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Tryptocidine C (TpcC), a Trp-rich cyclodecapeptide is a minor constituent in the antibiotic tyrothricin complex from Brevibacillus parabrevis. TpcC possesses a high tendency to oligomerise in aqueous solutions and dried TpcC forms distinct self-assembled nanoparticles. High-resolution scanning electron microscopy revealed the influence of different ethanol:water solvent systems on TpcC self-assembly, with the TpcC, dried from a high concentration in 15% ethanol, primarily assembling into small nanospheres with 24.3 nm diameter and 0.05 polydispersity. TpcC at 16 μM, near its CMC, formed a variety of structures such as small nanospheres, large dense nanospheroids and facetted 3-D-crystals, as well as sheets and coarse carpet-like structures which depended on ethanol concentration. Drying 16 μM TpcC from 75% ethanol resulted in highly facetted 3-D crystals, as well as small nanospheres, while those in 10% ethanol preparation had less defined facets. Drying from 20 to 50% ethanol led to polymorphic architectures with a few defined nanospheroids and various small nanoparticles, imbedded in carpet- and sheet-like structures. These polymorphic surface morphologies correlated with maintenance of fluorescence properties and the surface-derived antibacterial activity against Staphylococcus aureus over time, while there was a significant change in fluorescence and loss in activity in the 10% and 75% preparations where 3-D crystals were observed. This indicated that TpcC oligomerisation in solutions with 20–50% ethanol leads to metastable structures with a high propensity for release of antimicrobial moieties, while those leading to crystallisation limit active moieties release. TpcC nano-assemblies can find application in antimicrobial coatings, surface disinfectants, food packaging and wound healing materials.

This study demonstrates the application of a mathematical steroidogenic model, constructed with individual in vitro enzyme characterisations, to simulate in vivo steroidogenesis in a diseased state. This modelling approach was applied to the South African Angora goat, that suffers from hypocortisolism caused by altered adrenal function. These animals are extremely vulnerable to cold stress, leading to substantial monetary loss in the mohair industry. The Angora goat has increased CYP17A1 17,20-lyase enzyme activity in comparison with hardy livestock species. Determining the effect of this altered adrenal function on adrenal steroidogenesis during a cold stress response is difficult. We developed a model describing adrenal steroidogenesis under control conditions, and under altered steroidogenic conditions where the animal suffers from hypocortisolism. The model is parameterised with experimental data from in vitro enzyme characterisations of a hardy control species. The increased 17,20-lyase activity of the Angora goat CYP17A1 enzyme was subsequently incorporated into the model and the response to physiological stress is simulated under both control and altered adrenal steroidogenic conditions.

mRNA localization to subcellular compartments has been reported across all kingdoms of life and it is generally believed to promote asymmetric protein synthesis and localization. In striking contrast to previous observations, we show that in S. cerevisiae the B-type cyclin CLB2 mRNA is localized and translated in the yeast bud, while the Clb2 protein, a key regulator of mitosis progression, is concentrated in the mother nucleus. Using single-molecule RNA imaging in fixed (smFISH) and living cells (MS2 system), we show that the CLB2 mRNA is transported to the yeast bud by the She2-She3 complex, via an mRNA ZIP-code situated in the coding sequence. In CLB2 mRNA localization mutants, Clb2 protein synthesis in the bud is decreased resulting in changes in cell cycle distribution and genetic instability. Altogether, we propose that CLB2 mRNA localization acts as a sensor for bud development to couple cell growth and cell cycle progression, revealing a novel function for mRNA localization.

To move towards a circular bioeconomy, sustainable strategies for the utilization of renewable, non-food biomass wastes such as lignocellulose, are needed. To this end, an efficient bioconversion of D-xylose – after D-glucose the most abundant sugar in lignocellulose – is highly desirable. Most standard organisms used in biotechnology are limited in metabolising D-xylose, and also in vitro enzymatic strategies for its conversion have not been very successful. We herein discuss that bioconversion of D-xylose is mostly hampered by missing knowledge on the kinetic properties of the enzymes involved in its metabolism. We propose a combination of classical enzyme characterizations and mathematical modelling approaches as a workflow for rational, model-based design to optimize enzyme cascades and/or whole cell biocatalysts for efficient D-xylose metabolism.

