Biology subjects

Wang, K.

Publications and source records attributed to Wang, K..

At least 289 records · Page 16Linked to original sources

bioRxiv2023

AGILE Platform: A Deep Learning-Powered Approach to Accelerate LNP Development for mRNA Delivery

Ionizable lipid nanoparticles (LNPs) have seen widespread use in mRNA delivery for clinical applications, notably in SARS-CoV-2 mRNA vaccines. Despite their successful use, expansion of mRNA therapies beyond COVID-19 is impeded by the absence of LNPs tailored to different target cell types. The traditional process of LNP development remains labor-intensive and cost-inefficient, relying heavily on trial and error. In this study, we present the AI-Guided Ionizable Lipid Engineering (AGILE) platform, a synergistic combination of deep learning and combinatorial chemistry. AGILE streamlines the iterative development of ionizable lipids, crucial components for LNP-mediated mRNA delivery. This approach brings forth three significant features: efficient design and synthesis of combinatorial lipid libraries, comprehensive in silico lipid screening employing deep neural networks, and adaptability to diverse cell lines. Using AGILE, we were able to rapidly design, synthesize, and evaluate new ionizable lipids for mRNA delivery in muscle and immune cells, selecting from a library of over 10,000 candidates. Importantly, AGILE has revealed cell-specific preferences for ionizable lipids, indicating the need for different tail lengths and head groups for optimal delivery to varying cell types. These results underscore the potential of AGILE in expediting the development of customized LNPs. This could significantly contribute to addressing the complex needs of mRNA delivery in clinical practice, thereby broadening the scope and efficacy of mRNA therapies. One Sentence SummaryAI and combinatorial chemistry expedite ionizable lipid creation for mRNA delivery.

biochemistry↗

bioRxiv2023

The lipid phosphatase activity of PTEN dampens FRA1 expression via AKT/mTOR signaling to suppress melanoma

PTEN, a phosphatase frequently inactivated in melanoma, opposes PI3K/AKT/mTOR pathway activation. However, AKT- and mTOR-targeted therapies have so far yielded insufficient results in preclinical models and clinical trials of melanoma. We therefore examined whether PTEN suppresses melanoma through lipid phosphatase-independent functions or by opposing lipid phosphatase-dependent, AKT-independent pathways. Restoring different PTEN functions in PTEN-deficient cells or mouse models revealed that PTEN lipid phosphatase activity predominantly suppresses melanoma with minimal contribution from its protein phosphatase and scaffold functions. A drug screen highlighted the dependence of PTEN-deficient melanoma cells on the AKT/mTOR pathway. Moreover, activation of AKT was sufficient to overcome several aspects of PTEN-mediated melanoma suppression. Phosphoproteomics analysis of the PTEN lipid phosphatase activity identified the AP-1 transcription factor FRA1 as a downstream effector. PTEN regulates FRA1 translation via AKT/mTOR and FRA1 overexpression overcomes PTEN-mediated melanoma suppression. Our study affirms AKT as the key mediator of PTEN inactivation in melanoma and identifies an AKT/mTOR/FRA1 axis as a driver of melanomagenesis.

cancer biology↗

bioRxiv2023

Theoretical framework and experimental solution for the air-water interface adsorption problem in cryoEM

As cryogenic electron microscopy (cryoEM) gains traction in the structural biology community as a method of choice for determining atomic structures of biological complexes, it has been increasingly recognized that many complexes that behave well under conventional negative-stain electron microscopy tend to have preferential orientation, aggregate or simply mysteriously "disappear" on cryoEM grids, but the reasons for such misbehavior are not well understood, limiting systematic approaches to solving the problem. Here, we have developed a theoretical formulation that explains these observations. Our formulation predicts that all particles migrate to the air-water interface (AWI) to lower the total potential surface energy -- rationalizing the use of surfactant, which is a direct solution to reducing the surface tension of the aqueous solution. By conducting cryogenic electron tomography (cryoET) with the widely-tested sample, GroEL, we demonstrate that, in a standard buffer solution, nearly all particles migrate to the AWI. Gradual reduction of the surface tension by introducing surfactants decreased the percentage of particles exposed to the surface. By conducting single-particle cryoEM, we confirm that applicable surfactants do not damage the biological complex, thus suggesting that they might offer a practical, simple, and general solution to the problem for high-resolution cryoEM. Application of this solution to a real-world AWI adsorption problem with a more challenging membrane protein, namely, the ClC-1 channel, has led to its first near-atomic structure using cryoEM.

