Amino Acid Composition Research Articles

Antimicrobial neuropeptides and their therapeutic potential in vertebrate brain infectious disease

The defense mechanisms of the vertebrate brain against infections are at the forefront of immunological studies. Unlike other body parts, the brain not only fends off pathogenic infections but also minimizes the risk of self-damage from immune cell induced inflammation. Some neuropeptides produced by either nerve or immune cells share remarkable similarities with antimicrobial peptides (AMPs) in terms of size, structure, amino acid composition, amphiphilicity, and net cationic charge. These similarities extend to a wide range of antibacterial activities demonstrated in vitro, effectively protecting nerve tissue from microbial threats. This review systematically examines 12 neuropeptides, pituitary adenylate cyclase-activating peptide (PACAP), vasoactive intestinal peptide (VIP), α-melanocyte stimulating hormone (α-MSH), orexin-B (ORXB), ghrelin, substance P (SP), adrenomedullin (AM), calcitonin-gene related peptide (CGRP), urocortin-II (UCN II), neuropeptide Y (NPY), NDA-1, and catestatin (CST), identified for their antimicrobial properties, summarizing their structural features, antimicrobial effectiveness, and action mechanisms. Importantly, the majority of these antimicrobial neuropeptides (9 out of 12) also possess significant anti-inflammatory properties, potentially playing a key role in preserving immune tolerance in various disorders. However, the connection between this anti-inflammatory property and the brain’s infection defense strategy has rarely been explored. Our review suggests that the combined antimicrobial and anti-inflammatory actions of neuropeptides could be integral to the brain’s defense strategy against pathogens, marking an exciting direction for future research.

Designing proteins: Mimicking natural protein sequence heterogeneity.

This study presents an enhanced protein design algorithm that aims to emulate natural heterogeneity of protein sequences. Initial analysis revealed that natural proteins exhibit a permutation composition lower than the theoretical maximum, suggesting a selective utilization of the 20-letter amino acid alphabet. By not constraining the amino acid composition of the protein sequence but instead allowing random reshuffling of the composition, the resulting design algorithm generates sequences that maintain lower permutation compositions in equilibrium, aligning closely with natural proteins. Folding free energy computations demonstrated that the designed sequences refold to their native structures with high precision, except for proteins with large disordered regions. In addition, direct coupling analysis showed a strong correlation between predicted and actual protein contacts, with accuracy exceeding 82% for a large number of top pairs (>4L). The algorithm also resolved biases in previous designs, ensuring a more accurate representation of protein interactions. Overall, it not only mimics the natural heterogeneity of proteins but also ensures correct folding, marking a significant advancement in protein design and engineering.

Deciphering Membrane Proteins Through Deep Learning Models by Revealing Their Locale Within the Cell

Membrane proteins constitute essential biomolecules attached to or integrated into cellular and organelle membranes, playing diverse roles in cellular processes. Their precise localization is crucial for understanding their functions. Existing protein subcellular localization predictors are predominantly trained on globular proteins; their performance diminishes for membrane proteins, explicitly via deep learning models. To address this challenge, the proposed study segregates membrane proteins into three distinct locations, including the plasma membrane, internal membrane, and membrane of the organelle, using deep learning algorithms including recurrent neural networks (RNN) and Long Short-Term Memory (LSTM). A redundancy-curtailed dataset of 3000 proteins from the MemLoci approach is selected for the investigation, along with incorporating pseudo amino acid composition (PseAAC). PseAAC is an exemplary technique for extracting protein information hidden in the amino acid sequences. After extensive testing, the results show that the accuracy for LSTM and RNN is 83.4% and 80.5%, respectively. The results show that the LSTM model outperforms the RNN and is most commonly employed in proteomics.

