Biology subjects

Romero, R.

Publications and source records attributed to Romero, R..

At least 19 recordsLinked to original sources

bioRxiv2026

IL-1β/IL-6 signaling circuit in the tumor microenvironment drives prostate cancer development

Despite considerable progress in elucidating mechanisms leading to castration-resistant prostate cancer (CRPC), insight into the early stages of prostate cancer initiation and progression remains limited. Genomic drivers of prostate cancer initiation have been defined through patient tumor sequencing, but the subsequent events responsible for local tissue invasion are poorly understood. Here we leverage a well-studied genetically engineered mouse prostate cancer model (Hi-Myc) that, based on robust and reproducible kinetics for transitioning from pre-invasive prostatic intraepithelial neoplasia (PIN) to invasive prostate adenocarcinoma (PCa), provides an ideal system to systematically address this question using single-cell analysis. Surprisingly, the transcriptomic profiles of early PIN lesions are indistinguishable from those of late-stage, highly invasive tumor cells, suggesting that MYC activation at the PIN stage establishes a transcriptional program that is fully capable of driving invasion but is restrained by the local tumor microenvironment (TME). Indeed, we find that progression to PCa is associated with progressive infiltration of IL-1{beta}+ tumor-infiltrating macrophages at the PIN stage that, based on immunodepletion and cytokine neutralization experiments, are required for the PIN-to-PCa transition. Mechanistically, IL-1{beta} from macrophages acts directly on prostate fibroblasts, leading to the release of IL-6, which drives invasion by activating IL-6R in tumor cells. Collectively, these findings identify a pro-tumorigenic IL-1{beta}/IL-6 signaling circuit mediated through local macrophages and fibroblasts that unleashes the full oncogenic potential of a cancer driver (MYC) activated at the PIN stage. We also find evidence of this circuit in other (non-MYC-driven) prostate cancer models as well as human prostate and lung adenocarcinoma, with implications for TME-specific targeted therapeutics in early-stage disease.

cancer biology↗

bioRxiv2026

Cross-etiology transcriptomic conservation in hepatocellular carcinoma reveals opposing proliferation and hepatocyte-loss programs validated across cohorts

BackgroundHepatocellular carcinoma (HCC) arises from diverse etiologies, but the extent to which viral etiologies converge on reproducible transcriptomic state axes remains incompletely resolved. MethodsWe analyzed HBV- and HCV-associated HCC discovery cohorts using Hallmark GSVA, limma-based differential modeling, and cross-cohort meta-analysis. Conserved tumor-upregulated and tumor-downregulated genes were distilled into ProlifHub and HepLoss modules, combined as HCCStateScore = ProlifHubScore - HepLossScore. Module performance was evaluated across multiple independent GEO cohorts, module-size robustness was tested across alternative top-N definitions, and TCGA-LIHC was used for continuous Cox survival modeling. An HBV-derived injury axis was constructed from an ordinal ALT/AST/HBV-DNA injury index in GSE83148 and tested in GSE121248 with adjustment for E2F/G2M activity and CIBERSORTx-inferred immune composition. ResultsHBV- and HCV-associated HCC showed conserved activation of proliferation/repair programs and suppression of hepatocyte functional programs. The HCCStateScore validated across independent HCC cohorts with consistently positive tumor-non-tumor deltas and high discrimination, and module-size sensitivity analysis showed that performance was not dependent on the top-20 cutoff. In TCGA-LIHC, higher ProlifHubScore and HCCStateScore were associated with poorer overall survival in continuous Cox models, including after age/sex/stage adjustment. A compact HBV injury program remained tumor-associated after simultaneous adjustment for E2F/G2M activity and CIBERSORTx-derived immune-composition covariates, with concordant results using an extended FDR-defined injury set. ConclusionsHCC exhibits a robust cross-etiology transcriptomic state characterized by opposing proliferation and hepatocyte-loss programs. The module framework provides a portable bulk transcriptomic state score and supports a residual tumor-associated HBV injury component that is not fully explained by proliferation or inferred immune composition.

bioinformatics↗

bioRxiv2025

Distinct patterns of de novo coding variants contribute to Tourette Syndrome etiology

