Am J Hum Genet. 2025 Feb 18:S0002-9297(25)00044-8. doi: 10.1016/j.ajhg.2025.01.024. Online ahead of print.

ABSTRACT

Congenital heart disease (CHD) is the most common congenital anomaly and a leading cause of infant morbidity and mortality. Despite extensive exploration of the monogenic causes of CHD over the last decades, ∼55% of cases still lack a molecular diagnosis. Investigating digenic interactions, the simplest form of oligogenic interactions, using high-throughput sequencing data can elucidate additional genetic factors contributing to the disease. Here, we conducted a comprehensive analysis of digenic interactions in CHD by utilizing a large CHD trio exome sequencing cohort, comprising 3,910 CHD and 3,644 control trios. We extracted pairs of presumably deleterious rare variants observed in CHD-affected and unaffected children but not in a single parent. Burden testing of gene pairs derived from these variant pairs revealed 29 nominally significant gene pairs. These gene pairs showed a significant enrichment for known CHD genes (p < 1.0 × 10-4) and exhibited a shorter average biological distance to known CHD genes than expected by chance (p = 3.0 × 10-4). Utilizing three complementary biological relatedness approaches including network analyses, biological distance calculations, and candidate gene prioritization methods, we prioritized 10 final gene pairs that are likely to underlie CHD. Analysis of bulk RNA-sequencing data showed that these genes are highly expressed in the developing embryonic heart (p < 1 × 10-4). In conclusion, our findings suggest the potential role of digenic interactions in CHD pathogenesis and provide insights into unresolved molecular diagnoses. We suggest that the application of the digenic approach to additional disease cohorts will significantly enhance genetic discovery rates.

PMID:39983722 | DOI:10.1016/j.ajhg.2025.01.024

Dev Cell. 2025 Feb 18:S1534-5807(25)00059-0. doi: 10.1016/j.devcel.2025.01.018. Online ahead of print.

ABSTRACT

The neural crest is a highly plastic stem cell population that represents an exception to the germ layer theory. Despite being of ectodermal origin, cranial neural crest cells can differentiate into skeletal derivatives typically formed by mesoderm. Here, we report that SMAD2/3-mediated transforming growth factor β (TGF-β) signaling enhances neural crest developmental potential in the chicken embryo. Our results show that TGF-β signaling modulates neural crest axial identity and directly controls the gene circuits that support skeletal differentiation. Cooperation between TGF-β and low levels of WNT signaling in the embryonic head activates cranial-specific cis-regulatory elements. Activation of TGF-β signaling reprogrammed trunk neural crest cells into adopting an anterior identity and led to the development of an improved protocol for the generation of human cranial neural crest cells. Our findings indicate TGF-β signaling is required for the specification of cranial neural crest cells, endowing them with the potential to give rise to the craniofacial skeleton.

PMID:39983721 | DOI:10.1016/j.devcel.2025.01.018

Cell. 2025 Feb 20;188(4):958-977.e23. doi: 10.1016/j.cell.2024.11.034.

ABSTRACT

Membrane contact sites (MCSs) are fundamental for intracellular communication, but their role in intercellular communication remains unexplored. We show that in plants, plasmodesmata communication bridges function as atypical endoplasmic reticulum (ER)-plasma membrane (PM) tubular MCSs, operating at cell-cell interfaces. Similar to other MCSs, ER-PM apposition is controlled by a protein-lipid tethering complex, but uniquely, this serves intercellular communication. Combining high-resolution microscopy, molecular dynamics, and pharmacological and genetic approaches, we show that cell-cell trafficking is modulated through the combined action of multiple C2 domains transmembrane domain proteins (MCTPs) 3, 4, and 6 ER-PM tethers and phosphatidylinositol-4-phosphate (PI4P) lipid. Graded PI4P amounts regulate MCTP docking to the PM, their plasmodesmata localization, and cell-cell permeability. SAC7, an ER-localized PI4P-phosphatase, regulates MCTP4 accumulation at plasmodesmata and modulates cell-cell trafficking capacity in a cell-type-specific manner. Our findings expand MCS functions in information transmission from intracellular to intercellular cellular activities.

PMID:39983675 | DOI:10.1016/j.cell.2024.11.034

J Plant Physiol. 2025 Feb 15;306:154453. doi: 10.1016/j.jplph.2025.154453. Online ahead of print.