Unraveling the Amino Acid Synthesis in Maturity Sesame Seeds Based on the Integrative Analysis of Transcriptome and Metabolome

ABSTRACTSesame plays a vital role in food industry due to its high oil yield, antioxidant potential, and substantial protein content. Notably, there are significant differences in amino acid composition in sesame seeds at various developmental stages. However, the molecular basis and regulatory mechanism underlying amino acid production largely remain unexplored. To unravel these mechanisms, we analyzed the metabolome and transcriptome profiles of a sesame variety across four distinct growth stages (S1–S4). Our analysis identified a total of 17 amino acids, with glutamic acid (Glu), arginine (Arg), proline (Pro), and tyrosine (Tyr) exhibiting significantly higher abundances in mature stages. This increased abundance correlated with the elevated expression of genes involved in amino acid synthesis and regulatory genes. Using weighted gene co‐expression network analysis, we discovered modules associated with glutathione metabolism, arginine biosynthesis, proline, and tyrosine synthesis, along with candidate genes that regulate amino acid production and metabolism. Notably, the differential expression of genes within the amino acid pathways resulted in significant variations in the contents of Glu, Arg, Pro, and Tyr at the mature stage (28 days after flowering, S4) compared to other growth stages. Correlation analysis revealed strong association among the enzymes glutamine synthetase (GS), glutamate/aspartate–prephenate aminotransferase (PAT), and polyamine oxidase (PAO) with the 17 amino acids, suggesting their potential role in the amino acid synthesis. Our findings provide novel insights into the synthesis and accumulation of amino acids during the growth stages of sesame seeds, highlighting key regulatory genes and metabolic pathways involved in this process. Our study lays the groundwork for future studies aiming to enhance the nutritional quality and yield of sesame varieties.

The Bioavailability of Solid-State Fermented Feather Meal Using a Novel Feather-Degrading Bacterium Bacillus velezensis PN1 in Broilers

In this study, an effective feather-degrading bacterium was isolated and the solid-state fermentation condition for feather degradation was optimized. The resulting fermented feather meal (FFM) was evaluated for its bioavailability in broilers. Four Bacillus strains were examined for feather degradation rates, with Bacillus velezensis PN1 exhibiting the highest rate (83.24%, p < 0.05). A 3 × 3 × 3 factorial design was used to test substrate moisture content (45%, 55%, 65%), temperature (27 °C, 37 °C, 47 °C), and incubation time (24, 48, 72 h) for optimized fermentation conditions. In vitro pepsin digestibility (IVPD) revealed a significant interaction between temperature and time (p < 0.05), and the optimal performance was achieved at 37 °C for 72 h, followed by 37 °C for 48 h. Considering production time and cost, FFM2 (produced with 65% moisture at 37 °C for 48 h) was further compared with FFM1 (produced under the same conditions but at a lower temperature of 27 °C), and commercial hydrolyzed feather meal (HFM). IVPD did not differ significantly between FFM1, FFM2, and HFM, as they all showed significantly higher digestibility compared to raw feathers (RFs). FFM1, as well as FFM2, had significantly higher histidine and lysine concentrations than RF (p < 0.05), while FFM2 had a significantly lower cysteine content (p < 0.05). Based on fermentation conditions and amino acid composition, FFM2 was considered more suitable for large-scale production and was used in a broiler growth trial. The inclusion of 5% FFM2 in the broiler diet did not significantly affect body weight at 35 days compared to the 5% HFM group (p > 0.05), although both groups showed significantly lower weight gain than the 5% fish meal (FM) group (p < 0.05). The feed conversion ratio and performance efficiency factor did not differ significantly between the FFM2, HFM, and FM groups (p > 0.05). In groups fed diets without supplemental crystalline amino acids, growth performance did not significantly differ between the HFM and FFM2 groups (p > 0.05), although both performed significantly worse than groups with amino acid supplementation. In conclusion, FFM produced by B. velezensis PN1 through solid-state fermentation enhances feather bioavailability in poultry and can completely replace HFM when included at 5% in broiler diets, offering a potential sustainable alternative for poultry nutrition on a commercial scale.

Nonspecific Yet Selective Interactions Contribute to Small Molecule Condensate Binding.

