Motivation: Network alignment (NA) aims to find regions of similarities between species’ molecular networks. There exist two NA categories: local (LNA) and global (GNA). LNA finds small highly conserved network regions and produces a many-to-many node mapping. GNA finds large conserved regions and produces a one-to-one node mapping. Given the different outputs of LNA and GNA, when a new NA method is proposed, it is compared against existing methods from the same category. However, both NA categories have the same goal: to allow for transferring functional knowledge from well- to poorly-studied species between conserved network regions. So, which one to choose, LNA or GNA? To answer this, we introduce the first systematic evaluation of the two NA categories.Results: We introduce new measures of alignment quality that allow for fair comparison of the different LNA and GNA outputs, as such measures do not exist. We provide user-friendly software for efficient alignment evaluation that implements the new and existing measures. We evaluate prominent LNA and GNA methods on synthetic and real-world biological networks. We study the effect on alignment quality of using different interaction types and confidence levels. We find that the superiority of one NA category over the other is context-dependent. Further, when we contrast LNA and GNA in the application of learning novel protein functional knowledge, the two produce very different predictions, indicating their complementarity. Our results and software provide guidelines for future NA method development and evaluation.Availability and implementation: Software: http://www.nd.edu/~cone/LNA_GNAContact: tmilenko@nd.eduSupplementary information: Supplementary data are available at Bioinformatics online.

BackgroundThe genome of Schizophyllum commune encodes a diverse repertoire of degradative enzymes for plant cell wall breakdown. Recent comparative genomics study suggests that this wood decayer likely has a mode of biodegradation distinct from the well-established white-rot/brown-rot models. However, much about the extracellular enzyme system secreted by S. commune during lignocellulose deconstruction remains unknown and the underlying mechanism is poorly understood. In this study, extracellular proteins of S. commune colonizing Jerusalem artichoke stalk were analyzed and compared with those of two white-rot fungi Phanerochaete chrysosporium and Ceriporiopsis subvermispora and a brown-rot fungus Gloeophyllum trabeum.ResultsUnder solid-state fermentation (SSF) conditions, S. commune displayed considerably higher levels of hydrolytic enzyme activities in comparison with those of P. chrysosporium, C. subvermispora and G. trabeum. During biodegradation process, this fungus modified the lignin polymer in a way which was consistent with a hydroxyl radical attack, similar to that of G. trabeum. The crude enzyme cocktail derived from S. commune demonstrated superior performance over a commercial enzyme preparation from Trichoderma longibrachiatum in the hydrolysis of pretreated lignocellulosic biomass at low enzyme loadings. Secretomic analysis revealed that compared with three other fungi, this species produced a higher diversity of carbohydrate-degrading enzymes, especially hemicellulases and pectinases acting on polysaccharide backbones and side chains, and a larger set of enzymes potentially supporting the generation of hydroxyl radicals. In addition, multiple non-hydrolytic proteins implicated in enhancing polysaccharide accessibility were identified in the S. commune secretome, including lytic polysaccharide monooxygenases (LPMOs) and expansin-like proteins.ConclusionsPlant lignocellulose degradation by S. commune involves a hydroxyl radical-mediated mechanism for lignocellulose modification in parallel with the synergistic system of various polysaccharide-degrading enzymes. Furthermore, the complex enzyme system of S. commune holds significant potential for application in biomass saccharification. These discoveries will help unveil the diversity of natural lignocellulose-degrading mechanisms, and advance the design of more efficient enzyme mixtures for the deconstruction of lignocellulosic feedstocks.Electronic supplementary materialThe online version of this article (doi:10.1186/s13068-016-0461-x) contains supplementary material, which is available to authorized users.

Biological network alignment aims to find regions of topological and functional (dis)similarities between molecular networks of different species. Then, network alignment can guide the transfer of biological knowledge from well-studied model species to less well-studied species between conserved (aligned) network regions, thus complementing valuable insights that have already been provided by genomic sequence alignment. Here, we review computational challenges behind the network alignment problem, existing approaches for solving the problem, ways of evaluating their alignment quality, and the approaches’ biomedical applications. We discuss recent innovative efforts of improving the existing view of network alignment. We conclude with open research questions in comparative biological network research that could further our understanding of principles of life, evolution, disease, and therapeutics.

BackgroundLiquid hot water (LHW) pretreatment has been considered as one of the most industrially viable and environment-friendly methods for facilitating the transformation of lignocelluloses into biofuels through biological conversion. However, lignin fragments in pretreatment hydrolysates are preferential to condense with each other and then deposit back onto cellulose surface under severe conditions. Particularly, lignin tends to relocate or redistribute under high-temperature LHW pretreatment conditions. The lignin residues on the cellulose surface would result in significant nonproductive binding of cellulolytic enzymes, and therefore negatively affect the enzymatic conversion (EC) of glucan in pretreated substrates. Although additives such as bovine serum albumin (BSA) and Tween series have been used to reduce nonproductive binding of enzymes through blocking the lignin, the high cost or non-biocompatibility of these additives limits their potential in industrial applications.ResultsHere, we firstly report that a soluble soy protein (SP) extracted from inexpensive defatted soy powder (DSP) showed excellent performance in promoting the EC of glucan in LHW-pretreated lignocellulosic substrates. The addition of the SP (80 mg/g glucan) could readily reduce the cellulase (Celluclast 1.5 L®) loading by 8 times from 96.7 to 12.1 mg protein/g glucan and achieve a glucan EC of 80% at a hydrolysis time of 72 h. With the same cellulase (Celluclast 1.5 L®) loading (24.2 mg protein/g glucan), the ECs of glucan in LHW-pretreated bamboo, eucalyptus, and Masson pine substrates increased from 57%, 54% and 45% (without SP) to 87%, 94% and 86% (with 80 mg SP/g glucan), respectively. Similar effects were also observed when Cellic CTec2, a newer-generation cellulase preparation, was used. Mechanistic studies indicated that the adsorption of soluble SP onto the surface of lignin residues could reduce the nonproductive binding of cellulolytic enzymes to lignin. The cost of the SP required for effective promotion would be equivalent to the cost of 2.9 mg cellulase (Celluclast 1.5 L®) protein (or 1.2 FPU/g glucan), if a proposed semi-simultaneous saccharification and fermentation (semi-SSF) model was used.ConclusionsNear-complete saccharification of glucan in LHW-pretreated lignocellulosic substrates could be achieved with the addition of the inexpensive and biocompatible SP additive extracted from DSP. This simple but remarkably effective technique could readily contribute to improving the economics of the cellulosic biorefinery industry.Electronic supplementary materialThe online version of this article (10.1186/s13068-019-1387-x) contains supplementary material, which is available to authorized users.