Deer Data Research Articles

Self-assembly of spin-labeled antimicrobial peptides magainin 2 and PGLa in lipid bilayers

The cationic antimicrobial peptides PGLa and magainin 2 (Mag2) are known for their antimicrobial activity and synergistic enhancement in antimicrobial and membrane leakage assays. Further use of peptides in combinatory therapy requires knowledge of the mechanisms of action of both individual peptides and their mixtures. Here, electron paramagnetic resonance (EPR), double electron-electron resonance (DEER, also known as PELDOR) and electron spin echo envelope modulation (ESEEM) spectroscopies were applied to study self-assembly and localization of spin-labeled PGLa and Mag2 in POPE/POPG membranes with a wide range of peptide/lipid ratios (P/L) from ∼1/1500 to 1/50. EPR and DEER data showed that both peptides tend to organize in clusters, which occurs already at the lowest peptide/lipid molar ratio of 1/1500 (0.067 mol%). For individual peptides, these clusters are quite dense with intermolecular distances of the order of ∼2 nm. In the presence of a synergistic peptide partner, these homo-clusters are transformed into lipid-diluted hetero-clusters. These clusters are characterized by a local surface density that is several times higher than expected from a random distribution. ESEEM data indicate a slightly different insertion depth of peptides in hetero-clusters when compared to homo-clusters.

Structural insights into the semiquinone form of human Cytochrome P450 reductase by DEER distance measurements between a native flavin and a spin labelled non-canonical amino acid.

The flavoprotein Cytochrome P450 reductase (CPR) is the unique electron pathway from NADPH to Cytochrome P450 (CYPs). The conformational dynamics of human CPR in solution, which involves transitions from a "locked/closed" to an "unlocked/open" state, is crucial for electron transfer. To date, however, the factors guiding these changes remain unknown. By Site-Directed Spin Labelling coupled to Electron Paramagnetic Resonance spectroscopy, we have incorporated a non-canonical amino acid onto the flavin mononucleotide (FMN) and flavin adenine dinucleotide (FAD) domains of soluble human CPR, and labelled it with a specific nitroxide spin probe. Taking advantage of the endogenous FMN cofactor, we successfully measured for the first time, the distance distribution by DEER between the semiquinone state FMNH• and the nitroxide. The DEER data revealed a salt concentration-dependent distance distribution, evidence of an "open" CPR conformation at high salt concentrations exceeding previous reports. We also conducted molecular dynamics simulations which unveiled a diverse ensemble of conformations for the "open" semiquinone state of the CPR at high salt concentration. This study unravels the conformational landscape of the one electron reduced state of CPR, which had never been studied before.

Phenotype of White Sika Deer Due to SCF Gene Structural Variation.

Breeding ornamental white sika deer is a new notion that can be used to broaden the sika deer industry However, it is very rare for other coat phenotypes to occur, especially white (apart from albinism), due to the genetic stability and homogeneity of its coat color phenotype, making it difficult to breed white sika deer between species. We found a white sika deer and sequenced its whole genome. Then, the clean data obtained were analyzed on the basis of gene frequency, and a cluster of coat color candidate genes containing 92 coat color genes, one SV (structure variation), and five nonsynonymous SNPs (single nucleotide polymorphisms) was located. We also discovered a lack of melanocytes in the skin tissue of the white sika deer through histological examination, initially proving that the white phenotype of sika deer is caused by a 10.099 kb fragment deletion of the SCF gene(stem cell factor). By designing SCF-specific primers to detect genotypes of family members of the white sika deer, and then combining them with their phenotypes, we found that the genotype of the white sika deer is SCF789/SCF789, whereas that of individuals with white patches on their faces is SCF789/SCF1-9. All these results showed that the SCF gene plays an important role in the development of melanocytes in sika deer and is responsible for the appearance of the white coat color. This study reveals the genetic mechanism of the white coat color in sika deer and supplies data as a reference for breeding white ornamental sika deer.

