The taxonomic name resolution service : an online tool for automated standardization of plant names

© The Author(s), 2013. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in BMC Bioinformatics 14 (2013): 16, doi:10.1186/1471-2105-14-16.The digitization of biodiversity data is leading to the widespread application of taxon names that are superfluous, ambiguous or incorrect, resulting in mismatched records and inflated species numbers. The ultimate consequences of misspelled names and bad taxonomy are erroneous scientific conclusions and faulty policy decisions. The lack of tools for correcting this ‘names problem’ has become a fundamental obstacle to integrating disparate data sources and advancing the progress of biodiversity science. The TNRS, or Taxonomic Name Resolution Service, is an online application for automated and user-supervised standardization of plant scientific names. The TNRS builds upon and extends existing open-source applications for name parsing and fuzzy matching. Names are standardized against multiple reference taxonomies, including the Missouri Botanical Garden's Tropicos database. Capable of processing thousands of names in a single operation, the TNRS parses and corrects misspelled names and authorities, standardizes variant spellings, and converts nomenclatural synonyms to accepted names. Family names can be included to increase match accuracy and resolve many types of homonyms. Partial matching of higher taxa combined with extraction of annotations, accession numbers and morphospecies allows the TNRS to standardize taxonomy across a broad range of active and legacy datasets. We show how the TNRS can resolve many forms of taxonomic semantic heterogeneity, correct spelling errors and eliminate spurious names. As a result, the TNRS can aid the integration of disparate biological datasets. Although the TNRS was developed to aid in standardizing plant names, its underlying algorithms and design can be extended to all organisms and nomenclatural codes. The TNRS is accessible via a web interface at http://tnrs.iplantcollaborative.org/ webcite and as a RESTful web service and application programming interface. Source code is available at https://github.com/iPlantCollaborativeOpenSource/TNRS/ webcite.BJE was supported by NSF grant DBI 0850373 and TR by CSIRO Marine and Atmospheric Research, Australia,. BB and BJE acknowledge early financial support from Conservation International and TEAM who funded the development of early prototypes of taxonomic name resolution. The iPlant Collaborative (http://www.iplantcollaborative.org) is funded by a grant from the National Science Foundation (#DBI-0735191)

Predominantly Antibody-Deficient Patients With Non-infectious Complications Have Reduced Naive B, Treg, Th17, and Tfh17 Cells

Background: Patients with predominantly antibody deficiency (PAD) suffer from severe and recurrent infections that require lifelong immunoglobulin replacement and prophylactic antibiotic treatment. Disease incidence is estimated to be 1:25,000 worldwide, and up to 68% of patients develop non-infectious complications (NIC) including autoimmunity, which are difficult to treat, causing high morbidity, and early mortality. Currently, the etiology of NIC is unknown, and there are no diagnostic and prognostic markers to identify patients at risk. Objectives: To identify immune cell markers that associate with NIC in PAD patients. Methods: We developed a standardized 11-color flow cytometry panel that was utilized for in-depth analysis of B and T cells in 62 adult PAD patients and 59 age-matched controls. Results: Nine males had mutations in Bruton's tyrosine kinase (BTK) and were defined as having X-linked agammaglobulinemia. The remaining 53 patients were not genetically defined and were clinically diagnosed with agammaglobulinemia (n = 1), common variable immunodeficiency (CVID) (n = 32), hypogammaglobulinemia (n = 13), IgG subclass deficiency (n = 1), and specific polysaccharide antibody deficiency (n = 6). Of the 53, 30 (57%) had one or more NICs, 24 patients had reduced B-cell numbers, and 17 had reduced T-cell numbers. Both PAD-NIC and PAD+NIC groups had significantly reduced Ig class-switched memory B cells and naive CD4 and CD8 T-cell numbers. Naive and IgM memory B cells, Treg, Th17, and Tfh17 cells were specifically reduced in the PAD+NIC group. CD21lo B cells and Tfh cells were increased in frequencies, but not in absolute numbers in PAD+NIC. Conclusion: The previously reported increased frequencies of CD21lo B cells and Tfh cells are the indirect result of reduced naive B-cell and T-cell numbers. Hence, correct interpretation of immunophenotyping of immunodeficiencies is critically dependent on absolute cell counts. Finally, the defects in naive B- and T-cell numbers suggest a mild combined immunodeficiency in PAD patients with NIC. Together with the reductions in Th17, Treg, and Tfh17 numbers, these key differences could be utilized as biomarkers to support definitive diagnosis and to predict for disease progression

