High-performance signal peptide prediction based on sequence alignment techniques

Characterizing heterologous protein burden in Komagataella phaffii

Yeast is a widely utilized chassis for heterologous protein production, with Komagataella phaffii well-established as a prominent nonconventional yeast in this field. Despite its widespread recognition, there remains considerable potential to further optimize these cell factories to meet high production demands in a cost-effective and sustainable manner. Understanding the cellular response to the challenges of heterologous protein production can equip genetic engineers with crucial knowledge to develop enhanced strategies for constructing more efficient cell factories. In this study, we explore the molecular response of various K. phaffii strains that produce either the human insulin precursor or Mambalgin-1, examining changes in transcription and changes in intra- and extracellular protein levels. Our findings provide valuable insights into the molecular mechanisms that regulate the behaviour of K. phaffii production strains under the stress of producing different heterologous proteins. We believe that these results will serve as a foundation for identifying new genetic targets to improve strain robustness and productivity. In conclusion, we present new cellular and molecular insights into the response of K. phaffii cell factories to the challenges of burdensome heterologous protein production and our findings point to different engineering strategies for improved cell factory performance.

Computational identification of monkeypox virus epitopes to generate a novel vaccine antigen against Mpox

Monkeypox virus (MPXV) belonging to poxviridae family causes chronic viral disease in various mammals including human and monkeys. Conventional vaccines developed against smallpox of poxviridae, are not specific against Mpox. Also, they can cause various side effects after vaccination. In this study, we aimed to analyze the A17L, A28L, A37R, A43R, E8L, H3L, B6R, and M1R structural proteins of MPXV and identify epitopes in them which can be used to generate vaccine antigens. Among the proteins analyzed, the M1R protein was predicted to be more appropriate for use in vaccine research due to its high antigenicity value and other physicochemical features. Also, A17L, B6R and E8L had high antigenicity values. E8L protein was more conserved while the A37R, A43R, and B6R proteins had signal peptides. Although a total of eight B cell epitopes were predicted in all proteins analyzed, CNGETK epitope belonging to B6R protein had the highest antigenicity value (1.7083), as well as was non-allergenic, non-toxic, and soluble. Based on T cell epitope analyses performed on all proteins, fourteen MHC-I/II epitopes were predicted that are antigenic, non-allergenic and non-toxic, as well as soluble. Among them, MHC-I related-HEIYDRNVGF epitope in A28L protein had the highest antigenicity value (1.6650) and MHC-II related-IGNIKIVQIDIRDIK epitope in A37R protein had the highest antigenicity value (2.0280). In conclusion, eight structural proteins of MPXV were successfully analyzed and 22 important epitopes were identified that could serve as vaccine antigens or in serological studies to develop diagnostic tools.

Development of innovative multi-epitope mRNA vaccine against central nervous system tuberculosis using in silico approaches

Tuberculosis(TB) of the Central nervous system (CNS) is a rare and highly destructive disease. The emergence of drug resistance has increased treatment difficulty, leaving the Bacillus Calmette-Guérin (BCG) vaccine as the only licensed preventative immunization available. This study focused on identifying the epitopes of PknD (Rv0931c) and Rv0986 from Mycobacterium tuberculosis(Mtb) strain H37Rv using an in silico method. The goal was to develop a therapeutic mRNA vaccine for preventing CNS TB. The vaccine was designed to be non-allergenic, non-toxic, and highly antigenic. Codon optimization was performed to ensure effective translation in the human host. Additionally, the secondary and tertiary structures of the vaccine were predicted, and molecular docking with TLR-4 was carried out. A molecular dynamics simulation confirmed the stability of the complex. The results indicate that the vaccine structure shows effectiveness. Overall, the constructed vaccine exhibits ideal physicochemical properties, immune response, and stability, laying a theoretical foundation for future laboratory experiments.

In silico discovery of diagnostic/vaccine candidate antigenic epitopes and a multi-epitope peptide vaccine (NaeVac) design for the brain-eating amoeba Naegleria fowleri causing human meningitis

Naegleria fowleri, the brain-eating amoeba, is a free-living amoeboflagellate with three different life cycles (trophozoite, flagellated, and cyst) that lives in a variety of habitats around the world including warm freshwater and soil. It causes a disease called naegleriasis leading meningitis and primary amoebic meningoencephalitis (PAM) in humans. N. fowleri is transmitted through contaminated water sources such as insufficiently chlorinated swimming pool water or contaminated tap water, and swimmers are at risk. N. fowleri is found all over the world, and most infections were reported in both developed and developing countries with high mortality rates and serious clinical findings. Until now, there is no FDA approved vaccine and early diagnosis is urgent against this pathogen. In this study, by analyzing the N. fowleri vaccine candidate proteins (Mp2CL5, Nfa1, Nf314, proNP-A and proNP-B), it was aimed to discover diagnostic/vaccine candidate epitopes and to design a multi-epitope peptide vaccine against this pathogen. After the in silico evaluation, three prominent diagnostic/vaccine candidate epitopes (EAKDSK, LLPHIRILVY, and FYAKLLPHIRILVYS) with the highest antigenicities were discovered and a potentially highly immunogenic/antigenic multi-epitope peptide vaccine (NaeVac) was designed against the brain-eating amoeba N. fowleri causing human meningitis.

Molecular characterization of Anaplasma ovis Msp4 protein in strains isolated from ticks in Turkey: A multi-epitope synthetic vaccine antigen design against Anaplasma ovis using immunoinformatic tools

Tick-borne pathogens increasingly threaten animal and human health as well as cause great economic loss in the livestock industry. Among these pathogens, Anaplasma ovis causing a decrease in meat and milk yield is frequently detected in sheep in many countries including Turkey. This study aimed to reveal potential vaccine candidate epitopes in Msp4 protein using sequence data from Anaplasma ovis isolates and then to design a multi-epitope protein to be used in vaccine formulations against Anaplasma ovis. For this purpose, Msp4 gene was sequenced from Anaplasma ovis isolates (n:6) detected in ticks collected from sheep in Turkey and the sequence data was compared with previous sequences from different countries in order to detect the variations of Msp4 gene/protein. Potential vaccine candidate and diagnostic epitopes were predicted using various immunoinformatics tools. Among the discovered vaccine candidate epitopes, antigenic and conserved were selected, and then a multi-epitope protein was designed. The designed vaccine protein was tested for the assessment of TLR-2, IgG, and IFN-g responses by molecular docking and immune simulation analyses. Among the discovered epitopes, EVASEGSGVM and YQFTPEISLV epitopes with properties of high antigenicity, non-allergenicity, and non-toxicity were proposed to be used for Anaplasma ovis in further serodiagnostic and vaccine studies.

Unbiased organism-agnostic and highly sensitive signal peptide predictor with deep protein language model

Signal peptides (SPs) are essential to target and transfer transmembrane and secreted proteins to the correct positions. Many existing computational tools for predicting SPs disregard the extreme data imbalance problem and rely on additional group information of proteins. Here we introduce Unbiased Organism-agnostic Signal Peptide Network (USPNet), an SP classification and cleavage-site prediction deep learning method. Extensive experimental results show that USPNet substantially outperforms previous methods on classification performance by 10%. An SP-discovering pipeline with USPNet is designed to explore unprecedented SPs from metagenomic data. It reveals 347 SP candidates, with the lowest sequence identity between our candidates and the closest SP in the training dataset at only 13%. In addition, the template modeling scores between candidates and SPs in the training set are mostly above 0.8. The results showcase that USPNet has learnt the SP structure with raw amino acid sequences and the large protein language model, thereby enabling the discovery of unknown SPs.

Protein Sorting Prediction

Many computational methods are available for predicting protein sorting in bacteria. When comparing them, it is important to know that they can be grouped into three fundamentally different approaches: signal-based, global property-based, and homology-based prediction. In this chapter, the strengths and drawbacks of each of these approaches are described through many examples of methods that predict secretion, integration into membranes, or subcellular locations in general. The aim of this chapter is to provide a user-level introduction to the field with a minimum of computational theory.

