Utilising one-carbon substrates such as carbon dioxide, methane, and methanol is vital to address the current climate crisis. Methylotrophic metabolism enables growth and energy generation from methanol, providing an alternative to sugar fermentation. Saccharomyces cerevisiae is an important industrial microorganism for which growth on one-carbon substrates would be relevant. However, its ability to metabolize methanol has been poorly characterised. Here, using adaptive laboratory evolution and C-tracer analysis, we discover that S. cerevisiae has a native capacity for methylotrophy. A systems biology approach reveals that global rearrangements in central carbon metabolism fluxes, gene expression changes, and a truncation of the uncharacterized transcriptional regulator Ygr067cp supports improved methylotrophy in laboratory evolved S. cerevisiae. This research paves the way for further biotechnological development and fundamental understanding of methylotrophy in the preeminent eukaryotic model organism and industrial workhorse, S. cerevisiae.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7643182 | PMC |
| http://dx.doi.org/10.1038/s41467-020-19390-9 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Depot-specific acetylation profiles of adipose tissues-therapeutic targets for metabolically unhealthy obesity.
Diabetol Metab Syndr
January 2025
The Centre for Cleft Lip and Palate Treatment, Plastic Surgery Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 33 Badachu Road, Shijingshan District, Beijing, 100144, People's Republic of China.
Background: Adipose tissue plays a critical role in the development of metabolically unhealthy obesity (MUO), with distinct adipose depots demonstrating functional differences. This study aimed to investigate the unique characteristics of subcutaneous (SA) and visceral adipose tissue (VA) in MUO.
Methods: Paired omental VA and abdominal SA samples were obtained from four male patients with MUO and subjected to Four-Dimensional Data Independent Acquisition (4D-DIA) proteomic and lysine acetylation (Kac) analyses.
Evaluating simulated teaching audio for teacher trainees using RAG and local LLMs.
Sci Rep
January 2025
Office for the Advancement of Educational Information, Chengdu Normal University, Chengdu, 610000, China.
In the training of teacher students, simulated teaching is a key method for enhancing teaching skills. However, traditional evaluations of simulated teaching typically rely on direct teacher involvement and guidance, increasing teachers' workload and limiting the opportunities for teacher students to practice independently. This paper introduces a Retrieval-Augmented Generation (RAG) framework constructed using various open-source tools (such as FastChat for model inference and Whisper for speech-to-text) combined with a local large language model (LLM) for audio analysis of simulated teaching.
View Article and Find Full Text PDFA neural network for long-term super-resolution imaging of live cells with reliable confidence quantification.
Nat Biotechnol
January 2025
Department of Automation, Tsinghua University, Beijing, China.
Super-resolution (SR) neural networks transform low-resolution optical microscopy images into SR images. Application of single-image SR (SISR) methods to long-term imaging has not exploited the temporal dependencies between neighboring frames and has been subject to inference uncertainty that is difficult to quantify. Here, by building a large-scale fluorescence microscopy dataset and evaluating the propagation and alignment components of neural network models, we devise a deformable phase-space alignment (DPA) time-lapse image SR (TISR) neural network.
View Article and Find Full Text PDFZoonoses are infectious diseases transmitted from animals to humans. Bats have been suggested to harbour more zoonotic viruses than any other mammalian order. Infections in bats are largely asymptomatic, indicating limited tissue-damaging inflammation and immunopathology.
View Article and Find Full Text PDFNon-fullerene acceptors with high crystallinity and photoluminescence quantum yield enable >20% efficiency organic solar cells.
Nat Mater
January 2025
School of Chemistry, Beihang University, Beijing, China.
The rational design of non-fullerene acceptors (NFAs) with both high crystallinity and photoluminescence quantum yield (PLQY) is of crucial importance for achieving high-efficiency and low-energy-loss organic solar cells (OSCs). However, increasing the crystallinity of an NFA tends to decrease its PLQY, which results in a high non-radiative energy loss in OSCs. Here we demonstrate that the crystallinity and PLQY of NFAs can be fine-tuned by asymmetrically adapting the branching position of alkyl chains on the thiophene unit of the L8-BO acceptor.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!