Dmitry Ischenko

Comparative genomic analysis of Mycobacterium tuberculosis drug resistant strains from Russia.

Tuberculosis caused by multidrug-resistant (MDR) and extensively drug-resistant (XDR) Mycobacterium tuberculosis (MTB) strains is a growing problem in many countries. The availability of the complete nucleotide sequences of several MTB genomes allows to use the comparative genomics as a tool to study the relationships of strains and differences in their evolutionary history including acquisition of drug-resistance. In our work, we sequenced three genomes of Russian MTB strains of different phenotypes – drug susceptible, MDR and XDR. Of them, MDR and XDR strains were collected in Tomsk (Siberia, Russia) during the local TB outbreak in 1998–1999 and belonged to rare KQ and KY families in accordance with IS6110 typing, which are considered endemic for Russia. Based on phylogenetic analysis, our isolates belonged to different genetic families, Beijing, Ural and LAM, which made the direct comparison of their genomes impossible. For this reason we performed their comparison in the broader context of all M. tuberculosis genomes available in GenBank. The list of unique individual non-synonymous SNPs for each sequenced isolate was formed by comparison with all SNPs detected within the same phylogenetic group. For further functional analysis, all proteins with unique SNPs were ascribed to 20 different functional classes based on Clusters of Orthologous Groups (COG). We have confirmed drug resistant status of our isolates that harbored almost all known drug-resistance associated mutations. Unique SNPs of an XDR isolate CTRI-4XDR, belonging to a Beijing family were compared in more detail with SNPs of additional 14 Russian XDR strains of the same family. Only type specific mutations in genes of repair, replication and recombination system (COG category L) were found common within this group. Probably the other unique SNPs discovered in CTRI-4XDR may have an important role in adaptation of this microorganism to its surrounding and in escape from antituberculosis drugs treatment.

Genome-Wide Mycobacterium tuberculosis Variation (GMTV) Database: A New Tool for Integrating Sequence Variations and Epidemiology

BackgroundTuberculosis (TB) poses a worldwide threat due to advancing multidrug-resistant strains and deadly co-infections with Human immunodeficiency virus. Today large amounts of Mycobacterium tuberculosis whole genome sequencing data are being assessed broadly and yet there exists no comprehensive online resource that connects M. tuberculosis genome variants with geographic origin, with drug resistance or with clinical outcome.DescriptionHere we describe a broadly inclusive unifying Genome-wide Mycobacterium tuberculosis Variation (GMTV) database, (http://mtb.dobzhanskycenter.org) that catalogues genome variations of M. tuberculosis strains collected across Russia. GMTV contains a broad spectrum of data derived from different sources and related to M. tuberculosis molecular biology, epidemiology, TB clinical outcome, year and place of isolation, drug resistance profiles and displays the variants across the genome using a dedicated genome browser. GMTV database, which includes 1084 genomes and over 69,000 SNP or Indel variants, can be queried about M. tuberculosis genome variation and putative associations with drug resistance, geographical origin, and clinical stages and outcomes.ConclusionsImplementation of GMTV tracks the pattern of changes of M. tuberculosis strains in different geographical areas, facilitates disease gene discoveries associated with drug resistance or different clinical sequelae, and automates comparative genomic analyses among M. tuberculosis strains.

