PIK3CA ( asian musta aukko: inositoli , inositolifosfaatti, fosfatidyyli-inositoli - tämän kohdan normaali metabolinen kartta)

 

Aliases for PIK3CA Gene

• GeneCards Symbol: PIK3CA ²
• Phosphatidylinositol-4,5-Bisphosphate 3-Kinase Catalytic Subunit Alpha ^{2 3 5}
• PI3K ^{2 3 5}
• Phosphatidylinositol 4,5-Bisphosphate 3-Kinase Catalytic Subunit Alpha Isoform ^{3 4}
• Phosphoinositide-3-Kinase, Catalytic, Alpha Polypeptide ^{2 3}
• Serine/Threonine Protein Kinase PIK3CA ^{3 4}
• PtdIns-3-Kinase Subunit P110-Alpha ^{3 4}
• Phosphoinositide 3-Kinase Alpha ^{3 4}
• PI3K-Alpha ^{3 4}
• Phosphatidylinositol-4,5-Bisphosphate 3-Kinase 110 KDa Catalytic Subunit Alpha ³
• Phosphatidylinositol 4,5-Bisphosphate 3-Kinase 110 KDa Catalytic Subunit Alpha ⁴
• Mutant Phosphatidylinositol-4,5-Bisphosphate 3-Kinase Catalytic Subunit Alpha ³
• Phosphatidylinositol-4,5-Bisphosphate 3-Kinase, Catalytic Subunit Alpha ²
• Phosphatidylinositol 3-Kinase, Catalytic, Alpha Polypeptide ³
• Phosphatidylinositol 3-Kinase, Catalytic, 110-KD, Alpha ³
• Phosphoinositide-3-Kinase Catalytic Alpha Polypeptide ⁴
• PI3-Kinase P110 Subunit Alpha ³

• PtdIns-3-Kinase Subunit Alpha ⁴
• PI3-Kinase Subunit Alpha ⁴
• EC 2.7.1.137 ⁴
• EC 2.7.1.153 ⁴
• EC 2.7.11.1 ⁴
• P110-Alpha ³
• PI3Kalpha ⁴
• P110alpha ⁴
• EC 2.7.1 ⁴⁸
• CLAPO ³
• CLOVE ³
• MCMTC ³
• CCM4 ³
• CWS5 ³
• MCAP ³
• MCM ³

External Ids for PIK3CA Gene

• HGNC: 8975
• NCBI Gene: 5290
• Ensembl: ENSG00000121879
• OMIM®: 171834
• UniProtKB/Swiss-Prot: P42336

NCBI Gene Summary for PIK3CA Gene

• Phosphatidylinositol 3-kinase is composed of an 85 kDa regulatory subunit and a 110 kDa catalytic subunit. The protein encoded by this gene represents the catalytic subunit, which uses ATP to phosphorylate PtdIns, PtdIns4P and PtdIns(4,5)P2. This gene has been found to be oncogenic and has been implicated in cervical cancers. A pseudogene of this gene has been defined on chromosome 22. [provided by RefSeq, Apr 2016]

CIViC Summary for PIK3CA Gene

• PIK3CA is the most recurrently mutated gene in breast cancer, and has been found to important in a number of cancer types. An integral part of the PI3K pathway, PIK3CA has long been described as an oncogene, with two main hotspots for activating mutations, the 542/545 region of the helical domain, and the 1047 region of the kinase domain. PIK3CA, and its interaction with the AKT and mTOR pathways, is the subject of an immense amount of research and development, and PI3K inhibition has seen some limited success in recent clinical trials. While monotherapies seem to be limited in their potential, there is a recent interest in pursuing PI3K inhibition as part of a combination therapy regiment with inhibition partners including TKI's, MEK inhibitors, PARP inhibitors, and in breast cancer, aromatase inhibitors.

GeneCards Summary for PIK3CA Gene

PIK3CA (Phosphatidylinositol-4,5-Bisphosphate 3-Kinase Catalytic Subunit Alpha) is a Protein Coding gene. Diseases associated with PIK3CA include Megalencephaly-Capillary Malformation-Polymicrogyria Syndrome and Congenital Lipomatous Overgrowth, Vascular Malformations, And Epidermal Nevi. Among its related pathways are Downstream signaling of activated FGFR2 and Translation Insulin regulation of translation. Gene Ontology (GO) annotations related to this gene include transferase activity, transferring phosphorus-containing groups and protein serine/threonine kinase activity. An important paralog of this gene is PIK3CB.

UniProtKB/Swiss-Prot Summary for PIK3CA Gene

Phosphoinositide-3-kinase (PI3K) phosphorylates phosphatidylinositol (PI) and its phosphorylated derivatives at position 3 of the inositol ring to produce 3-phosphoinositides (PubMed:15135396, 23936502, 28676499). Uses ATP and PtdIns(4,5)P2 (phosphatidylinositol 4,5-bisphosphate) to generate phosphatidylinositol 3,4,5-trisphosphate (PIP3) (PubMed:15135396, 28676499). PIP3 plays a key role by recruiting PH domain-containing proteins to the membrane, including AKT1 and PDPK1, activating signaling cascades involved in cell growth, survival, proliferation, motility and morphology. Participates in cellular signaling in response to various growth factors. Involved in the activation of AKT1 upon stimulation by receptor tyrosine kinases ligands such as EGF, insulin, IGF1, VEGFA and PDGF. Involved in signaling via insulin-receptor substrate (IRS) proteins. Essential in endothelial cell migration during vascular development through VEGFA signaling, possibly by regulating RhoA activity. Required for lymphatic vasculature development, possibly by binding to RAS and by activation by EGF and FGF2, but not by PDGF. Regulates invadopodia formation through the PDPK1-AKT1 pathway. Participates in cardiomyogenesis in embryonic stem cells through a AKT1 pathway. Participates in vasculogenesis in embryonic stem cells through PDK1 and protein kinase C pathway. In addition to its lipid kinase activity, it displays a serine-protein kinase activity that results in the autophosphorylation of the p85alpha regulatory subunit as well as phosphorylation of other proteins such as 4EBP1, H-Ras, the IL-3 beta c receptor and possibly others (PubMed:23936502, 28676499). Plays a role in the positive regulation of phagocytosis and pinocytosis (By similarity). ( PK3CA_HUMAN,P42336 )

