Monitoring temporal trends in spatially structured populations: how should sampling effort be allocated between space and time?

Estimating temporal trends in spatially structured populations has a critical role to play in understanding regional changes in biological populations and developing management strategies. Designing effective monitoring programmes to estimate these trends requires important decisions to be made about how to allocate sampling effort among spatial replicates (i.e. number of sites) and temporal replicates (i.e. how often to survey) to minimise uncertainty in trend estimates. In particular, the optimal mix of spatial and temporal replicates is likely to depend upon the spatial and temporal correlations in population dynamics. Although there has been considerable interest in the ecological literature on understanding spatial and temporal correlations in species’ population dynamics, little attention has been paid to its consequences for monitoring design. We address this issue using model‐based survey design to identify the optimal allocation of sampling effort among spatial and temporal replicates for estimating population trends under different levels of spatial and temporal correlation. Based on linear trends, we show that how we should allocate sampling effort among spatial and temporal replicates depends crucially on the spatial and temporal correlations in population dynamics, environmental variation, observation error and the spatial variation in temporal trends. When spatial correlation is low and temporal correlation is high, the best option is likely to be to sample many sites infrequently, particularly when observation error and/or spatial variation in temporal trends are high. When spatial correlation is high and temporal correlation is low, the best option is likely to be to sample few sites frequently, particularly when observation error and/or spatial variation in temporal trends are low. When abundances are spatially independent, it is always preferable to maximise spatial replication. This provides important insights into how spatio‐temporal monitoring programmes should be designed to estimate temporal trends in spatially structured populations.     

Development of a seed DNA-based genotyping system for marker-assisted selection in maize

Leaf collection from the field, labeling and tracking back to the source plants after genotyping are rate limiting steps in leaf DNA-based genotyping. In this study, an optimized genotyping method using endosperm DNA sampled from single maize seeds was developed, which can be used to replace leaf DNA-based genotyping for both genetic studies and breeding applications. A similar approach is likely to be suitable for all plants with relatively large seeds. Part of the endosperm was excised from imbibed maize seeds and DNA extracted in 96-tube plates using individuals from eight F₂ populations and seven inbreds. The quality of the resultant DNA was functionally comparable to DNA extracted from leaf tissue. Extraction from 30 mg of endosperm yields 3–10 μg DNA, which is sufficient for analysis of 200–400 agarose-gel PCR-based markers, with the potential for several million chip-based SNP marker analyses. By comparing endosperm DNA and leaf DNA for individuals from an F₂ population, genotyping errors caused by pericarp contamination and hetero-fertilization were found to average 3.8 and 0.6%, respectively. Endosperm sampling did not affect germination rates under controlled conditions, although under normal field conditions the germination rate, seedling establishment, and growth vigor were significantly lower than that of non-sampled controls for some genotypes. However, careful field management can compensate for these effects. Seed DNA-based genotyping lowered costs by 24.6% compared to leaf DNA-based genotyping due to reduced field plantings and labor costs. A substantial advantage of this approach is that it can be used to select desirable genotypes before planting. As such it provides an opportunity for dramatic improvements in the efficiency and selective gain of breeding systems based on optimum combinations of marker-assisted selection and phenotypic selection within and between generations.     

Morphologically cryptic biological species within the liverwort Frullania asagrayana

