Search

Lysine crotonylation is a newly discovered and reversible posttranslational modification involved in various biological processes, especially metabolism regulation. A total of 5159 lysine crotonylation sites in 2272 protein groups were identified. Twenty-seven motifs were found to be the preferred amino acid sequences for crotonylation sites. Functional annotation analyses revealed that most crotonylated proteins play important roles in metabolic processes and photosynthesis. Bioinformatics analysis suggested that lysine crotonylation preferentially targets a variety of important biological processes, including ribosome, glyoxylate and dicarboxylate metabolism, carbon fixation in photosynthetic organisms, proteasome and the TCA cycle, indicating lysine crotonylation is involved in the common mechanism of metabolic regulation. A protein interaction network analysis revealed that diverse interactions are modulated by protein crotonylation. These results suggest that lysine crotonylation is involved in a variety of biological processes. HSP70 is a crucial protein involved in protecting plant cells and tissues from thermal or abiotic stress responses, and HSP70 protein was found to be crotonylated in paper mulberry. This systematic analysis provides the first comprehensive analysis of lysine crotonylation in paper mulberry and provides important resources for further study on the regulatory mechanism and function of the lysine crotonylated proteome. [ABSTRACT FROM AUTHOR]

The average content of casein in yak milk is 40.2 g/L. Casein can be degraded by enzymatic digestion or food processing to produce abundant degradation peptides. International researchers have studied the degradation peptides of yak milk casein by using multiple techniques and methods, such as in vitro activity tests, cellular experiments, proteomics, bioinformatics, etc., and found that the degradation peptides have a wide range of functional activities that are beneficial to the human body, such as angiotensin-converting enzyme (ACE) inhibitory, antioxidant, anti-inflammatory, antidiabetic, antimicrobial, anticancer, and immunomodulatory activities, etc., and it has been proved that the types and strengths of functional activities are closely related to the structural characteristics of the peptides. This paper describes the characteristics of yak milk proteins, the functional activities, and mechanism of action of degraded peptides. Based on the types of functional activities of yak milk casein degradation peptides, we classified and elucidated the effects of structural factors, such as peptide molecular weight, peptide length, amino acid sequence, physicochemical properties, electrical charge, hydrophobicity, spatial conformation, chain length, and the type of enzyme on these activities. It reveals the great potential of yak milk casein degradation peptides as functional active peptide resources and as auxiliary treatments for diseases. It also provides important insights for analyzing yak casein degradation peptide activity and exploring high-value utilization. [ABSTRACT FROM AUTHOR]

This paper presents the first in-depth research on the biological and genomic properties of lytic rhizobiophage AP-J-162 isolated from the soils of the mountainous region of Dagestan (North Caucasus), which belongs to the centers of origin of cultivated plants, according to Vavilov N.I. The rhizobiophage host strains are nitrogen-fixing bacteria of the genus Sinorhizobium spp., symbionts of leguminous forage grasses. The phage particles have a myovirus virion structure. The genome of rhizobiophage AP-J-162 is double-stranded DNA of 471.5 kb in length; 711 ORFs are annotated and 41 types of tRNAs are detected. The closest phylogenetic relative of phage AP-J-162 is Agrobacterium phage Atu-ph07, but no rhizobiophages are known. The replicative machinery, capsid, and baseplate proteins of phage AP-J-162 are structurally similar to those of Escherichia phage T4, but there is no similarity between their tail protein subunits. Amino acid sequence analysis shows that 339 of the ORFs encode hypothetical or functionally relevant products, while the remaining 304 ORFs are unique. Additionally, 153 ORFs are similar to those of Atu_ph07, with one-third of the ORFs encoding different enzymes. The biological properties and genomic characteristics of phage AP-J-162 distinguish it as a unique model for exploring phage–microbe interactions with nitrogen-fixing symbiotic microorganisms. [ABSTRACT FROM AUTHOR]

CRNDE is considered an oncogene expressed as long non-coding RNA. Our previous paper is the only one reporting CRNDE as a micropeptide-coding gene. The amino acid sequence of this micropeptide (CRNDEP) has recently been confirmed by other researchers. This study aimed at providing a mass spectrometry (MS)-based validation of the CRNDEP sequence and an investigation of how the differential expression of CRNDE(P) influences the metabolism and chemoresistance of ovarian cancer (OvCa) cells. We also assessed cellular localization changes of CRNDEP, looked for its protein partners, and bioinformatically evaluated its RNA-binding capacities. Herein, we detected most of the CRNDEP sequence by MS. Moreover, our results corroborated the oncogenic role of CRNDE, portraying it as the gene impacting carcinogenesis at the stages of DNA transcription and replication, affecting the RNA metabolism, and stimulating the cell cycle progression and proliferation, with CRNDEP being detected in the centrosomes of dividing cells. We also showed that CRNDEP is located in nucleoli and revealed interactions of this micropeptide with p54, an RNA helicase. Additionally, we proved that high CRNDE(P) expression increases the resistance of OvCa cells to treatment with microtubule-targeted cytostatics. Furthermore, altered CRNDE(P) expression affected the activity of the microtubular cytoskeleton and the formation of focal adhesion plaques. Finally, according to our in silico analyses, CRNDEP is likely capable of RNA binding. All these results contribute to a better understanding of the CRNDE(P) role in OvCa biology, which may potentially improve the screening, diagnosis, and treatment of this disease. [ABSTRACT FROM AUTHOR]

Dapsone (DDS), Rifampicin (RIF) and Ofloxacin (OFL) are drugs recommended by the World Health Organization (WHO) for the treatment of leprosy. In the context of leprosy, resistance to these drugs occurs mainly due to mutations in the target genes (Folp1, RpoB and GyrA). It is important to monitor antimicrobial resistance in patients with leprosy. Therefore, we performed a meta-analysis of drug resistance in Mycobacterium leprae and the mutational profile of the target genes. In this paper, we limited the study period to May 2022 and searched PubMed, Web of Science (WOS), Scopus, and Embase databases for identified studies. Two independent reviewers extracted the study data. Mutation and drug-resistance rates were estimated in Stata 16.0. The results demonstrated that the drug-resistance rate was 10.18% (95% CI: 7.85–12.51). Subgroup analysis showed the highest resistance rate was in the Western Pacific region (17.05%, 95% CI:1.80 to 13.78), and it was higher after 2009 than before [(11.39%, 7.46–15.33) vs. 6.59% (3.66–9.53)]. We can conclude that the rate among new cases (7.25%, 95% CI: 4.65–9.84) was lower than the relapsed (14.26%, 95 CI%: 9.82–18.71). Mutation rates of Folp1, RpoB and GyrA were 4.40% (95% CI: 3.02–5.77), 3.66% (95% CI: 2.41–4.90) and 1.28% (95% CI: 0.87–1.71) respectively, while the rate for polygenes mutation was 1.73% (0.83–2.63). For further analysis, we used 368 drug-resistant strains as research subjects and found that codons (Ser, Pro, Ala) on RpoB, Folp1 and GyrA are the most common mutation sites in the determining region (DRDR). In addition, the most common substitution patterns of Folp1, RpoB, and GyrA are Pro→Leu, Ser→Leu, and Ala→Val. This study found that a higher proportion of patients has developed resistance to these drugs, and the rate has increased since 2009, which continue to pose a challenge to clinicians. In addition, the amino acid alterations in the sequence of the DRDR regions and the substitution patterns mentioned in the study also provide new ideas for clinical treatment options. [ABSTRACT FROM AUTHOR]

