Dynamics of seminal fluid production after mating.

Seminal fluid proteins (SFPs) play vital roles for optimizing reproductive success in diverse animals. Underlining their significance, SFP production and transfer are highly plastic, e.g., depending on the presence of rivals or mating status of partners. However, surprisingly little is known about replenishing SFPs after mating. This is especially relevant in species that mate multiple times, as they continuously produce and use SFPs throughout their reproductive life. Here we examined the expression pattern of SFP genes after mating in the great pond snail, Lymnaea stagnalis. Our results show that two out of the six SFP genes investigated here were upregulated 1 week after mating. Surprisingly, most SFP genes did not change their expression immediately after mating. Even after 1 week, when supposedly seminal fluid is fully replenished, the expression of SFP genes is rather high. In addition, the difference with previous studies hints at the possibility that SFP production after mating is plastic and depends on the mating history of female-acting snails. Our results shed light on unexplored aspects of SFP production, thereby expanding the understanding of reproductive strategies in animals.

Synthesis and structural optimization of oncolytic peptide LTX-315.

Oncolytic peptides represented potential novel candidates for anticancer treatments especially drug-resistant cancer cell lines. One of the most promising and extensively studied is LTX-315, which is considered as the first in class oncolytic peptide and has entered phase I/II clinical trials. Nevertheless, the shortcomings including poor proteolytic stability, moderate anticancer durability and high synthesis costs may hinder the widespread clinical applications of LTX-315. In order to reduce the synthesis costs, as well as develop derivatives possessing both high protease-stability and durable anticancer efficiency, twenty LTX-315-based derived-peptides were designed and efficiently synthesized. Especially, through solid-phase S-alkylation, as well as the optimized peptide cleavage condition, the derived peptides could be prepared with drastically reduced synthesis cost. The in vitro anticancer efficiency, serum stability, anticancer durability, anti-migration activity, and hemolysis effect were systematically investigated. It was found that derived peptide MS-13 exhibited comparable anticancer efficiency and durability to those of LTX-315. Strikingly, the D-type peptide MS-20, which is the enantiomer of MS-13, was demonstrated to possess significantly high proteolytic stability and sustained anticancer durability. In general, the cost-effective synthesis and stability-guided structural optimizations were conducted on LTX-315, affording the highly hydrolysis resistant MS-20 which possessed durable anticancer activity. Meanwhile, this study also provided a reliable reference for the future optimization of anticancer peptides through the solid-phase S-alkylation and L-type to D-type amino acid substitutions.

The acyl carrier proteins of lipid synthesis are busy having other affairs.

This is a review of the acyl carrier proteins (ACPs) of type II fatty acid synthesis in bacteria and mitochondria, their structures and protein interactions. Type II fatty acid synthesis in bacteria (Prog. Lipid Res. (2013) 52, 249-276; Biochim. Biophys. Acta (1996) 1302, 1-16; Annu. Rev. Biochem. (2005) 74, 791-831) and in the mitochondria of yeast and mammals (Biochim. Biophys. Acta Mol. Cell. Res. (2019) 1866, 118540; MedChemComm (2019) 10, 209-220; Elife (2016) 5, e17828; Mol. Cell (2018) 71, 567-580.e4) will be discussed only tangentially in this review. The above references are excellent recent reviews. Bacterial fatty acid synthesis has been a popular target for the development of new antimicrobials and an up-to-date review of the field has been published (Annu. Rev. Microbiol. (2022) 76, 281-304). The ACP-like proteins of secondary metabolites (e.g. polyketide synthesis will not be reviewed). Escherichia coli ACP is now called AcpP to distinguish it from the enzymes that attach (AcpS) and remove (AcpH) the 4'-phosphopantetheine (4'PP) prosthetic group. Note that the primary translation product of the acpP gene is called apo-AcpP. The addition of the 4'PP prosthetic group converts apo-AcpP to holo-AcpP (commonly referred to as AcpP). Acylation of the 4'PP prosthetic group gives acyl-AcpP species. The length of the acyl chain determines the properties of the acyl-AcpP as will be discussed below.

