Decrypting lysine deacetylase inhibitor action and protein modifications by dose-resolved proteomics.

Lysine deacetylase inhibitors (KDACis) are approved drugs for cutaneous T cell lymphoma (CTCL), peripheral T cell lymphoma (PTCL), and multiple myeloma, but many aspects of their cellular mechanism of action (MoA) and substantial toxicity are not well understood. To shed more light on how KDACis elicit cellular responses, we systematically measured dose-dependent changes in acetylation, phosphorylation, and protein expression in response to 21 clinical and pre-clinical KDACis. The resulting 862,000 dose-response curves revealed, for instance, limited cellular specificity of histone deacetylase (HDAC) 1, 2, 3, and 6 inhibitors; strong cross-talk between acetylation and phosphorylation pathways; localization of most drug-responsive acetylation sites to intrinsically disordered regions (IDRs); an underappreciated role of acetylation in protein structure; and a shift in EP300 protein abundance between the cytoplasm and the nucleus. This comprehensive dataset serves as a resource for the investigation of the molecular mechanisms underlying KDACi action in cells and can be interactively explored online in ProteomicsDB.

Lower access to kidney transplantation for women in France is not explained by comorbidities and social deprivation.

BACKGROUND: Access to kidney transplantation (KT) remains challenging for patients with end-stage kidney disease. This study assessed women's access to KT in France by considering comorbidities and neighborhood social deprivation. METHODS: All incident 18-85-year-old patients starting dialysis in France between January 1, 2017 and December 31, 2019 were included. Three outcomes were assessed: (i) access to the KT waiting list after dialysis start, (ii) KT access after waitlisting, and (iii) KT access after dialysis start. Cox and Fine and Gray models were used. Gender-EDI and gender-age interactions were tested and analyses were performed among strata if required. RESULTS: 29,395 patients were included (35% of women). After adjusting for social deprivation and comorbidities, women were less likely to be waitlisted at 1 (adjHR: 0.91 [0.87-0.96]) and 3 years (adjHR: 0.87 [0.84-0.91]) post-dialysis initiation. This disparity concerned mainly ≥60-year-old women (adjHR: 0.76 [0.71-0.82] at 1 year and 0.75 [0.71-0.81] at 3 years). Access to KT, after 2 years of waitlisting was similar between genders. Access to KT was similar between genders at 3 years after dialysis start, but decreased for women after 4 years (adjHR: 0.93 [0.88-0.99]) and longer follow-up (adjHR: 0.90 [0.85-0.96]). CONCLUSIONS: In France, women are less likely to be waitlisted and undergo kidney transplantation. This is driven by the ≥60-year-old group and is not explained by comorbidities or social deprivation level.

Illuminating phenotypic drug responses of sarcoma cells to kinase inhibitors by phosphoproteomics.

Kinase inhibitors (KIs) are important cancer drugs but often feature polypharmacology that is molecularly not understood. This disconnect is particularly apparent in cancer entities such as sarcomas for which the oncogenic drivers are often not clear. To investigate more systematically how the cellular proteotypes of sarcoma cells shape their response to molecularly targeted drugs, we profiled the proteomes and phosphoproteomes of 17 sarcoma cell lines and screened the same against 150 cancer drugs. The resulting 2550 phenotypic profiles revealed distinct drug responses and the cellular activity landscapes derived from deep (phospho)proteomes (9-10,000 proteins and 10-27,000 phosphorylation sites per cell line) enabled several lines of analysis. For instance, connecting the (phospho)proteomic data with drug responses revealed known and novel mechanisms of action (MoAs) of KIs and identified markers of drug sensitivity or resistance. All data is publicly accessible via an interactive web application that enables exploration of this rich molecular resource for a better understanding of active signalling pathways in sarcoma cells, identifying treatment response predictors and revealing novel MoA of clinical KIs.

CurveCurator: a recalibrated F-statistic to assess, classify, and explore significance of dose-response curves.

