ORIGINAL RESEARCH published: 28 June 2022 doi: 10.3389/fcell.2022.937157 Seminal Microbiota of Idiopathic Infertile Patients and Its Relationship With Sperm DNA Integrity Sergio Garcia-Segura 1, Javier del Rey 1, Laia Closa 2,3, Iris Garcia-Martínez 3,4, Carlos Hobeich 3,4, Ana Belén Castel 5, Francisco Vidal 3,4,6, Jordi Benet 1, Jordi Ribas-Maynou 7,8* and Maria Oliver-Bonet 1* 1 Unit of Cell Biology and Medical Genetics, Department of Cell Biology, Physiology and Immunology, Universitat Autònoma de Barcelona (UAB), Bellaterra, Spain, 2Histocompatibility and Immunogenetics Laboratory, Banc de Sang i Teixits (BST), Barcelona, Spain, 3Medicina Transfusional, Vall d’Hebron Institut de Recerca (VHIR), Universitat Autònoma de Barcelona (UAB), Barcelona, Spain, 4Grup de Coagulopaties Congènites, Banc de Sang i Teixits (BST), Barcelona, Spain, 5Instituto de Fertilidad, Palma, Spain, 6 CIBER de Enfermedades Cardiovasculares (CIBERCV), Barcelona, Spain, 7Biotechnology of Animal and Human Reproduction (TechnoSperm), Institute of Food and Agricultural Technology, University of Girona, Girona, Spain, 8Unit of Cell Biology, Department of Biology, University of Girona, Girona, Spain The development of new biomarkers for human male infertility is crucial to improve the Edited by: Matteo Avella, diagnosis and the prognosis of this disease. Recently, seminal microbiota was shown to be Sidra Medicine, Qatar related to sperm quality parameters, suggesting an effect in human fertility and postulating Reviewed by: it as a biomarker candidate. However, its relationship to sperm DNA integrity has not been Sundus Javed, COMSATS University, Islamabad studied yet. The aim of the present study is to characterize the seminal microbiota of a Campus, Pakistan western Mediterranean population and to evaluate its relationship to sperm chromatin Charles Muller, integrity parameters, and oxidative stress. For that purpose, 14 samples from sperm University of Washington, United States donors and 42 samples from infertile idiopathic patients were obtained and were analyzed *Correspondence: to assess the composition of the microbiota through full-length 16S rRNA gene Jordi Ribas-Maynou sequencing (Illumina MiSeq platform). Microbial diversity and relative abundances were jordi.ribasmaynou@udg.edu Maria Oliver-Bonet compared to classic sperm quality parameters (macroscopic semen parameters, motility, maria.oliver@uab.cat morphology and concentration), chromatin integrity (global DNA damage, double- stranded DNA breaks and DNA protamination status) and oxidative stress levels Specialty section: This article was submitted to (oxidation-reduction potential). The seminal microbiota observed of these samples Molecular and Cellular Reproduction, belonged to the phyla Firmicutes, Proteobacteria, Actinobacteria and Bacteroidetes. a section of the journal The most abundant genera were Finegoldia, Peptoniphilus, Anaerococcus, Frontiers in Cell and Developmental Biology Campylobacter, Streptococcus, Staphylococcus, Moraxella, Prevotella, Ezakiella, Received: 05 May 2022 Corynebacterium and Lactobacillus. To our knowledge, this is the first detection of Accepted: 06 June 2022 Ezakiella genus in seminal samples. Two clusters of microbial profiles were built based Published: 28 June 2022 on a clustering analysis, and specific genera were found with different frequencies in Citation: Garcia-Segura S, del Rey J, Closa L, relation to seminal quality defects. The abundances of several bacteria negatively correlate Garcia-Martínez I, Hobeich C, with the sperm global DNA fragmentation, most notably Moraxella, Brevundimonas and Castel AB, Vidal F, Benet J, Flavobacterium. The latter two were also associated with higher sperm motility and Ribas-Maynou J and Oliver-Bonet M (2022) Seminal Microbiota of Idiopathic Brevundimonas additionally with lower oxidative-reduction potential. Actinomycetaceae, Infertile Patients and Its Relationship Ralstonia and Paenibacillus correlated with reduced chromatin protamination status and With Sperm DNA Integrity. Front. Cell Dev. Biol. 10:937157. increased double-stranded DNA fragmentation. These effects on DNA integrity coincide in doi: 10.3389/fcell.2022.937157 many cases with the metabolism or enzymatic activities of these genera. Significant Frontiers in Cell and Developmental Biology | www.frontiersin.org 1 June 2022 | Volume 10 | Article 937157 Garcia-Segura et al. Seminal Microbiome and Sperm DNA-Integrity differences between fertile and infertile men were found in the relative presence of the Propionibacteriaceae family and the Cutibacterium, Rhodopseudomonas and Oligotropha genera, which supports its possible involvement in male fertility. Our findings sustain the hypothesis that the seminal microbiome has an effect on male fertility. Keywords: seminal microbiome, human fertility, male infertility, sperm dna damage, oxidative stress, next generation sequencing INTRODUCTION association is still limited and results show discrepancies regarding microbiome composition, which suggests a very Infertility is a multiorganism and multifactorial disease affecting high interindividual variability. Although no definitive millions of humans worldwide. The male counterpart is known to consensus has been reached as yet, several authors agree that exert an impact in about 50% of couples who fail to conceive after seminal microbiota is composed of the phyla Firmicutes, a year of regular unprotected sexual intercourse (de Kretser, 1997; Bacteroidetes, Proteobacteria and Actinobacteria (Lundy Boivin et al., 2007; Agarwal et al., 2015). Nowadays, diagnostic et al., 2020; Tomaiuolo et al., 2020; Farahani et al., 2021). assessment of male infertility is rather limited, with only the Specifically, the most commonly identified genera are assessment of sperm motility, sperm count or sperm morphology Lactobacillus, Corynebacterium, Acinetobacter, Prevotella, parameters used universally. However, about 25% of infertile men Enterococcus, Veillonella, Streptococcus, Porphyromonas, present values within the normal range for these parameters and Staphylococcus and Pelomonas (Hou et al., 2013; Weng et al., are thus considered normozoospermic. In these cases, infertility 2014; Mändar et al., 2017; Chen et al., 2018; Monteiro et al., causes usually remain undiagnosed (Poongothai et al., 2009). 2018; Baud et al., 2019; Amato et al., 2020; Yang et al., 2020; Therefore, finding new biomarkers for idiopathic male infertility Bukharin et al., 2021; Lundy et al., 2021; Okwelogu et al., 2021; is key to advancing our knowledge of the disease. Biomarkers Yao et al., 2021). would, not only lay the groundwork for the development of new The lack of agreement on the role of the seminal therapeutic strategies, but also serve as diagnostic and prognostic microbiome on male fertility is manifold. Some authors tools with predictive value in in vitro fertilization methodologies report an increase of species diversity in infertile men’s (Brincat et al., 2015). In an attempt to address this need, several semen (Rehewy et al., 1979; Mändar et al., 2017; Amato fertility biomarkers have been studied over the last decade (Kovac et al., 2020; Lundy et al., 2021), while others do not find et al., 2013; Boissière et al., 2017; Martins and Agarwal, 2019; differences between clinical groups (Jarvi et al., 1996; Hou Mehrparavar et al., 2019). Among them, the measurement of et al., 2013; Weng et al., 2014; Yang et al., 2020). Several studies oxidative stress and sperm DNA integrity have provided valuable have found that Lactobacillus, frequently described as the most information related to the balance of the seminal redox system abundant genus in semen, is less present in men with decreased and the effect of reactive oxygen species (ROS) on chromatin seminal quality, and it is especially related to motility and integrity and other sperm structures such as plasma and viscosity parameters (Weng et al., 2014; Mändar et al., 2017; mitochondrial membranes (Aitken and De Iuliis, 2010; Ribas- Monteiro et al., 2018; Baud et al., 2019). However, other Maynou and Benet, 2019; Agarwal et al., 2020). In this regard, studies have reported opposite results, showing an increase different authors have shown that increased ROS levels and the of this genus (and others such as Ureaplasma, Finegoldia and incidence of DNA damage are factors intimately related to male Anaerococcus) in asthenozoospermic and azoospermic infertility (Lewis and Simon, 2010; Aitken et al., 2014; patients (Hou et al., 2013; Chen et al., 2018; Yang et al., Pourmasumi et al., 2017; Agarwal et al., 2019). However, the 2020). A higher consensus exists regarding the genus association of these biomarkers to success rates after Prevotella, which has always been associated with a decrease intracytoplasmic sperm injection are still controversial (Ribas- in sperm quality, mainly underlain by a reduction in sperm Maynou et al., 2021). motility (Weng et al., 2014; Baud et al., 2019; Yang et al., 2020; Recent studies focused on different human diseases support Lundy et al., 2021). Finally, some genera of Proteobacteria and the essential role of the microbiome in health-disease status Actinobacteria have also been directly related to seminal (Shreiner et al., 2015; Young, 2017; Giles and Couper, 2020). hyperviscosity, oligoasthenoteratozoospermia and The development of Next Generation Sequencing (NGS) azoospermia (Weng et al., 2014; Chen et al., 2018; Monteiro techniques has allowed a deeper analysis of the microbiomes et al., 2018; Yang et al., 2020). colonizing humans (Malla et al., 2019) and, for this reason, the Despite the growing evidence supporting the association number of studies analyzing the microbiomes’ composition and between the seminal microbiome and conventional sperm relation to health and diseases has grown exponentially over the quality parameters, no studies assessing the impact of seminal last decade (Laudes et al., 2021). Similarly, seminal microbiota microbiota on sperm chromatin and oxidative stress have been dysbiosis has recently been proposed as a potential cause of published so far. Therefore, the aim of the present study was to male infertility (Altmäe et al., 2019; Koedooder et al., 2019; analyze the seminal microbiota of a western Mediterranean Lundy et al., 2020; Tomaiuolo et al., 2020; Farahani et al., 2021). population and evaluate its relationship with sperm chromatin However, the number of published studies addressing this status, oxidative stress and sperm quality. Frontiers in Cell and Developmental Biology | www.frontiersin.org 2 June 2022 | Volume 10 | Article 937157 Garcia-Segura et al. Seminal Microbiome and Sperm DNA-Integrity FIGURE 1 | Relative abundances of bacteria included in seminal microbiome from control donors and idiopathic infertile patients at genus level. The X-axis shows each individual of our cohort, and the Y-axis corresponds to the relative abundance of each taxon in percentage. Clustering-based bacterial profiles to which each individual belongs is shown above the bar-graph at phylum, family and genera levels. MATERIALS AND METHODS Conventional Sperm Quality Assessment: Concentration, Motility, Morphology, pH Sample Collection Seminal samples were collected from 56 caucasian Mediterranean and Viscosity subjects, which were classified into two groups: 14 control Prior to cryopreservation, a basic semen analysis (sperm samples from healthy normozoospermic semen donors with concentration, motility, morphology, seminal volume and pH) no infertility diagnosis and 42 samples from idiopathic was performed. For concentration and motility, 7 μl of normozoospermic infertile patients with no apparent female prewarmed (37°C) and liquefied sperm were loaded into a factor as a possible cause of the couple’s infertility. Individuals prewarmed 10 micron Leja Chamber (Leja Products B.V., under antibiotic therapy for the last 21 days were excluded. Luzemestraat, Nieuw Vennep, Netherlands). Then, videos were Demographic and health information is shown in taken at 30 frames per second using the Sperm Class Analyzer Supplementary Table S1. A specific semen collection protocol (SCA, Microptic, Barcelona, Spain) software coupled to a negative adapted from the World Health Organization (WHO) phase contrast microscope (Olympus Provis AX70, Olympus procedures (World Health Organization, 2010), which Corporation, Tokio, JP). For each sample, at least 200 included urinating and washing hands and penis with soap spermatozoa in