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At least 595 records · Page 33Linked to original sources

An emergent biosynthetic pathway to essential amino acids by metabolic metathesis

An experimental approach to implanting foreign chemical reactions into living cells is to select for the catalytic production of a vital building-block such as an amino acid. Alkene metathesis is unknown in extant biochemistry, but is emerging as a new type of reaction to be catalyzed by protein enzymes. Here we show how the alkenic amino acid vinylglycine can be generated in a biocompatible reaction from 5-allyloxy-2-amino-pent-3-enoate (APE) by ring-closing metathesis catalyzed by a standard Hoveyda-Grubbs catalyst. The vinylglycine produced in situ is then used as a precursor of isoleucine and methionine, thus allowing the growth of strains of Escherichia coli requiring these essential amino acids. The robust nutritional screen we have developed paves the way for the directed evolution of genetically encoded metathesis enzymes and the chemical elaboration of metathesis coenzymes.

synthetic biology↗

A Multi-Layered Computational Structural Genomics Approach Enhances Domain-Specific Interpretation of Kleefstra Syndrome Variants in EHMT1

This study investigates the functional significance of assorted variants of uncertain significance (VUS) in euchromatic histone lysine methyltransferase 1 (EHMT1), which is critical for early development and normal physiology. EHMT1 mutations cause Kleefstra syndrome and are linked to various human cancers. However, accurate functional interpretation of these variants are yet to be made, limiting diagnoses and future research. To overcome this, we integrate conventional tools for variant calling with computational biophysics and biochemistry to conduct multi-layered mechanistic analyses of the SET catalytic domain of EHMT1, which is critical for this protein function. We use molecular mechanics and molecular dynamics (MD)-based metrics to analyze the SET domain structure and functional motions resulting from 97 Kleefstra syndrome missense variants within this domain. Our approach allows us to classify the variants in a mechanistic manner into SV (Structural Variant), DV (Dynamic Variant), SDV (Structural and Dynamic Variant), and VUS (Variant of Uncertain Significance). Our findings reveal that the damaging variants are mostly mapped around the active site, substrate binding site, and pre-SET regions. Overall, we report an improvement for this method over conventional tools for variant interpretation and simultaneously provide a molecular mechanism of variant dysfunction.

genomics↗

Enhancing Luciferase Activity and Stability through Generative Modeling of Natural Enzyme Sequences

The availability of natural protein sequences synergized with generative artificial intelligence (AI) provides new paradigms to create enzymes. Although active enzyme variants with numerous mutations have been produced using generative models, their performance often falls short compared to their wild-type counterparts. Additionally, in practical applications, choosing fewer mutations that can rival the efficacy of extensive sequence alterations is usually more advantageous. Pinpointing beneficial single mutations continues to be a formidable task. In this study, using the generative maximum entropy model to analyze Renilla luciferase homologs, and in conjunction with biochemistry experiments, we demonstrated that natural evolutionary information could be used to predictively improve enzyme activity and stability by engineering the active center and protein scaffold, respectively. The success rate of designed single mutants is [~]50% to improve either luciferase activity or stability. These finding highlights natures ingenious approach to evolving proficient enzymes, wherein diverse evolutionary pressures are preferentially applied to distinct regions of the enzyme, ultimately culminating in an overall high performance. We also reveal an evolutionary preference in Renilla luciferase towards emitting blue light that holds advantages in terms of water penetration compared to other light spectrum. Taken together, our approach facilitates navigation through enzyme sequence space and offers effective strategies for computer-aided rational enzyme engineering.

bioinformatics↗

Escherichia coli adapts metabolically to 6- and 7-fluoroindole, enabling proteome-wide fluorotryptophan substitution

Nature has scarcely evolved a biochemistry around fluorine. However, modern science proved fluorinated organic molecules to be suitable building blocks for biopolymers, from peptides and proteins up to entire organisms. Here, we conducted adaptive laboratory evolution (ALE) experiments to introduce fluorine into living microorganisms. By cultivating Escherichia coli with fluorinated indole analogues, we successfully evolved microbial cells capable of utilizing either 6-fluoroindole or 7-fluoroindole for growth. Our improved ALE protocols enabled us to overcome previous challenges and achieve consistent and complete adaptation of microbial populations to these unnatural molecules. In the ALE experiments, we supplied fluoroindoles to auxotrophic E. coli bacteria, exerting strong selective pressure that led to microbial adaptation and growth on monofluorinated indoles. Within the cells, these indoles were converted into corresponding amino acids (6- and 7-fluorotryptophan) and incorporated into the proteome at tryptophan sites. This study is a first step and establishes a strong foundation for further exploration of the mechanisms underlying fluorine-based life and how a formerly stressor (fluorinated indole) becomes a vital nutrient. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=64 SRC="FIGDIR/small/559291v1_ufig1.gif" ALT="Figure 1"> View larger version (17K): org.highwire.dtl.DTLVardef@1a3b17org.highwire.dtl.DTLVardef@1d716aorg.highwire.dtl.DTLVardef@10126d5org.highwire.dtl.DTLVardef@9c8a43_HPS_FORMAT_FIGEXP M_FIG C_FIG

