The role of GTP in transient splitting of 70S ribosomes by RRF (ribosome recycling factor) and EF-G (elongation factor G).

Ribosome recycling factor (RRF), elongation factor G (EF-G) and GTP split 70S ribosomes into subunits. Here, we demonstrated that the splitting was transient and the exhaustion of GTP resulted in re-association of the split subunits into 70S ribosomes unless IF3 (initiation factor 3) was present. However, the splitting was observed with sucrose density gradient centrifugation (SDGC) without IF3 if RRF, EF-G and GTP were present in the SDGC buffer. The splitting of 70S ribosomes causes the decrease of light scattering by ribosomes. Kinetic constants obtained from the light scattering studies are sufficient to account for the splitting of 70S ribosomes by RRF and EF-G/GTP during the lag phase for activation of ribosomes for the log phase. As the amount of 70S ribosomes increased, more RRF, EF-G and GTP were necessary to split 70S ribosomes. In the presence of a physiological amount of polyamines, GTP and factors, even 0.6 microM 70S ribosomes (12 times higher than the 70S ribosomes for routine assay) were split. Spermidine (2 mM) completely inhibited anti-association activity of IF3, and the RRF/EF-G/GTP-dependent splitting of 70S ribosomes

The ribosome-recycling step: consensus or controversy?

Ribosome recycling, the last step in translation, is now accepted as an essential process for prokaryotes. In 2005, three laboratories showed that ribosome-recycling factor (RRF) and elongation factor G (EF-G) cause dissociation of ribosomes into subunits, solving the long-standing problem of how this essential step of translation occurs. However, there remains ongoing controversy regarding the other actions of RRF and EF-G during ribosome recycling. We propose that the available data are consistent with the notion that RRF and EF-G not only split ribosomes into subunits but also participate directly in the release of deacylated tRNA and mRNA for the next round of translation

Ethnic Diversity, Democracy, and Health: Theory and Evidence

This paper examines the relationship between ethnic composition, political regimes, and the quality of public policy. Specifically, based on the citizen-candidate model, we assume individuals who have heterogeneous policy preferences and investigate how ethnic diversity affects selection of a politician and the resulting policy choices in democratic and dictatorial regimes. In the theoretical analysis, our model derives (1) a negative relationship between ethnic diversity and the quality of public policy, both in a democracy with a dominant group and in a dictatorship, and (2) a non-monotonic relationship in a democracy without a dominant group. In the empirical examination, using health outcomes as the proxy for the quality of public policy, our theoretical results are supported by evidence from the data of 154 countries.Citizen-candidate model; Ethnic fractionalization; Infant mortality.

Protein Electron Transfer Reorganization Energy Spectrum from Normal Mode Analysis. 2. Application to Ru-Modified Cytochrome c

In an accompanying paper (part 1) we presented a model (NMRES) that describes the coupling of protein fluctuations to electron transfer. The NMRES model, employing normal mode analysis that incorporates Tanford-Kirkwood reaction field energies, relates each normal mode to a mode-specific reorganization energy (λ k prot ), ultimately yielding a protein λ spectrum. In this paper we have successfully applied the NMRES model and analyzed intramolecular electron transfer in Ru-modified cytochrome c (at His33). The NMRES estimate for the total protein λ was found to be 15.6 kcal/mol, while the bulk solvent contribution was found to be 7.2 kcal/mol. Of this 15.6 kcal/mol, the high-frequency inner sphere protein modes contributed 3.2 kcal/mol (λ in prot ), while the remaining 12.4 kcal/mol (λ out prot ) arose from the low-frequency outer sphere protein modes, the focus of this paper. Out of about 600 "soft" low-frequency modes, 60% contributed very little, while the remaining 40% contributed more or less equally. There were no special soft modes in terms of contribution to λ out prot , structurally or energetically. In other words, although not all the soft modes contributed, those that did shared the coupling more or less equally, implying that minor changes in the dynamic structure will not alter the total λ significantly. This could be the reason that the experimental λ on Ru-modified (at various His sites) cytochrome c is found to be almost invariant

Sequence-dependent DNA deformability studied using molecular dynamics simulations

