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CRISPR Tools To Control Gene Expression in Bacteria | Microbiology and Molecular Biology Reviews

CRISPR Tools To Control Gene Expression in Bacteria | Microbiology and Molecular Biology Reviews | RMH | Scoop.it

CRISPR-Cas systems have been engineered as powerful tools to control gene expression in bacteria. The most common strategy relies on the use of Cas effectors modified to bind target DNA without introducing DNA breaks. These effectors can either block the RNA polymerase or recruit it through activation domains. Here, we discuss the mechanistic details of how Cas effectors can modulate gene expression by blocking transcription initiation or acting as transcription roadblocks. CRISPR-Cas tools can be further engineered to obtain fine-tuned control of gene expression or target multiple genes simultaneously. Several caveats in using these tools have also been revealed, including off-target effects and toxicity, making it important to understand the design rules of engineered CRISPR-Cas effectors in bacteria. Alternatively, some types of CRISPR-Cas systems target RNA and could be used to block gene expression at the posttranscriptional level. Finally, we review applications of these tools in high-throughput screens and the progress and challenges in introducing CRISPR knockdown to other species, including nonmodel bacteria with industrial or clinical relevance. A deep understanding of how CRISPR-Cas systems can be harnessed to control gene expression in bacteria and build powerful tools will certainly open novel research directions.

 
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Another unresolved problem is the “bad-seed effect” (BSE). Among all the possible seed sequences (the last 5 nucleotides at the 3= end of a guide), a few of them systematically cause a strong fitness defect when used with S. pyogenes dCas9 in E. coli. For instance, when a guide finishing in ACCCA is expressed in E. coli K-12, it causes a nearly complete growth arrest of the population.

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Paralog interference contributes to the preservation of genetic redundancy | curB

Paralog interference contributes to the preservation of genetic redundancy | curB | RMH | Scoop.it
Models of gene duplication often assume that loss-of-function mutations neutrally promote the return to the ancestral singleton state. They thus ignore the potential functional interference between duplicated proteins stemming from their physical interactions. Here, we show that for heteromerizing paralogs, such interference potentiates negative selection on loss-of-function mutations. This effect maintains genetic redundancy over longer timescales depending on the rate and severity of loss-of-function mutations. We experimentally estimate that around 6% of deleterious amino acid substitutions in a representative tetrameric protein interfere with a second copy. Interfering substitutions typically disrupt either catalysis or the final step of protein complex assembly, with varying degrees of severity. Our work shows that paralog interference renders the negative effects of loss-of-function mutations visible to purifying selection, contributing to the preservation of genetic redundancy.
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2st, Dimeric paralogs with the same abundance and binding affinity will form a mixture of 25% of each homodimer and 50% of the heterodimer. If interfering mutations inactivate the mutant homodimers and the heterodimer, the fraction of functional complexes would be reduced to 25%.

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February 28, 4:05 PM
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Omics analyses decoding mechanisms underlying the self-flocculating phenotype of yeast cells and stress tolerance for robust production | meg

Omics analyses decoding mechanisms underlying the self-flocculating phenotype of yeast cells and stress tolerance for robust production | meg | RMH | Scoop.it
A unique self-flocculating yeast strain SPSC01 was developed through protoplast fusion for fuel ethanol production with high product titers. In this study, we conducted comparative multi-omics analyses on SPSC01 to elucidate mechanisms underlying its self-flocculating phenotype and associated stress tolerance, the most desirable merit for robust production in industry. Leveraging two cutting-edge third-generation sequencing technologies, we achieved a gapless high-quality and chromosome-level assembly for the genomes of SPSC01 and its parental strains. Through comprehensive genome analyses, we identified 25 unique genes that are absent in the parental strains, along with 13 novel genes with unknown functions. The self-flocculation of yeast cells is driven by the copy number of genetic variations and significantly upregulated transcription of FLO genes. Mutations in both cis- and trans-regulatory elements contribute to the constitutive expression of FLO1 and its derivative genes, a prerequisite for developing the self-flocculating phenotype. Notably, we discovered a novel small protein G12 that harbors a zinc finger domain, and its overexpression substantially enhanced ethanol production of engineered yeast strains. Furthermore, alterations in metabolic pathways with ergosterol, glutathione, amino acid, and glycerophospholipid are implicated for developing tolerance to ethanol and major inhibitors acetic acid and furfural that are released during the pretreatment of lignocellulosic biomass. The progress provides strategies for engineering yeast cell factories with robustness through rational design to produce biofuels and bio-based chemicals with high product titers and productivities, in particular with the biorefinery of lignocellulosic biomass for sustainable socioeconomic development.
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2st, developed a self-flocculating yeast strain SPSC01 through protoplast fusion with the non-flocculating S. cerevisiae K2, an excellent industrial strain for ethanol fermentation

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February 28, 3:29 PM
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Development of a transcription factor-based biosensor strain for reporting α-terpineol production via the alcohol-dependent hemiterpene pathway in Escherichia coli | rsc

Development of a transcription factor-based biosensor strain for reporting α-terpineol production via the alcohol-dependent hemiterpene pathway in Escherichia coli | rsc | RMH | Scoop.it

