Data in Brief 11 (2017) 98–102
Contents lists available at ScienceDirect
Data in Brief journal homepage: www.elsevier.com/locate/dib
Data Article
Data on gut metagenomes of the patients with alcoholic dependence syndrome and alcoholic liver cirrhosis Alexander V. Tyakht a,n, Veronika B. Dubinkina a, Vera Y. Odintsova b, Konstantin S. Yarygin a,b, Boris A. Kovarsky b, Alexander V. Pavlenko a,b, Dmitry S. Ischenko a,b, Anna S. Popenko b, Dmitry G. Alexeev a,b, Anastasiya Y. Taraskina c, Regina F. Nasyrova c, Evgeny M. Krupitski c, Nino V. Shalikiani d, Igor G. Bakulin d, Petr L. Shcherbakov d, Lyubov O. Skorodumova b, Andrei K. Larin b, Elena S. Kostryukova a,b, Rustam A. Abdulkhakov e, Sayar R. Abdulkhakov e,f, Sergey Y. Malanin f, Ruzilya K. Ismagilova f, Tatiana V. Grigoryeva f, Elena N. Ilina b, Vadim M. Govorun a a Moscow Institute of Physics and Technology, Institutskiy per. 9, Dolgoprudny, Moscow Region 141700, Russia b Federal Research and Clinical Centre of Physical-Chemical Medicine, Malaya Pirogovskaya 1a, Moscow 119435, Russia c Saint-Petersburg Bekhterev Psychoneurological Research Institute, Bekhtereva 3, Saint-Petersburg 192019, Russia d Moscow Clinical Scientific Center, Shosse Entuziastov 86, Moscow 111123, Russia e Kazan State Medical University, Butlerova 49, Kazan 420012, Russia f Kazan Federal University, Kremlyovskaya 18, Kazan 420008, Russia
a r t i c l e i n f o
abstract
Article history: Received 8 December 2016 Received in revised form 28 December 2016 Accepted 11 January 2017 Available online 17 January 2017
Alcoholism is associated with significant changes in gut microbiota composition. Metagenomic sequencing allows to assess the altered abundance levels of bacterial taxa and genes in a cultureindependent way. We collected 99 stool samples from the patients with alcoholic dependence syndrome (n ¼72) and alcoholic liver cirrhosis (n ¼ 27). Each of the samples was surveyed
n
Corresponding author. E-mail address: [email protected] (A.V. Tyakht).
http://dx.doi.org/10.1016/j.dib.2017.01.008 2352-3409/& 2017 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
A.V. Tyakht et al. / Data in Brief 11 (2017) 98–102 Keywords: Gut microbiota Metagenome Alcoholism Alcohol dependence syndrome Alcoholic liver cirrhosis Dysbiosis “Shotgun” metagenomics
99
using “shotgun” (whole-genome) sequencing on SOLiD platform. The reads are deposited in the ENA (project ID: PRJEB18041). & 2017 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Specifications Table Subject area More specific subject area Type of data How data was acquired Data format Experimental factors Experimental features Data source location Data accessibility
Biology Bacterial metagenomics Text files: sequences DNA sequencing using SOLiD 5500xl platform Raw DNA extracted from stool samples Barcoded fragment (non-paired) read libraries were created from 5 μg of total DNA for each of the samples. The sequencing was performed using the SOLiD 5500xl platform according to the recommendations of the manufacturer. Kazan, Russian Federation; Moscow, Russian Federation; Saint-Petersburg, Russian Federation The datasets are deposited in the ENA (project ID: PRJEB18041, URL: http:// www.ebi.ac.uk/ena/data/view/PRJEB18041)
Value of the data
The data describes the human gut microbiota composition in two cohorts of the patients with
alcoholism manifesting distinct degrees of liver dysfunctions: patients with alcoholic dependence syndrome (ADS; alcoholics without advanced liver disease) and patients with alcoholic liver cirrhosis (ALC; alcoholics with advanced liver disease). The data can be used for identifying the changes of gut microbiota associated with alcoholism as well as with the associated liver damage at the levels of community structure (taxonomic composition) and gene potential (functional composition). The data can be used for validating the universality of potential biomarkers of alcoholismassociated dysbiosis via the meta-analysis together with the published gut metagenomes of the world populations. The data can be used in phylogeographic analyses of human microbiota to assess the genomic variations of the gut microbial species typical for Russian population as compared with the other world populations.
