SMDB: a Spatial Multimodal Data Browser.

Understanding the relationship between fine-scale spatial organization and biological function necessitates a tool that effectively combines spatial positions, morphological information, and spatial transcriptomics (ST) data. We introduce the Spatial Multimodal Data Browser (SMDB, https://www.biosino.org/smdb), a robust visualization web service for interactively exploring ST data. By integrating multimodal data, such as hematoxylin and eosin (H&E) images, gene expression-based molecular clusters, and more, SMDB facilitates the analysis of tissue composition through the dissociation of two-dimensional (2D) sections and the identification of gene expression-profiled boundaries. In a digital three-dimensional (3D) space, SMDB allows researchers to reconstruct morphology visualizations based on manually filtered spots or expand anatomical structures using high-resolution molecular subtypes. To enhance user experience, it offers customizable workspaces for interactive exploration of ST spots in tissues, providing features like smooth zooming, panning, 360-degree rotation in 3D and adjustable spot scaling. SMDB is particularly valuable in neuroscience and spatial histology studies, as it incorporates Allen's mouse brain anatomy atlas for reference in morphological research. This powerful tool provides a comprehensive and efficient solution for examining the intricate relationships between spatial morphology, and biological function in various tissues.

A Noncoding A-to-U Kozak Site Change Related to the High Transmissibility of Alpha, Delta, and Omicron VOCs.

Three prevalent SARS-CoV-2 variants of concern (VOCs) emerged and caused epidemic waves. It is essential to uncover advantageous mutations that cause the high transmissibility of VOCs. However, viral mutations are tightly linked, so traditional population genetic methods, including machine learning-based methods, cannot reliably detect mutations conferring a fitness advantage. In this study, we developed an approach based on the sequential occurrence order of mutations and the accelerated furcation rate in the pandemic-scale phylogenomic tree. We analyzed 3,777,753 high-quality SARS-CoV-2 genomic sequences and the epidemiology metadata using the Coronavirus GenBrowser. We found that two noncoding mutations at the same position (g.a28271-/u) may be crucial to the high transmissibility of Alpha, Delta, and Omicron VOCs although the noncoding mutations alone cannot increase viral transmissibility. Both mutations cause an A-to-U change at the core position -3 of the Kozak sequence of the N gene and significantly reduce the protein expression ratio of ORF9b to N. Using a convergent evolutionary analysis, we found that g.a28271-/u, S:p.P681H/R, and N:p.R203K/M occur independently on three VOC lineages, suggesting that coordinated changes of S, N, and ORF9b proteins are crucial to high viral transmissibility. Our results provide new insights into high viral transmissibility co-modulated by advantageous noncoding and nonsynonymous changes.

TransCirc: an interactive database for translatable circular RNAs based on multi-omics evidence.

TransCirc (https://www.biosino.org/transcirc/) is a specialized database that provide comprehensive evidences supporting the translation potential of circular RNAs (circRNAs). This database was generated by integrating various direct and indirect evidences to predict coding potential of each human circRNA and the putative translation products. Seven types of evidences for circRNA translation were included: (i) ribosome/polysome binding evidences supporting the occupancy of ribosomes onto circRNAs; (ii) experimentally mapped translation initiation sites on circRNAs; (iii) internal ribosome entry site on circRNAs; (iv) published N-6-methyladenosine modification data in circRNA that promote translation initiation; (v) lengths of the circRNA specific open reading frames; (vi) sequence composition scores from a machine learning prediction of all potential open reading frames; (vii) mass spectrometry data that directly support the circRNA encoded peptides across back-splice junctions. TransCirc provides a user-friendly searching/browsing interface and independent lines of evidences to predicte how likely a circRNA can be translated. In addition, several flexible tools have been developed to aid retrieval and analysis of the data. TransCirc can serve as an important resource for investigating the translation capacity of circRNAs and the potential circRNA-encoded peptides, and can be expanded to include new evidences or additional species in the future.

Integrated Metabolome and Transcriptome Analysis Provides New Insights into the Glossy Graft Cucumber Fruit (Cucumis sativus L.).