Proteins recognize specific DNA sequences not only through direct contact between amino acids and bases, but also indirectly based on the sequence-dependent conformation and deformability of the DNA (indirect readout). We used molecular dynamics simulations to analyze the sequence-dependent DNA conformations of all 136 possible tetrameric sequences sandwiched between CGCG sequences. The deformability of dimeric steps obtained by the simulations is consistent with that by the crystal structures. The simulation results further showed that the conformation and deformability of the tetramers can highly depend on the flanking base pairs. The conformations of xATx tetramers show the most rigidity and are not affected by the flanking base pairs and the xYRx show by contrast the greatest flexibility and change their conformations depending on the base pairs at both ends, suggesting tetramers with the same central dimer can show different deformabilities. These results suggest that analysis of dimeric steps alone may overlook some conformational features of DNA and provide insight into the mechanism of indirect readout during protein–DNA recognition. Moreover, the sequence dependence of DNA conformation and deformability may be used to estimate the contribution of indirect readout to the specificity of protein–DNA recognition as well as nucleosome positioning and large-scale behavior of nucleic acids

Amino acid residue doublet propensity in the protein–RNA interface and its application to RNA interface prediction

Protein–RNA interactions play essential roles in a number of regulatory mechanisms for gene expression such as RNA splicing, transport, translation and post-transcriptional control. As the number of available protein–RNA complex 3D structures has increased, it is now possible to statistically examine protein–RNA interactions based on 3D structures. We performed computational analyses of 86 representative protein–RNA complexes retrieved from the Protein Data Bank. Interface residue propensity, a measure of the relative importance of different amino acid residues in the RNA interface, was calculated for each amino acid residue type (residue singlet interface propensity). In addition to the residue singlet propensity, we introduce a new residue-based propensity, which gives a measure of residue pairing preferences in the RNA interface of a protein (residue doublet interface propensity). The residue doublet interface propensity contains much more information than the sum of two singlet propensities alone. The prediction of the RNA interface using the two types of propensities plus a position-specific multiple sequence profile can achieve a specificity of about 80%. The prediction method was then applied to the 3D structure of two mRNA export factors, TAP (Mex67) and UAP56 (Sub2). The prediction enables us to point out candidate RNA interfaces, part of which are consistent with previous experimental studies and may contribute to elucidation of atomic mechanisms of mRNA export

Early detection of pancreatic cancer by comprehensive serum miRNA sequencing with automated machine learning

血液中マイクロRNAによる膵がん診断法の開発に向けた研究 血中マイクロRNAの網羅的な解析により膵がん発症の有無を高精度に識別できる. 京都大学プレスリリース. 2024-08-28.Background: Pancreatic cancer is often diagnosed at advanced stages, and early-stage diagnosis of pancreatic cancer is difficult because of nonspecific symptoms and lack of available biomarkers. Methods: We performed comprehensive serum miRNA sequencing of 212 pancreatic cancer patient samples from 14 hospitals and 213 non-cancerous healthy control samples. We randomly classified the pancreatic cancer and control samples into two cohorts: a training cohort (N = 185) and a validation cohort (N = 240). We created ensemble models that combined automated machine learning with 100 highly expressed miRNAs and their combination with CA19-9 and validated the performance of the models in the independent validation cohort. Results: The diagnostic model with the combination of the 100 highly expressed miRNAs and CA19-9 could discriminate pancreatic cancer from non-cancer healthy control with high accuracy (area under the curve (AUC), 0.99; sensitivity, 90%; specificity, 98%). We validated high diagnostic accuracy in an independent asymptomatic early-stage (stage 0-I) pancreatic cancer cohort (AUC:0.97; sensitivity, 67%; specificity, 98%). Conclusions: We demonstrate that the 100 highly expressed miRNAs and their combination with CA19-9 could be biomarkers for the specific and early detection of pancreatic cancer

The status of MRI databases across the world focused on psychiatric and neurological disorders

