Biology subjects

Cai, E.

Publications and source records attributed to Cai, E..

At least 19 recordsLinked to original sources

bioRxiv2026

Receptor-like kinase RLK15 binds a fungal RNase effector to enhance autophosphorylation and activate host defense

Fungal pathogens secrete diverse effectors to suppress host immunity, yet the plant receptors that perceive these virulence factors often remain elusive. Here, we identify Ss1624, a secreted RNase from the sugarcane smut pathogen Sporisorium scitamineum, and show that it is recognized by the plasma-membrane-localized CrRLK1L-family receptor kinase RLK15. This recognition triggers canonical immune outputs, including reactive oxygen species burst, callose deposition, defense gene activation, and induces hypersensitive cell death. Mechanistically, Ss1624 physically interacts with the receptor-like kinase RLK15, which is required for Ss1624-triggered cell death. Functional assays indicate that this interaction enhances RLK15 autophosphorylation in a kinase activity-dependent manner, suggesting that Ss1624 can act as an elicitor. Transcript profiling further reveals coordinated expression patterns of Ss1624 and RLK15 during infection, and perturbation of Ss1624 expression alters RLK15 transcript levels and pathogenic outcomes. Extending these findings to rice, the ortholog OsRLK15 contributes positively to resistance to bacterial and fungal diseases without yield penalty in rice. Our results support a model in which a secreted RNase effector is directly sensed by a receptor kinase to initiate broad-spectrum immune responses, providing insights into host-pathogen interactions and identifying RLK15 as a candidate for crop improvement.

microbiology↗

bioRxiv2026

Nanoscale 3D profiling of the T cell membrane reveals CD2 enrichment at microvilli tips, positioning adhesion near TCR zones in the immunological synapse

The T cell membrane features a specialized molecular and topological organization critical for signaling and immune function. During antigen detection, T cells utilize finger-like protrusions called microvilli to dynamically scan the antigen-presenting cell (APC) surface. Enriched with T cell receptors (TCRs) and key signaling molecules, microvilli serve as primary signaling hubs, yet their nanoscale architecture remains poorly defined. Upon antigen engagement, TCR activation drives the formation of the immunological synapse (IS), a highly organized membrane contact with the APC critical for T cell function. However, profiling IS architecture at the nanoscale remains technically challenging. Here, we introduce NanoMAP (Nanoscale Membrane Architecture Profiling), an expansion microscopy-based platform that resolves receptor organization on T cell microvilli and within the IS at 35-60 nm resolution. Using NanoMAP, we show that effector CD8+ T cells possess a 5.1-fold higher microvillar density than naive CD8+ T cells. Mapping the adhesion receptors CD2 and LFA-1 on the T cell surface reveals that CD2 exhibits a stronger preference for localizing to microvilli tips compared to TCR and LFA-1. Within microvilli, CD2 displays a strong spatial association with TCR clusters, contrasting with a markedly weaker TCR-LFA-1 association. At the IS, TCR and CD2 co-occupy close membrane contacts, while LFA-1 is excluded to more distal regions. Upon termination of activation, TCR clusters selectively disengage from microvilli, whereas CD2 and LFA-1 persist. These results suggest a coordinated, activation-dependent organization of adhesion receptors that drives microvillar adhesion during scanning and stabilizes IS membrane contacts. Together, NanoMAP establishes a powerful framework for dissecting nanoscale membrane architecture and spatial signaling in T cells.

immunology↗

bioRxiv2026

Engineering nanoparticle surface chemistry for antigen-presenting cell targeting improves specificity and safety of TLR3 agonist cancer immunotherapy