synthetic biology↗

Bacteria face trade-offs in the decomposition of complex biopolymers

Although depolymerization of complex carbohydrates is a growth-limiting bottleneck for microbial decomposers, we still lack understanding about how the production of different types of extracellular enzymes affect individual microbes and in turn the performance of whole decomposer communities. In this work we use a theoretical model to evaluate the potential trade-offs faced by microorganisms in biopolymer decomposition which arise due to the varied biochemistry of different depolymerizing enzyme classes. We specifically consider two broad classes of depolymerizing extracellular enzymes, which are widespread across microbial taxa: exo-enzymes that cleave small units from the ends of polymer chains and endo-enzymes that act at random positions generating degradation products of varied sizes. Our results demonstrate a fundamental trade-off in the production of these enzymes, which is independent of systems complexity and which appears solely from the intrinsically different temporal depolymerization dynamics. As a consequence, specialists that produce either exo- or only endo-enzymes limit their growth to high or low substrate conditions, respectively. Conversely, generalists that produce both enzymes in an optimal ratio expand their niche and benefit from the synergy between the two enzymes. Finally, our results show that, in spatially-explicit environments, consortia composed of endo- and exo-specialists can only exist under oligotrophic conditions. In summary, our analysis demonstrates that the (evolutionary or ecological) selection of a depolymerization pathway will affect microbial fitness under low- or high substrate conditions, with impacts on the ecological dynamics of microbial communities. It provides a possible explanation why many polysaccharide degraders in nature show the genetic potential to produce both of these enzyme classes. Author summaryThe decomposition of polysaccharides by microbes is a key process in the global carbon cycle. It requires the joint action of a variety of microbially-produced extracellular enzymes. They can be broadly classified into endo-enzymes, that act in the middle of polymers, and exo-enzymes, that cleave units from polymer ends. Little is known about the benefits for microbes producing a certain enzyme type and the interplay between enzyme producing strategies in mixed communities. This hampers our comprehensive understanding of decomposition in terrestrial and marine ecosystems and thus limits the prediction of decomposition processes, for example in a changing climate. Based on theoretical modelling, we revealed a fundamental trade-off in the action of these enzymes. While exo-enzymes are more efficient at high substrate conditions, endo-enzymes perform better when substrate is low. Generalists producing both enzymes expand their ecological niche of substrate availability compared to specialists only producing one of the two types. Complementary specialists only co-exist in oligotrophic conditions. We conclude that producing enzymes for specific steps within polymer degradation represents relevant ecological strategies for microbes in decomposer communities.

microbiology↗

Genome sequences of equine influenza A subtype H3N8 viruses by long read sequencing and functional characterization of the PB1-F2 virulence factor of A/equine/Paris/1/2018

Equine influenza virus (EIV) remains a persistent threat to equines, despite the availability of vaccines. Currently, strategies to monitor the virus and prevent any potential vaccine failure revolve around serological assays, RT-qPCR amplification, and sequencing the viral hemagglutinin (HA) and neuraminidase (NA) genes. These approaches overlook the contribution of other viral proteins in driving virulence. This study assesses the potential of long-read nanopore sequencing for swift and precise sequencing of circulating equine influenza viruses. To this end, two French Florida Clade 1 strains, including the one circulating in winter 2018-2019 exhibiting more pronounced pathogenicity than usual, as well as the two currently used OIE-recommended vaccine strains, were sequenced. Our results demonstrated the reliability of this sequencing method in generating accurate sequences. Sequence analysis of HA revealed a subtle antigenic drift in the French EIV strains, with specific substitutions, such as T163I in A/equine/Paris/1/2018 and the N188T mutation in post-2015 strains; both substitutions were located in antigenic site B. Antigenic site E exhibited modifications in post-2018 strains, with the N63D substitution. Segment 2 sequencing also revealed that the A/equine/Paris/1/2018 strain encodes a longer variant of the PB1-F2 protein when compared to other Florida clade 1 strains (90 amino acids long versus 81 amino acids long). Further biological and biochemistry assays demonstrated that this PB1-F2 variant has enhanced abilities to abolish the mitochondrial membrane potential {Delta}{Psi}m and permeabilize synthetic membranes. Altogether, our results highlight the interest in rapidly characterizing the complete genome of circulating strains with next-generation sequencing technologies to adapt vaccines and identify specific virulence markers of EIV.

