Role of Fungi in Bioremediation and Environmental Sustainability

A comparative assessment of microbial biodiesel and its life cycle analysis

Biodiesel is a type of sustainable, biodegradable energy made from natural sources like vegetable oils, animal fat, and from microbes. Unlike traditional diesel, it has a lower carbon footprint and produces fewer harmful emissions when burned. Biodiesel has gained popularity as a more sustainable substitute for hydrocarbon-based diesel and may be utilized in diesel engines without any modification. In this review, biodiesel from microorganisms such as algae, yeast, and fungi and advantages over another feedstock were discussed. The life cycle evaluation of biodiesel is a thorough assessment of the ecological and economic effects of biodiesel production and use, from the extraction of raw ingredients to the waste disposal process. The life cycle analysis considers the entire process, including the production of feedstocks, the production of biodiesel, and the use of biodiesel in vehicles and other applications. Life cycle analysis of biodiesel produced from microorganisms takes into consideration the environmental impact and sustainability of each step in the production process, including the impact on land use, water use, greenhouse gas emissions, and the availability of resources. In this section, biodiesel produced from microorganisms and other raw materials, its comparisons, and also steps involved in the life cycle such as the cultivation of microorganisms, harvesting of biomass, and conversion to biodiesel were discussed. The processes like extraction and purification, hydrothermal liquefaction, and their environmental impacts were examined by using various LCA software from the previously mentioned process.

Review on the Significant Interactions between Ultrafine Gas Bubbles and Biological Systems

Having sizes comparable with living cells and high abundance, ultrafine bubbles (UBs) are prone to inevitable interactions with different types of cells and facilitate alterations in physiological properties. The interactions of four typical cell types (e.g., bacterial, fungal, plant, and mammalian cells) with UBs have been studied over recent years. For bacterial cells, UBs have been utilized in creating the capillary force to tear down biofilms. The release of high amounts of heat, pressure, and free radicals during bubble rupture is also found to affect bacterial cell growth. Similarly, the bubble gas core identity plays an important role in the development of fungal cells. By the proposed mechanism of attachment of UBs on hydrophobin proteins in the fungal cell wall, oxygen and ozone gas-filled ultrafine bubbles can either promote or hinder the cell growth rate. On the other hand, reactive oxygen species (ROS) formation and mass transfer facilitation are two means of indirect interactions between UBs and plant cells. Likewise, the use of different gas cores in generating bubbles can produce different physical effects on these cells, for example, hydrogen gas for antioxidation against infections and oxygen for oxidation of toxic metal ions. For mammalian cells, the importance of investigating their interactions with UBs lies in the bubbles' action on cell viability as membrane poration for drug delivery can greatly affect cells' survival. UBs have been utilized and tested in forming the pores by different methods, ranging from bubble oscillation and microstream generation through acoustic cavitation to bubble implosion.

Exploring the infiltrative and degradative ability of Fusarium oxysporum on polyethylene terephthalate (PET) using correlative microscopy and deep learning

Managing the worldwide steady increase in the production of plastic while mitigating the Earth's global pollution is one of the greatest challenges nowadays. Fungi are often involved in biodegradation processes thanks to their ability to penetrate into substrates and release powerful catabolic exoenzymes. However, studying the interaction between fungi and plastic substrates is challenging due to the deep hyphal penetration, which hinders visualisation and evaluation of fungal activity. In this study, a multiscale and multimodal correlative microscopy workflow was employed to investigate the infiltrative and degradative ability of Fusarium oxysporum fungal strain on polyethylene terephthalate (PET) fragments. The use of non-destructive high-resolution 3D X-ray microscopy (XRM) coupled with a state-of-art Deep Learning (DL) reconstruction algorithm allowed optimal visualisation of the distribution of the fungus on the PET fragment. The fungus preferentially developed on the edges and corners of the fragment, where it was able to penetrate into the material through fractures. Additional analyses with scanning electron microscopy (SEM), Raman and energy dispersive X-ray spectroscopy (EDX) allowed the identification of the different phases detected by XRM. The correlative microscopy approach unlocked a more comprehensive understanding of the fungus-plastic interaction, including elemental information and polymeric composition.

Ligninolytic enzymes in Basidiomycetes and their application in xenobiotics degradation

Variety of microorganisms have already proven their capabilities for degradation of wide range of wastes with anthropogenic nature. These pollutants, both liquid and solids, also include so called xenobiotics like phenol and its derivatives, PAHs, dyes, pesticides, pharmaceuticals, etc. Xenobiotics as bisphenol A (BPA), chlorhexidine (CHX), octenidine (OCT), other disinfectants and antiseptics have high ecotoxicological impact. Moreover, they can also impair our quality of life and our health interfering different metabolic and hormone receptors pathways in human body. Chemical treatment of such wastes is not a viable option because of its poor socio-economics and environmental merits. Therefore, applying effective, ecofriendly and cheap treatment methods is of great importance. Basidiomycetes are extensively investigated for their abilities to degrade numerous pollutants and xenobiotics. Through their extracellular ligninolytic enzymes they are capable of reducing or completely removing wide range of hazardous compounds. These enzymes can be categorized in two groups: oxidases (laccase) and peroxidases (manganese peroxidase, lignin peroxidase, versatile peroxidase). Due to the broad substrate specificity of the secreted enzymes Basidiomycetes can be applied as a powerful tool for bioremediation of diverse xenobiotics and recalcitrant compounds.

Trends in biological data integration for the selection of enzymes and transcription factors related to cellulose and hemicellulose degradation in fungi

Fungi are key players in biotechnological applications. Although several studies focusing on fungal diversity and genetics have been performed, many details of fungal biology remain unknown, including how cellulolytic enzymes are modulated within these organisms to allow changes in main plant cell wall compounds, cellulose and hemicellulose, and subsequent biomass conversion. With the advent and consolidation of DNA/RNA sequencing technology, different types of information can be generated at the genomic, structural and functional levels, including the gene expression profiles and regulatory mechanisms of these organisms, during degradation-induced conditions. This increase in data generation made rapid computational development necessary to deal with the large amounts of data generated. In this context, the origination of bioinformatics, a hybrid science integrating biological data with various techniques for information storage, distribution and analysis, was a fundamental step toward the current state-of-the-art in the postgenomic era. The possibility of integrating biological big data has facilitated exciting discoveries, including identifying novel mechanisms and more efficient enzymes, increasing yields, reducing costs and expanding opportunities in the bioprocess field. In this review, we summarize the current status and trends of the integration of different types of biological data through bioinformatics approaches for biological data analysis and enzyme selection.