Single Biological Sample Research Articles

Proteome Birthdating Reveals Age-Selectivity of Protein Ubiquitination

Within a cell, proteins have distinct and highly variable half-lives. As a result, the molecular ages of proteins can range from seconds to years. How the age of a protein influences its environmental interactions is a largely unexplored area of biology. To investigate the age-selectivity of cellular pathways, we developed a methodology termed “proteome birthdating” that barcodes proteins based on their time of synthesis. We demonstrate that this approach provides accurate measurements of protein turnover kinetics from a single biological sample encoding multiple labeling time-points. As a first application of the birthdated proteome, we investigated the age distribution of the human ubiquitinome. Our results indicate that the vast majority of ubiquitinated proteins in a cell consist of newly synthesized proteins and that these young proteins constitute the bulk of the degradative flux through the proteasome. Rapidly ubiquitinated nascent proteins are enriched in cytosolic subunits of large protein complexes. Conversely, proteins destined for the secretory pathway and vesicular transport have older ubiquitinated populations. Our data also identify a smaller subset of older ubiquitinated cellular proteins that do not appear to be targeted to the proteasome for rapid degradation. Together, our data provide an age census of the human ubiquitinome and establish proteome birthdating as a robust methodology for investigating the protein age-selectivity of diverse cellular pathways.

Multiplexed miRNA and Protein Analysis Using Digital Quantitative PCR in Microwell Arrays.

Proteins and microRNAs (miRNAs) act in tandem within biological pathways to regulate cellular functions, and their misregulation has been correlated to numerous diseases. Because of their interconnectedness, both miRNAs and proteins must be evaluated together to obtain accurate insights into the molecular pathways of pathogenesis. However, few analytical techniques can measure both classes of biomolecules in parallel from a single biological sample. Here, microfluidic digital quantitative PCR (dqPCR) was developed to simultaneously quantify miRNA and protein targets in a multiplexed assay using a single detection chemistry. This streamlined analysis was achieved by integrating base-stacking PCR and immuno-PCR in a microfluidic array platform. Analyses of let-7a (miRNA) and IL-6 (protein) were first optimized separately to identify thermocycling and capture conditions amenable to both biomolecules. Singleplex dqPCR studies exhibited the expected digital signals and quantification cycles for both analytes over a range of concentrations. Multiplexed analyses were then conducted to quantify both let-7a and IL-6 with high sensitivity (LODs ∼ 3 fM) over a broad dynamic range (5-5000 fM) using only standard PCR reagents. This multiplexed dqPCR was then translated to the analysis of HEK293 cell lysate, where endogenous let-7a and IL-6 were measured simultaneously without sample purification or pretreatment. Collectively, these studies demonstrate that the integration of BS-PCR and immuno-PCR achieves a sensitive and streamlined approach for multiplexed analyses of miRNAs and proteins, which will enable researchers to gain better insights into disease pathogenesis in future applications.

A quantifiler™ trio-based HRM screening assay for the accurate prediction of single source versus mixed biological samples.

At present, the forensic DNA workflow is not capable of providing information about the contributor status (single source vs. multiple contributors) of evidentiary samples prior to end-point analysis. This exacerbates the challenges inherent to mixtures and low-template DNA samples. If additional sample information could be provided earlier in the workflow, protocols could be implemented to mitigate these challenges. An integrated Quantiplex®- high resolution melt (HRM) assay was shown to be effective in distinguishing between single source and mixture DNA samples; however, integration of the HRM assay into a more commonly used chemistry would be beneficial to the practitioner community. Thus, the assay was redesigned as an integrated Quantifiler™ Trio-HRM assay, which included the identification of a new DNA-binding dye, an increased reaction volume, and the establishment of new data analysis and standard curve metrics for all targets. This redesigned assay produced quantification values and qualitative values that were comparable to those produced when the same samples were tested using the standard Quantifiler™ Trio chemistry and settings. Further, STR profiles generated with quantification values produced from the integrated Quantifiler™ Trio-HRM assay and standard Quantifiler™ Trio chemistry were complete and fully concordant. Most importantly, the integrated Quantifiler™ Trio-HRM assay was able to accurately predict whether a sample was single source or a mixture 79.2% of the time, demonstrating the potential of this approach. With the incorporation of an expanded training set for prediction modeling, and completion of critical developmental validation studies, this assay could prove useful to the forensic DNA practitioner community.

