MALDI-MS in first-line screening of newborns for sickle cell disease: results from a prospective study in comparison to HPLC.

OBJECTIVES: Newborn screening (NBS) for sickle cell disease (SCD) requires a robust, high-throughput method to detect hemoglobin S (HbS). Screening for SCD is performed by qualitative methods, such as isoelectric focusing (IEF), and both qualitative and quantitative methods such as high performance liquid chromatography (HPLC), capillary electrophoresis (CE), and tandem mass spectrometry (MS/MS). All these methods detect HbS, as well as low-level or absent HbA, and also other variants of hemoglobin. HPLC is considered as a reference method for NBS, because of its high sensitivity and specificity in detecting HbS. NeoSickle®, a fully automated matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) platform, combined with automated sample processing, a laboratory information management system and NeoSickle® software for automatic data interpretation, has increased the throughput of SCD testing. The purpose of this study was to compare the performances of NeoSickle® and HPLC. METHODS: A prospective study was conducted including 9,571 samples from the NBS program to compare MALDI-MS using NeoSickle® with an HPLC method. Correlation between the two methods was studied. For the MALDI-MS method, sensitivity, specificity, NPV, and PPV were calculated. RESULTS: We found over 99.4 % correlation between the HPLC and MALDI-MS results. NeoSickle® showed 100 % of sensitivity and specificity in detecting SCD syndrome, leading to positive and negative predictive values of 100 %. CONCLUSIONS: NeoSickle® is adapted to NBS for SCD, and can be used in first-line high-throughput screening to detect HbS, and beta-thalassemia major warning. When HbS is detected, second-line use of another specific method as HPLC is necessary.

Peroxisomal ATP-binding cassette transporters form mainly tetramers.

ABCD1 and its homolog ABCD2 are peroxisomal ATP-binding cassette (ABC) half-transporters of fatty acyl-CoAs with both distinct and overlapping substrate specificities. Although it is established that ABC half-transporters have at least to dimerize to generate a functional unit, functional equivalents of tetramers (i.e. dimers of full-length transporters) have also been reported. However, oligomerization of peroxisomal ABCD transporters is incompletely understood but is of potential significance because more complex oligomerization might lead to differences in substrate specificity. In this work, we have characterized the quaternary structure of the ABCD1 and ABCD2 proteins in the peroxisomal membrane. Using various biochemical approaches, we clearly demonstrate that both transporters exist as both homo- and heterotetramers, with a predominance of homotetramers. In addition to tetramers, some larger molecular ABCD assemblies were also found but represented only a minor fraction. By using quantitative co-immunoprecipitation assays coupled with tandem mass spectrometry, we identified potential binding partners of ABCD2 involved in polyunsaturated fatty-acid metabolism. Interestingly, we identified calcium ATPases as ABCD2-binding partners, suggesting a role of ABCD2 in calcium signaling. In conclusion, we have shown here that ABCD1 and its homolog ABCD2 exist mainly as homotetramers in the peroxisomal membrane.

Newborn screening for sickle cell disease in Europe: recommendations from a Pan-European Consensus Conference.

Sickle Cell Disease (SCD) is an increasing global health problem and presents significant challenges to European health care systems. Newborn screening (NBS) for SCD enables early initiation of preventive measures and has contributed to a reduction in childhood mortality from SCD. Policies and methodologies for NBS vary in different countries, and this might have consequences for the quality of care and clinical outcomes for SCD across Europe. A two-day Pan-European consensus conference was held in Berlin in April 2017 in order to appraise the current status of NBS for SCD and to develop consensus-based statements on indications and methodology for NBS for SCD in Europe. More than 50 SCD experts from 13 European countries participated in the conference. This paper aims to summarise the discussions and present consensus recommendations which can be used to support the development of NBS programmes in European countries where they do not yet exist, and to review existing programmes.

Variance component analysis to assess protein quantification in biomarker discovery. Application to MALDI-TOF mass spectrometry.

