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  • Characterization of trehalose-6-phosphate synthase gene family in linseed (Linum usitatissimum L.) and its potential implications in flowering time regulation | BMC Plant Biology

    Characterization of trehalose-6-phosphate synthase gene family in linseed (Linum usitatissimum L.) and its potential implications in flowering time regulation | BMC Plant Biology

    Identification and in silico characterization of LuTPS gene family

    A total of 18 LuTPS genes were identified in silico, distributed across 11 of the 15 linseed chromosomes, excluding Lu06, Lu08, Lu09, and Lu10 (Fig. 1, Table 1). The LuTPS proteins ranged from 800 (LuTPS11.2) to 971 (LuTPS1.1) amino acids long. The predicted isoelectric point (pI) values varied from 5.50 (LuTPS7.6) to 7.05 (LuTPS1.1), with an average pI of 6.08. The predicted localization of the LuTPS proteins varied across different cellular compartments, with the majority localized in the chloroplast (7 proteins), followed by cytoplasm (5 proteins), nucleus (5 proteins), and one in vacuole. The highest number of phosphorylation sites was predicted for LuTPS1.3 and LuTPS1.4 (47 each), followed by LuTPS6.1 and LuTPS6.2 (38 each), and LuTPS1.1 and LuTPS1.2 (34 each), whereas the lowest number of phosphorylation sites was found in LuTPS7.1 and LuTPS7.2 (23 each) (Table 1). The LuTPS1 paralogs exhibited the most complex gene structures, with LuTPS1.1 containing 16 exons and LuTPS1.2, LuTPS1.3, and LuTPS1.4 each containing 17 exons. In contrast, other LuTPS genes displayed simpler structures, with exon numbers ranging from 2 (LuTPS10.2) to 4 (LuTPS11.2) (Figure S1).

    Fig. 1

    Chromosomal positions of trehalose-6-phosphate synthase genes in linseed and their paralogues. Lines connecting TPS genes indicate paralogous relation

    Table 1 List of identified TPS genes in linseed and its in-silico characterization

    Phylogenetic analysis and nomenclature of linseed TPS

    The LuTPS genes were named according to their closest Arabidopsis orthologs as identified in the pairwise distance matrix. In cases where multiple linseed genes showed similarity to the same Arabidopsis TPS, they were designated with numerical suffixes indicating their relative similarity to the Arabidopsis ortholog (Table 1). For phylogenetic analysis of LuTPS, the protein sequences of 18 LuTPS along with 11 AtTPS were aligned using t-coffee, and a phylogenetic tree was constructed using the ML method implemented in MEGA 11. The linseed TPS, along with Arabidopsis TPS, clustered into two distinct groups, Cluster 1 and Cluster 2 (Fig. 2). The LuTPS1 paralogues (LuTPS1.1, LuTPS1.2, LuTPS1.3, LuTPS1.4) were found in Cluster 1, alongside the AtTPS1. Cluster 1 also included AtTPS2, AtTPS3, and AtTPS4. Cluster 2 was further divided into three subclusters, 2a, 2b, and 2c. Subcluster 2a contained LuTPS6.1 and LuTPS6.2, along with AtTPS6, as well as AtTPS5. Subcluster 2b was exclusively composed of LuTPS7 (LuTPS7.1, LuTPS7.2, LuTPS7.3, LuTPS7.4, LuTPS7.5, LuTPS7.6) together with AtTPS7. Subcluster 2c included paralogues of LuTPS8 (LuTPS8.1, LuTPS8.2), LuTPS10 (LuTPS10.1, LuTPS10.2), and LuTPS11 (LuTPS11.1, LuTPS11.2), which clustered alongside AtTPS8, AtTPS10, AtTPS11, and AtTPS9.

    Fig. 2
    figure 2

    Phylogenetic analysis of trehalose-6-phosphate synthase (TPS) genes from linseed and Arabidopsis thaliana. The TPS genes are grouped into two major clusters, reflecting their evolutionary relationships

    Expression analysis of LuTPS genes in vegetative and reproductive tissues

    Gene expression profiles of the LuTPS genes in linseed were analyzed from the available transcriptome sequence data across four different tissues, bud at two developmental stages (bud1, bud2), flower, leaf, and stem, using RNA sequencing data from two early flowering-maturing accessions, IC0523807 and IC0525939. LuTPS6.1, LuTPS6.2, and LuTPS10.1 showed relatively higher expression in all the studied tissues including floral buds, flowers, leaf and stem in both the accessions. LuTPS10.1 showed conspicuously high expression in leaf in both the accessions (Fig. 3a, b). Most of the LuTPS genes except LuTPS1.3, LuTPS1.4, LuTPS7.5, and LuTPS7.6 were found expressed in one or more studied tissue types in both the accessions. A few genes showed high expression across all tissues in both the early flowering accessions which included LuTPS7.1, LuTPS7.2, LuTPS7.3, LuTPS7.4, LuTPS8.1, LuTPS8.2, LuTPS10.1, and LuTPS10.2. In contrast, LuTPS1.1, LuTPS1.2, LuTPS11.1, and LuTPS11.2 exhibited relatively higher expression in flower compared to other reproductive and vegetative tissues. Overall, the top most expressing LuTPS genes were LuTPS6.1, LuTPS6.2, and LuTPS10.1.

