Biology subjects

Goods, B. A.

Publications and source records attributed to Goods, B. A..

11 recordsLinked to original sources

bioRxiv2026

Proprotein convertase activity regulates cumulus-oocyte-complex matrix integrity and cumulus cell migration during ovulation via a GDF9-dependent mechanism

Cumulus cells have well-established roles early in ovulation but the key molecules that drive their behavior in later stages, leading to follicle rupture, remain underexplored. Here, we observed that inhibition of proprotein convertases (PCSKs) via a pan-inhibitor (PCI) impaired follicular rupture and disrupted the cumulus matrix integrity within intact follicles. Reduced cumulus cell adherence to the cumulus-oocyte-complex (COC) matrix was also observed in isolated COCs and notably occurred late during the maturation window without affecting oocyte maturation. Visualization of PCSK transcript and protein expression, as well as selective inhibition of specific PCSKs, determined that the observed phenotype in COCs is likely attributed to PCSK5A inhibition. We conducted bulk RNA-sequencing and proteomics of PCI-treated COCs which revealed that PCSK inhibition caused dysregulation of extracellular matrix organization, cell migration/adhesion, and TGF-{beta} signaling pathways. Subsequent validation showed that this inhibition translated to disrupted matrix organization and altered migratory and adhesive behaviors in cumulus cells. The TGF-{beta} ligand GDF9 has a predicted PCSK cleavage site, and supplementation with GDF9 rescued matrix integrity suggesting its role as a downstream substrate of PCSKs to regulate matrix organization. Altogether, this study identified PCSK5A and GDF9 as key regulators of COC matrix integrity and cumulus cell migration during late ovulation. These findings highlight novel factors required for follicle rupture which can be leveraged for the development of fertility therapeutics and contraceptives.

cell biology↗

bioRxiv2025

Multiomic analysis reveals that polyamines alter G. vaginalis-induced cervicovaginal epithelial cell dysfunction

An anaerobe-dominant, Lactobacillus-deplete cervicovaginal microbiome is associated with adverse reproductive outcomes. Gardnerella vaginalis, a cervicovaginal anaerobe, alters cervicovaginal epithelial cell function, resulting in immune activation and barrier breakdown. Host-microbial mechanisms inducing this epithelial dysfunction remain unknown. We show microbe-specific alterations in cervicovaginal epithelial cell metabolite profiles where G. vaginalis, but not Lactobacillus crispatus, increases polyamine biosynthesis. Pretreatment with polyamines (putrescine, spermidine and spermine) globally shifts G. vaginalis-induced transcriptomic profiles. Alterations in enzyme transcripts responsible for polyamine synthesis and catabolism provide evidence that G. vaginalis modifies polyamine biosynthesis. Polyamine-mediated transcriptomic changes include genes related to bacterial defense, inflammation, and epigenetic processes. Polyamines mitigate G. vaginalis-induced inflammatory responses through reduction of cytokines/chemokines and matrix metalloproteinases. In vitro transcriptional signatures positively correlated to existing human datasets. The ability of cervicovaginal metabolites to alter microbe-mediated changes in epithelial cell function suggests that metabolite-microbe interactions are critical mediators of epithelial defense against a Lactobacillus-deplete microbiota.

microbiology↗

bioRxiv2025

Benchmarking sketching methods on spatial transcriptomics data

High-throughput spatial transcriptomics (ST) now profiles hundreds of thousands of cells or locations per section, creating computational bottlenecks for routine analysis. Sketching, or intelligent sub-sampling, addresses scale by selecting small, representative subsets. While effective for scRNA-seq data, existing sketching methods, which optimize coverage in expression space but ignore physical location, can introduce spatial bias when applied to ST data. To explore the impact of sketching on ST analysis, we systematically benchmarked uniform sampling, leverage-score sampling, Geosketch (minimax/Hausdorff), and scSampler (maximin) across multiple real ST datasets (mouse ovary, MERFISH brain, human breast cancer, lung) and simulations, using three input representations: PCA embeddings, spatial coordinates, and spatially smoothed embeddings. We show that expression-only designs capture global transcriptomic heterogeneity but distort tissue architecture by over-sampling high-variability regions and under-sampling homogeneous areas. Coordinate-only sampling restores tissue coverage but misses transcriptional extremes. A simple spatially aware extension, computing leverage scores from a randomized SVD basis smoothed by a spatial weights matrix, strikes a favorable balance, recovering rare cell states while maintaining uniform tissue coverage and avoiding edge effects. Across robust Hausdorff distances, clustering stability (ARI), PCA loading drift, and local cell-type MSE, spatially smoothed leverage scores match or outperform alternatives. These results motivate joint spatial-transcriptomic sketching objectives to enable fast, unbiased analyses of increasingly large ST datasets.

