Plasma proteomics in children with new-onset type 1 diabetes identifies new potential biomarkers of partial remission.

Partial remission (PR) occurs in only half of people with new-onset type 1 diabetes (T1D) and corresponds to a transient period characterized by low daily insulin needs, low glycemic fluctuations and increased endogenous insulin secretion. While identification of people with newly-onset T1D and significant residual beta-cell function may foster patient-specific interventions, reliable predictive biomarkers of PR occurrence currently lack. We analyzed the plasma of children with new-onset T1D to identify biomarkers present at diagnosis that predicted PR at 3 months post-diagnosis. We first performed an extensive shotgun proteomic analysis using Liquid Chromatography-Tandem-Mass-Spectrometry (LCMS/MS) on the plasma of 16 children with new-onset T1D and quantified 98 proteins significantly correlating with Insulin-Dose Adjusted glycated hemoglobin A1c score (IDAA1C). We next applied a series of both qualitative and statistical filters and selected protein candidates that were associated to pathophysiological mechanisms related to T1D. Finally, we translationally verified several of the candidates using single-shot targeted proteomic (PRM method) on raw plasma. Taken together, we identified plasma biomarkers present at diagnosis that may predict the occurrence of PR in a single mass-spectrometry run. We believe that the identification of new predictive biomarkers of PR and ß-cell function is key to stratify people with new-onset T1D for ß-cell preservation therapies.

Deep Plasma Proteomics with Data-Independent Acquisition: Clinical Study Protocol Optimization with a COVID-19 Cohort.

Plasma proteomics is a precious tool in human disease research but requires extensive sample preparation in order to perform in-depth analysis and biomarker discovery using traditional data-dependent acquisition (DDA). Here, we highlight the efficacy of combining moderate plasma prefractionation and data-independent acquisition (DIA) to significantly improve proteome coverage and depth while remaining cost-efficient. Using human plasma collected from a 20-patient COVID-19 cohort, our method utilizes commonly available solutions for depletion, sample preparation, and fractionation, followed by 3 liquid chromatography-mass spectrometry/MS (LC-MS/MS) injections for a 360 min total DIA run time. We detect 1321 proteins on average per patient and 2031 unique proteins across the cohort. Differential analysis further demonstrates the applicability of this method for plasma proteomic research and clinical biomarker identification, identifying hundreds of differentially abundant proteins at biological concentrations as low as 47 ng/L in human plasma. Data are available via ProteomeXchange with the identifier PXD047901. In summary, this study introduces a streamlined, cost-effective approach to deep plasma proteome analysis, expanding its utility beyond classical research environments and enabling larger-scale multiomics investigations in clinical settings. Our comparative analysis revealed that fractionation, whether the samples were pooled or separate postfractionation, significantly improved the number of proteins quantified. This underscores the value of fractionation in enhancing the depth of plasma proteome analysis, thereby offering a more comprehensive landscape for biomarker discovery in diseases such as COVID-19.

Spatial transcriptomics profiling of gallbladder adenocarcinoma: a detailed two-case study of progression from precursor lesions to cancer.

BACKGROUND: Most studies on tumour progression from precursor lesion toward gallbladder adenocarcinoma investigate lesions sampled from distinct patients, providing an overarching view of pathogenic cascades. Whether this reflects the tumourigenic process in individual patients remains insufficiently explored. Genomic and epigenomic studies suggest that a subset of gallbladder cancers originate from biliary intraepithelial neoplasia (BilIN) precursor lesions, whereas others form independently from BilINs. Spatial transcriptomic data supporting these conclusions are missing. Moreover, multiple areas with precursor or adenocarcinoma lesions can be detected within the same pathological sample. Yet, knowledge about intra-patient variability of such lesions is lacking. METHODS: To characterise the spatial transcriptomics of gallbladder cancer tumourigenesis in individual patients, we selected two patients with distinct cancer aetiology and whose samples simultaneously displayed multiple areas of normal epithelium, BilINs and adenocarcinoma. Using GeoMx digital spatial profiling, we characterised the whole transcriptome of a high number of regions of interest (ROIs) per sample in the two patients (24 and 32 ROIs respectively), with each ROI covering approximately 200 cells of normal epithelium, low-grade BilIN, high-grade BilIN or adenocarcinoma. Human gallbladder organoids and cell line-derived tumours were used to investigate the tumour-promoting role of genes. RESULTS: Spatial transcriptomics revealed that each type of lesion displayed limited intra-patient transcriptomic variability. Our data further suggest that adenocarcinoma derived from high-grade BilIN in one patient and from low-grade BilIN in the other patient, with co-existing high-grade BilIN evolving via a distinct process in the latter case. The two patients displayed distinct sequences of signalling pathway activation during tumour progression, but Semaphorin 4 A (SEMA4A) expression was repressed in both patients. Using human gallbladder-derived organoids and cell line-derived tumours, we provide evidence that repression of SEMA4A promotes pseudostratification of the epithelium and enhances cell migration and survival. CONCLUSION: Gallbladder adenocarcinoma can develop according to patient-specific processes, and limited intra-patient variability of precursor and cancer lesions was noticed. Our data suggest that repression of SEMA4A can promote tumour progression. They also highlight the need to gain gene expression data in addition to histological information to avoid understimating the risk of low-grade preneoplastic lesions.

