Enhanced protein-metabolite correlation analysis: To investigate the association between Staphylococcus aureus mastitis and metabolic immune pathways.

Mastitis is a disease characterized by congestion, swelling, and inflammation of the mammary gland and usually caused by infection with pathogenic microorganisms. Furthermore, the development of mastitis is closely linked to the exogenous pathway of the gastrointestinal tract. However, the regulatory mechanisms governing the gut-metabolism-mammary axis remain incompletely understood. The present study revealed alterations in the gut microbiota of mastitis rats characterized by an increased abundance of the Proteobacteria phylum. Plasma analysis revealed significantly higher levels of L-isoleucine and cholic acid along with 7-ketodeoxycholic acid. Mammary tissue showed elevated levels of arachidonic acid metabolites and norlithocholic acid. Proteomic analysis showed increased levels of IFIH1, Tnfaip8l2, IRGM, and IRF5 in mastitis rats, which suggests that mastitis triggers an inflammatory response and immune stress. Follistatin (Fst) and progesterone receptor (Pgr) were significantly downregulated, raising the risk of breast cancer. Extracellular matrix (ECM) receptors and focal adhesion signaling pathways were downregulated, while blood-milk barrier integrity was disrupted. Analysis of protein-metabolic network regulation revealed that necroptosis, protein digestion and absorption, and arachidonic acid metabolism were the principal regulatory pathways involved in the development of mastitis. In short, the onset of mastitis leads to changes in the microbiota and alterations in the metabolic profiles of various biological samples, including colonic contents, plasma, and mammary tissue. Key manifestations include disturbances in bile acid metabolism, amino acid metabolism, and arachidonic acid metabolism. At the same time, the integrity of the blood-milk barrier is compromised while inflammation is promoted, thereby reducing cell adhesion in the mammary glands. These findings contribute to a more comprehensive understanding of the metabolic status of mastitis and provide new insights into its impact on the immune system.

InsectBase: a resource for insect genomes and transcriptomes.

The genomes and transcriptomes of hundreds of insects have been sequenced. However, insect community lacks an integrated, up-to-date collection of insect gene data. Here, we introduce the first release of InsectBase, available online at http://www.insect-genome.com. The database encompasses 138 insect genomes, 116 insect transcriptomes, 61 insect gene sets, 36 gene families of 60 insects, 7544 miRNAs of 69 insects, 96,925 piRNAs of Drosophila melanogaster and Chilo suppressalis, 2439 lncRNA of Nilaparvata lugens, 22,536 pathways of 78 insects, 678,881 untranslated regions (UTR) of 84 insects and 160,905 coding sequences (CDS) of 70 insects. This release contains over 12 million sequences and provides search functionality, a BLAST server, GBrowse, insect pathway construction, a Facebook-like network for the insect community (iFacebook), and phylogenetic analysis of selected genes.

Automatic extraction of reference gene from literature in plants based on texting mining.

Real-Time Quantitative Polymerase Chain Reaction (qRT-PCR) is widely used in biological research. It is a key to the availability of qRT-PCR experiment to select a stable reference gene. However, selecting an appropriate reference gene usually requires strict biological experiment for verification with high cost in the process of selection. Scientific literatures have accumulated a lot of achievements on the selection of reference gene. Therefore, mining reference genes under specific experiment environments from literatures can provide quite reliable reference genes for similar qRT-PCR experiments with the advantages of reliability, economic and efficiency. An auxiliary reference gene discovery method from literature is proposed in this paper which integrated machine learning, natural language processing and text mining approaches. The validity tests showed that this new method has a better precision and recall on the extraction of reference genes and their environments.