EGR1, SOCS3, and THBS1, were related to FAdV-4 infection. Validation of nine randomly selected DEGs using quantitative reverse-transcription PCR produced results that were highly consistent with those of RNA sequencing. This transcriptomic profiling provides valuable information for investigating the molecular mechanisms underlying host–FAdV-4 interactions. These data support the current molecular knowledge regarding FAdV-4 infection and chicken defense mechanisms.Fowl adenovirus serotype 4 (FAdV-4) is a highly pathogenic virus with a broad host range that causes huge economic losses for the poultry industry worldwide. RNA sequencing has provided valuable and important mechanistic clues regarding FAdV-4–host interactions. However, the pathogenic mechanism and host's responses after FAdV-4 infection remains limited. In this study, we used transcriptome analysis to identify dynamic changes in differentially expressed genes (DEGs) at five characteristic stages  post infection (hpi) with FAdV-4. A total of 8,242 DEGs were identified based on comparison of five infection stages: 0 and 12, 12 and 24, 24 and 36, 36 and 48, and 48 and 60 hpi. In addition, at these five important time points, we found 37 common upregulated or downregulated DEGs, suggesting a common role for these genes in host response to viral infection. The predicted function of these DEGs using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses revealed that these DEGs were associated with viral invasion, host metabolic pathways and host immunosuppression. Interestingly, genes involved in viral invasion, probably  Aviadenovirus genus, Adenoviridae family. FAdV-4 is a non-enveloped virus with a double-stranded DNA genome. It is ~43.7 kb in length and encodes 11 and 32 structural and non-structural proteins, respectively (Fowl adenovirus serotype 4 (FAdV-4) is a member of the ectively –7.in vitro studies of host–FAdV-4 interactions  post infection (hpi) with FAdV-4. We then elucidated the molecular mechanisms  affected by viral infection. Our findings provide novel information regarding the mechanisms underlying virus–host interactions and the pathogenesis of FAdV-4.5 cells/well) were cultured in six-well plates maintained at 37°C in a 5% CO2 atmosphere in Dulbecco's modified Eagle's medium  with 10% fetal bovine serum (FBS). Cells were cultured for ~24 h to reach 80% confluence and subsequently infected with FAdV-4 (MOI = 0.1); uninfected LMH cells were used as a mock control. FAdV-4 infected with LMH Cells caused cytopathic effect (CPE), viral titers and viral loads as previously described (FAdV-4 isolate SX17 (GenBank: MF592716.1) and LMH cells were kindly provided by Dr. Jing-Yu Wang . LMH cells  was used to isolate total RNA from 18 samples (five groups) according to the manufacturer's instructions. RNA purity and concentration were determined by ultraviolet absorbance using a Nanodrop Nano Photometer spectrophotometer , while RNA integrity was evaluated using an Agilent 2100 Bioanalyzer . Total RNA (3 μg) was used to construct a cDNA library using an RNA Library Prep Kit for Illumina , according to the instructions provided by the manufacturer. In brief, total RNA was treated with DNaseI  to remove genomic DNA contamination. This was followed by enrichment of poly(A) mRNA using oligo d(T) magnetic beads (Invitrogen). mRNA was next treated with fragmentation buffer, and cleaved RNA was copied into first-strand cDNA fragments using reverse transcriptase (Invitrogen) and random hexamer primers. Second-strand cDNA fragments were synthesized using Second Strand Synthesis Enzyme Mix, including DNA polymerase I, buffer, deoxyribonucleoside triphosphate, and RNase H. After purification and paired-end repair, cDNA fragments were ligated to sequencing adapters and amplified by PCR to obtain the final paired-end library. Libraries were subsequently sequenced using the Illumina HiSeq 4000 sequencing platform .To ensure high accuracy and reliability of the results of subsequent analyses, the original ordinal number was determined by filtering to obtain high-quality sequencing data (clean data). The original sequencing data were filtered to remove low-quality reads as follows: (1) removal of adapter sequences with a quality score < 20 and sequences with an N base rate of raw reads > 10%; and (2) removal of adapter and quality-trimmed short segments <25 bp in length. The remaining reads were termed “clean reads” and stored in FASTQ format. For mapping clean reads, Bowtie 2 was used to build reference genes and HISAT  was used to reference the genome.http://www.geneontology.org) and Kyoto Encyclopedia of Genes and Genomes (KEGG) (http://www.genome.jp/kegg/) pathway databases. Cluster and Java Tree view software were used to conduct hierarchical cluster analysis of gene expression patterns. All gene expression data presented were obtained from three independent replicates. Original sequence data were submitted to the NCBI database (accession number: SUB9560975).For gene expression analysis, gene expression levels were calculated and RSEM (RNA-Seq by Expectation-Maximization) was used to estimate the unigene FPKM value. Default criteria of | log2 fold-change | > 1 and false discovery rate < 0.05 denoted significant changes in differentially expressed genes (DEGs). Gene Ontology (GO), and pathway annotation and enrichment analyses were performed using the National Center for Biotechnology Information GO  genome using HISAT  after infection with FAdV-4 ; the data obtained at these time points were compared with those obtained at 0 hpi . A total of 330.568 GB of clean data  were obtained. The average amount of clean data for each sample was 15.741 GB. The percentage of Q30 bases was > 92.28%, and the GC content ranged between 46.09 and 55.24%. Ribosomal RNA sequences were removed, and low-quality reads were discarded. We then mapped 18 high-quality reads to the chicken  . At 0 anHierarchical clustering analysis revealed gradual changes in gene expression across at 0 and 12, 12 and 24, 24 and 36, 36 and 48, and 48 and 60 hpi; the left side of the hierarchical clustering gene tree shows further classification of DEGs .We conducted GO analysis to identify the biological processes involved in FAdV-4 infection. Among DEGs between 0 and 12 hpi, 8,348 unigenes were assigned GO terms in the cellular component (676), molecular function , and biological process  categories, respectively. For the 12 and 24 hpi comparison, 9,742 unigenes were assigned to 834, 1,651, and 7,257 GO terms in the aforementioned categories, respectively. For the 24 and 36 hpi comparison, 9,695 unigenes were assigned to 844, 1,681, and 7,170 GO terms in the aforementioned categories, respectively. For the 36 and 48 hpi comparison, 9,856 unigenes were assigned to 831, 1,636, and 7,389 GO terms in the aforementioned categories, respectively. Finally, for the 48 and 60 hpi comparison, 10,482 unigenes were assigned to 906, 1,707, and 7,869 GO terms in the aforementioned categories, respectively. We next selected the 10 most significant molecular functions and biological processes with altered gene expression among viral infection stages .P-value < 0.05 , 12 and 24 hpi , 24 and 36 hpi (724 DEGs), 36 and 48 hpi , and 48 and 60 , were enriched to 138, 324, 321, 329, and 326 KEGG pathways, respectively. The 10 most enriched pathways were determined according to e < 0.05 . We idene < 0.05 .In order to further analyze the differential expression host immunosuppression genes response during FAdV-4 infection. KEGG enrichment analyze, the DEGs were significantly enriched in immune-related signaling pathways, such as, TNF signaling pathway, IL-17 signaling pathway, Apoptosis, P13K-Akt signaling pathway, cytokine-cytokine receptor interaction, Th17 cell differentiation, Th1 and Th2 cell differentiation, Toll-like receptor signaling path way . Meanwhiearly growth response 1 [EGR1], suppressor of cytokine signaling 3 [SOCS3], thrombospondin 1 [THBS1], interleukin-8 [IL8], suppressor of cytokine signaling 1 [SOCS1], TNF receptor superfamily member 8 [CD30], C-C motif chemokine ligand 4 [CCL4], phosphoenolpyruvate carboxykinase1 [PCK1], Apoptosis regulator proteins Bcl-2 [Bcl-2] and TNF receptor superfamily member 21 [TNFRSF21]  infection in broilers, laying hens, ducks, and geese have caused economic and social losses globally, including in India, South Korea, Hungary, Japan, Europe, and China , 18. As When FAdV-4 infects a host, a complex battle between host cells and the virus takes place. Continuous replication of the virus damages host cells to different degrees and alters their physiological functions, leading to differential gene expression. DEGs identified following FAdV-4 infection of LMH cells can be divided into five infection periods based on their differential expression patterns. At the first stage of infection (0 to 12 hpi), we detected 1,124 DEGs between 0 and 12 hpi. At 12 hpi, entry of FAdV-4 into LMH cells induces a strong immune response, and host cells enter a static phase of balanced offensive and defensive attacks , 20. TheFrom these five characteristic stages of FAdV-4 infection of host cells, we determined that regulation of host cell gene expression by FAdV-4 is specific, with FAdV-4 invading host cells to replicate its genome, produce new infectious virions, and spread virions to adjacent cells. These results are consistent with findings from previous studies on human adenovirus , 20. In SOCS1 or SOCS3 following viral infection promotes the replication of multiple viruses  pathway, toll-like receptor pathway, and endocytosis pathway, which are closely related to adenovirus infection , 19, 20.Therefore, further investigation the role of candidate genes and signal pathways may play essential roles in the regulation of FAdV-4 infection, will not only provide new molecular targets for the development of antiviral drugs but also contribute to research vaccines in poultry.As strictly intracellular parasites, viruses depend on manipulation of the host metabolism to obtain the necessary energy and nutrients for their own survival and proliferation. Considerable evidence has shown that viral infection  alters the metabolism of host cells –40. DiffPCK1, phosphofructokinase, muscle (PFKM), and alcohol