ABSTRACT

An interesting aspect that links the geomagnetic field (GMF) to the evolution of life lies in how plants respond to the reduction of the GMF, also known as hypomagnetic field (HMF). In this work, tomato plants (Solanum lycopersicum cv Microtom) were exposed either to GMF or HMF and were studied during the development of leaves and fruit set. Changes of expression of genes encoding for primary and secondary metabolites, including Reactive Oxygen Species (ROS), proteins, fatty acids, polyphenols, chlorophylls, carotenoids and phytohormones were assessed by qRT-PCR, while the corresponding metabolite levels were quantified by GC-MS and HPLC-MS. Two tomato homologs of the fruit fly magnetoreceptor MagR, Isca-like 1 and erpA 2, were modulated by HMF, as were numerous tomato genes under investigation. In tomato leaves, positive correlations were observed with most of the genes associated with phytohormones production, ROS scavenging and production, and lipid metabolism, whereas an almost reversed trend was found in flowers and fruits. Interestingly, downregulation of Isca-like 1 and erpA 2 was found to correlate with an upregulation of most unripe fruit genes. Exposure to HMF reduced chlorophyll and carotenoid content, decreased photosynthetic efficiency and increased non-photochemical quenching. Auxins, gibberellins, cytokinins, abscisic acid, jasmonic acid and salicylic acid content and the expression of genes related to their metabolism correlated with tomato ISCA modulation. The results here reported suggest that Isca-like 1 and erpA 2 might be important players in tomato magnetoreception.

PMID:39983659 | DOI:10.1016/j.jplph.2025.154453

PLoS One. 2025 Feb 21;20(2):e0313947. doi: 10.1371/journal.pone.0313947. eCollection 2025.

ABSTRACT

Bacteriophages largely impact bacterial communities via lysis, gene transfer, and metabolic reprogramming and thus are increasingly thought to alter nutrient and energy cycling across many of Earth's ecosystems. However, there are few model systems to mechanistically and quantitatively study phage-bacteria interactions, especially in soil systems. Here, we isolated, sequenced, and genomically characterized 24 novel phages infecting Klebsiella sp. M5al, a plant growth-promoting, nonencapsulated rhizosphere-associated bacterium, and compared many of their features against all 565 sequenced, dsDNA Klebsiella phage genomes. Taxonomic analyses revealed that these Klebsiella phages belong to three known phage families (Autographiviridae, Drexlerviridae, and Straboviridae) and two newly proposed phage families (Candidatus Mavericviridae and Ca. Rivulusviridae). At the phage family level, we found that core genes were often phage-centric proteins, such as structural proteins for the phage head and tail and DNA packaging proteins. In contrast, genes involved in transcription, translation, or hypothetical proteins were commonly not shared or flexible genes. Ecologically, we assessed the phages' ubiquity in recent large-scale metagenomic datasets, which revealed they were not widespread, as well as a possible direct role in reprogramming specific metabolisms during infection by screening their genomes for phage-encoded auxiliary metabolic genes (AMGs). Even though AMGs are common in the environmental literature, only one of our phage families, Straboviridae, contained AMGs, and the types of AMGs were correlated at the genus level. Host range phenotyping revealed the phages had a wide range of infectivity, infecting between 1-14 of our 22 bacterial strain panel that included pathogenic Klebsiella and Raoultella strains. This indicates that not all capsule-independent Klebsiella phages have broad host ranges. Together, these isolates, with corresponding genome, AMG, and host range analyses, help build the Klebsiella model system for studying phage-host interactions of rhizosphere-associated bacteria.

PMID:39982899 | DOI:10.1371/journal.pone.0313947

Mol Biol Rep. 2025 Feb 21;52(1):258. doi: 10.1007/s11033-025-10330-8.

ABSTRACT

BACKGROUND: Host DNA depletion is a critical tool for accessing the microbiomes of samples that have a small amount of microbial DNA contained in a high host background. Of critical practical importance is the ability to identify microbial DNA sequences in frozen tissue specimens. Here, we compare four existing commercial methods and two newly introduced methods involving chromatin immunoprecipitation (ChIP) on frozen human and pig intestinal biopsies.

