Visualization of synthetic retroelement integration reveals determinants of permissivity to retrotransposition

Real-time visualization of retrotransposon mobilization in Arabidopsis reveals that the DNA damage response pathways are involved in the retrotranspositional process.

Influence of DNP Polarizing Agents on Biochemical Processes: TEMPOL in Transient Ischemic Stroke

Hyperpolarization of 13C by dissolution dynamic nuclear polarization (dDNP) boosts the sensitivity of magnetic resonance spectroscopy (MRS), making possible the monitoring in vivo and in real time of the biochemical reactions of exogenously infused 13C-labeled metabolic tracers. The preparation of a hyperpolarized substrate requires the use of free radicals as polarizing agents. Although added at very low doses, these radicals are not biologically inert. Here, we demonstrate that the presence of the nitroxyl radical TEMPOL influences significantly the cerebral metabolic readouts of a hyperpolarized [1-13C] lactate bolus injection in a mouse model of ischemic stroke with reperfusion. Thus, the choice of the polarizing agent in the design of dDNP hyperpolarized MRS experiments is of great importance and should be taken into account to prevent or to consider significant effects that could act as confounding factors.

Induced Resistance in Fruit and Vegetables: A Host Physiological Response Limiting Postharvest Disease Development

Harvested fruit and vegetables are perishable, subject to desiccation, show increased respiration during ripening, and are colonized by postharvest fungal pathogens. Induced resistance is a strategy to control diseases by eliciting biochemical processes in fruits and vegetables. This is accomplished by modulating the progress of ripening and senescence, which maintains the produce in a state of heightened resistance to decay-causing fungi. Utilization of induced resistance to protect produce has been improved by scientific tools that better characterize physiological changes in plants. Induced resistance slows the decline of innate immunity after harvest and increases the production of defensive responses that directly inhibit plant pathogens. This increase in defense response in fruits and vegetables contributes to higher amounts of phenols and antioxidant compounds, improving both the quality and appearance of the produce. This review summarizes mechanisms and treatments that induce resistance in harvested fruits and vegetables to suppress fungal colonization. Moreover, it highlights the importance of host maturity and stage of ripening as limiting conditions for the improved expression of induced-resistance processes.

Electron transport chains as a window into the earliest stages of evolution

The origin and early evolution of life is generally studied under two different paradigms: bottom up and top down. Prebiotic chemistry and early Earth geochemistry allow researchers to explore possible origin of life scenarios. But for these "bottom-up" approaches, even successful experiments only amount to a proof of principle. On the other hand, "top-down" research on early evolutionary history is able to provide a historical account about ancient organisms, but is unable to investigate stages that occurred during and just after the origin of life. Here, we consider ancient electron transport chains (ETCs) as a potential bridge between early evolutionary history and a protocellular stage that preceded it. Current phylogenetic evidence suggests that ancestors of several extant ETC components were present at least as late as the last universal common ancestor of life. In addition, recent experiments have shown that some aspects of modern ETCs can be replicated by minerals, protocells, or organic cofactors in the absence of biological proteins. Here, we discuss the diversity of ETCs and other forms of chemiosmotic energy conservation, describe current work on the early evolution of membrane bioenergetics, and advocate for several lines of research to enhance this understanding by pairing top-down and bottom-up approaches.

A neural-mechanistic hybrid approach improving the predictive power of genome-scale metabolic models

Constraint-based metabolic models have been used for decades to predict the phenotype of microorganisms in different environments. However, quantitative predictions are limited unless labor-intensive measurements of media uptake fluxes are performed. We show how hybrid neural-mechanistic models can serve as an architecture for machine learning providing a way to improve phenotype predictions. We illustrate our hybrid models with growth rate predictions of Escherichia coli and Pseudomonas putida grown in different media and with phenotype predictions of gene knocked-out Escherichia coli mutants. Our neural-mechanistic models systematically outperform constraint-based models and require training set sizes orders of magnitude smaller than classical machine learning methods. Our hybrid approach opens a doorway to enhancing constraint-based modeling: instead of constraining mechanistic models with additional experimental measurements, our hybrid models grasp the power of machine learning while fulfilling mechanistic constrains, thus saving time and resources in typical systems biology or biological engineering projects.