Controlling the technological variability on an analytical chain is critical for biomarker discovery. The sources of technological variability should be modeled, which calls for specific experimental design, signal processing, and statistical analysis. Furthermore, with unbalanced data, the various components of variability cannot be estimated with the sequential or adjusted sums of squares of usual software programs. We propose a novel approach to variance component analysis with application to the matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) technology and use this approach for protein quantification by a classical signal processing algorithm and two more recent ones (BHI-PRO 1 and 2). Given the high technological variability, the quantification failed to restitute the known quantities of five out of nine proteins present in a controlled solution. There was a linear relationship between protein quantities and peak intensities for four out of nine peaks with all algorithms. The biological component of the variance was higher with BHI-PRO than with the classical algorithm (80-95% with BHI-PRO 1, 79-95% with BHI-PRO 2 vs. 56-90%); thus, BHI-PRO were more efficient in protein quantification. The technological component of the variance was higher with the classical algorithm than with BHI-PRO (6-25% vs. 2.5-9.6% with BHI-PRO 1 and 3.5-11.9% with BHI-PRO 2). The chemical component was also higher with the classical algorithm (3.6-18.7% vs. < 3.5%). Thus, BHI-PRO were better in removing noise from signal when the expected peaks are detected. Overall, either BHI-PRO algorithm may reduce the technological variance from 25 to 10% and thus improve protein quantification and biomarker validation.

Toward the Identification of Two Glycoproteins Involved in the Stomatal Deregulation of Downy Mildew-Infected Grapevine Leaves.

Stomata remain abnormally opened and unresponsive to abscisic acid in grapevine leaves infected by downy mildew. This deregulation occurs from 3 days postinoculation and increases concomitantly with leaf colonization by the pathogen. Using epidermal peels, we demonstrated that the active compound involved in this deregulation is located in the apoplast. Biochemical assays showed that the active compound present in the apoplastic fluids isolated from Plasmopara viticola-infected grapevine leaves (IAF) is a CysCys bridge-independent, thermostable and glycosylated protein. Fractionation guided assays based on chromatography coupled to stomatal response and proteomic analysis allowed the identification of both plant and pathogen proteins in the active fraction obtained from IAF. Further in silico analysis and discriminant filtrations based on the comparison between predictions and experimental indications lead to the identification of two Vitis vinifera proteins as candidates for the observed stomatal deregulation.

Comparison of classification methods that combine clinical data and high-dimensional mass spectrometry data.

BACKGROUND: The identification of new diagnostic or prognostic biomarkers is one of the main aims of clinical cancer research. Technologies like mass spectrometry are commonly being used in proteomic research. Mass spectrometry signals show the proteomic profiles of the individuals under study at a given time. These profiles correspond to the recording of a large number of proteins, much larger than the number of individuals. These variables come in addition to or to complete classical clinical variables. The objective of this study is to evaluate and compare the predictive ability of new and existing models combining mass spectrometry data and classical clinical variables. This study was conducted in the context of binary prediction. RESULTS: To achieve this goal, simulated data as well as a real dataset dedicated to the selection of proteomic markers of steatosis were used to evaluate the methods. The proposed methods meet the challenge of high-dimensional data and the selection of predictive markers by using penalization methods (Ridge, Lasso) and dimension reduction techniques (PLS), as well as a combination of both strategies through sparse PLS in the context of a binary class prediction. The methods were compared in terms of mean classification rate and their ability to select the true predictive values. These comparisons were done on clinical-only models, mass-spectrometry-only models and combined models. CONCLUSIONS: It was shown that models which combine both types of data can be more efficient than models that use only clinical or mass spectrometry data when the sample size of the dataset is large enough.

Symplekin, a polyadenylation factor, prevents MOZ and MLL activity on HOXA9 in hematopoietic cells.

