Genes and Genomes coding PHA synthases

Genes and Genomes coding PHA synthases

Abstract

PolyHydroxyAlkanoates (PHA) are microbially produced polymers that could represent a sustainable alternative to conventional synthetic polymers. Although they are relatively widely studied, much less is known on particular genes coding enzymes for their synthesis, i.e., PHA synthases. So far, four different classes of PHA synthases have been defined. Not only has this classification become obsolete, but computational resources and databases like COG and KEGG do not respect it. Therefore, their correct identification is cumbersome. Moreover, additional knowledge on their transcriptional and posttranscriptional regulation or epigenetic modification is generally missing. During the last several years, we sequenced, assembled, and analysed various genomes of PHA-producing bacteria, e.g. Caldimonas thermodepolymerans, Caldimonas aquatica, Tepidimonas taiwanensis, Aneurinibacillus thermoaerophilus, and others [1-3]. In this study, we utilized third-generation sequencing data, particularly PacBio and Oxford Nanopore Technologies, to reveal genome-wide DNA methylation patterns in selected PHA-producing strains. Moreover, we identified differentially methylated positions in several strains under different cultivation conditions and matched them with PHA production gene machinery. In addition, we utilized our genome-wide transcriptomic studies performed with RNA-Seq, to infer gene regulatory mechanisms around PHA synthase in C. thermodepolymerans and predicted its possible posttranscriptional regulation by hitherto undefined small RNA. Similarly, we predicted many regulatory non-coding elements in Rhodospirillum rubrum, another potent and versatile PHA producer. Finally, we shifted our focus to bioinformatics database mining to understand how correct and unambiguous identification of PHA synthases could be performed. We analysed publicly available resources for functional annotation, particularly KEGG and COG, and proposed our initial dataset to correct limitations of current resources. As we show, this resource can be continuously updated while screening all currently available microbial genomes.

PolyHydroxyAlkanoates (PHA) are microbially produced polymers that could represent a sustainable alternative to conventional synthetic polymers. Although they are relatively widely studied, much less is known on particular genes coding enzymes for their synthesis, i.e., PHA synthases. So far, four different classes of PHA synthases have been defined. Not only has this classification become obsolete, but computational resources and databases like COG and KEGG do not respect it. Therefore, their correct identification is cumbersome. Moreover, additional knowledge on their transcriptional and posttranscriptional regulation or epigenetic modification is generally missing. During the last several years, we sequenced, assembled, and analysed various genomes of PHA-producing bacteria, e.g. Caldimonas thermodepolymerans, Caldimonas aquatica, Tepidimonas taiwanensis, Aneurinibacillus thermoaerophilus, and others [1-3]. In this study, we utilized third-generation sequencing data, particularly PacBio and Oxford Nanopore Technologies, to reveal genome-wide DNA methylation patterns in selected PHA-producing strains. Moreover, we identified differentially methylated positions in several strains under different cultivation conditions and matched them with PHA production gene machinery. In addition, we utilized our genome-wide transcriptomic studies performed with RNA-Seq, to infer gene regulatory mechanisms around PHA synthase in C. thermodepolymerans and predicted its possible posttranscriptional regulation by hitherto undefined small RNA. Similarly, we predicted many regulatory non-coding elements in Rhodospirillum rubrum, another potent and versatile PHA producer. Finally, we shifted our focus to bioinformatics database mining to understand how correct and unambiguous identification of PHA synthases could be performed. We analysed publicly available resources for functional annotation, particularly KEGG and COG, and proposed our initial dataset to correct limitations of current resources. As we show, this resource can be continuously updated while screening all currently available microbial genomes.

SEDLÁŘ, K.; BUCHTÍKOVÁ, I.; HEŘMÁNKOVÁ, K.; BEZDÍČEK, M.; UMAIR, M.; KOUŘILOVÁ, X.; ŠABATOVÁ, K.; MUSILOVÁ, J.; ŠLOSÁROVÁ, K.; OBRUČA, S.

01.10.2025

12th European Symposium on Biopolymers Book of Abstracts

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