MCIC: Automated Identification of Cellulases From Metagenomic Data and Characterization Based on Temperature and pH Dependence

Shahraki, Mehdi Foroozandeh; Ariaeenejad, Shohreh; Atanaki, Fereshteh Fallah; Zolfaghari, Behrouz; Koshiba, Takeshi; Kavousi, Kaveh; Salekdeh, Ghasem Hosseini

doi:10.3389/fmicb.2020.567863

Cited by 21 publications

(7 citation statements)

References 56 publications

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“…Although in silico screening strategies for identifying novel enzymes are being used profitably, [31][32][33] automation of the selection of a limited number of promising hits for characterization is challenging.…”

Section: Discussionmentioning

confidence: 99%

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Functional Annotation of an Enzyme Family by Integrated Strategy Combining Bioinformatics with Microanalytical and Microfluidic Technologies

Vaňáček¹,

Vasina²,

Hon³

et al. 2021

Preprint

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<p>Next-generation sequencing technologies enable doubling of the genomic databases every 2.5 years. Collected sequences represent a rich source of novel biocatalysts. However, the rate of accumulation of sequence data exceeds the rate of functional studies, calling for acceleration and miniaturization of biochemical assays. Here, we present an integrated platform employing bioinformatics, <a></a><a>microanalytics, </a>and microfluidics and its application for exploration of unmapped sequence space, using haloalkane dehalogenases as model enzymes. First, we employed bioinformatic analysis for identification of 2,905 putative dehalogenases and rational selection of 45 representative enzymes. Second, we expressed and experimentally characterized 24 enzymes showing sufficient solubility for microanalytical and microfluidic testing. Miniaturization increased the throughput to 20,000 reactions per day with 1000-fold lower protein consumption compared to conventional assays. A single run of the platform doubled dehalogenation toolbox of family members characterized over three decades. Importantly, the dehalogenase activities of nearly one-third of these novel biocatalysts far exceed that of most published HLDs. Two enzymes showed unusually narrow substrate specificity, never before reported for this enzyme family. The strategy is generally applicable to other enzyme families, paving the way towards the acceleration of the process of identification of novel biocatalysts for industrial applications but also for the collection of homogenous data for machine learning. The automated <i>in silico</i> workflow has been released as a user-friendly web-tool EnzymeMiner: https://loschmidt.chemi.muni.cz/enzymeminer/.</p>

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Section: Discussionmentioning

confidence: 99%

“…Several sequence-based analysis tools have been developed for the prediction of key protein characteristics, e.g., thermostability, 34 optimum pH 31 or protein solubility. [35][36][37][38] Other computational tools help to analyze, filter and visualize the large sets of identified hits.…”

Section: Discussionmentioning

confidence: 99%

Functional Annotation of an Enzyme Family by Integrated Strategy Combining Bioinformatics with Microanalytical and Microfluidic Technologies

Vaňáček¹,

Vasina²,

Hon³

et al. 2021

Preprint

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“…Applying both the free and immobilized enzyme during the degradation of the rice straw in saline conditions leads to an increase in the production of reducing sugars [171]. In the field of microbial enzymes identification, more sophisticated, machine-learning-based tools were also developed, but they have not gained much popularity in halophilic research yet [173][174][175]. Most likely, it is related to the simplicity and clarity of the standard analytical pipelines.…”

Section: In Silico Methods For Identification Of Novel Halophiles Bioproductsmentioning

confidence: 99%

“…Limited customization options MCIC [174] FINDER [175] Ribosomally produced AMP Classic alignment-based approach DRAMP [176] The user is not limited by a predefined set of databases and comparison parameters Very flexible Any combination of databases for analysis can be selected Requires a combination of tools for the best effect In some cases a choice of optimal pipeline can be challenging Cannot identify the AMP types that are not included in the database CAMPR [177] LAMP [179] APD [178] Automated pipelines…”

Section: Automated Pipelinesmentioning

confidence: 99%

The Methods of Digging for “Gold” within the Salt: Characterization of Halophilic Prokaryotes and Identification of Their Valuable Biological Products Using Sequencing and Genome Mining Tools

