Strategies in Biomarker Discovery. Peak Annotation by MS and Targeted LC-MS Micro-Fractionation for De Novo Structure Identification by Micro-NMR

2013 ◽  
pp. 267-289 ◽  
Author(s):  
Philippe J. Eugster ◽  
Gaëtan Glauser ◽  
Jean-Luc Wolfender
Keyword(s):  
Biomarker Discovery ◽  
De Novo ◽  
Structure Identification ◽  
Peak Annotation

scholarly journals Glycosylation of Cancer Extracellular Vesicles: Capture Strategies, Functional Roles and Potential Clinical Applications

Cells ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 109
Author(s):  
Álvaro M. Martins ◽  
Cátia C. Ramos ◽  
Daniela Freitas ◽  
Celso A. Reis
Keyword(s):  
Extracellular Vesicles ◽  
Biomarker Discovery ◽  
De Novo ◽  
Recipient Cell ◽  
Cell Communication ◽  
Cancer Biomarkers ◽  
Functional Roles ◽  
Molecular Information ◽  
Glycosylation Pathway ◽  
Organ Tropism

Glycans are major constituents of extracellular vesicles (EVs). Alterations in the glycosylation pathway are a common feature of cancer cells, which gives rise to de novo or increased synthesis of particular glycans. Therefore, glycans and glycoproteins have been widely used in the clinic as both stratification and prognosis cancer biomarkers. Interestingly, several of the known tumor-associated glycans have already been identified in cancer EVs, highlighting EV glycosylation as a potential source of circulating cancer biomarkers. These particles are crucial vehicles of cell–cell communication, being able to transfer molecular information and to modulate the recipient cell behavior. The presence of particular glycoconjugates has been described to be important for EV protein sorting, uptake and organ-tropism. Furthermore, specific EV glycans or glycoproteins have been described to be able to distinguish tumor EVs from benign EVs. In this review, the application of EV glycosylation in the development of novel EV detection and capture methodologies is discussed. In addition, we highlight the potential of EV glycosylation in the clinical setting for both cancer biomarker discovery and EV therapeutic delivery strategies.

scholarly journals Analysis of Cerebrospinal Fluid Extracellular Vesicles by Proximity Extension Assay: A Comparative Study of Four Isolation Kits

2020 ◽  
Vol 21 (24) ◽  
pp. 9425
Author(s):  
Sebastian Sjoqvist ◽  
Kentaro Otake ◽  
Yoshihiko Hirozane
Keyword(s):  
Cerebrospinal Fluid ◽  
Extracellular Vesicles ◽  
Proteomic Analysis ◽  
Magnetic Beads ◽  
Biomarker Discovery ◽  
De Novo ◽  
Size Exclusion ◽  
Cell Regulation ◽  
Promising Source ◽  
Proximity Extension Assay

There is a lack of reliable biomarkers for disorders of the central nervous system (CNS), and diagnostics still heavily rely on symptoms that are both subjective and difficult to quantify. The cerebrospinal fluid (CSF) is a promising source of biomarkers due to its close connection to the CNS. Extracellular vesicles are actively secreted by cells, and proteomic analysis of CSF extracellular vesicles (EVs) and their molecular composition likely reflects changes in the CNS to a higher extent compared with total CSF, especially in the case of neuroinflammation, which could increase blood–brain barrier permeability and cause an influx of plasma proteins into the CSF. We used proximity extension assay for proteomic analysis due to its high sensitivity. We believe that this methodology could be useful for de novo biomarker discovery for several CNS diseases. We compared four commercially available kits for EV isolation: MagCapture and ExoIntact (based on magnetic beads), EVSecond L70 (size-exclusion chromatography), and exoEasy (membrane affinity). The isolated EVs were characterized by nanoparticle tracking analysis, ELISA (CD63, CD81 and albumin), and proximity extension assay (PEA) using two different panels, each consisting of 92 markers. The exoEasy samples did not pass the built-in quality controls and were excluded from downstream analysis. The number of detectable proteins in the ExoIntact samples was considerably higher (~150% for the cardiovascular III panel and ~320% for the cell regulation panel) compared with other groups. ExoIntact also showed the highest intersample correlation with an average Pearson’s correlation coefficient of 0.991 compared with 0.985 and 0.927 for MagCapture and EVSecond, respectively. The median coefficient of variation was 5%, 8%, and 22% for ExoIntact, MagCapture, and EVSecond, respectively. Comparing total CSF and ExoIntact samples revealed 70 differentially expressed proteins in the cardiovascular III panel and 17 in the cell regulation panel. To our knowledge, this is the first time that CSF EVs were analyzed by PEA. In conclusion, analysis of CSF EVs by PEA is feasible, and different isolation kits give distinct results, with ExoIntact showing the highest number of identified proteins with the lowest variability.