Biomolecular condensates are essential in various cellular processes, and their misregulation has been demonstrated to underlie disease. Small molecules that modulate condensate stability and material properties offer promising therapeutic approaches, but mechanistic insights into their interactions with condensates remain largely lacking. We employ a multiscale approach to enable long-time, equilibrated all-atom simulations of various condensate-ligand systems. Systematic characterization of the ligand binding poses reveals that condensates can form diverse and heterogeneous chemical environments with one or multiple chains to bind small molecules. Unlike traditional protein-ligand interactions, these chemical environments are dominated by nonspecific hydrophobic interactions. Nevertheless, the chemical environments feature unique amino acid compositions and physicochemical properties that favor certain small molecules over others, resulting in varied ligand partitioning coefficients within condensates. Notably, different condensates share similar sets of chemical environments but at different populations. This population shift drives ligand selectivity toward specific condensates. Our approach can enhance the interpretation of experimental screening data and may assist in the rational design of small molecules targeting specific condensates.

Direct and indirect salt effects on homotypic phase separation

The low-complexity domain of hnRNPA1 (A1-LCD) phase separates in a salt-dependent manner. Unlike many intrinsically disordered proteins (IDPs) whose phase separation is suppressed by increasing salt concentrations, the phase separation of A1-LCD is promoted by >100 mM NaCl. To investigate the atypical salt effect on A1-LCD phase separation, we carried out all-atom molecular dynamics simulations of systems comprising multiple A1-LCD chains at NaCl concentrations from 50 to 1000 mM NaCl. The ions occupy first shell as well as more distant sites around the IDP chains, with Arg sidechains and backbone carbonyls the favored partners of Cl– and Na+, respectively. They play two direct roles in driving A1-LCD condensation. The first is to neutralize the high net charge of the protein (+9) by an excess of bound Cl– over Na+; the second is to bridge between A1-LCD chains, thereby fortifying the intermolecular interaction networks in the dense phase. At high concentrations, NaCl also indirectly strengthens π–π, cation–π, and amino–π interactions, by drawing water away from the interaction partners. Therefore, at low salt, A1-LCD is prevented from phase separation by net charge repulsion; at intermediate concentrations, NaCl neutralizes enough of the net charge while also bridging IDP chains to drive phase separation. This drive becomes even stronger at high salt due to strengthened π-type interactions. Based on this understanding, four classes of salt dependence of IDP phase separation can be predicted from amino-acid composition.

Direct and indirect salt effects on homotypic phase separation.

The low-complexity domain of hnRNPA1 (A1-LCD) phase separates in a salt-dependent manner. Unlike many intrinsically disordered proteins (IDPs) whose phase separation is suppressed by increasing salt concentrations, the phase separation of A1-LCD is promoted by >100 mM NaCl. To investigate the atypical salt effect on A1-LCD phase separation, we carried out all-atom molecular dynamics simulations of systems comprising multiple A1-LCD chains at NaCl concentrations from 50 to 1000 mM NaCl. The ions occupy first shell as well as more distant sites around the IDP chains, with Arg sidechains and backbone carbonyls the favored partners of Cl- and Na+, respectively. They play two direct roles in driving A1-LCD condensation. The first is to neutralize the high net charge of the protein (+9) by an excess of bound Cl- over Na+; the second is to bridge between A1-LCD chains, thereby fortifying the intermolecular interaction networks in the dense phase. At high concentrations, NaCl also indirectly strengthens π-π, cation-π, and amino-π interactions, by drawing water away from the interaction partners. Therefore, at low salt, A1-LCD is prevented from phase separation by net charge repulsion; at intermediate concentrations, NaCl neutralizes enough of the net charge while also bridging IDP chains to drive phase separation. This drive becomes even stronger at high salt due to strengthened π-type interactions. Based on this understanding, four classes of salt dependence of IDP phase separation can be predicted from amino-acid composition.

Nectar and pollen in Acer trees can contribute to improvement of food resources for pollinators.

In the present study, we quantified floral resources (nectar and pollen production) and their quality (nectar sugar composition, pollen protein content, pollen amino acid composition) in five Acer species (f. Sapindaceae) growing in forests and commonly planted in urban areas in the temperate zone. Acer trees provide high amounts of sugars and/or pollen. No nectar was produced by A. negundo flowers. The other species produced nectar in functionally female flowers. The floral nectar was composed of sucrose, glucose, and fructose and was classified as hexose-rich or sucrose-rich. The pollen of all the Acer species contained essential amino acids. Acer trees should be planted for improvement of cost-effective food resources in various landscape types (agroforestry, urban areas), with the exception of A. negundo (an invasive species with no nectar available). However, maple trees alone are not sufficient to support pollinators, and other plant species flowering before and after Acer spp. should be planted to ensure a continued supply of food for pollinators.

