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HADEG: A Curated Database of Hydrocarbon
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Aerobic Degradation Enzymes and Genes
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Jorge Rojas-Vargas1*, Hugo G. Castelán-Sánchez 2, Liliana Pardo-López1*
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1Departamento de Microbiología Molecular, Instituto de Biotecnología, UNAM, Av.
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Universidad #2001, Col. Chamilpa, 62210 Cuernavaca, Morelos, México
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2Programa de Investigadoras e Investigadores por México. Grupo de Genómica y Dinámica
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Evolutiva de Microorganismos Emergentes. Consejo Nacional de Ciencia y Tecnología. Av.
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Insurgentes Sur 1582, Crédito Constructor, Benito Juárez, CP 03940, Ciudad de México,
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México.
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* Correspondence:
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Liliana Pardo-López, liliana.pardo@ibt.unam.mx
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Jorge Rojas-Vargas, jorge.rojas@ibt.unam.mx
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ABSTRACT
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Databases of genes and enzymes involved in natural and synthetic hydrocarbon degradation
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have been previously reported. However, these databases specialize on only a specific group
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of hydrocarbons and/or are constructed partly based on enzyme sequences with putative
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functions indicated by in silico research, with no experimental evidence. Here, we present a
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curated database of Hydrocarbon Aerobic Degradation Enzymes and Genes (HADEG)
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containing enzymes and genes involved in alkane, alkene, aromatic, and polymer aerobic
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degradation and biosurfactant production based solely on experimental evidence. HADEG
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includes 259 enzymes for petroleum hydrocarbon degradation, 160 for polymer degradation,
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and 32 for biosurfactant production. This database will help identify and predict hydrocarbon
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degradation genes/pathways and biosurfactant production in genomes.
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Keywords
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Curated database, hydrocarbon degradation, polymer degradation, biosurfactant production.
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Impact statement
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There is currently no database that integrates enzymes and genes with experimental evidence
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related to the degradation of different hydrocarbon groups (alkanes, alkenes, aromatics,
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polymers) or the production of biosurfactants. HADEG is an effort to assemble a single
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database of enzymes and gene sequences of the aforementioned groups. This database will
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be helpful for more fully predicting the potential degradation of microorganism genomes (or
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metagenomes), thus increasing knowledge about the biology of microbes that metabolize
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pollutants. Our findings from HADEG also shed light on the identification of a set of possible
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biomarkers for targeted searching of promising hydrocarbon-degrading microorganisms.
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Data summary
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The HADEG database repository is https://github.com/jarojasva/HADEG.
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.CC-BY-NC-ND 4.0 International licenseperpetuity. It is made available under a
preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in
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2
1 Introduction
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Crude oil spills and plastic pollution of anthropogenic origin are two major concerns in the
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context of environmental equilibrium and conservation (Bhattacharjee & Dutta, 2022; Horton,
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2022). Bioremediation technologies remain one of the most promising options for crude oil
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and plastic cleanup, based on microorganisms that can use hydrocarbons (HCs) and polymers
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as carbon sources. Interest in bioremediation has led to the identification and characterization
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of some enzymes involved in degradation processes. Among the features of these enzymes,
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studies have described their activity conditions, substrates, and products, in addition to their
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protein structures and active sites in some cases (Brzeszcz & Kaszycki, 2018; Kaushal et al.,
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2021; Pathak et al., 2022; Xu et al., 2018). Enzymes for biosurfactant production have also
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been studied; these microbial surface-active compounds increase the bioavailability of HCs
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and therefore promote higher levels of HC degradation (Banat, 1995).
