Timofey A. Skvortsov

Education

PeriodCountry, cityEducation institutionAdditional info
2002–2007 Russia, Moscow Lomonosov Moscow State University Graduated summa cum laude
2007–2010 Russia, Moscow M.M. Shemyakin and Yu.A. Ovchinnikov Institute of bioorganic chemistry of the Russian Academy of Sciences

Scientific interests

Research interests

RNA types, structure and functions

I have a keen interest in RNA biology in general and non-coding RNAs in particular. The structural and functional diversity of RNAs is very high, and there still are many unanswered questions in the field of RNA biology. The most obvious function of RNA is to facilitate the conversion of DNA information into polypeptides; but RNA can also store genetic information as well as act as an enzyme. However, only a small percentage of the DNA in eukaryotic genomes encodes proteins, though the vast majority of eukaryotic genomes are transcribed into RNA. A significant fraction of non-coding RNAs have no identified function and thus these RNA molecules were dubbed “dark matter in the genome”. And while the question whether this “RNA dark matter” has functional relevance, or is a product of protein-coding genes transcription, or even just represents transcriptional noise is open, there is no doubt that a significant number of non-coding RNAs participate in regulatory processes.

Transcriptome analysis methods

All RNAs in a cell are involved in an ultra-complex network of interactions with each other, DNA, proteins, and other molecules, and constitute a transcriptome of a cell. The transcriptome is highly dynamic and is constantly changing in response to endogenous and exogenous stimuli. Thus, transcriptome studies are cornerstone of functional genomics and provide insight into which genes and non-coding RNAs are expressed in specific circumstances. Nevertheles, transcriptome studies were hampered until recently due to the lack of methods for quantitative and qualitative analysis of RNA pool. DNA microarrays and next-generation sequencing have made it possible to accurately measure compositions of transcriptomes of many eukaryotic and prokaryotic species. Next-generation sequencing produces huge amounts of sequencing data, but gives no information on secondary structures of sequences. Since most non-coding RNAs are characterized by a specific secondary and tertiary structure, the structure of RNA must be known before the relationship between its structure and function can be determined. Prediction of RNA structure as well as analysis of next-generation sequencing data requires solid knowledge of existing bioinformatics software tools and programming languages and good computational skills, so I started to study bioinformatics during my research on mycobacterial transcriptomes and eventually developed a strong interest in this area.

Bacterial transcriptomics

Bacterial transcriptomics is a very interesting field of research, and working with bacteria has its own advantages, disadvantages and peculiarities. Bacteria grow fast, large amounts of RNA can be easily isolated from their cultures, but bacterial RNAs are not polyadenylated, and thus cannot be amplified using oligo-dT primers. Rapid advancements in sequencing technology have shifted the paradigm that considers bacterial transcriptomes as rather simple in comparison with the far more complex eukaryotic ones. It was shown recently that bacterial cells utilize most, If not all, transcriptional regulatory mechanisms of their eukaryotic counterparts, i.e. alternative transcription, RNA processing and splicing, regulation of mRNA stability by polyadenylation and small RNAs, to name a few. This unraveling of a whole new level of bacterial complexity is of the highest importance, not only for fundamental science, but also for biotechnology and medicine, and thus my current research is focused on investigating the role of small RNAs in mycobacterial infections and their potential as therapeutic targets.

Pathogenomics and bacterial physiology

Genome-wide studies of gene expression provide a window into how bacterium’s genetic makeup enables it to function and adapt to its environment. In case of pathogenic bacteria such studies are invaluable for identifying the virulence factors that allow a pathogen to survive a host's defence mechanism. Nevertheless, host-pathogen interactions are too complex to be deciphered by transcriptome analyses alone. For example, it was shown that genomic differences between two strains of the same bacterial species may be very significant, leading to different transcriptional outcomes in the same environment. This influences the metabolic profiles of bacterial cells and might contribute to variations in pathogenicity. This is the reason of my vivid interest in various aspects of bacterial structural and comparative genomics as well as in physiology and biochemistry of bacteria.

Unusual nucleic acid structures

One of my oldest interests, dating back to high school, is in unusual DNA structures and conformations. I have never had a chance to participate in any research projects in this area, but since I find such noncanonical structures intriguing and firmly believe they must have interesting and important biological roles to play, I read a lot of literature on the subject.

Skills

Biological

Isolation and purification of DNA and RNA from bacterial and eukaryotic cells; PCR; qPCR; RT-PCR; RACE; qPCR; PCR site-directed mutagenesis; restriction and cloning; enzymatic modification of nucleic acids; working with  bacterial cell cultures; preparation of DNA libraries (cDNA and genomic); agarose and polyacrylamide gel electrophoresis (both native and denaturating); Southern and Northern blotting methods; SAGE; nucleic acid sequence analysis; analysis of Illumina GA IIx and Roche GS FLX next-generation sequencing systems data; database mining.