Global xenobiotic profiling of rat plasma using untargeted metabolomics and background subtraction-based approaches: Method evaluation and comparison.

Global xenobiotic profiling (GXP) is to detect and structurally characterize all xenobiotics in biological samples using mainly liquid chromatography-high resolution mass spectrometry (LC-HRMS) based methods. GXP is highly needed in drug metabolism study, food safety testing, forensic chemical analysis, and exposome research. For detecting known or predictable xenobiotics, targeted LC-HRMS data processing methods based on molecular weights, mass defects and fragmentations of analytes are routinely employed. For profiling unknown xenobiotics, untargeted and LC-HRMS based metabolomics and background subtraction-based approaches are required. This study aimed to evaluate the effectiveness of untargeted metabolomics and the precise and thorough background subtraction (PATBS) in GXP of rat plasma. Rat plasma samples collected from an oral administration of nefazodone (NEF) or Glycyrrhizae Radix et Rhizoma (Gancao, GC) were analyzed by LC-HRMS. NEF metabolites and GC components in rat plasma were thoroughly searched and characterized via processing LC-HRMS datasets using targeted and untargeted methods. PATBS detected 68 NEF metabolites and 63 GC components, while the metabolomic approach (MS-DIAL) found 67 NEF metabolites and 60 GC components in rat plasma. The two methods found 79 NEF metabolites and 80 GC components with 96% and 91% successful rates, respectively. Metabolomics methods are capable of GXP and measuring alternations of endogenous metabolites in a group of biological samples, while PATBS is more suited for sensitive GXP of a single biological sample. A combination of metabolomics and PATBS approaches can generate better results in the untargeted profiling of unknown xenobiotics.

Evaluation of a Novel Skin Emollient Cream on Skin Lipidome and Lipid Organization

Introduction: The stratum corneum (SC) matrix is composed of free fatty acids, cholesterol, and ceramides (CERs), which play a key role in the skin barrier function. Changes in the composition and content of skin lipids will affect the function of the skin barrier. The effect of a glycerol/petrolatum-based emollient (G/P-emollient) cream on the lipid profiles of isolated ex vivo human SC and the SC of a reconstructed human epidermis (RHE) model was measured. Methods: The spatial organization of the cream and the isolated SC intercellular matrix were studied using X-ray diffraction. The inter-bilayer distances in the multi-lamellar lipid structures and lattice type were analyzed using small-angle X-ray scattering and wide-angle X-ray scattering (WAXS), respectively. Lipidomic analysis using shotgun lipidomics was performed on RHE models to quantify CER classes and chain lengths. This technology enables the analysis of thousands of lipids in a single biological sample. Results: The crystallized components of the cream are lipids, which were mainly packed in orthorhombic lattices, as well as hexagonal lattices and were similar to the SC structure. The cream penetrated the SC but did not alter the WAXS profile. It increased the amount of higher carbon number CERs (>42 carbons) and decreased lower carbon number CERs (<42 carbons). All chain length of CERs and acyl-CER classes (CER EOS, EOH, EOP, EOdS) were increased as the total CER classes. A decrease of the CER C34 for hydroxylated and non-hydroxylated CERs was also observed. The cream altered the S and P CER forms (increased the NP/NS and AP/AS ratios), indicating it could reduce the relative feedback mechanism observed in inflammatory pathologies, for example, atopic dermatitis. The cream increased CER NP, which is decreased in dry skin. Conclusion: G/P-emollient cream may be beneficial for skin pathologies by modifying SC lipids, balancing CER levels and ratios, and improving the barrier function. Importantly, the cream structure mimics that of the SC and penetrated the lower SC layers without compromising its lamellar structure.

