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Results for “Biochemistry”

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bioRxiv2019

An integrative model finds comparable contributions to drug resistance from poor drug adherence and adapting bacteria

Antibiotic resistance is a compound effect of several factors in the infection to healing cycle, from molecular factors such as mutation rate of bacteria to habitual behaviors such as adherence to a prescribed drug. Usually each of these factors is modeled separately from biochemistry, evolutionary biology or population health perspectives. To develop an understanding for the drug resistance at a population level, which is of high global significance, it is important to weigh all these factors in an integrated model. We develop RASAID, a model for resistance considering bacterial adaptation, infection spread, population adherence, immunity, and drug dosage. We apply the model to antibiotic resistance in the spread of resistant strains of Streptococcus Pneumoniae (Sp) in a finite community. We analyze the contributions from several factors to resistance, with a goal towards asking how important is the pursuit of newer drug developments relative to improving the awareness about the good practices in drug usage.

pharmacology and toxicology↗

bioRxiv2019

Intraflagellar transport complex B proteins regulate the Hippo effector Yap1 during cardiogenesis

Cilia and the intraflagellar transport (IFT) proteins involved in ciliogenesis are associated with congenital heart diseases (CHD). However, the molecular links between cilia, IFT proteins and cardiogenesis are yet to be established. Using a combination of biochemistry, genetics, and live imaging methods, we show that IFT complex B proteins (Ift88, Ift54 and Ift20) modulate the Hippo pathway effector YAP1 in zebrafish and mouse. We demonstrate that this interaction is key to restrict the formation of the proepicardium and the myocardium. In cellulo experiments suggest that IFT88 and IFT20 interact with YAP1 in the cytoplasm and functionally modulates its activity, identifying a molecular link between cilia related proteins and the Hippo pathway. Taken together, our results highlight a novel role for IFT complex B proteins during cardiogenesis and shed light on an unexpected mechanism of action for ciliary proteins in YAP1 regulation. These findings provide mechanistic insights into a non-canonical role for cilia related proteins during cardiogenesis.

developmental biology↗

bioRxiv2019

Applying knowledge-driven mechanistic inference totoxicogenomics

Government regulators and others concerned about toxic chemicals in the environment hold that a mechanistic, causal explanation of toxicity is strongly preferred over a statistical or machine learning-based prediction by itself. Elucidating a mechanism of toxicity is, however, a costly and time-consuming process that requires the participation of specialists from a variety of fields, often relying on animal models. We present an innovative mechanistic inference framework (MechSpy), which can be used as a hypothesis generation aid to narrow the scope of mechanistic toxicology analysis. MechSpy generates hypotheses of the most likely mechanisms of toxicity, by combining a semantically-interconnected knowledge representation of human biology, toxicology and biochemistry with gene expression time series on human tissue. Using vector representations of biological entities, MechSpy seeks enrichment in a manually-curated list of high-level mechanisms of toxicity, represented as biochemically- and causally-linked ontology concepts. Besides predicting the canonical mechanism of toxicity for many well-studied compounds, we experimentally validated some of our predictions for other chemicals without an established mechanism of toxicity. This framework can be modified to include additional mechanisms of toxicity, and is generalizable to other types of mechanisms of human biology.\n\nAuthor summarySeveral recent computational methods have displayed excellent performance in predicting toxicity outcomes [1-3] of chemicals. Yet, to our knowledge, there is to date no computational approach to generate mechanistic hypotheses to answer why these chemicals elicit a toxic response. There is great value in understanding the mechanism of toxicity for a chemical that appears to elicit an adverse response. Novel small molecule development is one example, where a chemical that failed initial toxicological screenings could be assessed to evaluate the actual mechanism of toxicity, greatly reducing research time and expenses on subsequent ones. The value of a mechanistic awareness of toxicity also applies to pharmacovigilance, when researching rare adverse effects of a drug in subsets of the population. The development of oncological chemotherapeutics is another example, where certain mechanisms of cytotoxicity can actually be desirable to eliminate different types of tumor cells. More importantly, the costs, time expenditure, and ethical concerns of toxicity animal models, make in vitro and in silico approaches an enticing alternative. We present a solution that uses a combination of gene expression assays and biomedical knowledge to address the gap of answering the why question.