In silico discovery of epitopes of gag and env proteins for the development of a multi-epitope vaccine candidate against Maedi Visna Virus using reverse vaccinology approach

Maedi Visna Virus (MVV) causes a chronic viral disease in sheep. Since there is no specific therapeutic drug that targets MVV, development of a vaccine against the MVV is inevitable. This study aimed to analyze the gag and env proteins as vaccine candidate proteins and to identify epitopes in these proteins. In addition, it was aimed to construct a multi-epitope vaccine candidate. According to the obtained results, the gag protein was detected to be more conserved and had a higher antigenicity value. Also, the number of alpha helix in the secondary structure was higher and transmembrane helices were not detected. Although many B cell and MHC-I/II epitopes were predicted, only 19 of them were detected to have the properties of antigenic, non-allergenic, non-toxic, soluble, and non-hemolytic. Of these epitopes, five were remarkable due to having the highest antigenicity value. However, the final multi-epitope vaccine was constructed with 19 epitopes. A strong affinity was shown between the final multi-epitope vaccine and TLR-2/4. In conclusion, the gag protein was a better antigen. However, both proteins had epitopes with high antigenicity value. Also, the final multi-epitope vaccine construct had a potential to be used as a peptide vaccine due to its immuno-informatics results.

Production of recombinant lytic polysaccharide monooxygenases and evaluation effect of its addition into Aspergillus fumigatus var. niveus cocktail for sugarcane bagasse saccharification

Lignocellulosic biomass is a promising alternative for producing biofuels, despite its recalcitrant nature. There are microorganisms in nature capable of efficiently degrade biomass, such as the filamentous fungi. Among them, Aspergillus fumigatus var. niveus (AFUMN) has a wide variety of carbohydrate-active enzymes (CAZymes), especially hydrolases, but a low number of oxidative enzymes in its genome. To confirm the enzymatic profile of this fungus, this study analyzed the secretome of AFUMN cultured in sugarcane bagasse as the sole carbon source. As expected, the secretome showed a predominance of hydrolytic enzymes compared to oxidative activity. However, it is known that hydrolytic enzymes act in synergy with oxidative proteins to efficiently degrade cellulose polymer, such as the Lytic Polysaccharide Monooxygenases (LPMOs). Thus, three LPMOs from the fungus Thermothelomyces thermophilus (TtLPMO9D, TtLPMO9H, and TtLPMO9O) were selected, heterologous expressed in Aspergillus nidulans, purified, and used to supplement the AFUMN secretome to evaluate their effect on the saccharification of sugarcane bagasse. The saccharification assay was carried out using different concentrations of AFUMN secretome supplemented with recombinant T. thermophilus LPMOs, as well as ascorbic acid as reducing agent for oxidative enzymes. Through a statistic design created by Design-Expert software, we were able to analyze a possible cooperative effect between these components. The results indicated that, in general, the addition of TtLPMO9D and ascorbic acid did not favor the conversion process in this study, while TtLPMO9O had a highly significant cooperative effect in bagasse saccharification compared to the control using only AFUMN secretome.

TSignal: a transformer model for signal peptide prediction

MOTIVATION

Signal peptides (SPs) are short amino acid segments present at the N-terminus of newly synthesized proteins that facilitate protein translocation into the lumen of the endoplasmic reticulum, after which they are cleaved off. Specific regions of SPs influence the efficiency of protein translocation, and small changes in their primary structure can abolish protein secretion altogether. The lack of conserved motifs across SPs, sensitivity to mutations, and variability in the length of the peptides make SP prediction a challenging task that has been extensively pursued over the years.

RESULTS

We introduce TSignal, a deep transformer-based neural network architecture that utilizes BERT language models and dot-product attention techniques. TSignal predicts the presence of SPs and the cleavage site between the SP and the translocated mature protein. We use common benchmark datasets and show competitive accuracy in terms of SP presence prediction and state-of-the-art accuracy in terms of cleavage site prediction for most of the SP types and organism groups. We further illustrate that our fully data-driven trained model identifies useful biological information on heterogeneous test sequences.

AVAILABILITY AND IMPLEMENTATION

TSignal is available at: https://github.com/Dumitrescu-Alexandru/TSignal.

Peptides and protein hydrolysates exhibiting anti-inflammatory activity: sources, structural features and modulation mechanisms

Inflammation is the response of the immune system to harmful stimuli such as tissue injury, infection or toxic chemicals, which has the aim of eliminating irritants or pathogenic microorganisms and enhancing tissue repair. Uncontrolled long-lasting acute inflammation can gradually progress to chronic, causing a variety of chronic inflammatory diseases that are usually treated with anti-inflammatory drugs, but most of them are inadequate to control chronic responses and are also associated with adverse side effects. Thus, many efforts are being directed to develop alternative and more selective anti-inflammatory therapies from natural products. One main field of interest is the obtaining of bioactive peptides exhibiting anti-inflammatory activity from sustainable protein sources like edible insects or agroindustry and fishing by-products. This work highlighted the structure-activity relationship of anti-inflammatory peptides. Small peptides with molecular weight under 1 kDa and amino acid chain length between 2 to 20 residues are generally the most active because of the higher probability to be absorbed in the intestine and penetrate into cells when compared with the larger size peptides. The presence of hydrophobic (Val, Ile, Pro) and positively charged (His, Arg, Lys) amino acids is another common occurrence for anti-inflammatory peptides. Interestingly, a high percentage (77%) of these bioactive peptides can be found in alternative sustainable protein sources such as Tenebrio molitor or sunflower, apart from its original protein source. However, not all of these peptides with anti-inflammatory potential in vitro achieve good scores by the in silico bioactivity predictors studied. Therefore, it is essential to implement current bioinformatics tools, in order to complement in vitro experiments with prior prediction of potential bioactive peptides.

Discovery of a new genus of anaerobic ammonium oxidizing bacteria with a mechanism for oxygen tolerance

In the past 20 years, there has been a major stride in understanding the core mechanism of anaerobic ammonium-oxidizing (anammox) bacteria, but there are still several discussion points on their survival strategies. Here, we discovered a new genus of anammox bacteria in a full-scale wastewater-treating biofilm system, tentatively named "Candidatus Loosdrechtia aerotolerans". Next to genes of all core anammox metabolisms, it encoded and transcribed genes involved in the dissimilatory nitrate reduction to ammonium (DNRA), which coupled to oxidation of small organic acids, could be used to replenish ammonium and sustain their metabolism. Surprisingly, it uniquely harbored a new ferredoxin-dependent nitrate reductase, which has not yet been found in any other anammox genome and might confer a selective advantage to it in nitrate assimilation. Similar to many other microorganisms, superoxide dismutase and catalase related to oxidative stress resistance were encoded and transcribed by "Ca. Loosdrechtia aerotolerans". Interestingly, bilirubin oxidase (BOD), likely involved in oxygen resistance of anammox bacteria under fluctuating oxygen concentrations, was identified in "Ca. Loosdrechtia aerotolerans" and four Ca. Brocadia genomes, and its activity was demonstrated using purified heterologously expressed proteins. A following survey of oxygen-active proteins in anammox bacteria revealed the presence of other previously undetected oxygen defense systems. The novel cbb3-type cytochrome c oxidase and bifunctional catalase-peroxidase may confer a selective advantage to Ca. Kuenenia and Ca. Scalindua that face frequent changes in oxygen concentrations. The discovery of this new genus significantly broadens our understanding of the ecophysiology of anammox bacteria. Furthermore, the diverse oxygen tolerance strategies employed by distinct anammox bacteria advance our understanding of their niche adaptability and provide valuable insight for the operation of anammox-based wastewater treatment systems.

Pectin Modification in Seed Coat Mucilage by In Vivo Expression of Rhamnogalacturonan-I- and Homogalacturonan-Degrading Enzymes

The cell wall is essential for plant survival. Determining the relationship between cell wall structure and function using mutant analysis or overexpressing cell wall-modifying enzymes has been challenging due to the complexity of the cell wall and the appearance of secondary, compensatory effects when individual polymers are modified. In addition, viability of the plants can be severely impacted by wall modification. A useful model system for studying structure-function relationships among extracellular matrix components is the seed coat epidermal cells of Arabidopsis thaliana. These cells synthesize relatively simple, easily accessible, pectin-rich mucilage that is not essential for plant viability. In this study, we expressed enzymes predicted to modify polysaccharide components of mucilage in the apoplast of seed coat epidermal cells and explored their impacts on mucilage. The seed coat epidermal-specific promoter TESTA ABUNDANT2 (TBA2) was used to drive expression of these enzymes to avoid adverse effects in other parts of the plant. Mature transgenic seeds expressing Rhamnogalacturonate lyase A (RglA) or Rhamnogalacturonate lyase B (RglB) that degrade the pectin rhamnogalacturonan-I (RG-I), a major component of mucilage, had greatly reduced mucilage capsules surrounding the seeds and concomitant decreases in the monosaccharides that comprise the RG-I backbone. Degradation of the minor mucilage component homogalacturonan (HG) using the HG-degrading enzymes Pectin lyase A (PLA) or ARABIDOPSIS DEHISCENCE ZONE POLYGALACTURONASE2 (ADPG2) resulted in developing seed coat epidermal cells with disrupted cell-cell adhesion and signs of early cell death. These results demonstrate the feasibility of manipulating the seed coat epidermal cell extracellular matrix using a targeted genetic engineering approach.

