Cell Biology & Molecular Genetics Theses and Dissertations
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Item THE ROLE OF GENOME ORGANIZATION AND FILAMENTOUS BACTERIOPHAGE ON GONOCOCCAL BIOLOGY AND PATHOGENICITY(2024) Kopew, Jessica; Stein, Daniel C; Cell Biology & Molecular Genetics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Gonorrhea, caused by the bacterium Neisseria gonorrhoeae (GC), represents a significant global health concern as it is the second most common bacterial STI and has a rising rate of antimicrobial resistance. The first study of this thesis aims to elucidate the causes and consequences of gonococcal genome reorganization. Here I found that when looking at many GC strains’ genomes, each GC strain had a unique genome organization including both inversions and translocation events. I also saw a consistent pattern of DNA high sequence similarity on both sides of the translocation or inversions, consistent with homologous recombination driven reorganization. PCR analysis of inversion events suggests that these large-scale reorganization events are both stable and rare. Growth curve analysis demonstrates a wide variability in growth rate between strains. Proteomic analysis suggests reorganization driven changes to replication termination location leads to upregulation of many kinds of proteins including energy metabolism and antimicrobial resistance associated genes. This study suggests that homologous recombination driven genome reorganization can have large impacts on gonococcal biology and pathogenicity. This study demonstrates the need for future gonococcal studies to use multiple GC strains from a diverse background to capture the wide variability in GC phenotypes. The second study of this thesis sought to uncover the role filamentous bacteriophage play in GC biology. I found that every GC strain currently in the NCBI database at the date of this study contains four filamentous bacteriophage gene regions in the GC genome. I found that FA1090Δfil (a GC strain lacking all four filamentous bacteriophage gene regions) grew poorly at 37⁰C both in broth and on agar, as compared to wild type FA1090. However, there was no difference when the strains were grown at 34⁰C or when grown without shaking, demonstrating the condition dependent nature of this growth advantage. FA1090Δfil formed larger bacterial aggregates than FA1090 WT. When these strains were analyzed for their ability to produce biofilms, no differences were seen in the overall biofilm’s biomass, yet the overall structure of the biofilms were different, with FA1090Δfil producing taller and rougher biofilms. Previous unpublished research in the Stein Lab demonstrates that filamentous phage derived proteins are capable of deteriorating the integrity of epithelial cell cultures and cervical tissue explants. The data from this chapter suggests that filamentous phage provide the gonococcus with a growth advantage, inhibit bacterial aggregation, alter the structure of the GC biofilm, and that phage proteins can lead to loss of the integrity of the epithelium. Taken en toto, these studies demonstrate that both alterations in bacterial genome organization and contributions from filamentous bacteriophage genomes can impact gonococcal biology and pathogenicity, which could be key to preventing and treating GC infections.Item Roles of Female Sex Hormones in Regulating Neisseria gonorrhoeae Colonization of the Human Cervix(2024) Di Benigno, Sofia; Song, Wenxia; Cell Biology & Molecular Genetics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Neisseria gonorrhoeae (GC) is a human-exclusive pathogen that infects the genital tract. Gonococcal infection may present with or without symptoms and can lead to a variety of serious sequelae if left untreated, especially in female patients. Despite this, there are few models that can effectively mimic GC infection in the female reproductive tract (FRT); of these, even fewer consider the impact of the menstrual cycle, an important feature of the FRT, on GC infection. I used the human cervical tissue explant model previously developed in our lab, which can recapitulate GC infection in vivo. Tissue explants were treated with the sex hormones estradiol and progesterone to mimic various stages of the menstrual cycle and examine its impact on GC infectivity. Estradiol was used to mimic the late proliferative phase, and a combination of estradiol and progesterone was used to mimic the middle of the secretory phase. The effects of hormones on GC infectivity were examined after 72 total hours of hormone treatment and 24 hours of inoculation with GC of strain MS11. My results show that treatment with estradiol and with a combination of estradiol and progesterone both increase the level of GC colonization on the endocervix, but not on the ectocervix, compared to controls that were not treated with hormones. However, the hormone treatment did not affect GC penetration of the cervical epithelium. Both hormone treatments increased the number of GC colonies on the endocervical epithelium, and a combination of estradiol and progesterone produced an additional population of large GC colonies, leading to an