Cucumber is an important vegetable crop, and grafts often affect the quality and wax loss in cucumber fruit and affect its value. However, their metabolites and molecular mechanisms of action remain unclear. Metabolome and transcriptome analyses were conducted on the fruit peels of self-rooted plants (SR) grafted with white seed pumpkin (WG). The results showed that there were 352 differential metabolites in the fruit peels of the SR and WG. The transcriptome analysis showed 1371 differentially expressed genes (DEGs) between the WG and SR. These differentially expressed genes were significantly enriched in plant hormone signal transduction, cutin, suberin, wax biosynthesis, phenylpropanoid biosynthesis, and zeatin biosynthesis. By analyzing the correlation between differential metabolites and differentially expressed genes, six candidate genes related to the synthesis of glycitein, kaempferol, and homoeriodictyol were identified as being potentially important. Key transcription factors belonging to the TCP and WRKY families may be the main drivers of transcriptional changes in the peel between the SR and WG. The results of this study have provided a basis for the biosynthesis and regulation of wax loss and quality in grafted cucumbers and represents an important step toward identifying the molecular mechanisms of grafting onto cucumber fruit.

Integrated Physiological and Transcriptomic Analyses Revealed Improved Cold Tolerance in Cucumber (Cucumis sativus L.) by Exogenous Chitosan Oligosaccharide.

Cucumber (Cucumis sativus L.), sensitive to cold stress, is one of the most economically important vegetables. Here, we systematically investigated the roles of exogenous glycine betaine, chitosan, and chitosan oligosaccharide in alleviating cold stress in cucumber seedlings. The results showed that 50 mg·L-1 chitosan oligosaccharide had the best activity. It effectively increases plant growth, chlorophyll content, photosynthetic capacity, osmotic regulatory substance content, and antioxidant enzyme activities while reducing relative electrical conductivity and malondialdehyde levels in cucumber seedlings under cold stress. To reveal the protective effects of chitosan oligosaccharide in cold stress, cucumber seedlings pretreated with 50 mg·L-1 chitosan oligosaccharide were sampled after 0, 3, 12, and 24 h of cold stress for transcriptome analysis, with distilled water as a control. The numbers of differentially expressed genes in the four comparison groups were 656, 1274, 1122, and 957, respectively. GO functional annotation suggested that these genes were mainly involved in "voltage-gated calcium channel activity", "carbohydrate metabolic process", "jasmonic acid biosynthetic", and "auxin response" biological processes. KEGG enrichment analysis indicated that these genes performed important functions in "phenylpropanoid biosynthesis", "MAPK signaling pathway-plant", "phenylalanine metabolism", and "plant hormone signal transduction." These findings provide a theoretical basis for the use of COS to alleviate the damage caused by cold stress in plant growth and development.

PGG.Han: the Han Chinese genome database and analysis platform.

As the largest ethnic group in the world, the Han Chinese population is nonetheless underrepresented in global efforts to catalogue the genomic variability of natural populations. Here, we developed the PGG.Han, a population genome database to serve as the central repository for the genomic data of the Han Chinese Genome Initiative (Phase I). In its current version, the PGG.Han archives whole-genome sequences or high-density genome-wide single-nucleotide variants (SNVs) of 114 783 Han Chinese individuals (a.k.a. the Han100K), representing geographical sub-populations covering 33 of the 34 administrative divisions of China, as well as Singapore. The PGG.Han provides: (i) an interactive interface for visualization of the fine-scale genetic structure of the Han Chinese population; (ii) genome-wide allele frequencies of hierarchical sub-populations; (iii) ancestry inference for individual samples and controlling population stratification based on nested ancestry informative markers (AIMs) panels; (iv) population-structure-aware shared control data for genotype-phenotype association studies (e.g. GWASs) and (v) a Han-Chinese-specific reference panel for genotype imputation. Computational tools are implemented into the PGG.Han, and an online user-friendly interface is provided for data analysis and results visualization. The PGG.Han database is freely accessible via http://www.pgghan.org or https://www.hanchinesegenomes.org.

Probiotics and fructo-oligosaccharide intervention modulate the microbiota-gut brain axis to improve autism spectrum reducing also the hyper-serotonergic state and the dopamine metabolism disorder.