Activities and metabolic versatility of distinct anammox bacteria in a full-scale wastewater treatment system

Anaerobic ammonium oxidation (anammox) is a key N₂-producing process in the global nitrogen cycle. Major progress in understanding the core mechanism of anammox bacteria has been made, but our knowledge of the survival strategies of anammox bacteria in complex ecosystems, such as full-scale wastewater treatment plants (WWTPs), remains limited. Here, by combining metagenomics with in situ metatranscriptomics, complex anammox-driven nitrogen cycles in an anoxic tank and a granular activated carbon (GAC) biofilm module of a full-scale WWTP treating landfill leachate were constructed. Four distinct anammox metagenome-assembled genomes (MAGs), representing a new genus named Ca. Loosdrechtii, a new species in Ca. Kuenenia, a new species in Ca. Brocadia, and a new strain in "Ca. Kuenenia stuttgartiensis", were simultaneously retrieved from the GAC biofilm. Metabolic reconstruction revealed that all anammox organisms highly expressed the core metabolic enzymes and showed a high metabolic versatility. Pathways for dissimilatory nitrate reduction to ammonium (DNRA) coupled to volatile fatty acids (VFAs) oxidation likely assist anammox bacteria to survive unfavorable conditions and facilitate switches between lifestyles in oxygen fluctuating environments. The new Ca. Kuenenia species dominated the anammox community of the GAC biofilm, specifically may be enhanced by the uniquely encoded flexible ammonium and iron acquisition strategies. The new Ca. Brocadia species likely has an extensive niche distribution that is simultaneously established in the anoxic tank and the GAC biofilm, the two distinct niches. The highly diverse and impressive metabolic versatility of anammox bacteria revealed in this study advance our understanding of the survival and application of anammox bacteria in the full-scale wastewater treatment system.

In Silico Investigation of Signal Peptide Sequences to Enhance Secretion of CD44 Nanobodies Expressed in Escherichia coli

BACKGROUND

The selection of a suitable signal peptide that can direct recombinant proteins from the cytoplasm to the extracellular space is an important criterion affecting the production of recombinant proteins in Escherichia coli, a widely used host. Nanobodies are currently attracting the attention of scientists as antibody alternatives due to their specific properties and feasibility of production in E. coli.

OBJECTIVE

CD44 nanobodies constitute a potent therapeutic agent that can block CD44/HA interaction in cancer and inflammatory diseases. This molecule may also function as a drug against cancer cells and has been produced previously in E. coli without a signal peptide sequence. The goal of this project was to find a suitable signal peptide to direct CD44 nanobody extracellular secretion in E. coli that will potentially lead to optimization of experimental methods and facilitate downstream steps such as purification.

METHODS

We analyzed 40 E. coli derived signal peptides retrieved from the Signal Peptide database and selected the best candidate signal peptides according to relevant criteria including signal peptide probability, stability, and physicochemical features, which were evaluated using signalP software version 4.1 and the ProtParam tool, respectively.

RESULTS

In this in silico study, suitable candidate signal peptide(s) for CD44 nanobody secretory expression were identified. CSGA, TRBC, YTFQ, NIKA, and DGAL were selected as appropriate signal peptides with acceptable D-scores, and appropriate physicochemical and structural properties. Following further analysis, TRBC was selected as the best signal peptide to direct CD44 nanobody expression to the extracellular space of E. coli.

CONCLUSION

The selected signal peptide, TRBC is the most suitable to promote high-level secretory production of CD44 nanobodies in E. coli and potentially will be useful for scaling up CD44 nanobody production in experimental research as well as in other CD44 nanobody applications. However, experimental work is needed to confirm the data.

Protein Secretion Prediction Tools and Extracellular Vesicles Databases

Secreted proteins play important roles in several biological processes such as growth, proliferation differentiation, cell-cell communication, migration, and apoptosis; moreover, these extracellular molecules mediate homeostasis by influencing the cross-talking within the surrounding tissues. Currently, the research area of cell secretome has become of great interest since the profiling of secreted proteins could be essential for the biomarker discovery and for the identification of new therapeutic strategies. Several bioinformatic platforms have been implemented for the in silico characterization of secreted proteins: this chapter describes a typical workflow for the analysis of proteins secreted by cultured cells through bioinformatic approaches. Central issue is related to discrimination between proteins secreted by classical and non-classical pathways. Therefore, specific prediction tools for the classification of candidate secreted proteins are here presented.

Computational prediction of secreted proteins in gram-negative bacteria

Gram-negative bacteria harness multiple protein secretion systems and secrete a large proportion of the proteome. Proteins can be exported to periplasmic space, integrated into membrane, transported into extracellular milieu, or translocated into cytoplasm of contacting cells. It is important for accurate, genome-wide annotation of the secreted proteins and their secretion pathways. In this review, we systematically classified the secreted proteins according to the types of secretion systems in Gram-negative bacteria, summarized the known features of these proteins, and reviewed the algorithms and tools for their prediction.

Bioinformatics analysis and biochemical characterisation of ABC transporter-associated periplasmic substrate-binding proteins ModA and MetQ from Helicobacter pylori strain SS1

The human gastric pathogen Helicobacter pylori relies on the uptake of host-provided nutrients for its proliferation and pathogenicity. ABC transporters that mediate import of small molecules into the cytoplasm of H. pylori employ their cognate periplasmic substrate-binding proteins (SBPs) for ligand capture in the periplasm. The genome of the mouse-adapted strain SS1 of H. pylori encodes eight ABC transporter-associated SBPs, but little is known about their specificity or structure. In this study, we demonstrated that the SBP annotated as ModA binds molybdate (MoO₄^2-, K_D = 3.8 nM) and tungstate (WO₄^2-, K_D = 7.8 nM). In addition, we showed that MetQ binds D-methionine (K_D = 9.5 μM), but not L-methionine, which suggests the existence of as yet unknown pathway for L-methionine uptake. Homology modelling has led to identification of the ligand-binding residues.

Functional screening of a Caatinga goat (Capra hircus) rumen metagenomic library reveals a novel GH3 β-xylosidase

Functional screening of metagenomic libraries is an effective approach for identification of novel enzymes. A Caatinga biome goat rumen metagenomic library was screened using esculin as a substrate, and a gene from an unknown bacterium encoding a novel GH3 enzyme, BGL11, was identified. None of the BGL11 closely related genes have been previously characterized. Recombinant BGL11 was obtained and kinetically characterized. Substrate specificity of the purified protein was assessed using seven synthetic aryl substrates. Activity towards nitrophenyl-β-D-glucopyranoside (pNPG), 4-nitrophenyl-β-D-xylopyranoside (pNPX) and 4-nitrophenyl-β-D-cellobioside (pNPC) suggested that BGL11 is a multifunctional enzyme with β-glucosidase, β-xylosidase, and cellobiohydrolase activities. However, further testing with five natural substrates revealed that, although BGL11 has multiple substrate specificity, it is most active towards xylobiose. Thus, in its native goat rumen environment, BGL11 most likely functions as an extracellular β-xylosidase acting on hemicellulose. Biochemical characterization of BGL11 showed an optimal pH of 5.6, and an optimal temperature of 50°C. Enzyme stability, an important parameter for industrial application, was also investigated. At 40°C purified BGL11 remained active for more than 15 hours without reduction in activity, and at 50°C, after 7 hours of incubation, BGL11 remained 60% active. The enzyme kinetic parameters of Km and Vmax using xylobiose were determined to be 3.88 mM and 38.53 μmol.min-1.mg-1, respectively, and the Kcat was 57.79 s-1. In contrast to BLG11, most β-xylosidases kinetically studied belong to the GH43 family and have been characterized only using synthetic substrates. In industry, β-xylosidases can be used for plant biomass deconstruction, and the released sugars can be fermented into valuable bio-products, ranging from the biofuel ethanol to the sugar substitute xylitol.

