Absolute Quantitative Data Research Articles

SCALiR: A Web Application for Automating Absolute Quantification of Mass Spectrometry-Based Metabolomics Data.

Quantitative liquid chromatography-mass spectrometry (LC-MS)-based metabolomics is becoming an important approach for studying complex biological systems but presents several technical challenges that limit its widespread use. Computing metabolite concentrations using standard curves generated from standard mixtures of known concentrations is a labor-intensive process that is often performed manually. Currently, there are few options for open-source software tools that can automatically calculate metabolite concentrations. Herein, we introduce SCALiR (standard curve application for determining linear ranges), a new web-based software tool specifically built for this task, which allows users to automatically transform LC-MS signals into absolute quantitative data (https://www.lewisresearchgroup.org/software). SCALiR uses an algorithm that automatically finds the equation of the line of best fit for each standard curve and uses this equation to calculate compound concentrations from the LC-MS signal. Using a standard mix containing 77 metabolites, we show a close correlation between the concentrations calculated by SCALiR and the expected concentrations of each compound (R2 = 0.99 for a y = x curve fitting). Moreover, we demonstrate that SCALiR reproducibly calculates concentrations of midrange standards across ten analytical batches (average coefficient of variation 0.091). SCALiR can be used to calculate metabolite concentrations either using external calibration curves or by using internal standards to correct for matrix effects. This open-source and vendor agnostic software offers users several advantages in that (1) it requires only 10 s of analysis time to compute concentrations of >75 compounds, (2) it facilitates automation of quantitative workflows, and (3) it performs deterministic evaluations of compound quantification limits. SCALiR therefore provides the metabolomics community with a simple and rapid tool that enables rigorous and reproducible quantitative metabolomics studies.

From the outer space to the inner cell: deconvoluting the complexity of Bacillus subtilis disulfide stress responses by redox state and absolute abundance quantification of extracellular, membrane, and cytosolic proteins.

Stress responses play a crucial role in bacterial survival and adaptation. The ability to quantitatively measure protein abundances and redox states in different cellular compartments and the extracellular environment is essential for understanding stress management mechanisms. In this study, we addressed the knowledge gap regarding absolute quantification of extracellular proteins and compared protein concentrations in various sub-cellular locations and in the extracellular medium under disulfide stress conditions. Our findings provide valuable insights into the protein production and secretion dynamics of B. subtilis, shedding light on its stress response strategies. Furthermore, the developed protocol for absolute quantification of extracellular proteins in bacteria presents a practical and efficient approach for future studies in the field. Overall, this research contributes to the quantitative understanding of stress management mechanisms and protein dynamics in B. subtilis, which can be used to enhance bacterial stress tolerance and protein-based biotechnological applications.

Bacterial load in meconium.

The spike-in plasmid method was utilized to perform an analysis on meconium and second-pass feces, yielding both relative and absolute quantitative results. With the absolute quantitative data, the abundance of bacteria in 17 meconium samples and 17 second-pass fecal samples were found to be 1.14 × 107 and 1.59 × 109 copies/g, respectively. The mode of delivery can significantly influence the alterations and compositions of gut bacteria in a newborn within 72 h.

Association between body mass index (BMI) and [123I]Ioflupane (DaTSCAN) availabilities in patients with parkinsonism using single-photon emission computed tomography–computed tomography (SPECT-CT)

