The effect of liquid-liquid extraction on metabolite detection and analysis using NMR spectroscopy in human synovial fluid.

The evaluation of joint disease using synovial fluid is an emerging field of metabolic profiling. The analysis is challenged by multiple macromolecules which can obscure the small molecule chemistry. The use of protein precipitation and extraction has been evaluated previously, but not in synovial fluid. We systematically review the published NMR spectroscopy methods of synovial fluid analysis and investigated the efficacy of three different protein precipitation techniques: methanol, acetonitrile and trichloroacetic acid. The trichloroacetic wash removed the most protein. However, metabolite recoveries were universally very poor. Acetonitrile liquid/liquid extraction gave metabolite gains from four unknown compounds with spectral peaks at δ = 1.91 ppm, 3.64 ppm, 3.95 ppm & 4.05 ppm. The metabolite recoveries for acetonitrile were between 1.5 and 7 times higher than the methanol method, across all classes of metabolite. The methanol method was more effective in removing protein as reported by the free GAG undefined peak (44 % vs 125 %). However, qualitative evaluation showed that acetonitrile and methanol provided good restoration of the spectra to baseline. The methanol extraction has issues of a gelatinous substrate in the samples. All metabolite recoveries had a CV of > 15 %. A recommendation of acetonitrile liquid/liquid extraction was made for human synovial fluid (HSF) analysis. This is due to consistency, effective protein precipitation, recovery of metabolites and additional compounds not previously visible.

Using a Secure, Continually Updating, Web Source Processing Pipeline to Support the Real-Time Data Synthesis and Analysis of Scientific Literature: Development and Validation Study.

BACKGROUND: The scale and quality of the global scientific response to the COVID-19 pandemic have unquestionably saved lives. However, the COVID-19 pandemic has also triggered an unprecedented "infodemic"; the velocity and volume of data production have overwhelmed many key stakeholders such as clinicians and policy makers, as they have been unable to process structured and unstructured data for evidence-based decision making. Solutions that aim to alleviate this data synthesis-related challenge are unable to capture heterogeneous web data in real time for the production of concomitant answers and are not based on the high-quality information in responses to a free-text query. OBJECTIVE: The main objective of this project is to build a generic, real-time, continuously updating curation platform that can support the data synthesis and analysis of a scientific literature framework. Our secondary objective is to validate this platform and the curation methodology for COVID-19-related medical literature by expanding the COVID-19 Open Research Dataset via the addition of new, unstructured data. METHODS: To create an infrastructure that addresses our objectives, the PanSurg Collaborative at Imperial College London has developed a unique data pipeline based on a web crawler extraction methodology. This data pipeline uses a novel curation methodology that adopts a human-in-the-loop approach for the characterization of quality, relevance, and key evidence across a range of scientific literature sources. RESULTS: REDASA (Realtime Data Synthesis and Analysis) is now one of the world's largest and most up-to-date sources of COVID-19-related evidence; it consists of 104,000 documents. By capturing curators' critical appraisal methodologies through the discrete labeling and rating of information, REDASA rapidly developed a foundational, pooled, data science data set of over 1400 articles in under 2 weeks. These articles provide COVID-19-related information and represent around 10% of all papers about COVID-19. CONCLUSIONS: This data set can act as ground truth for the future implementation of a live, automated systematic review. The three benefits of REDASA's design are as follows: (1) it adopts a user-friendly, human-in-the-loop methodology by embedding an efficient, user-friendly curation platform into a natural language processing search engine; (2) it provides a curated data set in the JavaScript Object Notation format for experienced academic reviewers' critical appraisal choices and decision-making methodologies; and (3) due to the wide scope and depth of its web crawling method, REDASA has already captured one of the world's largest COVID-19-related data corpora for searches and curation.

The influence of sample collection, handling and low temperature storage upon NMR metabolic profiling analysis in human synovial fluid.

The impact of metabolism upon the altered pathology of joint disease is rapidly becoming recognized as an important area of study. Synovial joint fluid is an attractive and representative biofluid of joint disease. A systemic review revealed little evidence of the metabolic stability of synovial joint fluid collection, handling or storage, despite recent reports characterizing the metabolic phenotype in joint disease. We aim to report the changes in small molecule detection within human synovial fluid (HSF) using nuclear magnetic resonance (NMR) spectroscopy at varying storage temperatures, durations and conditions. HSF was harvested by arthrocentesis from patients with isolated monoarthropathy or undergoing joint replacement (n = 30). Short-term storage (0-12 h, 4°C & 18°C) and the effect of repeated freeze-thaw cycles (-80°C to 18°C) was assessed. Long-term storage was evaluated by early (-80°C, <21days) and late analysis (-80°C, 10-12 months). 1D NMR spectroscopy experiments, NOESYGPPR1D and CPMG identified metabolites and semi-quantification was performed. Samples demonstrated broad stability to freeze-thaw cycling and refrigeration of <4 h. Short-term room temperature or refrigerated storage showed significant variation in 2-ketoisovalerate, valine, dimethylamine, succinate, 2-hydroxybutyrate, and acetaminophen glucuronide. Lipid and macromolecule detection was variable. Long-term storage demonstrated significant changes in: acetate, acetoacetate, creatine, N,N-dimethylglycine, dimethylsulfone, 3-hydroxybutyrate and succinate. Changeable metabolites during short-term storage appeared to be energy-synthesis intermediates. Most metabolites were stable for the first four hours at room temperature or refrigeration, with notable exceptions. We therefore recommend that HSF samples should be kept refrigerated for no more than 4 hours prior to freezing at -80°C. Furthermore, storage of HSF samples for 10-12 months before analysis can affect the detection of selected metabolites.

Differences between infected and noninfected synovial fluid.

AIMS: The diagnosis of joint infections is an inexact science using combinations of blood inflammatory markers and microscopy, culture, and sensitivity of synovial fluid (SF). There is potential for small molecule metabolites in infected SF to act as infection markers that could improve accuracy and speed of detection. The objective of this study was to use nuclear magnetic resonance (NMR) spectroscopy to identify small molecule differences between infected and noninfected human SF. METHODS: In all, 16 SF samples (eight infected native and prosthetic joints plus eight noninfected joints requiring arthroplasty for end-stage osteoarthritis) were collected from patients. NMR spectroscopy was used to analyze the metabolites present in each sample. Principal component analysis and univariate statistical analysis were undertaken to investigate metabolic differences between the two groups. RESULTS: A total of 16 metabolites were found in significantly different concentrations between the groups. Three were in higher relative concentrations (lipids, cholesterol, and N-acetylated molecules) and 13 in lower relative concentrations in the infected group (citrate, glycine, glycosaminoglycans, creatinine, histidine, lysine, formate, glucose, proline, valine, dimethylsulfone, mannose, and glutamine). CONCLUSION: Metabolites found in significantly greater concentrations in the infected cohort are markers of inflammation and infection. They play a role in lipid metabolism and the inflammatory response. Those found in significantly reduced concentrations were involved in carbohydrate metabolism, nucleoside metabolism, the glutamate metabolic pathway, increased oxidative stress in the diseased state, and reduced articular cartilage breakdown. This is the first study to demonstrate differences in the metabolic profile of infected and noninfected human SF, using a noninfected matched cohort, and may represent putative biomarkers that form the basis of new diagnostic tests for infected SF. Cite this article: Bone Joint Res 2021;10(1):85-95.