increase in the average colony size. These increases in colony number and size were not associated with an increase in the expression of carcinoembryonic antigen-related cell adhesion molecules (CEACAMs), which are the host receptors for GC Opa proteins. In contrast, treatment with estradiol induced a redistribution of CEACAMs from the luminal surface to the inside of epithelial cells. Additionally, estradiol altered the morphology of endocervical epithelial cells from columnar to cuboidal, but the integrity of cell-cell junctions was unchanged. The increase in colonization under high estradiol conditions was correlated with a decrease in levels of certain pro-inflammatory cytokines and chemokines, but this decrease was not sufficient to fully explain the increase in colonization. Next, I investigated the impact of cervical mucus on GC infectivity and interactions, as gel-forming mucin MUC5B but not MUC5AC increases with estradiol at the proliferation phase. Under both hormone treatment conditions, GC were able to establish close interaction with the luminal surface of the endocervical epithelial cells, displacing membrane-spanning mucin MUC1 in the membrane. Furthermore, GC were able to diffuse through an artificial mucin hydrogel and diffused more efficiently through a MUC5AC-dominant than a MUC5B-dominant hydrogel. Gel-forming mucins collected from cervical tissue explants enhanced GC aggregation in vitro, even at very low concentrations. However, mucins collected from estradiol-treated tissues showed less impact on GC aggregation than those collected from untreated tissues or tissues treated with both estradiol and progesterone. MUC5B and MUC5AC purified from cows and pigs also increase GC aggregation in vitro with GC aggregating more in a MUC5AC- than a MUC5B-dominant mucin mixture. Taken together, my research reveals for the first time that female sex hormones regulate GC colonization at the human cervix by changing the composition of the cervical mucus, providing a mechanism of hormonal regulation underlying the varying susceptibility of female patients to mucosal GC.Item Cell Population Shifts and Clinical Heterogeneity in Sjögren's Disease(2024) Pranzatelli, Thomas J; Johnson, Philip L.F.; Cell Biology & Molecular Genetics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Sjögren's disease (SjD) is a systemic autoimmune disease that causes loss of function of the salivary and lacrimal glands. Those with the disease, overwhelmingly female with an onset of disease in the fourth or fifth decade of life, commonly suffer from dry mouth, cavities and damage to the eyes. Patients present with a wide variety of clinical phenotypes, with variation in degree of immune infiltration and glandular damage as well as positivity for autoantibodies. This thesis uncovers the changes in cell population and gene expression in the gland that underpin diversity in disease severity. SjD patients lose the majority of a specific epithelial population in their labial salivary glands and, as the number of immune infiltrates grows the surviving members of this population can be found colocalizing with invading GZMK+ T cells and expressing markers of increased proliferation. Standard differential gene expression analysis highlighted gene markers of cell types changing in proportion with disease; an unenlightening result when the cell population changes are well-characterized. To avoid this pitfall an ensemble of random forests was trained to find genes predictive of patient subtypes without being correlated with diagnosis. Genes with high importance for autoantibody positivity were enriched for GO terms related to antigen processing and presentation. A master regulator of salivary gland identity, ZBTB7B, was identified from chromatin accessibility data. Mice with this transcription factor knocked out lose salivary flow and develop pockets of tissue in their glands that resemble other glands, eg., labial gland epithelium inside of parotid glands. This work supports a clinical presentation-specific approach to therapy and paves the path for reengineering the glands to correct the effects of disease.Item TRANSLATION, REPLICATION AND TRANSCRIPTOMICS OF THE SIMPLEST PLUS-STRAND RNA PLANT VIRUSES(2024) Johnson, Philip Zhao; Simon, Anne E; Cell Biology & Molecular Genetics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Plus (+)-strand RNA viruses are among the most common pathogens of plants and animals. Furthermore, they present model systems for the study of basic biological processes, including protein translation and RNA replication, and shed light on the versatile roles that RNA structures play in these processes. After cell entry, the next step in the (+)-strand RNA viral life cycle is translation of the viral genome to produce the viral RNA-dependent RNA polymerase (RdRp) and associated replication proteins necessary for viral replication to occur. For many (+)-strand RNA viruses lacking a 5´cap and 3´ poly(A) tail, translation depends upon RNA structural elements within their genomes capable of hijacking the host translation machinery, which for plant viruses are commonly located in their 3´ proximal regions and are termed 3´ cap-independent translation enhancer (CITE) elements. In Chapter 2, I report upon my work characterizing a new subclass of panicum mosaic virus-like translation enhancer (PTE) elements, which bind and co-opt for viral use the host translation initiation factor 4E (eIF4E) – the translation initiation factor normally responsible for binding and recognition of mRNA 5´caps during canonical eukaryotic translation initiation. Thus, PTE 3´CITEs present a novel mechanism for co-opting the critical host factor eIF4E. My work characterizing a new subclass of PTE 3´CITEs further revealed characteristics common among all PTE 3´CITEs pertaining to their mechanism of binding eIF4E.After translation of the necessary viral replication proteins, replication of the viral RNA occurs, which again is in large part mediated by RNA structural elements within the viral genome that can bind to the viral RdRp and/or host factors involved in viral replication. Indeed, RNA structural elements often serve dual roles in viral translation and replication and/or are located proximal to RNA structural elements involved in the alternate function. In Chapter 3, I discuss my work characterizing novel replication elements in the 3´ terminal regions of umbraviruses (family Tombusviridae). The uncovered replication elements appear to be specific to umbraviruses and are located immediately upstream of replication/translation elements that are common throughout the Tombusviridae, lending greater complexity to the already complex 3´ proximal structures of umbraviruses. While the study of (+)-strand RNA viruses has historically focused on their protein-coding transcripts, (+)-strand RNA viruses also commonly produce additional non-coding transcripts, including recombinant defective RNAs, typically containing 5´ and 3´ co-terminal viral genome segments, and (+/-)-foldback RNAs, composed of complementary (+)- and (-)-strand viral sequences joined together. Long non-coding RNAs that accumulate to high levels have also been reported for plant and animal (+)-strand RNA viruses in recent years, and truncations of viral transcripts also commonly arise due to host nuclease activity and/or premature termination of replication elongation by the viral RdRp. The rise of long-read high-throughput sequencing technologies such as nanopore sequencing presents an opportunity to fully map the complexity of (+)-strand RNA viral transcriptomes. In Chapter 4, I present my work performing this analysis, employing direct RNA nanopore sequencing, in which the transcripts present in an RNA sample of interest are directly sequenced. This analysis revealed for the umbra-like virus citrus yellow vein-associated virus (CY1): (i) three novel 5´ co-terminal long non-coding RNAs; (ii) D-RNA population dynamics; (iii) a common 3´ terminal truncation of 61 nt among (+)-strand viral transcripts; (iv) missing 3´ terminal CCC-OH motif in virtually all (-)-strand reads; (v) major timepoint- and tissue-specific differences; and (vi) an abundance of (+/-)-foldback RNAs at later infection timepoints in leaf tissues. This work also sheds light on the current shortcomings of direct RNA nanopore sequencing as a technique. Finally, the importance of RNA structural biology in the study of (+)-strand RNA viruses presents the need for specialized RNA structure drawing software with functionality to easily control the layout of nucleobases, edit base-pairs, and annotate/color the nucleobases and bonds in a drawing. It is through the visual exploration of RNA structures that RNA biologists routinely improve upon the outputs of RNA structure prediction programs and perform crucial phylogenetic analyses among related RNA structures. Large RNA structures, such as whole viral genomes thousands of nucleotides long, can only be studied in their entirety with the aid of RNA structure visualization tools. To this end, I have developed over the course of my doctoral education the 2D RNA structure drawing application RNAcanvas, which is available as a web app and has grown popular among the RNA biology community. RNAcanvas emphasizes graphical mouse-based interaction with RNA structure drawings and has special functionality well suited for the drawing and exploration of large RNA structures, such as automatic layout adjustment and maintenance, complementary sequence highlighting, motif finding, and performance optimizations. Large viral structures such as that of the 2.7 kb CY1 genomic RNA could not have been characterized without the aid of RNAcanvas. In Chapter 5, I present my work developing RNAcanvas.Item Mixture Models for Nucleic Acid Sequence Feature Analysis(2023) Wang, Bixuan; Mount, Stephen M; Cell Biology & Molecular Genetics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Signals in nucleotide sequences play a crucial role in interactions among macromolecules and the regulation of biological functional processes such as transcription, the splicing of messenger RNA precursors and translation. Recognition of signals in nucleotide sequences is the first step in functional annotation, which is critical for the identification of deleterious mutations and the identification of targets for disease