Aims: A mathematical model of the nonribosomal synthesis of tyrocidines and analogues by Brevibacillus parabrevis was constructed using a competitive binding mechanism (CBM) for the incorporation of the three variable aromatic amino acid (Aaa) residues in their sequence. These antimicrobial peptides have a conserved structure (D-Phe1-Pro2-Aaa3-D-Aaa4-Asn5-Gln6-Aaa7-Val8-Orn9-Leu10), apart from the Aaa in positions 3, 4 and 7 containing either Phe, Trp or Tyr. Methods and Results: Ultra-performance liquid chromatography linked mass spectrometry was used to profile peptides from extracts of cultures grown in media with various Phe : Trp ratios. The CBM model describes the production of peptides as a function of growth medium Aaa concentration. The model accounts for variable Aaa incorporation by simultaneously considering the influence of maximal incorporation rate and cooperativity, despite similar KM’s of synthetase modules. Conclusions: Our CBM model can be utilized to predict the Aaa composition of produced peptides from the concentration of Aaas in the growth medium. Significance and Impact of the Study: Subtly exploiting the inherent promiscuity of the nontemplate coded peptide synthesis allows for external control of peptide identity, without using genetic manipulation. Such versatility is exploitable in the production of targeted peptide complexes and rare peptides where production processes are reliant on nonribosomal synthesis.

In this unit, we provide a clear exposition of the methodology employed to study dynamic responses in individual cells, using microfluidics for controlling and adjusting the cell environment, optical tweezers for precise cell positioning, and fluorescence microscopy for detecting intracellular responses. This unit focuses on the induction and study of glycolytic oscillations in single yeast cells, but the methodology can easily be adjusted to examine other biological questions and cell types. We present a step-by-step guide for fabrication of the microfluidic device, for alignment of the optical tweezers, for cell preparation, and for time-lapse imaging of glycolytic oscillations in single cells, including a discussion of common pitfalls. A user who follows the protocols should be able to detect clear metabolite time traces over the course of up to an hour that are indicative of dynamics on the second scale in individual cells during fast and reversible environmental adjustments. © 2018 by John Wiley & Sons, Inc.

Significance Many organs have densely packed cells divided in subpopulations that display coherent and spatially differentiated behavior. Using yeast cells packed in a microfluidic device, constructed to mimic an organ structure with peripheral blood flow, we show that cells coupled via diffusion of metabolites can lead to spatially differentiated subpopulations with temporally synchronized behavior. A detailed mathematical model for each yeast cell simulated in its precise architectural location within the microfluidic system correctly predicts the cells’ behavior as a function of an external stress solution. Our results provide us with a mechanistic understanding of this system and indicate how a relatively simple mechanism can underlie a yet poorly understood cellular differentiation process., Many organs have internal structures with spatially differentiated and sometimes temporally synchronized groups of cells. The mechanisms leading to such differentiation and coordination are not well understood. Here we design a diffusion-limited microfluidic system to mimic a multicellular organ structure with peripheral blood flow and test whether a group of individually oscillating yeast cells could form subpopulations of spatially differentiated and temporally synchronized cells. Upon substrate addition, the dynamic response at single-cell level shows glycolytic oscillations, leading to wave fronts traveling through the monolayered population and to synchronized communities at well-defined positions in the cell chamber. A detailed mechanistic model with the architectural structure of the flow chamber incorporated successfully predicts the spatial-temporal experimental data, and allows for a molecular understanding of the observed phenomena. The intricate interplay of intracellular biochemical reaction networks leading to the oscillations, combined with intercellular communication via metabolic intermediates and fluid dynamics of the reaction chamber, is responsible for the generation of the subpopulations of synchronized cells. This mechanism, as analyzed from the model simulations, is experimentally tested using different concentrations of cyanide stress solutions. The results are reproducible and stable, despite cellular heterogeneity, and the spontaneous community development is reminiscent of a zoned cell differentiation often observed in multicellular organs.

