Comprehensive Evaluation and Application of Experimental Sources of Variation in Gut Microbiome Sequencing Studies / 中国生物化学与分子生物学报

Gut microbiome sequencing studies have great potential to translate microbial analysis outcomes into human health research. Sequencing strategies of 16S amplicon and whole-metagenome shotgun (WMS) are two main methods in microbiome research with respective advantages. However, how sample heterogeneity, sequencers and library preparation protocols affect the sequencing reproducibility of gut microbiome needs further investigation. This study aims to provide a reference for the selection of sequencing technologies by comparing differences in microbial composition from different sampling sites. The results of three widely adopted sequencers showed that the technical repetition correlation (r= 0. 94) was high in WMS method, while the biological repetition correlation (r = 0. 69) was low. Bray-Curtis distance identified that dissimilarity from biological replicates was larger than that of technical replicates (P<0. 001). In addition, dissimilarity and specific taxonomic profiles were observed between 16S and WMS datasets. Our results imply that homogenization is a necessary step before sample DNA extraction. The sequencers contributed less to taxonomic variation than the library preparation protocols. We developed an empirical Bayes approach that " borrowed information" in calculations and analyzed batch effect parameters using standardized data and prior distributions of (non-) parameters, which may improve population comparability between 16S and WMS and provide a basis for further application to fusion analysis of published 16S and microbial datasets.

Identification of activated pathways in lung adenocarcinoma based on network strategy

Background: Lung adenocarcinoma has increased incidence over the past years and is the cause for almost 50% of deaths attributable to lung cancer. The objective of this paper is to identify activated pathways associated with lung adenocarcinoma based on gene co-expression network analysis. Materials and Methods: Kyoto Encyclopedia of Genes and Genomes pathway analysis of dysregulated genes was performed based on Expression Analysis Systematic Explorer test to illuminate the biological pathways. Co-expression networks of lung adenocarcinoma in different tumor Stages (IA, IB, IIA, IIB, IIIA, IIIB, and IV) were constructed by Empirical Bayes approach to reweight gene pair scores. Pathway activity analysis was conducted to compute the distribution of pathways in different stages and to identify “activated” pathways in lung adenocarcinoma. Results: We evaluated 211 dysregulated genes between lung adenocarcinoma patients and normal controls. Pathway activity analysis was performed and P values of pathways, which obtained from co-expression networks (Stage IA, IB, IIA, IIB, IIIA, IIIB, and IV), were calculated. Cell cycle, progesterone-mediated oocyte maturation, and oocyte meiosis were activated during all stages in lung adenocarcinoma. Conclusions: We successfully identified three activated pathways (cell cycle, progesterone-mediated oocyte maturation, and oocyte meiosis) in different Stages (IA, IB, IIA, IIB, IIIA, IIIB, and IV) of lung adenocarcinoma

Standard Error of Empirical Bayes Estimate in NONMEM(R) VI

The pharmacokinetics/pharmacodynamics analysis software NONMEM(R) output provides model parameter estimates and associated standard errors. However, the standard error of empirical Bayes estimates of inter-subject variability is not available. A simple and direct method for estimating standard error of the empirical Bayes estimates of inter-subject variability using the NONMEM(R) VI internal matrix POSTV is developed and applied to several pharmacokinetic models using intensively or sparsely sampled data for demonstration and to evaluate performance. The computed standard error is in general similar to the results from other post-processing methods and the degree of difference, if any, depends on the employed estimation options.