BEROLECMI: a novel prediction method to infer circRNA-miRNA interaction from the role definition of molecular attributes and biological networks.

Circular RNA (CircRNA)-microRNA (miRNA) interaction (CMI) is an important model for the regulation of biological processes by non-coding RNA (ncRNA), which provides a new perspective for the study of human complex diseases. However, the existing CMI prediction models mainly rely on the nearest neighbor structure in the biological network, ignoring the molecular network topology, so it is difficult to improve the prediction performance. In this paper, we proposed a new CMI prediction method, BEROLECMI, which uses molecular sequence attributes, molecular self-similarity, and biological network topology to define the specific role feature representation for molecules to infer the new CMI. BEROLECMI effectively makes up for the lack of network topology in the CMI prediction model and achieves the highest prediction performance in three commonly used data sets. In the case study, 14 of the 15 pairs of unknown CMIs were correctly predicted.

A controllability reinforcement learning method for pancreatic cancer biomarker identification.

Pancreatic cancer is one of the most malignant cancers with rapid progression and poor prognosis. The use of transcriptional data can be effective in finding new biomarkers for pancreatic cancer. Many network-based methods used to identify cancer biomarkers are proposed, among which the combination of network controllability appears. However, most of the existing methods do not study RNA, rely on priori and mutations information, or can only achieve classification tasks. In this study, we propose a method combined Relational Graph Convolutional Network and Deep Q-Network called RDDriver to identify pancreatic cancer biomarkers based on multi-layer heterogeneous transcriptional regulation network. Firstly, we construct a regulation network containing long non-coding RNA, microRNA, and messenger RNA. Secondly, Relational Graph Convolutional Network is used to learn the node representation. Finally, we use the idea of Deep Q-Network to build a model, which score and prioritize each RNA with the Popov-Belevitch-Hautus criterion. We train RDDriver on three small simulated networks, and calculate the average score after applying the model parameters to the regulation networks separately. To demonstrate the effectiveness of the method, we perform experiments for comparison between RDDriver and other eight methods based on the approximate benchmark of three types cancer drivers RNAs.

Human esophageal cancer stem-like cells escape the cytotoxicity of natural killer cells via down-regulation of ULBP-1.

BACKGROUND: Cancer stem-like cells (CSCs) play an important role in initiation and progression of aggressive cancers, including esophageal cancer. Natural killer (NK) cells are key effector lymphocytes of innate immunity that directly attack a wide variety of cancer cells. NK cell-based therapy may provide a new treatment option for targeting CSCs. In this study, we aimed to investigate the sensitivity of human esophageal CSCs to NK cell-mediated cytotoxicity. METHODS: CSCs were enriched from human esophageal squamous cell carcinoma cell lines via sphere formation culture. Human NK cells were selectively expanded from the peripheral blood of healthy donors. qRT-PCR, flow cytometry and ELISA assays were performed to examine RNA expression and protein levels, respectively. CFSE-labeled target cells were co-cultured with human activated NK cells to detect the cytotoxicity of NK cells by flow cytometry. RESULTS: We observed that esophageal CSCs were more resistant to NK cell-mediated cytotoxicity compared with adherent counterparts. Consistently, esophageal CSCs showed down-regulated expression of ULBP-1, a ligand for NK cells stimulatory receptor NKG2D. Knockdown of ULBP-1 resulted in significant inhibition of NK cell cytotoxicity against esophageal CSCs, whereas ULBP-1 overexpression led to the opposite effect. Finally, the pro-differentiation agent all-trans retinoic acid was found to enhance the sensitivity of esophageal CSCs to NK cell cytotoxicity. CONCLUSIONS: This study reveals that esophageal CSCs are more resistant to NK cells through down-regulation of ULBP-1 and provides a promising approach to promote the activity of NK cells targeting esophageal CSCs.

Proximity labeling expansion microscopy (PL-ExM) evaluates interactome labeling techniques.

Understanding protein-protein interactions (PPIs) through proximity labeling has revolutionized our comprehension of cellular mechanisms and pathology. Various proximity labeling techniques, such as HRP, APEX, BioID, TurboID, and µMap, have been widely used to biotinylate PPIs or organelles for proteomic profiling. However, the variability in labeling precision and efficiency of these techniques often results in limited reproducibility in proteomic detection. We address this persistent challenge by introducing proximity labeling expansion microscopy (PL-ExM), a super-resolution imaging technique that combines expansion microscopy with proximity labeling techniques. PL-ExM enabled up to 17 nm resolution with microscopes widely available, providing visual comparison of the labeling precision, efficiency, and false positives of different proximity labeling methods. Our mass spectrometry proteomic results confirmed that PL-ExM imaging is reliable in guiding the selection of proximity labeling techniques and interpreting the proteomic results with new spatial information.

