HNOXPred: a web tool for the prediction of gas-sensing H-NOX proteins from amino acid sequence.

SUMMARY: HNOXPred is a webserver for the prediction of gas-sensing heme-nitric oxide/oxygen (H-NOX) proteins from amino acid sequence. H-NOX proteins are gas-sensing hemoproteins found in diverse organisms ranging from bacteria to eukaryotes. Recently, gas-sensing complex multi-functional proteins containing only the conserved amino acids at the heme centers of H-NOX proteins, have been identified through a motif-based approach. Based on experimental data and H-NOX candidates reported in the literature, HNOXPred is created to automate and facilitate the identification of similar H-NOX centers across systems. The server features HNOXSCORES scaled from 0 to 1 that consider in its calculation, the physicochemical properties of amino acids constituting the heme center in H-NOX in addition to the conserved amino acids within the center. From user input amino acid sequence, the server returns positive hits and their calculated HNOXSCORES ordered from high to low confidence which are accompanied by interpretation guides and recommendations. The utility of this server is demonstrated using the human proteome as an example. AVAILABILITY AND IMPLEMENTATION: The HNOXPred server is available at https://www.hnoxpred.com. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Amino acid motifs for the identification of novel protein interactants.

Biological systems consist of multiple components of different physical and chemical properties that require complex and dynamic regulatory loops to function efficiently. The discovery of ever more novel interacting sites in complex proteins suggests that we are only beginning to understand how cellular and biological functions are integrated and tuned at the molecular and systems levels. Here we review recently discovered interacting sites which have been identified through rationally designed amino acid motifs diagnostic for specific molecular functions, including enzymatic activities and ligand-binding properties. We specifically discuss the nature of the latter using as examples, novel hormone recognition and gas sensing sites that occur in moonlighting protein complexes. Drawing evidence from the current literature, we discuss the potential implications at the cellular, tissue, and/or organismal levels of such non-catalytic interacting sites and provide several promising avenues for the expansion of amino acid motif searches to discover hitherto unknown protein interactants and interaction networks. We believe this knowledge will unearth unexpected functions in both new and well-characterized proteins, thus filling existing conceptual gaps or opening new avenues for applications either as drug targets or tools in pharmacology, cell biology and bio-catalysis. Beyond this, motif searches may also support the design of novel, effective and sustainable approaches to crop improvements and the development of new therapeutics.

Plant adenylate cyclases have come full circle.

In bacteria, fungi and animals, 3'-5'-cyclic adenosine monophosphate (cAMP) and adenylate cyclases (ACs), enzymes that catalyse the formation of 3',5'-cAMP from ATP, are recognized as key signalling components. In contrast, the presence of cAMP and its biological roles in higher plants have long been a matter of controversy due to the generally lower amounts in plant tissues compared with that in animal and bacterial cells, and a lack of clarity on the molecular nature of the generating and degrading enzymes, as well as downstream effectors. While treatment with 3',5'-cAMP elicited many plant responses, ACs were, however, somewhat elusive. This changed when systematic searches with amino acid motifs deduced from the conserved catalytic centres of annotated ACs from animals and bacteria identified candidate proteins in higher plants that were subsequently shown to have AC activities in vitro and in vivo. The identification of active ACs moonlighting within complex multifunctional proteins is consistent with their roles as molecular tuners and regulators of cellular and physiological functions. Furthermore, the increasing number of ACs identified as part of proteins with different domain architectures suggests that there are many more hidden ACs in plant proteomes and they may affect a multitude of mechanisms and processes at the molecular and systems levels.

Twin cyclic mononucleotide cyclase and phosphodiesterase domain architecture as a common feature in complex plant proteins.

The majority of proteins in both prokaryote and eukaryote proteomes consist of two or more functional centers, which allows for intramolecular tuning of protein functions. Such architecture, as opposed to animal orthologs, applies to the plant cyclases (CNC) and phosphodiesterases (PDEs), the vast majority of which are part of larger multifunctional proteins. In plants, until recently, only two cases of combinations of CNC-PDE in one protein were reported. Here we propose that in plants, multifunctional proteins in which the PDE motif has been identified, the presence of the additional CNC center is common. Searching the Arabidopsis thaliana proteome with a combined PDE-CNC motif allowed the creation of a database of proteins with both activities. One such example is methylenetetrahydrofolate dehydrogenase, in which we determined the activities of adenylate cyclase (AC) and PDE. Based on biochemical and mutagenesis analyses we assessed the impact of the AC and PDE catalytic centers on the dehydrogenase activity. This allowed us to propose additional regulatory mechanism that govern folate metabolism by cAMP. It is therefore conceivable that the combined CNC-PDE architecture is a common regulatory configuration, where control of the level of cyclic nucleotides (cNMP) influences other catalytic activities of the protein.