dehydrogenase 1C (class I), gamma polypeptide (ADH1C), were upregulated at 12 and 48 hpi. Subsequently, during the rapid replication period of FAdV-4, expression levels of genes encoding various carbohydrate branch metabolites involved in fructose and mannose metabolism, glycosaminoglycan biosynthesis, tricarboxylic acid cycle, and the pentose phosphate pathway were significantly increased , BCL2L1 (Bcl-xL), BCL2 apoptosis regulator (BCL2); pro-apoptotic genes e.g., caspase 8 (CASP8), caspase 9 (CASP9), transcription factor subunit (FOS), Jun proto-oncogene, AP-1 transcription factor subunit (JUN), tubulin alpha 1a (TUBA1A), TUBA1B, TUBA1C, and TUBA3E  can be found in the article/XW conceived and designed the experiments and wrote sections of the manuscript. XW and BW performed the experiments. XZ, LM, and XL analyzed the data. MZ contributed reagents, materials, and analysis tools. All authors contributed to manuscript revision, read, and approved the submitted version.This work was supported by the National Natural Science Foundation of China [Grant No. NSFC32002313] and the Key Scientific Research Project of Henan Higher Education Institutions of China [Grant No. 20B230001].The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Mammalian LEM-domain proteins (LEMs) are encoded by seven genes, including LAP2, EMD, LEMD1, LEMD2, LEMD3, ANKLE1, and ANKLE2. Though some LEMs were involved in various tumor progression, the expression and prognostic values of LEMs in prostate adenocarcinoma (PRAD) have yet to be analyzed.Herein, we investigated the expression, survival data, and immune infiltration levels of LEMs in PRAD patients from ATCG, TIMER, LinkedOmics, and TISIDB databases. We also further validated the mRNA and protein expression levels of ANKLE1, EMD, and LEMD2 in human prostate tumor specimens by qPCR, WB, and IHC.We found that all LEM expressions, except for that of LAP2, were markedly altered in PRAD compared to the normal samples. Among all LEMs, only the expressions of ANKLE1, EMD, and LEMD2 were correlated with advanced tumor stage and survival prognosis in PRAD. Consistent with the predicted computational results, the mRNA and protein expression levels of these genes were markedly increased in the PRAD group. We then found that ANKLE1, EMD, and LEMD2 expressions were markedly correlated with immune cell infiltration levels. High ANKLE1, EMD, and LEMD2 expressions predicted a worse prognosis in PRAD based on immune cells. DNA methylation or/and copy number variations may contribute to the abnormal upregulation of ANKLE1, EMD, and LEMD2 in PRAD.Taken together, this study implied that ANKLE1, EMD, and LEMD2 were promising prognosis predictors and potential immunotherapy targets for PRAD patients.The online version contains supplementary material available at 10.1186/s12957-022-02640-z. LEM-domain proteins (LEMs), named for the founding human members Lamina-associated polypeptide 2 , Emerin (EMD), and MAN1 , represent one family of lamin-interacting proteins. In mammalian genomes, seven individual genes encode LEMs, including ANKLE1, ANKLE2, LEMD1, LEMD2, LAP2, EMD, and MAN1, five of which encode inner nuclear membrane proteins. Of those, ANKLE1 was an endonuclease possibly involved in DNA repair . LEMD2 wProstate cancer is the second most frequent cancer diagnosis made in men and the fifth leading cause of death worldwide, with 1,276,106 new cases and 358,989 deaths according to GLOBOCAN 2018 estimates . The priThe tumor microenvironment contains infiltrating immune cells, stromal cells, extracellular matrix, and tumor cells. Studies showed that tumor-infiltrating immune cells have different roles in the development of tumors. For example, N1 tumor-associated neutrophils suppressed tumor growth. In contrast, N2 tumor-associated neutrophils were shown to induce tumorigenesis and immunosuppression . For LEMThis study used the LinkedOmics database and R language to analyze LEM expressions and their association with the prognosis. Furthermore, we used TISIDB, TIMER, and UCSC Xena databases to investigate the correlation between ANKLE1, EMD, and LEMD2 expressions and tumor-infiltrated immune cells in the tumor microenvironment. We also further explored the molecular mechanisms of ANKLE1, EMD, and LEMD2 dysregulation, such as analysis of the DNA methylation, somatic mutations, and copy number variations. Our findings unveiled the crucial role of ANKLE1, EMD, and LEMD2 in PRAD prognosis. We further provided an underlying mechanism of the expressions of ANKLE1, EMD, and LEMD2 in potentially regulating the infiltration levels of immune cells, partly affecting the prognosis of PRAD.https://portal.gdc.cancer.gov/) and included 499 tumor samples and 52 normal samples. We used the deseq2 package (R version 3.6.3) for differentially expressed genes and clinical relevance analyses and ggplot2 for data visualization [The RNA-seq level 3 data and clinical data of PRAD patients were downloaded from the TCGA database . The TIMER web server (https://cistrome.shinyapps.io/timer/) was used to explore the relationship between immune-infiltrating cells/immune cell markers and gene expression that affects the clinical prognosis in PRAD. The levels of the gene expression were expressed as log2 RSEM.Survival analysis is a set of methods for evaluating time-to-event data that is widely applied across research disciplines. Standard survival analysis used the TCGA PRAD data and utilized the survminer and survival packages to display the KM plots . We calchttp://www.linkedomics.org/login.php) was used to analyze 32 TCGA cancer-associated multidimensional datasets. The co-expressed genes associated with LEM-domain proteins  were identified from the TCGA PRAD cohort through the LinkFinder module in the database, and the correlation of results was tested by the Pearson correlation coefficient and showed respectively in volcano plot and heat maps. Function module analyses of the Gene Ontology biological process (GO_BP), Gene Ontology cellular component (GO_CC), Gene Ontology molecular function (GO_MF), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were analyzed by the gene set enrichment analysis (GSEA) in the LinkInterpreter module.The LinkedOmics database , T cells, T helper cells, T central memory (Tcm), T effector memory (Tem), T follicular helper (Tfh), T gamma delta (Tgd), Th1 cells, Th17 cells, Th2 cells, and Treg cells [The GSVA package (R version 3.6.3) was used to infer the abundance of tumor-infiltrating immune cells from the gene expression profiles of the PRAD samples in the TCGA dataset . In thiseg cells . We usedhttp://cis.hku.hk/TISIDB) was utilized to analyze the associations of LEM-domain proteins  with lymphocytes, immunomodulators, and chemokines (or receptors).The TISIDB database (http://xena.ucsc.edu/) is a genome-related database, which brings approximately 200 public databases together, including TCGA, ICGC, TARGET, GTEx, and CCL. The database was used to examine the copy number and DNA methylation, somatic mutation, gene expression, and protein expression. Pearson’s correlation coefficient was used to evaluate the association between DNA methylation, gene mutation, and CNV and mRNA expressions of ANKLE1, EMD, and LEMD2.UCSC Xena database . Then, qRT-PCR was performed using a AG Biotechnology RT-PCR Kit with SYBR Green and specific primers. GAPDH-specific primers served as internal controls . qRT-PCR primer sequences were shown as follows: human ANKLE1 forward primer GACCCCAACGCTCGATCTG, reverse primer TCGGGCTCCTGAGTCTCTG; human EMD forward primer GCCATGGACAACTACGCAGA, reverse primer GTCGTCATTGTAGCCCTTGC; and human LEMD2 forward primer GGCTTGGTAATGCTTTACTCCC, reverse primer CTTGGCCTGACAGAACTCAT.Three-millimeter tumor sections were incubated with commercial polyclonal antibodies against ANKLE1 , EMD , and LEMD2  at 1:200 dilution overnight at 4 °C. Then, the sections were conjugated with horseradish peroxidase (HRP) antibody  at room temperature for 2 h, then covered by 3, 3-diaminobenzidine (DAB) . Then, all fields were observed under light microscopy. Control experiments without primary antibodies demonstrated that the signals observed were specific.For protein expression levels of ANKLE1, EMD, and LEMD2, the cell lysates were prepared by using RIPA (Elabscience). The above samples were subjected to SDS-PAGE gel, and the separated proteins were transferred onto the PVDF membranes. After blocking with 5% non-fat milk, the membranes were probed with primary Abs ANKLE1 , EMD , and LEMD2  overnight at 4 °C and then incubated with HRP-conjugated secondary Abs (1:7000) at room temperature for 2 h. The protein bands were examined by Fusion Fx7 (VILBER LOURMAT).t-test by using GraphPad Prism 7.0. . All p values less than 0.05 were considered significant.The LEM expressions were analyzed via the R project (3.6.3 version). Survival curves were generated using the TIMER web server and R project using the “survival” package. Spearman’s correlation analysis was used to evaluate the correlation of the gene expression in the TIMER. For bioassay validation, comparisons of the two groups of data were analyzed by a two-tailed Student’s p <0.001). However, the expressions of ANKLE2, TMPO, and LEMD3 had no significant differences between PRAD and normal samples  in PRAD. Similarly, upregulated level of EMD was correlated with worse prognostic outcomes in white populations  in PRAD. The increased expression of LEMD2 was correlated with worse prognostic outcomes in white populations  in PRAD. These results illustrated the prognostic value of the ANKLE1, EMD, and LEMD2 mRNA levels, following their clinical characteristics, particularly in the white populations of PRAD patients.Then, we investigated the association of ANKLE1, EMD, and LEMD2 expressions with different clinical characteristics of PRAD using the survival package of the R project  and CD8 T cells  in PRAD , neurophils , mast cells , and Th17 cells  in PRAD , pDC , and CD8 T cells  in PRAD , macrophages , mast cells , neurophils , Th1 cells , and Th17 cells  in PRAD  or CD8 T cells . However, LEMD2 expression was significantly negatively correlated with macrophages , neutrophil cells , mast cells , dendritic cells , B cells , Th1 cells , and Th17 cells  in PRAD  