Chrome Extension
WeChat Mini Program
Use on ChatGLM

Pre-B-cell Colony-Enhancing Factor, Whose Expression is Up-Regulated in Activated Lymphocytes, is a Nicotinamide Phosphoribosyltransferase, a Cytosolic Enzyme Involved in NAD Biosynthesis

European Journal Of Immunology(2002)SCI 3区

Free Univ Brussels

Cited 541|Views14
Abstract
The murine homologue of the previously identified human "pre-B-cell colony-enhancing factor" (PBEF) gene coding for a putative cytokine has been identified by screening a subtractive library enriched in genes expressed in activated T lymphocytes. Unlike most cytokine genes known to date, the PBEF gene is ubiquitously expressed in lymphoid and non-lymphoid tissues and displays significant homology with genes from primitive metazoans (marine sponges) and prokaryotic organisms. Recently, a bacterial protein encoded by nadV, a gene from the prokaryote Haemophilus ducreyi displaying significant homology with PBEF, has been identified as a nicotinamide phosphoribosyltranferase (NAmPRTase), an enzyme involved in nicotinamide adenine dinucleotide (NAD) biosynthesis. Using a panel of antibodies to murine PBEF, we demonstrate in this work that, similarly to its microbial counterpart, the murine protein is a NAmPRTase, catalyzing the condensation of nicotinamide with 5-phosphoribosyl-1-pyrophosphate to yield nicotinamide mononucleotide, an intermediate in the biosynthesis of NAD. The role of PBEF as a NAmPRTase was further confirmed by showing that the mouse gene was able to confer the ability to grow in the absence of NAD to a NAmPRTase-defective bacterial strain. The present findings are in keeping with the ubiquitous nature of this protein, and indicate that NAD biosynthesis may play an important role in lymphocyte activation.
More
Translated text
Key words
pre-B-cell colony-enhancing factor,nicotinamide phosphoribosyltransferase lymphocyte activation,NAD,EC 2.4.2.12
求助PDF
上传PDF
Bibtex
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
  • Pretraining has recently greatly promoted the development of natural language processing (NLP)
  • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
  • We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
  • The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
  • Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Related Papers
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
GPU is busy, summary generation fails
Rerequest