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The alteration of intrauterine microbiota in chronic endometritis patients based on 16S rRNA sequencing analysis

The alteration of intrauterine microbiota in chronic endometritis patients based on 16S rRNA... Background Chronic endometritis (CE) is a disease of continuous and subtle inflammation occurring in the endome - trial stromal area, which is often asymptomatic or present with non-specific clinical symptoms. Methods This study investigated the composition and distribution of the intrauterine microbiota of 71 patients who underwent hysteroscopy during the routine clinical inspection of infertility. Among them, patients who were diag- nosed with chronic endometritis (CE) were allocated into CE group (n = 29) and others into non-CE group (n = 42). There was no significant difference in average age between the two groups (P = 0.19). Uterine flushing fluid was col- lected by the self-developed cervical trocar uterine cavity sampler and 16S rRNA sequencing was performed. Results The alpha diversity in the CE group was significantly higher than that in the non-CE group (P < 0.05). Firmi- cutes (newly named Bacillota) were the dominant phylum in the non-CE group (72.23%), while their abundance was much lower in the CE group (49.92%), but there was no statistically significant difference between the two groups. The abundances of Actinobacteriota and Cyanobacteria in the CE group were significantly higher than those in the non-CE group (P < 0.05). At the genus level, the abundance of Lactobacillus dominated in all samples, which presented a significantly lower abundance in the CE group (40.88%) than that in the non-CE group (64.22%) (P < 0.05). Correspondingly, the abundance of non-Lactobacillus was higher in the CE group, among which Pseudomonas and Cutibacterium increased significantly (P < 0.01). Moreover, compared with the non-CE group, the pathways involved in arginine and proline metabolism and retinol metabolism were significantly enriched in the CE group (P < 0.05), while the metabolism of lipid and prenyltransferases were significantly decreased in the CE group (P < 0.05). Conclusions A certain microbial community was colonized in the uterine cavity, which was dominated by Lactoba- cillus. The structure and distribution of intrauterine microbiota in the CE group were different from those in the non- CE group by showing a lower abundance of Lactobacillus, and a significantly higher abundance of Pseudomonas and Cutibacterium. Additionally, the microbial metabolism was altered in the CE group. This study elaborated the alteration of intrauterine microbiota in CE patients, which may contribute to the diagnosis of CE and provide a reference for antibiotic treatment of CE. Keywords Chronic endometritis, Intrauterine microbiota, 16S rRNA sequencing, Firmicutes (Bacillota), Lactobacillus Qing Chen, Xiaowei Zhang and Qicai Hu contributed equally to this work Hospital, Shenzhen 518036, P. R. China and share first authorship. Institute of Obstetrics and Gynecology, Shenzhen PKU-HKUST Medical Center, Shenzhen 518036, P. R. China *Correspondence: Shenzhen Key Laboratory on Technology for Early Diagnosis of Major Weixia Wei Gynecologic Diseases, Shenzhen 518036, P. R. China weixwei_2013@126.com Department of Obstetrics and Gynecology, Peking University Shenzhen © The Author(s) 2023. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. 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The exclusion criteria Background were as follows: (1) patients with acute and chronic infec- Chronic endometritis (CE) is a disease of continuous and tious diseases, diabetes, cardiovascular diseases, autoim- subtle inflammation occurred in the endometrial stro - mune diseases, thyroid diseases and mental diseases; (2) mal area, which is often asymptomatic or present with patients who  have not received contraceptive or steroid non-specific clinical symptoms, such as pelvic pain, dys - treatment within six months and have not received sys- functional uterine bleeding, dyspareunia, vaginitis, etc. temic antibiotics within three months. This study was Studies have shown that CE is associated with infertil- approved by the Ethics Committee of Peking University ity, repeated abortion and repeated implant failure [1–3]. Shenzhen Hospital (No. 2019–064), and all participants As a result, most of the CE cases were diagnosed by the provided written informed consent. routine examination of infertility patients, and the preva- lence rate is as high as 67%. Currently, microbial infec- Sampling and hysteroscopic examination tion is regarded as one of the main causes of CE [1, 2]. During the surgery, the vulvovaginal was sterilized rou- Previous studies have confirmed that the administration tinely after intravenous general anesthesia, and then a of antibiotics is an effective treatment method for CE disposable sterile vaginal speculum was inserted into the which can improve fertility outcomes significantly [4, 5]. vagina. The self-developed transcervical cannula uterine With the rapid development of sequencing technology, cavity sampler (Patent Number: ZL 2018 2 1945014.0) more accurate molecular technology has been used for was used to avoid the contamination of vaginal and the diagnosis of CE toward pathogenic microorganism cervical secretions. Firstly, a disposable sterile external detection. On the other hand, with the improvement of cannula was placed in the cervical canal. Secondly, we intrauterine sampling technology, the traditional concept connected a uterine cavity sampling catheter to a 10  ml of sterile uterine cavity has been broken [6]. It has been syringe, which was pre-injected with 3  ml sterile saline, elaborated that a complex bacterial community was colo- and inserted into the cannula. After injecting the saline nized in the uterine cavity. Although the biomass of the for 1  min, the solution was extracted by turning the community is relatively low, they keep a balanced intrau- uterine cavity clockwise for a circle. Then, the sampling terine microenvironment through bacterial metabolisms catheter was returned back to the cannula and removed and interaction. The pathogenic invasion may disrupt the together. Finally, the sample was injected into a sterile balance, shape the microbial community, and may further EP tube, and stored in a –  80  °C refrigerator. Also, the cause endometritis. However, rare studies were focused uterine manifestations and endometrial biopsy were on the specific characteristics of the disordered micro - described according to the criteria of hysteroscopy for biota in the uterine cavity of CE patients. An explanation CE diagnosis [7]. of microbial community based on a large sample size will contribute to the precise diagnosis and treatment of CE. Histological analysis and immunohistochemistry In this study, 16S rRNA gene sequencing technology Endometrial samples were fixed in neutral formalin was used to study the microbiota in the uterine cavity of and embedded in paraffin for histological analysis and infertile patients  with CE. The community composition immunohistochemistry. All biopsy blocks were serially and distribution were characterized to provide a basis for sectioned at a thickness of 3–4 μm and incubated with improving the diagnosis rate of CE and guiding the selec- mouse anti-human monoclonal CD138 antibody (Biocare tion of antibiotic treatment for CE patients. Medical, Concord, CA, USA) and the secondary anti- body used was a labeled polymer horseradish peroxidase Methods anti-mouse antibody (Maixin, Fuzhou, China) following Participates the protocol. The number of CD138+ cells more than 4/ Patients who underwent hysteroscopic surgery for the HPF + was diagnosed as CE [7–9]. routine infertility examination at Peking University Shen- zhen Hospital  (Shenzhen, China) between January 2019 DNA extraction and 16S rRNA amplicon sequencing and December 2020 were recruited in this study. Among We sequenced the samples from cervix samples by them, the patients who did not receive vaginal medica- amplicon sequencing of partial 16S rRNA gene [10]. The tion and had no sexual behaviors within 7 days after men- genomic DNA from samples was extracted by QI Aamp struation, and