Phylogenomics and Morphological Reconstruction of Arcellinida Testate Amoebae Highlight Diversity of Microbial Eukaryotes in the Neoproterozoic

Life was microbial for the majority of Earth's history, but as very few microbial lineages leave a fossil record, the Precambrian evolution of life remains shrouded in mystery. Shelled (testate) amoebae stand out as an exception with rich documented diversity in the Neoproterozoic as vase-shaped microfossils (VSMs). While there is general consensus that most of these can be attributed to the Arcellinida lineage in Amoebozoa, it is still unclear whether they can be used as key fossils for interpretation of early eukaryotic evolution. Here, we present a well-resolved phylogenomic reconstruction based on 250 genes, obtained using single-cell transcriptomic techniques from a representative selection of 19 Arcellinid testate amoeba taxa. The robust phylogenetic framework enables deeper interpretations of evolution in this lineage and demanded an updated classification of the group. Additionally, we performed reconstruction of ancestral morphologies, yielding hypothetical ancestors remarkably similar to existing Neoproterozoic VSMs. We demonstrate that major lineages of testate amoebae were already diversified before the Sturtian glaciation (720 mya), supporting the hypothesis that massive eukaryotic diversification took place in the early Neoproterozoic and congruent with the interpretation that VSM are arcellinid testate amoebae

Synthetic RNA Silencing of Actinorhodin Biosynthesis in Streptomyces coelicolor A3(2)

We demonstrate the first application of synthetic RNA gene silencers in Streptomyces coelicolor A3(2). Peptide nucleic acid and expressed antisense RNA silencers successfully inhibited actinorhodin production. Synthetic RNA silencing was target-specific and is a new tool for gene regulation and metabolic engineering studies in Streptomyces.Peer reviewe

Vestiges of the Bacterial Signal Recognition Particle-Based Protein Targeting in Mitochondria

The main bacterial pathway for inserting proteins into the plasma membrane relies on the signal recognition particle (SRP), composed of the Ffh protein and an associated RNA component, and the SRP-docking protein FtsY. Eukaryotes use an equivalent system of archaeal origin to deliver proteins into the endoplasmic reticulum, whereas a bacteria-derived SRP and FtsY function in the plastid. Here we report on the presence of homologs of the bacterial Ffh and FtsY proteins in various unrelated plastid-lacking unicellular eukaryotes, namely Heterolobosea, Alveida, Goniomonas, and Hemimastigophora. The monophyly of novel eukaryotic Ffh and FtsY groups, predicted mitochondrial localization experimentally confirmed for Naegleria gruberi, and a strong alphaproteobacterial affinity of the Ffh group, collectively suggest that they constitute parts of an ancestral mitochondrial signal peptide-based protein-targeting system inherited from the last eukaryotic common ancestor, but lost from the majority of extant eukaryotes. The ability of putative signal peptides, predicted in a subset of mitochondrial-encoded N. gruberi proteins, to target a reporter fluorescent protein into the endoplasmic reticulum of Trypanosoma brucei, likely through their interaction with the cytosolic SRP, provided further support for this notion. We also illustrate that known mitochondrial ribosome-interacting proteins implicated in membrane protein targeting in opisthokonts (Mba1, Mdm38, and Mrx15) are broadly conserved in eukaryotes and nonredundant with the mitochondrial SRP system. Finally, we identified a novel mitochondrial protein (MAP67) present in diverse eukaryotes and related to the signal peptide-binding domain of Ffh, which may well be a hitherto unrecognized component of the mitochondrial membrane protein-targeting machinery

Machine learning on normalized protein sequences

<p>Abstract</p> <p>Background</p> <p>Machine learning techniques have been widely applied to biological sequences, e.g. to predict drug resistance in HIV-1 from sequences of drug target proteins and protein functional classes. As deletions and insertions are frequent in biological sequences, a major limitation of current methods is the inability to handle varying sequence lengths.</p> <p>Findings</p> <p>We propose to normalize sequences to uniform length. To this end, we tested one linear and four different non-linear interpolation methods for the normalization of sequence lengths of 19 classification datasets. Classification tasks included prediction of HIV-1 drug resistance from drug target sequences and sequence-based prediction of protein function. We applied random forests to the classification of sequences into "positive" and "negative" samples. Statistical tests showed that the linear interpolation outperforms the non-linear interpolation methods in most of the analyzed datasets, while in a few cases non-linear methods had a small but significant advantage. Compared to other published methods, our prediction scheme leads to an improvement in prediction accuracy by up to 14%.</p> <p>Conclusions</p> <p>We found that machine learning on sequences normalized by simple linear interpolation gave better or at least competitive results compared to state-of-the-art procedures, and thus, is a promising alternative to existing methods, especially for protein sequences of variable length.</p

