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Noda, K.

Publications and source records attributed to Noda, K..

2 recordsLinked to original sources
bioRxiv2023

NEDD4-binding protein 1 suppresses HBV replication by degrading pgRNA

Chronic infection with hepatitis B virus (HBV) places patients at increased risk for liver cirrhosis and hepatocellular carcinoma. Although nucleos(t)ide analogs are mainly used for the treatment of HBV, they require long-term administration and may lead to the emergence of drug resistant mutants. Therefore, to identify targets for the development of novel anti-HBV drugs, we screened for HBV-suppressive host factors using a plasmid expression library of RNA-binding proteins (RBPs). We screened 132 RBPs using an expression plasmid library by measuring HBV relaxed circular DNA (rcDNA) levels in hepatocellular carcinoma. Our screen identified NEDD4-binding protein 1 (N4BP1) as having an anti-HBV effect. In hepatocellular carcinoma cell lines transfected or infected with HBV, overexpression of N4BP1 decreased rcDNA levels while knockdown or knockout of the gene encoding N4BP1 rescued rcDNA levels. N4BP1 possesses the KH-like and RNase domains and both were required for the anti-HBV effect of N4BP1. Additionally, we measured levels of HBV pregenomic RNA (pgRNA) and covalently closed circular DNA (cccDNA) in the RBP-transfected cells and confirmed that N4BP1 binds pgRNA directly and degraded both the 3.5 kb and 2.4/2.1 kb HBV RNA. In summary, N4BP1 is a newly identified host factor able to counteract HBV production by promoting the degradation of 3.5 kb and 2.1/2.4 kb HBV RNA. ImportanceThere is still a large number of HBV-infected people in the world today because of no curative treatment for HBV infection. In this study, we focused on and screened RNA-binding proteins to identify new host factors which inhibit HBV replication. As a result, we found that NEDD4-binding protein 1 (N4BP1) expression suppresses rcDNA production by promoting the degradation of pregenomic RNA, 2.4kb and 2.1kb HBV RNA. Furthermore, KH-like domain or RNase domain of N4BP1 were involved in this anti-HBV effect. In addition, the N4BP1 levels were lower in HCC resection samples of exacerbated patients, suggesting that individual N4BP1 levels might be related to HCC progression. This novel factor can potentially become a key to new HBV treatments.

microbiology↗
bioRxiv2022

Validating the representation of distance between infarctdiseases using Word2Vec word embedding

ObjectiveTo determine if inter-disease distances between word embedding vectors using the picot-and-cluster strategy (PCS) are a valid quantitative representation of similar disease groups in a limited domain. Materials and MethodsAbstracts were extracted from the Ichushi-Web database and subjected to morphological analysis and training using the Word2Vec. From this, word embedding vectors were obtained. For words including "infarction", we calculated the cophenetic correlation coefficient (CCC) as an internal validity measure and the adjusted rand index (ARI), normalized mutual information (NMI), and adjusted mutual information (AMI) with ICD-10 codes as the external validity measures. This was performed for each combination of metric and hierarchical clustering method. ResultsSeventy-one words included "infarction", of which 38 diseases matched the ICD-10 standard with the appearance of 21 unique ICD-10 codes. The CCC was most significant at 0.8690 (metric and method: euclidean and centroid), while the AMI was maximal at 0.4109 (metric and method: cosine and correlation, and average and weighted). The NMI and ARI were maximal at 0.8463 and 0.3593, respectively (metric and method: cosine and complete). DiscussionThe metric and method that maximized the internal validity measure were different from those that maximized the external validity measures; both produced different results. The Cosine distance should be used when considering ICD-10, and the Euclidean distance when considering the frequency of word occurrence. ConclusionThe distributed representation, when trained by Word2Vec on the "infarction" domain from a Japanese academic corpus, provides an objective inter-disease distance used in PCS.

bioinformatics↗