bajos de compuestos fenólicos para todas las condiciones se obtuvieron en los árboles de cuatro años. Respecto a las ligninas, el contenido más bajo se presentó en las raíces más longevas, aunque la tendencia no se mantuvo para el resto de las partes de la planta. Conclusiones: La investigación muestra los primeros resultados del contenido de compuestos fenólicos y ligninas presentes en diferentes tejidos de una especie forestal de edades diferentes. Por lo tanto, son los primeros valores de referencia acerca del compromiso bioquímico para la síntesis fenólica según la edad y el estado de desarrollo específico de una planta leñosa.

Abstract Introduction: Melina (Gmelina arborea) is a tree species of great interest for its wood and medicinal properties. In Costa Rica, there are genetically superior clones that are propagated without knowledge of the ontogenic and physiological age of the materials. Objective: To evaluate how age influences the content of phenols and lignins in leaves, petioles, stems, and roots of melina plants. Methods: The total phenolic and lignins contents were determined using Folin-Ciocalteu colorimetric method and alkaline extraction method, respectively. Plants of five different ages were chosen for the investigation (in vitro plants "year 0" and trees of a year and a half, four, seven and 20 years). Sampling was done in March and April 2021. Results: All parts of the plant analyzed contain phenolic compounds and lignins, regardless of their age. There was no positive correlation between age and phenol and lignin content for any development condition, since the highest values were not obtained in the oldest trees. Leaf extracts from in vitro plants and seven-year-old trees showed, respectively, the highest phenol and lignin contents for all conditions (P < 0.05). The lowest average values of phenolic compounds for all conditions were obtained in four-year-old trees. Regarding lignins, the lowest content occurred in the oldest roots, although the trend was not maintained for the rest of the plant parts. Conclusions: This study provides the first results of the content of phenolic compounds and lignins present in different tissues of a forest species of different ages. Therefore, they are the first reference values about the biochemical commitment for phenolic synthesis according to the age and the specific developmental stage of a woody plant.

Oral microbiota and metabolites: key players in oral health and disorder, and microbiota-based therapies.

The review aimed to investigate the diversity of oral microbiota and its influencing factors, as well as the association of oral microbiota with oral health and the possible effects of dysbiosis and oral disorder. The oral cavity harbors a substantial microbial burden, which is particularly notable compared to other organs within the human body. In usual situations, the microbiota exists in a state of equilibrium; however, when this balance is disturbed, a multitude of complications arise. Dental caries, a prevalent issue in the oral cavity, is primarily caused by the colonization and activity of bacteria, particularly streptococci. Furthermore, this environment also houses other pathogenic bacteria that are associated with the onset of gingival, periapical, and periodontal diseases, as well as oral cancer. Various strategies have been employed to prevent, control, and treat these disorders. Recently, techniques utilizing microbiota, like probiotics, microbiota transplantation, and the replacement of oral pathogens, have caught the eye. This extensive examination seeks to offer a general view of the oral microbiota and their metabolites concerning oral health and disease, and also the resilience of the microbiota, and the techniques used for the prevention, control, and treatment of disorders in this specific area.

Insight into the differences in meat quality among three breeds of sheep on the Qinghai-Tibetan plateau from the perspective of metabolomics and rumen microbiota.

Mutton is one of the most popular meats among the general public due to its high nutritional value. This study evaluated the differences in meat quality among Chaka (CK), Black Tibetan (BT) and Oula (OL) sheep and investigated the metabolic mechanisms affecting meat quality using targeted and untargeted metabolomics and 16S rRNA. The results showed that the meat quality of CK sheep was superior to that of BT and OL sheep in terms of meat color, muscle fiber characteristics and nutritional quality. Pseudobutyrivibrio, Alloprevotella, Methanobrevibacter, unidentified_Christensenellaceae, and unidentified_Bacteroidales were key microbes involved in regulating meat color, muscle fiber characteristics, amino acid and fatty acid content. Protein digestion/absorption, pentose phosphate metabolism, carbon metabolism, and glyoxylate and dicarboxylate metabolism were important metabolic pathways involved in meat quality regulation. Our study is important for the development of sheep breeding strategy and sheep meat industry in Qinghai-Tibetan Plateau.

Multi-omics reveals protective effects of Ling Gui Zhu Gan Decoction on hyperlipidaemia in hamster.