In this paper, the influence of external terahertz electromagnetic fields with different frequencies of 4 THz, 10 THz, 15 THz, and 20 THz on the permeability of the Kv1.2 voltage-gated potassium ion channel on the nerve cell membrane was studied using the combined model of the "Constant Electric Field-Ion Imbalance" method by molecular dynamics. We found that although the applied terahertz electric field does not produce strong resonance with the –C=O groups of the conservative sequence T-V-G-Y-G amino acid residue of the selective filter (SF) of the channel, it would affect the stability of the electrostatic bond between potassium ions and the carbonyl group of T-V-G-Y-G of SF, and it would affect the stability of the hydrogen bond between water molecules and oxygen atoms of the hydroxyl group of the 374THR side chain at the SF entrance, changing the potential and occupied states of ions in the SF and the occurrence probability of the permeation mode of ions and resulting in the change in the permeability of the channel. Compared with no external electric field, when the external electric field with 15 THz frequency is applied, the lifetime of the hydrogen bond is reduced by 29%, the probability of the "soft knock on" mode is decreased by 46.9%, and the ion flux of the channel is activated by 67.7%. Our research results support the view that compared to "direct knock-on", "soft knock-on" is a slower permeation mode. [ABSTRACT FROM AUTHOR]

The formation of mature mRNA requires cutting introns and splicing exons. The occurrence of splicing involves the participation of the spliceosome. Common spliceosomes mainly include five snRNPs: U1, U2, U4/U6, and U5. SF3a2, an essential component of spliceosome U2 snRNP, participates in splicing a series of genes. There is no definition of SF3a2 in plants. The paper elaborated on SF3a2s from a series of plants through protein sequence similarity. We constructed the evolutionary relationship of SF3a2s in plants. Moreover, we analyzed the similarities and differences in gene structure, protein structure, the cis-element of the promoter, and expression pattern; we predicted their interacting proteins and constructed their collinearity. We have preliminarily analyzed SF3a2s in plants and clarified the evolutionary relationship between different species; these studies can better serve for in-depth research on the members of the spliceosome in plants. [ABSTRACT FROM AUTHOR]

For over 20 years, bovine beta-casein has been a subject of increasing scientific interest because its genetic A1 variant during gastrointestinal digestion releases opioid-like peptide β-casomorphin-7 (β-CM-7). Since β-CM-7 is involved in the dysregulation of many physiological processes, there is a growing discussion of whether the consumption of the β-casein A1 variant has an influence on human health. In the last decade, the number of papers dealing with this problem has substantially increased. The newest clinical studies on humans showed a negative effect of variant A1 on serum glutathione level, digestive well-being, cognitive performance score in children, and mood score in women. Scientific reports in this field can affect the policies of dairy cattle breeders and the milk industry, leading to the elimination of allele A1 in dairy cattle populations and promoting milk products based on milk from cows with the A2A2 genotype. More scientific proof, especially in well-designed clinical studies, is necessary to determine whether a little difference in the β-casein amino acid sequence negatively affects the health of milk consumers. [ABSTRACT FROM AUTHOR]

Xylanases (EC 3.2.1.8) hydrolyze the hemicellulose of plant cell walls. Xylanases are used in the food and paper industries and for bioconversion of lignocellulose to biofuel. In this work, the producer-strain with four copies of the xAor xylanase gene was organized in two tandem copies for optimal expression in Komagataella phaffii T07 yeast. The secreted 35 kDa xylanase was purified from culture medium by gel filtration on Sephadex G-25 and anion exchange chromatography on DEAE-Sepharose 6HF. Tryptic peptides of the recombinant enzyme were analyzed by liquid chromatography-tandem mass spectrometry where the amino acid sequence corresponded to Protein Accession # O94163 for Endo-1,4-beta-xylanase from Aspergillus oryzae RIB40. The recombinant xylanase was produced in a bioreactor where the secreted enzyme hydrolyzed oat xylane with an activity of 258240 IU/mL. High activity in the culture medium suggested xylanase could be used for industrial applications without being purified or concentrated. The pH optimum for xylanase xAor was 7.5, though the enzyme was active from pH 2.5 to pH 10. Xylanase was active at temperatures from 35 °C to 85 °C with a maximum at 60 °C. In conclusion, this protocol yields soluble, secreted xylanase suitable for industrial scale production. [ABSTRACT FROM AUTHOR]

Synonymous variants, traditionally regarded as silent mutations due to their lack of impact on protein sequence, structure and function, have been the subject of increasing scrutiny. This commentary explores the emerging evidence challenging the notion of synonymous variants as functionally inert. Analysis of the activity of 70 synonymous variants in the HIV Tat transcription factor revealed that 50% of the variants exhibited significant deviations from wild-type activity. Our analysis supports previous work and raises important questions about the broader impact of non-silent synonymous variants in human genes. Considering the potential functional implications, the authors propose classifying such variants as "synonymous variants of uncertain silence" (sVUS), highlighting the need for cautious interpretation and further investigations in clinical and genetic testing settings. [ABSTRACT FROM AUTHOR]

A gene encoding a polysaccharide-degrading enzyme was cloned from the genome of the bacterium Nocardiopsis halotolerans. Analysis of the amino acid sequence of the protein showed the presence of the catalytic domain of the endo-1,4-β-xylanases of the GH11 family. The gene was amplified by PCR and ligated into the pPic9m vector. A recombinant producer based on Pichia pastoria was obtained. The production of the enzyme, which we called NhX1, was carried out in a 10 L fermenter. Enzyme production was 10.4 g/L with an activity of 927 U/mL. Purification of NhX1 was carried out using Ni-NTA affinity chromatography. The purified enzyme catalyzed the hydrolysis of xylan but not other polysaccharides. Endo-1,4-β-xylanase NhX1 showed maximum activity and stability at pH 6.0–7.0. The enzyme showed high thermal stability, remaining active at 90 °C for 20 min. With beechwood xylan, the enzyme showed Km 2.16 mg/mL and Vmax 96.3 U/mg. The products of xylan hydrolysis under the action of NhX1 were xylobiose, xylotriose, xylopentaose, and xylohexaose. Endo-1,4-β-xylanase NhX1 effectively saccharified xylan-containing products used for the production of animal feed. The xylanase described herein is a thermostable enzyme with biotechnological potential produced in large quantities by P. pastoria. [ABSTRACT FROM AUTHOR]

The skin of amphibians is a rich source of peptides with a wide range of biological activities. They are stored in secretory granules in an inactive form. Upon stimulation, they are secreted together with proteases into the skin. Once activated, they rapidly exert their biological effects, including fighting microorganisms and predators, while their excess is immediately destroyed by the released proteases. To keep bioactive peptides in their initial form, it is necessary to inhibit these enzymes. Several inhibitors for this purpose have previously been mentioned; however, there has not been any reliable comparison of their efficiency so far. Here, we studied the efficiency of methanol and hydrochloric and formic acids, as well as phenylmethylsulfonyl fluoride, in the inhibition of nine frog peptides with the known sequence, belonging to five families in the secretion of Pelophylax esculentus. The results demonstrated that methanol had the highest inhibitory efficiency, while phenylmethylsulfonyl fluoride was the least efficient, probably due to its instability in aqueous media. Possible cleavages between certain amino acid residues in the sequence were established for each of the inhibitors. These results may be helpful for future studies on the nature of proteases and on prediction of the possible cleavage sites in novel peptides. [ABSTRACT FROM AUTHOR]

In this work, we explored the intrinsic disorder status of the three members of the synuclein family of proteins—α-, β-, and γ-synucleins—and showed that although all three human synucleins are highly disordered, the highest levels of disorder are observed in γ-synuclein. Our analysis of the peculiarities of the amino acid sequences and modeled 3D structures of the human synuclein family members revealed that the pathological mutations A30P, E46K, H50Q, A53T, and A53E associated with the early onset of Parkinson's disease caused some increase in the local disorder propensity of human α-synuclein. A comparative sequence-based analysis of the synuclein proteins from various evolutionary distant species and evaluation of their levels of intrinsic disorder using a set of commonly used bioinformatics tools revealed that, irrespective of their origin, all members of the synuclein family analyzed in this study were predicted to be highly disordered proteins, indicating that their intrinsically disordered nature represents an evolutionary conserved and therefore functionally important feature. A detailed functional disorder analysis of the proteins in the interactomes of the human synuclein family members utilizing a set of commonly used disorder analysis tools showed that the human α-synuclein interactome has relatively higher levels of intrinsic disorder as compared with the interactomes of human β- and γ- synucleins and revealed that, relative to the β- and γ-synuclein interactomes, α-synuclein interactors are involved in a much broader spectrum of highly diversified functional pathways. Although proteins interacting with three human synucleins were characterized by highly diversified functionalities, this analysis also revealed that the interactors of three human synucleins were involved in three common functional pathways, such as the synaptic vesicle cycle, serotonergic synapse, and retrograde endocannabinoid signaling. Taken together, these observations highlight the critical importance of the intrinsic disorder of human synucleins and their interactors in various neuronal processes. [ABSTRACT FROM AUTHOR]