Agent Based Modeling of Human Gut Microbiome Interactions and Perturbations

Background Intestinal microbiota plays an important role in the human health. It is involved in the digestion and protects the host against external pathogens. Examination of the intestinal microbiome interactions is required for understanding of the community influence on host health. Studies of the microbiome can provide insight on methods of improving health, including specific clinical procedures for individual microbial community composition modification and microbiota correction by colonizing with new bacterial species or dietary changes. Methodology/Principal Findings In this work we report an agent-based model of interactions between two bacterial species and between species and the gut. The model is based on reactions describing bacterial fermentation of polysaccharides to acetate and propionate and fermentation of acetate to butyrate. Antibiotic treatment was chosen as disturbance factor and used to investigate stability of the system. System recovery after antibiotic treatment was analyzed as dependence on quantity of feedback interactions inside the community, therapy duration and amount of antibiotics. Bacterial species are known to mutate and acquire resistance to the antibiotics. The ability to mutate was considered to be a stochastic process, under this suggestion ratio of sensitive to resistant bacteria was calculated during antibiotic therapy and recovery. Conclusion/Significance The model confirms a hypothesis of feedbacks mechanisms necessity for providing functionality and stability of the system after disturbance. High fraction of bacterial community was shown to mutate during antibiotic treatment, though sensitive strains could become dominating after recovery. The recovery of sensitive strains is explained by fitness cost of the resistance. The model demonstrates not only quantitative dynamics of bacterial species, but also gives an ability to observe the emergent spatial structure and its alteration, depending on various feedback mechanisms. Visual version of the model shows that spatial structure is a key factor, which helps bacteria to survive and to adapt to changed environmental conditions.

Assessment of k-mer spectrum applicability for metagenomic dissimilarity analysis

BackgroundA rapidly increasing flow of genomic data requires the development of efficient methods for obtaining its compact representation. Feature extraction facilitates classification, clustering and model analysis for testing and refining biological hypotheses. “Shotgun” metagenome is an analytically challenging type of genomic data - containing sequences of all genes from the totality of a complex microbial community. Recently, researchers started to analyze metagenomes using reference-free methods based on the analysis of oligonucleotides (k-mers) frequency spectrum previously applied to isolated genomes. However, little is known about their correlation with the existing approaches for metagenomic feature extraction, as well as the limits of applicability. Here we evaluated a metagenomic pairwise dissimilarity measure based on short k-mer spectrum using the example of human gut microbiota, a biomedically significant object of study.ResultsWe developed a method for calculating pairwise dissimilarity (beta-diversity) of “shotgun” metagenomes based on short k-mer spectra (5≤k≤11). The method was validated on simulated metagenomes and further applied to a large collection of human gut metagenomes from the populations of the world (n=281). The k-mer spectrum-based measure was found to behave similarly to one based on mapping to a reference gene catalog, but different from one using a genome catalog. This difference turned out to be associated with a significant presence of viral reads in a number of metagenomes. Simulations showed limited impact of bacterial genetic variability as well as sequencing errors on k-mer spectra. Specific differences between the datasets from individual populations were identified.ConclusionsOur approach allows rapid estimation of pairwise dissimilarity between metagenomes. Though we applied this technique to gut microbiota, it should be useful for arbitrary metagenomes, even metagenomes with novel microbiota. Dissimilarity measure based on k-mer spectrum provides a wider perspective in comparison with the ones based on the alignment against reference sequence sets. It helps not to miss possible outstanding features of metagenomic composition, particularly related to the presence of an unknown bacteria, virus or eukaryote, as well as to technical artifacts (sample contamination, reads of non-biological origin, etc.) at the early stages of bioinformatic analysis. Our method is complementary to reference-based approaches and can be easily integrated into metagenomic analysis pipelines.

Unusual Large-Scale Chromosomal Rearrangements in Mycobacterium tuberculosis Beijing B0/W148 Cluster Isolates

The Mycobacterium tuberculosis (MTB) Beijing family isolates are geographically widespread, and there are examples of Beijing isolates that are hypervirulent and associated with drug resistance. One-fourth of Beijing genotype isolates found in Russia belong to the B0/W148 group. The aim of the present study was to investigate features of these endemic strains on a genomic level. Four Russian clinical isolates of this group were sequenced, and the data obtained was compared with published sequences of various MTB strain genomes, including genome of strain W-148 of the same B0/W148 group. The comparison of the W-148 and H37Rv genomes revealed two independent inversions of large segments of the chromosome. The same inversions were found in one of the studied strains after deep sequencing using both the fragment and mate-paired libraries. Additionally, inversions were confirmed by RFLP hybridization analysis. The discovered rearrangements were verified by PCR in all four newly sequenced strains in the study and in four additional strains of the same Beijing B0/W148 group. The other 32 MTB strains from different phylogenetic lineages were tested and revealed no inversions. We suggest that the initial largest inversion changed the orientation of the three megabase (Mb) segment of the chromosome, and the second one occurred in the previously inverted region and partly restored the orientation of the 2.1 Mb inner segment of the region. This is another remarkable example of genomic rearrangements in the MTB in addition to the recently published of large-scale duplications. The described cases suggest that large-scale genomic rearrangements in the currently circulating MTB isolates may occur more frequently than previously considered, and we hope that further studies will help to determine the exact mechanism of such events.