Conducting a three-pulse DEER experiment without dead time: A review

Double electron-electron resonance spectroscopy (DEER, also known as PELDOR) is used to study spin-spin dipolar interactions between spin labels, at the nanoscale range of distances. The DEER effect is obtained as a signal generated by echo-forming microwave (mw) pulses with an additional mw pump pulse applied at a different frequency. It is important to carry out measurements without artefacts induced by overlap of the pulses in the time scale. Such an experiment without the dead-time effect is achieved using the 4-pulse (4p) DEER method. The analysis of the literature performed here shows however that the 3-pulse (3p) DEER can also be free of the dead time problem, for which there are two possibilities. The first occurs using a specially designed bimodal resonator, for which the two frequencies are completely decoupled. The second possibility, which can be implemented for any commercial spectrometer, involves the signal correction based on an additional “blank” measurement with the pump pulse applied outside the EPR resonance. A detailed comparison of the 3p and 4p DEER data obtained previously by Milov et al. [Appl. Magn. Reson. 41 (2011) 59–67] shows that 3p and 4p approaches give similar results. The advantages of the 3p DEER techniques are discussed.

Bayesian species distribution models integrate presence‐only and presence–absence data to predict deer distribution and relative abundance

Using geospatial data of wildlife presence to predict a species distribution across a geographic area is among the most common tools in management and conservation. The collection of high‐quality presence–absence (PA) data through structured surveys is, however, expensive, and managers usually have access to larger amounts of low‐quality presence‐only (PO) data collected by citizen scientists, opportunistic observations and culling returns for game species. Integrated species distribution models (ISDMs) have been developed to make the most of the data available by combining the higher‐quality, but usually scarcer and more spatially restricted, PA data with the lower‐quality, unstructured, but usually more extensive PO datasets. Joint‐likelihood ISDMs can be run in a Bayesian context using integrated nested laplace approximation methods that allow the addition of a spatially structured random effect to account for data spatial autocorrelation. Here, we apply this innovative approach to fit ISDMs to empirical data, using PA and PO data for the three prevalent deer species in Ireland: red, fallow and sika deer. We collated all deer data available for the past 15 years and fitted models predicting distribution and relative abundance at a 25 km2resolution across the island. Model predictions were associated to spatial estimate of uncertainty, allowing us to assess the quality of the model and the effect that data scarcity has on the certainty of predictions. Furthermore, we checked the performance of the three species‐specific models using two datasets, independent deer hunting returns and deer densities based on faecal pellet counts. Our work clearly demonstrates the applicability of spatially explicit ISDMs to empirical data in a Bayesian context, providing a blueprint for managers to exploit unexplored and seemingly unusable data that can, when modelled with the proper tools, serve to inform management and conservation policies.

A comparison of mixed‐mode survey designs for collecting deer and fall turkey harvest data in North Dakota

AbstractAchieving state wildlife agency biological goals for deer (Odocoileus spp.) and turkey (Meleagris gallopavo) rely on high quality data collection via hunter harvest surveys. Concomitantly, better information is needed to optimize harvest survey methods. From 2017 to 2019, we surveyed North Dakota, USA, deer and fall turkey hunters using a self‐administered mail survey as a control and 3 mixed‐mode, internet/mail surveys to evaluate the efficacy of alternative survey designs for estimating harvest of game populations and informing future management. We measured response rates across segments of North Dakota deer and fall turkey hunters, and across mixed‐mode treatments that could easily be implemented with existing wildlife agency resources. We also determined whether early survey respondents were more likely to harvest deer or turkey. Finally, we estimated the effects of demographic factors that may be associated with hunters returning survey treatment modes to further North Dakota Game and Fish Department's ability to tailor surveys to certain hunter groups. We found that internet‐mail and mail‐internet treatments resulted in significantly higher response rates than a traditional mail‐only survey mode. We also found that hunters who successfully harvested an animal were more likely to return questionnaires shortly after the initial wave of surveying. Finally, we found that older, nonresident, and urban hunters were more likely to return questionnaires. Our research demonstrates potential use of tailored mixed‐mode surveys to increase response rates.

DEER Data Analysis Software: A Comparative Guide.

Pulsed dipolar electron paramagnetic resonance (PDEPR) spectroscopy experiments measure the dipolar coupling, and therefore nanometer-scale distances and distance distributions, between paramagnetic centers. Of the family of PDEPR experiments, the most commonly used pulsed sequence is four-pulse double electron resonance (DEER, also known as PELDOR). There are several ways to analyze DEER data to extract distance distributions, and this may appear overwhelming at first. This work compares and reviews six of the packages, and a brief getting started guide for each is provided.

Monitoring partially marked populations using camera and telemetry data.

