Generating Reliable Genome Assemblies of Intestinal Protozoans from Clinical Samples for the Purpose of Biomarker Discovery

2020 ◽  
pp. 216-241
Author(s):  
Arthur Morris ◽  
Justin Pachebat ◽  
Graeme Tyson ◽  
Guy Robinson ◽  
Rachel Chalmers ◽  
...  
Keyword(s):  
Biomarker Discovery ◽  
Clinical Samples ◽  
Genome Assemblies

scholarly journals From raw reads to trees: Whole genome SNP phylogenetics across the tree of life

2015 ◽  
Author(s):  
Sanaa Afroz Ahmed ◽  
Chien-Chi Lo ◽  
Po-E Li ◽  
Karen W Davenport ◽  
Patrick S.G. Chain
Keyword(s):  
Ad Hoc ◽  
Phylogenetic Reconstruction ◽  
Clinical Samples ◽  
Nucleotide Polymorphisms ◽  
Single Nucleotide ◽  
Complex Samples ◽  
Phylogenetic Characterization ◽  
Genome Wide ◽  
Genome Assemblies

Next-generation sequencing is increasingly being used to examine closely related organisms. However, while genome-wide single nucleotide polymorphisms (SNPs) provide an excellent resource for phylogenetic reconstruction, to date evolutionary analyses have been performed using different ad hoc methods that are not often widely applicable across different projects. To facilitate the construction of robust phylogenies, we have developed a method for genome-wide identification/characterization of SNPs from sequencing reads and genome assemblies. Our phylogenetic and molecular evolutionary (PhaME) analysis software is unique in its ability to take reads and draft/complete genome(s) as input, derive core genome alignments, identify SNPs, construct phylogenies and perform evolutionary analyses. Several examples using genomes and read datasets for bacterial, eukaryotic and viral linages demonstrate the broad and robust functionality of PhaME. Furthermore, the ability to incorporate raw metagenomic reads from clinical samples with suspected infectious agents shows promise for the rapid phylogenetic characterization of pathogens within complex samples.

scholarly journals Gel-Based Proteomics of Clinical Samples Identifies Potential Serological Biomarkers for Early Detection of Colorectal Cancer

2019 ◽  
Vol 20 (23) ◽  
pp. 6082 ◽  
Author(s):  
Stine Thorsen ◽  
Irina Gromova ◽  
Ib Christensen ◽  
Simon Fredriksson ◽  
Claus Andersen ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Early Detection ◽  
Biomarker Discovery ◽  
Real Life ◽  
Clinical Samples ◽  
Plasma Samples ◽  
Healthy Individuals ◽  
Protein Biomarkers ◽  
2D Gel ◽  
Cancer Diseases

The burden of colorectal cancer (CRC) is considerable—approximately 1.8 million people are diagnosed each year with CRC and of these about half will succumb to the disease. In the case of CRC, there is strong evidence that an early diagnosis leads to a better prognosis, with metastatic CRC having a 5-year survival that is only slightly greater than 10% compared with up to 90% for stage I CRC. Clearly, biomarkers for the early detection of CRC would have a major clinical impact. We implemented a coherent gel-based proteomics biomarker discovery platform for the identification of clinically useful biomarkers for the early detection of CRC. Potential protein biomarkers were identified by a 2D gel-based analysis of a cohort composed of 128 CRC and site-matched normal tissue biopsies. Potential biomarkers were prioritized and assays to quantitatively measure plasma expression of the candidate biomarkers were developed. Those biomarkers that fulfilled the preset criteria for technical validity were validated in a case-control set of plasma samples, including 70 patients with CRC, adenomas, or non-cancer diseases and healthy individuals in each group. We identified 63 consistently upregulated polypeptides (factor of four-fold or more) in our proteomics analysis. We selected 10 out of these 63 upregulated polypeptides, and established assays to measure the concentration of each one of the ten biomarkers in plasma samples. Biomarker levels were analyzed in plasma samples from healthy individuals, individuals with adenomas, CRC patients, and patients with non-cancer diseases and we identified one protein, tropomyosin 3 (Tpm3) that could discriminate CRC at a significant level (p = 0.0146). Our results suggest that at least one of the identified proteins, Tpm3, could be used as a biomarker in the early detection of CRC, and further studies should provide unequivocal evidence for the real-life clinical validity and usefulness of Tpm3.

scholarly journals Integrated Analyses of Proteins and Their Glycans in a Magnetic Bead–Based Multiplex Assay Format

2013 ◽  
Vol 59 (1) ◽  
pp. 315-324 ◽  
Author(s):  
Danni Li ◽  
Hanching Chiu ◽  
Jing Chen ◽  
Hui Zhang ◽  
Daniel W Chan
Keyword(s):  
Prostate Cancer ◽  
Magnetic Beads ◽  
Biomarker Discovery ◽  
Magnetic Bead ◽  
Protein Quantification ◽  
Integrated System ◽  
Clinical Samples ◽  
Improved Performance ◽  
Integrated Detection ◽  
Cancer Tissues