Tourette syndrome (TS) is a highly heritable childhood-onset neuropsychiatric disorder characterized by persistent motor and vocal tics. While both common and rare variants contribute to TS susceptibility, the role of rare de novo mutations (DNMs) remains incompletely characterized. Here, we report findings from the largest TS whole-exome sequencing study to date, analyzing 1,466 TS trios alongside 6,714 autism spectrum disorder (ASD) trios and 5,880 unaffected sibling controls from the Simons Simplex Collection (SSC) and SPARK cohorts. Leveraging a trio-based design across these cohorts enabled calibrated assessment of DNM burden while controlling for background mutation rates. We observed a significant exome-wide enrichment of protein-truncating DNMs in TS probands, particularly within genes intolerant to loss-of-function variation (pLI [≥] 0.9), with little contribution from damaging missense variants. Notably, TS probands did not exhibit enrichment in previously implicated ASD or developmental delay (DD) genes, but elsewhere in the genome, suggesting a distinct rare variant architecture. Using a Bayesian statistical framework that integrates both de novo and rare inherited coding variants, we identified three candidate TS risk genes with FDR [≤] 0.05: PPP5C, EXOC1, and GXYLT1. Literature shows that they have prior links to neurodevelopmental and psychiatric disorders. These findings reveal a rare variant burden in TS that is genetically distinguishable from ASD, underscore the importance of loss-of-function mutations in TS risk, and nominate novel candidate genes for future functional investigation.

neuroscience↗

bioRxiv2024

Cultivation and molecular characterization of Foley catheterized urine, clean catch urine, and vaginal swabs from pregnant women prior to delivery

The bladder and urine have historically been considered sterile, especially in the context of clinical assessment. Yet, enhanced culture techniques and advances in DNA sequencing surveys have revealed a low microbial biomass microbiota in the bladders of most healthy individuals. Yet very few studies have investigated the urinary microbiota of pregnant women, who are at increased risk of urinary tract infections (UTIs) that can lead to pregnancy complications such as spontaneous preterm birth. To better understand the potential role of a bladder microbiota during pregnancy, we characterized the urinary microbiota of 25 pregnant women (delivering at or beyond 36 weeks gestation) by comparing the bacterial profiles of their paired catheter urine, clean catch urine, and vaginal swabs through both cultivation and molecular microbiological survey methods. For culture, three bacterial taxa were detected in at least 20% of all urine samples (Lactobacillus species, coagulase negative Staphylococcus species, and Ureaplasma urealyticum). All three taxa were detected less frequently in Foley catheter urine than in clean catch urine. Ureaplasma urealyticum was the most frequently recovered bacterium in Foley catheter urine (13/25 women). It was also identified as being more relatively abundant in Foley catheter urine than in the vagina through 16S rRNA gene surveys. Other lower abundance Gram-positive anaerobic cocci (i.e., Finegoldia and Anaerococcus) were also more relatively abundant in Foley catheter urine than clean catch urine or vaginal swabs. However, all sample types had high relative abundances of Lactobacillus and Gardnerella species. Overall, this suggests that, although vaginal microbiota contamination cannot be completely avoided, Foley catheterized urine is effective at characterizing the low abundance bladder microbiota, including Ureaplasma, Finegoldia, and Anaerococcus species. This warrants their further consideration as commensal members of the bladder microbiome during pregnancy.

microbiology↗

bioRxiv2024

Identification of Hub Genes and CDK1-Targeting Therapeutics in Hepatocellular Carcinoma: Bioinformatics and Simulation Study

BackgroundHepatocellular carcinoma (HCC) remains a significant global health challenge, often associated with chronic hepatitis B (HBV) and hepatitis C (HCV) infections. Novel therapeutic approaches are urgently needed to improve patient outcomes. ObjectiveTo identify and validate potential therapeutic targets and novel drug candidates for HBV, HCV, and associated HCC using integrative bioinformatics and molecular dynamics simulations. MethodsGene expression datasets from HCC studies were analyzed to identify dysregulated genes. Protein-protein interaction networks were constructed to determine hub genes. Virtual screening of kinase compound libraries against CDK1 was performed, followed by molecular docking and dynamics simulations. Drug-likeness and metabolic properties of hit compounds were evaluated. ResultsSeven hub genes were identified, including five upregulated (CDK1, AURKB, CCNA2, BUB1B, RRM2) and two downregulated (AGXT2, ESR1) genes. Virtual screening yielded three promising hit compounds (G213-0272, E130-0174, Z666960592) targeting CDK1. E130-0174 demonstrated the most favorable profile, with stable CDK1 binding and no inhibition of major cytochrome P450 enzymes. Two repurposed drugs, alvocidib and riviciclib, also showed potential as CDK1 inhibitors. ConclusionsThis study identified novel CDK1 inhibitors with promising profiles for HCC treatment. The integrative approach combining bioinformatics and molecular dynamics simulations provides a robust framework for identifying potential therapeutic targets and drug candidates in HCC and related liver diseases. Further experimental validation is warranted to confirm these findings and advance the development of new HCC treatments.