Standardized Workflow for Mass-Spectrometry-Based Single-Cell Proteomics Data Processing and Analysis Using the scp Package.

Mass-spectrometry (MS)-based single-cell proteomics (SCP) explores cellular heterogeneity by focusing on the functional effectors of the cells-proteins. However, extracting meaningful biological information from MS data is far from trivial, especially with single cells. Currently, data analysis workflows are substantially different from one research team to another. Moreover, it is difficult to evaluate pipelines as ground truths are missing. Our team has developed the R/Bioconductor package called scp to provide a standardized framework for SCP data analysis. It relies on the widely used QFeatures and SingleCellExperiment data structures. In addition, we used a design containing cell lines mixed in known proportions to generate controlled variability for data analysis benchmarking. In this chapter, we provide a flexible data analysis protocol for SCP data using the scp package together with comprehensive explanations at each step of the processing. Our main steps are quality control on the feature and cell level, aggregation of the raw data into peptides and proteins, normalization, and batch correction. We validate our workflow using our ground truth data set. We illustrate how to use this modular, standardized framework and highlight some crucial steps.

Identification of RSK substrates using an analog-sensitive kinase approach.

The p90 ribosomal S6 kinases (RSK) family of serine/threonine kinases comprises four isoforms (RSK1-4) that lie downstream of the ERK1/2 mitogen-activated protein kinase pathway. RSKs are implicated in fine tuning of cellular processes such as translation, transcription, proliferation, and motility. Previous work showed that pathogens such as Cardioviruses could hijack any of the four RSK isoforms to inhibit PKR activation or to disrupt cellular nucleocytoplasmic trafficking. In contrast, some reports suggest nonredundant functions for distinct RSK isoforms, whereas Coffin-Lowry syndrome has only been associated with mutations in the gene encoding RSK2. In this work, we used the analog-sensitive kinase strategy to ask whether the cellular substrates of distinct RSK isoforms differ. We compared the substrates of two of the most distant RSK isoforms: RSK1 and RSK4. We identified a series of potential substrates for both RSKs in cells and validated RanBP3, PDCD4, IRS2, and ZC3H11A as substrates of both RSK1 and RSK4, and SORBS2 as an RSK1 substrate. In addition, using mutagenesis and inhibitors, we confirmed analog-sensitive kinase data showing that endogenous RSKs phosphorylate TRIM33 at S1119. Our data thus identify a series of potential RSK substrates and suggest that the substrates of RSK1 and RSK4 largely overlap and that the specificity of the various RSK isoforms likely depends on their cell- or tissue-specific expression pattern.

CytoPipeline and CytoPipelineGUI: a Bioconductor R package suite for building and visualizing automated pre-processing pipelines for flow cytometry data.