Lach

Jecz

Strapagiel

et al. 2021

Genes

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Halophiles, the salt-loving organisms, have been investigated for at least a hundred years. They are found in all three domains of life, namely Archaea, Bacteria, and Eukarya, and occur in saline and hypersaline environments worldwide. They are already a valuable source of various biomolecules for biotechnological, pharmaceutical, cosmetological and industrial applications. In the present era of multidrug-resistant bacteria, cancer expansion, and extreme environmental pollution, the demand for new, effective compounds is higher and more urgent than ever before. Thus, the unique metabolism of halophilic microorganisms, their low nutritional requirements and their ability to adapt to harsh conditions (high salinity, high pressure and UV radiation, low oxygen concentration, hydrophobic conditions, extreme temperatures and pH, toxic compounds and heavy metals) make them promising candidates as a fruitful source of bioactive compounds. The main aim of this review is to highlight the nucleic acid sequencing experimental strategies used in halophile studies in concert with the presentation of recent examples of bioproducts and functions discovered in silico in the halophile’s genomes. We point out methodological gaps and solutions based on in silico methods that are helpful in the identification of valuable bioproducts synthesized by halophiles. We also show the potential of an increasing number of publicly available genomic and metagenomic data for halophilic organisms that can be analysed to identify such new bioproducts and their producers.

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“…From metagenome data, previous studies identified efficient high-potential glycoside hydrolases enzymes in lignocellulose-based industries ( Fatemeh et al, 2020 ; Maleki et al, 2020 ; Ariaeenejad et al, 2020b ; Motamedi et al, 2021a ; Ariaeenejad et al, 2021a ). Bioinformatics tools and computational methods are considered accessible and fast technological techniques for achieving new enzyme sequences ( Ariaeenejad et al, 2018 ; Foroozandeh Shahraki et al, 2020 , 2021 ).…”

Section: Introductionmentioning

confidence: 99%

Enhancing the ethanol production by exploiting a novel metagenomic-derived bifunctional xylanase/β-glucosidase enzyme with improved β-glucosidase activity by a nanocellulose carrier

Ariaeenejad

Motamedi²,

Kavousi³

et al. 2023

Front. Microbiol.

Self Cite

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Some enzymes can catalyze more than one chemical conversion for which they are physiologically specialized. This secondary function, which is called underground, promiscuous, metabolism, or cross activity, is recognized as a valuable feature and has received much attention for developing new catalytic functions in industrial applications. In this study, a novel bifunctional xylanase/β-glucosidase metagenomic-derived enzyme, PersiBGLXyn1, with underground β-glucosidase activity was mined by in-silico screening. Then, the corresponding gene was cloned, expressed and purified. The PersiBGLXyn1 improved the degradation efficiency of organic solvent pretreated coffee residue waste (CRW), and subsequently the production of bioethanol during a separate enzymatic hydrolysis and fermentation (SHF) process. After characterization, the enzyme was immobilized on a nanocellulose (NC) carrier generated from sugar beet pulp (SBP), which remarkably improved the underground activity of the enzyme up to four-fold at 80°C and up to two-fold at pH 4.0 compared to the free one. The immobilized PersiBGLXyn1 demonstrated 12 to 13-fold rise in half-life at 70 and 80°C for its underground activity. The amount of reducing sugar produced from enzymatic saccharification of the CRW was also enhanced from 12.97 g/l to 19.69 g/l by immobilization of the enzyme. Bioethanol production was 29.31 g/l for free enzyme after 72 h fermentation, while the immobilized PersiBGLXyn1 showed 51.47 g/l production titre. Overall, this study presented a cost-effective in-silico metagenomic approach to identify novel bifunctional xylanase/β-glucosidase enzyme with underground β-glucosidase activity. It also demonstrated the improved efficacy of the underground activities of the bifunctional enzyme as a promising alternative for fermentable sugars production and subsequent value-added products.

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MCIC: Automated Identification of Cellulases From Metagenomic Data and Characterization Based on Temperature and pH Dependence

Cited by 21 publications

References 56 publications

Functional Annotation of an Enzyme Family by Integrated Strategy Combining Bioinformatics with Microanalytical and Microfluidic Technologies

Functional Annotation of an Enzyme Family by Integrated Strategy Combining Bioinformatics with Microanalytical and Microfluidic Technologies

The Methods of Digging for “Gold” within the Salt: Characterization of Halophilic Prokaryotes and Identification of Their Valuable Biological Products Using Sequencing and Genome Mining Tools

Enhancing the ethanol production by exploiting a novel metagenomic-derived bifunctional xylanase/β-glucosidase enzyme with improved β-glucosidase activity by a nanocellulose carrier

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