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Results for “cell biology”

Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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At least 73 records · Page 4Linked to original sources

bioRxiv2021

Breathing on Chip: Biomechanical forces change airway epithelial cell biology ina human Airway Lung-Chip

Human lung function is intricately linked to blood flow and breathing cycles, but it remains unknown how these dynamic cues shape human airway epithelial biology. Here we report a state-of-the-art protocol for studying effects of physiological airflow and stretch on differentiation, cellular composition, and mucociliary clearance of human primary airway epithelial cells cultured on a perfused airway chip. Perfused epithelial tissue cultures developed a large airway-like cellular composition with accelerated maturation and polarization of mucociliary clearance when compared to traditional (static) culture methods. Additional application of airflow and stretch to the airway chip resulted in a cellular composition more comparable to the small(er) airways, reduced baseline secretion of interleukin-8 and other inflammatory proteins, and reduced gene expression of matrix metalloproteinase (MMP) 9, fibronectin, and other extracellular matrix factors. These results indicate that breathing-like mechanical stimuli are important modulators of airway epithelial cell differentiation and homeostasis and that their fine-tuned application could generate models of specific epithelial regions, pathologies, and mucociliary (dys)function.

cell biology↗

bioRxiv2021

New cell biological explanations for kinesin-linked axon degeneration

Axons are the slender, up to meter-long projections of neurons that form the biological cables wiring our bodies. Most of these delicate structures must survive for an organisms lifetime, meaning up to a century in humans. Axon maintenance requires life-sustaining motor protein-driven transport distributing materials and organelles from the distant cell body. It seems logic that impairing this transport causes systemic deprivation linking to axon degeneration. But the key steps underlying these pathological processes are little understood. To investigate mechanisms triggered by motor protein aberrations, we studied more than 40 loss- and gain-of-function conditions of motor proteins, cargo linkers or further genes involved in related processes of cellular physiology. We used one standardised Drosophila primary neuron system and focussed on the organisation of axonal microtubule bundles as an easy to assess readout reflecting axon integrity. We found that bundle disintegration into curled microtubules is caused by the losses of Dynein heavy chain and the Kif1 and Kif5 homologues Unc-104 and Kinesin heavy chain (Khc). Using point mutations of Khc and functional loss of its linker proteins, we studied which of Khcs sub-functions might link to microtubule curling. One cause was emergence of harmful reactive oxygen species through loss of Milton/Miro-mediated mitochondrial transport. In contrast, loss of the Kinesin light chain linker caused microtubule curling through an entirely different mechanism appearing to involve increased mechanical challenge to microtubule bundles through de-inhibition of Khc. The wider implications of our findings for the understanding of axon maintenance and pathology are discussed.

cell biology↗

bioRxiv2024

A CELL BIOLOGY STUDY REVEALS NEW INSIGHTS INTO THE TRANSPORT MECHANISMS OF OOMYCETE EFFECTORS

Oomycete pathogens use dedicated effector proteins (also known as virulence factors) that manipulate the host during infection to the benefit of the pathogen. Despite extensive efforts, the understanding of how oomycete effector proteins are transported and delivered to the host is limited. Here, we show that Phytophthora capsici infecting Nicotiana benthamiana secretes its effectors through secretory pockets, haustoria, and from hyphae. We provide evidence that Avr3, belonging to the class of RxLR effector proteins that can be secreted and translocated to the plant cell, is found to accumulate in a distinct ring-shaped zone around the neck region of haustoria. The association with the haustorial neck is determined by an RxLR-EER motif and mutating this motif redirects Avr3 to the extrahaustorial matrix enveloping the full haustoria body. Furthermore, mass spectrometry analysis of immunoprecipitated Avr3 indicates that the RXLR motif remains intact when Avr3 is secreted from the haustorium during plant infection. We thus propose that the RXLR-EER motif determines the entry in the host cell by guiding Avr3 to the haustorial neck region, which may be a structure analogous to the Biotrophic Interfacial Complex of the fungus Magnaporthe sp.

