Bioinformatics Technology Research Articles

Molecular Evolutionary Analyses of the Spike Protein Gene and Spike Protein in the SARS-CoV-2 Omicron Subvariants.

To better understand the evolution of the SARS-CoV-2 Omicron subvariants, we performed molecular evolutionary analyses of the spike (S) protein gene/S protein using advanced bioinformatics technologies. First, time-scaled phylogenetic analysis estimated that a common ancestor of the Wuhan, Alpha, Beta, Delta variants, and Omicron variants/subvariants diverged in May 2020. After that, a common ancestor of the Omicron variant generated various Omicron subvariants over one year. Furthermore, a chimeric virus between the BM.1.1.1 and BJ.1 subvariants, known as XBB, diverged in July 2021, leading to the emergence of the prevalent subvariants XBB.1.5 and XBB.1.16. Next, similarity plot (SimPlot) data estimated that the recombination point (breakpoint) corresponded to nucleotide position 1373. As a result, XBB.1.5 subvariants had the 5' nucleotide side from the breakpoint as a strain with a BJ.1 sequence and the 3' nucleotide side as a strain with a BM.1.1.1 sequence. Genome network data showed that Omicron subvariants were genetically linked with the common ancestors of the Wuhan and Delta variants, resulting in many amino acid mutations. Selective pressure analysis estimated that the prevalent subvariants, XBB.1.5 and XBB.1.16, had specific amino acid mutations, such as V445P, G446S, N460K, and F486P, located in the RBD when compared with the BA.4 and BA.5 subvariants. Moreover, some representative immunogenicity-associated amino acid mutations, including L452R, F486V, R493Q, and V490S, were also found in these subvariants. These substitutions were involved in the conformational epitopes, implying that these mutations affect immunogenicity and vaccine evasion. Furthermore, these mutations were identified as positive selection sites. These results suggest that the S gene/S protein Omicron subvariants rapidly evolved, and mutations observed in the conformational epitopes may reduce the effectiveness of the current vaccine, including bivalent vaccines such as mRNA vaccines containing the BA.4/BA.5 subvariants.

Removal of nitrate nitrogen by Pseudomonas JI-2 under strong alkaline conditions: Performance and mechanism

The nitrate nitrogen removal characteristics of Pseudomonas JI-2 under strong alkaline conditions and the composition and functional groups of extracellular polymeric substance were analyzed. Furthermore, nontargeted metabonomics and bioinformatics technology were used to investigate the alkaline tolerance mechanism. JI-2 removed 11.05 mg N/(L·h) of nitrate with the initial pH, carbon to nitrogen ratio and temperature were 11.0, 8 and 25 °C respectively. Even when the pH was maintained at 11.0, JI-2 could still effectively remove nitrate. JI-2 contains a large number of Na+/H+ antiporters, such as Mrp, Mnh (mnhACDEFG) and Pha (phaACDEFG), which can stabilize the intracellular acid–base environment, and SlpA can enable quick adaptation to alkaline conditions. Moreover, JI-2 responds to the strong alkaline environment by secreting more polysaccharides, acidic functional groups and compatible solutes and regulating key metabolic processes such as pantothenate and CoA biosynthesis and carbapenem biosynthesis. Therefore, JI-2 can survive in strong alkaline environments and remove nitrate efficiently.

Integrative Molecular Approaches to Plant Disease: A Review

Modern molecular and bioinformatics technologies have made understanding host-pathogen interactions easier. Plants have many ways to protect themselves from microbial diseases, such as physical barriers, PAMP detection, and R genes that recognize pathogen-effector proteins and turn on effector-triggered immunity. Plant pathogen genome databases provide genomic and phenotypic data on plant pathogen species and information on plant-pathogen interactions. Map-based or positional gene cloning is improving our understanding of plant-pathogen interactions, with R genes being used to develop resistance to pathogens. Plant genomes typically contain several hundred nucleotide-binding site-leucine-rich repeats (NLRs), with their number, arrangement, and domain combinations varying by species. Bacterial blight (BB) severely impacts rice production, and about 37 of 44 resistance genes have been mapped and 15 cloned. Many disease-resistant wheat cultivars have been developed using powdery mildew leaf rust (Lr) resistance genes from wild relatives of T. aestivum. Over 140 genes are linked to powdery mildew resistance in T. aestivum and MutChromSeq have found new target genes. Cloning Arabidopsis resistance genes is essential for developing resistant cultivars and understanding R gene evolution. Some R genes encode proteins with nucleotide-binding site (NBS) motifs, and an LRR protects against Erysiphe cruciferarum powdery mildew. CRISPR/Cas9 gene editing is a major tool in plant genome editing, efficiently introducing target site mutations and improving plant immunity. High-throughput sequencing can identify and clone candidate resistance genes in different plant species, and gene editing technologies like CRISPR/Cas have illuminated site-specific mutagenesis and durable resistance.

