Additional file 2 of Mutational Bias and Natural Selection Driving the Synonymous Codon Usage of Single-Exon Genes in Rice (Oryza sativa L.)

Additional file 2. Table 2 The dissection of ENC values of single-exon genes and multiple-exon genes in rice

Additional file 1 of Mutational Bias and Natural Selection Driving the Synonymous Codon Usage of Single-Exon Genes in Rice (Oryza sativa L.)

Additional file 1. Table 1 The gene ID of single-exon genes and multiple-exon genes in rice

Additional file 4 of Mutational Bias and Natural Selection Driving the Synonymous Codon Usage of Single-Exon Genes in Rice (Oryza sativa L.)

Additional file 4. Table 3. Paralogous gene pairs consisting of single-exon genes and multiple-exon genes generated via segmental and tandem duplications

Additional file 1 of Peripatric speciation within Torreya fargesii (Taxaceae) in the Hengduan Mountains inferred from multi-loci phylogeography

Supplementary Material

Additional file 3 of Mutational Bias and Natural Selection Driving the Synonymous Codon Usage of Single-Exon Genes in Rice (Oryza sativa L.)

Additional file 3. Figure 1. Internal correspondence analysis of single-exon genes with different gene expression level in rice. The total codon usage variability is decomposed into the synonymous codon usage variability (a, d, g), amino acid usage variability (b, e, h), and variability of within (a, b, c) and between different gene expression groups (d, e, f). The performance of ICA yields nine elementary analyses (a-i). In each peculiar analysis, the contribution to the total codon usage variability is indicated, where only the first 10 eigenvalues are represented for comparison. Figure 2. Internal correspondence analysis of single-exon genes with different gene function in rice. The total codon usage variability is decomposed into the synonymous codon usage variability (a, d, g), amino acid usage variability (b, e, h), and variability of within (a, b, c) and between different gene function groups (d, e, f). The performance of ICA yields nine elementary analyses (a-i). In each peculiar analysis, the contribution to the total codon usage variability is indicated, where only the first 10 eigenvalues are represented for comparison. Figure 3. Internal correspondence analysis of single-exon genes and multiple-exon genes in rice. In this analysis, the 581 paralogous gene pairs of single-exon genes and multiple-exon genes are excluded from the dataset. The total codon usage variability is decomposed into the synonymous codon usage (within-AA) variability (a, d, g), amino acid usage (between-AA) variability (b, e, h), and variability of within (a, b, c) and between gene types (d, e, f). In each peculiar analysis, the contribution to the total codon usage variation is indicated, where only the first 10 eigenvalues are represented for comparison

MOESM1 of Regioselectivity of oxidation by a polysaccharide monooxygenase from Chaetomium thermophilum

Additional file 1: Figure S1. SDS-PAGE of the purified Cu2+-CtPMO1 produced in Pichia pastoris. Figure S2. The N-terminal amino acid sequence analysis of CtPMO1 using LC-MS/MS. Figure S3. MALDI-TOF-MS/MS analysis of m/z 525 from MALDI-TOF-MS analysis. Figure S4. Types of fragmentation of CtPMO1 C4- and C6-oxidized products (m/z 525). Figure S5. 1H NMR spetra of CtPMO1 soluble reaction products with PASC as substrate in DMSO-d 6 . Figure S6. Sequence alignment of CtPMO1 and NCLPMO9C using ClastalW2. Figure S7. Homology model of the catalytic domain of CtPMO1 using SWISS-MODEL. Figure S8. Homology model of CtPMO1 binding with cellopentaose. Figure S9. Identification of the mutated CtPMO1 soluble reaction products oxidized by Br2 using with PASC as substrate MALDI-TOF-MS. Table S1. List of primers used for PCR of the CtPMO1 protein. Table S2. Fragmentation analysis of the peak of DP3-2 (m/z 525) according to Additional file 1: Figure S3, S4

Data_Sheet_1_Ideal serum non-ceruloplasmin bound copper prediction for long-term treated patients with Wilson disease: a nomogram model.docx

PurposeThis study aimed to explore the factors associated with the optimal serum non-ceruloplasmin bound copper (NCBC) level and develop a flexible predictive model to guide lifelong therapy in Wilson disease (WD) and delay disease progression.MethodsWe retrospectively collected clinical data from 144 patients hospitalized in the Encephalopathy Center of the first affiliated hospital of Anhui University of Chinese Medicine between May 2012 and April 2023. Independent variables were selected using variate COX and LASSO regressions, followed by multivariate COX regression analysis. A predictive nomogram was constructed and validated using the concordance index (C-index), calibration curves, and clinical decision curve analysis, of which nomogram pictures were utilized for model visualization.ResultsA total of 61 (42.36%) patients were included, with an average treatment duration of 55.0 (range, 28.0, 97.0) months. Multivariate regression analysis identified several independent risk factors for serum NCBC level, including age of diagnosis, clinical classification, laminin liver stiffness measurement, and copper to zinc ratio in 24-h urinary excretion. The C-index indicated moderate discriminative ability (48 months: 0.829, 60 months: 0.811, and 72 months: 0.819). The calibration curves showed good consistency and calibration; clinical decision curve analysis demonstrated clinically beneficial threshold probabilities at different time intervals.ConclusionThe predictive nomogram model can predict serum NCBC level; consequently, we recommend its use in clinical practice to delay disease progression and improve the clinical prognosis of WD.</p

