scholarly journals High-Throughput Simultaneous Analysis of RNA, Protein, and Lipid Biomarkers in Heterogeneous Tissue Samples

2011 ◽  
Vol 57 (11) ◽  
pp. 1545-1555 ◽  
Author(s):  
Vladimír Reiser ◽  
Ryan C Smith ◽  
Jiyan Xue ◽  
Marc M Kurtz ◽  
Rong Liu ◽  
...  
Keyword(s):  
High Throughput ◽  
Large Scale ◽  
Biomarker Discovery ◽  
Tissue Sample ◽  
Protein Composition ◽  
Analytical Techniques ◽  
Clinical Samples ◽  
Tissue Samples ◽  
Heterogeneous Tissue

BACKGROUND With expanding biomarker discovery efforts and increasing costs of drug development, it is critical to maximize the value of mass-limited clinical samples. The main limitation of available methods is the inability to isolate and analyze, from a single sample, molecules requiring incompatible extraction methods. Thus, we developed a novel semiautomated method for tissue processing and tissue milling and division (TMAD). METHODS We used a SilverHawk atherectomy catheter to collect atherosclerotic plaques from patients requiring peripheral atherectomy. Tissue preservation by flash freezing was compared with immersion in RNAlater®, and tissue grinding by traditional mortar and pestle was compared with TMAD. Comparators were protein, RNA, and lipid yield and quality. Reproducibility of analyte yield from aliquots of the same tissue sample processed by TMAD was also measured. RESULTS The quantity and quality of biomarkers extracted from tissue prepared by TMAD was at least as good as that extracted from tissue stored and prepared by traditional means. TMAD enabled parallel analysis of gene expression (quantitative reverse-transcription PCR, microarray), protein composition (ELISA), and lipid content (biochemical assay) from as little as 20 mg of tissue. The mean correlation was r = 0.97 in molecular composition (RNA, protein, or lipid) between aliquots of individual samples generated by TMAD. We also demonstrated that it is feasible to use TMAD in a large-scale clinical study setting. CONCLUSIONS The TMAD methodology described here enables semiautomated, high-throughput sampling of small amounts of heterogeneous tissue specimens by multiple analytical techniques with generally improved quality of recovered biomolecules.

scholarly journals In search of an evidence-based strategy for quality assessment of human tissue samples: report of the tissue Biospecimen Research Working Group of the Spanish Biobank Network

2019 ◽  
Vol 17 (1) ◽  
Author(s):  
Margalida Esteva-Socias ◽  
María-Jesús Artiga ◽  
Olga Bahamonde ◽  
Oihana Belar ◽  
Raquel Bermudo ◽  
...  
Keyword(s):  
Quality Assessment ◽  
Human Tissue ◽  
Working Group ◽  
Tissue Sample ◽  
Quality Criteria ◽  
Analytical Techniques ◽  
Sample Collection ◽  
Tissue Samples ◽  
The Impact

Abstract The purpose of the present work is to underline the importance of obtaining a standardized procedure to ensure and evaluate both clinical and research usability of human tissue samples. The study, which was carried out by the Biospecimen Science Working Group of the Spanish Biobank Network, is based on a general overview of the current situation about quality assurance in human tissue biospecimens. It was conducted an exhaustive review of the analytical techniques used to evaluate the quality of human tissue samples over the past 30 years, as well as their reference values if they were published, and classified them according to the biomolecules evaluated: (i) DNA, (ii) RNA, and (iii) soluble or/and fixed proteins for immunochemistry. More than 130 publications released between 1989 and 2019 were analysed, most of them reporting results focused on the analysis of tumour and biopsy samples. A quality assessment proposal with an algorithm has been developed for both frozen tissue samples and formalin-fixed paraffin-embedded (FFPE) samples, according to the expected quality of sample based on the available pre-analytical information and the experience of the participants in the Working Group. The high heterogeneity of human tissue samples and the wide number of pre-analytic factors associated to quality of samples makes it very difficult to harmonize the quality criteria. However, the proposed method to assess human tissue sample integrity and antigenicity will not only help to evaluate whether stored human tissue samples fit for the purpose of biomarker development, but will also allow to perform further studies, such as assessing the impact of different pre-analytical factors on very well characterized samples or evaluating the readjustment of tissue sample collection, processing and storing procedures. By ensuring the quality of the samples used on research, the reproducibility of scientific results will be guaranteed.

scholarly journals Hyperspectral Shortwave Infrared Image Analysis for Detection of Adulterants in Almond Powder with One-Class Classification Method