Henosepilachna vigintioctomaculata is distributed in several Asian countries. The larvae and adults often cause substantial economic losses to Solanaceae crops such as potato, tomato, eggplant, and Chinese boxthorn. Even though a chromosome-level genome has been documented, the expression profiles of genes involved in development are not determined. In this study, we constructed embryonic, larval, pupal, and adult transcriptomes, generated a comprehensive RNA-sequencing dataset including ~52 Gb of clean data, and identified 602,773,686 cleaned reads and 33,269 unigenes. A total of 18,192 unigenes were successfully annotated against NCBI nonredundant protein sequences, Swissprot, Eukaryotic Orthologous Groups, Gene Ontology (GO), or Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. There were 3580, 2040, 5160, 2496, 3008, and 3895 differentially expressed genes (DEGs) between adult/egg, egg/larval, larval/pupal, adult/pupal, egg/pupal, and adult/larval samples, respectively. GO and KEGG analyses of the DEGs highlighted several critical pathways associated with specific developing stages. This is the first comprehensive transcriptomic dataset encompassing all developmental stages in H. vigintioctomaculata. Our data may facilitate the exploitation of gene targets for pest control and can serve as a valuable gene resource for future molecular investigations. [ABSTRACT FROM AUTHOR]

The construction of peptides to mimic heterogeneous proteins such as type I collagen plays a pivotal role in deciphering their function and pathogenesis. However, progress in the field has been severely hampered by the lack of capability to create stable heterotrimers with desired functional sequences and without the effect of homotrimers. We have herein developed a set of triblock peptides that can assemble into collagen mimetic heterotrimers with desired amino acids and are free from the interference of homotrimers. The triblock peptides comprise a central collagen-like block and two oppositely charged N-/C-terminal blocks, which display inherent incompetency of homotrimer formation. The favorable electrostatic attraction between two paired triblock peptides with complementary terminal charged sequences promptly leads to stable heterotrimers with controlled chain composition. The independence of the collagen-like block from the two terminal blocks endows this system with the adaptability to incorporate desired amino acid sequences while maintaining the heterotrimer structure. The triblock peptides provide a versatile and robust tool to mimic the composition and function of heterotrimer collagen and may have great potential in the design of innovative peptides mimicking heterogeneous proteins. [ABSTRACT FROM AUTHOR]

Food allergies mediated by specific IgE (sIgE) have a significant socioeconomic impact on society. Evaluating the IgE cross-reactivity between allergens from different allergen sources can enable the better management of these potentially life-threatening adverse reactions to food proteins and enhance food safety. A novel banana fruit allergen, S-adenosyl-L-homocysteine hydrolase (SAHH), has been recently identified and its recombinant homolog was heterologously overproduced in E. coli. In this study, we performed a search in the NCBI (National Center for Biotechnology Information) for SAHH homologs in ryegrass, latex, and kiwifruit, all of which are commonly associated with pollen-latex-fruit syndrome. In addition, Western immunoblot analysis was utilized to identify the cross-reactive IgE to banana SAHH in the sera of patients with a latex allergy, kiwifruit allergy, and ryegrass allergy. ClustalOmega analysis showed more than 92% amino acid sequence identity among the banana SAHH homologs in ryegrass, latex, and kiwifruit. In addition to five B-cell epitopes, in silico analysis predicted eleven T-cell epitopes in banana SAHH, seventeen in kiwifruit SAHH, twelve in ryegrass SAHH, and eight in latex SAHH, which were related to the seven-allele HLA reference set (HLA-DRB1*03:01, HLA-DRB1*07:01, HLA-DRB1*15:01, HLA-DRB3*01:01, HLA-DRB3*02:02, HLA-DRB4*01:01, HLA-DRB5*01:01). Four T-cell epitopes were identical in banana and kiwifruit SAHH (positions 328, 278, 142, 341), as well as banana and ryegrass SAHH (positions 278, 142, 96, and 341). All four SAHHs shared two T-cell epitopes (positions 278 and 341). In line with the high amino acid sequence identity and B-cell epitope homology among the analyzed proteins, the cross-reactive IgE to banana SAHH was detected in three of three latex-allergic patients, five of six ryegrass-allergic patients, and two of three kiwifruit-allergic patients. Although banana SAHH has only been studied in a small group of allergic individuals, it is a novel cross-reactive food allergen that should be considered when testing for pollen-latex-fruit syndrome. [ABSTRACT FROM AUTHOR]

Synthetic polymers, commonly known as plastics, are currently present in all aspects of our lives. Although they are useful, they present the problem of what to do with them after their lifespan. There are currently mechanical and chemical methods to treat plastics, but these are methods that, among other disadvantages, can be expensive in terms of energy or produce polluting gases. A more environmentally friendly alternative is recycling, although this practice is not widespread. Based on the practice of the so-called circular economy, many studies are focused on the biodegradation of these polymers by enzymes. Using enzymes is a harmless method that can also generate substances with high added value. Novel and enhanced plastic-degrading enzymes have been obtained by modifying the amino acid sequence of existing ones, especially on their active site, using a wide variety of genetic approaches. Currently, many studies focus on the common aim of achieving strains with greater hydrolytic activity toward a different range of plastic polymers. Although in most cases the depolymerization rate is improved, more research is required to develop effective biodegradation strategies for plastic recycling or upcycling. This review focuses on a compilation and discussion of the most important research outcomes carried out on microbial biotechnology to degrade and recycle plastics. [ABSTRACT FROM AUTHOR]

The development of turn-based inhibitors of protein–protein interactions has attracted considerable attention in medicinal chemistry. Our group has synthesized a series of peptides derived from an amino-functionalized ferrocene to investigate their potential to mimic protein turn structures. Detailed DFT and spectroscopic studies (IR, NMR, CD) have shown that, for peptides, the backbone chirality and bulkiness of the amino acid side chains determine the hydrogen-bond pattern, allowing tuning of the size of the preferred hydrogen-bonded ring in turn-folded structures. However, their biological potential is more dependent on their lipophilicity. In addition, our pioneering work on the chiroptical properties of aminoferrocene-containing peptides enables the correlation of their geometry with the sign of the CD signal in the absorption region of the ferrocene chromophore. These studies have opened up the possibility of using aminoferrocene and its derivatives as chirooptical probes for the determination of various chirality elements, such as the central chirality of amino acids and the helicity of peptide sequences. [ABSTRACT FROM AUTHOR]