Designing Overlap Extension PCR Primers for Protein Mutagenesis: A Programmatic Approach.

Overlap extension PCR is one of the routinely used methods to generate mutagenic genes for the functional and structural study of proteins. However, it is time-consuming to design the overlapping mutagenic primers and gene primers by manual operation. In this chapter, we present a Python script that is able to search all the possible primer combinations according to the preset definitions and calculate the necessary parameters of each primer for the users, which could facilitate the primer design process. Up to 256 pairs of primers can be provided for selection using this script.

ProbResist: a database for drug-resistant probiotic bacteria.

Drug resistance remains a global threat, and the rising trend of consuming probiotic-containing foods, many of which harbor antibiotic resistant determinants, has raised serious health concerns. Currently, the lack of accessibility to location-, drug- and species-specific information of drug-resistant probiotics has hampered efforts to combat the global spread of drug resistance. Here, we describe the development of ProbResist, which is a manually curated online database that catalogs reports of probiotic bacteria that have been experimentally proven to be resistant to antibiotics. ProbResist allows users to search for information of drug resistance in probiotics by querying with the names of the bacteria, antibiotic or location. Retrieved results are presented in a downloadable table format containing the names of the antibiotic, probiotic species, resistant determinants, region where the study was conducted and digital article identifiers (PubMed Identifier and Digital Object Identifier) hyperlinked to the original sources. The webserver also presents a simple analysis of information stored in the database. Given the increasing reports of drug-resistant probiotics, an exclusive database is necessary to catalog them in one platform. It will enable medical practitioners and experts involved in policy making to access this information quickly and conveniently, thus contributing toward the broader goal of combating drug resistance. DATABASE URL: https://probresist.com.

A Python script to merge Sanger sequences.

Merging Sanger sequences is frequently needed during the gene cloning process. In this study, we provide a Python script that is able to assemble multiple overlapping Sanger sequences. The script utilizes the overlapping regions within the tandem Sanger sequences to merge the Sanger sequences. The results demonstrate that the script can produce the merged sequence from the input Sanger sequences in a single run. The script offers a simple and free method for merging Sanger sequences and is useful for gene cloning.

A python script to design site-directed mutagenesis primers.

Primer design is essential to conduct whole plasmid site-directed mutagenesis for protein study. Traditionally, primers of mutagenesis are designed manually that is time-consuming and fallible. Here, we present a Python script for searching primers by presetting parameters of nucleotide composition and percentage of guanine-cytosine (GC content). The running results showed that the script is able to search primers with mutations of target residue automatically. This script may facilitate primer design for whole plasmid site-directed mutagenesis and aid protein mutant construction.

Comparative proteomic analysis of the sweetpotato provides insights into response mechanisms to Fusarium oxysporum f. sp. batatas.

The Fusarium wilt disease caused by Fusarium oxysporum f. sp. batatas (Fob) is one of the devastating diseases of sweetpotato. However, the molecular mechanisms of sweetpotato response to Fob is poorly understood. In the present study, comparative quantitative proteomic analysis was conducted to investigate the defense mechanisms involved. Two sweetpotato cultivars with differential Fob infection responses were inoculated with Fob spore suspensions and quantitatively analyzed by Tandem Mass Tags (TMT). 2267 proteins were identified and 1897 of them were quantified. There were 817 proteins with quantitative ratios of 1.2-fold change between Fob-inoculated and mock-treated samples. Further, nine differentially expressed proteins were validated by Parallel Reaction Monitoring (PRM). According to Gene Ontology (GO) annotation information, the proteins functioned in molecular metabolism, cellular component formation, and biological processes. Interestingly, the results showed that sweetpotato resistant response to Fob infection included many proteins associated with signaling transduction, plant resistance, chitinase and subtilisin-like protease. The functions and possible roles of those proteins were discussed. The results provides first insight into molecular mechanisms involved in sweetpotato defense responses to Fob.