Tocris Summary for PIK3CA Gene

• PI 3-Kinases (phosphoinositide 3-kinases, PI 3-Ks) are a family of lipid kinases capable of phosphorylating the 3'OH of the inositol ring of phosphoinositides. They are responsible for coordinating a diverse range of cell functions including proliferation and survival.

Gene Wiki entry for PIK3CA Gene

Cytogenetic band:

• 3q26.32 by HGNC
• 3q26.32 by NCBI Gene
• 3q26.32 by Ensembl
•  

Protein Symbol:

P42336-PK3CA_HUMAN

Recommended name:

Phosphatidylinositol 4,5-bisphosphate 3-kinase catalytic subunit alpha isoform

Protein attributes for PIK3CA Gene

Size:

1068 amino acids

Molecular mass:

124284 Da

Protein existence level:

PE1

Quaternary structure:

• Heterodimer of a catalytic subunit PIK3CA and a p85 regulatory subunit (PIK3R1, PIK3R2 or PIK3R3) (PubMed:26593112).
  Interacts with IRS1 in nuclear extracts (By similarity).
  Interacts with RUFY3 (By similarity).
  Interacts with RASD2 (By similarity).
  Interacts with APPL1.
  Interacts with HRAS and KRAS (By similarity).
  Interaction with HRAS/KRAS is required for PI3K pathway signaling and cell proliferation stimulated by EGF and FGF2 (By similarity).
  Interacts with FAM83B; activates the PI3K/AKT signaling cascade (PubMed:23676467).

Miscellaneous:

• The avian sarcoma virus 16 genome encodes an oncogene derived from PIK3CA.

 

Molecular function for PIK3CA Gene according to UniProtKB/Swiss-Prot KTS- gene cards lähteestä jatkoteksti: https://www.genecards.org/cgi-bin/carddisp.pl?gene=PIK3CA&keywords=PIK3CA

Onkologia: Rintasyövän metastasoimissuunnat

 2020

 https://www.nature.com/articles/s41586-020-2969-2

• Article
• Open access
• Published: 09 December 2020

A metastasis map of human cancer cell lines

• Xin Jin,
• Zelalem Demere,
• et al
  

Nature volume 588, pages 331–336 (2020)Cite this article Abstract

Most deaths from cancer are explained by metastasis, and yet large-scale metastasis research has been impractical owing to the complexity of in vivo models. Here we introduce an in vivo barcoding strategy that is capable of determining the metastatic potential of human cancer cell lines in mouse xenografts at scale. We validated the robustness, scalability and reproducibility of the method and applied it to 500 cell lines^1,2 spanning 21 types of solid tumour. We created a first-generation metastasis map (MetMap) that reveals organ-specific patterns of metastasis, enabling these patterns to be associated with clinical and genomic features. We demonstrate the utility of MetMap by investigating the molecular basis of breast cancers capable of metastasizing to the brain—a principal cause of death in patients with this type of cancer. Breast cancers capable of metastasizing to the brain showed evidence of altered lipid metabolism. Perturbation of lipid metabolism in these cells curbed brain metastasis development, suggesting a therapeutic strategy to combat the disease and demonstrating the utility of MetMap as a resource to support metastasis research

 ..

 

a, Somatic mutations that associate with brain metastatic potential in the basal-like breast cancer cohort. The top correlate, PIK3CA, reaches statistical significance (FDR = 0.0034, highlighted in bold). All PIK3CA mutations are activating. Positive correlations are in red, negative correlations are in blue. Selected known oncogenes or tumour suppressors in basal-like breast cancer are presented for comparison. b, Alterations in copy number that associate with brain metastatic potential. The top correlates cluster in chr 8p12–8p21.2 (FDR = 0.0017, highlighted in bold). c, Gene-expression signatures that associate with brain metastatic potential. Bars indicate P values. Expression signature scores were projected for each cell line with their in vitro RNA-seq data and used for regression analysis. GO (Gene Ontology), Hallmark, Reactome and Burton are gene sets in the MSigDB gene set enrichment analysis (GSEA) collection. d, Lipid-metabolite species that associate with brain metastatic potential. Bars indicate P values. Lipid metabolites measured by mass spectrometry were grouped by species, and enrichment analysis of the species was performed using GSEA. CE, cholesterol ester; PC, phosphatidylcholine; SM, sphingomyelin; LPC, lysophosphatidylcholine; LPE, lysophosphatidylethanolamine; DAG, diacylglycerol; PPP, pentose phosphate pathway metabolites. e, Heat map presenting distribution of lipid species measured by mass spectrometry from different mouse tissues. Gastroc, gastrocnemius. f, CRISPR gene dependencies that associate with brain metastatic potential. The top gene, SREBF1 (FDR = 0.001), is a selective dependency in highly brain metastatic lines. Positive correlations are in red, negative correlations are in blue. g, Distribution of SREBF1 (top) and SREBF2 (bottom) dependencies across 688 human cancer cell lines. The positions of highly brain metastatic (met) breast lines are highlighted in red, whereas weakly metastatic or non-brain metastatic breast lines are highlighted in blue. h, Consensus alterations in lipid species abundance upon SREBF1 knockout (KO) in JIMT1 and HCC1806, two brain metastatic cell lines. Bars indicate adjusted P values. Lipid metabolites measured by mass spectrometry were grouped by species, and enrichment analysis of the species was performed using GSEA. WT, wild type. i, Consensus gene-expression changes upon SREBF1 knockout in JIMT1, HCC1806, HCC1954 and MDAMB231, four brain metastatic cell lines. The two top genes are SREBF1 and SCD (FDR <0.05, highlighted in bold). j, Co-dependencies of SREBF1 across 688 human cancer cell lines in genome-wide CRISPR viability screen. The two top genes are SCD and SCAP (FDR < 1 × 10⁻⁶⁰, highlighted in bold).

