Employing toxin-antitoxin genome markers for identification of Bifidobacterium and Lactobacillus strains in human metagenomes

Recent research has indicated that in addition to the unique genotype each individual may also have a unique microbiota composition. Difference in microbiota composition may emerge from both its species and strain constituents. It is important to know the precise composition especially for the gut microbiota (GM), since it can contribute to the health assessment, personalized treatment, and disease prevention for individuals and groups (cohorts). The existing methods for species and strain composition in microbiota are not always precise and usually not so easy to use. Probiotic bacteria of the genus Bifidobacterium and Lactobacillus make an essential component of human GM. Previously we have shown that in certain Bifidobacterium and Lactobacillus species the RelBE and MazEF superfamily of toxin-antitoxin (TA) systems may be used as functional biomarkers to differentiate these groups of bacteria at the species and strain levels. We have composed a database of TA genes of these superfamily specific for all lactobacilli and bifidobacteria species with complete genome sequence and confirmed that in all Lactobacillus and Bifidobacterium species TA gene composition is species and strain specific. To analyze composition of species and strains of two bacteria genera, Bifidobacterium and Lactobacillus, in human GM we developed TAGMA (toxin antitoxin genes for metagenomes analyses) software based on polymorphism in TA genes. TAGMA was tested on gut metagenomic samples. The results of our analysis have shown that TAGMA can be used to characterize species and strains of Lactobacillus and Bifidobacterium in metagenomes

CRISPR-Cas Systems in Gut Microbiome of Children with Autism Spectrum Disorders

The human gut microbiome is associated with various diseases, including autism spectrum disorders (ASD). Variations of the taxonomical composition in the gut microbiome of children with ASD have been observed repeatedly. However, features and parameters of the microbiome CRISPR-Cas systems in ASD have not been investigated yet. Here, we demonstrate such an analysis in order to describe the overall changes in the microbiome CRISPR-Cas systems during ASD as well as to reveal their potential to be used in diagnostics and therapy. For the systems identification, we used a combination of the publicly available tools suited for completed genomes with subsequent filtrations. In the considered data, the microbiomes of children with ASD contained fewer arrays per Gb of assembly than the control group, but the arrays included more spacers on average. CRISPR arrays from the microbiomes of children with ASD differed from the control group neither in the fractions of spacers with protospacers from known genomes, nor in the sets of known bacteriophages providing protospacers. Almost all bacterial protospacers of the gut microbiome systems for both children with ASD and the healthy ones were located in prophage islands, leaving no room for the systems to participate in the interspecies competition

CRISPR-Cas Systems in Gut Microbiome of Children with Autism Spectrum Disorders

The human gut microbiome is associated with various diseases, including autism spectrum disorders (ASD). Variations of the taxonomical composition in the gut microbiome of children with ASD have been observed repeatedly. However, features and parameters of the microbiome CRISPR-Cas systems in ASD have not been investigated yet. Here, we demonstrate such an analysis in order to describe the overall changes in the microbiome CRISPR-Cas systems during ASD as well as to reveal their potential to be used in diagnostics and therapy. For the systems identification, we used a combination of the publicly available tools suited for completed genomes with subsequent filtrations. In the considered data, the microbiomes of children with ASD contained fewer arrays per Gb of assembly than the control group, but the arrays included more spacers on average. CRISPR arrays from the microbiomes of children with ASD differed from the control group neither in the fractions of spacers with protospacers from known genomes, nor in the sets of known bacteriophages providing protospacers. Almost all bacterial protospacers of the gut microbiome systems for both children with ASD and the healthy ones were located in prophage islands, leaving no room for the systems to participate in the interspecies competition

Scheme of typing of <i>M</i>. <i>tuberculosis</i> strains using 13 genes of type II TA systems.

<p>The algorithm for determining the genotype is presented. The scheme shows that, after the first iteration to determine the genotype, the number of genes for the analysis is decreased twofold. Each gene in the brackets is given its position that is replaced, and the appropriate nucleotide is indicated. All replacements are calculated relative to the reference strain H37Rv.</p

<i>Mycobacterium tuberculosis</i> Type II Toxin-Antitoxin Systems: Genetic Polymorphisms and Functional Properties and the Possibility of Their Use for Genotyping

