Signal peptides (SPs) are short amino acid sequences that control protein secretion and translocation in all living organisms. SPs can be predicted from sequence data, but existing algorithms are unable to detect all known types of SPs. We introduce SignalP 6.0, a machine learning model that detects all five SP types and is applicable to metagenomic data. <<<

Hydrothermal plumes transport reduced chemical species and metals into the open ocean. Despite their considerable spatial scale and impact on biogeochemical cycles, niche differentiation of abundant microbial clades is poorly understood. Here, we analyzed the microbial ecology of two bathy- (Brothers volcano; BrV-cone and northwest caldera; NWC) and a mesopelagic (Macauley volcano; McV) plumes on the Kermadec intra-oceanic arc in the South Pacific Ocean. The microbial community structure, determined by a combination of 16S rRNA gene, fluorescence in situ hybridization and metagenome analysis, was similar to the communities observed in other sulfur-rich plumes. This includes a dominance of the vent characteristic SUP05 clade (up to 22% in McV and 51% in BrV). In each of the three plumes analyzed, the community was dominated by a different yet uncultivated chemoautotrophic SUP05 species, here, provisionally named, Candidatus Thioglobus vadi (McV), Candidatus Thioglobus vulcanius (BrV-cone) and Candidatus Thioglobus plumae (BrV-NWC). Statistical analyses, genomic potential and mRNA expression profiles suggested a SUP05 niche partitioning based on sulfide and iron concentration as well as water depth. A fourth SUP05 species was present at low frequency throughout investigated plume samples and may be capable of heterotrophic or mixotrophic growth. Taken together, we propose that small variations in environmental parameters and depth drive SUP05 niche partitioning in hydrothermal plumes. <<<

Acidobacteriota are widespread and often abundant in marine sediments, yet their metabolic and ecological properties are poorly understood. Here, we examined metabolisms and distributions of Acidobacteriota in marine sediments of Svalbard by functional predictions from metagenome-assembled genomes (MAGs), amplicon sequencing of 16S rRNA and dissimilatory sulfite reductase (dsrB) genes and transcripts, and gene expression analyses of tetrathionate-amended microcosms. Acidobacteriota were the second most abundant dsrB-harboring (averaging 13%) phylum after Desulfobacterota in Svalbard sediments, and represented 4% of dsrB transcripts on average. Meta-analysis of dsrAB datasets also showed Acidobacteriota dsrAB sequences are prominent in marine sediments worldwide, averaging 15% of all sequences analysed, and represent most of the previously unclassified dsrAB in marine sediments. We propose two new Acidobacteriota genera, Candidatus Sulfomarinibacter (class Thermoanaerobaculia, "subdivision 23") and Ca. Polarisedimenticola ("subdivision 22"), with distinct genetic properties that may explain their distributions in biogeochemically distinct sediments. Ca. Sulfomarinibacter encode flexible respiratory routes, with potential for oxygen, nitrous oxide, metal-oxide, tetrathionate, sulfur and sulfite/sulfate respiration, and possibly sulfur disproportionation. Potential nutrients and energy include cellulose, proteins, cyanophycin, hydrogen, and acetate. A Ca. Polarisedimenticola MAG encodes various enzymes to degrade proteins, and to reduce oxygen, nitrate, sulfur/polysulfide and metal-oxides. 16S rRNA gene and transcript profiling of Svalbard sediments showed Ca. Sulfomarinibacter members were relatively abundant and transcriptionally active in sulfidic fjord sediments, while Ca. Polarisedimenticola members were more relatively abundant in metal-rich fjord sediments. Overall, we reveal various physiological features of uncultured marine Acidobacteriota that indicate fundamental roles in seafloor biogeochemical cycling. <<<

Modern CNNs are learning the weights of vast numbers of convolutional operators. In this paper, we raise the fundamental question if this is actually necessary. We show that even in the extreme case of only randomly initializing and never updating spatial filters, certain CNN architectures can be trained to surpass the accuracy of standard training. By reinterpreting the notion of pointwise (1×1) convolutions as an operator to learn linear combinations (LC) of frozen (random) spatial filters, we are able to analyze these effects and propose a generic LC convolution block that allows tuning of the linear combination rate. Empirically, we show that this approach not only allows us to reach high test accuracies on CIFAR and ImageNet but also has favorable properties regarding model robustness, generalization, sparsity, and the total number of necessary weights. Additionally, we propose a novel weight sharing mechanism, which allows sharing of a single weight tensor between all spatial convolution layers to massively reduce the number of weights. <<<

