Graph data science in fungal biotechnology: Opportunities and applications.

https://fungidb.org/fungidb/app FungiDB is a fungal and Oomycete resource. It currently contains genomic, transcriptomic and phenotypic information on 317 organisms. https://mycocosm.jgi.doe.gov/mycocosm/home MycoCosm is a resource developed by the Joint Genome Institute that serves as a fungal genomics resource. They have an ongoing “1000 Fungal Genomes project.” http://fungi.ensembl.org/index.html This site provides a resource for fungal genomes, mostly derived from databases of the European Nucleotide Archive and the DNA Database of Japan. https://www.broadinstitute.org/fungal-genome-initiative The Fungal Genomics site sponsored by the Broad Institute focuses on fungal pathogens and the mechanisms by which certain fungi cause disease. https://www.yeastgenome.org This is a community resource devoted to providing comprehensive information about the Saccharomyces cerevisiae genome and its genes, proteins, and general features. https://www1.biologie.uni-hamburg.de/b-online/library/genomeweb/GenomeWeb/fungal-gen-db.html This page provides links to a significant collection of databases catering to yeast and filamentous fungal genomes. http://www.candidagenome.org The Candida Genome Database covers Candida albicans and related species with access to genomic sequence data and functional information. https://www.sciencedirect.com/topics/biochemistry-genetics-and-molecular-biology/fungal-genome This page provides a compendium of articles and chapters dealing with fungal genomes. https://www.nature.com/articles/s41559-023-02095-9 This study provides a catalogue of gene family changes across diverse fungal lineages to give insights into fungal evolution. https://journals.asm.org/doi/10.1128/microbiolspec.funk-0055-2016 This review article discusses the niches, properties and genomes of the fungal kingdom. https://www.pnas.org/doi/10.1073/pnas.2020230118 In this study, more than one thousand fungal genomes were analyzed for the presence and properties of natural product biosynthetic gene clusters. https://journals.plos.org/plosone/browse/fungal_genomics This page provides a compendium of 297 articles on fungal genomes published in the journal PLoS One.

Employing live fungi or fungal enzymes for industrial applications is known as fungal white biotechnology. White fungal biotechnology, an essential technology, uses renewable sources for sustainable growth of population. Fungi or fungal enzymes have role in food and feed industries. Fungal white biotechnology brings down greenhouse emissions and is eco-friendly in nature. The applications of fungi as food (edible fungi) and fodder and using fungi in processing food (bread, cheese and other bakery products) and fermenting food (alcohols, beverages) are indispensable. Fungal white biotechnology enhances flavour in cheese, bread and beverages; protein quality and yield in SCPs; and stability and shelf life of the products with much efficacy. Though there are many advantages with white fungal biotechnology, tolerance to the extreme conditions during processing and enrichment of products is the major challenge observed with white fungal biotechnology. This chapter reviews the opportunities and challenges of fungal white biotechnology to meet food security.

Fungal biotechnology plays a vital role in advancing sustainability by offering innovative solutions for resource efficiency, environmental protection, and health improvements. Fungal systems are highly adaptable compared with other biotechnologies, with unique genomic and metabolic functions that enable the large-scale production of valuable compounds. This review emphasizes how fungal biotechnology contributes to global sustainability goals, particularly through artificial intelligence (AI)-driven methods that accelerate strain optimization and metabolic engineering. Engineered Aspergillus strains, with enhanced enzyme production, and Neurospora, a model organism, demonstrate significant potential for industrial applications. These advancements offer cost-effective and resource-efficient solutions, underscoring the importance of interdisciplinary collaboration in fungal biology, genomics, enzymes, and computational approaches to scale fungal biotechnology for sustainable outcomes.

