Estimating survival of a streamside salamander: importance of temporary emigration,capture response,and location

Estimating survival for highly secretive aquatic animals, such as stream salamanders, presents numerous challenges. Salamanders often spend a considerable time in refugia where they are difficult to capture. Few studies have calculated vital rates for stream salamanders, yet the need is substantial as they are threatened by a wide range of land-use stressors, especially urban development. In this study, we used 34 months of continuous field samples collected at an urban and undisturbed stream and robust design mark-recapture analysis to evaluate the importance of temporary emigration, capture response, and location on survival estimates of the salamander Desmognathus fuscus. We constructed a set of candidate models incorporating combinations of time- and location-varying capture and recapture probabilities, capture responses, temporary emigration, and survival estimates and ranked models using Akaike’s Information Criterion. We found strong support for month-specific capture probabilities, recapture probabilities, temporary emigration and a negative behavioral response to capture in the majority of months. We found no support for variation in capture probabilities, recapture probabilities, and temporary emigration between locations. However, we found that location strongly influenced survival estimates. Specifically, survival estimates were significantly higher at the undisturbed site than at the urban site. Our results emphasize the importance of estimating capture probabilities, recapture probabilities, capture response, and temporary emigration when evaluating survival in highly secretive aquatic animals. Failure to account for these population parameters will likely yield biased estimates of survival in freshwater animal populations.     

Comparison of ARIMA and Random Forest time series models for prediction of avian influenza H5N1 outbreaks

Background

Time series models can play an important role in disease prediction. Incidence data can be used to predict the future occurrence of disease events. Developments in modeling approaches provide an opportunity to compare different time series models for predictive power.

Results

We applied ARIMA and Random Forest time series models to incidence data of outbreaks of highly pathogenic avian influenza (H5N1) in Egypt, available through the online EMPRES-I system. We found that the Random Forest model outperformed the ARIMA model in predictive ability. Furthermore, we found that the Random Forest model is effective for predicting outbreaks of H5N1 in Egypt.

Conclusions

Random Forest time series modeling provides enhanced predictive ability over existing time series models for the prediction of infectious disease outbreaks. This result, along with those showing the concordance between bird and human outbreaks (Rabinowitz et al. 2012), provides a new approach to predicting these dangerous outbreaks in bird populations based on existing, freely available data. Our analysis uncovers the time-series structure of outbreak severity for highly pathogenic avain influenza (H5N1) in Egypt.     

Purification of a hepatic S6 kinase from cycloheximide-treated Rats

Cycloheximide injection of rats results in the activation of a protein kinase that phosphorylates 40 S ribosomal protein S6. This Ca2+/cyclic nucleotide-independent kinase exhibits chromatographic properties that are indistinguishable from the S6 kinase in H4 hepatoma cells whose activity is stimulated by insulin and growth factors and the S6 kinase that is activated during liver regeneration. The enzyme has been purified 50,000-fold to near homogeneity: a critical step in purification employs a peptide affinity column using a synthetic peptide corresponding to the carboxyl-terminal 32-amino acid residues of mouse liver S6, which encompasses all S6 phosphorylation sites. The purified enzyme is a 70,000-dalton polypeptide that is reactive with azido-ATP. In addition to 40 S ribosomal S6 and the synthetic peptide, the S6 kinase catalyzes rapid phosphorylation of a number of other protein substrates including histone H2b, glycogen synthase, and ATP citrate lyase; this last protein is phosphorylated by S6 kinase in vitro on the same serine residue that is phosphorylated in response to insulin and epidermal growth factor in intact hepatocytes. Moreover, the S6 kinase catalyzes the phosphorylation of a number of hepatic nonhistone nuclear proteins. This S6 kinase probably underlies the increased hepatic S6 phosphorylation observed after cycloheximide treatment, which in turn corresponds to the mitogen-activated S6 kinase.     

