Can Abundance of Protists Be Inferred from Sequence Data: A Case Study of Foraminifera

Protists are key players in microbial communities, yet our understanding of their role in ecosystem functioning is seriously impeded by difficulties in identification of protistan species and their quantification. Current microscopy-based methods used for determining the abundance of protists are tedious and often show a low taxonomic resolution. Recent development of next-generation sequencing technologies offered a very powerful tool for studying the richness of protistan communities. Still, the relationship between abundance of species and number of sequences remains subjected to various technical and biological biases. Here, we test the impact of some of these biological biases on sequence abundance of SSU rRNA gene in foraminifera. First, we quantified the rDNA copy number and rRNA expression level of three species of foraminifera by qPCR. Then, we prepared five mock communities with these species, two in equal proportions and three with one species ten times more abundant. The libraries of rDNA and cDNA of the mock communities were constructed, Sanger sequenced and the sequence abundance was calculated. The initial species proportions were compared to the raw sequence proportions as well as to the sequence abundance normalized by rDNA copy number and rRNA expression level per species. Our results showed that without normalization, all sequence data differed significantly from the initial proportions. After normalization, the congruence between the number of sequences and number of specimens was much better. We conclude that without normalization, species abundance determination based on sequence data was not possible because of the effect of biological biases. Nevertheless, by taking into account the variation of rDNA copy number and rRNA expression level we were able to infer species abundance, suggesting that our approach can be successful in controlled conditions.     

Relative Amino Acid Composition Signatures of Organisms and Environments

Background

Identifying organism-environment interactions at the molecular level is crucial to understanding how organisms adapt to and change the chemical and molecular landscape of their habitats. In this work we investigated whether relative amino acid compositions could be used as a molecular signature of an environment and whether such a signature could also be observed at the level of the cellular amino acid composition of the microorganisms that inhabit that environment.

Methodologies/Principal Findings

To address these questions we collected and analyzed environmental amino acid determinations from the literature, and estimated from complete genomic sequences the global relative amino acid abundances of organisms that are cognate to the different types of environment. Environmental relative amino acid abundances clustered into broad groups (ocean waters, host-associated environments, grass land environments, sandy soils and sediments, and forest soils), indicating the presence of amino acid signatures specific for each environment. These signatures correlate to those found in organisms. Nevertheless, relative amino acid abundance of organisms was more influenced by GC content than habitat or phylogeny.

Conclusions

Our results suggest that relative amino acid composition can be used as a signature of an environment. In addition, we observed that the relative amino acid composition of organisms is not highly determined by environment, reinforcing previous studies that find GC content to be the major factor correlating to amino acid composition in living organisms.     

Leading compounds for the validation of animal models of psychopathology

Modelling of complex psychiatric disorders, e.g., depression and schizophrenia, in animals is a major challenge, since they are characterized by certain disturbances in functions that are absolutely unique to humans. Furthermore, we still have not identified the genetic and neurobiological mechanisms, nor do we know precisely the circuits in the brain that function abnormally in mood and psychotic disorders. Consequently, the pharmacological treatments used are mostly variations on a theme that was started more than 50 years ago. Thus, progress in novel drug development with improved therapeutic efficacy would benefit greatly from improved animal models. Here, we review the available animal models of depression and schizophrenia and focus on the way that they respond to various types of potential candidate molecules, such as novel antidepressant or antipsychotic drugs, as an index of predictive validity. We conclude that the generation of convincing and useful animal models of mental illnesses could be a bridge to success in drug discovery.     

Delivery and processing of exogenous double-stranded DNA in mouse CD34 + hematopoietic progenitor cells and their cell cycle changes upon combined treatment with cyclophosphamide and double-stranded DNA

We previously reported that fragments of exogenous double-stranded DNA can be internalized by mouse bone marrow cells without any transfection. Our present analysis shows that only 2% of bone marrow cells take up the fragments of extracellular exogenous DNA. Of these, ~ 45% of the cells correspond to CD34 + hematopoietic stem cells. Taking into account that CD34 + stem cells constituted 2.5% of the total cell population in the bone marrow samples analyzed, these data indicate that as much as 40% of CD34 + cells readily internalize fragments of extracellular exogenous DNA. This suggests that internalization of fragmented dsDNA is a general feature of poorly differentiated cells, in particular CD34 + bone marrow cells.     

Compensatory nature of Chargaff’s second parity rule

The second parity rule of Chargaff (A≈T and G≈C within one strand) holds all over the living world with minor exceptions. It is maintained with higher accuracy for long sequences. The question addressed in the article is how different sequence types, with different biases from the parity, contribute to the general effect. It appears that the sequence segments with biases of opposite sign are intermingled, so that with sufficient sequence lengths the parity is established. The parity rule seems to be a cumulative result of a number of independent processes in the genome evolution, with the parity as their intrinsic property. Symmetrical appearance of simple repeats and of Alu sequences in the human DNA strands, and other contributions to the Chargaff parity II rule are discussed.     

A comparison of the strength of biodiversity effects across multiple functions

In order to predict which ecosystem functions are most at risk from biodiversity loss, meta-analyses have generalised results from biodiversity experiments over different sites and ecosystem types. In contrast, comparing the strength of biodiversity effects across a large number of ecosystem processes measured in a single experiment permits more direct comparisons. Here, we present an analysis of 418 separate measures of 38 ecosystem processes. Overall, 45 % of processes were significantly affected by plant species richness, suggesting that, while diversity affects a large number of processes not all respond to biodiversity. We therefore compared the strength of plant diversity effects between different categories of ecosystem processes, grouping processes according to the year of measurement, their biogeochemical cycle, trophic level and compartment (above- or belowground) and according to whether they were measures of biodiversity or other ecosystem processes, biotic or abiotic and static or dynamic. Overall, and for several individual processes, we found that biodiversity effects became stronger over time. Measures of the carbon cycle were also affected more strongly by plant species richness than were the measures associated with the nitrogen cycle. Further, we found greater plant species richness effects on measures of biodiversity than on other processes. The differential effects of plant diversity on the various types of ecosystem processes indicate that future research and political effort should shift from a general debate about whether biodiversity loss impairs ecosystem functions to focussing on the specific functions of interest and ways to preserve them individually or in combination.