met the following inclusion and exclusion DNA Mini Kit (Qiagen, Hilden, Germany). The extracted criteria were informed and enrolled. The inclusion crite - product was used as a template to amplify the 16S rRNA ria were as follows: (1) patients who under went in vitro V4 region after passing the quality control of nanodrop fertilization and embryo transfer (IVF-ET) and failed no (Thermo  Fisher Scientific, Waltham, MA, USA), Qubit less than one time; (2) patients who experienced sponta- 3.0 (Invitrogen, Carlsbad, CA, USA), and agarose gel neous abortion no less than two times; (3) patients who Chen  et al. Ann Clin Microbiol Antimicrob (2023) 22:4 Page 3 of 10 electrophoresis. The V4 region of the 16S rRNA genes not associated with CE. In addition, among all the par- was amplified by PCR with universal primers V4-515F ticipants, 21 IVF-ET failure cases, 4 recurrent abor- (5ʹ-GTG CCA GCMGCC GCG GTAA-3ʹ) and 806R (5ʹ- tion patients, 4 uterine malformation patients, and 38 GGA CTA CHVGGG TWT CTAAT -3ʹ). After the PCR cases  with the previous history of gynecological surgery product was detected and purified by agarose gel electro - were included, and they all presented no significant dif - phoresis and the concentration was qualified, the library ference between the CE and non-CE groups. has obtained after polyadenylation. The Qubit 3.0  Fluo - rometer and Agilent 2100 Analyzer were used for quality A significantly higher intrauterine microbial α‑diversity control of the constructed library. Subsequently, the total was presented in CE patients DNA was sequenced by the Illumina Mini Seq platform The α-diversity of the uterine microbiota was calcu - for pair-end 300 bp sequencing. lated by Shannon–Wiener index at the genus level. The results showed that the microbial α-diversity in uter- Bioinformatic analysis ine cavity in the  CE group was significantly higher than The newly generated raw sequencing data were processed that in the non-CE group (P < 0.05) (Fig. 1a). Non-super- for quality control using the FASTX toolkit. QIIME2 vised partitioning around medoids (PAM) algorithm software was used to remove sequenced primers and was invited to explain the β-diversity of the intrauterine barcodes, obtain chimeric artifacts, calculate  Bray–Cur- microbiota of two groups (Fig.  1b). The result showed tis distance matrix construction, and pick Operational that most of the samples from CE and Non-CE groups Taxonomic Units (OTUs) [11, 12]. The sequences of the were overlapped and not separated clearly. The first remaining libraries were grouped into OTUs based on principal component (PC1), mainly contributed by Lac- 97% similarity using the UCLUST program. The seeded tobacillus, provided some non-CE samples  with more sequences of each OTU were chosen for taxonomic clas- positive values. This indicated that Lactobacillus might sification against the Silva 138 SSURef NR99 full-length be a potential biomarker for distinguishing CE from non- sequences [13] by the UCLUST taxonomy assigner. The CE samples. For the second principal component (PC2), relative abundance profiles of the main phylum and genus mainly driven by unknown bacteria, CE and non-CE sam- were quantified. STAMP software was invited to predict ples were mixed. Although CE and non-CE samples were the functional profiles of the microbial communities [14]. resided significantly different microbial communities, the key taxa were still unclear. Techniques with higher Statistical analysis resolution, such as metagenomic sequencing or whole SPSS  22.0 software was used for statistical analysis. The genome sequencing, and even the cultural methods could continuous variable data were confirmed as a normal dis - be more appropriate options to investigate the specific tribution before T-test was applied. The categorical vari - genus/species in further studies. The Wilcoxon test result able data were presented as percentages and the χ2 test showed P > 0.05, suggesting that there was no significant was used. P < 0.05 was considered statistically significant. difference between the community composition of intra - uterine microbiota in CE and non-CE groups. Results No significant difference was found in the clinical The intrauterine microbial composition and abundance characteristics between CE and non‑CE groups were different in CE patients A total of 71 participants were included, with an aver- In general, according to the annotation and abundance age age of 31.77 ± 3.88  years. Among them, 29 cases at the genus level, Lactobacillus was the most abundant with chronic endometritis (CE group) and 42 cases of genus in all samples. It was followed by Pseudomonas, non-chronic endometritis (non-CE group) were iden- Methylobacterium, Staphylococcus, and Proteobacteria in tified according to the results of  histophiological and order of abundance. However, the samples from the  CE immunohistochemical results. The age of the patients and non-CE groups could not be well-clustered into two in the  CE and non-CE groups was 32.11 ± 4.46 and groups (Fig. 2) indicating a similar composition of intrau- 32.33 ± 3.66  years, respectively, and there was no differ - terine microbiota in CE and non-CE participants. ence in age between the two groups (P = 0.19). At the phylum level, Firmicutes (Bacillota) domi- Among the 71 enrolled participants, 34 women had no nated in the non-CE group (identified as relative abun - history of pregnancy and delivery, including 16 CE cases dance ≥ 50%), accounting for 72.23% and followed by and 18 non-CE cases, while there were  37 patients with Proteobacteria (19.36%), Actinobacteriota (3.75%), Bacte- pregnancy histories, including 13 CE cases and 24 non- roidota (1.71%), Deinococcota (0.50%), Bdellovibrionota CE cases. The Chi-square test (Chi-square value = 1.043, (0.49%), Patescibacteria (0.25%), Cyanobacteria (0.10%) P = 0.307) indicated that the history of pregnancy was and others (1.59%) (Fig. 3a). In the CE group, Firmicutes Chen et al. Ann Clin Microbiol Antimicrob (2023) 22:4 Page 4 of 10 group cluster 1 2 CE non−CE Unknown Bacteria 0.2 Lactobasillus 0.0 −0.2 0.00.5 1.0 PC1 (79.51%) Fig. 1 a The α-diversity of the uterine microbiota in the CE and non-CE groups was shown by the Shannon–Wiener index at the genus level. The red bar stands for the CE group and the blue bar stands for the non-CE group. * denotes P < 0.05. b The non-supervised partitioning around medoids (PAM) clustering results of the samples from CE (circle) and non-CE groups (triangle) (Bacillota) was the phylum with the highest abundance Prevotella (0.58%), Cutibacterium (0.57%), Deinococcus but could not be identified as dominant since its relative (0.50%), Brevundimonas (0.50%), Mesorhizobium (0.46%), abundance (49.92%) was below 50%. The second abun - Acidibacter (0.29%), Peptoniphilus (0.09%) and others dant phylum was Proteobacteria, accounting for 37.19%, (14.02%) (Fig.  4a). In CE group, there was no dominant which was significantly higher than that in the non-CE genus, and Lactobacillus had the highest abundance, up group. The following abundant phyla were Actinobac - to 40.88%. Non-Lactobacillus genera  were Pseudomonas teriota (5.98%), Deinococcota (1.62%), Cyanobacteria (8.10%), Methylobacterium-Methylorubrum (8.06%), (1.45%), Bacteroidota (1.10%), Patescibacteria (0.86%), Staphylococcus (5.12%), Bradyrhizobium (4.12%),  Cuti- Bdellovibrionota (0.30%) and others (1.56%). Among bacterium (2.92%), Acidibacter (1.93%), Corynebac- them, the abundances of Actinobacteriota and Cyanobac- terium (1.71%), Deinococcus (1.60%), Brevundimonas teria in the CE group were significantly higher than those (1.47%), Mesorhizobium (1.22%), Peptoniphilus (1.11%), in the non-CE group (P < 0.05) (Fig.  3b). The results sug - Streptococcus (1.09%), Acinetobacter (1.08%), Prevo- gested that the abundance of Firmicutes (Bacillota) in the tella (0.36%) and others (19.22%) (Fig.  4b). Compared CE group was lower than that in the non-CE group, while with the non-CE group, the abundance of Lactobacillus the abundance of non-Firmicutes (non-Bacillota) phylum significantly decreased in the  CE group (P < 0.05), while were all higher than those in non-CE samples, demon- the abundances of non-Lactobacillus and other bacte- strating