CC BY
41MIRJournal
Microbiology Independent Research Journal
DOI: 10.18527/2500-2236-2022-9-1-18-30
RESEARCH PAPER
Gut microbiome of healthy people and patients with hematological malignancies in Belarus
Katsiaryna V. Akhremchuk1* , Katsiaryna Y. Skapavets2 , Artur E. Akhremchuk1 , Natalia P. Kirsanava2 , Anastasiya V. Sidarenka1 , Leonid N. Valentovich1 ©
!The Institute of Microbiology of the National Academy of Sciences of Belarus, 2, Kuprevich str., Minsk, 220141 Belarus 2Belarusian Research Center for Pediatric Oncology, Hematology, and Immunology; 43, Frunzenskaya str., Borovlyany, Minsk district, 223053 Belarus
ABSTRACT
Gut microbiota plays an important role in human health and the development of various diseases. We describe the intestinal microbiome of 31 healthy individuals and 29 patients who have hematological malignancies from Belarus. Bacteria that belong to Fae-calibacterium, Blautia, Bacteroides, Ruminococcus, Bifidobacterium, Prevotella, Lactobacillus, and Alistipes genera were predominant in the gut of healthy people. Based on the dominant microbiota species, two enterotype-like clusters that are driven by Bacteroides and Blautia, respectively, were identified. A significant decrease in alpha diversity and alterations in the taxonomic composition of the intestinal microbiota were observed in patients with hematological malignancies compared to healthy people. The microbiome of these patients contained a high proportion of Bacteroides, Blautia, Faecalibacterium, Lactobacillus, Prevotella, Alistipes, Enterococcus, Escherichia-Shigella, Ruminococcus gnavus group, Streptococcus, and Roseburia. An increased relative abundance of Bacteroides vulga-tus, Ruminococcus torques, Veillonella, Tuzzerella, Sellimonas, and a decreased number of Akkermansia, Coprococcus, Roseburia, Agatho-bacter, Lachnoclostridium, and Dorea were observed in individuals with hematological malignancies. Generally, the composition of the gut microbiome in patients was more variable than that of healthy individuals, and alterations in the abundance of certain microbial taxa were individually specific.
Keywords: intestinal microbiota, hematological neoplasms, metagenomics, dysbiosis, microbiota diversity #For correspondence: Katsiaryna V. Akhremchuk, Center of analytical and genetic engineering research, The Institute of Microbiology of the National Academy of Sciences of Belarus, 2, Kuprevich str., Minsk, 220141 Belarus, e-mail: katerina_akhr@bio.bsu.by Citation: Akhremchuk KV, Skapavets KY, Akhremchuk AE, Kirsanava NP, Sidarenka AV, Valentovich LN. Gut microbiome of healthy people and patients with hematological malignancies in Belarus. MIR J 2022; 9(1), 18-30. doi: 10.18527/2500-2236-2022-9-1-18-30. Received: November 23, 2021 Accepted: March 2, 2022 Published: March 29, 2022
Copyright: © 2022 Akhremchuk et al. This is an open access article distributed under the terms of the Creative Commons Attribu-tion-NonCommercial-ShareAlike 4.0 International Public License (CC BYNC-SA), which permits unrestricted use, distribution, and reproduction in any medium, as long as the material is not used for commercial purposes, provided that the original author and source are cited Conflict of interest: All of the authors declare no conflict of interest. Acknowledgements: This work was supported by the Government program "Science-Intensive Technologies and Equipment" for 2016-2020 (project No. 671).
INTRODUCTION
The gastrointestinal tract (GIT) is one of the largest (250400 m2) interfaces, where host, environmental factors, and antigens in the human body interact. A population of microorganisms residing in GIT is termed gut microbiota, and the combined genomes of these microorganisms are referred to as a microbiome. The number of microorganisms in GIT reaches 1013-1014 units, which is of the same
order as the number of cells in the human body. The number of microbial genes is about tenfold greater than the number of genes in the human genome [1-3].
Gut microbiota directly or indirectly impacts various physiological processes in the human body, including nutrient and energy metabolism, modulation of the immune system, protection against pathogens, detoxification of xenobiotics, etc. [1, 4]. Intestinal bacteria degrade
complex carbohydrates that are not digested by host enzymes and produce short-chain fatty acids (acetate, propionate, and butyrate) which contribute to gut homeo-stasis, genes expression, cell proliferation and apoptosis, inflammatory response, etc. [5].
