Primers used in fusion PCR to construct recombinant plasmids.

<p>Primers used in fusion PCR to construct recombinant plasmids.</p

RT-PCR analysis of singly (∼ 4.0 kb) and multiply (∼ 1.8 kb) spliced RNA species.

<p>Total cellular RNAs analyzed in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0078596#pone-0078596-g004" target="_blank">Figure 4</a> were subjected to semiquantitative RT-PCR. 4-16 µl of PCR products were heat-denatured, separated in 6% denaturing polyacrylamide gel, transferred onto GeneScreen Plus membrane, and then probed with [³²P]-labeled DNA oligonucleotide P131 that can recognize all HIV-1 RNA transcripts. The radioactive signals were visualized using a PhosphorImager. (A) Diagram showing the organization of major splice donor (SD1-5) and acceptor (SA1-8) sites, and the locations of viral exons and oligonucleotide primers on the HIV-1 genomic RNA. Filled boxes represent the exons detected in this study. The viral nucleotide numbers between 1 and 224 correspond to that of human immunodeficiency virus 1 (GenBank accession no. NC_001802). The viral nucleotide numbers between 225 and 9156 correspond to that between 1 and 8932 of human immunodeficiency virus type 1, isolate BH10 genome (GenBank accession no. M15654 K02008 K02009 K02010). (B) Analysis of ∼ 4.0 kb HIV-1 RNA species using primer pair Odp.045/KPNA. (C) Analysis of ∼ 1.8 kb HIV-1 RNA species using primer pair Odp.045/SJ4.7A. (D) Analysis of exon 6D-containing HIV-1 RNA species using primer pair Odp.045/3311A. Shown is a representative of 3 independent experiments.</p

Ability of mutant RHAs to promote the annealing of tRNA^Lys3 to viral RNA.

<p>293T cells were first treated with siRNA_Con or siRNA_RHA, and 16 hours later, were cotransfected with SVC21.BH10 and a plasmid expressing either 6×His tag, or His-tagged wild-type or mutant RHAs. 48 hours later, extracellular viruses were purified and cells were lysed. (A) Western blots of cell lysates probed with antibodies to RHA, His tag, or β-actin. (B) Western blots of viral lysates, containing equal amount of CAp24, probed with antibodies to RHA, His tag, CAp24, or RTp66/p51. (C) One nucleotide extension assay (+1 nt extension). Total viral RNA was isolated from purified HIV-1 particles, and tRNA^Lys3 annealed to viral RNA <i>in vivo</i> was extended by 1 nt ([³²P]-dCTP), using HIV-1 reverse transcriptase. The extended tRNA^Lys3 products are resolved by denaturing 1D PAGE, and visualized using a PhosphorImager. The control gel represents the +1 nt extension of a DNA primer annealed <i>in vitro</i> to viral RNA downstream of the tRNA^Lys3 binding site, and is used to show that approximately equal amounts of viral RNA were used in each extension reaction. (D) The values of the +1 nt extended tRNA^Lys3 products were quantitated using a PhosphorImager, normalized to the values obtained with virions produced from siRNA_Con-treated cells (lane 1), and are presented graphically as a percentage. Shown are the mean values ± standard deviations of 3 independent experiments. *, <i>P</i> < 0.05 compared with values obtained with virions produced from cells transfected with a plasmid expressing only His tag (lane 2).</p

Table_1_Association between gut microbiota and benign prostatic hyperplasia: a two-sample mendelian randomization study.xls