scholarly journals Metagenomic Noncoding RNA Profiling and Biomarker Discovery

2020 ◽  
Author(s):  
Ben Liu ◽  
Sirisha Thippabhotla ◽  
Jun Zhang ◽  
Cuncong Zhong
Keyword(s):  
Gut Microbiome ◽  
Noncoding Rna ◽  
Biomarker Discovery ◽  
Gene Expression Regulation ◽  
De Novo ◽  
Structural Information ◽  
Noncoding Rnas ◽  
Homology Search ◽  
Metagenomic Sequencing ◽  
Homology Detection

AbstractNoncoding RNA plays important regulatory and functional roles in microorganisms, such as gene expression regulation, signaling, protein synthesis, and RNA processing. Given its essential role in microbial physiology, it is natural to question whether we can use noncoding RNAs as biomarkers to distinguish among environments under different biological conditions, such as those between healthy versus disease status. The current metagenomic sequencing technology primarily generates short reads, which contain incomplete structural information that may complicate noncoding RNA homology detection. On the other hand, de novo assembly of the metagenomics sequencing data remains fragmentary and has a risk of missing low-abundant noncoding RNAs. To tackle these challenges, we have developed DRAGoM (Detection of RNA using Assembly Graph from Metagenomics data), a novel noncoding RNA homology search algorithm. DRAGoM operates on a metagenome assembly graph, rather than on unassembled reads or assembled contigs. Our benchmark experiments show DRAGoM’s improved performance and robustness over the traditional approaches. We have further demonstrated DRAGoM’s real-world applications in disease characterization via analyzing a real case-control gut microbiome dataset for Type-2 diabetes (T2D). DRAGoM revealed potential ncRNA biomarkers that can clearly separate the T2D gut microbiome from those of healthy controls. DRAGoM is freely available from https://github.com/benliu5085/DRAGoM.

scholarly journals exRNA Signatures in Extracellular Vesicles and their Tumor-Lineage from Prostate Cancer

2020 ◽  
Author(s):  
Navneet Dogra ◽  
Mehmet Eren Ahsen ◽  
Edgar Gonzalez Kozlova ◽  
Tzu-yi Chen ◽  
kimaada allette ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Differential Expression ◽  
Extracellular Vesicles ◽  
Small Rna ◽  
Tumor Tissue ◽  
Biomarker Discovery ◽  
De Novo ◽  
Culture Media ◽  
Tumor Resection ◽  
Small Rna Sequencing

Circulating extracellular vesicles (EVs) present in the bodily fluids of patients with cancer may provide non-invasive access to the tumor tissue. Yet, the transcriptomic lineage of tumor-derived EVs before and after tumor-resection remains poorly understood. Here, we established 60 total small RNA-sequencing profiles from 17 aggressive prostate cancer (PCa) patients tumor and adjacent normal tissue, and EVs isolated from urine, serum, and cancer cell culture media. We interrogated the key satellite alteration in tumor-derived EVs and found that resection of tumor prostate tissue leads to differential expression of reactive oxygen species (ROS), P53 pathways, inflammatory/cytokines, oncogenes, and tumor suppressor genes in the EV nanosatellites. Furthermore, we provide a set of novel EV-specific RNA signature, which are present in cancer but are nonexistent in post-resection patients with undetectable cancer. Finally, using a de novo RNAseq assembly followed by characterization of the small RNA landscape, we found novel small RNA clusters (smRCs) in the EVs, which reside in the unannotated regions. Novel smRCs were orthogonally validated for their differential expression in the biomarker discovery cohort using RT-qPCR. We demonstrate that circulating tumor EVs provide a glimpse of the tumor tissue biology, resolving a major bottleneck in the current liquid biopsy efforts. Secretory vesicles appear to be playing a key role in non-canonical Wnt signaling and miRNA pathways, similar to the circulating tumor cells (CTCs), hence, we propose that such vesicles be called circulating tumor extracellular vesicles (CTEVs).

