Structural Basis for Silicic Acid Uptake by Higher Plants

Many of the world's most important food crops such as rice, barley and maize accumulate silicon (Si) to high levels, resulting in better plant growth and crop yields. The first step in Si accumulation is the uptake of silicic acid by the roots, a process mediated by the structurally uncharacterised NIP subfamily of aquaporins, also named metalloid porins. Here, we present the X-ray crystal structure of the archetypal NIP family member from Oryza sativa (OsNIP2;1). The OsNIP2;1 channel is closed in the crystal structure by the cytoplasmic loop D, which is known to regulate channel opening in classical plant aquaporins. The structure further reveals a novel, five-residue extracellular selectivity filter with a large diameter. Unbiased molecular dynamics simulations show a rapid opening of the channel and visualise how silicic acid interacts with the selectivity filter prior to transmembrane diffusion. Our results will enable detailed structure–function studies of metalloid porins, including the basis of their substrate selectivity.     

MV-mimicking micelles loaded with PEG-serine-ACP nanoparticles to achieve biomimetic intra/extra fibrillar mineralization of collagen in vitro

Since their discovery, matrix vesicles (MVs) containing minerals have received considerable attention for their role in the mineralization of bone, dentin and calcified cartilage. Additionally, MVs' association with collagen fibrils, which serve as the scaffold for calcification in the organic matrix, has been repeatedly highlighted. The primary purpose of the present study was to establish a MVs–mimicking model (PEG-S-ACP/micelle) in vitro for studying the exact mechanism of MVs-mediated extra/intra fibrillar mineralization of collagen in vivo. In this study, high-concentration serine was used to stabilize the amorphous calcium phosphate (S-ACP), which was subsequently mixed with polyethylene glycol (PEG) to form PEG-S-ACP nanoparticles. The nanoparticles were loaded in the polysorbate 80 micelle through a micelle self-assembly process in an aqueous environment. This MVs–mimicking model is referred to as the PEG-S-ACP/micelle model. By adjusting the pH and surface tension of the PEG-S-ACP/micelle, two forms of minerals (crystalline mineral nodules and ACP nanoparticles) were released to achieve the extrafibrillar and intrafibrillar mineralization, respectively. This in vitro mineralization process reproduced the mineral nodules mediating in vivo extrafibrillar mineralization and provided key insights into a possible mechanism of biomineralization by which in vivo intrafibrillar mineralization could be induced by ACP nanoparticles released from MVs. Also, the PEG-S-ACP/micelle model provides a promising methodology to prepare mineralized collagen scaffolds for repairing bone defects in bone tissue engineering.     

N-Terminal sequencing by mass spectrometry through specific fluorescamine labeling of α-amino groups before tryptic digestion

We present a single-step procedure for the specific mass labeling of unblocked protein N termini. We show that the dye fluorescamine, which is commonly assumed to require mildly alkaline conditions for undergoing a nonspecific reaction with α- and ε-amino groups associated with amino acids, in fact shows a specific reaction only with α-amino groups present at protein N termini when mildly acidic conditions are used. We use this finding to label, identify, and sequence the trypsinolysis-derived N-terminal peptide of lysozyme, using only mass spectrometry, to illustrate how this method could be used with other proteins.     

A Cross-linking Mass Spectrometry Approach Defines Protein Interactions in Yeast Mitochondria

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Highlights

• •XL-MS reveals new PPIs in yeast mitochondria under glycerol and glucose condition.
• •Significant but limited results from quantitative XL-MS experiments.
• •Ndi1 participates in a CIII₂CIV₂ respiratory supercomplex.
• •Min8 promotes assembly of Cox12 into an intermediate complex IV.

     

The influence of alkyl pyridinium sponge toxins on membrane properties, cytotoxicity, transfection and protein expression in mammalian cells

The ability of two alkyl pyridinium sponge toxin preparations (poly-APS and halitoxin) to form transient pores/lesions in cell membranes and allow transfection of plasmid cDNA have been investigated using HEK 293 cells. Poly-APS and halitoxin preparations caused a collapse in membrane potential, reductions in input resistance and increased Ca²⁺ permeability. At least partial recovery was observed after poly-APS application but recovery was more rarely seen with halitoxin. The transfection with plasmid cDNAs for an enhanced green fluorescent protein (EGFP) and human tumour necrosis factor receptor 2 (TNFR2) was assessed for both toxin preparations and compared with lipofectamine. Stable transfection was achieved with poly-APS although it was less efficient than lipofectamine. These results show that viable cells transfected with alien cDNA can be obtained using novel transient pore-forming alkyl pyridinium sponge toxins and a simple pre-incubation protocol. This provides the first proof of principle that pore-forming alkyl pyridinium compounds can be used to deliver cDNA to the intracellular environment without permanently compromising the plasma membrane.     

Structure-wise discrimination of adenine and guanine by proteins on the basis of their nonbonded interactions

We have analyzed the nonbonded interactions of the structurally similar moieties, adenine and guanine forming complexes with proteins. The results comprise (a) the amino acid–ligand atom preferences, (b) solvent accessibility of ligand atoms before and after complex formation with proteins, and (c) preferred amino acid residue atoms involved in the interactions. We have observed that the amino acid preferences involved in the hydrogen bonding interactions vary for adenine and guanine. The structural variation between the purine atoms is clearly reflected by their burial tendency in the solvent environment. Correlation of the mean amino acid preference values show the variation that exists between adenine and guanine preferences of all the amino acid residues. All our observations provide evidence for the discriminating nature of the proteins in recognizing adenine and guanine.     