A novel variant in the SPTB gene underlying hereditary spherocytosis and a literature review of previous variants.

BACKGROUND: Hereditary spherocytosis (HS, MIM#612641) is one of the most common hereditary hemolytic disorders. This study aimed to confirm a novel variant's pathogenicity and reveal a patient's genetic etiology. METHODS: The clinical data of a patient with HS who underwent genetic sequencing at the Children's Hospital of Chongqing Medical University were reviewed retrospectively. In silico prediction and in vitro minigene splicing reporter system were then conducted on the detected variant to analyze its intramolecular impact. A summary of the literature related to HS due to SPTB gene variants was also presented. RESULTS: A novel variant (c.301-2 A > G) in the SPTB gene (NM_001024858.4) was identified in the proband. Using Sanger sequencing, we conclusively confirmed that the inheritance of the variant could not be traced to the biological parents. The in vitro minigene assay revealed three different transcripts derived from the c.301-2 A > G variant: r.301_474del, r.301_306delCCAAAG, and r.301-1_301-57ins. Through a literature review, patients with HS who had been genotypically validated were summarized and the SPTB gene variant profile was mapped. CONCLUSION: We identified a splicing variant of the SPTB gene, thus confirming its aberrant translation. The novel variant was the probable genetic etiology of the proband with HS. Our findings expanded the variant spectrum of the SPTB gene, thus improving the understanding of the associated hereditary hemolytic disorders from a clinical and molecular perspective and contributing to the foundation of genetic counseling and diagnosis.

Alstomaphylines A-K, monoterpenoid bisindole alkaloids from Alstonia macrophylla with AChE inhibitory activity and cytotoxicity.

Eleven undescribed monoterpenoid bisindole alkaloids, alstomaphyines A-K (1-11), along with three known analogues were isolated from the leaves and stem bark of the Alstonia macrophylla. Compounds 1-3 were unprecedented dimerization alkaloids incorporating a macroline-type motif with an ajmaline-type motif via a C-C linkage. Their structures and absolute configurations were elucidated by extensive spectroscopic analysis, electronic circular dichroism (ECD) calculation, and CD exciton chirality method. Compounds 1-3 displayed potential inhibitory bioactivity against AChE with IC50 values of 4.44 ± 0.35, 3.59 ± 0.18, and 3.71 ± 0.23 µM, respectively. Enzyme kinetic study revealed compounds 1-3 as mixed competitive AChE inhibitors. Besides, compounds 8 and 12-14 exhibited better cytotoxicity against human cancer cell line HT-29 than cisplatin. Flow cytometry data revealed that compounds 8, 13, and 14 significantly induced the HT-29 cells arrest in G0/G1 phase in a concentration-dependent manner.

A new neuroprotective candidate TJ1 targeting amyloidogenesis in 5xFAD Alzheimer's disease mice.

As one of the main pathmechanisms of Alzheimer's disease (AD), amyloid-ß (Aß) is widely considered to be the prime target for the development of AD therapy. Recently, imidazolylacetophenone oxime ethers or esters (IOEs) have shown neuroprotective effects against neuronal cells damage, suggesting their potential use in the prevention and treatment of AD. Thirty IOEs compounds from our lab in-house library were constructed and screened for the inhibitory effects on Aß42-induced cytotoxicity. Among them, TJ1, as a new IOEs hit, preliminarily showed the effect on inhibiting Aß42-induced cytotoxicity. Furthermore, the inhibitory effects of TJ1 on Aß42 aggregation were tested by ThT assays and TEM. The neuroprotective effects of TJ1 were evaluated in Aß42-stimulated SH-SY5Y cells, LPS-stimulated BV-2 cells, and H2O2- and RSL3-stimulated PC12 cells. The cognitive improvement of TJ1 was assessed in 5xFAD (C57BL/6J) transgenic mouse. These results showed that TJ1 had strong neuroprotective effects and high blood-brain barrier (BBB) permeability without obvious cytotoxicity. TJ1 impeded the self-accumulation process of Aß42 by acting on Aß oligomerization and fibrilization. Besides, TJ1 reversed Aß-, H2O2- and RSL3-induced neuronal cell damage and decreased neuroinflammation. In 5xFAD mice, TJ1 improved cognitive impairment, increased GSH level, reduced the level of Aß42 and Aß plaques, and attenuated the glia reactivation and inflammatory response in the brain,. Taken together, our results demonstrate that TJ1 improves cognitive impairments as a new neuroprotective candidate via targeting amyloidogenesis, which suggests the potential of TJ1 as a treatment for AD.