Ling Gui Zhu Gan decoction (LGZGD) is a traditional Chinese medicine (TCM) prescription that is widely used in cardiovascular disease clinical prevention and treatment with high efficacy. Recent studies have shown that LGZGD can also be used in hyperlipidemia (HL) intervention, but its pharmacodynamic material basis and its mechanisms remains unclear. This study aimed to reveal the protective effects of LGZGD on HL, elucidate the pharmacodynamic material basis. The hamster HL model was established by high-fat diet. Thereafter, non-targeted metabolomics and quantitative lipidomics were established for screening differential metabolites and pathways. Finally, the mechanisms were elucidated based on network pharmacology to screen for shared targets, which were computational selected by molecular docking. After four weeks of LGZGD administration, the TC, TG, and liver index levels decreased notably and hepatocyte injury was obviously reduced. The Multi-omics identified 62 differential metabolites and 144 differential lipids, respectively. The network pharmacology study predicted 343, 85, and 974 relevant targets from LGZGD components, HL, differential metabolites and lipids, respectively. Eventually, seven core targets were selected by molecular docking. Six key components in LGZGD, including genistein and naringenin, could play a therapeutic role in HL by regulating seven pathways, including HMGCR and PPARA. This comprehensive strategy provides a promising example and approach for further research on TCM for the treatment of lipid metabolic diseases.

Genetic liability to human serum metabolites is causally linked to telomere length: insights from genome-wide Mendelian randomization and metabolic pathways analysis.

Background: Telomere has been recognized as a biomarker of accelerating aging, and telomere length (TL) shortening is closely related to diverse chronic illnesses. Human serum metabolites have demonstrated close correlations with TL maintenance or shortening in observational studies. Nevertheless, little is known about the underlying pathological mechanisms, and Mendelian randomization (MR) analysis of serum metabolites may provide a more comprehensive understanding of the potential biological process. Methods: We employed a two-sample MR analysis method to assess the causal links between 486 serum metabolites and TL. We applied the inverse-variance weighted (IVW) approach as our primary analysis, and to assure the stability and robustness of our results, additional analysis methods including the weighted median, MR-Egger, and weighted mode were conducted. MR-Egger intercept test was utilized to detect the pleiotropy. Cochran's Q test was implemented to quantify the extent of heterogeneity. Furthermore, the pathway analysis was conducted to identify potential metabolic pathways. Results: We identified 11 known blood metabolites associated with TL. Among these metabolites, four were lipid (taurocholate, dodecanedioate, 5,8-tetradecadienoate, and 15-methylpalmitate), one amino acid (levulinate (4-oxovaleate)), one carbohydrate (lactate), one nucleotide (pseudouridine), one energy (phosphate), and three xenobiotics (2-hydroxyacetaminophen sulfate, paraxanthine, and ergothioneine). The known protective metabolites included levulinate (4-oxovaleate), dodecanedioate, 5,8-tetradecadienoate, lactate, phosphate, paraxanthine, and ergothioneine. Multiple metabolic pathways have been identified as being implicated in the maintenance of telomere length. Conclusion: Our MR analysis provided suggestive evidence supporting the causal relationships between 11 identified blood metabolites and TL, necessitating further exploration to clarify the mechanisms by which these serum metabolites and metabolic pathways may affect the progression of telomeres.

LAMAIS: A library-aided approach for efficient 1D 1H NMR qualitative analysis in plant metabolomics.

BACKGROUND: One-dimensional proton nuclear magnetic resonance (1D 1H NMR) spectroscopy is a non-destructive, non-targeted analytical technique providing both qualitative and quantitative insights, particularly beneficial for mixture analysis. However, the qualitative analysis of 1D 1H NMR spectra for mixture samples is laborious and time-consuming, involving extensive database searches and verification experiments like spiking. This process heavily relies on the analyst's expertise, leading to efficiency discrepancies. There is a pressing need for a reliable method to streamline operations and enhance the efficiency of qualitative analysis in complex mixtures. RESULTS: We introduce a library-aided method for spectral profiling, named LAMAIS. This method achieves compound identification through similarity assessment between samples and template data, allowing rapid, automatic compound identification and full-spectrum peak assignment without the need for fitting. LAMAIS correctly identifies over 90 % of components in synthetic mixtures and more than 75 % in experimental mixtures, surpassing other representative methods with a higher F2 score. Our reference library, which currently includes 71 compounds, is tailored to capture the commonality of primary metabolites across diverse plant species. The analysis of real-world samples yielded encouraging results, underscoring LAMAIS's versatility as an auxiliary tool suitable for a variety of botanical sources. For analyst convenience, interactive graphics are utilized as the output format. SIGNIFICANCE: LAMAIS excels, demonstrating competitiveness and reliability. The approach minimizes repetitive tasks and sample wastage, improving the efficiency of 1D 1H NMR qualitative analysis. Constructing a reference library effectively preserves knowledge, mitigates reliance on human experience, and addresses gaps in the analysis of plant source samples.