bioinformatics↗

bioRxiv2019

Multi Epitope Vaccine Prediction Against Aichi Virus using Immunoinformatic Approach

Aichi virus, AiV is single stranded negative sense RNA genome belonging to the genus Kobuviru, a family of Picornaviridae that causes severe gastroenteritis. There is no treatment or vaccine for it, thus the aim of this study is to design a peptide vaccine using immunoinformatic approaches to analyze the viral Protein VP1 of AiV-1 strain, to determine the conserved region which is further studied to predict all possible epitopes that can be used as a peptide vaccine. A total of 38 Aichi virus VP1 retrieved from NCBI database were aligned to determine the conservancy and to predict the epitopes using IEDB analysis resource. Three epitopes predicted as a peptide vaccine for B cell was (PLPPDT, PPLPTP, and LPPLPTP). For T cell, two epitopes showed high affinity to MHC class I (FSIPYTSPL and TMVSFSIPY) and high coverage against the whole world population. Also, in MHC class II, three epitopes that interact with most frequent MHC class II alleles (FTYIAADLR and YMAEVPVSA) with high coverage in the whole world population. For both MHCI and MHCII the T-cell peptide with the strongest affinity to the worldwide population was FSIPYTSPL.\n\nPeptide vaccine against AiV is powerfully displace the normal produced vaccines based on the experimental biochemistry tools, as it designed to handle with a wide range of mutated strains, which will effectively minimize the frequent outbreaks and their massive economical wastage consequences.

bioinformatics↗

bioRxiv2019

Selecting for altered substrate specificity reveals the evolutionary flexibility of ATP-binding cassette transporters

ABC transporters are the largest family of ATP-hydrolyzing transporters, with members in every sequenced genome, which transport substrates across membranes. Structural studies and biochemistry highlight the contrast between the global structural similarity of homologous transporters and the enormous diversity of their substrates. How do ABC transporters evolve to carry such diverse molecules and what variations in their amino acid sequence alter their substrate selectivity? We mutagenized the transmembrane domains of a conserved fungal ABC transporter that exports a mating pheromone and selected for mutants that export a non-cognate pheromone. Mutations that alter export selectivity cover a region that is larger than expected for a localized substrate-binding site. Individual selected clones have multiple mutations which have broadly additive contributions to specific transport activity. Our results suggest that multiple positions influence substrate selectivity, leading to alternative evolutionary paths towards selectivity for particular substrates, and explaining the number and diversity of ABC transporters.

evolutionary biology↗

bioRxiv2019

Zero-shot imputations across species are enabled through joint modeling of human and mouse epigenomics

Recent large-scale efforts to characterize functional activity in human have produced thousands of genome-wide experiments that quantify various forms of biochemistry, such as histone modifications, protein binding, transcription, and chromatin accessibility. Although these experiments represent a small fraction of the possible experiments that could be performed, they also make human more comprehensively characterized than any other species. We propose an extension to the imputation approach Avocado that enables the model to leverage genome alignments and the large number of human genomics data sets when making imputations in other species. We found that not only does this extension result in improved imputation of mouse functional experiments, but that the extended model is able to make accurate imputations for protein binding assays that have been performed in human but not in mouse. This ability to make "zero-shot" imputations greatly increases the utility of such imputation approaches and enables comprehensive imputations to be made for species even when experimental data are sparse. CCS CONCEPTS* Computing methodologies [->] Neural networks; Factorization methods; * Applied computing [->] Bioinformatics; Genomics. ACM Reference FormatJacob Schreiber, Deepthi Hegde, and William Noble. 2020. Zero-shot imputations across species are enabled through joint modeling of human and mouse epigenomics. In ACM-BCB 2020: 11th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics, Sept 21-24, 2020, Virtual. ACM, New York, NY, USA, 9 pages. https://doi.org/10.1145/1122445.1122456