cell biology↗

bioRxiv2024

Impact of flagellated and elongated morphological phenotypes on the focusing behaviours of biological cells in inertial microfluidic devices

Inertial microfluidics has demonstrated tremendous potential to impact biological - and notably medical - fields, by offering a highly versatile, portable and cost-effective approach to cell focusing and sorting. While the range of applications of inertial devices spans medical diagnostics, bioprocessing or water engineering to mention a few, translation is still impeded by the lack of clear understanding of cell interactions in such devices. This often leads to bespoke designs that take years of development and characterisation for one targeted application, and limited tools for informed optimisation. A more fundamental knowledge of inertial behaviours is key to future translational works and impact, by enabling a deeper understanding of inertial forces in biological systems. Towards this goal, this paper focuses on high-throughput morphological phenotyping of the single-celled, flagellated parasite Leishmania mexicana to better understand how variations in cell body length, width and flagellated status impact the focusing patterns of highly non-spherical cells in curved inertial devices. Some of the key findings in this study include i) not all organelles, such as flagella, will alter focusing if the body shape is conserved, ii) the impact of cell shape is specific to a channel design and slight changes in e.g., cell confinement can completely change focusing patterns, iii) elongated prolate-like cells align in different orientations depending on their lateral position with a curved channel and iv) despite variabilities observed in focusing patterns for elongated versus rounder cell phenotypes, large morphological variations can be completely overcome at high Reynolds numbers so that all phenotypes tightly focus at a single position (here towards the channel outer wall). This last finding, in particular, may open new avenues for highly efficient cell enrichment processes, such as for the detection of pathogens in water.

bioengineering↗

bioRxiv2019

Large-scale Analysis of 2,152 dataset reveals key features of B cell biology and the antibody repertoire

Antibody repertoire sequencing (Ig-seq) has been widely used in studying humoral responses, with promising results. However, the promise of Ig-seq has not yet been fully realized, and key features of the antibody repertoire remain elusive or controversial. To clarify these key features, we analyzed 2,152 high-quality heavy chain antibody repertoires, representing 582 donors and a total of 360 million clones. Our study revealed that individuals exhibit very similar gene usage patterns for germline V, D, and J genes and that 53 core V genes contribute to more than 99% of the heavy chain repertoire. We further found that genetic background is sufficient but not necessary to determine usage of V, D, and J genes. Although gene usage pattern is not affected by age, we observed a significant sex preference for 24 V genes, 9 D genes and 5 J genes, but found no positional bias for V-D and D-J recombination. In addition, we found that the number of observed clones that were shared between any two repertoires followed a linear model and noted that the mutability of hot/cold spots and single nucleotides within antibody genes suggested a strand-specific somatic hypermutation mechanism. This population-level analysis resolves some critical characteristics of the antibody repertoire and thus may serve as a reference for research aiming to unravel B cell-related biology or diseases. The metrics revealed here will be of significant value to the large cadre of scientists who study the antibody repertoire.

immunology↗

bioRxiv2026

Modeling the cell biology of PEX11β deficiency during human neurogenesis

Peroxisomes are highly specialized organelles that are important for various metabolic functions, including {beta}-oxidation of very-long-chain fatty acids and the synthesis of plasmalogens. Mutations in peroxisomal biogenesis proteins cause Zellweger spectrum disorders (ZSD), rare multisystem disorders often associated with neurological phenotypes. Unlike other peroxisome biogenesis proteins, PEX11{beta} regulates peroxisomal fission, and PEX11{beta} mutations result in milder metabolic phenotypes but persistent neurodevelopmental abnormalities, suggesting a role for PEX11{beta} in neurodevelopment. To model PEX11{beta} deficiency during human neurogenesis, we generated PEX11{beta} knockout human iPSCs and differentiated them into neural progenitors and neural rosettes. PEX11{beta} loss caused elongated peroxisomal morphology, reduced fission, and impaired recruitment of fission proteins, without affecting mitochondrial morphology or respiration. Elongated peroxisomal morphology was independent of the peroxisome-endoplasmic reticulum tether. Lipidomic analysis revealed reduced ether-linked phospholipids in PEX11{beta}-deficient neural progenitors, suggesting impaired peroxisomal function. Finally, PEX11{beta} deficiency led to increased neural rosette lumen size and neural progenitor number.