Whole-Genome Sequencing of Three Lactiplantibacillus plantarum Strains Reveals Potential Metabolites for Boosting Host Immunity Safely.

In response to the growing demand for immune-related products, this study evaluated the safety and immune-modulating potential of three newly discovered Lactiplantibacillus plantarum strains (GKM3, GKK1, and GKD7) through toxicity tests and whole-genome sequencing. Safety evaluations, including the analysis of antimicrobial resistance genes, virulence factors, plasmids, and prophages, classified these strains as safe for human consumption. Acute oral toxicity tests further supported their safety. To evaluate their immune-modulating potential, dendritic cells were exposed to these strains, and the secretion of key cytokines (IFN-ß and IL-12) was measured. Among the strains, GKK1 exhibited the highest enhancement of IFN-ß and IL-12 production, suggesting its potential as an immune-stimulating probiotic. Bioinformatics analysis revealed potential metabolic pathways and secondary metabolites, including predicted bacteriocins, associated with immune modulation. The presence of a nitrate reductase region in the GKK1 strain indicated its ability to produce nitric oxide, a critical molecule involved in immune regulation and host defense. The presence of glucorhamnanrelated gene clusters in GKK1 also suggested immune-enhancing effects. Nitrate reductase expression was confirmed using qPCR, with the highest levels detected in GKK1. Moreover, this study is the first to show an anti-inflammatory effect of plantaricin A, linked to its presence in strain GKM3 and its potential therapeutic applications due to sequence similarity to known antiinflammatory peptides. Overall, these three L. plantarum strains demonstrated a safe profile and GKK1 showed potential as an immunity-enhancing probiotic. However, additional investigation is required to confirm the involvement of specific metabolic pathways, secondary metabolites, and bacteriocins in immune responses.

Machine-Learning Analysis of Streptomyces coelicolor Transcriptomes Reveals a Transcription Regulatory Network Encompassing Biosynthetic Gene Clusters.

Streptomyces produces diverse secondary metabolites of biopharmaceutical importance, yet the rate of biosynthesis of these metabolites is often hampered by complex transcriptional regulation. Therefore, a fundamental understanding of transcriptional regulation in Streptomyces is key to fully harness its genetic potential. Here, independent component analysis (ICA) of 454 high-quality gene expression profiles of the model species Streptomyces coelicolor is performed, of which 249 profiles are newly generated for S. coelicolor cultivated on 20 different carbon sources and 64 engineered strains with overexpressed sigma factors. ICA of the transcriptome dataset reveals 117 independently modulated groups of genes (iModulons), which account for 81.6% of the variance in the dataset. The genes in each iModulon are involved in specific cellular responses, which are often transcriptionally controlled by specific regulators. Also, iModulons accurately predict 25 secondary metabolite biosynthetic gene clusters encoded in the genome. This systemic analysis leads to reveal the functions of previously uncharacterized genes, putative regulons for 40 transcriptional regulators, including 30 sigma factors, and regulation of secondary metabolism via phosphate- and iron-dependent mechanisms in S. coelicolor. ICA of large transcriptomic datasets thus enlightens a new and fundamental understanding of transcriptional regulation of secondary metabolite synthesis along with interconnected metabolic processes in Streptomyces.

Interplay of heavy metal accumulation, physiological responses, and microbiome dynamics in lichens: insights and future directions.