bioinformatics↗

bioRxiv2025

A streamlined and comprehensive protocol for the generation and multi-omic analysis of human monocyte-derived macrophages

Macrophages serve both as a first line of defense against invading pathogens and mediate tissue homeostasis. These cells are inherently responsive and heterogeneous and lie on a spectrum of activation states book-ended by M1-like (inflammatory) and M2-like (anti-inflammatory) extremes. The study of human macrophages is necessary to unravel the complex signals and environmental cues that these cells integrate to create their varied phenotypes. In vitro protocols to differentiate human monocytes into macrophages use many distinct activation stimuli at variable concentrations and for differing durations of treatment that can impact macrophage fate. These variations can make it challenging to reproduce findings and compare datasets across research environments. Additionally, few protocols to date have performed rigorous characterization with input material from frozen peripheral blood mononuclear cells (PBMCs). This is important since the availability of fresh blood can often be limiting and can lead to a loss of standardized procedures, particularly for cell therapy applications. Here, we have developed a comprehensive protocol to generate human macrophages from monocytes where we rigorously characterize the impact of differentiation conditions and polarization conditions on human macrophages. We provide a detailed protocol for their characterization using several omics readouts, including their cytokine production and transcriptomes. We also perform depolarization experiments to determine durability of macrophage immunophenotype post-removal of polarizing stimuli. Finally, we demonstrate that nuclei can be isolated and profiled by snRNA-seq directly from macrophages in culture, alleviating the need to detach these adherent cells for downstream multi-ome analyses. Taken together, we provide a comprehensive, detailed and streamlined procedure for the differentiation and characterization of human macrophages from monocytes isolated from frozen PBMCs. This is important for enabling the study of macrophages in a more systematic way from biobanked material.

immunology↗

bioRxiv2025

Disrupted MOS signaling alters meiotic cell cycle regulation and the egg transcriptome

Mammalian female meiosis is tightly regulated to produce a developmentally competent egg. Oocytes enter meiosis in the fetal ovary and then arrest at prophase I until sexual maturation. Upon hormonal stimulation, a subset of oocytes resumes meiosis at which time, new transcription is halted. Oocytes then complete meiosis I, enter metaphase II, and arrest until fertilization, a process essential for egg competency and fertility. The MOS kinase is a key regulator of the metaphase II arrest, activating the MAPK signaling cascade. Loss of MOS in female mice disrupts the maintenance of the metaphase II arrest, leading some eggs to extrude two polar bodies and some to divide beyond anaphase II. To investigate the consequences of the Mos deletion, we performed live imaging and found that mos-/- eggs exhibit transient chromosome separation events in meiosis I, suggesting a role for MOS in coordinating the timing of meiotic divisions. Further analysis showed that new transcription is required for mos-/- eggs to undergo additional divisions but not for second polar body extrusion. Surprisingly, single-egg sequencing revealed extensive differences in gene expression between wildtype and mos-/-eggs, including those with only one polar body. Many of the differentially expressed genes were involved in cell cycle regulation, including Aurka, Bub3, and Cdk7. Other upregulated pathways included metabolism of RNA, transcription, and neddylation. Furthermore, the gene expression profile of mos-/- eggs was markedly different from that of wildtype eggs chemically activated to undergo embryo-like divisions. Our findings demonstrate that MOS plays a crucial role in meiotic cell cycle regulation and helps ensure that the egg maintains the proper transcriptome necessary for developmental competence.

cell biology↗

bioRxiv2025

Transcriptomic analysis of whole staged ovarian follicles reveals stage-specific folliculogenesis signatures in mice

