Transcriptomics to evaluate the influence mechanisms of ethanol on the ester production of Wickerhamomyces anomalus with the induction of lactic acid.

Wickerhamomyces anomalus is one of the most important ester-producing strains in Chinese baijiu brewing. Ethanol and lactic acid are the main metabolites produced during baijiu brewing, but their synergistic influence on the growth and ester production of W. anomalus is unclear. Therefore, in this paper, based on the contents of ethanol and lactic acid during Te-flavor baijiu brewing, the effects of different ethanol concentrations (3, 6, and 9% (v/v)) combined with 1% lactic acid on the growth and ester production of W. anomalus NCUF307.1 were studied and their influence mechanisms were analyzed by transcriptomics. The results showed that the growth of W. anomalus NCUF307.1 under the induction of lactic acid was inhibited by ethanol. Although self-repair mechanism of W. anomalus NCUF307.1 induced by lactic acid was initiated at all concentrations of ethanol, resulting in significant up-regulation of genes related to the Genetic Information Processing pathway, such as cell cycle-yeast, meiosis-yeast, DNA replication and other pathways. However, the accumulation of reactive oxygen species and the inhibition of pathways associated with carbohydrate and amino acid metabolism may be the main reason for the inhibition of growth in W. anomalus NCUF307.1. In addition, 3% and 6% ethanol combined with 1% lactic acid could promote the ester production of W. anomalus NCUF307.1, which may be related to the up-regulation of EAT1, ADH5 and TGL5 genes, while the inhibition in 9% ethanol may be related to down-regulation of ATF2, EAT1, ADH2, ADH5, and TGL3 genes.

Comparative physiological and transcriptomic analysis of sono-biochemical control over post-acidification of Lactobacillus delbrueckii subsp. bulgaricus.

Thermosonication (UT) prestress treatments combining with varied fermentation patterns has been revealed as an effective method to regulate post-acidification as exerted by Lactobacillus delbrueckii subsp. bulgaricus (L. delbrueckii), but sono-biochemical controlling mechanisms remain elusive. This study employed physiological and transcriptomic analysis to explore the response mechanism of L. delbrueckii to UT-induced microstress (600 W, 33 kHz, 10 min). UT stress-induced inhibition of acidification of L. delbrueckii during (post)-fermentation was first confirmed, relying on the UT process parameters such as stress exposure duration and UT power. The significantly enhanced membrane permeability in cells treated by 600 W for 10 min than the microbes stressed by 420 W for 20 min suggested the higher dependence of UT-derived stresses on the treatment durations, relative to the ultrasonic powers. In addition, ultrasonication treatment-induced changes in cell membrane integrity enhanced and/or disrupted permeability of L. delbrueckii, resulting in an imbalance in intracellular conditions associated with corresponding alterations in metabolic behaviors and fermentation efficiencies. UT-prestressed inoculum exhibited a 21.46% decrease in the membrane potential during the lag phase compared to untreated samples, with an intracellular pH of 5.68 ± 0.12, attributed to the lower activities of H+-ATPase and lactate dehydrogenase due to UT stress pretreatments. Comparative transcriptomic analysis revealed that UT prestress influenced the genes related to glycolysis, pyruvate metabolism, fatty acid synthesis, and ABC transport. The genes encoding 3-oxoacyl-[acyl-carrier-protein] reductases I, II, and III, CoA carboxylase, lactate dehydrogenase, pyruvate oxidase, glucose-6-phosphate isomerase, and glycerol-3-phosphate dehydrogenase were downregulated, thus identifying the relevance of the UT microstresses-downregulated absorption and utilization of carbohydrates with the attenuated fatty acid production and energy metabolisms. These findings could contribute to provide a better understanding of the inactivated effects on the post-acidification of L. delbrueckii by ultrasonic pretreatments, thus providing theoretical basis for the targeted optimization of acidification inhibition efficiencies for yogurt products during chilled preservation processes.

A reanalysis and integration of transcriptomics and proteomics datasets unveil novel drug targets for Mekong schistosomiasis.

