Long noncoding RNA LINC01234 promoted cell proliferation and invasion via miR-1284/TRAF6 axis in colorectal cancer

Colorectal cancer is one of the most common and leading malignancies globally. Long noncoding RNAs (lncRNAs) function as potentially critical regulator in colorectal cancer. LINC01234, a novel lncRNA in tumor biology, regulates the progression of various tumors. However, the tumorigenic mechanism of LINC01234 in colorectal cancer is still unclear. This study was performed with the aim to prospectively investigate clinical significance, effect, and mechanism of lncRNA LINC01234 in colorectal cancer. First, we found that LINC01234, localized in the cytoplasm, was increased in both colorectal cancer cell lines and tissues. Subsequent functional assays suggested LINC01234 knockdown suppressed cell proliferation, migration, and invasion of colorectal cancer cells, while blocked cell cycle and induced cell apoptosis. Moreover, we identified that miR-1284 was target of LINC01234, we further demonstrated a negative correlation with LINC01234 in colorectal cancer tissues and cells. Furthermore, miR-1284 targeted and suppressed tumor necrosis factor receptor–associated factor 6 (TRAF6). Loss-of-function assay revealed that LINC01234 silencing suppressed colorectal cancer progression through inhibition of miR-1284. In vivo subcutaneous xenotransplanted tumor model indicated LINC01234 knockdown inhibited in vivo tumorigenic ability of colorectal cancer via downregulation of TRAF6. Collectively, this study clarified the biological significance of LINC01234/miR-1284/TRAF6 axis in colorectal cancer progression, providing insights into LINC01234 as novel potential therapeutic target for colorectal cancer therapeutic from bench to clinic.     

Genome Wide Identification of C2H2-Type Zinc Finger Proteins of Tomato and Expression Analysis Under Different Abiotic Stresses

In plants, C2H2-type zinc finger proteins play important roles in multiple processes, including plant growth and development, as well as biotic and abiotic responses. In the present study, based on the presence of the C2H2 domain (CX2~4CX3FX5LX2HX3~5H), 112 C2H2-type zinc finger proteins were predicted in tomato. Through gene and protein structures analyses and phylogenetic analysis, the 112 C2H2-type zinc finger proteins were divided into five subfamilies. Members of the same subfamily shared similarities in gene and protein structures, while members of different subfamilies contained different numbers of the C2H2 domain. The tissue expression pattern analysis showed that 24 C2H2-type zinc finger proteins are constitutively expressed in all tissues, indicating that they may play important roles in the growth and development of all tissues. In addition, under chilling (4 °C), heat (42 °C), high salinity (200 Mm NaCl), and osmotic (20% PEG) stresses, members of C2H2-type zinc finger family were induced to varying degrees, which suggested that these genes were involved in multiple abiotic stress responses. This study will provide theoretical basis for further research of C2H2-type zinc finger proteins in tomato.

     

Theoretical insight into the multiple interactions of quinazoline inhibitors with breast cancer resistance protein (BCRP/ABCG2)

Communicated by Ramaswamy H. Sarma     

ProDCoNN: Protein design using a convolutional neural network

Designing protein sequences that fold to a given three-dimensional (3D) structure has long been a challenging problem in computational structural biology with significant theoretical and practical implications. In this study, we first formulated this problem as predicting the residue type given the 3D structural environment around the C _α atom of a residue, which is repeated for each residue of a protein. We designed a nine-layer 3D deep convolutional neural network (CNN) that takes as input a gridded box with the atomic coordinates and types around a residue. Several CNN layers were designed to capture structure information at different scales, such as bond lengths, bond angles, torsion angles, and secondary structures. Trained on a very large number of protein structures, the method, called ProDCoNN (protein design with CNN), achieved state-of-the-art performance when tested on large numbers of test proteins and benchmark datasets.     

Joint analysis of single-cell and bulk tissue sequencing data to infer intratumor heterogeneity

Many computational methods have been developed to discern intratumor heterogeneity (ITH) using DNA sequence data from bulk tumor samples. These methods share an assumption that two mutations arise from the same subclone if they have similar mutant allele-frequencies (MAFs), and thus it is difficult or impossible to distinguish two subclones with similar MAFs. Single-cell DNA sequencing (scDNA-seq) data can be very informative for ITH inference. However, due to the difficulty of DNA amplification, scDNA-seq data are often very noisy. A promising new study design is to collect both bulk and single-cell DNA-seq data and jointly analyze them to mitigate the limitations of each data type. To address the analytic challenges of this new study design, we propose a computational method named BaSiC (B ulk tumor a nd Si ngle C ell), to discern ITH by jointly analyzing DNA-seq data from bulk tumor and single cells. We demonstrate that BaSiC has comparable or better performance than the methods using either data type. We further evaluate BaSiC using bulk tumor and single-cell DNA-seq data from a breast cancer patient and several leukemia patients.     

Randomization inference with general interference and censoring

Interference occurs between individuals when the treatment (or exposure) of one individual affects the outcome of another individual. Previous work on causal inference methods in the presence of interference has focused on the setting where it is a priori assumed that there is “partial interference,” in the sense that individuals can be partitioned into groups wherein there is no interference between individuals in different groups. Bowers et al. (2012, Political Anal, 21, 97–124) and Bowers et al. (2016, Political Anal, 24, 395–403) consider randomization-based inferential methods that allow for more general interference structures in the context of randomized experiments. In this paper, extensions of Bowers et al. that allow for failure time outcomes subject to right censoring are proposed. Permitting right-censored outcomes is challenging because standard randomization-based tests of the null hypothesis of no treatment effect assume that whether an individual is censored does not depend on treatment. The proposed extension of Bowers et al. to allow for censoring entails adapting the method of Wang et al. (2010, Biostatistics, 11, 676–692) for two-sample survival comparisons in the presence of unequal censoring. The methods are examined via simulation studies and utilized to assess the effects of cholera vaccination in an individually randomized trial of 73 000 children and women in Matlab, Bangladesh.     

Activation and competition of lipoylation of H protein and its hydrolysis in a reaction cascade catalyzed by the multifunctional enzyme lipoate–protein ligase A

Protein lipoylation is essential for the function of many key enzymes but barely studied kinetically. Here, the two-step reaction cascade of H protein lipoylation catalyzed by the multifunctional enzyme lipoate–protein ligase A (LplA) was quantitatively and differentially studied. We discovered new phenomena and unusual kinetics of the cascade: (a) the speed of the first reaction is faster than the second one by two orders of magnitude, leading to high accumulation of the intermediate lipoyl-AMP (Lip-AMP); (b) Lip-AMP is hydrolyzed, but only significantly at the presence of H protein and in competition with the lipoylation; (c) both the lipoylation of H protein and its hydrolysis is enhanced by the apo and lipoylated forms of H protein and a mutant without the lipoylation site. A conceptual mechanistic model is proposed to explain these experimental observations in which conformational change of LplA upon interaction with H protein and competitive nucleophilic attacks play key roles.