A microstructurally informed model for the mechanical response of three-dimensional actin networks

We propose a class of microstructurally informed models for the linear elastic mechanical behaviour of cross-linked polymer networks such as the actin cytoskeleton. Salient features of the models include the possibility to represent anisotropic mechanical behaviour resulting from anisotropic filament distributions, and a power law scaling of the mechanical properties with the filament density. Mechanical models within the class are parameterized by seven different constants. We demonstrate a procedure for determining these constants using finite element models of three-dimensional actin networks. Actin filaments and cross-links were modelled as elastic rods, and the networks were constructed at physiological volume fractions and at the scale of an image voxel. We show the performance of the model in estimating the mechanical behaviour of the networks over a wide range of filament densities and degrees of anisotropy.     

Isolation and characterization of a mycovirus in Lentinula edodes

A mycovirus was isolated from an edible mushroom, Lentinula edodes, that was suffering from a severe epidemic. Fractionation of the diseased cell extract by isopycnic centrifugation with 50% CsCl revealed that the diseased mushroom was infected by Lentinula edodes spherical virus (LeSV), a new spherical virus with a diameter of 55 nm. The particle of LeSV encapsidated the 12 kb RNA genome by a 120 kDa coat protein. BLAST analysis of the partially sequenced LeSV genome showed 95% sequence identity with a putative RNA-dependent RNA polymerase (RdRp) gene of the mycovirus HKB, which was previously reported as being a double-stranded RNA (dsRNA) element. In contrast to HKB, the RNA genome in LeSV is encapsidated by the 120 kDa coat protein. To confirm that the LeSV coat protein is encoded by the viral genome, the N-terminal amino acid sequence of the coat protein was determined. The resulting N-terminal amino acid sequence, N-SALDVAPVVPELYFXXLEV-C, was found to be located in the middle of the HKB ORF1, suggesting that the LeSV coat protein was indeed encoded by the virus. To detect LeSV in L. edodes, a primer set targeting the RdRp gene was designed based on the partial sequence of the LeSV genome. RT-PCR analysis showed that 56 of the 84 commercially available dikaryotic cultivars carry LeSV. The transmission pattern of the virus was determined by analysing basidiospores from LeSV-infected and LeSV-free fruiting bodies. Nine out of 10 basidiospores from the LeSV-infected cultivars contained the virus while the spores from the LeSV-free parent were free of LeSV, suggesting that vertical transmission is the primary mode of LeSV propagation.     

Rhodanobacter umsongensis sp. nov., isolated from a Korean ginseng field

A bacterial isolate designated GR24-2^T was isolated from Korean soil used for cultivating ginseng (Panax ginseng C. A. Meyer). The strain was aerobic, Gram-negative, motile, and rod-shaped. It grew optimally at 28–30°C, pH 7.0, and in a range of 0–1% NaCl. Phylogenetically, the strain clustered with members of the genus Rhodanobacter. The strain exhibited the highest sequence similarities (>98%) with R. panaciterrae LnR5-47^T (98.4%), R. soli DCY45^T (98.2%), and R. ginsengisoli GR17-7^T (98.0%). However, it also showed high sequence similarities (>97%) with some other Rhodanobacter and Dyella species. The strain contained Q-8 as the predominant respiratory quinone. The major fatty acids (greater than 10% of the total fatty acids) were iso-C_17:1 ω9c (24.5%), iso-C_16:0 (22.8%), anteiso-C_15:0 (10.5%), and iso-C_15:0 (10.1%). Its major polar lipids were phosphatidylethanolamine, phosphatidylglycerol, diphosphatidylglycerol, and an unknown aminophospholipid. The DNA G+C content of strain GR24-2^T was 65.6 mol%. The strain showed less than 70% DNA relatedness values between the closely related Rhodanobacter and Dyella species. The phylogeny, phenotype, DNA-DNA hybridization, and chemotaxonomic data generated in this study reveal that the isolate is a novel species of the genus Rhodanobacter. The name proposed for this strain is Rhodanobacter umsongensis sp. nov. (type strain GR24-2^T =KACC 12917^T =DSM 21300^T).     

Pontibacter jeungdoensis sp. nov., isolated from a solar saltern in Korea

A Gram-staining-negative, rod-shaped and red-pigmented bacterial strain, HMD3125^T, was isolated from a solar saltern in Jeungdo, Republic of Korea. A phylogenetic tree based on 16S rRNA gene sequences showed that strain HMD3125^T formed a lineage within the genus Pontibacter and was similar to Pontibacter salisaro (96.1%) and P. korlensis (95.3%). The major fatty acids of strain HMD3125^T were summed feature 4 (comprising iso-C_17:1 I and/or anteiso-C_17:1 B; 30.4%), iso-C_15:0 (20.4%) and iso-C_17:0 3OH (17.2%). The polar lipid profile of HMD3125^T consisted of the phosphatidylethanolamine, four unidentified polar lipids, unidentified phospholipid, unidentified aminolipid and unidentified aminophospholipid. Strain HMD3125^T contained MK-7 as the predominant menaquinone and sym-homospermidine as the major polyamine. The DNA G+C content of strain HMD3125^T was 45.6 mol%. Strain HMD3125^T assigned as a novel species in the genus Pontibacter, for which the name Pontibacter jeungdoensis sp. nov. is proposed. The type strain is HMD3125^T (=KCTC 23156^T =CECT 7710^T).     