BackgroundRecent researches have shown a correlation between the gut microbiota (GM) and various diseases. However, it remains uncertain whether the relationship between GM and benign prostatic hyperplasia (BPH) is causal.MethodsWe carried out a two-sample Mendelian randomization (MR) analysis, utilizing data from the most extensive GM-focused genome-wide association study by the MiBioGen consortium, with a sample size of 13,266. Data for BPH, encompassing 26,358 cases and 110,070 controls, were obtained from the R8 release of the FinnGen consortium. We employed multiple techniques, such as inverse variance weighted (IVW), constrained maximum likelihood and model averaging methods, maximum likelihood, MR-Pleiotropy RESidual Sum and Outlier (MRPRESSO),MR-Egger, and weighted median methods, to investigate the causal relationship between GM and BPH. To evaluate the heterogeneity among the instrumental variables, Cochran’s Q statistics were employed. Additionally, the presence of horizontal pleiotropy was assessed through the application of both MR-Egger and MR-PRESSO tests. The direction of causality was scrutinized for robustness using the MR-Steiger directionality test. A reverse MR analysis examined the GM previously linked to BPH through a causal relationship in the forward MR assessment.ResultsAccording to the analysis conducted using IVW,Eisenbergiella (odds ratio [OR]=0.92, 95% confidence interval [CI]: 0.85–0.99,P=0.022) and Ruminococcaceae (UCG009) (OR=0.88, 95% CI: 0.79–0.99, P=0.027) were found to reduce the risk of BPH, while Escherichia shigella (OR=1.19, 95% CI: 1.05–1.36, P=0.0082) appeared to increase it. The subsequent reverse MR analysis revealed that the three GM were not significantly influenced by BPH, and there was no noticeable heterogeneity or horizontal pleiotropy among the instrumental variables.Conclusion: These results indicated a causal relationship between Eisenbergiella, Ruminococcaceae (UCG009), and Escherichia shigella and BPH. Further randomized controlled trials are needed to explore more comprehensively the roles and operational mechanisms of these GM in relation to BPH.</p

DataSheet_1_Association between gut microbiota and benign prostatic hyperplasia: a two-sample mendelian randomization study.docx

BackgroundRecent researches have shown a correlation between the gut microbiota (GM) and various diseases. However, it remains uncertain whether the relationship between GM and benign prostatic hyperplasia (BPH) is causal.MethodsWe carried out a two-sample Mendelian randomization (MR) analysis, utilizing data from the most extensive GM-focused genome-wide association study by the MiBioGen consortium, with a sample size of 13,266. Data for BPH, encompassing 26,358 cases and 110,070 controls, were obtained from the R8 release of the FinnGen consortium. We employed multiple techniques, such as inverse variance weighted (IVW), constrained maximum likelihood and model averaging methods, maximum likelihood, MR-Pleiotropy RESidual Sum and Outlier (MRPRESSO),MR-Egger, and weighted median methods, to investigate the causal relationship between GM and BPH. To evaluate the heterogeneity among the instrumental variables, Cochran’s Q statistics were employed. Additionally, the presence of horizontal pleiotropy was assessed through the application of both MR-Egger and MR-PRESSO tests. The direction of causality was scrutinized for robustness using the MR-Steiger directionality test. A reverse MR analysis examined the GM previously linked to BPH through a causal relationship in the forward MR assessment.ResultsAccording to the analysis conducted using IVW,Eisenbergiella (odds ratio [OR]=0.92, 95% confidence interval [CI]: 0.85–0.99,P=0.022) and Ruminococcaceae (UCG009) (OR=0.88, 95% CI: 0.79–0.99, P=0.027) were found to reduce the risk of BPH, while Escherichia shigella (OR=1.19, 95% CI: 1.05–1.36, P=0.0082) appeared to increase it. The subsequent reverse MR analysis revealed that the three GM were not significantly influenced by BPH, and there was no noticeable heterogeneity or horizontal pleiotropy among the instrumental variables.Conclusion: These results indicated a causal relationship between Eisenbergiella, Ruminococcaceae (UCG009), and Escherichia shigella and BPH. Further randomized controlled trials are needed to explore more comprehensively the roles and operational mechanisms of these GM in relation to BPH.</p

The Effect of <i>MUC1</i> rs4072037 Functional Polymorphism on Cancer Susceptibility: Evidence from Published Studies

