Identification of a peptide sequence targeting mammary vasculature via RPLP0 during lactation

TNF-α and RPLP0 drive the apoptosis of endothelial cells and increase susceptibility to high-altitude pulmonary edema

High-altitude pulmonary edema (HAPE) is a fatal threat for sojourners who ascend rapidly without sufficient acclimatization. Acclimatized sojourners and adapted natives are both insensitive to HAPE but have different physiological traits and molecular bases. In this study, based on GSE52209, the gene expression profiles of HAPE patients were compared with those of acclimatized sojourners and adapted natives, with the common and divergent differentially expressed genes (DEGs) and their hub genes identified, respectively. Bioinformatic methodologies for functional enrichment analysis, immune infiltration, diagnostic model construction, competing endogenous RNA (ceRNA) analysis and drug prediction were performed to detect potential biological functions and molecular mechanisms. Next, an array of in vivo experiments in a HAPE rat model and in vitro experiments in HUVECs were conducted to verify the results of the bioinformatic analysis. The enriched pathways of DEGs and immune landscapes for HAPE were significantly different between sojourners and natives, and the common DEGs were enriched mainly in the pathways of development and immunity. Nomograms revealed that the upregulation of TNF-α and downregulation of RPLP0 exhibited high diagnostic efficiency for HAPE in both sojourners and natives, which was further validated in the HAPE rat model. The addition of TNF-α and RPLP0 knockdown activated apoptosis signaling in endothelial cells (ECs) and enhanced endothelial permeability. In conclusion, TNF-α and RPLP0 are shared biomarkers and molecular bases for HAPE susceptibility during the acclimatization/adaptation/maladaptation processes in sojourners and natives, inspiring new ideas for predicting and treating HAPE.

Genome-wide association study using haplotype libraries and repeated measures model to identify candidate genomic regions for stillbirth in Holstein cattle

Reduced fertility is one of the main causes of economic losses on dairy farms, resulting in economic losses estimated at $938 per stillbirth case in Holstein herds. The identification of genomic regions associated with stillbirth could help to develop better management and breeding strategies aimed to reduce the frequency of undesirable gestation outcomes. Here, 10,570 cows and 50,541 birth records were used to perform a haplotype-based GWAS. A total of 41 significantly associated pseudo-SNPs (haplotypes within haplotype blocks converted to a binary classification) were identified after Bonferroni adjustment for multiple tests. A total of 117 positional candidate genes were annotated within or close (in a 200-kb interval) to significant pseudo-SNPs (haplotype blocks). The guilt-by-association functional prioritization identified 31 potential functional candidate genes for reproductive performance out of the 117 positional candidate genes annotated. These genes play crucial roles in biological processes associated with pregnancy persistence, fetus development, immune response, among others. These results helped us to better understand the genetic basis of stillbirth in dairy cattle and may be useful for the prediction of stillbirth in Holstein cattle, helping to reduce the related economic losses caused by this phenotype.

Genes and Pathways Affecting Sheep Productivity Traits: Genetic Parameters, Genome-Wide Association Mapping, and Pathway Enrichment Analysis

Ewe productivity is a composite and maternal trait that is considered the most important economic trait in sheep meat production. The objective of this study was the application of alternative genome-wide association study (GWAS) approaches followed by gene set enrichment analysis (GSEA) on the ewes’ genome to identify genes affecting pregnancy outcomes and lamb growth after parturition in Iranian Baluchi sheep. Three maternal composite traits at birth and weaning were considered. The traits were progeny birth weight, litter mean weight at birth, total litter weight at birth, progeny weaning weight, litter mean weight at weaning, and total litter weight at weaning. GWASs were performed on original phenotypes as well as on estimated breeding values. The significant SNPs associated with composite traits at birth were located within or near genes RDX, FDX1, ARHGAP20, ZC3H12C, THBS1, and EPG5. Identified genes and pathways have functions related to pregnancy, such as autophagy in the placenta, progesterone production by the placenta, placental formation, calcium ion transport, and maternal immune response. For composite traits at weaning, genes (NR2C1, VEZT, HSD17B4, RSU1, CUBN, VIM, PRLR, and FTH1) and pathways affecting feed intake and food conservation, development of mammary glands cytoskeleton structure, and production of milk components like fatty acids, proteins, and vitamin B-12, were identified. The results show that calcium ion transport during pregnancy and feeding lambs by milk after parturition can have the greatest impact on weight gain as compared to other effects of maternal origin.

