Mass spectrometric fragmentation patterns discriminate C1- and C4-oxidised cello-oligosaccharides from their non-oxidised and reduced forms

Lytic polysaccharide monooxygenases (LPMOs) are powerful enzymes that degrade recalcitrant polysaccharides, such as cellulose. However, the identification of LPMO-generated C1- and/or C4-oxidised oligosaccharides is far from straightforward. In particular, their fragmentation patterns have not been well established when using mass spectrometry. Hence, we studied the fragmentation behaviours of non-, C1- and C4-oxidised cello-oligosaccharides, including their sodium borodeuteride-reduced forms, by using hydrophilic interaction chromatography and negative ion mode collision induced dissociation - mass spectrometry. Non-oxidised cello-oligosaccharides showed predominantly C- and A-type cleavages. In comparison, C4-oxidised ones underwent B-/Y- and X-cleavage close to the oxidised non-reducing end, while closer to the reducing end C-/Z- and A-fragmentation predominated. C1-oxidised cello-oligosaccharides showed extensively A-cleavage. Reduced oligosaccharides showed predominant glycosidic bond cleavage, both B-/Y- and C-/Z-, close to the non-reducing end. Our findings provide signature mass spectrometric fragmentation patterns to unambiguously elucidate the catalytic behaviour and classification of LPMOs.</p

Fungal glycoside hydrolase family 44 xyloglucanases are restricted to the phylum Basidiomycota and show a distinct xyloglucan cleavage pattern

Xyloglucan is a prominent matrix heteropolysaccharide binding to cellulose microfibrils in primary plant cellwalls. Hence, the hydrolysis of xyloglucan facilitates the overall lignocellulosic biomass degradation. Xyloglucanases (XEGs) are key enzymes classified in several glycoside hydrolase (GH) families. So far, family GH44 has been shown to contain bacterial XEGs only. Detailed genome analysis revealed GH44 members in fungal species from the phylum Basidiomycota, but not in other fungi, which we hypothesized to also be XEGs. Two GH44 enzymes from Dichomitus squalens and Pleurotus ostreatus were heterologously produced and characterized. They exhibited XEG activity and displayed a hydrolytic cleavage pattern different fromthat observed in fungal XEGs from other GH families. Specifically, the fungal GH44 XEGs were not hindered by substitution of neighboring glucosyl units and generated various," "XXXG- type,'' "GXXX(G)-type,'' and "XXX-type'' oligosaccharides. Overall, these fungal GH44 XEGs represent a novel class of enzymes for plant biomass conversion and valorization.Peer reviewe

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals &lt;1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

