UniProt: the universal protein knowledgebase in 2021

The Comparative Genome Dashboard

The Comparative Genome Dashboard is a web-based software tool for interactive exploration of the similarities and differences in gene functions between organisms. It provides a high-level graphical survey of cellular functions, and enables the user to drill down to examine subsystems of interest in greater detail. At its highest level the Comparative Dashboard contains panels for cellular systems such as biosynthesis, energy metabolism, transport, and response to stimulus. Each panel contains a set of bar graphs that plot the numbers of compounds or gene products for each organism across a set of subsystems of that panel. Users can interactively drill down to focus on subsystems of interest and see grids of compounds produced or consumed by each organism, specific GO term assignments, pathway diagrams, and links to more detailed comparison pages. For example, the dashboard enables users to compare the cofactors that a set of organisms can synthesize, the metal ions that they are able to transport, their DNA damage repair capabilities, their biofilm-formation genes, and their viral response proteins. The dashboard enables users to quickly perform comprehensive comparisons at varying levels of detail.

Integrating Network Pharmacology and Experimental Validation to Decipher the Mechanism of Action of Astragalus-Atractylodes Herb Pair in Treating Hepatocellular Carcinoma

Purpose

Traditional Chinese medicine (TCM) therapy is an important means to treat hepatocellular carcinoma (HCC), Astragalus (Latin name: Hedysarum Multijugum Maxim; Chinese name: Huangqi, HQ) and Atractylodes (Latin name: Atractylodes Macrocephala Koidz; Chinese name: Baizhu, BZ) (HQBZ), a classic herb pair, is often used in combination to HCC. However, the main components and potential mechanisms of HQBZ therapy in HCC remain unclear. This study aimed to identify the potential active ingredients and molecular mechanisms of action of HQBZ in HCC treatment.

Methods

The HQBZ-Compound-Target-HCC network and HQBZ-HCC transcriptional regulatory network were constructed to screen the core active compound components and targets of HQBZ therapy for HCC. Molecular docking techniques are used to verify the stability of binding core active compound components to targets. GO and KEGG enrichment analysis were used to explore the signaling pathway of HQBZ in HCC treatment, the mechanism of HQBZ treatment of HCC was verified based on in vivo H22 tumor bearing mice and in vitro cell experiments.

Results

Network pharmacology and molecular docking studies showed that HQBZ treatment of HCC was related to the targeted regulation of IL-6 and STAT3 by the active compound biatractylolide, KEGG pathway enrichment analysis suggest that HQBZ may play a role in the treatment of HCC through IL-6/STAT3 signaling pathway. In vitro experiment results proved that HQBZ could regulate IL-6/STAT3 signaling pathway transduction on CD8+T cells, inhibit CD8+T cell exhaustion and restore the function of exhausted CD8+T cells. In vivo experiment results proved that HQBZ can regulate IL-6/STAT3 signaling pathway transduction in H22 liver cancer model mouse tumor tissue, increased the proportion of tumor infiltrating CD8+T cells.

Conclusion

This study found that HQBZ may play a therapeutic role in HCC by targeting IL-6 and STAT3 through biatractylolide, its mechanism of action is related to regulating IL-6/STAT3 signaling pathway, reversing T cell failure and increasing tumor infiltration CD8+T cells.

Understanding Genetic Risks: Computational Exploration of Human β-Synuclein nsSNPs and their Potential Impact on Structural Alteration

Synucleins are pivotal in neurodegenerative conditions. Beta-synuclein (β-synuclein) is part of the synuclein protein family alongside alpha-synuclein (α-synuclein) and gamma-synuclein (γ-synuclein). These proteins, found mainly in brain tissue and cancers, are soluble and unstructured. β-synuclein shares significant similarity with α-synuclein, especially in their N-terminus, with a 90% match. However, their aggregation tendencies differ significantly. While α-synuclein aggregation is believed to be counteracted by β-synuclein, which occurs in conditions like Parkinson's disease, β-synuclein may counteract α-synuclein's toxic effects on the nervous system, offering potential treatment for neurodegenerative diseases. Under normal circumstances, β-synuclein may guard against disease by interacting with α-synuclein. Yet, in pathological environments with heightened levels or toxic substances, it might contribute to disease. Our research aims to explore potential harmful mutations in the β-synuclein using computational tools to predict their destabilizing impact on protein structure. Consensus analysis revealed rs1207608813 (A63P), rs1340051870 (S72F), and rs1581178262 (G36C) as deleterious. These findings highlight the intricate relationship between nsSNPs and protein function, shedding light on their potential implications in disease pathways. Understanding the structural consequences of nsSNPs is crucial for elucidating their role in pathogenesis and developing targeted therapeutic interventions. Our results offer a robust computational framework for identifying neurodegenerative disorder-related mutations from SNP datasets, potentially reducing the costs associated with experimental characterization.

Genome evolution of the ancient hexaploid Platanus × acerifolia (London planetree)

Whole-genome duplication (WGD; i.e., polyploidy) and chromosomal rearrangement (i.e., genome shuffling) significantly influence genome structure and organization. Many polyploids show extensive genome shuffling relative to their pre-WGD ancestors. No reference genome is currently available for Platanaceae (Proteales), one of the sister groups to the core eudicots. Moreover, Platanus × acerifolia (London planetree; Platanaceae) is a widely used street tree. Given the pivotal phylogenetic position of Platanus and its 2-y flowering transition, understanding its flowering-time regulatory mechanism has significant evolutionary implications; however, the impact of Platanus genome evolution on flowering-time genes remains unknown. Here, we assembled a high-quality, chromosome-level reference genome for P. × acerifolia using a phylogeny-based subgenome phasing method. Comparative genomic analyses revealed that P. × acerifolia (2n = 42) is an ancient hexaploid with three subgenomes resulting from two sequential WGD events; Platanus does not seem to share any WGD with other Proteales or with core eudicots. Each P. × acerifolia subgenome is highly similar in structure and content to the reconstructed pre-WGD ancestral eudicot genome without chromosomal rearrangements. The P. × acerifolia genome exhibits karyotypic stasis and gene sub-/neo-functionalization and lacks subgenome dominance. The copy number of flowering-time genes in P. × acerifolia has undergone an expansion compared to other noncore eudicots, mainly via the WGD events. Sub-/neo-functionalization of duplicated genes provided the genetic basis underlying the unique flowering-time regulation in P. × acerifolia. The P. × acerifolia reference genome will greatly expand understanding of the evolution of genome organization, genetic diversity, and flowering-time regulation in angiosperms.

A convenient model of serum-induced reactivity of human astrocytes to investigate astrocyte-derived extracellular vesicles

Extracellular vesicles (EVs) are secreted by all cells in the CNS, including neurons and astrocytes. EVs are lipid membrane enclosed particles loaded with various bioactive cargoes reflecting the dynamic activities of cells of origin. In contrast to neurons, the specific role of EVs released by astrocytes is less well understood, partly due to the difficulty in maintaining primary astrocyte cultures in a quiescent state. The aim of this study was to establish a human serum-free astrocyte culture system that maintains primary astrocytes in a quiescent state to study the morphology, function, and protein cargoes of astrocyte-derived EVs. Serum-free medium with G5 supplement and serum-supplemented medium with 2% FBS were compared for the culture of commercially available human primary fetal astrocytes. Serum-free astrocytes displayed morphologies similar to in vivo astrocytes, and surprisingly, higher levels of astrocyte markers compared to astrocytes chronically cultured in FBS. In contrast, astrocyte and inflammatory markers in serum-free astrocytes were upregulated 24 h after either acute 2% FBS or cytokine exposure, confirming their capacity to become reactive. Importantly, this suggests that distinct signaling pathways are involved in acute and chronic astrocyte reactivity. Despite having a similar morphology, chronically serum-cultured astrocyte-derived EVs (ADEVs) were smaller in size compared to serum-free ADEVs and could reactivate serum-free astrocytes. Proteomic analysis identified distinct protein datasets for both types of ADEVs with enrichment of complement and coagulation cascades for chronically serum-cultured astrocyte-derived EVs, offering insights into their roles in the CNS. Collectively, these results suggest that human primary astrocytes cultured in serum-free medium bear similarities with in vivo quiescent astrocytes and the addition of serum induces multiple morphological and transcriptional changes that are specific to human reactive astrocytes and their ADEVs. Thus, more emphasis should be made on using multiple structural, molecular, and functional parameters when evaluating ADEVs as biomarkers of astrocyte health.