? Premise of the study: The Frullania tamarisci complex includes eight Holarctic liverwort species. One of these, F. asagrayana, is distributed broadly throughout eastern North America from Canada to the Gulf Coast. Preliminary genetic data suggested that the species includes two groups of populations. This study was designed to test whether the two groups are reproductively isolated biological species. ? Methods: Eighty-eight samples from across the range of F. asagrayana, plus 73 samples from one population, were genotyped for 13 microsatellite loci. Sequences for two plastid loci and nrITS were obtained from 13 accessions. Genetic data were analyzed using coalescent models and Bayesian inference. ? Key results: Frullania asagrayana is sequence-invariant at the two plastid loci and ITS2, but two clear groups were resolved by microsatellites. The two groups are largely reproductively isolated, but there is a low level of gene flow from the southern to the northern group. No gene flow was detected in the other direction. A local population was heterogeneous but displayed strong genetic structure. ? Conclusions: The genetic structure of F. asagrayana in eastern North America reflects morphologically cryptic differentiation between reproductively isolated groups of populations, near-panmixis within groups, and clonal propagation at local scales. Reproductive isolation between groups that are invariant at the level of nucleotide sequences shows that caution must be exercised in making taxonomic and evolutionary inferences from reciprocal monophyly (or lack thereof) between putative species.     

Nitric oxide,NOC-12, and S-nitrosoglutathione modulate the skeletal muscle calcium release channel/ryanodine receptor by different mechanisms. An allosteric function for O2 in S-nitrosylation of the channel

The skeletal muscle Ca(2+) release channel/ryanodine receptor (RyR1) contains approximately 50 thiols per subunit. These thiols have been grouped according to their reactivity/responsiveness toward NO, O(2), and glutathione, but the molecular mechanism enabling redox active molecules to modulate channel activity is poorly understood. In the case of NO, very low concentrations (submicromolar) activate RyR1 by S-nitrosylation of a single cysteine residue (Cys-3635), which resides within a calmodulin binding domain. S-Nitrosylation of Cys-3635 only takes place at physiological tissue O(2) tension (pO(2); i.e. approximately 10 mm Hg) but not at pO(2) approximately 150 mm Hg. Two explanations have been offered for the loss of RyR1 responsiveness to NO at ambient pO(2), i.e. Cys-3635 is oxidized by O(2) versus O(2) subserves an allosteric function (Eu, J. P., Sun, J. H., Xu, L., Stamler, J. S., and Meissner, G. (2000) Cell 102, 499-509). Here we report that the NO donors NOC-12 and S-nitrosoglutathione both activate RyR1 by release of NO but do so independently of pO(2). Moreover, NOC-12 activates the channel by S-nitrosylation of Cys-3635 and thereby reverses channel inhibition by calmodulin. In contrast, S-nitrosoglutathione activates RyR1 by oxidation and S-nitrosylation of thiols other than Cys-3635 (and calmodulin is not involved). Our results suggest that the effect of pO(2) on RyR1 S-nitrosylation is exerted through an allosteric mechanism.     

Boats, Pathways, and Aquatic Biological Invasions: Estimating Dispersal Potential with Gravity Models

Biological invaders can have dramatic effects on the environment and the economy. To most effectively manage these invaders, we should consider entire pathways, because multiple species are dispersed through the same vectors. In this paper, we use production-constrained gravity models to describe movement of recreational boaters between lakes – potentially the most important pathway of overland dispersal for many aquatic organisms. These models are advantageous because they require relatively easily acquired data, hence are relatively easy to build. We compare linear and non-linear gravity models and show that, despite their simplicity, they are able to capture important characteristics of the recreational boater pathway. To assess our model, we compared observed data based on creel surveys and mailed surveys of recreation boaters to the model output. Specifically, we evaluate four metrics of pathway characteristics: boater traffic to individual lakes, distances traveled to reach these lakes, Great Lakes usage and movement from the Great Lakes to inland waters. These factors will influence the propagule pressure (hence the probability of establishment of invasive populations) and the rate of spread across a landscape. The Great Lakes are of particular importance because they are a major entry point of non-indigenous species from other continents, hence will act as the origin for further spread across states. The non-linear model had the best fit between model output and empirical observations with r² =0.80, r² =0.35, r² =0.57, and r² =0.36 for the four metrics, respectively. For the distances traveled to individual lakes, r² improved from 0.35 to 0.76 after removal of an outlier. Our results suggest that we were able to capture distances traveled to most but not all lakes. Thus, we demonstrate that production-constrained gravity models will be generally useful for modeling invasion pathways between non-contiguous locations.     

