206 research outputs found
Computational Metabolomics: From Spectra to Knowledge (Dagstuhl Seminar 22181)
No full textThe fourth edition of the Computational Metabolomics seminars, Dagstuhl Seminar 22181, brought together a wide range of computational and experimental experts to share state-of-the art methodologies and push our collective understanding of how to interpret and maximise insight of metabolomic data. With increasing amounts of metabolomic data being generated, including large-scale epidemiological studies, and increasing sensitivity of instrumentation, development of sophisticated and robust computational solutions is required. Further, community agreement on which data standards should be used and which data sets are most apt for benchmarking computational tools is needed in the field. Building upon the previous successful formats of previous seminars (17491, 15492, and 20051) on this topic, attendees gathered each morning to collectively agree on the number of sessions and topics to discuss. A summary of the daily sessions were shared amongst all participants after dinner during each day’s final formal session. Further, informal evening sessions were spontaneously created to further dive into specific topics. As with past seminars, this format was very well received and enabled all participants to weigh in. Of particular note, this seminar was delayed and travel was complicated due to the pandemic. Despite these setbacks, this seminar brought together a balanced number of previous and new, seasoned and early career participants. All participants were active in these discussions, and a true sense of renewed energy ensued from the seminar. This report provides highlights of formal and informal evening sessions, including future anticipated research directions rooted from this seminar. Possible future workshops, such as a next phase of this Computational Metabolomics Dagstuhl seminar in late 2023 or 2024 were also discussed and will be applied for
Computational Metabolomics: From Cheminformatics to Machine Learning (Dagstuhl Seminar 20051)
No full textDagstuhl Seminar 20051 on Computational Metabolomics is the third edition of seminars onthis topic and focused on Cheminformatics and Machine Learning. With the advent of higherprecision instrumentation, application of metabolomics to a wider variety of small molecules, andever increasing amounts of raw and processed data available, developments in cheminformaticsand machine learning are sorely needed to facilitate interoperability and leverage further insightsfrom these data. Following on from Seminars 17491 and 15492, this edition convened bothexperimental and computational experts, many of whom had attended the previous sessions andbrought much-valued perspective to the week’s proceedings and discussions. Throughout theweek, participants first debated on what topics to discuss in detail, before dispersing into smaller,focused working groups for more in-depth discussions. This dynamic format was found to bemost productive and ensured active engagement amongst the participants. The abstracts inthis report reflect these working group discussions, in addition to summarising several informalevening sessions. Action points to follow-up on after the seminar were also discussed, includingfuture workshops and possibly another Dagstuhl seminar in late 2021 or 2022
RAMSearchShare
No full textThis project hosts the RAMSearch Program, a tutorial document, and 1-SToP libraries generated in the [original publication][1
RAMSearchShare
No full textThis project hosts the RAMSearch Program, a tutorial document, and 1-SToP libraries generated in the [original publication][1
The role of olfaction in host-finding by two specialist predators of hemlock woolly adelgid
No full textThe hemlock woolly adelgid (HWA), Adelges tsugae Annand (Homoptera: Adelgidae), is forest pest introduced to eastern North America in the early 1950's. Although this pest occurs on both landscape and nursery stock as well as in natural stands of hemlock forest, pesticides are only practical and effective in urban settings. Ecological and economical considerations prevent utilization of chemical treatment in the forest setting, thus biological control is viewed as the most promising option for slowing the spread of HWA. It is essential for researchers to be able to accurately assess the population levels of biocontrol agents after release into the environment. No method currently exists for sampling HWA predators. This project was designed to determine whether two species of predators are able to utilize olfactory cues from eastern hemlock and/or HWA in host-finding. If predators use olfactory cues, we may develop an attractive sythnetic blend of compounds to draw them to a trap, thereby simplifying the sampling and improving its accuracy. To address this question we executed three experiments. The first involved examination of the antennae of the predators for the presence and abundance of olfactory sensilla. The second experiment was designed to detect a behavioral response by the predators following exposure to host volatile compounds. The final experiment involved identifying compounds emitted from eastern hemlock, and the affect of HWA-feeding on volatile emissions.
