Population Dynamics and Diversity of Viruses, Bacteria and Phytoplankton in a Shallow Eutrophic Lake

We have studied the temporal variation in viral abundances and community assemblage in the eutrophic Lake Loosdrecht through epifluorescence microscopy and pulsed field gel electrophoresis (PFGE). The virioplankton community was a dynamic component of the aquatic community, with abundances ranging between 5.5 × 107 and 1.3 × 108 virus-like particles ml−1 and viral genome sizes ranging between 30 and 200 kb. Both viral abundances and community composition followed a distinct seasonal cycle, with high viral abundances observed during spring and summer. Due to the selective and parasitic nature of viral infection, it was expected that viral and host community dynamics would covary both in abundances and community composition. The temporal dynamics of the bacterial and cyanobacterial communities, as potential viral hosts, were studied in addition to a range of environmental parameters to relate these to viral community dynamics. Cyanobacterial and bacterial communities were studied applying epifluorescence microscopy, flow cytometry, and denaturing gradient gel electrophoresis (DGGE). Both bacterial and cyanobacterial communities followed a clear seasonal cycle. Contrary to expectations, viral abundances were neither correlated to abundances of the most dominant plankton groups in Lake Loosdrecht, the bacteria and the filamentous cyanobacteria, nor could we detect a correlation between the assemblage of viral and bacterial or cyanobacterial communities during the overall period. Only during short periods of strong fluctuations in microbial communities could we detect viral community assemblages to covary with cyanobacterial and bacterial communities. Methods with a higher specificity and resolution are probably needed to detect the more subtle virus–host interactions. Viral abundances did however relate to cyanobacterial community assemblage and showed a significant positive correlation to Chl-a as well as prochlorophytes, suggesting that a significant proportion of the viruses in Lake Loosdrecht may be phytoplankton and more specific cyanobacterial viruses. Temporal changes in bacterial abundances were significantly related to viral community assemblage, and vice versa, suggesting an interaction between viral and bacterial communities in Lake Loosdrecht

Identification of a mitotic recombination hotspot on chromosome III of the asexual fungus Aspergillus niger and its possible correlation elevated basal transcription

Genetic recombination is an important tool in strain breeding in many organisms. We studied the possibilities of mitotic recombination in strain breeding of the asexual fungus Aspergillus niger. By identifying genes that complemented mapped auxotrophic mutations, the physical map was compared to the genetic map of chromosome III using the genome sequence. In a program to construct a chromosome III-specific marker strain by selecting mitotic crossing-over in diploids, a mitotic recombination hotspot was identified. Analysis of the mitotic recombination hotspot revealed some physical features, elevated basal transcription and a possible correlation with purine stretches

Genome sequencing and analysis of the versatile cell factory Aspergillus niger CBS 513.88

The filamentous fungus Aspergillus niger is widely exploited by the fermentation industry for the production of enzymes and organic acids, particularly citric acid. We sequenced the 33.9-megabase genome of A. niger CBS 513.88, the ancestor of currently used enzyme production strains. A high level of synteny was observed with other aspergilli sequenced. Strong function predictions were made for 6,506 of the 14,165 open reading frames identified. A detailed description of the components of the protein secretion pathway was made and striking differences in the hydrolytic enzyme spectra of aspergilli were observed. A reconstructed metabolic network comprising 1,069 unique reactions illustrates the versatile metabolism of A. niger. Noteworthy is the large number of major facilitator superfamily transporters and fungal zinc binuclear cluster transcription factors, and the presence of putative gene clusters for fumonisin and ochratoxin A synthesis

Exploring Sequence Characteristics Related to High- Level Production of Secreted Proteins in Aspergillus niger

Protein sequence features are explored in relation to the production of over-expressed extracellular proteins by fungi. Knowledge on features influencing protein production and secretion could be employed to improve enzyme production levels in industrial bioprocesses via protein engineering. A large set, over 600 homologous and nearly 2,000 heterologous fungal genes, were overexpressed in Aspergillus niger using a standardized expression cassette and scored for high versus no production. Subsequently, sequence-based machine learning techniques were applied for identifying relevant DNA and protein sequence features. The amino-acid composition of the protein sequence was found to be most predictive and interpretation revealed that, for both homologous and heterologous gene expression, the same features are important: tyrosine and asparagine composition was found to have a positive correlation with high-level production, whereas for unsuccessful production, contributions were found for methionine and lysine composition. The predictor is available online at http://bioinformatics.tudelft.nl/hipsec. Subsequent work aims at validating these findings by protein engineering as a method for increasing expression levels per gene copy.Computer Science & EngineeringElectrical Engineering, Mathematics and Computer Scienc

Classification performances.

<p>ROC-curves of composition-based classifiers using the codon sequence (), the signal peptide sequence (), and the protein sequence (). Performances are shown for classifiers <b>A)</b> trained and tested on , <b>B)</b> trained and tested on , and <b>C)</b> trained on and tested on .</p

Different sequence-based protein representations.

<p>The different shades of gray denote predicted buried (B) and exposed (E) regions in case of the the solvent accessibility, and predicted helix (H), strand (E), and random coil (C) region in case of the secondary structure.</p

Prediction performance scores (auroc).

<p>Prediction performance scores (auroc).</p

Predefined amino acid clusters.

<p>Predefined amino acid clusters.</p

Comparing <i>hom</i> and <i>het</i> classifiers.

<p>Amino acid contributions obtained from and trained classifiers are the - and -values respectively, the correlation is denoted by . Contributions are normalized per classifier (axis): each contribution is divided by the maximum absolute contribution. The plots show the contributions obtained from classifiers trained using <b>A)</b> the protein amino acid composition () and <b>B)</b> the predefined amino acid cluster composition ().</p