MOZ and MLL encoding a histone acetyltransferase and a histone methyltransferase, respectively, are targets for recurrent chromosomal translocations found in acute myeloblastic or lymphoblastic leukemia. We have previously shown that MOZ and MLL cooperate to activate HOXA9 gene expression in hematopoietic stem/progenitors cells. To dissect the mechanism of action of this complex, we decided to identify new proteins interacting with MOZ. We found that the scaffold protein Symplekin that supports the assembly of polyadenylation machinery was identified by mass spectrometry. Symplekin interacts and co-localizes with both MOZ and MLL in immature hematopoietic cells. Its inhibition leads to a decrease of the HOXA9 protein level but not of Hoxa9 mRNA and to an over-recruitment of MOZ and MLL onto the HOXA9 promoter. Altogether, our results highlight the role of Symplekin in transcription repression involving a regulatory network between MOZ, MLL and Symplekin.

Evaluation of MALDI-TOF mass spectrometry for the identification of medically-important yeasts in the clinical laboratories of Dijon and Lille hospitals.

Conventional identification (CI) of yeasts is based on morphological, biochemical and/or immunological methods. Matrix-assisted laser desorption/ionization - time of flight (MALDI-TOF or MT-MS) mass spectrometry has been proposed as a new method for the identification of microorganisms. This prospective study compared the performance of MT-MS and CI for the identification of yeasts isolated from clinical samples. Sequencing of the internal transcribed spacer (ITS) regions of ribosomal DNA was used as the reference method in the analysis of a total of 1207 yeast isolates. Concordance between MT-MS and CI was observed for 1105 isolates (91.5%), while 74 isolates (6.1%) were misidentified. Molecular identification revealed that 73 of these 74 isolates were identified correctly by MT-MS and CI correctly identified the last one. Concordance between the two techniques was excellent for the medically-important species (98-100%), including the identification of closely-related species (Candida albicans/C. dubliniensis; C. inconspicua/C. norvegensis; C. parapsilosis/C. metapsilosis/C. orthopsilosis). Only 2.3% of isolates belonging to C. famata, C. lambica and C. magnoliae or to Geotrichum spp. and Trichosporon spp. were not identified by MT-MS. This investigation highlights the potential of MT-MS-based yeast identification as a reliable, time and cost-efficient alternative to CI.

Optimization of the preanalytical steps of matrix-assisted laser desorption ionization-time of flight mass spectrometry identification provides a flexible and efficient tool for identification of clinical yeast isolates in medical laboratories.

We report here that modifications of the preanalytical steps of matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) identification of yeasts, with regard to the original protocol provided by the manufacturers, appear to be efficient for the reliable routine identification of clinical yeast isolates in medical laboratories. Indeed, when one colony was sampled instead of five and the protein extraction protocol was modified, the performance of MALDI-TOF MS was superior to that of the API ID 32C method (discrepancies were confirmed by using molecular identification), allowing the correct identification of 94% of the 335 clinical isolates prospectively tested. We then demonstrated that the time for which the primary cultures were preincubated on CHROMagar did not impact the identification of yeasts by MALDI-TOF MS, since 95.1 and 96.2% of the 183 clinical yeast isolates prospectively tested were correctly identified after 48 and 72 h of preincubation, respectively.

Alpha-defensins secreted by dysplastic granulocytes inhibit the differentiation of monocytes in chronic myelomonocytic leukemia.

Chronic myelomonocytic leukemia (CMML) is a clonal hematopoietic disorder that occurs in elderly patients. One of the main diagnostic criteria is the accumulation of heterogeneous monocytes in the peripheral blood. We further explored this cellular heterogeneity and observed that part of the leukemic clone in the peripheral blood was made of immature dysplastic granulocytes with a CD14(-)/CD24(+) phenotype. The proteome profile of these cells is dramatically distinct from that of CD14(+)/CD24(-) monocytes from CMML patients or healthy donors. More specifically, CD14(-)/CD24(+) CMML cells synthesize and secrete large amounts of alpha-defensin 1-3 (HNP1-3). Recombinant HNPs inhibit macrophage colony-stimulating factor (M-CSF)-driven differentiation of human peripheral blood monocytes into macrophages. Using transwell, antibody-mediated depletion, suramin inhibition of purinergic receptors, and competitive experiments with uridine diphosphate (UDP)/uridine triphosphate (UTP), we demonstrate that HNP1-3 secreted by CD14(-)/CD24(+) cells inhibit M-CSF-induced differentiation of CD14(+)/CD24(-) cells at least in part through P2Y6, a receptor involved in macrophage differentiation. Altogether, these observations suggest that a population of immature dysplastic granulocytes contributes to the CMML phenotype through production of alpha-defensins HNP1-3 that suppress the differentiation capabilities of monocytes.