RNA-Seq gene expression profiling of HepG2 cells: the influence of experimental factors and comparison with liver tissue.

BackgroundHuman hepatoma HepG2 cells are used as an in vitro model of the human liver. High-throughput transcriptomic sequencing is an advanced approach for assessing the functional state of a tissue or cell type. However, the influence of experimental factors, such as the sample preparation method and inter-laboratory variation, on the transcriptomic profile has not been evaluated.ResultsThe whole-transcriptome sequencing of HepG2 cells was performed using the SOLiD platform and validated using droplet digital PCR. The gene expression profile was compared to the results obtained with the same sequencing method in another laboratory and using another sample preparation method. We also compared the transcriptomic profile HepG2 cells with that of liver tissue. Comparison of the gene expression profiles between the HepG2 cell line and liver tissue revealed the highest variation, followed by HepG2 cells submitted to two different sample preparation protocols. The lowest variation was observed between HepG2 cells prepared by two different laboratories using the same protocol. The enrichment analysis of the genes that were differentially expressed between HepG2 cells and liver tissue mainly revealed the cancer-associated gene signature of HepG2 cells and the activation of the response to chemical stimuli in the liver tissue. The HepG2 transcriptome obtained with the SOLiD platform was highly correlated with the published transcriptome obtained with the Illumina and Helicos platforms, with moderate correspondence to microarrays.ConclusionsIn the present study, we assessed the influence of experimental factors on the HepG2 transcriptome and identified differences in gene expression between the HepG2 cell line and liver cells. These findings will facilitate robust experimental design in the fields of pharmacology and toxicology. Our results were supported by a comparative analysis with previous HepG2 gene expression studies.

Links of gut microbiota composition with alcohol dependence syndrome and alcoholic liver disease

BackgroundAlcohol abuse has deleterious effects on human health by disrupting the functions of many organs and systems. Gut microbiota has been implicated in the pathogenesis of alcohol-related liver diseases, with its composition manifesting expressed dysbiosis in patients suffering from alcoholic dependence. Due to its inherent plasticity, gut microbiota is an important target for prevention and treatment of these diseases. Identification of the impact of alcohol abuse with associated psychiatric symptoms on the gut community structure is confounded by the liver dysfunction. In order to differentiate the effects of these two factors, we conducted a comparative “shotgun” metagenomic survey of 99 patients with the alcohol dependence syndrome represented by two cohorts—with and without liver cirrhosis. The taxonomic and functional composition of the gut microbiota was subjected to a multifactor analysis including comparison with the external control group.ResultsAlcoholic dependence and liver cirrhosis were associated with profound shifts in gut community structures and metabolic potential across the patients. The specific effects on species-level community composition were remarkably different between cohorts with and without liver cirrhosis. In both cases, the commensal microbiota was found to be depleted. Alcoholic dependence was inversely associated with the levels of butyrate-producing species from the Clostridiales order, while the cirrhosis—with multiple members of the Bacteroidales order. The opportunist pathogens linked to alcoholic dependence included pro-inflammatory Enterobacteriaceae, while the hallmarks of cirrhosis included an increase of oral microbes in the gut and more frequent occurrence of abnormal community structures. Interestingly, each of the two factors was associated with the expressed enrichment in many Bifidobacterium and Lactobacillus—but the exact set of the species was different between alcoholic dependence and liver cirrhosis. At the level of functional potential, the patients showed different patterns of increase in functions related to alcohol metabolism and virulence factors, as well as pathways related to inflammation.ConclusionsMultiple shifts in the community structure and metabolic potential suggest strong negative influence of alcohol dependence and associated liver dysfunction on gut microbiota. The identified differences in patterns of impact between these two factors are important for planning of personalized treatment and prevention of these pathologies via microbiota modulation. Particularly, the expansion of Bifidobacterium and Lactobacillus suggests that probiotic interventions for patients with alcohol-related disorders using representatives of the same taxa should be considered with caution. Taxonomic and functional analysis shows an increased propensity of the gut microbiota to synthesis of the toxic acetaldehyde, suggesting higher risk of colorectal cancer and other pathologies in alcoholics.