Full size image

Given the observation that SREBF1 knockout resulted in a viability defect in vitro (Extended Data Fig. 10a), we compared the relative effect of knockout on metastasis to different organs, to determine whether the viability defect was preferentially observed in brain (Fig. 5d). Five weeks following intracardiac injection of SREBF1-knockout cells, we observed a marked defect in brain metastasis (196-fold reduction), compared with a modest defect in other organs (9–21 fold) (Fig. 5d). Histologic examination of brains from xenografted mice revealed large metastatic lesions in mice receiving wild-type cells, whereas those receiving SREBF1-knockout cells contained micrometastases (Extended Data Fig. 10b), suggesting that SREBF1 is not required for seeding the brain, but rather for proliferation in the brain microenvironment. Consistent with this hypothesis, injection of tumour cells into the carotid artery increased the probability of seeding the brain, but nevertheless a marked growth defect was still observed in SREBF1-knockout cells (Fig. 5e).

To determine the generality of the SREBF1 requirement for breast cancer growth in the brain, we knocked out SREBF1 in additional brain metastatic lines including HCC1954, MDAMB231 and HCC1806 using CRISPR–Cas9. As with JIMT1, a significant inhibition in brain metastatic growth was also observed in these lines, although the magnitude and duration of growth inhibition varied (Extended Data Fig. 10c, d). The least responsive cell line was HCC1806, in which SREBF1-knockout cells displayed a brain growth defect for the first week, but then assumed a growth trajectory that paralleled wild-type cells. This restoration of growth was not explained by reversion of the genome editing, as brain metastases at the end of the experiment showed evidence of editing at the SREBF1 locus and minimal SREBF1 protein expression (Extended Data Fig. 10e, f). Instead, we found that the SREBF1-independent growth was associated with upregulation of the fatty acid transporter CD36 and the fatty acid-binding protein FABP6 (Extended Data Fig. 10g). Of note, culture of HCC1806 in mouse brain-slice-conditioned medium similarly resulted in upregulation of SCD and CD36 expression (Extended Data Fig. 10h, i). JIMT1 cells did not upregulate CD36 or FABP6 expression following SREBF1 knockout (Extended Data Fig. 10g), perhaps explaining their inability to survive in the brain. Together, these results further demonstrate the relationship between lipid metabolism and brain metastasis, as cells under the selective pressure of SREBF1 loss must acquire lipids by other means to survive in the brain microenvironment.

Discussion

This work describes MetMap as an approach for large-scale in vivo characterization of human cancer cell lines. The MetMap resource (available at https://pubs.broadinstitute.org/metmap) currently includes metastasis profiles of 500 cell lines spanning 21 tumour types, providing a large repertoire of models for exploration of metastasis mechanisms. A limitation of the use of human cell lines for such experiments is that they require the use of immunodeficient mice. The extent to which the immune system has a role in mediating patterns of metastasis remains to be determined³⁷.

We followed up only a small proportion of the MetMap findings—specifically, breast cancer metastasis to brain. Multiple lines of experimental and clinical evidence pointed to a role of lipid metabolism in governing the ability of cells to survive in the brain microenvironment. The importance of lipid metabolism in cancer has been highlighted by a number of studies, but its role in brain metastasis has, to our knowledge, not been fully appreciated^38,39,40,41. The possibility that interfering with lipid or cholesterol metabolism might abrogate metastatic growth in the brain is particularly intriguing. More generally, this work illustrates the complex interplay between cancer cell growth and the tissue microenvironment.

 

 2023

 https://www.nature.com/articles/s41467-023-44206-x

Pathway centric analysis for single-cell RNA-seq and spatial transcriptomics data with GSDensity

• Qingnan Liang,
• Yuefan Huang,
• Shan He &
• Ken Chen 

Nature Communications volume 14, Article number: 8416 (2023)

GSDensity can identify spatially relevant pathways in mouse brains and human tumors including those following high-order organizational patterns in the ST data. Particularly, we create a pan-cancer ST map revealing spatially relevant and recurrently active pathways across six different tumor types.

