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At least 19 recordsLinked to original sources
PubMed2025

Genomically integrated cassettes swapping: bringing modularity to the strain level in Saccharomyces cerevisiae.

A large variety of synthetic biology toolkits for the introduction of multiple expression cassettes is available for Saccharomyces cerevisiae. Unfortunately, none of these tools is designed to allow the modification - exchange or removal - of the cassettes already integrated into the genome in a standardized way. The application of the modularity principle therefore ends to the steps preceding the final host engineering, making microbial cell factories construction stiff and strictly sequential. In this work, we describe a system that easily allows CRISPR-mediated swapping or removal of previously integrated cassettes, thus bringing the modularity to the strain level, enhancing the possibility of modifying existing strains with a reduced number of steps. In the system, each cassette is tagged with specific barcodes, which can be used as targets for CRISPR nucleases (Cas9 and Cas12a), allowing the excision of the construct from the genome and its substitution with another expression cassette or the restoration of the wild type locus in one single standardized step. The system has been applied to the previously developed Easy-MISE toolkit and tested by swapping fluorescent protein expression cassettes with an efficiency of ∼90% quantified by PCR and flow cytometry.

Saccharomyces cerevisiae↗
PubMed2025

Modularization of the type II secretion gene cluster from Xanthomonas euvesicatoria facilitates the identification of a structurally conserved XpsCLM assembly platform complex.

Many bacterial pathogens depend on a type II secretion (T2S) system to secrete virulence factors from the periplasm into the extracellular milieu. T2S systems consist of an outer membrane secretin channel, a periplasmic pseudopilus and an inner membrane-associated assembly platform including a cytoplasmic ATPase. The components of T2S systems are often conserved in different bacterial species, however, the architecture of the assembly platform is largely unknown. Here, we analysed predicted assembly platform components of the Xps-T2S system from the plant-pathogenic bacterium Xanthomonas euvesicatoria. To facilitate these studies, we generated a modular xps-T2S gene cluster by Golden Gate assembly of single promoter and gene fragments. The modular design allowed the efficient deletion and replacement of T2S genes and the insertion of reporter fusions. Mutant approaches as well as interaction and crosslinking studies showed that the predicted assembly platform components XpsC, XpsL and XpsM form a trimeric complex which is essential for T2S and associates with the cytoplasmic ATPase XpsE and the secretin XpsD. Structural modeling revealed a similar trimeric architecture of XpsCLM homologs from Pseudomonas, Vibrio and Klebsiella species, despite overall low amino acid sequence similarities. In X. euvesicatoria, crosslinking and fluorescence microscopy studies showed that the formation of the XpsCLM complex is independent of the secretin and vice versa, suggesting that the assembly of the T2S system is a dynamic process which involves the association of preformed subcomplexes.

Xanthomonas↗
PubMed2026

Systematic modular engineering of genome-integrated Escherichia coli MG1655 for high-level 2'-fucosyllactose production.

2'-Fucosyllactose (2'-FL), the most abundant human milk oligosaccharide (HMO), has attracted considerable interest for its prebiotic and immunomodulatory functions, with broad applications in infant nutrition. In this study, we report the development of a high-yield, genome-integrated 2'-FL-producing strain based on Escherichia coli MG1655 through systematic modular optimization. Starting from a single-copy BKHT strain (MGC06), we first optimized the copy number of the α-1,2-fucosyltransferase (α-1,2-FT) gene BKHT. Subsequently, the GDP-L-fucose supply was enhanced through coordinated genomic integration of the gene clusters cpsG-cpsB and gmd-fcl, while the multidrug efflux transporter gene mdfA was integrated to improve product export and strain robustness. BKHT copy number was then re-evaluated in the optimized background, with four copies yielding the highest production. The final engineered strain, harboring all genetic modifications stably integrated into the chromosome, produced 17.18 g/L 2'-FL in shake-flask culture. In fed-batch fermentation using a 5-L bioreactor, this strain achieved a titer of 154.12 g/L after 60 h, with a productivity of 2.57 g/L/h. Notably, throughout the entire fermentation process, no antibiotics or inducers were supplemented, underscoring the genetic stability and regulatory compliance of this plasmid-free system. To our knowledge, this represents the highest 2'-FL titer reported to date, positioning our engineered strain as a promising candidate for commercial 2'-FL production.