An integrative analysis of reprogramming in human isogenic system identified a clone selection criterion

ABSTRACT The pluripotency of newly developed human induced pluripotent stem cells (iPSCs) is usually characterized by physiological parameters; i.e., by their ability to maintain the undifferentiated state and to differentiate into derivatives of the 3 germ layers. Nevertheless, a molecular comparison of physiologically normal iPSCs to the “gold standard” of pluripotency, embryonic stem cells (ESCs), often reveals a set of genes with different expression and/or methylation patterns in iPSCs and ESCs. To evaluate the contribution of the reprogramming process, parental cell type, and fortuity in the signature of human iPSCs, we developed a complete isogenic reprogramming system. We performed a genome-wide comparison of the transcriptome and the methylome of human isogenic ESCs, 3 types of ESC-derived somatic cells (fibroblasts, retinal pigment epithelium and neural cells), and 3 pairs of iPSC lines derived from these somatic cells. Our analysis revealed a high input of stochasticity in the iPSC signature that does not retain specific traces of the parental cell type and reprogramming process. We showed that 5 iPSC clones are sufficient to find with 95% confidence at least one iPSC clone indistinguishable from their hypothetical isogenic ESC line. Additionally, on the basis of a small set of genes that are characteristic of all iPSC lines and isogenic ESCs, we formulated an approach of “the best iPSC line” selection and confirmed it on an independent dataset.

Dissection of affinity captured LINE-1 macromolecular complexes

Long Interspersed Nuclear Element-1 (LINE-1, L1) is a mobile genetic element active in human genomes. L1-encoded ORF1 and ORF2 proteins bind L1 RNAs, forming ribonucleoproteins (RNPs). These RNPs interact with diverse host proteins, some repressive and others required for the L1 lifecycle. Using differential affinity purifications, quantitative mass spectrometry, and next generation RNA sequencing, we have characterized the proteins and nucleic acids associated with distinctive, enzymatically active L1 macromolecular complexes. Among them, we describe a cytoplasmic intermediate that we hypothesize to be the canonical ORF1p/ORF2p/L1-RNA-containing RNP, and we describe a nuclear population containing ORF2p, but lacking ORF1p, which likely contains host factors participating in target-primed reverse transcription.

Evolutionary pathway analysis and unified classification of East Asian lineage of Mycobacterium tuberculosis

Due to its rapid spread and association with the numerous outbreaks, the global spread of East Asian lineage of Mycobacterium tuberculosis strains presents a global concern. Although there were many attempts to describe its population structure, no consensus has been reached yet. To define unbiased classification that will facilitate future studies of this lineage, we analyzed the performance and congruence of eight different genotyping schemes based on phylogenetic analysis of 1,398 strains from 32 countries using whole-genome sequencing (WGS) data. We confirm that East Asian lineage comprises two major clades, designated proto-Beijing, which harbors unusual 43-signal spoligoprofile, and Beijing, with well-known spoligoprofile (deleted signals from 1 to 34). We show that different genotyping methods give high consistency results in description of ancient Beijing strains while the classification of modern Beijing strains is significantly divergent due to star-shaped phylogeny. Using WGS data we intersect different studies and for the first time provide balanced classification with well-defined major groups and their genetic markers. Our reconstructed phylogenetic tree can also be used for further analysis of epidemiologically important clusters and their ancestors as well as white spots of unclassified strains, which are prospective areas of research.