Marine algal lectins specific for high-mannose N-glycans have attracted attention because they strongly inhibit the entry of enveloped viruses, including influenza viruses and SARS-CoV-2, into host cells by binding to high-mannose-type N-glycans on viral surfaces. Here, we report a novel anti-influenza virus lectin (named HBL40), specific for complex-type N-glycans, which was isolated from a marine green alga, Halimeda borneensis. The hemagglutination activity of HBL40 was inhibited with both complex-type N-glycan and O-glycan-linked glycoproteins but not with high-mannose-type N-glycan-linked glycoproteins or any of the monosaccharides examined. In the oligosaccharide-binding experiment using 26 pyridylaminated oligosaccharides, HBL40 only bound to complex-type N-glycans with bi- and triantennary-branched sugar chains. The sialylation, core fucosylation, and the increased number of branched antennae of the N-glycans lowered the binding activity with HBL40. Interestingly, the lectin potently inhibited the infection of influenza virus (A/H3N2/Udorn/72) into NCI-H292 cells at IC50 of 8.02 nM by binding to glycosylated viral hemagglutinin (KD of 1.21 × 10−6 M). HBL40 consisted of two isolectins with slightly different molecular masses to each other that could be separated by reverse-phase HPLC. Both isolectins shared the same 16 N-terminal amino acid sequences. Thus, HBL40 could be useful as an antivirus lectin specific for complex-type N-glycans. [ABSTRACT FROM AUTHOR]

Salinity is one of the most serious threats to sustainable agriculture. The Salt Overly Sensitive (SOS) signaling pathway plays an important role in salinity tolerance in plants, and the SOS2 gene plays a critical role in this pathway. Mulberry not only has important economic value but also is an important ecological tree species; however, the roles of the SOS2 gene associated with salt stress have not been reported in mulberry. To gain insight into the response of mulberry to salt stress, SOS2 (designated MulSOS2) was cloned from mulberry (Morus atropurpurea Roxb), and sequence analysis of the amino acids of MulSOS2 showed that it shares some conserved domains with its homologs from other plant species. Our data showed that the MulSOS2 gene was expressed at different levels in different tissues of mulberry, and its expression was induced substantially not only by NaCl but also by ABA. In addition, MulSOS2 was exogenously expressed in Arabidopsis, and the results showed that under salt stress, transgenic MulSOS2 plants accumulated more proline and less malondialdehyde than the wild-type plants and exhibited increased tolerance to salt stress. Moreover, the MulSOS2 gene was transiently overexpressed in mulberry leaves and stably overexpressed in the hairy roots, and similar results were obtained for resistance to salt stress in transgenic mulberry plants. Taken together, the results of this study are helpful to further explore the function of the MulSOS2 gene, which provides a valuable gene for the genetic breeding of salt tolerance in mulberry. [ABSTRACT FROM AUTHOR]

Bioluminescent proteins are important for various cellular processes, such as gene expression analysis, drug discovery, bioluminescent imaging, toxicity determination, and DNA sequencing studies. Hence, the correct identification of bioluminescent proteins is of great importance both for helping genome annotation and providing a supplementary role to experimental research to obtain insight into bioluminescent proteins' functions. However, few computational methods are available for identifying bioluminescent proteins. Therefore, in this paper we develop a new method to predict bioluminescent proteins using a model based on position specific scoring matrix and auto covariance. Tested by 10-fold cross-validation and independent test, the accuracy of the proposed model reaches 85.17% for the training dataset and 90.71% for the testing dataset respectively. These results indicate that our predictor is a useful tool to predict bioluminescent proteins. This is the first study in which evolutionary information and local sequence environment information have been successfully integrated for predicting bioluminescent proteins. A web server (BLPre) that implements the proposed predictor is freely available. [ABSTRACT FROM AUTHOR]

Protein–protein interactions (PPIs) are essential for most living organisms’ process. Thus, detecting PPIs is extremely important to understand the molecular mechanisms of biological systems. Although many PPIs data have been generated by high-throughput technologies for a variety of organisms, the whole interatom is still far from complete. In addition, the high-throughput technologies for detecting PPIs has some unavoidable defects, including time consumption, high cost, and high error rate. In recent years, with the development of machine learning, computational methods have been broadly used to predict PPIs, and can achieve good prediction rate. In this paper, we present here PCVMZM, a computational method based on a Probabilistic Classification Vector Machines (PCVM) model and Zernike moments (ZM) descriptor for predicting the PPIs from protein amino acids sequences. Specifically, a Zernike moments (ZM) descriptor is used to extract protein evolutionary information from Position-Specific Scoring Matrix (PSSM) generated by Position-Specific Iterated Basic Local Alignment Search Tool (PSI-BLAST). Then, PCVM classifier is used to infer the interactions among protein. When performed on PPIs datasets of Yeast and H. Pylori, the proposed method can achieve the average prediction accuracy of 94.48% and 91.25%, respectively. In order to further evaluate the performance of the proposed method, the state-of-the-art support vector machines (SVM) classifier is used and compares with the PCVM model. Experimental results on the Yeast dataset show that the performance of PCVM classifier is better than that of SVM classifier. The experimental results indicate that our proposed method is robust, powerful and feasible, which can be used as a helpful tool for proteomics research. [ABSTRACT FROM AUTHOR]

Caffeic acid O-methyltransferase (COMT) participates in various physiological activities in plants, such as positive responses to abiotic stresses and the signal transduction of phytohormones. In this study, 18 COMT genes were identified in the chromosome-level reference genome of mango, named MiCOMTs. A phylogenetic tree containing nine groups (I-IX) was constructed based on the amino acid sequences of the 71 COMT proteins from seven species. The phylogenetic tree indicated that the members of the MiCOMTs could be divided into four groups. Quantitative real-time PCR showed that all MiCOMT genes have particularly high expression levels during flowering. The expression levels of MiCOMTs were different under abiotic and biotic stresses, including salt and stimulated drought stresses, ABA and SA treatment, as well as Xanthomonas campestris pv. mangiferaeindicae and Colletotrichum gloeosporioides infection, respectively. Among them, the expression level of MiCOMT1 was significantly up-regulated at 6–72 h after salt and stimulated drought stresses. The results of gene function analysis via the transient overexpression of the MiCOMT1 gene in Nicotiana benthamiana showed that the MiCOMT1 gene can promote the accumulation of ABA and MeJA, and improve the salt tolerance of mango. These results are beneficial to future researchers aiming to understand the biological functions and molecular mechanisms of MiCOMT genes. [ABSTRACT FROM AUTHOR]

The GRAS (GAI\RGA\SCL) gene family encodes plant-specific transcription factors that play crucial roles in plant growth and development, stress tolerance, and hormone network regulation. Plant dwarfing symptom is mainly regulated by DELLA proteins of the GRAS gene subfamily. In this study, the association between the GRAS gene family and Paulownia witches' broom (PaWB) was investigated. A total of 79 PfGRAS genes were identified using bioinformatics methods and categorized into 11 groups based on amino acid sequences. Tandem duplication and fragment duplication were found to be the main modes of amplification of the PfGRAS gene family. Gene structure analysis showed that more than 72.1% of the PfGRASs had no introns. The genes PfGRAS12/18/58 also contained unique DELLA structural domains; only PfGRAS12, which showed significant response to PaWB phytoplasma infection in stems, showed significant tissue specificity and responded to gibberellin (GA3) in PaWB-infected plants. We found that the internodes were significantly elongated under 100 µmol·L−1 GA3 treatment for 30 days. The subcellular localization analysis indicated that PfGRAS12 is located in the nucleus and cell membrane. Yeast two-hybrid (Y2H) and bimolecular fluorescence complementation (BiFC) assays confirmed that PfGRAS12 interacted with PfJAZ3 in the nucleus. Our results will lay a foundation for further research on the functions of the PfGRAS gene family and for genetic improvement and breeding of PaWB-resistant trees. [ABSTRACT FROM AUTHOR]

