Identification of a novel zinc-binding protein, C1orf123, as an interactor with a heavy metal-associated domain

Overexpression of PavHIPP16 from Prunus avium enhances cold stress tolerance in transgenic tobacco

BACKGROUND

The heavy metal-associated isoprenylated plant protein (HIPP) is an important regulatory element in response to abiotic stresses, especially playing a key role in low-temperature response.

RESULTS

This study investigated the potential function of PavHIPP16 up-regulated in sweet cherry under cold stress by heterologous overexpression in tobacco. The results showed that the overexpression (OE) lines' growth state was better than wild type (WT), and the germination rate, root length, and fresh weight of OE lines were significantly higher than those of WT. In addition, the relative conductivity and malondialdehyde (MDA) content of the OE of tobacco under low-temperature treatment were substantially lower than those of WT. In contrast, peroxidase (POD), superoxide dismutase (SOD), catalase (CAT) activities, hydrogen peroxide (H2O2), proline, soluble protein, and soluble sugar contents were significantly higher than those of WT. Yeast two-hybrid assay (Y2H) and luciferase complementation assay verified the interactions between PavbHLH106 and PavHIPP16, suggesting that these two proteins co-regulated the cold tolerance mechanism in plants. The research results indicated that the transgenic lines could perform better under low-temperature stress by increasing the antioxidant enzyme activity and osmoregulatory substance content of the transgenic plants.

CONCLUSIONS

This study provides genetic resources for analyzing the biological functions of PavHIPPs, which is important for elucidating the mechanisms of cold resistance in sweet cherry.

Genome-wide identification of heavy-metal ATPases genes in Areca catechu: investigating their functionality under heavy metal exposure

Heavy-metal ATPases (HMAs) play a vital role in plants, helping to transport heavy metal ions across cell membranes.However, insufficient data exists concerning HMAs genes within the Arecaceae family.In this study, 12 AcHMA genes were identified within the genome of Areca catechu, grouped into two main clusters based on their phylogenetic relationships.Genomic distribution analysis reveals that the AcHMA genes were unevenly distributed across six chromosomes. We further analyzed their physicochemical properties, collinearity, and gene structure.Furthermore, RNA-seq data analysis exhibited varied expressions in different tissues of A. catechu and found that AcHMA1, AcHMA2, and AcHMA7 were highly expressed in roots, leaves, pericarp, and male/female flowers. A total of six AcHMA candidate genes were selected based on gene expression patterns, and their expression in the roots and leaves was determined using RT-qPCR under heavy metal stress. Results showed that the expression levels of AcHMA1 and AcHMA3 genes were significantly up-regulated under Cd2 + and Zn2 + stress. Similarly, in response to Cu2+, the AcHMA5 and AcHMA8 revealed the highest expression in roots and leaves, respectively. In conclusion, this study will offer a foundation for exploring the role of the HMAs gene family in dealing with heavy metal stress conditions in A. catechu.

Hunting down zinc(II)-binding sites in proteins with distance matrices

MOTIVATION

In recent years, high-throughput sequencing technologies have made available the genome sequences of a huge variety of organisms. However, the functional annotation of the encoded proteins often still relies on low-throughput and costly experimental studies. Bioinformatics approaches offer a promising alternative to accelerate this process. In this work, we focus on the binding of zinc(II) ions, which is needed for 5%-10% of any organism's proteins to achieve their physiologically relevant form.

RESULTS

To implement a predictor of zinc(II)-binding sites in the 3D structures of proteins, we used a neural network, followed by a filter of the network output against the local structure of all known sites. The latter was implemented as a function comparing the distance matrices of the Cα and Cβ atoms of the sites. We called the resulting tool Master of Metals (MOM). The structural models for the entire proteome of an organism generated by AlphaFold can be used as input to our tool in order to achieve annotation at the whole organism level within a few hours. To demonstrate this, we applied MOM to the yeast proteome, obtaining a precision of about 76%, based on data for homologous proteins.

AVAILABILITY AND IMPLEMENTATION

Master of Metals has been implemented in Python and is available at https://github.com/cerm-cirmmp/Master-of-metals.