Laricobius nigrinus Fender (Coleoptera: Derodontidae) antennae are densely populated with sensilla, several of which are potentially olfactory in function. In addition, we observed a behavioral response to olfactory cues which included altered flight behavior. However, the behavior was not clearly attraction. Pseudoscymnus tsugae Sasaji and McClure (Coleoptera: Coccinellidae) has few sensilla on a very short antennae and only one type of sensilla possesses wall pores suggestive of an olfactory function. In addition, we did not observe a significant behavioral response to host-volatiles. It seems unlikely that this species uses olfaction in long-range host location. We identified 10 monoterpenes that were consistently expressed in the hemlock volatile profile and were unable to isolate volatile emissions from HWA. There is an increased monoterpene release rate from HWA-infested hemlock foliage as compared to uninfested foliage apparently driven indirectly by HWA through a reduction in new growth at branch tips. In addition there was a slight but statistically significant change in the percent composition of the individual compounds.
We see potential in developing a more efficient sampling procedure for L. nigrinus through utilization of olfactory cues. More biological assays must be conducted to determine whether an attractive blend exists and electrophysiological assays are required to isolate physiologically active compounds. However, our data suggest that P. tsugae is not likely to be reliant on olfaction in long-range host location.Master of Scienc
Modeling and data analysis of emergent properties in different biological systems
No full textBiological systems exhibit a wide array of rich and diverse emergent phenomena, resulting from the intricate modulation of interactions between their components. This modulation can involve changes in both the strength and nature of interactions, leading to complex behaviors and properties. To gain insights into these complex phenomena, various computational and modeling approaches are employed to decipher experimental observations and allow for a deeper understanding of the underlying mechanisms at play. This thesis aims to explore emergent properties in Neuroscience and Microbiology. In Neuroscience, connections between neurons are known to store memories, although it is not clear how. To investigate how memory forms and changes with learning locally between neurons, I proposed a novel molecular mechanism of temporal learning in the Cerebellum part of the brain and validated it using mathematical models. My investigations aimed to shed light on the fundamental processes that lie at the core of learning and cognitive function, providing a deeper understanding of how our brains acquire and learn from experiences. In Microbiology, the behavior of microbes is closely linked to their metabolism, which is often constructed from the genome sequence using algorithmic genetic annotation pipelines. However, these methods can leave gaps in the metabolic network, leading to incorrect interpretations of a pathogen’s metabolic capabilities and hindering therapeutic interventions. To address this, I developed the MINNO network analysis web application, which allows one to identify gaps and explore potential targets for drugs. As microorganisms continue to develop resistance to existing drugs, the need for novel drugs and therapeutic targets becomes increasingly pressing. Moreover, determining the targets of these novel drugs is crucial yet challenging. I addressed this issue using metabolic fingerprinting, which can classify known antibiotics based on the metabolic phenotype they induce in Escherichia coli. Additionally, I formulated an extension of kinetic flux profiling for perturbed cases to gain insights into cellular responses to antibiotics or other stresses in general. Due to their versatility and general applicability, both the MINNO and perturbed kinetic flux profiling are anticipated to enable novel insights into microbial metabolism and various complex biological phenomena observed in nature
Assessing Drought and Heat Stress-Induced Changes in the Cotton Leaf Metabolome and Their Relationship With Hyperspectral Reflectance