BACKGROUND Well-annotated clinical samples are valuable resources for biomarker discovery and validation. Multiplex and integrated methods that simultaneously measure multiple analytes and generate integrated information about these analytes from a single measurement are desirable because these methods help conserve precious samples. We developed a magnetic bead–based system for multiplex and integrated glycoprotein quantification by immunoassays and glycan detection by lectin immunosorbent assays (LISAs). METHODS Magnetic beads coupled with antibodies were used for capturing proteins of interest. Biotinylated antibodies in combination with streptavidin-labeled phycoerythrin were used for protein quantification. In the LISAs, biotinylated detection antibodies were replaced by biotinylated lectins for glycan detection. RESULTS Using tissue inhibitor of metallopeptidase 1 (TIMP-1), tissue plasminogen activator, membrane metallo-endopeptidase, and dipeptidyl peptidase-IV (DPP-4) as models, we found that the multiplex integrated system was comparable to single immunoassays in protein quantification and LISAs in glycan detection. The merits of this system were demonstrated when applied to well-annotated prostate cancer tissues for validation of biomarkers in aggressive prostate cancer. Because of the system's multiplex ability, we used only 300 ng of tissue protein for the integrated detection of glycans in these proteins. Fucosylated TIMP-1 and DPP-4 offered improved performance over the proteins in distinguishing aggressive and nonaggressive prostate cancer. CONCLUSIONS The multiplex and integrated system conserves samples and is a useful tool for validation of glycoproteins and their glycoforms as biomarkers.

scholarly journals PATRI, a Genomics Data Integration Tool for Biomarker Discovery

2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
G. Ukmar ◽  
G. E. M. Melloni ◽  
L. Raddrizzani ◽  
P. Rossi ◽  
S. Di Bella ◽  
...  
Keyword(s):  
Drug Sensitivity ◽  
Biomarker Discovery ◽  
Task Demands ◽  
Ease Of Use ◽  
Clinical Samples ◽  
Precision Oncology ◽  
Analysis Workflow ◽  
Drug Treatments ◽  
Sensitivity Data ◽  
Treatment Sensitivity

The availability of genomic datasets in association with clinical, phenotypic, and drug sensitivity information represents an invaluable source for potential therapeutic applications, supporting the identification of new drug sensitivity biomarkers and pharmacological targets. Drug discovery and precision oncology can largely benefit from the integration of treatment molecular discriminants obtained from cell line models and clinical tumor samples; however this task demands comprehensive analysis approaches for the discovery of underlying data connections. Here we introduce PATRI (Platform for the Analysis of TRanslational Integrated data), a standalone tool accessible through a user-friendly graphical interface, conceived for the identification of treatment sensitivity biomarkers from user-provided genomics data, associated with information on sample characteristics. PATRI streamlines a translational analysis workflow: first, baseline genomics signatures are statistically identified, differentiating treatment sensitive from resistant preclinical models; then, these signatures are used for the prediction of treatment sensitivity in clinical samples, via random forest categorization of clinical genomics datasets and statistical evaluation of the relative phenotypic features. The same workflow can also be applied across distinct clinical datasets. The ease of use of the PATRI tool is illustrated with validation analysis examples, performed with sensitivity data for drug treatments with known molecular discriminants.

scholarly journals Proteomics in Liver Transplantation: A Systematic Review

2021 ◽  
Vol 12 ◽  
Author(s):  
Victor López-López ◽  
Fernando Pérez-Sánz ◽  
Carlos de Torre-Minguela ◽  
Josefa Marco-Abenza ◽  
Ricardo Robles-Campos ◽  
...  
Keyword(s):  
Liver Transplantation ◽  
Molecular Mechanisms ◽  
Biomarker Discovery ◽  
Dynamic Range ◽  
Ischemia Reperfusion Injury ◽  
Ischemia Reperfusion ◽  
Differential Expression Analysis ◽  
Clinical Samples ◽  
Large Numbers ◽  
Meta Analyses

BackgroundAlthough proteomics has been employed in the study of several models of liver injury, proteomic methods have only recently been applied not only to biomarker discovery and validation but also to improve understanding of the molecular mechanisms involved in transplantation.MethodsThe study was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology and the guidelines for performing systematic literature reviews in bioinformatics (BiSLR). The PubMed, ScienceDirect, and Scopus databases were searched for publications through April 2020. Proteomics studies designed to understand liver transplant outcomes, including ischemia-reperfusion injury (IRI), rejection, or operational tolerance in human or rat samples that applied methodologies for differential expression analysis were considered.ResultsThe analysis included 22 studies after application of the inclusion and exclusion criteria. Among the 497 proteins annotated, 68 were shared between species and 10 were shared between sample sources. Among the types of studies analyzed, IRI and rejection shared a higher number of proteins. The most enriched pathway for liver biopsy samples, IRI, and rejection was metabolism, compared to cytokine-cytokine receptor interactions for tolerance.ConclusionsProteomics is a promising technique to detect large numbers of proteins. However, our study shows that several technical issues such as the identification of proteoforms or the dynamic range of protein concentration in clinical samples hinder the successful identification of biomarkers in liver transplantation. In addition, there is a need to minimize the experimental variability between studies, increase the sample size and remove high-abundance plasma proteins.