scholarly journals ZODIAC: database-independent molecular formula annotation using Gibbs sampling reveals unknown small molecules

2019 ◽  
Author(s):  
Marcus Ludwig ◽  
Louis-Félix Nothias ◽  
Kai Dührkop ◽  
Irina Koester ◽  
Markus Fleischauer ◽  
...  
Keyword(s):  
Small Molecules ◽  
Gibbs Sampling ◽  
De Novo ◽  
Structure Identification ◽  
Algorithm Engineering ◽  
Molecular Formula ◽  
Tandem Mass Spectra ◽  
Challenging Tasks ◽  
Structure Databases ◽  
Fragmentation Tree

1AbstractThe confident high-throughput identification of small molecules remains one of the most challenging tasks in mass spectrometry-based metabolomics. SIRIUS has become a powerful tool for the interpretation of tandem mass spectra, and shows outstanding performance for identifying the molecular formula of a query compound, being the first step of structure identification. Nevertheless, the identification of both molecular formulas for large compounds above 500 Daltons and novel molecular formulas remains highly challenging. Here, we present ZODIAC, a network-based algorithm for the de novo estimation of molecular formulas. ZODIAC reranks SIRIUS’ molecular formula candidates, combining fragmentation tree computation with Bayesian statistics using Gibbs sampling. Through careful algorithm engineering, ZODIAC’s Gibbs sampling is very swift in practice. ZODIAC decreases incorrect annotations 16.2-fold on a challenging plant extract dataset with most compounds above 700 Dalton; we then show improvements on four additional, diverse datasets. Our analysis led to the discovery of compounds with novel molecular formulas such as C24H47BrNO8P which, as of today, is not present in any publicly available molecular structure databases.

scholarly journals De Novo Transcriptome Assembly and Development of EST-SSR Markers for Pterocarpus Santalinus L. f. (Red sanders) , a Threatened and Endemic Timber Tree of India

2021 ◽  
Author(s):  
Sindhu Agastikumar ◽  
Maheswari Patturaj ◽  
Aghila Samji ◽  
Balasubramanian Aiyer ◽  
Aiswarya Munnusamy ◽  
...  
Keyword(s):  
Ssr Markers ◽  
De Novo ◽  
Transcriptome Assembly ◽  
In Situ Conservation ◽  
Timber Harvest ◽  
Eastern Ghats ◽  
Structure Identification ◽  
Peninsular India ◽  
Pterocarpus Santalinus ◽  
Red Sanders

Abstract The endemic and precious timber Pterocarpus santalinus L. f. (Red sanders) is a drought hardy tree species for conservation in peninsular India due to its high risk of illegal timber harvest. It is only found in Eastern Ghats of India, and has become threatened owing to overexploitation of its valuable timber. The development of genomic resources, particularly simple sequence repeat (SSR) markers, is essential for strict implementation of in situ conservation measures and application of DNA information based red sanders genetic resource management. However, a lack of genomic data and efficient molecular markers limit the study of its spatial and temporal population genetic structure, identification of diversity hotspots and tree improvement. The current study aims at comprehensive molecular characterization of red sanders and the somatic chromosome counts, flow cytometry and EST-SSR analyses. The results revealed that red sanders is diploid with 2n=20 and the 2C genome size was 0.7872 ± 0.0561pg for the first time in this species. A total of 3128 EST-SSRs were detected based on 25,854 de novo assembled unigenes from transcriptome data and primer sets designed for 1953 SSRs. Fifty-nine EST-SSR markers were evaluated for polymorphism in the natural populations of red sanders and 13 were found to be suitable for genetic analysis. Two major transcription factor families bHLH and ERF, responsible for abiotic stress and secondary metabolite synthesis were analysed which would provide the foundation for further research on production of medicinally important biocompounds.

