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.

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.

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.

Defining the carrier proteome limit for single-cell proteomics.

Single-cell proteomics by mass spectrometry (SCoPE-MS) is a recently introduced method to quantify multiplexed single-cell proteomes. While this technique has generated great excitement, the underlying technologies (isobaric labeling and mass spectrometry (MS)) have technical limitations with the potential to affect data quality and biological interpretation. These limitations are particularly relevant when a carrier proteome, a sample added at 25-500× the amount of a single-cell proteome, is used to enable peptide identifications. Here we perform controlled experiments with increasing carrier proteome amounts and evaluate quantitative accuracy, as it relates to mass analyzer dynamic range, multiplexing level and number of ions sampled. We demonstrate that an increase in carrier proteome level requires a concomitant increase in the number of ions sampled to maintain quantitative accuracy. Lastly, we introduce Single-Cell Proteomics Companion (SCPCompanion), a software tool that enables rapid evaluation of single-cell proteomic data and recommends instrument and data analysis parameters for improved data quality.

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.

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.

Resident microbial communities inhibit growth and antibiotic-resistance evolution of Escherichia coli in human gut microbiome samples.

Countering the rise of antibiotic-resistant pathogens requires improved understanding of how resistance emerges and spreads in individual species, which are often embedded in complex microbial communities such as the human gut microbiome. Interactions with other microorganisms in such communities might suppress growth and resistance evolution of individual species (e.g., via resource competition) but could also potentially accelerate resistance evolution via horizontal transfer of resistance genes. It remains unclear how these different effects balance out, partly because it is difficult to observe them directly. Here, we used a gut microcosm approach to quantify the effect of three human gut microbiome communities on growth and resistance evolution of a focal strain of Escherichia coli. We found the resident microbial communities not only suppressed growth and colonisation by focal E. coli but also prevented it from evolving antibiotic resistance upon exposure to a beta-lactam antibiotic. With samples from all three human donors, our focal E. coli strain only evolved antibiotic resistance in the absence of the resident microbial community, even though we found resistance genes, including a highly effective resistance plasmid, in resident microbial communities. We identified physical constraints on plasmid transfer that can explain why our focal strain failed to acquire some of these beneficial resistance genes, and we found some chromosomal resistance mutations were only beneficial in the absence of the resident microbiota. This suggests, depending on in situ gene transfer dynamics, interactions with resident microbiota can inhibit antibiotic-resistance evolution of individual species.

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.

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.

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.

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.

Data, Reagents, Assays and Merits of Proteomics for SARS-CoV-2 Research and Testing.

As the COVID-19 pandemic continues to spread, thousands of scientists around the globe have changed research direction to understand better how the virus works and to find out how it may be tackled. The number of manuscripts on preprint servers is soaring and peer-reviewed publications using MS-based proteomics are beginning to emerge. To facilitate proteomic research on SARS-CoV-2, the virus that causes COVID-19, this report presents deep-scale proteomes (10,000 proteins; >130,000 peptides) of common cell line models, notably Vero E6, Calu-3, Caco-2, and ACE2-A549 that characterize their protein expression profiles including viral entry factors such as ACE2 or TMPRSS2. Using the 9 kDa protein SRP9 and the breast cancer oncogene BRCA1 as examples, we show how the proteome expression data can be used to refine the annotation of protein-coding regions of the African green monkey and the Vero cell line genomes. Monitoring changes of the proteome on viral infection revealed widespread expression changes including transcriptional regulators, protease inhibitors, and proteins involved in innate immunity. Based on a library of 98 stable-isotope labeled synthetic peptides representing 11 SARS-CoV-2 proteins, we developed PRM (parallel reaction monitoring) assays for nano-flow and micro-flow LC-MS/MS. We assessed the merits of these PRM assays using supernatants of virus-infected Vero E6 cells and challenged the assays by analyzing two diagnostic cohorts of 24 (+30) SARS-CoV-2 positive and 28 (+9) negative cases. In light of the results obtained and including recent publications or manuscripts on preprint servers, we critically discuss the merits of MS-based proteomics for SARS-CoV-2 research and testing.