    Fig. 3
    figure 3

    Gene expression profiles of TPS genes in reproductive and vegetative tissues of early-flowering linseed genotypes IC0523807 and IC0525939 based on transcriptome data. Gene names are displayed on the right, with expression-based hierarchical clustering shown on the left. The color gradient from red to blue represents transcript abundance in TPM (Transcripts Per Million), ranging from high to low expression levels

    To further pinpoint the potential linseed TPS genes involved in flowering regulation linseed, TPS gene expressions was compared to that of gene expression of important flowering regulators including FLOWERING LOCUS T (FT) (Lus10013532), FRUITFULL (FUL) paralogs (Lus10011349, Lus10021140), SUPPRESSOR OF OVEREXPRESSION OF CONSTANS 1 (SOC1) (Lus10036543), Squamosa Promoter Binding Protein-Like 9 (SPL9) (Lus10007984) using the transcriptome of floral buds at two stages, flowers, leaves and stem of two early flowering linseed accessions IC0523807 and IC0525939 (Fig. 4). A positive correlation of FT was observed only with LuTPS1.1; while FUL (Lus10011349) showed positive correlation with LuTPS1.2, LuTPS6.1, LuTPS6.2, LuTPS7.2, LuTPS7.3, LuTPS7.4 and LuTPS8.2, indicating possible functional redundancy. Interestingly, LuTPS10.1 was the only gene which showed positive correlation with expression of the other FUL paralog (Lus10021140) and SOC1. There was no significant correlation of any TPS gene expression to that of SPL9, indicating no probable role of the latter in regulating TPS gene expression.

    Fig. 4
    figure 4

    Homology-based 3D structures of the LuTPS10.2 protein variant in linseed, showing the amino acid substitution at position 782: (a) GLY-782 in late-flowering genotypes and (b) VAL-782 in early-flowering genotypes. Intramolecular interactions of the LuTPS10.2 variants are illustrated for (c) GLY-782 and (d) VAL-782

    Allelic variation in LuTPS genes in early and late linseed accessions

    To investigate the allelic variations in LuTPS gene family, available whole genome sequencing data of two early flowering-maturing (IC0523807, IC0525939) and two late flowering-maturing (EC0115148, EC0718827) linseed germplasm accessions (Bio-project ID-PRJNA1207411; Table S1) was used and the reference-based SNP calling was performed. Trait-specific SNPs (those capable of distinguishing between early and late flowering-maturing accessions) were identified in two genes, LuTPS6.1 (3 SNPs: 2 SNPs in exons, 1 SNP in intron) (Table 2), and LuTPS10.2 (3 SNPs, all in exons) (Table 3). Both the exonic SNPs in LuTPS6.1 gene were synonymous in nature and therefore had no alteration in the protein sequence. Additionally, in the promoter sequence of the LuTPS6.1 gene, a total of 16 SNPs/indels were identified (Table 2). However, these variations in the promoter region did not exhibit any clear pattern associated with early or late flowering phenotypes. In LuTPS10.2, from the 3 SNPs, one SNP was non-synonymous at nucleotide position 2439 (‘G’ in late flowering-maturing group changed to ‘T’ in early flowering-maturing group) which resulted in an amino acid substitution, Glycine (a non-polar amino acid) to Valine (an aliphatic and hydrophobic amino acid) at position 782 in the resulting protein (Table 3, Figure S2). The other two SNPs were synonymous, causing no change in the protein sequence. Further, in the promoter sequence of LuTPS10.2, a total of 9 SNPs, and 18 indels were identified (Table 3). Of these, 10 SNPs exhibited phenotype-specific patterns, differing between early and late flowering-maturing accessions. Further, two insertions of 2 and 11 nucleotides (at position −1117 to −1116 and −627 to −617, respectively) and a single nucleotide deletion (at position−685) were observed in both early flowering accessions.

