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At least 19 recordsLinked to original sources
PubMed2025

FluxRETAP: a REaction TArget Prioritization genome-scale modeling technique for selecting genetic targets.

MOTIVATION: Metabolic engineering is rapidly evolving as a result of new advances in synthetic biology tools and automation platforms that enable high throughput strain construction, as well as the development of machine learning tools (ML) for biology. However, selecting genetic engineering targets that effectively guide the metabolic engineering process is still challenging. ML can provide predictive power for synthetic biology, but current technical limitations prevent the independent use of ML approaches without previous biological knowledge. RESULTS: Here, we present FluxRETAP, a simple and computationally inexpensive method that leverages the prior mechanistic knowledge embedded in genome-scale models for suggesting targets for genetic overexpression, downregulation or deletion, with the final goal of increasing the production of a desired metabolite. This method can provide a list of desirable engineering targets that can be combined with current ML pipelines. FluxRETAP captured 100% of reaction targets experimentally verified to improve Escherichia coli isoprenol production, 50% of targets that experimentally improved taxadiene production in E. coli and ∼60% of genetic targets from a verified minimal constrained cut-set in Pseudomonas putida, while providing additional high priority targets that could be tested. Overall, FluxRETAP is an efficient algorithm for identifying a prioritized list of testable genetic and reaction targets. AVAILABILITY AND IMPLEMENTATION: FluxRETAP is implemented in python and released under the creative commons license. The implementation and code are freely available at: https://github.com/JBEI/FluxRETAP.

Escherichia coli↗
PubMed2022

Inhibition of RAS-driven signaling and tumorigenesis with a pan-RAS monobody targeting the Switch I/II pocket.

RAS mutants are major therapeutic targets in oncology with few efficacious direct inhibitors available. The identification of a shallow pocket near the Switch II region on RAS has led to the development of small-molecule drugs that target this site and inhibit KRAS(G12C) and KRAS(G12D). To discover other regions on RAS that may be targeted for inhibition, we have employed small synthetic binding proteins termed monobodies that have a strong propensity to bind to functional sites on a target protein. Here, we report a pan-RAS monobody, termed JAM20, that bound to all RAS isoforms with nanomolar affinity and demonstrated limited nucleotide-state specificity. Upon intracellular expression, JAM20 potently inhibited signaling mediated by all RAS isoforms and reduced oncogenic RAS-mediated tumorigenesis in vivo. NMR and mutation analysis determined that JAM20 bound to a pocket between Switch I and II, which is similarly targeted by low-affinity, small-molecule inhibitors, such as BI-2852, whose in vivo efficacy has not been demonstrated. Furthermore, JAM20 directly competed with both the RAF(RBD) and BI-2852. These results provide direct validation of targeting the Switch I/II pocket for inhibiting RAS-driven tumorigenesis. More generally, these results demonstrate the utility of tool biologics as probes for discovering and validating druggable sites on challenging targets.

Biological Products↗
PubMed2026

Engineering Bacillus Subtilis for Efficient Biosynthesis of Riboflavin: Current Knowledge and Future Perspectives.

Riboflavin is an essential water-soluble vitamin that serves as a precursor for the biosynthesis of the flavin cofactors FMN and FAD, which play pivotal roles in numerous redox and energy metabolism reactions. With the growing global demand for sustainable vitamin production, microbial fermentation has become an attractive alternative to chemical synthesis due to its environmental and economic advantages. Among microbial hosts, Bacillus subtilis has emerged as a leading cell factory for riboflavin production owing to its GRAS status, well-characterized genetics, and efficient protein secretion system. This review provides a comprehensive overview of recent advances in metabolic engineering strategies to enhance riboflavin biosynthesis in B. subtilis. Key topics include strengthening biosynthetic and precursor pathways, relieving feedback inhibition, balancing metabolic flux and cell growth, employing adaptive laboratory evolution, and utilizing omics-guided optimization and 13C metabolic flux analysis. Moreover, the integration of synthetic biology tools such as riboswitch engineering, regulatory element design, and high-throughput screening has significantly accelerated strain improvement. Despite remarkable progress, challenges remain in achieving precise regulatory control, optimizing multi-gene expression, and enhancing genome integration efficiency. Future research combining multi-omics data, synthetic regulatory design, and machine learning-driven predictive modeling is expected to further advance the development of intelligent B. subtilis cell factories. However, the practical implementation of these systems remains constrained by the metabolic burden of overproduction and the lack of universal regulatory models that can predict strain performance across varying industrial scales.

Bacillus subtilis↗
PubMed2026

An inducer-independent, single-plasmid CRISPR-Cas9 system for genome editing in Bacillus species.

