ReviewApplied microbiology and biotechnology2025
Advancing cellulose utilization and engineering consolidated bioprocessing yeasts: current state and perspectives.
Review in Applied microbiology and biotechnology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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.
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.
Who cites it
7 citing papers in PubMed.
- Alkaliphilic microbial cellulases: sources, structural insights, and bioengineering approaches for industrial applications.Archives of microbiology · 2026Review
- Harnessing the potential of lignocellulosic biomass for biofuels production.Applied microbiology and biotechnology · 2026Review
- Utilization of lignocellulosic mushroom cultivation residues for bioethanol production via consolidated bioprocessing.World journal of microbiology & biotechnology · 2026Article
- Engineering natural Saccharomyces cerevisiae isolates for enhanced one-step cellulosic ethanol production.Applied microbiology and biotechnology · 2026Article
- Waking up of sleeping giant ligno-cellulosic biomass for biofuel production.Sustainable microbiology · 2026Article
- EngineeringFrontiers in microbiology · 2026Review
- Selective Dehydration of Pentoses and Hexoses ofInternational journal of molecular sciences · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Despite the lack of implementation of consolidated bioprocessing (CBP) at an industrial scale, this bioconversion strategy still holds significant potential as an economically viable solution for converting lignocellulosic biomass (LCB) into biofuels and green chemicals, provided an appropriate organism can be isolated or engineered. The use of Saccharomyces cerevisiae for this purpose requires, among other things, the development of a cellulase expression system within the yeast. Over the past three decades, numerous studies have reported the expression of cellulase-encoding genes, both individually and in combination, in S. cerevisiae. Various strategies have emerged to produce a core set of cellulases, with differing degrees of success. While one-step conversion of cellulosic substrates to ethanol has been reported, the resulting titers and productivities fall well below industrial requirements. In this review, we examine the strategies employed for cellulase expression in yeast, highlighting the successes in developing basic cellulolytic CBP-enabled yeasts. We also summarize recent advancements in rational strain design and engineering, exploring how these approaches can be further enhanced through modern synthetic biology tools to optimize CBP-enabled yeast strains for potential industrial applications. KEY POINTS: • S. cerevisiae's lack of cellulolytic ability warrants its engineering for industry. • Advancements in the expression of core sets of cellulases have been reported. • Rational engineering is needed to enhance cellulase secretion and strain robustness. • Insights gained from omics strategies will direct the future development of CBP strains.
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Registered trials
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.