Heterogeneity in human interleukin-3 receptors. A subclass that binds human granulocyte/macrophage colony stimulating factor

125I-Labeled recombinant human interleukin-3 (IL-3) was used to study the characteristics and distribution of receptors for IL-3 on human cells. Receptors were found on primary monocytes, on some strains of KG-1 cells, and on pre-B cell lines. Binding was rapid at 37 degrees C, while requiring several hours to reach equilibrium at 4 degrees C. Equilibrium binding studies indicated that IL-3 bound to a single class of high affinity receptor (less than 500 receptors/cell) with a Ka of approximately 1 x 10(10) M-1. Inhibition studies revealed that human granulocyte/macrophage colony stimulating factor partially inhibited the binding of 125I-IL-3 to human monocytes but not JM-1 cells. Additional analysis showed that on KG-1 cells, both IL-3 and GM-CSF partially competed specific binding of heterologous radiolabeled ligand, with approximately equivalent capacities. This competition occurred at both 37 and 4 degrees C. These results suggest heterogeneity in the binding sites for IL-3 and GM-CSF in which a subset of receptors binds only IL-3, a subset only GM-CSF, and another subset can bind both, all with high affinity. Additional heterogeneity was suggested by equilibrium binding of 125I-IL-3 to KG-1 cells which revealed a biphasic Scatchard plot containing a low affinity component not observed on monocytes and JM-1 cells.     

Learning and signal copying facilitate communication among bird species

Signals relevant to different sets of receivers in different contexts create a conflict for signal design. A classic example is vocal alarm signals, often used both during intraspecific and interspecific interactions. How can signals alert individuals from a variety of other species in some contexts, while also maintaining efficient communication among conspecifics? We studied heterospecific responses to avian alarm signals that drive the formation of anti-predator groups but are also used during intraspecific interactions. In three species-rich communities in the western Himalayas, alarm signals vary drastically across species. We show that, independently of differences in their calls, birds respond strongly to the alarm signals of other species with which they co-occur and much more weakly to those of species with which they do not co-occur. These results suggest that previous exposure and learning maintain heterospecific responses in the face of widespread signal divergence. At an area where only two species regularly interact, one species'' calls incorporate the call of the other. We demonstrate experimentally that signal copying allows strong responses even without previous exposure and suggest that such hybrid calls may be especially favoured when pairwise interactions between species are strong.     

Chromosomal mapping of Xenopus 5S genes: somatic-type versus oocyte-type.

Xenopus 5S RNA genes exhibit a pattern of differential expression during development in which some members (oocyte-type) are transcribed only in oocytes, while others (somatic-type) are expressed in both oocytes and somatic cells. Using cloned DNA probes specific for each gene type, we determined the positions of these genes on Xenopus metaphase chromosomes by in situ hybridization. Somatic-type 5S genes in both X. laevis and X. borealis are located at the distal end of the long arm of only one chromosome (number 9). The oocyte-type 5S RNA genes are found at the distal ends of the long arms of most Xenopus chromosomes, including chromosome 9. Thus, large scale differences in chromosomal location cannot explain the selective expression of these genes, as suggested previously.     

Human TEN1 Maintains Telomere Integrity and Functions in Genome-wide Replication Restart

TEN1 is a component of the mammalian CTC1-STN1-TEN1 complex. CTC1 and/or STN1 functions in telomere duplex replication, C-strand fill-in, and genome-wide restart of replication following fork stalling. Here we examine the role of human TEN1 and ask whether it also functions as a specialized replication factor. TEN1 depletion causes an increase in multitelomere fluorescent in situ hybridization (FISH) signals similar to that observed after CTC1 or STN1 depletion. However, TEN1 depletion also results in increased telomere loss. This loss is not accompanied by increased telomere deprotection, recombination, or T-circle release. Thus, it appears that both the multiple telomere signals and telomere loss stem from problems in telomere duplex replication. TEN1 depletion can also affect telomere length, but whether telomeres lengthen or shorten is cell line-dependent. Like CTC1 and STN1, TEN1 is needed for G-overhang processing. Depletion of TEN1 does not effect overhang elongation in mid-S phase, but it delays overhang shortening in late S/G₂. These results indicate a role for TEN1 in C-strand fill-in but do not support a direct role in telomerase regulation. Finally, TEN1 depletion causes a decrease in genome-wide replication restart following fork stalling similar to that observed after STN1 depletion. However, anaphase bridge formation is more severe than with CTC1 or STN1 depletion. Our findings indicate that TEN1 likely functions in conjunction with CTC1 and STN1 at the telomere and elsewhere in the genome. They also raise the possibility that TEN1 has additional roles and indicate that TEN1/CTC1-STN1-TEN1 helps solve a wide range of challenges to the replication machinery.     

