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Abstract Carbohydrate active enzymes (CAZymes) are made by various organisms for complex carbohydrate metabolism. Genome mining of CAZymes has become a routine data analysis in (meta-)genome projects, owing to the importance of CAZymes in bioenergy, microbiome, nutrition, agriculture, and global carbon recycling. In 2012, dbCAN was provided as an online web server for automated CAZyme annotation. dbCAN2 (https://bcb.unl.edu/dbCAN2) was further developed in 2018 as a meta server to combine multiple tools for improved CAZyme annotation. dbCAN2 also included CGC-Finder, a tool for identifying CAZyme gene clusters (CGCs) in (meta-)genomes. We have updated the meta server to dbCAN3 with the following new functions and components: (i) dbCAN-sub as a profile Hidden Markov Model database (HMMdb) for substrate prediction at the CAZyme subfamily level; (ii) searching against experimentally characterized polysaccharide utilization loci (PULs) with known glycan substates of the dbCAN-PUL database for substrate prediction at the CGC level; (iii) a majority voting method to consider all CAZymes with substrate predicted from dbCAN-sub for substrate prediction at the CGC level; (iv) improved data browsing and visualization of substrate prediction results on the website. In summary, dbCAN3 not only inherits all the functions of dbCAN2, but also integrates three new methods for glycan substrate prediction. 

Abstract Carbohydrate Active EnZymes (CAZymes) are significantly important for microbial communities to thrive in carbohydrate rich environments such as animal guts, agricultural soils, forest floors, and ocean sediments. Since 2017, microbiome sequencing and assembly have produced numerous metagenome assembled genomes (MAGs). We have updated our dbCAN-seq database (https://bcb.unl.edu/dbCAN_seq) to include the following new data and features: (i) ∼498 000 CAZymes and ∼169 000 CAZyme gene clusters (CGCs) from 9421 MAGs of four ecological (human gut, human oral, cow rumen, and marine) environments; (ii) Glycan substrates for 41 447 (24.54%) CGCs inferred by two novel approaches (dbCAN-PUL homology search and eCAMI subfamily majority voting) (the two approaches agreed on 4183 CGCs for substrate assignments); (iii) A redesigned CGC page to include the graphical display of CGC gene compositions, the alignment of query CGC and subject PUL (polysaccharide utilization loci) of dbCAN-PUL, and the eCAMI subfamily table to support the predicted substrates; (iv) A statistics page to organize all the data for easy CGC access according to substrates and taxonomic phyla; and (v) A batch download page. In summary, this updated dbCAN-seq database highlights glycan substrates predicted for CGCs from microbiomes. Future work will implement the substrate prediction function in our dbCAN2 web server. 

Abstract A cantilever‐free scanning probe lithography (CF‐SPL)‐based method for the rapid polymerization of nanoscale features on a surface via crosslinking and thiol‐acrylate photoreactions is described, wherein the nanoscale position, height, and diameter of each feature can be finely and independently tuned. With precise spatiotemporal control over the illumination pattern, beam pen lithography (BPL) allows for the photo‐crosslinking of polymers into ultrahigh resolution features over centimeter‐scale areas using massively parallel >160 000 pen arrays of individually addressable pens that guide and focus light onto the surface with sub‐diffraction resolution. The photoinduced crosslinking reaction of the ink material, which is composed of photoinitiator, diphenyl(2,4,6‐trimethylbenzoyl) phosphine oxide, poly(ethylene glycol) diacrylate, and thiol‐modified functional binding molecules (i.e., thiol‐PEG‐biotin or 16‐mercaptohexanoic acid), proceeds to ≈80% conversion with UV exposure (72 mW cm⁻²) for short time periods (0.5 s). Such polymer patterns are further reacted with proteins (streptavidin and fibronectin) to yield protein arrays with feature arrangements at high resolution and densities controlled by local UV exposure. This platform, which combines polymer photochemistry and massive arrays of scanning probes, constitutes a new approach to making biomolecular microarrays in a high‐throughput and high‐yielding manner, opening new routes for biochip synthesis, bioscreening, and cell biology research.