    Table 2 SNP haplotype of LuTPS6.1 gene along with 2 kb promoter sequence in 2 early and 2 late flowering-maturing germplasm accessions of linseed. SNPs highlighted in bold font can differentiate between early and late flowering-maturing accessions
    Table 3 SNP haplotype of LuTPS10.2 gene along with 2 kb promoter sequence in 2 early and 2 late flowering-maturing germplasm accessions of linseed. SNPs highlighted in bold font can differentiate between early and late flowering-maturing accessions

    Effect of amino acid substitution on 3D structure of TPS protein

    To evaluate the impact of the amino acid substitution on the LuTPS10.2 protein’s 3D structure, homology-based modeling was performed and the 3D structures of both the original protein (prior to amino acid substitution) and the modified protein (after substitution) were predicted and compared to evaluate any structural changes (Fig. 5a-d). Notably, the proteins from the early flowering-maturing group demonstrated an increase in intramolecular interactions, which typically enhances protein stability (Fig. 5c, d). The substitution of ‘G’ with ‘V’ in the early flowering-maturing group led to a significant reduction in potential energy, contributing to a stabilizing effect on the proteins within these accessions (Table 4).

    Fig. 5
    figure 5

    Correlation of expression of TPS genes and key flowering genes FT (Lus10013532), FUL paralogs (Lus10011349, Lus10021140), SOC1 (Lus10036543) and SPL9 (Lus10007984) in linseed. a Pairwise correlation between gene pairs. Color gradient of the circle from blue to red denotes positive to negative correlation. Size of the circle indicates the strength of p value. b, g Line plots depicting the normalized expression (Transcripts per Million) of TPS paralogs and flowering genes across tissues, floral bud 1, bud 2, flower, leaves, and stem in early-flowering linseed accessions IC0525939 and IC0523807. Expression data under NCBI, BioProject ID PRJNA773597 was used

    Table 4 Potential energy of LuTPS10.2 protein before and after amino acid substitution in late and early flowering-maturing accessions

    Analysis of CREs in LuTPS genes and their enrichment

    2 kb promoter sequences upstream of the start codon of 37,999 linseed genes were extracted from the linseed genome assembly. The position weight matrix data of 2,254 TF binding sites (TFBS) from the PlantPAN 3.0 database were used to predict the occurrence of CRE motifs within these promoter sequences. The CREs within the 2 kb promoter regions of 18 LuTPS genes were identified, and their enrichment was assessed by statistically comparing their frequency against the background frequency across the entire linseed genome (37,999 genes). A total of 32 CREs were identified as significantly enriched in the promoter sequences of LuTPS genes compared to the average genomic distribution at a threshold of q-value ≤ 0.1 (Table 5). Among the significantly enriched CREs, flowering and photoperiod related CREs included TF_motif_seq_0250, TF_motif_seq_0146, TF_motif_seq_0321, TFmatrixID_1221, TFmatrixID_0797, and TF_motif_seq_0481. It is intriguing to note that from the 32 enriched CREs, at least 15 were related to Dof-type domain-containing protein (Table 5). In addition, the promoter sequences of individual LuTPS genes were also analyzed for the presence of CREs using the PlantPAN4 database [62]. The analysis identified a total of 104 CREs, each present at least once in the promoter region of every LuTPS gene (Table S3). It is also important to highlight that six of the enriched CREs (TF_motif_seq_0250, TF_motif_seq_0315, TF_motif_seq_0344, TF_motif_seq_0238, TF_motif_seq_0321, and TF_motif_seq_0458) were consistently present in the promoter of all TPS genes in linseed (Table 5, Table S3).

    Table 5 List of cis-regulatory elements enriched in LuTPS promoter sequences

    Genome scale syntenic network analysis of linseed and nine other plant genomes

    To understand synteny of TPS genes in different crop plants, The genome scale syntenic network analysis of linseed and nine other plants representing cereals, oilseeds, pulses, and a model plant species (Arabidopsis, rice, barley, wheat, sesame, sunflower, soybean, greengram, and cowpea) was performed. A total of 68,930 conserved syntenic blocks (CSBs) were identified in the studied 10 plant species (Table 6). Among the comparisons, the highest number of CSBs involving linseed was found with soybean, (3,673 CSBs), followed by sunflower (2,159), cowpea (2,092), and sesame (2,018) while barley exhibited the fewest CSBs with linseed (588) (Fig. 6, Figure S3, Table 6). Notably, 179 of the 68,930 CSBs contained at least one LuTPS gene (Table 7). The highest number of LuTPS-containing CSBs was observed between linseed and soybean (43), followed by cowpea (25), sunflower (24), and sesame (22). Linseed itself had 15 intraspecific CSBs with gene counts per CSB ranging from 9 to 399 (Fig. 6, Table 7).