Long-term monitoring is an important component of effective wildlife conservation. However, many methods for estimating density are too costly or difficult to implement over large spatial and temporal extents. Recently developed spatial mark-resight (SMR) models are increasingly being applied as a cost-effective method to estimate density when data include detections of both marked and unmarked individuals. We developed a generalized SMR model that can accommodate long-term camera data and auxiliary telemetry data for improved spatiotemporal inference in monitoring efforts. The model can be applied in two stages, with detection parameters estimated in the first stage using telemetry data and camera detections of instrumented individuals. Density is estimated in the second stage using camera data, with all individuals treated as unmarked. Serial correlation in detection and density parameters is accounted for using time-series models. The two-stage approach reduces computational demands and facilitates the application to large data sets from long-term monitoring initiatives. We applied the model to 3 years (2015-2017) of white-tailed deer (Odocoileus virginianus) data collected in three study areas of the Big Cypress Basin, Florida, USA. In total, 59 females marked with ear tags and fitted with GPS-telemetry collars were detected along with unmarked females on 180 remote cameras. Most of the temporal variation in density was driven by seasonal fluctuations, but one study area exhibited a slight population decline during the monitoring period. Modern technologies such as camera traps provide novel possibilities for long-term monitoring, but the resulting massive data sets, which are subject to unique sources of observation error, have posed analytical challenges. The two-stage spatial mark-resight framework provides a solution with lower computational demands than joint SMR models, allowing for easier implementation in practice. In addition, after detection parameters have been estimated, the model may be used to estimate density even if no synchronous auxiliary information on marked individuals is available, which is often the case in long-term monitoring.

Population genomics of free-ranging Great Plains white-tailed and mule deer reflects a long history of interspecific hybridization.

Hybridization is a natural process at species‐range boundaries that may variably promote the speciation process or break down species barriers but minimally will influence management outcomes of distinct populations. White‐tailed deer (Odocoileus virginianus) and mule deer (Odocoileus hemionus) have broad and overlapping distributions in North America and a recognized capacity for interspecific hybridization. In response to contemporary environmental change to any of one or multiple still‐unknown factors, mule deer range is contracting westward accompanied by a westward expansion of white‐tailed deer, leading to increasing interactions, opportunities for gene flow, and associated conservation implications. To quantify genetic diversity, phylogenomic structure, and dynamics of hybridization in sympatric populations of white‐tailed and mule deer, we used mitochondrial cytochrome b data coupled with SNP loci discovered with double‐digest restriction site‐associated DNA sequencing. We recovered 25,018 SNPs across 92 deer samples from both species, collected from two regions of western Kansas. Eight individuals with unambiguous external morphology representing both species were of hybrid origin (8.7%), and represented the product of multi‐generational backcrossing. Mitochondrial data showed both ancient and recent directional discordance with morphological species assignments, reflecting a legacy of mule deer males mating with white‐tailed deer females. Mule deer had lower genetic diversity than white‐tailed deer, and both mitochondrial and nuclear data suggest contemporary mule deer effective population decline. Landscape genetic analyses show relative isolation between the two study regions for white‐tailed deer, but greater connectivity among mule deer, with predominant movement from north to south. Collectively, our results suggest a long history of gene flow between these species in the Great Plains and hint at evolutionary processes that purge incompatible functional genomic elements as a result of hybridization. Surviving hybrids evidently may be reproductive, but with unknown consequences for the future integrity of these species, population trajectories, or relative susceptibility to emerging pathogens.

Clustering of Stearic Acids in Model Phospholipid Membranes Revealed by Double Electron-Electron Resonance.

Free fatty acids play various important roles in biological membranes. Double electron-electron resonance spectroscopy (DEER, also known as PELDOR) of spin-labeled biomolecules is capable of studying magnetic dipole-dipole (d-d) interactions between spin labels at the nanoscale range of distances. Here, DEER is applied to study intermolecular d-d interactions between doxyl-spin-labeled stearic acids (DSA) in gel-phase phospholipid bilayers composed either of an equimolecular mixture of 1,2-dipalmitoyl-sn-glycero-3-phosphocholine and 1,2-dioleoyl-sn-glycero-3-phosphocholine or of 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine. DEER data obtained for different DSA concentrations showed that DSA molecules at their concentration in the bilayer χ larger than 0.5 mol % are assembled into lateral lipid-mediated clusters, with a characteristic intermolecular distance of 2 nm. Some evidences were obtained indicating that clusters may consist of "subclusters", alternatively appearing in two opposite leaflets. Conventional electron paramagnetic resonance (EPR) spectra for the gel-phase bilayers showed that for χ larger than 2 mol % the molecules in the clusters stick together, forming oligomers. Room-temperature EPR spectra for the liquid-crystalline phase were found to change noticeably for χ larger than 0.5 mol %, which may indicate the clustering in a liquid-crystalline phase similar to that observed by DEER in the gel phase.