Variation of digital economy's effect on carbon emissions: improving energy efficiency and structure for energy conservation and emission reduction

The significance of accurately assessing the influence of digital economy growth upon reducing emission of carbon in the context of worldwide climate governance cannot be overstated. This is crucial in encouraging low-carbon economic advancement at national level, achieving carbon peak and neutrality as soon as possible, and creating a shared future for humanity. A mediating effect model is established using cross-country panel data from 100 countries, ranging from 1990 to 2019, to assess the influence of digital economy development upon emission of carbon and to explore its underlying mechanism. The study found that: the growth of national emission of carbon can be considerably suppressed by digital economy development, and the reduction of emissions is positively associated to each country's level of economic advancement. Digital economy growth influences regional emission of carbon via intermediary channels like energy structure and efficiency, with energy intensity having a particularly noticeable intermediary impact. The inhibitory influence of digital economy development upon emission of carbon differs among countries with different levels of income, and improvements in energy structure and efficiency can precede to energy savings and emission reduction in both middle- and high-income countries. The above findings offer policy guidance for harmoniously advancing the growth of digital economy and climate management, hastening the low-carbon transformation of national economies, and implementing China's carbon peaking initiative.

Targeting Riboswitches with Beta-Axial-Substituted Cobalamins

RNA-targeting small-molecule therapeutics is an emerging field hindered by an incomplete understanding of the basic principles governing RNA-ligand interactions. One way to advance our knowledge in this area is to study model systems where these interactions are better understood, such as riboswitches. Riboswitches bind a wide array of small molecules with high affinity and selectivity, providing a wealth of information on how RNA recognizes ligands through diverse structures. The cobalamin-sensing riboswitch is a particularly useful model system, as similar sequences show highly specialized binding preferences for different biological forms of cobalamin. This riboswitch is also widely dispersed across bacteria and therefore holds strong potential as an antibiotic target. Many synthetic cobalamin forms have been developed for various purposes including therapeutics, but their interaction with cobalamin riboswitches is yet to be explored. In this study, we characterize the interactions of 11 cobalamin derivatives with three representative cobalamin riboswitches using in vitro binding experiments (both chemical footprinting and a fluorescence-based assay) and a cell-based reporter assay. The derivatives show productive interactions with two of the three riboswitches, demonstrating simultaneous plasticity and selectivity within these RNAs. The observed plasticity is partially achieved through a novel structural rearrangement within the ligand binding pocket, providing insight into how similar RNA structures can be targeted. As the derivatives also show in vivo functionality, they serve as several potential lead compounds for further drug development.

Role of Strong Localized vs Weak Distributed Interactions in Disordered Protein Phase Separation

Interaction strength and localization are critical parameters controlling the single-chain and condensed-state properties of intrinsically disordered proteins (IDPs). Here, we decipher these relationships using coarse-grained heteropolymers comprised of hydrophobic (H) and polar (P) monomers as model IDPs. We systematically vary the fraction of P monomers XP and employ two distinct particle-based models that include either strong localized attractions between only H-H pairs (HP model) or weak distributed attractions between both H-H and H-P pairs (HP+ model). To compare different sequences and models, we first carefully tune the attraction strength for all sequences to match the single-chain radius of gyration. Interestingly, we find that this procedure produces similar conformational ensembles, nonbonded potential energies, and chain-level dynamics for single chains of almost all sequences in both models, with some deviations for the HP model at large XP. However, we observe a surprisingly rich phase behavior for the sequences in both models that deviates from the expectation that similarity at the single-chain level will translate to a similar phase-separation propensity. Coexistence between dilute and dense phases is only observed up to a model-dependent XP, despite the presence of favorable interchain interactions, which we quantify using the second virial coefficient. Instead, the limited number of attractive sites (H monomers) leads to the self-assembly of finite-sized clusters of different sizes depending on XP. Our findings strongly suggest that models with distributed interactions favor the formation of liquid-like condensates over a much larger range of sequence compositions compared to models with localized interactions.

