Evidence map›Paper›PMID 28674932›Full record

ArticleJournal of industrial microbiology & biotechnology2017

Use of transcription activator-like effector for efficient gene modification and transcription in the filamentous fungus Trichoderma reesei.

Pei Liu, Wei Wang, Dongzhi Wei

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Article in Journal of industrial microbiology & biotechnology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
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

6 citing papers in PubMed.

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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.

Pei LiuState Key Lab of Bioreactor Engineering, New World Institute of Biotechnology, East China University of Science and Technology, P.O.B. 311, 130 Meilong Road, Shanghai, 200237, China.
Wei WangState Key Lab of Bioreactor Engineering, New World Institute of Biotechnology, East China University of Science and Technology, P.O.B. 311, 130 Meilong Road, Shanghai, 200237, China. wadexp@ecust.edu.cn.
Dongzhi WeiState Key Lab of Bioreactor Engineering, New World Institute of Biotechnology, East China University of Science and Technology, P.O.B. 311, 130 Meilong Road, Shanghai, 200237, China.

Funding

Fundamental Research Funds for the Central Universities 222201714053National Natural Science Foundation of China C010302-31500066
6 · The paper itself

Abstract

Filamentous fungi have wide applications in the field of biotechnology. The use of transcription activator-like effectors (TALEs) is a powerful genome-engineering tool, which can facilitate genome editing and transcriptional modulation, and has been used for genetic modification in a variety of organisms. However, a transcription activator-like effectors nuclease (TALEN) approach has not been used in filamentous fungi so far. Here, we aimed to establish the shortest TALEN and TALE-transcription factor (TALE-TF) proteins for use in gene modification and transcription in the filamentous fungus Trichoderma reesei. The alternative tandem repeat unit of the TALEs was first established by the ligation of two isocaudamers: XbaI and SpeI, instead of the natural unit. In addition, we adopted T. reesei expression assays to monitor the activities of the TALENs and TALE-TF in vivo in T. reesei. Our results showed that TALEs are a powerful genome-manipulating tool for use in T. reesei and other filamentous fungal species and that their use might facilitate studies on functional genomics and strain improvement in these filamentous fungi.

Indexed as

Genetic EngineeringTranscription, GeneticGene Expression RegulationGenome, FungalTranscription Activator-Like EffectorsTrichodermaTranscription Activator-Like EffectorsFilamentous fungusGenome editingGenome-manipulating toolTALENTALE-TFTrichoderma reesei

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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.