Irisin attenuates acute glaucoma-induced neuroinflammation by activating microglia-integrin αVß5/AMPK and promoting autophagy.

Neuroinflammation, characterized by microglial activation and the release of multiple inflammatory mediators, is a key factor in acute glaucomatous injury leading to retinal ganglion cell (RGC) death and ultimately irreversible vision loss. Irisin, a novel exercise-induced myokine, has demonstrated anti-inflammatory activity in ischemia/reperfusion injuries across multiple organs and has displayed a significant neuroprotective role in experimental stroke disease models. This study examined the protective impact of irisin and investigated its potential mechanism involved in this process utilizing an acute ocular hypertension (AOH)-induced retinal injury model in mice and a microglia inflammation model induced by lipopolysaccharide (LPS). There was a transient downregulation of irisin in the retina after AOH injury, with parallel emergence of retinal neuroinflammation and RGC death. Irisin attenuated retinal and optic nerve damage and promotes the phenotypic conversion of microglia from M1 to M2. Mechanistically, irisin significantly upregulated the expression of integrin αVß5, p-AMPK, and autophagy-related markers. Integrin αVß5 was highly expressed on microglia but hardly expressed on RGC. The integrin αVß5 inhibitor cilengitide, the AMPK inhibitor dorsomorphin, and the autophagy inhibitor 3-Methyladenine (3-MA) blocked the neuroprotective effects of irisin. Our results suggest irisin attenuates acute glaucoma-induced neuroinflammation and RGC death by activating integrin αVß5/AMPK in microglia and promoting autophagy. It should be considered a potential neuroprotective therapy for acute glaucoma.

Using ensemble learning and hierarchical strategy to predict the outcomes of ESWL for upper ureteral stone treatment.

Urinary tract stones are a common and frequently recurring medical issue. Accurately predicting the success rate after surgery can help avoid ineffective medical procedures and reduce unnecessary healthcare costs. This study collected data from patients with upper ureter stones who underwent extracorporeal shock wave lithotripsy, including cases of successful as well as unsuccessful stone removal after the first and second lithotripsy procedures, and constructed prediction systems for the outcomes of the first and second lithotripsy procedures. Features were extracted from three categories of information: patient characteristics, stone characteristics, and extracorporeal shock wave lithotripsy machine data, and additional features were created using Feature Creation. Finally, the impact of features on the models was analyzed using six methods to calculate feature importance. Our prediction model for the first lithotripsy, selected from among 43 methods and seven ensemble learning techniques, achieves an AUC of 0.91. For the second lithotripsy, the AUC reaches 0.76. The results indicate that the detailed and binary information provided by patients regarding their history of stone experiences contributes differently to the predictive accuracy of the first and second lithotripsy procedures. The prediction tool is available at https://predictor.isu.edu.tw/ks.

Huntingtin contains an ubiquitin-binding domain and regulates lysosomal targeting of mitochondrial and RNA-binding proteins.

Understanding the normal function of the Huntingtin (HTT) protein is of significance in the design and implementation of therapeutic strategies for Huntington's disease (HD). Expansion of the CAG repeat in the HTT gene, encoding an expanded polyglutamine (polyQ) repeat within the HTT protein, causes HD and may compromise HTT's normal activity contributing to HD pathology. Here, we investigated the previously defined role of HTT in autophagy specifically through studying HTT's association with ubiquitin. We find that HTT interacts directly with ubiquitin in vitro. Tandem affinity purification was used to identify ubiquitinated and ubiquitin-associated proteins that copurify with a HTT N-terminal fragment under basal conditions. Copurification is enhanced by HTT polyQ expansion and reduced by mimicking HTT serine 421 phosphorylation. The identified HTT-interacting proteins include RNA-binding proteins (RBPs) involved in mRNA translation, proteins enriched in stress granules, the nuclear proteome, the defective ribosomal products (DRiPs) proteome and the brain-derived autophagosomal proteome. To determine whether the proteins interacting with HTT are autophagic targets, HTT knockout (KO) cells and immunoprecipitation of lysosomes were used to investigate autophagy in the absence of HTT. HTT KO was associated with reduced abundance of mitochondrial proteins in the lysosome, indicating a potential compromise in basal mitophagy, and increased lysosomal abundance of RBPs which may result from compensatory up-regulation of starvation-induced macroautophagy. We suggest HTT is critical for appropriate basal clearance of mitochondrial proteins and RBPs, hence reduced HTT proteostatic function with mutation may contribute to the neuropathology of HD.