Genome-scale community modeling for deciphering the inter-microbial metabolic interactions in fungus-farming termite gut microbiome

Specialized microbial communities in the fungus-farming termite gut and fungal comb microbiome help maintain host nutrition through interactive biochemical activities of complex carbohydrate degradation. Numerous research studies have been focused on identifying the microbial species in the termite gut and fungal comb microbiota, but the community-wide metabolic interaction patterns remain obscure. The inter-microbial metabolic interactions in the community environment are essential for executing biochemical processes like complex carbohydrate degradation and maintaining the host's physicochemical homeostasis. Recent progress in high-throughput sequencing techniques and mathematical modeling provides suitable platforms for constructing multispecies genome-scale community metabolic models that can render sound knowledge about microbial metabolic interaction patterns. Here, we have implemented the genome-scale metabolic modeling strategy to map the relationship between genes, proteins, and reactions of 12 key bacterial species from fungal cultivating termite gut and fungal comb microbiota. The resulting individual genome-scale metabolic models (GEMs) have been analyzed using flux balance analysis (FBA) to optimize the metabolic flux distribution pattern. Further, these individual GEMs have been integrated into genome-scale community metabolic models where a heuristics-based computational procedure has been employed to track the inter-microbial metabolic interactions. Two separate genome-scale community metabolic models were reconstructed for the O. badius gut and fungal comb microbiome. Analysis of the community models showed up to ∼167% increased flux range in lignocellulose degradation, amino acid biosynthesis, and nucleotide metabolism pathways. The inter-microbial metabolic exchange of amino acids, SCFAs, and small sugars was also upregulated in the multispecies community for maximum biomass formation. The flux variability analysis (FVA) has also been performed to calculate the feasible flux range of metabolic reactions. Furthermore, based on the calculated metabolic flux values, newly defined parameters, i.e., pairwise metabolic assistance (PMA) and community metabolic assistance (CMA) showed that the microbial species are getting up to 15% higher metabolic benefits in the multispecies community compared to pairwise growth. Assessment of the inter-microbial metabolic interaction patterns through pairwise growth support index (PGSI) indicated an increased mutualistic interaction in the termite gut environment compared to the fungal comb. Thus, this genome-scale community modeling study provides a systematic methodology to understand the inter-microbial interaction patterns with several newly defined parameters like PMA, CMA, and PGSI. The microbial metabolic assistance and interaction patterns derived from this computational approach will enhance the understanding of combinatorial microbial activities and may help develop effective synergistic microcosms to utilize complex plant polymers.

A tour de force provides novel insights into CD19-CAR T cell resistance mechanisms

Sworder et al.¹ developed an integrated simultaneous tumor and effector profiling (STEP) approach to study resistance mechanisms to CD19-CAR T cell therapy in large B-cell lymphomas. Their study provides novel biological insights and paves the way for future interventions.

Strategies to increase uptake of voluntary medical male circumcision among men aged 25-39 years in Nyanza Region, Kenya: Results from a cluster randomized controlled trial (the TASCO study)

INTRODUCTION

Voluntary medical male circumcision (VMMC) for HIV prevention began in Nyanza Region, Kenya in 2008. By 2014, approximately 800,000 VMMCs had been conducted, and 84.9% were among males aged 15-24 years. We evaluated the impact of interpersonal communication (IPC) and dedicated service outlets (DSO) on VMMC uptake among men aged 25-39 years in Nyanza Region.

MATERIALS AND METHODS

We conducted a cluster randomized controlled trial in 45 administrative Locations (clusters) in Nyanza Region between May 2014 and June 2016 among uncircumcised men aged 25-34 years. In arm one, an IPC toolkit was used to address barriers to VMMC. In the second arm, men were referred to DSO that were modified to address their preferences. Arm three combined the IPC and DSO arms, and arm four was standard of care (SOC). Randomization was done at Location level (11-12 per arm). The primary outcome was the proportion of enrolled men who received VMMC within three months. Generalized estimating equations were used to evaluate the effect of interventions on the outcome.

RESULTS

At baseline, 9,238 households with men aged 25-39 years were enumerated, 9,679 men were assessed, and 2,792 (28.8%) were eligible. For enrollment, 577 enrolled in the IPC arm, 825 in DSO, 723 in combined IPC + DSO, and 667 in SOC. VMMC uptake among men in the SOC arm was 3.2%. In IPC, DSO, and combined IPC + DSO arms, uptake was 3.3%, 4.5%, and 4.4%, respectively. The adjusted odds ratio (aOR) of VMMC uptake in the study arms compared to SOC were IPC aOR = 1.03; 95% CI: 0.50-2.13, DSO aOR = 1.31; 95% CI: 0.67-2.57, and IPC + DSO combined aOR = 1.31, 95% CI: 0.65-2.67.

DISCUSSION

Using these interventions among men aged 25-39 years did not significantly impact VMMC uptake. These findings suggest that alternative demand creation strategies for VMMC services are needed to reach men aged 25-39 years.

TRIAL REGISTRATION

clinicaltrials.gov identifier: NCT02497989.