It is commonly accepted that the development of microbiota begins shortly after birth, although recent studies have demonstrated the presence of microbes in the placenta. During the first year of life, the microbial diversity increases, and both the composition and functional capacity of a child microbiota resemble that of an adult by around 2-3 years of age [1]. The dominant phyla of a healthy intestinal tract ecosystem are Firmicutes, Bacteroidetes, Actinobacteria, Proteobacteria, Fusobacte-ria, and Verrucomicrobia, representing more than 95% of gut microbiota. The main genera of Firmicutes phylum include Faecalibacterium, Blautia, Dorea, Roseburia, Co-prococcus, Lactobacillus, Clostridium, Enterococcus, and Ruminococcus. The phylum Bacteroidetes consists of predominant genera such as Bacteroides, Parabacteroides, Prevotella, Odoribacter, Barnesiella, and Alistipes. The Actinobacteria phylum is mainly represented by the genus Bifidobacterium [6]. Gut microbiota varies taxonomically and functionally between individuals and depends on genetic factors, diet, lifestyle, and the character of interaction between microorganisms residing in a host. On the other hand, healthy people can be divided into three distinct robust clusters driven by high proportions of a specific taxon in a microbiome, which are called entero-types. These include Bacteroides (enterotype 1), Prevotella (enterotype 2), and Ruminococcus (enterotype 3). However, the existence of enterotypes remains a subject of debate [7, 3].
The imbalance of the gut microbiota is linked to many diseases such as irritable bowel syndrome, inflammatory bowel disease, obesity, type 2 diabetes, neurologic disorders, etc. Significant changes in the intestinal microbiome are associated with tumorigenesis, including the development of pancreatic carcinoma, esophageal, gastric, rectum, hepatic, lung, breast, and gynecological cancer. Some bacteria, like Helicobacter pylori and Chlamydia sp., are considered carcinogenic agents under certain conditions [8].
The role of microbiota in cancer pathogenesis remains poorly understood. In particular, contradictory data was obtained in the case of hematological malignancies. Different studies demonstrate both an increase [9] and decrease [10, 11] in the relative abundance of Clostridiace-ae in children with acute lymphoblastic leukemia (ALL). Similarly, both increase [10, 12] and decrease [9, 13] in the occurrence of Firmicutes were observed in patients with hematological malignancies. Children with ALL and
adults with acute myeloid leukemia (AML) demonstrated higher baseline levels of Staphylococcaceae, Streptococcus [9, 14], and Enterococcus faecalis [10]. The abundance of Blautia decreased in patients with leukemia [10, 11]. The significant reduction in the microbiome diversity was reported for all patients suffering from different types of leukemia [10, 12]. Such alterations in a GIT microbial community may be associated with anticancer therapy, and inter-individual variations in microbial composition could be related to different regimens of chemotherapy and antibiotic treatment. At the same time, a decrease of gut microbiota alpha diversity has been observed in the mouse leukemia model without any anticancer therapy
[15], indicating a possible influence of other factors. Gut microbiota, in turn, modulates the host response
to cancer therapy and susceptibility to toxic side effects
[16]. The restoration of the altered microbial community is regarded as a promising way to enhance the efficacy and reduce the toxicity of chemotherapeutic drugs. Further studies are needed to explore the dynamics of mi-crobiota in health and disease.
Nowadays, numerous metagenomic studies that are focused on the GIT microbiome of healthy individuals and patients with various diseases have been performed around the world. We are aware of the reports about the gut microbiome of people from the United States, European countries, China, Taiwan, Russia, and Kazakhstan. However, no such studies have been conducted in Belarus yet. Therefore, this study describes the intestinal mi-crobiome of healthy individuals and its alterations related to hematological malignancies in patients in Belarus for the first time.
MATERIALS AND METHODS
Ethics statement
This study was approved by the Ethics Committee of the Belarusian Research Center for Pediatric Oncology, He-matology, and Immunology. A written informed consent was obtained from all of the participants or their parents for the collection and analysis of stool samples.
Sample collection
A total of 60 individuals (33 males and 27 females) ranging from 2 to 29 years old were enrolled in the study.
The group of healthy volunteers included 31 individuals (17 males and 14 females) who were 2 to 27 years old (median age 8.7 years old). Healthy status was defined by the absence of disorders of digestive, nervous, cardiovascular, and other systems in their medical history, and
any disease symptoms at the time of the sample collection. The healthy individuals had not been taking antibiotics or non-steroidal anti-inflammatory drugs for 3 months before the sample collection.
The group of patients with hematological malignancies comprised 29 individuals (16 males and 13 females) who were 2 to 29 years old (median age 10.9 years). The patients enrolled in this study were suffering from acute lymphocytic leukemia (n=6), acute myeloid leukemia (n=6), acquired aplastic anemia (n=5), non-Hodgkin lymphoma (n=3), primary immune deficiency (n=3), myelo-dysplastic syndrome (n=1), Diamond-Blackfan anemia (n=1), neuroblastoma (n=1), thalassemia (n=1), bipheno-typic acute leukemia (n=1), and lymphogranulomatosis (n=1). All of the patients were treated in the Belarusian Research Center for Pediatric Oncology, Hematology, and Immunology. They received the standard anti-cancer treatment and no changes were introduced to their therapy or diet before the sample collection.