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Advances in sequencing technologies have allowed the nucleotide sequences of
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hydrocarbon-degrading genes and, thus, the amino acid sequences of the encoded proteins
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to be obtained. Some of these sequences can be found in existing tailored data repositories
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and can be used to identify and predict the degradation potential of microbial genomes and
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metagenomes. Regarding hydrocarbon degradation, the AromaDeg database is focused on
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the aerobic degradation of aromatic compounds. It was constructed based on a phylogenomic
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approach considering different oxygenases with known and unknown aromatic substrates
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(Duarte et al., 2014). A more recent database is that of the Calgary approach to ANnoTating
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HYDrocarbon degradation genes (CANT-HYD), which contains genes involved in aerobic and
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anaerobic aliphatic and aromatic hydrocarbon degradation pathways. CANT-HYD uses
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Hidden Markov Models (HMMs) for the annotation of six monophyletic clades of genes related
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to aliphatic aerobic degradation (alkB, almA, ladA, bmo, CYP153, prm), six related to
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aromatics (dmp, dsz, MAH, ndo, tmo, tom), and eight related to anaerobic pathways (Khot et
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al., 2021). The workflow derives 37 HMMs from experimental and in silico-inferred functional
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enzymes and is designed for the identification and annotation of marker genes, not including
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some pathways of hydrocarbon degradation.
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For polymers, the Plastics Microbial Biodegradation Database (PMBD) (http://pmbd.genome-
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mining.cn/home/) is an online resource containing 79 experimentally predicted and ~8000 in
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silico-predicted sequences of enzymes from the literature and the UniProt database (Gan &
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Zhang, 2019). The Plastics-Active Enzymes Database (PAZy) is an inventory of enzymes that
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act on only four synthetic fossil fuel-based polymers and three polymers mainly found in
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renewable resources (Buchholz et al., 2022). Additionally, PlasticDB (Gambarini et al., 2022)
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includes 174 experimentally tested enzymes (consulted on July 15, 2022) related to the
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degradation of seven natural and twenty synthetic polymers. Regarding biosurfactants, the
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only reported database for these compounds is BioSurfDB (www.biosurfdb.org) (Oliveira et
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al., 2015), which includes experimental and predicted enzymes.
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Here, we introduce the manually curated database of Hydrocarbon Aerobic Degradation
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Enzymes and Genes (HADEG), which is a public repository containing sequences of
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experimentally characterized enzymes and genes to be used for annotation purposes. HADEG
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groups these molecules according to their substrates (in the case of alkane, alkene, aromatic,
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and polymer aerobic degradation) and products (in the case of biosurfactant production). In
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this work, we also briefly reviewed the enzymes and pathways involved in petroleum
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hydrocarbon and polymer degradation.
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2 Materials and methods
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2.1 Selection of reference sequences
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For enzymes involved in alkane, alkene, and aromatic aerobic degradation, we compiled and
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classified metabolic pathways from the primary literature and two experimentally validated
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curated databases, MetaCyc (Krieger et al., 2004) and KEGG (Ogata et al., 1999). We
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searched the sequences of enzymes and genes involved in the aforementioned metabolic
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pathways in the well-characterized UniProtKB/Swiss-Prot database (Boutet et al., 2007), the
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NCBI portal, and in the literature if sequences were not available in any database
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(Supplementary Tables 1, 2, and 3).
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To obtain polymer degradation enzymes, we selected nonredundant protein sequences from
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PlasticDB (Gambarini et al., 2022). To obtain biosurfactant production enzymes, we used the
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UniProt platform with different biosurfactants as keywords, and the corresponding proteins
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included in the UniProtKB/Swiss-Prot database were collected. In constructing our polymer
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and biosurfactant database, we added some new proteins from a search of the primary
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literature (Supplementary Tables 4 and 5). The nucleotide sequences of all proteins were
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retrieved from the European Nucleotide Archive (ENA) platform (Leinonen et al., 2011) or the
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literature.
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2.2 Protein annotation and orthology
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We used eggNOG-mapper (Huerta-Cepas et al., 2019) online version 2.1.9, run on July 23
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(2022), to annotate our protein database, identify orthologs, and study their taxonomic
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distribution at the phylum level. Protein sequences without orthologs were considered seed
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sequences (Supplementary Table 6). We used InterProScan v.5.51-85.0 (Jones et al., 2014)
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for protein domain inference with the default parameters to identify the shared protein domains
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predicted with Pfam-33.1 (Supplementary Table 7).