Innate immune agonists are promising therapeutic agents to induce immune responses against cancer. However, these agents have been limited by toxicity associated with systemic accumulation and activity in off-target cells. In this work, a targeted nanoparticle (NP) platform to encapsulate and protect the Toll-like receptor 3 (TLR3) agonist polyinosinic-polycytidylic acid (poly(I:C)) and promote its specific delivery to antigen presenting cells (APCs), macrophages and dendritic cells, for activation of this cell population was designed. To determine NP physiochemical properties that promote APC delivery, we developed a library of NP surface chemistries formed by electrostatic adsorption of polyanion coatings onto liposomes using layer-by-layer (LbL) assembly and screened the particles on APCs and off-target cells. Dextran sulfate was identified as a promising coating to enhance specific APC delivery. We applied these design parameters to develop a poly(I:C)-loaded NP for an APC-targeted immunotherapy. In a model of metastatic ovarian cancer, the LbL NP prolonged poly(I:C) retention in the peritoneal space--with 2-fold remaining 24-48hr after administration compared to free poly(I:C)--ultimately reducing systemic accumulation and associated toxicities. Compared to free drug, the NP reduced the increase in serum levels of TNF, IL-6, and CXCL10 by 9-, 4-, and 31-fold respectively. NP-treated mice experienced lower weight loss and recovered more quickly at a higher poly(I:C) dose, indicating a widening of the therapeutic window. The NP formulation enhanced accumulation of poly(I:C) in the tumor 2-fold and activation of the target APC population compared to free drug, and ultimately slowed tumor growth and extended survival in combination with doxorubicin chemotherapy. Overall, this work demonstrates a modular NP delivery strategy to improve the delivery, safety, and therapeutic window of a TLR3 agonist.

bioengineering↗

bioRxiv2025

Identifying the therapeutic potential of Niclosamide in overcoming IFN-gamma dependent cancer immune evasion in the Tumor Microenvironment

BackgroundTumor cells frequently develop immune resistance through interferon-{gamma} (IFN-{gamma})-induced PD-L1 expression, acquisition of cancer stem cell (CSC)-like features, and adaptation to hypoxia within the tumor microenvironment (TME). Although IFN-{gamma} activates both STAT1 and STAT3, how these pathways interact to regulate immune evasion under hypoxia remains unclear. MethodsUsing the MC38 murine colorectal cancer model and T cell-tumor spheroid co-culture assays, we examined how IFN-{gamma} signaling through STAT1 and STAT3 influences PD-L1 expression, CSC plasticity, and cytotoxic T cell function under normoxic and hypoxic conditions. Pharmacologic inhibitors and siRNA knockdown were used to dissect pathway function, and Niclosamide, an FDA-approved anthelmintic, was evaluated as a dual STAT1/STAT3 inhibitor. ResultsWe found that IFN-{gamma} primarily induced PD-L1 through STAT1 activation, while CSC plasticity was associated with STAT3 signaling. STAT1 and STAT3 displayed reciprocal regulation--blocking one enhanced activation of the other. Niclosamide effectively inhibited phosphorylation of both STAT1 and STAT3, which led to suppressed PD-L1 upregulation and reduced CSC enrichment. In addition, it also partially inhibited hypoxia-induced HIF-1 expression. In co-culture assays, Niclosamide improved T cell infiltration and reduced exhaustion under hypoxic conditions, resulting in improved T cell killing. ConclusionsOur findings identified Niclosamide as a potent dual STAT1/3 inhibitor capable of reversing IFN-{gamma} and hypoxia-driven immune evasion. Repurposing Niclosamide may represent a promising strategy to enhance the efficacy of immune checkpoint blockade in solid tumors. key messagesInterferon-{gamma} (IFN-{gamma}) enhances cytotoxic T cell function but also promotes tumor immune evasion by upregulating PD-L1 and inducing cancer stem cell- like properties. Our study identifies a reciprocal regulatory mechanism between STAT1 and STAT3 in IFN-{gamma}-treated tumor cells that shapes immune evasion outcomes. We demonstrate that Niclosamide, an FDA-approved anthelmintic, acts as a dual STAT1/STAT3 inhibitor, effectively suppressing PD-L1 induction, limiting cancer stemness, and reducing HIF-1 expression under hypoxia. Niclosamide also restores T cell infiltration and decreases exhaustion in a 3D tumor spheroid model. By repurposing Niclosamide, this work provides a feasible approach to enhance the efficacy of immune checkpoint blockade and guide future translational and clinical studies in immunotherapies against solid tumors.

immunology↗

bioRxiv2025

Surface avidity of anionic polypeptide coatings target nanoparticles to cancer-associated amino acid transporters