Exploring the Molecular Mechanism of Cross-Resistance to HIV‑1 Integrase Strand Transfer Inhibitors by Molecular Dynamics Simulation and Residue Interaction Network Analysis

The rapid emergence of cross-resistance to the integrase strand transfer inhibitors (INSTIs) has become a serious problem in the therapy of human immunodeficiency virus type 1 (HIV-1) infection. Understanding the detailed molecular mechanism of INSTIs cross-resistance is therefore critical for the development of new effective therapy against cross-resistance. On the basis of the homology modeling constructed structure of tetrameric HIV-1 intasome, the detailed molecular mechanism of the cross-resistance mutation E138K/Q148K to three important INSTIs (Raltegravir (RAL, FDA approved in 2007), Elvitegravir (EVG, FDA approved in 2012), and Dolutegravir (DTG, phase III clinical trials)) was investigated by using molecular dynamics (MD) simulation and residue interaction network (RIN) analysis. The results from conformation analysis and binding free energy calculation can provide some useful information about the detailed binding mode and cross-resistance mechanism for the three INSTIs to HIV-1 intasome. Binding free energy decomposition analysis revealed that Pro145 residue in the 140s 1oop (Gly140 to Gly149) of the HIV-1 intasome had strong hydrophobic interactions with INSTIs and played an important role in the binding of INSTIs to HIV-1 intasome active site. A systematic comparison and analysis of the RIN proves that the communications between the residues in the resistance mutant is increased when compared with that of the wild-type HIV-1 intasome. Further analysis indicates that residue Pro145 may play an important role and is relevant to the structure rearrangement in HIV-1 intasome active site. In addition, the chelating ability of the oxygen atoms in INSTIs (e.g., RAL and EVG) to Mg²⁺ in the active site of the mutated intasome was reduced due to this conformational change and is also responsible for the cross-resistance mechanism. Notably, the cross-resistance mechanism we proposed could give some important information for the future rational design of novel INSTIs overcoming cross-resistance. Furthermore, the combination use of molecular dynamics simulation and residue interaction network analysis can be generally applicable to investigate drug resistance mechanism for other biomolecular systems

Image_8_Immunogenic landscape and risk score prediction based on unfolded protein response (UPR)-related molecular subtypes in hepatocellular carcinoma.jpg

BackgroundHepatocellular carcinoma (HCC) is the most common type of cancer and causes a significant number of cancer-related deaths worldwide. The molecular mechanisms underlying the development of HCC are complex, and the heterogeneity of HCC has led to a lack of effective prognostic indicators and drug targets for clinical treatment of HCC. Previous studies have indicated that the unfolded protein response (UPR), a fundamental pathway for maintaining endoplasmic reticulum homeostasis, is involved in the formation of malignant characteristics such as tumor cell invasiveness and treatment resistance. The aims of our study are to identify new prognostic indicators and provide drug treatment targets for HCC in clinical treatment based on UPR-related genes (URGs).MethodsGene expression profiles and clinical information were downloaded from the TCGA, ICGC and GEO databases. Consensus cluster analysis was performed to classify the molecular subtypes of URGs in HCC patients. Univariate Cox regression and machine learning LASSO algorithm were used to establish a risk prognosis model. Kaplan–Meier and ROC analyses were used to evaluate the clinical prognosis of URGs. TIMER and XCell algorithms were applied to analyze the relationships between URGs and immune cell infiltration. Real time-PCR was performed to analyze the effect of sorafenib on the expression levels of four URGs.ResultsMost URGs were upregulated in HCC samples. According to the expression pattern of URGs, HCC patients were divided into two independent clusters. Cluster 1 had a higher expression level, worse prognosis, and higher expression of immunosuppressive factors than cluster 2. Patients in cluster 1 were more prone to immune escape during immunotherapy, and were more sensitive to chemotherapeutic drugs. Four key UPR genes (ATF4, GOSR2, PDIA6 and SRPRB) were established in the prognostic model and HCC patients with high risk score had a worse clinical prognosis. Additionally, patients with high expression of four URGs are more sensitive to sorafenib. Moreover, ATF4 was upregulated, while GOSR2, PDIA6 and SRPRB were downregulated in sorafenib-treated HCC cells.ConclusionThe UPR-related prognostic signature containing four URGs exhibits high potential application value and performs well in the evaluation of effects of chemotherapy/immunotherapy and clinical prognosis.</p

Logic Nanodevice-Mediated Receptor Assembly for Nongenetic Regulation of Cell Behavior in Tumor-like Microenvironment

The reprogramming of cell signaling and behavior through the artificial control of cell surface receptor oligomerization shows great promise in biomedical research and cell-based therapy. However, it remains challenging to achieve combinatorial recognition in a complicated environment and logical regulation of receptors for desirable cellular behavior. Herein, we develop a logic-gated DNA nanodevice with responsiveness to multiple environmental inputs for logically controlled assembly of heterogeneous receptors to modulate signaling. The “AND” gate nanodevice uses an i-motif and an ATP-binding aptamer as environmental cue-responsive units, which can successfully implement a logic operation to manipulate receptors on the cell surface. In the presence of both protons and ATP, the DNA nanodevice is activated to selectively assemble MET and CD71, which modulate the HGF/MET signaling, resulting in cytoskeletal reorganization to inhibit cancer cell motility in a tumor-like microenvironment. Our strategy would be highly promising for precision therapeutics, including controlled drug release and cancer treatment