at least five homogeneous fields were and water before masturbation into a sterile container, was evaluated, and the following parameters were recorded: sperm followed to prevent bacterial contamination of samples. concentration, percentage of motile sperm, percentage of Environmental samples were also collected from collection progressively motile sperm, percentage of non-progressive room by moving a sterile swab in the air. A seminogram was motile sperm and percentage of immotile sperm. For performed on samples from all groups according to the WHO morphology, Sperm Blue (Microptic, Barcelona, Spain) was 2010 guidelines (World Health Organization, 2010). used to stain sperm cells. Briefly, 10–15 μl were poured onto Samples were obtained after 2–5 days of sexual abstinence the slides, covered with a 22 × 22 mm coverslip and visualized from patients attending the Instituto de Fertilidad of Palma under a morphology module of the SCA software on a brightfield (Mallorca, Spain). After liquefaction at room temperature, microscope (Olympus Provis AX70). The percentage of abnormal samples were aliquoted and frozen at −20°C without sperm was assessed using Kruger strict criteria, recording cryopreservation medium, transported to the laboratory and alterations in head, midpiece, tail and cytoplasmic droplets. stored in liquid nitrogen at −196°C until further use. Informed PH indicator strips (MColorpHast, Merck, Darmstadt, consent was obtained from all donors, and the study was Germany) were used to determine the sample pH. Seminal approved by the Parc Taulí Hospital ethics committee viscosity was measured using 20 micron Leja Chambers (Leja according to the Declaration of Helsinki. Products B.V.), following a protocol previously described by Frontiers in Cell and Developmental Biology | www.frontiersin.org 3 June 2022 | Volume 10 | Article 937157 Garcia-Segura et al. Seminal Microbiome and Sperm DNA-Integrity FIGURE 2 | Microbiome profiles’ composition from clustering analysis of (A) phylum and (B) genus taxonomic levels. Clustering analysis was performed using the between-groups linkage method based on the Euclidean distance. The bar-plots show the relative abundance in percentage of the most representative bacteria of each profile. The scatter dot-plots display the alpha diversity distribution of each profile, where the Y-axis represents the Shannon index. Thin horizontal lines delimit the 95% confidence interval (CI), whereas the thick horizontal mark denotes the median value. Rijnders et al., 2007. Briefly, a standard curve relating viscosity Sperm Chromatin Evaluation and time to fill the chamber was generated using solutions with Sperm DNA Integrity different known viscosity. Seminal viscosity was then measured Global sperm DNA fragmentation analysis, including single- and by calculating the sample’s capillary filling time and results were double-stranded DNA breaks, was performed by the TUNEL and reported in centipoise (cps). Alkaline Comet assays. Double-stranded DNA breaks were also analyzed by Neutral Comet. Oxidative Stress Evaluation (MiOXSYS) For the TUNEL assay, the In Situ Cell Death Detection Kit Seminal oxidative stress was assessed by oxidation-reduction (Roche Diagnostic GmbH, Penzberg, Germany) was used, potential (ORP) measurement using the MiOXSYS system following the manufacturer’s instructions. Semen samples were (Aytu BioScience, Englewood, CO, United States) and washed three times in phosphate buffered saline solution (PBS) following the manufacturer’s instructions. Briefly, 30 μl were before adjusting the sperm concentration to 5 × 106 cells/ml. loaded onto a cassette and inserted into the apparatus, which Resuspended sperm samples were divided into three 200 µl tubes provided a relative value indicating static oxidation-reduction (positive control, negative control and test sample), fixed with 4% potential. Two replicates were conducted per sample, and the paraformaldehyde in PBS for 1 h at room temperature and then obtained average was normalized by sperm concentration (mV/ washed in PBS supplemented with 1% bovine serum albumin 106 sperm/ml) to obtain normalized static oxidation-reduction (BSA; Sigma-Aldrich, St. Louis, MO, United States). Sperm cells potential (nsORP). were permeabilized using 0.1% Triton X-100 in 0.1% sodium Frontiers in Cell and Developmental Biology | www.frontiersin.org 4 June 2022 | Volume 10 | Article 937157 Garcia-Segura et al. Seminal Microbiome and Sperm DNA-Integrity TABLE 1 | Distribution of infertile patients and donors between the two The Comet assay was performed in both alkaline and neutral microbiome profiles revealed by the clustering analysis based on the bacterial conditions, according to previously described methodology relative abundance both at the phylum and genus taxonomic levels, using the between-groups linkage method based on the Euclidean distance. (Casanovas et al., 2019). First, samples were washed and adjusted to 1 × 106 sperm/ml. Sperm cells were mixed with Phylum level Genus level low-melting-point 1% agarose in a 1:2 proportion to achieve a Cluster 1 Cluster 2 Cluster 1 Cluster 2 final agarose concentration of 0.66%. Then, a drop of the mix was allowed to gel at 4°C on an agarose-pretreated slide and an 8-mm Donors 10 4 8 6 Infertile 31 11 27 15 round coverslip was applied. Sperm nucleus decondensation was p-value 0.862 0.633 effected by incubating the slides in two consecutive lysis solutions: lysis solution one, containing 0.8 M DTT, 0.8 M Tris, 1% SDS, pH The p value for the association analysis with the Pearson’s Chi-square test is shown. The threshold for statistical significance was set at p < 0.05. = 7.5, for 30 min, and lysis solution two, containing 0.4 M DTT, 0.4 M Tris, 2 M NaCl, 50 mM EDTA, 1% Tween20, pH 7.5, for 30 min. Subsequently, for the Alkaline Comet assay slide, a citrate for 2 min in ice and then washed in PBS supplemented denaturing treatment in an alkaline solution (0.03 M NaOH with 1% BSA. A positive control was prepared by incubating the and 1 M NaCl) for 2.5 min at 4°C was performed, followed by sample in 100 IU DNAse I (Roche Diagnostic GmbH) for 10 min electrophoresis at 1 V/Cm for 4 min in 0.03 M NaOH buffer. In at 37°C while the test sample and the negative control were kept parallel, for the Neutral Comet assay slide, electrophoresis was on ice. The positive control and test sample pellets were then performed for 12.5 min at 1 V/Cm in TBE buffer with a incubated in 45 µl of labelling solution plus 5 µl of terminal subsequent wash in 0.9% NaCl solution. Finally, both slides deoxynucleotidyl transferase (TdT) enzyme (Roche Diagnostic were washed in a neutralization solution (0.04 M Tris-HCl, pH GmbH) for 1 h at 37°C in the dark, while the negative control 7.5), dehydrated in ethanol series (70, 90 and 100%) and dried followed the same procedure, with the omission of the TdT horizontally before staining with DAPI SlowFade Gold anti-fade enzyme. Finally, samples were washed twice using 1% BSA in (Invitrogen, Carlsbad, CA, United States). Samples were analyzed PBS. Pellets were resuspended in 1 ml of PBS and analyzed by and evaluated under a fluorescence microscope by a single flow cytometry. In order to detect the TUNEL-positive cells researcher to avoid intra-observer variability. Fragmented and (TUNEL+; green fluorescent cells), samples were excited with a non-fragmented spermatozoa were manually classified, using blue laser (488 nm) and the emitted fluorescence was collected criteria reported earlier (Ribas-Maynou et al., 2012), and the using a 530 ± 30 nm band-pass filter. A total of 10,000 events at percentage of sperm cells with DNA fragmentation was recorded. 200–300 cells/s were recorded on a flow cytometer (FACSCalibur; To assess and quantify the incidence of DNA breaks, both Becton Dickinson, NJ, United States), and data were processed alkaline and neutral Comets were captured under the same using CELLQUEST analysis software (Becton Dickinson). epifluorescence microscope and analyzed using Komet 7 Negative and positive controls were used to establish the analysis software (Andor Technologies, Oxford, threshold values for TUNEL+ cells and, finally, the percentage United Kingdom). The Olive Tail Moment (OTM), calculated of TUNEL+ cells was recorded. as [(Tail mean intensity–Head mean intensity) × Tail DNA/100] TABLE 2 | Comparative study of seminal and sperm parameters (Mann-Whitney’s U) between microbiome profile 1 (P1) and profile 2 (P2) at phylum and genera levels. Phylum level Genera level P1 (n = P2 (n = p-value P1 (n = P2 (n = p-value 41) 15) 35) 21) Volume (ml) 2.93 2.35 0.134 2.90 2.70 0.662 pH 8.23 8.15 0.555 8.20 8.24 0.617 Viscosity (cps) 5.75 5.35 0.483 5.63 5.59 0.626 Sperm concentration (M sperm/ml) 59.00 88.60 0.295 76.00 54.45 0.399 Sperm total number (×10^6) 199.80 174.00 0.961 177.30 160.50 0.714 Total motility (%) 49.50 62.00 0.09 49.17 61.00 0.204 Progressive motility (%) 32.66 49.58 0.221 38.00 34.99 0.978 Sperm morphology (%) 8.80 9.50 0.235 9.75 8.25 0.298 Normed sORP (mV/106 sperm/ml) 0.74 0.38 0.179 0.60 0.53 0.546 CMA3+ cells (%) 39.00 39.04 0.858 39.00 39.04 0.759 TUNEL+ cells (%) 40.46 41.30 0.685 40.75 41.79 0.879 Alkaline comet (%) 38.00 33.00 0.63 34.33 39.00 0.298 Alkaline OTM 0.87 0.80 0.767 0.86 0.86 0.431 Neutral comet (%) 65.66 65.00 0.882 65.33 66.00 0.472 Neutral OTM 0.61 0.58 0.218 0.60 0.58 0.509 Median of each parameter for each cluster is shown. The threshold for statistical significance was set at p < 0.05. Frontiers in Cell and Developmental Biology | www.frontiersin.org 5 June 2022 | Volume 10 | Article 937157 Garcia-Segura et al. Seminal Microbiome and Sperm DNA-Integrity TABLE 3 | Results from the correlation analyses between alpha diversity and samples were washed twice in PBS, permeabilized with 0.5% seminal and sperm parameters. Triton X-100, and resuspended to a sperm concentration of 107 Seminal or sperm Spearman ρ p-value cells/ml. Sperm cells were subsequently spread on a slide and air- parameter (units) dried. The slide was then incubated with 50 µl of a staining solution containing 250 μg/ml CMA3, 10 mM MgCl2, 30 mmol/L Seminal volume (ml) -0.056 0.686 pH 0.198 0.147 citric acid, 140 mmol/L Na2HPO4 at room temperature for Seminal viscosity (cps) -0.037 0.79 20 min in the dark and covered with Parafilm. Finally, the Sperm concentration (M/ml) 0.106 0.45 Parafilm was gently removed and sperm cells were Total sperm number (×106) 0.072 0.607 counterstained with DAPI SlowFade Gold antifade Total motility (%) -0.018 0.897 Progressive motility (%) 0.037 0.795 (Invitrogen), and a coverslip was applied. A total of 400 cells Sperm morphology (%) 0.089 0.567 was analyzed under an epifluorescence microscope and evaluated Normed sORP (mV/106sperm/ml) 0.08 0.575 to obtain the percentage of CMA3 positive cells, as described CMA3+ cells (%) -0.003 0.983 previously (Garcia-Segura et al., 2020). TUNEL+ cells (%) -0.146 0.292 Alkaline comet (%) -0.143 0.292 Alkaline OTM -0.064 0.642 Microbiome Analysis Neutral comet (%) 0.320 0.016 Microbiota DNA Extraction Neutral OTM 0.23 0.089 Bacterial DNA isolation from seminal samples was performed The Spearman Rho (ρ) and the associated p-value are shown. The threshold for statistical with ZymoBIOMICS DNA Microprep kit (Zymo Research, CA, significance was set at p < 0.05. Values in bold indicate nominally significant associations. EEUU) following the manufacturer’s instructions with slight modifications. In order to lyse cell walls and membranes to allow the release of DNA, a bead beating step in lysis solution was recorded for each Comet variant as an indicator of DNA was performed. Then, all supernatant was filtered in Zymo-Spin damage intensity, in arbitrary units. III-F by centrifugation at 8,000 g for 1 min and washing repeatedly in a Zymo-Spin IC-Z column to purify DNA before Sperm Chromatin Protamination Status elution. The researcher worked with sterile gloves in a horizontal (Chromomycin A3 Test) laminar flow cabinet previously sterilized with DNA-degrading Sperm chromatin protamination was assessed using the products and UV irradiation. A sterile swab was placed inside the Chromomycin A3 (CMA3, Sigma-Aldrich) test. Briefly, semen cabinet as a negative environmental control and the FIGURE 3 | Alpha diversity distribution for microbiota of donors and infertile patients. Y-axis represents the Shannon index of the groups displayed at the X-axis. Thin horizontal lines delimit the 95% confidence interval (CI), whereas the thick horizontal