biophysics↗

bioRxiv2023

RealSeq2: a software integrated with UMI identification, error correction, and methylation modifications storing

High-throughput UMI technology sequencing is widely used in early tumor screening, detection, recurrence monitoring, etc. Detecting extremely low-frequency mutations is especially important for monitoring tumor recurrence, so high-precision data, as well as high-quality data, are required. We developed RealSeq2, a new integrated data-preprocessing software based on fastp and gencore, to achieve adapter removal, quality control, UMI identification, and generate consensus reads by clustering and error correction using multithreading in high-throughput next-generation sequencing background. RealSeq2 also supports methylation data of 5-methylcytosine bisulfite-free sequencing. RealSeq2 defined a new tag in SAM for storing methylation information, which is beneficial for co-identifying methylation sites and mutation sites for downstream analysis. RealSeq2 includes three submodules: ReadsProfiler, ReadsCleaner, and ReadsRecycler. In addition, the output format file (BAM or SAM) is universal for downstream analyses. RealSeq2 is the preferred upstream analysis software for the co-detection of ultra-low frequency mutations and bisulfite-free methylation data. The error profile provides data support for downstream analysis. Additionally, XM tags will become a standard protocol for recording methylation signals.

bioinformatics↗

bioRxiv2023

Temperature-dependent regulation of Arabidopsis thaliana growth and development by LSM7

Temperature affects plant growth by modulating the expression of genes and subsequent processing of RNAs that govern essential physiological processes. Here, we show that Arabidopsis thaliana Sm-like7 (LSM7), a core component of the splicing and decapping machinery, is indispensable for embryogenesis and development. Hypomorphic lsm7-2 mutants display severe developmental defects that are exacerbated by high temperatures. Transcriptome analysis verified LSM7s extensive role in gene regulation. In particular, we found that the key regulator of thermomorphogenesis, PHYTOCHROME INTERACTING FACTOR 4 (PIF4), and auxin-related genes, including SMALL AUXIN UP-REGULATED (SAUR) genes, are misregulated in lsm7-2. Auxin metabolic profiling confirmed that auxin homeostasis was disturbed in lsm7-2. Importantly, overexpression of the auxin-responsive SAUR19 gene partially restored thermomorphogenesis defects in lsm7-2 under high ambient temperature. Taken together, our research provides mechanistic insights into the interplay between RNA processing, hormone homeostasis, and the response to temperature regulation in plants and elucidates LSM7s essential function in plant temperature acclimation and resilience. Significance StatementGiven their sessile nature, plants cannot escape adverse environmental conditions such as cold or heat. Instead, they continuously adjust their gene expression and RNA processing to regulate growth and physiology in response to their surroundings. In this study, we investigated the role of the core RNA processing factor LSM7 in temperature acclimation in Arabidopsis thaliana. We found that LSM7 knockdown mutants were impaired in thermomorphogenesis and, as a result, were hypersensitive to elevated temperatures. At the molecular level, we demonstrated that this temperature sensitivity was caused by the misregulation of key regulators of thermomorphogenesis, including PIF4, auxin homeostasis and signaling, and SAUR genes. Our findings provide valuable insights into the role of RNA processing in plant temperature acclimation.

plant biology↗

bioRxiv2023

Artificial selection footprints in domestic chicken genomes

Accurate and low-cost next generation sequencing technologies make re-sequencing of large populations of a species possible. Although many studies related to artificial selection signatures of commercial and indigenous chickens have been carried out, quite a small number of genes have been found to be under selection. In this study, we re-sequenced 85 individuals of five indigenous chicken breeds with distinct traits from Yunnan, a southwest province of China. By analyzing these indigenous chickens together with 116 individuals of commercial chickens (broilers and layers) and 35 individuals of red jungle fowl, we find a substantially large number of selective sweeps and affected genes for each chicken breed using a rigorous statistic model than previously reported. We confirm most of previously identified selective sweeps and affected genes. Meanwhile the vast majority ([~]98.3%) of our identified selective sweeps overlap known chicken quantitative trait loci. Thus, our predictions are highly reliable. For each breed, we also identify candidate genes and selective sweeps that might be related to the unique traits of the chickens.

