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What human sperm RNA-Seq tells us about the microbiome



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.


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.


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.


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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Cancer Cell Line Encyclopedia


Human sperm RNA-seq


Intracytoplasmic sperm injection


Intrauterine Insemination


In vitro fertilization


Live birth


Combined LB and NLB group samples excluding the outlier


Escherichia virus MS2


Next-generation sequencing


No live birth


Non-metric multidimensional scaling


Operational taxonomic unit


Permutational multivariate analysis of variance test


Enterobacteria phage phiX174 sensu lato


DNA sequencing of rRNA


Ribosomal RNA


16S rDNA sequencing by NGS


The Cancer Genome Atlas


Timed intercourse


Transcript Integrity Index


World Health Organization


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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.


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).

Author information




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.

Corresponding author

Correspondence to Stephen A. Krawetz.

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Conflict of interest

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).

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  • Human sperm RNA-seq
  • Microbiome
  • Bacterial identification
  • Microbial RNA