Evidence map›Paper›PMID 31956399›Full record

ArticleF1000Research2019

Profile Comparer Extended: phylogeny of lytic polysaccharide monooxygenase families using profile hidden Markov model alignments.

Gerben P Voshol, Peter J Punt, Erik Vijgenboom

Open access · goldAbstract read
In one paragraph

Article in F1000Research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.5field-weighted citation impact, top 35% 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

7 citing papers in PubMed, 11 citations in OpenAlex.

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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

3 authors.

Gerben P VosholDepartment of Microbial Biotechnology and Health, Insitute of Biology Leiden, Leiden, 2333BE, The Netherlands.
Peter J PuntDepartment of Microbial Biotechnology and Health, Insitute of Biology Leiden, Leiden, 2333BE, The Netherlands.
Erik VijgenboomDepartment of Microbial Biotechnology and Health, Insitute of Biology Leiden, Leiden, 2333BE, The Netherlands.ORCID 0000-0002-5059-069X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Insight into the inter- and intra-family relationship of protein families is important, since it can aid understanding of substrate specificity evolution and assign putative functions to proteins with unknown function. To study both these inter- and intra-family relationships, the ability to build phylogenetic trees using the most sensitive sequence similarity search methods (e.g. profile hidden Markov model (pHMM)-pHMM alignments) is required. However, existing solutions require a very long calculation time to obtain the phylogenetic tree. Therefore, a faster protocol is required to make this approach efficient for research. To contribute to this goal, we extended the original Profile Comparer program (PRC) for the construction of large pHMM phylogenetic trees at speeds several orders of magnitude faster compared to pHMM-tree. As an example, PRC Extended (PRCx) was used to study the phylogeny of over 10,000 sequences of lytic polysaccharide monooxygenase (LPMO) from over seven families. Using the newly developed program we were able to reveal previously unknown homologs of LPMOs, namely the PFAM Egh16-like family. Moreover, we show that the substrate specificities have evolved independently several times within the LPMO superfamily. Furthermore, the LPMO phylogenetic tree, does not seem to follow taxonomy-based classification.

Indexed as

Mixed Function OxygenasesPhylogenyPolysaccharidesProteinsMixed Function OxygenasesPolysaccharidesProteinsHidden Markov ModelHMMLPMOLytic Polysaccharide Mono-oxygenasephylogeny

Identifiers

PMID31956399
PMCPMC6950343
OpenAlexW2982689446

What OpenQuestion holds

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Registered trials

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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.