Full size image

The proliferative ability of tumor cells could be regulated through their interactions with the TIME^27,28. We then compared these actively dividing cells with other tumor cells from the angle of cell-cell interaction between tumor and TIME. We annotated the normal cells in the TNBC-1 dataset into two groups, fibroblasts, and immune cells (Supplementary Fig. 6b, c) and inferred the ligand-receptor interactions²⁹ between immune and tumor cells and between tumor and tumor cells. We displayed all the ligand receptor-pairs in Supplementary Fig. 7a and found that the dividing cells showed a distinct profile of the GAS6-TYRO3 axis. All the other ligand-receptor pairs showed differential enrichments in either immune-tumor interaction or tumor-tumor interaction, while GAS6-TYRO3 was the only pair that showed differential enrichments in both groups. We then found that both the tumor cells and the immune cells could express the ligand, GAS6, while only the dividing tumor cells displayed high expression of the receptor, TYRO3 (Fig. 3h), which indicated the specific activation of the TYRO3 downstream signaling in those cells. For confirmation, we also fetched actively dividing tumor cells from another two TNBC datasets²⁵, TNBC-2 and TNBC-5, and these cells also consistently showed high relevance to glycolysis, mTORC1 signaling, and mitotic spindle (Supplementary Fig. 6d–k, p-value < 2.2e−16 for all groups, Chi-squared test). The high expression of TYRO3 in actively dividing cells was also observed in the TNBC-5, confirming the previous finding (p-value = 3.18e−8, Wilcoxon test, Supplementary Fig. 6l–m). We then investigated this TYRO3 expression pattern in another published cohort with 8 TNBC patient samples³⁰. TYRO3 were lowly detected in 7 of the samples (detected in 1–8% of tumor cells). In the only sample (GSM4909284_TN-MH0114-T2) with relative high expression of TYRO3 (detected in 24% of tumor cells), the actively dividing cells showed higher expression of TYRO3 than other tumor cells (p-value = 0.039, Wilcoxon test, Supplementary Fig. 6n). These results indicated that the overall expression level of TYRO3 in breast cancer cells is highly patient specific, while the high-TYRO3 expressing samples always had TYRO3 preferably express in a small group of actively dividing cells. The GAS6-TYRO3 axis has been associated with tumor cell proliferation, malignancy, and anti-PD1/PD-L1 resistance in previous studies^{31,32,33,34,35}. Thus, through the integration of data and prior knowledge using GSDensity, we postulated a potential role TYRO3 in TNBC proliferation using only a few TNBC samples with very sparse single-cell gene expression profiles and generated a testable hypothesis for further studies.

..

We applied GSDensity to a ST mouse forebrain dataset generated by the 10X Visium technology. We first clustered the data spots based on the transcriptome (Fig. 5a) and observed that all the clusters were also spatially segregated on the spatial map (Fig. 5b). Thus, the pathways with cluster-wise specificity would naturally display spatial relevance in this data. However, it is unclear whether there are high order organization of pathway activities across multiple clusters, which would be undetectable in cluster-centric analysis. To address this question, we first identified 727 GO biological process terms with coordination in the dataset using GSDensity. For each term, we calculated its spatial relevance and specificity for each cluster. The spatial relevance is quantified by KL-divergence between the pathway weighted kernel density estimation (KDE) and the equally weighted KDE (Methods). The specificity of a pathway for a cluster is quantified by a specificity score based on Jensen-Shannon divergence, with larger values being more specific. We then plotted the 727 GO terms with their spatial relevance and maximum cluster-wise specificity (Fig. 5c). As expected, the spatial relevance showed largely positive correlation with cluster-wise specificity. Among the GO terms with high cluster-wise specificity (Fig. 5c, red) are dopamine receptor signaling for Cluster 1, amyloid beta formation for Cluster 5, ARP2/3 complex mediated actin nucleation for Cluster 8/11, and oligodendrocyte development for Cluster 2 (Fig. 5d–g). Interestingly, we also observed some GO terms with high spatial relevance and low cluster-wise specificity (Fig. 5c, blue). The cells highly relevant to these terms consisted of data spots from multiple clusters with higher-order spatial organization (Fig. 5h–k). For example, positive regulation of cellular response to insulin stimulus appeared highly active in the spots close to the caudal side (Fig. 5i), while fatty acid oxidation to the ventral side (Fig. 5j). It has been known that insulin receptors are expressed in hypothalamus and hippocampus⁴³ which are both located close to the caudal side of this anterior section. Although GSDensity was designed to perform cluster-independent data analysis, we demonstrated that the pathway activity calculation by GSDensity can be easily integrated with cell information, such as cluster partition or spatial coordinates, when available. 

..

Like the scenario of the mouse brain data, some pathways were both highly spatially relevant and highly cell-type specific, for example, protein localization to synapse was highly specific to inhibitory neurons and sensory perception of smell was highly specific to excitatory neurons, both of which occupied localizations with spatial relevance on the map (Supplementary Fig. 10c, d). 

