The complete mitochondrial genome analysis of the tiger (<Emphasis Type="Italic">Panthera tigris</Emphasis>)

The complete mitochondrial genomes of five tiger samples from three subspecies (P. t. sumatrae, P. t. altica, and P. t. tigris) were successfully obtained by using 26 specifically designed Panthera-specific primer sets. The genome organization and gene arrangement of the five tiger samples were similar to each other; however polymorphic tandem repeat sequences were observed in the control region (CR). This led to a difference in the genome lengths obtained from these five samples with an average size of 16,994 bp for the five tiger mitochondrial genomes. The nucleotide base composition was on average as follows: A, 31.8%; T, 27.0%; C, 26.6%; G, 14.6% and exhibited compositional asymmetry. Most of tiger mitochondrial genome characteristics are similar to those of other common vertebrate species; however, some distinctive features were observed in the CR. First, the repetitive sequence 2 (RS 2) contained two repeat units of 80 bp and the first 15 bp of what would be the third repeat motif. The repetitive sequence 3 (RS 3) contained 47–50 repeat motifs of a shorter 8 bp (ACGTAYAC)_n. Second, length heteroplasmy polycystosine (poly-C) stretches was observed at the end of the HV I locus in all tiger samples.     

Microbial 16S rRNA Ion Tag and community metagenome sequencing using the Ion Torrent (PGM) Platform

Here we demonstrate a cost effective and scalable microbial ecology sequencing platform using the Ion Torrent Personal Genome Machine (PGM). We assessed both PCR amplified 16S rRNA and shotgun metagenomic approaches and generated 100,000+ to 1,000,000+ reads using 'post-light' based sequencing technology within different sized semi-conductor chips. Further development of Golay barcoded Ion Tags allowed multiplex analyses of microbial communities with substantially reduced costs compared with platforms such as 454/GS-FLX. Using these protocols we assessed the bacterial and archaeal dynamics within covered anaerobic digesters used to treat piggery wastes. Analysis of these sequence data showed that these novel methanogenic waste treatment systems are dominated by bacterial taxa, in particular Clostridium, Synergistia and Bacteroides that were maintained as a stable community over extended time periods. Archaeal community dynamics were more stochastic with the key methanogenic taxa more difficult to resolve, principally due to the poor congruence seen between community structures generated either by nested PCR or metagenomic approaches for archaeal analyses. Our results show that for microbial community structure and function analyses, the PGM platform provides a low cost, scalable and high throughput solution for both Tag sequencing and metagenomic analyses.     

Interaction specificity between the chaperone and proteolytic components of the cyanobacterial Clp protease

The Clp protease is conserved among eubacteria and most eukaryotes, and uses ATP to drive protein substrate unfolding and translocation into a chamber of sequestered proteolytic active sites. In plant chloroplasts and cyanobacteria, the essential constitutive Clp protease consists of the Hsp100/ClpC chaperone partnering a proteolytic core of catalytic ClpP and noncatalytic ClpR subunits. In the present study, we have examined putative determinants conferring the highly specific association between ClpC and the ClpP3/R core from the model cyanobacterium Synechococcus elongatus. Two conserved sequences in the N-terminus of ClpR (tyrosine and proline motifs) and one in the N-terminus of ClpP3 (MPIG motif) were identified as being crucial for the ClpC-ClpP3/R association. These N-terminal domains also influence the stability of the ClpP3/R core complex itself. A unique C-terminal sequence was also found in plant and cyanobacterial ClpC orthologues just downstream of the P-loop region previously shown in Escherichia coli to be important for Hsp100 association to ClpP. This R motif in Synechococcus ClpC confers specificity for the ClpP3/R core and prevents association with E. coli ClpP; its removal from ClpC reverses this core specificity.     

Patch Use in Free‐Ranging Goats: Does a Large Mammalian Herbivore Forage like Other Central Place Foragers?

Classic central place foraging theory does not focus on the foraging of central place herbivores. This is especially true with regard to large mammalian herbivores. To understand the foraging dynamics of these neglected foragers, we measured giving‐up densities (GUDs) in artificial food patches. We did this at different distances away from the central point (i.e. corral) for a herd of free‐ranging domestic goats. To determine temporal changes, we conducted the study over a 3‐mo period during an extended dry season. Throughout our study, goats foraged across a gradient of food availability where forage was more available farther away from the central point. In contrast to the prediction that predation risk and/or increased travel costs were the main drivers of foraging decisions, we found that the goats increased their feeding effort (i.e. achieved lower GUDs) the farther away they moved from the central point. This suggests that either metabolic or missed opportunity costs were the main factors that influenced foraging decisions. In addition, we suggest that social foraging may have also played a role. With increases in foraging opportunities away from the central point, a herd will likely move slowly while foraging. As a result, individuals can feed intensively from patches but remain part of the group. Ironically, owing to the sustained close proximity of other group members, individuals may perceive patches farther from the central point as being safer. Temporally, the goats increased their feeding effort throughout the dry season. This suggests there was a decline in food quality and/or availability across the environment as the study progressed. Despite this increase in feeding effort, the negative relationship with distance did not change. Ultimately, our results provide key insight into how metabolic, missed opportunity and perceived predation costs influence the feeding decisions of large central place herbivores.     