Ketosynthase mutants enable short-chain fatty acid biosynthesis in E. coli.

Cells build fatty acids in tightly regulated assembly lines, or fatty acid synthases (FASs), in which ß-ketoacyl-acyl carrier protein (ACP) synthases (KSs) catalyze sequential carbon-carbon bond forming reactions that generate acyl-ACPs of varying lengths-precursors for a diverse set of lipids and oleochemicals. To date, most efforts to control fatty acid synthesis in engineered microbes have focused on modifying termination enzymes such as acyl-ACP thioesterases, which release free fatty acids from acyl-ACPs. Changes to the substrate specificity of KSs provide an alternative-and, perhaps, more generalizable-approach that focuses on controlling the acyl-ACPs available for downstream products. This study combines mutants of FabF and FabB, the two elongating KSs of the E. coli FAS, with in vitro and in vivo analyses to explore the use of KS mutants to control fatty acid synthesis. In vitro, single amino acid substitutions in the gating loop and acyl binding pocket of FabF shifted the product profiles of reconstituted FASs toward short chains and showed that KS mutants, alone, can cause large shifts in average length (i.e., 6.5-13.5). FabB, which is essential for unsaturated fatty acid synthesis, blunted this effect in vivo, but exogenously added cis-vaccenic acid (C18:1) enabled sufficient transcriptional repression of FabB to restore it. Strikingly, a single mutant of FabB afforded titers of octanoic acid as high as those generated by an engineered thioesterase. Findings indicate that fatty acid synthesis must be decoupled from microbial growth to resolve the influence of KS mutants on fatty acid profiles but show that these mutants offer a versatile approach for tuning FAS outputs.

Rational design of an anti-cancer peptide inhibiting CD147 / Cyp A interaction.

The CD147 / Cyp A interaction is a critical pathway in cancer types and an essential factor in entering the COVID-19 virus into the host cell. Melittin acts as an inhibitory peptide in cancer types by blocking the CD147/ Cyp A interaction. The clinical application of Melittin is limited due to weak penetration into cancer cells. TAT is an arginine-rich peptide with high penetration ability into cells widely used in drug delivery systems. This study aimed to design a hybrid peptide derived from Melittin and TAT to inhibit CD147 /Cyp A interaction. An amino acid region with high anti-cancer activity in Melittin was selected based on the physicochemical properties. Based on the results, a truncated Melittin peptide with 15 amino acids by the GGGS linker was fused to a TAT peptide (nine amino acids) to increase the penetration rate into the cell. A new hybrid peptide analog(TM) was selected by replacing the glycine with serine based on random point mutation. Docking results indicated that the TM peptide acts as an inhibitory peptide with high binding energy when interacting with CD147 and the CypA proteins. RMSD and RMSF results confirmed the high stability of the TM peptide in interaction with CD147. Also, the coarse-grained simulation showed the penetration potential of TM peptide into the DOPS-DOPC model membrane. Our findings indicated that the designed multifunctional peptide could be an attractive therapeutic candidate to halter tumor types and COVID-19 infection.

Metabolic flux analysis of the non-transitory starch tradeoff for lipid production in mature tobacco leaves.

The metabolic plasticity of tobacco leaves has been demonstrated via the generation of transgenic plants that can accumulate over 30% dry weight as triacylglycerols. In investigating the changes in carbon partitioning in these high lipid-producing (HLP) leaves, foliar lipids accumulated stepwise over development. Interestingly, non-transient starch was observed to accumulate with plant age in WT but not HLP leaves, with a drop in foliar starch concurrent with an increase in lipid content. The metabolic carbon tradeoff between starch and lipid was studied using 13CO2-labeling experiments and isotopically nonstationary metabolic flux analysis, not previously applied to the mature leaves of a crop. Fatty acid synthesis was investigated through assessment of acyl-acyl carrier proteins using a recently derived quantification method that was extended to accommodate isotopic labeling. Analysis of labeling patterns and flux modeling indicated the continued production of unlabeled starch, sucrose cycling, and a significant contribution of NADP-malic enzyme to plastidic pyruvate production for the production of lipids in HLP leaves, with the latter verified by enzyme activity assays. The results suggest an inherent capacity for a developmentally regulated carbon sink in tobacco leaves and may in part explain the uniquely successful leaf lipid engineering efforts in this crop.

agroString: Visibility and Provenance through a Private Blockchain Platform for Agricultural Dispense towards Consumers.

