Artificial tethering of constitutive centromere-associated network proteins induces CENP-A deposition without Knl2 in DT40 cells.

The kinetochore is an essential structure for chromosome segregation. Although the kinetochore is usually formed on a centromere locus, it can be artificially formed at a non-centromere locus by protein tethering. An artificial kinetochore can be formed by tethering of CENP-C or CENP-I, members of the constitutive centromere-associated network (CCAN). However, how CENP-C or CENP-I recruit the centromere-specific histone CENP-A to form an artificial kinetochore remains unclear. In this study, we analyzed this issue using the tethering assay combined with an auxin-inducible degron (AID)-based knockout method in chicken DT40 cells. We found that tethering of CENP-C or CENP-I induced CENP-A incorporation at the non-centromeric locus in the absence of Knl2 (or MIS18BP1), a component of the Mis18 complex, and that Knl2 tethering recruited CENP-A in the absence of CENP-C. We also showed that CENP-C coimmunoprecipitated with HJURP, independently of Knl2. Considering these results, we propose that CENP-C recruits CENP-A by HJURP binding to form an artificial kinetochore. Our results suggest that CENP-C or CENP-I exert CENP-A recruitment activity, independently of Knl2, for artificial kinetochore formation in chicken DT40 cells. This gives us a new insight into mechanisms for CENP-A incorporation.

Essentiality of CENP-A Depends on Its Binding Mode to HJURP.

CENP-A incorporation is critical for centromere specification and is mediated by the chaperone HJURP. The CENP-A-targeting domain (CATD) of CENP-A specifically binds to HJURP, and this binding is conserved. However, the binding interface of CENP-A-HJURP is yet to be understood. Here, we identify the critical residues for chicken CENP-A or HJURP. The A59Q mutation in the α1-helix of chicken CENP-A causes CENP-A mis-incorporation and subsequent cell death, whereas the corresponding mutation in human CENP-A does not. We also find that W53 of HJURP, which is a contact site of A59 in CENP-A, is also essential in chicken cells. Our comprehensive analyses reveal that the affinities of HJURP to CATD differ between chickens and humans. However, the introduction of two arginine residues to the chicken HJURP αA-helix suppresses CENP-A mis-incorporation in chicken cells expressing CENP-AA59Q. Our data explain the mechanisms and evolution of CENP-A essentiality by the CENP-A-HJURP interaction.

Dietary Safety Assessment of Flk1-Transgenic Fish.

Genetic engineering, also called genetic modification, is facing with growing demands of aquaculture and aquatic products. Although various genetically modified (GM) aquatics have been generated, it is important to evaluate biosafety of GM organisms on the human health before entering into our food chain. For this purpose, we establish a zebrafish wild adult feeding Flk1-transgenic larvae model to examine the predatory fish's histology in multiple tissues, and the global gene expression profile in the liver. 180 days of feeding trial show that there are no significantly morphological changes in intestine, liver, kidney, and sex gonads between fish fed with Flk1 transgenic fish diet (TFD) and fish fed with regular food meal (RFM). However, a characteristic skin spot and autofluorescence increase in the theca of follicle are observed in F1 generation of TFD fish. Liver RNA-sequencing analyses demonstrate that 53 out of 56712 genes or isoforms are differentially transcribed, and mostly involved in proteolysis in extracellular region. According to GO enrichment terms these deregulated genes function in catalytic activity, steroid storing, lipid metabolic process and N-Glycan biosynthesis. These results suggest that a long term of Flk1-transgenic fish diet could alter certain metabolic pathways and possibly cause related tissue deformation. Compared to the previous reports, our feasible transgenic dietary assess system could evaluate subchronic and potential health impact of transgenic fish diet by combining multi-tissue histology and liver transcriptome analyses.

Identifying and Analyzing Novel Epilepsy-Related Genes Using Random Walk with Restart Algorithm.

As a pathological condition, epilepsy is caused by abnormal neuronal discharge in brain which will temporarily disrupt the cerebral functions. Epilepsy is a chronic disease which occurs in all ages and would seriously affect patients' personal lives. Thus, it is highly required to develop effective medicines or instruments to treat the disease. Identifying epilepsy-related genes is essential in order to understand and treat the disease because the corresponding proteins encoded by the epilepsy-related genes are candidates of the potential drug targets. In this study, a pioneering computational workflow was proposed to predict novel epilepsy-related genes using the random walk with restart (RWR) algorithm. As reported in the literature RWR algorithm often produces a number of false positive genes, and in this study a permutation test and functional association tests were implemented to filter the genes identified by RWR algorithm, which greatly reduce the number of suspected genes and result in only thirty-three novel epilepsy genes. Finally, these novel genes were analyzed based upon some recently published literatures. Our findings implicate that all novel genes were closely related to epilepsy. It is believed that the proposed workflow can also be applied to identify genes related to other diseases and deepen our understanding of the mechanisms of these diseases.

Control strategies for effective robot assisted gait rehabilitation: the state of art and future prospects.

A large number of gait rehabilitation robots, together with a variety of control strategies, have been developed and evaluated during the last decade. Initially, control strategies applied to rehabilitation robots were adapted from those applied to traditional industrial robots. However, these strategies cannot optimise effectiveness of gait rehabilitation. As a result, researchers have been investigating control strategies tailored for the needs of rehabilitation. Among these control strategies, assisted-as-needed (AAN) control is one of the most popular research topics in this field. AAN training strategies have gained the theoretical and practical evidence based backup from motor learning principles and clinical studies. Various approaches to AAN training have been proposed and investigated by research groups all around the world. This article presents a review on control algorithms of gait rehabilitation robots to summarise related knowledge and investigate potential trends of development. There are existing review papers on control strategies of rehabilitation robots. The review by Marchal-Crespo and Reinkensmeyer (2009) had a broad cover of control strategies of all kinds of rehabilitation robots. Hussain et al. (2011) had specifically focused on treadmill gait training robots and covered a limited number of control implementations on them. This review article encompasses more detailed information on control strategies for robot assisted gait rehabilitation, but is not limited to treadmill based training. It also investigates the potential to further develop assist-as-needed gait training based on assessments of patients' ability. In this paper, control strategies are generally divided into the trajectory tracking control and AAN control. The review covers these two basic categories, as well as other control algorithm and technologies derived from them, such as biofeedback control. Assessments on human gait ability are also included to investigate how to further develop implementations based on assist-as-needed concept. For the consideration of effectiveness, clinical studies on robotic gait rehabilitation are reviewed and analysed from the viewpoint of control algorithm.