Fresh feces were collected in sterile cryovials with a metal ball (diameter 4.5 mm) for better sample ho-mogenization. The samples were immediately frozen at -20°C and stored at -80°C until the DNA extraction was performed. To assess the relative stability of the gut mi-crobiome composition, fecal samples were repeatedly collected from several healthy individuals within a few months after the first sampling.
DNA extraction and sequencing
DNA extraction from the stool samples was performed using the NucleoSpin® DNA Soil kit (740780.50, Mache-rey-Nagel) according to the manufacturer's instructions.
Library preparation was carried out according to the Illumina guide (16S Metagenomic Sequencing Library Preparation), using Flash DNA polymerase (PF1/1, ArtBioTech). The quality of the library was assessed using the OFX Fluorometer (DeNovix). Sequencing was performed using the Illumina MiSeq platform and MiSeq Reagent Kit v3 (MS-102-3003, Illumina). ZymoBIOMICS Spike-in Control I (D6320, Zymo Research), containing Gram-negative bacteria Imtechella halotolerans and Gram-positive bacteria Allobacillus halotolerans, served as a positive control for DNA extraction, sequencing and bioinformatic analysis.
Data analysis
The preprocess16S script (https://github.com/masikol/ preprocess16S) was applied to detect and remove primer sequences from reads. Paired-end reads were merged with NGmerge algorithm, which is bundled with the
preprocess16S script. The DADA2 R package was employed to filter merged sequences (maxEE=2) and then the makeSequenceTable function of the DADA2 package was used to construct an amplicon sequence variant (ASV) table, a higher-resolution version of an operational taxonomic unit (OTU) table. Chimeric sequences were identified and removed with the removeBimeraDenovo function. The assignTaxonomy function was applied to assign a taxonomy to the sequence variants. Silva tax-onomic training data formatted for DADA2 (Silva version 132) was used as a reference for taxonomy assignment. Decontam, an open-source R package, was employed to identify contaminant sequences.
Clustering of samples was performed according to the enterotyping tutorial provided by the EMBL (https://enterotype.embl.de/enterotypes.html). Prior to the analysis, sequences belonging to poorly represented genera were removed to decrease the noise. We considered genera poorly represented if their relative abundance across all samples was below 0.01%. The result of clustering was visualized on the principal coordinates analysis (P^A) plot using the ade4 package. The heat-map was generated by means of the microbiome R package. Rarefaction curves and indices of alpha-diversity were calculated using the phyloseq R package. To estimate the significance of differences between groups, we performed the Wilcoxon rank sum test. The differential abundance analysis was carried out using the DESeq2 R package.
Accession number for the sequencing data
The sequence data has been deposited in the NCBI Short Read Archive database under accession number PRJNA777832.
RESULTS
Summary of the sequencing data
To investigate the GIT microbial diversity of healthy people and patients with hematological malignancies, amplicons of V3-V4 regions of 16S rRNA genes were se-quenced. The minimum, maximum, and average number of raw reads were 133,352, 1,790,875, and 449,587, respectively. After the quality control step, the minimum percent of surviving reads was 12.2% and the maximum was 82.9%. The minimum, maximum, and average number of merged reads were 45,159, 908,737, and 255,223, respectively. The reads were classified into 14,204 am-plicon sequence variants (ASVs). Since the rarefaction curves reached a plateau for all of the samples, the
sequencing depth was considered sufficient for further data analysis.
Core microbiome of healthy individuals
The core microbiome of healthy individuals was represented by 4 bacterial phyla (Actinobacteria, Bacteroide-tes, Firmicutes, Proteobacteria), 5 classes (Actinobacteria, Bacteroidia, Bacilli, Clostridia, Gammaproteobacteria), 17 families, and 39 genera. The relative abundance of bacterial genera detected in 560% fecal samples is presented as a heat map (Fig. 1). Considering the low number of common ASVs with relative abundance >1%, the values of the horizontal axis ranges from 0.01% to 1%.
The Lachnospiraceae, Ruminococcaceae, and Bacteroi-daceae families were predominant in the gut of healthy individuals. Among them, Lachnospiraceae was the most abundant, it prevailed in the microbiome of 18 individuals (58%), and it was present in the top three taxa in all of the studied people. The Ruminococcaceae family dominated in 6 individuals (19%) and was among the top three
families in 15 people (48%). The Bacteroidaceae family was predominant in 2 individuals (6%) and was present among the top three taxa in 10 people (32%). The microbiome of some healthy individuals contained a high proportion of the Prevotellaceae, Clostridiaceae, Lacto-bacillaceae, and Enterobacteriaceae families. Moreover, the intestines of individuals were massively colonized by Rikenellaceae (up to 12.7% of reads), Akkermansiace-ae (up to 6.4% of reads), Christensenellaceae (up to 5.6% of reads), Barnesiellaceae (less than 5%), Anaerovoracace-ae (less than 5%), Eggerthellaceae (less than 5%), etc.