treatment. One of the essential steps in gene expression, RNA splicing removes introns from newly transcribed RNA, ligating exons to generate mature RNA. Splicing involves the formation and recycling of the spliceosome, a large macromolecular complex whose assembly requires complex coordination by splicing factors through the recognition of RNA-protein binding sites. One potential method to reveal unknown subtypes of samples and identify distinctively distributed features is by applying a mixture model called the admixture model or Latent Dirichlet Allocation (LDA), which allows samples to have partial memberships of different clusters that can be interpreted for functional motif identification. By applying mixture models to RNA sequences, I found splicing signals such as the polypyrimidine tract and the branch point in intron sequences. Mixture models also showed motifs associated with reading frames from coding sequences, which further revealed potential coding regions from 5’ untranslated regions and long non-coding RNAs. Dynamic single-molecule imaging of nascent RNAs coupled with multiple genome-wide assays reveals that splicing happens far more often than expected, and partial intron removal can be captured prior to completion of the entire transcript. I hypothesize that the spliceosome progressively removes large introns in small pieces through 'recursive splicing' instead of removing the whole intron at once. However, the sequence features that distinguish sites of recursive splicing from canonical splice sites remain to be discovered. Here, I applied mixture models to sequences from human introns to identify sequence features associated with recursive splicing. This method helped me to recognize and visualize splicing signals from annotated intron sequences and identify potential coding sequences from human 5' untranslated regions and long non-coding RNA. After applying mixture models to the sequences surrounding recursive and canonical splicing sites, I found that transcripts where large introns can be recursively spliced can be distinguished from those without recursive splicing by the presence of CG-rich motifs flanking 5' splice sites upstream of first introns, and the absence of DNA methylation at these sites.In addition to applications of mixture models, I also explored RNA Bind-N-Seq data reflecting the binding activities of the splicing factor U2AF and found that the recursive 3' splice sites have higher U2AF binding affinities than the downstream canonical 3'SS. The observations suggest that, first, mixture models have the potential to identify functional motifs, including subtle signals in sequences such as the branch sites that only occur in a subgroup of introns. Second, the usage of recursive splicing sites is associated with sequence features in the first exons of the transcripts, suggesting a testable model for the regulation of recursive splicing in human introns.Item HIGH RESOLUTION MODELING OF ANTIBODY AND T CELL RECEPTOR RECOGNITION USING DEEP LEARNING(2024) Yin, Rui; Pierce, Brian G; Cell Biology & Molecular Genetics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Antibodies and T cell receptors (TCRs) are crucial for the immune system's ability to recognize and combat pathogens and cancer cells. High resolution structures of antibody-antigen complexes and TCR-peptide-MHC (TCR-pMHC) complexes provide key insights into their targeting. This knowledge has enabled the structure-based design of vaccines against viruses and pathogens, and therapeutics against cancer, immunological disorders, and viral infection. However, the vast diversity of the immune repertoire, along with limited resources and time constraints, makes experimentally determining the structures of most antibody-antigen and TCR-pMHC interactions challenging. To support these experimental efforts, computational approaches have been developed to model the structures of these protein-protein interactions. Despite decades of development, an accurate predictive understanding of the structural basis of antibody and TCR targeting remains a challenge. Recently, deep learning algorithms have shown major promise in the field of molecular modeling, due to their ability to analyze and learn complex non-linear features underlying molecular systems. For my research, I harnessed the power of deep learning tools toward predictive modeling of antibody and TCR recognition. First, I examined the structural and physiochemical features underlying antibody-antigen recognition for antibodies that interact with the SARS-CoV-2 receptor-binding domain (RBD). Then, as a critical step toward the development of highly accurate modeling tools, I conducted a thorough benchmarking of the state-of-the-art deep learning algorithm, AlphaFold, in modeling protein-protein complexes. Focusing on antibody-antigen complexes, I identified critical areas where AlphaFold's modeling capabilities could be enhanced. Next, I developed improvements of AlphaFold to perform accurate modeling of TCR-pMHC complexes, leading to the TCRmodel2 algorithm, which is available to the community as a public web server. This was followed by an effort to explore the use of increased