SUFI: an automated approach to spectral unmixing of fluorescent multiplex images captured in mouse and post-mortem human brain tissues

BackgroundMultispectral fluorescence imaging coupled with linear unmixing is a form of image data collection and analysis that allows for measuring multiple molecular signals in a single biological sample. Multiple fluorescent dyes, each measuring a unique molecule, are simultaneously measured and subsequently “unmixed” to provide a read-out for each molecular signal. This strategy allows for measuring highly multiplexed signals in a single data capture session, such as multiple proteins or RNAs in tissue slices or cultured cells, but can often result in mixed signals and bleed-through problems across dyes. Existing spectral unmixing algorithms are not optimized for challenging biological specimens such as post-mortem human brain tissue, and often require manual intervention to extract spectral signatures. We therefore developed an intuitive, automated, and flexible package called SUFI: spectral unmixing of fluorescent images.ResultsThis package unmixes multispectral fluorescence images by automating the extraction of spectral signatures using vertex component analysis, and then performs one of three unmixing algorithms derived from remote sensing. We evaluate these remote sensing algorithms’ performances on four unique biological datasets and compare the results to unmixing results obtained using ZEN Black software (Zeiss). We lastly integrate our unmixing pipeline into the computational tool dotdotdot, which is used to quantify individual RNA transcripts at single cell resolution in intact tissues and perform differential expression analysis, and thereby provide an end-to-end solution for multispectral fluorescence image analysis and quantification.ConclusionsIn summary, we provide a robust, automated pipeline to assist biologists with improved spectral unmixing of multispectral fluorescence images.

Mass Spectrometry Approaches for Detection and Determination of Prostaglandins from Biological Samples.

Accurate determination of prostaglandins (PGs) from biological samples is critical for understanding their biological functions and interactions during physiological and pathological processes. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) is a highly sensitive, accurate, and high-throughput approach for simultaneous detection of ultra-trace PGs from a single biological sample. Here we describe LC-MS/MS techniques and related sample pretreatment methods including both off-line and on-line SPE for the determination of PGs in biological samples.

"Guess Who's Coming to Dinner": Molecular Tools to Reconstruct multilocus Genetic Profiles from Wild Canid Consumption Remains.

Simple SummaryWolves and European wildcats are two iconic predator species that can live in overlapping ecological contexts and also share their habitats with their domestic free-ranging relatives, increasing the risk of anthropogenic hybridisation and its possible deleterious consequences. By applying a multidisciplinary approach, we morphologically and molecularly analysed the cat remains found in a canid faecal sample collected in a forested area of central Italy. Individual multilocus genotypes of both predator and prey were identified turning out to be, respectively, a wolf showing traces of dog ancestry at autosomal microsatellite loci and a domestic cat.Non-invasive genetic sampling is a practical tool to monitor pivotal ecological parameters and population dynamic patterns of endangered species. It can be particularly suitable when applied to elusive carnivores such as the Apennine wolf (Canis lupus italicus) and the European wildcat (Felis silvestris silvestris), which can live in overlapping ecological contexts and sometimes share their habitats with their domestic free-ranging relatives, increasing the risk of anthropogenic hybridisation. In this case study, we exploited all the ecological and genetic information contained in a single biological canid faecal sample, collected in a forested area of central Italy, to detect any sign of trophic interactions between wolves and European wildcats or their domestic counterparts. Firstly, the faecal finding was morphologically examined, showing the presence of felid hair and claw fragment remains. Subsequently, total genomic DNA contained in the hair and claw samples was extracted and genotyped, through a multiple-tube approach, at canid and felid diagnostic panels of microsatellite loci. Finally, the obtained individual multilocus genotypes were analysed with reference wild and domestic canid and felid populations to assess their correct taxonomic status using Bayesian clustering procedures. Assignment analyses classified the genotype obtained from the endothelial cells present on the hair sample as a wolf with slight signals of dog ancestry, showing a qi = 0.954 (C.I. 0.780–1.000) to the wolf cluster, and the genotype obtained from the claw as a domestic cat, showing a qi = 0.996 (95% C.I. = 0.982–1.000) to the domestic cat cluster. Our results clearly show how a non-invasive multidisciplinary approach allows the cost-effective identification of both prey and predator genetic profiles and their taxonomic status, contributing to the improvement of our knowledge about feeding habits, predatory dynamics, and anthropogenic hybridisation risk in threatened species.

