Mesoscale oceanographic meanders influence protist community function and structure in the southern Indian Ocean

The interface between the nutrient-rich Southern Ocean and oligotrophic Indian Ocean creates unique environmental conditions that can strongly influence biological processes. We investigated protist communities across a mesoscale meander of the Subtropical Front within the Southern Indian Ocean. 18S V9 rDNA metabarcoding suggests a diverse protist community in which the dinoflagellates and parasitic Syndiniales were abundant. Diversity was highest in frontal waters of the mesoscale meander, with differences in community structure inside and outside the meander. While the overall community was dominated by mixotrophic taxa, the frontal boundary of the meander had increased abundances of heterotrophic taxa, with potential implications for net atmospheric CO2 drawdown. Pulse amplitude modulated (PAM) fluorimetry revealed significant differences in the photophysiology of phytoplankton communities inside and outside the meander. By using single-cell PAM microscopy, we identified physiological differences between dinoflagellate and coccolithophore taxa, which may have contributed to changes in photophysiology observed at community level. Overall, our results demonstrate that frontal areas have a strong impact on the composition of protist communities in the Southern Ocean with important implications for understanding biological processes in this region

Digging the optimum pit: Antlions, spirals and spontaneous stratification

Most animal traps are constructed from self-secreted silk, so antlions are rare among trap builders because they use only materials found in the environment. We show how antlions exploit the properties of the substrate to produce very effective structures in the minimum amount of time. Our modelling demonstrates how antlions: (i) exploit self-stratification in granular media differentially to expose deleterious large grains at the bottom of the construction trench where they can be ejected preferentially, and (ii) minimize completion time by spiral rather than central digging. Both phenomena are confirmed by our experiments. Spiral digging saves time because it enables the antlion to eject material initially from the periphery of the pit where it is less likely to topple back into the centre. As a result, antlions can produce their pits—lined almost exclusively with small slippery grains to maximize powerful avalanches and hence prey capture—much more quickly than if they simply dig at the pit’s centre. Our demonstration, for the first time to our knowledge, of an animal using self-stratification in granular media exemplifies the sophistication of extended phenotypes even if they are only formed from material found in the animal’s environment

Biotic carbon feedbacks in a materially-closed soil-vegetation-atmosphere system

The magnitude and direction of the coupled feedbacks between the biotic and abiotic components of the terrestrial carbon cycle is a major source of uncertainty in coupled climate–carbon-cycle models1, 2, 3. Materially closed, energetically open biological systems continuously and simultaneously allow the two-way feedback loop between the biotic and abiotic components to take place4, 5, 6, 7, but so far have not been used to their full potential in ecological research, owing to the challenge of achieving sustainable model systems6, 7. We show that using materially closed soil–vegetation–atmosphere systems with pro rata carbon amounts for the main terrestrial carbon pools enables the establishment of conditions that balance plant carbon assimilation, and autotrophic and heterotrophic respiration fluxes over periods suitable to investigate short-term biotic carbon feedbacks. Using this approach, we tested an alternative way of assessing the impact of increased CO2 and temperature on biotic carbon feedbacks. The results show that without nutrient and water limitations, the short-term biotic responses could potentially buffer a temperature increase of 2.3 °C without significant positive feedbacks to atmospheric CO2. We argue that such closed-system research represents an important test-bed platform for model validation and parameterization of plant and soil biotic responses to environmental changes

Characterisation and expression of SPLUNC2, the human orthologue of rodent parotid secretory protein

We recently described the Palate Lung Nasal Clone (PLUNC) family of proteins as an extended group of proteins expressed in the upper airways, nose and mouth. Little is known about these proteins, but they are secreted into the airway and nasal lining fluids and saliva where, due to their structural similarity with lipopolysaccharide-binding protein and bactericidal/permeability-increasing protein, they may play a role in the innate immune defence. We now describe the generation and characterisation of novel affinity-purified antibodies to SPLUNC2, and use them to determine the expression of this, the major salivary gland PLUNC. Western blotting showed that the antibodies identified a number of distinct protein bands in saliva, whilst immunohistochemical analysis demonstrated protein expression in serous cells of the major salivary glands and in the ductal lumens as well as in cells of minor mucosal glands. Antibodies directed against distinct epitopes of the protein yielded different staining patterns in both minor and major salivary glands. Using RT-PCR of tissues from the oral cavity, coupled with EST analysis, we showed that the gene undergoes alternative splicing using two 5' non-coding exons, suggesting that the gene is regulated by alternative promoters. Comprehensive RACE analysis using salivary gland RNA as template failed to identify any additional exons. Analysis of saliva showed that SPLUNC2 is subject to N-glycosylation. Thus, our study shows that multiple SPLUNC2 isoforms are found in the oral cavity and suggest that these proteins may be differentially regulated in distinct tissues where they may function in the innate immune response

