Biology subjects

Landry, C. R.

Publications and source records attributed to Landry, C. R..

At least 19 recordsLinked to original sources

bioRxiv2026

Adaptive gene duplication can exceed optimal dosage

Gene duplication is an important evolutionary mechanism contributing to genomic innovation and adaptation. While the long term fate of duplicated genes has been extensively studied, immediate effects such as those resulting from increase in gene dosage remain understudied. Of particular interest is the question of how expression level relates to the optimum after a duplication, as it could fall short, exceed or directly reach the optimal expression. In this study, we investigated the relationship between expression and fitness for 11 genes previously reported to increase fitness when duplicated in Saccharomyces cerevisiae to compare the expression level achieved by duplication to the one maximizing fitness. While most of the studied genes show little fitness variation across the expression levels tested, we found that ESP1, which encodes a separase essential to anaphase initiation, exhibits a clear fitness optimum at an expression level above the native single-copy state. However, the expression level associated with gene duplication exceeds the optimum. We find that ESP1 overexpression is associated with a reduced cell size and a lower proportion of the cell cycle spent in G2 phase, consistent with its role in cell cycle progression. We propose that the duplication of ESP1 accelerates the cell cycle, resulting in smaller, faster-dividing cells. When measured in different environments, the fitness functions also exhibit similar shapes, with slight variation in the optimal expression. Our findings highlight how gene duplication can confer an immediate selective advantage through dosage increase while being non-optimal, reversing the directionality of natural selection on expression level after duplication.

evolutionary biology↗

bioRxiv2026

A heterologous expression system allows rapid testing and discovery of resistance-conferring mutations from multiple pathogenic fungi

To face the fungal infections that affect millions of people every year, a better understanding of resistance-conferring mutations is necessary. One obstacle is the considerable time and effort necessary to construct point mutations in pathogenic species, which is required to validate their role in resistance. To overcome this problem, we have constructed a series of heterologous expression plasmids that allow expression of the ERG3, ERG6 and ERG11 orthologs from Candida albicans, Candidozyma auris, Nakaseomyces glabratus, Candida parapsilosis, Candida tropicalis, and the CYP51A and CYP51B genes of Aspergillus fumigatus. All orthologs are codon-optimized and synthesized for expression in the budding yeast Saccharomyces cerevisiae. We also constructed host strains in which the native ERG genes are either deleted or under the control of a repressible promoter. We showed that all orthologs complement the function of the native genes when expressed from the S. cerevisiae native promoters. We recreated previously reported resistance-conferring mutations, and showed that expression in S. cerevisiae replicates known resistance phenotypes. We then used the system to test corresponding mutations across orthologs, and showed that most resistance phenotypes are conserved. The heterologous expression system allows rapid construction of mutants, by taking advantage of the abundant genetic tools available for S. cerevisiae. Screening of mutants can be done within a few experimental steps, greatly increasing the throughput compared to the introduction of mutations in pathogenic fungi. As a proof-of-concept, we used the system to discover new resistance-conferring mutations, using random mutagenesis. All plasmids are made publicly available.

microbiology↗

bioRxiv2026

The hydrophobicity of peptides limits their availability to bind to interacting domains

A challenge in synthetic biology is to transfer the knowledge acquired in vitro to in vivo applications. For instance, binding affinity between peptide binding domains (PBDs) and their binding peptides is usually measured in simple buffers and in the absence of the cell machinery responsible for synthesis and proteostasis. Consequently, there is often a discrepancy between interaction quantified in vitro and in vivo. To identify strongly binding PBD-peptide pairs for in vivo applications, we aim to better understand the determinants of synthetic interaction in living yeast cells. We designed libraries of peptides expected to bind to PBDs based on data collected by phage-display. Using an in vivo protein interaction assay, we assessed the interaction strength of >6,500 PBD-peptide variants in yeast. We found that most substitutions disrupt binding, but that 3.4% increased binding strength to levels higher than expected from the phage-display data. We asked if, by using our mutational data, it was possible to optimize peptide sequences to gain even more binding strength and show additivity effect up to four substitutions. We found that PBD specificity is consistent between in vitro and in vivo assays. We hypothesized that in vivo peptide abundance could contribute to the discrepancy between the PCA and the phage-display results. We performed assays to detect in vivo peptide availability, reporting on peptide abundance, and we found that peptides with a stronger binding also show a higher availability in cells. We show that peptide availability, which seems mainly defined by peptide hydrophobicity, is key for the design of strong synthetic interactions.

