Deep Learning in Proteomics Wen, Bo; Zeng, Wen‐Feng; Liao, Yuxing ...
Proteomics,
November 2020, Volume:
20, Issue:
21-22
Journal Article
Peer reviewed
Open access
Proteomics, the study of all the proteins in biological systems, is becoming a data‐rich science. Protein sequences and structures are comprehensively catalogued in online databases. With recent ...advancements in tandem mass spectrometry (MS) technology, protein expression and post‐translational modifications (PTMs) can be studied in a variety of biological systems at the global scale. Sophisticated computational algorithms are needed to translate the vast amount of data into novel biological insights. Deep learning automatically extracts data representations at high levels of ion from data, and it thrives in data‐rich scientific research domains. Here, a comprehensive overview of deep learning applications in proteomics, including retention time prediction, MS/MS spectrum prediction, de novo peptide sequencing, PTM prediction, major histocompatibility complex‐peptide binding prediction, and protein structure prediction, is provided. Limitations and the future directions of deep learning in proteomics are also discussed. This review will provide readers an overview of deep learning and how it can be used to analyze proteomics data.
The electrocatalytic oxygen evolution reaction (OER) is a critical half-cell reaction for hydrogen production
via
water electrolysis. However, the practical OER suffers from sluggish kinetics and ...thus requires efficient electrocatalysts. Transition metal-based layered double hydroxides (LDHs) represent one of the most active classes of OER catalysts. An in-depth understanding of the activity of LDH based electrocatalysts can promote further rational design and active site regulation of high-performance electrocatalysts. In this review, the fundamental understanding of the structural characteristics of LDHs is demonstrated first, then comparisons and in-depth discussions of recent advances in LDHs as highly active OER catalysts in alkaline media are offered, which include both experimental and computational methods. On top of the active site identification and structural characterization of LDHs on an atomic scale, strategies to promote the OER activity are summarised, including doping, intercalation and defect-making. Furthermore, the concept of superaerophobicity, which has a profound impact on the performance of gas evolution electrodes, is explored to enhance LDHs and their derivatives for a large scale OER. In addition, certain operating standards for OER measurements are proposed to avoid inconsistency in evaluating the OER activity of LDHs. Finally, several key challenges in using LDHs as anode materials for large scale water splitting, such as the issue of stability and the adoption of membrane-electrode-assembly based electrolysers, are emphasized to shed light on future research directions.
Opportunities and challenges in tailoring layered double hydroxides and constructing them into superaerophobic nanoarray electrodes for an efficient oxygen evolution reaction
We explored whether medical health workers had more psychosocial problems than nonmedical health workers during the COVID-19 outbreak.
An online survey was run from February 19 to March 6, 2020; a ...total of 2,182 Chinese subjects participated. Mental health variables were assessed via the Insomnia Severity Index (ISI), the Symptom Check List-revised (SCL-90-R), and the Patient Health Questionnaire-4 (PHQ-4), which included a 2-item anxiety scale and a 2-item depression scale (PHQ-2).
Compared with nonmedical health workers (n = 1,255), medical health workers (n = 927) had a higher prevalence of insomnia (38.4 vs. 30.5%, p < 0.01), anxiety (13.0 vs. 8.5%, p < 0.01), depression (12.2 vs. 9.5%; p< 0.04), somatization (1.6 vs. 0.4%; p < 0.01), and obsessive-compulsive symptoms (5.3 vs. 2.2%; p < 0.01). They also had higher total scores of ISI, GAD-2, PHQ-2, and SCL-90-R obsessive-compulsive symptoms (p ≤ 0.01). Among medical health workers, having organic disease was an independent factor for insomnia, anxiety, depression, somatization, and obsessive-compulsive symptoms (p < 0.05 or 0.01). Living in rural areas, being female, and being at risk of contact with COVID-19 patients were the most common risk factors for insomnia, anxiety, obsessive-compulsive symptoms, and depression (p < 0.01 or 0.05). Among nonmedical health workers, having organic disease was a risk factor for insomnia, depression, and obsessive-compulsive symptoms (p < 0.01 or 0.05).
During the COVID-19 outbreak, medical health workers had psychosocial problems and risk factors for developing them. They were in need of attention and recovery programs.
