Dynamic localization of a yeast development–specific PP1 complex during prospore membrane formation is dependent on multiple localization signals and complex formation

During the developmental process of sporulation in Saccharomyces cerevisiae, membrane structures called prospore membranes are formed de novo, expand, extend, acquire a round shape, and finally become plasma membranes of the spores. GIP1 encodes a regulatory/targeting subunit of protein phosphatase type 1 that is required for sporulation. Gip1 recruits the catalytic subunit Glc7 to septin structures that form along the prospore membrane; however, the molecular basis of its localization and function is not fully understood. Here we show that Gip1 changes its localization dynamically and is required for prospore membrane extension. Gip1 first associates with the spindle pole body as the prospore membrane forms, moves onto the prospore membrane and then to the septins as the membrane extends, distributes around the prospore membrane after closure, and finally translocates into the nucleus in the maturing spore. Deletion and mutation analyses reveal distinct sequences in Gip1 that are required for different localizations and for association with Glc7. Binding to Glc7 is also required for proper localization. Strikingly, localization to the prospore membrane, but not association with septins, is important for Gip1 function. Further, our genetic analysis suggests that a Gip1–Glc7 phosphatase complex regulates prospore membrane extension in parallel to the previously reported Vps13, Spo71, Spo73 pathway

Single-Cell Analysis of the Multicellular Ecosystem in Viral Carcinogenesis by HTLV-1

成人T細胞白血病リンパ腫の多段階発がん分子メカニズムを解明 --難治性疾患の新規治療標的候補を複数同定--. 京都大学プレスリリース. 2021-09-07.Premalignant clonal expansion of human T-cell leukemia virus type-1 (HTLV-1)–infected cells occurs before viral carcinogenesis. Here we characterize premalignant cells and the multicellular ecosystem in HTLV-1 infection with and without adult T-cell leukemia/lymphoma (ATL) by genome sequencing and single-cell simultaneous transcriptome and T/B-cell receptor sequencing with surface protein analysis. We distinguish malignant phenotypes caused by HTLV-1 infection and leukemogenesis and dissect clonal evolution of malignant cells with different clinical behavior. Within HTLV-1–infected cells, a regulatory T-cell phenotype associates with premalignant clonal expansion. We also delineate differences between virus- and tumor-related changes in the nonmalignant hematopoietic pool, including tumor-specific myeloid propagation. In a newly generated conditional knockout mouse model recapitulating T-cell–restricted CD274 (encoding PD-L1) gene lesions found in ATL, we demonstrate that PD-L1 overexpressed by T cells is transferred to surrounding cells, leading to their PD-L1 upregulation. Our findings provide insights into clonal evolution and immune landscape of multistep virus carcinogenesis

Integrated genetic and clinical prognostic factors for aggressive adult T-cell leukemia/lymphoma

成人T細胞白血病リンパ腫（ATL）におけるゲノム情報と臨床情報を統合したリスクモデルを確立 --ATLの個別化医療を推進--. 京都大学プレスリリース. 2023-04-10.The prognosis of aggressive adult T-cell leukemia/lymphoma (ATL) is poor, and allogeneic hematopoietic stem-cell transplantation (allo-HSCT) is a curative treatment. To identify favorable prognostic patients after intensive chemotherapy, and who therefore might not require upfront allo-HSCT, we aimed to improve risk stratification of aggressive ATL patients aged <70 years. The clinical risk factors and genetic mutations were incorporated into risk modeling for overall survival (OS). We generated the m7-ATLPI, a clinicogenetic risk model for OS, that included the ATL prognostic index (PI) (ATL-PI) risk category, and non-silent mutations in seven genes, namely TP53, IRF4, RHOA, PRKCB, CARD11, CCR7, and GATA3. In the training cohort of 99 patients, the m7-ATLPI identified a low-, intermediate-, and high-risk group with 2-year OS of 100%, 43%, and 19%, respectively (hazard ratio [HR] 5.46, p < 0.0001). The m7-ATLPI achieved superior risk stratification compared to the current ATL-PI (C-index 0.92 vs. 0.85, respectively). In the validation cohort of 84 patients, the m7-ATLPI defined low-, intermediate-, and high-risk groups with a 2-year OS of 81%, 30%, and 0%, respectively (HR 2.33, p = 0.0094), and the model again outperformed the ATL-PI (C-index 0.72 vs. 0.70, respectively). The simplified m7-ATLPI, which is easier to use in clinical practice, achieved superior risk stratification compared to the ATL-PI, as did the original m7-ATLPI; the simplified version was calculated by summing the following: high-risk ATL-PI category (+10), low-risk ATL-PI category (−4), and non-silent mutations in TP53 (+4), IRF4 (+3), RHOA (+1), PRKCB (+1), CARD11 (+0.5), CCR7 (−2), and GATA3 (−3)

Omecamtiv mecarbil in chronic heart failure with reduced ejection fraction, GALACTIC‐HF: baseline characteristics and comparison with contemporary clinical trials

Aims: The safety and efficacy of the novel selective cardiac myosin activator, omecamtiv mecarbil, in patients with heart failure with reduced ejection fraction (HFrEF) is tested in the Global Approach to Lowering Adverse Cardiac outcomes Through Improving Contractility in Heart Failure (GALACTIC‐HF) trial. Here we describe the baseline characteristics of participants in GALACTIC‐HF and how these compare with other contemporary trials. Methods and Results: Adults with established HFrEF, New York Heart Association functional class (NYHA) ≥ II, EF ≤35%, elevated natriuretic peptides and either current hospitalization for HF or history of hospitalization/ emergency department visit for HF within a year were randomized to either placebo or omecamtiv mecarbil (pharmacokinetic‐guided dosing: 25, 37.5 or 50 mg bid). 8256 patients [male (79%), non‐white (22%), mean age 65 years] were enrolled with a mean EF 27%, ischemic etiology in 54%, NYHA II 53% and III/IV 47%, and median NT‐proBNP 1971 pg/mL. HF therapies at baseline were among the most effectively employed in contemporary HF trials. GALACTIC‐HF randomized patients representative of recent HF registries and trials with substantial numbers of patients also having characteristics understudied in previous trials including more from North America (n = 1386), enrolled as inpatients (n = 2084), systolic blood pressure &lt; 100 mmHg (n = 1127), estimated glomerular filtration rate &lt; 30 mL/min/1.73 m2 (n = 528), and treated with sacubitril‐valsartan at baseline (n = 1594). Conclusions: GALACTIC‐HF enrolled a well‐treated, high‐risk population from both inpatient and outpatient settings, which will provide a definitive evaluation of the efficacy and safety of this novel therapy, as well as informing its potential future implementation

Super-Resolution and Feature Extraction for Ocean Bathymetric Maps Using Sparse Coding

The comprehensive production of detailed bathymetric maps is important for disaster prevention, resource exploration, safe navigation, marine salvage, and monitoring of marine organisms. However, owing to observation difficulties, the amount of data on the world’s seabed topography is scarce. Therefore, it is essential to develop methods that effectively use the limited data. In this study, based on dictionary learning and sparse coding, we modified the super-resolution technique and applied it to seafloor topographical maps. Improving on the conventional method, before dictionary learning, we performed pre-processing to separate the teacher image into a low-frequency component that has a general structure and a high-frequency component that captures the detailed topographical features. We learn the topographical features by training the dictionary. As a result, the root-mean-square error (RMSE) was reduced by 30% compared with bicubic interpolation and accuracy was improved, especially in the rugged part of the terrain. The proposed method, which learns a dictionary to capture topographical features and reconstructs them using a dictionary, produces super-resolution with high interpretability