cell biology↗

bioRxiv2026

{Sigma}0-EvoCell: An AI-Native Ontology that Unifies Evolutionary and Cell Biology in Latent Space

Foundation models for biology achieve impressive pattern recognition on molecular sequences and single-cell transcriptomics, yet they fail to outperform simple linear baselines for predicting genetic perturbation effects, exposing a gap between statistical correlation and mechanistic understanding. This gap is compounded by an interface problem: biological knowledge lives in human-readable formats (FASTA, SBML, ontology triples) that must be lossily re-encoded before a neural network can reason about them. Here we introduce the Evolutionary Cell Ontology (ECO), an AI-native formal language built on the {Sigma}0 substrate that represents biological knowledge directly as vector-encoded relational graphs. ECO uses 16 structural operators that serve simultaneously as knowledge glyphs, tensor operations, and--critically--carry a dual semantics spanning both evolutionary and cellular timescales, so the same operator that denotes speciation at the phylogenetic scale denotes irreversible APC/C commitment at the cell-cycle scale. We define a Latent Space Communication Protocol (LSCP) that maps ECO graphs into the residual stream of large language models, enabling systematic auditing of the biological knowledge a model actually contains. We illustrate ECO across three domains using controlled simulations: (i) globin protein-family evolution across roughly 1.5 billion years, where ECO epistatic attention recovers long-range coevolutionary couplings and ancestral-state reconstruction reaches 82-91% accuracy graded by conservation class; (ii) mammalian cell-cycle dynamics, where a CDK-cyclin attention graph with GATE checkpoints and FUSE commitment nodes reproduces two full oscillatory cycles with a four-attractor phase portrait emerging without explicit programming; and (iii) latent-space alignment, where ECO embedding distance tracks divergence across 60 protein families (Pearson r = 0.50) and an illustrative LSCP audit projects that relational, multi-scale concepts are encoded far more weakly than sequence-level facts. ECO replaces the human-readability constraint with an AI-processing constraint and, in doing so, turns the opacity of foundation models into a measurable, navigable coverage map.

bioinformatics↗

bioRxiv2025

Nutrient availability-driven changes in extracellular matrix biochemical and mechanical properties regulate pancreatic cancer cell biology

The extracellular matrix (ECM) provides key biochemical and biomechanical cues that govern fundamental cellular processes, including growth and migration. ECM dysregulation and altered cell-matrix interactions are a driver of cancer progression, exemplified by pancreatic ductal adenocarcinoma (PDAC), where an abnormally dense, collagen-rich, and stiff ECM correlates with poor patient outcomes. The PDAC microenvironment is poorly perfused, resulting in altered nutrient availability, yet how this metabolic stress shapes the ECM and its biological activity remains poorly understood. Herein, we demonstrate that glutamine, a key amino acid depleted in poorly perfused PDAC regions, regulates the biochemical composition, mechanical properties, and biological activity of fibroblast-derived ECM. As glutamine availability increases, fibroblasts shift from producing a basement membrane-like ECM toward an interstitial, mature ECM enriched in fibrillar collagens. The ECM generated under glutamine-rich conditions is stiffer, which limits PDAC cell growth, while simultaneously, the elevated collagen I content promotes migration in a 3D spheroid model. Mechanistically, glutamine-dependent collagen I engages integrin 2 (ITGA2) to activate focal adhesion kinase signaling, driving PDAC cell migration independent of growth. In PDAC patients, glutamine stress inversely correlates with collagen expression in CAFs, with collagen I-ITGA2 as the most enriched ECM receptor interaction pair compared to the normal pancreas. These findings establish nutrient availability as a key regulator of ECM biology and offer new avenues to therapeutically intervene with dysregulated cell-matrix interactions in PDAC.

