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Whole genome sequence and manual annotation of Clostridium autoethanogenum, an industrially relevant bacterium

Overview of attention for article published in BMC Genomics, December 2015
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  • Good Attention Score compared to outputs of the same age and source (65th percentile)

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1 patent

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Title
Whole genome sequence and manual annotation of Clostridium autoethanogenum, an industrially relevant bacterium
Published in
BMC Genomics, December 2015
DOI 10.1186/s12864-015-2287-5
Pubmed ID
Authors

Christopher M. Humphreys, Samantha McLean, Sarah Schatschneider, Thomas Millat, Anne M. Henstra, Florence J. Annan, Ronja Breitkopf, Bart Pander, Pawel Piatek, Peter Rowe, Alexander T. Wichlacz, Craig Woods, Rupert Norman, Jochen Blom, Alexander Goesman, Charlie Hodgman, David Barrett, Neil R. Thomas, Klaus Winzer, Nigel P. Minton

Abstract

Clostridium autoethanogenum is an acetogenic bacterium capable of producing high value commodity chemicals and biofuels from the C1 gases present in synthesis gas. This common industrial waste gas can act as the sole energy and carbon source for the bacterium that converts the low value gaseous components into cellular building blocks and industrially relevant products via the action of the reductive acetyl-CoA (Wood-Ljungdahl) pathway. Current research efforts are focused on the enhancement and extension of product formation in this organism via synthetic biology approaches. However, crucial to metabolic modelling and directed pathway engineering is a reliable and comprehensively annotated genome sequence. We performed next generation sequencing using Illumina MiSeq technology on the DSM10061 strain of Clostridium autoethanogenum and observed 243 single nucleotide discrepancies when compared to the published finished sequence (NCBI: GCA_000484505.1), with 59.1 % present in coding regions. These variations were confirmed by Sanger sequencing and subsequent analysis suggested that the discrepancies were sequencing errors in the published genome not true single nucleotide polymorphisms. This was corroborated by the observation that over 90 % occurred within homopolymer regions of greater than 4 nucleotides in length. It was also observed that many genes containing these sequencing errors were annotated in the published closed genome as encoding proteins containing frameshift mutations (18 instances) or were annotated despite the coding frame containing stop codons, which if genuine, would severely hinder the organism's ability to survive. Furthermore, we have completed a comprehensive manual curation to reduce errors in the annotation that occur through serial use of automated annotation pipelines in related species. As a result, different functions were assigned to gene products or previous functional annotations rejected because of missing evidence in various occasions. We present a revised manually curated full genome sequence for Clostridium autoethanogenum DSM10061, which provides reliable information for genome-scale models that rely heavily on the accuracy of annotation, and represents an important step towards the manipulation and metabolic modelling of this industrially relevant acetogen.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 124 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 <1%
New Zealand 1 <1%
United States 1 <1%
Unknown 121 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 26 21%
Student > Ph. D. Student 24 19%
Student > Bachelor 15 12%
Student > Master 13 10%
Professor > Associate Professor 6 5%
Other 20 16%
Unknown 20 16%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 35 28%
Agricultural and Biological Sciences 28 23%
Computer Science 7 6%
Chemistry 6 5%
Chemical Engineering 6 5%
Other 16 13%
Unknown 26 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 30 June 2021.
All research outputs
#6,981,478
of 22,889,074 outputs
Outputs from BMC Genomics
#3,229
of 10,669 outputs
Outputs of similar age
#110,694
of 389,554 outputs
Outputs of similar age from BMC Genomics
#103
of 324 outputs
Altmetric has tracked 22,889,074 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 10,669 research outputs from this source. They receive a mean Attention Score of 4.7. This one has gotten more attention than average, scoring higher than 68% of its peers.
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 389,554 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 70% of its contemporaries.
We're also able to compare this research output to 324 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 65% of its contemporaries.