bioinformatics↗

bioRxiv2019

Tissue evolution: Mechanical interplay of adhesion, pressure, and heterogeneity

The evolution of various competing cell types in tissues, and the resulting persistent tissue population, is studied numerically and analytically in a particle-based model of active tissues. Mutations change the properties of cells in various ways, including their mechanical properties. Each mutation results in an advantage or disadvantage to grow in the competition between different cell types. While changes in signaling processes and biochemistry play an important role, we focus on changes in the mechanical properties by studying the result of variation of growth force and adhesive cross-interactions between cell types. For independent mutations of growth force and adhesion strength, the tissue evolves towards cell types with high growth force and low internal adhesion strength, as both increase the homeostatic pressure. Motivated by biological evidence, we postulate a coupling between both parameters, such that an increased growth force comes at the cost of a higher internal adhesion strength or vice versa. This tradeoff controls the evolution of the tissue, ranging from unidirectional evolution to very heterogeneous and dynamic populations. The special case of two competing cell types reveals three distinct parameter regimes: Two in which one cell type outcompetes the other, and one in which both cell types coexist in a highly mixed state. Interestingly, a single mutated cell alone suffices to reach the mixed state, while a finite mutation rate affects the results only weakly. Finally, the coupling between changes in growth force and adhesion strength reveals a mechanical explanation for the evolution towards intra-tumor heterogeneity, in which multiple species coexist even under a constant evolutianary pressure.\n\nAuthor summaryThe evolution of cell populations in growing tissues is due to mutations during cell division, and subsequent competition through various biochemical and mechanical factors. Cancer represents an example of such an evolution on a short time scale. It is a multistep process, where several mutations are needed in order for a tumor to develop and become malignant. Furthermore, cell types in a tumor are often found to be very heterogeneous. We employ computer simulations of a particle-based model of growing tissues to study the competition of various cell types through variations of the mechanical cell properties. Unconstraint evolution drives the tissue towards cell types with stronger growth force and reduced adhesion. However, growth force and adhesion are not independent. Motivated by biologcal evidence, we consider a tissue, where enhanced growth force is coupled to increased adhesion. In a regime around a balanced tradeoff, multiple cell types coexist in a tissue, providing a tentative explanation for tumor heterogeneity. The special case of a competition between two cell types facilitates the study of the underlying competition mechanism. For example, we find that the number fraction of mutated cells is nearly independent of the mutation rate km, as long as km is much smaller than the apoptosis rate ka.

biophysics↗

bioRxiv2019

Interconversion between Anticipatory and Active GID E3 Ubiquitin Ligase Conformations via Metabolically Driven Substrate Receptor Assembly

Cells respond to environmental changes by toggling metabolic pathways, preparing for homeostasis, and anticipating future stresses. For example, in Saccharomyces cerevisiae, carbon stress-induced gluconeogenesis is terminated upon glucose availability, a process that involves the multiprotein E3 ligase, GIDSR4, recruiting N-termini and catalyzing ubiquitylation of gluconeogenic enzymes. Here, genetics, biochemistry, and cryo electron microscopy define molecular underpinnings of glucose-induced degradation. Unexpectedly, carbon stress induces an inactive anticipatory complex (GIDAnt), which awaits a glucose-induced substrate receptor to form the active GIDSR4. Meanwhile, other environmental perturbations elicit production of an alternative substrate receptor assembling into a related E3 ligase complex. The intricate structure of GIDAnt enables anticipating and ultimately binding various N-degron targeting (i.e. \"N-end rule\") substrate receptors, while the GIDSR4 E3 forms a clamp-like structure juxtaposing substrate lysines with the ubiquitylation active site. The data reveal evolutionarily conserved GID complexes as a family of multisubunit E3 ubiquitin ligases responsive to extracellular stimuli.

molecular biology↗

bioRxiv2019

Vibrio deploys Type 2 secreted lipase to esterify cholesterol with host fatty acids and mediate cell egress