Computational

GeneRunner, Vector NTI; Gel-Pro Analyzer; Chromas; GraphPad Prism; programming languages: Perl (beginner), R (beginner).

Main scientific results

10/2011-present Research Fellow
  I am currently working on the structural and functional characterization of several Mycobacterium tuberculosis proteins identified in earlier transcriptomic studies as potential therapeutical targets; I am also conducting a study of small RNAs in Mycobacterium avium
2007-2011 Junior Research Fellow
  Developed a new method for transcriptional profiling of intracellular pathogens in vivo based on DNA-DNA hybridization and RNA-Seq; applied this method for mapping and quantifying transcriptomes of Mycobacterium tuberculosis and Mycobacterium avium during infection in a mouse model; identified a set of M. tuberculosis genes that invariably demonstrated increased expression in unfavorable for pathogen conditions.
2006-2007 Undergraduate student
  Evaluated gene expression differences between two Mycobacterium tuberculosis strains; optimized real-time qPCR data analysis methods.
2005-2006 Undergraduate student
  Conducted a study of Mycobacterium tuberculosis genomic DNA methylation using methyl-sensitive restriction analysis, affinity chromatography, bisulfite sequencing and methylated DNA immunoprecipitation (MeDIP).

 

Selected publications

  1. Ignatov D.V., Salina E.G., Fursov M.V., Skvortsov T.A., Azhikina T.L., Kaprelyants A.S. (2015). Dormant non-culturable Mycobacterium tuberculosis retains stable low-abundant mRNA. BMC Genomics 16 (1), 954 [+]

    Dormant Mycobacterium tuberculosis bacilli are believed to play an important role in latent tuberculosis infection. Previously, we have demonstrated that cultivation of M. tuberculosis in K(+)-deficient medium resulted in generation of dormant cells. These bacilli were non-culturable on solid media (a key feature of dormant M. tuberculosis in vivo) and characterized by low metabolism and tolerance to anti-tuberculosis drugs. The dormant bacteria demonstrated a high potential to reactivation after K(+) reintroduction even after prolonged persistence under rifampicin. In this work, we studied the transcriptome and stability of transcripts in persisting dormant bacilli under arrest of mRNA de novo synthesis.

    ID:1340
  2. Bychenko O.S., Sukhanova L.V., Azhikina T.L., Skvortsov T.A., Belomestnykh T.V., Sverdlov E.D. (2014). Differences in brain transcriptomes of closely related baikal coregonid species. Biomed Res Int 2014, 857329 [+]

    The aim of this work was to get deeper insight into genetic factors involved in the adaptive divergence of closely related species, specifically two representatives of Baikal coregonids-Baikal whitefish (Coregonus baicalensis Dybowski) and Baikal omul (Coregonus migratorius Georgi)-that diverged from a common ancestor as recently as 10-20 thousand years ago. Using the Serial Analysis of Gene Expression method, we obtained libraries of short representative cDNA sequences (tags) from the brains of Baikal whitefish and omul. A comparative analysis of the libraries revealed quantitative differences among ~4% tags of the fishes under study. Based on the similarity of these tags with cDNA of known organisms, we identified candidate genes taking part in adaptive divergence. The most important candidate genes related to the adaptation of Baikal whitefish and Baikal omul, identified in this work, belong to the genes of cell metabolism, nervous and immune systems, protein synthesis, and regulatory genes as well as to DTSsa4 Tc1-like transposons which are widespread among fishes.

    ID:1014
  3. Skvortsov T.A., Ignatov D.V., Majorov K.B., Apt A.S., Azhikina T.L. (2013). Mycobacterium tuberculosis Transcriptome Profiling in Mice with Genetically Different Susceptibility to Tuberculosis. Acta Naturae 5 (2), 62–9 [+]

    Whole transcriptome profiling is now almost routinely used in various fields of biology, including microbiology. In vivo transcriptome studies usually provide relevant information about the biological processes in the organism and thus are indispensable for the formulation of hypotheses, testing, and correcting. In this study, we describe the results of genome-wide transcriptional profiling of the major human bacterial pathogen M. tuberculosis during its persistence in lungs. Two mouse strains differing in their susceptibility to tuberculosis were used for experimental infection with M. tuberculosis. Mycobacterial transcriptomes obtained from the infected tissues of the mice at two different time points were analyzed by deep sequencing and compared. It was hypothesized that the changes in the M. tuberculosis transcriptome may attest to the activation of the metabolism of lipids and amino acids, transition to anaerobic respiration, and increased expression of the factors modulating the immune response. A total of 209 genes were determined whose expression increased with disease progression in both host strains (commonly upregulated genes, CUG). Among them, the genes related to the functional categories of lipid metabolism, cell wall, and cell processes are of great interest. It was assumed that the products of these genes are involved in M. tuberculosis adaptation to the host immune system defense, thus being potential targets for drug development.

