Elucidating immunological characteristics of the adenoma-carcinoma sequence in colorectal cancer patients in South Korea using a bioinformatics approach.

Colorectal cancer (CRC) is one of the top five most common and life-threatening malignancies worldwide. Most CRC develops from advanced colorectal adenoma (ACA), a precancerous stage, through the adenoma-carcinoma sequence. However, its underlying mechanisms, including how the tumor microenvironment changes, remain elusive. Therefore, we conducted an integrative analysis comparing RNA-seq data collected from 40 ACA patients who visited Dongguk University Ilsan Hospital with normal adjacent colons and tumor samples from 18 CRC patients collected from a public database. Differential expression analysis identified 21 and 79 sequentially up- or down-regulated genes across the continuum, respectively. The functional centrality of the continuum genes was assessed through network analysis, identifying 11 up- and 13 down-regulated hub-genes. Subsequently, we validated the prognostic effects of hub-genes using the Kaplan-Meier survival analysis. To estimate the immunological transition of the adenoma-carcinoma sequence, single-cell deconvolution and immune repertoire analyses were conducted. Significant composition changes for innate immunity cells and decreased plasma B-cells with immunoglobulin diversity were observed, along with distinctive immunoglobulin recombination patterns. Taken together, we believe our findings suggest underlying transcriptional and immunological changes during the adenoma-carcinoma sequence, contributing to the further development of pre-diagnostic markers for CRC.

Contrastive learning for enhancing feature extraction in anticancer peptides.

Cancer, recognized as a primary cause of death worldwide, has profound health implications and incurs a substantial social burden. Numerous efforts have been made to develop cancer treatments, among which anticancer peptides (ACPs) are garnering recognition for their potential applications. While ACP screening is time-consuming and costly, in silico prediction tools provide a way to overcome these challenges. Herein, we present a deep learning model designed to screen ACPs using peptide sequences only. A contrastive learning technique was applied to enhance model performance, yielding better results than a model trained solely on binary classification loss. Furthermore, two independent encoders were employed as a replacement for data augmentation, a technique commonly used in contrastive learning. Our model achieved superior performance on five of six benchmark datasets against previous state-of-the-art models. As prediction tools advance, the potential in peptide-based cancer therapeutics increases, promising a brighter future for oncology research and patient care.

Identifying novel antimicrobial peptides from venom gland of spider Pardosa astrigera by deep multi-task learning.

Antimicrobial peptides (AMPs) show promises as valuable compounds for developing therapeutic agents to control the worldwide health threat posed by the increasing prevalence of antibiotic-resistant bacteria. Animal venom can be a useful source for screening AMPs due to its various bioactive components. Here, the deep learning model was developed to predict species-specific antimicrobial activity. To overcome the data deficiency, a multi-task learning method was implemented, achieving F1 scores of 0.818, 0.696, 0.814, 0.787, and 0.719 for Bacillus subtilis, Escherichia coli, Pseudomonas aeruginosa, Staphylococcus aureus, and Staphylococcus epidermidis, respectively. Peptides PA-Full and PA-Win were identified from the model using different inputs of full and partial sequences, broadening the application of transcriptome data of the spider Pardosa astrigera. Two peptides exhibited strong antimicrobial activity against all five strains along with cytocompatibility. Our approach enables excavating AMPs with high potency, which can be expanded into the fields of biology to address data insufficiency.

Prediction Models for Identifying Ion Channel-Modulating Peptides via Knowledge Transfer Approaches.

