Elizaveta Starikova

Elizaveta Starikova


Research Focus & Metrics

Academic Career Length

12Years (2015-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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20 April 2020 in Bioinformatics
Verified
Journal Article
Closed access
ESElizaveta Starikova
Elizaveta Starikova
PTPolina Tikhonova
Polina Tikhonova
NPNikita A Prianichnikov
Nikita A Prianichnikov
CRChris M Rands
Chris M Rands
EZEvgeny M Zdobnov
Evgeny M Zdobnov
VGVadim M Govorun
Vadim M Govorun
Summary: Phigaro is a standalone command-line application that is able to detect prophage regions taking raw genome and metagenome assemblies as an input. It also produces dynamic annotated ‘prophage genome maps’ and marks possible transposon insertion spots inside prophages. It is applicable for mining prophage regions from large metagenomic datasets. Availability and implementation: Source code for Phigaro is freely available for download at https://github.com/bobeobibo/phigaro along with test data. The code is written in Python. Supplementary information: Supplementary data are available at Bioinformatics online.

25 January 2015 in Euphytica
Verified
Journal Article
Closed access
PDF file
ESElena A. Salina
Elena A. Salina
IAIrina G. Adonina
Irina G. Adonina
Ekaterina D. BadaevaEkaterina D. Badaeva
Ekaterina D. Badaeva
PKPavel Yu. Kroupin
Pavel Yu. Kroupin
ASAnatoliy I. Stasyuk
Anatoliy I. Stasyuk
GKGennady Karlov
Gennady Karlov

27 August 2019 in Frontiers in Microbiology
Verified
Journal Article
Open access
PDF file
EOEvgenii I. Olekhnovich
Evgenii I. Olekhnovich
AMAlexander I. Manolov
Alexander I. Manolov
ASAndrei Samoilov
Andrei Samoilov
NPNikita A. Prianichnikov
Nikita A. Prianichnikov
MMMaja V. Malakhova
Maja V. Malakhova
EIElena N. Ilina
Elena N. Ilina
The human gut microbiome plays an important role both in health and disease. Use of antibiotics can alter gut microbiota composition, which can lead to various deleterious events. Here we report a whole genome sequencing metagenomic/genomic study of the intestinal microbiota changes caused by Helicobacter pylori (HP) eradication therapy. Using approaches for metagenomic data analysis we revealed a statistically significant decrease in alpha-diversity and relative abundance of Bifidobacterium adolescentis due to HP eradication therapy, while the relative abundance of Enterococcus faecium increased. We have detected changes in general metagenome resistome profiles as well: after HP eradication therapy, the ermB, CFX group, and tetQ genes were overrepresented, while tetO and tetW genes were underrepresented. We have confirmed these results with genome-resolved metagenomic approaches. MAG (metagenome-assembled genomes) abundance profiles have changed dramatically after HP eradication therapy. Focusing on ermB gene conferring resistance to macrolides, which were included in the HP eradication therapy scheme, we have shown a connection between antibiotic resistance genes (ARGs) and some overrepresented MAGs. Moreover, some E. faecium strains isolated from stool samples obtained after HP eradication have manifested greater antibiotic resistance in vitro in comparison to other isolates, as well as the higher number of ARGs conferring resistance to macrolides and tetracyclines.

1 June 2018 in Environmental Microbiology
Verified
Journal Article
Open access
PDF file
CRChris M. Rands
Chris M. Rands
ESElizaveta Starikova
Elizaveta Starikova
HBHarald Brüssow
Harald Brüssow
EKEvgenia V. Kriventseva
Evgenia V. Kriventseva
VGVadim M. Govorun
Vadim M. Govorun
EZEvgeny Zdobnov
Evgeny Zdobnov
Summary: Antibiotic resistance is increasing among pathogens, and the human microbiome contains a reservoir of antibiotic resistance genes. Acidaminococcus intestini is the first Negativicute bacterium (Gram‐negative Firmicute) shown to be resistant to beta‐lactam antibiotics. Resistance is conferred by the aci1 gene, but its evolutionary history and prevalence remain obscure. We discovered that ACI‐1 proteins are phylogenetically distinct from beta‐lactamases of Gram‐positive Firmicutes and that aci1 occurs in bacteria scattered across the Negativicute clade, suggesting lateral gene transfer. In the reference A. intestini RyC‐MR95 genome, we found transposons residing within a tailed prophage context are likely vehicles for aci1 's mobility. We found aci1 in 56 (4.4%) of 1,267 human gut metagenomes, mostly hosted within A. intestini , and, where could be determined, mostly within a consistent mobile element constellation. These samples are from Europe, China and the USA, showing that aci1 is distributed globally. We found that for most Negativicute assemblies with aci1 , the prophage observed in A. instestini is absent, but in all cases aci1 is flanked by varying transposons. The chimeric mobile elements we identify here likely have a complex evolutionary history and potentially provide multiple complementary mechanisms for antibiotic resistance gene transfer both within and between cells.