Terpenes constitute a vast and industrially important class of natural products. Yet, microbial production of many high-value terpenoids remains limited by the difficulty of rationally engineering their biosynthetic pathways and the lack of high-throughput screening systems that directly report product formation. This challenge is especially acute for monoterpene alcohols such as α-terpineol (1), whose biosynthesis in heterologous hosts requires coordinated precursor formation, cyclization, and water-capture chemistry. Here, we develop a transcription factor–based whole-cell biosensor strain capable of detecting 1 by engineering the p-cumate repressor CymR through structure-guided directed evolution. Guided by a model of the putative ligand-binding pocket, focused libraries at residues implicated in effector accommodation yielded variants with dramatically improved sensitivity. This culminated in the CymR variant 3-A8, which exhibits a 22-fold increase in dynamic range relative to wild-type. Using this optimized biosensor, we demonstrate in vivo monitoring of 1 production in E. coli by coupling it to an artificial alcohol-dependent hemiterpene (ADH) pathway and downstream modules expressing GPPS and α-terpineol synthase. The integrated biosensor–production system effectively distinguishes the complete biosynthetic pathway from deletions and reports intracellular titers consistent with GC-MS quantification. Together, these results provide the first biosensor for monocyclic monoterpene alcohols and establish a compact, modular framework for high-throughput screening and pathway optimization. This platform sets the stage for accelerating the discovery, engineering, and scalable bioproduction of valuable isoprenoids and other terpene-derived natural products.

mhryu@live.com's insight:

An AlphaFold computational model53 facilitated docking54–56 of 1 and the identification of the putative effector binding site. 

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February 28, 3:11 PM
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Harnessing AI to Decode Protein Kinases: Structural, Functional, and Therapeutic Design Perspectives

Harnessing AI to Decode Protein Kinases: Structural, Functional, and Therapeutic Design Perspectives | RMH | Scoop.it
Recent advances in Artificial Intelligence (AI) are reshaping kinase research by uncovering complex regulatory mechanisms and accelerating drug discovery. These advances have enabled the capture of elusive allosteric transitions and transient cryptic pockets by exploring dynamic conformational landscapes, revealing features critical for understanding ligand interactions and enzymatic regulation. AI-driven structure prediction tools, such as AlphaFold (AF)-based models, offer high-resolution insights into kinase conformations and complex assembly, thereby clarifying receptor activation in signaling pathways. Moreover, cutting-edge AI frameworks provide fresh perspectives on substrate prediction, cofactor mapping, and mutation-induced structural changes. Integrative strategies that combine Machine Learning (ML), molecular docking, Molecular Dynamics (MD) simulation, and experimental validation have further streamlined the discovery of novel kinase inhibitors and related studies. Collectively, these AI-enhanced approaches deepen our understanding of kinase-mediated signaling—from developmental processes to oncogenic transformation—and highlight the powerful synergy between computational and experimental research in advancing therapeutic innovations.
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February 28, 2:52 PM
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The type VI secretion system of Acinetobacter: mechanisms, biology and therapeutic potential | ComB

The type VI secretion system of Acinetobacter: mechanisms, biology and therapeutic potential | ComB | RMH | Scoop.it

The Type VI secretion system (T6SS) is widely recognized as a contractile nanomachine that mediates interbacterial antagonism, yet its biological roles and evolutionary logic vary substantially across bacterial lineages. In this Review, we synthesize recent advances in the Acinetobacter T6SS field and propose a unifying perspective in which the system functions as a context-dependent fitness module rather than a constitutive virulence weapon. We highlight how Acinetobacter has rewired a single T6SS platform through non-canonical structural solutions, multilayered regulatory integration, and an unusually expansive effector repertoire. Beyond microbial competition, emerging clinical and experimental evidence links T6SS activity to host immune amplification, disease severity, and the dynamics of horizontal gene transfer and antibiotic resistance. By integrating structural biology, regulatory logic, effector function, and clinical observations, this Review reframes the Acinetobacter T6SS as an adaptable system that balances aggression, persistence, and metabolic cost in polymicrobial and host-associated environments. This perspective not only advances conceptual understanding of T6SS diversity but also highlights translational opportunities for diagnostics, vaccines, and anti-virulence strategies targeting multidrug-resistant Acinetobacter infections. We synthesize advances in Acinetobacter T6SS biology, revealing how non-canonical structural solutions and multilayered regulation create an adaptable system for competition, persistence, and host immune modulation.

