Disentangling the counteracting effects of water content and carbon mass on zooplankton growth

Abstract Zooplankton vary widely in carbon percentage (carbon mass as a percentage of wet mass), but are often described as either gelatinous or non-gelatinous. Here we update datasets of carbon percentage and growth rate to investigate whether carbon percentage is a continuous trait, and whether its inclusion improves zooplankton growth models. We found that carbon percentage is continuous, but that species are not distributed homogenously along this axis. To assess variability of this trait in situ, we investigated the distribution of biomass across the range of carbon percentage for a zooplankton time series at station L4 off Plymouth, UK. This showed separate biomass peaks for gelatinous and crustacean taxa, however, carbon percentage varied 8-fold within the gelatinous group. Species with high carbon mass had lower carbon percentage, allowing separation of the counteracting effects of these two variables on growth rate. Specific growth rates, g (d−1) were negatively related to carbon percentage and carbon mass, even in the gelatinous taxa alone, suggesting that the trend is not driven by a categorical difference between these groups. The addition of carbon percentage doubled the explanatory power of growth models based on mass alone, demonstrating the benefits of considering carbon percentage as a continuous trait

BAAV Transcytosis Requires an Interaction with β-1-4 Linked- Glucosamine and gp96

Cell surface carbohydrates play an important role in virus entry and intracellular trafficking. Bovine Adeno-Associated Virus (BAAV) uses plasma membrane gangliosides for transduction and infection. In addition, independent of the infectious pathway, BAAV also has the ability to pass through barrier epithelia and endothelia using a transcytosis pathway dependent upon the presence of cell surface carbohydrates. Thus, in order to better define the carbohydrate interactions that are necessary for BAAV infection or transcytosis, a glycan microarray composed of both natural and synthetic carbohydrates was probed with HA-tagged BAAV particles. This identified chitotriose, a trimer of β-1-4-linked N-acetyl glucosamine, as having an interaction with BAAV. Competition experiments showed that the BAAV interaction with this carbohydrate is not necessary for infection but is instead important in the transcytosis pathway. The β-1-4-linked N-acetyl glucosamine modification has been reported on gp96, a glycoprotein involved in the transcytosis of bacteria and toxins. Significantly, immunoprecipitation and competition experiments with an anti-gp96 antibody and a soluble form of gp96, respectively, showed this glycoprotein can also interact with BAAV to serve as a receptor for its transcytosis

Discovery of a Sub-Parsec Radio Counterjet in the Nucleus of Centaurus A

A sub-parsec scale radio counterjet has been detected in the nucleus of the closest radio galaxy, Centaurus A (NGC 5128), with VLBI imaging at 2.3 and 8.4 GHz. This is one of the first detections of a VLBI counterjet and provides new constraints on the kinematics of the radio jets emerging from the nucleus of Cen A. A bright, compact core is seen at 8.4 GHz, along with a jet extending along P.A. 51 degrees. The core is completely absorbed at 2.3 GHz. Our images show a much wider gap between the base of the main jet and the counterjet at 2.3 GHz than at 8.4 GHz and also that the core has an extraordinarily inverted spectrum. These observations provide evidence that the innermost 0.4-0.8 pc of the source is seen through a disk or torus of ionized gas which is opaque at low frequencies due to free-free absorption.Comment: 3 pages, 2 postscript figures, scheduled for publication in August 1, 1996 issue of Ap.J. Letter

G-Quadruplex DNA Sequences Are Evolutionarily Conserved and Associated with Distinct Genomic Features in Saccharomyces cerevisiae

G-quadruplex DNA is a four-stranded DNA structure formed by non-Watson-Crick base pairing between stacked sets of four guanines. Many possible functions have been proposed for this structure, but its in vivo role in the cell is still largely unresolved. We carried out a genome-wide survey of the evolutionary conservation of regions with the potential to form G-quadruplex DNA structures (G4 DNA motifs) across seven yeast species. We found that G4 DNA motifs were significantly more conserved than expected by chance, and the nucleotide-level conservation patterns suggested that the motif conservation was the result of the formation of G4 DNA structures. We characterized the association of conserved and non-conserved G4 DNA motifs in Saccharomyces cerevisiae with more than 40 known genome features and gene classes. Our comprehensive, integrated evolutionary and functional analysis confirmed the previously observed associations of G4 DNA motifs with promoter regions and the rDNA, and it identified several previously unrecognized associations of G4 DNA motifs with genomic features, such as mitotic and meiotic double-strand break sites (DSBs). Conserved G4 DNA motifs maintained strong associations with promoters and the rDNA, but not with DSBs. We also performed the first analysis of G4 DNA motifs in the mitochondria, and surprisingly found a tenfold higher concentration of the motifs in the AT-rich yeast mitochondrial DNA than in nuclear DNA. The evolutionary conservation of the G4 DNA motif and its association with specific genome features supports the hypothesis that G4 DNA has in vivo functions that are under evolutionary constraint

