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Heparan sulfate (HS) acts as a co-receptor of angiotensin-converting enzyme 2 (ACE2) by interacting with severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) spike glycoprotein (SGP) facilitating host cell entry of SARS-CoV-2 virus. Heparin, a highly sulfated version of heparan sulfate (HS), interacts with a variety of proteins playing key roles in many physiological and pathological processes. In this study, SARS-CoV-2 SGP receptor binding domain (RBD) wild type (WT), Delta and Omicron variants were expressed in Expi293F cells and used in the kinetic and structural analysis on their interactions with heparin. Surface plasmon resonance (SPR) analysis showed the binding kinetics of SGP RBD from WT and Delta variants were very similar while Omicron variant SGP showed a much higher association rate. The SGP from Delta and Omicron showed higher affinity ( K D ) to heparin than the WT SGP. Competition SPR studies using heparin oligosaccharides indicated that binding of SGP RBDs to heparin requires chain length greater than 18. Chemically modified heparin derivatives all showed reduced interactions in competition assays suggesting that all the sulfo groups in the heparin polysaccharide were critical for binding SGP RBDs with heparin. These interactions with heparin are pH sensitive. Acidic pH (pH 6.5, 5.5, 4.5) greatly increased the binding of WT and Delta SGP RBDs to heparin, while acidic pH slightly reduced the binding of Omicron SGP RBD to heparin compared to binding at pH 7.3. In contrast, basic pH (pH 8.5) greatly reduced the binding of Omicron SGP RBDs to heparin, with much less effects on WT or Delta. The pH dependence indicates different charged residues were present at the Omicron SGP-heparin interface. Detailed kinetic and structural analysis of the interactions of SARS-CoV-2 SGP RBDs with heparin provides important information for designing anti-SARS-CoV-2 molecules. 

Over the last couple of decades, there has been a rapid growth in the number and scope of agricultural genetics, genomics and breeding databases and resources. The AgBioData Consortium (https://www.agbiodata.org/) currently represents 44 databases and resources (https://www.agbiodata.org/databases) covering model or crop plant and animal GGB data, ontologies, pathways, genetic variation and breeding platforms (referred to as ‘databases’ throughout). One of the goals of the Consortium is to facilitate FAIR (Findable, Accessible, Interoperable, and Reusable) data management and the integration of datasets which requires data sharing, along with structured vocabularies and/or ontologies. Two AgBioData working groups, focused on Data Sharing and Ontologies, respectively, conducted a Consortium-wide survey to assess the current status and future needs of the members in those areas. A total of 33 researchers responded to the survey, representing 37 databases. Results suggest that data-sharing practices by AgBioData databases are in a fairly healthy state, but it is not clear whether this is true for all metadata and data types across all databases; and that, ontology use has not substantially changed since a similar survey was conducted in 2017. Based on our evaluation of the survey results, we recommend (i) providing training for database personnel in a specific data-sharing techniques, as well as in ontology use; (ii) further study on what metadata is shared, and how well it is shared among databases; (iii) promoting an understanding of data sharing and ontologies in the stakeholder community; (iv) improving data sharing and ontologies for specific phenotypic data types and formats; and (v) lowering specific barriers to data sharing and ontology use, by identifying sustainability solutions, and the identification, promotion, or development of data standards. Combined, these improvements are likely to help AgBioData databases increase development efforts towards improved ontology use, and data sharing via programmatic means.

Database URL https://www.agbiodata.org/databases

 

The role of the tumor microenvironment (TME) in immuno‐oncology has driven demand for technologies that deliverin situ, or spatial, molecular information. Compartmentalized heterogeneity that traditional methods miss is becoming key to predicting both acquired drug resistance to targeted therapies and patient response to immunotherapy. Here, we describe a novel method for assay‐agnostic spatial profiling and demonstrate its ability to detect immune microenvironment signatures in breast cancer patients that are unresolved by the immunohistochemical (IHC) assessment of programmed cell death ligand‐1 (PD‐L1) on immune cells, which represents the only FDA microenvironment‐based companion diagnostic test that has been approved for triple‐negative breast cancer (TNBC). Two distinct physiological states were found that are uncorrelated to tumor mutational burden (TMB), microsatellite instability (MSI),PD‐L1expression, and intrinsic cancer subtypes.