bioinformatics↗

bioRxiv2023

Xiphoid nucleus of the midline thalamus controls cold-induced food seeking

Maintaining body temperature is calorically expensive for endothermic animals. Mammals eat more in the cold to compensate for energy expenditure, but the neural mechanism underlying this coupling is not well understood. Through behavioral and metabolic analyses, we found that mice dynamically switch between energy conservation and food-seeking states in the cold, the latter of which is primarily driven by energy expenditure rather than the sensation of cold. To identify the neural mechanisms underlying cold-induced food seeking, we use whole-brain cFos mapping and found that the xiphoid (Xi), a small nucleus in the midline thalamus, was selectively activated by prolonged cold associated with elevated energy expenditure but not with acute cold exposure. In vivo calcium imaging showed that Xi activity correlates with food-seeking episodes in cold conditions. Using activity-dependent viral strategies, we found that optogenetic and chemogenetic stimulation of cold-activated Xi neurons recapitulated cold-induced feeding, whereas their inhibition suppressed it. Mechanistically, Xi encodes a context-dependent valence switch promoting food-seeking behaviors in cold but not warm conditions. Furthermore, these behaviors are mediated by a Xi to nucleus accumbens projection. Our results establish Xi as a key region for controlling cold-induced feeding, an important mechanism for maintaining energy homeostasis in endothermic animals.

neuroscience↗

bioRxiv2023

Phosphorylation of pyruvate dehydrogenase marks the inhibition of in vivo neuronal activity

For decades, the expression of immediate early genes (IEGs) such as c-fos has been the most widely used molecular marker representing neuronal activation. However, to date, there is no equivalent surrogate available for the decrease of neuronal activity (i.e., inhibition). Here, we developed an optogenetic-based biochemical screen in which population neural activities can be controlled by light with single action potential precision, followed by unbiased phosphoproteomic profiling. We identified that the phosphorylation of pyruvate dehydrogenase (pPDH) inversely correlated with the intensity of action potential firing in primary neurons. In in vivo mouse models, monoclonal antibody-based pPDH immunostaining detected neuronal inhibition across the brain induced by a wide range of factors including general anesthesia, sensory experiences, and natural behaviors. Thus, as an in vivo marker for neuronal inhibition, pPDH can be used together with IEGs or other cell-type markers to profile and identify bi-directional neural dynamics induced by experiences or behaviors.

neuroscience↗

bioRxiv2023

Mapping the landscape of magnetic field effects on neural regeneration and repair: a systematic review, mathematical model, and meta-analysis

Although magnetic field exposure is a well-established diagnostic tool, its use as a therapeutic in regenerative medicine is relatively new. Our goal here was to evaluate how magnetic fields affect neural repair in vitro by performing a systematic review of the literature, mathematical modeling, and meta-analyses. The 38 included articles presented with high heterogeneity, representing 13 cell types, magnitudes ranging from 0.0002-10,000 mT, frequencies from 0-150 Hz, and exposure times lasting from one hour to several weeks. Mathematical modeling revealed that increasing magnetic field magnitude increases neural progenitor cell (NPC) viability. For regenerative processes that were not influenced by magnitude, frequency, and time, we integrated data with meta-analyses. Results revealed that magnetic field exposure increases NPC proliferation while decreasing astrocytic differentiation. Collectively, our work identifies neural repair processes that may be most responsive to magnetic field exposure and provides a framework for novel hypothesis and technology development.

neuroscience↗

bioRxiv2023

PIFiA: Self-supervised Approach for Protein Functional Annotation from Single-Cell Imaging Data

Fluorescence microscopy data describe protein localization patterns at single-cell resolution and have the potential to reveal whole-proteome functional information with remarkable precision. Yet, extracting biologically meaningful representations from cell micrographs remains a major challenge. Existing approaches often fail to learn robust and noise-invariant features or rely on supervised labels for accurate annotations. We developed PIFiA, (Protein Image-based Functional Annotation), a self-supervised approach for protein functional annotation from single-cell imaging data. We imaged the global yeast ORF-GFP collection and applied PIFiA to generate protein feature profiles from single-cell images of fluorescently tagged proteins. We show that PIFiA outperforms existing approaches for molecular representation learning and describe a range of downstream analysis tasks to explore the information content of the feature profiles. Specifically, we cluster extracted features into a hierarchy of functional organization, study cell population heterogeneity, and develop techniques to distinguish multi-localizing proteins and identify functional modules. Finally, we confirm new PIFiA predictions using a colocalization assay, suggesting previously unappreciated biological roles for several proteins. Paired with a fully interactive website (https://thecellvision.org/pifia/), PIFiA is a resource for the quantitative analysis of protein organization within the cell.