Functional Characterization of Transcription Factor Motifs Using Cross-species Comparison across Large Evolutionary Distances

We address the problem of finding statistically significant associations between cis-regulatory motifs and functional gene sets, in order to understand the biological roles of transcription factors. We develop a computational framework for this task, whose features include a new statistical score for motif scanning, the use of different scores for predicting targets of different motifs, and new ways to deal with redundancies among significant motif–function associations. This framework is applied to the recently sequenced genome of the jewel wasp, Nasonia vitripennis, making use of the existing knowledge of motifs and gene annotations in another insect genome, that of the fruitfly. The framework uses cross-species comparison to improve the specificity of its predictions, and does so without relying upon non-coding sequence alignment. It is therefore well suited for comparative genomics across large evolutionary divergences, where existing alignment-based methods are not applicable. We also apply the framework to find motifs associated with socially regulated gene sets in the honeybee, Apis mellifera, using comparisons with Nasonia, a solitary species, to identify honeybee-specific associations

The Cardiac Transcription Network Modulated by Gata4, Mef2a, Nkx2.5, Srf, Histone Modifications, and MicroRNAs

The transcriptome, as the pool of all transcribed elements in a given cell, is regulated by the interaction between different molecular levels, involving epigenetic, transcriptional, and post-transcriptional mechanisms. However, many previous studies investigated each of these levels individually, and little is known about their interdependency. We present a systems biology study integrating mRNA profiles with DNA–binding events of key cardiac transcription factors (Gata4, Mef2a, Nkx2.5, and Srf), activating histone modifications (H3ac, H4ac, H3K4me2, and H3K4me3), and microRNA profiles obtained in wild-type and RNAi–mediated knockdown. Finally, we confirmed conclusions primarily obtained in cardiomyocyte cell culture in a time-course of cardiac maturation in mouse around birth. We provide insights into the combinatorial regulation by cardiac transcription factors and show that they can partially compensate each other's function. Genes regulated by multiple transcription factors are less likely differentially expressed in RNAi knockdown of one respective factor. In addition to the analysis of the individual transcription factors, we found that histone 3 acetylation correlates with Srf- and Gata4-dependent gene expression and is complementarily reduced in cardiac Srf knockdown. Further, we found that altered microRNA expression in Srf knockdown potentially explains up to 45% of indirect mRNA targets. Considering all three levels of regulation, we present an Srf-centered transcription network providing on a single-gene level insights into the regulatory circuits establishing respective mRNA profiles. In summary, we show the combinatorial contribution of four DNA–binding transcription factors in regulating the cardiac transcriptome and provide evidence that histone modifications and microRNAs modulate their functional consequence. This opens a new perspective to understand heart development and the complexity cardiovascular disorders

Measuring the Evolutionary Rewiring of Biological Networks

We have accumulated a large amount of biological network data and expect even more to come. Soon, we anticipate being able to compare many different biological networks as we commonly do for molecular sequences. It has long been believed that many of these networks change, or “rewire”, at different rates. It is therefore important to develop a framework to quantify the differences between networks in a unified fashion. We developed such a formalism based on analogy to simple models of sequence evolution, and used it to conduct a systematic study of network rewiring on all the currently available biological networks. We found that, similar to sequences, biological networks show a decreased rate of change at large time divergences, because of saturation in potential substitutions. However, different types of biological networks consistently rewire at different rates. Using comparative genomics and proteomics data, we found a consistent ordering of the rewiring rates: transcription regulatory, phosphorylation regulatory, genetic interaction, miRNA regulatory, protein interaction, and metabolic pathway network, from fast to slow. This ordering was found in all comparisons we did of matched networks between organisms. To gain further intuition on network rewiring, we compared our observed rewirings with those obtained from simulation. We also investigated how readily our formalism could be mapped to other network contexts; in particular, we showed how it could be applied to analyze changes in a range of “commonplace” networks such as family trees, co-authorships and linux-kernel function dependencies