that  the decrease of Firmicutes (Bacillota) may ria increased in the  CE group but with no statistically be associated with CE. significant (P = 0.089 and 0.107, respectively). This sug - The microbial community composition could be gested an important role of Lactobacillus played in keep- grouped into three categories at the genus level, includ- ing a healthy intrauterine microbial environment that ing Lactobacillus, non-Lactobacillus (Top 15 abundant is similar to the vaginal environment. What’s more, the genera except for  Lactobacillus) and others. In the non- abundances of  Pseudomonas and Cutibacterium were CE group, Lactobacillus was identified as the dominant significantly higher in the CE group (P < 0.01), which may genus (relative abundance ≥ 50%), accounting for 64.22%. disturb the balance of the intrauterine microbiota. Non-Lactobacillus genera were Methylobacterium-Meth- ylorubrum (6.13%), Staphylococcus (4.65%), Bradyrhizo- bium (3.30%), Pseudomonas (1.65%), Corynebacterium (1.38%), Acinetobacter (0.87%), Streptococcus (0.78%), PC2 (19.58%) W1_S9 W1_S10 W1_S5 W1_S7 W1_S8 W1_S1 W3_S12 W2_S14 W4_S9 W3_S33 W3_S3 W3_S9 W3_S23 W3_S15 W4_S3 W3_S26 W3_S30 W4_S12 W2_S1 W2_S9 W2_S20 W2_S4 W2_S15 W2_S16 W2_S18 W2_S6 W2_S22 W2_S8 W2_S7 W2_S21 W2_S19 W3_S25 W3_S36 W3_S18 W3_S4 W3_S27 W3_S5 W3_S19 W4_S2 W4_S4 W3_S6 W4_S5 W3_S28 W1_S4 W3_S8 W3_S16 W2_S13 W3_S24 W4_S6 W3_S35 W1_S6 W3_S7 W3_S2 W3_S37 W3_S38 W4_S1 W3_S20 W3_S29 W3_S10 W3_S21 W4_S8 W2_S10 W2_S3 W2_S12 W2_S11 W3_S32 W1_S2 W3_S17 W3_S31 W3_S1 W4_S11 Chen  et al. Ann Clin Microbiol Antimicrob (2023) 22:4 Page 5 of 10 group group Lactobacillus CE Methylobacterium−Methylorubrum 0.8 non-CE Pseudomonas Staphylococcus Bradyrhizobium 0.6 Brevundimonas Sphingomonas Cutibacterium 0.4 Denitratisoma Atopobium Chlamydia 0.2 Mesorhizobium Acinetobacter Acidibacter Allorhizobium−Neorhizobium−Pararhizobium−Rhizobium Streptococcus Prevotella Haemophilus Veillonella Gemella Deinococcus Delftia Gardnerella Blastomonas Peptoniphilus Stenotrophomonas 0319−6G20 Comamonas Caulobacter Paracoccus Enhydrobacter Aerococcus Chloroplast Corynebacterium Pseudoxanthomonas Fig. 2 The heatmap of the microbiota in all samples at the genus level. The color from white to peony means the increasing abundance of the genus. The color bar at the top of the heatmap denotes the groups that the sample is from. Blue stands for the CE group, and red stands for the non-CE group Microbial metabolic pathways were significantly different plasma cells, its workload is noticeable. Currently, there is in the intrauterine microbiota of CE patients no unified standard for the minimum number of plasma The metabolic pathways of the intrauterine microbiota cells for the diagnosis of CE, which may lead to overdiag- were predicted based on the microbial composition. nosis [15–17]. Although CE can be diagnosed by observ- Compared with the non-CE group, the pathways involved ing the full vision of the intrauterine and finding tiny arginine and proline metabolism (P = 0.048) and retinol lesions through hysteroscopy, it can be affected by the metabolism (P = 0.049) were significantly enriched in hysteroscopic media, the clarity of the hysteroscopic field the  CE group, while the metabolism of lipid (P = 0.028) of vision, and the subjective judgment of laboratory phy- and prenyltransferases (P = 0.046) were significantly sicians [18]. In addition, non-specific CE patients cannot decreased in the CE group (Fig. 5). be diagnosed independently by hysteroscopy since most of them do not present typical hysteroscopic manifesta- Discussion tions. Additionally, the detection of pathogenic micro- Currently, the diagnostic methods for CE include organisms with traditional microbial culture methods immunohistochemical, hysteroscopy, and detection of also has some limitations, such as being time consuming, pathogenic microorganisms. CD138, a plasma cell sur- a  low detection rate, and a  high risk of contamination face-specific antigen, could be labeled by immunohis - [2, 19]. Detecting the pathogenic microorganisms using tochemical to determine the existence of plasma cells molecular methods, such as quantitative PCR, 16S rRNA in the endometrial matrix, which is the gold standard sequencing and metagenomic sequencing, are faster and for CE diagnosis. However, it is difficult to distinguish more accurate which is better than traditional cultivation using H&E staining, and relies a lot on the experiences of methods, and they have been used in clinical diagnosis of Laboratory physicians. Although CD138 immunohisto- infectious diseases, but not in CE yet. One of the reasons chemical staining can improve the detection sensitivity of is lack of  studies on elaborating the correlation between Chen et al. Ann Clin Microbiol Antimicrob (2023) 22:4 Page 6 of 10 Fig. 3 The percentage of the bacterial phylum in the uterine microbiota of the CE (a) and non-CE groups (b) CE and intrauterine microbiota which can contribute to be developed. However, the composition of intrauterine the discovery of specific microbial diagnostic  markers. microbiota has been reported differently so far due to Moreover, in view of the clinical limitations of the above the contamination from vaginal discharge that may be diagnostic methods  for CE, in addition to the fact that involved during the uterine sample collection. Hence, CE is infected with specific pathogens, new methods for this study is trying to eliminate these deficiencies by com - CE diagnosis based on explaining the microbiome should paring the distribution characteristics of the intrauterine Chen  et al. Ann Clin Microbiol Antimicrob (2023) 22:4 Page 7 of 10 Fig. 4 The percentage of the bacterial genus in the uterine microbiota of the CE (a) and non-CE groups (b) microbiota in the  CE and non-CE groups by using 16S history could be regarded as one of the independent risk rRNA sequencing technology, and further providing a factors for CE has still remained controversial issue [20]. possibility for screening the marker bacteria for diagnosis Fang et  al. found that the intrauterine bacteria popu- of CE, which will also guide clinical treatment of CE and lation in patients with chronic endometritis was more the prognosis of fertility. diverse than that in endometrial polyps patients, and There was no significant difference in age distribution a higher proportion of Prevotella was also observed in between the CE and non-CE groups in this study. Also, patients with  chronic endometritis [21]. Consistently, the results showed that there was no correlation between results in this study showed that the abundance of Prevo- pregnancy history and CE. Previous studies have shown tella in the CE group was higher than that in the non-CE that obesity, oral contraceptives, history of spontane- group. Liu et al. evaluated the intrauterine microbiota of ous abortion, premature delivery and cesarean section CE and non-CE patients on the seventh day after the lute- are not risk factors for CE. Whether induced abortion inizing hormone (LH) surge by 16S rRNA sequencing. Chen et al. Ann Clin Microbiol Antimicrob (2023) 22:4 Page 8 of 10 non-CE Fig. 5 The predicted microbial metabolism pathways of the uterine microbiota of the CE and non-CE groups. The left bar stands for the mean proportion of the pathways, and the right figure shows the difference in the pathway enriched in the two groups. Blue stands for the non-CE group, and red stands for the CE group Compared with the non-CE group, the abundance of been detected in the microbiota of endometrium, vaginal Lactobacillus in the  CE group was significantly higher, fluid and amniotic fluid in recent years [25, 26], and Cuti - while the abundance of non-Lactobacillus genera, includ- bacterium acnes was considered as a discriminant species ing Haemophilus, Bifidobacteria and Prevotella, was of the endometrium. In addition, it has been reported lower [22]. In this study, Lactobacillus was the dominant that the abundance of  Cutibacterium acnes in the endo- bacterium in the intrauterine microbiota in the non-CE metrium is decreased in healthy pregnant women [26], group, accounting for 64.22%. Hence, the pathogenesis while in our study, the abundance of Cutibacterium was of CE may be related to