    ID:867
  4. Ignatov D., Malakho S., Majorov K., Skvortsov T., Apt A., Azhikina T. (2013). RNA-Seq Analysis of Mycobacterium avium Non-Coding Transcriptome. PLoS ONE 8 (9), e74209 [+]

    Deep sequencing was implemented to study the transcriptional landscape of Mycobacterium avium. High-resolution transcriptome analysis identified the transcription start points for 652 genes. One third of these genes represented leaderless transcripts, whereas the rest of the transcripts had 5' UTRs with the mean length of 83 nt. In addition, the 5' UTRs of 6 genes contained SAM-IV and Ykok types of riboswitches. 87 antisense RNAs and 10 intergenic small RNAs were mapped. 6 intergenic small RNAs, including 4.5S RNA and rnpB, were transcribed at extremely high levels. Although several intergenic sRNAs are conserved in M. avium and M. tuberculosis, both of these species have unique intergenic sRNAs. Moreover, we demonstrated that even conserved small RNAs are regulated differently in these species. Different sets of intergenic sRNAs may underlie differences in physiology between conditionally pathogenic M. avium and highly specialized pathogen M. tuberculosis.

    ID:866
  5. Azhikina T., Kozlova A., Skvortsov T., Sverdlov E. (2011). Heterogeneity and degree of TIMP4, GATA4, SOX18, and EGFL7 gene promoter methylation in non-small cell lung cancer and surrounding tissues. Cancer Genet 204 (9), 492–500 [+]

    We used methylation-sensitive high resolution melting analysis to assess methylation of CpG islands within the promoters of the TIMP4, GATA4, SOX18, and EGFL7 genes in samples of non-small cell lung cancer and surrounding apparently normal tissue and noncancerous lung tissues. We found that the promoter methylation was heterogeneous in both tumor and surrounding normal tissue. This is in contrast to healthy lung tissue, where the promoters were normally either non- or hypomethylated, and the heterogeneity of methylation was low. An increased heterogeneity of methylation in the normal tissues surrounding the tumor may suggest an early start of epigenetic processes preceding genetic and morphologic changes and can be used as a biomarker of early cancerization events. This analysis is an easy and sensitive tool for studying epigenetic heterogeneity and could be used in clinical practice.

    ID:704
  6. Ignatov D.V., Skvortsov T.A., Majorov K.B., Apt A.S., Azhikina T.L. (2010). Adaptive Changes in Mycobacterium avium Gene Expression Profile Following Infection of Genetically Susceptible and Resistant Mice. Acta Naturae 2 (3), 78–83 [+]

    We performed a comparative analysis ofMycobacterium aviumtranscriptomes (strain 724R) in infected mice of two different strains- resistant and susceptible to infection. Sets of mycobacterial genes transcribed in lung tissue were defined, and differentially transcribed genes were revealed. Our results indicate thatM. aviumgenes coding for enzymes of the Krebs cycle, oxidative phosphorylation, NO reduction, fatty acid biosynthesis, replication, translation, and genome modification are expressed at high levels in the lungs of genetically susceptible mice. The expression of genes responsible for cell wall properties, anaerobic nitrate respiration, fatty acid degradation, synthesis of polycyclic fatty acid derivatives, and biosynthesis of mycobactin and other polyketides is increased in the resistant mice. In the resistant host environment,Mycobacterium aviumapparently transitions to a latent state caused by the deficiency in divalent cations and characterised by anaerobic respiration, degradation of fatty acids, and modification of cell wall properties.