Lichens are increasingly recognised as valuable bioindicators for environmental heavy metal pollution due to their sensitivity to spatial and temporal variations in pollution levels and their ability to adapt to diverse and often harsh habitats. This review initially examines the mechanisms of metal absorption in lichens, including particulate entrapment, ion exchange, and intracellular absorption, as well as their physiological responses to abiotic stressors such as heavy metal exposure and desiccation. In the latter part, we compile and synthesise evidence showing that secondary metabolites in lichens are significantly influenced by metal concentrations, with varying impacts across different species. Although extensive research has addressed the broader physiological effects of heavy metal hyperaccumulation in lichens, there remains a significant gap in understanding the direct or indirect influences of heavy metals on the lichen microbiome, possibly mediated by changes in secondary metabolite production. Our review integrates these aspects to propose new research directions aimed at elucidating the mechanisms underlying physiological responses such as resilience and adaptability in lichens. Overall, this review highlights the dynamic interplay between microbiome composition, secondary metabolite variation, and metal accumulation, suggesting that these factors collectively contribute to the physiological responses of lichens in polluted environments.

Variability of Bile Baseline Excitation-emission Fluorescence of Two Tropical Freshwater Fish Species.

The quantification of pollutant metabolites in fish bile is an efficient approach to xenobiotic pollution monitoring in freshwaters since these measurements directly address exposure. Fluorescence excitation-emission matrix spectroscopy (EEMS) has demonstrated to be a highly specific and cost-effective technique for polycyclic aromatic hydrocarbon (PAH) and PAH-metabolite identification and quantification. EEMS ability to quantify these compounds strongly depends on the intensity and variability of the bile baseline fluorescence (BBF). We found large differences in BBF among Aequidens metae (AME) individuals and of these with Piaractus orinoquensis (PIO). Moreover, BBF was large enough that solvent dilutions of over 1:400 were needed to avoid inner filter effects. We used parallel factor analysis (PARAFAC) to model the intra- and inter-species BBF variability. PARAFAC successfully decomposed the EEMS set into three fluorophores present in all samples, although in concentrations spreading over ~ 3 orders of magnitude. One of the factors was identified as tryptophan. Tryptophan and Factor 2 were covariant and much more abundant in AME than in PIO, while Factor 3 was ~ 6 times more abundant in PIO than in AME. Also, tryptophan was ~ 10x more abundant in AME specimens immediately caught in rivers than in their laboratory-adapted peers. The PARAFAC decomposition effectiveness was confirmed by the positive proportionality of scores to dilution ratios. A large inner filter indicates that Factor 2 is as strong a light absorber as tryptophan. Our results stress the need to include bile matrix variable components for the detection and quantification of pollutant metabolites using PARAFAC.

The Influence of Metabolites of Microorganisms of the Genus Bacillus from Permafrost Rocks on T Lymphocyte Differentiation.

We studied the influence of metabolites of permafrost microorganisms obtained at different temperature incubation conditions on activity of differentiation of regulatory (Treg) and effector T lymphocytes. It was found that the effect of metabolites is largely regulated by their type that depends on the temperature of production ("cold" at 5°C, "medium temperature" at 22°C, and "warm" at 37°C). The studied metabolites influenced the differentiation of Tregs (CD4+CD25hiCD127-) and the expression of markers of early (CD69), middle (CD25), and late (HLA DR) activation of CD4+ and CD8+ T lymphocytes. In the case of "cold" metabolites, the increase in Treg levels was associated with a decrease in the intensity of CD4+ T lymphocyte differentiation, and under the influence of "warm" metabolites - with a decrease in the activity of CD8+ T lymphocyte differentiation. Under the influence of "medium-temperature" metabolites, Tregs had approximately the same effect on the intensity of CD4+ and CD8+ T lymphocyte differentiation.

A study on the determination of the metabolites of 2,4,6-Trinitrotoluene using a dual-drift tube ion mobility spectrometer.