bioinformatics↗

bioRxiv2023

Dynamical modeling reveals RNA decay mediates the effect of matrix stiffness on aged muscle stem cell fate

Loss of muscle stem cell (MuSC) self-renewal with aging reflects a combination of influences from the intracellular (e.g., post-transcriptional modifications) and extracellular (e.g., matrix stiffness) environment. Whereas conventional single cell analyses have revealed valuable insights into factors contributing to impaired self-renewal with age, most are limited by static measurements that fail to capture nonlinear dynamics. Using bioengineered matrices mimicking the stiffness of young and old muscle, we showed that while young MuSCs were unaffected by aged matrices, old MuSCs were phenotypically rejuvenated by young matrices. Dynamical modeling of RNA velocity vector fields in silico revealed that soft matrices promoted a self-renewing state in old MuSCs by attenuating RNA decay. Vector field perturbations demonstrated that the effects of matrix stiffness on MuSC self-renewal could be circumvented by fine-tuning the expression of the RNA decay machinery. These results demonstrate that post-transcriptional dynamics dictate the negative effect of aged matrices on MuSC self-renewal. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=125 SRC="FIGDIR/small/529950v2_ufig1.gif" ALT="Figure 1"> View larger version (39K): org.highwire.dtl.DTLVardef@1a840corg.highwire.dtl.DTLVardef@d354cforg.highwire.dtl.DTLVardef@650556org.highwire.dtl.DTLVardef@41587c_HPS_FORMAT_FIGEXP M_FIG Graphical abstract description: The balance of self-renewal and differentiation in young muscle stem cells (MuSCs) is robust to perturbations of the biophysical microenvironment. In contrast, aged MuSCs are highly sensitive to extrinsic perturbations, and exposure to a youthful microenvironment rejuvenates the self-renewing potential of aged MuSCs by modulating post-transcriptional RNA dynamics. C_FIG

cell biology↗

bioRxiv2023

NeoTCR: an immunoinformatic database of experimentally-supported functional neoantigen-specific TCR sequences

Neoantigen-based immunotherapy has demonstrated of long-lasting antitumor activity. Recognition of neoantigens by T cell receptors (TCRs) is considered a trigger for antitumor responses. Due to the overwhelming number of TCR repertoires in the human genome, it is challenging to computationally pinpoint neoantigen-specific TCRs. Recent studies have identified a number of functional neoantigen-specific TCRs, but the corresponding information is scattered across published literature and is difficult to retrieve. To improve access to these data, we developed the NeoTCR, an immunoinformatic database containing a unified description of publicly available neoantigen-specific TCR sequences, as well as relevant information on targeted neoantigens, from experimentally supported studies across 18 cancer subtypes. A user-friendly web interface allows interactive browsing and running of complex database queries based on numerous criteria. To facilitate rapid identification of neoantigen-specific TCRs from raw sequencing data, NeoTCR offers a one-stop analysis for annotation and visualization of TCR clonotypes, discovery of existing neoantigen-specific TCRs, and exclusion of bystander viral-associated TCRs. NeoTCR will serve as a valuable platform to study the biological functions of neoantigen-associated T-cells in anti-tumor immunity to better apply neoantigen-specific TCRs in clinics. NeoTCR is available at http://www.neotcrdb.com/.

bioinformatics↗

bioRxiv2023

Duck pan-genome reveals two transposon-derived structural variations caused bodyweight enlarging and white plumage phenotype formation during evolution

Structural variations (SVs) are a major source of domestication and improvement traits, however SV profiles of duck and their phenotypic impacts largely hidden. We present the first duck pan-genome constructed using five genome assemblies capturing [~]40.98 Mb new sequences. This pan-genome together with high-depth sequencing data ([~]46.5X) identified 101,041 SVs, of which substantial proportions were derived from transposable element (TE) activity. Many TE-derived SVs anchoring in a gene body or regulatory region are linked to ducks domestication and improvement. By combining quantitative genetics with molecular experiments, we dissect how TE-derived SVs change gene expression of IGF2BP1 and generate a novel transcript of MITF, shaping bodyweight and white plumage. In the IGF2BP1 locus, the TE-derived SV explains the largest effect on bodyweight among avian species (27.61% of phenotypic variation). Our findings highlight the importance of using a pan-genome as a reference in genomics studies and explore the roles of TE-derived SVs in trait formation and in livestock breeding.

