The lion's share of bacteria in various environments cannot be cloned in the laboratory and thus cannot be sequenced using existing technologies. A major goal of single-cell genomics is to complement gene-centric metagenomic data with whole-genome assemblies of uncultivated organisms. Assembly of single-cell data is challenging because of highly non-uniform read coverage as well as elevated levels of sequencing errors and chimeric reads. We describe SPAdes, a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler (specialized for single-cell data) and on popular assemblers Velvet and SoapDeNovo (for multicell data). SPAdes generates single-cell assemblies, providing information about genomes of uncultivatable bacteria that vastly exceeds what may be obtained via traditional metagenomics studies. SPAdes is available online ( http://bioinf.spbau.ru/spades ). It is distributed as open source software.

SPAdes, a new genome assembly algorithm and its applications to single-cell sequencing ( 7th Annual SFAF Meeting, 2012)

Gene families are growing rapidly, but standard methods for inferring phylogenies do not scale to alignments with over 10,000 sequences. We present FastTree, a method for constructing large phylogenies and for estimating their reliability. Instead of storing a distance matrix, FastTree stores sequence profiles of internal nodes in the tree. FastTree uses these profiles to implement neighbor-joining and uses heuristics to quickly identify candidate joins. FastTree then uses nearest-neighbor interchanges to reduce the length of the tree. For an alignment with N sequences, L sites, and a different characters, a distance matrix requires O(N^2) space and O(N^2 L) time, but FastTree requires just O( NLa + N sqrt(N) ) memory and O( N sqrt(N) log(N) L a ) time. To estimate the tree's reliability, FastTree uses local bootstrapping, which gives another 100-fold speedup over a distance matrix. For example, FastTree computed a tree and support values for 158,022 distinct 16S ribosomal RNAs in 17 hours and 2.4 gigabytes of memory. Just computing pairwise Jukes-Cantor distances and storing them, without inferring a tree or bootstrapping, would require 17 hours and 50 gigabytes of memory. In simulations, FastTree was slightly more accurate than neighbor joining, BIONJ, or FastME; on genuine alignments, FastTree's topologies had higher likelihoods. FastTree is available at http://microbesonline.org/fasttree.

/pdf/fast-tree-computing-large-minimum-evolution-trees-with-4grq0gwfpy.pdf

Fast Tree: Computing Large Minimum-Evolution Trees with Profiles instead of a Distance Matrix

https://cbs.umn.edu/sites/cbs.umn.edu/files/public/downloads/Nguyenetal2015b.pdf

FUNGuild: An open annotation tool for parsing fungal community datasets by ecological guild

Biosorbents for heavy metals removal and their future

Laccases of fungi attract considerable attention due to their possible involvement in the transformation of a wide variety of phenolic compounds including the polymeric lignin and humic substances. So far, more than a 100 enzymes have been purified from fungal cultures and characterized in terms of their biochemical and catalytic properties. Most ligninolytic fungal species produce constitutively at least one laccase isoenzyme and laccases are also dominant among ligninolytic enzymes in the soil environment. The fact that they only require molecular oxygen for catalysis makes them suitable for biotechnological applications for the transformation or immobilization of xenobiotic compounds.

Fungal laccases - occurrence and properties.

16S ribosomal RNA currently represents the most important target of study in bacterial ecology. Its use for the description of bacterial diversity is, however, limited by the presence of variable copy numbers in bacterial genomes and sequence variation within closely related taxa or within a genome. Here we use the information from sequenced bacterial genomes to explore the variability of 16S rRNA sequences and copy numbers at various taxonomic levels and apply it to estimate bacterial genome and DNA abundances. In total, 7,081 16S rRNA sequences were in silico extracted from 1,690 available bacterial genomes (1–15 per genome). While there are several phyla containing low 16S rRNA copy numbers, in certain taxa, e.g., the Firmicutes and Gammaproteobacteria, the variation is large. Genome sizes are more conserved at all tested taxonomic levels than 16S rRNA copy numbers. Only a minority of bacterial genomes harbors identical 16S rRNA gene copies, and sequence diversity increases with increasing copy numbers. While certain taxa harbor dissimilar 16S rRNA genes, others contain sequences common to multiple species. Sequence identity clusters (often termed operational taxonomic units) thus provide an imperfect representation of bacterial taxa of a certain phylogenetic rank. We have demonstrated that the information on 16S rRNA copy numbers and genome sizes of genome-sequenced bacteria may be used as an estimate for the closest related taxon in an environmental dataset to calculate alternative estimates of the relative abundance of individual bacterial taxa in environmental samples. Using an example from forest soil, this procedure would increase the abundance estimates of Acidobacteria and decrease these of Firmicutes. Using the currently available information, alternative estimates of bacterial community composition may be obtained in this way if the variation of 16S rRNA copy numbers among bacteria is considered.

