Biology subjects

Giai Gianetto, Q.

Publications and source records attributed to Giai Gianetto, Q..

At least 19 recordsLinked to original sources

bioRxiv2026

SARS-CoV-2 ORF9b exploits mitochondrial recruitment to TOMM70 for proteasomal protection and tunes inflammatory remodeling during lung infection

Mitochondrial outer membrane proteins are exploited by diverse intracellular pathogens, to modulate cell metabolism and innate sensing pathways. Here, we demonstrate that TOMM70-dependent mitochondrial recruitment is required to protect SARS-CoV-2 ORF9b from proteasomal degradation, a dependency conserved across ORF9b homologs from related coronaviruses. ORF9b mitochondrial recruitment requires the E477 residue of TOMM70, a surface distinct from that used by the parasite Toxoplasma gondii to engage host mitochondria. We further show that TOMM70 is not a passive scaffold: its depletion activates interferon-stimulated gene expression independently of infection and remodels host immunity distinctly from ORF9b, establishing the receptor and viral protein as mechanistically separable. Using ORF9b-deficient SARS-CoV-2, we demonstrate that ORF9b is dispensable for viral replication and pathological responses in human respiratory epithelial cells and lungs of infected golden Syrian hamsters. Omics profiling of SARS-CoV-2 infected lungs revealed an induction of pathways related to COVID-19 in the absence of ORF9b. Notably, ORF9b-deficient virus-infected lungs show elevated expression of C15ORF48, a nuclear-encoded mitochondrial protein that substitutes for Complex IV subunit NDUFA4 to attenuate inflammation. Collectively, we propose that ORF9b is a receptor-gated viral protein whose principal measurable consequence during authentic infection is a restraint on inflammatory respiratory-chain remodeling.

cell biology↗

bioRxiv2026

diagFDR: Verifiable False Discovery Rate Reporting in Proteomics via Scope, Calibration, and Stability Diagnostics

AO_SCPLOWBSTRACTC_SCPLOWIn mass spectrometry-based proteomics, false discovery rate (FDR) control underpins the credibility of peptide and protein identifications. In contemporary workflows, including multi-run Data Independent Acquisition (DIA), deep learning-assisted scoring, library-free searches, and extensive post-processing, the statement "1% FDR" has become increasingly ambiguous, potentially referring to different statistical entities, multiple-testing scopes, and null models. We propose a standardized framework requiring explicit specification of three complementary properties: "scope", meaning which statistical universe is controlled; "calibration", meaning whether confidence measures behave consistently with their intended interpretation on the reported unit; and "stability", meaning whether acceptance thresholds and resulting identification lists remain robust to perturbations. Building on routine target/decoy outputs, we introduce pipeline-agnostic diagnostics that audit internal coherence of scores, q-values, and posterior error probabilities, quantify tail support and cutoff fragility, and test plausibility of target-decoy assumptions. We further complement internal checks with external validation via entrapment, which measures empirical false positives on knownabsent sequences. We highlight a "granularity paradox": as scoring becomes more discriminative, decoy matches can become so sparse near stringent cutoffs that the numerical support for decoy-based estimation deteriorates, making reported FDR thresholds increasingly fragile despite improved separation between the distributions of target and decoy scores. Applications to DIA-NN and MS2Rescore show that scope and aggregation choices can materially alter both estimated error rates and list reproducibility. We provide a practical reporting checklist and an open-source R package (diagFDR, available from CRAN) that generates diagnostic reports from standard software outputs. As a minimal verifiable reporting standard, we recommend that any "FDR = %" claim specify the controlled unit and scope, report tail support at the operating cutoff, and make decoy-inclusive outputs available for independent verification. HighlightsO_LIFDR claims can be misleading without explicit scope, calibration, and stability assessment. C_LIO_LIdiagFDR introduces pipeline-agnostic diagnostics from standard software outputs. C_LIO_LIThe granularity paradox shows sparse decoy tails can make stringent cutoffs numerically fragile. C_LIO_LICase studies show that scope misuse and rescoring can affect both error rates and stability. C_LIO_LIdiagFDR produces reviewer-ready reports and a practical reporting checklist. C_LI