scholarly journals Systematic evaluation of multiple qPCR platforms, NanoString and miRNA-Seq for microRNA biomarker discovery in human biofluids

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Lewis Z. Hong ◽  
Lihan Zhou ◽  
Ruiyang Zou ◽  
Chin Meng Khoo ◽  
Adeline Lai San Chew ◽  
...  
Keyword(s):  
Biomarker Discovery ◽  
Treatment Options ◽  
Systematic Evaluation ◽  
Clinical Samples ◽  
Early Detection Of Disease ◽  
Non Invasive ◽  
Extracellular Mirnas ◽  
Cross Platform ◽  
Reference Samples ◽  
Selection Of

AbstractAberrant miRNA expression has been associated with many diseases, and extracellular miRNAs that circulate in the bloodstream are remarkably stable. Recently, there has been growing interest in identifying cell-free circulating miRNAs that can serve as non-invasive biomarkers for early detection of disease or selection of treatment options. However, quantifying miRNA levels in biofluids is technically challenging due to their low abundance. Using reference samples, we performed a cross-platform evaluation in which miRNA profiling was performed on four different qPCR platforms (MiRXES, Qiagen, Applied Biosystems, Exiqon), nCounter technology (NanoString), and miRNA-Seq. Overall, our results suggest that using miRNA-Seq for discovery and targeted qPCR for validation is a rational strategy for miRNA biomarker development in clinical samples that involve limited amounts of biofluids.

scholarly journals Detection of Aberrant Glycosylation of Serum Haptoglobin for Gastric Cancer Diagnosis Using a Middle-Up-Down Glycoproteome Platform

2021 ◽  
Vol 11 (6) ◽  
pp. 575
Author(s):  
Seunghyup Jeong ◽  
Unyong Kim ◽  
Myungjin Oh ◽  
Jihyeon Nam ◽  
Sehoon Park ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Biomarker Discovery ◽  
High Reliability ◽  
Clinical Samples ◽  
Efficient Tool ◽  
Diagnostic Efficacy ◽  
Aberrant Glycosylation ◽  
Serum Haptoglobin ◽  
Gastric Cancer Patients ◽  
Glycan Heterogeneity

Gastric cancer is a frequently occurring cancer and is the leading cause of cancer-related deaths. Recent studies have shown that aberrant glycosylation of serum haptoglobin is closely related to gastric cancer and has enormous potential for use in diagnosis. However, there is no platform with high reliability and high reproducibility to comprehensively analyze haptoglobin glycosylation covering microheterogeneity to macroheterogeneity for clinical applications. In this study, we developed a middle-up-down glycoproteome platform for fast and accurate monitoring of haptoglobin glycosylation. This platform utilizes an online purification of LC for sample desalting, and an in silico haptoglobin glycopeptide library constructed by combining peptides and N-glycans to readily identify glycopeptides. In addition, site-specific glycosylation with glycan heterogeneity can be obtained through only a single MS analysis. Haptoglobin glycosylation in clinical samples consisting of healthy controls (n = 47) and gastric cancer patients (n = 43) was extensively investigated using three groups of tryptic glycopeptides: GP1 (including Asn184), GP2 (including Asn207 and Asn211), and GP3 (including Asn241). A total of 23 individual glycopeptides were determined as potential biomarkers (p < 0.00001). In addition, to improve diagnostic efficacy, we derived representative group biomarkers with high AUC values (0.929 to 0.977) through logistic regression analysis for each GP group. It has been found that glycosylation of haptoglobin is highly associated with gastric cancer, especially the glycosite Asn241. Our assay not only allows to quickly and easily obtain information on glycosylation heterogeneity of a target glycoprotein but also makes it an efficient tool for biomarker discovery and clinical diagnosis.

A new strategy for protein biomarker discovery utilizing 2-nitrobenzenesulfenyl (NBS) reagent and its applications to clinical samples

2009 ◽  
Vol 877 (25) ◽  
pp. 2607-2614 ◽  
Author(s):  
Ei-ichi Matsuo ◽  
Makoto Watanabe ◽  
Hiroki Kuyama ◽  
Osamu Nishimura
Keyword(s):  
Biomarker Discovery ◽  
Clinical Samples ◽  
Protein Biomarker ◽  
New Strategy
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