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Twitter Demographics
Mendeley readers
Attention Score in Context
| Title |
Boosting LPMO-driven lignocellulose degradation by polyphenol oxidase-activated lignin building blocks
|
|---|---|
| Published in |
Biotechnology for Biofuels and Bioproducts, May 2017
|
| DOI | 10.1186/s13068-017-0810-4 |
| Pubmed ID | |
| Authors |
Matthias Frommhagen, Sumanth Kumar Mutte, Adrie H. Westphal, Martijn J. Koetsier, Sandra W. A. Hinz, Jaap Visser, Jean-Paul Vincken, Dolf Weijers, Willem J. H. van Berkel, Harry Gruppen, Mirjam A. Kabel |
| Abstract |
Many fungi boost the deconstruction of lignocellulosic plant biomass via oxidation using lytic polysaccharide monooxygenases (LPMOs). The application of LPMOs is expected to contribute to ecologically friendly conversion of biomass into fuels and chemicals. Moreover, applications of LPMO-modified cellulose-based products may be envisaged within the food or material industry. Here, we show an up to 75-fold improvement in LPMO-driven cellulose degradation using polyphenol oxidase-activated lignin building blocks. This concerted enzymatic process involves the initial conversion of monophenols into diphenols by the polyphenol oxidase MtPPO7 from Myceliophthora thermophila C1 and the subsequent oxidation of cellulose by MtLPMO9B. Interestingly, MtPPO7 shows preference towards lignin-derived methoxylated monophenols. Sequence analysis of genomes of 336 Ascomycota and 208 Basidiomycota reveals a high correlation between MtPPO7 and AA9 LPMO genes. The activity towards methoxylated phenolic compounds distinguishes MtPPO7 from well-known PPOs, such as tyrosinases, and ensures that MtPPO7 is an excellent redox partner of LPMOs. The correlation between MtPPO7 and AA9 LPMO genes is indicative for the importance of the coupled action of different monooxygenases in the concerted degradation of lignocellulosic biomass. These results will contribute to a better understanding in both lignin deconstruction and enzymatic lignocellulose oxidation and potentially improve the exploration of eco-friendly routes for biomass utilization in a circular economy. |
Twitter Demographics
The data shown below were collected from the profiles of 3 tweeters who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 3 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 177 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Thailand | 1 | <1% |
| Unknown | 176 | 99% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 38 | 21% |
| Researcher | 30 | 17% |
| Student > Master | 28 | 16% |
| Student > Bachelor | 14 | 8% |
| Professor > Associate Professor | 11 | 6% |
| Other | 32 | 18% |
| Unknown | 24 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 45 | 25% |
| Agricultural and Biological Sciences | 30 | 17% |
| Chemistry | 16 | 9% |
| Engineering | 15 | 8% |
| Unspecified | 7 | 4% |
| Other | 23 | 13% |
| Unknown | 41 | 23% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 16 August 2017.
All research outputs
#14,558,031
of 23,314,015 outputs
Outputs from Biotechnology for Biofuels and Bioproducts
#804
of 1,468 outputs
Outputs of similar age
#174,725
of 311,625 outputs
Outputs of similar age from Biotechnology for Biofuels and Bioproducts
#35
of 62 outputs
Altmetric has tracked 23,314,015 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,468 research outputs from this source. They receive a mean Attention Score of 4.8. This one is in the 42nd percentile – i.e., 42% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 311,625 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 62 others from the same source and published within six weeks on either side of this one. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.