Glycine soja, PI424025, is a valuable genetic resource to improve soybean seed-protein content and composition.

Soybean seed-protein content and composition is important because it contributes over half the value of this $61 billion crop. Historic negative correlation between seed-protein content and oil have been reported. Similarly, negative correlation between seed-protein content and yield have been reported but may be at least in part mitigated by increasing the genetic diversity of the elite soybean germplasm. Improvements in amino acid composition of seed-protein would increase the value of soybean meal and protein for animal and human consumption. We have identified a genetic resource in wild soybean germplasm, PI424025B, with elevated seed-protein, elevated cysteine in the seed and increased sulfur content in the seed. We have developed a population of Recombinant Inbred Lines derived from a cross between NC-Raleigh and PI424025B. We evaluated the carbon, nitrogen and sulfur (C, N and S) content of seeds from the progeny, the parents and other high-seed protein soybean lines. N content and C/N (ratio of C to N) were well correlated with protein content measured by NIR. PI424025B had a N content comparable to high-protein soybean lines and a superior N/S. These traits were inherited by some of the progeny. Quantitative Trait Loci (QTL) associated with high-seed protein were identified on chr2, chr20 and chr15 and colocalizes with well characterized loci on chr 15 and chr 20 known to affect seed-protein content and quality. A potentially unique QTL was identified on Chr15. Unlike the chr20 QTL, the chr15 QTL improved S content relative to N content and was superior to other high seed-protein phenotypes tested. These data indicate that PI424025B is a valuable resource to diversify the genetics of soybean while improving soybean seed-protein content and composition.

From coffee waste to nutritional gold: bioreactor cultivation of single‐cell protein from Candida sorboxylosa

AbstractBACKGROUNDIndustrial effluents are continuously discharged into the environment. These wastewaters contain valuable compounds that can be reused for biotechnological applications. Coffee wastewater (CWW) is a powerful effluent that can be used for single‐cell protein (SCP) production reaching important content (up to 80%). Several yeast species can be used for SCP production, but Candida species are commonly applied for this purpose (17 species reported including the novel C. sorboxylosa). In addition, SCP can be produced in bioreactors under controlled conditions under three operation modes. Thus, batch mode is frequently used but continuous mode presents interesting advantages in economic terms, although it has been poorly applied in SCP production.RESULTSThe initial evaluation under batch operation mode showed that volumetric oxygen transfer coefficient (kLa of 101 h−1) improved biomass production (1.39 g L−1) and SCP yield (59.9%) in C. sorboxylosa. Thus, continuous mode was established at selected kLa and feeding with optimized medium composed of 87.5% (v/v) CWW, 1.38 g L−1 yeast extract, and 7.24 g L−1 (NH4)2SO4, in order to provided necessary nutrients. In this sense, the process presented higher values in dry cell weight and SCP productivity (0.57 and 0.29 g L−1·h, respectively), achieving a 3.35‐ and 2.90‐fold increase in biomass and protein productivity, respectively, compared to batch mode. The SCP from C. sorboxylosa exhibited an interesting essential amino acid profile under continuous mode (33.704%).CONCLUSIONThe bioprocess highlights several advantages during bioreactor cultivation, including: (i) reduced energy consumption for temperature control; (ii) successful establishment of an initial continuous operation mode with promising performance; and (iii) SCP from C. sorboxylosa exhibited a notable composition of essential amino acids, which could be beneficial for potential use in animal feed. © 2024 Society of Chemical Industry (SCI).