BACKGROUND: With the increase of the dimensionality in flow cytometry data over the past years, there is a growing need to replace or complement traditional manual analysis (i.e. iterative 2D gating) with automated data analysis pipelines. A crucial part of these pipelines consists of pre-processing and applying quality control filtering to the raw data, in order to use high quality events in the downstream analyses. This part can in turn be split into a number of elementary steps: signal compensation or unmixing, scale transformation, debris, doublets and dead cells removal, batch effect correction, etc. However, assembling and assessing the pre-processing part can be challenging for a number of reasons. First, each of the involved elementary steps can be implemented using various methods and R packages. Second, the order of the steps can have an impact on the downstream analysis results. Finally, each method typically comes with its specific, non standardized diagnostic and visualizations, making objective comparison difficult for the end user. RESULTS: Here, we present CytoPipeline and CytoPipelineGUI, two R packages to build, compare and assess pre-processing pipelines for flow cytometry data. To exemplify these new tools, we present the steps involved in designing a pre-processing pipeline on a real life dataset and demonstrate different visual assessment use cases. We also set up a benchmarking comparing two pre-processing pipelines differing by their quality control methods, and show how the package visualization utilities can provide crucial user insight into the obtained benchmark metrics. CONCLUSION: CytoPipeline and CytoPipelineGUI are two Bioconductor R packages that help building, visualizing and assessing pre-processing pipelines for flow cytometry data. They increase productivity during pipeline development and testing, and complement benchmarking tools, by providing user intuitive insight into benchmarking results.

Post-Hypoglycemic hyperglycemia are highly relevant markers for stratification of glycemic variability and partial remission status of pediatric patients with new-onset type 1 diabetes.

AIMS: To evaluate whether parameters of post-hypoglycemic hyperglycemia (PHH) correlated with glucose homeostasis during the first year after type 1 diabetes onset and helped to distinguish pediatric patients undergoing partial remission or not. METHODS: In the GLUREDIA (GLUcagon Response to hypoglycemia in children and adolescents with new-onset type 1 DIAbetes) study, longitudinal values of clinical parameters, continuous glucose monitoring metrics and residual ß-cell secretion from children with new-onset type 1 diabetes were analyzed during the first year after disease onset. PHH parameters were calculated using an in-house algorithm. Correlations between PHH parameters (i.e., PHH frequency, PHH duration, PHH area under the curve [PHHAUC]) and glycemic homeostasis markers were studied using adjusted mixed-effects models. RESULTS: PHH parameters were strong markers to differentiate remitters from non-remitters with PHH/Hyperglycemia duration ratio being the most sensitive (ratio<0.02; sensitivity = 86% and specificity = 68%). PHHAUC moderately correlated with parameters of glucose homeostasis including TIR (R2 = 0.35, p-value < 0.05), coefficient of variation (R2 = 0.22, p-value < 0.05) and Insulin-Dose Adjusted A1c (IDAA1C) (R2 = 0.32, p-value < 0.05) and with residual ß-cell secretion (R2 = 0.17, p-value < 0.05). Classification of patients into four previously described glucotypes independently validated PHH parameters as reliable markers of glucose homeostasis and improved the segregation of patients with intermediate values of IDAA1C and estimated C-peptide (CPEPEST). Finally, a combination of PHH parameters identified groups of patients with specific patterns of hypoglycemia. CONCLUSION: PHH parameters are new minimal-invasive markers to discriminate remitters from non-remitters and evaluate glycemic homeostasis during the first year of type 1 diabetes. PHH parameters may also allow patient-targeted therapeutic management of hypoglycemic episodes.

Revisiting the Thorny Issue of Missing Values in Single-Cell Proteomics.

Missing values are a notable challenge when analyzing mass spectrometry-based proteomics data. While the field is still actively debating the best practices, the challenge increased with the emergence of mass spectrometry-based single-cell proteomics and the dramatic increase in missing values. A popular approach to deal with missing values is to perform imputation. Imputation has several drawbacks for which alternatives exist, but currently, imputation is still a practical solution widely adopted in single-cell proteomics data analysis. This perspective discusses the advantages and drawbacks of imputation. We also highlight 5 main challenges linked to missing value management in single-cell proteomics. Future developments should aim to solve these challenges, whether it is through imputation or data modeling. The perspective concludes with recommendations for reporting missing values, for reporting methods that deal with missing values, and for proper encoding of missing values.

Curated single cell multimodal landmark datasets for R/Bioconductor.