and ANKLE1 expression (p = 0.001) were significantly correlated with clinical prognosis in PRAD , general T cell markers , exhausted T cell marker , Th2 markers (GATA3), Th17 markers (STAT3), Treg markers , Tfh marker (BCL6), neutrophils markers , DC markers , B cells markers , and macrophages in PRAD  had a worse prognosis  and gene mutation  in PRAD , but not with a gene mutation in PRAD , but not with a gene mutation in PRAD  were critically involved in genetic and epigenetic regulation and were highly associated with the development of cancers. We verified the DNA methylation, gene mutation, and CNV levels of ANKLE1, EMD, and LEMD2 in PRAD via the UCSC Xena database. The results indicated that the expression of ANKLE1 mRNA correlated with DNA methylation, but not with CNV , produces type I pro-inflammatory cytokines IFN gamma and tumor necrosis factor (TNF) alpha [brightCD16dim/-CD9+CD49+ phenotype has also been observed in colorectal cancer patients [bright NK cell function in PRAD. Hence, the poor prognosis of PRAD may be associated with its recruiting and regulating immune cells.Then, we for the first time investigated the correlation between ANKLE1, EMD, and LEMD2 expression levels and immunotype markers in PRAD. The results implied that ANKLE1, EMD, and LEMD2 expressions were associated with immune infiltration in PRAD, especially in CD56F) alpha , 37, andF) alpha , 39. Morpatients . These pbright NK cells, it is inferred that these genes enriched in resting CD56bright NK cells of PRAD patients had a poor prognosis, which needs to be further validated by bioassays. In addition, co-expressed genes of ANKLE1, EMD, and LEMD2 were involved mainly in oxidoreductase activity. Oxidative phosphorylation-related genes were previously reported to be potential biomarkers of PRAD [Through the Kaplan-Meier plotter analysis by the TIMER database, high expression levels of ANKLE1, EMD, and LEMD2 enriched in resting NK cell cohorts of PRAD had a worse prognosis. Since ANKLE1, EMD, and LEMD2 expression levels were mainly associated with CD56 of PRAD . Then, iGenetic and epigenetic processes are very important in the regulation of gene expression . This stIn summary, the upregulated ANKLE1, EMD, and LEMD2 were strongly associated with clinicopathological features, poor prognosis, and immune cell infiltration. DNA methylation may attribute to ANKLE1 upregulated. DNA methylation and CNV may contribute to the increased levels of EMD and LEMD2 in PRAD. This study further found a new mechanism that ANKLE1, EMD, and LEMD2 expressions may affect the prognosis of PRAD through tumor immune infiltration. Hence, our study offers insights for further studies on tumor immunotherapy of PRAD. We also performed the validation bioassay for measurements of ANKLE1, EMD, and LEMD2 expression levels by qPCR, WB, and IHC. However, the current study is the preliminary part of a larger study. Undoubtedly, we will further study ANKLE1, EMD, and LEMD2 in PRAD to elaborate on the biological function of ANKLE1, EMD, and LEMD2 in the immune microenvironment and prognosis of PRAD patients.Additional file 1: Figure S1. The expression of LEM-domain proteins in PRAD. (A-C) The expression levels of ANKLE1, EMD and LEMD2 in different cancer tissues compared 42 to normal tissues in the TIMER database. (D-G) LEMD1, ANKLE2, TMPO and LEMD3 expression level in PRAD tissues compared to normal tissues (RNA-seq data from ATCG PRAD). The number of normal group is 52, the number of tumor group is 499. Compared with indicated group, * p<0.05, ** p<0.01, *** p<0.001, n.s.: no significant difference. Figure S2. The co-expression genes with ANKLE1 in prostate adenocarcinoma (PRAD) from the LinkedOmics database. (A-B) Top 50 genes positively and negatively related to ANKLE1 in PRAD showed, respectively, by heat maps. Red represents positively linked genes and blue represents negatively linked genes. (C) Survival map of the top genes positively and negatively associated with ANKLE1 54 in PRAD. (D-F) GO annotations of ANKLE1 in PRAD cohort. Figure S3. The co-expression genes with EMD in prostate adenocarcinoma (PRAD) from the LinkedOmics database. (A-B) Top 50 genes positively and negatively related to EMD in PRAD showed, respectively, by heat maps. Red represents positively linked genes and blue represents negatively linked genes. (C) Survival map of the top 20 genes positively and negatively associated with EMD in PRAD. 65 (D-F) GO annotations of EMD in PRAD cohort. Figure S4. The co-expression genes with LEMD2 in prostate adenocarcinoma (PRAD) from the LinkedOmics database. (A-B) Top 50 genes positively and negatively related to LEMD2 in PRAD showed, respectively, by heat maps. Red represents positively linked genes and blue represents negatively linked genes. (C) Survival map of the top 20 genes positively and negatively associated with LEMD2 in PRAD. 76 (D-F) GO annotations of LEMD2 in PRAD cohort. Figure S5. Comparison of Kaplan-Meier survival curves of the high and low expression of ANKLE1 in PRAD based on immune cells subgroups. (A–I) High ANKLE1 level enriched in Naïve B cells, resting dendritic cells, M2 macrophages, activated mast cells, neutrophils, M1 macrophage, monocytes, CD8 T cells and resting mast cells exhibited no significant differences in OS in PRAD. Figure S6. Comparison of Kaplan-Meier survival curves of the high and low expression of EMD in PRAD based on immune cells subgroups. (A–I) High EMD level enriched in Naïve B cells, resting dendritic cells, M2 macrophages, activated mast cells, neutrophils, M1 macrophage, monocytes, CD8 T cells and resting mast cells exhibited no significant differences in OS in PRAD. Figure S7. Comparison of Kaplan-Meier survival curves of the high and low expression of LEMD2 in PRAD based on immune cells subgroups. (A–I) High LEMD2 level enriched in Naïve B cells, resting dendritic cells, M2 macrophages, activated mast cells, neutrophils, M1 macrophage, monocytes, CD8 T cells and resting mast cells exhibited no significant differences in OS in PRAD. Figure S8. Raw data for western blot shown in Fig. Table S1. Correlation of ANKLE1, EMD and LEMD2 mRNA expression and prognosis in PRAD with different clinicopathological factors by R project. Table S2. The cox proportional hazard model of ANKLE1/135 EMD/LEMD2 and resting NK cells in PRAD (TIMER). Table S3. Correlation analysis between ANKLE1/155 EMD/LEMD2 and related gene markers of immune cells in prostate cancer samples (n=498) in TIMER 2.0.


Arachis hypogaea L.), a cosmopolitan oil crop, is susceptible to a variety of pathogens, especially Aspergillus flavus L., which not only vastly reduce the quality of peanut products but also seriously threaten food safety for the contamination of aflatoxin. However, the key genes related to resistance to Aspergillus flavus L. in peanuts remain unclear. This study identifies hub genes positively associated with resistance to A. flavus in two genotypes by comparative transcriptome and weighted gene co-expression network analysis (WGCNA) method. Compared with susceptible genotype , the rapid response to A. flavus and quick preparation for the translation of resistance-related genes in the resistant genotype  may be the drivers of its high resistance. WGCNA analysis revealed that 18 genes encoding pathogenesis-related proteins (PR10), 1-aminocyclopropane-1-carboxylate oxidase (ACO1), MAPK kinase, serine/threonine kinase (STK), pattern recognition receptors (PRRs), cytochrome P450, SNARE protein SYP121, pectinesterase, phosphatidylinositol transfer protein, and pentatricopeptide repeat (PPR) protein play major and active roles in peanut resistance to A. flavus. Collectively, this study provides new insight into resistance to A. flavus by employing WGCNA, and the identification of hub resistance-responsive genes may contribute to the development of resistant cultivars by molecular-assisted breeding.Cultivated peanut ( Aspergillus flavus L. during drying, storage, and transportation processes , such as PR10 , an approach that can be used to identify certain traits-related modules  agar plates. After incubation for 7 days at 30°C, conidia were collected and suspended in sterile water containing 0.05% tween-80 with a concentration of 2 × 106 CFU (spores/ml).Experiments were conducted at the Henan Provincial Key Laboratory for Oil Crops Improvement, Henan Institute of Crop Molecular Breeding, Zhengzhou city, Henan, China. Highly toxigenic strain R (J-11) and S (Zhonghua 12) genotypes were collected for the experiment. Samples were collected at 0 (T0), 24 (T1), 48 (T2), 72 (T3), 120 (T5), and 168 h (T7) after inoculation from the infected samples of R and S genotypes. In total, 36 samples (2 genotypes × 6 stages × 3 replicates) were analyzed. At each time interval , 10–12 seeds were frozen in liquid nitrogen for RNA isolation and subsequently RNA-seq. Three seeds were immediately fixed by electron microscopy fixative and scanned in Wuhan Sevicebio Biological Technology, Wuhan city, Hubei, China. Seven days after inoculation, the infection index was scored according to the previously described method  method  following the instructions of the manufacturer and deep sequenced by GENE DENOVO , using Illumina sequencing platform. Three independent biological replications were used, and each biological replication contained five samples.Arachis hypogaea L. genome  using HISAT 2. 2.4 with “-RNA-strandness RF” and other parameters set as a default  > 2 and false discovery rate (FDR) < 0.01. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of DEGs were also carried out to identify A. flavus stress-related genes involved in the key biological processes and metabolic pathways associated with A. flavus response. Mapping of the top 30 significant enriched ones (p < 0.05) was generated on the online website (https://www.omicshare.com/tools/) by GENE DENOVO , as described in the study by Li et al.  was selected as the internal reference  (2020). Peanut accessions with higher resistance  and susceptibility  to A. flavus (A. flavus infection process was observed by scanning electron microscopy (R and S penetrated the seed coat on the second day of infection (T2) and reached the cotyledons, where they acquired nutrients and produced aflatoxin (R seed coat compared with S (S was compared to genotype R on the third day after inoculation (T3)  aflatoxin B1 was detected  . At T7, detected . These rS-T5 and S-T7, which contained more mycelium and spores in kernels, the average mapping genome ratio of which was only 23.12 and 17.27%, respectively  database under accession: PRJNA825125.A total of 380,590,871,700 raw reads and 377,441,077,140 clean reads (clean ratio > 99.15 %) were obtained after filtering reads with low-quality. On average, 91.77% of reads could be mapped to the reference genome of peanut, except for ectively . As the  results . Pearson results  and prin results  manifest2fold change| > 2 and FDR < 0.01, a total of 3,670, 7,888, 4,708, 6,545, and 7,533, respectively, upregulated DEGs and 2,392, 3,872, 2,910, 3,138, and 3,273 downregulated DEGs in R were screened, while 6,601, 5,870, 6,838, 6,425, and 6,732 DEGs were significantly upregulated and 3,649, 3,389, 3,731, 4,444, and 5,057 DEGs downregulated in S at T1, T2, T3, T5, and T7 after infection, respectively  at the stage of T1, T3, T5, and T7. Whereas the number of DEGs  in R was significantly higher than that in S  at T2, which was the time when mycelial penetrated seed coat, implying that R developed a very strong and quick resistant response to A. flavus at T2, thus preventing the seed from being contaminated by aflatoxin  in genotype ylation” , suggested at T2 . Meanwhiansport” . It was  based on the similarity of their expression patterns  were analyzed subsequently  and AFB1 content, whereas darkslateblue (r2 = −0.75/−0.77) and maroon (r2 = −0.75/−0.73) were negatively correlated with the corresponding traits, implying that DEGs in darkslateblue and maroon may act positively in inhibiting the growth of A. flavus and aflatoxin production in seeds. Subsequently, sample expression patterns were clustered and visualized by heatmap to clearly understand the expression of genes in modules at different time points after inoculation by A. flavus. As shown in A. flavus, and was higher in R than in S from T1 to T7, implying their positive roles in A. flavus resistance in R. Whereas the genes in darkslateblue expressed more strongly in S than in R from T1 to T3, suggesting its relatively low correlation with A. flavus defense. Heatmap of module-module relationship showed that maroon was significantly negatively correlated with deeppink1  (To identify the key genes associated with resistance to 0 edges) , S5. Aft0 edges) . FurtherArahy. 8M77KD, arahy. FJZ5Z0, arahy. BKK3KP, arahy. TQJ4QI, arahy. EK7MW8 and arahy. 3X96H9) was characterized as members of Bet V 1 family protein, which were reported to function in degrading microbial nucleic acid for its ribonuclease activity , which catalyze the formation of ethylene from 1-aminocyclopropane-1-carboxylic acid (ACC) and play key roles in ethylene signaling pathway  in MAPK cascades, which could sense the extracellular stimuli and conduct signaling transduction process  , cytochrome P450 (arahy. DB7AVX), syntaxin of plants 121 , and pectinesterase (Arahy. 323PP5) were also identified as hub genes with resistance to A. flavus. Three genes were identified in maroon. Arahy. HTAW4M and arahy. E2N38F encode phosphatidylinositol transfer family protein (PITPs), which is a class of proteins ubiquitous in eukaryotes that can promote the transfer of lipid molecules between intracellular membrane components, and participate in the signal transduction process of plant stresses  superfamily protein that mainly regulates the expression of genes related to plant stress resistance through post-transcriptional modification of RNA  play an essential role in pattern-triggered immunity (PTI) response  is one of the major types of disease resistance proteins (R), which are sorted into other four categories, namely, detoxifying enzymes, NB-LRR proteins, transmembrane receptor protein with leucine-rich repeat structure, and protein kinase with leucine-rich repeat structure Pamela, . In prevPR10 genes, can enhance the resistance against both biotic and abiotic stresses in plants  detected, which were upregulated in R compared with S (arahy. DB7AVX). Gunupuru et al.  significantly increases the endogenous ethylene content of rice and enhances rice sheath blight resistance. Two ACC genes (Arahy.78SDCB.1 and Arahy.GI6PPK.1) were characterized as hub genes associated with A. flavus stress in peanut, suggesting that ethylene-mediated resistance responses may play an unignored role in resistance to A. flavus. Another hub gene identified in salmon4 was arahy. 323PP5 encoding pectinesterase or pectinesterase inhibitor. It is reported that pectin is the main component of plant cell wall, exists in the intercellular layer and the middle layer, and affects the rheology and adhesion properties of cells. Overexpression of AtPMEI2 and AtPMEI3 enhanced the resistance to Botrytis cinerea , is one of the SNARE  proteins and encodes syntaxin that has been shown to reside on the plasma membrane  identified from Salmon 4 module by WGCNA analysis implied that a more severe papilla response exists in R compared with S genotype, thus eventually preventing the A. flavus infection in kernels.It is reported that phosphorylation cascades, containing calcium-dependent protein kinases (CDPKs) and mitogen-activated protein kinase (MAPK), play a major role in PRR-derived signals transmission  were identified by the WGCNA method from DEGs , 1-aminocyclopropane-1-carboxylate oxidase (ACO1), MAPK kinase, STK, PRRs, cytochrome P450, SNARE protein SYP121, pectinesterase, phosphatidylinositol transfer protein, and PPR protein involved in PTI and ETI response in R compared with S from T3 to T7 may be the cause of R showing resistance to A. flavus. Our study provides a new insight into future peanut breeding and development of A. flavus resistant peanut varieties to mitigate aflatoxin contamination for food safety and peanut industry.A total of 18 genes were identified, which might be associated with resistance to PRJNA825125.The data presented in the study are deposited in the NCBI Sequence Read Archive (SRA) repository, accession number MC, SH, and XZ conceived the study and research plans. MC, JG, and DW collected plant materials and performed the experiments. MC, QZ, and MH analyzed the data. PD, ZS, and FQ participated in handling figures and tables. MC, ZZ, and BH drafted the manuscript. WD, PL, and XZ revised the manuscript. All authors read and approved the final manuscript.This study was supported by the China Agriculture Research System (CARS-13), the Key Scientific and Technological Project of Henan Province (201300111000), and the Henan Provincial Agriculture Research System, China (S2012-5).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Selenium-binding protein 1 (SELENBP1), a member of the selenium-containing protein family, plays an important role in malignant tumorigenesis and progression. However, it is currently lacking research about relationship between SELENBP1 and immunotherapy in colorectal cancer (CRC).We first analyzed the expression levels of SELENBP1 based on the Cancer Genome Atlas (TCGA), Oncomine andUALCAN. Chisq.test, Fisher.test, Wilcoxon-Mann-Whitney test and logistic regression were used to analyze the relationship of clinical characteristics with SELENBP1 expression. Then Gene ontology/ Kyoto encyclopedia of genes and genomes (GO/KEGG), Gene set enrichment analysis (GSEA) enrichment analysis to clarify bio-processes and signaling pathways. The cBioPortal was used to perform analysis of mutation sites, types, etc. of SELENBP1. In addition, the correlation of SELENBP1 gene with tumor immune infiltration and prognosis was analyzed using ssGSEA, ESTIMATE, tumor immune dysfunction and rejection (TIDE) algorithm and Kaplan-Meier (KM) Plotter database. Quantitative real-time PCR (qRT-PCR) and western blotting (WB) were used to validate the expression of SELENBP1 in CRC samples and matched normal tissues. Immunohistochemistry (IHC) was further performed to detect the expression of SELENBP1 in CRC samples and matched normal tissues.We found that SELENBP1 expression was lower in CRC compared to normal colorectal tissue and was associated with poor prognosis. The aggressiveness of CRC increased with decreased SELENBP1 expression. Enrichment analysis showed that the SELENBP1 gene was significantly enriched in several pathways, such as programmed death 1 (PD-1) signaling, signaling by interleukins, TCR signaling, collagen degradation, costimulation by the CD28 family. Decreased expression of SELENBP1 was associated with DNA methylation and mutation. Immune infiltration analysis identified that SELENBP1 expression was closely related to various immune cells and immune chemokines/receptors. With increasing SELENBP1 expression, immune and stromal components in the tumor microenvironment were significantly decreased. SELENBP1 expression in CRC patients affects patient prognosis by influencing tumor immune infiltration. Beside this, SELENBP1 expression is closely related to the sensitivity of chemotherapy and immunotherapy.Survival analysis as well as enrichment and immunoassay results suggest that SELENBP1 can be considered as a promising prognostic biomarker for CRC. SELENBP1 expression is closely associated with immune infiltration and immunotherapy. Collectively, our study provided useful information on the oncogenic role of SELENBP1, contributing to further exploring the underlying mechanisms.The online version contains supplementary material available at 10.1186/s12876-022-02532-2. CRC ranks third in incidence and second in mortality among all malignancies, and with environmental changes and an aging population, the incidence and mortality rates of CRC continue to rise significantly . CurrentSelenium is the only essential trace element that is genetically regulated and can be converted in vivo into selenium-containing amino acids for insertion into various proteins, regulating the activity of different selenoproteins . PreviouWe evaluated the association of SELENBP1 gene expression with immune infiltration and prognosis in CRC by analyzing clinical indicators and survival data from several databases. Our study revealed the molecular mechanism of SELENBP1 dysregulation in CRC, and the