Host-Guest Protein Assembly for Affinity Purification of Methyllysine Proteomes

Overcoming barriers with non-covalent interactions: supramolecular recognition of adamantyl cucurbit[n]uril assemblies for medical applications

Adamantane, a staple in medicinal chemistry, recently became a cornerstone of a supramolecular host-guest drug delivery system, ADA/CB[n]. Owing to a good fit between the adamantane cage and the host cavity of the cucurbit[n]uril macrocycle, formed strong inclusion complexes find applications in drug delivery and controlled drug release. Note that the cucurbit[n]uril host is not solely a delivery vehicle of the ADA/CB[n] system but rather influences the bioactivity and bioavailability of drug molecules and can tune drug properties. Namely, as host-guest interactions are capable of changing the intrinsic properties of the guest molecule, inclusion complexes can become more soluble, bioavailable and more resistant to metabolic conditions compared to individual non-complexed molecules. Such synergistic effects have implications for practical bioapplicability of this complex system and provide a new viewpoint to therapy, beyond the traditional single drug molecule approach. By achieving a balance between guest encapsulation and release, the ADA/CB[n] system has also found use beyond just drug delivery, in fields like bioanalytics, sensing assays, bioimaging, etc. Thus, chemosensing in physiological conditions, indicator displacement assays, in vivo diagnostics and hybrid nanostructures are just some recent examples of the ADA/CB[n] applicability, be it for displacements purposes or as cargo vehicles.

A ratiometric fluorescent probe for the detection of biological thiols based on a new supramolecular design

A new ratiometric fluorescent probe is designed and prepared based on the concept of supramolecular encapsulation and dye competition. This supramolecular probe is based on two commercially-available dyes, one common guest and a simple-to-synthesize host. Fluorescence spectroscopy confirms that the supramolecular probe is capable of detecting thiols quantitatively with a broad linear region in phosphate buffered saline or fetal bovine serum. Mechanistic study shows a reaction between thiol specie and the guest to alter the distribution of encapsulated dyes. The supramolecular probes are demonstrated to quantitatively detect extracellular biological thiols by plate reader, which shows it keeps its effectiveness in complex buffered systems.

Site-specific crosslinking and assembly of tetrameric β-glucuronidase improve glycyrrhizin hydrolysis

In this study, eight nonconserved residues with exposed surfaces and flexible conformations of the homotetrameric PGUS (β-glucuronidase from Aspergillus oryzae Li-3) were identified. Single-point mutation into cysteine enabled the thiol-maleimide reaction and site-specific protein assembly using a two-arm polyethylene glycol (PEG)-maleimide crosslinker (Mal2 ). The Mal2 (1k) (with 1 kDa PEG spacer)-crosslinked PGUS assemblies showed low crosslinking efficiency and unimproved thermostability except for G194C-Mal2 (1k). To improve the crosslinking efficiency, a lengthened crosslinker Mal2 (2k) (with 2 kDa PEG spacer) was used to produce PGUS assembly and a highly improved thermostability was achieved with a half-life of 47.2-169.2 min at 70°C, which is 1.04-3.74 times that of wild type PGUS. It is found that the thermostability of PGUS assembly was closely associated with the formation of inter-tetramer assembly and intratetramer crosslinking, rather than the PEGylation of the enzyme. Therefore, the four-arm PEG-maleimide crosslinker Mal4 (2k) (with 2 kDa PEG spacer) was employed to simultaneously increase the inter-tetramer assembly and intratetramer crosslinking, and the resulting PGUS assemblies showed further improved thermostabilities compared with Mal2 (2k)-crosslinked assemblies. Finally, the application of PGUS assemblies with significantly improved thermostability to the bioconversion of GL proved that the PGUS assembly is a strong catalyst for glycyrrhizin (GL) hydrolysis in industrial applications.

Bioinspired Adhesive Antibacterial Hydrogel with Self-Healing and On-Demand Removability for Enhanced Full-Thickness Skin Wound Repair