RESULTS: We find that all methods that rely on differential lysis of host and microbial cells introduce substantial biases as assessed by 16 S rRNA gene amplicon profiling. However, ChIP enables 10-fold enrichment of microbial DNA while introducing less bias, sufficient to make assessment possible against background, in both pigs and humans.

CONCLUSIONS: We recommend ChIP in situations where host depletion is important but where minimizing taxonomic bias is essential, and the MolYsis or Zymo kit for situations where host depletion level is more important than taxonomic bias.

CONCLUSIONS: We recommend ChIP in situations where host depletion is important but where minimizing taxonomic bias is essential, and the MolYsis or Zymo kit for situations where host depletion level is more important than taxonomic bias.

PMID:39982577 | DOI:10.1007/s11033-025-10330-8

Ann Hematol. 2025 Feb 21. doi: 10.1007/s00277-025-06254-9. Online ahead of print.

ABSTRACT

Monitoring anemia recovery is crucial for clinical intervention. Morphological assessment of red blood cells (RBCs) with peripheral blood smears (PBSs) provides additional information beyond routine blood tests. However, the PBS test is labor-intensive, reliant on manual analysis, and susceptible to variability in expert interpretations. Here we introduce a deep semi-supervised learning method, RBCMatch, to classify RBCs during anemia recovery. Using an acute hemolytic anemic mouse model, PBS images at four different time points during anemia recovery were acquired and segmented into 10,091 single RBC images, with only 5% annotated and used in model training. By employing the semi-supervised strategy Fixmatch, RBCMatch achieved an impressive average classification accuracy of 91.2% on the validation dataset and 87.5% on a held-out dataset, demonstrating its superior accuracy and robustness compared to supervised learning methods, especially when labeled samples are scarce. To characterize the anemia recovery process, principal components (PCs) of RBC embeddings were extracted and visualized. Our results indicated that RBC embeddings quantified the state of anemia recovery, and the second PC had a strong correlation with RBC count and hemoglobin concentration, demonstrating the model's ability to accurately depict RBC morphological changes during anemia recovery. Thus, this study provides a valuable tool for the automatic classification of RBCs and offers novel insights into the assessment of anemia recovery, with the potential to aid in clinical decision-making and prognosis analysis in the future.

PMID:39982510 | DOI:10.1007/s00277-025-06254-9

Proteomes. 2025 Feb 10;13(1):9. doi: 10.3390/proteomes13010009.

ABSTRACT

Background: Chinese hamster ovary (CHO) cells are extensively used in the pharmaceutical industry for producing complex proteins, primarily because of their ability to perform human-like post-translational modifications. However, the efficiency of high-quality protein production can vary significantly for monoclonal antibody-producing cell lines, within the CHO host cell lines or by extrinsic factors. Methods: To investigate the complex cellular mechanisms underlying this variability, a phosphoproteomics analysis was performed using label-free quantitative liquid chromatography after a phosphopeptide enrichment of recombinant CHO cells producing two different antibodies and a tunicamycin treatment experiment. Using MaxQuant and Perseus for data analysis, we identified 2109 proteins and quantified 4059 phosphosites. Results: Significant phosphorylation dynamics were observed in nuclear proteins of cells producing the difficult-to-produce 2G12 mAb. It suggests that the expression of 2G12 regulates nuclear pathways based on increases and decreases in phosphorylation abundance. Furthermore, a substantial number of changes in the phosphorylation pattern related to tunicamycin treatment have been detected. TM treatment affects, among other phosphoproteins, the eukaryotic elongation factor 2 kinase (Eef2k). Conclusions: The alterations in the phosphorylation landscape of key proteins involved in cellular processes highlight the mechanisms behind stress-induced cellular responses.

PMID:39982319 | DOI:10.3390/proteomes13010009

J Funct Morphol Kinesiol. 2025 Feb 10;10(1):61. doi: 10.3390/jfmk10010061.

