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Background: Laccases can oxidize a broad spectrum of substrates, offering promising applications in various sectors, such as bioremediation, biomass fractionation in future biorefineries, and synthesis of biochemicals and biopolymers. However, laccase discovery and optimization with a desirable pH optimum remains a challenge due to the labor-intensive and time-consuming nature of the traditional laboratory methods., Results: This study presents a machine learning (ML)-integrated approach for predicting pH optima of basidiomycete fungal laccases, utilizing a small, curated dataset against a vast metagenomic data. Comparative computational analyses unveiled the structural and pH-dependent solubility differences between acidic and neutral-alkaline laccases, helping us understand the molecular bases of enzyme pH optimum. The pH profiling of the two ML-predicted alkaline laccase candidates from the basidiomycete fungus Lepista nuda further validated our computational approach, showing the accuracy of this comprehensive method., Conclusions: This study uncovers the efficacy of ML in the prediction of enzyme pH optimum from minimal datasets, marking a significant step towards harnessing computational tools for systematic screening of enzymes for biotechnology applications., (© 2024. The Author(s).)

Aspergillus terreus has attracted interest due to its application in industrial biotechnology, particularly for the production of itaconic acid and bioactive secondary metabolites. As related species also seem to possess a prosperous secondary metabolism, they are of high interest for genome mining and exploitation. Here, we present draft genome sequences for six species from Aspergillus section Terrei and one species from Aspergillus section Nidulantes . Whole-genome phylogeny confirmed that section Terrei is monophyletic. Genome analyses identified between 70 and 108 key secondary metabolism genes in each of the genomes of section Terrei , the highest rate found in the genus Aspergillus so far. The respective enzymes fall into 167 distinct families with most of them corresponding to potentially unique compounds or compound families. Moreover, 53% of the families were only found in a single species, which supports the suitability of species from section Terrei for further genome mining. Intriguingly, this analysis, combined with heterologous gene expression and metabolite identification, suggested that species from section Terrei use a strategy for UV protection different to other species from the genus Aspergillus . Section Terrei contains a complete plant polysaccharide degrading potential and an even higher cellulolytic potential than other Aspergilli, possibly facilitating additional applications for these species in biotechnology.

Background: Colletotrichum fungi infect a wide diversity of monocot and dicot hosts, causing diseases on almost all economically important plants worldwide. Colletotrichum is also a suitable model for studying gene family evolution on a fine scale to uncover events in the genome associated with biological changes., Results: Here we present the genome sequences of 30 Colletotrichum species covering the diversity within the genus. Evolutionary analyses revealed that the Colletotrichum ancestor diverged in the late Cretaceous in parallel with the diversification of flowering plants. We provide evidence of independent host jumps from dicots to monocots during the evolution of Colletotrichum, coinciding with a progressive shrinking of the plant cell wall degradative arsenal and expansions in lineage-specific gene families. Comparative transcriptomics of 4 species adapted to different hosts revealed similarity in gene content but high diversity in the modulation of their transcription profiles on different plant substrates. Combining genomics and transcriptomics, we identified a set of core genes such as specific transcription factors, putatively involved in plant cell wall degradation., Conclusions: These results indicate that the ancestral Colletotrichum were associated with dicot plants and certain branches progressively adapted to different monocot hosts, reshaping the gene content and its regulation., (© The Author(s) 2024. Published by Oxford University Press GigaScience.)

The import of plant-derived small sugars by sugar transporters (STs) has received increasing interest due to its important biological role and great industrial potential. STs are important targets of genetic engineering to improve fungal plant biomass conversion. Comparatively analysis of the genome-wide prevalence and transcriptomics of STs was performed in four filamentous fungi: Aspergillus niger, Aspergillus nidulans, Penicillium subrubescens and Trichoderma reesei. Using phylogenetic analysis and literature mining, their predicted STs were divided into ten subfamilies with putative sugar specificities assigned. In addition, transcriptome analysis revealed complex expression profiles among different STs subfamilies and fungal species, indicating a sophisticated transcriptome regulation and functional diversity of fungal STs. Several STs showed strong co-expression with other genes involved in sugar utilization, encoding CAZymes and sugar catabolic enzymes. This study provides new insights into the diversity of STs at the genomic/transcriptomic level, facilitating their biochemical characterization and metabolic engineering., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)