Medication rule and mechanism of traditional Chinese medicine in treating metabolism-associated fatty liver disease based on bioinformatics technology

Medication rule and mechanism of traditional Chinese medicine in treating metabolism-associated fatty liver disease based on bioinformatics technology

Bioinformatics led discovery of biomarkers related to immune infiltration in diabetes nephropathy.

The leading cause of end-stage renal disease is diabetic nephropathy (DN). A key factor in DN is immune cell infiltration (ICI). It has been shown that immune-related genes play a significant role in inflammation and immune cell recruitment. However, neither the underlying mechanisms nor immune-related biomarkers have been identified in DNs. Using bioinformatics, this study investigated biomarkers associated with immunity in DN. Using bioinformatic methods, this study aimed to identify biomarkers and immune infiltration associated with DN. Gene expression profiles (GSE30528, GSE47183, and GSE104948) were selected from the Gene Expression Omnibus database. First, we identified 23 differentially expressed immune-related genes and 7 signature genes, LYZ, CCL5, ALB, IGF1, CXCL2, NR4A2, and RBP4. Subsequently, protein-protein interaction networks were created, and functional enrichment analysis and genome enrichment analysis were performed using the gene ontology and Kyoto Encyclopedia of Genes and Genome databases. In the R software, the ConsensusClusterPlus package identified 2 different immune modes (cluster A and cluster B) following the consistent clustering method. The infiltration of immune cells between the 2 clusters was analyzed by applying the CIBERSORT method. And preliminarily verified the characteristic genes through in vitro experiments. In this study, the samples of diabetes nephropathy were classified based on immune related genes, and the Hub genes LYZ, CCL5, ALB, IGF1, CXCL2, NR4A2 and RBP4 related to immune infiltration of diabetes nephropathy were obtained through the analysis of gene expression differences between different subtypes. This study was based on bioinformatics technology to analyze the biomarkers of immune related genes in diabetes nephropathy. To analyze the pathogenesis of diabetes nephropathy at the RNA level, and ultimately provide guidance for disease diagnosis, treatment, and prognosis.

A genome-wide analysis of the GRAS gene family in upland cotton and a functional study of the role of the GhGRAS55 gene in regulating early maturity in cotton.

The members of the GRAS gene family play important roles in regulating plant growth and development, but their functions in regulating early plant maturity traits are still unknown. In this study, we used a series of bioinformatics tools to identify GRAS gene family members and investigate the function of the gene family (GhGRAS55) using a genome-wide database of upland cotton samples. A total of 58 members of the GRAS gene family were identified and screened, which were distributed on 21 chromosomes within the whole cotton genome. The results of the phylogenetic analysis showed that the genes of upland cotton, island cotton, African cotton, Raymond cotton, and Arabidopsis were distributed in subfamilies I-VIII, although subfamily II did not contain any upland cotton or Arabidopsis GRAS family members. The structures and other characteristics of the genes in this family were clarified using bioinformatics technology. The transcriptomic sequencing results for early and late maturing cotton species showed that the expression of most GRAS family genes, such as GhGRAS10, GhGRAS5511, and GhGRAS55, was lower in early maturing species than late maturing species. We also found that cotton plants with GhGRAS55 genes that were silenced by virus-induced gene silencing (VIGS) technology showed early bud emergence phenotypes, so it could be speculated that the GhGRAS55 gene has the function of regulating early maturity in cotton.

Pathogen Profiles in Outpatients with Non-COVID-19 during the 7th Prevalent Period of COVID-19 in Gunma, Japan.