 

The Genome Context Viewer is a visual data-mining tool that allows users to search across multiple providers of genome data for regions with similarly annotated content that may be aligned and visualized at the level of their shared functional elements. By handling ordered sequences of gene family memberships as a unit of search and comparison, the user interface enables quick and intuitive assessment of the degree of gene content divergence and the presence of various types of structural events within syntenic contexts. Insights into functionally significant differences seen at this level of abstraction can then serve to direct the user to more detailed explorations of the underlying data in other interconnected, provider-specific tools.

GCV is provided under the GNU General Public License version 3 (GPL-3.0). Source code is available at https://github.com/legumeinfo/lis_context_viewer.

Supplementary data are available at Bioinformatics online.

 

Cowpea,Vigna unguiculata L. Walp., is a diploid warm‐season legume of critical importance as both food and fodder in sub‐Saharan Africa. This species is also grown in Northern Africa, Europe, Latin America, North America, and East to Southeast Asia. To capture the genomic diversity of domesticates of this important legume, de novo genome assemblies were produced for representatives of six subpopulations of cultivated cowpea identified previously from genotyping of several hundred diverse accessions. In the most complete assembly (IT97K‐499‐35), 26,026 core and 4963 noncore genes were identified, with 35,436 pan genes when considering all seven accessions. GO terms associated with response to stress and defense response were highly enriched among the noncore genes, while core genes were enriched in terms related to transcription factor activity, and transport and metabolic processes. Over 5 million single nucleotide polymorphisms (SNPs) relative to each assembly and over 40 structural variants >1 Mb in size were identified by comparing genomes. Vu10 was the chromosome with the highest frequency of SNPs, and Vu04 had the most structural variants. Noncore genes harbor a larger proportion of potentially disruptive variants than core genes, including missense, stop gain, and frameshift mutations; this suggests that noncore genes substantially contribute to diversity within domesticated cowpea.

 

With growing populations and pressing environmental problems, future economies will be increasingly plant-based. Now is the time to reimagine plant science as a critical component of fundamental science, agriculture, environmental stewardship, energy, technology and healthcare. This effort requires a conceptual and technological framework to identify and map all cell types, and to comprehensively annotate the localization and organization of molecules at cellular and tissue levels. This framework, called the Plant Cell Atlas (PCA), will be critical for understanding and engineering plant development, physiology and environmental responses. A workshop was convened to discuss the purpose and utility of such an initiative, resulting in a roadmap that acknowledges the current knowledge gaps and technical challenges, and underscores how the PCA initiative can help to overcome them. 

Legumes, comprising one of the largest, most diverse, and most economically important plant families, are the subject of vibrant research and development worldwide. Continued improvement of legume crops will benefit from the recent proliferation of genetic (including genomic) resources; but the diversity, scale, and complexity of these resources presents challenges to those managing and using them. A workshop held in March of 2019 addressed questions of data resources and priorities for the legumes. The workshop identified various needs and recommendations: (a) Develop strategies to effectively store, integrate, and relate genetic resources collected in different projects. (b) Leverage information collected across many legume species by standardizing data formats and ontologies, improving the state of metadata about datasets, and increasing use of the FAIR data principles. (c) Advocate for the critical role that curators exercise in integrating complex datasets into databases and adding high value metadata that enable downstream analytics and facilitate practical applications. (d) Implement standardized software and database development practices to best leverage limited developer time and expertise gained from the various legume (and other) species. (e) Develop tools and databases that can manage genetic information for the world's plant genetic resources, enabling efficient incorporation of important traits into breeding programs. (f) Centralize information on databases, tools, and training materials and establish funding streams to support training and outreach.