Adhesive-caused injury is a great threat for extensive full-thickness skin trauma because extra-strong adhesion can incur unbearable pain and exacerbate trauma upon removal. Herein, inspired by the mussel, we designed and fabricated an adhesive antibacterial hydrogel dressing based on dynamic host-guest interaction that enabled on-demand stimuli-triggered removal to effectively care for wounds. In contrast with most hard-to-removable dressing, this adhesive antibacterial hydrogel exhibited strong adhesion property (85 kPa), which could achieve painless and noninvasive on-demand separation within 2 s through a host-guest competition mechanism (amantadine). At the same time, the hydrogel exhibited rapid self-healing properties, and the broken hydrogel could be completely repaired within 5 min. The hydrogel also had excellent protein adsorption properties, mechanical properties, antibacterial properties, and biocompatibility. This on-demand removal was facilitated by the introduction of amantadine as a competitive guest, without any significant adverse effects on cell activity (>90%) or wound healing (98.5%) in vitro. The full-thickness rat-skin defect model and histomorphological evaluation showed that the hydrogel could significantly promote wound healing and reduce scar formation by regulating inflammation, accelerating skin re-epithelialization, and promoting granulation tissue formation. These results indicate that the developed adhesive antibacterial hydrogel offers a promising therapeutic strategy for the healing of extensive full-layer skin injuries.

Co-expression module analysis reveals high expression homogeneity for both coding and non-coding genes in sepsis

Sepsis is a life-threatening condition characterized by a harmful host response to infection with organ dysfunction. Annually about 20 million people are dead owing to sepsis and its mortality rates is as high as 20%. However, no studies have been carried out to investigate sepsis from the system biology point of view, as previous research predominantly focused on individual genes without considering their interactions and associations. Here, we conducted a comprehensive exploration of genome-wide expression alterations in both mRNAs and long non-coding RNAs (lncRNAs) in sepsis, using six microarray datasets. Co-expression networks were conducted to identify mRNA and lncRNA modules, respectively. Comparing these sepsis modules with normal modules, we observed a homogeneous expression pattern within the mRNA/lncRNA members, with the majority of them displaying consistent expression direction. Moreover, we identified consistent modules across diverse datasets, consisting of 20 common mRNA members and two lncRNAs, namely CHRM3-AS2 and PRKCQ-AS1, which are potential regulators of sepsis. Our results reveal that the up-regulated common mRNAs are mainly involved in the processes of neutrophil mediated immunity, while the down-regulated mRNAs and lncRNAs are significantly overrepresented in T-cell mediated immunity functions. This study sheds light on the co-expression patterns of mRNAs and lncRNAs in sepsis, providing a novel perspective and insight into the sepsis transcriptome, which may facilitate the exploration of candidate therapeutic targets and molecular biomarkers for sepsis.

GPGPS: a robust prognostic gene pair signature of glioma ensembling IDH mutation and 1p/19q co-deletion

MOTIVATION

Many studies have shown that IDH mutation and 1p/19q co-deletion can serve as prognostic signatures of glioma. Although these genetic variations affect the expression of one or more genes, the prognostic value of gene expression related to IDH and 1p/19q status is still unclear.

RESULTS

We constructed an ensemble gene pair signature for the risk evaluation and survival prediction of glioma based on the prior knowledge of the IDH and 1p/19q status. First, we separately built two gene pair signatures IDH-GPS and 1p/19q-GPS and elucidated that they were useful transcriptome markers projecting from corresponding genome variations. Then, the gene pairs in these two models were assembled to develop an integrated model named Glioma Prognostic Gene Pair Signature (GPGPS), which demonstrated high area under the curves (AUCs) to predict 1-, 3- and 5-year overall survival (0.92, 0.88 and 0.80) of glioma. GPGPS was superior to the single GPSs and other existing prognostic signatures (avg AUC = 0.70, concordance index = 0.74). In conclusion, the ensemble prognostic signature with 10 gene pairs could serve as an independent predictor for risk stratification and survival prediction in glioma. This study shed light on transferring knowledge from genetic alterations to expression changes to facilitate prognostic studies.

AVAILABILITY AND IMPLEMENTATION

Codes are available at https://github.com/Kimxbzheng/GPGPS.git.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Applications of Synthetic Receptors in Bioanalysis and Drug Transport

Synthetic receptors are powerful tools for molecular recognition. They can bind to guests with high selectivity and affinity, and their structures are tunable and diversified. These features, plus the relatively low cost and high simplicity in synthesis and modification, support the feasibility of array-based molecular analysis with synthetic receptors for improved selectivity in the recognition of a wide range of targets. More attractively, host-guest interaction is reversible and guest displacement allows biocompatible and gentle release of the host-bound molecules, simplifying the stimulation designs needed to control analyte sensing, enrichment, and transportation. Here, we highlight a few recent advancements in using synthetic receptors for molecular analysis and manipulation, with the focus on macrocyclic receptors and their applications in displacement sensing, separation, imaging, and drug transport.

