ARC Centre of Excellence in Synthetic Biology, Macquarie University, Sydney, NSW, Australia; Department of Molecular Sciences, Macquarie University, Sydney, NSW, Australia. Electronic address:
Published: December 2021
AI Article Synopsis
Article Abstract
Since the late 1990's the genome sequences for thousands of species of bacteria have been released into public databases. The release of each new genome sequence typically revealed the presence of tens to hundreds of uncharacterised genes encoding putative membrane proteins and more recently, microbial metagenomics has revealed countless more of these uncharacterised genes. Given the importance of small molecule efflux in bacteria, it is likely that a significant proportion of these genes encode for novel efflux proteins, but the elucidation of these functions is challenging. We used transcriptomics to predict that the function of a gene encoding a hypothetical membrane protein is in efflux-mediated antimicrobial resistance. We subsequently confirmed this function and the likely native substrates of the pump by using detailed biochemical and biophysical analyses. Functional studies of homologs of the protein from other bacterial species determined that the protein is a prototype for a family of multidrug efflux pumps - the Proteobacterial Antimicrobial Compound Efflux (PACE) family. The general functional genomics approach used here, and its expansion to functional metagenomics, will very likely reveal the identities of more efflux pumps and other transport proteins of scientific, clinical and commercial interest in the future.
Genome rearrangements are events where large blocks of DNA exchange places during evolution. The analysis of these events is a promising tool for understanding evolutionary genomics, providing data for phylogenetic reconstruction based on genome rearrangement measures. Many pairwise rearrangement distances have been proposed, based on finding the minimum number of rearrangement events to transform one genome into the other, using some predefined operation.
Engineering Research Center of Edible and Medicinal Fungi, Ministry of Education, Jilin Agricultural University, No. 2888 Xincheng Street, Changchun , Jilin Province, 130118, China.
Background: Hericium coralloides is a traditional edible and medicinal mushroom. Light is a key factor in forming fruiting bodies of fungi; however, the effects of different light on the yield and morphogenesis of H. coralloides are still unknown.
Background: Fat traits in cattle are considered important due to their contribution to beef eating quality and carcass economic value. Discovering the genes controlling fat traits in cattle will enable better selection of these traits, but identifying these genes in individual experiments has proven difficult. Compared to individual experiments, meta-analyses allow greater statistical power for detecting quantitative trait loci and identifying genes that influence single and multiple economically important fat traits.
Background: Lablab is one of the conventionally grown multi-purpose crops that originated in Africa. It is an annual or short-lived perennial forage legume which has versatile uses (as a vegetable and dry seeds, as food or feed, or as green manure) but is yet to receive adequate research attention and hence remains underexploited. To develop new and highly productive lablab varieties, using genomics-assisted selection, the present study aimed to identify quantitative trait loci associated with agronomically important traits in lablab and to assess the stability of these traits across two different agro-ecologies in Ethiopia.
Background: Genetic markers are crucial for breeding crops with desired agronomic traits, and their development can be expedited using next-generation sequencing (NGS) and bioinformatics tools. Numerous tools have been developed to design molecular markers, enhancing the convenience, accuracy, and efficiency of molecular breeding. However, these tools primarily focus on genetic variants within short user-input sequences, despite the availability of extensive omics data for genomic variants.