Double Electron-Electron Resonance of Spin-Labeled Cholestane in Model Membranes: Evidence for Substructures inside the Lipid Rafts.

Plasma membranes are assumed to be highly compartmentalized, which is believed to be important for the membrane protein functionality. The liquid ordered-disordered phase segregation in the membranes results in nanoscale liquid-ordered assemblies-lipid rafts. Double electron-electron resonance spectroscopy (DEER, also known as PELDOR) is sensitive to spin-spin dipolar interactions between spin labels at the nanoscale range of distances. Here, DEER is applied to spin-labeled cholestane, 3β-doxyl-5α-cholestane (DChl), diluted in bilayers composed of an equimolar mixture of dioleoyl-glycero-phosphocholine (DOPC) and dipalmitoyl-glycero-phosphocholine (DPPC) phospholipids, with cholesterol (Chol) added. The DEER data allowed us to detect clustering of the DChl molecules. Their lateral distribution in the clusters in the absence of Chol was found to be random, while in the presence of Chol it became quasi-regular. DEER time traces are fairly well simulated within a simple square superlattice model. For the 20 mol % Chol content, for which at physiological temperatures, the lipid rafts are formed, the found superlattice parameter was 3.7 nm. Assuming that lipid rafts are captioned upon shock freezing at the temperature of investigation (80 K), the found regularity of DChl lateral distribution was interpreted by raft substructuring, with the DChl molecules embedded between the substructures.

Assessing the behaviour, welfare and husbandry of mouse deer (Tragulus spp.) in European zoos

Mouse deer are primitive, forest ungulates found in Asia and Africa. Both the lesser mouse deer (Tragulus javanicus) and the Philippine mouse deer (T. nigricans) are managed in European zoos, but inconsistent breeding success between institutions, high neonatal mortality and a general lack of research on their husbandry and behaviour were identified by the coordinators of the European Endangered Species Programme (EEP) and the European Studbook (ESB) for each species, respectively. This study is the first to provide a behavioural description for the Philippine mouse deer and to compile a detailed behavioural repertoire for both species. Our aim was to identify the effects of current husbandry and management practices on the reproduction, behaviour and welfare of zoo-housed mouse deer. Questionnaires on husbandry and management practices were sent to all institutions in the EEP and ESB for the lesser and Philippine mouse deer, respectively, and behavioural data were collected in 15 of these zoos. For the lesser mouse deer, results show a positive effect of vegetation cover on breeding success, foraging and moving behaviours. The provision of enrichment and presence of water ponds also positively affected these behaviours. The time that pairs spent in close proximity had a negative effect on breeding success, but animals in more vegetated enclosures spent less time in close proximity to each other. Results could be partially explained by the natural habitat of this usually solitary species being tropical forest, which provides local water sources and undergrowth for cover from predators. For the Philippine mouse deer there were differences in activity measures recorded between zoos, but the sample size was small with differences in training, enrichment and vegetation cover likely to have been important. In conclusion, since mouse deer inhabit overlapping male and female territories, the usual practice of housing breeding pairs together may be appropriate, but we suggest that they should be provided with opportunities to avoid each other in complex enclosures with ample vegetation cover to maximise their natural behavioural repertoire and breeding success.

An isolated white-tailed deer (Odocoileus virginianus) population on St. John, US Virgin Islands shows low inbreeding and comparable heterozygosity to other larger populations.

This is the first study to document the genetic diversity of the white‐tailed deer population on St. John, US Virgin Islands. The island population was founded by a small number of animals, has very limited hunting or predation, and recently experienced a reduction in size following an extended drought in 2015. DNA samples were collected from hair from 23 anesthetized adult deer (13 males, 10 females) ranging in age from 1 to 8 years (3.36 ± 1.9 years) and also from fecal DNA samples, for a total of 42 individuals analyzed for genetic diversity. The St. John deer data set averaged 4.19 alleles per marker and demonstrates the second lowest number of alleles (A) when compared to other populations of Odocoileus virginianus (4.19). Heterozygosity was similar to the other studies (0.54) with little evidence of inbreeding. To explain the level of heterozygosity and level of inbreeding within the St. John population, three hypotheses are proposed, including the effect of intrinsic biological traits within the population, a recent infusion of highly heterogeneous loci from North American populations, and a consistent level of immigration from a nearby island. Additional work is needed to further understand the genetic history of the St. John and regional deer populations.