molecular biology↗

bioRxiv2026

Epistasis limits but does not prevent the transfer of mutation-drug resistance mapping across 600 million years of fungal evolution

Whether different pathogens acquire resistance to antimicrobials through the same mutations is a major question in evolution and microbiology. Most antifungal drugs are used to treat infections caused by multiple fungal species, many of which have diverged for millions of years. If the evolution of resistance was to converge onto the same set of mutations across species, knowing the mechanism of resistance in one would allow us to predict and track it in others. The extent of this convergence remains unknown due to the lack of systematic data on resistance mutations. Here, we quantify the conservation of resistance mutations in the cytosine deaminase (CD), a protein responsible for resistance to flucytosine, one of the oldest antifungal drugs. By comparing the crystal structures of this enzyme through 600 My of evolution, we show that the CD structure is highly conserved. We compared the full CD mutational resistance spectrum of resistance from an ascomycete and a basidiomycete. We found that resistance mutations in one ortholog can be used to predict resistance in the other at a high level of accuracy. However, because of epistasis, around 10% of mutations have distinct effects in the two orthologs, which imposes an upper limit to the transferability of the knowledge of resistance mutations from one species to another. Using biochemical assays and by structural characterization of several mutants, we identify distinct mechanisms of epistasis, one important being that the local physiochemical environment of some position has evolved in a way that makes the same substitutions destabilizing or entirely inactivating in an ortholog-specific manner. Our results show that resistance mutations can be conserved in fungi across hundreds of millions of years of evolution but that epistasis eventually limits the accuracy of these predictions.

microbiology↗

bioRxiv2025

Adaptation is less accessible through mutations in promoters than in coding sequences when large effect sizes are needed

Mutations in gene regulatory regions have been shown to play a role in rapid adaptation but the factors determining their contribution are largely unknown. Using the yeast metabolic enzyme cytosine deaminase, we examine if adaptation to 5-fluorocytosine (5-FC), which requires reduced cytosine deamination and can readily arise from amino acid substitutions, may be reached by single promoter mutations. We generated all single-nucleotide substitutions and indels in the FCY1 promoter and assayed the resulting mutants in presence of 5-FC. This revealed that no promoter mutation is sufficient for adaptation to occur. We next investigated how this inaccessibility of adaptation arises by combining large-scale expression measurements with the experimental characterization of the corresponding expression-fitness function. These experiments showed that the shape of this function precludes single promoter mutations from being adaptive. Although 24% of mutations significantly affect expression, the fitness curve is flat around wild-type level. As such, adaptation can only emerge from a severe reduction of expression, which cannot occur from a single mutation in the promoter. Our results show that the contribution of regulatory mutations to rapid adaptation not only depends on the distribution of mutational effect sizes on expression level but also on the shape of the function linking fitness to expression levels.

evolutionary biology↗

bioRxiv2025

Paralog interference preserves genetic redundancy

Models of gene duplication often assume that loss-of-function mutations neutrally promote the return to the ancestral singleton state. They thus ignore the potential functional interference between duplicated proteins stemming from their physical interactions. Here, we show that for heteromerizing paralogs, such interference potentiates negative selection on loss-of-function mutations. This effect maintains genetic redundancy over longer timescales depending on the rate and severity of loss-of-function mutations. We experimentally estimate that around 6% of deleterious amino acid substitutions for a representative tetrameric protein interfere with a second copy. Interfering substitutions typically disrupt either catalysis or the final step of protein complex assembly, with varying degrees of severity. Our work shows that paralog interference renders the negative effects of loss-of-function mutations visible to purifying selection, contributing to the preservation of genetic redundancy.

evolutionary biology↗

bioRxiv2025

Making deep mutational scanning accessible: a cost-efficient approach to construct barcoded libraries for genes of any length