During its asexual growth, Plasmodium falciparum undergoes a number of 48 h intra-erythrocytic cycles, punctuated by reinvasion events. The biomass formation dynamics can be described by three key parameters: the period of the growth cycle (for P. falciparum, typically 48 h), the merozoite release number (variable between 8 and 32), and the reinvasion efficiency (variable between 20 and 40% in cell cultures). An accurate estimation of these parameters is important to describe growth dynamics, and for evaluating working mechanisms of anti-malaria drugs. Standard techniques for the estimation of merozoite release number and reinvasion efficiency are based on interpretation of microscope images, typically involve fairly low numbers of observations and are laborious. Here, we employ a combined experimental and mathematical modelling approach that is based on metabolic end-product formation and parasitaemia dynamics, to quantify the key parameters for Plasmodium biomass formation in cell cultures in vitro. We present experimental data for Plasmodium falciparum, together with a mechanistic model for the mathematical analysis, and finally an easy-to-use method for a direct analysis of the experimental data. The results are in agreement with previously published results, but–importantly–are average values for all cells in the culture, i.e. based on a large number of cells, and are reproducible between independent experiments.

The response of oscillatory systems to external perturbations is crucial for emergent properties such as synchronisation and phase locking and can be quantified in a phase response curve (PRC). In individual, oscillating yeast cells, we characterised experimentally the phase response of glycolytic oscillations for external acetaldehyde pulses and followed the transduction of the perturbation through the system. Subsequently, we analysed the control of the relevant system components in a detailed mechanistic model. The observed responses are interpreted in terms of the functional coupling and regulation in the reaction network. We find that our model quantitatively predicts the phase-dependent phase shift observed in the experimental data. The phase shift is in agreement with an adaptation leading to synchronisation with an external signal. Our model analysis establishes that phosphofructokinase plays a key role in the phase shift dynamics as shown in the PRC and adaptation time to external perturbations. Specific mechanism-based interventions, made possible through such analyses of detailed models, can improve upon standard trial and error methods, e.g. melatonin supplementation to overcome jet-lag, which are error-prone, specifically, since the effects are phase dependent and dose dependent. The models by Gustavsson and Goldbeter discussed in the text can be obtained from the JWS Online simulation database: (https://jjj.bio.vu.nl/models/gustavsson5 and https://jjj.bio.vu.nl/models/goldbeter1)

The oxidative Weimberg pathway for the five-step pentose degradation to α-ketoglutarate is a key route for sustainable bioconversion of lignocellulosic biomass to added-value products and biofuels. The oxidative pathway from Caulobacter crescentus has been employed in in-vivo metabolic engineering with intact cells and in in-vitro enzyme cascades. The performance of such engineering approaches is often hampered by systems complexity, caused by non-linear kinetics and allosteric regulatory mechanisms. Here we report an iterative approach to construct and validate a quantitative model for the Weimberg pathway. Two sensitive points in pathway performance have been identified as follows: (1) product inhibition of the dehydrogenases (particularly in the absence of an efficient NAD+ recycling mechanism) and (2) balancing the activities of the dehydratases. The resulting model is utilized to design enzyme cascades for optimized conversion and to analyse pathway performance in C. cresensus cell-free extracts., Metabolic engineering is often hampered by non-linear kinetics and allosteric regulatory mechanisms. Here, the authors construct a quantitative model for the pentose degradation Weimberg pathway in Caulobacter crescentus and demonstrate its biotechnological applications in cell-free system and standard metabolic engineering.

Testosterone and its 5α-reduced form, 5α-dihydrotestosterone, were previously thought to represent the only active androgens in humans. However, recent studies have shown that the potent androgen, 11-ketotestosterone, derived from the adrenal androgen precursor, 11β-hydroxyandrostenedione, may in fact serve as the primary androgen in healthy women. Yet, despite recent renewed interest in these steroids, their downstream metabolism has remained undetermined. We therefore set out to investigate the metabolism of 11-ketotestosterone by characterising the 5α- or 5β-reduction commitment step. We show that inactivation of 11-ketotestosterone is predominantly driven by AKR1D1, which efficiently catalyses the 5β-reduction of 11-ketotestosterone, committing it to a metabolic pathway that terminates in 11-ketoetiocholanolone. We demonstrate that 5α-reduction of 11-ketotestosterone is catalysed by SRD5A2, but not SRD5A1, and terminates in 11-ketoandrosterone, but is only responsible for a minority of 11-ketotestosterone inactivation. However, as 11-ketoetiocholanolone is also generated by the metabolism of the glucocorticoid cortisone, 11-ketoandrosterone should be considered a more specific urinary marker of 11-ketotestosterone production.