Dose-response curves are key metrics in pharmacology and biology to assess phenotypic or molecular actions of bioactive compounds in a quantitative fashion. Yet, it is often unclear whether or not a measured response significantly differs from a curve without regulation, particularly in high-throughput applications or unstable assays. Treating potency and effect size estimates from random and true curves with the same level of confidence can lead to incorrect hypotheses and issues in training machine learning models. Here, we present CurveCurator, an open-source software that provides reliable dose-response characteristics by computing p-values and false discovery rates based on a recalibrated F-statistic and a target-decoy procedure that considers dataset-specific effect size distributions. The application of CurveCurator to three large-scale datasets enables a systematic drug mode of action analysis and demonstrates its scalable utility across several application areas, facilitated by a performant, interactive dashboard for fast data exploration.

Health care provision / Offre de soins

On the occasion of the 20th anniversary of the REIN (French Renal Epidemiology and Information Network), a summary work on the contributions of the French national ESKD register was carried out. On the issue of healthcare provision, the following key messages were retained. France offers diversified, local healthcare that adapts to the patients' needs with several additional players (public, university, lucrative private, solidarity private). However, the spatial distribution of this offer shows differences between territories as regards the distribution of the different treatment modalities. For several years now, the REIN proposes a new way of representing the provision of care using groups of establishments working together, a granularity that seems more suited to the evaluation of practices than isolated dialysis units.

À l'occasion des 20 ans du REIN (Réseau Épidémiologie et Information en Néphrologie), un travail de synthèse sur les apports du registre a été mené. Sur la question de l'offre de soins, les messages clés suivants ont été retenus. La France dispose d'une offre de soins diversifiée, de proximité, qui s'adapte aux besoins des patients avec plusieurs acteurs complémentaires (public, universitaire, privé lucratif, privé solidaire). La répartition spatiale de l'offre montre cependant des différences entre les territoires en ce qui concerne la répartition des différentes modalités de traitement. Depuis plusieurs années, le REIN propose un nouveau mode de représentation de l'offre de soins à partir de regroupements d'établissements travaillant en filière, granularité qui semble plus adaptée à l'évaluation des pratiques que l'échelon unité de dialyse.

The ecology of scale: impact of volume on coalescence and function in methanogenic communities.

Engineered ecosystems span multiple volume scales, from a nano-scale to thousands of cubic metres. Even the largest industrial systems are tested in pilot scale facilities. But does scale affect outcomes? Here we look at comparing different size laboratory anaerobic fermentors to see if and how the volume of the community affects the outcome of community coalescence (combining multiple communities) on community composition and function. Our results show that there is an effect of scale on biogas production. Furthermore, we see a link between community evenness and volume, with smaller scale communities having higher evenness. Despite those differences, the overall patterns of community coalescence are very similar at all scales, with coalescence leading to levels of biogas production comparable with that of the best-performing component community. The increase in biogas with increasing volume plateaus, suggesting there is a volume where productivity stays stable over large volumes. Our findings are reassuring for ecologists studying large ecosystems and industries operating pilot scale facilities, as they support the validity of pilot scale studies in this field.

Unified Workflow for the Rapid and In-Depth Characterization of Bacterial Proteomes.