potential role in its development. In addition, we demonstrated the association between SELENBP1 and immunotherapy and chemotherapy. This may provide new insights into the treatment of CRC.http://www.cancergenome.nih.gov/) is a very important cancer database that containing clinical data, genomic variants, m/mi/lncRNA expression, DNA methylation and other data on various human cancers. The Genotype-tissue expression (GTEx) (https://cancergenome.nih.gov/) database is a normal tissue gene expression database, which is often used in conjunction with TCGA. We downloaded all SELENBP1 clinicopathological data, mRNA expression, methylation and other data from TCGA website in CRC, and collected transcripts per kilobase of exon model per million mapped reads (TPM) expression values of SELENBP1 in normal colorectal tissues from GTEx database to add supplementary control tissues.TCGA (https://www.oncomine.org/resource/main.html) contains comprehensive cancer mutation profiles, gene expression data and relevant clinical information to facilitate the discovery of new biomarkers [The Oncomine database  database is an interactive web-based resource platform that facilitate gene queries of the TCGA database, analyze and identify tumor-associated biomolecular markers, and analyze the molecular mechanisms of tumorigenesis, progression and metastasis, which are important for the diagnosis, treatment and prognosis of tumors, and can make researchers easier access to TCGA data and analysis results [The UALCAN (  results . This sthttp://biocc.hrbmu.edu.cn/CancerSEA/) is a single-cell sequencing database. It decodes the different functions of cancer cells from single-cell level, thus revealing the functional heterogeneity of cancer cells [CancerSEA  were screened between the two groups, and GO/KEGG analysis was performed on the upregulated DEGs using the clusterProfiler R package –21. In ahttp://www.cbioportal.org/index.do) contains data from 200 tumor genomic studies, including large tumor research projects such as TCGA and International Cancer Genome Consortium (ICGC). It can be used to analyze the mutation of a gene in different cancers, including the mutation site, type, amino acid change and the corresponding protein 3D structure, etc. [The cBioPortal database  [The association of SELENBP1 and 24 immune cells was analyzed by the ssGSEA algorithm in the "GSVA" package , 26. We alysis/) .https://www.cancerrxgene.org/), which contains a large number of drug sensitivity and genomic datasets [http://www.broadinstitute.org/ctrp/) covers associations between compound sensitivities and genetic or genealogical characteristics for a wide range of cancer cell lines [The Genomics of Cancer Drug Sensitivity (GDSC) database . Tissue protein (20 μg) were separated via 8% SDS-PAGE. After the run in electrode buffer the gel was transferred to PVDF membranes . Membranes were blocked with 5% bovine serum albumin in TBST (TBS with 0.1% Tween-20), and incubated with primary antibodies specific for SELENBP1  and β-actin  overnight at 4℃. PVDF membranes were washed three times for 5 min in TBST and incubated with anti-rabbit secondary antibody  or anti-mouse secondary antibody  for 1 h at room temperature. The membranes were washed as described above and developed using enhanced chemiluminescence assay (PJ2022-09-57)., and the total RNA was reverse transcribed with HiScript QRT SuperMix for qPCR Kit . The cDNA was amplified using SYBR Green Master mix . The amount of target gene was calculated by 2-ΔΔCt with as reference gene β-actin. The PCR primers used were as follows: SELENBP1 forward: ACCCAGGGAAGAGATCGTCTA, reverse: ACTTGGGGTCAACATCCACAG; β-actin forward: CATGTACGTTGCTATCCAGGC, reverse: CTCCTTAATGTCACGCACGAT.Paracancer tissues and cancer tissues of total RNA were collected and isolated using TRIzol . Before synthesizing cDNA, gDNA-wiper mix  was used to remove genomic DNASection of colorectal cancer tissue were obtained from 5 operable patients who underwent curative surgery in The First Affiliated Hospital of Anhui Medical University. The study was approved by the ethics committee of First Affiliated Hospital of Anhui Medical University (PJ2022-09-57).Tumor tissues were used by immunohistochemical staining, performed on formalin-fixed paraffin-embedded, and cut into 4-μm thickness section. After overnight incubation with anti-SELEBNP1 antibody , the sections were incubated with secondary antibody, visualized with DAB detection.GraphPad Prism and R software were used for data analysis and visualization. RT-PCR results were compared using Students' t-test. Chisq.test, Fisher.test, Wilcoxon rank sum test and Logistic regression were used to correlate SELENBP1 expression and clinicopathological characteristics. The relationship between SELENBP1 gene expression and survival of patients was analyzed using the Kaplan–Meier (KM) model. Correlations between the SELENBP1 gene and other genes was performed by using Spearman's correlation analysis. P < 0.05 indicates a significant difference.We first assessed SELENBP1 expression in pan-cancer data from TCGA and GTEx. The analysis revealed SELENBP1 expression was decreased in 27 different types of tumors, including ACC, BLCA, BRCA, CESC, CHOL, COAD, DLBC, ESCA, HNSC, GBM, KICH, KIRC, KIRP, LAML, LGG, LIHC, LUAD, LUSC, OV, PAAD, PCPG, PRAD, STAD, READ, THCA, THYM, and UCS. In contrast, its expression of SELENBP1 was high in SKCM, TGCT, and UCEC  was significantly prolonged in the high expression group Fig. a. We alsP < 0.05). The volcano plot showed that 429 genes were differentially expressed, containing 249 up-regulated and 180 down-regulated genes  were screened between the two groups , cg16911672 , cg07680533  cg24486037 , cg26065909 , cg24480379 , and cg18515587 , with a significant negative correlation in methylation  can eliminate tumors by suppressing the immune escape of tumor cells and enhancing the immune response of T cells . SubsequTo assess the effect of SELENBP1 expression on the efficacy of chemotherapy and immunotherapy, we calculated the drug half maximal inhibitory concentration (IC50) and TIDE values in the SELENBP1 high expression group versus the low expression group. First, we predicted the response of SELENBP1 expression to several common targeted and chemotherapeutic agents such as GW 441756, WZ3105, Axitinib, Foretinib, Cisplatin, Vinorelbine, Paclitaxel, Gemcitabine, based on GDSC database. The results showed that the IC50 values of all these drugs were higher in the high SELENBP1 expression group, which indicated better drug efficacy in the low SELENBP1 expression group Fig. a–h. In aCRC is one of the leading causes of cancer-related deaths. Screening and diagnosis of CRC is crucial for reducing incidence rate and mortality rate. Studies have shown that biomarkers can be used for early diagnosis, treatment options and prognostic assessment of CRC , 48. HowSelenium as a microelement has important functions in physiological processes and cancer prevention . Its rolThrough a comprehensive analysis of multiple databases, we found that SELENBP1 was expressed at a low level in a variety of cancers. In addition, the expression of SELENBP1 was low in all subtypes of CRC. Our further analysis revealed that low expression of SELENBP1 usually indicates poor prognosis, such as shortened OS. To further investigate the functions of SELENBP1 in CRC, we performed enrichment analysis using TCGA data. The results showed that PD-1 signaling, signaling by interleukins, TCR signaling, collagen degradation, MHC class II antigen presentation, costimulation by the CD28 family, antigen processing cross presentation, was enriched to different degrees. SELENBP1 may influence the development of CRC by affecting these pathways, leading to poor prognosis for CRC patients.In the past few years, immunotherapy has developed rapidly and has become an important tool in the treatment of CRC . Our stuThrough the analysis we found negative correlation between SELENBP1 expression and TMB and MSI, however, based on TMB, MSI did not accurately predict the efficacy of ICB therapy. The effectiveness of ICB treatment is influenced by various factors such as PD-L1 expression , MSI 5656, interIn summary, this analysis showed that SELENBP1 may be lower expressed in CRC due to mutation and DNA methylation and is associated with poorer survival. Reduced SELENBP1 expression increased the invasiveness of CRC. In addition, SELENBP1 expression was also associated with immune infiltration and the efficacy of immunotherapy. Therefore, SELENBP1 is an important prognostic biomarker in CRC, and further exploration of the relationship between SELENBP1 and immune infiltration is essential to elucidate the value of SELENBP1 in the treatment of CRC.Additional file 1. Supplementary Figs. 1–4. Supplementary Fig. 1. The scans of immunoblots from Fig. Supplementary Fig. 2. Relationship between SELENBP1 expression and prognosis of cancer patients.  OS was significantly prolonged in patients with high SELENBP1 expression in HNSC, LUAD, LIHC, THCA, MESO, SARC, BLCA.  Reliability of SELENBP1 expression in HNSC, LUAD, LIHC, THCA, MESO, SARC, BLCA in predicting OS. Supplementary Fig. 3. Correlation of SELENBP1 with immune cell infiltration in CRC. (a) Lollipop plot showing the correlation of SELENBP1 with 24 immune cell subsets in CRC. (b–r) Scatter plots showing positive correlation of SELENBP1 with eosinophils, B cells and Th17 cells, and negative correlation with macrophages, Th1 cells, neutrophils, Th2 cells, Tgd, NK cells, T helper cells, Tem, cytotoxic cells, Tcm, CD8 T cells, aDC and DC. Supplementary Fig. 4. Immune cell subgroup-based analysis of SELENBP1 expression levels in relation to OS in CRC patients(a)  Decreased B cells, (b) Enriched B cells, (c) Enriched CD4+T cells, (d)Enriched CD8+T cells, (e) Decreased CD8+T cells, (f)Enriched eosinophils, (g)Decreased eosinophils, (h)Enriched macrophages, (i) Decreased macrophages, (j)Enriched mesenchymal stem cells, (k) Decreased mesenchymal stem cells, (l)Enriched Natural killer T cells, (m) Decreased Natural killer T cells, (n) Enriched regulatory T cells, (o) Decreased regulatory T cells, (p) Enriched type 1 T-helper cells, (q) Decreased type 1 T-helper cells, (r) Enriched type 2 T-helper cells.