DeerLab: a comprehensive software package for analyzing dipolar electron paramagnetic resonance spectroscopy data.

Dipolar EPR spectroscopy (DEER and other techniques) enables the structural characterization of macromolecular and biological systems by measurement of distance distributions between unpaired electrons on a nanometer scale. The inference of these distributions from the measured signals is challenging due to the ill-posed nature of the inverse problem. Existing analysis tools are scattered over several applications with specialized graphical user interfaces. This renders comparison, reproducibility, and method development difficult. To remedy this situation, we present DeerLab, an open-source software package for analyzing dipolar EPR data that is modular and implements a wide range of methods. We show that DeerLab can perform one-step analysis based on separable non-linear least squares, fit dipolar multi-pathway models to multi-pulse DEER data, run global analysis with non-parametric distributions, and use a bootstrapping approach to fully quantify the uncertainty in the analysis.

Continuous time resource selection analysis for moving animals

Abstract Resource selection analysis (RSA) seeks to understand how spatial abundance covaries with environmental features. By combining RSA with movement, step selection analysis (SSA) has helped uncover the mechanisms behind animal relocations, thereby giving insight into the movement decisions underlying spatial patterns. However, SSA typically assumes that at each observed location, an animal makes a ‘selection’ of the next observed location. This conflates observation with behavioural mechanism and does not account for decisions occurring at any other time along the animal’s path. To address this, we introduce a continuous time framework for resource selection. It is based on a switching Ornstein–Uhlenbeck (OU) model, parameterized by Bayesian Monte Carlo techniques. Such OU models have been used successfully to identify switches in movement behaviour, but hitherto not combined with resource selection. We test our inference procedure on simulated paths, representing both migratory movement (where landscape quality varies according to season) and foraging with depletion and renewal of resources (where the variation is due to past locations of the animals). We apply our framework to location data of migrating mule deer (Odocoileus hemionus) to shed light on the drivers of migratory decisions. In a wide variety of simulated situations, our inference procedure returns reliable estimations of the parameter values, including the extent to which animals trade‐off resource quality and travel distance (within 95% posterior intervals for the vast majority of cases). When applied to the mule deer data, our model reveals some individual variation in parameter values. Nevertheless, the migratory decisions of most individuals are well‐described by a model that accounts for the cost of moving and the difference between instantaneous change of vegetation quality at source and target patches. We have introduced a technique for inferring the resource‐driven decisions behind animal movement that accounts for the fact that these decisions may take place at any point along a path, not just when the animal’s location is known. This removes an oft‐acknowledged but hitherto little‐addressed shortcoming of stepwise movement models. Our work is of key importance in understanding how environmental features drive movement decisions and, as a consequence, space use patterns.

What are the methodological and theoretical prospects for paramagnetic NMR in structural biology? A glimpse into the crystal ball.

NMR spectroscopy is very sensitive to the presence of unpaired electrons, which perturb the NMR chemical shifts, J splittings and nuclear relaxation rates. These paramagnetic effects have attracted increasing attention over the last decades, and their use is expected to increase further in the future because they can provide structural information not easily achievable with other techniques. In fact, paramagnetic data provide long range structural restraints that can be used to assess the accuracy of crystal structures in solution and to improve them by simultaneous refinements with the X-ray data. They are also precious for obtaining information on the conformational variability of biomolecular systems, possibly in conjunction with SAXS and/or DEER data. We foresee that new tools will be developed in the next years for the simultaneous analysis of the paramagnetic data with data obtained from different techniques, in order to take advantage synergistically of the information content of all of them. Of course, the use of the paramagnetic data for structural purposes requires the knowledge of the relationship between these data and the molecular coordinates. Recently, the equations commonly used, dating back to half a century ago, have been questioned by first principle quantum chemistry calculations. Our prediction is that further theoretical/computational improvements will essentially confirm the validity of the old semi-empirical equations for the analysis of the experimental paramagnetic data.