The identification of pathogens associated with respiratory symptoms other than the novel coronavirus disease 2019 (COVID-19) can be challenging. However, the diagnosis of pathogens is crucial for assessing the clinical outcome of patients. We comprehensively profiled pathogens causing non-COVID-19 respiratory symptoms during the 7th prevalent period in Gunma, Japan, using deep sequencing combined with a next-generation sequencer (NGS) and advanced bioinformatics technologies. The study included nasopharyngeal swabs from 40 patients who tested negative for severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) using immuno-chromatography and/or quantitative reverse transcription polymerase chain reaction (qRT-PCR) methods. Comprehensive pathogen sequencing was conducted through deep sequencing using NGS. Additionally, short reads obtained from NGS were analyzed for comprehensive pathogen estimation using MePIC (Metagenomic Pathogen Identification Pipeline for Clinical Specimens) and/or VirusTap. The results revealed the presence of various pathogens, including respiratory viruses and bacteria, in the present subjects. Notably, human adenovirus (HAdV) was the most frequently detected virus in 16 of the 40 cases (40.0%), followed by coryneforms, which were the most frequently detected bacteria in 21 of the 40 cases (52.5%). Seasonal human coronaviruses (NL63 type, 229E type, HKU1 type, and OC43 type), human bocaviruses, and human herpesviruses (human herpesvirus types 1-7) were not detected. Moreover, multiple pathogens were detected in 50% of the subjects. These results suggest that various respiratory pathogens may be associated with non-COVID-19 patients during the 7th prevalent period in Gunma Prefecture, Japan. Consequently, for an accurate diagnosis of pathogens causing respiratory infections, detailed pathogen analyses may be necessary. Furthermore, it is possible that various pathogens, excluding SARS-CoV-2, may be linked to fever and/or respiratory infections even during the COVID-19 pandemic.

First Report of Cotton Leafroll Dwarf Virus infection of Malvaviscus arboreus in China.

Cotton leafroll dwarf virus (CLRDV, genus Polerovirus, family Solemoviridae) has been reported to infect cotton in Brazil, Argentina, India, Thailand and Timor-Leste (Agrofoglio YC et al. 2017; Corrêa RL et al. 2005; Mukherjee et al. 2012; Ray et al. 2016; Sharman et al. 2015), and in the United States (Ali and Mokhtari et al. 2020; Avelar et al. 2019). It has also been recently reported to infect Cicer arietinum (chickpea) in Uzbekistan and Hibiscus syriacus in Korea (Igori et al. 2022; Kumari et al. 2020). In China, the natural infection of plants by CLRDV has not been reported previously. In August 2017, leaf samples were collected from a wild plant of Malvaviscus arboreus (Malvaceae) exhibiting symptoms including leaf yellowing and distorting in Tengchong County of Yunnan Province. Leaves were used for total RNA extraction using TRIzol Reagent (Invitrogen, USA). Small RNA library construction and deep sequencing was performed on illumina HiSeqTM 2000 platform by Novogene Bioinformatic Technology Co., Ltd (Beijing, China). A total of 11, 525, 708 raw reads were obtained and further computationally analyzed by Perl scripts. The adaptors were removed and the obtained 7, 520, 902 clean reads with size of 18- to 26-nucleotide (nt) were aligned with the GenBank virus RefSeq database using Bowtie software. These reads were mainly mapped to the genomes of hibiscus bacilliform virus (genusBadnavirus,familyCaulimoviridae), hibiscus chlorotic ringspot virus (genus Betacarmovirus, family Procedovirinae), hibiscus latent Singapore virus (genus Tobamovirus, family Virgaviridae) and CLRDV isolate ARG (accession no. GU167940). The average coverage depth of clean reads mapped to CLRDV genome was 97.76%. Contigs greater than 50 nt were used to search for similar sequences by BLASTx, and 107 contigs were annotated as homologous to CLRDV isolates. To confirm CLRDV infection, reverse transcription polymerase chain reaction (RT-PCR) was performed using the specific primer pair CLRDV-F (5'-TCCACAGGAAGTATCACGTTCG-3') and CLRDV-R (5'-CCTTGTGTGGTTTGATTCGTGA-3') designed based on two of these contigs well-aligned to the genome of CLRDV isolate ARG. An amplicon of 1095-bp size was amplified, and was sequenced by Sanger sequencing (TsingKe Biological Technology, Chengdu, China), and BLASTn search results showed a maximum nucleotide identity of 95.45% with CLRDV isolate CN-S5, an isolate obtained from soybean aphid host in China (accession no. KX588248). To obtain more information on this CLRDV isolate, four primer pairs were designed and used for RT-PCR amplification (TableS1). The amplicons with size of about 860-, 1400-, 3200- and 1100-bp, were obtained separately and assembled into a complete genome sequence up to 5, 865-nt in length (isolate YN, deposited under GenBank accession no. MN057665). BLASTn showed the highest nucleotide similarity of 94.61% with CLRDV isolate CN-S5. From 2018 to 2022, additional M. arboreus samples with leaf yellowing or curling symptoms (9 from Shapingba District in Chongqing City, 5 from Nanchong City in Sichuan Province, 9 from Kunming City and 12 from Tengchong County in Yunnan Province) were collected and tested for CLRDV by RT-PCR using primer pairs CLRDV-F/CLRDV-R. The nucleotide sequences of the CLRDV P0 gene in two samples from Tengchong County were obtained by Sanger sequencing and deposited under GenBank (CLRDV isolate TCSL1 P0 gene, accession no. OQ749809; CLRDV isolate TCSW2 P0 gene, accession no. OQ749809). To our knowledge, this is the first report of CLRDV naturally infecting Malvaviscus arboreus in China, thus extending the information on its geographical distribution and host range. Malvaviscus arboreus is a widely cultivated ornamental plant in Yunnan Province, China. The natural occurrence of CLRDV not only affects the ornamental value of Malvaviscus arboreus, but also poses a potential threat to cotton production in China. This study will assist further surveillance of CLRDV infection and future development of effective protection strategies against CLRDV in China.