microbiology↗

Spatial control of the APC/C ensures the rapid degradation of Cyclin B1

The proper control of mitosis depends on the ubiquitin-mediated degradation of the right mitotic regulator at the right time. This is under the control of the anaphase promoting complex/cyclosome (APC/C) ubiquitin ligase that is regulated by the Spindle Assembly Checkpoint (SAC). The Checkpoint prevents the APC/C from recognizing Cyclin B1, the essential anaphase and cytokinesis inhibitor, until all chromosomes are attached to the spindle. Once chromosomes are attached, Cyclin B1 is rapidly degraded to enable chromosome segregation and cytokinesis. We have a good understanding of how the SAC inhibits the APC/C, but relatively little is known about how the APC/C recognises Cyclin B1 as soon as the SAC is turned off. Here, by combining live cell imaging, in vitro reconstitution, biochemistry, and structural analysis by cryo-electron microscopy, we provide evidence that the rapid recognition of Cyclin B1 in metaphase requires spatial regulation of the APC/C. Using fluorescence cross correlation spectroscopy, we find that Cyclin B1 and the APC/C primarily interact at the mitotic apparatus. We further show that this is because Cyclin B1, like the APC/C, binds to nucleosomes, and identify an arginine-anchor in the N-terminus as necessary and sufficient for binding to the nucleosome. Mutating the nucleosome binding motif on Cyclin B1 reduces its interaction with APC/C and delays its degradation, and cells with the mutant, non-nucleosome-binding Cyclin B1 become aneuploid, demonstrating the physiological relevance of our findings. Together, our data demonstrate that mitotic chromosomes constitute a platform to promote the efficient interaction between Cyclin B1 and APC/C and ensure the timely degradation of Cyclin B1 and genomic stability.

cell biology↗

Observations of Elemental Composition of Enceladus Consistent with Generalized Models of Theoretical Ecosystems

Recent analysis of data from the Cassini Cosmic Dust Analyzer confirm geochemical modeling work that shows that the ocean of Enceladus contains considerable quantities of inorganic phosphorus as well as ammonium [55]. Technological advancement in flight instrumentation will continue to yield increasingly detailed data about the relative elemental and molecular composition of life detection candidates. Apart from speculating about threshold concentrations of bioactive compounds to support ecosystems, metabolic and ecological theory can provide a powerful interpretative lens to assess whether extraterrestrial environments are compatible with living ecosystems. Using multiple levels of ecological analysis, spanning from assuming strictly Earth-like organismal physiology to more agnostic understandings of putative biochemistries, we compare the proposed N:P stoichiometries of the Enceledus ocean to possible ecologies. We use chemostat models to predict potentially supportable biomass concentrations under different energy and matter flux regimes, macromolecular allometric theory to compare hypothetical biomass N:P ratios to possible environmental N:P supply ratios, and finally take a data-driven biogeochemical approach to predict possible biomass N:P ratios from the observed dissolved ratios. All three of our modeling approaches suggest marginal compatibility of an ecosystem with the ranges of dissolved N and P concentrations in the Enceledean ocean. Based on our analysis, we suggest two main priorities for further research into terrestrial analogs to improve our ability to interpret geochemical ratios as a life detection instrument.

microbiology↗

Do color polymorphisms reflect pollinator shifts?: Integrating floral traits as signals to a novel pollinator to understand species divergence