<div><p>Various genetic markers such as IS-elements, DR-elements, variable number tandem repeats (VNTR), single nucleotide polymorphisms (SNPs) in housekeeping genes and other groups of genes are being used for genotyping. We propose a different approach. We suggest the type II toxin-antitoxin (TA) systems, which play a significant role in the formation of pathogenicity, tolerance and persistence phenotypes, and thus in the survival of <i>Mycobacterium tuberculosis</i> in the host organism at various developmental stages (colonization, infection of macrophages, etc.), as the marker genes. Most genes of TA systems function together, forming a single network: an antitoxin from one pair may interact with toxins from other pairs and even from other families. In this work a bioinformatics analysis of genes of the type II TA systems from 173 sequenced genomes of <i>M</i>. <i>tuberculosis</i> was performed. A number of genes of type II TA systems were found to carry SNPs that correlate with specific genotypes. We propose a minimally sufficient set of genes of TA systems for separation of <i>M</i>. <i>tuberculosis</i> strains at nine basic genotype and for further division into subtypes. Using this set of genes, we genotyped a collection consisting of 62 clinical isolates of <i>M</i>. <i>tuberculosis</i>. The possibility of using our set of genes for genotyping using PCR is also demonstrated.</p></div

The type II TA systems of mycobacteria were investigated. Schematic diagram of the toxin-antitoxin system.

<p>(A) TA systems are annotated according to the GenBank database, excluding VapBC50 (rv3750c-rv3749c), VapBC49 (rv3180c-rv3181c), HigBA3 (rv3182-rv3183), HigBA2 (rv2022c-rv2021c), MazEF10 (rv0298-rv0299) and VapBC45 (rv2018-rv2019) systems; these systems are annotated according to Sala et al. [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0143682#pone.0143682.ref032" target="_blank">32</a>]. The system RelBE3 (rv3358-rv3357, GenBank database, NCBI) is called the YefM/YoeB system by Sala. All of the TA systems depicted here are type II (systems marked with an asterisk are novel TA systems that are not classified to any family, but for which functional activity has been shown [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0143682#pone.0143682.ref032" target="_blank">32</a>]). The 13 genes, our proposed set for genotyping, are highlighted in bold. (B) Type II TA systems are encoded by two genes, a toxin and an antitoxin, that form one operon with a promoter located upstream of the first antitoxin gene. PIN domain is the functional part of the toxin gene, the four conserved acidic residues marked at the picture: the three well-conserved acidic residues, at positions 4[D], 40[E] and 93[D], and with fourth acidic residue is less well conserved at position 112[D].</p

Phylogenetic relationship between different genotypes of the <i>M</i>. <i>tuberculosis</i>.

<p>(A) Phylogenetic tree constructed on the basis of polymorphisms (SNP) in all of the considered genes of type II TA systems. An unrooted phylogenetic tree for the 173 strains from this study was constructed based on the presence/absence of SNPs in the nucleotide sequences of 71 TA systems (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0143682#pone.0143682.s003" target="_blank">S3 Table</a>); (B) Phylogenetic tree constructed on the basis of SNP in a minimum set of genes of type II TA systems. An unrooted phylogenetic tree for 173 strains constructed based on SNPs in the nucleotide sequences of 13 genes (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0143682#pone.0143682.t002" target="_blank">Table 2</a>). In both of cases strains included in the one cluster belong to the same genotype (various genotypes highlighted by color). The trees was constructed by the neighbor-joining approach. The TA systems sequences were retrieved from different databases (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0143682#sec002" target="_blank">Materials and Methods</a>). Sequences were multiply aligned by using ClustalW ver. 2.1 software. The trees was calculated using MEGA ver. 6. Bootstrap support > 60% is indicated for the trees.</p

Detection of the Ural genotype by qPCR.

<p>Fluorescence in the FAM channel (blue): (1)13_2978, (2) 13–3114, (3) 13–3086, (4) 13_3158, (5) 13_4178, (6) 13_3539, (7) 13_2566, (8) 13_3632, (9) 13_3599, (10) 13_3896, (11) 13_3582, (12) 13_4189, (13) 13_3535, (15) 13_3147; Fluorescence in the HEX channel (green): (14) 13_3147, (16) 13_2978. Fluorescence of the channel FAM (blue) indicates the accumulation of the PCR product containing cytosine (C); the fluorescence of the channel HEX (green) indicates the accumulation of the PCR product containing thymine (T, the variable nucleotide) and indicates the SNP in the <i>vapC10</i> gene (C394→T394) characteristic of the Ural genotype. Line 14 (13_3147) and 16 (13_2978) belong to the Ural genotype. For isolate 13_2978 fluorescence is detected on the two channels (FAM and HEX), this can indicate the presence of impurities (coinfection). qPCR fluorescence in RFU (relative fluorescence units) vs. PCR cycles. Intensity of fluorescence depending on the number of qPCR cycles for strains belonging to the Euro-American lineage.</p