mark denotes the median value. Frontiers in Cell and Developmental Biology | www.frontiersin.org 6 June 2022 | Volume 10 | Article 937157 Garcia-Segura et al. Seminal Microbiome and Sperm DNA-Integrity TABLE 4 | Correlation coefficients for the abundance of identified (A) phylum, (B) family or (C) genera and basic sperm quality parameters. A PHYLUM Semen Sperm Total Progressive Normal pH Semen volume concentration motile motility (%) morphology viscosity (ml) (×10^6) sperm (%) (cps) (%) Firmicutes 0.067 −0.165 0.019 −0.118 −0.183 0.097 −0.163 Proteobacteria −0.155 0.064 −0.093 −0.062 0.255 0.027 0.124 Actinobacteria 0.035 0.084 0.020 0.225 0.016 −0.201 0.046 Tenericutes −0.101 0.079 −0.049 0.074 −0.241 −0.106 −0.019 Bacteroidetes −0.003 −0.041 0.160 0.100 −0.020 0.106 −0.003 Saccharibacteria 0.022 −0.035 −0.099 −0.031 −0.158 0.160 0.057 Deinococcus.Thermus −0.098 −0.114 0.107 0.112 −0.243 0.187 0.018 Fusobacteria −0.206 0.084 −0.019 −0.109 0.124 0.136 −0.168 Spirochaetes 0.065 −0.054 −0.128 −0.209 −0.090 0.095 −0.249 B FAMILY Semen Sperm Total Progressive Normal pH Semen volume concentration motile motility (%) morphology viscosity (ml) (×10^6) sperm (%) (%) (cps) Peptoniphilaceae −0.046 −0.069 −0.073 −0.176 0.062 0.027 −0.168 Campylobacteraceae −0.172 0.012 −0.085 −0.193 −0.139 −0.078 −0.089 Streptococcaceae 0.077 0.035 −0.059 −0.047 0.110 0.171 −0.257 Moraxellaceae 0.047 0.112 −0.166 −0.029 0.351* 0.032 0.026 Staphylococcaceae 0.086 0.094 −0.05 0.093 −0.057 −0.249 −0.088 Prevotellaceae −0.058 −0.091 0.101 0.004 0.052 0.199 0.045 Corynebacteriaceae 0.041 0.089 −0.133 0.007 0.062 −0.214 −0.161 Peptostreptococcaceae −0.088 −0.071 −0.004 −0.085 0.037 0.093 −0.053 Lactobacillaceae −0.025 0.013 0.196 0.252 −0.167 0.011 −0.097 Veillonellaceae −0.083 −0.047 0.051 −0.064 −0.024 0.031 −0.173 Mycoplasmataceae −0.038 0.027 −0.199 −0.097 −0.141 −0.185 −0.179 Oxalobacteraceae −0.085 0.1 −0.113 −0.051 0.374* 0.015 −0.126 Propionibacteriaceae 0.092 −0.156 0.097 0.290* 0.039 −0.052 0.089 Fusobacteriaceae −0.236 0.164 0.013 −0.102 0.209 0.090 −0.118 Actinomycetaceae −0.043 −0.057 0.114 −0.009 −0.120 0.037 −0.172 Burkholderiaceae 0.156 −0.21 0.021 −0.058 −0.026 0.227 −0.061 Bradyrhizobiaceae 0.184 −0.151 −0.033 0.088 −0.064 −0.051 0.005 Rhodobacteraceae 0.061 0.119 0.125 0.005 0.215 0.059 −0.023 Caulobacteraceae −0.003 0.165 0.196 0.331* −0.013 −0.157 −0.053 Bacillaceae 0.245 −0.117 0.109 0.003 −0.111 −0.035 −0.228 Porphyromonadaceae −0.044 −0.002 0.023 0.024 −0.163 0.026 −0.122 Sphingomonadaceae 0.022 −0.062 −0.291* −0.232 −0.045 0.128 −0.064 Bifidobacteriaceae 0.09 −0.013 0.293* 0.362** −0.326* 0.001 −0.19 Aerococcaceae 0.027 −0.024 0.097 0.027 −0.198 0.179 −0.167 Clostridiaceae −0.079 −0.179 0.227 0.049 −0.137 0.082 −0.031 Flavobacteriaceae −0.064 −0.032 0.107 0.173 −0.173 −0.101 −0.14 Neisseriaceae −0.098 −0.088 −0.062 −0.106 −0.019 0.345** −0.198 Deinococcaceae −0.112 −0.095 0.195 0.179 −0.384* 0.042 −0.1 Paenibacillaceae 0.245 −0.336* 0.023 −0.01 −0.202 0.080 −0.053 Bacteroidaceae −0.049 −0.075 0.098 0.058 −0.091 0.046 −0.066 Micrococcaceae −0.016 −0.019 0.064 0.033 0.040 0.068 −0.19 Lachnospiraceae −0.027 −0.341* 0.074 0.1 −0.293 0.214 −0.071 Comamonadaceae 0.163 0.01 −0.032 0.01 0.030 −0.050 −0.386** Enterobacteriaceae 0.162 −0.154 −0.039 0.073 −0.081 −0.031 −0.021 Intrasporangiaceae −0.204 0.024 0.067 0.045 0.137 −0.201 −0.095 Thermoanaerobacteraceae −0.082 −0.197 0.015 0.082 −0.140 −0.005 0.016 Pasteurellaceae 0.029 −0.189 0.035 0.104 −0.285 0.029 −0.309* Promicromonosporaceae 0.158 −0.164 −0.048 −0.039 −0.055 −0.148 −0.325* Methylobacteriaceae 0.038 −0.043 0.046 −0.093 0.145 −0.033 −0.205 Listeriaceae 0.157 0.033 0.09 −0.045 −0.022 0.152 −0.158 Erysipelotrichaceae 0.003 −0.038 0.201 0.102 −0.036 0.143 −0.106 Hungateiclostridiaceae −0.196 0.089 0.151 0.006 −0.143 0.104 −0.006 Tissierellaceae −0.035 −0.134 0.031 −0.056 −0.088 −0.160 −0.013 Steroidobacteraceae 0.256 −0.019 0.133 0.11 −0.053 0.237 −0.051 Acidiferrobacteraceae 0.199 −0.03 0.108 0.079 0.082 0.205 0.092 Erwiniaceae −0.084 −0.209 −0.038 −0.133 −0.360* 0.056 0.006 Enterococcaceae −0.07 0.015 −0.063 −0.085 −0.079 −0.125 −0.15 Spirochaetaceae 0.077 −0.079 −0.127 −0.238 −0.092 0.086 −0.198 (Continued on following page) Frontiers in Cell and Developmental Biology | www.frontiersin.org 7 June 2022 | Volume 10 | Article 937157 Garcia-Segura et al. Seminal Microbiome and Sperm DNA-Integrity TABLE 4 | (Continued) Correlation coefficients for the abundance of identified (A) phylum, (B) family or (C) genera and basic sperm quality parameters. B FAMILY Semen Sperm Total Progressive Normal pH Semen volume concentration motile motility (%) morphology viscosity (ml) (×10^6) sperm (%) (%) (cps) Sinobacteraceae 0.182 −0.087 0.027 0.047 −0.007 0.227 0.012 Alteromonadaceae −0.142 −0.01 −0.056 −0.235 −0.049 −0.109 0.036 Thermoanaerobacterales.Family.III..Incertae.Sedis −0.078 −0.127 0.037 −0.16 −0.195 0.107 −0.013 Leptotrichiaceae −0.167 −0.094 0.003 −0.021 −0.134 0.291* −0.053 Atopobiaceae 0.051 −0.076 0.093 0.069 0.030 −0.033 −0.11 Piscirickettsiaceae 0.218 −0.098 0.147 0.126 −0.069 0.170 0.141 C GENERA Semen Sperm Total Proggressive Normal pH Semen volume concentration motile motility (%) morphology viscosity (ml) (×10^6) sperm (%) (%) (cps) Finegoldia 0.127 −0.159 −0.088 −0.144 0.045 −0.099 −0.268 Peptoniphilus −0.190 0.049 −0.147 −0.306* −0.018 0.127 0.005 Anaerococcus −0.110 0.011 0.028 0.044 0.253 0.224 −0.094 Campylobacter −0.127 0.017 −0.086 −0.203 −0.111 −0.073 −0.083 Streptococcus 0.104 0.035 −0.064 −0.050 0.113 0.170 −0.256 Staphylococcus 0.067 0.104 −0.044 0.095 −0.057 −0.245 −0.09 Moraxella −0.092 0.142 −0.045 0.085 0.357* −0.006 0.049 Prevotella −0.026 −0.106 0.090 −0.008 0.043 0.196 0.032 Ezakiella −0.071 −0.036 −0.062 −0.243 −0.053 −0.051 0.047 Corynebacterium 0.027 0.077 −0.142 0.006 0.036 −0.214 −0.152 Lactobacillus −0.026 0.027 0.214 0.258 −0.142 0.021 −0.08 Ureaplasma −0.110 0.153 −0.102 −0.063 0.272 −0.179 −0.119 Dialister −0.006 −0.065 0.078 −0.016 −0.044 −0.054 −0.084 Fusobacterium −0.187 0.170 0.013 −0.107 0.221 0.084 −0.132 Massilia −0.110 0.083 −0.108 −0.035 0.337* −0.004 −0.143 Cutibacterium 0.118 −0.078 −0.046 0.189 0.231 −0.162 −0.006 Ralstonia 0.307* −0.322* 0.047 −0.032 −0.116 0.168 −0.346* Veillonella −0.093 0.150 0.094 −0.059 0.119 0.106 −0.005 Mobiluncus −0.182 −0.188 0.082 0.003 −0.109 −0.091 −0.013 Parvimonas −0.138 0.002 −0.090 −0.117 −0.019 0.000 −0.055 Murdochiella 0.070 −0.241 −0.094 −0.112 −0.230 −0.110 −0.007 Acinetobacter 0.132 −0.085 −0.127 −0.062 0.237 0.070 −0.156 Gemella −0.069 0.017 −0.026 −0.037 −0.325* 0.085 −0.159 Porphyromonas −0.003 −0.006 0.031 0.020 −0.160 0.039 −0.118 Brevundimonas −0.088 0.244 0.118 0.266* 0.067 −0.140 −0.034 Paracoccus −0.110 0.047 0.104 0.096 0.184 0.049 0.035 Gardnerella −0.153 0.024 0.227 0.289* −0.417** 0.028 −0.002 Clostridium −0.040 −0.168 0.251 0.082 −0.140 0.054 0.004 Actinomyces 0.121 −0.179 0.154 0.052 −0.221 −0.012 −0.237 Deinococcus −0.081 −0.095 0.195 0.179 −0.384* 0.042 −0.1 Bacillus 0.284* −0.114 0.061 −0.025 −0.104 −0.030 −0.172 Sphingobium −0.064 −0.130 −0.172 −0.215 0.067 0.214 −0.101 Suicoccus −0.016 0.025 0.113 0.034 −0.016 0.240 0.08 Bradyrhizobium 0.117 −0.153 −0.028 0.020 −0.084 −0.060 −0.096 Bacteroides −0.015 −0.075 0.098 0.058 −0.091 0.046 −0.066 Schaalia −0.050 0.014 −0.033 −0.122 0.118 0.089 −0.289* Neisseria −0.093 −0.065 −0.081 −0.105 0.001 0.332* −0.143 Paenibacillus 0.249 −0.328* −0.048 −0.073 −0.228 0.089 −0.034 Aerococcus 0.051 −0.118 0.185 0.135 −0.262 −0.058 −0.290* Actinotignum 0.025 0.122 0.118 −0.105 0.052 −0.065 −0.01 Flavobacterium −0.206 0.100 0.243 0.292* −0.119 −0.163 −0.159 Sphingomonas −0.100 0.075 0.081 0.050 0.007 0.075 −0.115 Cupriavidus 0.089 −0.109 −0.021 −0.016 0.075 0.115 0.003 Fermentimonas −0.189 0.110 −0.083 −0.071 −0.160 −0.103 −0.163 Xylanimonas 0.131 −0.164 −0.048 −0.039 −0.055 −0.148 −0.325* Janibacter −0.266* 0.107 0.038 0.030 0.290 −0.024 −0.162 Tepidanaerobacter 0.001 −0.258 −0.039 0.003 −0.149 0.002 −0.045 Bifidobacterium 0.249 −0.149 0.138 0.157 −0.119 0.009 −0.137 Kocuria 0.027 0.044 −0.162 −0.095 0.243 −0.097 −0.141 Propionimicrobium −0.025 −0.057 0.108 −0.013 −0.083 0.145 0.037 Megasphaera 0.094 −0.231 0.093 −0.041 −0.129 −0.082 −0.356** Steroidobacter 0.272* −0.019 0.133 0.110 −0.053 0.237 −0.051 (Continued on following page) Frontiers in Cell and Developmental Biology | www.frontiersin.org 8 June 2022 | Volume 10 | Article 937157 Garcia-Segura et al. Seminal Microbiome and Sperm DNA-Integrity TABLE 4 | (Continued) Correlation coefficients for the abundance of identified (A) phylum, (B) family or (C) genera and basic sperm quality parameters. B FAMILY Semen Sperm Total Progressive Normal pH Semen volume concentration motile motility (%) morphology viscosity (ml) (×10^6) sperm (%) (%) (cps) Brochothrix 0.092 −0.103 0.180 0.220 −0.039 0.115 −0.111 Rhodopseudomonas 0.008 −0.170 0.021 0.207 −0.110 −0.004 0.08 Haemophilus −0.112 −0.134 −0.077 −0.080 −0.221 0.096 −0.183 Enterococcus −0.033 0.040 −0.048 −0.101 −0.023 −0.216 −0.204 Oligotropha 0.037 −0.028 0.047 0.205 0.024 −0.062 0.076 Glaciecola −0.125 0.004 0.004 −0.219 −0.022 −0.052 0.105 Filifactor 0.042 −0.090 0.369** 0.256 −0.124 0.102 −0.093 Thermoanaerobacterium −0.061 −0.135 0.051 −0.137 −0.187 0.099 0.022 Labeled in bold are the statistically significant correlations. *Statistically significant correlations (p < 0.05) ** Statistically significant correlations (p < 0.01). negative blanks of extraction were also sequenced to observe the MiSeq system (Illumina, San Diego, CA, United States), kitome. according to the manufacturer’s instructions. 16S rRNA Gene Sequencing Bioinformatics Analysis To characterize seminal microbiota, all nine hypervariable The quality of paired-end sequencing data in FASTQ file format regions of 16S rRNA gene (V1-V9) were sequenced. The was evaluated with the CLC Genomics Workbench software amplicons of the V1-V9 16S rRNA gene regions were obtained (Qiagen, Hilden, Germany). Subsequently, sequencing data by two consecutive PCRs. The universal 16S rRNA primers 27F were processed with the FastQC Toolkit (BaseSpace, Illumina) and 1492R (Lane, 1991) were used in the first PCR with the and reads were descarted based on the following criteria: read addition of a specific tag (27F: 5′-TTTCTGTTGGTGCTGATA length <140 bp and Q-Phred score <30. Taxonomic classification TTGCAGRGTTTGATYHTGGCTCAG-3′; 1492R: 5′-ACTTGC of bacterial reads and alpha diversity (Shannon index) of each CTGTCGCTCTATCTTCTACCTTGTTAYGACTT-3′, tag sample was performed following the DRAGEN Metagenomics underlined). The PCR Mix contained 10.3 µl nuclease-free pipeline (v3.5) (BaseSpace, Illumina), which uses the Kraken2 water, 4 µl 5X buffer, 2 µl 2 mM dNTP, 0.8 µl 10 µM forward algorithm (v2.0) and the corresponding Extended Kraken2 primer, 1.6 µl 10 µM reverse primer, 0.3 µl 2 U/µl Phusion Hot taxonomic database (March 2020) (Wood and Salzberg, 2014). Start II Taq HIFI polymerase (Thermo Fisher Scientific; Waltham Prior to analysis, human reads were dehosted from each sample MA, United States) and 1 µl DNA template per sample. The using the same application (UCSC HG19Alt-Aware). Raw reactions were carried out in an Veriti Thermal Cycler (Applied relative abundances at phyla, families and genera taxonomic Biosystems, Thermo Fisher Scientific) and set as follows: initial levels were formatted using the R environment. Dataset denaturation at 98°C for 30 s, followed by 25 cycles of obtained from sequencing and associated metadata, with the denaturation at 98°C for 15 s, annealing at 62.5°C for 15 s and results of seminal quality analyses, is available on-line (Garcia- extension at 72°C for 45 s. The program was completed with a Segura et al., 2022) in the Dipòsit Digital de Documents (DDD) of final extension at 72°C for 7 min. Universitat Autònoma de Barcelona. The second PCR was performed using SequalPrep polymerase (Thermo Fisher Scientific) with self-designed Statistical Analyses primers that targeted the specific tag incorporated in the Statistical analyses were conducted using the IBM SPSS Statistics first PCR. PCR mix per sample was as follows: 4.67 µl 25.0 software (IBM Corp., Armonk, NY, United States), and nuclease-free water, 1 µl 10X buffer, 0.55 µl 5.5% DMSO, graphs were generated in GraphPad Prism v.8 (GraphPad 1 µl 10X Enhancer, 0.1 µl 50 mM MgCl2, 1.5 µl 10 µM Software, La Jolla, CA, United States). First, statistical primer mix, 0.18 µl 5 U/ml SequalPrep polymerase and 1 µl normality of quantitative