Adipocyte pyroptosis occurs in omental tumor microenvironment and is associated with chemoresistance of ovarian cancer.

BACKGROUND: Ovarian carcinoma (OC) is a fatal malignancy, with most patients experiencing recurrence and resistance to chemotherapy. In contrast to hematogenous metastasizing tumors, ovarian cancer cells disseminate within the peritoneal cavity, especially the omentum. Previously, we reported omental crown-like structure (CLS) number is associated with poor prognosis of advanced-stage OC. CLS that have pathologic features of a dead or dying adipocyte was surrounded by several macrophages is well known a histologic hallmark for inflammatory adipose tissue. In this study, we attempted to clarify the interaction between metastatic ovarian cancer cells and omental CLS, and to formulate a therapeutic strategy for advanced-stage ovarian cancer. METHODS: A three-cell (including OC cells, adipocytes and macrophages) coculture model was established to mimic the omental tumor microenvironment (TME) of ovarian cancer. Caspase-1 activity, ATP and free fatty acids (FFA) levels were detected by commercial kits. An adipocyte organoid model was established to assess macrophages migration and infiltration. In vitro and in vivo experiments were performed for functional assays and therapeutic effect evaluations. Clinical OC tissue samples were collected for immunochemistry stain and statistics analysis. RESULTS: In three-cell coculture model, OC cells-derived IL-6 and IL-8 could induce the occurrence of pyroptosis in omental adipocytes. The pyroptotic adipocytes release ATP to increase macrophage infiltration, release FFA into TME, uptake by OC cells to increase chemoresistance. From OC tumor samples study, we demonstrated patients with high gasdermin D (GSDMD) expression in omental adipocytes is highly correlated with chemoresistance and poor outcome in advanced-stage OC. In animal model, by pyroptosis inhibitor, DSF, effectively retarded tumor growth and prolonged mice survival. CONCLUSIONS: Omental adipocyte pyroptosis may contribute the chemoresistance in advanced stage OC. Omental adipocytes could release FFA and ATP through the GSDMD-mediate pyroptosis to induce chemoresistance and macrophages infiltration resulting the poor prognosis in advanced-stage OC. Inhibition of adipocyte pyroptosis may be a potential therapeutic modality in advanced-stage OC with omentum metastasis.

Contrast­associated acute kidney injury in myocardial infarction patients undergoing elective percutaneous coronary intervention: insight from the Iodixanol-AKI Registry.

Previous studies have reported a high occurrence of contrast-associated acute kidney injury (CA-AKI) in myocardial infarction (MI) patients undergoing primary percutaneous coronary intervention (PCI). However, the data on CA-AKI in MI patients who underwent elective PCI are limited. To evaluate the incidence of CA-AKI in MI patients undergoing elective PCI. The data were sourced from the Iodixanol-AKI Registry of MI patients scheduled to undergo elective PCI in 8 medical centers from May 2020 to November 2021. The participants were divided into three groups: acute, prior, and multiple MI. The outcomes measured were CA-AKI and the composite endpoint of major adverse renal and cardiovascular events (MARCE). The incidence of CA-AKI was 4.46% (37/830) in the MI patients, 4.40% (7/159) in the acute MI patients, 4.41% (22/499) in the prior MI patients, and 4.65% (8/172) in the multiple MI patients. Of note, 36 patients (97.30%) at AKI stage 1, and only 1 patient at AKI stage 2. There was no difference in the incidence of CA-AKI (P = 0.991) among the three groups. Multivariate regression analysis revealed that the independent risk factors for CA-AKI were diabetes and an estimated glomerular filtration rate (eGFR) < 60 mL/min/1.73 m2. MARCE occurred in 3.4% (28/830) of the total patients and was not associated with either any subgroup of patients with MI or AKI. The incidence of CA-AKI was low and mainly limited to mildly impaired renal function in MI patients undergoing elective PCI.

A joint model for lesion segmentation and classification of MS and NMOSD.