Apostichopus japonicus embryo and larvae. Collectively, this research will enable us to have a more comprehensive understanding of the holothuroid embryonic and larval nervous system and gain insights into the potential functions of neuropeptidergic systems in holothuroid larvae.Pentamerous radial symmetrical echinoderm adults develop from bilaterally symmetrical larvae and are a great model for understanding the origin and evolution of deuterostome nervous systems. Neuropeptides are important neuronal signaling molecules that regulate diverse behavioral and physiological processes in animals including echinoderms. In this study, we revealed the remarkable complexity of embryonic and larval nervous systems, identified the neuropeptide profile, and quantified the expressions of specific neuropeptide precursor genes in Apostichopus japonicus. The results revealed that the nervous system of embryos and larvae is mainly distributed in the anterior apical region, ciliary bands or rings, and the feeding and attachment organs, and that serotonergic immunoreactivity was not observed until the embryo developed into the late gastrula; these are evolutionarily conserved features of echinoderm, hemichordate and protostome larvae. Furthermore, based on available transcriptome data, we reported the neuropeptide precursors profile at different embryonic and larval developmental stages. This analysis showed that 40 neuropeptide precursors present in adult sea cucumbers were also identified at different developmental stages of embryos and larvae, and only four neuropeptide precursors  predicted in adults were absent in embryos and larvae. Combining the quantitative expression of ten specific neuropeptide precursor genes (NPs) by qRT-PCR, we revealed the potential important roles of neuropeptides in embryo development, feeding and attachment in A. japonicus larvae. In conclusion, this work provides novel perspectives on the diverse physiological functions of neuropeptides and contributes to understanding the evolution of neuropeptidergic systems in echinoderm embryos and larvae.Here, we described the complex nervous system at five early developmental stages  of a holothurian species with highly economic value,  Echinoderms have attracted attention from many scholars because of their key evolutionary status, strong regenerative ability, and morphological diversity . Adult eStrongylocentrotus purpuratus, Paracentrotus lividus, the asteroids Patiria miniata, Asterias rubens, the ophiuroids Amphipholis kochii, the crinoids Antedon mediterranea, Metacrinus rotundus, Anneissia japonica, and also the holothuroids Apostichopus californicus, Apostichopus parvimensis and Apostichopus japonicus [Apostichopus japonicus, a classical planktotrophic sea cucumber, has multiple larval strategies and its life cycle can be divided into eight major stages: fertilization (0 hpf (hours post fertilization)), blastula (14 hpf), gastrula (24 hpf), auricularia (48 hpf), doliolaria (11 dpf (days post fertilization)), pentactula (12 dpf), juvenile (16 dpf), and adult [Unlike their pentaradial adults, the echinoderm larval nervous system usually shows bilateral serotonergic neurons and nerve tracts along the ciliary bands, serotonin-positive cells first appear at the gastrula stage in holothuroids, echinoids, asteroids and ophuiroids, playing a role in embryogenesis and swimming ,12,13,14aponicus ,20,21,22aponicus ,20,21,22aponicus ,23. Aposgastrula  hpf, aurnd adult , a comprNeuropeptides are considered to be the oldest neuronal signaling molecules in metazoans, which makes them optimal tracers for neuroendocrine activity ,27,28. SA. japonicus, which represents the most comprehensive resource to date for sea cucumber neuropeptide research [A. japonicus Kisspeptin-type precursor (AjKPP), A. japonicus Gonadotropin-releasing hormone-type precursor (AjGnRHP), A. japonicus Calcitonin-type precursors (AjCTP1/2: AjCTP1 and AjCTP2), A. japonicus MPMNPADYFSRGTVYIPTRDS precursor (AjMS21P), A. japonicus Pedal peptide-type precursor 2 (AjPPLNP2), A. japonicus Vasopressin/oxytocin-type precursor (AjholotocinP), A. japonicus Thyrotropin-releasing hormone (TRH)-type precursor (AjTRHP), A. japonicus Bursicon alpha-type precursors (AjBAP), and A. japonicus Orexin-type precursors (AjOXP1 and AjOXP2) by quantitative real-time PCR (qRT-PCR). Nine of the NPs that we selected, except AjMS21P, were chosen because they have been reported in other echinoderms previously and our group has performed functional research on these and proven their importance in biological processes in adult sea cucumbers (unpublished data). The remaining NP (AjMS21P) has only been identified in A. japonicus to date and possibly plays important roles in adult sea cucumbers [The foundation for the present study was our recent identification of 44 neuropeptide precursor transcripts in the CNR of adult research . Howeverucumbers . The preA. japonicus (blastula (14 hpf), gastrula (24 hpf), late-gastrula (34 hpf), auricularia (48 hpf), doliolaria (11 dpf), and pentactula (12 dpf)) specimens were collected from Shandong oriental ocean sea cucumber breeding farm  in May 2020. The embryos and larvae were cultured in filtered sea water  under the density of 0.5~0.8 individual/ml (ind/mL) and all specimens were collected using a 60 μm filter. For immunostaining, the specimens were fixed in 4% paraformaldehyde (PFA) in 0.1 M phosphate-buffered saline (PBS) for 15 min at room temperature (RT) and were washed four times in PBS. The animals were dehydrated through a graded methanol series and then transferred into ice-cold methanol and stored at −20 °C until use [Typical early period embryos and larvae of gastrula 4 hpf, lantil use . For qRTA. japonicus larvae were transferred onto adhesion microscope slides (Citotest) and dried at 25 °C for 10 mins. Specimens were then circled with a Liquid Blocker pen and incubated with 3% H2O2 resolutions at room temperature (RT) for 25 min to pre-block. Blocking was carried out using 5% goat serum  for 30 min at RT followed by subsequent incubation with primary antibodies in PBST overnight at 4 °C. The primary antibodies were: mouse anti-acetylated α-tubulin  used at 1:200 and rabbit anti-serotonin  used at 1:200. After incubation, primary antibodies were removed by three washes in PBST for 10 mins each at RT. Specimens were then incubated for 1 hour at RT with one of two secondary antibodies diluted 1:600 in PBS: Alexa Fluor 488-AffiniPure Goat Anti-Rabbit IgG (H+L)  or Rhodamine (TRITC)–conjugated Goat Anti-Mouse IgG(H+L) . Nuclear staining was performed for 10 mins at RT using DAPI . To test the specificity of the antibodies, negative control treatments were carried out by omission of the primary antibody  were downloaded from the NCBI database (accession numbers: SRR6075435-SRR6075438). As the original source reported, one replicate per stage (~100 embryos/larvae) was used for transcriptome sequencing, resulting in 230.8 million raw paired-end reads [A. japonicus [The transcriptomes of nd reads . Low-quand reads . The clend reads ,74. Finand reads  with accaponicus  were subA. japonicus embryos and larvae using Trizol  according to the manufacturer’s instructions, and the RNA quality was determined via spectrophotometry using a NanoDrop 2000  and 1% agarose gel electrophoresis. The full-length cDNA sequences encoding AjTRHP, AjPPLNP2, AjMS21P, AjCTP1, AjCTP2 and AjHolotocinP were amplified using a SMARTer® RACE 50/30 Kit  as described in Wang et al. (2019) [Total RNA was isolated from . (2019)  and sequ3–7 × 103 individuals/replicate per stage) was isolated. Relative transcript levels were determined using a TB Green® Premix Ex Taq™ (Tli RNaseH Plus)  with a StepOnePlus . Each sample was run in triplicate. The specific primers for NPs were designed using Primer 6 software (Version 5.0) and are listed in the AjCTP1, which has only one more short-fragment exon as compared with AjCTP2, making it difficult to design specific primers to distinguish them. Therefore, the common part of the two sequences was applied to design a specific primer for detecting the total relative transcript levels of AjCTP1/2 (AjCTP1 + AjCTP2). β-actin  and β-Tubulin  were used as housekeeping genes for standardization, as previously validated [−ΔΔCT method was applied to analyze the comparative expression levels. All data are given as the mean ± S.E. (n = 6) and were analyzed using a one-way analysis of variance (ANOVA) followed by a Tukey post hoc test . The level of statistical significance was set at p < 0.05.The samples at five stages were collected and RNA from six biological replicates , SRR6075438 (gastrula), SRR6075435 (auricularia), and SRR6075436 (pentactula) with the e-value setting set to 0.01 [Cholecystokinin-type precursor1 (CCKP1), Somatostatin-type precursors (SSP1 and SSP2) and Corazonin-type precursor (CRZP) were only present at the pentactula stage. One third of the NPs were not transcribed until the larvae developed into the auricularia stage, and Bursicon beta-type precursors (BBP) were only found in blastula. NP9 and NP15 of NPs that have, thus far, been expressed as specific to echinoderms appeared at all four stages. L-type SALMFamide precursor (L-SALMFaP) was absent only in gastrula larvae; whereas F-type SALMFamide precursor (F-SALMFaP) was absent at the blastula and pentactula stages. Some NPs, such as AN peptide precursor (ANPP) and NP23, were present only at the pentactula or auricularia stages. NP25 were not transcribed at the first two stages (blastula and gastrula). For NPs that were previously discovered in A. japonicus, none of the NPs were present at all four stages and the GLRFA precursor (GLRFA-P), GN19 precursor (GN19P) and MS21P were found at the late developmental stages (auricularia and pentactula stages). StichopinP was only expressed in the pentactula stage. Other novel putative neuropeptide precursors were found only when neuropeptide precursor 11-like precursor (NP11LP) were expressed in pentactula. Interestingly, four neuropeptide precursors  predicted in adults were absent in embryos and larvae.A total of 44 neuropeptide precursor transcripts predicted in adult aponicus  were sub to 0.01 . The resAjKPP were detected in the first three stages, which was significantly lower than that in the doliolaria and pentactula (p < 0.05) (AjGnRHP was significantly highly expressed in the blastula stage (p < 0.05) (AjCTP1/2 was barely expressed until the larvae developed into thee pentactula stage (AjMS21P (AjPPLNP2 (p < 0.05). Similar with AjPPLNP2 and AjMS21P, AjHolotocinP had a peak expression at the auricularia stage, but there was no difference among the five stages (p > 0.05)  (AjBAP was significantly highly expressed in embryos (blastula and gastrula) than in larvae, especially in the blastula  and larvae  stages  were detected using quantitative real-time PCR (qRT-PCR) . The ten < 0.05) A, and Aj < 0.05) B. AjCTP1la stage C. AjMS21(AjMS21P D and AjPAjPPLNP2 E had a d > 0.05) F. For Aj < 0.05) G. AjBAP blastula H. AjOXP1la stage I, whereala stage J. Overalla stage K,L.A. japonicus embryos and larvae, supporting the potential role of serotonin in the modulation of ciliary beating and metamorphosis. Similarly, the nervous system of echinoderm larvae, like those of the starfish Asterina pectinifera and the sea urchin S. purpuratus, appears to be centered on the ciliary band, whose function may be to sense environmental cues [Serotonergic neurons are the first neurons to differentiate in most echinoderm and hemichordate species and are thought to be primary sensory neurons with short apical dendritic poles and basal axonal projections ,16. In ttal cues ,82,83.A. japonicus. Consistent with the previous study in A. japonicus [A. japonicus and regularly spaced within the ciliary rings in doliolaria and early pentactula larvae, which is consistent with the dipleurula-type larvae of sea urchin, starfish, brittle star and feather star echinoderms, and evolutionarily closely related cephalochordates and hemichordates [Unlike asteroids ,16, earlaponicus , the reaaponicus ,70,84. Ahordates ,69,70,85hordates ,87. Nervhordates ,19. A. japonicus, we found intense serotonergic immunoreactions in the anterior-most region, which is consistent with the observations in metamorphosing larvae of the asteroid, A. kochii, and the pentacrinoid larvae of the crinoid A. mediterranea [A. japonicus [At the initial stage of the adult nervous system, the early pentactula stage in terranea ,85. In taponicus ,89. Thisaponicus . Therefoaponicus ,18. HoweA. japonicus, and note that four neuropeptide precursors  predicted in adults were absent in embryo and larvae [Neuropeptides are present across the bilaterians, suggesting that these ancient molecules play a vital role in the function and evolution of nervous systems ,90. Reced larvae . The difA. japonicus, including NPS/CCAP-type precursor , Cholecystokinin-type precursor 2 (CCKP2), TRHP, Orexin-type precursor 2 (OXP2), Kisspeptin-type precursor (KPP), Calcitonin-type precursor 1 (CTP1), Pigment-dispersing factor-type precursors (PDFP1a and PDFP1b), Glycoprotein hormone alpha-2-type precursor 2 (GPA2P2), NP25, GLRFA-P, GN19P, MS21P. Our qRT-PCR analysis also revealed peak expressions of AjTRHP, AjPPLNP2, AjHolotocinP and AjMS21P at the auricularia larvae stage.  