It is a known fact that large quantities of farm and meat products rot and are wasted if correct actions are not taken, which may lead to serious health issues if consumed. There is no proper system for tracking and communicating the status of the goods to their respective stakeholders in a secure way. Consumers have every right to know the quality of the products they consume. Using monitoring tools, such as the Internet of Agricultural Things (IoAT), and modern data protection techniques for storing and sharing, will help mitigate data integrity issues during the transmission of sensor records, increasing the data quality. The visibility state at the customer end is also improved, and they are aware of the agricultural product's conditions throughout the real-time distribution process. In this paper, we developed and implemented a CorDapp application to manage the data for the supply chain, called "agroString". We collected the temperature and humidity data using IoAT-Edge devices and various datasets from multiple sources. We then sent those readings to the CorDapp agroString and successfully shared them among the relevant parties. With the help of a Corda private blockchain, we attempted to increase data integrity, trust, visibility, provenance, and quality at each logistic step, while decreasing blockchain and central system limitations.

Antimicrobial Peptides as Anticancer Agents: Functional Properties and Biological Activities.

Antimicrobial peptides (AMPs), or host defense peptides, are small cationic or amphipathic molecules produced by prokaryotic and eukaryotic organisms that play a key role in the innate immune defense against viruses, bacteria and fungi. AMPs have either antimicrobial or anticancer activities. Indeed, cationic AMPs are able to disrupt microbial cell membranes by interacting with negatively charged phospholipids. Moreover, several peptides are capable to trigger cytotoxicity of human cancer cells by binding to negatively charged phosphatidylserine moieties which are selectively exposed on the outer surface of cancer cell plasma membranes. In addition, some AMPs, such as LTX-315, have shown to induce release of tumor antigens and potent damage associated molecular patterns by causing alterations in the intracellular organelles of cancer cells. Given the recognized medical need of novel anticancer drugs, AMPs could represent a potential source of effective therapeutic agents, either alone or in combination with other small molecules, in oncology. In this review we summarize and describe the properties and the mode of action of AMPs as well as the strategies to increase their selectivity toward specific cancer cells.

Atherosclerotic carotid plaque on panoramic radiographs: neural network detection.

AIM: Atherosclerotic carotid plaques (ACPs) constitute the main etiological factor in about 15% of strokes. ACPs can be detected on routine dental panoramic radiographs. As these are one of the most commonly performed dental images, they can be used as a source of available data for computerized methods of automatic detection of ACPs in order to significantly increase their timely diagnosis. The aim of this study was to present the potential of applying deep learning methodology to detect ACPs on routine panoramic radiographs with the ultimate goal of preventing strokes. METHODS: The Faster Region-based Convolutional Neural Network (Faster R-CNN) for deep learning was used. The operation of the algorithm was assessed on a small dataset of 65 panoramic images. As the available training data was limited, data augmentation was performed by changing the brightness and randomly flipping and rotating cropped regions of interest in multiple angles. Receiver operating characteristic (ROC) analysis was performed to calculate the accuracy of detection. RESULTS: ACPs were detected with a sensitivity of 75%, a specificity of 80%, and an accuracy of 83%. The ROC analysis showed a significant area under curve (AUC), different from 0.5. CONCLUSIONS: The novelty of the study lies in showing the efficiency of a deep learning method for the detection of ACPs on routine panoramic images based on a small dataset. Further improvement is needed as regards the application of the algorithm to the level of introducing this methodology in routine dental practice for stroke prevention.

A male's seminal fluid increases later competitors' productivity.