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February 28, 2:33 PM
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Shear flow promotes bacterial growth and shapes spatial gradients by rapidly replenishing scarce nutrients | mBio

Shear flow promotes bacterial growth and shapes spatial gradients by rapidly replenishing scarce nutrients | mBio | RMH | Scoop.it
In laboratory settings, bacteria grow in static culture with more nutrients than they require. However, bacteria in nature experience flowing environments that are nutrient-limited. Using microfluidics and single-cell imaging, we discover that shear flow promotes growth of the human pathogens Pseudomonas aeruginosa and Vibrio cholerae at surprisingly low nutrient concentrations. In static environments, cells require high nutrient concentrations as they steadily consume non-renewable resources. In slower-flowing environments, cells grow and deplete nutrients, which generates spatial gradient profiles. In faster-flowing environments, cells grow robustly and form microcolonies even at very low concentrations due to rapid nutrient replenishment. By precisely delivering nutrients using microfluidics, we learned that cells in flow can grow on glucose concentrations 1,000 times lower than those observed in typical laboratory experiments. The ultralow glucose concentrations sufficient for growth in flow closely align with the affinity of bacterial glucose transporters, suggesting that bacteria have evolved in flowing environments with scarce nutrients. Collectively, our results emphasize the limits of traditional culturing approaches and highlight how shear flow can promote bacterial growth and shape spatial gradients.
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February 28, 2:13 PM
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An Engineered Variant of E. coli Nissle 1917 with Enhanced Transformation Efficiency and Robustness | asb

An Engineered Variant of E. coli Nissle 1917 with Enhanced Transformation Efficiency and Robustness | asb | RMH | Scoop.it

The gut microbiome and its effects on human health have generated considerable scientific, veterinary, and medical interest in recent years. Several gut bacterial species have emerged as potential chassis organisms for the delivery of therapeutics in this milieu. Among these, E. coli Nissle 1917 (EcN), a nonpathogenic gut isolate bacterium, is quickly gaining popularity. However, a bottleneck in harnessing EcN’s potential has been its poor transformation efficiency relative to other bacterial strains. In this study, we present the use of adaptive laboratory evolution to increase EcN’s transformation efficiency by subjecting the strain to repeated cycles of electroporation and recovery. This new strain has been comprehensively characterized in comparison to the wild-type EcN, including assessments of growth under gut-mimicking duress conditions, permeability, motility, hydrophobicity, and plasmid replication. Since EcN is known to compete with pathogenic strains in the gut for iron, the competition dynamics and iron consumption of the strain were also significant factors to consider. Furthermore, we conducted genome sequencing and gene ontology enrichment analysis to identify affected genes and pathways to probe the potential mechanisms of the improved phenotype. Overall, the strain shows improved transformation efficiency and robustness while preserving its key biological functionality.

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1str, ale for efficient transformation

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Advances in multiplex precision genome editing in eukaryotic and prokaryotic systems | Cin

Advances in multiplex precision genome editing in eukaryotic and prokaryotic systems | Cin | RMH | Scoop.it
Multiplex genome editing (MGE) enables coordinated modification of multiple genomic loci and is foundational for engineering complex biological traits. Traditional CRISPR-Cas nuclease-based strategies rely on DNA double-strand breaks (DSBs), which limit precision and pose scaling challenges for incorporating simultaneous edits across different loci. Recent advances in genome editing technologies that operate without generating DSBs have expanded the accuracy and feasibility of multiplexed genomic manipulation. This review focuses on emerging strategies for precise MGE, including base editing, prime editing, and related genome rewriting platforms. We highlight key engineering principles that impact the success of scalable multiplexing, including the choice of editing platform, edit size, and guide RNA architecture, and discuss applications across mammalian, plant, fungal, and bacterial systems. Together, these technologies establish MGE as a versatile framework for precise multigene control in biotechnology and agriculture.
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February 28, 1:37 PM
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Editing and synthetic applications of chloroplast genomes | pcm

Editing and synthetic applications of chloroplast genomes | pcm | RMH | Scoop.it
Chloroplasts are central to photosynthesis and metabolic biosynthesis in plants and algae, offering immense potential for synthetic biology. This review highlights recent advances in chloroplast genome minimization, high-efficiency genome editing, and metabolic pathway redesign to optimize chloroplast functionality. We begin by summarizing strategies to relocate chloroplast-encoded genes to the nuclear genome, facilitating chloroplast genome streamlining while maintaining gene expression. We then discuss cutting-edge tools for precise chloroplast genome editing, enabling knockout, knock-in, base substitution, and multiplex modifications. Finally, we explore the dynamic regulation of chloroplast energy metabolism and the redesign of core pathways to establish de novo biosynthesis of high-value compounds, enhancing production efficiency and enabling crop trait improvement. These integrated approaches pave the way for next-generation chloroplast engineering with broad implications for biotechnology and agriculture.
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synbio

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February 28, 11:25 AM
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Skin androgens regulate Staphylococcus aureus pathogenicity via quorum sensing | Nmb

Skin androgens regulate Staphylococcus aureus pathogenicity via quorum sensing | Nmb | RMH | Scoop.it

Skin cells secrete testosterone, with greater amounts secreted at the skin surface of males compared with females. Males are also more susceptible to skin infections than females. Here we report that mice engineered with testosterone-deficient skin are resistant to methicillin-resistant Staphylococcus aureus infections. Testosterone promoted the expression of S. aureus cytotoxic virulence factors by activating the accessory gene regulator (agr) quorum-sensing pathway in a concentration-dependent manner and independent of quorum-sensing-activating auto-inducing peptides. Mutational analysis revealed that a functional histidine kinase AgrC in S. aureus was required for testosterone to exert its effect, with in silico evidence indicating a direct interaction between testosterone and AgrC. An isomer of testosterone, enantiomer-testosterone, that blocked bacterial quorum sensing, inhibited S. aureus-induced cytotoxicity of human cells. These findings advance our understanding of how the skin regulates bacterial virulence and reveals a potential therapeutic strategy for the management of infections. Testosterone produced by skin cells enhances Staphylococcus aureus pathogenicity by activating quorum sensing, and a stereoisomer of testosterone that blocks this interaction inhibits bacterial cytotoxicity towards human cells.