1. Data The data represent 99 “shotgun” metagenomes of stool samples collected from the patients with ADS and ALC in 3 clinical centers from 3 Russian cities - Moscow, Kazan and Saint-Petersburg. The datasets include 25.8 716.1 mln of 50 bp reads per sample (mean7 s.d., 127.5 Gbp in total). The description of the data is listed in Table 1.
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A.V. Tyakht et al. / Data in Brief 11 (2017) 98–102
Table 1 Information about the datasets, samples and subjects. Abbreviations: ADS - alcohol dependence syndrome, ALC - alcoholic liver cirrhosis, BMI – body-mass index, ENA – European Nucleotide Archive, NA – not available. Sample ID
ENA sample accession
ENA experiment ID
Group
Collection site
Age, years
Gender
BMI
ADS_1 ADS_10 ADS_11 ADS_12 ADS_13 ADS_14 ADS_15 ADS_16 ADS_17 ADS_18 ADS_19 ADS_2 ADS_20 ADS_21 ADS_22 ADS_23 ADS_24 ADS_25 ADS_26 ADS_27 ADS_28 ADS_29 ADS_3 ADS_30 ADS_31 ADS_32 ADS_33 ADS_34 ADS_35 ADS_36 ADS_37 ADS_38 ADS_39 ADS_4 ADS_40 ADS_41 ADS_42 ADS_43 ADS_44 ADS_45 ADS_46 ADS_47 ADS_48 ADS_49 ADS_5 ADS_50 ADS_51 ADS_52 ADS_53 ADS_54 ADS_55 ADS_56 ADS_57 ADS_58 ADS_59 ADS_6 ADS_60 ADS_61 ADS_62
ERS1454656 ERS1454657 ERS1454658 ERS1454659 ERS1454660 ERS1454661 ERS1454662 ERS1454663 ERS1454664 ERS1454665 ERS1454666 ERS1454667 ERS1454668 ERS1454669 ERS1454670 ERS1454671 ERS1454672 ERS1454673 ERS1454674 ERS1454675 ERS1454676 ERS1454677 ERS1454678 ERS1454679 ERS1454680 ERS1454681 ERS1454682 ERS1454683 ERS1454684 ERS1454685 ERS1454686 ERS1454687 ERS1454688 ERS1454689 ERS1454690 ERS1454691 ERS1454692 ERS1454693 ERS1454694 ERS1454695 ERS1454696 ERS1454697 ERS1454698 ERS1454699 ERS1454700 ERS1454701 ERS1454702 ERS1454703 ERS1454704 ERS1454705 ERS1454706 ERS1454707 ERS1454708 ERS1454709 ERS1454710 ERS1454711 ERS1454712 ERS1454713 ERS1454714
ERR1748966 ERR1748967 ERR1748968 ERR1748969 ERR1748970 ERR1748971 ERR1748972 ERR1748973 ERR1748974 ERR1748975 ERR1748976 ERR1748977 ERR1748978 ERR1748979 ERR1748980 ERR1748981 ERR1748982 ERR1748983 ERR1748984 ERR1748985 ERR1748986 ERR1748987 ERR1748988 ERR1748989 ERR1748990 ERR1748991 ERR1748992 ERR1748993 ERR1748994 ERR1748995 ERR1748996 ERR1748997 ERR1748998 ERR1748999 ERR1749000 ERR1749001 ERR1749002 ERR1749003 ERR1749004 ERR1749005 ERR1749006 ERR1749007 ERR1749008 ERR1749009 ERR1749010 ERR1749011 ERR1749012 ERR1749013 ERR1749014 ERR1749015 ERR1749016 ERR1749017 ERR1749018 ERR1749019 ERR1749020 ERR1749021 ERR1749022 ERR1749023 ERR1749024
ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS
Saint-Petersburg Saint-Petersburg Saint-Petersburg Saint-Petersburg Saint-Petersburg Saint-Petersburg Saint-Petersburg Saint-Petersburg Saint-Petersburg Saint-Petersburg Saint-Petersburg Saint-Petersburg Saint-Petersburg Saint-Petersburg Saint-Petersburg Saint-Petersburg Saint-Petersburg Saint-Petersburg Saint-Petersburg Saint-Petersburg Saint-Petersburg Saint-Petersburg Saint-Petersburg Saint-Petersburg Saint-Petersburg Saint-Petersburg Saint-Petersburg Saint-Petersburg Saint-Petersburg Saint-Petersburg Saint-Petersburg Saint-Petersburg Kazan Saint-Petersburg Kazan Kazan Kazan Kazan Kazan Kazan Kazan Kazan Kazan Kazan Saint-Petersburg Kazan Kazan Kazan Kazan Kazan Kazan Kazan Kazan Kazan Kazan Saint-Petersburg Kazan Kazan Kazan
