Cargando…
Genomic and proteomic biases inform metabolic engineering strategies for anaerobic fungi
Anaerobic fungi (Neocallimastigomycota) are emerging non-model hosts for biotechnology due to their wealth of biomass-degrading enzymes, yet tools to engineer these fungi have not yet been established. Here, we show that the anaerobic gut fungi have the most GC depleted genomes among 443 sequenced o...
Autores principales: | , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6883316/ https://www.ncbi.nlm.nih.gov/pubmed/31799118 http://dx.doi.org/10.1016/j.mec.2019.e00107 |
_version_ | 1783474354556764160 |
---|---|
author | Wilken, St. Elmo Seppälä, Susanna Lankiewicz, Thomas S. Saxena, Mohan Henske, John K. Salamov, Asaf A. Grigoriev, Igor V. O’Malley, Michelle A. |
author_facet | Wilken, St. Elmo Seppälä, Susanna Lankiewicz, Thomas S. Saxena, Mohan Henske, John K. Salamov, Asaf A. Grigoriev, Igor V. O’Malley, Michelle A. |
author_sort | Wilken, St. Elmo |
collection | PubMed |
description | Anaerobic fungi (Neocallimastigomycota) are emerging non-model hosts for biotechnology due to their wealth of biomass-degrading enzymes, yet tools to engineer these fungi have not yet been established. Here, we show that the anaerobic gut fungi have the most GC depleted genomes among 443 sequenced organisms in the fungal kingdom, which has ramifications for heterologous expression of genes as well as for emerging CRISPR-based genome engineering approaches. Comparative genomic analyses suggest that anaerobic fungi may contain cellular machinery to aid in sexual reproduction, yet a complete mating pathway was not identified. Predicted proteomes of the anaerobic fungi also contain an unusually large fraction of proteins with homopolymeric amino acid runs consisting of five or more identical consecutive amino acids. In particular, threonine runs are especially enriched in anaerobic fungal carbohydrate active enzymes (CAZymes) and this, together with a high abundance of predicted N-glycosylation motifs, suggests that gut fungal CAZymes are heavily glycosylated, which may impact heterologous production of these biotechnologically useful enzymes. Finally, we present a codon optimization strategy to aid in the development of genetic engineering tools tailored to these early-branching anaerobic fungi. |
format | Online Article Text |
id | pubmed-6883316 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-68833162019-12-03 Genomic and proteomic biases inform metabolic engineering strategies for anaerobic fungi Wilken, St. Elmo Seppälä, Susanna Lankiewicz, Thomas S. Saxena, Mohan Henske, John K. Salamov, Asaf A. Grigoriev, Igor V. O’Malley, Michelle A. Metab Eng Commun Article Anaerobic fungi (Neocallimastigomycota) are emerging non-model hosts for biotechnology due to their wealth of biomass-degrading enzymes, yet tools to engineer these fungi have not yet been established. Here, we show that the anaerobic gut fungi have the most GC depleted genomes among 443 sequenced organisms in the fungal kingdom, which has ramifications for heterologous expression of genes as well as for emerging CRISPR-based genome engineering approaches. Comparative genomic analyses suggest that anaerobic fungi may contain cellular machinery to aid in sexual reproduction, yet a complete mating pathway was not identified. Predicted proteomes of the anaerobic fungi also contain an unusually large fraction of proteins with homopolymeric amino acid runs consisting of five or more identical consecutive amino acids. In particular, threonine runs are especially enriched in anaerobic fungal carbohydrate active enzymes (CAZymes) and this, together with a high abundance of predicted N-glycosylation motifs, suggests that gut fungal CAZymes are heavily glycosylated, which may impact heterologous production of these biotechnologically useful enzymes. Finally, we present a codon optimization strategy to aid in the development of genetic engineering tools tailored to these early-branching anaerobic fungi. Elsevier 2019-11-15 /pmc/articles/PMC6883316/ /pubmed/31799118 http://dx.doi.org/10.1016/j.mec.2019.e00107 Text en © 2019 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Article Wilken, St. Elmo Seppälä, Susanna Lankiewicz, Thomas S. Saxena, Mohan Henske, John K. Salamov, Asaf A. Grigoriev, Igor V. O’Malley, Michelle A. Genomic and proteomic biases inform metabolic engineering strategies for anaerobic fungi |
title | Genomic and proteomic biases inform metabolic engineering strategies for anaerobic fungi |
title_full | Genomic and proteomic biases inform metabolic engineering strategies for anaerobic fungi |
title_fullStr | Genomic and proteomic biases inform metabolic engineering strategies for anaerobic fungi |
title_full_unstemmed | Genomic and proteomic biases inform metabolic engineering strategies for anaerobic fungi |
title_short | Genomic and proteomic biases inform metabolic engineering strategies for anaerobic fungi |
title_sort | genomic and proteomic biases inform metabolic engineering strategies for anaerobic fungi |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6883316/ https://www.ncbi.nlm.nih.gov/pubmed/31799118 http://dx.doi.org/10.1016/j.mec.2019.e00107 |
work_keys_str_mv | AT wilkenstelmo genomicandproteomicbiasesinformmetabolicengineeringstrategiesforanaerobicfungi AT seppalasusanna genomicandproteomicbiasesinformmetabolicengineeringstrategiesforanaerobicfungi AT lankiewiczthomass genomicandproteomicbiasesinformmetabolicengineeringstrategiesforanaerobicfungi AT saxenamohan genomicandproteomicbiasesinformmetabolicengineeringstrategiesforanaerobicfungi AT henskejohnk genomicandproteomicbiasesinformmetabolicengineeringstrategiesforanaerobicfungi AT salamovasafa genomicandproteomicbiasesinformmetabolicengineeringstrategiesforanaerobicfungi AT grigorievigorv genomicandproteomicbiasesinformmetabolicengineeringstrategiesforanaerobicfungi AT omalleymichellea genomicandproteomicbiasesinformmetabolicengineeringstrategiesforanaerobicfungi |