Autophagy is a fundamental process for plants that plays a crucial role in maintaining cellular homeostasis and promoting survival in response to various environmental stresses. One of the lesser-known stages of plant autophagy is the degradation of autophagic bodies in vacuoles. To this day, no plant vacuolar enzyme has been confirmed to be involved in this process. On the other hand, several enzymes have been described in yeast (Saccharomyces cerevisiae), including Atg15, that possess lipolytic activity. In this preliminary study, which was conducted on isolated embryonic axes of the white lupin (Lupinus albus L.) and Andean lupin (Lupinus mutabilis Sweet), the potential involvement of plant vacuolar lipases in the degradation of autophagic bodies was investigated. We identified in transcriptomes (using next-generation sequencing (NGS)) of white and Andean lupin embryonic axes 38 lipases with predicted vacuolar localization, and for three of them, similarities in amino acid sequences with yeast Atg15 were found. A comparative transcriptome analysis of lupin isolated embryonic axes cultured in vitro under different sucrose and asparagine nutrition, evaluating the relations in the levels of the transcripts of lipase genes, was also carried out. A clear decrease in lipase gene transcript levels caused by asparagine, a key amino acid in lupin seed metabolism which retards the degradation of autophagic bodies during sugar-starvation-induced autophagy in lupin embryonic axes, was detected. Although the question of whether lipases are involved in the degradation of autophagic bodies during plant autophagy is still open, our findings strongly support such a hypothesis. [ABSTRACT FROM AUTHOR]

The aim of this work is the full characterization of all the nocturnin (noc) paralogues expressed in a teleost, the goldfish. An in silico analysis of the evolutive origin of noc in Osteichthyes is performed, including the splicing variants and new paralogues appearing after teleostean 3R genomic duplication and the cyprinine 4Rc. After sequencing the full-length mRNA of goldfish, we obtained two isoforms for noc-a (noc-aa and noc-ab) with two splice variants (I and II), and only one for noc-b (noc-bb) with two transcripts (II and III). Using the splicing variant II, the prediction of the secondary and tertiary structures renders a well-conserved 3D distribution of four α-helices and nine β-sheets in the three noc isoforms. A synteny analysis based on the localization of noc genes in the patrilineal or matrilineal subgenomes and a phylogenetic tree of protein sequences were accomplished to stablish a classification and a long-lasting nomenclature of noc in goldfish, and valid to be extrapolated to allotetraploid Cyprininae. Finally, both goldfish and zebrafish showed a broad tissue expression of all the noc paralogues. Moreover, the enriched expression of specific paralogues in some tissues argues in favour of neo- or subfunctionalization. [ABSTRACT FROM AUTHOR]

Protein-Protein Interactions (PPIs) play essential roles in most cellular processes. Knowledge of PPIs is becoming increasingly more important, which has prompted the development of technologies that are capable of discovering large-scale PPIs. Although many high-throughput biological technologies have been proposed to detect PPIs, there are unavoidable shortcomings, including cost, time intensity, and inherently high false positive and false negative rates. For the sake of these reasons, in silico methods are attracting much attention due to their good performances in predicting PPIs. In this paper, we propose a novel computational method known as RVM-AB that combines the Relevance Vector Machine (RVM) model and Average Blocks (AB) to predict PPIs from protein sequences. The main improvements are the results of representing protein sequences using the AB feature representation on a Position Specific Scoring Matrix (PSSM), reducing the influence of noise using a Principal Component Analysis (PCA), and using a Relevance Vector Machine (RVM) based classifier. We performed five-fold cross-validation experiments on yeast and Helicobacter pylori datasets, and achieved very high accuracies of 92.98% and 95.58% respectively, which is significantly better than previous works. In addition, we also obtained good prediction accuracies of 88.31%, 89.46%, 91.08%, 91.55%, and 94.81% on other five independent datasets C. elegans, M. musculus, H. sapiens, H. pylori, and E. coli for cross-species prediction. To further evaluate the proposed method, we compare it with the state-of-the-art support vector machine (SVM) classifier on the yeast dataset. The experimental results demonstrate that our RVM-AB method is obviously better than the SVM-based method. The promising experimental results show the efficiency and simplicity of the proposed method, which can be an automatic decision support tool. To facilitate extensive studies for future proteomics research, we developed a freely available web server called RVMAB-PPI in Hypertext Preprocessor (PHP) for predicting PPIs. The web server including source code and the datasets are available at http://219.219.62.123:8888/ppi_ab/. [ABSTRACT FROM AUTHOR]

Proteins and RNA interaction have vital roles in many cellular processes such as protein synthesis, sequence encoding, RNA transfer, and gene regulation at the transcriptional and post-transcriptional levels. Approximately 6%-8% of all proteins are RNA-binding proteins (RBPs). Distinguishing these RBPs or their binding residues is a major aim of structural biology. Previously, a number of experimental methods were developed for the determination of protein-RNA interactions. However, these experimental methods are expensive, time-consuming, and labor-intensive. Alternatively, researchers have developed many computational approaches to predict RBPs and protein-RNA binding sites, by combining various machine learning methods and abundant sequence and/or structural features. There are three kinds of computational approaches, which are prediction from protein sequence, prediction from protein structure, and protein-RNA docking. In this paper, we review all existing studies of predictions of RNA-binding sites and RBPs and complexes, including data sets used in different approaches, sequence and structural features used in several predictors, prediction method classifications, performance comparisons, evaluation methods, and future directions. [ABSTRACT FROM AUTHOR]

Bioluminescent proteins are important for various cellular processes, such as gene expression analysis, drug discovery, bioluminescent imaging, toxicity determination, and DNA sequencing studies. Hence, the correct identification of bioluminescent proteins is of great importance both for helping genome annotation and providing a supplementary role to experimental research to obtain insight into bioluminescent proteins' functions. However, few computational methods are available for identifying bioluminescent proteins. Therefore, in this paper we develop a new method to predict bioluminescent proteins using a model based on position specific scoring matrix and auto covariance. Tested by 10-fold cross-validation and independent test, the accuracy of the proposed model reaches 85.17% for the training dataset and 90.71% for the testing dataset respectively. These results indicate that our predictor is a useful tool to predict bioluminescent proteins. This is the first study in which evolutionary information and local sequence environment information have been successfully integrated for predicting bioluminescent proteins. A web server (BLPre) that implements the proposed predictor is freely available.

SLURP-1 is a three-finger human protein targeting nicotinic acetylcholine receptors (nAChRs). The recombinant forms of SLURP-1 produced in E. coli differ in added fusion fragments and in activity. The closest in sequence to the naturally occurring SLURP-1 is the recombinant rSLURP-1, differing by only one additional N-terminal Met residue. sSLURP-1 can be prepared by peptide synthesis and its amino acid sequence is identical to that of the natural protein. In view of recent NMR analysis of the conformational mobility of rSLURP-1 and cryo-electron microscopy structures of complexes of α-bungarotoxin (a three-finger snake venom protein) with Torpedo californica and α7 nAChRs, we compared conformations of sSLURP-1 and rSLURP-1 by Raman spectroscopy and CD-controlled thermal denaturation, analyzed their competition with α-bungarotoxin for binding to the above-mentioned nAChRs, compared the respective receptor complexes with computer modeling and compared their inhibitory potency on the α9α10 nAChR. The CD revealed a higher thermostability of sSLURP-1; some differences between sSLURP-1 and rSLURP-1 were observed in the regions of disulfides and tyrosine residues by Raman spectroscopy, but in binding, computer modeling and electrophysiology, the proteins were similar. Thus, sSLURP-1 and rSLURP-1 with only one additional Met residue appear close in structure and functional characteristics, being appropriate for research on nAChRs. [ABSTRACT FROM AUTHOR]

Machine learning has been increasingly utilized in the field of protein engineering, and research directed at predicting the effects of protein mutations has attracted increasing attention. Among them, so far, the best results have been achieved by related methods based on protein language models, which are trained on a large number of unlabeled protein sequences to capture the generally hidden evolutionary rules in protein sequences, and are therefore able to predict their fitness from protein sequences. Although numerous similar models and methods have been successfully employed in practical protein engineering processes, the majority of the studies have been limited to how to construct more complex language models to capture richer protein sequence feature information and utilize this feature information for unsupervised protein fitness prediction. There remains considerable untapped potential in these developed models, such as whether the prediction performance can be further improved by integrating different models to further improve the accuracy of prediction. Furthermore, how to utilize large-scale models for prediction methods of mutational effects on quantifiable properties of proteins due to the nonlinear relationship between protein fitness and the quantification of specific functionalities has yet to be explored thoroughly. In this study, we propose an ensemble learning approach for predicting mutational effects of proteins integrating protein sequence features extracted from multiple large protein language models, as well as evolutionarily coupled features extracted in homologous sequences, while comparing the differences between linear regression and deep learning models in mapping these features to quantifiable functional changes. We tested our approach on a dataset of 17 protein deep mutation scans and indicated that the integrated approach together with linear regression enables the models to have higher prediction accuracy and generalization. Moreover, we further illustrated the reliability of the integrated approach by exploring the differences in the predictive performance of the models across species and protein sequence lengths, as well as by visualizing clustering of ensemble and non-ensemble features. [ABSTRACT FROM AUTHOR]