the decrease in the proportion significantly increased in CE  patients. Since CE is one of Lactobacillus and the increase of the proportion of of the major driving factors of infertility, the increased non-Lactobacillus, suggesting that maintaining a certain abundance of Cutibacterium may be a potentially associ- abundance of Lactobacillus in the uterine cavity is con- ated factor leading to infertility. ducive to maintaining a healthy uterine microenviron- In our study, arginine and proline metabolism of intra- ment. What’s more, among the non-Lactobacillus genera, uterine microbiota were significantly increased in the CE it was found that the abundances of  Pseudomonas and group. The disorder of the arginine metabolism can be Cutibacterium were significantly higher in the CE group attributed to the pathogenic factors of microorganisms at the genus level (P < 0.01). Although Pseudomonas has [27], which may prompt the development of CE. Also, been confirmed as  one of the dominant bacteria in the since arginine and proline metabolism in the serum and endometrial cavity [21] and not related to a significant uterine tissue has been reported to relate with endome- inflammatory immune response [23], its significantly tritis in mice [21], the increased microbial arginine and increased abundance was found in the inflammation of proline metabolism might break the homeostasis in the the upper reproductive tract, such as endometriosis [24] uterine cavity environment and further linked with the and uterine pyogenesis [14], which is consistent with pathogenesis of CE. In addition, retinol metabolism was our results. This indicated that the overgrowth of Pseu - also enriched in the microbiota of CE patients. Reti- domonas could disturb the balance and induce inflam - nol metabolism has been recognized as an irreplaceable matory reactions. But the related mechanisms still need pathway during endometrium regeneration by regulating further studies. Cutibacterium has long been considered the differentiation and apoptosis or senescence of endo - as a common skin commensal, which contributes to acne metrial cells [28, 29]. However, whether microbial retinol pathogenesis and is associated with the host immune sys- metabolism contributed to CE through endometrial cells tem through shaping the skin microbiota. Whereas, it has still needs further studies. Chen  et al. Ann Clin Microbiol Antimicrob (2023) 22:4 Page 9 of 10 JCYJ20220531093617038 and JCYJ20220530160206014) and the Scien- The innovation of this study is the use of a self-devel - tific Research Foundation of PEKING UNIVERSITY SHENZHEN HOSPITAL oped uterine sampler, which has been patented and clini- (LCYJ2021024, KYQD202100X). cally verified. The use of this uterine sampler can avoid Availability of data and materials the contamination of the secretion in the vagina and cer- The datasets generated and/or analyzed during the current study are available vical canal during uterine sampling. Using this method, in the NCBI, https:// www. ncbi. nlm. nih. gov/ biopr oject/ 839449. we have reported that distinct microbial communities were colonized in cervical canal, uterus, fallopian tubes Declarations and peritoneal fluid, differing from that of the vagina, Ethics approval and consent to participate which reflects a microbiota continuum along the female This study was performed in line with the principles of the Declaration of reproductive tract [6]. However, the sample size was Helsinki. Approval was granted by the Ethics Committee of Peking Univer- small, and the distribution and structure of CE uterine sity Shenzhen Hospital (No. 2019-064), and all participants provided written informed consent. microbiota and the bacterial  markers  need to be further verified by expanding the research cohort. Additionally, Consent for publication metagenomic sequencing technology should be applied Not applicable. to verify the function of the microbiota. Competing interests The authors declare that they have no competing interests. Conclusion Received: 29 May 2022 Accepted: 5 January 2023 In conclusion, a certain microbial community was colo- nized in the uterine cavity, with Lactobacillus as the dominant genus, while non-Lactobacillus  genera, such as Methylobacterium-Methylorubrum, Staphylococcus, References Bradyrhizobium, Pseudomonas and Corynebacterium 1. Song D, Li T-C, Zhang Y, Feng X, Xia E, Huang X, Xiao Y. 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Cicinelli E, Matteo M, Trojano G, Mitola PC, Tinelli R, Vitagliano A, Crupano of arginine, proline and retinol may be involved in the FM, Lepera A, Miragliotta G, Resta L. Chronic endometritis in patients with pathogenesis of CE. Whereas, research based on a larger unexplained infertility: prevalence and effects of antibiotic treatment on spontaneous conception. Am J Reprod Immunol. 2018;79(1): e12782. sample size should be performed and verified in further 5. Kitaya K, Matsubayashi H, Takaya Y, Nishiyama R, Yamaguchi K, Takeuchi T, study. Ishikawa T. Live birth rate following oral antibiotic treatment for chronic endometritis in infertile women with repeated implantation failure. Am J Reprod Immunol. 2017;78(5): e12719. Abbreviations 6. Chen C, Song X, Wei W, Zhong H, Dai J, Lan Z, Li F, Yu X, Feng Q, Wang Z. CE Chronic endometritis The microbiota continuum along the female reproductive tract and its IVF-ET I n vitro fertilization and embryo transfer relation to uterine-related diseases. Nat Commun. 2017;8(1):1–11. HPF High power field 7. Cicinelli E, De Ziegler D, Nicoletti R, Colafiglio G, Saliani N, Resta L, Rizzi OTUs Operational tax onomic units D, De Vito D. Chronic endometritis: correlation among hysteroscopic, PAM Partitioning around medoids histologic, and bacteriologic findings in a prospective trial with 2190 consecutive office hysteroscopies. Fertil Steril. 2008;89(3):677–84. Acknowledgements 8. Park HJ, Kim YS, Yoon TK, Lee WS. Chronic endometritis and infertility. Clin Firstly, we thank all participants for their support. We also appreciate the doc- Exp Reprod Med. 2016;43(4):185. tors and nurses from the Department of Obstetrics and Gynecology of Peking 9. Bouet P-E, El Hachem H, Monceau E, Gariépy G, Kadoch I-J, Sylvestre C. university Shenzhen hospital for assisting the research team in the clinical Chronic endometritis in women with recurrent pregnancy loss and recur- examinations and sample collection. rent implantation failure: prevalence and role of office hysteroscopy and immunohistochemistry in diagnosis. Fertil Steril. 2016;105(1):106–10. Author contributions 10. Ye Y. Identification and quantification of abundant species from pyrose - QC and WW managed the project. QC, QH, WZ and YX collected the samples. quences of 16S rRNA by consensus alignment. IEEE Int Conf Bioinformat- QC and QH analyzed data. XZ optimized the graph and performed statistical ics Biomed. 2011;2010:153–7. analysis. XZ and QC wrote the manuscript. WW directed and organized the 11. Caporaso JG, Kuczynski J, Stombaugh J, Bittinger K, Bushman FD, project and manuscript. All the authors reviewed the manuscript. All authors Costello EK, Fierer N, Peña AG, Goodrich JK, Gordon JI, et al. QIIME allows read and approved the final manuscript. analysis of high-throughput community sequencing data. Nat Methods. 2010;7(5):335–6. Funding 12. Bolyen E, Rideout JR, Dillon MR, Bokulich NA, Abnet CC, Al-Ghalith This work was supported by Shenzhen Science and Technology Innovation GA, Alexander H, Alm EJ, Arumugam M, Asnicar F, et al. Reproducible, Committee Technical Research Project (Grant No. JCYJ20190809144801670, Chen et al. Ann Clin Microbiol Antimicrob (2023) 22:4 Page 10 of 10 interactive, scalable and extensible microbiome data science using QIIME 2. Nat Biotechnol. 2019;37(8):852–7. 13 Quast C, Pruesse E, Yilmaz P, Gerken J, Schweer T, Yarza P, Peplies J, Glöck- ner FO. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res. 2013;41(D1):D590-6. 14. Parks DH, Tyson GW, Hugenholtz P, Beiko RG. STAMP: statistical analysis of taxonomic and functional profiles. Bioinformatics. 2014;30(21):3123–4. 15. Kasius J, Broekmans F, Sie-Go D, Bourgain C, Eijkemans M, Fauser B, Dev- roey P, Fatemi H. The reliability of the histological diagnosis of endometri- tis in asymptomatic IVF cases: a multicenter observer study. Hum Reprod. 