Recent developments in DNA synthesis and sequencing have allowed the construction of comprehensive gene variant libraries and their functional analysis. Achieving high-replication and thorough mutation characterization remains technically and financially challenging for long genes. Here, we developed an efficient, affordable and scalable library construction approach that relies on low-cost DNA synthesis and standard cloning technologies, which will increase accessibility to systematic mutational studies and help advance the field of protein science.

synthetic biology↗

bioRxiv2025

Predicting antifolate resistance in the unculturable fungal pathogen Pneumocystis jirovecii

Pneumocystis jirovecii is a fungal pathogen causing Pneumocystis pneumonia in humans, mainly in immunocompromised individuals. Infections by P. jirovecii are treated using the antifolate combination drug trimethoprim-sulfamethoxazole (TMP-SMX), targeting the dihydrofolate reductase (DHFR) and the dihydropteroate synthase (DHPS). In recent years, there has been an increase of treatment failure, with no mutations observed in the DHPS, implying the potential evolution of resistance through this pathogens DHFR (PjDHFR). Experimental methods to study this pathogen are limited, as it cannot be grown in vitro. Model fungi are insensitive to TMP-SMX due to unknown mechanisms, preventing the use of functional complementation to study mutations causing resistance to this specific drug combination. In a previous study, we conducted deep mutational scanning (DMS) on PjDHFR to identify resistance mutations to methotrexate (MTX), another antifolate drug. Here, by leveraging this data, as well as computational data modeling aspects of protein function and stability in the PjDHFR-MTX complex, we train a machine learning model to predict the effect of mutations on MTX resistance. We find that the model can predict the effect of mutations outside of its training dataset (balanced accuracy on training set: 98.3%, and 88.3% on testing set). We also find that the best predictors of resistance, such as distance to ligand and effect on region flexibility, are coherent with previously established models, and that experimental data about the effect of mutations on protein function is critical to optimize model performance. Using this model on computational data generated using the PjDHFR-TMP complex, we predict the effect of mutations on resistance to TMP. We predict TMP resistance mutations in PjDHFR that did not confer resistance to MTX, one of which had been characterized in vitro as reducing affinity to TMP by 100-folds. We compare the predictions from this model to PjDHFR sequences from previously and newly sequenced clinical samples. Our results offer a resource to interpret the impact of amino acid variants in PjDHFR on TMP resistance, as well as methods to predict resistance in hard-to-study organisms. Author summaryPneumocystis jirovecii is a fungal pathogen causing pneumonia in immunocompromised humans. Infections by P. jirovecii are treated using drugs that prevent this pathogen from making folate, an essential component of many cellular mechanisms. In recent years, this treatment has been failing in an increasing number of cases, implying the evolution of resistance to this treatment. As P. jirovecii does not grow in the lab, the investigation of this resistance has been difficult, and common lab models do not respond to the drugs used to treat it. To overcome these limitations, we use a combination of experimental data and computer modeling to train a machine learning model to predict how genetic changes in one of the drug targets might cause drug resistance in this pathogen. The presented model predicts mutations in the drug target that may make this pathogen resistant to treatment, including mutations that have been previously characterized in vitro as drastically reducing drug binding. To investigate if our model predicted mutations that accrued in nature, we also sequenced the largest number of this pathogens drug target to date. Our study provides new tools to predict drug resistance in hard-to-study pathogens, helping to understand and potentially respond to treatment failure.

biochemistry↗

bioRxiv2025

A protein-fragment complementation assay to quantify synthetic protein scaffold efficiency