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2.3 Searching for hydrocarbon degradation enzymes in genomes using
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HADEG
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We selected 60 genomes (Supplementary Table 8) of recognized HC- and plastic-degrading
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microorganisms and biosurfactant producers for validation purposes. The protein FASTA files
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were retrieved from the NCBI web portal (consulted on July 1, 2022). BLAST software
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(McGinnis & Madden, 2004) was used to predict enzymes by applying the following cutoff
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values: 50 for the percentage of identity, 1x10-60 for the e-value, ±10% of the variation in the
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query sequences, and the higher bit score, using the protein FASTA files from our database.
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3 Results and discussion
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3.1 Hydrocarbon aerobic degradation
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HCs are relatively stable molecules but can serve as a source of carbon and energy for any
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organism able to activate them. This activation by the aerobic insertion of oxygen or the
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anaerobic addition of succinate distinguishes hydrocarbon-degrading organisms from their
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counterparts (Prince et al., 2010). In HADEG, we included enzymes related to aerobic HC
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degradation, such as alkanes, alkenes, aromatics, and polymers (Supplementary Tables 1-4).
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3.1.1 Alkanes
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Alkanes are the principal components of crude oil. Four microbial pathways of alkane
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degradation have been identified (Fig. 1) (Ji et al., 2013; Moreno & Rojo, 2019; Wentzel et al.,
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2007). All of them begin with the activation of the alkane chain through its oxidation to a
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primary or secondary alcohol, as observed in terminal (TO), biterminal (BO), and subterminal
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oxidation (SO), or to an n-alkyl hydroperoxide via the Finnerty pathway (FP). Among the
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activation enzymes included in HADEG, we report the extensively studied alkane
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monooxygenase (alkB), cytochrome P153 (CYP153), and P450 (CYP450), flavin-binding
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protein monooxygenase (almA), long-chain alkane monooxygenase (ladA), and terminal
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alkane-hydroxylase (alkM). The rubredoxins (rubA, rubB), which play a crucial role in electron
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transfer to alkB, are also included. Some other included enzymes belong to a particular
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pathway, such as Baeyer-Villiger monooxygenase (BVMO) in SO and alkyl hydroperoxide
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reductase (ahpCF) in FP. Enzymes with specific substrates, such as methane
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monooxygenase (pmoA), propane 2-monooxygenase (prm), and butane monooxygenase
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hydroxylase (bmo), are also included in HADEG.
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Some other enzymes included in HADEG are alcohol and aldehyde dehydrogenases (adh,
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ald), cyclohexanone 1,2-monooxygenase (CHMO), alkanesulfonate monooxygenase (ssuD),
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the helix-turn-helix transcriptional regulator of alkB (alkS), and enzymes related to the uptake
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of alkanes, such as an outer membrane protein (alkL), an outer membrane lipoprotein (blc),
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long-chain fatty acid transport enzyme (fadL), and a methyl-accepting chemotaxis protein
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(alkN or mcp).
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3.1.2 Alkenes
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Alkenes are transformed into corresponding epoxides by an alkene monooxygenase.
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Epoxides are somewhat toxic to cells but can be processed using epoxide hydrolases, such
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as the enzyme epoxyalkane CoM transferase, and their products ultimately enter the central
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metabolism. HADEG includes the alkene monooxygenase complex (amoABCD) identified in
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Nocardia corallina B-276, isoprene monooxygenase (isoABCDEHI) from Rhodococcus sp.
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AD45, the propene monooxygenase system (xamoABCDE) and epoxyalkane CoM system
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(xecADC) from Xanthobacter autotrophicus Py2, the epoxyalkane CoM (etnE) from
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Mycolicibacterium rhodesiae, and the dehydrogenase mpdBC from M. austroafricanum.