Peptides for tumor-specific drug targeting: state of the art and beyond

This review outlines the most recent advances in peptide-mediated tumor-targeting and gives insight into the direction of the field.

Targeting osteosarcoma vasculature with peptide obtained by phage display

Aim of the study

Tumour endothelial cells have been proven to have molecular markers distinct from normal endothelial cells. These specific molecular markers allow for targeting of the tumour vasculature with specific pharmacological vehicles to direct diagnostic or therapeutic modalities at the endothelial cells. By performing a phage display-based screening, this study aimed to identify a certain short peptide that could specifically bind to osteosarcoma vasculature.

Material and methods

We performed in vivo screening in the murine models of osteosarcoma with annular Ph.D.-C7C library in the present study. To explore the in vivo binding specificity of the retrieved peptide, we conjugated the peptide with fluorescein isothiocyanate (FITC) and injected it intravenously into osteosarcoma-bearing BALB-c mice.

Results

CTKPDKGYC was the dominant sequence isolated from in vivo screening and was named as NF-1. Fluorescence staining found that FITC-NF-1 peptide could be specifically homed to osteosarcoma vasculature while being almost undetectable in the heart, brain, lung and liver. Simultaneously, a small amount of fluorescence could also be detected in the renal glomerulus and renal tubule but not in renal vascular endothelium, indicating that FITC-NF-1 peptide might be excreted mainly through the renal-urinary route.

Conclusions

Our data suggest that, with high binding specificity to osteosarcoma vasculature, peptide NF-1 may have potential value in early diagnosis or targeted therapy for osteosarcoma.

Identification of chondrocyte-binding peptides by phage display

As an initial step toward targeting cartilage tissue for potential therapeutic applications, we sought cartilage-binding peptides using phage display, a powerful technology for selection of peptides that bind to molecules of interest. A library of phage displaying random 12-amino acid peptides was iteratively incubated with cultured chondrocytes to select phage that bind cartilage. The resulting phage clones demonstrated increased affinity to chondrocytes by ELISA, when compared to a wild-type, insertless phage. Furthermore, the selected phage showed little preferential binding to other cell types, including primary skin fibroblast, myocyte and hepatocyte cultures, suggesting a tissue-specific interaction. Immunohistochemical staining revealed that the selected phage bound chondrocytes themselves and the surrounding extracellular matrix. FITC-tagged peptides were synthesized based on the sequence of cartilage-binding phage clones. These peptides, but not a random peptide, bound cultured chondrocytes, and extracelluar matrix. In conclusion, using phage display, we identified peptide sequences that specifically target chondrocytes. We anticipate that such peptides may be coupled to therapeutic molecules to provide targeted treatment for cartilage disorders.

In vivo phage display--a discovery tool in molecular biomedicine

In vivo phage display is a high-throughput method for identifying target ligands specific for different vascular beds. Targeting is possible due to the heterogeneous expression of receptors and other antigens in a particular vascular bed. Such expression is additionally influenced by the physiological or pathological status of the vasculature. In vivo phage display represents a technique that is usable in both, vascular mapping and targeted drug development. In this review, several important methodological aspects of in vivo phage display experiments are discussed. These include choosing an appropriate phage library, an appropriate animal model and the route of phage library administration. In addition, peptides or antibodies identified by in vivo phage display homing to specific types of vascular beds, including the altered vasculature present in several types of diseases are summarized. Still, confirmation in independent experiments and reproduction of identified sequences are needed for enhancing the clinical applicability of in vivo phage display research.

Machine learning study for the prediction of transdermal peptide

In order to develop a computational method to rapidly evaluate transdermal peptides, we report approaches for predicting the transdermal activity of peptides on the basis of peptide sequence information using Artificial Neural Network (ANN), Partial Least Squares (PLS) and Support Vector Machine (SVM). We identified 269 transdermal peptides by the phage display technique and use them as the positive controls to develop and test machine learning models. Combinations of three descriptors with neural network architectures, the number of latent variables and the kernel functions are tried in training to make appropriate predictions. The capacity of models is evaluated by means of statistical indicators including sensitivity, specificity, and the area under the receiver operating characteristic curve (ROC score). In the ROC score-based comparison, three methods proved capable of providing a reasonable prediction of transdermal peptide. The best result is obtained by SVM model with a radial basis function and VHSE descriptors. The results indicate that it is possible to discriminate between transdermal peptides and random sequences using our models. We anticipate that our models will be applicable to prediction of transdermal peptide for large peptide database for facilitating efficient transdermal drug delivery through intact skin.