SUMMARY MutS protein homolog 2 (MSH2) is a key DNA mismatch repair protein. It forms the MSH2-MSH6 (MutSα) and MSH2-MSH3 (MutSβ) heterodimers, which help to ensure genomic integrity. MutSα not only recognizes and repairs mismatched nucleotides but also recognizes DNA adducts induced by DNA-damaging agents, and triggers cell-cycle arrest and apoptosis. Loss or depletion of MutSα from cells leads to microsatellite instability (MSI) and resistance to DNA damage. Although the level of MutSα can be reduced by the ubiquitin-proteasome pathway, the detailed mechanisms of this regulation remain elusive. Here we report that histone deacetylase 6 (HDAC6) sequentially deacetylates and ubiquitinates MSH2, leading to MSH2 degradation. In addition, HDAC6 significantly reduces cellular sensitivity to DNA-damaging agents and decreases cellular DNA mismatch repair activities by downregulation of MSH2. Overall, these findings reveal a mechanism by which proper levels of MutSα are maintained.

Cellulose represents the most abundant biopolymer in nature and has great economic importance. Cellulose chains pack laterally into crystalline forms, stacking into a complicated crystallographic structure. However, the mechanism of cellulose crystallization is poorly understood. Here, via functional characterization, we report that Brittle Culm1 (BC1), a COBRA-like protein in rice, modifies cellulose crystallinity. BC1 was demonstrated to be a glycosylphosphatidylinositol (GPI) anchored protein and can be released into cell walls by removal of the GPI anchor. BC1 possesses a carbohydrate-binding module (CBM) at its N-terminus. In vitro binding assays showed that this CBM interacts specifically with crystalline cellulose, and several aromatic residues in this domain are essential for binding. It was further demonstrated that cell wall-localized BC1 via the CBM and GPI anchor is one functional form of BC1. X-ray diffraction (XRD) assays revealed that mutations in BC1 and knockdown of BC1 expression decrease the crystallite width of cellulose; overexpression of BC1 and the CBM-mutated BC1s caused varied crystallinity with results that were consistent with the in vitro binding assay. Moreover, interaction between the CBM and cellulose microfibrils was largely repressed when the cell wall residues were pre-stained with two cellulose dyes. Treating wild-type and bc1 seedlings with the dyes resulted in insensitive root growth responses in bc1 plants. Combined with the evidence that BC1 and three secondary wall cellulose synthases (CESAs) function in different steps of cellulose production as revealed by genetic analysis, we conclude that BC1 modulates cellulose assembly by interacting with cellulose and affecting microfibril crystallinity.

SummaryGlycosyltransferases (GTs) are one of the largest enzyme groups required for the synthesis of complex wall polysaccharides and glycoproteins in plants. However, due to the limited number of related mutants that have observable phenotypes, the biological function(s) of most GTs in cell-wall biosynthesis and assembly have remained elusive. We report here the isolation and in-depth characterization of a brittle rice mutant, brittle culm 10 (bc10). bc10 plants show pleiotropic phenotypes, including brittleness of the plant body and retarded growth. The BC10 gene was cloned through a map-based approach, and encodes a Golgi-located type II membrane protein that contains a domain designated as 'domain of unknown function 266' (DUF266) and represents a multiple gene family in rice. BC10 has low sequence similarity with the domain to a core 2 b-1,6-N-acetylglucosaminyltransferase (C2GnT), and its in vitro enzymatic activity suggests that it functions as a glycosyltransferase. Monosaccharide analysis of total and fractioned wall residues revealed that bc10 showed impaired cellulose biosynthesis. Immunolocalization and isolation of arabinogalactan proteins (AGPs) in the wild-type and bc10 showed that the level of AGPs in the mutant is significantly affected. BC10 is mainly expressed in the developing sclerenchyma and vascular bundle cells, and its deficiency causes a reduction in the levels of cellulose and AGPs, leading to inferior mechanical properties.

SUMMARYKinesins are encoded by a large gene family involved in many basic processes of plant development. However, the number of functionally identified kinesins in rice is very limited. Here, we report the functional characterization of Brittle Culm12 (BC12), a gene encoding a kinesin-4 protein. bc12 mutants display dwarfism resulting from a significant reduction in cell number and brittleness due to an alteration in cellulose microfibril orientation and wall composition. BC12 is expressed mainly in tissues undergoing cell division and secondary wall thickening. In vitro biochemical analyses verified BC12 as an authentic motor protein. This protein was present in both the nucleus and cytoplasm and associated with microtubule arrays during cell division. Mitotic microtubule array comparison, flow cytometric analysis and expression assays of cyclin-dependent kinase (CDK) complexes in root-tip cells showed that cell-cycle progression is affected in bc12 mutants. BC12 is very probably regulated by CDKA;3 based on yeast two-hybrid and microarray data. Therefore, BC12 functions as a dual-targeting kinesin protein and is implicated in cell-cycle progression, cellulose microfibril deposition and wall composition in the monocot plant rice.

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The ETS-related transcription factor Fli-1 affects many developmental programs including erythroid and megakaryocytic differentiation, and is frequently de-regulated in cancer. Fli-1 was initially isolated following retrovirus insertional mutagenesis screens for leukemic initiator genes, and accordingly, inhibition of this transcription factor can suppress leukemia through induction of erythroid differentiation. To search for modulators of Fli-1, we hereby performed repurposing drug screens with compounds isolated from Chinese medicinal plants. We identified agents that can transcriptionally activate or inhibit a Fli-1 reporter. Remarkably, agents that increased Fli-1 transcriptional activity conferred a strong anti-cancer activity upon Fli-1-expressing leukemic cells in culture. As opposed to drugs that suppress Fli1 activity and lead to erythroid differentiation, growth suppression by these new Fli-1 transactivating compounds involved erythroid to megakaryocytic conversion (EMC). The identified compounds are structurally related to diterpene family of small molecules, which are known agonists of protein kinase C (PKC). In accordance, these PKC agonists (PKCAs) induced PKC phosphorylation leading to activation of the mitogen-activated protein kinase (MAPK) pathway, increased cell attachment and EMC, whereas pharmacological inhibition of PKC or MAPK diminished the effect of our PKCAs. Moreover, in a mouse model of leukemia initiated by Fli-1 activation, the PKCA compounds exhibited strong anti-cancer activity, which was accompanied by increased presence of CD41/CD61 positive megakaryocytic cells in leukemic spleens. Thus, PKC agonists offer a novel approach to combat Fli-1-induced leukemia, and possibly other cancers,by inducing EMC in part through over-activation of the PKC-MAPK-Fli-1 pathway.

Driver fatigue has become one of the major causes of traffic accidents, and is a complicated physiological process. However, there is no effective method to detect driving fatigue. Electroencephalography (EEG) signals are complex, unstable, and non-linear; non-linear analysis methods, such as entropy, maybe more appropriate. This study evaluates a combined entropy-based processing method of EEG data to detect driver fatigue. In this paper, 12 subjects were selected to take part in an experiment, obeying driving training in a virtual environment under the instruction of the operator. Four types of enthrones (spectrum entropy, approximate entropy, sample entropy and fuzzy entropy) were used to extract features for the purpose of driver fatigue detection. Electrode selection process and a support vector machine (SVM) classification algorithm were also proposed. The average recognition accuracy was 98.75%. Retrospective analysis of the EEG showed that the extracted features from electrodes T5, TP7, TP8 and FP1 may yield better performance. SVM classification algorithm using radial basis function as kernel function obtained better results. A combined entropy-based method demonstrates good classification performance for studying driver fatigue detection.

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