Aim[123I]Ioflupane (DaTSCAN) has a high binding affinity to the dopamine (DA) transporter (DaT) and tenfold less affinity to serotonin (5-HT) transporter (SERT). Both neurotransmitters are considered to contribute to body weight regulation. This study assesses the association between body mass index (BMI) and DaTSCAN availability in brain.MethodScans from 74 consecutive patients who had undergone DaTSCAN single-photon emission computed tomography–computed tomography (SPECT-CT) were used to obtain semi- and absolute quantitative data in several volumes of interest (VOIs). Relative semi-quantitative specific binding ratios (SBRs) from Chang attenuated SPECT were obtained from GE DaTQUANT. Absolute normalised concentration (NC) was calculated from attenuation/scatter corrected SPECT-CT images, using an adapted version of the EARL Ltd (European Association of Nuclear Medicine (EANM) Research 4 Life) template. Scans were subdivided into either degenerative parkinsonism (abnormal = 49), borderline (n = 14) or scan without evidence of dopaminergic deficit (SWEDD = 11) using visual assessment and SBR values by two nuclear medicine consultants.ResultsSBRs did not correlate with BMI. However, NC values correlated negatively in the entire cohort, with the strongest correlation in the frontal (r = − 0.649. p = 0.000), occipital (r = − 0.555, p = 0.000) regions and pons (r = − 0.555, p = 0.000). In the abnormal (n = 49) and SWEDD group (n = 11), NC of the frontal region was the most correlated with BMI (r = − 0.570, p = 0.000; r = − 0.813, p = 0.002, respectively). In the borderline group (n = 14), the left posterior putamen displayed the strongest correlation (r = − 0.765, p = 0.001).ConclusionAbsolute NC values demonstrate a strong inverse correlation with BMI, strongest in the extrastriatal regions. Due to the predominately non-overlapping distribution of DaT and SERT, this study suggests greater involvement of SERT in obesity with possible interplay with DA transmission.

Blood Plasma Proteome: A Meta-Analysis of the Results of Protein Quantification in Human Blood by Targeted Mass Spectrometry.

A meta-analysis of the results of targeted quantitative screening of human blood plasma was performed to generate a reference standard kit that can be used for health analytics. The panel included 53 of the 296 proteins that form a “stable” part of the proteome of a healthy individual; these proteins were found in at least 70% of samples and were characterized by an interindividual coefficient of variation <40%. The concentration range of the selected proteins was 10−10−10−3 M and enrichment analysis revealed their association with rare familial diseases. The concentration of ceruloplasmin was reduced by approximately three orders of magnitude in patients with neurological disorders compared to healthy volunteers, and those of gelsolin isoform 1 and complement factor H were abruptly reduced in patients with lung adenocarcinoma. Absolute quantitative data of the individual proteome of a healthy and diseased individual can be used as the basis for personalized medicine and health monitoring. Storage over time allows us to identify individual biomarkers in the molecular landscape and prevent pathological conditions.

INNOVATIONS IN DIAGNOSTIC METHODS: NUCLEAR MEDICINE — MYOCARDIAL PERFUSION, FLOW RESERVE AND MYOCARDIAL VIABILITY

Nuclear Medicine, by integrating information on relative myocardial perfusion, ventricular function and absolute quantitative data such as myocardial blood flow and coronary flow reserve, expands and modifies the scope of evaluation of patients with chronic coronary insufficiency. These measures are producing a paradigm shift in the assessment and management of patients with CAD, allowing the definition of a broad spectrum of coronary vascular dysfunction. These quantitative tools provide a measure of the integrated effects of focal coronary stenoses, diffuse atherosclerosis, and microvascular dysfunction on myocardial perfusion. This data set allows improving the diagnosis and assessment of the extent of epicardial disease, reclassifying the prognosis, demonstrated through robust literature data that confirm the incremental value over other variables in the risk stratification of patients with ischemic heart disease, and allow to identify coronary microcirculatory disease with or without epicardial CAD. A more accurate and sensitive assessment of myocardial tissue ischemia is then obtained. This chapter explores these possibilities, the assessment of myocardial viability, and the future perspectives of Nuclear Medicine, which include the development of new radiopharmaceuticals focused on molecular imaging and the creation of new hybrid devices that combine functional and anatomical information in a single test

Neutron encoded derivatization of endothelial cell lysates for quantitation of aldehyde metabolites using nESI-LC-HRMS