In silico discovery of antigenic proteins and epitopes of SARS-CoV-2 for the development of a vaccine or a diagnostic approach for COVID-19

In the genome of SARS-CoV-2, the 5′-terminus encodes a polyprotein, which is further cleaved into 15 non-structural proteins whereas the 3′ terminus encodes four structural proteins and eight accessory proteins. Among these 27 proteins, the present study aimed to discover likely antigenic proteins and epitopes to be used for the development of a vaccine or serodiagnostic assay using an in silico approach. For this purpose, after the full genome analysis of SARS-CoV-2 Wuhan isolate and variant proteins that are detected frequently, surface proteins including spike, envelope, and membrane proteins as well as proteins with signal peptide were determined as probable vaccine candidates whereas the remaining were considered as possible antigens to be used during the development of serodiagnostic assays. According to results obtained, among 27 proteins, 26 of them were predicted as probable antigen. In 26 proteins, spike protein was selected as the best vaccine candidate because of having a signal peptide, negative GRAVY value, one transmembrane helix, moderate aliphatic index, a big molecular weight, a long-estimated half-life, beta wrap motifs as well as having stable, soluble and non-allergic features. In addition, orf7a, orf8, and nsp-10 proteins with signal peptide were considered as potential vaccine candidates. Nucleocapsid protein and a highly antigenic GGDGKMKD epitope were identified as ideal antigens to be used in the development of serodiagnostic assays. Moreover, considering MHC-I alleles, highly antigenic KLNDLCFTNV and ITLCFTLKRK epitopes can be used to develop an epitope-based peptide vaccine.

Expression of four new ferritins from grooved carpet shell clam Ruditapes decussatus challenged with Perkinsus olseni and metals (Cd, Cu and Zn)

Iron has a fundamental role in life and in its biochemical reactions but, when in excess, it can promote the formation of free radicals which can lead to cell death. Therefore, managing the levels of iron is essential to regulate the production of oxidative stress related to iron, and ferritins are one of the main protein families involved in this process. Ferritins are ≈480 kDa multimeric proteins composed by 24 subunits, each with 19-26 kDa, which can accumulate up to 4500 iron atoms. Besides their role in managing iron bioavailability, they have also developed a role in organism immunity and defence present throughout evolution. In this work, we identified and characterized, for the first time, four different ferritin subunits in the clam Ruditapes decussatus, a bivalve commercially and ecologically important along the south Atlantic coast and in the Mediterranean basin, which is a major target of the parasitic protozoa Perkinsus olseni, considered one of the main causes of high levels of clam mortality. Following phylogenetic annotation, the four ferritins subunits identified were subdivided into two cytosolic and two secreted forms. All four subunits maintain the canonical ferritin structure with four main helices α (A-D) and a small helix (E), but the secreted ferritins present an additional helix in their N-terminal region (F), located after the signal peptide and with possible antimicrobial properties. Additionally, we identified in ferritin 4 an extra helix α (G) located between helices B and C. These alpha helix domains revealed high degree of similarity with antimicrobial peptides associated with antibacterial and antifungal activities. Analysis of the expression of these subunits showed that ferritins 1 and 2 are ubiquitously expressed while ferritins 3 and 4 are present mainly in visceral mass. Ferritin 1 lacked a putative functional iron response element (IRE) and appeared to be under a tight regulation. Ferritins 2 and 3 showed a strong response to infection by parasite Perkinsus olseni in contrast to ferritin 4, whose main response was related to exposure to a combination of metals. The synergistic effect between metals and infection promoted a general upregulation of the four ferritins. In conclusion, our results suggest that ferritins, besides their function in iron and metals detoxification, may play a determinant role in clam immune response.

Non-adaptive Evolution of Trimeric Autotransporters in Brucellaceae

Brucella species are Gram-negative, facultative intracellular pathogens. They are the main cause of brucellosis, which has led to a global health burden. Adherence of the pathogen to the host cells is the first step in the infection process. The bacteria can adhere to various biotic and abiotic surfaces using their outer membrane proteins. Trimeric autotransporter adhesins (TAAs) are modular homotrimers of various length and domain complexity. They are a diverse, and widespread gene family constituting the type Vc secretion pathway. These adhesins have been established as virulence factors in Brucellaceae. To date, no comprehensive and exhaustive study has been performed on the trimeric autotransporter family in the genus. In the present study, various bioinformatics tools were used to provide a novel evolutionary insight into the sequence and structure of this protein family in Brucellaceae. To this end, a dataset of all trimeric autotransporters from the Brucella genomes was built. Analyses included but were not limited to sequence alignment, phylogenetic tree constructions, codon-based test for selection, clustering of the sequences, and structure (primary to quaternary) predictions. Batch analyzes of the dataset suggested the existence of a few structural domains within the whole population. BatA from the B. abortus 2308 genome was selected as a reference to describe the features of these structural domains. Furthermore, we examined the structural basis for the observed rigidity and resiliency of the protein structure through a molecular dynamics evaluation, which led us to deduce that the random drift results in the non-adaptive evolution of the trimeric autotransporter genes in the Brucella genus. Notably, the modifications have occurred across the genus without interference of gene transmission.

Alpha-Carbonic Anhydrases from Hydrothermal Vent Sources as Potential Carbon Dioxide Sequestration Agents: In Silico Sequence, Structure and Dynamics Analyses

With the increase in CO2 emissions worldwide and its dire effects, there is a need to reduce CO2 concentrations in the atmosphere. Alpha-carbonic anhydrases (α-CAs) have been identified as suitable sequestration agents. This study reports the sequence and structural analysis of 15 α-CAs from bacteria, originating from hydrothermal vent systems. Structural analysis of the multimers enabled the identification of hotspot and interface residues. Molecular dynamics simulations of the homo-multimers were performed at 300 K, 363 K, 393 K and 423 K to unearth potentially thermostable α-CAs. Average betweenness centrality (BC) calculations confirmed the relevance of some hotspot and interface residues. The key residues responsible for dimer thermostability were identified by comparing fluctuating interfaces with stable ones, and were part of conserved motifs. Crucial long-lived hydrogen bond networks were observed around residues with high BC values. Dynamic cross correlation fortified the relevance of oligomerization of these proteins, thus the importance of simulating them in their multimeric forms. A consensus of the simulation analyses used in this study suggested high thermostability for the α-CA from Nitratiruptor tergarcus. Overall, our novel findings enhance the potential of biotechnology applications through the discovery of alternative thermostable CO2 sequestration agents and their potential protein design.

Signal-3L 3.0: Improving Signal Peptide Prediction through Combining Attention Deep Learning with Window-Based Scoring

Signal peptides play an important role in guiding and transferring transmembrane proteins and secreted proteins. In recent years, with the explosive growth of protein sequences, computationally predicting signal peptides and their cleavage sites from protein sequences is highly desired. In this work, we present an improved approach, Signal-3L 3.0, for signal peptide recognition and cleavage-site prediction using a 3-layer hybrid method of integrating deep learning algorithms and window-based scoring. There are three main components in the Signal-3L 3.0 prediction engine: (1) a deep bidirectional long short-term memory (Bi-LSTM) network with a soft self-attention learns abstract features from sequences to determine whether a query protein contains a signal peptide; (2) the statistics propensity window-based cleavage site screening method is applied to generate the set of candidate cleavage sites; (3) the prediction of a conditional random field with a hybrid convolutional neural network (CNN) and Bi-LSTM is fused with the window-based score for identifying the final unique cleavage site. Experimental results on the benchmark datasets show that the new deep learning-driven Signal-3L 3.0 yields promising performance. The online server of Signal-3L 3.0 is available at http://www.csbio.sjtu.edu.cn/bioinf/Signal-3L/.

CIRFESS: An Interactive Resource for Querying the Set of Theoretically Detectable Peptides for Cell Surface and Extracellular Enrichment Proteomic Studies

Cell surface transmembrane, extracellular, and secreted proteins are high value targets for immunophenotyping, drug development, and studies related to intercellular communication in health and disease. As the number of specific and validated affinity reagents that target this subproteome are limited, mass spectrometry (MS)-based approaches will continue to play a critical role in enabling discovery and quantitation of these molecules. Given the technical considerations that make MS-based cell surface proteome studies uniquely challenging, it can be difficult to select an appropriate experimental approach. To this end, we have integrated multiple prediction strategies and annotations into a single online resource, Compiled Interactive Resource for Extracellular and Surface Studies (CIRFESS). CIRFESS enables rapid interrogation of the human proteome to reveal the cell surface proteome theoretically detectable by current approaches and highlights where current prediction strategies provide concordant and discordant information. We applied CIRFESS to identify the percentage of various subsets of the proteome which are expected to be captured by targeted enrichment strategies, including two established methods and one that is possible but not yet demonstrated. These results will inform the selection of available proteomic strategies and development of new strategies to enhance coverage of the cell surface and extracellular proteome. CIRFESS is available at www.cellsurfer.net/cirfess.