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3.1.3 Aromatics
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Aromatic compounds are commonly known as recalcitrant pollutants because they show
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relatively low susceptibility to microbial degradation (Ghosal et al., 2016). Some also represent
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mutagenic and carcinogenic risks to human health. In contrast to alkanes and alkenes,
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aromatic compound degradation requires complex metabolic machinery. In general, aerobic
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organisms take advantage of the availability of molecular oxygen and use oxygenases that
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introduce hydroxyl groups and cleave aromatic rings. These pathways usually involved a few
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central intermediates, most commonly including catechol, protocatechuate, and gentisate
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(Phale et al., 2020).
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The goal of enzymatic degradation is the activation and cleavage of aromatic rings to obtain
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products that can subsequently be integrated into central pathways. Our research included
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pathways with characterized enzymes involved in the metabolic processes of poly- and
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monoaromatic degradation. Regarding polyaromatic degradation pathways, HADEG includes
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enzymes involved in the degradation of anthracene, biphenyl, dibenzothiophene, fluorene,
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naphthalene, and phenanthrene. Pyrene degradation involves pyrene dioxygenases, but none
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of these enzymes had been experimentally characterized when this manuscript was written,
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although their activity has been inferred in Pseudomonas sp. Jpyr-1 and Mycolicibacterium
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sp. 16F. Nevertheless, cytochrome P450 monooxygenase (CYP450), which is involved in
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alkane degradation, seems to participate in pyrene degradation in Roseobacter (Zhou et al.,
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2020). Regarding monoaromatic degradation pathways, we included enzymes involved in the
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degradation of benzene, toluene, xylene (BTX), anthranilate, benzoate, 2-nitrobenzoate,
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catechol (ortho- and meta-cleavage pathways), gentisate, phenol, phenylacetate, phthalate,
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protocatechuate (ortho- and meta-cleavage pathways), salicylate, styrene, and terephthalate.
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3.1.4 Polymers
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Enzymes involved in the degradation of polymers were also added to the HADEG database,
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since polymers are important environmental contaminants, and it has been reported that some
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microorganisms can degrade them (Kaushal et al., 2021). Polymers can be classified
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according to their origin into natural or synthetic polymers. Natural polymers, also known as
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biopolymers, are derived from plants, animals, and microorganisms, are degradable and
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environmentally sensitive, and have been studied for potential medical and engineering
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applications (Kumbar et al., 2014; Shrivastava, 2018; Swain & Jawaid, 2019; Wagner et al.,
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2020); (Garcia-Gareta, 2019). Some natural polymers are essential for life, such as
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polysaccharides (e.g., cellulose, pectin, chitin, and alginic acid), polypeptides (e.g., proteins),
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and polynucleotides (e.g., DNA). On the other hand, synthetic or man-made polymers are
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obtained in the laboratory (Saldívar-Guerra & Vivaldo-Lima, 2013), and they can have an
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organic or inorganic backbone (Zainudin et al., 2020). They are commonly derived from
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petroleum (e.g., polyethylene terephthalate-PET, polyurethane-PU, polyvinyl chloride-PVC,
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polystyrene-PS, and polypropylene-PP) and have many applications (Shrivastava, 2018).
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Most of them are very difficult to degrade due to inherent characteristics such as high
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molecular weights, crystallinity, and hydrophobicity (Amobonye et al., 2021; Geyer, 2020). In
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this context, microorganisms with the capacity for polymer degradation remain one of the most
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promising options for the reduction or recycling of synthetic polymers with long lifetimes
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(Muriel-Millán et al., 2021).
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The polymer degradation process begins with the superficial deterioration and subsequent
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cleavage of polymers into intermediates, which can be used as energy and carbon sources.
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The depolymerization process mainly involves the hydrolytic cleavage of glycosidic, ester, and
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peptide bonds, resulting in constituent oligomers or monomers (Amobonye et al., 2021).
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Implementing physicochemical pretreatments such as the application of chemical additives or
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UV irradiation can facilitate microbial polymer degradation (Ru et al., 2020).