2,4,6-Trinitrotoluene (TNT) and its four metabolites, namely 2-ADNT, 4-ADNT, 2,4-DANT, and 2,6-DANT, are highly toxic substances. These metabolites also serve as biomarkers for assessing the health of individuals exposed to TNT. In this study, a homemade DDT-IMS apparatus was utilized to detect these metabolites. Under negative detection mode, the drift times of 2-ADNT and 4-ADNT showed subtle shifts within a drift tube temperature range of 100 °C-120 °C, aiding in their differentiation. In positive detection mode for 2,4-DANT and 2,6-DANT, significant variations were observed in both the number and drift time of their positive product ions across a drift tube temperature range of 80 °C-120 °C. Consequently, optimal analytical performance for these metabolites was achieved at approximately 100 °C. Evaluation of the instrumental response during the measurement of the four metabolites in both positive and negative modes revealed that negative detection mode offered greater advantages of detecting these compounds. The working ranges for measuring the four metabolites spanned two orders of magnitude, with detection limits for each metabolite nearly below 1 ng. Notably, clear identification of the signals for these metabolites was achieved even when samples were mixed in urine, highlighting the ability of the DDT-IMS in detecting TNT metabolites. The developed DDT-IMS detection method has significant potential for enhancing environmental risk assessment and biological hazard evaluation, particularly in relation to human exposure to TNT.

Absorption, transportation, residual distribution of chiral 14C-dufulin in garlics and metabolism of its racemate.

Dufulin is a novel chiral plant antiviral agent. In this study, we investigated the uptake, translocation and accumulation of 14C-dufulin stereoisomers in different tissues of garlic via leaf introduction and root uptake. The behavior of dufulin enantiomers in plants is not stereoselective, and dufulin is more likely to be absorbed by leaves than by roots. The metabolites of 14C-dufulin with high specific activity in garlic were qualitatively and quantitatively analyzed by HPLC-QTOF-MS, and the metabolic pathway involved was elucidated. In the leaf and bulb, dufulin underwent phase I and phase II metabolism and produced four metabolites. The ratios and concentrations of these four metabolites in the bulb, but not in the leaf, met the residue criterion. Overall, our results provide relatively accurate predictions for the risk assessment of dufulin, which will help guide its rational use and ensure its ecological safety and human health.

Exploiting the gut microbiome for brain tumour treatment.

Increasing evidence suggests that the gut microbiome plays a key role in a host of pathological conditions, including cancer. Indeed, the bidirectional communication that occurs between the gut and the brain, known as the 'gut-brain axis,' has recently been implicated in brain tumour pathology. Here, we focus on current research that supports a gut microbiome-brain tumour link with emphasis on high-grade gliomas, the most aggressive of all brain tumours, and the impact on the glioma tumour microenvironment. We discuss the potential use of gut-brain axis signals to improve responses to current and future therapeutic approaches. We highlight that the success of novel treatment strategies may rely on patient-specific microbiome profiles, and these should be considered for personalised treatment approaches.

The possible inhibition mechanism of low salt dry-curing on volatile flavor deterioration in refrigerated grass carp (Ctenopharyngodon idella) blocks: Metabolomics and microorganisms.

Complex microbial communities have an important impact on the flavor of low salt dry-curing (LSD)-pretreated grass carp blocks. Here, the flavors, metabolites, and bacterial diversity of LSD-pretreated fish during cold storage were analyzed using flavor analysis, metabolomics, and high-throughput sequencing to investigate their correlations in detail. LSD promoted the volatile flavor deterioration of grass carp blocks under 6 days of refrigeration but inhibited it under 15 days of refrigeration. Furthermore, 924 metabolites were identified in the refrigerated grass carp blocks, and LSD inhibited the growth of Psychrophilic dominant spoilage microorganisms (Proteobacteria) and promoted microbial abundance (Actinobacteriota, Firmicutes, Bacteroidota, and Cyanobacteria). Correlation analysis revealed that the degradation of phosphatidylcholine connected with the monomonas genus in LSD-pretreated fish blocks played a vital role in inhibiting the key volatile flavor (esters, aldehydes, and alcohols) deterioration. This information is useful for elucidating the inhibition mechanism of LSD on flavor deterioration in refrigerated fish blocks.

Advances in CRISPR-Cas systems for fungal infections.