cell biology↗

bioRxiv2019

Genetic predisposition to myeloproliferative neoplasms implicates hematopoietic stem cell biology

Myeloproliferative neoplasms (MPNs) are blood cancers characterized by excessive production of mature myeloid cells that result from the acquisition of somatic driver mutations in hematopoietic stem cells (HSCs)1. While substantial progress has been made to define the causal somatic mutation profile for MPNs2, epidemiologic studies indicate a significant heritable component for the disease that is among the highest known for all cancers3. However, only a limited set of genetic risk loci have been identified, and the underlying biological mechanisms leading to MPN acquisition remain unexplained. Here, to define the inherited risk profile, we conducted the largest genome-wide association study of MPNs to date (978,913 individuals with 3,224 cases) and identified 14 genome-wide significant loci, as well as a polygenic signature that increases the odds for disease acquisition by nearly 3-fold between the top and median deciles. Interestingly, we find a shared genetic architecture between MPN risk and several hematopoietic traits spanning distinct lineages, as well as an association between increased MPN risk and longer leukocyte telomere length, collectively implicating HSC function and self-renewal. Strikingly, we find a significant enrichment for risk variants mapping to accessible chromatin in HSCs compared with other hematopoietic populations. Finally, gene mapping identifies modulators of HSC biology and targeted variant-to-function analyses suggest likely roles for CHEK2 and GFI1B in altering HSC function to confer disease risk. Overall, we demonstrate the power of human genetic studies to illuminate a previously unappreciated mechanism for MPN risk through modulation of HSC function.

genetics↗

bioRxiv2021

How biological cells including platelets and megakaryocytes decide complex problems fast but risky

Short AbstractMathematical decision processes are accurate but sometimes take very long time or simply do not happen. Decisions in biology happen fast and driven by evolution, optimizing survival chances. This results in stochastic decisions with on average good adaptation to the environment but an inherent risk of individual errors e.g. developing cancer during cell regeneration. We calculate and show in platelets and megakaryocytes how cellular decision processes increases risk for errors and inflammation. Short cut solutions adapted from nature improve computer strategies for protein folding and network decision processes. Complex problems are not always solved in foreseeable time, instead the fast solutions in biology speed up errors everywhere including biochemical aging of blood vessels, misfolded proteins, mis-programmed cells, cancer and heart failure. One sentence abstractWe investigate in biological networks how complex decision problems are mastered not by an accurate but unforeseeable long mathematical search but rather pragmatic and fast, with an inherent risk of error, a basis for inflammation and cancer.

bioinformatics↗

bioRxiv2021

Molecular and cell biological analysis of SwrB in Bacillus subtilis

Swarming motility is flagellar-mediated movement over a solid surface and Bacillus subtilis cells require an increase in flagellar density to swarm. SwrB is a protein of unknown function required for swarming that is necessary to increase the number of flagellar hooks but not basal bodies. Previous work suggested that SwrB activates flagellar type III secretion but the mechanism by which it might perform this function is unknown. Here we show that SwrB likely acts sub-stoichiometrically as it localizes as puncta at the membrane in numbers fewer than that of flagellar basal bodies. Moreover the action of SwrB is likely transient as puncta of SwrB were not dependent on the presence of the basal bodies and rarely co-localized with flagellar hooks. Random mutagenesis of the SwrB sequence found that a histidine within the transmembrane segment was conditionally required for activity and punctate localization. Finally, three hydrophobic residues that precede a cytoplasmic domain of poor conservation abolished SwrB activity when mutated and caused aberrant migration during electrophoresis. Our data are consistent with a model in which SwrB interacts with the flagellum, changes conformation to activate type III secretion, and departs. IMPORTANCEType III secretion systems (T3SS) are elaborate nanomachines that form the core of the bacterial flagellum and injectisome of pathogens. The machines not only secrete proteins like virulence factors but also secrete the structural components for their own assembly. Moroever, proper construction requires complex regulation to ensure that the parts are roughly secreted in the order in which they are assembled. Here we explore a poorly understood activator the flagellar T3SS activation in Bacillus subtilis called SwrB. To aid mechanistic understanding, we determine the rules for subcellular punctate localization, the topology with respect to the membrane, and critical residues required for SwrB function.