Peptidomic Analysis of Potential Bioactive Peptides in Mare Milk Under Different Heat Treatment Conditions

Active peptides in mare milk have unique biological activities, but how the bioactive protein in mare’s milk changes under the influence of temperature has not been fully studied. Therefore, in this study, the differential expression of bioactive peptides potentially present in horse milk under different heat treatment conditions was investigated for the first time using peptidomic and bioinformatic techniques. We collected a total of 15 samples. In this study, we divided the samples into five groups, specifically, 65 °C, 30 min; 72 °C, 15 min; 83 °C; 10 min; 95 °C, 5 min; and an untreated group as a control, which involved four different temperature treatments, in order to understand changes in bioactive peptides and to identify the sequence of bioactive peptides. In the experiment, a total of 2341 active peptides were identified. The amino acid composition of the potential active peptides remained stable across different temperatures, but their abundance varied with temperature. In all, 23 peptides from 20 different proteins were identified, with the highest number of active peptides identified at 72 °C. Through database searches, we found that a majority of these peptides were within β-lactoglobulin and immunoglobulin domain proteins, which are known for their potential biological activities. These findings provide a theoretical foundation for the development of peptides with different bioactivities as potential functional foods.

Dietary amino acids intake and all-cause and cause-specific mortality: results from the Golestan Cohort Study

BackgroundLess is known whether the amino acid composition of dietary protein sources effects on long-term health outcomes. We aimed to evaluate the association between dietary amino acid composition and all-cause and cause-specific mortality.MethodsThis study used data from the Golestan Cohort Study, which was performed in the Golestan Province of Iran from January 2004 to June 2008. Mortality, which was the primary outcome, was ascertained through September 2022. The Cox proportional hazards regression models were used to determine the adjusted hazard ratios (HR) and 95% confidence intervals (CI) for mortality according to the quintiles of amino acid consumption, taking the third quintile as the reference.ResultsA total of 47,337 participants (27,293 [57.7%] women) with a mean (standard deviation) age of 51.9 (8.9) years were included. During a median follow-up of 15 years, 9,231 deaths were documented. Regarding essential amino acid intakes, the HRs of all-cause mortality were 1.16 (95% CI, 1.07–1.26) in the first quintile, compared with the reference group (P for non-linear trend < 0.001). Similarly, non-linear associations were observed between risk of all-cause mortality and intake of branched-chain, aromatic, sulfur-containing, or non-essential amino acids (P for non-linear trend < 0.001 for all comparisons), with higher HRs for participants in the first quintiles. There was an age interaction for the associations between dietary amino acids and mortality (P for interaction ˂0.05). While high amino acid diets were detrimental in middle-aged adults (< 65 years), increased hazards of mortality were observed among older adults (≥ 65 years) with low amino acid intake.ConclusionsThis study showed the non-linear trend between amino acids intake and risk of mortality in the middle-aged and older Iranian population. Overall, our findings suggest that diets lower in amino acids were associated with increased hazards of mortality, particularly among older adults.

Antioxidants, ACE I Inhibitory Peptides, and Physicochemical Composition, with a Special Focus on Trace Elements and Pollutants, of SPRING Spawning Atlantic Herring (Clupea harengus) Milt and Hydrolysates for Functional Food Applications

Norwegian spring spawning (NVG) herring milt is a raw material with high nutritional and functional values. However, its incorporation into food presents physicochemical and sensory challenges. Its high DNA content, the presence of TMA/TMAO and possibly heavy metal and/or environmental pollutants, and its bitter taste due to amino acids or peptides requires a careful approach to food development. Hydrolysis with food-grade enzymes enable an improvement in both the functional and sensory properties of the substrate and the increased stability of the raw materials and end products. HLPC, GC-MS, and in vitro protocols were used for the characterisation of manually extracted material (sample code: HMC) and milt from a fish-filleting line from early spring/late autumn catches. Three different food-grade protein hydrolysates were prepared from these raw materials (sample codes: H1, H2, and H3) as a means to estimate their functional food development potential. Combinations of three commercial enzymatic preparations were applied, targeting specific sensory properties. Parameters related to consumer safety (e.g., the presence of heavy metals and TMA/TMAO); beneficial health effects, such as antioxidant or antihypertensive bioactivities (measured using in vitro TAC, ORAC, DPPH, and ACE I inhibitory activity assays); the presence of beneficial fatty acids and micronutrients; and the protein quality were studied. On the basis of their total amino acid compositions, freeze-dried herring milt and hydrolysates could provide high-quality protein with most of the essential amino acids and taurine. Powdered milt has a particularly high fatty acid profile of bioavailable omega-3 fatty acids (2024.06 mg/100 g docosahexaenoic acid (DHA; 22:6n-3) and 884 mg/100 g eicosapentaenoic acid (EPA; 20:5n-3)). The experimentally measured levels of arsenic (3.9 ± 1.2 mg/kg) and cadmium (0.15 ± 0.05 mg/kg) were higher than the levels of the other two heavy metals (mercury and lead). The bioactivity is concentration-dependent. Overall, this work presents complementary information for the future utilisation of C. harengus powdered milt (possibly obtained directly from a fish-filleting line) and some of its protein hydrolysates as food ingredients.