Genetic markers on BTA14 predictive for residual feed intake in beef steers and their effects on carcass and meat quality traits

With the high cost of feed for animal production, genetic selection for animals that metabolize feed more efficiently could result in substantial cost savings for cattle producers. The purpose of this study was to identify DNA markers predictive for differences among cattle for traits associated with feed efficiency. Crossbred steers were fed a high‐corn diet for 140 days and average daily feed intake (ADFI), average daily gain (ADG), and residual feed intake (RFI) phenotypes were obtained. A region on chromosome 14 was previously associated with RFI in this population of animals. To develop markers with the highest utility for predicting an animal's genetic potential for RFI, we genotyped additional markers within this chromosomal region. These polymorphisms were genotyped on the same animals (n = 1066) and tested for association with ADFI, ADG and RFI. Six markers within this region were associated with RFI (P ≤ 0.05). After conservative correction for multiple testing, one marker at 25.09 Mb remained significant (P = 0.02) and is responsible for 3.6% of the RFI phenotypic variation in this population of animals. Several of these markers were also significant for ADG, although none were significant after correction. Marker alleles with positive effects on ADG corresponded to lower RFI, suggesting an effect increasing growth without increasing feed intake. All markers were also assessed for their effects on meat quality and carcass traits. All of the markers associated with RFI were associated with adjusted fat thickness (AFT, P ≤ 0.009) and three were also associated with hot carcass weight (HCW, P ≤ 0.003). Marker alleles associated with lower RFI were also associated with reduced AFT, and if they were associated for HCW, the effect was an increase in weight. These markers may be useful as prediction tools for animals that utilize feed more efficiently; however, validation with additional populations of cattle is required.     

Protein dynamics and enzyme catalysis: the ghost in the machine?

One of the most controversial questions in enzymology today is whether protein dynamics are significant in enzyme catalysis. A particular issue in these debates is the unusual temperature-dependence of some kinetic isotope effects for enzyme-catalysed reactions. In the present paper, we review our recent model [Glowacki, Harvey and Mulholland (2012) Nat. Chem. 4, 169-176] that is capable of reproducing intriguing temperature-dependences of enzyme reactions involving significant quantum tunnelling. This model relies on treating multiple conformations of the enzyme-substrate complex. The results show that direct 'driving' motions of proteins are not necessary to explain experimental observations, and show that enzyme reactivity can be understood and accounted for in the framework of transition state theory.     

Drivers and stressors of freshwater biodiversity patterns across different ecosystems and scales: a review

The present review with focus on the last decade (2000–2010) aims to (i) collecting the major hypotheses explaining freshwater biodiversity patterns, (ii) identifying the main stressors affecting freshwater biodiversity, and (iii) revealing information gaps regarding ecosystem types, organism groups, spatial and temporal scales to highlight research needs to better propose sound conservation measures. The comparative analysis addresses six organism groups ranging from microorganisms to fish in basins, rivers, lakes, wetlands, ponds and groundwater. Short-term studies at ecoregion and catchment scale focusing on invertebrates, macrophytes and fish in Palaearctic and Nearctic regions dominated. The most frequent hypotheses tested were the landscape filter concept, the species–area relationship, the metacommunity concept. Dominating natural drivers were area, heterogeneity and disturbance. Land use, eutrophication and habitat destruction were identified as most important stressors. Generally, freshwater biodiversity declined in response to these stressors in contrast to increasing biodiversity determined by natural drivers across all ecosystems. Preferred organism groups were fish and invertebrates, most frequently studied in rivers, in contrast to smaller organisms (e.g. bacteria) and, e.g. groundwater being underrepresented. Hypotheses originating from the last century are still tested in freshwater research, while novel concepts are either missing or untested. Protection of freshwater biodiversity is the ultimate challenge since it supports valuable ecosystems services ensuring perpetuation of mankind. For that, comprehensive large-scale studies with holistic approaches are urgently needed.     

Comparison of regression methods for phenology

Several methods exist for investigation of the relationship between records and weather data. These can be broadly classified into models that attempt to incorporate information about underlying biological processes, such as those based on the concept of thermal time, and linear regression methods. The latter are less driven by the biology but have the advantages of ease of use and flexibility. Regression can be used where there is no obvious mechanistic model or to suggest the form of a mechanistic or empirical model where there are several to choose from. Stepwise regression is commonly used in phenology. However, it requires aggregation of the weather records, resulting in loss of information. Penalised signal regression (PSR) was recently introduced to overcome this weakness. Here, we introduce a further method to the phenology context called fusion, which is a sparse version of PSR. In this paper, we compare the performance of these three regression methods based on simulations from two types of mechanistic models, the spring warming and sequential models. Given a suitable choice of temperature days as regression covariates, PSR and fusion performed better than stepwise regression for the spring warming model and PSR performed best for the sequential model. However, if a large number of redundant temperature days were included as covariates, the performance of PSR fell off whilst fusion was quite robust to this change. For this reason, it is best to use PSR and fusion methods in tandem, and to vary the number of covariates included.