microbiology↗

bioRxiv2025

De novo single-cell biological analysis of drug resistance in human melanoma through a novel deep learning-powered approach

Elucidating drug response mechanisms in human melanoma is crucial for improving treatment outcomes. Although scRNA-seq captures gene expression at the individual cell level, existing tools to gain deeper insights into a studied population pertaining to melanoma drug resistance are far from perfect. Therefore, we propose a deep learning (DL)-based approach to unveil molecular mechanisms underlying melanoma drug resistance as follows. First, we processed two single-cell datasets related to human melanoma from GEO (GSE108383_A375 and GSE108383_451Lu) database and trained a fully connected neural network with five adapted methods (L1-Regularization, DeepLIFT, SHAP, IG, LRP) to discriminate between BRAFi-resistant and parental cell lines, followed by identifying top 100 genes. Compared to existing bioinformatics tools from a biological perspective, the presented DL-based methods identified more expressed genes in four well-established melanoma cell lines, including MALME-3M, MDA-MB435, SK-MEL-28, and SK-MEL-5. Moreover, we identified FDA-approved melanoma drugs (e.g., Vemurafenib and Dabrafenib), critical genes such as ARAF, SOX10, DCT, AXL, and key TFs including MITF and TFAP2A. From a classification perspective, we provided gene sets by all methods to three machine learning algorithms, including support vector machine, random forests, and neural networks. Results demonstrate that Integrated gradients (IG) method adapted in our DL approach contributed to 2.2% and 0.5% overall performance improvements over the best-performing baselines when using A375 and 451Lu cell line datasets.

bioinformatics↗

bioRxiv2021

Versioning Biological Cells for Trustworthy Cell Engineering

"Full-stack" biotechnology platforms for cell line (re)programming are on the horizon, due mostly to (a) advances in gene synthesis and editing techniques as well as (b) the growing integration with informatics, the internet of things and automation. These emerging platforms will accelerate the production and consumption of biological products. Hence, transparency, traceability and -ultimately-trustworthiness is required -from cradle to grave- for engineered cell lines and their engineering processes. We report here the first version control system for cell engineering that integrates a new cloud-based version control software for cell lines digital footprint with molecular barcoding of living samples. We argue that version control for cell engineering marks a significant step towards more open, reproducible, easier to trace and share, and more trustworthy engineering biology. One Sentence SummaryWe demonstrate a transparent and open way of engineering and sharing cell lines.

synthetic biology↗

bioRxiv2025

EZ-FRCNN: A Fast, Accessible and Robust Deep Learning Package for Object Detection Applications from Ethology to Cell Biology

Advances in high-throughput imaging and experimental automation have dramatically increased the scale of biological datasets, creating a growing need for tools that can efficiently identify and localize features in complex image data. Although deep learning has transformed image analysis, methods such as region-based convolutional neural networks remain underutilized in biology due to technical barriers such as coding requirements and reliance on cloud infrastructure. We present EZ-FRCNN, a locally hosted, user-friendly package that enables the accessible and scalable application of object detection to biological datasets. Through graphical and scriptable interfaces, users can annotate data, train models, and perform inference entirely offline. We demonstrate its utility in detecting cell phenotypes for large-scale screening, enabling the first label-free tracking of grinder motion in freely moving C. elegans to quantify feeding dynamics, and identifying animals in naturalistic environments for ecological field studies. These once-infeasible analyses now enable rapid screening of cell therapies, investigation of internal state-behavior coupling without immobilization or genetic modification, and efficient wildlife tracking with minimal computational cost. Together, these examples demonstrate how accessible tools like EZ-FRCNN can drive new biological discoveries in both laboratory and field environments.