scholarly journals Spec2Mol: An end-to-end deep learning framework for translating MS/MS Spectra to de-novo molecules

2021 ◽  
Author(s):  
Eleni Litsa ◽  
Vijil Chenthamarakshan ◽  
Payel Das ◽  
Lydia Kavraki
Keyword(s):  
Deep Learning ◽  
Mass Spectrum ◽  
Chemical Compound ◽  
Biomarker Discovery ◽  
De Novo ◽  
Reference Database ◽  
Original Structure ◽  
Audio Signals ◽  
Chemical Structures ◽  
Fragmentation Tree

Elucidating the structure of a chemical compound is a fundamental task in chemistry with application in multiple domains including the emerging field of metabolomics, with promising applications in drug discovery, precision medicine, and biomarker discovery. The common practice for elucidating the structure of a chemical compound is to obtain a mass spectrum and subsequently retrieve its structure from spectral databases. However, database retrieval methods fail to identify novel molecules that are not present in the reference database. In this work, we propose Spec2Mol, a deep learning architecture for molecular structure recommendation given mass spectra alone. Spec2Mol is inspired by the Speech2Text deep learning architectures for translating audio signals into text. Our approach is based on an encoder-decoder architecture. The encoder learns the spectra embeddings, while the decoder, pre-trained on a massive dataset of chemical structures for translating between different molecular representations, reconstructs SMILES sequences of the recommended chemical structures. We have evaluated Spec2Mol by assessing the molecular similarity between the recommended structures and the original structure. Our analysis showed that Spec2Mol is able to identify the presence of key substructures in the molecule from its mass spectrum, and shows on par performance, when compared to existing fragmentation tree based methods, in recommending molecules for a given mass spectrum.

scholarly journals Virion Proteins of Kaposi's Sarcoma-Associated Herpesvirus

2005 ◽  
Vol 79 (2) ◽  
pp. 800-811 ◽  
Author(s):  
Fan Xiu Zhu ◽  
Jae Min Chong ◽  
Lijun Wu ◽  
Yan Yuan
Keyword(s):  
Kaposi's Sarcoma ◽  
De Novo ◽  
Polyacrylamide Gel Electrophoresis ◽  
Sodium Dodecyl ◽  
Kaposi’S Sarcoma ◽  
Structure Identification ◽  
Functional Roles ◽  
Tegument Proteins ◽  
Kaposi's Sarcoma Associated Herpesvirus ◽  
Kaposi’S Sarcoma Associated Herpesvirus

ABSTRACT The proteins that compose a herpesvirus virion are thought to contain the functional information required for de novo infection, as well as virion assembly and egress. To investigate functional roles of Kaposi's sarcoma-associated herpesvirus (KSHV) virion proteins in viral productive replication and de novo infection, we attempted to identify virion proteins from purified KSHV by a proteomic approach. Extracellular KSHV virions were purified from phorbol-12-tetradecanoate-13-acetate-induced BCBL-1 cells through double-gradient ultracentrifugation, and their component proteins were resolved by sodium dodecyl sulfate-polyacrylamide gel electrophoresis. Thirty prominent protein bands were excised and subjected to high-performance liquid chromatography ion trap mass spectrometric analysis. This study led to the identification of 24 virion-associated proteins. These include five capsid proteins, eight envelope glycoproteins, six tegument proteins, and five proteins whose locations in the virions have not yet been defined. Putative tegument proteins encoded by open reading frame 21 (ORF21), ORF33, and ORF45 were characterized and found to be resistant to protease digestion when purified virions were treated with trypsin, confirming that they are located within the virion particles. The ORF64-encoded large tegument protein was found to be associated with capsid but sensitive to protease treatment, suggesting its unique structure and array in KSHV virions. In addition, cellular β-actin and class II myosin heavy chain type A were found inside KSHV virions and associated with tegument-capsid structure. Identification of KSHV virion proteins makes it possible to study the functional roles of these virion proteins in KSHV replication and pathogenicity.

scholarly journals Concentration Determination of >200 Proteins in Dried Blood Spots for Biomarker Discovery and Validation