mhryu@live.com's insight:

testosterone sensor, testosterone signalling of quorum sensing requires the expression of the S. aureus histidine kinase receptor AgrC and the response regulator AgrA

The sensory domain of a single subunit (residues 1–207) was selected for ligand docking. AIP-I was docked in silico using SwissDock35,37 with nuclear-magnetic-resonance-derived coordinates for AIP-I. The docking pose for AIP-I that best aligned with reported structure–activity relationships11,41 was selected as the AgrC–AIP-I complex for subsequent steroid docking. To refine the complex, co-folding of AgrC in the presence of both AIP-I and testosterone was performed using AF364, implemented in PXDesign65,66 on the Protenix Server (https://protenix-server.com). AF3 successfully docked both ligands but introduced stereochemical distortions consistent with known AF3 limitations64

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February 27, 4:54 PM
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Kinetic Plasticity of Nitrite-Oxidizing Bacteria Containing Cytoplasmic Nitrite Oxidoreductase | isme

Kinetic Plasticity of Nitrite-Oxidizing Bacteria Containing Cytoplasmic Nitrite Oxidoreductase | isme | RMH | Scoop.it

Nitrite-oxidizing bacteria (NOB) use either periplasmic (pNXR) or cytoplasmic (cNXR) nitrite oxidoreductase to oxidize nitrite, and this distinction influences nitrite affinity and energy yield. cNXR-containing NOB have historically been considered low-affinity, copiotrophic nitrifiers adapted to high nitrite and neutral pH. Here, we report a previously uncharacterized pH- and substrate-dependent modulation of nitrite affinity in cNXR NOB that is not observed in pNXR NOB and is not a universal microbial trait. Nitrobacter winogradskyi Nb-255, grown at low nitrite (1 mM), had a high apparent affinity (Km(app) = 25.9 μM; specific affinity ao = 440.5 l g cells−1 h−1) comparable to oligotrophic pNXR NOB. However, when grown at high nitrite (10 mM), these cells showed a low affinity at pH 7.5 (Km(app) = 388.0 μM) but exhibited a rapid increase in affinity upon immediate exposure to pH 5.5 (Km(app) = 19.2 μM) without prior acid adaptation. In contrast, pNXR NOB exhibited consistent kinetic behavior across different pH conditions, underscoring that this kinetic plasticity is unique to cNXR NOB. Kinetic inhibition assays revealed that this plasticity is mechanistically underpinned by a shift from a low-affinity nitrite/nitrate antiporter (NarK) to a high-affinity nitrite channel (NirC), coupled with enhanced HNO2 diffusion at low pH, together increasing intracellular nitrite availability. These findings establish that cNXR NOB can dynamically tune nitrite affinity via transporter-level regulation in response to nitrite concentration and pH. This novel mechanism provides a mechanistic explanation for the unexpected prevalence of Nitrobacter in acidic, low-nitrite environments, highlighting its ecological relevance.

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nitrite transporter affinity change

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February 27, 4:32 PM
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Mixed-species interactions constrain diversification and shape biofilm evolution | brve

Mixed-species interactions constrain diversification and shape biofilm evolution | brve | RMH | Scoop.it

Long-term experimental evolution (LTEE) provides a powerful framework for dissecting how ecological interactions shape adaptive trajectories. Here, we evolved Klebsiella pneumoniae, Pseudomonas protegens and Pseudomonas aeruginosa in single- and mixed-species biofilm communities for 24 weeks and tracked changes in population dynamics, phenotypes, and genomes. In mono-species evolution, all three species exhibited similar dynamics of adaptation, with steadily increasing biofilm-associated populations. In contrast, mixed-species communities displayed striking compositional shifts, with P. protegens emerging as the dominant biofilm former and K. pneumoniae dominating the supernatant. Phenotypic assays revealed that all three species showed enhanced biofilm formation, but this increase was consistently greater in isolates from mono-species than mixed species communities, with P. protegens showing the largest gains. Beyond biofilm production, biofilm-associated isolates exhibited greater phenotypic diversification than planktonic isolates, whereas mixed-species interactions constrained diversification. Whole-genome sequencing identified species-specific putative adaptations such as csrD in K. pneumoniae, yfiBNR in P. protegens, and cheA in P. aeruginosa that arose early, persisted, and were enriched in mixed-species isolates. Functional assays confirmed that these mutations were indeed adaptive by enhancing biofilm formation, with yfiBNR mutations in P. protegens increasing cyclic-di-GMP production and producing a competitive advantage that recapitulated its dominance in LTEE biofilms. Our findings show that biofilm evolution fosters phenotypic diversification, whereas interspecific interactions shape adaptive trajectories, with specific mutations acting as keystone drivers of long-term ecological dynamics in multi-species communities.

