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...
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Autor*in:	St. Elmo Wilken [verfasserIn] Susanna Seppälä [verfasserIn] Thomas S. Lankiewicz [verfasserIn] Mohan Saxena [verfasserIn] John K. Henske [verfasserIn] Asaf A. Salamov [verfasserIn] Igor V. Grigoriev [verfasserIn] Michelle A. O’Malley [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2020

Schlagwörter:	Codon optimization Amino acid distribution Anaerobe Genome sequencing Fungi Neocallimastigomycota

Übergeordnetes Werk:	In: Metabolic Engineering Communications - Elsevier, 2015, 10(2020), Seite e00107-
Übergeordnetes Werk:	volume:10 ; year:2020 ; pages:e00107-

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1016/j.mec.2019.e00107

Katalog-ID:	DOAJ001890875

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520			\|a 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.
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publishDate	2020
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spelling	10.1016/j.mec.2019.e00107 doi (DE-627)DOAJ001890875 (DE-599)DOAJ36cbda714d80446ea2f3a1fe43c914a8 DE-627 ger DE-627 rakwb eng TP248.13-248.65 QH301-705.5 St. Elmo Wilken verfasserin aut Genomic and proteomic biases inform metabolic engineering strategies for anaerobic fungi 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. Codon optimization Amino acid distribution Anaerobe Genome sequencing Fungi Neocallimastigomycota Biotechnology Biology (General) Susanna Seppälä verfasserin aut Thomas S. Lankiewicz verfasserin aut Mohan Saxena verfasserin aut John K. Henske verfasserin aut Asaf A. Salamov verfasserin aut Igor V. Grigoriev verfasserin aut Michelle A. O’Malley verfasserin aut In Metabolic Engineering Communications Elsevier, 2015 10(2020), Seite e00107- (DE-627)826104924 (DE-600)2821894-2 22140301 nnns volume:10 year:2020 pages:e00107- https://doi.org/10.1016/j.mec.2019.e00107 kostenfrei https://doaj.org/article/36cbda714d80446ea2f3a1fe43c914a8 kostenfrei http://www.sciencedirect.com/science/article/pii/S2214030119300276 kostenfrei https://doaj.org/toc/2214-0301 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 10 2020 e00107-
allfields_unstemmed	10.1016/j.mec.2019.e00107 doi (DE-627)DOAJ001890875 (DE-599)DOAJ36cbda714d80446ea2f3a1fe43c914a8 DE-627 ger DE-627 rakwb eng TP248.13-248.65 QH301-705.5 St. Elmo Wilken verfasserin aut Genomic and proteomic biases inform metabolic engineering strategies for anaerobic fungi 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. Codon optimization Amino acid distribution Anaerobe Genome sequencing Fungi Neocallimastigomycota Biotechnology Biology (General) Susanna Seppälä verfasserin aut Thomas S. Lankiewicz verfasserin aut Mohan Saxena verfasserin aut John K. Henske verfasserin aut Asaf A. Salamov verfasserin aut Igor V. Grigoriev verfasserin aut Michelle A. O’Malley verfasserin aut In Metabolic Engineering Communications Elsevier, 2015 10(2020), Seite e00107- (DE-627)826104924 (DE-600)2821894-2 22140301 nnns volume:10 year:2020 pages:e00107- https://doi.org/10.1016/j.mec.2019.e00107 kostenfrei https://doaj.org/article/36cbda714d80446ea2f3a1fe43c914a8 kostenfrei http://www.sciencedirect.com/science/article/pii/S2214030119300276 kostenfrei https://doaj.org/toc/2214-0301 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 10 2020 e00107-
allfieldsGer	10.1016/j.mec.2019.e00107 doi (DE-627)DOAJ001890875 (DE-599)DOAJ36cbda714d80446ea2f3a1fe43c914a8 DE-627 ger DE-627 rakwb eng TP248.13-248.65 QH301-705.5 St. Elmo Wilken verfasserin aut Genomic and proteomic biases inform metabolic engineering strategies for anaerobic fungi 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. Codon optimization Amino acid distribution Anaerobe Genome sequencing Fungi Neocallimastigomycota Biotechnology Biology (General) Susanna Seppälä verfasserin aut Thomas S. Lankiewicz verfasserin aut Mohan Saxena verfasserin aut John K. Henske verfasserin aut Asaf A. Salamov verfasserin aut Igor V. Grigoriev verfasserin aut Michelle A. O’Malley verfasserin aut In Metabolic Engineering Communications Elsevier, 2015 10(2020), Seite e00107- (DE-627)826104924 (DE-600)2821894-2 22140301 nnns volume:10 year:2020 pages:e00107- https://doi.org/10.1016/j.mec.2019.e00107 kostenfrei https://doaj.org/article/36cbda714d80446ea2f3a1fe43c914a8 kostenfrei http://www.sciencedirect.com/science/article/pii/S2214030119300276 kostenfrei https://doaj.org/toc/2214-0301 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 10 2020 e00107-