Activity and Metabolic Versatility of Complete Ammonia Oxidizers in Full-Scale Wastewater Treatment Systems

The recent discovery of complete ammonia oxidizers (comammox) contradicts the paradigm that chemolithoautotrophic nitrification is always catalyzed by two different microorganisms. However, our knowledge of the survival strategies of comammox in complex ecosystems, such as full-scale wastewater treatment plants (WWTPs), remains limited. Analyses of genomes and in situ transcriptomes of four comammox organisms from two full-scale WWTPs revealed that comammox were active and showed a surprisingly high metabolic versatility. A gene cluster for the utilization of urea and a gene encoding cyanase suggest that comammox may use diverse organic nitrogen compounds in addition to free ammonia as the substrates. The comammox organisms also encoded the genomic potential for multiple alternative energy metabolisms, including respiration with hydrogen, formate, and sulfite as electron donors. Pathways for the biosynthesis and degradation of polyphosphate, glycogen, and polyhydroxyalkanoates as intracellular storage compounds likely help comammox survive unfavorable conditions and facilitate switches between lifestyles in fluctuating environments. One of the comammox strains acquired from the anaerobic tank encoded and transcribed genes involved in homoacetate fermentation or in the utilization of exogenous acetate, both pathways being unexpected in a nitrifying bacterium. Surprisingly, this strain also encoded a respiratory nitrate reductase which has not yet been found in any other Nitrospira genome and might confer a selective advantage to this strain over other Nitrospira strains in anoxic conditions.IMPORTANCE The discovery of comammox in the genus Nitrospira changes our perception of nitrification. However, genomes of comammox organisms have not been acquired from full-scale WWTPs, and very little is known about their survival strategies and potential metabolisms in complex wastewater treatment systems. Here, four comammox metagenome-assembled genomes and metatranscriptomic data sets were retrieved from two full-scale WWTPs. Their impressive and-among nitrifiers-unsurpassed ecophysiological versatility could make comammox Nitrospira an interesting target for optimizing nitrification in current and future bioreactor configurations.

Interaction of Human Herpesvirus 8 Viral Interleukin-6 with Human Interleukin-6 Receptor Using In Silico Approach: The Potential Role in HHV-8 Pathogenesis

Introduction:

Human Herpesvirus 8 (HHV-8) causes classical, endemic (African), and Acquired Immunodeficiency Syndrome (AIDS)-related Kaposi’s Sarcoma (KS), Body Cavity-Based Primary Effusion Lymphomas (BCBL), HHV-8-associated peritoneal Primary Effusion Lymphoma (PEL), and Multicentric Castleman’s Disease (MCD). HHV8 genome encodes several structural and non-structural proteins, among which vIL6 is a functional homologue of Interleukin-6 (IL-6). It has been established that vIL6 plays a vital role in HHV8 infections; also, it has been suggested that its function was mediated through gp130, rather than the gp80 (IL-6 receptor [IL-6R]). This study aimed to investigate the physicochemical and structural properties as well as the immunological features, and finally the interaction between vIL6 and IL6 receptor (IL6R) by using several bioinformatics tools which could provide both valuable insight into vIL6 protein and advantageous data for further studies on HHV8 inhibitors and new vaccines.

Material and Methods:

vIL6, human IL6 (hIL6), and IL6R were obtained from NCBI GenBank and Uniport, which were aligned by The CLC Genomics Workbench. "Signal-BLAST" and “predisi" were employed to define signal peptide; also, “Expasy’sProtParam” was used to predict physicochemical properties as well as "DiANNA", and "SCRATCH" predicted the disulfide bonds. “NetPhosK”, “DISPHOS”, “NetPhos”, ”NetNGlyc”, and ”GlycoEP” were involved to determine post-modification sites. To define immunoinformatics analysis, “BcePred”, “ABCpred”, “Bepipred”, “AlgPred”, and "VaxiJen" were used. “SOPMA”, “I-TASSER”, “GalaxyRefine”, and “3D-Refine” predicted and refined the secondary and tertiary structures. TM-align server was used to align 3D structures. In addition, docking analysis was done by “Hex 5.0.”, and finally the results were illustrated by “Discovery Studio”.

Results:

A signal peptide (1-22) was defined in the vIL6 sequences and analysis has shown that vIL6 is an acidic protein which is significantly stable in all organisms. Three Disulfide bonds were predicted and immunoinformatics analysis showed 5 distinct B-cell epitopes. vIL6 is predicted as a non-allergen protein and the majority of its structure consists of Alpha helix. TM-align pointed the significant similarity between vIL6 and hIL6 in protein folding. The high energy value between vIL6 protein and IL6R was calculated and further analysis illustrated 5 conserved regions as well as 4 conserved amino acids which had a significant role in vIL6 and IL6R interaction.

Discussion:

An in silico study by numerous software determined the possible interaction between vIL6 and IL6R and the possible role of this interaction in HHV8 pathogenesis and the progress of infection. These have been overlooked by previous studies and will be beneficial to gain a more comprehensive understanding of vIL6 function during HHV8 lifecycle and infections. Structural analysis showed the significant similarity between vIL6 and hIL6 folding which can describe the similarity of the functions or interactions of both proteins. Furthermore, several conserved regions in the interaction site which interestingly were highly conserved among all vIL6 sequences can be used as new target for vIL6 inhibitors. Moreover, our results could predict immunological properties of vIL6 which suggested the ability of this protein in induction of the humoral immune response. Such a protein may be used for further studies on therapeutic vaccine fields.

The possible regions to design Human Papilloma Viruses vaccine in Iranian L1 protein

Human Papilloma Virus (HPV) genome encodes several proteins, as L1is major capsid protein and L2 is minor capsid protein. Among all HPV types HPV-16 and HPV-18 are the most common high-risk HPV (HR-HPV) types globally and the majority of cases are infected with these types. HPV entry and the initial interaction with the host cell are mainly related to the L1 protein which is the main component of HPV vaccines. The aim of this research was comparison analysis among all Iranian L1 protein sequences submitted in NCBI GenBank to find the major substitutions as well as structural and immune properties of this protein. All sequences HPV L1 protein from Iranian isolates from 2014 to 2016 were selected and obtained from NCBI data bank. "CLC Genomics Workbench" was used to translate alignment. To predict B cell epitopes, we employed several programs. Modification sites such as phosphorylation, glycosylation, and disulfide bonds were determined. Secondary and tertiary structures of all sequences were analyzed. Several mutations were found and major mutations were in amino acid residues 102, 202, 207, 292, 379, and 502. The mentioned mutations showed the minor effect on B cell and physicochemical properties of the L1 protein. Six disulfide bonds were determined in L1 protein and also in several N-link glycosylation and phosphorylation sites. Five L1 loops were determined, which had great potential to be B cell epitopes with high antigenic properties. All in all, this research as the first report from Iran described the tremendous potential of two L1 loops (BC and FG) to induce immune system which can be used as the descent candidate to design a new vaccine against HPV in the Iranian population. In addition, some differences between the reference sequence and Iranian patients' sequences were determined. It is essential to consider these differences to monitor the effectiveness and efficacy of the vaccine for the Iranian population. Our results provide a vast understanding of L1 protein that can be useful for further studies on HPV infections and new vaccine generations.

A Primate-Specific Isoform of PLEKHG6 Regulates Neurogenesis and Neuronal Migration

The mammalian neocortex has undergone remarkable changes through evolution. A consequence of such rapid evolutionary events could be a trade-off that has rendered the brain susceptible to certain neurodevelopmental and neuropsychiatric conditions. We analyzed the exomes of 65 patients with the structural brain malformation periventricular nodular heterotopia (PH). De novo coding variants were observed in excess in genes defining a transcriptomic signature of basal radial glia, a cell type linked to brain evolution. In addition, we located two variants in human isoforms of two genes that have no ortholog in mice. Modulating the levels of one of these isoforms for the gene PLEKHG6 demonstrated its role in regulating neuroprogenitor differentiation and neuronal migration via RhoA, with phenotypic recapitulation of PH in human cerebral organoids. This suggests that this PLEKHG6 isoform is an example of a primate-specific genomic element supporting brain development.