Escherichia coli↗
PubMed2025

Modular Photoswitchable Molecular Glues for Chemo-Optogenetic Control of Protein Function in Living Cells.

Optogenetic systems using photosensitive proteins and chemically induced dimerization/proximity (CID/CIP) approaches enabled by chemical dimerizers (also termed molecular glues), are powerful tools to elucidate the dynamics of biological systems and to dissect complex biological regulatory networks. Here, we report a versatile chemo-optogenetic system using modular, photoswitchable molecular glues (sMGs) that can undergo repeated cycles of optical control to switch protein function on and off. We use molecular dynamics (MD) simulations to rationally design the sMGs and further expand their scope by incorporating different photoswitches, resulting in sMGs with customizable properties. We demonstrate that this system can be used to reversibly control protein localization, organelle positioning, protein-fragment complementation as well as posttranslational protein levels by light with high spatiotemporal precision. This system enables sophisticated optical manipulation of cellular processes and thus opens up a new avenue for chemo-optogenetics.

Optogenetics↗
PubMed2025

A Versatile Disulfide-Containing Solid-Support Strategy for 3'-Modifiers in Oligonucleotides: Introducing Modular Tandem Oligonucleotide Synthesis.

Chemical modifications of oligonucleotides are routinely employed to enhance their functional properties. Amino-modifiers serve as versatile chemical handles for postsynthetic (bio)conjugation, nucleic acid immobilization on solid supports, and investigations into nonenzymatic genome replication relevant to the origins of life, to name a few. Here, we report a cost-effective, disulfide-containing solid-support linkage that enables the on-column synthesis of nucleic acids with 3'-amino or 3'-phosphate modifications. The orthogonality of this solid-support linker facilitates an on-column protecting group strategy, enabling the synthesis of DNA and RNA containing 3'-amino-2',3'-dideoxyribosides from commercial unprotected mononucleosides. Additionally, we present an on-column deprotection protocol for DNA and RNA, prior to cleavage from the solid support, eliminating the precipitation step typically required in conventional RNA workflows, leading to higher recovery for certain strands. Expanding on our previous work, we introduce a versatile modular tandem oligonucleotide synthesis (mTOS) approach, allowing selective release of downstream strands from the one directly bound to the solid-support via the disulfide-containing linker. Together, these advances in solid-support design and oligonucleotide synthesis unlock new opportunities in bioconjugation, biotechnology, and the study of prebiotic replication mechanisms, broadening the utility of chemically modified nucleic acids across research disciplines.

Disulfides↗
PubMed2026

KG-Microbe: Building modular and scalable knowledge graphs for microbiome and microbial sciences.

BACKGROUND: The integration of many disparate forms of data is essential for understanding the microbial world and its interaction with the environment and human health. Doing so is particularly challenging in the context of microbe-host and microbe-microbe interactions that contribute to health or environmental outcomes. There are thousands of relevant microbial species, and millions of interactions among those microbes and with their environment or host. Integrated information (e.g., about host and microbial physiology, genetics, and metabolism) facilitates deeper understanding of complex mechanisms and helps interpret correlative results. RESULTS: The KG-Microbe construction framework is a novel approach to harmonizing bacterial and archaeal data in the form of a findable, accessible, interoperable, reusable and AI-ready knowledge graph (KG). Starting from a core KG with organismal traits, environments, and growth preferences and the integration of established ontologies, the framework generates a hierarchy of related KGs targeting specific use cases, including the human microbiome in the context of disease, or environmental microbiomes. The framework supports customizable taxa subsets representing communities or clades of interest. Evaluations of the KG-Microbe KGs through a series of competency questions demonstrate the accuracy and effectiveness of the data harmonization, and the utility of the resulting KGs in studies of inflammatory bowel disease and Parkinson's disease. Finally, the predictive and environmental capabilities of the KGs are demonstrated by predicting growth preferences using graph features. CONCLUSIONS: The KG-Microbe framework unifies microbial contexts in a single resource to support integrative analyses across biomedical, host, and environmental domains. KG-Microbe is a flexible, modular enabling technology for humans and machine learning methods to uncover candidate mechanistic explanations of microbial associations.

Microbiota↗
PubMed2026

Modular synthetic cross-kingdom promoters enable coordinated expression in Escherichia coli and Saccharomyces cerevisiae.