Multiomic Metabolic Enrichment Network Analysis Reveals Metabolite–Protein Physical Interaction Subnetworks Altered in Cancer

Metabolism is recognized as an important driver of cancer progression and other complex diseases, but global metabolite profiling remains a challenge. Protein expression profiling is often a poor proxy since existing pathway enrichment models provide an incomplete mapping between the proteome and metabolism. To overcome these gaps, we introduce multiomic metabolic enrichment network analysis (MOMENTA), an integrative multiomic data analysis framework for more accurately deducing metabolic pathway changes from proteomics data alone in a gene set analysis context by leveraging protein interaction networks to extend annotated metabolic models. We apply MOMENTA to proteomic data from diverse cancer cell lines and human tumors to demonstrate its utility at revealing variation in metabolic pathway activity across cancer types, which we verify using independent metabolomics measurements. The novel metabolic networks we uncover in breast cancer and other tumors are linked to clinical outcomes, underscoring the pathophysiological relevance of the findings.     

Structure-based protein design with deep learning

Since the first revelation of proteins functioning as macromolecular machines through their three dimensional structures, researchers have been intrigued by the marvelous ways the biochemical processes are carried out by proteins. The aspiration to understand protein structures has fueled extensive efforts across different scientific disciplines. In recent years, it has been demonstrated that proteins with new functionality or shapes can be designed via structure-based modeling methods, and the design strategies have combined all available information — but largely piece-by-piece — from sequence derived statistics to the detailed atomic-level modeling of chemical interactions. Despite the significant progress, incorporating data-derived approaches through the use of deep learning methods can be a game changer. In this review, we summarize current progress, compare the arc of developing the deep learning approaches with the conventional methods, and describe the motivation and concepts behind current strategies that may lead to potential future opportunities.     

A comparative Proteomics Analysis Identified Differentially Expressed Proteins in Pancreatic Cancer–Associated Stellate Cell Small Extracellular Vesicles

Human pancreatic stellate cells (HPSCs) are an essential stromal component and mediators of pancreatic ductal adenocarcinoma (PDAC) progression. Small extracellular vesicles (sEVs) are membrane-enclosed nanoparticles involved in cell-to-cell communications and are released from stromal cells within PDAC. A detailed comparison of sEVs from normal pancreatic stellate cells (HPaStec) and from PDAC-associated stellate cells (HPSCs) remains a gap in our current knowledge regarding stellate cells and PDAC. We hypothesized there would be differences in sEVs secretion and protein expression that might contribute to PDAC biology. To test this hypothesis, we isolated sEVs using ultracentrifugation followed by characterization by electron microscopy and Nanoparticle Tracking Analysis. We report here our initial observations. First, HPSC cells derived from PDAC tumors secrete a higher volume of sEVs when compared to normal pancreatic stellate cells (HPaStec). Although our data revealed that both normal and tumor-derived sEVs demonstrated no significant biological effect on cancer cells, we observed efficient uptake of sEVs by both normal and cancer epithelial cells. Additionally, intact membrane-associated proteins on sEVs were essential for efficient uptake. We then compared sEV proteins isolated from HPSCs and HPaStecs cells using liquid chromatography–tandem mass spectrometry. Most of the 1481 protein groups identified were shared with the exosome database, ExoCarta. Eighty-seven protein groups were differentially expressed (selected by 2-fold difference and adjusted p value ≤0.05) between HPSC and HPaStec sEVs. Of note, HPSC sEVs contained dramatically more CSE1L (chromosome segregation 1–like protein), a described marker of poor prognosis in patients with pancreatic cancer. Based on our results, we have demonstrated unique populations of sEVs originating from stromal cells with PDAC and suggest that these are significant to cancer biology. Further studies should be undertaken to gain a deeper understanding that could drive novel therapy.     

Role of actin in the cAMP-dependent activation of sodium/glucose cotransporter in renal epithelial cells

We examined whether actin filaments are involved in the cAMP-dependent activation of a high affinity sodium/glucose cotransporter (SGLT1) using epithelial expression systems. The expression of enhanced green fluorescent protein-tagged SGLT1 (EGFP-SGLT1) in Madin-Darby canine kidney (MDCK) cells was revealed by Western blotting and confocal laser microscopy. 8-Br-cAMP, a membrane permeable cAMP analog, enhanced [¹⁴C]-α-methyl glucopyranoside ([¹⁴C]-AMG) uptake. Both basal and 8-Br-cAMP-elicited [¹⁴C]-AMG uptakes were inhibited by N-(2{[3-(4-bromophenyl)-2-propenyl]-amino}-ethyl)-5-isoquinolinesulfonamide (H-89), a protein kinase A inhibitor, and cytochalasin D, an actin filament formation inhibitor. Furthermore, cytochalasin D inhibited the distribution of EGFP-SGLT1 at the apical surface. These results suggest that the EGFP-SGLT1 protein is functionally expressed in the apical membrane of MDCK cells, and is up-regulated by a cAMP-dependent pathway requiring intact actin filaments.