seminal parameters was checked of a 1:10 dilution of the first PCR’s DNA product. The using the Shapiro-Wilk test. If parametric assumptions were thermocycler was set with an initial denaturation at 94°C not fitted even after linear transformation (arcsin √x, √x), for 60 s, followed by 20 cycles of denaturation at 94°C for non-parametric assumptions were necessary to analyze the 30 s, annealing at 62 °C for 30 s and extension at 65°C for 75 s. results. Correlations between quantitative variables were The program ended with a final extension at 65°C for 5 min. assessed through the non-parametric Spearman test. Negative PCR blanks products from both amplifications were Differences of microbiological relative abundance (phyla, pooled and sequenced as a kitome control for PCR reagents. families and genera) between donors and infertile patients, as DNA library preparation was performed by enzymatic well as between samples with altered/normal oxidative stress or fragmentation of the PCR product and double indexing using chromatin damage, were assessed using the Mann-Whitney U the NGSgo kit (GenDx, Utrecht, Netherlands), according to the test. Differences regarding the presence or absence of a particular GENDX NGSgo workflow (2017, 4th edition). The indexed microorganism between clinical conditions, oxidative stress libraries were pooled, denatured, and diluted to a final status or presence of chromatin damage were assessed using concentration of 4 nM. Pooled libraries were sequenced on the the Chi-squared test. Frontiers in Cell and Developmental Biology | www.frontiersin.org 9 June 2022 | Volume 10 | Article 937157 Garcia-Segura et al. Seminal Microbiome and Sperm DNA-Integrity FIGURE 4 | Relative abundance for donors and fertile individuals and infertile patients for (A) families, and (B) genera. For each family or genera, the relative abundance and the ROC curve for the prediction of infertility is shown. Lines and bars show average ±SEM. *Statistically significant differences between the two groups. To investigate the presence of distinct microbiologic profiles at were compared using the Mann-Whitney U test, and fertility the phyla, families or genera taxonomic levels, a cluster analysis condition was compared using the Chi-squared test. For those was conducted considering the relative abundances of identified genera with a significant association to fertility status, a Principal bacteria in the whole sample, using the between-groups linkage Component Analysis (PCA) was run to sort the genera into a method based on the Euclidean distance. Clustering for families single component. The obtained data was rotated with the and genera was tested using only taxa with >1% of abundance. Varimax procedure (Kaiser, 1959) and a variable with a Clustering analysis was performed regardless of fertility status of loading factor higher than 0.6 and lower than 0.3 in the samples. Differences in sperm quality quantitative parameters rotated matrix was selected. The component was used to and alpha diversity between individuals assigned to each cluster calculate a regression score for each sample to identify the Frontiers in Cell and Developmental Biology | www.frontiersin.org 10 June 2022 | Volume 10 | Article 937157 Garcia-Segura et al. Seminal Microbiome and Sperm DNA-Integrity TABLE 5 | Correlation coefficients for the abundance of identified phylum, family or genera and oxidative stress and chromatin status. A PHYLUM Normalized CMA3+ TUNEL+ Global DNA Percentage of Double Percentage of sORP cells (%) (%) breaks fragmented strand DNA fragmented intensity cells (% breaks cells (% neutral (alkaline alkaline intensity comet) comet comet) (neutral olive tail comet olive moment) tail moment) Firmicutes 0.114 −0.014 0.233 0.233 0.2 0.022 −0.177 Proteobacteria −0.028 −0.098 −0.143 −0.382** −0.226 0.136 0.015 Actinobacteria −0.069 −0.13 0.099 0.053 −0.137 −0.022 −0.046 Tenericutes −0.09 0.072 0.118 −0.182 −0.254 −0.141 0.204 Bacteroidetes 0.047 −0.004 −0.193 −0.018 −0.042 −0.025 0.203 Saccharibacteria 0.019 0.083 −0.001 −0.109 −0.156 0.04 0.093 Deinococcus.Thermus 0 0.122 0.193 0.194 0.217 −0.17 −0.103 Fusobacteria −0.09 0.055 −0.106 −0.104 0.004 0.066 0.027 Spirochaetes 0.159 0.183 0.059 0.088 0.196 0.031 −0.045 B FAMILY Normalized Sperm with Sperm DNA Percentage of Double Percentage of sORP poor with DNA breaks fragmented strand DNA fragmented protamination breaks intensity cells (% breaks cells (% CMA3+ (%) TUNEL+ (Alkaline Alkaline intensity Neutral (%) Comet Comet) (Neutral Comet) Olive Tail Comet Moment) Olive Tail Moment) Peptoniphilaceae 0.026 0.035 0.057 0.155 0.263 0.105 −0.158 Campylobacteraceae 0.046 0.093 0.003 0.094 0.101 −0.12 0.089 Streptococcaceae −0.143 −0.056 0.158 0.189 0.06 −0.056 −0.147 Moraxellaceae −0.093 −0.014 −0.041 −0.248 −0.288* 0.189 −0.004 Staphylococcaceae −0.135 −0.033 −0.019 0.039 −0.02 0.016 0.039 Prevotellaceae 0.073 0.143 −0.182 0.091 0.079 0.069 0.173 Corynebacteriaceae −0.156 0.081 0.203 0.225 0.03 −0.047 −0.146 Peptostreptococcaceae 0.061 0.223 0.185 0.134 0.238 −0.153 −0.12 Lactobacillaceae −0.03 −0.175 0.089 −0.242 −0.285* −0.041 0.115 Veillonellaceae 0.122 0.026 −0.055 0.075 −0.015 0.041 0.207 Mycoplasmataceae −0.071 0.069 0.135 −0.078 −0.17 −0.105 0.227 Oxalobacteraceae −0.081 −0.227 −0.092 −0.2 −0.192 0.259 0.074 Propionibacteriaceae 0.191 −0.229 −0.177 −0.2 −0.178 0.074 0.149 Fusobacteriaceae −0.141 0.035 −0.119 −0.128 −0.045 0.016 0.007 Actinomycetaceae −0.014 0.107 0.061 0.153 0.041 0.197 0.084 Burkholderiaceae 0.055 −0.142 0.024 −0.07 0.004 0.378** 0.144 Bradyrhizobiaceae 0.252 −0.178 −0.163 0 0.066 −0.011 −0.067 Rhodobacteraceae −0.003 0.048 −0.011 −0.317* −0.256 0.242 0.015 Caulobacteraceae −0.167 −0.042 −0.376** −0.155 −0.207 0.021 0.154 Bacillaceae 0.161 −0.259 0.128 0.193 0.039 0.047 −0.004 Porphyromonadaceae 0.064 −0.046 0.015 0.001 −0.134 −0.129 0.164 Sphingomonadaceae 0.128 0.301* −0.011 −0.124 −0.053 0.075 0.06 Bifidobacteriaceae 0.093 −0.178 0.079 −0.173 −0.136 0.075 0.17 Aerococcaceae 0.001 −0.042 0.188 −0.004 −0.023 −0.093 −0.078 Clostridiaceae 0.11 0.037 0.06 0.153 0.135 0.012 0.024 Flavobacteriaceae −0.018 −0.15 −0.16 −0.089 −0.136 −0.038 0.117 Neisseriaceae 0.003 0.228 0.04 −0.116 −0.058 −0.018 −0.011 Deinococcaceae −0.045 0.027 0.176 0.17 0.179 −0.151 0.002 Paenibacillaceae 0.323* −0.390** −0.121 0.2 −0.037 0.26 0.290* Bacteroidaceae 0.131 −0.049 −0.085 0.054 −0.021 −0.133 0.147 Micrococcaceae 0.076 0.058 0.11 −0.19 −0.231 0.016 0.04 Lachnospiraceae 0.235 −0.102 −0.039 −0.07 0.043 0.228 0.239 Comamonadaceae 0.167 −0.071 −0.12 −0.248 −0.166 0.264* 0.165 Enterobacteriaceae 0.082 0.006 −0.082 0.013 −0.017 −0.114 −0.021 Intrasporangiaceae 0.032 −0.049 −0.07 0.027 −0.033 −0.2 0.057 Thermoanaerobacteraceae 0.142 0 0.104 0.158 0.294* −0.005 −0.025 Pasteurellaceae 0.213 0.078 −0.05 −0.004 −0.01 −0.008 0.163 Promicromonosporaceae 0.242 −0.142 0.007 0.212 0.151 −0.181 −0.178 (Continued on following page) Frontiers in Cell and Developmental Biology | www.frontiersin.org 11 June 2022 | Volume 10 | Article 937157 Garcia-Segura et al. Seminal Microbiome and Sperm DNA-Integrity TABLE 5 | (Continued) Correlation coefficients for the abundance of identified phylum, family or genera and oxidative stress and chromatin status. B FAMILY Normalized Sperm with Sperm DNA Percentage of Double Percentage of sORP poor with DNA breaks fragmented strand DNA fragmented protamination breaks intensity cells (% breaks cells (% CMA3+ (%) TUNEL+ (Alkaline Alkaline intensity Neutral (%) Comet Comet) (Neutral Comet) Olive Tail Comet Moment) Olive Tail Moment) Methylobacteriaceae 0.15 −0.014 0.11 0.018 −0.036 0.158 0.053 Listeriaceae −0.207 0.046 0.049 0.009 −0.077 0.017 0.102 Erysipelotrichaceae 0.114 0.047 0.07 −0.026 0.012 −0.013 0.056 Hungateiclostridiaceae −0.039 0.186 0.143 0.063 0.127 −0.083 0.14 Tissierellaceae 0.182 −0.045 0.027 0.086 0.085 0.068 0.152 Steroidobacteraceae 0.016 0.012 −0.011 −0.192 −0.143 0.172 −0.085 Acidiferrobacteraceae −0.025 0.045 0.096 −0.184 −0.108 0.006 −0.214 Erwiniaceae 0.191 0.135 0.1 0.018 0.144 −0.154 0.012 Enterococcaceae 0.136 −0.005 −0.005 0.246 0.127 0.228 0.304* Spirochaetaceae 0.141 0.189 0.063 0.108 0.225 −0.024 −0.096 Sinobacteraceae 0.043 0.01 0.128 −0.081 −0.045 0.058 −0.236 Alteromonadaceae 0.079 0.03 −0.052 0.033 0.023 −0.041 0.167 Thermoanaerobacterales.Family.III..Incertae.Sedis 0.095 0.105 0.085 0.221 0.218 0.114 0.116 Leptotrichiaceae −0.046 0.219 −0.037 0.151 0.156 0.024 0.176 Atopobiaceae 0.014 0.084 0.003 0.015 0.134 −0.038 0.054 Piscirickettsiaceae 0.068 0.166 0.095 −0.099 −0.043 −0.093 −0.098 C GENERA Normalized Sperm with Sperm DNA Percentage of Double Percentage of sORP poor with DNA breaks fragmented strand DNA fragmented protamination breaks intensity cells (% breaks cells (% CMA3+ (%) TUNEL+ (Alkaline Alkaline intensity Neutral (%) Comet Comet) (Neutral Comet) Olive Tail Comet Moment) Olive Tail Moment) Finegoldia 0.053 −0.007 0.043 0.088 0.133 0.087 −0.196 Peptoniphilus −0.016 0.166 0.088 0.046 0.142 0.23 −0.025 Anaerococcus 0.058 0.086 0.019 −0.017 0.206 0.074 −0.117 Campylobacter 0.047 0.119 0.014 0.082 0.109 −0.126 0.071 Streptococcus −0.146 −0.053 0.156 0.196 0.067 −0.061 −0.153 Staphylococcus −0.148 −0.02 −0.01 0.035 −0.024 0.01 0.036 Moraxella −0.075 0.018 −0.045 −0.319* −0.343** 0.104 −0.033 Prevotella 0.085 0.131 −0.181 0.084 0.07 0.073 0.176 Ezakiella 0.03 0.031 −0.039 0.06 0.123 −0.072 0.04 Corynebacterium −0.143 0.083 0.204 0.227 0.027 −0.058 −0.144 Lactobacillus −0.04 −0.157 0.083 −0.252 −0.280* −0.052 0.115 Ureaplasma −0.206 0.064 −0.113 0.006 −0.117 −0.178 0.094 Dialister 0.115 −0.072 −0.1 0.146 0.046 −0.052 0.186 Fusobacterium −0.142 0.032 −0.114 −0.132 −0.049 0.018 0.006 Massilia −0.066 −0.248 −0.098 −0.197 −0.215 0.259 0.094 Cutibacterium 0.113 −0.22 −0.167 −0.219 −0.298* 0.178 0.09 Ralstonia 0.209 −0.326* −0.08 −0.098 −0.163 0.282* 0.148 Veillonella −0.135 0.084 −0.105 −0.139 −0.131 0.097 0.204 Mobiluncus 0.092 0.002 −0.098 0.073 0.084 0.144 0.289* Parvimonas 0.049 0.162 −0.095 0.216 0.247 0.05 0.132 Murdochiella 0.249 −0.153 0.083 0.241 0.282* −0.063 0.012 Acinetobacter 0.09 0.055 −0.051 −0.214 −0.266* 0.234 0.201 Gemella −0.117 −0.037 −0.126 0.038 0.031 0.211 0.308* Porphyromonas 0.064 −0.044 0.023 0.017 −0.127 −0.137 0.157 Brevundimonas −0.280* −0.079 −0.365** −0.136 −0.292* 0.135 0.274* Paracoccus 0.025 0.107 −0.115 −0.174 −0.115 0.224 0.013 Gardnerella 0.02 −0.062 0.045 −0.092 0.012 −0.046 0.178 Clostridium 0.084 0.058 0.028 0.16 0.139 0.003 0.022 Actinomyces 0.142 −0.11 0.061 0.021 −0.116 0.2 0.146 Deinococcus −0.045 0.027 0.176 0.17 0.179 −0.151 0.002 Bacillus 0.165 −0.284* 0.058 0.192 0.001 0.087 0.032 (Continued on following page) Frontiers in Cell and Developmental Biology | www.frontiersin.org 12 June 2022 | Volume 10 | Article 937157 Garcia-Segura et al. Seminal Microbiome and Sperm DNA-Integrity TABLE 5 | (Continued) Correlation coefficients for the abundance of identified phylum, family or genera and oxidative stress and chromatin status. C GENERA Normalized Sperm with Sperm DNA Percentage of Double Percentage of sORP poor with DNA breaks fragmented strand DNA fragmented protamination breaks intensity cells (% breaks cells (% CMA3+ (%) TUNEL+ (Alkaline Alkaline intensity Neutral (%) Comet Comet) (Neutral Comet) Olive Tail Comet Moment) Olive Tail Moment) Sphingobium 0.109 0.218 0.101 −0.029 0.071 0.119 0.084 Suicoccus −0.024 −0.054 0.025 0.056 −0.061 0.046 0.005 Bradyrhizobium 0.269 −0.164 −0.104 −0.032 0.037 −0.061 −0.151 Bacteroides 0.131 −0.049 −0.085 0.054 −0.021 −0.133 0.147 Schaalia −0.053 0.353** 0.086 0.19 0.203 −0.041 −0.146 Neisseria −0.018 0.223 0.037 −0.101 −0.062 −0.021 −0.018 Paenibacillus 0.321* −0.358** −0.114 0.226 0.012 0.234 0.264* Aerococcus 0.096 −0.144 0.206 −0.016 0.018 −0.2 −0.025 Actinotignum −0.029 0.068 0.097 0.002 0.022 −0.048 −0.054 Flavobacterium −0.059 −0.106 −0.015 −0.307* −0.317* −0.111 0.049 Sphingomonas −0.054 0.281* 0.067 −0.312* −0.296* 0.119 0.121 Cupriavidus 0.023 −0.156 0.001 −0.123 −0.04 0.378** 0.157 Fermentimonas −0.06 0.094 −0.069 −0.112 −0.138 −0.101 0.179 Xylanimonas 0.242 −0.142 0.007 0.212 0.151 −0.181 −0.178 Janibacter −0.033 −0.038 0.002 −0.05 −0.144 −0.139 0.129 Tepidanaerobacter 0.17 −0.03 0.066 0.156 0.272* 0.053 0.037 Bifidobacterium 0.14 −0.122 0.048 −0.081 −0.161 0.083 0.096 Kocuria 0.046 0.137 −0.02 −0.102 −0.154 −0.005 −0.042 Propionimicrobium 0.062 −0.053 0.1 0.161 0.092 −0.206 −0.026 Megasphaera 0.297* −0.142 0.15 0.069 0.031 −0.07 −0.019 Steroidobacter 0.016 0.012 −0.011 −0.192 −0.143 0.172 −0.085 Brochothrix −0.038 −0.076 −0.096 −0.045 0.075 −0.047 0.031 Rhodopseudomonas 0.310* −0.08 −0.231 −0.241 −0.126 0.032 0.004 Haemophilus 0.169 0.078 0.077 0.053 0.11 0.036 0.114 Enterococcus 0.098 −0.036 −0.055 0.279* 0.137 0.229 0.288* Oligotropha 0.279* −0.056 −0.270* −0.218 −0.11 0.025 0.017 Glaciecola 0.036 0.059 −0.061 0.021 0.069 −0.006 0.138 Filifactor 0.002 −0.017 0.023 0.132 −0.055 −0.079 0.151 Thermoanaerobacterium 0.101 0.107 0.056 0.214 0.206 0.131 0.139 Labeled in bold are the statistically significant correlations. *Statistically significant correlations (p < 0.05) ** Statistically significant correlations (p < 0.01). predictive value for male infertility. For all statistical tests, the Considering the whole sample, seminal microbiota was mainly level of significance was set at 95% of the confidence interval composed of four phyla: Firmicutes (~59%), Proteobacteria (p < 0.05). (~19%), Actinobacteria (~8%) and Bacteroidetes (~5%). A total of 168 genera were identified, among which the most abundant were Finegoldia, Peptoniphilus, Anaerococcus, Campylobacter, RESULTS Streptococcus, Staphylococcus, Moraxella, Prevotella, Ezakiella, Corynebacterium and Lactobacillus (Figure 1). These 11 Seminal Microbiota Composition genera accounted for 75.24% of all reads classified in the After applying the quality criteria, the sequencing of the 16S rRNA in Bacteria Kingdom, and the least represented genus showed an the study samples generated an average of 221,542.88 reads per abundance of >3%. At the family level, Peptostreptococcaceae and sample with a mean length of 146.76 bp and an average depth of Veillonellaceae were also found among the most abundant, along 21,517.51 defined theoretically as LN/G, where L is the read length, N with the families to which the previous genera belonged is the number of reads and G is the gene length (Sims et al., 2014). The (Supplementary Table S2). Of note, these results highlight the percentage of reads that exceeded the established Q-Phred 30 was great interindividual variability among the relative abundances of 87.99%. In contrast, contamination controls (sample collection, DNA these taxa (Figure 1). extraction and PCR controls) displayed 10-fold fewer DNA copies, with an average of 6,321 reads. Due to this low reads count in the contamination controls, no contamination of the study samples was Seminal Microbiota Structure: Bacterial assumed, so no correction of the relative abundances of the detected Profiles and Diversity bacteria was applied. Bacterial profiles observed in contamination Two bacterial profiles were identified for each taxonomical level controls are shown in Supplementary Figure S1. (phylum, family and genus) by clustering analysis of whole Frontiers in Cell and Developmental Biology | www.frontiersin.org 13 June 2022 | Volume 10 | Article 937157 Garcia-Segura et al. Seminal Microbiome and Sperm DNA-Integrity sample (Supplementary Table S3). At the phylum level, phylum- Paenibacillus) and Lachnospiraceae families, and the Ralstonia profile 1 was dominated mainly by Firmicutes while phylum-profile genus. Sperm morphology was found associated with an 2 maintained similar frequencies of Firmicutes and Proteobacteria, increased presence of Moraxella and Massilia, and a decreased with the presence of Tenericutes and Fusobacteria as well presence of the Deinococcaceae family and the Deinococcus and (Figure 2A). However, the alpha diversity was not found Gardnerella genera. Finally, total motility was found to increase significantly different between these clusters (p = 0.760). with the presence of the Filifactor genus, as well as with the family At the family-level, Peptoniphilaceae was predominant in both Bifidobacteriaceae and its genus Gardnerella. This genus showed clusters, but more abundant in the family-profile 1. Family- an even more intense association with increased progressive profile 1 was characterized by the presence of motility. Likewise, the Propionibacteriaceae and Campylobacteraceae, Prevotellaceae, Peptostreptococcaceae, Caulobacteraceae families and the Flavobacterium genus were Veillonellaceae, Fusobacteriaceae and Actinomycetaceae, and associated with higher progressive motility, whereas the presence family-profile 2 comprised Moraxellaceae, Staphylococcaceae, of the Peptoniphilus genus correlated with a decreased progressive Corynebacteriaceae, Lactobacillaceae, Mycoplasmaceae, motility. Finally, the presence of Sphingomonadaceae family also Oxalobacteraceae, Propionibacteriaceae and Burkholderiaceae correlated with a decreased total motility. (Supplementary Table S3). As for the phylum level, no significant differences in alpha diversity were found between these clusters (p = 0.088). Impact of Microbiome on Oxidative Stress At the genus-level, Finegoldia was the most abundant in profile and Sperm Chromatin 1, followed by Staphylococcus, Moraxella, Corynebacterium, Table 5 shows correlation analysis results between the relative Ureaplasma, Massilia and Cutibacterium. In contrast, abundance of bacterial taxa, oxidative stress and sperm Peptoniphilus and Campylobacter predominated in profile 2, chromatin parameters, regardless the fertility status. Increased shared with Prevotella, Ezakiella, Dialister and Fusobacterium. oxidative stress, assessed as higher nsORP, was found to correlate Genus-profile 1 showed an enrichment of Streptococcus and with higher abundance of Oligotropha, Rhodopseudomonas (both Lactobacillus when compared to genus-profile 2 (Figure 2B). genera of the Bradyrhizobiaceae family), Megasphaera and As in the previous clusterings, alpha diversity was not different Paenibacillus (also with Paenibacillaceae family). On the other between the two clusters (p = 0.980). hand, the Brevundimonas genus was associated with lower Association analysis between microbiome profiles and nsORP. An increased abundance of Sphingomonadaceae different clinical phenotypes retrieved no significant results (p (especially with its genus Sphingomonas) and Schaalia was > 0.05). Patients and controls were evenly distributed between the associated with sperm chromatin compaction alterations, two observed clusters at all taxa levels (Table 1). Similarly, no whereas the abundance of the Paenibacillaceae family, significant differences in conventional sperm quality parameters, specifically Paenibacillus, and the Bacillus and Ralstonia genera chromatin status or oxidative stress were found between the correlated to better protamination status. microbiome profile 1 and 2 (p > 0.05) (Table 2). Although the Alkaline assay and the TUNEL assay evaluate the The correlation analysis between alpha diversity and seminal presence of equivalent parameters (i.e. global DNA damage or quality parameters in all samples revealed a significant association fragmentation), the microbiome that correlates with one assay between higher alpha diversity and increased percentage of sperm differs substantially from that of the other (Table 5). Higher with double-stranded DNA fragmentation (Neutral Comet assay) abundances of the Caulobacteraceae family and its genus (Table 3). However, no significant differences in alpha diversity were Brevundimonas was found in samples with lower levels of global observed between infertile patients and the control group (Figure 3). sperm DNA fragmentation obtained by the TUNEL assay, as well as the Oligotropha genus. However, Alkaline Comet assay’s fragmentation levels was found to increase with higher abundance Impact of Seminal Microbiota on of Thermoanaerobacteriaceae, Murdochiella, Tepidanaerobacter and Conventional Semen Quality Parameters Enterococcus, and to decrease with higher abundance of the Significant correlations were found between the relative Moraxellaceae (specially Moraxella genus) and Lactobacillaceae abundances of bacterial taxa and some seminogram parameters, (specially Lactobacillus genus) families and Cutibacterium, in all samples of our cohort regardless the fertility status (Table 4). Acinetobacter, Brevundimonas, Flavobacterium and Sphingomonas Increased seminal volume was found associated with higher genera. Finally, sperm double-stranded DNA fragmentation assessed abundance of Ralstonia, Bacillus and Steroidobacter, and lower by Neutral Comet assay was associated with increased abundance of presence of Janibacter. The abundance of the Leptotrichiaceae and the Burkholderiaceae family (and its genera Ralstonia and Neisseriaceae families (specifically, the Neisseria genus) was found Cupriavidus), and with Paenibacillaceae (and Paenibacillus genus), to increase with higher seminal pH. Lower seminal viscosity was Enterococcaceae (and Enterococcus genus), Mobiluncus, associated with an increase of the Comamonadaceae, Brevundimonas and Gemella. Pasteurellaceae and Promicromonosporaceae (especially, the Xylanomonas genus) families, as well as of the Ralstonia, Impact of Seminal Microbiota on Fertility Schaalia, Aerococcus and Megasphaera genera. Regarding the presence/absence of bacteria, results obtained Decreased sperm concentration was found to correlate with showed that the abundance of the Phylobacteriaceae and higher abundance of the Paenibacillaceae (specifically Vibrionaceae families was lower in seminal samples from Frontiers in Cell and Developmental Biology | www.frontiersin.org 14 June 2022 | Volume 10 | Article 937157 Garcia-Segura et al. Seminal Microbiome and Sperm DNA-Integrity donors than from infertile patients (p < 0.001 and p < 0.002, previous studies (Mändar et al., 2017; Chen et al., 2018; respectively). The use of these families for the prediction of Monteiro et al., 2018; Baud et al., 2019; Yang et al., 2020; infertility leads to an odds ratio of 0.052 (95% confidence Lundy et al., 2021; Okwelogu et al., 2021; Yao et al., 2021). interval [CI]: 0.005–0.364) with a sensitivity of 0.038 and a When analyzing deeper into family and genus levels, specificity of 0.567 in the case of Phylobacteriaceae, and an Streptococcus, Staphylococcus and Dialister and its family odds ratio of 0.122 (95% CI: 0.034–0.467) with a sensitivity of Veillonellaceae were found as recurrent genera in our samples, 0.094 and a specificity of 0.542 in the case of Vibrionaceae. in agreement with previous published works, (Hou et al., 2013; Comparing the relative abundance of all bacteria between Weng et al., 2014; Mändar et al., 2017; Chen et al., 2018; Monteiro control and infertile groups, results showed that the et al., 2018; Baud et al., 2019; Yang et al., 2020; Bukharin et al., Propionibacteriaceae family presented differences between 2021; Lundy et al., 2021; Yao et al., 2021). In the Proteobacteria groups (p = 0.008). The evaluation of the abundance of this phylum, the most relevant genera in our analysis were family as a predictor for fertility presented an area under the ROC Campylobacter, Moraxella and Ralstonia. Of these, curve (AUC) of 0.735 (95% CI: 0.593–0.876), with a cut-off value Campylobacter has been previously described as a member of of 0.78% (Figure 4). Differences between control and infertile seminal microbiome (Weng et al., 2014; Mändar et al., 2017; groups were also observed in the genera Oligotropha (p = 0.036) Chen et al., 2018; Baud et al., 2019). Ralstonia was detected in (AUC: 0.660; CI: 0.512 to 0.807; cut off value: 0.001%), Chinese populations (Hou et al., 2013; Yao et al., 2021) and the Rhodopseudomonas (p = 0.008) (AUC: 0.711; CI: 0.573 to abundance of Moraxella was highlighted only by Monteiro 0.849; cut off value: 0.001%) and Cutibacterium (p = 0.024) (Monteiro et al., 2018). Corynebacterium and Prevotella, the (AUC: 0.701; CI: 0.551–0.851; cut off value: 0.743%) (Figure 4). more representative genera of phyla Actinobacteria and In order to test if a combination of the three genera might lead Bacteroidetes respectively, are both among the most recurrent to a higher predictive value for male infertility, a regression bacteria in the literature (Hou et al., 2013; Weng et al., 2014; variable was generated through the Principal Component Mändar et al., 2017; Chen et al., 2018; Monteiro et al., 2018; Analysis. The regression component was defined by the Baud et al., 2019; Amato et al., 2020; Yang et al., 2020; Bukharin following formula: et al., 2021; Lundy et al., 2021; Okwelogu et al., 2021; Yao et al., 2021). Regression variable  0.999 × Oligotropha However, other genera observed in our samples contrasted with the relative abundances found in previous reports. For the + 0.999 × Rhodopseudomonas Firmicutes phylum, the three most abundant genera in our − 0.031 × Cutibacterium sample study, Finegoldia, Peptoniphilus and Anaerococcus, have also been described in several previous studies as highly The newly-generated regression variable depicted differences abundant in seminal microbiota, although none of them has been between control and infertile individuals (p = 0.001), an area previously characterized as the most abundant genera (Hou et al., under the curve of 0.780, CI: 0.650 to 0.909 for the cut-off value 2013; Weng et al., 2014; Mändar et al., 2017; Monteiro et al., 2018; −0.287. Baud et al., 2019; Yao et al., 2021). The relative abundance of Lactobacillus, found in most of our samples, is lower than the abundance found in previous works (Hou et al., 2013; Weng et al., DISCUSSION 2014; Mändar et al., 2017; Chen et al., 2018; Baud et al., 2019; Amato et al., 2020; Yang et al., 2020; Okwelogu et al., 2021), a fact Seminal Microbiota also reported by Monteiro et al. and Lundy et al. (Monteiro et al., Seminal microbiota has become a research topic of interest thanks 2018; Lundy et al., 2021) (Figure 1). Finally, to our knowledge to recent findings that link the presence of seminal dysbiosis to this is the first time that the genus Ezakiella has been detected in male infertility (Altmäe et al., 2019; Koedooder et al., 2019; Lundy seminal samples. et al., 2020; Farahani et al., 2021). However, the limited number of The genera identified so far in the seminal microbiome have a published studies still makes information regarding the seminal common characteristic: they all include bacteria that live in microbiome unclear and sometimes even contradictory, perhaps conditions of very low oxygen levels, whether they are strictly due to methodological variability. One of the factors that anaerobic, microaerophilic, or facultatively anaerobic (William B. influences the information published so far is which 16S rRNA Whitman, 2015). They are common in epithelial and mucous hypervariable regions were sequenced. It was shown that each of membranes, so can often be found on the skin or in the the nine regions (V1-V9) provided different microbial gastrointestinal and genitourinary tracts. Some have been identification resolution (Guo et al., 2013; Kerrigan et al., described as opportunistic pathogens, and all except the genera 2019; Sirichoat et al., 2020). To overcome this limitation, the Campylobacter and Prevotella are gram-positive. Some have been present study is based on full-length 16S rRNA gene described in female genital microbiota, being the predominant amplification. taxonomic group in the vaginal tract Lactobacillus, although The microbiome composition of the samples analyzed in this studies have also found Prevotella, Dialister, Peptoniphilus, work comprised the phyla Firmicutes, Proteobacteria, Anaerococcus, Ezakiella and Finegoldia (Ravel et al., 2011; Gajer Actinobacteria and Bacteroidetes. This phylum-level et al., 2012; Human Microbiome Project Consortium, 2012; Mändar composition and its relative abundance was consistent with et al., 2015; Diop et al., 2017; Koedooder et al., 2019). Frontiers in Cell and Developmental Biology | www.frontiersin.org 15 June 2022 | Volume 10 | Article 937157 Garcia-Segura et al. Seminal Microbiome and Sperm DNA-Integrity In terms of phylum, family and genus with similar have described an increased presence of this genus in characteristics, the bacteria found in our samples can be asthenozoospermic and azoospermic patients (Hou et al., 2013; structured in two profiles. One of the profiles presented a Chen et al., 2018; Yang et al., 2020). In our cohort, samples with a prevalence of Firmicutes, where Finegoldia predominated, high relative abundance of these bacteria showed a reduction in while the other had similar frequencies of Firmicutes and global sperm DNA fragmentation, suggesting a possible Proteobacteria, with Peptoniphilus and Campylobacter protective effect of Lactobacillus on DNA integrity. The predominant. However, neither cluster correlated with sperm mechanism by which this genus could act as a DNA integrity quality parameters or clinical groups. Thus, two subgroups of protector is not known. It has been suggested that the production individuals exist, in terms of microbiota that may be due to of short-chain fatty acids (SCFA) by Lactobacillus prevents sperm aspects other than fertility. Several studies point out that other lipid peroxidation by ROS (Barbonetti et al., 2011; Markowiak- bacterial communities inhabiting different organs are affected by Kopeć and Śliżewska, 2020), and contributes to the seminal diet (Bibbò et al., 2016; Kolodziejczyk et al., 2019; Barrientos- plasma antioxidant defense. Durán et al., 2020; Dall’Asta et al., 2021). In addition, the fact that Another Firmicutes that negatively correlates with sperm there are bacteria in semen which have also been observed in the DNA integrity is Megasphaera. The presence of this genus is vaginal tract could be evidence of a possible relationship between increased in infertile individuals and also in samples with high male and female microbiota, and would make a study of oxidative stress. Megasphaera members are known to produce interactions between the two bacterial populations of a acyl-CoA dehydrogenases (DuPlessis et al., 1998) which could sexually active couple interesting, as suggested by Mändar increase ROS levels in seminal plasma and the risk of sperm et al. (2015). Cluster analyses carried out so far have observed DNA damage. Finally, an increased presence of Enterococcus some coincident profiles, such as those characterized by has been observed in samples with a high degree of global and Prevotella- or Lactobacillus-enrichment (Hou et al., 2013; double-stranded DNA fragmentation. Other research groups Weng et al., 2014; Baud et al., 2019), but none of them were have linked the presence of Enterococcus in seminal plasma observed in this study. with high levels of sperm DNA damage, in bacteriospermia No differences in alpha diversity were observed between patients and in vitro studies (Zeyad et al., 2018; Duracka et al., clusters or clinical groups in our cohort. The Mändar group 2019). reported higher species diversity in male reproductive disease, Comamonadaceae, Megasphaera, Ralstonia and Schaalia are while the Chen group reported a reduction in diversity in the taxa that have shown a large negative correlation with seminal azoospermic patients (Mändar et al., 2017; Chen et al., 2018). viscosity. These bacteria might benefit from a more liquid Despite this, not all authors conducted a study of bacterial medium, which would allow for higher mobility and would diversity, so information is still limited. made resource availability easier, giving them a proliferative advantage. Alternatively, some of these genera might act directly on the viscosity of the medium through the Impact of Seminal Microbiota on Sperm production of acids or hydrolase enzymes, which would Quality Parameters degrade seminal fluid proteins and promote their liquefaction As shown by this study, and by previous studies, the most (Kershaw-Young et al., 2013; da Fonseca Junior et al., 2020; Rateb, common bacterial phylum in seminal fluid is Firmicutes (Hou 2021). et al., 2013; Weng et al., 2014; Mändar et al., 2017; Chen et al., As for possible beneficial relationships between host and 2018; Monteiro et al., 2018; Baud et al., 2019; Amato et al., 2020; seminal microbiome, the Proteobacteria phylum correlates Yang et al., 2020; Bukharin et al., 2021; Lundy et al., 2021; with better seminal and sperm parameters. The genus Okwelogu et al., 2021; Yao et al., 2021). Some of the most Moraxella and its family, largely represented in our samples, representative taxa are good candidates to play a role in have been found in high proportions in samples of donors, and in maintaining or affecting the patient’s fertility capacity. Our samples with low levels of global DNA fragmentation and better results show that the genus Peptoniphilus, for example, sperm morphology. Beneficial effects of Moraxella have also been correlates with a decrease in progressive sperm motility, thus observed in both respiratory and intestinal tracts, where stable suggesting a negative impact on this sperm characteristic. We colonies of this genus have been associated with good health and observed that the Bacilli group contains genera that present the its deregulation has been linked to pathogenic effects (Clemente strongest correlations with fertility traits: some genera of the et al., 2012; Biesbroek et al., 2014; Bosch et al., 2017; van den Bacillaceae and the Paenibacillaceae families have been linked to Munckhof et al., 2020). poor sperm quality, with negative impact on morphology, According to our data, the family Burkholderiaceae, mainly concentration, and higher levels of double-stranded DNA represented by Ralstonia, is also associated with a favorable fragmentation and oxidative stress. Reports on Lactobacillus, semen viscosity, sperm morphology and DNA protamination, perhaps the most documented genus of the Bacilli group, suggesting a beneficial effect. In contrast, Yang and others show conflicting results regarding its role in seminal quality. identified an abundant presence of Ralstonia in Some authors have found a decrease in the amount of asthenozoospermic patients (Yang et al., 2020), suggesting a Lactobacillus in infertile men with sperm motility problems or detrimental relationship between this genus and sperm seminal hyperviscosity (Weng et al., 2014; Mändar et al., 2017; motility. More research needs to be done on the effects of this Monteiro et al., 2018; Baud et al., 2019). In contrast, other authors genus on male fertility. Frontiers in Cell and Developmental Biology | www.frontiersin.org 16 June 2022 | Volume 10 | Article 937157 Garcia-Segura et al. Seminal Microbiome and Sperm DNA-Integrity Another Proteobacteria with potentially beneficial results is the way for predictive models based on multiple specific bacterial Brevundimonas, a genus that has been observed most abundantly profiles. Accordingly, in our analyses, the AUC value for such a in individuals with low oxidative stress, high progressive sperm combination was superior to those for the separate genera. motility and low levels of global DNA fragmentation. These parameters are all intrinsically related to each other and, as suggested by several authors, this could imply a cause-effect CONCLUSION mechanism (Taha et al., 2012; Peluso et al., 2013; Ribas- Maynou and Benet, 2019). The catalase activity and carotenoid Seminal microbiota analysis based on the amplification of the full- production observed in Brevundimonas could contribute to the length 16S rRNA gene is a methodology that allows the identification reduction of seminal oxidative stress (Vancanneyt et al., 2015; Liu of the most abundant bacterial groups in seminal plasma. In et al., 2020), through a decrease in cell membrane damage caused agreement with previous studies, seminal microbiota found in this by lipid peroxidation. If this peroxidation occurs, DNA would be study consisted mainly of bacteria belonging to four phyla: more exposed to oxidative stress, and extensive DNA damage Firmicutes, Proteobacteria, Actinobacteria and Bacteroidetes. The would be generated. Moreover, the cell membrane might become most abundant bacterial genera found were Finegoldia, damaged, affecting sperm viability. Similar results are found in Peptoniphilus, Anaerococcus, Campylobacter, Streptococcus, Flavobacterium, the only bacterial genus in the phylum Staphylococcus, Moraxella, Prevotella, Corynebacterium and Bacteroidetes which, according to our analysis, has a potential Lactobacillus. This methodology also allowed us to identify genera relationship with fertility. not previously described in the seminal microbiome, such as Finally, within the phylum Actinobacteria, Gardnerella and its Ezakiella, a component in vaginal microbiota. family Bifidobacteriaceae are associated with better sperm Our findings and those of other research groups provide motility, both total and progressive. The relationship between evidence for the role of seminal microbiota in male fertility. this taxon and sperm motility was also observed by Weng and Despite having a low biomass, some of these bacteria show a others (Weng et al., 2014), and may be due to the consistent relationship with their metabolic or enzymatic activity, Bifidobacteriaceae antioxidant