Sentence examples for microbial genes from from inspiring English sources

Qin et al. analyzed 3.3 million non-redundant microbial genes from intestinal samples of 124 Europeans [55].

To the best of our knowledge, this is the first report of direct, nonamplified metagenomic cloning of microbial genes from a complex fermented food matrix.

In order to generate a primary catalogue of microbial genes from the fish intestines, and explore the data differences caused from the fasting challenge, we first performed de novo assembly for the high quality reads.

To determine how the gut microbiota can augment and complement A. glabripennis' endogenous digestive repertoire, annotations of microbial genes assembled from the intact midgut and midgut contents libraries were compared to annotations of insect-derived genes that were previously assembled and annotated from the A. glabripennis midgut [ 33].

The development of sequencing and high-throughput methods for cloning microbial genes directly from environment has opened the possibilities for ecological microbiology, mostly considering that microbes possess the highest potential of producing bioactive metabolites, enzymes, and polymers and other tools with biotechnological application.

Our inclusive multi-marker network-based approach efficiently recovered novel evidence of highly divergent microbial genes, possibly partly originating from microbial dark matter, even in the human gut.

Here, we present for the first time a gene catalogue containing the prevalent microbial genes in faecal samples from guinea pigs, covering phylogenetic composition as well as main functional categories.

However, the evaluation of microbial gene expression from in vivo biofilm samples is not trivial, specifically, assessment via quantitative PCR (qPCR) can be a challenge because of several species present in clinical samples.

To quantify the observed effect regarding start codon usage, we compared the start codons of potentially misannotated genes with those from randomly chosen microbial genes.

From the resulting scaffolds, microbial genes were predicted using Prokka [ 71], and compared to Pfam [ 35] using HMMER [ 72].

For this, we calculated the correlations between microbial genes that were part of the microbial network with mouse gene expression from the second subnetwork (steps 3, 4).