bioinformatics↗

bioRxiv2024

Identification and Functional Characterization of Up-Regulated Hub Genes in Adenocarcinoma Across Multiple Organ Sites

Adenocarcinoma is a prevalent and aggressive form of cancer affecting various organ systems. To gain deeper insights into the molecular mechanisms underlying adenocarcinoma, we conducted a comprehensive bioinformatics analysis to identify consistently up-regulated hub genes and their regulatory networks across multiple adenocarcinoma types. By integrating gene expression data from GEO and GEPIA2 databases, we identified 129 commonly up-regulated genes, from which 10 key hub genes were further characterized: CHEK1, CDC20, ANLN, RRM2, CCNB1, CCNA2, KIF23, TOP2A, BUB1, and KIF11. These hub genes were found to be significantly overexpressed in several adenocarcinoma types, including colorectal, lung, pancreatic, and ovarian cancer, except for prostate adenocarcinoma. The regulatory network analysis revealed that the expression of these hub genes is controlled by transcription factors, such as YBX1, E2F1, MYC, E2F3, and TP53, as well as miRNAs, including hsa-miR-103a-3p, hsa-let-7e-5p, and hsa-miR-15b-5p, which were consistently downregulated across the adenocarcinoma types studied. Functional enrichment analysis highlighted the involvement of these hub genes in critical cellular processes, including cell cycle regulation, mitotic division, and cellular senescence. These findings provide a comprehensive understanding of the molecular landscape of adenocarcinoma and identify potential therapeutic targets and prognostic biomarkers for further investigation.

bioinformatics↗

bioRxiv2024

Elucidating the Type 2 Diabetes Regulatory Network: Identification of EGFR as a Key Hub and Novel Drug Candidates

IntroductionType 2 diabetes (T2D) is a complex metabolic disorder with incompletely understood molecular mechanisms. This study aimed to elucidate the T2D regulatory network and identify potential drug targets and candidates. MethodsWe performed differential gene expression analysis on multiple T2D datasets, constructed protein-protein interaction networks, and conducted a meta-analysis to identify key hub genes. Functional enrichment analysis was performed on the resulting network. Structure-based virtual screening targeting EGFR, followed by molecular dynamics simulations, was used to identify potential drug candidates. ResultsEGFR emerged as a consistently top-ranked hub gene across studies. The regulatory network comprised hub genes, transcription factors, and miRNAs involved in processes such as apoptosis regulation, cellular response to organic substances, and reactive oxygen species metabolism. Virtual screening identified three compounds with favorable ADMET properties and strong binding affinities to EGFR, outperforming control drugs. These compounds demonstrated stable interactions in molecular dynamics simulations. ConclusionsOur integrative analysis provides new insights into the T2D regulatory network, highlighting EGFR as a potential therapeutic target. The identified drug candidates offer promising avenues for T2D treatment and related disorders involving EGFR signaling, bridging systems biology and drug discovery approaches in metabolic disease research.

bioinformatics↗

bioRxiv2024

The neuroendocrine transition in prostate cancer is dynamic and dependent on ASCL1