Biological aldehydes are difficult to analyze by electrospray ionization mass spectrometry due to their poor proton affinity and low biological concentrations. Chemical derivatization with stable isotope tags is used here for sample multiplexing, increased throughput, improved signal intensity, and quantitation. Nine quaternary amine tags with mass differences as low as 0.0058 Da had no observable chromatographic shifts, small amounts of ion suppression, and minimal matrix effects. Low concentration perfluoropentanoic acid was used as an ion pairing reagent to improve the retention of derivatized aldehydes. Perfluoropentanoic acid addition showed an average of three-fold improvement in limits of detection, 50% reduction in peak width, and 2.5 fold increase in analyte retention. Analysis of fifteen tagged aldehydes yielded an average of 13 nM limit of detection, 9 %RSD, R2 of 0.995, and linear dynamic range of 40–1000 nM. In a single 20 min separation, absolute quantitative data was obtained for 11 reactive aldehydes across 8 aortic endothelial cell samples. High glucose treatment produced significant changes to malondialdehyde, decanal, and (2E)-hexadecenal. These changes are consistent with glucose-induced oxidative stress. This method demonstrates that neutron encoded tagging of aldehydes is suitable for the analysis of complex samples.

Correlation of μXRF and LA-ICP-MS in the analysis of a human bone-cartilage sample

In this study we combined μXRF and LA-ICP-MS on the very same human femoral head sample. Obtained spatial elemental distributions within bone and cartilage tissues are accompanied by absolute quantitative data.

Classification of Brazilian roasted coffees from different geographical origins and farming practices based on chlorogenic acid profiles

Sixty-seven roasted coffee samples from different regions of Brazil cultivated using organic, conventional and biodynamic farming practices were analysed and quantified using high performance liquid chromatography coupled with mass spectrometry, and treated with supervised (PLS-DA) and unsupervised (PCA) multivariate statistical tools. The profile of the chlorogenic acids constituents were analysed by high resolution and tandem mass spectrometry, which allowed the identification of mono- caffeoyl-, feruloyl-, para-Coumaroylquinic acids and their respective regio-isomers. This study provides a comprehensive analysis of absolute quantitative data set of chlorogenic acids constituents (CQA, FQA and pCoQA isomers) in Brazilian coffee beans produced from different regions of the country. Variations in the chlorogenic acids compositions were observed if organic and conventional roasted coffee beans were compared. The use of multivariate statistical tools allowed the identification of suitable biomarkers for determining significant differences between the three coffee agricultural practices, while coffees produced from the diverse geographical regions showed no significant difference.

Quantitative Isotope-Dilution High-Resolution-Mass-Spectrometry Analysis of Multiple Intracellular Metabolites in Clostridium autoethanogenum with Uniformly 13C-Labeled Standards Derived from Spirulina.

We have investigated the applicability of commercially available lyophilized spirulina ( Arthrospira platensis), a microorganism uniformly labeled with 13C, as a readily accessible source of multiple 13C-labeled metabolites suitable as internal standards for the quantitative determination of intracellular bacterial metabolites. Metabolites of interest were analyzed by hydrophilic-interaction liquid chromatography coupled with high-resolution mass spectrometry. Multiple internal standards obtained from uniformly (U)-13C-labeled extracts from spirulina were used to enable isotope-dilution mass spectrometry (IDMS) in the identification and quantification of intracellular metabolites. Extraction of the intracellular metabolites of Clostridium autoethanogenum using 2:1:1 chloroform/methanol/water was found to be the optimal method in comparison with freeze-thaw, homogenization, and sonication methods. The limits of quantification were ≤1 μM with excellent linearity for all of the calibration curves ( R2 ≥ 0.99) for 74 metabolites. The precision and accuracy were found to be within relative standard deviations (RSDs) of 15% for 49 of the metabolites and within RSDs of 20% for all of the metabolites. The method was applied to study the effects of feeding different levels of carbon monoxide (as a carbon source) on the central metabolism and Wood-Ljungdahl pathway of C. autoethanogenum grown in continuous culture over 35 days. Using LC-IDMS with U-13C spirulina allowed the successful quantification of 52 metabolites in the samples, including amino acids, carboxylic acids, sugar phosphates, purines, and pyrimidines. The method provided absolute quantitative data on intracellular metabolites that was suitable for computational modeling to understand and optimize the C. autoethanogenum metabolic pathways active in gas fermentation.