Bioinformatics analysis of Ras homologue enriched in the striatum, a potential target for Huntington's disease therapy

Huntington's disease (HD) is a lethal neurodegenerative disorder for which no cure is available yet. It is caused by abnormal expansion of a CAG triplet in the gene encoding the huntingtin protein (Htt), with consequent expansion of a polyglutamine repeat in mutated Htt (mHtt). This makes mHtt highly unstable and aggregation prone. Soluble mHtt is linked to cytotoxicity and neurotoxicity, whereas mHtt aggregates are thought to be neuroprotective. While Htt and mHtt are ubiquitously expressed throughout the brain and peripheral tissues, HD is characterized by selective degradation of the corpus striatum, without notable alterations in peripheral tissues. Screening for mRNAs preferentially expressed in rodent striatum led to the discovery of a GTP binding protein homologous to Ras family members. Due to these features, the newly discovered protein was termed Ras Homolog Enriched in Striatum (RHES). The aetiological role of RHES in HD has been ascribed to its small ubiquitin-like modifier (SUMO)-E3 ligase function. RHES sumoylates mHtt with higher efficiency than wild-type Htt, thereby protecting mHtt from degradation and increasing the amounts of the soluble form. Although RHES is an attractive target for HD treatment, essential information about protein structure and function are still missing. With the aim of investigating RHES 3D structure and function, bioinformatic analyses and molecular modelling have been performed in the present study, based on which, RHES regions predicted to be involved in the interaction with mHtt or the SUMO-E2 ligase Ubc9 have been identified. These regions have been used to design peptides aimed at inhibiting RHES interactions and, therefore, mHtt sumoylation; in turn, these peptides will be used to develop small molecule inhibitors by both rational design and virtual screening of large compound libraries. Once identified, RHES sumoylation inhibitors may open the road to the development of therapeutic agents against the severe, and currently untreatable, HD.

Identification of a Ribosomal Protein RpsB as a Surface-Exposed Protein and Adhesin of Rickettsia heilongjiangensis

Rickettsia heilongjiangensis is an obligate intracellular bacterium that is responsible for far-eastern spotted fever. Surface-exposed proteins (SEPs) play important roles in its pathogenesis. Previous work identified a ribosomal protein RpsB as an SEP by biotin-avidin affinity, a seroreactive antigen, and a diagnostic candidate protein, indicating that it might play an important role in the pathogenesis of rickettsiae. However, in the absence of other evidence, its subcellular location of being surface-exposed was puzzling because ribosomal proteins are located in the cytoplasm. In the present study, the subcellular location of RpsB was analyzed with bioinformatics tools coupled with immunoelectron microscopy. The adhesion ability of RpsB was evaluated by protein microarray and cellular ELISA. Consequently, different bioinformatics tools gave different location predication results. Thus, RpsB was found in the cytoplasma and inner and outer membranes of R. heilongjiangensis by transmission electron microscopy. Protein microarray and cellular ELISA showed that RpsB binds to the host cell surface and its adhesion ability was even stronger than the known adhesin Adr1. In conclusion, RpsB was visually and directly shown for the time to be an SEP of rickettsiae and might be an important ligand and adhesin of rickettsiae. Its roles in pathogenesis warrant further study.

A Brief History of Protein Sorting Prediction

Ever since the signal hypothesis was proposed in 1971, the exact nature of signal peptides has been a focus point of research. The prediction of signal peptides and protein subcellular location from amino acid sequences has been an important problem in bioinformatics since the dawn of this research field, involving many statistical and machine learning technologies. In this review, we provide a historical account of how position-weight matrices, artificial neural networks, hidden Markov models, support vector machines and, lately, deep learning techniques have been used in the attempts to predict where proteins go. Because the secretory pathway was the first one to be studied both experimentally and through bioinformatics, our main focus is on the historical development of prediction methods for signal peptides that target proteins for secretion; prediction methods to identify targeting signals for other cellular compartments are treated in less detail.

The classical NLRP3 inflammasome controls FADD unconventional secretion through microvesicle shedding

Fas-associated death domain (FADD) is a key adaptor molecule involved in numerous physiological processes including cell death, proliferation, innate immunity and inflammation. Therefore, changes in FADD expression have dramatic cellular consequences. In mice and humans, FADD regulation can occur through protein secretion. However, the molecular mechanisms accounting for human FADD secretion were still unknown. Here we report that canonical, non-canonical, but not alternative, NLRP3 inflammasome activation in human monocytes/macrophages induced FADD secretion. NLRP3 inflammasome activation by the bacterial toxin nigericin led to the proinflammatory interleukin-1β (IL-1β) release and to the induction of cell death by pyroptosis. However, we showed that FADD secretion could occur in absence of increased IL-1β release and pyroptosis and, reciprocally, that IL-1β release and pyroptosis could occur in absence of FADD secretion. Especially, FADD, but not IL-1β, secretion following NLRP3 inflammasome activation required extracellular glucose. Thus, FADD secretion was an active process distinct from unspecific release of proteins during pyroptosis. This FADD secretion process required K⁺ efflux, NLRP3 sensor, ASC adaptor and CASPASE-1 molecule. Moreover, we identified FADD as a leaderless protein unconventionally secreted through microvesicle shedding, but not exosome release. Finally, we established human soluble FADD as a new marker of joint inflammation in gout and rheumatoid arthritis, two rheumatic diseases involving the NLRP3 inflammasome. Whether soluble FADD could be an actor in these diseases remains to be determined. Nevertheless, our results advance our understanding of the mechanisms contributing to the regulation of the FADD protein expression in human cells.

SignalP 5.0 improves signal peptide predictions using deep neural networks

Signal peptides (SPs) are short amino acid sequences in the amino terminus of many newly synthesized proteins that target proteins into, or across, membranes. Bioinformatic tools can predict SPs from amino acid sequences, but most cannot distinguish between various types of signal peptides. We present a deep neural network-based approach that improves SP prediction across all domains of life and distinguishes between three types of prokaryotic SPs.

Integration of Self and Non-self Recognition Modulates Asexual Cell-to-Cell Communication in Neurospora crassa

Cells rarely exist alone, which drives the evolution of diverse mechanisms for identifying and responding appropriately to the presence of other nearby cells. Filamentous fungi depend on somatic cell-to-cell communication and fusion for the development and maintenance of a multicellular, interconnected colony that is characteristic of this group of organisms. The filamentous fungus Neurospora crassa is a model for investigating the mechanisms of somatic cell-to-cell communication and fusion. N. crassa cells chemotropically grow toward genetically similar cells, which ultimately make physical contact and undergo cell fusion. Here, we describe the development of a Pprm1-luciferase reporter system that differentiates whether genes function upstream or downstream of a conserved MAP kinase (MAPK) signaling complex, by using a set of mutants required for communication and cell fusion. The vast majority of these mutants are deficient for self-fusion and for fusion when paired with wild-type cells. However, the Δham-11 mutant is unique in that it fails to undergo self-fusion, but chemotropic interactions and cell fusion are restored in Δham-11 + wild-type interactions. In genetically dissimilar cells, chemotropic interactions are regulated by genetic differences at doc-1 and doc-2, which regulate prefusion non-self recognition; cells with dissimilar doc-1 and doc-2 alleles show greatly reduced cell-fusion frequencies. Here, we show that HAM-11 functions in parallel with the DOC-1 and DOC-2 proteins to regulate the activity of the MAPK signaling complex. Together, our data support a model of integrated self and non-self recognition processes that modulate somatic cell-to-cell communication in N. crassa.

A specialized MreB-dependent cell wall biosynthetic complex mediates the formation of stalk-specific peptidoglycan in Caulobacter crescentus

Many bacteria have complex cell shapes, but the mechanisms producing their distinctive morphologies are still poorly understood. Caulobacter crescentus, for instance, exhibits a stalk-like extension that carries an adhesive holdfast mediating surface attachment. This structure forms through zonal peptidoglycan biosynthesis at the old cell pole and elongates extensively under phosphate-limiting conditions. We analyzed the composition of cell body and stalk peptidoglycan and identified significant differences in the nature and proportion of peptide crosslinks, indicating that the stalk represents a distinct subcellular domain with specific mechanical properties. To identify factors that participate in stalk formation, we systematically inactivated and localized predicted components of the cell wall biosynthetic machinery of C. crescentus. Our results show that the biosynthesis of stalk peptidoglycan involves a dedicated peptidoglycan biosynthetic complex that combines specific components of the divisome and elongasome, suggesting that the repurposing of preexisting machinery provides a straightforward means to evolve new morphological traits.