High resolution product profiling of lytic polysaccharide monooxygenases

Lytic polysaccharide monooxygenases (LPMOs) have been shown to play an important role in enzymatic conversion of plant cell wall polysaccharides during lignocellulose-based biorefinery, which is considered as a sustainable process for the production of biofuels, biochemicals and biomaterials. In the last decade, advances have been achieved in revealing the three-dimensional structure and catalytic mechanism of LPMOs, however, (bio-)chemical characterization and understanding cleavage profiles&nbsp; is still limited. Assigning such characteristics will contribute to the understanding of biological functions and roles of LPMOs in nature, and to the further implementation of LPMOs for industrial applications. Therefore, this thesis attempted to provide deeper insights into the mode-of-action, regioselectivity, substrate cleavage profiles and specificity of Auxiliary Activity (AA) family 9 LPMOs from the fungus Myceliophthora thermophila C1 (MtLPMOs), and from the fungus Neurospora crassa (NcLPMOs).In Chapter 1, the background and objectives of this PhD project are described.In Chapter 2, we investigated product profiles of four fungal AA9 LPMOs (MtLPMO9B, MtLPMO9H, MtLPMO9I and NcLPMO9M) during their oxidative cleavage of three types of cellulose: bacterial cellulose (BC), Avicel® PH-101 (AVI), and regenerated amorphous cellulose (RAC). First, we showed that removal of a CBM1 did not alter the substrate specificity of MtLPMO9B, but decreased the efficiency of degradation of all three types of cellulose. Subsequently, we quantified the oxidized ends in both soluble and insoluble fractions, and profiled the oxidized cello-oligosaccharide patterns generated by MtLPMO9B (with and without a CBM1) from time-course incubations. It was found that MtLPMO9B released mainly oxidized cellobiose from BC, while a more evenly in degree of polymerization (DP) distributed mixture of oxidized cello-oligosaccharide (DP2‒8) was found for AVI and RAC. Our findings suggest that cellulose specificity and product profiles of AA9 LPMOs are modulated by the type of cellulose rather than being LPMO type dependent.In Chapter 3, mass spectrometric fragmentation behaviors and patterns of (NaBD4-reduced) non-, C4- and C1-oxidized cello-oligosaccharides were studied by using hydrophilic interaction chromatography and negative ion mode collision induced dissociation‒mass spectrometry (HILIC-ESI-CID-MS/MS2). We revealed that each type of cello-oligosaccharide studied showed a distinct “signature mass spectrometric fragmentation pattern”: i) non-oxidized showed predominantly C- and A-type cleavages; ii) C4-oxidized underwent B-/Y and X-cleavage close to the oxidized non-reducing end, while C-/Z- and A-fragmentation were predominated closer to the reducing end; iii) C1-oxidized showed extensively A-cleavage, and iv) reduced&nbsp; showed predominant both B-/Y- and C-/Z-, close to the non-reducing end.In Chapter 4, we reported for the first time, identification of a series of LPMO products: C4/C6-double oxidized cello-oligosaccharides aided by NaBD4 reduction and HILIC-ESI-CID-MS/MS2. We found that C4/C6-double oxidized cello-oligosaccharides were generated by C4- and C1/C4-oxidizing LPMOs, but not by C1-oxidizing ones. By using isotope labelled H218O, we confirmed that the C6-gem-diol structure resulted from monooxygenation, though oxidation to a C6-aldehyde, followed by hydration to the C6-gem-diol, could not be excluded.In Chapter 5, five segments around the LPMO active site (Seg1‒Seg5) involved in substrate recognition were defined based on a structure-based alignment. Next, we investigated the changes in activity induced by shortening the Seg2 or removing the CBM1 from NcLPMO9C. The absence of CBM1 reduced the binding affinity and activity of NcLPMO9C, but did not alter its regioselectivity. The linker was found important for the thermal stability of NcLPMO9C and the CBM1 improved binding to RAC. The wild-type NcLPMO9C exhibited the highest activity and strongest substrate binding. Shortening of Seg2 greatly reduced the activity on RAC and completely abolished the activity on xyloglucan.In Chapter 6, we characterized xyloglucan degradation profiles and elucidated structures of oxidized xylogluco-oligosaccharide formed by NcLPMO9C and NcLPMO9M. Our detailed structural characterization showed that oxidative cleavage occurred next to glucosyl units substituted with galactosyl and xylosyl substituted units. This chapter further shows our&nbsp; structure-based phylogenetic analysis of AA9 LPMOs. By assigning substrate cleavage specificities of NcLPMO9C, NcLPMO9M and other published xyloglucan-(in)active LPMOs to this structure-based phylogeny, we indicated a correlation between the configuration of active site segments and xyloglucan specificity of AA9 LPMOs. In brief, LPMOs with +Seg1‒Seg2 were found to be tolerant to xyloglucan substitution, while LPMOs with ‒Seg1+Seg2 were found to be intolerant to xyloglucan substitution. LPMOs with ‒Seg1‒Seg2 or ‒Seg1+Seg2+Seg3 were not active towards xyloglucan. All three types could oxidatively cleave cellulose.In Chapter 7, a new MtLPMO9F and a partially characterized MtLPMO9H were studied for their substrate specificity, especially for their xyloglucan specificity. Aided by NaBD4 reduction and HILIC-ESI-CID-MS/MS2 analysis, we found that both MtLPMOs released predominately C4-oxidized, and C4/C6-double oxidized xylogluco-oligosaccharides. Further characterization showed that MtLPMO9F, having –Seg1+Seg2, generated a “substitution-intolerant” xyloglucan cleavage profile, while for MtLPMO9H (+Seg1–Seg2) a “substitution-tolerant” profile was found. The here characterized xyloglucan specificity and substitution (in)tolerance of MtLPMO9F and MtLPMO9H was as predicted according to our previously published phylogenetic grouping of AA9 LPMOs based on structural active site segment configurations (in Chapter 6).In Chapter 8, we studied a new AA16 member from M. thermophila C1 (MtAA16A), which was suggested to act as LPMO. We found that MtAA16A did not show any oxidative cleavage of carbohydrate substrates including cellulose, hemicellulose, chitin and starch. However, MtAA16A largely boosted all three AA9 MtLPMOs in their oxidative cellulose degradation. The same boosting effect was observed for another AA16 enzyme from Aspergillus nidulans (AnAA16A). However, oxidative cellulose degradation by three NcLPMOs was not boosted by the two AA16 oxidoreductases. The boosting effect was found to relate to H2O2 production by the AA16s and suggested to relate to a fine-tuned H2O2 delivery helped by specific protein-protein interaction.In the final Chapter 9, outcomes and findings of the previous chapters are discussed in context of recent literature (2018-2021). The current applications and future perspectives of LPMOs in lignocellulosic biomass degradation and valorization are also discussed.&nbsp