Unveiling the Ro60-Ro52 complex

The coexistence within a subcellular complex of inter-cellular proteins Ro60, responsible for preserving ncRNA quality, and Ro52, involved in intracellular proteolysis, has been a subject of ongoing debate. Employing molecular docking in tandem with experimental methods like Quartz Crystal Microbalance with Dissipation (QCM-D), Proximity Ligation Assay (PLA), and Indirect Immunofluorescence (IIF), we reveal the presence of Ro60 associating with Ro52 within the cytoplasm. This result unveils the formation of a weak transient complex with a Ka ≈ (3.7 ± 0.3) x 106 M-1, where the toroid-shaped Ro60 structure interacts with the Ro52's Fc receptor, aligning horizontally within the PRY-SPRY domains of the Ro52's homodimer. The stability of this complex relies on the interaction between Ro52 chain A and specific Ro60 residues, such as K133, W177, or L185, vital in the Ro60-YRNA bond. These findings bridge the role of Ro60 in YRNA management with Ro52's function in intracellular proteolysis, emphasizing the potential impact of transient complexes on cellular pathways. See also the graphical abstract(Fig. 1).

Arid5a uses disordered extensions of its core ARID domain for distinct DNA- and RNA-recognition and gene regulation

AT-rich interacting domain (ARID)-containing proteins, Arids, are a heterogeneous DNA-binding protein family involved in transcription regulation and chromatin processing. For the member Arid5a, no exact DNA-binding preference has been experimentally defined so far. Additionally, the protein binds to mRNA motifs for transcript stabilization, supposedly through the DNA-binding ARID domain. To date, however, no unbiased RNA motif definition and clear dissection of nucleic acid-binding through the ARID domain have been undertaken. Using NMR-centered biochemistry, we here define the Arid5a DNA preference. Further, high-throughput in vitro binding reveals a consensus RNA-binding motif engaged by the core ARID domain. Finally, transcriptome-wide binding (iCLIP2) reveals that Arid5a has a weak preference for (A)U-rich regions in pre-mRNA transcripts of factors related to RNA processing. We find that the intrinsically disordered regions flanking the ARID domain modulate the specificity and affinity of DNA binding, while they appear crucial for RNA interactions. Ultimately, our data suggest that Arid5a uses its extended ARID domain for bifunctional gene regulation and that the involvement of IDR extensions is a more general feature of Arids in interacting with different nucleic acids at the chromatin-mRNA interface.

A systematic analysis of the effects of splicing on the diversity of post-translational modifications in protein isoforms

Post-translational modifications (PTMs) and splicing are known to be important regulatory processes for controlling protein function and activity. However, there have been limitations in analyzing the interplay of alternative splicing and PTMs, which stems from the deep differences in genomic and proteomic databases. In this work, we bridged the protein- and genome-centric world views to map PTMs to genomic locations for subsequent projection of PTMs onto alternative isoforms. We then performed a systematic analysis of the diversification of PTMs by alternative splicing, including exploration of the modification-specific rates of inclusion across isoforms and how often the regulatory sequences directly flanking a PTM are impacted by splicing, which might indicate altered regulatory or binding interactions in the alternatively spliced isoform. We found that 6-51% of PTMs are excluded from at least one isoform, depending on the modification type. Further, approximately 2% of prospective PTM sites exhibited altered regulatory sequences surrounding the modification site, suggesting that regulatory or binding interactions might be diversified in these proteoforms. Lastly, we applied this PTM-to-isoform mapping approach to explore the impacts of disease-related splicing in prostate cancer, identifying possible new hypotheses explaining the variable consequences of ESRP1 expression in different cancers. As a part of this work, we have provided an easily implementable tool for annotating splice events identified from RNA-sequencing with PTMs and their functional consequences, called PTM-POSE.

Genomic exploration of the fermented meat isolate Staphylococcus shinii IMDO-S216 with a focus on competitiveness-enhancing secondary metabolites

BACKGROUND

Staphylococcus shinii appears as an umbrella species encompassing several strains of Staphylococcus pseudoxylosus and Staphylococcus xylosus. Given its phylogenetic closeness to S. xylosus, S. shinii can be found in similar ecological niches, including the microbiota of fermented meats where the species may contribute to colour and flavour development. In addition to these conventional functionalities, a biopreservation potential based on the production of antagonistic compounds may be available. Such potential, however, remains largely unexplored in contrast to the large body of research that is available on the biopreservative properties of lactic acid bacteria. The present study outlines the exploration of the genetic basis of competitiveness and antimicrobial activity of a fermented meat isolate, S. shinii IMDO-S216. To this end, its genome was sequenced, de novo assembled, and annotated.

RESULTS

The genome contained a single circular chromosome and eight plasmid replicons. Focus of the genomic exploration was on secondary metabolite biosynthetic gene clusters coding for ribosomally synthesized and posttranslationally modified peptides. One complete cluster was coding for a bacteriocin, namely lactococcin 972; the genes coding for the pre-bacteriocin, the ATP-binding cassette transporter, and the immunity protein were also identified. Five other complete clusters were identified, possibly functioning as competitiveness factors. These clusters were found to be involved in various responses such as membrane fluidity, iron intake from the medium, a quorum sensing system, and decreased sensitivity to antimicrobial peptides and competing microorganisms. The presence of these clusters was equally studied among a selection of multiple Staphylococcus species to assess their prevalence in closely-related organisms.

CONCLUSIONS

Such factors possibly translate in an improved adaptation and competitiveness of S. shinii IMDO-S216 which are, in turn, likely to improve its fitness in a fermented meat matrix.

Chromosome-scale genome assembly of oil-tea tree Camellia crapnelliana

Camellia crapnelliana Tutch., belonging to the Theaceae family, is an excellent landscape tree species with high ornamental values. It is particularly an important woody oil-bearing plant species with high ecological, economic, and medicinal values. Here, we first report the chromosome-scale reference genome of C. crapnelliana with integrated technologies of SMRT, Hi-C and Illumina sequencing platforms. The genome assembly had a total length of ~2.94 Gb with contig N50 of ~67.5 Mb, and ~96.34% of contigs were assigned to 15 chromosomes. In total, we predicted 37,390 protein-coding genes, ~99.00% of which could be functionally annotated. The chromosome-scale genome of C. crapnelliana will become valuable resources for understanding the genetic basis of the fatty acid biosynthesis, and greatly facilitate the exploration and conservation of C. crapnelliana.

A Comprehensive Analysis of Non-Desmosomal Rare Genetic Variants in Arrhythmogenic Cardiomyopathy: Integrating in Padua Cohort Literature-Derived Data

Arrhythmogenic cardiomyopathy (ACM) is an inherited myocardial disease at risk of sudden death. Genetic testing impacts greatly in ACM diagnosis, but gene-disease associations have yet to be determined for the increasing number of genes included in clinical panels. Genetic variants evaluation was undertaken for the most relevant non-desmosomal disease genes. We retrospectively studied 320 unrelated Italian ACM patients, including 243 cases with predominant right-ventricular (ARVC) and 77 cases with predominant left-ventricular (ALVC) involvement, who did not carry pathogenic/likely pathogenic (P/LP) variants in desmosome-coding genes. The aim was to assess rare genetic variants in transmembrane protein 43 (TMEM43), desmin (DES), phospholamban (PLN), filamin c (FLNC), cadherin 2 (CDH2), and tight junction protein 1 (TJP1), based on current adjudication guidelines and reappraisal on reported literature data. Thirty-five rare genetic variants, including 23 (64%) P/LP, were identified in 39 patients (16/243 ARVC; 23/77 ALVC): 22 FLNC, 9 DES, 2 TMEM43, and 2 CDH2. No P/LP variants were found in PLN and TJP1 genes. Gene-based burden analysis, including P/LP variants reported in literature, showed significant enrichment for TMEM43 (3.79-fold), DES (10.31-fold), PLN (117.8-fold) and FLNC (107-fold). A non-desmosomal rare genetic variant is found in a minority of ARVC patients but in about one third of ALVC patients; as such, clinical decision-making should be driven by genes with robust evidence. More than two thirds of non-desmosomal P/LP variants occur in FLNC.

Protein function annotation and virulence factor identification of Klebsiella pneumoniae genome by multiple machine learning models

Klebsiella pneumoniae is a type of Gram-negative bacterium which can cause a range of infections in human. In recent years, an increasing number of strains of K. pneumoniae resistant to multiple antibiotics have emerged, posing a significant threat to public health. The protein function of this bacterium is not well known, thus a systematic investigation of K. pneumoniae proteome is in urgent need. In this study, the protein functions of this bacteria were re-annotated, and their function groups were analyzed. Moreover, three machine learning models were built to identify novel virulence factors. Results showed that the functions of 16 uncharacterized proteins were first annotated by sequence alignment. In addition, K. pneumoniae proteins share a high proportion of homology with Haemophilus influenzae and a low homology proportion with Chlamydia pneumoniae. By sequence analysis, 10 proteins were identified as potential drug targets for this bacterium. Our model achieved a high accuracy of 0.901 in the benchmark dataset. By applying our models to K. pneumoniae, we identified 39 virulence factors in this pathogen. Our findings could provide novel clues for the treatment of K. pneumoniae infection.

