Search

In proteomics, a crucial aspect is to identify peptide sequences. De novo sequencing methods have been widely employed to identify peptide sequences, and numerous tools have been proposed over the past two decades. Recently, deep learning approaches have been introduced for de novo sequencing. Previous methods focused on encoding tandem mass spectra and predicting peptide sequences from the first amino acid onwards. However, when predicting peptides using tandem mass spectra, the peptide sequence can be predicted not only from the first amino acid but also from the last amino acid due to the coexistence of b-ion (or a- or c-ion) and y-ion (or x- or z-ion) fragments in the tandem mass spectra. Therefore, it is essential to predict peptide sequences bidirectionally. Our approach, called NovoB, utilizes a Transformer model to predict peptide sequences bidirectionally, starting with both the first and last amino acids. In comparison to Casanovo, our method achieved an improvement of the average peptide-level accuracy rate of approximately 9.8% across all species. Author summary: Understanding the characteristics of data is very important in deep learning methods. When predicting sentences, the transformer model naturally predicts from the first word. For this reason, previous methods predicted peptide sequences from the first amino acid. However, in tandem mass spectra, it is possible to predict peptide sequences bidirectionally. This method shows better results than previous approaches because it can better encode tandem mass spectra. We have demonstrated that good results can be achieved simply by understanding the characteristics of such data and using the model appropriately. We hope that this paper will help various readers improve the performance capabilities of their models. Furthermore, given that bidirectional peptide sequence prediction is crucial in de novo peptide sequence analysis, we hope that this approach will be applied to both existing and future methods utilizing deep learning techniques. [ABSTRACT FROM AUTHOR]

With the increasing problem of antimicrobial drug resistance, the search for new antimicrobial agents has become a crucial task in the field of medicine. Antimicrobial peptides, as a class of naturally occurring antimicrobial agents, possess broad-spectrum antimicrobial activity and lower risk of resistance development. However, traditional screening methods for antimicrobial peptides are inefficient, necessitating the development of an efficient screening model. In this study, we aimed to develop an ensemble learning model for the identification of antimicrobial peptides, named E-CLEAP, based on the Multilayer Perceptron Classifier (MLP Classifier). By considering multiple features, including amino acid composition (AAC) and pseudo amino acid composition (PseAAC) of antimicrobial peptides, we aimed to improve the accuracy and generalization ability of the identification process. To validate the superiority of our model, we employed five-fold cross-validation and compared it with other commonly used methods for antimicrobial peptide identification. In the experimental results on an independent test set, E-CLEAP achieved accuracies of 97.33% and 84% for the AAC and PseAAC features, respectively. The results demonstrated that our model outperformed other methods in all evaluation metrics. The findings of this study highlight the potential of the E-CLEAP model in enhancing the efficiency and accuracy of antimicrobial peptide screening, which holds significant implications for drug development, disease treatment, and biotechnology advancement. Future research can further optimize the model by incorporating additional features and information, as well as validating its reliability on larger datasets and in real-world environments. The source code and all datasets are publicly available at https://github.com/Wangsicheng52/E-CLEAP. [ABSTRACT FROM AUTHOR]

A DNA cassette assembly method is described which utilizes inexpensive oligomers no longer than 40 nt in length. The five-segment cassettes have 20 nt overlaps which give an effective length of 80 nt, making it possible to code for peptides up to 20 amino acids long. The cassettes have three phosphate free nicks, which can be successfully inserted into plasmid DNA and used to transform E. coli. The nicks are repaired in vivo by an unknown mechanism. Insertions are not successful for cassettes with greater than three nicks. A procedure is provided for rapid turnaround from DNA design to peptides, which are easily isolated as C-terminal fusions with GFP. The technique generally gives the expected sequence, with errors which occur about 1% of the time. Several representative DNA inserts are described which illustrate the method, as well as chemical details on the new peptides coded for. The peptides can be readily mutated to make it possible to understand how polar and aromatic residues affect GFP-fusion solubility, and how histidine residues can be strategically placed in a peptide for good IMAC retention. The method can be used to explore a large number of new designed peptides as fusion products quickly and economically. [ABSTRACT FROM AUTHOR]