Ion channels, which can be modulated by peptides, are promising drug targets for neurological, metabolic, and cardiovascular disorders. Because it is expensive and labor-intensive to experimentally screen ion channel-modulating peptides (IMPs), in-silico approaches can serve as excellent alternatives. In this study, we present PrIMP, prediction models for screening IMPs that can target sodium, potassium, and calcium ion channels, as well as nicotine acetylcholine receptors (nAChRs). To overcome the data insufficiency of the IMPs, we utilized two types of knowledge transfer approaches: multi-task learning (MTL) and transfer learning (TL). MTL enabled model training for four target tasks simultaneously with hard parameter sharing, thereby increasing model generalization. TL transferred knowledge of pre-trained model weights from antimicrobial peptide data, which was a much larger, naturally-occurring functional peptide dataset that could potentially improve the model performance. MTL and TL successfully improved the prediction performance of prediction models. In addition, a hybrid approach by implementing deep learning along with traditional machine learning was utilized, with additional performance improvements. PrIMP achieved F1 scores of 0.924 (sodium ion channel), 0.937 (potassium ion channel), 0.898 (calcium ion channel), and 0.931 (nAChRs). The pre-processed dataset and proposed model are available at https://github.com/bzlee-bio/PrIMP.

Identification of Mucilaginibacter conchicola sp. nov., Mucilaginibacter achroorhodeus sp. nov. and Mucilaginibacter pallidiroseus sp. nov. and emended description of the genus Mucilaginibacter.

Three chitinolytic, Gram-negative, light pink, capsule-forming, rod-shaped bacterial strains with gliding motion (MYSH2T, MJ1aT and dk17T) were isolated from seashells, soil and foxtail, respectively. Phylogenetic analysis of the 16S rRNA gene sequences and concatenated alignment of 92 core genes indicated that strains MYSH2T, MJ1aT and dk17T were novel species of the genus Mucilaginibacter and exhibited a high 16S rRNA sequence similarity (i.e. more than 97.2 %) among each other. These novel strains contained summed feature 3 (C16:1 ω7c and/or C16:1 ω6), iso-C15:0 and MK-7 as the predominant fatty acids and menaquinone. According to the CAZys coding gene of KAAS, MYSH2T and MJ1aT were interpreted as strains containing both GH18 and 19 family coding genes, except for dk17T, which shows only GH19 family genes. These strains likely degrade chitin to chitobiose or directly to N-acetyl-d-glucosamine, which may enhance their chitinolytic capacity, thus making these stains potentially useful for industrial chitin degradation. Based on distinct morphological, physiological, chemotaxonomic and phylogenetic differences from their closest phylogenetic neighbours, we propose that strains MYSH2T, MJ1aT and dk17T represent three novel species in the genus Mucilaginibacter, for which the names Mucilaginibacter conchicola sp. nov. (=KACC 19716T=JCM 32787T), Mucilaginibacter achroorhodeus sp. nov. (=KACC 19906T=NBRC 113667T) and Mucilaginibacter pallidiroseus sp. nov. (=KACC 19907T=NBRC 113666T) are proposed. An emended description of the genus Mucilaginibacter is proposed.

Designing a Novel Functional Peptide With Dual Antimicrobial and Anti-inflammatory Activities via in Silico Methods.

As spider venom is composed of various bioactive substances, it can be utilized as a platform for discovering future therapeutics. Host defense peptides are great candidates for developing novel antimicrobial agents due to their multifunctional properties. In this study, novel functional peptides were rationally designed to have dual antibacterial and anti-inflammatory activities with high cytocompatibility. Based on a template sequence from the transcriptome of spider Agelena koreana, a series of via in silico analysis were conducted, incorporating web-based machine learning tools along with the alteration of amino acid residues. Two peptides, Ak-N' and Ak-N'm, were designed and were subjected to functional validation. The peptides inhibited gram-negative and gram-positive bacteria by disrupting the outer and bacterial cytoplasmic membrane. Moreover, the peptides down-regulated the expression of pro-inflammatory mediators, tumor necrosis factor-α, interleukin (IL)-1ß, and IL6. Along with low cytotoxicity, Ak-N'm was shown to interact with macrophage surface receptors, inhibiting both Myeloid differentiation primary response 88-dependent and TIR-domain-containing adapter-inducing interferon-ß-dependent pathways of Toll-like receptor 4 signaling on lipopolysaccharide-stimulated THP-1-derived macrophages. Here, we rationally designed functional peptides based on the suggested in silico strategy, demonstrating new insights for utilizing biological resources as well as developing therapeutic agents with enhanced properties.

Halomonas antri sp. nov., a carotenoid-producing bacterium isolated from surface seawater.

