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

All photosynthetic multicellular Eukaryotes, including land plants and algae, have cells that are surrounded by a dynamic, complex, carbohydrate-rich cell wall. The cell wall exerts considerable biological and biomechanical control over individual cells and organisms, thus playing a key role in their environmental interactions. This has resulted in compositional variation that is dependent on developmental stage, cell type, and season. Further variation is evident that has a phylogenetic basis. Plants and algae have a complex phylogenetic history, including acquisition of genes responsible for carbohydrate synthesis and modification through a series of primary (leading to red algae, green algae, and land plants) and secondary (generating brown algae, diatoms, and dinoflagellates) endosymbiotic events. Therefore, organisms that have the shared features of photosynthesis and possession of a cell wall do not form a monophyletic group. Yet they contain some common wall components that can be explained increasingly by genetic and biochemical evidence.

/pdf/evolution-and-diversity-of-plant-cell-walls-from-algae-to-4erdp32ps7.pdf

Evolution and diversity of plant cell walls: from algae to flowering plants.

Recent progress in the identification and characterization of pectin biosynthetic proteins and the discovery of pectin domain–containing proteoglycans are changing our view of how pectin, the most complex family of plant cell wall polysaccharides, is synthesized. The functional confirmation of four types of pectin biosynthetic glycosyltransferases, the identification of multiple putative pectin glycosyl- and methyltransferases, and the characteristics of the GAUT1:GAUT7 homogalacturonan biosynthetic complex with its novel mechanism for retaining catalytic subunits in the Golgi apparatus and its 12 putative interacting proteins are beginning to provide a framework for the pectin biosynthetic process. We propose two partially overlapping hypothetical and testable models for pectin synthesis: the consecutive glycosyltransferase model and the domain synthesis model.

Evolving Views of Pectin Biosynthesis

Advances in biomedical applications of pectin gels

Salinity is detrimental to plant growth, crop production and food security worldwide. Excess salt triggers increases in cytosolic Ca2+ concentration, which activate Ca2+-binding proteins and upregulate the Na+/H+ antiporter in order to remove Na+. Salt-induced increases in Ca2+ have long been thought to be involved in the detection of salt stress, but the molecular components of the sensing machinery remain unknown. Here, using Ca2+-imaging-based forward genetic screens, we isolated the Arabidopsis thaliana mutant monocation-induced [Ca2+]i increases 1 (moca1), and identified MOCA1 as a glucuronosyltransferase for glycosyl inositol phosphorylceramide (GIPC) sphingolipids in the plasma membrane. MOCA1 is required for salt-induced depolarization of the cell-surface potential, Ca2+ spikes and waves, Na+/H+ antiporter activation, and regulation of growth. Na+ binds to GIPCs to gate Ca2+ influx channels. This salt-sensing mechanism might imply that plasma-membrane lipids are involved in adaption to various environmental salt levels, and could be used to improve salt resistance in crops. The sphingolipid GIPC in the plant cell plasma membrane binds to sodium and triggers calcium influx, thereby triggering responses to excess salt such as efflux of sodium ions from cells.