Polyandrous females allow for sexual selection to persist after mating. In the event that females successfully mate with more than one male, sperm competition can occur. Seminal fluid proteins can indirectly affect a male's success in sperm competition through reducing the remating behaviour of females and can directly influence sperm competition through directly displacing competitor sperm or inducing females to eject it. These direct effects on competitor sperm are thought to contribute to the 'second male advantage', whereby the second male to mate sires the majority of offspring. Here, we show an additional mechanism where seminal proteins already present within a mated female appear to enhance offspring production of later competitor males, and contribute to second male advantage. Counter to expectation, increased offspring production was not due to a priming effect of greater early female productivity, nor was it through a general and consistent increase in offspring production. Instead, enhanced productivity was solely through lengthening the time that offspring are sired by the second male, indicating that seminal proteins from the first male to mate may enhance second male advantage through a presumably unintended protective effect on subsequent competitor sperm.

ACPPfel: Explainable deep ensemble learning for anticancer peptides prediction based on feature optimization.

Background: Cancer is a significant global health problem that continues to cause a high number of deaths worldwide. Traditional cancer treatments often come with risks that can compromise the functionality of vital organs. As a potential alternative to these conventional therapies, Anticancer peptides (ACPs) have garnered attention for their small size, high specificity, and reduced toxicity, making them as a promising option for cancer treatments. Methods: However, the process of identifying effective ACPs through wet-lab screening experiments is time-consuming and requires a lot of labor. To overcome this challenge, a deep ensemble learning method is constructed to predict anticancer peptides (ACPs) in this study. To evaluate the reliability of the framework, four different datasets are used in this study for training and testing. During the training process of the model, integration of feature selection methods, feature dimensionality reduction measures, and optimization of the deep ensemble model are carried out. Finally, we explored the interpretability of features that affected the final prediction results and built a web server platform to facilitate anticancer peptides prediction, which can be used by all researchers for further studies. This web server can be accessed at http://lmylab.online:5001/. Results: The result of this study achieves an accuracy rate of 98.53% and an AUC (Area under Curve) value of 0.9972 on the ACPfel dataset, it has improvements on other datasets as well.

In silico investigations and molecular insights for designing tRNA-encoded peptides as potential therapeutics for targeting over-expressed receptors in breast cancer.

tRNA- Encoded Peptides (tREPs) have recently been discovered as new functional peptides and hold promise as therapeutics for anti-parasitic applications. In this study, in silico investigations were conducted to design tRNA-encoded peptides with the potential to target over-expressed receptors in breast cancer cells. tRNA genes were translated into corresponding peptides (tREPs) using computational tools. The tREPs, which were predicted as anticancer peptides, were then screened for various ADMET properties. Molecular docking studies were conducted for three cancer target receptors, the Estrogen Receptor (ER), Peroxisome Proliferator-Activated Receptor (PPAR) and the Epidermal Growth Factor Receptor (EGFR). Based on the docking results, specific tREPs were screened and molecular dynamics simulations were performed, and the binding energies were further explored using MMPBSA calculations. The peptide Pep1 (DWIAWRHHNDIVSWLTCGPRFKSWS) and Pep2 (GFIAWWSRHLELAQTRFKSWWS) exhibited a good binding affinity against the Estrogen Receptor (ER) and the Peroxisome Proliferator-Activated Receptor Alpha (PPAR) cancer target. The Pep1-ER and Pep1-PPAR complex maintained an average of two hydrogen bonds throughout the simulation and demonstrated a higher negative binding free energy of -72.27 kcal/mol and -65.16 kcal/mol respectively, as calculated by MMPBSA. Therefore, the tREPs designed as anticancer peptides in this study provide novel approaches for potential anticancer therapeutic modalities.Communicated by Ramaswamy H. Sarma.

Detection of soluble co-factor dependent protein expression in vivo: application to the 4'-phosphopantetheinyl transferase PptT from Mycobacterium tuberculosis.