Scaffolds are powerful tools in synthetic biology used for various applications, from increasing yield to optimizing signalling specificity. Protein scaffolds can be built by fusing peptide binding domains (PBD) and attaching the peptide they bind to the enzymes, inducing spatial proximity. Only a few PBD-peptide combinations have been tested in this context, and no combination produced a high yield in yeast, an important chassis in biotechnology. Therefore, there is a need for more exploration of PBD-peptide pairs to be used in this model. Scaffold characterization is challenging because it is often dependent on a model pathway with an output that is difficult to measure quantitatively. Here, we use a protein-fragment complementation assay (PCA) to study scaffolding efficiency in yeast, which allows to couple scaffolding efficiency with growth rate. First, we characterize the strength of PBD-peptide interactions (PPI) and the binding availability of the PBDs and peptides. Then, we test different scaffold architectures and expression levels to quantify the simultaneous binding of peptide pairs to the scaffold. We show that PPI strength of the weakest binding PBD-peptide pair is critical for scaffolding efficiency and that PPI strength is limited by low binding availability of some domains and peptides in vivo. Also, we find that slight architectural variations and expression levels have a significant impact on scaffolding efficiency detected by DHFR PCA. Finally, we used DHFR PCA approaches to characterize novel PBD-peptide pairs and we identified pairs to expand the sequence toolbox for scaffold design in yeast through DHFR PCA easy-to-read signal.

synthetic biology↗

bioRxiv2025

gyoza: a Snakemake workflow for modular analysis of deep-mutational scanning data

Deep-mutational scanning (DMS) is a powerful technique that allows screening large libraries of mutants at high throughput. It has been used in many applications, including to estimate the fitness impact of all single mutants of entire proteins, to catalog drug resistance mutations and even to predict protein structures. Here, we present gy[o]za, a Snakemake-based workflow to analyze DMS data. gy[o]za requires little programming knowledge and comes with comprehensive documentation to help the user go from raw sequencing data to functional impact scores. Complete with quality control and an automatically generated HTML report, this new pipeline should facilitate the analysis of time-series DMS experiments. gy[o]za is freely available on GitHub (https://github.com/durr1602/gyoza). Article summaryDeep-mutational scanning (DMS) refers to molecular biology methods used to generate many genetic variants and evaluate their effect on adaptive fitness. It is used both in fundamental and applied research, with implications in genomic medicine. Many data processing steps are needed to transform the output of DMS, high-throughput sequencing data, into scores that quantify the fitness effect of each variant. The analysis is tailored to the type of experimental design, which can vary a lot. To facilitate such analysis and make it accessible to people with limited knowledge in bioinformatics, we have developed gy[o]za, a free and easy-to-use program to analyze DMS data.

bioinformatics↗

bioRxiv2024

Mutational landscape and molecular bases of echinocandin resistance

One of the front-line drug classes used to treat invasive fungal infections is echinocandins, which target the fungal-specific beta-glucan synthase (Fks). Treatment failure due to resistance often coincides with mutations in three protein regions defined as hotspots. Unfortunately, the scarcity of the mutational data reported, combined with the large size and membrane-embedded nature of the enzyme hinder any effort to characterize genotype-phenotype links. Recent advances in solving the structure of Fks bring us one step closer to reliable predictions of the binding modes of each echinocandin. To help with that endeavor, we used molecular dynamics simulations to develop a membrane-embedded model of Fks that captures key structural and environmental features. Our results show that the three hotspots shape a single solvent-exposed binding cavity, hinting at the orientation and positioning of echinocandins. This structural framework is integrated with deep-mutational scanning to comprehensively assess the impact of mutations across the three hotspots in the model yeast Saccharomyces cerevisiae. We elucidate several key molecular bases of resistance to the three most widely used echinocandins; anidulafungin, caspofungin and micafungin and provide clues to better understand intrinsic resistance of critical fungal pathogens. One sentence summaryKey residues at specific positions in Fks hotspots lead to echinocandin-specific resistance.

molecular biology↗

bioRxiv2024

Residues Neighboring an SH3-Binding Motif Participate in Determining Affinity and Specificity In Vivo