Development of novel biodosimetry assays and medical countermeasures is needed to obtain a level of radiation preparedness in the event of malicious or accidental mass exposures to ionizing radiation (IR). For biodosimetry, metabolic profiling with mass spectrometry (MS) platforms has identified several small molecules in easily accessible biofluids that are promising for dose reconstruction. As our microbiome has profound effects on biofluid metabolite composition, it is of interest how variation in the host microbiome may affect metabolomics based biodosimetry. Here, we 'knocked out' the microbiome of male and female C57BL/6 mice (Abx mice) using antibiotics and then irradiated (0, 3, or 8 Gy) them to determine the role of the host microbiome on biofluid radiation signatures (1 and 3 d urine, 3 d serum). Biofluid metabolite levels were compared to a sham and irradiated group of mice with a normal microbiome (Abx-con mice). To compare post-irradiation effects in urine, we calculated the Spearman's correlation coefficients of metabolite levels with radiation dose. For selected metabolites of interest, we performed more detailed analyses using linear mixed effect models to determine the effects of radiation dose, time, and microbiome depletion. Serum metabolite levels were compared using an ANOVA. Several metabolites were affected after antibiotic administration in the tryptophan and amino acid pathways, sterol hormone, xenobiotic and bile acid pathways (urine) and lipid metabolism (serum), with a post-irradiation attenuative effect observed for Abx mice. In urine, dose×time interactions were supported for a defined radiation metabolite panel (carnitine, hexosamine-valine-isoleucine [Hex-V-I], creatine, citric acid, and Nε,Nε,Nε-trimethyllysine [TML]) and dose for N1-acetylspermidine, which also provided excellent (AUROC ≥ 0.90) to good (AUROC ≥ 0.80) sensitivity and specificity according to the area under the receiver operator characteristic curve (AUROC) analysis. In serum, a panel consisting of carnitine, citric acid, lysophosphatidylcholine (LysoPC) (14:0), LysoPC (20:3), and LysoPC (22:5) also gave excellent to good sensitivity and specificity for identifying post-irradiated individuals at 3 d. Although the microbiome affected the basal levels and/or post-irradiation levels of these metabolites, their utility in dose reconstruction irrespective of microbiome status is encouraging for the use of metabolomics as a novel biodosimetry assay. [ABSTRACT FROM AUTHOR]

Globally, the rapid aging of the population is predicted to become even more severe in the second half of the 21st century. Thus, it is expected to establish a growing expectation for innovative, non-invasive health indicators and diagnostic methods to support disease prevention, care, and health promotion efforts. In this study, we aimed to establish a new health index and disease diagnosis method by analyzing the minerals and free amino acid components contained in hair shaft. We first evaluated the range of these components in healthy humans and then conducted a comparative analysis of these components in subjects with diabetes, hypertension, androgenetic alopecia, major depressive disorder, Alzheimer's disease, and stroke. In the statistical analysis, we first used a student's t test to compare the hair components of healthy people and those of patients with various diseases. However, many minerals and free amino acids showed significant differences in all diseases, because the sample size of the healthy group was very large compared to the sample size of the disease group. Therefore, we attempted a comparative analysis based on effect size, which is not affected by differences in sample size. As a result, we were able to narrow down the minerals and free amino acids for all diseases compared to t test analysis. For diabetes, the t test narrowed down the minerals to 15, whereas the effect size measurement narrowed it down to 3 (Cr, Mn, and Hg). For free amino acids, the t test narrowed it down to 15 minerals. By measuring the effect size, we were able to narrow it down to 7 (Gly, His, Lys, Pro, Ser, Thr, and Val). It is also possible to narrow down the minerals and free amino acids in other diseases, and to identify potential health indicators and disease-related components by using effect size. [ABSTRACT FROM AUTHOR]

The effects of jogi (the fish Atlantic croaker, Micropogonias undulatus) on the production of physicochemical components, such as color, organic acids, and amino acids, in kimchi, a traditional fermented vegetable food of Korea, were determined. As fermentation progressed, the color change of jogi-added kimchi increased, but in comparison with that of the control group without jogi-added kimchi, was difficult to distinguish with the naked eye. Reducing sugar decreased in all experimental groups, and as fermentation progressed, kimchi with jogi showed a lower value. Acetic acid, citric acid, lactic acid, and ethanol, were highly produced in both types of kimchi, and above all, the jogi—baechu—kimchi group showed higher acetic acid and lactic acid contents than the control group. The increase and decrease of amino acids were similar in both types of kimchi. However, significantly, immediately after manufacture, the savory components aspartic acid and glutamic acid were detected higher than the control group. Subsequently, the fermentation tended to decrease as it progressed, but the content was higher than that of the control group. The above results show that jogi addition has a greater effect on the contents of amino acid, especially the savory component, than on the physicochemical components. [ABSTRACT FROM AUTHOR]