Methylation of hMLH1 promoter correlates with the gene silencing with a region-specific manner in colorectal cancer

Microsatellite instability is present in over 80% of the hereditary non-polyposis colorectal carcinoma and about 15–20% of the sporadic cancer. Microsatellite instability is caused by the inactivation of the mismatch repair genes, such as primarily hMLH1, hMSH2. To study the mechanisms of the inactivation of mismatch repair genes in colorectal cancers, especially the region-specific methylation of hMLH1 promoter and its correlation with gene expression, we analysed microsatellite instability, expression and methylation of hMLH1 and loss of heterozygosity at hMLH1 locus in these samples. Microsatellite instability was present in 17 of 71 primary tumours of colorectal cancer, including 14 of 39 (36%) mucinous cancer and three of 32 (9%) non-mucinous cancer. Loss of hMLH1 and hMSH2 expression was detected in nine and three of 16 microsatellite instability tumours respectively. Methylation at CpG sites in a proximal region of hMLH1 promoter was detected in seven of nine tumours that showed no hMLH1 expression, while no methylation was present in normal mucosa and tumours which express hMLH1. However, methylation in the distal region was observed in all tissues including normal mucosa and hMLH1 expressing tumours. This observation indicates that methylation of hMLH1 promoter plays an important role in microsatellite instability with a region-specific manner in colorectal cancer. Loss of heterozygosity at hMLH1 locus was present in four of 17 cell lines and 16 of 54 tumours with normal hMLH1 status, while loss of heterozygosity was absent in all nine cell lines and nine tumours with abnormal hMLH1 status (mutation or loss of expression), showing loss of heterozygosity is not frequently involved in the inactivation of hMLH1 gene in sporadic colorectal cancer

Maximum Parsimony on Phylogenetic networks

Abstract Background Phylogenetic networks are generalizations of phylogenetic trees, that are used to model evolutionary events in various contexts. Several different methods and criteria have been introduced for reconstructing phylogenetic trees. Maximum Parsimony is a character-based approach that infers a phylogenetic tree by minimizing the total number of evolutionary steps required to explain a given set of data assigned on the leaves. Exact solutions for optimizing parsimony scores on phylogenetic trees have been introduced in the past. Results In this paper, we define the parsimony score on networks as the sum of the substitution costs along all the edges of the network; and show that certain well-known algorithms that calculate the optimum parsimony score on trees, such as Sankoff and Fitch algorithms extend naturally for networks, barring conflicting assignments at the reticulate vertices. We provide heuristics for finding the optimum parsimony scores on networks. Our algorithms can be applied for any cost matrix that may contain unequal substitution costs of transforming between different characters along different edges of the network. We analyzed this for experimental data on 10 leaves or fewer with at most 2 reticulations and found that for almost all networks, the bounds returned by the heuristics matched with the exhaustively determined optimum parsimony scores. Conclusion The parsimony score we define here does not directly reflect the cost of the best tree in the network that displays the evolution of the character. However, when searching for the most parsimonious network that describes a collection of characters, it becomes necessary to add additional cost considerations to prefer simpler structures, such as trees over networks. The parsimony score on a network that we describe here takes into account the substitution costs along the additional edges incident on each reticulate vertex, in addition to the substitution costs along the other edges which are common to all the branching patterns introduced by the reticulate vertices. Thus the score contains an in-built cost for the number of reticulate vertices in the network, and would provide a criterion that is comparable among all networks. Although the problem of finding the parsimony score on the network is believed to be computationally hard to solve, heuristics such as the ones described here would be beneficial in our efforts to find a most parsimonious network.</p

On the Generalizability of Experimental Results

The age-old question of the generalizability of the results of experiments that are conducted in artificial laboratory settings to more realistic inferential and decision making situations is considered in this paper. Conservatism in probability revision provides an example of a result that 1) has received wide attention, including attention in terms of implications for real-world decision making, on the basis of experiments conducted in artificial settings and 2) is now apparently thought by many to be highly situational and not at all a ubiquitous phenomenon, in which case its implications for real-world decision making are not as extensive as originally claimed. In this paper we consider the questions of generalizations from the laboratory to the real world in some detail, both within the context of the experiments regarding conservatism and within a more general context. In addition, we discuss some of the difficulties inherent in experimentation in realistic settings, suggest possible procedures for avoiding or at least alleviating such difficulties, and make a plea for more realistic experiments