2012;27(1):153–8. 16. McQueen DB, Perfetto CO, Hazard FK, Lathi RB. Pregnancy outcomes in women with chronic endometritis and recurrent pregnancy loss. Fertil Steril. 2015;104(4):927–31. 17. Cicinelli E, De Ziegler D, Nicoletti R, Tinelli R, Saliani N, Resta L, Bellavia M, De Vito D. Poor reliability of vaginal and endocervical cultures for evaluating microbiology of endometrial cavity in women with chronic endometritis. Gynecol Obstet Invest. 2009;68(2):108–15. 18 Cicinelli E, Vitagliano A, Kumar A, Lasmar RB, Bettocchi S, Haimovich S, Kitaya K, de Ziegler D, Simon C, Moreno I. Unified diagnostic criteria for chronic endometritis at fluid hysteroscopy: proposal and reliability evalu- ation through an international randomized-controlled observer study. Fert Ster. 2019;112(1):162–73. 19. Vitagliano A, Saccardi C, Noventa M, Sardo ADS, Saccone G, Cicinelli E, Pizzi S, Andrisani A, Litta PS. Eec ff ts of chronic endometritis therapy on in vitro fertilization outcome in women with repeated implantation fail- ure: a systematic review and meta-analysis. Fert Ster. 2018;110(1):103–12. 20. Chen Y-q, Fang R-l, Luo Y-n, Luo C-q. Analysis of the diagnostic value of CD138 for chronic endometritis, the risk factors for the pathogenesis of chronic endometritis and the effect of chronic endometritis on preg- nancy: a cohort study. BMC Womens Health. 2016;16(1):1–7. 21. Fang R-L, Chen L-X, Shu W-S, Yao S-Z, Wang S-W, Chen Y-Q. Barcoded sequencing reveals diverse intrauterine microbiomes in patients suffering with endometrial polyps. Am J Transl Res. 2016;8(3):1581. 22. Liu Y, Ko EY-L, Wong KK-W, Chen X, Cheung W-C, Law TS-M, Chung JP-W, Tsui SK-W, Li T-C, Chim SS-C. Endometrial microbiota in infertile women with and without chronic endometritis as diagnosed using a quantitative and reference range-based method. Fert Ster. 2019;112(4):707–17. 23 Mitchell CM, Haick A, Nkwopara E, Garcia R, Rendi M, Agnew K, Fredricks DN, Eschenbach D. Colonization of the upper genital tract by vagi- nal bacterial species in nonpregnant women. Am J Obstet Gynecol. 2015;212(5):611. 24. Wei W, Zhang X, Tang H, Zeng L, Wu R. Microbiota composition and distribution along the female reproductive tract of women with endome- triosis. Ann Clin Microbiol Antimicrob. 2020;19(1):15. 25. He Q, Kwok L-Y, Xi X, Zhong Z, Ma T, Xu H, Meng H, Zhao F, Zhang H. The meconium microbiota shares more features with the amniotic fluid microbiota than the maternal fecal and vaginal microbiota. Gut Microbes. 2020;12(1):1794266. 26. Riganelli L, Iebba V, Piccioni M, Illuminati I, Bonfiglio G, Neroni B, Calvo L, Gagliardi A, Levrero M, Merlino L. Structural variations of vaginal and endometrial microbiota: hints on female infertility. Front Cell Infect Micro- biol. 2020;10:350. 27. E3S web of conferences: 2021 EDP sciences; 2021: 03017. 28 Kuroda K. Impaired endometrial function and unexplained recurrent pregnancy loss. Hypertens Res Pregnancy. 2019. https:// doi. org/ 10. 4390/ jsshp. HRP20 18- 012. Re Read ady y to to submit y submit your our re researc search h ? Choose BMC and benefit fr ? Choose BMC and benefit from om: : 29. Mao Y, Wang M, Xiong Y, Wen X, Zhang M, Ma L, Zhang Y. 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The alteration of intrauterine microbiota in chronic endometritis patients based on 16S rRNA sequencing analysis

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10.1186/s12941-023-00556-4
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Abstract

Background Chronic endometritis (CE) is a disease of continuous and subtle inflammation occurring in the endome - trial stromal area, which is often asymptomatic or present with non-specific clinical symptoms. Methods This study investigated the composition and distribution of the intrauterine microbiota of 71 patients who underwent hysteroscopy during the routine clinical inspection of infertility. Among them, patients who were diag- nosed with chronic endometritis (CE) were allocated into CE group (n = 29) and others into non-CE group (n = 42). There was no significant difference in average age between the two groups (P = 0.19). Uterine flushing fluid was col- lected by the self-developed cervical trocar uterine cavity sampler and 16S rRNA sequencing was performed. Results The alpha diversity in the CE group was significantly higher than that in the non-CE group (P < 0.05). Firmi- cutes (newly named Bacillota) were the dominant phylum in the non-CE group (72.23%), while their abundance was much lower in the CE group (49.92%), but there was no statistically significant difference between the two groups. The abundances of Actinobacteriota and Cyanobacteria in the CE group were significantly higher than those in the non-CE group (P < 0.05). At the genus level, the abundance of Lactobacillus dominated in all samples, which presented a significantly lower abundance in the CE group (40.88%) than that in the non-CE group (64.22%) (P < 0.05). Correspondingly, the abundance of non-Lactobacillus was higher in the CE group, among which Pseudomonas and Cutibacterium increased significantly (P < 0.01). Moreover, compared with the non-CE group, the pathways involved in arginine and proline metabolism and retinol metabolism were significantly enriched in the CE group (P < 0.05), while the metabolism of lipid and prenyltransferases were significantly decreased in the CE group (P < 0.05). Conclusions A certain microbial community was colonized in the uterine cavity, which was dominated by Lactoba- cillus. The structure and distribution of intrauterine microbiota in the CE group were different from those in the non- CE group by showing a lower abundance of Lactobacillus, and a significantly higher abundance of Pseudomonas and Cutibacterium. Additionally, the microbial metabolism was altered in the CE group. This study elaborated the alteration of intrauterine microbiota in CE patients, which may contribute to the diagnosis of CE and provide a reference for antibiotic treatment of CE. Keywords Chronic endometritis, Intrauterine microbiota, 16S rRNA sequencing, Firmicutes (Bacillota), Lactobacillus Qing Chen, Xiaowei Zhang and Qicai Hu contributed equally to this work Hospital, Shenzhen 518036, P. R. China and share first authorship. Institute of Obstetrics and Gynecology, Shenzhen PKU-HKUST Medical Center, Shenzhen 518036, P. R. China *Correspondence: Shenzhen Key Laboratory on Technology for Early Diagnosis of Major Weixia Wei Gynecologic Diseases, Shenzhen 518036, P. R. China weixwei_2013@126.com Department of Obstetrics and Gynecology, Peking University Shenzhen © The Author(s) 2023. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http:// creat iveco mmons. org/ licen ses/ by/4. 0/. The Creative Commons Public Domain Dedication waiver (http:// creat iveco mmons. org/ publi cdoma in/ zero/1. 0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Chen et al. Ann Clin Microbiol Antimicrob (2023) 22:4 Page 2 of 10 were  diagnosed with infertility. The exclusion criteria Background were as follows: (1) patients with acute and chronic infec- Chronic endometritis (CE) is a disease of continuous and tious diseases, diabetes, cardiovascular diseases, autoim- subtle inflammation occurred in the endometrial stro - mune diseases, thyroid diseases and mental diseases; (2) mal area, which is often asymptomatic or present with patients who  have not received contraceptive or steroid non-specific clinical symptoms, such as pelvic pain, dys - treatment within six months and have not received sys- functional uterine bleeding, dyspareunia, vaginitis, etc. temic antibiotics within three months. This study was Studies have shown that CE is associated with infertil- approved by the Ethics Committee of Peking University ity, repeated abortion and repeated implant failure [1–3]. Shenzhen Hospital (No. 2019–064), and all participants As a result, most of the CE cases were diagnosed by the provided written informed consent. routine examination of infertility patients, and the preva- lence rate is as high as 67%. Currently, microbial infec- Sampling and hysteroscopic examination tion is regarded as one of the main causes of CE [1, 2]. During the surgery, the vulvovaginal was sterilized rou- Previous