Signal peptidases are vital enzymes in the protein secretion pathway. In Archaea, type I signal peptidase, responsible for the cleavage of secretory signal peptides from the majority of secreted proteins, and prepilin peptidase-like signal peptidase, responsible for processing signal peptides from prepilin-like proteins like the preflagellins and various sugar-binding proteins, have been identified. In addition, the archaeal signal peptide peptidase, responsible for degradation of signal peptides after their removal from precursor proteins, has been characterized. These enzymes seem to have a mosaic of eukaryal and bacterial characteristics, and also possess unique archaeal traits. In this review, the most current knowledge with regard to these enzymes is summarized, including their cellular function, catalytic mechanism and distribution and conservation among archaeal species. Comparisons are drawn of these enzymes to their bacterial and eukaryal counterparts, and unique archaeal features highlighted. <<<

β-Galactosidases catalyze the hydrolysis of β(1-3) and β(1-4) galactosyl bonds in oligosaccharides as well as the inverse reaction of enzymatic condensation and transglycosylation. Here we report the crystallographic structures of Penicillium sp. β-galactosidase and its complex with galactose solved by the SIRAS quick cryo-soaking technique at 1.90 Å and 2.10 Å resolution, respectively. The amino acid sequence of this 120 kDa protein was first assigned putatively on the basis of inspection of the experimental electron density maps and then determined by nucleotide sequence analysis. Primary structure alignments reveal that Penicillium sp. β-galactosidase belongs to family 35 of glycosyl hydrolases (GHF-35). This model is the first 3D structure for a member of GHF-35. Five distinct domains which comprise the structure are assembled in a way previously unobserved for β-galactosidases. Superposition of this complex with other β-galactosidase complexes from several hydrolase families allowed the identification of residue Glu200 as the proton donor and residue Glu299 as the nucleophile involved in catalysis. Penicillium sp. β-galactosidase is a glycoprotein containing seven N-linked oligosaccharide chains and is the only structure of a glycosylated β-galactosidase described to date. <<<

Species of the Enterobacter cloacae complex are widely encountered in nature, but they can act as pathogens. The biochemical and molecular studies on E. cloacae have shown genomic heterogeneity, comprising six species: Enterobacter cloacae, Enterobacter asburiae, Enterobacter hormaechei, Enterobacter kobei, Enterobacter ludwigii and Enterobacter nimipressuralis, E. cloacae and E. hormaechei are the most frequently isolated in human clinical specimens. Phenotypic identification of all species belonging to this taxon is usually difficult and not always reliable; therefore, molecular methods are often used. Although the E. cloacae complex strains are among the most common Enterobacter spp. causing nosocomial bloodstream infections in the last decade, little is known about their virulence-associated properties. By contrast, much has been published on the antibiotic-resistance features of these microorganisms. In fact, they are capable of overproducing AmpC β-lactamases by derepression of a chromosomal gene or by the acquisition of a transferable ampC gene on plasmids conferring the antibiotic resistance. Many other resistance determinants that are able to render ineffective almost all antibiotic families have been recently acquired. Most studies on antimicrobial susceptibility are focused on E. cloacae, E. hormaechei and E. asburiae; these studies reported small variations between the species, and the only significant differences had no discriminating features. <<<

G(M1) gangliosidosis and Morquio B are autosomal recessive lysosomal storage diseases associated with a neurodegenerative disorder or dwarfism and skeletal abnormalities, respectively. These diseases are caused by deficiencies in the lysosomal enzyme β-d-galactosidase (β-Gal), which lead to accumulations of the β-Gal substrates, G(M1) ganglioside, and keratan sulfate. β-Gal is an exoglycosidase that catalyzes the hydrolysis of terminal β-linked galactose residues. This study shows the crystal structures of human β-Gal in complex with its catalytic product galactose or with its inhibitor 1-deoxygalactonojirimycin. Human β-Gal is composed of a catalytic TIM barrel domain followed by β-domain 1 and β-domain 2. To gain structural insight into the molecular defects of β-Gal in the above diseases, the disease-causing mutations were mapped onto the three-dimensional structure. Finally, the possible causes of the diseases are discussed. <<<