Tumor-targeted drug delivery enhances therapeutic efficacy while minimizing toxicity. Layer-by-layer nanoparticles (LbL-NPs) coated with anionic polypeptides selectively bind to cancer cells, though the mechanisms have been unclear. Here, we integrated in silico and in vitro approaches--including gene expression analysis, receptor inhibition, and AI-based protein modeling--to show that poly(L-glutamate) (PLE)-coated LbL-NPs bind with high avidity to SLC1A5, a glutamine transporter overexpressed in cancer. We also discovered that PLE clusters SLC1A5 on the cell membrane, promoting prolonged cell surface retention. Poly(L-aspartate) (PLD)-coated NPs similarly bind SLC1A5 but also interact with faster internalizing transporters of anionic amino acids. Correlation analyses across cancer cell lines confirmed a strong link between transporter expression and nanoparticle association. These findings demonstrate that dense glutamate or aspartate presentation through electrostatically adsorbed polypeptides enables selective targeting of overexpressed transporters, providing a mechanistic framework for receptor-targeted delivery that leverages metabolic characteristics of a range of solid tumor types.

bioengineering↗

bioRxiv2025

Proteomic profiling of primary cilia in the developing brain uncovers newregulators of cortical development

In the developing brain, the primary cilia of radial glial cells extend from the surface of the lateral ventricle, serving as the signaling hub to integrate environmental cues critical for brain formation. Dysfunctions in ciliary proteins contribute to a wide range of brain structural abnormalities in ciliopathies, yet identifying the bona fide ciliary protein components in the brain remains a significant challenge. Here, using proximity labeling and quantitative proteomics, we systematically charted proteins localized to the cilia of radial glial cells in the dorsal and ventral regions of the embryonic brain. From this dataset, we identified cohorts of new molecules intrinsic to the cilia at distinct regions of the developing brain. We validated the cilium localization of several components of the translation machinery and studied the mechanistic roles of ciliary candidates previously linked to brain malformation, including Marcks, a key regulator of radial glial polarity, and Ckap2l, a protein associated with Filippi syndrome. These results revealed previously unrecognized ciliary mechanisms that regulate brain development. Thus, our brain proteomic dataset provides a unique resource for understanding ciliary functions in brain development and the molecular etiology of developmental disorders.

developmental biology↗

bioRxiv2025

Deep learning reveals functional archetypes in the adult human gut microbiome that underlie interindividual variability and confound disease signals

Understanding the functional diversity of the gut microbiome is essential for decoding its roles in health and disease. Using a deep-learning framework, we identified three functional archetypes defining healthy adult gut microbiomes, each characterized by specific metabolic potentials: sugar metabolism with branched-chain amino acid and cell wall synthesis (Archetype 1), fatty acid and TCA cycle metabolism (Archetype 2), and amino acid and nitrogen metabolism (Archetype 3). Archetype proximity is linked to stability, with Archetype 2 representing the most resilient state, likely due to its metabolic flexibility. Functional diversity emerged as a confounder in disease-associated microbial signatures. In inflammatory bowel disease, we observed archetype-specific shifts, including increased carbohydrate metabolism in Archetype 1-dominant samples and inflammatory pathways in Archetype 3-dominant samples, suggesting distinct opportunities for microbiome-targeted interventions. This framework addresses key challenges in microbiome research, including inter-individual variability and confounding, while providing robust insights into disease-associated functional shifts and microbial ecosystem dynamics. HighlightsO_LIAdult gut microbiomes are defined by three functional archetypes C_LIO_LIArchetypes reveal distinct metabolic potentials and inform on microbiome stability C_LIO_LIArchetype-specific functional profiles confound disease associations and reveal therapeutic targets C_LIO_LIA deep-learning framework enables robust characterization of microbial functional ecosystems C_LI

microbiology↗

bioRxiv2024

Renalase inhibition regulates β cell metabolism to defend against acute and chronic stress

Renalase (Rnls), annotated as an oxidase enzyme, is a GWAS gene associated with Type 1 Diabetes (T1D) risk. We previously discovered that Rnls inhibition delays diabetes onset in mouse models of T1D in vivo, and protects pancreatic {beta} cells against autoimmune killing, ER and oxidative stress in vitro. The molecular biochemistry and functions of Rnls are entirely uncharted. Here we find that Rnls inhibition defends against loss of {beta} cell mass and islet dysfunction in chronically stressed Akita mice in vivo. We used RNA sequencing, untargeted and targeted metabolomics and metabolic function experiments in mouse and human {beta} cells and discovered a robust and conserved metabolic shift towards glycolysis, amino acid abundance and GSH synthesis to counter protein misfolding stress, in vitro. Our work illustrates a function for Rnls in mammalian cells, and suggests an axis by which manipulating intrinsic properties of {beta} cells can rewire metabolism to protect against diabetogenic stress.