genetics↗

bioRxiv2023

Predicting tumor immune microenvironment and checkpoint therapy response of head & neck cancer patients from blood immune single-cell transcriptomics

The immune state of tumor microenvironment is crucial for determining immunotherapy response but is not readily accessible. Here we investigate if we can infer the tumor immune state from the blood and further predict immunotherapy response. First, we analyze a dataset of head and neck squamous cell carcinoma (HNSCC) patients with matched scRNA-Seq of peripheral blood mononuclear cells (PBMCs) and tumor tissues. We find that the tumor immune cell fractions of different immune cell types and many of the genes they express can be inferred from the matched PBMC scRNA-Seq. Second, analyzing another HNSCC dataset with PBMC scRNA-Seq and immunotherapy response, we find that the inferred ratio between tumor memory B and regulatory T cell fractions is predictive of immunotherapy response and is superior to the well-established cytolytic and exhausted T-cell signatures. Overall, these results showcase the potential of scRNA-Seq liquid biopsies in cancer immunotherapy, calling for their larger-scale testing. SignificanceThis head and neck cancer study demonstrates the potential of using blood single-cell transcriptomics to (1) infer the tumor immune status and (2) predict immunotherapy response from the tumor immune status inferred from blood. These results showcase the potential of single-cell transcriptomics liquid biopsies for further advancing personalized cancer immunotherapy.

bioinformatics↗

bioRxiv2023

Decoupling the correlation between cytotoxic and exhausted T lymphocyte transcriptomic signatures enhances melanoma immunotherapy response prediction

BackgroundCytotoxic T lymphocytes (CTL) play a crucial role in anti-cancer immunity. Progression of CTL to terminal exhausted T lymphocytes (ETL) that overexpress inhibitory receptors can substantially decrease effector cytokines production and diminish cytolytic activity and terminal exhausted T cell cannot be reprogrammed by ICIs in tumor microenvironment (TME). However, while the activity levels of CTL and ETL are considered important determinants of immune checkpoint inhibitors (ICIs) response, it has been repeatedly observed that their predictive power of the latter is quite limited. Studying this conundrum on a large scale across the TCGA cohort, we find that ETL and CTL activity (estimated based on conventional gene signatures in the bulk tumor expression) is strongly positively correlated in most cancer types. We hypothesized that the limited predictive power of CTL activity might result from the high concordance of CTL and ETL activities, which mutually cancels out their individual antagonistic effects on ICI response. MethodsConsequently, we have set out to identify a set of genes whose expression identifies a subset of patients where the CTL and ETL correlation is diminished, such that the association between these CD8+ T cell states and ICIs response is enhanced. Resultsnalyzing TCGA melanoma bulk gene expression, we identified a set of genes whose over-expression markedly diminishes the CTL and ETL correlation, termed a decoupling signature (DS). Reassuringly, we first find that the correlation between ETL and CTL activities is indeed markedly lower across high scoring DS patients than that observed across low scoring DS patients in numerous independent melanoma ICIs cohorts. Second, indeed, this successful decoupling increases the power of CTL activity in predicting ICIs response in high DS scoring patients. We show that the resulting prediction accuracy is superior to other state-of-art ICI predictive transcriptomic signatures. ConclusionThe new decoupling score boosts the power of CTL activity in predicting ICIs response in melanoma from the tumor bulk expression. Its use enables a two-step stratification approach, where the response of high scoring DS patient can be predicted more accurately that with extant transcriptomic signatures. What is already known on this topicThe predictive power of CTL activity based on bulk tumor transcriptomics, despite being a widely studied important determinant of ICI treatment, is very limited. What this study addsThe efficacy of CTL activity in predicting ICI therapy response is significantly higher among patients with decoupled CTL and ETL activities. How this study might affect research, practice or policyWe identified a set of genes as the decoupling signature, whose upregulation markedly diminishes the correlation between CTL and ETL activities. Our decoupling signature enhances the power of CTL in predicting ICI treatment response, outperforming other extant expression-based signatures.