Schistosomiasis, caused by Schistosoma trematodes, is a significant global health concern, particularly affecting millions in Africa and Southeast Asia. Despite efforts to combat it, the rise of praziquantel (PZQ) resistance underscores the need for new treatment options. Protein kinases (PKs) are vital in cellular signaling and offer potential as drug targets. This study focused on focal adhesion kinase (FAK) as a candidate for anti-schistosomal therapy. Transcriptomic and proteomic analyses of adult S. mekongi worms identified FAK as a promising target due to its upregulation and essential role in cellular processes. Molecular docking simulations assessed the binding energy of FAK inhibitors to Schistosoma FAK versus human FAK. FAK inhibitor 14 and PF-03814735 exhibited strong binding to Schistosoma FAK with minimal binding for human FAK. In vitro assays confirmed significant anti-parasitic activity against S. mekongi, S. mansoni, and S. japonicum, comparable to PZQ, with low toxicity in human cells, indicating potential safety. These findings highlight FAK as a promising target for novel anti-schistosomal therapies. However, further research, including in vivo studies, is necessary to validate efficacy and safety before clinical use. This study offers a hopeful strategy to combat schistosomiasis and reduce its global impact.

Cuproptosis-related lncRNA signature as a prognostic tool and therapeutic target in diffuse large B cell lymphoma.

Cuproptosis is a newly defined form of programmed cell death that relies on mitochondria respiration. Long noncoding RNAs (lncRNAs) play crucial roles in tumorigenesis and metastasis. However, whether cuproptosis-related lncRNAs are involved in the pathogenesis of diffuse large B cell lymphoma (DLBCL) remains unclear. This study aimed to identify the prognostic signatures of cuproptosis-related lncRNAs in DLBCL and investigate their potential molecular functions. RNA-Seq data and clinical information for DLBCL were collected from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). Cuproptosis-related lncRNAs were screened out through Pearson correlation analysis. Utilizing univariate Cox, least absolute shrinkage and selection operator (Lasso) and multivariate Cox regression analysis, we identified seven cuproptosis-related lncRNAs and developed a risk prediction model to evaluate its prognostic value across multiple groups. GO and KEGG functional analyses, single-sample GSEA (ssGSEA), and the ESTIMATE algorithm were used to analyze the mechanisms and immune status between the different risk groups. Additionally, drug sensitivity analysis identified drugs with potential efficacy in DLBCL. Finally, the protein-protein interaction (PPI) network were constructed based on the weighted gene co-expression network analysis (WGCNA). We identified a set of seven cuproptosis-related lncRNAs including LINC00294, RNF139-AS1, LINC00654, WWC2-AS2, LINC00661, LINC01165 and LINC01398, based on which we constructed a risk model for DLBCL. The high-risk group was associated with shorter survival time than the low-risk group, and the signature-based risk score demonstrated superior prognostic ability for DLBCL patients compared to traditional clinical features. By analyzing the immune landscapes between two groups, we found that immunosuppressive cell types were significantly increased in high-risk DLBCL group. Moreover, functional enrichment analysis highlighted the association of differentially expressed genes with metabolic, inflammatory and immune-related pathways in DLBCL patients. We also found that the high-risk group showed more sensitivity to vinorelbine and pyrimethamine. A cuproptosis-related lncRNA signature was established to predict the prognosis and provide insights into potential therapeutic strategies for DLBCL patients.

An integrated bioinformatic analysis of microarray datasets to identify biomarkers and miRNA-based regulatory networks in leishmaniasis.

Micro RNAs (miRNAs, miRs) and relevant networks might exert crucial functions during differential host cell infection by the different Leishmania species. Thus, a bioinformatic analysis of microarray datasets was developed to identify pivotal shared biomarkers and miRNA-based regulatory networks for Leishmaniasis. A transcriptomic analysis by employing a comprehensive set of gene expression profiling microarrays was conducted to identify the key genes and miRNAs relevant for Leishmania spp. infections. Accordingly, the gene expression profiles of healthy human controls were compared with those of individuals infected with Leishmania mexicana, L. major, L. donovani, and L. braziliensis. The enrichment analysis for datasets was conducted by utilizing EnrichR database, and Protein-Protein Interaction (PPI) network to identify the hub genes. The prognostic value of hub genes was assessed by using receiver operating characteristic (ROC) curves. Finally, the miRNAs that interact with the hub genes were identified using miRTarBase, miRWalk, TargetScan, and miRNet. Differentially expressed genes were identified between the groups compared in this study. These genes were significantly enriched in inflammatory responses, cytokine-mediated signaling pathways and granulocyte and neutrophil chemotaxis responses. The identification of hub genes of recruited datasets suggested that TNF, SOCS3, JUN, TNFAIP3, and CXCL9 may serve as potential infection biomarkers and could deserve value as prognostic biomarkers for leishmaniasis. Additionally, inferred data from miRWalk revealed a significant degree of interaction of a number of miRNAs (hsa-miR-8085, hsa-miR-4673, hsa-miR-4743-3p, hsa-miR-892c-3p, hsa-miR-4644, hsa-miR-671-5p, hsa-miR-7106-5p, hsa-miR-4267, hsa-miR-5196-5p, and hsa-miR-4252) with the majority of the hub genes, suggesting such miRNAs play a crucial role afterwards parasite infection. The hub genes and hub miRNAs identified in this study could be potentially suggested as therapeutic targets or biomarkers for the management of leishmaniasis.