Pathogens find diverse niches for survival inside host cells where replication occurs in a relatively protected environment. Vibrio parahaemolyticus, a facultative intracellular pathogen, uses its type 3 secretion system 2 (T3SS2) to invade and replicate inside host cells. However, after extensive analysis, the T3SS2 pathogenicity island appeared to lack a mechanism for egress of this bacterium from the invaded host cell. Using a combination of cell biology, microbial genetics and lipid biochemistry, we found that VPA0226, a constitutively secreted lipase, is required for escape of Vibrio parahaemolyticus from host cells. Remarkably, this lipase must be delivered into the host cytoplasm where it preferentially uses fatty acids associated with innate immune response (i.e. arachidonic acid, 20:4) to esterify cholesterol, weakening the plasma membrane and allowing egress of the bacteria. This study reveals the resourcefulness of microbes and the interplay between virulence systems to evolve an ingenious scheme for survival and escape. Impact StatementConsidering the course of a pathogens evolution, there appears to be interplay between secretion systems, providing unique, synergistic mechanisms to support a successful lifestyle for possibly pathogenesis, symbiosis and/or parasitosis.

microbiology↗

bioRxiv2019

Cutting in-line with iron: ribosomal function and non-oxidative RNA cleavage

Divalent metal cations are essential to the structure and function of the ribosome. Previous characterizations of the ribosome performed under standard laboratory conditions have implicated Mg2+ as a primary mediator of ribosomal structure and function. Possible contributions of Fe2+ as a ribosomal cofactor have been largely overlooked, despite the ribosomes early evolution in a high Fe2+ environment, and its continued use by obligate anaerobes inhabiting high Fe2+ niches. Here we show that (i) Fe2+ cleaves RNA by in-line cleavage, a non-oxidative mechanism that has not previously been shown experimentally for this metal, (ii) the first-order rate constant with respect to divalent cations is more than 200 times greater with Fe2+ than with Mg2+, (iii) functional ribosomes are associated with Fe2+ after purification from cells grown under low O2 and high Fe2+, and (iv) a small fraction of Fe2+ that is associated with the ribosome is not exchangeable with surrounding divalent cations, presumably because it is tightly coordinated by rRNA and buried in the ribosome. In total, these results expand the ancient role of iron in biochemistry and highlight a possible new mechanism of iron toxicity. Key PointsO_LIFe2+ cleaves rRNA by a non-oxidative in-line cleavage mechanism that is more than 200 times faster than in-line cleavage with Mg2+; C_LIO_LIribosomes purified from cells grown under low O2 and high Fe2+ retain ~10 Fe2+ ions per ribosome and produce as much protein as low O2, high Mg2+-grown ribosomes; C_LIO_LIa small fraction (~2%) of Fe2+ that is associated with the ribosome is not exchangeable. C_LI

molecular biology↗

bioRxiv2019

Genome-Scale Characterization of Predicted Plastid-Targeted Proteomes in Higher Plants

Plastids are morphologically and functionally diverse organelles that are dependent on nuclear-encoded, plastid-targeted proteins for all biochemical and regulatory functions. However, how plastid proteomes vary temporally, spatially, and taxonomically has been historically difficult to analyze at genome-wide scale using experimental methods. A bioinformatics workflow was developed and evaluated using a combination of fast and user-friendly subcellular prediction programs to maximize performance and accuracy for chloroplast transit peptides and demonstrate this technique on the predicted proteomes of 15 sequenced plant genomes. Gene family grouping was then performed in parallel using modified approaches of reciprocal best BLAST hits (RBH) and UCLUST. Between 628 protein families were found to have conserved plastid targeting across angiosperm species using RBH, and 828 using UCLUST. However, thousands of clusters were also detected where only one species had predicted plastid targeting, most notably in Panicum virgatum which had 1,458 proteins with species-unique targeting. An average of 45% overlap was found in plastid-targeted gene families compared with Arabidopsis, but an additional 20% of proteins matched against the full Arabidopsis proteome, indicating a unique evolution of plastid targeting. Neofunctionalization through subcellular relocalization is known to impart novel biological functions but has not been described before on genome-wide scale for the plastid proteome. Further work to correlate these predicted novel plastid-targeted proteins to transcript abundance and high-throughput proteomics will uncover unique aspects of plastid biology and shed light on how the plastid proteome has evolved to change plastid morphology and biochemistry.