Lineage plasticity is a recognized hallmark of cancer progression that can shape therapy outcomes. The underlying cellular and molecular mechanisms mediating lineage plasticity remain poorly understood. Here, we describe a versatile in vivo platform to identify and interrogate the molecular determinants of neuroendocrine lineage transformation at different stages of prostate cancer progression. Adenocarcinomas reliably develop following orthotopic transplantation of primary mouse prostate organoids acutely engineered with human-relevant driver alterations (e.g., Rb1-/-; Trp53-/-; cMyc+ or Pten-/-; Trp53-/-; cMyc+), but only those with Rb1 deletion progress to ASCL1+ neuroendocrine prostate cancer (NEPC), a highly aggressive, androgen receptor signaling inhibitor (ARSI)-resistant tumor. Importantly, we show this lineage transition requires a native in vivo microenvironment not replicated by conventional organoid culture. By integrating multiplexed immunofluorescence, spatial transcriptomics and PrismSpot to identify cell type-specific spatial gene modules, we reveal that ASCL1+ cells arise from KRT8+ luminal epithelial cells that progressively acquire transcriptional heterogeneity, producing large ASCL1+;KRT8- NEPC clusters. Ascl1 loss in established NEPC results in transient tumor regression followed by recurrence; however, Ascl1 deletion prior to transplantation completely abrogates lineage plasticity, yielding adenocarcinomas with elevated AR expression and marked sensitivity to castration. The dynamic feature of this model reveals the importance of timing of therapies focused on lineage plasticity and offers a platform for identification of additional lineage plasticity drivers.

cell biology↗

bioRxiv2024

Identification of Potential Therapeutic Targets and Biomarkers for Glioblastomas Through Integrative Analysis of Gene Expression Data

BackgroundIn this study, we conducted a comprehensive analysis of differential gene expression data from studies GSE15824, GSE4290 and GEPIA2 data to identify up-regulated hub genes with potential as therapeutic targets for glioblastomas. Through virtual screening, we also aimed to identify novel VEGFA inhibitors. ResultsSeven up-regulated hub genes (TYROBP, ITGB2, C1QA, C1QB, CTSS, TLR2, and CD163) were identified. Virtual screening of VEGFA inhibitors led to the discovery of six significant hits, including three from the ChemDiv library (D519-0372, G868-0191, and Y031-5201) and three from the ZINC20 database (ZINC57658, ZINC57652, ZINC57679). Molecular dynamics simulations highlighted G868-0191 as the most stable VEGFA inhibitor. Two repurposed drugs, Sunitinib and Ticlopidine hydrochloride, were also identified as potential candidates. In addition, the down-regulated hub genes GABARAPL1, OPTN, and CDH8 were proposed as potential biomarkers for glioblastomas. ConclusionThis study underscores the significance of immune-related hub genes in glioblastoma pathology and suggests new VEGFA inhibitors as promising therapeutic agents. The identification of down-regulated genes as potential biomarkers offers further avenues for clinical application. However, experimental validation is needed to confirm the clinical utility of these findings.

bioinformatics↗

bioRxiv2024

A nascent riboswitch helix orchestrates robust transcriptional regulation through signal integration

Widespread manganese-sensing transcriptional riboswitches effect the dependable gene regulation needed for bacterial manganese homeostasis in changing environments. Riboswitches - like most structured RNAs - are believed to fold co-transcriptionally, subject to both ligand binding and transcription events; yet how these processes are orchestrated for robust regulation is poorly understood. Through a combination of single molecule and bulk approaches, we discovered how a single Mn2+ ion and the transcribing RNA polymerase (RNAP), paused immediately downstream by a DNA template sequence, are coordinated by the bridging switch helix P1.1 in the paradigmatic Lactococcus lactis riboswitch. This coordination achieves a heretofore-overlooked semi-docked global conformation of the nascent RNA, P1.1 base pair stabilization, transcription factor NusA ejection, and RNAP pause extension, thereby enforcing transcription readthrough. Our work demonstrates how a central, adaptable RNA helix functions analogous to a molecular fulcrum of a first-class lever system to integrate disparate signals for finely balanced gene expression control.

molecular biology↗

bioRxiv2023

In silico ADMET, virtual screening and machine learning study of EGFR inhibitors for the treatment of type 2 diabetes and pancreatic cancer