    Table 6 Number of total CSBs identified among the 10 crops under study. The numbers in parentheses indicate the size (number of genes) of the smallest and largest CSBs. The numbers in curly braces denote the count of CSBs in the plus and minus orientations, respectively
    Fig. 6
    figure 6

    Genome-wide synteny analysis of linseed with soybean (Glycine max) (a), sunflower (Helianthus annuus) (b), and cowpea (Vigna unguiculata) (c). The genome wide conserved syntenic blocks (CSB) between the two species are depicted in grey shade, and the CSBs harbouring linseed TPS are shown with red lines

    Table 7 Number of CSBs containing at least one LuTPS gene. The numbers in parentheses indicate the size (number of genes) of the smallest and largest CSBs. The numbers in curly braces denote the count of CSBs in the plus and minus orientations, respectively

    Syntenic gene collinearity networks (GCN) of linseed TPS

    In order to identify LuTPS-specific syntenic block networks (SBN), the 179 CSBs (containing at least one LuTPS gene) were analyzed using Cytoscape software [48]. Accordingly, the 179 CSBs clustered into four distinct SBNs. The interaction of linseed TPS genes within these four SBNs was visualized as nodes (representing genes) and edges (representing syntenic relationships). Consequently, the linseed TPS genes formed four gene collinearity networks (GCN) (Fig. 7). Each node (gene) within the GCN represents the CSB in which this gene was located, while the edges highlight the syntenic relationships between them. The largest cluster, GCN Cluster-I (Fig. 7a), comprised of 35 genes, including 10 linseed TPS genes, LuTPS1.1, LuTPS1.2, LuTPS1.3, LuTPS1.4, LuTPS7.1, LuTPS7.2, LuTPS7.3, LuTPS7.4, LuTPS7.5, and LuTPS7.6. The remaining genes in this GCN were TPS genes from soybean, sunflower, cowpea, sesame, Arabidopsis, greengram, barley, and rice. The highest syntenic relationship for linseed TPS genes was observed with soybean and sunflower (6 genes each), followed by cowpea (4 genes), sesame (2 genes), Arabidopsis (2 genes), greengram (2 genes), rice (2 genes), and barley (1 gene). Within Cluster-I, subcluster-Ia consists of four linseed TPS genes (LuTPS1.1, LuTPS1.2, LuTPS1.3, and LuTPS1.4). Syntenic relationships were observed between LuTPS1.1 & LuTPS1.2, and between LuTPS1.3 & LuTPS1.4, though no direct connections were found between the two pairs. However, connections were observed with TPS genes from other plants, suggesting an ancient duplication event that led to the divergence of these gene pairs. Subcluster-Ia and subcluster-Ib were connected through a syntenic relationship between LuTPS1.2 and LuTPS7.5, facilitated by a TPS gene from greengram (XP_014493970.1). In subcluster-Ib, two linseed TPS genes, LuTPS7.5 and LuTPS7.6, displayed direct syntenic relationships. LuTPS7.5 also showed syntenic connections with TPS genes from cowpea and soybean. Subcluster-Ib was linked to Subcluster-Ic through syntenic relationships involving LuTPS7.5 and LuTPS7.6, both of which exhibited synteny with a TPS gene from sesame (XP_020550607.1). Subcluster-Ic comprised four linseed TPS genes (LuTPS7.1, LuTPS7.2, LuTPS7.3, and LuTPS7.4), all of which exhibited direct syntenic relationships with each other, indicating a high degree of conservation within this group. Cluster II was the smallest, with only 9 genes, including two linseed TPS genes, LuTPS6.1 and LuTPS6.2, which did not share direct syntenic interactions (Fig. 7b). Other genes in this cluster were from soybean, cowpea, greengram, sesame, and an Arabidopsis UDP-Glycosyltransferase/trehalose-phosphatase family protein (NP_001322467.1). LuTPS6.1 displayed direct syntenic connections with 7 genes, including the Arabidopsis gene, whereas LuTPS6.2 was connected with TPS genes from soybean, cowpea, greengram, and sesame. Interestingly, this cluster appears specific to dicot species, as no TPS genes from monocots (rice, barley, and wheat) were represented. Cluster III, containing 23 genes, featured four linseed TPS genes, LuTPS8.1, LuTPS8.2, LuTPS10.1, and LuTPS10.2 displaying direct syntenic relationships with one another (Fig. 7c). Other genes in the cluster are from soybean, cowpea, Arabidopsis, sunflower, sesame, greengram, and rice. Notably, wheat and barley TPS genes are absent from this cluster. LuTPS8.1 and LuTPS8.2 both interacted with 18 other TPS genes. The syntenic relationship with the sunflower TPS gene (XP_021976108.1) was specific to LuTPS8.1, while LuTPS8.2 uniquely showed interaction with the soybean TPS gene (XP_006578621.1). Additionally, both LuTPS10.1 and LuTPS10.2 demonstrate syntenic connections with 17 other TPS genes. Cluster IV consists of 17 genes, including two linseed TPS genes, LuTPS11.1 and LuTPS11.2, alongside TPS genes from other species (Fig. 7d). Notably, LuTPS11.1 and LuTPS11.2 exhibited a direct syntenic relationship with each other. Additionally, LuTPS11.1 displayed syntenic connections with all 16 other genes in the cluster, whereas LuTPS11.2 was syntenically linked to 14 genes, with the exceptions being the TPS genes from rice (XP_015610911.1) and soybean (XP_006593555.1). Notably, this cluster included TPS genes from all the ten plant species under study.