BACKGROUND: The majority of high-throughput single-cell molecular profiling methods quantify RNA expression; however, recent multimodal profiling methods add simultaneous measurement of genomic, proteomic, epigenetic, and/or spatial information on the same cells. The development of new statistical and computational methods in Bioconductor for such data will be facilitated by easy availability of landmark datasets using standard data classes. RESULTS: We collected, processed, and packaged publicly available landmark datasets from important single-cell multimodal protocols, including CITE-Seq, ECCITE-Seq, SCoPE2, scNMT, 10X Multiome, seqFISH, and G&T. We integrate data modalities via the MultiAssayExperiment Bioconductor class, document and re-distribute datasets as the SingleCellMultiModal package in Bioconductor's Cloud-based ExperimentHub. The result is single-command actualization of landmark datasets from seven single-cell multimodal data generation technologies, without need for further data processing or wrangling in order to analyze and develop methods within Bioconductor's ecosystem of hundreds of packages for single-cell and multimodal data. CONCLUSIONS: We provide two examples of integrative analyses that are greatly simplified by SingleCellMultiModal. The package will facilitate development of bioinformatic and statistical methods in Bioconductor to meet the challenges of integrating molecular layers and analyzing phenotypic outputs including cell differentiation, activity, and disease.

SUZ domain-containing proteins have multiple effects on nonsense-mediated decay target transcripts.

Many transcripts are targeted by nonsense-mediated decay (NMD), leading to their degradation and the inhibition of their translation. We found that the protein SUZ domain-containing protein 1 (SZRD1) interacts with the key NMD factor up-frameshift 1. When recruited to NMD-sensitive reporter gene transcripts, SZRD1 increased protein production, at least in part, by relieving translational inhibition. The conserved SUZ domain in SZRD1 was required for this effect. The SUZ domain is present in only three other human proteins besides SZRD1: R3H domain-containing protein 1 and 2 (R3HDM1, R3HDM2) and cAMP-regulated phosphoprotein 21 (ARPP21). We found that ARPP21, similarly to SZRD1, can increase protein production from NMD-sensitive reporter transcripts in an SUZ domain-dependent manner. This indicated that the SUZ domain-containing proteins could prevent translational inhibition of transcripts targeted by NMD. Consistent with the idea that SZRD1 mainly prevents translational inhibition, we did not observe a systematic decrease in the abundance of NMD targets when we knocked down SZRD1. Surprisingly, knockdown of SZRD1 in two different cell lines led to reduced levels of the NMD component UPF3B, which was accompanied by increased levels in a subset of NMD targets. This suggests that SZRD1 is required to maintain normal UPF3B levels and indicates that the effect of SZRD1 on NMD targets is not limited to a relief from translational inhibition. Overall, our study reveals that human SUZ domain-containing proteins play a complex role in regulating protein output from transcripts targeted by NMD.

Gut microbiome modulates tacrolimus pharmacokinetics through the transcriptional regulation of ABCB1.

BACKGROUND: Following solid organ transplantation, tacrolimus (TAC) is an essential drug in the immunosuppressive strategy. Its use constitutes a challenge due to its narrow therapeutic index and its high inter- and intra-pharmacokinetic (PK) variability. As the contribution of the gut microbiota to drug metabolism is now emerging, it might be explored as one of the factors explaining TAC PK variability. Herein, we explored the consequences of TAC administration on the gut microbiota composition. Reciprocally, we studied the contribution of the gut microbiota to TAC PK, using a combination of in vivo and in vitro models. RESULTS: TAC oral administration in mice resulted in compositional alterations of the gut microbiota, namely lower evenness and disturbance in the relative abundance of specific bacterial taxa. Compared to controls, mice with a lower intestinal microbial load due to antibiotics administration exhibit a 33% reduction in TAC whole blood exposure and a lower inter-individual variability. This reduction in TAC levels was strongly correlated with higher expression of the efflux transporter ABCB1 (also known as the p-glycoprotein (P-gp) or the multidrug resistance protein 1 (MDR1)) in the small intestine. Conventionalization of germ-free mice confirmed the ability of the gut microbiota to downregulate ABCB1 expression in a site-specific fashion. The functional inhibition of ABCB1 in vivo by zosuquidar formally established the implication of this efflux transporter in the modulation of TAC PK by the gut microbiota. Furthermore, we showed that polar bacterial metabolites could recapitulate the transcriptional regulation of ABCB1 by the gut microbiota, without affecting its functionality. Finally, whole transcriptome analyses pinpointed, among others, the Constitutive Androstane Receptor (CAR) as a transcription factor likely to mediate the impact of the gut microbiota on ABCB1 transcriptional regulation. CONCLUSIONS: We highlight for the first time how the modulation of ABCB1 expression by bacterial metabolites results in changes in TAC PK, affecting not only blood levels but also the inter-individual variability. More broadly, considering the high number of drugs with unexplained PK variability transported by ABCB1, our work is of clinical importance and paves the way for incorporating the gut microbiota in prediction algorithms for dosage of such drugs. Video Abstract.