A Genome-Wide Identification and Comparative Analysis of the Heavy-Metal-Associated Gene Family in Cucurbitaceae Species and Their Role in Cucurbita pepo under Arsenic Stress

The heavy-metal-associated (HMA) proteins are a class of PB1-type ATPases related to the intracellular transport and detoxification of metals. However, due to a lack of information regarding the HMA gene family in the Cucurbitaceae family, a comprehensive genome-wide analysis of the HMA family was performed in ten Cucurbitaceae species: Citrullus amarus, Citrullus colocynthis, Citrullus lanatus, Citrullus mucosospermus, Cucumis melo, Cucumis sativus, Cucurbita maxima, Cucurbita moschata, Cucurbita pepo, and Legenaria siceraria. We identified 103 Cucurbit HMA proteins with various members, ranging from 8 (Legenaria siceraria) to 14 (Cucurbita pepo) across species. The phylogenetic and structural analysis confirmed that the Cucurbitaceae HMA protein family could be further classified into two major clades: Zn/Co/Cd/Pb and Cu/Ag. The GO-annotation-based subcellular localization analysis predicted that all HMA gene family members were localized on membranes. Moreover, the analysis of conserved motifs and gene structure (intron/exon) revealed the functional divergence between clades. The interspecies microsynteny analysis demonstrated that maximum orthologous genes were found between species of the Citrullus genera. Finally, nine candidate HMA genes were selected, and their expression analysis was carried out via qRT-PCR in root, leaf, flower, and fruit tissues of C. pepo under arsenic stress. The expression pattern of the CpeHMA genes showed a distinct pattern of expression in root and shoot tissues, with a remarkable expression of CpeHMA6 and CpeHMA3 genes from the Cu/Ag clade. Overall, this study provides insights into the functional analysis of the HMA gene family in Cucurbitaceae species and lays down the basic knowledge to explore the role and mechanism of the HMA gene family to cope with arsenic stress conditions.

Uncharacterized Proteins CxORFx: Subinteractome Analysis and Prognostic Significance in Cancers

Functions of about 10% of all the proteins and their associations with diseases are poorly annotated or not annotated at all. Among these proteins, there is a group of uncharacterized chromosome-specific open-reading frame genes (CxORFx) from the 'Tdark' category. The aim of the work was to reveal associations of CxORFx gene expression and ORF proteins' subinteractomes with cancer-driven cellular processes and molecular pathways. We performed systems biology and bioinformatic analysis of 219 differentially expressed CxORFx genes in cancers, an estimation of prognostic significance of novel transcriptomic signatures and analysis of subinteractome composition using several web servers (GEPIA2, KMplotter, ROC-plotter, TIMER, cBioPortal, DepMap, EnrichR, PepPSy, cProSite, WebGestalt, CancerGeneNet, PathwAX II and FunCoup). The subinteractome of each ORF protein was revealed using ten different data sources on physical protein-protein interactions (PPIs) to obtain representative datasets for the exploration of possible cellular functions of ORF proteins through a spectrum of neighboring annotated protein partners. A total of 42 out of 219 presumably cancer-associated ORF proteins and 30 cancer-dependent binary PPIs were found. Additionally, a bibliometric analysis of 204 publications allowed us to retrieve biomedical terms related to ORF genes. In spite of recent progress in functional studies of ORF genes, the current investigations aim at finding out the prognostic value of CxORFx expression patterns in cancers. The results obtained expand the understanding of the possible functions of the poorly annotated CxORFx in the cancer context.

Zinc-mediated interaction of copper chaperones through their heavy-metal associated domains

BACKGROUND

A copper chaperone CCS is a multi-domain protein that supplies a copper ion to Cu/Zn-superoxide dismutase (SOD1). Among the domains of CCS, the N-terminal domain (CCS^dI) belongs to a heavy metal-associated (HMA) domain, in which a Cys-x-x-Cys (CxxC) motif binds a heavy metal ion. It has hence been expected that the HMA domain in CCS has a role in the metal trafficking; however, the CxxC motif in the domain is dispensable for supplying a copper ion to SOD1, leaving an open question on roles of CCS^dI in CCS.

METHODS

To evaluate protein-protein interactions of CCS through CCS^dI, yeast two-hybrid assay, a pull-down assay using recombinant proteins, and the analysis with fluorescence resonance energy transfer were performed.

RESULTS

We found that CCS specifically interacted with another copper chaperone HAH1, a HMA domain protein, through CCS^dI. The interaction between CCS^dI and HAH1 was not involved in the copper supply from CCS to SOD1 but was mediated by a zinc ion ligated with Cys residues of the CxxC motifs in CCS^dI and HAH1.