bioinformatics↗

bioRxiv2023

Genomic evolution of non-small cell lung cancer patient-derived xenograft models

Patient-derived xenograft (PDX) models of cancer, developed through injection of patient tumour cells into immunocompromised mice, have been widely adopted in preclinical studies, as well as in precision oncology approaches. However, the extent to which PDX models represent the underlying genetic diversity of a patients tumour and the extent of on-going genomic evolution in PDX models are incompletely understood, particularly in the context of heterogeneous cancers such as non-small cell lung cancer (NSCLC). To investigate the depiction of intratumour heterogeneity by PDX models, we derived 47 new subcutaneous multi-region PDX models from 22 patients with primary NSCLC enrolled in the clinical longitudinal cohort study TRACERx. By analysing whole exome sequencing data from primary tumours and PDX models, we find that PDX establishment creates a genomic bottleneck, with 76% of PDX models being derived from a single primary tumour subclone. Despite this, multiple primary tumour subclones were capable of PDX establishment in regional PDX models, indicating that PDX libraries derived from multiple tumour regions can capture intratumour heterogeneity. Acquisition of somatic mutations continued during PDX model expansion, and was associated with APOBEC- or mismatch repair deficiency-induced mutational signatures in a subset of models. Overall, while NSCLC PDX models retain truncal genomic alterations, the absence of subclonal heterogeneity representative of the primary tumour is a major limitation. Our results emphasise the importance of characterising and monitoring intratumour heterogeneity in the context of pre-clinical cancer studies.

cancer biology↗

bioRxiv2023

Systematic assessment of the contribution of structural variants to inherited retinal diseases

Despite increasing success in determining genetic diagnosis for patients with inherited retinal diseases (IRDs), mutations in about 30% of the IRD cases remain unclear or unsettled after targeted gene panel or whole exome sequencing. In this study, we aimed to investigate the contributions of structural variants (SVs) to settling the molecular diagnosis of IRD with whole-genome sequencing (WGS). A cohort of 755 IRD patients whose pathogenic mutations remain undefined was subjected to WGS. Four SV calling algorithms including include MANTA, DELLY, LUMPY, and CNVnator were used to detect SVs throughout the genome. All SVs identified by any one of these four algorithms were included for further analysis. AnnotSV was used to annotate these SVs. SVs that overlap with known IRD-associated genes were examined with sequencing coverage, junction reads, and discordant read pairs. PCR followed by Sanger sequencing was used to further confirm the SVs and identify the breakpoints. Segregation of the candidate pathogenic alleles with the disease was performed when possible. In total, sixteen candidate pathogenic SVs were identified in sixteen families, including deletions and inversions, representing 2.1% of patients with previously unsolved IRDs. Autosomal dominant, autosomal recessive, and X-linked inheritance of disease-causing SVs were observed in 12 different genes. Among these, SVs in CLN3, EYS, PRPF31 were found in multiple families. Our study suggests that the contribution of SVs detected by short-read WGS is about 0.25% of our IRD patient cohort and is significantly lower than that of single nucleotide changes and small insertions and deletions.

genetics↗

bioRxiv2022

Lipoprotein sorting to the cell surface via a crosstalk between the Lpt and Lol pathways during outer membrane biogenesis

Lipopolysaccharide (LPS) and lipoprotein, two essential components of the outer membrane (OM) in Gram-negative bacteria, play critical roles in bacterial physiology and pathogenicity. LPS translocation to the OM is mediated by LptDE, yet how lipoproteins sort to the cell surface remains elusive. Here we report the identification of an inventory of lipoproteins that are transported to the cell surface via LptDE. Notably, we determined crystal structures of LptDE from Pseudomonas aeruginosa and its complex with an endogenous Escherichia coli lipoprotein YifL. The paLptDE-YifL structure demonstrates that YifL translocates to the OM via LptDE, in a manner similar to LPS transport. The {beta}-barrel domain serves as a passage for the proteinaceous moiety while its acyl chains are transported outside. Our finding has been corroborated by results from native mass spectrometry, immunofluorescence, and photocrosslinking assays, revealing a unique mechanism through which lipoproteins are translocated across the OM in an ATP- and LPS-dependent manner. Moreover, our study expands the scope of current knowledge of lipoprotein sorting by disclosing a crosstalk between the Lpt and Lol pathways.

microbiology↗