ABSTRACT

Background/Objectives: In recent years, there has been a significant increase in studies examining motor learning during preschool age and the early years of primary school. This study aimed to investigate sex differences in gross motor competence among Italian children aged 3-11 years. Methods: A convenience sample of 8500 children (mean age = 8.37 years, SD = 1.98; 50% female) was included in this cross-sectional study. Gross motor skills were assessed using the Italian version of the Test of Gross Motor Development-3, which evaluates locomotion and ball control skills. A Linear Mixed Model was applied to examine the interaction between sex and age, with school included as a random intercept and BMI as a covariate. Results: The results revealed a consistent trend of boys achieving significantly higher total scores for global motor competence (p < 0.001) across all age groups, except at age 11. Boys also demonstrated superior performance in ball control skills (p < 0.005) at all ages. In contrast, no significant differences were observed for locomotion skills overall. However, girls outperform boys in locomotor skills at ages 6, 7, and 8 (p < 0.001), with this trend disappearing by age 9. Conclusions: These findings highlight important sex-related differences in gross motor development during childhood, influenced by both biological and environmental factors. The results underscore the need for targeted interventions in educational settings to provide equitable opportunities for motor skill development, particularly for girls. Enhancing the quality of physical education and addressing gender disparities can support the acquisition of essential motor skills and promote lifelong physical activity.

PMID:39982301 | DOI:10.3390/jfmk10010061

Epigenomes. 2025 Feb 5;9(1):5. doi: 10.3390/epigenomes9010005.

ABSTRACT

Genomic and epigenomic instability are defining features of cancer, driving tumor progression, heterogeneity, and therapeutic resistance. Central to this process are epigenetic echoes, persistent and dynamic modifications in DNA methylation, histone modifications, non-coding RNA regulation, and chromatin remodeling that mirror underlying genomic chaos and actively influence cancer cell behavior. This review delves into the complex relationship between genomic instability and these epigenetic echoes, illustrating how they collectively shape the cancer genome, affect DNA repair mechanisms, and contribute to tumor evolution. However, the dynamic, context-dependent nature of epigenetic changes presents scientific and ethical challenges, particularly concerning privacy and clinical applicability. Focusing on lung cancer, we examine how specific epigenetic patterns function as biomarkers for distinguishing cancer subtypes and monitoring disease progression and relapse.

PMID:39982247 | DOI:10.3390/epigenomes9010005

Cytometry A. 2025 Feb 21. doi: 10.1002/cyto.a.24917. Online ahead of print.

ABSTRACT

Alterations in nuclear morphology are useful adjuncts and even diagnostic tools used by pathologists in the diagnosis and grading of many tumors, particularly malignant tumors. Large datasets such as TCGA and the Human Protein Atlas, in combination with emerging machine learning and statistical modeling methods, such as feature extraction and deep learning techniques, can be used to extract meaningful knowledge from images of nuclei, particularly from cancerous tumors. Here, we describe a new technique based on the mathematics of optimal transport for modeling the information content related to nuclear chromatin structure directly from imaging data. In contrast to other techniques, our method represents the entire information content of each nucleus relative to a template nucleus using a transport-based morphometry (TBM) framework. We demonstrate that the model is robust to different staining patterns and imaging protocols, and can be used to discover meaningful and interpretable information within and across datasets and cancer types. In particular, we demonstrate morphological differences capable of distinguishing nuclear features along the spectrum from benign to malignant categories of tumors across different cancer tissue types, including tumors derived from liver parenchyma, thyroid gland, lung mesothelium, and skin epithelium. We believe these proof-of-concept calculations demonstrate that the TBM framework can provide the quantitative measurements necessary for performing meaningful comparisons across a wide range of datasets and cancer types that can potentially enable numerous cancer studies, technologies, and clinical applications and help elevate the role of nuclear morphometry into a more quantitative science.

PMID:39982036 | DOI:10.1002/cyto.a.24917

Protein Sci. 2025 Mar;34(3):e70069. doi: 10.1002/pro.70069.

ABSTRACT

Chikungunya virus (CHIKV) is an emerging pathogen with pandemic potential. CHIKV infection in humans is transmitted by mosquitoes and induces common symptoms of high fever, arthralgia and myalgia. Because no specific antiviral drugs for treatment of CHIKV infection are available, drug development remains a central goal. The chikungunya virus protease from nsP2 (CHIKVP) has emerged as a key drug target due to its indispensable role in viral replication via cleavage of the viral polyprotein. To date, effective tools for screening for CHIKVP inhibitors that reflect the most critical polyprotein cleavage sites have been lacking, hampering drug-development efforts. We found that the recognition ability of CHIKVP is sensitive to the length of peptide substrates. In this study, we report a robust fluorogenic substrate comprising a 15-mer peptide derived from the nsP3/4 junction from the CHIKV polyprotein. This peptide is flanked by an ACC-Lys(dnp) donor-quencher pair. Our new substrate acc-CHIK15-dnp shows a 30-fold improved signal-to-noise ratio as compared to the previously reported edab8 substrate, which is also based on the nsP3/4 junction. We found acc-CHIK15-dnp is recognized only by CHIKVP but not by other alphavirus proteases. This is surprising due to the high level of sequence conservation in the alpha virus polyprotein junctions and indicates that the P-side residues are more important than the P'-side sequence for effective CHIKVP cleavage. The robust signal-to-noise ratio obtained using acc-CHIK15-dnp derived from the nsP3/4 cleavage site enabled much improved small molecule HTS on CHIKV relative to other fluorogenic reporters.