A Gram-negative, moderately halophilic bacterium, designated as strain Y3S6T, was isolated from a surface seawater sample collected from Dongangyoeng cave, Udo-myeon, Jeju-si, Jeju-do, Repulic of Korea. Cells of strain Y3S6T were aerobic, rod-shaped, non-sporulated, yellow, catalase- negative, oxidase-negative and motile with one polar flagellum. Growth of strain Y3S6T occurred at 15-40 °C (optimum: 25-30 °C), at pH 6.0-9.0 (optimum: pH 7.0) and in the presence of 0-13% NaCl (optimum: 1-6 %, w/v). The novel strain was able to produce carotenoids. Its chemotaxonomic and morphological characteristics were consistent with those of members of the genus Halomonas. Phylogenetic analysis of the 16S rRNA gene sequence revealed that strain Y3S6T formed a clade with Halomonas pellis L5T (98.97 %) and Halomonas saliphila LCB169T(98.90%). The average nucleotide identity and digital DNA-DNA hybridization values of strain Y3S6T with the most closely related strains for which whole genomes are publicly available were 82.3-85.2% and 62.8-66.1 %, respectively. The major fatty acids in strain Y3S6T were C16 : 0, C19 : 0 cyclo ω8c and summed feature 8 (composed of C18 : 1 ω7c and/or C18 : 1 ω6c), and the predominant quinone was Q-9. Its polar lipid profile consisted of diphosphatidylglycerol, phosphatidylglycerol, phosphatidylethanolamine, two unidentified phosphoglycolipid, one unidentified phosphoaminoglycolipid and one unidentified phospholipid. The genomic DNA G+C content based on the draft genome sequence was 64.2 mol%. The results of physiological and biochemical tests and 16S rRNA sequence analysis clearly revealed that strain Y3S6T represents a novel species in the genus Halomonas, for which the name Halomonas antri sp. nov. has been proposed. The type strain is Y3S6T (=KACC 21536T=NBRC 114315=TBRC 15164T).

Nocardioides donggukensis sp. nov. and Hyunsoonleella aquatilis sp. nov., isolated from Jeongbang Waterfall on Jeju Island.

Two bacterial strains, designated MJB4T and SJ7T, were isolated from water samples collected from Jeongbang Falls on Jeju Island, Republic of Korea. Phylogenetic analysis of 16S rRNA gene sequences indicated that the two strains belonged to the genera Nocardioides and Hyunsoonleella, owing to their high similarities to Nocardioides jensenii DSM 29641T (97.5 %) and Hyunsoonleella rubra FA042 T (96.3 %), respectively. These values are much lower than the gold standard for bacterial species (98.7 %). The average nucleotide identity values between strains MJB4T, SJ7T and the reference strains, Nocardioides jensenii DSM 29641T, Nocardioides daejeonensis MJ31T and Hyunsoonleella flava T58T were 77.2, 75.9 and 75.4 %, respectively. Strains MJB4T and SJ7T and the type strains of the species involved in system incidence have average nucleotide identity and average amino acid threshold values of 60.1-82.6 % for the species boundary (95-96 %), which confirms that strains MJB4T and SJ7T represent two new species of genus Nocardioides and Hyunsoonleella, respectively. Based on phylogenetic and phenotypic data, strains MJB4T and SJ7T are considered to represent novel species of the genus Nocardioides and Hyunsoonleella, respectively, for which the names Nocardioides donggukensis sp. nov. (type strain MJB4T=KACC 21724T=NBRC 114402T) and Hyunsoonleella aquatilis sp. nov., (type strain SJ7T=KACC 21715T=NBRC 114486T) have been proposed.

A Deep Learning Approach with Data Augmentation to Predict Novel Spider Neurotoxic Peptides.