This study conducted a differential gene expression analysis in two independent studies of type 2 diabetes using pancreatic samples, specifically Langerhans cells. Through protein-protein interaction network analysis, the Epidermal Growth Factor Receptor (EGFR) emerged as the top hub gene among the upregulated genes in both studies. Furthermore, functional enrichment analysis revealed the involvement of EGFR in pancreatic cancer signaling pathways, indicating its potential role beyond diabetes. To identify potential EGFR inhibitors, a virtual screening approach was employed using tyrosine kinase inhibitors. Two separate deep learning classification models were developed and trained on distinct sets of ligands, one for predicting bioactivity and the other for assessing toxicity. The ligands underwent rigorous filtering based on binding energies and absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties. This filtering process resulted in the identification of nine hits that demonstrated promising characteristics in terms of both bioactivity and druglikeness, making them viable candidates for further development as EGFR inhibitors. To evaluate the performance of the identified hits, approved drugs including Afatinib, Almonertinib, Erlotinib, Gefitinib, and Osimertinib were used as controls. Notably, the finalist compounds consistently outperformed the control drugs across all evaluated parameters, indicating their superior potential as EGFR inhibitors. This study provides valuable insights into the molecular mechanisms underlying type 2 diabetes by highlighting the significant role of EGFR and its potential association with pancreatic cancer signaling pathways. Moreover, the identified hits from the virtual screening represent promising candidates for further investigation and development of improved drugs targeting EGFR.

bioinformatics↗

bioRxiv2023

M2-polarized macrophages prevent preterm birth and improve neonatal survival and immunity

Preterm birth (PTB), often preceded by preterm labor, is a major cause of neonatal morbidity and mortality worldwide. Most PTB cases involve intra-amniotic inflammation without detectable microorganisms, termed in utero sterile inflammation, for which there is no established treatment. Here, we propose homeostatic macrophages to prevent PTB and adverse neonatal outcomes caused by in utero sterile inflammation. Single-cell atlases of the maternal-fetal interface revealed that homeostatic maternal macrophages are reduced with human labor. M2 macrophage treatment prevented PTB and reduced adverse neonatal outcomes in mice with in utero sterile inflammation. Specifically, M2 macrophages halted premature labor by suppressing inflammatory responses in the amniotic cavity, including inflammasome activation, and mitigated placental and offspring lung inflammation. Moreover, M2 macrophages restored neonatal gut homeostasis and enhanced resistance to systemic bacterial infection. Our findings show that M2 macrophages are a promising strategy to mitigate PTB and improve neonatal outcomes from in utero sterile inflammation.

immunology↗

bioRxiv2023

The vaginal microbiota of pregnant women varies with gestational age, maternal age, and parity

The composition of the vaginal microbiota is heavily influenced by pregnancy and may factor into pregnancy complications, including spontaneous preterm birth. However, results among studies have been inconsistent, due in part to variation in sample sizes and ethnicity. Thus an association between the vaginal microbiota and preterm labor continues to be debated. Yet, before assessing associations between the composition of the vaginal microbiota and preterm labor, a robust and in-depth characterization of the vaginal microbiota throughout pregnancy in the specific study population under investigation is required. Herein, we report a large longitudinal study (N = 474 women, 1862 vaginal samples) of a primarily African-American cohort- which experiences a relatively high rate of pregnancy complications - evaluating associations between individual identity, gestational age, and other maternal characteristics with the composition of the vaginal microbiota throughout gestation resulting in term delivery. The primary factors influencing the composition of the vaginal microbiota in pregnancy are individual identity and gestational age at sampling. Secondary factors are maternal age, parity, obesity, and self-reported Cannabis use. The principal pattern across gestation is for the vaginal microbiota to remain or transition to a state of Lactobacillus dominance. This pattern can be mitigated by maternal parity and obesity. Regardless, network analyses reveal dynamic associations among specific bacterial taxa within the vaginal ecosystem, which shift throughout the course of pregnancy. This study provides a robust foundational understanding of the vaginal microbiota in pregnancy among African-Americans, in particular, and sets the stage for further investigation of this microbiota in obstetrical disease. IMPORTANCEThere is debate regarding links between the vaginal microbiota and pregnancy complications, especially spontaneous preterm birth. Inconsistencies in results among studies are likely due to differences in sample sizes and cohort ethnicity. Ethnicity is a complicating factor because, although all bacterial taxa commonly inhabiting the vagina are present among all ethnicities, the frequencies of these taxa vary among ethnicities. Therefore, an in-depth characterization of the vaginal microbiota throughout pregnancy in the specific study population under investigation is required prior to evaluating associations between the vaginal microbiota and obstetrical disease. This initial investigation is a large longitudinal study of the vaginal microbiota throughout gestation resulting in a term delivery in a primarily African-American cohort, a population that experiences disproportionally negative maternal-fetal health outcomes. It establishes the magnitude of associations between maternal characteristics, such as age, parity, BMI, and self-reported Cannabis use, on the vaginal microbiota in pregnancy.

microbiology↗

bioRxiv2023

MNRR1 activation by nitazoxanide abrogates lipopolysaccharide- induced preterm birth in mice

Intra-amniotic inflammation leading to preterm birth is one of the leading causes of neonatal morbidity and mortality. We recently found that the mitochondrial levels of MNRR1 (Mitochondrial Nuclear Retrograde, Regulator 1; also called CHCHD2, AAG10, or PARK22), an important bi-organellar regulator of cellular function, are reduced in the context of inflammation and that both genetic and pharmacological increase in MNRR1 levels can counter the inflammatory profile. We show here that nitazoxanide, a clinically-approved drug, is an activator of MNRR1 and prevents preterm birth in a well-characterized murine model caused by intra-amniotic lipopolysaccharide (LPS) injection. HighlightsO_LINitazoxanide exerts anti-inflammatory functions via activation of MNRR1. C_LIO_LIOral administration of nitazoxanide prevents preterm birth in mouse model of intra-intraamniotic LPS-induced inflammation. C_LI

immunology↗

bioRxiv2022

Systematic analysis of the genomic features involved in the binding preferences of transcription factors

Transcription factors (TFs) orchestrate gene expression and are at the core of cell-specific phenotypes and functions. One given TF can therefore have different binding sites depending on cell type and conditions. However, the TF core motif, as represented by Position Weight Matrix for instance, are often, if not invariably, cell agnostic. Likewise, paralogous TFs recognize very similar motifs while binding different genomic regions. We propose a machine learning approach called TFscope aimed at identifying the DNA features explaining the binding differences observed between two ChIP-seq experiments targeting either the same TF in two cell types or treatments or two paralogous TFs. TFscope systematically investigates differences in i) core motif, ii) nucleotide environment around the binding site and iii) presence and location of co-factor motifs. It provides the main DNA features that have been detected, and the contribution of each of these features to explain the binding differences. TFscope has been applied to more than 350 pairs of ChIP-seq. Our experiments showed that the approach is accurate and that the genomic features distinguishing TF binding in two different settings vary according to the TFs considered and/or the conditions. Several samples are presented and discussed to illustrate these findings. For TFs in different cell types or with different treatments, co-factors and nucleotide environment often explain most of the binding-site differences, while for paralogous TFs, subtle differences in the core motif seem to be the main reason for the observed differences in our experiments. The source code (python), data and results of the experiments described in this article are available at https://gite.lirmm.fr/rromero/tfscope.

bioinformatics↗

bioRxiv2022

Is there a placental microbiota? A critical review and re-analysis of published placental microbiota datasets

The existence of a placental microbiota is under debate. The human placenta has historically been considered sterile and microbial colonization has been associated with adverse pregnancy outcomes. Yet, recent investigations using DNA sequencing reported a microbiota in human placentas from typical term pregnancies. However, this detected microbiota could represent background DNA contamination. Using fifteen publicly available 16S rRNA gene datasets, existing data were uniformly re-analyzed. 16S rRNA gene Amplicon Sequence Variants (ASVs) identified as Lactobacillus were highly abundant in eight of fifteen studies. However, the prevalence of Lactobacillus, a typical vaginal bacterium, was clearly driven by bacterial contamination from vaginal delivery and background DNA. After removal of likely DNA contaminants, Lactobacillus ASVs were highly abundant in only one of five studies for which data analysis could be restricted to placentas from term cesarean deliveries. A six study sub-analysis targeting the 16S rRNA gene V4 hypervariable region demonstrated that bacterial profiles of placental samples and technical controls share principal bacterial ASVs and that placental samples clustered primarily by study origin and mode of delivery. Across studies, placentas from typical term pregnancies did not share a consistent bacterial taxonomic signal. Contemporary DNA- based evidence does not support the existence of a placental microbiota. IMPORTANCEEarly-gestational microbial influences on human development are unclear. By applying DNA sequencing technologies to placental tissue, bacterial DNA signals were observed, leading some to conclude that a live bacterial placental microbiome exists in typical term pregnancy. However, the low-biomass nature of the proposed microbiome and high sensitivity of current DNA sequencing technologies indicate that the signal may alternatively derive from environmental or delivery-associated bacterial DNA contamination. Here we address these alternatives with a re- analysis of 16S rRNA gene sequencing data from 15 publicly available placental datasets. After identical DADA2 pipeline processing of the raw data, subanalyses were performed to control for mode of delivery and environmental DNA contamination. Both environment and mode of delivery profoundly influenced the bacterial DNA signal from term-delivered placentas. Aside from these contamination-associated signals, consistency was lacking across studies. Thus, placentas delivered at term are unlikely to be the original source of observed bacterial DNA signals.