Bacteria are the most abundant and diverse organisms among the kingdoms of life. Due to this excessive variance, finding a unified, comprehensive, and safe workflow for quantitative bacterial proteomics is challenging. In this study, we have systematically evaluated and optimized sample preparation, mass spectrometric data acquisition, and data analysis strategies in bacterial proteomics. We investigated workflow performances on six representative species with highly different physiologic properties to mimic bacterial diversity. The best sample preparation strategy was a cell lysis protocol in 100% trifluoroacetic acid followed by an in-solution digest. Peptides were separated on a 30-min linear microflow liquid chromatography gradient and analyzed in data-independent acquisition mode. Data analysis was performed with DIA-NN using a predicted spectral library. Performance was evaluated according to the number of identified proteins, quantitative precision, throughput, costs, and biological safety. With this rapid workflow, over 40% of all encoded genes were detected per bacterial species. We demonstrated the general applicability of our workflow on a set of 23 taxonomically and physiologically diverse bacterial species. We could confidently identify over 45,000 proteins in the combined dataset, of which 30,000 have not been experimentally validated before. Our work thereby provides a valuable resource for the microbial scientific community. Finally, we grew Escherichia coli and Bacillus cereus in replicates under 12 different cultivation conditions to demonstrate the high-throughput suitability of the workflow. The proteomic workflow we present in this manuscript does not require any specialized equipment or commercial software and can be easily applied by other laboratories to support and accelerate the proteomic exploration of the bacterial kingdom.

Decrypting drug actions and protein modifications by dose- and time-resolved proteomics.

Although most cancer drugs modulate the activities of cellular pathways by changing posttranslational modifications (PTMs), little is known regarding the extent and the time- and dose-response characteristics of drug-regulated PTMs. In this work, we introduce a proteomic assay called decryptM that quantifies drug-PTM modulation for thousands of PTMs in cells to shed light on target engagement and drug mechanism of action. Examples range from detecting DNA damage by chemotherapeutics, to identifying drug-specific PTM signatures of kinase inhibitors, to demonstrating that rituximab kills CD20-positive B cells by overactivating B cell receptor signaling. DecryptM profiling of 31 cancer drugs in 13 cell lines demonstrates the broad applicability of the approach. The resulting 1.8 million dose-response curves are provided as an interactive molecular resource in ProteomicsDB.

Functional representation of the network organisation of dialysis activities in France: A novel level for assessing quality of care.

To assess quality of care, groups of care units that cared for the same patients at various stages of end-stage renal disease, might be more appropriate than the centre level. These groups constitute "communities" that need to be delineated to evaluate their practices and outcomes. In this article, we describe the use of an agglomerative (Fast Greedy) and a divisive (Edge Betweenness) method to describe dialysis activities in France. The validation was based on the opinion of the field actors at the regional level of the REIN registry. At the end of 2018, ESRD care in France took place in 1,166 dialysis units. During 2016-2018, 32 965 transfers occurred between dialysis units. With the Edge Betweenness method, the 1,114 French dialysis units in metropolitan France were classified into 156 networks and with the Fast Greedy algorithm, 167 networks. Among the 32 965 transfers, 23 168 (70%) were defined in the same cluster by the Edge Betweenness algorithm and 26 016 (79%) in the same cluster by the Fast Greedy method. According to the Fast Greedy method, during the study period, 95% of patients received treatment in only one network. According to the opinion of the actors in the field, the Fast Greedy algorithm seemed to be the best method in the context of dialysis activity modelling. The Edge Betweenness classification was not retained because it seemed too sensitive to the volume of links between dialysis units.

Women's Access to Kidney Transplantation in France: A Mixed Methods Research Protocol.

Kidney transplantation is the best renal replacement therapy (medically and economically) for eligible patients with end-stage kidney disease. Studies in some French regions and in other countries suggest a lower access to the kidney transplant waiting listing and also to kidney transplantation, once waitlisted, for women. Using a mixed methods approach, this study aims to precisely understand these potential sex disparities and their causes. The quantitative study will explore the geographic disparities, compare the determinants of access to the waiting list and to kidney transplantation, and compare the reasons and duration of inactive status on the waiting list in women and men at different scales (national, regional, departmental, and census-block). The qualitative study will allow describing and comparing women's and men's views about their disease and transplantation, as well as nephrologists' practices relative to the French national guidelines on waiting list registration. This type of study is important in the current societal context in which the reduction of sex/gender-based inequalities is a major social expectation.

The new French kidney allocation system for donations after brain death: Rationale, implementation, and evaluation.

