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      Distinct effector functions mediated by Fc regions of bovine IgG subclasses and their interaction with Fc gamma receptors

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          Abstract

          Cattle possess three IgG subclasses. However, the key immune functions, including complement and NK cell activation, and enhancement of phagocytosis, are not fully described for bovine IgG1, 2 and 3. We produced chimeric monoclonal antibodies (mAbs) consisting of a defined variable region linked to the constant regions of bovine IgG1, 2 and 3, and expressed His-tagged soluble recombinant bovine Fc gamma receptors (FcγRs) IA (CD64), IIA (CD32A), III (CD16) and Fcγ2R. Functional assays using bovinized mAbs were developed. IgG1 and IgG3, but not IgG2, activated complement-dependent cytotoxicity. Only IgG1 could activate cattle NK cells to mobilize CD107a after antigen crosslinking, a surrogate assay for antibody-dependent cell cytotoxicity. Both IgG1 and IgG2 could trigger monocyte-derived macrophages to phagocytose fluorescently labelled antigen-expressing target cells. IgG3 induced only weak antibody-dependent cellular phagocytosis (ADCP). By contrast, monocytes only exhibited strong ADCP when triggered by IgG2. IgG1 bound most strongly to recombinant FcγRs IA, IIA and III, with weaker binding by IgG3 and none by IgG2, which bound exclusively to Fcγ2R. Immune complexes containing IgG1, 2 and 3 bound differentially to leukocyte subsets, with IgG2 binding strongly to neutrophils and monocytes and all subclasses binding platelets. Differential expression of the FcγRs on leukocyte subsets was demonstrated by surface staining and/or RT-qPCR of sorted cells, e.g., Fcγ2R mRNA was expressed in monocytes/macrophages, neutrophils, and platelets, potentially explaining their strong interactions with IgG2, and FcγRIII was expressed on NK cells, presumably mediating IgG1-dependent NK cell activation. These data reveal differences in bovine IgG subclass functionality, which do not correspond to those described in humans, mice or pigs, which is relevant to the study of these IgG subclasses in vaccine and therapeutic antibody development.

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          Most cited references42

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          IgG Subclasses and Allotypes: From Structure to Effector Functions

          Of the five immunoglobulin isotypes, immunoglobulin G (IgG) is most abundant in human serum. The four subclasses, IgG1, IgG2, IgG3, and IgG4, which are highly conserved, differ in their constant region, particularly in their hinges and upper CH2 domains. These regions are involved in binding to both IgG-Fc receptors (FcγR) and C1q. As a result, the different subclasses have different effector functions, both in terms of triggering FcγR-expressing cells, resulting in phagocytosis or antibody-dependent cell-mediated cytotoxicity, and activating complement. The Fc-regions also contain a binding epitope for the neonatal Fc receptor (FcRn), responsible for the extended half-life, placental transport, and bidirectional transport of IgG to mucosal surfaces. However, FcRn is also expressed in myeloid cells, where it participates in both phagocytosis and antigen presentation together with classical FcγR and complement. How these properties, IgG-polymorphisms and post-translational modification of the antibodies in the form of glycosylation, affect IgG-function will be the focus of the current review.
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            Artemis: sequence visualization and annotation

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              De novo assembly of the cattle reference genome with single-molecule sequencing

              Abstract Background Major advances in selection progress for cattle have been made following the introduction of genomic tools over the past 10–12 years. These tools depend upon the Bos taurus reference genome (UMD3.1.1), which was created using now-outdated technologies and is hindered by a variety of deficiencies and inaccuracies. Results We present the new reference genome for cattle, ARS-UCD1.2, based on the same animal as the original to facilitate transfer and interpretation of results obtained from the earlier version, but applying a combination of modern technologies in a de novo assembly to increase continuity, accuracy, and completeness. The assembly includes 2.7 Gb and is >250× more continuous than the original assembly, with contig N50 >25 Mb and L50 of 32. We also greatly expanded supporting RNA-based data for annotation that identifies 30,396 total genes (21,039 protein coding). The new reference assembly is accessible in annotated form for public use. Conclusions We demonstrate that improved continuity of assembled sequence warrants the adoption of ARS-UCD1.2 as the new cattle reference genome and that increased assembly accuracy will benefit future research on this species.
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                Author and article information

                Contributors
                URI : https://loop.frontiersin.org/people/1219540Role: Role: Role: Role: Role:
                URI : https://loop.frontiersin.org/people/1500405Role: Role:
                URI : https://loop.frontiersin.org/people/392631Role: Role: Role: Role:
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                URI : https://loop.frontiersin.org/people/2555307Role: Role: Role:
                URI : https://loop.frontiersin.org/people/300164Role: Role: Role:
                URI : https://loop.frontiersin.org/people/38633Role: Role: Role: Role: Role: Role:
                URI : https://loop.frontiersin.org/people/78089Role: Role: Role: Role:
                Journal
                Front Immunol
                Front Immunol
                Front. Immunol.
                Frontiers in Immunology
                Frontiers Media S.A.
                1664-3224
                22 November 2023
                2023
                : 14
                : 1286903
                Affiliations
                [1] The Pirbright Institute , Woking, United Kingdom
                Author notes

                Edited by: Robert David Miller, University of New Mexico, United States

                Reviewed by: Lars T. Hellman, Uppsala University, Sweden; Fabián Esteban Díaz, Iowa State University, United States

                *Correspondence: Simon P. Graham, simon.graham@ 123456pirbright.ac.uk
                Article
                10.3389/fimmu.2023.1286903
                10702552
                38077405
                ff3eb1b7-e51f-46c6-9850-c12053618e3f
                Copyright © 2023 Noble, Paudyal, Schwartz, Mwangi, Munir, Tchilian, Hammond and Graham

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 31 August 2023
                : 07 November 2023
                Page count
                Figures: 9, Tables: 2, Equations: 0, References: 42, Pages: 14, Words: 7028
                Funding
                Funded by: Bill and Melinda Gates Foundation , doi 10.13039/100000865;
                Award ID: OPP1215550
                Funded by: Biotechnology and Biological Sciences Research Council , doi 10.13039/501100000268;
                Award ID: BBS/E/I/00007030, BBS/E/I/00007031, BBS/E/I/00007038, BBS/E/I/00007039, BB/V019031/1
                The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This research was funded by the Bill and Melinda Gates Foundation ‘Pirbright Livestock Antibody Hub’ grant (OPP1215550). The authors would like to acknowledge the Pirbright Flow Cytometry facility and support through the UKRI Biotechnology and Biological Sciences Research Council (BBSRC) Institute Strategic Programme and Core Capability Grants to The Pirbright Institute (BBS/E/I/00007030, BBS/E/I/00007031, BBS/E/I/00007038 and BBS/E/I/00007039) and grant BB/V019031/1. SPG is a Jenner Institute Investigator.
                Categories
                Immunology
                Original Research
                Custom metadata
                Comparative Immunology

                Immunology
                cattle,igg subclasses,fc gamma receptor,fc region,nk cell,monocyte,macrophage
                Immunology
                cattle, igg subclasses, fc gamma receptor, fc region, nk cell, monocyte, macrophage

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