PMSPcnn: Predicting protein stability changes upon single point mutations with convolutional neural network

Protein missense mutations and resulting protein stability changes are important causes for many human genetic diseases. However, the accurate prediction of stability changes due to mutations remains a challenging problem. To address this problem, we have developed an unbiased effective model: PMSPcnn that is based on a convolutional neural network. We have included an anti-symmetry property to build a balanced training dataset, which improves the prediction, in particular for stabilizing mutations. Persistent homology, which is an effective approach for characterizing protein structures, is used to obtain topological features. Additionally, a regression stratification cross-validation scheme has been proposed to improve the prediction for mutations with extreme ΔΔG. For three test datasets: Ssym, p53, and myoglobin, PMSPcnn achieves a better performance than currently existing predictors. PMSPcnn also outperforms currently available methods for membrane proteins. Overall, PMSPcnn is a promising method for the prediction of protein stability changes caused by single point mutations.

Are there double knots in proteins? Prediction and in vitro verification based on TrmD-Tm1570 fusion from C. nitroreducens

We have been aware of the existence of knotted proteins for over 30 years-but it is hard to predict what is the most complicated knot that can be formed in proteins. Here, we show new and the most complex knotted topologies recorded to date-double trefoil knots (31 #31). We found five domain arrangements (architectures) that result in a doubly knotted structure in almost a thousand proteins. The double knot topology is found in knotted membrane proteins from the CaCA family, that function as ion transporters, in the group of carbonic anhydrases that catalyze the hydration of carbon dioxide, and in the proteins from the SPOUT superfamily that gathers 31 knotted methyltransferases with the active site-forming knot. For each family, we predict the presence of a double knot using AlphaFold and RoseTTaFold structure prediction. In the case of the TrmD-Tm1570 protein, which is a member of SPOUT superfamily, we show that it folds in vitro and is biologically active. Our results show that this protein forms a homodimeric structure and retains the ability to modify tRNA, which is the function of the single-domain TrmD protein. However, how the protein folds and is degraded remains unknown.

Reproductive chemical database: a curated database of chemicals that modulate protein targets regulating important reproductive biological processes

Recent studies have shifted the spotlight from adult disease to gametogenesis and embryo developmental events, and these are greatly affected by various environmental chemicals, such as drugs, metabolites, pollutants, and others. Growing research has highlighted the critical importance of identifying and understanding the roles of chemicals in reproductive biology. However, the functions and mechanisms of chemicals in reproductive processes remain incomplete. We developed a comprehensive database called the Reproductive Chemical Database (RCDB) ( https://yu.life.sjtu.edu.cn/ChenLab/RCDB ) to facilitate research on chemicals in reproductive biology. This resource is founded on rigorous manual literature extraction and precise protein target prediction methodologies. This database focuses on the delineation of chemicals associated with phenotypes, diseases, or endpoints intricately associated with four important reproductive processes: female and male gamete generation, fertilization, and embryo development in human and mouse. The RCDB encompasses 93 sub-GO processes, and it revealed 1447 intricate chemical-biological process interactions. To date, the RCDB has meticulously cataloged and annotated 830 distinct chemicals, while also predicting 614 target proteins from a selection of 3800 potential candidates. Additionally, the RCDB offers an online predictive tool that empowers researchers to ascertain whether specific chemicals play discernible functional roles in these reproductive processes. The RCDB is an exhaustive, cross-platform, manually curated database, which provides a user-friendly interface to search, browse, and use reproductive processes modulators and their comprehensive related information. The RCDB will help researchers to understand the whole reproductive process and related diseases and it has the potential to promote reproduction research in the pharmacological and pathophysiological areas.

Pan-Cancer Analysis and Experimental Validation of CEND1 as a Prognostic and Immune Infiltration-Associated Biomarker for Gliomas

Cell cycle exit and neuronal differentiation 1 (CEND1), highly expressed in the brain, is a specific transmembrane protein which plays a tumor suppressor role. This study is performed to investigate the role of CEND1 in various cancers through pan-cancer analysis, and further investigate its functions in gliomas by cell experiments. The expression and subcellular localization of CEND1 in different cancer types were analyzed utilizing the data from the GEPIA, UCSC, UALCAN and HPA databases. Relationships of CEND1 expression with prognosis, immunomodulation-related genes, immune checkpoint genes, microsatellite instability (MSI), tumor mutation burden (TMB) and RNA modifications were analyzed based on the TCGA database. The ESTIMATE algorithm was utilized to evaluate tumors' StromalScore, Immune Score, and ESTIMATES Score. The cBioPortal database was employed to analyze the categories and frequencies of CEND1 gene alterations. Biological functions and co-expression patterns of CEND1 in gliomas were explored using the LinkedOmics database, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted. The interactions between CEND1 and drugs were explored employing the Comparative Toxicogenomics Database and molecular docking technology. Cell experiments were conducted to analyze triptonide's effects on glioma cells through CCK-8, flow cytometry and qRT-PCR. CEND1 was lowly expressed in gliomas, and high CEND1 expression was correlated to better overall survival of glioma patients (HR = 0.65, P = 0.02). Deep deletion was the main type of hereditary change of CEND1 mutation. CEND1 expression was markedly associated with immune infiltration, TMB, MSI, and RNA modification in various tumors (r > 0.3, P < 0.05). CEND1 co-expressed genes in gliomas were markedly correlated with immune responses and cell cycle (FDR < 0.05). Triptonide could bind well to CEND1 (-5.0 kcal/mol), and triptonide could facilitate CEND1 expression in glioma cells and cell apoptosis, and block the cell cycle progression (P < 0.05). CEND1 serves as a potential biomarker for pan-cancer. Particularly in gliomas, CEND1 is a key regulator of cell apoptosis and cell cycle, and a potential target for glioma treatment.

Haplotype-resolved chromosome-level genome assembly of Ehretia macrophylla

Ehretia macrophylla Wall, known as wild loquat, is an ecologically, economically, and medicinally significant tree species widely grown in China, Japan, Vietnam, and Nepal. In this study, we have successfully generated a haplotype-resolved chromosome-scale genome assembly of E. macrophylla by integrating PacBio HiFi long-reads, Illumina short-reads, and Hi-C data. The genome assembly consists of two haplotypes, with sizes of 1.82 Gb and 1.58 Gb respectively, and contig N50 lengths of 28.11 Mb and 21.57 Mb correspondingly. Additionally, 99.41% of the assembly was successfully anchored into 40 pseudo-chromosomes. We predicted 58,886 protein-coding genes, of which 99.60% were functionally annotated from databases. We furthermore detected 2.65 Gb repeat sequences, 659,290 rRNAs, 4,931 tRNAs and 4,688 other ncRNAs. The high-quality assembly of the genome offers a solid basis for furthering the fields of molecular breeding and functional genomics of E. macrophylla.

OPTICS: An interactive online platform for photosensory and bio-functional proteins in optogenetic systems

High-precise modulation of bio-functional proteins related to signaling is crucial in life sciences and human health. The cutting-edge technology of optogenetics, which combines optical method with genetically encoded protein expression, pioneered new pathways for the control of cellular bio-functional proteins (CPs) using optogenetic tools (OTs) in spatial and temporal. Over the past decade, hundreds of optogenetic systems (OSs) have been developed for various applications from living cells to freely moving organisms. However, no database has been constructed to comprehensively provide the valuable information of OSs yet. In this work, a new database named OPTICS (an interactive online platform for photosensory and bio-functional proteins in optogenetic systems) is introduced. Our OPTICS is unique in (i) systematically describing diverse OSs from the perspective of photoreceptor-based classification and mechanism of action, (ii) featuring the detailed biophysical properties and functional data of OSs, (iii) providing the interaction between OT and CP for each OS referring to distinct applications in research, diagnosis, and therapy, and (iv) enabling a light response property-based search against all OSs in the database. Since the information on OSs is essential for rapid and predictable design of optogenetic controls, the comprehensive data provided in OPTICS lay a solid foundation for the future development of novel OSs. OPTICS is freely accessible without login requirement at https://idrblab.org/optics/.

A transcriptome-wide association study identified susceptibility genes for hepatocellular carcinoma in East Asia

Background

Hepatocellular carcinoma (HCC) is one of the most common cancers worldwide and is prevalent in East Asia. Although genome-wide association studies (GWASs) of HCC have identified 23 risk regions, the susceptibility genes underlying these associations largely remain unclear. To identify novel candidate genes for HCC, we conducted liver single-tissue and cross-tissue transcriptome-wide association studies (TWASs) in two populations of East Asia.