Molecular characterization of proprotein convertase subtilisin/kexin type 9-mediated degradation of the LDLR

Proprotein convertase subtilisin/kexin type 9 (PCSK9) is a secreted protein that promotes degradation of cell surface LDL receptors (LDLRs) in selected cell types. Here we used genetic and pharmacological inhibitors to define the pathways involved in PCSK9-mediated LDLR degradation. Inactivating mutations in autosomal recessive hypercholesterolemia (ARH), an endocytic adaptor, blocked PCSK9-mediated LDLR degradation in lymphocytes but not in fibroblasts. Thus, ARH is not specifically required for PCSK9-mediated LDLR degradation. Knockdown of clathrin heavy chain with siRNAs prevented LDLR degradation. In contrast, prevention of ubiquitination of the LDLR cytoplasmic tail, inhibition of proteasomal activity, or disruption of proteins required for lysosomal targeting via macroautophagy (autophagy related 5 and 7) or the endosomal sorting complex required for trafficking (ESCRT) pathway (hepatocyte growth factor-regulated Tyr-kinase substrate and tumor suppressor gene 101) failed to block PCSK9-mediated LDLR degradation. These findings are consistent with a model in which the LDLR-PCSK9 complex is internalized via clathrin-mediated endocytosis and then routed to lysosomes via a mechanism that does not require ubiquitination and is distinct from the autophagy and proteosomal degradation pathways. Finally, the PCSK9-LDLR complex appears not to be transported by the canonical ESCRT pathway.     

Status,trends, and equilibrium abundance estimates of the translocated sea otter population in Washington State

Sea otters (Enhydra lutris kenyoni) historically occurred in Washington State, USA, until their local extinction in the early 1900s as a result of the maritime fur trade. Following their extirpation, 59 sea otters were translocated from Amchitka Island, Alaska, USA, to the coast of Washington, with 29 released at Point Grenville in 1969 and 30 released at La Push in 1970. The Washington Department of Fish and Wildlife has outlined 2 main objectives for sea otter recovery: a target population level and a target geographic distribution. Recovery criteria are based on estimates of population abundance, equilibrium abundance (K), and geographic distribution; therefore, estimates of these parameters have important management implications. We compiled available survey data for sea otters in Washington State since their translocation (1977–2019) and fit a Bayesian state-space model to estimate past and current abundance, and equilibrium abundance at multiple spatial scales. We then used forward projections of population dynamics to explore potential scenarios of range recolonization and as the basis of a sensitivity analysis to evaluate the relative influence of movement behavior, frontal wave speed, intrinsic growth, and equilibrium density on future population recovery potential. Our model improves upon previous analyses of sea otter population dynamics in Washington by partitioning and quantifying sources of estimation error to estimate population dynamics, by providing robust estimates of K, and by simulating long-term population growth and range expansion under a range of realistic parameter values. Our model resulted in predictions of population abundance that closely matched observed counts. At the range-wide scale, the population size in our model increased from an average of 21 independent sea otters (95% CI = 13–29) in 1977 to 2,336 independent sea otters (95% CI = 1,467–3,359) in 2019. The average estimated annual growth rate was 12.42% and varied at a sub-regional scale from 6.42–14.92%. The overall estimated mean K density of sea otters in Washington was 1.71 ± 0.90 (SD) independent sea otters/km² of habitat (1.96 ± 1.04 sea otters/km², including pups), and estimated densities within the current range correspond on average to 87% of mean sub-regional equilibrium values (range = 66–111%). The projected value of K for all of Washington was 5,287 independent sea otters (95% CI = 2,488–8,086) and 6,080 sea otters including pups (95% CI = 2,861–9,300), assuming a similar range of equilibrium densities in currently un-occupied habitats. Sensitivity analysis of simulations of sea otter population growth and range expansion suggested that mean K density estimates in currently occupied sub-regions had the largest impact on predicted future population growth (r² = 0.52), followed by the rate of southward range expansion (r² = 0.26) and the mean K density estimate of currently unoccupied sub-regions to the south of the current range (r² = 0.04). Our estimates of abundance and sensitivity analysis of simulations of future population abundance and geographic range help determine population status in relation to population recovery targets and identify the most influential parameters affecting future population growth and range expansion for sea otters in Washington State.     