Introduction: Multiple sclerosis (MS) and neuromyelitis optic spectrum disorder (NMOSD) are mimic autoimmune diseases of the central nervous system with a very high disability rate. Their clinical symptoms and imaging findings are similar, making it difficult to diagnose and differentiate. Existing research typically employs the T2-weighted fluid-attenuated inversion recovery (T2-FLAIR) MRI imaging technique to focus on a single task in MS and NMOSD lesion segmentation or disease classification, while ignoring the collaboration between the tasks. Methods: To make full use of the correlation between lesion segmentation and disease classification tasks of MS and NMOSD, so as to improve the accuracy and speed of the recognition and diagnosis of MS and NMOSD, a joint model is proposed in this study. The joint model primarily comprises three components: an information-sharing subnetwork, a lesion segmentation subnetwork, and a disease classification subnetwork. Among them, the information-sharing subnetwork adopts a dualbranch structure composed of a convolution module and a Swin Transformer module to extract local and global features, respectively. These features are then input into the lesion segmentation subnetwork and disease classification subnetwork to obtain results for both tasks simultaneously. In addition, to further enhance the mutual guidance between the tasks, this study proposes two information interaction methods: a lesion guidance module and a crosstask loss function. Furthermore, the lesion location maps provide interpretability for the diagnosis process of the deep learning model. Results: The joint model achieved a Dice similarity coefficient (DSC) of 74.87% on the lesion segmentation task and accuracy (ACC) of 92.36% on the disease classification task, demonstrating its superior performance. By setting up ablation experiments, the effectiveness of information sharing and interaction between tasks is verified. Discussion: The results show that the joint model can effectively improve the performance of the two tasks.

Ursodeoxycholic Acid Modulates the Interaction of miR-21 and Farnesoid X Receptor and NF-κB Signaling.

(1) Background: This study investigates the effects of Ursodeoxycholic acid (UDCA) on NF-κB signaling, farnesoid X receptor (FXR) singling, and microRNA-21 in HepG2 cells. (2) Methods: HepG2 cells were treated with lipopolysaccharide (LPS) to simulate hepatic inflammation. The investigation focused on the expression of NF-κB activation, which was analyzed using Western blot, confocal microscopy, and Electrophoretic Mobility-shift Assays (EMSA). Additionally, NF-κB and farnesoid X receptor (FXR) singling expressions of micro-RNA-21, COX-2, TNF-α, IL-6, cyp7A1, and shp were assessed by RT-PCR. (3) Results: UDCA effectively downregulated LPS-induced expressions of NF-κB/65, p65 phosphorylation, and also downregulated FXR activity by Western blot. Confocal microscopy and EMSA results confirmed UDCA's role in modulating NF-κB signaling. UDCA reduced the expressions of LPS-induced COX-2, TNF-α, and IL-6, which were related to NF-κB signaling. UDCA downregulated LPS-induced cyp7A1 gene expression and upregulated shp gene expression, demonstrating selective gene regulation via FXR. UDCA also significantly decreased micro-RNA 21 levels. (4) Conclusions: This study demonstrates UDCA's potent anti-inflammatory effects on NF-κB and FXR signaling pathways, and thus its potential to modulate hepatic inflammation and carcinogenesis through interactions with NF-κB and FXR. The decrease in micro-RNA 21 expression further underscores its therapeutic potential.

The Molecular Mechanisms of Cuproptosis and Small-Molecule Drug Design in Diabetes Mellitus.

In the field of human health research, the homeostasis of copper (Cu) is receiving increased attention due to its connection to pathological conditions, including diabetes mellitus (DM). Recent studies have demonstrated that proteins associated with Cu homeostasis, such as ATOX1, FDX1, ATP7A, ATPB, SLC31A1, p53, and UPS, also contribute to DM. Cuproptosis, characterized by Cu homeostasis dysregulation and Cu overload, has been found to cause the oligomerization of lipoylated proteins in mitochondria, loss of iron-sulfur protein, depletion of glutathione, production of reactive oxygen species, and cell death. Further research into how cuproptosis affects DM is essential to uncover its mechanism of action and identify effective interventions. In this article, we review the molecular mechanism of Cu homeostasis and the role of cuproptosis in the pathogenesis of DM. The study of small-molecule drugs that affect these proteins offers the possibility of moving from symptomatic treatment to treating the underlying causes of DM.

Cytological and Molecular Characterization of a New Ogura Cytoplasmic Male Sterility Restorer of Brassica napus L.