AimPrimary ciliary dyskinesia (PCD) is a genetic disorder affecting motile cilia. Most cases are inherited recessively, due to variants in more than 50 genes that result in abnormal or absent motile cilia. This leads to chronic upper and lower airway disease, sub-fertility and laterality defects in some cases. Given overlapping clinical features and genetic heterogeneity, diagnosis can be difficult and often occurs late. Of those tested, an estimated 30% of genetically screened PCD patients still lack a molecular diagnosis. Here, we aimed to identify how readily a genetic diagnosis could be made in a clinically diagnosed population using whole genome sequencing (WGS) to facilitate identification of pathogenic variants in known genes as well as identify novel PCD candidate genes.MaethodsWGS was used to screen for variants causing PCD in 8 clinically diagnosed PCD patients, sequenced as trios where parental samples were available.ResultsSeven of the eight cases (87.5%) had homozygous or biallelic variants inDNAH5,DNAAF4orDNAH11that were classified as pathogenic or likely pathogenic. Three of the variants were deletions, ranging from 3kb to 13kb, for which WGS identified precise breakpoints, permitting confirmation by Sanger sequencing. WGS yielded a high genetic diagnostic rate from this clinically diagnosed population, in part through detection of structural variants as well as identification of ade novovariant in a novel PCD geneTUBB4B.ConclusionA molecular diagnosis allows for appropriate clinical management for cases and their families, including prediction of phenotypic features correlated to genotype. Here, WGS uplifted genetic diagnosis in cases of clinically diagnosed PCD by identifying structural variants and novel modes of inheritance in new candidate genes. Our study suggests that WGS could be a powerful part of the PCD diagnostic toolkit to increase the current molecular diagnostic yield from 70%. It provides important new insight into our understanding of fundamental biology of motile cilia as well as of variation in the non-coding genome in PCD.SummaryWhole genome sequencing (WGS) yielded a high genetic diagnostic rate (100%) in eight Scottish patients with clinically diagnosed primary ciliary dyskinesia (PCD) by detection of large structural variants, homology modelling and identification of a novel disease gene with a dominant mode of inheritance. Prioritised WGS may facilitate early genetic diagnosis in PCD.

IntroductionPrecision prevention implements highly precise, tailored health interventions for individuals by directly addressing personal and environmental determinants of health. However, precision prevention does not yet appear to be fully established in occupational health. There are numerous understandings and conceptual approaches, but these have not yet been systematically presented or synthesized. Therefore, this conceptual analysis aims to propose a unified understanding and develop an integrative conceptual framework for precision prevention in occupational health.MethodsFirstly, to systematically present definitions and frameworks of precision prevention in occupational health, six international databases were searched for studies published between January 2010 and January 2024 that used the term precision prevention or its synonyms in the context of occupational health. Secondly, a qualitative content analysis was conducted to analyze the existing definitions and propose a unified understanding. Thirdly, based on the identified frameworks, a multi-stage exploratory development process was applied to develop and propose an integrative conceptual framework for precision prevention in occupational health.ResultsAfter screening 3,681 articles, 154 publications were reviewed, wherein 29 definitions of precision prevention and 64 different frameworks were found, which can be summarized in eight higher-order categories. The qualitative content analysis revealed seven themes and illustrated many different wordings. The proposed unified understanding of precision prevention in occupational health takes up the identified themes. It includes, among other things, a contrast to a “one-size-fits-all approach” with a risk- and resource-oriented data collection and innovative data analytics with profiling to provide and improve tailored interventions. The developed and proposed integrative conceptual framework comprises three overarching stages: (1) data generation, (2) data management lifecycle and (3) interventions (development, implementation and adaptation).DiscussionAlthough there are already numerous studies on precision prevention in occupational health, this conceptual analysis offers, for the first time, a proposal for a unified understanding and an integrative conceptual framework. However, the proposed unified understanding and the developed integrative conceptual framework should only be seen as an initial proposal that should be critically discussed and further developed to expand and strengthen both research on precision prevention in occupational health and its practical application in the workplace.