Methods

GWAS summary statistics of 2,514 subjects (1,161 HCC cases and 1,353 controls) from the Chinese Qidong cohort and 161,323 subjects (2,122 HCC cases and 159,201 controls) from the BioBank Japan project were used to conduct TWAS analysis. The single-tissue and cross-tissue TWAS approaches were both used to detect the association between susceptible genes and the risk of HCC. TWAS identified genes were further annotated by Metascape, UALCAN, GEPIA2, and DepMap.

Results

We identified 22 novel genes at 16 independent loci significantly associated with HCC risk after Bonferroni correction. Of these, 13 genes were located in novel regions. Besides, we found 83 genes overlapped in the Chinese and Japanese cohorts with P < 0.05, of which, three genes (NUAK2, HLA-DQA1, and ATP6V1G2) were discerned by both single-tissue and cross-tissue TWAS approaches. Among the genes identified through TWAS, a significant proportion of them exhibit a credible role in HCC biology, such as FAM96B, HSPA5, POLRMT, MPHOSPH10, and RABL2A. HLA-DQA1, NUAK2, and HSPA5 associated with the process of carcinogenesis in HCC as previously reported.

Conclusions

Our findings highlight the value of leveraging the gene expression data to identify new candidate genes beyond the GWAS associations and could further provide a genetic insight for the biology of HCC.

High-throughput mass spectrometry maps the sepsis plasma proteome and differences in patient response

Sepsis, the dysregulated host response to infection causing life-threatening organ dysfunction, is a global health challenge requiring better understanding of pathophysiology and new therapeutic approaches. Here, we applied high-throughput tandem mass spectrometry to delineate the plasma proteome for sepsis and comparator groups (noninfected critical illness, postoperative inflammation, and healthy volunteers) involving 2612 samples (from 1611 patients) and 4553 liquid chromatography-mass spectrometry analyses acquired through a single batch of continuous measurements, with a throughput of 100 samples per day. We show how this scale of data can delineate proteins, pathways, and coexpression modules in sepsis and be integrated with paired leukocyte transcriptomic data (837 samples from n = 649 patients). We mapped the plasma proteomic landscape of the host response in sepsis, including changes over time, and identified features relating to etiology, clinical phenotypes (including organ failures), and severity. This work reveals subphenotypes informative for sepsis response state, disease processes, and outcome; identifies potential biomarkers; and advances opportunities for a precision medicine approach to sepsis.

Novel metagenomics analysis of stony coral tissue loss disease

Stony coral tissue loss disease (SCTLD) has devastated coral reefs off the coast of Florida and continues to spread throughout the Caribbean. Although a number of bacterial taxa have consistently been associated with SCTLD, no pathogen has been definitively implicated in the etiology of SCTLD. Previous studies have predominantly focused on the prokaryotic community through 16S rRNA sequencing of healthy and affected tissues. Here, we provide a different analytical approach by applying a bioinformatics pipeline to publicly available metagenomic sequencing samples of SCTLD lesions and healthy tissues from four stony coral species. To compensate for the lack of coral reference genomes, we used data from apparently healthy coral samples to approximate a host genome and healthy microbiome reference. These reads were then used as a reference to which we matched and removed reads from diseased lesion tissue samples, and the remaining reads associated only with disease lesions were taxonomically classified at the DNA and protein levels. For DNA classifications, we used a pathogen identification protocol originally designed to identify pathogens in human tissue samples, and for protein classifications, we used a fast protein sequence aligner. To assess the utility of our pipeline, a species-level analysis of a candidate genus, Vibrio, was used to demonstrate the pipeline's effectiveness. Our approach revealed both complementary and unique coral microbiome members compared to a prior metagenome analysis of the same dataset.

The Maintenance of Deleterious Variation in Wild Chinese Rhesus Macaques

Understanding how deleterious variation is shaped and maintained in natural populations is important in conservation and evolutionary biology, as decreased fitness caused by these deleterious mutations can potentially lead to an increase in extinction risk. It is known that demographic processes can influence these patterns. For example, population bottlenecks and inbreeding increase the probability of inheriting identical-by-descent haplotypes from a recent common ancestor, creating long tracts of homozygous genotypes called runs of homozygosity (ROH), which have been associated with an accumulation of mildly deleterious homozygotes. Counterintuitively, positive selection can also maintain deleterious variants in a population through genetic hitchhiking. Here, we analyze the whole genomes of 79 wild Chinese rhesus macaques across five subspecies and characterize patterns of deleterious variation with respect to ROH and signals of recent positive selection. We show that the fraction of homozygotes occurring in long ROH is significantly higher for deleterious homozygotes than tolerated ones, whereas this trend is not observed for short and medium ROH. This confirms that inbreeding, by generating these long tracts of homozygosity, is the main driver of the high burden of homozygous deleterious alleles in wild macaque populations. Furthermore, we show evidence that homozygous LOF variants are being purged. Next, we identify seven deleterious variants at high frequency in regions putatively under selection near genes involved with olfaction and other processes. Our results shed light on how evolutionary processes can shape the distribution of deleterious variation in wild nonhuman primates.

SERPINA11 related novel serpinopathy - A perinatal lethal disorder

SERPINA11 is a hitherto poorly characterised gene belonging to Clade A of the SERPIN superfamily, with unknown expression pattern and functional significance. We report a perinatal lethal phenotype in two foetuses from the same family associated with a biallelic loss of function variant in SERPINA11, and provide functional evidence to support its candidature as a Mendelian disorder. The SERPINA11 variant-associated foetal phenotype is characterised by gross and histopathological features of extracellular matrix disruption. Western blot and immunofluorescence analyses revealed SERPINA11 expression in multiple mouse tissues, with pronounced expression in the bronchiolar epithelium. We observed a significant decrease in SERPINA11 immunofluorescence in the affected foetal lung compared with a healthy gestation-matched foetus. Protein expression data from HEK293T cell lines following site-directed mutagenesis support the loss of function nature of the variant. Transcriptome analysis from the affected foetal liver indicated the possibility of reduced SERPINA11 transcript abundance. This novel serpinopathy appears to be a consequence of the loss of inhibition of serine proteases involved in extracellular matrix remodelling, revealing SERPINA11 as a protease inhibitor critical for embryonic development.

Sororin is an evolutionary conserved antagonist of WAPL

Cohesin mediates sister chromatid cohesion to enable chromosome segregation and DNA damage repair. To perform these functions, cohesin needs to be protected from WAPL, which otherwise releases cohesin from DNA. It has been proposed that cohesin is protected from WAPL by SORORIN. However, in vivo evidence for this antagonism is missing and SORORIN is only known to exist in vertebrates and insects. It is therefore unknown how important and widespread SORORIN's functions are. Here we report the identification of SORORIN orthologs in Schizosaccharomyces pombe (Sor1) and Arabidopsis thaliana (AtSORORIN). sor1Δ mutants display cohesion defects, which are partially alleviated by wpl1Δ. Atsororin mutant plants display dwarfism, tissue specific cohesion defects and chromosome mis-segregation. Furthermore, Atsororin mutant plants are sterile and separate sister chromatids prematurely at anaphase I. The somatic, but not the meiotic deficiencies can be alleviated by loss of WAPL. These results provide in vivo evidence for SORORIN antagonizing WAPL, reveal that SORORIN is present in organisms beyond the animal kingdom and indicate that it has acquired tissue specific functions in plants.

BCL6 is a context-dependent mediator of the glioblastoma response to irradiation therapy

Glioblastoma is a rapidly fatal brain cancer that does not respond to therapy. Previous research showed that the transcriptional repressor protein BCL6 is upregulated by chemo and radiotherapy in glioblastoma, and inhibition of BCL6 enhances the effectiveness of these therapies. Therefore, BCL6 is a promising target to improve the efficacy of current glioblastoma treatment. BCL6 acts as a transcriptional repressor in germinal centre B cells and as an oncogene in lymphoma and other cancers. However, in glioblastoma, BCL6 induced by therapy may not be able to repress transcription. Using a BCL6 inhibitor, the whole proteome response to irradiation was compared with and without BCL6 activity. Acute high dose irradiation caused BCL6 to switch from repressing the DNA damage response to promoting stress response signalling. Rapid immunoprecipitation mass spectrometry of endogenous proteins (RIME) enabled comparison of BCL6 partner proteins between untreated and irradiated glioblastoma cells. BCL6 was associated with transcriptional coregulators in untreated glioblastoma including the known partner NCOR2. However, this association was lost in response to acute irradiation, where BCL6 unexpectedly associated with synaptic and plasma membrane proteins. These results reveal the activity of BCL6 under therapy-induced stress is context-dependent, and potentially altered by the intensity of that stress.