PsbS is one of the key photoprotective proteins, ensuring the tolerance of the photosynthetic apparatus (PSA) of a plant to abrupt changes in irradiance. Being a component of photosystem II, it provides the formation of quenching centers for excited states of chlorophyll in the photosynthetic antenna with an excess of light energy. The signal for "turning on" the photoprotective function of the protein is an excessive decrease in pH in the thylakoid lumen occurring when all the absorbed light energy (stored in the form of transmembrane proton potential) cannot be used for carbon assimilation. Hence, lumen-exposed protonatable amino acid residues that could serve as pH sensors are the essential components of PsbS-dependent photoprotection, and their pKa values are necessary to describe it. Previously, calculations of the lumen-exposed protonatable residue pKa values in PsbS from spinach were described in the literature. However, it has recently become clear that PsbS, although typical of higher plants and charophytes, can also provide photoprotection in green algae. Namely, the stress-induced expression of PsbS was recently shown for two green microalgae species: Chlamydomonas reinhardtii and Lobosphaera incisa. Therefore, we determined the amino acid sequence and modeled the three-dimensional structure of the PsbS from L. incisa, as well as calculated the pKa values of its lumen-exposed protonatable residues. Despite significant differences in amino acid sequence, proteins from L. incisa and Spinacia oleracea have similar three-dimensional structures. Along with the other differences, one of the two pH-sensing glutamates in PsbS from S. oleracea (namely, Glu-173) has no analogue in L. incisa protein. Moreover, there are only four glutamate residues in the lumenal region of the L. incisa protein, while there are eight glutamates in S. oleracea. However, our calculations show that, despite the relative deficiency in protonatable residues, at least two residues of L. incisa PsbS can be considered probable pH sensors: Glu-87 and Lys-196. [ABSTRACT FROM AUTHOR]

Lysozyme amyloidosis is caused by an amino acid substitution in the sequence of this protein. In our study, we described a clinical case of lysozyme amyloidosis in a Russian family. In our work, we described in detail the histological changes in tissues that appeared as a result of massive deposition of amyloid aggregates that affected almost all organ systems, with the exception of the central nervous system. We determined the type of amyloidosis and mutations using mass spectrometry. Using mass spectrometry, the protein composition of tissue samples of patient 1 (autopsy material) and patient 2 (biopsy material) with histologically confirmed amyloid deposits were analyzed. Amino acid substitutions p.F21L/T88N in the lysozyme sequence were identified in both sets of samples and confirmed by sequencing of the lysozyme gene of members of this family. We have shown the inheritance of these mutations in the lysozyme gene in members of the described family. For the first time, we discovered a mutation in the first exon p.F21L of the lysozyme gene, which, together with p.T88N amino acid substitution, led to amyloidosis in members of the studied family. [ABSTRACT FROM AUTHOR]

Post-translational modifications (PTMs) play crucial roles in various cell functions and biological processes. Protein hydroxylation is one type of PTM that usually occurs at the sites of proline and lysine. Given an uncharacterized protein sequence, which site of its Pro (or Lys) can be hydroxylated and which site cannot? This is a challenging problem, not only for in-depth understanding of the hydroxylation mechanism, but also for drug development, because protein hydroxylation is closely relevant to major diseases, such as stomach and lung cancers. With the avalanche of protein sequences generated in the post-genomic age, it is highly desired to develop computational methods to address this problem. In view of this, a new predictor called "iHyd-PseAAC" (identify hydroxylation by pseudo amino acid composition) was proposed by incorporating the dipeptide position-specific propensity into the general form of pseudo amino acid composition. It was demonstrated by rigorous cross-validation tests on stringent benchmark datasets that the new predictor is quite promising and may become a useful high throughput tool in this area. A user-friendly web-server for iHyd-PseAAC is accessible at http://app.aporc.org/iHyd-PseAAC/. Furthermore, for the convenience of the majority of experimental scientists, a step-by-step guide on how to use the web-server is given. Users can easily obtain their desired results by following these steps without the need of understanding the complicated mathematical equations presented in this paper just for its integrity. [ABSTRACT FROM AUTHOR]

This article examines the presence of the empirical tendency known as the Menzerath–Altmann Law (MAL) on protein secondary structures. MAL is related to optimization principles observed in natural languages and in genetic information on chromosomes or protein domains. The presence of MAL is examined on a non-redundant dataset of 4728 proteins by verifying significant, negative correlations and testing classical and newly proposed formulas by fitting the observed trend. We conclude that the lengths of secondary structures are specifically dependent on their number inside the protein sequence, while possibly reflecting the formula proposed in this paper. This behavior is observed on average but is individually avoidable and possibly driven by a latent cost function. The data suggest that MAL could provide a useful guiding principle in protein design. [ABSTRACT FROM AUTHOR]

The protein structural entries grew far slower than the sequence entries. This is partly due to the bottleneck in obtaining diffraction quality protein crystals for structural determination using X-ray crystallography. The first step to achieve protein crystallization is to find out suitable chemical reagents. However, it is not an easy task. Exhausting trial and error tests of numerous combinations of different reagents mixed with the protein solution are usually necessary to screen out the pursuing crystallization conditions. Therefore, any attempts to help find suitable reagents for protein crystallization are helpful. In this paper, an analysis of the relationship between the protein sequence similarity and the crystallization reagents according to the information from the existing databases is presented. We extracted information of reagents and sequences from the Biological Macromolecule Crystallization Database (BMCD) and the Protein Data Bank (PDB) database, classified the proteins into different clusters according to the sequence similarity, and statistically analyzed the relationship between the sequence similarity and the crystallization reagents. The results showed that there is a pronounced positive correlation between them. Therefore, according to the correlation, prediction of feasible chemical reagents that are suitable to be used in crystallization screens for a specific protein is possible. [ABSTRACT FROM AUTHOR]

Antifreeze proteins (AFPs) are ice-binding proteins. Accurate identification of new AFPs is important in understanding ice-protein interactions and creating novel ice-binding domains in other proteins. In this paper, an accurate method, called AFP_PSSM, has been developed for predicting antifreeze proteins using a support vector machine (SVM) and position specific scoring matrix (PSSM) profiles. This is the first study in which evolutionary information in the form of PSSM profiles has been successfully used for predicting antifreeze proteins. Tested by 10-fold cross validation and independent test, the accuracy of the proposed method reaches 82.67% for the training dataset and 93.01% for the testing dataset, respectively. These results indicate that our predictor is a useful tool for predicting antifreeze proteins. A web server (AFP_PSSM) that implements the proposed predictor is freely available. [ABSTRACT FROM AUTHOR]

Ubiquitylation is an important process of post-translational modification. Correct identification of protein lysine ubiquitylation sites is of fundamental importance to understand the molecular mechanism of lysine ubiquitylation in biological systems. This paper develops a novel computational method to effectively identify the lysine ubiquitylation sites based on the ensemble approach. In the proposed method, 468 ubiquitylation sites from 323 proteins retrieved from the Swiss-Prot database were encoded into feature vectors by using four kinds of protein sequences information. An effective feature selection method was then applied to extract informative feature subsets. After different feature subsets were obtained by setting different starting points in the search procedure, they were used to train multiple random forests classifiers and then aggregated into a consensus classifier by majority voting. Evaluated by jackknife tests and independent tests respectively, the accuracy of the proposed predictor reached 76.82% for the training dataset and 79.16% for the test dataset, indicating that this predictor is a useful tool to predict lysine ubiquitylation sites. Furthermore, site-specific feature analysis was performed and it was shown that ubiquitylation is intimately correlated with the features of its surrounding sites in addition to features derived from the lysine site itself. The feature selection method is available upon request. [ABSTRACT FROM AUTHOR]