2020 ◽  
Vol 19 (3) ◽  
pp. 540-553 ◽  
Author(s):  
Azad Eshghi ◽  
Adam J. Pistawka ◽  
Jun Liu ◽  
Michael Chen ◽  
Nicholas J. T. Sinclair ◽  
...  
Keyword(s):  
Protein Concentration ◽  
Biomarker Discovery ◽  
De Novo ◽  
Multiple Reaction Monitoring ◽  
Dried Blood Spots ◽  
Cold Chain ◽  
Spectrometric Method ◽  
Mass Spectrometric Method ◽  
Protein Biomarkers ◽  
Limit Of Quantification

The use of protein biomarkers as surrogates for clinical endpoints requires extensive multilevel validation including development of robust and sensitive assays for precise measurement of protein concentration. Multiple reaction monitoring (MRM) is a well-established mass-spectrometric method that can be used for reproducible protein-concentration measurements in biological specimens collected via microsampling. The dried blood spot (DBS) microsampling technique can be performed non-invasively without the expertise of a phlebotomist, and can enhance analyte stability which facilitate the application of this technique in retrospective studies while providing lower storage and shipping costs, because cold-chain logistics can be eliminated. Thus, precise, sensitive, and multiplexed methods for measuring protein concentrations in DBSs can be used for de novo biomarker discovery and for biomarker quantification or verification experiments. To achieve this goal, MRM assays were developed for multiplexed concentration measurement of proteins in DBSs.The lower limit of quantification (LLOQ) was found to have a median total coefficient of variation (CV) of 18% for 245 proteins, whereas the median LLOQ was 5 fmol of peptide injected on column, and the median inter-day CV over 4 days for measuring endogenous protein concentration was 8%. The majority (88%) of the assays displayed parallelism, whereas the peptide standards remained stable throughout the assay workflow and after exposure to multiple freeze-thaw cycles. For 190 proteins, the measured protein concentrations remained stable in DBS stored at ambient laboratory temperature for up to 2 months. Finally, the developed assays were used to measure the concentration ranges for 200 proteins in twenty same sex, same race and age matched individuals.

scholarly journals Isolation and Characterization of Carnocyclin A, a Novel Circular Bacteriocin Produced by Carnobacterium maltaromaticum UAL307

2008 ◽  
Vol 74 (15) ◽  
pp. 4756-4763 ◽  
Author(s):  
Leah A. Martin-Visscher ◽  
Marco J. van Belkum ◽  
Sylvie Garneau-Tsodikova ◽  
Randy M. Whittal ◽  
Jing Zheng ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Molecular Mass ◽  
De Novo ◽  
Structure Identification ◽  
Flight Mass Spectrometry ◽  
Isolation And Characterization ◽  
Circular Bacteriocin ◽  
Ph Range ◽  
Aqueous Conditions ◽  
Carnocyclin A

ABSTRACT Carnobacterium maltaromaticum UAL307, isolated from fresh pork, exhibits potent activity against a number of gram-positive organisms, including numerous Listeria species. Three bacteriocins were isolated from culture supernatant, and using matrix-assisted laser desorption ionization-time of flight mass spectrometry and Edman sequencing, two of these bacteriocins were identified as piscicolin 126 and carnobacteriocin BM1, both of which have previously been described. The remaining bacteriocin, with a molecular mass of 5,862 Da, could not be sequenced by traditional methods, suggesting that the peptide was either cyclic or N-terminally blocked. This bacteriocin showed remarkable stability over a wide temperature and pH range and was unaffected by a variety of proteases. After digestion with trypsin and α-chymotrypsin, the peptide was de novo sequenced by tandem mass spectrometry and a linear sequence deduced, consisting of 60 amino acids. Based on this sequence, the molecular mass was predicted to be 5,880 Da, 18 units higher than the observed molecular mass, which suggested that the peptide has a cyclic structure. Identification of the genetic sequence revealed that this peptide is circular, formed by a covalent linkage between the N and C termini following cleavage of a 4-residue peptide leader sequence. The results of structural studies suggest that the peptide is highly structured in aqueous conditions. This bacteriocin, named carnocyclin A, is the first reported example of a circular bacteriocin produced by Carnobacterium spp.

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