bioinformatics↗

bioRxiv2026

Bacterial targeting of host paraspeckles uncovers a new SFPQ-based regulation

Nuclear functions are key in protecting cells against infections, yet intracellular pathogens like Legionella pneumophila can exploit these mechanisms to survive. We characterized a L. pneumophila protein, LpDot1, which shares sequence similarity with the eukaryotic catalytic domain of the histone methyltransferase DOT1. Structure determination, together with biochemical and biophysical analyses, revealed that LpDot1 methylates non-histone nuclear proteins, notably the splicing factor proline-glutamine rich protein (SFPQ). Importantly, LpDot1 targets the previously uncharacterized K518, located on an important structural motif of SFPQ, therefore impairing its dimerization in vitro. During infection, L. pneumophila modulates SFPQ abundance and activities in a LpDot1-dependent manner, thereby hijacking paraspeckle organization and the host cell splicing machinery, leading to alternative splice variants of infection related genes such as NF-kB2 and CD45. To our knowledge, this is the first report of a bacterial effector directly modifying paraspeckle dynamics, providing new insight into previously uncharacterized eukaryotic regulatory pathways.

microbiology↗

bioRxiv2025

ProteoBench: the community-curated platform for comparing proteomics data analysis workflows

Mass spectrometry (MS)-based proteomics is a well-established strategy for analyzing complex biological mixtures. Many MS instruments and data acquisition strategies are available, and the data they acquire differ substantially, thus requiring tailored analysis algorithms. Hence, many dedicated bioinformatics workflows are developed. These are in constant evolution, and the community lacks a centralized platform for comparing their performance. Here, we propose ProteoBench, a single platform that brings together software developers and software users to provide an ever-evolving comparison of state-of-the-art proteomics data processing tools. ProteoBench is an open-source resource that enables the community to evaluate data analysis workflows, develop benchmarking modules dedicated to specific comparisons, and discuss the best methods to compare software tools. The platform ensures that the benchmark evolves alongside advances in proteomics data analysis workflows. ProteoBench guides researchers towards the best-suited tool and parameters for their specific project and data according to their needs, and developers can test their newly developed tools or workflows privately, before adding them as public references. This community-driven effort will increase transparency and reproducibility between MS data analysis workflows, as well as facilitate the development and publication of software workflows in the field.

bioinformatics↗

bioRxiv2025

Exploring the multi-protein assembly of the enzymes of the de novo purine nucleotide biosynthetic pathway from Pseudomonas aeruginosa

Purine nucleotide biosynthesis is a crucial metabolic pathway responsible that produces building blocks essential for a plethora of cellular processes. In bacteria, the de novo purine nucleotide biosynthetic pathway (DNPNB) involves fifteen chemical steps catalysed by fourteen different enzymes. While the mammalian orthologues have been extensively shown to interact and form a metabolon named "purinosome", the possible existence of a prokaryotic equivalent was only recently revealed for the case of Escherichia coli. In this study, we explored the potential conservation of a bacterial purinosome-like complex in Pseudomonas aeruginosa, an opportunistic pathogen known for its high antibiotic resistance. Using a bacterial two-hybrid system, we mapped protein-protein interactions among all tested DNPNB enzymes in P. aeruginosa and revealed a dense interaction network. An in-silico protein-protein docking approach on three core enzymes allowed the structural reconstitution of a complex composed of PurK, PurE and PurC with a 4:8:8 stoichiometry, respectively. Interestingly, a tunnel connecting the different active sites has been revealed, showing a metabolon-like property for possible efficient substrate channelling. These findings support a conserved regulatory organization of purine biosynthesis in bacteria, providing deeper insights into bacterial metabolism and paving the way for potential antibiotic targets.

biochemistry↗

bioRxiv2025

Mapping regulatory networks underlying Leishmania stage differentiation reveals an essential role for protein degradation in parasite development