Integrated transcriptomic and proteomic analyses of a molecular mechanism of radular teeth biomineralization in Cryptochiton stelleri

Many species of chiton are known to deposit magnetite (Fe₃O₄) within the cusps of their heavily mineralized and ultrahard radular teeth. Recently, much attention has been paid to the ultrastructural design and superior mechanical properties of these radular teeth, providing a promising model for the development of novel abrasion resistant materials. Here, we constructed de novo assembled transcripts from the radular tissue of C. stelleri that were used for transcriptome and proteome analysis. Transcriptomic analysis revealed that the top 20 most highly expressed transcripts in the non-mineralized teeth region include the transcripts encoding ferritin, while those in the mineralized teeth region contain a high proportion of mitochondrial respiratory chain proteins. Proteomic analysis identified 22 proteins that were specifically expressed in the mineralized cusp. These specific proteins include a novel protein that we term radular teeth matrix protein1 (RTMP1), globins, peroxidasins, antioxidant enzymes and a ferroxidase protein. This study reports the first de novo transcriptome assembly from C. stelleri, providing a broad overview of radular teeth mineralization. This new transcriptomic resource and the proteomic profiles of mineralized cusp are valuable for further investigation of the molecular mechanisms of radular teeth mineralization in chitons.

Transcriptome and Comparative Genomics Analyses Reveal New Functional Insights on Key Determinants of Pathogenesis and Interbacterial Competition in Pectobacterium and Dickeya spp

Soft-rot Enterobacteriaceae (SRE), typified by Pectobacterium and Dickeya genera, are phytopathogenic bacteria inflicting soft-rot disease in crops worldwide. By combining genomic information from 100 SRE with whole-transcriptome data sets, we identified novel genomic and transcriptional associations among key pathogenicity themes in this group. Comparative genomics revealed solid linkage between the type I secretion system (T1SS) and the carotovoricin bacteriophage (Ctv) conserved in 96.7% of Pectobacterium genomes. Moreover, their coactivation during infection indicates a novel functional association involving T1SS and Ctv. Another bacteriophage-borne genomic region, mostly confined to less than 10% of Pectobacterium strains, was found, presumably comprising a novel lineage-specific prophage in the genus. We also detected the transcriptional coregulation of a previously predicted toxin/immunity pair (WHH and SMI1_KNR4 families), along with the type VI secretion system (T6SS), which includes hcp and/or vgrG genes, suggesting a role in disease development as T6SS-dependent effectors. Further, we showed that another predicted T6SS-dependent endonuclease (AHH family) exhibited toxicity in ectopic expression assays, indicating antibacterial activity. Additionally, we report the striking conservation of the group 4 capsule (GFC) cluster in 100 SRE strains which consistently features adjacently conserved serotype-specific gene arrays comprising a previously unknown organization in GFC clusters. Also, extensive sequence variations found in gfcA orthologs suggest a serotype-specific role in the GfcABCD machinery.IMPORTANCE Despite the considerable loss inflicted on important crops yearly by Pectobacterium and Dickeya diseases, investigations on key virulence and interbacterial competition assets relying on extensive comparative genomics are still surprisingly lacking for these genera. Such approaches become more powerful over time, underpinned by the growing amount of genomic information in public databases. In particular, our findings point to new functional associations among well-known genomic themes enabling alternative means of neutralizing SRE diseases through disruption of pivotal virulence programs. By elucidating novel transcriptional and genomic associations, this study adds valuable information on virulence candidates that could be decisive in molecular applications in the near future. The utilization of 100 genomes of Pectobacterium and Dickeya strains in this study is unprecedented for comparative analyses in these taxa, and it provides novel insights on the biology of economically important plant pathogens.

Bioconversion of lignin into bioplastics by Pandoraea sp. B-6: molecular mechanism

Lignin is a byproduct in the pulp and paper industry and is considered as a promising alternative for the provision of energy and chemicals. Currently, the efficient valorization of lignin is a challenge owing to its polymeric structure complexity. Here, we present a platform for bio-converting Kraft lignin (KL), to polyhydroxyalkanoate (PHA) by Pandoraea sp. B-6 (hereafter B-6). Depolymerization of KL by B-6 was first confirmed, and > 40% KL was degraded by B-6 in the initial 4 days. Characterization of PHA showed that up to 24.7% of PHA accumulated in B-6 grown in 6-g/L KL mineral medium. The composition, structure, and thermal properties of the produced PHA were analyzed, revealing that 3-hydroxybutyrate was the only monomer and that PHA was comparable with the commercially available bioplastics. Moreover, the genomic analysis illustrated three core enzymatic systems for lignin depolymerization including laccases, peroxidases, and Fenton-reaction enzymes; five catabolic pathways for LDAC degradation and a gene cluster consisting of bktB, phaR, phaB, phaA, and phaC genes involved in PHA biosynthesis. Accordingly, a basic model for the process from lignin depolymerization to PHA production was constructed. Our findings provide a comprehensive perspective for lignin valorization and bio-material production from waste.

Sequential cleavage of the proteins encoded by HNOT/ALG3, the human counterpart of the Drosophila NOT and yeast ALG3 gene, results in products acting in distinct cellular compartments

This study provides first insights into the biosynthesis, structure, biochemistry and complex processing of the proteins encoded by hNOT/ALG3, the human counterpart of the Drosophila Neighbour of TID (NOT) and the yeast asparagine linked glycosylation 3 gene (ALG3), which encodes a mannosyltransferase. Unambiguous evidence that both the fly and human proteins act as mannosyltransferases has not been provided yet. Previously, we showed that hNOT/ALG3 encodes two alternatively spliced main transcripts, hNOT-1/ALG3-1 and hNOT-4/ALG3-4, and their 15 truncated derivatives that lack diverse sets of exons and/or carry point mutations that result in premature termination codons. Here we show that the truncated transcripts are not translated. The two main forms hNOT-1/ALG3-1 and -4, distinguishable by alternative exon 1, encode full-length precursors that undergo a complex posttranslational processing. To specifically detect the two full-length hNOT/ALG3 proteins and their distinct derivatives and to examine their expression profiles and cellular location we generated polyclonal antibodies against diverse parts of the putative full-length proteins. We provide experimental evidence for the N-glycosylation of the two precursors. This modification seems to be a prerequisite for their sequential cleavage resulting in derivatives destined to distinct cellular compartments and links them with the N-glycosylation machinery not as its functional component but as molecules functionally dependent on its action. We present the expression profiles and subcellular location of the two full-length proteins, their N-glycosylated forms and distinct cleavage products. Furthermore, using diverse bioinformatics tools, we characterize the properties and predict the 2D and 3D structure of the two proteins and, for comparative purposes, of their Drosophila counterpart.

RNA Viruses in Blechomonas (Trypanosomatidae) and Evolution of Leishmaniavirus

In this work, we analyzed viral prevalence in trypanosomatid parasites (Blechomonas spp.) infecting Siphonaptera and discovered nine species of viruses from three different groups (leishbunyaviruses, narnaviruses, and leishmaniaviruses). Most of the flagellate isolates bore two or three viral types (mixed infections). Although no new viral groups were documented in Blechomonas spp., our findings are important for the comprehension of viral evolution. The discovery of bunyaviruses in blechomonads was anticipated, since these viruses have envelopes facilitating their interspecific transmission and have already been found in various trypanosomatids and metatranscriptomes with trypanosomatid signatures. In this work, we also provided evidence that even representatives of the family Narnaviridae are capable of host switching and evidently have accomplished switches multiple times in the course of their evolution. The most unexpected finding was the presence of leishmaniaviruses, a group previously solely confined to the human pathogens Leishmania spp. From phylogenetic inferences and analyses of the life cycles of Leishmania and Blechomonas, we concluded that a common ancestor of leishmaniaviruses most likely infected Leishmania first and was acquired by Blechomonas by horizontal transfer. Our findings demonstrate that evolution of leishmaniaviruses is more complex than previously thought and includes occasional host switching.IMPORTANCE Flagellates belonging to the genus Leishmania are important human parasites. Some strains of different Leishmania species harbor viruses (leishmaniaviruses), which facilitate metastatic spread of the parasites, thus aggravating the disease. Up until now, these viruses were known to be hosted only by Leishmania Here, we analyzed viral distribution in Blechomonas, a related group of flagellates parasitizing fleas, and revealed that they also bear leishmaniaviruses. Our findings shed light on the entangled evolution of these viruses. In addition, we documented that Blechomonas can be also infected by leishbunyaviruses and narnaviruses, viral groups known from other insects' flagellates.