Identifying the Optimal Level of Regularization in Deer Data Analysis

Double Electron-Electron Resonance (DEER) spectroscopy is an Electron Paramagnetic Resonance (EPR) experiment that accurately reports the distribution of distances, P(r), between two or more unpaired electrons over the range of about 10 to 160 ångströms. DEER is becoming increasingly important as a tool for structural biology due to its ability to elucidate protein conformational landscapes, as well as its amenability to complex samples such as membrane-bound proteins and large protein complexes. The spin-spin distance distribution, P(r), is most often inferred from the time-domain experimental data with a regularized least-squares method known as Tikhonov regularization. Although this method typically provides reliable estimates of P(r), it requires the input of a regularization parameter, α, which scales the magnitude of a penalty term with respect to the fitting error. This regularization parameter significantly affects the estimated P(r), so selecting its optimal value is crucial for accurate analysis of DEER data. The most popular procedure for selecting α in DEER data analysis is a graphical method called the L-curve criterion, which has empirical justification. However, to date, a systematic exploration of the many extant regularization parameter selection methods has not been carried out in the context of DEER data analysis. Here, we evaluate 16 methods, including the L-curve criterion, against a large, physically-derived test set of simulated DEER data. The test set of P(r)s was generated using a side-chain rotamer library in conjunction with a crystal structure (2LZM). This test set was then used to generate a large set of experimentally realistic simulated time-domain data.

Assessing protein conformational landscapes: integration of DEER data in Maximum Occurrence analysis.

The properties of the conformational landscape of a biomolecule are of capital importance to understand its function. It is widely accepted that a statistical ensemble is far more representative than a single structure, especially for proteins with disordered regions. While experimental data provide the most important handle on the conformational variability that the system is experiencing, they usually report on either time or ensemble averages. Since the available conformations largely outnumber the (independent) available experimental data, the latter can be equally well reproduced by a variety of ensembles. We have proposed the Maximum Occurrence (MaxOcc) approach to provide an upper bound of the statistical weight of each conformation. This method is expected to converge towards the true statistical weights by increasing the number of independent experimental datasets. In this paper we explore the ability of DEER (Double Electron Electron Resonance) data, which report on the distance distribution between two spin labels attached to a biomolecule, to restrain the MaxOcc values and its complementarity to previously introduced experimental techniques such as NMR and Small-Angle X-ray Scattering. We here present the case of Ca2+ bound calmodulin (CaM) as a test case and show that DEER data impose a sizeable reduction of the conformational space described by high MaxOcc conformations.

Clay content and pH: soil characteristic associations with the persistent presence of chronic wasting disease in northern Illinois

Environmental reservoirs are important to infectious disease transmission and persistence, but empirical analyses are relatively few. The natural environment is a reservoir for prions that cause chronic wasting disease (CWD) and influences the risk of transmission to susceptible cervids. Soil is one environmental component demonstrated to affect prion infectivity and persistence. Here we provide the first landscape predictive model for CWD based solely on soil characteristics. We built a boosted regression tree model to predict the probability of the persistent presence of CWD in a region of northern Illinois using CWD surveillance in deer and soils data. We evaluated the outcome for possible pathways by which soil characteristics may increase the probability of CWD transmission via environmental contamination. Soil clay content and pH were the most important predictive soil characteristics of the persistent presence of CWD. The results suggest that exposure to prions in the environment is greater where percent clay is less than 18% and soil pH is greater than 6.6. These characteristics could alter availability of prions immobilized in soil and contribute to the environmental risk factors involved in the epidemiological complexity of CWD infection in natural populations of white-tailed deer.

Model-free extraction of spin label position distributions from pseudocontact shift data.

A significant problem with paramagnetic tags attached to proteins and nucleic acids is their conformational mobility. Each tag is statistically distributed within a volume between 5 and 10 Angstroms across; structural biology conclusions from NMR and EPR work are necessarily diluted by this uncertainty. The problem is solved in electron spin resonance, but remains open in the other major branch of paramagnetic resonance - pseudocontact shift (PCS) NMR spectroscopy, where structural biologists have so far been reluctantly using the point paramagnetic centre approximation. Here we describe a new method for extracting probability densities of lanthanide tags from PCS data. The method relies on Tikhonov-regularised 3D reconstruction and opens a new window into biomolecular structure and dynamics because it explores a very different range of conditions from those accessible to double electron resonance work on paramagnetic tags: a room-temperature solution rather than a glass at cryogenic temperatures. The method is illustrated using four different Tm3+ DOTA-M8 tagged mutants of human carbonic anhydrase II; the results are in good agreement with rotamer library and DEER data. The wealth of high-quality pseudocontact shift data accumulated by the biological magnetic resonance community over the last 30 years, and so far only processed using point models, could now become a major source of useful information on conformational distributions of paramagnetic tags in biomolecules.