Fungi contain a wide range of bioactive secondary metabolites (SMs) that have numerous applications in various fields, including agriculture, medicine, human health, and more. It is common for genes responsible for the production of secondary metabolites (SMs) to form biosynthetic gene clusters (BGCs). The identification and analysis of numerous unexplored gene clusters (BGCs) and their corresponding substances (SMs) has been significantly facilitated by the recent advancements in genomic and genetic technologies. Nevertheless, the exploration of secondary metabolites with commercial value is impeded by a variety of challenges. The emergence of modern CRISPR/Cas technologies has brought about a paradigm shift in fungal genetic engineering, significantly streamlining the process of discovering new bioactive compounds. This study begins with an examination of fungal biosynthetic gene clusters (BGCs) and their interconnections with the secondary metabolites (SMs) they generate. Following that, a brief summary of the conventional methods employed in fungal genetic engineering is provided. This study explores various sophisticated CRISPR/Cas-based methodologies and their utilization in examining the synthesis of secondary metabolites (SMs) in fungi. The chapter provides an in-depth analysis of the limitations and obstacles encountered in CRISPR/Cas-based systems when applied to fungal genetic engineering. It also proposes promising avenues for future research to optimize the efficiency of these systems.

Elucidation of toxic effects of 1,2-diacetylbenzene: an in silico study.

PURPOSE: We aimed to explore the metabolite products of 1,2-diacetylbenzene (DAB) and investigate their harmful effects, physicochemical properties, and biological activities, along with those of DAB itself. METHODS: Key approaches included MetaTox, PASS online, ADMESWISS, ADMETlab 2.0, molecular docking, and molecular dynamic simulation to identify metabolites, toxic effects, Lipinski's rule criteria, absorption, distribution, metabolism, and excretion properties, interactions with cytochrome (CYP) 450 isoforms, and the stability of the DAB-cytochrome complex. RESULTS: A total of 13 metabolite products from DAB were identified, involving Phase I reactions (aliphatic hydroxylation, epoxidation, oxidative dehydrogenation, and hydrogenation) and Phase II reactions (oxidative sulfation and methylation). Molecular dynamics and modeling revealed a stable interaction between CYP1A2 and DAB, suggesting the involvement of CYP1A2 in DAB metabolism. All studied compounds adhered to Lipinski's rule, indicating their potential as inducers or activators of toxic mechanisms. The physicochemical parameters and pharmacokinetics of the investigated compounds were consistent with their harmful effects, which included neurotoxic, nephrotoxic, endocrine disruptor, and hepatotoxic consequences due to their high gastrointestinal absorption and ability to cross the blood-brain barrier. Various CYP450 isoforms exhibited different functions, and the compounds were found to act as superoxide dismutase inhibitors, neuropeptide Y2 antagonists, glutaminase inhibitors, and activators of caspases 3 and 8. DAB and its metabolites were also associated with apoptosis, oxidative stress, and neuroendocrine disruption. CONCLUSION: The toxic effects of DAB and its metabolites were predicted in this study. Further research is warranted to explore their effects on other organs, such as the liver and kidneys, and to validate our findings.

Causal effects of gut microbiota, metabolites, immune cells, liposomes, and inflammatory proteins on anorexia nervosa: A mediation joint multi-omics Mendelian randomization analysis.