PMID:39981948 | DOI:10.1002/pro.70069

Digit Health. 2025 Feb 19;11:20552076241288724. doi: 10.1177/20552076241288724. eCollection 2025 Jan-Dec.

ABSTRACT

Digital biomarkers are quantifiable and objective indicators of a person's physiological function, behavioral state or treatment response, that can be captured using connected sensor technologies such as wearable devices and mobile apps. We envision that continuous and 24-h monitoring of the underlying physiological and behavioral processes through digital biomarkers can enhance early diagnostics, disease management, and self-care of cardiometabolic diseases. Cardiometabolic diseases, which include a combination of cardiovascular and metabolic disorders, represent an emerging global health threat. The prevention potential of cardiometabolic diseases is around 80%, indicating a promising role for interventions in the lifestyle and/or the environmental context. Disruption of sleep and circadian rhythms are increasingly recognized as risk factors for cardiometabolic disease. Digital biomarkers can be used to measure around the clock, that is, day and night, to quantify not only sleep patterns but also diurnal fluctuations of certain biomarkers and processes. In this way, digital biomarkers can support the delivery of optimal timed medical care. Night-time cardiometabolic patterns, such as blood pressure dipping, are predictive of cardiometabolic health outcomes. In addition, the sleep period provides an opportunity for digital cardiometabolic health monitoring with relatively low influence of artifacts, such as physical activity and eating. Digital biomarkers that utilize sleep as a window of health can be used during daily life to enable early diagnosis of cardiometabolic diseases, facilitate remote patient monitoring, and support self-management in people with cardiometabolic diseases. This review describes the influence of sleep and circadian rhythms on cardiometabolic disease and highlights the state-of-the-art sleep and circadian digital biomarkers which could be of benefit in the prevention of cardiometabolic disease.

PMID:39980570 | PMC:PMC11840856 | DOI:10.1177/20552076241288724

Genome Biol. 2025 Feb 20;26(1):33. doi: 10.1186/s13059-025-03497-7.

ABSTRACT

Liquid-liquid phase separation (LLPS) enables the formation of membraneless organelles, essential for cellular organization and implicated in diseases. We introduce catGRANULE 2.0 ROBOT, an algorithm integrating physicochemical properties and AlphaFold-derived structural features to predict LLPS at single-amino-acid resolution. The method achieves high performance and reliably evaluates mutation effects on LLPS propensity, providing detailed predictions of how specific mutations enhance or inhibit phase separation. Supported by experimental validations, including microscopy data, it predicts LLPS across diverse organisms and cellular compartments, offering valuable insights into LLPS mechanisms and mutational impacts. The tool is freely available at https://tools.tartaglialab.com/catgranule2 and https://doi.org/10.5281/zenodo.14205831 .

PMID:39979996 | DOI:10.1186/s13059-025-03497-7

BMC Vet Res. 2025 Feb 20;21(1):81. doi: 10.1186/s12917-025-04517-1.

ABSTRACT

BACKGROUND: The therapeutic potential of exosomes derived from mesenchymal stem cells (MSCs) is increasingly recognized in veterinary medicine. This study explored the feasibility of a microcarrier-based three-dimensional (3D) culture system for producing the exosomes (cEXO). Investigations were conducted to enhance production efficiency, ensure stability, and evaluate the therapeutic potential of cEXO for anti-inflammatory applications while assessing their safety profile.