    ID:869
  7. Azhikina T., Skvortsov T., Radaeva T., Mardanov A., Ravin N., Apt A., Sverdlov E. (2010). A new technique for obtaining whole pathogen transcriptomes from infected host tissues. BioTechniques 48 (2), 139–44 [+]

    We propose a novel experimental approach based on coincidence cloning for analyzing sequences of bacterial intracellular pathogens specifically transcribed in affected tissues. Co-denaturation and co-renaturation of excess bacterial genomic DNA with the cDNA prepared on total RNA of the infected tissue allows one to select the bacterial fraction of the cDNA sample. We used this technique for preparing and characterizing the Mycobacterium tuberculosis cDNA pool, representing the transcriptome of infected mouse lungs in the chronic phase of infection. A cDNA pool enriched in fragments of mycobacterial cDNA was analyzed by the high-throughput 454 sequencing procedure. We demonstrated that its composition corresponded to what can be expected in the chronic phase of infection and, after the adaptation of M. tuberculosis to the host immune system, was characterized by an active lipid metabolism and switched from aerobic to anaerobic respiration. The technique is universal and requires no prior knowledge of the pathogen genome sequence. Pools of transcribed sequences obtained by this technique retain the main characteristics of the genome-wide gene transcription pattern within infected tissue, and can be used for in vivo analysis of gene expression of a wide spectrum of infection agents, such as viruses, bacteria, and protista.

    ID:701
  8. Skvortsov T.A., Azhikina T.L. (2009). [Transcriptome analysis of bacterial pathogens in vivo: problems and solutions]. Bioorg. Khim. 36 (5), 596–606 [+]

    This review considers modern strategy of whole-transcriptome investigation of intracellular pathogens in vivo. The methods of preliminary enrichment for bacterial RNA are discussed in details, including hybridization-based approaches and the peculiarities of cDNA synthesis in bacteria; methods of synthesizing cDNA from the view of features of prokaryotic RNAs and methods of bacterial cDNA analysis are also described, including high-throughput RNA-seq. The discussed methods are exemplified by analysis of Mycobacterium tuberculosis in different infection models: in cell lines, infected animal tissues and organs, and human surgical samples of lung. The advantages and limitations of different methodological approaches are discussed.

    ID:702
  9. Bychenko O.S., Sukhanova L.V., Ukolova S.S., Skvortsov T.A., Potapov V.K., Azhikina T.L., Sverdlov E.D. (2009). [Genome similarity of Baikal omul and sig]. Bioorg. Khim. 35 (1), 95–102 [+]

    Two members of the Baikal sig family, a lake sig (Coregonus lavaretus baicalensis Dybovsky) and omul (C. autumnalis migratorius Georgi), are close relatives that diverged from the same ancestor 10-20 thousand years ago. In this work, we studied genomic polymorphism of these two fish species. The method of subtraction hybridization (SH) did not reveal the presence of extended sequences in the sig genome and their absence in the omul genome. All the fragments found by SH corresponded to polymorphous noncoding genome regions varying in mononucleotide substitutions and short deletions. Many of them are mapped close to genes of the immune system and have regions identical to the Tc-1-like transposons abundant among fish, whose transcription activity may affect the expression of adjacent genes. Thus, we showed for the first time that genetic differences between Baikal sig family members are extremely small and cannot be revealed by the SH method. This is another endorsement of the hypothesis on the close relationship between Baikal sig and omul and their evolutionarily recent divergence from a common ancestor.

    ID:703
  10. Ignatov D.V., Mefodeva L.G., Maĭorov K.B., Skvortsov T.A., Azhikina T.L. (2009). [Identified small RNAs of Mycobacterium avium]. Bioorg. Khim. 38 (4), 509–12 [+]

    Posttranscriptional regulation of gene expression by small RNAs was shown for multiple pathogenic microorganisms and plays an important role in virulence. 4 putative sRNA genes located in intergenic loci were identified: MAV_0380-0381 (4.5S RNA), MAV_1034-1035 (trans-encoded sRNA), MAV_1415-1416 (antisense or trans-encoded sRNA) and MAV_1531-1532 (processed 5' UTR of 16S rRNA gene). The revealed sRNAs represent the first small noncoding RNAs identified in M. avium.

    ID:870
  11. Skvortsov T.A., Azhikina T.L. (2009). [Adaptive changes of Mycobacterium tuberculosis gene expression during the infectious process]. Bioorg. Khim. 38 (4), 391–405 [+]

    Mycobacterium tuberculosis causes an infection in humans with clinical manifestations varying from asymptomatic carriage of bacteria to rapidly progressing tuberculosis. Infection outcomes depend on complex and still not fully understood interactions between the pathogenic bacteria and their host organism. Gene expression changes in response to host defense mechanisms are needed for M. tuberculosis survival and functioning. This review focuses on the analysis of dynamic changes in the M. tuberculosis transcriptome taking place during infection processes in host tissues. Presently available data on mycobacterial transcriptome changes obtained from different infection models are discussed. A major part of this review is devoted to the description of biochemical changes occurring in M. tuberculosis infection process, from the primary through latent infection to pathogen reactivation. At each stage of the infection, gene expression changes and induced bacterial metabolic variations are discussed.

    ID:871