physiology↗

bioRxiv2023

A deep learning convolutional neural network distinguishes neuronal models of Parkinson's disease from matched controls

Parkinsons disease (PD) is a neurodegenerative disorder that results in the loss of dopaminergic neurons in the substantia nigra pars compacta. Despite advances in understanding PD, there is a critical need for novel therapeutics that can slow or halt its progression. Induced pluripotent stem cell (iPSC)-derived dopaminergic neurons have been used to model PD but measuring differences between PD and control cells in a robust, reproducible, and scalable manner remains a challenge. In this study, we developed a binary classifier convolutional neural network (CNN) to accurately classify microscopy images of PD models and matched control cells. We acquired images of iPSC-derived neural precursor cells (NPCs) and dopaminergic (DANs) and trained multiple CNN models comparing control cells to genetic and chemical models of PD. Our CNN accurately predicted whether control NPC cells were treated with the PD-inducing pesticide rotenone with 97.60% accuracy. We also compared control to a genetic model of PD (deletion of the Parkin gene) and found a predictive accuracy of 86.77% and 95.47% for NPC and DAN CNNs, respectively. Our cells were stained for nuclei, mitochondria, and plasma membrane, and we compared the contribution of each to the CNNs accuracy. Using all three features together produced the best accuracy, but nuclear staining alone produced a highly predictive CNN. Our study demonstrates the power of deep learning and computer vision for analyzing complex PD-related phenotypes in DANs and suggests that these tools hold promise for identifying new targets for therapy and improving our understanding of PD.

neuroscience↗

bioRxiv2022

Cilium proteomics reveals Numb as a positive regulator of the Hedgehog signaling pathway

The transduction of Hedgehog (Hh) signaling relies on the primary cilium, a cell surface organelle serving as a signaling hub for the cell. Using proximity labeling and quantitative proteomics, we identified Numb as a new ciliary protein that positively regulates Hh signaling. Numb localizes to the ciliary pocket and acts as an endocytic adaptor to incorporate Ptch1 into clathrin-coated vesicles, thereby promoting Ptch1 exit from the cilium, a key step in Hh signaling activation. Numb loss hampers Sonic Hedgehog (Shh)-induced Ptch1 departure from the cilium, resulting in reduced activation of Hh signaling. Numb loss in spinal neural progenitors reduces Shh-induced differentiation into Nkx2.2-positive progenitors, a process reliant on high Hh signaling activity. Genetic ablation of Numb in the developing cerebellum impaired the proliferation of granule cell precursors, a Hh-dependent process, resulting in reduced cerebellar size. This study highlights Numb as a critical regulator of Ptch1 levels in the cilium during Hh signal activation and demonstrates the key role of ciliary pocket-mediated endocytosis in modulating the transduction of cell signaling.

cell biology↗

bioRxiv2022

T cells use distinct topological and membrane receptor scanning strategies that individually coalesce during receptor recognition

During immune surveillance, CD8 T cells scan the surface of antigen presenting cells using dynamic microvillar palpation and movements as well as by having their receptors pre-concentrated into patches. Here, we use real-time lattice light sheet microscopy to demonstrate the independence of microvillar and membrane receptor patch scanning. While T cell receptor (TCR) patches can distribute to microvilli, they do so stochastically and not preferentially as for other receptors such as CD62L. The distinctness of TCR patch movement from microvillar movement extends to many other receptors that form patches that also scan independently of the TCR. An exception to this is the CD8 co-receptor which largely co-migrates in patches that overlap with or are closely adjacent to those containing TCRs. Microvilli that assemble into a synapse contain various arrays of the engaged patches, notably of TCRs and the inhibitory receptor PD-1, creating a pastiche of occupancies that vary from microvillar contact to contact. In summary, this work demonstrates that localization of receptor patches within the membrane and on microvillar projections is stochastic prior to antigen detection and that such stochastic variation may play into the generation of many individually-composed receptor patch compositions at a single synapse. Significance statementMotile T cell microvilli palpate surfaces to facilitate surface scanning in a pattern that is independent of the movement of pre-formed patches of transmembrane antigen-receptors across those microvilli; once T cell receptors engage, the microvilli act to scaffold multiple receptors within a microvillar close-contact.

immunology↗

bioRxiv2021

Spatiotemporal co-dependency between macrophages and exhausted CD8+ T cells in cancer