A Robust and Generalizable Immune-Related Signature for Sepsis Diagnostics

High-throughput sequencing can detect tens of thousands of genes in parallel, providing opportunities for improving the diagnostic accuracy of multiple diseases including sepsis, which is an aggressive inflammatory response to infection that can cause organ failure and death. Early screening of sepsis is essential in clinic, but no effective diagnostic biomarkers are available yet. Here, we present a novel method, Recurrent Logistic Regression, to identify diagnostic biomarkers for sepsis from the blood transcriptome data. A panel including five immune-related genes, LRRN3, IL2RB, FCER1A, TLR5, and S100A12, are determined as diagnostic biomarkers (LIFTS) for sepsis. LIFTS discriminates patients with sepsis from normal controls in high accuracy (AUROC = 0.9959 on average; IC = [0.9722-1.0]) on nine validation cohorts across three independent platforms, which outperforms existing markers. Our analysis determined an accurate prediction model and reproducible transcriptome biomarkers that can lay a foundation for clinical diagnostic tests and biological mechanistic studies.

Iron metabolism-related genes reveal predictive value of acute coronary syndrome

Iron deficiency has detrimental effects in patients with acute coronary syndrome (ACS), which is a common nutritional disorder and inflammation-related disease affects up to one-third people worldwide. However, the specific role of iron metabolism in ACS progression is opaque. In this study, we construct an iron metabolism-related genes (IMRGs) based molecular signature of ACS and to identify novel iron metabolism gene markers for early stage of ACS. The IMRGs were mainly collected from Molecular Signatures Database (mSigDB) and two relevant studies. Two blood transcriptome datasets GSE61144 and GSE60993 were used for constructing the prediction model of ACS. After differential analysis, 22 IMRGs were differentially expressed and defined as DEIGs in the training set. Then, the 22 DEIGs were trained by the Elastic Net to build the prediction model. Five genes, PADI4, HLA-DQA1, LCN2, CD7, and VNN1, were determined using multiple Elastic Net calculations and retained to obtain the optimal performance. Finally, the generated model iron metabolism-related gene signature (imSig) was assessed by the validation set GSE60993 using a series of evaluation measurements. Compared with other machine learning methods, the performance of imSig using Elastic Net was superior in the validation set. Elastic Net consistently scores the higher than Lasso and Logistic regression in the validation set in terms of ROC, PRC, Sensitivity, and Specificity. The prediction model based on iron metabolism-related genes may assist in ACS early diagnosis.

Supramolecular Thermo-Contracting Adhesive Hydrogel with Self-Removability Simultaneously Enhancing Noninvasive Wound Closure and MRSA-Infected Wound Healing

Conventional wound closure and dressing are two crucial, time-consuming but isolated principles in wound care. Even though tissue adhesive opens a new era for wound closure, the method and biomaterial that can simultaneously achieve noninvasive wound closure and promote wound healing are highly appreciated. Herein, a novel supramolecular poly(N-isopropylacrylamide) hybrid hydrogel dressing composed of quaternized chitosan-graft-β-cyclodextrin, adenine, and polypyrrole nanotubes via host-guest interaction and hydrogen bonds is developed. The hydrogel demonstrates thermal contraction of 47% remaining area after 2 h at 37 ℃ and tissue adhesion of 5.74 kPa, which are essential for noninvasive wound closure, and multiple mechanical and biological properties including suitable mechanical properties, self-healing, on-demand removal, antioxidant, hemostasis, and photothermal/intrinsic antibacterial activity (higher 99% killing ratio within 5 min after irradiation). In both full-thickness skin incision and excision wound models, the hydrogel reveals significant wound closure after 24 h post-surgery. In acute and methicillin-resistant Staphylococcus aureus-infected wound and photothermal/intrinsic antibacterial activity assays, wounds treated with the hydrogel demonstrate enhanced wound healing with rapid wound closure rate, mild inflammatory response, advanced angiogenesis, and well-arranged collagen fibers. Altogether, the results indicate the hydrogel is promising in synchronously noninvasive wound closure and enhanced wound healing.