Increased anthropogenic nitrogen (N) deposition is driving N-limited ecosystems towards phosphorus (P) limitation. Plants have evolved strategies to respond to P limitation which affect N cycling in ...plant‐soil systems. A comprehensive understanding of how plants with efficient P‐acquisition or ‐use strategies influence carbon (C) and N cycling remains elusive. We highlight how P‐acquisition/-use strategies, particularly the release of carboxylates into the rhizosphere, accelerate soil organic matter (SOM) decomposition and soil N mineralisation by destabilising aggregates and organic‐mineral associations. We advocate studying the effects of P-acquisition/-use strategies on SOM formation, directly or through microbial turnover.
In response to low P availability, plants have evolved a variety of P‐acquisition/‐use strategies. These may affect N cycling by influencing SOM turnover.Two microbial strategies (N-mining and co-metabolism) have been proposed to explain microbially mediated priming effects. We suggest that priming should be explained from the perspective of the capacity of a plant to acquire or utilise P under low-P conditions.Efficient P‐acquisition/-use strategies may change N cycling by affecting SOM decomposition. For example, a highly efficient P-mobilising strategy, carboxylate release, may destabilise aggregates and organic‐mineral associations through chelation of metals (such as Fe, Al) and then accelerate SOM decomposition; flavonoids may work in a similar way.Efficient P‐acquisition/-use strategies may affect SOM formation directly or indirectly through microbial turnover.
Sign language recognition, especially the sentence recognition, is of great significance for lowering the communication barrier between the hearing/speech impaired and the non-signers. The general ...glove solutions, which are employed to detect motions of our dexterous hands, only achieve recognizing discrete single gestures (i.e., numbers, letters, or words) instead of sentences, far from satisfying the meet of the signers' daily communication. Here, we propose an artificial intelligence enabled sign language recognition and communication system comprising sensing gloves, deep learning block, and virtual reality interface. Non-segmentation and segmentation assisted deep learning model achieves the recognition of 50 words and 20 sentences. Significantly, the segmentation approach splits entire sentence signals into word units. Then the deep learning model recognizes all word elements and reversely reconstructs and recognizes sentences. Furthermore, new/never-seen sentences created by new-order word elements recombination can be recognized with an average correct rate of 86.67%. Finally, the sign language recognition results are projected into virtual space and translated into text and audio, allowing the remote and bidirectional communication between signers and non-signers.
Single-atom electrocatalysts (SAECs) have gained tremendous attention due to their unique active sites and strong metal–substrate interactions. However, the current synthesis of SAECs mostly relies ...on costly precursors and rigid synthetic conditions and often results in very low content of single-site metal atoms. Herein, we report an efficient synthesis method to prepare metal–nitrogen–carbon SAECs based on formamide condensation and carbonization, featuring a cost-effective general methodology for the mass production of SAECs with high loading of atomically dispersed metal sites. The products with metal inclusion were termed as formamide-converted metal–nitrogen–carbon (shortened as f-MNC) materials. Seven types of single-metallic f-MNC (Fe, Co, Ni, Mn, Zn, Mo and Ir), two bi-metallic (ZnFe and ZnCo) and one tri-metallic (ZnFeCo) SAECs were synthesized to demonstrate the generality of the methodology developed. Remarkably, these f-MNC SAECs can be coated onto various supports with an ultrathin layer as pyrolysis-free electrocatalysts, among which the carbon nanotube-supported f-FeNC and f-NiNC SAECs showed high performance for the O
2
reduction reaction (ORR) and the CO
2
reduction reaction (CO
2
RR), respectively. Furthermore, the pyrolysis products of supported f-MNC can still render isolated metallic sites with excellent activity, as exemplified by the bi-metallic f-FeCoNC SAEC, which exhibited outstanding ORR performance in both alkaline and acid electrolytes by delivering ∼70 and ∼20 mV higher half-wave potentials than that of commercial 20 wt% Pt/C, respectively. This work offers a feasible approach to design and manufacture SAECs with tuneable atomic metal components and high density of single-site metal loading, and thus may accelerate the deployment of SAECs for various energy technology applications.
We describe pLink 2, a search engine with higher speed and reliability for proteome-scale identification of cross-linked peptides. With a two-stage open search strategy facilitated by fragment ...indexing, pLink 2 is ~40 times faster than pLink 1 and 3~10 times faster than Kojak. Furthermore, using simulated datasets, synthetic datasets,
N metabolically labeled datasets, and entrapment databases, four analysis methods were designed to evaluate the credibility of ten state-of-the-art search engines. This systematic evaluation shows that pLink 2 outperforms these methods in precision and sensitivity, especially at proteome scales. Lastly, re-analysis of four published proteome-scale cross-linking datasets with pLink 2 required only a fraction of the time used by pLink 1, with up to 27% more cross-linked residue pairs identified. pLink 2 is therefore an efficient and reliable tool for cross-linking mass spectrometry analysis, and the systematic evaluation methods described here will be useful for future software development.