Sensors ◽  
2020 ◽  
Vol 20 (20) ◽  
pp. 5855
Author(s):  
Mohammad Akbar Faqeerzada ◽  
Santosh Lohumi ◽  
Geonwoo Kim ◽  
Rahul Joshi ◽  
Hoonsoo Lee ◽  
...  
Keyword(s):  
High Throughput ◽  
Large Scale ◽  
Analytical Techniques ◽  
Error Rates ◽  
Partial Least Square ◽  
Least Square ◽  
Partial Least Square Regression ◽  
Analysis Model ◽  
One Class Classifier ◽  
Shortwave Infrared

The widely used techniques for analyzing the quality of powdered food products focus on targeted detection with a low-throughput screening of samples. Owing to potentially significant health threats and large-scale adulterations, food regulatory agencies and industries require rapid and non-destructive analytical techniques for the detection of unexpected compounds present in products. Accordingly, shortwave-infrared hyperspectral imaging (SWIR-HSI) for high throughput authenticity analysis of almond powder was investigated in this study. Two different varieties of almond powder, adulterated with apricot and peanut powder at different concentrations, were imaged using the SWIR-HSI system. A one-class classifier technique, known as data-driven soft independent modeling of class analogy (DD-SIMCA), was used on collected data sets of pure and adulterated samples. A partial least square regression (PLSR) model was further developed to predict adulterant concentrations in almond powder. Classification results from DD-SIMCA yielded 100% sensitivity and 89–100% specificity for different validation sets of adulterated samples. The results obtained from the PLSR analysis yielded a high determination coefficient (R2) and low error values (<1%) for each variety of almond powder adulterated with apricot; however, a relatively higher error rates of 2.5% and 4.4% for the two varieties of almond powder adulterated with peanut powder, which indicates the performance of quantitative analysis model could vary with sample condition, such as variety, originality, etc. PLSR-based concentration mapped images visually characterized the adulterant (apricot) concentration in the almond powder. These results demonstrate that the SWIR-HSI technique combined with the one-class classifier DD-SIMCA can be used effectively for a high-throughput quality screening of almond powder regarding potential adulteration.

scholarly journals Uranium Concentrations in Tissues and Other Clinical Samples of the Serbian Population

2021 ◽  
Vol 13 (1) ◽  
pp. 97-104
Author(s):  
A. Stojsavljević ◽  
◽  
V.V. Avdin ◽  
D.A. Zherebtsov ◽  
D. Manojlović ◽  
...  
Keyword(s):  
Thyroid Carcinoma ◽  
Tissue Sample ◽  
Clinical Samples ◽  
Papillary Thyroid ◽  
Sample Analysis ◽  
Follicular Variant ◽  
Tissue Samples ◽  
Blood Samples ◽  
Inductively Coupled ◽  
Plasma Mass Spectrometry

The prevalence of numerous malignant diseases is on the rise, while the mechanism of metal-induced oncogenesis has not been elucidated so far. The aim of this study was to determine the amount of uranium (U) in blood samples of the Serbian population (n = 305) and to perform a comparative analysis with the amounts of U in the blood of patients with thyroid carcinoma (TC, n = 103) and malignant brain tumors (MBTs, n = 157). This study also aimed to extend data on the tissue sample analysis. Uranium was quantified by inductively coupled quadrupole plasma mass spectrometry (ICP-Q-MS). The content of U was approximately 15 times higher in the Serbian population compared to other population groups worldwide that did not suffer from the war, while its amount showed similarities with the countries that directly suffered from the war. Furthermore, the U content was up to twice as high in the blood samples of TC patients compared to the control, while the U content in the TC tissue samples was approximately 10 times higher than in healthy thyroid tissues and showed a tendency to be higher in follicular variant of papillary thyroid carcinoma. However, the highest alterations in U content were obtained in samples of MBT patients, both in liquid clinical samples (serum, lysate, and cerebrospinal fluid) and in tissue samples. The results of this study could highlight the unresolved etiology of TC and MBT. Moreover, the reported results indicated the importance of regular monitoring of U in the blood of the Serbian population.

scholarly journals Effects of processing, storage time, and tissue volume in the retrieval and quality of RNA and the expression level of RNU6

2021 ◽  
Author(s):  
Ines Benedetti ◽  
Laura De León ◽  
Niradiz Reyes
Keyword(s):  
Storage Time ◽  
Inverse Correlation ◽  
Ffpe Tissue ◽  
Expression Level ◽  
Clinical Samples ◽  
Tissue Storage ◽  
Tissue Samples ◽  
Rna Quality ◽  
Ffpe Tissues

