The evolution of CRISPR–cas loci, which encode adaptive immune systems in archaea and bacteria, involves rapid changes, in particular numerous rearrangements of the locus architecture and horizontal transfer of complete loci or individual modules. These dynamics complicate straightforward phylogenetic classification, but here we present an approach combining the analysis of signature protein families and features of the architecture of cas loci that unambiguously partitions most CRISPR–cas loci into distinct classes, types and subtypes. The new classification retains the overall structure of the previous version but is expanded to now encompass two classes, five types and 16 subtypes. The relative stability of the classification suggests that the most prevalent variants of CRISPR–Cas systems are already known. However, the existence of rare, currently unclassifiable variants implies that additional types and subtypes remain to be characterized.
The number and diversity of CRISPR-Cas systems has substantially increased in recent years. Here, we provide an updated evolutionary classification of CRISPR-Cas systems and cas genes, with an emphasis on the major developments that occurred since the publication of the latest classification in 2015. The new classification includes 2 classes, 6 types and 33 subtypes compared to 5 types and 16 subtypes in 2015. A key development is the ongoing discovery of multiple, novel class 2 CRISPR-Cas systems that now include 3 types and 17 subtypes. A second major novelty is the discovery of numerous derived CRISPR-Cas variants, often associated with mobile genetic elements that lack the nucleases required for interference. Some of these variants are involved in RNA-guided transposition whereas others are predicted to perform functions distinct from adaptive immunity that remain to be characterized experimentally. The third highlight is the discovery of numerous families of ancillary CRISPRlinked genes, often implicated in signal transduction. Together, these findings substantially clarify the functional diversity and evolutionary history of CRISPR-Cas. This work complements Ref. 34 by experimentally validating the prediction made in Ref. 33, that interference-deficient subtype IF CRISPR-Cas systems encoded in Tn7like transposons enable crRNA-dependent transposition.
The protein cytotoxic T lymphocyte antigen-4 (CTLA-4) is an essential negative regulator of immune responses and its loss causes fatal autoimmunity in mice. We investigated a large autosomal-dominant family with five individuals presenting with a complex immune dysregulation syndrome characterized by hypogammaglobulinemia, recurrent infections and multiple autoimmune features. We identified a heterozygous nonsense mutation in exon 1 of CTLA4. Screening of 71 unrelated patients with comparable clinical phenotypes identified five additional families (nine individuals) with novel splice site and missense mutations in CTLA4. While clinical penetrance was incomplete (eight adults of a total of 19 CTLA4 mutation carriers were considered unaffected), CTLA-4 protein expression was decreased in regulatory T cells (Treg cells) in patients and carriers with CTLA4 mutations. Whilst Treg cells were generally present at elevated numbers, their suppressive function, CTLA-4 ligand binding and transendocytosis of CD80 were impaired. Mutations in CTLA4 were also associated with decreased circulating B cell numbers and antibody levels. Taken together, mutations in CTLA-4 resulting in CTLA-4 haploinsufficiency or impaired ligand binding results in a complex syndrome with features of both autoimmunity and immunodeficiency.
Motivation: During the last few years, several new small regulatory RNAs (sRNAs) have been discovered in bacteria. Most of them act as post-transcriptional regulators by base pairing to a target mRNA, causing translational repression or activation, or mRNA degradation. Numerous sRNAs have already been identified, but the number of experimentally verified targets is considerably lower. Consequently, computational target prediction is in great demand. Many existing target prediction programs neglect the accessibility of target sites and the existence of a seed, while other approaches are either specialized to certain types of RNAs or too slow for genome-wide searches.Results: We introduce INTARNA, a new general and fast approach to the prediction of RNA–RNA interactions incorporating accessibility of target sites as well as the existence of a user-definable seed. We successfully applied INTARNA to the prediction of bacterial sRNA targets and determined the exact locations of the interactions with a higher accuracy than competing programs.Availability: http://www.bioinf.uni-freiburg.de/Software/Contact: IntaRNA@informatik.uni-freiburg.deSupplementary information: Supplementary data are available at Bioinformatics online.
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