plant biology↗

bioRxiv2019

Shotgun metagenomics and metabolomics reveal glyphosate alters the gut microbiome of Sprague-Dawley rats by inhibiting the shikimate pathway

There is intense debate as to whether glyphosate can interfere with aromatic amino acid biosynthesis in microorganisms inhabiting the gastrointestinal tract, which could potentially lead to negative health outcomes. We have addressed this major gap in glyphosate toxicology by using a multi-omics strategy combining shotgun metagenomics and metabolomics. We tested whether glyphosate (0.5, 50, 175 mg/kg bw/day), or its representative EU commercial herbicide formulation MON 52276 at the same glyphosate equivalent doses, has an effect on the rat gut microbiome in a 90-day subchronic toxicity test. Clinical biochemistry measurements in blood and histopathological evaluations showed that MON 52276 but not glyphosate was associated with statistically significant increase in hepatic steatosis and necrosis. Similar lesions were also present in the liver of glyphosate-treated groups but not in the control group. Caecum metabolomics revealed that glyphosate inhibits the enzyme 5-enolpyruvylshikimate-3-phosphate (EPSP) synthase in the shikimate pathway as evidenced by an accumulation of shikimic acid and 3-dehydroshikimic acid. Levels of caecal microbiome dipeptides involved in the regulation of redox balance ({gamma}-glutamylglutamine, cysteinylglycine, valylglycine) had their levels significantly increased. Shotgun metagenomics showed that glyphosate affected caecum microbial community structure and increased levels of Eggerthella spp. and Homeothermacea spp.. MON 52276, but not glyphosate, increased the relative abundance of Shinella zoogleoides. Since Shinella spp. are known to degrade alkaloids, its increased abundance may explain the decrease in solanidine levels measured with MON 52776 but not glyphosate. Other glyphosate formulations may have different effects since Roundup(R) GT Plus inhibited bacterial growth in vitro at concentrations at which MON 52276 did not present any visible effect. Our study highlights the power of a multiomics approach to investigate effects of pesticides on the gut microbiome. This revealed the first biomarker of glyphosate effects on rat gut microbiome. Although more studies will be needed to ascertain if there are health implications arising from glyphosate inhibition of the shikimate pathway in the gut microbiome, our findings can be used in environmental epidemiological studies to understand if glyphosate can have biological effects in human populations. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=97 SRC="FIGDIR/small/870105v1_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@66578corg.highwire.dtl.DTLVardef@fddcd9org.highwire.dtl.DTLVardef@ae4ffforg.highwire.dtl.DTLVardef@5f7ed_HPS_FORMAT_FIGEXP M_FIG C_FIG

pharmacology and toxicology↗

bioRxiv2025

Capturing Multi-Scale Dynamics of Aortic Valve Calcification With a Coupled Fluid Structure and Systems Biology Model

Calcific aortic valve disease (CAVD) arises from coupled interactions between blood flow, tissue mechanics, and cellular signaling. Hemodynamic forces influence endothelial and interstitial cell behavior, while the resulting tissue remodeling alters valve motion and flow patterns. Capturing this two-way feedback requires models that integrate fluid-structure mechanics with biochemical regulation, yet such multiscale coupling remains technically challenging. Previous computational models have focused on isolated aspects of the disease: fluid-structure interaction (FSI) simulations reproduce valve deformation and flow, and systems biology (SB) models describe molecular signaling that drives fibrosis and calcification. However, without coupling, these approaches cannot predict how mechanical dysfunction initiates biochemical remodeling or how biochemical changes feed back on mechanics. Here, we present a proof-of-principle, multi-physics computational framework that couples three-dimensional FSI simulations of aortic valve dynamics with a mechanistic SB model of calcification signaling. The FSI module resolves pulsatile blood flow and leaflet deformation, yielding local wall shear stresses and tissue strains throughout the cardiac cycle. These mechanical quantities are used as inputs to the SB module, which comprises key biochemical pathways governing inflammation, TGF-{beta}/SMAD signaling, and nitric-oxide (NO)-mediated inhibition within valvular cells. Simulations predict long-term calcification trajectories for valves of varying thickness, showing that fibrosis-induced stiffening lowers shear stress, reduces NO synthesis, and enhances TGF-{beta} activation, thereby accelerating calcification. While the current one-way coupling implementation is not intended yet for clinical applications, the framework is modular and extensible, allowing for future enhancements that will advance towards this goal. These include the incorporation of additional biological pathways in the SB model and implementation of a fully two-way coupling scheme between the FSI and SB models that will increase accuracy and predictive capability of the framework. By integrating physics-based hemodynamics with systems-level biochemistry, this study demonstrates the utility of a next-generation, multi-scale modeling platform for studying cardiovascular disease that unites blood flow dynamics and biochemical signaling.