sampling to improve AlphaFold success, which generated near-native predictions for approximately half of antibody-antigen test cases and nearly all TCR-pMHC test cases. These advances in modeling accuracy constitute a leap forward in our predictive understanding of immune recognition and can serve as a step toward successful design of more effective vaccines and therapeutics.Item TLR9 Activation as Immunotherapy in a Murine Model of Metastatic Lymphangioleiomyomatosis(2024) Amosu, Oluwamayowa; Maisel, Katharina; Cell Biology & Molecular Genetics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Pulmonary Lymphangioleiomyomatosis (LAM) is a slow progressing, metastasizing neoplasm primarily affecting women of reproductive age, marked by abnormal growth of smooth muscle-like cells leading to cystic lung destruction. Rapamycin, the only approved treatment for LAM, slows disease progression but ~40% of patients have partial or no response to treatment. There is an urgent need for new treatments. Research shows that LAM has hallmarks of cancer, like expression of immune checkpoint receptors, and is responsive to immune checkpoint inhibition in mouse models. This suggests that other anti-cancer strategies could be effective in treating LAM. In this thesis, we investigated toll like receptor (TLR) activation using intranasal administration of CpG, a TLR9 agonist, as LAM immunotherapy. We used a mouse model of metastatic LAM to determine survival after biweekly intranasal CpG therapy (10µg/ 5µg) with and without systemic α-PD-1, rapamycin, or α-CD317 therapy. We used ELISA to measure the cytokine profile and flow cytometry to quantify cell populations and characterize differences in the immune response between CpG-treated and untreated LAM lungs. We found that CpG treatment enhanced median survival from 32 to 60 days in murine LAM. Survival benefit of CpG treatment was inversely dose-dependent and more effective during early stages of disease. CpG-treatment was synergistic with both α-PD-1 checkpoint inhibition and rapamycin, with survival increasing from 60 days (CpG) to 71 days (CpG + α-PD-1) and 100 days (CpG + Rapamycin). Histological analysis showed that CpG treatment decreased the LAM nodule burden but inevitably caused tissue inflammation. Efficacy of CpG treatment in LAM is facilitated in part by plasmacytoid dendritic cells through decreased regulatory T cell numbers, priming of Th17 cells, and increased secretion of inflammatory and cytotoxic cytokines by CD8 T cells. Our findings suggest that adjuvant immunotherapy, like CpG, may offer new treatment strategies for LAM that are compatible with the current standard of care, rapamycin.Item Methods for Efficient Processing and Comprehensive Analysis of Single Cell Sequencing Data(2024) He, Dongze; Patro, Rob R.P.; Cell Biology & Molecular Genetics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Over the past decade, the rapid development of single-cell RNA-sequencing (scRNA-seq) technology has revolutionized the understanding of cellular differentiation, heterogeneity, transcriptional dynamics, and, many other biological processes. Despite the explosive growth of data analysis methods that aid in biological discovery, there are still many unsolved questions in raw data processing (also known as preprocessing) of scRNA-seq data --- the procedure for analyzing the raw sequenced fragments to generate the quantitative measurements of gene expression. In this dissertation, we first describe a computational ecosystem we developed that provides an end-to-end pipeline for accurately and efficiently processing single-cell sequencing data. Then, we will discuss the computational and analytical challenges we found during the development of alevin-fry and the solutions we provided for tackling these challenges. Chapters 2 and 3 demonstrate the computational successes we achieved for single-cell data processing. In Chapter 2, we present a novel computational framework, alevin-fry, for rapid, accurate, and memory-frugal quantification of single-cell sequencing data. In Chapter 3, we discuss an augmented execution context, simpleaf, of alevin-fry that not only provides a simplified user interface to the alevin-fry framework, but also offers many high-level simplifications for single-cell data processing, and for assisting with data provenance propagation and reproducible analyses. Our results demonstrate that, with the help of alevin-fry and simpleaf, we are able to process single-cell data from both "standard'' chemistries, as well as from more advanced and complex data types, and achieve the same level of accuracy as existing best-in-class methods, while being substantially faster and more memory efficient. Chapter 4 introduces Forseti, a mechanistic model to probabilistically assign a splicing status to scRNA-seq reads. As the first probabilistic and mechanistic model for solving the ambiguity of splicing status in tagged-end, short-read scRNA-seq data, we show that Forseti can be used to accurately and efficiently infer the splicing status of scRNA-seq reads, and to help identify the correct gene origin for multigene-mapped reads. In Chapter 5, we describe the results