Co-expression analysis reveals distinct alliances around two carbon fixation pathways in hydrothermal vent symbionts.

Most autotrophic organisms possess a single carbon fixation pathway. The chemoautotrophic symbionts of the hydrothermal vent tubeworm Riftia pachyptila, however, possess two functional pathways: the Calvin-Benson-Bassham (CBB) and the reductive tricarboxylic acid (rTCA) cycles. How these two pathways are coordinated is unknown. Here we measured net carbon fixation rates, transcriptional/metabolic responses and transcriptional co-expression patterns of Riftia pachyptila endosymbionts by incubating tubeworms collected from the East Pacific Rise at environmental pressures, temperature and geochemistry. Results showed that rTCA and CBB transcriptional patterns varied in response to different geochemical regimes and that each pathway is allied to specific metabolic processes; the rTCA is allied to hydrogenases and dissimilatory nitrate reduction, whereas the CBB is allied to sulfide oxidation and assimilatory nitrate reduction, suggesting distinctive yet complementary roles in metabolic function. Furthermore, our network analysis implicates the rTCA and a group 1e hydrogenase as key players in the physiological response to limitation of sulfide and oxygen. Net carbon fixation rates were also exemplary, and accordingly, we propose that co-activity of CBB and rTCA may be an adaptation for maintaining high carbon fixation rates, conferring a fitness advantage in dynamic vent environments.

Machine learning survival prediction using tumor lipid metabolism genes for osteosarcoma.

Osteosarcoma is a primary malignant tumor that commonly affects children and adolescents, with a poor prognosis. The existence of tumor heterogeneity leads to different molecular subtypes and survival outcomes. Recently, lipid metabolism has been identified as a critical characteristic of cancer. Therefore, our study aims to identify osteosarcoma's lipid metabolism molecular subtype and develop a signature for survival outcome prediction. Four multicenter cohorts-TARGET-OS, GSE21257, GSE39058, and GSE16091-were amalgamated into a unified Meta-Cohort. Through consensus clustering, novel molecular subtypes within Meta-Cohort patients were delineated. Subsequent feature selection processes, encompassing analyses of differentially expressed genes between subtypes, univariate Cox analysis, and StepAIC, were employed to pinpoint biomarkers related to lipid metabolism in TARGET-OS. We selected the most effective algorithm for constructing a Lipid Metabolism-Related Signature (LMRS) by utilizing four machine-learning algorithms reconfigured into ten unique combinations. This selection was based on achieving the highest concordance index (C-index) in the test cohort of GSE21257, GSE39058, and GSE16091. We identified two distinct lipid metabolism molecular subtypes in osteosarcoma patients, C1 and C2, with significantly different survival rates. C1 is characterized by increased cholesterol, fatty acid synthesis, and ketone metabolism. In contrast, C2 focuses on steroid hormone biosynthesis, arachidonic acid, and glycerolipid and linoleic acid metabolism. Feature selection in the TARGET-OS identified 12 lipid metabolism genes, leading to a model predicting osteosarcoma patient survival. The LMRS, based on the 12 identified genes, consistently accurately predicted prognosis across TARGET-OS, testing cohorts, and Meta-Cohort. Incorporating 12 published signatures, LMRS showed robust and significantly superior predictive capability. Our results offer a promising tool to enhance the clinical management of osteosarcoma, potentially leading to improved clinical outcomes.

Multiomics analysis of platelet-rich plasma promoting biological performance of mesenchymal stem cells.

Mesenchymal Stem Cells are ideal seed cells for tissue repair and cell therapy and have promising applications in regenerative medicine and tissue engineering. Using Platelet-Rich Plasma as an adjuvant to create and improve the microenvironment for Mesenchymal Stem Cells growth can enhance the biological properties of Mesenchymal Stem Cells and improve the efficacy of cell therapy. However, the mechanism by which Platelet-Rich Plasma improves the biological performance of Mesenchymal Stem Cells is still unknown. In this study, by examining the effects of Platelet-Rich Plasma on the biological performance of Mesenchymal Stem Cells, combined with multiomics analysis (Transcriptomics, Proteomics and Metabolomics) and related tests, we analyzed the specific pathways, related mechanisms and metabolic pathways of Platelet-Rich Plasma to improve the biological performance of Mesenchymal Stem Cells. In an in vitro cell culture system, the biological performance of Mesenchymal Stem Cells was significantly improved after replacing Foetal Bovine Serum with Platelet-Rich Plasma, and the genes (ESM1, PDGFB, CLEC7A, CCR1 and ITGA6 et al.) related to cell proliferation, adhesion, growth, migration and signal transduction were significantly upregulated. Platelet-Rich Plasma can enhance the secretion function of MSC exosomes, significantly upregulate many proteins related to tissue repair, immune regulation and anti-infection, and enhance the repair effect of exosomes on skin injury. After replacing Foetal Bovine Serum with Platelet-Rich Plasma, Mesenchymal Stem Cells underwent metabolic reprogramming, the metabolism of amino acids and fatty acids and various signaling pathways were changed, the anabolic pathways of various proteins were enhanced. These results provide a theoretical and technical reference for optimizing the Mesenchymal Stem Cells culture system, improving the biological characteristics and clinical application effects of Mesenchymal Stem Cells.