The prevalence of autism spectrum disorders (ASD) is increasing, but its etiology remains elusive and hence an effective treatment is not available. Previous research conducted on animal models suggests that microbiota-gut-brain axis may contribute to ASD pathology and more human research is needed. This study was divided into two stages,.At the discovery stage, we compared the differences in gut microbiota profiles (using 16S rRNA sequencing), fecal SCFAs (using GC-MS) and plasma neurotransmitters (using UHPLC-MS/MS) of 26 children with ASD and 24 normal children. All 26 children with ASD participated in the intervention stage, and we measured the gut microbiota profiles, SCFAs and neurotransmitters before and after probiotics + FOS (n = 16) or placebo supplementation (n = 10). We found that gut microbiota was in a state of dysbiosis and significantly lower levels of Bifidobacteriales and Bifidobacterium longum were observed at the discovery stage in children with ASD. An increase in beneficial bacteria (Bifidobacteriales and B. longum) and suppression of suspected pathogenic bacteria (Clostridium) emerged after probiotics + FOS intervention, with significant reduction in the severity of autism and gastrointestinal symptoms. Compared to children in the control group, significantly lower levels of acetic acid, propionic acid and butyric acid were found, and a hyperserotonergic state (increased serotonin) and dopamine metabolism disorder (decreased homovanillic acid) were observed in children with ASD. Interestingly, the above SCFAs in children with autism significantly elevated after probiotics + FOS intervention and approached those in the control group. In addition, our data demonstrated that decreased serotonin and increased homovanillic acid emerged after probiotics + FOS intervention. However, the above-mentioned changes did not appear in the placebo group for ASD children. Probiotics + FOS intervention can modulate gut microbiota, SCFAs and serotonin in association with improved ASD symptoms, including a hyper-serotonergic state and dopamine metabolism disorder.

Formation of homochiral helical nanostructures in diblock copolymers under the confinement of nanopores.

The control of the homochirality of helical structures formed in achiral systems is of great interest as it is helpful for understanding the origin of homochirality in life. In this work, we introduce a spiral arrangement of patches into the inner surface of a nanopore to guide the self-assembly of a cylinder-forming AB diblock copolymer melt into a homochiral single helix. We calculate the free energy of the single-helical structures with different handedness using self-consistent field theory (SCFT). Moreover, we simulate the self-assembly process using an iterative process of SCFT solution starting from a disordered state, and count the formation probability of different helical structures. We find that the formation probability of the homochiral helix with favorable free energy increases rapidly, leading to the conclusion that a minuscule difference of 0.5-1.0 × 10-4kBT per chain is enough to obtain the homochiral helix by suppressing its counterpart of a higher free energy. However, for a stronger chiral guiding field, other homochiral helical structures with unfavorable handedness and thus increasingly higher free energy become more likely to be formed. Morphological snapshots during the self-assembly process reveal that the formation of these metastable helical structures is induced by their kinetic pathways, which are altered to be favorable by the strong chiral field of the patch pattern. Therefore, our work suggests that both thermodynamics and kinetics are important for controlling the chirality of helical structures.

dbSAP: single amino-acid polymorphism database for protein variation detection.

Millions of human single nucleotide polymorphisms (SNPs) or mutations have been identified so far, and these variants could be strongly correlated with phenotypic variations of traits/diseases. Among these variants, non-synonymous ones can result in amino-acid changes that are called single amino-acid polymorphisms (SAPs). Although some studies have tried to investigate the SAPs, only a small fraction of SAPs have been identified due to inadequately inferred protein variation database and the low coverage of mass spectrometry (MS) experiments. Here, we present the dbSAP database for conveniently accessing the comprehensive information and relationships of spectra, peptides and proteins of SAPs, as well as related genes, pathways, diseases and drug targets. In order to fully explore human SAPs, we built a customized protein database that contained comprehensive variant proteins by integrating and annotating the human SNPs and mutations from eight distinct databases (UniProt, Protein Mutation Database, HPMD, MSIPI, MS-CanProVar, dbSNP, Ensembl and COSMIC). After a series of quality controls, a total of 16 854 SAP peptides involving in 439 537 spectra were identified with large scale MS datasets from various human tissues and cell lines. dbSAP is freely available at http://www.megabionet.org/dbSAP/index.html.

zMAP toolset: model-based analysis of large-scale proteomic data via a variance stabilizing z-transformation.

