Phylogeny and Classification of Yersinia pestis Through the Lens of Strains From the Plague Foci of Commonwealth of Independent States

Кутырев, Владимир; Eroshenko, G. A.; Motin, Vladimir L.; Nosov, N. Yu.; Krasnov, Jaroslav M.; Куклева, Л. М.; Nikiforov, K. A.; Al’khova, Zhanna V.; Оглодин, Е. Г.; Guseva, Natalya V.

doi:10.3389/fmicb.2018.01106

Cited by 71 publications

(54 citation statements)

References 20 publications

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“…Early evolution: plague in prehistory. The time of divergence between Y. pestis and Y. pseudotuberculosis has been difficult to determine given the wide temporal interval produced by recent molecular dating attempts 92,130,[169][170][171][172][173][187][188][189][190][191][192][193][194][195][196][197][198][199]200 , are shown as grey circles within their geographical country or region of isolation, and the size of each circle is proportional to the number of strains sequenced from each location (number indicated when more than one genome is shown). The areas highlighted in brown are regions that contain active plague foci as determined by contemporary or historical data.…”

Section: Demographic Modelmentioning

confidence: 99%

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Ancient pathogen genomics as an emerging tool for infectious disease research

et al. 2019

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| Over the past decade, a genomics revolution, made possible through the development of high-throughput sequencing, has triggered considerable progress in the study of ancient DNA , enabling complete genomes of past organisms to be reconstructed. A newly established branch of this field, ancient pathogen genomics, affords an in-depth view of microbial evolution by providing a molecular fossil record for a number of human-associated pathogens. Recent accomplishments include the confident identification of causative agents from past pandemics, the discovery of microbial lineages that are now extinct, the extrapolation of past emergence events on a chronological scale and the characterization of long-term evolutionary history of microorganisms that remain relevant to public health today. In this Review , we discuss methodological advancements, persistent challenges and novel revelations gained through the study of ancient pathogen genomes.

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Section: Demographic Modelmentioning

confidence: 99%

“…4). More recent investigations have revealed previously uncharacterized genetic diversity in the Caucasus region and in the central Asian steppe that ought to be further explored [169][170][171][172] (Fig. 4).…”

Section: Molecular Insights From Three Historical Plague Pandemicsmentioning

confidence: 99%

Ancient pathogen genomics as an emerging tool for infectious disease research

et al. 2019

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“…для штаммов возбудителя чумы характерно генетическое разнообразие, которое связано с их распро-странением в различных ландшафтно-климатических зонах [7][8][9][10][11][12][13]. на территории псзспо, как и в других очагах прикаспия, циркулируют штаммы Y. pestis средневекового биовара, являющиеся высоко вирулентными и эпидемически значимыми.…”

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“…Штаммы средневекового биовара (филогенетическая ветвь 2.MED) получили распространение, по-видимому, позже -в XVIII-XX столетиях. наиболее древние из них обнаружены в центрально-кавказском высокогорном очаге российской Федерации и по генетической классификации филогенетических ветвей обозначаются как 2.MED0 [12,17]. Штаммы 2.MED2 и 2.MED3 обнаружены в очагах китая [11].…”

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Phylogenetic Analysis of Yersinia pestis Strains of Medieval Biovar, Isolated in Precaspian North-Western Steppe Plague Focus in the XX Century

Eroshenko

Попов

Альхова

et al. 2019

Problemy Osobo Opasnykh Infektsii

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Objective of the study – comparative phylogenetic analysis of Yersinia pestis strains, isolated in Precaspian North-Western steppe focus in 1924–1926, 1972, and 1986–1990 to understand the causes of focal reactivation during different time periods of the XX century.Materials and methods. The work included 30 strains of Yersinia pestis from Precaspian North-Western steppe natural focus and adjacent plague foci. Whole genome sequencing of eight Y. pestis strains from the former was carried out. Also whole-genome sequences of 16 strains from neighboring natural foci were used. Whole-genome sequencing of Y. pestis strains was conducted in Ion PGM system (Life technologies). SNPs search across the core genome was performed using software package Wombac 2.0. Tree diagram Maximum Likelihood, HKU85 model, was constructed to analyze phylogenetic relations.Results and discussion. It is established that in early XX century (1924–1926), strains of phylogenetic branches 2.MED4 and 2.MED1, belonging to medieval biovar, main subspecies, circulated on Ergenin Upland in the Precaspian North-Western steppe natural focus. Later on they became extinct in the territory. It is shown that the strains, isolated on Ergenin Upland in 1972, constituted a common subcluster on the dendrogram with the strains from low-mountain and piedmont plague foci of Caucasus and Transcaucasia, dated the same time period. It was inferred that epizootic manifestations on Ergenin upland in 1972, after a long recess since 1938, were caused by importation of Y. pestis strains from low-mountain natural plague foci of Caucasus and Transcaucasia. It was noted that expansion of Caucasian strains was of short-term character, and plague infected animals have not been found on Ergenin Upland since 1974 (including modern period). It is established that Y. pestis strains isolated in the eastern part of Precaspian North-Western steppe focus between 1986 and 1990, do not have close genetic relation to the strains that circulated on Ergenin Upland in 1924–1926 and 1972. It is determined that each epizootic period (1913–1938 and 1972–1973) in Precaspian North-Western steppe natural focus culminated in the elimination of the circulating Y. pestis strains and rehabilitation of the focal territory.