HyperGCN: an effective deep representation learning framework for the integrative analysis of spatial transcriptomics data.

BACKGROUND: Advances of spatial transcriptomics technologies enabled simultaneously profiling gene expression and spatial locations of cells from the same tissue. Computational tools and approaches for integration of transcriptomics data and spatial context information are urgently needed to comprehensively explore the underlying structure patterns. In this manuscript, we propose HyperGCN for the integrative analysis of gene expression and spatial information profiled from the same tissue. HyperGCN enables data visualization and clustering, and facilitates downstream analysis, including domain segmentation, the characterization of marker genes for the specific domain structure and GO enrichment analysis. RESULTS: Extensive experiments are implemented on four real datasets from different tissues (including human dorsolateral prefrontal cortex, human positive breast tumors, mouse brain, mouse olfactory bulb tissue and Zabrafish melanoma) and technologies (including 10X visium, osmFISH, seqFISH+, 10X Xenium and Stereo-seq) with different spatial resolutions. The results show that HyperGCN achieves superior clustering performance and produces good domain segmentation effects while identifies biologically meaningful spatial expression patterns. This study provides a flexible framework to analyze spatial transcriptomics data with high geometric complexity. CONCLUSIONS: HyperGCN is an unsupervised method based on hypergraph induced graph convolutional network, where it assumes that there existed disjoint tissues with high geometric complexity, and models the semantic relationship of cells through hypergraph, which better tackles the high-order interactions of cells and levels of noise in spatial transcriptomics data.

Integrated metabolomic and transcriptomic analysis reveals the regulatory mechanisms of flavonoid and alkaloid biosynthesis in the new and old leaves of Murraya tetramera Huang.

BACKGROUND: Murraya tetramera Huang is a traditional Chinese woody medicine. Its leaves contain flavonoids, alkaloids, and other active compounds, which have anti-inflammatory and analgesic effects, as well as hypoglycemic and lipid-lowering effects, and anti-tumor effects. There are significant differences in the content of flavonoids and alkaloids in leaves during different growth cycles, but the synthesis mechanism is still unclear. RESULTS: In April 2021, new leaves (one month old) and old leaves (one and a half years old) of M. tetramera were used as experimental materials to systematically analyze the changes in differentially expressed genes (DEGs) and differentially accumulated metabolites (DAMs) with transcriptomics and metabolomics technology. This was done to identify the signaling pathways of flavonoid and alkaloid synthesis. The results showed that the contents of total alkaloids and flavonoids in old leaves were significantly higher than those in new leaves. Thirteen flavonoid compounds, three isoflavone compounds, and nineteen alkaloid compounds were identified, and 125 and 48 DEGs related to flavonoid and alkaloid synthesis were found, respectively. By constructing the KEGG (Kyoto Encyclopedia of Genes and Genomes) network of DEGs and DAMs, it was shown that the molecular mechanism of flavonoid biosynthesis in M. tetramera mainly focuses on the "flavonoid biosynthetic pathway" and the "flavonoid and flavonol biosynthetic pathway". Among them, p-Coumaryl alcohol, Sinapyl alcohol, Phloretin, and Isoquercitrin were significantly accumulated in old leaves, the up-regulated expression of CCR (cinnamoyl-CoA reductase) might promote the accumulation of p-Coumaryl alcohol, upregulation of F5H (ferulate-5-hydroxylase) might promote Sinapyl alcohol accumulation. Alkaloids, including indole alkaloids, pyridine alkaloids, imidazole alkaloids, and quinoline alkaloids, were significantly accumulated in old leaves, and a total of 29 genes were associated with these substances. CONCLUSIONS: These data are helpful to better understand the biosynthesis of flavonoids and alkaloids in M. tetramera and provide a scientific basis for the development of medicinal components in M. tetramera.