22 January 2024 in BMC Genomic Data
Verified
Journal Article
Open access
PDF file
ALAndrey K Larin
Andrey K Larin
KKKsenia Klimina
Ksenia Klimina
VVVladimir Alexandrovich Veselovsky
Vladimir Alexandrovich Veselovsky
EOEvgenii I. Olekhnovich
Evgenii I. Olekhnovich
MMMaxim Morozov
Maxim Morozov
EIElena Ilina
Elena Ilina
Background: Recent advancements in next-generation sequencing (NGS) technology have ushered in significant improvements in sequencing speed and data throughput, thereby enabling the simultaneous analysis of a greater number of samples within a single sequencing run. This technology has proven particularly valuable in the context of microbial community profiling, offering a powerful tool for characterizing the microbial composition at the species level within a given sample. This profiling process typically involves the sequencing of 16S ribosomal RNA (rRNA) gene fragments. By scaling up the analysis to accommodate a substantial number of samples, sometimes as many as 2,000, it becomes possible to achieve cost-efficiency and minimize the introduction of potential batch effects. Our study was designed with the primary objective of devising an approach capable of facilitating the comprehensive analysis of 1,711 samples sourced from diverse origins, including oropharyngeal swabs, mouth cavity swabs, dental swabs, and human fecal samples. This analysis was based on data obtained from 16S rRNA metagenomic sequencing conducted on the Illumina MiSeq and HiSeq sequencing platforms. Results: We have designed a custom set of 10-base pair indices specifically tailored for the preparation of libraries from amplicons derived from the V3-V4 region of the 16S rRNA gene. These indices are instrumental in the analysis of the microbial composition in clinical samples through sequencing on the Illumina MiSeq and HiSeq platforms. The utilization of our custom index set enables the consolidation of a significant number of libraries, enabling the efficient sequencing of these libraries in a single run. Conclusions: The unique array of 10-base pair indices that we have developed, in conjunction with our sequencing methodology, will prove highly valuable to laboratories engaged in sequencing on Illumina platforms or utilizing Illumina-compatible kits.

30 July 2020 in Microorganisms
Verified
Journal Article
Open access
PDF file
DKDaria Kashtanova
Daria Kashtanova
NKNatalia Klimenko
Natalia Klimenko
ISIrina D. Strazhesko
Irina D. Strazhesko
ESElizaveta Starikova
Elizaveta Starikova
OGOksana E. Glushchenko
Oksana E. Glushchenko
OTOlga N. Tkacheva
Olga N. Tkacheva
The aim was to assess the gut microbiota of long-livers from Moscow. This study included two groups of patients who signed their consent to participate. The group of long-livers (LL) included 20 participants aged 97–100 years (4 men and 16 women). The second group included 22 participants aged 60–76 years (6 men) without clinical manifestations of chronic diseases (healthy elderly). Gut microbiota was studied by 16S rRNA sequencing. Long-livers underwent a complex geriatric assessment as well as expanded blood biochemistry. Gut microbiota composition in the cohorts was also compared with microbiome in long-livers from Japan and Italy. Russian long-livers’ microbiome contained more beneficial bacteria than healthy elderly including Ruminococcaceae, Christensenellaceae, Lactobacillaceae families. Conditional pathogens like Veillonellaceae, Mogibacteriaceae, Alcaligenaceae, Peptococcaceae, Peptostreptococcaceae were more abundant in the healthy elderly. Compared with Italian and Japanese microbiome LL, the Russian LL appeared to be more similar to the Italian cohort. Bifidobacterium/Coprococcus and Faecalibacterium/Coprococcus balances were associated with femoral and carotid intima–media thickness, respectively. Bifidobacterium/Coriobacteriaceae balance was assessed with the folic acid level and Faecalibacterium/Coriobacteriaceae_u the with Mini Nutritional Assessment score. Long-livers’ microbiome appeared to be unexpectedly balanced. The high representation of beneficial bacteria in long-livers may prevent them from low-grade inflammation and thus protect them from the development of atherosclerosis and other aging-associated conditions.