Profiling, quantification and classification of cocoa beans based on chemometric analysis of carbohydrates using hydrophilic interaction liquid chromatography coupled to mass spectrometry

Fifty-six cocoa bean samples from different origins and status of fermentation were analyzed by a validated hydrophilic interaction liquid chromatography-electrospray ionization-time of flight-mass spectrometry (HILIC-ESI-TOF-MS) method. The profile of the low molecular weight carbohydrate (LMWC) was analyzed by high resolution and tandem mass spectrometry, which allowed the identification of mono-, di-, tri- and tetrasaccharides, sugar alcohols and iminosugars.This study provides, for the first time in a large set of samples, a comprehensive absolute quantitative data set for the carbohydrates identified in cocoa beans (fructose, glucose, mannitol, myo-inositol, sucrose, melibiose, raffinose and stachyose). Differences in the content of carbohydrates were observed between unfermented (range of 0.9–4.9 g/g DM) and fermented (range 0.1–0.5 g/g DM) cocoa beans.The use of multivariate statistical tools allowed the identification of biomarkers suitable for cocoa bean classification according to the status of fermentation, procedure of fermentation employed and number of days of fermentation.

Single-molecule Fluorescence in situ Hybridization (smFISH) for RNA Detection in Adherent Animal Cells.

Transcription and RNA decay play critical roles in the process of gene expression and the ability to accurately measure cellular mRNA levels is essential for understanding this regulation. Here, we describe a single-molecule fluorescent in situ hybridization (smFISH) method (as performed in Haimovich et al., 2017 ) that detects single RNA molecules in individual cells. This technique employs multiple single-stranded, fluorescent labeled, short DNA probes that hybridize to target RNAs in fixed cells, allowing for both the quantification and localization of cytoplasmic and nuclear RNAs at the single-cell level and single-molecule resolution. Analyzing smFISH data provides absolute quantitative data of the number of cytoplasmic ("mature") mRNAs, the number of nascent RNA molecules at distinct transcription sites, and the spatial localization of these RNAs in the cytoplasm and/or nucleoplasm.

Quantitation of isobaric phosphatidylcholine species in human plasma using a hybrid quadrupole linear ion-trap mass spectrometer

Phosphatidylcholine (PC) species in human plasma are used as biomarkers of disease. PC biomarkers are often limited by the inability to separate isobaric PCs. In this work, we developed a targeted shotgun approach for analysis of isobaric and isomeric PCs. This approach is comprised of two MS methods: a precursor ion scanning (PIS) of mass m/z 184 in positive mode (PIS m/z +184) and MS3 fragmentation in negative mode, both performed on the same instrument, a hybrid triple quadrupole ion-trap mass spectrometer. The MS3 experiment identified the FA composition and the relative abundance of isobaric and sn-1, sn-2 positional isomeric PC species, which were subsequently combined with absolute quantitative data obtained by PIS m/z +184 scan. This approach was applied to the analysis of a National Institute of Standards and Technology human blood plasma standard reference material (SRM 1950). We quantified more than 70 PCs and confirmed that a majority are present in isobaric and isomeric mixtures. The FA content determined by this method was comparable to that obtained using GC with flame ionization detection, supporting the quantitative nature of this MS method. This methodology will provide more in-depth biomarker information for clinical and mechanistic studies.

FRET: signals hidden within the noise.