The need for early-on diagnostic tools to assess the folding and solubility of expressed protein constructs in vivo is of great interest when dealing with recalcitrant proteins. In this paper, we took advantage of the picomolar sensitivity of the bipartite GFP1-10/GFP11 system to investigate the solubility of the Mycobacterium tuberculosis 4'-phosphopantetheinyl transferase PptT, an enzyme essential for the viability of the tubercle bacillus. In vivo and in vitro complementation assays clearly showed the improved solubility of the full-length PptT compared to its N- and C-terminally truncated counterparts. However, initial attempts to purify the full-length enzyme overexpressed in Escherichia coli cells were hampered by aggregation issues overtime that caused the protein to precipitate within hours. The fact that the naturally occurring Coenzyme A and Mg(2+), essentials for PptT to carry out its function, could play a role in stabilizing the enzyme was confirmed using DSF experiments. In vitro activity assays were performed using the ACP substrate from the type I polyketide synthase PpsC from M. tuberculosis, a 2188 amino-acid enzyme that plays a major role in the virulence and pathogenicity of this microbial pathogen. We selected the most soluble and compact ACP fragment (2042-2188), identified by genetic selection of in-frame fragments from random library experiments, to monitor the transfer of the P-pant moiety from Coenzyme A onto a conserved serine residue of this ACP domain.

The AT2 domain of KirCI loads malonyl extender units to the ACPs of the kirromycin PKS.

The antibiotic kirromycin is assembled by a hybrid modular polyketide synthases (PKSs)/nonribosomal peptide synthetases (NRPSs). Five of six PKSs of this complex assembly line do not have acyltransferase (AT) and have to recruit this activity from discrete AT enzymes. Here, we show that KirCI is a discrete AT which is involved in kirromycin production and displays a rarely found three-domain architecture (AT1-AT2-ER). We demonstrate that the second AT domain, KirCI-AT2, but not KirCI-AT1, is the malonyl-CoA-specific AT which utilizes this precursor for loading the acyl carrier proteins (ACPs) of the trans-AT PKS in vitro. In the kirromycin biosynthetic pathway, ACP5 is exclusively loaded with ethylmalonate by the enzyme KirCII and is not recognized as a substrate by KirCI. Interestingly, the excised KirCI-AT2 can also transfer malonate to ACP5 and thus has a relaxed ACP-specificity compared to the entire KirCI protein. The ability of KirCI-AT2 to load different ACPs provides opportunities for AT engineering as a potential strategy for polyketide diversification.

Bioinformatics evaluation of anticancer properties of GP63 protein-derived peptides on MMP2 protein of melanoma cancer.

Background: GP63, also known as Leishmanolysin, is a multifunctional virulence factor abundant on the surface of Leishmania spp. small peptides with anticancer capabilities that are selective and toxic to cancer cells are known as anticancer peptides. We aimed to demonstrate the activity of GP63 and its anticancer properties on melanoma using a range of in silico tools and screening methods to identify predicted and designed anticancer peptides. Methods: Various in silico modeling methodologies are used to establish the three-dimensional (3D) structure of GP63. Refinement and re-evaluation of the modeled structures and the built models' quality evaluated using the different docking used to find the interacting amino acids between MMP2 and GP63 and its anticancer peptides. AntiCP2.0 is used for screening anticancer peptides. 2D interaction plots of protein-ligand complexes evaluated by Protein-Ligand Interaction Profiler server. It is for the first time that used anticancer peptides of GP63 and the predicted and designed peptides. Results: We used 3 peptides of GP63 based on the AntiCP 2.0 server with scores of 0.63, 0.53, and 0.49, and common peptides of GP63/MMP2 (continues peptide: mean the completely selected peptide after docking with non-anticancer effect, predicted with 0.58 score and designed peptides with 0.47 and 0.45 scores by AntiCP 2.0 server). Conclusions: The antileishmanial and anticancer peptide research topics exemplify the multidisciplinary nature of peptide research. The advancement of therapeutics targeting cancer and/or Leishmania requires an interconnected research strategy shown in this work.

Peptide-Based Drug Predictions for Cancer Therapy Using Deep Learning.