were expressed in the blastula, indicating that neuropeptidergic systems appear from the early stage of embryonic development. Thirteen of them were not identified until the auricularia stage of e stage. . Auricul. rubens . Interes. rubens ,93,94, sCRZP, Cholecystokinin-type precursor 1 (CCKP1), SSP1, SSP2, ANPP, StichopinP and NP11LP were found only in the pentactula stage, which indicates a potential for these NPs in the attachment of larvae. We also observed the expression of AjCTP and AjKPP in the early pentactula stage to be significantly higher than in other stages (p < 0.05)  A,C. Prev. rubens . TherefoAjGnRHP and AjBAP showed statistically significant differences in transcript levels at the embryo stage, suggesting their potential roles in embryo development. Previous studies also indicated that GnRH improves blastula formation and the quality of embryos, further supporting our suggestion that GnRH is involved in embryo development [SSP1/2 and PDFP1a/1b were identified at the same developmental stages, which suggests the potential complex regulatory patterns of these neuropeptide families.elopment ,100. It A. japonicus, reported the NPs at early stages, and detected the quantitative expression of ten specific NPs in echinoderm embryos and larvae. By describing the complex nervous system in A. japonicus larvae, we provide new insights into the neurophysiology of echinoderm embryos and larvae. Our present study also revealed the potential roles of neuropeptides in regulating physiological activities including embryo development, feeding and attachment. Future classification of nerve cells and functional studies of neuropeptides will continue to be carried out in larvae and adult deuterostome including our echinoderm species A. japonicus, which will broaden our view about the diverse physiological functions of neuropeptides in these animals and contribute to our understanding of the evolution of neuropeptidergic systems.In conclusion, this study reveals the remarkable complexity of the embryonic and larval nervous system of


Gastric cancer (GC) is one of the most common tumour diseases worldwide and has poor survival, especially in the Asian population. Exploration based on biomarkers would be efficient for better diagnosis, prediction, and targeted therapy.Expression profiles were downloaded from the Gene Expression Omnibus (GEO) database. Survival-related genes were identified by gene set enrichment analysis (GSEA) and univariate Cox. Then, we applied a Bayesian hierarchical lasso Cox model for prognostic signature screening. Protein-protein interaction and Spearman analysis were performed. Kaplan–Meier and receiver operating characteristic (ROC) curve analysis were applied to evaluate the prediction performance. Multivariate Cox regression was used to identify prognostic factors, and a prognostic nomogram was constructed for clinical application.TNFRSF11A, NMNAT1, EIF5A, NOTCH3, TOR2A, E2F8, PSMA5, TPMT, and KIF11 was established to predict overall survival in GC. Protein-protein interaction analysis indicated that E2F8 was likely related to KIF11. Kaplan-Meier analysis showed a significant difference between the high-risk and low-risk groups (P<0.001). Multivariate analysis demonstrated that the 9-gene signature was an independent predictor , and the C-index of the integrative model reached 0.75. Function enrichment analysis for different risk groups revealed the most significant enrichment pathway/term, including pyrimidine metabolism and respiratory electron transport chain.With the Bayesian lasso Cox model, a 9-gene signature included Our findings suggested that a novel prognostic model based on a 9-gene signature was developed to predict GC patients in high-risk and improve prediction performance. We hope our model could provide a reference for risk classification and clinical decision-making. Gastric cancer (GC) has become a pervasive cancer worldwide and was responsible for over 1 million new cases and approximately 0.78 million deaths in 2018, making it the third leading cause of cancer death . Therefoet al. proposed a novel Bayesian hierarchical Cox proportional hazards model  for adapting high-dimensional molecular data . The low-risk group was defined as . The Kaplan-Meier survival analysis demonstrated a statistically significant difference between the low-risk and high-risk groups  between the low-risk and high-risk groups. As shown in the chart, we intuitively discovered that DRGs were enriched mainly in particular molecular terms/pathways, such as pyrimidine metabolism and respiratory electron transport chain .Next, we integrated the gene signature plus several clinical factors, including age, sex and stage, into a super prognostic model to completely predict the OS of GC patients. After integration, the C-index of the final prognostic model reached 0.75, in contrast to the model that considered only clinical factors (C-index = 0.686) . The HR P = 0.0001, P<0.001)  .i.e., giving relatively small shrinkage to those predictors with large effect and giving strong shrinkage to irrelevant or weak predictors at the same time). Therefore, to some extent, this Bayesian model could reduce the estimation bias of lasso Cox. Our study also demonstrated that the cross-validated C-index of the Bayesian model was better than the traditional lasso (0.684 vs 0.643).As one of the most common tumour diseases, GC has a relatively high incidence and mortality rate, especially in Asia . ReliablAfter choosing the optimal model, 9 prognostic genes with non-zero coefficients were selected. Next, we established the risk score index based on these genes, and Kaplan-Meier analysis demonstrated that GC patients in the high-risk group (> = -0.077) had a shorter survival time than those in the low-risk group (<-0.077). Additionally, we tested the predictive power of the 9-gene signature alone, and the results showed that it was a great predictor for OS . Compared to a 4-gene signature reported by a previous study, our signature acquired a higher level  . FurtherNOTCH3, a member of the NOTCH family, is involved in the NOTCH signalling pathway, which is regarded as one of the key pathways constituting the stem cell signalling network [NOTCH3 was associated with poor OS among GC patients, which was consistent with previous studies [TNFRSF11A, also regarded as the receptor activator of NF-κB (RANK), can activate several pathways, such as NF-κB, JNK, ERK, p38, and Akt/PKB, and was reported to be a novel and frequent target for de novo methylation in gliomas [TNFRSF11A was positively associated with survival (HR = 0.7964<1), which was consistent with another study [TPMT, TOR2A, KIF11, and EIF5A were reported to be associated with prognosis in other tumours, such as childhood acute lymphoblastic leukaemia [Through the Bayesian hierarchical lasso Cox model, the 9 genes we found were also the focus of other basic researches or population studies.  network . Our res studies , 22. TNF gliomas . Our stuer study . In popueukaemia , 26, ovaeukaemia , 28, breeukaemia , and coleukaemia .NMNAT1 is involved in the NAD+ salvage/recycling pathway, which is crucial for maintaining the functions of a wide variety of NAD+-dependent enzymes in the cytoplasm and nucleus [NMNAT1 enhanced rRNA transcription, which might facilitate increased ribosome biogenesis and tumour development [NMNAT1 signature, there have been no relevant studies based on populations. Our study revealed that high expression of NMNAT1 was associated with lower mortality risk and higher OS than low expression. E2F8 is a member of the E2F family of transcription factors that regulates various cellular functions related to the cell cycle and apoptosis [E2F8 is considered to be a kind of transcriptional repressor that is similar to E2F7 in that it can inhibit E2F-driven promoters [E2F2, E2F5, E2F6, and E2F7) was significantly associated with favourable OS in GC [E2F8 was also associated with favourable prognosis. nucleus . Knockdoelopment . Howeverpoptosis . E2F8 isromoters . A previOS in GC . Our resPSMA5 and KIF11, can be treated as potential therapeutic targets for tumours [PSMA5, by activating the key Nrf2/ARE signalling pathway, played a critical role in the mechanism of inducing tumour cell apoptosis caused by combined chemotherapy regimens [KIF11 silencing induced chromosome instability (CIN), which might contribute to cancer development and progression [PSMA5 could strengthen the sensitivity of myeloma to bortezomib [PSMA5 [Notably, some previously reported genes, such as  tumours , 37. Preregimens , 39. KIFgression . Howeverrtezomib . Apigenib [PSMA5 . These sIn general, our study used a Bayesian hierarchical lasso Cox model to screen a prognosis-related gene signature. It was the first to apply this Bayesian approach to construct prognosis-related models in GC. Notably, there might be some restrictions regarding generalizability to populations in other regions because this model we built was based on the Asian population. Moreover, our analysis focused mainly on mRNA expression data, but other molecular types, such as microRNA, CNV, or methylation, might contain important prognostic information in GC. Therefore, in further research, we would consider establishing a more generalized model that combines different molecular data for better prediction based on our Bayesian approach. Finally, although the 9-gene signature was explored by statistical analysis or database validation, we expect to further verify these genes by in vitro/vivo experiments in the future study.Our research confirmed that the Bayesian hierarchical lasso Cox model had great prediction power than the traditional Cox model. Based on this Bayesian approach, we proposed a 9-gene prognostic signature as an independent predictor for the overall survival of GC patients. Finally, combined with clinical characteristics, a comprehensive nomogram was provided for clinical application. Overall, our study offers certain reference significance for clinical prognosis prediction in GC.S1 Table(XLSX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S1 Fig(DOCX)Click here for additional data file.S2 Fig(DOCX)Click here for additional data file.