Genome-wide characterization, functional analysis, and expression profiling of the Aux/IAA gene family in spinach.

BACKGROUND: The auxin/indole-3-acetic acid (Aux/IAA) gene family is a crucial element of the auxin signaling pathway, significantly influencing plant growth and development. Hence, we conducted a comprehensive investigation of Aux/IAAs gene family using the Sp75 and Monoe-Viroflay genomes in spinach. RESULTS: A total of 24 definitive Aux/IAA genes were identified, exhibiting diverse attributes in terms of amino acid length, molecular weight, and isoelectric points. This diversity underscores potential specific roles within the family, such as growth regulation and stress response. Structural analysis revealed significant variations in gene length and molecular weight. These variations indicate distinct roles within the Aux/IAA gene family. Chromosomal distribution analysis exhibited a dispersed pattern, with chromosomes 4 and 1 hosting the highest and lowest numbers of Aux/IAA genes, respectively. Phylogenetic analysis grouped the identified genes into distinct clades, revealing potential evolutionary relationships. Notably, the phylogenetic tree highlighted specific gene clusters suggesting shared genetic ancestry and potential functional synergies within spinach. Expression analysis under NAA treatment unveiled gene-specific and time-dependent responses, with certain genes exhibiting distinct temporal expression patterns. Specifically, SpoIAA5 displayed a substantial increase at 2 h post-NAA treatment, while SpoIAA7 and SpoIAA9 demonstrated continuous rises, peaking at the 4-hour time point. CONCLUSIONS: These observations indicate a complex interplay of gene-specific and temporal regulation in response to auxin. Moreover, the comparison with other plant species emphasized both shared characteristics and unique features in Aux/IAA gene numbers, providing insights into the evolutionary dynamics of this gene family. This comprehensive characterization of Aux/IAA genes in spinach not only establishes the foundation for understanding their specific functions in spinach development but also provides a valuable resource for experimental validation and further exploration of their roles in the intricate network of auxin signaling pathways.

Deep learning-based pathway-centric approach to characterize recurrent hepatocellular carcinoma after liver transplantation.

BACKGROUND: Liver transplantation (LT) is offered as a cure for Hepatocellular carcinoma (HCC), however 15-20% develop recurrence post-transplant which tends to be aggressive. In this study, we examined the transcriptome profiles of patients with recurrent HCC to identify differentially expressed genes (DEGs), the involved pathways, biological functions, and potential gene signatures of recurrent HCC post-transplant using deep machine learning (ML) methodology. MATERIALS AND METHODS: We analyzed the transcriptomic profiles of primary and recurrent tumor samples from 7 pairs of patients who underwent LT. Following differential gene expression analysis, we performed pathway enrichment, gene ontology (GO) analyses and protein-protein interactions (PPIs) with top 10 hub gene networks. We also predicted the landscape of infiltrating immune cells using Cibersortx. We next develop pathway and GO term-based deep learning models leveraging primary tissue gene expression data from The Cancer Genome Atlas (TCGA) to identify gene signatures in recurrent HCC. RESULTS: The PI3K/Akt signaling pathway and cytokine-mediated signaling pathway were particularly activated in HCC recurrence. The recurrent tumors exhibited upregulation of an immune-escape related gene, CD274, in the top 10 hub gene analysis. Significantly higher infiltration of monocytes and lower M1 macrophages were found in recurrent HCC tumors. Our deep learning approach identified a 20-gene signature in recurrent HCC. Amongst the 20 genes, through multiple analysis, IL6 was found to be significantly associated with HCC recurrence. CONCLUSION: Our deep learning approach identified PI3K/Akt signaling as potentially regulating cytokine-mediated functions and the expression of immune escape genes, leading to alterations in the pattern of immune cell infiltration. In conclusion, IL6 was identified to play an important role in HCC recurrence.

Identification and analysis of short-term and long-term salt-associated lncRNAs in the leaf of Avicennia marina.

As a highly salt-resistant mangrove, Avicennia marina can thrive in the hypersaline water. The leaves of Avicennia marina play a crucial role in salinity stress adaptability by secreting salt. Although the functions of long non-coding RNAs (lncRNAs) in leaves remain unknown, they have emerged as regulators in leaf development, aging and salt response. In this study, we employed transcriptomic data of both short-term and long-term salt treated leaves to identify salt-associated lncRNAs of leaf tissue. As a result, 687 short-term and 797 long-term salt-associated lncRNAs were identified. Notably, both short-term and long-term salt-associated lncRNAs exhibited slightly longer lengths and larger exons, but smaller introns compared with salt-non-associated lncRNAs. Furthermore, salt-associated lncRNAs also displayed higher tissue-specificity than salt-non-associated lncRNAs. Most of the salt-associated lncRNAs were common to short- and long-term salt treatments. And about one fifth of the downregulated salt-associated lncRNAs identified both in two terms were leaf tissue-specific lncRNAs. Besides, these leaf-specific lncRNAs were found to be involved in the oxidation-reduction and photosynthesis processes, as well as several metabolic processes, suggesting the noticeable functions of salt-associated lncRNAs in regulating salt responses of Avicennia marina leaves.