    Fig. 7
    figure 7

    Gene collinearity networks (GCNs) derived from conserved syntenic blocks (CSBs) containing TPS genes. Four GCN clusters (I–IV) are shown in panels (a–d). Each node represents a gene, annotated with the corresponding CSB, and edges indicate syntenic relationships between genes

    To study if any of the genes in the linseed TPS specific CSBs also show any molecular interactions with TPS, we studied protein–protein interaction (PPI) network of TPS using the STRING database. The potentially interacting partners of each linseed TPS have been given in Table S4. There were a total of 27 unique interacting proteins identified for all 18 linseed TPS. Most linseed TPS paralogues shared the same interacting partners. Three of the interacting proteins, Lus10017984 (Uncharacterized protein), Lus10038739 (Hexosyltransferase), and Lus10041979 (Sucrose synthase) were part of the linseed TPS specific CSBs. Of which, Lus10017984 (Uncharacterized protein) showed PPI with LuTPS1.1, LuTPS1.2, LuTPS11.2. The other proteins, Lus10041979 (Sucrose synthase) showed PPI with 6 linseed TPS (LuTPS1.1, LuTPS1.2, LuTPS1.3, LuTPS1.4, LuTPS6.1, LuTPS6.2), whereas Lus10038739 (Hexosyltransferase) showed PPI specifically with LuTPS6.1, LuTPS6.2 (Table S4, Fig. 8a). From the 18 LuTPS, for the top ten expressing TPS genes (LuTPS6.1, LuTPS6.2, LuTPS10.1, LuTPS10.2, LuTPS7.1, LuTPS7.2, LuTPS7.3, LuTPS7.4, LuTPS8.1, LuTPS8.2) (Fig. 3), PPI network was drawn (Fig. 8a). For these 10 TPS, there were 20 unique interacting proteins, consisting mainly, trehalose 6-phosphate phosphatases, glucose-1-phosphate adenylyltransferase, sucrose-phosphate synthase, hexosyltransferase etc. (Table S5). The co-expression analysis of these TPS genes with the interacting partners was done using the transcriptome data of two early flowering linseed accessions in floral buds at two stages, flowers, leaves and stem (Fig. 8b). Correlation analysis of LuTPS and their respective interacting partners showed significant positive correlation of Lus10038739 (Hexosyltransferase) with six TPS genes, LuTPS6.1, LuTPS6.2, LuTPS10.2, LuTPS7.1, LuTPS7.2, and LuTPS8.2 (Fig. 8c). Interestingly, Lus10041979 (Sucrose synthase) showed significant positive and negative correlation with LuTPS7.1 and LuTPS10.1, respectively. Five of the ten potential interacting partners of LuTPS6.1 and LuTPS6.2 showed positive correlation with them, which included hexosyltransferases (Lus10038739, Lus10003045), starch synthases (Lus1003324, Lus10008279), and glucose-1-phosphate adenylyltransferase (Lus10023553). It is interesting to note that all linseed TPS, except LuTPS6.1 and LuTPS6.2 showed at least one of the interacting partners as trehalose 6-phosphate phosphatase.

    Fig. 8
    figure 8

    LuTPS protein–protein interactions and co-expression with the potential interacting genes. a Protein–protein interaction network of linseed TPS as identified using string database. The central node with red color is TPS protein, other nodes with different colors indicate the interacting protein and edges indicate their interactions. b Co-expression of TPS genes and respective potential interacting partners in floral buds at two developmental stages, flower, leaf and stem in two biological replicates of early flowering linseed genotypes IC0523807 and IC0525939 based on transcriptome data. The gene expression value is in TPM. c Correlation of gene expression of linseed TPS genes and their potential interacting partners. Size of the circle indicates the strength of p value and color gradient of the circle from blue to red denotes positive to negative correlation

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  • Inpatient versus outpatient management of community-acquired acute skin and soft tissue infections. Clinical outcomes and factors associated with eligibility for early discharge | BMC Infectious Diseases