Salivary protein profiles and sensitivity to the bitter taste of caffeine.

The interindividual variation in the sensitivity to bitterness is attributed in part to genetic polymorphism at the taste receptor level, but other factors, such as saliva composition, might be involved. In order to investigate this, 2 groups of subjects (hyposensitive, hypersensitive) were selected from 29 healthy male volunteers based on their detection thresholds for caffeine, and their salivary proteome composition was compared. Abundance of 26 of the 255 spots detected on saliva electrophoretic patterns was significantly different between hypo- and hypersensitive subjects. Saliva of hypersensitive subjects contained higher levels of amylase fragments, immunoglobulins, and serum albumin and/or serum albumin fragments. It also contained lower levels of cystatin SN, an inhibitor of protease. The results suggest that proteolysis occurring within the oral cavity is an important perireceptor factor associated to the sensitivity to the bitter taste of caffeine.

Immuno-MALDI-MS in human plasma and on-chip biomarker characterizations at the femtomole level.

Immuno-SPR-MS is the combination of immuno-sensors in biochip format with mass spectrometry. This association of instrumentation allows the detection and the quantification of proteins of interest by SPR and their molecular characterization by additional MS analysis. However, two major bottlenecks must be overcome for a wide diffusion of the SPR-MS analytical platform: (i) To warrant all the potentialities of MS, an enzymatic digestion step must be developed taking into account the spot formats on the biochip and (ii) the biological relevancy of such an analytical solution requires that biosensing must be performed in complex media. In this study, we developed a procedure for the detection and the characterization at ~1 µg/mL of the LAG3 protein spiked in human plasma. The analytical performances of this new method was established, particularly its specificity (S/N > 9) and sensitivity (100% of LAG3 identification with high significant mascot score >68 at the femtomole level). The collective and automated on-chip MALDI-MS imaging and analysis based on peptidic fragments opens numerous applications in the fields of proteomics and diagnosis.

Multivariate denoising methods combining wavelets and principal component analysis for mass spectrometry data.

The identification of new diagnostic or prognostic biomarkers is one of the main aims of clinical cancer research. In recent years, there has been a growing interest in using mass spectrometry for the detection of such biomarkers. The MS signal resulting from MALDI-TOF measurements is contaminated by different sources of technical variations that can be removed by a prior pre-processing step. In particular, denoising makes it possible to remove the random noise contained in the signal. Wavelet methodology associated with thresholding is usually used for this purpose. In this study, we adapted two multivariate denoising methods that combine wavelets and PCA to MS data. The objective was to obtain better denoising of the data so as to extract the meaningful proteomic biological information from the raw spectra and reach meaningful clinical conclusions. The proposed methods were evaluated and compared with the classical soft thresholding denoising method using both real and simulated data sets. It was shown that taking into account common structures of the signals by adding a dimension reduction step on approximation coefficients through PCA provided more effective denoising when combined with soft thresholding on detail coefficients.

The Reliable, Automatic Classification of Neonates in First-Tier MALDI-MS Screening for Sickle Cell Disease.