Vector-borne, protist parasites have evolved complex developmental programs to adapt to very distinct host environments. How these important pathogens transition between insect and mammalian stages is only poorly understood. Here we investigate stage differentiation in the trypanosomatid parasite Leishmania that shows constitutive gene transcription, thus providing a unique model system to assess how development is governed by post-transcriptional mechanisms. Using a five-layer integrative systems analysis (from genome to metabolome), we examined hamster-isolated Leishmania donovani amastigotes and culture-derived, insect-stage promastigotes. This approach enabled us to rule out genomic adaptation as a key driver of parasite stage differentiation, while confirming the pivotal role of differential mRNA turnover in stage-specific gene expression. Assessing transcriptomic against proteomic expression changes uncovered an unexpectedly broad dynamic range of stage-regulated changes in protein abundance that only poorly correlated with mRNA levels. This discrepancy correlated with (i) alterations in snoRNA expression and changes in rRNA modification they guide suggesting stage-specific adaptation of the protein translation apparatus that can uncouple mRNA from protein abundancies, and (ii) differential protein degradation as revealed by quantitative proteomics of parasites treated with the proteasomal inhibitor lactacystin. Lactacystin treatment stalled the transition of spleen-derived amastigotes into promastigotes in culture, further underscoring the role of proteasomal activity in stage differentiation. Integration of our five-layer systems analysis established the first link between Leishmania development and the expression of co-regulated genetic networks encompassing mRNA turnover, protein translation, phosphorylation, and degradation. Our findings provide a powerful new resource for research programs that aim to dissect the emergent properties of regulatory networks and feedback loops underlying Leishmania stage differentiation, serving as a blueprint for other vector-borne pathogens that rely on disease-associated developmental transitions.

systems biology↗

bioRxiv2024

Influenza A virus-induced production of PI4P at the endoplasmic reticulum involves ATG16L1 and promotes the egress of viral ribonucleoproteins

The genomic RNAs of influenza A viruses (IAVs) are replicated in the nucleus of infected cells in the form of viral ribonucleoproteins (vRNP) before being exported to the cytoplasm. The small GTPase RAB11A is involved in the transport of vRNPs to the sites of viral assembly at the plasma membrane, but the molecular mechanisms involved remain largely unknown. Here we show that IAV infection remodels the architecture of the endoplasmic reticulum (ER) sheets, where vRNPs tend to accumulate in the absence of RAB11A. To decipher the interplay between RAB11A, vRNPs and the ER, we investigated viral-induced perturbations of RAB11A proximity interactome. To this end, we generated cells stably expressing a TurboID-RAB11A fusion protein and performed biotin-based proximity labeling upon viral infection. We found that cellular regulators of phophatidylinositol-4-phosphate (PI4P) homeostasis, including the autophagic and stress response protein ATG16L1, are significantly enriched at the vicinity of RAB11A in infected cells. Infection induces an increase in cellular PI4P levels in an ATG16L1-dependent manner, while ATG16L1 relocalizes to ER membranes upon infection. Depletion of ATG16L1 decreases the co-distribution of vRNPs with PI4P punctae on ER membranes, and reduces the accumulation of vRNPs at the plasma membrane as well as the production of IAV infectious particles. Our data extend to IAVs the notion that viruses can modulate the metabolism and localization of phosphoinositides to control host membrane dynamics and point to the ER as an essential platform for vRNP transport. They provide evidence for a pivotal role of ATG16L1 in regulating the identity of endomembranes and coordinating RAB11A and PI4P-enriched membranes to ensure delivery of vRNPs to the plasma membrane.

microbiology↗

bioRxiv2023

Dual proteomic signature of immune cells and Yersinia pestis upon blood infection