In signaling networks, protein-protein interactions are often mediated by modular domains that bind short linear motifs. The motifs sequences affect many factors, among them affinity and specificity, or the ability to bind strongly and to the appropriate partners. Using Deep Mutational Scanning to create a mutant library, and protein complementation assays to measure protein-protein interactions, we determined the in vivo binding strength of a library of mutants of a binding motif on the MAP kinase kinase Pbs2, which binds the SH3 domain of the osmosensor protein Sho1 in Saccharomyces cerevisiae. These measurements were made using the full-length endogenous proteins, in their native cellular environment. We find that along with residues within the canonical motif, many mutations in the residues neighboring the motif also modulate binding strength. Interestingly, all Pbs2 mutations which increase binding are situated outside of the Pbs2 region that interacts with the canonical SH3 binding pocket, suggesting that other surfaces on Sho1 contribute to binding. We use predicted structures and mutations to propose a model of binding which involves residues neighboring the canonical Pbs2 motif binding outside of the canonical SH3 binding pocket. We compared this predicted structure with known structures of SH3 domains binding peptides through residues outside of the motif, and put forth possible mechanisms through which Pbs2 can bind specifically to Sho1. We propose that for certain SH3 domain-motif pairs, affinity and specificity are determined by a broader range of sequences than what has previously been considered, potentially allowing easier differentiation between otherwise similar partners. SummaryProtein-protein interactions are often mediated by a binding domain on one protein and a short disordered binding motif on another protein. We measured the binding strength of a mutant library of a binding motif situated in the yeast protein Pbs2 to the SH3 domain of Sho1. Many mutations in the residues neighboring the motif affect binding. A protein structure prediction of the interaction partners shows that residues neighboring the motif bind residues outside the known binding pocket on the SH3 domain. The Sho1-Pbs2 interaction differs enough from other known SH3-motif pairs to allow specific binding.

systems biology↗

bioRxiv2024

Patch-walking: Coordinated multi-pipette patch clamp for efficiently finding synaptic connections

Significant technical challenges exist when measuring synaptic connections between neurons in living brain tissue. The patch clamping technique, when used to probe for synaptic connections, is manually laborious and time-consuming. To improve its efficiency, we pursued another approach: instead of retracting all patch clamping electrodes after each recording attempt, we cleaned just one of them and reused it to obtain another recording while maintaining the others. With one new patch clamp recording attempt, many new connections can be probed. By placing one pipette in front of the others in this way, one can "walk" across the tissue, termed "patch-walking." We performed 136 patch clamp attempts for two pipettes, achieving 71 successful whole cell recordings (52.2%). Of these, we probed 29 pairs (i.e., 58 bidirectional probed connections) averaging 91 {micro}m intersomatic distance, finding 3 connections. Patch-walking yields 80-92% more probed connections, for experiments with 10-100 cells than the traditional synaptic connection searching method. MotivationRecognizing the manual labor and time-intensive nature of patch clamping when trying to find synaptic connections, we aim to improve its efficiency. We introduce a novel approach, termed "patch-walking," where one patch clamping electrode is cleaned and reused, enabling the exploration of numerous connections with a single recording attempt and improving the efficiency of identifying synaptic connections.

bioengineering↗

bioRxiv2024

Evolution and inhibition of the FIKK effector kinase family in P. falciparum

Among the [~]200 Plasmodium species that infect vertebrates, six infect humans. Of these, P. falciparum causes >95% of all [~]500,000 annual fatalities. Phylogenetically, P. falciparum belongs to the Laverania subgenus, a group of Plasmodium species that infect great apes. Common to Laverania species is the family of FIKK kinases. One million years ago, a single FIKK kinase conserved in all Plasmodium species gained an export element in the Laverania subgenus and expanded into the family of [~]20 atypical FIKK kinases, most of which are exported into the host cell. The fikk genes are conserved in syntenic loci across the Laverania, arguing for a rapid expansion controlling important functions in host cell remodelling and pathogenesis. We provide evidence that the FIKK paralogues evolved specific and mutually exclusive phosphorylation motif preferences, conserved across their Laverania orthologues, in a short evolutionary timeframe. Surprisingly, we find that FIKK13 has evolved exclusive tyrosine-phosphorylation preference, which was thought to be absent in Plasmodium species. Combining a crystal structure with AlphaFold2 predictions, we identify residues that determine kinase-specificity within the FIKK family in a fast-evolving flexible loop. Finally, we show that all expressed members of the FIKK kinase family can be chemically inhibited in vitro using a single compound. Such a pan-specific inhibitor of this kinase family important for virulence could reduce the ability of the parasite to gain escape-mutations and resistance.

microbiology↗

bioRxiv2024

Compensatory mutations potentiate constructive neutral evolution by gene duplication