Growth behavior and mRNA expression profiling during growth of IPEC-J2 cells.

OBJECTIVE: The IPEC-J2 cell line is used as an in vitro small intestine model for swine, but it is also used as a model for the human intestine, presenting a relatively unique setting. By combining electric cell-substrate impedance sensing, with next-generation-sequencing technology, we showed that mRNA gene expression profiles and related pathways can depend on the growth phase of IPEC-J2 cells. Our investigative approach welcomes scientists to reproduce or modify our protocols and endorses putting their gene expression data in the context of the respective growth phase of the cells. RESULTS: Three time points are presented: (TP1) 1 h after medium change (= 6 h after seeding of cells), (TP2) the time point of the first derivative maximum of the cell growth curve, and a third point at the beginning of the plateau phase (TP3). Significantly outstanding at TP1 compared to TP2 was upregulated PLEKHN1, further FOSB and DEGS2 were significantly downregulated at TP2 compared to TP3. Any provided data can be used to improve next-generation experiments with IPEC-J2 cells.

The draft genome of Nitzschia closterium f. minutissima and transcriptome analysis reveals novel insights into diatom biosilicification.

BACKGROUND: Nitzschia closterium f. minutissima is a commonly available diatom that plays important roles in marine aquaculture. It was originally classified as Nitzschia (Bacillariaceae, Bacillariophyta) but is currently regarded as a heterotypic synonym of Phaeodactylum tricornutum. The aim of this study was to obtain the draft genome of the marine microalga N. closterium f. minutissima to understand its phylogenetic placement and evolutionary specialization. Given that the ornate hierarchical silicified cell walls (frustules) of diatoms have immense applications in nanotechnology for biomedical fields, biosensors and optoelectric devices, transcriptomic data were generated by using reference genome-based read mapping to identify significantly differentially expressed genes and elucidate the molecular processes involved in diatom biosilicification. RESULTS: In this study, we generated 13.81 Gb of pass reads from the PromethION sequencer. The draft genome of N. closterium f. minutissima has a total length of 29.28 Mb, and contains 28 contigs with an N50 value of 1.23 Mb. The GC content was 48.55%, and approximately 18.36% of the genome assembly contained repeat sequences. Gene annotation revealed 9,132 protein-coding genes. The results of comparative genomic analysis showed that N. closterium f. minutissima was clustered as a sister lineage of Phaeodactylum tricornutum and the divergence time between them was estimated to be approximately 17.2 million years ago (Mya). CAFF analysis demonstrated that 220 gene families that significantly changed were unique to N. closterium f. minutissima and that 154 were specific to P. tricornutum, moreover, only 26 gene families overlapped between these two species. A total of 818 DEGs in response to silicon were identified in N. closterium f. minutissima through RNA sequencing, these genes are involved in various molecular processes such as transcription regulator activity. Several genes encoding proteins, including silicon transporters, heat shock factors, methyltransferases, ankyrin repeat domains, cGMP-mediated signaling pathways-related proteins, cytoskeleton-associated proteins, polyamines, glycoproteins and saturated fatty acids may contribute to the formation of frustules in N. closterium f. minutissima. CONCLUSIONS: Here, we described a draft genome of N. closterium f. minutissima and compared it with those of eight other diatoms, which provided new insight into its evolutionary features. Transcriptome analysis to identify DEGs in response to silicon will help to elucidate the underlying molecular mechanism of diatom biosilicification in N. closterium f. minutissima.

Transcriptome profiling of immune rejection mechanisms in a porcine vascularized composite allotransplantation model.