N/A 39 60 41 55 29 47 43 52 41 36 50 29 45 49 26 45 50 40 29 52 44 37 54 31 49 40 25 38 54 32 43 20 53 30 40 59 31 60 53 48 55 45 54 33 36 41 32 41 34 30 59 55 31 38 44 56 53 44
M M M M M M M M M M M M M M M M M M M M M M M M M M M M M M M M M M M M F M M M M M M M M M M M M M M M M M M M F F M
21.67 20.13 NA 20.46 19.86 23.5 24.76 20.45 19.35 21.59 19.23 21.52 26.8 24.23 23.04 23.69 NA 19.46 24.26 NA NA 23.6 21.41 NA 22.6 NA 16.58 19.7 21.69 NA 17.25 NA NA 23.23 21.97 19.66 30.76 20.98 25.62 20.72 22.49 27.89 21.26 28.33 19.1 21.14 18.26 23.6 22.53 28 23.24 24.69 26.99 23.46 23.33 NA 36.85 29.74 20.05
A.V. Tyakht et al. / Data in Brief 11 (2017) 98–102
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Table 1 (continued ) Sample ID
ENA sample accession
ENA experiment ID
Group
Collection site
Age, years
Gender
BMI
ADS_63 ADS_64 ADS_65 ADS_66 ADS_67 ADS_68 ADS_69 ADS_7 ADS_70 ADS_71 ADS_72 ADS_8 ADS_9 ALC_1 ALC_10 ALC_11 ALC_12 ALC_13 ALC_14 ALC_15 ALC_16 ALC_17 ALC_18 ALC_19 ALC_2 ALC_20 ALC_21 ALC_22 ALC_23 ALC_24 ALC_25 ALC_26 ALC_27 ALC_3 ALC_4 ALC_5 ALC_6 ALC_7 ALC_8 ALC_9
ERS1454715 ERS1454716 ERS1454717 ERS1454718 ERS1454719 ERS1454720 ERS1454721 ERS1454722 ERS1454723 ERS1454724 ERS1454725 ERS1454726 ERS1454727 ERS1454728 ERS1454729 ERS1454730 ERS1454731 ERS1454732 ERS1454733 ERS1454734 ERS1454735 ERS1454736 ERS1454737 ERS1454738 ERS1454739 ERS1454740 ERS1454741 ERS1454742 ERS1454743 ERS1454744 ERS1454745 ERS1454746 ERS1454747 ERS1454748 ERS1454749 ERS1454750 ERS1454751 ERS1454752 ERS1454753 ERS1454754
ERR1749025 ERR1749026 ERR1749027 ERR1749028 ERR1749029 ERR1749030 ERR1749031 ERR1749032 ERR1749033 ERR1749034 ERR1749035 ERR1749036 ERR1749037 ERR1749038 ERR1749039 ERR1749040 ERR1749041 ERR1749042 ERR1749043 ERR1749044 ERR1749045 ERR1749046 ERR1749047 ERR1749048 ERR1749049 ERR1749050 ERR1749051 ERR1749052 ERR1749053 ERR1749054 ERR1749055 ERR1749056 ERR1749057 ERR1749058 ERR1749059 ERR1749060 ERR1749061 ERR1749062 ERR1749063 ERR1749064
ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ALC ALC ALC ALC ALC ALC ALC ALC ALC ALC ALC ALC ALC ALC ALC ALC ALC ALC ALC ALC ALC ALC ALC ALC ALC ALC ALC
Kazan Kazan Kazan Kazan Kazan Kazan Kazan Saint-Petersburg Kazan Kazan Kazan Saint-Petersburg Saint-Petersburg Moscow Moscow Moscow Moscow Moscow Moscow Moscow Moscow Moscow Moscow Moscow Moscow Moscow Moscow Moscow Moscow Moscow Moscow Moscow Moscow Moscow Moscow Moscow Moscow Moscow Moscow Moscow
52 43 47 57 57 51 33 37 32 60 41 56 56 46 58 55 37 32 39 50 53 54 40 50 41 52 52 52 52 54 44 55 47 57 52 58 49 42 57 44
M M M M M M M M M F M M M M F M M M F F M M M M M M M M M M M M M M F M F M M M
23.94 25.98 24.54 22.72 26.78 29.75 25.47 21.46 19.25 35.49 25.66 20.17 21.19 33.33 25.08 24.49 28.53 37.65 23.44 27.34 26.78 30.45 23.89 30.02 23.93 20.05 22.83 28.39 24.9 26.59 30.25 33.91 25.99 25 22.77 30.93 27.06 31.83 24.07 30.72