GDNF triggers proliferation of rat C6 glioma cells via the NF-κB/CXCL1 signaling pathway.

Glioblastoma multiforme (GBM) is the most common primary malignant brain tumor that is characterized by its high proliferative and migratory potential, leading to a high invasiveness of this tumor type. However, the underlying mechanism of GBM proliferation and migration has not been fully elucidated. In this study, at first, we used RNA-seq together with bioinformatics technology to screen for C-X-C motif ligand 1 (CXCL1) as a proliferation-related gene. And exogenous glial cell line-derived neurotrophic factor (GDNF) induced proliferation and up-regulated the level of CXCL1 in rat C6 glioma cells determined by sqPCR and ELISA. Then, we manipulated the CXCL1 expression by using a lentiviral vector (CXCL1-RNAi) approach. By this, the proliferation of C6 cells was decreased, suggesting that CXCL1 plays a key role in proliferation in these cells. We hypothesized that exogenous GDNF promoted NF-κB nuclear translocation and therefore, analyzed the interaction of CXCL1 with NF-κB by Western Blot and immunofluorescence. Additionally, we used BAY 11-7082, a phosphorylation inhibitor of NF-κB, to elucidate NF-κB mediated the effect of GDNF on CXCL1. These results demonstrated that GDNF enhanced the proliferation of rat C6 glioma cells through activating the NF-κB/CXCL1 signaling pathway. In summary, these studies not only revealed the mechanism of action of exogenous GDNF in promoting the proliferation of C6 glioma cells but may also provide a new biological target for the treatment of malignant glioma.

Bioinformatics-based analysis of core genes and pathway enrichment in early diabetic nephropathy.

Diabetic nephropathy (DN) is the main cause of end-stage renal disease (ESRD). Bioinformatics technology was adopted to screen and analyze the core genes of early DN to explore its pathogenesis. GSE30528, GSE96804, and GSE30122 chip data were obtained from Gene Expression Omnibus (GEO) database to screen DN and healthy controls for differentially expressed genes. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) for functional annotation and signaling pathway enrichment; String and Cytoscape were used for protein-protein interaction (PPI) network construction and core gene screening, NCBI-Genes to search the expression profile of core genes. 17 common genes were screened, with 6 genes up-regulated and 11 genes down-regulated. The major functional annotations of differential genes were the generation of precursor metabolites and energy, Immune response, and Phosphorylation. They were concentrated on Focal adhesion, PI3K/Akt signaling pathway, and Human papillomavirus infection pathway. The expressions of VEGFA and THBS1 were down-regulated, while the expressions of ITGB1, MMP7, and SOX9 were up-regulated. The core genes VEGFA and THBS1 were highly expressed in Thyroid and Appendix, but lowly expressed in Testis. MMP7 was highly expressed in the Gall bladder and low in the Adrenal. SOX9 was highly expressed in Thyroid and lowly expressed in the bone marrow. ITGB1 was highly expressed in Fat and low in Pancreas. Bioinformatics technology can mine chip data and present new targets for diagnosing and treating DN, but further verification is needed.