As major components of spider venoms, neurotoxic peptides exhibit structural diversity, target specificity, and have great pharmaceutical potential. Deep learning may be an alternative to the laborious and time-consuming methods for identifying these peptides. However, the major hurdle in developing a deep learning model is the limited data on neurotoxic peptides. Here, we present a peptide data augmentation method that improves the recognition of neurotoxic peptides via a convolutional neural network model. The neurotoxic peptides were augmented with the known neurotoxic peptides from UniProt database, and the models were trained using a training set with or without the generated sequences to verify the augmented data. The model trained with the augmented dataset outperformed the one with the unaugmented dataset, achieving accuracy of 0.9953, precision of 0.9922, recall of 0.9984, and F1 score of 0.9953 in simulation dataset. From the set of all RNA transcripts of Callobius koreanus spider, we discovered neurotoxic peptides via the model, resulting in 275 putative peptides of which 252 novel sequences and only 23 sequences showing homology with the known peptides by Basic Local Alignment Search Tool. Among these 275 peptides, four were selected and shown to have neuromodulatory effects on the human neuroblastoma cell line SH-SY5Y. The augmentation method presented here may be applied to the identification of other functional peptides from biological resources with insufficient data.

Adhaeribacter rhizoryzae sp. nov., a fibrillar matrix-producing bacterium isolated from the rhizosphere of rice plant.

A novel fibrillar matrix-producing, rod-shaped, red-orange, asporogenous, aerobic bacterium, designated DK36T, was isolated from roots of a rice plant in the Ilsan region near Dongguk University, South Korea. Cells of strain DK36T were Gram-stain-negative and motile by means of gliding. The temperature and pH ranges for growth were 7-35 °C (optimum: 30 °C) and pH 5-10 (optimum: pH 7.0). The strain did not require NaCl for growth but tolerated up to 8 % (w/v) NaCl. Phylogenetic anlaysis of the 16S rRNA gene sequence revealed that DK36T formed a monophyletic clade with Adhaeribacter aerophilus 6425 S-25T, Adhaeribacter aerolatus 6515 J-31T and Adhaeribacter swui 17mud1-7T with sequence similarities of 96.3, 95.5 and 95.2%, respectively. The average nucleotide identity and in silico DNA-DNA hybridization values of strain DK36T with the most closely related strains whose whole genomes are publicly available were 72.5-83.6% and 19-28 %, respectively. The strain showed the typical chemotaxonomic characteristics of the genus Adhaeribacter, with the presence of menaquinone MK-7 as the respiratory quinone, and C16 : 1ω5c, iso-C15 : 0 and summed feature 4 (composed of iso-C17 : 1 I/anteiso-C17 : 1 B) as the major fatty acids. The polar lipid profile consisted of phosphatidylethanolamine, one unidentified aminophosphoglycolipid, one unidentified phospholipid, two unidentified aminolipids and five unidentified polar lipids. The genomic DNA G+C content based on the draft genome sequence was 43.4 mol%. The results of physiological and biochemical tests and 16S rRNA gene sequence analysis clearly revealed that strain DK36T represents a novel species of the genus Adhaeribacter, for which the name Adhaeribacter rhizoryzae sp. nov. is proposed. The type strain is DK36T (=KACC 19902T=NBRC 113689T).

Methylobacterium terricola sp. nov., a gamma radiation-resistant bacterium isolated from gamma ray-irradiated soil.

A gamma radiation-resistant and pink-pigmented bacterial strain, designated as 17Sr1-39T, was isolated from a gamma ray-irradiated soil sample collected in the Republic of Korea. Cells were Gram-stain-negative, strictly aerobic, flagellated, asporogenous, rod-shaped and methylotrophic. Results of 16S rRNA gene sequence analysis showed that strain 17Sr1-39T was phylogenetically related to Methylobacterium currus PR1016AT (97.3 %), Methylobacterium aquaticum DSM 16371T (97.2 %), Methylobacterium platani PMB02T (97.0 %), Methylobacterium frigidaeris IER25-16T (96.6 %), Methylobacterium terrae 17Sr1-28T (96.6 %) and Methylobacterium organophilum JCM 2833T (93.4 %). The G+C content calculated based on the genome sequence was 70.4 mol%. The average nucleotide identity and in silico DNA-DNA hybridization values between strain 17Sr1-39T and M. currus, M. aquaticum, M. platani, M. frigidaeris, M. terrae and M. organophilum were 77.3-89.9 and 22-38.2 %, respectively. The predominant fatty acids were summed feature 8 (C18 : 1ω7c and/or C18 : 1ω6c) and summed feature 3 (C16 : 1ω7c and/or C16 : 1ω6c). The predominant quinone was ubiquinone 10 and the major polar lipids were diphosphatidylglycerol, phosphatidylglycerol and phosphatidylethanolamine. Based on the data from phenotypic tests and genotypic differences between strain 17Sr1-39T and its close phylogenetic relatives, strain 17Sr1-39T represented a new species belonging to the genus Methylobacterium, for which the name Methylobacterium terricola sp. nov. (=KACC 52905T=NBRC 112874T) is proposed.

