2022
DOI: 10.1002/prot.26325
|View full text |Cite
|
Sign up to set email alerts
|

Plastics degradation by hydrolytic enzymes: The plastics‐active enzymes database—PAZy

Abstract: Petroleum-based plastics are durable and accumulate in all ecological niches. Knowledge on enzymatic degradation is sparse. Today, less than 50 verified plastics-active enzymes are known. First examples of enzymes acting on the polymers polyethylene terephthalate (PET) and polyurethane (PUR) have been reported together with a detailed biochemical and structural description. Furthermore, very few polyamide (PA) oligomer active enzymes are known. In this article, the current known enzymes acting on the synthetic… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

0
71
0

Year Published

2022
2022
2023
2023

Publication Types

Select...
7
1

Relationship

2
6

Authors

Journals

citations
Cited by 96 publications
(72 citation statements)
references
References 108 publications
(103 reference statements)
0
71
0
Order By: Relevance
“…Unfortunately, most of these labeled substrates are not yet commercially available. Finally, yet importantly, the development of bioinformatics tools and novel databases (e.g., PlasticDB, PMBD, and PAZy) ( 41 43 ) is crucial to identifying PDE from global metagenome/proteome data sets ( 20 ).…”
Section: Relevance Of and Interplay Between Plastics Enzymes And Asse...mentioning
confidence: 99%
“…Unfortunately, most of these labeled substrates are not yet commercially available. Finally, yet importantly, the development of bioinformatics tools and novel databases (e.g., PlasticDB, PMBD, and PAZy) ( 41 43 ) is crucial to identifying PDE from global metagenome/proteome data sets ( 20 ).…”
Section: Relevance Of and Interplay Between Plastics Enzymes And Asse...mentioning
confidence: 99%
“…An HMM constructed from all PET-degrading enzymes listed in the PAZy database 16 was used to search against NCBI's non-redundant protein database (ftp.ncbi.nlm.nih.gov/blast/db/FASTA/nr.gz) filtered for sequences of archaeal origin (tax ID: 2157) as described previously 13,23,32 .…”
Section: Profile Hidden-markov Model (Hmm) Searches Identify Putative...mentioning
confidence: 99%
“…Nevertheless, in recent years, several studies have identified microbial enzymes that are able to degrade some of these synthetic polymers, including PET, polyurethane (PUR), PA, and a few others from mainly renewable sources 13,15 . To date, approximately 120 enzymes have been described to act on these polymers (PAZy database 16 ), most of them being esterases, amidases, and oxygenases. Many of these proteins have relatively low conversion rates, show promiscuous activity or are only active on oligomers.…”
Section: Introductionmentioning
confidence: 99%
“…Quantification of plastic degradation and metaomics (metagenomics, metatranscriptomics, metaproteomics, and metabolomics) could be determined for these cultures in time-serial analysis for following microbial dynamics over polymer degradation. Through Hidden Markov Models (HMMs) and Basic Local Alignment Search Tools (BLAST), homology-based metagenomics identify putative degrading pathways or enzymes according to the similarity between query sequences and known sequences deposited in databases such as: MetaCyc and BioCyc ( Caspi et al, 2016 ), CAZy ( Cantarel et al, 2009 ), the University of Minnesota Biocatalysis/Biodegradation Database and Pathway Prediction System (UM-BBD/PPS; Gao et al, 2010 ), Biochemical Network Integrated Computational Explorer (BNICE.ch; Hatzimanikatis et al, 2005 ), KEGG ( Kanehisa et al, 2014 ), Plastics Microbial Biodegradation Database (PMBD; Gan and Zhang, 2019 ), and Plastics-Active Enzymes Database (PAZy; Buchholz et al, 2022 ). Such powerful method could reveal the phylogenetic distribution of plastic degraders across the microbial tree of life, highlighting the diversity and evolution of these traits ( Gambarini et al, 2021 ).…”
Section: What Biotechnology Could Learn From Insect Fungiculture?mentioning
confidence: 99%