 

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Virusten replikaatiossa on tärkeä osa fosfatidyyli-inositoli-4- kinaasilla (PI4K) ja sen produktilla PI(4)P

 https://www.sciencedirect.com/science/article/pii/S0006295212005163?via%3Dihub#fig0005

 

Volume 84, Issue 11, 1 December 2012, Pages 1400-140

Commentary

The role of phosphatidylinositol 4-kinases and phosphatidylinositol 4-phosphate during viral replication

Author links open overlay panel

, ,

https://doi.org/10.1016/j.bcp.2012.07.034Get rights and content

Abstract

Phosphoinositides (PI) are phospholipids that mediate signaling cascades in the cell by binding to effector proteins. Reversible phosphorylation of the inositol ring at positions 3, 4 and 5 results in the synthesis of seven different phosphoinositides. Each phosphoinositide has a unique subcellular distribution with a predominant localization in subsets of membranes. These lipids play a major role in recruiting and regulating the function of proteins at membrane interfaces [1]. Several bacteria and viruses modulate and exploit the host PI metabolism to ensure efficient replication and survival. Here, we focus on the roles of cellular phosphatidylinositol 4-phosphate (PI4P) and phosphatidylinositol 4-kinases (PI4Ks) during the replication cycle of various viruses. It has been well documented that phosphatidylinositol 4-kinase IIIβ (PI4KIIIβ, EC 2.7.1.67) is indispensable for viral RNA replication of several picornaviruses. Two recruitment strategies were reported: (i) binding and modulation of GBF1/Arf1 to enhance recruitment of PI4KIIIβ and (ii) interaction with ACBD3 for recruitment of PI4KIIIβ. PI4KIII has also been demonstrated to be crucial for hepatitis C virus (HCV) replication. PI4KIII appears to be directly recruited and activated by HCV NS5A protein to the replication complexes. In contrast to picornaviruses, it is still debated whether the α or the β isoform is the most important. PI4KIII can be explored as a target for inhibition of viral replication. The challenge will be to develop highly selective inhibitors for PI4KIIIα and/or β and to avoid off-target toxicity.

...

 Various viruses have an impact on the host's lipid metabolism, lipid/membrane transport and lipid mediated signal transduction. A key class of lipids involved in these cellular processes is the class of phosphoinositides (PIs). Phosphatidylinositol (PtdIns) is the basic scaffold of the PIs (Fig. 1).

 

PI fosfolipidiaineenvaihdunta Sars-Cov-1 koronavirusten infektiossa , PI4Kbeta tuottaa PI-4P fosfolipidiä, Fosfatidyyli.4-fosfaattia, (Ptd4P)

 DOI: 10.1074/jbc.M111.312561  Tietoa vuodelta 2012

 Tämä tutkimus on Sars-Cov-1 viruksesta. Tämä  sars-Cov-2 on  tehnyt olennaisen muutoksen juuri tuohon kohtaan  , johon mahdollisesti on  voitu kehittää jokin  inhibiittori.  Koetan   ottaa selvää löytyykö  nykyisestä pandemisesta jotakin  vastaava  akilleenkantapääkohtaa. Tässä ei tarkemmin näytetä tai kerrota mekanismia  sars-1 viruksessa.  (Aichi virus mainitaan).

 2012 Mar 9;287(11):8457-67.

doi: 10.1074/jbc.M111.312561. Epub 2012 Jan 17.

Phosphatidylinositol 4-kinase IIIβ is required for severe acute respiratory syndrome coronavirus spike-mediated cell entry

Ning Yang  ¹ , Ping Ma, Jianshe Lang, Yanli Zhang, Jiejie Deng, Xiangwu Ju, Gongyi Zhang, Chengyu Jiang

• PMCID: PMC3318727
• DOI: 10.1074/jbc.M111.312561

Free PMC article

Abstract

Phosphatidylinositol kinases (PI kinases) play an important role in the life cycle of several viruses after infection. Using gene knockdown technology, we demonstrate that phosphatidylinositol 4-kinase IIIβ (PI4KB) is required for cellular entry by pseudoviruses bearing the severe acute respiratory syndrome-coronavirus (SARS-CoV) spike protein and that the cell entry mediated by SARS-CoV spike protein is strongly inhibited by knockdown of PI4KB. Consistent with this observation, pharmacological inhibitors of PI4KB blocked entry of SARS pseudovirions. Further research suggested that PI4P plays an essential role in SARS-CoV spike-mediated entry, which is regulated by the PI4P lipid microenvironment. We further demonstrate that PI4KB does not affect virus entry at the SARS-CoV S-ACE2 binding interface or at the stage of virus internalization but rather at or before virus fusion. Taken together, these results indicate a new function for PI4KB and suggest a new drug target for preventing SARS-CoV infection.

Katson Gene Cards tiedon:

Entrez Gene Summary for PI4KB Gene

• Enables 1-phosphatidylinositol 4-kinase activity and 14-3-3 protein binding activity. Predicted to be involved in phosphatidylinositol phosphate biosynthetic process and phosphatidylinositol-mediated signaling. Located in Golgi membrane. [provided by Alliance of Genome Resources, Apr 2022]

GeneCards Summary for PI4KB Gene

PI4KB (Phosphatidylinositol 4-Kinase Beta) is a Protein Coding gene. Diseases associated with PI4KB include Nonparalytic Poliomyelitis and Poliomyelitis. Among its related pathways are Metabolism and PI Metabolism. Gene Ontology (GO) annotations related to this gene include transferase activity, transferring phosphorus-containing groups and 1-phosphatidylinositol 4-kinase activity. An important paralog of this gene is PI4KA.