RESULTS: The microcarrier-based 3D culture system improved efficient production of cEXO, yielding exosomes with acceptable profiles, including a size of approximately 81.22 nm, negative surface charge, and high particle concentration (1.32 × 109 particles/mL). Confocal imaging proved dynamic changes in cell viability across culture phases, highlighting the challenges of maintaining cell viability during repeated exosome collection cycles. Characterization via transmission electron microscopy, nanoparticle tracking analysis, and zeta-potential measurements confirmed the stability and functionality of cEXO, particularly when stored at -20 °C. Functional assays showed that cEXO exerted significant anti-inflammatory activity in RAW264.7 macrophages in an inverse dose-dependent manner, with no observed cytotoxicity to fibroblasts or macrophages. Acute toxicity testing in rats revealed no adverse effects on clinical parameters, organ health, or body weight, supporting the safety of cEXO for therapeutic use.

CONCLUSIONS: This study highlights the potential of a microcarrier-based 3D culture system for scalable cEXO production with robust anti-inflammatory activity, stability, and safety profiles. These findings advance the development of cEXO-based therapies and support their application in veterinary regenerative medicine.

PMID:39979916 | DOI:10.1186/s12917-025-04517-1

BMC Genomics. 2025 Feb 20;26(1):169. doi: 10.1186/s12864-025-11309-2.

ABSTRACT

Common bean (Phaseolus vulgaris), a staple food in Latin America and Africa, serves as a vital source of energy, protein, and essential minerals for millions of people. However, genomics knowledge that breeders could leverage for improvement of this crop is scarce. We have developed and validated a comparative genomics approach to predict conserved transcription factor binding sites (TFBS) in common bean and studied gene regulatory networks. We analyzed promoter regions and identified TFBS for 12,631 bean genes with an average of 6 conserved motifs per gene. Moreover, we discovered a statistically significant relationship between the number of conserved motifs and amount of available experimental evidence of gene regulation. Notably, ERF, MYB, and bHLH transcription factor families dominated conserved motifs, with implications for starch biosynthesis regulation. Furthermore, we provide gene regulatory data as a resource that can be interrogated for the regulatory landscape of any set of genes. Our results underscore the significance of TFBS conservation in legumes and aligns with the notion that core genes often exhibit a more conserved regulatory makeup. The study demonstrates the effectiveness of a comparative genomics approach for addressing genome information gaps in non-model organisms and provides valuable insights into the regulatory networks governing starch biosynthesis genes that can support crop improvement programs.

PMID:39979816 | DOI:10.1186/s12864-025-11309-2

BMC Plant Biol. 2025 Feb 20;25(1):232. doi: 10.1186/s12870-025-06248-9.

ABSTRACT

BACKGROUND: Ca2+ and H2O2 are second messengers that regulate a wide range of cellular events in response to different environmental and developmental cues. In plants, stress-induced H2O2 has been shown to initiate characteristic Ca2+ signatures; however, a clear picture of the molecular connection between H2O2-induced Ca2+ signals and H2O2-induced cellular responses is missing, particularly in cereal crops such as barley. Here, we employed RNA-seq analyses to identify transcriptome changes in roots and leaves of barley after H2O2 treatment under conditions that inhibited the formation of cytosolic Ca2+ transients. To that end, plasma membrane Ca2+ channels were blocked by LaCl3 application prior to stimulation of barley tissues with H2O2.

RESULTS: We examined the expression patterns of 4246 genes that had previously been shown to be differentially expressed upon H2O2 application. Here, we further compared their expression between H2O2 and LaCl3 + H2O2 treatment. Genes showing expression patterns different to the previous study were considered to be Ca2+-dependent H2O2-responsive genes. These genes, numbering 331 in leaves and 1320 in roots, could be classified in five and four clusters, respectively. Expression patterns of several genes from each cluster were confirmed by RT-qPCR. We furthermore performed a network analysis to identify potential regulatory paths from known Ca2+-related genes to the newly identified Ca2+-dependent H2O2 responsive genes, using the recently described Stress Knowledge Map. This analysis indicated several transcription factors as key points of the responses mediated by the cross-talk between H2O2 and Ca2+.