DeepCatra: Learning flow‐ and graph‐based behaviours for Android malware detection

Abstract As Android malware grows and evolves, deep learning has been introduced into malware detection, resulting in great effectiveness. Recent work is considering hybrid models and multi‐view learning. However, they use only simple features, limiting the accuracy of these approaches in practice. This study proposes DeepCatra, a multi‐view learning approach for Android malware detection, whose model consists of a bidirectional LSTM (BiLSTM) and a graph neural network (GNN) as subnets. The two subnets rely on features extracted from statically computed call traces leading to critical APIs derived from public vulnerabilities. For each Android app, DeepCatra first constructs its call graph and computes call traces reaching critical APIs. Then, temporal opcode features used by the BiLSTM subnet are extracted from the call traces, while flow graph features used by the GNN subnet are constructed from all call traces and inter‐component communications. We evaluate the effectiveness of DeepCatra by comparing it with several state‐of‐the‐art detection approaches. Experimental results on over 18,000 real‐world apps and prevalent malware show that DeepCatra achieves considerable improvement, for example, 2.7%–14.6% on the F1 measure, which demonstrates the feasibility of DeepCatra in practice

DeepCatra: Learning Flow- and Graph-based Behaviors for Android Malware Detection

As Android malware is growing and evolving, deep learning has been introduced into malware detection, resulting in great effectiveness. Recent work is considering hybrid models and multi-view learning. However, they use only simple features, limiting the accuracy of these approaches in practice. In this paper, we propose DeepCatra, a multi-view learning approach for Android malware detection, whose model consists of a bidirectional LSTM (BiLSTM) and a graph neural network (GNN) as subnets. The two subnets rely on features extracted from statically computed call traces leading to critical APIs derived from public vulnerabilities. For each Android app, DeepCatra first constructs its call graph and computes call traces reaching critical APIs. Then, temporal opcode features used by the BiLSTM subnet are extracted from the call traces, while flow graph features used by the GNN subnet are constructed from all the call traces and inter-component communications. We evaluate the effectiveness of DeepCatra by comparing it with several state-of-the-art detection approaches. Experimental results on over 18,000 real-world apps and prevalent malware show that DeepCatra achieves considerable improvement, e.g., 2.7% to 14.6% on F1-measure, which demonstrates the feasibility of DeepCatra in practice.Comment: IET Information Security (to appear