Evaluation of a Novel Commercial Real-Time PCR Assay for the Simultaneous Detection of Cryptosporidium spp., Giardia duodenalis, and Entamoeba histolytica.

ABSTRACTCryptosporidium spp., Giardia duodenalis, and Entamoeba histolytica are the most common diarrhea-causing protozoan species globally. Misdiagnosis is a concern for asymptomatic and chronic infections. Multiplexing, i.e., the detection of more than one parasite in a single test by real-time PCR, allows high diagnostic performance with favorable cost-effectiveness. We conducted a clinical evaluation of the VIASURE Cryptosporidium, Giardia, & E. histolytica real-time PCR assay (CerTest Biotec, San Mateo de Gállego, Spain) against a large panel (n = 358) of well-characterized DNA samples positive for Cryptosporidium spp. (n = 96), G. duodenalis (n = 115), E. histolytica (n = 25), and other parasitic species of the phyla Amoebozoa (n = 11), Apicomplexa (n = 14), Euglenozoa (n = 8), Heterokonta (n = 42), Metamonada (n = 37), Microsporidia (n = 4), and Nematoda (n = 6). DNA samples were obtained from clinical stool specimens or cultured isolates in a national reference center. Estimated sensitivity and specificity were 0.96 and 0.99 for Cryptosporidium spp., 0.94 and 1 for G. duodenalis, and 0.96 and 1 for E. histolytica, respectively. Positive and negative predictive values were calculated as 1 and 0.98 for Cryptosporidium spp., 0.99 and 0.98 for G. duodenalis, and 1 and 0.99 for E. histolytica, respectively. The assay identified six Cryptosporidium species (Cryptosporidium hominis, Cryptosporidium parvum, Cryptosporidium canis, Cryptosporidium felis, Cryptosporidium scrofarum, and Cryptosporidium ryanae) and four G. duodenalis assemblages (A, B, C, and F). The VIASURE assay provides rapid and accurate simultaneous detection and identification of the most commonly occurring species and genetic variants of diarrhea-causing parasitic protozoa in humans.IMPORTANCE Thorough independent assessment of the diagnostic performance of novel diagnostic assays is essential to ascertain their true usefulness and applicability in routine clinical practice. This is particularly true for commercially available kits based on multiplex real-time PCR aimed to detect and differentiate multiple pathogens in a single biological sample. In this study, we conducted a clinical evaluation of the VIASURE Cryptosporidium, Giardia, & E. histolytica real-time PCR assay (CerTest Biotec) for the detection and identification of the diarrhea-causing enteric protozoan parasites Cryptosporidium spp., G. duodenalis, and E. histolytica. A large panel of well-characterized DNA samples from clinical stool specimens or cultured isolates from a reference center was used for this purpose. The VIASURE assay demonstrated good performance for the routine testing of these pathogens in clinical microbiological laboratories.

Concurrent mapping of multiple epigenetic marks and co-occupancy using ACT2-seq

BackgroundGenome-wide profiling of epigenetic marks is a core technology in molecular genetics. Co-occupancy of different epigenetic marks or protein factors at the same genomic locations must often be inferred from multiple independently collected data sets. However, this strategy does not provide direct evidence of co-enrichment in the same cells due to the existence of cellular heterogeneity. To address this issue, we have developed a technique termed ACT2-seq that is capable of concurrently profiling multiple epigenetic marks in a single biological sample. In addition to reducing the numbers of samples required for experiments, ACT2-seq is capable of mapping co-occupancy of epigenetic factors on chromatin. This strategy provides direct evidence of co-enrichment without requiring complex single-molecule, single-cell, or magnetic bead-based approaches.ResultsWe concurrently profiled pairs of two epigenetic marks using ACT2-seq as well as three marks in individual samples. Data obtained using ACT2-seq were found to be reproducible and robust. ACT2-seq was capable of cleanly partitioning concurrently mapped data sets that exhibited distinct enrichment patterns. Using ACT2-seq, we identified distinct relationships between co-occupancy of specific histone modifications and gene expression patterns.ConclusionsWe conclude that ACT2-seq presents an attractive option for epigenomic profiling due to its ease of use, potential for reducing sample and sequencing costs, and ability to simultaneously profile co-occupancy of multiple histone marks and/or chromatin-associated proteins.

