RESUMO
Recently, the incidence of malignant tumors is on the rise and searching for new treatments on it has become the research priority. Blocking the vascular endothelial growth factor (VEGF) and its receptor (VEGFR) is one of the treatment strategies that used in the development of specific anti-angiogenic drugs. The deficiencies in tissue penetration and affinity maturation become the weakness of these drugs in anti-tumors applications. The single heavy chain antibody found in Chiloscyllium plagiosum, which has a low molecular weight and superior tissue penetration of variable region (VNARs), was considered to have the high antigen binding activity and stability. This type of antibody has a simple structure that can be prokaryoticaly expressed, which makes it easily to produce new antiangiogenic target drugs. Specific anti-IgNAR rabbit multiple antibodies have been used to assess the level of VNARs in sharks and have shown a significant enrichment of IgNAR after triple immunization. An anti-VEGFR2 phage library was used for the targeted VNARs screening, and five candidate VNARs sequences were subsequently obtained by phage screening, followed by combined screening with the transcriptome library, and analysis of conserved regions along with 3D modelling matched the VNAR profile. ELISA and cell-based assays showed that two of the VNARs, VNAR-A6 and VNAR-E3, had a superior antigen affinity and anti-angiogenic activity thereby being able to inhibit human Umbilical Vein Endothelial Cells proliferation and migration. The anti-VEGFR2 VNARs derived from the immunized Chiloscyllium plagiosum and screened by phage library, which provide the new research ideas and specific approaches for the development of new drugs. The anti-VEGFR2 VNARs are capable for blocking the VEGF-VEGFR pathway, which of these may contribute to expanding the use of anti-angiogenic drugs.
RESUMO
IgNAR exhibits significant promise in the fields of cancer and anti-virus biotherapies. Notably, the variable regions of IgNAR (VNAR) possess comparable antigen binding affinity with much smaller molecular weight (â¼12 kDa) compared to IgNAR. Antigen specific VNAR screening is a changeling work, which limits its application in medicine and therapy fields. Though phage display is a powerful tool for VNAR screening, it has a lot of drawbacks, such as small library coverage, low expression levels, unstable target protein, complicating and time-consuming procedures. Here we report VANR screening with next generation sequencing (NGS) could effectively overcome the limitations of phage display, and we successfully identified approximately 3000 BAFF-specific VNARs in Chiloscyllium plagiosum vaccinated with the BAFF antigen. The results of modelling and molecular dynamics simulation and ELISA assay demonstrated that one out of the top five abundant specific VNARs exhibited higher binding affinity to the BAFF antigen than those obtained through phage display screening. Our data indicates NGS would be an alternative way for VNAR screening with plenty of advantages.
Assuntos
Sequenciamento de Nucleotídeos em Larga Escala , Tubarões , Tubarões/imunologia , Tubarões/genética , Animais , Proteínas de Peixes/genética , Proteínas de Peixes/imunologia , Proteínas de Peixes/química , Antígenos/imunologia , Antígenos/genética , Doenças dos Peixes/imunologiaRESUMO
The automatic classification of epilepsy electroencephalogram (EEG) signals plays a crucial role in diagnosing neurological diseases. Although promising results have been achieved by deep learning methods in this task, capturing the minute abnormal characteristics, contextual information, and long dependencies of EEG signals remains a challenge. To address this challenge, a positional multi-length and mutual-attention (PMM) network is proposed for the automatic classification of epilepsy EEG signals. The PMM network incorporates a positional feature encoding process that extracts minute abnormal characteristics from the EEG signal and utilizes a multi-length feature learning process with a hierarchy residual dilated LSTM (RDLSTM) to capture long contextual dependencies. Furthermore, a mutual-attention feature reinforcement process is employed to learn the global and relative feature dependencies and enhance the discriminative abilities of the network. To validate the effectiveness PMM network, we conduct extensive experiments on the public dataset and the experimental results demonstrate the superior performance of the PMM network compared to state-of-the-art methods.
RESUMO
Escherichia coli Nissle 1917 (EcN) is an important chassis strain widely used for the development of live biotherapeutic products (LBPs). EcN strain naturally harbors two cryptic plasmids with unknown function. During the development of LBPs using EcN strain, the cryptic plasmids were cured usually to avoid plasmid incompatibility or alleviate metabolic burdens associated with these cryptic plasmids. While the cryptic plasmids curing in EcN may appear to be a routine procedure, the comprehensive impact of cryptic plasmids curing on the EcN strain remains incompletely understood. In the present study, the effects of cryptic plasmids curing on EcN were investigated using transcriptome sequencing. The results revealed that only a small number of genes showed significant changes in mRNA levels after cryptic plasmid curing (4 upregulated and 6 downregulated genes), primarily involved in amino acid metabolism. Furthermore, the flu gene showed the most significant different expression, encoding Antigen 43 (Ag43) protein, a Cah family adhesin. Mass spectrometry analysis further confirmed the significant increase in Ag43 expression. Ag43 is commonly present in Escherichia coli and mediates the bacterial autoaggregation. However, despite the upregulation of Ag43 expression, no Ag43-mediated cell self-sedimentation was observed in the cured EcN strain. These findings contribute to making informed decisions regarding the curing of the cryptic plasmids when Escherichia coli Nissle 1917 is used as the chassis strain.