The impact of ovarian stimulation on the human endometrial microenvironment.

STUDY QUESTION: How does ovarian stimulation (OS), which is used to mature multiple oocytes for ART procedures, impact the principal cellular compartments and transcriptome of the human endometrium in the periovulatory and mid-secretory phases? SUMMARY ANSWER: During the mid-secretory window of implantation, OS alters the abundance of endometrial immune cells, whereas during the periovulatory period, OS substantially changes the endometrial transcriptome and impacts both endometrial glandular and immune cells. WHAT IS KNOWN ALREADY: Pregnancies conceived in an OS cycle are at risk of complications reflective of abnormal placentation and placental function. OS can alter endometrial gene expression and immune cell populations. How OS impacts the glandular, stromal, immune, and vascular compartments of the endometrium, in the periovulatory period as compared to the window of implantation, is unknown. STUDY DESIGN, SIZE, DURATION: This prospective cohort study carried out between 2020 and 2022 included 25 subjects undergoing OS and 25 subjects in natural menstrual cycles. Endometrial biopsies were performed in the proliferative, periovulatory, and mid-secretory phases. PARTICIPANTS/MATERIALS, SETTING, METHODS: Blood samples were processed to determine serum estradiol and progesterone levels. Both the endometrial transcriptome and the principal cellular compartments of the endometrium, including glands, stroma, immune, and vasculature, were evaluated by examining endometrial dating, differential gene expression, protein expression, cell populations, and the three-dimensional structure in endometrial tissue. Mann-Whitney U tests, unpaired t-tests or one-way ANOVA and pairwise multiple comparison tests were used to statistically evaluate differences. MAIN RESULTS AND THE ROLE OF CHANCE: In the periovulatory period, OS induced high levels of differential gene expression, glandular-stromal dyssynchrony, and an increase in both glandular epithelial volume and the frequency of endometrial monocytes/macrophages. In the window of implantation during the mid-secretory phase, OS induced changes in endometrial immune cells, with a greater frequency of B cells and a lower frequency of CD4 effector T cells. LARGE SCALE DATA: The data underlying this article have been uploaded to the Genome Expression Omnibus/National Center for Biotechnology Information with accession number GSE220044. LIMITATIONS, REASONS FOR CAUTION: A limited number of subjects were included in this study, although the subjects within each group, natural cycle or OS, were homogenous in their clinical characteristics. The number of subjects utilized was sufficient to identify significant differences; however, with a larger number of subjects and additional power, we may detect additional differences. Another limitation of the study is that proliferative phase biopsies were collected in natural cycles, but not in OS cycles. Given that the OS cycle subjects did not have known endometrial factor infertility, and the comparisons involved subjects who had a similar and robust response to stimulation, the findings are generalizable to women with a normal response to OS. WIDER IMPLICATIONS OF THE FINDINGS: OS substantially altered the periovulatory phase endometrium, with fewer transcriptomic and cell type-specific changes in the mid-secretory phase. Our findings show that after OS, the endometrial microenvironment in the window of implantation possesses many more similarities to that of a natural cycle than does the periovulatory endometrium. Further investigation of the immune compartment and the functional significance of this cellular compartment under OS conditions is warranted. STUDY FUNDING/COMPETING INTERESTS: Research reported in this publication was supported by the National Institute of Allergy and Infectious Diseases (R01AI148695 to A.M.B. and N.C.D.), Eunice Kennedy Shriver National Institute of Child Health and Human Development (R01HD109152 to R.A.), and the March of Dimes (5-FY20-209 to R.A.). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health or March of Dimes. All authors declare no conflict of interest.

Gut Microbial Shifts Indicate Melanoma Presence and Bacterial Interactions in a Murine Model.

Through a multitude of studies, the gut microbiota has been recognized as a significant influencer of both homeostasis and pathophysiology. Certain microbial taxa can even affect treatments such as cancer immunotherapies, including the immune checkpoint blockade. These taxa can impact such processes both individually as well as collectively through mechanisms from quorum sensing to metabolite production. Due to this overarching presence of the gut microbiota in many physiological processes distal to the GI tract, we hypothesized that mice bearing tumors at extraintestinal sites would display a distinct intestinal microbial signature from non-tumor-bearing mice, and that such a signature would involve taxa that collectively shift with tumor presence. Microbial OTUs were determined from 16S rRNA genes isolated from the fecal samples of C57BL/6 mice challenged with either B16-F10 melanoma cells or PBS control and analyzed using QIIME. Relative proportions of bacteria were determined for each mouse and, using machine-learning approaches, significantly altered taxa and co-occurrence patterns between tumor- and non-tumor-bearing mice were found. Mice with a tumor had elevated proportions of Ruminococcaceae, Peptococcaceae.g_rc4.4, and Christensenellaceae, as well as significant information gains and ReliefF weights for Bacteroidales.f__S24.7, Ruminococcaceae, Clostridiales, and Erysipelotrichaceae. Bacteroidales.f__S24.7, Ruminococcaceae, and Clostridiales were also implicated through shifting co-occurrences and PCA values. Using these seven taxa as a melanoma signature, a neural network reached an 80% tumor detection accuracy in a 10-fold stratified random sampling validation. These results indicated gut microbial proportions as a biosensor for tumor detection, and that shifting co-occurrences could be used to reveal relevant taxa.

Intrabacterial Metabolism Obscures the Successful Prediction of an InhA Inhibitor of Mycobacterium tuberculosis.

Tuberculosis, caused by Mycobacterium tuberculosis (M. tuberculosis), kills 1.6 million people annually. To bridge the gap between structure- and cell-based drug discovery strategies, we are pioneering a computer-aided discovery paradigm that merges structure-based virtual screening with ligand-based, machine learning methods trained with cell-based data. This approach successfully identified N-(3-methoxyphenyl)-7-nitrobenzo[c][1,2,5]oxadiazol-4-amine (JSF-2164) as an inhibitor of purified InhA with whole-cell efficacy versus in vitro cultured M. tuberculosis. When the intrabacterial drug metabolism (IBDM) platform was leveraged, mechanistic studies demonstrated that JSF-2164 underwent a rapid F420H2-dependent biotransformation within M. tuberculosis to afford intrabacterial nitric oxide and two amines, identified as JSF-3616 and JSF-3617. Thus, metabolism of JSF-2164 obscured the InhA inhibition phenotype within cultured M. tuberculosis. This study demonstrates a new docking/Bayesian computational strategy to combine cell- and target-based drug screening and the need to probe intrabacterial metabolism when clarifying the antitubercular mechanism of action.