At the genus level, Faecalibacterium and Blautia were present among the top three genera in 55% of healthy individuals, Bacteroides - in 45%, Ruminococcus/Rumino-coccaceae CAG-352 - in 16%, Bifidobacterium - in 13%, Prevotella, Lactobacillus, and Alistipes - in 10% (Supplementary Table S1). The Bacteroides genus dominated the gut microbiome of 11 healthy individuals (35%) and the relative abundance of this taxon ranged from 12 to 40%. Blautia was the dominant genus in 7 individuals (23%) with a relative abundance of 17-24%. The
Tannerellaceae; Parabacteroides; ASV24 Streptococcaceae; Streptococcus; ASV3 Streptococcaceae; Streptococcus; ASV200 Streptococcaceae; Streptococcus; ASV17 Streptococcaceae; Lactococcus; ASV74 Ruminococcaceae; UBA1819; ASV103 Ruminococcaceae; Subdoligranulum; 4SV69 Ruminococcaceae; Subdoligranulum; ASV29 Ruminococcaceae; Incertae Sedis; ASV150 Ruminococcaceae; Faecalibacterium; ASV4 Ruminococcaceae; Faecalibacterium; ASV21 Ruminococcaceae; Faecalibacterium; ASV16 Ruminococcaceae; Faecalibacterium; ASV14 Rikenellaceae; Alistipes; ASV70 Rikenellaceae; Alistipes; ASV208 Peptostreptococcaceae; Terrisporobacter; ASV50 Peptostreptococcaceae; Romboutsia; ASV12 Peptostreptococcaceae; Intestinibacter; ASV7 Oscillospiraceae: UCG-005; ASV123 Oscillospiraceae; UCG-002; ASV62 Oscillospiraceae; UCG-002; ASV217 Oscillospiraceae; UCG-002; ASV119 Oscillospiraceae; UCG-002; ASV100 Oscillospiraceae; Oscillibacter; ASV66 Oscillospiraceae; NK4A214 group; ASV133 Monoglobaceae; Monoglobus; ASV84 Lachnospiraceae; Roseburia; ASV44 Lachnospiraceae; Roseburia; ASV310 Lachnospiraceae; Roseburia; ASV31 Lachnospiraceae; Roseburia; ASV167 Lachnospiraceae; Lachnospiraceae NK4A136 group; ASV132 Lachnospiraceae; Lachnospiraceae ND3007 group; ASV42 Lachnospiraceae; Lachnospiraceae FCS020 group; ASV427 ΠLachnospiraceae; Lachnospira; ASV97
x Lachnospiraceae; Lachnospira; ASV11
.ΠLachnospiraceae; Lachnoclostridium; ASV196
r~ Lachnospiraceae; Lachnoclostridium; ASV163
Lachnospiraceae; Fusicatenibacter; ASV22 Lachnospiraceae; Dorea; ASV49 Lachnospiraceae; Dorea; ASV105 Lachnospiraceae; Coprococcus; ASV94 Lachnospiraceae; Coprococcus; ASV113 Lachnospiraceae; Blautia; ASV51 Lachnospiraceae; Blautia; ASV45 Lachnospiraceae; Blautia; ASV2 Lachnospiraceae; Blautia; ASV19 Lachnospiraceae; Blautia; ASV128 Lachnospiraceae; Anaerostipes; ASV26 Lachnospiraceae; Agathobacter; ASV41 Lachnospiraceae; Agathobacter; ASV13 Lachnospiraceae; [Ruminococcus] torques group; ASV58 Lachnospiraceae; [Eubacteriuml hallii group; ASV93 Lachnospiraceae; jEubacteriuml hallii group; ASV35 Lachnospiraceae' [Eubacteriumlhallii group; ASV207 Lachnospiraceae; [Eubacterium] eliaens group; ASV106 Erysipelotrichaceae; Turicibacter; ASV110 Erysipelatoclostridiaceae; Erysipelotrichaceae UCG-003; ASV124 Enterobacteriaceae; Escherichia-Shigella; ASV6 Clostridlaceae; Clostridium sensu stricto 1; ASV67 Clostridiaceae; Clostridium sensu stricto 1; ASV39 Clostridiaceae; Clostridium sensu stricto 1; ASV27 Christensenellaceae; Christensenellaceae R-7 group; ASV508 Butyricicoccaceae; Butyricicoccus; ASV211 Bifiaobacteriaceae; Bifidobacterium; ASV47 Bifidobacteriaceae; Bifidobacterium; ASV25 Bacteroidaceae; Bacteroides; /4SV9 Bacteroidaceae; Bacteroides; ASV5 Bacteroidaceae; Bacteroides; ASV40 Bacteroidaceaer Bacteroides; ASV18 Anaerovoracaceae; Family XIIIAD3011 group; ASV384
Prevalence
■ 1.0
0.9 0.8 0.7 0.6 0.5 0.4
10.3 0.2 0.1 0.0
Fig. 1. Bacterial core in the intestinal microbiome of healthy individuals. The heatmap displays bacterial genera with relative abundance >0.01-1% detected in >50% of the fecal samples surveyed in this study. Each column represents a microbial taxon with the relative abundance (%) indicated by shading according to the legend.