Identification of protein-protein interface residues is crucial for structural biology. This paper proposes a covering algorithm for predicting protein-protein interface residues with features including protein sequence profile and residue accessible area. This method adequately utilizes the characters of a covering algorithm which have simple, lower complexity and high accuracy for high dimension data. The covering algorithm can achieve a comparable performance (69.62%, Complete dataset; 60.86%, Trim dataset with overall accuracy) to a support vector machine and maximum entropy on our dataset, a correlation coefficient (CC) of 0.2893, 58.83% specificity, 56.12% sensitivity on the Complete dataset and 0.2144 (CC), 53.34% (specificity), 65.59% (sensitivity) on the Trim dataset in identifying interface residues by 5-fold cross-validation on 61 protein chains. This result indicates that the covering algorithm is a powerful and robust protein-protein interaction site prediction method that can guide biologists to make specific experiments on proteins. Examination of the predictions in the context of the 3-dimensional structures of proteins demonstrates the effectiveness of this method. [ABSTRACT FROM AUTHOR]

Diatoms synthesize species-specific exoskeletons inside cells under the control of the cytoskeleton and microtubule center. Previous studies have been conducted with the visualization of the microtubule center; however, its composition has not been studied and reliably established. In the present study, several components of MTOC in diatoms, GCP (gamma complex proteins), Aurora A, and centrins have been identified. Analysis of the predicted amino acid sequences of these proteins revealed structural features typical for diatoms. We analyzed the conserved amino acids and the motives necessary for the functioning of proteins. Phylogenetic analysis of GCP showed that all major groups of diatoms are distributed over phylogenetic trees according to their systematic position. This work is a theoretical study; however, it allows drawing some conclusions about the functioning of the studied components and possible ways to regulate them. [ABSTRACT FROM AUTHOR]

As crucial enzymes in the lipid metabolic network, long-chain acyl-CoA synthases (LACSs) are members of the acyl-activated enzyme superfamily and play a crucial role in epidermal wax synthesis, plant lipid anabolic metabolism, and stress tolerance. In this study, 11 pecan LACS genes were identified and categorized into five groups and located on nine chromosomes. The significant degree of conservation in the AtLACS and CiLACS protein sequences was demonstrated by multiple sequence alignment and conserved motif analysis. Cis-acting element analysis identified numerous stress-responsive and hormone-inducible elements in the promoter regions of CiLACS genes. The expression levels of CiLACS9 and CiLACS9-1 were considerably up-regulated under salt and drought stress, according to the qRT-RCR study. Treatment with ABA also led to increased expression levels of CiLACS1, CiLACS1-1, CiLACS2, and CiLACS9-1. Notably, CiLACS4, CiLACS4-1, CiLACS9, and CiLACS9-1 exhibited peak expression levels at 135 days after anthesis and are likely to have been crucial in the accumulation of seed kernel oil. Moreover, the CiLACS9 gene was shown to be located in the cytoplasm. These findings offer a theoretical framework for clarifying the roles of LACS genes in the processes of pecan kernel oil synthesis and response to abiotic stressors. [ABSTRACT FROM AUTHOR]

Anticancer peptides (ACPs) represent a promising new therapeutic approach in cancer treatment. They can target cancer cells without affecting healthy tissues or altering normal physiological functions. Machine learning algorithms have increasingly been utilized for predicting peptide sequences with potential ACP effects. This study analyzed four benchmark datasets based on a well-established random forest (RF) algorithm. The peptide sequences were converted into 566 physicochemical features extracted from the amino acid index (AAindex) library, which were then subjected to feature selection using four methods: light gradient-boosting machine (LGBM), analysis of variance (ANOVA), chi-squared test (Chi2), and mutual information (MI). Presenting and merging the identified features using Venn diagrams, 19 key amino acid physicochemical properties were identified that can be used to predict the likelihood of a peptide sequence functioning as an ACP. The results were quantified by performance evaluation metrics to determine the accuracy of predictions. This study aims to enhance the efficiency of designing peptide sequences for cancer treatment. [ABSTRACT FROM AUTHOR]

Recent findings qualified aldehydes as potential biomarkers for disease diagnosis. One of the possibilities is to use electrochemical biosensors in point-of-care (PoC), but these need further development to overcome some limitations. Currently, the primary goal is to enhance their metrological parameters in terms of sensitivity and selectivity. Previous findings indicate that peptide OBPP4 (KLLFDSLTDLKKKMSEC-NH2) is a promising candidate for further development of aldehyde-sensitive biosensors. To increase the affinity of a receptor layer to long-chain aldehydes, a structure stabilization of the peptide active site via the incorporation of different linkers was studied. Indeed, the incorporation of linkers improved sensitivity to and binding of aldehydes in comparison to that of the original peptide-based biosensor. The tendency to adopt disordered structures was diminished owing to the implementation of suitable linkers. Therefore, to improve the metrological characteristics of peptide-based piezoelectric biosensors, linkers were added at the C-terminus of OBPP4 peptide (KLLFDSLTDLKKKMSE-linker-C-NH2). Those linkers consist of proteinogenic amino acids from group one: glycine, L-proline, L-serine, and non proteinogenic amino acids from group two: β-alanine, 4-aminobutyric acid, and 6-aminohexanoic acid. Linkers were evaluated with in silico studies, followed by experimental verification. All studied linkers enhanced the detection of aldehydes in the gas phase. The highest difference in frequency (60 Hz, nonanal) was observed between original peptide-based biosensors and ones based on peptides modified with the GSGSGS linker. It allowed evaluation of the limit of detection for nonanal at the level of 2 ppm, which is nine times lower than that of the original peptide. The highest sensitivity values were also obtained for the GSGSGS linker: 0.3312, 0.4281, and 0.4676 Hz/ppm for pentanal, octanal, and nonanal, respectively. An order of magnitude increase in sensitivity was observed for the six linkers used. Generally, the linker's rigidity and the number of amino acid residues are much more essential for biosensors' metrological characteristics than the amino acid sequence itself. It was found that the longer the linkers, the better the effect on docking efficiency. [ABSTRACT FROM AUTHOR]

Protein solubility is based on the compatibility of the specific protein surface with the polar aquatic environment. The exposure of polar residues to the protein surface promotes the protein's solubility in the polar environment. The aquatic environment also influences the folding process by favoring the centralization of hydrophobic residues with the simultaneous exposure to polar residues. The degree of compatibility of the residue distribution, with the model of the concentration of hydrophobic residues in the center of the molecule, with the simultaneous exposure of polar residues is determined by the sequence of amino acids in the chain. The fuzzy oil drop model enables the quantification of the degree of compatibility of the hydrophobicity distribution observed in the protein to a form fully consistent with the Gaussian 3D function, which expresses an idealized distribution that meets the preferences of the polar water environment. The varied degrees of compatibility of the distribution observed with the idealized one allow the prediction of preferences to interactions with molecules of different polarity, including water molecules in particular. This paper analyzes a set of proteins with different levels of hydrophobicity distribution in the context of the solubility of a given protein and the possibility of complex formation. [ABSTRACT FROM AUTHOR]