A quantitative and site-specific atlas of the citrullinome reveals widespread existence of citrullination and insights into PADI4 substrates

Despite the importance of citrullination in physiology and disease, global identification of citrullinated proteins, and the precise targeted sites, has remained challenging. Here we employed quantitative-mass-spectrometry-based proteomics to generate a comprehensive atlas of citrullination sites within the HL60 leukemia cell line following differentiation into neutrophil-like cells. We identified 14,056 citrullination sites within 4,008 proteins and quantified their regulation upon inhibition of the citrullinating enzyme PADI4. With this resource, we provide quantitative and site-specific information on thousands of PADI4 substrates, including signature histone marks and transcriptional regulators. Additionally, using peptide microarrays, we demonstrate the potential clinical relevance of certain identified sites, through distinct reactivities of antibodies contained in synovial fluid from anti-CCP-positive and anti-CCP-negative people with rheumatoid arthritis. Collectively, we describe the human citrullinome at a systems-wide level, provide a resource for understanding citrullination at the mechanistic level and link the identified targeted sites to rheumatoid arthritis.

Apprehensions and emerging solutions in ML-based protein structure prediction

The three-dimensional structure of proteins determines their function in vital biological processes. Thus, when the structure is known, the molecular mechanism of protein function can be understood in more detail and obtained information utilized in biotechnological, diagnostics, and therapeutic applications. Over the past five years, machine learning (ML)-based modeling has pushed protein structure prediction to the next level with AlphaFold in the front line, predicting the structure for hundreds of millions of proteins. Further advances recently report promising ML-based approaches for solving remaining challenges by incorporating functionally important metals, co-factors, post-translational modifications, structural dynamics, and interdomain and multimer interactions in the structure prediction process.

Quercetin, Main Active Ingredient of Moutan Cortex, Alleviates Chronic Orofacial Pain via Block of Voltage-Gated Sodium Channel

BACKGROUND

Chronic orofacial pain (COP) therapy is challenging, as current medical treatments are extremely lacking. Moutan Cortex (MC) is a traditional Chinese medicine herb widely used for chronic inflammatory diseases. However, the mechanism behind MC in COP therapy has not been well-established. The purpose of this study was to identify the active ingredients of MC and their specific underlying mechanisms in COP treatment.

METHODS

In this study, the main active ingredients and compound-target network of MC in COP therapy were identified through network pharmacology and bioinformatics analysis. Adult male Sprague-Dawley rats received oral mucosa lipopolysaccharide (LPS) injection to induce COP. Pain behaviors were evaluated by orofacial mechanical nociceptive assessment after intraganglionar injection. In vitro inflammatory cytokines in LPS-pretreated human periodontal ligament stem cells (hPDLSCs) and rat primary cultural trigeminal ganglion (TG) neurons were quantified by real-time quantitative polymerase chain reaction (RT-qPCR). Schrödinger software was used to verify the molecular docking of quercetin and critical targets. Whole-cell recording electrophysiology was used to evaluate the effect of quercetin on voltage-gated sodium (Na v ) channel in rat TG neurons.

RESULTS

The assembled compound-target network consisted of 4 compounds and 46 targets. As 1 of the active components of MC correlated with most related targets, quercetin alleviated mechanical allodynia in LPS-induced rat model of COP (mechanical allodynia threshold median [interquartile range (IQR) 0.5 hours after drug administration: vehicle 1.3 [0.6-2.0] g vs quercetin 7.0 [6.0-8.5] g, P = .002). Gene ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed that immune response and membrane functions play essential roles in MC-COP therapy. Five of the related targets were identified as core targets by protein-protein interaction analysis. Quercetin exerted an analgesic effect, possibly through blocking Na v channel in TG sensory neurons (peak current density median [IQR]: LPS -850.2 [-983.6 to -660.7] mV vs LPS + quercetin -589.6 [-711.0 to -147.8] mV, P = .006) while downregulating the expression level of proinflammatory cytokines-FOS (normalized messenger RNA [mRNA] level mean ± standard error of mean [SEM]: LPS [2. 22 ± 0.33] vs LPS + quercetin [1. 33 ± 0.14], P = .034) and TNF-α (normalized mRNA level mean ± SEM: LPS [8. 93 ± 0.78] vs LPS + quercetin [3. 77 ± 0.49], P < .0001).

CONCLUSIONS

Identifying Na v as the molecular target of quercetin clarifies the analgesic mechanism of MC, and provides ideas for the development of novel selective and efficient chronic pain relievers.

The Crk4-Cyc4 complex regulates G2/M transition in Toxoplasma gondii

A versatile division of apicomplexan parasites and a dearth of conserved regulators have hindered the progress of apicomplexan cell cycle studies. While most apicomplexans divide in a multinuclear fashion, Toxoplasma gondii tachyzoites divide in the traditional binary mode. We previously identified five Toxoplasma CDK-related kinases (Crk). Here, we investigated TgCrk4 and its cyclin partner TgCyc4. We demonstrated that TgCrk4 regulates conventional G2 phase processes, such as repression of chromosome rereplication and centrosome reduplication, and acts upstream of the spindle assembly checkpoint. The spatial TgCyc4 dynamics supported the TgCrk4-TgCyc4 complex role in the coordination of chromosome and centrosome cycles. We also identified a dominant TgCrk4-TgCyc4 complex interactor, TgiRD1 protein, related to DNA replication licensing factor CDT1 but played no role in licensing DNA replication in the G1 phase. Our results showed that TgiRD1 also plays a role in controlling chromosome and centrosome reduplication. Global phosphoproteome analyses identified TgCrk4 substrates, including TgORC4, TgCdc20, TgGCP2, and TgPP2ACA. Importantly, the phylogenetic and structural studies suggest the Crk4-Cyc4 complex is limited to a minor group of the binary dividing apicomplexans.

ProkDBP: Toward more precise identification of prokaryotic DNA binding proteins

Prokaryotic DNA binding proteins (DBPs) play pivotal roles in governing gene regulation, DNA replication, and various cellular functions. Accurate computational models for predicting prokaryotic DBPs hold immense promise in accelerating the discovery of novel proteins, fostering a deeper understanding of prokaryotic biology, and facilitating the development of therapeutics targeting for potential disease interventions. However, existing generic prediction models often exhibit lower accuracy in predicting prokaryotic DBPs. To address this gap, we introduce ProkDBP, a novel machine learning-driven computational model for prediction of prokaryotic DBPs. For prediction, a total of nine shallow learning algorithms and five deep learning models were utilized, with the shallow learning models demonstrating higher performance metrics compared to their deep learning counterparts. The light gradient boosting machine (LGBM), coupled with evolutionarily significant features selected via random forest variable importance measure (RF-VIM) yielded the highest five-fold cross-validation accuracy. The model achieved the highest auROC (0.9534) and auPRC (0.9575) among the 14 machine learning models evaluated. Additionally, ProkDBP demonstrated substantial performance with an independent dataset, exhibiting higher values of auROC (0.9332) and auPRC (0.9371). Notably, when benchmarked against several cutting-edge existing models, ProkDBP showcased superior predictive accuracy. Furthermore, to promote accessibility and usability, ProkDBP (https://iasri-sg.icar.gov.in/prokdbp/) is available as an online prediction tool, enabling free access to interested users. This tool stands as a significant contribution, enhancing the repertoire of resources for accurate and efficient prediction of prokaryotic DBPs.

phuEGO: A Network-Based Method to Reconstruct Active Signaling Pathways From Phosphoproteomics Datasets

Signaling networks are critical for virtually all cell functions. Our current knowledge of cell signaling has been summarized in signaling pathway databases, which, while useful, are highly biased toward well-studied processes, and do not capture context specific network wiring or pathway cross-talk. Mass spectrometry-based phosphoproteomics data can provide a more unbiased view of active cell signaling processes in a given context, however, it suffers from low signal-to-noise ratio and poor reproducibility across experiments. While progress in methods to extract active signaling signatures from such data has been made, there are still limitations with respect to balancing bias and interpretability. Here we present phuEGO, which combines up-to-three-layer network propagation with ego network decomposition to provide small networks comprising active functional signaling modules. PhuEGO boosts the signal-to-noise ratio from global phosphoproteomics datasets, enriches the resulting networks for functional phosphosites and allows the improved comparison and integration across datasets. We applied phuEGO to five phosphoproteomics data sets from cell lines collected upon infection with SARS CoV2. PhuEGO was better able to identify common active functions across datasets and to point to a subnetwork enriched for known COVID-19 targets. Overall, phuEGO provides a flexible tool to the community for the improved functional interpretation of global phosphoproteomics datasets.