Activation and maturation of ovarian follicles are essential for female reproduction, yet the underlying molecular and transcriptional mechanisms that govern these processes remain poorly understood. In this study, we used single follicle RNA-sequencing (RNA-seq) to identify transcriptional signatures of staged ovarian follicles, from primordial to secondary stages, to uncover the genes and pathways involved in early folliculogenesis. Our findings demonstrate that primordial follicles are transcriptionally distinct from growing follicles, with enrichment in DNA integrity and RNA processing pathways, which may play a role in preserving oocyte genomic stability and cell state during dormancy. Additionally, our analysis reveals minimal transcriptomic differences between primary and secondary follicles using traditional differential expression analysis. To better distinguish growing follicle stages, we introduce unsupervised approaches, including discrete-variable predictors of follicle stage and weighted gene co-expression analysis. We identified pathways involved in DNA integrity, meiotic arrest, and cellular metabolism that drive the transition from dormant to active follicle states, as well as pathways related to cellular growth, ECM organization, and biosynthesis in growing follicle stages. Our study offers novel insights into the molecular mechanisms governing early follicle activation and growth, providing a foundation for future research with applications in reproductive biology, contraception, and fertility preservation. Author SummaryThe development of ovarian follicles is essential for female fertility, but the molecular signals that control their growth remain unclear. In this study, we used advanced gene sequencing techniques to analyze the genetic activity of individual ovarian follicles at different stages of early development. We found that dormant follicles have unique gene expression patterns that help protect the genetic material of the egg and maintain their inactive state. In contrast, follicles that have begun to grow show increased activity in genes related to cell growth, communication, and structural changes. Interestingly, we observed that early growing follicles are more similar to each other than previously thought, prompting us to apply new analytical methods to better distinguish their developmental stages. Our findings highlight key biological pathways that regulate the transition from dormant to active follicles and uncover new genes that may play a role in this process. Understanding these mechanisms provides valuable insights into ovarian biology and could inform future research on fertility treatments, contraception, and reproductive health.

bioinformatics↗

bioRxiv2024

Single-cell and spatiotemporal profile of ovulation in the mouse ovary

Ovulation is a spatiotemporally coordinated process that involves several tightly controlled events, including oocyte meiotic maturation, cumulus expansion, follicle wall rupture and repair, and ovarian stroma remodeling. To date, no studies have detailed the precise window of ovulation at single-cell resolution. Here, we performed parallel single-cell RNA-seq and spatial transcriptomics on paired mouse ovaries across an ovulation time course to map the spatiotemporal profile of ovarian cell types. We show that major ovarian cell types exhibit time-dependent transcriptional states enriched for distinct functions and have specific localization profiles within the ovary. We also identified gene markers for ovulation-dependent cell states and validated these using orthogonal methods. Finally, we performed cell-cell interaction analyses to identify ligand-receptor pairs that may drive ovulation, revealing previously unappreciated interactions. Taken together, our data provides a rich and comprehensive resource of murine ovulation that can be mined for discovery by the scientific community.

bioinformatics↗

bioRxiv2023

Systematic benchmarking of imaging spatial transcriptomics platforms in FFPE tissues

Emerging imaging spatial transcriptomics (iST) platforms and coupled analytical methods can recover cell-to-cell interactions, groups of spatially covarying genes, and gene signatures associated with pathological features, and are thus particularly well-suited for applications in formalin fixed paraffin embedded (FFPE) tissues. Here, we benchmarked the performance of three commercial iST platforms on serial sections from tissue microarrays (TMAs) containing 23 tumor and normal tissue types for both relative technical and biological performance. On matched genes, we found that 10x Xenium shows higher transcript counts per gene without sacrificing specificity, but that all three platforms concord to orthogonal RNA-seq datasets and can perform spatially resolved cell typing, albeit with different false discovery rates, cell segmentation error frequencies, and with varying degrees of sub-clustering for downstream biological analyses. Taken together, our analyses provide a comprehensive benchmark to guide the choice of iST method as researchers design studies with precious samples in this rapidly evolving field.