Axon guidance genes control hepatic artery development.

Earlier data on liver development demonstrated that morphogenesis of the bile duct, portal mesenchyme and hepatic artery is interdependent, yet how this interdependency is orchestrated remains unknown. Here, using 2D and 3D imaging, we first describe how portal mesenchymal cells become organised to form hepatic arteries. Next, we examined intercellular signalling active during portal area development and found that axon guidance genes are dynamically expressed in developing bile ducts and portal mesenchyme. Using tissue-specific gene inactivation in mice, we show that the repulsive guidance molecule BMP co-receptor A (RGMA)/neogenin (NEO1) receptor/ligand pair is dispensable for portal area development, but that deficient roundabout 2 (ROBO2)/SLIT2 signalling in the portal mesenchyme causes reduced maturation of the vascular smooth muscle cells that form the tunica media of the hepatic artery. This arterial anomaly does not impact liver function in homeostatic conditions, but is associated with significant tissular damage following partial hepatectomy. In conclusion, our work identifies new players in development of the liver vasculature in health and liver regeneration.

Tumour immune rejection triggered by activation of α2-adrenergic receptors.

Immunotherapy based on immunecheckpoint blockade (ICB) using antibodies induces rejection of tumours and brings clinical benefit in patients with various cancer types1. However, tumours often resist immune rejection. Ongoing efforts trying to increase tumour response rates are based on combinations of ICB with compounds that aim to reduce immunosuppression in the tumour microenvironment but usually have little effect when used as monotherapies2,3. Here we show that agonists of α2-adrenergic receptors (α2-AR) have very strong anti-tumour activity when used as monotherapies in multiple immunocompetent tumour models, including ICB-resistant models, but not in immunodeficient models. We also observed marked effects in human tumour xenografts implanted in mice reconstituted with human lymphocytes. The anti-tumour effects of α2-AR agonists were reverted by α2-AR antagonists, and were absent in Adra2a-knockout (encoding α2a-AR) mice, demonstrating on-target action exerted on host cells, not tumour cells. Tumours from treated mice contained increased infiltrating T lymphocytes and reduced myeloid suppressor cells, which were more apoptotic. Single-cell RNA-sequencing analysis revealed upregulation of innate and adaptive immune response pathways in macrophages and T cells. To exert their anti-tumour effects, α2-AR agonists required CD4+ T lymphocytes, CD8+ T lymphocytes and macrophages. Reconstitution studies in Adra2a-knockout mice indicated that the agonists acted directly on macrophages, increasing their ability to stimulate T lymphocytes. Our results indicate that α2-AR agonists, some of which are available clinically, could substantially improve the clinical efficacy of cancer immunotherapy.

Senescence and senotherapies in biliary atresia and biliary cirrhosis.

BACKGROUND: Premature senescence occurs in adult hepatobiliary diseases and worsens the prognosis through deleterious liver remodeling and hepatic dysfunction. Senescence might also arises in biliary atresia (BA), the first cause of pediatric liver transplantation. Since alternatives to transplantation are needed, our aim was to investigate premature senescence in BA and to assess senotherapies in a preclinical model of biliary cirrhosis. METHODS: BA liver tissues were prospectively obtained at hepatoportoenterostomy (n=5) and liver transplantation (n=30) and compared to controls (n=10). Senescence was investigated through spatial whole transcriptome analysis, SA-ß-gal activity, p16 and p21 expression, γ-H2AX and senescence-associated secretory phenotype (SASP). Human allogenic liver-derived progenitor cells (HALPC) or dasatinib and quercetin (D+Q) were administrated to two-month-old Wistar rats after bile duct ligation (BDL). RESULTS: Advanced premature senescence was evidenced in BA livers from early stage and continued to progress until liver transplantation. Senescence and SASP were predominant in cholangiocytes, but also present in surrounding hepatocytes. HALPC but not D+Q reduced the early marker of senescence p21 in BDL rats and improved biliary injury (serum γGT and Sox9 expression) and hepatocytes mass loss (Hnf4a). CONCLUSIONS: BA livers displayed advanced cellular senescence at diagnosis that continued to progress until liver transplantation. HALPC reduced early senescence and improved liver disease in a preclinical model of BA, providing encouraging preliminary results regarding the use of senotherapies in pediatric biliary cirrhosis.