Emerging and reemerging infectious diseases represent major public health concerns. The urgent need for infection control measures requires deep understanding of molecular pathogenesis. Global approaches to study biological systems such as mass-spectrometry based proteomics benefited from groundbreaking physical and bioinformatical technological developments over recent years. However, dual proteomic study of highly pathogenic microorganisms and their hosts in complex matrices encountered during infection remains challenging due to high protein dynamic range of samples and requirements imposed in biosafety level 3 or 4 laboratories. Here, we constructed a dual proteomic pipeline of Yersinia pestis in human blood and plasma, mirroring bacteremic phase of plague. We provide the most complete Y. pestis proteome revealing a major reshaping of important bacterial path-ways such as methionine biosynthesis and iron acquisition in human plasma. Remarkably, proteomic profiling in human blood highlights a greater Yersinia outer proteins intoxication of monocytes than neutrophils. Our study unravels global expression changes and points to a specific pathogenic signature during infection, paving the way for future exploration of proteomes in the complex context of host-pathogen interactions. Subject CategoriesMicrobiology, Virology and Host Pathogen Interaction, Proteomics

systems biology↗

bioRxiv2023

The RBPome of influenza A virus mRNA reveals a role for TDP-43 in viral replication

Recent technical advances have significantly improved our understanding of the RNA-binding protein (RBP) repertoire present within eukaryotic cells, with a particular focus on the RBPs that interact with cellular polyadenylated mRNAs. However, recent studies utilising the same technologies have begun to tease apart the RBP interactome of viral mRNAs, notably SARS-CoV-2, revealing both similarities and differences between the RBP profiles of viral and cellular mRNAs. Herein, we comprehensively identified the RBPs that associate with the NP mRNA of an influenza A virus. Moreover, we provide evidence that the viral polymerase is essential for the recruitment of RPBs to viral mRNAs through direct polymerase-RBP interactions during transcription. We show that loss of TDP-43, which associates with the viral mRNAs, results in lower levels of viral mRNAs within infected cells, and a decreased yield of infectious viral particles. Overall, our results uncover an important role for TDP-43 in the influenza A virus replication cycle via a direct interaction with viral mRNAs, and point to a role of the viral polymerase in orchestrating the assembly of viral mRNPs.

microbiology↗

bioRxiv2022

Queuosine modification of tRNA-Tyrosine elicits translational reprogramming and enhances growth of Vibrio cholerae with aminoglycosides.

Tgt is the enzyme modifying the guanine (G) in tRNAs with GUN anticodon to queuosine (Q). tgt is required for optimal growth of Vibrio cholerae in the presence of sub-lethal aminoglycoside concentrations. We further explored here the role of the Q34 in the efficiency of codon decoding upon tobramycin exposure. We characterized its impact on the overall bacterial proteome, and elucidated the molecular mechanisms underlying the effects of Q34 modification in antibiotic translational stress response. Using molecular reporters, we showed that Q34 impacts the efficiency of decoding at tyrosine TAT and TAC codons. Proteomics analyses revealed that the anti-SoxR factor RsxA is better translated in the absence of tgt. RsxA displays a codon bias towards tyrosine TAT and overabundance of RsxA leads to decreased expression of genes belonging to SoxR oxidative stress regulon. We also identified conditions that regulate tgt expression. We propose that regulation of Q34 modification in response to environmental cues leads to translational reprogramming of transcripts bearing a biased tyrosine codon usage. In silico analysis further identified candidate genes which could be subject to such translational regulation, among which DNA repair factors. Such transcripts, fitting the definition of modification tunable transcripts, are central in the bacterial response to antibiotics.

microbiology↗

bioRxiv2022

Arp2/3 inhibition switches Eps8's network associations to favour longer actin filament formation necessary for tunneling nanotubes

Tunneling nanotubes (TNTs) connect distant cells and mediate cargo transfer for intercellular communication in physiological and pathological contexts. How cells generate these actin-mediated protrusions to span lengths beyond those attainable by canonical filopodia remains unknown. Through a combination of micropatterning, microscopy and optical tweezer-based approaches, we demonstrate that TNTs forming through the outward extension of actin (not through cellular dislodgement) achieve distances greater than the mean length of filopodia, and that branched Arp2/3-dependent pathways attenuate the extent to which actin polymerizes in nanotubes, limiting TNT occurrence. Proteomic analysis using Epidermal growth factor receptor kinase substrate 8 (Eps8) as a positive effector of TNTs showed that upon Arp2/3 inhibition, proteins enhancing filament turnover and depolymerization were reduced and Eps8 instead exhibited heightened interactions with the inverted Bin/Amphiphysin/Rvs (I-BAR) domain protein IRSp53 that provides a direct connection with linear actin polymerases. Our data reveals how common protrusion players (Eps8 and IRSp53) form TNTs, and that when competing pathways overutilizing such proteins and monomeric actin in Arp2/3 networks are inhibited, processes promoting linear actin growth dominate to favour TNT formation. Thus, this work reinforces a general principle for actin network control for cellular protrusions where simple shifts in the balance between processes that inhibit actin growth versus those that promote growth dictate protrusion formation and the ultimate length scales protrusions achieve.