Advances in molecular biology tools are essential for streamlining and accelerating genetic engineering of cells across industrial and academic applications. While CRISPR-Cas improves genome editing efficiency, current systems have limitations and are often host specific, which restricts their versatility. This study describes a versatile CRISPR-Cas9 system for genome editing in industrially relevant Bacillus species. By adapting the well-established pJOE8999 vector-based CRISPR-Cas9 genome editing system, we constructed an inducer-independent, broad-host-range genome editing system. It maintains the benefits of low toxicity to the target cell and the cloning host as well as the ease to use of a single-plasmid CRISPR-Cas9 system. We utilized the constitutive Sigma70-type promoter from the conserved veg gene of Bacillus, to develop and test the suitability of promoter variants of different strengths for Cas9 expression. Successful gene deletions in three different Bacillus species demonstrated the versatility of the modified system for this industrially important genus. This was further confirmed by the integration of a reporter gene fusion and the introduction of a single point mutation in the genome of Bacillus licheniformis. This one-step CRISPR-based transformation protocol developed in this study enables fast genome editing workflows with minimal hands-on time. KEY POINTS: • Editing and screening of promoter variants for balanced Cas9 expression in Bacillus. • Development of a versatile inducer-independent, single-plasmid CRISPR-Cas-based system. • Verification of the modified CRISPR-based system for genome editing in different Bacilli.

CRISPR-Cas Systems↗
PubMed2026

Uchimata: a toolkit for visualization of 3D genome structures on the web and in computational notebooks.

SUMMARY: Uchimata is a toolkit for visualization of 3D structures of genomes. It consists of two packages: a Javascript library facilitating the rendering of 3D models of genomes, and a Python widget for visualization in Jupyter Notebooks. Main features include an expressive way to specify visual encodings, and filtering of 3D genome structures based on genomic semantics and spatial aspects. Uchimata is designed to be highly integratable with biological tooling available in Python. AVAILABILITY AND IMPLEMENTATION: Uchimata is released under the MIT License. The Javascript library is available on NPM, while the widget is available as a Python package hosted on PyPI. The source code for both is available publicly on Github (https://github.com/hms-dbmi/uchimata and https://github.com/hms-dbmi/uchimata-py) and Zenodo (https://doi.org/10.5281/zenodo.17831959 and https://doi.org/10.5281/zenodo.17832045). The documentation with examples is hosted at https://hms-dbmi.github.io/uchimata/.

Software↗
PubMed1976

Immunology of the acetylcholine receptor.

Myasthenia gravis is a spontaneously occurring autoimmune disease in which antibodies and lymphocytes are specifically reactive with nicotinic ACh receptors of skeletal muscle. Antibodies reactive with junctional receptors of human muscle are found in 90% of patients with myasthenia gravis and not at all in other diseases. Their capacity to cross the placenta suggests their involvement in the pathogenesis of neonatal myasthenia. The role of the thymus in myasthenia gravis remains a mystery, but it has a recently been established that the thymus contains nicotinic ACh receptors and that anti-receptor antibodies are present in myasthenic thymuses. Antibodies of myasthenic patients detect only partial cross reactivity between ACh receptors of different species. However, greater antibody binding is observed with receptors isolated from denervated rat muscle than with receptors from normal rat muscle. This suggests that extrajunctional and junctional ACh receptors might express different antigenic determinants. Although human antibodies bind minimally to ACh receptors of the electric organs of eels and marine rays, lymphocyte reactivity to electric eel receptors is found in high incidence in myasthenic patients. This suggests that electric organ and mammalian muscle ACh receptors may share more lymphocyte-defined than serologically-defined antigenic determinants. Both cellular and humoral immune responses to ACh receptors can be induced experimentally. Sufficient antigenic homology exists between receptors of different species that electric organ receptors are capable of inducing in mammals experimental autoimmune myasthenia gravis. Syngeneic muscle receptor also is immunogenic in rats. Induction of both myasthenia and antibodies to ACh receptor requires participation of thymus-derived lymphocytes. The majority of ACh receptors in myasthenic rat muscle exist complexed with antibody, but antibody is not bound directly to the receptor's ACh-binding site. Anti-receptor antibodies in vitro are capable of impairing the electrophysiological function of ACh receptors with minimal blocking of the ACh-binding site and in the absence of complement. Thus, myasthenia gravis and its experimental model provide unique biological tools for studying the structure, function and pathology of cell membrane receptors.

Acetylcholine↗
PubMed2025

Uchimata: a toolkit for visualization of 3D genome structures on the web and in computational notebooks.