mhryu@live.com's insight:

ale of microbial consortia

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February 27, 4:04 PM
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Engineered Escherichia coli as a microbial cell factory for intracellular protein delivery: strains, vectors, mechanisms, and therapeutic applications | Mcf

Engineered Escherichia coli as a microbial cell factory for intracellular protein delivery: strains, vectors, mechanisms, and therapeutic applications | Mcf | RMH | Scoop.it

E. coli has emerged as a promising vector of therapeutic proteins into target cells due to its high fidelity to genetic manipulations, short generation times, and well-known molecular pathways. Over the years, the use of E. coli as a delivery vector has been explored in various mechanisms. This review aims to discuss the mechanisms through which E. coli can express and transport therapeutic proteins to target cells. Various delivery systems have been developed using E. coli, starting from the simple plasmid vectors, to outer membrane vesicles and, in some cases, live bacteria itself which can transport proteins into cells. These E. coli based systems are of immense potential in targeted drug delivery and therapeutic applications and have made E. coli to lead in novel biotechnological developments. However, there are still many challenges, concerning the improvement of the safety and efficacy of E. coli for protein delivery into cells, especially in regards to delivery efficiency and directional control in a real biological environment. Most of these challenges have been solved by the recent developments in synthetic biology, genetic engineering and E. coli is gradually becoming a versatile vector for protein therapeutic delivery into cells.

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February 28, 4:09 PM
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Membrane and proteome allocation constraints in Escherichia coli models during overflow metabolism | bphy

Membrane and proteome allocation constraints in Escherichia coli models during overflow metabolism | bphy | RMH | Scoop.it
The allocation of finite cellular resources is a fundamental principle that dictates microbial metabolic strategies and gives rise to complex phenomena, such as overflow metabolism, characterized by the production of respiro-fermentative by-products, including acetate, during rapid growth. Although proteome-constrained models have successfully predicted overflow metabolism in E. coli, they often overlook the distinct biophysical and energetic costs associated with protein localization. The cellular membrane, in particular, represents a critical and constrained compartment where competition for space and synthesis machinery can create significant metabolic bottlenecks.  To investigate this, we developed the membrane-associated constrained flux balance analysis (MAFBA), a scalable, genome-scale metabolic model that introduces a tunable constraint on the total protein mass allocated to the cellular membrane. Our model demonstrates that the overall and membrane-associated proteome allocation constraints interact to improve the accuracy of predicting the onset of overflow metabolism. It mechanistically reveals that at high growth rates, competition for limited membrane allocation forces a trade-off between growth-essential functions and respiratory capacity, leading to acetate production. Furthermore, MAFBA quantitatively explains the widely observed experimental phenomenon that expressing heterologous membrane proteins imposes a significantly higher metabolic burden than expressing cytosolic proteins.  This study establishes membrane resource allocation as a key constraint governing bacterial physiology, acting in concert with overall proteome limitations. The resulting MAFBA framework provides a powerful and accessible tool for synthetic biology and metabolic engineering, enabling the prediction of metabolic costs associated with expressing membrane-bound proteins and guiding strain design strategies, holding promise for applications in bioproduction and metabolic engineering.
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February 28, 3:51 PM
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Ecological tristability driven by total carbon availability over resource complexity in a synthetic microbial community | brveco

Ecological tristability driven by total carbon availability over resource complexity in a synthetic microbial community | brveco | RMH | Scoop.it

Even though complex microbial communities are ubiquitous and provide essential services for natural and human-associated ecosystems, our knowledge about their assembly and dynamics is incomplete. There is an ongoing debate whether the behavior of complex communities can be predicted from the outcome of pairwise competition of species, and whether communities reach alternative stable states depending on the level and complexity of resource provided for growth. To estimate the effect of two resource gradients, total carbon availability and resource complexity, on the compositional dynamics of a complex microbial community, we conducted a 16-day serial passage experiment, transferring a 16-species synthetic community in 96 different resource environments. We observed that although both resource dimensions influenced community composition, total carbon exerted a considerably larger effect. Additionally, we saw the emergence of a tristable pattern along the total carbon gradient, a feature not observed for the resource complexity gradient. Using monoculture assays, we identified lag phase duration as the dominant predictor of competitive success at carbon extremes, with maximum growth rate increasing in importance as lag times converged. Total carbon availability thus structured community state transitions and regulated which growth trait governed competitive sorting. These results suggest the importance of total carbon level over resource complexity and identifying dominant species for the quest to successfully manage, maintain and manipulate complex microbial communities.

