Standardization and omics science: technical and social dimensions are inseparable and demand symmetrical study

Influence of plasma collection tubes on N-glycome in human blood samples

Background and aims

Quantitative analysis of plasma N-glycome is a promising method for identifying disease biomarkers. This study aimed to investigate the impact of using blood collection tubes with different anticoagulants on plasma N-glycome.

Materials and methods

We used a robust mass spectrometry method to profile plasma N-glycomes in two cohorts of healthy volunteers (cohort 1, n = 16; cohort 2, n = 53). The influence of three commonly used blood collection tubes on fully characterized N-glycomic profiles were explored.

Results

Principal component analysis revealed distinct clustering of blood samples based on the collection tubes. Pairwise comparisons demonstrated significant differences between EDTA and heparin plasma in 55 out of 82 quantified N-glycan traits, and between EDTA and citrate plasma in 62 out of 82 traits. These differences encompassed various N-glycan features, including glycan type, sialylation, galactosylation, fucosylation, and bisection. Trends in N-glycan variations in citrate and heparin plasma were largely consistent compared to EDTA plasma. In correlation analysis (EDTA vs. heparin; EDTA vs. citrate), Pearson's correlation coefficients were consistently higher than 0.7 for the majority of N-glycan traits.

Conclusion

Sample matrix variations impact plasma N-glycome measurements. Caution is crucial when comparing samples from different plasma collection tubes in glycomics projects.

The ethical aspects of exposome research: a systematic review

In recent years, exposome research has been put forward as the next frontier for the study of human health and disease. Exposome research entails the analysis of the totality of environmental exposures and their corresponding biological responses within the human body. Increasingly, this is operationalized by big-data approaches to map the effects of internal as well as external exposures using smart sensors and multiomics technologies. However, the ethical implications of exposome research are still only rarely discussed in the literature. Therefore, we conducted a systematic review of the academic literature regarding both the exposome and underlying research fields and approaches, to map the ethical aspects that are relevant to exposome research. We identify five ethical themes that are prominent in ethics discussions: the goals of exposome research, its standards, its tools, how it relates to study participants, and the consequences of its products. Furthermore, we provide a number of general principles for how future ethics research can best make use of our comprehensive overview of the ethical aspects of exposome research. Lastly, we highlight three aspects of exposome research that are most in need of ethical reflection: the actionability of its findings, the epidemiological or clinical norms applicable to exposome research, and the meaning and action-implications of bias.

Omics technologies in allergy and asthma research: An EAACI position paper

Allergic diseases and asthma are heterogenous chronic inflammatory conditions with several distinct complex endotypes. Both environmental and genetic factors can influence the development and progression of allergy. Complex pathogenetic pathways observed in allergic disorders present a challenge in patient management and successful targeted treatment strategies. The increasing availability of high-throughput omics technologies, such as genomics, epigenomics, transcriptomics, proteomics, and metabolomics allows studying biochemical systems and pathophysiological processes underlying allergic responses. Additionally, omics techniques present clinical applicability by functional identification and validation of biomarkers. Therefore, finding molecules or patterns characteristic for distinct immune-inflammatory endotypes, can subsequently influence its development, progression, and treatment. There is a great potential to further increase the effectiveness of single omics approaches by integrating them with other omics, and nonomics data. Systems biology aims to simultaneously and longitudinally understand multiple layers of a complex and multifactorial disease, such as allergy, or asthma by integrating several, separated data sets and generating a complete molecular profile of the condition. With the use of sophisticated biostatistics and machine learning techniques, these approaches provide in-depth insight into individual biological systems and will allow efficient and customized healthcare approaches, called precision medicine. In this EAACI Position Paper, the Task Force "Omics technologies in allergic research" broadly reviewed current advances and applicability of omics techniques in allergic diseases and asthma research, with a focus on methodology and data analysis, aiming to provide researchers (basic and clinical) with a desk reference in the field. The potential of omics strategies in understanding disease pathophysiology and key tools to reach unmet needs in allergy precision medicine, such as successful patients' stratification, accurate disease prognosis, and prediction of treatment efficacy and successful prevention measures are highlighted.

Standardized pyrogen testing of medical products with the bacterial endotoxin test (BET) as a substitute for rabbit Pyrogen testing (RPT): A scoping review

The Bacterial Endotoxin Test (BET) is a method for exclusion of endotoxin-related pyrogen contamination in pharmaceutical products, as an alternative to the Rabbit Pyrogen Test (RPT). However, BET does not detect a broad range of biologically relevant pyrogens, and interferences can limit its practical use for different medical products. This work aimed to scope the evidence in the scientific literature for case-by-case validity assessments of BET in different uses for medical products. A search strategy was conducted in PubMed, Scopus, and Web of Science in April 2020, according to the PRISMA-ScR statement. Twenty-two references were included, evaluating medical products for endotoxin contamination through both BET and RPT according to standardized protocols. A critical appraisal was performed through ToxRTool, followed by data extraction and qualitative synthesis of outcomes and methodological issues. Four classes of products assessed by BET were identified, including nanoparticles, drugs, blood and biological products. A considerable variation was observed on the BET methods used. Collectively, the evidence indicates different factors influencing the outcome of BET, including the chemical nature of samples that may cause interference depending on the selected method. While some applications to medical products appear adequate, others, such as nanoparticles, may require the use of different in vitro pyrogen testing methods, reinforcing the need for case-by-case validation for each BET method and type of medical product.

Having Our “Omic” Cake and Eating It Too?: Evaluating User Response to Using Blockchain Technology for Private and Secure Health Data Management and Sharing

This paper reports on end users' perspectives on the use of a blockchain solution for private and secure individual “omics” health data management and sharing. This solution is one output of a multidisciplinary project investigating the social, data, and technical issues surrounding application of blockchain technology in the context of personalized healthcare research. The project studies potential ethical, legal, social, and cognitive constraints of self-sovereign healthcare data management and sharing, and whether such constraints can be addressed through careful design of a blockchain solution.

Reproducibility of animal research in light of biological variation

Context-dependent biological variation presents a unique challenge to the reproducibility of results in experimental animal research, because organisms' responses to experimental treatments can vary with both genotype and environmental conditions. In March 2019, experts in animal biology, experimental design and statistics convened in Blonay, Switzerland, to discuss strategies addressing this challenge. In contrast to the current gold standard of rigorous standardization in experimental animal research, we recommend the use of systematic heterogenization of study samples and conditions by actively incorporating biological variation into study design through diversifying study samples and conditions. Here we provide the scientific rationale for this approach in the hope that researchers, regulators, funders and editors can embrace this paradigm shift. We also present a road map towards better practices in view of improving the reproducibility of animal research.

Microbial resolution of whole genome shotgun and 16S amplicon metagenomic sequencing using publicly available NEON data

Microorganisms are ubiquitous in the biosphere, playing a crucial role in both biogeochemistry of the planet and human health. However, identifying these microorganisms and defining their function are challenging. Widely used approaches in comparative metagenomics, 16S amplicon sequencing and whole genome shotgun sequencing (WGS), have provided access to DNA sequencing analysis to identify microorganisms and evaluate diversity and abundance in various environments. However, advances in parallel high-throughput DNA sequencing in the past decade have introduced major hurdles, namely standardization of methods, data storage, reproducible interoperability of results, and data sharing. The National Ecological Observatory Network (NEON), established by the National Science Foundation, enables all researchers to address queries on a regional to continental scale around a variety of environmental challenges and provide high-quality, integrated, and standardized data from field sites across the U.S. As the amount of metagenomic data continues to grow, standardized procedures that allow results across projects to be assessed and compared is becoming increasingly important in the field of metagenomics. We demonstrate the feasibility of using publicly available NEON soil metagenomic sequencing datasets in combination with open access Metagenomics Rapid Annotation using the Subsystem Technology (MG-RAST) server to illustrate advantages of WGS compared to 16S amplicon sequencing. Four WGS and four 16S amplicon sequence datasets, from surface soil samples prepared by NEON investigators, were selected for comparison, using standardized protocols collected at the same locations in Colorado between April-July 2014. The dominant bacterial phyla detected across samples agreed between sequencing methodologies. However, WGS yielded greater microbial resolution, increased accuracy, and allowed identification of more genera of bacteria, archaea, viruses, and eukaryota, and putative functional genes that would have gone undetected using 16S amplicon sequencing. NEON open data will be useful for future studies characterizing and quantifying complex ecological processes associated with changing aquatic and terrestrial ecosystems.

A Perspective on Brain-Gut Communication: The American Gastroenterology Association and American Psychosomatic Society Joint Symposium on Brain-Gut Interactions and the Intestinal Microenvironment

BACKGROUND

Alterations in brain-gut communication and the intestinal microenvironment have been implicated in a variety of medical and neuropsychiatric diseases. Three central areas require basic and clinical research: (1) how the intestinal microenvironment interacts with the host immune system, central nervous system, and enteric nervous system; (2) the role of the intestinal microenvironment in the pathogenesis of medical and neuropsychiatric disease; and (3) the effects of diet, prebiotics, probiotics, and fecal microbiota transplantation on the intestinal microenvironment and the treatment of disease.