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Among the polymer enzymes included in HADEG, there are some hydrolases for PET
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degradation, such as the recently well-characterized polyester hydrolase of
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Halopseudomonas aestusnigri VXGO4 (6SCD PDB), one hydrolase from a marine
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metagenome (Hajighasemi et al., 2018), a lacasse of Rhodococcus ruber C208, and some
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6
cutinases. These enzymes also include PVA dehydrogenase (pvaA, pvaB) for polyvinyl
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alcohol (PVA) degradation (Shimao, 2001); exo-cleaving and endo-cleaving rubber
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dioxygenases (roxA, roxB) for natural rubber degradation from Xanthomonas sp. 35Y;
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polyurethanases (pueA, pueB) for PU degradation from Pseudomonas choloraphis and
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Pseudomonas protegens Pf-5; manganese peroxidase 1 (mnp1) for polyethylene degradation
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from Phanerodontia chrysosporium; and a cutinase for poly(epsilon-caprolactone) (PCL) and
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poly(1,3-propylene adipate) (PPA) degradation from Kineococcus radiotolerans DSM 14245.
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3.2 Biosurfactant production
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The first step in HC degradation is accessing the molecules. Short-chain alkanes of less than
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9 carbons are soluble enough to be transported into cells (Moreno & Rojo, 2017; Wang &
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Shao, 2013) Alkanes of greater length require cell adhesion to crude oil droplets, as is the
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case in Acinetobacter, which uses adhesion protein filaments (fimbriae) or the action of
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biosurfactants (Baldi et al., 1999). Biosurfactants increase the bioavailability of HCs (Patowary
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et al., 2016), and it is speculated that once they are excreted, they cannot enter cells (Wang
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& Shao, 2013). Some microorganisms capable of degrading HCs secrete biosurfactants of a
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different nature, such as lipoproteins or rhamnolipids, to emulsify HCs. Biosurfactants have
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also been associated with viral factors (Sharma et al., 2021).
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The HADEG database includes the enzymes involved in the production of fengycin (ffp),
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plipastatin (ppsABCDE), surfactin (srf), iturin (itu), and mycosubtilin (mycABC) in Bacillus
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subtilis. Additionally, enzymes related to rhamnolipids (rhl) from Pseudomonas aeruginosa;
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emulsan from Acinetobacter lwoffii RAG-1 (wzb, wzc); arthrofactin (arfABC) from
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Pseudomonas sp. MIS38; amphisin (amsY) from Pseudomonas sp. DSS73; serrawetin
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(pswP) in Serratia marcescens; and lactonic sophorose lipid (sble), and sophorolipids (at) from
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Starmerella bombicola are also included. Two fungal biosurfactants are also included;
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mannosylerythritol lipids (emt1) from Ustilago maydis and hydrophobin (hfb1, hfb2) from
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Hypocrea jecorina.
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3.3 Taxonomic distribution of orthologs in the HADEG database
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Among the proteins present in HADEG, a search for orthologs was carried out to determine
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their distribution in different microorganisms and their taxonomic assignment. We used
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eggNOG-mapper to identify 19,749 orthologs of 445 protein sequences among the 451
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sequences included in HADEG (Supplementary Table 6). The six proteins without identified
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orthologs were the PBAT esterase of an uncultured bacterium (accession no. A0A1C9T7G6),
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the PVA hydrolase of Sphingomonas sp. (accession no. Q588Z2, oph), the butane
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monooxygenase hydroxylase gamma subunit of Thauera butanivorans (a.n. Q8KQE7, bmoZ),
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the fluoren-9-ol dehydrogenase of Terrabacter sp. DBF63 (a.n. Q93UV4, flnB), the oxidized
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PVA hydrolase of Pseudomonas sp. (a.n. Q9LCQ7, pvaB), and the anthranilate-CoA ligase of
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Rhodococcus erythropolis (a.n. S6BVH5, rauF).