Background: Molecular analyses of tumor RNA expression have become widely used both for research and clinical purposes. Tumoral tissue preservation is a critical step to ensure accuracy of molecular-based diagnostics, for which, formalin-fixed and paraffin-embedded (FFPE) tissues represent a valuable source of clinical samples. MicroRNAs are ideal biomarkers in FFPE-tissues, in whose expression evaluation RNU6 is one of the genes used as a normalizer. Our aim was to determine, in FFPE tissue samples, the effects of length of storage and corresponding volume of each studied sample, on the RNA retrieval, quality and concentration, as well as their correlation to the expression level of RNU6. Methods: Fifty tissue blocks with a mean length of tissue storage of 30 months (SD=±12.07, 95% CI= 27.4-34.3). were included. Total RNA was isolated, absorbance and concentrations were determined and correlated with length of storage and volume of tissue. RT-qPCR for RNU6 was performed and their Ct results were correlated to the same parameters. Results: There was a direct correlation between the concentration and quality of the obtained RNA, and an inverse correlation between the tissue storage time and the RNA quality. The volume of tissue studied was not correlated with the RNA quality or concentration. The RNA quality and the length of tissue storage directly correlated to the RNU6 expression level, while RNA concentration and the volume of tissue studied did not affect it. Conclusions: There is an association between longer FFPE tissue storage time with lower RNA quality and lower RNU6 expression level.

scholarly journals Obesity Proteomics: An Update on the Strategies and Tools Employed in the Study of Human Obesity

2018 ◽  
Vol 7 (3) ◽  
pp. 27 ◽  
Author(s):  
Afshan Masood ◽  
Hicham Benabdelkamel ◽  
Assim Alfadda
Keyword(s):  
Mass Spectrometry ◽  
High Throughput ◽  
Large Scale ◽  
Protein Identification ◽  
Biochemical Characterization ◽  
Biological Fluids ◽  
Protein Composition ◽  
Cellular Protein ◽  
Human Obesity ◽  
Two Dimensional Gel Electrophoresis

Proteomics has become one of the most important disciplines for characterizing cellular protein composition, building functional linkages between protein molecules, and providing insight into the mechanisms of biological processes in a high-throughput manner. Mass spectrometry-based proteomic advances have made it possible to study human diseases, including obesity, through the identification and biochemical characterization of alterations in proteins that are associated with it and its comorbidities. A sizeable number of proteomic studies have used the combination of large-scale separation techniques, such as high-resolution two-dimensional gel electrophoresis or liquid chromatography in combination with mass spectrometry, for high-throughput protein identification. These studies have applied proteomics to comprehensive biochemical profiling and comparison studies while using different tissues and biological fluids from patients to demonstrate the physiological or pathological adaptations within their proteomes. Further investigations into these proteome-wide alterations will enable us to not only understand the disease pathophysiology, but also to determine signature proteins that can serve as biomarkers for obesity and related diseases. This review examines the different proteomic techniques used to study human obesity and discusses its successful applications along with its technical limitations.

scholarly journals Biomarker discovery in heterogeneous tissue samples -taking the in-silico deconfounding approach

2010 ◽  
Vol 11 (1) ◽  
Author(s):  
Dirk Repsilber ◽  
Sabine Kern ◽  
Anna Telaar ◽  
Gerhard Walzl ◽  
Gillian F Black ◽  
...  
Keyword(s):  
In Silico ◽  
Biomarker Discovery ◽  
Tissue Samples ◽  
Heterogeneous Tissue

scholarly journals HOPS: Automated detection and authentication of pathogen DNA in archaeological remains

2019 ◽  
Author(s):  
Ron Hübler ◽  
Felix M. Key ◽  
Christina Warinner ◽  
Kirsten I. Bos ◽  
Johannes Krause ◽  
...  
Keyword(s):  
High Throughput ◽  
Ancient Dna ◽  
High Throughput Screening ◽  
Large Scale ◽  
Sequence Data ◽  
Evolutionary Relationship ◽  
Molecular Data ◽  
Clinical Samples ◽  
Archaeological Remains ◽  
Archaeological Material

AbstractHigh-throughput DNA sequencing enables large-scale metagenomic analyses of complex biological systems. Such analyses are not restricted to present day environmental or clinical samples, but can also be fruitfully applied to molecular data from archaeological remains (ancient DNA), and a focus on ancient bacteria can provide valuable information on the long-term evolutionary relationship between hosts and their pathogens. Here we present HOPS (HeuristicOperations forPathogenScreening), an automated bacterial screening pipeline for ancient DNA sequence data that provides straightforward and reproducible information on species identification and authenticity. HOPS provides a versatile and fast pipeline for high-throughput screening of bacterial DNA from archaeological material to identify candidates for subsequent genomic-level analyses.

scholarly journals TissUUmaps: interactive visualization of large-scale spatial gene expression and tissue morphology data