F€ orster resonance energy transfer (FRET) is a physical phenomenon that has been of incredible utility to the scientific community, enabling the study of a wide range of nanoscale, distance-dependent measurements. FRET occurs when energy is nonradiatively transferred from an excited fluorophore (the donor fluorophore) to a second fluorophore in near proximity (the acceptor fluorophore) (1,2). Because the rate at which energy is transferred from the donor to the acceptor fluorophore depends on the intermolecular distance raised to the sixth power, FRET provides a highly sensitive measure of intermolecular spacing (2,3). The key parameter in FRET measurements is the FRET efficiency. FRET efficiency is most often described as the ratio of the number of quantized energy events (sometimes referred to as virtual photons (4)) transferred from the donor fluorophore to the acceptor fluorophore, divided by the total number of quantized energy events (photons) absorbed by the donor fluorophore (5). Using appropriate measurement and computational techniques, FRET efficiency represents a quantifiable value describing the intermolecular spacing and orientation within a sample. For fluorophores with fixed intermolecular spacing, the value of the measured FRET efficiency has been shown to be relatively constant, regardless of the measurement technique used (6). Hence, FRET reporters can be used to provide absolute quantitative data describing interand intramolecular interactions. Computing the FRET efficiency, whether in fluorescence microscopy or flow cytometry measurements, typically requires a ratiometric calculation (7). Because FRET efficiencies often range from 20 to 60% for biological reporters, the fluorescence emission from the acceptor fluorophore, when excited via energy transfer, usually provides lower signal strength than measurements of acceptor fluorophore emission resulting from direct excitation. Performing ratiometric calculations using relatively weak signals as the inputs can result in compounding error propagation (8). Thus, while FRET, as a tool, offers the ability to probe molecular distances within images or flow cytometry data, it also introduces substantial limitations in sensitivity and variance, due to low signal strength. Low signal strength may also limit spatial and temporal resolution. When performing FRET experiments, trade-offs must usually be made between signal strength (accuracy of the FRET efficiency calculation), spatial resolution, and temporal

Quantification of the concentration gradient of biomarkers between ovarian carcinoma interstitial fluid and blood

BackgroundTumor interstitial fluid (TIF) rather than plasma should be used in cancer biomarker discovery because of the anticipated higher concentration of locally produced proteins in the tumor microenvironment. Nevertheless, the actual TIF-to-plasma gradient of tumor specific proteins has not been quantified. We present the proof-of-concept for the quantification of the postulated gradient between TIF and plasma. MethodsTIF was collected by centrifugation from serous (n=19), endometrioid (n=9) and clear cell (n=3) ovarian carcinomas with early (n=15) and late stage (n=16) disease in grades 1 (n=2), 2 (n=8) and 3 (n=17), and ELISA was used for the determination of CA-125, osteopontin and VEGF-A. ResultsAll three markers were significantly up-regulated in TIF compared with plasma (p<0.0001). The TIF-to-plasma ratio of the ovarian cancer biomarker CA-125 ranged from 1.4 to 24,300 (median=194) and was inversely correlated to stage (p=0.0006). The cancer related osteopontin and VEGF-A had TIF-to-plasma ratios ranging from 1 to 62 (median=15) and 2 to 1040 (median=59), respectively. The ratios were not affected by tumor stage, indicative of more widespread protein expression. ConclusionWe present absolute quantitative data on the TIF-to-plasma gradient of selected proteins in the tumor microenvironment, and demonstrate a substantial and stage dependent gradient for CA-125 between TIF and plasma, suggesting a relation between total tumor burden and tissue-to-plasma gradient. General significanceWe present novel quantitative data on biomarker concentration in the tumor microenvironment, and a new strategy for biomarker selection, applicable in future biomarker studies.

Absolute quantification of apolipoproteins and associated proteins on human plasma lipoproteins.