UniProtKB/Swiss-Prot Summary for PI4KB Gene

Phosphorylates phosphatidylinositol (PI) in the first committed step in the production of the second messenger inositol-1,4,5,-trisphosphate (PIP). May regulate Golgi disintegration/reorganization during mitosis, possibly via its phosphorylation. Involved in Golgi-to-plasma membrane trafficking (By similarity). ( PI4KB_HUMAN,Q9UBF8 )

(Microbial infection) Plays an essential role in Aichi virus RNA replication (PubMed:22124328, 27989622, 22258260). Recruited by ACBD3 at the viral replication sites (PubMed:22124328, 27989622). ( PI4KB_HUMAN,Q9UBF8 )

(Microbial infection) Required for cellular spike-mediated entry of human coronavirus SARS-CoV. ( PI4KB_HUMAN,Q9UBF8 )

Gene Wiki entry for PI4KB Gene

Aliases for PI4KB Gene

• GeneCards Symbol: PI4KB ²
• Phosphatidylinositol 4-Kinase Beta ^{2 3 4 5}
• PI4K-BETA ^{2 3 5}
• PIK4CB ^{3 4 5}
• Phosphatidylinositol 4-Kinase, Catalytic, Beta ^{2 3}
• PtdIns 4-Kinase Beta ^{3 4}
• EC 2.7.1.67 ^{4 48}
• PI4KIII ^{3 4}
• Pi4K92 ^{2 5}

• PI4K92 ^{3 4}
• NPIK ^{3 4}
• Phosphatidylinositol 4-Kinase, Wortmannin-Sensitive ³
• Type III Phosphatidylinositol 4-Kinase Beta ³
• PI4KIIIBETA ³
• PI4K-Beta ⁴
• PI4KBETA ³
• PI4Kbeta ⁴
• EC 2.7.1 ⁴⁸

 1q21.3

Protein Symbol: Q9UBF8-PI4KB_HUMAN

Recommended name: Phosphatidylinositol 4-kinase beta

Size: 816 amino acids

Molecular mass: 91379 Da

Cofactor: Name=Mg(2+); Xref=ChEBI:CHEBI:18420;

Cofactor: Name=Mn(2+); Xref=ChEBI:CHEBI:29035;

Protein existence level:

PE1

Quaternary structure:

• Interacts with ARF1 and ARF3 in the Golgi complex, but not with ARF4, ARF5 or ARF6 (PubMed:17555535).
  Interacts with NCS1/FREQ in a calcium-independent manner.
  Interacts with CALN1/CABP8 and CALN2/CABP7; in a calcium-dependent manner; this interaction competes with NCS1/FREQ binding (By similarity).
  Interacts with ACBD3 (PubMed:23572552, 27009356, 27989622, 22124328, 22258260).
  Interacts with ARMH3, YWHAB, YWHAE, YWHAG, YWHAH, YWHAQ, YWHAZ and SFN (PubMed:23572552).
  Interacts with GGA2 (via VHS domain); the interaction is important for PI4KB location at the Golgi apparatus membrane (PubMed:28289207).
  Interacts with ATG9A (PubMed:30917996).
• (Microbial infection) Interacts with Aichi virus protein 3A.
  Part of a complex Aichi virus protein 3A/ACBD3/PI4KB that allows the synthesis of PI4P at the viral RNA replication sites.

 

( Toinen artikkeli seuraavassa otsikossa  tästä entsyymistä)

Kertailen ja pohdin M.Türkin antamia tietoja fytiinistä

 Annedalsklinikan krijastossa nin tämän kirjan  ensimmäisen kirjan. ja vuonna 2005  poimin muutamia asioita esiin ja nyt kertailen ja kommentoin 11.3. 2023

Lähde Türk (Larsen) Maria. Cereal- and Microbial Phytases. Phytate Degradation. Mineral binding and Absorption(1999 GU, Chalmers University of technology. Department of Food Science)

Oma alkulause:

Fytiini on pääasiallinen fosfaatin lähde kehoon. Se on myös merkittävä tekijä essentiellien mineraalien lähteenä. Fytiinin rakenteen ytimenä on myo-inositoli ja se on tärkeä  lipositoliryhmän  fosfolipidien muodostukselle:  PI (PtdIns, Fosfatidyyli-inositoli), PIP3, PIP2, IP3) nimisiä molekyylejä sisältävässä aineenvaihdunnan ja signaloinnin modulissa. Tähän moduliin kuuluu ainakin 35 eri jäsentä, sekä rasvaliukoisia että vesiliukoisia. Inositoli itse on vesiliukoinen. Inositolijohdannaiset osallistuvat laajaan solun sisäiseen fosfaattiaineenvaihduntaan ja myös tuman ja genomin asioihin. Tämän takia valitsin suomentaa kappaleita tästä molekyylistä INOSITOLI, joka tulee kasvikunnan fytiinistä. Fytiini-nimensä se sai aluksi sen takia, ettei oikein tiedetty kuuluuko se kasviskuituihin vai ei, vaikka nyt tiedetään, että se on myös osa kiertokulkua animaalisen kudoksen metabolisissa reiteissä, vaikkakaan sitä ei riittävästi syntetisoidukaan kehossa ,sen sijaan sen perusrengasta kierrättyy aikansa. Luonto kyllä tarjoaa runsaasti fytiiniä varsinkin viljassa, jyvissä, pähkinössä ja siemenissä.

Väitöskirja keskittyy kehon ulkopuoliseen tapahtumaan, ravintofytiinin entsymaattiseen pilkkoutumiseen fytaaseilla, mutta poimin väitöskirjsta varsinaisesta fytiinimolekyylistä eräitä olennaisia ja ainutlaatuisia seikkoja tähän suomennokseen. Joku onkin sanonut että fytiini on kehon vahvin antioksidantti. Mene ja tiedä.