2. Experimental design, materials and methods 2.1. Cohorts assembly The study was approved by the ethical committee of the Federal Research Clinical Centre of Physical-Chemical Medicine. Each patient signed an informed consent before the start of the study. The patients were enrolled in Moscow Clinical Scientific Center (Moscow), Narcology Dispensary of Republic of Tatarstan (Kazan) and Saint-Petersburg Bekhterev Psychoneurological Research Institute (Saint-Petersburg). The cohort included 2 groups: 72 patients with the diagnosis “alcoholic dependence syndrome” and 27 - with “alcoholic liver cirrhosis”. 2.2. Patients inclusion and exclusion criteria General exclusion criteria: non-alcoholic liver diseases, decompensated diseases of other organs, intake of probiotics and/or prebiotics, medications (non-steroidal anti-inflammatory drugs, antibiotics and proton pump inhibitors) less than 1 month prior to the sample collection, abdominal
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surgery less than 3 months prior to the sample collection. Additional inclusion criteria for the ALC group: alcoholic liver cirrhosis, age over 18 years and alcohol abuse history; the exclusion criteria were the stool changes and bowel movement frequency. Additional inclusion criteria for the ADS group: alcoholic dependence syndrome, alcohol abuse history of Z 8 years. Additional exclusion criteria specific for the ADS cohort: decrease of thrombocytes, albumin and/or prothrombin, increase of INR (international normalized ratio). 2.3. Sample collection and metagenomic sequencing Stool samples were collected from the subjects, stored and subject to DNA extraction as described before [1]. “Shotgun” metagenomic libraries preparation and sequencing using SOLiD 5500xl platform (Life Technology, USA) was performed according to the recommendations of the manufacturer using the following reagent kits: 5500 SOLiD Fragment Library Core Kit, SOLiD Fragment Library Barcoding Kit, SOLiD FlowChip Kit, SOLiD FWD SR S50 Kit, SOLiD Run Cycle Buffer Kit. Barcoded fragment (nonpaired) read libraries were created from 5 μg of total DNA for each of the samples. The resulting read length was 50 bp.
Acknowledgments This work was financially supported by Ministry of Education and Science of the Russian Federation (unique project identifier RFMEFI60414X0119).
Transparency document. Supporting information Transparency data associated with this article can be found in the online version at http://dx.doi. org/10.1016/j.dib.2017.01.008.
Reference [1] A.V. Tyakht, E.S. Kostryukova, A.S. Popenko, M.S. Belenikin, A.V. Pavlenko, A.K. Larin, I.Y. Karpova, O.V. Selezneva, T.A. Semashko, E.A. Ospanova, V.V. Babenko, I.V. Maev, S.V. Cheremushkin, Y.A. Kucheryavyy, P.L. Shcherbakov, V.B. Grinevich, O.I. Efimov, E.I. Sas, R.A. Abdulkhakov, S.R. Abdulkhakov, E.A. Lyalyukova, M.A. Livzan, V.V. Vlassov, R.Z. Sagdeev, V.V. Tsukanov, M.F. Osipenko, I.V. Kozlova, A.V. Tkachev, V.I. Sergienko, D.G. Alexeev, V.M. Govorun, Human gut microbiota community structures in urban and rural populations in Russia, Nat. Commun. 4 (2013) 2469. http://dx.doi. org/10.1038/ncomms3469.