CONCLUSION

While physiological significance of the interaction between copper chaperones awaits further investigation, we propose that CCS^dI would have a role in the metal-mediated interaction with other proteins including heterologous copper chaperones.

Genome-wide identification and transcriptome analysis of the heavy metal-associated (HMA) gene family in Tartary buckwheat and their regulatory roles under cadmium stress

Heavy metal-associated (HMA) genes are those related to heavy metal transport and detoxification in plants. HMA genes have not been reported in Tartary buckwheat so far. In this study, we accessed the HMA genes of Tartary buckwheat by genome-wide identification for the first time. A total of 56 HMA genes were identified, including 36 ATX1 (antioxidant protein1) genes, 13 HIPP (heavy metal-associated isoprenylated plant protein) genes, and 7 P_1B-ATPase (P_1B-type adenosine triphosphatase) genes. These gene structures, motif compositions, chromosomal distribution, phylogenetic relationship, duplication events, interaction networks, cis-acting elements, and transcriptional expression under cadmium (Cd) stress were investigated. Among them, genes in HIPP and ATX1 subfamilies were more closely related. The 56 HMA genes were involved in the regulation of metal ion transport and homeostasis by binding metal ions, likely triggered by signals transducted by plant hormones. Fifteen of these HMA genes played regulatory roles under Cd stress. FtP1bA1 was identified to be a core gene involved in the defense regulation of Cd stress. Our results provide not only the first overview and characteristics of HMA genes in the whole genome of Tartary buckwheat but also a valuable reference for the functional analysis of HMA genes under Cd stress. Understanding changes in gene regulation induced by Cd stress lays the foundation for breeding resistant varieties.

New Proteins Contributing to Immune Cell Infiltration and Pannus Formation of Synovial Membrane from Arthritis Diseases

An inflamed synovial membrane plays a major role in joint destruction and is characterized by immune cells infiltration and fibroblast proliferation. This proteomic study considers the inflammatory process at the molecular level by analyzing synovial biopsies presenting a histological inflammatory continuum throughout different arthritis joint diseases. Knee synovial biopsies were obtained from osteoarthritis (OA; n = 9), chronic pyrophosphate arthropathy (CPPA; n = 7) or rheumatoid arthritis (RA; n = 8) patients. The histological inflammatory score was determined using a semi-quantitative scale based on synovial hyperplasia, lymphocytes, plasmocytes, neutrophils and macrophages infiltration. Proteomic analysis was performed by liquid chromatography-mass spectrometry (LC-MS/MS). Differentially expressed proteins were confirmed by immunohistochemistry. Out of the 1871 proteins identified and quantified by LC-MS/MS, 10 proteins (LAP3, MANF, LCP1, CTSZ, PTPRC, DNAJB11, EML4, SCARA5, EIF3K, C1orf123) were differentially expressed in the synovial membrane of at least one of the three disease groups (RA, OA and CPPA). Significant increased expression of the seven first proteins was detected in RA and correlated to the histological inflammatory score. Proteomics is therefore a powerful tool that provides a molecular pattern to the classical histology usually applied for synovitis characterization. Except for LCP1, CTSZ and PTPRC, all proteins have never been described in human synovitis.

TMT based deep proteome analysis of buffalo mammary epithelial cells and identification of novel protein signatures during lactogenic differentiation

The lactating mammary gland harbours numerous matured alveoli with their lumen surrounded by differentiated mammary epithelial cells (MECs), which are exclusively involved in milk synthesis and secretion. Buffalo (Bubalus bubalis) is the second major milk-producing animal, and its physiology is different from cattle. The complete protein machinery involved in MECs differentiation is still not defined in ruminants, in particular, buffalo. Therefore, we have studied the differential expression of regulated proteins in the in vitro grown buffalo MECs (BuMECs) at different time points (on 3, 6, 12, and 15 days) of their differentiation in the presence of lactogenic hormones. TMT-based MS analysis identified 4,934 proteins; of them, 681 were differentially expressed proteins (DEPs). The principal component analysis suggested a highly heterogeneous expression of DEPs at the four-time points of hormone treatment, with most of them (307) attained the highest expression on 12 days. Bioinformatics analysis revealed the association of DEPs with 24 KEGG pathways. We observed few new proteins, namely ABCA13, IVL, VPS37, CZIB, RFX7, Rab5, TTLL12, SMEK1, GDI2, and TMEM131 in BuMECs. The function of one of the highly upregulated proteins, namely involucrin in the differentiation of BuMECs was confirmed based on biochemical inhibition assay. The results further conclude that the proteins with higher abundance can be considered as the potential biomarkers for differentiation, and they may have a significant association with the lactation process in buffalo too. The proteome dataset obtained can be used to understand the species-specific variations among other lactating animals.