Minding the gaps: metabolomics mends functional genomics

Two recent studies in PNAS and Nat Chem Biol highlight the power of modern mass-spectrometry techniques for enzyme discovery applied to microbiology. In so doing, they have uncovered new potential targets for the treatment of tuberculosis.Proc Natl Acad Sci USA (2013) 110 28, 11320–11325 doi: 10.1073/pnas.1221597110Nat Chem Biol (2013). doi:10.1038/nchembio.1355. Advance online publication 29 September 2013Many have come to regard metabolism as a well-understood housekeeping activity of all cells, functionally compartmentalized away from other biological processes. However, growing reports of unexpected links between a diverse range of disease states and specific metabolic enzymes or pathways have begun to challenge this view. In doing so, such discoveries have exposed more glaring, and neglected, deficiencies in our understanding of cellular metabolism, triggering a broad resurgence of interest in metabolism.“Metabolomics […] offers a global window into the biochemical state of a cell or organism…”Metabolomics is the newest of the systems-level disciplines and seeks to reveal the physiological state of a given cell or organism through the global and unbiased study of its small-molecule metabolites [1]. Metabolites are the final products of enzymes and enzyme networks, the substrates and products of which often cannot be deduced from genetic information and the levels of which reflect the integrated product of the genome, proteome and environment [2]. Metabolomics thus offers a global window into the biochemical state of a cell or organism, made experimentally possible by the unprecedented discriminatory power and sensitivity of modern mass-spectrometry-based technologies (Fig 1). Two recent reports from the Carvalho and Neyrolles groups, published recently in Proceedings of the National Academy of Science USA and Nature Chemical Biology [3,4], exemplify the rapidly growing impact of metabolomics-based approaches on tuberculosis research.Open in a separate windowFigure 1Modern mass spectrometry illuminates bacterial metabolism. A comparison of activity-based metabolomic profiling with classic metabolic tracing. See the text for details.Within the field of infectious diseases, the deficiencies in our understanding of microbial metabolism have emerged most prominently in the area of tuberculosis research. Despite the development of the first chemotherapies more than 50 years ago, tuberculosis remains the leading bacterial cause of death worldwide, due in part to a failure to keep pace with the emergence of drug resistance [5]. The causes of this shortfall are multifactorial. However, a key contributing factor is our incomplete understanding of the metabolic properties of Mycobacterium tuberculosis (Mtb), its aetiological agent. Unlike most bacterial pathogens, Mtb infects humans as its only known host and reservoir, within whom it resides largely isolated from other microbes. Mtb has thus evolved its metabolism to serve interdependent physiological and pathogenic roles. Yet, more than a century after Koch''s initial discovery of Mtb and 15 years after the first publication of its genome sequence, knowledge of Mtb''s metabolic network remains surprisingly incomplete [6,7,8].“…tuberculosis remains the leading bacterial cause of death worldwide…”As for almost all sequenced microbial genomes, homology-based in silico approaches have failed to suggest a function for nearly 40% of Mtb genes that, presumably, include a significant number of orphan enzyme activities for which no gene has been ascribed [8]. Such approaches have further neglected the impact of evolutionary selection and its ability to dissociate sequence conservation from biochemical activity and physiological function, in order to help optimize the fitness of a given organism within its specific niche. For Mtb, such genes and enzymes represent an especially promising and biologically selective, but untapped, source of potential drug targets.In the study from the Carvalho group, successful application of a recently developed metabolomics assay—known as activity-based metabolomic profiling (ABMP)—allowed the authors to reassign a putatively annotated nucleotide phosphatase (Rv1692) as a D,L-glycerol 3-phosphate phosphatase [3,9]. ABMP was specifically developed to identify enzymatic activities for genes of unknown function by leveraging the analytical discriminatory power of liquid-chromatography-coupled high-resolution mass spectrometry (LC-MS) to analyse the impact of a recombinant enzyme and potential co-factors on a highly concentrated, small-molecule extract derived from the homologous organism (Fig 1). By monitoring for the matched time and enzyme-dependent depletion and accumulation of putative substrates and products, this assay enables the discovery of catalytic activities—rather than simple binding—by using the cellular metabolome as arguably the most physiological chemical library of potential substrates that can be tested, in a label and synthesis-free manner. Moreover, candidate activities assigned by this method can be confirmed by using independent biochemical approaches—such as reconstitution with purified components—and genetic techniques—such as wild-type and genetic knockout, knockdown or overexpression strains. In reassigning Rv1692 as a glycerol phosphate phosphatase, rather than a nucleotide phosphatase, Carvalho and colleagues demonstrate the potential of ABMP to overcome the biochemical challenge of assigning substrate specificity to a member of a large enzyme superfamily—in this case, the haloacid dehydrogenase superfamily. But, perhaps more significantly, they also direct new biological attention to the largely neglected area of Mtb membrane homeostasis, in which Rv1692 might play an important role in glycerophospholipid recycling and catabolism.“…knowledge of Mtb''s metabolic network remains surprisingly incomplete”Neyrolles and colleagues make use of the same metabolomics platform to perform metabolite-tracing studies by using stable-isotope-labelled precursors, which led them to reassign a putatively annotated asparagine transporter (AnsP1) as an aspartate transporter. AnsP1 bears 55% sequence identity and 70% similarity to an orthologue in Salmonella that belongs to the amino acid transporter family 2.A.3.1, whereas aspartate transporters are typically members of the dicarboxylate amino acid:cation symporter family 2.A.23 [4]. This study demonstrates the ability of metabolomic platforms to not only characterize the activity of a given protein within its natural physiological milieu, but also revive classical experimental methods by using modern technologies. The availability of stable (non-radioactive) isotopically labelled precursors has now made it possible to resolve their specific metabolic fates. In this case, such an approach revealed that Mtb can use aspartate as both a carbon and nitrogen source, after its uptake through AnsP1. Looking beyond the specific biochemical assignment of AnsP1 as an aspartate—rather than asparagine—transporter, this study illustrates the potential impact of such discoveries on downstream paths of investigation. In this case, the remarkable application of high-resolution dynamic secondary ion mass spectroscopy to provide the first direct biochemical images of the nutritional environment of the Mtb-infected phagosome.New technologies are often developed in the context of specific needs. However, their impact is usually not realized until extended beyond such contexts, sometimes resulting in major paradigm shifts. The above examples highlight just two emerging possibilities of how metabolomics technologies can be extended beyond the context of global comparisons and provide unique biological insights. To the extent that the analytical power of these platforms can be adapted to other functional approaches, metabolomics promises to pay handsome biochemical and physiological dividends.     