PvGeneExpDB: An integrative gene expression database for in-depth understanding on the Pacific white shrimp (Litopenaeus vannamei)

The Pacific white shrimp (Litopenaeus vannamei) is a high-valued economic farming species. With the development of high-throughput sequencing technology, cumulative large-scale transcriptomic studies have been revealing molecular landscape of various biological conditions including genetic selection, breeding, evolution, disease landscape, etc. However, no single experiment or databases allow thorough investigations of transcriptomic dynamics for these progressions. Meanwhile, the available datasets are often scattered and lack management. Here, we have established PvGeneExpDB, the first gene expression database for L. vannamei (www.bio-marine-scau.com/pv_ex/), which encompasses gene expression profiles, differential expression, and co-expression analyses under various biological conditions. Based on the analyses of 7 datasets, which include 53 samples with accurate and detailed records, PvGeneExpDB identifies 20,599 novel transcripts, shows expression profiles of a total of 20,817 genes, and implements Gene Ontology (GO) reconstruction of 76.7 % of these genes. Besides, 26 co-expressed groups were first identified by large-scale, cross-sample Weighted Gene Co-expression Network Analysis (WGCNA). By integrating the gene expression data in the database, our goal is to deepen the biological understanding of L. vannamei.

A Systematic Bioinformatics Approach for Mapping the Minimal Set of a Viral Peptidome

Sequence changes in viral genomes generate protein sequence diversity that enables viruses to evade the host immune system, hindering the development of effective preventive and therapeutic interventions. The massive proliferation of sequence data provides unprecedented opportunities to study viral adaptation and evolution. An alignment-free approach removes various restrictions posed by an alignment-dependent approach for studying sequence diversity. The publicly available tool, UNIQmin, offers an alignment-free approach for studying viral sequence diversity at any given rank of taxonomy lineage and is big data ready. The tool performs an exhaustive search to determine the minimal set of sequences required to capture the peptidome diversity within a given dataset. This compression is possible through the removal of identical sequences and unique sequences that do not contribute effectively to the peptidome diversity pool. Herein, we describe a detailed four-part protocol utilizing UNIQmin to generate the minimal set for the purpose of viral diversity analyses, alignment-free at any rank of the taxonomy lineage, using the recent global public health threat Monkeypox virus (MPX) sequence data as a case study. The protocol enables a systematic bioinformatics approach to study sequence diversity across taxonomic lineages, which is crucial for our future preparedness against viral epidemics. This is particularly important when data are abundant, freely available, and alignment is not an option. © 2024 Wiley Periodicals LLC. Basic Protocol 1: Tool installation and input file preparation Basic Protocol 2: Generation of a minimal set of sequences for a given dataset Basic Protocol 3: Comparative minimal set analysis across taxonomic lineage ranks Basic Protocol 4: Factors affecting the minimal set of sequences.

Cyclotides: The next generation in biopesticide development for eco-friendly agriculture

Chemical pesticides remain the predominant method for pest management in numerous countries. Given the current landscape of agriculture, the development of biopesticides has become increasingly crucial. The strategy empowers farmers to efficiently manage pests and diseases, while prioritizing minimal adverse effects on the environment and human health, hence fostering sustainable management. In recent years, there has been a growing interest and optimism surrounding the utilization of peptide biopesticides for crop protection. These sustainable and environmentally friendly substances have been recognized as viable alternatives to synthetic pesticides due to their outstanding environmental compatibility and efficacy. Numerous studies have been conducted to synthesize and identify peptides that exhibit activity against significant plant pathogens. One of the peptide classes is cyclotides, which are cyclic cysteine-rich peptides renowned for their wide range of sequences and functions. In this review, we conducted a comprehensive analysis of cyclotides, focusing on their structural attributes, developmental history, significant biological functions in crop protection, techniques for identification and investigation, and the application of biotechnology to enhance cyclotide synthesis. The objective is to emphasize the considerable potential of cyclotides as the next generation of plant protection agents on the global scale.

LORE receptor homomerization is required for 3-hydroxydecanoic acid-induced immune signaling and determines the natural variation of immunosensitivity within the Arabidopsis genus

The S-domain-type receptor-like kinase (SD-RLK) LIPOOLIGOSACCHARIDE-SPECIFIC REDUCED ELICITATION (LORE) from Arabidopsis thaliana is a pattern recognition receptor that senses medium-chain 3-hydroxy fatty acids, such as 3-hydroxydecanoic acid (3-OH-C10:0), to activate pattern-triggered immunity. Here, we show that LORE homomerization is required to activate 3-OH-C10:0-induced immune signaling. Fluorescence lifetime imaging in Nicotiana benthamiana demonstrates that AtLORE homomerizes via the extracellular and transmembrane domains. Co-expression of AtLORE truncations lacking the intracellular domain exerts a dominant negative effect on AtLORE signaling in both N. benthamiana and A. thaliana, highlighting that homomerization is essential for signaling. Screening for 3-OH-C10:0-induced reactive oxygen species production revealed natural variation within the Arabidopsis genus. Arabidopsis lyrata and Arabidopsis halleri do not respond to 3-OH-C10:0, although both possess a putative LORE ortholog. Both LORE orthologs have defective extracellular domains that bind 3-OH-C10:0 to a similar level as AtLORE, but lack the ability to homomerize. Thus, ligand binding is independent of LORE homomerization. Analysis of AtLORE and AlyrLORE chimera suggests that the loss of AlyrLORE homomerization is caused by several amino acid polymorphisms across the extracellular domain. Our findings shed light on the activation mechanism of LORE and the loss of 3-OH-C10:0 perception within the Arabidopsis genus.

Proteomics-based identification of biomarkers reflecting endogenous and exogenous exposure to the advanced glycation end product precursor methylglyoxal in SH-SY5Y human neuroblastoma cells

Methylglyoxal (MGO), a highly reactive precursor of advanced glycation end products, is endogenously produced and prevalent in various food products. This study aimed to characterize protein modifications in SH-SY5Y human neuroblastoma cells induced by MGO and identify potential biomarkers for its exposure and toxicity. A shot-gun proteomic analysis was applied to characterize protein modifications in cells incubated with and without exogenous MGO. Seventy-seven proteins were identified as highly susceptible to MGO modification, among which eight, including vimentin and histone H2B type 2-F, showing concentration-dependent modifications by externally added MGO, were defined as biomarkers for exogenous MGO exposure. Remarkably, up to 10 modification sites were identified on vimentin. Myosin light polypeptide 6 emerged as a biomarker for MGO toxicity, with modifications exclusively observed under cytotoxic MGO levels. Additionally, proteins like serine/threonine-protein kinase SIK2 and calcyphosin, exhibiting comparable or even higher modification levels in control compared to exogenous MGO-treated cells, were defined as biomarkers for endogenous exposure. Bioinformatics analysis revealed that motor proteins, cytoskeleton components, and glycolysis proteins were overrepresented among those highly susceptible to MGO modification. These results identify biomarkers for both endogenous and exogenous MGO exposure and provide insights into the cellular effects of endogenously formed versus externally added MGO.

Genome-wide identification and examination of the wheat glycosyltransferase family 43 regulation during Fusarium graminearum infection

In Arabidopsis and rice, the glycosyltransferase (GT) 43 family is involved in xylan synthesis. However, there have been limited reports on the study of the TaGT43 family in wheat. In this study, 28 TaGT43 family members were identified in wheat (Triticum aestivum L.) and clustered into three major groups based on the similarity of amino acid sequences. The results of the TaGT43 family's conserved motif and gene structure analyses agree with this result. Collinearity analysis revealed segmental duplications mainly promoted TaGT43 family expansion. cis-Acting element analysis revealed that the TaGT43 genes were involved in the light response, phytohormone response, abiotic/biotic stress response, and growth and development. The TaGT43 family showed a tissue-specific expression pattern, primarily expressed in roots and stems. Besides, the transcriptional and expression levels of multiple TaGT43 genes were upregulated during the infection of F. graminearum. According to metabolomics studies, F. graminearum infection affected the phenylpropanoid biosynthesis pathway in wheat, a critical factor in cell wall construction. Furthermore, GO enrichment analysis indicated that the TaGT43 genes play a significant role in cell wall organization. Based on these results, it may be concluded that the TaGT43 family mediates cell wall organization in response to F. graminearum infection.

Identification and Characterization of the Lipoprotein N-acyltransferase in Bacteroides

Members of the Bacteroidota compose a large portion of the human gut microbiota, contributing to overall gut health via the degradation of various polysaccharides. This process is facilitated by lipoproteins, globular proteins anchored to the cell surface by a lipidated N-terminal cysteine. Despite their importance, lipoprotein synthesis by these bacteria is understudied. In E. coli, the α-amino linked lipid of lipoproteins is added by the lipoprotein N-acyltransferase Lnt. Herein, we have identified a protein distinct from Lnt responsible for the same process in Bacteroides, named lipoprotein N-acyltransferase in Bacteroides (Lnb). Deletion of Lnb yields cells that synthesize diacylated lipoproteins, with impacts on cell viability and morphology, growth on polysaccharides, and protein composition of membranes and outer membrane vesicles (OMVs). Our results not only challenge the accepted paradigms of lipoprotein biosynthesis in Gram-negative bacteria, but also support the establishment of a new family of lipoprotein N-acyltransferases.