Protein functions generally depend on their assembly into complexes. During evolution, some complexes have transitioned from homomers encoded by a single gene to heteromers encoded by duplicate genes. This transition could occur without adaptive evolution through intermolecular compensatory mutations. Here, we experimentally duplicate and evolve an homodimeric enzyme to examine if and how this could happen. We identify hundreds of deleterious mutations that inactivate individual homodimers but produce functional enzymes when co-expressed as duplicated proteins that heterodimerize. The structure of one such heteromer reveals how both losses of function are buffered through the introduction of asymmetry in the complex that allows them to subfunctionalize. Constructive neutral evolution can thus occur by gene duplication followed by only one deleterious mutation per duplicate. One sentence summaryCompensatory deleterious mutations entangle gene duplicates

evolutionary biology↗

bioRxiv2023

Most azole antifungal resistance mutations in the drug target provide cross-resistance and carry no intrinsic fitness cost

Azole antifungals are among the most frequently used drugs to treat fungal infections. Amino acid substitutions in and around the binding site of the azole target Erg11 (Cyp51) are a common resistance mechanism in pathogenic yeasts such as Candida albicans. How many and which mutations confer resistance, and at what cost, is however largely unknown. Here, we measure the impact of nearly 4,000 amino acid variants of the Erg11 ligand binding pocket on the susceptibility to six medical azoles. We find that a large fraction of amino acid substitutions lead to resistance (33%), most resistance mutations confer cross-resistance to two or more azoles (88%) and most importantly, only a handful of resistance mutations show a significant fitness cost in the absence of drug (9%). Our results reveal that resistance to azoles can arise through a large set of mutations and this will likely lead to azole pan-resistance, with very little evolutionary compromise. Such a resource will help inform treatment choices in clinical settings and guide the development of new drugs.

microbiology↗

bioRxiv2023

Mutational biases contribute to the neutral complexification of protein interaction networks following gene duplication

Biological systems can gain complexity over time. While some of these transitions are likely driven by natural selection, the extent to which they occur without providing an adaptive benefit is unknown. At the molecular level, one example is heteromeric complexes replacing homomeric ones following gene duplication. Here, we build a biophysical model and simulate the evolution of homodimers and heterodimers following gene duplication using distributions of mutational effects inferred from available protein structures. We keep the specific activity of each dimer identical, so their concentrations drift neutrally without new functions. We show that for more than 60% of tested dimer structures, the relative concentration of the heteromer increases over time due to mutational biases that favor the heterodimer. However, allowing mutational effects on synthesis rates and differences in the specific activity of homo- and heterodimers can limit or reverse the observed bias toward heterodimers. Our results show that the accumulation of more complex protein quaternary structures is likely under neutral evolution, and that natural selection would be needed to reverse this tendency.

systems biology↗

bioRxiv2023

The fitness cost of spurious phosphorylation

The fidelity of signal transduction requires the binding of regulatory molecules to their cognate targets. However, the crowded cell interior risks off-target interactions between proteins that are functionally unrelated. How such off-target interactions impact fitness is not generally known, but quantifying this is required to understand the constraints faced by cell systems as they evolve. Here, we use the model organism S. cerevisiae to inducibly express tyrosine kinases. Because yeast lacks bona fide tyrosine kinases, most of the resulting tyrosine phosphorylation is spurious. This provides a suitable system to measure the impact of artificial protein interactions on fitness. We engineered 44 yeast strains each expressing a tyrosine kinase, and quantitatively analysed their phosphoproteomes. This analysis resulted in [~]30,000 phosphosites mapping to [~]3,500 proteins. Examination of the fitness costs in each strain revealed a strong correlation between the number of spurious pY sites and decreased growth. Moreover, the analysis of pY effects on protein structure and on protein function revealed over 1000 pY events that we predict to be deleterious. However, we also find that a large number of the spurious pY sites have a negligible effect on fitness, possibly because of their low stoichiometry. This result is consistent with our evolutionary analyses demonstrating a lack of phosphotyrosine counter-selection in species with bona fide tyrosine kinases. Taken together, our results suggest that, alongside the risk for toxicity, the cell can tolerate a large degree of non-functional crosstalk as interaction networks evolve.

systems biology↗