No full textThe study of phenotypes that reveal mechanisms of adaptation to drought and heat stress is crucial for the development of climate resilient crops in the face of climate uncertainty. The leaf metabolome effectively summarizes stress-driven perturbations of the plant physiological status and represents an intermediate phenotype that bridges the plant genome and phenome. The objective of this study was to analyze the effect of water deficit and heat stress on the leaf metabolome of 22 genetically diverse accessions of upland cotton grown in the Arizona low desert over two consecutive years. Results revealed that membrane lipid remodeling was the main leaf mechanism of adaptation to drought. The magnitude of metabolic adaptations to drought, which had an impact on fiber traits, was found to be quantitatively and qualitatively associated with different stress severity levels during the two years of the field trial. Leaf-level hyperspectral reflectance data were also used to predict the leaf metabolite profiles of the cotton accessions. Multivariate statistical models using hyperspectral data accurately estimated (R2 > 0.7 in ∼34% of the metabolites) and predicted (Q2 > 0.5 in 15–25% of the metabolites) many leaf metabolites. Predicted values of metabolites could efficiently discriminate stressed and non-stressed samples and reveal which regions of the reflectance spectrum were the most informative for predictions. Combined together, these findings suggest that hyperspectral sensors can be used for the rapid, non-destructive estimation of leaf metabolites, which can summarize the plant physiological status. Copyright © 2021 Melandri, Thorp, Broeckling, Thompson, Hinze and Pauli.Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]
Author Correction: Pollen foraging preferences in honey bees and the nutrient profiles of the pollen
No full textTryptophan catabolism in acute exacerbations of chronic obstructive pulmonary disease
No full textMakedonka Gulcev,1 Cavan Reilly,2 Timothy J Griffin,3 Corey D Broeckling,4 Brian J Sandri,1 Bruce A Witthuhn,3 Shane W Hodgson,1 Prescott G Woodruff,5 Chris H Wendt1,6,* 1Department of Medicine, 2Division of Biostatistics, School of Public Health, 3Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota, Minneapolis, MN, USA; 4Department of Computer Science, Colorado State University, Fort Collins, CO, USA; 5Division of Pulmonary, Critical Care, Sleep and Allergy, Department of Medicine and the CVRI, University of California, San Francisco, CA, USA; 6Department of Medicine, Minneapolis VA Medical Center, Minneapolis, MN, USA *For the COPD Clinical Research Network Introduction: Exacerbations are a leading cause of morbidity in COPD. The objective of this study was to identify metabolomic biomarkers of acute exacerbations of COPD (AECOPD). Methods: We measured metabolites via mass spectrometry (MS) in plasma drawn within 24 hours of admission to the hospital for 33 patients with an AECOPD (day 0) and 30 days later and for 65 matched controls. Individual metabolites were measured via selective reaction monitoring with mass spectrometry. We used a mixed-effect model to compare metabolite levels in cases compared to controls and a paired t-test to test for differences between days 0 and 30 in the AECOPD group. Results: We identified 377 analytes at a false discovery rate of 5% that differed between cases (day 0) and controls, and 31 analytes that differed in the AECOPD cases between day 0 and day 30 (false discovery rate: 5%). Tryptophan was decreased at day 0 of AECOPD compared to controls corresponding to an increase in indoleamine 2,3-dioxygenase activity. Conclusion: Patients with AECOPD have a unique metabolomic signature that includes a decrease in tryptophan levels consistent with an increase in indoleamine 2,3-dioxygenase activity. Keywords: Chronic Obstructive Pulmonary Disease, metabolomics, tryptopha
A novel culture medium with reduced nutrient concentrations supports the development and viability of mouse embryos
No full textFurther refinement of culture media is needed to improve the quality of embryos generated in vitro. Previous results from our laboratory demonstrated that uptake of nutrients by the embryo is significantly less than what is supplied in traditional culture media. Our objective was to determine the impact of reduced nutrient concentrations in culture medium on mouse embryo development, metabolism, and quality as a possible platform for next generation medium formulation. Concentrations of carbohydrates, amino acids, and vitamins could be reduced by 50% with no detrimental effects, but blastocyst development was impaired at 25% of standard nutrient provision (reduced nutrient medium; RN). Addition of pyruvate and L-lactate (+PL) to RN at 50% of standard concentrations restored blastocyst development, hatching, and cell number. In addition, blastocysts produced in RN +PL contained more ICM cells and ATP than blastocysts cultured in our control (100% nutrient) medium; however, metabolic activity was altered. Similarly, embryos produced in the RN medium with elevated (50% control) concentrations of pyruvate and lactate in the first step medium and EAA and Glu in the second step medium were competent to implant and develop into fetuses at
a similar rate as embryos produced in the control medium. This novel approach to culture medium formulation could help define the optimal nutrient requirements of embryos in culture and provide a means of shifting metabolic activity towards the utilization of specific metabolic pathways that may be beneficial for embryo viability
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