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The taxonomic analysis of orthologs at the phylum level revealed that Proteobacteria was the
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most abundant phylum related to HC degradation pathways and biosurfactant production
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(forest-green color in Fig. 2A). Many studies have confirmed the degradation capacities of
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species in genera such as Alcanivorax and Marinobacter (hydrocarbonoclastics),
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Acinetobacter (versatile HC degraders), and ubiquitous Pseudomonas. Biosurfactants such
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as amphisin, arthrobactin, emulsan and serrawetin have only been described in
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Proteobacteria (Soberón-Chávez, 2010), and rhamnolipid production mechanisms have been
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well described in Pseudomonas (Soberón-Chávez et al., 2021) (Fig. 2B). Actinobacteria was
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the second most abundant phylum related to HC degradation pathways (goldenrod color in
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Fig. 2), and it includes the hydrocarbon-degrading genera Rhodococcus, Mycobacterium,
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Norcadia, Gordonia, and Streptomyces, among others. Firmicutes was the third most
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abundant phylum related to HC pathways and the second most abundant related to
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biosurfactant production (Bacillus, Geobacillus, and Paenibacillus) (royal blue color in Fig. 2),
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within which surfactin and iturin production by Bacillus genus members has been well studied
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(Soberón-Chávez, 2010). In the Bacteria domain, the fourth most abundant phylum was
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Bacteroidetes (Aequorivita, Algoriphagus, Cytophaga), particularly related to alkene
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degradation (orange color in Fig. 2). Ascomycota was the most abundant phylum from the
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fungal domain and was mainly associated with alkane and polymer degradation and
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biosurfactant production (brick color in Fig. 2). Fungi have received interest in relation to
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bioremediation applications because they do not rely solely on soluble organic compounds for
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nutrition; they also show diverse enzymatic mechanisms and distinct mechanisms of
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physiological adaptability to environmental conditions (Prenafeta-Boldú et al., 2018).
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3.4 HADEG Pfams network
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A network analysis was performed to determine whether the HADEG proteins shared
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domains, which may indicate that a protein could participate in the degradation of more than
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one type of HC (Fig. 3). Identifying the shared and nonshared protein domains between
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hydrocarbon degradation groups will be helpful to establish a set of biomarkers for the targeted
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searching of potential hydrocarbon-degrading microorganisms. A total of 166 Pfam domains
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were identified in HADEG (Supplementary Table 7). Network analyses reveal that the polymer
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and aromatic degradation groups contained the largest numbers of protein domains, at 75 and
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48, respectively. These results are congruent with the diversity and complexity of aromatic
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and polymeric chemical structures. On the other hand, we predicted 30 Pfams among
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biosurfactants, 28 among alkanes, and 18 among alkenes.
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Among the protein domains without connectivity or nonshared protein domains, the alkane set
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included 16 Pfams such as the related to rubredoxin proteins (PF00301 and PF18113) and a
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flavin-binding monooxygenase-like protein (PF00743) in almA and BVMO. The alkene set
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included four Pfams with no connectivity: cobalamin-independent synthase (PF01717) in etnE,
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a glutathione S-transferase C-terminal domain (PF17171 and PF17172) in isoI, and a pyridine
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nucleotide-disulfide oxidoreductase dimerization domain (PF02852) in xecC. The aromatic set
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included 57 nonshared Pfams like the ring-hydroxylating alpha and beta subunits (PF00848
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and PF00866) present in aromatic-ring dioxygenase systems, the dioxygenase superfamily
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(PF00903), and the catechol dioxygenase N-terminus (PF04444). The polymer set included
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42 nonshared protein domains like the RTX calcium-binding nonapeptide repeat 4 copies
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(PF00353) present in the polyester polyurethanases pueA and pueB, the alpha/beta hydrolase
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family (PF12695) involved in PET degradation, the esterase PHB depolymerase (PF10503)
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involved in PHA/PHB degradation and a cutinase (PF01083) that acts on carboxylic ester
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bonds. Finally, the biosurfactant set included 26 nonshared Pfams like a condensation domain
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(PF00668) present in Bacillus biosurfactants synthesis proteins (iturin, mycosubtilin, surfactin,
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and plipastatin), the 4’-phosphopantetheinyl transferase superfamily (PF01648) in ffp, pswP
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and sfp, and helicase domains (PF00270 and PF00271) in rhlB and (PF13641) in rhlC, both
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involved in rhamnolipids production.
