Abstract
Purpose
The study was designed to assess the capacity of human sperm RNA-seq data to gauge the diversity of the associated microbiome within the ejaculate.
Methods
Semen samples were collected, and semen parameters evaluated at time of collection. Sperm RNA was isolated and subjected to RNA-seq. Microbial composition was determined by aligning sequencing reads not mapped to the human genome to the NCBI RefSeq bacterial, viral and archaeal genomes following RNA-Seq. Analysis of microbial assignments utilized phyloseq and vegan.
Results
Microbial composition within each sample was characterized as a function of microbial associated RNAs. Bacteria known to be associated with the male reproductive tract were present at similar levels in all samples representing 11 genera from four phyla with one exception, an outlier. Shannon diversity index (p < 0.001) and beta diversity (unweighted UniFrac distances, p = 9.99e-4; beta dispersion, p = 0.006) indicated the outlier was significantly different from all other samples. The outlier sample exhibited a dramatic increase in Streptococcus. Multiple testing indicated two operational taxonomic units, S. agalactiae and S. dysgalactiae (p = 0.009), were present.
Conclusion
These results provide a first look at the microbiome as a component of human sperm RNA sequencing that has sufficient sensitivity to identify contamination or potential pathogenic bacterial colonization at least among the known contributors.
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Abbreviations
- BH:
-
Benjamini-Hochberg
- CCLE:
-
Cancer Cell Line Encyclopedia
- hNGS:
-
Human sperm RNA-seq
- ICSI:
-
Intracytoplasmic sperm injection
- IUI:
-
Intrauterine Insemination
- IVF:
-
In vitro fertilization
- LB:
-
Live birth
- LB + NLB:
-
Combined LB and NLB group samples excluding the outlier
- MS2:
-
Escherichia virus MS2
- NGS:
-
Next-generation sequencing
- NLB:
-
No live birth
- NMDS:
-
Non-metric multidimensional scaling
- OTU:
-
Operational taxonomic unit
- PERMANOVA:
-
Permutational multivariate analysis of variance test
- phiX:
-
Enterobacteria phage phiX174 sensu lato
- rDNA:
-
DNA sequencing of rRNA
- rRNA:
-
Ribosomal RNA
- Seq:
-
16S rDNA sequencing by NGS
- TCGA:
-
The Cancer Genome Atlas
- TIC:
-
Timed intercourse
- TII:
-
Transcript Integrity Index
- WHO:
-
World Health Organization
References
Kiessling AA, Desmarais BM, Yin H-Z, Loverde J, Eyre RC. Detection and identification of bacterial DNA in semen. Fertil Steril. 2008;90(5):1744–56. https://doi.org/10.1016/j.fertnstert.2007.08.083.
Franasiak JM, Scott RT. Reproductive tract microbiome in assisted reproductive technologies. Fertil Steril. 2015;104(6):1364–71. https://doi.org/10.1016/j.fertnstert.2015.10.012.
Franasiak JM, Scott RT. Introduction: microbiome in human reproduction. Fertil Steril. 2015;104(6):1341–3. https://doi.org/10.1016/j.fertnstert.2015.10.021.
Mändar R. Microbiota of male genital tract: impact on the health of man and his partner. Pharmacol Res. 2013;69(1):32–41. https://doi.org/10.1016/j.phrs.2012.10.019.
Qing L, Song Q-X, Feng J-L, Li H-Y, Liu G, Jiang H-H. Prevalence of Chlamydia trachomatis, Neisseria gonorrhoeae, Mycoplasma genitalium and Ureaplasma urealyticum infections using a novel isothermal simultaneous RNA amplification testing method in infertile males. Ann Clin Microbiol Antimicrob. 2017;16(1):45. https://doi.org/10.1186/s12941-017-0220-2.
Moretti E, Capitani S, Figura N, Pammolli A, Federico MG, Giannerini V, et al. The presence of bacteria species in semen and sperm quality. J Assist Reprod Genet. 2009;26(1):47–56. https://doi.org/10.1007/s10815-008-9283-5.
Clarridge JE 3rd. Impact of 16S rRNA gene sequence analysis for identification of bacteria on clinical microbiology and infectious diseases. Clin Microbiol Rev. 2004;17(4):840–62. https://doi.org/10.1128/CMR.17.4.840-862.2004.
Chen M, Cai L-Y, Kanno N, Kato T, Lu J, Jin F, et al. Detection of human herpesviruses (HHVs) in semen of human male infertile patients. J Reprod Dev. 2013;59(5):457–62. https://doi.org/10.1262/jrd.2013-023.
Cordeiro CN, Bano R, Washington Cross CI, Segars JH. Zika virus and assisted reproduction. Curr Opin Obstet Gynecol. 2017;29(3):175–9. https://doi.org/10.1097/GCO.0000000000000366.
Lai YM, Yang F-P, Pao CC. Human papillomavirus deoxyribonucleic acid and ribonucleic acid in seminal plasma and sperm cells**Supported by research grant NSC83-0412-B182-001 from National Science Council of Republic of China and by medical research grant CMRP-343 from Chang Gung College of Medicine and Technology and Memorial Hospital, Taipei, Taiwan, Republic of China, both awarded to C.C.P. Fertil Steril. 1996;65(5):1026–30. https://doi.org/10.1016/S0015-0282(16)58281-8.
Diemer T, Huwe P, Ludwig M, Schroeder-Printzen I, Michelmann HW, Schiefer HG, et al. Influence of autogenous leucocytes and Escherichia coli on sperm motility parameters in vitro. Andrologia. 2003;35(2):100–5. https://doi.org/10.1046/j.1439-0272.2003.00523.x.
Hou D, Zhou X, Zhong X, Settles ML, Herring J, Wang L, et al. Microbiota of the seminal fluid from healthy and infertile men. Fertil Steril. 2013;100(5):1261–9.e3. https://doi.org/10.1016/j.fertnstert.2013.07.1991.
Weidner W, Jantos C, Schiefer HG, Haidl G, Friedrich HJ. Semen parameters in men with and without proven chronic prostatitis. Arch Androl. 1991;26(3):173–83. https://doi.org/10.3109/01485019108987640.
Vetrosky D, White GL Jr. Prostatitis. Lippincotts Prim Care Pract. 1997;1(4):437–41.
Weng S-L, Chiu C-M, Lin F-M, Huang W-C, Liang C, Yang T, et al. Bacterial communities in semen from men of infertile couples: metagenomic sequencing reveals relationships of seminal microbiota to semen quality. PLoS One. 2014;9(10):e110152-e. https://doi.org/10.1371/journal.pone.0110152.
Jodar M, Sendler E, Moskovtsev SI, Librach CL, Goodrich R, Swanson S, et al. Absence of sperm RNA elements correlates with idiopathic male infertility. Sci Transl Med. 2015;7(295):295re6. https://doi.org/10.1126/scitranslmed.aab1287.
Goodrich R, Johnson G, Krawetz SA. The preparation of human spermatozoal RNA for clinical analysis. Arch Androl. 2007;53(3):161–7. https://doi.org/10.1080/01485010701216526.
Goodrich RJ, Anton E, Krawetz SA. Isolating mRNA and small noncoding RNAs from human sperm. Methods Mol Biol. 2013;927:385–96. https://doi.org/10.1007/978-1-62703-038-0_33.
Mao S, Goodrich RJ, Hauser R, Schrader SM, Chen Z, Krawetz SA. Evaluation of the effectiveness of semen storage and sperm purification methods for spermatozoa transcript profiling. Syst Biol Reprod Med. 2013;59(5):287–95. https://doi.org/10.3109/19396368.2013.817626.
Estill MS, Hauser R, Krawetz SA. RNA element discovery from germ cell to blastocyst. Nucleic Acids Res. 2018. https://doi.org/10.1093/nar/gky1223.