Optimising a self-assembling peptide hydrogel as a Matrigel alternative for 3-dimensional mammary epithelial cell culture

Three-dimensional (3D) organoid models have been instrumental in understanding molecular mechanisms responsible for many cellular processes and diseases. However, established organic biomaterial scaffolds used for 3D hydrogel cultures, such as Matrigel, are biochemically complex and display significant batch variability, limiting reproducibility in experiments. Recently, there has been significant progress in the development of synthetic hydrogels for in vitro cell culture that are reproducible, mechanically tuneable, and biocompatible. Self-assembling peptide hydrogels (SAPHs) are synthetic biomaterials that can be engineered to be compatible with 3D cell culture. Here we investigate the ability of PeptiGel® SAPHs to model the mammary epithelial cell (MEC) microenvironment in vitro. The positively charged PeptiGel®Alpha4 supported MEC viability, but did not promote formation of polarised acini. Modifying the stiffness of PeptiGel® Alpha4 stimulated changes in MEC viability and changes in protein expression associated with altered MEC function, but did not fully recapitulate the morphologies of MECs grown in Matrigel. To supply the appropriate biochemical signals for MEC organoids, we supplemented PeptiGels® with laminin. Laminin was found to require negatively charged PeptiGel® Alpha7 for functionality, but was then able to provide appropriate signals for correct MEC polarisation and expression of characteristic proteins. Thus, optimisation of SAPH composition and mechanics allows tuning to support tissue-specific organoids.

Phylogenomics reveals Adeleorina are an ancient and distinct subgroup of Apicomplexa

Apicomplexans are a diverse phylum of unicellular eukaryotes that share obligate relationships with terrestrial and aquatic animal hosts. Many well-studied apicomplexans are responsible for several deadly zoonotic and human diseases, most notably malaria caused by Plasmodium. Interest in the evolutionary origin of apicomplexans has also spurred recent work on other more deeply-branching lineages, especially gregarines and sister groups like squirmids and chrompodellids. But a full picture of apicomplexan evolution is still lacking several lineages, and one major, diverse lineage that is notably absent is the adeleorinids. Adeleorina apicomplexans comprises hundreds of described species that infect invertebrate and vertebrate hosts across the globe. Although historically considered coccidians, phylogenetic trees based on limited data have shown conflicting branch positions for this subgroup, leaving this question unresolved. Phylogenomic trees and large-scale analyses comparing cellular functions and metabolism between major subgroups of apicomplexans have not incorporated Adeleorina because only a handful of molecular markers and a couple organellar genomes are available, ultimately excluding this group from contributing to our understanding of apicomplexan evolution and biology. To address this gap, we have generated complete genomes from mitochondria and plastids, as well as multiple deep-coverage single-cell transcriptomes of nuclear genes from two Adeleorina species, Klossia helicina and Legerella nova, and inferred a 206-protein phylogenomic tree of Apicomplexa. We observed distinct structures reported in species descriptions as remnant host structures surrounding adeleorinid oocysts. Klossia helicina and L. nova branched, as expected, with monoxenous adeleorinids within the Adeleorina and their mitochondrial and plastid genomes exhibited similarity to published organellar adeleorinid genomes. We show with a phylogeneomic tree and subsequent phylogenomic analyses that Adeleorina are not closely related to any of the currently sampled apicomplexan subgroups, and instead fall as a sister to a large clade encompassing Coccidia, Protococcidia, Hematozoa, and Nephromycida, collectively. This resolves Adeleorina as a key independently-branching group, separate from coccidians, on the tree of Apicomplexa, which now has all known major lineages sampled.

Structure-based learning to predict and model protein-DNA interactions and transcription-factor co-operativity in cis-regulatory elements

Transcription factor (TF) binding is a key component of genomic regulation. There are numerous high-throughput experimental methods to characterize TF-DNA binding specificities. Their application, however, is both laborious and expensive, which makes profiling all TFs challenging. For instance, the binding preferences of ∼25% human TFs remain unknown; they neither have been determined experimentally nor inferred computationally. We introduce a structure-based learning approach to predict the binding preferences of TFs and the automated modelling of TF regulatory complexes. We show the advantage of using our approach over the classical nearest-neighbor prediction in the limits of remote homology. Starting from a TF sequence or structure, we predict binding preferences in the form of motifs that are then used to scan a DNA sequence for occurrences. The best matches are either profiled with a binding score or collected for their subsequent modeling into a higher-order regulatory complex with DNA. Co-operativity is modelled by: (i) the co-localization of TFs and (ii) the structural modeling of protein-protein interactions between TFs and with co-factors. We have applied our approach to automatically model the interferon-β enhanceosome and the pioneering complexes of OCT4, SOX2 (or SOX11) and KLF4 with a nucleosome, which are compared with the experimentally known structures.

Transcriptome-wide gene expression outlier analysis pinpoints therapeutic vulnerabilities in colorectal cancer

Multiple strategies are continuously being explored to expand the drug target repertoire in solid tumors. We devised a novel computational workflow for transcriptome-wide gene expression outlier analysis that allows the systematic identification of both overexpression and underexpression events in cancer cells. Here, it was applied to expression values obtained through RNA sequencing in 226 colorectal cancer (CRC) cell lines that were also characterized by whole-exome sequencing and microarray-based DNA methylation profiling. We found cell models displaying an abnormally high or low expression level for 3533 and 965 genes, respectively. Gene expression abnormalities that have been previously associated with clinically relevant features of CRC cell lines were confirmed. Moreover, by integrating multi-omics data, we identified both genetic and epigenetic alternations underlying outlier expression values. Importantly, our atlas of CRC gene expression outliers can guide the discovery of novel drug targets and biomarkers. As a proof of concept, we found that CRC cell lines lacking expression of the MTAP gene are sensitive to treatment with a PRMT5-MTA inhibitor (MRTX1719). Finally, other tumor types may also benefit from this approach.

Multi-targeted therapeutic potential of stigmasterol from the Euphorbia ammak plant in treating lung and breast cancer

Cancer is the most prevalent disease globally, which presents a significant challenge to the healthcare industry, with breast and lung cancer being predominant malignancies. This study used RNA-seq data from the TCGA database to identify potential biomarkers for lung and breast cancer. Tumor Necrosis Factor (TNFAIP8) and Sulfite Oxidase (SUOX) showed significant expression variation and were selected for further study using structure-based drug discovery (SBDD). Compounds derived from the Euphorbia ammak plant were selected for in-silico study with both TNFAIP8 and SUOX. Stigmasterol had the greatest binding scores (normalized scores of -8.53 kcal/mol and -9.69 kcal/mol) with both proteins, indicating strong stability in their binding pockets throughout the molecular dynamics' simulation. Although Stigmasterol first changed its initial conformation (RMSD = 0.5 nm with the starting conformation) in SUOX, it eventually reached a stable conformation (RMSD of 1.5 nm). The compound on TNFAIP8 showed a persistent shape (RMSD of 0.35 nm), indicating strong protein stability. The binding free energy of the complex was calculated using the MM/GBSA technique; TNFAIP8 had a ΔGTOTAL of -24.98 kcal/mol, with TYR160 being the most significant residue, contributing -2.52 kcal/mol. On the other hand, the SUOX complex had a binding free energy of -16.87 kcal/mol, with LEU151 being the primary contributor (-1.17 kcal/mol). Analysis of the complexes' free energy landscape unveiled several states with minimum free energy, indicating robust interactions between the protein and ligand. In its conclusion, this work emphasises the favourable ability of Stigmasterol to bind with prospective targets for lung and breast cancer, indicating the need for more experimental study.

Comprehensive structural overview of the C-terminal ligand-binding domains of the TetR family regulators

TetR family regulators (TFRs) represent a large group of one-component bacterial signal transduction systems which recognize environmental signals, like the presence of antibiotics or other bactericidal compounds, and trigger the cell response by regulating the expression of genes that secure bacterial survival in harsh environmental conditions. TFRs act as homodimers, each protomer is composed of a conserved DNA-binding N-terminal domain (NTD) and a variable ligand-binding C-terminal domain (CTD). Currently, there are about 500 structures of TFRs available in the Protein Data Bank and one-fourth of them represent the structures of TFR-ligand complexes. In this review, we summarized information on the ligands interacting with TFRs and based on structural data, we compared the CTDs of the TFR family members, as well as their ligand-binding cavities. Additionally, we divided the whole TFR family, including more than half of a million sequences, into subfamilies according to calculated multiple sequence alignment and phylogenetic tree. We also highlighted structural elements characteristic of some of the subfamilies. The presented comprehensive overview of the TFR CTDs provides good bases and future directions for further studies on TFRs that are not only important targets for battling multidrug resistance but also good candidates for many biotechnological approaches, like TFR-based biosensors.