Compound specific stable isotope analysis of amino acids (CSIA-AA) is a powerful tool for determining dietary behaviors in complex environments and improving dietary reconstructions. Here, we conducted CSIA-AA on human (n = 32) and animal (n = 13) remains from two prehistoric archaeological sites (Mumun, Imdang) to assess in more detail the dietary sources consumed by prehistoric Korean populations. Results of estimated trophic position (TP) using Δ15NGlx-Phe show that the Imdang individuals consumed aquatic resources, as well as terrestrial resources. Principal component analysis (PCA) using δ13C and δ15N essential amino acid (EAA) values show that the Imdang humans closely cluster with game birds and terrestrial herbivores, whilst the Mumun humans closely cluster with C4 plants. Quantitative estimation by a Bayesian mixing model (MixSIAR) indicates that the Imdang humans derived a large proportion of their proteins from terrestrial animals and marine fish, whereas the main protein sources for the Mumun humans were C4 plants and terrestrial animals. Additionally, the comparison between the EAA and bulk isotope models shows that there is a tendency to overestimate the consumption of plant proteins when using bulk isotopic data. Our CSIA-AA approach reveals that in prehistoric Korea there were clear differences in human diets through time. This study adds to a growing body of literature that demonstrates the potential of CSIA-AA to provide more accurate estimations of protein consumption in mixed diets than previous bulk isotopic studies. [ABSTRACT FROM AUTHOR]

Antimicrobial peptides (AMPs) are at the interface of interactions between hosts and microbes and are therefore expected to be rapidly evolving in a coevolutionary arms race with pathogens. In contrast, previous work demonstrated that insect AMPs tend to evolve more slowly than the genome average. Metchikowin (Mtk) is a Drosophila AMP that has a single amino acid residue that segregates as either proline (P) or arginine (R) in populations of four different species, some of which diverged more than 10 million years ago. These results suggest that there is a distinct functional importance to each allele. The most likely hypotheses are driven by two main questions: does each allele have a different efficacy against different specific pathogens (specificity hypothesis)? Or, is one allele a more potent antimicrobial, but with a host fitness cost (autoimmune hypothesis)? To assess their functional differences, we created D. melanogaster lines with the P allele, R allele, or Mtk null mutation using CRISPR/Cas9 genome editing and performed a series of life history and infection assays to assess them. In males, testing of systemic immune responses to a repertoire of bacteria and fungi demonstrated that the R allele performs as well or better than the P and null alleles with most infections. Females show some results that contrast with males, with Mtk alleles either not contributing to survival or with the P allele outperforming the R allele. In addition, measurements of life history traits demonstrate that the R allele is more costly in the absence of infection for both sexes. These results are consistent with both the specificity hypothesis (either allele can perform better against certain pathogens depending on context), and the autoimmune hypothesis (the R allele is generally the more potent antimicrobial in males, and carries a fitness cost). These results provide strong in vivo evidence that differential fitness with or without infection and sex-based functional differences in alleles may be adaptive mechanisms of maintaining immune gene polymorphisms in contrast with expectations of rapid evolution. Therefore, a complex interplay of forces including pathogen species and host sex may lead to balancing selection for immune genotypes. Strikingly, this selection may act on even a single amino acid polymorphism in an AMP. Author summary: Antimicrobial peptides (AMPs) are small peptides produced by many living organisms as a frontline immune response to a variety of microbial pathogens. These peptides directly interface with pathogens to kill them shortly after infection. Importantly, multiple AMP alleles can be balanced within a population, but little is known about how this immune variation among individuals is maintained over time. Multiple species of Drosophila balance two specific alleles of the AMP, Metchnikowin (Mtk), a canonically antifungal and antibacterial peptide. Here, various life-history and infection assays assess the mechanism of Metchnikowin balancing selection using CRISPR-generated D. melanogaster with a null mutation or either of the two alleles, MtkR or MtkP. Findings demonstrate that the MtkR allele usually confers greater protection than the MtkP allele in males, but carries a fitness cost without infection. However, this pattern flips in females with certain infections, with the MtkP allele conferring greater protection than MtkR. This suggests that the two alleles are repeatedly maintained in fly populations due to differential fitness of hosts in the context of many variables including host genotype, sex, infection status, and pathogen species. It also suggests that maintenance of immune variation in a population can be based on just a single amino acid difference between individuals. [ABSTRACT FROM AUTHOR]