Synthetic biology and metabolic engineering increasingly demand predictable and interoperable gene expression across phylogenetically distant organisms, as the need for portable genetic systems and transferable metabolic pathways continues to grow. However, fundamental differences in promoter architecture and transcriptional logic across kingdoms remain a key bottleneck in developing universal expression platforms. Here, we designed a set of modular hybrid promoters that enable tunable and quantitatively consistent gene expression in both Escherichia coli and Saccharomyces cerevisiae. These promoters integrate bacterial -10/-35 motifs and Shine-Dalgarno sequences with minimal yeast TATA boxes and Kozak sequences to ensure transcriptional and translational compatibility. The promoter set supported weak, moderate, and strong expression with high relative consistency across species. Applied to the biosynthetic pathway for the valuable pigment prodeoxyviolacein, the hybrid promoters enabled coordinated production in both hosts. This work establishes a broadly compatible promoter architecture and provides a foundational toolkit for cross-kingdom, multi-host synthetic biology.

Promoter Regions, Genetic↗
PubMed2025

A Modular Platform for the Optogenetic Control of Small GTPase Activity in Living Cells Reveals Long-Range RhoA Signaling.

Small GTPases are critical regulators of cellular processes, such as cell migration, and comprise a family of over 167 proteins in the human genome. Importantly, the location-dependent regulation of small GTPase activity is integral to coordinating cellular signaling. Currently, there are no generalizable methods for directly controlling the activity of these signaling enzymes with subcellular precision. To address this issue, we introduce a modular, optogenetic platform for the spatial control of small GTPase activity within living cells, termed spLIT-small GTPases. This platform enabled spatially precise control of cytoskeletal dynamics such as filopodia formation (spLIT-Cdc42) and directed cell migration (spLIT-Rac1). Furthermore, a spLIT-RhoA system uncovered previously unreported long-range RhoA signaling in HeLa cells, resulting in bipolar membrane retraction. These results establish spLIT-small GTPases as a versatile platform for the direct, spatial control of small GTPase signaling and demonstrate the ability to uncover spatially defined aspects of small GTPase signaling.

Journal Article↗
PubMed2026

A modular class-aware workflow for small RNA sequencing analysis using mouse sperm as a case study.

BACKGROUND: Small RNA sequencing analysis is challenging because RNA classes differ in biogenesis, sequence redundancy, genomic organization, and annotation reliability. Integrated workflows accommodating these constraints remain limited, particularly for fragment-level and cluster-level analysis. METHODS: We present a reproducible, containerized, class-aware workflow for small RNA sequencing analysis, using mouse sperm as a case study. The workflow combines standardized preprocessing with complementary annotation and quantification strategies for microRNAs (miRNAs), transfer RNA-derived small RNAs (tsRNAs), ribosomal RNA-derived small RNAs (rsRNAs), and PIWI-interacting RNA (piRNA)-enriched genomic clusters. Using sperm small RNA data from offspring of lipopolysaccharide (LPS)-exposed male mice, we compared integrated-reference mapping, multi-class annotation, fragment-level tsRNA profiling, and genome-based piRNA cluster analysis, with custom modules for locus-aware harmonization and condition-specific cluster analysis. RESULTS: Integrated-reference mapping aligned 88.17% of reads and retained 690 features after filtering. It identified 11 differentially expressed miRNAs between LPS and controls, while other classes showed limited signal. Fragment-level profiling improved tsRNA resolution. piRNA cluster analysis identified 958 control and 940 LPS clusters, with 18 control-specific and no LPS-specific clusters. CONCLUSION: This workflow supports transparent, reproducible, class-aware interpretation of small RNA sequencing data while emphasizing cautious interpretation of piRNA-enriched signals from total small RNA sequencing.

Small non-coding RNA analysis↗
PubMed2025

OpenSpliceAI: An efficient, modular implementation of SpliceAI enabling easy retraining on non-human species.