bioengineering↗

bioRxiv2026

Cross-species graph-embedding unmasks the ageing microenvironment as a key determinant of pancreatic cancer malignant cell biology and therapy response

Pancreatic ductal adenocarcinoma (PDAC) has a dismal prognosis and is characterised by an extensive pro-tumorigenic stroma. Although most PDAC cases occur in older patients, the impact of ageing on malignant-stromal interactions and therapy response remains poorly understood. Here, we established orthotopically-grafted organoid-derived PDAC models across three murine age groups to characterise changes in the PDAC stroma and malignant cells with ageing. Cross-species analyses of tumour transcriptomes using a graph-embedding approach showed that integrating mouse models of different ages better captures the diversity of human PDAC, and that aged models more faithfully recapitulate the biology of older patients with PDAC. We also demonstrated that aged PDAC models have a more inflammatory stroma than that of younger tumours, shaping the malignant cell transcriptome. Finally, graph-embedding identified IRAK4 as a candidate therapeutic vulnerability in aged, but not young, KRAS- and p53-mutant PDAC, which we validated in preclinical drug studies. These findings highlight how ageing is a critical determinant of PDAC biology and associated therapeutic vulnerabilities, which should be an important consideration when designing disease models for preclinical development of precision therapies.

cancer biology↗

bioRxiv2020

Eukaryotic cell biology is temporally coordinated to support the energetic demands of protein homeostasis

Every aspect of yeast physiology is subject to robust temporal regulation, this becomes apparent under nutrient-limiting conditions 1-6 and results in biological oscillations whose function and mechanism is poorly resolved7. These yeast metabolic oscillations share features with circadian rhythms and typically interact with, but are independent of, the cell division cycle. Here we show that these cellular rhythms act to minimise energy expenditure by temporally restricting protein synthesis until sufficient cellular resources are present, whilst maintaining osmotic homeostasis and protein quality control. Although nutrient supply is constant, cells initially sequester and store metabolic resources such as carbohydrates, amino acids, K+ and other osmolytes; which accumulate via increased synthesis, transport, autophagy and biomolecular condensation that is stimulated by low glucose and cytosolic acidification. Replete stores trigger increased H+ export to elevate cytosolic pH, thereby stimulating TORC1 and liberating proteasomes, ribosomes, chaperones and metabolic enzymes from non-membrane bound compartments. This facilitates a burst of increased protein synthesis, the liquidation of storage carbohydrates to sustain higher respiration rates and increased ATP turnover, and the export of osmolytes to maintain osmotic potential. As the duration of translational bursting is determined by cell-intrinsic factors, the period of oscillation is determined by the time cells take to store sufficient resources to license passage through the pH-dependent metabolic checkpoint that initiates translational bursting. We propose that dynamic regulation of ion transport and metabolic plasticity are required to maintain osmotic and protein homeostasis during remodelling of eukaryotic proteomes, and that bioenergetic constraints have selected for temporal organisation that promotes oscillatory behaviour.

molecular biology↗

bioRxiv2026

Spatial multi-omics reveals novel vascular adipocyte and B cell biology in human abdominal aortic aneurysm