Testosterone promotes the migration, invasion and EMT process of papillary thyroid carcinoma by up-regulating Tnnt1

PurposeTo explore the key genes and molecular pathways in the progression of thyroid papillary carcinoma (PTC) promoted by testosterone using RNA-sequencing technology, and to provide new drug targets for improving the therapeutic effect of PTC.MethodsOrchiectomy (ORX) was carried out to construct ORX mouse models. TPC-1 cells were subcutaneously injected for PTC formation in mice, and the tumor tissues were collected for RNA-seq. The key genes were screened by bioinformatics technology. Tnnt1 expression in PTC cells was knocked down or overexpressed by transfection. Cell counting kit-8 (CCK-8), colony formation assay, scratch assay and transwell assay were adopted, respectively, for the detection of cell proliferation, colony formation, migration and invasion. Besides, quantification real-time polymerase chain reaction (qRT-PCR) and western blot were utilized to determine the mRNA and protein expression levels of genes in tissues or cells.ResultsBoth estradiol and testosterone promoted the growth of PTC xenografts. The key gene Tnnt1 was screened and obtained by bioinformatics technology. Functional analysis revealed that overexpression of Tnnt1 could markedly promote the proliferation, colony formation, migration, invasion, and epithelial-to-mesenchymal transition (EMT) process of PTC cells, as well as could activate p38/JNK pathway. In addition, si-Tnt1 was able to inhibit the cancer-promoting effect of testosterone.ConclusionBased on the outcomes of bioinformatics and basic experiments, it is found that testosterone can promote malignant behaviors such as growth, migration, invasion and EMT process of PTC by up-regulating Tnnt1 expression. In addition, the function of testosterone may be achieved by activating p38/JNK signaling pathway.

Identification of predictive markers in the cerebrospinal fluid of patients with glioblastoma

Introduction. Glioblastoma (GB) is not yet curable despite recent advances in the treatment of other malignant solid tumors. The management of GB is based solely on histopathological features, imaging of the tumor and its genomic analysis (somatic mutations in the isocitrate dehydrogenase genes, methylation status of the O6-methylguanine-DNA methyltransferase gene promoter). To adapt the treatment to the most recent tumor evolution, molecular information should be received regularly throughout the course of therapy. However, tumor tissue is often not available for diagnosis as the disease progresses. In this regard, the development of less invasive methods, such as analysis of the proteome of biological fluids of patients, is of particular interest. Cerebrospinal fluid (CSF) is an important source disease biomarkers to monitor the presence and progression of the disease.Aim. To identify proteomic predictive biomarkers in the CSF of patients with GB.Materials and methods. During the study, samples of patients’ CSF samples, high-resolution proteomic mass spectrometry, modern biochemical methods and bioinformatic technologies were used.Results. For the first time, the analysis of proteomes of CSF samples of patients with GB obtained before and 7 days after the removal of the primary tumor was carried out. Potential biomarkers of GB have been identified. After their validation using open databases, 11 proteomic predictive markers of GB (S100A9, S100A8, PLA2G15, PPIB, LTBP2, VIM, LAMB1, STC1, NRP1, COL6A1, HSPA5) were selected and their role in the molecular mechanisms of gliomagenesis was assessed. Conclusion. The proposed panel of proteomic predictive CSF biomarkers in GB patients can be further used in the development of test systems for assessing the effectiveness of therapy and early detection of disease relapses.

Shared Genes and Molecular Mechanisms between Nonalcoholic Fatty Liver Disease and Hepatocellular Carcinoma Established by WGCNA Analysis.