microbiology↗

bioRxiv2022

Bacterial profiles of the human placenta from term and preterm deliveries

Whether the human placenta is a sterile organ is under debate. Yet, infection of the amniotic cavity, including the placenta, is causally linked to preterm birth. This study compares the bacterial profiles of term and preterm placentas through culture and 16S rRNA gene sequencing of the amnion, amnion-chorion interface, subchorion, villous tree, and basal plate, while accounting for patient identity, mode of delivery, presence/absence of labor, and potential background DNA contamination. As no evidence of a placental microbiota in term pregnancy was found, these placentas were considered as controls. Placentas from preterm birth cases were more likely to yield bacterial cultures, and their bacterial DNA profiles were less rich than those of term controls, suggesting the predominance of only a few bacteria. Nevertheless, the bacterial DNA profiles of placentas from preterm cases and term controls were not consistently different. The placentas from preterm cases may often have a microbiota but the bacteria constituting these communities varied among the women. Mode of delivery had a pronounced effect on the bacterial profiles of all sampled levels of the placenta. Specifically, the bacterial DNA profiles of vaginally delivered placentas had higher relative abundances of Finegoldia, Gardnerella, Peptoniphilus, and Prevotella (each a common resident of the vaginal microbiota) than the profiles of cesarean-delivered placentas. Collectively, these data indicate that there is a not a placental microbiota in normal term pregnancy, and that although the placentas of some preterm cases were populated by bacteria, the identities of these bacteria varied among women delivering preterm. IMPORTANCEIf a placental microbiota exists, then current understanding of the roles of microorganisms in pregnancy outcomes need to be reconsidered. For instance, we will need to determine if a placental microbiota is beneficial to pregnancy outcome by excluding potential pathogens from colonizing the placenta and/or effectively priming the fetal immune system, and furthermore which characteristics of the placental microbiota preclude versus promote placental infection, which can result in pregnancy complications such as preterm birth. Our findings here are consistent with prior investigations that have reported that there is not a placental microbiota in typical human pregnancies. Yet, bacteria can be detected in placentas from preterm deliveries. The principal source of microorganisms invading the amniotic cavity, including the placenta, is the vaginal microbiota. Focus should be on elucidating the metabolic and/or virulence characteristics of the subset of bacteria within the vaginal microbiota that commonly invade the amniotic cavity, resulting in infection.

microbiology↗

bioRxiv2022

The single-cell atlas of the murine reproductive tissues during preterm labor

Preterm birth, the leading cause of perinatal morbidity and mortality worldwide, frequently results from the syndrome of preterm labor. Intra-amniotic infection is the best-established causal link to preterm labor, and involves premature activation of the parturition cascade in the reproductive tissues. Herein, we utilized single-cell RNA-sequencing (scRNA-seq) to generate a single-cell atlas of the murine uterus, decidua, and cervix in a model of infection-induced preterm labor. We show that preterm labor affects the transcriptomic profiles of specific immune and non-immune cell subsets. Shared and tissue-specific gene expression signatures were identified among affected cells. Importantly, determination of intercellular communications implicates specific cell types preterm labor-associated signaling pathways across tissues. Last, in silico comparison of murine and human uterine cell-cell interactions reveals conserved signaling pathways implicated in labor. Thus, scRNA-seq provides new insights into the preterm labor-driven cellular landscape and communications in the reproductive tissues.

immunology↗