Previous research has shown that a MALDI-MS technique can be used to screen for sickle cell disease (SCD), and that a system combining automated sample preparation, MALDI-MS analysis and classification software is a relevant approach for first-line, high-throughput SCD screening. In order to achieve a high-throughput "plug and play" approach while detecting "non-standard" profiles that might prompt the misclassification of a sample, we have incorporated various sets of alerts into the decision support software. These included "biological alert" indicators of a newborn's clinical status (e. g., detecting samples with no or low HbA), and "technical alerts" indicators for the most common non-standard profiles, i.e., those which might otherwise lead to sample misclassification. We evaluated these alerts by applying them to two datasets (produced by different laboratories). Despite the random generation of abnormal spectra by one-off technical faults or due to the nature and quality of the samples, the use of alerts fully secured the process of automatic sample classification. Firstly, cases of ß-thalassemia were detected. Secondly, after a visual check on the tagged profiles and reanalysis of the corresponding biological samples, all the samples were correctly reclassified without prompting further alerts. All of the samples for which the results were not tagged were well classified (i.e., sensitivity and specificity = 1). The alerts were mainly designed for detecting false-negative classifications; all the FAS samples misclassified by the software as FA (a false negative) were marked with an alert. The implementation of alerts in the NeoScreening® Laboratory Information Management System's decision support software opens up perspectives for the safe, reliable, automated classification of samples, with a visual check solely on abnormal results or samples. It should now be possible to evaluate the combination of the NeoSickle® analytical solution and the NeoScreening® Laboratory Information Management System in a real-life, prospective study of first-line SCD screening.

A Multicentre Pilot Study of a Two-Tier Newborn Sickle Cell Disease Screening Procedure with a First Tier Based on a Fully Automated MALDI-TOF MS Platform.

The reference methods used for sickle cell disease (SCD) screening usually include two analytical steps: a first tier for differentiating haemoglobin S (HbS) heterozygotes, HbS homozygotes and ß-thalassemia from other samples, and a confirmatory second tier. Here, we evaluated a first-tier approach based on a fully automated matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) platform with automated sample processing, a laboratory information management system and NeoSickle® software for automatic data interpretation. A total of 6701 samples (with high proportions of phenotypes homozygous (FS) or heterozygous (FAS) for the inherited genes for sickle haemoglobin and samples from premature newborns) were screened. The NeoSickle® software correctly classified 98.8% of the samples. This specific blood sample collection was enriched in qualified difficult samples (premature newborns, FAS samples, late and very late samples, etc.). In this study, the sensitivity of FS sample detection was found to be 100% on the Lille MS facility and 99% on the Dijon MS facility, and the specificity of FS sample detection was found to be 100% on both MS facilities. The MALDI-MS platform appears to be a robust solution for first-tier use to detect the HbS variant: it is reproducible and sensitive, it has the power to analyze 600-1000 samples per day and it can reduce the unit cost of testing thanks to maximal automation, minimal intervention by the medical team and good overall practicability. The MALDI-MS approach meets today's criteria for the large-scale, cost-effective screening of newborns, children and adults.

S-Nitrosylation of cIAP1 Switches Cancer Cell Fate from TNFα/TNFR1-Mediated Cell Survival to Cell Death.

TNFα is a prominent proinflammatory cytokine and a critical mediator for the development of many types of cancer such as breast, colon, prostate, cervical, skin, liver, and chronic lymphocytic leukemia. Binding of TNFα to TNFR1 can lead to divergent signaling pathways promoting predominantly NF-κB activation but also cell death. We report here that the nitric oxide (NO) donor glyceryl trinitrate (GTN) converts TNFα, generated from immune cells or cancer cells stimulated by chemotherapy, into a prodeath mediator in colon and mammary cancer cells. GTN-mediated S-nitrosylation of cIAP1 on cysteines 571 and 574 inhibited its E3 ubiquitin ligase activity, which in turn reduced Lys63-linked ubiquitination of RIP1 and initiated assembly of a death complex. These findings provide insights into how NO can harness advantageous aspects of inflammation in cancer and provide new therapeutic strategies.Significance: Combination of an NO donor with chemotherapeutic drug-induced TNFα represents a potentially valuable anticancer strategy. Cancer Res; 78(8); 1948-57. ©2018 AACR.

[Towards a standardization of the tools for the studies of clinical proteomics]. / Vers une standardisation des outils pour les études de protéomique clinique.