systems biology↗

bioRxiv2025

Going Against the Grain: Investigating the C4 Wheat Hypothesis with Spatial Transcriptomics

The possibility of a C4 photosynthetic pathway present in the developing grain of wheat, a C3 plant, has been the source of scientific debate. Wheat is critical to food security and may benefit greatly from the biological advantages conferred by C4 photosynthesis under heat and drought stress. Therefore, significant research has gone towards engineering wheat to use C4 biochemistry, resulting in the discovery of a unique photosynthetic pathway in the grain that has been suggested to be C4 specific. Here, we employed a spatial transcriptomics analysis of the developing wheat grain to further investigate the spatial expression patterns of C4 specific genes. Our results showed that most of the genes related to C4 photosynthesis were expressed in the grain in the theorised tissue locations, including phosphoenolpyruvate carboxylase (ppc) and pyruvate orthophosphate dikinase (ppdk). The photosynthetic pericarp cells were the site of ppc synthesis while the endosperm was the site of ppc carboxylation activity. Notably, isoforms of aspartate aminotransferase, alanine aminotransferase and malate dehydrogenase exhibited spatially distinct expression patterns, with tissue specificity, possibly linked to the unique functions of individual isoforms. As wheat performance under stress has been associated with the levels of expression of these C4 genes, confirmation of an active C4 pathway in the grain would have significant agronomic implications. Our results provide novel gene expression data for key genes related to photosynthesis, which could contribute to future development of highly productive, climate change resilient wheat varieties.

genetics↗

bioRxiv2025

Quantifying (de)Mixing of Disordered Proteins in Molecular Dynamics Simulations

Biomolecular condensates control the spatial and temporal organization of cellular biochemistry. Their architectures often arise from complex, multicomponent mixtures governed by weak, multivalent interactions between intrinsically disordered regions (IDRs) of proteins. However, current approaches lack generalizable metrics to determine whether IDRs will mix or segregate within condensates. Here, we present a domain decomposition method (DDM) that accurately determines phase concentrations without identifying condensate interfaces. When tested against 399 IDR simulations, the DDM recovers dense- and dilute-phase concentrations within 1% agreement of established surface-based methods. By calculating spatial variances to map three-dimensional organization, this approach successfully distinguishes homogeneous mixing from surface enrichment, core--shell architectures, and complete segregation. Applying this continuous metric to 2,068 binary mixtures of 32 distinct IDRs, we demonstrate that physicochemical similarity strongly promotes mixing. Hydrophobic IDRs mixed promiscuously across all partner chemistries, whereas charged sequences mixed in a way highly sensitive to charge complementarity, forming the most stable condensates as net charge approached zero. Compared with experimental networks, our IDR-only simulations predicted the partitioning preferences for 10 of 13 proteins, with discrepancies accurately isolating cases where colocalization strictly requires RNA or folded domains. Quantifying mixing in this way provides a robust and reproducable method for predicting IDR interactomes and understanding the composition of complex cellular condensates.

biophysics↗

bioRxiv2025

Structural basis for the inhibition of Trypanosoma brucei enolase by a camelid single-domain antibody