Faecalibacterium genus prevailed in 5 individuals (15%) and accounted for 12-20% of a total microbial community. Prevotella was the most abundant genus in 2 individuals constituted 33-37% of microbiota. The microbiome of some individuals was enriched with Bifidobacterium, Escherichia-Shigella, Dialister, Sarcina, Citrobacter, and Muribaculaceae CAG-873.
Detection of the enterotypes
Profiling of the GIT microbiome of 31 healthy individuals using PCoA demonstrated clustering into two enterotype-like groups driven by Bacteroides and Blautia (Fig. 2). The majority of the samples (61%) were grouped into a Bacteroides-driven cluster similar to enterotype 1. This cluster contained three sub-types of microbiota enriched with Bacteroides, Faecalibacterium, and Prevotella, respectively, and also included the microbiomes with a prevalence of Dialister and Muribaculaceae CAG-873. The Blautia-driven cluster comprised 39% of the analyzed samples with a high proportion of Bifidobacterium, Lactobacillus, Citrobacter, or Sarcina. This cluster is similar to enterotype 3 characterized by the dominance of Ruminococcus or related groups of the order Clostridiales, genus Blautia, and family Lachnospiraceae. Furthermore, some Blautia species were previously assigned to the Ruminococcus genus [7, 17, 18]. Enterotype 2 driven by Prevotella was not detected in the analyzed samples.
Microbiota of patients with hematological malignancies
In the current study, we compared the microbiome of healthy individuals with the microbiome of patients suffering from hematological malignancies to investigate a cancer-related disturbance.
At the family level, the microbiome of patients was similar to that of healthy people. Lachnospiraceae, Bac-teroidaceae, and Ruminococcaceae were among the top three families in 86%, 45%, and 34% of individuals, respectively, but the relative abundance of these taxa differed from healthy people. Other bacterial families that were widely distributed among the patients included Enterobacteriaceae (detected in 17% of individuals with a relative abundance from 8% to 60%), Enterococcaceae (present in 21% of individuals with the relative abundance from 3% up to 95%), Streptococcaceae (found in 21% of individuals with relative abundance from 9% to 82%), and Peptostreptococcaceae and Lactobacillaceae in lower numbers.
At the genus level, considerable inter-individual variability was found in the composition of the gut microbi-ome of patients with hematological malignancies. Only 17 ASVs were detected in the fecal samples of 50% (or more) of the patients compared to 70 common ASVs present in the microbiome of healthy individuals. The majority of the detected ASVs were assigned to Firmicutes and only one ASV was assigned to Proteobacteria. The three most
Fig. 2. The enterotypes identified in healthy individuals using Principal Coordinate Analysis. mir-journal.org
abundant genera varied between individuals and were represented by Bacteroides (48% of patients), Blautia (24%), Faecalibacterium (17%), Lactobacillus (10%), Prevotella, and Alistipes (7%), widely distributed among healthy people, and Enterococcus (21%), Escherichia-Shigella (17%), Ruminococcus gnavus group (17%), Streptococcus (14%), and Roseburia (10%), detected in healthy people in small amounts. In some cases, we observed the prevalence of the genera Megasphaera, Subdoligranulum, Phascolarcto-bacterium, Citrobacter, Klebsiella, Lachnospira, and Rothia.
The significant difference in genera/species abundance of some families (Bacteroidaceae, Veillonellaceae, Lachnospiraceae, Ruminococcaceae, Enterobacteriaceae, etc.) on a log2-fold change scale was observed between the healthy people and patients suffering from hemato-logical malignancies (Fig. 3). A decrease in the relative abundance of Akkermansia, one of the most abundant taxa in the microbiome of healthy adults, was detected in patients. Only Bacteroides vulgatus was present in high abundance in the fecal samples of people with hemato-logical malignancies, whereas the number of other Bac-teroides was lower compared to the samples of healthy
individuals. The Veillonella genus was the main representative of the family Veillonellaceae in patients.