Exposure to cyanotoxins has been linked to neurodegenerative diseases, including amyotrophic lateral sclerosis, Alzheimer’s, and Parkinson’s disease. While the cyanotoxin β-methylamino-L-alanine (BMAA) has received much attention, cyanobacteria produce many cyanotoxic compounds, several of which have been detected in nature alongside BMAA, including 2,4-diaminobutyric acid  and N-(2-aminoethyl)glycine (AEG). Thus, the question of whether 2,4-DAB and AEG also cause neurotoxic effects in vivo is of great interest, as is the question of whether they interact to enhance toxicity. Here, we evaluate the toxic and neurotoxic effects of these cyanotoxins alone or in combination by measuring zebrafish larval viability and behavior after exposure. 2,4-DAB was the most potent cyanotoxin as it decreased larval viability by approximately 50% at 6 days post fertilization, while BMAA and AEG decreased viability by just 16% and 8%, respectively. Although we only observed minor neurotoxic effects on spontaneous locomotion, BMAA and AEG enhanced acoustic startle sensitivity, and they interacted in an additive manner to exert their effects. 2,4-DAB; however, only modulated startle kinematics, an indication of motor dysfunction. To investigate the mechanisms of 2,4-DAB’s effects, we analyzed the protein profile of larval zebrafish exposed to 500 μM 2,4-DAB at two time points and identified molecular signatures consistent with neurodegeneration, including disruption of metabolic pathways and downregulation of the ALS-associated genes SOD1 and UBQLN4. Together, our data demonstrate that BMAA and its isomers AEG and 2,4-DAB cause neurotoxic effects in vivo, with 2,4-DAB as the most potent of the three in the zebrafish model. Exposure to BMAA , a non-canonical amino acid, has been epidemiologically associated with the onset of sporadic neurodegenerative diseases, including amyotrophic lateral sclerosis (ALS) , ParkinsWhile laboratory studies have largely focused on BMAA in isolation, in the environment, it has been detected along with other cyanotoxins, including the BMAA isomers 2,4 diaminobutyric acid  and aminoethyl glycine (AEG)  Metcalf. Variati2+ signaling, the unfolded protein response, and endoplasmic reticulum stress. Together, our data highlight the importance of studying mixtures and reveal 2,4-DAB to be a more potent neurotoxin than BMAA and AEG in the zebrafish model.A preliminary binary mixture study showed synergistic neurotoxic effects of low concentrations of BMAA (10–100 μM) and methylmercury (3 μM) in primary cortical cell cultures . We have−1 were used for all mixture’s dilutions. All dilutions were prepared in HPLC-grade water.Synthetic BMAA, AEG, and 2,4-DAB standards were obtained from Sigma Aldrich . Water, acetonitrile, methanol, acetic acid, and formic acid were all Optima LC–MS grade solvents purchased from Fisher Scientific . Stock solutions of BMAA, AEG, and 2,4-DAB at 10 mg mLExperiments were designed to address in vivo toxicity after exposure to BMAA, AEG, and 2,4-DAB alone or in combination, in which both variation in experiment replicates and reproducibility were assessed. To detect interactive effects in a three-component mixture, we used simplex axial design . Three cDanio rerio) embryos from multiple crosses of wild-type tupfel longfin (TLF) strain adults were collected and placed into Petri dishes containing E3 medium, and unfertilized eggs were removed as described previously. Embryos from all clutches were mixed and randomly sorted into 24 well plates  containing 1 mL of E3 per well.All animal use and procedures were approved by the North Carolina State University IACUC. Zebrafish (At 6 h post fertilization (hpf), embryos were treated with vehicle, individual cyanotoxins, their binary mixtures, and their three-component mixtures . All treMortality due to treatment toxicity was assessed daily and dead fish were counted and removed. During daily media changes, each fish was also assessed for a set of developmental phenotypes , and any fish exhibiting these phenotypes was removed. Significant differences in viability data were analyzed via Kaplan-Meir survival analysis with Mantel-Cox Log-rank test using Prism 8.Prior to behavior testing, any dead fish or fish exhibiting developmental malformations such as pericardial edema, otic vesicle defects, pigmentation defects, small eyes, small heads, body axis defects such as curved or bent tails, and uninflated swim bladders were removed. Screened 6 dpf larvae were adapted to the testing lighting and temperature conditions for 30 min prior to testing. Behavior testing was done as previously described . BrieflyZebrafish embryos from at least ten different fish pairs per batch were collected and randomized immediately after fertilization and transferred in groups of 10 into 24-well plates in E3 media. At 6 hpf, zebrafish embryos were treated with vehicle or 2,4-DAB at 500 μM in E3. Embryos were incubated at 29 °C on a 14 h:10 h light–dark cycle, and 100% of the media was exchanged for fresh treated solutions daily. Embryos/larvae were exposed to 2,4-DAB until 2 or 4 dpf. Exactly ten screened larvae were pooled for each of 3 biological replicates for each condition and then flash frozen in liquid nitrogen and stored at −80 °C. Any dead fish or fish exhibiting developmental malformations such as pericardial edema, otolith malformations, pigmentation defects, small eyes, small heads, body axis defects such as curved or bent tails, and uninflated swim bladders were removed prior to proteomic analysis.Details of sample preparation, protein extraction, and digestion via filter aided sample preparation (FASP) can be found in Danio rerio Swiss Prot protein database . Comparison of LFQ intensities across the whole set of measurements was investigated using Perseus software (version 1.5.1.6), where calculation of statistical significance was determined using two-way Student’s t-test and FPR .Label-free quantification (LFQ) was performed in Max-Quant (version.1.5.60), which uses the Andromeda algorithm . Both dyp value ≤ 0.05) were submitted to IPA. We used an empirical background protein database to evaluate the significance of pathway enrichment. The database was created by using all the proteins that were detected in our samples  software was used to identify the function, specific processes, and enriched pathways of the differentially expressed proteins using the “Core Analysis” function. Only significantly differentially expressed proteins ( samples .An overview of the experiments in this study is illustrated in P = 0.0531). Larval survival after exposure to either BMAA or 2,4-DAB was significantly reduced by 16% (P = 0.0008) and 50% (P < 0.0001), respectively   for the larval group exposed to the cyanotoxic mixtures containing increasing concentrations of 2,4-DAB . Thus, 2 0.0001) .Yi represents the predicted response, βο is the intercept coefficient, and βi is the coefficient of the linear regression.Thus, we conclude that these three cyanotoxins do not interact to decrease survival in vivo and that 2,4-DAB is more toxic than BMAA and AEG, meaning the viability response tracks linearly with 2,4-DAB alone. The response is modeled by the below linear model in which All zebrafish larvae that survived to 6 dpf had no overt developmental or morphological phenotypes. To determine if exposure to BMAA, AEG, and 2,4-DAB alone or in combination causes neurotoxicity, we first examined spontaneous locomotion across all 10 treatment groups . At 6 dpP < 0.0001)  is displayed in  0.0001) . These dTo assess whether cyanotoxin mixtures cause more subtle defects in motor control, we examined the kinematic performance of SLC responses in the exposed larvae, as these rapid movements require coordinated activation of large sets of motor neurons and muscle. Using FLOTE tracking software, we looked at a set of kinematic parameters including latency, body curvature, angular velocity, and duration , b. We fOur data show that 2,4-DAB not only alters motor function during the startle response but more significantly reduces viability of larval zebrafish by approximately 50% by 4 days of development . To undet-test (P < 0.05). All DEPs in both larval groups along with their significance values and fold change can be found in First, we analyzed the regulation of protein abundance by identifying all differentially expressed proteins (DEPs) in the 2,4-DAB samples by comparing the mean abundance at each time point  to their respective controls using a two-way Student’s t-test to determine the probability that DEPs from the dataset correspond with targets which are known to be activated/inhibited by those molecules based on knowledge in the Ingenuity database , leading to the predicted activation of metabolic diseases such as glucose metabolism disorders . Moreover, five key regulators in the data set  were altered in the direction consistent with increased protein damage . These proteins are known to decrease damage of proteins in neurons   . In agrere >|2|) , glycolyp-value < 0.05 and z-score >|2|) upstream regulators and diseases  in the 2,4-DAB exposed samples  that have been observed experimentally to affect protein expression . Here, wdiseases , D. All  samples . NFE2L1  samples . In addi samples . Several samples . Control samples .p-value = 0.012; Log2 fold-change = −1.41) was significantly downregulated in our samples. We also found that another ALS-associated protein, ubiquilin 4  isomer 2,4-diaminobutyric acid  on zebrafish larvae. For many years, BMAA has been studied for its association with sporadic neurodegenerative disease, with several epidemiological studies revealing clusters of cases linked with environmental exposure to BMAA . HoweverOur data show that 2,4-DAB is a more potent toxin than BMAA and AEG in vivo. The principle finding from our study is that 2,4-DAB caused 50% mortality at 500 μM after just 4 days of exposure, while BMAA and AEG caused very little mortality under the same conditions . The eff−1) in freshwater fish, crustaceans, and other types of seafood as well as in the crop plant alfalfa (Medicago sativa)  . Thus, o sativa) , several sativa) . Based o sativa) . Our spo sativa) .Our analysis of sensorimotor function using an acoustic startle assay with precise kinematic tracking further revealed that BMAA, AEG, and 2,4-DAB all impair startle performance. We have previously shown that BMAA increases the frequency of Mauthner-cell-dependent short-latency C-bends (SLCs) in larval zebrafish , and ourprdm12b, dolk, and kcna1a causing a similar increase in body curvature (kcna1a (dolk have been identified in patients with neuropathological conditions such as seizures (Although 2,4-DAB can also agonize NMDA receptors and depolarize neurons , we did urvature  to that  (kcna1a , and mutseizures  and autiseizures . These sdolk mutants, 2,4-DAB inhibited glycosylation (Our unbiased proteomics analysis following in vivo 2,4-DAB exposure, to the best of our knowledge the first such dataset, further implicates 2,4-DAB in neurotoxic processes. We found that at both 2 dpf and 4 dpf 2,4-DAB strongly impacts metabolic function , and consylation  and 7B. sylation . These psylation . Interessylation . Moreovesylation . We founsylation . Consistsylation . We alsosylation . Furthersylation . Thus, tAltogether, our findings provide new evidence that 2,4-DAB drives toxicity in zebrafish larvae. Although BMAA, AEG, and 2,4-DAB all show signs of both toxicity and neurotoxicity in larval zebrafish, 2,4-DAB alone causes both increased mortality and motor dysfunction. Finally, developmental exposure to 2,4-DAB affects zebrafish protein homeostasis and biological processes related to neurodegeneration. These results highlight the need for further investigation into 2,4-DAB’s role in disease and the specific mechanisms by which it exerts its effects.Supplementary Material