Neuronal nicotinic acetylcholine receptor antibodies in autoimmune central nervous system disorders

BackgroundNeuronal nicotinic acetylcholine receptors (nAChRs) are abundant in the central nervous system (CNS), playing critical roles in brain function. Antigenicity of nAChRs has been well demonstrated with antibodies to ganglionic AChR subtypes (i.e., subunit α3 of α3β4-nAChR) and muscle AChR autoantibodies, thus making nAChRs candidate autoantigens in autoimmune CNS disorders. Antibodies to several membrane receptors, like NMDAR, have been identified in autoimmune encephalitis syndromes (AES), but many AES patients have yet to be unidentified for autoantibodies. This study aimed to develop of a cell-based assay (CBA) that selectively detects potentially pathogenic antibodies to subunits of the major nAChR subtypes (α4β2- and α7-nAChRs) and its use for the identification of such antibodies in “orphan” AES cases.MethodsThe study involved screening of sera derived from 1752 patients from Greece, Turkey and Italy, who requested testing for AES-associated antibodies, and from 1203 “control” patients with other neuropsychiatric diseases, from the same countries or from Germany. A sensitive live-CBA with α4β2-or α7-nAChR–transfected cells was developed to detect antibodies against extracellular domains of nAChR major subunits. Flow cytometry (FACS) was performed to confirm the CBA findings and indirect immunohistochemistry (IHC) to investigate serum autoantibodies’ binding to rat brain tissue.ResultsThree patients were found to be positive for serum antibodies against nAChR α4 subunit by CBA and the presence of the specific antibodies was quantitatively confirmed by FACS. We detected specific binding of patient‐derived serum anti‐nAChR α4 subunit antibodies to rat cerebellum and hippocampus tissue. No serum antibodies bound to the α7-nAChR-transfected or control-transfected cells, and no control serum antibodies bound to the transfected cells. All patients positive for serum anti‐nAChRs α4 subunit antibodies were negative for other AES-associated antibodies. All three of the anti‐nAChR α4 subunit serum antibody-positive patients fall into the AES spectrum, with one having Rasmussen encephalitis, another autoimmune meningoencephalomyelitis and another being diagnosed with possible autoimmune encephalitis.ConclusionThis study lends credence to the hypothesis that the major nAChR subunits are autoimmune targets in some cases of AES and establishes a sensitive live-CBA for the identification of such patients

BioTIME 2.0 : expanding and improving a database of biodiversity time series

Funding: H2020 European Research Council (Grant Number(s): GA 101044975, GA 101098020).Motivation: Here, we make available a second version of the BioTIME database, which compiles records of abundance estimates for species in sample events of ecological assemblages through time. The updated version expands version 1.0 of the database by doubling the number of studies and includes substantial additional curation to the taxonomic accuracy of the records, as well as the metadata. Moreover, we now provide an R package (BioTIMEr) to facilitate use of the database. Main Types of Variables: Included The database is composed of one main data table containing the abundance records and 11 metadata tables. The data are organised in a hierarchy of scales where 11,989,233 records are nested in 1,603,067 sample events, from 553,253 sampling locations, which are nested in 708 studies. A study is defined as a sampling methodology applied to an assemblage for a minimum of 2 years. Spatial Location and Grain: Sampling locations in BioTIME are distributed across the planet, including marine, terrestrial and freshwater realms. Spatial grain size and extent vary across studies depending on sampling methodology. We recommend gridding of sampling locations into areas of consistent size. Time Period and Grain: The earliest time series in BioTIME start in 1874, and the most recent records are from 2023. Temporal grain and duration vary across studies. We recommend doing sample-level rarefaction to ensure consistent sampling effort through time before calculating any diversity metric. Major Taxa and Level of Measurement: The database includes any eukaryotic taxa, with a combined total of 56,400 taxa. Software Format: csv and. SQL.Peer reviewe

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Sex-stratified Genome-wide Association Studies Including 270,000 Individuals Show Sexual Dimorphism in Genetic Loci for Anthropometric Traits