Contents lists available at ScienceDirect
Data in Brief journal homepage: www.elsevier.com/locate/dib
Data Article
Data on gut metagenomes of the patients with alcoholic dependence syndrome and alcoholic liver cirrhosis Alexander V. Tyakht a,n, Veronika B. Dubinkina a, Vera Y. Odintsova b, Konstantin S. Yarygin a,b, Boris A. Kovarsky b, Alexander V. Pavlenko a,b, Dmitry S. Ischenko a,b, Anna S. Popenko b, Dmitry G. Alexeev a,b, Anastasiya Y. Taraskina c, Regina F. Nasyrova c, Evgeny M. Krupitski c, Nino V. Shalikiani d, Igor G. Bakulin d, Petr L. Shcherbakov d, Lyubov O. Skorodumova b, Andrei K. Larin b, Elena S. Kostryukova a,b, Rustam A. Abdulkhakov e, Sayar R. Abdulkhakov e,f, Sergey Y. Malanin f, Ruzilya K. Ismagilova f, Tatiana V. Grigoryeva f, Elena N. Ilina b, Vadim M. Govorun a a Moscow Institute of Physics and Technology, Institutskiy per. 9, Dolgoprudny, Moscow Region 141700, Russia b Federal Research and Clinical Centre of Physical-Chemical Medicine, Malaya Pirogovskaya 1a, Moscow 119435, Russia c Saint-Petersburg Bekhterev Psychoneurological Research Institute, Bekhtereva 3, Saint-Petersburg 192019, Russia d Moscow Clinical Scientific Center, Shosse Entuziastov 86, Moscow 111123, Russia e Kazan State Medical University, Butlerova 49, Kazan 420012, Russia f Kazan Federal University, Kremlyovskaya 18, Kazan 420008, Russia
a r t i c l e i n f o
abstract
Article history: Received 8 December 2016 Received in revised form 28 December 2016 Accepted 11 January 2017 Available online 17 January 2017
Alcoholism is associated with significant changes in gut microbiota composition. Metagenomic sequencing allows to assess the altered abundance levels of bacterial taxa and genes in a cultureindependent way. We collected 99 stool samples from the patients with alcoholic dependence syndrome (n ¼72) and alcoholic liver cirrhosis (n ¼ 27). Each of the samples was surveyed
n
Corresponding author. E-mail address: [email protected] (A.V. Tyakht).
http://dx.doi.org/10.1016/j.dib.2017.01.008 2352-3409/& 2017 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
A.V. Tyakht et al. / Data in Brief 11 (2017) 98–102 Keywords: Gut microbiota Metagenome Alcoholism Alcohol dependence syndrome Alcoholic liver cirrhosis Dysbiosis “Shotgun” metagenomics
99
using “shotgun” (whole-genome) sequencing on SOLiD platform. The reads are deposited in the ENA (project ID: PRJEB18041). & 2017 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Specifications Table Subject area More specific subject area Type of data How data was acquired Data format Experimental factors Experimental features Data source location Data accessibility
Biology Bacterial metagenomics Text files: sequences DNA sequencing using SOLiD 5500xl platform Raw DNA extracted from stool samples Barcoded fragment (non-paired) read libraries were created from 5 μg of total DNA for each of the samples. The sequencing was performed using the SOLiD 5500xl platform according to the recommendations of the manufacturer. Kazan, Russian Federation; Moscow, Russian Federation; Saint-Petersburg, Russian Federation The datasets are deposited in the ENA (project ID: PRJEB18041, URL: http:// www.ebi.ac.uk/ena/data/view/PRJEB18041)
Value of the data
The data describes the human gut microbiota composition in two cohorts of the patients with
alcoholism manifesting distinct degrees of liver dysfunctions: patients with alcoholic dependence syndrome (ADS; alcoholics without advanced liver disease) and patients with alcoholic liver cirrhosis (ALC; alcoholics with advanced liver disease). The data can be used for identifying the changes of gut microbiota associated with alcoholism as well as with the associated liver damage at the levels of community structure (taxonomic composition) and gene potential (functional composition). The data can be used for validating the universality of potential biomarkers of alcoholismassociated dysbiosis via the meta-analysis together with the published gut metagenomes of the world populations. The data can be used in phylogeographic analyses of human microbiota to assess the genomic variations of the gut microbial species typical for Russian population as compared with the other world populations.