BackgroundCharacterization of genomic structural variation (SV) is essential to expanding the research and clinical applications of genome sequencing. Reliance upon short DNA fragment paired end sequencing has yielded a wealth of single nucleotide variants and internal sequencing read insertions-deletions, at the cost of limited SV detection. Multi-kilobase DNA fragment mate pair sequencing has supplemented the void in SV detection, but introduced new analytic challenges requiring SV detection tools specifically designed for mate pair sequencing data. Here, we introduce SVachra – Structural Variation Assessment of CHRomosomal Aberrations, a breakpoint calling program that identifies large insertions-deletions, inversions, inter- and intra-chromosomal translocations utilizing both inward and outward facing read types generated by mate pair sequencing.ResultsWe demonstrate SVachra’s utility by executing the program on large-insert (Illumina Nextera) mate pair sequencing data from the personal genome of a single subject (HS1011). An additional data set of long-read (Pacific BioSciences RSII) was also generated to validate SV calls from SVachra and other comparison SV calling programs. SVachra exhibited the highest validation rate and reported the widest distribution of SV types and size ranges when compared to other SV callers.ConclusionsSVachra is a highly specific breakpoint calling program that exhibits a more unbiased SV detection methodology than other callers.

Acute myeloid leukemia (AML) is a particularly devastating collection of hematological cancers and whilst somewhat rare, the patient survival rate is abysmal without bone marrow transplantation. Traditional chemotherapies administered to AML patients cause significant and devastating side effects. Additionally, more than 30% of patients fail to respond to these initial treatments and most patients that do respond will eventually relapse within 5 years. As such, understanding the evolution of AML to identify novel targets, and therefore drug treatment regimens, is a significant medical need. Genomic rearrangements and other Structural Variations (SVs) have long been known to be causative and pathogenic in multiple cancers, including leukemias. Indeed the discovery of the “Philadelphia chromosome” (eventually identified as a BCR-ABL translocation) as causative in Chronic Myeloid Leukemia has prompted much research into SVs in cancers, including the development of targeted therapeutics against oncogenic proteins resulting from genomic rearrangements. These SVs may be involved in cancer initiation, progression, clonal evolution, and drug resistance, and a better understanding of SVs from individual AML patients may help guide therapeutic options. Here we show utilization of an innovative whole genome imaging technology to detect known, and novel, SVs in AML patients' samples. Importantly, this new technology provides an unprecedented level of granularity and quantitation unavailable to other current techniques and it allows an unbiased detection of novel SVs, which may be relevant for disease pathogenesis and/ or drug resistance. Coupled with standard gene expression analyses we have also assessed the chemosensitivities of these samples to 120 FDA approved oncology drugs and 335 epigenetic modulating agents. Here we show how integrative analysis of these diverse datasets is used to associate the detected genomic rearrangements with drug sensitivity profiles, potentially identifying novel therapeutic targets for individual AML patients. Citation Format: Darren Finlay, Rabi Murad, Karl Hong, Joyce Lee, Andy Pang, Chi-Yu Lai, Carol Burian, James Mason, Alex Hastie, Jun Yin, Kristiina Vuori. Detection of genomic structural variations associated with drug sensitivities and resistance in AML using novel whole genome imaging [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 3529.