Abstraktin ja taustan suomennosta eräin osin

“ Viljaruoat sisältävät suuret määrät fytiiniä (myo-inositoliheksafosfaattia; IP6), joka on kasvin pääasiallinen fosforin varastomuoto. Fytiinillä on suuri kyky kelatoida divalentteja mineraaleja kuten Fe(2+), Zn (2+), Mg(2+) ja Ca(2+). Asialla on ravitsemuksellista merkitystä, koska sillä on negatiivista (?) vaikutusta ruoan välttämättömien elementtien biologiseen saatavuuteen, ( niin sanotaan, vaikka mielestäni asia voi olla mitä tärkeintä säätelevää ja modifioivaa sekä todella tasapainottavaa vaikutusta ottaen huomioon millä tavalla nykyajan ihminen syö erilaisia absorboituvia mineraaleja ravinnossaan Tämä on oma mielipiteeni). Ruoan valmistuksen kuluessa voi IP6 osittain tai kokonaan hajota pienemmiksi fosfaateiksi. Sen takia prosessoidut ruoat sisältävät seoksen erilaisia inositolifosfaatteja, fosfaattiryhmiä on kuudesta alaspäin IP6, IP5, IP4, IP3, IP2, IP. Pelkkä fosfaattien kantoydin on polyalkoholi myo-inositoli Se on syklinen polyalkoholi, rengasrakenteinen. (Siis syklitolirenkaassa on kuudessa hiilessä kuusi alkoholiryhmää (OH).

Tämä väitöskirja käsittää kuvauksen IP6-molekyylistä ja sen hajoamisesta kohotetusta taikinasta tehtyä leipää valmistettaessa, sen hajomistuotteiden mineraaleja sitovista ominaisuuksista ja viljaperäisten ja mikrobiperäisten fytaasien vaikutuksesta IP6-hydrolyysissä ja ravinnon raudan imeytymisestä ihmisellä.

Fytaasientsyymi

Fytaasi on fytiinille spesifinen entsyymi. Kun tässä puhutaan IP6 -molekyylin entsymaattisesta hajoittamisesta, tarkoitetaan sivuketjujen, eri fosfaattiryhmien purkamisesta.

( ja samalla fosfaattien kiinnittämien mineraalien irtoamisesta eri PH miljöössä, fosfaattiryhmien pilkkoutumisestä irti syklitolista, joka itse ei tässä hajoa,  vaan sitten taas sopivassa tilanteessa kuten  ruoansulatuksen alavirrassa- kon ihminen on syönyt fytaasilla pilkkoutunutta  fytiiniä leivässään- kerää takaisin kudos- ja soluspesifisesti fosfaattia ja niihin mineraaleja riippuen uudesta fosfaattiryhmäkonformaatiosta.  Tutkimustyö  kohdistui  erilaisten pH-miljöiden merkitykseen tässä asiassa)

( Tässä käännän vain osia itse fytiinistä)

 

” Metallijonien Cu (2+), Zn (2+) ja Cd (2+) sitoutuminen inositolifosfaattien (IP6-IP3) eristettyihin fraktioihin tutkittiin pH 3-7 miljöössä. Kaikilla tutkituilla inositolifosfaattifraktioilla oli huomattavaa sitomiskykyä pH 5-7 miljöössä. Tämä osoittaa, että mineraalikompleksin muodostuminen uudestaan alemmissa polyfosfaateissa (IP4 ja IP3) saattaa tapahtua duodenumin alueella, mikä on ravitsemukselliselta kannalta tärkeää tietää, jos kerran nämä kompleksit saattavat estää mineraalien absorboitumista."

"Fytaasit ovat fosfataaseja.

Fytaasit, jotka pystyvät hydrolysoimaan IP6 molekyyliä, jolloin syntyy alempiasteisesti fosforyloituja inositolifosfaatteja. Tutkittiin sitä vaikutusta inositoliheksafosfaatin hydrolysaatioon, mikä viljan ( vehnän) ja mikrobien ( Aspergillus niger ja Saccharomyces cerevisiae) fytaaseilla vehnässä on.

Kun tehtiin endogeeninen vehnäfytaasin aktivaatio, Bakerin hiivan ( S.cerevisiae) lisäys ja erityisesti A.niger-peräisen fytaasin lisäys, aleni fytiinin (IP6) pitoisuus leivottaessa."

"Fytaasiaktiivisuuden mittaus

Tutkija kehitteli erityisen metodin, jolla voitiin määrätä fytaasin aktiviteetti

mittaamalla IP3 muodostusta. Koska eri fytaasit tuottavat erilaisia IP3-isomeerejä, tätä metodia voidaan myös käyttää erottamaan eri lähteistä tulevia fytaaseja.

Markkinoilla olevat S-cerevisiae- kannat ovat osoittautuneet kykeneviksi kehittämään fytaasiaktiviteettia, esim. kasvamaan synteettisessä mediumissa IP6 ainoana fosforilähteenä. Molemmat tutkitut kannat ilmensivät sellaista aineenvaihduntaa, joka oli hyvin sopeutunut IP6-peräisen fosfaatin hyväksikäyttöön.

Fytaasit osoittautuivat olevan 3-fytaasi tyyppiä eli fytaasit poistavat inositolirenkaan kolmoshiilessä olevan fosfaatin. Tästä seuraa hajoamistuotteet IP5, IP4 ja IP3, tarkemmin: DL-Ins ( 1, 2, 4, 5, 6)P5, DL-Ins (1, 2, 5, 6)P4 ja DL-Ins (1,2,6)P3.

