Comparative proteomic analysis of hypothalamus tissue from Huoyan geese between pre-laying period and laying period using an iTRAQ-based approach

iTRAQ-based quantitative proteomic analysis of the antimicrobial mechanism of lactobionic acid against Staphylococcus aureus

Staphylococcus aureus is a common pathogenic microorganism that causes foodborne diseases. Lactobionic acid (LBA) is a natural polyhydroxy acid widely used in the food industry. To understand the antibacterial action of LBA against S. aureus better and identify 274 differentially expressed proteins upon LBA treatment, an isobaric tag was used for relative and absolute quantification-based quantitative proteomics. Combined with ultrastructural observations, results suggested that LBA inhibited S. aureus by disrupting cell wall and membrane integrity, regulating adenosine triphosphate binding cassette transporter expression, affecting cellular energy metabolism, attenuating S. aureus virulence and reducing infection, and decreasing the levels of proteins involved in stress and starvation responses. Quantitative real-time polymerase chain reaction analysis was used to validate the proteomic data. The results provide new insights into the inhibitory effects of LBA on S. aureus and suggest that LBA application may be a promising method to ensure food and pharmaceutical product safety.

Whole Genome Sequencing Reveals the Effects of Recent Artificial Selection on Litter Size of Bamei Mutton Sheep

Simple Summary

Bamei mutton sheep is a Chinese domestic sheep breed developed by crossing German Mutton Merino sheep and indigenous Mongolian sheep for meat production. There is large variation in the reproductive abilities of Bamei mutton sheep. After recent artificial selection, the average lambing rate of the Bamei mutton nucleus group was over 150%. We used the FST (Fixation Index) and XP-EHH (The Cross-Population Extended Haplotype Homozygosity) statistical approach to detect the selective sweeps between high- and low-fecundity Bamei mutton sheep groups. JUN (JUN proto-oncogene, AP-1 transcription factor subunit), ITPR3 (inositol 1,4,5-trisphosphate receptor type 3, PLCB2 (phospholipase C beta 2), HERC5 (HECT and RLD domain containing E3 ubiquitin protein ligase 5), and KDM4B (lysine demethylase 4B) were detected that are potential responsible for litter size. These observations provide a new opportunity to research the genetic variation influencing fecundity traits within a population evolving under artificial selection.

Abstract

Bamei mutton sheep is a Chinese domestic sheep breed developed by crossing German Mutton Merino sheep and indigenous Mongolian sheep for meat production. Here, we focused on detecting candidate genes associated with the increasing of the litter size in this breeds under recent artificial selection to improve the efficiency of mutton production. We selected five high- and five low-fecundity Bamei mutton sheep for whole-genome resequencing to identify candidate genes for sheep prolificacy. We used the FST and XP-EHH statistical approach to detect the selective sweeps between these two groups. Combining the two selective sweep methods, the reproduction-related genes JUN, ITPR3, PLCB2, HERC5, and KDM4B were detected. JUN, ITPR3, and PLCB2 play vital roles in GnRH (gonadotropin-releasing hormone), oxytocin, and estrogen signaling pathway. Moreover, KDM4B, which had the highest FST value, exhibits demethylase activity. It can affect reproduction by binding the promoters of estrogen-regulated genes, such as FOXA1 (forkhead box A1) and ESR1 (estrogen receptor 1). Notably, one nonsynonymous mutation (p.S936A) specific to the high-prolificacy group was identified at the TUDOR domain of KDM4B. These observations provide a new opportunity to research the genetic variation influencing fecundity traits within a population evolving under artificial selection. The identified genomic regions that are responsible for litter size can in turn be used for further selection.

Mapping Molecular Datasets Back to the Brain Regions They are Extracted from: Remembering the Native Countries of Hypothalamic Expatriates and Refugees

This article focuses on approaches to link transcriptomic, proteomic, and peptidomic datasets mined from brain tissue to the original locations within the brain that they are derived from using digital atlas mapping techniques. We use, as an example, the transcriptomic, proteomic and peptidomic analyses conducted in the mammalian hypothalamus. Following a brief historical overview, we highlight studies that have mined biochemical and molecular information from the hypothalamus and then lay out a strategy for how these data can be linked spatially to the mapped locations in a canonical brain atlas where the data come from, thereby allowing researchers to integrate these data with other datasets across multiple scales. A key methodology that enables atlas-based mapping of extracted datasets-laser-capture microdissection-is discussed in detail, with a view of how this technology is a bridge between systems biology and systems neuroscience.