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Record W4410720509 · doi:10.1016/j.jobab.2025.05.004

Splitting the difference: Genetically-tunable mycelial films using natural genetic variations in schizophyllum commune

2025· article· en· W4410720509 on OpenAlexafffundvenue
Viraj Whabi, Jianping Xu

Bibliographic record

VenueJournal of Bioresources and Bioproducts · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and Biological Electrophysiology Studies
Canadian institutionsMcMaster University
FundersMcMaster UniversityUniversity of Michigan
KeywordsSchizophyllum communeMyceliumNatural (archaeology)BiologyGeneticsBotany

Abstract

fetched live from OpenAlex

Fungal mycelium, renowned for its robust fiber structure, is gaining widespread attention as a sustainable alternative to traditional plastics and textiles. Strain optimization offers the opportunity to improve these mycelial materials by systematically selecting specific phenotypes that have ideal mechanical and physiochemical properties. Schizophyllum commune , the common split gill mushroom, is a cosmopolitan species with over 23 000 mating types and abundant genetic diversity. In this study, this species was used as a model to explore the potential of leveraging natural genetic variation within species to develop fungal mycelial materials with diverse properties. Specifically, four divergent monokaryotic strains of S. commune sourced globally were selected, and through mating, 12 dikaryotic progeny, each with their unique combinations of nuclear and mitochondrial deoxyribonucleic acid (DNA) were derived. These 16 strains were assessed for their growth in both solid and liquid media. Their mycelia from liquid media were further processed, including by linking with two different crosslinkers, polyethylene glycol 400, and glycerol, to form mycelial films. Mechanical testing and surface characterization showed that the mycelial films differed greatly in a diversity of features, from water retention to strength, ductility, morphology, and hydrophobicity. Moreover, Fourier transform infrared spectroscopy showed that different strains had unique chemical fingerprints revealing diverse cell wall composition that interfaced with each of the crosslinkers uniquely. Statistical analyses revealed that, along with the highly influential crosslinker effects, nuclear-mitochondrial genotype interactions were key factors in tuning the performances of these materials. The two-layer tunability of the fungal materials points to the novel potential for genetically optimized strains, such as through protoplasting to separate nuclei in dikaryons to monokaryons with new nuclear-mitochondrial combinations and/or protoplast fusion to artificially create novel dikaryons, with tailored mycelial materials properties for applications in textiles, coatings, and mycoremediation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.959
Threshold uncertainty score0.280

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.212
Teacher spread0.201 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2025
Admission routes3
Has abstractyes

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