/pdf/the-variability-of-the-16s-rrna-gene-in-bacterial-genomes-2oymlzftul.pdf

The Variability of the 16S rRNA Gene in Bacterial Genomes and Its Consequences for Bacterial Community Analyses

Cellulose is the main polymeric component of the plant cell wall, the most abundant polysaccharide on Earth, and an important renewable resource. Basidiomycetous fungi belong to its most potent degraders because many species grow on dead wood or litter, in environment rich in cellulose. Fungal cellulolytic systems differ from the complex cellulolytic systems of bacteria. For the degradation of cellulose, basidiomycetes utilize a set of hydrolytic enzymes typically composed of endoglucanase, cellobiohydrolase and β-glucosidase. In some species, the absence of cellobiohydrolase is substituted by the production of processive endoglucanases combining the properties of both of these enzymes. In addition, systems producing hydroxyl radicals based on cellobiose dehydrogenase, quinone redox cycling or glycopeptide-based Fenton reaction are involved in the degradation of several plant cell wall components, including cellulose. The complete cellulolytic complex used by a single fungal species is typically composed of more than one of the above mechanisms that contribute to the utilization of cellulose as a source of carbon or energy or degrade it to ensure fast substrate colonization. The efficiency and regulation of cellulose degradation differs among wood-rotting, litter-decomposing, mycorrhizal or plant pathogenic fungi and yeasts due to the different roles of cellulose degradation in the physiology and ecology of the individual groups.

Degradation of cellulose by basidiomycetous fungi.

Soils of coniferous forest ecosystems are important for the global carbon cycle, and the identification of active microbial decomposers is essential for understanding organic matter transformation in these ecosystems By the independent analysis of DNA and RNA, whole communities of bacteria and fungi and its active members were compared in topsoil of a Picea abies forest during a period of organic matter decomposition Fungi quantitatively dominate the microbial community in the litter horizon, while the organic horizon shows comparable amount of fungal and bacterial biomasses Active microbial populations obtained by RNA analysis exhibit similar diversity as DNA-derived populations, but significantly differ in the composition of microbial taxa Several highly active taxa, especially fungal ones, show low abundance or even absence in the DNA pool Bacteria and especially fungi are often distinctly associated with a particular soil horizon Fungal communities are less even than bacterial ones and show higher relative abundances of dominant species While dominant bacterial species are distributed across the studied ecosystem, distribution of dominant fungi is often spatially restricted as they are only recovered at some locations The sequences of cbhI gene encoding for cellobiohydrolase (exocellulase), an essential enzyme for cellulose decomposition, were compared in soil metagenome and metatranscriptome and assigned to their producers Litter horizon exhibits higher diversity and higher proportion of expressed sequences than organic horizon Cellulose decomposition is mediated by highly diverse fungal populations largely distinct between soil horizons The results indicate that low-abundance species make an important contribution to decomposition processes in soils

/pdf/active-and-total-microbial-communities-in-forest-soil-are-2oc9rcjyqg.pdf

Petr Baldrian

Papers

Fungal laccases - occurrence and properties.

The Variability of the 16S rRNA Gene in Bacterial Genomes and Its Consequences for Bacterial Community Analyses

Degradation of cellulose by basidiomycetous fungi.

Active and total microbial communities in forest soil are largely different and highly stratified during decomposition.

Interactions of heavy metals with white-rot fungi