cancer biology↗

bioRxiv2021

Cellular and transcriptional diversity over the course of human lactation

Human breast milk is a dynamic fluid that contains millions of cells, but their identities and phenotypic properties are poorly understood. We used single-cell RNA-seq (scRNA-seq) to characterize the transcriptomes of cells from human breast milk (hBM) across lactational time from 3 to 632 days postpartum in 15 donors. We find that the majority of cells in human breast milk are lactocytes, a specialized epithelial subset, and cell type frequencies shift over the course of lactation yielding greater epithelial diversity at later points. Analysis of lactocytes reveals a continuum of cell states characterized by transcriptional changes in hormone, growth factor, and milk production related pathways. Generalized additive models suggest that one sub-cluster, LALBAlow epithelial cells, increase as a function of time postpartum, daycare attendance, and the use of hormonal birth control. We identify several sub-clusters of macrophages in hBM that are enriched for tolerogenic functions, possibly playing a role in protecting the mammary gland during lactation. Our description of the cellular components of breast milk, their association with maternal-infant dyad metadata and quantification of alterations at the gene and pathways levels provides the first detailed longitudinal picture of human breast milk cells across lactational time. This work paves the way for future investigations of how a potential division of cellular labor and differential hormone regulation might be leveraged therapeutically to support healthy lactation and potentially aid in milk production.

genomics↗

bioRxiv2021

Tissue engineered organoid co-culture model of the cycling human endometrium in a fully-defined synthetic extracellular matrix

The human endometrium undergoes recurring cycles of growth, differentiation, and breakdown in response to sex hormones. Dysregulation of epithelial-stromal communication during hormone cycles is linked to myriad gynecological disorders for which treatments remain inadequate. Here, we describe a completely defined, synthetic extracellular matrix that enables co-culture of human endometrial epithelial and stromal cells in a manner that captures healthy and disease states across a simulated menstrual cycle. We parsed cycle-dependent endometrial integrin expression and matrix composition to define candidate cell-matrix interaction cues for inclusion in a polyethylene glycol (PEG)-based hydrogel crosslinked with matrix metalloproteinase-labile peptides. We semi-empirically screened a parameter space of biophysical and molecular features representative of the endometrium to define compositions suitable for hormone-driven expansion and differentiation of epithelial organoids, stromal cells, and co-cultures of the two cell types. Each cell type exhibited characteristic morphological and molecular responses to hormone changes when co-encapsulated in hydrogels tuned to a stiffness regime similar to the native tissue and functionalized with a collagen-derived adhesion peptide (GFOGER) and a fibronectin-derived peptide (PHSRN-K-RGD). Analysis of cell-cell crosstalk during IL-1{beta}-induced inflammation revealed dysregulation of epithelial proliferation mediated by stromal cells. Altogether, we demonstrate the development of a fully synthetic matrix to sustain the dynamic changes of the endometrial microenvironment and support its applications to understand menstrual health and endometriotic diseases. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=114 SRC="FIGDIR/small/462577v2_ufig1.gif" ALT="Figure 1"> View larger version (47K): org.highwire.dtl.DTLVardef@1cc97dcorg.highwire.dtl.DTLVardef@1061157org.highwire.dtl.DTLVardef@15c8c35org.highwire.dtl.DTLVardef@f902d7_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

bioRxiv2020

Leukocyte dynamics after intracerebral hemorrhage in a living patient reveal rapid adaptations to tissue milieu

Intracerebral hemorrhage (ICH) is a devastating form of stroke with a high mortality rate and few treatment options. Discovery of therapeutic interventions has been slow given the challenges associated with studying acute injury, particularly over time, in the human brain. Inflammation induced by exposure of brain tissue to blood appears to be a major part of brain tissue injury. Here we longitudinally profiled blood and cerebral hematoma effluent from a patient enrolled in the Minimally Invasive Surgery with Thrombolysis in Intracerebral Haemorrhage Evacuation (MISTIEIII) trial, offering a rare window into the local and systemic immune responses to acute brain injury. Using single-cell RNA-sequencing, we characterized the local cellular response during ICH in the brain of a living patient at single-cell resolution for the first time. Our analysis revealed rapid shifts in the activation states of myeloid and T cells in the brain over time, suggesting that leukocyte responses are dynamically reshaped by the hematoma microenvironment. Interestingly, the patient had an asymptomatic re-bleed (second local exposure to blood) that our transcriptional data indicated occurred more than 30 hours prior to detection by CT scan. This case highlights the rapid immune dynamics in the brain after ICH and suggests that sensitive methods like scRNA-seq can inform our understanding of complex intracerebral events.

immunology↗