Blood Circulating miRNA Pairs as a Robust Signature for Early Detection of Esophageal Cancer

Esophageal cancer (EC) is a common malignant tumor in the digestive system which is often diagnosed at the middle and late stages. Noninvasive diagnosis using circulating miRNA as biomarkers enables accurate detection of early-stage EC to reduce mortality. We built a diagnostic signature consisting of four miRNA pairs for the early detection of EC using individualized Pairwise Analysis of Gene Expression (iPAGE). Profiling of miRNA expression identified 496 miRNA pairs with significant relative expression change. Four miRNA pairs consistently selected from LASSO were used to construct the final diagnostic model. The performance of the signature was validated using two independent datasets, yielding both AUCs and PRCs over 0.99. Furthermore, precision, recall, and F-score were also evaluated for clinical application, when a fixed threshold is given, resulting in all the scores are larger than 0.92 in the training set, test set, and two validation sets. Our results suggested that the 4-miRNA signature is a new biomarker for the early diagnosis of patients with EC. The clinical use of this signature would have improved the detection of EC for earlier therapy and more favorite prognosis.

Evaluating the Consistency of Gene Methylation in Liver Cancer Using Bisulfite Sequencing Data

Bisulfite sequencing is considered as the gold standard approach for measuring DNA methylation, which acts as a pivotal part in regulating a variety of biological processes without changes in DNA sequences. In this study, we introduced the most prevalent methods for processing bisulfite sequencing data and evaluated the consistency of the data acquired from different measurements in liver cancer. Firstly, we introduced three commonly used bisulfite sequencing assays, i.e., reduced-representation bisulfite sequencing (RRBS), whole-genome bisulfite sequencing (WGBS), and targeted bisulfite sequencing (targeted BS). Next, we discussed the principles and compared different methods for alignment, quality assessment, methylation level scoring, and differentially methylated region identification. After that, we screened differential methylated genes in liver cancer through the three bisulfite sequencing assays and evaluated the consistency of their results. Ultimately, we compared bisulfite sequencing to 450 k beadchip and assessed the statistical similarity and functional association of differentially methylated genes (DMGs) among the four assays. Our results demonstrated that the DMGs measured by WGBS, RRBS, targeted BS and 450 k beadchip are consistently hypo-methylated in liver cancer with high functional similarity.

Long non-coding RNA pairs to assist in diagnosing sepsis

Background

Sepsis is the major cause of death in Intensive Care Unit (ICU) globally. Molecular detection enables rapid diagnosis that allows early intervention to minimize the death rate. Recent studies showed that long non-coding RNAs (lncRNAs) regulate proinflammatory genes and are related to the dysfunction of organs in sepsis. Identifying lncRNA signature with absolute abundance is challenging because of the technical variation and the systematic experimental bias.

Results

Cohorts (n = 768) containing whole blood lncRNA profiling of sepsis patients in the Gene Expression Omnibus (GEO) database were included. We proposed a novel diagnostic strategy that made use of the relative expressions of lncRNA pairs, which are reversed between sepsis patients and normal controls (eg. lncRNA_i > lncRNA_j in sepsis patients and lncRNA_i < lncRNA_j in normal controls), to identify 14 lncRNA pairs as a sepsis diagnostic signature. The signature was then applied to independent cohorts (n = 644) to evaluate its predictive performance across different ages and normalization methods. Comparing to common machine learning models and existing signatures, SepSigLnc consistently attains better performance on the validation cohorts from the same age group (AUC = 0.990 & 0.995 in two cohorts) and across different groups (AUC = 0.878 on average), as well as cohorts processed by an alternative normalization method (AUC = 0.953 on average). Functional analysis demonstrates that the lncRNA pairs in SepsigLnc are functionally similar and tend to implicate in the same biological processes including cell fate commitment and cellular response to steroid hormone stimulus.

Conclusion

Our study identified 14 lncRNA pairs as signature that can facilitate the diagnosis of septic patients at an intervenable point when clinical manifestations are not dramatic. Also, the computational procedure can be generalized to a standard procedure for discovering diagnostic molecule signatures.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07576-4.

Selective recognition of tryptophan by a methylpillar[5]arene-based supramolecular fuorescent probe

Herein we present a simple fluorescence quenching method to selectively recognise and determine L-tryptophan (L-Trp) out of other 19 natural amino acids. Methylpillar[5]arene (MeP5), which is employed as a macrocyclic fluorescent probe, exhibits fluorescence activity in the solution of poor solvents because of aggregation-induced emission (AIE) effect. Fluorescence quenching of MeP5 in the solution of EtOH/CH₂Cl₂ (98/2, v/v) was observed upon the addition of L-Trp whereas other 19 natural amino acids did not bring about obvious change in fluorescence intensity. ¹H NMR titration, fluorescence spectroscopy, mass spectrometry and theoretical analysis revealed that L-Trp can be encapsulated into the cavity of MeP5 to form a stable 1:1 host-guest inclusion complex which accounts for the quenching characteristics. The proposed procedure in this investigation offers an attractive and promising method for the selective detection of L-Trp in a mixture of natural amino acids.

