Biology subjects

Arcanjo, R. B.

Publications and source records attributed to Arcanjo, R. B..

4 recordsLinked to original sources

bioRxiv2026

Single-cell roadmap of bovine oogenesis and somatic niche interactions during fetal ovarian development

The major events of female germline establishment, from primordial germ cell (PGC) specification to assembly of primordial follicles, occur during embryonic/fetal development. This study presents a single-cell RNA-sequencing atlas of the bovine fetal ovary at four gestational timepoints: estimated day 50, and timed pregnancies at days 70, 90, and 120, capturing the progression of PGCs through commitment, meiotic entry, and early oocyte growth. Fourteen transcriptionally distinct cell populations were identified, including stromal, epithelial, endothelial, immune, somatic support cell, and germ cell lineages. Sub-clustering of the germ cell population resolved six developmental stages (PGCs, transitioning oogonia, proliferative oogonia, committed oogonia, meiotic prophase I oogonia, and oocytes), while that of the somatic support cell compartment revealed five granulosa cell subtypes (steroidogenic, pre-granulosa 1, pre-granulosa 2, pre-granulosa 3, and epithelial cells). Trajectory analysis reconstructed the developmental path of PGCs to oocytes, with sequential activation of meiotic and oocyte-specific gene programs. Representation of all six germ cell stages at day 120 pointed to asynchronous oogenesis in the fetal ovary, which was validated and shown to be region-specific by protein immunolocalization. Intercellular signaling networks between germ cells and the somatic niche were mapped, revealing strong interactions through BMP, KIT, IGF, IGFBP, WNT, and MDK pathways with temporal specificity across gestational ages. The bovine germ cell and pre-granulosa cell subtypes demonstrate significant transcriptional parallels with similarly-staged cells from human fetal ovaries, establishing the cow as a reliable model for human germ cell and ovarian development. Collectively, these data provide a developmental roadmap for bovine oogenesis at the single-cell resolution that advances fundamental understanding of gametogenesis and informs strategies for advanced assisted reproduction.

developmental biology↗

bioRxiv2025

Molecular profiling of bovine primordial germ cell specification and migration onset reveals a conserved program in bilaminar disc embryos

The goal of this study was to establish the timing and location of bovine primordial germ cell (PGC) specification, as well as the molecular characteristics that differentiate early PGCs from other cells in the embryo. A founder population of PGCs was identified via protein immunolocalization in the posterior epiblast (TBXT+) region at E16, by the unique co-expression of OCT4, SOX17, PRDM1, and TFAP2C with absent SOX2. At E20, PGCs were spread along the allantois and hindgut endoderm, indicative of migration onset. Single-cell RNA-sequencing at E20-22 revealed ten PGCs that were subset using the above markers. Further analysis of this population uncovered conserved and novel markers of the early germline and gave numerous insights into their developmental status, including markers associated with pluripotency maintenance, cell migration, repression of the somatic program, and initiation of epigenetic remodeling. This work establishes the region and transcription factor network of bovine PGC specification at day 16 of embryonic development and the first transcriptomic profile of migratory PGCs in cattle, demonstrating a conserved program with other species that form as a bilaminar embryonic disc leading to gastrulation.

developmental biology↗

bioRxiv2024

Primed bovine embryonic stem cell lines can be derived at diverse stages of blastocyst development with similar efficiency and molecular characteristics

In this study, we established bovine embryonic stem cell (bESC) lines from early (eBL) and full (BL) blastocysts to determine the efficiency of bESC derivation from an earlier embryonic stage and compare the characteristics of the resulting lines. Using established medium and protocols for derivation of primed bESCs from expanded blastocysts, we derived bESC lines from eBLs and BLs with the same efficiency (4/12 each, 33%). Regardless of original blastocyst stage, bESC lines had a similar phenotype, including differentiation capacity, stable karyotype, and pluripotency marker expression over feeder-free transition and long-term culture. Transcriptome and functional analyses indicated that eBL- and BL-derived lines were in primed pluripotency. We additionally compared RNA-sequencing data from our lines to bovine embryos and stem cells from other recent reports, finding that base medium was the predominant source of variation among cell lines. In conclusion, our results show that indistinguishable bESC lines can be readily derived from eBL and BL, widening the pool of embryos available for bESC establishment. Finally, our investigation points to sources of variation in cell phenotype among recently reported bESC conditions, opening the door to future studies investigating the impact of factors aside from signaling molecules on ESC derivation, maintenance, and performance. SUMMARY STATEMENTPrimed bovine embryonic stem cell lines can be readily established from early blastocysts and are indistinguishable from full blastocyst-derived lines, widening the pool of embryos available for stem cell derivation.

cell biology↗

bioRxiv2023

Machine learning assisted health viability assay for mouse embryos with artificial confocal microscopy (ACM)

The combination of a good quality embryo and proper maternal health factors promise higher chances of a successful in vitro fertilization (IVF) procedure leading to clinical pregnancy and live birth. Of these two factors, selection of a good embryo is a controllable aspect. The current gold standard in clinical practice is visual assessment of an embryo based on its morphological appearance by trained embryologists. More recently, machine learning has been incorporated into embryo selection "packages". Here, we report a machine-learning assisted embryo health assessment tool utilizing a quantitative phase imaging technique called artificial confocal microscopy (ACM). We present a label-free nucleus detection method with novel quantitative embryo health biomarkers. Two viability assessment models are presented for grading embryos into two classes: healthy/intermediate (H/I) or sick (S) class. The models achieve a weighted F1 score of 1.0 and 0.99 respectively on the in-distribution test set of 72 fixed embryos and a weighted F1 score of 0.9 and 0.95 respectively on the out-of-distribution test dataset of 19 time-instances from 8 live embryos.

bioengineering↗