Phosphate is one of the essential mineral nutrients. Phosphate transporter genes (PHTs) play an important role in Pi acquisition and homeostasis in tomato plants. However, basic biological information on PHT genes and their responses of symbiosis with arbuscular mycorrhizal in the genome remains largely unknown. We analyzed the physiological changes and PHT gene expression in tomatoes (Micro-Tom) inoculated with arbuscular mycorrhizal (AM) fungi (Funneliformis mosseae) under different phosphate conditions (P1: 0 µM, P2: 25 µM, and P3: 200 µM Pi). Twenty-three PHT genes were identified in the tomato genomics database. Protein sequence alignment further divided the 23 PHT genes into three groups, with similar classifications of exons and introns. Good colonization of plants was observed under low phosphate conditions (25 µM Pi), and Pi stress and AM fungi significantly affected P and N accumulation and root morphological plasticity. Moreover, gene expression data showed that genes in the SlPHT1 (SlPT3, SlPT4, and SlPT5) gene family were upregulated by Funneliformis mosseae under all conditions, which indicated that these gene levels were significantly increased with AM fungi inoculation. None of the analyzed SlPHT genes in the SlPH2, SlPHT3, SlPHT4, and SlPHO gene families were changed at any Pi concentration. Our results indicate that inoculation with AM fungi mainly altered the expression of the PHT1 gene family. These results will lay a foundation for better understanding the molecular mechanisms of inorganic phosphate transport under AM fungi inoculation. [ABSTRACT FROM AUTHOR]

Innovations in biocatalysts provide great prospects for intolerant environments or novel reactions. Due to the limited catalytic capacity and the long-term and labor-intensive characteristics of mining enzymes with the desired functions, de novo enzyme design was developed to obtain industrial application candidates in a rapid and convenient way. Here, based on the catalytic mechanisms and the known structures of proteins, we proposed a computational protein design strategy combining de novo enzyme design and laboratory-directed evolution. Starting with the theozyme constructed using a quantum-mechanical approach, the theoretical enzyme-skeleton combinations were assembled and optimized via the Rosetta "inside-out" protocol. A small number of designed sequences were experimentally screened using SDS-PAGE, mass spectrometry and a qualitative activity assay in which the designed enzyme 1a8uD1 exhibited a measurable hydrolysis activity of 24.25 ± 0.57 U/g towards p-nitrophenyl octanoate. To improve the activity of the designed enzyme, molecular dynamics simulations and the RosettaDesign application were utilized to further optimize the substrate binding mode and amino acid sequence, thus keeping the residues of theozyme intact. The redesigned lipase 1a8uD1–M8 displayed enhanced hydrolysis activity towards p-nitrophenyl octanoate—3.34 times higher than that of 1a8uD1. Meanwhile, the natural skeleton protein (PDB entry 1a8u) did not display any hydrolysis activity, confirming that the hydrolysis abilities of the designed 1a8uD1 and the redesigned 1a8uD1–M8 were devised from scratch. More importantly, the designed 1a8uD1–M8 was also able to hydrolyze the natural middle-chained substrate (glycerol trioctanoate), for which the activity was 27.67 ± 0.69 U/g. This study indicates that the strategy employed here has great potential to generate novel enzymes exhibiting the desired reactions. [ABSTRACT FROM AUTHOR]

Participating in both biotic and abiotic stress responses, plant-specific class III peroxidases (PERs) show promise as candidates for crop improvement. The multigenic PER family is known to take part in diverse functions, such as lignin formation and defense against pathogens. Traditionally linked to hydrogen peroxide (H2O2) consumption, PERs can also produce reactive oxygen species (ROS), essential in tissue development, pathogen defense and stress signaling. The amino acid sequences of both orthologues and paralogues of PERs are highly conserved, but discovering correlations between sequence differences and their functional diversity has proven difficult. By combining meta-analysis of transcriptomic data and sequence alignments, we discovered a correlation between three key amino acid positions and gene expression in response to biotic and abiotic stresses. Phylogenetic analysis revealed evolutionary pressure on these amino acids toward stress responsiveness. Using AlphaFold modeling, we found unique interdomain and protein–heme interactions involving those key amino acids in stress-induced PERs. Plausibly, these structural interactions may act as "gate keepers" by preventing larger substrates from accessing the heme and thereby shifting PER function from consumption to the production of ROS. [ABSTRACT FROM AUTHOR]

Inhibins suppress the FSH production in pituitary gonadotrope cells by robustly antagonizing activin signaling by competitively binding to activin type II receptors (ACTR II). The binding of inhibin A to ACTR II requires the presence of its co-receptor, namely, betaglycan. In humans, the critical binding site for betaglycan to inhibin A was identified on the inhibin α subunit. Through conservation analysis, we found that a core 13-amino-acid peptide sequence within the betaglycan-binding epitope on human inhibin α subunit is highly conserved across species. Based on the tandem sequence of such a conserved 13-amino-acid betaglycan-binding epitope (INHα13AA-T), we developed a novel inhibin vaccine and tested its efficacy in promoting female fertility using the female rat as a model. Compared with placebo-immunized controls, INHα13AA-T immunization induced a marked (p < 0.05) antibody generation, enhanced (p < 0.05) ovarian follicle development, and increased ovulation rate and litter sizes. Mechanistically, INHα13AA-T immunization promoted (p < 0.05) pituitary Fshb transcription and increased (p < 0.05) serum FSH and 17β-estradiol concentrations. In summary, active immunization against INHα13AA-T potently increased FSH levels, ovarian follicle development, ovulation rate and litter sizes, thus causing super-fertility in females. Therefore, immunization against INHα13AA is a promising alternative to the conventional approach of multiple ovulation and super-fertility in mammals. [ABSTRACT FROM AUTHOR]

Bovine mastitis is the most common disease affecting dairy cattle worldwide and it generates substantial losses for cattle breeders. One of the most common pathogens identified in infected milk samples is Staphylococcus aureus. Currently, there is no fast test for recognizing bacteria species on the market. The aim of this study was to bioinformatically and laboratory detect and characterize the fibronectin binding protein A (FnBPA) of S. aureus (SA) in milk samples obtained from cows diagnosed with mastitis. More than 90,000,000 amino acid sequences were subjected to bioinformatic detection in the search for a potential biomarker for bovine SA. The analysis of FnBPA included the detection of signal peptides and nonclassical proteins, antigenicity, and the prediction of epitopes. To confirm the presence of the fnbA gene in four SA isolates, amplification with specific primers was performed. FnBPA was detected by immunoblotting. The immunoreactivity and selectivity were performed with monoclonal anti-FnBPA antibodies and SA-negative serum. The bioinformatic analysis showed that FnBPA is a surface, conservative, immunoreactive, and species-specific protein with antigenic potential. Its presence was confirmed in all of the SA isolates we studied. Immunoblotting proved its immunoreactivity and specificity. Thus, it can be considered a potential biomarker in mastitis immunodiagnostics. [ABSTRACT FROM AUTHOR]

Helicases are nucleic acid-unwinding enzymes that are involved in the maintenance of genome integrity. Several parts of the amino acid sequences of helicases are very similar, and these quite well-conserved amino acid sequences are termed "helicase motifs". Previous studies by X-ray crystallography and single-molecule measurements have suggested a common underlying mechanism for their function. These studies indicate the role of the helicase motifs in unwinding nucleic acids. In contrast, the sequence and length of the C-terminal amino acids of helicases are highly variable. In this paper, I review past and recent studies that proposed helicase mechanisms and studies that investigated the roles of the C-terminal amino acids on helicase and dimerization activities, primarily on the non-hexermeric Escherichia coli (E. coli) UvrD helicase. Then, I center on my recent study of single-molecule direct visualization of a UvrD mutant lacking the C-terminal 40 amino acids (UvrDΔ40C) used in studies proposing the monomer helicase model. The study demonstrated that multiple UvrDΔ40C molecules jointly participated in DNA unwinding, presumably by forming an oligomer. Thus, the single-molecule observation addressed how the C-terminal amino acids affect the number of helicases bound to DNA, oligomerization, and unwinding activity, which can be applied to other helicases. [ABSTRACT FROM AUTHOR]