T cell exhaustion is a major impediment to anti-tumor immunity. However, it remains elusive how other immune cells in the tumor microenvironment (TME) contribute to this dysfunctional state. Here we show that the biology of tumor-associated macrophages (TAM) and exhausted T cells (Tex) in the TME is extensively linked. We demonstrate that in vivo depletion of TAM reduces exhaustion programs in tumor-infiltrating CD8+ T cells and reinvigorates their effector potential. Reciprocally, transcriptional and epigenetic profiling reveals that Tex express factors that actively recruit monocytes to the TME and shape their differentiation. Using lattice light sheet microscopy, we show that TAM and CD8+ T cells engage in unique long-lasting antigen-specific synaptic interactions that fail to activate T cells, but prime them for exhaustion, which is then accelerated in hypoxic conditions. Spatially resolved sequencing supports a spatiotemporal self-enforcing positive feedback circuit that is aligned to protect rather than destroy a tumor. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/461866v1_ufig1.gif" ALT="Figure 1"> View larger version (65K): org.highwire.dtl.DTLVardef@1fb1c4aorg.highwire.dtl.DTLVardef@fe4571org.highwire.dtl.DTLVardef@1812f76org.highwire.dtl.DTLVardef@5317d5_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2021

Imaging-guided fine tuning of CAR synapse dynamics and T cell triggering

T cells typically recognize their ligands using a defined cell biology - the scanning of their membrane microvilli to palpate their environment - while that same membrane scaffolds T cell receptors (TCRs) that can signal upon ligand binding. Chimeric antigen receptors (CARs) present both a therapeutic promise as well as a tractable means to study the interplay between receptor affinity, microvillar dynamics and T cell function. CARs are often built using single-chain variable fragments (scFvs) with far greater affinity than that of natural TCRs. We used high resolution lattice lightsheet (LLS) and total internal reflection fluorescence (TIRF) imaging to visualize microvillar scanning in the context of variations in CAR design. This demonstrated that conventional CARs hyper-stabilized microvillar contacts relative to TCRs. Reducing the affinity and/or avidity of binding brought synapse microvillar dynamics into natural ranges, normalized synapse resolution and improved downstream effector function. This work highlights the importance of understanding the underlying cell biology when designing receptors for optimal antigen engagement.

immunology↗

bioRxiv2021

Midbrain organoids with an SNCA gene triplication model key features of synucleinopathy

SNCA, the first gene associated with Parkinsons disease, encodes the -synuclein (-syn) protein, the predominant component within pathological inclusions termed Lewy bodies (LBs). The presence of LBs is one of the classical hallmarks found in the brain of patients with Parkinsons disease, and LBs have also been observed in patients with other synucleinopathies. However, the study of -syn pathology in cells has relied largely on two-dimensional culture models, which typically lack the cellular diversity and complex spatial environment found in the brain. Here, to address this gap, we use 3D midbrain organoids (hMOs), differentiated from human induced pluripotent stem cells derived from patients carrying a triplication of the SNCA gene and from CRISPR/Cas9 corrected isogenic control iPSCs. These hMOs recapitulate key features of -syn pathology observed in the brains of patients with synucleinopathies. In particular, we find that SNCA triplication hMOs express elevated levels of -syn and exhibit an age-dependent increase in -syn aggregation, manifested by the presence of both oligomeric and phosphorylated forms of -syn. These phosphorylated -syn aggregates were found in both neurons and glial cells and their time-dependent accumulation correlated with a selective reduction in dopaminergic neuron numbers. Thus, hMOs from patients carrying SNCA gene multiplication can reliably model key pathological features of Parkinsons disease and provide a powerful system to study the pathogenesis of synucleinopathies.

neuroscience↗

bioRxiv2021

Auto-qPCR: A Python based web app for automated and reproducible analysis of qPCR data

Quantifying changes in DNA and RNA levels is essential in numerous molecular biology protocols. Quantitative real time PCR (qPCR) techniques have evolved to become commonplace, however, data analysis includes many time-consuming and cumbersome steps, which can lead to mistakes and misinterpretation of data. To address these bottlenecks, we have developed an open-source Python software to automate processing of result spreadsheets from qPCR machines, employing calculations usually performed manually. Auto-qPCR is a tool that saves time when computing qPCR data, helping to ensure reproducibility of qPCR experiment analyses. Our web-based app (https://auto-q-pcr.com/) is easy to use and does not require programming knowledge or software installation. Using Auto-qPCR, we provide examples of data treatment, display and statistical analyses for four different data processing modes within one program: (1) DNA quantification to identify genomic deletion or duplication events; (2) assessment of gene expression levels using an absolute model, and relative quantification (3) with or (4) without a reference sample. Our open access Auto-qPCR software saves the time of manual data analysis and provides a more systematic workflow, minimizing the risk of errors. Our program constitutes a new tool that can be incorporated into bioinformatic and molecular biology pipelines in clinical and research labs.