Background: Vascularized composite allotransplantation (VCA) offers the potential for a biological, functional reconstruction in individuals with limb loss or facial disfigurement. Yet, it faces substantial challenges due to heightened immune rejection rates compared to solid organ transplants. A deep understanding of the genetic and immunological drivers of VCA rejection is essential to improve VCA outcomes. Methods: Heterotopic porcine hindlimb VCA models were established and followed until reaching the endpoint. Skin and muscle samples were obtained from VCA transplant recipient pigs for histological assessments and RNA sequencing analysis. The rejection groups included recipients with moderate pathological rejection, treated locally with tacrolimus encapsulated in triglycerol-monostearate gel (TGMS-TAC), as well as recipients with severe end-stage rejection presenting evident necrosis. Healthy donor tissue served as controls. Bioinformatics analysis, immunofluorescence, and electron microscopy were utilized to examine gene expression patterns and the expression of immune response markers. Results: Our comprehensive analyses encompassed differentially expressed genes, Gene Ontology, and Kyoto Encyclopedia of Genes and Genomes pathways, spanning various composite tissues including skin and muscle, in comparison to the healthy control group. The analysis revealed a consistency and reproducibility in alignment with the pathological rejection grading. Genes and pathways associated with innate immunity, notably pattern recognition receptors (PRRs), damage-associated molecular patterns (DAMPs), and antigen processing and presentation pathways, exhibited upregulation in the VCA rejection groups compared to the healthy controls. Our investigation identified significant shifts in gene expression related to cytokines, chemokines, complement pathways, and diverse immune cell types, with CD8 T cells and macrophages notably enriched in the VCA rejection tissues. Mechanisms of cell death, such as apoptosis, necroptosis and ferroptosis were observed and coexisted in rejected tissues. Conclusion: Our study provides insights into the genetic profile of tissue rejection in the porcine VCA model. We comprehensively analyze the molecular landscape of immune rejection mechanisms, from innate immunity activation to critical stages such as antigen recognition, cytotoxic rejection, and cell death. This research advances our understanding of graft rejection mechanisms and offers potential for improving diagnostic and therapeutic strategies to enhance the long-term success of VCA.

Identifying hub genes in response to ustekinumab and the impact of ustekinumab treatment on fibrosis in Crohn's disease.

Introduction: Crohn's disease (CD) is a chronic inflammatory disease. Approximately 50% of patients with CD progressed from inflammation to fibrosis. Currently, there are no effective drugs for treating intestinal fibrosis. Biologic therapies for CD such as ustekinumab have benefited patients; however, up to 30% of patients with CD have no response to initial treatment, and the effect of ustekinumab on intestinal fibrosis is still uncertain. Therefore, it is of great significance to explore the predictive factors of ustekinumab treatment response and the effect of ustekinumab on intestinal fibrosis. Materials and methods: Public datasets-GSE207465 (blood samples) and GSE112366 and GSE207022 (intestinal samples)-were downloaded and analyzed individually (unmerged) based on the treatment response. Differentially expressed genes (DEGs) were identified by the "limma" R package and changes in immune cell infiltration were determined by the "CIBERSORT" R package in both blood and intestinal samples at week 0 (before treatment). To find predictive factors of ustekinumab treatment response, the weighted gene co-expression network analysis (WGCNA) R package was used to identify hub genes in GSE112366. Hub genes were then verified in GSE207022, and a prediction model was built by random forest algorithm. Furthermore, fibrosis-related gene changes were analyzed in ileal samples before and after treatment with ustekinumab. Results: (1) Our analysis found that MUC1, DUOX2, LCN2, and PDZK1IP1 were hub genes in GSE112366. GSE207022 revealed that MUC1 (AUC:0.761), LCN2 (AUC:0.79), and PDZK1IP1 (AUC:0.731) were also lower in the response group. Moreover, the random forest model was shown to have strong predictive capabilities in identifying responders (AUC = 0.875). To explore the relationship between intestinal tissue and blood, we found that ITGA4 had lower expression in the intestinal and blood samples of responders. The expression of IL18R1 is also lower in responders' intestines. IL18, the ligand of IL18R1, was also found to have lower expression in the blood samples from responders vs. non-responders. (2) GSE112366 revealed a significant decrease in fibrosis-related module genes (COL4A1, TUBB6, IFITM2, SERPING1, DRAM1, NAMPT, MMP1, ZEB2, ICAM1, PFKFB3, and ACTA2) and fibrosis-related pathways (ECM-receptor interaction and PI3K-AKT pathways) after ustekinumab treatment. Conclusion: MUC1, LCN2, and PDZK1IP1 were identified as hub genes in intestinal samples, with lower expression indicating a positive prediction of ustekinumab treatment response. Moreover, ITGA4 and IL18/IL18R1 may be involved in the treatment response in blood and intestinal samples. Finally, ustekinumab treatment was shown to significantly alter fibrotic genes and pathways.

Immune cell infiltration and prognostic index in cervical cancer: insights from metabolism-related differential genes.