Understanding how evolution proceeds from molecules to organisms to interactions is critical for evolutionary biology and requires integrative studies that span biological levels. By linking phenotypic changes with associated genes and fitness implications, we gain insight on the repeatability of evolution and how adaptive walks move organisms between fitness peaks, which remains poorly understood at intermediate stages, e.g. potential fitness valleys. Floral trait evolution can proceed rapidly, confer reproductive isolation, and provides numerous examples of convergent evolution associated with pollinator guilds. Within the monkeyflowers (Mimulus sect. Erythranthe), intraspecific shifts to yellow flowers within red hummingbird-pollinated species have arisen at least twice and may represent incipient shifts between optima of pollinator adaptation. Here, we compare two natural yellow-flowered forms of M. cardinalis and M. verbenaceus to their red conspecifics in floral phenotypes, biochemistry, transcriptomic and genomic variation, and interactions with pollinators. We find convergent evolution in the adaptive walks of yellow morphs in both species, with consistent changes in traits of large effect (floral pigments and associated gene expression), which result in strong preference for yellow flowers by bumblebees. Shifts in additional traits (scent emissions and floral opening size) are also consistent with bee pollination, which may represent smaller-effect steps in an ongoing walk from hummingbird to bee pollination. By examining intraspecific variation representing incipient pollinator shifts in two related species, this work elucidates how adaptive walks proceed at early stages by highlighting how convergent large effect mutations (floral color) may drive pollinator attraction, preceding smaller effect changes controlling pollinator fit and reward access. This work integrates phenotypic, biochemical, genomic, and behavioral evidence to shed light on how repeated steps in adaptive walks to new fitness optima may impact reproductive isolation and incipient speciation via convergent evolution.

evolutionary biology↗

Perilipin membrane association determines Lipid Droplet heterogeneity in differentiating adipocytes

The storage of fat within lipid droplets (LDs) of adipocytes is critical for whole-body health. Acute fatty acid (FA) uptake by differentiating adipocytes leads to the formation of at least two LD-classes marked by distinct perilipins (PLINs). How this LD-heterogeneity arises is an important yet unresolved cell biological problem. Here, we show that an unconventional integral membrane-segment (iMS) targets the adipocyte specific LD-surface factor PLIN1 to the endoplasmic reticulum (ER) and facilitates high affinity binding to the first LD-class. The other PLINs remain largely excluded from these LDs until FA-influx recruits them to a second LD-population. Preventing ER-targeting turns PLIN1 into a soluble, cytoplasmic LD-protein, reduces its LD-affinity and switches its LD-class specificity. Conversely, moving the iMS to PLIN2 leads to ER-insertion and formation of a separate LD-class. Our results shed light on how differences in organelle targeting and disparities in lipid-affinity of LD-surface factors contribute to formation of LD-heterogeneity. HighlightsO_LIPLIN1 is an integral membrane protein behaving as a class I LD protein. C_LIO_LIAn unconventional integral membrane segment (iMS) mediates ER insertion. C_LIO_LIThe iMS is required for LD-heterogeneity in differentiating adipocytes. C_LIO_LIHigh affinity LD-targeting from the ER is likely a gated process. C_LI eTOC blurbMajchrzak et al. use biochemistry, imaging and in vitro experiments to identify molecular features in PLIN1 that determine ER insertion and high lipid droplet affinity which are both important in the generation of LD-heterogeneity within differentiating adipocytes.

cell biology↗

Ipl1-controlled attachment maturation regulates Mps1 association with its kinetochore receptor

Faithful chromosome segregation requires that sister chromatids establish bi-oriented kinetochore-microtubule attachments. The spindle assembly checkpoint (SAC) prevents premature anaphase onset with incomplete attachments. However, how microtubule attachment and checkpoint signaling are coordinated remains unclear. The conserved kinase Mps1 initiates SAC signaling by localizing transiently to kinetochores in prometaphase and is released upon bi-orientation. Using biochemistry, structure predictions, and cellular assays, we shed light on this dynamic behaviour in Saccharomyces cerevisiae. A conserved N-terminal segment of Mps1 binds the neck region of Ndc80:Nuf2, the main microtubule receptor of kinetochores. Mutational disruption of this interface, located at the backside of the paired CH-domains and opposite the microtubule-binding site, prevents Mps1 localization, eliminates SAC signalling, and impairs growth. The same interface of Ndc80:Nuf2 binds the microtubule-associated Dam1 complex. We demonstrate that the error correction kinase Ipl1/Aurora B controls the competition between Dam1 and Mps1 for the same binding site. Thus, binding of the Dam1 complex to Ndc80:Nuf2 may release Mps1 from the kinetochore to allow anaphase onset.

cell biology↗

DeepVASP-S: a deep-learning tool for explaining steric mechanism that controls binding specificity