Influenza-specific IgG1(+) memory B-cell numbers increase upon booster vaccination in healthy adults but not in patients with predominantly antibody deficiency

Background: Annual influenza vaccination is recommended to all individuals over 6 months of age, including predominantly antibody deficiency (PAD) patients. Vaccination responses are typically evaluated by serology, and because PAD patients are by definition impaired in generating IgG and receive immunoglobulin replacement therapy (IgRT), it remains unclear whether they can mount an antigen-specific response. Objective: To quantify and characterise the antigen-specific memory B (Bmem) cell compartment in healthy controls and PAD patients following an influenza booster vaccination. Methods: Recombinant hemagglutinin (HA) from the A/Michigan/2015 H1N1 (AM15) strain with an AviTag was generated in a mammalian cell line, and following targeted biotinylation, was tetramerised with BUV395 or BUV737 streptavidin conjugates. Multicolour flow cytometry was applied on blood samples before and 28 days after booster influenza vaccination in 16 healthy controls and five PAD patients with circulating Bmem cells. Results: Recombinant HA tetramers were specifically recognised by 0.5-1% of B cells in previously vaccinated healthy adults. HA-specific Bmem cell numbers were significantly increased following booster vaccination and predominantly expressed IgG1. Similarly, PAD patients carried HA-specific Bmem cells, predominantly expressing IgG1. However, these numbers were lower than in controls and did not increase following booster vaccination. Conclusion: We have successfully identified AM15-specific Bmem cells in healthy controls and PAD patients. The presence of antigen-specific Bmem cells could offer an additional diagnostic tool to aid in the clinical diagnosis of PAD. Furthermore, alterations in the number or immunophenotype of HA-specific Bmem cells post-booster vaccination could assist in the evaluation of immune responses in individuals receiving IgRT

Rapid generation of durable B cell memory to SARS-CoV-2 spike and nucleocapsid proteins in COVID-19 and convalescence

Lasting immunity following SARS-CoV-2 infection is questioned because serum antibodies decline in convalescence. However, functional immunity is mediated by long-lived memory T and B (Bmem) cells. Therefore, we generated fluorescently-labeled tetramers of the spike receptor binding domain (RBD) and nucleocapsid protein (NCP) to determine the longevity and immunophenotype of SARS-CoV-2-specific Bmem cells in COVID-19 patients. A total of 36 blood samples were obtained from 25 COVID-19 patients between 4 and 242 days post-symptom onset including 11 paired samples. While serum IgG to RBD and NCP was identified in all patients, antibody levels began declining at 20 days post-symptom onset. RBD- and NCP-specific Bmem cells predominantly expressed IgM+ or IgG1+ and continued to rise until 150 days. RBD-specific IgG+ Bmem were predominantly CD27+, and numbers significantly correlated with circulating follicular helper T cell numbers. Thus, the SARS-CoV-2 antibody response contracts in convalescence with persistence of RBD- and NCP-specific Bmem cells. Flow cytometric detection of SARS-CoV-2-specific Bmem cells enables detection of long-term immune memory following infection or vaccination for COVID-19

Peptide mimic for influenza vaccination using nonnatural combinatorial chemistry

Polypeptide vaccines effectively activate human T cells but suffer from poor biological stability, which confines both transport logistics and in vivo therapeutic activity. Synthetic biology has the potential to address these limitations through the generation of highly stable antigenic “mimics” using subunits that do not exist in the natural world. We developed a platform based on D–amino acid combinatorial chemistry and used this platform to reverse engineer a fully artificial CD8+ T cell agonist that mirrored the immunogenicity profile of a native epitope blueprint from influenza virus. This nonnatural peptide was highly stable in human serum and gastric acid, reflecting an intrinsic resistance to physical and enzymatic degradation. In vitro, the synthetic agonist stimulated and expanded an archetypal repertoire of polyfunctional human influenza virus–specific CD8+ T cells. In vivo, specific responses were elicited in naive humanized mice by subcutaneous vaccination, conferring protection from subsequent lethal influenza challenge. Moreover, the synthetic agonist was immunogenic after oral administration. This proof-of-concept study highlights the power of synthetic biology to expand the horizons of vaccine design and therapeutic delivery