No abstract

BACKGROUND: Carboxylesterases (CCEs) are one of three large detoxification enzyme families. Some CCEs are active on synthetic insecticides with ester structures. Anopheles sinensis is an important malaria vector in eastern Asia. This study identified and characterized the CCE genes in the A. sinensis genome and determined CCE genes associated with pyrethroid resistance using RNA sequencing (RNA-seq) and quantitative reverse transcription − polymerase chain reaction (qRT-PCR), in A. sinensis from Anhui, Chongqing, and Yunnan in China.RESULTS: Fifty-seven putative CCEs were identified and placed into three classes, 12 subfamilies and 14 clades through phylogenetic and homology analyses. Exon sizes ranged from 31 to 4317 bp, with 49 CCEs having two to five exons and eight having six to 11 exons. A total of 183 introns were recognized with sizes ranging from 31 to 4317 bp. The 57 CCEs were located on 14 scaffolds, with 70% located on four scaffolds. The alpha-esterase subfamily was significantly expanded compared with that of Anopheles gambiae. In a pyrethroid-resistant strain, RNA-seq detected five upregulated CCE genes and qRT-PCR detected 12 upregulated CCE genes. The -esterase 10 (AsAe10) and acetylcholinesterase 1 (AsAce1) genes were the main CCE genes associated with pyrethroid resistance. CONCLUSION: This information will be useful for further study of the CCE gene family and pyrethroid resistance mechanisms mediated by CCEs.

Asthma is a common chronic airway disease worldwide. Due to its clinical and genetic heterogeneity, the cellular and molecular processes in asthma are highly complex and relatively unknown. To discover novel biomarkers and the molecular mechanisms underlying asthma, several studies have been conducted by focusing on gene expression patterns in epithelium through microarray analysis. However, few robust specific biomarkers were identified and some inconsistent results were observed. Therefore, it is imperative to conduct a robust analysis to solve these problems. Herein, an integrated gene expression analysis of ten independent, publicly available microarray data of bronchial epithelial cells from 348 asthmatic patients and 208 healthy controls was performed. As a result, 78 up- and 75 down-regulated genes were identified in bronchial epithelium of asthmatics. Comprehensive functional enrichment and pathway analysis revealed that response to chemical stimulus, extracellular region, pathways in cancer, and arachidonic acid metabolism were the four most significantly enriched terms. In the protein-protein interaction network, three main communities associated with cytoskeleton, response to lipid, and regulation of response to stimulus were established, and the most highly ranked 6 hub genes (up-regulated CD44, KRT6A, CEACAM5, SERPINB2, and down-regulated LTF and MUC5B) were identified and should be considered as new biomarkers. Pathway cross-talk analysis highlights that signaling pathways mediated by IL-4/13 and transcription factor HIF-1α and FOXA1 play crucial roles in the pathogenesis of asthma. Interestingly, three chemicals, polyphenol catechin, antibiotic lomefloxacin, and natural alkaloid boldine, were predicted and may be potential drugs for asthma treatment. Taken together, our findings shed new light on the common molecular pathogenesis mechanisms of asthma and provide theoretical support for further clinical therapeutic studies.

For accurate gene expression quantification, normalization of gene expression data against reliable reference genes is required. It is known that the expression levels of commonly used reference genes vary considerably under different experimental conditions, and therefore, their use for data normalization is limited. In this study, an unbiased identification of reference genes in Caenorhabditis elegans was performed based on 145 microarray datasets (2296 gene array samples) covering different developmental stages, different tissues, drug treatments, lifestyle, and various stresses. As a result, thirteen housekeeping genes (rps-23, rps-26, rps-27, rps-16, rps-2, rps-4, rps-17, rpl-24.1, rpl-27, rpl-33, rpl-36, rpl-35, and rpl-15) with enhanced stability were comprehensively identified by using six popular normalization algorithms and RankAggreg method. Functional enrichment analysis revealed that these genes were significantly overrepresented in GO terms or KEGG pathways related to ribosomes. Validation analysis using recently published datasets revealed that the expressions of newly identified candidate reference genes were more stable than the commonly used reference genes. Based on the results, we recommended using rpl-33 and rps-26 as the optimal reference genes for microarray and rps-2 and rps-4 for RNA-sequencing data validation. More importantly, the most stable rps-23 should be a promising reference gene for both data types. This study, for the first time, successfully displays a large-scale microarray data driven genome-wide identification of stable reference genes for normalizing gene expression data and provides a potential guideline on the selection of universal internal reference genes in C. elegans, for quantitative gene expression analysis.

A protocell is a synthetic form of cellular life that is constructed from phospholipid vesicles and used to understand the emergence of life from a nonliving chemical network. To be considered ‘living’, a protocell should be capable of self-proliferation, which includes successive growth and division processes. The growth of protocells can be achieved via vesicle fusion approaches. In this review, we provide a brief overview of recent research on the formation of a protocell, fusion and division processes of the protocell, and encapsulation of a defined chemical network such as the genetic material. We also provide some perspectives on the challenges and future developments of synthetic protocell research.