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“…ulegeica belong to a branch which is from a phylogenetic point of view more closely related to the ancestor Y. pseudotuberculosis than members from other branches of Y. pestis, including recent strains from Y. pestis ssp. pestis (Kutyrev et al, 2018;Demeure et al, 2019).…”

Section: Ms 1 Identification Analysis By Using the Silico Databasementioning

confidence: 99%

Identification of Microorganisms by Liquid Chromatography-Mass Spectrometry (LC-MS¹) and in silico Peptide Mass Data

Schneider

Blumenscheit

Doellinger

2019

Preprint

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1.ABSTRACTOver the past decade, modern methods of mass spectrometry (MS) have emerged that allow reliable, fast and cost-effective identification of pathogenic microorganisms. While MALDI-TOF MS has already revolutionized the way microorganisms are identified, recent years have witnessed also substantial progress in the development of liquid chromatography (LC)-MS based proteomics for microbiological applications. For example, LC-tandem mass spectrometry (LC-MS2) has been proposed for microbial characterization by means of multiple discriminative peptides that enable identification at the species, or sometimes at the strain level. However, such investigations can be very time-consuming, especially if the experimental LC-MS2 data are tested against sequence databases covering a broad panel of different microbiological taxa.In this proof of concept study, we present an alternative bottom-up proteomics method for microbial identification. The proposed approach involves efficient extraction of proteins from cultivated microbial cells, digestion by trypsin and LC-MS measurements. MS1 data are then extracted and systematically tested against an in silico library of peptide mass data compiled in house. The library has been computed from the UniProt Knowledgebase Swiss-Prot and TrEMBL databases and comprises more than 12,000 strain-specific in silico profiles, each containing tens of thousands of peptide mass entries. Identification analysis involves computation of score values derived from spectral distances between experimental and in silico peptide mass data and compilation of score ranking lists. The taxonomic positions of the microbial samples are then determined by using the best-matching database entries. The suggested method is computationally efficient – less than two minutes per sample - and has been successfully tested by a set of 19 different microbial pathogens. The approach is rapid, accurate and automatable and holds great potential for future microbiological applications.

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Phylogeny and Classification of Yersinia pestis Through the Lens of Strains From the Plague Foci of Commonwealth of Independent States

Cited by 71 publications

References 20 publications

Ancient pathogen genomics as an emerging tool for infectious disease research

Ancient pathogen genomics as an emerging tool for infectious disease research

Phylogenetic Analysis of Yersinia pestis Strains of Medieval Biovar, Isolated in Precaspian North-Western Steppe Plague Focus in the XX Century

Identification of Microorganisms by Liquid Chromatography-Mass Spectrometry (LC-MS¹) and in silico Peptide Mass Data

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Phylogeny and Classification of Yersinia pestis Through the Lens of Strains From the Plague Foci of Commonwealth of Independent States

Cited by 71 publications

References 20 publications

Ancient pathogen genomics as an emerging tool for infectious disease research

Ancient pathogen genomics as an emerging tool for infectious disease research

Phylogenetic Analysis of Yersinia pestis Strains of Medieval Biovar, Isolated in Precaspian North-Western Steppe Plague Focus in the XX Century

Identification of Microorganisms by Liquid Chromatography-Mass Spectrometry (LC-MS1) and in silico Peptide Mass Data

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Product

Resources

About

Identification of Microorganisms by Liquid Chromatography-Mass Spectrometry (LC-MS¹) and in silico Peptide Mass Data