of a comprehensive analysis of "off-target'' reads (reads whose mappings cannot be accounted for under the presumed and intended components of the underlying protocol) in scRNA-seq. Overall, our results suggest that off-target scRNA-seq reads contain underappreciated information about various transcriptional activities. These observations about yet-unexploited information in existing scRNA-seq data will help guide and motivate the community to improve current algorithms and analysis methods, and to develop novel approaches that utilize off-target reads to extend the reach and accuracy of single-cell data analysis pipelines.Item STUDIES ON VARIABILITY IN CANCER GENE EXPRESSION: FROM SINGLE PROTEINS TO POPULATIONS(2023) Crawford, David Robert; Mount, Stephen M; Cell Biology & Molecular Genetics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)In this dissertation I describe four projects investigating different aspects of the variability of gene expression in human cancers. In the first chapter, we analyze epidemiological incidence rates for autoimmune diseases and cancers across numerous populations and find that sex biases in incidence rates are positively correlated between autoimmune diseases and cancers arising from the same tissue. We find that across these tissues the expression of protein-codingmitochondrial genes is positively correlated with both autoimmune disease and cancer incidence rate sex biases, suggesting a possible direction for further investigation. In the second chapter, I construct a computational pipeline to conduct unbiased searches in large databases for possible events accounting for cancer neopeptides predicted by mass spectrometry. I identify several ribosomal frameshift-derived neopeptides from HLA-peptidomics data and discuss future approaches for further improving the accuracy and flexibility of our approach. In the third chapter, I compare the power of different multivariate Cox proportional hazards survival models based on gene- and below-gene-level expression measures to predict genes whose expression in tumor samples at diagnosis affects subsequent survival of cancer patients. I find that models based on both gene-level expression and isoform-level expression (whether transcript abundance or relative transcript abundance) identify the greatest number of statistically significant genes of interest. Finally, in the fourth chapter I briefly explore how heteroformity and entropy measures can be used to examine differences in mRNA splicing diversity at numerous levels of comparison. I propose some simple visualizations that harness these measures to display patterns in splicing diversity.Item Molecular and Biophysical Bases of Intracellular Electric Fields in Pollen Tubes(2022) Oliveira Nunes, Custódio; Feijό, José A.; Cell Biology & Molecular Genetics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Pollen tubes are the male gametophyte of flowering plants. They are arguably one of the fastest-growing cells in nature and inherently an excellent model for studying cellular processes like apical growth, polarity, and chemotropism. Pollen tube development is associated with a unique choreography of ion fluxes and cytosolic ion gradients of Cl-, Ca2+, H+, and K+, creating a unique electrochemical environment, where alternating depolarizing ionic currents at their growing apex are spatially separated from hyperpolarizing currents in their shank. We hypothesize that these electrical differences generated by the opposite ionic patterns could sustain a standing membrane potential gradient at the growing apex. In agreement with evidence from other cellular electrotaxis phenomena, we further hypothesize that a standing electric field gradient could be mechanistic in terms of cell polarity and chemotropism of pollen tubes.Here we show, for the first time, the existence of a standing membrane potential gradient in pollen tubes, confirmed in three different species, thus suggesting a conserved role in apical growth. This conclusion was achieved using three complementary methods, two membrane potential dyes with opposite fluorescence kinetics, and a genetic probe for cytosolic potassium (K+). The K+ gradient is focused at the pollen tube tip, and is compatible with previous information on the individual ion features. Of relevance, K+ shows a negative gradient from the tip, the first ever described in a living cell, suggestive of K+ apical efflux that contributes to the depolarized state. Quantifications of the fluorescent dyes estimate an apical depolarization of approximately 30mV compared to the shank. Screening of ion-channel mutants inducing male-fertility phenotypes supports the hypothesis that this bioelectric oddity is mechanistic for pollen tube’s critical functions, fast invasive growth and chemotropism. Furthermore, we determined that anionic lipids determine the emergence of the pollen tube and correlate with the apical depolarization area, suggesting that they may act as physical determinants of the growing apex. These results open important questions in our understanding of the bioelectrical processes determining cell growth, polarity, morphogenesis, and chemotropic reactions.