    Inpatient versus outpatient management of community-acquired acute skin and soft tissue infections. Clinical outcomes and factors associated with eligibility for early discharge | BMC Infectious Diseases

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  • CIArb Guidelines on AI: Key Soft Law Step in Arbitration – Natalia Chumak – Signature Litigation

    1. CIArb Guidelines on AI: Key Soft Law Step in Arbitration – Natalia Chumak  Signature Litigation
    2. AI Arbitrators Will Destroy the Legal Profession (And That’s a Good Thing)  JD Supra
    3. Stop worrying and learn to love AI  Wisconsin Law Journal
    4. Commentary: AI and the Legal Profession at a Crossroads  Caixin Global
    5. When AI’s the Arbiter, What Role Do Humans Play?  Commercial Search

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  • Innovative CRISPR strategy resensitizes lung cancer to treatment

    Innovative CRISPR strategy resensitizes lung cancer to treatment

    In a major step forward for cancer care, researchers at ChristianaCare’s Gene Editing Institute have shown that disabling the NRF2 gene with CRISPR technology can reverse chemotherapy resistance in lung cancer. The approach restores drug sensitivity and slows tumor growth. The findings appear today in the journal Molecular Therapy Oncology.

    This breakthrough stems from more than a decade of research by the Gene Editing Institute into the NRF2 gene, a known driver of treatment resistance. The results were consistent across multiple in vitro studies using human lung cancer cell lines and in vivo animal models.

    We’ve seen compelling evidence at every stage of research. It’s a strong foundation for taking the next step toward clinical trials.”


    Kelly Banas, Ph.D., lead author of the study and associate director of research, Gene Editing Institute

    Potential beyond lung cancer

    The study focused on lung squamous cell carcinoma, an aggressive and common form of non-small cell lung cancer (NSCLC) that accounts for 20% to 30% of all lung cancer cases, according to the American Cancer Society. It’s estimated that over 190,000 people in the U.S. will be diagnosed in 2025.

    While the research centered on this cancer type, the implications are broader. Overactive NRF2 contributes to chemotherapy resistance in several solid tumors, including liver, esophageal and head and neck cancers. The results suggest a CRISPR-based strategy targeting NRF2 could help resensitize a wide range of treatment-resistant tumors to standard chemotherapy.

    “This is a significant step toward overcoming one of the biggest challenges in cancer therapy – drug resistance,” Banas said. “By targeting a key transcription factor that drives resistance, we’ve shown that gene editing can re-sensitize tumors to standard treatment. We’re hopeful that in clinical trials and beyond, this is what will allow chemotherapy to improve outcomes for patients and could enable them to remain healthier during the entirety of their treatment regimen.”

    Targeting a master switch for resistance

    The research zeroed in on a tumor-specific mutation, R34G, in the NRF2 gene, which acts as a master regulator of cellular stress responses. When overactive, NRF2 helps cancer cells withstand chemotherapy.

    Using CRISPR/Cas9, the team engineered lung cancer cells with the R34G mutation and successfully knocked out NRF2. This restored sensitivity to chemotherapy drugs such as carboplatin and paclitaxel. In animal models, tumors directly treated with CRISPR to knockout NRF2 grew more slowly and responded better to treatment.

    “This work brings transformational change to how we think about treating resistant cancers,” said Eric Kmiec, Ph.D., senior author of the study and executive director of the Gene Editing Institute. “Instead of developing entirely new drugs, we are using gene editing to make existing ones effective again.”

    Editing reaches threshold levels

    One of the most promising discoveries was that disrupting NRF2 in just 20% to 40% of tumor cells, was enough to improve the response to chemotherapy and shrink tumors. This insight is particularly relevant for clinical use, where editing every cancer cell may not be feasible.

    To test therapy in mice, the researchers used lipid nanoparticles (LNPs), a non-viral method with high efficiency and low risk of unintended, off-target effects. Sequencing confirmed that the edits were highly specific to the mutated NRF2 gene, with minimal unintended changes elsewhere in the genome.

    “The power of this CRISPR therapy lies in its precision. It’s like an arrow that hits only the bullseye,” said Banas. “This level of specificity with minimal unanticipated genomic side effects offers real hope for the cancer patients who could one day receive this treatment.”