Isobaric labeling-based mass spectrometry (ILMS) has been widely used to quantify, on a proteome-wide scale, the relative protein abundance in different biological conditions. However, large-scale ILMS data sets typically involve multiple runs of mass spectrometry, bringing great computational difficulty to the integration of ILMS samples. We present zMAP, a toolset that makes ILMS intensities comparable across mass spectrometry runs by modeling the associated mean-variance dependence and accordingly applying a variance stabilizing z-transformation. The practical utility of zMAP is demonstrated in several case studies involving the dynamics of cell differentiation and the heterogeneity across cancer patients.

MASH-Ocean 1.0: Interactive platform for investigating microbial diversity, function, and biogeography with marine metagenomic data.

A large number of oceanic metagenomic data and environmental metadata have been published. However, most studies focused on limited ecosystems using different analysis tools, making it challenging to integrate these data into robust results and comprehensive global understanding of marine microbiome. Here, we constructed a systematic and quantitative analysis platform, the Microbiome Atlas/Sino-Hydrosphere for Ocean Ecosystem (MASH-Ocean: https://www.biosino.org/mash-ocean/), by integrating global marine metagenomic data and a unified data processing flow. MASH-Ocean 1.0 comprises 2147 metagenomic samples with five analysis modules: sample view, diversity, function, biogeography, and interaction network. This platform provides convenient and stable support for researchers in microbiology, environmental science, and biogeochemistry, to ensure the integration of omics data generated from hydrosphere ecosystems, to bridge the gap between elusive omics data and biological, ecological, and geological discovery, ultimately to foster the formation of a comprehensive atlas for aquatic environments.

Early warning of emerging infectious diseases based on multimodal data.

The coronavirus disease 2019 (COVID-19) pandemic has dramatically increased the awareness of emerging infectious diseases. The advancement of multiomics analysis technology has resulted in the development of several databases containing virus information. Several scientists have integrated existing data on viruses to construct phylogenetic trees and predict virus mutation and transmission in different ways, providing prospective technical support for epidemic prevention and control. This review summarized the databases of known emerging infectious viruses and techniques focusing on virus variant forecasting and early warning. It focuses on the multi-dimensional information integration and database construction of emerging infectious viruses, virus mutation spectrum construction and variant forecast model, analysis of the affinity between mutation antigen and the receptor, propagation model of virus dynamic evolution, and monitoring and early warning for variants. As people have suffered from COVID-19 and repeated flu outbreaks, we focused on the research results of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and influenza viruses. This review comprehensively viewed the latest virus research and provided a reference for future virus prevention and control research.

Transcriptome Analyses Revealed the Wax and Phenylpropanoid Biosynthesis Pathways Related to Disease Resistance in Rootstock-Grafted Cucumber.

Cucumbers (Cucumis sativus L.) are a global popular vegetable and are widely planted worldwide. However, cucumbers are susceptible to various infectious diseases such as Fusarium and Verticillium wilt, downy and powdery mildew, and bacterial soft rot, which results in substantial economic losses. Grafting is an effective approach widely used to control these diseases. The present study investigated the role of wax and the phenylpropanoid biosynthesis pathway in black-seed pumpkin rootstock-grafted cucumbers. Our results showed that grafted cucumbers had a significantly higher cuticular wax contents on the fruit surface than that of self-rooted cucumbers at all stages observed. A total of 1132 differently expressed genes (DEGs) were detected in grafted cucumbers compared with self-rooted cucumbers. Pathway enrichment analysis revealed that phenylpropanoid biosynthesis, phenylalanine metabolism, plant circadian rhythm, zeatin biosynthesis, and diterpenoid biosynthesis were significantly enriched. In this study, 1 and 13 genes involved in wax biosynthesis and the phenylpropanoid biosynthesis pathway, respectively, were up-regulated in grafted cucumbers. Our data indicated that the up-regulated genes in the wax and phenylpropanoid biosynthesis pathways may contribute to disease resistance in rootstock-grafted cucumbers, which provides promising targets for enhancing disease resistance in cucumbers by genetic manipulation.

Genome-wide identification and expression analysis of glutathione S-transferase gene family to reveal their role in cold stress response in cucumber.