Prokaryotic chromosomes contain numerous small open reading frames (ORFs) of less than 200 bases. Since high-throughput proteomics methods often miss proteins containing fewer than 60 amino acids, it is difficult to decern if they encode proteins. Recent studies have revealed that many small proteins are membrane proteins with a single membrane-anchoring α-helix. As membrane anchoring or transmembrane motifs are accurately identifiable with high confidence using computational algorithms like Phobius and TMHMM, small membrane proteins (SMPS) can be predicted with high accuracy. This study employed a systematic approach, utilizing well-verified algorithms such as Orfipy, Phobius, and Blast to identify SMPs in prokaryotic organisms. Our main search parameters targeted candidate SMPs with an open reading frame between 60–180 nucleotides, a membrane-anchoring or transmembrane region 15 and 30 amino acids long, and sequence conservation among other microorganisms. Our findings indicate that each prokaryote possesses many SMPs, with some identified in the intergenic regions of currently annotated chromosomes. More extensively studied microorganisms, such as Escherichia coli and Bacillus subtilis, have more SMPs identified in their genomes compared to less studied microorganisms, suggesting the possibility of undiscovered SMPs in less studied microorganisms. In this study, we describe the common SMPs identified across various microorganisms and explore their biological roles. We have also developed a software pipeline and an accompanying online interface for discovering SMPs (http://cs.indstate.edu/pro-smp-finder). This resource aims to assist researchers in identifying new SMPs encoded in microbial genomes of interest. [ABSTRACT FROM AUTHOR]

Newcastle disease virus (NDV) has been extensively studied as a promising oncolytic virus for killing tumor cells in vitro and in vivo in clinical trials. However, the viral components that regulate the oncolytic activity of NDV remain incompletely understood. In this study, we systematically compared the replication ability of different NDV genotypes in various tumor cells and identified NP protein determines the oncolytic activity of NDV. On the one hand, NDV strains with phenylalanine (F) at the 450th amino acid position of the NP protein (450th-F-NP) exhibit a loss of oncolytic activity. This phenotype is predominantly associated with genotype VII NDVs. In contrast, the NP protein with a leucine amino acid at this site in other genotypes (450th-L-NP) can facilitate the loading of viral mRNA onto ribosomes more effectively than 450th-F-NP. On the other hand, the NP protein from NDV strains that exhibit strong oncogenicity interacts with eIF4A1 within its 366–489 amino acid region, leading to the inhibition of cellular mRNA translation with a complex 5' UTR structure. Our study provide mechanistic insights into how highly oncolytic NDV strains selectively promote the translation of viral mRNA and will also facilitate the screening of oncolytic strains for oncolytic therapy. Author summary: The oncolytic potential of NDV has gained significant attention in the context of clinical trials. Therefore, it is crucial to systematically compare the oncolytic activities of different NDV subtypes and understand their underlying mechanisms. Our previous investigations revealed that genotype VII NDVs, predominant during the fourth epidemic, exhibit heightened avian pathogenicity compared to other subtypes. Interestingly, in tumor cells, NDV strains of varying virulence and genotypes possess some oncolytic capacity. However, in several genotype VII strains, the NP protein fails to facilitate the efficient loading of viral mRNA onto ribosomes. This is primarily attributed to the presence of phenylalanine at the 450th amino acid position of the NP protein. Additionally, it loses its ability to inhibit the eIF4A1-relative cellular mRNA translation through interaction with eIF4A1, mainly because of differences in its non-conserved region (366-489aa) of NP protein compared to other genotypes. These significantly hinder its ability to establish effective infections in tumor cells. Our study provides valuable insights for oncolytic NDV strain screening and enhances understanding of the functional role of NP protein. [ABSTRACT FROM AUTHOR]