BACKGROUND: Anorexia nervosa (AN) is a significant psychological disorder influenced by environmental and genetic elements. Emerging research highlights the pivotal role of the gut microbiome in the development of diverse mental health conditions. This study aims to explore the causal effects and interactions of the gut microbiome, metabolites, immune cells, lipids, and inflammatory proteins on the risk of anorexia nervosa through mediation and multi-omics Mendelian Randomization (MR) analysis. METHODS: This study used data from the FinnGen genome-wide association study (GWAS) of AN (N = 402,625), integrated with GWAS data on 473 of gut microbiota (N = 5959), 233 metabolites (N = 136,016), 731 immune cells (N = 3757), 179 lipids (N = 7174), and 91 inflammatory proteins (N = 14,824). This study used the univariate MR (UVMR), mediation MR analysis, and sensitivity analysis to assess the potential causal associations between these biomarkers and AN. RESULTS: The inverse variance weighted (IVW) results suggest that 25 gut microbiota have causal effects on AN. Firmicutes E (OR: 0.294, 95 % CI: 0.107-0.806, P = 0.017), RUG147 (OR: 0.386, 95 % CI: 0.151-0.990, P = 0.048), CAG-977 (OR: 0.562, 95 % CI: 0.378-0.837, P = 0.005), Desulfobacterota A (OR: 0.651, 95 % CI: 0.466-0.909, P = 0.012), CAG-269 sp002372935 (OR: 0.673, 95 % CI: 0.483-0.937, P = 0.019), Klebsiella (OR: 0.684, 95 % CI: 0.566-0.827, P = 0.00009), Desulfovibrionia (OR: 0.706, 95 % CI: 0.538-0.926, P = 0.012), Klebsiella pneumoniae (OR: 0.737, 95 % CI: 0.600-0.906, P = 0.004), Desulfovibrionales (OR: 0.786, 95 % CI: 0.631-0.979, P = 0.031), CAG-776 (OR: 0.787, 95 % CI: 0.632-0.980, P = 0.032), Desulfovibrionaceae (OR: 0.788, 95 % CI: 0.635-0.978, P = 0.030). 13 gut microbiota were risk factors for AN, including Parachlamydiales (OR: 3.134，95%CI: 1.185-8.287, P = 0.021), Paenibacillus J (OR: 2.366，95%CI: 1.305-4.29, P = 0.005), Gillisia (OR: 1.947，95%CI: 1.135-3.339, P = 0.016), UBA1191 (OR: 1.856，95%CI: 1.221-2.822, P = 0.004), UBA7703 (OR: 1.843，95%CI: 1.032-3.289, P = 0.039), Faecalicatena sp002161355 (OR: 1.788，95%CI: 1.114-2.870, P = 0.016), Johnsonella ignava (OR: 1.742，95%CI: 1.031-2.944, P = 0.038), Staphylococcus aureus (OR: 1.614, 95%CI: 1.007-2.588, P = 0.047), Comamonas (OR: 1.522，95%CI: 1.004-2.307, P = 0.048), Ruminococcus D (OR: 1.24，95%CI: 1.050-1.464, P = 0.011), CAG-349 (OR: 1.198，95%CI: 1.048-1.370, P = 0.008), Ruminococcus D bicirculans (OR: 1.175，95%CI: 1.001-1.379, P = 0.048), CAG-177 (OR: 1.272，95%CI: 1.077-1.503, P = 0.005). Reverse MR analysis showed that causal effect of AN on 18 gut microbiota, but to a lesser extent. 12 metabolites have causal effects on AN. There are 7 protective factors, including glucose levels (OR: 0.700, 95%CI: 0.550-0.893, P = 0.004), isoleucine levels (OR: 0.769, 95%CI: 0.602-0.983, P = 0.036), phospholipids in large VLDL (OR: 0.856, 95%CI: 0.736-0.996, P = 0.044), total lipids in large VLDL (OR: 0.860, 95%CI: 0.740-0.999, P = 0.049), total lipids in small VLDL (OR: 0.863, 95%CI: 0.751-0.992, P = 0.038), free cholesterol in small VLDL (OR: 0.86, 95%CI: 0.752-0.996, P = 0.044), and free cholesterol in medium VLDL (OR: 0.866, 95%CI: 0.752-0.998, P = 0.047). There are 5 risk factors, including estimated degree of unsaturation (OR: 1.174, 95%CI: 1.009-1.367, P = 0.039), free cholesterol to total lipids ratio in small VLDL (OR: 1.199, 95%CI: 1.017-1.414, P = 0.031), phospholipids to total lipids ratio in small VLDL (OR: 1.216, 95%CI: 1.008-1.467, P = 0.041), total cholesterol levels in small HDL (OR: 1.241, 95%CI: 1.008-1.530, P = 0.042), and phospholipids to total lipids ratio in medium VLDL (OR: 1.280, 95%CI: 1.055-1.553, P = 0.012). Reverse MR analysis showed that AN had a causal effect on 15 metabolites. Mediation analysis reveals that the estimated degree of unsaturation mediates 0.69 % of the effect of Klebsiella pneumoniae on AN. Total lipids in small VLDL mediate 0.358 % of the effect of CAG-177 on AN, with a mediated proportion of 1.490 %. The mediation proportions for Estimated degree of unsaturation and Total lipids in small VLDL are relatively small. 