METHODS

This review article is based on a symposium convened by the American Gastroenterology Association and the American Psychosomatic Society to foster interest in the role of the intestinal microenvironment in brain-gut communication and pathogenesis of neuropsychiatric and biopsychosocial disorders. The aims were to define the state of the art of the current scientific knowledge base and to identify guidelines and future directions for new research in this area.

RESULTS

This review provides a characterization of the intestinal microbial composition and function. We also provide evidence for the interactions between the intestinal microbiome, the host, and the environment. The role of the intestinal microbiome in medical and neuropsychiatric diseases is reviewed as well as the treatment effects of manipulation of the intestinal microbiome.

CONCLUSIONS

Based on this review, opportunities and challenges for conducting research in the field are described, leading to potential avenues for future research.

Metabolomics in toxicology and preclinical research

Metabolomics, the comprehensive analysis of metabolites in a biological system, provides detailed information about the biochemical/physiological status of a biological system, and about the changes caused by chemicals. Metabolomics analysis is used in many fields, ranging from the analysis of the physiological status of genetically modified organisms in safety science to the evaluation of human health conditions. In toxicology, metabolomics is the -omics discipline that is most closely related to classical knowledge of disturbed biochemical pathways. It allows rapid identification of the potential targets of a hazardous compound. It can give information on target organs and often can help to improve our understanding regarding the mode-of-action of a given compound. Such insights aid the discovery of biomarkers that either indicate pathophysiological conditions or help the monitoring of the efficacy of drug therapies. The first toxicological applications of metabolomics were for mechanistic research, but different ways to use the technology in a regulatory context are being explored. Ideally, further progress in that direction will position the metabolomics approach to address the challenges of toxicology of the 21st century. To address these issues, scientists from academia, industry, and regulatory bodies came together in a workshop to discuss the current status of applied metabolomics and its potential in the safety assessment of compounds. We report here on the conclusions of three working groups addressing questions regarding 1) metabolomics for in vitro studies 2) the appropriate use of metabolomics in systems toxicology, and 3) use of metabolomics in a regulatory context.

NeuPAT: an intranet database supporting translational research in neuroblastic tumors

Translational research in oncology is directed mainly towards establishing a better risk stratification and searching for appropriate therapeutic targets. This research generates a tremendous amount of complex clinical and biological data needing speedy and effective management. The authors describe the design, implementation and early experiences of a computer-aided system for the integration and management of data for neuroblastoma patients. NeuPAT facilitates clinical and translational research, minimizes the workload in consolidating the information, reduces errors and increases correlation of data through extensive coding. This design can also be applied to other tumor types.

Omics strategies for revealing Yersinia pestis virulence

Omics has remarkably changed the way we investigate and understand life. Omics differs from traditional hypothesis-driven research because it is a discovery-driven approach. Mass datasets produced from omics-based studies require experts from different fields to reveal the salient features behind these data. In this review, we summarize omics-driven studies to reveal the virulence features of Yersinia pestis through genomics, trascriptomics, proteomics, interactomics, etc. These studies serve as foundations for further hypothesis-driven research and help us gain insight into Y. pestis pathogenesis.

Bioinformatics Tools for Mass Spectroscopy-Based Metabolomic Data Processing and Analysis

Biological systems are increasingly being studied in a holistic manner, using omics approaches, to provide quantitative and qualitative descriptions of the diverse collection of cellular components. Among the omics approaches, metabolomics, which deals with the quantitative global profiling of small molecules or metabolites, is being used extensively to explore the dynamic response of living systems, such as organelles, cells, tissues, organs and whole organisms, under diverse physiological and pathological conditions. This technology is now used routinely in a number of applications, including basic and clinical research, agriculture, microbiology, food science, nutrition, pharmaceutical research, environmental science and the development of biofuels. Of the multiple analytical platforms available to perform such analyses, nuclear magnetic resonance and mass spectrometry have come to dominate, owing to the high resolution and large datasets that can be generated with these techniques. The large multidimensional datasets that result from such studies must be processed and analyzed to render this data meaningful. Thus, bioinformatics tools are essential for the efficient processing of huge datasets, the characterization of the detected signals, and to align multiple datasets and their features. This paper provides a state-of-the-art overview of the data processing tools available, and reviews a collection of recent reports on the topic. Data conversion, pre-processing, alignment, normalization and statistical analysis are introduced, with their advantages and disadvantages, and comparisons are made to guide the reader.