The progression of castration resistant prostate cancer (CRPC) is driven by the intratumoral conversion of adrenal androgen precursors to potent androgens. The expression of aldo-keto reductase 1C3 (AKR1C3), which catalyses the reduction of weak androgens to more potent androgens, is significantly increased in CRPC tumours. The oxidation of androgens to their inactive form is catalysed by 17β-hydroxysteroid dehydrogenase type 2 (17βHSD2), but little attention is given to the expression levels of this enzyme. In this study, we show that the 11-oxygenated androgen precursors of adrenal origin are the preferred substrate for AKR1C3. In particular we show that the enzymatic efficiency of AKR1C3 is 8- and 24-fold greater for 11-ketoandrostenedione than for the classic substrates androstenedione and 5α-androstanedione, respectively. Using three independent experimental systems and a computational model we subsequently show that increased ratios of AKR1C3:17βHSD2 significantly favours the flux through the 11-oxygenated androgen pathway as compared to the classical or 5α-androstanedione pathways. Our findings reveal that the flux through the classical and 5α-androstanedione pathways are limited by the low catalytic efficiently of AKR1C3 towards classical androgens combined with the high catalytic efficiency of 17βHSD2, and that the expression of the oxidative enzyme therefore plays a vital role in determining the steady state concentration of active androgens. Using microarray data from prostate tissue we confirm that the AKR1C3:17βHSD2 ratio is significantly increased in patients undergoing androgen deprivation therapy as compared to benign tissue, and further increased in patients with CRPC. Taken together this study therefore demonstrates that the ratio of AKR1C3:17βHSD2 is more important than AKR1C3 expression alone in determining intratumoral androgen levels and that 11-oxygenated androgens may play a bigger role in CRPC than previously anticipated.

Life science researchers use computational models to articulate and test hypotheses about the behavior of biological systems. Semantic annotation is a critical component for enhancing the interoperability and reusability of such models as well as for the integration of the data needed for model parameterization and validation. Encoded as machine-readable links to knowledge resource terms, semantic annotations describe the computational or biological meaning of what models and data represent. These annotations help researchers find and repurpose models, accelerate model composition, and enable knowledge integration across model repositories and experimental data stores. However, realizing the potential benefits of semantic annotation requires the development of model annotation standards that adhere to a community-based annotation protocol. Without such standards, tool developers must account for a variety of annotation formats and approaches, a situation that can become prohibitively cumbersome and which can defeat the purpose of linking model elements to controlled knowledge resource terms. Currently, no consensus protocol for semantic annotation exists among the larger biological modeling community. Here, we report on the landscape of current semantic annotation practices among the COmputational Modeling in BIology NEtwork (COMBINE) community and provide a set of recommendations for building a consensus approach to semantic annotation.

N-substituted pantothenamides are analogues of pantothenic acid, the vitamin precursor of CoA, and constitute a class of well-studied bacterial growth inhibitors that show potential as new antibacterial agents. Previous studies have highlighted the importance of pantothenate kinase (PanK; EC 2.7.1.33) (the first enzyme of CoA biosynthesis) in mediating pantothenamide-induced growth inhibition by one of two proposed mechanisms: first, by acting on the pantothenamides as alternate substrates (allowing their conversion into CoA antimetabolites, with subsequent effects on CoA- and acyl carrier protein-dependent processes) or, second, by being directly inhibited by them (causing a reduction in CoA biosynthesis). In the present study we used structurally modified pantothenamides to probe whether PanKs interact with these compounds in the same manner. We show that the three distinct types of eubacterial PanKs that are known to exist (PanKI , PanKII and PanKIII ) respond very differently and, consequently, are responsible for determining the pantothenamide mode of action in each case: although the promiscuous PanKI enzymes accept them as substrates, the highly selective PanKIII s are resistant to their inhibitory effects. Most unexpectedly, Staphylococcus aureus PanK (the only known example of a bacterial PanKII ) experiences uncompetitive inhibition in a manner that is described for the first time. In addition, we show that pantetheine, a CoA degradation product that closely resembles the pantothenamides, causes the same effect. This suggests that, in S. aureus, pantothenamides may act by usurping a previously unknown role of pantetheine in the regulation of CoA biosynthesis, and validates its PanK as a target for the development of new antistaphylococcal agents.