Integrating sample similarities into latent class analysis: a tree-structured shrinkage approach

This paper is concerned with using multivariate binary observations to estimate the probabilities of unobserved classes with scientific meanings. We focus on the setting where additional information about sample similarities is available and represented by a rooted weighted tree. Every leaf in the given tree contains multiple samples. Shorter distances over the tree between the leaves indicate a priori higher similarity in class probability vectors. We propose a novel data integrative extension to classical latent class models with tree-structured shrinkage. The proposed approach enables (1) borrowing of information across leaves, (2) estimating data-driven leaf groups with distinct vectors of class probabilities, and (3) individual-level probabilistic class assignment given the observed multivariate binary measurements. We derive and implement a scalable posterior inference algorithm in a variational Bayes framework. Extensive simulations show more accurate estimation of class probabilities than alternatives that suboptimally use the additional sample similarity information. A zoonotic infectious disease application is used to illustrate the proposed approach. The paper concludes by a brief discussion on model limitations and extensions.     

Inhibition of in vitro nuclear transport by a lectin that binds to nuclear pores

Selective transport of proteins is a major mechanism by which biochemical differences are maintained between the cytoplasm and nucleus. To begin to investigate the molecular mechanism of nuclear transport, we used an in vitro transport system composed of a Xenopus egg extract, rat liver nuclei, and a fluorescently labeled nuclear protein, nucleoplasmin. With this system, we screened for inhibitors of transport. We found that the lectin, wheat germ agglutinin (WGA), completely inhibits the nuclear transport of fluorescently labeled nucleoplasmin. No other lectin tested affected nuclear transport. The inhibition by WGA was not seen when N-acetylglucosamine was present and was reversible by subsequent addition of sugar. When rat liver nuclei that had been incubated with ferritin-labeled WGA were examined by electron microscopy, multiple molecules of WGA were found bound to the cytoplasmic face of each nuclear pore. Gel electrophoresis and nitrocellulose transfer identified one major and several minor nuclear protein bands as binding 125I-labeled WGA. The most abundant protein of these, a 63-65-kD glycoprotein, is a candidate for the inhibitory site of action of WGA on nuclear protein transport. WGA is the first identified inhibitor of nuclear protein transport and interacts directly with the nuclear pore.     

Dissecting a complex chemical stress: chemogenomic profiling of plant hydrolysates

The efficient production of biofuels from cellulosic feedstocks will require the efficient fermentation of the sugars in hydrolyzed plant material. Unfortunately, plant hydrolysates also contain many compounds that inhibit microbial growth and fermentation. We used DNA‐barcoded mutant libraries to identify genes that are important for hydrolysate tolerance in both Zymomonas mobilis (44 genes) and Saccharomyces cerevisiae (99 genes). Overexpression of a Z. mobilis tolerance gene of unknown function (ZMO1875) improved its specific ethanol productivity 2.4‐fold in the presence of miscanthus hydrolysate. However, a mixture of 37 hydrolysate‐derived inhibitors was not sufficient to explain the fitness profile of plant hydrolysate. To deconstruct the fitness profile of hydrolysate, we profiled the 37 inhibitors against a library of Z. mobilis mutants and we modeled fitness in hydrolysate as a mixture of fitness in its components. By examining outliers in this model, we identified methylglyoxal as a previously unknown component of hydrolysate. Our work provides a general strategy to dissect how microbes respond to a complex chemical stress and should enable further engineering of hydrolysate tolerance.