cell biology↗

bioRxiv2022

MSclassifR: an R package for supervised classification of mass spectra with machine learning methods

MSclassifR is an R package that has been specifically designed to improve the classification of mass spectra obtained from MALDI-TOF mass spectrometry. It offers a comprehensive range of functions that are focused on processing mass spectra, identifying discriminant m/z values, and making accurate predictions. The package introduces innovative algorithms for selecting discriminating m/z values and making predictions. To assess the effectiveness of these methods, extensive tests were conducted using challenging real datasets, including bacterial subspecies of the Mycobacterium abscessus complex, virulent and avirulent phenotypes of Escherichia coli, different species of Streptococci and nasal swabs from individuals infected and uninfected with SARS-CoV-2. Additionally, multiple datasets of varying sizes were created from these real datasets to evaluate the robustness of the algorithms. The results demonstrated that the Machine Learning-based pipelines in MSclassifR achieved high levels of accuracy and Kappa values. On an in-house dataset, some pipelines even achieved more than 95% mean accuracy, whereas commercial system only achieved 62% mean accuracy. Certain methods showed greater resilience to changes in dataset sizes when constructing Machine Learning-based pipelines. These simulations also helped determine the minimum sizes of training sets required to obtain reliable results. The package is freely available online, and its open-source nature encourages collaborative development, customization, and fosters innovation within the community focused on improving diagnosis based on MALDI-TOF spectra. Key pointsO_LIMSclassifR is a comprehensive R package enabling the construction of data analysis pipelines for the precise classification of mass spectra. C_LIO_LIOur R package contains an innovative method for variable selection from random forests, which delivered excellent results on real data. C_LIO_LIIn-depth analysis of various machine learning-based pipelines using our package allowed us to make conclusions about the optimal m/z selection and prediction methods depending on the size of the training dataset. C_LIO_LIUsing a publicly available dataset of mass spectra obtained from various MALDI-TOF instruments across different countries, MSclassifR is able to build robust pipelines capable of adapting to different instruments in an automatic way. C_LIO_LIWhen tested on an in-house dataset, MSclassifR pipelines consistently outperformed a commercial software in terms of prediction accuracy. C_LI

bioinformatics↗

bioRxiv2021

Post-transcriptional regulation of Leishmania fitness gain

The protozoan parasite Leishmania donovani causes fatal human visceral leishmaniasis in absence of treatment. Genome instability has been recognized as a driver in Leishmania fitness gain in response to environmental change or chemotherapy. How genome instability generates beneficial phenotypes despite potential deleterious gene dosage effects is unknown. Here we address this important open question applying experimental evolution and integrative systems approaches on parasites adapting to in vitro culture. Phenotypic analyses of parasites from early and late stages of culture adaptation revealed an important fitness tradeoff, with selection for accelerated growth in promastigote culture (fitness gain) impairing infectivity (fitness costs). Comparative genomics, transcriptomics and proteomics analyses revealed a complex regulatory network driving parasite fitness, with genome instability causing highly reproducible, gene dosage-dependent changes in protein abundance linked to post-transcriptional regulation. These in turn were associated with a gene dosage-independent reduction in abundance of flagellar transcripts and a coordinated increase in abundance of coding and non-coding RNAs implicated in ribosomal biogenesis and protein translation. We correlated differential expression of small nucleolar RNAs (snoRNAs) with changes in rRNA modification, providing first evidence that Leishmania fitness gain in culture may be controlled by post-transcriptional and epitranscriptomic regulation. Our findings propose a novel model for Leishmania fitness gain in culture, where differential regulation of mRNA stability and the generation of fitness-adapted ribosomes may potentially filter deleterious from beneficial gene dosage effects and provide proteomic robustness to genetically heterogenous, adapting parasite populations. This model challenges the current, genome-centric approach to Leishmania epidemiology and identifies the Leishmania transcriptome and non-coding small RNome as potential novel sources for the discovery of biomarkers that may be associated with parasite phenotypic adaptation in clinical settings.