effect (Valcarce et al., 2017; as well as correlations with several interrelated parameters, such Valcarce et al., 2019). Propionibacteriaceae bacteria, although as oxidative stress, DNA fragmentation and sperm motility. The increased in infertile patients, has been shown to be associated mechanisms by which they interfere with these seminal and with sperm motility and low levels of global DNA fragmentation. spermatic parameters are still unknown in most cases, but In contrast, Schaalia and Mobiluncus, from Actinomycetaceae may be related to their metabolism or enzymatic activities. family, appears to be at increased levels in patients with poor Further studies are needed to determine the true effect of each sperm chromatin protamination and high levels of double- of the identified bacteria and the possible clinical applications that stranded DNA fragmentation. In fact, Actinomycetaceae has may improve semen quality and pregnancy expectations. been shown to produce isoprenoids (Kawasaki et al., 2003), molecules that cause DNA fragmentation and induce apoptosis in tumoral cells (Mo and Elson, 1999). More studies DATA AVAILABILITY STATEMENT are needed to better determine the possibility of this effect on sperm cells. The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/ Impact of Seminal Microbiota on Fertility Supplementary Material. Prognosis In order to assess whether the observed microbiota can predict male infertility and become a potential biomarker, the presence or absence ETHICS STATEMENT and differential abundance of identified bacteria was analyzed. Our data suggest that the presence of the Phylobacteriaceae and The studies involving human participants were reviewed and Vibrionaceae families are more frequently associated with approved by Parc Taulí Hospital ethics committee, Consorci infertility. In addition, the proportion of the family Corporació Sanitària Parc Taulí de Sabadell. The patients/ Propionibacteriaceae was different between the control and patient participants provided their written informed consent to groups, with a greater abundance in the latter at a significance below participate in this study. 0.01. Its predictive capacity has an AUC of 0.73, considering infertile those individuals who exceed the cut-off point of 0.78% relative abundance. We can also highlight three genera with similar AUTHOR CONTRIBUTIONS characteristics: Oligotropha and Rhodopseudomonas, both with a cut-off value of 0.001%, and Cutibacterium, with a cut-off value of SG-S, JdR, FV, JB, and MO-B conceived the experimental design. 0.74%. On their own, these bacteria may predict the fertility potential SG-S, ABC, and MO-B collected seminal samples. SG-S processed of an individual, but their low cut-off values suggest that utility may the samples to assess sperm quality. JR-M processed Comet assay. be limited. For this reason, a combination of the three genera’s SG-S, JdR, and LC extracted, amplified and sequenced the abundances in a principal component analysis was expected to open bacterial DNA. SG-S, IG-M, and CH processed and analyzed Frontiers in Cell and Developmental Biology | www.frontiersin.org 17 June 2022 | Volume 10 | Article 937157 Garcia-Segura et al. Seminal Microbiome and Sperm DNA-Integrity sequencing data. SG-S wrote the original manuscript. JR-M, JB, ACKNOWLEDGMENTS and MO-B critically revised the manuscript. JdR, LC, IG-M, CH, FV, JB, JR-M, and MO-B reviewed and edited the manuscript. All Authors would like to thank Servei de Cultius Cel·lulars, authors read and approved the final manuscript. Producció d’Anticossos i Citometria (SCAC) of Universitat Autònoma de Barcelona, for the service provided for the FACSCalibur cytometer. Additionally, our thanks to Servei FUNDING Veterinari de Genètica Molecular (SVGM) for his assistance in experimental design process. This research was funded by the European Regional Development Fund and Instituto de Salud Carlos III (Economy, Industry and Competitiveness Ministry, Madrid, Spain; Project PI14/00119) and SUPPLEMENTARY MATERIAL Generalitat de Catalunya (2017SGR1796). Supported by the European Union’s Horizon 2020 Research and Innovation scheme The Supplementary Material for this article can be found online at: under the Marie Skłodowska-Curie grant agreement No. 801342 https://www.frontiersin.org/articles/10.3389/fcell.2022.937157/ (Tecniospring INDUSTRY; TECSPR-19-1-0003, to JR-M). full#supplementary-material Boissière, A., Gala, A., Ferrières-Hoa, A., Mullet, T., Baillet, S., Petiton, A., et al. (2017). REFERENCES Cell-free and Intracellular Nucleic Acids: New Non-invasive Biomarkers to Explore Male Infertility. Basic Clin. Androl. 27, 7. doi:10.1186/S12610-017-0052-0 Agarwal, A., Parekh, N., Panner Selvam, M. K., Henkel, R., Shah, R., Homa, S. T., Boivin, J., Bunting, L., Collins, J. A., and Nygren, K. G. (2007). International et al. (2019). Male Oxidative Stress Infertility (MOSI): Proposed Terminology Estimates of Infertility Prevalence and Treatment-Seeking: Potential Need and and Clinical Practice Guidelines for Management of Idiopathic Male Infertility. Demand for Infertility Medical Care. Hum. Reprod. 22, 1506–1512. doi:10. World J. Mens. Health 37, 296–312. doi:10.5534/wjmh.190055 1093/humrep/dem046 Agarwal, A., Majzoub, A., Baskaran, S., Panner Selvam, M. K., Cho, C. L., Henkel, Bosch, A. A. T. M., de Steenhuijsen Piters, W. A. A., van Houten, M. A., Chu, M. L. R., et al. (2020). Sperm DNA Fragmentation: A New Guideline for Clinicians. J. N., Biesbroek, G., Kool, J., et al. (2017). Maturation of the Infant Respiratory World J. Mens. Health 38, 412. doi:10.5534/WJMH.200128 Microbiota, Environmental Drivers, and Health Consequences. A Prospective Agarwal, A., Mulgund, A., Hamada, A., and Chyatte, M. R. (2015). A Unique View Cohort Study. Am. J. Respir. Crit. Care Med. 196, 1582–1590. doi:10.1164/rccm. on Male Infertility Around the Globe. Reprod. Biol. Endocrinol. 13, 37. doi:10. 201703-0554OC 1186/s12958-015-0032-1 Brincat, D., Catania, S., Wismayer, P. S., and Calleja-Agius, J. (2015). Male Factors Aitken, R. J., and De Iuliis, G. N. (2010). On the Possible Origins of DNA Damage in ART Outcome Prediction. Gynecol. Endocrinol. 31, 169–175. doi:10.3109/ in Human Spermatozoa. Mol. Hum. Reprod. 16, 3–13. doi:10.1093/molehr/ 09513590.2014.984678 gap059 Bukharin, O. V., Perunova, N. B., Ivanova, E. V., Chaynikova, I. N., Bekpergenova, Aitken, R., Smith, T., Jobling, M., Baker, M., and De Iuliis, G. (2014). Oxidative A. V., Bondarenko, T. A., et al. (2021). Semen Microbiota and Cytokines of Stress and Male Reproductive Health. Asian J. Androl. 16, 31–38. doi:10.4103/ Healthy and Infertile Men. Asian J. Androl 23, 1–6. doi:10.4103/aja202169 1008-682X.122203 Casanovas, A., Ribas-Maynou, J., Lara-Cerrillo, S., Jimenez-Macedo, A. R., Hortal, Altmäe, S., Franasiak, J. M., and Mändar, R. (2019). The Seminal Microbiome in O., Benet, J., et al. (2019). Double-stranded Sperm DNA Damage Is a Cause of Health and Disease. Nat. Rev. Urol. 16, 703–721. doi:10.1038/s41585-019- Delay in Embryo Development and Can Impair Implantation Rates. Fertil. 0250-y Steril. 111, 699–707. doi:10.1016/j.fertnstert.2018.11.035 Amato, V., Papaleo, E., Pasciuta, R., Viganò, P., Ferrarese, R., Clementi, N., et al. Chen, H., Luo, T., Chen, T., and Wang, G. (2018). Seminal Bacterial Composition (2020). Differential Composition of Vaginal Microbiome, but Not of Seminal in Patients with Obstructive and Non-obstructive A-zoospermia. Exp. Ther. Microbiome, Is Associated with Successful Intrauterine Insemination in Med. 15, 2884–2890. doi:10.3892/etm.2018.5778 Couples with Idiopathic Infertility: A Prospective Observational Study. Open Clemente, J. C., Ursell, L. K., Parfrey, L. W., and Knight, R. (2012). The Impact of Forum Infect. Dis. 7, ofz525. doi:10.1093/ofid/ofz525 the Gut Microbiota on Human Health: an Integrative View. Cell 148, Barbonetti, A., Cinque, B., Vassallo, M. R. C., Mineo, S., Francavilla, S., Cifone, M. 1258–1270. doi:10.1016/j.cell.2012.01.035 G., et al. (2011). Effect of Vaginal Probiotic Lactobacilli on In Vitro-induced da Fonseca Junior, A. M., Gaita, V., Argumedo, D. R., Castro, L. S., Losano, J. D., Sperm Lipid Peroxidation and its Impact on Sperm Motility and Viability. Leite, R. F., et al. (2020). Changes in Fertilization Medium Viscosity Using Fertil. Steril. 95, 2485–2488. doi:10.1016/j.fertnstert.2011.03.066 Hyaluronic Acid Impact Bull Sperm Motility and Acrosome Status. Reprod. Barrientos-Durán, A., Fuentes-López, A., de Salazar, A., Plaza-Díaz, J., and García, Dom. Anim. 55, 974–983. doi:10.1111/rda.13739 F. (2020). Reviewing the Composition of Vaginal Microbiota: Inclusion of Dall’Asta, M., Laghi, L., Morselli, S., Re, M. C., Zagonari, S., Patuelli, G., et al. Nutrition and Probiotic Factors in the Maintenance of Eubiosis. Nutrients 12, (2021). Pre-Pregnancy Diet and Vaginal Environment in Caucasian Pregnant 419. doi:10.3390/NU12020419 Women: An Exploratory Study. Front. Mol. Biosci. 8, 726. doi:10.3389/FMOLB. Baud, D., Pattaroni, C., Vulliemoz, N., Castella, V., Marsland, B. J., and Stojanov, 2021.702370/BIBTEX M. (2019). Sperm Microbiota and its Impact on Semen Parameters. Front. de Kretser, D. (1997). Male Infertility. Lancet 349, 787–790. doi:10.1016/S0140- Microbiol. 10, 234. doi:10.3389/fmicb.2019.00234 6736(96)08341-9 Bibbò, S., Ianiro, G., Giorgio, V., Scaldaferri, F., Masucci, L., Gasbarrini, A., et al. Diop, K., Andrieu, C., Michelle, C., Armstrong, N., Bittar, F., Bretelle, F., et al. (2016). The Role of Diet on Gut Microbiota Composition. Eur. Rev. Med. (20172017). Characterization of a New Ezakiella Isolated from the Human Pharmacol. Sci. 20, 4742–4749. Available at: http://www.ncbi.nlm.nih.gov/ Vagina: Genome Sequence and Description of Ezakiella Massiliensis Sp. Nov. pubmed/27906427 (Accessed September 13, 2021). Curr. Microbiol. 75, 456–463. doi:10.1007/S00284-017-1402-Z Biesbroek, G., Tsivtsivadze, E., Sanders, E. A. M., Montijn, R., Veenhoven, R. H., DuPlessis, E. R., Pellett, J., Stankovich, M. T., and Thorpe, C. (1998). Oxidase Keijser, B. J. F., et al. (2014). Early Respiratory Microbiota Composition Activity of the Acyl-CoA Dehydrogenases. Biochemistry 37, 10469–10477. Determines Bacterial Succession Patterns and Respiratory Health in doi:10.1021/bi980767s Children. Am. J. Respir. Crit. Care Med. 190, 1283–1292. doi:10.1164/rccm. Duracka, M., Lukac, N., Kacaniova, M., Kantor, A., Hleba, L., Ondruska, L., et al. 201407-1240OC (2019). Antibiotics versus Natural Biomolecules: The Case of In Vitro Induced Frontiers in Cell and Developmental Biology | www.frontiersin.org 18 June 2022 | Volume 10 | Article 937157 Garcia-Segura et al. Seminal Microbiome and Sperm DNA-Integrity Bacteriospermia by Enterococcus Faecalis in Rabbit Semen. Molecules 24, 4329. Lundy, S. D., Sangwan, N., Parekh, N. V., Selvam, M. K. P., Gupta, S., McCaffrey, P., doi:10.3390/molecules24234329 et al. (2021). Functional and Taxonomic Dysbiosis of the Gut, Urine, and Farahani, L., Tharakan, T., Yap, T., Ramsay, J. W., Jayasena, C. N., and Minhas, S. Semen Microbiomes in Male Infertility. Eur. Urol. 79, 826–836. doi:10.1016/j. (2021). The Semen Microbiome and its Impact on Sperm Function and Male eururo.2021.01.014 Fertility: A Systematic Review and Meta-analysis. Andrology 9, 115–144. doi:10. Lundy, S. D., Vij, S. C., Rezk, A. H., Cohen, J. A., Bajic, P., and Ramasamy, R. 1111/andr.12886 (2020). The Microbiome of the Infertile Male. Curr. Opin. Urology 30, 355–362. Gajer, P., Brotman, R. M., Bai, G., Sakamoto, J., Schütte, U. M. E., Zhong, X., et al. doi:10.1097/MOU.0000000000000742 (2012). Temporal Dynamics of the Human Vaginal Microbiota. Sci. Transl. Malla, M. A., Dubey, A., Kumar, A., Yadav, S., Hashem, A., and Abd_Allah, E. F. Med. 4, 132ra52. doi:10.1126/scitranslmed.3003605 (2019). Exploring the Human Microbiome: The Potential Future Role of Next- Garcia-Segura, S., Oliver-Bonet, M., and Benet, J. (2022). Data from: Seminal Generation Sequencing in Disease Diagnosis and Treatment. Front. Immunol. Microbiota of Idiopathic Infertile Patients and its Relationship with Sperm DNA 9, 2868. doi:10.3389/FIMMU.2018.02868/BIBTEX Integrity. Bellaterra: Dipòsit Digit. Doc. la Univ. Autònoma Barcelona. doi:10. Mändar, R., Punab, M., Borovkova, N., Lapp, E., Kiiker, R., Korrovits, P., et al. 5565/DDD.UAB.CAT/258024 (2015). Complementary Seminovaginal Microbiome in Couples. Res. Microbiol. Garcia-Segura, S., Ribas-Maynou, J., Lara-Cerrillo, S., Garcia-Peiró, A., Castel, A. 166, 440–447. doi:10.1016/J.RESMIC.2015.03.009 B., Benet, J., et al. (2020). Relationship of Seminal Oxidation-Reduction Mändar, R., Punab, M., Korrovits, P., Türk, S., Ausmees, K., Lapp, E., et al. (2017). Potential with Sperm DNA Integrity and pH in Idiopathic Infertile Patients. Seminal Microbiome in Men with and without Prostatitis. Int. J. Urol. 24, Biology 9, 262. doi:10.3390/biology9090262 211–216. doi:10.1111/iju.13286 Giles, E. M., and Couper, J. (2020). Microbiome in Health and Disease. J. Paediatr. Markowiak-Kopeć, P., and Śliżewska, K. (2020). The Effect of Probiotics on the Child. Health 56, 1735–1738. doi:10.1111/JPC.14939 Production of Short-Chain Fatty Acids by Human Intestinal Microbiome. Guo, F., Ju, F., Cai, L., and Zhang, T. (2013). Taxonomic Precision of Different Nutrients 12, 1107. doi:10.3390/nu12041107 Hypervariable Regions of 16S rRNA Gene and Annotation Methods for Martins, A. D., and Agarwal, A. (2019). Oxidation Reduction Potential: A New Functional Bacterial Groups in Biological Wastewater Treatment. PLoS One Biomarker of Male Infertility. Panminerva Med. 61, 108–117. doi:10.23736/ 8, e76185. doi:10.1371/JOURNAL.PONE.0076185 S0031-0808.18.03529-2 Hou, D., Zhou, X., Zhong, X., Settles, M. L., Herring, J., Wang, L., et al. (2013). Mehrparavar, B., Minai-Tehrani, A., Arjmand, B., and Gilany, K. (2019). Microbiota of the Seminal Fluid from Healthy and Infertile Men. Fertil. Steril. Metabolomics of Male Infertility: A New Tool for Diagnostic Tests. 