Trypanosoma brucei is an extracellular protozoan that causes neglected tropical diseases in both humans and livestock. The parasite has a bipartite life cycle involving an insect vector and a mammalian host. Within the latter, it mainly thrives as a blood-borne parasite that relies on glycolysis to support its energy metabolism. It is for this reason that trypanosomal glycolytic enzymes have been investigated as potential targets for the development of trypanosome-killing drugs. Recent work from our lab has shown that they are also interesting biomarkers for the detection of active trypanosome infections. T. brucei enolase (TbrENO) is a trypanosomal glycolytic enzyme that has gathered interest in both drug and diagnostics development. In this paper, we report the discovery of a camelid single domain antibody (sdAb aka nanobody) that specifically recognises and inhibits TbrENO. The sdAbs inhibitory mechanism is unraveled through a combination of protein biochemistry, biophysics, and structural biology. Author summaryTrypanosoma brucei is a unicellular parasite that lives in the bloodstream of humans and animals, where it causes serious but often overlooked diseases. Because it depends heavily on breaking down glucose to produce energy, the parasites glucose-processing proteins (called glycolytic enzymes) have become important targets for both new treatments and improved diagnostic tools. One of these proteins, called T. brucei enolase (TbrENO), has recently drawn attention for its potential in drug development and disease detection. In this study, we discovered a special type of antibody, known as a camelid single-domain antibody (sdAb aka nanobody), that can specifically recognize and block the activity of TbrENO. We employed a combination of various laboratory techniques to understand exactly how the sdAb binds to and inhibits the enzyme. Our findings provide new insight into how TbrENO can be inhibited in a way that does not require active site binding and highlight the value of sdAbs as precise tools for targeting key parasite proteins.

bioengineering↗

bioRxiv2025

Enzyme-driven phase separation of synthetic condensates enables self-organizing compartments and protective microenvironments

Compartmentalization via phase separation is increasingly recognized as a dynamic regulator of cellular biochemistry, yet the consequences of coupling enzymatic reactions to compartmentalization remain poorly understood. We combine a minimal, cell-free expression system with kinetic modeling to show how coupling enzymatic activity to biomolecular condensates drives emergent self-regulation via droplet formation and dissolution. In-vitro mRNA transcription induces phase separation with an intrinsically disordered protein (mutant G3BP1), forming condensates that modulate transcription and degradation kinetics. Our kinetic model shows that phase separation reduces rate constants, with slower degradation within condensates than in the mRNA-protein-poor phase. This leads to more mRNA with a prolonged lifetime of mRNA relative to the case without condensates. Extending the model to sustained and oscillatory resource supply reveals that condensates elevate mean mRNA levels and buffer deviations from the mean compared to the non-condensate scenario. These findings provide a general mechanism of cross-regulation and feedback between phase separation and enzymatic networks, highlighting condensates as active regulators of biochemical flux rather than as passive organizers. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=172 SRC="FIGDIR/small/696465v1_ufig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@d48750org.highwire.dtl.DTLVardef@ffc9eeorg.highwire.dtl.DTLVardef@1222de6org.highwire.dtl.DTLVardef@f36701_HPS_FORMAT_FIGEXP M_FIG C_FIG

synthetic biology↗

bioRxiv2026

Biomolecular condensate architecture of an autophagic cargo at molecular resolution in situ

Biomolecular condensates organise cellular biochemistry, yet their molecular architecture in situ remains poorly understood. During selective autophagy, macromolecules frequently accumulate into biomolecular condensates, forming discrete entities for autophagic engulfment and degradation - ideal systems for structural analysis. We employed in situ cryo-electron tomography to determine the near-atomic resolution structure of Aminopeptidase 1 condensates within cells. These condensates form densely packed, spherical assemblies with amorphous organisation and liquid-like properties, elucidating the requirements of a selective autophagic cargo for exclusive targeting. Structural analysis and multiscale simulations reveal that the short, transient -helical structures in the disordered N-terminus of Aminopeptidase 1 enable site-specific, coiled-coil-like interactions required for condensate formation and properties. A single point mutation that increases -helical propensity directly modulates condensate viscosity and dynamics from a liquid-like to a glass-like state, while preserving local molecular packing. Our results demonstrate that disordered regions encode both specificity and material properties through transiently structured motifs, linking sequence specificity to phase behaviour in cells and expanding the molecular logic of phase separation in cells.

cell biology↗