molecular biology↗

bioRxiv2021

Standardized quality control workflow to evaluate the reproducibility and differentiation potential of human iPSCs into neurons

Induced pluripotent stem cells (iPSCs) derived from human somatic cells have created new opportunities to generate disease-relevant cells. Thus, as the use of patient-derived stem cells has become more widespread, having a workflow to monitor each line is critical. This ensures iPSCs pass a suite of quality control measures, promoting reproducibility across experiments and between labs. With this in mind, we established a multistep workflow to assess our newly generated iPSCs for variations and reproducibility relative to each other and iPSCs obtained from external sources. Our benchmarks for evaluating iPSCs include examining iPSC morphology and proliferation in two different media conditions and evaluating their ability to differentiate into each of the three germ layers, with a particular focus on neurons. Genomic integrity in the human iPSCs was analyzed by G-band karyotyping and a qPCR-based test for the detection of hotspot mutations test. Cell-line identity was authenticated by Short Tandem Repeat (STR) analysis. Using standardized dual SMAD inhibition methods, all iPSC lines gave rise to neural progenitors that could subsequently be differentiated into cortical neurons. Neural differentiation was analyzed qualitatively by immunocytochemistry and quantitatively by qPCR for progenitor, neuronal, cortical, and glial markers. Taken together, we present a multistep quality control workflow to evaluate variability and reproducibility across and between iPSCs.

cell biology↗

bioRxiv2019

Tumors Exploit Dedicated Intracellular Vesicles to Program T cell Responses

In order to drive productive tumor-infiltrating lymphocyte (TIL) function, myeloid populations must direct antigens to the lymph node, including to resident antigen-presenting cells (APCs) that have never touched the tumor. It has long been supposed that APCs trade antigens with one another, but the dominant cell biology underlying that remains unknown. We used in vitro and in vivo assays together with lattice light sheet and multiphoton imaging to show that myeloid cells carry tumor antigen-laden vesicles that they trade with one another as they reach distant sites. This accounts for the majority of antigen displayed to T cells and provides tumors with a mechanism to access APCs that differentially direct T cell activation away from memory phenotypes. This work defines efficient cell biology that drives the first steps of TIL generation and represents a new frontier for engineering tumoral immunity.

immunology↗

bioRxiv2017

Single-molecule tracking in live Yersinia enterocolitica reveals distinct cytosolic complexes of injectisome subunits

In bacterial type 3 secretion, substrate proteins are actively transported from the bacterial cytoplasm into the host cell cytoplasm by a large membrane-embedded machinery called the injectisome. Injectisomes transport secretion substrates in response to specific environmental signals, but the molecular details by which the cytosolic secretion substrates are selected and transported through the type 3 secretion pathway remain unclear. Secretion activity and substrate selectivity are thought to be controlled by a sorting platform consisting of the proteins SctK, SctQ, SctL, and SctN, which together localize to the cytoplasmic side of membrane-embedded injectisomes. However, recent work revealed that sorting platform proteins additionally exhibit substantial cytosolic populations and that SctQ reversibly binds to and dissociates from the cytoplasmic side of membrane-embedded injectisomes. Based on these observations, we hypothesized that dynamic molecular turnover at the injectisome and cytosolic assembly among sorting platform proteins is a critical regulatory component of type 3 secretion. To determine whether sorting platform complexes exist in the cytosol, we measured the diffusive properties of the two central sorting platform proteins, SctQ and SctL, using live cell high-throughput 3D single-molecule tracking microscopy. Single-molecule trajectories, measured in wild-type and mutant Yersinia enterocolitica cells, reveal that both SctQ and SctL exist in several distinct diffusive states in the cytosol, indicating that these proteins form stable homo- and hetero-oligomeric complexes in their native environment. Our findings provide the first diffusive state-resolved insights into the dynamic regulatory network that interfaces stationary membrane-embedded injectisomes with the soluble cytosolic components of the type 3 secretion system.

biophysics↗