allfieldsSound	10.1016/j.mec.2019.e00107 doi (DE-627)DOAJ001890875 (DE-599)DOAJ36cbda714d80446ea2f3a1fe43c914a8 DE-627 ger DE-627 rakwb eng TP248.13-248.65 QH301-705.5 St. Elmo Wilken verfasserin aut Genomic and proteomic biases inform metabolic engineering strategies for anaerobic fungi 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. Codon optimization Amino acid distribution Anaerobe Genome sequencing Fungi Neocallimastigomycota Biotechnology Biology (General) Susanna Seppälä verfasserin aut Thomas S. Lankiewicz verfasserin aut Mohan Saxena verfasserin aut John K. Henske verfasserin aut Asaf A. Salamov verfasserin aut Igor V. Grigoriev verfasserin aut Michelle A. O’Malley verfasserin aut In Metabolic Engineering Communications Elsevier, 2015 10(2020), Seite e00107- (DE-627)826104924 (DE-600)2821894-2 22140301 nnns volume:10 year:2020 pages:e00107- https://doi.org/10.1016/j.mec.2019.e00107 kostenfrei https://doaj.org/article/36cbda714d80446ea2f3a1fe43c914a8 kostenfrei http://www.sciencedirect.com/science/article/pii/S2214030119300276 kostenfrei https://doaj.org/toc/2214-0301 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 10 2020 e00107-
language	English
source	In Metabolic Engineering Communications 10(2020), Seite e00107- volume:10 year:2020 pages:e00107-
sourceStr	In Metabolic Engineering Communications 10(2020), Seite e00107- volume:10 year:2020 pages:e00107-
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Codon optimization Amino acid distribution Anaerobe Genome sequencing Fungi Neocallimastigomycota Biotechnology Biology (General)
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container_title	Metabolic Engineering Communications
authorswithroles_txt_mv	St. Elmo Wilken @@aut@@ Susanna Seppälä @@aut@@ Thomas S. Lankiewicz @@aut@@ Mohan Saxena @@aut@@ John K. Henske @@aut@@ Asaf A. Salamov @@aut@@ Igor V. Grigoriev @@aut@@ Michelle A. O’Malley @@aut@@
publishDateDaySort_date	2020-01-01T00:00:00Z
hierarchy_top_id	826104924
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language_de	englisch
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callnumber-first	T - Technology
author	St. Elmo Wilken
spellingShingle	St. Elmo Wilken misc TP248.13-248.65 misc QH301-705.5 misc Codon optimization misc Amino acid distribution misc Anaerobe misc Genome sequencing misc Fungi misc Neocallimastigomycota misc Biotechnology misc Biology (General) Genomic and proteomic biases inform metabolic engineering strategies for anaerobic fungi
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topic_title	TP248.13-248.65 QH301-705.5 Genomic and proteomic biases inform metabolic engineering strategies for anaerobic fungi Codon optimization Amino acid distribution Anaerobe Genome sequencing Fungi Neocallimastigomycota
topic	misc TP248.13-248.65 misc QH301-705.5 misc Codon optimization misc Amino acid distribution misc Anaerobe misc Genome sequencing misc Fungi misc Neocallimastigomycota misc Biotechnology misc Biology (General)
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title	Genomic and proteomic biases inform metabolic engineering strategies for anaerobic fungi
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title_full	Genomic and proteomic biases inform metabolic engineering strategies for anaerobic fungi
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author_browse	St. Elmo Wilken Susanna Seppälä Thomas S. Lankiewicz Mohan Saxena John K. Henske Asaf A. Salamov Igor V. Grigoriev Michelle A. O’Malley
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title_sort	genomic and proteomic biases inform metabolic engineering strategies for anaerobic fungi
callnumber	TP248.13-248.65
title_auth	Genomic and proteomic biases inform metabolic engineering strategies for anaerobic fungi
abstract	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.
abstractGer	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.
abstract_unstemmed	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.
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title_short	Genomic and proteomic biases inform metabolic engineering strategies for anaerobic fungi
url	https://doi.org/10.1016/j.mec.2019.e00107 https://doaj.org/article/36cbda714d80446ea2f3a1fe43c914a8 http://www.sciencedirect.com/science/article/pii/S2214030119300276 https://doaj.org/toc/2214-0301
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Genomic and proteomic biases inform metabolic engineering strategies for anaerobic fungi

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