Proteins identified in biological fluids of cancer patients could be helpful for both diagnosis and prognosis. However, clinical proteomics based on analysis of protein profiles in biological fluids has demonstrated various flaws, most of them related to the difficulties met in reproducibility. These difficulties could be partly overcome by accurate standardisation of pre-analytical and analytical steps of these studies. The size of the patient cohort is one of the parameters that determine the powerfulness of the study. Recruitment of a cohort with a sufficient size often implies multicentric studies in which analysis of the reproducibility between centres and standardisation of pre-analytical and analytical steps are essential. Such a standardisation requires the use of calibrated samples as common references.

Bayesian inference for biomarker discovery in proteomics: an analytic solution.

This paper addresses the question of biomarker discovery in proteomics. Given clinical data regarding a list of proteins for a set of individuals, the tackled problem is to extract a short subset of proteins the concentrations of which are an indicator of the biological status (healthy or pathological). In this paper, it is formulated as a specific instance of variable selection. The originality is that the proteins are not investigated one after the other but the best partition between discriminant and non-discriminant proteins is directly sought. In this way, correlations between the proteins are intrinsically taken into account in the decision. The developed strategy is derived in a Bayesian setting, and the decision is optimal in the sense that it minimizes a global mean error. It is finally based on the posterior probabilities of the partitions. The main difficulty is to calculate these probabilities since they are based on the so-called evidence that require marginalization of all the unknown model parameters. Two models are presented that relate the status to the protein concentrations, depending whether the latter are biomarkers or not. The first model accounts for biological variabilities by assuming that the concentrations are Gaussian distributed with a mean and a covariance matrix that depend on the status only for the biomarkers. The second one is an extension that also takes into account the technical variabilities that may significantly impact the observed concentrations. The main contributions of the paper are: (1) a new Bayesian formulation of the biomarker selection problem, (2) the closed-form expression of the posterior probabilities in the noiseless case, and (3) a suitable approximated solution in the noisy case. The methods are numerically assessed and compared to the state-of-the-art methods (t test, LASSO, Battacharyya distance, FOHSIC) on synthetic and real data from proteins quantified in human serum by mass spectrometry in selected reaction monitoring mode.

Associations between food consumption patterns and saliva composition: Specificities of eating difficulties children.

Identifying objective markers of diet would be beneficial to research fields such as nutritional epidemiology. As a preliminary study on the validity of using saliva for this purpose, and in order to explore the relationship between saliva and diet, we focused on clearly contrasted groups of children: children with eating difficulties (ED) receiving at least 50% of their energy intake through artificial nutrition vs healthy controls (C). Saliva of ED and C children was analyzed by various methods (targeted biochemical analyses, 2-D electrophoresis coupled to MS, 1H NMR) and their diet was characterized using food frequency questionnaires, considering 148 food items grouped into 13 categories. Complete datasets were obtained for 16 ED and 16 C subjects (median age 4.7y and 5.0y, respectively) and the statistical link between salivary and dietary characteristics was studied by Multiple Factor Analysis (MFA). Overall, ED children showed as expected lower consumption frequency scores and higher food selectivity. The two groups of children differed in "diet/saliva" associations. Some distinctive salivary variables were common to both groups of children. For example, carbonic anhydrase 6 and the consumption frequency of biscuits & sweets and drinks were positively associated with the MFA axis 1 in C children, but oppositely associated in ED children. Specifically for ED children, abundant salivary proteins (cystatins, amylase, amylase fragments) and some metabolites (amino acids, galactose, lactate) correlated with axis 1, together with the consumption frequency of sauces & seasonings, bread & cereal products, ready-to-eat meals, fish, biscuits & sweets, drinks and potatoes. Specifically for C children, several proteins (serum albumin, haptoglobin, Igκ, apolipoprotein A-1, α-1 antitrypsin) correlated with axis 1, together with the consumption frequency of biscuits & sweets, milk & dairy products, drinks, fruit, meat and vegetables. This study demonstrates that the qualitative aspect of diet is linked to saliva composition, and that the associations between dietary consumption and salivary composition differ between groups of subjects with contrasted diets.