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Concerning the protein domains that were connected in the network or shared, only the
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aldehyde dehydrogenase family (PF00171) participates in the degradation of the four HC
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groups. This domain is responsible for the oxidation of aldehydes, which is considered a
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detoxification reaction (Pfam: Family: Aldedh (PF00171), n.d.). The largest set of shared
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domains was found between alkenes and aromatics, which shared 19 Pfams. These domains
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included the Rieske [2Fe-2S] domain (PF00355), which is involved in the electron transfer
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chain. PF00355 was present in enzymes such as andA, benA, doxAB, ndoAB, tmoC, todB,
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bedB, isoC, and xamoC. The alkane, alkene and aromatic groups shared seven Pfam
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domains, including the oxidoreductase NAD-binding and FAD-binding domains (PF00175 and
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PF00970), present in prmB, isoF, xamoF, benC, and tmoF; the methane/phenol/toluene
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hydroxylase domains (PF02332), found in bmoX, xamoA, and tmoA; and the MmoB/DmpM
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family (PF02406), found in prmD, xamoD, and tmoD. The alkane and aromatic groups shared
304
a fatty acid desaturase domain (PF00487) that catalyzes the insertion of a double bond at the
305
delta position in fatty acids (Pfam: Family: FA_desaturase (PF00487), n.d.). This domain is
306
present in alkane monooxygenases (alkB), alkane hydroxylases (alkMa, alkMb), and xylene
307
monooxygenase subunit 1 (xylM).
308
3.5 Hydrocarbon degradation enzymes in different genomes
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One way to use this database could be to identify hydrocarbon degradation genes in different
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genomes based on homology through BLAST searches, although other methods can be used
311
for this purpose. To this end, a BLAST comparison was conducted using the amino acid
312
sequences of HADEG against 60 genomes with previously proven hydrocarbon degradation
313
and/or biosurfactant production activity. The results of this comparison showed that 53 of 60
314
genomes presented experimentally verified hydrocarbon degradation genes; thus, the data
315
were consistent with previous reports (Fig. 4). Among the remaining 7 genomes, three
316
exhibited experimental evidence hits with a percentage of identity between 44% and 49%,
317
which was below the cutoff (50%). This was the case for the BVMO gene of Thalassolituus
318
oleivorans MIL-1 involved in the SO pathway, pegAC of Sphingopyxis macrogoltabida 203
319
involved in polyethylene glycol degradation, and rhlABC of Burkholderia thailandensis E264
320
involved in rhamnolipid synthesis. Although genomes (11, 28, 42, and 50) showed some hits
321
against the HADEG database, they did not show matches with any genes or substrates with
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previously reported experimental results. These genomes likely include other potential
323
pathways that are not covered in the HADEG database.
324
Additionally, it was possible to identify unreported hydrocarbon degradation and biosurfactant
325
production capabilities in 59 genomes with HADEG. Many of these genomes included genes
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for the degradation of aliphatic and aromatic HCs and polymers and the production of multiple
327
biosurfactants on the same chromosome. The occurrence of these numerous pathways might
328
be due to microbial environmental adaptations and be widely observed within the bacterial
329
world (Brzeszcz & Kaszycki, 2018). However, empirical evidence indicates that microbes show
330
metabolic pathway preferences (Brzeszcz & Kaszycki, 2018). The concordance with
331
experimental evidence and the predicted pathway repertoire show that the HADEG database
332
is a reliable resource for identifying and predicting hydrocarbon degradation pathways and
333
biosurfactant production in genomes.