Proteomic Analyses of Acinetobacter baumannii Clinical Isolates to Identify Drug Resistant Mechanism

Acinetobacter baumannii is one of the main causes of nosocomial infections. Increasing numbers of multidrug-resistant Acinetobacter baumannii cases have been reported in recent years, but its antibiotic resistance mechanism remains unclear. We studied 9 multidrug-resistant (MDR) and 10 drug-susceptible Acinetobacter baumannii clinical isolates using Label free, TMT labeling approach and glycoproteomics analysis to identify proteins related to drug resistance. Our results showed that 164 proteins exhibited different expressions between MDR and drug-susceptible isolates. These differential proteins can be classified into six groups: a. proteins related to antibiotic resistance, b. membrane proteins, membrane transporters and proteins related to membrane formation, c. Stress response-related proteins, d. proteins related to gene expression and protein translation, e. metabolism-related proteins, f. proteins with unknown function or other functions containing biofilm formation and virulence. In addition, we verified seven proteins at the transcription level in eight clinical isolates by using quantitative RT-PCR. Results showed that four of the selected proteins have positive correlations with the protein level. This study provided an insight into the mechanism of antibiotic resistance of multidrug-resistant Acinetobacter baumannii.

Zincbindpredict-Prediction of Zinc Binding Sites in Proteins

Background: Zinc binding proteins make up a significant proportion of the proteomes of most organisms and, within those proteins, zinc performs rôles in catalysis and structure stabilisation. Identifying the ability to bind zinc in a novel protein can offer insights into its functions and the mechanism by which it carries out those functions. Computational means of doing so are faster than spectroscopic means, allowing for searching at much greater speeds and scales, and thereby guiding complimentary experimental approaches. Typically, computational models of zinc binding predict zinc binding for individual residues rather than as a single binding site, and typically do not distinguish between different classes of binding site—missing crucial properties indicative of zinc binding. Methods: Previously, we created ZincBindDB, a continuously updated database of known zinc binding sites, categorised by family (the set of liganding residues). Here, we use this dataset to create ZincBindPredict, a set of machine learning methods to predict the most common zinc binding site families for both structure and sequence. Results: The models all achieve an MCC ≥ 0.88, recall ≥ 0.93 and precision ≥ 0.91 for the structural models (mean MCC = 0.97), while the sequence models have MCC ≥ 0.64, recall ≥ 0.80 and precision ≥ 0.83 (mean MCC = 0.87), with the models for binding sites containing four liganding residues performing much better than this. Conclusions: The predictors outperform competing zinc binding site predictors and are available online via a web interface and a GraphQL API.

Evolutionary compaction and adaptation visualized by the structure of the dormant microsporidian ribosome

Microsporidia are eukaryotic parasites that infect essentially all animal species, including many of agricultural importance^1-3, and are significant opportunistic parasites of humans⁴. They are characterized by having a specialized infection apparatus, an obligate intracellular lifestyle⁵, rudimentary mitochondria and the smallest known eukaryotic genomes^5-7. Extreme genome compaction led to minimal gene sizes affecting even conserved ancient complexes such as the ribosome^8-10. In the present study, the cryo-electron microscopy structure of the ribosome from the microsporidium Vairimorpha necatrix is presented, which illustrates how genome compaction has resulted in the smallest known eukaryotic cytoplasmic ribosome. Selection pressure led to the loss of two ribosomal proteins and removal of essentially all eukaryote-specific ribosomal RNA (rRNA) expansion segments, reducing the rRNA to a functionally conserved core. The structure highlights how one microsporidia-specific and several repurposed existing ribosomal proteins compensate for the extensive rRNA reduction. The microsporidian ribosome is kept in an inactive state by two previously uncharacterized dormancy factors that specifically target the functionally important E-site, P-site and polypeptide exit tunnel. The present study illustrates the distinct effects of evolutionary pressure on RNA and protein-coding genes, provides a mechanism for ribosome inhibition and can serve as a structural basis for the development of inhibitors against microsporidian parasites.