    Source:

    ChristianaCare Gene Editing Institute

    Journal reference:

    Banas, K. H., et al. (2025). Functional Characterization of Tumor-Specific CRISPR-Directed Gene Editing as a Combinatorial Therapy for the Treatment of Solid Tumors. Molecular Therapy Oncology. doi:10.1016/j.omton.2025.201079. https://www.sciencedirect.com/science/article/pii/S2950329925001481?via%3Dihub

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  • Capturing the spatial structure of the benthic microbiome under an intensive aquaculture scenario in Chilean Patagonia | BMC Microbiology

    Capturing the spatial structure of the benthic microbiome under an intensive aquaculture scenario in Chilean Patagonia | BMC Microbiology

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  • EU awards over €600 million to alternative fuel projects to boost zero-emission mobility

    EU awards over €600 million to alternative fuel projects to boost zero-emission mobility

    70 projects are receiving over €600 million in EU grants to electrify and decarbonise road, maritime, inland waterway and air transport along the trans-European transport network (TEN-T). These projects will deploy alternative fuels supply infrastructure such as electric recharging stations, hydrogen refuelling stations, electricity supply and ammonia and methanol bunkering facilities across 24 EU countries.

    Europe’s transport network will be electrified through the installation of more than 1 000 electric recharging points for light-duty vehicles with a capacity of 150 kW. 2 000 new recharging points for heavy-duty vehicles will deliver a capacity of 350kW and 586 recharging points with a 1 MW power output. Additionally, 16 European airports will electrify their ground handling services, making a key contribution towards reducing aviation emissions.

    The hydrogen economy will also be boosted through the installation of 38 hydrogen refuelling stations for cars, trucks and buses. Finally, 24 maritime ports will benefit from the integration of greener technologies, including Onshore Power Supply (OPS), electrification of port services and ammonia bunkering facilities to fuel maritime vessels. 

    Commissioner for Sustainable Transport and Tourism Apostolos Tzitzikostas said:  

    We are currently supporting 70 projects with €600 million in EU funding to accelerate the deployment of alternative fuels infrastructure across Europe. These investments will strengthen our competitiveness and help make the transition to zero-emission mobility easier and more accessible for all citizens.

    Paloma Aba Garrote, Director of the European Climate, Infrastructure and Environment Executive Agency added: 

    This significant EU support for public and private organisations will accelerate the transport sector’s transition toward a sustainable future. With these new projects, more than €2.5 billion in EU grants has been allocated to alternative fuels projects through AFIF since 2021. This demonstrates EU’s ambition to make zero-emission mobility an everyday reality.

    Next steps

    Following the approval of the 70 selected projects by the EU Member States on 13 November 2025, the European Commission will adopt the award decision. The European Climate, Infrastructure and Environment Executive Agency (CINEA) is starting the preparation of the grant agreements with the successful projects.

    Due to the exhaustion of funds, the third cut-off will be cancelled. The Commission will now assess the potential reflows and subsequently prepare a new work programme and call for proposals in the coming months. 

    Background

    The projects have been selected under the second cut-off of the 2024-2025 AFIF call which closed on 11 June 2025. The total awarded grant for these projects is €600 million: €505 million under the General envelope and €95 million under the Cohesion envelope. 

    A total budget of €1 billion was available under this Call: €780 million under the General envelope and €220 million under the Cohesion envelope. This call supports the objectives for publicly accessible electric recharging pools and hydrogen refuelling stations across the EU’s main transport corridors and hubs as set out in the Regulation for the deployment of alternative fuels infrastructure (AFIR), in the ReFuelEU aviation regulation and in the FuelEU maritime regulation. 

    AFIF also aims to improve alternative fuels infrastructure in ports by investing strongly in OPS. This facilitates the transition to renewable and low-carbon fuels by ships, which is also a main priority outlined in the Sustainable Transport Investment Plan. Regarding heavy-duty vehicle charging infrastructure, the Automotive Action Plan encourages the adoption of zero-emission vehicles by speeding up the deployment of necessary infrastructure. 

    For more information

    Continue Reading

  • Hyundai Teases CRATER Concept Global Debut Ahead of AutoMobility LA 2025

    Hyundai Teases CRATER Concept Global Debut Ahead of AutoMobility LA 2025

    The CRATER Concept will be viewable throughout AutoMobility LA 2025 media days, as well as Los Angeles Auto Show public days from Fri., Nov. 21 – Sun., Nov. 30. In addition, the vehicle’s global debut press conference will be livestreamed around the world. The broadcast can be viewed beginning at 9:45 a.m. PT. Tune in to see the reveal of Hyundai’s bold new off-road concept vehicle.

    CRATER Concept is a compact off-road SUV show vehicle that embodies capability and toughness. It is a design exploration that captures the spirit of adventure. Inspired by extreme environments, the CRATER Concept was conceived at Hyundai America Technical Center (HATCI) in Irvine, Calif. and has been crafted to amplify the same spirit and robustness found in Hyundai’s XRT production vehicles, including the IONIQ 5 XRT , SANTA CRUZ XRT , and the new PALISADE XRT PRO .

