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Record W2607027454

Targeted enrichment of cellulase genes using stable-isotope probing and metagenomics

2012· dissertation· en· W2607027454 on OpenAlexfundno aff
Lee J. Pinnell

Bibliographic record

VenueUWSpace (University of Waterloo) · 2012
Typedissertation
Languageen
FieldEngineering
TopicBiofuel production and bioconversion
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMetagenomicsCellulaseComputational biologyGeneChemistryStable isotope ratioBiologyEnzymeMicrobiologyBiochemistryPhysics
DOInot available

Abstract

fetched live from OpenAlex

Cellulose is the most abundant organic compound on the planet, and is found in nearly every ecosystem. Cellulose is also the most abundant waste product produced by human activity. These enormous stores of natural cellulose and cellulose-containing wastes are a potential renewable energy source. The hydrolysis of cellulose is referred to as cellulolysis and is carried out by cellulase enzymes, which are members of certain glycoside hydrolase families. For most of its history, the microbiology of organisms like those that hydrolyze cellulose was based solely on the testing of physiological and biochemical behaviour of isolated organisms in pure cultures. Despite having gained an important foundation of knowledge in the characterization of microorganisms, cultivation-based techniques introduce major bias into understanding the role that specific microorganisms play because the majority of microorganisms are not readily cultured. Two of the most powerful culture-independent approaches for accessing microbial communities are DNA stable-isotope probing (DNA-SIP) and metagenomics. Though each methodology has been used on its own, it is a combination of these two approaches that has enormous potential to generate results for industrial applications and to help characterize biogeochemical cycling. This thesis presents the first research combining DNA-SIP and metagenomics using cellulose, and the first to target glycoside hydrolase genes from Arctic tundra. For this research, two-month DNA-SIP incubations were carried out with 200 mg of 13C-labelled cellulose as a substrate. Denaturing gradient gel electrophoresis (DGGE) provided evidence indicating the successful enrichment of microorganisms able to metabolize cellulose. Multiple displacement amplification (MDA) was applied to both the bulk-soil samples and DNA-SIP samples. Following MDA, all DNA samples were subjected to Illumina sequencing, including DNA from a cellulose-degrading enrichment. Functional annotation for each Illumina library was done using the SwissProt database within MG-RAST. The DNA-SIP enrichment resulted in a ~3 fold increase in the relative abundance of glycoside hydrolases and cellulase enzymes in relation to bulk soil samples. A cellulose degrading enrichment contained the highest relative abundance of glycoside hydrolases and cellulase enzymes, with a five fold increase relative to the DNA-SIP enrichment. The enrichment culture had a much lower relative diversity, which was measured using the Shannon Index. An unrooted neighbor-joining tree constructed using Bray-Curtis similarity coefficients for each sample demonstrated that as a result of a considerably higher proportion of cellulase gene sequences and a lower diversity the enrichment culture was the most distinct library, with the DNA-SIP library most closely related to it. DGGE provided initial evidence that MDA introduced bias into the amplification of DNA from the DNA-SIP sample. This was confirmed following sequencing and annotation as the proportion of glycoside hydrolase enzymes sequences decreased 67% following MDA of DNA-SIP enriched DNA and the mean G+ C content of libraries decreased. This research provides evidence indicating that DNA-SIP enrichment prior to the construction of metagenomic libraries increases the abundance of targeted gene sequences, which should enable greater access to functional genes of active microorganisms for potential industrial applications.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.013
GPT teacher head0.182
Teacher spread0.170 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2012
Admission routes1
Has abstractyes

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