Antonella Amore, Brandon C Knott, Nitin T Supekar, Asif Shajahan, Parastoo Azadi, Peng Zhao, Lance Wells, Jeffrey G Linger, Sarah E Hobdey, Todd A Vander Wall, Todd Shollenberger, John M Yarbrough, Zhongping Tan, Michael F Crowley, Michael E Himmel, Stephen R Decker, Gregg T Beckham, Larry E Taylor <<<

In nature, many microbes secrete mixtures of glycoside hydrolases, oxidoreductases, and accessory enzymes to deconstruct polysaccharides and lignin in plants. These enzymes are often decorated with N- and O-glycosylation, the roles of which have been broadly attributed to protection from proteolysis, as the extracellular milieu is an aggressive environment. Glycosylation has been shown to sometimes affect activity, but these effects are not fully understood. Here, we examine N- and O-glycosylation on a model, multimodular glycoside hydrolase family 7 cellobiohydrolase (Cel7A), which exhibits an O-glycosylated carbohydrate-binding module (CBM) and an O-glycosylated linker connected to an N- and O-glycosylated catalytic domain (CD)-a domain architecture common to many biomass-degrading enzymes. We report consensus maps for Cel7A glycosylation that include glycan sites and motifs. Additionally, we examine the roles of glycans on activity, substrate binding, and thermal and proteolytic stability. N-glycan knockouts on the CD demonstrate that N-glycosylation has little impact on cellulose conversion or binding, but does have major stability impacts. O-glycans on the CBM have little impact on binding, proteolysis, or activity in the whole-enzyme context. However, linker O-glycans greatly impact cellulose conversion via their contribution to proteolysis resistance. Molecular simulations predict an additional role for linker O-glycans, namely that they are responsible for maintaining separation between ordered domains when Cel7A is engaged on cellulose, as models predict α-helix formation and decreased cellulose interaction for the nonglycosylated linker. Overall, this study reveals key roles for N- and O-glycosylation that are likely broadly applicable to other plant cell-wall-degrading enzymes. <<<

Abstract Background Efficient targeting to appropriate cell organelles is one of the bottlenecks for the production of recombinant proteins in plant systems. A common practice is to use the native secretory signal peptide of the heterologous protein to be produced. Though general features of secretion signals are conserved between plants and animals, the broad sequence variability among signal peptides suggests differing efficiency of signal peptide recognition. Results Aiming to improve secretion in moss bioreactors, we quantitatively compared the efficiency of two human signal peptides and six signals from recently isolated moss (Physcomitrella patens) proteins. We therefore used fusions of the different signals to heterologous reporter sequences for transient transfection of moss cells and measured the extra- and intracellular accumulation of the recombinant proteins rhVEGF and GST, respectively. Our data demonstrates an up to fivefold higher secretion efficiency with endogenous moss signals compared to the two utilised human signal peptides. Conclusion From the distribution of extra- and intracellular recombinant proteins, we suggest translational inhibition during the signal recognition particle-cycle (SRP-cycle) as the most probable of several possible explanations for the decreased extracellular accumulation with the human signals. In this work, we report on the supremacy of moss secretion signals over the utilised heterologous ones within the moss-bioreactor system. Though the molecular details of this effect remain to be elucidated, our results will contribute to the improvement of molecular farming systems. <<<

Gram-negative bacteria harness multiple protein secretion systems and secrete a large proportion of the proteome. Proteins can be exported to periplasmic space, integrated into membrane, transported into extracellular milieu, or translocated into cytoplasm of contacting cells. It is important for accurate, genome-wide annotation of the secreted proteins and their secretion pathways. In this review, we systematically classified the secreted proteins according to the types of secretion systems in Gram-negative bacteria, summarized the known features of these proteins, and reviewed the algorithms and tools for their prediction. <<<

Gram-negative bacteria harness multiple protein secretion systems and secrete a large proportion of the proteome. Proteins can be exported to periplasmic space, integrated into membrane, transported into extracellular milieu, or translocated into cytoplasm of contacting cells. It is important for accurate, genome-wide annotation of the secreted proteins and their secretion pathways. In this review, we systematically classified the secreted proteins according to the types of secretion systems in Gram-negative bacteria, summarized the known features of these proteins, and reviewed the algorithms and tools for their prediction. <<<