Recombinant Human Triosephosphate Isomerase 1 TPI1
- Known as:
- Recombinant Human Triosephosphate Isomerase 1 TPI1
- Catalog number:
- enz-017
- Product Quantity:
- 5
- Category:
- -
- Supplier:
- Prospecbio
- Gene target:
- Recombinant Human Triosephosphate Isomerase 1 TPI1
Related genes to: Recombinant Human Triosephosphate Isomerase 1 TPI1
- Gene:
- TPI1 NIH gene
- Name:
- triosephosphate isomerase 1
- Previous symbol:
- -
- Synonyms:
- -
- Chromosome:
- 12p13.31
- Locus Type:
- gene with protein product
- Date approved:
- 2001-06-22
- Date modifiied:
- 2019-04-23
Related products to: Recombinant Human Triosephosphate Isomerase 1 TPI1
Related articles to: Recombinant Human Triosephosphate Isomerase 1 TPI1
- This study identified zinc finger protein 544 (ZNF544) as a biomarker in hepatocellular carcinoma (HCC) and aims to delineate its functional role. - Source: PubMed
Publication date: 2026/04/02
Tang JieXu MingOu Xilong - Constraint-based modelling (CBM) is a powerful computational approach that reconstructs cellular metabolism by integrating ‘omics data with genome-scale metabolic models (GEMs), enabling in silico hypothesis generation and genetic engineering studies. Advances in high-throughput ‘omics technologies and the complete mapping of the human genome have expanded the application of CBM to human systems. Given that altered metabolism is a hallmark of cancer, this disease represents an ideal context for developing and applying CBM workflows. Despite the presence of well-characterised metabolic signatures and vulnerabilities in ovarian cancer, this tumour type remains under-explored within the CBM field. Meanwhile, the limited efficacy of current therapies and the frequent emergence of chemoresistance underscore the need for novel, mechanism-based approaches to therapeutic discovery. In this study, we constructed ovarian cancer-specific metabolic models using an ‘omics integration algorithm that incorporates transcriptomic data in a way that is directed by experimental proliferation measurements. Simulations identified multiple candidate molecules predicted to influence cancer cell proliferation. Among these, triosephosphate isomerase 1 (TPI1) was selected for experimental validation based on qualitative prioritisation criteria. Notably, model predictions were supported by RNA sequencing and colony-formation assays, implicating TPI1 in ovarian cancer cell survival. Our results provide novel insights into the metabolic dependencies of ovarian cancer and demonstrate an omics-integrated CBM workflow that may be broadly applicable for uncovering therapeutic vulnerabilities in other malignancies. - Source: PubMed
Publication date: 2026/03/19
Meeson Kate EMcGrail Joanne CSchwartz Jean-MarcTaylor Stephen S - - Source: PubMed
Publication date: 2026/03/19
Wang ZhiyongChen XiaoHan XiaoCao XuchenWang Xin - Advancements in synthetic genetic circuits have enabled programmable and condition-dependent control of microbial cell growth. CRISPR-Cas9-based kill switches, genetic systems that program cells to lose viability in response to specific conditions, have recently been demonstrated for bacterial cell factories but not yet in yeast. - Source: PubMed
Publication date: 2026/02/20
Umashankar PavithraChoi BohyunNygård Yvonne - High-abundance proteins (HAPs) constitute more than 90% of total serum proteins, and their selective removal is crucial for improving the detection of low-abundance proteins that play key roles in disease mechanisms and potential biomarker discovery. In rheumatoid arthritis (RA), existing diagnostic potential biomarkers exhibit limited sensitivity and specificity, underscoring the need for more accurate molecular indicators. This study integrates HAPs depletion with advanced proteomic profiling to improve serum protein analysis and identify novel potential biomarkers associated with RA. A polyoxometalate-mosified metal-organic framework (POM-MOF) composite, SiMoO@UiO-66, was synthesized by immobilizing silicomolybdic acid (SiMoO) onto the UiO-66 framework via hydrogen bonding. The resulting oxygen-rich composite selectively adsorbs human serum albumin (HSA), transferrin (Trf), and immunoglobulin G (IgG) through electrostatic interactions with positively charged lysine and arginine residues. Under optimized experimental conditions (pH 5.0, 700 mmol·L NaCl, BR buffer), 1.0 mg of SiMoO@UiO-66 achieved removal efficiencies of 95.8% for HSA, 93.5% for Trf, and 75.0% for IgG from 1.0 mL of 100 μg·mL protein solutions. Adsorption kinetics and equilibrium data fitted well to the pseudo-first-order and Langmuir models, respectively, confirming monolayer adsorption behavior. Proteomic analysis using the application of liquid chromatography-mass spectrometry (LC-MS/MS) identified 203 proteins in untreated human serum and 214 proteins following HAP depletion, including 46 newly detected low-abundance proteins. Comparative proteomic profiling of RA and healthy sera revealed 154 differentially expressed proteins. Subsequent bioinformatics analysis highlighted five potential biomarkers, GAPDH, TPI1, PFN1, HSP90AA1, and CALM1, with CALM1 reported here for the first time in association with RA, indicating its potential diagnostic relevance. - Source: PubMed
Publication date: 2026/02/12
Wang YingWu SuqinZhu QingtaoSun ShiweiZhao YuchunZheng ZiyuLiu YunMei XifanHu XueChen Qing