In recent decades, the allocation policies of many countries have moved from center-based to patient-based approaches. The new French kidney allocation system (KAS) of donations after brain death for adult recipients, implemented in 2015, was principally designed to introduce a unified allocation score (UAS) to be applied locally for one kidney and nationally for the other and to replace regional borders by a new geographical model. The new KAS balances dialysis duration and waiting time to compensate for listing delays and provides more effective longevity matching between donors and recipients with better HLA and age matching. We report these changes, with their rationale and main results. Results show improved HLA matching for young recipients and more rapid access to transplant for older recipients. Young recipients also had better access to transplantation. Transplant access decreased for recipients aged 60-69 and required tuning of KAS parameters. In conclusion, our results strongly indicate that national or adequately broad geographic allocation areas, combined with multiplicative interactions between allocation criteria, permit multivariate optimization of organ allocation and thus improve national kidney sharing and balance HLA matching and age matching, at the price of longer cold ischemic times and more logistical constraints than with local allocation.

France's New Lung Transplant Allocation System: Combining Equity With Proximity by Optimizing Geographic Boundaries Through the Supply/Demand Ratio.

A new lung allocation system was introduced in France in September 2020. It aimed to reduce geographic disparities in lung allocation while maintaining proximity. In the previous two-tiered priority-based system, grafts not allocated through national high-urgency status were offered to transplant centres according to geographic criteria. Between 2013 and 2018, significant geographic disparities in transplant allocation were observed across transplant centres with a mean number of grafts offered per candidate ranging from 1.4 to 5.2. The new system redistricted the local allocation units according to supply/demand ratio, removed regional sharing and increased national sharing. The supply/demand ratio was defined as the ratio of lungs recovered within the local allocation unit to transplants performed in the centre. A driving time between the procurement and transplant centres of less than 2 h was retained for proximity. Using a brute-force algorithm, we designed new local allocation units that gave a supply/demand ratio of 0.5 for all the transplant centres. Under the new system, standard-deviation of graft offers per candidate decreased from 0.9 to 0.5 (p = 0.08) whereas the mean distance from procurement to transplant centre did not change. These preliminary results show that a supply/demand ratio-based allocation system can achieve equity while maintaining proximity.

Mass spectrometry-based draft of the mouse proteome.

The laboratory mouse ranks among the most important experimental systems for biomedical research and molecular reference maps of such models are essential informational tools. Here, we present a quantitative draft of the mouse proteome and phosphoproteome constructed from 41 healthy tissues and several lines of analyses exemplify which insights can be gleaned from the data. For instance, tissue- and cell-type resolved profiles provide protein evidence for the expression of 17,000 genes, thousands of isoforms and 50,000 phosphorylation sites in vivo. Proteogenomic comparison of mouse, human and Arabidopsis reveal common and distinct mechanisms of gene expression regulation and, despite many similarities, numerous differentially abundant orthologs that likely serve species-specific functions. We leverage the mouse proteome by integrating phenotypic drug (n > 400) and radiation response data with the proteomes of 66 pancreatic ductal adenocarcinoma (PDAC) cell lines to reveal molecular markers for sensitivity and resistance. This unique atlas complements other molecular resources for the mouse and can be explored online via ProteomicsDB and PACiFIC.

Prosit-TMT: Deep Learning Boosts Identification of TMT-Labeled Peptides.