studies have confirmed that the administration tinely after intravenous general anesthesia, and then a of antibiotics is an effective treatment method for CE disposable sterile vaginal speculum was inserted into the which can improve fertility outcomes significantly [4, 5]. vagina. The self-developed transcervical cannula uterine With the rapid development of sequencing technology, cavity sampler (Patent Number: ZL 2018 2 1945014.0) more accurate molecular technology has been used for was used to avoid the contamination of vaginal and the diagnosis of CE toward pathogenic microorganism cervical secretions. Firstly, a disposable sterile external detection. On the other hand, with the improvement of cannula was placed in the cervical canal. Secondly, we intrauterine sampling technology, the traditional concept connected a uterine cavity sampling catheter to a 10  ml of sterile uterine cavity has been broken [6]. It has been syringe, which was pre-injected with 3  ml sterile saline, elaborated that a complex bacterial community was colo- and inserted into the cannula. After injecting the saline nized in the uterine cavity. Although the biomass of the for 1  min, the solution was extracted by turning the community is relatively low, they keep a balanced intrau- uterine cavity clockwise for a circle. Then, the sampling terine microenvironment through bacterial metabolisms catheter was returned back to the cannula and removed and interaction. The pathogenic invasion may disrupt the together. Finally, the sample was injected into a sterile balance, shape the microbial community, and may further EP tube, and stored in a –  80  °C refrigerator. Also, the cause endometritis. However, rare studies were focused uterine manifestations and endometrial biopsy were on the specific characteristics of the disordered micro - described according to the criteria of hysteroscopy for biota in the uterine cavity of CE patients. An explanation CE diagnosis [7]. of microbial community based on a large sample size will contribute to the precise diagnosis and treatment of CE. Histological analysis and immunohistochemistry In this study, 16S rRNA gene sequencing technology Endometrial samples were fixed in neutral formalin was used to study the microbiota in the uterine cavity of and embedded in paraffin for histological analysis and infertile patients  with CE. The community composition immunohistochemistry. All biopsy blocks were serially and distribution were characterized to provide a basis for sectioned at a thickness of 3–4 μm and incubated with improving the diagnosis rate of CE and guiding the selec- mouse anti-human monoclonal CD138 antibody (Biocare tion of antibiotic treatment for CE patients. Medical, Concord, CA, USA) and the secondary anti- body used was a labeled polymer horseradish peroxidase Methods anti-mouse antibody (Maixin, Fuzhou, China) following Participates the protocol. The number of CD138+ cells more than 4/ Patients who underwent hysteroscopic surgery for the HPF + was diagnosed as CE [7–9]. routine infertility examination at Peking University Shen- zhen Hospital  (Shenzhen, China) between January 2019 DNA extraction and 16S rRNA amplicon sequencing and December 2020 were recruited in this study. Among We sequenced the samples from cervix samples by them, the patients who did not receive vaginal medica- amplicon sequencing of partial 16S rRNA gene [10]. The tion and had no sexual behaviors within 7 days after men- genomic DNA from samples was extracted by QI Aamp struation, and met the following inclusion and exclusion DNA Mini Kit (Qiagen, Hilden, Germany). The extracted criteria were informed and enrolled. The inclusion crite - product was used as a template to amplify the 16S rRNA ria were as follows: (1) patients who under went in vitro V4 region after passing the quality control of nanodrop fertilization and embryo transfer (IVF-ET) and failed no (Thermo  Fisher Scientific, Waltham, MA, USA), Qubit less than one time; (2) patients who experienced sponta- 3.0 (Invitrogen, Carlsbad, CA, USA), and agarose gel neous abortion no less than two times; (3) patients who Chen  et al. Ann Clin Microbiol Antimicrob (2023) 22:4 Page 3 of 10 electrophoresis. The V4 region of the 16S rRNA genes not associated with CE. In addition, among all the par- was amplified by PCR with universal primers V4-515F ticipants, 21 IVF-ET failure cases, 4 recurrent abor- (5ʹ-GTG CCA GCMGCC GCG GTAA-3ʹ) and 806R (5ʹ- tion patients, 4 uterine malformation patients, and 38 GGA CTA CHVGGG TWT CTAAT -3ʹ). After the PCR cases  with the previous history of gynecological surgery product was detected and purified by agarose gel electro - were included, and they all presented no significant dif - phoresis and the concentration was qualified, the library ference between the CE and non-CE groups. has obtained after polyadenylation. The Qubit 3.0  Fluo - rometer and Agilent 2100 Analyzer were used for quality A significantly higher intrauterine microbial α‑diversity control of the constructed library. Subsequently, the total was presented in CE patients DNA was sequenced by the Illumina Mini Seq platform The α-diversity of the uterine microbiota was calcu - for pair-end 300 bp sequencing. lated by Shannon–Wiener index at the genus level. The results showed that the microbial α-diversity in uter- Bioinformatic analysis ine cavity in the  CE group was significantly higher than The newly generated raw sequencing data were processed that in the non-CE group (P < 0.05) (Fig. 1a). Non-super- for quality control using the FASTX toolkit. QIIME2 vised partitioning around medoids (PAM) algorithm software was used to remove sequenced primers and was invited to explain the β-diversity of the intrauterine barcodes, obtain chimeric artifacts, calculate  Bray–Cur- microbiota of two groups (Fig.  1b). The result showed tis distance matrix construction, and pick Operational that most of the samples from CE and Non-CE groups Taxonomic Units (OTUs) [11, 12]. The sequences of the were overlapped and not separated clearly. The first remaining libraries were grouped into OTUs based on principal component (PC1), mainly contributed by Lac- 97% similarity using the UCLUST program. The seeded tobacillus, provided some non-CE samples  with more sequences of each OTU were chosen for taxonomic clas- positive values. This indicated that Lactobacillus might sification against the Silva 138 SSURef NR99 full-length be a potential biomarker for distinguishing CE from non- sequences [13] by the UCLUST taxonomy assigner. The CE samples. For the second principal component (PC2), relative abundance profiles of the main phylum and genus mainly driven by unknown bacteria, CE and non-CE sam- were quantified. STAMP software was invited to predict ples were mixed. Although CE and non-CE samples were the functional profiles of the microbial communities [14]. resided significantly different microbial communities, the key taxa were still unclear. Techniques with higher Statistical analysis resolution, such as metagenomic sequencing or whole SPSS  22.0 software was used for statistical analysis. The genome sequencing, and even the cultural methods could continuous variable data were confirmed as a normal dis - be more appropriate options to investigate the specific tribution before T-test was applied. The categorical vari - genus/species in further studies. The Wilcoxon test result able data were presented as percentages and the χ2 test showed P > 0.05, suggesting that there was no significant was used. P < 0.05 was considered statistically significant. difference between the community composition of intra - uterine microbiota in CE and non-CE groups. Results No significant difference was found in the clinical The intrauterine microbial composition and abundance characteristics between CE and non‑CE groups were different in CE patients A total of 71 participants were included, with an aver- In general, according to the annotation and abundance age age of 31.77 ± 3.88  years. Among them, 29 cases at the genus level, Lactobacillus was the most abundant with chronic endometritis (CE group) and 42 cases of genus in all samples. It was followed by Pseudomonas, non-chronic endometritis (non-CE group) were