microbiology↗

bioRxiv2020

Ser/Thr kinase-dependent phosphorylation of the peptidoglycan hydrolase CwlA controls its export and modulates cell division in Clostridioides difficile

Cell growth and division require a balance between synthesis and hydrolysis of the peptidoglycan (PG). Inhibition of PG synthesis or uncontrolled PG hydrolysis can be lethal for the cells, making it imperative to control peptidoglycan hydrolase (PGH) activity. The serine/threonine kinases (STKs) of the Hanks family control cell division and envelope homeostasis, but only a few kinase substrates and associated molecular mechanisms have been identified. In this work, we identified CwlA as the first STK-PrkC substrate in the human pathogen Clostridiodes difficile and showed that CwlA is an endopeptidase involved in daughter cell separation. We demonstrated that PrkC-dependent phosphorylation inhibits CwlA export, therefore controlling the hydrolytic activity in the cell wall. High level of CwlA at the cell surface led to cell elongation, whereas low level caused cell separation defects. We thus provided evidence that the STK signaling pathway regulates PGH homeostasis to precisely control PG hydrolysis during cell division.

microbiology↗

bioRxiv2020

Preventing neutrophil from oxygen exposure allows their basal state maintenance

Neutrophils are the most abundant circulating white blood cells and are central players of the innate immune response. During their lifecycle, neutrophils mainly evolve under low oxygen conditions (0.1 - 4% O2) to which they are well adapted. Neutrophils are atypical cells since they are mainly glycolytic, and highly susceptible to oxygen-exposure, which induces their activation and death, through mechanisms which remain currently elusive. Nevertheless, nearly all studies conducted on neutrophils are carried out under atmospheric oxygen (21%), corresponding to hyperoxic conditions. Here we investigated the impact of hyperoxia during neutrophil purification and culture on neutrophil viability, activation and cytosolic protein content. Neutrophil hyper-activation (CD62L shedding) is induced during culture under hyperoxic conditions (24h), compared to neutrophils cultured under anoxic conditions. In addition, we show that maintaining neutrophils in autologous plasma is the most suitable strategy to maintain their basal state. Our results show that manipulating neutrophils under hyperoxic conditions leads to the loss of ~100 cytosolic proteins during purification, while it does not lead to an immediate impact on neutrophils activation (CD11bhigh, CD54high, CD62Llow) or viability (DAPI+). We identified two clusters of proteins belonging to the cholesterol metabolism and to the complement and coagulation cascade pathways, which are highly susceptible to neutrophil oxygen-exposure during their purification. In conclusion, preserving neutrophil from oxygen-exposure during their manipulation - purification and culture- is recommended to avoid their experimental activation and for preserving a large set of cytosolic proteins from alteration.

immunology↗

bioRxiv2020

A peptide-level multiple imputation strategy accounting for the different natures of missing values in proteomics data

MotivationQuantitative mass spectrometry-based proteomics data are characterized by high rates of missing values, which may be of two kinds: missing completely-at-random (MCAR) and missing not-at-random (MNAR). Despite numerous imputation methods available in the literature, none account for this duality, for it would require to diagnose the missingness mechanism behind each missing value. ResultsA multiple imputation strategy is proposed by combining MCAR-devoted and MNAR-devoted imputation algorithms. First, we propose an estimator for the proportion of MCAR values and show it is asymptotically unbiased under assumptions adapted to label-free proteomics data. This allows us to estimate the number of MCAR values in each sample and to take into account the nature of missing values through an original multiple imputation method. We evaluate this approach on simulated data and shows it outperforms traditionally used imputation algorithms. AvailabilityThe proposed methods are implemented in the R package imp4p (available on the CRAN Giai Gianetto (2020)), which is itself accessible through Prostar software. Contactquentin.giaigianetto@pasteur.fr; thomas.burger@cea.fr

bioinformatics↗

bioRxiv2020

Proteomic Analysis Uncovers Measles Virus Protein C Interaction with p65/iASPP/p53 Protein Complex