Background: Cervical cancer remains a significant gynecologic malignancy in both China and the United States, posing a substantial threat to women's lives and health due to its high morbidity and mortality rates. Altered energy metabolism and dysregulated mitochondrial function play crucial roles in the development, growth, metastasis, and recurrence of malignant tumors. In this study, we aimed to predict prognosis and assess efficacy of anti-tumor therapy in cervical cancer patients based on differential genes associated with mitochondrial metabolism. Methods: Transcriptomic data and clinical profiles of cervical cancer patients were retrieved from the TCGA and GEO databases. Differential gene-related cellular pathways were identified through GO, KEGG, and GSEA analyses. Prognostic indices were constructed using LASSO regression analysis. Immune cell infiltration was assessed using CIBERSORT and ssGSEA, and the correlation between immune checkpoint inhibitor genes and differential genes was examined. Tumor mutation load (TMB) and its association with prognostic indices were analyzed using nucleotide variant data from the TCGA database. Patient response to immunotherapy and sensitivity to antitumor drugs were determined using the TIDE algorithm and the oncoPredic algorithm, respectively. Results: A prognostic index based on metabolism-related differential genes was developed to predict the clinical outcome of cervical cancer patients, enabling their classification into two distinct subtypes. The prognostic index emerged as an independent risk factor for unfavorable prognosis. The high-index group exhibited a significantly worse overall prognosis, along with elevated tumor mutation burden (TMB), increased immune cell infiltration, and lower TIDE scores, indicating a potential benefit from immunotherapy. Conversely, the low-index group demonstrated increased sensitivity to metabolism-related antitumor agents, specifically multikinase inhibitors. Conclusion: The aim of this study was to develop a prognostic index based on differential genes associated with mitochondrial metabolism, which could be used to predict cervical cancer patients' prognoses. When combined with TIDE and TMB analyses, this prognostic index offers insights into the immune cell infiltration landscape, as well as the potential efficacy of immunotherapy and targeted therapy. Our analysis suggests that the Iron-Sulfur Cluster Assembly Enzyme (ISCU) gene holds promise as a biomarker for cervical cancer immunotherapy.

Reduced protein-coding transcript diversity in severe dengue emphasises the role of alternative splicing.

Dengue fever, a neglected tropical arboviral disease, has emerged as a global health concern in the past decade. Necessitating a nuanced comprehension of the intricate dynamics of host-virus interactions influencing disease severity, we analysed transcriptomic patterns using bulk RNA-seq from 112 age- and gender-matched NS1 antigen-confirmed hospital-admitted dengue patients with varying severity. Severe cases exhibited reduced platelet count, increased lymphocytosis, and neutropenia, indicating a dysregulated immune response. Using bulk RNA-seq, our analysis revealed a minimal overlap between the differentially expressed gene and transcript isoform, with a distinct expression pattern across the disease severity. Severe patients showed enrichment in retained intron and nonsense-mediated decay transcript biotypes, suggesting altered splicing efficiency. Furthermore, an up-regulated programmed cell death, a haemolytic response, and an impaired interferon and antiviral response at the transcript level were observed. We also identified the potential involvement of the RBM39 gene among others in the innate immune response during dengue viral pathogenesis, warranting further investigation. These findings provide valuable insights into potential therapeutic targets, underscoring the importance of exploring transcriptomic landscapes between different disease sub-phenotypes in infectious diseases.

Effect of cellular senescence on the response of human peritoneal mesothelial cells to TGF-ß.

Transforming growth factor ß (TGF-ß) is implicated in both mesothelial-to-mesenchymal transition (MMT) and cellular senescence of human peritoneal mesothelial cells (HPMCs). We previously showed that senescent HPMCs could spontaneously acquire some phenotypic features of MMT, which in young HPMCs were induced by TGF-ß. Here, we used electron microscopy, as well as global gene and protein profiling to assess in detail how exposure to TGF-ß impacts on young and senescent HPMCs in vitro. We found that TGF-ß induced structural changes consistent with MMT in young, but not in senescent HPMCs. Of all genes and proteins identified reliably in HPMCs across all treatments and states, 4,656 targets represented overlapping genes and proteins. Following exposure to TGF-ß, 137 proteins and 46 transcripts were significantly changed in young cells, compared to 225 proteins and only 2 transcripts in senescent cells. Identified differences between young and senescent HPMCs were related predominantly to wound healing, integrin-mediated signalling, production of proteases and extracellular matrix components, and cytoskeleton structure. Thus, the response of senescent HPMCs to TGF-ß differs or is less pronounced compared to young cells. As a result, the character and magnitude of the postulated contribution of HPMCs to TGF-ß-induced peritoneal remodelling may change with cell senescence.