Assessment and characterization of gut microbiota has become a major research area in human disease, including type 2 diabetes, the most prevalent endocrine disease worldwide. To carry out analysis on gut microbial content in patients with type 2 diabetes, we developed a protocol for a metagenome-wide association study (MGWAS) and undertook a two-stage MGWAS based on deep shotgun sequencing of the gut microbial DNA from 345 Chinese individuals. We identified and validated approximately 60,000 type-2-diabetes-associated markers and established the concept of a metagenomic linkage group, enabling taxonomic species-level analyses. MGWAS analysis showed that patients with type 2 diabetes were characterized by a moderate degree of gut microbial dysbiosis, a decrease in the abundance of some universal butyrate-producing bacteria and an increase in various opportunistic pathogens, as well as an enrichment of other microbial functions conferring sulphate reduction and oxidative stress resistance. An analysis of 23 additional individuals demonstrated that these gut microbial markers might be useful for classifying type 2 diabetes.

We present primary results from the Sequencing Quality Control (SEQC) project, coordinated by the United States Food and Drug Administration. Examining Illumina HiSeq, Life Technologies SOLiD and Roche 454 platforms at multiple laboratory sites using reference RNA samples with built-in controls, we assess RNA sequencing (RNA-seq) performance for junction discovery and differential expression profiling and compare it to microarray and quantitative PCR (qPCR) data using complementary metrics. At all sequencing depths, we discover unannotated exon-exon junctions, with >80% validated by qPCR. We find that measurements of relative expression are accurate and reproducible across sites and platforms if specific filters are used. In contrast, RNA-seq and microarrays do not provide accurate absolute measurements, and gene-specific biases are observed, for these and qPCR. Measurement performance depends on the platform and data analysis pipeline, and variation is large for transcript-level profiling. The complete SEQC data sets, comprising >100 billion reads (10Tb), provide unique resources for evaluating RNA-seq analyses for clinical and regulatory settings.

Rechargeable lithium-ion batteries (LIBs) are important electrochemical energy storage devices for consumer electronics and emerging electrical/hybrid vehicles. However, one of the formidable challenges is to develop ultrafast charging LIBs with the rate capability at least one order of magnitude (>10 C) higher than that of the currently commercialized LIBs. This tutorial review presents the state-of-the-art developments in ultrafast charging LIBs by the rational design of materials. First of all, fundamental electrochemistry and related ionic/electronic conduction theories identify that the rate capability of LIBs is kinetically limited by the sluggish solid-state diffusion process in electrode materials. Then, several aspects of the intrinsic materials, materials engineering and processing, and electrode materials architecture design towards maximizing both ionic and electronic conductivity in the electrode with a short diffusion length are deliberated. Finally, the future trends and perspectives for the ultrafast rechargeable LIBs are discussed. Continuous rapid progress in this area is essential and urgent to endow LIBs with ultrafast charging capability to meet huge demands in the near future.

We determined the role of Phospholipase Da1 (PLDa1) and its lipid product phosphatidic acid (PA) in abscisic acid (ABA)-induced production of reactive oxygen species (ROS) in Arabidopsis thaliana guard cells. The plda1 mutant failed to produce ROS in guard cells in response to ABA. ABA stimulated NADPH oxidase activity in wild-type guard cells but not in plda1 cells, whereas PA stimulated NADPH oxidase activity in both genotypes. PA bound to recombinant Arabidopsis NADPH oxidase RbohD (respiratory burst oxidase homolog D) and RbohF. The PA binding motifs were identified, and mutation of the Arg residues 149, 150, 156, and 157 in RbohD resulted in the loss of PA binding and the loss of PA activation of RbohD. The rbohD mutant expressing non-PA-binding RbohD was compromised in ABA-mediated ROS production and stomatal closure. Furthermore, ABA-induced production of nitric oxide (NO) was impaired in plda1 guard cells. Disruption of PA binding to ABI1 protein phosphatase 2C did not affect ABA-induced production of ROS or NO, but the PA-ABI1 interaction was required for stomatal closure induced by ABA, H 2 O 2 , or NO. Thus, PA is as a central lipid signaling molecule that links different components in the ABA signaling network in guard cells.

Esophageal squamous cell carcinoma (ESCC) is one of the most common cancers worldwide and the fourth most lethal cancer in China. However, although genomic studies have identified some mutations associated with ESCC, we know little of the mutational processes responsible. To identify genome-wide mutational signatures, we performed either whole-genome sequencing (WGS) or whole-exome sequencing (WES) on 104 ESCC individuals and combined our data with those of 88 previously reported samples. An APOBEC-mediated mutational signature in 47% of 192 tumors suggests that APOBEC-catalyzed deamination provides a source of DNA damage in ESCC. Moreover, PIK3CA hotspot mutations (c.1624G>A [p.Glu542Lys] and c.1633G>A [p.Glu545Lys]) were enriched in APOBEC-signature tumors, and no smoking-associated signature was observed in ESCC. In the samples analyzed by WGS, we identified focal (<100 kb) amplifications of CBX4 and CBX8. In our combined cohort, we identified frequent inactivating mutations in AJUBA, ZNF750, and PTCH1 and the chromatin-remodeling genes CREBBP and BAP1, in addition to known mutations. Functional analyses suggest roles for several genes (CBX4, CBX8, AJUBA, and ZNF750) in ESCC. Notably, high activity of hedgehog signaling and the PI3K pathway in approximately 60% of 104 ESCC tumors indicates that therapies targeting these pathways might be particularly promising strategies for ESCC. Collectively, our data provide comprehensive insights into the mutational signatures of ESCC and identify markers for early diagnosis and potential therapeutic targets.