The long-term feeding of a high-concentrate diet (the concentrate ratio is greater than 60 %) leads to mammary gland inflammatory response in ruminants and decreased quality in dairy cows and affects the robust development of the dairy industry. The main reason is closely related to elevated lipopolysaccharide (LPS) in the body. In this experiment, a bovine mammary epithelial cell line (MAC-T) was used as a model, and LPS at different concentrations (0 ng/ml, 1 ng/ml, 10 ng/ml, 100 ng/ml, 1000 ng/ml, 10000 ng/ml) was added to the cells. The cell survival rate, oxidative stress indicators, total lipid droplet area, triglyceride content and key genes regulating lipid metabolism were detected by 3-(4,5)-dimethylthiahiazo(-z-y1)3,5-di-phenytetrazoliumromide (MTT), assay kit, microscope observation and RT-PCR methods to explore the regulatory mechanism of mammary health and milk fat synthesis. The results showed that compared with those of the control group, the survival rates of cells were significantly decreased after 9 h of stimulation with 1000 ng/ml and 10000 ng/ml LPS (P<0.01). The contents of superoxide dismutase (SOD), catalase (CAT) and total antioxidant capacity (T-AOC) in cells were significantly decreased (P<0.05). Compared with that of the control group, the content of malondialdehyde (MDA) in cells was significantly increased (P<0.05) after stimulation with 10000 ng/ml LPS for 9 h. After 9 h of stimulation with 100 ng/ml, 1000 ng/ml and 10000 ng/ml LPS, the total lipid drop area and triglyceride (TG) content of MAC-T cells were significantly decreased (P<0.05). The expression levels of fatty acid synthesis-related genes AcetylCoA carboxylase (ACC) and Stearoyl-CoA desaturase 1 (SCD-1) were significantly decreased after 9 h of stimulation with 100 ng/ml, 1000 ng/ml and 10000 ng/ml LPS (P<0.05), while the expression levels of Fatty Acid synthetase (FAS) were significantly decreased after stimulation with 1000 ng/ml and 10000 ng/ml LPS (P<0.05). TG synthesis by the related gene Diacylglycerol acyltransferase-1 (DGAT1) was significantly lower than that of the control group after stimulation with 1000 ng/ml and 10000 ng/ml LPS for 9 h (P<0.05), and Diacylglycerol acyltransferase-2 (DGAT2) also showed a significant decrease after 10000 ng/ml LPS stimulation (P<0.05). In conclusion, adding different concentrations of LPS to MAC-T cells not only led to a decrease in cell activity, resulting in oxidative damage, but also affected fatty acid and TG synthesis, which may ultimately be closely related to the decrease in milk fat synthesis.

This study aimed to explore the effects of sodium butyrate on liver metabolism in goats subjected to a high-concentrate diet. We randomly assigned twelve Saanen-lactating goats into two groups, one of which received a high-concentrate diet (concentrate: forage = 60:40, control group), while the other received the same basal diet supplemented with sodium butyrate (SB) (10 g/kg basal diet, SB group). Compared with the control diet, the SB diet considerably increased the milk fat percentage and content (p < 0.05), with an increase of 0.67% in the milk fat content of the SB group. By employing a global metabolomics approach based on ultra-performance liquid chromatography–tandem mass spectrometry (UPLC–MS/MS), we identified 6748 ions in ESI+ mode and 3573 ions in ESI− mode after liver isolation from both groups. A total of twenty-three metabolites, including phospholipids, fatty acids, and ribose phosphate, were found to be dysregulated according to a search against the human metabolome database (HMDB). Pathway analysis revealed activation of the pentose phosphate pathway, glycerophospholipid metabolism, and unsaturated fatty acid synthesis. The SB diet also modulated the expression of key lipogenic enzymes, such as acetyl-CoA carboxylase (ACC) and stearoyl-CoA desaturase (SCD-1), which are downstream targets of the transcription factor sterol regulatory element-binding proteins-1c (SREBP-1c), inducing a significant upregulation (p < 0.05). Furthermore, 6-phosphogluconate dehydrogenase (6PGDH) levels in the liver were elevated after the lactating goats were fed the SB diet (p < 0.05). Our study reveals that the SB diet may offer substantial benefits in enhancing the milk quality of subacute ruminal acidosis (SARA) goats. This is accomplished by augmenting the activity of the liver pentose phosphate pathway and the process of de novo fatty acid synthesis in lactating goats.

Insect resistance is an inherent characteristic of plants and determined by genotypic differences across plants. In this study, we determined differences in the gene expression patterns between two clones of Populus section Aigeiros after insect infestation and elucidated the mechanism of resistance induced by insect feeding. We performed differential gene expression (DEG) analysis by using Illumina Hiseq 2000 high-throughput sequencing of leaf samples from the upper, middle, and lower parts of Populus euramericana cv. ‘Neva’ (“P107”) and P. deltoids ‘Chuangxin’ (“P17-2”) infested with the insect. We selected 3,462 DEGs through a comparison between “P107” and “P17-2” (A vs. B). Based on the gene ontology analysis, the identified DEGs were functionally annotated, which revealed 20, 23, and 22 functional categories of “biological process”, “cellular component”, and “molecular function”, with enrichment mainly in “cellular process”, “cell part”, and “binding functions”, respectively. After insect feeding, the damaged leaves of “P107” and “P17-2” showed different degrees of resistance, along with upregulated defense gene expressions, reduced nutrient accumulation and photosynthesis, and enhanced secondary metabolite biosynthesis. This study provides a molecular basis for understanding the mechanism underlying insect resistance in plants.

The study of protein–protein interactions (PPIs) is of significant importance for elucidating biological processes, clarifying pathological mechanisms, and promoting drug development. In this study, we proposed a method to predict PPIs based on protein sequence and gene sequence information, combined with convolutional neural networks (CNNs). First, we extracted three types of features from protein sequence: global physicochemical properties features of the protein sequence, local same type of amino acid position variation features, and protein evolutionary conservation features; simultaneously, we extracted single nucleotide frequency and positional features, dinucleotide frequency features, and trinucleotide frequency features from the corresponding gene sequence. During the feature extraction process, we employed the amphiphilic pseudo amino acid composition (APAAC) method to extract the global hydrophobicity and hydrophilicity features of the protein sequence; we defined a new mathematical descriptor—$\mathsf{\theta }$ interval deviation product factor—to extract protein evolutionary conservation features from Position Specific Scoring Matrix (PSSM); we also defined a mapping function to map all nucleotides in the gene sequence onto a unit circle, and then extracted nucleotide positional features from the mapped points. Second, based on extracted features, we constructed a 36 × 32 sample feature grayscale map to represent a protein pair sample. Finally, we developed a CNN model to predict PPIs. Our method achieved superior results on four species test sets: an accuracy of 99.28% on the Saccharomyces cerevisiae dataset, 98.15% on the Drosophila melanogaster dataset, 98.62% on the Homo sapiens dataset, and 96.84% on the Mus musculus dataset, outperforming existing computational methods. Furthermore, we extended the application of this method to the prediction of protein–protein interaction networks and non-interaction networks, and also achieved promising results.