570 Biowissenschaften; Biologie
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Physically interacting proteins form macromolecule complexes that drive diverse cellular processes. Advances in experimental techniques that capture interactions between proteins provide us with protein-protein interaction (PPI) networks from several model organisms. These datasets have enabled the prediction and other computational analyses of protein complexes. Here we provide a systematic review of the state-of-the-art algorithms for protein complex prediction from PPI networks proposed in the past two decades. The existing approaches that solve this problem are categorized into three groups, including: cluster-quality-based, node affinity-based, and network embedding-based approaches, and we compare and contrast the advantages and disadvantages. We further include a comparative analysis by computing the performance of eighteen methods based on twelve well-established performance measures on four widely used benchmark protein-protein interaction networks. Finally, the limitations and drawbacks of both, current data and approaches, along with the potential solutions in this field are discussed, with emphasis on the points that pave the way for future research efforts in this field. (c) 2022 The Author(s). Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology. This is an open access article under the CC BY license (http://creativecommons. org/licenses/by/4.0/).
Starch is a complex carbohydrate polymer produced by plants and especially by crops in huge amounts. It consists of amylose and amylopectin, which have alpha-1,4-and alpha-1,6-linked glucose units. Despite this simple chemistry, the entire starch metabolism is complex, containing various (iso)enzymes/proteins. However, whose interplay is still not yet fully understood. Starch is essential for humans and animals as a source of nutrition and energy. Nowadays, starch is also commonly used in non-food industrial sectors for a variety of purposes. However, native starches do not always satisfy the needs of a wide range of (industrial) applications. This review summarizes the structural properties of starch, analytical methods for starch characterization, and in planta starch modifications.
The biosynthesis of the molybdenum cofactor (Moco) is highly conserved among all kingdoms of life. In all molybdoenzymes containing Moco, the molybdenum atom is coordinated to a dithiolene group present in the pterin-based 6-alkyl side chain of molybdopterin (MPT). In general, the biosynthesis of Moco can be divided into four steps in in bacteria: (i) the starting point is the formation of the cyclic pyranopterin monophosphate (cPMP) from 5 '-GTP, (ii) in the second step the two sulfur atoms are inserted into cPMP leading to the formation of MPT, (iii) in the third step the molybdenum atom is inserted into MPT to form Moco and (iv) in the fourth step bis-Mo-MPT is formed and an additional modification of Moco is possible with the attachment of a nucleotide (CMP or GMP) to the phosphate group of MPT, forming the dinucleotide variants of Moco. This review presents an update on the well-characterized Moco biosynthesis in the model organism Escherichia coli including novel discoveries from the recent years.
Starch is one of the most popular nutritional sources for both human and animals. Due to the variation of its nutritional traits and biochemical specificities, starch has been classified into rapidly digestible, slowly digestible and resistant starch. Resistant starch has its own unique chemical structure, and various forms of resistant starch are commercially available. It has been found being a multiple-functional regulator for treating metabolic dysfunction. Different functions of resistant starch such as modulation of the gut microbiota, gut peptides, circulating growth factors, circulating inflammatory mediators have been characterized by animal studies and clinical trials. In this mini-review, recent remarkable progress in resistant starch on gut microbiota, particularly the effect of structure, biochemistry and cell signaling on nutrition has been summarized, with highlights on its regulatory effect on gut microbiota.
Macroecology and biogeography are concerned with understanding biodiversity patterns across space and time. In the past, the two disciplines have addressed this question mainly with correlative approaches, despite frequent calls for more mechanistic explanations. Recent advances in computational power, theoretical understanding, and statistical tools are, however, currently facilitating the development of more system-oriented, mechanistic models. We review these models, identify different model types and theoretical frameworks, compare their processes and properties, and summarize emergent findings. We show that ecological (physiology, demographics, dispersal, biotic interactions) and evolutionary processes, as well as environmental and human-induced drivers, are increasingly modelled mechanistically; and that new insights into biodiversity dynamics emerge from these models. Yet, substantial challenges still lie ahead for this young research field. Among these, we identify scaling, calibration, validation, and balancing complexity as pressing issues. Moreover, particular process combinations are still understudied, and so far models tend to be developed for specific applications. Future work should aim at developing more flexible and modular models that not only allow different ecological theories to be expressed and contrasted, but which are also built for tight integration with all macroecological data sources. Moving the field towards such a ‘systems macroecology’ will test and improve our understanding of the causal pathways through which eco-evolutionary processes create diversity patterns across spatial and temporal scales.