The plant glutathione S-transferases (GSTs) are versatile proteins encoded by several genes and play vital roles in responding to various physiological processes. Members of plant GSTs have been identified in several species, but few studies on cucumber (Cucumis sativus L.) have been reported. In this study, we identified 46 GST genes, which were divided into 11 classes. Chromosomal location and genome mapping revealed that cucumber GSTs (CsGSTs) were unevenly distributed in seven chromosomes, and the syntenic regions differed in each chromosome. The conserved motifs and gene structure of CsGSTs were analyzed using MEME and GSDS 2.0 online tools, respectively. Transcriptome and RT-qPCR analysis revealed that most CsGST members responded to cold stress. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses for differentially expressed CsGSTs under cold stress revealed that these genes responded to cold stress probably through "glutathione metabolism." Finally, we screened seven candidates that may be involved in cold stress using Venn analysis, and their promoters were analyzed using PlantCARE and New PLACE tools to predict the factors regulating these genes. Antioxidant enzyme activities were increased under cold stress conditions, which conferred tolerance against cold stress. Our study illustrates the characteristics and functions of CsGST genes, especially in responding to cold stress in cucumber.

Linking genomic and epidemiologic information to advance the study of COVID-19.

The outbreak of Coronavirus Disease 2019 (COVID-19) at the end of 2019 turned into a global pandemic. To help analyze the spread and evolution of the virus, we collated and analyzed data related to the viral genome, sequence variations, and locations in temporal and spatial distribution from GISAID. Information from the Wikipedia web page and published research papers were categorized and mined to extract epidemiological data, which was then integrated with the public dataset. Genomic and epidemiological data were matched with public information, and the data quality was verified by manual curation. Finally, an online database centered on virus genomic information and epidemiological data can be freely accessible at https://www.biosino.org/kgcov/ , which is helpful to identify relevant knowledge and devising epidemic prevention and control policies in collaboration with disease control personnel.

SAS: A Platform of Spike Antigenicity for SARS-CoV-2.

Since the outbreak of SARS-CoV-2, antigenicity concerns continue to linger with emerging mutants. As recent variants have shown decreased reactivity to previously determined monoclonal antibodies (mAbs) or sera, monitoring the antigenicity change of circulating mutants is urgently needed for vaccine effectiveness. Currently, antigenic comparison is mainly carried out by immuno-binding assays. Yet, an online predicting system is highly desirable to complement the targeted experimental tests from the perspective of time and cost. Here, we provided a platform of SAS (Spike protein Antigenicity for SARS-CoV-2), enabling predicting the resistant effect of emerging variants and the dynamic coverage of SARS-CoV-2 antibodies among circulating strains. When being compared to experimental results, SAS prediction obtained the consistency of 100% on 8 mAb-binding tests with detailed epitope covering mutational sites, and 80.3% on 223 anti-serum tests. Moreover, on the latest South Africa escaping strain (B.1.351), SAS predicted a significant resistance to reference strain at multiple mutated epitopes, agreeing well with the vaccine evaluation results. SAS enables auto-updating from GISAID, and the current version collects 867K GISAID strains, 15.4K unique spike (S) variants, and 28 validated and predicted epitope regions that include 339 antigenic sites. Together with the targeted immune-binding experiments, SAS may be helpful to reduce the experimental searching space, indicate the emergence and expansion of antigenic variants, and suggest the dynamic coverage of representative mAbs/vaccines among the latest circulating strains. SAS can be accessed at https://www.biosino.org/sas.

GTDB: an integrated resource for glycosyltransferase sequences and annotations.

Glycosyltransferases (GTs), a large class of carbohydrate-active enzymes, adds glycosyl moieties to various substrates to generate multiple bioactive compounds, including natural products with pharmaceutical or agrochemical values. Here, we first collected comprehensive information on GTs, including amino acid sequences, coding region sequences, available tertiary structures, protein classification families, catalytic reactions and metabolic pathways. Then, we developed sequence search and molecular docking processes for GTs, resulting in a GTs database (GTDB). In the present study, 520 179 GTs from approximately 21 647 species that involved in 394 kinds of different reactions were deposited in GTDB. GTDB has the following useful features: (i) text search is provided for retrieving the complete details of a query by combining multiple identifiers and data sources; (ii) a convenient browser allows users to browse data by different classifications and download data in batches; (iii) BLAST is offered for searching against pre-defined sequences, which can facilitate the annotation of the biological functions of query GTs; and lastly, (iv) GTdock using AutoDock Vina performs docking simulations of several GTs with the same single acceptor and displays the results based on 3Dmol.js allowing easy view of models.