Ogura cytoplasmic male sterility (CMS) is considered the rapeseed (Brassica napus L.) with the most potential to be utilized as a heterosis system worldwide, but it lacks sufficient restorers. In this study, root tip cell (RTC) mitotic and pollen mother cell (PMC) meiosis observations were compared to ensure the number of chromosomes and the formation of a chromosomal bridge using restorer lines R2000, CLR650, and Zhehuhong (a new restorer) as the experimental material. Further, molecular markers of exogenous chromosomal fragments were detected and the sequence and expression differences of restorer genes in the three lines were determined to identify the distinctive characteristics of Zhehuhong. The results showed that the number of chromosomes in Zhehuhong was stable (2n = 38), indicating that the exogenous radish chromosome segment had been integrated into the chromosome of Zhehuhong. Molecular marker detection revealed that Zhehuhong was detected at most loci, with only the RMA05 locus being missed. The exogenous radish chromosome segment of Zhehuhong differed from R2000 and CLR650. The pollen mother cells of Zhehuhong showed chromosome lagging in the meiotic metaphase I, meiotic anaphase I, and meiotic anaphase II, which was consistent with R2000 and CLR650. The restorer gene PPRB in Zhehuhong had 85 SNPs compared with R2000 and 119 SNPs compared with CLR650, indicating the distinctive characteristic of PPRB in Zhehuhong. In terms of the spatial expression of PPRB, the highest level was detected in the anthers in the three restorer lines. In addition, in terms of temporal expression, the PPRB gene expression of Zhehuhong was highest at a bud length of 4 mm. Our results clearly indicated that Zhehuhong is a new restorer line for the Ogura CMS system, which can be used further in rapeseed heterosis utilization.

ESMSec: Prediction of Secreted Proteins in Human Body Fluids Using Protein Language Models and Attention.

The secreted proteins of human body fluid have the potential to be used as biomarkers for diseases. These biomarkers can be used for early diagnosis and risk prediction of diseases, so the study of secreted proteins of human body fluid has great application value. In recent years, the deep-learning-based transformer language model has transferred from the field of natural language processing (NLP) to the field of proteomics, leading to the development of protein language models (PLMs) for protein sequence representation. Here, we propose a deep learning framework called ESM Predict Secreted Proteins (ESMSec) to predict three types of proteins secreted in human body fluid. The ESMSec is based on the ESM2 model and attention architecture. Specifically, the protein sequence data are firstly put into the ESM2 model to extract the feature information from the last hidden layer, and all the input proteins are encoded into a fixed 1000 × 480 matrix. Secondly, multi-head attention with a fully connected neural network is employed as the classifier to perform binary classification according to whether they are secreted into each body fluid. Our experiment utilized three human body fluids that are important and ubiquitous markers. Experimental results show that ESMSec achieved average accuracy of 0.8486, 0.8358, and 0.8325 on the testing datasets for plasma, cerebrospinal fluid (CSF), and seminal fluid, which on average outperform the state-of-the-art (SOTA) methods. The outstanding performance results of ESMSec demonstrate that the ESM can improve the prediction performance of the model and has great potential to screen the secretion information of human body fluid proteins.

COVID-19 Serum Drives Spike-Mediated SARS-CoV-2 Variation.

Neutralizing antibodies targeting the spike (S) protein of SARS-CoV-2, elicited either by natural infection or vaccination, are crucial for protection against the virus. Nonetheless, the emergence of viral escape mutants presents ongoing challenges by contributing to breakthrough infections. To define the evolution trajectory of SARS-CoV-2 within the immune population, we co-incubated replication-competent rVSV/SARS-CoV-2/GFP chimeric viruses with sera from COVID-19 convalescents. Our findings revealed that the E484D mutation contributes to increased viral resistant against both convalescent and vaccinated sera, while the L1265R/H1271Y double mutation enhanced viral infectivity in 293T-hACE2 and Vero cells. These findings suggest that under the selective pressure of polyclonal antibodies, SARS-CoV-2 has the potential to accumulate mutations that facilitate either immune evasion or greater infectivity, facilitating its adaption to neutralizing antibody responses. Although the mutations identified in this study currently exhibit low prevalence in the circulating SARS-CoV-2 populations, the continuous and meticulous surveillance of viral mutations remains crucial. Moreover, there is an urgent necessity to develop next-generation antibody therapeutics and vaccines that target diverse, less mutation-prone antigenic sites to ensure more comprehensive and durable immune protection against SARS-CoV-2.