Background Hepatocellular carcinoma (HCC) is one of the leading causes of death from cancer worldwide. The histopathological features, risk factors, and prognosis of HCC caused by nonalcoholic fatty liver disease (NAFLD) appear to be significantly different from those of HCC caused by other etiologies of liver disease. Objective This article explores the shared gene and molecular mechanism between NAFLD and HCC through bioinformatics technologies such as weighted gene co-expression network analysis (WGCNA), so as to provide a reference for comprehensive understanding and treatment of HCC caused by NAFLD. Methods NAFLD complementary deoxyribonucleic acid microarrays (GSE185051) from the Gene Expression Omnibus database and HCC ribonucleic acid (RNA)-sequencing data (RNA-seq data) from The Cancer Genome Atlas database were used to analyze the differentially expressed genes (DEGs) between NAFLD and HCC. Then, the clinical traits and DEGs in the two disease data sets were analyzed by WGCNA to obtain W-DEGs, and cross-W-DEGs were obtained by their intersection. We performed subsequent Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genome (KEGG) enrichment analyses of the cross-W-DEGs and established protein-protein interaction networks. Then, we identified the hub genes in them by Cytoscape and screened out the final candidate genes. Finally, we validated candidate genes by gene expression, survival, and immunohistochemical analyses. Results The GO analysis of 79 cross-W-DEGs showed they were related mainly to RNA polymerase II (RNAP II) and its upstream transcription factors. KEGG analysis revealed that they were enriched predominantly in inflammation-related pathways (tumor necrosis factor and interleukin-17). Four candidate genes (JUNB, DUSP1, NR4A1, and FOSB) were finally screened out from the cross-W-DEGs. Conclusion JUNB, DUSP1, NR4A1, and FOSB inhibit NAFLD and HCC development and progression. Thus, they can serve as potential useful biomarkers for predicting and treating NAFLD progression to HCC.

The human gut phageome: composition, development, and alterations in disease.

The human gastrointestinal tract is colonized by a large number of microorganisms, including bacteria, archaea, viruses, and eukaryotes. The bacterial community has been widely confirmed to have a significant impact on human health, while viruses, particularly phages, have received less attention. Phages are viruses that specifically infect bacteria. They are abundant in the biosphere and exist in a symbiotic relationship with their host bacteria. Although the application of high-throughput sequencing and bioinformatics technology has greatly improved our understanding of the genomic diversity, taxonomic composition, and spatio-temporal dynamics of the human gut phageome, there is still a large portion of sequencing data that is uncharacterized. Preliminary studies have predicted that the phages play a crucial role in driving microbial ecology and evolution. Prior to exploring the function of phages, it is necessary to address the obstacles that hinder establishing a comprehensive sequencing database with sufficient biological properties and understanding the impact of phage-bacteria interactions on human health. In this study, we provide an overview of the human gut phageome, including its composition, structure, and development. We also explore the various factors that may influence the phageome based on current research, including age, diet, ethnicity, and geographical location. Additionally, we summarize the relationship between the phageome and human diseases, such as IBD, IBS, obesity, diabetes, and metabolic syndrome.

Molecular Evolutionary Analyses of the RNA-Dependent RNA Polymerase (RdRp) Region and VP1 Gene in Human Norovirus Genotypes GII.P6-GII.6 and GII.P7-GII.6.

To understand the evolution of GII.P6-GII.6 and GII.P7-GII.6 strains, the prevalent human norovirus genotypes, we analysed both the RdRp region and VP1 gene in globally collected strains using authentic bioinformatics technologies. A common ancestor of the P6- and P7-type RdRp region emerged approximately 50 years ago and a common ancestor of the P6- and P7-type VP1 gene emerged approximately 110 years ago. Subsequently, the RdRp region and VP1 gene evolved. Moreover, the evolutionary rates were significantly faster for the P6-type RdRp region and VP1 gene than for the P7-type RdRp region and VP1 genes. Large genetic divergence was observed in the P7-type RdRp region and VP1 gene compared with the P6-type RdRp region and VP1 gene. The phylodynamics of the RdRp region and VP1 gene fluctuated after the year 2000. Positive selection sites in VP1 proteins were located in the antigenicity-related protruding 2 domain, and these sites overlapped with conformational epitopes. These results suggest that the GII.6 VP1 gene and VP1 proteins evolved uniquely due to recombination between the P6- and P7-type RdRp regions in the HuNoV GII.P6-GII.6 and GII.P7-GII.6 virus strains.