1. Data The data represent 99 “shotgun” metagenomes of stool samples collected from the patients with ADS and ALC in 3 clinical centers from 3 Russian cities - Moscow, Kazan and Saint-Petersburg. The datasets include 25.8 716.1 mln of 50 bp reads per sample (mean7 s.d., 127.5 Gbp in total). The description of the data is listed in Table 1.
100
A.V. Tyakht et al. / Data in Brief 11 (2017) 98–102
Table 1 Information about the datasets, samples and subjects. Abbreviations: ADS - alcohol dependence syndrome, ALC - alcoholic liver cirrhosis, BMI – body-mass index, ENA – European Nucleotide Archive, NA – not available. Sample ID
ENA sample accession
ENA experiment ID
Group
Collection site
Age, years
Gender
BMI
ADS_1 ADS_10 ADS_11 ADS_12 ADS_13 ADS_14 ADS_15 ADS_16 ADS_17 ADS_18 ADS_19 ADS_2 ADS_20 ADS_21 ADS_22 ADS_23 ADS_24 ADS_25 ADS_26 ADS_27 ADS_28 ADS_29 ADS_3 ADS_30 ADS_31 ADS_32 ADS_33 ADS_34 ADS_35 ADS_36 ADS_37 ADS_38 ADS_39 ADS_4 ADS_40 ADS_41 ADS_42 ADS_43 ADS_44 ADS_45 ADS_46 ADS_47 ADS_48 ADS_49 ADS_5 ADS_50 ADS_51 ADS_52 ADS_53 ADS_54 ADS_55 ADS_56 ADS_57 ADS_58 ADS_59 ADS_6 ADS_60 ADS_61 ADS_62
ERS1454656 ERS1454657 ERS1454658 ERS1454659 ERS1454660 ERS1454661 ERS1454662 ERS1454663 ERS1454664 ERS1454665 ERS1454666 ERS1454667 ERS1454668 ERS1454669 ERS1454670 ERS1454671 ERS1454672 ERS1454673 ERS1454674 ERS1454675 ERS1454676 ERS1454677 ERS1454678 ERS1454679 ERS1454680 ERS1454681 ERS1454682 ERS1454683 ERS1454684 ERS1454685 ERS1454686 ERS1454687 ERS1454688 ERS1454689 ERS1454690 ERS1454691 ERS1454692 ERS1454693 ERS1454694 ERS1454695 ERS1454696 ERS1454697 ERS1454698 ERS1454699 ERS1454700 ERS1454701 ERS1454702 ERS1454703 ERS1454704 ERS1454705 ERS1454706 ERS1454707 ERS1454708 ERS1454709 ERS1454710 ERS1454711 ERS1454712 ERS1454713 ERS1454714
ERR1748966 ERR1748967 ERR1748968 ERR1748969 ERR1748970 ERR1748971 ERR1748972 ERR1748973 ERR1748974 ERR1748975 ERR1748976 ERR1748977 ERR1748978 ERR1748979 ERR1748980 ERR1748981 ERR1748982 ERR1748983 ERR1748984 ERR1748985 ERR1748986 ERR1748987 ERR1748988 ERR1748989 ERR1748990 ERR1748991 ERR1748992 ERR1748993 ERR1748994 ERR1748995 ERR1748996 ERR1748997 ERR1748998 ERR1748999 ERR1749000 ERR1749001 ERR1749002 ERR1749003 ERR1749004 ERR1749005 ERR1749006 ERR1749007 ERR1749008 ERR1749009 ERR1749010 ERR1749011 ERR1749012 ERR1749013 ERR1749014 ERR1749015 ERR1749016 ERR1749017 ERR1749018 ERR1749019 ERR1749020 ERR1749021 ERR1749022 ERR1749023 ERR1749024
ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS
Saint-Petersburg Saint-Petersburg Saint-Petersburg Saint-Petersburg Saint-Petersburg Saint-Petersburg Saint-Petersburg Saint-Petersburg Saint-Petersburg Saint-Petersburg Saint-Petersburg Saint-Petersburg Saint-Petersburg Saint-Petersburg Saint-Petersburg Saint-Petersburg Saint-Petersburg Saint-Petersburg Saint-Petersburg Saint-Petersburg Saint-Petersburg Saint-Petersburg Saint-Petersburg Saint-Petersburg Saint-Petersburg Saint-Petersburg Saint-Petersburg Saint-Petersburg Saint-Petersburg Saint-Petersburg Saint-Petersburg Saint-Petersburg Kazan Saint-Petersburg Kazan Kazan Kazan Kazan Kazan Kazan Kazan Kazan Kazan Kazan Saint-Petersburg Kazan Kazan Kazan Kazan Kazan Kazan Kazan Kazan Kazan Kazan Saint-Petersburg Kazan Kazan Kazan