Neuroimaging databases for neuro-psychiatric disorders enable researchers to implement data-driven research approaches by providing access to rich data that can be used to study disease, build and validate machine learning models, and even redefine disease spectra. The importance of sharing large, multi-center, multi-disorder databases has gradually been recognized in order to truly translate brain imaging knowledge into real-world clinical practice. Here, we review MRI databases that share data globally to serve multiple psychiatric or neurological disorders. We found 42 datasets consisting of 23,293 samples from patients with psychiatry and neurological disorders and healthy controls; 1245 samples from mood disorders (major depressive disorder and bipolar disorder), 2015 samples from developmental disorders (autism spectrum disorder, attention-deficit hyperactivity disorder), 675 samples from schizophrenia, 1194 samples from Parkinson's disease, 5865 samples from dementia (including Alzheimer's disease), We recognize that large, multi-center databases should include governance processes that allow data to be shared across national boundaries. Addressing technical and regulatory issues of existing databases can lead to better design and implementation and improve data access for the research community. The current trend toward the development of shareable MRI databases will contribute to a better understanding of the pathophysiology, diagnosis and assessment, and development of early interventions for neuropsychiatric disorders.journal articl

Separated Transcriptomes of Male Gametophyte and Tapetum in Rice: Validity of a Laser Microdissection (LM) Microarray

In flowering plants, the male gametophyte, the pollen, develops in the anther. Complex patterns of gene expression in both the gametophytic and sporophytic tissues of the anther regulate this process. The gene expression profiles of the microspore/pollen and the sporophytic tapetum are of particular interest. In this study, a microarray technique combined with laser microdissection (44K LM-microarray) was developed and used to characterize separately the transcriptomes of the microspore/pollen and tapetum in rice. Expression profiles of 11 known tapetum specific-genes were consistent with previous reports. Based on their spatial and temporal expression patterns, 140 genes which had been previously defined as anther specific were further classified as male gametophyte specific (71 genes, 51%), tapetum-specific (seven genes, 5%) or expressed in both male gametophyte and tapetum (62 genes, 44%). These results indicate that the 44K LM-microarray is a reliable tool to analyze the gene expression profiles of two important cell types in the anther, the microspore/pollen and tapetum

Serum anti-DIDO1, anti-CPSF2, and anti-FOXJ2 antibodies as predictive risk markers for acute ischemic stroke

Background Acute ischemic stroke (AIS) is a serious cause of mortality and disability. AIS is a serious cause of mortality and disability. Early diagnosis of atherosclerosis, which is the major cause of AIS, allows therapeutic intervention before the onset, leading to prevention of AIS. Methods Serological identification by cDNA expression cDNA libraries and the protein array method were used for the screening of antigens recognized by serum IgG antibodies in patients with atherosclerosis. Recombinant proteins or synthetic peptides derived from candidate antigens were used as antigens to compare serum IgG levels between healthy donors (HDs) and patients with atherosclerosis-related disease using the amplified luminescent proximity homogeneous assay-linked immunosorbent assay. Results The first screening using the protein array method identified death-inducer obliterator 1 (DIDO1), forkhead box J2 (FOXJ2), and cleavage and polyadenylation specificity factor (CPSF2) as the target antigens of serum IgG antibodies in patients with AIS. Then, we prepared various antigens including glutathione S-transferase-fused DIDO1 protein as well as peptides of the amino acids 297–311 of DIDO1, 426–440 of FOXJ2, and 607–621 of CPSF2 to examine serum antibody levels. Compared with HDs, a significant increase in antibody levels of the DIDO1 protein and peptide in patients with AIS, transient ischemic attack (TIA), and chronic kidney disease (CKD) but not in those with acute myocardial infarction and diabetes mellitus (DM). Serum anti-FOXJ2 antibody levels were elevated in most patients with atherosclerosis-related diseases, whereas serum anti-CPSF2 antibody levels were associated with AIS, TIA, and DM. Receiver operating characteristic curves showed that serum DIDO1 antibody levels were highly associated with CKD, and correlation analysis revealed that serum anti-FOXJ2 antibody levels were associated with hypertension. A prospective case–control study on ischemic stroke verified that the serum antibody levels of the DIDO1 protein and DIDO1, FOXJ2, and CPSF2 peptides showed significantly higher odds ratios with a risk of AIS in patients with the highest quartile than in those with the lowest quartile, indicating that these antibody markers are useful as risk factors for AIS. Conclusions Serum antibody levels of DIDO1, FOXJ2, and CPSF2 are useful in predicting the onset of atherosclerosis-related AIS caused by kidney failure, hypertension, and DM, respectively.journal articl