Shining Ma

In both Turner syndrome (TS) and Klinefelter syndrome (KS) copy number aberrations of the X chromosome lead to various developmental symptoms. We report a comparative analysis of TS vs. KS regarding differences at the genomic network level measured in primary samples by analyzing gene expression, DNA methylation, and chromatin conformation. X-chromosome inactivation (XCI) silences transcription from one X chromosome in female mammals, on which most genes are inactive, and some genes escape from XCI. In TS, almost all differentially expressed escape genes are down-regulated but most differentially expressed inactive genes are up-regulated. In KS, differentially expressed escape genes are up-regulated while the majority of inactive genes appear unchanged. Interestingly, 94 differentially expressed genes (DEGs) overlapped between TS and female and KS and male comparisons; and these almost uniformly display expression changes into opposite directions. DEGs on the X chromosome and the autosomes are coexpressed in both syndromes, indicating that there are molecular ripple effects of the changes in X chromosome dosage. Six potential candidate genes ( RPS4X , SEPT6 , NKRF , CX0rf57 , NAA10 , and FLNA ) for KS are identified on Xq, as well as candidate central genes on Xp for TS. Only promoters of inactive genes are differentially methylated in both syndromes while escape gene promoters remain unchanged. The intrachromosomal contact map of the X chromosome in TS exhibits the structure of an active X chromosome. The discovery of shared DEGs indicates the existence of common molecular mechanisms for gene regulation in TS and KS that transmit the gene dosage changes to the transcriptome.

AIMS: The aims of this study were to develop an effective oral vaccine against enterotoxigenic Escherichia coli (ETEC) infection and to design new and more versatile mucosal adjuvants. METHODS AND RESULTS: Genetically engineered Lactobacillus casei strains expressing F4 (K88) fimbrial adhesin FaeG (rLpPG-2-FaeG) and either co-expressing heat-labile enterotoxin A (LTA) subunit with an amino acid mutation associated with reduced virulence (LTAK63) and a heat-labile enterotoxin B (LTB) subunit of E. coli (rLpPG-2-LTAK63-co-LTB) or fused-expressing LTAK63 and LTB (rLpPG-2-LTAK63-fu-LTB) were constructed. The immunogenicity of rLpPG-2-FaeG in conjunction with rLpPG-2-LTAK63-co-LTB or rLpPG-2-LTAK63-fu-LTB as an orally administered mucosal adjuvant in mice was evaluated. Results showed that the levels of FaeG-specific serum IgG and mucosal sIgA, as well as the proliferation of lymphocytes, were significantly higher in mice orally co-administered rLpPG-2-FaeG and rLpPG-2-LTAK63-fu-LTB compared with those administered rLpPG-2-FaeG alone, and were lower than those co-administered rLpPG-2-FaeG and rLpPG-2-LTAK63-co-LTB. Moreover, effective protection was observed after challenge with F4+ ETEC strain CVCC 230 in mice co-administered rLpPG-2-FaeG and rLpPG-2-LTAK63-co-LTB or rLpPG-2-FaeG and rLpPG-2-LTAK63-fu-LTB group compared with those that received rLpPG-2-FaeG alone. CONCLUSIONS: rLpPG-2-FaeG showed greater immunogenicity in combination with LTAK63 and LTB as molecular adjuvants. SIGNIFICANCE AND IMPACT OF THE STUDY: Recombinant Lactobacillus provides a promising platform for the development of vaccines against F4+ ETEC infection.

BACKGROUND: RNA-Seq based transcriptome assembly has become a fundamental technique for studying expressed mRNAs (i.e., transcripts or isoforms) in a cell using high-throughput sequencing technologies, and is serving as a basis to analyze the structural and quantitative differences of expressed isoforms between samples. However, the current transcriptome assembly algorithms are not specifically designed to handle large amounts of errors that are inherent in real RNA-Seq datasets, especially those involving multiple samples, making downstream differential analysis applications difficult. On the other hand, multiple sample RNA-Seq datasets may provide more information than single sample datasets that can be utilized to improve the performance of transcriptome assembly and abundance estimation, but such information remains overlooked by the existing assembly tools. RESULTS: We formulate a computational framework of transcriptome assembly that is capable of handling noisy RNA-Seq reads and multiple sample RNA-Seq datasets efficiently. We show that finding an optimal solution under this framework is an NP-hard problem. Instead, we develop an efficient heuristic algorithm, called Iterative Shortest Path (ISP), based on linear programming (LP) and integer linear programming (ILP). Our preliminary experimental results on both simulated and real datasets and comparison with the existing assembly tools demonstrate that (i) the ISP algorithm is able to assemble transcriptomes with a greatly increased precision while keeping the same level of sensitivity, especially when many samples are involved, and (ii) its assembly results help improve downstream differential analysis. The source code of ISP is freely available at http://alumni.cs.ucr.edu/~liw/isp.html.