Background: Genomic Structural variation (SV) refer to abnormalities in chromosome structure, is a normal part of variation in the human genome. Now Genomics SVs are recognized as the largest source of interindividual genetic variation and are closely associated with oncogenesis. The ability to identify constitutive and low-allelic fraction SVs is crucial. Standard SV detection method include chromosome banding, fluorescence in situ hybridization (FISH), and array comparative genome hybridization (CGH), which are manually intensive and have trouble finding low-frequency mutations. In recent year, genome physical mapping technologies have received increasing attention and optical mapping-based methods can well-accomplish sufficient to detect large size SVs or SVs within repetitive regions. Lately, Bionano optical mapping technology rapidly expanded its applications in the detection of structural variations. As well known, Acute Leukemia show distinct patterns of genetic aberrations including chromosome translocations, mutations, and aneuploidies in genes responsible for cell cycle regulation and lymphoid cell development. Method: We use our liver cancer model LI6671 to establish the Bionano Saphyr Gen2 genome imaging platform. DNA >100kbp is extracted, “CTTAAG” sequences were labelled across the entire genome by using Direct-Label-Enzyme (DLE) and linearized through chips for visualizations. Saphyr was loaded, linearized, and imaged labeled DNA in repeated cycles. Assembly Algorithms covert collected DNA images into constructing consensus genome maps. And this assay platform will be used to comprehensively identify SVs for studying our 21 HuKemia models. Results: By using this fluorescence labels distribution patterns, we find different structure variants among genome. We used filtered data for genome map assembly and compared with human genome hg38 for SV detection. In LI6671, we found out 3952 SVs in LI667 including 1166 deletion, 2497 insertion, 101 duplication, 78 inversion breakpoints, 66 interchr. translocation breakpoints and intrachr. translocation. Oncogenesis related SVs, such as a ~13Kb heterozygous deletion at KCNQ1 region, EPC1::SP1 gene fusions have be founded. Conclusion: Saphyr is a comprehensive platform, can discover a broad range of Genomic SVs and further improves our understanding of Acute Lymphocytic Leukemia (ALL) and Acute Myelocytic Leukemia (AML). Citation Format: Xiaobo Chen, Huan Tian, Wubin Qian, Henry Q. Li, Sheng Guo. Detection of structural variation and analysis on HuKemia models by Using Bionano optical mapping [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2234.

Spatial patterns of intraspecific variation are shaped by geographical distance among populations, historical changes in gene flow and interactions with local environments. Although these factors are not mutually exclusive and operate on both genomic and phenotypic variation, it is unclear how they affect these two axes of variation. We address this question by exploring the predictors of genomic and phenotypic divergence in Icterus gularis, a broadly distributed Middle American bird that exhibits marked geographical variation in body size across its range. We combined a comprehensive single nucleotide polymorphism and phenotypic data set to test whether genome-wide genetic and phenotypic differentiation are best explained by (i) isolation by distance, (ii) isolation by history or (iii) isolation by environment. We find that the pronounced genetic and phenotypic variation in I. gularis are only partially correlated and differ regarding spatial predictors. Whereas genomic variation is largely explained by historical barriers to gene flow, phenotypic diversity can be best predicted by contemporary environmental heterogeneity. Our genomic analyses reveal strong phylogeographical structure coinciding with the Chivela Pass at the Isthmus of Tehuantepec that was formed during the Pleistocene, when populations were isolated in north-south refugia. In contrast, we found a strong association between body size and environmental variables, such as temperature and precipitation. The relationship between body size and local climate is consistent with a pattern produced by either natural selection or environmental plasticity. Overall, these results provide empirical evidence for why phenotypic and genomic data are often in conflict in taxonomic and phylogeographical studies.

Recent technological advances in the detection of genomic structural variation have revolutionized the field of medical genetics. Genome-wide screening for copy-number variants in routine molecular diagnostics unveiled the presence of an unforeseen amount of structural variation in the genome. Owing to the massive amount of patients analyzed, the analysis of the resulting data became exponentially more complex. Simultaneously, novel insights in the impact of structural variation on the phenotype forced the re-evaluation of the pathogenicity of copy-number variations in more complex inheritance models. As a consequence, the challenge of today’s genetics shifted from the mere detection of structural variation to the correct annotation and interpretation of the data. Various databases and data mining tools are available to help in the interpretation of the data, but making decisions on the pathogeniticy of the variation is still challenging. This review provides an overview of current laboratory techniques to detect structural variation, options to analyze and annotate data from genome-wide methods and caveats to take into account in interpretation of results.