Epistasis between promoter activity and coding mutations shapes gene evolvability

The evolution of protein-coding genes proceeds as mutations act on two main dimensions: regulation of transcription level and the coding sequence. The extent and impact of the connection between these two dimensions are largely unknown because they have generally been studied independently. By measuring the fitness effects of all possible mutations on a protein complex at various levels of promoter activity, we show that promoter activity at the optimal level for the wild-type protein masks the effects of both deleterious and beneficial coding mutations. Mutations that are deleterious at low activity but masked at optimal activity are slightly destabilizing for individual subunits and binding interfaces. Coding mutations that increase protein abundance are beneficial at low expression but could potentially incur a cost at high promoter activity. We thereby demonstrate that promoter activity in interaction with protein properties can dictate which coding mutations are beneficial, neutral, or deleterious.

Dynein-Mediated Trafficking: A New Mechanism of Diabetic Podocytopathy

Key Points

The expression of dynein is increased in human and rodent models of diabetic nephropathy (DN), eliciting a new dynein-driven pathogenesis. Uncontrolled dynein impairs the molecular sieve of kidney by remodeling the postendocytic triage and homeostasis of nephrin. The delineation of the dynein-driven pathogenesis promises a broad spectrum of new therapeutic targets for human DN.

Background

Diabetic nephropathy (DN) is characterized by increased endocytosis and degradation of nephrin, a protein that comprises the molecular sieve of the glomerular filtration barrier. While nephrin internalization has been found activated in diabetes-stressed podocytes, the postinternalization trafficking steps that lead to the eventual depletion of nephrin and the development of DN are unclear. Our work on an inherited podocytopathy uncovered that dysregulated dynein could compromise nephrin trafficking, leading us to test whether and how dynein mediates the pathogenesis of DN.

Methods

We analyzed the transcription of dynein components in public DN databases, using the Nephroseq platform. We verified altered dynein transcription in diabetic podocytopathy by quantitative PCR. Dynein-mediated trafficking and degradation of nephrin was investigated using an in vitro nephrin trafficking model and was demonstrated in a mouse model with streptozotocin (STZ)-induced DN and in human kidney biopsy sections.

Results

Our transcription analysis revealed increased expression of dynein in human DN and diabetic mouse kidney, correlated significantly with the severity of hyperglycemia and DN. In diabetic podocytopathy, we observed that dynein-mediated postendocytic sorting of nephrin was upregulated, resulting in accelerated nephrin degradation and disrupted nephrin recycling. In hyperglycemia-stressed podocytes, Dynll1 , one of the most upregulated dynein components, is required for the recruitment of dynein complex that mediates the postendocytic sorting of nephrin. This was corroborated by observing enhanced Dynll1-nephrin colocalization in podocytes of diabetic patients, as well as dynein-mediated trafficking and degradation of nephrin in STZ-induced diabetic mice with hyperglycemia. Knockdown of Dynll1 attenuated lysosomal degradation of nephrin and promoted its recycling, suggesting the essential role of Dynll1 in dynein-mediated mistrafficking.

Conclusions

Our studies show that hyperglycemia stimulates dynein-mediated trafficking of nephrin to lysosomes by inducing its expression. The decoding of dynein-driven pathogenesis of diabetic podocytopathy offers a spectrum of new dynein-related therapeutic targets for DN.

Strategies for manipulating Rubisco and creating photorespiratory bypass to boost C3 photosynthesis: Prospects on modern crop improvement

Photosynthesis is a process that uses solar energy to fix CO₂ in the air and converts it into sugar, and ultimately powers almost all life activities on the earth. C₃ photosynthesis is the most common form of photosynthesis in crops. Current efforts of increasing crop yields in response to growing global food requirement are mostly focused on improving C₃ photosynthesis. In this review, we summarized the strategies of C₃ photosynthesis improvement in terms of Rubisco properties and photorespiratory limitation. Potential engineered targets include Rubisco subunits and their catalytic sites, Rubisco assembly chaperones, and Rubisco activase. In addition, we reviewed multiple photorespiratory bypasses built by strategies of synthetic biology to reduce the release of CO₂ and ammonia and minimize energy consumption by photorespiration. The potential strategies are suggested to enhance C₃ photosynthesis and boost crop production.