A more comprehensive picture about the protein complement on individual lipoprotein classes is the goal of lipoprotein proteomics analyses. Despite many such studies, there is a lack of absolute quantitative data on lipoproteins isolated from individual subjects. The stoichiometry of lipoprotein-associated proteins rather than their presence or absence could provide insights into an individual's predisposition for disease such as heart disease or diabetes. Our study provides a comprehensive overview of the absolute quantity of proteins on the major apolipoprotein classes VLDL, LDL, Lp(a) and HDL.

The meaning of sensitivity functions in signaling pathways analysis

The paper deals with local sensitivity analysis of signaling pathway models, based on sensitivity functions. Though the methods are well known, their application to various models is always based on the assumption that the output of the system whose sensitivity is analyzed is given by absolute quantitative data. In signaling pathways models, however, this data is always normalized. In this paper we show what are the implications of the way the signaling pathways models are built for the interpretation of sensitivity functions and parameter rankings based on them. The reasoning is illustrated using simple first- and second order systems as well as an example of a simple regulatory module.

Quantification of protein modification by oxidants

Proteins are major targets for oxidative damage due to their abundance and rapid rates of reaction with a wide range of radicals and excited state species, such as singlet oxygen. Exposure of proteins to these oxidants results in loss of the parent amino acid residue, formation of unstable intermediates, and the generation of stable products. Each of these events can be used, to a greater or lesser extent, to quantify damage to proteins. In this review the advantages and disadvantages of a number of these approaches are discussed, with an emphasis on methods that yield absolute quantitative data on the extent of protein modification. Detailed methods sheets are provided for many of these techniques.

Quantitative proteomics for identification of cancer biomarkers

Quantitative proteomics can be used for the identification of cancer biomarkers that could be used for early detection, serve as therapeutic targets, or monitor response to treatment. Several quantitative proteomics tools are currently available to study differential expression of proteins in samples ranging from cancer cell lines to tissues to body fluids. 2-DE, which was classically used for proteomic profiling, has been coupled to fluorescence labeling for differential proteomics. Isotope labeling methods such as stable isotope labeling with amino acids in cell culture (SILAC), isotope-coded affinity tagging (ICAT), isobaric tags for relative and absolute quantitation (iTRAQ), and (18) O labeling have all been used in quantitative approaches for identification of cancer biomarkers. In addition, heavy isotope labeled peptides can be used to obtain absolute quantitative data. Most recently, label-free methods for quantitative proteomics, which have the potential of replacing isotope-labeling strategies, are becoming popular. Other emerging technologies such as protein microarrays have the potential for providing additional opportunities for biomarker identification. This review highlights commonly used methods for quantitative proteomic analysis and their advantages and limitations for cancer biomarker analysis.

Quantitative characterization of friction coefficient using lateral force microscope in the wearless regime

Absolute quantitative data from atomic force microscopy (AFM)/lateral force microscopy experiments are always difficult to obtain mainly due to the need of the normal force FN and the friction force FF calibration. In this article, we developed an experimental method which allows us to extract absolute quantitative friction data without calibrating any force when the relation between FN and FF is linear or only calibrating the normal force when the relationship is nonlinear. The technique reported here, is suitable for an atomic force microscope that has the cantilever attached to the piezotube translator and an unguided incident laser beam on the cantilever. We take advantage of the piezotube bending during a large scan (5 μm×5 μm), generally considered as an undesirable effect, to calculate a detection factor that allows the determination of quantitative tribological data. The validity of our experimental method is checked on the extensively AFM studied materials, such as muscovite, silicon, and highly oriented pyrolytic graphite. The experiments are carried out in a load range where the shear stress τ can be expressed as τ=τ0+μP, where μ is the friction coefficient, P is the mean contact pressure, and τ0 is a parameter related to the tip/sample adhesion. The value of μ is found to be independent of the tip geometry and the pull-off force, and always constant for a given tip/sample couple in the load range investigated.