Long-Lost Relative Claims Orphan Gene: oskar in a Wasp

Organismic and Evolutionary Biolog

Quantum Gravity in 2+1 Dimensions: The Case of a Closed Universe

In three spacetime dimensions, general relativity drastically simplifies, becoming a ``topological'' theory with no propagating local degrees of freedom. Nevertheless, many of the difficult conceptual problems of quantizing gravity are still present. In this review, I summarize the rather large body of work that has gone towards quantizing (2+1)-dimensional vacuum gravity in the setting of a spatially closed universe.Comment: 61 pages, draft of review for Living Reviews; comments, criticisms, additions, missing references welcome; v2: minor changes, added reference

Large-Scale Phylogenetic Analysis of Emerging Infectious Diseases

Microorganisms that cause infectious diseases present critical issues of national security, public health, and economic welfare.  For example, in recent years, highly pathogenic strains of avian influenza have emerged in Asia, spread through Eastern Europe and threaten to become pandemic. As demonstrated by the coordinated response to Severe Acute Respiratory Syndrome (SARS) and influenza, agents of infectious disease are being addressed via large-scale genomic sequencing.  The goal of genomic sequencing projects are to rapidly put large amounts of data in the public domain to accelerate research on disease surveillance, treatment, and prevention. However, our ability to derive information from large comparative genomic datasets lags far behind acquisition.  Here we review the computational challenges of comparative genomic analyses, specifically sequence alignment and reconstruction of phylogenetic trees.  We present novel analytical results on from two important infectious diseases, Severe Acute Respiratory Syndrome (SARS) and influenza.SARS and influenza have similarities and important differences both as biological and comparative genomic analysis problems.  Influenza viruses (Orthymxyoviridae) are RNA based.  Current evidence indicates that influenza viruses originate in aquatic birds from wild populations. Influenza has been studied for decades via well-coordinated international efforts.  These efforts center on surveillance via antibody characterization of the hemagglutinin (HA) and neuraminidase (N) proteins of the circulating strains to inform vaccine design. However we still do not have a clear understanding of: 1) various transmission pathways such as the role of intermediate hosts such as swine and domestic birds and 2) the key mutation and genomic recombination events that underlie periodic pandemics of influenza.  In the past 30 years, sequence data from HA and N loci has become an important data type. In the past year, full genomic data has become prominent.  These data present exciting opportunities to address unanswered questions in influenza pandemics.SARS is caused by a previously unrecognized lineage of coronavirus, SARS-CoV, which like influenza has an RNA based genome.  Although SARS-CoV is widely believed to have originated in animals there remains disagreement over the candidate animal source that lead to the original outbreak of SARS.  In contrast to the long history of the study of influenza, SARS was only recognized in late 2002 and the virus that causes SARS has been documented primarily by genomic sequencing.In the past, most studies of influenza were performed on a limited number of isolates and genes suited to a particular problem.  Major goals in science today are to understand emerging diseases in broad geographic, environmental, societal, biological, and genomic contexts. Synthesizing diverse information brought together by various researchers is important to find out what can be done to prevent future outbreaks {JON03}.  Thus comprehensive means to organize and analyze large amounts of diverse information are critical.  For example, the relationships of isolates and patterns of genomic change observed in large datasets might not be consistent with hypotheses formed on partial data.  Moreover when researchers rely on partial datasets, they restrict the range of possible discoveries.Phylogenetics is well suited to the complex task of understanding emerging infectious disease. Phylogenetic analyses can test many hypotheses by comparing diverse isolates collected from various hosts, environments, and points in time and organizing these data into various evolutionary scenarios.  The products of a phylogenetic analysis are a graphical tree of ancestor-descendent relationships and an inferred summary of mutations, recombination events, host shifts, geographic, and temporal spread of the viruses.  However, this synthesis comes at a price.  The cost of computation of phylogenetic analysis expands combinatorially as the number of isolates considered increases. Thus, large datasets like those currently produced are commonly considered intractable.  We address this problem with synergistic development of heuristics tree search strategies and parallel computing.Fil: Janies, D.. Ohio State University; Estados UnidosFil: Pol, Diego. Ohio State University; Estados Unidos. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin