Biology subjects

Shmakov, S. A.

Publications and source records attributed to Shmakov, S. A..

8 recordsLinked to original sources

bioRxiv2026

A Unique Type V CRISPR-Cas System Encoded by a Group of Thermus Viruses

CRISPR-Cas are widespread adaptive immune systems that protect bacteria and archaea from mobile genetic elements such as bacteriophages. Metagenomic sequencing identified CRISPR-Cas systems in phage genomes; however, their functions remain largely unknown. Here, we present Cas12r-CRISPR, a novel type V CRISPR-Cas system encoded by Lalka phages infecting thermophilic Thermus bacteria. We determined Cas12r-CRISPR PAM consensus sequence and crRNA structure and showed, that when provided with appropriate spacers and expressed in Thermus thermophilus, Cas12r-CRISPR efficiently interferes with plasmid transformation as well as infection by diverse Thermus phages. In the course of Lalka phage infection, the Cas12r-CRISPR locus is expressed with middle phage genes and its transcripts are among the most abundant phage RNAs. Notably, most Cas12r-CRISPR spacers target integrative mobile elements widespread in Thermus genomes. Both Lalka phages and targeted integrative mobile elements use host tRNA genes as attachment sites. We therefore propose that Cas12r-CRISPR participates in an inter-MGEs conflict. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=81 SRC="FIGDIR/small/719267v1_ufig1.gif" ALT="Figure 1"> View larger version (23K): org.highwire.dtl.DTLVardef@f90c35org.highwire.dtl.DTLVardef@90a063org.highwire.dtl.DTLVardef@111f936org.highwire.dtl.DTLVardef@1008132_HPS_FORMAT_FIGEXP M_FIG C_FIG

molecular biology↗

bioRxiv2023

Widespread CRISPR repeat-like RNA regulatory elements in CRISPR-Cas systems

CRISPR-cas loci typically contain CRISPR arrays with unique spacers separating direct repeats. Spacers along with portions of adjacent repeats are transcribed and processed into CRISPR(cr) RNAs that target complementary sequences (protospacers) in mobile genetic elements, resulting in cleavage of the target DNA or RNA. Additional, standalone repeats in some CRISPR-cas loci produce distinct cr-like RNAs implicated in regulatory or other functions. We developed a computational pipeline to systematically predict crRNA-like elements by scanning for standalone repeat sequences that are conserved in closely related CRISPR-cas loci. Numerous crRNA-like elements were detected in diverse CRISPR-Cas systems, mostly, of type I, but also subtype V-A. Standalone repeats often form mini-arrays containing two repeat-like sequence separated by a spacer that is partially complementary to promoter regions of cas genes, in particular cas8, or cargo genes located within CRISPR-Cas loci, such as toxins-antitoxins. We show experimentally that a mini-array from a type I-F1 CRISPR-Cas system functions as a regulatory guide. We also identified mini-arrays in bacteriophages that could abrogate CRISPR immunity by inhibiting effector expression. Thus, recruitment of CRISPR effectors for regulatory functions via spacers with partial complementarity to the target is a common feature of diverse CRISPR-Cas systems.

genomics↗

bioRxiv2020

CRISPRIdentify: Identification of CRISPR arrays using machine learning approach

CRISPR-Cas are adaptive immune systems that degrade foreign genetic elements in archaea and bacteria. In carrying out their immune functions, CRISPR- Cas systems heavily rely on RNA components. These CRISPR (cr) RNAs are repeat-spacer units that are produced by processing of pre-crRNA, the transcript of CRISPR arrays, and guide Cas protein(s) to the cognate invading nucleic acids, enabling their destruction. Several bioinformatics tools have been developed to detect CRISPR arrays based solely on DNA sequences, but all these tools employ the same strategy of looking for repetitive patterns, which might correspond to CRISPR array repeats. The identified patterns are evaluated using a fixed, built-in scoring function, and arrays exceeding a cut-off value are reported. Here, we instead introduce a data-driven approach that uses machine learning to detect and differentiate true CRISPR arrays from false ones based on several features. Our CRISPR detection tool, CRISPRidentify, performs three steps: detection, feature extraction and classification based on manually curated sets of positive and negative examples of CRISPR arrays. The identified CRISPR arrays are then reported to the user accompanied by detailed annotation. We demonstrate that our approach identifies not only previously detected CRISPR arrays, but also CRISPR array candidates not detected by other tools. Compared to other methods, our tool has a drastically reduced false positive rate. In contrast to the existing tools, our approach not only provides the user with the basic statistics on the identified CRISPR arrays but also produces a certainty score as a practical measure of the likelihood that a given genomic region is a CRISPR array.

bioinformatics↗

bioRxiv2020

Thousands of previously unknown phages discovered in whole-community human gut metagenomes

BackgroundDouble-stranded DNA bacteriophages (dsDNA phages) play pivotal roles in structuring human gut microbiomes; yet, the gut phageome is far from being fully characterized, and additional groups of phages, including highly abundant ones, continue to be discovered by metagenome mining. A multilevel framework for taxonomic classification of viruses was recently adopted, facilitating the classification of phages into evolutionary informative taxonomic units based on hallmark genes. Together with advanced approaches for sequence assembly and powerful methods of sequence analysis, this revised framework offers the opportunity to discover and classify unknown phage taxa in the human gut. ResultsA search of human gut metagenomes for circular contigs encoding phage hallmark genes resulted in the identification of 3,738 apparently complete phage genomes that represent 451 putative genera. Several of these phage genera are only distantly related to previously identified phages and are likely to found new families. Two of the candidate families, "Flandersviridae" and "Quimbyviridae", include some of the most common and abundant members of the human gut virome that infect Bacteroides, Parabacteroides and Prevotella. The third proposed family, "Gratiaviridae", consists of less abundant phages that are distantly related to the families Autographiviridae, Drexlerviridae and Chaseviridae. Analysis of CRISPR spacers indicates that phages of all three putative families infect bacteria of the phylum Bacteroidetes. Comparative genomic analysis of the three candidate phage families revealed features without precedent in phage genomes. Some "Quimbyviridae" phages possess Diversity-Generating Retroelements (DGRs) that generate hypervariable target genes nested within defense-related genes, whereas the previously known targets of phage-encoded DGRs are structural genes. Several "Flandersviridae" phages encode enzymes of the isoprenoid pathway, a lipid biosynthesis pathway that so far has not been known to be manipulated by phages. The "Gratiaviridae" phages encode a HipA-family protein kinase and glycosyltransferase, suggesting these phages modify the host cell wall, preventing superinfection by other phages. Hundreds of phages in these three and other families are shown to encode catalases and iron-sequestering enzymes that can be predicted to enhance cellular tolerance to reactive oxygen species. ConclusionsAnalysis of phage genomes identified in whole-community human gut metagenomes resulted in the delineation of at least three new candidate families of Caudovirales and revealed diverse putative mechanisms underlying phage-host interactions in the human gut. Addition of these phylogenetically classified, diverse and distinct phages to public databases will facilitate taxonomic decomposition and functional characterization of human gut viromes.

microbiology↗

bioRxiv2020

Unique genomic features of crAss-like phages, the dominant component of the human gut virome

CrAssphage is the most abundant virus identified in the human gut virome and the founding member of a large group of bacteriophages that infect bacteria of the phylum Bacteroidetes and have been discovered by metagenomics of both animal-associated and environmental habitats. By analysis of circular contigs from human gut microbiomes, we identified nearly 600 genomes of crAss-like phages. Phylogenetic analysis of conserved genes demonstrates the monophyly of crAss-like phages, which can be expected to become a new order of viruses, and of 5 distinct branches, likely, families within that order. Two of these putative families have not been identified previously. The phages in one of these groups have large genomes (145-192 kilobases) and contain an unprecedented high density of self-splicing introns and inteins. Many crAss-like phages encode suppressor tRNAs that enable readthrough of UGA or UAG stop-codons, mostly, in late phage genes, which could represent a distinct anti-defense strategy. Another putative anti-defense mechanism that might target an unknown defense system in Bacteroidetes inhibiting phage DNA replication involves multiple switches of the phage DNA polymerase type between A and B families. Thus, comparative genomic analysis of the expanded assemblage of crAss-like phages reveals several unusual features of genome architecture and expression as well as phage biology that were not apparent from the previous crAssphage analyses.

microbiology↗

bioRxiv2020

Vast diversity of anti-CRISPR proteins predicted with a machine-learning approach

Bacteria and archaea evolve under constant pressure from numerous, diverse viruses and thus have evolved multiple defense systems. The CRISPR-Cas are adaptive immunity systems that have been harnessed for the development of the new generation of genome editing and engineering tools. In the incessant host-parasite arms race, viruses evolved multiple anti-defense mechanisms including numerous, diverse anti-CRISPR proteins (Acrs) that can inhibit CRISPR-Cas and therefore have enormous potential for application as modulators of genome editing tools. Most Acrs are small, highly variable proteins which makes their prediction a formidable task. We developed a machine learning approach for comprehensive Acr prediction. The model showed high predictive power when tested against an unseen test set that included several families of recently discovered Acrs and was employed to predict 2,500 novel candidate Acr families. An examination of the top candidates confirms that they possess typical Acr features. One of the top candidates was independently tested and found to possess anti-CRISPR activity (AcrIIA12). We provide a web resource (http://acrcatalog.pythonanywhere.com/) to access the predicted Acrs sequences and annotation. The results of this analysis expand the repertoire of predicted Acrs almost by two orders of magnitude and provide a rich resource for experimental Acr discovery.

microbiology↗

bioRxiv2018

Towards comprehensive characterization of CRISPR-linked genes

The CRISPR-Cas systems of bacterial and archaeal adaptive immunity consist of arrays of direct repeats separated by unique spacers and multiple CRISPR-associated (cas) genes encoding proteins that mediate the adaptation, CRISPR RNA maturation and interference stages of the CRISPR response. In addition to the relatively small set of core cas genes that are typically present in all representatives of each (sub)type of CRISPR-Cas systems and are essential for the defense function, numerous genes occur in CRISPR-cas loci only sporadically. Some of these have been shown to perform various ancillary roles in CRISPR response whereas the functional relevance of many others, if any, remains obscure. We developed a computational strategy for systematically detecting genes that are likely to be functionally linked to CRISPR-Cas systems. The approach is based on a \"CRISPRicity\" metric that measures the strength of CRISPR association for all protein-coding genes from sequenced bacterial and archaeal genomes. Uncharacterized genes with CRISPRicity values comparable to those of known cas genes are considered candidate CRISPR-ancillary genes, and we describe additional criteria to identify functionally relevant genes in the candidate set. About 80 genes that were not previously reported to be associated with CRISPR-Cas were identified as probable CRISPR-ancillary genes. A substantial majority of these genes reside in type III CRISPR-cas loci which implies exceptional functional versatility of type III systems. Numerous candidate CRISPR-ancillary genes encode integral membrane proteins suggestive of tight membrane connections of type III CRISPR-Cas whereas many other candidates are proteins implicated in various signal transduction pathways. These predictions provide ample material for improving annotation of CRISPR-cas loci and experimental characterization of previously unsuspected aspects of CRISPR-Cas functionality.\n\nSIGNIFICANCEThe CRISPR-Cas systems that mediate adaptive immunity in bacteria and archaea encompass a small set of core cas genes that are essential in a broad range of CRISPR-Cas systems. However, a much greater number of genes only sporadically co-occur with CRISPR-Cas, and for most of these, involvement in CRISPR-Cas functions has not been demonstrated. We developed a computational strategy that provides for systematic identification of CRISPR-linked proteins and prediction of their functional association with CRISPR-Cas systems. About 80 previously undetected, putative CRISPR-accessory proteins were identified. A large fraction of these proteins are predicted to be membrane-associated revealing an unknown side of CRISPR biology.

genomics↗

bioRxiv2017

The CRISPR Spacer Space Is Dominated By Sequences From The Species-Specific Mobilome

The CRISPR-Cas is the prokaryotic adaptive immunity system that stores memory of past encounters with foreign DNA in spacers that are inserted between direct repeats in CRISPR arrays 1,2. Only for a small fraction of the spacers, homologous sequences, termed protospacers, are detectable in viral, plasmid or microbial genomes 3,4. The rest of the spacers remain the CRISPR \"dark matter\". We performed a comprehensive analysis of the spacers from all CRISPR-cas loci identified in bacterial and archaeal genomes, and found that, depending on the CRISPR-Cas subtype and the prokaryotic phylum, protospacers were detectable for 1 to about 19% of the spacers ([~]7% global average). Among the detected protospacers, the majority, typically, 80 to 90%, originate from viral genomes, and among the rest, the most common source are genes integrated in microbial chromosomes but involved in plasmid conjugation or replication. Thus, almost all spacers with identifiable protospacers target mobile genetic elements (MGE). The GC-content, as well as dinucleotide and tetranucleotide compositions, of microbial genomes, their spacer complements, and the cognate viral genomes show a nearly perfect correlation and are almost identical. Given the near absence of self-targeting spacers, these findings are best compatible with the possibility that the spacers, including the dark matter, are derived almost completely from the species-specific microbial mobilomes.

microbiology↗