Viruses manipulate central machineries of host cells to their advantage. They prevent host cell antiviral responses to create a favorable environment for their survival and propagation. Measles virus (MV) encodes two non-structural proteins MV-V and MV-C known to counteract the host interferon response and to regulate cell death pathways. Several molecular mechanisms underlining MV-V regulation of innate immunity and cell death pathways have been proposed, whereas MV-C host protein partners are less studied. We suggest that some cellular factors that are controlled by MV-C protein during viral replication could be components of innate immunity and the cell death pathways. To determine which host factors are targeted by MV-C, we captured both direct and indirect host protein partners of MV-C protein. For this, we used a strategy based on recombinant viruses expressing tagged viral proteins followed by affinity purification and a bottom-up mass spectrometry analysis. From the list of host proteins specifically interacting with MV-C protein in different cell lines we selected the host targets that belong to immunity and cell death pathways for further validation. Direct protein partners of MV-C were determined by applying protein complementation assay (PCA) and the bioluminescence resonance energy transfer (BRET) approach. As a result, we found that MV-C protein specifically interacts with p65/iASPP/p53 protein complex that controls both cell death and innate immunity pathways.

microbiology↗

bioRxiv2020

Phosphorylation Dependent Assembly of a 14-3-3 Mediated Signaling Complex During Red Blood Cell Invasion by Plasmodium falciparum Merozoites

Red blood cell (RBC) invasion by Plasmodium merozoites requires multiple steps that are regulated by signaling pathways. Exposure of P. falciparum merozoites to the physiological signal of low K+, as found in blood plasma, leads to a rise in cytosolic Ca2+, which mediates microneme secretion, motility, and invasion. We have used global phosphoproteomic analysis of merozoites to identify signaling pathways that are activated during invasion. Using quantitative phosphoproteomics we found 394 protein phosphorylation site changes in merozoites subjected to different ionic environments (high K+/ low K+) out of which 143 were Ca2+-dependent. These included a number of signaling proteins such as catalytic and regulatory subunits of protein kinase A (PfPKAc and PfPKAr) and calcium-dependent protein kinase 1 (PfCDPK1). Proteins of the 14-3-3 family interact with phosphorylated target proteins to assemble signaling complexes. Here, using co-immunoprecipitation and gel filtration chromatography, we demonstrate that Pf14-3-3I binds phosphorylated PfPKAr and PfCDPK1 to mediate the assembly of a multi-protein complex in P. falciparum merozoites. A phospho-peptide, P1, based on the Ca2+ dependent phosphosites of PKAr, binds Pf14-3-3I and disrupts assembly of the Pf14-3-3I-mediated multi-protein complex. Disruption of the multi-protein complex with P1 inhibits microneme secretion and RBC invasion. This study thus identifies a novel signaling complex that plays a key role in merozoite invasion of RBCs. Disruption of this signaling complex could serve as a novel approach to inhibit blood stage growth of malaria parasites. ImportanceInvasion of red blood cells (RBCs) by Plasmodium falciparum merozoites is a complex process that is regulated by intricate signaling pathways. Here, we have used phosphoproteomic profiling to identify the key proteins involved in signaling events during invasion. We found changes in the phosphorylation of various merozoite proteins including multiple kinases previously implicated in the process of invasion. We also found that a phosphorylation dependent multi-protein complex including signaling kinases assembles during the process of invasion. Disruption of this multi-protein complex impairs merozoite invasion of RBCs providing a novel approach for the development of inhibitors to block the growth of blood stage malaria parasites.

microbiology↗