Influenza A virus (FLUAV) infects a wide range of hosts and human-to-swine spillover events are frequently reported. However, only a few of these human viruses have become established in pigs and the host barriers and molecular mechanisms driving adaptation to the swine host remain poorly understood. We previously found that infection of pigs with a 2:6 reassortant virus (hVIC/11) containing the hemagglutinin (HA) and neuraminidase (NA) gene segments from the human strain A/Victoria/361/2011 (H3N2) and internal gene segments of an endemic swine strain (sOH/04) resulted in a fixed amino acid substitution in the HA (A138S, mature H3 HA numbering). In silico analysis revealed that S138 became predominant among swine H3N2 virus sequences deposited in public databases, while 138A predominates in human isolates. To understand the role of the HA A138S substitution in the adaptation of a human-origin FLUAV HA to swine, we infected pigs with the hVIC/11A138S mutant and analyzed pathogenesis and transmission compared to hVIC/11 and sOH/04. Our results showed that the hVIC/11A138S virus had an intermediary pathogenesis between hVIC/11 and sOH/04. The hVIC/11A138S infected the upper respiratory tract, right caudal, and both cranial lobes while hVIC/11 was only detected in nose and trachea samples. Viruses induced a distinct expression pattern of various pro-inflammatory cytokines such as IL-8, TNF-α, and IFN-β. Flow cytometric analysis of lung samples revealed a significant reduction of porcine alveolar macrophages (PAMs) in hVIC/11A138S-infected pigs compared to sOH/04 while a MHCIIlowCD163neg population was increased. The hVIC/11A138S showed a higher affinity for PAMs than hVIC/11, noted as an increase of infected PAMs in bronchoalveolar lavage fluid (BALF), and showed no differences in the percentage of HA-positive PAMs compared to sOH/04. This increased infection of PAMs led to an overexpression of granulocyte-monocyte colony-stimulating factor (GM-CSF) stimulation but a reduced expression of peroxisome proliferator-activated receptor gamma (PPARγ) in the sOH/04-infected group. Analysis using the PAM cell line 3D4/21 revealed that the A138S substitution improved replication and apoptosis induction in this cell type compared to hVIC/11 but at lower levels than sOH/04. Overall, our study indicates that adaptation of human viruses to the swine host involves an increased affinity for the lower respiratory tract and alveolar macrophages. Author summary: Human-to-swine FLUAV spillover events are relatively common and have led to the establishment of multiple evolutionarily distinct virus lineages in the swine population worldwide, leading to important economic losses in the pork industry. This also increases the risk of reassortment and emergence of novel FLUAV that may retain the ability to infect and transmit in humans, an event exemplified by the H1N1 pandemic in 2009. However, the molecular mechanisms driving FLUAV adaptation to pigs following the introduction of a human virus are still not fully understood. In this study we found that a point mutation in a human-origin HA improved infection and transmissibility in pigs characterized by an enhanced lung replication and the disruption of lung-resident immune cell populations. This relationship between improved replication and infectivity of lung-resident cells provides insights into host barriers limiting human FLUAV adaptation to pigs and the complexities associated with the host immune response that influenza A viruses must overcome to become established in the swine population. [ABSTRACT FROM AUTHOR]

Breast tumours are embedded in a collagen I-rich extracellular matrix (ECM) network, where nutrients are scarce due to limited blood flow and elevated tumour growth. Metabolic adaptation is required for cancer cells to endure these conditions. Here, we demonstrated that the presence of ECM supported the growth of invasive breast cancer cells, but not non-transformed mammary epithelial cells, under amino acid starvation, through a mechanism that required macropinocytosis-dependent ECM uptake. Importantly, we showed that this behaviour was acquired during carcinoma progression. ECM internalisation, followed by lysosomal degradation, contributed to the up-regulation of the intracellular levels of several amino acids, most notably tyrosine and phenylalanine. This resulted in elevated tyrosine catabolism on ECM under starvation, leading to increased fumarate levels, potentially feeding into the tricarboxylic acid (TCA) cycle. Interestingly, this pathway was required for ECM-dependent cell growth and invasive cell migration under amino acid starvation, as the knockdown of p-hydroxyphenylpyruvate hydroxylase-like protein (HPDL), the third enzyme of the pathway, opposed cell growth and motility on ECM in both 2D and 3D systems, without affecting cell proliferation on plastic. Finally, high HPDL expression correlated with poor prognosis in breast cancer patients. Collectively, our results highlight that the ECM in the tumour microenvironment (TME) represents an alternative source of nutrients to support cancer cell growth by regulating phenylalanine and tyrosine metabolism. Breast tumors are embedded in a collagen-rich extracellular matrix (ECM) network, where nutrients are scarce due to limited blood flow and elevated tumor growth. This study shows that invasive breast cancer cells use macropinocytosis-dependent uptake and lysosomal degradation of ECM to promote their growth. [ABSTRACT FROM AUTHOR]