SUMMARY: Uchimata is a toolkit for visualization of 3D structures of genomes. It consists of two packages: a Javascript library facilitating the rendering of 3D models of genomes, and a Python widget for visualization in Jupyter Notebooks. Main features include an expressive way to specify visual encodings, and filtering of 3D genome structures based on genomic semantics and spatial aspects. Uchimata is designed to be highly integratable with biological tooling available in Python. AVAILABILITY AND IMPLEMENTATION: Uchimata is released under the MIT License. The Javascript library is available on NPM, while the widget is available as a Python package hosted on PyPI. The source code for both is available publicly on Github (https://github.com/hms-dbmi/uchimata and https://github.com/hms-dbmi/uchimata-py). The documentation with examples is hosted at https://hms-dbmi.github.io/uchimata/. CONTACT: david_kouril@hms.harvard.edu or nils@hms.harvard.edu.

Journal Article↗
PubMed2025

High-Affinity, Structure-Validated and Selective Macrocyclic Peptide Tools for Chemical Biology Studies of Huntingtin.

Huntington's disease (HD) is a fatal neurodegenerative disorder caused by a CAG repeat expansion in the Huntingtin (HTT) gene, with no disease-modifying therapies currently available. The precise molecular function of the HTT protein is unclear, and the lack of selective chemical tools has limited functional studies. We have identified and characterized macrocyclic peptide binders targeting HTT. These binders exhibit low-nanomolar affinity in vitro and engage distinct HTT and HTT-HAP40 interfaces, as revealed by hydrogen-deuterium exchange mass spectrometry and cryo-electron microscopy. Chemoproteomics confirmed selective binding in cell extracts from wildtype but not HTT-null cell lines. HAP40 consistently and stoichiometrically co-purified with HTT across cell lines, including with HTT variants containing different CAG repeat lengths, highlighting the broad presence of the HTT-HAP40 complex.

HAP40↗
PubMed2026

High-affinity, structure-validated and selective macrocyclic peptide tools for chemical biology studies of Huntingtin.

Huntington's disease (HD) is a fatal neurodegenerative disorder caused by a Cytosine-Adenosine-Guanine (CAG) repeat expansion in the Huntingtin (HTT) gene, with no disease-modifying therapies currently available. The precise molecular function of the HTT protein is unclear, and the lack of selective chemical tools has limited functional studies. We have identified and characterized macrocyclic peptide binders targeting HTT. These binders exhibit low-nanomolar affinity in vitro and engage distinct HTT and HTT-HAP40 interfaces, as revealed by hydrogen-deuterium exchange mass spectrometry and cryoelectron microscopy. Chemoproteomics confirmed selective binding in cell extracts from wildtype but not HTT-null cell lines. HAP40 consistently and stoichiometrically copurified with HTT across cell lines, including with HTT variants containing different CAG repeat lengths, highlighting the broad presence of the HTT-HAP40 complex.

Huntingtin Protein↗
PubMedDate not supplied

[Nucleotide and oligonucleotide derivatives--a research tool of molecular biology].

The work of the authors are discussed, that they have been engaged in since the late forties, on synthesis and investigation of mono- and oligonucleotide derivatives. One class of mixed biopolymers (mono (oligo) nucleotides) is used to demonstrate the effect of covalent and noncovalent intramolecular interactions on the character of various protein-nucleic acid contacts. General approaches to creating regioselective reagents are outlined, that can be widely used for modification of both proteins and nucleic acids. Designing and application of some of such reagents is analyzed.

Amino Acids↗
PubMed2025

Beyond Blacklists: A Critical Assessment of Exclusion Set Generation Strategies and Alternative Approaches.

Short-read sequencing data can be affected by alignment artifacts in certain genomic regions. Removing reads overlapping these exclusion regions, previously known as Blacklists, help to potentially improve biological signal. Tools like the widely used Blacklist software facilitate this process, but their algorithmic details and parameter choices are not always clearly documented, affecting reproducibility and biological relevance. We examined the Blacklist software and found that pre-generated exclusion sets were difficult to reproduce due to variability in input data, aligner choice, and read length. We also identified and addressed a coding issue that led to over-annotation of high-signal regions. We further explored the use of "sponge" sequences-unassembled genomic regions such as satellite DNA, ribosomal DNA, and mitochondrial DNA-as an alternative approach. Aligning reads to a genome that includes sponge sequences reduced signal correlation in ChIP-seq data comparably to Blacklist-derived exclusion sets while preserving biological signal. Sponge-based alignment also had minimal impact on RNA-seq gene counts, suggesting broader applicability beyond chromatin profiling. These results highlight the limitations of fixed exclusion sets and suggest that sponge sequences offer a flexible, alignment-guided strategy for reducing artifacts and improving functional genomics analyses.

Journal Article↗
PubMed2026

Phasis: a software tool for register-resolved discovery of plant phased small RNA loci.