iden- Methylobacterium, Staphylococcus, and Proteobacteria in tified according to the results of  histophiological and order of abundance. However, the samples from the  CE immunohistochemical results. The age of the patients and non-CE groups could not be well-clustered into two in the  CE and non-CE groups was 32.11 ± 4.46 and groups (Fig. 2) indicating a similar composition of intrau- 32.33 ± 3.66  years, respectively, and there was no differ - terine microbiota in CE and non-CE participants. ence in age between the two groups (P = 0.19). At the phylum level, Firmicutes (Bacillota) domi- Among the 71 enrolled participants, 34 women had no nated in the non-CE group (identified as relative abun - history of pregnancy and delivery, including 16 CE cases dance ≥ 50%), accounting for 72.23% and followed by and 18 non-CE cases, while there were  37 patients with Proteobacteria (19.36%), Actinobacteriota (3.75%), Bacte- pregnancy histories, including 13 CE cases and 24 non- roidota (1.71%), Deinococcota (0.50%), Bdellovibrionota CE cases. The Chi-square test (Chi-square value = 1.043, (0.49%), Patescibacteria (0.25%), Cyanobacteria (0.10%) P = 0.307) indicated that the history of pregnancy was and others (1.59%) (Fig. 3a). In the CE group, Firmicutes Chen et al. Ann Clin Microbiol Antimicrob (2023) 22:4 Page 4 of 10 group cluster 1 2 CE non−CE Unknown Bacteria 0.2 Lactobasillus 0.0 −0.2 0.00.5 1.0 PC1 (79.51%) Fig. 1 a The α-diversity of the uterine microbiota in the CE and non-CE groups was shown by the Shannon–Wiener index at the genus level. The red bar stands for the CE group and the blue bar stands for the non-CE group. * denotes P < 0.05. b The non-supervised partitioning around medoids (PAM) clustering results of the samples from CE (circle) and non-CE groups (triangle) (Bacillota) was the phylum with the highest abundance Prevotella (0.58%), Cutibacterium (0.57%), Deinococcus but could not be identified as dominant since its relative (0.50%), Brevundimonas (0.50%), Mesorhizobium (0.46%), abundance (49.92%) was below 50%. The second abun - Acidibacter (0.29%), Peptoniphilus (0.09%) and others dant phylum was Proteobacteria, accounting for 37.19%, (14.02%) (Fig.  4a). In CE group, there was no dominant which was significantly higher than that in the non-CE genus, and Lactobacillus had the highest abundance, up group. The following abundant phyla were Actinobac - to 40.88%. Non-Lactobacillus genera  were Pseudomonas teriota (5.98%), Deinococcota (1.62%), Cyanobacteria (8.10%), Methylobacterium-Methylorubrum (8.06%), (1.45%), Bacteroidota (1.10%), Patescibacteria (0.86%), Staphylococcus (5.12%), Bradyrhizobium (4.12%),  Cuti- Bdellovibrionota (0.30%) and others (1.56%). Among bacterium (2.92%), Acidibacter (1.93%), Corynebac- them, the abundances of Actinobacteriota and Cyanobac- terium (1.71%), Deinococcus (1.60%), Brevundimonas teria in the CE group were significantly higher than those (1.47%), Mesorhizobium (1.22%), Peptoniphilus (1.11%), in the non-CE group (P < 0.05) (Fig.  3b). The results sug - Streptococcus (1.09%), Acinetobacter (1.08%), Prevo- gested that the abundance of Firmicutes (Bacillota) in the tella (0.36%) and others (19.22%) (Fig.  4b). Compared CE group was lower than that in the non-CE group, while with the non-CE group, the abundance of Lactobacillus the abundance of non-Firmicutes (non-Bacillota) phylum significantly decreased in the  CE group (P < 0.05), while were all higher than those in non-CE samples, demon- the abundances of non-Lactobacillus and other bacte- strating that  the decrease of Firmicutes (Bacillota) may ria increased in the  CE group but with no statistically be associated with CE. significant (P = 0.089 and 0.107, respectively). This sug - The microbial community composition could be gested an important role of Lactobacillus played in keep- grouped into three categories at the genus level, includ- ing a healthy intrauterine microbial environment that ing Lactobacillus, non-Lactobacillus (Top 15 abundant is similar to the vaginal environment. What’s more, the genera except for  Lactobacillus) and others. In the non- abundances of  Pseudomonas and Cutibacterium were CE group, Lactobacillus was identified as the dominant significantly higher in the CE group (P < 0.01), which may genus (relative abundance ≥ 50%), accounting for 64.22%. disturb the balance of the intrauterine microbiota. Non-Lactobacillus genera were Methylobacterium-Meth- ylorubrum (6.13%), Staphylococcus (4.65%), Bradyrhizo- bium (3.30%), Pseudomonas (1.65%), Corynebacterium (1.38%), Acinetobacter (0.87%), Streptococcus (0.78%), PC2 (19.58%) W1_S9 W1_S10 W1_S5 W1_S7 W1_S8 W1_S1 W3_S12 W2_S14 W4_S9 W3_S33 W3_S3 W3_S9 W3_S23 W3_S15 W4_S3 W3_S26 W3_S30 W4_S12 W2_S1 W2_S9 W2_S20 W2_S4 W2_S15 W2_S16 W2_S18 W2_S6 W2_S22 W2_S8 W2_S7 W2_S21 W2_S19 W3_S25 W3_S36 W3_S18 W3_S4 W3_S27 W3_S5 W3_S19 W4_S2 W4_S4 W3_S6 W4_S5 W3_S28 W1_S4 W3_S8 W3_S16 W2_S13 W3_S24 W4_S6 W3_S35 W1_S6 W3_S7 W3_S2 W3_S37 W3_S38 W4_S1 W3_S20 W3_S29 W3_S10 W3_S21 W4_S8 W2_S10 W2_S3 W2_S12 W2_S11 W3_S32 W1_S2 W3_S17 W3_S31 W3_S1 W4_S11 Chen  et al. Ann Clin Microbiol Antimicrob (2023) 22:4 Page 5 of 10 group group Lactobacillus CE Methylobacterium−Methylorubrum 0.8 non-CE Pseudomonas Staphylococcus Bradyrhizobium 0.6 Brevundimonas Sphingomonas Cutibacterium 0.4 Denitratisoma Atopobium Chlamydia 0.2 Mesorhizobium Acinetobacter Acidibacter Allorhizobium−Neorhizobium−Pararhizobium−Rhizobium Streptococcus Prevotella Haemophilus Veillonella Gemella Deinococcus Delftia Gardnerella Blastomonas Peptoniphilus Stenotrophomonas 0319−6G20 Comamonas Caulobacter Paracoccus Enhydrobacter Aerococcus Chloroplast Corynebacterium Pseudoxanthomonas Fig. 2 The heatmap of the microbiota in all samples at the genus level. The color from white to peony means the increasing abundance of the genus. The color bar at the top of the heatmap denotes the groups that the sample is from. Blue stands for the CE group, and red stands for the non-CE group Microbial metabolic pathways were significantly different plasma cells, its workload is noticeable. Currently, there is in the intrauterine microbiota of CE patients no unified standard for the minimum number of plasma The metabolic pathways of the intrauterine microbiota cells for the diagnosis of CE, which may lead to overdiag- were predicted based on the microbial composition. nosis [15–17]. Although CE can be diagnosed by observ- Compared with the non-CE group, the pathways involved ing the full vision of the intrauterine and finding tiny arginine and proline metabolism (P = 0.048) and retinol lesions through hysteroscopy, it can be affected by the metabolism (P = 0.049) were significantly enriched in hysteroscopic media, the clarity of the hysteroscopic field the  CE group, while the metabolism of lipid (P = 0.028) of vision, and the subjective judgment of laboratory phy- and prenyltransferases (P = 0.046) were significantly sicians [18]. In addition, non-specific CE patients cannot decreased in the CE group (Fig. 5). be diagnosed independently by hysteroscopy since most of them do not present typical hysteroscopic manifesta- Discussion tions. Additionally, the detection of pathogenic micro- Currently, the diagnostic methods for CE include organisms with traditional microbial culture methods immunohistochemical, hysteroscopy, and detection of also has some limitations, such as being time consuming, pathogenic microorganisms. CD138, a plasma cell sur- a  low detection rate, and a  high risk of contamination face-specific antigen, could be labeled by immunohis - [2, 19]. Detecting the pathogenic microorganisms using tochemical to determine the existence of plasma cells molecular methods, such as quantitative PCR, 16S rRNA in the endometrial matrix, which is the gold standard sequencing and metagenomic sequencing, are faster and for CE diagnosis. However, it is difficult to distinguish more accurate which is better than traditional cultivation using H&E staining, and relies a lot on the experiences of methods, and they have been used in clinical diagnosis of Laboratory physicians. Although CD138 immunohisto- infectious diseases, but not in CE yet. One of the reasons chemical staining can improve the detection sensitivity of is lack of  studies on elaborating the