The Lachnospiraceae family predominated both in healthy people and in patients. At the genus level, the genera Coprococcus, Roseburia, Agathobacter, Lachno-clostridium, and Dorea were predominant among healthy individuals. In patients, the abundance of these taxa was lower, whereas the relative abundance of Tuzzerel-la and Sellimonas was noticeably higher. In addition, we detected an increase in the relative abundance of Ruminococcus torques in the microbiome of patients compared to healthy individuals.
Alpha diversity
Diversity indices, which provide information about the rarity and commonness of taxa in a community (Shannon, InvSimpson), were significantly higher for healthy individuals than for patients suffering from hematolog-ical malignancies. Alpha diversity estimation based on the Shannon index showed a median of 2.99 for patients, which was far from the median (4.02) and close to the
Fig. 3. Log2-fold change in the relative abundance of individual ASVs in healthy individuals relative to patients suffering from hematological malignancies based on the DeSeq2 package. Positively enriched ASVs are more abundant in healthy individuals than in patients with malignancies while negatively enriched ASVs are more abundant in patients with malignancies. ASVs are separated horizontally by family and colored by phylum.
minimum value (2.92) for healthy people. The median value of InvSimpson was 26.20 for healthy individuals and 11.09 for patients (Fig. 4). These results correspond well to the other studies demonstrating a significant decrease in taxonomic diversity of the intestinal microbiome in patients with different types of blood cancer [19]. Notably, the loss of fecal microbiota diversity is generally associated with a high risk of infectious diseases and was proposed as a marker to predict the potential complications associated with intensive chemotherapy in AML patients [20].
The microbiome composition was more variable in patients than in healthy individuals, which is reflected in the distribution pattern of samples from healthy people (Fig. 5). Notably, the microbiomes of two patients (O08 and O22) were close to the microbiomes of healthy individuals, which may be explained by the high alpha diversity in these samples (Shannon=4.6 and 4.7; InvSimpson=50.6 and 51.3, respectively).
DISCUSSION
Microbiome of healthy individuals
The current study indicates that the Lachnospiraceae, Ru-minococcaceae, Bacteroidaceae, Prevotellaceae, and Clos-tridiaceae families, widely distributed in the intestinal tracts of adults all over the world [21], were predominant in the microbiome of healthy Belarusians. Notably, we detected a high abundance of the Rikenellaceae, Christensenellaceae, Akkermansiaceae, Barnesiellaceae,
Anaerovoracaceae, and Eggerthellaceae families in the analyzed fecal samples. Recent studies suggest that the Rikenellaceae and Barnesiellaceae families may be regarded as markers of normal-weight adolescents [22]. The Christensenellaceae and Rikenellaceae families are abundant in normal-weight adults without metabolic disorders [23, 24]. The Barnesiellaceae and Clostridiaceae families (genus Roseburia) are considered as indicators of a highfiber diet [25]. Therefore, our findings confirmed a high abundance of the Rikenellaceae, Christensenellaceae, and Barnesiellaceae families in the intestines of healthy adolescents and young adults of normal weight.
The genera Bacteroides, Eubacterium, Faecalibacteri-um, Alistipes, Ruminococcus, Clostridium, Roseburia, and Blautia dominate in the microbiome of the majority of healthy adults [21]. In turn, the genera Bacteroides, Bi-fidobacterium, Prevotella, Faecalibacterium, and Blautia prevail in school-age children [26, 27]. Similarly, the Fae-calibacterium, Blautia, Bacteroides, Ruminococcus, Bifido-bacterium, Prevotella, Lactobacillus, and Alistipes genera were the predominant taxa in the gut of healthy Belaru-sians. The microbiome of some individuals was enriched with Sarcina, Citrobacter, and Muribaculaceae CAG-873, which are considered normal inhabitants of the human GIT, although their presence in such high numbers is not typical for healthy people. The overabundance of these bacteria may be associated with a specific diet or living conditions, which requires further investigation.
In the present study, we revealed that the gut mi-crobiota of healthy individuals cluster into two groups driven by Bacteroides and Blautia, similar to enterotype
Fig. 4. A violin plot representing the alpha diversity measures in healthy individuals and in patients. (A) Shannon Diversity Index; (B) Inverse Simpson Index. The boxes span from first to third quartiles; the horizontal lines inside the boxes represent medians and the dots represent outliers. P-values were estimated using the Wilcoxon rank sum test.