DeepVASP-S is a computational tool that leverages the capabilities of convolutional neural networks (CNNs) to analyze steric aspects of protein-ligand interactions and predict amino acid contributions to binding specificity. This tool combines structural bioinformatics with machine learning to address the complex problem of understanding how specific amino acids contribute to the specificity of binding. Here, we use this tool to predict subclasses for Enolase and Serine Protease according to their binding specificity, and explain it through the underlying steric mechanism. The strength of DeepVASP-S lies in its ability to identify and highlight these specific regions, providing researchers with insights into the molecular determinants of protein function and interaction. Such information is extremely valuable for the field of drug design, as it enables the creation of more targeted and effective therapeutics with minimized side effects. The approach taken by DeepVASP-S represents a significant step forward in computational biochemistry, merging high-resolution 3D structural data with the predictive power of machine learning to unlock a deeper understanding of protein-ligand interactions.

bioinformatics↗

Bioenergetic mapping of 'healthy microbiomes' via compound processing potential imprinted in gut and soil metagenomes

Despite mounting evidence of their importance in human health and ecosystem functioning, the definition and measurement of healthy microbiomes remain unclear. More advanced knowledge exists on health associations for compounds used or produced by microbes. Environmental microbiome exposures (especially via soils) also help shape, and may supplement, the functional capacity of human microbiomes. Given the synchronous interaction between microbes, their feedstocks, and micro-environments, with functional genes facilitating chemical transformations, there exists an intriguing opportunity to examine microbiomes in terms of their capacity to process compounds relevant to human health. Here we integrate functional genomics and biochemistry frameworks to derive new quantitative measures of the potential for human gut and environmental soil metagenomes to process major compound classes (e.g., lipids, carbohydrates) and selected biomolecules (e.g., vitamins, short-chain fatty acids) linked to human health. Metagenome functional potential profile data were translated into a universal compound mapping landscape based on bioenergetic van Krevelen mapping of function-level meta-compounds and corresponding functional relative abundances, reflecting imprinted genetic capacity of microbiomes to metabolize an array of different compounds. We show that measures of compound processing potential associated with human health and disease (examining atherosclerotic cardiovascular disease, colorectal cancer, type 2 diabetes and anxious-depressive behavior case studies), and displayed seemingly predictable shifts along gradients of ecological disturbance in plant-soil ecosystems (three case studies). Ecosystem quality explained 60-92% of variation in soil metagenome compound processing potential measures in a post-mining restoration case study dataset. With growing knowledge of the varying proficiency of environmental microbiota to process human health associated compounds, we might design environmental interventions or nature prescriptions to modulate our exposures, thereby advancing microbiota-oriented approaches to human health. Compound processing potential offers a simplified, integrative approach for applying metagenomics in ongoing efforts to understand and quantify the role and linkages of microbiota in environmental- and human-health.

bioinformatics↗

New learning principles emerge from biomimetic computational primitives

Although computational models have deepened our understanding of neuroscience, it is still highly challenging to link actual low-level physiological activity (spiking, field potentials) and biochemistry (transmitters and receptors) with high-level cognitive abilities (decision-making, working memory) nor with corresponding disorders. We introduce an anatomically-organized multi-scale model directly generating simulated physiology from which extended neural and cognitive phenomena emerge. The model produces spiking, fields, phase synchronies, and synaptic change, directly generating working memory, decisions, and categorization, all of which were then validated on extensive experimental macaque data from which the model received zero prior training of any kind. Moreover, the simulation uncovered a previously unknown neural code specifically predicting upcoming erroneous ("incongruous") behaviors, also subsequently confirmed in empirical data. The biomimetic model thus directly and predictively links novel decision and reinforcement signals, of computational interest, with novel spiking and field codes, of potential behavioral and clinical relevance.

neuroscience↗

Thermodynamically-consistent, reduced models of gene regulatory networks

Synthetic biology aims to engineer novel functionalities into biological systems. While the approach has to date been predominantly applied to single cells, a richer set of biological phenomena can be engineered by applying synthetic biology to cell populations. To rationally design cell populations, we require mathematical models that link between intracellular biochemistry and intercellular interactions. In this study, we develop a kinetic model of gene expression that is suitable for incorporation into agent-based models of cell populations. To be scalable to large cell populations, models of gene expression should be both computationally efficient and compliant with the laws of physics. We satisfy the first requirement by applying a model reduction scheme to translation, and the second requirement by formulating models using bond graphs. Our reduced model is significantly faster to simulate than the full model, and faithfully reproduces important behaviours of the full model. We couple separate models of gene expression to build models of the toggle switch and repressilator. With these models, we explore the effects of resource availability and cell-to-cell heterogeneity on circuit behaviour. The modelling approaches developed in this study are a bridge towards engineering collective cell behaviours such as synchronisation and division of labour.