nocoRNAc: Characterization of non-coding RNAs in prokaryotes

<p>Abstract</p> <p>Background</p> <p>The interest in non-coding RNAs (ncRNAs) constantly rose during the past few years because of the wide spectrum of biological processes in which they are involved. This led to the discovery of numerous ncRNA genes across many species. However, for most organisms the non-coding transcriptome still remains unexplored to a great extent. Various experimental techniques for the identification of ncRNA transcripts are available, but as these methods are costly and time-consuming, there is a need for computational methods that allow the detection of functional RNAs in complete genomes in order to suggest elements for further experiments. Several programs for the genome-wide prediction of functional RNAs have been developed but most of them predict a genomic locus with no indication whether the element is transcribed or not.</p> <p>Results</p> <p>We present <smcaps>NOCO</smcaps>RNAc, a program for the genome-wide prediction of ncRNA transcripts in bacteria. <smcaps>NOCO</smcaps>RNAc incorporates various procedures for the detection of transcriptional features which are then integrated with functional ncRNA loci to determine the transcript coordinates. We applied RNAz and <smcaps>NOCO</smcaps>RNAc to the genome of <it>Streptomyces coelicolor </it>and detected more than 800 putative ncRNA transcripts most of them located antisense to protein-coding regions. Using a custom design microarray we profiled the expression of about 400 of these elements and found more than 300 to be transcribed, 38 of them are predicted novel ncRNA genes in intergenic regions. The expression patterns of many ncRNAs are similarly complex as those of the protein-coding genes, in particular many antisense ncRNAs show a high expression correlation with their protein-coding partner.</p> <p>Conclusions</p> <p>We have developed <smcaps>NOCO</smcaps>RNAc, a framework that facilitates the automated characterization of functional ncRNAs. <smcaps>NOCO</smcaps>RNAc increases the confidence of predicted ncRNA loci, especially if they contain transcribed ncRNAs. <smcaps>NOCO</smcaps>RNAc is not restricted to intergenic regions, but it is applicable to the prediction of ncRNA transcripts in whole microbial genomes. The software as well as a user guide and example data is available at <url>http://www.zbit.uni-tuebingen.de/pas/nocornac.htm</url>.</p

Integrating anaerobic digestion and pyrolysis for treating digestates derived from sewage sludge and fat wastes

P. 32603-32614The coupling of biological and thermal technologies allows for the complete conversion of wastes into energy and biochar eliminating the problem of sludge disposal. The valorisation of fatty residues as co-substrate in a mesophilic digester of a wastewater treatment plant was studied considering an integrated approach of co-digestion and pyrolysis. Four digested samples obtained from co-digestion of sewage sludge and butcher’s fat waste were studied by thermogravimetric analysis. The activation energy corresponding to the sludge pyrolysis was calculated by a non-isothermal kinetic. Arrhenius activation energy was lower for the pyrolysis of a digested grease sample (92 kJ mol−1 obtained by OFW and 86 kJ mol−1 obtained by Vyazovkin) than for the pyrolysis of sewage sludge and its blends (164–190 kJ mol−1 obtained by OFW and 162–190 kJ mol−1 obtained by Vyazovkin). The analysis of the integrated approach of anaerobic co-digestion and pyrolysis of digestates demonstrated that the addition of 3% (w/v) of fat to the feeding sludge results in a 25% increase in the electricity obtained from biogas (if a combined heat and power unit is considered for biogas valorisation) and increasing the fat content to 15% allows for covering all thermal needs for drying of digestate and more than doubles (2.4 times) the electricity production when the scenario of digestion and pyrolysis is contemplated.S

Static characteristics of pulsed actuator with plunger consisting of carbon steel and permanent magnet

A novel type of pulsed electromagnetic actuator is presented and modeled. Its plunger consists of two separate (but mutually connected) cylindrical parts made of classical magnetic material and permanent magnet, respectively, and its motion is controlled by short current pulses of the defined amplitude. The paper starts with the definition of the technical problem and formulation of its mathematical model. This model is then solved numerically and the whole methodology is illustrated by a typical example. It is shown that unlike the classical devices the above actuator exhibits high holding force and low consumption of energy