Predicting viral proteins that evade the innate immune system: a machine learning-based immunoinformatics tool

Viral proteins that evade the host’s innate immune response play a crucial role in pathogenesis, significantly impacting viral infections and potential therapeutic strategies. Identifying these proteins through traditional methods is challenging and time-consuming due to the complexity of virus-host interactions. Leveraging advancements in computational biology, we present VirusHound-II, a novel tool that utilizes machine learning techniques to predict viral proteins evading the innate immune response with high accuracy. We evaluated a comprehensive range of machine learning models, including ensemble methods, neural networks, and support vector machines. Using a dataset of 1337 viral proteins known to evade the innate immune response (VPEINRs) and an equal number of non-VPEINRs, we employed pseudo amino acid composition as the molecular descriptor. Our methodology involved a tenfold cross-validation strategy on 80% of the data for training, followed by testing on an independent dataset comprising the remaining 20%. The random forest model demonstrated superior performance metrics, achieving 0.9290 accuracy, 0.9283 F1 score, 0.9354 precision, and 0.9213 sensitivity in the independent testing phase. These results establish VirusHound-II as an advancement in computational virology, accessible via a user-friendly web application. We anticipate that VirusHound-II will be a crucial resource for researchers, enabling the rapid and reliable prediction of viral proteins evading the innate immune response. This tool has the potential to accelerate the identification of therapeutic targets and enhance our understanding of viral evasion mechanisms, contributing to the development of more effective antiviral strategies and advancing our knowledge of virus-host interactions.

Does metabolic rate influence genome-wide amino acid composition in the course of animal evolution?

Does metabolic rate influence genome-wide amino acid composition in the course of animal evolution?

Effects of replacing fish meal with pork meal and supplementing with crystalline amino acids and fish oil on growth performance, body composition, enzyme activity, intestinal morphology, and immune response of Penaeus monodon

IntroductionThe present study aimed to evaluate the effects of substituting fish meal with pork meal in feed on the growth performance, feed utilization, intestinal morphology, and immune function of Penaeus monodon.MethodsA total of 600 uniformly sized juvenile shrimp with an initial weight of 1.20 ± 0.03 g were randomly assigned to four groups, with each group consisting of six replicates of 25 shrimp each. Fish meal protein was replaced with 0%, 5%, 10%, and 15% pork meal, and crystalline amino acids and fish oil were supplemented accordingly. The groups were designated as P0, P5, P10, and P15, and the study duration was 70 days.ResultsResults indicated no significant difference in specific growth rate (SGR) between the P5 and P10 groups compared to the P0 group. However, the SGR in the P15 group was significantly lower than that in the P5 and P10 groups. Feed conversion rates (FCRs) for the P5 and P10 groups were comparable to the P0 group, whereas the P15 group showed a significantly higher FCR than the other groups. There were no significant differences in whole body composition among all the groups. Apart from alanine, the amino acid composition of muscles did not differ significantly among all the groups. Results of enzyme activity in plasma revealed that the replacement of fish meal with pork meal reduced levels of aspartate aminotransferase (AST) and superoxide dismutase (SOD). Specifically, levels of AST in the P5 and P15 groups were significantly lower compared to the P0 and P10 groups. Histological examination of midgut tissues showed that villus height initially increased and then decreased with higher replacement ratios. The P5 group had the highest villus height, while the P15 group had the lowest villus height. Analysis of gene expression related to liver immune functions indicated that genes in TLR signaling pathway were significantly elevated in the P15 group compared to the other groups.DiscussionIn conclusion, even with the supplementation of crystalline amino acids and fish oil, pork meal should not replace more than 10% of fish meal in the feed of P. monodon to maintain optimal growth and feed efficiency.

Effect of Processing Methods on Amino Acid and Fatty Acid Composition of Parkia biglobosa Seeds

Parkia biglobosa (PB) is among the various underexploited nutritious plants. A comparative study was conducted on the effect processing PB has on the amino and fatty acid composition. Fermented (FPB), defatted (DPB), and protein isolates (PI) samples were prepared from Parkia biglobosa seeds using various processing methods, and evaluated using standard analytical protocols. The PI showed the highest significant total non-essential amino acids, essential amino acids, and conditionally essential amino acids when compared with FPB and DPB. In addition, the PI showed the highest significant (p &lt; 0.05) total neutral amino acids, basic amino acids, total aromatic amino acids, and the lowest percentage cystine ratio of total sulphur amino acids and total amino acids in comparison with FPB and DPB. The PI also showed a better-predicted protein efficient ratio, essential amino acid index, biological value, protein content, and nutritional index than FPB and DPB. Furthermore, PI amino acid composition was compared favourably with the reference scores for a whole hen’s egg, preschool child, and provisional scoring pattern. Arginine and histidine values of PI were higher than the recommended values. The FPB (42.29%) showed the highest polyunsaturated fatty acids compared with the DPB (41.94%) and PI (26.7%). The dominant saturated, monounsaturated, and polyunsaturated fatty acids were stearic acid (15.1 DPB), linoleic acid (42.29 DPB), and oleic acid (14.05 PI). The DPB (1.84) showed a better polyunsaturated to saturated (P:S) ratio than FPB (1.74) and PI (0.91). The results revealed that the processing methods improved the relative amino acid composition, whereas the fatty acid composition improved in DPB. Therefore, PI could serve as an alternative in the formulation of complementary foods.

TCellR2Vec: efficient feature selection for TCR sequences for cancer classification

Cancer remains one of the leading causes of death globally. New immunotherapies that harness the patient’s immune system to fight cancer show promise, but their development requires analyzing the diversity of immune cells called T-cells. T-cells have receptors that recognize and bind to cancer cells. Sequencing these T-cell receptors allows to provide insights into their immune response, but extracting useful information is challenging. In this study, we propose a new computational method, TCellR2Vec, to select key features from T-cell receptor sequences for classifying different cancer types. We extracted features like amino acid composition, charge, and diversity measures and combined them with other sequence embedding techniques. For our experiments, we used a dataset of over 50,000 T-cell receptor sequences from five cancer types, which showed that TCellR2Vec improved classification accuracy and efficiency over baseline methods. These results demonstrate TCellR2Vec’s ability to capture informative aspects of complex T-cell receptor sequences. By improving computational analysis of the immune response, TCellR2Vec could aid the development of personalized immunotherapies tailored to each patient’s T-cells. This has important implications for creating more effective cancer treatments based on the individual’s immune system.

Comparative Study of Amino Acids in the Life Stages of Silkworm (Bombyx mori L.)

The silkworm (Bombyx mori L.) undergoes distinct life stages, including egg, larva (caterpillar), pupa (chrysalis), and adult moth(imago), each with specific physiological requirements. Amino acids are essential for the growth and development of the silkworm. In this study, we work in paper chromatography to compare the amino acid profiles in different life stages of the silkworm. Samples were collected from eggs, larvae, pupae, and adult moths. Amino acids were extracted and separated on chromatographic paper using a suitable solvent system. The developed chromatograms were analyzed to determine the relative concentrations of specific amino acids. Our results revealed variations in the amino acid composition across the life stages. The amino acids such as glycine, methionine, leucine, and aspartic acid were common in all life stages of silkworms. These differences may be attributed to the physiological changes associated with metamorphosis and reproduction in adult silkworms. Overall, this study provides valuable insights into the dynamic changes in amino acid profiles during the life stages of silkworms, highlighting the importance of amino acids in their growth, development, and silk production. And, this study demonstrates the utility of paper chromatography as a cost-effective and reliable method for analyzing amino acid composition in complex biological samples, providing valuable insights into the nutritional dynamics of the silkworm lifecycle.