Integrative genomic and transcriptomic analysis of genetic markers in Dupuytren's disease.

BACKGROUND: Dupuytren's disease (DD) is a fibroproliferative disorder characterized by thickening and contracting palmar fascia. The exact pathogenesis of DD remains unknown. RESULTS: In this study, we identified co-expressed gene set (DD signature) consisting of 753 genes via weighted gene co-expression network analysis. To confirm the robustness of DD signature, module enrichment analysis and meta-analysis were performed. Moreover, this signature effectively classified DD disease samples. The DD signature were significantly enriched in unfolded protein response (UPR) related to endoplasmic reticulum (ER) stress. Next, we conducted multiple-phenotype regression analysis to identify trans-regulatory hotspots regulating expression levels of DD signature using Genotype-Tissue Expression data. Finally, 10 trans-regulatory hotspots and 16 eGenes genes that are significantly associated with at least one cis-eQTL were identified. CONCLUSIONS: Among these eGenes, major histocompatibility complex class II genes and ZFP57 zinc finger protein were closely related to ER stress and UPR, suggesting that these genetic markers might be potential therapeutic targets for DD.

Flavobacterium baculatum sp. nov., a carotenoid and flexirubin-type pigment producing species isolated from flooded paddy field.

A Gram-stain-negative, aerobic, asporogenous, motile by gliding, dull-yellow, long rod-shaped bacterial strain, designated SNL9T, was isolated from a flooded paddy field near Dongguk University, Republic of Korea. The results of phylogenetic analyses based on 16S rRNA gene sequences indicated that SNL9T represents a member of the genus Flavobacterium and is most closely related to Flavobacterium ummariense DS-12T (96.2%) and Flavobacterium viscosum YIM 102796T (96.3%). The average nucleotide identity and in silico DNA-DNA hybridization (DDH) values with F. ummariense DS-12T and F. viscosum YIM 102796T were 89.3/39.1 and 87.1/33 %, respectively. The major fatty acids of SNL9T were identified as iso-C15 : 0, summed feature 3 (comprising C16  :  1ω6c and/or C16  :  1ω7c) and summed feature 9 (comprising iso-C17 : 1ω9c and/or 10 methyl C16 : 0). SNL9T contained MK-6 as the major respiratory quinone. The polar lipids were phoshatidylethanolamine, one unidentified aminophosphoglycolipid, three unidentified aminoglycolipids, two unidentified glycolipids and one unidentified phosphoglycolipid. The DNA G+C content was 34.2 mol%. SNL9T produces carotenoid and flexirubin-type pigments. Among them, carotenoids are particularly valuable for the biotechnological and pharmaceutical industries due to their antioxidant activity. Aryl polyenes (APE) pigments were also found in SNL9T which are responsible for yellow pigment in bacteria. They are stored in the bacterial membrane and protect the bacteria from oxidative stress, particularly from reactive oxygen species. In this paper, we describe a novel isolate, SNL9T, which protect itself from the attack of free radicals using specific natural products in the membrane. Because of their anti-oxidation properties, aryl polyenes may also be of interest to the cosmetic industry. On the basis of the results of phenotypic, genotypic and chemotaxonomic analyses, SNL9T represents a novel species of the genus Flavobacterium, for which the name Flavobacterium baculatum sp. nov. is proposed. The type is SNL9T (=KACC 21170T=NBRC 113746T).