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.

Stress causes interspecific facilitation within a compost community.

Ecological theory predicts interactions between species to become more positive under abiotic stress, while competition should prevail in more benign environments. However, experimental tests of this stress gradient hypothesis in natural microbial communities are lacking. We test this hypothesis by measuring interactions between 10 different members of a bacterial community inhabiting potting compost in the presence or absence of toxic copper stress. We found that copper stress caused significant net changes in species interaction signs, shifting the net balance towards more positive interactions. This pattern was at least in part driven by copper-sensitive isolates - that produced relatively small amounts of metal-detoxifying siderophores - benefitting from the presence of other species that produce extracellular detoxifying agents. As well as providing support for the stress gradient hypothesis, our results highlight the importance of community-wide public goods in shaping microbial community composition.

Removing administrative boundaries using a gravity model for a national liver allocation system.

Geographic disparities emerged as an increasing issue in organ allocation policies. Because of the sequential and discrete geographical models used for allocation scores, artificial regional boundaries may impede the access of candidates with the greatest medical urgency to vital organs. This article describes a continuous geographical allocation model that provides accurate organ access by introducing a multiplicative interaction between the patient's condition and the distance to the graft by using a gravity model. Patients with the most urgent need will thus have access to organs from farther away, while those in less urgent need may only have access to organs geographically closer. Compared to the previous French liver allocation scheme, the gravity model precluded transplantations for candidates with a Model for End-Stage Liver Disease (MELD) ≤ 14 for decompensated cirrhosis from 10.3% to 0.6%. Death and delisting while on the waiting list at 1 year also decreased from 30.1% to 22.4% for MELD ≥ 35. Waiting list (cumulative hazard ratio (CHR)  0.84 after adjustment) and posttransplant survival improved significantly (hazard ratio = 0.83 after adjustment). This new liver allocation system provides more equitable access to liver transplants and an efficient and safe alternative to administrative boundaries for geographical models in organ allocation.

Effect of age and care organization on sources of variation in kidney transplant waiting list registration.

Despite national guidelines, medical practices and kidney transplant waiting list registration policies may differ from one dialysis/transplant unit to another. Benefit risk assessment variations, especially for elderly patients, have also been described. The aim of this study was to identify sources of variation in early kidney transplant waiting list registration in France. Among 16 842 incident patients during the period 2016-2017, 4386 were registered on the kidney transplant waiting list at the start of, or during the first year after starting, dialysis (26%). We developed various log-linear mixed effect regression models on three levels: patients, dialysis networks, and transplant centers. Variability was expressed as variance from the random intercepts (± standard error). Although patient characteristics have an important impact on the likelihood of registration, the overall magnitude of variability in registration was low and shared by dialysis networks and transplant centers. Between-transplant center variability (0.23 ± 0.08) was 1.8 higher than between-dialysis network variability (0.13 ± 0.004). Older age was associated with a lower probability of registration and greater variability between networks (0.04, 0.20, & 0.93 in the 18-64, 65-74, and 75-84 age groups). Targeted interventions should focus on elderly patients and/or certain regions with greater variability in waiting list access.

Robust Microflow LC-MS/MS for Proteome Analysis: 38 000 Runs and Counting.

Microflow liquid chromatography tandem mass spectrometry (µLC-MS/MS) is becoming a viable alternative to nanoflow LC-MS/MS for the analysis of proteomes. We have recently demonstrated the potential of such a system operating with a 1 mm i.d. × 150 mm column and at a flow rate of 50 µL/min for high-throughput applications. On the basis of the analysis of ∼38 000 samples measured on two instruments over the past two years, we now show that the approach is extremely robust. Up to 1500 analyses were performed within one month, and >14 000 samples could be analyzed on a single column without loss of chromatographic performance. Samples included proteomes of cell lines, tissues, and human body fluids, which were analyzed with or without prior peptide fractionation or stable isotope labeling. We show that the µLC-MS/MS system is capable of measuring 2600 proteins from undepleted human plasma and ∼5000 proteins from crude human urine in 1 day, demonstrating its potential for in-depth as well as high-throughput clinical application.