M-Finder: Uncovering functionally associated proteins from interactome data integrated with GO annotations

Background

Protein-protein interactions (PPIs) play a key role in understanding the mechanisms of cellular processes. The availability of interactome data has catalyzed the development of computational approaches to elucidate functional behaviors of proteins on a system level. Gene Ontology (GO) and its annotations are a significant resource for functional characterization of proteins. Because of wide coverage, GO data have often been adopted as a benchmark for protein function prediction on the genomic scale.

Results

We propose a computational approach, called M-Finder, for functional association pattern mining. This method employs semantic analytics to integrate the genome-wide PPIs with GO data. We also introduce an interactive web application tool that visualizes a functional association network linked to a protein specified by a user. The proposed approach comprises two major components. First, the PPIs that have been generated by high-throughput methods are weighted in terms of their functional consistency using GO and its annotations. We assess two advanced semantic similarity metrics which quantify the functional association level of each interacting protein pair. We demonstrate that these measures outperform the other existing methods by evaluating their agreement to other biological features, such as sequence similarity, the presence of common Pfam domains, and core PPIs. Second, the information flow-based algorithm is employed to discover a set of proteins functionally associated with the protein in a query and their links efficiently. This algorithm reconstructs a functional association network of the query protein. The output network size can be flexibly determined by parameters.

Conclusions

M-Finder provides a useful framework to investigate functional association patterns with any protein. This software will also allow users to perform further systematic analysis of a set of proteins for any specific function. It is available online at http://bionet.ecs.baylor.edu/mfinder

     

Change of arthropod abundance in burned forests: Different patterns according to functional guilds

Forest fires are one of the most frequent and important causes of forest disturbances, the occurrence of which is globally increasing due to the effects of climate change. This study aimed to determine the impacts of fire and human activity on arthropod communities in affected forests. Twelve study sites in three burned areas were selected for this study. Intensities of disturbance in the study sites were characterized as follows: Disturbance Degree (DD) 0 (no fire), DD 1 (surface fire), DD 2 (crown fire), and DD 3 (crown fire followed by reforestation). Arthropods were collected using pitfall traps. Fourteen arthropod taxa (families, orders or classes), which are relatively homogeneous in their feeding habits and abundant, were analyzed. Depth of litter layer was selected as an environmental indicator for disturbance intensity, as it decreases linearly as the degree of disturbance increased. Changes of arthropod abundance in response to disturbance differed among functional guilds. As disturbance intensity increased, the abundance of detritivores decreased, but the abundance of herbivores increased. However, the abundance of predators varied between taxa. Formicidae and Araneae increased in disturbed sites, whereas Carabidae and Staphylinidae did not change. The abundance of Thysanura and Diptera was highly correlated with disturbance intensity, and may be suitable as a bioindicator for forest disturbance. Arthropod communities were more heterogeneous in forests of intermediate disturbance.