Graph of graphs analysis for multiplexed data with application to imaging mass cytometry.

Imaging Mass Cytometry (IMC) combines laser ablation and mass spectrometry to quantitate metal-conjugated primary antibodies incubated in intact tumor tissue slides. This strategy allows spatially-resolved multiplexing of dozens of simultaneous protein targets with 1μm resolution. Each slide is a spatial assay consisting of high-dimensional multivariate observations (m-dimensional feature space) collected at different spatial positions and capturing data from a single biological sample or even representative spots from multiple samples when using tissue microarrays. Often, each of these spatial assays could be characterized by several regions of interest (ROIs). To extract meaningful information from the multi-dimensional observations recorded at different ROIs across different assays, we propose to analyze such datasets using a two-step graph-based approach. We first construct for each ROI a graph representing the interactions between the m covariates and compute an m dimensional vector characterizing the steady state distribution among features. We then use all these m-dimensional vectors to construct a graph between the ROIs from all assays. This second graph is subjected to a nonlinear dimension reduction analysis, retrieving the intrinsic geometric representation of the ROIs. Such a representation provides the foundation for efficient and accurate organization of the different ROIs that correlates with their phenotypes. Theoretically, we show that when the ROIs have a particular bi-modal distribution, the new representation gives rise to a better distinction between the two modalities compared to the maximum a posteriori (MAP) estimator. We applied our method to predict the sensitivity to PD-1 axis blockers treatment of lung cancer subjects based on IMC data, achieving 97.3% average accuracy on two IMC datasets. This serves as empirical evidence that the graph of graphs approach enables us to integrate multiple ROIs and the intra-relationships between the features at each ROI, giving rise to an informative representation that is strongly associated with the phenotypic state of the entire image.

Support of a laboratory-hosted Athlete Biological Passport Management Unit (APMU) to the anti-doping organisations

AbstractThe athlete biological passport (ABP) is an established means for longitudinal monitoring of selected individual biomarkers of an athlete to obtain indirect but potentially long-term indications of the use of substances or methods prohibited in sport. Along the change from population-based reference values to individual profiling, the ABP aims at triggering follow-up investigations concerning the potential use of endogenous substances with doping potential, which might be difficult either to identify with the existing analytical methods or to interpret based only on the results of a single biological sample. The ABP program has been on-going within the World Anti-Doping Agency (WADA) management since 2009, when the hematological module was officially established to discover blood doping practices, such as administration of erythropoietin (EPO) or application of blood transfusion. Since 2014, the ABP has been complemented by the steroid module, with the aim of targeting the prohibited use of testosterone and other endogenous anabolic androgenic steroids with performance enhancing or masking capability. Although the main objective is to guide and assist the anti-doping organizations in their test distribution plans, the ABP may also be used to proceed with a case to an anti-doping rule violation. Evaluation of biological markers, especially in distinguishing between doping from other confounding factors, requires high level and diversity of expertise, which is coordinated by the athlete biological passport management unit (APMU). Since 2019, the WADA accredited anti-doping laboratories are defined as the host organizations for the APMUs. The benefit of such a structure is to obtain a fully anonymous evaluation process for the passports and an additional level of expertise for the interpretation of analytical results as well as to have a fluent communication line with the analyzing laboratories when further details are needed for the analytical testing and documentation.

System-Wide Profiling of Protein Complexes Via Size Exclusion Chromatography-Mass Spectrometry (SEC-MS).

In living cells, most proteins are organized in stable or transient functional assemblies, protein complexes, which control a multitude of vital cellular processes such as cell cycle progression, metabolism, and signal transduction. Over several decades, specific protein complexes have been analyzed by structural biology methods, initially X-ray crystallography and more recently single particle cryoEM. In parallel, mass spectrometry (MS)-based methods including in vitro affinity-purification coupled to MS or in vivo protein proximity-dependent labeling methods have proven particularly effective to detect complexes, thus nominating new assemblies for structural analysis. Those approaches, however, are either of limited in throughput or require specifically engineered protein systems.In this chapter, we present protocols for a workflow that supports the parallel analysis of multiple complexes from the same biological sample with respect to abundance, subunit composition, and stoichiometry. It consists of the separation of native complexes by size-exclusion chromatography (SEC) and the subsequent mass spectrometric analysis of the proteins in consecutive SEC fractions. In particular, we describe (1) optimized conditions to achieve native protein complex separation by SEC, (2) the preparation of the SEC fractions for MS analysis, (3) the acquisition of the MS data at high throughput via SWATH/DIA (data-independent analysis) mass spectrometry and short chromatographic gradients, and (4) a set of bioinformatic tools for the targeted analysis of protein complexes. Altogether, the parallel measurement of a high number of complexes from a single biological sample results in unprecedented system-level insights into the remodeling of cellular protein complexes in response to perturbations of a broad range of cellular systems.

Synergistic Analysis of Protein Corona and Haemoglobin Levels Detects Pancreatic Cancer.

Simple SummaryPancreatic ductal adenocarcinoma (PDAC) is often diagnosed at an advanced stage and is burdened by poor prognosis. Its early diagnosis is rare because the disease is frequently asymptomatic for a long time. Our research aims to identify a useful and simple diagnostic tool for early PDAC detection. The combination of user-friendly, nanotechnology-based tools and standard blood tests showed high accuracy in discriminating PDAC patients from healthy subjects. If confirmed in large-cohort studies, these findings could represent an innovative and non-invasive method with a potential impact in clinical practice in early detection of PDAC.Simultaneous detection of multiple analytes from a single biological sample is gaining more attention in the development of more reliable and point-of-care diagnostic devices. We developed a multiplexed strategy that combined outcomes of clinical biomarkers with analysis of the protein corona that forms around graphene oxide sheets upon exposure to patient’s plasma. As a paradigmatic case study, we selected pancreatic ductal adenocarcinoma (PDAC), mainly because of the absence of effective detection strategies that resulted in an extremely low five-year survival rate after diagnosis (<10%). Association of protein corona analysis and haemoglobin levels discriminated PDAC patients from healthy volunteers in up to 90% of cases. If further confirmed in larger-cohort studies, this approach may be used in the detection of PDAC.

An Optimized Dual Extraction Method for the Simultaneous and Accurate Analysis of Polar Metabolites and Lipids Carried out on Single Biological Samples.

The functional understanding of metabolic changes requires both a significant investigation into metabolic pathways, as enabled by global metabolomics and lipidomics approaches, and the comprehensive and accurate exploration of specific key pathways. To answer this pivotal challenge, we propose an optimized approach, which combines an efficient sample preparation, aiming to reduce the variability, with a biphasic extraction method, where both the aqueous and organic phases of the same sample are used for mass spectrometry analyses. We demonstrated that this double extraction protocol allows working with one single sample without decreasing the metabolome and lipidome coverage. It enables the targeted analysis of 40 polar metabolites and 82 lipids, together with the absolute quantification of 32 polar metabolites, providing comprehensive coverage and quantitative measurement of the metabolites involved in central carbon energy pathways. With this method, we evidenced modulations of several lipids, amino acids, and energy metabolites in HepaRG cells exposed to fenofibrate, a model hepatic toxicant, and metabolic modulator. This new protocol is particularly relevant for experiments involving limited amounts of biological material and for functional metabolic explorations and is thus of particular interest for studies aiming to decipher the effects and modes of action of metabolic disrupting compounds.

Fluorescent bead-based serological detection of Toxoplasma gondii infection in chickens

BackgroundFree-ranging chickens are often infected with Toxoplasma gondii and seroconvert upon infection. This indicates environmental contamination with T. gondii.MethodsHere, we established a bead-based multiplex assay (BBMA) using the Luminex technology for the detection of T. gondii infections in chickens. Recombinant biotinylated T. gondii surface antigen 1 (TgSAG1bio) bound to streptavidin-conjugated magnetic Luminex beads served as antigen. Serum antibodies were detected by a fluorophore-coupled secondary antibody. Beads of differing color codes were conjugated with anti-chicken IgY or chicken serum albumin and served for each sample as an internal positive or negative control, respectively. The assay was validated with sera from experimentally and naturally infected chickens. The results were compared to those from reference methods, including other serological tests, PCRs and bioassay in mice.ResultsIn experimentally infected chickens, the vast majority (98.5%, n = 65/66) of birds tested seropositive in the BBMA. This included all chickens positive by magnetic-capture PCR (100%, n = 45/45). Most, but not all inoculated and TgSAG1bio-BBMA-positive chickens were also positive in two previously established TgSAG1-ELISAs (TgSAG1-ELISASL, n = 61/65; or TgSAG1-ELISASH, n = 60/65), or positive in an immunofluorescence assay (IFAT, n = 64/65) and in a modified agglutination test (MAT, n = 61/65). All non-inoculated control animals (n = 28/28, 100%) tested negative. In naturally exposed chickens, the TgSAG1bio-BBMA showed a high sensitivity (98.5%; 95% confidence interval, CI: 90.7–99.9%) and specificity (100%; 95% CI: 85.0–100%) relative to a reference standard established using ELISA, IFAT and MAT. Almost all naturally exposed chickens that were positive in bioassay or by PCR tested positive in the TgSAG1bio-BBMA (93.5%; 95% CI: 77.1–98.9%), while all bioassay- or PCR-negative chickens remained negative (100%; 95% CI: 85.0–100%).ConclusionsThe TgSAG1bio-BBMA represents a suitable method for the detection of T. gondii infections in chickens with high sensitivity and specificity, which is comparable or even superior to other tests. Since assays based on this methodology allow for the simultaneous analysis of a single biological sample with respect to multiple analytes, the described assay may represent a component in future multiplex assays for broad serological monitoring of poultry and other farm animals for various pathogens.

Criteria for evaluating risk prediction of multiple outcomes.

Risk prediction models have been developed in many contexts to classify individuals according to a single outcome, such as risk of a disease. Emerging “-omic” biomarkers provide panels of features that can simultaneously predict multiple outcomes from a single biological sample, creating issues of multiplicity reminiscent of exploratory hypothesis testing. Here I propose definitions of some basic criteria for evaluating prediction models of multiple outcomes. I define calibration in the multivariate setting and then distinguish between outcome-wise and individual-wise prediction, and within the latter between joint and panel-wise prediction. I give examples such as screening and early detection in which different senses of prediction may be more appropriate. In each case I propose definitions of sensitivity, specificity, concordance, positive and negative predictive value and relative utility. I link the definitions through a multivariate probit model, showing that the accuracy of a multivariate prediction model can be summarised by its covariance with a liability vector. I illustrate the concepts on a biomarker panel for early detection of eight cancers, and on polygenic risk scores for six common diseases.

50 years existence and active participation of EEMS (now EEMGS) in the scientific community: A driver of European and international scientific collaborations for the protection of the environment and human health from genome stressors