Qi-dan-dihuang decoction ameliorates renal fibrosis in diabetic rats via p38MAPK/AKT/mTOR signaling pathway

CONTEXT

Qi-dan-dihuang decoction (QDD) has been used to treat diabetic kidney disease (DKD), but the underlying mechanisms are poorly understood.

OBJECTIVE

This study reveals the mechanism by which QDD ameliorates DKD.

MATERIALS AND METHODS

The compounds in QDD were identified by high-performance liquid chromatography and quadrupole-time-of-flight tandem mass spectrometry (HPLC-Q-TOF-MS). Key targets and signaling pathways were screened through bioinformatics. Nondiabetic Lepr db/m mice were used as control group, while Lepr db/db mice were divided into model group, dapagliflozin group, 1% QDD-low (QDD-L), and 2% QDD-high (QDD-H) group. After 12 weeks of administration, 24 h urinary protein, serum creatinine, and blood urea nitrogen levels were detected. Kidney tissues damage and fibrosis were evaluated by pathological staining. In addition, 30 mmol/L glucose-treated HK-2 and NRK-52E cells to induce DKD model. Cell activity and migration capacity as well as protein expression levels were evaluated.

RESULTS

A total of 46 key target genes were identified. Functional enrichment analyses showed that key target genes were significantly enriched in the phosphatidylinositol 3-kinase (PI3K)/protein kinase B (AKT) and mitogen-activated protein kinase (MAPK) signaling pathways. In addition, in vivo and in vitro experiments confirmed that QDD ameliorated renal fibrosis in diabetic mice by resolving inflammation and inhibiting the epithelial-mesenchymal transition (EMT) via the p38MAPK and AKT-mammalian target of rapamycin (mTOR) pathways.

DISCUSSION AND CONCLUSION

QDD inhibits EMT and the inflammatory response through the p38MAPK and AKT/mTOR signaling pathways, thereby playing a protective role in renal fibrosis in DKD.

A comprehensive immunoinformatics study to explore and characterize potential vaccine constructs against Ole e 9 allergen of Olea europaea

Immunoglobulin E (IgE)-mediated allergy, which affects more than 30% of the population, is the most prevalent hypersensitivity illness. In an atopic individual, even a small amount of allergen exposure can cause IgE antibodies to be produced. Due to the engagement of receptors that are highly selective for IgE, even tiny amounts of allergens can induce massive inflammation. This study focuses on the exploration and characterization of the allergen potential of Olea europaea allergen (Ole e 9) affecting the population in Saudi Arabia. A systematic computational approach was performed to identify potential epitopes of allergens and complementary determining regions of IgE. In support, physiochemical characterization and secondary structure analysis unravel the structural conformations of allergens and active sites. Epitope prediction uses a pool of computational algorithms to identify plausible epitopes. Furthermore, the vaccine construct was assessed for its binding efficiency using molecular docking and molecular dynamics simulation studies, which led to strong and stable interactions. This is because IgE is known to play a role in allergic responses, which facilitate host cell activation for an immune response. Overall, the immunoinformatics analysis advocates that the proposed vaccine candidate is safe and immunogenic and therefore can be pushed as a lead for in vitro and in vivo investigations.Communicated by Ramaswamy H. Sarma.

Human indoleamine-2,3-dioxygenase 2 cofactor lability and low substrate affinity explained by homology modeling, molecular dynamics and molecular docking

The human indoleamine-2,3-dioxygenase 2 (hIDO2) protein is growing of interest as it is increasingly implicated in multiple diseases (cancer, autoimmune diseases, COVID-19). However, it is only poorly reported in the literature. Its mode of action remains unknown because it does not seem to catalyze the reaction for which it is attributed: the degradation of the L-Tryptophan into N-formyl-kynurenine. This contrasts with its paralog, the human indoleamine-2,3-dioxygenase 1 (hIDO1), which has been extensively studied in the literature and for which several inhibitors are already in clinical trials. Yet, the recent failure of one of the most advanced hIDO1 inhibitors, the Epacadostat, could be caused by a still unknown interaction between hIDO1 and hIDO2. In order to better understand the mechanism of hIDO2, and in the absence of experimental structural data, a computational study mixing homology modeling, Molecular Dynamics, and molecular docking was conducted. The present article highlights an exacerbated lability of the cofactor as well as an inadequate positioning of the substrate in the active site of hIDO2, which might bring part of an answer to its lack of activity.Communicated by Ramaswamy H. Sarma.

Illuminating the neuropeptide Y4 receptor and its ligand pancreatic polypeptide from a structural, functional, and therapeutic perspective

The neuropeptide Y4 receptor (Y4R), a rhodopsin-like G protein-coupled receptor (GPCR) and the hormone pancreatic polypeptide (PP) are members of the neuropeptide Y family consisting of four receptors (Y1R, Y2R, Y4R, Y5R) and three highly homologous peptide ligands (neuropeptide Y, peptide YY, PP). In this family, the Y4R is of particular interest as it is the only subtype with high affinity to PP over NPY. The Y4R, as a mediator of PP signaling, has a pivotal role in appetite regulation and energy homeostasis, offering potential avenues for the treatment of metabolic disorders such as obesity. PP as anorexigenic peptide is released postprandial from the pancreas in response to food intake, induces satiety signals and contributes to hamper excessive food intake. Moreover, this system was also described to be associated with different types of cancer: overexpression of Y4R have been found in human adenocarcinoma cells, while elevated levels of PP are related to the development of pancreatic endocrine tumors. The pharmacological relevance of the Y4R advanced the search for potent and selective ligands for this receptor subtype, which will be significantly progressed through the elucidation of the active state PP-Y4R cryo-EM structure. This review summarizes the development of novel PP-derived ligands, like Obinepitide as dual Y2R/Y4R agonist in clinical trials or UR-AK86c as small hexapeptide agonist with picomolar affinity, as well as the first allosteric modulators that selectively target the Y4R, e.g. VU0506013 as potent Y4R positive allosteric modulator or (S)-VU0637120 as allosteric antagonist. Here, we provide valuable insights into the complex physiological functions of the Y4R and PP and the pharmacological relevance of the system in appetite regulation to open up new avenues for the development of tool compounds for targeted therapies with potential applications in metabolic disorders.

Effect of temperature on structural configuration and immunoreactivity of pH-stressed soybean (Glycine max) agglutinin

Soybean agglutinin (SBA) was purified using ammonium sulfate precipitation and liquid chromatography. Purified SBA was used to produce monoclonal antibodies through hybridoma technology. SBA secondary structure was studied using circular dichroism. pH-stressed (pHs 3.0, 7.2, 8.5, and 9.6) SBA physical properties (particle size, ζ-potential, and aggregation temperature) were investigated. Gel electrophoresis (non-native and native) was used to study heat-induced structural configuration changes in SBA. The effect of pH and temperature on the immunoreactivity of SBA was analyzed using enzyme-linked immunosorbent assay and immunoblots probed with two anti-SBA monoclonal antibodies with either linear or conformational epitopes. The hemagglutinating activity of heated SBA was measured by hemagglutination assay. Our results indicated that SBA had the least thermostability at pH 3.0 and the highest at pH 8.5. Temperature-induced structural configuration change on pH-stressed SBA led to immunoreactivity change. Heat-induced (70 and 80 °C) soluble SBA aggregation was proportionally related to hemagglutinating activity reduction.

Genome, HLA and polygenic risk score analyses for prevalent and persistent cervical human papillomavirus (HPV) infections

Genetic variants that underlie susceptibility to cervical high-risk human papillomavirus (hrHPV) infections are largely unknown. We conducted discovery genome-wide association studies (GWAS), replication, meta-analysis and colocalization, generated polygenic risk scores (PRS) and examined the association of classical HLA alleles and cervical hrHPV infections in a cohort of over 10,000 women. We identified genome-wide significant variants for prevalent hrHPV around LDB2 and for persistent hrHPV near TPTE2, SMAD2, and CDH12, which code for proteins that are significantly expressed in the human endocervix. Genetic variants associated with persistent hrHPV are in genes enriched for the antigen processing and presentation gene set. HLA-DRB1*13:02, HLA-DQB1*05:02 and HLA-DRB1*03:01 were associated with increased risk, and HLA-DRB1*15:03 was associated with decreased risk of persistent hrHPV. The analyses of peptide binding predictions showed that HLA-DRB1 alleles that were positively associated with persistent hrHPV showed weaker binding with peptides derived from hrHPV proteins and vice versa. The PRS for persistent hrHPV with the best model fit, had a P-value threshold (PT) of 0.001 and a p-value of 0.06 (-log10(0.06) = 1.22). The findings of this study expand our understanding of genetic risk factors for hrHPV infection and persistence and highlight the roles of MHC class II molecules in hrHPV infection.