Plant PHAS locus discovery remains challenging because phasiRNA-producing loci must be distinguished from other sRNA-producing regions with high abundance or apparent periodicity. This problem is especially acute for reproductive 24-PHAS loci, which occur within genomes that also produce abundant 24-nt siRNAs from nonPHAS regions. We present Phasis, an open-source Python software tool for plant PHAS-locus discovery from small RNA sequencing data. Phasis combines statistical evidence for phased accumulation with locus-level features and a Register-Resolved Locus Interpretation Layer that evaluates whether candidate loci show coherent phased architecture. Across diverse plant datasets, Phasis recovered validated or annotated 21- and 24-PHAS loci with a strong balance between call-level precision and reference-locus recall, and generally outperformed PhaseTank and ShortStack in matched benchmark analyses. The register-resolved interpretation layer reduced unsupported calls by separating coherent phased loci from ambiguous sRNA-producing regions. In maize dcl5 mutant libraries, Phasis showed strong depletion of 24-PHAS recovery, supporting DCL5-dependent recovery of reproductive 24-PHAS signal. Together, these results support Phasis as a biologically interpretable tool for large-scale discovery of plant DCL-dependent phasiRNA loci.

bioinformatics↗
PubMed2026

Non-linear predictive modeling and comprehensive meta-analysis of rectal temperature in Santa Inês sheep: a systematic review of thermal challenges and biometerological trends.

A systematic and bibliometric review, combined with a meta-analysis, was used to adjust an equation for estimating the physiological responses of Santa Inês sheep subjected to different thermal challenges. The systematic review compiled data on physiological responses and the thermal environment, which were then used in the meta-analysis to adjust regression models. The bibliometric analysis mapped the relationships among studies, highlighting their usefulness in interpreting research findings and biases. Addressing prior methodological critiques, the core of this study involves replacing the linear approach with a non-linear segmented regression model to accurately define the Thermal Neutral Zone (TNZ). The Segmented Regression Model was crucial, establishing the upper limit of the Thermal Neutral Zone (TNZ) at an air temperature (tair) of 34.64 °C, where trectal begins to increase abruptly. The model, while identifying a biologically significant breakpoint, exhibited a moderate Multiple R-squared of 0.3529, highlighting the high heterogeneity and methodological variability in the current Santa Inês literature. This non-linear approach offers a biologically superior tool for identifying the onset of thermal distress.

Animals↗
PubMed1975

DNA-RNA hybridization.

Interest in nucleic acid hybridization stems mainly from its great power as a tool in biological research. It is used in several quite distinct ways. Because of the high degree of specificity that they show, hybridization techniques can be used to measure the amount of one specific sequence within a very heterogeneous mixture of sequences. Measurements of 1/10(6)-10(7) have been recorded. In extension of this, various properties of a specific sequence can often be studied. Secondly, because the kinetics of nucleic acid hybridization are quite well understood, it can be used to characterize both a pure sequence and a very complex mixture of sequences, like the genome of a vertebrate. Thirdly, again because of its specificity, it can be used to measure homologies between different populations of nucleic acids. Lastly, in conjunction with other techniques, it can be used as a basis for the fractionation of nucleic acid populations and the purification of specific sequences. Specific examples of these applications are given, with special reference to the organization of the genome in higher eukaryotes.

Animals↗
PubMed2025

Inference and visualization of complex genotype-phenotype maps with gpmap-tools.

Understanding how biological sequences give rise to observable traits, that is, how genotype maps to phenotype, is a central goal in biology. Yet our knowledge of genotype-phenotype maps in natural systems is limited due to the high dimensionality of sequence space and the context-dependent effects of mutations. The emergence of Multiplex assays of variant effect (MAVEs), along with large collections of natural sequences, offer new opportunities to empirically characterize these maps at an unprecedented scale. However, tools for statistical and exploratory analysis of these high-dimensional data are still needed. To address this gap, we developed gpmap-tools (https://github.com/cmarti/gpmap-tools), a python library that integrates a series of models for inference, phenotypic imputation, and error estimation from MAVE data or collections of natural sequences in the presence of genetic interactions of every possible order. gpmap-tools also provides methods for summarizing patterns of epistasis and visualization of genotype-phenotype maps containing up to millions of genotypes. To demonstrate its utility, we used gpmap-tools to infer genotype-phenotype maps containing 262,144 variants of the Shine-Dalgarno sequence from both genomic 5'UTR sequences and experimental MAVE data. Visualization of the inferred landscapes consistently revealed high-fitness ridges that link core motifs at different distances from the start codon. In summary, gpmap-tools provides a flexible, interpretable framework for studying complex genotype-phenotype maps, opening new avenues for understanding the architecture of genetic interactions and their evolutionary consequences.

Gaussian process↗