Objective: Perivascular Adipose Tissue (PVAT), tertiary lymphoid structures (TLS), and the B lymphocytes they harbor have been implicated in regulating vascular diseases, including abdominal aortic aneurysm (AAA). Yet, the relationship of adipose tissue to TLS and B cell responses is poorly understood. Approach and Results: Here, we used a multi-omic approach to rigorously define the landscape of human AAA and characterize the adipocyte and TLS microenvironment with regard to B-cell responses to vascular antigens in human AAA and control non-aneurysmal abdominal aortas. Single-nucleus and single-cell RNA sequencing identified transcripts for lipogenesis, lipolysis, extracellular remodeling, haptotactic and chemotactic factors, with potential to recruit CD44+ leukocytes within AAAs. Immunohistology and Visium HD spatial transcriptomics revealed that at least two adipocyte types exist: one in the PVAT and another as isolated clusters in the medial-adventitial region in human AAAs but not in control aortas. Further characterization of these medial-adventitial adipocytes in the AAAs showed close association with TLSs. Mature TLSs recapitulated the organization of functional secondary lymphoid structures, with multiple B-cell follicles clustered to form a nodular structure partly covered by a layer of smooth muscle cells. The TLSs harbored isotype-switched B cells expressing IgG1, IgG3, or IgA, with dominant kappa chain usage and abundant IgG antibodies to aortic wall. Myeloid cells in AAA were implicated in promoting B cell effects, as they were the primary producers of B-cell activating factor (BAFF), a cytokine that promotes B cell infiltration, survival, and function. Conclusion: Altogether, our results support a novel model in which new adipocytes in the medial-adventitial layer produce factors that promote early TLS formation, and BAFF produced by myeloid cells promotes the survival and maturation of vascular wall-antigen-exposed B cells, leading to mature TLS formation, production of antibodies to AAA antigens, fueling inflammation and AAA growth.

immunology↗

bioRxiv2022

The interactome of Cryptococcus neoformans Rmt5 reveals multiple regulatory points in fungal cell biology and pathogenesis

Protein arginine methylation is a key post-translational modification in eukaryotes that modulates core cellular processes, including translation, morphology, transcription, and RNA fate. However, this has not been explored in Cryptococcus neoformans, a human-pathogenic basidiomycetous encapsulated fungus. We characterized the five protein arginine methyltransferases in C. neoformans and highlight Rmt5 as critical regulator of cryptococcal morphology and virulence. An rmt5{Delta} mutant was defective in thermotolerance, had a remodeled cell wall, and exhibited enhanced growth in an elevated carbon dioxide atmosphere and in chemically induced hypoxia. We revealed that Rmt5 interacts with post-transcriptional gene regulators, such as RNA-binding proteins and translation factors. Further investigation of the rmt5{Delta} mutant showed that Rmt5 is critical for the homeostasis of eIF2 and its phosphorylation state following 3-amino-1,2,4-triazole-induced ribosome stalling. RNA sequencing of one rmt5{Delta} clone revealed stable chromosome 9 aneuploidy that was ameliorated by complementation but did not impact the rmt5{Delta} phenotype. As a result of these diverse interactions and functions, loss of RMT5 enhanced phagocytosis by murine macrophages and attenuated disease progression in mice. Taken together, our findings link arginine methylation to critical cryptococcal cellular processes that impact pathogenesis, including post-transcriptional gene regulation by RNA-binding proteins. SignificanceThe fungal pathogen Cryptococcus neoformans is a huge threat for people living with immune deficits, especially HIV/AIDS. Its virulence potential is dependent on virulence factors, stress adaptation, and thermotolerance. Post-transcriptional gene regulation is important for these pathogenic processes, but the mechanisms that govern post-transcriptional regulator function are unexplored. Protein arginine methylation is a major modification of post-transcriptional regulators that has not been investigated in pathogenic fungi. Here we investigated the role of arginine methylation by arginine methyltransferases on the biology and virulence of C. neoformans. Phenotypic characterization of deletion mutants revealed pleiotropic functions for RMTs in this pathogen. Further investigation of the Rmt5 interactome using proximity-dependent biotinylation revealed interactions with RNA binding proteins and translation factors, thereby impacting virulence-associated processes.

microbiology↗