36 immune cells have causal effects on AN. There are 7 protective factors, including Switched memory B cells %B cell (OR: 0.892，95%CI: 0.801-0.994, P = 0.038), CD127-CD8+ T cell absolute count (OR: 0.888，95%CI: 0.789-1.000, P = 0.049), IgD + CD24- B cell (OR: 0.917，95%CI: 0.862-0.975, P = 0.006), HVEM+ T cell (OR: 0.945，95%CI: 0.894-0.999, P = 0.045), CD40 + CD14 + CD16- monocyte (OR: 0.937，95%CI: 0.882-0.996, P = 0.038), CD64 + CD14 + CD16- monocyte (OR: 0.966，95%CI: 0.939-0.993, P = 0.016), CD8+ natural killer T cells (OR: 0.911，95%CI: 0.836-0.992, P = 0.032), HLA-DR+ T cells (OR: 0.921，95%CI: 0.866-0.980, P = 0.010), CD28-CD8+ T cells (OR: 0.886，95%CI: 0.792-0.991, P = 0.034). There are 26 risk factors. Reverse MR analysis showed that AN had a causal effect on 31 immune cells. AN increases the expression levels of five types of immune cells, including CD40 + CD14-CD16+ monocytes (OR: 1.087，95%CI: 1.004-1.177, P = 0.041), PDL-1+ CD14-CD16+ monocytes (OR: 1.082，95%CI: 1.002-1.168, P = 0.046), CD45+ CD33dim HLA-DR+ cells (OR: 1.145，95%CI: 1.019-1.287, P = 0.023), CD45+ basophils (OR: 1.164，95%CI: 1.036-1.307, P = 0.011), CD8+ natural killer T cells (OR: 1.102, 95%CI: 1.015-1.196, P = 0.020), and also decreases the expression levels of 26 immune cells. 6 liposomes showed exhibit protective effects against AN, including phosphatidylcholine (18:0_20:3) levels (OR: 0.852, 95%CI: 0.740-0.981, P = 0.026), phosphatidylcholine (O-18:2_18:1) levels (OR: 0.800, 95%CI: 0.672-0.952, P = 0.012), phosphatidylinositol (18:0_18:1) levels (OR: 0.873, 95%CI: 0.773-0.986, P = 0.029), phosphatidylinositol (18:1_18:2) levels (OR: 0.844, 95%CI: 0.734-0.971, P = 0.018), sphingomyelin (d38:1) levels (OR: 0.903，95%CI: 0.820-0.995, P = 0.039), and triacylglycerol (56:4) levels (OR: 0.786, 95%CI: 0.660-0.936, P = 0.007). There are 3 risk factors, including diacylglycerol (16:1_18:1) levels (OR: 1.208, 95%CI: 1.040-1.404, P = 0.014), phosphatidylcholine (18:1_18:3) levels (OR: 1.237, 95%CI: 1.003-1.526, P = 0.047), and phosphatidylinositol (16:0_20:4) levels (OR: 1.148, 95%CI: 1.003-1.314, P = 0.045). Reverse MR analysis showed that AN had a causal effect on 3 phosphatidylcholine (15:0_18:2) levels (OR: 1.075, 95%CI: 1.001-1.154, P = 0.048), phosphatidylcholine (O-16:2_18:0) levels (OR: 1.078, 95%CI: 1.002-1.159, P = 0.043), and triacylglycerol (51:1) levels (OR: 0.919, 95%CI: 0.850-0.994, P = 0.035). 6 inflammatory proteins have causal effects on AN, with protective factors including Glial cell line-derived neurotrophic factor levels (OR: 0.822，95%CI: 0.692-0.978, P = 0.027) and Interleukin-15 receptor subunit alpha levels (OR: 0.886, 95%CI: 0.789-0.995, P = 0.041) and risk factors including CC motif chemokine 4 levels (OR: 1.126, 95%CI: 1.011-1.254, P = 0.031), Interleukin-12 subunit beta levels (OR: 1.135, 95%CI: 1.033-1.248, P = 0.008), Monocyte chemoattractant protein-1 levels (OR: 1.152, 95%CI: 1.010-1.314, P = 0.035), and Sulfotransferase 1A1 levels (OR: 1.166, 95%CI: 1.006-1.351, P = 0.042). Reverse MR analysis showed that AN had a causal effect on Transforming growth factor-alpha (OR: 1.054，95%CI: 1.010-1.101, P = 0.016). CONCLUSIONS: This study used large-scale and novel GWAS data, for the first time reveals through mediation analysis and multi-omics MR analysis the roles of gut microbiota, metabolites, immune cells, lipids, and inflammatory proteins in the pathogenesis of AN. These findings provide new biomarkers and targets for further prevention and treatment strategies.