<div><p>Genome-wide association studies have identified a susceptibility variation <i>MUC1</i> rs4072037 for gastric cancer in Chinese population. Subsequent case-control studies have reported this association in other populations. However, the results remain controversial and ambiguous. The aim of this study is to provide a precise quantification for the association between <i>MUC1</i> rs4072037 variation and the risk of cancer. We performed pooled analysis of 10 case-control designed studies including 4,220 cases and 6,384 controls. Odds ratios (OR) and 95% confidence interval (95%CI) were calculated to assess strength of association in overall studies and in subgroup analysis stratified by ethnicity and cancer types. All statistical analyses were performed by Manager 5.0 and Stata 12.0 software. Overall, the <i>MUC1</i> rs4072037 polymorphism was associated with risk of cancer in all genetic models (G vs A: OR = 0.71, 95%CI: 0.63–0.80, <i>p</i><0.01; GA vs AA: OR = 0.61, 95%CI:0.55–0.67, <i>p</i><0.01; GG vs AA: OR = 0.58, 95%CI: 0.47–0.71, <i>p</i><0.01; AG+AA vs GG: OR = 0.60, 95%CI: 0.55–0.60, <i>p</i><0.01; GG vs AG+AA: OR = 0.70, 95%CI: 0.58–0.85, <i>p</i><0.01). Further, subgroup analysis based on ethnicity suggested <i>MUC1</i> rs4072037 polymorphism had a subtly reduced cancer risk among Asian population, and stratified analysis by cancer types showed significantly decreased risk of gastric cancer in all genetic models. In conclusion, <i>MUC1</i> rs4072037 polymorphism may be used as potential biomarker for cancer susceptibility particularly for gastric cancer and for Asian population.</p></div

The Significance of <i>Exo1</i> K589E Polymorphism on Cancer Susceptibility: Evidence Based on a Meta-Analysis

<div><p>The exonuclease1 (<i>Exo1</i>) gene is a key component of mismatch repair (MMR) by resecting the damaged strand, which is the only exonuclease involved in the human MMR system. The gene product is a member of the RAD2 nuclease family and functions in DNA replication, repair and recombination. However, whether <i>Exo1</i> is required to activate MMR-dependent DNA damage response (DDR) remains unknown, the conclusions of the <i>Exo1</i> polymorphisms on cancer susceptibility studies were not consistent. We carried out a meta-analysis of 7 case-control studies to clarify the association between the <i>Exo1</i> K589E polymorphism and cancer risk. Overall,a significant association of the <i>Exo1</i> K589E polymorphism with cancer risk in all genetic models (Lys vs Glu: OR = 1.51, 95%CI:1.39–1.99, <i>P</i><0.01; Glu/Lys vs Glu/Glu: OR = 1.43, 95%CI:1.28–1.60, <i>P</i><0.01; Lys/Lys vs Glu/Glu: OR = 2.45, 95%CI:1.90–3.17, <i>P</i><0.01; Lys/Lys+Glu/Lys vs Glu/Glu: OR = 1.53, 95%CI:1.38–1.71, <i>P</i><0.01; Glu/Glu vs Glu/Lys+Lys/Lys: OR =  2.27, 95%CI:1.79–2.89, <i>P</i><0.01). In the stratified analysis by ethnicity, significantly increased risk was observed in Asian population (Lys vs Glu: OR = 1.53, 95%CI:1.39–1.69, <i>P</i><0.01; Glu/Lys vs Glu/Glu: OR = 1.50, 95%CI:1.34–1.69, <i>P</i><0.01; Lys/Lys vs Glu/Glu: OR = 2.48, 95%CI:1.84–3.34, <i>P</i><0.01; Lys/Lys+Glu/Lys vs Glu/Glu: OR = 1.58, 95%CI:1.41–1.78, <i>P</i><0.01; Glu/Glu vs Glu/Lys+Lys/Lys: OR = 2.18, 95%CI:1.62–2.93, <i>P</i><0.01). Subgroup analysis based on smoking suggested <i>Exo1</i> K589E polymorphism conferred significant risk among smokers (Lys/Lys+Glu/Lys vs Glu/Glu: OR = 2.16, 95%CI:1.77–2.63, <i>P</i><0.01), but not in non-smokers (Lys/Lys+Glu/Lys vs Glu/Glu: OR = 0.89, 95%CI:0.64–1.24, <i>P</i> = 0.50). In conclusion, <i>Exo1</i> K589E Lys allele may be used as a novel biomarker for cancer susceptibility, particularly in smokers.</p></div