Oscillations are widely distributed in nature and synchronization of oscillators has been described at the cellular level (e.g. heart cells) and at the population level (e.g. fireflies). Yeast glycolysis is the best known oscillatory system, although it has been studied almost exclusively at the population level (i.e. limited to observations of average behaviour in synchronized cultures). We studied individual yeast cells that were positioned with optical tweezers in a microfluidic chamber to determine the precise conditions for autonomous glycolytic oscillations. Hopf bifurcation points were determined experimentally in individual cells as a function of glucose and cyanide concentrations. The experiments were analyzed in a detailed mathematical model and could be interpreted in terms of an oscillatory manifold in a three-dimensional state-space; crossing the boundaries of the manifold coincides with the onset of oscillations and positioning along the longitudinal axis of the volume sets the period. The oscillatory manifold could be approximated by allosteric control values of phosphofructokinase for ATP and AMP.The mathematical models described here have been submitted to the JWS Online Cellular Systems Modelling Database and can be accessed at http://jjj.mib.ac.uk/webMathematica/UItester.jsp?modelName=gustavsson5. [Database section added 14 May 2014 after original online publication].

There are many examples of oscillations in biological systems and one of the most investigated is glycolytic oscillations in yeast. These oscillations have been studied since the 1950s in dense, synchronized populations and in cell-free extracts, but it has for long been unknown whether a high cell density is a requirement for oscillations to be induced, or if individual cells can oscillate also in isolation without synchronization. Here we present an experimental method and a detailed kinetic model for studying glycolytic oscillations in individual, isolated yeast cells and compare them to previously reported studies of single-cell oscillations. The importance of single-cell studies of this phenomenon and relevant future research questions are also discussed. © 2013 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

The development of drugs that can inactivate disease-causing cells (e.g. cancer cells or parasites) without causing collateral damage to healthy or to host cells is complicated by the fact that many proteins are very similar between organisms. Nevertheless, due to subtle, quantitative differences between the biochemical reaction networks of target cell and host, a drug can limit the flux of the same essential process in one organism more than in another. We identified precise criteria for this ‘network-based’ drug selectivity, which can serve as an alternative or additive to structural differences. We combined computational and experimental approaches to compare energy metabolism in the causative agent of sleeping sickness, Trypanosoma brucei, with that of human erythrocytes, and identified glucose transport and glyceraldehyde-3-phosphate dehydrogenase as the most selective antiparasitic targets. Computational predictions were validated experimentally in a novel parasite-erythrocytes co-culture system. Glucose-transport inhibitors killed trypanosomes without killing erythrocytes, neurons or liver cells.

Mathematical models are key to systems biology where they typically describe the topology and dynamics of biological networks, listing biochemical entities and their relationships with one another. Some (hyper)thermophilic Archaea contain an enzyme, called non-phosphorylating glyceraldehyde-3-phosphate dehydrogenase (GAPN), which catalyzes the direct oxidation of glyceraldehyde-3-phosphate to 3-phosphoglycerate omitting adenosine 5′-triphosphate (ATP) formation by substrate-level-phosphorylation via phosphoglycerate kinase. In this study we formulate three hypotheses that could explain functionally why GAPN exists in these Archaea, and then construct and use mathematical models to test these three hypotheses. We used kinetic parameters of enzymes of Sulfolobus solfataricus (S. solfataricus) which is a thermo-acidophilic archaeon that grows optimally between 60 and 90 °C and between pH 2 and 4. For comparison, we used a model of Saccharomyces cerevisiae (S. cerevisiae), an organism that can live at moderate temperatures. We find that both the first hypothesis, i.e., that the glyceraldehyde-3-phosphate dehydrogenase (GAPDH) plus phosphoglycerate kinase (PGK) route (the alternative to GAPN) is thermodynamically too much uphill and the third hypothesis, i.e., that GAPDH plus PGK are required to carry the flux in the gluconeogenic direction, are correct. The second hypothesis, i.e., that the GAPDH plus PGK route delivers less than the 1 ATP per pyruvate that is delivered by the GAPN route, is only correct when GAPDH reaction has a high rate and 1,3-bis-phosphoglycerate (BPG) spontaneously degrades to 3PG at a high rate. OA gold