Advances in machine learning for predicting protein functions

Proteins play a variety of functional roles in cellular activities and are indispensable for life. Understanding the functions of proteins is crucial in many fields such as medicine and drug development. In addition, the application of enzymes in green synthesis has been of great interest, but the high cost of obtaining specific functional enzymes as well as the variety of enzyme types and functions hamper their application. At present, the specific functions of proteins are mainly determined through tedious and time-consuming experimental characterization. With the rapid development of bioinformatics and sequencing technologies, the number of protein sequences that have been sequenced is much larger than those can be annotated, thus developing efficient methods for predicting protein functions becomes crucial. With the rapid development of computer technology, data-driven machine learning methods have become a promising solution to these challenges. This review provides an overview of protein function and its annotation methods as well as the development history and operation process of machine learning. In combination with the application of machine learning in the field of enzyme function prediction, we present an outlook on the future direction of efficient artificial intelligence-assisted protein function research.

Data Center Efficiency Model: A New Approach and the Role of Artificial Intelligence

Bioinformatics technologies play a significant and growing role in life science research, and as these technologies develop, so does the complexity of data. The challenge of biological data growth has given rise to a number of bioinformatics data centers that offer services and solutions ranging from large-scale biosystems analyze that accounts for entire OMICs to nanoscale experiments where molecular modeling can provide insight o structure and dynamics of molecular complexes of biological components. Obviously, this kind of research requires a highly specialized level of computational and statistical expertise, as well as high-performance resources. The importance of information technology is growing, as is the use of computer information systems throughout the world. There are more and more specialized data centers and they consume more energy. The development of new strategies for energy efficiency of data centers is becoming relevant. These strategies aim to reduce the amount of energy consumed by data centers and their environmental impact without sacrificing performance. The article examines performance metrics, proposes a new method for data center energy efficiency, and discusses the role of artificial intelligence techniques in achieving these goals.

Association analysis of PMEL gene expression and single nucleotide polymorphism with plumage color in quail

To explore the relationship between PMEL gene and quail plumage color, to provide a reference for subsequent quail plumage color breeding. In this experiment, RT-qPCR technology was used to analyze the relative mRNA expression levels of Korean quail (maroon) and Beijing white quail embryos at different developmental stages. Two SNPs in PMEL gene were screened based on the RNA-Seq data of skin tissues of Korean quail and Beijing white quail during embryonic stage. The KASP technology was used for genotyping in the resource population and correlation analysis was carried out with the plumage color traits of quail. Finally, the bioinformatics technology was used to predict the effects of these two SNPs on the structure and function of the encoded protein. The results showed that the expression levels of PMEL gene during the embryonic development of Beijing white quail were extremely significantly higher than that of Korean quail (p < 0.01). The frequency distribution of the three genotypes (AA, AB, and BB) of the Beijing white quail at the c. 1030C > T and c. 1374A > G mutation sites were extremely significantly different from that of the Korean quail (p < 0.01). And there was a significant correlation between the c. 1374A > G mutation site with white plumage phenotype. Bioinformatics analysis showed that SNP1 (c. c1030t) located in exon 6 was a harmful mutation site, and SNP2 (c. a1374g) located in exon 7 was a neutral mutation site. Protein conservation prediction showed that the coding protein P344S site caused by SNP1 (c. c1030t) site and the coding protein I458M site caused by SNP2 (c. g2129a) site were non-conservative sites. The results of this experiment showed that the PMEL gene was associated with the plumage color traits of quail and could be used as a candidate gene for studying the plumage color of quail.