Low incidence of SARS-CoV-2, risk factors of mortality and the course of illness in the French national cohort of dialysis patients.

The aim of this study was to estimate the incidence of COVID-19 disease in the French national population of dialysis patients, their course of illness and to identify the risk factors associated with mortality. Our study included all patients on dialysis recorded in the French REIN Registry in April 2020. Clinical characteristics at last follow-up and the evolution of COVID-19 illness severity over time were recorded for diagnosed cases (either suspicious clinical symptoms, characteristic signs on the chest scan or a positive reverse transcription polymerase chain reaction) for SARS-CoV-2. A total of 1,621 infected patients were reported on the REIN registry from March 16th, 2020 to May 4th, 2020. Of these, 344 died. The prevalence of COVID-19 patients varied from less than 1% to 10% between regions. The probability of being a case was higher in males, patients with diabetes, those in need of assistance for transfer or treated at a self-care unit. Dialysis at home was associated with a lower probability of being infected as was being a smoker, a former smoker, having an active malignancy, or peripheral vascular disease. Mortality in diagnosed cases (21%) was associated with the same causes as in the general population. Higher age, hypoalbuminemia and the presence of an ischemic heart disease were statistically independently associated with a higher risk of death. Being treated at a selfcare unit was associated with a lower risk. Thus, our study showed a relatively low frequency of COVID-19 among dialysis patients contrary to what might have been assumed.

IMPact of the COVID-19 epidemic on the moRTAlity of kidney transplant recipients and candidates in a French Nationwide registry sTudy (IMPORTANT).

End stage kidney disease increase the risk of COVID-19 related death but how the kidney replacement strategy should be adapted during the pandemic is unknown. Chronic hemodialysis makes social distancing difficult to achieve. Alternatively, kidney transplantation could increase the severity of COVID-19 due to therapeutic immunosuppression and contribute to saturation of intensive care units. For these reasons, kidney transplantation was suspended in France during the first epidemic wave. Here, we retrospectively evaluated this strategy by comparing the overall and COVID-19 related mortality in kidney transplant recipients and candidates over the last three years. Cross-interrogation of two national registries for the period 1 March and 1 June 2020, identified 275 deaths among the 42812 kidney transplant recipients and 144 deaths among the 16210 candidates. This represents an excess of deaths for both populations, as compared with the same period the two previous years (mean of two previous years: 253 in recipients and 112 in candidates). This difference was integrally explained by COVID-19, which accounted for 44% (122) and 42% (60) of the deaths in recipients and candidates, respectively. Taking into account the size of the two populations and the geographical heterogeneity of virus circulation, we found that the excess of risk of death due to COVID-19 was similar for recipients and candidates in high viral risk area but four-fold higher for candidates in the low viral risk area. Thus, in case of a second epidemic wave, kidney transplantation should be suspended in high viral risk areas but maintained outside those areas, both to reduce the excess of deaths of candidates and avoid wasting precious resources.

New French heart allocation system: Comparison with Eurotransplant and US allocation systems.

Graft allocation rules for heart transplantation are necessary because of the shortage of heart donors, resulting in high waitlist mortality. The Agence de la biomédecine is the agency in charge of the organ allocation system in France. Assessment of the 2004 urgency-based allocation system identified challenging limitations. A new system based on a score ranking all candidates was implemented in January 2018. In the revised system, medical urgency is defined according to candidate characteristics rather than the treatment modalities, and an interplay between urgency, donor-recipient matching, and geographic sharing was introduced. In this article, we describe in detail the new allocation system and compare these allocation rules to Eurotransplant and US allocation policies.