Kim D, Langmead B, Salzberg SL. HISAT: a fast spliced aligner with low memory requirements. Nat Methods. 2015;12:357–60. https://doi.org/10.1038/nmeth.3317 https://www.nature.com/articles/nmeth.3317#supplementary-information.
Wood DE, Salzberg SL. Kraken: ultrafast metagenomic sequence classification using exact alignments. Genome Biol. 2014;15(3):R46. https://doi.org/10.1186/gb-2014-15-3-r46.
Team RC. R: a language and environment for statistical computing. 2013.
McMurdie PJ, Holmes S. phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data. PLoS One. 2013;8(4):e61217. https://doi.org/10.1371/journal.pone.0061217.
Shen W, Xiong J. TaxonKit: a cross-platform and efficient NCBI taxonomy toolkit. bioRxivorg. 2019;513523. https://doi.org/10.1101/513523.
Oksanen J, Blanchet FG, Friendly M, Kindt R, Legendre P, McGlinn D, et al. vegan: Community Ecology Package. 2019.
Kim D, Hofstaedter CE, Zhao C, Mattei L, Tanes C, Clarke E, et al. Optimizing methods and dodging pitfalls in microbiome research. Microbiome. 2017;5(1):52. https://doi.org/10.1186/s40168-017-0267-5.
Barton H, Taylor N, Lubbers B, Pemberton A. DNA extraction from low-biomass carbonate rock: an improved method with reduced contamination and the low-biomass contaminant database. J Microbiol Methods. 2006;66(1):21–31.
Salter SJ, Cox MJ, Turek EM, Calus ST, Cookson WO, Moffatt MF, et al. Reagent and laboratory contamination can critically impact sequence-based microbiome analyses. BMC Biol. 2014;12(1):87. https://doi.org/10.1186/s12915-014-0087-z.
Cooper TG, Noonan E, von Eckardstein S, Auger J, Baker HW, Behre HM, et al. World Health Organization reference values for human semen characteristics. Hum Reprod Update. 2010;16(3):231–45. https://doi.org/10.1093/humupd/dmp048.
Simon LM, Karg S, Westermann AJ, Engel M, Elbehery AHA, Hense B, et al. MetaMap: an atlas of metatranscriptomic reads in human disease-related RNA-seq data. Gigascience. 2018;7(6):giy070. https://doi.org/10.1093/gigascience/giy070.
Strong MJ, Xu G, Morici L, Splinter Bon-Durant S, Baddoo M, Lin Z, et al. Microbial contamination in next generation sequencing: implications for sequence-based analysis of clinical samples. PLoS Pathog. 2014;10(11):e1004437. https://doi.org/10.1371/journal.ppat.1004437.
Tae H, Karunasena E, Bavarva JH, McIver LJ, Garner HR. Large scale comparison of non-human sequences in human sequencing data. Genomics. 2014;104(6 Pt B):453–8. https://doi.org/10.1016/j.ygeno.2014.08.009.
Uphoff CC, Pommerenke C, Denkmann SA, Drexler HG. Screening human cell lines for viral infections applying RNA-Seq data analysis. PLoS One. 2019;14(1):e0210404-e. https://doi.org/10.1371/journal.pone.0210404.
Anantha RV, Kasper KJ, Patterson KG, Zeppa JJ, Delport J, McCormick JK. Fournier’s gangrene of the penis caused by Streptococcus dysgalactiae subspecies equisimilis: case report and incidence study in a tertiary-care hospital. BMC Infect Dis. 2013;13(1):381. https://doi.org/10.1186/1471-2334-13-381.
Takakura S, Gibo K, Takayama Y, Shiiki S, Narita M. Clinical characteristics of Streptococcus pyogenes, Streptococcus agalactiae and Streptococcus dysgalactiae subsp. equisimilis bacteremia in adults: a 15-year retrospective study at a major teaching hospital in Okinawa, Japan. Open Forum Infect Dis. 2017;4(suppl_1):S559-S. https://doi.org/10.1093/ofid/ofx163.1457.