The application of drug loading and drug release characteristics of two-dimensional nanocarriers for targeted treatment of leukemia

The development of bioinformatics technology has enabled nanomedicine to play a significant role in drug delivery systems. Its low toxicity, high efficiency, and controllable drug release advantages make it have good application effects. Moreover, common targeted therapeutic drug formulations have weak stability in malignant tumor leukemia, and their application effects are limited. Therefore, based on the characteristics of black phosphorus two-dimensional nanomedicine, experimental designs were conducted on its nanosheet preparation, polyethylene glycol modification, and anti-tumor drug loading. Experimental analysis was also conducted on the characterization ability, drug release, and targeted therapy of nanomedicine. The results show that polyethylene glycol (PEG) modified black phosphorus crystals (BP) nanoparticles can effectively improve their negative electricity, and have relatively stable photothermal properties. The release of doxorubicin hydrochloride (DOX) loaded nanoparticles was analyzed. It was found that the maximum drug release efficiency of BP-PEG-DOX was higher than that of BP-DOX at pH 5 and 7.5 (12.13% &amp;gt; 7.69%, 29.46% &amp;gt; 28.69%). The maximum drug release rates of BP-PEG-DOX-NIR reached 33.23% and 28.67% at temperatures of 35°C and 45°C, with differences of over 10% compared to the non laser group. Moreover, the nano drug loaded particles modified with PEG and treated with laser have a significant killing effect on cells, with a decrease in cell survival rate of over 15%. The two-dimensional nano drug carrier has high safety and effectiveness in drug delivery, and its targeted treatment effect on acute T lymphoblastic leukemia cells is obvious. Its drug release characteristics perform well in photothermal therapy, indicating that black phosphorus nano drugs can improve the biological safety and applicability of drugs in new tumor targeted therapy.

Biochemical-molecular-genetic biomarkers in the tear film, aqueous humor, and blood of primary open-angle glaucoma patients.

Glaucoma is a chronic neurodegenerative disease, which is the leading cause of irreversible blindness worldwide. As a response to high intraocular pressure, the clinical and molecular glaucoma biomarkers indicate the biological state of the visual system. Classical and uncovering novel biomarkers of glaucoma development and progression, follow-up, and monitoring the response to treatment are key objectives to improve vision outcomes. While the glaucoma imaging field has successfully validated biomarkers of disease progression, there is still a considerable need for developing new biomarkers of early glaucoma, that is, at the preclinical and initial glaucoma stages. Outstanding clinical trials and animal-model study designs, innovative technology, and analytical approaches in bioinformatics are essential tools to successfully uncover novel glaucoma biomarkers with a high potential for translation into clinical practice. To better understand the clinical and biochemical-molecular-genetic glaucoma pathogenesis, we conducted an analytical, observational, and case-comparative/control study in 358 primary open-angle glaucoma (POAG) patients and 226 comparative-control individuals (CG) to collect tears, aqueous humor, and blood samples to be processed for identifying POAG biomarkers by exploring several biological pathways, such as inflammation, neurotransmitter/neurotrophin alteration, oxidative stress, gene expression, miRNAs fingerprint and its biological targets, and vascular endothelial dysfunction, Statistics were done by using the IBM SPSS 25.0 program. Differences were considered statistically significant when p ≤ 0.05. Mean age of the POAG patients was 70.03 ± 9.23 years, and 70.62 ± 7.89 years in the CG. Malondialdehyde (MDA), nitric oxide (NO), interleuquin (IL)-6, endothelin-1 (ET-1), and 5 hydroxyindolacetic acid (5-HIAA), displayed significantly higher levels in the POAG patients vs. the CG (p < 0.001). Total antioxidant capacity (TAC), brain derived neurotrophic factor (BDNF), 5-hydroxy tryptamine (5-HT), solute carrier family 23-nucleobase transporters-member 2 (SLC23A2) gene, and the glutathione peroxidase 4 (GPX4) gene, showed significantly lower levelsin the POAG patients than in the CG (p < 0.001). The miRNAs that differentially expressed in tear samples of the POAG patients respect to the CG were the hsa miR-26b-5p (involved in cell proliferation and apoptosis), hsa miR-152-3p (regulator of cell proliferation, and extracellular matrix expression), hsa miR-30e-5p (regulator of autophagy and apoptosis), and hsa miR-151a-3p (regulator of myoblast proliferation). We are incredibly enthusiastic gathering as much information as possible on POAG biomarkers to learn how the above information can be used to better steer the diagnosis and therapy of glaucoma to prevent blindness in the predictable future. In fact, we may suggest that the design and development of blended biomarkers is a more appropriate solution in ophthalmological practice for early diagnosis and to predict therapeutic response in the POAG patients.