CONCLUSION: Our study indicates that about 70% of the H2O2-responsive genes in barley roots require a transient increase in cytosolic Ca2+ concentrations for alteration in their transcript abundance, whereas in leaves, the Ca2+ dependency was much lower at about 33%. Targeted gene analysis and pathway modeling identified not only known components of the Ca2+ signaling cascade in plants but also genes that are not yet connected to stimuli-associated signaling. Potential key transcription factors identified in this study can be further analyzed in barley and other crops to ultimately disentangle the underlying mechanisms of H2O2-associated signal transduction mechanisms. This could aid breeding for improved stress resistance to optimize performance and productivity under increasing climate challenges.

PMID:39979811 | DOI:10.1186/s12870-025-06248-9

Mol Syst Biol. 2025 Feb 20. doi: 10.1038/s44320-025-00086-5. Online ahead of print.

ABSTRACT

Understanding the biochemistry behind whole-organism traits such as flowering time is a longstanding challenge, where mathematical models are critical. Very few models of plant gene circuits use the absolute units required for comparison to biochemical data. We refactor two detailed models of the plant circadian clock from relative to absolute units. Using absolute RNA quantification, a simple model predicted abundant clock protein levels in Arabidopsis thaliana, up to 100,000 proteins per cell. NanoLUC reporter protein fusions validated the predicted levels of clock proteins in vivo. Recalibrating the detailed models to these protein levels estimated their DNA-binding dissociation constants (Kd). We estimate the same Kd from multiple results in vitro, extending the method to any promoter sequence. The detailed models simulated the Kd range estimated from LUX DNA-binding in vitro but departed from the data for CCA1 binding, pointing to further circadian mechanisms. Our analytical and experimental methods should transfer to understand other plant gene regulatory networks, potentially including the natural sequence variation that contributes to evolutionary adaptation.

PMID:39979593 | DOI:10.1038/s44320-025-00086-5

NPJ Sci Food. 2025 Feb 20;9(1):24. doi: 10.1038/s41538-025-00385-z.

ABSTRACT

Amylase/trypsin-inhibitors (ATIs) are triggers for wheat-related disorders like baker's asthma and non-celiac wheat sensitivity. With the rise of wheat-related disorders among the population, the hypothesis that breeding may have resulted in changes in the protein composition of wheat was put forward. The ATI content of 14 German common wheat landraces and six modern varieties harvested in three consecutive years was analyzed by liquid chromatography-tandem mass spectrometry, and the inhibitory activity against α-amylase was measured with an enzymatic assay. The mean ATI content and proportion of crude protein of both groups did not differ. There were also only small differences in the content and proportion of single ATIs. The mean values for the inhibitory activity of both groups were also similar. These results indicate that breeding might not have led to changes in the protein composition and landraces are unlikely to be better tolerated than modern varieties.

PMID:39979280 | DOI:10.1038/s41538-025-00385-z

Adv Protein Chem Struct Biol. 2025;144:33-76. doi: 10.1016/bs.apcsb.2024.10.011. Epub 2025 Jan 31.

ABSTRACT

Immunotherapy, harnessing components like antibodies, cells, and cytokines, has become a cornerstone in treating diseases such as cancer and autoimmune disorders. Therapeutic antibodies, in particular, have transformed modern medicine, providing a targeted approach that destroys disease-causing cells while sparing healthy tissues, thereby reducing the side effects commonly associated with chemotherapy. Beyond oncology, these antibodies also hold promise in addressing chronic infections where conventional therapeutics may fall short. However, antibodies identified through in vivo or in vitro methods often require extensive engineering to enhance their therapeutic potential. This optimization process, aimed at improving affinity, specificity, and reducing immunogenicity, is both challenging and costly, often involving trade-offs between critical properties. Traditional methods of antibody development, such as hybridoma technology and display techniques, are resource-intensive and time-consuming. In contrast, computational approaches offer a faster, more efficient alternative, enabling the precise design and analysis of therapeutic antibodies. These methods include sequence and structural bioinformatics approaches, next-generation sequencing-based data mining, machine learning algorithms, systems biology, immuno-informatics, and integrative approaches. These approaches are advancing the field by providing new insights and enhancing the accuracy of antibody design and analysis. In conclusion, computational approaches are essential in the development of therapeutic antibodies, significantly improving the precision and speed of discovery, optimization, and validation. Integrating these methods with experimental approaches accelerates therapeutic antibody development, paving the way for innovative strategies and treatments for various diseases ranging from cancers to autoimmune and infectious diseases.

PMID:39978970 | DOI:10.1016/bs.apcsb.2024.10.011