The Amazon Biome is known as the greatest biological diversity and forest richness of the planet, constitutes a source of great value for the search of new enzymatic extracts to be explored for biotechnological application. In this context, fungi are used in food production, in the pharmaceutical industry, in the biodegradation process, in the biological treatment of effluents, they act in the enzymatic activity, of industrial interest and biotransformation, they are also of great agricultural and ecological importance. Thus, the present work aimed to perform a systematic review on fungal biotechnology in the Brazilian Amazon, presenting works developed in the region, noting the period of inclusion in the last 10 years (2010-2020). It was verified the publication of 31 works of bibliographic productions on biotechnological applications. The productions on the theme of fungal biotechnology were infrequently comprehensive in the year 2010 until the year 2013. It was found that there was a following growth of stability of the theme's incidence in publications in the subsequent years, especially in the year 2017 until the year 2020. Based on the study conducted, it was verified the importance of different works that address the study of Biotechnology to obtain various substances through the manipulation of fungi, in order to obtain new technologies for the benefit of society and importance to the environment.

Basidiomycete fungi are efficient organisms for conversion and degradation of plant biomass. This is due to combination of their extracellular enzymes and chemical reactions targeted to plant cell wall degradation. Wood- and litter-decomposing white rot fungi have unique ability to degrade and even mineralize all polymeric components of plant cell walls, including aromatic lignin, which makes them promising candidates for biotechnological applications using plant biomass as feedstock. Rapidly increasing whole genome sequence data has revealed the content of plant biomass modification related genes in different basidiomycete species. Comparative genome analyses have enlightened evolutionary events that have led to development of different fungal plant cell wall decay strategies, which are reflected in nuances detected between basidiomycete rot types and life styles in nature. However, basidiomycete genomes harbour a large number of genes encoding proteins with unknown functions, which remains to be characterized to fully understand the degradation process. In addition, fungal aromatic metabolism of plant biomass-derived compounds has gained relatively little attention, although aromatic metabolic enzymes specifically acting on lignin structures would provide interesting options for biotechnological use. Still, low production levels of basidiomycete enzymes in commonly used ascomycete or bacterial host organisms often hamper their use in biotechnological applications. Another aspect that is in its infancy in basidiomycetes and restricts the use of their full potential is understanding of the regulatory systems driving the production of plant biomass-degrading enzymes. In this chapter, recent developments in basidiomycete research with respect to plant biomass conversion will be discussed.

Fungal biotechnology can advance the transition to a bio-based circular economy and has the ability to sustainably produce economic food, chemicals, fuels, textiles, and contribute to pharmaceutical and medical applications. Fungal and bacterial lipases as versatile biological catalysts have given a promising prospect in meeting the needs for most industries employing catalytic abilities, hydrolysis, esterification, and transesterification. Fungal lipases exhibit various classes with broad stability to pH ranging from pH 4.0 to 11.0 (alkaline or acidic), temperature ranging from 10 to 96 °C (thermophilic or psychotropic) with diverse catalytic abilities including reversibility of reaction, broad isoelectric points, and substrate specificity. Reduced production costs and easy genetic manipulation supported gaining increased interest. Fungal lipases are extracellular, and their production is influenced by nutritional and physicochemical factors which emphasis the optimization role of fermentation condition for their production. Knowledge of structural features plays an important role in designing and engineering lipases for specific purposes. In silico methods help in the predictions of enzymatic affinity, activity, specificity, and selectivity of newly discovered proteins. This kind of bioinformatics approaches allow the screening of potential target for application in bioremediation and take advantage of fungi enzymes for industrial applications. This chapter describes various sources of lipases, their properties, purification methods, classification, catalytic mechanism, and optimization. We will also shed the light on the3D molecular structures of fungal lipases, bioinformatics approaches, and potential sustainable industrial applications of fungal and bacterial lipases for a green economy which make lipases as biocatalysts of choice for the present and future.