Intercropping is a farming practice involving two or more crop species, or genotypes, growing together and coexisting for a time. On the fringes of modern intensive agriculture, intercropping is ...important in many subsistence or low‐input/resource‐limited agricultural systems. By allowing genuine yield gains without increased inputs, or greater stability of yield with decreased inputs, intercropping could be one route to delivering ‘sustainable intensification’. We discuss how recent knowledge from agronomy, plant physiology and ecology can be combined with the aim of improving intercropping systems. Recent advances in agronomy and plant physiology include better understanding of the mechanisms of interactions between crop genotypes and species – for example, enhanced resource availability through niche complementarity. Ecological advances include better understanding of the context‐dependency of interactions, the mechanisms behind disease and pest avoidance, the links between above‐ and below‐ground systems, and the role of microtopographic variation in coexistence. This improved understanding can guide approaches for improving intercropping systems, including breeding crops for intercropping. Although such advances can help to improve intercropping systems, we suggest that other topics also need addressing. These include better assessment of the wider benefits of intercropping in terms of multiple ecosystem services, collaboration with agricultural engineering, and more effective interdisciplinary research.
Human infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes coronavirus disease 2019 (COVID-19) and there is no cure currently. The 3CL protease (3CLpro) is a highly ...conserved protease which is indispensable for CoVs replication, and is a promising target for development of broad-spectrum antiviral drugs. In this study we investigated the anti-SARS-CoV-2 potential of Shuanghuanglian preparation, a Chinese traditional patent medicine with a long history for treating respiratory tract infection in China. We showed that either the oral liquid of Shuanghuanglian, the lyophilized powder of Shuanghuanglian for injection or their bioactive components dose-dependently inhibited SARS-CoV-2 3CLpro as well as the replication of SARS-CoV-2 in Vero E6 cells. Baicalin and baicalein, two ingredients of Shuanghuanglian, were characterized as the first noncovalent, nonpeptidomimetic inhibitors of SARS-CoV-2 3CLpro and exhibited potent antiviral activities in a cell-based system. Remarkably, the binding mode of baicalein with SARS-CoV-2 3CLpro determined by X-ray protein crystallography was distinctly different from those of known 3CLpro inhibitors. Baicalein was productively ensconced in the core of the substrate-binding pocket by interacting with two catalytic residues, the crucial S1/S2 subsites and the oxyanion loop, acting as a "shield" in front of the catalytic dyad to effectively prevent substrate access to the catalytic dyad within the active site. Overall, this study provides an example for exploring the in vitro potency of Chinese traditional patent medicines and effectively identifying bioactive ingredients toward a specific target, and gains evidence supporting the in vivo studies of Shuanghuanglian oral liquid as well as two natural products for COVID-19 treatment.
Cell membrane–based nanosystems with desirable characteristics have been studied extensively for many therapeutic applications. However, current research has focused on single cell membrane, and ...multifunctional fused membrane materials from different membrane types are still rare. Herein, a platelet–cancer stem cell (CSC) hybrid membrane‐coated iron oxide magnetic nanoparticle (MN) {CSC‐PMN} is presented for the first time for the enhanced photothermal therapy of head and neck squamous cell carcinoma (HNSCC). Inherited from the original source cells, the platelet membrane shows immune evading ability due to the surface marker comprising a number of “don't eat me” signals, and the CSC membrane has homotypic targeting capabilities due to the specific surface adhesion molecules. The CSC‐PMNs possess superior characteristics for immune evasion, active cancer targeting, magnetic resonance imaging, and photothermal therapy. Compared with single cell membrane–coated MNs, CSC‐PMNs exhibit prolonged circulation times and enhanced targeting abilities. Moreover, the CSC‐PMNs exhibit a superior photothermal ability that provides excellent HNSCC tumor growth inhibition, particularly in an immunocompetent Tgfbr1/Pten conditional double knockout HNSCC mouse model that contains a more complex tumor microenvironment that is similar to the human HNSCC microenvironment. Collectively, this biomimetic multimembrane‐coated nanoplatform may provide enhanced antitumor efficacy in the complex tumor microenvironment.
A natural cancer stem cell‐platelet hybrid mimic membrane is collected from tumor‐bearing mice and further used for magnetic nanoparticle coating. The obtained biomimetic nanoparticles are then injected into the same mice for magnetic resonance imaging and photothermal therapy. The work presents a novel design strategy for personalized cancer theranostics.
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