The SpliceAI deep learning system is currently one of the most accurate methods for identifying splicing signals directly from DNA sequences. However, its utility is limited by its reliance on older software frameworks and human-centric training data. Here we introduce OpenSpliceAI, a trainable, open-source version of SpliceAI implemented in PyTorch to address these challenges. OpenSpliceAI supports both training from scratch and transfer learning, enabling seamless retraining on species-specific datasets and mitigating human-centric biases. Our experiments show that it achieves faster processing speeds and lower memory usage than the original SpliceAI code, allowing large-scale analyses of extensive genomic regions on a single GPU. Additionally, OpenSpliceAI's flexible architecture makes for easier integration with established machine learning ecosystems, simplifying the development of custom splicing models for different species and applications. We demonstrate that OpenSpliceAI's output is highly concordant with SpliceAI. In silico mutagenesis (ISM) analyses confirm that both models rely on similar sequence features, and calibration experiments demonstrate similar score probability estimates.

Journal Article↗
PubMed2026

A modular γδ TCR-T platform combining KRAS pMHC targeting with re-dosable mRNA engager redirection.

Solid tumors often evade TCR-engineered αβ T cells when antigen expression varies or when the restricting Human Leukocyte Antigen (HLA) allele is lost. γδ T cells, in contrast, detect cellular dysregulation through non-peptide/Major Histocompatibility Complex (MHC) cues, including phosphoantigens and stress ligands, and can be developed as allogeneic therapies. Although intratumoral γδ T cell signatures are associated with improved outcome across cancers, γδ recognition itself is broad and still selected within the thymus just as αβ T cell receptors (TCRs) are. It does not, however, anchor specificity to a defined driver-mutation pMHC epitope. We therefore asked whether a high-affinity, co-receptor-independent αβ TCR could graft oncogenic-driver specificity onto γδ T cells while leaving the endogenous γδ TCR intact. We knocked the KRASG12V/HLA-A*11:01 TCR A11v into primary human γδ T cells. Engineered cells co-expressed the transgenic αβ TCR and the endogenous γδ TCR and lysed KRASG12V/HLA-A*11:01+ tumor cells in vitro and in vivo. To cover potential resistance through loss of HLA-A*11:01, we delivered an mRNA lipid nanoparticle (LNP) encoding a secreted mesothelin×CD3 (M5) bispecific T cell engager (TCE). LNP-M5 produced circulating TCE that redirected γδ A11v T cells and polyclonal bystander T cells to kill mesothelin+ targets, accompanied by development of higher γδ A11v T cell counts in vivo. In humanized mice bearing mixed HLA-A*11:01+ and HLA-A*11:01 - KRASG12V tumors, γδ A11v T cells produced transient control, whereas adding LNP-M5 yielded complete responses and prolonged survival. Thus, this two-part therapy couples invariant driver targeting to tunable redirection and addresses loss of the restricting HLA allele, a central escape route for TCR-based therapy. It provides an off-the-shelf reagent to enable KRAS-anchored treatment with the ability to redeliver the reagent.

Humans↗
PubMed1976

The appraisal of mediated materials for use in a modular curriculum.

The faculty of the Nurse-Midwifery Education Program at the Medical University of South Carolina utilized a specially designed appraisal process to select mediated materials for use in the modules of their student-centered, self-paced curriculum. This appraisal process was successful and may serve as a model for other programs.

Audiovisual Aids↗
PubMed2026

Synthetic transcriptional repression systems in plants.

Transcriptional repression is a fundamental regulatory mechanism that enables precise control of gene expression in response to developmental signals and environmental stimuli. Synthetic biology can leverage this process within plants to engineer programmable transgene repression systems. This review examines strategies for harnessing prokaryotic repressors in eukaryotic systems to develop synthetic repression systems in plants. These systems utilize modular promoter and repressor architectures that can be tuned through operator placement and repression-domain fusion, respectively, to adjust transcriptional regulation. Chemically dependent inducibility can also be introduced either through use of native derepression mechanisms of the prokaryotic repressors or the incorporation of ligand-binding domains. Finally, this review explores key challenges in designing synthetic repression systems, including kinetics constraints, balancing ON and OFF states, and differences between transient and transgenic expression contexts. Overall, this review highlights modular design frameworks for tunable transgene expression in plants.

Gene Expression Regulation, Plant↗
PubMed2025

Guidelines for T cell nomenclature.

