Functionally pathogenic EARS2 variants in vitro may not manifest a phenotype in vivo

OBJECTIVE: To investigate the genetic etiology of a patient diagnosed with leukoencephalopathy, brain calcifications, and cysts (LCC). METHODS: Whole-exome sequencing was performed on a patient with LCC and his unaffected family members. The variants were subject to in silico and in vitro functional testing to determine pathogenicity. RESULTS: Whole-exome sequencing uncovered compound heterozygous mutations in EARS2, c.328G>A (p.G110S), and c.1045G>A (p.E349K). This gene has previously been implicated in the autosomal recessive leukoencephalopathy with thalamus and brainstem involvement and high lactate (LTBL). The p.G110S mutation has been found in multiple patients with LTBL. In silico analysis supported pathogenicity in the second variant. In vitro functional testing showed a significant mitochondrial dysfunction demonstrated by an ∼11% decrease in the oxygen consumption rate and ∼43% decrease in the maximum respiratory rate in the patient's skin fibroblasts compared with the control. EARS2 protein levels were reduced to 30% of normal controls in the patient's fibroblasts. These deficiencies were corrected by the expression of the wild-type EARS2 protein. However, a further unrelated genetic investigation of our patient revealed the presence of biallelic variants in a small nucleolar RNA (SNORD118) responsible for LCC. CONCLUSIONS: Here, we report seemingly pathogenic EARS2 mutations in a single patient with LCC with no biochemical or neuroimaging presentations of LTBL. This patient illustrates that variants with demonstrated impact on protein function should not necessarily be considered clinically relevant.Funding provided by the Baylor Scott & White Healthcare Foundation

A CESA from Griffithsia monilis (Rhodophyta, Florideophyceae) has a family 48 carbohydrate-binding module

Cellulose synthases form rosette terminal complexes in the plasma membranes of Streptophyta and various linear terminal complexes in other taxa. The sequence of a putative CESA from Griffithsia monilis (Rhodophyta, Floridiophyceae) was deduced using a cloning strategy involving degenerate primers, a cDNA library screen, and 5′ and 3′ rapid amplification of cDNA ends (RACE). RACE identified two alternative transcriptional starts and four alternative polyadenylation sites. The first translation start codon provided an open reading frame of 2610 bp encoding 870 amino acids and was PCR amplified without introns from genomic DNA. Southern hybridization indicated one strongly hybridizing gene with possible weakly related genes or pseudogenes. Amino acid sequence analysis identified a family 48 carbohydrate-binding module (CBM) upstream of the protein's first predicted transmembrane domain. There are broad similarities in predicted 3D structures of the family 48 modules from CESA, from several glycogen- and starch-binding enzymes, and from protein kinases, but there are substitutions at some residues thought to be involved in ligand binding. The module in G. monilis CESA will be on the cytoplasmic face of the plasma membrane so that it could potentially bind either low molecular weight ligands or starch which is cytosolic rather than inside membrane-bound plastids in red algae. Possible reasons why red algal CESAs have evolved family 48 modules perhaps as part of a system to regulate cellulose synthase activity in relation to cellular carbohydrate status are briefly discussed

DendroBlast: approximate phylogenetic trees in the absence of multiple sequence alignments

The rapidly growing availability of genome information has created considerable demand for both fast and accurate phylogenetic inference algorithms. We present a novel method called DendroBLAST for reconstructing phylogenetic dendrograms/trees from protein sequences using BLAST. This method differs from other methods by incorporating a simple model of sequence evolution to test the effect of introducing sequence changes on the reliability of the bipartitions in the inferred tree. Using realistic simulated sequence data we demonstrate that this method produces phylogenetic trees that are more accurate than other commonly-used distance based methods though not as accurate as maximum likelihood methods from good quality multiple sequence alignments. In addition to tests on simulated data, we use DendroBLAST to generate input trees for a supertree reconstruction of the phylogeny of the Archaea. This independent analysis produces an approximate phylogeny of the Archaea that has both high precision and recall when compared to previously published analysis of the same dataset using conventional methods. Taken together these results demonstrate that approximate phylogenetic trees can be produced in the absence of multiple sequence alignments, and we propose that these trees will provide a platform for improving and informing downstream bioinformatic analysis. A web implementation of the DendroBLAST method is freely available for use at http://www.dendroblast.com/

Discovery and characterization of a new family of lytic polysaccharide monooxygenases

Lytic polysaccharide monooxygenases (LPMOs) are a recently discovered class of enzymes capable of oxidizing recalcitrant polysaccharides. They are attracting considerable attention owing to their potential use in biomass conversion, notably in the production of biofuels. Previous studies have identified two discrete sequence-based families of these enzymes termed AA9 (formerly GH61) and AA10 (formerly CBM33). Here, we report the discovery of a third family of LPMOs. Using a chitin-degrading exemplar from Aspergillus oryzae, we show that the three-dimensional structure of the enzyme shares some features of the previous two classes of LPMOs, including a copper active center featuring the 'histidine brace' active site, but is distinct in terms of its active site details and its EPR spectroscopy. The newly characterized AA11 family expands the LPMO clan, potentially broadening both the range of potential substrates and the types of reactive copper-oxygen species formed at the active site of LPMOs

