Evidence map›Paper›PMID 26909078›Full record

ArticleFrontiers in microbiology2016

Development of Thermophilic Tailor-Made Enzyme Mixtures for the Bioconversion of Agricultural and Forest Residues.

Anthi Karnaouri, Leonidas Matsakas, Evangelos Topakas, Ulrika Rova, Paul Christakopoulos

Open access · goldAbstract read
In one paragraph

Article in Frontiers in microbiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
3.1field-weighted citation impact, top 9% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 35 citations in OpenAlex.

  1. Arginine-EnhancedFoods (Basel, Switzerland) · 2025
    Article
  2. Microbiology spectrum · 2024
    Article
  3. Review
  4. Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Recombinant expression of thermostable processiveBiotechnology for biofuels · 2017
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 1 institution in 2 countries.

Anthi KarnaouriBiochemical Process Engineering, Chemical Engineering, Department of Civil, Environmental and Natural Resources Engineering, Luleå University of Technology Luleå, Sweden.
Leonidas MatsakasBiochemical Process Engineering, Chemical Engineering, Department of Civil, Environmental and Natural Resources Engineering, Luleå University of Technology Luleå, Sweden.
Evangelos TopakasBiochemical Process Engineering, Chemical Engineering, Department of Civil, Environmental and Natural Resources Engineering, Luleå University of TechnologyLuleå, Sweden; Biotechnology Laboratory, Department of Synthesis and Development of Industrial Processes, School of Chemical Engineering, National Technical University of AthensAthens, Greece.
Ulrika RovaBiochemical Process Engineering, Chemical Engineering, Department of Civil, Environmental and Natural Resources Engineering, Luleå University of Technology Luleå, Sweden.
Paul ChristakopoulosBiochemical Process Engineering, Chemical Engineering, Department of Civil, Environmental and Natural Resources Engineering, Luleå University of Technology Luleå, Sweden.
Luleå University of Technology · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Even though the main components of all lignocellulosic feedstocks include cellulose, hemicellulose, as well as the protective lignin matrix, there are some differences in structure, such as in hardwoods and softwoods, which may influence the degradability of the materials. Under this view, various types of biomass might require a minimal set of enzymes that has to be tailor-made. Partially defined complex mixtures that are currently commercially used are not adapted to efficiently degrade different materials, so novel enzyme mixtures have to be customized. Development of these cocktails requires better knowledge about the specific activities involved, in order to optimize hydrolysis. The role of filamentous fungus Myceliophthora thermophila and its complete enzymatic repertoire for the bioconversion of complex carbohydrates has been widely proven. In this study, four core cellulases (MtCBH7, MtCBH6, MtEG5, and MtEG7), in the presence of other four "accessory" enzymes (mannanase, lytic polyssacharide monooxygenase MtGH61, xylanase, MtFae1a) and β-glucosidase MtBGL3, were tested as a nine-component cocktail against one model substrate (phosphoric acid swollen cellulose) and four hydrothermally pretreated natural substrates (wheat straw as an agricultural waste, birch, and spruce biomass, as forest residues). Synergistic interactions among different enzymes were determined using a suitable design of experiments methodology. The results suggest that for the hydrolysis of the pure substrate (PASC), high proportions of MtEG7 are needed for efficient yields. MtCBH7 and MtEG7 are enzymes of major importance during the hydrolysis of pretreated wheat straw, while MtCBH7 plays a crucial role in case of spruce. Cellobiohydrolases MtCBH6 and MtCBH7 act in combination and are key enzymes for the hydrolysis of the hardwood (birch). Optimum combinations were predicted from suitable statistical models which were able to further increase hydrolysis yields, suggesting that tailor-made enzyme mixtures targeted toward a particular residual biomass can help maximize hydrolysis yields. The present work demonstrates the change from "one cocktail for all" to "tailor-made cocktails" that are needed for the efficient saccharification of targeted feed stocks prior to the production of biobased products through the biorefinery concept.

Indexed as

enzyme mixtureexperimental designhydrolysisMyceliophthora thermophilathermostable enzymes

Identifiers

PMID26909078
PMCPMC4754399
OpenAlexW2278790473

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.