Extending the diversity of Myceliophthora thermophila LPMOs : Two different xyloglucan cleavage profiles

Lytic polysaccharide monooxygenases (LPMOs) play a key role in enzymatic conversion of plant cell wall polysaccharides. Continuous discovery and functional characterization of LPMOs highly contribute to the tailor-made design and improvement of hydrolytic-activity based enzyme cocktails. In this context, a new MtLPMO9F was characterized for its substrate (xyloglucan) specificity, and MtLPMO9H was further delineated. Aided by sodium borodeuteride reduction and hydrophilic interaction chromatography coupled to mass spectrometric analysis, we found that both MtLPMOs released predominately C4-oxidized, and C4/C6-double oxidized xylogluco-oligosaccharides. Further characterization showed that MtLPMO9F, having a short active site segment 1 and a long active site segment 2 (−Seg1+Seg2), followed a “substitution-intolerant” xyloglucan cleavage profile, while for MtLPMO9H (+Seg1−Seg2) a “substitution-tolerant” profile was found. The here characterized xyloglucan specificity and substitution (in)tolerance of MtLPMO9F and MtLPMO9H were as predicted according to our previously published phylogenetic grouping of AA9 LPMOs based on structural active site segment configurations

Strategy to identify reduced arabinoxylo-oligosaccharides by HILIC-MSn

Identification of arabinoxylo-oligosaccharides (AXOS) within complex mixtures is an ongoing analytical challenge. Here, we established a strategy based on hydrophilic interaction chromatography coupled to collision induced dissociation-mass spectrometry (HILIC-MSn) to identify a variety of enzyme-derived AXOS structures. Oligosaccharide reduction with sodium borohydride remarkably improved chromatographic separation of isomers, and improved the recognition of oligosaccharide ends in MS-fragmentation patterns. Localization of arabinosyl substituents was facilitated by decreased intensity of Z ions relative to corresponding Y ions, when fragmentation occurred in the vicinity of substituents. Interestingly, the same B fragment ions (MS2) from HILIC-separated AXOS isomers showed distinct MS3 spectral fingerprints, being diagnostic for the linkage type of arabinosyl substituents. HILIC-MSn identification of AXOS was strengthened by using specific and well-characterized arabinofuranosidases. The detailed characterization of AXOS isomers currently achieved can be applied for studying AXOS functionality in complex (biological) matrices. Overall, the present strategy contributes to the comprehensive carbohydrate sequencing

Active Electromagnetically Induced Transparency Effect in Graphene-Dielectric Hybrid Metamaterial and Its High-Performance Sensor Application

Electromagnetically induced transparency (EIT) based on dielectric metamaterials has attracted attentions in recent years because of its functional manipulation of electromagnetic waves and high refractive index sensitivity, such as high transmission, sharp phase change, and large group delay, etc. In this paper, an active controlled EIT effect based on a graphene-dielectric hybrid metamaterial is proposed in the near infrared region. By changing the Fermi level of the top-covered graphene, a dynamic EIT effect with a high quality factor (Q-factor) is realized, which exhibits a tunable, slow, light performance with a maximum group index of 2500. Another intriguing characteristic of the EIT effect is its high refractive index sensitivity. In the graphene-covered metamaterial, the refractive index sensitivity is simulated as high as 411 nm/RIU and the figure-of-merit (FOM) is up to 159, which outperforms the metastructure without graphene. Therefore, the proposed graphene-covered dielectric metamaterial presents an active EIT effect in the near infrared region, which highlights its great application potential in deep optical switching, tunable slow light devices, and sensitive refractive index sensors, etc

Additional file 1: Figure S1. of A system biology approach to understanding the molecular mechanisms of Gubentongluo decoction acting on IgA Nephropathy

Overview of data generation, processing and analysis. (JPEG 118 kb