correlation between Chen et al. Ann Clin Microbiol Antimicrob (2023) 22:4 Page 6 of 10 Fig. 3 The percentage of the bacterial phylum in the uterine microbiota of the CE (a) and non-CE groups (b) CE and intrauterine microbiota which can contribute to be developed. However, the composition of intrauterine the discovery of specific microbial diagnostic  markers. microbiota has been reported differently so far due to Moreover, in view of the clinical limitations of the above the contamination from vaginal discharge that may be diagnostic methods  for CE, in addition to the fact that involved during the uterine sample collection. Hence, CE is infected with specific pathogens, new methods for this study is trying to eliminate these deficiencies by com - CE diagnosis based on explaining the microbiome should paring the distribution characteristics of the intrauterine Chen  et al. Ann Clin Microbiol Antimicrob (2023) 22:4 Page 7 of 10 Fig. 4 The percentage of the bacterial genus in the uterine microbiota of the CE (a) and non-CE groups (b) microbiota in the  CE and non-CE groups by using 16S history could be regarded as one of the independent risk rRNA sequencing technology, and further providing a factors for CE has still remained controversial issue [20]. possibility for screening the marker bacteria for diagnosis Fang et  al. found that the intrauterine bacteria popu- of CE, which will also guide clinical treatment of CE and lation in patients with chronic endometritis was more the prognosis of fertility. diverse than that in endometrial polyps patients, and There was no significant difference in age distribution a higher proportion of Prevotella was also observed in between the CE and non-CE groups in this study. Also, patients with  chronic endometritis [21]. Consistently, the results showed that there was no correlation between results in this study showed that the abundance of Prevo- pregnancy history and CE. Previous studies have shown tella in the CE group was higher than that in the non-CE that obesity, oral contraceptives, history of spontane- group. Liu et al. evaluated the intrauterine microbiota of ous abortion, premature delivery and cesarean section CE and non-CE patients on the seventh day after the lute- are not risk factors for CE. Whether induced abortion inizing hormone (LH) surge by 16S rRNA sequencing. Chen et al. Ann Clin Microbiol Antimicrob (2023) 22:4 Page 8 of 10 non-CE Fig. 5 The predicted microbial metabolism pathways of the uterine microbiota of the CE and non-CE groups. The left bar stands for the mean proportion of the pathways, and the right figure shows the difference in the pathway enriched in the two groups. Blue stands for the non-CE group, and red stands for the CE group Compared with the non-CE group, the abundance of been detected in the microbiota of endometrium, vaginal Lactobacillus in the  CE group was significantly higher, fluid and amniotic fluid in recent years [25, 26], and Cuti - while the abundance of non-Lactobacillus genera, includ- bacterium acnes was considered as a discriminant species ing Haemophilus, Bifidobacteria and Prevotella, was of the endometrium. In addition, it has been reported lower [22]. In this study, Lactobacillus was the dominant that the abundance of  Cutibacterium acnes in the endo- bacterium in the intrauterine microbiota in the non-CE metrium is decreased in healthy pregnant women [26], group, accounting for 64.22%. Hence, the pathogenesis while in our study, the abundance of Cutibacterium was of CE may be related to the decrease in the proportion significantly increased in CE  patients. Since CE is one of Lactobacillus and the increase of the proportion of of the major driving factors of infertility, the increased non-Lactobacillus, suggesting that maintaining a certain abundance of Cutibacterium may be a potentially associ- abundance of Lactobacillus in the uterine cavity is con- ated factor leading to infertility. ducive to maintaining a healthy uterine microenviron- In our study, arginine and proline metabolism of intra- ment. What’s more, among the non-Lactobacillus genera, uterine microbiota were significantly increased in the CE it was found that the abundances of  Pseudomonas and group. The disorder of the arginine metabolism can be Cutibacterium were significantly higher in the CE group attributed to the pathogenic factors of microorganisms at the genus level (P < 0.01). Although Pseudomonas has [27], which may prompt the development of CE. Also, been confirmed as  one of the dominant bacteria in the since arginine and proline metabolism in the serum and endometrial cavity [21] and not related to a significant uterine tissue has been reported to relate with endome- inflammatory immune response [23], its significantly tritis in mice [21], the increased microbial arginine and increased abundance was found in the inflammation of proline metabolism might break the homeostasis in the the upper reproductive tract, such as endometriosis [24] uterine cavity environment and further linked with the and uterine pyogenesis [14], which is consistent with pathogenesis of CE. In addition, retinol metabolism was our results. This indicated that the overgrowth of Pseu - also enriched in the microbiota of CE patients. Reti- domonas could disturb the balance and induce inflam - nol metabolism has been recognized as an irreplaceable matory reactions. But the related mechanisms still need pathway during endometrium regeneration by regulating further studies. Cutibacterium has long been considered the differentiation and apoptosis or senescence of endo - as a common skin commensal, which contributes to acne metrial cells [28, 29]. However, whether microbial retinol pathogenesis and is associated with the host immune sys- metabolism contributed to CE through endometrial cells tem through shaping the skin microbiota. Whereas, it has still needs further studies. Chen  et al. Ann Clin Microbiol Antimicrob (2023) 22:4 Page 9 of 10 JCYJ20220531093617038 and JCYJ20220530160206014) and the Scien- The innovation of this study is the use of a self-devel - tific Research Foundation of PEKING UNIVERSITY SHENZHEN HOSPITAL oped uterine sampler, which has been patented and clini- (LCYJ2021024, KYQD202100X). cally verified. The use of this uterine sampler can avoid Availability of data and materials the contamination of the secretion in the vagina and cer- The datasets generated and/or analyzed during the current study are available vical canal during uterine sampling. Using this method, in the NCBI, https:// www. ncbi. nlm. nih. gov/ biopr oject/ 839449. we have reported that distinct microbial communities were colonized in cervical canal, uterus, fallopian tubes Declarations and peritoneal fluid, differing from that of the vagina, Ethics approval and consent to participate which reflects a microbiota continuum along the female This study was performed in line with the principles of the Declaration of reproductive tract [6]. However, the sample size was Helsinki. Approval was granted by the Ethics Committee of Peking Univer- small, and the distribution and structure of CE uterine sity Shenzhen Hospital (No. 2019-064), and all participants provided written informed consent. microbiota and the bacterial  markers  need to be further verified by expanding the research cohort. Additionally, Consent for publication metagenomic sequencing technology should be applied Not applicable. to verify the function of the microbiota. Competing interests The authors declare that they have no competing interests. Conclusion Received: 29 May 2022 Accepted: 5 January 2023 In conclusion, a certain microbial community was colo- nized in the uterine cavity, with Lactobacillus as the dominant genus, while non-Lactobacillus  genera, such as Methylobacterium-Methylorubrum, Staphylococcus, References Bradyrhizobium, Pseudomonas and Corynebacterium 1. Song D, Li T-C, Zhang Y, Feng X, Xia E, Huang X, Xiao Y. 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Journal

Annals of Clinical Microbiology and AntimicrobialsSpringer Journals

Published: Jan 12, 2023

Keywords: Chronic endometritis; Intrauterine microbiota; 16S rRNA sequencing; Firmicutes (Bacillota); Lactobacillus

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