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The most successful strains exhibited a combination of high growth rate and short lag phase. Others have provided evidence, that in batch and serial-transfer systems, shorter lag phases alone can confer priority effects, allowing for early resource capture that may outweigh differences in maximal growth rate

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February 28, 3:17 PM
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Harnessing eCISs for precision phytomicrobiome engineering and biocontrol | fems rev

Harnessing eCISs for precision phytomicrobiome engineering and biocontrol | fems rev | RMH | Scoop.it

Plant microbiome disruption often increases vulnerability to crop diseases, endangering worldwide food production, while chemical pesticides become increasingly less viable and continue to damage ecosystems. To safeguard plant microbiome health, several biological control strategies offer alternatives, yet many operate through broader or weakly defined target mechanisms. In recent years, bacterial contractile injection systems (BCISs) have emerged as a promising class of naturally evolved nanomachines that translocate molecular payloads directly into target cells. Subsets of these systems, extracellular contractile injection systems (eCISs), are distinguished by their specific narrow host range and receptor-dependent specificity. Recent studies have demonstrated that eCISs provide a transformative approach for targeted microbial manipulation, enabling the delivery of specialized molecules into particular microbes with higher precision. However, despite their potential, the integration of these engineered injection systems with microbial modulation for phytomicrobiome remains largely underexplored. Here, we explore the capabilities of eCISs as an advanced approach for the biocontrol, leveraging their tailored mechanisms for targeted payload delivery in plant-associated microbial communities with enhanced host specificity. This study aims to address the potential of engineered injection systems in facilitating sustainable phytomicrobiome engineering strategies that enhance biocontrol, aiming to reduce environmental harm while improving agricultural productivity.

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2st

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Automated high-throughput selection of DNA aptamers using a common optical next-generation sequencer | nar

Automated high-throughput selection of DNA aptamers using a common optical next-generation sequencer | nar | RMH | Scoop.it

Aptamers are conventionally selected via ‘Systematic Evolution of Ligands by Exponential Enrichment’ (SELEX). However, this process is laborious, time-consuming, and has a relatively low efficacy. In this study, we present a novel automated high-throughput screening platform that augments the conventional selection of DNA aptamers. To this end, the software of an optical next-generation sequencer has been modified to automatically perform fluorescence-based binding assays on the displayed DNA sequences subsequent to sequencing. Utilizing this platform, high-affinity DNA aptamers were identified for the proteins LecA, LecB, and Pseudomonas Exotoxin A (PEA) of Pseudomonas aeruginosa following pre-enrichment by a mere three to five SELEX rounds. Conversely, 12 rounds of conventional SELEX yielded aptamers exhibiting three-fold lower affinity for LecA and PEA, with no aptamers obtained for LecB. Furthermore, we demonstrate that the proposed method is suitable for the study of molecules ranging from small molecules to whole cells. This is evidenced by a mutation assay for a kanamycin-binding aptamer and the monitoring of E. coli binding to aptamers. The present study proposes a high-throughput approach to enhance SELEX, with the potential to provide greater insight into the selection process and to significantly increase efficacy, enabling the selection of aptamers within a week.

mhryu@live.com's insight:

2st, tool hts aptamer, A more recent method with enormous potential for aptamer selection is ‘High-Throughput Sequencing–Fluorescent Ligand Interaction Profiling’ (HiTS-FLIP) [7].

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Industrial perspective validation of a neutralizer-free l-lactic acid production process by engineered acid-tolerant yeast Pichia kudriavzevii | Tin

Industrial perspective validation of a neutralizer-free l-lactic acid production process by engineered acid-tolerant yeast Pichia kudriavzevii | Tin | RMH | Scoop.it
Large amounts of waste salt formation are a major bottleneck in the industrial production of l-lactic acid (l-LA). In this study, we developed a cost-effective, neutralizer-free process with industrial potential using acid-tolerant yeast Pichia kudriavzevii. Based on the previously engineered P. kudriavzevii Pkz04, we further improved l-LA production by inserting multicopy l-lactate dehydrogenase, performing promoter replacement, and introducing a lactate transporter, resulting in 102.32 g/l l-LA without neutralizers. Subsequently, we performed batch fermentation in a low-cost inorganic salt medium containing only 0.03 g/l yeast extract and achieved 75.09 g/l l-LA, which outperformed most reported strains with respect to a yield of 0.99 g/g glucose. Finally, a detailed technoeconomic analysis was conducted, including an analysis of low concentrations of organic nitrogen sources, pH-adjustment and nonadjustment processes, and carbon losses in different fermentation processes. Our results highlight the potential of low-pH production of l-LA from an industrial perspective, which is both financially viable and environmentally beneficial.
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February 28, 2:29 PM
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Enzyme-enhanced RNA isolation from biofilm-producing bacteria | msp

Enzyme-enhanced RNA isolation from biofilm-producing bacteria | msp | RMH | Scoop.it
RNA isolation is a critical first step for gene expression analysis; however, obtaining high-quality RNA from polysaccharide-rich or biofilm-producing microbial samples remains challenging. High polysaccharide content hinders cell lysis, decreases RNA yield, and reduces sample purity, limiting the reliability and accuracy of downstream techniques such as RNA-seq and RT-qPCR. In this study, we evaluated the use of polysaccharide lyase, Smlt1473, as a pre-processing step to improve RNA isolation from Pseudomonas species. Incorporation of Smlt1473 into a commercial RNA extraction kit workflow significantly improved RNA extraction for mucoid clinical and agricultural pseudomonads and did not adversely affect the non-mucoid isolate, PA14. More specifically, RNA-seq analysis demonstrated that pre-processing with Smlt1473 increased the proportion of assigned reads without introducing significant changes in gene expression. Only a limited set of genes—primarily hypothetical proteins and potential phage-associated elements—were differentially expressed, while global transcriptional profiles remained stable. Together, these findings demonstrate that pre-processing with Smlt1473 provides an effective, easily integrated method to enhance RNA isolation from biofilm-forming bacteria and improves RNA-seq data quality without perturbing the underlying biology.
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methods, 300 μL of culture was added to 300 μL of a cold 1:1 ethanol:acetone solution to stabilize RNA and mixed. The mixture was centrifuged at 10,000 rpm for 5 min, and then the supernatant was discarded. For those that did not receive enzyme, 25 μL of 4 mg/mL lysozyme (Affymetrix) was added. For those receiving enzyme treatment, 25 μL of 4 mg/mL lysozyme was added, in addition to 100 μg of Smlt1473.