EEMS and its successor Society EEMGS have provided a dynamic and successful platform to stimulate research and exchanges among the different actors involved in the protection of the environment and of human health from exposure to genome stressors. It includes basic, translational and applied research projects. This was possible due to the enthusiasm, creativity and support of scientists convinced of the importance of these issues.In the future young scientists will take over with new questions, new challenges, new technologies, new discoveries and new applications. A major challenge is the ethical questions emerging from the impressive potential of present genetic technologies capable of impacting the evolution of nature and humankind. The EEMGS, where academics, regulators and industries meet, should play a central role in these aspects, in particular in support of primary prevention and the establishment of internationally recognized guidelines. Collaboration with colleagues and other teams are of great importance to establish a stimulating open dialogue on scientific questions. However the key issues remain to do careful and rigorous research; to use logic and background knowledge; to define adequate experimental designs; to provide transparency in the protocols; to check repeatability of the results and to combine several statistical approaches in the quest to get to the truth.Among the many challenges ahead, re-evaluation of some key fundamental questions is necessary, such as the interplay between genetics and epigenetics, the existence of specific germ cell mutagens or the identification of the mechanisms leading to mutagen induced diseases. Translational and applied research will further include the development of systemic biomonitoring protocols, if possible in a single biological sample, the redaction of internationally harmonized guidelines but also the organization of platforms between geneticists and physicians open to all actors in the field. The creation of an independent European center to assess risk from exposure to mutagens, in particular in the light of the problematic of global warming might be very helpful.

In situ analysis of single cell and biological samples with rGO-Cu functional probe ESI-MS spectrometry

At present, probe electrospray ionization mass spectrometry is widely used in the single cell analysis. As the continuous expansion of requirements for detecting more metabolite species from single cells, the sensitivity and accuracy of the instrument and the enrichment capacity of the probes are in high demand. Therefore, a high efficiency functional probe electrospray ionization mass spectrometry (FPESI–MS) analysis platform is established. In this platform, nitrogen aggregation/gas heating system and reduced graphene oxide functional copper probe (rGO-Cu probe) are firstly reported. The nitrogen aggregation/gas heating system can promote desorption of the analytes from probe and aggregate the product ions into the ion cluster to increase the ion transport capacity and the detection efficiency. rGO-Cu probe formed huge specific surface area to enrich the analytes without sacrificing the electrical conductivity. The probe substrates were prepared by electrochemical etching, after rGO-functionalization, the tip diameter of all kinds of the probes were measured to be less than 100 nm, which is much smaller than the PC12 single cells. Graphene oxide cannot be completely reduced by electrochemical methods, thus the rGO-Cu probe can enrich the analytes through the huge surface area of the graphene thin layer, as well as the hydrogen bond and the electrostatic absorption of the surface oxygen-containing groups. Seven AD related neurotransmitters and sixteen biomarkers in PC12 single cells and twelve metabolites in serum of AD rats were successfully analyzed by using FPESI–MS, and this method is expected to be used in the rapid detection of metabolites in biological samples and living organism.

Quantification of ERK Kinase Activity in Biological Samples Using Differential Sensing.

The understanding of complex biological systems requires an ability to evaluate interacting networks of genes, proteins, and cellular reactions. Enabling technologies that support the rapid quantification of these networks will facilitate the development of biological models and help to identify treatment targets and to assess treatment plans. The biochemical process of protein phosphorylation, which underlies almost all aspects of cell signaling, is typically evaluated by immunoblotting procedures (Western blot) or more recently proteomics procedures, which provide qualitative estimates of the concentration of proteins and their modifications in cells. However, protein modifications are difficult to correlate with activity, and while immunoblotting and proteomics approaches have the potential to be quantitative, they require a complex series of steps that diminish reproducibility. Here, a complementary approach is presented that allows for the rapid quantification of a protein kinase activity in cell lysates and tumor samples. Using the activity of cellular ERK (extracellular signal-regulated kinase) as a test case, an array sensing approach that utilizes a library of differential peptide-based biosensors and chemometric tools was used to rapidly quantify nanograms of active ERK in micrograms of unfractionated cell lysates and tumor extracts. This approach has the potential both for high-throughput and for quantifying the activities of multiple protein kinases in a single biological sample. The critical advantages of this differential sensing approach over others are that it removes the need for the addition of exogenous inhibitors to suppress the activities of major off-target kinases and allows us to quantitate the amount of active kinase in tested samples rather than measuring the changes in its activity upon induction or inhibition.