2020 ◽  
Vol 36 (15) ◽  
pp. 4363-4365 ◽  
Author(s):  
Leslie Solorzano ◽  
Gabriele Partel ◽  
Carolina Wählby
Keyword(s):  
Gene Expression ◽  
Large Scale ◽  
Tissue Sample ◽  
Visual Assessment ◽  
Supplementary Information ◽  
Tissue Samples ◽  
Image Pyramids ◽  
Levels Of Detail ◽  
Multiple Resolutions ◽  
Data Points

Abstract Motivation Visual assessment of scanned tissue samples and associated molecular markers, such as gene expression, requires easy interactive inspection at multiple resolutions. This requires smart handling of image pyramids and efficient distribution of different types of data across several levels of detail. Results We present TissUUmaps, enabling fast visualization and exploration of millions of data points overlaying a tissue sample. TissUUmaps can be used both as a web service or locally in any computer, and regions of interest as well as local statistics can be extracted and shared among users. Availability and implementation TissUUmaps is available on github at github.com/wahlby-lab/TissUUmaps. Several demos and video tutorials are available at http://tissuumaps.research.it.uu.se/howto.html. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Shape decomposition algorithms for laser capture microdissection

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Leonie Selbach ◽  
Tobias Kowalski ◽  
Klaus Gerwert ◽  
Maike Buchin ◽  
Axel Mosig
Keyword(s):  
Laser Capture Microdissection ◽  
Biomarker Discovery ◽  
Decomposition Algorithms ◽  
Tissue Samples ◽  
Decomposition Approach ◽  
Shape Decomposition ◽  
Novel Approach ◽  
Algorithmic Framework ◽  
Heterogeneous Tissue ◽  
Laser Capture

Abstract Background In the context of biomarker discovery and molecular characterization of diseases, laser capture microdissection is a highly effective approach to extract disease-specific regions from complex, heterogeneous tissue samples. For the extraction to be successful, these regions have to satisfy certain constraints in size and shape and thus have to be decomposed into feasible fragments. Results We model this problem of constrained shape decomposition as the computation of optimal feasible decompositions of simple polygons. We use a skeleton-based approach and present an algorithmic framework that allows the implementation of various feasibility criteria as well as optimization goals. Motivated by our application, we consider different constraints and examine the resulting fragmentations. We evaluate our algorithm on lung tissue samples in comparison to a heuristic decomposition approach. Our method achieved a success rate of over 95% in the microdissection and tissue yield was increased by 10–30%. Conclusion We present a novel approach for constrained shape decomposition by demonstrating its advantages for the application in the microdissection of tissue samples. In comparison to the previous decomposition approach, the proposed method considerably increases the amount of successfully dissected tissue.

scholarly journals Comparison of Kit-Based Metabolomics with Other Methodologies in a Large Cohort, towards Establishing Reference Values

Metabolites ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. 652
Author(s):  
Daisuke Saigusa ◽  
Eiji Hishinuma ◽  
Naomi Matsukawa ◽  
Masatomo Takahashi ◽  
Jin Inoue ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Tandem Mass Spectrometry ◽  
Reference Values ◽  
Metabolic Profiling ◽  
Large Scale ◽  
Biomarker Discovery ◽  
Tandem Mass ◽  
Reference Ranges ◽  
Lipid Species

Metabolic profiling is an omics approach that can be used to observe phenotypic changes, making it particularly attractive for biomarker discovery. Although several candidate metabolites biomarkers for disease expression have been identified in recent clinical studies, the reference values of healthy subjects have not been established. In particular, the accuracy of concentrations measured by mass spectrometry (MS) is unclear. Therefore, comprehensive metabolic profiling in large-scale cohorts by MS to create a database with reference ranges is essential for evaluating the quality of the discovered biomarkers. In this study, we tested 8700 plasma samples by commercial kit-based metabolomics and separated them into two groups of 6159 and 2541 analyses based on the different ultra-high-performance tandem mass spectrometry (UHPLC-MS/MS) systems. We evaluated the quality of the quantified values of the detected metabolites from the reference materials in the group of 2541 compared with the quantified values from other platforms, such as nuclear magnetic resonance (NMR), supercritical fluid chromatography tandem mass spectrometry (SFC-MS/MS) and UHPLC-Fourier transform mass spectrometry (FTMS). The values of the amino acids were highly correlated with the NMR results, and lipid species such as phosphatidylcholines and ceramides showed good correlation, while the values of triglycerides and cholesterol esters correlated less to the lipidomics analyses performed using SFC-MS/MS and UHPLC-FTMS. The evaluation of the quantified values by MS-based techniques is essential for metabolic profiling in a large-scale cohort.

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