Nitrous oxide emissions from European agriculture - An analysis of variability and drivers of emissions from field experiments

Nitrous oxide emissions from a network of agricultural experiments in Europe were used to explore the relative importance of site and management controls of emissions. At each site, a selection of management interventions were compared within replicated experimental designs in plot-based experiments. Arable experiments were conducted at Beano in Italy, El Encin in Spain, Foulum in Denmark, Logården in Sweden, Maulde in Belgium, Paulinenaue in Germany, and Tulloch in the UK. Grassland experiments were conducted at Crichton, Nafferton and Peaknaze in the UK, Gödöllö in Hungary, Rzecin in Poland, Zarnekow in Germany and Theix in France. Nitrous oxide emissions were measured at each site over a period of at least two years using static chambers. Emissions varied widely between sites and as a result of manipulation treatments. Average site emissions (throughout the study period) varied between 0.04 and 21.21 kg N₂O-N ha⁻¹ yr⁻¹, with the largest fluxes and variability associated with the grassland sites. Total nitrogen addition was found to be the single most important determinant of emissions, accounting for 15% of the variance (using linear regression) in the data from the arable sites (<i>p</i> < 0.0001), and 77% in the grassland sites. The annual emissions from arable sites were significantly greater than those that would be predicted by IPCC default emission factors. Variability of N₂O emissions within sites that occurred as a result of manipulation treatments was greater than that resulting from site-to-site and year-to-year variation, highlighting the importance of management interventions in contributing to greenhouse gas mitigation

Metabolic Reconstruction for Metagenomic Data and Its Application to the Human Microbiome

Microbial communities carry out the majority of the biochemical activity on the planet, and they play integral roles in processes including metabolism and immune homeostasis in the human microbiome. Shotgun sequencing of such communities' metagenomes provides information complementary to organismal abundances from taxonomic markers, but the resulting data typically comprise short reads from hundreds of different organisms and are at best challenging to assemble comparably to single-organism genomes. Here, we describe an alternative approach to infer the functional and metabolic potential of a microbial community metagenome. We determined the gene families and pathways present or absent within a community, as well as their relative abundances, directly from short sequence reads. We validated this methodology using a collection of synthetic metagenomes, recovering the presence and abundance both of large pathways and of small functional modules with high accuracy. We subsequently applied this method, HUMAnN, to the microbial communities of 649 metagenomes drawn from seven primary body sites on 102 individuals as part of the Human Microbiome Project (HMP). This provided a means to compare functional diversity and organismal ecology in the human microbiome, and we determined a core of 24 ubiquitously present modules. Core pathways were often implemented by different enzyme families within different body sites, and 168 functional modules and 196 metabolic pathways varied in metagenomic abundance specifically to one or more niches within the microbiome. These included glycosaminoglycan degradation in the gut, as well as phosphate and amino acid transport linked to host phenotype (vaginal pH) in the posterior fornix. An implementation of our methodology is available at http://huttenhower.sph.harvard.edu/human​n. This provides a means to accurately and efficiently characterize microbial metabolic pathways and functional modules directly from high-throughput sequencing reads, enabling the determination of community roles in the HMP cohort and in future metagenomic studies.National Institutes of Health (U.S.) (U54HG004968

Genomics of Aerobic Cellulose Utilization Systems in Actinobacteria

Cellulose degrading enzymes have important functions in the biotechnology industry, including the production of biofuels from lignocellulosic biomass. Anaerobes including Clostridium species organize cellulases and other glycosyl hydrolases into large complexes known as cellulosomes. In contrast, aerobic actinobacteria utilize systems comprised of independently acting enzymes, often with carbohydrate binding domains. Numerous actinobacterial genomes have become available through the Genomic Encyclopedia of Bacteria and Archaea (GEBA) project. We identified putative cellulose-degrading enzymes belonging to families GH5, GH6, GH8, GH9, GH12, GH48, and GH51 in the genomes of eleven members of the actinobacteria. The eleven organisms were tested in several assays for cellulose degradation, and eight of the organisms showed evidence of cellulase activity. The three with the highest cellulase activity were Actinosynnema mirum, Cellulomonas flavigena, and Xylanimonas cellulosilytica. Cellobiose is known to induce cellulolytic enzymes in the model organism Thermobifida fusca, but only Nocardiopsis dassonvillei showed higher cellulolytic activity in the presence of cellobiose. In T. fusca, cellulases and a putative cellobiose ABC transporter are regulated by the transcriptional regulator CelR. Nine organisms appear to use the CelR site or a closely related binding site to regulate an ABC transporter. In some, CelR also regulates cellulases, while cellulases are controlled by different regulatory sites in three organisms. Mining of genome data for cellulose degradative enzymes followed by experimental verification successfully identified several actinobacteria species which were not previously known to degrade cellulose as cellulolytic organisms