Complete genome sequence of a novel sea otterpox virus

Members of the Poxviridae family are large, double-stranded DNA viruses that replicate in the cytoplasm of their host cells. The subfamily Chordopoxvirinae contains viruses that infect a wide range of vertebrates including marine mammals within the Balaenidae, Delphinidae, Mustelidae, Odobenidae, Otariidae, Phocidae, and Phocoenidae families. Recently, a novel poxvirus was found in a northern sea otter pup (Enhydra lutris kenyoni) that stranded in Alaska in 2009. The phylogenetic relationships of marine mammal poxviruses are not well established because of the lack of complete genome sequences. The current study sequenced the entire sea otterpox virus Enhydra lutris kenyoni (SOPV-ELK) genome using an Illumina MiSeq sequencer. The SOPV-ELK genome is the smallest poxvirus genome known at 127,879 bp, is 68.7% A+T content, is predicted to encode 132 proteins, and has 2546 bp inverted terminal repeats at each end. Genetic and phylogenetic analyses based on the concatenated amino acid sequences of 7 chorodopoxvirus core genes revealed the SOPV-ELK is 52.5-74.1% divergent from other known chordopoxviruses and is most similar to pteropoxvirus from Australia (PTPV-Aus). SOPV-ELK represents a new chordopoxvirus species and may belong to a novel genus. SOPV-ELK encodes eight unique genes. While the function of six predicted genes remains unknown, two genes appear to function as novel immune-modulators. SOPV-ELK-003 appears to encode a novel interleukin-18 binding protein (IL-18 BP), based on limited sequence and structural similarity to other poxviral IL-18 BPs. SOPV-ELK-035 appears to encode a novel tumor necrosis factor receptor-like (TNFR) protein that may be associated with the depression of the host's antiviral response. Additionally, SOPV-ELK-036 encodes a tumor necrosis factor-like apoptosis-inducing ligand (TRAIL) protein that has previously only been found in PTPV-Aus. The SOPV-ELK genome is the first mustelid poxvirus and only the second poxvirus from a marine mammal to be fully sequenced. Sequencing of the SOPV-ELK genome is an important step in unraveling the position of marine mammal poxviruses within the larger Poxviridae phylogenetic tree and provides the necessary sequence to develop molecular tools for future diagnostics and epidemiological studies.

Wireless control of cellular function by activation of a novel protein responsive to electromagnetic fields

The Kryptopterus bicirrhis (glass catfish) is known to respond to electromagnetic fields (EMF). Here we tested its avoidance behavior in response to static and alternating magnetic fields stimulation. Using expression cloning we identified an electromagnetic perceptive gene (EPG) from the K. bicirrhis encoding a protein that responds to EMF. This EPG gene was cloned and expressed in mammalian cells, neuronal cultures and in rat’s brain. Immunohistochemistry showed that the expression of EPG is confined to the mammalian cell membrane. Calcium imaging in mammalian cells and cultured neurons expressing EPG demonstrated that remote activation by EMF significantly increases intracellular calcium concentrations, indicative of cellular excitability. Moreover, wireless magnetic activation of EPG in rat motor cortex induced motor evoked responses of the contralateral forelimb in vivo. Here we report on the development of a new technology for remote, non-invasive modulation of cell function.

nifPred: Proteome-Wide Identification and Categorization of Nitrogen-Fixation Proteins of Diaztrophs Based on Composition-Transition-Distribution Features Using Support Vector Machine

As inorganic nitrogen compounds are essential for basic building blocks of life (e.g., nucleotides and amino acids), the role of biological nitrogen-fixation (BNF) is indispensible. All nitrogen fixing microbes rely on the same nitrogenase enzyme for nitrogen reduction, which is in fact an enzyme complex consists of as many as 20 genes. However, the occurrence of six genes viz., nifB, nifD, nifE, nifH, nifK, and nifN has been proposed to be essential for a functional nitrogenase enzyme. Therefore, identification of these genes is important to understand the mechanism of BNF as well as to explore the possibilities for improving BNF from agricultural sustainability point of view. Further, though the computational tools are available for the annotation and phylogenetic analysis of nifH gene sequences alone, to the best of our knowledge no tool is available for the computational prediction of the above mentioned six categories of nitrogen-fixation (nif) genes or proteins. Thus, we proposed an approach, which is first of its kind for the computational identification of nif proteins encoded by the six categories of nif genes. Sequence-derived features were employed to map the input sequences into vectors of numeric observations that were subsequently fed to the support vector machine as input. Two types of classifier were constructed: (i) a binary classifier for classification of nif and non-nitrogen-fixation (non-nif) proteins, and (ii) a multi-class classifier for classification of six categories of nif proteins. Higher accuracies were observed for the combination of composition-transition-distribution (CTD) feature set and radial kernel, as compared to the other feature-kernel combinations. The overall accuracies were observed >90% in both binary and multi-class classifications. The developed approach further achieved >92% accuracy, while evaluated with blind (independent) test datasets. The developed approach also produced higher accuracy in identifying nif proteins, while evaluated using proteome-wide datasets of several species. Furthermore, we established a prediction server nifPred (http://webapp.cabgrid.res.in/nifPred) to assist the scientific community for proteome-wide identification of six categories of nif proteins. Besides, the source code of nifPred is also available at https://github.com/PrabinaMeher/nifPred. The developed web server is expected to supplement the transcriptional profiling and comparative genomics studies for the identification and functional annotation of genes related to BNF.

Alpha-linolenic acid and linoleic acid differentially regulate the skeletal muscle secretome of obese Zucker rats

Evidence shows that proteins secreted from skeletal muscle influence a broad range of metabolic signaling pathways. We previously reported that essential polyunsaturated fatty acids (PUFA) improved whole-body glucose homeostasis in obese Zucker rats; however, the mechanisms underlying these benefits remain enigmatic. While PUFA and obesity influence skeletal muscle function, their effects on the secretome are unknown. The aim of this work was to determine if improvements in whole-body glucose homeostasis in obese Zucker rats fed diets supplemented with either linoleic acid (LA) or alpha-linolenic acid (ALA) for 12 wk are related to changes in the skeletal muscle secretome. Secreted proteins were identified with a predictive bioinformatic analysis of microarray gene expression from red tibialis anterior skeletal muscle. Approximately 130 genes were differentially expressed (false discovery rate = 0.05) in obese rats compared with lean controls. The expression of 15 genes encoding secreted proteins was differentially regulated in obese controls, obese LA-supplemented, and obese ALA-supplemented rats compared with lean controls. Five secreted proteins ( Col3a1, Col15a1, Pdgfd, Lyz2, and Angptl4) were differentially regulated by LA and ALA. Most notably, ALA supplementation reduced Angptl4 gene expression compared with obese control and obese-LA supplemented rats and reduced circulating ANGPTL4 serum concentrations. ALA also influenced Angptl4 gene expression and ANGPTL4 secretion from differentiated rat L6 myotubes. Altogether, the present data indicate that obesity has a greater global impact on skeletal muscle gene expression than either essential PUFA; however, LA and ALA may exert their metabolic benefits in part by regulating the skeletal muscle secretome.

Protein Sorting Prediction

Many computational methods are available for predicting protein sorting in bacteria. When comparing them, it is important to know that they can be grouped into three fundamentally different approaches: signal-based, global-property-based and homology-based prediction. In this chapter, the strengths and drawbacks of each of these approaches is described through many examples of methods that predict secretion, integration into membranes, or subcellular locations in general. The aim of this chapter is to provide a user-level introduction to the field with a minimum of computational theory.

Characterization of PL-7 Family Alginate Lyases From Marine Organisms and Their Applications

Alginate, an anionic heteropolysaccharide extracted from natural brown algae, has useful properties for the food, chemical, medical, and agricultural industries. Degradation of alginate by alginate lyase is a key process to produce unsaturated oligoalginate and unsaturated monosaccharide 4-deoxy-l-erythro-5-hexoseulose uronic acid. Alginate lyases belonging to the polysaccharide lyase family 7 have been found in, and isolated from, organisms thriving in various environments. Furthermore, research on their function and structure has also progressed well. Here, the preparation of native and recombinant PL-7 alginate lyases and the methods for evaluation of enzymatic activity are summarized. Examples of PL-7 alginate lyase applications are also described.