Specific HIF-2α (Hypoxia-Inducible Factor-2) Inhibitor PT2385 Mitigates Placental Dysfunction In Vitro and in a Rat Model of Preeclampsia (RUPP).

BACKGROUND: Preeclampsia is one of the leading causes of maternal mortality worldwide and is strongly associated with long-term morbidity in mothers and newborns. Referred to as one of the deep placentation disorders, insufficient remodeling of the spiral arteries during the first trimester remains a major cause of placental dysfunction. Persisting pulsatile uterine blood flow causes abnormal ischemia/reoxygenation phenomenon in the placenta and stabilizes the HIF-2α (hypoxia-inducible factor-2α) in the cytotrophoblasts. HIF-2α signaling impairs trophoblast differentiation and increases sFLT-1 (soluble fms-like tyrosine kinase-1) secretion, which reduces fetal growth and causes maternal symptoms. This study aims to evaluate the benefits of using PT2385-an oral specific HIF-2α inhibitor-to treat severe placental dysfunction. METHODS: To evaluate its therapeutic potential, PT2385 was first studied in primary human cytotrophoblasts isolated from term placenta and exposed to 2.5% O2 to stabilize HIF-2α. Viability and luciferase assays, RNA sequencing, and immunostaining were used to analyze differentiation and angiogenic factor balance. The ability of PT2385 to mitigate maternal manifestations of preeclampsia was studied in the selective reduced uterine perfusion pressure model performed in Sprague-Dawley rats. RESULTS: In vitro, RNA sequencing analysis and conventional techniques showed that treated cytotrophoblast displayed an enhanced differentiation into syncytiotrophoblasts and normalized angiogenic factor secretion compared with vehicle-treated cells. In the selective reduced uterine perfusion pressure model, PT2385 efficiently decreased sFLT-1 production, thus preventing the onset of hypertension and proteinuria in pregnant dams. CONCLUSIONS: These results highlight HIF-2α as a new player in our understanding of placental dysfunction and support the use of PT2385 to treat severe preeclampsia in humans.

Initial recommendations for performing, benchmarking and reporting single-cell proteomics experiments.

Analyzing proteins from single cells by tandem mass spectrometry (MS) has recently become technically feasible. While such analysis has the potential to accurately quantify thousands of proteins across thousands of single cells, the accuracy and reproducibility of the results may be undermined by numerous factors affecting experimental design, sample preparation, data acquisition and data analysis. We expect that broadly accepted community guidelines and standardized metrics will enhance rigor, data quality and alignment between laboratories. Here we propose best practices, quality controls and data-reporting recommendations to assist in the broad adoption of reliable quantitative workflows for single-cell proteomics. Resources and discussion forums are available at https://single-cell.net/guidelines .

Splenectomy improves erythrocyte functionality in spherocytosis based on septin abundance, but not maturation defects.

Splenectomy improves the clinical parameters of patients with hereditary spherocytosis, but its potential benefit to red blood cell (RBC) functionality and the mechanism behind this benefit remain largely overlooked. Here, we compared 7 nonsplenectomized and 13 splenectomized patients with mutations in the ß-spectrin or the ankyrin gene. We showed that hematological parameters, spherocyte abundance, osmotic fragility, intracellular calcium, and extracellular vesicle release were largely but not completely restored by splenectomy, whereas cryohemolysis was not. Affected RBCs exhibited decreases in ß-spectrin and/or ankyrin contents and slight alterations in spectrin membrane distribution, depending on the mutation. These modifications were found in both splenectomized and nonsplenectomized patients and poorly correlated with RBC functionality alteration, suggesting additional impairments. Accordingly, we found an increased abundance of septins, small guanosine triphosphate-binding cytoskeletal proteins. Septins-2, -7, and -8 but not -11 were less abundant upon splenectomy and correlated with the disease severity. Septin-2 membrane association was confirmed by immunolabeling. Except for cryohemolysis, all parameters of RBC morphology and functionality correlated with septin abundance. The increased septin content might result from RBC maturation defects, as evidenced by (1) the decreased protein 4.2 and Rh-associated glycoprotein content in all patient RBCs, (2) increased endoplasmic reticulum remnants and endocytosis proteins in nonsplenectomized patients, and (3) increased lysosomal and mitochondrial remnants in splenectomized patients. Our study paves the way for a better understanding of the involvement of septins in RBC membrane biophysical properties. In addition, the lack of restoration of septin-independent cryohemolysis by splenectomy may call into question its recommendation in specific cases.