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1 and enterotype 3, respectively. Enterotype 2 dominated by Prevotella was not found. The existence of separate enterotypes is still in doubt, and several studies
have demonstrated both the absence of any enterotype and the presence of up to 6 enterotype-like clusters [28,
29]. Only two enterotypes dominated by Bacteroides and Prevotella were found in adult people from Thailand, Chi-
na, and Kazakhstan [30-32]. Similar results have been
reported for Asian school-age children, where a Prevotel-la-driven cluster dominated among children from Indonesia, Thailand, Hong Kong, and a Bifidobacterium/Bacte-roides-driven cluster was prevalent among children from China, Japan, and Taiwan [26]. Three enterotypes driven
by Bacteroides, Prevotella, and Bifidobacterium, respectively, were detected in Dutch children [33]. Our results correlate with those of other authors and support the existence of enterotype gradient, rather than three "classic" enterotypes.
Traditionally, the enterotype dominated by the Bac-teroides is associated with the Western diet, which is rich in animal protein and saturated fat. It is common among Europeans and Americans. Oppositely, the Prevotella-driven enterotype is associated with a diet rich in vegetables and complex carbohydrates and is common among residents of Asia and Africa [7,34]. Furthermore, enterotype 1 with a high proportion of Bacteroides
is widely represented in the urban population, and en-terotype 2 with the dominance of Prevotella is more typical for people from rural areas. Our results are consistent with these findings, as Belarus is a country with a high consumption of meat and meat products (about 91 kg per person annually), and all of the studied individuals lived in Minsk city or its suburbs.
Interestingly, the microbiome of individuals from Belarus differed from that of people from rural and urban areas of Russia, despite the territorial proximity and similar lifestyle of the two countries. The Bacteroides--driven enterotype 1 was widely distributed among those from Belarus, but not in the Russian population, where clusters driven by Prevotella (enterotype 2), or Bifidobacteri-um and some other genera of Firmicutes (similar to en-terotype 3), dominated [35].
It is noteworthy that the healthy people enrolled in the current study significantly differed in their age (from 2 to 27 years). It is generally accepted that age impacts the gut microbiome composition, which changes greatly from childhood to old age. At the same time, for a long period of adulthood (ignoring the influence of other factors), the personal core microbiome remains relatively stable [6]. Recent reports have indicated that the composition and diversity of a child's microbiome became like those of adults at the age about 3-4 years, and another broad shift in the gut microbiome occurs around the age of 60-70 years [6, 36]. Therefore, the presence of children younger than 4 years old, whose microbiome is believed to be just under development toward an adultlike configuration, in the group of healthy individuals may potentially distort the general picture. We analyzed the taxonomic diversity and core microbiome composition of healthy individuals, excluding those younger than 4 years old, and found only minor differences compared to those of the whole studied group (the data is not presented). Taking into account this finding and the suggestion of Odamaki et al. [36] that the age-associated shifts of the microbiome are apparent in subjects younger than 20 years old due to the maturation of the gut microbi-al population, further studies are required in larger and more homogeneous groups to determine the taxonom-ic diversity and specific features of the gut microbiome of healthy Belarusians.
Microbiota of patients with hematological malignancies
We conducted this study with the goal to determine how the gut microbiota of patients with hematological malignancies differs from that of healthy individuals. At the family level, we detected an increase in the relative
abundance of Enterobacteriaceae, Enterococcaceae, Strep-tococcaceae, Peptostreptococcaceae, and, to a lesser extent, Lactobacillaceae. An increase in the relative abundance of Enterococcaceae, Streptococcaceae, and Lactobacil-laceae in patients with blood cancer has been reported in several studies. The number of Enterococcus and Streptococcus increased after intensive chemotherapy and was associated with a high risk of infectious complications [19, 27]. Similarly, the relative abundance of Lactobacilla-ceae increased during anticancer treatment and was associated with intestinal inflammation [37]. Nevertheless, the high number of Lactobacillaceae should not be considered a negative factor as infectious complications after hematopoietic stem-cell transplantation (HSCT) were observed in Lactobacillus-free mice, and the restoration of the Lactobacillaceae population positively influenced the transplantation outcome [38, 39].
The high abundance of Enterococcus, Streptococcus, and Klebsiella found in the microbiome of patients with hematological malignancies may be regarded as a marker of chemo- and/or antibiotic therapy-induced gut dysbiosis associated with a high risk of infectious complications [19]. In the current study, only one patient, whose microbiome was enriched with Bacteroides (relative abundance 61%), Faecalibacterium (6%), and Escherichia/Shigella (6%), did not suffer from bacterial and/or viral infection during anticancer therapy. Patients with a high proportion of intestinal Enterococcus and Streptococcus developed human herpesvirus 6 (HSV6) and cytomegalovirus infections, bacterial bloodstream infection, pneumonia, and enterocolitis. It is noteworthy that the same complications were observed in patients whose microbiome was not dominated by enterococci and streptococci. Concerning R. gnavus, we suppose that the increase in the relative abundance of these bacteria might be due to intestinal inflammation. In previous studies, R. gnavus was associated with blood sepsis in patients suffering from multiple myeloma and myelodysplastic syndrome [40-42]. In our study, two out of four patients with a high relative abundance of R. gnavus developed bacterial bloodstream infections. The increase of B. vulgatus in the intestine of patients was reported to be caused by treatment with an H2 receptor blocker or proton pump inhibitors [43]. This finding might explain the high abundance of B. vulgatus in the studied patients, whose treatment regimen included omeprazole or, rarely, pantoprazole. Although it was shown that the prevalence of B. vulgatus in patients suffering from non-small cell lung cancer correlated with the absence of chemotherapy-induced dermatological toxic-ity [44], we observed no significant difference between the severity of dermatological toxicity and the relative abundance of B. vulgatus in patients with hematological
malignancies. The Veillonella genus seemed to be the main representative of the Veillonellaceae family in the microbiome of the studied patients. Similar shifts in microbiome composition were shown for individuals with lung cancer, diabetes, irritable bowel syndrome, hypertension, obesity, and hepatopathy [45-47].
In the current study, we found an increase in the relative abundance of Tuzzerella, Sellimonas, and R. torques in the microbiome of patients with hematological malignancies compared to healthy individuals. Other research groups detected an increased relative abundance of Sellimonas in patients who have recovered from intestinal homeostasis following chemotherapy treatment for colorectal cancer or therapeutic splenectomy for liver cirrhosis. Conversely, some studies have demonstrated an increased relative abundance of Sellimonas intestinalis in individuals with chronic kidney disease and systemic-onset juvenile idiopathic arthritis [48]. Bacteria R. torques and related species are considered to be able to degrade mucus and thereby reduce the integrity of the intestinal barrier. Furthermore, the high abundance of these bacteria is associated with a high level of triglycerides in blood serum. The abundance of the R. torques group was positively correlated with irritable bowel syndrome. These bacteria also were regarded as a metagenomic biomarker for the prediction of upper gastrointestinal tract involvement in patients with Crohn's disease [49, 50]. This emphasizes the importance of monitoring R. torques overabundance in immunocom-promised patients including individuals suffering from hematological malignancies.
Generally, we observed high individual-specific variations in the taxonomic composition of patients' microbi-ota, which can be connected to a number of factors. Our study was limited to a rather small group of patients with different hematological malignancies, including ALL, AML, acquired aplastic anemia, non-Hodgkin lymphoma, primary immune deficiency, etc. These malignancies differ in their pathophysiology and may be associated with different changes in the composition and function of the intestinal microbiota. As each subgroup with specific diagnosis contained a maximum of 6 patients (e.g. ALL, AML) and a minimum of 1 patient (e.g., myelodysplastic syndrome, Diamond-Blackfan anemia), it was impossible
to analyze the intra- and inter-group variations to determine the shifts in the microbiome compositions that are common for all patients with hematological malignancies and those related to a certain type of disease. Moreover, the patients enrolled in this study belonged to different age groups (from 2 to 29 years old), which might also impact their individual gut microbial population. The other factors contributing to observed variations in the gut microbiota included differences in the severity of disease manifestation and/or in an anticancer treatment regimen.
CONCLUSION
In this study, we made the first attempt to characterize the healthy microbiome and to reveal the hematological malignancies-related alterations of the intestinal micro-bial community in people living in Belarus. We showed that the core microbiome of healthy individuals was represented by 39 genera, among which Faecalibacte-rium, Blautia, Bacteroides, Ruminococcus, Bifidobacteri-um, Prevotella, Lactobacillus, and Alistipes were the most abundant. The variation in the gut microbiota of individuals' clusters into two enterotype-like groups was driven by Bacteroides and Blautia, respectively. The significant reduction of alpha diversity and the high inter-individual variability in the abundance of certain taxa were observed in the microbiome of patients compared to that of healthy individuals. Thus, we found an increase in the relative abundance of Enterococcus, Streptococcus, Veillonella, Tuzzerella, Sellimonas, Escherichia-Shigella, R. gnavus group, B. vulgatus, and R. torques, and reduced numbers of Akkermansia, Coprococcus, Roseburia, Agatho-bacter, Lachnoclostridium, and Dorea in patients. We hypothesize that, at least partially, these alterations in the gut microbiome composition are related to medication, especially antibiotic treatment. A significant decrease of bacterial alpha diversity observed in the fecal samples of all patients may be regarded as a warning sign that the gut ecosystem is compromised and the risk of infectious complications is rather high.
Further comprehensive studies are required to improve our understanding of the role of the gut microbi-ome in the development of hematological malignancies.
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