Advances in T cell biology have revealed heterogeneity among T cell populations that is not captured by existing general nomenclature. This issue has caused an ad hoc broadening of core T cell subset definitions and the invention of new subset designations that have not been uniformly delineated. To address this issue, in this Consensus Statement, we propose guidelines that serve three goals. First, they advocate that primary research reports define the experimental basis by which relevant subsets are designated in the methods section of each study. Second, they provide standardized definitions for existing subset designations in popular use, and common experimental criteria for defining each subset are noted. Last, they present an alternative 'modular nomenclature' paradigm. The newly proposed modular nomenclature eschews conceptualization of antigen-experienced T cells as belonging to a few idealized subsets, and the nomenclature instead simply indicates individual biological properties present in a T cell population with brief descriptors. Collectively, these guidelines intend to enhance transparency in the literature while facilitating clearer communication of findings and concepts to researchers, students and clinicians.

Terminology as Topic↗
PubMed2025

Prediction of local convergent shifts in evolutionary rates with phyloConverge.

MOTIVATION: Convergence analysis can characterize genetic elements underlying morphological adaptations. However, its performance on regulatory elements is limited due to their modular composition of transcription factor motifs, which have rapid turnover and experience different evolutionary pressures. RESULTS: We introduce phyloConverge, a phylogenetic method that performs scalable, fine-grained local convergence analysis of genomic elements at flexible length scales. Using a benchmarking case of convergent subterranean mammal adaptation, phyloConverge identifies rate-accelerated conserved noncoding elements (CNEs) with high specificity and statistical robustness relative to competing methods. From CNE-level scoring, we detect the convergent regression of entire CNE units and highlight the contrast that subterranean-associated coding region regression is highly specific to ocular functions, whereas regulatory element regression is enriched for accompanying neuronal phenotypes and other developmental processes. From transcription factor motif-level scoring, we dissect elements into subregions with uneven convergence signals and demonstrate the modular adaptation of CNEs with high functional specificity. Finally, we demonstrate phyloConverge's scalability to perform high-resolution convergence analysis genome-wide. AVAILABILITY AND IMPLEMENTATION: phyloConverge is available at https://github.com/ECSaputra/phyloConverge.

Evolution, Molecular↗
PubMed2025

Pedigree Painter (pepa): a tool for the visualization of genetic inheritance in chromosomal context.

MOTIVATION: Data visualization is increasingly important in genomics, enabling researchers to uncover inheritance and recombination patterns across generations. While most existing tools focus on ancestry prediction, they lack functionality for analyzing known ancestries in controlled settings, such as determining parental contributions to offspring genomes. To address this gap, I developed pepa, a lightweight, deterministic, modular tool that visualizes and quantifies genomic inheritance, designed for beginner and advanced users. RESULTS: pepa is a program for processing VCF files, assigning ancestries to homozygous SNPs, and clustering them into biologically meaningful regions. It generates human-readable comparison tables and visualizes inheritance patterns with chromosome paintings through R. Tested on fission yeast, pepa revealed non-uniform recombination patterns, with chromosomes largely inherited from one parent and seemingly random recombination. Quantitative analyses showed differences in parental contributions at the nucleotide and gene levels, with some offspring inheriting similar percentages from parents. However, the painted chromosomes revealed that even offspring with similar percentages from one parent rarely inherit the same genomic region, highlighting the importance of this tool in drawing biologically meaningful insights. pepa provides an accessible and powerful solution for analyzing genomic inheritance, bridging experimental and computational biology. Its modular design and minimal dependencies allow adaptation to diverse organisms, facilitating intuitive visualization and quantitative insights into recombination dynamics.

Pedigree↗
PubMed2026

Hotgenes: an R package for reducing bottlenecks in bulk omics data exploration and collaboration.

SUMMARY: A critical part of omics analysis is the transition from early data exploration to final interpretation, often including different analytical platforms and the proliferation of figures, tables, and files. To minimize potential errors and delays that can occur during this process, we have developed an R package called "Hotgenes" that contains a wide range of flexible utilities available in a single modular Shiny application. With Hotgenes, differential expression results generated from bulk omics platforms can be imported and shared among collaborators with minimal coding. Furthermore, the modular Hotgenes user interface can be customized by advanced users to fit the needs of their evolving pipelines. AVAILABILITY AND IMPLEMENTATION: Hotgenes is implemented in R and is freely available at https://github.com/pfizer-opensource/Open-Hotgenes. A permanent archived version is available at https://doi.org/10.5281/zenodo.20129460.

Software↗