    Hyundai Motor America

    Hyundai Motor America offers U.S. consumers a technology-rich lineup of cars, SUVs, and electrified vehicles, while supporting Hyundai Motor Company’s Progress for Humanity vision. Hyundai has significant operations in the U.S., including its North American headquarters in California, the Hyundai Motor Manufacturing Alabama assembly plant, the all-new Hyundai Motor Group Metaplant America, and several cutting-edge R&D facilities. These operations, combined with those of Hyundai’s 850 independent dealers, contribute $20.1 billion annually and 190,000 jobs to the U.S. economy, according to a published economic impact report. For more information, visit www.hyundainews.com .

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  • GWR train fitted with F1 tech for two-month superfast wifi trial | Rail industry

    GWR train fitted with F1 tech for two-month superfast wifi trial | Rail industry

    Train wifi in the UK, long a source of frustration for passengers, is about to get radically faster – for a lucky few at least.

    A two-month trial has begun on one Great Western Railway (GWR) train, fitted with technology from Formula One that switches between the signals from 5G masts to low Earth-orbit satellites to provide almost seamless, superfast wifi.

    For now, only one of GWR’s 57 intercity express trains will have a connection good enough to deliver a Netflix series to the seat. However, a successful trial and the promise of lower costs could spell a wider rollout to the rest of the mainline railway by 2030.

    On a test run from London Paddington to Newbury and back, the Guardian found the wifi fast and reliable enough to video call editors at the office, catch up on old Match of the Days on iPlayer and listen to songs on YouTube at the same time, with only occasional blips and pixelation.

    Download speeds reached more than 120 megabytes a second, faster than many homes.

    Speaking at Paddington at the launch of the trial, the rail minister, Peter Hendy, said: “Passenger experience is top of our agenda – and 21st-century experience ought to be seamless fast wifi … which will make the time spent travelling by train even more valuable.”

    He said the trial would complement government investment in improving mobile connectivity, with another £41m set aside for train wifi and low-orbit satellite connections, announced in June’s spending review. The Department for Transport is funding work to eliminate mobile signal black spots in rail tunnels and upgrading 5G infrastructure at stations on GWR routes.

    Lord Hendy said the new state-owned Great British Railways would aspire to fast wifi across the entire railway, but added: “The real question is how quickly and how cheaply it can be rolled out.”

    Hendy said it could be “a real productivity benefit for the whole country, hopefully at a modest cost”.

    He said the department would be awaiting the results of the trial, but its advocates claim the new system could be installed relatively quickly and cheaply without requiring extra infrastructure on the railway. The previous government was considering scrapping free wifi on trains because of the unreliability and cost.

    Nick Fry, the chair of Motion Applied, a tech company spun out of the McLaren racing division, said the pilot would demonstrate the technology was ready. The UK-made tech, pioneered in F1, combines “several pizza-sized boxes” and antennae attached to the roof of the train, allowing it to connect and switch between the best available network, from wifi to 5G to satellite, he said. “It’s very fast with fewer dropouts.”

    The system is also being rolled out on Deutsche Bahn services in Germany and on Brightline and Amtrak trains in the US.

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    “We look forward to providing rail passengers with the same service we provide for Lando Norris and Lewis Hamilton,” Fry added.

    Part of the trial will be to track passenger behaviour to see how much satellite data would be required if free, fast wifi was available for streaming.

    The £300k cost is being funded by Peninsula Transport, a body combining Devon, Cornwall, Plymouth, Somerset and Torbay, with better connectivity seen as a critical investment for parts of England where mobile coverage is patchy.

    Businesses have welcomed the trial. Andy Jasper, the chief executive of the Eden Project in Cornwall, said GWR trains were his “travelling office, and a bloodstream between Cornwall and London – new wifi is going to be the oxygen that keeps everything pumping”.

    Jasper said he was used to having to time conversations onboard for when he knew the wifi would work, such as a quick 10-minute Teams meeting in Plymouth. “Reliable wifi puts your mind at ease – it turns the journey into a prime opportunity to get things done.”

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  • Treasurys, Dollar Rangebound Amid Cloudy Fed Outlook – The Wall Street Journal

    1. Treasurys, Dollar Rangebound Amid Cloudy Fed Outlook  The Wall Street Journal
    2. Treasury yields inch lower as investors anticipate delayed economic data  CNBC
    3. US 10-Year Yield Holds Advance  TradingView
    4. Treasuries, Dollar Rangebound Amid Cloudy Fed Outlook  Barron’s
    5. Bond Traders Eye Make-or-Break Data to Chart Fed’s Next Move  Yahoo Finance

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