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.CC-BY-NC-ND 4.0 International licenseperpetuity. It is made available under a
preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in
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9
4 Conclusions
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The HADEG database is a bioinformatic resource that can be used to identify potential
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microorganisms for developing HC-bioremediation methods. To the best of our knowledge,
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HADEG, which contains 451 experimentally verified proteins, is the first database to integrate
338
different types of HCs (alkane, alkenes, aromatics, and polymers) and biosurfactants in a
339
single resource. Through ortholog analysis, we found that the HADEG proteins are distributed
340
in bacteria and fungi and that they are most highly represented in Proteobacteria. Additionally,
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Pfam analysis showed that the domains of the HC degradation proteins correspond primarily
342
to polymers and aromatics. Most domains are not shared among HC groups, indicating that
343
their functions are HC-degradation-specific and that they can probably be used as biomarkers
344
for the identification of microbes with degradation abilities. Finally, we show that HADEG is a
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reliable tool for annotating HC degradation and biosurfactant production proteins.
346
Author contributions
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JR-V conceived the initial study. JR-V and HGC-S designed the experiments and analyzed
348
the data. JR-V, HGC-S, and LP-L contributed to the interpretation and discussion of the
349
results. LP-L provided financial support. All authors contributed to the writing of the manuscript
350
and approved the final version.
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Funding
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Jorge Rojas-Vargas is a doctoral student from Programa de Doctorado en Ciencias
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Bioquímicas, Universidad Nacional Autónoma de México (UNAM), and received fellowship
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965003 from the Consejo Nacional de Ciencia y Tecnología (CONACYT). Liliana Pardo-Lopez
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received financial support from PASPA DGAPA-UNAM for a sabbatical year.
356
Acknowledgments
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We thank the Unidad de Secuenciación Masiva y Bioinformática del Instituto de Biotecnología-
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UNAM for giving us access to its computer cluster.
359
Conflict of interest
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The authors declare that there are no conflicts of interest.
361
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Fig. 1. Alkane aerobic degradation pathways. A. Terminal oxidation (black color). B. Biterminal
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oxidation (blue). C. Subterminal oxidation (green). D. Finnerty pathway (red).
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A
536
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B
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Fig. 2. Taxonomic distribution of enzyme orthologs obtained with eggNOG-Mapper. A.
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Hydrocarbon groups. B. Degradation pathways. A_alkane groups, B_alkenes, C_aromatics,
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D_polymers, E_biosrufactants.
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preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in
The copyright holder for thisthis version posted September 1, 2022. ; https://doi.org/10.1101/2022.08.30.505856doi: bioRxiv preprint
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546
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Fig. 3. HADEG Pfam network. Hydrocarbon degradation groups and biosurfactant production
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are represented by squared: alkanes (red), alkenes (magenta), aromatics (yellow), polymers
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(orange), and biosurfactants (blue). Pfams are represented by circles, and the color
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convention is as described above. The shared protein domains among groups are shown on
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green scale. The list of the Pfams is shown in Supplementary Table 7.
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.CC-BY-NC-ND 4.0 International licenseperpetuity. It is made available under a
preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in
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Fig. 4. BLAST annotation of genomes with the HADEG database and experimentally validated
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activities. The corresponding hydrocarbon groups are used to organize both the genomes (x-
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axis) and the HADEG pathways (y-axis). Bubble indicates hits above the confidence threshold.
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The hits with experimental evidence are shown in black, and the predicted hits are shown in
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gray. The number of hits in the genome is indicated by the size of the bubble. Supplementary
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Table 8 contains a complete list of isolated genomes and their accession numbers.
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A
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B
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Supplementary Fig. 1. Orthologous proteins obtained with eggNOG-mapper. A. Hydrocarbon
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groups. B. Degradation pathways. A_alkane groups, B_alkenes, C_aromatics, D_polymers,
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E_biosrufactants.
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preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in
The copyright holder for thisthis version posted September 1, 2022. ; https://doi.org/10.1101/2022.08.30.505856doi: bioRxiv preprint