Modifications of transfer RNA (tRNA) have been shown to play critical roles in the biogenesis, metabolism, structural stability and function of RNA molecules, and the specific modifications of nucleobases with sulfur atoms in tRNA are present in pro- and eukaryotes. Here, especially the thiomodifications xm(5)s(2)U at the wobble position 34 in tRNAs for Lys, Gln and Glu, were suggested to have an important role during the translation process by ensuring accurate deciphering of the genetic code and by stabilization of the tRNA structure. The trafficking and delivery of sulfur nucleosides is a complex process carried out by sulfur relay systems involving numerous proteins, which not only deliver sulfur to the specific tRNAs but also to other sulfur-containing molecules including iron-sulfur clusters, thiamin, biotin, lipoic acid and molybdopterin (MPT). Among the biosynthesis of these sulfur-containing molecules, the biosynthesis of the molybdenum cofactor (Moco) and the synthesis of thio-modified tRNAs in particular show a surprising link by sharing protein components for sulfur mobilization in pro- and eukaryotes.
Aldehyde oxidases (AOXs) are molybdo-flavoenzymes characterized by broad substrate specificity, oxidizing aromatic/aliphatic aldehydes into the corresponding carboxylic acids and hydroxylating various heteroaromatic rings. Mammals are characterized by a complement of species specific AOX isoenzymes, that varies from one in humans (AOX1) to four in rodents (AOX1, AOX2, AOX3 and AOX4). The physiological function of mammalian AOX isoenzymes is unknown, although human AOX1 is an emerging enzyme in phase-I drug metabolism. Indeed, the number of therapeutic molecules under development which act as AOX substrates is increasing. The recent crystallization and structure determination of human AOX1 as well as mouse AOX3 has brought new insights into the mechanisms underlying substrate/inhibitor binding as well as the catalytic activity of this class of enzymes.
Diabetic nephropathy is one of the most frequent, devastating and costly complications of diabetes. The available therapeutic approaches are limited. Dipeptidyl peptidase type 4 (DPP-4) inhibitors represent a new class of glucose-lowering drugs that might also have reno-protective properties. DPP-4 exists in two forms: a plasma membranebound form and a soluble form, and can exert many biological actions mainly through its peptidase activity and interaction with extracellular matrix components. The kidneys have the highest DPP-4 expression level in mammalians. DPP-4 expression and urinary activity are up-regulated in diabetic nephropathy, highlighting its role as a potential target to manage diabetic nephropathy. Preclinical animal studies and some clinical data suggest that DPP-4 inhibitors decrease the progression of diabetic nephropathy in a blood pressure-and glucose-independent manner. Many studies reported that these reno-protective effects could be due to increased half-life of DPP-4 substrates such as glucagon-like peptide-1 (GLP-1) and stromal derived factor-1 alpha (SDF-1a). However, the underlying mechanisms are far from being completely understood and clearly need further investigations.
Second harmonic generation (SHG) is a nonlinear optical process that inherently generates signal in non-centrosymmetric materials, such as starch granules, and therefore can be used for label-free imaging. Both intensity and polarization of SHG are determined by material properties that are characterized by the nonlinear susceptibility tensor, ((2)). Examination of the tensor is performed for each focal volume of the image by measuring the outgoing polarization state of the SHG signal for a set of incoming laser beam polarizations. Mapping of nonlinear properties expressed as the susceptibility ratio reveals structural features including the organization of crystalline material within a single starch granule, and the distribution of structural properties in a population of granules. Isolated granules, as well as in situ starch, can be analyzed using polarimetric SHG microscopy. Due to the fast sample preparation and short imaging times, polarimetric SHG microscopy allows for a quick assessment of starch structure and permits rapid feedback for bioengineering applications. This article presents the basics of SHG theory and microscopy applications for starch-containing materials. Quantification of ultrastructural features within individual starch granules is described. New results obtained by polarization resolved SHG microscopy of starch granules are presented for various maize genotypes revealing heterogeneity within a single starch particle and between various granules.
Single molecule RNA fluorescent in situ hybridization (smFISH) enables gene transcription to be assessed at the cellular level. In this point of view article, we describe our recent smFISH research in the model plant Arabidopsis thaliana and discuss how this technique could further knowledge of plant gene transcription in the future.