100, 1261–1269. doi:10.1016/j.fertnstert.2013.07.1991 J. Reprod. Infertil. 20, 64–69. Human Microbiome Project Consortium (2012). Structure, Function and Diversity Mo, H., and Elson, C. E. (1999). Apoptosis and Cell-Cycle Arrest in Human and of the Healthy Human Microbiome. Nature 486, 207–214. doi:10.1038/ Murine Tumor Cells Are Initiated by Isoprenoids. J. Nutr. 129, 804–813. doi:10. nature11234 1093/jn/129.4.804 Jarvi, K., Lacroix, J.-M., Jain, A., Dumitru, I., Heritz, D., and Mittelman, M. W. Monteiro, C., Marques, P. I., Cavadas, B., Damião, I., Almeida, V., Barros, N., et al. (1996). Polymerase Chain Reaction-Based Detection of Bacteria in Semen. (2018). Characterization of Microbiota in Male Infertility Cases Uncovers Fertil. Steril. 66, 463–467. doi:10.1016/S0015-0282(16)58520-3 Differences in Seminal Hyperviscosity and Oligoasthenoteratozoospermia Kaiser, H. F. (1959). Computer Program for Varimax Rotation in Factor Analysis. Possibly Correlated with Increased Prevalence of Infectious Bacteria. Am. Educ. Psychol. Meas. 19, 413–420. doi:10.1177/001316445901900314 J. Reprod. Immunol. 79, e12838. doi:10.1111/aji.12838 Kawasaki, T., Kuzuyama, T., Furihata, K., Itoh, N., Seto, H., and Dairi, T. (2003). A Okwelogu, S. I., Ikechebelu, J. I., Agbakoba, N. R., and Anukam, K. C. (2021). Relationship between the Mevalonate Pathway and Isoprenoid Production in Microbiome Compositions from Infertile Couples Seeking In Vitro Actinomycetes. J. Antibiot. 56, 957–966. doi:10.7164/antibiotics.56.957 Fertilization, Using 16S rRNA Gene Sequencing Methods: Any Correlation Kerrigan, Z., Kirkpatrick, J. B., and D’Hondt, S. (2019). Influence of 16S rRNA to Clinical Outcomes? Front. Cell. Infect. Microbiol. 11, 709372. doi:10.3389/ Hypervariable Region on Estimates of Bacterial Diversity and Community FCIMB.2021.709372 Composition in Seawater and Marine Sediment. Front. Microbiol. 10, 1640. Peluso, G., Palmieri, A., Cozza, P. P., Morrone, G., Verze, P., Longo, N., et al. doi:10.3389/FMICB.2019.01640 (2013). The Study of Spermatic DNA Fragmentation and Sperm Motility in Kershaw-Young, C. M., Stuart, C., Evans, G., and Maxwell, W. M. C. (2013). The Infertile Subjects. Arch. Ital. Urol. Androl. 85, 8–13. doi:10.4081/aiua.2013.1.8 Effect of Glycosaminoglycan Enzymes and Proteases on the Viscosity of Alpaca Poongothai, J., Gopenath, T. S., Manonayaki, S., and Poongothai, S. (2009). Seminal Plasma and Sperm Function. Animal Reproduction Sci. 138, 261–267. Genetics of Human Male Infertility. Singap. Med. J. 50, 336–347. doi:10.1016/j.anireprosci.2013.02.005 Pourmasumi, S., Sabeti, P., Rahiminia, T., Mangoli, E., Tabibnejad, N., and Talebi, Koedooder, R., Mackens, S., Budding, A., Fares, D., Blockeel, C., Laven, J., et al. A. R. (2017). The Etiologies of Sperm DNA Abnormalities in Male Infertility: (2019). Identification and Evaluation of the Microbiome in the Female and An Assessment and Review. Int. J. Reprod. Biomed. 15, 331–344. doi:10.29252/ Male Reproductive Tracts. Hum. Reprod. Update 25, 298–325. doi:10.1093/ ijrm.15.6.331 humupd/dmy048 Rateb, S. A. (2021). Purification of Cryopreserved Camel Spermatozoa Following Kolodziejczyk, A. A., Zheng, D., and Elinav, E. (2019). Diet-microbiota Protease-based Semen Liquefaction by Lectin-functionalized DNA-defrag Interactions and Personalized Nutrition. Nat. Rev. Microbiol. 17, 742–753. Magnetic Nanoparticles. Reprod. Dom. Anim. 56, 183–192. doi:10.1111/rda. doi:10.1038/s41579-019-0256-8 13863 Kovac, J. R., Pastuszak, A. W., and Lamb, D. J. (2013). The Use of Genomics, Ravel, J., Gajer, P., Abdo, Z., Schneider, G. M., Koenig, S. S. K., McCulle, S. L., et al. Proteomics, and Metabolomics in Identifying Biomarkers of Male Infertility. (2011). Vaginal Microbiome of Reproductive-Age Women. Proc. Natl. Acad. Fertil. Steril. 99, 998–1007. doi:10.1016/J.FERTNSTERT.2013.01.111 Sci. U.S.A. 108, 4680–4687. doi:10.1073/pnas.1002611107 Lane, D. J. (1991). “16S/23S rRNA Sequencing,” in Nucleic Acid Techniques in Rehewy, M. S. E., Hafez, E. S. E., Thomas, A., and Brown, W. J. (1979). Aerobic and Bacterial Systematics. Editors E. Stackebrandt and M. Goodfellow (New York, Anaerobic Bacterial Flora in Semen from Fertile and Infertile Groups of Men. NY: John Wiley & Sons), 115–175. Archives Androl. 2, 263–268. doi:10.3109/01485017908987323 Laudes, M., Geisler, C., Rohmann, N., Bouwman, J., Pischon, T., and Schlicht, K. Ribas-Maynou, J., Yeste, M., Becerra-Tomás, N., Aston, K. I., James, E. R., and (2021). Microbiota in Health and Disease-Potential Clinical Applications. Salas-Huetos, A. (2021). Clinical Implications of Sperm DNA Damage in IVF Nutrients 13, 3866. doi:10.3390/NU13113866 and ICSI: Updated Systematic Review and Meta-analysis. Biol. Rev. 96, Lewis, S. E. M., and Simon, L. (2010). Clinical Implications of Sperm DNA 1284–1300. doi:10.1111/BRV.12700 Damage. Hum. Fertil. 13, 201–207. doi:10.3109/14647273.2010.528823 Ribas-Maynou, J., and Benet, J. (2019). Single and Double Strand Sperm DNA Liu, H., Zhang, C., Zhang, X., Tan, K., Zhang, H., Cheng, D., et al. (2020). A Novel Damage: Different Reproductive Effects on Male Fertility. Genes 10, 105. doi:10. Carotenoids-Producing Marine Bacterium from Noble Scallop Chlamys 3390/genes10020105 Nobilis and Antioxidant Activities of its Carotenoid Compositions. Food Ribas-Maynou, J., García-Peiró, A., Abad, C., Amengual, M. J., Navarro, J., and Chem. 320, 126629. doi:10.1016/j.foodchem.2020.126629 Benet, J. (2012). Alkaline and Neutral Comet Assay Profiles of Sperm DNA Frontiers in Cell and Developmental Biology | www.frontiersin.org 19 June 2022 | Volume 10 | Article 937157 Garcia-Segura et al. Seminal Microbiome and Sperm DNA-Integrity Damage in Clinical Groups. Hum. Reprod. 27, 652–658. doi:10.1093/humrep/ Metagenomic Sequencing Reveals Relationships of Seminal Microbiota to der461 Semen Quality. PLoS One 9, e110152. doi:10.1371/journal.pone.0110152 Rijnders, S., Bolscher, J. G. M., McDonnell, J., and Vermeiden, J. P. W. (2007). W. B. Whitman (Editor) (2015). Bergey’s Manual of Systematics of Archaea and Filling Time of a Lamellar Capillary-Filling Semen Analysis Chamber Is a Bacteria (New Jersey, NJ: John Wiley & Sons). doi:10.1002/9781118960608 Rapid, Precise, and Accurate Method to Assess Viscosity of Seminal Plasma. Wood, D. E., and Salzberg, S. L. (2014). Kraken: Ultrafast Metagenomic Sequence J. Androl. 28, 461–465. doi:10.2164/jandrol.106.002360 Classification Using Exact Alignments. Genome Biol. 15, R46. doi:10.1186/gb- Shreiner, A. B., Kao, J. Y., and Young, V. B. (2015). The Gut Microbiome in Health 2014-15-3-r46 and in Disease. Curr. Opin. Gastroenterology 31, 69–75. doi:10.1097/MOG. World Health Organization (2010). WHO Laboratory Manual for the Examination 0000000000000139 and Processing of Human Semen. Geneva, Switzerland: WHO. Available at: Sims, D., Sudbery, I., Ilott, N. E., Heger, A., and Ponting, C. P. (20142014). http://www.ncbi.nlm.nih.gov/pubmed/22235670 (Accessed June 25, 2020). Sequencing Depth and Coverage: Key Considerations in Genomic Analyses. Yang, H., Zhang, J., Xue, Z., Zhao, C., Lei, L., Wen, Y., et al. (2020). Potential Nat. Rev. Genet. 15, 121–132. doi:10.1038/nrg3642 Pathogenic Bacteria in Seminal Microbiota of Patients with Different Types of Sirichoat, A., Sankuntaw, N., Engchanil, C., Buppasiri, P., Faksri, K., Namwat, W., et al. Dysspermatism. Sci. Rep. 10, 6876. doi:10.1038/s41598-020-63787-x (20202020). Comparison of Different Hypervariable Regions of 16S rRNA for Yao, Y., Qiu, X.-J., Wang, D.-S., Luo, J.-K., Tang, T., Li, Y.-H., et al. (2021). Semen Taxonomic Profiling of Vaginal Microbiota Using Next-Generation Sequencing. Microbiota in Normal and Leukocytospermic Males. Asian J. Androl 24, 1–8. Arch. Microbiol. 203, 1159–1166. doi:10.1007/S00203-020-02114-4 doi:10.4103/aja202172 Taha, E. A., Ez-Aldin, A. M., Sayed, S. K., Ghandour, N. M., and Mostafa, T. (2012). Young, V. B. (2017). The Role of the Microbiome in Human Health and Disease: an Effect of Smoking on Sperm Vitality, DNA Integrity, Seminal Oxidative Stress, Introduction for Clinicians. BMJ 356, j831. doi:10.1136/BMJ.J831 Zinc in Fertile Men. Urology 80, 822–825. doi:10.1016/j.urology.2012.07.002 Zeyad, A., Hamad, M., Amor, H., and Hammadeh, M. E. (2018). Relationships Tomaiuolo, R., Veneruso, I., Cariati, F., and D’Argenio, V. (2020). Microbiota and between Bacteriospermia, DNA Integrity, Nuclear Protamine Alteration, Sperm Human Reproduction: The Case of Male Infertility. High-Throughput 9, 10. Quality and ICSI Outcome. Reprod. Biol. 18, 115–121. doi:10.1016/j.repbio. doi:10.3390/ht9020010 2018.01.010 Valcarce, D. G., Genovés, S., Riesco, M. F., Martorell, P., Herráez, M. P., Ramón, D., et al. (2017). Probiotic Administration Improves Sperm Quality in Conflict of Interest: The authors declare that the research was conducted in the Asthenozoospermic Human Donors. Benef. Microbes 8, 193–206. doi:10. absence of any commercial or financial relationships that could be construed as a 3920/BM2016.0122 potential conflict of interest. Valcarce, D. G., Riesco, M. F., Martínez-Vázquez, J. M., and Robles, V. (2019). Long Exposure to a Diet Supplemented with Antioxidant and Anti- Publisher’s Note: All claims expressed in this article are solely those of the authors inflammatory Probiotics Improves Sperm Quality and Progeny Survival in and do not necessarily represent those of their affiliated organizations, or those of the Zebrafish Model. Biomolecules 9, 338. doi:10.3390/biom9080338 the publisher, the editors and the reviewers. Any product that may be evaluated in van den Munckhof, E. H. A., Hafkamp, H. C., de Kluijver, J., Kuijper, E. J., de this article, or claim that may be made by its manufacturer, is not guaranteed or Koning, M. N. C., Quint, W. G. V., et al. (2020). Nasal Microbiota Dominated endorsed by the publisher. by Moraxella Spp. Is Associated with Respiratory Health in the Elderly Population: a Case Control Study. Respir. Res. 21, 181. doi:10.1186/s12931- Copyright © 2022 Garcia-Segura, del Rey, Closa, Garcia-Martínez, Hobeich, Castel, 020-01443-8 Vidal, Benet, Ribas-Maynou and Oliver-Bonet. This is an open-access article Vancanneyt, M., Segers, P., Abraham, W. R., and Vos, P. D. (2015). distributed under the terms of the Creative Commons Attribution License (CC “Brevundimonas,” in Bergey’s Manual of Systematics of Archaea and BY). The use, distribution or reproduction in other forums is permitted, provided the Bacteria (New Jersey, NJ: American Cancer Society), 1–14. doi:10.1002/ original author(s) and the copyright owner(s) are credited and that the original 9781118960608.gbm00791 publication in this journal is cited, in accordance with accepted academic practice. Weng, S.-L., Chiu, C.-M., Lin, F.-M., Huang, W.-C., Liang, C., Yang, T., et al. No use, distribution or reproduction is permitted which does not comply with (2014). Bacterial Communities in Semen from Men of Infertile Couples: these terms. Frontiers in Cell and Developmental Biology | www.frontiersin.org 20 June 2022 | Volume 10 | Article 937157