Crowding-induced phase separation and gelling by co-condensation of PEG in NPM1-rRNA condensates

The crowdedness of the cell calls for adequate intracellular organization. Biomolecular condensates, formed by liquid-liquid phase separation of intrinsically disordered proteins and nucleic acids, are important organizers of cellular fluids. To underpin the molecular mechanisms of protein condensation, cell-free studies are often used where the role of crowding is not investigated in detail. Here, we investigate the effects of macromolecular crowding on the formation and material properties of a model heterotypic biomolecular condensate, consisting of nucleophosmin (NPM1) and ribosomal RNA (rRNA). We studied the effect of the macromolecular crowding agent poly(ethylene glycol) (PEG), which is often considered an inert crowding agent. We observed that PEG could induce both homotypic and heterotypic phase separation of NPM1 and NPM1-rRNA, respectively. Crowding increases the condensed concentration of NPM1 and decreases its equilibrium dilute phase concentration, although no significant change in the concentration of rRNA in the dilute phase was observed. Interestingly, the crowder itself is concentrated in the condensates, suggesting that co-condensation rather than excluded volume interactions underlie the enhanced phase separation by PEG. Fluorescence recovery after photobleaching measurements indicated that both NPM1 and rRNA become immobile at high PEG concentrations, indicative of a liquid-to-gel transition. Together, these results provide more insight into the role of synthetic crowding agents in phase separation and demonstrate that condensate properties determined in vitro depend strongly on the addition of crowding agents.

The interplay of active and passive mechanisms in slow axonal transport

A combination of intermittent active movement of transient aggregates and a paused state that intervenes between periods of active transport has been proposed to underlie the slow, directed transport of soluble proteins in axons. A component of passive diffusion in the axoplasm may also contribute to slow axonal transport, although quantitative estimates of the relative contributions of diffusive and active movement in the slow transport of a soluble protein, and in particular how they might vary across developmental stages, are lacking. Here, we propose and study a model for slow axonal transport, addressing data from bleach recovery measurements on a small, soluble, protein, choline acetyltransferase, in thin axons of the lateral chordotonal (lch5) sensory neurons of Drosophila. Choline acetyltransferase is mainly present in soluble form in the axon and catalyzes the acetylation of choline at the synapse. It does not form particulate structures in axons and moves at rates characteristic of slow component b (≈ 1-10 mm/day or 0.01-0.1 μm/s). Using our model, which incorporates active transport with paused and/or diffusive states, we predict bleach recovery, transport rates, and cargo trajectories obtained through kymographs, comparing these with experimental observations at different developmental stages. We show that changes in the diffusive fraction of cargo during these developmental stages dominate bleach recovery and that a combination of active motion with a paused state alone cannot reproduce the data. We compared predictions of the model with results from photoactivation experiments. The importance of the diffusive state in reproducing the bleach recovery signal in the slow axonal transport of small soluble proteins is our central result.

A Spectrophotometric Turbidity Assay to Study Liquid-Liquid Phase Separation of UBQLN2 In Vitro

Liquid-liquid phase separation (LLPS) is hypothesized to be the underlying mechanism for how membraneless organelles or biomolecular condensates form inside both prokaryotic and eukaryotic cells. Protein LLPS is a biophysical process during which proteins demix from homogeneous solution to form protein-dense droplets with liquid-like properties. Disruptions to LLPS, such as changes to material properties of condensates or physicochemical parameters for LLPS onset, are implicated in neurodegenerative diseases and cancer. Therefore, it is essential to determine the physicochemical parameters that promote protein LLPS. Here, we present our UV-Vis spectrophotometric turbidity assay to characterize the temperature and concentration dependence of LLPS for UBQLN2, a protein that undergoes LLPS via homotypic interactions in vitro and forms stress-induced condensates in cells. Mutations in UBQLN2 cause amyotrophic lateral sclerosis (ALS) and disrupt UBQLN2 LLPS. We present a detailed expression and purification protocol for a C-terminal construct of UBQLN2 and how we use microscopy to image UBQLN2 LLPS. We use our UV-Vis assay to construct temperature-concentration phase diagrams for wild-type and mutant UBQLN2 constructs to determine the effects of domain deletions and/or mutations on UBQLN2 phase separation.

Exploiting valuable supramolecular materials from waste plastics

A new family of supramolecular materials is exploited from waste thermosets via a one-step retrosynthetic approach, which exhibits distinguished adhesion properties in dry/wet environments, good corrosion resistance and dynamic reversibility. This work opens up a wide design space for supramolecular materials with excellent performances and proposes a new strategy for efficient utilization of hybrid degraded products.