//Huom: IP3 tarkoittaa, että inositoli on sitä sarjaa , jossa on kolme fosfaattiryhmää P. Mutta nämä kolme fosfaattiryhmää voivat sijaita monella eri tavalla myo-inositolirenkaassa. Elävässä solussa ne sijaitsevat usein asemissa 1,4 ja 5 ja IP3 voidaan tarkentaa: Ins (1,4,5) P3 ja se kuuluu tärkeimpiin signaalinvälittäjäaineisiin ihmissoluissa.

Jos P-kirjain on alussa, kuten PI, se tarkoittaa fosfatidyyliryhmää. Inositoli on silloin fosfatidyloitunut.  Jos P on I:n jäljessä, se tarkoittaa fosfaattia.Inositoli on fosforyloitunut. 

(Fosfatidyyli on fosfatidihapon (PA) happotähde ja sitä on fosfolipideissä vastaamassa rasvahappojen kantamisesta ja fosfolipidin kiinnittymisestä membraanirakenteisiin.muita fosfolipidejä ja membraanilipidejä  ovat fosfatidyylikoliini eli lesitiini, fosfatidyyliseriini ja fosfatidyylietanolamini eli kefaliini sekä sfingomyeliini. Mitokondrioissa on kardiolipiini. Inositolien fosfolipidejä sanotaan lipositoleiksi.) 

Kun PIP2 pilkkoutuu entsymaattisesti membraaneista esiin ja antaa IP3-molekyyliä ja toista molekyyliä DAG ja (diacylglyseroli) kaikki molekyylit jatkavat kiertokulkuaan ja uudelleen rakentumistaan ne ovat  kuin solukonelaitteen osia  signaalitehtävissä ja siksi niitä hyödynnetään ja kierrätetään, esim. PI muotoon takaisin ja sitten taas rasvaliukoisiksi membraaniosiksi (PIP, PIP2, PIP3) kun taas vesiliukoiset IPx fosfaatit omaavat funktioverkostonsa sytosolin puolella. Ne voivat myös rikastua jopa kantamaan 7 tai 8 fosfaattiakin. Mutta IP6 muoto on tärkeä siksi että siinä vaiheessa se pääsee solusta ulos ja munuaisiin asti ja tarvittaessa erittyy kehosta pois liikaa fosfaattia sen avulla. Rikastuneet insitolifosfaatit voivat antaa selustatukea jopa  ATP/GTP energiajärjestelmille. Sivumennen: Hai käyttää inositolienergiaa. Ihmisen harmaat aivosolut myös. Solutumissakin on näitä korkeaenergisiä inositolifosfaatteja. Oma muistiinpanoni //

”Vehnäfytaasin ja A-niger-fytaasin kyky lisätä raudan imeytymistä fytaattipitoisesta ateriasta tutkittiin radioisotooppitekniikalla koehenkilöiltä. Kun niitä fytaaseja lisättiin ravintoon juuri kun alettiin syödä, endogeenisella vehnäfytaasilla ei näyttänyt olleen tehoa, kun taas A.niger -fytaasin havaittiin huomattavasti lisäävän raudan imeytymistä.

Abstraktin avain sanat ovat: Fytaasi, fytiinin pilkkoutuminen, mineraalien sitoutuminen, raudan absorptio, vilja, dietääriset fytaasit, A.niger, S.cerevisiae.

(Johdanto-osasta löytyy perusteellista tietoa fytiinistä! Tekniikan paraneminen  johti syvällisempään tietoon fosfaattiaineenvaihdunnasta  niihin aikoinin! Tässähän on kyse  ihmisen bioenergiatason  virrankannon välittäjämolekyyleistä ja "maadutustavoista"  tietynlaisen elektroneutraaliuden pitämiseksi yllä eikä fosfaatti koskaan esiinny yksinään. Se on puskuriaines, toisaalta  se toimii vahvistajana  tarpeellisille Ca(2+)-stimuluksille.)

 

"Nyo-inositoli

Myo-inositoli molekyylillä on kaksi chiraalipuoliskoa. Sillä on C2 -ja C5 -hiilien kautta kulkevan tason suhteen symmetriaa. Jos C2 -tai C5- OH-substituoituu, se ei häiritse yhtäläisyyttä, sen sijaan muitten asemien substituutio johtaa chiraaliseen tuotteeseen, joka on merkittävä joko D- tai L-muodoksi. Chiraaliset agenssit, kuten entsyymit, pystyvät erottamaan näitä eri muotoja, D- tai L- isomeerejä, enantiomeereja. Aiemmin suositeltu numerointi oli sellainen, että pyrittiin matalimpiin subtituenttinumeroihin. Mutta nykyään suositellaan numerointi tehtävän D-muotoon ”counterclock wise”, vastapäivään Agranofin kilpikonnahahmoisessa molekyylissä (Agranofs turtle). Tämä kilpikonna oli kirjan kansikuvana.

Fosfatidyyli-ryhmä (Ptd) asettuu ykköskohtaan; ykköskohdan voi sijoittaa oikealle alakulmaan.

Tällöin Agranofin vuonna 1983 esitetty muistiapu kilpikonna katsoo oikealle, oikea tassu on 1-, pää 2-( aksiaalisen hydroksyylin paikka), vasen tassu 3-, vasen takatassu 4-, häntä 5-, ja oikea takatassu 6-hiilessä)

NC-IUB- nimitys ”ins” tarkoittaa D-konfiguraatiossa olevaa myo-inositolisa, ellei erikseen ole mainittu etuliite L. 

(jatkuu)