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5,10-Methylenetetrahydrofolate Reductase─the Key Allosteric Regulator in One-Carbon Metabolism | acs

5,10-Methylenetetrahydrofolate Reductase─the Key Allosteric Regulator in One-Carbon Metabolism | acs | RMH | Scoop.it

Collectively known as one-carbon metabolism (OCM), both the folate and methionine cycles are highly regulated to meet cellular demands. These cycles are key in the production and recycling of methyl groups to be used in many essential cellular processes such as the production of nucleotides, as well as S-adenosyl-l-methionine (SAM) the global methyl donor for DNA, RNA, and post translational modifications. Within the folate cycle, 5,10-methylenetetrahydrofolate is the main species through which methyl groups enter OCM. Therefore, 5,10-methylenetetrahydrofolate reductase (MTHFR), which reduces 5,10-methylenetetrahydrofolate into 5-methyltetrahydrofolate, is the central enzyme that directs methyl groups for use within the methionine cycle. MTHFR is an enzyme found in all domains of life, but unlike in prokaryotes, eukaryotic MTHFR activity is highly regulated by the level of SAM, to balance the one-carbon needs of the cell. In this perspective, we review the catalytic mechanism of MTHFR, evolutionary differences, and the regulatory mechanisms that have evolved to alter its activity. We also discuss recent structural findings that reveal a unique mechanism for inactivation by SAM as a feedback loop and its consequences for understanding inherited MTHFR deficiency.

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Methanotroph-embedded hydrogels as platforms for methane removal | Cin

Methanotroph-embedded hydrogels as platforms for methane removal | Cin | RMH | Scoop.it
Methane is a potent greenhouse gas with a short atmospheric lifetime, making its removal critical for mitigating climate change. Methanotrophic microorganisms enzymatically oxidize methane at ambient temperatures, offering a biological route for mitigation. However, conventional liquid-based bioreactors face mass transfer limitations and scalability challenges. Here, we review studies of methanotrophic biofilms and explore their embedding within hydrogel matrices, which can enhance gas diffusion, support stable biofilm growth, and improve methane uptake rates, as a biotechnology for methane removal. These hydrogel-embedded methanotrophic systems combine biocompatibility and structural advantages to facilitate efficient methane uptake and removal. This approach holds promise for scalable, cost-effective bioreactors capable of reducing methane emissions from diverse sources, thereby contributing to near-term climate change mitigation efforts.
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1str, hydrogel type

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MPNN-guided redesign of PET hydrolases with enhanced catalytic activity below the PET glass transition temperature | brvm

MPNN-guided redesign of PET hydrolases with enhanced catalytic activity below the PET glass transition temperature | brvm | RMH | Scoop.it

The enzymatic depolymerization of polyethylene terephthalate (PET) presents a sustainable route for plastic circularity, but its industrial viability is disadvantaged by the need for thermostable enzymes that remain active under mild, energy-efficient conditions. While the Polyester Hydrolase Leipzig 7 (PHL7) rapidly degrades amorphous PET near its melting point, its poor protein expression, inactivation issues at temperatures above 60°C and slow depolymerization activity below 60°C limit its practical application. Here, we employ inverse folding models ProteinMPNN and LigandMPNN, informed by structural and evolutionary information, to redesign the sequence of PHL7, aiming to improve protein expression, thermal stability and activity. From 36 designed variants, we identified two (termed D5 and D11) with significantly enhanced PET depolymerization rates at lower temperatures, where enzymatic performance is typically limited. Remarkably, design D5 at 50°C achieved the same product yield as PHL7 at 70°C in 24 h PET microparticle degradation assays, with a shifted product profile favoring mono-(2-hydroxyethyl) terephthalate (MHET) over terephthalic acid (TPA). Molecular dynamics simulations revealed that the active redesigns exhibit enhanced local flexibility in key active site regions at 50°C, providing a mechanistic understanding of their low-temperature catalysis. This work demonstrates that computational sequence redesign can optimize biocatalysts for lower production costs and milder operational conditions. Furthermore, the D5 variant enables a potential route to resynthesize virgin PET via MHET polycondensation, offering an efficient circular economy pathway.