25-Hydroxyvitamin D depletion does not exacerbate MPTP-induced dopamine neuron damage in mice

Recent clinical evidence supports a link between 25-hydroxyvitamin D insufficiency (serum 25-hydroxyvitamin D [25(OH)D] levels <30 ng/mL) and Parkinson's disease. To investigate the effect of 25(OH)D depletion on neuronal susceptibility to toxic insult, we induced a state of 25(OH)D deficiency in mice and then challenged them with the dopaminergic neurotoxin 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP). We found there was no significant difference between control and 25(OH)D-deficient animals in striatal dopamine levels or dopamine transporter and tyrosine hydroxylase expression after lesioning with MPTP. Additionally, we found no difference in tyrosine hydroxylase expression in the substantia nigra pars compacta. Our data suggest that reducing 25(OH)D serum levels in mice has no effect on the vulnerability of nigral dopaminergic neurons in vivo in this model system of parkinsonism.     

Multi-Stability and Multi-Instability Phenomena in a Mathematical Model of Tumor-Immune-Virus Interactions

Recent advances in virology, gene therapy, and molecular and cell biology have provided insight into the mechanisms through which viruses can boost the anti-tumor immune response, or can infect and directly kill tumor cells. A recent experimental report (Bridle et al. in Molec. Ther. 18(8):1430–1439, 2010) showed that a sequential treatment approach that involves two viruses that carry the same tumor antigen leads to an improved anti-tumor response compared to the effect of each virus alone. In this article, we derive a mathematical model to investigate the anti-tumor effect of two viruses, and their interactions with the immune cells. We discuss the conditions necessary for permanent tumor elimination and, in this context, we stress the importance of investigating the long-term effect of non-linear interactions. In particular, we discuss multi-stability and multi-instability, two complex phenomena that can cause abrupt transitions between different states in biological and physical systems. In the context of cancer immunotherapies, the transitions between a tumor-free and a tumor-present state have so far been associated with the multi-stability phenomenon. Here, we show that multi-instability can also cause the system to switch from one state to the other. In addition, we show that the multi-stability is driven by the immune response, while the multi-instability is driven by the presence of the virus.     

A high-confidence human plasma proteome reference set with estimated concentrations in PeptideAtlas

Human blood plasma can be obtained relatively noninvasively and contains proteins from most, if not all, tissues of the body. Therefore, an extensive, quantitative catalog of plasma proteins is an important starting point for the discovery of disease biomarkers. In 2005, we showed that different proteomics measurements using different sample preparation and analysis techniques identify significantly different sets of proteins, and that a comprehensive plasma proteome can be compiled only by combining data from many different experiments. Applying advanced computational methods developed for the analysis and integration of very large and diverse data sets generated by tandem MS measurements of tryptic peptides, we have now compiled a high-confidence human plasma proteome reference set with well over twice the identified proteins of previous high-confidence sets. It includes a hierarchy of protein identifications at different levels of redundancy following a clearly defined scheme, which we propose as a standard that can be applied to any proteomics data set to facilitate cross-proteome analyses. Further, to aid in development of blood-based diagnostics using techniques such as selected reaction monitoring, we provide a rough estimate of protein concentrations using spectral counting. We identified 20,433 distinct peptides, from which we inferred a highly nonredundant set of 1929 protein sequences at a false discovery rate of 1%. We have made this resource available via PeptideAtlas, a large, multiorganism, publicly accessible compendium of peptides identified in tandem MS experiments conducted by laboratories around the world.