synthetic biology↗

Diving into bacterial dormancy: emergence of osmotically stable wall-less forms in an aquatic environment

Bacteria can respond to environmental stresses by entering a dormant state, called viable but non-culturable (VBNC) state, in which they no longer grow in routine culture media. VBNC pathogens pose thus a significant risk for human and animal health as they are not detected by standard growth-based techniques and can "wake up" back into a vegetative and virulent state. Although hundreds of species were reported to become VBNC in response to different stresses, the molecular mechanisms governing this phenotypic switch remain largely elusive. Here, we characterized the VBNC state transition process in the Gram-positive pathogen Listeria monocytogenes in response to nutritional deprivation. By combining fluorescence microscopy, cryo-electron tomography and analytical biochemistry, we found that starvation in mineral water drives L. monocytogenes into a VBNC state via a mechanism of cell wall (CW) shedding that generates osmotically stable CW-deficient (CWD) coccoid forms. This phenomenon occurs in multiple L. monocytogenes strains and in other Listeria species, suggesting it may be a stress-adapting process transversal to the Listeria genus. Transcriptomic and gene-targeted approaches revealed the stress response regulator SigB and the autolysin NamA as major moderators of CW loss and VBNC state transition. Finally, we show that this CWD dormant state is transient as VBNC Listeria revert back to a walled, vegetative and virulent state after passage in embryonated eggs. Our findings provide unprecedented detail on the mechanisms governing the transition to a VBNC state, and reveal that dormant CWD bacterial forms can naturally arise in aquatic environments without osmotic stabilization. This may represent an alternative strategy for bacterial survival in oligotrophic conditions, which can potentially generate public health-threatening reservoirs of undetectable pathogens.

microbiology↗

The Role of Electron Spin-Polarizability and Charge Dynamics in Protein Function

Primitive nucleic acids and peptides likely collaborated during the earliest stages of biochemistry. What forces drove their interactions, and how did these forces shape the properties of primitive complexes? We investigated the association of two model primordial polypeptides with DNA. Coupling the peptides to a ferromagnetic substrate results in a dependence of the association rate and the extent of DNA binding on the orientation of magnetic moment of the substrate. The DNA binding could be nearly abolished by inverting the orientation of the magnetic field, despite the two polymers having complementary net charges. Inverting the chirality of either the entire peptide or just the connecting cysteine residue inverted the effect of the magnetic moment orientation. These results are attributed to the chiral-induced spin selectivity (CISS) effect, in which molecular chirality and electron spin interact to alter the electric polarizability of the protein. The observation of CISS effects governing simple protein-DNA complexes, suggests that this phenomenon was plausibly operative and potentially significant for primitive biomolecules. A key consequence of the CISS effect is to increase the kinetic stability of primitive protein-nucleic acid complexes. Taken together, our results show how emergent phenomena due to chirality and spin enhance bio-association.

biophysics↗

Biomolecular condensates in fungi are tuned to function at specific temperatures

Temperature can impact every reaction and molecular interaction essential to a cell. For organisms that cannot regulate their own temperature, a major challenge is how to adapt to temperatures that fluctuate unpredictability and on variable timescales. Biomolecular condensation offers a possible mechanism for encoding temperature-responsiveness and robustness into cell biochemistry and organization. To explore this idea, we examined temperature adaptation in a filamentous-growing fungus called Ashbya gossypii that engages biomolecular condensates containing the RNA-binding protein Whi3 to regulate mitosis and morphogenesis. We collected wild isolates of Ashbya that originate in different climates and found that mitotic asynchrony and polarized growth, which are known to be controlled by the condensation of Whi3, are temperature sensitive. Sequence analysis in the wild strains revealed changes to specific domains within Whi3 known to be important in condensate formation. Using an in vitro condensate reconstitution assay we found that temperature impacts the relative abundance of protein to RNA within condensates and that this directly impacts the material properties of the droplets. Finally, we found that exchanging Whi3 genes between warm and cold isolates was sufficient to rescue some, but not all, condensate-related phenotypes. Together these data demonstrate that material properties of Whi3 condensates are temperature sensitive, that these properties are important for function, and that sequence optimizes properties for a given climate.

cell biology↗