Systematic prediction of autophagy-related proteins using Arabidopsis thaliana interactome data

Autophagy is a self-degradative process that is crucial for maintaining cellular homeostasis by removing damaged cytoplasmic components and recycling nutrients. Such an evolutionary conserved proteolysis process is regulated by the autophagy-related (Atg) proteins. The incomplete understanding of plant autophagy proteome and the importance of a proteome-wide understanding of the autophagy pathway prompted us to predict Atg proteins and regulators in Arabidopsis. Here, we developed a systems-level algorithm to identify autophagy-related modules (ARMs) based on protein subcellular localization, protein-protein interactions, and known Atg proteins. This generates a detailed landscape of the autophagic modules in Arabidopsis. We found that the newly identified genes in each ARM tend to be upregulated and coexpressed during the senescence stage of Arabidopsis. We also demonstrated that the Golgi apparatus ARM, ARM13, functions in the autophagy process by module clustering and functional analysis. To verify the in silico analysis, the Atg candidates in ARM13 that are functionally similar to the core Atg proteins were selected for experimental validation. Interestingly, two of the previously uncharacterized proteins identified from the ARM analysis, AGD1 and Sec14, exhibited bona fide association with the autophagy protein complex in plant cells, which provides evidence for a cross-talk between intracellular pathways and autophagy. Thus, the computational framework has facilitated the identification and characterization of plant-specific autophagy-related proteins and novel autophagy proteins/regulators in higher eukaryotes.

Knockdown of lncRNA MALAT1 Alleviates LPS-Induced Acute Lung Injury via Inhibiting Apoptosis Through the miR-194-5p/FOXP2 Axis

Purpose

We aimed to identify and verify the key genes and lncRNAs associated with acute lung injury (ALI) and explore the pathogenesis of ALI. Research showed that lower expression of the lncRNA metastasis-associated lung carcinoma transcript 1 (MALAT1) alleviates lung injury induced by lipopolysaccharide (LPS). Nevertheless, the mechanisms of MALAT1 on cellular apoptosis remain unclear in LPS-stimulated ALI. We investigated the mechanism of MALAT1 in modulating the apoptosis of LPS-induced human pulmonary alveolar epithelial cells (HPAEpiC).

Methods

Differentially expressed lncRNAs between the ALI samples and normal controls were identified using gene expression profiles. ALI-related genes were determined by the overlap of differentially expressed genes (DEGs), genes correlated with lung, genes correlated with key lncRNAs, and genes sharing significantly high proportions of microRNA targets with MALAT1. Quantitative real-time PCR (qPCR) was applied to detect the expression of MALAT1, microRNA (miR)-194-5p, and forkhead box P2 (FOXP2) mRNA in 1 μg/ml LPS-treated HPAEpiC. MALAT1 knockdown vectors, miR-194-5p inhibitors, and ov-FOXP2 were constructed and used to transfect HPAEpiC. The influence of MALAT1 knockdown on LPS-induced HPAEpiC proliferation and apoptosis via the miR-194-5p/FOXP2 axis was determined using Cell counting kit-8 (CCK-8) assay, flow cytometry, and Western blotting analysis, respectively. The interactions between MALAT1, miR-194-5p, and FOXP2 were verified using dual-luciferase reporter gene assay.

Results

We identified a key lncRNA (MALAT1) and three key genes (EYA1, WNT5A, and FOXP2) that are closely correlated with the pathogenesis of ALI. LPS stimulation promoted MALAT1 expression and apoptosis and also inhibited HPAEpiC viability. MALAT1 knockdown significantly improved viability and suppressed the apoptosis of LPS-stimulated HPAEpiC. Moreover, MALAT1 directly targeted miR-194-5p, a downregulated miRNA in LPS-stimulated HPAEpiC, when FOXP2 was overexpressed. MALAT1 knockdown led to the overexpression of miR-194-5p and restrained FOXP2 expression. Furthermore, inhibition of miR-194-5p exerted a rescue effect on MALAT1 knockdown of FOXP2, whereas the overexpression of FOXP2 reversed the effect of MALAT1 knockdown on viability and apoptosis of LPS-stimulated HPAEpiC.

Conclusion

Our results demonstrated that MALAT1 knockdown alleviated HPAEpiC apoptosis by competitively binding to miR-194-5p and then elevating the inhibitory effect on its target FOXP2. These data provide a novel insight into the role of MALAT1 in the progression of ALI and potential diagnostic and therapeutic strategies for ALI patients.