Anticancer peptides (ACPs) are selective and toxic to cancer cells as new anticancer drugs. Identifying new ACPs is time-consuming and expensive to evaluate all candidates' anticancer abilities. To reduce the cost of ACP drug development, we collected the most updated ACP data to train a convolutional neural network (CNN) with a peptide sequence encoding method for initial in silico evaluation. Here we introduced PC6, a novel protein-encoding method, to convert a peptide sequence into a computational matrix, representing six physicochemical properties of each amino acid. By integrating data, encoding method, and deep learning model, we developed AI4ACP, a user-friendly web-based ACP distinguisher that can predict the anticancer property of query peptides and promote the discovery of peptides with anticancer activity. The experimental results demonstrate that AI4ACP in CNN, trained using the new ACP collection, outperforms the existing ACP predictors. The 5-fold cross-validation of AI4ACP with the new collection also showed that the model could perform at a stable level on high accuracy around 0.89 without overfitting. Using AI4ACP, users can easily accomplish an early-stage evaluation of unknown peptides and select potential candidates to test their anticancer activities quickly.

Predictive Significance of Enhanced Level of Angiogenesis and Tissue Neutrophils for Antrochoanal Polyps Recurrence in Children.

BACKGROUND: The pathologic features and potential predictive biomarkers for recurrence of antrochoanal polyps (ACPs) in children are not fully understood. OBJECTIVES: To identify the pathologic differences between recurrent and nonrecurrent group and to explore potential clinical markers which predict recurrence of ACPs in children. MATERIAL AND METHODS: A total of 11 recurrent and 21 nonrecurrent ACPs children were enrolled into this retrospect study. Clinical basic information was collected before the first surgery. The counts of vessels were evaluated by hematoxylin-eosin (HE) staining, and CD34 was detected by immunohistochemistry. Meanwhile, the percentage of each tissue inflammatory cells (eosinophils, neutrophils, lymphocytes, and plasma cells) was assessed by HE staining. RESULTS: No statistical significance was observed between the 2 groups in the basic clinical features. Moreover, both the counts of blood vessels and the tissue neutrophils percentage were enhanced significantly in group with ACPs recurrence (P < .05). According to the receiver operating characteristic curves, the area under the curve for the counts of blood vessels and tissue neutrophils percentage in the prediction of ACPs' recurrence was 0.779 (P = .0105) and 0.989 (P < .0001) respectively. CONCLUSIONS AND SIGNIFICANCE: It was concluded that the counts of blood vessels and the percentage of tissue neutrophils appeared to be potential excellent predictors of ACPs recurrence in children.

Role of Anti-Cancer Peptides as Immunomodulatory Agents: Potential and Design Strategy.

The usage of peptide-based drugs to combat cancer is gaining significance in the pharmaceutical industry. The collateral damage caused to normal cells due to the use of chemotherapy, radiotherapy, etc. has given an impetus to the search for alternative methods of cancer treatment. For a long time, antimicrobial peptides (AMPs) have been shown to display anticancer activity. However, the immunomodulatory activity of anti-cancer peptides has not been researched very extensively. The interconnection of cancer and immune responses is well-known. Hence, a search and design of molecules that can show anti-cancer and immunomodulatory activity can be lead molecules in this field. A large number of anti-cancer peptides show good immunomodulatory activity by inhibiting the pro-inflammatory responses that assist cancer progression. Here, we thoroughly review both the naturally occurring and synthetic anti-cancer peptides that are reported to possess both anti-cancer and immunomodulatory activity. We also assess the structural and biophysical parameters that can be utilized to improve the activity. Both activities are mostly reported by different groups, however, we discuss them together to highlight their interconnection, which can be used in the future to design peptide drugs in the field of cancer therapeutics.

Clinical Applications and Anticancer Effects of Antimicrobial Peptides: From Bench to Bedside.

Cancer is a multifaceted global health issue and one of the leading causes of death worldwide. In recent years, medical science has achieved great advances in the diagnosis and treatment of cancer. Despite the numerous advantages of conventional cancer therapies, there are major drawbacks including severe side effects, toxicities, and drug resistance. Therefore, the urgency of developing new drugs with low cytotoxicity and treatment resistance is increasing. Antimicrobial peptides (AMPs) have attracted attention as a novel therapeutic strategy for the treatment of various cancers, targeting tumor cells with less toxicity to normal tissues. In this review, we present the structure, biological function, and underlying mechanisms of AMPs. The recent experimental studies and clinical trials on anticancer peptides in different cancer types as well as the challenges of their clinical application have also been discussed.