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thermo

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The dynamic distribution of genetic tandem amplifications in a heteroresistant Escherichia coli population revealed by ultra-deep long read sequencing | Ncm

The dynamic distribution of genetic tandem amplifications in a heteroresistant Escherichia coli population revealed by ultra-deep long read sequencing | Ncm | RMH | Scoop.it

Antibiotic heteroresistance, characterized by rare resistant subpopulations of bacteria within a susceptible main population, is associated with treatment failure and often caused by tandem amplification of resistance genes. Here, we investigated how the distribution of tandem amplifications affects heteroresistance using an approach combining genetic engineering and ultra-deep Nanopore sequencing to accurately quantify the distribution of tandem amplification copy numbers on plasmids down to frequencies of 10-5. Using an Escherichia coli isolate, we describe the direct relation between the distribution of tandem amplifications increasing the copy number of a blaSHV gene and a heteroresistance phenotype to piperacillin-tazobactam, and reveal how this distribution expands under antibiotic pressure and partially reverts upon its removal. Mathematical modeling indicates that indirect resistance and fitness cost of amplifications influence the dynamic distribution of tandem amplifications. These findings provide insights into amplification-mediated phenotypes and enhance possibilities for the development of improved therapeutic and diagnostics strategies for heteroresistance. Antibiotic heteroresistence is commonly caused by repeated amplification of resistance genes. Jonsson et al., reveals the relation between these two events, and how antibiotic pressure, fitness cost and indirect resistance affect the distribution of tandem repeats.

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replicated genes in tandem

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Engineering sensor-based antithetic integral controllers for enhanced dynamic performance and noise attenuation | Csys

Engineering sensor-based antithetic integral controllers for enhanced dynamic performance and noise attenuation | Csys | RMH | Scoop.it
Effective cellular regulation relies on feedback control mechanisms to maintain homeostasis and mitigate environmental fluctuations. We develop and analyze a sensor-based antithetic integral feedback (sAIF) controller that achieves this by embedding proportional and integral actions within a minimal genetic architecture. Arising from a single modification to the classical antithetic control motif, this sAIF architecture intrinsically incorporates proportional feedback without requiring additional circuitry. Control-theoretic and stochastic analyses show that this proportional action speeds up the system’s dynamic response and counteracts the noise amplification typical of pure integral feedback, enabling both improved speed and reduced cellular variability. Using intein-mediated splicing, we implement sAIF in E. coli and demonstrate robust perfect adaptation, strong disturbance rejection, and favorable noise properties. These findings establish a generalizable design principle for engineering high-performance biological controllers, with broad implications for synthetic biology, metabolic engineering, and cell-based therapies. 
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khammash

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Calibrating for absolute microbiome abundances without spike-ins | brvm

Calibrating for absolute microbiome abundances without spike-ins | brvm | RMH | Scoop.it

Metagenomics is a widely used approach in microbiome research. However, a major limitation of metagenomic datasets is their compositional nature, which prevents direct quantification of absolute abundances and complicates cross-sample comparisons. Existing strategies for absolute quantification typically require additional experiments or spike-in controls. Here, we introduce the MetaGenome Calibrator (MGCalibrator), a new tool that enables spike-in free, absolute abundance estimation based on routine DNA concentration measurements. We validated the accuracy of absolute abundances obtained with MGCalibrator against qPCR for 5 targets. Our results show a strong correlation with qPCR data, indicating that MGCalibrator enables qPCR-like trend analyses. For Bacteroides dorei, the estimated abundances were highly similar between the two methods (r2 = 0.98, y = 1.00x). For other targets like crAssphage or the bacterial 16S rRNA gene, qPCR values were underrepresented by a factor of 7 or overrepresented by a factor of 4. Benchmarking with synthetic microbiome data demonstrated that our method accurately determines copy numbers in sequencing datasets, and application to whole-cell mock community samples produced expected values based on known extraction biases. In an extraction-bias-free experiment, MGCalibrator accurately quantified genome copy numbers within a twofold range in 98% of cases and determined 16S rRNA gene copies within 1.6-fold or less. Finally, we applied MGCalibrator to track temporal trends in antibiotic resistance genes (ARGs) in wastewater treatment plants in two Dutch provincial capitals. We observed an overall increase in ARGs—such as sul2 in Utrecht and qnrS5 in Houtrust—likely driven by rising bacterial loads. Our findings demonstrate that MGCalibrator provides robust calibration of metagenomic data, paving the way for metagenomics to play a central role in future surveillance by enabling trend analysis across thousands of genetic targets, similar to the capabilities of qPCR for individual genes. The source code and documentation for MGCalibrator are available at github.com/NimroddeWit/MGCalibrator.

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r-3st, Extracted DNA is quantified to obtain the total extracted mass (e). Following metagenomic sequencing, the total sequenced DNA length (sl) is converted to sequenced DNA mass (sm), allowing calculation of the sequenced proportion (p = sm / e). A scaling factor (f = 1 / p) is derived to correct for subsampling during sequencing. Reads are aligned to target sequences (BAM), and target-specific depth (d = aligned bp / target bp) is estimated using Monte Carlo simulation to account for relative error. Calibrated abundance (c) is then computed as c = d × f, yielding target-specific copy number estimates with associated uncertainty.

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