Plant cell-surface GIPC sphingolipids sense salt to trigger Ca 2+ influx

Carbohydrate-active enzyme glycosyltransferase family 8 (GT8) includes the plant galacturonosyltransferase1-related gene family of proven and putative a-galacturonosyltransferase (GAUT) and GAUT-like (GATL) genes. We computationally identified and investigated this family in 15 fully sequenced plant and green algal genomes and in the National Center for Biotechnology Information nonredundant protein database to determine the phylogenetic relatedness of the GAUTs and GATLs to other GT8 family members. The GT8 proteins fall into three well-delineated major classes. In addition to GAUTs and GATLs, known or predicted to be involved in plant cell wall biosynthesis, class I also includes a lower plantspecific GAUT and GATL-related (GATR) subfamily, two metazoan subfamilies, and proteins from other eukaryotes and cyanobacteria. Class II includes galactinol synthases and plant glycogenin-like starch initiation proteins that are not known to be directly involved in cell wall synthesis, as well as proteins from fungi, metazoans, viruses, and bacteria. Class III consists almost entirely of bacterial proteins that are lipooligo/polysaccharide a-galactosyltransferases and a-glucosyltransferases. Sequence motifs conserved across all GT8 subfamilies and those specific to plant cell wall-related GT8 subfamilies were identified and mapped onto a predicted GAUT1 protein structure. The tertiary structure prediction identified sequence motifs likely to represent key amino acids involved in catalysis, substrate binding, protein-protein interactions, and structural elements required for GAUT1 function. The results show that the GAUTs, GATLs, and GATRs have a different evolutionary origin than other plant GT8 genes, were likely acquired from an ancient cyanobacterium (Synechococcus) progenitor, and separate into unique subclades that may indicate functional specialization. Plant cell walls are composed of three principal types of polysaccharides: cellulose, hemicellulose, and pectin. Studying the biosynthesis and degradation of these biopolymers is important because cell walls have multiple roles in plants, including providing structural support to cells and defense against pathogens, serving as cell-specific developmental and differentiation markers, and mediating or facilitating cell-cell communication. In addition to their important roles within plants, cell walls also have many economic uses in human and animal nutrition and as sources of natural textile fibers, paper and wood products, and components of fine chemicals and medicinal products. The study of the biosynthesis and biodegradation of plant cell walls has become evenmore significant because cell

Evolution and Function of the Plant Cell Wall Synthesis-Related Glycosyltransferase Family 8

Optimal Mutation Sites for PRE Data Collection and Membrane Protein Structure Prediction

We have recently developed a database, pDAWG, focused on information related to plant cell walls. Currently, pDAWG contains seven complete plant genomes, 12 complete algal genomes, along with computed information for individual proteins encoded in these genomes of the following types: (a) carbohydrate active enzyme (CAZy) family information when applicable; (b) phylogenetic trees of cell wall-related CAZy family proteins; (c) protein structure models if available; (d) physical and predicted interactions among proteins; (e) subcellular localization; (f) Pfam domain information; and (g) homology-based functional prediction. A querying system with a graphical interface allows a user to quickly compose information of different sorts about individual genes/proteins and to display the composite information in an intuitive manner, facilitating comparative analyses and knowledge discovery about cell wall genes. pDAWG can be accessed at http://csbl1.bmb.uga.edu/pDAWG/.

pDAWG: An Integrated Database for Plant Cell Wall Genes

Background: The genomes of numerous cellulolytic organisms have been recently sequenced or in the pipeline of being sequenced. Analyses of these genomes as well as the recently sequenced metagenomes in a systematic manner could possibly lead to discoveries of novel biomass-degradation systems in nature. Description: We have identified 4,679 and 49,099 free acting glycosyl hydrolases with or without carbohydrate binding domains, respectively, by scanning through all the proteins in the UniProt Knowledgebase and the JGI Metagenome database. Cellulosome components were observed only in bacterial genomes, and 166 cellulosomedependent glycosyl hydrolases were identified. We observed, from our analysis data, unexpected wide distributions of two less well-studied bacterial glycosyl hydrolysis systems in which glycosyl hydrolases may bind to the cell surface directly rather than through linking to surface anchoring proteins, or cellulosome complexes may bind to the cell surface by novel mechanisms other than the other used SLH domains. In addition, we found that animalgut metagenomes are substantially enriched with novel glycosyl hydrolases. Conclusions: The identified biomass degradation systems through our large-scale search are organized into an easy-to-use database GASdb at http://csbl.bmb.uga.edu/~ffzhou/GASdb/, which should be useful to both experimental and computational biofuel researchers.

/pdf/gasdb-a-large-scale-and-comparative-exploration-database-of-5d02xe0noe.pdf

GASdb: a large-scale and comparative exploration database of glycosyl hydrolysis systems

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Evolution and Function of the Plant Cell Wall Synthesis-Related Glycosyltransferase Family 8

Optimal Mutation Sites for PRE Data Collection and Membrane Protein Structure Prediction

pDAWG: An Integrated Database for Plant Cell Wall Genes

GASdb: a large-scale and comparative exploration database of glycosyl hydrolysis systems