Bliss SJ, Pearlman MD, Marrs CF, Tallman P, Manning SD, Foxman B, et al. Group B Streptococcus colonization in male and nonpregnant female university students: a cross-sectional prevalence study. Clin Infect Dis. 2002;34(2):184–90. https://doi.org/10.1086/338258.
Foxman B, Gillespie BW, Manning SD, Marrs CF. Risk factors for group B streptococcal colonization: potential for different transmission systems by capsular type. Ann Epidemiol. 2007;17(11):854–62. https://doi.org/10.1016/j.annepidem.2007.05.014.
D'Urzo N, Martinelli M, Pezzicoli A, De Cesare V, Pinto V, Margarit I, et al. Acidic pH strongly enhances in vitro biofilm formation by a subset of Hypervirulent ST-17 Streptococcus agalactiae strains. Appl Environ Microbiol. 2014;80(7):2176–85. https://doi.org/10.1128/aem.03627-13.
Furfaro LL, Chang BJ, Payne MS. Perinatal Streptococcus agalactiae epidemiology and surveillance targets. Clin Microbiol Rev. 2018;31(4):e00049–18. https://doi.org/10.1128/cmr.00049-18.
Parks T, Barrett L, Jones N. Invasive streptococcal disease: a review for clinicians. Br Med Bull. 2015;115(1):77–89. https://doi.org/10.1093/bmb/ldv027.
Parida R, Samanta L. In silico analysis of candidate proteins sharing homology with Streptococcus agalactiae proteins and their role in male infertility. Syst Biol Reprod Med. 2017;63(1):15–28. https://doi.org/10.1080/19396368.2016.1243741.
Rosini R, Margarit I. Biofilm formation by Streptococcus agalactiae: influence of environmental conditions and implicated virulence factors. Front Cell Infect Microbiol. 2015;5(6). https://doi.org/10.3389/fcimb.2015.00006.
Acknowledgments
The use of samples from the Eunice Kennedy Silver National Institute of Child Health and Human Development (Assessment of Multiple Intrauterine Gestations from Ovarian Stimulation (AMIGOS) study are gratefully acknowledged. Support from the Postdoctoral Recruiting Fellowship from Wayne State University to GMS and from the Charlotte B. Failing Professorship to SAK and the Wayne State University OVPR Grants Boost award to SAK is gratefully acknowledged. The authors would like to thank Dr. Kevin Theis, Department of Biochemistry, Microbiology and Immunology and Obstetrics and Gynecology, Wayne State University School of Medicine for his thoughtful review of the manuscript. Merck KGaA Darmstadt, Germany reviewed the manuscript for medical accuracy only before journal submission. The authors are fully responsible for the content of this manuscript, and the views and opinions described in the publication reflect solely those of the authors. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NICHD or NIH.
Funding
This study was funded by a 2016 Grant for Fertility Innovation (25RJY1) from Merck KGaA Darmstadt, Germany and a National Institute of Health (NIH)/National Institute of Environmental Health Sciences (NIEHS) Grant (R01-ES028298).
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SAK and GMS were responsible for study design. Sample acquisition was by SM, CL, and JRP. RNA isolation and sequencing were performed by RG. Sequence alignment, analysis, and manuscript preparation was performed by GMS. All the authors contributed to the editing of the manuscript.
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Stephen Krawetz has received grants from EMD Serono and GFI Fertility Innovation. Stephen Krawetz reports honoraria from Taylor and Francis and KINBRE.
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Estimated sample richness (alpha diversity) by sequencing run; Next-seq 500 and Hi-seq 4000. The observed microbial richness (Observed) and Shannon diversity index (Shannon) of the sequencing runs are significantly different (p-value < 0.001). Group mean and 95% confidence intervals are reported. (PNG 633 kb)
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Swanson, G.M., Moskovtsev, S., Librach, C. et al. What human sperm RNA-Seq tells us about the microbiome. J Assist Reprod Genet 37, 359–368 (2020). https://doi.org/10.1007/s10815-019-01672-x
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DOI: https://doi.org/10.1007/s10815-019-01672-x