Peer reviewe

BioTIME 2.0 : expanding and improving a database of biodiversity time series

Motivation. Here, we make available a second version of the BioTIME database, which compiles records of abundance estimates for species in sample events of ecological assemblages through time. The updated version expands version 1.0 of the database by doubling the number of studies and includes substantial additional curation to the taxonomic accuracy of the records, as well as the metadata. Moreover, we now provide an R package (BioTIMEr) to facilitate use of the database. Main Types of Variables Included. The database is composed of one main data table containing the abundance records and 11 metadata tables. The data are organised in a hierarchy of scales where 11,989,233 records are nested in 1,603,067 sample events, from 553,253 sampling locations, which are nested in 708 studies. A study is defined as a sampling methodology applied to an assemblage for a minimum of 2 years. Spatial Location and Grain. Sampling locations in BioTIME are distributed across the planet, including marine, terrestrial and freshwater realms. Spatial grain size and extent vary across studies depending on sampling methodology. We recommend gridding of sampling locations into areas of consistent size. Time Period and Grain. The earliest time series in BioTIME start in 1874, and the most recent records are from 2023. Temporal grain and duration vary across studies. We recommend doing sample-level rarefaction to ensure consistent sampling effort through time before calculating any diversity metric. Major Taxa and Level of Measurement. The database includes any eukaryotic taxa, with a combined total of 56,400 taxa. Software Format. csv and. SQL

T_1/2 of Various (α6β2)₂β3 AChR Constructs against 30µM ACh.

<p>T_1/2 of Various (α6β2)₂β3 AChR Constructs against 30µM ACh.</p

Efficient Expression of Functional (α6β2)₂β3 AChRs in Xenopus Oocytes from Free Subunits Using Slightly Modified α6 Subunits

<div><p>Human (α6β2)(α4β2)β3 nicotinic acetylcholine receptors (AChRs) are essential for addiction to nicotine and a target for drug development for smoking cessation. Expressing this complex AChR is difficult, but has been achieved using subunit concatamers. In order to determine what limits expression of α6* AChRs and to efficiently express α6* AChRs using free subunits, we investigated expression of the simpler (α6β2)₂β3 AChR. The concatameric form of this AChR assembles well, but is transported to the cell surface inefficiently. Various chimeras of α6 with the closely related α3 subunit increased expression efficiency with free subunits and produced pharmacologically equivalent functional AChRs. A chimera in which the large cytoplasmic domain of α6 was replaced with that of α3 increased assembly with β2 subunits and transport of AChRs to the oocyte surface. Another chimera replacing the unique methionine 211 of α6 with leucine found at this position in transmembrane domain 1 of α3 and other α subunits increased assembly of mature subunits containing β3 subunits within oocytes. Combining both α3 sequences in an α6 chimera increased expression of functional (α6β2)₂β3 AChRs to 12-fold more than with concatamers. This is pragmatically useful, and provides insights on features of α6 subunit structure that limit its expression in transfected cells.</p></div

Pharmacological Properties of Various (α6β2)₂β3 AChR Constructs.

<p>Note the EC₅₀ values for construct <b>6</b>, which contains the α3 cytoplasmic domain, transmembrane domain 4, and the extracellular C-terminal domain, are significantly different from those of construct <b>1</b> for nicotine (p = 0.0266).</p

Assembly of (α6β2)₂β3 AChRs constructs evaluated by sucrose sedimentation velocity gradient analysis.

<p>After centrifugation, gradient fractions were immunoisolated on microwells coated with mAb 295 to β2 to isolate α6β2β3 AChRs prior to labeling with ³H epibatidine. Properly assembled mature (α6β2)₂β3 AChRs sediment between the two internal standards, 9S monomer and 13S dimer of <i>Torpedo californica</i> AChRs. Peaks on the left of dimers in the gradient indicate multimers or aggregates of AChRs, while peaks on the right of monomers represent partially assembled AChRs. A) Expression of pentameric concatamer construct <b>1</b> (β3−α6−β2−α6−β2) resulted in a high proportion of mature AChRs, as expected (16). B) Expression of construct <b>2</b> (α6+β2+β3) resulted in a high proportion of aggregates and partially assembled AChRs and a very low proportion of mature AChRs, as expected (12). C) Expression of construct <b>3</b> (α6_211L+β2+β3) resulted in a large proportion of mature AChRs. D) Expression of construct <b>4</b> (α6_α3cyt+β2+β3) resulted in mature AChRs but also partially assembled AChRs and both large and very large aggregates. E) Expression of construct <b>5</b> (α6_211L,α3cyt+β2+β3) showed mature AChRs and some aggregates. F) Expresion of construct <b>6</b> (α6_α3cyt-C+β2+β3) showed a high proportion of mature AChRs and few aggregates.</p