The prediction of fragment ion intensities and retention time of peptides has gained significant attention over the past few years. However, the progress shown in the accurate prediction of such properties focused primarily on unlabeled peptides. Tandem mass tags (TMT) are chemical peptide labels that are coupled to free amine groups usually after protein digestion to enable the multiplexed analysis of multiple samples in bottom-up mass spectrometry. It is a standard workflow in proteomics ranging from single-cell to high-throughput proteomics. Particularly for TMT, increasing the number of confidently identified spectra is highly desirable as it provides identification and quantification information with every spectrum. Here, we report on the generation of an extensive resource of synthetic TMT-labeled peptides as part of the ProteomeTools project and present the extension of the deep learning model Prosit to accurately predict the retention time and fragment ion intensities of TMT-labeled peptides with high accuracy. Prosit-TMT supports CID and HCD fragmentation and ion trap and Orbitrap mass analyzers in a single model. Reanalysis of published TMT data sets show that this single model extracts substantial additional information. Applying Prosit-TMT, we discovered that the expression of many proteins in human breast milk follows a distinct daily cycle which may prime the newborn for nutritional or environmental cues.

Social Deprivation Is Associated With Lower Access to Pre-emptive Kidney Transplantation and More Urgent-Start Dialysis in the Pediatric Population.

Introduction: Socioeconomic status (SES) is recognized as an important determinant of kidney health. We aimed to evaluate the association of social deprivation with different indicators at kidney replacement therapy (KRT) initiation in the French pediatric metropolitan population. Methods: All patients with end-stage kidney disease (ESKD) who started KRT before 20 years old in France between 2002 and 2015 were included. We investigated different indicators at KRT initiation, which are as follows: KRT modality (dialysis vs. pre-emptive transplantation), late referral to a nephrologist, and dialysis modality (hemodialysis [HD] vs. peritoneal dialysis [PD], urgent vs. planned start of dialysis, use of catheter vs. use of fistula for HD vascular access). An ecological index (European Deprivation Index [EDI]) was used as a proxy for social deprivation. Results: A total of 1115 patients were included (males 59%, median age at dialysis 14.4 years, glomerular/vascular diseases 36.8%). The most deprived group represented 38.7% of the patients, suggesting pediatric patients with ESKD come from a more socially deprived background. The most deprived group was more likely to initiate KRT with dialysis versus kidney transplantation. Among patients on HD, the odds of starting treatment in emergency with a catheter was >2-fold higher for the most deprived compared with the least deprived children (adjusted odds ratio [aOR] 2.35, 95% CI 1.16-4.78). Conclusion: Children from the most deprived area have lower access to pre-emptive transplantation, have lower access to PD, tend to be late referred to a nephrologist, and have more urgent initiation of HD with a catheter.

SIMSI-Transfer: Software-Assisted Reduction of Missing Values in Phosphoproteomic and Proteomic Isobaric Labeling Data Using Tandem Mass Spectrum Clustering.

Isobaric stable isotope labeling techniques such as tandem mass tags (TMTs) have become popular in proteomics because they enable the relative quantification of proteins with high precision from up to 18 samples in a single experiment. While missing values in peptide quantification are rare in a single TMT experiment, they rapidly increase when combining multiple TMT experiments. As the field moves toward analyzing ever higher numbers of samples, tools that reduce missing values also become more important for analyzing TMT datasets. To this end, we developed SIMSI-Transfer (Similarity-based Isobaric Mass Spectra 2 [MS2] Identification Transfer), a software tool that extends our previously developed software MaRaCluster (© Matthew The) by clustering similar tandem MS2 from multiple TMT experiments. SIMSI-Transfer is based on the assumption that similarity-clustered MS2 spectra represent the same peptide. Therefore, peptide identifications made by database searching in one TMT batch can be transferred to another TMT batch in which the same peptide was fragmented but not identified. To assess the validity of this approach, we tested SIMSI-Transfer on masked search engine identification results and recovered >80% of the masked identifications while controlling errors in the transfer procedure to below 1% false discovery rate. Applying SIMSI-Transfer to six published full proteome and phosphoproteome datasets from the Clinical Proteomic Tumor Analysis Consortium led to an increase of 26 to 45% of identified MS2 spectra with TMT quantifications. This significantly decreased the number of missing values across batches and, in turn, increased the number of peptides and proteins identified in all TMT batches by 43 to 56% and 13 to 16%, respectively.