N/A 39 60 41 55 29 47 43 52 41 36 50 29 45 49 26 45 50 40 29 52 44 37 54 31 49 40 25 38 54 32 43 20 53 30 40 59 31 60 53 48 55 45 54 33 36 41 32 41 34 30 59 55 31 38 44 56 53 44
M M M M M M M M M M M M M M M M M M M M M M M M M M M M M M M M M M M M F M M M M M M M M M M M M M M M M M M M F F M
21.67 20.13 NA 20.46 19.86 23.5 24.76 20.45 19.35 21.59 19.23 21.52 26.8 24.23 23.04 23.69 NA 19.46 24.26 NA NA 23.6 21.41 NA 22.6 NA 16.58 19.7 21.69 NA 17.25 NA NA 23.23 21.97 19.66 30.76 20.98 25.62 20.72 22.49 27.89 21.26 28.33 19.1 21.14 18.26 23.6 22.53 28 23.24 24.69 26.99 23.46 23.33 NA 36.85 29.74 20.05
A.V. Tyakht et al. / Data in Brief 11 (2017) 98–102
101
Table 1 (continued ) Sample ID
ENA sample accession
ENA experiment ID
Group
Collection site
Age, years
Gender
BMI
ADS_63 ADS_64 ADS_65 ADS_66 ADS_67 ADS_68 ADS_69 ADS_7 ADS_70 ADS_71 ADS_72 ADS_8 ADS_9 ALC_1 ALC_10 ALC_11 ALC_12 ALC_13 ALC_14 ALC_15 ALC_16 ALC_17 ALC_18 ALC_19 ALC_2 ALC_20 ALC_21 ALC_22 ALC_23 ALC_24 ALC_25 ALC_26 ALC_27 ALC_3 ALC_4 ALC_5 ALC_6 ALC_7 ALC_8 ALC_9
ERS1454715 ERS1454716 ERS1454717 ERS1454718 ERS1454719 ERS1454720 ERS1454721 ERS1454722 ERS1454723 ERS1454724 ERS1454725 ERS1454726 ERS1454727 ERS1454728 ERS1454729 ERS1454730 ERS1454731 ERS1454732 ERS1454733 ERS1454734 ERS1454735 ERS1454736 ERS1454737 ERS1454738 ERS1454739 ERS1454740 ERS1454741 ERS1454742 ERS1454743 ERS1454744 ERS1454745 ERS1454746 ERS1454747 ERS1454748 ERS1454749 ERS1454750 ERS1454751 ERS1454752 ERS1454753 ERS1454754
ERR1749025 ERR1749026 ERR1749027 ERR1749028 ERR1749029 ERR1749030 ERR1749031 ERR1749032 ERR1749033 ERR1749034 ERR1749035 ERR1749036 ERR1749037 ERR1749038 ERR1749039 ERR1749040 ERR1749041 ERR1749042 ERR1749043 ERR1749044 ERR1749045 ERR1749046 ERR1749047 ERR1749048 ERR1749049 ERR1749050 ERR1749051 ERR1749052 ERR1749053 ERR1749054 ERR1749055 ERR1749056 ERR1749057 ERR1749058 ERR1749059 ERR1749060 ERR1749061 ERR1749062 ERR1749063 ERR1749064
ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ADS ALC ALC ALC ALC ALC ALC ALC ALC ALC ALC ALC ALC ALC ALC ALC ALC ALC ALC ALC ALC ALC ALC ALC ALC ALC ALC ALC
Kazan Kazan Kazan Kazan Kazan Kazan Kazan Saint-Petersburg Kazan Kazan Kazan Saint-Petersburg Saint-Petersburg Moscow Moscow Moscow Moscow Moscow Moscow Moscow Moscow Moscow Moscow Moscow Moscow Moscow Moscow Moscow Moscow Moscow Moscow Moscow Moscow Moscow Moscow Moscow Moscow Moscow Moscow Moscow
52 43 47 57 57 51 33 37 32 60 41 56 56 46 58 55 37 32 39 50 53 54 40 50 41 52 52 52 52 54 44 55 47 57 52 58 49 42 57 44
M M M M M M M M M F M M M M F M M M F F M M M M M M M M M M M M M M F M F M M M
23.94 25.98 24.54 22.72 26.78 29.75 25.47 21.46 19.25 35.49 25.66 20.17 21.19 33.33 25.08 24.49 28.53 37.65 23.44 27.34 26.78 30.45 23.89 30.02 23.93 20.05 22.83 28.39 24.9 26.59 30.25 33.91 25.99 25 22.77 30.93 27.06 31.83 24.07 30.72