The Current State of Single-Cell Proteomics Data Analysis.

Sound data analysis is essential to retrieve meaningful biological information from single-cell proteomics experiments. This analysis is carried out by computational methods that are assembled into workflows, and their implementations influence the conclusions that can be drawn from the data. In this work, we explore and compare the computational workflows that have been used over the last four years and identify a profound lack of consensus on how to analyze single-cell proteomics data. We highlight the need for benchmarking of computational workflows and standardization of computational tools and data, as well as carefully designed experiments. Finally, we cover the current standardization efforts that aim to fill the gap, list the remaining missing pieces, and conclude with lessons learned from the replication of published single-cell proteomics analyses. © 2023 Wiley Periodicals LLC.

Semi-Supervised Non-Parametric Bayesian Modelling of Spatial Proteomics.

Understanding sub-cellular protein localisation is an essential component in the analysis of context specific protein function. Recent advances in quantitative mass-spectrometry (MS) have led to high resolution mapping of thousands of proteins to sub-cellular locations within the cell. Novel modelling considerations to capture the complex nature of these data are thus necessary. We approach analysis of spatial proteomics data in a non-parametric Bayesian framework, using K-component mixtures of Gaussian process regression models. The Gaussian process regression model accounts for correlation structure within a sub-cellular niche, with each mixture component capturing the distinct correlation structure observed within each niche. The availability of marker proteins (i.e. proteins with a priori known labelled locations) motivates a semi-supervised learning approach to inform the Gaussian process hyperparameters. We moreover provide an efficient Hamiltonian-within-Gibbs sampler for our model. Furthermore, we reduce the computational burden associated with inversion of covariance matrices by exploiting the structure in the covariance matrix. A tensor decomposition of our covariance matrices allows extended Trench and Durbin algorithms to be applied to reduce the computational complexity of inversion and hence accelerate computation. We provide detailed case-studies on Drosophila embryos and mouse pluripotent embryonic stem cells to illustrate the benefit of semi-supervised functional Bayesian modelling of the data.

Cardiovirus leader proteins retarget RSK kinases toward alternative substrates to perturb nucleocytoplasmic traffic.

Proteins from some unrelated pathogens, including small RNA viruses of the family Picornaviridae, large DNA viruses such as Kaposi sarcoma-associated herpesvirus and even bacteria of the genus Yersinia can recruit cellular p90-ribosomal protein S6 kinases (RSKs) through a common linear motif and maintain the kinases in an active state. On the one hand, pathogens' proteins might hijack RSKs to promote their own phosphorylation (direct target model). On the other hand, some data suggested that pathogens' proteins might dock the hijacked RSKs toward a third interacting partner, thus redirecting the kinase toward a specific substrate. We explored the second hypothesis using the Cardiovirus leader protein (L) as a paradigm. The L protein is known to trigger nucleocytoplasmic trafficking perturbation, which correlates with hyperphosphorylation of phenylalanine-glycine (FG)-nucleoporins (FG-NUPs) such as NUP98. Using a biotin ligase fused to either RSK or L, we identified FG-NUPs as primary partners of the L-RSK complex in infected cells. An L protein mutated in the central RSK-interaction motif was readily targeted to the nuclear envelope whereas an L protein mutated in the C-terminal domain still interacted with RSK but failed to interact with the nuclear envelope. Thus, L uses distinct motifs to recruit RSK and to dock the L-RSK complex toward the FG-NUPs. Using an analog-sensitive RSK2 mutant kinase, we show that, in infected cells, L can trigger RSK to use NUP98 and NUP214 as direct substrates. Our data therefore illustrate a novel virulence mechanism where pathogens' proteins hijack and retarget cellular protein kinases toward specific substrates, to promote their replication or to escape immunity.