Dialysis-network variability in home dialysis use not explained by patient characteristics: a national registry-based cohort study in France.

BACKGROUND: Although associated with better quality of life and potential economic advantages, home dialysis use varies greatly internationally and appears to be underused in many countries. This study aimed to estimate the dialysis-network variability in home dialysis use and identify factors associated with (i) the uptake in home dialysis, (ii) the proportion of time spent on home dialysis and (iii) home dialysis survival (patient and technique). METHODS: All adults ≥18 years old who had dialysis treatment during 2017-2019 in mainland France were included. Mixed-effects regression models were built to explore factors including patient or residence characteristics and dialysis network associated with variation in home dialysis use. RESULTS: During 2017-2019, 7728/78 757 (9.8%) patients underwent dialysis at least once at home for a total of 120 594/1 508 000 (8%) months. The heterogeneity at the dialysis-network level and to a lesser extent the regional level regarding home dialysis uptake or total time spent was marginally explained by patient characteristics or residence and dialysis-network factors. Between-network heterogeneity was less for patient and technique survival. These results were similar when the analysis was restricted to home peritoneal dialysis or home hemodialysis. CONCLUSIONS: Variability between networks in the use of home dialysis was not fully explained by non-modifiable patient and residence characteristics. Our results suggest that to increase home dialysis use in France, one should focus on home dialysis uptake rather than survival. Financial incentives and a quality improvement programme should be implemented at the dialysis-network level to increase home dialysis use.

Colour Calibration of a Head Mounted Display for Colour Vision Research Using Virtual Reality.

Virtual reality (VR) technology offers vision researchers the opportunity to conduct immersive studies in simulated real-world scenes. However, an accurate colour calibration of the VR head mounted display (HMD), both in terms of luminance and chromaticity, is required to precisely control the presented stimuli. Such a calibration presents significant new challenges, for example, due to the large field of view of the HMD, or the software implementation used for scene rendering, which might alter the colour appearance of objects. Here, we propose a framework for calibrating an HMD using an imaging colorimeter, the I29 (Radiant Vision Systems, Redmond, WA, USA). We examine two scenarios, both with and without using a rendering software for visualisation. In addition, we present a colour constancy experiment design for VR through a gaming engine software, Unreal Engine 4. The colours of the objects of study are chosen according to the previously defined calibration. Results show a high-colour constancy performance among participants, in agreement with recent studies performed on real-world scenarios. Our studies show that our methodology allows us to control and measure the colours presented in the HMD, effectively enabling the use of VR technology for colour vision research.

Evaluation of Disposable Trap Column nanoLC-FAIMS-MS/MS for the Proteomic Analysis of FFPE Tissue.

Proteomic biomarker discovery using formalin-fixed paraffin-embedded (FFPE) tissue requires robust workflows to support the analysis of large cohorts of patient samples. It also requires finding a reasonable balance between achieving a high proteomic depth and limiting the overall analysis time. To this end, we evaluated the merits of online coupling of single-use disposable trap column nanoflow liquid chromatography, high-field asymmetric-waveform ion-mobility spectrometry (FAIMS), and tandem mass spectrometry (nLC-FAIMS-MS/MS). The data show that ≤600 ng of peptide digest should be loaded onto the chromatographic part of the system. Careful characterization of the FAIMS settings enabled the choice of optimal combinations of compensation voltages (CVs) as a function of the employed LC gradient time. We found nLC-FAIMS-MS/MS to be on par with StageTip-based off-line basic pH reversed-phase fractionation in terms of proteomic depth and reproducibility of protein quantification (coefficient of variation ≤15% for 90% of all proteins) but requiring 50% less sample and substantially reducing sample handling. Using FFPE materials from the lymph node, lung, and prostate tissue as examples, we show that nLC-FAIMS-MS/MS can identify 5000-6000 proteins from the respective tissue within a total of 3 h of analysis time.