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List of Contributors. Preface. 1. Introduction to Fungal Physiology (Graeme M. Walker and Nia A. White). 1.1 Introduction. 1.2 Morphology of yeasts and fungi. 1.3 Ultrastructure and function of fungal cells. 1.4 Fungal nutrition and cellular biosyntheses. 1.5 Fungal metabolism. 1.6 Fungal growth and reproduction. 1.7 Conclusions. 1.8 Further reading. 1.9 Revision questions. 2. Fungal Genetics (Malcolm Whiteway and Catherine Bachewich). 2.1 Introduction. 2.2 Life cycles. 2.3 Sexual analysis: Regulation of mating. 2.4 Unique characteristics of filamentous fungi that are advantageous for genetic analysis. 2.5 Genetics as a tool. 2.6 Conclusions. 2.7 Further reading. 2.8 Revision questions. 3. Fungal Genetics: A Post-Genomic Perspective (Brendan Curran and Virginia Bugeja). 3.1 Introduction. 3.2 Genomics. 3.3 Transcriptomics and proteomics. 3.4 Proteomics. 3.5 Systems biology. 3.6 Conclusions. 3.7 Further reading. 3.8 Revision questions. 4. Fungal Fermentation Systems and Products (Kevin Kavanagh). 4.1 Introduction. 4.2 Fungal fermentation systems. 4.3 Ethanol production. 4.4 Commercial fungal products. 4.5 Genetic manipulation of fungi. 4.6 Conclusion. 4.7 Further reading. 4.8 Revision questions. 5. Antibiotics, Enzymes and Chemical Commodities from Fungi (Richard A. Murphy and Karina A. Horgan). 5.1 Introduction. 5.2 Fungal metabolism. 5.3 Antibiotic production. 5.4 Pharmacologically active products. 5.5 Enzymes. 5.6 Chemical commodities. 5.7 Yeast extracts. 5.8 Enriched yeast. 5.9 Further reading. 5.10 Revision questions. 6. The Biotechnological Exploitation of Heterologous Protein Production in Fungi (Brendan Curran and Virginia Bugeja). 6.1 Fungal biotechnology. 6.2 Heterologous protein expression in fungi. 6.3 Budding stars. 6.4 Methylotrophic yeast species. 6.5 Case study - hepatitis B vaccine - a billion dollar heterologous protein from yeast. 6.6 Further biotechnological applications of expression technology. 6.7 Conclusion. 6.8 Further reading. 6.9 Revision questions. 7. Fungal Diseases of Humans (Derek Sullivan, Gary Moran and David Coleman). 7.1 Introduction. 7.2 Fungal diseases. 7.3 Superficial mycoses. 7.4 Opportunistic mycoses. 7.5 Endemic systemic mycoses. 7.6 Concluding remarks. 7.7 Further reading. 7.8 Revision questions. 8. Antifungal Agents for Use in Human Therapy (Khaled H. Abu-Elteen and Mawieh Hamad). 8.1 Introduction. 8.2 Polyene antifungal agents. 8.3 The azole antifungal agents. 8.4 Flucytosine. 8.5 Novel antifungal agents. 8.6 Miscellaneous antifungal agents. 8.7 New strategies and future prospects. 8.8 Conclusion. 8.9 Further reading. 8.10 Revision questions. 9. Fungal Pathogens of Plants (Fiona Doohan). 9.1 Fungal pathogens of plants. 9.2 Disease symptoms. 9.3 Factors influencing disease development. 9.4 The disease cycle. 9.5 Genetics of the plant-fungal pathogen interaction. 9.6 Mechanisms of fungal plant parasitism. 9.7 Mechanisms of host defence. 9.8 Disease control. 9.9 Disease detection and diagnosis. 9.10 Vascular wilt diseases. 9.11 Blights. 9.12 Rots and damping-off diseases. 9.13 Leaf and stem spots, anthracnose and scabs. 9.14 Rusts, smuts and powdery mildew diseases. 9.15 Global repercussions of fungal diseases of plants. 9.16 Conclusion. 9.17 Acknowledgements. 9.18 Further reading. 9.19 Revision questions. Answers to Revision Questions. Chapter 1. Chapter 2. Chapter 3. Chapter 4. Chapter 5. Chapter 6. Chapter 7. Chapter 8. Chapter 9. Index.