In many disciplines, data is highly decentralized across thousands of online databases (repositories, registries, and knowledgebases). Wringing value from such databases depends on the discipline of data science and on the humble bricks and mortar that make integration possible; identifiers are a core component of this integration infrastructure. Drawing on our experience and on work by other groups, we outline ten lessons we have learned about the identifier qualities and best practices that facilitate large-scale data integration. Specifically, we propose actions that identifier practitioners (database providers) should take in the design, provision and reuse of identifiers; we also outline important considerations for those referencing identifiers in various circumstances, including by authors and data generators. While the importance and relevance of each lesson will vary by context, there is a need for increased awareness about how to avoid and manage common identifier problems, especially those related to persistence and web-accessibility/resolvability. We focus strongly on web-based identifiers in the life sciences; however, the principles are broadly relevant to other disciplines.

In (hyper)thermophilic organisms metabolic processes have to be adapted to function optimally at high temperature. Wecompared the gluconeogenic conversion of 3-phosphoglycerate via 1,3-bisphosphoglycerate to glyceraldehyde-3-phosphateat 30 C and at 70 C. At 30 C it was possible to produce 1,3-bisphosphoglycerate from 3-phosphoglycerate withphosphoglycerate kinase, but at 70 C, 1,3-bisphosphoglycerate was dephosphorylated rapidly to 3-phosphoglycerate,effectively turning the phosphoglycerate kinase into a futile cycle. When phosphoglycerate kinase was incubated togetherwith glyceraldehyde 3-phosphate dehydrogenase it was possible to convert 3-phosphoglycerate to glyceraldehyde 3-phosphate, both at 30 C and at 70 C, however, at 70 C only low concentrations of product were observed due to thermalinstability of glyceraldehyde 3-phosphate. Thus, thermolabile intermediates challenge central metabolic reactions andrequire special adaptation strategies for life at high temperature.

Background Glutathione metabolism can determine an individual's ability to detoxify drugs. To increase understanding of the dynamics of cellular glutathione homeostasis, we have developed an experiment-based mathematical model of the kinetics of the glutathione network. This model was used to simulate perturbations observed when human liver derived THLE cells, transfected with human cytochrome P452E1 (THLE-2E1 cells), were exposed to paracetamol (acetaminophen). Methods Human liver derived cells containing extra human cytochrome P4502E1 were treated with paracetamol at various levels of methionine and in the presence and absence of an inhibitor of glutamyl-cysteine synthetase (GCS). GCS activity was also measured in extracts. Intracellular and extracellular concentrations of substances involved in glutathione metabolism were measured as was damage to mitochondria and proteins. A bottom up mathematical model was made of the metabolic pathways around and including glutathione. Results Our initial model described some, but not all the metabolite-concentration and flux data obtained when THLE-2E1 cells were exposed to paracetamol at concentrations high enough to affect glutathione metabolism. We hypothesized that the lack of correspondence could be due to upregulation of expression of glutamyl cysteine synthetase, one of the enzymes controlling glutathione synthesis, and confirmed this experimentally. A modified model which incorporated this adaptive response adequately described the observed changes in the glutathione pathway. Use of the adaptive model to analyze the functioning of the glutathione network revealed that a threshold input concentration of methionine may be required for effective detoxification of reactive metabolites by glutathione conjugation. The analysis also provided evidence that 5-oxoproline and ophthalmic acid are more useful biomarkers of glutathione status when analyzed together than when analyzed in isolation, especially in a new, model-assisted integrated biomarker strategy. Conclusion A robust mathematical model of the dynamics of cellular changes in glutathione homeostasis in cells has been developed and tested in vitro. General significance Mathematical models of the glutathione pathway that help examine mechanisms of cellular protection against xenobiotic toxicity and the monitoring thereof, can now be made. © 2013 Elsevier B.V.

The FAIRDOMHub is a repository for publishing FAIR (Findable, Accessible, Interoperable and Reusable) Data, Operating procedures and Models (https://fairdomhub.org/) for the Systems Biology community. It is a web-accessible repository for storing and sharing systems biology research assets. It enables researchers to organize, share and publish data, models and protocols, interlink them in the context of the systems biology investigations that produced them, and to interrogate them via API interfaces. By using the FAIRDOMHub, researchers can achieve more effective exchange with geographically distributed collaborators during projects, ensure results are sustained and preserved and generate reproducible publications that adhere to the FAIR guiding principles of data stewardship.