2. Experimental design, materials and methods 2.1. Cohorts assembly The study was approved by the ethical committee of the Federal Research Clinical Centre of Physical-Chemical Medicine. Each patient signed an informed consent before the start of the study. The patients were enrolled in Moscow Clinical Scientific Center (Moscow), Narcology Dispensary of Republic of Tatarstan (Kazan) and Saint-Petersburg Bekhterev Psychoneurological Research Institute (Saint-Petersburg). The cohort included 2 groups: 72 patients with the diagnosis “alcoholic dependence syndrome” and 27 - with “alcoholic liver cirrhosis”. 2.2. Patients inclusion and exclusion criteria General exclusion criteria: non-alcoholic liver diseases, decompensated diseases of other organs, intake of probiotics and/or prebiotics, medications (non-steroidal anti-inflammatory drugs, antibiotics and proton pump inhibitors) less than 1 month prior to the sample collection, abdominal
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surgery less than 3 months prior to the sample collection. Additional inclusion criteria for the ALC group: alcoholic liver cirrhosis, age over 18 years and alcohol abuse history; the exclusion criteria were the stool changes and bowel movement frequency. Additional inclusion criteria for the ADS group: alcoholic dependence syndrome, alcohol abuse history of Z 8 years. Additional exclusion criteria specific for the ADS cohort: decrease of thrombocytes, albumin and/or prothrombin, increase of INR (international normalized ratio). 2.3. Sample collection and metagenomic sequencing Stool samples were collected from the subjects, stored and subject to DNA extraction as described before [1]. “Shotgun” metagenomic libraries preparation and sequencing using SOLiD 5500xl platform (Life Technology, USA) was performed according to the recommendations of the manufacturer using the following reagent kits: 5500 SOLiD Fragment Library Core Kit, SOLiD Fragment Library Barcoding Kit, SOLiD FlowChip Kit, SOLiD FWD SR S50 Kit, SOLiD Run Cycle Buffer Kit. Barcoded fragment (nonpaired) read libraries were created from 5 μg of total DNA for each of the samples. The resulting read length was 50 bp.
Acknowledgments This work was financially supported by Ministry of Education and Science of the Russian Federation (unique project identifier RFMEFI60414X0119).
Transparency document. Supporting information Transparency data associated with this article can be found in the online version at http://dx.doi. org/10.1016/j.dib.2017.01.008.
Reference [1] A.V. Tyakht, E.S. Kostryukova, A.S. Popenko, M.S. Belenikin, A.V. Pavlenko, A.K. Larin, I.Y. Karpova, O.V. Selezneva, T.A. Semashko, E.A. Ospanova, V.V. Babenko, I.V. Maev, S.V. Cheremushkin, Y.A. Kucheryavyy, P.L. Shcherbakov, V.B. Grinevich, O.I. Efimov, E.I. Sas, R.A. Abdulkhakov, S.R. Abdulkhakov, E.A. Lyalyukova, M.A. Livzan, V.V. Vlassov, R.Z. Sagdeev, V.V. Tsukanov, M.F. Osipenko, I.V. Kozlova, A.V. Tkachev, V.I. Sergienko, D.G. Alexeev, V.M. Govorun, Human gut microbiota community structures in urban and rural populations in Russia, Nat. Commun. 4 (2013) 2469. http://dx.doi. org/10.1038/ncomms3469.
